Table of Contents • Part One Biosensor and Biochip Technologies
•
Introduction to Biosensor and Biochip Technologies Full Text: HTML PDF (46K)
•
1 Overview of Biosensor and Bioarray Technologies Abstract | Full Text: HTML PDF (171K)
•
2 Overview of Modern Analytical Needs Abstract | Full Text: HTML PDF (176K)
•
3 Historical Perspective of Biosensor and Biochip Development Abstract | Full Text: HTML PDF (839K) • Part Two Biological and Molecular Recognition Systems
•
Biological and Molecular Recognition Systems Full Text: HTML PDF (36K)
•
4 Protein Recognition in Biology Abstract | Full Text: HTML PDF (1195K)
•
5 Enzymology Abstract | Full Text: HTML PDF (311K)
•
6 Molecular Antibody Technologies for Biosensors and Bioanalytics Abstract | Full Text: HTML PDF (230K)
•
7 Phage-Displayed Epitopes as Bioreceptors for Biosensors Abstract | Full Text: HTML PDF (279K)
•
8 Luciferase Reporter Bacteriophages Abstract | Full Text: HTML PDF (146K)
•
9 Natural Luminescent Whole-Cell Bioreporters Abstract | Full Text: HTML PDF (116K)
•
10 Recombinant Bacterial Reporter Systems Abstract | Full Text: HTML PDF (120K)
•
11 Recombinant Whole-Cell Bioreporter Systems Based on Beetle Luciferases
Abstract | Full Text: HTML PDF (154K)
•
12 Recombinant Aequorin-Based Systems for Biomarker Analysis Abstract | Full Text: HTML PDF (246K)
•
13 Yeast-Based Biosensors and Their Incorporation of Mammalian Protein Receptors for HighThroughput Screening Abstract | Full Text: HTML PDF (579K)
•
14 Molecularly Imprinted Polymers as Recognition Elements in Sensors Abstract | Full Text: HTML PDF (324K)
•
15 Aptameric Biosensors Abstract | Full Text: HTML PDF (236K) • Part Three The Biology–Materials Interface
•
The Biology–Materials Interface: Interfacial Science and Receptor Integration Full Text: HTML PDF (36K)
•
16 Immobilization of Biomolecules by Electropolymerized Films Abstract | Full Text: HTML PDF (173K)
•
17 Electrochemical Polymerization for Preparation of Electrochemical Sensors Abstract | Full Text: HTML PDF (105K)
•
18 Smart Hydrogel Materials Abstract | Full Text: HTML PDF (268K)
•
19 Scanning Electrochemical Microscopy for Biomolecular Immobilization and Imaging Abstract | Full Text: HTML PDF (450K)
•
20 Modeling of Biosensor Interfaces Abstract | Full Text: HTML PDF (622K)
•
21 Ion Channel Biosensors Abstract | Full Text: HTML PDF (342K) • Part Four Transducer Technologies for Biosensors
•
Transducer Technologies for Biosensors and Bioarray Technologies Full Text: HTML PDF (57K)
•
22 Electrochemical Techniques in Biosensors Abstract | Full Text: HTML PDF (341K)
•
23 Conductometric Enzyme Biosensors Abstract | Full Text: HTML PDF (169K)
•
24 Chemical and Biological Field-Effect Sensors for Liquids—A Status Report Abstract | Full Text: HTML PDF (290K)
•
25 Overview of Optical Biosensing Techniques Abstract | Full Text: HTML PDF (380K)
•
26 Localized Surface Plasmon Resonance (LSPR) Spectroscopy in Biosensing Abstract | Full Text: HTML PDF (1171K)
•
27 Picoscopes, New Label-Free Biosensors Abstract | Full Text: HTML PDF (428K)
•
28 Chemiluminescent Optical Fiber Immunosensor Abstract | Full Text: HTML PDF (147K)
•
29 Bioluminescent Whole-Cell Optical Fiber Sensors Abstract | Full Text: HTML PDF (401K)
•
30 Phagocyte Luminescent Sensor Abstract | Full Text: HTML PDF (396K)
•
31 Applications of the Electrogenerated Luminescent Reactions in Biosensor and Biochip Developments Abstract | Full Text: HTML PDF (457K)
•
32 Dual Polarization Interferometry: A Real-Time Optical Technique for Measuring (Bio)molecular Orientation, Structure and Function at the Solid/Liquid Interface Abstract | Full Text: HTML PDF (249K)
•
33 Grating-Based Optical Biosensors Abstract | Full Text: HTML PDF (424K)
•
34 Holographic Sensors Abstract | Full Text: HTML PDF (207K)
•
35 Introduction to Acoustic Technologies Abstract | Full Text: HTML PDF (252K)
•
36 Love Wave Biosensors Abstract | Full Text: HTML PDF (109K)
•
37 Magnetic Acoustic Resonator Sensor (MARS)
Abstract | Full Text: HTML PDF (251K)
•
38 Thermal Biosensor and Microbiosensor Techniques Abstract | Full Text: HTML PDF (279K)
•
39 Microcalorimetry and Related Techniques Abstract | Full Text: HTML PDF (246K)
•
40 Magnetic Biosensor Techniques Abstract | Full Text: HTML PDF (462K) • Part Five Miniaturized, Micro and Particle Systems
•
Miniaturized, Microengineered, and Particle Systems Full Text: HTML PDF (40K)
•
41 Introduction to Microfluidic Techniques Abstract | Full Text: HTML PDF (297K)
•
42 Practical Aspects of Microfluidic Devices: Moving Fluids and Building Devices Abstract | Full Text: HTML PDF (564K)
•
43 Polymer-Based Microsystem Techniques Abstract | Full Text: HTML PDF (249K)
•
44 Microelectrochemical Systems Abstract | Full Text: HTML PDF (128K)
•
45 Micro- and Nanoelectromechanical Sensors Abstract | Full Text: HTML PDF (413K)
•
46 Nanobiolithography of Biochips Abstract | Full Text: HTML PDF (339K)
•
47 Nanosphere Lithography-Based Chemical Nanopatterns for Biosensor Design Abstract | Full Text: HTML PDF (268K)
•
48 Quantum Dots: Their Use in Biomedical Research and Clinical Diagnostics Abstract | Full Text: HTML PDF (91K)
•
49 Manipulation and Detection of Magnetic Nanoparticles for Diagnostic Applications Abstract | Full Text: HTML PDF (154K)
•
50 The Detection and Characterization of Ions, DNA, and Proteins Using Nanometer-Scale Pores Abstract | Full Text: HTML PDF (411K)
•
51 Conducting Polymer Nanowire-Based Biosensors Abstract | Full Text: HTML PDF (323K)
•
52 Biosensors Based on Single-Walled Carbon Nanotube Near-Infrared Fluorescence Abstract | Full Text: HTML PDF (377K) • Part Six Array Technologies
•
Array Technologies Full Text: HTML PDF (40K)
•
53 Nucleic Acid Arrays Abstract | Full Text: HTML PDF (222K)
•
54 Protein Chips and Detection Tools Abstract | Full Text: HTML PDF (263K)
•
55 Surface-Enhanced Laser Desorption/Ionization (SELDI) Technology Abstract | Full Text: HTML PDF (238K)
•
56 Fiber-Optic Array Biosensors Abstract | Full Text: HTML PDF (577K)
•
57 Surface Plasmon Resonance Array Devices Abstract | Full Text: HTML PDF (170K)
•
58 Label-Free Gene and Protein Sensors Based on Electrochemical and Local Plasmon Resonance Devices Abstract | Full Text: HTML PDF (293K)
•
59 An Electrochemical Biochip Sensor for the Detection of Pollutants Abstract | Full Text: HTML PDF (249K)
•
60 Microcantilever Array Devices Abstract | Full Text: HTML PDF (211K)
•
61 Biosniffers (Gas-Phase Biosensors) as Artificial Olfaction Abstract | Full Text: HTML PDF (348K) • Part Seven Data Analysis, Conditioning, and Presentation
•
Data Analysis, Conditioning and Presentation Full Text: HTML PDF (35K) • Part Seven Data Analysis, Conditioning and Presentation
•
62 Design of Data Algorithms for Blood Glucose Biosensors Abstract | Full Text: HTML PDF (138K)
•
63 Microarray Analysis Software and its Applications Abstract | Full Text: HTML PDF (620K)
•
64 Data Validation and Interpretation Abstract | Full Text: HTML PDF (147K)
•
65 Introduction to Bayesian Methods for Biosensor Design Abstract | Full Text: HTML PDF (153K) • Part Eight Biosensor Applications
•
Areas and Examples of Biosensor Applications Full Text: HTML PDF (40K)
•
66 Genetic and Other DNA-Based Biosensor Applications Abstract | Full Text: HTML PDF (329K)
•
67 Examples of Biosensors for the Measurement of Trace Medical Analytes Abstract | Full Text: HTML PDF (154K)
•
68 Biosensors for Monitoring Metabolites in Clinical Medicine Abstract | Full Text: HTML PDF (87K)
•
69 Need for Biosensors in Infectious Disease Epidemiology Abstract | Full Text: HTML PDF (101K)
•
70 Biosensors for Neurological Disease Abstract | Full Text: HTML PDF (140K)
•
71 Utility of Biosensors in the Pharmaceutical Industry Abstract | Full Text: HTML PDF (159K)
•
72 Glucose Measurement Within Diabetes via “Traditional” Electrochemical Biosensors Abstract | Full Text: HTML PDF (491K)
•
73 Field-Operable Biosensors for Tropical Dispatch Abstract | Full Text: HTML PDF (189K)
•
74 Lateral-Flow Immunochromatographic Assays Abstract | Full Text: HTML PDF (310K)
•
75 Chip-Based Biosensors for Environmental Monitoring Abstract | Full Text: HTML PDF (83K)
•
76 Environmental Biochemical Oxygen Demand and Related Measurement Abstract | Full Text: HTML PDF (145K)
•
77 Optical Biosensor for the Determination of Trace Pollutants in the Environment Abstract | Full Text: HTML PDF (162K)
•
78 Food and Beverage Applications of Biosensor Technologies Abstract | Full Text: HTML PDF (104K)
•
79 Agriculture, Horticulture, and Related Applications Abstract | Full Text: HTML PDF (119K)
•
80 From Earth to Space: Biosensing at the International Space Station Abstract | Full Text: HTML PDF (420K)
•
81 Life Detection within Planetary Exploration: Context for Biosensor and Related Bioanalytical Technologies Abstract | Full Text: HTML PDF (239K) • Part Nine Business and Regulatory Issues
•
Commercialization, Business and Regulatory Issues Full Text: HTML PDF (38K)
•
82 Biacore—Creating the Business of Label-Free Protein-Interaction Analysis Abstract | Full Text: HTML PDF (273K)
•
83 Commercialization of DNA Arrays—Affymetrix a Case Study Abstract | Full Text: HTML PDF (82K)
•
84 RAPTOR: Development of a Fiber-Optic Biosensor Abstract | Full Text: HTML PDF (273K)
•
85 Regulatory and Validation Issues for Biosensors and Related Bioanalytical Technologies Abstract | Full Text: HTML PDF (126K) • Part Ten Implications, Trends and Perspectives
•
The Future Full Text: HTML PDF (44K)
1 Overview of Biosensor and Bioarray Technologies Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
1 INTRODUCTION
Biosensors and related bioarray techniques represent the end product of a rapidly growing field, which combines fundamental biological, chemical, and physical sciences with engineering and computer science to satisfy needs in a broad range of application areas. Not surprisingly, therefore, the term biosensor has different connotations depending on what field the user comes from: for example, to the biologist, a biosensor is “a device, which translates biological variables such as electric potentials, movement, or chemical concentrations into electrical signals”. To the chemist, a more apt definition might be “a device that uses specific biochemical reactions mediated by isolated enzymes, immunosystems, tissues, organelles, or whole cells to detect chemical compounds, usually by electrical, thermal, or optical signals”. The physicist might define a biosensor as “a device, which detects, records, and transmits information regarding a physiological change or process”. For the purpose of this review, the author defines a biosensor as “an analytical device, which converts the concentration of the target substance, the analyte, into an electrical signal through a combination of a biological or biologically derived recognition system either integrated within or intimately associated with a suitable physico-chemical transducer”.1
The term biosensor first appeared in the scientific literature in the late 1970s and the field was reviewed several times in the early 1980s.1–3 However, the first “biosensor” was generally recognized as being introduced by Clark in 19564 and subsequently exemplified by Clark and Lyons in 1962 by sandwiching soluble glucose oxidase (GOx) between an outer dialysis membrane and the gas permeable membrane of an amperometric oxygen (O2 ) electrode.5 The reduction in the concentration of dissolved oxygen was detected by the electrode and shown to be proportional to the concentration of glucose in the sample. Later, Updike and Hicks6 used a second O2 electrode to correct for oxygen variations in the sample. It was soon realized that enzyme electrodes for a variety of other clinically important analytes could be created by coupling relevant enzymes to appropriate electrode systems.7 Rechnitz8 described a selective electrode for arginine in 1977 by immobilizing living microorganisms on the surface of an NH3 gas-sensing electrode and used the term bioselective sensor. This term was subsequently shortened to “biosensor” and has remained the popular choice for any analytical device, which combines a recognition system of biological origin and a physico-chemical transducer. The biological or biologically derived element is capable of recognizing the presence, activity, or concentration of a specific target analyte in a complex mixture of other components. The recognition
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR AND BIOCHIP TECHNOLOGIES
element may comprise one of three different types: affinity biosensors are based on ligand-receptor interactions such as those involving antibodies, nucleic acids, aptamers, peptides, protein, or cell receptors, while the second principal class involves binding and catalysis, and involves enzymes, abzymes, microorganisms, organelles, plant or animal cells or tissue slices, and the third involves biomimetic receptors based on various synthetic binding and/or catalytic systems. The interaction or subsequent reaction of the recognition element with the analyte in the sample matrix results in a measurable change in a solution property, such as depletion of a reactant or formation of a product, immediately proximal to the transducer. The latter converts the change in solution property into a quantifiable and processible electrical signal. The transducer is a device, usually electronic, electroacoustic, electro-optical, electromagnetic, electrothermal, or electromechanical, that converts one type of energy (electricity, sound, light, magnetism, heat, or mechanical) into another (usually electrical) for various purposes including measurement or information transfer.
2 THE BIORECOGNITION SYSTEM
The fundamental and crucial distinguishing feature of a biosensor is the recognition system for the target analyte, since this determines both the selectivity and sensitivity of the device. Generally speaking, choice of these biological materials depends on the nature of the target analyte, its concentration in the sample matrix, the presence or absence of interfering substances, and whether the measurement is discrete “one-shot”, real-time, or continuous.
2.1
Biocatalytic Systems
Biosensors that use single or multiple enzyme sequences as the recognition and response elements are the most extensively investigated area where the target analyte is amenable to enzymatic modification and its concentration is typically in the range 10−1 –10−7 M. The high specificity and high turnover rates of enzymatic reactions suggests ways to create tailor-made sensitive and
specific enzyme-based biosensors for their respective substrates.9–12 The enzyme catalyst is integrated either on, adjacent to, or into the materials comprising the transducer in order to ensure that the biocatalytic transformation is selectively transduced into the electrical signal. From an analytical perspective, the most important classes of enzymes are the oxido–reductases, which catalyze the oxidation of substrates using molecular oxygen, NAD+ , or pyrroloquinoline quinine (PQQ), and the hydrolases, which catalyze the hydrolysis of substrates.2,3 The oxidation of glucose catalyzed by GOx is an example of the archetypal enzyme biosensor: Glucose + O2 → Gluconic acid + H2 O2 H2 O2 → 2H+ + O2 + 2e−
(1) (2)
with the steady-state current produced by oxidation of the product hydrogen peroxide on a platinum electrode poised positive (∼ + 0.7 V) relative to an Ag/AgCl reference electrode.13 Good precision and accuracy were obtained with 100-µl blood samples, but since then a wide range of amperometric enzyme electrodes, differing in electrode configuration, material, membrane composition, or immobilization approach have been described.12 Intense activity during the 1980s focused on the development of mediator based “second-generation” glucose biosensors,14,15 the use of modified electrodes for enhancing the sensor performance16,17 , and the introduction of commercial strips for self-monitoring of blood glucose.18,19 During the late 1980s and early 1990s, attention was focused on promoting direct electrical communication between the redox center of GOx and the electrode surface20–22 and the development of minimally-invasive subcutaneously implantable devices.23–25 Enzymes isolated from extremophilic organisms such as thermophilic, hyperthermophilic, psychrophilic, halophilic, acidophilic, and alkaliphilic organisms have extended the range of conventional enzyme-based biosensors26,27 by improving key operational parameters. Furthermore, enzymes have been cloned, overexpressed and engineered by site-directed and other mutagenesis techniques to improve sensor performance such as lifetime, thermostability, pH tolerance, and kinetic properties. For example, the PQQ-dependent glucose
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES
dehydrogenase (GDH) from Klebsiella pneumoniae has been engineered to enhance thermostability by a single amino acid replacement,28 luciferase stability has been improved by multiple replacements29 and the Km value for a cyanidase from Pseudomonas stutzeri has been made more suitable for its analytical application.30 Organelles (mitochondria, microsomes, and chloroplasts), whole cells (bacteria) and tissue slices (plant and animal sources) have been used extensively as biocatalytic packages in biosensors for a large range of analytes of clinical, environmental, or defence interest.31 Such packages include all the numerous enzymes and other cofactors required to convert substrates into products in an evolutionary optimized environment.32,33 However, a major drawback with the use of such systems is their multiple content of enzymes, which results in decreased substrate specificity and relatively slow response times. Nevertheless, whole-cell systems also have advantages since by altering the external conditions, different substrates can be measured with the same biocatalytic system, and the use of inhibitors, activators and stabilizing agents can be used to optimize the selectivity and lifetimes of cell- and tissue-based biosensors.33 Whole-cell sensors are highly appropriate for the monitoring of genotoxic substances34 and obviate the expense and time required to perform bioassays. Wholecell assays based on the use of geneticallyengineered bioluminescent bacteria have become very popular since they are more rapid and costeffective than traditional methodologies.35
if durable antibodies with affinities >10−10 M are used.39 Furthermore, a high affinity constant coupled with a labile immobilized antibody, makes regeneration of the transducer surface difficult and limits practical application to single-use devices.40 Natural receptor systems have also been investigated as recognition-response elements in biosensors. However, while ion-channel devices have been proposed,41 the stability of the lipid membrane, the incorporation of the receptor into these structures, and the combination of the modified membrane with the transducer initially proved problematic and conspired to limit their introduction in practice. However, the use of a stable membrane from a thermophilic bacterium containing gramicidin ion channels coupled to a microgold electrode (<30-µm diameter) looks more promising.42 There are two antibodies on the membrane, one tethered to the channel and the other is fixed to the electrode. When the target analyte bound to both antibodies, in a sandwich assay, the ion channel was interrupted and the current to the electrode reduced. Using this approach, the target protein was detected at nanomolar concentrations. In a related technique, engineered protein pores have been exploited for the rapid, sensitive, selective, and reversible monitoring of a variety of analytes43 ; for example, heteromeric protein pores were used for the detection of single or multiple divalent MeII ions by measuring the change in ionic current passing through single pores in planar lipid bilayers.
2.3 2.2
Affinity Binding Systems
Antibodies and their various truncated antigenbinding elements are the most commonly employed biorecognition systems for use in biosensors for analytes at concentrations in the 10−6 –10−10 M range. Whole polyclonal and monoclonal antibodies, recombinant antibodies, phage display systems, Fab, single chain antibodies (scfv), and minibodies have all been exploited in biosensors.36,37 The sensitivity and specificity of an immunosensor are governed by specificity and affinity of the antigen–antibody interaction and the signal-noise ratio of the transducer.38 However, in practice, adequate sensitivity can only be achieved
3
Synthetic Biomimetic Systems
Issues associated with cost-effectiveness, manufacturability, and durability tend to mitigate against the use of natural biological recognition systems in biosensors in favor of synthetic equivalents. Molecularly imprinted polymers are artificial recognition systems, which mimic natural molecular recognition44–46 and are of two types, covalent and noncovalent. These systems have been exploited in sensors for a variety of analytes, including pesticides, biotin derivatives, metalloporphyrins, sterols, polymers, anti-idiotypes and chloramphenicol.47 However, some difficulties associated with complete removal of the template molecule, kinetics, selectivity, and affinity still remain with this emerging technology.
4
BIOSENSOR AND BIOCHIP TECHNOLOGIES
Aptamers, from the latin aptus, meaning “to fit”, are artificial nucleic acid ligands that can be generated from combinatorial libraries of oligonucleotides by an iterative process of adsorption, recovery, and reamplification, can be generated against amino acids, drugs, proteins, and other molecules.48 Aptamers were first reported in 1990 and possess the ability to discriminate targets on the basis of subtle structural differences and with selectivity, specificity, and affinity, equal and often superior to those of antibodies.49,50 Typically, libraries of at least 1013 –1018 independent oligonucleotide sequences are employed. A number of “aptasensors” have now been reported, such as those recognizing thrombin51 and cocaine.52 Aptamers have several advantages compared to antibodies: they are stable to long-term storage, are produced by chemical synthesis resulting in little or no batch-to-batch variation, the binding partners can be regenerated within minutes and the kinetic parameters, such as on/off rates can be selected on demand.48 Peptide nucleic acid (PNA) is an artificial oligo-amide comprising N -(2-aminoethyl)-glycine with each nucleobase attached to the backbone through a methylenecarbonyl linker that forms highly stable complexes with nucleic acids of complementary sequence53 PNA forms both double-stranded and triple-stranded complexes with oligonucleotides and has been used as a biosensor recognition element.54 Finally, low molecular weight affinity ligands designed and synthesized de novo from the x-ray crystallographic structure of the target protein have been exploited in optical biosensors. A triazinebased ligand with demonstrated selectivity for human insulin has been immobilized to the surface of a surface plasmon resonance (SPR) device and used for monitoring recombinant insulin in process media.55
3 IMMOBILIZATION TECHNIQUES
Immobilization of the recognition system on the transducer is essential to promote easier biosensor manipulation, operation and reuse and hence leading to longer use times and potential cost-savings. Numerous methods based on physical or chemical processes have been developed since the 1960s and involving adsorption,
entrapment in inorganic or organic gels, confinement within semipermeable membranes, and various functionalization, cross-linking, and photoimmobilization strategies.11,56 However, three methodologies are worthy of further mention; electro-deposition, photo-polymerization, and soft patterning approaches allow immobilization of the biorecognition system with XY-dimensionality and are therefore applicable to multiplexed or array systems. For example, the use of electronically conducting polymers allows the deposition of recognition systems in defined regions of small area electrodes.57 The technique was originally developed as a mild procedure to deposit enzymes in polypyrrole onto microamperometric16,20,58,59 or microconductimetric electrodes,60 and has since been revived to graft GOx onto a poly(dicarbazole) film covered electrode by immersion in an aqueous solution61 and oligothiophene-based polyamide thin films fabricated by vapor deposition.62 It has been suggested that electropolymerized films prevent interferences and electrode fouling in biosensors. Photoimmobilization through p-nitrophenylazides or photodeprotection has been used extensively for the fabrication of oligonucleotide and protein arrays.63,64 Finally, soft lithography has been used for patterning proteins and cells.65
4 TRANSDUCER TECHNOLOGIES
The transducer is the device that converts a wide range of physical, chemical, or biological effects into an electrical signal with high sensitivity and minimum disturbance to the measurand. Transducers are often described in terms of their sensitivity to input signals or responsivity, which is simply the ratio of the output to input signals. Different types of transducers act on heat, light, sound, magnetism, electricity, radiation, strain, vibrations, pressure, and acceleration, and most types have been used in biosensors at some point in time.
4.1
Electrochemical Transducers
Biosensors based on electrochemical transducers are the most common and most frequently cited in the literature. In fact, the entire history
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES
of biosensors can be traced back to the original enzymatic glucose sensor introduced over 40 years ago and based on current measuring or amperometric techniques.5 Amperometry takes advantage of the fact that certain electroactive chemical species are oxidized or reduced (redox reactions) at conducting electrodes driven at a constant applied potential. A variety of electrode materials have been exploited, including noble metals, graphite, semiconductors, electronically conducting polymers, paper, and conducting salts such as tetrathiafulvaliniumtetracyanoquinomethane (TTF-TCNQ).66 Coulometry determines the total amount of charge (coulombs) passing between two electrodes, which is directly proportional to the oxidation or reduction of the electroactive species at one electrode.67 The number of coulombs passed in this process is related to the absolute amount of electroactive substance by Faraday’s Law: n = Q/zF
(3)
where n is the amount of substance oxidized or reduced in moles, Q is the amount of charge transferred in coulombs, z is the number of electrons transferred in the redox reaction and F is the Faraday constant (96 487 C mol−1 ). Potentiometry measures the difference in electrical potential between two electrodes when the cell current is zero and this technique is used in ion selective electrodes (ISE), such as the classical glass pH electrode. When linked with appropriate enzyme systems, ISEs act as transducers in potentiometric biosensors. For example, a biosensor for blood urea nitrogen (BUN) has been constructed on a polyvinyl chloride ISE for NH4 + using the ionophore nonactin.7 Subsequent attempts to miniaturize ISEs using microfabrication technology have met with mixed success. The principles underpinning the ion selective field effect transistor (ISFET) and its manifestations with enzyme (ENFET) and antibody (ImmunoFET) coated gates are well understood.68 The potentiometric electrode has been proposed as a direct probe for following antigen–antibody reactions by monitoring the change in surface charge density on formation of the complex. However, this simple concept has been difficult to realize in practice, largely due to the high interfacial charge resistance required and the susceptibility of the sensor
5
itself to matrix effects with biological samples. These concerns with bioFETs revolve around the construction and transduction mechanisms, the stabilities of the sensing membranes and coatings, and the biology of the sample, particularly with respect to biocompatibility, buffer capacity, and enzyme loading and lifetime. The major technical hurdles appear to reside in miniaturization, especially with respect to referencing and instability, associated with degradation of encapsulation or the absence of a well-defined thermodynamically reversible interface between the recognition element and the transducer electronics.69 These inherent issues boil down to two—packaging and drift—and lead to disappointing results with most impedance and potentiometric measurements aimed at the direct detection of an immunological reaction at the surface of an electrode or gate region.70 Nevertheless, the recent introduction of the enzyme-channeling immunopotentiometric sensor71 and the use of polycationic labels72 have given some room for optimism. Potentiometric sensors exhibiting responses to polycation-labelled analytes have been demonstrated with submicromolar levels of the drug theophylline being measured without any washing or separation steps. Electrochemical devices have been developed for detecting other polyelectrolytes such as DNA sequences for the construction of genoelectronic chips.73 These devices are based on the detection of hybridization, on redox intercalation for doublestranded DNA detection, on DNA-mediated electron transfer, on signal amplification with enzymes such as peroxidase or PQQ-dependent GDH.
4.2
Optical Transducers
Optical transduction methods have attracted a great deal of interest in the biosensors field for many reasons: they have a long history of use in chemical and biochemical analysis, they work well in aqueous solution, the methods are nondestructive, and can be used for real-time analysis and kinetic measurements, the methods can be configured to be surface-specific, i.e. only respond to adsorbed species at or close to the transducer surface such that interference from the bulk solution is minimized, and finally, they are sensitive. The number of receptor molecules that can be bound to a planar surface is relatively low; for example,
6
BIOSENSOR AND BIOCHIP TECHNOLOGIES
for a medium size protein such as streptavidin (∼72 000 Da) quantitative surface coverage corresponds to about 1010 molecules mm−2 . This overview will only cover those optical methodologies, which satisfy all of the above advantages without the requirement for sample preparation, washing, or various amplification techniques and which are generally referred to as direct optical sensors.74,75 Direct detection is based on the difference in refractive index (n) between water (n600 nm ∼ 1.333) and biological molecules (n600 nm ∼ 1.5), which results in a minute change in the refractive index at the surface of the transducer when a biological molecule of typical diameter 4 nm binds. Two fundamentally different detection principles have been introduced for the direct measurement of biological reactions on surfaces: the first is based on the interference of light reflected from planar multilayer structures. Ellipsometry and related reflectometric methods measure the optical thickness of the biomolecular layer74,76,77 and are less well developed than the second major type of direct optical sensor principle based on guided electromagnetic wave modes, a waveguide mode, or a surface plasmon polariton mode, which are effectively highly sensitive refractometers that measure the refractive index of the solution proximal to the surface.74 Waveguiding exploits the phenomenon of total internal reflection within a high refractive index material bounded on either side by two low refractive index media. Total internal reflection of the light beam at the interface of the waveguide generates an exponentially decaying electromagnetic field, the so-called evanescent wave, in the less dense media, which is described by: Es = E0s e−βz
(4)
where Es is the electric field outside the waveguide and β is given by: β = ks
n2w sin2 θ −1 n2s
(5)
where nw and ns are the refractive indices of the waveguide and sample respectively, ks is the wave vector along the propagation direction and 1/β is the decay length of the evanescent field, typically in the range 100–300 nm for visible light. For light
to couple into a waveguide, both the energy of the light and the component of the wave vector kx along the propagation direction should be identical for both the waveguide mode and the incident light beam. This condition is usually met by shining the incident beam on the end face of the waveguide (end-fire coupling), by totally internally reflecting light at the base of a prism in close contact with the waveguide (prism coupling) or by coupling externally incident light into the waveguide by diffraction (grating coupling).74 Surface plasmon polariton modes resemble planar waveguide modes in many respects except that they propagate at the interface between a metal and a dielectric, but are attenuated laterally as they travel by absorption in the metal film. Surface plasmons have typical propagation distances of 4 µm and 25 µm on gold and silver surfaces respectively. As in the case of guided modes, the intensity of the electric field associated with the surface plasmon mode decays exponentially according to the above equation where β is defined by: β=
2π λ0
n2s + n2 εm s
(6)
where λ0 is the wavelength, ns is the refractive index of the sample and εm is the real part of the dielectric constant of the metal layer. A number of sensor geometries have been developed, which exploit these guided wave principles. Probably, one of the earliest was the use of a grating coupler system using a collimated beam of light from a low power laser78 to excite a waveguide and detect the presence of adsorbed protein with a surface coverage of 2 pg mm−2 within an hour.79 A monomode fibre optic waveguide sensor has also been proposed.80 The best known example of a prism coupled system is that of the so-called resonant mirror (RM).81–83 This device comprises a high refractive index lead-doped glass cube, a low index (SiO2 ) spacer layer about 500-nm thick and a high refractive index, typically hafnia (nD ∼ 2; thickness ∼100 nm), waveguiding layer. Laser light at 670 nm is passed through a polarizer to equalize the transverse electric (TE) and transverse magnetic (TM) intensities and then swept across one face of the cube until it reaches the “resonance angle” from where it couples into the high index layer and an evanescent field is established
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES
at the aqueous/high index interface. At the lower surface light couples out and interferes with the light reflected from the top of the cube. This system is available commercially as IASysTM and has been used extensively to study protein–protein, whole cell, protein–lipid, protein–carbohydrate, and nucleic acid interactions.83 The sensitivity of the RM has been reported to be better than 9 pg mm−2 .83 Two different types of waveguide interferometer75 have also been developed for use as direct immunosensors: the Mach–Zehnder interferometer (MZI) uses two spatially separated waveguides, a sensing and a reference arm,84 while the polarimetric interferometer uses two different guided modes, usually TE and TM, to interrogate the same sensing sweet spot.85 In the MZI, the measurement arm is coated with the biorecognition system such that binding of the analyte changes the effective refractive index of the waveguide, neff , and thus the propagation or phase velocity of the guided wave. The wave recombines with the guided wave emanating from the reference arm to give an output signal, which depends on their phase difference and hence neff and the mass of analyte bound can be determined. If the change in refractive index at the surface nc is small, then the phase change, φ, is given by:
2π φ = L λ0
∂neff ∂nc
nc
(7)
where L is the interaction length of the measurement with bound receptors, λ0 is the wavelength of the light source and neff the effective refractive index of the waveguide mode. Providing the lengths of the two arms are identical, the sensitivity of the device increases with interaction length L and sensitivities better than 1 pg mm−2 can be achieved.86 The second approach, polarimetric interferometry, uses different guided modes as measurement and reference beams. Polarized light is end-coupled into the waveguide such that both TE0 and TM0 modes are coherently excited and propagate through the waveguide, from where the phase difference induced by binding of the analyte to receptor molecules coated on the waveguide is analyzed by polarimetry.87 Binding of the complementary biomolecule to the receptor on
7
the surface of the waveguide changes the effective refractive index, neff , of the waveguide, and since the distribution of field strengths is different for the TE0 and TM0 modes, the change in effective refractive index, neff , is also different between the two modes: observation of the outcoupled light shows that there is a change in phase difference, which can then be related to analyte loading. Unfortunately, both interferometric principles require accurate optical alignment to achieve the best results. Optical fibre sensors employ an optical fibre or fibre bundle both as a platform for the biological recognition system and as a conduit for the excitation and/or return signal.88 Their inherent advantages and disadvantages are well established. Optical measurements in fibre sensors are generally based on the use of conventional enzyme, cell, or oligonucleotide assays linked into a detection mode comprising absorbance, reflectance, fluorescence, chemiluminescence, bioluminescence, or electrogenerated chemiluminescence.88 However, these sensors only exploit the fibre as a light guide and do not exploit some of the more interesting properties of fibre optics. Early work demonstrated that a single-mode fibre optic evanescent wave biosensor could be fabricated80 while more recently an optical fibre based SPR sensor has been demonstrated.89,90 Most optical fibre based SPR devices exploit propagating SPR with multimode fibres, which are side polished to expose the core and then coated with a thin metal layer to support plasmon waves.89,90 Unfortunately, multimode fibres suffer from reduced resolution due to modal noise, whilst side polished fibres are susceptible to fibre deformation. Single-mode tapered fibre SPR systems have been proposed, although these too suffer from limited sensitivity due to operation at shorter wavelengths or in amplitude interrogation mode.91,92 More recently, two other techniques have been used with fibre optic sensors: the first exploits localized SPR on a sensor fabricated by depositing self-assembled colloidal gold on the exposed core of a fibre optic sensor,93 whilst the second uses light from a blue LED (∼470 nm) guided by a fibre optic and reflecting off a 300-nm-thick layer of gold deposited on a silica substrate.94 Any change in the refractive index surrounding the gold, such as would be induced on binding proteins or other biological species, produces a change in
8
BIOSENSOR AND BIOCHIP TECHNOLOGIES
reflectivity of the gold, since gold behaves as a dielectric for blue light. The extensive literature on the development of fibre optic chemical sensors and biosensors has paved the way for the introduction of fibre optic nanosensors.95 Sub-micron sensors with distal diameters between 20 and 500 nm have been used to study submicron spatial resolution using near field scanning optical microscopy (NSOM), biochemicals on surfaces with surface-enhanced Raman scattering (SERS) at 100 nm resolution and analytical targets within single cells.95 Such sensors have been used for the measurement of pH, ions, and other chemical species: for example, they have been used for the measurement of Na+ concentrations in the cytoplasm of a single mouse oocyte and were able to monitor the relative concentrations of Na+ as ion channels were opened and closed in response to the external stimulant, kainic acid.96
4.3
Acoustic Transducers
The development of new acoustic sensors has lagged behind those of electrochemical and optical devices, although recent research in the area suggests that the applications of acoustic wave sensors will expand significantly in the future. An acoustic wave propagates in a solid as a deformation of the crystal structure, which if it occurs in a time-dependent fashion, gives rise to a wave motion with each atom oscillating about its equilibrium position. The simplest acoustic waves, plane waves, comprise two types depending on their polarization: longitudinal waves oscillate in the direction of propagation, while shear waves vibrate in the plane normal to the propagation direction. The waves can propagate on the surface of the medium, surface acoustic waves (SAWs), in the bulk medium, bulk waves, or be generated on the surface but propagate in the bulk medium, surface generated bulk waves.97 SAWs also comprise many types, including Rayleigh waves (longitudinal waves with a shear 1/2πphase shifted component), Love waves (horizontally polarized shear waves) and Stoneley waves (sagittally polarized waves), while surface generated bulk waves can exist as surface skimming bulk waves (SSBW) and acoustic plate mode (APM) waves.
Acoustic wave devices exploit piezoelectric materials for the excitation and detection of the wave since these materials can convert electrical signals into acoustic waves and vice versa. Quartz (SiO2 ), cadmium sulfide (CdS), zinc oxide (ZnO), gallium arsenide (GaAs), lithium tantalite (LiTaO3 ), lithium niobate (LiNbO3 ), lithium tetraborate (Li2 B4 O7 ) and bismuth germanium oxide (Bi13 GeO20 ) are piezoelectric materials. Quartz is weakly piezoelectric although it is the most commonly employed material since it is readily available and different cuts of the quartz crystal give rise to acoustic devices with different properties.97 The most common acoustic wave device is the thickness-shear mode (TSM) resonator or quartz crystal microbalance (QCM), which consists of a parallel-sided disc of crystalline quartz with actuating electrodes on both sides. If the thickness of the plate is small compared to its major dimensions, then application of an RF potential across the electrodes causes the plate to resonate at a fundamental frequency (f0 ) given by: f0 =
VB 2d
(8)
where is the plate thickness and VB is the bulk wave propagation velocity. Frequencies up to about 50 MHz are feasible although higher frequencies are problematic since thinner, more fragile, crystals are required. Adsorption of foreign material on the crystal surface will result in an increase in disc thickness and thus cause a change in resonant frequency according to the so-called Sauerbrey equation98 : m f = −2f02 √ A µq ρq
(9)
where f is the change in frequency due to mass deposition, f0 is the fundamental frequency of the naked device, m is the deposited mass, A is the coated area, ρq is the density of the substrate and µq is the shear modulus of quartz. This equation only applies to AT-cut quartz crystals vibrating in shear thickness mode in vacuo and makes the assumption that the change in frequency is attributable only to a change in thickness of the crystal. Sadly, not only does immersion of an oscillating crystal into a
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES
liquid sample create energy losses through viscous coupling, but deposited biomaterials have a different density to quartz and themselves display viscoelastic properties. Kanazawa & Gordon (1985) took this into account and derived the following equation99 : f =
−f032
ρl η l πρq µq
(10)
where ηl and ρl are the viscosity and density of the viscous material, and ρq and µq are the density and shear modulus of the quartz crystal respectively. This analysis shows that only a thin layer of the viscous liquid will undergo displacement at the surface of the resonant device and that the response of the resonator will be a function of both the viscosity and mass of this proximal layer. The TSM resonator has been applied to the study of biological interactions such as DNA/RNA hybridization, biotin–avidin complex formation, biomolecule and cell adsorption, antigen/antibody binding, and receptor-lipid bilayers. SAW devices operating in the shear mode are fabricated by depositing metal electrodes on the surface of a piezoelectric substrate with alternate electrodes or fingers being attached to two different connection bars. When an alternating voltage is applied across the two connection bars, oscillating electrical fields and consequently acoustic vibrations, are induced between each finger pair and propagate, given an appropriate choice of the piezoelectric substrate and orientation, along the device. A second set of interdigitated fingers detects the propagating wave by the converse mechanism. The spacing between the fingers (λ) determines the operating frequency (f0 ) of the SAW device according to: f0 =
Vs λ
(11)
where Vs is the velocity of the surface wave. Interdigitated transducers can also excite bulk acoustic waves such as SSBW, Love waves, and APMs in a SAW device.100 Other devices that have been reported include the fibre acoustic wave (FAW) device,101 tube acoustic wave devices,102 ball SAW devices103 , and film bulk acoustic resonator (FBAR) devices.104
9
The quest for improved sensitivity is still a major driving force in acoustic sensor development and may be achieved by making the devices smaller, such that the ratio of bound mass to the overall vibrating mass ( m M ) is optimized, or by increasing the resonant frequency. The socalled magnetic acoustic resonator sensor (MARS) uses a planar coil to generate an electromagnetic field at radio frequencies.105 This field induces eddy currents in a thin metallic film deposited on the underside of a nonpiezoelectric resonant disc, which, in the presence of a strong magnetic field induce Lorentz forces and drive the resonator. Several acoustic waves can be excited if the frequency of the applied current coincides with the resonant frequencies of the disc. The two key features of this system are the high quality (Q) factor of the mechanical oscillator and the ability to excite harmonics up to the GHz range.106,107 Silicon microfabrication technology has been exploited to detect even smaller mass changes, to integrate circuitry and to permit mass production at low cost.108 Cantilever devices fabricated in silicon, silicon nitride, or silicon dioxide are commercially available in a variety of dimensions and configurations and can be used in resonant or nonresonant modes. In resonant mode, the deposited mass reduces the resonant frequency of the cantilever, where the mass sensitivity is determined by the force constant, a function of the geometry and apparent Young’s modulus.108 In nonresonant mode, changes in surface stress of the cantilever as a result of physical interaction or chemically-induced swelling or conformation of adsorbed polymers, result in cantilever bending. In a liquid sample, the outof-plane vibration of the cantilever is strongly damped and results in reduced Q-factors in the tens, although it can be enhanced by incorporating a monolithographically integrated differential feedback circuit and a cantilever with electromagnetic actuation.109 Alternative procedures avoid the out-of-plane vibration either by using a discshaped microstructure operating in a rotational in-plane mode110 with resonance frequencies in the range 300–700 kHz and a Q-factor in water of 100 or by feeding the analyte through channels buried in the cantilever.111 The cantilever still vibrates in air with the mass change resulting from adsorption of the target molecules on the
10
BIOSENSOR AND BIOCHIP TECHNOLOGIES
walls of the channel and the difference in density between the adsorbed molecule and the bathing buffer.111 There is continuing interest in microgravimetric sensors due to the fact that mass is a universal molecular property, which does not require any charge transfer or specific labelling, and sensors based on such measurements work well in viscous and opaque sample media. Sensitivity is the current limiting factor compared to optical technologies, although recent advances in high Q and high frequency may well change this perspective.105–107,112,113 4.4
Other Transducer Technologies
Electrochemical, optical, and acoustic transducers probably account for well over 90% of the published literature in label-free biosensors. However, two other approaches based on thermal and magnetic principles are worthy of mention since they have found extensive commercial application. For example, it is well-known that when molecules interact with each other, heat is either generated or absorbed. Measurement of this change in heat allows determination of binding constants, reaction stoichiometry, and the thermodynamic profile, enthalpy and entropy, of the interaction.114 The “gold standards” for characterizing the thermodynamics and stoichiometry of molecular interactions are isothermal titration calorimetry (ITC), which does not require immobilization and/or modification of reactants, and differential scanning calorimetry (DSC), which measures ligand-induced conformational changes in macromolecules and by measuring the temperature (Tm ) at which these transitions occur and the corresponding heat capacity (Cp ), detailed information on the dynamic structures of macromolecules can be obtained.115,116 The total heat evolved in a biochemical transformation (Q), such an enzyme catalyzed reaction, is proportional to the molar enthalpy change (H ) and to the total number of moles of product (np ) created: Q = −np (H ) (12) and on the heat capacity (Cp ) of the system, including the solvent: Q = Cp (T )
(13)
where the temperature change recorded by the biosensor (T ) is directly proportional to the enthalpy change, and thus: T = −
(np H ) Cp
(14)
Enthalpy changes for most enzymatic catalyzed reactions lie within the range −10 to −200 kJ mol−1 and the temperature changes are measured on thermomechanical, thermoresistive, thermocouple, or junction based transducers. The most commonly employed transducers are based on thermistors, thermocouples, or thermopiles,117 although most systems now integrate the microfluidic reactor with the thermal transducer.118 Thermal biosensors have been widely exploited to determine metabolites, blood analytes, and various applications in amplified enzyme-linked immunosorbent assay (ELISA), on-line monitoring of bioprocesses, chromatographic elution, environmental control, and measurements in organic solvents. The evolution of magnetic biosensors was based on the early use of magnetic force microscopy to apply indirect forces to biomolecular bonds119 and subsequently introduced as a bead array counter (BARC) concept120 using a microfabricated magnetoresistive transducer. By adapting giant magnetoresistive (GMR) computer technology, it was perceived as possible to fabricate millions of transducers on a single chip. This system has been developed to monitor multiple analytes simultaneously with 64 sensor zones and a detection threshold of approximately 10 assay-ready Dynal M-280 microbeads (2.8 µm diameter) per 200 µm diameter sensor121 and for the detection of biological warfare agents.122 Single beads fabricated from Ni30 Fe70 could be detected although issues of biocompatibility remain. Two encouraging trends are emerging in this area: first, the rapid detection of biological target molecules by using sperparamagnetic nanoparticles and a high-transition temperature dc superconducting quantum interference device (SQUID)123 , which may bring down the detection limits to single molecules, and secondly, the ability to magnetic resonance image using magnetic field strengths in the microtesla range.124
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES
5 BIOARRAY TECHNOLOGIES
In principle, the recognition elements, immobilization approaches, transducer and measurement techniques involved in bioarray technologies are not very different from conventional biosensor technologies. In reality, however, there is considerable confusion over the definition of the term and whether it should include dot blots, microtiter plate assays, suspension arrays, multiplexed bead assays and various encoded microsphere assays or be restricted solely to “spatially ordered, miniaturized arrangements of a multitude of immobilized reagents”.125 The latter definition is used here where the devices are usually classified according to the type of immobilized reagent or probe; for example, microarrays involving DNA (gene expression profiling), oligonucleotides (single nucleotide polymorphisms), proteins (diagnostics), antibodies (immunoassays), haptens (immunosensors), peptides (high-throughput pharmaceutical screening), carbohydrates (cellular communication), synthetic chemicals (screening), tissues (localization of proteins) and whole cells (toxicity assays), rather than the analytes they are targeting.125 However, in almost all of these cases, the measurement mode or readout is indirect and usually based on fluorescence or some similar reporting strategy. An early paper describing “microspot multianalyte immunoassays” lead to a true paradigm shift in analytical chemistry126 and stimulated the development of photolithographic techniques127,128 for the synthesis of high-density arrays of peptides and oligonucleotides.128 It is worth noting that the term microarray was largely unknown before being introduced in the mid1990s.129,130 Today, DNA and oligonucleotide microarrays are overwhelmingly dominant, partly due to the relatively facile synthesis and chemical durability of DNA and partly to the substantial applications pull from gene expression profiling, singlenucleotide polymorphism identification, paternity and forensic testing, and high-throughput sequencing, with direct on-surface synthesis and PCR amplification being performed routinely.131 The first so-called DNA chip was developed for the quantitative monitoring of gene expression patterns using complementary deoxyribonucleic acid (cDNA) with attached fluorescent labels to probe the array.129 Several reviews have summarized
11
the current state-of-play with 2D and 3D DNA chip array technology.37,132–134 Plasma polymerized hexamethyldisiloxane (HMDS) films have been used to bind biotinylated oligonucleotides to a DNA array with a claimed improvement in nonspecific DNA binding compared to the more conventional poly-L-lysine coated glass chips.135 Protein microarrays are more problematic due to the inherent lability of proteins, the fact that no direct on-chip synthesis is feasible and the difficulties associated with high-throughput expression and purification of recombinant proteins.125 Protein chips are used primarily in proteomics and are produced by using contact or noncontact arraying systems. Both systems have their merits, although the reliable production of protein arrays is still some way off. The detection of binding events on oligonucleotide or protein chips is usually achieved with various labelled reagents. Most frequently used are fluorescent dyes, or enzymes, which catalyze a luminescent reaction, with detection being achieved with sensitive charge coupled devices (CCD), or with sensitive evanescent field techniques, SPR, reflectometric interference spectroscopy, or mass spectrometry.125 Array reading technologies based on microamperometry, acoustic wave techniques, magnetic, and thermal labelling are also known.
6 APPLICATIONS OF BIOSENSORS AND BIOARRAYS
In principle, biosensors and bioarray technologies can be applied in any circumstance where chemical intelligence is required quickly, accurately, and proximal to where the analytical sample is taken. The major applications sectors are clinical, environmental, industrial, security and defence, food and beverage, and toxicity monitoring. For example, sensors have been developed for biological oxygen demand (BOD), detergents, phosphates, acid rain, red tide, toxicity, insecticides, herbicides, odors, meat quality, fish freshness, fermentation and bioreactor processes, food components, and allergens.37 Several reviews have summarized the applications of biosensors in the environmental,136 electrochemical,137 clinical,67 and security31 sectors.
12
BIOSENSOR AND BIOCHIP TECHNOLOGIES
7 SUMMARY
The substantial and ever burgeoning academic literature reporting biosensor research reflects a number of converging events: excitement associated with the vision that many biological, chemical, physical, and engineering disciplines focusing in on a single analytical science sector must deliver something of value, frustration that, as yet, such elegant devices have not found a commercial niche, with the exception of blood glucose devices, and exasperation coupled with an unswerving belief that such devices really must find a home in the not too distant future. The recent history of these efforts reminds us of several important facts: first, that the notion that such a facile concept as a biosensor can be realized simply by coupling two or more sciences without much intervening experience is not borne out by the two to three decades of research to date and the necessary complexity of the resulting technology; secondly, biosensors are really not very clever devices—they combine a very smart bit of biology with a transducer of near zero intelligence quotient; thirdly, the market is king, and is not unduly influenced by elegant science that does not satisfy unmet needs. The old adage that new technology has to be “10 times cheaper or 10 times better” still holds sway in the open market. Finally, the marriage of biology with physical science seemed like a good idea nearly three decades ago, but history has taught us that taking physics to biology is a lot more productive than taking biology to physics.
8.
9.
10.
11.
12. 13.
14.
15. 16.
17.
18. 19.
REFERENCES 20. 1. C. R. Lowe and M. J. Goldfinch, Novel electrochemical sensors for clinical analysis. Biochemical Society Transactions, 1983, 11, 448–451. 2. C. R. Lowe, Biosensors. Trends in Biotechnology, 1984, 2, 59–65. 3. C. R. Lowe, An introduction to the concepts and technology of biosensors. Biosensors, 1985, 1, 3–16. 4. L. C. Clark Jr., Monitor and control of blood and tissue oxygen tensions. Transactions American Society for Artificial Internal Organs, 1956, 2, 41–57. 5. L. C. Clark Jr. and C. Lyons, Electrode systems for continuous monitoring in cardiovascular surgery, Annals of the New York Academy of Sciences, 1962, 102, 29–45. 6. S. J. Updike and G. P. Hicks, The enzyme electrode. Nature, 1967, 214, 986–988. 7. G. G. Guilbault, Enzyme Electrodes, in Biomedical Applications of Immobilized Enzymes and Proteins,
21.
22.
23.
T. M. S. Chang (ed), Plenum Press, New York, 1977, 163–176. G. A. Rechnitz, R. K. Kobos, S. J. Reichel, and C. R. Gebauer, A bioselective membrane electrode prepared with living bacterial cells. Analytica Chimica Acta, 1977, 94, 357–365. M. J. Goldfinch and C. R. Lowe, Solid-phase optoelectronic sensors for biochemical analysis. Analytical Biochemistry, 1984, 138, 430–436. E. Katz, V. Heleg-Shabtai, B. Willner, I. Willner, and A. F. B¨uckmann, Electrical contact of redox enzymes with electrodes: novel approaches for amperometric biosensors. Bioelectrochemistry and Bioenergetics, 1997, 42, 95–104. M. M. F. Choi, Progress in enzyme-based biosensors using optical transducers. Microchimica Acta, 2004, 148, 107–132. J. Wang, Glucose biosensors: 40 years of advances and challenges. Electroanalysis, 2001, 13, 983–988. G. G. Guilbault and G. Lubrano, An enzyme electrode for the amperometric determination of glucose. Analytica Chimica Acta, 1973, 64, 439–455. A. Cass, G. Davis, G. Francis, H. A. O. Hill, W. Aston, I. J. Higgins, E. Plotkin, L. Scott, and A. P. Turner, Ferrolene-mediated enzyme electrode for amperometric determination of glucose. Analytical Chemistry, 1984, 56, 667–671. J. Frew and H. A. O. Hill, Electrochemical biosensors. Analytical Chemistry, 1987, 59, 933A–944A. N. C. Foulds and C. R. Lowe, Enzyme entrapment in electrically-conducting polymers. Journal of the Chemical Society, Faraday Transactions, 1986, 1, 1259–1264. R. W. Murray, A. Ewing, and R. Durst, Chemically modified electrodes. Molecular design for electroanalysis. Analytical Chemistry, 1987, 59, 379A–390A. P. Hilditch and M. Green, Disposable electrochemical biosensors. Analyst, 1991, 116, 1217–1220. J. P. Hart, A. Crew, E. Crouch, K. C. Honeychurch, and R. M. Pemberton, Some recent designs and developments of screen-printed carbon electrochemical sensors/biosensors for biomedical, environmental, and industrial analyses. Analytical Letters, 2004, 37, 789–830. N. C. Foulds and C. R. Lowe, Immobilisation of glucose oxidase in ferrocene-modified pyrrole polymers. Analytical Chemistry, 1988, 60, 2473–2478. Y. Degani and A. Heller, Direct electrical communication between chemically modified enzymes and metal electrodes. I. electron transfer from glucose oxidase to metal electrodes via electron relays, bound covalently to the enzyme. Journal of Physical Chemistry, 1987, 91, 1285–1289. T. Ohara, R. Rajogopalan, and A. Heller, ‘Wired’ enzyme electrodes for amperometric determination of glucose or lactate in the presence of interfering substances. Analytical Chemistry, 1994, 66, 2451–2457. D. Bindra, Y. Zhang, G. S. Wilson, R. Sternberg, D. Trevenot, G. Reach, and D. Moatti, Design and in vitro studies of a needle-type glucose sensor for subcutaneous monitoring. Analytical Chemistry, 1991, 63, 1692–1696.
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES 24. C. Henry, Getting under the skin: implanting glucose sensors. Analytical Chemistry, 1998, 70, 594A–598A. 25. D. Schmidtke, A. Freeland, A. Heller, and R. Bonnecaze, Measurement and modeling of the transient difference between blood and subcutaneous glucose concentrations in the rat after injection of insulin. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95, 294–299. 26. I. Helianti, Y. Morita, A. Yamaura, Y. Murakami, K. Yokoyama, and E. Tamiya, Characterization of native glutamate dehydrogenase from an aerobic hyperthermophilic archaeon Aeropyrum pernix K1. Applied Microbiology and Biotechnology, 2001, 56, 388–394. 27. Y. Morita, K. Kondoh, Q. Hasan, T. Sakaguchi, Y. Murakami, K. Yokoyama, and E. Tamiya, Purification and characterization of a cold-active protease from psychrotrophic Serratia marcescens AP3801. Journal of the American Oil Chemists Society, 1997, 74, 1377–1383. 28. K. Sode, T. Ootera, M. Shirahane, A. B. Witarto, S. Igarashi, and H. Yoshida, Increasing the thermal stability of the water soluble pyrroloquinoline quinine glucose dehydrogenase by single amino acid replacement. Enzyme and Microbial Technology, 2000, 26, 491–496. 29. G. H. E. Law, O. A. Gandelman, L. C. Tisi, C. R. Lowe, and J. A. H. Murray, Mutagenesis of solvent-exposed amino acids in Photinus pyralis luciferase improves thermostability and pH tolerance. Biochemical Journal, 2006, 397(2), 305–312. 30. A. Watanabe, K. Yano, K. Ikebukuro, and I. Karube, Cloning and expression of a gene encoding cyanidase from pseudomonas stutzeri AK61. Applied Microbiology and Biotechnology, 1998, 50, 93–97. 31. B. M. Paddle, Biosensors for chemical and biological agents of defence interest. Biosensors and Bioelectronics, 1996, 11, 1079–1113. 32. F. Scheller, F. Schubert, D. Pfeiffer, R. Hintsche, I. Dransfeld, R. Renneberg, U. Wollenberger, K. Reidel, M. Pavlova, M. Kuhn, H. G. M¨uller, P. M. Tan, W. Hoffmann, and W. Moritz, Research and development of biosensors. The Analyst, 1989, 114, 653–662. 33. G. A. Rechnitz and M. Y. Ho, Biosensors based on cell and tissue material. Journal of Biotechnology, 1990, 15, 201–218. 34. D. J. Monk and D. R. Walt, Optical fiber-based biosensors. Analytical and Bioanalytical Chemistry, 2004, 379, 931–945. 35. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Bioluminescents whole cell optical fiber sensor to genotoxicants: system optimization. Sensors and Actuators B-Chemical, 2001, B74, 18–26. 36. J. R. North, Immunosensors: antibody-based biosensors. Trends in Biotechnology, 1985, 3, 180–185. 37. H. Nakamura and I. Karube, Current research activity in biosensors. Analytical and Bioanalytical Chemistry, 2003, 377, 446–468. 38. P. B. Luppa, L. J. Sokoll, and D. W. Chan, Immunosensors–principles and applications to clinical chemistry. Clinica Chimica Acta, 2001, 314, 1–26. 39. B. Hock, Antibodies for immunosensors. A review. Analytica Chimica Acta, 1997, 347, 177–186.
13
40. C. L. Morgan, D. L. Newman, and C. P. Price, Immunosensors: technology and opportunities in laboratory medicine. Clinical Chemistry, 1996, 42, 193–209. 41. A. P. F. Turner, Biosensors: switching channels makes sense. Nature, 1997, 387, 555–557. 42. B. A. Cornell, V. L. B. Braach-Maksvytis, L. G. King, P. D. J. Osman, B. Raguse, L. Wieczorek, and R. J. Pace, A biosensor that uses ion-channel switches. Nature, 1997, 387, 580–583. 43. O. Braha, L. Q. Gu, L. Zhou, X. Lu, S. Cheley, and H. Bayley, Simultaneous stochastic sensing of divalent metal ions. Nature Biotechnology, 2000, 18, 1005–1007. 44. T. Takeuchi and J. Matsui, Molecular imprinting: an approach to tailor-made synthetic polymers with biomimetic functions. Acta Polymerica, 1996, 47, 471–484. 45. D. Kriz, O. Ramstr¨om, and K. Mosbach, Molecular imprinting-based biomimetic sensors could provide an alternative to often unstable biosensors for industry, medicine, and environmental analysis. Analytical Chemistry, 1997, 69, 345A–349A. 46. O. Ramstr¨om and R. J. Ansell, Molecular imprinting technology: challenges and prospects for the future. Chirality, 1998, 10, 195–209. 47. K. Haupt and K. Mosbach, Molecularly imprinted polymers and their use in biometric sensors. Chemical Reviews, 2000, 100, 2495–2504. 48. C. K. O’Sullivan, Aptasensors–the future of biosensing? Analytical and Bioanalytical Chemistry, 2002, 372, 44–48. 49. M. Famulok, Molecular recognition of amino acids by RNA aptamers: am L-citrulline binding RNA motif and its evolution into an L-arginine binder. Journal of the Chemical Society, 1994, 116, 1698–1706. 50. D. S. Wilson, A. D. Keefe, and J. S. Szostak, The use of mRNA display to select high-affinity proteinbinding peptides. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98, 3750–3755. 51. M. Lee and D. R. Walt, A fiber-optic microarray biosensor using aptamers as receptors. Analytical Biochemistry, 2000, 282, 142–146. 52. M. N. Stojanovic, P. De Prada, and D. W. Landry, Aptamer-based folding fluorescent sensor for cocaine. Journal of the American Chemical Society, 2001, 123, 4928–4931. 53. P. E. Nielsen, M. Egholm, R. H. Berg, and O. Buchardt, Sequence-selective recognition of DNA by strand displacement with a thymine-substituted polyamide. Science, 1991, 254, 1497–1500. 54. J. Wang, DNA biosensors based on peptide nucleic acid (PNA) recognition layers. a review. Biosensors and Bioelectronics, 1998, 13, 757–762. 55. D. M. Disley, P. R. Morrill, K. Sproule, and C. R. Lowe, An optical biosensor for monitoring recombinant proteins in process media. Biosensors and Bioelectronics, 1999, 14, 481–493. 56. B. C. Dave, B. Dunn, J. S. Valentine, and J. I. Zink, Sol-gel encapsulation methods for biosensors. Analytical Chemistry, 1994, 66, 1120–1127.
14
BIOSENSOR AND BIOCHIP TECHNOLOGIES
57. M. Gerard, A. Chaubey, and B. D. Malhotra, Application of conducting polymers to biosensors. Biosensors and Bioelectronics, 2002, 17, 345–359. 58. B. F. Y. Yon Hin, R. S. Sethi, and C. R. Lowe, Multi-analyte microelectronic biosensors. Sensors And Actuators, 1990, B1, 550–554. 59. S. E. Wolowacz, B. F. Y. Yon Hin, and C. R. Lowe, Covalent electropolymerisation of glucose oxidase in polypyrrole. Analytical Chemistry, 1992, 64, 1541–1545. 60. D. C. Cullen, R. S. Sethi, and C. R. Lowe, A multi-analyte miniature conductance biosensor. Analytica Chimica Acta, 1990, 231, 33–40. 61. S. Cosnier, R. S. Marks, J. P. Lellouche, K. Perie, D. Fologea, and S. Szunerits, Electrogenerated ploy (chiral dicarbozole) films for the reagentless grafting of enzymes. Electroanalysis, 2000, 12, 1107–1112. 62. H. Muguruma, K. Matsumura, and S. Hotta, Molecular orientation of oligothiopene-based polyamide thin films fabricated by vapour deposition polymerization. Thin Solid Films, 2002, 405, 77–80. 63. A. G. Mayes, Immobilisation Chemistry of Biological Recognition Molecules, in Biomolecular Sensors, E. Gizeli and C. R. Lowe (eds), Taylor & Francis, London, 2002, pp. 49–86. 64. J. W. Jacobs and S. P. A. Fodor, Combinatorial chemistry–applications of light-directed chemical synthesis. Trends in Biotechnology, 1994, 12, 19–26. 65. R. S. Kane, S. Takayama, E. Ostuni, D. E. Ingber, and G. M. Whitesides, Patterning proteins and cells using soft lithography. Biomaterials, 1999, 20, 2363–2376. 66. K. W. Sim, Bioelectrochemical detection of three alcohols based on a conducting organic salt electrode. Biosensors and Bioelectronics, 1991, 6, 317–323. 67. P. D’Orazio, Biosensors in clinical chemistry. Clinica Chimica Acta, 2003, 334, 41–69. 68. J. R. Sandifer and J. J. Voycheck, A review of biosensor and industrial applications of pH-ISFETs and an evaluation of Honeywell’s “DuraFET”. Microchimica Acta, 1999, 131, 91–98. 69. P. Skladal, Advances in electrochemical immunosensors. Electroanalysis, 1997, 9, 737–745. 70. P. Bergveld, A critical evaluation of direct electrical protein detection methods. Biosensors and Bioelectronics, 1991, 6, 55–72. 71. D. V. Brown and M. E. Meyerhoff, Potentiometric enzyme channelling immunosensor for proteins. Biosensors and Bioelectronics, 1991, 6, 615–622. 72. S. Dai and M. E. Meyerhoff, Non-separation binding immunoassays using polycation-sensitive membrane electrode detection. Electroanalysis, 2001, 13, 276–283. 73. J. Wang, Towards genoelectronics: electrochemical biosensing of DNA hybridization. Chemistry—A European Journal, 1999, 5, 1681–1685. 74. M. Liley, Optical Transducers, in Biomolecular Sensors, E. Gizeli and C. R. Lowe (eds), Taylor & Francis, London, 2002, pp. 123–175. 75. G. Gauglitz, Direct optical sensors: principles and selected applications. Analytical and Bioanalytical Chemistry, 2005, 381, 141–155. 76. A. Brecht and G. Gauglitz, Recent developments in optical transducers for chemical or biochemical applications. Sensors and Actuators B, 1997, 38 – 39, 1–7.
77. V. S.-Y. Lin, K. Motessharei, K.-P. S. Dancil, M. J. Sailor, and M. R. Ghadiri, A porous silicon-based optical interferometric biosensor. Science, 1997, 278, 840–843. 78. K. Lukosz and K. Tiefenthaler, Sensitivity of integrated optical grating and prism couplers as (bio)chemical sensors. Sensors and Actuators, 1988, 15, 273–284. 79. R. E. Kunz, G. Duveneck, and M. Ehrat, Sensing Pads For Hybrid And Monolithic Integrated Optical Immunosensing, In: Proceedings of the SPIE 2331 Medical Sensors II and Fibre Optic Sensors, 1994, 2–17. 80. E. E. Carlyon, C. R. Lowe, D. Reid, and I. Bennion, A single-mode fibre optic evanescent wave biosensor. Biosensors and Bioelectronics, 1992, 7, 141–146. 81. R. J. Davies, P. R. Edwards, H. J. Watts, C. R. Lowe, P. E. Buckle, D. Yeung, T. M. Kinning, and D. V. PollardKnight, The Resonant Mirror: A Versatile Tool For The Study of Biomolecular Interactions, in Techniques in Protein Chemistry V, J. W. Crabb (ed), Academic Press, San Diego, 1994, pp. 285–292. 82. H. J. Watts, C. R. Lowe, and D. V. Pollard-Knight, An optical sensor for monitoring whole microbial cells. Analytical Chemistry, 1994, 66, 2465–2470. 83. R. J. Davies and P. R. Edwards, The Resonant Mirror Biosensor, in Biomolecular Sensors, E. Gizeli and C. R. Lowe (eds), Taylor & Francis, London, 2002, pp. 267–290. 84. A. Brandenburg and R. Henninger, Integrated optical young interferometer. Applied Optics, 1994, 33, 5941–5947. 85. J. Spinke, N. Oranth, C. Fattinger, H. Koller, C. Mangold, and D. Voegelin, The bidiffractive grating coupler: application to immunosensing. Sensors and Actuators B, 1997, 38 – 39, 256–260. 86. M. Weisser, G. Tovar, S. Mittler-Neyer, W. Knoll, F. Brosinger, H. Freimuth, M. Lacher, and W. Ehrfeld, Specific biorecognition reactions observed with an integrated mach-zehnder interferometer. Biosensors and Bioelectronics, 1999, 14, 405–411. 87. C. Stamm and W. Lukosz, Integrated optical difference interferometer as immunosensor. Sensors and Actuators B, 1996, 31, 203–207. 88. D. J. Monk and D. R. Walt, Optical fibre-based biosensors. Analytical and Bioanalytical Chemistry, 2004, 379, 931–945. 89. R. Slavik, J. Homola, J. Ctyroky, and E. Brynda, Novel spectral fibre optic sensor based on surface plasmon resonance. Sensors and Actuators B-Chemical, 2001, 74, 106–111. 90. R. Slavik, J. Homola, and E. Brynda, A miniature fibre optic surface plasmon resonance sensor for fast setection of Staphylococcal enterotoxin B. Biosensors and Bioelectronics, 2002, 17, 591–595. 91. A. J. C. Tubb, F. P. Payne, R. B. Millington, and C. R. Lowe, Single-mode optical fibre surface plasma wave chemical sensor. Electronics Letters, 1995, 31, 1770–1771. 92. A. J. C. Tubb, F. P. Payne, R. B. Millington, and C. R. Lowe, Single-mode optical fibre surface plasma wave chemical sensor. Sensors and Actuators B-Chemical, 1997, 41, 71–79.
OVERVIEW OF BIOSENSOR AND BIOARRAY TECHNOLOGIES 93. S.-F. Cheng and L.-K. Chau, Colloidal gold-modified optical fibre for chemical and biochemical sensing. Analytical Chemistry, 2003, 75, 16–21. 94. S. Watanabe, K. Usui, K.-Y. Tomizaki, K. Kajikawa, and H. Mihara, Anomalous reflection of gold applicable for a practical protein-detecting chip platform. Molecular BioSystem, 2005, 1, 363–365. 95. T. Vo-Dinh and P. Kasili, Fibre-optic nanosensors for single cell monitoring. Analytical and Bioanalytical Chemistry, 2005, 382, 918–925. 96. W. H. Tan, Z. Y. Shi, and R. Kopelman, Development of sub-micron chemical fibre optic sensors. Analytical Chemistry, 1992, 64, 2985–2990. 97. E. Gizeli, Acoustic Transducers, in Biomolecular Sensors, E. Gizeli and C. R. Lowe (eds), Taylor & Francis, London, 2002, pp. 176–206. 98. G. Sauerbrey, Use of a quartz vibrator for weighing thin layers on a microbalance. Zeitschrift fur Physik, 1959, 155, 206–222. 99. K. K. Kanazawa and J. G. Gordon, The oscillation frequency of a quartz resonator in contact with a liquid. Analytica Chimica Acta, 1985, 157, 99–105. 100. E. Gizeli, A. C. Stevenson, N. J. Goddard, and C. R. Lowe, A love plate biosensor utilising a polymer overlayer. Sensors and Actuators B, 1992, 6, 131–137. 101. M. Viens, P. Li, Z. Wang, C. K. Jen, M. Thompson, and J. D. N. Cheeke, Mass sensitivity of thin rod acousticwave sensors. IEEE Transactions On Ultrasonics Ferroelectrics And Frequency Control, 1996, 43, 852–857. 102. P. C. H. Li and M. Thompson, Mass sensitivity of the tube acoustic wave sensor in the extensional mode. Analytica Chimica Acta, 1996, 336, 13–21. 103. K. Yamanaka, S., Ishikawa, N. Nakaso, T. Takeda, T. Mihara, and Y. Tsukahara, Ball SAW Devices For Hydrogen Gas Sensor, In: IEEE Ultrason Symposium Proceedings, 2003, 299–302. 104. C. L. Huang, K. W. Tay, and L. Wu, Fabrication and performance analysis of film bulk acoustic wave resonators. Materials Letters, 2005, 59, 1012–1016. 105. A. C. Stevenson and C. R. Lowe, Non-contact excitation of high Q acoustic resonances in glass plates. Applied Physics Letters, 1998, 73, 447–449. 106. A. C. Stevenson and C. R. Lowe, Magnetic acoustic resonator sensors (MARS): a new sensing technology. Sensors And Actuators A, 1999, 72, 32–37. 107. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Metha, and C. R. Lowe, Planar coil excitation of multi-frequency shear wave transducers. Biosensors and Bioelectronics, 2005, 20, 1298–1304. 108. R. Lucklum and P. Hauptmann, Acoustic microsensors—the challenge behind microgravity. Analytical and Bioanalytical Chemistry, 2006, 384, 667–682. 109. C. Vancura, Y. Li, K. U. Kirstein, F. Josse, A. Hierlemann, and J. Lichtenberg, Fully Integrated CMOS Resonant Cantilever Sensor For Biochemical Detection In Liquid Environments, In: Proceedings of the 13th International Conference of Solid State Actuators Microsystem (Transducers 2005), 2005, 640–643. 110. J. H. Seo and O. Brand, Novel High Q-Factor Resonant Microsensor Platform For Chemical And Biological Applications, In: Proceedings of the 13th
111.
112.
113.
114.
115.
116.
117.
118.
119.
120.
121.
122.
123.
124.
15
International Conference of Solid State Actuators Microsystem (Transducers 2005), 2005, 247–251. T. B. Burg and S. R. Manalis, Suspended microchannel resonators for biomolecule detection. Applied Physics Letters, 2003, 83, 2698–2700. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Mehta, and C. R. Lowe, The acoustic spectrophonometer: a novel bioanalytical technique based on multifrequency acoustic devices. Analyst, 2003, 128, 1222–1227. M. Thompson, S. M. Ballantyne, A. C. Stevenson, and C. R. Lowe, Electromagnetic excitation of high frequency acoustic waves and detection in the liquid phase. Analyst, 2003, 128, 1048–1055. J. E. Ladbury and B. Z. Chowdhry, Sensing the heat: the application of isothermal titration calorimetry to thermodynamic studies of biomolecular interactions. Chemico-Biological, 1996, 3, 791–801. A. Cooper, Thermodynamic analysis of biomolecular interactions. Current Opinion in Chemical Biology, 1999, 3, 557–563. I. Jelesarov and H. R. Bosshard, Isothermal titration calorimetry and differential scanning calorimetry as complementary tools to investigate the energetics of biomolecular recognition. Journal of Molecular Recognition, 1999, 12, 3–18. U. Harborn, B. Xie, and B. Danielsson, Determination of glucose in diluted blood with a thermal flow injection analysis biosensor. Analytical Letters, 1994, 27, 2639–2645. B. Xie, B. Danielsson, P. Norberg, F. Winquist, and I. Lundstr¨om, Development of a thermal microbiosensor fabricated on a silicon chip. Sensors and Actuators B, 1992, 6, 127–130. J. H. Hoh, P. E. Hillner, and P. K. Hansma, Measuring the streptavidin-biotin binding force. Proceedings of the Micrological Society of America, 1994, 52, 1054–1055. D. R. Baselt, G. U. Lee, M. Natesan, S. W. Metzger, P. E. Sheehan, and R. J. Colton, A biosensor based on magnetoresistance technology. Biosensors and Bioelectronics, 1998, 13, 731–739. J. C. Rife, M. M. Miller, P. E. Sheehan, C. R. Tamanaha, M. Tondra, and L. J. Whitman, Design and performance of GMR sensors for the detection of magnetic microbeads in biosensors. Sensors and Actuators A, 2003, 107, 209–218. R. L. Edelstein, C. R. Tamanaha, P. E. Sheehan, M. M. Miller, D. R. Baselt, L. J. Whitman, and R. J. Colton, The BARC biosensor applied to the detection of biological warfare agents. Biosensors and Bioelectronics, 2000, 14, 805–813. Y. R. Chemla, H. L. Grossman, Y. Poon, R. McDermott, R. Stevens, M. D. Alper, and J. Clarke, Ultrasensitive magnetic biosensor for homogeneous immunoassay. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97, 14268–14272. P. C. Hammel, D. V. Pelekhov, P. E. Wigen, T. R. Gosnell, M. M. Midzor, and M. L. Roukes, The magnetic resonance force microscope: a new tool for high resolution 3D subsurface scanned probe imaging. Proceedings of the IEEE, 2003, 91, 789–798.
16
BIOSENSOR AND BIOCHIP TECHNOLOGIES
125. M. G. Weller, Classification of protein microarrays and related techniques. Analytical and Bioanalytical Chemistry, 2003, 375, 15–17. 126. R. Ekins, F. Chu, and E. Biggart, Development of microspot multi-analyte ratiometric immunoassay using dual fluorescent-labelled antibodies. Analytica Chimica Acta, 1989, 227, 73–96. 127. C. R. Lowe and F. G. P. Early, Diagnostic Device Incorporating A Biochemical Ligand , 1984, EP 127438. 128. S. P. A. Fodor, J. L. Read, M. C. Pirrung, L. Stryer, A. T. Lu, and D. Solas, Light directed spatially addressable parallel chemical synthesis. Science, 1991, 251, 767–773. 129. M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270, 467–470. 130. J. A. Ferguson, T. C. Boles, C. P. Adams, and D. R. Walt, A fiber-optic DNA biosensor microarray for the analysis of gene expression. Nature Biotechnology, 1996, 14, 1681–1684.
131. M. C. Pirrung, How to make a DNA chip. Angewandte Chemie International Edition, 2002, 41, 1276–1289. 132. P. O. Brown and D. Botstein, Exploring the new world of the genome with DNA microarrays, Nature Genetics 1999 21, (Suppl. 1), 33–37. 133. D. J. Lockhart and F. A. Winzeler, Genomics, gene expression and DNA arrays. Nature, 2000, 405, 827–836. 134. D. R. Walt, Bead-based fiber-optic arrays. Science, 2000, 287, 451–452. 135. H. Miyachi, H. Hiratsuka, K. Ikebukuro, K. Yano, H. Muguruma, and I. Karube, Application of polymerembedded proteins to fabrication of DNA array. Biotechnology and Bioengineering, 2000, 69, 323–329. 136. I. Karube and Y. Nomura, Enzyme sensors for environmental analysis. Journal of Molecular Catalysis, 2000, 10, 177–181. 137. S. Dong and B. Wang, Electrochemical biosensing in extreme environment. Electroanalysis, 2002, 14, 7–16.
2 Overview of Modern Analytical Needs Frank Davis, Stuart D. Collyer and S´eamus P. J. Higson Institute of Bioscience and Analytical Technology, Cranfield University, Silsoe, UK
1 NEEDS OF THE ANALYTICAL COMMUNITY 1.1
Introduction
The detection of a wide variety of compounds is necessary in today’s world. Many common chemicals and biological materials pose dangers to human health and well-being as well as to livestock, plants, and the environment in general. The accidental or deliberate release of these species can have devastating effects, as was seen after, for example, the release of methyl isocyanate at Bhopal, or the contamination of water supplies with arsenic in many parts of Bangladesh. While compounds such as these are often easily detected, there are many species that pose longer-term and sometimes hidden dangers when released into the environment at low concentrations, some examples of which are given in the subsequent text. Besides environmental problems such as these, we also have to consider the possibility of terrorist attacks in which chemical and/or biological toxins are deliberately released, as seen, for example, following the release of sarin in the Tokyo underground in 1995. Industrial or agricultural use of chemicals can also lead to potential contamination, and this can of course give rise to widespread health concerns if it enters the water supply or food chain. Analysis of medical samples such as blood or serum is also of great importance for health care applications. The use of glucose biosensors,
for example, to monitor blood glucose levels has provided a reliable and convenient method for diabetics to easily monitor their own blood glucose levels at any time. The detection of low levels of many other compounds within living systems is also crucial, for instance, to allow us to diagnose and follow cases of accidental poisoning. In many diseases such as AIDS, infections can be determined by identifying the presence of the antibodies within clinical samples such as blood. Agricultural or industrial practices can lead to the contamination of food and water supplies, while the deterioration of food with time can lead to bacteriological contamination. Analysis of both food and water can, in both these cases, provide early warning of any problems and possibly help prevent exposure of people or animals to these toxins. The nature of the sample to be analyzed will inevitably influence the choice of analytical technique to be used. Two of the most common forms of samples include biological fluids viz., blood, plasma, urine, saliva, plant sap, and so on, or environmental samples such as water, soil, and air. The nature of the sample also dictates which, if any, preparation techniques need to be used. We may, for example, wish to analyze metal concentrations in soil; however, many techniques cannot tolerate particulates and/or suspensions and can only be applied to true solutions. In cases such as these, the analyte must be extracted from the soil sample by some washing and the dissolution approach. In
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR AND BIOCHIP TECHNOLOGIES
some cases, the analyte must also be concentrated. For biological samples such as blood, many components such as erythrocytes (red blood cells) and leukocytes (white blood cells) need to be removed before analysis can proceed. The nature of the sample also affects the level of detection that is needed. Very low levels of pesticides in the environment, for example, may not be considered a hazard or breach of legislation. However, with time these types of materials can be concentrated by living systems, especially when entering a food chain in which low levels in the environment rapidly become concentrated and, hence, injurious to higher animals. In such cases, the detection levels required for many analytes in environmental samples can be orders of magnitude lower than those required for determination within biological samples. Medical samples again provide different problems in the context that biological fluids are often very complex mixtures and therefore techniques with high specificity are required. Utilizing biological molecules themselves within sensors is a solution to this, since many of these moieties react to the presence of just one analyte. In many cases, there is interest in limited ranges of detection, as can be seen when we consider, for example, glucose levels within blood which can only vary between 0 and 35–40 mM since death occurs beyond these limits. Complementary methods are often used to analyze samples within different settings or for differing requirements. Spectroscopic techniques tend to be laboratory based and can often give quite a detailed breakdown of the constituents of a sample. The disadvantages of such approaches are associated with the cost and time delay of transporting large numbers of samples to the laboratory as well as the provision of skilled personnel to operate and maintain equipment. This has led to an explosion in the provision of sensor-based approaches. Sensors are often portable and offer simplicity for the operator, although many sensors can detect only a single analyte. A possible solution to this is the use of chips containing multiple sensors (some of which are described later), in which each sensor detects a different analyte. Often, both methods are used in conjunction with each other; a few soil samples, for example, may first be obtained from a landfill site and the major contaminants determined spectroscopically. Once the major contaminants
have been determined, their distribution across the site could then be mapped using specific sensors that permit greater numbers of samples to be analyzed in a given time.
1.2
Neurotoxins
Nerve gases (although most reagents labeled as such are actually liquids at room temperature) represent a group of highly toxic chemical warfare agents. Usually based on organophosphorus compounds, they work by inhibition of acetylcholine esterase enzymes within humans or animals. They can be adsorbed through the skin or the respiratory system, and symptoms include breathing problems and convulsions, which can ultimately lead to collapse of the respiratory systems and death. Although initially developed during World War II, they were not deployed, but were later used during the Iran–Iraq war1 and against the Kurdish town of Halabja. Exposure can be treated by the use of anticholinergic drugs.1 Early detection of these compounds upon environmental release is vital since they can be lethal at low concentrations, with exposure to sarin levels of 70 mg m−3 , for example, being capable of causing death in 1 min.2
1.3
Pesticides
While pesticides are used extensively within modern agricultural techniques to control insect infestation, indiscriminate use can lead to long-term effects on the environment, livestock, and human health. A significant proportion of the pesticides used within agriculture are washed off or are otherwise lost from the large areas of agricultural land treated surfaces and for this reason, an excess of active ingredient is commonly applied. Another factor to consider is that many pesticides, especially organochlorine materials such as dichlorodiphenyl-trichloroethane (DDT), have very long lifetimes under environmental conditions. This means that they can become incorporated within the food chain, leading to higher concentrations within higher species.3 Organophosphate pesticides are now commonly used instead of the organochlorine pesticides because of their lower
OVERVIEW OF MODERN ANALYTICAL NEEDS
persistence in the environment while still remaining effective. They are, however, neurotoxins and therefore present a serious risk to human health. These compounds may still find their way into our food and water supplies, which necessitates the use of analytical approaches for the reliable detection of pesticides for environmental protection and food safety purposes. Legislation has now been passed to help restrict pesticides within water supplies (e.g., the European Commission: EU Water Framework Directive 2000/60/EC, European Commission: Drinking Water Directive 98/83/EC).
1.4
Drug Detection
The detection of low levels of drugs in the environment and within medical samples is of great importance. Many pharmaceuticals commonly used for human and veterinary medication are now beginning to be found and detected within the environment since they are excreted by the user, often in an unmodified or slightly modified form, and thence into rivers and seas.4 The levels of these compounds are usually extremely low, requiring sensitive detection but which cannot be ignored because of their high biochemical activity.4 Since many farm animals are given pharmaceutical supplements, there are also worries relating to how much of the pharmaceutical (or its degradation products) is retained in products such as meat or milk. Another concern is centered around the routine administration of antibiotics to animals and whether this will promote the formation of strains of antibiotic-resistant bacteria.5 The detection of drugs of abuse is a topic that is receiving widespread interest. The detection of the drug in bulk while being transported (e.g., at airports to prevent trafficking) is often carried out using trained “sniffer” dogs. Dogs, however, can have difficulty in detecting drugs in the presence of other strong odors such as coffee, a fact that smugglers are aware of. Such dogs also require skilled training. Even when a dog successfully locates a suspect substance, it must still be sent to a laboratory for analysis. The development of electronic noses, which can selectively and rapidly detect a series of target compounds, is being widely investigated. The detection of drugs in biological samples such as within
3
forensic examinations is more complex, usually requiring solid-phase extraction followed by chromatographic techniques.
1.5
Microbial Contamination
Microbial infections can cause major problems for human health, the production of food, and disruption to the environment in general. For example, in recent years, there has been much publicity surrounding antibiotic-resistant methicillin resistant staphylococcus aureus (MRSA) infection within hospitals, which in many cases has proven fatal. Contamination of water by Legionella or contamination of food by bacteria such as Salmonella can have equally grave consequences. The potential of using microorganisms such as Anthrax as a biological weapon, especially by terrorist organizations, has also posed a major security issue. Besides human infection, other diseases can have devastating effects, as seen, for example, during the 1967 and 2001 outbreaks of foot-and-mouth disease within the United Kingdom. The detection of microbial contamination of drinking water has traditionally been based on the detection of indicators of fecal pollution. Coliform bacteria are the most common microorganisms found in water supplies and the populations present have been taken as a key indicator of water quality.6 Simple inexpensive tests exist that provide assessments of the levels of water quality by detection of coliform bacteria.6 In many examples, water samples are passed through membrane filters, added to a nutrient broth culture plate and incubated at 35 ◦ C for 24 h. The plate is then removed and the number of bacterial colonies counted. However, these tests are not capable of identifying the presence of specific pathogens. Usually there are too many pathogens to determine individually and the monitoring methods for individual pathogens are often much more cumbersome or expensive. Moreover, some pathogens may reside in water at very low concentrations, and it follows that a simple test for specific pathogens would be of great benefit to the water industry. Another problem faced by the water industry is that of chlorination, a common and necessary method for disinfecting water supplies, and it should not be forgotten that the release of
4
BIOSENSOR AND BIOCHIP TECHNOLOGIES
chlorinated compounds into the environment can represent a problem in its own right. Current methods for measuring chlorine are usually based on either colorimetric or cumbersome electrochemical approaches and, in this case, a simple handheld electrochemical monitoring device for chlorine concentrations in water would have a large potential market.
1.6
Carcinogens
The presence of possible carcinogens within our environment represents another potential threat to human health. One of the major dangers of such compounds is that quite often there are no immediate observable effects on health and therefore large numbers of people may suffer longterm consequences before it is realized that there is an issue that needs to be addressed. Carcinogens can be released by industrial processes and can be transported within the environment by air or alternatively be waterborne. Typical carcinogens include organic solvents such as benzene (found in unleaded petrol) together with its derivatives, some monomers used in the polymer industry (such as vinyl chloride and acrylonitrile), and many previously used food dyes that have now been banned from use in many parts of the world due to their carcinogenicity, for example, Sudan Red. There exists many classical methods for the analysis of food, water, and medical samples; however, many of these are based on laboratory techniques such as high performance liquid chromatography (HPLC), mass spectroscopy (MS), atomic adsorption spectroscopy, and/or bacteriological techniques such as growing of cell cultures. Although these techniques work very well in the laboratory, they often require expensive laboratory-based equipment, which can be bulky and also be sensitive to being moved—thus limiting their application within field situations. What is often required is a relatively inexpensive, robust, and above all portable sensing technology, which can be operated preferably by relatively unskilled personnel. The utilization of sensor chips specific to certain compounds would greatly improve the rapid detection and quantification of many species of interest, and some of the approaches taken over recent years are detailed in the subsequent text.
2 ELECTROCHEMICAL METHODS
The continual advancement in electrochemical methodologies and techniques can be related to the need for more sensitive, selective, and rapid analysis of species of interest. This is particularly true for many biological and environmental analyses where field-based, point-of-care, or in situ monitoring is becoming more widely used due to advances in microfabrication technology. This in turn facilitates analyses to be undertaken on site and negates the need for samples to be returned to a central laboratory. Advancements in understanding of areas such as the Human Genome Project, coupled with the amount of data this provides, has led to investigations into delivering sensors for DNA, based upon the specific interactions between single-stranded DNA immobilized upon the sensing surface and its complementary sequence. Methods of immobilization such as adsorption, affinity binding, and film entrapment have been utilized and the reader is referred to separate reviews of the various methods.7,8 Signal detection can either be undertaken directly9 or more commonly exploits a hybridization event to increase selectivity.10 Recently, DNA chips have been reported, where problems previously associated with reproducible immobilization and effective detection methods are being overcome with, for example, the use of scanning electrochemical microscopy (SECM) as a reliable method for the “writing” of pyrroleoligonucleotide patterns on thin gold films.11 This procedure has led to the generation of DNA chips, and SECM has been used in conjunction with surface plasmon resonance (SPR) imaging for the monitoring and detection of hybridization techniques.12 DNA detection is also being combined with nanomaterial analyses: here DNA is being both detected with, and used as, nanoparticulate material. A review of the uses of DNA as a nanomaterial has been provided by Ito and Fukusaki,13 and two excellent reviews by Wang14,15 detail the detection of DNA using nanomaterials. Recently, a new method for the fabrication of a regent-free immunoassay has been reported.16 Here, bovine serum albumin (BSA) was detected using anti-BSA up to concentrations of 75 ppm without the need of a secondary label (such as an enzyme or radioisotope). Despite this new
OVERVIEW OF MODERN ANALYTICAL NEEDS
advance, the best limits of detection found within enzyme immunoassays are still obtained when heterogeneous assays (involving a “separation step”) are undertaken. Work is still being undertaken on reducing the many nonspecific adsorptions that occur at the electrode surface (thus lowering sensitivity), and also to regenerate the sensor to allow multiple determinations. However, owing to the number of publications over recent years, the immunosensor is one of the most promising techniques existing within the field of electrochemical enzyme immunoassays. Coupled to advances in the miniaturization of instrumentation, it is possible that this technique could soon produce portable electrochemical analyzers, which will undergo enzyme immunoassay protocols, with both simplicity and sensitivity, at cost-effective levels, for both single and multiple analyses. Aptamers could also be used electrochemical systems owing to their ability to mimic the properties of, for example, antibodies, but are only a fraction of the size in terms of molecular weight and are highly specific toward target analytes. Aptamers also offer advantages in terms of easier regeneration when compared to antibodies and have therefore already found use within biosensor-based systems.17 Therefore they offer a highly exploitable alternative in the fabrication of immunosensors. A review of aptamers, detailing their possible application within analytical systems, has recently been published.17 Biosensor research is now being aimed at realtime “in vivo” monitoring, where sensors capable of continuous measurement of analytes of significant importance are measured within biological media such as single cells and tissue slices, as well as within animals and humans themselves. Commercial systems have already been approved for glucose monitoring.18 Research is also being directed into using electrochemical techniques for subcellular analysis of biologically significant compounds. For example, an amperometric detection of neurotransmitter release from single vesicles of cells via a carbon fiber microelectrode has recently been reported.19 Most samples for electrochemical analysis are in the form of an aqueous-based system, with examples ranging from river water through to biological fluids. In a few instances, organic solvent extracts can also be used. In many cases, an additional electrolyte, for example, NaCl may have to be added
5
to the sample and, for samples in which pH is critical, buffer salts such as phosphates may also need to be introduced. The choice of the electrochemical technique may be determined by the nature of the sample since some electrochemical methods display differing sensitivities. The presence of interfering compounds can also cause additional problems. Should the experiment be run within a cathodic potential window (relative to the formal potential for the redox couple in question), interference can be encountered from species capable of being electrochemically reduced, while within the anodic region, oxidizable species can in a similar manner lead to erroneous readings. Glucose biosensors, for example, often rely on the oxidation of either hydrogen peroxide or a ferrocenebased mediator at an electrode surface. If blood is being analyzed, problems associated with species such as ascorbate or uric acid can be encountered, both of which are capable of being oxidized at the electrode. Care has to be taken to exclude these species, with one of the most common methods being based upon the introduction of a permselective membrane.
3 OPTICAL METHODS
As an alternative to electrochemical approaches, optical methods can be used for a wide variety of tests. Optical techniques can be as simple as visually determining pH by the color change of indicator paper through to utilizing complex spectroscopic equipment. Optical sensors display several advantages over electronic devices. They are much less sensitive to electronic interference since the information is carried as photons rather than as electrons. Usually the optical components are made of glass chips or fiber-optic cable fibers, which minimizes the weight and the size of the sensors, since recent advances originating from the telecommunications industry enable the manufacturing of small sensors. Finally, glass sensors usually display a high chemical stability, that is, they are not corroded easily and are usually unaffected by organic solvents besides displaying good thermal and mechanical stability.20 A schematic of a fiber-optic sensor is shown in Figure 1. Firstly, there must be a component that displays chemical sensitivity. The first of
6
BIOSENSOR AND BIOCHIP TECHNOLOGIES
Light source (LED, laser)
Detector, e.g., photodiode Optical chip or fibre
Figure 1. Schematic of a fiber-optic-based sensor.
these main components of the sensor is an optical chip or fiber (known as the optrode). This will often contain a chemical indicator, which has optical properties that depend on the presence or absence of an analyte. The indicator is chosen to have, for example, a strong optical adsorption or be fluorescent with its adsorption or fluorescence being modulated by interaction with the analyte. The use of indicators is often necessary because the analyte may not give or exhibit changes with readily determined optical properties. This can be thought of as a transduction event, that is, the presence of the analyte affecting a property within the sensor that can be followed. Finally, there has to be a method of following the transduction event. A light source is used, often with its wavelength specifically matched to the adsorption maximum of the indicator, so as to maximize the sensitivity. Light from the source is passed through the chip and the output, which could be affected by adsorption or fluorescence events that can be measured with a suitable detector. Photodiodes are popular in this respect since they convert the optical information into an electrical signal, thereby allowing the information to be easily processed. Fluorescence is often measured instead of absorbance (assuming either the analyte is fluorescent or a suitable indicator can be found), due to the inherent higher sensitivity of the technique. Fluorescent species utilized include many dyes and, more recently, nanoparticles of materials such as gold, partly because of their resistance to photobleaching. Again the samples utilized are normally liquid in form, usually as an extract in either water or an organic solvent. Choice of the solvent is important since it must not only dissolve the analytes in question but must also not display any interfering absorbances or fluorescence characteristics. Another factor that must also be taken into account is that the particulate material in the sample will lead to light scattering and so must be eliminated by filtration. Finally, the concentration of the analyte can also be important. Various compounds
of interest have variable adsorption coefficients or fluorescence emission levels. Care must be taken that the level of analyte in the sample is neither too low (or it will be undetectable) nor too high, which can lead to either saturation of the detector or non-obedience of the Beer–Lambert law. These problems, however, can often be solved by simple dilution or concentration of the sample. Initially, adsorption or fluorescent measurements required the use of a spectrometer, the size and other requirements of which often meant that measurements could only be made in a laboratory environment. However, much recent work has gone into the manufacturing of portable, preferably handheld equipment capable of utilizing these techniques. A recent review elsewhere, describes how the small size of optical fibers enables them to be utilized to form optical arrays.21 Bundles comprised of thousands of fused optical fibers can be easily assembled into arrays. The versatility of optical fibers and their ability to be easily integrated with a multitude of different sensing schemes enables them to be utilized for the preparation of a multitude of sensors including artificial noses21 and high-density oligonucleotide arrays.21 The fiber-optic bundles possess diameters of 3–10 µm, which allows high-density packing (2 × 107 sensors/cm2 ). Selective etching of individual fiber cores is possible, enabling the formation of a high-density microwell array, which can serve as a platform for an array of microsensors. Transmission from individual bundles can be monitored, allowing the responses monitored by the sensor to be correlated with sensing events occurring at individual locations on a chip. The fast response and versatility of this method enables the monitoring of single analytes through to more complex mixtures. A number of sensing schemes and applications are described in this review.21 The reliable detection of explosive compounds is a field in which many advances have been made recently. The factors driving this research include defense against terrorism together with
OVERVIEW OF MODERN ANALYTICAL NEEDS
problems in many parts of the world such as the widespread deployment of land mines and other unexploded ordnances. Aromatic nitro compounds such as trinitrotoluene (TNT) (Figure 2) are the active part of many of these devices and therefore attempts have been made to develop sensors capable of detecting low levels of this and similar compounds. Electron-deficient aromatic compounds such as TNT are known to form strong π –π bonds to other aromatic species. For this reason, fluorescent polymers such as polyarylethynylenes (Figure 2) have been utilized in attempts to detect TNT.22 The polymers are highly fluorescent in the solid state; however, when exposed to small quantities of TNT vapor, this fluorescence is dramatically quenched because of electron donation from the polymer to the analyte. What makes this technique especially sensitive is the combination of high affinity between the polymer and analyte and also the fact that it is not just a single polymer repeat unit that is quenched, but rather the whole polymer chain. The conjugated structure of the polymer makes it act like a molecular wire, so when one unit is quenched, the conjugation is broken and the entire chain ceases to fluoresce, thereby amplifying the effect of each TNT molecule.22 This has led to the development of an instrument known as FIDO, in which the active component is a glass capillary coated with a suitable polymer.22 The polymer is activated by light and fluoresces while air is passed through the capillary. The presence of nitroaromatics quenches the fluorescence, NO2 O2N
CH3 NO2
(a) OR
OR
OR
OR
n
(b) Figure 2. (a) Structure of TNT, (b) general structure of polyarylethynylenes.
7
which is monitored by a photodetector. FIDO (www.nomadics.com) weighs about 1 kg and can detect a range of nitroaromatics, with sensitivities claimed to be as low as 0.1 ppt. Besides detection of explosives, a range of other chemical and biological analytes are being studied.22 A wide variety of polymers have been studied, including polymers with extremely bulky side groups that hinder chain packing and create cavities within the polymer network, allowing rapid diffusion through the sensing material. Other polymeric materials have been developed, which, under the correct conditions, undergo stimulated emission—that is, laser emission—and the efficiency of this process is also disrupted by TNT and enables an increase in sensitivity and lowering of the detection limit by a factor of 30.
4 SURFACE PLASMON RESONANCE
The field of optical biosensors is dominated by the method of SPR. Commercial SPR systems are widely available, with Biacore AB being the major systems provider at the time of writing.23 SPR is a method that combines optical and electrochemical phenomena at a metal surface and is a powerful technique to measure biomolecular interactions in real time in a label-free environment. A schematic of a basic SPR setup is shown in Figure 3. In this approach, a laser beam is focused onto the back of a metal film (usually gold of thickness about 40 nm, but other metals such as silver have been used).23,24 The film is deposited onto a glass prism, or alternatively at the surface of a microscope slide clamped to a prism with an index-matching fluid placed between them. At a critical angle of incidence, energy is adsorbed and used to create surface plasmons, which can propagate along the metal surface. This means that the reflected light intensity at this angle can drop dramatically, often to almost zero (Figure 4). However, the plasmons are not strictly located at the surface but rather the intensity of its electromagnetic field exponentially decays from the metal surface into the adjacent medium. What renders this system of interest to the analyst is that the position and the width of this adsorption are somewhat dependent on the evanescent wave and therefore are sensitive to the environment up
8
BIOSENSOR AND BIOCHIP TECHNOLOGIES Incident light
Reflected light
Prism Slide
Metal film
Sensing film
Figure 3. Schematic of a typical SPR apparatus.
Before binding
on the binding of species to the surface of the optical chip, it follows that a major drawback of the technique will be interference by species other than the analyte adsorbing to the surface. This is especially significant when attempts are being made to analyze biological fluids such as blood from which protein may deposit upon almost any type of surface. To minimize this problem, it is usual to attempt to clean up the sample by methods such as centrifugation or filtration to remove as many interferents as possible. Several methods also exist for coating SPR chips with a variety of materials in an attempt to minimize nonselective deposition.
After binding
5 QUARTZ CRYSTAL MICROBALANCE Intensity reflected light
Angle of reflection Figure 4. Shifts in the reflected light intensity curve with binding of analyte.
to a distance of about a wavelength from the actual metal surface.24 Changes in the refractive index of this region, say by adsorption onto the metal surface or binding of analyte molecules to recognition elements previously immobilized on the metal surface, result in a change in the resultant SPR curve (Figure 4). The wide range of commercial instruments has made SPR a popular technique for studying intramolecular interactions. Several application areas are emerging and detailed reviews beyond the scope of this chapter have been published elsewhere.23,24 The emerging applications include food analysis, for example: the direct detection of Salmonella observed using antibody-modified SPR sensors, a variety of drug detection applications, the development of immunosensors, and the study of protein interactions.23 Samples for SPR are usually in the form of a solution or dispersion. Since SPR is dependent
The quartz crystal microbalance (QCM) is a highly sensitive method for studying changes in the mass of thin films. Many important physical and chemical processes can be followed by observing the mass changes. A QCM consists of a thin disk cut from a single crystal of quartz onto which electrodes have been plated, normally by evaporation of metals such as gold or platinum (Figure 5). Quartz itself is a piezoelectric material, that is, when an oscillating electric field is applied across the plate, a resultant acoustic wave is induced throughout the crystal in a direction perpendicular to the crystal surface. The frequency of this oscillation is dependent on the mass of the crystal,
Quartz disk Au or Pt
Electrical contacts
Figure 5. Schematic of a QCM crystal.
OVERVIEW OF MODERN ANALYTICAL NEEDS
including any thin surface layers deposited on it.25 Although the QCM itself is a very sensitive detector for mass changes, it has no inherent specificity. However, deposition of a thin sensing layer onto the QCM is possible and therefore the resultant device should combine the sensitivity of the QCM to mass changes with the specificity conferred by the coating. A typical application of the QCM is for use as a component within an immunosensor.25 A wide variety of antibodies have been immobilized onto QCM surfaces and many applications of this technology have been reviewed, along with the various methods used to immobilize the antibodies onto the QCM plate.25 The species that have been detected include drugs such as cocaine, quinine, and atropine.25 Other uses include detection of the HIV virus by immobilization of its antibodies and detection of specific single strands of DNA by immobilization of their complementary counterstrands and selective hybridization. QCM has also found application in detecting microorganisms, as reviewed elsewhere.26 Early work simply involved passing water streams over clean QCM crystals and using the resonant frequency to monitor the build up of biofilms. This process is typically unselective since it responds to any microbes that colonize the surface. Selectivity can be introduced by, once again, immobilizing antibodies on the surface. This has led to specific sensors for the presence of Candida albicans with response times of just 30 min. In other studies, further workers have reported sensors for Salmonella and Escherichia coli.26 Similar methods have also been applied to detection of viruses such as foot-and-mouth and plant viruses (in this case, infection could be detected in crude plant sap).26 Other workers have allowed biofilms to grow on QCM crystals and then exposed these to solutions of various antibodies, which selectively bind to immobilized antigen cells, thereby allowing identification of microorganisms that are present in the biofilm.26 Samples for QCM analysis can be either liquid or gaseous in form. Liquid samples are usually more difficult to analyze since, like SPR, interference can be encountered from species other than the analyte adsorbing to the surface. Again, techniques are used to either clean up the sample or to protect QCM chips with a variety of coatings in an attempt to minimize nonselective deposition
9
of contaminants. Physical parameters such as the viscosity of the liquid can also affect the QCM response, and so care must be taken to ensure that changes to the properties of the liquid (e.g., via temperature fluctuations) are kept to a minimum.
6 MINIATURIZATION AND MICROFLUIDICS
Microchip-based analyses have over the last decade made enormous advances and as a consequence are progressively becoming more important within analytical chemistry. The term microfluidics refers to devices, systems, and methods for the manipulation of fluid flows with characteristic length scales in the micrometer range.27 The ability to create the so-called “lab-on-a-chip” or miniaturized total analysis systems (µ-TAS) has allowed for the integration of several procedures onto a single device, such as sample preparation, separation, and, ultimately, detection. The advances in microchip design, coupled to electrode materials available lead to numerous advantages in using this type of technique, such as speed of analysis, reduced sample volumes, and the possibility of “point-of-care” tests or “on-site” functionality. Detection methods utilized within microfluidic systems are analogous to those used within macrobased devices. Techniques such as electrochemical, optical, mass spectrometry, and infrared analysis have all been employed within miniaturized devices to yield signal responses. Two of the most widely used methods of detection are those based upon electrochemical and optical measurements. Within electrochemical detection, there are three main methods of analysis: amperometry, potentiometry, and conductometry. Amperometry, utilizing current changes against applied potential over time, has found the most success since being first reported in the case of microfluidics applications in 1998.28 Owing to the wide variety of materials available for use as the working electrode, such as carbon (in both ink and fiber forms) and metals (such as gold and platinum), this approach is becoming widely applied as the materials involved lend themselves well to undergoing surface modification, allowing for an increase in selectivity and sensitivity in the analysis of biologically significant species such as neurotransmitters,29
10
BIOSENSOR AND BIOCHIP TECHNOLOGIES
environmentally important compounds,30 and for use within clinical assays.31 A comprehensive review of recent applications utilizing amperometric detection on various working electrode materials has been published.32 Miniaturized potentiometric detection is not as advanced as that based upon amperometric detection; however, examples of miniaturized potentiometric devices have been recently reported.33 Devices based on conductometric methodologies have also received much recent attention, with two types of detection systems emerging: contact and contactless detection. Contact conductivity detection involves the direct contact of the sample solution with the detection electrode, whereas contactless approaches involve placing the detecting electrodes around the outside of a sample capillary. Contactless conductometric detection offers advantages over its contact-based counterpart in terms of decreased background noise, thus lowering limits of detection. The electrodes can moreover be easily and reproducibly fabricated via photolithographic techniques. It is these advantages that have made contactless conductometric detection the focus of recent research, where this technique has been utilized to form the basis of analysis procedures for, amongst other species, nerve agents34 and human immunoglobulin.35 Despite the advantages of contactless detection, both contact and contactless detection methodologies are easily transferable onto microchip devices and it is expected that both will therefore continue to find use in applications aimed toward “lab-on-a-chip”-type devices. As mentioned previously, techniques utilizing optical detection are also at the forefront of methods used in conjunction with miniaturized analytical devices. There have been a number of excellent reviews detailing the various techniques being utilized for optical detection of microfluidic devices. An overview of recent publications has been published,36 along with reports on other detection methods such as mass spectrometry and flame ionization. Schwarz and Hauser37 give a brief overview of optical detection techniques based on absorbance, fluorescence, and chemiluminescence, techniques which are further expanded upon by Swinney and Bornhop.38 The area of microfluidic devices is still expanding into a field that encompasses large numbers of research groups and an ever increasing number of companies. Indeed, Vilkner et al. reported that an on-line search in
2003 scored some 3000 separate hits for this area of technology.39 The rheological and other physical properties of the analyte and its matrix are often important factors that must be considered when using microfluidic devices. The viscosity of the sample, for example, greatly affects its behavior while inside a microfluidic device, as does the interaction between the liquid and the surface of the device. Biological fluids and other complex matrices, which exhibit thixotropic properties, especially blood, often prove especially difficult in the context of microfluidic sample handling.
7 MICROELECTRODE ARRAYS
Microelectrode arrays, while offering significant advantages over sensing devices incorporating macro-based electrodes, are still an underdeveloped area in terms of commercial exploitation. The advantages offered by microelectrode array-based devices, include enhanced sensitivity, smaller double-layer capacitances, and lower solutional ohmic losses. The improved diffusional characteristics of microelectrode arrays moreover allow for measurement in both quiescent and stirred solutions. This quality has opened many new possibilities in the development of sensors used as disposable “dip-stick” devices, where the sensor may be placed into analyte solutions without convection giving rise to unwanted fluctuations in the electrode response. To date, the majority of sensors that have reached commercial success have avoided this problem by inhibiting stirring by some means; however, this is not possible for all applications. While the fabrication methods of single microelectrodes are well established,40 such as the embedding of Pt wire or carbon fibers into tapered glass pipettes, they are expensive to produce, are often restricted to use within research applications, and, most importantly, are limited in terms of size of signal response. These limitations can be overcome by the production of microelectrode arrays, where many single microelectrodes are linked together. Microelectrode arrays have previously been fabricated using photolithographic or laser ablation techniques; however, despite various production methodologies, the fabrication of a reproducible
OVERVIEW OF MODERN ANALYTICAL NEEDS
array that may be manufactured at an economical volume and price has yet to be commercialized on a widespread scale. Microelectrode arrays have also been produced by utilizing screen-printing techniques since this method is relatively inexpensive due to the equipment used. The microelectrode geometries produced by such apparatus tend to be relatively large (≥50 µm in comparison to approximately 0.5 µm via photolithographic techniques).41 Recently, however, a new novel technique for the mass production of microelectrode arrays has been reported.42 This new technique utilizes sonochemical ablation of thinfilm polymer layers to produce single discrete microelectrodes (between 1 and 4 µm in diameter) which are interlinked via underlying carbon ink to form an array (Figure 6a). This technique is the first to offer an economically viable fabrication approach for the mass production of microelectrode arrays and lends itself to commercial realization in terms of “one-shot” sensor applications. Microelectrode arrays fabricated by this method have already undergone surface enhancement (Figure 6b) via modification with conductive polymer/enzyme mixtures to allow for measurement of biologically important species.43,44 This fabrication method could therefore open up new research areas in disposable microelectrode arraybased sensing devices, incorporating all the advantages that microelectrodes have to offer.
11
sciences for many years. Early methods involved the chemical cleavage of DNA strands and identification of the individual bases. This intensively laborious, expensive, and time-consuming process has now been superseded by the appearance of DNA arrays that allow multiple sequence detection with high specificity and rapid response times. The sequencing can be performed automatically with small volumes of DNA solution. This field has expanded hugely over the last decade or so and a wide variety of instruments for construction of DNA microarrays and their interrogation are now commercially available. The recent history and construction of DNA microarrays has been extensively reviewed45,46 and has only been summarized here. A DNA microarray can be defined as the integration of a number of DNA sensors onto a single device. The basic principles of the technology are summarized in Figure 7 and depend on the ability of singlestranded DNA to selectively hybridize with its complementary sequence. Firstly, a DNA microarray is constructed by spotting a variety of known oligonucleotides onto precisely defined locations on a solid substrate, often a glass microscope slide. The oligonucleotides are of a precise length and usually all possible combinations are utilized. This requires the precise spotting of a great number of oligonucleotides since the number of possible combinations of oligonucleotides of length n is 4n , for example, there are 65 536 possible DNA 8-mers and over a million possible 10-mers. Other
8 DNA MICROARRAYS
One of the major biotechnology success stories of recent times has been the sequencing of the human genome. The detection of specific DNA sequences has been a major issue in the field of biological
DNA 1 Substrate, e.g., poly(lysine)-coated glass
DNA 2
Label (green)
Label (red)
Spotting of DNA
Combined labeled DNA (a)
(b)
Figure 6. (a) Electron micrograph of sonochemically fabricated microelectrode array showing discrete microelectrodes, (b) scanning electron micrograph of sonochemically fabricated microelectrode array modified with conducting polymer protrusions doped with enzyme.
Hybridization Interrogation (fluorescence)
Figure 7. Typical procedure for comparing gene expression of two species of yeast.
12
BIOSENSOR AND BIOCHIP TECHNOLOGIES
types of sequences have also been utilized such as peptide nucleic acids (PNAs) or RNAs.45 PNA is proving of increasing interest due to higher thermal stability. Simply placing the oligonucleotides onto the chip surface is not sufficient, but rather they must be immobilized to prevent any redissolution. However, the immobilization methods must be stable under the conditions found in subsequent arraying steps, not interfere with the probe functionality, and allow immobilization of the probe in such a manner that the base pairing interactions leading to hybridization are not hindered. Several techniques may be used for this purpose. One of the simplest and most common methods is to precoat the slide with a positively charged polymer, such as polylysine, and utilize the strong electrostatic interactions between the cationic polymer and the anionic phosphate groups of the nucleic acid to immobilize the probe strands. Precoated slides are now widely commercially available. Other methods have also been utilized,45,46 and include techniques such as covalently coupling the free residues at one end of the DNA chain to an active group on the glass surface or to cross-link the deposited DNA via either chemical or photochemical means. The possibility of using the strong gold–thiol interaction or the use of avidin–biotin interactions have also been investigated in this context.45,47 Owing to the high density and small spot size required for DNA microarrays, a variety of methods have been studied.45 The most common method is that of pin deposition where small pins are immersed into solutions of the DNA probes and withdrawn, taking with them small amounts of solution. When the pins are touched against the solid substrate, a drop of solution is transferred. Spot sizes of 50–360 µm can be obtained by this method. As an alternative, ink-jet printing technology has been adapted for the purpose of creating microarrays. This has the advantage that it is a noncontact technique, thus reducing the risk of cross contamination between spots. DNA solutions are withdrawn from a reservoir and then ejected from the print head onto the substrate. Spot densities of up to 2500 spots/cm2 can be obtained using these types of methods, although commercial systems tend to be somewhat lower in number.45 Both pin deposition and ink-jet printing approaches utilize preformed oligonucleotide strands. Photolithographic techniques were first introduced
by Affymetrix and involve the in situ synthesis of oligonucleotides with specific structure and location on a solid substrate.48 The process involves generating a reactive surface, usually containing amino groups, and then chemically passivating it with a photolabile protecting group (Figure 8). Exposure to light through a mask then activates certain areas of the substrate, which may then be derivatized with a nucleic acid monomer, with no reaction occurring in unactivated areas. A further irradiation through a second mask takes place, with some of the activated sites being the same as those activated previously and some being different. Multiple repetitions of this procedure allow the build up of different oligonucleotide sequences at every site on the chip addressable by light. The high resolution attainable by photolithographic methods gives this protocol one of the highest spot densities available;45 however, there are problems in that each synthetic step must proceed with an exceedingly high yield to give good spot qualities. An example (Figure 7) is given here for the comparison of gene expression through two different organisms, such as wild-type yeast and a mutant. Firstly, the mRNA from each organism is extracted and this is then transformed to cDNA by reverse transcription. DNA from the first culture is then labeled with a green fluorescent dye, whereas DNA from the second culture is labeled with a red fluorescent dye. Once labeled, the two mixtures are then combined, placed onto the DNA microarray and incubated at 60 ◦ C overnight. The slide is then thoroughly rinsed and dried, ready for interrogation. Usually the slide is scanned with a laser and any fluorescence detected with a confocal microscope. A picture is built up, showing whether each spot has bound green-labeled DNA, red-labeled DNA, a mixture of both, or neither. Differences in the amount of labeled DNA bound to each oligonucleotide give a measurement of which genes are expressed by which phenotype. Other uses could include the comparison of pathogenic and related nonpathogenic organisms or the differentiation of healthy and cancerous cells.
9 PROTEIN MICROARRAYS
DNA microarray technology has played a major role in the analysis of genomes and gene expression. However, biological functions are carried
OVERVIEW OF MODERN ANALYTICAL NEEDS
13
Mask 1 NHP NHP
NHP
Substrate
P = Protecting group Mask 2 G-P
Light NHP NH
NHP
NHP NH
G-P NHP
Substrate
Substrate
NHP NH
NHP
Substrate
G-P 1. Light 2. A-P
T-P
A-P
A-P
G
T-P
NH
NH
NH
Mask 3
T-P G NHP NH
Substrate
T-P T-P NH
Substrate
G NHP NH
T-P NH
Substrate
1. Light 2. A-P Figure 8. Photolithographic method for controlled synthesis of oligonucleotides to form a microarray.
out not by DNA itself but by other biomolecules such as proteins. This has led to the development of protein-based biochips, similar in structure to DNA microarrays, to allow identification of protein–ligand interactions.49,50 The initial requirement for protein biochips is the generation of a wide variety of proteins for immobilization. These are usually generated by recombinant expression within E. coli and purification.50 The proteins once generated can then be immobilized using methods similar to those used to generate DNA microarrays. Similar interrogation methods can also be used. There are numerous potential uses for protein microarrays. For example, the selectivity and cross-reactivity of antibodies can be determined by placing them on a protein microarray and then monitoring their binding. Alternatively, of course, a series of antibodies can be immobilized instead, which can then be exposed to a mixture of proteins. Immobilization of antibodies to form an array is often simpler since most antibodies have the same basic structure and can be immobilized using the same techniques, whereas different proteins often have widely different structures.
Once the selectivity and sensitivity of each antibody has been assessed, the resulting antibody array can then be used to investigate proteomes of interest. For example, antibody arrays were exposed to serum from a number of patients with a variety of differing diseases.50 It was found that different diseases led to different binding patterns, indicating the possibility of using these chips for diagnosis. Other potential uses of protein microarrays involve the study of interactions of proteins with a wide variety of species such as other proteins, DNA, RNA, peptides, oligosaccarides, and other chemical compounds. For example, a chip containing 37 000 yeast recombinant proteins (requiring just 10 pg of each material) was used to identify proteins which bound a peptide that was part of the platelet membrane protein integrin.51 This approach demonstrates the high potential of these biochips to detect and identify previously unknown protein interactions. Other uses of these chips include identification of protein–drug interactions and, in this context, it should be noted that arrays of enzymes can also be used to assess their activities toward a variety of substrates.50
14
BIOSENSOR AND BIOCHIP TECHNOLOGIES
Enzyme-based chips can be used in the detection of many compounds. Many species, which require monitoring (e.g., blood glucose in a diabetic patient), are quite difficult to detect as the primary analyte. Enzymes such as glucose oxidase can be used to generate a more detectable species, such as hydrogen peroxide, which can be determined electrochemically, and related back to the glucose concentration. This is of course the principle of the biosensor; however, sometimes it can be advantageous to actually separate the enzyme reaction from the detection event. For example, the optimum detection of a certain species may require different temperature and pH conditions than the optimum enzyme reaction conditions.52 Enzymes can be immobilized within microfluidic chip devices to enable testing of small volumes of solution.52 Firstly, the sample is introduced and flows over an immobilized enzyme. Owing to the high turnover rate of enzymes, there is conversion of much of the substrate to a detectable form. This flows on further down the chip and is introduced to the detector. The microfluidic nature also allows the splitting of the sample into two or more fractions, each of which can be introduced to a different enzyme, for example, for the simultaneous detection of glucose and alcohol in wine.52 The small size of these devices may in future years allow many parallel analyses to be run simultaneously. All of the microarrays described in the preceding text deal with samples in solution—usually aqueous, since many biomolecules either do not dissolve in or are denatured by organic solvents. Again, the problem of nonspecific absorbance needs to be addressed. The limiting factor for the processing ability of these systems is often how many dots or microwells can be laid down in a given area and this is a rapidly advancing field in which ever greater density of arrays are being reported regularly.
10 PERSONALIZED MEDICINE
In most cases, patients first present themselves to primary practitioners who either prescribe treatment directly or refer the patient to the hospital that often runs a series of tests having taken a number of biological samples. As an alternative to this,
there has been a burgeoning research effort into developing simple, so-called point-of-care tests that may be used by doctors, other health practitioners, and/or the patient themselves. The most common example of this is seen in the patient self-testing devices for diabetics to regularly test their own blood sugar at frequent intervals without the requirement for skilled medical help. The availability of this technology has meant a huge improvement in the quality of life for patients and there is a sustained research effort toward further exploring these and many of the other sensor devices. Patient compliance with a strict testing regime can be a major problem and if not addressed can lead to complications. There is much interest in sensors that can log the times for readings for any tests so that these can be reviewed in followup sessions. There is also the potential to upload results from the sensor to a home computer or personal digital assistants (PDA) and then send the results via the Internet or global positioning system (GPS) network to the clinic, so opening up the field of “e-medicine”. In this way, results of tests can be processed and any potential long-term problems identified. Some of the characteristics of e-medicine that set it apart from the more traditional doctor–patient interactions are the need for fewer face-to-face appointments. Patients and doctors can access each other remotely and necessary information can be transferred at any time and not only during a consultation. The fact that the information is electronically stored also allows medical staff and/or patients to compare readings with previous trends. This is an important factor, which is, for example, allowing patients to regulate conditions such as diabetes with far greater control. Location issues are also avoided, so opening up the (albeit limited) possibilities for clinical care in remote regions. Sensors can be used for preventative medicine as well as those with prediagnosed conditions, with applications ranging from the monitoring of cholesterol levels through to markers for early stage carcinoma. Each individual has his/her own genome, his/her own proteome, and often different responses toward various drugs. This opens up the field of personalized medicine. Previously, many treatments were based on simple determinations such
OVERVIEW OF MODERN ANALYTICAL NEEDS
as sex, age, and body mass index. Modern techniques are being applied to develop tailored health care for individual patients. For example, the DNA microarray technology described earlier can be utilized to test for genes for hereditary diseases and/or a susceptibility to differing cancers. The costs associated with assays of this type are diminishing rapidly, therefore permitting widespread screening of the population, thereby highlighting possible future health problems and so allowing preventative treatment to be initiated. A similar approach can be utilized in patient treatment; for example, biopsies can be taken from cancer patients and the cells from these tested for susceptibility to chemotherapy drugs and combinations thereof. Should the samples prove particularly susceptible to a particular drug or combination, then this can be utilized to treat the individual patient with optimized efficiency. For example, biopsy samples can be immobilized on gold electrodes and the electrochemical potentials of the cell membranes measured.53 When these cells are exposed to different chemotherapy drugs, the changes in potential reflect the sensitivity of the cells to individual drugs, thereby giving a measure of the most effective treatment.53
11
CONCLUSIONS
As this chapter has shown, there are a wide variety of novel exciting techniques becoming ever more widely available to the analytical biochemist. The development of a wide variety of sensing techniques for measuring a wide range of properties such as electrochemical parameters, optical phenomena such as fluorescence, and also mass changes greatly opens up the range of materials that can be studied. The combination of this with the miniaturization afforded by the use of microfluidics and also arraying techniques (which can lay down thousands of different biological samples on a microscope slide) should greatly increase the throughput and decrease the time and cost of these measurements. This leads to the possibility of concepts such as each person being able to have his/her own genomes readily sequenced at an economically viable cost or having a medical treatment personalized to give optimal efficacy for each individual patient.
15
REFERENCES 1. M. A. Brown and K. A. Brix, Review of health consequences from high-, intermediate- and low-level exposure to organophosphorus nerve agents. Journal of Applied Toxicology, 1998, 18, 393–408. 2. Material Safety Data Sheet—Lethal Nerve Agent Sarin, U.S. Army Chemical and Biological Defense Agency. Edgewood Research, Development and Engineering Center, Aberdeen Proving Ground, MD. 3. C. D’Amato, J. P. M. Torres, and O. Malm, DDT (Dichlorodiphenyltrichloro ethane): toxicity and environmental contamination—A review. Quimica Nova, 2002, 25, 995–1002. 4. J. Debska, A. Kot-Wasik, and J. Namiesnik, Fate and analysis of pharmaceutical residues in the aquatic environment. Critical Reviews in Analytical Chemistry, 2004, 34, 51–67. 5. A. E. van den Bogaard and E. E. Stobberingh, Epidemiology of resistance to antibiotics: links between animals and humans. International Journal of Antimicrobial Agents, 2000, 14, 327–335. 6. E. R. Weiner, Applications of Environmental Chemistry, Lewis, 2000. 7. J. J. Gooding, Electrochemical DNA hybridisation biosensors. Electroanalysis, 2002, 14, 1149–1156. 8. P. Santos-Alvarez, M. J. Lobo-Castanon, A. J. MirandaOrdieres, and P. Tunon-Blanco, Current strategies for electrochemical detection of DNA with solid electrodes. Analytical and Bioanalytical Chemistry, 2004, 378, 104–118. 9. E. Palecek, Past, present and future of nucleic acids electrochemistry. Talanta, 2002, 56, 809–819. 10. F. Davis, A. V. Nabok, and S. P. J. Higson, Species differentiation by DNA-modified carbon electrodes using an AC impedimetric approach. Biosensors and Bioelectronics, 2004, 20, 1531–1538. 11. E. Fortin, Y. Defontaine, P. Mailley, T. Livache, and S. Szunerits, Micro-imprinting of oligonucleotides and oligonucleotide gradients on gold surfaces: a new approach based on the combination of scanning electrochemical microscopy and surface plasmon resonance imaging (SECM/SPR-i). Electroanalysis, 2005, 17, 495–503. 12. S. Szunerits, L. Bouffier, R. Calemczuk, B. Corso, M. Demeunynck, E. Descamps, Y. Defontaine, J.-B. Fiche, E. Fortin, T. Livache, P. Mailley, A. Roget, and E. Vieil, Comparison of different strategies on DNA chip fabrication and DNA-sensing: optical and electrochemical approaches. Electroanalysis, 2005, 22, 2001–2017. 13. Y. Ito and E. Fukusaki, DNA as a nanomaterial. Journal of Molecular Catalysis B: Enzymatic, 2004, 28, 155–166. 14. J. Wang, Nanoparticle-based electrochemical DNA detection. Analytica Chimica Acta, 2003, 500, 247–257. 15. J. Wang, Nanomaterial-based amplified transduction of biomolecular interactions. Small, 2005, 11, 1036–1043. 16. S. Grant, F. Davis, K. A. Law, A. C. Barton, S. D. Collyer, S. P. J. Higson, and T. D. Gibson, Label-free and reversible immunosensor based upon an ac impedance interrogation protocol. Analytica Chimica Acta, 2005, 537, 163–168.
16
BIOSENSOR AND BIOCHIP TECHNOLOGIES
17. V. B. Kandimalla and H. Ju, New horizons with a multi dimensional tool for applications within analytical chemistry—aptamers. Analytical Letters, 2004, 11, 2215–2233. 18. G. S. Wilson and R. Gifford, Biosensors for real-time in vivo measurements. Biosensors and Bioelectronics, 2005, 20, 2388–2403. 19. L. A. Sombers, H. J. Hanchar, T. L. Colliver, N. Wittenburg, A. Cans, S. Arbault, C. Amatore, and A. G. Ewing, The effects of vesicular volume on secretion through the fusion pore in exocytotic release from PC12 cells. Journal of Neuroscience, 2004, 24, 303–309. 20. O. S. Wolfbeis, Fiber-optic chemical sensors and biosensors. Analytical Chemistry, 2002, 74, 2663–2678. 21. J. R. Epstein and D. R. Walt, Fluorescence-based fibre optic arrays: a universal platform for sensing. Chemical Society Reviews, 2003, 32, 203–214. 22. Z. Juan and T. M. Swager, Poly(arylene ethynylene)s in chemosensing and biosensing. Advances in Polymer Science, 2005, 177, 151–179. 23. R. Karlsson, SPR for molecular interaction analysis: a review of emerging application areas. Journal of Molecular Recognition, 2004, 17, 151–161. 24. B. Ivarsson and M. Malmqvist, in Biomolecular Sensors, E. Gizeli and C. R. Lowe (eds), Taylor & Francis, 2002. 25. C. K. O’Sullivan and G. G. Guilbault, Commercial quartz crystal microbalances—theory and applications. Biosensors and Bioelectronics, 1999, 14, 663–670. 26. F. L. Dickert, P. Lieberzeit, and O. Hayden, Sensor strategies for micro-organism detection—from physical principles to imprinting procedures. Analytical and Bioanalytical Chemistry, 2003, 377, 540–549. 27. H. A. Stone, A. D. Strook, and A. Ajdari, Engineering flows in small devices: microfluidics toward a lab-ona-chip. Annual Review of Fluid Mechanics, 2004, 36, 381–411. 28. A. T. Woolley, K. Q. Lao, A. N. Glazer, and R. A. Mathies, Capillary electrophoresis chips with integrated electrochemical detection. Analytical Chemistry, 1998, 70, 684–688. 29. J. Wang, G. Chen, M. P. Chatrathi, and M. Musameh, Capillary electrophoresis microchip with a carbon nanotube-modified electrochemical detector. Analytical Chemistry, 2004a, 76, 298–302. 30. G. Che and J. Wang, Fast and simple sample introduction for capillary electrophoresis microsystems. Analyst, 2004, 129, 507–511. 31. R. Wilke and S. Buttgenbach, A micromachined capillary electrophoresis chip with fully integrated electrodes for separation and electrochemical detection. Biosensors and Bioelectronics, 2003, 19, 149–153. 32. W. R. Vandaveer, S. A. Pasas-Farmer, D. J. Fischer, C. N. Frankenfeld, and S. M. Lunte, Recent developments in electrochemical detection for microchip capillary electrophoresis. Electrophoresis, 2004, 25, 3528–3549. 33. R. Ferrigno, J. N. Lee, X. Jiang, and G. M. Whitesides, Potentiometric titrations in a poly(dimethylsiloxane)-based microfluidic device. Analytical Chemistry, 2004, 76, 2273–2280.
34. J. Wang, G. Chen, A. Muck Jr, M. P. Chatrathi, and A. Mulchandani, Microchip enzymatic assay of organophosphate nerve agents. Analytica Chimica Acta, 2004b, 505, 183–187. 35. E. M. Abad-Villar, J. Tanyanyiwa, M. T. FernandezAbedul, A. Costa-Garcia, and P. C. Hauser, Detection of human immunoglobulin in microchip and conventional electrophoresis with contactless conductivity measurements. Analytical Chemistry, 2004, 76, 1282–1288. 36. K. B. Mogensen, H. Klank, and J. P. Kutter, Recent developments in detection for microfluidic systems. Electrophoresis, 2004, 25, 3498–3512. 37. M. A. Schwarz and P. C. Hauser, Recent developments in detection methods for microfabricated analytical devices. Lab on a Chip, 2001, 1, 1–6. 38. K. Swinney and D. J. Bornhop, Detection in capillary electrophoresis. Electrophoresis, 2000, 21, 1239–1250. 39. T. Vilkner, D. Janasek, and A. Manz, Micro total analysis systems. Recent developments. Analytical Chemistry, 2004, 76, 3373–3386. 40. C. G. Zoski, Ultramicroelectrodes: design, fabrication and characterisation. Electroanalysis, 2002, 14, 1041–1051. 41. X. Xie, D. Stueben, and Z. Berner, The application of microelectrodes for the measurements of trace metals in water. Analytical Letters, 2005, 38, 2281–2300. 42. A. C. Barton, S. D. Collyer, F. Davis, D. D. Gornall, K. A. Law, E. C. D. Lawrence, D. W. Mills, S. Myler, J. A. Pritchard, M. Thompson, and S. P. J. Higson, Sonochemically fabricated microelectrode arrays for biosensors offering widespread applicability: Part I. Biosensors and Bioelectronics, 2004, 20, 328–337. 43. S. Myler, F. Davis, S. D. Collyer, and S. P. J. Higson, Sonochemically fabricated microelectrode arrays for biosensors—Part II modification with a polysiloxane coating. Biosensors and Bioelectronics, 2004, 20, 408–412. 44. S. Myler, S. D. Collyer, F. Davis, D. D. Gornall, and S. P. J. Higson, Sonochemically fabricated microelectrode arrays for biosensors Part III. AC impedimetric study of aerobic and anaerobic response of alcohol oxidase within polyaniline. Biosensors and Bioelectronics, 2005, 21, 666–671. 45. M. Campas and I. Katakis, DNA biochip arraying, detection and amplification strategies. Trends in Analytical Chemistry, 2004, 23, 49–62. 46. G. H. W. Sanders and A. Manz, Chip based microsystems for genomic and proteomic analysis. Trends in Analytical Chemistry, 2000, 19, 364–378. 47. F. Davis and S. P. J. Higson, Structured thin films as functional components within biosensors. Biosensors and Bioelectronics, 2005, 21, 1–20. 48. S. P. A. Fodor, J. L. Read, M. C. Pirrung, L. Stryer, A. Tsai-Lu, and D. Solas, Light-directed, spatially addressable parallel chemical synthesis. Science, 1991, 251, 767–773. 49. K. K. Jain, Applications of biochips: from diagnostics to personalized medicine. Current Opinion in Drug Discovery and Development, 2004, 7, 285–289. 50. A. Lueking, D. J. Cahill, and S. Mullner, Protein biochips: a new and versatile platform technology for molecular medicine. Drug Discovery Today, 2005, 10, 789–794.
OVERVIEW OF MODERN ANALYTICAL NEEDS 51. A. Lueking, M. Horn, H. Eickhoff, K. B¨ussow, H. Lehrach, and G. Walter, Protein microarrays for gene expression and antibody screening. Analytical Biochemistry, 1999, 270, 103–111. 52. J. Wang, On-chip enzymatic assays. Electrophoresis, 2002, 23, 713–718.
17
53. D. E. Woolley, L. C. Tetlow, D. J. Adlam, D. Gearey, R. D. Eden, T. H. Ward, and T. D. Allen, Electrochemical monitoring of anticancer compounds on the human ovarian carcinoma cell line A2780 and its adriamycin- and cisplatin-resistant variants. Experimental Cell Biology, 2002, 272, 65–72.
3 Historical Perspective of Biosensor and Biochip Development Jeffrey D. Newman and Anthony P. F. Turner Cranfield Health, Cranfield University, Silsoe, UK
The following chapter aims to review the relatively brief history of biosensors. The use of the word brief, may surprise some readers, since at the time of writing, it is already 45 years since the first device was described (almost an eternity in modern science!). However, developments were originally very slow, and it was around 15 years before interest and progress picked up pace. A couple of years ago marked the 20th anniversary of the journal Biosensors and Bioelectronics. The journal appeared in 1985 and was simply called Biosensors (the name was changed in 1992). The first issue contained three reviews and one research paper. Indeed, only 10 papers were published in the whole of the first year—a far cry from the 298 articles that appeared in Biosensors and Bioelectronics in 2005 and the 1000 papers that were submitted in 2006. Widening the search to all journals, using the ISI Web of Knowledge, and the search term biosensor(s) reveals 35 hits in 1985 and 2090 in 2005. The early days, when only a handful of groups were operating worldwide, were however, extremely inventive. A scan of the biosensor literature is not a straightforward task; nevertheless, it is an interesting exercise to carry out. In 2000, for example, a total of 956 papers were identified worldwide in the biosensor area. This figure rose by almost 60%, to the staggering figure of 1525 in 2002, reaching, as we have seen, 2090 by 2005. It possibly comes as no great surprise that the United States is the
world leader in terms of biosensor publications, especially in view of their commercial dominance. What is, perhaps, more surprising is that China is currently at number three in the list and was second in 2000. The top five is completed by Japan, Germany, and the United Kingdom.1 A timeline, such as that shown in Table 1, illustrates how, after a slow start, biosensor concepts rapidly multiplied. It also demonstrates how much things have changed, commercially speaking, in recent years, dominated by headlines involving huge business deals. The total world market for biosensors was recently estimated to be nearly $7 billion, of which around 85% involved home blood glucose monitors.2
1 THE EARLY DAYS
The father of the biosensor concept can be identified clearly as the late Professor Leland C. Clark Jr. In 1956, Clark published his definitive paper3 on the oxygen electrode, a schematic of which is shown in Figure 1. The Clark electrode was a considerable breakthrough and devices based on this design have remained in production ever since. However, Clark was keen to expand the range of analytes that could be measured in the body and realized that this could be achieved, by modifying
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR AND BIOCHIP TECHNOLOGIES Table 1. Some defining events in the history of biosensor development
Date 1916 1922 1956 1962 1969 1970 1972–1975 1975
1976 1980 1982 1983 1984 1987 1990 1992 1996 1996 1998 1998 2001 2003 2004
Event First report on the immobilization of proteins: adsorption of invertase on activated charcoal First glass pH electrode Invention of the oxygen electrode First description of a biosensor: an amperometric enzyme electrode for glucose First potentiometric biosensor: urease immobilized on an ammonia electrode to detect urea Invention of the ISFET First commercial biosensor: Yellow Springs Instruments glucose biosensor First microbe-based biosensor First immunosensor: ovalbumin on a platinum wire Invention of the pO2 /pCO2 optode First bedside artificial pancreas (Miles) First fiber-optic pH sensor for in vivo blood gases First fiber-optic-based biosensor for glucose First SPR immunosensor First mediated amperometric biosensor: ferrocene used with GOx for the detection of glucose Launch of the MediSense ExacTech blood glucose biosensor Launch of the Pharmacia BIACore SPR-based biosensor system i-STAT launches handheld blood analyzer Glucocard launched Abbott acquires MediSense for $867 million Launch of LifeScan FastTake blood glucose biosensor Merger of Roche and Boehringer Mannheim to form Roche Diagnostics LifeScan purchases Inverness Medical’s glucose testing business for $1.3 billion i-STAT acquired by Abbott for $392 million Abbott acquires TheraSense for $1.2 billion
ISFET, ion-selective field-effect transistor; SPR, surface plasmon resonance; GOx, glucose oxidase.
Connections to amplifier Epoxy seal
Silver wire coated with AgCl
Hole to add 100 mM KCl electrolyte
Plexiglass cylinder O2-permeable membrane, held in place with
Pt wire melted to give bead at end, sealed in glass, ground down to expose Flat surface
O-ring in groove
Figure 1. Schematic of Clark oxygen electrode.
the oxygen electrode, with enzymes. He made a landmark address in 1962 at a New York Academy of Sciences symposium, in which he described “how to make electrochemical sensors
(pH, polarographic, potentiometric or conductometric) more intelligent” by adding “enzyme transducers as membrane enclosed sandwiches”. The concept was illustrated by an experiment in which glucose oxidase (GOx) was entrapped at a Clark oxygen electrode using a dialysis membrane. The decrease in measured oxygen concentration was proportional to glucose concentration. In the published paper Ref. 4, the term enzyme electrode was coined, which many reviewers have mistakenly attributed to Updike and Hicks, who, in 1967, expanded on the experimental detail necessary to build functional enzyme electrodes for glucose.5 Clark-type devices rely on the application of a potential of between −0.6 and −0.8 V between the Ag/AgCl reference and the platinum working electrode. The oxygen dissolved in the solution between the electrodes is reduced (Figure 2). The resultant current is proportional to the local oxygen concentration. From the reaction scheme in Figure 2, it is apparent that it is also possible to measure glucose via the oxidation of the hydrogen peroxide produced by the enzymatic reaction, since this is
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
Enzyme [red]
Product
H2O2 Electrode
Enzyme [ox]
Substrate
3
O2
Oxygen electrode or peroxide oxidation
Figure 2. Clark-type biosensor schematic.
also directly proportional to the concentration of glucose. This can be measured amperometrically at a potential of approximately +0.7 V versus Ag/AgCl, when a platinum working electrode is used. The Clark-style sensor is not restricted to measuring glucose. Particularly in the early years of biosensor development, numerous variations on the basic design and many other (oxidase) enzymes were immobilized by various workers as a result.6–8 Other electrode configurations, featuring carbon and other working electrodes can be constructed and operated via amperometry in a similar manner.9 For the interested reader, Clark wrote a fascinating article in 1993, in which he recounted the historical development of his oxygen and enzyme electrodes.10 In principle, many transducers can be used in a biosensor and early researchers were quick to exploit these opportunities. In 1969, Guilbault and Montalvo were the first to detail a potentiometric enzyme electrode.11 They described a urea sensor based on urease immobilized at an ammonium-selective liquid membrane electrode (see reaction scheme below). Others have used pH electrodes12 and pH ion-selective field-effect transistors (ISFETs)13 as transducers.
Urease
Urea + H2 O −−−→ CO2 + 2NH3
One of the drawbacks of potentiometric devices is the cost of producing the transducer, which has been a particular parameter for biosensors, which have largely been produced for the medical market as disposable devices. In 1970, Bergveld described the first ISFET14 which, by the early 1980s was seen by many as the way to go. Such sensors are produced by silicon processing and, hence, are scalable to very high volume, inexpensive, production. However, there were numerous production problems, which took many years to overcome, and these resulted in devices that were simply too expensive for most applications. Nevertheless, much research has been carried out15 and today there are niche applications for this technology.16
2 THE INVENTIVE SEVENTIES
The mid to late 1970s witnessed an explosion of biosensor concepts. It was quickly realized that there were an enormous number of combinations of transducers (Table 2) and bioreceptors. During this time, many of these combinations were tested, initially with enzymes and then with other biological components. Academic journals now contain descriptions of a wide variety of devices exploiting enzymes, nucleic acids, cell receptors, antibodies, and intact cells, in combination with electrochemical, optical, piezoelectric, thermometric, magnetic, and micromechanical transducers. Within
4
BIOSENSOR AND BIOCHIP TECHNOLOGIES Table 2. Examples of transducers used in biosensor construction
Transducer
Examples
Electrochemical Optical Piezoelectric Calorimetric Magnetic Micromechanical
Clark electrode, mediated electrodes, ISEs, FET-based devices, LAPS Photodiodes, waveguide systems, integrated optical devices Quartz crystals, SAW devices Thermistor, thermopile Hall effect, magnetoresistive Viscosity, pressure, force, and oscillating cantilevers
ISEs, ion-selective electrodes; FET, field-effect transistor; LAPS, light-addressable potentiometric sensors; SAW, surface acoustic wave.
each permutation lies a myriad of alternative transduction strategies and each approach can be applied to numerous analytical problems in healthcare,17 food and drink,18 the process industries,19 environmental monitoring,20 and defense and security.21 An excellent summary list, by analyte, is provided in Alice Cunningham’s 1998 text.22 The use of thermal transducers for biosensors was proposed in 1974 and the new devices were christened thermal enzyme probes 23 and enzyme thermistors.24 The greatest drawback of thermal devices is their inherent lack of selectivity with respect to ambient thermal fluctuations, which has resulted in numerous attempts at designing systems and strategies to overcome this. In order to enhance selectivity and sensitivity, two main methods have been employed. The first is to use well-insulated, microfabricated25 devices. The second is to use coupled enzymatic reactions, so that the reaction enthalpies are added. An early example of this approach was the coimmobilization of GOx and catalase26 in the following scheme: H (KJ mol−1 ) GOx
Glucose + O2 −−−→ Gluconolactone + H2 O 2 Catalase
H2 O2 −−−→ H2 O + 1/2 O2
−50 −100
Thermometric approaches were used to develop novel enzyme-linked immunosorbent assays (TELISAs),27 which are early examples of an immunological biosensor. These will be discussed in more detail later. Another fledgling incarnation of a particular type of device, the inhibitor detector, was also demonstrated using thermal principles. In this case, the inhibition of urease
by heavy metal ions was monitored via an enzyme thermistor.28 In contrast with most analytical devices, the inhibitor detector monitors the decrease in response of a sensor in the presence of the target compound. Once more, this approach was to become more broadly adopted using other transducers. The most significant work was the study the inhibition of enzymes such as acetylcholine esterase (ACh) or butyrylcholine esterase (BCh) by a variety of toxins. This approached formed the basis for an early range of chemical defense systems and were therefore one of the earliest commercial successes of biosensors. Initial device designs were really enzyme reactors29 with electrochemical detection, but this clearly laid the foundation for biosensor configurations exploiting the same principles. This work has remained popular with many groups exploiting the concept. An interesting example uses amperometric biosensors based on Ach or BCh the kinetic determination of organophosphate and carbamate pesticides.30
2.1
Optical Solutions
The term optode was first used by Lubbers and Opitz, in 1975 to describe a fiber-optic sensor with immobilized indicator to measure carbon dioxide or oxygen.31 Although these devices were not biosensors, the authors subsequently extended the concept to make an optical biosensor for alcohol by immobilizing alcohol oxidase on the end of a fiber-optic oxygen sensor. Commercial optodes are now showing excellent performance for in vivo measurement of pH, pCO2 , and pO2 , but enzyme optodes have not thrived to the same extent, despite the fact that it is relatively simple to
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
construct optical devices of this type. Descriptions of devices do crop up in the literature, where a common format is to use optical fibers, which have a chemically modified tip containing either a pH sensitive material32 or a fluorophore.33 An optical phenomenon that has proved very useful in biosensing applications occurs when total internal reflection occurs at an interface. When this occurs, there is interference between the incident and reflected waves, which results in a standing wave. This causes a light intensity that extends beyond the edge of the waveguide and is referred to as the evanescent wave. The intensity drops off exponentially away from the surface over an effective depth of a few tens of nanometers. However, if the interface between the waveguide and the external medium is coated with a thin layer of metal, such as gold, and monochromatic, p-polarized light is used, the intensity of the reflected light decreases sharply at a specific incident angle producing a shadow. This effect is termed surface plasmon resonance (SPR) and is due to the resonance energy transfer between the evanescent wave and surface plasmons (Figure 3). The resonance conditions are influenced by properties such as the refractive index of the material adsorbed onto the metal film. As can be seen from Figure 3, one could monitor the resonance angle itself, which varies as the conditions close to the sensor alter. However, a very sensitive approach is to monitor the sharp increase in reflected light intensity as the system moves away from resonance.
These properties make SPR very useful in many biosensing applications, since they allow many biological interactions to be monitored directly, at the surface. The SPR signal, which is often expressed in resonance units, is therefore a measure of mass concentration at the sensor chip surface. This means that the analyte and ligand association and dissociation can be observed and ultimately, rate constants as well as equilibrium constants can be calculated. First described34 in 1965, evanescent wave excitation for analysis is not particularly new. It has been used in numerous spectroscopic applications, particularly in the study of adsorption phenomena.35 So, in retrospect, it is perhaps surprising that SPR (and other evanescent techniques) were not directly referred to for biosensing until the early 1980s,36 although this was predated by a description of evanescent wave excitation for a fluorescence immunoassay in 1975.37 Evanescent wave fluorescence biosensors provide the considerable advantage of improved discrimination of specific binding from nonspecific adsorption of components from the sample. An enormous number of analytes have been detected by a variety of fluorescence approaches.38 The technology has been driven more recently by defense applications, for which it has proved particularly well suited. The use of many optical transduction schemes soon followed, based on effects including mode beat and dual beam interferometry; phase changes; reflectance techniques such as elipsometry; and coupling effects between waveguide structures.39 Optical detection unit
Light source
Intensity
I Polarized light Prism
Sensor chip with gold film
5
II Reflected light
I
II
Angle
Resonance II signal I
Time Sensorgram
Flow channel Figure 3. Surface plasmon resonance.
6
2.2
BIOSENSOR AND BIOCHIP TECHNOLOGIES
Acoustic Wave Devices
The measurement of mass changes on a surface, due to a biological binding reaction such as an immunoreaction, is not restricted to the use of optical devices. Acoustic wave devices also emerged relatively early in the biosensor story. Early uses of piezoelectric transducers involved the measurement of gases such as sulfur dioxide.40 The first piezoelectric device (often termed quartz crystal microbalances or QCMs) in a biosensor format was produced in 1972, for the determination of bovine serum albumin (BSA) antibodies.41 Early quartz devices were hampered by poor selectivity and sensitivity. The technology was also not widely available, so few groups were active in the area. Sixteen years passed before Fawcett et al. described the first piezoelectric biosensor for DNA by immobilizing single-stranded DNA on the crystals and detecting the mass change after hybridization.42
2.3
Whole-cell Biosensors
A new direction for biosensors was proposed in 1975, when Divi`es suggested that bacteria could be harnessed as the biological element in microbial electrodes for the measurement of alcohol.43 This paper marked the beginning of a major research effort, in Japan and elsewhere, into biotechnological and environmental applications of whole-cell biosensors. Some early attempts at harnessing living cells in sensors looked at measuring individual compounds or closely related compounds, as suggested in the original paper, but this did not play to the strengths of the technology. A particular advantage of these systems is their ability to measure direct effects on living cells, such as changes in respiratory activity due to the impact of environmental pollutants. The fundamental idea was not particularly new. The miner’s canary (Figure 4) is an early example of the use of a whole organism as a pollution monitor. A more recent and sophisticated system used rainbow trout as pollution detectors.44 The difference with the bacterial approach was the degree of integration with a sensor. Work in the area diverged into several types of device, some of which stretch the definition of a biosensor somewhat. Many examples of
Figure 4. The miner’s canary.
microorganisms were incorporated into amperometric devices to produce environmental biosensors. Typical of this approach is the use of eukaryotic algae for monitoring pollution of aquatic systems.45 In this approach one is able to compare the sensor response obtained prior to challenge with pollutants with that following the challenge, by measuring the photosynthetic activity. The most important biosensor to emerge from this work, however, is the biochemical oxygen demand (BOD) sensor. Pioneered in Japan, this provided a realistic alternative to the conventional 5-day test. The conventional test, first adopted in 1908, measures the rate of oxygen uptake, at 20 ◦ C over 5 days in the dark, by aerobic microorganisms present in an aliquot of diluted activated sludge added to the sample of water. Early approaches were manometric, although this has been replaced by more convenient ways of measuring dissolved oxygen content. The innovation of the BOD sensor was first reported46 by Karube et al. in 1977. By immobilizing microorganisms on the tip of an oxygen electrode they were able to measure oxygen consumption over a period of just a few minutes and correlate this with BOD. The method has since been used extensively in Japan and several companies have produced BOD sensors around the world. However, the 100-year-old standard method has not been widely displaced due to the lack of exact correlation between the two somewhat arbitrary measurements of assimilable
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
carbon in a water sample and the consequent recalcitrance of the old method due to its embodiment in legislation. The area that has received the most attention for toxicity monitoring is one that stretches the biosensor definition the most in this area, and involves the use of bioluminescent organisms (Figure 5). With their inherent beauty and ease of detection, these have always attracted the attention of scientists, but their usefulness was greatly enhanced, starting about 30 years ago, due to the great deal of progress in the physiology, biochemistry, and genetic control of bacterial bioluminescence. The process requires the enzyme luciferase, which was first purified by McElroy and Green47 in the 1950s. With the advent of molecular biology, it has been possible to construct bioluminescent bacteria that are naturally dark by insertion of lux genes. The reaction proceeds as follows: Luciferase
ATP + Luciferin + O2 −−−→ Oxyluciferin + Light The technology is frequently referred to as reporter technology. It is versatile and provides a sensitive, nondestructive real-time measurement, based on the ability of the organism to emit light, which is dependent on the reducing power of the organism. Hence, only metabolically active cells can produce light. The direct relationship between viability and light emission allows the use of bioluminescent
Figure 5. Dunce cap or helmet jelly (Periphylla periphylla). [Copyright Edie Widder HBOI].
7
bacteria to assess the effect of various chemical, biological, and physical signals.
2.4
Electrochemistry – Entering the Commercial Stage
Electrochemical methodologies were also far from ignored during the early days of the 1970s. It was in this period that the first immunosensor was reported, which was based on amperometric detection.48 This concept of building direct immunosensors by fixing antibodies to electrodes was expanded using piezoelectric and potentiometric transducers. The binding of an antigen to an antibody often results in relatively small physicochemical changes, which makes the event difficult to detect. Over the years, many types of labels have been used to amplify the effect, often through an auxillary reaction. Two common examples are fluorescent labels and enzymes. The latter reacts with a chromogenic or electrochemically reactive material to produce a chemical signal that can be detected at a suitable transducer. However, it was a paper by Liedberg et al. in 1983 that was to pave the way for commercial success for devices of the direct immunosensor.49 They described the use of SPR to monitor affinity reactions in real time. The BIAcore instrument (Pharmacia, Sweden), originally launched in 1990, is based on this technology. In 1976, Clemens et al. incorporated an electrochemical glucose biosensor in a bedside artificial pancreas50 and this was later marketed by Miles (Elkhart) as the Biostator. The invasive sensor was revolutionary in that it enabled the fluctuations of blood glucose to be followed in real time and was the forerunner of recent commercial introductions of Continuous Glucose Monitoring Systems (CGMS). Although the Biostator is no longer commercially available, a new semicontinuous catheter-based blood glucose analyzer was introduced by VIA Medical (San Diego) in the 1990s. The 1980s saw a great deal of research into amperometric enzyme electrodes, which led to some important leaps forward. One of the drawbacks of the early Clark-type biosensor designs was their somewhat cumbersome (and costly) construction. Part of this problem was connected with the need to immobilize the enzyme and eliminate
8
BIOSENSOR AND BIOCHIP TECHNOLOGIES
interferences. The other issue was the difficulty in automating the manufacture of the conventional types of electrochemical cells used until then. Many of the early biosensors used oxidase enzymes that catalyzed the production of hydrogen peroxide. One method of simplification was proposed by Gorton in 1985, which involved the use of electrode materials that lower the required applied voltage for hydrogen peroxide detection.51 The rates of many electrochemical reactions can be tremendously enhanced by the deposition of very small particles of metals or metal oxides on the surface of the electrode. The highly catalytic nature of these surfaces is strongly dependent on the particle size of the deposited metals, which should be comparable to that of the electrical double layer. When deposited on carbon electrodes, for example, the difference in the electronic work functions of the metal and the carbon result in an increase in the electron density on the metal, resulting in an electrocatalytic surface. The most commonly used metals for deposition onto electrodes and in biosensors are platinum and rhodium. Incorporation of the metal into the carbon matrix can be achieved by: • electrochemical deposition, • sputtering, and • straightforward mixing of the metal into a carbon paste. The ability of these materials to reduce the oxidation potential of hydrogen peroxide is very attractive. In addition, the amperometric signal is greatly enhanced, producing a high signal-tonoise ratio. There is, however, a drawback. The electrocatalytic behavior is not very selective, resulting in lowered oxidation potentials for many other potentially interfering compounds, including reducing sugars, paracetamols (acetaminofen), and uric acid, which may be present in significant concentrations in blood. To overcome this problem, selectivity may be enhanced in much the same way as for the earlier, YSI-type biosensors. Membranes, typically constructed from polymers such as cellulose acetate, polyurethane, Nafion, and many others, can be applied to the electrode surface to exclude interferences by size or charge exclusion.52 On first sight, this may appear to offer no advantage over
the previous type of biosensor, but the material costs are much lower, and the resultant device is amenable to mass production, using techniques such as screen-printing. Such devices can be produced in large numbers and can be inexpensive enough to be disposable, if required. Reuse of the devices, however, is possible and biosensors based on such principles have been used in applications where they have made over 1000 measurements over a 7-day period.53 Direct electron transfer from the enzyme to the electrode would greatly enhance performance, potentially greatly reducing interference and the need for cofactors. However, for the vast majority of enzymes, direct electron transfer is not straightforward. This difficulty may be due to the location of the electroactive center of the enzyme, which is often deep within its structure, or it may be due to electrode surface effects connected with immobilization and orientation of the macromolecule. Although very specific with regard to the reducing substrate, enzymes such as GOx show a high degree of flexibility with regard to the second substrate, that is the electron acceptor. Thus, many inorganic redox couples and organic dyes have been successfully utilized as electron sinks for the GOx-catalyzed oxidation of glucose. Although it was not a commercial success at the time, the launch, in 1976, of the Lactate Analyzer LA 640 by La Roche (Switzerland), was an important step forward. The device incorporated the soluble electron transfer compound, potassium hexacyanoferrate, which was used to shuttle electrons from lactate dehydrogenase to an electrode. This turned out in retrospect to be an important forerunner of a new generation of mediated biosensors and of lactate analyzers for sports and clinical applications. In the early 1980s, it was realized that this method of operation facilitated the transfer of electrons in enzyme electrodes which was independent of the local oxygen concentration and allowed operation at much lower potentials, eliminating many of the problems associated with interference noted with the previously discussed devices. A group of workers based at Cranfield and Oxford universities, while working on a fuel-cell project, realized that the electron transfer compounds, which they were using to increase the efficiency of their fuel cells, held a great deal of promise in biosensor applications.54 These redox couples, known as mediators, are able to shuttle
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
Product
Enzyme [ox]
Enzyme [red]
Mediator [red]
Mediator [ox]
Electrode
Substrate
9
e−
Mediated enzyme
Figure 6. Mediated biosensor schematic.
electrons between the redox center of the enzyme and the electrode. Depending on the compound used, they can also be regenerated at potentials where interference from species such as ascorbate, urate, and paracetamol is minimal. The principle of operation is shown in Figure 6. A vast number of compounds are capable of acting as enzyme mediators, and the groups which are most frequently used in the construction of enzyme electrodes, are detailed below (Table 3). Of these, mediators based on metal complexes are the most popular. Arguably the most important examples of this class are those based on ferrocene and its derivatives. This can be attributed to three main factors: they have a wide range of redox potentials; the redox potentials are independent of pH; and the synthetic schemes involved in making derivatives are usually straightforward. In order to ensure the electron transfer, the mediator must be present in both its oxidized and Table 3. Electrochemical mediators commonly used in enzyme electrodes
Mediator Ferrocene 1,1-dicarboxylic acid Ferrocene+/0 Potassium ferricyanide/ferrocyanide 1,4-Benzoquinone/hydroquinone Phenazine methosulfate
E 0 (V) 0.64 0.44 0.36 0.28 0.08
Formal potentials (E 0 ) are quoted versus normal hydrogen electrode (NHE), at pH 7.0 and standard conditions.
reduced forms, which must remain in the vicinity of the electrode. In some formats, this means that the mediator must be insoluble, but in certain designs, it is possible to use one that is soluble. The mediator should also have a rate constant for the reaction with GOx that is sufficiently competitive with the natural mediator, oxygen. In many cases, especially for the measurement of blood glucose, it is acceptable to use a biosensor design, which is suitable only for a single measurement. This is convenient from the point of view of using a mediated biosensor format, since one of the major drawbacks of most mediators is that they are relatively soluble, leading to short operational lifetimes and irreproducible results. This is even true of one of the most popular mediators, ferrocene (and its derivatives), which despite being relatively insoluble in its oxidized form, becomes quite soluble when reduced to the ferricinium ion. A crucial manufacturing breakthrough, based on the use of screen-printing (Figure 7) led to the successful construction of inexpensive enzyme electrodes, based on the above mediated-sensor concepts.55 The first products were launched, in 1987, by MediSense (Cambridge, USA), as a pen-sized meter for home blood glucose monitoring. The electronics were redesigned into popular credit-card and computer-mouse style formats and the sensor designs have evolved, but the basic concepts have remained largely unchanged. Abbott, Boehringer Mannheim (now Roche Diagnostics), Bayer, and LifeScan now all offer competing
10
BIOSENSOR AND BIOCHIP TECHNOLOGIES
and Drug Administration (FDA) clearance for its product, which restricted access of the information obtained, to the physician, but access by the patient is now allowed. The latest device is designed to communicate directly with an implantable pump, with the eventual goal of “closed-loop” control using continuous glucose information to automatically regulate insulin delivery. Other manufacturers are following this lead with devices either on the market or announced.
3.1
Figure 7. Laboratory-scale screen-printer.
mediated biosensors and the combined sales of the four companies dominate the world market, through blood glucose monitoring.
3 MODERN IN VIVO DEVICES
The “holy grail” in terms of diabetes treatment is the successful introduction of an artificial pancreas. In order to facilitate continuous subcutaneous insulin infusion, with a portable and stable delivery system, it is necessary to undertake frequent or preferably continuous glucose measurements. An implantable glucose measurement system is seen as a key component of such a closed-loop glycemic control system. Such sensors can be broadly classified into intravenous and subcutaneous categories. A major potential advance in the in vivo application of glucose biosensors was reported by Shichiri et al., who described the first needle-type enzyme electrode for subcutaneous implantation in 1982.56 This can be considered a forerunner of the MiniMed (Sylmar CA, USA) GCMS. Human testing of this sensor (Figure 8), began in 2000, leading to its successful launch, for physicians’ use only, in 2002 and for general use in 2004. MiniMed originally obtained limited Food
Minimally Invasive Systems
In an attempt to minimize the discomfort caused by regular fingerpricking, as encountered with many blood analysis biosensors, and to overcome the significant problems inherent in the introduction of in vivo devices, some workers have looked at ways of measurement which are minimally invasive. Most efforts have targeted methods of drawing fluid through the skin without conventional puncture. Early work involved abrasion of the skin, but a more sophisticated approach was adopted in the mid-1990s, which was based on electroosmosis and electrochemical measurement of interstitial fluid.57 The resultant device was named the GlucoWatch, and was produced by Cygnus Inc. (Redwood City CA, USA). It is a wrist-worn device intended for detecting trends and tracking patterns in glucose levels in adults with diabetes. The device was intended for use at home and
Figure 8. MiniMed implantable glucose sensor.
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
in healthcare facilities to supplement, not replace, information obtained from standard home blood glucose monitoring devices. The attractive feature of the device was the frequency of the automatic and noninvasive measurements, which offered the potential to provide previously unavailable information about blood glucose, including automatic and frequent measurements and alerts for high and low glucose levels. Following a 3-h warm-up period, the device was designed to provide up to three glucose readings per hour for 12 h after a single point calibration, with the results from a standard finger-stick meter. The GlucoWatch biographer uses reverse iontophoresis to collect glucose samples through intact skin (Figure 9). The glucose molecules are collected in gel collection discs that are part of a single-use AutoSensor. The gel collection discs contains GOx. As glucose enters the discs, it reacts with the GOx in the gel to form hydrogen peroxide. A biosensor in contact with each gel collection disc detects the hydrogen peroxide, generating an electronic signal. The biographer uses the calibration value previously entered by the patient to convert the signal into a glucose measurement. The glucose measurement is then displayed on the biographer and
− −
−
−
−
− −
−
g
−
+ g g + + g + g + + g+ g g + g
= Glucose molecules − = Negative ion + = Positive ion
Figure 9. GlucoWatch operating principle.
11
stored in its memory. In 2001, the GlucoWatch biographer received approval from the US FDA. There are questions about the reliability of the device and also the degree of discomfort, which can be high for some patients, but at the time of writing, the biographer is still being supported following the purchase of Cygnus by Animas Corporation (West Chester, PA, USA) and its subsequent purchase by Johnson & Johnson.
3.2
Electrical Wires
Redox enzymes in biosensors usually lack direct electrical contact with electrodes, due to the spatial separation of their redox centers from the conductive surfaces by the protein shells. An elegant solution is to seek connection of the redox center to an electrode via a so called “molecular wire”. This approach was pioneered in the early 1990s by Heller and his coworkers.58 Novel heteroarene oligomers, consisting of two pyridinium groups, linked by thiophene units of variable length (thienoviologens) are promising candidates for such conducting molecular wires and may be used in conjunction with self-assembly techniques to produce an insulated electrode which transfer electrons specifically along predetermined molecular paths. An approach of this type forms the basis of the recent and commercially successful biosensors produced by TheraSense (Alameda CA, USA), which is now part of Abbott. The great advantage of the efficient wiring of the enzyme is that it makes glucose sensing unaffected by oxygen fluctuations and minimizes the effect of other interferents.
3.3
Nonaqueous Measurements
Enzyme activity in organic solvents was studied extensively in the 1980s, not least by Klibanov and coworkers.59 This interesting work meant that biosensor applications soon followed, using electrochemical transducers to perform analysis in organic solvents.60 The resulting devices were popularly termed organic-phase enzyme electrodes (OPEEs). Advances have not been limited to the liquid phase. Gas-phase biosensors for formic acid61 have been reported, with a detection limit of less than 1 mg m−3 and a response time of 4 min.
12
3.4
BIOSENSOR AND BIOCHIP TECHNOLOGIES
Decentralized Testing
A revolution in patient care was initiated in the 1980s, when liver and heart transplant centers, as well as operating rooms and other critical care areas first implemented whole-blood analysis to provide rapid test results in 2–5 min. This initiated a trend toward decentralized testing and provided numerous opportunities for biosensors. The rapid response of biosensors, coupled with improved real-world reliability, meant that patient outcomes could be significantly improved. The i-STAT instrument (now owned by Abbott Laboratories) was developed in the early 1990s and launched successfully in 1992. Originally measuring electrolytes, glucose, urea, nitrogen, and hematocrit,62 the device was a significant departure from the single analyte biosensors that had been produced for these types of application and provided an attractive alternative to centralized multianalyte analyzers. It was also the first siliconbased biosensor to find commercial success.
3.5
DNA Bioarrays
Ever since Watson and Crick established the double helical structure of DNA in 1953,63 nucleic acid research has become one of the most important fields in science. For the past 25 years, DNA hybridization has been used as a standard technique to detect specific DNA or RNA sequences. A single-stranded DNA molecule with a known sequence is labeled with a radioactive isotope or fluorescent dye and then used as a “probe” to detect a fragment of DNA or messenger RNA (mRNA, the molecule that is produced when a gene is turned on or “expressed”) with the complementary sequence. Early biosensors for DNA analysis focused on detection of a single sequence.64 Electrochemical, optical (particularly SPR), and piezoelectric devices of this type were all studied extensively in the early 1990s following the first description of a DNA biosensor by Fawcett65 in 1988. However, it was the ability to construct DNA microarrays that led to a huge growth in interest and activity in this area. A DNA microarray is a collection of microscopic DNA spots, commonly representing single genes, positioned in an array, on a solid surface.
Qualitative and quantitative measurements with DNA microarrays utilize the selective nature of DNA–DNA or DNA–RNA hybridization often using fluorophore-based detection. DNA arrays were first used for expression profiling in 1995 by Schena et al.66 mRNA or gene expression profiling examines expression levels for thousands of genes simultaneously and has many applications in biology and medicine, such as identifying disease genes by comparing gene expression in diseased and normal cells. In addition to expression profiling, applications of these arrays has broadened, to include comparative genomic hybridization67 (assessing large genomic rearrangements); single-nucleotide polymorphism (SNP) detection arrays68 (looking for SNP in the genome of populations); and chromatin immunoprecipitation studies69 (determining protein binding site occupancy throughout the genome). More recent examples of DNA microarray biosensors include optical and electrochemical approaches. Fiber-optic DNA microarrays were produced from etched optical fiber bundles,70 filled with oligonucleotide-functionalized microspheres. This bundle comprises thousands of individually addressable fibers, which enabled massive parallel detection capabilities. Specific hybridization was detected by fluorescence, only at the probe positions complementary to the targets. Impedance measurement was used by Jacobs et al. in disposable biochips for low-cost DNA analysis.71 The chip featured 128 sensors, each of which contained a 200 × 200 µm array of interdigitated electrodes (Figure 10). In order to produce arrays of sensors, reagents need to be handled and deposited onto the correct part of the array. For large arrays, this means that many different liquids need to be deposited at high speed. This is not simple to do in a reliable way. There are many ways of tackling this problem and many companies have become involved in producing deposition equipment.
3.6
Biomimicry
The popularity of biomimics, which use synthetic receptors derived from, or modeled on biological materials, has gained momentum over the last decade. Combinatorial chemistry was used
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
Figure 10. Disposable DNA biochip.
to synthesize peptide libraries, which could be screened for appropriate affinity ligands.72 This period has seen advances in computational techniques, which facilitate improved modeling of both electron transfer reactions and receptor binding interactions. This not only enhances understanding of the receptor/transducer interface, but also allows consideration of the design of new receptors based on biological molecules.73 Molecular imprinted polymers (MIPs) are based on the concept of substituting relatively unstable antibodies, receptors, and enzymes, with their stable synthetic mimics, which is very appealing.74 Using a process based on modeling of complex formation between template and functional monomers, it is possible to produce polymers with enhanced and predictable properties.75 The computational approach permits the following: • selection of the best monomers for polymer formation, possessing high affinity for the template; • mimicry of the specific polymerization or binding conditions by changing the dielectric constant and atomic charges of the monomer/template models; and • prediction of the relative polymer specificity and affinity.
3.7
Competing with Dipstick Technology
One of the drawbacks of biosensors compared with other diagnostic techniques is, very often, the need
13
for relatively expensive instrumentation. This is particularly true when they are compared with the various dipstick technologies, which rely on color changes or the appearance of bands, indicating the presence or absence of a particular material. It is often true that such devices are either not quantitative, or only semiquantitative, but the cost differential between them and the biosensors can be prohibitive. Holographic biosensors76 have been developed at the Institute of Biotechnology (University of Cambridge, UK). These “smart holograms” do not need an electronic instrument, as they are a virtual instrument. Holographic sensors are test strips, which provide a changing optical image (color, alphanumerics, messages) as the test result. A reflection hologram provides an image when it is illuminated by white light. The image is stored in a thin polymer film using patented photosensitizing technology. The polymer film is also chemically sensitized to react with a substance in, for example, a sample of bodily fluid. During the test, the target substance reacts with the polymer leading to an alteration in the image displayed by the hologram as shown in Figure 11.
4 CONCLUSION
Combining synthetic receptor properties with noninstrumental transducers could be an exciting way forward provided current design limitations can be overcome. There are also concepts that reduce this to the molecular level so that the sensing molecule delivers a signal directly in the form of, for example, fluorescence. Taking this extrapolation still further, sensing and actuation can be combined so that a material is capable of responding to, for example, a specific pathophysiological condition with the release of a therapeutic. This molecular device may even be delivered to a specific tissue by way of an affinity reaction. All this, however, strays beyond the brief of this contribution to deliver a historical perspective and looks toward
Positive
Figure 11. Holographic sensor display.
Negative
14
BIOSENSOR AND BIOCHIP TECHNOLOGIES
a future heavily influenced by nanotechnology. Today we can say that biosensors have emerged from obscurity to realize many of the visions of their founders. The industry is now equivalent in size to that of a fair-sized consumer product and shows no sign of reduced growth or diversity. The biosensor concept may change in name or embodiment in the future, but it has already established its place in scientific history.
REFERENCES 1. J. D. Newman, L. J. Tigwell, A. P. F. Turner, and P. J. Warner, Biosensors: A Clearer View. Cranfield University, 2004, 216. 2. A. P. F. Turner, J. D. Newman, L. J. Tigwell, and P. J. Warner, Biosensors: A Global View, In: Proceedings of the 9th World Congress on Biosensors, Toronto, Canada, 2006. 3. L. C. Clark Jr, Monitor and control of blood and tissue oxygen tensions. Transactions American Society for Artificial Internal Organs, 1956, 2, 41–48. 4. L. C. Clark Jr and C. Lyons, Electrode systems for continuous monitoring in cardiovascular surgery. Annals of the New York Academy of Sciences, 1962, 102, 29–45. 5. S. J. Updike and J. P. Hicks, The enzyme electrode. Nature, 1967, 214, 986–988. 6. G. G. Guilbault and G. J. Lubrano, Amperometric enzyme electrodes part II: amino-acid oxidase. Analytica Chimica Acta, 1974, 69(1), 183–188. 7. G. G. Guilbault and G. J. Lubrano, Amperometric enzyme electrodes part III: alcohol oxidase. Analytica Chimica Acta, 1974, 69(1), 189–194. 8. D. L. Williams, A. R. Doig, and A. Korosi, Electrochemical-enzymatic analysis of blood glucose and lactate. Analytical Chemistry, 1970, 42(1), 118–121. 9. J. D. Newman, S. F. White, I. E. Tothill, and A. P. F. Turner, Catalytic materials, membranes and fabrication processes suitable for the construction of amperometric biosensors. Analytical Chemistry, 1995, 67, 4594–4599. 10. L. C. Clark, Guest editorial—how the first enzyme electrode was invented. Biosensors and Bioelectronics, 1993, 8(1), 3–7. 11. G. G. Guilbault and J. Montalvo, A urea specific enzyme electrode. Journal of the American Chemical Society, 1969, 91, 2164–2569. 12. M. M. Yanina, V. I. Sorochinskii, B. I. Kurganov, and R. S. Balugyan, Urease pH electrode. Journal of the Analytical Chemistry of the USSR, 1987, 42(8), 1208–1213. 13. S. Arisawa and R. Yamamoto, Quantitative characterization of enzymes adsorbed on to Langmuir-Blodgett-films and the application to a urea sensor. Thin Solid Films, 1992, 210(1–2), 443–445. 14. P. Bergveld, Development of an ion-sensitive solidstate device for neurophysiological measurements. IEEE Transactions on Biomedical Engineering, 1970, BM17(1), 70–77.
15. P. Bergveld, Thirty years of ISFETOLOGY—what happened in the past 30 years and what may happen in the next 30 years. Sensors and Actuators B-Chemical, 2003, 88(1), 1–20. 16. X. L. Luo, J. J. Xu, and H. Y. Chen, Biosensors based on field-effect transistors. Chinese Journal of Analytical Chemistry, 2004, 32(10), 1395–1400. 17. J. D. Newman, Self-testing of blood glucose: biosensors and beyond. Medical Device Technology, 2002, 12–15. 18. E. C. Alocilja and S. M. Radke, Market analysis of biosensors for food safety. Biosensors and Bioelectronics, 2003, 18(5), 841–846. 19. S. L. Brooks, I. J. Higgins, J. D. Newman, and A. P. F. Turner, Biosensors for process control. Enzyme and Microbial Technology, 1991, 13, 946–955. 20. U. Bilitewski and A. P. F. Turner, Biosensors for Environmental Monitoring, Harwood Academic Publishers, Amsterdam, 2000, p. 409. 21. S. S. Iqbal, M. W. Mayo, J. G. Bruno, B. V. Bronk, C. A. Batt, and J. P. Chambers, A review of molecular recognition technologies for detection of biological threat agents. Biosensors and Bioelectronics, 2000, 15(11), 549–578. 22. A. J. Cunningham, Appendix A-1, A-2, B , in Introduction to Bioanalytical Sensors, John Wiley & Sons, New York, 1998, pp. 319–338. 23. C. L. Cooney J. C. Weaver, S. R. Tannebaum, S. R. Faller, D. V. Shields, and M. Jahnke, The Thermal Enzyme Probe—A Novel Approach to Chemical Analysis, in Enzyme Engineering, E. K. Pye and L. B. Wingard Jr (eds), Plenum Publishing Corporation, New York, 1974, Vol. 2, pp. 411–417. 24. K. Mosbach and B. Danielsson, An enzyme thermistor. Biochimica et Biophysica Acta, 1974, 364, 140–145. 25. B. Xie, B. Danielsson, P. Norberg, F. Winquist, and I. Lundstr¨om, Development on a micro-thermal biosensor fabricated on a silicon chip. Sensors and Actuators, B, 1992, 6, 127–130. 26. B. Xie, U. Hedberg, M. Mecklenburg, and B. Danielsson, Fast determination of whole-blood glucose with a calorimetric micro-biosensor. Sensors and Actuators B-Chemical, 1993, 15(1–3), 141–144. 27. B. Mattiasson, C. Borrebaeck, B. Sanfridsson, and K. Mosbach, Thermometric enzyme-linked immunosorbent assay: TELISA. Biochimica et Biophysica Acta, 1977, 483, 221–227. 28. B. Mattiasson, B. Danielsson, C. Hermansson, and K. Mosbach, Enzyme thermistor analysis of heavy-metal with use of immobilized urease. FEBS Letters, 1978, 85(2), 203–206. 29. G. G. Guilbault, M. H. Sadar, S. Kuan, and D. Casey, Effect of pesticides on liver cholinesterases from rabbit, pigeon, chicken, sheep and pig. Analytica Chimica Acta, 1970, 51(1), 83–93. 30. P. Skladal, M. Fiala, and J. Krejci, Detection of pesticides in the environment using biosensors based on cholinesterases. International Journal of Environmental Analytical Chemistry, 1996, 65(1–4), 139–148. 31. D. W. Lubbers and N. Opitz, The pCO2 − /pO2 —optode. New probe for the measurement of the partial pressure of carbon dioxide or the partial pressure of oxygen in fluids
HISTORY OF BIOSENSOR AND BIOCHIP DEVELOPMENT
32.
33.
34. 35.
36.
37.
38.
39. 40.
41.
42.
43.
44.
45.
46.
47.
48. 49.
50.
and gases. Zeitschrift Fur Naturforschung C-A Journal of Biosciences, 1975, 30c, 532–533. R. Koncki, T. Lenarczuk, A. Radomska, and S. Glab, Optical biosensors based on Prussian blue films. The Analyst, 2001, 126(7), 1080–1085. S. de Marcos, J. Galindo, J. F. Sierra, J. Galban, and J. R. Castillo, An optical glucose biosensor based on derived glucose oxidase immobilised onto a sol-gel matrix. Sensors and Actuators B-Chemical, 1999, 57(1–3), 227–232. T. E. Hirschfeld, Total reflection fluorescence. Canadian Journal of Spectroscopy, 1965, 10, 128. A. J. Braundme and E. T. Arakawa, Effect of surface roughness on surface plasmon resonance—absorption. Journal of Physics and Chemistry of Solids, 1974, 35(4), 517–520. B. Liedberg, C. Nylander, and I. Lundstrom, Surface plasmon resonance for gas-detection and biosensing. Sensors and Actuators, 1983, 4(2), 299–304. M. N. Kronick and W. A. Little, New immunoassay based on fluorescence excitation by internal-reflection spectroscopy. Journal of Immunological Methods, 1975, 8, 235–240. C. R. Taitt, G. P. Anderson, and F. S. Ligler, Evanescent wave fluorescence biosensors. Biosensors and Bioelectronics, 2005, 20(12), 2470–2487. A. Brecht and G. Gauglitz, Optical probes and transducers. Biosensors and Bioelectronics, 1995, 10(9–10), 923–936. A. Lopezrom and G. G. Guilbault, Use of piezoelectric crystals as sensitive and specific detectors for SO2 . Analytical Letters, 1972, 5(4), 254. A. Shons, F. Dorman, and J. Najarian, The piezoelectric quartz immunosensor. Journal of Biomedical Materials Research, 1972, 6, 565–570. N. C. Fawcett, J. A. Evans, L. C. Chen, K. A. Drozda, and N. Flowers, A quartz crystal detector for DNA. Analytical Letters, 1988, 21, 1099–1110. C. Divi`es, Remarques sur l’oxydation de l’ethanol par une “electrode microbienne” d’acetobacter xylinum. Annals of Microbiology, 1975, 126A, 175–186. T. L. Shaw, A fast indicator for detecting gross pollution by hazardous chemicals. New Zealand Journal of Marine and Freshwater Research, 1979, 13(3), 393–394. P. Pandard, P. Vasseur, and D. M. Rawson, Comparison of 2 types of sensors using eukaryotic algae to monitor pollution of aquatic systems. Water Research, 1993, 27(3), 427–431. I. Karube, T. Matsunaga, and S. Suzuki, A new microbial electrode for BOD estimation. Journal of Solid Phase Biochemistry, 1977, 2(2), 97–104. W. D. McElroy and A. A. Green, Enzymatic properties of bacterial luciferase. Archives of Biochemistry and Biophysics, 1955, 56, 240–255. J. Janata, Immunoelectrode. Journal of the American Chemical Society, 1975, 97(10), 2914–2916. B. Liedberg, C. Nylander, and I. Lundstrom, Surface plasmon resonance for gas detection and biosensing. Sensors and Actuators, 1983, 4, 299–304. A. H. Clemens, P. H. Chang, and R. W. Myers, Le d´eveloppement d’un syst´eme automatique d’infusion d’insuline control´e par la glyc´emie, son syst´eme de dosage du glucose et ses algorithmes de control. Proceedings
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63. 64.
65.
66.
15
of the Journal Annuale de Diabetologie de l’Hotel-Dieux, 1976, 269–278. L. Gorton, A carbon electrode sputtered with palladium and gold for the amperometric detection of hydrogen peroxide. Analytica Chimica Acta, 1985, 178, 247–253. J. D. Newman, S. F. White, I. E. Tothill, and A. P. F. Turner, Catalytic materials, membranes and fabrication technologies, suitable for the construction of amperometric biosensors. Analytical Chemistry, 1995, 67, 4594–4599. I. E. Tothill, J. D. Newman, S. F. White, and A. P. F. Turner, Monitoring of the glucose concentration during microbial fermentation using a novel mass-producible biosensor suitable for on-line use. Enzyme and Microbial Technology, 1997, 20, 590–596. A. E. G. Cass, G. Davis, G. D. Francis, H. A. O. Hill, W. J. Aston, I. J. Higgins, E. V. Plotkin, L. D. L. Scott, and A. P. F. Turner, Ferrocene-mediated enzyme electrode for amperometric determination of glucose. Analytical Chemistry, 1984, 56, 667–671. J. D. Newman, L. J. Tigwell, P. J. Warner, and A. P. F. Turner, Biosensors: boldly going into the new millennium. Sensor Review, 2001, 21(4), 268–271. M. Shichiri, R. Kawamori, R. Yamaski, Y. Hakai, and H. Abe, Wearable artificial endocrine pancreas with needle-type glucose biosensor. Lancet, 1982, 2, 1129–1131. G. Rao, R. H. Guy, P. Glikfeld, P. W. R. LaCourse, L. Leung, J. Tamada, R. O. Potts, and N. Azimi, Reverse iontophoresis: noninvasive glucose monitoring in vivo in humans. Pharmaceutical Research, 1995, 12, 1322–1326. A. Heller, B. A. Gregg, M. V. Pishko, and A. Michael, Amperometric glucose sensors based on electrically wired enzymes. Journal of the American Chemical Society, 1991, 201, 16–ANYLPart1 (abstr). A. M. Klibanov, Enzymatic catalysis in anhydrous organic solvents. Trends in Biochemical Sciences, 1989, 14, 141–144. G. F. Hall, D. J. Best, and A. P. F. Turner, Amperometric enzyme electrode for the determination of phenols in chloroform. Enzyme and Microbial Technology, 1988, 10, 543–546. K. J. M. Sandstrom, J. D. Newman, A.-L. Sunesson, J.O. Levin, and A. P. F. Turner, Amperometric biosensor for formic acid in air. Sensors and Actuators, B, 2000, 70, 182–187. P. Wilding and K. A. Erikson, Evaluation of a handheld micro-fabricated sensor system, the I-Stat 100, for rapid assay of electrolytes, glucose, urea nitrogen and hematocrit. Clinical Chemistry, 1990, 36(6), 1206. J. D. Watson and F. H. C. Crick, A structure for deoxyribose nucleic acid. Nature, 1953, 171, 737–738. M. E. A. Downs, S. Kobayashi, and I. Karube, New DNA technology and the DNA biosensor. Analytical Letters, 1987, 20(12), 1897–1927. N. C. Fawcett, J. A. Evans, L. C. Chien, and N. Flowers, Nucleic acid hybridization detected by piezoelectric resonance. Analytical Letters, 1988, 21, 1099–1114. M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270(5235), 467–470.
16
BIOSENSOR AND BIOCHIP TECHNOLOGIES
67. H. Bornfleth, K. Aldinger, M. Hausmann, A. Jauch, and C. Cremer, Comparative genomic hybridization imaging by the one-chip true-color CCD camera Kappa CF 15 MC. Cytometry, 1996, 24(1), 1–13. 68. R. J. Sapolsky, L. Hsie, A. Berno, G. Ghandour, M. Mittman, and J.-B. Fan, High-throughput polymorphism screening and genotyping with high-density oligonucleotide arrays. Genetic Analysis-Biomolecular Engineering, 1999, 14(5–6), 187–192. 69. A. W. I. Lo, D. J. Magliano, M. C. Sibson, P. Kalitsis, J. M. Craig, and K. H. A. Choo, A novel chromatin immunoprecipitation and array (CIA) analysis identifies a 460-kb CENP-A-binding neocentromere DNA. Genome Research, 2001, 11(3), 448–457. 70. K. L. Michael, L. C. Taylor, S. L. Schultz, and D. R. Walt, Randomly ordered addressable high-density optical sensor arrays. Analytical Chemistry, 1998, 70(7), 1242–1248. 71. P. Jacobs, W. Hofer, R. Rossau, W. Tachelet, A. Campitelli, P. DeTemple, J. D. Newman, C. Flack, and A. Van de Koorde, Novel Fabrication Technique for
72.
73.
74. 75.
76.
the Development of Polymer-Based Microsensor Arrays for Molecular Diagnostics, In: Proceedings of the SPIE 2000 Symposium on Smart Materials and MEMS , Melbourne, Australia, December 13–15, Vol. 4235, 15. B. Chen, G. Bestetti, R. M. Day, and A. P. F. Turner, The synthesis and screening of a combinatorial peptide library for affinity ligands for glycosylated haemoglobin. Biosensors and Bioelectronics, 1998, 13, 779–785. S. Piletsky and A. P. F. Turner, Molecular Imprinting of Polymers, Landes Bioscience, Georgetown, 2006, ISBN 1 58706 2194. A. P. F. Turner, Biosensors—sense and sensitivity. Science, 2000, 290(5495), 1315–1317. I. Chianella, M. Lotierzo, S. A. Piletsky, I. E. Tothill, B. N. Chen, K. Karim, and A. P. F. Turner, Rational design of a polymer specific for microcystin-LR using a computational approach. Analytical Chemistry, 2002, 74(6), 1288–1293. R. B. Millington, A. G. Mayes, J. Blyth, and C. R. Lowe, A hologram biosensor for proteases. Sensors and Actuators B-Chemical, 1996, 33(1–3), 55–59.
4 Protein Recognition in Biology Paula McCourt, Joseph Nickels, Tetsuya Ishino and Irwin Chaiken Department of Biochemistry and Molecular Biology, Drexel University College of Medicine, Philadelphia, PA, USA
1 THE CHALLENGE AND THE OPPORTUNITY FOR SENSING PROTEINS INTERACTIONS IN SOLUTION AND IN CELLS
As described elsewhere in this volume, biochips and biosensors have evolved into a powerful set of technologies for measuring proteins and their interactions. Indeed, as more has been learned about interaction partners of biologically important proteins, the molecular components of interaction have been valuable tools to probe the protein landscape of living systems. Can the continued evolution of these technologies define the interaction landscapes as they occur at the complexity of machines and networks on and in cells? Attempting to reveal the signatures and quantitative properties of protein interactions ultimately will require technologies that can provide temporal resolution down to seconds or perhaps lower timescales, spatial resolution down to nanometer or smaller distances and abundance levels of perhaps only a few molecules per cell. These present technological challenges for the biosensing field, and the opportunity to map and reveal increasingly high resolution understanding of interaction processes as they occur in living systems. It is not surprising from current studies in proteomics and interactomics that protein recognition is so pervasive and important. And, it is becoming increasingly appreciated that these interaction processes occur in a crowded and dynamic
environment in living systems. A main message we hope to convey in this chapter is that, in biology, it is machines and networks that ultimately convey how protein recognition drives health and disease. We hope that this message will provide a useful context for those members of the biosensor and biochip communities that are developing relevant technologies. 2 INTRODUCTION: MOLECULAR ORGANIZATION AND CELLULAR FUNCTION
Biological processes, and specifically cellular function, regulation, proliferation, and programmed death of cells, are driven by complex, dynamic, and ordered macromolecular arrays. An overarching goal of modern biology is to determine the spatial and temporal organization of the molecular building blocks that drive cellular processes. Proteins comprise the working machinery of a cell. Their functions are implicated in every facet of cell survival, as well as both self-induced and externally imposed pathogenic processes that can lead to cell death. The identification of all proteins is being driven by genomic and proteomic technologies, and structural mechanisms are being elucidated for an increasing subset of these biological macromolecules through structural and molecular biological approaches. What is increasingly clear from such discoveries is that a fundamental
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
mechanism of protein function in the cell is noncovalent recognition. Proteins use mainly a combination of electrostatic, hydrophobic, and other noncovalent interactions to specifically interact with each other and with other cellular components. Understanding the molecular organization of the proteins of cells and the structural mechanism of the protein assemblies, lies at the root of revealing underlying molecular mechanisms in health and disease pathogenesis and approaches to disease treatment. Within cells, protein interactions occur in a crowded environment filled with many other proteins, cytoskeleton, and organelles and, hence, are likely to lead to assemblies of molecular machines and networks to carry out their functions. As just one example, metabolic pathways such as those leading to oxidative phosphorylation and adenosine 5 -triphosphate (ATP) synthesis reflect the importance of large-scale molecular order in function and regulation.1 The pathways of pyruvate dehydrogenase (PDH), tricarboxylic acid cycle (TCA), electron transport chain (ETC), and ATP synthase are localized in the mitochondrial matrix and membrane surrounding the matrix, in linked reaction paths that lead to respiration and ATP production. Even a cursory glance at the interrelationships among the components of these reactions shows the overarching importance of machines and networks. PDH is a multiprotein complex with multiple copies of three different enzymes that are organized spatially to enable efficient utilization of catalytic as well as stoichiometric cofactors to produce acetyl CoA. This latter intermediate is utilized by the TCA cycle to produce electrons to drive the ETC. The TCA cycle itself is composed of nine enzymes working coordinately mainly in the matrix but almost certainly organized into at least a loose supramolecular assembly. One of the enzyme components of the TCA cycle, succinate dehydrogenase, is associated with the ETC, which itself is assembled as a set of complexes in the inner mitochondrial membrane that surrounds the matrix. The ETC pumps protons out of the matrix into the intermembrane space between the inner and outer mitochondrial membranes. The proton gradient thus produced drives ATP synthesis by proton pumping back into the matrix through the ATP synthase machine, a multiprotein, membrane-inserted assembly in which the ATP synthesizing subunits extend into the matrix where adenosine diphosphate (ADP) and inorganic phosphate are utilized.
The magnitude of protein machines and networks in the oxidative phosphorylation pathways likely is not unique in biology but more likely the rule. We know much about the metabolic machinery of oxidative phosphorylation, surely due at least in part to the overwhelming importance of the process for survival of life, and the ability to identify and study the individual components because of their unique enzymatic conversions. In this chapter, we will review some selected classes of other protein assemblies important to cell function, including those that are important for signaling and transcriptional regulation. We also will discuss how understanding recognition mechanisms can help reveal paths to treatments for disease. The latter can occur because of disruption of the regulation of normal cellular machines by externally imposed factors such as allergens or by mutation of the protein components. 3 INTRACELLULAR COMPLEXES OF TRANSCRIPTIONAL REGULATION: THE CASE OF STEROL TRANSCRIPTIONAL REGULATION IN MAMMALS
Sterols are essential lipids in all eukaryotes. They function in regulating membrane fluidity and raft formation.2,3 Cholesterol also has emerged as a critical second messenger involved in developmental signaling.4 On the other hand, a chronic increase in blood cholesterol levels in humans is implicated as a progenitor of heart disease and atherosclerosis.5,6 And in lower eukaryotes, loss of sterol biosynthesis following antifungal chemotherapy results in cessation of cell growth.7 Together, these observations underscore the need for sophisticated multitiered regulatory machineries, whose functions are to modulate sterol homeostasis in all eukaryotes. Their discovery and thorough biochemical and biophysical characterizations will provide great insight into the diverse ways eukaryotic cells maintain proper sterol levels. Moreover, an understanding of the regulation of sterol biosynthesis through these types of studies will provide novel methods in controlling human diseases, whose pathologies are caused by underlying defects in sterol metabolism, including atherosclerosis and cardiovascular disease,6,8 diabetes,9 Niemann Pick diseases,10 and cancer.11
PROTEIN RECOGNITION IN BIOLOGY
3
of LDL particles. Low cholesterol levels, in turn, coordinately induce transcription, causing an increase in de novo cholesterol biosynthesis and an increase in the cellular uptake of serum LDL particles. Mutational studies have defined a sterol response element-1 (SRE-1) within the promoters of these genes that is required for sterolmediated regulation of transcription.18–23 SRE-1 and its variants thus function as conditional positive elements necessary for activated transcription in sterol-deprived cells. The modulators of SRE-1 activity are the basic region helix-loop-helixleucine zipper (bHLH-ZIP) family of membrane-associated transcription factors called sterol regulatory element-binding proteins (SREBP s) (Figure 1).24–28 Mammals contain three different SREBPs that are produced from two separate genes.17 SREBP-1a and SREBP-1c are produced through alternative splicing of SREBP1 and differ in the length of a common acidic transactivation domain harboring potent transcriptional activation activity.29 SREBP-1c lacks 29 acidic amino acid residues within this domain, while containing 5 unique amino acids, and is a much weaker activator of gene expression than is SREBP-1a. SREBP-2 is the sole product of the
Furthermore, there has been an increased incidence in antifungal resistance in patients with compromised immune systems, such as those individuals with HIV and cancer, and in transplantation patients. The antifungal drugs given to these patients target the sterol pathway, but their efficacy is greatly reduced because these drugs merely inhibit microbial growth rather than kill them. Over time, long-term treatment actually results in resistance and is a major mortality factor.12–14 Understanding the interactions underlying how these molecular machines function to regulate the sterol pathway represents an opportunity to precisely target them as novel pharmacological sterol targets. A major pathway regulating cholesterol levels in mammals causes the transcriptional feedback regulation of specific genes involved in sterol homeostasis.15–17 Genes involved include HMGCoA synthase, HMG-CoA reductase, farnesyl diphosphate synthase, and squalene synthase, as well as the gene encoding the low-density lipoprotein (LDL) receptor involved in cholesterol uptake.18 High levels of cholesterol cause decreased transcription, resulting in reduced sterol biosynthesis and decreased uptake in the form S2P C WD
N
bHLH-ZIP
N
bHLH-ZIP
N
C
Golgi Lumen S1P
bHLH-ZIP
Low cholesterol
N
C
N
C WD C
N
SRE
bHLH-ZIP
N
Nucleus
ER Lumen Insig
SCAP
SREBP
Figure 1. The SRE/SREBP pathway in mammals. A schematic representation of SREBP translocation and activation in response to blocks in sterols. Translocation of SREBP (aqua) from the ER-to-Golgi is dependent on the functions of Insig (light blue) and the SCAP (dark blue/pink) sterol-sensing domain (pink). When sterol levels are low, SREPB is translocated to the Golgi, where S1P and S2P (red) proteolytically release the bHLH-ZIP domain of SREBP. This domain ultimately enters the nucleus and through its binding to various SREs regulates gene expression.
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
SREBP-2 gene. SREBPs act as dimers to regulate gene expression through dimerization of their bHLH-ZIP domains and bind DNA through their basic region.17 Regulated expression and ultimate changes in the relative levels of homo- versus heterodimers found in a cell may modulate transcriptional activity. To support this hypothesis, tethering experiments have shown that heterodimers containing SREBP-1c have reduced transcriptional activity.30 Interestingly, changes in the level of SREBP-1c are seen in response to insulin signaling and liver X receptor signaling and may represent a mode of regulating overall SREBP activity in a tissue-specific manner.31,32 Moreover, the molecular make-up of a particular SREBP dimer may regulate its cellular localization and thus transcriptional activity. Studies have shown that SREBP-1a homodomers localize diffusely within the nucleus, whereas SREBP-2 homodomers and a SREBP-1a-SREBP-2 heterodimer localize to promyelocytic leukemia (PML)-like bodies.33 PML bodies are present in all mammalian cells and are implicated in regulating transcription, apoptosis, DNA damage repair, and the antiviral response.34,35 There is further interaction between the small ubiquitin modifier-1 (SUMO1) and SREBP-2 within these PML-like bodies that may negatively regulate transcriptional activity through a mechanism that is independent of the ubiquitin-proteosome pathway.33 Thus, while SREBP inhabits the nucleus, several intra- and intermolecular recognition steps seem to be critically important for transcriptional regulation. When cholesterol levels are high, SREBPs localize in the endoplasmic reticulum (ER) through the presence of two membrane-spanning domains. As sterol levels become depleted, they are translocated to the Golgi, where proteolytic processing releases an amino-terminal fragment containing the transcriptionally active bHLH-ZIP domain. The Site-1 protease (S1P) and Site-2 protease (S2P) proteolytically process SREBPs.16 S1P is a membrane-associated serine protease belonging to the subtilisin family.36 Its activity first generates an intermediate membrane-bound aminoterminal fragment,37 and subsequent cleavage by the metalloprotease,38 S2P, releases the bHLH-ZIP domain.39 Importantly, sterol levels indirectly regulate Site-1-dependent proteolysis by regulating the association of SREBP with the membrane-
associated SREBP cleavage activating protein (SCAP). SCAP is required for SREBP translocation to the Golgi, which contains active S1P. SCAP is a 1276 amino acid membrane-bound protein. It contains a 730 amino acid amino-terminal domain containing eight membrane-spanning regions and a carboxy-terminal cytosolic domain that includes five copies of a WD repeat sequence (TrpAsp).15,16 SCAP binds to the carboxy-terminal domain of SREBP through these WD repeats. Within the eight membrane-spanning region of SCAP is a putative sterol-sensing domain that is critical for cholesterol-dependent response.40–43 It is common to several proteins, including HMGCoA reductase,44 the Niemann Pick type C (NPC) protein, Npc1,45 and the Drosophila signaling protein, patched.46 Several studies implicate cholesterol binding to the sterol-sensing domain as the trigger that causes an important conformational change to SCAP that subsequently mediates protein–protein interactions.47,48 Importantly, these changes in conformation result in SCAP binding to the ER membrane-associated proteins, Insig-1/Insig-2, ultimately inhibiting SCAP function.48,49 Thus, when cholesterol levels are high, the SCAP–Insig interaction prevents SCAP from translocating SREBP to the Golgi for proteolytic processing and translocation to the nucleus. Amino acid residues critical for this interaction have been mapped within SCAP, and a strong correlation exists between mutations in these residues and SREBP processing and subsequent transcriptional activity. Those that disrupt SCAP–Insig interaction cause constitutive proteolytic processing of SREBP, while those that enhance this interaction act as a dominant negative, as SREBP cannot translocate to the nucleus when cholesterol levels are depleted.40,48,50 Mutational analyses with Insigs have not been as extensive. However, Asp-205 within Insig-1 has been found to be critical for the SCAP–Insig1 interaction.51 Interestingly, Insig-1 is stabilized by its interaction with SCAP, as it is normally rapidly degraded by the proteasome.52 In addition to dissociating from Insig-1/2 when cholesterol levels are depleted, SCAP must also interact with the coat proteins, Sec23/24, to segregate SREBP into COPII-coated vesicles for translocation to the Golgi.53,54 A hexapeptide sequence, MELADL, within a cytoplasmic loop of SCAP is required for binding. Moreover, SCAP-Sec23/24 binding
PROTEIN RECOGNITION IN BIOLOGY
is dependent on the GTP-binding protein, Sar1.54 Sterols are selective in blocking incorporation of only SCAP/SREBP into these vesicles, as studies have shown that vesicular stomatitis virus glycoprotein incorporation into COPII vesicles still occurs under cholesterol conditions able to block SCAP/SREBP translocation.53 Once proteolytically released, the aminoterminal bHLH-ZIP SREBP fragment interacts with importin-β and enters the nucleus.55 Importin-β, along with importin-α, binds the nuclear pore complex and facilitates the import of proteins into the nucleus. Binding of SREBP with importin-β occurs through the direct interaction of the bHLH-ZIP domain. The crystal structure of importin-β complexed with SREBP-2 has been solved.56 It demonstrates that the SREBP-2 dimer directly interacts with characteristic multiple HEAT repeats57 within importin-β, and is stabilized by multiple hydrophobic interactions. Once in the nucleus, SREBPs bind to various variants of the SRE-1 promoter sequence (original SRE sequence, ATCACCCCAC), as well as classical palindromic E-boxes (CAXXTG).17 Interestingly, SREBPs contain an atypical Tyr320 residue rather than a conserved Arg residue found in all other known bHLH-ZIP domains.17 Conversion of this tyrosine to an arginine abolishes the ability of SREBP to bind SRE-1, but not various E-box sequences.58 Crystal structures of various bHLH-ZIP–DNA interactions have demonstrated that the conserved arginine makes contact with the DNA backbone and a conserved glutamic acid forming a tight bridgelike structure.59–61 Modeling predictions indicate that substitution of the tyrosine would disrupt this bridging, thereby possibly reducing nucleotide specificity for binding.58 The molecular interactions of the SRE/SREBP pathway underscore the absolute need for all “generic” signaling pathways to incorporate sophisticated protein–protein and protein-lipid recognition points to precisely fine tune activity. The loss of these putative “protein recognition checkpoints”, if you will, could result in activating or inhibiting the pathway to a degree that is highly deleterious to cell viability. We have reviewed several well-characterized recognition points, cholesterol binding to the SCAP “sterolsensing domain”, SREBP cleavage by S1P and
5
S2P, the SCAP–Insig interaction, and the interaction of the amino-terminal bHLH-ZIP SREBP fragment with importin-β and SRE-1. Many more as yet uncharacterized protein–protein interactions surely exist, as multiple-signaling pathways influence SREBP transcriptional activity.17,62–64 Clearly the SRE/SREBP pathway is regulated through the integration of multiple signals using various specific protein–protein interactions, all representing potential novel targets for pharmacological intervention.
4 MEMBRANE-ASSOCIATED COMPLEXES AND TRAFFICKING
Human amphiphysins, along with human BIN1, BIN2, and BIN3, the Schizosaccharomyces pombe hob1+ and hob3+ genes, the murine Alp1 and the Saccharomyces cerevisiae amphiphysin orthologs, RVS161 and RVS167, are all members of the BAR (Bin/Amphiphysin/Rvs) family of proteins.65,66 Initially, BAR family function was thought to be involved only in regulating early endocytosis and the actin cytoskeleton,67,68 but with the discovery of the amphiphysin II isoform, BIN1, functions have expanded to include signaling from the plasma membrane to the nucleus.69,70 In addition, it is now believed that BAR family proteins may function to regulate critical membrane topological/morphological changes. Work has demonstrated that Drosophila amphiphysin regulates the organization of specialized membrane domains that are required for cortical protein localization.71 Moreover, biophysical and crystallographic studies have shown that the BAR domain itself binds directly to membranes and may initiate membrane curvature events that facilitate the development of a tubulovesicular membrane system required for clathrin-mediated endocytosis, regulation of membrane dynamics, and depolarization-contraction coupling in striated muscle.65,66,72–74 Although the exact functions of BAR proteins in yeast are not known, they do appear to regulate similar events, such as, endocytosis, actin cytoskeletal structure, and certain nuclear events.67,68,75–80 Thus, understanding how BAR proteins function within various yeast pathways will increase our understanding of their roles in higher eukaryotes, as well. In the subsequent text, we have summarized what is known about the yeast BAR protein, Rvs167.
6
4.1
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Structure-function Relationships of Rvs167
The S. cerevisiae genes, RVS167 and RVS161, were first identified in a screen for mutations that caused reduced viability upon starvation.67,76 Mutations in RVS167 are highly pleiotropic, resulting in a delocalization of the actin cytoskeleton,68 sensitivity to high salt, starvation, and nonfermentable carbon sources,67,76 defective fluid-phase and receptor-mediated endocytosis,75 and a random daughter budding pattern in diploid cells.68,76,81 Additionally, cells harboring mutations in RVS161 exhibit most of the same phenotypes as rvs167 mutant cells.82,83 This diverse range of phenotypes displayed by rvs mutants suggests that Rvs167 and Rvs161 are multifunctional proteins. Rvs167 consists of 482 amino acids and three different domains, a BAR domain, a glycine, proline, and alanine (GPA) domain, and a Src homology 3 (SH3) domain. The BAR domain of Rvs167 is located at the amino-terminus region similar to other BAR proteins, the GPA domain of Rvs167 is located in the central region and consists mostly of GPA residues, while the SH3 domain of Rvs167 is present at its carboxy terminus (Figure 2).76,78,84 These domains have been shown
Rvs167
Rvs161
BAR
to directly interact with many proteins, including Rvs161, resulting in the post-translational modification of Rvs167 and the regulation of its cell function. Rvs167 also interacts with many proteins indirectly as indicated by many high-throughput genetic interaction studies. 4.2
Functional Requirement of Rvs167 Domains
While examining the ability of various truncated Rvs167 constructs to complement the phenotypes of an rvs167 null mutant, researchers determined that the BAR domain alone was sufficient to rescue each phenotype tested, although not as efficient as rescue by full-length Rvs167. In contrast, a fragment containing the GPA domain, the SH3 domain, or both was unable to rescue any of the rvs167 null mutant defects.84 Additionally, a full-length Rvs167 construct containing a P473L substitution in the SH3 domain, which eliminates binding to proline-rich motifs, and expressed at the same steady-state level as wild-type Rvs167, fully rescued all rvs167 null mutant defects.78 These studies concluded that Rvs167 does not require a functional SH3 domain to be completely functional.
GPA
SH3
BAR
Amphiphysin I
BAR
Bin I
BAR
SH3
SH3
N -terminal amphipathic a-helix
Myc-binding domain
BAR domain
Nuclear localization sequence
Gly/Pro/AIa (GPA)-rich domain SH3 domain Figure 2. BAR proteins. A schematic representation of the protein domains within BAR proteins.
PROTEIN RECOGNITION IN BIOLOGY
Since the BAR domains of Rvs167 and Rvs161 are highly homologous, a study was performed to determine the effect of swapping the BAR domains of each protein.84 The Rvs167 GPA and SH3 domains were fused to Rvs161 creating an Rvs161-GPA-SH3 construct, which retained full ability to rescue the defects of rvs161 mutant cells, however, could not rescue the defects of rvs167 mutant cells. The fragment of Rvs167 containing only the BAR domain, known as Rvs167BAR, was partially functional in rescuing the defects of rvs167 mutant cells, but lacked the ability to rescue the defects of rvs161 mutant cells. When Rvs167-BAR and Rvs161-GPA-SH3 were coexpressed in rvs161 rvs167 double mutant cells, they were still unable to rescue the growth, actin cytoskeleton, or bud site selection defects of these cells.84 Therefore, the two BAR domains of Rvs167 and Rvs161 have distinct functions, suggesting that multiple protein complex machineries having distinct functions nucleate within the Rvs167-Rvs161 heterodimer (see subsequent text). Interestingly, overexpression of Rvs167 is lethal to cells growing at normal temperature and the SH3 domain is required for this lethal phenotype, while overexpression of the Rvs167 GPA-SH3 fragment does not affect cell growth. Additionally, overexpression of the full-length Rvs167P473L allele harboring a recessive mutation within the SH3 domain has milder deleterious effects than wild-type Rvs167, but only at an elevated temperature.78 Therefore, the Rvs167 SH3 domain and those proteins associated with it do have an important role in cell growth, possibly under conditions of stress.85 Unfortunately, the mechanism by which Rvs167 overexpression inhibits growth has not been studied.
4.3
The BAR Domain of Rvs167 Interacts with Rvs161
The 281 residues that make up the N-terminal region of Rvs167 exhibit a strong amino acid sequence homology with the total length (265 residues) of Rvs161; for that reason, it was initially named the Rvs domain.84 Subsequently, the Rvs domain was renamed the BAR domain because of its presence in vertebrate amphiphysin 1 and Bin 1.86 Over this region, Rvs167 exhibits 27% amino acid sequence identity and 52% amino
7
acid sequence similarity with Rvs161.68,80,87 It is subdivided into a short N-terminal amphipathic α-helix (approximately 40–45 residues) and the BAR domain itself (Figure 3), which has a propensity to form a coiled-coil structure that most likely mediates its interaction with Rvs161 (Figure 3).87,88 The interaction between the BAR domains of Rvs167 and Rvs161 was revealed by two-hybrid analysis, while the in vivo association of Rvs167 with Rvs161 was confirmed by co-immunoprecipitation.87 Two studies found that Rvs167 also forms homodimers via the BAR domain;78,89 however, it was later concluded that Rvs167 does not form homodimers in vegetatively growing cells.85,90 Interestingly, cells lacking Rvs161 have a reduced steady-state level of Rvs167 due to its accelerated proteolysis and vice versa.89 Thus, Rvs161 plays a role in maintaining Rvs167 stability.
4.4
The GPA and SH3 Domains Collectively Regulate the Function of Rvs167
Following the BAR domain of Rvs167 is the GPArich region (Figure 2), which lacks any charged amino acids, includes a hydrophobic sequence, and interestingly is not predicted to adopt any defined secondary structure.80 Additionally, located at the C-terminus of Rvs167 is the SH3 domain of approximately 50–70 amino acids, which has the potential to mediate protein–protein interactions by binding to short proline-rich regions (Figure 2).76,91–93 The GPA domain can be phosphorylated to regulate the interaction of the SH3 domain with other proteins,78,79,94,95 and it can also bind with the ubiquitin ligase, Rsp5, to regulate the monoubiquitination of the SH3 domain (Figure 3).96 Therefore, both the GPA domain and the SH3 domain act in concert to regulate the function of Rvs167. The GPA domain of Rvs167 has three major phosphorylation sites, S299, S321, and S379. In addition, T323 can act as a potential phosphorylation site, but only when S321 is mutated. The in vitro phosphorylation of Rvs167 is dependent on a yeast cyclin-dependent kinase, Pho85, while phosphorylation of Rvs167 in vivo is partially dependent on the cyclin subfamily, Pcl1/Pcl2 (Figure 3a).79,94 The discovery that Pho85 regulates Rvs167 demonstrates that Rvs167 may
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
BAR
K4 81
79 S3
S2 9 S3 9 2 T3 1 23
Actin
GPA
SH3
Vrp1 Las17
Rvs161 P
S2 S3 99 T3 21 23
S379
K481
PcI1/2 Pho85
BAR
3
SH
GPA P
RVS161
PPP
Vrp1 Las 17 Arp2/3
Sla1-End3-Pan1
BAR
GPA
81 K4
79 S3
S2 9 S3 9 T3 21 23
(a)
SH3
PPXY
Rvs161
PPXY
WW Rsp5
Rvs161
81 K4
S3
GPA
BAR
(b)
79
Ub
S2 9 S3 9 T3 21 23
WW Rsp5
SH3 Ub
Sla1
Figure 3. Schematic representation of regulation of Rvs167 protein complexes by phosphorylation (a) and ubiquitination (b) of Rsv167.
link nutrient availability to cell-cycle progression. Pho85 plays a role in G1 -S cell-cycle progression while associating with the cyclins, Pcl1 and Pcl297,98 and Rvs167 is phosphorylated only in G1 phase.79,94 Phosphorylation of Rvs167 by Pho85/Pcl2 has also been suggested to play a role in the mating response, since Rvs167
is hyperphosphorylated once cells are exposed to mating pheromone.94 Hyperphosphorylation of Rvs167 also requires the mitogen-activated protein kinase (MAPK), Fus3, which is induced by mating pheromone and functions in the mating pheromone response pathway. Fus3 phosphorylates the same sites in the Rvs167 GPA domain as Pho85/Pcl2.94
PROTEIN RECOGNITION IN BIOLOGY
The GPA domain has previously been shown to be nonessential for known Rvs167 functions, and replacing all four of the Rvs167 protein phosphorylation sites with alanine (rvs167-4A) did not result in rvs167 null mutant phenotypes.78,84 Additionally, rvs167-4A was not lethal in combination with any mutations that are known to be synthetically lethal with RVS167 under normal conditions.77 However, under conditions of high temperature and in the presence of salt, rvs167-4A is synthetically lethal in combination with the loss of SLA1 or END3. Therefore, phosphorylation of Rvs167 may be essential during certain stress conditions.94 Sla1 and End3 form a complex with Pan1, which activates the Arp2/3 protein complex required for nucleating branched actin filaments at endocytic vesicles.99,100 The Wiskott-Aldrich syndrome protein (WASP) homolog, Las17, can also activate the Arp2/3 protein complex in budding yeast,95,101,102 and Las17 binding to the GPA-SH3 domains of Rvs167 is severely reduced by Pho85/Pcl2-dependent phosphorylation of the GPA domain. Therefore, loss of Rvs167 phosphorylation may cause Las17 to bind too strongly and inhibit it from activating Arp2/3, resulting in the dependency on the Sla1-End3–Pan1 complex for Arp2/3 activation during stress conditions (Figure 3a).78,94,95 Rvs167 can also interact with Vrp1, the yeast ortholog of human WASPinteracting protein (WIP),95,101 through its SH3 domain95,103 and researchers believe that Vrp1 and/or Las17 mediates the putative interaction of Rvs167 with actin.104 Consequently, phosphorylation of the Rvs167 GPA domain may induce a major conformational change that affects the neighboring SH3 domain and its ability to bind proteins regulating endocytosis and the actin cytoskeleton. The GPA domain also mediates the direct binding of Rvs167 to the WW domains of the ubiquitin ligase, Rsp5, and this binding induces the monoubiquitination of K481 in the Rvs167 SH3 domain (Figure 3b).96 WW domains bind to PPXY motifs and mutation of the PPXY, PSY, and PQY motifs in the Rvs167 GPA domain reduces the Rvs167-Rsp5 association and the level of monoubiquitinated Rvs167 in vivo.96 Consistent with the result that neither the GPA nor the SH3 domain is required for known Rvs167 functions,78 Rvs167 mutants either lacking the PPXY and PXY motifs in the GPA domain, containing a
9
K481R substitution in the SH3 domain to prevent ubiquitin attachment, or lacking the SH3 domain entirely, were fully functional for receptormediated endocytosis.96 However, in the presence of salt, the Rvs167-K481R mutant is only partially functional for growth, and this requirement is for K481 only, since an Rvs167 mutant construct lacking a PPXY motif that does not bind Rsp5 and is not ubiquitinated on K481, is fully functional for growth in the presence of salt.96 Hence, K481 in the SH3 domain of Rvs167, but not ubiquitination of K481, is important for some functions of Rvs167 during stress conditions. Sla1, another protein implicated in cytoskeletal function,99,105,106 can interact with Rvs167 in vivo and directly binds to recombinant Rvs167 in vitro, but the Rvs167 domain that mediates these interactions is not yet known (Figure 3b).96,107,108 The Sla1–Rvs167 complex may be the yeast equivalent of the vertebrate CIN8–endophilin complex, since Sla1 exhibits sequence homology to CIN8 and Rvs167 is related to endophilin. Moreover, like the yeast Sla1–Rvs167 complex, the vertebrate CIN8–endophilin complex interacts with the ubiquitin ligase, Nedd4, and plays a role in endocytosis.96,109,110
4.5
Indirect and Genetic Interactions of Rvs167
Rvs167 interacts with actin using a two-hybrid screen, and this interaction is dependent upon the SH3 domain (Figure 4).104 Although actin contains a short proline-rich motif that might mediate interaction with the Rvs167 SH3 domain, it was proposed that the Rvs167-actin interaction is indirect.77,78,89 This Rvs167-actin association may be mediated by Abp1, an actin binding protein that is capable of binding to the SH3 domain of Rvs167 using a proline-rich region located near its own C-terminal SH3 domain.77,111 Phenotypes associated with abp1 and rvs167 mutations strongly suggest that the functions of the two proteins are closely related. Therefore, binding to Abp1 may modify the activity of Rvs167, perhaps by influencing the association of Rvs167 with actin or other cellular factors.80 However, deletion of ABP1 does not affect Rvs167 localization to actin patches,112 and is not required for the two-hybrid interaction of Rvs167 and actin.89
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Figure 4. Putative interaction of Rvs167 with factors regulating membrane-associated endocytic events.
Another protein that may mediate the association between Rvs167 and actin is the adaptor protein, Sla2. Sla2 contains a coiled-coil region, known as the Sla2 coil1 domain, which has been reported to interact with the Rvs167 BAR domain and is important for growth, actin patch polarization, and endocytosis.113 Nevertheless, this function is fully redundant with Abp1, since the Sla2 coil1 mutant phenotypes only become apparent in cells that lack Abp1.113 Consequently, interactions of the Rvs167 BAR domain with Sla2 coil1 and the Rvs167 SH3 domain with Abp1 may work in concert to facilitate Rvs167 localization to actin patches. Genetic studies have also revealed that Rvs167 plays a role in membrane-dependent secretory and endocytic events (Figure 4). rvs167 mutations exhibit negative genetic interactions with mutations affecting the MYO2 gene, which encodes the unconventional type V myosin.114 Myo2 regulates motor-driven polarized transport of vesicles, derived from the Golgi apparatus, along actin cables to the bud.115–120 Researchers also discovered interactions between Rvs167 and components of the exocyst complex, Sec8 and Exo70, using large-scale two-hybrid screens.121 Moreover, Rvs167 has been shown to directly bind to Gyp5 and Gyl1, two
proteins involved in the ER-to-Golgi apparatus traffic.122 Combining mutations in RVS167 with mutations in YPT51 and VPS20, which encode proteins known to function in the late endocytic pathway,123,124 results in double mutant cells that either have severely reduced viability or are completely inviable.90,125 Interestingly, vps20 mutants exhibit severely reduced viability upon nutrient starvation,126 further supporting a link between Vps20 and Rvs167. Large-scale two-hybrid and peptide scanning screens have also identified a putative interaction between Rvs167 and Bsp1, a protein that interacts with Inp52 and Inp53, yeast orthologs of vertebrate synaptojanin.103,107,127,128 Additionally, studies using subcellular fractionation have revealed that most Rvs167 is associated with membranes in vivo129,130 and purified Rvs167 can directly bind liposomes in vitro, 85 while mutations in genes that encode proteins involved in the sphingolipid biosynthetic pathway can suppress all Rvs167 mutant phenotypes,131 further supporting the view that Rvs167 functions in the regulation of membrane-associated endocytic and/or exocytic events, possibly through the interaction of its BAR domain with nascent endo- or exocytic buds.
PROTEIN RECOGNITION IN BIOLOGY
In S. cerevisiae, the proper stoichiometry of Rvs167 is critical to cellular growth due to the association of Rvs167 in many protein complexes. The diverse range of phenotypes displayed by an rvs167 mutant suggests Rvs167 is a multifunctional protein, with three domains conferring different biological activities. The interaction of Rvs167 with many proteins that are known actin cytoskeletal regulators, together with its ability to directly bind membranes, makes Rvs167 an ideal candidate for linking actin filament assembly to membrane dynamics. The diversity of potential Rvs167 interactors is striking. An assorted network of protein interactions that involves Rvs167 has been revealed using genomic and proteomic approaches. A study aimed at producing a protein interaction map for cell polarity proteins found 14 proteins interacting with Rvs167.107 Another study combined computational prediction of interactions using phage display ligand consensus sequences and large-scale two-hybrid interaction analysis to identify nine interactions involving the Rvs167 SH3 domain.103 High-throughput mass spectrophotometric analysis identified 27 interactions with Rvs167,108 while a synthetic genetic array analysis found 49 lethal combinations with the RVS167 gene.85,132 Although Rvs167 interactions represent a diversity of cellular processes, the interactions found by these high-throughput approaches should be regarded as putative until further characterized. However, we can conclude, based on the crystal structure of the BAR domain and the biophysical studies demonstrating its interactions with membranes that Rvs167, and thus eukaryotic amphyphysins as a group, most likely perform the critical function of integrating membrane events with cell pathways required for cell viability under a wide range of environmental stresses. 5 SIGNALING MACHINES – THE INTERLEUKIN 5 CYTOKINE RECEPTOR SYSTEM 5.1
Assembly and Activation
The class I cytokine receptor superfamily, which is characterized by the presence of the so-called cytokine recognition motif (CRM, two fibronectin domain framework typified by growth hormone
11
receptor),133 can be divided into four classes with unique structural characteristics based on signaling receptor usage:
1. homodimer-family (growth hormone and erythropoietin); 2. gp130 family (interleukin (IL) 6 and 11, and leukemia inhibitory factor); 3. γ c family (IL2, IL4, IL7, IL9, and IL15); and 4. βc family (IL5 and IL3, and granulocyte macrophage-colony stimulating factor (GMCSF)).
Knowledge of the assembly mechanisms has been determined for the first three of these (Figure 5). Extensive crystallographic studies have been accomplished for the receptor homodimersignaling system (GH-GHR,134 PL-PLR,135 EPO-EPOR136 ). More recently, receptor complex structures have been solved for the gp130-system (IL6-gp130,137 IL6-IL6R-gp130138 ). Additionally, γ c-systems have been solved (IL4-IL4R,139 IL2IL2Rα,140,141 IL2-IL2Ra-IL2Rβ-γ c).140,141 As yet, there is less structural mechanism information about the βc-type signaling system. βc cytokine receptors are responsible for regulation of myeloid cell development in hematopoiesis. The family of IL5, IL3, and GM-CSF cytokines all function through βc (common β) subunit signaling, in a receptor activation process that also requires a cytokine-specific coreceptor, a subunit, for cytokine presentation to βc. The actions of this family of cytokines have been correlated with pathogenesis of diverse inflammatory diseases. For the case of IL5, there is a clear causal relationship between cytokine, eosinophilia, and allergic inflammation. Activation of the IL5 receptor system appears to involve both a sequential noncovalent assembly of IL5, IL5Rα and βc into a 2 : 2 : 2 complex followed by a disulfide bond cross-linking of the receptor subunits that are unique among class I cytokines. An emerging model for sequential assembly of IL5 and receptor subunits is shown in Figures 5 and 6. The α subunit is primarily responsible for ligand recognition, consistent with the Kd of 0.3–0.6 nM reported for IL5 obtained using receptor α subunit expressed in COS7 cells.142
12
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Homodimer family
gp130 family IL6
GH
2:2:2
gp130 1: 2
Ra
GHR
(b)
(a) g c family
b c family IL5
IL2 1:1:1:1 Ra
Rb
gc
2:2:2 (disulfide)
bc Ra
(c)
(d)
Figure 5. Schemes of Class 1 cytokine receptor complexes. The class I cytokine receptor superfamily can be subdivided into four major families according to the signaling subunits. The number of receptors involved and the configuration of receptor complexes are different among these families. While the structures and assembly processes of the first three of these are known, the characteristics for the βc family in (d) are largely conjectural. The biological and pathogenic functions of the βc family make it compelling to learn about these complexes and to develop a mechanistic basis for ultimate therapeutic intervention.
IL5
1:1 complex
1:1:2 complex 2 × bc
2:2:2 complex (non covalent)
2:2:2 complex (covalent)
∗
IL5Rα
JAK JAK STAT
Syntenin
Lyn
STAT Btk MAPK
Sox4
Cytoplasm Transcription Nucleus Figure 6. Working model of receptor recruitment by IL5 leading to receptor activation and signal transduction. IL5 initially binds to IL5Rα to form a high-affinity 1:1 complex. Although IL5 is a homodimeric protein, it has been shown that the stoichiometry of IL5–IL5Rα interaction is 1:1. This IL5–IL5Rα complex is thought to bind to preformed dimer of common receptor β (βc) to form 1:1:2 intermediate complex. Subsequently, another IL5–IL5Rα complex binds to the 1:1:2 complex to form 2:2:2 complex. It is proposed that this complex is further matured by disulfide-bond formation between IL5Rα and βc, and this final complex can induce cytoplasmic signaling through JAK/STAT and MAPK pathways in eosinophils.154
PROTEIN RECOGNITION IN BIOLOGY
The βc subunit also contributes, albeit relatively weakly, to ligand binding, as judged by increased (two to fourfold) IL5 affinity when α and βc chains are coexpressed.143–145 Nonetheless, binding of βc to IL5 has not been observed directly,143 suggesting that IL5 first binds to IL5Rα, and that it is the IL5Rα complex that recruits βc. The latter has been observed by kinetics interaction analysis using a surface plasmon resonance biosensor.146 Thus, the IL5Rα subunit appears to function as what has been termed a signaling coreceptor,147 binding the ligand and presenting it to the signaling subunit, in this case βc. Currently, there is no direct measurement of whether βc is recruited by binding residues in IL5, binding residues in α chain, or a combination of both. Conformational maturation upon IL5–IL5Rα complexation is likely required for βc recruitment though its nature is not known at present. The IL5 binding site of receptor α is located in its extracellular domain. IL5 must form a complex at the cell membrane with both α and β chains to trigger a full intracellular signal. However, the α and βc chains do not appear to be preassembled,148 and assembly of receptor subunits induced by IL5 is likely an early and essential step in signaling. The model in Figure 6 envisions that βc dimers are preformed, as has been observed crystallographically,149 as well as in solution.150 This model also draws upon recent results reported from the GM-CSF system, which is highly similar to the IL5 system. The Lopez group has shown that GM-CSF signaling proceeds through an intermediate state composed of one GM-CSF ligand, one receptor α chain, and two βc chains (1 : 1 : 2 complex). However, it has long been believed that the final signaling complex is composed of two GMCSF, two α chains, and two βc chains (2 : 2 : 2 complex; Figure 6). Hence, one can hypothesize that in the case of IL5 the ligand first binds to IL5Rα, and then two IL5Rα heterodimers bind sequentially to a preformed βc dimer. Recent mutagenic data151 show that combined epitopes in βc composed of residues from the D1 and D4 domain pairs are important for this recruitment of the IL5–IL5Rα complex into a high affinity assembly. Experiments with the IL3 receptor system have demonstrated that disulfide bonds are formed between the α and βc chains and appear to be essential for at least some aspects of cytoplasmic signaling.152 Consistent with the notion that such
13
a bond may also be required in the IL5 system, chemical modification of a free cysteine residue in domain 1 of IL5Rα diminished the signaling activity by IL5.153 In mutational analysis and binding assays, this cysteine was found not to be important for the interaction of IL5Rα with IL5, and its sulfhydryl group did not appear to be exposed to solvent. Hence, we currently assume that some conformational change occurs in receptor α during receptor assembly. In addition, because the βc dimer is thought to be preformed, some conformational change in the βc subunits upon assembly would appear to be necessary for signaling, since βc dimerization by itself is clearly insufficient to trigger a signal. It may well be the formation of the covalent disulfide bonds between IL5Rα and βc that provides the molecular switch for receptor activation in the βc cytokine receptor machines. Binding of IL5 to receptor rapidly stimulates receptor phosphorylation, which utilizes receptorassociated tyrosine kinases (Figure 6), including Lyn, JAK1, and JAK2.155–157 The active JAKs phosphorylate tyrosine residues on the receptor, leading to the recruitment and activation of the signal transducer and activator of transcription (STAT) family, primarily STAT1 and STAT5. In addition to JAKs, Lyn kinase also is an early activated kinase after IL5 stimulation and is constitutively associated with the βc receptor. Researchers have found that the Lyn binding site of the βc receptor is different from the binding site for JAK2. Both Lyn and JAK2 kinases play a key role in eosinophil development from bone marrow progenitors, and promote eosinophil survival.155,156,158 However, it appears that Lyn kinase is more specific for the IL5 system (e.g., eosinophil), while JAK kinases are involved in signal transduction of other cytokine systems in addition to IL5. The βc subunit physically associates with Lyn and JAKs kinases, and signaling also involves the activation of the Ras-MAPK pathway. Although βc is the main signaling component for the receptor complex, the α chain might be involved in cytokine-specific signaling. Recently, researchers have proposed a syntenin/Sox4 activation pathway as a cytokine-specific signaling mechanism involving IL5Rα (Figure 6).159 They found that syntenin can bind to carboxyterminal residues of cytoplasmic region of IL5Rα. Moreover, it was demonstrated that syntenin is
14
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
a binding partner of Sox4, a transcriptional activator. These results suggest that IL5Rα-induced Sox4 activation could play a role in the regulation of early B cell development. The overall relevance of this signaling pathway to IL5-specific functions remains to be elucidated.
5.2
Epitopes Driving the IL5 Receptor Machine and Antagonist Design
While the assembly and structure of the IL5–IL5Rα–βc complex is still not known at high atomic resolution, structural epitopes for interaction among the components have been evaluated by mutagenic analysis. These sites have been mapped by a combination of mutational variation and interaction studies in solution160,161 and in cells151,162,163 and are depicted in Figure 7. One can propose a model for how the extracellular domains of IL5 and receptor subunits could form IL5
bc
IL5Ra
Activation complex
Figure 7. Modeled interaction of IL5-IL5Rα with one of the D1D4 domains of βc. The overall 3-component model is based on the structure of placental lactogen and prolactin receptor in their experimentally determined, high-resolution complex,135 where these components were replaced with IL5 (crystal structure),164 IL5Rα (homology model),161 and one D1D4 tandem domain of βc homodimer (crystal structure),149 by superimposition. Experimentally determined epitope residues for IL5 (Glu13, Lys40, His42, Glu89, Arg91, and Glu110), IL5Rα (Asp55, Asp56, Glu58, Lys186, Arg188, and Arg297) and βc (Tyr15, Phe79, Tyr347, and Tyr403) are expressed in the Corey, Pauling, and Koltun (CPK) models [Reviewed by Ishino et al.].165
based on binding epitopes mapped so far, shown in Figure 7. Screening of random recombinant peptide libraries has led to the identification of sequence-related monomeric and dimeric inhibitors of IL5Rα.166 These peptides are believed to bind to the ligand binding ectodomain of the α subunit. Cyclic peptide AF17121, the most potent member of the cyclic monomer family, is an 18-mer that has been shown to bind IL5Rα with an affinity of 50 nM and to block IL5-dependent eosinophil activation. Recent studies have demonstrated the importance of charged residues in this peptide.167 In particular, Arg6 has been found to be indispensable for inhibitor activity. The 2 DEXXR6 motif present in AF17121 resembles the sequence epitope present in the turn between helices C and D (88 EERRR92 ) of IL5.168 Single residue mutagenesis in this latter sequence has shown that Glu89 and Arg91 are important for receptor α binding.169 Furthermore, sequence randomization studies have shown that 88 SLRGG92 derivative of IL5 can act as a functional surrogate. These observations have led us to postulate that AF17121 may function by mimicking the charge distribution of the receptor recognition epitope of IL5. Indeed, the binding epitope in IL5Rα for AF17121 includes residues that also are important for IL5 binding, that is Asp55, Arg188, and Arg297.170 The IL5 receptor system exemplifies a multiprotein machine, composed of transmembrane assembling receptor subunits coupled with an intracellular signal protein network that can transduce extracellular binding into cell regulation through molecular switches driven by protein interaction processes. Defining the molecularstructural nature of the interactions in this machine can help deduce molecular mechanisms underlying biological mechanism and disease pathogenesis and help lead to approaches to structure-based antagonism.
6 A FINAL MESSAGE
In brief summary, a major challenge in biological sensing is to detect the components of organized protein machines and networks, to measure the interactions with these assemblies, and to use the signatures of protein complexes as indicators of biological state and function.
PROTEIN RECOGNITION IN BIOLOGY
REFERENCES 1. D. L. Nelson and M. M. Cox, Lehninger Principles of Biochemistry, 3rd Edn, Worth Publishers, New York, 2000. 2. D. A. Brown and E. London, Structure and function of sphingolipid- and cholesterol-rich membrane rafts. Journal of Biological Chemistry, 2000, 275(23), 17221–17224. 3. F. R. Maxfield and I. Tabas, Role of cholesterol and lipid organization in disease. Nature, 2005, 438(7068), 612–621. 4. J. P. Incardona and S. Eaton, Cholesterol in signal transduction. Current Opinion in Cell Biology, 2000, 12(2), 193–203. 5. D. R. Illingworth, Management of hypercholesterolemia. Medicine Clinics of North America, 2000, 84(1), 23–42. 6. O. Stein and Y. Stein, Lipid transfer proteins (LTP) and atherosclerosis. Atherosclerosis, 2005, 178(2), 217–230. 7. D. W. Denning, G. G. Baily, and S. V. Hood, Azole resistance in candida. European Journal of Clinical Microbiology and Infectious Diseases, 1997, 16(4), 261–280. 8. J. M. Lee and R. P. Choudhury, Prospects for atherosclerosis regression: Hdl elevation and other emerging therapeutic technologies. Heart, 2006. 9. B. Verges, New insight into the pathophysiology of lipid abnormalities in type 2 diabetes. Diabetes and Metabolism, 2005, 31(5), 429–439. 10. T. Y. Chang, P. C. Reid, S. Sugii, N. Ohgami, J. C. Cruz, and C. C. Chang, Niemann-pick type c disease and intracellular cholesterol trafficking. Journal of Biological Chemistry, 2005, 280(22), 20917–20920. 11. M. S. Katz, Therapy insight: potential of statins for cancer chemoprevention and therapy. Nature Clinical Practical Oncology, 2005, 2(2), 82–89. 12. V. Krcmery and A. J. Barnes, Non-albicans candida spp. causing fungaemia: pathogenicity and antifungal resistance. Journal of Hospital Infection, 2002, 50(4), 243–260. 13. M. Y. Moosa and J. D. Sobel, Non-albicans candida infections in patients with hematologic malignancies. Seminars in Respiratory Infections, 2002, 17(2), 91–98. 14. T. C. White, S. Holleman, F. Dy, L. F. Mirels, and D. A. Stevens, Resistance mechanisms in clinical isolates of candida albicans. Antimicrobial Agents and Chemotherapy, 2002, 46(6), 1704–1713. 15. M. S. Brown and J. L. Goldstein, The SREBP pathway: regulation of cholesterol metabolism by proteolysis of a membrane-bound transcription factor. Cell, 1997, 89(3), 331–340. 16. M. S. Brown and J. L. Goldstein, A proteolytic pathway that controls the cholesterol content of membranes, cells, and blood. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96(20), 11041–11048. 17. T. F. Osborne, Sterol regulatory element-binding proteins (SREBPs): key regulators of nutritional homeostasis and insulin action. Journal of Biological Chemistry, 2000, 275(42), 32379–32382. 18. J. L. Goldstein and M. S. Brown, Regulation of the mevalonate pathway. Nature, 1990, 343(6257), 425–430.
15
19. P. A. Dawson, S. L. Hofmann, D. R. van der Westhuyzen, T. C. Sudhof, M. S. Brown, and J. L. Goldstein, Steroldependent repression of low density lipoprotein receptor promoter mediated by 16-base pair sequence adjacent to binding site for transcription factor Sp1. Journal of Biological Chemistry, 1988, 263(7), 3372–3379. 20. T. F. Osborne, G. Gil, M. S. Brown, R. C. Kowal, and J. L. Goldstein, Identification of promoter elements required for in vitro transcription of hamster 3-hydroxy-3-methylglutaryl coenzyme a reductase gene. Proceedings of the National Academy of Sciences of the United States of America, 1987, 84(11), 3614–3618. 21. T. F. Osborne, G. Gil, J. L. Goldstein, and M. S. Brown, Operator constitutive mutation of 3-hydroxy-3methylglutaryl coenzyme a reductase promoter abolishes protein binding to sterol regulatory element. Journal of Biological Chemistry, 1988, 263(7), 3380–3387. 22. J. R. Smith, T. F. Osborne, M. S. Brown, J. L. Goldstein, and G. Gil, Multiple sterol regulatory elements in promoter for hamster 3-hydroxy-3-methylglutarylcoenzyme a synthase. Journal of Biological Chemistry, 1988, 263(34), 18480–18487. 23. T. C. Sudhof, D. R. Van der Westhuyzen, J. L. Goldstein, M. S. Brown, and D. W. Russell, Three direct repeats and a TATA-like sequence are required for regulated expression of the human low density lipoprotein receptor gene. Journal of Biological Chemistry, 1987, 262(22), 10773–10779. 24. M. R. Briggs, C. Yokoyama, X. Wang, M. S. Brown, and J. L. Goldstein, Nuclear protein that binds sterol regulatory element of low density lipoprotein receptor promoter. I. Identification of the protein and delineation of its target nucleotide sequence. Journal of Biological Chemistry, 1993, 268(19), 14490–14496. 25. G. P. Gasic, Basic-helix-loop-helix transcription factor and sterol sensor in a single membrane-bound molecule. Cell, 1994, 77(1), 17–19. 26. H. Shimano, Sterol regulatory element-binding proteins (SREBPs): transcriptional regulators of lipid synthetic genes. Progress in Lipid Research, 2001, 40(6), 439–452. 27. X. Wang, M. R. Briggs, X. Hua, C. Yokoyama, J. L. Goldstein, and M. S. Brown, Nuclear protein that binds sterol regulatory element of low density lipoprotein receptor promoter. II. purification and characterization. Journal of Biological Chemistry, 1993, 268(19), 14497–14504. 28. L. W. Weber, M. Boll, and A. Stampfl, Maintaining cholesterol homeostasis: sterol regulatory elementbinding proteins. World Journal of Gastroenterology, 2004, 10(21), 3081–3087. 29. H. Shimano, J. D. Horton, I. Shimomura, R. E. Hammer, M. S. Brown, and J. L. Goldstein, Isoform 1c of sterol regulatory element binding protein is less active than isoform 1a in livers of transgenic mice and in cultured cells. The Journal of Clinical Investigation, 1997, 99(5), 846–854. 30. S. Datta and T. F. Osborne, Activation domains from both monomers contribute to transcriptional stimulation by sterol regulatory element-binding protein dimers. Journal of Biological Chemistry, 2005, 280(5), 3338–3345. 31. J. D. Horton, Y. Bashmakov, I. Shimomura, and H. Shimano, Regulation of sterol regulatory element
16
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS binding proteins in livers of fasted and refed mice. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95(11), 5987–5992. J. J. Repa, G. Liang, J. Ou, Y. Bashmakov, J. M. Lobaccaro, I. Shimomura, B. Shan, M. S. Brown, J. L. Goldstein, and D. J. Mangelsdorf, Regulation of mouse sterol regulatory element-binding protein-1c gene (SREBP-1c) by oxysterol receptors, LXRalpha and LXRbeta. Genes and Development, 2000, 14(22), 2819–2830. A. Zoumi, S. Datta, L. H. Liaw, C. J. Wu, G. Manthripragada, T. F. Osborne, and V. J. Lamorte, Spatial distribution and function of sterol regulatory element-binding protein 1a and 2 homoand heterodimers by in vivo two-photon imaging and spectroscopy fluorescence resonance energy transfer. Molecular and Cellular Biology, 2005, 25(8), 2946–2956. G. Dellaire and D. P. Bazett-Jones, PML nuclear bodies: dynamic sensors of DNA damage and cellular stress. Bioessays, 2004, 26(9), 963–977. Y. Takahashi, V. Lallemand-Breitenbach, J. Zhu, and H. de The, PML nuclear bodies and apoptosis. Oncogene, 2004, 23(16), 2819–2824. L. Polgar, The catalytic triad of serine peptidases. Cellular and Molecular Life Sciences, 2005, 62(19–20), 2161–2172. J. Sakai, R. B. Rawson, P. J. Espenshade, D. Cheng, A. C. Seegmiller, J. L. Goldstein, and M. S. Brown, Molecular identification of the sterol-regulated luminal protease that cleaves SREBPs and controls lipid composition of animal cells. Molecular Cell, 1998, 2(4), 505–514. E. I. Deryugina and J. P. Quigley, Matrix metalloproteinases and tumor metastasis. Cancer Metastasis Reviews, 2006, 25(1), 9–34. R. B. Rawson, N. G. Zelenski, D. Nijhawan, J. Ye, J. Sakai, M. T. Hasan, T. Y. Chang, M. S. Brown, and J. L. Goldstein, Complementation cloning of S2P, a gene encoding a putative metalloprotease required for intramembrane cleavage of SREBPs. Molecular Cell, 1997, 1(1), 47–57. J. D. Feramisco, A. Radhakrishnan, Y. Ikeda, J. Reitz, M. S. Brown, and J. L. Goldstein, Intramembrane aspartic acid in SCAP protein governs cholesterolinduced conformational change. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(9), 3242–3247. A. Nohturfft, M. S. Brown, and J. L. Goldstein, Topology of SREBP cleavage-activating protein, a polytopic membrane protein with a sterol-sensing domain. Journal of Biological Chemistry, 1998, 273(27), 17243–17250. A. Radhakrishnan, L. P. Sun, H. J. Kwon, M. S. Brown, and J. L. Goldstein, Direct binding of cholesterol to the purified membrane region of SCAP: mechanism for a sterol-sensing domain. Molecular Cell, 2004, 15(2), 259–268. J. Sakai, A. Nohturfft, D. Cheng, Y. K. Ho, M. S. Brown, and J. L. Goldstein, Identification of complexes between the COOH-terminal domains of sterol regulatory element-binding proteins (SREBPs) and SREBP cleavage-activating protein. Journal of Biological Chemistry, 1997, 272(32), 20213–20221.
44. T. Y. Chang, C. C. Chang, N. Ohgami, and Y. Yamauchi, Cholesterol sensing, trafficking, and esterification. Annual Review of Cell and Developmental Biology, 2006, 22, 129–157. 45. E. D. Carstea, J. A. Morris, K. G. Coleman, S. K. Loftus, D. Zhang, C.Cummings, J. Gu, M.A. Rosenfeld, W.J. Pavan, D. B. Krizman, J. Nagle, M. H. Polymeropoulos, S. L. Sturley, Y. A. Ioannou, M. E. Higgins, M. Comly, A. Cooney, A. Brown, C.R. Kaneski, E. J. BlanchetteMackie, N .K. Dwyer, E. B. Neufeld, T. Y. Chang, L. Liscum, J.F. Strauss III, K. Ohno, M. Zeigler, R. Carmi, J. Sokol, D. Markie, R. R. O’Neill, O. P. van Diggelen, M. Elleder, M. C. Patterson, R. O. Brady, M. T. Vanier, P. G. Pentchev, and D. A. Tagle, Niemann-pick C1 disease gene: homology to mediators of cholesterol homeostasis. Science, 1997, 277(5323), 228–231. 46. P. E. Kuwabara and M. Labouesse, The sterol-sensing domain: multiple families, a unique role? Trends in Genetics, 2002, 18(4), 193–201. 47. A. Nohturfft, R. A. DeBose-Boyd, S. Scheek, J. L. Goldstein, and M. S. Brown, Sterols regulate cycling of SREBP cleavage-activating protein (SCAP) between endoplasmic reticulum and golgi. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96(20), 11235–11240. 48. T. Yang, P. J. Espenshade, M. E. Wright, D. Yabe, Y. Gong, R. Aebersold, J. L. Goldstein, and M. S. Brown, Crucial step in cholesterol homeostasis: sterols promote binding of SCAP to INSIG-1, a membrane protein that facilitates retention of SREBPs in ER. Cell, 2002, 110(4), 489–500. 49. D. Yabe, M. S. Brown, and J. L. Goldstein, Insig-2, a second endoplasmic reticulum protein that binds SCAP and blocks export of sterol regulatory elementbinding proteins. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(20), 12753–12758. 50. D. Yabe, Z. P. Xia, C. M. Adams, and R. B. Rawson, Three mutations in sterol-sensing domain of SCAP block interaction with insig and render SREBP cleavage insensitive to sterols. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(26), 16672–16677. 51. Y. Gong, J. N. Lee, P. C. Lee, J. L. Goldstein, M. S. Brown, and J. Ye, Sterol-regulated ubiquitination and degradation of insig-1 creates a convergent mechanism for feedback control of cholesterol synthesis and uptake. Cell Metabolism, 2006, 3(1), 15–24. 52. Y. Gong, J. N. Lee, M. S. Brown, J. L. Goldstein, and J. Ye, Juxtamembranous aspartic acid in Insig-1 and Insig-2 is required for cholesterol homeostasis. Proceedings of the National Academy of Sciences of the United States of America, 2006, 103(16), 6154–6159. 53. P. J. Espenshade, W. P. Li, and D. Yabe, Sterols block binding of COPII proteins to SCAP, thereby controlling SCAP sorting in ER. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(18), 11694–11699. 54. L. P. Sun, L. Li, J. L. Goldstein, and M. S. Brown, Insig required for sterol-mediated inhibition of Scap/SREBP binding to COPII proteins in vitro. Journal of Biological Chemistry, 2005, 280(28), 26483–26490.
PROTEIN RECOGNITION IN BIOLOGY 55. D. Gorlich, F. Vogel, A. D. Mills, E. Hartmann, and R. A. Laskey, Distinct functions for the two importin subunits in nuclear protein import. Nature, 1995, 377(6546), 246–248. 56. S. J. Lee, T. Sekimoto, E. Yamashita, E. Nagoshi, A. Nakagawa, N. Imamoto, M. Yoshimura, H. Sakai, K. T. Chong, T. Tsukihara, and Y. Yoneda, The structure of importin-beta bound to SREBP-2: nuclear import of a transcription factor. Science, 2003, 302(5650), 1571–1575. 57. B. Kobe, T. Gleichmann, J. Horne, I. G. Jennings, P. D. Scotney, and T. Teh, Turn up the heat. Structure, 1999, 7(5), R91–R97. 58. J. B. Kim, G. D. Spotts, Y. D. Halvorsen, H. M. Shih, T. Ellenberger, H. C. Towle, and B. M. Spiegelman, Dual DNA binding specificity of ADD1/SREBP1 controlled by a single amino acid in the basic helix-loop-helix domain. Molecular and Cellular Biology, 1995, 15(5), 2582–2588. 59. T. Ellenberger, D. Fass, M. Arnaud, and S. C. Harrison, Crystal structure of transcription factor E47: E-box recognition by a basic region helix-loop-helix dimer. Genes and Development, 1994, 8(8), 970–980. 60. A. R. Ferre-D’Amare, G. C. Prendergast, E. B. Ziff, and S. K. Burley, Recognition by max of its cognate DNA through a dimeric b/HLH/Z domain. Nature, 1993, 363(6424), 38–45. 61. A. R. Ferre-D’Amare, P. Pognonec, R. G. Roeder, and S. K. Burley, Structure and function of the b/HLH/Z domain of USF. Embo Journal, 1994, 13(1), 180–189. 62. K. A. Dooley, M. K. Bennett, and T. F. Osborne, A critical role for cAMP response element-binding protein (CREB) as a co-activator in sterol-regulated transcription of 3-hydroxy-3-methylglutaryl coenzyme a synthase promoter. Journal of Biological Chemistry, 1999, 274(9), 5285–5291. 63. S. K. Halder, M. Fink, M. R. Waterman, and D. Rozman, A cAMP-responsive element binding site is essential for sterol regulation of the human lanosterol 14alphademethylase gene (CYP51). Molecular Endocrinology, 2002, 16(8), 1853–1863. 64. A. M. Naar, P. A. Beaurang, K. M. Robinson, J. D. Oliner, D. Avizonis, S. Scheek, J. Zwicker, J. T. Kadonaga, and R. Tjian, Chromatin, TAFs, and a novel multiprotein coactivator are required for synergistic activation by Sp1 and SREBP-1a in vitro. Genes and Development, 1998, 12(19), 3020–3031. 65. B. J. Peter, H. M. Kent, I. G. Mills, Y. Vallis, P. J. Butler, P. R. Evans, and H. T. McMahon, BAR domains as sensors of membrane curvature: the amphiphysin BAR structure. Science, 2004, 303(5657), 495–499. 66. B. Zhang, and A. C. Zelhof, Amphiphysins: raising the BAR for synaptic vesicle recycling and membrane dynamics. Bin-amphiphysin-rvsp. Traffic, 2002, 3(7), 452–460. 67. M. Crouzet, M. Urdaci, L. Dulau, and M. Aigle, Yeast mutant affected for viability upon nutrient starvation: characterization and cloning of the RVS161 gene. Yeast, 1991, 7(7), 727–743. 68. P. Sivadon, F. Bauer, M. Aigle, and M. Crouzet, Actin cytoskeleton and budding pattern are altered in the yeast rvs161 mutant: the Rvs161 protein shares common
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
17
domains with the brain protein amphiphysin. Molecular and General Genetics, 1995, 246(4), 485–495. R. Wechsler-Reya, R. K. Elliott, M. Herlyn, and G. C. Prendergast, The putative tumor suppressor BIN1 is a short-lived nuclear phosphoprotein, the localization of which is altered in malignant cells. Cancer Research, 1997, 57(15), 3258–3263. R. Wechsler-Reya, D. Sakamuro, J. Zhang, J. Duhadaway, and G. C. Prendergast, Structural analysis of the human BIN1 gene. Evidence for tissue-specific transcriptional regulation and alternate RNA splicing. Journal of Biological Chemistry, 1997, 272(50), 31453–31458. A. C. Zelhof, H. Bao, R. W. Hardy, A. Razzaq, B. Zhang, and C. Q. Doe, Drosophila amphiphysin is implicated in protein localization and membrane morphogenesis but not in synaptic vesicle endocytosis. Development, 2001, 128(24), 5005–5015. E. Lee, M. Marcucci, L. Daniell, M. Pypaert, O. A. Weisz, G. C. Ochoa, K. Farsad, M. R. Wenk, and P. De Camilli, Amphiphysin 2 (bin1) and t-tubule biogenesis in muscle. Science, 2002, 297(5584), 1193–1196. K. Takei, V. I. Slepnev, V. Haucke, and P. De Camilli, Functional partnership between amphiphysin and dynamin in clathrin-mediated endocytosis. Nature Cell Biology, 1999, 1(1), 33–39. J. Zimmerberg and S. McLaughlin, Membrane curvature: how BAR domains bend bilayers. Current Biology, 2004, 14(6), R250–R252. A. L. Munn, B. J. Stevenson, M. I. Geli, and H. Riezman, End5, end6, and end7: mutations that cause actin delocalization and block the internalization step of endocytosis in saccharomyces cerevisiae. Molecular Biology of the Cell, 1995, 6(12), 1721–1742. F. Bauer, M. Urdaci, M. Aigle, and M. Crouzet, Alteration of a yeast SH3 protein leads to conditional viability with defects in cytoskeletal and budding patterns. Molecular and Cellular Biology, 1993, 13(8), 5070–5084. T. Lila and D. G. Drubin, Evidence for physical and functional interactions among two saccharomyces cerevisiae SH3 domain proteins, an adenylyl cyclaseassociated protein and the actin cytoskeleton. Molecular Biology of the Cell, 1997, 8(2), 367–385. K. Colwill, D. Field, L. Moore, J. Friesen, and B. Andrews, In vivo analysis of the domains of yeast Rvs167p suggests Rvs167p function is mediated through multiple protein interactions. Genetics, 1999, 152(3), 881–893. J. Lee, K. Colwill, V. Aneliunas, C. Tennyson, L. Moore, Y. Ho, and B. Andrews, Interaction of yeast Rvs167 and Pho85 cyclin-dependent kinase complexes may link the cell cycle to the actin cytoskeleton. Current Biology, 1998, 8(24), 1310–1321. G. Ren, P. Vajjhala, J. S. Lee, B. Winsor, and A. L. Munn, The BAR domain proteins: molding membranes in fission, fusion, and phagy. Microbiology and Molecular Biology Reviews, 2006, 70(1), 37–120. P. Durrens, E. Revardel, M. Bonneu, and M. Aigle, Evidence for a branched pathway in the polarized cell division of saccharomyces cerevisiae. Current Genetics, 1995, 27(3), 213–216.
18
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
82. A. E. Gammie, V. Brizzio, and M. D. Rose, Distinct morphological phenotypes of cell fusion mutants. Molecular Biology of the Cell, 1998, 9(6), 1395–1410. 83. V. Brizzio, A. E. Gammie, and M. D. Rose, Rvs161p interacts with Fus2p to promote cell fusion in saccharomyces cerevisiae. Journal of Cell Biology, 1998, 141(3), 567–584. 84. P. Sivadon, M. Crouzet, and M. Aigle, Functional assessment of the yeast Rvs161 and Rvs167 protein domains. Febs Letters, 1997, 417(1), 21–27. 85. H. Friesen, C. Humphries, Y. Ho, O. Schub, K. Colwill, and B. Andrews, Characterization of the yeast amphiphysins Rvs161p and Rvs167p reveals roles for the Rvs heterodimer in vivo. Molecular Biology of the Cell, 2006, 17(3), 1306–1321. 86. D. Sakamuro, K. J. Elliott, R. Wechsler-Reya, and G. C. Prendergast, BIN1 is a novel MYC-interacting protein with features of a tumour suppressor. Nature Genetics, 1996, 14(1), 69–77. 87. P. Navarro, P. Durrens, and M. Aigle, Protein-protein interaction between the RVS161 and RVS167 gene products of Saccharomyces cerevisiae. Biochimica Et Biophysica Acta, 1997, 1343(2), 187–192. 88. C. David, M. Solimena, and P. De Camilli, Autoimmunity in stiff-man syndrome with breast cancer is targeted to the C-terminal region of human amphiphysin, a protein similar to the yeast proteins, Rvs167 and Rvs161. Febs Letters, 1994, 351(1), 73–79. 89. R. Lombardi and H. Riezman, Rvs161p and Rvs167p, the two yeast amphiphysin homologs, function together in vivo. Journal of Biological Chemistry, 2001, 276(8), 6016–6022. 90. M. Germann, E. Swain, L. Bergman, and J. T. Nickels, Jr., Characterizing the sphingolipid signaling pathway that remediates defects associated with loss of the yeast amphiphysin-like orthologs, Rvs161p and Rvs167p. Journal of Biological Chemistry, 2005, 280(6), 4270–4278. 91. T. Pawson and G. D. Gish, SH2 and SH3 domains: from structure to function. Cell, 1992, 71(3), 359–362. 92. R. Ren, B. J. Mayer, P. Cicchetti, and D. Baltimore, Identification of a ten-amino acid proline-rich SH3 binding site. Science, 1993, 259(5098), 1157–1161. 93. H. Yu, J. K. Chen, S. Feng, D. C. Dalgarno, A. W. Brauer, and S. L. Schreiber, Structural basis for the binding of proline-rich peptides to SH3 domains. Cell, 1994, 76(5), 933–945. 94. H. Friesen, K. Murphy, A. Breitkreutz, M. Tyers, and B. Andrews, Regulation of the yeast amphiphysin homologue Rvs167p by phosphorylation. Molecular Biology of the Cell, 2003, 14(7), 3027–3040. 95. A. Madania, P. Dumoulin, S. Grava, H. Kitamoto, C. Scharer-Brodbeck, A. Soulard, V. Moreau, and B. Winsor, The saccharomyces cerevisiae homologue of human wiskott-aldrich syndrome protein Las17p interacts with the Arp2/3 complex. Molecular Biology of the Cell, 1999, 10(10), 3521–3538. 96. S. D. Stamenova, R. Dunn, A. S. Adler, and L. Hicke, The Rsp5 ubiquitin ligase binds to and ubiquitinates members of the yeast CIN85-endophilin complex, Sla1Rvs167. Journal of Biological Chemistry, 2004, 279(16), 16017–16025.
97. D. O. Morgan, Principles of CDK regulation. Nature, 1995, 374(6518), 131–134. 98. V. Measday, L. Moore, R. Retnakaran, J. Lee, M. Donoviel, A. M. Neiman, and B. Andrews, A family of cyclin-like proteins that interact with the Pho85 cyclindependent kinase. Molecular and Cellular Biology, 1997, 17(3), 1212–1223. 99. H. Y. Tang, J. Xu, and M. Cai, Pan1p, End3p, and S1a1p, three yeast proteins required for normal cortical actin cytoskeleton organization, associate with each other and play essential roles in cell wall morphogenesis. Molecular and Cellular Biology, 2000, 20(1), 12–25. 100. M. C. Duncan, M. J. Cope, B. L. Goode, B. Wendland, and D. G. Drubin, Yeast Eps15-like endocytic protein, Pan1p, activates the Arp2/3 complex. Nature Cell Biology, 2001, 3(7), 687–690. 101. S. N. Naqvi, R. Zahn, D. A. Mitchell, B. J. Stevenson, and A. L. Munn, The WASp homologue Las17p functions with the WIP homologue End5p/verprolin and is essential for endocytosis in yeast. Current Biology, 1998, 8(17), 959–962. 102. A. A. Rodal, A. L. Manning, B. L. Goode, and D. G. Drubin, Negative regulation of yeast WASp by two SH3 domain-containing proteins. Current Biology, 2003, 13(12), 1000–1008. 103. A. H. Tong, B. Drees, G. Nardelli, G. D. Bader, B. Brannetti, L. Castagnoli, M. Evangelista, S. Ferracuti, B. Nelson, S. Paoluzi, M. Quondam, A. Zucconi, C. W. Hogue, S. Fields, C. Boone, and G. Cesareni, A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules. Science, 2002, 295(5553), 321–324. 104. D. C. Amberg, E. Basart, and D. Botstein, Defining protein interactions with yeast actin in vivo. Nature Structural Biology, 1995, 2(1), 28–35. 105. D. A. Holtzman, S. Yang, and D. G. Drubin, Syntheticlethal interactions identify two novel genes, SLA1 and SLA2, that control membrane cytoskeleton assembly in saccharomyces cerevisiae. Journal of Cell Biology, 1993, 122(3), 635–644. 106. D. T. Warren, P. D. Andrews, C. W. Gourlay, and K. R. Ayscough, Sla1p couples the yeast endocytic machinery to proteins regulating actin dynamics. Journal of Cell Science, 2002, 115(Pt 8), 1703–1715. 107. B. L. Drees, B. Sundin, E. Brazeau, J. P. Caviston, G. C. Chen, W. Guo, K. G. Kozminski, M. W. Lau, J. J. Moskow, A. Tong, L. R. Schenkman, A. McKenzie, 3rd, P. Brennwald, M. Longtine, E. Bi, C. Chan, P. Novick, C. Boone, J. R. Pringle, T. N. Davis, S. Fields, and D. G. Drubin, A protein interaction map for cell polarity development. Journal of Cell Biology, 2001, 154(3), 549–571. 108. Y. Ho, A. Gruhler, A. Heilbut, G. D. Bader, L. Moore, S. L. Adams, A. Millar, P. Taylor, K. Bennett, K. Boutilier, L. Yang, C. Wolting, I. Donaldson, S. Schandorff, J. Shewnarane, M. Vo, J. Taggart, M. Goudreault, B. Muskat, C. Alfarano, D. Dewar, Z. Lin, K. Michalickova, A. R. Willems, H. Sassi, P. A. Nielsen, K. J. Rasmussen, J. R. Andersen, L. E. Johansen, L. H. Hansen, H. Jespersen, A. Podtelejnikov, E. Nielsen, J. Crawford, V. Poulsen, B. D. Sorensen, J. Matthiesen, R. C. Hendrickson, F. Gleeson, T. Pawson, M. F. Moran,
PROTEIN RECOGNITION IN BIOLOGY
109.
110.
111.
112.
113.
114.
115.
116.
117.
118.
119.
120.
121.
122.
D. Durocher, M. Mann, C. W. Hogue, D. Figeys, and M. Tyers, Systematic identification of protein complexes in saccharomyces cerevisiae by mass spectrometry. Nature, 2002, 415(6868), 180–183. P. Soubeyran, K. Kowanetz, I. Szymkiewicz, W. Y. Langdon, and I. Dikic, Cbl-CIN85-endophilin complex mediates ligand-induced downregulation of EGF receptors. Nature, 2002, 416(6877), 183–187. I. Szymkiewicz, K. Kowanetz, P. Soubeyran, A. Dinarina, S. Lipkowitz, and I. Dikic, CIN85 participates in Cbl-b-mediated down-regulation of receptor tyrosine kinases. Journal of Biological Chemistry, 2002, 277(42), 39666–39672. N. L. Freeman, T. Lila, K. A. Mintzer, Z. Chen, A. J. Pahk, R. Ren, D. G. Drubin, and J. Field, A conserved proline-rich region of the saccharomyces cerevisiae cyclase-associated protein binds SH3 domains and modulates cytoskeletal localization. Molecular and Cellular Biology, 1996, 16(2), 548–556. A. Balguerie, P. Sivadon, M. Bonneu, and M. Aigle, Rvs167p, the budding yeast homolog of amphiphysin, colocalizes with actin patches. Journal of Cell Science, 1999, 112(Pt 15), 2529–2537. A. Wesp, L. Hicke, J. Palecek, R. Lombardi, T. Aust, A. L. Munn, and H. Riezman, End4p/Sla2p interacts with actin-associated proteins for endocytosis in saccharomyces cerevisiae. Molecular Biology of the Cell, 1997, 8(11), 2291–2306. A. M. Breton and M. Aigle, Genetic and functional relationship between Rvsp, myosin and actin in saccharomyces cerevisiae. Current Genetics, 1998, 34(4), 280–286. B. Govindan, R. Bowser, and P. Novick, The role of myo2, a yeast class V myosin, in vesicular transport. Journal of Cell Biology, 1995, 128(6), 1055–1068. G. C. Johnston, J. A. Prendergast, and R. A. Singer, The saccharomyces cerevisiae MYO2 gene encodes an essential myosin for vectorial transport of vesicles. Journal of Cell Biology, 1991, 113(3), 539–551. T. S. Karpova, S. L. Reck-Peterson, N. B. Elkind, M. S. Mooseker, P. J. Novick, and J. A. Cooper, Role of actin and Myo2p in polarized secretion and growth of saccharomyces cerevisiae. Molecular Biology of the Cell, 2000, 11(5), 1727–1737. D. W. Provance and J. A. Mercer, Myosin-V: head to tail. Cellular and Molecular Life Sciences, 1999, 56(3–4), 233–242. O. W. Rossanese, C. A. Reinke, B. J. Bevis, A. T. ´ Hammond, I. B. Sears, J. OConnor, and B. S. Glick, A role for actin, Cdc1p, and Myo2p in the inheritance of late golgi elements in saccharomyces cerevisiae. Journal of Cell Biology, 2001, 153(1), 47–62. D. Schott, J. Ho, D. Pruyne, and A. Bretscher, The COOH-terminal domain of Myo2p, a yeast myosin V, has a direct role in secretory vesicle targeting. Journal of Cell Biology, 1999, 147(4), 791–808. E. Bon, P. Recordon-Navarro, P. Durrens, M. Iwase, E. A. Toh, and M. Aigle, A network of proteins around Rvs167p and Rvs161p, two proteins related to the yeast actin cytoskeleton. Yeast, 2000, 16(13), 1229–1241. H. Friesen, K. Colwill, K. Robertson, O. Schub, and B. Andrews, Interaction of the saccharomyces cerevisiae
123.
124.
125.
126.
127.
128.
129.
130.
131.
132.
133.
19
cortical actin patch protein Rvs167p with proteins involved in ER to golgi vesicle trafficking. Genetics, 2005, 170(2), 555–568. B. Singer-Kruger, H. Stenmark, A. Dusterhoft, P. Philippsen, J. S. Yoo, D. Gallwitz, and M. Zerial, Role of three rab5-like GTPases, Ypt51p, Ypt52p, and Ypt53p, in the endocytic and vacuolar protein sorting pathways of yeast. Journal of Cell Biology, 1994, 125(2), 283–298. S. C. Yeo, L. Xu, J. Ren, V. J. Boulton, M. D. Wagle, C. Liu, G. Ren, P. Wong, R. Zahn, P. Sasajala, H. Yang, R. C. Piper, and A.L. Munn, Vps20p and Vta1p interact with Vps4p and function in multivesicular body sorting and endosomal transport in saccharomyces cerevisiae. Journal of Cell Science, 2003, 116(Pt 19), 3957–3970. B. Singer-Kruger and S. Ferro-Novick, Use of a synthetic lethal screen to identify yeast mutants impaired in endocytosis, vacuolar protein sorting and the organization of the cytoskeleton. European Journal of Cell Biology, 1997, 74(4), 365–375. K. Ashrafi, T. A. Farazi, and J. I. Gordon, A role for saccharomyces cerevisiae fatty acid activation protein 4 in regulating protein N-myristoylation during entry into stationary phase. Journal of Biological Chemistry, 1998, 273(40), 25864–25874. C. Landgraf, S. Panni, L. Montecchi-Palazzi, L. Castagnoli, J. Schneider-Mergener, R. Volkmer-Engert, and G. Cesareni, Protein interaction networks by proteome peptide scanning. PLoS Biology, 2004, 2(1), E14. S. Wicky, S. Frischmuth, and B. Singer-Kruger, Bsp1p/Ypr171p is an adapter that directly links some synaptojanin family members to the cortical actin cytoskeleton in yeast. Febs Letters, 2003, 537(1–3), 35–41. A. Balguerie, M. Bagnat, M. Bonneu, M. Aigle, and A. M. Breton, Rvs161p and sphingolipids are required for actin repolarization following salt stress. Eukaryotic cell, 2002, 1(6), 1021–1031. J. E. Gerst, L. Rodgers, M. Riggs, and M. Wigler, SNC1, a yeast homolog of the synaptic vesicle-associated membrane protein/synaptobrevin gene family: genetic interactions with the RAS and CAP genes. Proceedings of the National Academy of Sciences of the United States of America, 1992, 89(10), 4338–4342. L. Desfarges, P. Durrens, H. Juguelin, C. Cassagne, M. Bonneu, and M. Aigle, Yeast mutants affected in viability upon starvation have a modified phospholipid composition. Yeast, 1993, 9(3), 267–277. A. H. Tong, G. Lesage, G. D. Bader, H. Ding, H. Xu, X. Xin, J. Young, G. F. Berriz, R. L. Brost, M. Chang, Y. Chen, X. Cheng, G. Chua, H. Friesen, D. S. Goldberg, J. Haynes, C. Humphries, G. He, S. Hussein, L. Ke, N. Krogan, Z. Li, J.N. Levinson, H. Lu, P. Menard, C. Munyana, A. B. Parsons, O. Ryan, R. Tonikian, T. Roberts, A. M. Sdicu, J. Shapiro, B. Sheikh, B. Suter, S. L. Wong, L. V. Zhang, H. Zhu, C. G. Burd, S. Munro, C. Sander, J. Rine, J. Greenblatt, M. Peter, A. Bretscher, G. Bell, F. P. Roth, G. W. Brown, B. Andrews, H. Bussey, and C. Boone, Global mapping of the yeast genetic interaction network. Science, 2004, 303(5659), 808–813. J. F. Bazan, Structural design and molecular evolution of a cytokine receptor superfamily. Proceedings of the
20
134.
135.
136.
137.
138.
139.
140.
141.
142.
143.
144.
145.
146.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS National Academy of Sciences of the United States of America, 1990, 87(18), 6934–6938. A. M. de Vos, M. Ultsch, and A. A. Kossiakoff, Human growth hormone and extracellular domain of its receptor: crystal structure of the complex. Science, 1992, 255(5042), 306–312. P. A. Elkins, H. W. Christinger, Y. Sandowski, E. Sakal, A. Gertler, A. M. de Vos, and A. A. Kossiakoff, Ternary complex between placental lactogen and the extracellular domain of the prolactin receptor. Nature Structural Biology, 2000, 7(9), 808–815. R. S. Syed, S. W. Reid, C. Li, J. C. Cheetham, K. H. Aoki, B. Liu, H. Zhan, T. D. Osslund, A. J. Chirino, J. Zhang, J. Finer-Moore, S. Elliott, K. Sitney, B. A. Katz, D. J. Matthews, J. J. Wendoloski, J. Egrie, and R. M. Stroud, Efficiency of signalling through cytokine receptors depends critically on receptor orientation. Nature, 1998, 395(6701), 511–516. D. Chow, X. He, A. L. Snow, S. Rose-John, and K. C. Garcia, Structure of an extracellular gp130 cytokine receptor signaling complex. Science, 2001, 291(5511), 2150–2155. M. J. Boulanger, D. C. Chow, E. E. Brevnova, and K. C. Garcia, Hexameric structure and assembly of the interleukin-6/IL-6 alpha-receptor/gp130 complex. Science, 2003, 300(5628), 2101–2104. T. Hage, W. Sebald, and P. Reinemer, Crystal structure of the interleukin-4/receptor alpha chain complex reveals a mosaic binding interface. Cell, 1999, 97(2), 271–281. M. Rickert, X. Wang, M. J. Boulanger, N. Goriatcheva, and K. C. Garcia, The structure of interleukin-2 complexed with its alpha receptor. Science, 2005, 308(5727), 1477–1480. X. Wang, M. Rickert, and K. C. Garcia, Structure of the quaternary complex of interleukin-2 with its alpha, beta, and gammac receptors. Science, 2005, 310(5751), 1159–1163. Y. Murata, S. Takaki, M. Migita, Y. Kikuchi, A. Tominaga, and K. Takatsu, Molecular cloning and expression of the human interleukin 5 receptor. Journal of Experimental Medicine, 1992, 175(2), 341–351. J. Tavernier, R. Devos, S. Cornelis, T. Tuypens, J. Van der Heyden, W. Fiers, and G. Plaetinck, A human high affinity interleukin-5 receptor (IL5R) is composed of an IL5-specific alpha chain and a beta chain shared with the receptor for GM-CSF. Cell, 1991, 66(6), 1175–1184. R. Devos, Y. Guisez, S. Cornelis, A. Verhee, J. Van der Heyden, M. Manneberg, H. W. Lahm, W. Fiers, J. Tavernier, and G. Plaetinck, Recombinant soluble human interleukin-5 (hIL-5) receptor molecules. Crosslinking and stoichiometry of binding to IL-5. Journal of Biological Chemistry, 1993, 268(9), 6581–6587. S. Mita, A. Tominaga, Y. Hitoshi, K. Sakamoto, T. Honjo, M. Akagi, Y. Kikuchi, N. Yamaguchi, and K. Takatsu, Characterization of high-affinity receptors for interleukin 5 on interleukin 5-dependent cell lines. Proceedings of the National Academy of Sciences of the United States of America, 1989, 86(7), 2311–2315. J. J. Scibek, E. Evergren, S. Zahn, G. A. Canziani, D. Van Ryk, and I. M. Chaiken, Biosensor analysis of dynamics of interleukin 5 receptor subunit beta(c)
147.
148.
149.
150.
151.
152.
153.
154.
155.
156.
157.
interaction with IL5:IL5R(alpha) complexes. Analytical Biochemistry, 2002, 307(2), 258–265. K. C. Kirkbride, B. N. Ray, and G. C. Blobe, Cellsurface co-receptors: emerging roles in signaling and human disease. Trends in Biochemical Sciences, 2005, 30(11), 611–621. A. F. Lopez, M. J. Elliott, J. Woodcock, and M. A. Vadas, GM-CSF, IL-3 and IL-5: cross-competition on human haemopoietic cells. Immunology Today, 1992, 13(12), 495–500. P. D. Carr, S. E. Gustin, A. P. Church, J. M. Murphy, S. C. Ford, D. A. Mann, D. M. Woltring, I. Walker, D. L. Ollis, and I. G. Young, Structure of the complete extracellular domain of the common beta subunit of the human GM-CSF, IL-3, and IL-5 receptors reveals a novel dimer configuration. Cell, 2001, 104(2), 291–300. B. J. McClure, T. R. Hercus, B. A. Cambareri, J. M. Woodcock, C. J. Bagley, G. J. Howlett, and A. F. Lopez, Molecular assembly of the ternary granulocytemacrophage colony-stimulating factor receptor complex. Blood, 2003, 101(4), 1308–1315. J. M. Murphy, S. C. Ford, U. M. Wiedemann, P. D. Carr, D. L. Ollis, and I. G. Young, A novel functional epitope formed by domains 1 and 4 of the human common beta-subunit is involved in receptor activation by granulocyte macrophage colony-stimulating factor and interleukin 5. Journal of Biological Chemistry, 2003, 278(12), 10572–10577. F. Le, F. Stomski, J. M. Woodcock, A. F. Lopez, and T. J. Gonda, The role of disulfide-linked dimerization in interleukin-3 receptor signaling and biological activity. Journal of Biological Chemistry, 2000, 275(7), 5124–5130. R. Devos, Y. Guisez, G. Plaetinck, S. Cornelis, J. Tavernier, J. van der Heyden, L. H. Foley, and J. E. Scheffler, Covalent modification of the interleukin5 receptor by isothiazolones leads to inhibition of the binding of interleukin-5. European Journal of Biochemistry, 1994, 225(2), 635–640. M. Martinez-Moczygemba and D. P. Huston, Biology of common beta receptor-signaling cytokines: IL-3, IL-5, and GM-CSF. Journal of Allergy and Clinical Immunology, 2003, 112(4), 653–665. quiz 666. R. Alam, K. Pazdrak, S. Stafford, and P. Forsythe, The interleukin-5/receptor interaction activates Lyn and Jak2 tyrosine kinases and propagates signals via the Ras-Raf-1-MAP kinase and the Jak-STAT pathways in eosinophils. International Archives of Allergy and Applied Immunology, 1995, 107(1–3), 226–227. K. Pazdrak, B. Olszewska-Pazdrak, S. Stafford, R. P. Garofalo, and R. Alam, Lyn, Jak2, and Raf-1 kinases are critical for the antiapoptotic effect of interleukin 5, whereas only Raf-1 kinase is essential for eosinophil activation and degranulation. Journal of Experimental Medicine, 1998, 188(3), 421–429. T. van der Bruggen, E. Caldenhoven, D. Kanters, P. Coffer, J. A. Raaijmakers, J. W. Lammers, and L. Koenderman, Interleukin-5 signaling in human eosinophils involves JAK2 tyrosine kinase and Stat1 alpha. Blood, 1995, 85(6), 1442–1448.
PROTEIN RECOGNITION IN BIOLOGY 158. T. Adachi, S. Stafford, S. Sur, and R. Alam, A novel Lyn-binding peptide inhibitor blocks eosinophil differentiation, survival, and airway eosinophilic inflammation. Journal of Immunology, 1999, 163(2), 939–946. 159. N. Geijsen, J. Uings, C. Pals, J. Armstrong, M. McKinnon, J. A. Raaijmakers, J. W. Lammers, L. Koenderman, and P. J. Coffer, Cytokine-specific transcriptional regulation through an IL-5Ralpha interacting protein. Science, 2001, 293(5532), 1136–1138. 160. T. Morton, J. Li, R. Cook, and I. Chaiken, Mutagenesis in the C-terminal region of human interleukin 5 reveals a central patch for receptor alpha chain recognition. Proceedings of the National Academy of Sciences of the United States of America, 1995, 92(24), 10879–10883. 161. T. Ishino, G. Pasut, J. Scibek, and I. Chaiken, Kinetic interaction analysis of human interleukin 5 receptor alpha mutants reveals a unique binding topology and charge distribution for cytokine recognition. Journal of Biological Chemistry, 2004, 279(10), 9547–9556. 162. J. Tavernier, T. Tuypens, A. Verhee, G. Plaetinck, R. Devos, J. Van der Heyden, Y. Guisez, and C. Oefner, Identification of receptor-binding domains on human interleukin 5 and design of an interleukin 5-derived receptor antagonist. Proceedings of the National Academy of Sciences of the United States of America, 1995, 92(11), 5194–5198. 163. J. M. Woodcock, B. Zacharakis, G. Plaetinck, C. J. Bagley, S. Qiyu, T. R. Hercus, J. Tavernier, and A. F. Lopez, Three residues in the common beta chain of the human GM-CSF, IL-3 and IL-5 receptors are essential for GM-CSF and IL-5 but not IL-3 high affinity binding and interact with Glu21 of GM-CSF. Embo Journal, 1994, 13(21), 5176–5185. 164. M. V. Milburn, A. M. Hassell, M. H. Lambert, S. R. Jordan, A. E. Proudfoot, P. Graber, and T. N. Wells, A novel dimer configuration revealed by the crystal
165.
166.
167.
168.
169.
170.
21
structure at 2.4 A resolution of human interleukin-5. Nature, 1993, 363(6425), 172–176. T. Ishino, N. Robertsonm, and I. Chaiken, Cytokine Recognition by Human Interleukin-5 Receptor, in Vitamins and Hormones, G. Litwack (ed), Academic Press, New York, 2005, 321–344. B. P. England, P. Balasubramanian, I. Uings, S. Bethell, M. J. Chen, P. J. Schatz, Q. Yin, Y. F. Chen, E. A. Whitehorn, A. Tsavaler, C. L. Martens, R. W. Barrett, and M. McKinnon, A potent dimeric peptide antagonist of interleukin-5 that binds two interleukin-5 receptor alpha chains. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97(12), 6862–6867. T. Ishino, U. Pillalamarri, D. Panarello, M. Bhattacharya, C. Urbina, S. Horvat, S. Sarkhel, B. Jameson, and I. Chaiken, Asymmetric usage of antagonist charged residues drives interleukin-5 receptor recruitment but is insufficient for receptor activation. Biochemistry, 2006, 45(4), 1106–1115. S. J. Wu, J. Li, P. Tsui, R. Cook, W. Zhang, Y. Hu, G. Canziani, and I. Chaiken, Randomization of the receptor alpha chain recruitment epitope reveals a functional interleukin-5 with charge depletion in the CD loop. Journal of Biological Chemistry, 1999, 274(29), 20479–20488. P. Graber, A. E. Proudfoot, F. Talabot, A. Bernard, M. McKinnon, M. Banks, D. Fattah, R. Solari, M. C. Peitsch, and T. N. Wells, Identification of key charged residues of human interleukin-5 in receptor binding and cellular activation. Journal of Biological Chemistry, 1995, 270(26), 15762–15769. T. Ishino, C. Urbina, M. Bhattacharya, D. Panarello, and I. Chaiken, Receptor epitope usage by interleukin 5 mimetic peptide. Journal of Biological Chemistry, 2005, 280, 22951–22961.
5 Enzymology Tony Cass Institute of Biomedical Engineering, Imperial College London, London, UK
1 INTRODUCTION
Although the traditional processing of foodstuffs (baking, brewing, and other fermentations) involves enzyme-catalyzed reactions, the scientific understanding of enzyme catalysis developed over a period of about 50 years from the late nineteenth to mid-twentieth centuries. Following increased understanding of both the structure and function of enzymes their application in both traditional and nontraditional industries developed and in 2000 the global value of industrial enzymes was $2 billion with a growth rate of around 5–10% per annum. Within the field of biosensors and bioelectronics the drivers for using enzymes integrated into devices are to increase the latter’s specificity and to extend the range of molecules that can be acted upon. The role of enzymes in this respect stems both from their tremendous capability in molecular recognition and their catalytic efficiency. In the following sections the underlying molecular basis of both of these characteristics will be discussed and illustrated through pertinent examples. Despite this capability however it has to be appreciated that the properties of enzymes have evolved to meet the specific physiological requirements of the organisms in which they are found. While these properties may also be suitable for device applications this is by no means certain and developments over the past 20 years in DNA technology have provided the tools to precisely and selectively modify (“engineer”) proteins to better tailor
their properties for biosensors and bioelectronics. The methods for engineering proteins will form the penultimate section of this chapter. It is not feasible within the confines of this chapter to give a detailed account of enzyme structure and mechanism and the bibliography documents books1–5 and reviews6,7 that give more depth and further detail. 1.1
Enzymes as Catalysts and Their Classification
The word enzyme derives from the Greek word for yeast reflecting the observation of Eduard Buchner that cell-free extracts of yeast could carry out the conversion of sucrose to carbon dioxide, a reaction previously attributed only to the intact organism (a discovery for which he was awarded the Nobel Prize in 1907). The substance(s) that the enzyme acts upon is called the substrate and it is converted to the product. The realization that enzymes retained their function after release from living organisms opened the way to their purification and characterization as discrete entities. As more and more enzymes were purified and their catalytic activities determined, some method of classification was needed and this resulted in the Enzyme Nomenclature Commission, setup in 1955. The classification groups enzymes into six broad groups of activity: • Group 1 oxidoreductases
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
• • • • •
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Group Group Group Group Group
2 3 4 5 6
transferases hydrolases lyases isomerases ligases.
Within this there are further subdivisions depending upon the detailed reaction type, cosubstrate, and substrate resulting in a unique number for each enzyme and this is written as EC a.b.c.d. Thus the enzyme glucose oxidase, widely used in glucose sensors, is EC 1.1.3.4. This defines it as an oxidoreductase (1) acting on the CH–OH group of electron donors (1) with dioxygen as the electron acceptor (3) and having the specific substrate β-D-glucose (4). Originally the recommendations were published in book form (currently in the 6th edition) but now are most readily accessed via a web site, (http://www.expasy.org/enzyme/) which at the time of writing has around 4000 active entries. As we shall see later in this chapter, despite the diverse reactions catalyzed by enzymes and irrespective of detailed mechanistic considerations, there is now a general framework of enzyme catalysis into which specific cases can be fitted and which accounts for both the kinetic and chemical mechanisms that enzymes adopt. Like all catalysts, enzymes work by lowering the activation energy associated with the reaction and the rate accelerations can be in excess of 1015 -fold in some cases. The amount of an enzyme is defined in terms of the rate of substrate consumption and is a measure of catalytic activity rather than mass quantity. One Unit of activity is the amount of enzyme that converts 1 µmol of substrate to product in 1 min. As it is a measure of the catalytic potency the unit must be defined under specific conditions of temperature, pH, buffer conditions, substrate type, and concentration. The specific activity is the number of units in 1 mg of protein. Unlike many conventional catalysts however the rate enhancements are accompanied by specificity with respect to the substrate, the part of the substrate at which reaction takes place (regiospecificity) and the chirality of the substrates and/or products (stereospecificity). Taking the example of glucose oxidase, glucose is effectively the only sugar that is a substrate; moreover it is only the D-enantiomer as its β-anomer that is oxidized. It is this potential for high specificity that gives
enzymes their analytical utility as they can react with a single compound in a complex mixture. As we will see later both the specificity and rate enhancement are a consequence of the fit between the substrate and the enzyme’s active site.
1.2
Sources of Enzymes and Enzyme Immobilization
The commercial applications of enzymes are predominantly in the fields of foodstuffs, laundry detergents, and textiles when measured in terms of the quantities and value of the enzymes. In analytical (including biosensor) applications the quantities of enzymes used are much smaller and although their cost (per gram) is higher, the value lies in the device or kit rather than the enzyme itself. Amongst the commercial diagnostic enzymes, applications tend to be both as reagents to detect substrates or inhibitors and as labels in immunoassays. In the latter case there are relatively few widely used enzymes (alkaline phosphatase, horseradish peroxidase (HRP), glucose6-phosphate dehydrogenase), while in the former there are many more enzymes employed, leading to a highly fragmented market with many “boutique” suppliers. Traditionally enzymes have been isolated from their “natural” sources, that is those organisms that have for historical reasons provided an abundant and/or easily isolated source. Thus glucose oxidase is predominantly from Aspergillus niger where it was a by product of gluconic acid production, alkaline phosphatase is typically produced from calf intestine and peroxidase from horseradish roots. Once a particular source is established then a combination of regulatory requirements and familiarity tends to fix this over time. More recently as the demand for enzymes from more esoteric or difficult-to-culture organisms has grown, and with the establishment of suitable manufacturing facilities, commercial recombinant enzymes have become more common. In many commercial applications of enzymes they may be immobilized, that is restricted to a particular location. In the context of biosensors and biochips this has the advantage that the enzyme remains associated with the rest of the device rather than diffusing into solution where it will become diluted. This also allows continuous use of
ENZYMOLOGY
the device and is especially important in instances where contamination is to be avoided, for example when used in vivo. A variety of strategies have been employed to immobilize enzymes including attachment to a solid phase, entrapment in a polymer, and retention behind a membrane. Many of these methods were developed for large-scale bioreactor processes such as enzymatic processing of foodstuffs or biotransformations of fine chemicals. Often the scale was sufficiently large and the enzymes sufficiently cheap that the process did not require high retention of catalytic activity. In biosensors and biochips applications the situation is more challenging, as there is often a limited amount of surface on which to immobilize the enzyme, both the enzyme and the surface need to retain most of their function and the enzyme deposition may need high spatial precision. Whether on large or small scale the immobilization of enzymes introduces an additional reaction step as, unlike soluble enzymes, the spatial restriction now introduces a mass transport step to bring the substrate from the solution to the site of the enzyme.
2 ENZYME KINETICS
The most obvious feature of enzymes is their catalytic activity and it is therefore natural to start our discussion with the kinetics of enzymes. What follows is a brief summary of the standard treatment of enzyme kinetics and more detailed descriptions can be found in text books.4,5 The original description of enzyme kinetic mechanisms is attributed to Michaelis and Menten, who assumed that enzyme catalysis proceeded through a noncovalent complex between enzyme and substrate that could breakdown either to product(s) or to the starting materials: E+S
Km −−− − −− − −
E·S
kcat −−−−→
E+P
(1)
In this model the rate of product formation, v, is given by: v=
kcat [E] · [S] Km + [S]
(2)
Michaelis and Menten assumed that the enzyme–substrate complex (often called the
3
Michaelis complex ) is in equilibrium with the enzyme and substrate and that the Michaelis Constant, Km , is the substrate dissociation constant. This in turn assumes that the rate of substrate dissociation is fast relative to the catalytic rate, kcat , an assumption that does not always hold. Briggs and Haldane subsequently showed that the equilibrium assumption was not necessary and that a more general case is when the Michaelis complex is in a steady state with respect to both starting materials and products (i.e., d[E · S]/ dt = 0): E+S
k1 −−− − −− − − k−1
E·S
k2 −−−−→
E+P
(3)
The steady state is usually reached very soon (typically less than a second) after the enzyme and substrate are mixed and in this case the rate equation is given by: v=
k2 [E] · [S] k−1 + k2 + [S] k1
(4)
The collection of rate constants in the denominator is the Haldane constant (Ks ). Despite the more general formulation of equation (4) most enzyme kinetics are expressed in terms of equation (2) and in many cases kcat [E] is referred to as Vmax the maximal velocity. The functional form of equation (2) is a hyperbola and the relationship between substrate concentration and reaction rate is shown in Figure 1. The treatment so far assumes a single substrate; however, most enzymes have two or more substrates and our treatment of the kinetics needs to take this into account. In the simplest case the second substrate is water and its concentration can be considered to be constant so these enzymes (hydrolases) behave as single-substrate enzymes. Before we look at the complexities of multisubstrate enzymes it is worth turning to the implications of equation (2) and Figure 1 for the use of enzymes as analytical reagents in biosensors and biochip devices. The classes of analyte measured with enzyme-based sensors are shown in Table 1. Where the enzyme is being used to measure [S] through its conversion to a detectable product, the first point is to note is that the relationship between the rate and the substrate (analyte) concentration
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS 1
1 ∆
0.75
0.75
Normalized rate
Normalized rate
4
0.50
0.25
0
0.50
0.25 ∆
0 0
2.5
5 [S] /Km
7.5
10
Figure 1. The dependence of the rate of an enzyme reaction on the substrate concentration. The substrate concentration is expressed as a multiple of Km , while the rate is normalized to a maximum rate of 1. Note that at [S]/Km = 1 the rate is 0.5 of the maximal rate. Table 1. Classes of analytes that can be determined with enzyme-based sensors
Target analyte class
Substrate
Substrate
Enzyme
Saturating
Inhibitor
Ki
Comments Highest precision and linearity Minimizes errors due to errors in [S] Depends on mechanism of inhibition
is only linear for values of [S] that are much less than Km . It is usually the case that rate of reaction translates to the sensor output and hence Figure 1 can be recast as signal versus analyte concentration. If we assume that the uncertainty (error) in the output is a constant proportion of the value then the error in the derived analyte concentration at low analyte concentrations will be smaller than at high analyte concentrations where the slope of the curve becomes shallower. Using equation (2) we see that an error in v of 5% at v = 0.1 of its maximum value leads to an error in analyte concentration of 6% while a 5% error in v at v = 0.9 of its maximum value results in an error in analyte concentration of approximately 90%. At v = 0.5 of its maximum value there would be approximately a 20% error in analyte concentration. This is illustrated graphically in Figure 2. As these calculations show, enzyme sensors are most reliable when measuring analyte concentrations below Km .
0
2.5
5 [S] /Km
7.5
10
Figure 2. Effects of errors in the measured rate on the derived concentration at medium and high rates. Note that at higher rates there is a larger error in the derived concentration.
As equation (2) shows, the rate (sensor output) is proportional to the amount of enzyme present and is maximal at high substrate concentration (saturating substrate). Figure 3 shows how the rate depends on enzyme concentration for a range of the latter. There are three broad classes of measurement where the enzyme is the analyte rather than the reagent. One of these is in clinical diagnostics where an elevated level of the enzyme in the blood is a marker for disease. The second is where the enzyme is used as a label in an affinity assay (e.g., in immunoassays) and finally where the target analyte is an enzyme inhibitor. The saturation of the dose response at high substrate concentration has the advantage that the rate becomes relatively independent of the substrate concentration thus reducing errors associated with the amount of substrate added.
2.1
Enzyme Inhibition
Many circumstances can result in loss of enzyme activity, for example the pH may not be optimal or the enzyme may have become denatured or degraded. A further reason for loss of catalytic activity is inhibition where a molecule binds to the enzyme and lowers its activity. The three commonest mechanisms of inhibition are where the inhibitor competes with the substrate for a common binding site (competitive inhibition), where the inhibitor binds elsewhere on the enzyme and lowers the turnover rate (noncompetitive
ENZYMOLOGY
5 1
1
No inhibitor
0.75 Rate
0.7 0.50
0.5
0.25
0.2
Relative rate
1
Competitive inhibitor
0.75
Noncompetitive inhibitor Uncompetitive inhibitor
0.50 0.25 0
0 0
2.5
5 Analyte
7.5
10
0
10 20 Normalized (Substrate)
30
Figure 3. Dose–response characteristics as a function of enzyme concentration. The values on the right-hand side show the relative levels of enzyme for each curve.
Figure 4. The effects of different types of inhibitor on the rate versus substrate concentration curves for an enzyme-catalyzed reaction.
inhibition) and where the inhibitor binds only to the enzyme–substrate complex and lowers its turnover rate (uncompetitive inhibition). These can be shown schematically as:
remains as Km while the maximum velocity is decreased to Vmax /α . Uncompetitive: the inhibitor only binds to the E · S complex so α = 1 and both the Michaelis constant and maximum velocity are decreased to Km /α and Vmax /α , respectively.
E+S Ki
Km
E·S Ki′
I
E·I
kcat
E+P
These cases are shown graphically in Figure 4.
I
E·S·I
3 ENZYMES: CHEMICAL MECHANISMS
To show quantitatively the effect of inhibition on enzyme kinetics it is common to use the inhibitor constants α and α where: α =1+
[I ] Ki
and α = 1 +
[I ] Ki
(5)
The Michaelis–Menten equation can then be rewritten as follows: v=
Vmax (1/α )[S] Km (α/α ) + [S]
(6)
This leads to the common forms of inhibition: Competitive: the inhibitor binds to E competitively with S so α = 1 and the Michaelis constant becomes Km α (i.e., greater than Km ) while the maximum velocity remains as Vmax . Noncompetitive: the inhibitor binds to both E and E · S with equal affinity (i.e., away from the active site) so α = α and the Michaelis constant
Kinetic models of enzyme reactions are consistent with a reaction whereby the enzyme and substrate(s) form a complex that subsequently breaks down to yield the product(s). The formation of the Michaelis complex goes some way toward explaining the specificity of enzymes in both recognizing their substrates and in the reaction that they catalyze. However the kinetic models give no indication of how enzymes achieve their rate enhancements or the exact chemical mechanism by which they act. While each enzyme is distinct in its chemical mechanism there are some general guiding principles. Like all chemical reactions enzyme catalysis passes through a high-energy state (the transition state) and the rate of reaction is determined by the height of this barrier. In the case of the uncatalyzed reaction the height of the barrier is shown by the dashed line in Figure 5, when the enzyme is present the substrate is bound and so has a lower free energy than the free substrate. If the energy
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS A
[S ]†
X
Y
B + H2O
AXH + BYOH
X = O, NH Y = CO, PO3 Scheme 1. Typical, hydrolase-catalyzed reactions.
While transition state stabilization offers a general explanation of enzymatic rate enhancement the exact chemical mechanism of enzyme action varies greatly depending upon the nature of the substrate and the reaction catalyzed. From the perspective of biosensors and bioelectronics the two most significant classes of enzymes employed are the oxidoreductases and the hydrolases. In both cases the chemical mechanisms have been the subject of extensive investigation.
Free energy
[E ⋅ S ]†
E+S
[E ⋅ P ]†
E⋅S
E+P
E⋅P
Extent of reaction
Figure 5. Reaction profile of an enzyme-catalyzed reaction (solid line) and an uncatalyzed reaction (dashed line) showing the effect of transition state stabilization.
barrier from the enzyme bound substrate to the enzyme bound transition state is to be lower, then the transition state must be relatively more tightly bound and it is this transition state stabilization that provides a unifying theory to account for enzymatic rate enhancementsa .6,7 The nature of the transition state and the interactions through which the enzyme effects its stabilization depend upon the reaction being catalyzed. Many of the suggested mechanisms of catalysis for particular enzymes, for example, can ultimately be seen as specific routes to transition state stabilization. The transition state typically exists for the duration of a single bond vibration (around 10−14 s) and is therefore not readily amenable to structural characterization. Insight into the nature of the transition state may be obtained by applying the Hammond postulate; this asserts that the structure of the transition state is close to that of the preceding or succeeding intermediate.
3.1
Hydrolases
These enzymes catalyze the overall reaction shown in Scheme 1. The enzymes’ catalytic group is a nucleophile and the mechanism often proceeds through an intermediate, covalently bound to the enzyme. Hydrolase reactions usually involve additional active site groups that act as acid/base catalysts (either Bronsted or Lewis) and others that stabilize the transition state (typically through stabilizing developing negative charge). As an illustration of the level of detail that a combination of kinetic, chemical, and structural tools can yield, two examples are discussed. These are bacterial alkaline phosphatase (BAP) and acetylcholine esterase (AChE). The former is a zinc containing enzyme with broad activity in the hydrolysis of phospho monoesters while the latter is a highly specific esterase that is irreversibly inhibited by organophosphorous pesticides and nerve agents. Physiologically BAP acts to release phosphate form phospho monoesters under conditions of phosphorous limitation. Its structure has been determined to high resolution (Figure 6) and the active site contains two zinc and one magnesium ion as well as the nucleophilic serine residue (phosphate acceptor) and an arginine residue to bind the phosphate group of the substrate.8 Figure 7 shows the active site with a phosphate ion bound and catalytically important residues indicated.
ENZYMOLOGY
7
Figure 6. The X-ray structure of alkaline phosphatase from Escherichia coli. The dimer interface runs down the middle of the structure and the metal ions and phosphate are shown as spheres.
Figure 7. A close up picture of the active site of alkaline phosphatase from E. coli .
AChE catalyzes the hydrolysis of acetylcholine (X = O) and acetylthiocholine (X = S) as well as many other ester substrates but has the distinction of having a near-diffusion-controlled second-order rate constant (kcat /Km = 109 M−1 s−1 ).9 The mechanism of the reaction involves an active site serine residue that undergoes acetylation in the first step of the reaction with a nearby histidine acting as a general acid/base catalyst. In the second step the acylenzyme intermediate is then hydrolyzed by an active site water molecule. An interesting structural feature is that the substrate is deeply buried down a hydrophobic “gorge” in the enzyme (likely the main interaction site with nonphysiological aromatic ester substrates). A cluster of
Figure 8. The active site of Torpedo california acetylcholinesterase with a covalently bound methyl phosphate group following reaction with the nerve agent sarin.
negatively charge residues that bind the quaternary amine group on acetylcholine seem to be responsible for this. The enzyme is potently inhibited by organophosphorous compounds through phospho transfer to the catalytic serine residue (Figure 8).
3.2
Oxidoreductases
Glucose oxidase (GOx) is a typical flavoprotein oxidase that plays a role in many glucose sensors. It has been extensively investigated with respect to
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
its chemical mechanism10,11 and a high-resolution X-ray structure is available. The kinetics is a strictly ordered BiBi ping pong mechanism, during the catalytic cycle the active site flavin adenine dinucleotide (FAD) is alternately reduced and oxidized, passing through a stable (in the absence of oxidant) dihydroflavin (FADH2 ) intermediate. This means that the two half-reactions can be individually investigated. The most thoroughly studied GOx is that from A. niger and its structure is shown in Figure 9. It is a homodimer with a subunit molecular weight of around 80 kDa and is both O- and N-glycosylated, primarily by mannose. The mechanism of the enzyme has been reviewed several times and most recently by Leskovac et al.10 This section will therefore covers the basic aspects of the enzyme and more detailed discussion can be found in the reviews. The reducing half reaction is highly specific for β-D-glucose and most probably proceeds through hydride transfer of the anomeric proton to the N5 atom of FAD, as shown in Scheme 2. The hydride (electron) transfer is coupled to two proton transfer reactions of groups on the enzyme that result in the formation of gluconolactone which dissociates from the enzyme and undergoes nonenzymatic hydrolysis to produce gluconic acid. The significant kinetic isotope (kH /kD ≈ 5) effect suggests that the hydride transfer step is
H OH H
O
HO O
HO H
H
:B
OH
H
H O N
HN
BH
O
N
N R
H OH H
O
HO O
HO H
OH
H O H N HN
HO
N
N R
Scheme 2. The hydride transfer reaction from glucose to the flavin center in glucose oxidase.
Figure 9. The glucose oxidase monomer showing the buried FAD moiety and the residual glycans.
rate limiting and a variety of structural kinetic and mutagenesis evidence points to the base being Glu412 and the acid being His516 (Figure 10). The oxidative half reaction, unlike the reductive one, is quite unspecific and kinetically more complex. Physiologically dioxygen reacts with FADH2 in two one-electron transfer steps, yielding initially the flavosemiquinone–superoxide intermediate and then the final products (oxidized flavin and hydrogen peroxide). It is the first electron transfer step that is likely to be rate limiting as the reaction of superoxide with flavosemiquinones is known to occur at near-diffusion-limited rates (around 109 M−1 s−1 ). Molecular dynamics simulations suggest
ENZYMOLOGY
Glu412 His559
His516
9
Another well-studied class of oxidants are quinones and unlike the ferrocenes the kinetics in this case are determined by the acid/base chemistry of the oxidant as well as the enzyme.10 Peroxidases are a diverse group of enzymes that catalyze the following reaction: H2 O2 + 2e− + 2H+ −−−→ 2H2 O
Figure 10. The active site of glucose oxidase.
that it is histidine 516, in its protonated state, that plays a key role in lowering the outer sphere reorganization energy in the first electron transfer step.12 A wide variety of alternative (nonphysiological) oxidants have been shown to react with glucose oxidase and these include both two- and oneelectron donors. Among the former are quinones while the latter include metal ion complexes of ruthenium and osmium as well as organometallic compounds, especially ferrocenes. In many cases the oxidants have been employed in electrochemical sensors and have not been extensively characterized in terms of their reaction kinetics. Those oxidants that have been subjected to a detailed kinetic analysis have shown that structural factors are important in controlling reaction rates; however, as changes in structure also change the redox potential (i.e., the driving force), it is not easy to uncouple these two effects. Steady-state kinetics have led Ryabov and coworkers to conclude that there is a noncovalent (Michaelis) complex formed between the enzyme and the oxidant.13 In a study of over 50 ferrocene derivatives with glucose oxidase Forrow et al.14 concluded that steric factors, along with charge were the main determinants of reaction rate (as determined by cyclic voltammetry). In general, negatively charged ferrocenes reacted more slowly. Within a homologous series of monosubstituted derivatives there was a linear free energy relationship between rate constant and redox potential.13
The electrons can come from proteins (e.g., cytochrome c peroxidase), phenols (plant peroxidases), thiols (glutathione peroxidase), or even halide ions (myelperoxidase). Just as in the case of the oxidases the oxidative and reductive halfreactions can be separately investigated and the intermediates characterized. One of the best-studied peroxidase is that from horseradish roots (HRP). Like many plant peroxidases (such as those from peanut and soybean) it has a redox center with a ferric protoporphyrin IX group with a histidine residue as the fifth ligand. Reaction with hydrogen peroxide generates an oxyferryl cation radical. This intermediate (“compound I”) is then reduced to the oxyferryl (“compound II”) state and finally back to the resting, ferric, state in oneelectron transfers. The formation of compound I is fast and for many years there was no evidence of a Michaelis complex (“compound 0”); however, there is now spectroscopic evidence for such a species from low-temperature stopped flow studies. As in many redox enzymes there are associated proton transfers and the distal histidine residue acts as a general acid with an arginine residue also on the distal side helping to stabilize the developing positive charge. Various lines of evidence are consistent with the electron transfer to the donor occurring through the heme edge and the rate-limiting second electron transfer is associated with the reduction of compound II to the native state. As with glucose oxidase there have been extensive structure–function studies, taking advantage of the wide substrate specificity for the reducing agent. Transient kinetics using stopped flow is consistent with a Marcus type behavior in the electron transfer reaction, reflecting the different substrate affinities and electron transfer distances in compound I and compound II.15,16
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
4 ENZYME IMMOBILIZATION
Many applications of enzymes in biochips (sensors, devices, arrays) require that they be held on or very close to a solid surface, that is they are immobilized.17 Historically enzyme immobilization first appeared commercially in the design and operation of bioreactors for enzyme-catalyzed transformations. These typically operated on a large scale, for example in the production of 6aminopenicillanic acid, a precursor of semisynthetic penicillins. In these large-scale processes the solid phases tended to be low-cost rigid porous materials to which enzymes could be bound by covalent or noncovalent interactions. Similarly the enzymes were robust, often of high-specific activity, and typically carried out straightforward reactions, primarily hydrolysis. This combination of cheap enzymes and porous supports resulted in a high loading of catalytic activity such that substantial denaturation of the enzyme could be tolerated. In contrast to this situation, with biochip applications the surfaces are often planar and of low surface area, the enzymes are required to carry out more complex reactions and so both retention of catalytic activity and surface functionality are critical. This places additional demands on the immobilization methods and the specifics of these will be covered later; however, in the next section we will consider the general aspects of immobilization on the kinetic properties of enzyme.
4.1
Immobilized Enzyme Kinetics
Immobilization of enzymes introduces an additional step into the kinetics as the enzyme and the substrate are separated in space. On first exposure to substrate those molecules immediately adjacent to the immobilized enzyme are converted to product, and to sustain further reaction more substrate has to be transported to the surface. This will occur by diffusion in the absence of any other processes, due to the concentration gradient between the surface and the bulk solution. However there is also often an additional transport process in the shape of convection that increases the rate at which more substrate arrives at the surface. Irrespective of the exact mechanism of mass transport, the kinetics of an immobilized enzyme can be considered as a two-step process:
Step 1: Mass transport of substrate to the electrode surface. Step 2: Catalytic conversion of substrate to product. Figure 11 illustrates the two processes and the observed reaction rate will be determined by a ratecontrolling step, either transport or catalysis. A further complication in investigating the kinetics of immobilized enzymes is that the immobilization itself can alter their properties in the absence of any mass transport–dependent effects. There are then three types of property that need to be distinguished: Inherent Properties that are a consequence of the threedimensional structure of the enzyme in solution. Intrinsic Properties that are due to the immobilization in the absence of any mass transport effects. Apparent (or observed) Properties of an immobilized enzyme that also include mass transport effects. Intrinsic properties can include not just changes in the enzyme’s properties following immobilization but also effects of the enzyme’s microenvironment. Such effects include partitioning where the local substrate concentration at the enzyme surface is altered by the local physicochemical properties. As an example if the enzyme layer is charged then protons will be excluded (positively charged layer)
Immobilized enzyme surface
10
Transport step Substrate
Substrate
Catalysis step Product
Figure 11. Reaction rate of immobilized enzyme with transport and catalysis steps.
ENZYMOLOGY
or concentrated (negatively charged layer) thereby altering the intrinsic pH optimum. A further additional kinetic step that needs to be included is in the case where the product of the reaction at the immobilized enzyme surface undergoes a further reaction at the solid phase to generate a signal. A typical circumstance in which this occurs is where the solid phase is an electrode at which the product of the enzyme reaction is oxidized or reduced, generating a current. In general, solving coupled transport/reaction differential equations cannot be done analytically and a numerical solution is often necessary; however, it is instructive to consider limiting cases of the transport/reaction process where either transport is limiting or catalysis is limiting. The latter situation is one where the transport of substrate to the enzyme surface is sufficiently fast to “keep up” with the catalytic reaction, the surface concentration of substrate is replenished and there is little depletion. This means that the local concentration of substrate in the vicinity of the active site is close to the bulk concentration and, in the absence of any intrinsic effects, the properties of the enzyme are close to those measured for the soluble form (i.e., they are close to the inherent properties). When the transport step is rate limiting, the surface concentration of substrate is depleted relative to the bulk concentration and hence the apparent kinetic properties change. In effect there is an excess of enzyme activity over that required to turnover all the substrate arriving at the surface. In particular the apparent activity (expressed in units mg−1 enzyme) is decreased and the apparent Km is increased. This latter effect can obviously perturb the dynamic range of enzyme-based sensors and reduce the sensitivity. An additional enzyme property that is dependent on the nature of the rate-limiting step is the apparent stability. Under transport limitation, because there is an “excess” of catalytic activity over that necessary to keep up with the mass transport rate the immobilized enzyme can suffer loss of activity without affecting the overall rate of reaction (and hence signal generation). This means that the immobilized enzyme appears more stable than the soluble form when, for example, the stability is expressed as the halftime for loss of activity. The above description of the kinetics of immobilized enzymes is quite general and demonstrates how controlling the balance between transport,
11
microenvironment, and catalysis can change the device response characteristics markedly. In the following section some common device formats will be examined and the effects on performance discussed. Product consumption In many enzyme sensors a product of the reaction is consumed at the surface in generating a signal. Probably the best example of this is in amperometric enzyme sensors where an electroactive product is oxidized or reduced at an applied potential, thereby generating a current. The product consumption reaction introduces an additional kinetic step that may or may not be rate limiting and, exactly as in the comparison of transport and catalysis limitations, this may affect the apparent properties of the enzyme. Membrane-coated devices In many immobilized enzyme devices there is a membrane coating over the device and this leads to an additional mass transport step as well as a partitioning step. The additional mass transport step comes from an internal diffusion process once the substrate has crossed the membrane behind which there is effectively a thin layer of solution. Altering either the membrane permeability and/or its thickness has been a widely used strategy in membrane sensors and can affect device characteristics quite dramatically. Microareas The discussion of diffusional mass transport has assumed that the active area over which the enzyme is immobilized is large relative to the bulk solution thickness. Where this is the case, the edge effects can be neglected and so-called semiinfinite diffusion conditions apply. As the area of the immobilized enzyme is decreased, for example in enzyme microarrays, this condition no longer holds and there is a change from linear (onedimensional) to hemispherical (two-dimensional) diffusion. This results in the flux of substrate to the enzyme surface being much greater. The combination of increased flux and decreased enzyme loading (smaller surface area) results in a catalysislimited kinetic regime and also in an insensitivity to convective mass transport.
12
4.2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Immobilization Methods
These can be broadly grouped into two classes: entrapment and attachment. As illustrated in Figure 12, entrapment retains the enzyme in solution and uses a selective permeability barrier to prevent it diffusing away from the surface. Entrapment can entail the use of either a macroscopic membrane to trap a thin layer of enzyme solution at the surface or a polymer that traps enzyme molecules within aqueous pockets. The use of a macroscopic membrane is simple in concept and has the added advantage of excluding macromolecules that may foul (irreversibly adsorb to) the underlying solid phase as well as other interferents. Macroscopic membranes however have a number of drawbacks that render their use rather limited, they are prone to leakage if the seal between the membrane and the solid phase is not good, they are difficult to apply to microdevices in a spatially controlled manner and the thinner membranes (to minimize diffusional resistance and lower response times) are mechanically fragile. Macroscopic membranes therefore tend to be an additional layer over a preimmobilized enzyme where they can be cast or spun on. Product
Substrate Permselective membrane
Solid phase
(a)
Solid phase
(b)
Figure 12. Examples of enzyme entrapment based on macroscopic membranes (a) or polymers (b).
Polymer entrapment can be via an in situ polymerization from monomers18 or by using preformed polymers that are soluble under one set of conditions and precipitate when the physical or chemical conditions are altered.19 Both the in situ polymerization and controlled precipitation lend themselves to spatially controlled deposition, particularly with amperometric sensors where a potential is applied to the underlying sensor. In situ polymerization has been extensively employed with polymers that can be generated through oxidation (or, more rarely, reduction) of the monomer. Examples include polypyrrole, polythiophene, polyaniline, and polyphenol. The resulting polymer may be either electrically conducting or insulating, and the film morphology depends on the monomer, the polymerization conditions, and the counterion (if the film is charged). Controlled precipitation of preformed polymers has been achieved electrochemically by using water electrolysis to generate a local decrease in pH that causes the polymer (typically a polyacid such as polyacrylic acid) to precipitate on the electrode. Potential pulsing schemes have been put to good use to give fine control over the deposition process. The materials used to entrap enzymes do not need to be exclusively organic and the method of solgel processing has been adapted to enzyme immobilization, particularly those based on silica. The silica structures (“monoliths”) combine an open porous structure with good mechanical rigidity and have a high capacity for enzyme activity.20 Attachment methods form covalent or noncovalent bonds between the protein and the surface, and there are three broad approaches to achieving this. The first is where nonspecific, noncovalent interactions occur between surface functional groups and amino acid residues on the protein. The interactions may be electrostatic or van der Waals but in either case the strength of binding will be a function of the solution conditions (e.g., pH or ionic strength) as well as the protein and surface chemistries.21 Proteins can thus desorb or undergo surface reorganizations when exposed to different solution conditions and this will have implications for their catalytic activity. As these noncovalent interactions are individually weak, appreciable binding only occurs where there are multiple points of contact. This can be significant
ENZYMOLOGY
where electrostatic interactions are responsible for immobilization. As protein surfaces show a heterogeneous charge distribution, patches of residues with the opposite charge can dominate the interaction with the surface even where the net charge has one value. Moreover as surfaces are often heterogeneous with respect to their functional groups, multiple different noncovalent attachment modes may be present, and a particular problem with nonpolar surfaces is surface-induced denaturation and aggregation. During the process of protein folding the hydrophobic driving forces bury nonpolar residues in the interior of the protein. Where there is a hydrophobic surface it may now be energetically favorable for the protein to unfold at the surface so that the nonpolar residues bind to the surface. Exposure of the hydrophobic core then induces further unfolding and subsequent aggregation of other enzyme molecules resulting ultimately in a nonfunctional surface. This process is illustrated in Figure 13 and can be minimized through making the device surface as hydrophilic as possible, often by using coatings such as polyethyleneglycol (PEG).22 Nonspecific, covalent attachment to surfaces is essentially a process of covalent cross-linking between functional groups on the protein and on the surface. The most commonly targeted amino acid is lysine a consequence of its high abundance (6%) along with its surface localization and nucleophilic reactivity. The reactivity of any given lysine residue (or the N-terminal amino group) depends on a variety of factors some of which can be manipulated (such as pH), while others are
Approach/contact Diffusion
Adsorption Dehydration
13
residue specific (pKa , accessibility, local environment). In favorable circumstances there may only be a single reactive amino group, but, in general, multiple sites of attachment can occur. Amino acid residues are not the only groups that can be used for nonspecific covalent attachment; glycan groups can be readily modified, often without significant effects on the catalytic activity. Less common is the attachment through a prosthetic group (such as flavin or heme) where the enzyme can be reconstituted around the immobilized group. While the functional groups on the enzyme surface are relatively limited there is considerable scope for modifying the surface through polymers, self-assembled monolayers (SAMs), and oligomeric linkers. The use of flexible links between the protein and the surface has advantages in allowing conformational changes to occur in the enzyme during the catalytic cycle. Affinity attachment relies on specific molecular recognition between the protein and the surface. One of the earliest and most widespread instances of affinity attachment uses the avidin/biotin couple and the reasons for this are several fold.23 Biotinylation of proteins can be readily achieved, often with little loss of activity, and the biotinylated protein can be readily characterized. Avidin (or its bacterial equivalent streptavidin) is a robust protein that is readily immobilized without significant loss of activity and as it has four identical subunits each with a biotin binding site immobilization leaves at least one available binding site. Finally the (noncovalent) interaction between biotin and (strept)avidin is of high affinity (KD 10−15 M), making it virtually irreversible. Other examples of
Irreversible adsorption Denaturation
Material surface = Water
Solid phase
= Protein
Figure 13. Processes leading to surface-induced inactivation of proteins.
Figure 14. Representation of carrier binding surfaces with immobilized enzymes.
14
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
affinity attachment include the use of anti enzyme antibodies or lectins, such as concanavalin A, with glycoproteins. The typical situation following enzyme immobilization is shown in Figure 14, where the immobilized molecules are spatially disordered and randomly oriented arrays on the surface with any unfilled sites are capped with a hydrophilic polymer. The use of genetically introduced immobilization tags is discussed in the next section.
5 PROTEIN ENGINEERING
The rapid development of tools for manipulating the sequence of DNA with single-base precision and the range of protein expression systems for producing altered proteins from modified genes has opened up the possibility of making directed changes in enzymes to alter or enhance their function in a variety of ways. The reasons for wishing to do this in the context of biosensors and bioelectronics arise from the observation that the structures of enzymes are a consequence of their physiological functions and have evolved to maximize their “fitness” in that context. Once they are removed from their physiological context, only by chance will their properties be suitable for the particular application for which they are being used. There are two broadly complementary approaches that have been used to engineer enzymes. The first, often referred to as “rational” design, predicts the changes needed to give a particular alteration in function, while the second, “evolutionary design”, makes random changes and then selects or screens for the desired properties. The two approaches are compared in Table 2 and it can be seen that both start from the cloned gene for the protein of interest.
Recent large-scale genome sequencing projects have made available the sequences of large numbers of genes and it is a simple task to obtain the required DNA. Changing the sequence of this DNA can be readily done in vitro either by sitespecific changes or at random. The modified DNA is then introduced into an independently replicating piece of DNA (the vector) to form a construct that is then introduced into the expression host and the modified protein produced. A workflow from DNA to protein is shown in Figure 15. The types of changes in the DNA sequence that are typically carried out in protein engineering experiments include base changes (giving rise to amino acid changes or point mutations), base removal (“deletions”), introducing additional sequences at the ends of the protein (“tagging”), introducing additional sequences within the protein (“loop insertions”),24 and joining two genes together (“protein fusions”). There are a number of methods for in vitro mutagenesis and nearly all involve the PCR, in which the DNA is modified and amplified using synthetic DNA fragments known as primers. Methods for engineering proteins for biosensor and bioelectronics applications have been reviewed and technical details are described more fully in those publications.25–27 One of the advantages of using gene technology to engineer enzymes for biosensor and bioelectronics applications is that a modular design approach can be adopted whereby the final protein can be considered to be comprised of a set of functional modules. Depending upon the application these could be as follows: A signaling module The part of the protein that is responsible for communicating externally via an electronic or photonic exchange with some device.
Table 2. A comparison of “rational design” and “evolutionary design” approaches to protein engineering
Cloned gene X-ray structure Screening/selection method Source of mutation Computational needs PCR: polymerase chain reaction.
Rational design
Evolutionary design
Necessary Necessary Low throughput: individual mutants Mutagenic primer Modest to high
Necessary Not needed High throughput: large mutant libraries Error prone PCR, DNA shuffling, mutator strains Low to modest
ENZYMOLOGY
15
Wild-type gene
Mutagenesis
Further mutagenesis
Mutagen gene
Expression
No
Function OK?
Mutant protein
Yes
Device incorporation
Figure 15. The protein engineering workflow.
An active site module The part of the protein that carries out its function, typically catalysis in the case of an enzyme. An immobilization module Where the protein is immobilized, the part that is involved in immobilization. In some cases the module may involve only one or a small number of amino acid residues, in others it may be another protein fused to the first. The use of fusion proteins for enzyme immobilization illustrates how this modular approach can be used. Many different surfaces can be employed for protein immobilization and the different surfaces will have complementary chemistries to one of the fusion partners. This means that the interaction with the surface will ideally be dominated by one part of the fusion protein irrespective of the
other. Some instances of immobilization modules are given in Table 3. Other examples where two genes might be fused together include creating a single polypeptide chain with two active sites, where the product of the first active site is the substrate for the second. In this case an enhanced rate of catalysis is observed due to the phenomenon of “substrate channeling” whereby the diffusion distance between the two enzymes is reduced. In the past such fused enzymes were produced by chemically cross-linking the two proteins. In this case the reaction is difficult to control and can give multiple variable products. In contrast a gene fusion yields an “end-to-end” link that is a betterdefined entity. An example of such a fusion is that between glucoamylase (maltose hydrolysis to glucose) and glucose oxidase.28 Often with fusion proteins it can be advantageous to also incorporate a flexible linker sequence between the partner proteins to avoid steric conflicts. Suitable
16
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS Table 3. Some examples of immobilization tags and the corresponding surfaces
Surface
Tag
Comments
Metal chelate
Hexahistidine
Reduced stability under acidic or metal complexing conditions29
Gold and silver Polyaniline
Cysteine Cysteine
(Strept)avidin Polystyrene
GLNDIFEAQK(Biotin)IEWHE (APGVGV)12
Streptavidin
AGSAWR
linkers are often of the form (Gly.Ser)n where n is 2–4.
6 CONCLUSIONS
Biosensor technology (and its more recent extension to biochips) was founded on the realization that enzyme layers on the base transducers could greatly extend the analytical utility of such devices. Since then there have been many illustrations of this principle and the current book describes many of the clever and innovative ways in which enzymes have been used in biosensors and biochips. While in the vast majority of these devices the effort has been directed toward working with enzymes having “native” properties, the recent advances in protein design and modeling mean that we are no longer restricted by what nature offers in terms of structure and function. The engineering of the protein component will become as much a part of sensor design as the base transducer or the readout electronics.
END NOTES
Strictly this is the case when [S] Km , that is the enzyme is saturated. When [S] Km the relevant stabilization energy is between the transition state and E and S separately. a.
REFERENCES 1. T. Bugg, An Introduction to Enzyme and Coenzyme Chemistry, Blackwell Science, Oxford, 1997.
A covalent bond forms between the cysteine and the polymer30 The biotin is biosynthetically incorporated31 This elastin-derived sequence forms a β-corrugated structure with a hydrophobic face interacting with the surface32 The pentapeptide sequence at the C-terminus is a biotin mimic33
2. A. R. Fersht, Structure and Mechanism in Protein Science, W.H. Freeman, New York, 1999. 3. T. Palmer, Understanding Enzymes, 4th Edn, Prentice Hall, London, 1995. 4. D. L. Purich, Contemporary Enzyme Kinetics and Mechanism, 2nd Edn, Academic Press, San Diego, 1996. 5. A. R. Schulz, Enzyme Kinetics, Cambridge University Press, Cambridge, 1994. 6. S. J. Benkovic and S. Hammes-Schiffer, A perspective on enzyme catalysis. Science, 2003, 301(5637), 1196–1202. 7. M. Garcia-Viloca, J. Gao, and M. Karplus, How enzymes work: analysis by modern rate theory and computer simulations. Science, 2004, 303(5655), 186–195. 8. J. E. Coleman, Structure and mechanism of alkaline phosphatase. Annual Review of Biophysics and Biomolecular Structure, 1992, 21, 441–483. 9. D. M. Quinn, Acetylcholinesterase: enzyme structure, reaction dynamics, and virtual transition states. Chemical Reviews, 1987, 87, 955–979. 10. V. Leskovac, S. Trivic, G. Wohlfahrt, J. Kandrac, and D. Pericin, Glucose oxidase from Aspergillus niger: the mechanism of action with molecular oxygen, quinones, and one-electron acceptors. International Journal of Biochemistry and Cell Biology, 2005, 37(4), 731–750. 11. R. Wilson and A. P. F. Turner, Glucose-oxidase—an ideal enzyme. Biosensors and Bioelectronics, 1992, 7(3), 165–185. 12. J. P. Roth and J. P. Klinman, Catalysis of electron transfer during activation of O-2 by the flavoprotein glucose oxidase. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100(1), 62–67. 13. A. D. Ryabov, Y. N. Firsova, and M. I. Nelen, Ferricenium salts as true substrates of glucose oxidase—a steady-state kinetic study. Applied Biochemistry and Biotechnology, 1996, 61(1–2), 25–37. 14. N. J. Forrow, G. S. Sanghera, and S. J. Walters, The influence of structure in the reaction of electrochemically generated ferrocenium derivatives with reduced glucose oxidase. Journal of the Chemical Society-Dalton Transactions, 2002, (16), 3187–3194. 15. L. K. Folkes and L. P. Candeias, Interpretation of the reactivity of peroxidase compounds I and II with phenols
ENZYMOLOGY
16.
17.
18.
19.
20.
21.
22.
23.
24. 25.
26.
by the Marcus equation. FEBS Letters, 1997, 412(2), 305–308. L. P. Candeias, L. K. Folkes, and P. Wardman, Factors controlling the substrate specificity of peroxidases: kinetics and thermodynamics of the reaction of horseradish peroxidase compound I with phenols and indole-3-acetic acids. Biochemistry, 1997, 36(23), 7081–7085. T. Cass and F. S. Ligler (eds), Immobilized Biomolecules in Analysis a Practical Approach, Oxford University Press, Oxford, 1998, p. 216. T. Ahuja, I. Mir, A. Kumar, and D. Rajesh, Biomolecular immobilization on conducting polymers for biosensing applications. Biomaterials, 2007, 28(5), 791–805. S. Neugebauer, S. Isik, A. Schulte, and W. Schuhmann, Acrylic acid-based copolymers as immobilization matrix for amperometric biosensors. Analytical Letters, 2003, 36(9), 2005–2020. T. Coradin, J. Allouche, M. Boissiere, and J. Livage, Solgel biopolymer/silica nanocomposites in biotechnology. Current Nanoscience, 2006, 2(3), 219–230. E. Topoglidis, C. J. Campbell, A. E. G. Cass, and J. R. Durrant, Factors that affect protein adsorption on nanostructured titania films. A novel spectroelectrochemical application to sensing. Langmuir, 2001, 17(25), 7899–7906. B. D. Ratner and S. J. Bryant, Biomaterials: where we have been and where we are going. Annual Review of Biomedical Engineering, 2004, 6, 41–75. M. Wilchek and E. Bayer, Avidin-biotin immobilization systems, in immobilized biomolecules in analysis-A practical approach, T. Cass and F. S. Ligler (eds), OUP, Oxford, 1998, pp. 15–34. A. Svendsen (ed), Enzyme Functionality: Design, Engineering and Screening, Marcel Dekker, 2003. H. W. Hellinga and J. S. Marvin, Protein engineering and the development of generic biosensors. Trends in Biotechnology, 1998, 16(4), 183–189. G. Gilardi, Protein Engineering for Biosensors, in Biosensors: A Practical Approach, J. Cooper and T. Cass (eds), Oxford University Press, Oxford, 2004.
17
27. R. M. Ferraz, A. Vera, A. Aris, and A. Villaverde, Insertional protein engineering for analytical molecular sensing. Microbial Cell Factories, 2006, 5, p. 7. 28. Y. F. Zhou, X. E. Zhang, H. Liu, Z. P., Zhang, C. G. Zhang, and A. E. G. Cass, Construction of a fusion enzyme system by gene splicing as a new molecular recognition element for a sequence biosensor. Bioconjugate Chemistry, 2001, 12(6), 924–931. 29. S. Lata and J. Piehler, Stable and functional immobilization of histidine-tagged proteins via multivalent chelator headgroups on a molecular poly(ethylene glycol) brush. Analytical Chemistry, 2005, 77(4), 1096–1105. 30. L. Q. Chen, X. E. Zhang, W. H. Xie, Y. F. Zhou, Z. P. Zhang, and A. E. G. Cass, Genetic modification of glucose oxidase for improving performance of an amperometric glucose biosensor. Biosensors and Bioelectronics, 2002, 17(10), 851–857. 31. C. M. Halliwell, E. Simon, C. S. Toh, A. E. G. Cass, and P. N. Bartlett, The design of dehydrogenase enzymes for use in a biofuel cell: the role of genetically introduced peptide tags in enzyme immobilization on electrodes. Bioelectrochemistry, 2002, 55(1–2), 21–23. 32. A. Tirat, F. Freuler, T. Stettler, L. M. Mayr, and L. Leder, Evaluation of two novel tag-based labelling technologies for site-specific modification of proteins. International Journal of Biological Macromolecules, 2006, 39(1–3), 66–76. 33. A. Wada, M. Mie, M. Aizawa, P. Lahoud, A. E. G. Cass, and E. Kobatake, Design and construction of glutamine binding proteins with a self-adhering capability to unmodified hydrophobic surfaces as reagentless fluorescence sensing devices. Journal of the American Chemical Society, 2003, 125(52), 16228–16234. 34. W.-H. Shao, X.-E. Zhang, H. Liu, Z. P. Zhang, and A. E. G. Cass, An ‘anchor-chain’ molecular system for orientation control of enzyme immobilization with high recovery of activity. Bioconjugate Chemistry, 2000, 11, 822–826.
6 Molecular Antibody Technologies for Biosensors and Bioanalytics Karl Kramer, Georg Mahlknecht and Bertold Hock Center of Life Sciences, Technical University of Muenchen, Freising, Germany
1 INTRODUCTION
Biosensors take advantage of biomolecular interactions, which are applicable to various analytical areas.1,2 Sensitivity and selectivity of bioanalytical systems essentially depend on the properties of the biorecognition elements to be used for analyte binding. Biological structures required for the selective receptor unit of the sensor are usually derived from subcellular components and include in most of the studies reported so far on enzymes, antibodies, hormone receptors, nucleic acids, and membrane components. These are complemented with biorecognition elements organized on a higher functional level such as organelles or entire cells. The latter are giving access to additional information beyond the receptor ligandbinding event. Immunochemical assay systems employing Abs as binding components are effective tools for the analysis of a wide variety of analytes ranging from low molecular weight xenobiotics (e.g., herbicides, insecticides) to complex proteins (e.g., structural elements of pathogenic microorganisms, disease associated protein misfolding e.g., Creutzfeld Jacob Disease or tumor associated antigens). However, the main strength of antibodies is a potentially high affinity and selectivity toward the target molecule. Despite optimism for the potential of biosensors, there are many examples successfully
tested in a laboratory or at prototype level but only few of them entered the analytical praxis. This has been hampered by several obstacles. With respect to Ab immobilization on transducers, stability, sensitivity, and susceptibility to matrix effects are frequently mentioned.3 One of the most remarkable developments in Ab production techniques emerged in the last two decades, when scientists started to produce Abs in vitro. Avoiding the vertebrate in vivo system offered new facilities, since this approach was considered to solve several problems encountered with Ab obtained from sera or by the aid of hybridoma technology. In this chapter state of the art Ab technologies are briefly introduced and major achievements are summarized. Aspects, which still suffer from the current technological standard and therefore need further development are discussed. Finally, limitations of the molecular Ab approach are indicated, which are already apparent.
1.1
The Antibody Scaffold
The key reaction at the recognition part of immunosensors is based on the interaction between the Ab molecule and the corresponding antigen as ligand. The potential of immunosensors is crucially determined by the selectivity and affinity
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
of the individual Ab applied for the detection of a particular ligand. Ab molecules are members of the immunoglobulin superfamily. They consist of two identical heavy chains and two identical light chains (Figure 1). Two antigenbinding Fab fragments are assembled each by the complete light chain combined with the corresponding part of the first two N-terminal heavy chain domains. Two Fab fragments are linked via flexible hinge regions with the crystallizable fragment Fc , which harbors the remaining constant heavy chain domains CH 2 and CH 3. The globular structure of Ab domains is caused by the characteristic immunoglobulin fold.4 Antiparallel β-strands form a typical double layer in each domain, which is stabilized by hydrophobic interactions and conserved intradomain disulfide bonds. The antigen-binding site is localized at the N-terminal moiety of the variable regions. Owing to the frequency of sequence variation between different Ab molecules, sections with hypervariable or complementarity-determining regions (CDR) and conserved or framework regions can be distinguished for these domains.5,6 Each of the variable (V) regions contains three CDR loops that are embedded into four sections of the framework region. In addition to their elevated sequence variability, most of the CDR loops are characterized by significant differences in length.7 Antigen contact sites are mainly provided by distinct amino acid residues of the three CDRs of each V domain. The composition and conformation of the six CDRs (three from the light and three from the heavy chain V domain) in each paratope determines the topography of the antigen-binding site and, hence, the “recognition” of the ligand. Additional interactions by residues of the framework region are reported for discrete ligands.8 Binding energy between the paratope and the antigenic epitope involves hydrogen bond, hydrophobic, van der Waals, and coulombic interactions as well as calcium bridges.9 Since these multiple forces are exclusively effective on short molecular distances, they require a complementary topography at the Ab–antigen interface. The affinity and selectivity of an Ab is thereby defined by the total of the intermolecular forces and by the degree of complementarity. At the beginning of genetic engineering of biosensors, Ab were predominantly prepared as
monovalent fragments either in the scFv10,11 or Fab format.12 Fab fragments are comprising the entire Ab light chain and the corresponding part of the Ab heavy chain. The scFv fragments are reduced to the variable domains of the Ab heavy and light chain, which are connected by an artificial peptide linker (Figure 1). The proper functioning of biosensors essentially depends on the immobilization of the respective ligands, Ab, or coating conjugates on the sensor surface, their correct orientation, and homogeneity. Recombinant approaches are also intensively used for the addition of functional structures, for example, for the attachment of anchor groups. Furthermore, Ab fragments that are fused with marker proteins offer the advantage of a reduced number of assay steps in the analytical test format. The genetically engineered fusion of the Ab binding function with marker enzymes was already reported in bioanalytics.13 The corresponding vector was developed to contain an alkaline phosphatase and generic restriction sites for the convenient one-step cloning of scFv fragments isolated from Ab library repertoires. Similarly, a gene encoding green fluorescent protein was inserted into a vector harboring a picloram-specific Ab fragment.14 The resulting “fluobody” avoids the enzyme–substrate reaction for colorimetric detection that is required in a conventional analytical format with substrate turnover. Finally, fusion proteins can offer new strategies of bioanalytical assays. The assay utilizes the antigen-dependent reassociation of Ab variable domains and concomitant complementation of the enzyme β-galactosidase (β-gal),15 in order to enable a noncompetitive homogeneous immunoassay for small target molecules instead of the standard competitive heterogeneous enzyme-linked immunosorbent assay (ELISA). In a proof of principle approach, the reassociation of two fusion proteins was monitored by restoring the enzymatic activity. The first protein consists of an anti-4-hydroxy-3-nitrophenylacetyl variable heavy chain (VH ) fragment fused to an N-terminal deletion mutant of β-gal (VH α), and the second protein correspond to the variable light chain (VL ) fragment fused to a C-terminal deletion mutant of β-gal (VL ω). Upon mixing of the reagents with the sample, an analytedependent increase in reassociation and thus, in
MOLECULAR ANTIBODY TECHNOLOGIES FOR BIOSENSORS AND BIOANALYTICS
VH
VL
VL
VH
Tag
VH
scFv
VL
CH1
CL
3
1 CH
Fab
CL
H3
L1 L2
H1
CH2
H2
Carbohydrate L3
CH3
Antibody (IgG)
VH gene FR1
CDR1
FR2
CDR2
FR3
CDR3
FR4
CDR1
FR2
CDR2
FR3
CDR3
FR4
VL gene FR1
Figure 1. Domain structure of native IgG antibody molecule (top left) and genetically engineered single domain antibody (sdAb), single-chain Fv (scFv), disulfide stabilized Fv (dsFv) and Fab fragments. Some of the fragments are genetically fused to affinity tags, for example, Strep tag (Strep), E tag (E). Middle right: Ribbon model of the VH and VL domain with pesticide analyte complexed in the Ab binding site (L1-3: VL CDR1-3; H1-3: VH CDR1-3). Bottom: Segmentation of VH and VL encoding genes into framework regions FR1-4 and the hypervariable complementarity-determining regions CDR1-3. The ribbon model was kindly provided by S. H¨orsch.
enzymatic activity was observed. Compared to the corresponding heterogeneous open sandwich ELISA, a 1000-fold improvement in sensitivity was attained.
1.2
The Evolutionary Cycle
The evolutionary cycle is the central aspect of Ab engineering in order to alter the Ab affinity
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
profile. Applying the Darwinian principle of variation and selection in vitro elegantly circumvents extended immunization periods as required in classical Ab production schemes.16,17 The rationale behind the concept evolved as modern evolutionary theory in the first half of the twentieth century, when population biologists started to describe the natural selection of gene populations. They established mathematical models for the evolution of genes under the influence of recursive rounds of mutation, recombination, and selection.18 Applying principles of natural selection to the evolution of genes in the laboratory, fundamental evolutionary theorems predict that the fitness of a gene will evolve most rapidly in a population of high genetic variability, which is exposed to selection pressure.19 The methodology of choice in a directed evolution experiment is therefore to construct a library of variant genes, and screen or select improved variants from the protein products of these genes. The principles of directed evolution in vitro are very similar to the mechanisms of somatic mutation in vivo. The Ab repertoire of the primary immune response in vivo is predominantly the result of recombining germ line genes of the V, D, J clusters (i.e., the genes constituting elements of the finally expressed VH and VL genes). The primary response yields Ab with generally low affinities. Thereafter, Ab variable genes of the primary repertoire are modified during the secondary immune response in the microenvironment of lymphoid germinal centers by somatic hypermutation. Physiologically appropriate variants are subsequently selected from this pool of mutant immunoglobulins upon their improved affinity to the antigen.20 In vitro, Ab genes are subjected to iterative evolutionary cycles of mutation and selection, until they meet the requirements for the designated application (Figure 2). Frequently applied in vitro methods for sequence diversification include random and directed nucleotide alterations or recombination techniques.21 Random techniques are for instance, based on the introduction of point mutations by error prone polymerase chain reaction (PCR). Nucleotides throughout the entire gene are hence randomly exchanged.22 In contrast to random methods, oligonucleotide-directed procedures insert synthetic sequences into the gene of interest at specific sites, for example,
strand overlap extension23 or megaprimer-based PCR.24 Recombination techniques are based on randomized recombination of gene segments or complete genes (e.g., Ab VH and VL encoding genes). Ab gene repertoires encoding highly functional diversity can be subsequently selected either by physical or genetic techniques. The most frequently applied physical selection methods comprise phage display,25,26 cellular display on the surface of bacteria or yeast,27,28 ribosome display,29 and mRNA display.30 These procedures are all characterized by the physical linkage of proteins and their encoding genes, which can be reamplified for further processing. In phage and cell surface display the Ab library is fused to virus coat or cellular membrane proteins of virions and cells.31 In contrast to phage or cell surface display, ribosome display does not depend on a transformation step for creating a selectable library of protein variants. Here the Ab library is fused to a C-terminal tether and transcribed into mRNA in vitro, which subsequently recombines with ribosome particles. Following in vitro translation, functional proteins are processed in the selection step. Even more advanced methods are based on RNA display, where the procedure omits the presence of instable ribosome complexes.32 For the selection of the most favorable binding proteins the ligand is prevalently immobilized on a solid phase, for example, at the surface of a polystyrene tube, microtiter plate well or pin and incubated with the phage library. Complexes that recognize the ligand are subsequently eluted, after nonbinding variants have been removed by washing. Since selection at the surface of a solid phase may put problems on the procedure, selection strategies were developed for in solution separation of ligand-binders. Binders of biotin-labeled ligands can be tackled using streptavidin-coated magnetic beads.33 Another strategy, the selectively infective phage (SIP) technology is based on the fusion of receptor protein and C-terminal domains of the pIII coat protein in the phage display system.34 Recombinant phages displaying the Ab fragments on their surface are lacking the protein domain, which enables the infection of bacteria. Infectivity is exclusively restored upon the specific interaction of the displayed Ab and the ligand,
MOLECULAR ANTIBODY TECHNOLOGIES FOR BIOSENSORS AND BIOANALYTICS
5
J
J
J
J
J
Coupling of Ab genotype with phenotype
Recursive evolutionary cycles
Selection by analyte-driven evolutionary pressure
J
VL
MRNA–DNA
Generation of Ab encoding gene repertoire
Identification of best variants
Bioanalytical application
VL
Tag Figure 2. Principle of directed evolution. J: joining element.
which is coupled to the protein domain for host infection. All physical selection methods require significant quantities of the ligand in order to perform selection and screening, whereas genetic methods rely on the in situ synthesis of, and subsequent interaction between, binding ligand and target to confer a selectable phenotype. The receptor and a peptide- or protein-ligand are synthesized in vivo and interact in the host cell.
Various yeast hybrid systems have been designed, which utilize the transcriptional activation mechanism for selection.35 For example, a DNA-binding domain of the transcription activator can be fused to the N-terminus of the receptor protein, whereas the activation domain of the transcription activator is fused to the potential ligand. The DNA-binding domain binds to a promoter, but transcription is exclusively activated, if the DNA-binding domain is connected to the
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
activation domain by the interaction of receptor and ligand. If no receptor–ligand binding occurs, the reporter gene transcription is not triggered. The concept effectively facilitates the distinction between cells harboring potent and weak binders. A similar concept is pursued by the protein complementation assay.36,37 In this case, the gene coding for an essential enzyme (e.g., dihydrofolate reductase or β-lactamase) is deliberately cleaved into two fragments. Each of the resulting domains is fused to either the receptor or the ligand. The resulting fusion proteins are coexpressed and the enzyme restores functionality, if the domains get into close contact via the receptor–ligand interaction. Finally compartmentalization strategies using the not-natural compartments of cells as mentioned before, but artificial water-in-oil emulsions can be essentially considered as in vitro methods. Cellular compartimentalization is mimicked by adding an in vitro transcription/translation reaction mixture to a stirred suspension of mineral oil and surfactants, which results in an emulsion with mean droplet diameter similar to that of bacterial cells.38 A mixture of two genes, the M. HaeIII gene (which encodes DNA methyltransferaseHaeIII) and the folA gene (which encodes DHFR), were transcribed and translated in the aqueous compartments. Then the emulsion was broken, and the DNA in the aqueous phase was subjected to cleavage by HaeIII endonuclease followed by amplification by PCR. Because the DNAmethyltransferase methylated HaeIII-cleavage sites in droplets that contained the M. HaeIII gene, only the M. HaeIII gene would survive the cleavage by HaeIII and be amplified by PCR. After one round of selection, a mixture of M. HaeIII to folA gene with a ratio of 1 : 1000 was enriched to a 1 : 1 ratio.38 Since all of the steps in in vitro compartmentalization are performed in vitro, this approach has the potential to reach the limit at which the DNA is the limiting reagent in library size.39
1.3
Primary Antibody Repertoires for Bioanalytics
A very common approach to generate Ab diversity is the cloning of natural Ab gene repertoires, which are isolated from donor organisms, for example, mice. The corresponding repertoire is expected to
be unbiased, which means that the immune system of the donor organism has not been challenged by an antigen. These na¨ıve repertoires theoretically harbor Abs for any target structure, however, at a moderate affinity level for the majority of binding molecules. In contrast, biased Ab repertoires can be cloned from immunized sources. The latter strategy benefits from in vivo mechanisms of the immune system, since Ab variable genes encoding the antigen-binding domains are modified during the secondary immune response in the microenvironment of lymphoid germinal centers by somatic hypermutation. Appropriate variants are subsequently selected from this pool of mutant immunoglobulins upon their improved affinity to the antigen.47 Therefore, immunizing an organism with a specific antigen serves as an in vivo preselection of potent Ab genes for the immunogen. We developed a strategy to generate a groupselective library representing a large natural Ab gene pool. This library was designed to include a range of s-triazine-specific Abs in order to facilitate the selection of Abs against defined members of the s-triazine family.40 For this purpose, Absecreting B cells were derived from Balb/c mice, which had previously been immunized with different s-triazine immunogens including derivatives of atrazine, ametryn, terbuthylazine, deethylatrazine, and simazine. B cells secreting s-triazineselective Abs were separated from unspecific B cells by means of immunomagnetic separation. This method takes advantage of the membranebound receptor molecules on the B cell surface, that is, transmembrane protein complexes that share their ligand-binding characteristics with the secreted Ab. These surface receptors can be tagged by target molecules covalently linked to paramagnetic particles. After magnetizing the particles in a magnetic field, specific B cells were removed from bulk cultures by magnetic force.41 Ab-encoding genes from magnet-bound B cells were subsequently cloned into a phage display system. The resulting library comprised all target relevant sequences that have been included in the starting B cell repertoire. The group-selective Ab library was then used to select Ab variants selective for s-triazines containing a tertiary butyl group (BUT), that is, terbutryn and terbuthylazine as well as those s-triazines bearing an isopropylamino residue (IPR), that is, atrazine and propazine. Specific
MOLECULAR ANTIBODY TECHNOLOGIES FOR BIOSENSORS AND BIOANALYTICS
160
Association
450 400
IPR-7 IPR-32 BUT-4 BUT-8 BUT-56
350 300 RLU
phages were enriched by three repetitive cycles of selection applying immunoaffinity chromatography with BUT derivative-coated and IPR derivative-coated columns. Binding studies for the characterization of selected Ab clones were essentially performed by an ELISA and an optical biosensor. The clones could be selectively displaced by atrazine as indicated by the corresponding calibration curves (Figure 3). Reaction kinetics of the three best binding clones for triazine herbicides containing tertiary butylamino and isopropylamino groups were determined with the BIAcore 2000 sensor. Figure 4 shows representative sensorgrams for the binding of a recombinant Ab, derived from clone BUT-4, to a tertiary butyl derivative-ovalbumin conjugate or ovalbumin as a control. The binding constants KD ranged from 1.2 × 10−8 M for IPR-7 to 8 × 10−8 M for BUT-56, which corresponds to the affinity level of maturated Abs that are obtained during the secondary immune response.40 In a second approach, we employed the fully synthetic human combinatorial Ab library HuCAL (MorphoSys AG, Martinsried, Germany) as a primary immune repertoire for the selection of pathogen-directed Ab variants. The library is based on consensus sequences for each of those seven VH and VL germline families, which are most frequently used in the human immune response. Diversity is created by replacing the VH and VL CDR3 of the master genes by CDR3 library cassettes, generated from mixed trinucleotides42
7
250 200 150 100 50 0 100
0
101
102
s -Triazine [ µg
103
104
l−1]
Figure 3. Calibration curves of IPR and BUT clones for the analysis of atrazine and terbutryn, respectively, by direct heterogeneous competitive ELISA. IPR and BUT clones were selected by phage display technology employing s-triazine derivatives, which contain isopropylamino (IPR) and butylamino (BUT) residues. RLU: Relative luminescence units.
and biased toward natural human Ab CDR3 sequences.43 Specific clones were selected from the HuCAL library by means of phage display for the detection of several food-born pathogens. The stability of selected Ab fragments was investigated with respect to their thermal stability, which is a rough indicator for their long-term storage properties, for example, immobilized on sensorchips, and their molecular integrity at unfavorable temperature conditions. For this purpose Ab fragments Dissociation
140 120
RU
100
28 nM
80 60
14 nM
40
7 nM 3.5 nM 1.8 nM 0.9 nM
20 0 −20 −200
0
200
400 Time (s)
600
800
1000
Figure 4. Sensorgrams of scFv binding (clone 4). CM5 chips were coated with 4000 RU terbuthylazine-ovalbumin conjugate (channel 2) or ovalbumin (channel 1) as a control using amine coupling. Affinity measurements were performed at 25 ◦ C with 1–28 nM of active scFv (diluted in PBS containing 0.005% Tween 20) for 3 min using a flow rate of 30 µl/min.
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
of selected clones were incubated for 24 h at various temperatures and their functionality was tested by ELISA. The corresponding results for the pathogen-selective Abs are presented in Figure 5. Almost all Ab fragments were stable up to temperatures of 37 ◦ C and 50 ◦ C, respectively. Most of the Abs showed reduced or even completely lost ligand binding at higher temperatures. These observations are consistent with analogous experiments performed with conventional monoclonal Abs derived from hybridoma cultures in our laboratory. However, one out of the six fragments depicted in Figure 5 retained full functionality even after incubation at 80 ◦ C, which indicates an exceptional stability with respect to the considered protein family. Sequence alignment with human germline genes revealed that the immunoglobulin VH genes of the clones providing the highest stabilities could be predominantly assigned to the VH 3 gene family. This is at least a hint that the stability of Ab fragments may be an inherent structural feature of particular germline families. These results are well in line with investigations of the biophysical properties of Ab fragments performed by other groups employing the HuCAL library. Ab
fragments containing the variable domain combinations H3κ3 and H5κ3 showed superior stability. Combination with λ light chains exhibited also high levels of stability depending on the particular amino acid sequence of the CDR-L3. Another issue in Ab engineering is the availability of the antigen. We encountered this problem, when raising Abs against genetically modified organisms (GMO). Since posttranslational processing in plants is significantly different from analogous processes of bacteria physiology, we avoided cloning and expression of the GMO antigen in Escherichia coli. However, antigen was only available at low percentage of purity, which would have affected all subsequent processes, for example, immune response biased to immunogen contaminants, inefficient screening, and problematic identification of positive clones. Applying conventional Ab synthesis protocol by using animals as Ab source, rough samples of ground flour from GMO corn had to be extracted and purified chromatographically. However, yield of purified antigen turned out to be poor and the procedure itself very laborious. In order to circumvent the problems raised by the lack of appropriate antigen quantity and purity, human germline gene Ab 80 °C 65 °C 50 °C 37 °C 22 °C 4 °C
SaBa/6H
Sasig Da/12D
Lmb/1B
Esco Heb/4A
CjBa/1F
Bace L2a/2c 0
20
40
60
80
100
Binding activity (%) Figure 5. Thermal stability of pathogen-selective Ab clones isolated from the HuCAL library. Ab fragments were incubated for 24 h at temperatures ranging from 4–80 ◦ C. Binding activity was subsequently evaluated by measuring the maximum and minimum signal in ELISA according to the formula: (Amax − Amin temperature treated Ab)/(Amax − Amin of untreated control) × 100%.
MOLECULAR ANTIBODY TECHNOLOGIES FOR BIOSENSORS AND BIOANALYTICS
libraries (Tomlinson)44 were used as a primary repertoire for a subtractive selection strategy. Each panning round started with a selection against flour extracts derived from non-GMO soybean. Thereby, all Abs directed against components of the extract were retained in the panning vessel. Unbound clones were transferred to a second panning vessel coated with flour extracts from GMO plants. Since the majority of Abs directed against non-GMO protein in the plant extract have been effectively removed in the prepanning step, GMO selective Abs were now the remaining fraction, which could bind specifically. Thus several clones from the primary library repertoire could be identified, which were appropriate for GMO monitoring. Figure 6 gives an example for the performance of the clone G7 in a simple ELISA format. By the selection method several parameters of the final Ab characteristics were considered. The subtractive selection procedure enabled the isolation of Abs against a nonpurified antigen. Furthermore, the amount of antigen applied in the panning corresponded exactly to that present in sample extracts of GMO plants. Thus, the affinity level of Ab variants was precisely adjusted to the needs in GMO monitoring. Third, since panning was performed in plant sample extracts, the
1 OD450 nm 0.8 0.6 0.4 0.2 0 0
2.5
5
Content GMO (%) Figure 6. ELISA for GMO detection in crude flour extracts from genetically engineered soy bean based on recombinant scFv fragments. Percentage of contamination with flour derived from GMO plants is indicated. The GMO protein corresponds to CP4- EPSPS (i.e., 5-enolpyruvylshikimate-3-phosphate synthase from the Agrobacterium sp. strain CP4), which confers tolerance to the glyphosate herbicide.
9
selected clones recognize conformation of GMO proteins, even after they have been processed for sampling. Finally, interference by sample components (for instance, non-GMO soy bean proteins, extraction solvents) were considered by the selection protocol too. 1.4
Secondary Antibody Repertoires for Bianalytics
The gene repertoire of the group-selective Ab library presented in the preceding text was employed for subsequent optimization of individual Ab molecules by directed evolution.45 It was expected that this library would substantially facilitate the engineering of desired Ab specificities and affinities to any member of the triazine group without the need of new immunizations. The Ab clone IPR-7 was used as a template for the optimization process. This clone was initially selected from the group-selective library (see Figure 4) and provided the highest affinity to s-triazines bearing an IPR, that is, atrazine and propazine (Table 1).40 Chain shuffling was applied as a directed, recombinatorial approach for improving the affinity of this clone. At the outset the light chain of the template Ab IPR7 was shuffled with the heavy-chain repertoire of the group-specific library, and subsequently selected by phage display. Then, the heavy chain of the best binder (IPR-26) was shuffled against the library light-chain repertoire. The kinetic data of the Ab variants are detailed in Table 1. The equilibrium dissociation constants of the Ab variants are approaching the typical KD level of affinity matured Ab in vivo. The optimized variant IPR-83 showed a 17-fold increase in affinity as compared to the template Ab IPR-7. Interestingly, sequence analysis of the shuffled clones revealed a bias of amino acid substitutions Table 1. Association rate constant ka , dissociation rate constant kd and equilibrium dissociation constant KD for IPR obtained from the scFv clones IPR-7, IPR-26 and IPR-83. The values for ka , kd and KD were measured utilizing the BIAcore 2000 system
Clone
ka (M−1 s−1 )
IPR-7 IPR-26 IPR-83
1.38 × 10 2.10 × 105 6.73 × 105 5
kd (s−1 )
KD = kd /ka (M) −3
1.75 × 10 1.93 × 10−3 5.02 × 10−4
1.27 × 10−8 9.20 × 10−9 7.46 × 10−10
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
from the template IPR-7 to the optimized variant IPR-83 in the 5 moiety of the V genes including the first two CDRs and the flanking frame regions.45 This is in contrast to a series of Ab optimization experiments that are primarily targeting on the variation of the CDR3 regions at the 3 moiety of the Ab gene.46,47 The VH CDR3 region is generally considered to constitute the key determinant for the antigen selectivity.48 However, the distribution of sequence alterations obtained in the presented Ab optimization is consistent with proposed models for mutational mechanisms during the secondary immune response in vivo.47,48 In addition, experimental data obtained from in vivo immune repertoires are confirming individual sites at the V genes that are prone to hypermutation. These mutational “hot-spots” for affinity maturation are strategically located at the CDR1 and CDR2 rather than in the CDR3 loop.49,50 Therefore, the applied in vitro optimization strategy resulted in a distribution of sequence alterations, which is fitting very well into the current knowledge of natural affinity maturation. The applicability of the optimized Ab variant IPR-83 was tested by measuring environmental samples. IPR-83 was applied to determine atrazine contaminations of soil samples collected in Southern Germany. Although atrazine has been banned in Germany by the European Community in 1991, environmental contaminations have been observed during the last years due to illegal applications. The corresponding threshold for atrazine is 100 µg kg−1 soil. The immunochemical analysis
Table 2. Atrazine analyses of soil samples by ELISA employing the mutant antibody IPR-83. Validation was performed by HPLC
Soil sample
ELISA atrazine (µg kg−1 )
HPLC atrazine (µg kg−1 )
1 2 3 4 5 6 7 8 9
43 ± 4 323 ± 8 35 ± 8 91 ± 13 126 ± 4 141 ± 6 65 ± 5 108 ± 11 121 ± 3
49 ± 3 313 ± 12 33 ± 3 85 ± 10 120 ± 21 135 ± 14 59 ± 8 115 ± 9 113 ± 7
[HPLC data were kindly provided by Dr. J. Lepschy, Bayerische Landesanstalt f¨ur Bodenkultur und Pflanzenbau, Freising, Germany.]
was complemented by HPLC analyses as reference method for validation (Table 2). The ELISA measurements were consistent with the HPLC data within the experimental error.45 Thus, the engineered scFv mutants proved to be suitable for the application in environmental analyses under real sample conditions.
2 DISCUSSION AND OUTLOOK
The principles of directed evolution in vitro are very similar to the mechanisms of somatic mutation in vivo. The Ab repertoire of the primary immune response in vivo is predominantly the result of recombining germ line genes of the V, D, J clusters (i.e., the genes constituting elements of the finally expressed VH and VL genes). The primary response yields Abs with generally low affinities. Thereafter, Ab variable genes of the primary repertoire are modified during the secondary immune response in the microenvironment of lymphoid germinal centers by somatic hypermutation. Physiologically appropriate variants are subsequently selected from this pool of mutant immunoglobulins upon their improved affinity to the antigen.20 The primary repertoire in vitro is established by cloning synthetic or natural Ab genes as described above for the fully synthetic HuCAL and the group-selective library, respectively. The former one is a commercially available library. Other examples of accessible primary repertoires include the Tomlinson I and J Ab libraries.44 Some of these primary libraries are very large (containing more than 1010 different Ab variants) and therefore considered to be “universal”, which suggests that the corresponding Abs are covering a huge panel of various specificities. However, even at its best these libraries will represent no more than a basic immune repertoire. The optimization by means of molecular evolution strategies or alternatively by rational design probably remains therefore an integral part in the synthesis of appropriate Abs for the majority of immunochemical applications in environmental analysis. Therefore, one of the vital goals for the future is the simple and cheap access to evolutionary technologies for tailored binders with predefined properties such as selectivity, affinity, stability,
MOLECULAR ANTIBODY TECHNOLOGIES FOR BIOSENSORS AND BIOANALYTICS
and more. Massive parallel processing combined with high-throughput strategies as well as highcontent screening will have a beneficial impact on this new era of Ab production. The hardware is already available for a straightforward production of rAbs. From automated plating and picking of bacteria colonies up to robotic screening and data processing. Self controlled variation and selection has to be integrated in the concept. For instance, recombination in vivo can be achieved by coupling chain shuffling with the phage infection of bacteria as demonstrated for the cre/lox system. An Ab light-chain repertoire in the phage is recombined with the heavy-chain repertoire in the bacteria host by infection.51 Selection of specific Ab variants can be controlled by integrating the SIP technology (see preceding text).34 Currently the potential of alternative Ab molecules is being exploited, a trend, which is mainly driven by the complex patent situation in the Ab area. For instance, single domain Ab (sdAb) are naturally occurring in camelids and sharks.52,53 In addition to Ab domains, so-called Ab mimics have been reported to be amenable to molecular optimization. The tenth fibronectin type III domain (10 Fn3),54 a monomeric member of the immunoglobulin superfamily, and the extracellular domain of human cytotoxic T-lymphocyte associated antigen (CTLA4)55 were used as a scaffold for library synthesis. In addition to immunoglobulins and immunoglobulin-like polypeptides, some specific affinity reagents have been selected from small, globular protein scaffolds not related to Ab. For instance, the α-helical Z-domain of protein A, designated as “affibodies” was improved in directed evolution experiments to the nanomolar range.56 Similarly, the bilin-binding protein (BBP), a lipocalin from the butterfly Pieris brassicae, was used for library synthesis.57 The protein has a conserved β-barrel core formed by eight antiparallel β-strands. Peptide loops, which connect the individual strands, confer binding to the ligand. Affinities in the picomolar range for digoxigenin were achieved by selective mutation of these “anticalins”.58 Another type of protein scaffold is the ankyrin repeat (AR). AR proteins are composed of several 33 amino acid repeats stacked in a row. Each repeat comprises a β-turn followed by two antiparallel α-helices and a C-terminal loop reaching the β-turn of the adjacent loop.59
11
Synthetic libraries were developed by randomizing amino acid positions at the β-turn and the short hinge connecting the two α-helices.60 The AR libraries yielded high-affinity binding variants with KD in the nanomolar range against various protein targets. These binding proteins show that there are promising candidates with a potential for environmental analysis, which could provide an alternative for the classical Ab molecule.
ACKNOWLEDGMENTS
The authors would like to thank MorphoSys AG for providing the HuCAL library and the MRC HGMP Resource Centre for giving access to the Tomlinson I + J library. Further thanks are addressed to Mrs H. Geltl and Mrs A. Hubauer for their excellent technical assistance. Financial support was obtained from the EC (ENVIROSENSE ENV4-CT96-0333; IMAGEMO QLK3-CT-200202141) and the Bavarian Government (Project no. BFS 306/98).
REFERENCES 1. B. D. Malhotra and A. P. F. Turner, Preface. Advances in Biosensors: Perspectives in Biosensors, 5th Edn, B. D. Malhotra and A. P. F. Turner (eds), Elsevier, Amsterdam, 2003. 2. A. Warsinke, W. St¨ocklein, E. Leupold, E. Micheel, and F. W. Scheller, Electrochemical Immunosensors on the Route to Proteomic Chips, in Electrochemistry of Nucleic Acids and Proteins. Towards Electrochemical Sensors for Genomics and Proteomics, E. Palecek, F. W. Scheller, and J. Wang (eds), Elsevier, 451–483. 3. M. N. Velasco-Garcia and T. Mottram, Biosensor technology addressing agricultural problems. Biosystems Engineering, 2003, 84, 1–12. 4. R. J. Poljak, L. M. Amzel, H. P. Avey, B. L. Chen, R. P. Phizackerley, and F. Saul, Three-dimensional structure of the Fab fragment of a human immunoglobulin at a ˚ resolution. Proceedings of the National Academy 2.8-A of Sciences of the United States of America, 1973, 70, 3305–3310. 5. T. T. Wu and E. A. Kabat, An analysis of the sequences of the variable regions of Bence-Jones proteins and myeloma light chains and their implication for antibody complementarity. Journal of Experimental Medicine, 1970, 132, 211–249. 6. E. A. Kabat, T. T. Wu, H. M. Perry, K. S. Gottesman, C. Foeller, Sequences of Proteins of Immunological Interest, 5th Edn, US Department of Health and Human
12
7. 8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18. 19.
20. 21.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS Services, Public Health Service, National Institutes of Health (NIH Publication No. 91-3242), Washington, 1991. E. A. Padlan, The anatomy of the antibody molecule. Molecular Immunology, 1994, 31, 169–217. W. R. Tulip, J. N. Varghese, W. G. Laver, R. G. Webster, and P. M. Colman, Refined crystal structure of the influenza virus N9 neuraminidase-NC41 Fab complex. Journal of Molecular Biology, 1992, 227, 122–148. C. J. Van Oss, Antibody-Antigen Intermolecular Forces, in Encyclopedia of Immunology, I. M. Roitt and P. J. Daves (eds), Academic Press, London, 1992, Vol. 1, pp. 97–100. S. R. Webb, H. Lee, and J. C. Hall, Cloning and expression of Escherichia coli of an anti-cyclohexanedione singlechain variable antibody fragment and comparison to the parent monoclonal antibody. Journal of Agricultural and Food Chemistry, 1997, 45, 535. S. D. Garrett , D. J. A. Appleford, H. A. Lee, and M. R. A. Morgan, Production of a recombinant antiparathion antibody (scFv); stability in methanolic food extracts and comparison to an anti-parathion monoclonal antibody. Journal of Agricultural and Food Chemistry, 1997, 45, 4183. V. K. Ward, P. G. Sehneider, S. B. Kreissig, B. D. Hammock, and P. V. Choudary, Cloning, sequencing and expression of the Fab fragment of a monoclonal antibody to the herbicide atrazine. Protein Engineering, 1993, 6, 981. D. Rau, K. Kramer, and B. Hock, Single-chain Fv antibody-alkaline phosphatase fusion proteins produced by one-step cloning as rapid detection tools for ELISA. Journal of Immunoassay and Immunochemistry, 2002, 23, 129. I. S. Kim, J. H. Shim, Y. T. Suh, K. Y. F. Yau, J. C. Hall, J. T. Trevors, and H. Lee, Green fluorescent proteinlabeled recombinant fluobody for detecting the picloram herbicide. Bioscience, Biotechnology, and Biochemistry, 2002, 66, 1148. T. Yokozeki, H. Ueda, R. Arai, W. Mahoney, and T. Nagamune, A homogeneous noncompetitive immunoassay for the detection of small haptens. Analytical Chemistry, 2002, 74, 2500. P. S. Daugherty, G. Chen, B. L. Iverson, and G. Georgiou, Quantitative analysis of the effect of the mutation frequency on the affinity maturation of single chain Fv antibodies. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97, 2029. J. Hanes, C. Schaffitzel, A. Knappik, and A. Pl¨uckthun, Picomolar affinity antibodies from a fully synthetic naive library selected and evolved by ribosome display. Nature Biotechnology, 2000, 18, 1287. R. A. Fisher, The Genetical Theory of Natural Selection, 2nd Edn, Dover Publications, New York, 1958. A. L. Kurtzman, S. Govindarajan, K. Vahle, J. T. Jones, V. Heinrichs, and P. A. Patten, Advances in directed protein evolution by recursive genetic recombination: applications to therapeutic proteins. Current Opinion in Biotechnology, 2001, 12, 361. K. Rajewsky, Clonal selection and learning in the antibody system. Nature, 1996, 381, 751. C. Neylon, Chemical and biochemical strategies for the randomization of protein encoding DNA sequences:
22.
23.
24.
25.
26.
27.
28.
29.
30.
31. 32.
33.
34.
35. 36.
37.
38.
library construction methods for directed evolution. Nucleic Acids Research, 2004, 32, 1448. P. C. Cirino, K. M. Mayer, and D. Umeno, Generating mutant libraries using error-prone PCR. Methods in Molecular Biology, 2003, 231, 3. S. N. Ho, H. D. Hunt, R. M. Horton, J. K. Pullen, and L. R. Pease, Site-directed mutagenesis by overlap extension using the polymerase chain reaction. Gene, 1989, 77, 51. K. Miyazaki, Creating random mutagenesis libraries by megaprimer PCR of whole plasmid (MEGAWHOP). Methods in Molecular Biology, 2003, 231, 23. G. P. Smith, Filamentous fusion phage: novel expression vectors that display cloned antigens on the virion surface. Science, 1985, 228, 1315. G. P. Smith and J. K. Scott, Libraries of peptides and proteins displayed on filamentous phage. Methods in Enzymology, 1993, 217, 228. G. Georgiou, C. Stathopoulos, P. S. Daugherty, A. R. Nayak, B. L. Iverson, and L. Curtiss, Display of heterologous proteins on the surface of microorganisms: from the screening of combinatorial libraries to live recombinant vaccines. Nature Biotechnology, 1997, 15, 29. E. T. Boder and K. D. Wittrup, Yeast surface display for screening combinatorial polypeptide libraries. Nature Biotechnology, 1997, 15, 553. J. Hanes and A. Pl¨uckthun, In vitro selection and evolution of functional proteins by using ribosome display. Proceedings of the National Academy of Sciences of the United States of America, 1997, 94, 4937. R. W. Roberts and J. W. Szostak, RNA-peptide fusions for the in vitro selection of peptides and proteins. Proceedings of the National Academy of Sciences of the United States of America, 1997, 94, 12297. K. D. Wittrup, Protein engineering by cell-surface display. Current Opinion in Biotechnology, 2001, 12, 395. N. Nemoto, E. Miyamoto-Sato, Y. Husimi, and H. Yanagawa, In vitro virus: bonding of mRNA bearing puromycin at the 3 -terminal end to the C-terminal end of its encoded protein on the ribosome in vitro. FEBS Letters, 1997, 414, 405. R. E. Hawkins, S. J. Russell, and G Winter, Selection of phage antibodies by binding affinity: mimicking affinity maturation. Journal of Molecular Biology, 1992, 226, 889. M. Due˜nas and C. A. Borrebaeck, Clonal selection and amplification of phage displayed antibodies by linking antigen recognition and phage replication. Biotechnology, 1994, 12, 999. S. Fields and O. Song, A novel genetic system to detect protein-protein interactions. Nature, 1989, 340, 245. J. N. Pelletier, K. M. Arndt, A. Pluckthun, and S. W. Michnick, An in vivo library-versus-library selection of optimized protein-protein interactions. Nature Biotechnology, 1999, 17, 683. E. M¨ossner, H. Koch, and A. Pl¨uckthun, Fast selection of antibodies without antigen purification: adaptation of the protein fragment complementation assay to select antigenantibody Pairs. Journal of Molecular Biology, 2001, 308, 115. D. S. Tawfik and A. D. Griffiths, Man-made celllike compartments for molecular evolution. Nature Biotechnology, 1998, 16, 652–656.
MOLECULAR ANTIBODY TECHNOLOGIES FOR BIOSENSORS AND BIOANALYTICS 39. H. Lin and V. W. Cornish, Screening and selection methods for large-scale analysis of protein function. Angewandte Chemie International ed, 2002, 41, 4402. 40. K. Kramer, Synthesis of a group-selective antibody library against haptens. Journal of Immunological Methods, 2002, 266, 211. 41. K. Kramer, T. Giersch and B. Hock, Magnetic bead selection of hybridomas producing pesticide antibodies. Food and Agricultural Immunology, 1994, 6, 5. 42. B. Virnek¨as, L. Ge, A. Pluckthun, K. C. Schneider, G. Wellnhofer, and S. E. Moroney, Trinucleotide phosphoramidites: ideal reagents for the synthesis of mixed oligonucleotides for random mutagenesis. Nucleic Acids Research, 1994, 22, 5600. 43. A. Knappik, L. Ge, A. Honegger, P. Pack, M. Fischer, G. Wellnhofer, A. Hoess, J. W¨olle, A. Pl¨uckthun, and B. Virnek¨as, Fully synthetic human combinatorial antibody libraries (HuCAL) based on modular consensus frameworks and CDRs randomized with trinucleotides. Journal of Molecular Biology, 2000, 296, 57. 44. MRC HGMP Resource Centre, Tomlinson I + J. http:// www.geneservice.co.uk/products/proteomic/datasheets/ tomlinsonIJ.pdf. 45. K. Kramer, Evolutionary affinity and selectivity optimization of a pesticide-selective antibody utilizing a haptenselective immunoglobulin repertoire. Environmental Science and Technology, 2002, 36, 4892. 46. E. T. Boder, K. S. Midelfort, and K. D. Wittrup, Directed evolution of antibody fragments with monovalent femtomolar antigen-binding affinity. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97, 10701. 47. G. M. Wyatt, S. D. Garrett, H. A. Lee, and M. R. A. Morgan, Alteration of the binding characteristics of a recombinant scFv anti-parathion antibody: 1. Mutagenesis targeted at the VH CDR3 domain. Food and Agricultural Immunology, 1999, 11, 207. 48. J. L. Xu and M. M. Davis, Diversity in the CDR3 region of VH is sufficient for most antibody specificities. Immunity, 2000, 13, 37. 49. C.-A. Reynaud, L. Quint, B. Bertocci, and J.C. Weill, Introduction: what mechanism(s) drive hypermutation? Seminars in Immunology, 1996, 8, 125. 50. E. J. Steele, H. S. Rothenfluh, and R. V. Blanden, Mechanism of antigen-driven somatic hypermutation of
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
13
rearranged immunoglobulin V(D)J genes in the mouse. Immunology and Cell Biology, 1997, 75, 82. D. Sblattero, and A. Bradbury, Exploiting recombination in single bacteria to make large phage antibody libraries. Nat. Biotechnol., 2000, 18, 75. A. Desmyter, K. Decanniere, S. Muyldermans, and L. Wyns, Antigen specificity and high affinity binding provided by one single loop of a camel single-domain antibody. Journal of Biological Chemistry, 2001, 276, 26285. H. Dooley, M. F. Flajnik, and A. J. Porter, Selection and characterization of naturally occurring single-domain (IgNAR) antibody fragments from immunized sharks by phage display. Molecular Immunology, 2003, 40, 25. L. Xu, P. Aha, K. Gu, R. G. Kuimelis, M. Kurz, T. Lam, A. C. Lim, H. Liu, P. A. Lohse, L. Sun, S. Weng, R. W. Wagner, and D. Lipovsek, Directed evolution of highaffinity antibody mimics using mRNA display. Chemistry and Biology, 2002, 9, 933. S. E. Hufton, N. van Neera, T. van den Beukena, J. Desmet, E. Sablond, H. R. Hoogenboom, Development and application of cytotoxic T-lymphocyte-associated antigen 4 as a protein scaffold for the generation of novel binding ligands. FEBS Letters, 2000, 475, 225. ˚ Nygren, E. Gunneriusson, K. Nord, M. Uhl´en and P.-A. Affinity maturation of a Taq DNA polymerase specific affibody by helix shuffling. Protein Engineering, 1999, 12, 873. G. Beste, F. S. Schmidt, T. Stibora, and A. Skerra, Small antibody-like proteins with prescribed ligand specificities derived from the lipocalin fold. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96, 1898. S. Schlehuber and A. Skerra, Lipocalins in drug discovery: from natural ligand-binding proteins to ‘anticalins’. Drug Discovery Today, 2005, 10, 23. S. G. Sedgwick and S. J. Smerdon, The ankyrin repeat: a diversity of interactions on a common structural framework. Trends in Biochemical Sciences, 1999, 24, 311. H. K. Binz, P. Amstutz, A. Kohl, M. T. Stumpp, C. Briand, P. Forrer, M. G. Gr¨utter, and A. Pl¨uckthun, High-affinity binders selected from designed ankyrin repeat protein libraries. Nature Biotechnology, 2004, 22, 575.
7 Phage-Displayed Epitopes as Bioreceptors for Biosensors Danit Atias,1,2 Leslie Lobel,1 Marko Virta3 and Robert S. Marks2,4 1
Department of Virology, Ben-Gurion University of the Negev, Beer-Sheva, Israel, 2 Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel, 3 Department of Applied Chemistry and Microbiology, University of Helsinki, Helsinki, Finland and 4 National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
1 INTRODUCTION
“Phage display”, first introduced by George Smith,1 is a powerful technique that allows expression and presentation of peptides or proteins on the surface of phages. According to this method, a coding domain of interest is fused to that of a bacteriophage coat protein, resulting in phage particles that display the encoded protein as a chimeric protein.2,3 This procedure can also be performed with an ensemble of coding domains resulting in a phage library that can potentially contain billions of phage variants (up to 1010 ).3 In general, the DNA that encodes the displayed protein is encapsulated within the same virion, therefore providing a direct link between phenotype and genotype.2,4 This enables rapid amplification and characterization of the desired clone through DNA sequence analysis of the insert. Phage display has many advantages over other methods for recombinant protein expression including, ease of manipulation, protein folding, and ability to affinity mature a collection of recombinant molecules to identify those with the highest affinity.3,5,6 Phage display is not limited
to short peptides as it can be used to express polypeptides of a variety of sizes and with varied biological activity (e.g., cytokines, antibodies, receptors, enzymes, DNA binding proteins).4 In particular, phage display can solve some of the problems that result from using antibodies as recognition reagents. In some cases, antibodies are difficult to isolate because of the nonantigenic nature of the analyte, or because the target to be analyzed consists of a special matrix that is not compatible with antibody function. Additionally, conventional polyclonal antibody technology is time consuming and requires much manpower to obtain antisera from animals, whereas production of monoclonal antibodies is also complicated and time consuming.7,8 Phage libraries are screened and enriched by a process known as biopanning. In this technique, a phage library is incubated with an immobilized target. Few phages in the population with an affinity for the target attach to the receptor molecule, while the remaining phages, which do not bind, are washed away. Bound phages are subsequently eluted following thorough washing. Infection of bacteria with the eluted phage results in amplification of the recombinant phage. After several
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
rounds of such enrichment, a phage population with high affinity and specificity to the target can thereby be obtained.8
2 BIOLOGY OF PHAGES
Bacteriophages, like animal viruses, can be divided into those containing RNA genomes (typically small and single stranded), those with small DNA genomes (generally less than 10 kb, usually single stranded), and those with medium to large DNA genomes (30–200 kb, double-stranded DNA genomes). The last group includes most of the temperate phages, as well as the first virulent phage to be studied intensively.9 Bacteriophages can further be classified according to three primary types of life cycles: lytic, temperate, and filamentous. Lytic or virulent phages can only multiply in bacteria, and kill the cell by lysis at the end of the life cycle. Examples of this group are the tailed phages T7, T3, and T4 that were originally isolated as a member of the seven Type phages that grow in Escherichia coli (E. coli ) B.10 Temperate or lysogenic phages are those that can either multiply via the lytic cycle or may enter a quiescent state in the cell. Whereas most of the phage genes are not transcribed in the quiescent state, the phage genome exists in a repressed state. The phage DNA, in this repressed state, is called a prophage because it is not a phage but it has the potential to produce a phage. In most cases, the phage DNA actually integrates into the host chromosome and is replicated along with the host chromosome. The lysogenic state may persist indefinitely. The cell harboring a prophage is termed a lysogen. The λ phage is one notable example of this group of phages.9,11 Filamentous phages consist of a group of bacteriophages that do not lyse their host cells but rather are secreted from the bacterium.12,13 More importantly, capsid proteins that are displayed on the membrane of the phage are secreted into the periplasmic space of the bacterium where they fold prior to secretion of the phage. The periplasmic space of E. coli provides a favorable redox potential (as compared to the bacterial cytoplasm) for proper folding of disulfide-linked proteins. As such, recombinant proteins tethered to filamentous phage capsid proteins tend to fold in their native conformation when expressed for display on the surface of the filamentous phage.
In this overview on phage display systems, we focus on two common phages, the filamentous and the T7 phage. Both have been utilized for display of recombinant proteins on the surface of phage and have mature vector systems. In addition, each has its own unique advantages for incorporation into biosensors that will be examined in the subsequent text.
2.1
Biology of T7 Phage
2.1.1 Structure of the Virion
T3 and T7 virions have very similar structures (Figure 1) consisting of an icosahedral capsid (the head) with a diameter of 60–61 nm, which encloses a volume of about 105 nm3 .10,14–17 The T7 phage genome contains 39 936 base pairs (bp) of linear double-stranded DNA.9 The DNA has a center-to-center helix spacing of 2.4 nm, in β form.18 The capsid shell consists of 415 molecules of two forms of the gene 10 protein (gp10A and gp10B).14,19–21 Inserted at one vertex of the capsid is the head–tail connector, composed of 12 gp8 molecules.22,23 The connector has a 12-lobed wide domain inserted into the head cavity and a narrower domain that interacts with the tail.24 A channel in the narrower domain almost closes along the wider domain, probably according to DNA packaging during assembly. 25,26 Inside the head, and attached to the head–tail connector in the coaxial orientation, is a 26 × 21 nm2 cylindrical structure that is usually referred to as the internal core.27 The core, which exhibits eightfold symmetry,28 consists of stacked rings and contains three distinct proteins, gp14, gp15, and gp16.14 The genome is spooled around the internal core in six coaxial shells.15,18 The stubby tail is 23 nm long, tapering from a diameter of 21 nm at the connector to 9 nm at its distal end, and is known to consist of several proteins like gp11, gp12, and gp 7.3, the exact position of gp 7.3 has not yet been determined. Particles assembled in the absence of gp 7.3 actually fail to adsorb to cells.10,15 Attached to the tail are six symmetrically positioned tail fibers. Each fiber is composed of a trimer of gp17 that forms a kinked structure.29,30 The tail fibers are attached through the N-terminal 150 residues of gp17; the next 117 residues form a rod that is flexibly joined to the distal half of
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
3
Capsid gp10A+B
Internal core gp14, gp15, gp16 Head protein gp6.7 Connecter gp8 Tail protein gp7.3
Major tail gp11, gp12
Tail fiber gp17 Figure 1. Schematic diagram of T7 virion. [Reprinted from Kemp et al.14 , copyright 2005, with permission from Elsevier.]
the fiber. The latter consists of a linear array of four globules that is thought to bind directly to the bacterial cell.14,29 gp11 gp12
2.1.2 Life Cycle (Adsorption, Penetration, Replication, Assembly, and Lysis)
Adsorption and Initiation of Infection Bacteriophage T7 initiates an infection in E. coli by the interaction of its tail fibers with the lipopolysaccharide (LPS) on the cell surface (Figure 2). However, the stubby T7 tail is too short to span the E. coli cell envelope, and a channel needs to be made to allow the phage genome to travel from the virion into the cytoplasm. It was proposed that virion proteins are ejected into the cell and function as an extensible tail to form a channel across the cell envelop, in contrast to the well-known contractile tail of T4. This channel is subsequently used for translocation of the phage genome into the cell (Figure 2).14,15 Replication and Gene Expression Immediately after infection, the phage nucleic acid takes over the host biosynthetic machinery and phage specified mRNAs and early proteins are
gp14 gp15 gp16 gp6 gp17 Outer membrane Peptidoglycan Inner membrane gp16/gp15
gp14
Figure 2. Internal core proteins (18 molecules of gp14, 12 of gp15, 3 of gp16) ejected from the T7 particle form an extensible tail, providing a channel for DNA transport into the cell. The head–tail connector (gp8), tail (gp11 + gp12), and tail fibers (gp17) are also indicated. [Reprinted with permission Molineux15 copyright 2001, Blackwell Publishing Ltd.]
made. Host RNA polymerase initiates transcription from a promoter near the left end of the molecule, whose products include an antirestriction factor, a protein kinase that phosphorylates and inactivates E. coli RNA polymerase, a new T7-specific RNA polymerase, and a DNA ligase. After a few minutes, T7 polymerase replaces host polymerase and all transcription takes place on 81% of the genome toward the right end. Early proteins are needed for phage DNA synthesis, shutting off host DNA and
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
protein biosynthesis. The first genes transcribed by T7 polymerase (nearer to the left end) include a DNA polymerase and recombination genes. Later, after replication ensues, the late genes encoding virion components and at least one lysis gene are expressed. Late gene expression does not require replication, as it does in T4. The first cycle of DNA replication proceeds bidirectionally from a unique origin on the linear monomer.9,31 Because DNA polymerase moves only in one direction, unit-size DNA has no means of replicating the 3 terminal gaps, which arise by excision of primer RNA. To solve this problem, T7 replication generates concatemers that form by hybridization of the unreplicated 3 redundant regions of newly synthesized DNA.9,31 To complete replication, T7 completes the left and right ends of the genome, a task facilitated by the terminal redundancy of the T7 genome; the first and the last 160 bp are identical.9,31 Virion Assembly At this stage, the nucleic acid and structural proteins that have been made are assembled and infectious phage particles accumulate within the cell. Assembly starts with proheads that contain the proteins gp8, gp10, gp14, gp15, gp16, and scaffolding protein gp9.10,31,32 In the presence of gp18 and gp19 plus DNA, packaging begins. Mature phage particles do not contain the protein gp9, gp18, and gp19. Final DNA maturation and completion of packaging are synchronous.31 A connector protein and three core proteins assemble and are used as an initiator for scaffold and capsid protein assembly. Alternatively, the scaffold and capsid proteins may assemble to form incomplete prohead shells, which are then closed by insertion of a connector–core complex.10,33 After DNA packaging, the tail proteins collectively assemble on the full head. Separated tail structures that are without connection to the head are not found.10 Lysis and Release Following assembly of phage particles, bacterial hosts begin to lyse because of the accumulation of the phage and lysis proteins and intracellular phages are released into the medium. The only T7 proteins known to function in lysis are the products of genes 3.5 (lysozyme) and 17.5 (holing).31,34 Gene 3.5 was initially thought to be responsible only for cell lysis. It has been demonstrated, however, that its most important
function is in control of initiation and termination by T7 RNA polymerase, which in turn affects DNA replication and packaging.12,34,35 T7 lysozyme is also an N -acetylmuramyl-L-alanine amidase, which breaks up the peptidoglycan wall. The lysozyme is blocked from access to the cell wall by the inner membrane. It has been suggested that at some point, the phage-encoded holing (gp17.5), enlarges the membrane penetrability, which exposes the peptidoglycan wall to lysozyme, and rapid lysis of the cells then ensues.34,36 T7 Phage Display The T7 phage is released by cell lyses and the translocation of fusion proteins through the cell membrane/wall is thus avoided. The biology of the T7 phage is very well understood and offers a variety of host–vector systems for a range of applications.10 It is reported that the vector T7Select415-1b, Novagen, is capable of accepting peptides of up to 40–50 amino acids in length for display at 415 copies per particle.37–40 The vector T7Select1-1b, from Novagen, is designed for display of peptides and proteins of less than 1 copy per phage particle and can tolerate fusions of up to 900–1200 amino acids at that display density.41 cDNA libraries constructed with the T7Select1-1b system or its derivatives have been used for display and panning against a variety of different targets including small molecule chemical probes.42–46 The T7 display (select 1–2 series) system has also been used to select for RNA binding proteins from cDNA libraries.47 Lehmann et al. reported that in an indirect enzyme linked immunosorbent assay (ELISA), C-terminal T7 phage display systems have some major advantages in comparison with N-terminal pVII or pIII filamentous phage display systems.40 2.2
Biology of Filamentous Phages
Filamentous phages constitute a large family of bacterial viruses that infect mainly gram-negative bacteria. Their defining characteristic is a circular, single-stranded deoxyribonucleic acid (ssDNA) genome which is encased in a long flexible cylinder.2,48 The best characterized of these phage are M13, f1, and fd, which infect E. coli containing the F conjugative plasmid; these filamentous phage are those that have been used for phage display.41
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
Because of their similarity in structure, homologous genomes, and their dependence on the F plasmid for infection, M13, f1, and fd are collectively referred to as the F-specific filamentous (Ff ) phage; unless specified, the properties of filamentous phage described in the subsequent text refer to the Ff phage. Unlike most bacterial viruses, a normal assembly process in filamentous phages ends with secretion from the infected bacteria of the phage particles without cell killing or lysis.2,12 2.2.1 Structure of the Phage Particle
Filamentous phages have a fixed diameter of about 6.5 nm with length determined by the size of their
5
genome, which is normally 6–7 kb. The 6400nucleotide ssDNA of Ff phages is encapsidated in a 930-nm particle, whereas a 221-nucleotide “microphage” variant is 50 nm long.49 Cloning DNA into a nonessential region of the genome can create longer phage particles, although the longer they are, the more sensitive the particles are to breakage.2,12 Phage particles are normally composed of five coat proteins (Figure 3) arranged in a long, flexible cylinder approximately 7 nm wide by 900–2000 nm in length, depending upon the size of the recombinant genome. The cylinder is composed of thousands of copies of a single major coat protein, pVIII, oriented at a 20◦ angle from the particle axis and overlapped like fish scales to
pIX
pVII
II/X (a)
V
VII IX VIII
Replication
III
VI
Virion
I / IX
IV
Assembly /export pVIII
FT bacteriophage
E.coli
ps
pVI ssDNA Gene expression
TolA
F pIIus pIII
dsDNA (RF)
(c)
pIII + pVI
pVIII
pI/pXI + pIV
pV dimers
pVII + pIX
Thioredoxin
(b)
Figure 3. Filamentous phage: (a) genes and gene products,2 (b) structure [Reproduced from Arap3 by permission of the Brazilian Society of Genetics] and (c) life cycle.2
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
form a right-handed helix.50 The pVIII protein is a commonly used coat protein for mulitcopy phage display. Electron microscopy reveals that each end of the particle has a distinct morphology.2,12 The blunt end contains three to five copies each of pVII and pIX capsid proteins. Immunological evidence indicates that at least some of pIX is exposed51 and antibody variable regions have been successfully displayed on the amino termini of pVII and pIX.52 This data indicates that probably the N-termini of both proteins are at or near the surface.12 Phage assembly begins at the pVII–pIX end, and in the absence of either protein, no particle is formed.53 The other end of the particle is pointed and lollipop–like knobs can be seen extending from the tip in certain preparations.54 This end contains about five copies each of pIII and pVI, both of which are needed in order for the phage to enter and detach from the cell membrane; without these two proteins assembly cannot terminate.2,12 The N-terminal domain of pIII binds to bacterial cell receptors, the tip of the pilus, and the C-terminal domain of TolA.55 pIII can only incorporate into the particle if pVI is present.56 The 406-residue pIII capsid protein is responsible for the “knob” structure at the end of the phage particle.57 The phage genome is oriented within the phage particle. Its orientation is determined by the packaging signal (PS), which is located in the noncoding IG region of the genome (IG located near gene IV). The PS is positioned at the pVII-pIX end of the particle and is necessary for efficient encapsidation of circular ssDNA into phage particle.58
2.2.2 Life Cycle (Adsorption, Penetration, Replication, Assembly, and Lysis)
Infection Filamentous phages utilize the F-factor encoded bacterial pilus (conjugative pilus) as a primary receptor for infection of bacterial cells (Figure 3). Infection normally begins when the N2 (or D2) domain of the capsid pIII protein binds the tip of a F pilus from a E. coli cell.12,59 The interaction between N2 and the pilus releases the N1 (or D1) domain from its normal interaction with N2 making it available to bind a discrete domain (D3) of the bacterial TolA protein.59–61 Three Tol proteins (Q, R, and A) are required for phage infection.62–65 They mediate depolymerization of the phage coat
protein into the cytoplasmic membrane and the translocation of the viral ssDNA into the bacterial cytoplasm, although the details of how this process is accomplished remain unclear. Replication Once the viral ssDNA enters the cytoplasm, host enzymes (RNA and DNA polymerases, topoisomerase, and gyrase) convert it into a doublestranded, supercoiled molecule called the replicative form (RF). The RF serves as a template for phage gene expression and rolling circle replication, which generates an ssDNA molecule. Early after infection when the concentration of the phage-encoded ssDNA-binding protein (pV) is low, newly synthesized ssDNAs are converted to RFs and both RF and phage protein increase exponentially. When sufficient pV has accumulated, pV dimers cover the ssDNA and prevent polymerase access, thereby blocking their conversion to RF. The pII (or pX) protein is required for the stable accumulation of ssDNA at this stage, but the mechanism by which it acts is not known.66,67 The DNA is oriented in pV–ssDNA complexes, with the PS hairpin protruding from one end; this complex is a substrate for phage assembly.68 Genes and Gene Expression The Ff genome contains nine closely packed genes and one major noncoding region (IG), which contains the origin of replication for “+” and “–” strand synthesis, and the PS. Two of the phage genes (I and II) have internal start sites from which in-frame restart proteins are produced. Both kinds of proteins are necessary for successful phage production. The phage genome encodes for 11 proteins, 3 (pII, pX, and pV) are needed to generate ssDNA, 3 (pI, pXI, and pIV) are required for phage assembly, and 5 (pIII, pVI, pVII, pVIII, and pIX) are part of the phage particle (Table 1). All phage proteins are synthesized concurrently, but at an appropriate rate.2,12 Assembly Filamentous phages assemble and are secreted by a unique process that does not kill or lyse bacterial cells. Assembly takes place in the cytoplasmic membrane, and nascent phages are secreted from the cell as they assemble. The eight phage-encoded proteins that are directly involved in assembly are integral membrane proteins. Two nonvirion proteins are located on the cytoplasmic membrane (pI
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
7
Table 1. Comparison between filamentous proteins that are used for display2,41
Type of protein
Size (aa)
Location
Type of display
Type of fusion
References
pIII
406 (mature protein without signal sequence)
Virion tip (end)
C- and N-terminal
69–82
pVI
112
Virion tip (end)
C-terminal
83,84
pVII
33
Virion tip (start)
N-terminal
52
pVIII
50 (mature protein without signal sequence) 32
Virion filament
Peptides and functional proteins (large insertions), cDNA cloning, antibodies, cytokines, receptors, enzymes, enzymes inhibitors, DNA binding proteins, cellulose binding proteins, Polypeptides encoded by cDNA, enzymes, enzymes inhibitors Peptides, fusion of antibody fragments, enzymes, enzymes inhibitors Short peptides
C- and N-terminal
2, 12, 85–88
N-terminal
52
pIX
Virion tip (start)
and its restart partner, pXI).2,89 Another nonvirion protein (pIV) is located at the outer membrane and used as a channel.2,90 The five viral coat proteins (pIII, pVI, pVII, pVIII, and pIX) reside in the cytoplasmic membrane prior to their incorporation into the phage.51 Two of these proteins, pIII and pVIII, are synthesized as precursors. The first progeny phage particles can be found in the culture supernatant about 10 min after infection (at 37 ◦ C). The phage numbers increase exponentially for about 40 min, after which the rate becomes linear. About 1000 phages per cell are produced during the first hour. Under optimal conditions, the infected cells can continue to grow and divide and, thus, produce phage indefinitely. Assembly sites are composed of the three morphogenetic proteins, pI, pXI, and pIV, which interact via their periplasmic domains. Phage assembly begins when pI recognizes the PS, which protrudes from one end of the pV–ssDNA complex. Initiation takes place only if the two minor coat proteins (pVII and pIX) are located at the tip of the particle and the ssDNA is present.91 It is believed that pVII and pIX interact with the PS.92 During elongation, pV is removed from the ssDNA and several thousand copies of pVIII are added to the ssDNA. The elongation requires host thioredoxin (TrxA) and ATP hydrolysis, presumably by pI. When the end of the DNA is reached, assembly is terminated by
Fusion of antibody fragments
the addition of pIII and pVI, and a conformational change in pIII, which detaches the nascent particles from the membrane through the pIV channel. 2.2.3 Filamentous Phage Display
All five coat proteins have been used to display proteins or peptides, to varying degrees (Table 1). However, by far the most commonly used virion proteins for phage display are pVIII and pIII. pVI has been shown useful for display through a C-terminal fusion.83 pVII and pIX have been used for fusion of antibody fragments to their Ntermini.52 pIII is commonly used for phage display of functional proteins because of its tolerance for large insertions, its compatibility with monovalent display, and the broad availability of appropriate vectors. pIII fusions are typically constructed at the N-terminus but pIII C-terminal fusions are also possible through a linker peptide.69 pVIII phage display systems are mainly useful for display of short peptides sequences tethered to every copy of the protein on the phage capsid. These sequences are inserted typically at the N-terminus of the pVIII capsid protein.2 The main difference between pIII and pVIII phage display systems is in the capacity of the former to display large proteins in, on average, a single copy and of the
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
latter to optimally display peptides in many copies on the capsid.41,93–95 Large proteins can also be displayed tethered to pVIII; however, the copy number of these molecules on the surface of the capsid is limited by strict hindrance to only a few copies, and a wild-type copy of the pVIII gene must also be supplied in these recombinants for proper phage assembly.2,41,94 Small peptides (6–10 residues) tethered to pVIII can be expressed in approximately as many as 2700 copies on the surface of the phage particle, and wild-type copies of pVIII, in this case, are not required.2,41,96 In addition to the display of single proteins and peptides, filamentous phages have also been utilized for the production of phage display libraries that express all open reading frame (ORFs) within a given cDNA library. Filamentous phage display libraries of this type have proved useful for identification of bacterial proteins as well as domains that interact with a range of target molecules.97–99 In some cases, recombinant proteins within these libraries can be toxic to filamentous phages or interfere with release of the recombinant capsid protein. Therefore, special phagemid systems have been developed to facilitate toxic protein display.100 3 PRINCIPLES OF PHAGE DISPLAY
One of the most impressive aspects of phage display is the variety of uses for the technology.13 The main applications are discussed in the subsequent text. As an example, phage display libraries expressing a vast variety of peptides and proteins on their surface, such as epitope targets of antibodies, have been used for the development of probes for the detection of biological threat agents.6 Another example is the use of phage display for diagnosis and therapy of diseases such as cancer.101 3.1
Phage Display of Natural Peptides
There are several applications for display of natural peptides on a phage particle13 : 1. Mapping epitopes of monoclonal and polyclonal antibodies In this application, DNA segments encoding peptides that are approximately 10 amino acid
long are inserted into the coding domain of a capsid protein and thus are expressed on the phage capsid. These short peptides consist of linear epitopes from the original antigenic protein. A library of this phage can then be screened against a given antibody to identify the specific epitope to which it binds. The peptide fragments from the original protein are chosen such that there is as complete a representation as possible of the original protein.102–105 2. Generating immunogens Phage display can also be used for the purpose of generating immunogens. Short peptides derived from the coat proteins of certain pathogens can be expressed on a phage and used to elicit or identify antibodies against these pathogenic epitopes.106,107 This method might be used for vaccination purposes and diagnostics methods.108–110
3.2
Phage Display of Random Peptides
Random peptide phage display libraries, in general, consist of a combinatorial representation of all linear peptide epitopes of a defined length. These segments are produced by the production of degenerate synthetic oligonucleotides with a specified length that are cloned into the capsid protein of a phage. This method is useful for producing combinatorial peptide libraries. They can then be screened to identify members that bind to target molecules of interest. This is usually performed by means of “biopanning”, an affinity selection technique.8 After screening and enrichment of phages that bind the target molecule, the primary structure of the peptide can be deduced by means of DNA sequencing of the original insert. This method has proved successful for identifying peptides that bind to antibodies, cell surface receptors, cytosolic receptors, extracellular and intracellular proteins, DNA, and many other targets.13 This method is useful for several applications such as: 1. Mapping epitopes of monoclonal and polyclonal antibodies As previously described, random peptide libraries can be used in the same manner to map the target epitopes of polyclonal and monoclonal antibodies.105 This approach can prove invaluable
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
for some of these mapping processes.3 It has been successfully used to identify immunodominant peptide sequences of antigens, generate peptide competitors of antigen–antibody interactions, and map accessible and/or functional sites of numerous antigens.8,13,105,111,112 2. Identifying peptide ligands A great variety of potential ligands for a vast array of receptors is present in a random peptide library.113 In some cases, the peptides resemble the receptor’s ligand in terms of sequence. In other cases, the ligand mimics the binding of a nonprotein ligand. A number of successful studies using this method have been published.13,114–116 3. Defining post-translational substrate sequences The development of “substrate phage” is another important application of this technology. In this case, libraries are not used for simply identifying a ligand for a target molecule but rather for defining substrate specificity. Many different posttranslational modifications can also be mapped using this approach.117,118 3.3
Phage Display of Proteins or Protein Domains
In this approach, whole proteins or specific domains are displayed on the phage.101 Even though these proteins and domains are tethered to a phage protein, they usually retain their normal binding and enzymatic activity. This method allows for fast screening of a large number of mutant proteins when trying to identify those with altered or improved affinity for a target.13 A few applications are as follows: 1. Directed evolution of proteins Proteins or various subdomains are expressed on the phage such that they retain their normal binding to a target molecule. The coding sequences of these proteins or subdomains are then mutated by either cassette mutagenesis, errorprone PCR, or shuffling to generate a vast range of altered sequences.3,8 The members of such a mutant library, containing greater than 108 phages, can be isolated through an appropriate screen for those that have the desired binding properties. Furthermore, the displayed protein sequence of an
9
isolated, plaque-purified phage can be easily determined through DNA sequencing of the construct. For example, novel enzyme inhibitors have been identified by this method.104,119 2. Isolation of high-affinity antibodies One of the most promising applications of the phage display technology is the ability to isolate recombinant antibodies (expressed as single-chain variable fragments) with a desired binding property for a wide variety of antigens. The antibody library is generated by a random combination of variable light (VL ) and variable heavy (VH ) chain coding domains produced as single-chain variable antibody fragments (scFvs).13,120,121 Once the library is constructed, it can be screened against any desirable antigen by the biopanning technique. Many recombinant antibodies that were isolated by phage display showed high affinity and specificity.122–124 This method has helped overcome some of the current limitations in generating human monoclonal antibodies or humanizing mouse antibodies. It is cost effective, less time consuming, and a relatively easy technique.8 However, once a suitable scFv is isolated by phage display it needs to be reengineered into a human antibody backbone and tuned for optimal specificity and sensitivity. The reengineered human soluble recombinant antibodies can then be produced in cell culture systems and used as in vitro diagnostic reagents.8 3. cDNA expression screening Protein–protein interactions have also been investigated with phage-displayed libraries. For this purpose, we do not wish to explore all combinatorial combinations of amino acids as defined by random peptide libraries but merely the amino acid combinations defined by the genome under study. To this end, it is possible to express cDNA encoded proteins on the surface of the phage, which can then be tested against particular immobilized targets in vitro using biopanning enrichment. The yeast two-hybrid system is the traditional method for identifying protein– protein interactions. While phage systems obviously lack post-translational modifications, they offer a number of advantages including the capability of constructing a more complete cDNA library than can be currently done in yeast. In
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
production of wild-type proteins. A new phage was produced with pVIII protein displaying the various epitopes (Figure 4). This offers an efficient solution when simultaneous analysis of binding to multiple epitopes is required or even increasing the density of specific bioreceptors. Furthermore, it affords a simple solution for incorporation of multiple peptides into a small footprint diagnostic system and is especially suited for inclusion in nanoscale-based diagnostics such as in lab-on-achip technology. The ability to simultaneously display two different peptides on the surface of filamentous (fd) bacteriophages has been shown in 1997. Cells that contain a plasmid with modified gene pVIII were infected with an engineered bacteriophage carrying
addition, they can be readily used to demonstrate a direct physical interaction by in vitro biopanning.13
3.4
Multiple Display Phage
An innovative way of utilizing phage display for simultaneous recognition of multiple epitopes has recently been developed. In this system, filamentous (M13) phage particles (pVIII capsid protein) display multiple distinct peptides on their surface, each of them in multiple copies. A phagemid encoding 5 epitopes from the West Nile virus (WNV) was introduced to E. coli cells JM109 (DE3) (Promega). These cells were infected with helper phage (VCSM13) in order to enable the 3a
p8
p8
p8
p8
p8
p8
p8
p8 E1 P8
p10
p9
p1
1
f1 (+) origin lac Z T7 E1 P8 E2 E3 P8 E4
p6
P3
E5 P8
p8
p4
E3 P8 E4 P8
E4 P8 2
E1 P8
E5 P8 E2 P8
E3 P8
E P8 4
P8
E5
P8
p8
E2 P8
E3 P8
T3
p8 p2
3c
P8
Col E1 origin
p7
E1 P8 2 E 8 P
E1 E2 P8 P8
Phagemid 4599 bp
p5
p8
4
E1 8 P
AmpR
p8
E3 P8
p8
3b
E4 P8
p8
E2 P8
p8
E3 P8
p8
E4 P8
p8
E5 8 P
p8
8 E5 p P8
Figure 4. Multiple display phage system. (1) Transformation of a phagemid, containing five epitopes, each one fused to p8 protein, to competent E. coli cells (JM109(DE3)). (2) Growing the cells; during this time the phagemid multiples. (3a) Infecting the cells with helper phage (VCSM13). (3b) Production of wild-type proteins. (3c) Production of p8 with various epitopes and fusion peptides. (4) Assembly and secretion of recombinant phages display multiepitope.
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
a second and different copy of modified gene pVIII. Hybrid virions were created in which the pVIII capsid protein consists of a mixture of the wild type and two modified coat proteins carrying different peptide inserts.125 Only recently the ability to display different peptides on the surface of T4 phages was shown.126 Multiple components of human immunodeficiency virus (HIV) were displayed on the capsid protein of T4 phages in order to construct multicomponent HIV vaccines. The assembly system allows display of three different HIV antigens, on capsid surface through Hoc–capsid interactions. In-frame fusions were constructed by splicing the HIV genes to the end of the hoc gene. The Hoc fusion proteins were expressed, purified, and displayed on hoc– phage particles in a defined in vitro system. Single or multiple antigens were efficiently displayed, leading to saturation of all available capsid binding sites. This system offers a new direction and insights for HIV vaccine development with the potential to increase the breadth of both cellular and humoral immune responses.126
4 USE OF PHAGE DISPLAY EPITOPES IN BIOSENSORS
The term biosensor generally refers to an analytical device based on the combination of recognition biomolecules with an appropriate transducer that is capable of detecting chemical or biological materials selectively and with a high sensitivity. Ultimately, the signal of the recognition event can be detected by electrochemical, optical, acoustic, or calorimetric transducers, and so on. They give detailed information on the binding affinity and in many cases also the binding kinetics of an interaction. Typically, one of the molecules is tethered in some way to a transducer that can then be monitored by a computer.127
4.1
Fiber-optic Phage Immunosensors
Optical fiber biosensors based on biological or chemical luminescence have already demonstrated their ability to detect biological entities.128–130 In this method, the photon reading instrument is based on a photomultiplier tube (PMT). It has
11
been demonstrated that optical fiber biosensors are more sensitive than standard colorimetric and chemiluminescent ELISA-based assays.128 Several investigators have demonstrated the potential of phage display-based sensor reagents that are coupled to a fiber optic and employ an ELISAbased detection method. Goldman et al. showed the potential of utilizing phage-displayed peptides as a reagent in sensor applications. They scanned phage-displayed random peptides library against staphylococcal enterotoxin B (SEB) and found and isolated the phage with specificity for SEB. The isolated phage clone was labeled and studied using ELISA, fluorescence microplate assays, and fiber-optic biosensors. In this research, they used a RAPTOR automated fiber-optic biosensor.7
4.2
Optical Biosensors Based on Surface Plasmon Resonance
Surface plasmon resonance (SPR) is an electron charge–density wave phenomenon that arises at the surface of a metallic film when light is reflected at the film under specific conditions. The resonance is a result of energy and momentum being transformed from incident photons into surface plasmons. Biosensors based on SPR enable observation of binding rates and binding levels that offer the possibility to calculate kinetic parameters, specificity and affinity of the interactions, and the concentration of the analyte.127 An extremely wide range of molecules can be analyzed, from small molecular weight drugs to multiprotein complexes and phage particles, with interaction affinities ranging from millimolar to picomolar.127,131 Combination of phage-displayed technique with optical biosensors based on SPR such as BIAcore biosensor provides a powerful methodology for generating antibodies by genetic engineering (i.e., screening, selection, characterization, and epitope mapping). In addition, optical biosensors themselves provide a simple and rapid approach for analyzing recombinant antibodies and phagedisplayed antibody libraries.132,133 Furthermore, it enables facile selection of highaffinity binders from phage display libraries and identification of molecules with differing dissociation rate constants.133,134
12
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
H2Q Q
H 2O 2 H 2O phages (T7) display WNV
+ 2e− Anti WNV-Ab IgG
Polymer Electrode Goat anti mouse IgG HRP conjugated
Figure 5. Schematic representation of the functioning principle of the WNV amperometric immunosensor through HRP-conjugated secondary antibody that catalyzed the formation of electroactive quinone species (Q) in the presence of hydroquinone (HQ) as a substrate.138
4.3
Acoustic Biosensors
Acoustic biosensors, generally, are based on quartz crystal resonators and on the linear relationship between mass adsorbed to the surface and the resonant frequency of the crystal in air or a vacuum.127,135 Quartz crystal microbalance (QCM) sensors allow the label-free detection of molecules and the analysis of binding events by monitoring the change in resonant frequency and motional resistance that occurs upon adsorption of a ligand to a surface. The acoustic sensor is sensitive not only to the mass of bound ligand but also to changes in viscoelastic properties and charge of the receptor–ligand complex. The technology can thus be applied to an extremely wide range of biological and chemical entities, including molecules with a molecular weight range from less than 200 Da to intact eukaryotic cells. Acoustic biosensors have also been used to screen phage display libraries in order to identify and characterize molecule binding to a target of interest.127 Hengerer et al. compared QCM with ELISA and demonstrated that the QCM is well suited for the detection of single high-affinity clones isolated from large phage display libraries. They used these
methods for isolating antigen-specific recombinant antibodies and antigen-specific human pancreatic secretory trypsin inhibitor (hPSTI) mutant from a large phage library. Measurements were performed using a biotinylated antigen (protein of Legionella pneumophila) immobilized by streptavidin onto the gold surface of the quartz crystal and phages displaying recombinant antibodies or hPSTI mutants. For the analysis of large sample numbers, the QCM was integrated into a flow injection analysis system. The results obtained by the QCM were in accordance with those obtained by ELISA.135,136 They suggest that, in the future, controlling the enrichment procedure (i.e., panning) itself could be possible by using QCM. The stringency of the selection can be adjusted to the percentage of binding phages present in the library after each round of panning. This would facilitate the panning process and reduce the number of enrichment cycles necessary to isolate strong binders. Furthermore, combination of the enrichment and screening procedures is possible since the enrichment procedure may be performed on the antigen layer of the quartz crystal itself.135
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
4.4
Electrochemical Phage Immunosensors
An electrochemical biosensor is a self-contained integrated device, which is capable of providing specific quantitative or semiquantitative analytical information using a biological recognition element (biochemical receptor), which is retained in direct spatial contact with an electrochemical transduction element.137 Recently, an anti-WNV IgG amperometric immunosensor based on the immobilization of phages displaying WNV peptides incorporated into a poly (pyrrole-alkyl ammonium) film electrogenerated at the surface of glassy carbon electrode was reported. The designed immunosensor has proved to have high analytical performances in terms of a low limit of detection (107 ), a fast response time (5–20 s), and great reproducibility (Figure5).138
5 PROSPECTS FOR THE USE OF PHAGE DISPLAY IN BIOSENSORS AND BIOCHIPS
Although phage display was first introduced over 20 years ago, the development and application of this technology is still being explored and new applications are constantly being found. Exploitation of phage display technology will lead to the isolation and production of a broad range of binders, including recombinant antibodies and peptides, with predefined specificities. Furthermore, emergent technologies based on phage display will benefit diagnostics by producing molecules that are otherwise unobtainable by traditional approaches. Specifically, recombinant antibodies against toxic antigens, nonimmunogenic sequences, and carbohydrates can be isolated.8 Exploitation of the advantages of the phage display system together with the ongoing development in the biosensor field will lead to revolutionary diagnostic devices.
REFERENCES 1. G. P. Smith, Filamentous fusion phage: novel expression vectors that display cloned antigens on the virion surface. Science, 1985, 228(4705), 1315–1317. 2. M. Russel, H. B. Lowman, and T. Clackson, Introduction to Phage Biology and Phage Display, in Phage Display a Practical Approach, H. B. Lowman and T. Clackson (eds), Oxford University Press, 2004, pp. 1–26.
13
3. M. A. Arap, Phage display technology-applications and innovations. Genetics and Molecular Biology, 2005, 28, 1–9. 4. I. Benhar, Biotechnological applications of phage and cell display. Biotechnology Advances, 2001, 19(1), 1–33. 5. G. Cesareni, L. Castagnoli, and G. Cestra, Phage displayed peptide libraries. Combinatorial Chemistry and High Throughput Screening, 1999, 2(1), 1–17. 6. V. A. Petrenko and V. J. Vodyanoy, Phage display for detection of biological threat agents. Journal of Microbiological Methods, 2003, 53(2), 253–262. 7. E. R. Goldman, M. P. Pazirandeh, J. M. Mauro, K. D. King, J. C. Frey, and G. P. Anderson, Phage-displayed peptides as biosensor reagents. Journal of Molecular Recognition, 2000, 13(6), 382–387. 8. H. M. Azzazy and W. E. Highsmith Jr., Phage display technology: clinical applications and recent innovations. Clinical Biochemistry, 2002, 35(6), 425–445. 9. A. M. Campbell, Bacteriophages, in Fields Virology, D. Mk. Bernard, N. Fields, and P. M. Howley (eds), Lippincott-Raven, 1996. 10. R. Calendar (ed), The Bacteriophages, Chapter 20—The T7 Group, 2nd Edn, Oxford University Press, 2006, pp. 277–301. 11. R. Calendar (ed), The Bacteriophages, Chapter 27— Lambda and its Genetic Neighborhood, 2nd Edn, Oxford University Press, 2006, pp. 409–447. 12. R. Calendar (ed), The Bacteriophages, Chapter 12— Filamentous Phage, 2nd Edn, Oxford University Press, 2006, pp. 146–160. 13. B. K. Kay and R. H. Hoess, Principles and Applications of Phage Display, in Phage Display of Peptides and Proteins, J. Winter, B. K. Kay, and J. McCafferty (eds), Academic Press, 1996, pp. 21–28. 14. P. Kemp, L. R. Garcia, and I. J. Molineux, Changes in bacteriophage T7 virion structure at the initiation of infection. Virology, 2005, 340(2), 307–317. 15. I. J. Molineux, No syringes please, ejection of phage T7 DNA from the virion is enzyme driven. Molecular Microbiology, 2001, 40(1), 1–8. 16. R. M. Stroud, P. Serwer, and M. J. Ross, Assembly of bacteriophage T7. Dimensions of the bacteriophage and its capsids. Biophysical Journal, 1981, 36(3), 743–757. 17. G. Ronto, M. M. Agamalyan, G. M. Drabkin, L. A. Feigin, and Y. M. Lvov, Structure of bacteriophage T7. Small-angle X-ray and neutron scattering study. Biophysical Journal, 1983, 43(3), 309–314. 18. M. E. Cerritelli, N. Cheng, A. H. Rosenberg, C. E. McPherson, F. P. Booy, and A. C. Steven, Encapsidated conformation of bacteriophage T7 DNA. Cell, 1997, 91(2), 271–280. 19. J. P. Condreay, S. E. Wright, and I. J. Molineux, Nucleotide sequence and complementation studies of the gene 10 region of bacteriophage T3. Journal of Molecular Biology, 1989, 207(3), 555–561. 20. B. G. Condron, J. F. Atkins, and R. F. Gesteland, Frameshifting in gene 10 of bacteriophage T7. Journal of Bacteriology, 1991, 173(21), 6998–7003. 21. B. G. Condron, R. F. Gesteland, and J. F. Atkins, An analysis of sequences stimulating frameshifting in the decoding of gene 10 of bacteriophage T7. Nucleic Acids Research, 1991, 19(20), 5607–5612.
14
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
22. M. E. Cerritelli and F. W. Studier, Purification and characterization of T7 head-tail connectors expressed from the cloned gene. Journal of Molecular Biology, 1996, 258(2), 299–307. 23. E. Kocsis, M. E. Cerritelli, B. L. Trus, N. Cheng, and A. C. Steven, Improved methods for determination of rotational symmetries in macromolecules. Ultramicroscopy, 1995, 60(2), 219–228. 24. J. M. Valpuesta, N. Sousa, I. Barthelemy, J. J. Fernandez, H. Fujisawa, B. Ibarra, and J.L., Carrascosa, Structural analysis of the bacteriophage T3 head-to-tail connector. Journal of Structural Biology, 2000, 131(2), 146–155. 25. L. E. Donate, L. Herranz, J. P. Secilla, J. M. Carazo, H. Fujisawa, and J. L. Carrascosa, Bacteriophage T3 connector: three-dimensional structure and comparison with other viral head-tail connecting regions. Journal of Molecular Biology, 1988, 201(1), 91–100. 26. A. Kuhn and E. Kellenberger, Productive phage infection in Escherichia coli with reduced internal levels of the major cations. Journal of Bacteriology, 1985, 163(3), 906–912. 27. P. Serwer, S. A. Khan, S. J. Hayes, R. H. Watson, and G. A. Griess, The conformation of packaged bacteriophage T7 DNA: informative images of negatively stained T7. Journal of Structural Biology, 1997, 120(1), 32–43. 28. M. E. Cerritelli B. L. Trus, C. S. Smith, N. Cheng, J. F. Conway, and A. C. Steven, A second symmetry mismatch at the portal vertex of bacteriophage T7: 8-fold symmetry in the procapsid core. Journal of Molecular Biology, 2003, 327(1), 1–6. 29. A. C. Steven, B. L. Trus, J. V. Maizel, M. Unser, D. A. Parry, J. S. Wall, J. F. Hainfeld, and F. W. Studier, Molecular substructure of a viral receptor-recognition protein. The gp17 tail-fiber of bacteriophage T7. Journal of Molecular Biology, 1988, 200(2), 351–365. 30. H. Kato, H. Fujisawa, and T. Minagawa, Subunit arrangement of the tail fiber of bacteriophage T3. Virology, 1986, 153(1), 80–86. 31. D. H. Kruger and C. Schroeder, Bacteriophage T3 and bacteriophage T7 virus-host cell interactions. Microbiological Reviews, 1981, 45(1), 9–51. 32. P. Serwer, R. H. Watson, and S. J. Hayes, Detection and characterization of agarose-binding, capsid-like particles produced during assembly of a bacteriophage T7 procapsid. Journal of Virology, 1982, 42(2), 583–594. 33. M. E. Cerritelli and F. W. Studier, Assembly of T7 capsids from independently expressed and purified head protein and scaffolding protein. Journal of Molecular Biology, 1996, 258(2), 286–298. 34. R. H. Heineman, I. J. Molineux, and J. J. Bull, Evolutionary robustness of an optimal phenotype: re-evolution of lysis in a bacteriophage deleted for its lysin gene. Journal of Molecular Evolution, 2005, 61(2), 181–191, Epub 2005 Jul 26. 35. X. Zhang and F. W. Studier, Mechanism of inhibition of bacteriophage T7 RNA polymerase by T7 lysozyme. Journal of Molecular Biology, 1997, 269(1), 10–27. 36. R. Young, Bacteriophage lysis: mechanism and regulation. Microbiological Reviews, 1992, 56(3), 430–481. 37. J. Castillo, B. Goodson, and J. Winter, T7 displayed peptides as targets for selecting peptide specific scFvs from
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
M13 scFv display libraries. Journal of Immunological Methods, 2001, 257(1–2), 117–122. H. Houshmand, G. Froman, and G. Magnusson, Use of bacteriophage T7 displayed peptides for determination of monoclonal antibody specificity and biosensor analysis of the binding reaction. Analytical Biochemistry, 1999, 268(2), 363–370. A. V. Sokoloff, I. Bock, G. Zhang, M. G. Sebestyen, and J. A. Wolff, The interactions of peptides with the innate immune system studied with use of T7 phage peptide display. Molecular Therapeutics, 2000, 2(2), 131–139. D. Lehmann, R. Sodoyer, and S. Leterme, Characterization of BoHV-1 gE envelope glycoprotein mimotopes obtained by phage display. Veterinary Microbiology, 2004, 104(1–2), 1–17. R. Calendar (ed), The Bacteriophages, Chapter 44— Phage in Display, 2nd Edn, Oxford University Press, 2006, pp. 686–694. M. H. Hansen, B. Ostenstad, and M. Sioud, Identification of immunogenic antigens using a phage-displayed cDNA library from an invasive ductal breast carcinoma tumour. International Journal of Oncology, 2001, 19(6), 1303–1309. S. N. Savinov and D. J. Austin, The cloning of human genes using cDNA phage display and small-molecule chemical probes. Combinatorial Chemistry and High Throughput Screening, 2001, 4(7), 593–597. P. P. Sche, K. M. McKenzie, J. D. White, and D. J. Austin, Corrigendum to: “Display cloning: functional identification of natural product receptors using cDNA-phage display” [Chemistry and Biology 6 (1999) 707–716] Chemistry and Biology, 2001, 8(4), 399–400. M. Yamamoto, Y. Kominato, and F. Yamamoto, Phage display cDNA cloning of protein with carbohydrate affinity. Biochemical and Biophysical Research Communications, 1999, 255(2), 194–199. K. Kataoka K. Yoshitomo-Nakagawa, S. Shioda, and M. Nishizawa, A set of Hox proteins interact with the Maf oncoprotein to inhibit its DNA binding, transactivation, and transforming activities. Journal of Biological Chemistry, 2001, 276(1), 819–826. S. Danner and J. G. Belasco, T7 phage display: a novel genetic selection system for cloning RNA-binding proteins from cDNA libraries. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98(23), 12954–12959, Epub 2001 Oct 23. M. C. Chopin, A. Rouault, S. D. Ehrlich, and M. Gautier, Filamentous phage active on the gram-positive bacterium Propionibacterium freudenreichii . Journal of Bacteriology, 2002, 184(7), 2030–2033. L. Specthrie, E. Bullitt, K. Horiuchi, P. Model, M. Russel, and L. Makowski, Construction of a microphage variant of filamentous bacteriophage. Journal of Molecular Biology, 1992, 228(3), 720–724. D. A. Marvin, Filamentous phage structure, infection and assembly. Current Opinion in Structural Biology, 1998, 8(2), 150–158. H. Endemann and P. Model, Location of filamentous phage minor coat proteins in phage and in infected cells. Journal of Molecular Biology, 1995, 250(4), 496–506. C. Gao, S. Mao, C. H. Lo, P. Wirsching, R. A. Lerner, and K. D. Janda, Making artificial antibodies: a format
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
for phage display of combinatorial heterodimeric arrays. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96(11), 6025–6030. J. Lopez and R. E. Webster, Morphogenesis of filamentous bacteriophage f1: orientation of extrusion and production of polyphage. Virology, 1983, 127(1), 177–193. C. W. Gray, R. S. Brown, and D. A. Marvin, Adsorption complex of filamentous fd virus. Journal of Molecular Biology, 1981, 146(4), 621–627. D. E. Bradley and J. Whelan, Escherichia coli tolQ mutants are resistant to filamentous bacteriophages that adsorb to the tips, not the shafts, of conjugative pili. Journal of General Microbiology, 1989, 135(7), 1857–1863. J. Rakonjac, J. Feng, and P. Model, Filamentous phage are released from the bacterial membrane by a twostep mechanism involving a short C-terminal fragment of pIII. Journal of Molecular Biology, 1999, 289(5), 1253–1265. J. Armstrong, R. N. Perham, and J. E. Walker, Domain structure of bacteriophage fd adsorption protein. FEBS Letters, 1981, 135(1), 167–172. J. Griffith, M. Manning, and K. Dunn, Filamentous bacteriophage contract into hollow spherical particles upon exposure to a chloroform-water interface. Cell, 1981, 23(3), 747–753. L. W. Deng, P. Malik, and R. N. Perham, Interaction of the globular domains of pIII protein of filamentous bacteriophage fd with the F-pilus of Escherichia coli . Virology, 1999, 253(2), 271–277. L. Riechmann and P. Holliger, The C-terminal domain of TolA is the coreceptor for filamentous phage infection of Escherichia coli . Cell, 1997, 90(2), 351–360. I. Stengele, P. Bross, X. Garces, J. Giray, and I. Rasched, Dissection of functional domains in phage fd adsorption protein. Discrimination between attachment and penetration sites. Journal of Molecular Biology, 1990, 212(1), 143–149. T. P. Sun and R. E. Webster, fii, a bacterial locus required for filamentous phage infection and its relation to colicintolerant tolA and tolB. Journal of Bacteriology, 1986, 165(1), 107–115. T. P. Sun and R. E. Webster, Nucleotide sequence of a gene cluster involved in entry of E colicins and singlestranded DNA of infecting filamentous bacteriophages into Escherichia coli. Journal of Bacteriology, 1987, 169(6), 2667–2674. E. M. Click and R. E. Webster, Filamentous phage infection: required interactions with the TolA protein. Journal of Bacteriology, 1997, 179(20), 6464–6471. E. M. Click and R. E. Webster, The TolQRA proteins are required for membrane insertion of the major capsid protein of the filamentous phage f1 during infection. Journal of Bacteriology, 1998, 180(7), 1723–1728. W. Fulford and P. Model, Gene X of bacteriophage f1 is required for phage DNA synthesis. Mutagenesis of inframe overlapping genes. Journal of Molecular Biology, 1984, 178(2), 137–153. W. Fulford and P. Model, Regulation of bacteriophage f1 DNA replication. I. New functions for genes II and X. Journal of Molecular Biology, 1988, 203(1), 49–62. M. Bauer and G. P. Smith, Filamentous phage morphogenetic signal sequence and orientation of DNA in
69.
70. 71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
15
the virion and gene-V protein complex. Virology, 1988 166–175. G. Fuh and S. S. Sidhu, Efficient phage display of polypeptides fused to the carboxy-terminus of the M13 gene-3 minor coat protein. FEBS Letters, 2000, 480(2–3), 231–234. D. A. Daniels and D. P. Lane, Phage peptide libraries. Methods, 1996, 9(3), 494–507. S. Cabilly, The basic structure of filamentous phage and its use in the display of combinatorial peptide libraries. Molecular Biotechnology, 1999, 12(2), 143–148. D. J. Rodi and L. Makowski, Phage-display technology– finding a needle in a vast molecular haystack. Current Opinion in Biotechnology, 1999, 10(1), 87–93. H. R. Hoogenboom, A. P. de Bruine, S. E. Hufton, R. M. Hoet, J. W. Arends, and R. C. Roovers, Antibody phage display technology and its applications. Immunotechnology, 1998, 4(1), 1–20. A. D. Griffiths and A. R. Duncan, Strategies for selection of antibodies by phage display. Current Opinion in Biotechnology, 1998, 9(1), 102–108. P. J. Buchli, Z. Wu, and T. L. Ciardelli, The functional display of interleukin-2 on filamentous phage. Archives of Biochemistry and Biophysics, 1997, 339(1), 79–84. E. Scarselli, G. Esposito, and C. Traboni, Receptor phage. Display of functional domains of the human high affinity IgE receptor on the M13 phage surface. FEBS Letters, 1993, 329(1–2), 223–226. P. Forrer, S. Jung, and A. Pluckthun, Beyond binding: using phage display to select for structure, folding and enzymatic activity in proteins. Current Opinion in Structural Biology, 1999, 9(4), 514–520. W. Huang, J. Petrosino, and T. Palzkill, Display of functional beta-lactamase inhibitory protein on the surface of M13 bacteriophage. Antimicrob Agents Chemother, 1998, 42(11), 2893–2897. I. Fujii, S. Fukuyama, Y. Iwabuchi, and R. Tanimura, Evolving catalytic antibodies in a phage-displayed combinatorial library. Nature Biotechnology, 1998, 16(5), 463–467. E. J. Rebar and C. O. Pabo, Zinc finger phage: affinity selection of fingers with new DNA-binding specificities. Science, 1994, 263(5147), 671–673. Y. Choo, A. Castellanos, B. Garcia-Hernandez, I. Sanchez-Garcia, and A. Klug, Promoter-specific activation of gene expression directed by bacteriophage-selected zinc fingers. Journal of Molecular Biology, 1997, 273(3), 525–532. Y. Berdichevsky, E. Ben-Zeev, R., Lamed, and I. Benhar, Phage display of a cellulose binding domain from Clostridium thermocellum and its application as a tool for antibody engineering. Journal of Immunological Methods, 1999, 228(1–2), 151–162. L. S. Jespers, J. H. Messens, A. De Keyser, D. Eeckhout, I. Van den Brande, Y. G. Gansemans, M. J. Lauwereys, G. P. Vlasuk, and P. E. Stanssens, Surface expression and ligand-based selection of cDNAs fused to filamentous phage gene VI. Biotechnology, 1995, 13(4), 378–382. S. E. Hufton, P. T. Moerkerk, E. V. Meulemans, A. de Bruine, J. W. Arends, and H. R. Hoogenboom, Phage display of cDNA repertoires: the pVI display system and
16
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS its applications for the selection of immunogenic ligands. Journal of Immunological Methods, 1999 231(1–2), 39–51. D. R. Wilson and B. B. Finlay, Phage display: applications, innovations, and issues in phage and host biology. Canadian Journal of Microbiology, 1998, 44(4), 313–329. D. R. Corey, A. K. Shiau, Q. Yang, B. A. Janowski, and C. S. Craik, Trypsin display on the surface of bacteriophage. Gene, 1993, 128(1), 129–134. L. Wang, M. Z. Radic, D. Siegel, T. Chang, J. Bracy, and U. Galili, Cloning of anti-Gal Fabs from combinatorial phage display libraries: structural analysis and comparison of Fab expression in pComb3H and pComb8 phage. Molecular Immunology, 1997, 34(8–9), 609–618. W. Markland, B. L. Roberts, M. J. Saxena, S. K. Guterman, and R. C. Ladner, Design, construction and function of a multicopy display vector using fusions to the major coat protein of bacteriophage M13. Gene, 1991, 109(1), 13–19. J. I. Horabin and R. E. Webster, An amino acid sequence which directs membrane insertion causes loss of membrane potential. Journal of Biological Chemistry, 1988, 263(23), 11575–11583. J. L. Brissette and M. Russel, Secretion and membrane integration of a filamentous phage-encoded morphogenetic protein. Journal of Molecular Biology, 1990, 211(3), 565–580. J. N. Feng, P. Model, and M. Russel, A trans-envelope protein complex needed for filamentous phage assembly and export. Molecular Microbiology, 1999, 34(4), 745–755. M. Russel and P. Model, Genetic analysis of the filamentous bacteriophage packaging signal and of the proteins that interact with it. Journal of Virology, 1989, 63(8), 3284–3295. G. R. Nakayama, G. Valkirs, D. McGrath, and W. D. Huse, Improving the copy numbers of antibody fragments expressed on the major coat protein of bacteriophage M13. Immunotechnology, 1996, 2(3), 197–207. S. S. Sidhu, G. A. Weiss, and J. A. Wells, High copy display of large proteins on phage for functional selections. Journal of Molecular Biology, 2000, 296(2), 487–495. J. L. Jestin, G. Volioti, and G. Winter, Improving the display of proteins on filamentous phage. Research in Microbiology, 2001, 152(2), 187–191. A. C. Zeri, M. F. Mesleh, A. A. Nevzorov, and S. J. Opella, Structure of the coat protein in fd filamentous bacteriophage particles determined by solid-state NMR spectroscopy. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100(11), 6458–6463. K. Jacobsson and L. Frykberg, Shotgun phage display cloning. Combinatorial Chemistry and High Throughput Screening, 2001, 4(2), 135–143. B. M. Djojonegoro, M. J. Benedik, and R. C. Willson, Bacteriophage surface display of an immunoglobulinbinding domain of Staphylococcus aureus protein A. Biotechnology, 1994, 12(2), 169–172.
99. G. W. Rudgers and T. Palzkill, Protein minimization by random fragmentation and selection. Protein Engineering, 2001, 14(7), 487–492. 100. J. Beekwilder, J. Rakonjac, M. Jongsma, and D. Bosch, A phagemid vector using the E. coli phage shock promoter facilitates phage display of toxic proteins. Gene, 1999, 228(1–2), 23–31. 101. Y. L. Yip and R. L. Ward, Application of phage display technology to cancer research. Current Pharmaceutical Biotechnology, 2002, 3(1), 29–43. 102. Y. Tsunetsugu-Yokota, M. Tatsumi, V. Robert, C. Devaux, B. Spire, J. C. Chermann, and I. Hirsch, Expression of an immunogenic region of HIV by a filamentous bacteriophage vector. Gene, 1991, 99(2), 261–265. 103. L. F. Wang, D. H. Du Plessis, J. R. White, A. D. Hyatt, and B. T. Eaton, Use of a gene-targeted phage display random epitope library to map an antigenic determinant on the bluetongue virus outer capsid protein VP5. Journal of Immunological Methods, 1995, 178(1), 1–12. 104. V. P. Valuev, D. A. Afonnikov, M. P. Ponomarenko, L. Milanesi, and N. A. Kolchanov, ASPD (Artificially Selected Proteins/Peptides Database): a database of proteins and peptides evolved in vitro. Nucleic Acids Research, 2002, 30(1), 200–202. 105. L. F. Wang and M. Yu, Epitope identification and discovery using phage display libraries: applications in vaccine development and diagnostics. Current Drug Targets, 2004, 5(1), 1–15. 106. V. F. de la Cruz, A. A. Lal, and T. F. McCutchan, Immunogenicity and epitope mapping of foreign sequences via genetically engineered filamentous phage. Journal of Biological Chemistry, 1988, 263(9), 4318–4322. 107. J. Greenwood, A. E. Willis, and R. N. Perham, Multiple display of foreign peptides on a filamentous bacteriophage. Peptides from Plasmodium falciparum circumsporozoite protein as antigens. Journal of Molecular Biology, 1991, 220(4), 821–827. 108. O. O. Minenkova, A. A. Ilyichev, G. P. Kishchenko, and V. A. Petrenko, Design of specific immunogens using filamentous phage as the carrier. Gene, 1993, 128(1), 85–88. 109. F. di Marzo Veronese, A. E. Willis, C. Boyer-Thompson, E. Appella, and R. N. Perham, Structural mimicry and enhanced immunogenicity of peptide epitopes displayed on filamentous bacteriophage. The V3 loop of HIV-1 gp120. Journal of Molecular Biology, 1994, 243(2), 167–172. 110. S. Herrmann, B. Leshem, L. Leslie, H. Bin, E. Mendelson, D. Ben-Nathan, P. Dussart, A. Porgador, B. Ragerzisman, and R. S. Marks, T7 phage display of Ep15 peptide for the detection of WNV IgG. Virological Methods, 2006. 111. V. Bottger, A. Bottger, E. B. Lane, and B. A. Spruce, Comprehensive epitope analysis of monoclonal antiproenkephalin antibodies using phage display libraries and synthetic peptides: revelation of antibody fine specificities caused by somatic mutations in the variable region genes. Journal of Molecular Biology, 1995, 247(5), 932–946.
PHAGE-DISPLAYED EPITOPES AS BIORECEPTORS FOR BIOSENSORS 112. R. M. Wright, H. Gram, A. Vattay, S. Byme, P. Lake, and D. Dottavio, Binding epitope of somatostatin defined by phage-displayed peptide libraries. Biotechnology, 1995, 13(2), 165–169. 113. R. Cortese, P. Monaci, A. Nicosia, A. Luzzago, F. Felici, G. Galfre, A. Pessi, A. Tramontano, and M. Sollazzo, Identification of biologically active peptides using random libraries displayed on phage. Current Opinion in Biotechnology, 1995, 6(1), 73–80. 114. M. R. Dyson and K. Murray, Selection of peptide inhibitors of interactions involved in complex protein assemblies: association of the core and surface antigens of hepatitis B virus. Proceedings of the National Academy of Sciences of the United States of America, 1995, 92(6), 2194–2198. 115. K. R. Oldenburg, D. Loganathan, I. J. Goldstein, P. G. Schultz, and M. A. Gallop, Peptide ligands for a sugarbinding protein isolated from a random peptide library. Proceedings of the National Academy of Sciences of the United States of America, 1992, 89(12), 5393–5397. 116. D. A. Daniels and D. P. Lane, The characterisation of p53 binding phage isolated from phage peptide display libraries. Journal of Molecular Biology, 1994, 243(4), 639–652. 117. J. M. Westendorf, P. N. Rao, and L. Gerace, Cloning of cDNAs for M-phase phosphoproteins recognized by the MPM2 monoclonal antibody and determination of the phosphorylated epitope. Proceedings of the National Academy of Sciences of the United States of America, 1994, 91(2), 714–718. 118. M. M. Smith, L. Shi, and M. Navre, Rapid identification of highly active and selective substrates for stromelysin and matrilysin using bacteriophage peptide display libraries. Journal of Biological Chemistry, 1995, 270(12), 6440–6449. 119. B. L. Roberts, W. Markland, A. C. Ley, R. B. Kent, D. W. White, S. K. Guterman, and R. C. Ladner, Directed evolution of a protein: selection of potent neutrophil elastase inhibitors displayed on M13 fusion phage. Proceedings of the National Academy of Sciences of the United States of America, 1992, 89(6), 2429–2433. 120. C. Dantas-Barbosa, M. M. Brigido, and A. Q. Maranhao, Construction of a human Fab phage display library from antibody repertoires of osteosarcoma patients. Genetics and Molecular Research, 2005, 4(2), 126–140. 121. A. Q. Maranhao and M. M. Brigido, Expression of antiZ-DNA single chain antibody variable fragment on the filamentous phage surface. Brazilian Journal of Medical and Biological Research, 2000, 33(5), 569–579. 122. J. McCafferty, A. D. Griffiths, G. Winter, and D. J. Chiswell, Phage antibodies: filamentous phage displaying antibody variable domains. Nature, 1990, 348(6301), 552–554. 123. C. F. Barbas, A. S. Kang, R. A. Lerner, and S. J. Benkovic, Assembly of combinatorial antibody libraries on phage surfaces: the gene III site. Proceedings of the National Academy of Sciences of the United States of America, 1991, 88(18), 7978–7982.
17
124. T. Clackson, H. R. Hoogenboom, A. D. Griffiths, and G. Winter, Making antibody fragments using phage display libraries. Nature, 1991, 352(6336), 624–628. 125. P. Malik and R. N. Perham, Simultaneous display of different peptides on the surface of filamentous bacteriophage. Nucleic Acids Research, 1997, 25(4), 915–916. 126. T. Sathaliyawala, M. Rao, D. M. Maclean, D. L. Birx, C. R. Alving, and V. B. Rao, Assembly of human immunodeficiency virus (HIV) antigens on bacteriophage T4: a novel in vitro approach to construct multicomponent HIV vaccines. Journal of Virology, 2006, 80(15), 7688–7698. 127. M. A. Cooper, Advances in membrane receptor screening and analysis. Journal of Molecular Recognition, 2004, 17(4), 286–315. 128. S. Herrmann, B. Leshem, S. Landes, B. Rager-Zisman, and R. S. Marks, Chemiluminescent optical fiber immunosensor for the detection of anti-West Nile virus IgG. Talanta, 2005, 66, 6–14. 129. B. Leshem, G. Sarfati, A. Novoa, I. Breslav, and R. S. Marks, Photochemical attachment of biomolecules onto fibre-optics for construction of a chemiluminescent immunosensor. Luminescence, 2004, 19(2), 69–77. 130. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Bioluminescent whole cell optical fiber sensor to genotoxicants. Sensors and Actuators B: Chemical, 2001, 72(1–3), 18–26. 131. A. M. Hutchinson, Evanescent wave biosensors. Realtime analysis of biomolecular interactions. Molecular Biotechnology, 1995, 3(1), 47–54. 132. A. C. Malmborg and C. A. Borrebaeck, BIAcore as a tool in antibody engineering. Journal of Immunological Methods, 1995, 183(1), 7–13. 133. A. C. Malmborg, M. Duenas, M. Ohlin, E. Soderlind, and C. A. Borrebaeck, Selection of binders from phage displayed antibody libraries using the BIAcore biosensor. Journal of Immunological Methods, 1996, 198(1), 51–57. 134. M. Duenas, A. C. Malmborg, R. Casalvilla, M. Ohlin, and C. A. Borrebaeck, Selection of phage displayed antibodies based on kinetic constants. Molecular Immunology, 1996, 33(3), 279–285. 135. A. Hengerer, J. Decker, E. Prohaska, S. Hauck, C. Kosslinger, and H. Wolf, Quartz crystal microbalance (QCM) as a device for the screening of phage libraries. Biosensors and Bioelectronics, 1999, 14(2), 139–144. 136. J. Decker, K. Weinberger, E. Prohaska, S. Hauck, C. Kosslinger, H. Wolf, and A. Hengerer, Characterization of a human pancreatic secretory trypsin inhibitor mutant binding to Legionella pneumophila as determined by a quartz crystal microbalance. Journal of Immunological Methods, 2000, 233(1–2), 159–165. 137. D. R. Thevenot, K. Toth, R. A. Durst, and G. S. Wilson, Electrochemical biosensors: recommended definitions and classification. Biosensors and Bioelectronics, 2001, 16(1–2), 121–131. 138. R. E. Ionescu, S. Herrmann, S. Cosnier, and S. R. Marks, Amperometric immunosensor for the detection of anti West Nile virus IgG. In printing.
8 Luciferase Reporter Bacteriophages Steven Hagens and Martin J. Loessner Institute of Food Science and Nutrition, ETH Zurich, Zurich, Switzerland
1 INTRODUCTION
The detection of pathogenic bacteria in clinical, food, and environmental samples is essential in treating and preventing disease. In general, standard culturing techniques still represent the most widely used and accepted methods for bacterial detection. However, although conclusive, they are highly time consuming and labor intensive. Detection of the genetic material of a given pathogen, although extremely rapid, has the inherent disadvantage that the presence of DNA alone does not necessarily reveal bacterial viability, that is, the presence of live organisms. Immunological methods often lack the required specificity, are hampered by the availability of suitable antibodies, and are often not sufficiently sensitive. Bacterial viruses (bacteriophages or phages) show an extreme biological specificity; they only infect bacteria of a specific genus, species, or even specific strains. Since viruses lack a metabolism of their own, they can multiply only by replication within a living host cell. Phages have been employed for typing purposes, that is, to differentiate bacterial species and isolates, and also to detect their presence. It should be noted that multiplication of phages depends on the presence of viable host bacteria only; the infection of a target cell results in the release of progeny phages. However, it is very difficult to reliably measure the resulting amplification of phages in a test sample. The need to better visualize and measure
the activity of phages on the potentially present host cells in a test sample has led to the genetic modification and construction of phages that carry heterologous reporter-genes, whose products can be readily detected in the infected host cell. In fact, several genes encoding very different products whose presence or activity can be monitored (various enzymes, fluorescent proteins, ice nucleation factors, etc.) have been used for this purpose (reviewed in Ref. 1). This chapter will focus on the use of luciferases in recombinant reporter bacteriophages.
2 LUCIFERASE REPORTER PHAGES (LRPs)
In 1987, Ulitzur and Kuhn first demonstrated that light emission could be measured from target bacteria infected by a genetically modified phage λ into which marine bacterial luciferase (lux ) genes had been cloned. Luciferase genes are highly suitable for this procedure because they produce a strong and unique signal, and a photon background signal in a given sample is unlikely. Thereafter, other recombinant phages encoding luciferase genes have been developed for the detection of Listeria, Salmonella, Escherichia coli, and mycobacteria. The main strength of such luciferase reporter phages (LRPs) is the speed and relative simplicity with which viable bacteria can be detected in any given sample. The system is limited only by minimum detection limits and,
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS 1
2
3
Addition of substrate long-chain aldehyde or luciferin
Detection of light emission by luminometry or light-sensitive film
LRP
Addition of LRP and incubation
luxAB /luc transcription Luciferase
Sample
Target bacterium Figure 1. Schematic representation of LRP assays. (1) LRP is added to a sample. Depending on bacterial and phage species, varying incubation times are needed for the LRP to infect cells and to allow for maximum expression of the luciferase. (2) The appropriate luciferase substrate is added to the sample. (3) Emitted photons can then be measured in a variety of ways.
Bacterial luciferase genes were the first to be described in detail. They are functionally organized in an operon. A schematic representation of part of the Vibrio lux operon is shown in Figure 2. The catalytically active luciferase enzyme is a heterodimer and consists of one copy each of LuxA and LuxB subunits. It should be mentioned that this dimeric form does not work well in gram-positive bacteria, but that single proteins translated from luxAB fusion genes are fully functional.2–5 The luxCDE genes encode products necessary for the conversion of fatty acids into the long-chain aldehyde that serves as the
foremost, the host ranges of the phages used. A schematic overview of the detection principle is shown in Figure 1.
3 LUCIFERASE GENES
Luciferase genes are harbored by a variety of organisms. In conjunction with reporter phages, the bacterial luciferase genes (luxA and luxB) from Vibrio harveyi or Vibrio fischeri, or the insect luciferase gene luc from the firefly Photinus pyralis have been employed.
AHL
luxR
luxR
Pluxl
luxl
AHL
C
D
A
B
E
Bioluminescence genes
Figure 2. Schematic representation of the V. fischeri lux operon. Genes luxC and luxE encode the fatty-acid reductase, and luxD encodes a fatty-acid acyltransferase (striped arrows). Together, these enzymes are involved in synthesis of the long-chain aldehyde substrate. The catalytic enzyme subunit genes luxA and luxB are represented by plain arrows. The diffusible acylhomoserine lactone (AHL)-autoinducer molecule is produced by the synthetase encoded by luxI. AHL molecules bind to the regulatory proteins specified by luxR (spotted arrows), and this complex then initiates an autostimulatory loop at the PluxI promoter.
LUCIFERASE REPORTER BACTERIOPHAGES
substrate for the luciferase reaction. These genes are flanked in many bioluminescent bacteria by a variety of genes responsible for flavin metabolism. Reduced flavin mononucleotide (FMNH2 ) and the long-chain aldehyde are oxidized in the following reaction. FMNH2 + R–COH + O2
Bacterial luciferase −−−−−−−−−−−−−−→
FMN + R–COOH + H2 O + Light Expression of the lux genes is controlled by a two-component regulatory system encoded by the luxI and luxR genes. The luxI gene encodes a synthetase responsible for generation of N -acyl-Lhomoserine lactone (AHL) signaling molecules. This is a diffusible autoinducer, which interacts with the LuxR protein to bind to the PluxI promoter and thereby initiates transcription of the entire bioluminescence operon (Fuqua et al., 1994). In LRP assays, the LuxA and LuxB proteins or a LuxAB fusion protein is encoded by the LRP; FMNH2 is provided by the target bacteria and, in order to start the reaction, the aldehyde is supplied from without. Light emission can easily be detected by means of a luminometer. Figure 3 shows images of a double-layer agar plate with plaques of the LRP A511::luxAB multiplying on a Listeria host strain. After supplying the nonanal luciferase substrate in the gas phase, light emission
3
from phage plaques (actually, from the infected bacteria) can be monitored with a light-sensitive camera. The insect luciferase protein Luc acts as a monomer and requires the presence of ATP and the substrate luciferin to perform an oxidation reaction: Luciferin + ATP + O2 (+Mg2+ ) Firefly luciferase −−−−−−−−−−−−→
Oxyluciferin + AMP + PPi + CO2 + Light In prokaryotes, a cDNA version of the luciferase gene lacking introns is used under transcriptional control of selected promoters. In LRP assays, the Luc protein is encoded by the phage, while target cells provide the ATP, and luciferin is added from without. Unlike the first bacterial luciferases described, insect luciferase is fully active at temperatures above 30 ◦ C. However, the luciferin substrate is expensive and does not readily diffuse across membranes. As a result, only luciferase from lysed bacteria has access to the substrate. The long-chain aldehydes recognized by bacterial luciferases readily diffuse across membranes, and enzymes that function at temperatures well above 30 ◦ C have been described.6
Figure 3. Imaging of plaques produced by luciferase reporter bacteriophage A511::luxAB growing on Listeria host cells (left panel, normal lighting), and after addition of the luciferase substrate nonyl-aldehyde (right panel, in the dark). Light emission from the plaques through phage-encoded luciferase is clearly visible.
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
4 CONSTRUCTION OF LRPs
For LRP design, several intrinsic properties of phages need to be taken into account. Ideally, the phage should be able to infect all strains of the target species. Even with strictly lytic, broadhost-range phages this can hardly be achieved; the continuous evolution of both hosts and phages inevitably results in the appearance of phageresistant bacterial strains, which will not respond to LRP detection and must be regarded as “false negatives”. In addition, the host ranges of some phages (in particular among the Enterobacteriaceae) extend beyond the actual target level (species or genus), and may therefore deliver falsepositive results. The useful LRPs are those that are able to infect the majority (at least 80%) of all target strains, and yield very few or no falsepositive reactions. Lytic and temperate phages can be found in nature. The latter generally display narrower host ranges, which limit their usefulness as reporter phages. The ability of the phage genome to incorporate the additional genetic information specifying the luciferase is another required attribute. Although (in theory) nonessential genes can be replaced or deleted, essential genes can be provided in trans; this is difficult to accomplish because even the increasing number of complete phage genome sequences do not automatically provide information as to which genes are nonessential. Several different strategies exist for the introduction of the chosen luciferase gene(s) into a phage genome: (i) Direct cloning of the foreign DNA is possible only with a very limited number of phages. Suitable cloning systems are available on the basis of E. coli phage λ, M13, and similar ones, and Salmonella phage P22. The lack of sequence information, a multitude of restriction sites (or lack thereof) in desirable locations, the sheer size of some phage genomes, and the lack of suitable packaging extracts to incorporate the manipulated phage genome into an empty virus head make this strategy virtually impossible for most other, less well characterized phages. (ii) Random insertion of the luciferase genes equipped with a suitable, strong promoter (or without promoter, to be expressed by a phage promoter) into a nonessential or intergenic region can be accomplished using transposons. Transposons are mobile genetic elements that are able to self-excise and integrate into random DNA
regions. They can be modified to contain antibiotic resistance genes and genes of interest and have been extensively used to insert specific markers into DNA and to create mutations by gene disruption. Their use is especially attractive for creating LRPs from (integrated) prophages. After transposon insertion, a culture can be induced, and the phages can be isolated and used to re-lysogenize the bacteria. The presence of a drug-resistance marker allows screening for those phages where the transposon has integrated. Transposons can also be used to integrate into strictly lytic (virulent) phages that are unable to form lysogens. However, resistance screening cannot be used in these cases and the more laborious route of finding luminescence-transducing phages has to be taken. Alternatively, if phage genome structure and size permit, target-phage DNA can be used to construct cosmid libraries. Cosmids are vectors that allow cloning of large DNA fragments. They consist of the cohesive ends of phage λ DNA and an origin of replication, allowing them to replicate as a plasmid in E. coli. DNA fragments roughly the size of the phage λ genome can be inserted and packaged into phagelike particles in vitro. These infective particles allow efficient transfer of the DNA to E. coli cells. After extraction from E. coli, cosmids can be transfected into target bacteria, functional phages isolated from plaques can be reintroduced into E. coli, and the luciferase genes can be inserted. Subsequent transfer into target bacteria then permits screening for the functional reporter phage. Some cosmid vectors allow for excision of most of the cosmid DNA, thus minimizing the amount of foreign DNA in the LRPs. Depending on the location and size of nonessential regions, this method can lead to the creation of several different LRPs with varying properties in a single experiment. (iii) Homologous recombination of the target genes into a selected site of the phage genome. At least part of the phage DNA sequence must be known. This approach allows introduction of luciferase genes from a plasmid containing the luciferase construct flanked by phage sequence, at virtually any desired coordinate of the phage genome. However, recombination events are not common, often resulting in laborious screening efforts to identify the recombinant phage particles from the bacterial lysates.
LUCIFERASE REPORTER BACTERIOPHAGES
5 SPECIFIC LRPs AND THEIR APPLICATION 5.1
E. coli LRPs
The first LRP ever constructed was based on the temperate E. coli phage λ.7 Ulitzur and Kuhn demonstrated that as little as 10 viable E. coli cells could be detected within 100 min post infection. Two λ Charon 30 –based LRPs containing the entire lux operon of V. fischeri were constructed. In one version, the luxR gene was directed in the same orientation as the phage leftward operon, with the other genes luxI, C, D, A, B, and E directed in the opposite orientation. The phage late promoter enhances luxI production only at the end of the infection cycle, leading to slow accumulation of the inducer molecule synthesized by luxI and, consequently, to light production relatively late in the infective cycle. In another version, the orientation of the lux operon within the phage is reversed, resulting in an early onset of luminescence, since the phage early promoter (although in itself not very strong) induces early production of luxI protein. Later studies dealt with the construction of various other E. coli LRPs, encoding only luxA and luxB, made by either direct cloning in M13; transposition of lux genes into λ, 80, PRD1, and T5; or by cloning and recombination to generate LRPs of λ and T7.8 Unfortunately, no detailed information concerning the properties or application of these LRPs is available. Construction of three Salmonella LRPs based on P1, P22, and Felix O1 and one Pseudomonas LRP based on phage N4 is also reported. Some information on two of the Salmonella LRPs is available and is discussed below. One study describing the use of some unpublished LRPs specific for Enterobacteriaceae claims the detection of >104 bacteria g−1 or cm−2 in 50 min without prior enrichment, and detection of 10 bacteria g−1 or cm−2 after a 4-h enrichment, in various samples.9 Foodborne infections due to E. coli O157:H7 contamination make these organisms highly desirable targets for rapid detection, which could help avoid subsequent outbreaks. An O157:H7-specific LRP based on the temperate phage V10 and the promoterless V. harveyi luxA/luxB genes was constructed by transposon insertion in a lysogenized strain.10 The experiments demonstrated that the resulting LRP was able to detect viable bacteria after approximately 1 h following infection of target cells in
5
broth cultures. However, as pointed out above, temperate phages such as V10 usually exhibit a rather narrow host range and will also fail to infect homolysogenic host bacteria. Nevertheless, the authors report that V10 could infect about 64% of the O157:H7 isolates screened. They suggested construction of further O157:H7-specific LRPs, to be used in a cocktail for detection of a larger percentage of strains. Recently, a variation on the classic lux gene– encoding LRP has been published, involving the construction and use of a λ phage encoding the LuxI protein of V. fischeri. Infection of E. coli target cells by the recombinant virus results in the production of the diffusible AHL autoinducer: in this case, N -3-(oxohexanoyl)-Lhomoserine (OHHL). The rising AHL levels are detected by light emission from a second reporter bacterium, which contains and expresses the luxRCDABE genes only. When the AHL diffuses into the reporter cells, it associates with LuxR and binds to the PluxI promoter, resulting in the synthesis of all proteins and products necessary for bioluminescence.11 A potential disadvantage of this system is the induction of the lux operon by any compatible quorum-sensing molecules provided by the unknown bacterial flora of the sample. Such interference by other AHLs was tested with 10 species known to produce quorum-sensing molecules, and it was found that two species, Erwinia carotovora and Yersinia enterocolitica, were able to elicit a bioluminescence response from the reporter cells. Hence, adopting this reporter system would necessitate the use of control samples to screen for intrinsic AHL content of the sample or enrichment culture. Such falsepositive samples would then need to be screened by alternative means. Possible advantages of this system are the much longer signal-integration times and the associated greater sensitivity since FMNH2 is continuously regenerated in the living reporter cells. Moreover, the smaller size of the luxI gene (∼600 bp) compared to luxA and B (∼2 kbp) may in some cases allow it to be more readily incorporated into phage genomes.
5.2
Salmonella LRPs
Salmonellosis is contracted through consumption of food contaminated with organisms of the
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Salmonella enterica species group: it ranks among the most common foodborne diseases worldwide. Therefore, suitable LRPs to rapidly detect these pathogens are highly desirable. The construction of a number of Salmonella LRPs was based on phages P1, P22, and Felix-O1,8,12 and the P22based LRP was evaluated in two independent studies.13,14 This phage allowed a quite rapid detection of Salmonella cells from various (artificially) contaminated samples. However, the drawback is that P22 is a phage with a narrow host range, which severely restricts its use in detecting unknown Salmonella from foods. Phage Felix-O1 has a much broader host range, infecting a large number of clinically important strains.15,16 This makes the phage ideally suited for LRP construction. In their 2002 study on the construction of a Felix O1-based LRP, Kuhn et al. reported several difficulties. No bioluminescent phage could be found after various attempts at transposon insertion, leading to the speculation that the genome may not be able to accommodate the additional genetic information. By replacing one essential and two nonessential genes with luxA/luxB genes in a cloned phage genomic region, supply of the essential gene in trans, and homologous recombination it was possible to isolate luminescencetransducing Felix-O1. Although significant levels of light could be detected when infecting the laboratory strain, strongly reduced levels of light output were observed when infecting other strains. This may in part be explained by varying efficiencies in infection of different strains but may also indicate that either the missing genes or polar effects of the recombination event have an influence on translation in some strains.
5.3
Listeria LRPs
Listeriosis, caused by Listeria monocytogenes and contracted exclusively through contaminated food, is considered a significant threat in spite of its relatively low incidence, because of the high mortality rate of approximately 30% and an unknown infectious dose.17,18 Classical culture methods involve selective enrichment followed by plating on selective media, and take 4 days until preliminary results are obtained, followed by further confirmatory biochemical tests, which take another 2–3 days. This seems quite unreasonable,
compared to the short shelf life of many perishable, ready-to-eat foods known to be contaminated with Listeria. Therefore, as for Salmonella, a Listeria LRP could provide a very useful detection system. A Listeria-specific LRP A511::luxAB has been reported, based on the virulent broad-hostrange phage A511, which infects roughly 95% of L. monocytogenes strain of serovars 1/2 and 4, which are most commonly found in food and implicated in the disease.19–22 The phage was constructed by recombination of A511 DNA with homologous DNA fragments cloned into a plasmid, into which a fused V. harveyi luxAB cassette had been inserted. The reporter gene was placed immediately downstream of the major capsid protein gene and under transcriptional control of the strong PCps promoter. Phage A511 is not species specific; infection and thus detection of other, nonpathogenic Listeria species is possible. However, this may not necessarily be considered a disadvantage, because any Listeria contamination is undesirable and indicates either contaminated raw products, and/or lack of hygiene, and/or improper processing and storage conditions. In an evaluation of A511::luxAB performance, detection of the bacteria in artificially and naturally contaminated foodstuffs was comparable to standard plating methods.20 L. monocytogenes was detected in 55 out of 57 positive naturally contaminated samples from a total of 348 examined food samples. In many of the artificially contaminated foods, as little as 1 cell g−1 could be detected within only 24 h, a clear advantage of this system. Further developments such as the combination of immunomagnetic separation (IMS) with subsequent reporter-phage detection have also been reported.23,24 Recently, the combination of highly specific magnetic separation by alternative affinity proteins (cell-wall-binding domain proteins (CBD) of bacteriophage endolysins) coated onto magnetic beads with LRP A511::luxAB as the detector system was tested in a 96-well format (Kretzer et al. submitted for publication). As little as 0.1–1 cell g−1 could be detected in artificially contaminated food within 22 h. The study also described the use of sodium azide (NaN3 ), which was found to significantly increase the light output when added to Lux-phage infected samples. The azide is believed to shift the equilibrium of FMNH2 ↔ FMN to the reduced form, which is necessary for the luciferase-catalyzed reaction.
LUCIFERASE REPORTER BACTERIOPHAGES
5.4
Mycobacterial LRPs
Most studies involving LRPs for detection and drug-susceptibility testing have been done with mycobacteria. This is likely due to the fact that LRPs generally reduce the overall screening time, which is especially attractive with respect to notoriously slow-growing organisms such as Mycobacterium tuberculosis. Several different firefly luciferase (luc)-encoding phages have been constructed. All of these are based on phages TM4, D29, and L5 and were generated by cloning phage DNA into cosmid libraries,25–27 as described. Second-generation LRPs based on the same phages have been reported, including temperature-sensitive mutants allowing accurate timing of host lysis and thus increasing sensitivity.28 Phages TM4 and D29 exhibit a relatively broad host range, infecting strains of M. tuberculosis, Mycobacterium smegmatis, and Mycobacterium bovis, while TM4 is also able to infect mycobacteria of the Mycobacterium avium complex. These phages were long considered to be strictly lytic, but some degree of homoimmunity is observed between phage D29 and L5 lysogenic strains. Sequence analysis of these phages revealed a very high level of similarity between D29 and L5 but also exposed a ∼4-kbp deletion including the putative repressor gene in D29.29 Although the integrase and the genomic attachment site core sequence (attP ) are identical to those of L5, lack of the repressor gene in D29 explains the broadened host range and inability to form stable lysogens. Sequence analysis of phage TM4 did not reveal any genes normally associated with lysogeny.30 Under normal conditions, phage L5 long showed a much narrower host range, infecting only fast-growing mycobacterial species such as M. smegmatis where it forms stable lysogens. A later study showed that by varying culture conditions, slow-growing M. bovis BCG-C cells could also be infected, thus potentially broadening the use of L5-based LRPs.31 Although adsorption of phage particles to Mycobacterium leprae has been observed, successful infection of this species has not been demonstrated, owing to the inability to propagate these bacteria in laboratory media.32 Regardless of their nature, the fact that these phages can be propagated on M. smegmatis and form plaques overnight on double-layer agar plates allows for relatively simple cultivation and
7
enumeration of the LRPs. However, infection of nontuberculous mycobacteria can lead to falsepositive results. A confirmatory test can be incorporated into the luciferase detection assay. Growth of M. tuberculosis complex bacteria but not that of other mycobacteria is inhibited by p-nitro-αacetylamino-β-hydroxy propiophenone (NAP).33 Adding NAP to a second sample of a culture abolishes light emission in samples containing tuberculous mycobacteria, while samples containing nontuberculous mycobacteria emit light, allowing discrimination between the two.34 Most studies were done using laboratory strains, and application data of LRPs used for detection in clinical samples are scarce. One study conducted in Mexico, applying LRPs to 71 culture-positive sputum samples, reports a detection rate of 76%.35 From the beginning, the mycobacterial LRPs have been employed to test the drug sensitivity of target bacteria. Because bacteriophages require actively growing cells to propagate and because the firefly luciferase needs ATP to react with the substrate, growth inhibition abolishes the production of light. The failure of phage-susceptible isolates to produce light after incubation with an antibiotic indicates sensitivity to this drug, and light emission after phage LRP infection in the presence of a given antibiotic indicates resistance. Here the true forte of the mycobacterial LRPs can be demonstrated. Resistance to fast-acting drugs such as rifampicin can be determined within hours, and resistance to slower acting drugs, such as ethambutol, isoniazid, and ciprofloxacin can be tested within 2–3 days.36 In a second study, LRPs were used to screen resistance to 4 first-line antibiotics in 50 clinical isolates. Resistance to rifampicin, streptomycin, isoniazid, and ethambutol was detected in three of three, two of two, six of seven, and three of three confirmed strains, respectively. Complete LRP results were available within 4 days and 96% of the results were available within 2 days compared to 16 days needed to obtain complete results from standard culturing method.35 In a third study, LRPs were used to confirm 84 clinical isolates and test for drug sensitivity. LRP–NAP testing showed a sensitivity and specificity of 97 and 100%, respectively. Overall agreement for drug susceptibility was 98.6%. The four discrepant results indicated resistance to ethambutol in susceptible strains.37 The LRP assay can be performed in 96well plates and emitted light can be detected by
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
a luminometer; this allows for automated largescale screening programs.36 However, the machinery needed would be very expensive and beyond the means of poorly equipped laboratories, especially in poorer countries. A low-tech alternative has been described, where a cassette holds a microwell plate over a sheet of photographic film. The device, termed Bronx Box, was used to screen M. tuberculosis isolates for resistance to rifampicin and isoniazid and results were obtained within 3 days.38,39 A prototype device consisting of a self-contained cassette using dental Xray film has been developed (Sequella, Rockville, MD, USA), and evaluation studies have been announced but no data have been made public until now. 6 CONCLUSIONS AND OUTLOOK
It is clear that LRPs can represent valuable tools for rapid, sensitive, and inexpensive detection of various pathogenic bacteria. The major advantage of LRPs is the combination of speed and the ability to conclusively show viability of the target organisms. This makes them useful especially for detecting bacteria in foods with short shelf life, where extensive culturing technique results are obtained only after potential damage has already occurred, or in use with slow-growing pathogens such as Mycobacteria, allowing doctors to quickly decide on therapeutic regimens. New technologies, such as IMS or CBD-MS can further speed up detection times and might make control experiments as described in the luxI reporter assay superfluous. Automation of sampling and detection may allow high-throughput screening of samples, and integrated-circuit microluminometers40 may permit the creation of miniaturized stand-alone biosensors capable of remote on-site monitoring. Furthermore, as our understanding of phage and bacterial genetics grows, faster creation of LRPs with customtailored host ranges may be possible in future. Certainly, the full potential of phage-based detection systems is yet to be utilized.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
REFERENCES 13. 1. C. E. D. Rees and M. J. Loessner, Phage for the Detection of Pathogenic Bacteria, in Bacteriophages: Biology and
Applications, E. Kutter and A. Sulakvelidze (eds), CRC Press, Boca Raton, 2005, pp. 276–284. M. O. Boylan, J. Pelletier, S. Dhepagnon, S. Trudel, N. Sonenberg, and E. A. Meighen, Construction of a fused lux AB gene by site-directed mutagenesis. Journal of Bioluminescence and Chemiluminescence, 1989, 4, 310–316. A. Escher, D. J. O’Kane, J. Lee, and A. A. Szalay, Bacterial luciferase alpha beta fusion protein is fully active as a monomer and highly sensitive in vivo to elevated temperature. Proceedings of the National Academy of Sciences of the USA, 1989, 86, 6528–6532. P. J. Hill, S. Swift, and G. S. Stewart, PCR based gene engineering of the Vibrio harveyi lux operon and the Escherichia coli trp operon provides for biochemically functional native and fused gene products. Molecular and General Genetics, 1991, 226, 41–48. O. Olsson, A. Escher, G. Sandberg, J. Schell, C. Koncz, and A. A. Szalay, Engineering of monomeric bacterial luciferases by fusion of luxA and luxB genes in Vibrio harveyi . Gene, 1989, 81, 335–347. M. K. Winson, S. Swift, P. J. Hill, C. M. Sims, G. Griesmayr, B. W. Bycroft, P. Williams, and G. S. Stewart, Engineering the luxCDABE genes from Photorhabdus luminescens to provide a bioluminescent reporter for constitutive and promoter probe plasmids and mini-Tn5 constructs. FEMS Microbiology Letters, 1998, 163, 193–202. S. Ulitzur and J. Kuhn, Introduction of Lux Genes into Bacteria, a New Approach for Specific Determination of Bacteria and their Antibiotic Susceptibility, in Bioluminescence and Chemiluminescence New Perspectives, J. Schlomerich, R. Andreesen, A. Kapp, M. Ernst, and W. G. Woods (eds), John Wiley & Sons, New York, 1987, pp. 463–472. S. Ulitzur and J. Kuhn, Construction of lux bacteriophages and the determination of specific bacteria and their antibiotic sensitivities. Methods in Enzymology, 2000, 305, 543–557. C. P. Kodikara, H. H. Crew, and G. S. Stewart, Near online detection of enteric bacteria using lux recombinant bacteriophage. FEMS Microbiology Letters, 1991, 67, 261–265. T. E. Waddell and C. Poppe, Construction of miniTn10luxABcam/Ptac-ATS and its use for developing a bacteriophage that transduces bioluminescence to Escherichia coli O157:H7. FEMS Microbiology Letters, 2000, 182, 285–289. S. Ripp, P. Jegier, M. Birmele, C. M. Johnson, K. A. Daumer, J. L. Garland, and G. S. Sayler, Linking bacteriophage infection to quorum sensing signaling and bioluminescent bioreporter monitoring for direct detection of bacterial agents. Journal of Applied Microbiology, 2006, 100, 488–499. J. Kuhn, M. Suissa, J. Wyse, I. Cohen, I. Weiser, S. Reznick, S. Lubinsky-Mink, G. Stewart, and S. Ulitzur, Detection of bacteria using foreign DNA: the development of a bacteriophage reagent for Salmonella. International Journal of Food Microbiology, 2002, 74, 229–238. G. Stewart, T. Smith, and S. Denyer, Genetic engineering for bioluminescent bacteria. Food Science and Technology Today, 1989, 3, 19–22.
LUCIFERASE REPORTER BACTERIOPHAGES 14. P. E. Turpin, K. A. Maycroft, J. Bedford, C. L. Rowlands, and E. M. H. Wellington, A rapid luminescent-phage based MPN method for the enumeration of Salmonella typhimurium in environmental samples. Letters in Applied Microbiology, 1993, 16, 24–27. 15. H. Fey, E. Burgi, A. Margadant, and E. Boller, An economic and rapid diagnostic procedure for the detection of salmonella/shigella using the polyvalent salmonella phage O-1. Zentralblatt Fur Bakteriologie [Originale A], 1978, 240, 7–15. 16. A. A. Lindberg and T. Holme, Influence of O side chains on the attachment of the Felix O-1 bacteriophage to Salmonella bacteria. Journal of Bacteriology, 1969, 99, 513–519. 17. J. M. Farber and P. I. Peterkin, Listeria monocytogenes, a food-borne pathogen. Microbiological Reviews, 1991, 55, 476–511. 18. J. McLauchlin, R. T. Mitchell, W. J. Smerdon, and K. Jewell, Listeria monocytogenes and listeriosis: a review of hazard characterisation for use in microbiological risk assessment of foods. International Journal of Food Microbiology, 2004, 92, 15–33. 19. M. J. Loessner, C. E. Rees, G. S. Stewart, and S. Scherer, Construction of luciferase reporter bacteriophage A511::luxAB for rapid and sensitive detection of viable Listeria cells. Applied and Environmental Microbiology, 1996, 62, 1133–1140. 20. M. J. Loessner, M. Rudolf, and S. Scherer, Evaluation of luciferase reporter bacteriophage A511:luxAB for detection of Listeria monocytogenes in contaminated foods. Applied and Environmental Microbiology, 1997, 63, 2961–2965. 21. G. Wendlinger, M. J. Loessner, and S. Scherer, Bacteriophage receptors on Listeria monocytogenes cells are the N-acetylglucosamine and rhamnose substituents of teichoic acids or the peptidoglycan itself. Microbiology, 1996, 142, 985–992. 22. R. Zink and M. J. Loessner, Classification of virulent and temperate bacteriophages of Listeria spp. on the basis of morphology and protein analysis. Applied and Environmental Microbiology, 1992, 58, 296–302. 23. S. J. Favrin, S. A. Jassim, and M. W. Griffiths, Application of a novel immunomagnetic separation-bacteriophage assay for the detection of Salmonella enteritidis and Escherichia coli O157:H7 in food. International Journal of Food Microbiology, 2003, 85, 63–71. 24. L. Goodridge, J. Chen, and M. Griffiths, Development and characterization of a fluorescent-bacteriophage assay for detection of Escherichia coli O157:H7. Applied and Environmental Microbiology, 1999, 65, 1397–1404. 25. W. R. Jacobs Jr, R. G. Barletta, R. Udani, J. Chan, G. Kalkut, G. Sosne, T. Kieser, G. J. Sarkis, G. F. Hatfull, and B. R. Bloom, Rapid assessment of drug susceptibilities of Mycobacterium tuberculosis by means of luciferase reporter phages. Science, 1993, 260, 819–822. 26. R. E. Pearson, S. Jurgensen, G. J. Sarkis, G. F. Hatfull, and W. R. Jacobs Jr, Construction of D29 shuttle phasmids and luciferase reporter phages for detection of mycobacteria. Gene, 1996, 183, 129–136. 27. G. J., Sarkis, W. R. Jacobs Jr, and G. F. Hatfull, L5 luciferase reporter mycobacteriophages: a sensitive tool for
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
9
the detection and assay of live mycobacteria. Molecular Microbiology, 1995, 15, 1055–1067. C. Carriere, P. F. Riska, O. Zimhony, J. Kriakov, S. Bardarov, J. Burns, J. Chan, and W. R. Jacobs Jr, Conditionally replicating luciferase reporter phages: improved sensitivity for rapid detection and assessment of drug susceptibility of Mycobacterium tuberculosis. Journal of Clinical Microbiology, 1997, 35, 3232–3239. M. E. Ford, G. J. Sarkis, A. E. Belanger, R. W. Hendrix, and G. F. Hatfull, Genome structure of mycobacteriophage D29: implications for phage evolution. Journal of Molecular Biology, 1998, 279, 143–164. M. E. Ford, C. Stenstrom, R. W. Hendrix, and G. F. Hatfull, Mycobacteriophage TM4: genome structure and gene expression. Tuberculosis and Lung Disease, 1998, 79, 63–73. K. J. Fullner and G. F. Hatfull, Mycobacteriophage L5 infection of Mycobacterium bovis BCG: implications for phage genetics in the slow-growing mycobacteria. Molecular Microbiology, 1997, 26, 755–766. H. L. David, F. Clement, S. Clavel-Seres, and N. Rastogi, Abortive infection of Mycobacterium leprae by the mycobacteriophage D29. International Journal of Leprosy and Other Mycobacterial Diseases, 1984, 52, 515–523. A. Laszlo and L. Eidus, Test for differentiation of M tuberculosis and M. bovis from other mycobacteria. Canadian Journal of Microbiology, 1978, 24, 754–756. P. F. Riska, W. R. Jacobs Jr, B. R. Bloom, J. McKitrick, and J. Chan, Specific identification of Mycobacterium tuberculosis with the luciferase reporter mycobacteriophage: use of p-nitro-alpha-acetylamino-beta-hydroxy propiophenone. Journal of Clinical Microbiology, 1997, 35, 3225–3231. N. Banaiee, M. Bobadilla-Del-Valle, S. Bardarov Jr, P. F. Riska, P. M. Small, A. Ponce-De-Leon, W. R. Jacobs Jr, G. F. Hatfull, and J. Sifuentes-Osornio, Luciferase reporter mycobacteriophages for detection, identification, and antibiotic susceptibility testing of Mycobacterium tuberculosis in Mexico. Journal of Clinical Microbiology, 2001, 39, 3883–3888. P. F. Riska and W. R. Jacobs Jr, The use of luciferasereporter phage for antibiotic-susceptibility testing of mycobacteria. Methods in Molecular Biology, 1998, 101, 431–455. N. Banaiee, M. Bobadilla-Del-Valle, P. F. Riska, S. Bardarov Jr, P. M. Small, A. Ponce-de-Leon, W. R. Jacobs Jr, G. F. Hatfull, and J. Sifuentes-Osornio, Rapid identification and susceptibility testing of Mycobacterium tuberculosis from MGIT cultures with luciferase reporter mycobacteriophages. Journal of Medical Microbiology, 2003, 52, 557–561. M. H., Hazbon, N. Guarin, B. E. Ferro, A. L. Rodriguez, L. A. Labrada, R. Tovar, P. F. Riska, and W. R. Jacobs Jr, Photographic and luminometric detection of luciferase reporter phages for drug susceptibility testing of clinical Mycobacterium tuberculosis isolates. Journal of Clinical Microbiology, 2003, 41, 4865–4869. P. F. Riska, Y. Su, S. Bardarov, L. Freundlich, G. Sarkis, G. Hatfull, C. Carriere, V. Kumar, J. Chan, and W. R. Jacobs Jr, Rapid film-based determination of antibiotic susceptibilities of Mycobacterium tuberculosis strains by
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
using a luciferase reporter phage and the Bronx Box. Journal of Clinical Microbiology, 1999, 37, 1144–1149. 40. D. E. Nivens, T. E. McKnight, S. A. Moser, S. J. Osbourn, M. L. Simpson, and G. S. Sayler,
Bioluminescent bioreporter integrated circuits: potentially small, rugged and inexpensive whole-cell biosensors for remote environmental monitoring. Journal of Applied Microbiology, 2004, 96, 33–46.
9 Natural Luminescent Whole-Cell Bioreporters Shimon Ulitzur Department of Biotechnology and Food Engineering, Technion Institute, Haifa, Israel
The analytical applications of the bacterial luminescence system have been reviewed by several authors.1–6 Most of the analytical applications described before 1982 were based on the luminescence system of cell-free extracts, while the use of intact luminous bacteria for analytical purposes has been largely ignored. Luminescent bacteria occur mainly in the sea. Eleven species in 4 genera have been described, namely, Vibrio, Photobacterium, Shewanella (Altermonas), and Photorhabdus (Xenorhabdus). The last-mentioned one is a terrestrial genus, while the others are marine. The enzyme luciferase, a mixed-function oxidase, simultaneously oxidizes both reduced flavin mononucleotide (FMNH2 ) and a long-chain aldehyde to give FMN, water, and the corresponding fatty acid, leading to the emission of blue–green (490 nm) light. Molecular aspects of the bacterial lux system have been reviewed.7–9 The use of the intact luminous bacteria for analytical purposes has some clear advantages: the bacterium is a self-maintained luminescence unit that, under proper conditions, emits a high and steady level of luminescence. The light of a single bacterium may reach 5 × 104 quanta/s/cell, a level that can be readily determined with the aid of a photon counter. Thus, one can use a simple luminometer for determination of a few hundred cells per milliliter. In addition to the advantages of sensitivity and the
real-time noninvasive nature of this reporter, the imaging potential of using low-light and photoncounting video cameras has been particularly influential in establishing its ascendancy over more traditional reporter systems. The level of in vivo luminescence reflects the metabolic activity of the luminous bacteria and the integrity of the bacterial cells. Chemophysical and biological factors that affect cell respiration and the rate of protein or lipid synthesis promptly alter the level of luminescence. Similarly, factors that affect the cell’s integrity, and especially membrane function, have an effect on in vivo luminescence. The stress-controlled regulons, cAMP/CRP system, rpoH rpoS, GroESL, heat shock proteins (sigma 32), SOS system, and HNS protein are closely involved in the regulatory activity of the lux operon.10–12 Hence, any factor that influences these stress systems, directly or indirectly, affects the induction and activity of the lux genes. The luminous bacteria reagents can be stored for years at −18 ◦ C in a freeze-dried state. Upon hydration, lyophilized cultures of luminous bacteria yield 95–98% of their original viability as well as their level of in vivo luminescence. Thus, the use of these preparations for analytical purposes is not different, in practice, from other biochemical tests. This chapter focuses on the description of the novel principles and approaches that have been
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
applied in using intact luminous bacteria for analytical purposes.
1 DETERMINATION OF BACTERIAL METABOLIC ACTIVITY IN FOOD PRODUCTS
Most of the raw materials and final food products are characterized by low water activity (Aw). In addition, the metabolic activity of the bacteria that survive in processed food products is very low. These facts and the absence of a continuous water phase limit the use of standard analytical tools for monitoring bacterial metabolic activity in food products. Reinhertz et al.13 were the first to show a correlation between bacterial viability and in vivo luminescence of different natural and cloned luminous bacteria in low Aw, before and after recovery. Luminous bacteria were incubated at different concentrations of sucrose, glycerol, or milk powder in different water activities. Recombinant strains of Escherichia coli and Salmonella carrying lux genes showed an excellent correlation between their ultimate level of in vivo luminescence and their viability. On the other hand, the in vivo luminescence of the terrestrial luminescent species Vibrio cholerae var. albensis-240 was more sensitive to low water activity than was their viability. Using this approach, one could estimate the proportion of “injured” luminous bacteria in the population. This information could be obtained by determining the viability as well as the level of in vivo luminescence before and after a short recovery period in rich medium. It has been shown that “lightly injured” cells were still able to develop a considerable level of luminescence after a short period of recovery, although their viability dropped sharply. However, at Aw values below 0.6, both luminescence and viability dropped to the same extent. This relationship was also found under other stress conditions, such as high temperature or in the presence of antibacterial agents. Similar observations were made by Stewart.14 Another application of bacterial bioluminescence is to monitor the metabolic activity of bacteria at low temperatures. It was shown13 that the luminescence of Photobacterium leiognathi could be determined at temperatures as low as −18 ◦ C.
1.1
Use of Aldehyde- and Myristic Acid-requiring Mutants of Luminous Bacteria for Analytical Purposes15 – 18
The synthesis of aldehyde required for the bioluminescence reaction is catalyzed by a multienzyme fatty acid reductase complex containing three proteins; reductase, transferase, and synthetase.7 These three polypeptides, encoded by luxC, luxD, and luxE, respectively, are found in the lux operons of all luminous bacteria. The transferase subunit catalyzes the transfer of activated fatty acyl groups to water as well as other oxygen and thiol acceptors, with the enzyme being acylated during the course of the reaction. This system shows high specificity for 14C acyl groups. The primary reaction catalyzed by the fatty acid reductase complex is the reduction of fatty acids to aldehydes. Both ATP and NADPH2 are required for this process. Dim strains of aldehyde-requiring mutants of luminous bacteria have been isolated from all four species of luminous bacteria. Some of these mutants, such as M42 of Vibrio harveyi, emit high luminescence in the presence of nanomole per liter concentrations of long-chain (C8–C16) fatty aldehydes, while other mutants of V. harveyi, such as M17, also respond to myristic acid and, to a much lesser extent, to C12 or C16 fatty acids. These mutants have been used for developing rapid and sensitive bioluminescent assays for lipases, phospholipases, long-chain unsaturated fatty acids, lipopolysaccharide (LPS), monoamine oxidase (MAO), antilipogenic agents, and for determination of oil oxidation. A short description of these tests is given below. 1.1.1 Assays for lipases, phospholipases, and esterase18 – 20
Quantitative determination of free fatty acids, or monitoring the kinetics of their release from a complex lipid, is very complicated and laborious. The bioluminescence assays utilize a dim mutant of V. harveyi (M17) that emits light upon the addition of myristic acid.21 The luminescence response was found to be proportional to the amount of added myristic acid over a 100-fold range, down to 10 pmol ml−1 . The substrate for the lipase test is trimyristin, a commercially available
NATURAL LUMINESCENT WHOLE-CELL BIOREPORTERS
product. The assay could be run continuously, where the M17 cells are incubated together with the lipase and the substrate, or in two steps, where the hydrolytic stage is done separately followed by an independent detecting system. These procedures allow rapid determination (5 min) of lipase activity corresponding to the release of as little as 1–2 pmol min−1 of myristic acid. Of all the aliphatic long-chain fatty acids tested, myristic acid was the most active, being at least 20 times more active than other even-chain fatty acids. It is possible, therefore, to use mixed fatty acid triglycerides having stearic acid in the α position and myristic acid in the β position, or vice versa, to determine lipase specificity. In addition to lipase, other enzymes or any hydrolytic activity that liberates free myristic acid from a more complex lipid could be equally well followed using this bioassay.20 The bioluminescent assay for phospholipase A uses L-dimyristoyl phosphorylcholine as a substrate. For phospholipase C, the detection is based on a coupled system in which the assay mixture contains an excess of lipase, which hydrolyzes the diglyceride formed. To avoid any lipolytic activities of M17 cells, a mutant M17LP2, lacking both phospholipase and lipase activities, was isolated.18
1.1.2 Determination of Long-chain Fatty Acids 17
Long-chain unsaturated fatty acids, as well as certain saturated fatty acids such as lauric acid, are strong inhibitors of the in vivo luminescence of wild-type strains of four species of luminous bacteria. The principal site of action of all inhibitory fatty acids appears to be the reductase activity that converts myristic acid to myristyl aldehyde. A good correlation was found between the concentration of unsaturated fatty acids and the degree of inhibition of luminescence. In the presence of myristic acid, the unsaturated fatty acids 16 : 1, 18 : 1, and 18 : 2, at nmol l−1 levels, inhibited the development of luminescence in V. harveyi M17 cells. Externally added long-chain aldehyde fully abolished the inhibitory effect of the unsaturated fatty acids.
3
1.1.3 Determination of Lipopolysaccharide (LPS)22
All gram-negative bacterial cell walls contain a lipid-A component as part of the LPS. One of the components of lipid-A is 3-hydroxy-myristic acid, which occurs only in LPS and is absent in other cellular components of the bacterial cell. Chemical conversion of 3-OH-myristic acid to myristic acid allows specific determination of LPS with the aid of the previously described V. harveyi M17 mutant. As little as 1 ng of LPS, which is equivalent to about 104 bacteria, could be detected by this test. This assay also enables rapid identification of rough and smooth variants of bacteria. 1.1.4 Determination of Antilipogenic Compounds
A sensitive and rapid bioassay for the determination of antilipogenic compounds such as cerulenin and CM-55 was developed by Ulitzur and Goldberg.23 The bioassay is based on the inhibitory effect of cerulenin and CM-55 on the in vivo luminescence of the myristic acid–requiring mutant of V. harveyi M17 cells. A total quantity as low as 0.1 µg of cerulenin could be determined within 15 min. 1.1.5 Determination of Oil Oxidation24
This test utilizes the aldehyde-requiring dark mutant of V. harveyi (M42) that emits light in the presence of long-chain (C8–C16) aliphatic aldehydes. The procedure consists of treating the oil or fat with Co++ ions in an ethanolic solution at alkaline pH. This treatment facilitates the decomposition of the hydroperoxides into long-chain aldehydes, part of which is used by the bacteria to produce light. The test was evaluated with corn, soybean, and sunflower oils and showed excellent correlation with the commonly used peroxide value assay. 1.1.6 A Sensitive Assay for Monoamine Oxidase Activity and Its Inhibitors 25,26
In vivo luminescence of the aldehyde-requiring mutant of luminous bacteria V. harveyi (M42)
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
increases dramatically upon addition of long-chain aliphatic aldehydes (C8–C16). This property was utilized for the determination of MAO activity using n-octylamine and decylamine as substrates. MAO oxidizes these substrates to the corresponding aldehydes. The rate of initial increase in luminescence and the final steady state level of luminescence were directly proportional to the concentration of MAO. The new test could be used to continuously monitor MAO activity and was found to be highly sensitive and rapid. This method has also been applied to determine the activity of different MAO inhibitors. 1.1.7 Determination of NAD+ , NADH2 , and Ethanol (S. Ulitzur – unpublished data)
This assay is based on the enzyme alcohol dehydrogenase from horse liver. The enzyme is incubated in the assay buffer in the presence of NAD+ and excess ethanol. The alcohol dehydrogenase generates NADH2 by ethanol oxidation and uses it to reduce the long-chain aldehyde to the corresponding alcohol. Neither acetaldehyde nor the long-chain alcohol is active in the production of light by the aldehyde-requiring mutant M42 of V. harveyi. This assay allows the detection of as low as nanomolar concentrations of NAD+ , within 5 min. The assay allows determination of ethanol or NADH2 when these substrates are in limited concentrations. 1.1.8 Determination of Antibiotic Activity 4,27,28
Rapid assays for antibiotics are needed for the determination of their concentration in biological fluids. In medicinal practice, such tests are essential for the detection of antibiotics that are more likely to exert a toxic effect above a certain therapeutic concentration. In the dairy industry, such tests are required to detect the presence of antibiotics in milk. Similarly, in plants that produce antibiotics, it is often necessary to determine the momentary concentration of the antibiotics in fermentors. The bacterial luminescence system can be used to determine the activity of different kinds of antibiotics. With regard to the specific end point of
the antibiotics, the developed tests can be divided into four groups: (i) the lysis test, (ii) the induced test, (iii) the bacteriophage-coupled test, and (iv) the test for miscoding agents. The lysis test uses sensitive and highly luminescent bacteria and compares the level of in vivo luminescence with and without the antibiotic in question. Antibiotics that affect the integrity of the cell wall or the cytoplasmic membrane result in the decrease of the in vivo luminescence of the treated culture. This principle has been applied for determination of the activity of b-lactams antibiotics and polymyxin.4 For determination of polymyxin B (PMB) in milk, highly luminescent P. leiognathi cells were used. Crystal violet (1 µg ml−1 ) was added to the milk to increase the sensitivity of the test. As low as 40 ng ml−1 of PMB was detected in milk in a procedure that lasted 15 min. The induced test was applied to determine the activity of protein synthesis inhibitors. The test is based on the ability of the tested antibiotics to inhibit synthesis of the luciferase in the treated cells. This test used a dark mutant of luminous bacteria that undergoes prompt induction of the luminescence system in the presence of certain DNA intercalating agents, such as proflavine or caffeine.29 Alternatively, an inducer-requiring mutant of luminous bacteria was used.30 In this case, an autoinducer (50 ng ml−1 ) was added to the assay medium. The in vivo luminescence level of the control cells increased over 50 fold within 30 min. Protein synthesis inhibitors that inhibit the de novo synthesis of proteins could be determined within 30 min.29 The third test utilized a biological coupled system in which highly luminous bacteria were infected by a specific bacteriophage. In the absence of antibiotics, the luminous bacteria were lysed within 45 min and consequently their luminescence dropped to zero. Antibiotics that inhibit DNA, RNA, or protein synthesis were found to inhibit the intracellular bacteriophage development and thus rescue the luminous bacteria.4 The fourth test used a dark miscoding mutant of the P. leiognathi luciferase to determine a specific group of antibiotics that act as miscoding or misreading agents.28 mRNA-misreading aminoglycosides such as streptomycin and neomycin increased luciferase activity in a dark nonsense mutant of luminous bacteria by more than 100
NATURAL LUMINESCENT WHOLE-CELL BIOREPORTERS
fold. This test is the simplest and most sensitive assay for determination of misreading agents. When high specificity for a given antibiotic was required, a resistant mutant for the relevant antibiotic was selected. 1.1.9 Determination of Serum Bactericidal Activity31,32
The nonmarine luminous bacteria V. cholerae var. albensis-240 were found to be extremely sensitive to the bactericidal activity of human serum. Luminous bacteria incubated in a medium containing serum showed a decrease in their in vivo luminescence that was directly proportional to the decrease in viable count and was a function of serum concentration. Both immunoglobulins and the complement system were required to exert the bactericidal activity of the serum. Serum lacking immunoglobulins or certain complement components, especially C 3, did not affect luminescence. The bactericidal effect of the serum on luminous bacteria was diminished in the presence of LPS or by pretreatment of the serum with different species of killed bacteria. As was found in other systems, the bacteriolytic activity of serum was only augmented by lysozyme, but was not lysozyme dependent; although the luminous bacteria were converted into spheroplasts in serum containing 0.5 M sucrose, their in vivo luminescence was hardly affected. This bioluminescence assay system could be used as a substitute for the hemolytic system in complement-fixation tests.
1.1.10 Determination of Phagocytosis 33 – 35
Existing methods for the evaluation of phagocytosis are inadequate for assessing all the events occurring during phagocytosis or for continuously following the kinetics of the process. The bioluminescence test offers an easy and simple method to determine the kinetics of phagocytosis by following bacterial luminescence. The terrestrial luminous bacteria V. cholerae var. albensis are readily phagocytosed by polymorphonuclear (PMN) cells. The correlation coefficient between the decrease in luminescence and the decrease in viable count was found to be 0.999. The rate of decrease in luminescence and the residual level of luminescence after
5
60 min of phagocytosis were proportional to the rate of increase in phagocytosis-induced chemiluminescence and to its maximal level, respectively. Opsonization requirements were comparable in both tests. Different inhibitors of the phagocytosis process caused very similar changes in the rates of the biochemiluminescence and in the maximal luminescence level. This assay provides a unique approach for the determination of the mutagenic activity associated with the formation of the oxidative burst in PMN cells during phagocytosis. For this purpose V. cholerae cells were replaced with the dim K variant of P. leiognathi SD-18 and were utilized to determine the appearance of luminescence due to the mutagenic activity of oxygen radicals. Hansen et al.36 used P. phosphoreum to study the phagocytosis of mussel hemocytes. This system enabled these authors to establish the effect of chemicals and polluted rivers or sewage on the immunological defense mechanism of the exposed organisms.
1.1.11 Determination of a Cyclic Adenosine 3 , 5 -Monophosphate (cAMP)37
A mutant of the luminous bacterium Vibrio (Beneckea) harveyi that requires exogenous cyclic AMP to synthesize luciferase and emit light was isolated. The mutant was pleiotropic, lacking not only the ability to emit light, but also the capacity to form flagella and the ability to utilize a variety of carbohydrates for growth. All these deficiencies could be corrected by adding cAMP. The cAMP-induced de novo synthesis of luciferase was possible only after autoinduction had occurred. The induction time by cyclic AMP ranged from 6 to 10 min at 20 ◦ C. As low as 50 ng ml−1 of cAMP was detected in an hour-long procedure and a linear correlation between cAMP concentration and in vivo luminescence in the range of 0.1–100 ng ml−1 was shown. A similar dependence of luminescence on cAMP was also shown by others for V. fischeri.7
1.1.12 Determination of Oxygen Transmission Rates through Plastic Films 38
The method is based on the measurement of in vivo light intensity emitted by luminous bacteria
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
confined in a pouch made of the tested plastic film. The measured light intensity was found to be linearly proportional to the oxygen transmissibility of different plastic films.
2 BACTERIAL LUMINESCENCE AS AN EARLY INDICATION OF MARINE FISH SPOILAGE39
Aristotle (384–322 B.C.) was the first to describe the bioluminescence of dead fish. Marine luminous bacteria are readily isolated from the sea as well as from the gut and surface of marine creatures. The relationship between different microbiological and biochemical parameters and the development of bacterial bioluminescence associated with spoilage of marine fish was studied by Barak and Ulitzur.39 The bioluminescence level of bacterial suspensions taken from the fish skin increases during the storage of the fish at 20 ◦ C. The growth and luminescence of the intrinsic luminous bacteria correlated well with the total bacterial count. When fish were stored at 5 ◦ C, the increase in total count was not always accompanied by a parallel increase in luminescence. However, the transfer of fish from 20 to 5 ◦ C did not diminish existing luminescence and did not “erase the history” of the spoiled fish. This study also concluded that luminescence above 5 × 106 quanta/s/cm2 of skin indicates early stages of fish spoilage.
3 STUDYING THE MECHANISM OF ATP FORMATION IN BACTERIA (S. ULITZUR – UNPUBLISHED DATA)
The mechanism of ATP formation in bacterial cells has been studied intensively. The chemiosmotic theory predicts that the Fo-F1-ATPase utilizes the proton potential across the membrane to form ATP. A simple way to demonstrate this process with the aid of luminous bacteria has been developed. A washed culture of V. fischeri (or any other luminous bacteria that carries the whole lux system of V. fischeri ) was depleted of ATP by treating it with the uncoupler FCCP (0.01 mM in MOPS buffer at pH 6.8) or by incubation with sodium arsenate (40 mM). This treatment results in a strong drop in luminescence that can be largely recovered by
externally added aldehyde (as ATP is required for aldehyde formation). When the ATP-depleted culture was diluted in a buffered solution at low pH, the level of luminescence was rapidly restored. At a given time, a linear correlation was established between the pH values in the range of 5–7 and the level of luminescence. The lower the pH, the higher the generated luminescence. FCCP (10 nM) largely blocked this process. Hence, these ATPdepleted cells could be used to study the physiological conditions that are involved in ATP formation and for the identification of uncouplers. This assay also provides a simple way for determining the pH inside the cells, since the development of luminescence depends on the existence of a pH gradient between the two sides of the membrane.
3.1
Determination of Specific Nutrients and Vitamins (S. Ulitzur – unpublished data)
Auxotrophic mutants of luminous bacteria that require specific amino acids or vitamins can be used for sensitive determination of specific nutrients. Starved cells of auxotrophic V. fischeri mutants for trypthophane or arginine can detect 10 ng ml−1 of these amino acids.
3.2
Determination of Catalytic Antibodies40
V. harveyi M42 aldehyde-requiring mutant was used to detect the catalytic activity of an antibody that catalyzed the production of a long-chain aldehyde. The commercially available aldolase antibody 38C2 catalyzes the aldol addition and retroaldol fragmentation of 4-hydroxy-2-dodecanone to produce nonanal aldehyde and acetone. The formation of aldehyde was detected by M42. This assay, which is sensitive, inexpensive, and easy to perform, could be suitable for the early detection of catalytic antibodies in hybridoma cultures.
4 DETERMINATION OF WATER QUALITY
Water quality monitoring tests have expanded over the years to include the use of bioassays for routine testing and screening of water quality in an attempt to overcome several drawbacks of the
NATURAL LUMINESCENT WHOLE-CELL BIOREPORTERS
commonly used physiochemical tests. The identification of chemicals by sophisticated chemical and instrumental methods is conditioned by the presence of a reference sample. Such methods are unable to estimate a possible biological synergistic or antagonistic interaction between chemicals, and their routine use is limited due to their high cost and the requirement for skilled personal. The routine use of aquatic bioassays has been limited by the time required (usually days) to perform such tests as well as the cost and skill level. In order to overcome these limitations, numerous short-term bioassays have been developed in the past 15 years, but the most commonly used and thoroughly validated rapid tests are the luminescence-based bioassays based on the use of luminescent bacteria. Chemophysical and biological factors that affect cell respiration, the rate of protein or lipid synthesis, promptly alter the level of luminescence. The following sections will describe the various approaches and technologies that utilize luminescent bacteria for determination of water quality.
4.1
Microtox Test
The use of the bacterial luminescence system for the rapid assessment of aquatic toxicity was first suggested by Bulich41 and later commercially marketed as Microtox . The bioassay is based on a preparation of lyophilized cultures of V. fischeri (NRRL B11177). The lyophilized culture is hydrated with high-purity water from which 10 µl aliquots, each containing 106 cells, are added to serial dilutions of the tested water supplemented with NaCl. Light measurements from the diluted water sample and the clean water control are obtained after 5–15 min of incubation at 15 ◦ C. The minimal concentration of tested water that results in 50% inhibition of light relative to the light level of the control is defined as IC50 (or EC50) of the said water sample or of the tested chemical spiked into it. The Microtox test has been successfully applied worldwide for quality testing of industrial water, sewage, effluents, and contaminated sediments41,42 and has been qualified as a standard for certain types of samples by various standards organizations in the United States and Europe. For many chemicals and toxic water samples, the sensitivity of the tested water
7
in Microtox agreed well with the results obtained with daphnia- or fish-based bioassays.43 In order to meet the need for the higher sensitivity required for drinking water analysis, we developed for AZUR Environmental a 22-h chronic test that involves bacterial growth and de novo synthesis of the lux system in V. fischeri.44 The test has been successfully used to screen drinking water samples for the presence of unexpected chemical contamination. The test system is now commercially available as “chronic Microtox test” from Strategic Diagnostics Inc.
4.2
ToxScreen Test
A suitable test for drinking water toxicants should be rapid and sensitive enough to detect very low concentrations of diverse groups of toxic agents. Other requirements from such a test include simple operation, minimal false-positive or -negative responses, affordability, and the capability to run the test outside the laboratory. A novel bioassay (ToxScreen) that demonstrates those requirements has been developed.9 ToxScreen utilizes a marine luminescent bacterium (P. leiognathi ) and applies unique assay buffers that markedly increase the sensitivity of the test and also enable the preliminary discrimination between organic and cationic metals toxicants. Cationic heavy metals can be detected at submilligram per liter levels; many of them were detected at 10–50 µg l−1 range. Similarly, pesticides, PAHs, and chlorinated hydrocarbons were detected in a separate test, all within 20–45 min. For most of the tested toxic agents, ToxScreen was found to be markedly (over 10–100 fold) more sensitive than Microtox . 9 A practical feature of the new bioassay is the option of running the test at ambient temperatures (18–30 ◦ C). In addition, the stability of the freezedried bacterial reagent preparation precludes the need for refrigeration or freezing during shipment. These features, together with its simple operation procedure, suggest that it has potential applications as a cost-effective prescreening tool to appraise chemical toxicity in various water sources. The higher sensitivity and simplicity of the ToxScreen and has been recently confirmed by EPA’s Environmental Technology Verification (ETV) program for rapid toxicity technologies
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
(http://www.epa.gov/etv/verifications/vcenter1-12. html).
4.3
On-line Monitoring of Water Toxicity
The increasing concern for drinking water quality, together with the growing awareness of terrorism, has emphasized the need for real-time monitoring of drinking water quality. Two kinds of bioluminescence-based on-line monitors for water quality have been developed so far. An on-line monitor that utilizes lyophilized cultures of luminescent bacteria was first developed by AZUR Environmental and Siemens in the mid-1990s. The device (Microtox-OS) was designed to automate the standard Microtox test and operate on site, unattended for two weeks. The Microtox-OS Test System was equipped with a statistical process control software to continuously monitor data and was user configurable to identify test results that were statistically different from preceding values. Owing to its high operation cost, however, only a few units were sold. The TOXcontrol-BioMonitor (now available through Microlan, The Netherlands) is based on freshly cultivated, light-emitting V. fischeri cells that are continuously mixed with clean water and tested water. Light is detected using an on-line dual-monitoring luminometer as it passes through twin flow cells. Any significant difference in light detected from the reference and monitoring streams results in a number of programmable events: an alarm can be programmed, a valve can be switched to collect samples for further analysis, and so on. No information has been published on the sensitivity of this automatic bioluminescent test. In general, luminescent bacteria growing in a liquid medium in the presence of nutrients are not expected to show high sensitivity toward toxic agents. The system is mainly used for river biomonitoring and wastewater monitoring in Europe. The integration of the ToxScreen test into an automatic on-line monitor was recently introduced by CheckLight Ltd and Systea Srl. MicroMACToxScreen is an innovative, automated, on-line water quality monitoring system that utilizes the ToxScreen reagents to detect microgram per liter concentrations of toxic organic and inorganic chemical pollutants in surface- or groundwater, as
well as raw and treated drinking water. Freezedried luminescent bacteria are hydrated and kept in the device at 3 ◦ C to maintain a stable luminescent culture. The instrument is resupplied with newly hydrated, luminescent bacteria and a fresh inventory of liquid assay every 10 days. Automatic safeguards have been engineered into the system to assure reagent and data quality and appropriate instrument functioning. The instrument is also equipped with autocalibration features to assure reliable instrument performance; microprocessorbased system controls provide for data storage, data downloading, real-time communication with a remote PC, and user-adjustable alarm levels.
5 DETERMINATION OF MUTAGENIC AND CARCINOGENIC AGENTS
Ulitzur et al.3,29,45,46 were the first to use luminescent bacteria for the determination of mutagenic and genotoxic agents. The first test, later commercialized as Mutatox , was based on a spontaneous dark variant (M169) of the luminescent bacterium P. leiognathi.47,48 Light production was restored when cells were incubated in the presence of subacute concentrations of genotoxic agents, including base substitution, frameshift, DNA synthesis inhibitors, DNA damaging agents, and DNA intercalating agents.4 The Mutatox test showed very good correlation with the Ames test.3 The primary genetic lesion of M169 was later discovered to be due to the presence of a mutation in the rpoS gene.11,12
6 DETERMINATION OF NUTRIENTS IN WATER 6.1
AOC (Assimilable Organic Carbon)
The regrowth potential of heterotrophic bacteria in potable water depends mainly on the presence of an assimilable organic carbon (AOC) source. Many bacteria are capable of dividing in water containing as little as 5–10 µg l−1 of various carbon sources. Most of the standard or proposed AOC methodologies are hindered by their long duration and require between 5 and 14 days
NATURAL LUMINESCENT WHOLE-CELL BIOREPORTERS
for completion. A bioassay that utilizes nutrientdeprived cultures of V. harveyi or autoinducerrequiring mutants of V. fischeri has been developed and is commercially available (CheckLight Ltd). Luminescence in these strains is directly proportional to the concentration of utilizable organic material in the water sample. This 2-h test enables the detection of as little as 5 µg l−1 of organic carbon and the test has shown high correlation with the standard 7-day-long AOC test.
7.
8.
9.
10.
6.2
BOD (Biochemical Oxygen Demand)
The biochemical oxygen demand (BOD) test (BOD5) is a crucial environmental index for monitoring organic pollutants in wastewater but is practically limited by the 5-day requirement for completing the test. A rapid BOD test based on V. harveyi or an autoinducer-requiring mutant of V. fischeri is now commercially available (CheckLight). The test procedure requires the water in question to be boiled for 30 min in the presence of 1 N HCl, followed by addition of 1 N NaOH and MOPS buffer to neutralize the sample. This brief hydrolysis step is sufficient to break down proteins and complex carbohydrates into oligomers or monomers that can be assimilated by the bacteria. A good correlation was found between the 2-h bioluminescent test and the 5-day standard BOD test.
11.
12.
13.
14.
15.
16.
17.
REFERENCES 18. 1. P. J. Hill, S. P. Denyer, and G. S. A. B. Stewart, Rapid assays based on in vivo bacterial bioluminescence. Microbiology Europe, 1993, 1, 16–21. 2. P. J. Hill and G. S. A. B. Stewart, Use of lux genes in applied biochemistry. Journal of Bioluminescence and Chemiluminescence, 1994, 9, 211–215. 3. S. Ulitzur, Bioluminescence test for genotoxic agents. Methods in Enzymology, 1986, 133, 264–274. 4. S. Ulitzur, Determination of antibiotic activities with the aid of luminous bacteria. Methods in Enzymology, 1986, 133, 275–284. 5. S. Ulitzur, The Use of Intact Luminous Bacteria for Analytical Purposes, in Luminescent Assays, Perspectives in Endocrinology and Clinical Chemistry, M. Serio and M. Pazzagli, Raven Press, New York, 2002, pp. 95–108. 6. E. Soudry, S. Ulitzur, and S. Gepstein, Accumulation and remobilization of amino acids during senescence of detached and attached leaves: in planta analysis of
19.
20.
21.
22.
9
tryptophan levels by recombinant luminescent bacteria, Journal of Experimental Botany, 2004, 56, 695–702. E. A. Meighen and P. V. Dunlap, Physiology biochemical and genetic control of bacterial bioluminescence. Advances in Microbiology and Physiology, 1993, 34, 1–67. D. M. Sitnkov, J. B. Schineller, and T. O. Baldwin, Transcriptional regulation of bioluminescence genes from Vibrio fischeri . Molecular Microbiology, 1995, 17, 901–912. S. Ulitzur, T. Lahav, and N. Ulitzur, A novel and sensitive test for rapid determination of water toxicity. Environmental Toxicology, 2002, 17, 291–296. S. Ulitzur and P. Dunlap, The role of LuxR protein in regulation of the lux system of Vibrio fischeri . Photochemistry and Photobiology, 1995, 62, 625–632. S. Ulitzur, A. Matin, C. Fraley, and E. Meighen, HNS protein represses transcription of the lux systems of Vibrio fischeri and other luminous bacteria cloned into. Escherichia coli, 1997, 35(6), 336–342. S. Ulitzur, H-NS controls the transcription of three promoters of Vibrio fischeri lux cloned in Escherichia coli. Journal of Bioluminescence and Chemiluminescence, 1998, 13(4), 185–188. A. Reinhertz, I. J. Kopelman, and S. Ulitzur, The Metabolic Activity of Bacteria Under Conditions of Low Water Activity—Luminous Bacteria as a Model , in Analytical Applications of Bioluminescence and Chemiluminescence, L. J. Kricka, P. E. Stanley, G. H. G. Thorpe, and T. P. Whitehead (eds), Academic Press Inc, New York, 1984, pp. 541–544. G. S. A. B. Stewart, A review: In vivo bioluminescence: new potentials for microbiology. Letters in Applied Microbiology, 1990, 10, 1–8. S. Ulitzur and J. W. Hastings, Bioassay for myristic acid and ‘long chain’ aldehydes. Methods in Enzymology, 1978, LVII, 189–193. S. Ulitzur and J. W. Hastings, The control of aldehyde synthesis in the luminous bacterium, Beneckea harveyi . Journal of Bacteriology, 1979, 137, 854–859. S. Ulitzur and J. W. Hastings, Reversible inhibition of bacterial bioluminescence by long chain fatty acids. Current Microbiology, 1980, 3, 295–300. S. Ulitzur and M. Heller, A sensitive bioassay for lipase, phospholipase A2 and phospholipase C using bacterial luminescence. Methods in Enzymology, 1981, 72, 338–346. K. W. Cho, A new bioluminescent assay of cholesterol esterase using luminescent marine bacterium Vibrio harveyi mutant M-17. The Korean Journal of Microbiology, 1993, 31, 532–536. S. Ulitzur and M. Heller, New, fast and very sensitive bioluminescence assay for phospholipase A and C. Analytical Biochemistry, 1978, 91, 421–431. S. Ulitzur and J. W. Hastings, Myristic acid stimulation of bacterial luminescence in “aldehyde” mutants. Proceedings of the National Academy of Sciences of the United States of America, 1978, 75, 266–269. S. Ulitzur, I. Yagen, and S. Rottem, Determination of lipopolysaccharide by a bioluminescence technique. Applied and Environmental Microbiology, 1979, 37, 782–894.
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
23. S. Ulitzur and I. Goldberg, A sensitive, rapid and specific bioassay for the determination of antilipogenic compounds. Antimicrobial Agents and Chemotherapy, 1977, 12, 308–313. 24. A. Berkovich, U. Cogan, and S. Ulitzur, Determination of oil oxidation by an aldehyde-requiring mutant of luminous bacteria. Journal of Bioluminescence and Chemiluminescence, 1989, 3, 125–129. 25. M. Tenne, M. B. H. Youdim, S. Ulitzur, and J. P. M. Finberg, Determination of aliphatic amines by monoamine oxidase A and B studied by using bioluminescence technique. Journal of Neurochemistry, 1985, 44, 1373–1377. 26. M. Tenne, J. P. M. Finberg, M. B. Youdim, and S. Ulitzur, A new, rapid and sensitive bioluminescence assay for monamine oxidase activity. Journal of Neurochemistry, 1985, 44, 1378–1384. 27. A. Naveh, J. I. Potasman, H. Bassan, and S. Ulitzur, A new, rapid and sensitive bioluminescence of protein synthesis inhibitors antibiotics. Journal of Applied Bacteriology, 1983, 56, 457–462. 28. A. Naveh and S. Ulitzur, Determination of misreading effect of antibiotics with the aid of luminous bacteria. Journal of Microbiological Methods, 1986, 4, 241–249. 29. S. Ulitzur and I. Weiser, Acridine dyes and other DNAintercalating agents induce the luminescence in luminous bacteria and their dark variants. Proceedings of the National Academy of Sciences of the United States of America, 1981, 78, 3338–3342. 30. Y. Adar, M. Siman, and S. Ulitzur, Formation of the LuxR protein in the Vibrio fischeri lux system is controlled by HtpR through the GroESL proteins. Journal of Bacteriology, 1992, 174, 7138–7143. 31. M. Barak, S. Ulitzur, and D. Merzbach, Determination of serum bactericidal activity with the aid of luminous bacteria. Journal of Clinical Microbiology, 1983, 18, 248–253. 32. M. Barak, D. Merzbach, and S. Ulitzur, Opsonization increases permeability of the outer membrane of the luminous bacteria. Journal of Applied Bacteriology, 1985, 59, 57–61. 33. M. Barak, S. Ulitzur, and D. Merzbach, Phagocytosis induced mutagenesis in bacteria. Mutation Research, 1983, 12, 7–16. 34. M. Barak, S. Ulitzur, and D. Merzbach, Elucidation of phagocytosis mechanism with the aid of luminous bacteria. Journal of Medical Microbiology, 1983, 18, 65–72. 35. M. Barak, S. Ulitzur, and D. Merzbach, The use of luminous bacteria for determination of phagocytosis. Journal of Immunology Methods, 1983, 64, 353–363. 36. P. D. Hansen, R. Bock, and F. Brauer, Investigations of phagocytosis concerning the immunological defense mechanism of Mytilus edulis using a sublethal luminescent bacterial assay (Photobacterium phosphoreum). Comparative Biochemical and Physiology, 1991, 100, 129–132. 37. S. Ulitzur and J. Yashphe, An adenosine 3 , 5 -cyclic monophosphate requiring mutant of the luminous bacteria Beneckea harveyi . Biochimica et Biophysica Acta, 1975, 404, 321–328.
38. J. Miltz and S. Ulitzur, A new and fast bioluminescence method for determination of oxygen transmission through plastic films used in food packaging. Food Technology, 1980, 15, 389–390. 39. M. Barak and S. Ulitzur, Bacterial luminescence as an early indication of marine fish spoilage. European Journal of Applied Microbiology, 1980, 10, 155–165. 40. H. Shulman, A. Eberhard, C. Eberhard, S. Ulitzur, and E. Keinan, Highly sensitive and rapid detection of antibody catalysis by luminescent bacteria. Bioorganic and Medicinal Chemistry Letters, 2000, 10, 2353–2356. 41. A. A. Bulich and D. L. Isenberg, Use of the luminescent bacterial system for the rapid assessment of aquatic toxicity. ISA Transactions, 1981, 20, 20–33. 42. A. A. Bulich, and G. Bailey, Environmental Toxicity Assessment Using Luminescent Bacteria, in Environmental Toxicology Assessment, M. Richardson (ed), Taylor and Francis, London, 1995, pp. 29–40. 43. K. L. E. Kaiser, Qualitative and Quantitative Relationships of Microtox Data with Toxicity Data for Other Aquatic Species, in Ecotoxicology Monitoring, M. Richardson (ed), VCH, Weinheim, 1993, pp. 197–211. 44. A. A. Bulich and H. Huynh, Measuring chronic toxicity using luminescent bacteria. Canadian Technical Report of Fisheries and Aquatic Science, 1995, 2050, 23. 45. S. Ulitzur, I. Weiser, and S. Yannai, A new, sensitive, fast and simple bioluminescence assay for mutagenic compounds. Mutation Research, 1980, 74, 113–124. 46. I. Weiser, S. Ulitzur, and S. Yannai, DNA damaging agents and DNA synthesis inhibitors induce the luminescence in dark variants of luminescent bacteria. Mutation Research, 1981, 91, 443–450. 47. A. A. Bulich, Mutatox: a genotoxicity assay using luminescent bacteria. Schriftenr Ver Wasser Boden Lufthyg, 1992, 89, 763–770. 48. K. K. Kwan, B. J. Dutka, S. S. Rao, and D. Liu, Mutatox test: a new test for monitoring environmental genotoxic agents, Environmental Pollution, 1990, 65(4), 323–332.
FURTHER READING J. Engebrecht, K. Nealson, and M. Silverman, Bacterial bioluminescence: isolation and genetic analysis of functions from Vibrio fischeri . Cell, 1983, 32, 773–781. G. S. A. B. Stewart, Bacterial luminescence: development and application, Lancet, 1993, 341, 279–280. T. S. Sun and H. M. Stahr, Evaluation and application of a bioluminescent bacterial genotoxicity test. Journal of AOAC International, 1993, 76, 893–898. S. Ulitzur, A fast and sensitive assay for lipase. Biochimica et Biophysica Acta, 1979, 572, 211–211. S. Ulitzur, A. Reinhertz, and J. W. Hastings, Low oxygen favors the expression of bacterial luciferase, The luminescence system as an alternative pathway for electron transport at low oxygen tensions. Archives fur Mikrobiology, 1980, 129, 67–71.
10 Recombinant Bacterial Reporter Systems Shimshon Belkin Institute of Life Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
1 INTRODUCTION
There are two general approaches to the monitoring of chemicals in the environment. The traditional one is based on chemical or physical analysis: it allows highly accurate and sensitive determination of the exact composition of any sample, it is essential for regulatory purposes, and is necessary for understanding both the causes of pollution and the means for its potential remediation. However, a complete array of analytical instrumentation necessary for such an exhaustive analysis is complex and costly, and requires specialized laboratories. In addition, such methodologies do not provide data as to the bioavailability of pollutants, their effects on living systems, and their synergistic/antagonistic behavior in mixtures. As a partial response to these needs, a complementary approach makes use of bioassays based on living entities. Numerous biological systems have been used for such purposes, ranging from live-organism assays such as fish or Daphnia toxicity tests to others based on subcellular components or enzymes. All of them share the same characteristic: rather than identify the target chemical, they assay its effect. A special position among the test organisms utilized for such purposes is held by unicellular microorganisms, particularly bacteria. Their large population sizes, rapid growth rates, low costs, and facile maintenance make them an attractive option for environmental monitoring or for the
screening of chemicals. An additional lucrative characteristic is that bacteria can be genetically modified to respond by a detectable signal to prespecified changes in their environmental conditions. In this article we describe this class of environmental monitoring tools: genetically engineered microorganisms “tailored” to respond in a dose-dependent manner to changes in their environment. Several recent reviews1–10 have addressed different aspects of the use of such genetically engineered microorganisms as bioreporters. This chapter highlights some the recent advances in this rapidly developing field.
2 WHOLE-CELL SENSING
The most obvious criterion for the selection of the biological element at the heart of a biosensor, and for evaluating its success, is the specificity of its recognition of the target molecule. Building upon the extremely high specificity of biological molecules, biosensors have been based on the interactions between enzymes and their substrates, the recognition between antibodies and antigens, accessibility of specific target molecules to their receptors, or the high affinity of nucleic acids strands to their complementary sequences. In all of these, examples for which are abundant throughout this book, the focus is on the unique biorecognition of two molecules.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
In whole-cell biosensors, in contrast to molecule-based ones, the biological entity in question is not a molecule but rather a live, intact cell. While a lot of the specificity described above may be lost, it is more than compensated for by the fact that by monitoring such an activity we are able to detect very complex series of reactions that can exist only in an intact, functioning cell. Global parameters such as bioavailability, toxicity, or genotoxicity cannot be probed with molecular recognition or chemical analysis; they can only be assayed by live systems.
3 TOXICITY AND GENOTOXICITY TESTING; ‘‘LIGHTS OFF’’ AND ‘‘LIGHTS ON’’ ASSAYS
As implied above, the obvious strength of wholecell biosensing is not in the specificity of the observed responses but rather in their generality. This is most apparent in toxicity bioassays, designed to sum the negative impacts of the sample on a living system. In such assays, the question asked is not “what toxicants does the sample contain” but rather “how toxic is the sample”. In recent years, genetically engineered microorganisms have played roles in two parallel research directions in the development of toxicity bioassays, which may be addressed as “lights off” and “lights on” assays. The differences between the two concepts4 are schematically represented in Figure 1. The “lights off” concept is an extension of the widely accepted microbial toxicity bioassay, based
upon measurement of the decrease in light emission as a function of sample concentration by the wild-type luminescent bacterium Vibrio fischeri following a short-term exposure to the sample.11 A drawback often mentioned with regard to the Vibrio fischeri toxicity bioassay is the marine origin of the test organism. Consequently, in the search for more “environmentally relevant” systems, other microorganisms were modified to emit light constitutively and thus serve as possibly more realistic indicators of environmental toxicity. This list contains an Escherichia coli harboring luxCDABE of V. fischeri, immobilized in polyvinyl alcohol,12 a Pseudomonas fluorescens transformed with the same plasmid,13 or the cyanobacterium Synechocystis PCC6803, marked with luc from the firefly Photinus pyralis.14 In the latter case the luciferase substrate—firefly luciferin—had to be added externally. Using a different approach, Ulitzur et al.15 report the use of a highly sensitive variant of the marine bioluminescent Photobacterium leiognathi ; Weitz et al.16 demonstrate the use of two naturally bioluminescent fungi, Armillaria mellea and Mycena citricolor, for the same purpose. A different approach to toxicant-effect bioassays is based upon the molecular fusion of a reporter system to selected gene promoters of different stress response regulons. Assuming that no single reporter strain will be able to cover all potential cellular stress factors, it has been proposed that a panel of such strains be used.17 Similar panels have recently been shown to sensitively respond to important environmental pollutants such as dioxins18 and endocrine disruptors.19
Analyte
Analyte Signal
Signal
Promoter element DNA
(a)
mRNA
Reporter protein(s)
“Lights off”
Signal transduction
Reporter gene(s)
(b)
mRNA
Reporter protein(s)
“Lights on”
Figure 1. “Lights off ” (a) and “lights on” (b) bacterial reporter assay principles. [Reprinted from Belkin4 with permission from Elsevier.]
RECOMBINANT BACTERIAL REPORTER SYSTEMS
In these and many similar studies, the reporter system of choice was most often a microbial bioluminescence operon (luxCDABE ); hence the reference to the “lights on” assays (Figure 1). In all cases, the genetic stability of the strain or the reporter fusion was not reported to present a problem. In a similar manner, bacterial strains have also been developed for assaying genotoxicity, rather than “regular” toxicity. In these cases, the promoters serving as the sensing elements were selected from among DNA-repair operons such as the SOS system, and the reporters were either bacterial lux or β-gal.2,20 Recent reports propose the use of a fluorescent protein gene—Aquorea victoria gfp—as an alternative reporter system.21,22 Using gfp as a reporter, Norman et al.23 have demonstrated that the ColD cda promoter was preferable to other SOS gene promoters recA, sulA, and umuDC. A yeast-based (Saccharomyces cerevisiae) system for genotoxicity assessment is being continuously improved upon by Walmsley et al.24,25 4 NONMICROBIAL WHOLE-CELL REPORTERS
The routine use of promoter–reporter fusions in the study of regulatory pathways and other molecular mechanisms in bacteria has paved the way for the application of similar constructs in the biosensor arena; consequently, the bulk of the work in the field and hence the largest number of publications is on bacteria-based systems. This is the reason that the present review is focused around the use of prokaryotes as the live elements in whole-cell biosensors. Nevertheless, there have been reports on the use of genetically engineered eukaryotic sensors as well. For many applications, especially those pertinent to human health, the use of eukaryotic systems appears much more relevant; reports on such systems are thus likely to increase in number in the near future. At present, most published works report yeast-based systems.26 Three notable examples are the fluorescent sensing of DNAdamaging agents,25 the bioluminescent or colorimetric detection of estrogenic compounds,27,28 and the detection of toxic metals;29 in all cases, S. cerevisiae served as the host organism. These three examples, which incorporate human regulatory elements in the genetic engineering of the
3
yeast reporter, illustrate the potential for possible future emulation of mammalian reactions in singlecell systems.
5 DETECTION OF SPECIFIC CHEMICALS AND GROUPS OF CHEMICALS
Since the pioneering work of Sayler and coworkers in the construction of a lux fusion for the specific detection of naphthalene and salicylate,30 there has been a steady stream of similar constructs responsive to distinct organic or inorganic pollutants or classes of pollutants.1–10,31 Bioluminescence has served as the reporter in many of these cases, with a few examples of β-galactosidase activity and—more recently—GFP accumulation. Recent additions to these bioreporter families include a bioluminescent phenol-sensing Acinetobacter,32 a GFP-based toluene-responsive P. fluorescens,33 and a β-gal reporter of 3-chlorocatechol.34 Prominent among the analytes detected in this manner over the last decade are heavy metals,31 from mercury detection by E. coli 35 to As, Fe, Pb, and Cd sensing in S. cerevisiae.29 A different class of pollutants that naturally lends itself to detection by microbial reporters is antibiotics. Bahl et al.36 have recently demonstrated fluorescent detection of tetracycline in a rat intestine using an E. coli reporter. In general, microbial reporters are likely to provide less sensitive and less accurate detection and quantification of specific pollutants than analytical chemical techniques2 ; a good example to the contrary has been provided by Stocker et al.37 and Harms et al.9 who discuss the successful application of As(III)/As(V) biosensing in developing regions. Furthermore, insights as to potential avenues for modifying reporter specificities are provided by Galvao and de Lorenzo;38 considerations for performance optimization are elegantly outlined by van der Meer et al.7 as well as by Marqu´es et al.39 Pathways for achieving enhanced sensitivity in optical signal acquisition, down to single-molecule detection, are proposed and demonstrated by Wells et al.40,41 Nevertheless, quite possibly the main advantage offered by whole-cell sensors of specific pollutants over chemical analysis is their unique ability to detect only the bioavailable fraction of the target chemical,4,9 thus allowing its differentiation from
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
the nonavailable one. Such information may be highly valuable for risk assessment, as well as for the comparison and design of remediation options.
et al.50 who have reported the development of a fluorescence-quenching-based siderophore biosensor for measurement of Fe(III), essential for photosynthesis in oceanic waters and thus for global primary productivity and CO2 balance.
6 MEASURING THE BIOAVAILABILITY OF NUTRIENTS
An interesting variation of environmental promoter–reporter fusions was the construction of bioreporters of nutrient bioavailability. Although wastewater nitrogen and phosphorus are not the first on the “most wanted” pollutant lists, they are nevertheless primary drivers in the eutrophication of aquatic environments and the direct trigger for the development of algal and cyanobacterial blooms. It was thus of interest to see what fraction of the total limiting nutrient concentration, as determined by chemical means, is actually “seen” by phytoplankton cells. Using similar strategies, Gillor et al.42 and Mbeunkui et al.43 have reported on a Synechococcus sp. with a glnA::lux fusion and a Synechocystis sp. with an nblA::lux fusion, respectively, both of them sensitive reporters of bioavailable nitrogen. The former sensed the presence of ammonia, nitrate, nitrite, and organic nitrogen, whereas the latter was characterized mostly for nitrate detection. Similarly, Ivanikova et al.44 have reported a Synechocystis strain with the NtcA/B-dependent nitrate/nitrite-activated nirA promoter fused to bacterial luxAB that generates nitrate-dependent bioluminescence. Gillor et al.45 have also reported a highly sensitive phosphorus bioavailability sensor based upon a phoA::lux fusion in Synechococcus. Using the latter strain, it was demonstrated that under phosphorus limitation, “bioavailable P” constituted 1% or less of the chemically determined element in a freshwater lake. Dollard and Billard46 and Taylor et al.47 have demonstrated similar P- and N-responsive constructs in E. coli, the former using a phoA promoter fused to lux, the latter a nar promoter fused to GFP. An additional element highly significant to primary producers is iron; to assess the bioavailability of Fe in a freshwater environment, Durham et al.48 have fused Vibrio harveyi luxAB genes to the isiAB promoter of Synechococcus PCC 7942. They have reported a sensitive dosedependent response, which they have used to study iron bioavailability in Lake Erie.49 A completely different strategy was adopted by Chung Chun
7 SELECTION OF REPORTER FUNCTION
As indicated several times above, bacterial bioluminescence genes played a most prominent role among the possible quantifiable cellular outputs used over the years as reporting elements in sensor systems. Several bioluminescence reporters are available, some of them recently compared by Mitchell et al.51 In recent years, as increasingly versatile fluorescent protein genes became available for general use,52 their popularity as reporters increased as well. At least two studies22,53 compared bioluminescent to fluorescent reporting and came up with similar conclusions: bioluminescence allows a much faster and more sensitive detection of the target analyte than fluorescence. The advantages of bioluminescence over fluorescent reporting are not surprising, as the former is a measure of enzymatic activity whereas the latter quantifies the presence of the protein. However, a unique advantage offered by fluorescent proteins is their stability. When real-time monitoring of the developing signal is impractical, fluorescence may prove to be much more reliable; furthermore, if sufficient time is allowed for signal accumulation, even the sensitivity will be significantly improved.22 Recent improvements in available fluorescent protein reporters and in detection technologies appear to be closing this gap. Indeed, Wells et al.40 have demonstrated arsenic-inducible eGFP production in single E. coli cells. Another attractive enzymatic reporting option is based on electrochemical rather than optical detection: with a suitable substrate, the product of the activity of the reporter enzyme can be detected electrochemically. This has been utilized for rapid and sensitive detection of heavy metals and other toxicants54–56 and has recently been miniaturized and incorporated into a silicon chip.57 The use of these and other reporter functions (including amperometric, potentiometric, conductimetric, and colorimetric) has recently been reviewed by Lei et al.8 Most bioluminescence reporter genes used to date
RECOMBINANT BACTERIAL REPORTER SYSTEMS
have been limited to a small set of bacterial and insect species; other luminescent organisms, abundant especially in marine environments, may serve as sources for additional, potential light-emitting reporter genes. One such example is provided by Wiles et al.58 who describe superior performance by a luciferase (Gluc) from the marine copepod Gaussia princeps.
8 MULTIPLE REPORTERS
Several reports have been published on the incorporation of two distinct reporters in a single organism. In an early study, Wood and Gruber59 introduced two beetle luciferases, different in their light-emission spectra, into E. coli. Similarly, Mirasoli et al.60 described two fluorescent proteins, green (GFPuv) and yellow (YFP), that were introduced into the same bacterial host species. In both of these studies, one of the reporters served as the responder to the analyte, and the other as an internal control. Unge et al.61 have combined bioluminescence (luxAB) and fluorescence (gfp) reporting in both E. coli and P. fluorescens to simultaneously quantify cell numbers and monitor the level of their metabolic activity. A different approach was used by Mitchell and Gu,62 who constructed bacterial reporter strains that responded by fluorescence to DNA damage hazards (recA::GFPuv4 ) and by luminescence to oxidative stress (a katG::luxCDABE fusion). Baumstark et al.63 have engineered a Salmonella strain that expressed gfp constitutively and lux, driven by an SOS promoter, inductively, to simultaneously detect cytotoxicity and genotoxicity. Similarly, Hever and Belkin64 constructed a double-labeled E. coli reporter strain, containing two inducible promoters fused to different fluorescent protein genes: recA ::egfp and grpE ::dsRedExpress. The recA promoter is a part of the bacterial SOS system and its activation is considered an indication of DNA damage hazard;20 GrpE is a heat shock protein, induced by a broad spectrum of chemicals, and was shown to be an excellent indicator of general toxic cellular stress.65 Their combination, therefore, potentially allows an assay of both genotoxicity and “regular” toxicity by the same organism. Ponomarev et al.66 have described
5
a triple-modality mammalian reporter gene for fluorescence, bioluminescence, and nuclear wholebody noninvasive imaging.
9 THE MAKING OF A WHOLE-CELL BIOSENSOR: INTEGRATING REPORTER CELLS INTO HARDWARE PLATFORMS
Regardless of the sophistication of its genetic engineering, the applicability of a bacterial reporter strain “as is” may be limited to its use as a laboratory reagent only. To be taken outside these boundaries, it needs to be incorporated into a biosensing device that will allow storage and maintenance of the live cells, sample introduction, and signal transduction. Various approaches for viability and activity maintenance of live reporter cells over prolonged periods of time have recently been reviewed by Bjerketorp et al.67 Potential incorporation solutions include alginate attachment onto optic fiber tips,68 agar immobilization at the bottom of microtiter plate wells,43 and encapsulation in sol gel matrices.69 In the latter report, encapsulated luminescent bacteria maintained full activity at 4 ◦ C for over 3 months. A different approach, that of random embedding of individual fluorescent E. coli and S. cerevisiae cells into a high-density microwell array etched at the distal edge of an optical imaging fiber was reported by Biran and Walt.70 The location and fluorescence of each individual cell was monitored using an optical decoding system, based upon the specific “signature” of each cell type. A chip-based system was developed by Simpson, Sayler, and coworkers, who used a CMOS (complementary metal-oxide semiconductor) imager for very lowlevel detection of the bioluminescent signal of a P. fluorescens strain induced by naphthalene or salicylate.71 Their device, termed bioluminescent bioreporter integrated circuit (BIBIC ), is probably the first integrated whole-cell biochip. A different tack toward the production of a whole-cell biochip is pursued in our laboratory, in which fluorescent E. coli sensor cells are maintained in millimeter-size cavities on a silicon chip. The fluorescence induced following an introduction of the sample into the cavity is recorded by a CMOS imager and quantified. Figure 2 displays an on-chip image of a recA ::egfp harboring strain, induced by nalidixic acid.
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
(a)
(b)
Figure 2. On-chip images of an E. coli strain containing a recA’::egfp fusion, noninduced (a) or induced by 3 mg l−1 nalidixic acid (b). Images were taken 3 h after induction. The cavity area was 1 mm2 and it contained circa 107 cells.
10 THE NEXT STEP: WHOLE-CELL ARRAYS
Microarrays have revolutionized our ability to characterize and quantify biologically relevant molecules. A large family of well-defined reactive molecules, affixed to a mapped, solid-surface grid, is exposed to a multicomponent analyte mixture. Sites in which a recognition event (most often by a complementary nucleic acid sequence) has occurred are identified by one of several possible detection techniques (e.g., fluorescence). The characteristics of the sample—and hence the constituents and/or the response of the studied system—can then be discerned from the nature of the bioreceptor molecules occupying these sites. Using this principle, an increasingly large number of applications are being developed in medicine, biology, toxicology, drug screening, and other fields. Most of the arrays described are based on oligonucleotides, some on antibodies, proteins, or enzymes. The concept of using live cells as the array components in a “whole-cell array” has been advanced by Van Dyk et al.,72 who described the LuxArray: a collection of 689 nonredundant functional promoter fusions to Photorhabdus luminescens luxCDABE in live E. coli strains, representing close to 30% of the predicted transcriptional units in this bacterium. High-density printing of the reporter strains to membranes on agar plates was used for simultaneous assays of gene expression with impressive results. Initially aimed toward gene expression studies, this approach can also be successfully utilized for biosensing purposes, efficiently combining effect testing with
analyte identification. Descriptions of such arrays have recently been published by Lee et al.,73 Biran et al.,74 and by Kuang et al.,75 the former utilizing miniature agar-immobilized culture drops and the latter two using individual cells attached to the end of an optic fiber bundle. 11 SUMMARY
A novel class of biosensors has emerged over the last decade: genetically engineered microorganisms that respond in a dose-dependent manner to the presence of target chemicals. Recent advances in the field include the expansion of available reporter functions (with multicolored fluorescent proteins), a broadening of the detected chemical effects (such as the availability of nutrients) and enhancement of the spectrum of reporter microorganisms to include cyanobacteria, yeast, and fungi. Most importantly, the stage has been set for the incorporation of such cells into various whole-cell array formats on silicon chips, optic fibers, and other configurations. ACKNOWLEDGMENTS
Research in the Belkin laboratory was supported by Defense Advanced Research Projects Agency (DARPA) of the US Department of Defense (Grant N00173-01-1-G009). The CMOS images (Figure 2) are by R. Rosen (Hebrew University), A. Rabner, and Y. Shacham (Tel Aviv University, Israel).
RECOMBINANT BACTERIAL REPORTER SYSTEMS
REFERENCES 1. S. Daunert, G. Barret, J. S. Feliciano, R. S. Shetty, S. Shrestha, and W. Smith-Spencer, Genetically engineered whole-cell sensing systems: coupling biological recognition with reporter genes. Chemical Reviews, 2000, 100, 2705–2738. 2. S. Kohler, S. Belkin, and R. D. Schmid, Reporter gene bioassays in environmental analysis. Fresenius Journal of Analytical Chemistry, 2000, 366, 769–779. 3. L. H. Hansen and S. J. Sørensen, The use of whole-cell biosensors to detect and quantify compounds or conditions affecting biological systems. Microbial Ecology, 2001, 42, 483–494. 4. S. Belkin, Microbial whole-cell sensing systems of environmental pollutants. Current Opinion in Microbiology, 2003, 6, 206–212. 5. M. B. Gu, R. J. Mitchell, and B. C. Kim, Whole-cell-based biosensors for environmental biomonitoring and application. Advances in Biochemical Engineering/Biotechnology, 2004, 87, 269–305. 6. A. C. Vollmer and T. K. Van Dyk, Stress responsive bacteria: biosensors as environmental monitors. Advances in Microbial Physiology, 2004, 49, 131–174. 7. J. R. van der Meer, D. Tropel, and M. Jaspers, Illuminating the detection chain of bacterial bioreporters. Environmental Microbiology, 2004, 6, 1005–1020. 8. Y. Lei, W. Chen, and A. Mulchandani, Microbial biosensors. Analytica Chimica Acta, 2006, 568, 200–210. 9. H. Harms, M. C. Wells, and J. R. van der Meer, Wholecell living biosensors—are they ready for environmental application? Applied Microbiology and Biotechnology, 2006, 70, 273–280. 10. S. J. Sørensen, M. Burmølle, and L. H. Hansen, Making bio-sense of toxicity: new developments in whole-cell biosensors. Current Opinion in Biotechnology, 2006, 17, 11–16. 11. A. A. Quershi, A. A. Bulich, and D. L. Isenberg, Microtox Toxicity Test Systems—Where They Stand Today, in Microscale Testing in Aquatic Toxicology: Advances, Techniques, and Practice, P. G. Wells, K. Lee, and C. Blaise (eds), CRC Press, Boca Raton, 1998, pp. 185–199. 12. A. M. Horsburgh, D. P. Mardlin, N. L. Turner, R. Henkler, N. Strachan, L. A. Glover, G. I. Paton, and K. Killham, On-line microbial biosensing and fingerprinting of water pollutants. Biosensors and Bioelectronics, 2002, 17, 495–501. 13. T. Tiensing, N. Strachan, and G. I. Paton, Evaluation of interactive toxicity of chlorophenols in water using luxmarked biosensors. Journal of Environmental Monitoring, 2002, 4, 482–489. 14. C. Y. Shao, C. J. Howe, A. J. R. Porter, and L. A. Glover, Novel cyanobacterial biosensor for detection of herbicides. Applied and Environmental Microbiology, 2002, 68, 5026–5033. 15. S. Ulitzur, T. Lahav, and N. Ulitzur, A novel and sensitive test for rapid determination of water toxicity. Environmental Toxicology, 2002, 17, 291–296. 16. H. J. Weitz, C. D. Campbell, and K. Killham, Development of a novel, bioluminescence-based, fungal bioassay for
17.
18.
19.
20.
21.
22.
23.
24.
25. 26.
27.
28.
29.
30.
7
toxicity testing. Environmental Toxicology, 2002, 4, 422–429. S. Belkin, D. R. Smulski, S. Dadon, A. C. Vollmer, T. K. Van Dyk, and R. A. LaRossa, A panel of stress-responsive luminous bacteria for toxicity detection. Water Research, 1997, 31, 3009–3016. J. Min, C. H. Pham, and M. B. Gu, Specific responses of bacterial cells to dioxins. Environmental Toxicology and Chemistry, 2003, 22, 233–238. M. B. Gu, J. Min, and E. J. Kim, Toxicity monitoring and classification of endocrine disrupting chemicals (EDCs) using recombinant bioluminescent bacteria. Chemosphere, 2002, 46, 289–294. A. C. Vollmer, S. Belkin, D. R. Smulski, T. K. Van Dyk, and R. A. LaRossa, Detection of DNA damage by use of Escherichia coli carrying recA ::lux, uvrA ::lux, or alkA ::lux reporter plasmids. Applied and Environmental Microbiology, 1997, 63, 2566–2571. M. Kostrzynska, K. T. Leung, H. Lee, and J. T. Trevors, Green fluorescent protein-based biosensor for detecting SOS-inducing activity of genotoxic compounds. Journal of Microbiological Methods, 2002, 48, 43–51. E. Sagi, N. Hever, R. Rosen, A. J. Bartolome, J. R. Premkumar, R. Ulber, O. Lev, T. Scheper, and S. Belkin, Fluorescence and bioluminescence reporter functions in genetically modified bacterial sensor strains. Sensors and Actuators B-Chemical, 2003, 90, 2–8. A. Norman, L. H. Hansen, and S. J. Sørensen, Construction of a ColD cda promoter-based SOS-green fluorescent protein whole-cell biosensor with higher sensitivity toward genotoxic compounds than constructs based on recA, umuDC, or sulA promoters. Applied and Environmental Microbiology, 2005, 71, 2338–2346. A. W. Knight, P. O. Keenan, N. J. Goddard, P. R. Fielden, and R. M. Walmsley, A yeast-based cytotoxicity and genotoxicity assay for environmental monitoring using novel portable instrumentation. Journal of Environmental Monitoring, 2004, 6, 71–79. A. W. Knight, Using yeast to shed light on DNA damaging toxins and irradiation. Analyst, 2004, 129, 866–869. K. H. Baronian, The use of yeast and moulds as sensing elements in biosensors. Biosensors and Bioelectronics, 2004, 19, 953–962. J. Sanseverino, R. K. Gupta, A. C. Layton, S. S. Patterson, S. A. Ripp, L. Saidak, M. L. Simpson, T. W. Schultz, and G. S. Sayler, Use of Saccharomyces cerevisiae BLYES expressing bacterial bioluminescence for rapid, sensitive detection of estrogenic compounds. Applied Environmental Microbiology, 2005, 71, 4455–4460. E. J. Routledge and J. P. Sumpter, Estrogenic activity of surfactants and some of their degradation products assessed using a recombinant yeast screen. Environmental Toxicology and Chemistry, 1996, 15, 241–248. V. Radhika, M. Milkevitch, V. Audige, T. ProikasCezanne, and D. Dhanasekaran, Engineered Saccharomyces cerevisiae strain BioS-1, for the detection of water-borne toxic metal contaminants. Biotechnology and Bioengineering, 2005, 90, 29–35. R. S. Burlage, G. S. Sayler, and F. Larimer, Monitoring of naphthalene catabolism by bioluminescence with nahlux transcriptional fusions. Journal of Bacteriology, 1990, 172, 4749–4757.
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
31. N. Verma and M. Singh, Biosensors for heavy metals. Biometals, 2005, 18, 121–129. 32. D. Abd-El Haleem, S. Ripp, C. Scott, and G. S. Sayler, A luxCDABE-based bioluminescent bioreporter for the detection of phenol. Journal of Industrial Microbiology and Biotechnology, 2002, 29, 233–237. 33. L. Stiner and L. J. Halverson, Development and characterization of a green fluorescent protein-based bacterial biosensor for bioavailable toluene and related compounds. Applied Environmental Microbiology, 2002, 68, 1962–1971. 34. X. Guan, E. d’Angelo, W. Luo, and S. Daunert, Whole-cell biosensing of 3-chlorocatechol in liquids and soils. Analytical and Bioanalytical Chemistry, 2002, 374, 841–847. 35. O. Selifonova, R. Burlage, and T. Barkay, Bioluminescent sensors for detection of bioavailable Hg(II) in the environment. Applied Environmental Microbiology, 2003, 59, 3083–3090. 36. M. I. Bahl, L. H. Hansen, T. R. Licht, and S. J. Sorensen, In vivo detection and quantification of tetracycline by use of a whole-cell biosensor in the rat intestine. Antimicrobial Agents and Chemotherapy, 2004, 48, 1112–1117. 37. J. Stocker, D. Balluch, M. Gsell, H. Harms, J. S. Feliciano, K. A. Malik, S. Daunert, and J. R. van der Meer, Development of a set of simple bacterial biosensors for quantitative and rapid field measurements of arsenite and arsenate in potable water. Environmental Science and Technology, 2003, 37, 4743–4750. 38. T. C. Galvao and V. de Lorenzo, Transcriptional regulators a la carte: engineering new effector specificities in bacterial regulatory proteins. Current Opinion in Biotechnology, 2006, 17, 34–42. 39. S. Marqu´es, I. Aranda-Olmedo, and J. L. Ramos, Controlling bacterial physiology for optimal expression of gene reporter constructs. Current Opinion in Biotechnology, 2006, 17, 50–56. 40. M. Wells, M. Gosch, R. Rigler, H. Harms, T. Lasser, and J. R. van der Meer, Ultrasensitive reporter protein detection in genetically engineered bacteria. Analytical Chemistry, 2005, 77, 2683–2689. 41. M. Wells, Advances in optical detection strategies for reporter signal measurements. Current Opinion in Biotechnology, 2006, 17, 28–33. 42. O. Gillor, A. Harush, O. Hadas, A. F. Post, and S. Belkin, A cyanobacterial glnA::lux fusion for assessment of nitrogen bioavailability in a freshwater lake. Applied and Environmental Microbiology, 2003, 69, 1465–1474. 43. F. Mbeunkui, C. Richaud, A. L. Etienne, R. D. Schmid, and T. T. Bachmann, Bioavailable nitrate detection in water by an immobilized luminescent cyanobacterial reporter strain. Applied and Environmental Microbiology, 2002, 60, 306–312. 44. N. V. Ivanikova, R. M. L. McKay, and G. S. Bullerjahn, Construction and characterization of a cyanobacterial bioreporter capable of assessing nitrate assimilatory capacity in freshwater. Limnology and OceanographyMethods, 2005, 3, 86–93. 45. O. Gillor, O. Hadas, A. F. Post, and S. Belkin, Phosphorus bioavailability monitoring by a luminescent cyanobacterial sensor strain. Journal of Phycology, 2002, 38, 107–115.
46. M. A. Dollard and P. Billard, Whole-cell bacterial sensors for the monitoring of phosphate bioavailability. Journal of Microbiological Methods, 2003, 55, 221–229. 47. C. J. Taylor, L. A. Bain, D. J. Richardson, S. Spiro, and D. A. Russell, Construction of a whole-cell gene reporter for the fluorescent bioassay of nitrate. Analytical Biochemistry, 2004, 328, 60–66. 48. K. A. Durham, D. Porta, M. R. Twiss, R. M. L. McKay, and G. S. Bullerjahn, Construction and initial characterization of a luminescent Synechococcus sp. PCC 7942 Fe-dependent bioreporter. FEMS Microbiology Letters, 2002, 209, 215–221. 49. D. Porta, G. S. Bullerjahn, M. R. Twiss, S. W. Wilhelm, L. Poorvin, and R. M. L. McKay, Determination of bioavailable Fe in Lake Erie using a luminescent cyanobacterial bioreporter. Journal of Great Lakes Research, 2005, 31(Suppl. 2), 180–194. 50. L. C. K. Chung Chun, T. D. Jickells, D. J. Richardson, and D. A. Russel, Fluorescence-based siderophore biosensor for the determination of bioavailable iron in oceanic waters. Analytical Chemistry, 2006, 78, 5040–5045. 51. R. J. Mitchell, J. M. Ahn, and M. B. Gu, Comparison of Photorhabdus luminescens and Vibrio fischeri lux fusions to study gene expression pattern. Journal of Microbiology and Biotechnology, 2005, 15, 48–54. 52. J. Zhang, R. E. Campbell, A. Y. Ting, and R. Y. Tsien, Creating new fluorescent probes for cell biology. Nature Reviews Molecular Cell Biology, 2002, 3, 906–918. 53. K. Hakkila, M. Maksimow, M. Karp, and M. Virta, Reporter genes lucFF, luxCDABE, gfp and dsred have different characteristics in whole-cell bacterial sensors. Analytical Biochemistry, 2002, 301, 235–242. 54. I. Biran, R. Babai, K. Levcov, J. Rishpon, and E. Z. Ron, Online and in situ monitoring of environmental pollutants: electrochemical biosensing of cadmium. Environmental Microbiology, 2000, 2, 285–290. 55. Y. Paitan, I. Biran, N. Shechter, D. Biran, J. Rishpon, and E. Z. Ron, Monitoring aromatic hydrocarbons by whole cell electrochemical biosensors. Analytical Biochemistry, 2004, 335, 175–183. 56. T. Neufeld, D. Biran, R. Popovtzer, T. Erez, E. Z. Ron, and J. Rishpon, Genetically engineered pfabA pfabR bacteria: an electrochemical whole cell biosensor for detection of water toxicity. Analytical Chemistry, 2006, 78, 4952–4956. 57. R. Popovtzer, T. Neufeld, D. Biran, E. Z. Ron, J. Rishpon, and Y. R. Shacham-Diamand, Novel integrated electrochemical nano-biochip for toxicity detection in water. Nano Letters, 2005, 5, 1023–1027. 58. S. Wiles, K. Ferguson, M. Stefanidou, D. B. Young, and B. D. Robertson, Alternative luciferase for monitoring bacterial cells under adverse conditions. Applied Environmental Microbiology, 2005, 71, 3427–3432. 59. K. V. Wood and M. G. Gruber, Transduction in microbial biosensors using multiplexed bioluminescence. Biosensors and Bioelectronics, 1996, 11, 207–214. 60. M. Mirasoli, J. Feliciano, E. Michelini, S. Daunert, and A. Roda, A. Internal response correction for fluorescent whole-cell biosensors. Analytical Chemistry, 2002, 74, 5948–5953. 61. A. Unge, R. Tombolini, L. Mølbak, and J. K. Jansson, Simultaneous monitoring of cell number and
RECOMBINANT BACTERIAL REPORTER SYSTEMS
62.
63.
64.
65.
66.
67.
metabolic activity of specific bacterial populations with a dual gfp-luxAB marker system. Applied Environmental Microbiology, 1999, 65, 813–821. R. J. Mitchell and M. B. Gu, An Escherichia coli biosensor capable of detecting both genotoxic and oxidative damage. Applied Microbiology and Biotechnology, 2004, 64, 46–52. C. Baumstark-Khan, K. Cioara, P. Rettberg, and G. Horneck, Determination of geno- and cytotoxicity of groundwater and sediments using the recombinant SWITCH test. Journal of Environmental Science and Health Part A, 2005, 40, 245–263. N. Hever and S. Belkin, A dual-color bacterial reporter strain for the detection of toxic and genotoxic effects. Engineering in Life Sciences, 2006, 6, 319–323. T. K. Van Dyk, W. R. Majarian, K. B. Konstantinov, R. M. Young, P. S. Dhurjati, and R. A. LaRossa, Rapid and sensitive pollutant detection by induction of heat shock gene-bioluminescence gene fusions. Applied Environmental Microbiology, 1994, 60, 1414–1420. V. Ponomarev, M. Doubrovin, I. Serganova, J. Vider, A. Shavrin, T. Beresten, A. Ivanova, L. Ageyeva, V. Tourkova, J. Balatoni, W. Bornmann, R. Blasberg, and J. Gelovani Tjuvajev, A novel triple-modality reporter gene for whole-body fluorescent, bioluminescent, and nuclear noninvasive imaging. European Journal of Nuclear Medicine, 2004, 31, 740–751. J. Bjerketorp, S. Hakansson, S. Belkin, and J. K. Jansson, Advances in preservation methods: keeping biosensor microorganisms alive and active. Current Opinion in Biotechnology, 2006, 17, 43–49.
9
68. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Bioluminescent whole cell optical fiber sensor to genotoxicants: system optimization. Sensors and Actuators B-Chemical, 2001, 74, 18–26. 69. J. R. Premkumar, R. Rosen, S. Belkin, and O. Lev, Sol-gel luminescence biosensors: encapsulation of recombinant E. coli reporters in thick silicate films. Analytica Chimica Acta, 2002, 462, 11–23. 70. I. Biran and D. R. Walt, Optical imaging fiber-based single live cell arrays: a high-density cell assay platform. Analytical Chemistry, 2002, 74, 3046–3054. 71. D. E. Nivens, T. E. McKnight, S. A. Moser, S. J. Osbourn, M. L. Simpson, and G. S. Sayler, Bioluminescent bioreporter integrated circuits: potentially small, rugged and inexpensive whole-cell biosensors for remote environmental monitoring. Journal of Applied Microbiology, 2004, 96, 33–46. 72. T. K. Van Dyk, E. J. DeRose, and G. E. Gonye, LuxArray, a high-density, genome wide transcription analysis of Escherichia coli using bioluminescent reporter strains. Journal of Bacteriology, 2001, 183, 5496–5505. 73. J. H. Lee, R. J. Mitchell, B. C. Kim, D. C. Cullen, and M. B. Gu, A cell array biosensor for environmental toxicity analysis. Biosensors and Bioelectronics, 2005, 21, 500–507. 74. I. Biran, D. M. Rissin, E. Z. Ron, and D. R. Walt, Optical imaging fiber-based live bacterial cell array biosensor. Analytical Biochemistry, 2003, 315, 106–113. 75. Y. Kuang, I. Biran, and D. R. Walt, Living bacterial cell array for genotoxin monitoring. Analytical Chemistry, 2004, 76, 2902–2909.
11 Recombinant Whole-Cell Bioreporter Systems Based on Beetle Luciferases Angela Ivask,1 Anne Kahru1 and Marko Virta2 1
National Institute of Chemical Physics and Biophysics, Tallinn, Estonia and 2 Department of Applied Chemistry and Microbiology, University of Helsinki, Helsinki, Finland
1 INTRODUCTION
Bioluminescence is one of the most widely used reporter system in living cells. There is a wide variety of naturally bioluminescent, both marine and terrestrial organisms, in which the luminescence production occurs during oxidation reaction catalyzed by an enzyme luciferase. Although carrying similar name, luciferase enzymes found in pro- and eukaryotic organisms do not share much similarity. Prokaryotic luciferases consist usually of two subunits (products of luxA and luxB genes) whereas eukaryotic enzymes are encoded by a single gene (usually luc). In reporter applications, the most often used eukaryotic luciferases originate from beetles whereas the luciferase encoded by luc gene from firefly Photinus pyralis is the most favorite. This enzyme has been expressed in a wide variety of host cells, from prokaryotes to plants and mammalian cells (reviewed by1 ) having thus certain advantages in front of bacterial luciferase, whose use is generally restricted to prokaryotes. In this chapter an overview is given on the possibilities and limitations of beetle luciferases in whole-cell bioreporter systems and biosensors. Examples on the use of beetle luciferase-based bacterial and yeast-based bioreporter systems for the quantification of bioavailable heavy metals
and organic compounds in environmental samples as well as identifying endocrine disruptive compounds are given.
2 BEETLE LUCIFERASES
Many eukaryotic species produce enzymes— luciferases—that produce luminescence during their catalysis of reaction. Eukaryotic luciferases may catalyze different reactions, depending on the source organism. Only luciferase (synthesized from gene luc) originating from American firefly (P. pyralis) has been widely used as a reporter gene. One reason for this may be the fact that it was the first one that was cloned, now nearly twenty years ago.2 In addition, luciferase purified from firefly tails had been used for the measurement of adenosine triphosphate (ATP) long before the cloning of the gene. Because of this, laboratories already had the necessary instruments to measure luciferase activity. Firefly luciferase catalyzes oxidation of Dluciferin to oxyluciferin and uses ATP and molecular oxygen as its other substrates (Figure 1). In the reaction, adenosine monophosphate (AMP), PPi , and CO2 are produced, in addition to yellow light with an emission maximum at 560 nm. Firefly luciferin is a benzothiazoyl-thiazole. The
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS N
N
S
S
HO
CO2H
+ATP −PPi AMP
HO
N
N
S
S +O2
C O
−H+
HO
N
O O N C
S
S
− O
−CO2
HO
N
N
S
S
* O
hν (red)
HO
N
N
S
S
*− O
hν (green)
Figure 1. The hypothetical reaction mechanism of firefly luciferase.3 Luciferase first catalyzes the condensation of ATP with luciferin in the presence of Mg2+ , followed by the reaction of adenylate with oxygen and cyclization of the peroxide. The breakdown of the dioxetanone ring releases the energy necessary to generate the excited state of oxyluciferin and CO2 . The reaction mechanism of click beetle luciferases (Phyrophorus plagiophthalamus) is very likely to be similar.4
critical energy-rich intermediate in the reaction is a four-membered dioxetanone ring, which decomposes to CO2 and an electronically excited carbonyl compound. The quantum yield of the firefly luciferase is relatively high, about 0.885 and the enzyme can be detected at subattomole levels.6 The structure of firefly luciferase shows two distinct domains, a large N-terminal domain and a small C-terminal domain.7 The domains are linked together by a flexible four-residue loop, which is also the most conserved part of the structure among all beetle luciferases and other ATP activating enzymes, together with the residues that face the cleft between domains. The active site may be located in this region. However, the cleft is too wide to allow both surfaces to interact with luciferin simultaneously. In addition, the cleft is exposed to water in a crystal structure determined without substrates, whereas the active site of luciferase is reported to be very hydrophobic.8 Therefore, a
conformational change probably occurs on binding of the substrate and water is excluded from the cleft. Luciferases that catalyze the same reaction as the firefly enzyme, have been classified as beetle luciferases.9 A series of four luciferases, which catalyze the same reaction as firefly luciferase, has been cloned from American click beetle, Pyrophorus plagiophthalamus.10 Amino acid sequences of those proteins are very homologous but not identical and they emit luminescence at different wavelengths. The emission maximums range from 545 (LucGR) to 595 nm (LucOR). The mechanism of such a large difference in emission maximums with the same substrate is not totally clear. It is likely that the energy of the excited state of the mono-anion of luciferin, and hence the color of emission, depends on the tertiary structure of the catalytic site because the emission occurs when oxyluciferin is still bound to the enzyme. The difference in the
RECOMBINANT WHOLE-CELL BIOREPORTER SYSTEMS
regulatory protein and its corresponding promoter. In the absence of analyte, the regulatory protein is either repressing the transcription initiation from the corresponding promoter, or simply does not activate the transcription (Figure 2). However, when the analyte is present in the bioreporter cells, it binds with the regulatory protein, which initiates the transcription and thus, the expression of the reporter gene and the specificity of a bioreporter are mostly defined by the regulatory unit. It should me mentioned that as the binding of analyte by regulatory protein takes place intracellularly the bioreporters measure only the bioavailable fraction of analyte, that is, the fraction passing the biological membrane. The bioavailability issue will be addressed later in this chapter. Beetle luciferases (mostly firefly luciferase) have been used in bioreporters based on bacteria and yeast. The analyte can be a single compound (such as mercury ion13 ) or group of structurally related compounds (such as metals14 phenolic compounds15 or water-soluble aromatic compounds of related structure for example, benzene, toluene, ethylbenzene, and xylenes BTEX compounds16 ). It can also be a group of structurally unrelated compounds (such as endocrine disruptive ligands, see later in this chapter).
energy between 560 and 595 nm photons is only ≈4 kcal mol−1 . 2.1
Practical Viewpoint
The expression of firefly luciferase in different organisms (including eukaryotes) is usually very straightforward issue since the enzyme is a single polypeptide. A major drawback for the use of firefly luciferase in biosensors is the fact that substrate of the enzyme, luciferin, has to be added exogenously and usually at acidic pH. This is a serious drawback in the development of for example, on-line biosensors and it should be solved before luc-based systems will become widely used in biosensors applications (see later in this chapter). Cloning of the genes responsible for the biosynthesis and/or recycling of luciferin should solve the issue. Some progress in the area has been made recently11 but the breakthrough remains to be seen. 3 APPLICATIONS OF BEETLE LUCIFERASES IN BIOREPORTERS AND BIOSENSORS 3.1
3
Bioreporters Using Firefly Luciferase, luc
It is more than a decade since the first recombinant bacterial whole-cell bioreporters based on luciferase synthesized from luc were constructed.12,13 In a classical bioreporters the expression of a reporter gene is controlled by a natural regulatory circuit, which in many cases consists of a
3.2
Applications of Firefly Luciferase in Biosensors
According International Union of Pure and Applied Chemistry (IUPAC) a biosensor is a 30
Firefly luciferase
mRNA P
R
luc gene
Luminescence (RLU)
Luminescence
T (a)
Mercury compound
(b)
10
1 0 10−10 10−9 10−8 10−7 10−6 10−5 Mercury compound (M)
Figure 2. Working principle (a) and a typical concentration-response curve (b) of a bioreporter. Bioreporter for mercury and organomercurial compounds is shown here as an example. P: promoter; R: regulatory protein; T: transport protein; RLU: relative light units; MeHg: methylmercury.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
4 APPLICATIONS OF LUC-BASED BIOREPORTERS IN HUMAN AND ENVIRONMENTAL RISK ASSESSMENT 4.1
Bioavailability
The term “bioavailability” has many definitions. In environmental sciences, bioavailability represents
a fraction of a compound, which is freely available to cross-cellular membrane of an organism from the medium the organism inhabits at a given time.25 The bioavailability issues have been discussed in environmental sciences for about 30 years since it became evident that some contaminants in soils and sediments appear to be less available to cause harm to humans and ecological receptors than is suggested by their total concentration.26 Currently the importance of bioavailability in environmental risk assessment has been accepted also by legislative bodies. This has lead to the development of a draft International Organization for Standardization (ISO) guideline on bioavailability assessment in soils. Indeed, due to high sorption capability of soils and sediments for different pollutants, including heavy metals and hydrophobic organic compounds, the bioavailability issues are most important in these matrices. As seen in Figure 3, bioavailability processes in soils and sediments include the contaminant interactions with solid/liquid phase (association, dissociation), the transport of contaminants to recipient organisms (either via liquid phase or direct interaction between organisms and solid phase), the entry of contaminants into living cells (passage through a biological membrane), contaminant accumulation within organisms and possible toxic effects. Due to a number of processes playing a vital role in modulation of the bioavailability of contaminants in soils and sediments the determination of bioavailable amounts of pollutants in these matrices is very complicated and no universal test has been developed. Also, within different test organisms used, the bioavailability may differ remarkably (e.g., prevailing route of uptake is different) and thus, when presenting the data or predictions
Bound contaminant
membrane
self-contained integrated device, which is capable of providing specific quantitative or semiquantitative analytical information using a biological recognition element (biochemical receptor), which is retained in direct spatial contact with an transduction element.17 Most commonly the biological element has been defined as an immobilized macromolecule such as enzyme or antibody and another, less common, approach uses the term “biosensor” more widely and adds also living micro-organisms or sections of organs or tissues as the biological element.18 Various methods exist for the entrapment of viable microbial cells into biosensor systems including immobilization in polyvinyl acetate matrix,19 latex film,20 alginatemediated immobilization onto optical fiber tips,21 agar-mediated immobilization at the bottom of microtiter plate wells,22 and encapsulation in solgel matrices. The immobilization matrix should be carefully chosen as it may interfere with the test chemicals by complexing the target analyte or shading them from bioreporter cells. Whole-cell luminescent bioreporters have been used as biological sensing elements in biosensors in several studies. However, it has to be mentioned that the luminescent bioreporter cells used for the construction of biosensors usually contain the luciferin-luciferase system from prokaryotes, mostly from Vibrio fischeri or Photorhabdus luminescens (lux genes) enabling a continuous detection of luminescence. As discussed previously in this chapter the issue connected with exogenous addition of the reaction substrate at acidic pH in the case of luc bioreporter systems should be overcome before their successful use in biosensors. Currently there is one publication on firefly luciferase-based whole-cell biosensor for toluene and its derivatives.23 In addition, yeast luc-based bioreporters for endocrine disruptive compounds have been immobilized in calcium alginate and polyvinyl acetate-based hydrogels with perspective to be used in fiber-optic biosensors.24
Association Dissociation
Released contaminant
Biological response
Biological
4
Figure 3. Bioavailability processes in soils and sediments.27
RECOMBINANT WHOLE-CELL BIOREPORTER SYSTEMS
on contaminant bioavailability, the target organism, and exposure pathway should always be mentioned. One group of organisms widely used in ecotoxicology and bioavailability measurements is bacteria—among the most numerous organisms in the environment and thus good representatives of aqueous environment as well as of soils. Bacteria as decomposers are also very important part of the environmental food-chain and thus the bioavailability of potentially biodegradable pollutants or, toxicity of nonbiodegradable pollutants (e.g., heavy metals) to biodegraders, is crucial. In following chapters some examples on the use of bacterial bioreporters for the determination of bioavailable pollutants in different environmental matrices will be discussed. 4.2
Quantification of Bioavailable Compounds in Environmental Samples by luc-based Bacterial Bioreporters
The general scheme for the analysis of bioavailable compounds including heavy metals from natural samples by luminescent bacterial bioreporters (also applicable for yeast bioreporter cells) is presented in Figure 4. In brief, the sample of interest, water, and standard solution(s) of target compound Sample (dilutions)
Standard solution of target compound
Luminescent bioreporter cells
Water
Luminescent control cells
2-h incubation Addition of D-luciferin Luminometry: Net luminescent response to bioavailable target compound modulated by potential stimulation, inhibition, or quenching by sample
Luminometry: Net luminescent response modulated by potential stimulation, inhibition, or quenching by sample
Quantification of bioavailable amount of target compound Figure 4. Scheme of analysis of bioavailable compounds from environmental samples by luminescent bioreporters.
5
is mixed with bioreporter cells as well as luminescent control cells (constitutively luminescent), incubated, the luminescent response is measured and bioavailable amount of target compound in the sample is quantified. In the case of aqueous samples no pretreatment of the sample is needed before the bioassay. In the case of soils and sediments, however, water has usually to be added to samples unless very watery sediments are analyzed. For bioreporter measurements of dry soils/sediments most often the sample is diluted 10 times with water before the analysis,28,29–31 although ratios of 1:832 , 1:533 or 1:434,35 have also been used. For soil and sediment samples it is also possible to prepare aqueous extracts (leachates) in order to determine the water-extracted bioavailable amounts of pollutants, which in many papers has been considered as bioavailable.32,36–38 In order to obtain accurate results on the samples usually a series of dilutions of the samples is analyzed. In parallel with environmental sample, a set of dilutions of the standard chemical is always included to obtain the standard curve. Incubation with environmental sample or standard chemical lasts usually for 2 h in order to give bioreporter cells enough time to synthesize luciferase as an answer to molecules in the sample analyzed. In some cases other incubation times have also been reported starting from 0.533 to 4 h.38 In order to start the bioluminescence reaction, D-luciferin is added and usually after 20 min bioluminescence is measured. During this period soil suspensions settle and the luminescent signal stabilizes. In the case of natural samples it is highly advisable to run in parallel the tests with constitutively luminescent “control cells”13,29,39 as schematically depicted on Figure 4. The increase or decrease of bioluminescence in these control cells treated similarly to bioreporter cells reports in the possible toxic, stimulating or other (e.g., light quenching) effects caused by either toxicants, nutrients, colour or turbidity, of the sample to bioluminescence production. Bioavailable fraction of the target chemical in the sample is calculated40 as follows: CF =
LB LS
(1)
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
where LB and LS indicate the luminescence produced by control cells in blank water or sample (see analysis procedure in Figure 4); CSLS = CF ∗ SLS
(2)
where SLS is the luminescence produced by bioreporter cells in the sample (see analysis procedure in Figure 4); CSLS (3) SLB where SLB is the luminescence produced by bioreporter cells in blank water (see analysis procedure in Figure 4). In a broad sense, the normalized luminescence (NL) values show how many times the luminescence of the sensor bacteria increases due to the exposure to the sample or standard analyte compared to the exposure of the same bacteria to water. NL values plotted against standard target metal constitute the standard curve. NL =
4.3
Analysis of Bioavailable Heavy Metals by luc-based Bacterial Bioreporters
A number of papers have been published on the use of luminescent whole-cell bioreporters in the analysis of bioavailable heavy metals from different environmental samples. Both, water samples as well soil and sediment matrices have been subjects of analysis. As it could be expected, the bioavailability of metals has been reported to be different in these different sample types. In aqueous samples usually very high percentage of metals has been
reported bioavailable. According to41 in natural waters 100 % of Hg, Pb, Cd, and As was bioavailable to bacterial heavy metal bioreporters. Beside the natural waters about 100% bioavailability of (water extracted) metals has also been demonstrated in aqueous extracts of metal-polluted soils: for example, As,33,35 Cd, and Pb.29,30 However, different results have also been obtained for aqueous extracts of polluted soils:28,38 have shown that bioavailability of As in soil-water extracts ranged from 15 to 35 % and the bioavailability of Pb from 4 to 21 % indicating that the bioavailability of metals in soil aqueous extracts is greatly dependent on the sample properties whereas among the most contributing factors are usually dissolved organic carbon (DOC) and hardness. In solid matrices of soils and sediments bioavailability of heavy metals has been shown to be considerably lower than in aqueous samples. Table 1 summarizes the data from different papers on bioavailable fractions of five heavy metals in soils. As it could be seen, the bioavailability of metals in different soils varies greatly. Moreover, bioavailability of metals in soils located nearby the same pollution source may differ greatly (see Table 1 and Refs. 29,30), even up to two orders of magnitude. Thus, most probably the key factors influencing the heavy metal bioavailability are soil physico-chemical properties. In general it could be concluded that in spiked samples (data from Ref. 42) the bioavailability of metals was higher than in natural samples most probably due to the lack of sufficient ageing in the spiked soils.
Table 1. Bioavailability of heavy metals in soil-water suspensions and respective particle-free extracts
Bioavailable (% of the total metal) Metal 2+
Hg
Cd2+
Pb2+ Zn2+ Cr6+ (a)
Soil-water suspension (a)
40 0.12(b) 12(a) 11.5 (0.5–56)(c) 1.02 (0.14–13.9)(d) 2.8 (0.24–8.6)(c) 0.42 (0.25–0.5)(d) 2.6(a) 46(a)
Soil-water extract (a)
1.3 0.007(b) 0.6(a) 0.1 (0.09–0.27)(c) 0 (0–2.4)(d) <0.12(c) 0.048 (0–0.62)(d) 2.6(a) 46(a)
data for a spiked agricultural soil. data for a contaminated mud sample. (c) median(min-max) value for 50 naturally polluted agricultural soils. (d) median(min-max) value for 60 naturally polluted agricultural soils. n.c.: not calculated. (b)
Ratio between bioavailability in soil-water suspension/water extact 31 17 20 115 n.c. >23 9 1 1
Reference 42 33 42 29 30 29 30 42 42
RECOMBINANT WHOLE-CELL BIOREPORTER SYSTEMS
In a number of papers the bioavailability of heavy metals in soils has been estimated by analyzing the aqueous extracts of these soils. However, as seen from Table 1 this approach is not usually an appropriate method: as shown by several authors29,33,42 bioavailability in soil suspension may exceed the one in (centrifuged) soil-water suspension up to two orders of magnitude. This may be due to the detachment of the metals in the case of direct cell-particle contact during for example, adhesion of microbial cells onto soil surfaces43 and/or released by either indirect (production of organic and inorganic acids changing soil pH and redox potential,44,45 ) or direct (production of enzymes and extracellular polymers for heavy metal mobilization) action. 4.4
Analysis of Bioavailable Organic Pollutants by luc-based Bacterial Bioreporters
Several luminescent bioreporters sensitive toward organic substances like naphthalene and its chlorinated derivates, benzene derivatives, phenols, polychlorinated biphenyls, 2,4,-dichlorophenol, 2,4-dichlorophenoxyacetic acid have been developed.39,46 However, differently from heavy metal bioreporters, which may be highly sensitive toward one metal ion only (e.g., Cr responding bacteria do not react with any other metals42 ) the differentiation capability of bioreporters for organic compounds is often low. Thus, it is not possible to use these bioreporters for the measurement of a certain pollutant but rather a class of structurally related pollutants, for example toluene-like (toluene, benzene, xylenes, methyl-and nitrotoluenes) or phenolic compounds (phenol, methylphenols, dimethylphenols, chlorophenols39,47 ). To overcome this problem, the data from environmental analysis are usually presented not as absolute concentrations but as equivalents of a selected inducer. For example, the response of a bioreporter for toluene-like compounds in natural samples may be expressed as toluene equivalents,48 which translates to amounts of other inducing compounds is dependent on the sensitivity of the bioreporter toward these compounds compared with the sensitivity toward toluene. It has to be stressed, that although poorly specific, the bacterial bioreporters are indispensable in bioavailability analysis also for organic
7
compounds. Moreover, as the “sensing elements” of the bioreporters for organics originate usually from the biodegradation pathways, the results from bioreporter analysis reflect also the potential biodegradability of the organic pollutants providing thus, the unique information about the possible remediation strategies.39,46 The general scheme for the analysis of organic compounds by bacterial bioreporters is similar with the one described for metals (Figure 4). Probably due to difficulties in interpretation of the results, the practical use of luminescent bioreporters in the measurement of bioavailable organic compounds from natural samples has not been as extensive as in the case of heavy metals. To our knowledge, only one report has been published on the analysis of bioavailable toluenelike compounds in natural samples by luc-based bioreporters.48
4.5
Measurement of Endocrine Disruptive Compounds by luc-based Yeast Bioreporters
The Organization for Economic Co-operation and Development (OECD) has defined an endocrine disrupting chemical (EDC) as “an exogenous substance that causes adverse health effects in an intact organism, or its progeny, consequent to changes in endocrine function”. Chemicals, which have so far been identified as being capable of producing estrogenic effects in some organisms, include industrial substances (e.g., phtalates and alkylphenols), pharmaceuticals, and pesticides (e.g., kepone and methoxychlor).49 It has been reported that certain sewage treatment processes and pulp mill effluents are responsible for the existence of EDCs in the aquatic ambience.50,51 Since the chemical structures of EDCs vary, the assessment of the risk must be based on biological effect monitoring, rather than chemical analysis.52 Therefore, methods based on biological recognition of EDCs, are needed to identify such chemicals and to detect their presence in the environment. Luminescent yeast-based bioreporters for measuring androgenic/estrogenic activity of different samples are possible candidates for that purpose Refs. 53 and 54 have reported on luminescent strains of Saccharomyces
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS Table 2. Bioluminescent Saccharomyces cerevisiae-based EDC assays. (Reprinted with permission Leskinen et al.54 copyright 2005, Elsevier)
Sensor strain
Receptor expression
Use
Lowest detectable concentration
S. cerevisiae BMAEREluc/ERα S. cerevisiae BMAEREluc/ERβ S. cerevisiae BMAAREluc/AR
Human estrogen receptor α (hERα) Human estrogen receptor β (hERβ) Human androgen receptor (hAR)
Detection of estrogenic activity Detection of estrogenic activity Detection of androgenic activity
0.3 × 10−10 M (17-β estradiol) 1.4 × 10−10 M (17-β estradiol) 5.3 × 10−10 M (5α-dihydrotestosterone)
LIGHT
Ligand Receptor mRNA
Luciferase +D-luciferin mRNA
Rcds
Plasmid
RE
luc
Yeast cell
Chromosome
Figure 5. Bioreporter for the detection of Endocrine disruptive activity. Rcds: estrogen or androgen receptor encoding sequence; RE: estrogen of androgen receptor responsive element; luc: insect luciferase encoding enzyme.
cerevisiae expressing human androgen and estrogen receptors (Table 2). These receptors bind the cell-entered EDCs and the receptor-EDC complex will then bind to its responsive element in DNA activating thus the expression of luc reporter gene (Figure 5). Consequently, the presence of estrogenic/androgenic activity causes increase in the luminescence produced by the yeast cells. There are several EDC detecting assays, which have been calibrated (Table 2) and even used for the analysis of real samples including effluents from sewage treatment plants24 and cosmetics.54 The yeast strains are easy to handle and because they are relatively tolerant to environmental chemicals they can be used for the detection of hormonal activity of various samples without any pretreatment.54 Those bioreporters have been used as biological sensing elements in enclosed gels as a first step to producing of fiber-optic biosensors.24
5 OUTLOOK
The use of bioluminescence as a reporter system has been and probably will remain one of the most
popular reporter systems in whole-cell bioreporters and biosensors. There are many reasons for this, the most essential being the absence of natural background (good signal-to-noise ratio) and the ease of the detection of the luminescent signal. Moreover, for the construction of the sensors only slight modifications for the natural genetic system are required, especially when luc-gene is used. Another essential advantage of the use of eukaryotic luciferase is the possibility to use this system in almost every host cell. In addition to the increasing number of constructed sensor organisms also their use in real applications, for example, environmental monitoring has greatly advanced. There are several essential arguments for the use of bioreporters in environmental analysis: they measure bioavailable rather than total concentrations of compounds, which is of great importance from risk assessment point of view; they can be used in practically nontreated samples and thus, have potential for in field analysis; the analysis is smallsized, rapid, and cost-effective compared with conventional physico-chemical techniques. Technically, many luminescent bacterial sensors are ready for real applications in the future.
RECOMBINANT WHOLE-CELL BIOREPORTER SYSTEMS
ACKNOWLEDGMENT
Financial support from Academy of Finland, Maj and Tor Nessling Foundation, World Federation of Scientists, grants from Estonian Science Foundation and Estonian Ministry of Science and Education (targeted funding project 0222601Bs03) is acknowledged. REFERENCES 1. I. Bronstein, J. Fortin, P. E. Stanley, G. S. A. B. Stewart, and L. J. Kricka, Review: chemiluminescent and bioluminescent reporter gene assays. Analytical Biochemistry, 1994, 219, 169–181. 2. J. R. deWet, K. W. Wood, and M. De Luca, Cloning of firefly luciferase cDNA and the expression of active luciferse in Escherichia coli. Proceedings of the National Academy of Sciences of the United States of America, 1985, 80, 7870–7873. 3. J.-Y. Koo, S. P. Schmidt, and G. B. Schuster, Bioluminescence of firefly: key steps in the formation of the electronically excited state. Proceedings of the National Academy of Sciences of the United States of America, 1978, 75, 30–33. 4. K. V. Wood, The chemical mechanism and evolutionary development of beetle bioluminescence. Photochemistry and Photobiology, 1995, 62, 662–673. 5. H. H. Seliger and W. D. McElroy, Quantum yield in the oxidation of firefly luciferin. Biochemical and Biophysical Research Communications, 1960, 1, 21–24. 6. M. Pazzagli, J. H. Devine, D. O. Peterson, and T. O. Baldwin, Use of bacterial and firefly luciferases as reporter genes in DEAE-Dextran-mediated transfection of mammalian cells. Analytical Biochemistry, 1992, 204, 315–323. 7. E. Conti, N. P. Franks, and P. Brick, Crystal structure of firefly luciferase throws light on a superfamily of adenylate-forming enzymes. Structure, 1996, 4, 287–298. 8. M. DeLuca, Hydrophobic nature of the active site of firefly luciferase. Biochemistry, 1969, 8, 160–166. 9. T. Wilson and J. W. Hastings, Bioluminescence. Annual Reviews in Cellular and Developmental Biology, 1998, 14, 197–230. 10. K. V. Wood, Y. A. Lam, H. H. Seliger, and W. D. McElroy, Complementary DNA coding beetle luciferases can elicit bioluminescence of different colors. Science, 1989, 244, 700–702. 11. K. Gomi and N. Kajiyama, Oxyluciferin, a luminescence product of firefly luciferase, is enzymatically regenerated into luciferin. Journal of Biological Chemistry, 2001, 76, 36508–36513. 12. E. Kobatake, T. Niimi, T. Haruyama, Y. Ikariyama, and M. Aizawa, Biosensing of benzene derivatives in the environment by luminescent Escherichia coli. Biosensors and Bioelectronics, 1995, 10, 601–605. 13. M. Virta, J. Lampinen, and M. Karp, A luminescencebased mercury biosensor. Analytical Chemistry, 1995, 67, 667–669.
9
14. S. Tauriainen, M. Karp, W. Chang, and M. Virta, Luminescent bacterial sensor for cadmium and lead. Biosensors and Bioelectronics, 1998, 13(9), 931–938. 15. S. M. Park, H. H. Park, W. K. Lim, and H. J. Shin, A new variant activator involved in the degradation of phenolic compounds from a strain of Pseudomonas putida. Journal of Biotechnology, 2003, 103, 227–236. 16. M. N. Kim, H. H. Park, W. K. Lim, and H. J. Shin, Construction and comparison of Escherichia coli wholecell biosensors capable of detecting aromatic compounds. Journal of Microbiological Methods, 2005, 60, 235–245. 17. D. R. Thevenot, K. Toth, R. A. Durst, and G. S. Wilson, Electrochemical biosensors: recommended definitions and classification. Biosensors and Bioelectronics, 2001, 16, 121–131. 18. M. L. Simpson, G. S. Sayler, B. M. Applegate, S. Ripp, D. E. Nivens, M. J. Paulus, and G. E. Jellison Jr., Bioluminescent-bioreporter integrated circuits form novel whole-cell biobioreporters. Trends in Biotechnology, 1998, 16, 332–338. 19. A. M. Horsburgh, D. P. Mardlin, N. L. Turner, R. Henkler, N. Strachan, L. A. Glover, G. I. Paton, and K. Killham, On-line microbial biosensing and fingerprinting of water pollutants. Bioreporters in Bioelectronics, 2002, 17, 495–501. 20. O. K. Lyngberg, D. J. Stemke, J. L. Schottel, and M. C. Flickinger, A single-use luciferase-based mercury bioreporter using Escherichia coli HB101 immobilized in a latex copolymer film. Journal of Industrial Microbiology and Biotechnology, 1999, 23, 668–676. 21. B. Polyak, S. Geresh, and R. S. Marks, Synthesis and characterization of a biotin-alginate conjugate and its application in a biosensor construction. Biomacromolecules, 2004, 5, 389–396. 22. F. Mbeunkui, C. Richaud, A. L. Etienne, R. D. Schmid, and T. T. Bachmann, Bioavailable nitrate detection in water by an immobilized luminescent cyanobacterial reporter strain. Applied Microbiology and Biotechnology, 2002, 60, 306–312. 23. Y. Ikariyama, S. Nishiguchi, T. Koyama, E. Kobatake, and M. Aizawa, Fibre-optic-based biomonitoring of benzene derivatives by recombinant E.coli bearing luciferase gene-fused TOL-plasmid immobilized in the fibre-optic end. Analytical Chemistry, 1997, 69, 2600–2605. 24. T. Fine, P. Leskinen, T. Isobe, H. Shiraishi, M. Morita, R. S. Marks, and M. Virta, Luminescent yeast cellbased hydrogels for estrogenic compound biodetection. Biosensors and Bioelectronics, 2006, 21, 2263–2269. 25. K. T. Semple, K. J. Doick, K. C. Jones, P. Burauel, A. Craven, and H. Harms, Defining bioavailability and bioaccessibility of contaminated soil and sediment is complicated. Environmental Science and Technology, 2004, 38, 228A–231A. 26. National Research Council of the National Academies, Division of Eart and Life Studies, Water Science and Technology Board, Committee on Bioavailability of Contaminants in Soils and Sediments, Bioavailability of Contaminants in Soils and Sediments: Processes, Tools, and Applications, The National Academies Press, Washington, DC, 2004.
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
27. L. J. Ehlers and R. G. Luthy, Contaminant bioavailability in soil and sediment. Environmental Science and Technology, 2003, 37, 295A–302A. 28. R. Turpeinen, M. Virta, and M. M. H¨aggblom, Analysis of arsenic bioavailability in contaminated soils. Environmental Toxicology and Chemistry, 2003, 22, 1–6. 29. A. Ivask, M. Francois, A. Kahru, H. C. Dubourguier, M. Virta, and F. Douay, Recombinant luminescent bacterial bioreporters for the measurement of bioavailability of cadmium and lead in soils polluted by metal smelters. Chemosphere, 2004, 22, 147–156. 30. A. Kahru, A. Ivask, K. Kasemets, L. P˜ollumaa, I. Kurvet, M. Francois, and H. C. Dubourguier, Biotests and biobioreporters in ecotoxicological risk assessment of field soils polluted with zinc, lead and cadmium. Environmental Toxicology and Chemistry, 2005, 24, 2973–2982. 31. P. Peltola, A. Ivask, M. Astrom, and M. Virta, Lead and Cu in contaminated urban soils: extraction with chemical reagents and bioluminescent bacteria and yeast. Science of the Total Environment, 2005, 350, 194–203. 32. H. Fritze, J. Perikom¨aki, T. Pet¨anen, T. Pennanen, M. Romantschuk, M. Karp, and K. Yrj¨al¨a, A microcosms study on the effects of Cd-containing wood ash on the coniferous humus fungal community and the Cd bioavailability. Journal of Soils and Sediments, 2001, 1, 146–150. 33. T. Pet¨anen and M. Romantschuk, Toxicity and bioavailability to bacteria of particle-associated arsenite and mercury. Chemosphere, 2003, 50, 409–413. 34. T. Pet¨anen and M. Romantschuk, Use of bioluminescent bacterial bioreporters as an alternative method for measuring heavy metals in soil extracts. Analytica Chimica Acta, 2002, 45, 55–61. 35. T. Pet¨anen, M. Virta, M. Karp, and M. Romantschuk, Construction and use of broad host range mercury and arsenite bioreporter plasmids in the soil bacterium Pseudomonas fluorescens OS8. Microbial Ecology, 2001, 41, 360–368. 36. H. C. Flynn, V. Mc Mahon, G. C. Diaz, C. S. Demergasso, P. Corbisier, A. A. Meharg, and G. I. Paton, Assessment of bioavailable arsenic and copper in soils and sediments from the Antofagasta region of northern Chile. Science of the Total Environment, 2002, 286, 51–59. 37. L. D. Rasmussen, S. J. Sorensen, R. R. Turner, and T. Barkay, Application of a mer-lux biobioreporter for estimating bioavailable mercury in soil. Soil Biology and Biochemistry, 2000, 32, 639–646. 38. R. Turpeinen, J. Salminen, and T. Kairesalo, Mobility and bioavailability of lead in contaminated boreal forest soil. Environmental Science and Technology, 2000, 34, 5152–5156. 39. A. Leedj¨arv, A. Ivask, M. Virta, and A. Kahru, Analysis of bioavailable phenols from natural samples by recombinant luminescent bacterial sensors. Chemosphere, 2006, 64, 1910–1919. 40. K. Hakkila, T. Green, P. Leskinen, A. Ivask, R. Marks, and M. Virta, Detection of bioavailable heavy metals in EILATox-oregon samples using whole-cell luminescent bacterial bioreporters in suspension or immobilized onto fibre-optic tips. Journal of Applied Toxicology, 2004, 24, 333–342.
41. S. M. Tauriainen, M. P. J. Virta, and M. T. Karp, Detecting bioavailable toxic metals and metalloids from natural water samples using luminescent bioreporter bacteria. Water Research, 2000, 34, 2661–2666. 42. A. Ivask, M. Virta, and A. Kahru, Construction and use of specific luminescent recombinant bacterial bioreporters for the assessment of bioavailable fraction of cadmium, zinc, mercury and chromium in the soil. Soil Biology and Biochemistry, 2002, 34, 1439–1447. 43. C. Chenu and G. Stotzky, Interactions Between Microorganisms and Soil Particles: An Overview , in Interactions Between Soil Particles and Microorganisms, P. M. Huang, J.-M. Bollag, and N. Senesi (eds), John Wiley & Sons, 2002, pp. 4–40. 44. G. M. Gadd, Microbial influence on metal mobility and application for bioremediation. Geoderma, 2004, 122, 109–119. 45. C. Rensing and R. M. Maier, Issues underlying use of biobioreporters to measure metal bioavailability. Ecotoxicology and Environmental Safety, 2003, 56, 140–147. 46. A. Keane, P. Phoenix, S. Ghoshal, and P. C. K. Lau, Exposing culprit organic pollutants: a review. Journal of Microbiological Methods, 2002, 49, 103–119. 47. A. A. Wise and C. R. Kuske, Generation of novel bacterial regulatory proteins that detect priority pollutant phenols. Applied and Environmental Microbiology, 2000, 66, 163–169. 48. B. M. Willardson, J. F. Wilkins, T. A. Rand, J. M. Schupp, K. K. Hill, P. Keim, and P. J. Jackson, Development and testing of a bacterial biobioreporter for toluene-based environmental contaminants. Applied and Environmental Microbiology, 1998, 64, 1006–1012. 49. R. J. Witorsch, Endocrine disruptors: Can biological effects and environmental risks be predicted? Regulatory Toxicology and Pharmacology, 2002, 36, 118–130. 50. E. J. Durhan, C. Lambright, V. Wilson, B. C. Butterworth, O. W. Kuehl, E. F. Orlando, L. J. Guillette Jr., L. E. Gray, and G. T. Ankley, Evaluation of androstenedione as an androgenic component of river water downstream of a pulp and paper mill effluent. Environmental Toxicology and Chemistry, 2002, 21, 1973–1976. 51. L. A. Kirk, C. R. Tyler, C. M. Lye, and J. P. Sumpter, Changes in estrogenic and androgenic activities at different stages of treatment in wastewater treatment works. Environmental Toxicology and Chemistry, 2002, 21, 972–979. 52. J. Legler, Determination of the Estrogenic Potency of Phyto-and Synthetic Estrogens Using in Vitro Bioassays, in Natural and Synthetic Estrogens Aspects of the Cellular and Molecular Activity, E., Dopp, H., Stopper, and G., Alink (eds), Transworld Research Network, Trivandrum, 2002. 53. E. Michelini, P. Leskinen, M. Virta, M. Karp, and A. Roda, A new recombinant cell-based bioluminescent assay for sensitive androgen-like compound detection. Biosensors and Bioelectronics, 2005, 20, 2261–2267. 54. P. Leskinen, E. Michelini, D. Picard, M. Karp, and M. Virta, Bioluminescent yeast assays for detecting estrogenic and androgenic activity in different matrices. Chemosphere, 2005, 61, 259–266.
12 Recombinant Aequorin-Based Systems for Biomarker Analysis Laura Rowe,1 Krystal Teasley,1 Emre Dikici,1 Xiaoge Qu,1 Mark Ensor,1 Sapna Deo2 and Sylvia Daunert1 1
Department of Chemistry, University of Kentucky, Lexington, KY, USA and 2 Department of Chemistry, Indiana University Purdue-University Indianapolis, Indianapolis, IN, USA
1 INTRODUCTION
Over the past 20 years significant efforts have been devoted to the characterization and development of bioluminescent proteins. Bioluminescent proteins are proteins that have been isolated from living organisms that naturally emit light via a biochemical reaction. Well-known examples of bioluminescence include the nocturnal flickering of fireflies and the glow of foxfire fungi. Although there are numerous terrestrial examples of bioluminescence, the sea is nature’s true incandescent stronghold, with over 80% of all marine organisms exhibiting some form of bioluminescence.1 The jellyfish Aequorea victoria is one such marine organism. A. victoria is the source of both the green fluorescent protein (GFP) and the protein that is the focus of this chapter, aequorin. Similar to the way our ancestors lit their way through dark and unknown territory using bioluminescent foxfire torches, researchers today use bioluminescent proteins, such as aequorin, to light their way through the largely unknown terrains that exist at cellular and molecular dimensions. Aequorin has been employed extensively in biomedical and chemical research. Specifically, it has been used to sense calcium in vivo, in single-cell analysis, and
as an ultrasensitive label for a variety of binding assays.2 In nature, aequorin serves as an excitation light source for A. victoria’s GFP. GFP emits fluorescent green light, which can be observed as green spots along the bell margin of the jellyfish.3 GFPs fluoresce after they have been electronically excited by aequorin’s blue (469 nm), bioluminescent light emission. Aequorin and GFP have both been prepared recombinantly, allowing for their separate use as labels.4,5 Aequorin is composed of apoaequorin, molecular oxygen, and the chromophore, coelenterazine (Figure 1). Apoaequorin is a globular, 189–amino acid, protein that is composed of 4 EF-hand domains (α-helix-loop-α-helix), 3 of which are calcium binding.6 Coelenterazine is a highly aromatic imidazopyrazinone, which serves as a chromophore in many bioluminescent marine organisms. Coelenterazine binds noncovalently to the hydrophobic core cavity of aequorin. Following the binding of calcium, aequorin undergoes a conformational change that causes the oxidation of coelenterazine to an excited coelenteramide and the production of CO2 (Figure 2). The high level of conjugation of coelenteramides allows radiative relaxation, and bioluminescence occurs with the emission of a blue photon.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS Bioluminescence of aequorin ‡
3Ca2+
−CO2 Aequorin
Light at 469 nm
Coelenterazine Apoaequorin + O2
Figure 1. Aequorin is composed of apoaequorin, molecular oxygen, and coelenterazine. Following calcium binding aequorin emits bioluminescent light at 469 nm.
OH O N
N
N H Aequorin Coelenterazine
Oxidized OH
OH ∗
O H N
O H N
N
N
Emission of light
N H
Relaxes to ground state
Coelenteramide
N H
Coelenteramide ∗
Figure 2. This figure shows the mechanism of aequorin’s bioluminescent light emission. Calcium binding causes a conformational change that leads to coelenterazine forming an excited coelenteramide. This reaction produces CO2 as a by-product, and bioluminescent light is released as this excited coelenteramide relaxes to its ground state.
Aequorin has been employed in a variety of detection techniques and has been especially popular as a label in immunoassays. In this regard, as an example of the breadth of assays that can be
developed with this photoprotein, we describe a series of aequorin-based immunoassays that are important in the detection and monitoring of cardiovascular disease (CVD) and hormonal disorders.
RECOMBINANT AEQUORIN-BASED SYSTEMS FOR BIOMARKER ANALYSIS
2 PROPERTIES AND APPLICATIONS OF AEQUORIN AS A LABEL
Historically, researchers have employed a large variety of label types in the development of customized assays. The first immunological assays employed radioactive isotopes as their label. Radiolabels are very sensitive reporters, but their radioactive nature makes them toxic to cells and difficult to dispose of. Fluorescent, chemiluminescent, and enzymatic labels have therefore replaced radiolabels in many applications. In addition to these substrates, luminescent proteins have also become popular labels in recent years because of their sensitivity and nontoxicity to cells. The lack of bioluminescent background noise in biological fluids allows bioluminescent labels to have a significantly lower detection limit than fluorescent labels. Aequorin can be detected with attomolar sensitivity, and this high sensitivity is important when detecting an analyte that is present at very low concentration and/or when analyzing minute sample volumes.7 Additionally, aequorin is active at physiological pH, does not photobleach, does not require an external excitation light source, and is amenable to genetic manipulation.8
2.1
Random Chemical Conjugation
There are two general labeling strategies utilized with aequorin when attaching an analyte to the photoprotein, namely, chemical conjugation and genetic fusion. Aequorin is chemically conjugated to an analyte by linking the analyte to an appropriately functionalized amino acid via a cross-linker. A cross-linker is defined as a molecule that is capable of covalently bonding two separate macromolecules. There are a wide variety of cross-linkers available commercially, but any cross-linker used with aequorin must function at the pH, polarity, and temperature range that will not compromise aequorin’s full bioluminescence activity. Two general chemical conjugation schemes are common when using aequorin. These involve the attachment of an analyte via an N-hydroxysuccinimidyl (NHS)-esterbased linker specific to the primary amine group of aequorin’s lysine residues and the attachment via a maleimide linker specific to the sulfhydryl group
3
of aequorin’s cysteine residues.9 The options available when selecting a conjugation strategy for aequorin, or any protein, in terms of amino acids and cross-linkers, are far too vast for the scope of this chapter. The reader is referred to the book Bioconjugate Techniques 9 for further information regarding chemical conjugation strategies.
2.2
Site-specific Chemical Conjugation
The aforementioned chemical conjugation techniques randomly conjugate the target analyte to all of the available amino acids containing the appropriate functional group. This random conjugation near the active site of a protein can perturb the protein’s structure dramatically. Such structural alterations can lead to significant losses in the activity and biorecognition capabilities of the protein. Therefore, an alternative conjugation method, site-specific conjugation, has been developed. Because site-specific conjugation methods involve the reaction of the analyte to just one chosen functional group on the protein, they overcome the problems that chemical conjugation presents. Therefore, site-specific conjugation methods are often preferred to such random conjugation strategies. Site-specific conjugation allows for the reaction between a functional group from just one amino acid on the protein and one molecule of analyte. This gives rise to only one conjugation product. Thus, site-specific conjugates are also preferred over multisite conjugates because of the increased homogeneity of the reaction products. The intrinsic nature of homogeneous conjugates makes them superior to those present in a heterogeneous mixture with regard to the reproducibility of their performance when employed in a variety of bioanalytical applications. Native aequorin contains 3 cysteine residues at positions 145, 152, and 180 in the protein structure. Inouye and colleagues found that the individual mutation of any of these three cysteine residues to serine residues resulted in a large activity loss.10 However, the simultaneous mutation of all three cysteine residues to serine residues resulted in a protein with increased activity and stability. In addition to being more stable and active, this mutant does not require the addition of a sulfhydryl-reducing reagent during assay development.
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
The addition of a single cysteine to this cysteinefree aequorin by site-directed mutagenesis then permits site-specific chemical conjugation. Our laboratory has developed several single-cysteine aequorin mutants using the cysteine-free aequorin as a template, with a single cysteine residue added at positions 5, 53, 69, 70, 71, 74, 76, and 84.11,12 Some of these mutants exhibited reduced activity when compared to the cysteine-free aequorin, while others retained over 80% of the original activity. The activity loss is postulated to be the result of altering the amino acids that are structurally close to the active center of aequorin. These single-cysteine aequorins have been employed in the development of several “artificial jellyfish”.12 Artificial jellyfish mimic aequorin’s natural function in A. victoria. Specifically, a fluorophore whose excitation spectrum overlaps the emission spectrum of aequorin is conjugated to a site near aequorin’s active center using the sulfhydryl group of a single cysteine residue. The bioluminescent energy released from aequorin can then be transferred to the fluorophore via a F¨orstertype energy transfer. Thus, the bioluminescence of aequorin serves as the fluorophore’s excitation light source, causing the fluorophore to then emit
its fluorescent signal at a different spectral location (Figure 3). In order to produce these artificial jellyfish, 2 different aequorin mutants with a single cysteine residue at positions 69 and 71, respectively, were conjugated to 2 different fluorophores, namely IANBD ester (λex = 478 nm, λem = 536 nm) and lucifer yellow (λex = 428 nm, λem = 531 nm) through their sulfhydryl group. The emission spectra of each of these four artificial jellyfish were then scanned with a spectrofluorometer following the incremental addition of a calciumcontaining buffer. All 4 artificial jellyfish showed evidence of resonance energy transfer, with the aequorin 69 conjugate with both IANBD ester and lucifer yellow, exhibiting a 30% energy transfer, and the aequorin 70 mutants with both IANBD ester and lucifer yellow exhibiting a 17% transfer of energy. The different transfer rates can be attributed to the different distances and orientations of the fluorophores with respect to the active center of aequorin. Applications of these artificial jellyfish include their use in the simultaneous multianalyte detection of biomolecules, drug targets, and environmental samples.
Energy transfer to a fluorescent probe ‡
Aequorin
Intermediate
Excited state Energy transfer
= Fluorophore = Calcium
Emission of fluorescence Figure 3. Following the addition of calcium, aequorin transfers its bioluminescent energy to the nearby fluorophore. The fluorophore is thereby excited, and subsequently emits its fluorescent signal at a spectral location different than that of the 469-nm aequorin emission peak.
RECOMBINANT AEQUORIN-BASED SYSTEMS FOR BIOMARKER ANALYSIS
2.3
Genetic Conjugation
A site-specific alternative to chemical conjugation is labeling by genetic methods. Genetically fused proteins are protein chimeras that contain both the target and the labeling protein. Fusion proteins are, by nature, site-specific and homogeneous, with the label being located either at the N- or C-terminus of the target protein.13 The general method for the production of genetically fused proteins involves the preparation of a plasmid where both proteins, target and label, are genetically encoded. This plasmid is then transformed into a suitable host organism (such as Escherichia coli ) and the fusion protein is expressed during bacterial growth. Following expression, the fusion protein needs to be purified by employing chromatographic methods and characterized in terms of its ability to be used as a label (Figure 4). The labeling ability of the fusion protein is assessed by monitoring the extent of the intrinsic activity change of the label following the addition of the target protein, as demonstrated by the activity of the newly created fusion protein. Fusion proteins have several advantages over chemically conjugated proteins. Besides being homogeneous, they also do not require time
5
consuming and costly organic reactions and purification steps, and once the initial genetic engineering is complete they are available in virtually limitless supply. A potential disadvantage of fusion proteins is the fact that both the target and the label must be proteins, and both proteins must have the ability to be actively expressed in a cell line. However, if the fusion protein has the potential to be used often and in large quantities, as in the clinical development of immunoassays and/or sensors, then genetic fusion is often the most efficient, reproducible, and cost-effective method of protein labeling. Aequorin fusion proteins in particular have been created for several purposes, including in vivo calcium sensing and assay development.
3 DETECTION OF DISEASE BIOMARKERS IN BIOLOGICAL FLUIDS
Biomarkers are quantifiable analytes that reflect a physiological state or change in the overall health, disease progression, or drug treatment status of an individual. The detection and quantitation of disease specific biomarkers can aid in the diagnosis and treatment of patients with such a disease before gross symptoms appear.14 Aequorin
Creating a fusion protein
Enz1
Analyte gene
+
Fuse genes for analyte and aequorin with PCR Cut with restriction enzymes (Enz1, Enz2 )
Enz1
Enz2
Analyte– aequorin
MCS
Vector plasmid
+
Aequorin gene
Ligate vector and fusion gene together Analyte–aequorin
Analyte–aequorin fusion protein Transform into E. coli Express and purify protein
Engineered plasmid
Figure 4. Overview of how to construct a fusion protein using molecular biology techniques.
Enz2
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
has been used as a label for both in vivo calcium detection and as a label in a variety of assay designs. One of the most relevant in vivo aequorin methods is the sensing of calcium fluctuations in relation to studying G-protein-coupled receptors (GPCRs). GPCRs are transmembrane receptor proteins that are pervasive throughout biological organisms and affect a diverse array of signaling pathways and physiological responses. Because of their role in so many pathological conditions, they are currently the target of 40–50% of modern medical drugs. Many GPCRs are calcium-coupled receptors whose activation results in an increased amount of intracellular calcium. Aequorin-based functional assays have been developed to screen the efficiency of various GPCR ligands and inhibitors. In these assays, aequorin is first stably expressed in cloned cell lines that contain the specific calcium-coupled GPCR to be studied. Various ligands and inhibitors of the calcium-coupled GPCR are then added to the cell cultures, and the resulting bioluminescence intensities within the cells indicate the efficacy of the various GPCR ligands and inhibitors.15 Aequorin has also been employed as a label in a number of different assay designs, including homogeneous and heterogeneous immunoassays, bioluminescence resonance energy transfer assays, and DNA hybridization assays. For example, Smith and colleagues pioneered the conjugation of aequorin with biotin and streptavidin and the development of several aequorin-based immunoassays.16 Christopoulous and colleagues expanded aequorin’s applications by developing aequorin-based DNA hybridization assays.17 In order to narrow the scope of this chapter, only aequorin-based assays detecting biomolecules relevant to both hormonal disorder and CVD will be discussed. The reader is referred to the book Photoproteins in Bioanalysis or a recent review article for a detailed discussion on all of aequorin’s applications.18 Most of aequorin-based assays detecting biomolecules relevant to hormonal disorders and CVD use a competitive heterogeneous immunoassay format. Aequorin-based heterogeneous immunoassays function by first conjugating, by either a chemical or a genetic method, aequorin to the analyte of interest.19 The second important component in this type of assays is the antibody,
which is specific to the target analyte. This antibody is immobilized on a solid surface, such as beads, microtiter plate wells, nanoparticles, membranes, polymers, filter paper, and so on. In such an assay, all the reagent components need to be allowed to react with the biological fluid of interest. When exposed to a biological sample, the aequorin–analyte conjugate competes with the native analyte present in a blood, urine, or saliva sample for a limited amount of immobilized antibody sites. Following a series of incubation and washing steps, all unbound analyte and aequorin–analyte conjugate are removed, leaving only the antibody–aequorin–analyte complex in the solid phase. Addition of a calcium buffer triggers the emission of bioluminescence from the aequorin–analyte conjugate. The amount of bioluminescence signal emitted is correlated to the concentration of aequorin–analyte present, which in turn is directly proportional to the concentration of native analyte in the solution (Figure 5a). Dose–response curves for the analyte can be constructed by plotting the bioluminescence signal observed against the concentration of the analyte (Figure 5b). Since the aequorin–analyte conjugate competes with the native analyte, the more of the native analyte present in a solution, the less of the bioluminescent light detected.
3.1
Detection of Hormones
Hormonal disorders result from either the underor the overabundance of certain hormones that are necessary for proper physiological functioning. Such disorders cause a significant decrease in the quality of life of a patient and can lead to death if left untreated.20 Aequorin-based assays capable of detecting physiologically relevant levels of cortisol and thyroxine, two hormones that are implicated in several disorders, have been reported. The advantages of these aequorin-based assays are that they have extremely low detection limits due to the lack of background bioluminescence and can be employed to analyze biological samples without any pretreatment or extraction of the sample. Also, these assays avoid problems associated with using radioisotopes, such as instability, health hazards, and waste disposal.18 Cortisol is a corticosteroid hormone that responds to stress by increasing blood sugar and blood
RECOMBINANT AEQUORIN-BASED SYSTEMS FOR BIOMARKER ANALYSIS
7
Heterogeneous immunoassay format
Light from aequorinlabeled analyte Add secondary Ab
Secondary Ab Primary Ab
Add triggering buffer
Add primary Ab
Analyte Labeled analyte Add analyte and labeled analyte
(a)
Typical dose–response curve 200
Signal
150 100 50 0 0
1
2
(b)
3
4
5
6
7
8
log(dose)
Figure 5. (a) Generic schematic of a competitive, heterogeneous immunoassay employing aequorin as a photolabel. (b) A generic sigmoid dose–response curve.
pressure levels and suppressing the immune system. Excessive levels of cortisol results in Cushing’s syndrome, while an insufficient amount causes Addison’s disease. Because of the circadian rhythms of hormonal secretion, the clinical assessment of these diseases requires multiple measurements of a patient’s cortisol levels over a 24-h period. Therefore, a noninvasive technique of sample collection, such as saliva sampling, is often the method of choice during the treatment of these diseases. The concentration of hormones in saliva has proved to accurately reflect the biologically active, non-protein-bound fraction
of cortisol in blood, which is the important fraction in the diagnosis of pathological conditions. However, hormone concentrations in saliva are 10–50 times lower than hormone concentrations in plasma, thus, requiring more sensitive detection methods. For example, physiological levels of cortisol in serum are 300–750 nmol l−1 , whereas cortisol levels in saliva are 10–25 nmol l−1 . In order to address this need for highly sensitive methods, Mirasoli and colleagues developed an aequorin-based immunoassay for the detection of cortisol levels in untreated human saliva samples.21
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
This assay employed secondary antibody (Ab)coated magnetic microspheres as the solid phase. Anticortisol antibodies were allowed to bind to these secondary Ab-coated microspheres. Then, cortisol and cortisol–aequorin were able to bind to these anticortisol-coated microspheres. Cortisol was chemically conjugated to the cysteine-free aequorin through the lysine residues in the protein molecule. This cortisol–aequorin conjugate then competed with native cortisol for the antibody sites microspheres. Separation of the solid phase from on the analyte and wash solutions was accomplished by applying a magnetic field to the microspheres and then removing the solution. This assay achieved a 3 × 10−9 M limit of detection for cortisol and a dynamic range of 3 orders of magnitude (Figure 6). The inter- and intra-assay precision was determined to be less than 15%, and the aequorin–cortisol conjugate was found to be stable for at least 6 months at 4 ◦ C. The sensitivity of this assay allows for the determination of Dose–response curve of cortisol
Bioluminescence intensity
200 150 100 50 0 −11 −10
−9
−8
−7
−6
−5
−4
log(cortisol, M)
Figure 6. Dose–response curve of the aequorin-based immunoassay for cortisol. As the cortisol concentration increases (x axis) the bioluminescence of aequorin decreases (y axis). Cortisol concentration levels that are physiologically relevant fall in the linear portion of the curve.
salivary cortisol concentrations utilizing the linear portion of the calibration curve, where error is the least. Moreover, the large dynamic range will also permit the analysis of serum samples. In order to test this assay’s effectiveness with real biological samples, saliva samples from 15 healthy subjects were analyzed. The analysis of these saliva samples demonstrated that the assay was acceptably accurate and sensitive for the determination of salivary cortisol (Table 1). This was the first study to employ aequorin for the determination of a small analyte in saliva samples. Moreover, unlike other commercially available cortisol assays, this aequorin-based assay did not require any pretreatment or extraction of the saliva samples prior to analysis. Pretreatment and extraction of biological samples is often a very time consuming process. The elimination of these steps, along with no external substrate addition, no need for an incubation period prior to measurement, and the faster immunological reaction kinetics afforded by the use of magnetic microspheres as a solid phase, allowed for the rapid detection of salivary cortisol from real human subjects. The speed, sensitivity, and simplicity of this assay make it amenable to automation and miniaturization, with a microfluidics-based point-of-care device for bedside cortisol analysis being foreseeable in the future. Another important hormone, which plays a major role in the proper functioning and metabolism of the human body, is thyroxine. Thyroxine is a hormone produced in the thyroid gland, which is involved in the regulation of metabolic pathways and in the growth process. Too much or too little thyroxine can cause a dangerously high or low metabolic rate, respectively. It is estimated that almost 10% of the US population has a thyroid abnormality of some kind. The acceptable physiological range of free thyroxine in serum
Table 1. Percent recovery data: known amounts of cortisol were added to the saliva pool and spiked samples were analyzed with the developed method. Values are the mean of three measurements
Percent recovery of cortisol in saliva −1
Cortisol (nmol l ) 6.0 60.0 600.0 6000.0 Mean
Observed value (nmol l−1 )
Expected value (nmol l−1 )
Mean recovery (%)
57.6 ± 1.2 103.2 ± 2.5 746.2 ± 6.1 6140.0 ± 17.2
54.0 108.0 648.0 6008.0
106.6 ± 2.2 95.6 ± 2.3 115.1 ± 1.0 101.5 ± 0.3 104.7 ± 1.5
Bias (%) 6.6 −4.4 −15.1 1.5 4.7
RECOMBINANT AEQUORIN-BASED SYSTEMS FOR BIOMARKER ANALYSIS
is 10.3–34.7 pmol l−1 , a level that requires highly sensitive detection methods. Many commercially available assays for free thyroxine in plasma require time-consuming and labor-intensive filtration and extraction steps. Given the importance of this hormone and the need for highly sensitive and relatively rapid assays, an aequorin-based immunoassay for thyroxine was developed in our laboratory. This assay was based on the use of modified aequorin mutants containing a unique single cysteine residue for the production of homogeneous, nonpeptide, conjugates.22 Homogeneous conjugates have been found to produce more sensitive and reproducible assays than heterogeneous conjugates. In order to create homogeneous aequorin conjugates, aequorin and the analyte of interest are usually genetically fused. However, genetic fusion limits the analytes to peptides that can be actively expressed in a bacterial host. Lewis and colleagues created genetically modified aequorin mutants containing single cysteine residues in order to expand the range of analytes amenable to homogeneous conjugation with aequorin to include nonpeptide analytes. Four different aequorin mutants were prepared that contained a single cysteine at either position 5, 53, 71, or 84. A maleimide derivative of thyroxine was site-specifically attached to each of these four aequorin mutants. The resulting one-to-one homogeneous conjugate was then used to develop a heterogeneous assay for thyroxine using a monoclonal antithyroxine Ab. This assay demonstrated a detection limit for thyroxine of 10−14 M and a dynamic range of 6 orders of magnitude, which is within the levels of the hormone in physiological fluids. In addition, the aequorin-71–thyroxine conjugate exhibited a homogeneous response following incubation with varying concentrations of the antithyroxine monoclonal antibody, suggesting that a homogeneous immunoassay could be developed using this conjugation protocol. This thyroxine assay represents the first time that aequorin had been genetically modified and then site-specifically conjugated to a nonpeptide analyte for the development of an immunoassay, thus serving as a model for the development of homogeneous nonpeptide conjugates using aequorin. Additionally, this homogeneous thyroxine–aequorin conjugate assay exhibited analytical performance that was superior to previously
9
reported thyroxine assays, yielding a detection limit that was 1000-fold more sensitive. The advantages of this aequorin-based thyroxine assay include increased sensitivity, simplicity, and speed and the potential for future automation and miniaturization. 3.2
Detection of Cardiovascular Disease – related Analytes
CVD is the most common cause of death in the world, with approximately 16.7 million human fatalities being attributed to CVD annually. Currently, it is practically impossible for physicians to predict the future occurrence of a heart attack or a stroke. Because of the severity of this issue, recent cardiovascular research has focused on the identification and quantification of cardiovascular biomarkers, be that a specific single biomarker or the fluctuation of several proteins and hormones that are related to cardiovascular health. The goal of this research is both to better understand the progress of CVD from a molecular level and to ideally identify a set of biomarkers that can be used to predict, and therefore prevent, future heart attacks and strokes in CVD patients.23 To that end, cardiovascular disease–related assays for analytes such as 6-keto-prostaglandin-F1-alpha (6-keto-PGF1α), protein C, and digoxin have recently been developed using aequorin. Prostacyclin is an eicosanoid that is important for vasodilation, platelet inhibition, and antiproliferative and fibronolytic activities. It has a significant role in the treatment of primary pulmonary hypertension (PPH). The exact dose needed for an individual patient’s effective PPH treatment is unknown, so a 4–20 ng kg−1 min−1 dose of prostacyclin in administered to all patients being treated for PPH. This dosage may be excessive for specific individuals, and uncomfortable side effects are caused by prostacyclin overdosing during PPH treatment. A rapid and effective method for detecting a patient’s free plasma prostacyclin level is therefore needed in order to determine the optimal prostacyclin dose required for the treatment of an individual patient that will lead to a functional improvement in the patient’s pathophysiology without causing untoward side effects. To that end, we developed a rapid and effective aequorin-based assay for 6-keto-PGF1α. Prostacyclin itself is very unstable, having a half-life of less
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
than 3 min in a buffer solution. The stable product of prostacyclin’s metabolic hydrolysis, 6-ketoPGF1α, is therefore the analyte measured when monitoring the levels of prostacyclin in patients (Figure 7). Our laboratory developed the assay for 6-ketoPGF1α using a cysteine-free aequorin mutant that was chemically conjugated to 6-keto-PGF1α through aequorin’s lysine residues.24 This assay gave a 2 × 10−12 M detection limit for 6-ketoPGF1α and a working range that spanned 3 orders of magnitude. Inter- and intra-assay precision had coefficients of variation (CV) of less than 5%, and the low cross-reactivities observed indicated that this assay was specific for the detection of 6-keto-PGF1α in physiological samples. To demonstrate the applicability of this bioluminescent immunoassay in clinical analysis, dose–response curves were generated using 6-keto-PGF1α in either a buffer solution or an untreated serum solution. These two dose–response curves were almost identical, indicating the lack or minimal matrix effects affecting the assay. A percent recovery study of real samples from patients suffering from PPH showed that the assay produced accuracy between 7 and 17%. Moreover, the assay detected 6-keto-PGF1α concentrations in untreated plasma samples that correlated well with 6-keto-PGF1α concentrations detected in extracted and pretreated plasma samples. Alternative, commercially available methods for detecting 6-keto-PGF1α include radio and enzyme immunoassays, GC/MS, and GC/SIM. However, all these methods are relatively slow because they require the extraction of 6-keto-PGF1α from biological samples. This aequorin-based assay is the first direct assaying technique for 6-keto-PGF1α
reported that does not require such extraction. For this reason, this acceptably sensitive, single-step assay is much faster than previously developed detection methods for 6-keto-PGF1α in plasma. Furthermore, the simplicity of this assay could allow for the high-throughput analysis of prostacyclin plasma levels in patients with PPH, leading to a more thorough understanding of the pathophysiology of PPH.21 Two additional aequorin-based assays that find applications in CVD management and diagnosis are those developed for digoxin and protein C. Protein C is a 62-kDa, vitamin K–dependent plasma zymogen that serves as an anticoagulant in blood. A deficiency in protein C will lead to thrombosis, and protein C levels need to be monitored when either fatal neonatal or familial venous thrombosis is suspected. The healthy physiological range of protein C in human plasma is approximately 65 nM, and those who are protein C deficient have levels ranging from 26–39 nM. The importance of protein C and the need for methods that would be capable of detecting this protein in a faster and simpler manner than the existing methods prompted Desai and colleagues to develop an assay for protein C using the HPC4 epitope of protein C.25 An epitope is a small molecular region on an antigen’s surface that triggers the antibodyrecognition and immune response in an organism.26 The rationale behind employing the epitope of an analyte instead of the entire sequence of an analyte lies in the difficulty, and at times impossibility, of expressing homogeneous conjugates of large, multidomain proteins in bacterial systems. As previously discussed, homogeneous conjugates, which are often produced using genetic fusion methods, are preferred over heterogeneous
COOH
COOH Hydrolysis
O
O
CH3 OH
OH
Prostacyclin
CH3 OH OH 6-keto-Prostaglandin-F-1a
Figure 7. The unstable prostacyclin undergoes hydrolysis to form the stable 6-keto-PGF1α. 6-keto-PGF1α is stable for over 10 h in plasma and is therefore the accepted surrogate marker for prostacyclin levels in plasma.
RECOMBINANT AEQUORIN-BASED SYSTEMS FOR BIOMARKER ANALYSIS
conjugates because they produce more sensitive and reproducible assays. However, a difficulty in expressing large, multidomain proteins, such as protein C, in bacterial systems arises from the fact that these types of proteins degrade quickly and generally require posttranslational modifications that the bacterial system is incapable of accommodating. In an effort to overcome this difficulty, researchers have started employing epitopes that bind to the monoclonal antibodies of these large, multidomain proteins in genetic fusions. In our laboratory, HPC4 epitope, which is a binding region of protein C, was genetically fused to the N-terminus of a cysteine-free aequorin. This HPC4–aequorin fusion protein was then employed in the development of a heterogeneous immunoassay for protein C. This assay resulted in a detection limit of 4 × 10−10 M and a dynamic range of 6 orders of magnitude, which will allow for the use of this assay in clinical diagnostics. Additionally, protein C was serially spiked into protein C–free human plasma and the resulting dose–response curve was almost identical to the dose–response curve generated from a buffer solution spiked with protein C. This indicates that the plasma matrix effects were minimal and that this assay can be used for real-sample analysis in the future. This was the first study demonstrating that aequorin can be genetically conjugated to an epitope of a large, multidomain protein and that such a conjugate can be successfully employed in the development of an assay for the detection of the whole protein in biological samples. Additionally, this protein C assay serves as a model for a general methodology for developing assays for large, multidomain proteins using epitope–aequorin homogeneous conjugates. Finally, a heterogeneous assay for digoxin was developed by chemically conjugating digoxin to the lysine residues of a cysteine-free aequorin mutant.27 Digoxin is a cardiac glycoside that is used in the treatment of congestive heart failure. Digoxin has a very narrow therapeutic range (0.8–2.0 ng ml−1 ) and the potential for fatal toxicity if overdosed. Therefore, during treatment a patient requires therapeutic drug monitoring, where the concentration of digoxin is periodically monitored. For this reason, digoxin assays must be extremely sensitive, rapid, and selective. Several immunoassays for digoxin are commercially available, most of which employ enzymatic
11
substrates for labels. However, these enzymatic assays require the time-consuming extraction of digoxin from the biological sample. This aequorinbased assay did not require any pretreatment or extraction of biological samples prior to assaying, thereby making it much faster than other commercially available assays. The detection limit of this assay was 3 × 10−10 M and had a working range of 4 orders of magnitude, a range that is well suited to detecting digoxin levels within the therapeutic window. This assay was also acceptably reproducible, precise, and specific toward digoxin. In order to demonstrate this assay’s compatibility with untreated biological samples, human serum samples were spiked with digoxin and a percent recovery study was undertaken. The percent recovery data showed a CV of less that 17%, indicating that this assay has the potential to accurately analyze human serum samples. This work demonstrates how aequorin can be used with real samples for the detection of analytes that require sensitive detection and therapeutic drug monitoring. Moreover, the fact that this aequorin-based digoxin assay did not require any pretreatment or extraction of biological samples suggests that this assay will be amenable to automation and pointof-care diagnostics. The five aforementioned assays are important in that each of them not only demonstrated value in contributing to CVD management and diagnosis but they have also demonstrated the broader use of aequorin in the development of new bioanalytical methods of analysis that can overcome existing drawbacks (Table 2). In this regard, it is noteworthy to restate that these are by no means the only aequorin-based assays reported in the literature. Many others have been developed for analytes not specifically related to cardiovascular or hormonal disorders, such as assays for biotin, amplified cytokine products, tumor necrosis factor-α, protein A, Forssman antigen, prostate-specific antigen RNA, HIV-1 protease, and Salmonella antigen.28–35 A comprehensive review describing the more specific biological nature of aequorin, its properties, commercial sources, and applications in bioanalysis has been recently published, and we refer interested readers to the book Photoproteins in Bioanalysis for further information on both aequorin and the other photoproteins.36
12
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Table 2. Table summarizing the important analytical parameters of the aequorin-based immunoassays for CVD-related analytes and hormones
Analytical performance of aequorin-based assays Analyte 6-keto-PGF1α Cortisol Thyroxine Protein C
Sample type/ pretreated
Analyte’s physiological range (M)
Assay’s dynamic range (M)
Assay’s detection limit (M)
Plasma/no Saliva/no
2.0 × 10−9 − 2.0 × 10−7 1.0 − 2.5 × 10−8 1.0 − 3.5 × 10−11 Approx. 6.5 × 10−8
10−12 − 10−8 10−8 − 10−6 10−12 − 10−7 10−13 − 10−7
2.0 × 10−12 3.0 × 10−12 5.0 × 10−12 4.0 × 10−10
Plasma/no
4 INCORPORATING AEQUORIN-BASED ASSAYS INTO DEVICES
Important analytical research areas include miniaturization, multianalyte detection, and point-ofcare analysis. Many researchers have in mind an ideal future sensing device when pursuing these areas of research. The ideal device is a handheld or benchtop instrument that is capable of quantifying a wide variety of disease biomarkers from a few microliters of sample within a time frame of seconds to minutes. Such an instrument would allow the facile and almost immediate diagnosis of many health conditions. However, the research areas critical to such an ideal sensing device host a number of challenges. Miniaturization, for example, requires the use of very small sample volumes. Such minute sample volumes create difficulties from both engineering and labeling perspectives. Efficient mass transport and reproducible volumes are two of the engineering hurdles. In an attempt to overcome these challenges significant advances have recently been made in microfluidics technology, such as electrokinetic and centrifugal flow and pumping methods. These methods are being utilized to create miniaturized “lab-on-a-chip” and “lab-on-a-CD” detection platforms (Figure 8).37 Often in these miniaturized systems, analytes must be labeled for quantitation, and the small sample volume requires a label with extremely low detection limits. Bioluminescent labels, such as aequorin, can be an appropriate label when miniaturizing an immunoassay because of their inherent sensitivity and compatibility with biological fluids. Aequorin has been used as a label for a DNA hybridization assay located on such a miniaturized compact disc platform. In this compact disc platform, centrifugal force was used
Figure 8. A “lab-on-a-chip” from Agilent Technologies (http://www.chem.agilent.com/cag/feature/10-00/feature graph ics/04 ProteinLabChip.jpg) and a “lab- on-a-CD” from our laboratory in collaboration with Dr Marc Madou at U.C., Irvine that utilizes centrifugal force for pumping and mixing.
to manipulate the samples and reagents through a network of microreservoirs and microchannels within polydimethylsiloxane (PDMS), which had been created using lithography and master molding techniques.38 DNA capture probes were immobilized onto the PDMS using patterned gold pads, and the complementary DNA target was labeled with aequorin using biotin–streptavidin affinity binding. The labeled DNA target competed with the unlabeled DNA target for the immobilized DNA probes, and the hybridization dose–response curve exhibited sensitivity to concentrations as low as 1 pM. Multianalyte detection requires labels that can be easily discriminated from one another. The artificial jellyfish described in the previous section also demonstrates how aequorin can be used for multianalyte detection. These artificial jellyfish utilized the light from a conjugated fluorophore to produce different signals. Combining several different types of photolabels whose signals can be individually activated or detected is another method of multianalyte detection. For example, a dual-analyte heterogeneous assay was
RECOMBINANT AEQUORIN-BASED SYSTEMS FOR BIOMARKER ANALYSIS
developed using both aequorin and acridinium-9carboxamide as labels.39 Aequorin was conjugated to biotin, and acridinium was conjugated to myoglobin. These conjugates competed with biotinylated bovine serum albumin (BSA) and myoglobin for immobilized avidin and antimyoglobin Ab sites located in a single well. The aequorin signal occurred following the addition of calcium and ended within 10 s. At the 10-s point a basic peroxidase solution was injected into the well to trigger the luminescence of the acridinium, whose signal was collected from 10–20 s. Using this method, a dual-luminescence assay for biotinylated BSA and myoglobin was successfully developed.
13
in vitro sensing systems, detection devices, and as reporters in intracellular imaging. Aequorin is the most thoroughly studied bioluminescent photoprotein, with a variety of aequorin-based assays and sensing techniques currently available. However, there is still a great deal to learn about aequorin, as well as the other bioluminescent proteins. An increased knowledge of aequorin will lead to the production of superior labels, which will facilitate advancement in several fields of research, and will hopefully lead to the development of more ideal biosensing systems.
ACKNOWLEDGMENTS 5 FUTURE PERSPECTIVES AND CONCLUSION
Miniaturized analysis systems and point-of-care diagnostics will require very robust and ultrasensitive labels. Bioluminescent proteins represent one viable alternative for such a label in terms of sensitivity. However, there is a definite need to improve the robustness of aequorin. Increasing the stability and activity of aequorin under a plethora of nonoptimal environmental conditions will create a greater acceptance of this photoprotein in mainstream and industrial research. In addition to increasing the robustness of aequorin, there is a need to create a repertoire of spectrally diverse aequorin variants that will allow for aequorin-based multianalyte detection and imaging. Aequorin-based multianalyte detection and imaging will simultaneously require more sensitive and advanced luminescence detectors.40 For example, luminescent multianalyte experiments will need luminometers capable of detecting a wide range of wavelengths combined with chemometrics programs that can analyze and filter spectral overlap. Aequorin-based imaging will require highly sensitive detectors that, ideally, can also discriminate spectral variety. Electron-multiplying charge-coupled device (EMCCD) cameras represent a recent optical technology that could potentially become useful in both aequorin-based multianalyte detection and imaging.41 Multicolored, robust aequorin mutants have the potential to be employed in a variety of methods in the future, such as in situ, in vivo, and
This work was funded by the National Institutes of Health (NIH), the National Institute of Environmental Health Sciences (NIEHS), the National Science Foundation (NSF), and the National Aeronautics and Space Administration (NASA).
REFERENCES 1. O. Shimomura, Bioluminescence in the sea: photoprotein systems. Symposia of the Society for Experimental Biology, 1985, 39, 351–372. 2. J. Lewis and S. Daunert, Photoproteins as luminescent labels in binding assays. Fresenius Journal of Analytical Chemistry, 2000, 366, 760–769. 3. H. Morise, O. Shimomura, F. Johnson, and J. Winant, Intermolecular energy transfer in the bioluminescent system of aequorea. Biochemistry, 1974, 13(12), 2656–2662. 4. S. Inouye, M. Noguchi, Y. Sakaki, Y. Takagi, T. Miyata, I. Sadaaki, T. Miyata, and F. Tsuji, Cloning and sequence analysis of cDNA for the luminescent protein aequorin. Proceedings of the National Academy of Sciences of the United States of America, 1985, 82, 3154–3158. 5. W. Miller and S. Lindow, An improved GFP cloning cassette designed for prokaryotic transcriptional fusions. Gene, 1997, 191(2), 149–153. 6. J. Head, S. Inouye, K. Teranishi, and O. Shimomura, The ˚ crystal structure of the photoprotein aequorin at 2.3 A resolution. Nature, 2000, 405, 372–376. 7. O. Shimomura, A short story of aequorin. Biological Bulletin, 1995, 189(1), 1–5. 8. J. Lewis and S. Daunert, Photoproteins as luminescent labels in binding assays. Fresenius Journal of Analytical Chemistry, 2000, 366, 760–769. 9. G. Hermanson, Bioconjugate Techniques, Academic Press, San Diego, 1996. 10. F. Tsuji, S. Inouye, T. Goto, and Y. Sakaki, SiteDirected mutagenesis of the calcium binding photoprotein aequorin. Proceedings of the National Academy of
14
11.
12.
13. 14.
15.
16.
17.
18.
19. 20.
21.
22.
23.
24.
25.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS Sciences of the United States of America, 1987, 83, 8107–8111. J. Lewis, C. Cullen, and S. Daunert, Site-Specifically labeled photoprotein-Thyroxine conjugates using aequorin mutants containing unique cysteine residues: applications for binding assays. Bioconjugate Chemistry, 2000, 11, 140–145. S. Deo, M. Mirasoli, and S. Daunert, Bioluminescence resonance energy transfer from aequorin to a fluorophore: an artificial jellyfish for applications in multianalyte detection. Analytical and Bioanalytical Chemistry, 2005, 381, 1387–1394. A. Doerr, Teaching cell biologists how to count. Nature Methods, 2005, 2(12), 892–893. A. K. Trull, L. M. Demers, D. W. Holt, A. Johnston, J. M. Tredger, and C. P. Price, Biomarkers of Disease: An Evidence Based Approach, Cambridge University Press, Cambridge, 2002. D. New and D. Y. Wong, Chimeric and promiscuous G proteins in drug discovery and the deorphanization of GPCRs. Drug Design Reviews, 2005, 2, 66–79. H. R. Rivera, M. T. Patel, N. L. Stults, D. F. Smith, and C. T. Rigl, A single-addition bioluminescent immunoassay for HCG that features recombinant aequorin as a dried reagent. Bioluminescence and Chemiluminescence:Fundamentals and Applied Aspects, Proceedings of the 8th International Symposium on Bioluminescence and Chemiluminescence, Cambridge, Sept. 5–8, 1994, pp. 349–352. B. Galvan and T. Christopoulous, Bioluminescence hybridization assays using recombinant aequorin. Analytical Chemistry, 1996, 68, 3545–3550. J. Lewis and S. Daunert, Photoproteins as luminescent labels in binding assays. Fresenius Journal of Analytical Chemistry, 2000, 366, 760–769. E. Diamandis and T. Christopoulous, Immunoassay, Academic Press, San Diego, 1996. G. Tortora and S. Grabowski, Principles of Anatomy and Physiology, Harper Collins College Publishers, Menlo Park, 1996. M. Mirasoli, S. Deo, J. Lewis, A. Roda, and S. Daunert, Bioluminescence immunoassay for cortisol using recombinant aequorin as a label. Analytical Biochemistry, 2002, 306, 204–211. J. Lewis and S. Daunert, Bioluminescence immunoassay for thyroxine employing genetically engineered mutant aequorins containing unique cysteine residues. Analytical Chemistry, 2001, 73, 3227–3233. G. Tortora and S. Grabowski, Principles of Anatomy and Physiology, Harper Collins College Publishers, Menlo Park, CA, 1996. U. Desai, S. Deo, K. Hyland, M. Poon, and S. Daunert, Determination of prostacyclin in plasma through a bioluminescent immunoassay for 6-keto-prostaglandin F1α: implication of dosage in patients with primary pulmonary hypertension. Analytical Chemistry, 2002, 74, 3892–3898. U. Desai, J. Winiger, J. Lewis, S. Ramanthan, and S. Daunert, Using epitope-Aequorin conjugate recognition in immunoassays for complex proteins. Analytical Biochemistry, 2001, 294, 132–140.
26. S. Stevanovic, Antigen processing is predictable: from genes to T cell epitopes. Transplant Immunology, 2005, 14(3–4), 171–174. 27. S. Shrestha, I. Paeng, S. Deo, and S. Daunert, Cysteine-Free mutant of aequorin as a photolabel in immunoassay development. Bioconjugate Chemistry, 2002, 13, 269–275. 28. L. Xiao, C. Yang, C. O. Nelson, B. P. Holloway, V. Udhayakumar, and A. A. Lal, Quantitation of RT-PCR amplified cytokine mRNA by aequorin-Based bioluminescence immunoassay. Journal of Immunological Methods, 1996, 199(2), 139–147. 29. T. Erikaku, S. Zenno, and S. Inouye, Bioluminescent immunoassay using a monomeric fab’-Photoprotein aequorin conjugate. Biochemical and Biophysical Research Communications, 1991, 174(3), 1331–1336. 30. S. Zenno and S. Inouye, Bioluminescent immunoassay using a fusion protein of protein A and the photoprotein aequorin. Biochemical and Biophysical Research Communications, 1990, 171(1), 169–174. 31. N. L. Stults, N. F. Stocks, H. Rivera, J. Gray, R. O. McCann, D. O’Kane, R. D. Cummings, M. J. Cormier, and D. F. Smith, Use of recombinant biotinylated aequorin in microtiter and membranebased assays: purification of recombinant apoaequorin from Escherichia coli. Biochemistry, 1992, 31(5), 1433–1442. 32. B. Galvan and T. Christopoulous, Bioluminescence hybridization assays using recombinant aequorin. Application to the detection of prostate-specific antigen mRNA. Analytical Chemistry, 1996, 68(20), 3545–3550. 33. S. Deo, J. Lewis, and S. Daunert, Bioluminescence detection of proteolytic bond cleavage by using recombinant aequorin. Analytical Biochemistry, 2001, 281(1), 87–94. 34. J. Wang, M. Ensor, G. Dubuc, S. Narang, and S. Daunert, Genetically fused single-chain anti-Salmonella antibody with aequorin: a bioluminescence immunoassay for a salmonella antigen. Analytica Chimica Acta, 2001, 435(2), 255–263. 35. A. Gorokhovatsky, Homogeneous assay for biotin based on aequorea victoria bioluminescence resonance energy transfer system. Analytical Biochemistry, 2003, 13(1), 68–75. 36. S. Daunert and S. Deo, Photoproteins in Bioanalysis, Wiley-VCH, 2006. 37. M. Madou, Fundamentals of Microfabrication: the Science of Miniaturization, 2nd Edn, CRC Press, 2002. 38. G. Jia, K.-S. Ma, J. Kim, J. V. Zoval, M. J. Madou, S. K. Deo, S. Daunert, R. Peytavi, and M. G. Bergeron, CD (compact disc)-based DNA hybridization and detection. SPIE Proceedings, 2004, 5455(341), 341–353. 39. M. Adamczyk, J. Moore, and K. Shreder, Dual analyte detection using tandem flash luminescence. Bioorganic and Medicinal Chemistry Letters, 2005, 12, 395–398. 40. D. Welsh and S. Kay, Bioluminescence imaging in living organisms. Current Opinion in Biotechnology, 2005, 16, 73–78. 41. O. Bernard and C. Coates, Electron multiplying charge coupled devices remove low light barriers. Laser Focus World, 2005, 41, 133–134.
13 Yeast-Based Biosensors and Their Incorporation of Mammalian Protein Receptors for High-Throughput Screening John B. C. Findlay, Lisa Tang and Graham Whyteside Institute of Membrane and Systems Biology, University of Leeds, Leeds, UK
1 MICROORGANISMS AS BIOSENSORS 1.1
G-protein Coupled Receptors (GPCR): A Yeast-based Biosensor Paradigm
Biosensors, in the simplest sense, are devices that harness a biological entity to record and report on changes, including physiological, environmental, and biochemical stimuli. The biological entities that have been employed so far include enzymes, antibodies, DNA, receptors, organelles, and microorganisms as well as some plant and animal tissues. This plethora of biological detectors has been recruited to detect a diverse range of molecules ranging in complexity from relatively simple, chemical compounds through nucleic acids, proteins (e.g., antigens and hormones) to whole organisms.1,2 The wide range of materials that can be used to make a device, the wide range of components that can be detected, and the tight specificity that can be obtained are advantages of using biological detectors over more traditional approaches. Other advantages include their sensitivity, portability, simplicity of operation, real-time analysis, and ability to work even in opaque solutions. However, there are disadvantages—the detector can lack robustness and be liable to poisoning, the association of the detector with the reporting system can be
technically demanding, stability and life times can be limiting, and their very sensitivity can make them prone to variability and environmental influence.
1.2
The Systems
By far, the most common form of biological moiety incorporated into biosensors are purified enzymes due to their catalytic amplification and high analytical specificity. However, there are major drawbacks to using purified enzymes in that they can be expensive to acquire, prone to poisoning, and sensitive to the environment. The manufacture of biosensors incorporating purified enzyme can also be inefficient and technically demanding. One solution to these problems that is gaining popularity is the use of whole cells. Microorganisms have many advantages; for example, they are easy and cheap to culture, they are abundant and robust, they can metabolize a large number of diverse compounds, they can adapt to new compounds and molecules over time, and they can be easily stored and manipulated (genetically and biochemically). In addition to the above assets, whole cells can be used for single enzymatic reactions and as multipurpose catalysts where a whole
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
sequence of reactions is required. Therefore, it is no surprise to find that whole cells are becoming an increasingly popular choice. Whole cells can be utilized in either a viable or a nonviable state, depending on the biosensors’ requirements. At present, nonviable cells predominate but the use of viable cells is predicted to become more prevalent. 1.3
Viable Cells
Viable cells have the ability to metabolize a number of compounds and molecules either anaerobically or aerobically. The result of this metabolism is a series of end products such as ammonia, carbon dioxide, and acids, which can then be monitored and quantified. The most common type of biosensors uses the measurement of respiratory activity as a measure of substrate concentration. Examples of this approach include the measurement of biological oxygen demand and the utilization of growth or metabolically related nutrients like vitamins, sugars, organic acids, and nitrogenous compounds.3 In addition to these applications, biosensors based on viable cells have been used as environmental monitors. These devices make use of the inhibition of the respiratory chain as a measure of the levels of environmental pollutants. Growth characteristics can also give indications of mutational effects and toxicity.4 The main disadvantages are the slow rate of diffusion through cell walls and membranes and a slow response rate compared to biosensors incorporating purified enzymes.5 1.4
Nonviable Cells
Nonviable cells, normally permeabilized, are the most common form of whole cell that is integrated into a biosensor. Permeabilization can be obtained in a number of ways, for example, freezethawing, chemical or detergent treatment, or most commonly with organic solvents such as toluene, chloroform, ethanol, or butane.6–8 These treatments cause minute pores to be formed in the cell membrane by removing some of the lipids, thereby allowing faster diffusion times and subsequently quicker reaction times. The pores created by such treatments are large enough to allow diffusion of the substrate of interest but small
enough to maintain the macromolecular structures, like enzymes, within the cell. This is becoming a popular method as it is more economical than purifying enzymes.9 A distinct advantage of this method is that due to permeabilization, the cell is emptied of most of its cofactors, and there is a consequent reduction in the amount of unwanted side reactions that can take place. For example, the use of β-galactosidase as a detection method requires the production of galactose from lactose; in whole yeast cells lactose is metabolized in to ethanol and carbon dioxide, whereas in permeabilized cells glucose and galactose are produced, allowing β-galactosidase to operate.10,11 In a similar vein, unwanted transport processes of the cell are also reduced, thereby resolving problems with substrate localization and subsequent metabolism. Once again, however, the disadvantages of using this system is that its detection time is slow compared to biosensors containing purified enzymes.
1.5
Use of Yeast as Biosensor Material
Most cell-based biosensors have focused on bacterial cells but recently there has been an increased use of yeast. This can be attributed in part to the relative fragility of bacterial systems with poor pH, osmotic and temperature tolerances leading to limited operating parameters, and short shelf lives. Also prokaryotic metabolism can react differently to that of eukaryotes making toxicity and drug screening data unrepresentative of higher organisms. As yeast are eukaryotic, this poses less of a problem and examples of highly accurate yeast toxicity assays are described below.12,13 Another advantage of using yeast is their superior physical robustness as they show far greater tolerance to pH, osmotic/ionic, and temperature variations. This is exemplified by the preparation of baker’s yeast, which is dried in air at 28–40 ◦ C, to a moisture content of between 7.5 and 8.3%. These cells have a shelf life of over a year during which they will only lose about 10% of their activity.14 These advantages plus elucidation of the genome sequence of Saccharomyces cerevisiae, coupled to the pliability of yeast genomes, ease of growth, and lack of pathogenicity makes yeast an attractive option for biosensor application. There are about
YEAST-BASED BIOSENSORS FOR HIGH-THROUGHPUT SCREENING
1000 yeast strains identified so far. This added to the expectation of many more yet-to-be discovered strains illustrates the scope for variety, which will underpin its attractiveness as a vehicle for biosensor development. 2 EXAMPLES OF YEAST BIOSENSORS 2.1
Wild-type Yeasts
Yeasts occupy a wide variety of niches and therefore demonstrate considerable metabolic diversity, the substrates varying from sugars to nitrogenous and aromatic compounds.15 As early as 1979, Trichosporon cutaneum was being used in a biosensor for measuring biochemical oxygen demand (BOD).16 Subsequently, this technology was expanded to include the BOD of starch, cellulose, and milk powder.17 In addition, two species of Candida isolated from wood pulp mill effluent have been used to detect the BOD of the waste stream.18 More recently, a range of yeast-based systems have been developed that allow for the detection of or discrimination between specific molecules, particularly common catabolic substrates like ethanol and glucose. However, viable wild-type yeasts can encounter interference from other substrates creating a problem with specificity. For example, Hansenula anomala and S. cerevisiae, yeast biosensors developed for the detection of glucose based on lowering of pH were susceptible to interference from the likes of mannose, fructose, and maltose.19,20 The problem is not restricted to glucose. A system using the physcotropic yeast, Yarrowia lipolytica, isolated from alpine land contaminated with diesel oil, which was developed to detect middle-chain alkanes, also responded well to diesel oil and catechol as well as the middlechain alkanes dodecane, undecane, and decane.21 Despite these problems, there have been yeastbased biosensors that are sensitive, specific, and successful. In 1987, a biosensor able to detect lactate in blood samples was constructed using H. anomala. The specificity was achieved by adding sodium fluoride, which blocked the cellular response to glucose, whereas reaction to other blood constituents was minimal.22 In 1992, a biosensor was developed using the same strain that was able to detect 100% of lactate present in the
3
blood sample with no interference from glucose, glycerol, and ascorbic acid.23 In 2001, a combination of the bacteria Gluconobacter oxydans and the yeast Pischia methanolica was used to discriminate between mixtures of ethanol and glucose ranging from 1 to 8 mM.24 As yeast are eukaryotic organisms, they appear more suitable than bacteria for use in toxicity assays. S. cerevisiae has been employed to measure the toxicity of the antifungal agent nystatin as well as of conjugated cholanic acids.25,26 The former was based on a decrease of catabolism, which was dependent on the concentration of the agent present. The latter was so reliable that a toxicity scale could be constructed. Another four S. cerevisiae biosensors have also been developed as general toxicity monitors, the decrease in metabolic activity being the measurement of toxicity.27,28
2.2
Genetically Modified Yeast Strains
Due to the strength of yeast genetics, the usefulness of this organism for biosensor development is increasing. The model organism is S. cerevisiae, which has been used as a model eukaryote in a number of toxicity and genotoxicity assays where they can detect either specific molecules or groups of molecules in, for example, environmental samples. One such sensor makes use of the DNA repair promoter RAD54 of S. cerevisiae coupled to EGFP to detect DNA damage by analytes. RAD54 is activated only by DNA damage and not by anything that interferes with mitosis. Therefore, when the cell encounters a chemical that causes DNA damage, RAD54 will be activated and will subsequently cause the cell to make EGFP, which can then be detected. This biosensor is now available commercially.28,29 Further modification of these cells by expression of human cytochrome P450 allows this biosensor to give a more accurate simulation of human responses to any agents other than bacterial tests.30,31 In addition, it has been shown that biosensors incorporating firefly luciferase which detect toxic or metabolism-interfering compounds through a decrease in luminescence are sensitive to chemicals judged nontoxic by bacterial systems.32 In 2000, a S. cerevisiae based biosensor was developed that was genetically modified to be sensitive
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
to mutagens and carcinogens in environmental samples which proved to be more sensitive than any bacterial test that was available.33 In addition to toxicity monitors, many yeast strains were manipulated to detect specific groups of molecules. For example, an estrogen and an estrogen analog biosensor was developed with S. cerevisiae by deleting the dihydrofolate reductase gene (DHFR) and replacing it with the mouse homolog containing the ligand-binding domain for estrogen.34 S. cerevisiae was also engineered to respond to octyl aldehyde by transfecting cells with the rat olfactory receptor R17. This was coupled to the cAMP signal transduction pathway for R17, which in turn was coupled to a cAMP responsive green fluorescent protein (GFP) reporter construct.35 Other S. cerevisiae biosensors that have been reported include cells capable of metabolizing and reporting on polychlorinated dibenzo-p-dioxins (PCDD’s) via the rat CYP1A1 and CYP1A2 genes. This was shown to be useful for the elucidation of dioxin metabolism in the liver.36 A biosensor has also been developed for the detection of copper by fusing the coppersensitive CUP1 promoter to a lacZ reporter gene, therefore allowing detection of copper concentrations by means of luminescence.37 Finally, a sensitive and specific sensor for formaldehyde was developed using the methylotrophic yeast Hansenula polymorpha.38
2.3
The Detector
Thus far, we have discussed biosensors, mostly in the context of enzymes, which are able to transduce a catalytic event involving an analyte into a signal by way of a chemical transformation. However, enzymes are characterized by relatively low affinities in contrast to binding proteins whose function has evolved to provide a recognition function rather than chemical manipulation. Such systems, of which antibodies and receptors are prime examples, characteristically have much higher affinities for the ligand thereby giving both great sensitivity as well as high selectivity. Since proteins such as receptors (and unlike most antibodies) have a dual role in recognizing and then communicating the binding event via a transduction process, they also have the potential to initiate a response that can be recognized. The challenge
now is to couple the recognition event (the detector) to a response, which can form the basis of a dose-dependent readout system (the reporter). For the remainder of this review, we will outline perhaps the most widespread, versatile, and efficient receptor system in eukaryotic biology—G-protein coupled receptors (GPCRs). It has evolved to recognize a wide range of biological analytes, which attest its versatility as a molecular platform par excellence for detection and transduction.
2.4
The GPCR Cascade
GPCRs contain seven transmembrane segments, the N-terminal being extracellular and the C-terminal intracellular. They can be organized into six classes that exhibit considerable sequence diversity. Their general architecture remains well conserved, however, the only significant difference being the highly variable size of the N-terminal extracellular domain. While most of the families have a relatively short aminoterminus, a lengthy and highly structured N-terminus is characteristic of family B, such as the parathyroid hormone receptor. This region, along with the external facing loops between the TM segments, play significant roles in binding, particularly, of large protein or peptide ligands. The extracellular third of the transmembrane segments are involved in ligand binding, especially of small molecules such as dopamine. These regions are also centrally responsible for mediating the conformational changes that distinguish the active and inactive states of the receptor. Several of the transmembrane helices are involved in the movements that produce the activated state. These changes are reflected in altered conformation of inward facing hydrophilic domains, which are responsible for first binding then activating the specific G-protein. Of the four regions on the inner surface, loop 3 plays the most prominent role in G-protein binding/activation, with the other regions being supporting players. Phosphorylation of intracellular loop 3 and the C-terminal tail usually signals termination of activation. Finally, GPCRs mostly occur as dimers but there is increasing evidence of higher order oligomers, though all the interactions are not strong/permanent. This quaternary structure has a
YEAST-BASED BIOSENSORS FOR HIGH-THROUGHPUT SCREENING
number of implications for the binding and specificity of ligands, cooperative behavior, transactivation, and the association of G-protein (indeed, many consider only one G-protein is associated per dimer). These features are all illustrated in a generic structure for a GPCR. GPCRs transduce their signal response via a heterotrimeric G-protein complex, which is composed of α, β, and γ subunits. Upon agonist binding to the GPCR, the activated conformation of the receptor is stabilized which leads to the activation of the associated G-protein. This involves nucleotide exchange of the bound guanosinediphosphate (GDP) by guanosine-triphosphate (GTP) to generate the active form of Gα. This conformational change causes dissociation of the Gβγ subcomplex from Gα and modulation of secondary effector/messenger systems. Gα reassociates with Gβγ only after the GTPase activity in the Gα subunit hydrolyzes the GTP nucleotide to GDP. To date, 20 different Gα subunits have been identified and they have been subdivided into four groups according to their sequence similarity.39–41 The four major classes of the Gα family are termed Gαs , Gαi/o , Gαq , and Gα12/13 . There have been at least five Gβ subunits identified which share a 50–90% sequence identity.42 So far, 12 Gγ subunits have been identified and are structurally diverse sharing only 50% sequence similarity.41,43,44 This variety of subunits provides an array of different heterotrimeric subunit combinations; this in turn can increase the variety of effector systems associated with GPCR activation. The major effectors identified so far with which G-proteins couple are adenylate cyclase, Ca2+ channels, phosphodiesterase, phospholipase C, G-protein regulated inward rectifier potassium channels, phosphoinositide-3-kinase, G-protein regulated kinase, and Rho guanine nucleotide exchange factor (RhoGEF).41 Coupling can be through the Gα subunit or the Gβγ subcomplex. The G-protein subunits can have either an inhibitory or a stimulatory effect on their target system, which in turn, can modulate intracellular levels of secondary messengers such as cAMP, cGMP, inositol 1,4,5 trisphosphate (IP3), 1,2diacylglycerol (DAG), and Ca2+ ions. These second messengers regulate cascades throughout the cell resulting in cell-specific events41 (Figure 1 and Table 1).
5
Table 1. Effectors modulated by different effector systems. The table lists effectors of G-proteins and the subunits that regulate them.
Effector Adenylate cyclase Phosphodiesterase Phospholipase C Potassium channel (inward rectifier) Ca2+ channel Phosphoinositide-3kinase G-protein regulated kinase RhoGEF
α subunit
βγ complex
↑, ↓ ↑ ↑
↓
↑, ↓
↑ ↑ ↓ ↑ ↑
↑
[Reprinted with permission Offermanns41 copyright 2003, Elsevier.]
2.5
Functional Assays for Screening
To date, there are a number of assays for screening GPCR activation utilizing the numerous downstream messengers. These include measuring the activation of the G-protein as well as the secondary messengers (cAMP, Ca2+ mobilization, and reporter genes) and the receptor desensitization regulators. The primary event in receptor stimulation, G-protein activation, does not require amplification by other processes. The assay exploits the nonhydrolyzable guanosine-5 (γ -thio) triphosphate (GTPγ S) that prevents the reassociation of the G-protein heterotrimer that can therefore, be measured.46 The production of cAMP is directly controlled by the adenylate cyclase family, which in turn is regulated by Gα subunits, either through activation by Gαs or inhibition by Gαi. Levels of cAMP are directly related to G-protein activation and so can be used to measure receptor stimulation. The two broad methods for monitoring cAMP are reporter gene and accumulation assays. The latter can be directly measured using radiolabeled cAMP or by fluorescence polarization (FP) assays.47 One of the more universal and popular high-throughput screening (HTS) of GPCRs measures the mobilization of Ca2+ , utilizing calcium-binding fluorescent dyes: fluo3, fura-2, and aequorin.45,48 Calcium stores are released upon activation of phospholipase C-β (PLC-β) by GTP-associated Gα/Gβγ that leads to an intracellular cascade culminating in
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS Biogenic amines, lipids, phospholipids, peptides, proteins, glycoproteins, nucleotides, purines, amino acids, ions, and sensory stimuli
GPCR
Plasma membrane a
b g GTP
GDP
b
a
g
GTP
GDP
RGS
as
ai/o
Adenylyl cyclase
Adenylyl cyclase
aq/11
a12/13
Adenylyl cyclase
Phospholipase Cb/e
cAMP PKA
Phospholipase Cb
Rho GEF
GPCA kinasses
IP1 IP2 IP3 + DAG Ca2+
PKC
RhoA ROCK
Phosphorylation of cellular substrates
PI3-K PKD Raf-1 c-src RACK1
MAPKs
Responses
Figure 1. GPCR signaling pathways. The Gαs subfamily activates the adenylyl cyclase pathway to ultimately lead to the activation of protein kinase A (PKA) via the stimulation of cAMP. The Gαi/o subfamily primarily inhibits adenylate cyclase. The Gαq/11 family stimulates phospholipase Cβ, leading to an increase of intracellular calcium and activation of protein kinase C (PKC). The main effector system for the Gα12/13 subfamily is the RhoGEF. The Gβγ subunits also regulate several effector proteins. [Reprinted from permission Simpson48 copyright 2005, Elsevier.]
the mobilization of Ca2+ . The HTS of Ca2+ mobilization is measured using the fluorescent imaging plate reader (FLIPR).49 Currently, 30 GPCRs are known to transduce their signal through the activation of PLC-β, and the Gα17/z recognizes a large number of GPCRs that are not linked to PLC-β activation.50,51 Reporter gene assays are based on the ability of GPCR secondary messengers (cAMP or Ca2+ ) to activate/inhibit a responsive element upstream of a minimal promoter, regulating the expression of a reporter protein.45 Commonly used reporter genes are β-galactosidase, GFP, luciferase, and βlactamase.45 Desensitization assays exploit the β arrestins that are involved in the down regulation of GPCRs from the cell surface via clathrin-coated pits (for a recent review,52 ). The technology uses bioluminescence resonance transfer (BRET)
assays and fluorescently tagged β arrestins. A β arrestin fused between Renilla luciferase (Rluc) and yellow fluorescent protein (YFP) at the Nand C-termini, respectively, was used to detect GPCR activation.53 Upon attenuation of β arrestin by a ligand-activated GPCR, a conformational change results in the termini of β arrestin coming into close proximity and hence inducing a BRET response.53
2.6
Surface Plasmon Resonance (SPR)
SPR is a major development which has had widespread use throughout the biosensor world. The technology measures the variation in the interaction between biological molecules by detecting a change in the refractive index on the sensorchip surface.54 SPR has already been demonstrated
YEAST-BASED BIOSENSORS FOR HIGH-THROUGHPUT SCREENING
as a useful tool in measuring ligand–receptor interactions with rhodopsin. Ligand-activated stim˚ increase in ulation of rhodopsin leads to a 4–6 A membrane thickness, corresponding to the elongation of the protein and exposure of G-protein recognition sites.54 The screening of GPCRs by SPR depends upon the immobilization of the protein on the chip surface, while a ligand solution is flowed over. The main advantages in using the SPR system are that the GPCR remains in the native state, molecular tagging of the receptor is not necessary, and ligand association/dissociation can be measured without labels.55 The analysis of the samples is rapid and constitutes an advantage in HTS.55 Furthermore, the SPR system has been effectively used to monitor the association/dissociation of the rhodopsin G-protein, transducin, therefore, demonstrating the universal properties of this technique.56 The major requirement for SPR is the immobilization of the GPCR onto the sensor-chip surface while preserving its function.57 The GPCR structure of seven transmembrane regions makes this family of proteins very hydrophobic, and therefore they require a lipid or detergent environment to maintain their native conformation.57 Therefore, GPCRs are typically immobilized on the sensorchip surface by incorporation into a supported lipid bilayer or indirectly via antibody coupling.58 All this makes for a rather expensive high technology which requires considerable expertise and very careful manipulation. As such, it is a useful and effective research tool. As a practical everyday sensor system, however, it lacks robustness and is too open to variability.
2.7
Yeast GPCRs
There are two known GPCR systems expressed in the yeast strain, S. cerevisiae: the pheromone pathway (Ste2p and Ste3p) and a putative glucose receptor GPR1. GPR1 couples to the Gpa2 G-protein that, upon activation, stimulates the activation of a cAMP-dependent protein kinase A, which in turn is involved in cellular processes such as transcription, energy metabolism, and cell cycle progression.59 S. cerevisiae exists in the two mating types A and α and expresses the pheromone receptors Ste2p and Ste3p, respectively. Although these
7
receptors are functionally coupled to similar cascades and responses, they possess little sequence similarity.
2.8
The Ste2p Receptor
Ste2p is the yeast pheromone mating receptor expressed in S. cerevisiae mating type MATa. The GPCR is coupled to a mitogen-activated protein (MAP) kinase pathway that culminates in preventing cell division and promoting cell growth in readiness for mating to the other cell type (MATα).60 Stimulation of the G-protein releases the βγ subunits (Ste4p and Ste18p, respectively) initiating the MAP kinase response, and ultimately influencing three effector systems (i) the Ste5p/Ste11p complex, (ii) the Ste20p protein kinase, and (iii) the Far1/Cdc24 complex. The pathway leads to the phosphorylation of transcription factors resulting in growth arrest and preparation for cell fusion60 (see Figure 2). Since this is an efficient signaling pathway, it opens the route to developing effective detector and reporter systems whereby analytes can be monitored.
2.9
Coupling of Mammalian Receptors to the Yeast Mating Pathway
Pharmaceutical companies regularly create libraries of 106 organic compounds to screen against GPCRs for agonist and antagonist activity. It is necessary therefore, to have a HTS that is reliable, inexpensive, and robust. The unicellular eukaryotic system of yeast is attractive for the creation of a universal screen that is not only effective but also for stable, easy to handle and low in cost. To create this HTS, several groups have attempted to couple heterologous GPCRs to the yeast mating pathway. Construction of receptor chimeras by exchanging the intracellular regions can be useful in identifying natural agonists, antagonists, and intracellular pathways. However, only a proportion of receptors readily couple to the yeast G-protein, Gpa1p, and replacing the subunit with the mammalian homolog has met with variable success, partly as a result of the low affinity of mammalian Gα subunits for the Gβγ complex.61 Success was achieved when coexpressing β2 -adrenergic receptor to the
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Ste2p
Cdc42 a
b
Ste20p
g
Bem1
Ste50p Ste11pMEKK Ste5p Ste7pMEK Fus3/Kss1MAPK
Ste12p
Dig 1/2
Transcription of matingspecific genes Pheromone production (MFa1 and MFa2)
Far1
Stimulation of polarized growth (Gb and Cdc24) Cell cycle arrest
Pheromone response (Ste2p) Aggluination (Aga) Desensitization and recovery (Sst2 and Bar1) Cell fusion (Fus1 and Fus2)
Figure 2. Schematic view of the yeast pheromone response pathway. Activation of Ste2p receptor releases Gβγ subunits leading to the stimulation of the MAP kinase cascade and cell cycle arrest. [Reprinted with permission Bardwell60 copyright 2005, Elsevier.]
GαS subunit in a yeast strain with Gpa1p deleted.62 Construction of G-protein chimeras by exchanging the C-terminus of the yeast G-protein with equivalent residues from the mammalian subunits retains interaction to the Gβγ subunits and coupling to
the mammalian receptor. Examples are the mammalian somatostatin receptor, human formyl peptide receptor like-1 (FPRL-1), and the muscarinic receptors M1 , M3 , and M5 .63–65 More recently, a library of chimeric mammalian/yeast G-proteins
YEAST-BASED BIOSENSORS FOR HIGH-THROUGHPUT SCREENING
known as “Gpa1p transplants” have been constructed allowing the coupling of many receptors to the yeast mating pathway.66 Although “transplant” G-proteins can be effective in coupling mammalian receptors to the yeast mating pathway, they can also display differences in receptor coupling specificity and the system can efficiently couple only 60–70% of mammalian GPCRs.67 A variety of chimeric Gpa1p-mammalian G-proteins have been used to identify ligands for orphan receptors such as the KIAA0001, now identified as UDP-glucose receptor, by screening for G-protein and agonist activation.68 The human FPRL-1 receptor was originally identified as an orphan receptor in this way using a random peptide library as ligands from which six agonists were identified.69 Alternatively, exchanging the intracellular regions of the vasopressin receptor with that of the orphan vasopressin-related receptor (VRR1), enabled the identification of potential G-protein partners for VRR1.70 The use of heterologous receptor expression in yeast can be used as a screening system for drug development or as a means of identifying natural agonists for orphan receptors.
2.10
Agonist Assays
Modified yeast strains that are transfected with a mammalian GPCR of interest that couples to the mating pathway once activated, can then activate a reporter gene fused to a ste12p-inducible promoter, for example, FUS1-lacZ, which will produce β-galactosidase upon activation, or FUS1HIS3, which allows for selection via the production of the histidine gene.67 Activation of a GPCR therefore activates one of these reporter genes and allows detection of novel agonists. For HTS, the β-galactosidase assay is most apt, as it can be performed in multiwell plates with each well containing a different GPCR expressing yeast.
2.11
Antagonist Screening
The most common way of screening for a GPCR antagonist is to use a modified version of the agonist screen described above. This is where
9
activation of the GPCR leads to the production of an agent that will kill the yeast cell, for example, FUS2-canavanine. Yeast cells with such modifications are incubated with a known agonist so that the GPCR is continually activated and the yeast is therefore unable to grow. However, in the presence of an antagonist, the activation of the GPCR is blocked and the yeast is therefore able to grow.67
2.12
Autocrine Assays
A major disadvantage of employing yeast for screening of novel agonists and antagonists is illustrated by the screening of peptide libraries. This problem arises because of the yeast cell wall, which prevents larger peptides from crossing into the periplasm and therefore interacting with the GPCR. To overcome this difficulty, the yeast can be transfected with the GPCR and peptide, or peptide library of interest in which, the peptide is attached to a yeast leader sequence. This results in secretion of the peptide into the periplasm where it can interact with the GPCR. This method has been shown to be successful for GPCRs whose ligands are too large to cross the cell wall and are thus unable to interact with the GPCR when added to the growth medium. This assay can be used in the identification of new ligands for orphan receptors whereby a whole peptide library is expressed in yeast cultures along with the orphan GPCR.67
3 SUMMARY
In this chapter, we have attempted to describe in relatively straightforward terms, the use of biological membrane transduction systems. We have concentrated on GPCRs as an example that illustrates great evolutionary variability, high sensitivity and selectivity, and good amplification potential. When coupled with the ease of transduction, robustness, and plasticity presented by the likes of yeast, they represent an attractive, relatively straightforward complementary technology which can be used either in a visual detection mode or by instrumentation where accurate quantification is required.
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
REFERENCES 1. D. Nikollelis, U. Krull, J. Wang, and M. Mascini, Biosensors for Direct Monitoring of Environmental Pollutants in Field, Kluwer Academic, London, 1998. 2. G. E. Ramsey, Commercial Biosensors: Applications to Clinical, Bioprocess and Environmental Samples, John Wiley & Sons, Chichester, 1998. 3. K. Riedel, Microbial Biosensors Based on Oxygen Electrodes, in Enzyme and Microbial Biosensors: Techniques and Protocols, A. Mulchandani and K. R. Rogers (eds), Humane Press, Totowa, 1998, pp. 199–223. 4. Y. Arikawa, K. Ikebukuro, and I. Karube, Microbial Biosensors Based on Respiratory Inhibition, in Enzyme and Microbial Biosensors: Techniques and Protocols, A. Mulchandani and K. R. Rogers (eds), Humane Press, Totowa, 1998, pp. 225–235. 5. E. I. Rainina, E. N. Efremenco, S. D. Varfolomeyev, A. L. Simonian, and J. R. Wild, The development of a new biosensor based on recombinant E. coli for the direct detection of organophosphorus neurotoxins. Biosensors and Bioelectronics, 1996, 11(10), 991–1000. 6. S. F. D’Souza, Immobilised cells: techniques and applications. Indian Journal of Microbiology, 1989, 29, 991–1000. 7. A. Batil and S. F. D’Souza, Measurement of in situ halophilic glyceraldehydes-3-phosphate dehydrogenase activity from permeabilised cells of archaebacterium Haloarcula vallisortis. Journal of General and Applied Microbiology, 1997, 43, 163–167. 8. S. F. D’Souza and K. Z. Marolia, Stabilisation of Micrococcus lysodeikticus cells towards lysis by lysozyme using glutaraldehyde: application as a novel biospecific ligand for the purification of lysozyme. Biotechnology Techniques, 1999, 13, 375–378. 9. S. F. D’Souza, Immobilization and stabilization of biomaterials for biosensor applications. Applied Biochemistry and Biotechnology, 2001, 96(1–3), 225–238. 10. B. Y. K. Rao, L. R. Godbole, L. C. Katwa, and S. G. Bhat, Preparation of lactose free milk by fermentation using immobilised Saccharomyces fragilis. Biotechnology Letters, 1988, 10, 427–430. 11. M. S. Joshi, L. R. Gowda, L. C. Katwa, and S. G. Bhat, Permeabilisation of yeast cells to lactose by digitonin. Enzyme and Microbial Technology, 1989, 11, 439–443. 12. J. M. Parry, Use of Tests in Yeast and Fungi in the Detection of and Evaluation of Carcinogens, in The use of shortand Medium Term Tests for Carcinogens and Data on Genetic Defects in Carcinogenic Hazard Evaluation, D. B. McGregor, J. M. Rice, and S. Venitt (eds), IARC Scientific Publications, Lyon, 1999, pp. 471–485. 13. R. M. Walmsley and P. Keenan, The eukaryote alternative: advantages of using yeast in place of a microbial biosensor development. Biotechnology and Bioprocess Engineering, 2000, 5, 387–394. 14. J. J. G. Ponte and C. C. Tsen, Bakery Products, in Food and Beverage Mycology, L. R. Beuchat (ed), Reinhold, New York, 1987, pp. 241–243. 15. J. M. Middlehoven, I. de Jong, and M. de Winter, Arxula adeninivorans, a yeast assimilating many nitrogenous and aromatic compounds. Antonie van Leeuwenhoek, 1991, 59, 129–137.
16. M. Hikuma, H. Suzuki, T. Yusuda, I. Karube, and S. Suzuki, Amperometric estimation of BOD using living immobilised yeasts. European Journal of Applied Environmental Microbiology Biotechnology, 1979, 8, 1676–1679. 17. K. Tag, A. W. K. Kwong, M. Lehman, C. Chan, R. Renneberg, K. Riedel, and G. Kunze, Fast detection of high molecular weight substances in wastewater based on enzymatic hydrolysis combined with the Arxula BOD system. Journal of Chemical Technology and Biotechnology, 2000, 75(11), 1080–1082. 18. S. P. Trosok, B. T. Driscoll, and J. H. Luong, Mediated microbial biosensor using a novel yeast strain for wastewater BOD measurement. Applied Microbiology and Biotechnology, 2001, 56(3–4), 550–554. 19. M. Mascini and A. Memoli, Comparison of microbial sensors based on amperometric and potentiometric electrodes. Analytical Chemistry Acta, 1986, 182, 113–122. 20. J. Racek, A yeast biosensor for glucose determination. Applied Microbiology and Biotechnology, 1991, 34(4), 473–477. 21. M. Alkasrawi, R. Nandakumar, R. Margesin, F. Schinner, and B. Mattiasson, A microbial biosensor based on Yarrowia lipolytica for the off-line determination of middle-chain alkanes. Biosensors and Bioelectronics, 1999, 14(8–9), 723–727. 22. J. Racek and J. Musil, Biosensor for lactate determination in biological fluids. I. Construction and properties of the biosensor. Clinica Chimica Acta, 1987, 162(2), 129–139. 23. J. Kulys, L. Wang, and V. Razumas, Sensitive yeast bioelectrode to L-lactate. Electroanalysis, 1992, 4, 527–532. 24. A. V. Lobanov, I. A. Borisov, S. H. Gordon, R. V. Greene, T. D. Leathers, and A. N. Reshetilov, Analysis of ethanol-glucose mixtures by two microbial sensors: application of chemometrics and artificial neural networks for data processing. Biosensors and Bioelectronics, 2001, 16(9–12), 1001–1007. 25. I. Karube and M. Suzuki, Microbial Biosensors, in Biosensors- A Practical Approach, E. A. G. Cass (ed), IRL Press, Oxford, 1990, pp. 155–169. 26. L. Campanella, G. Favero, and M. Tomassetti, Further developments in toxicity cell biosensors. Sensors and Actuators, B Chemical, 1997, 44(1–3), 279–285. 27. L. Campanella, G. Favero, D. Mastrofini, and M. Tomassetti, Toxicity order of cholanic acids using an immobilised cell biosensor. Journal of Pharmaceutical and Biomedical Analysis, 1996, 14(8–10), 1007–1013. 28. L. Campanella, G. Favero, and M. Tomassetti, Immobilised yeast cells biosensor for total toxicity testing. Science of the Total Environment, 1995, 171(1–3), 227–234. 29. N. Billington, M. G. Barker, C. E. Michel, A. E. Knight, W. D. Heyer, N. J. Goddard, P. R. Fielen, and R. M. Walmsley, Development of a green fluorescent protein reporter for a yeast genotoxicity biosensor. Biosensors and Bioelectronics, 1998, 13, 831–838. 30. R. M. Walmsley, P. Keenan, A. W. Knight, and J. Schmuckli, Rad54-GFP , Proceedings of the Bioset Technical Workshop on Genotoxicity Testing, Technotox, Belgium, 2000.
YEAST-BASED BIOSENSORS FOR HIGH-THROUGHPUT SCREENING 31. V. Afanassiev, M. Sefton, T. Anantachaiyong, G. Barker, R. Walmsley, and S. Wolfl, Application of yeast cells transformed with GFP expression constructs containing the RAD54 or RNR2 promoter as a test for the genotoxic potential of chemical substances. Mutation Research, 2000, 464(2), 297–308. 32. R. P. Hollis, K. Killham, and L. A. Glover, Design and application of a biosensor for monitoring toxicity of compounds to eukaryotes. Applied and Environment Microbiology, 2000, 66(4), 1676–1679. 33. A. Terziyska, L. Waltschewa, and P. Venkov, A new sensitive test based on yeast cells for studying environmental pollution. Environmental Pollution, 2000, 109(1), 43–52. 34. C. L. Tucker and S. Fields, A yeast sensor of ligand binding. Nature Biotechnology, 2001, 19(11), 1042–1046. 35. S. F. D’Souza, Microbial biosensors. Biosensors and Bioelectronics, 2001, 16, 337–353. 36. T. Sakaki, R. Shinkyo, T. Takita, M. Ohta, and K. Inouye, Biodegradation of polychlorinated dibenzo-p-dioxins by recombinant yeast expressing rat CYP1A subfamily. Archives of Biochemistry and Biophysics, 2002, 401(1), 91–98. 37. M. Lehman, K. Riedel, K. Adler, and G. Kunze, Amperometric measurement of copper ions with a deputy substrate using novel saccharomyces cerevisiae sensor. Biosensors and Bioelectronics, 2000, 15, 211–219. 38. Y. I. Kopran, M. V. Gonchar, N. F. Starodub, A. A. Shul’ga, A. A. Sibirny, and A. V. El’skaya, A cell biosensor specific for formaldehyde based on pH sensitive transistors coupled to methylotrophic yeast cells with genetically adjusted metabolism. Analytical Biochemistry, 1993, 215, 216–222. 39. S. R. Neves, P. T. Ram, and R. Iyengar, G protein pathways. Science, 2002, 296(5573), 1636–1639. 40. S. R. Sprang, G protein mechanisms: insights from structural analysis. Annual Review of Biochemistry, 1997, 66, 639–678. 41. S. Offermanns, G-proteins as transducers in transmembrane signalling. Progress in Biophysics and Molecular Biology, 2003, 83(2), 101–130. 42. E. J. Neer, Heterotrimeric G proteins: organizers of transmembrane signals. Cell, 1995, 80(2), 249–257. 43. K. Ray, C. Kunsch, L. M. Bonner, and J. D. Robishaw, Isolation of cDNA clones encoding eight different human G protein gamma subunits, including three novel forms designated the gamma 4, gamma 10, and gamma 11 subunits. Journal of Biological Chemistry, 1995, 270(37), 21765–21771. 44. J. D. Robishaw and C. H. Berlot, Translating G protein subunit diversity into functional specificity. Current Opinion in Cell Biology, 2004, 16(2), 206–209. 45. W. Thomsen, J. Frazer, and D. Unett, Functional assays for screening GPCR targets. Current Opinion in Biotechnology, 2005, 16(6), 655–665. 46. C. Harrison and J. R. Traynor, The [35S]GTPgammaS binding assay: approaches and applications in pharmacology. Life Sciences, 2003, 74(4), 489–508. 47. C. Williams, cAMP detection methods in HTS: selecting the best from the rest. Nature Reviews Drug Discovery, 2004, 3(2), 125–135.
11
48. A. W. Simpson, Fluorescent measurement of [Ca2+]c. Basic practical considerations. Methods in Molecular Biology, 1999, 114, 3–30. 49. B. R. Conway and K. T. Demarest, The use of biosensors to study GPCR function: applications for highcontent screening. Receptors and Channels, 2002, 8(5–6), 331–341. 50. D. E. Clapham, Calcium signaling. Cell, 1995, 80(2), 259–268. 51. A. M. Liu, M. K. Ho, C. S. Wong, J. H. Chan, A. H. Pau, and Y. H. Wong, G alpha(16/z) chimeras efficiently link a wide range of G protein-coupled receptors to calcium mobilization. Journal of Biomolecular Screening, 2003, 8(1), 39–49. 52. S. K. Shenoy and R. J. Lefkowitz, Multifaceted roles of beta-arrestins in the regulation of seven-membranespanning receptor trafficking and signalling. Biochemical Journal, 2003, 375(Pt 3), 503–515. 53. P. G. Charest, S. Terrillon, and M. Bouvier, Monitoring agonist-promoted conformational changes of beta-arrestin in living cells by intramolecular BRET. EMBO Reports, 2005, 6(4), 334–340. 54. I. D. Alves, C. K. Park, and V. J. Hruby, Plasmon resonance methods in GPCR signaling and other membrane events. Current Protein and Peptide Science, 2005, 6(4), 293–312. 55. S. Sen, V. P. Jaakola, P. Pirila, M. Finel, and A. Goldman, Functional studies with membrane-bound and detergentsolubilized alpha2-adrenergic receptors expressed in Sf9 cells. Biochimica et Biophysica Acta, 2005, 1712(1), 62–70. 56. S. Heyse, O. P. Ernst, Z. Dienes, K. P. Hofmann, and H. Vogel, Incorporation of rhodopsin in laterally structured supported membranes: observation of transducin activation with spatially and time-resolved surface plasmon resonance. Biochemistry, 1998, 37(2), 507–522. 57. J. Minic, J. Grosclaude, J. Aioun, M. A. Persuy, T. Gorojankina, R. Salesse, E. Pajot-Augy, Y. Hou, S. Helali, N. Jaffrezic-Renault, F. Bessueille, A. Errachid, G. Gomila, O. Ruiz, and J. Samitier, Immobilization of native membrane-bound rhodopsin on biosensor surfaces. Biochimica et Biophysica Acta, 2005, 1724(3), 324–332. 58. K. E. Komolov, I. I. Senin, P. P. Philippov, and K. W. Koch, Surface plasmon resonance study of g protein/receptor coupling in a lipid bilayer-free system. Analytical Chemistry, 2006, 78(4), 1228–1234. 59. G. M. Santangelo, Glucose signaling in saccharomyces cerevisiae. Microbiology and Molecular Biology Reviews, 2006, 70(1), 253–282. 60. L. Bardwell, A walk-through of the yeast mating pheromone response pathway. Peptides, 2005, 26(2), 439–450. 61. G. Ladds, A. Goddard, and J. Davey, Functional analysis of heterologous GPCR signalling pathways in yeast. Trends in Biotechnology, 2005, 23(7), 367–373. 62. K. King, H. G. Dohlman, J. Thorner, M. G. Caron, and R. J. Lefkowitz, Control of yeast mating signal transduction by a mammalian beta 2-adrenergic receptor and Gs alpha subunit. Science, 1990, 250(4977), 121–123. 63. L. A. Price, E. M. Kajkowski, J. R. Hadcock, B. A. Ozenberger, and M. H. Pausch, Functional coupling of a
12
64.
65.
66.
67.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS mammalian somatostatin receptor to the yeast pheromone response pathway. Molecular and Cell Biology, 1995, 15(11), 6188–6195. R. Qanbar and M. Bouvier, Role of palmitoylation/ depalmitoylation reactions in G-protein-coupled receptor function. Pharmacology and Therapeutics, 2003, 97(1), 1–33. I. Erlenbach, E. Kostenis, C. Schmidt, F. F. Hamdan, M. H. Pausch, and J. Wess, Functional expression of M(1), M(3) and M(5) muscarinic acetylcholine receptors in yeast. Journal of Neurochemistry, 2001, 77(5), 1327–1337. A. J. Brown, S. L. Dyos, M. S. Whiteway, J. H. White, M. A. Watson, M. Marzioch, J. J. Clare, D. J. Cousens, C. Paddon, C. Plumpton, M. A. Romanos, and S. J. Dowell, Functional coupling of mammalian receptors to the yeast mating pathway using novel yeast/mammalian G protein alpha-subunit chimeras. Yeast, 2000, 16(1), 11–22. S. J. Dowell and A. J. Brown, Yeast assays for G-proteincoupled receptors. Receptors and Channels, 2002, 8(5–6), 343–352.
68. J. K. Chambers, L. E. Macdonald, H. M. Sarau, R. S. Ames, K. Freeman, J. J. Foley, Y. Zhu, M. M. McLaughlin, P. Murdock, L. McMillan, J. Trill, A. Swift, N. Aiyar, P. Taylor, L. Vawter, S. Naheed, P. Szekeres, G. Hervieu, C. Scott, J. M. Watson, A. J. Murphy, E. Duzic, C. Klein, D. J. Bergsma, S. Wilson, and G. P. Livi, A G protein-coupled receptor for UDPglucose. Journal of Biological Chemistry, 2000, 275(15), 10767–10771. 69. C. Klein, J. I. Paul, K. Sauve, M. M. Schmidt, L. Arcangeli, J. Ransom, J. Trueheart, J. P. Manfredi, J. R. Broach, and A. J. Murphy, Identification of surrogate agonists for the human FPRL-1 receptor by autocrine selection in yeast. Nature Biotechnology, 1998, 16(13), 1334–1337. 70. J. Gupte, G. Cutler, J. L. Chen, and H. Tian, Elucidation of signaling properties of vasopressin receptor-related receptor 1 by using the chimeric receptor approach. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(6), 1508–1513.
14 Molecularly Imprinted Polymers as Recognition Elements in Sensors Karsten Haupt and Anne-Sophie Belmont Compi`egne University of Technology, Compi`egne, France
1 MOLECULARLY IMPRINTED POLYMERS 1.1
General Principle of Molecular Imprinting
Like a hand in a glove, specialized structures such as antibodies, hormone receptors, and enzymes fit perfectly into their natural targets. Such macromolecules are, therefore, invaluable in biotechnology, medicine, and analytic chemistry. However, although “nature’s own”, such structures are far from perfect “tools”—they are unstable out of their native environment and often low in abundance, and a natural receptor for the particular molecule of interest may not exist. Researchers have long dreamed of building such structures de novo: creating tailor-made receptors for the desired molecular target in bulk. One surprisingly simple way of generating artificial macromolecular receptors is through the molecular imprinting of synthetic polymers. In molecular imprinting, a target molecule (or a derivative thereof) acts as the template around which interacting and cross-linking monomers are arranged and copolymerized to form a cast-like shell (Figure 1). Initially, the monomers form a complex with the template through covalent or noncovalent interactions. When the polymerization is initiated, polymer chains start to form that are still flexible in the beginning, but as polymerization proceeds, they become cross-linked and the functional groups of the interacting monomers are
now held in place by the polymer scaffold. After polymerization and removal of the template, binding sites complementary to the target molecule in size, shape, and position of functional groups are exposed and their confirmation is preserved by the cross-linked structure. In essence, a molecular memory is imprinted on the polymer, which is now capable of selectively rebinding the target. Thus, molecularly imprinted polymers (MIPs) possess two of the most important features of biological receptors—the ability to recognize and bind specific target molecules. The complex between monomers and imprint molecules can be formed via reversible covalent bonds or via noncovalent interactions such as, hydrogen bonds, ionic bonds, van der Waals forces, metal coordination, or the hydrophobic effect. A combination of the two can also be used. In order to compare the covalent and noncovalent imprinting approaches, different aspects have to be taken into account. The noncovalent imprinting approach, which has been pioneered by Mosbach and coworkers,1 is more flexible concerning the choice of interacting monomers, possible target molecules, and the use of the imprinted materials. After polymerization, the imprint molecule can be removed from the polymer by simple solvent extraction. However, the prepolymerization complex is an equilibrium system, the stability of which depends on the affinity constants between imprint molecule and interacting monomers. This
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS CL
T (a)
M
(b)
Figure 1. (a) Schematic representation of the molecular-imprinting principle with T: imprinting template, M: interacting monomers, CL: cross-linking monomers; (b) computer drawing of a molecular model with methacrylic acid as interacting monomer and an aminoacid derivative as the imprinting template.
may yield to a certain heterogeneity in binding sites. For covalent imprinting, a polymerizable derivative of the imprint molecule has to be synthesized, and after synthesis of the polymer, the imprint molecule has to be removed by chemical cleavage. If upon use of the polymer the covalent bonds have to be reformed, association kinetics may be low. On the other hand, owing to the greater stability of covalent bonds, covalent imprinting protocols should yield a more homogeneous population of binding sites. Moreover, the yield in binding sites relative to the amount of imprint molecule used (imprinting efficiency) should be higher than with noncovalent protocols. This approach has been developed primarily by Wulff and coworkers.2 Protocols have also been suggested that combine the advantages of both covalent and noncovalent imprinting, that is, the
O
NH2
O N
O
H N
N
(a)
OH
OH
HN
O
O
O O
O
target molecule is imprinted as a stable complex with the interacting monomer formed via covalent bonds, whereas upon later use of the MIP, only noncovalent interactions come to play. As an example, Whitcombe and coworkers have reported the imprinting of a tripeptide (Lys-Trp-Asp) using a sacrificial spacer (o-hydroxybenzamide) between the imprint molecule and monomer. In addition to these covalent bonds, other interacting monomers were added in order to form noncovalent interactions. After polymerization, the covalent bonds between the imprint molecule and the monomers are hydrolyzed leaving precisely positioned carboxyl groups (Figure 2). During rebinding the peptide interacts with the polymer only via noncovalent interactions.3 A simple demonstration of the molecularimprinting effect4 is shown in Figure 3(a). A nonimprinted polymer based on trifluoromethylacrylic acid as the interacting monomer and divinylbenzene as the cross-linker was synthesized, and affinity for a target molecule (theophylline) was evaluated using radioligand binding assays. Very low binding capacity was obtained with this nonimprinted polymer. More polymers were then synthesized following the same recipe, while adding to the monomer mixture increasing amounts of theophylline as imprint molecule in order to create imprinted sites. When the resultant polymers were checked for binding of radiolabeled theophylline, it turned out that already a very small quantity of imprint molecule (a molar ratio of 1 : 5000 relative to the amount of the interacting monomer trifluoromethylacrylic acid) doubled the binding capacity
COOH
O N H
O
N
N
OH
OH O
O
N H
(b)
H N
H 2N
N
COOH N
COOH
O N H
O
COOH N
N H
(c)
Figure 2. Molecular imprinting of the tripeptide Lys-Trp-Asp using both covalent and noncovalent interactions. (a) Binding site with covalently bound imprint molecule; (b) binding site after chemical cleavage and extraction of the imprint molecule; (c) rebinding of the imprint molecule via only noncovalent interactions. [Reprinted with permission Klein et al.3 copyright 1999, Wiley VCH.]
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS
3
Imprinting template (T) O H N
N N
O
Bound 3H-theophylline (%)
N
Theophylline
Bound 3H-theophylline (%)
100
100
75
75
Control Imprinted
Interacting monomer (M) R
50
50
25
25
OH O
Trifluoromethylacrylic acid Cross-linker
0
0 no T 1:5000 1:500 1:100
1:12
19
1:4
(a)
Divinylbenzene
(b)
36
69
19
36
69
Cross-linking (%)
T:M (c)
Figure 3. The imprinting effect: (a) Structures of monomers and template for a theophylline-imprinted polymer, (b) the binding capacity for radiolabeled theophylline of a series of polymers synthesized with different amounts of template, (c) the binding capacity for radiolabeled theophylline of a series of polymers synthesized with different degrees of cross-linking.4 [Adapted from Pichon and Haupt.5 Copyright 2006 Taylor & Francis.]
of the polymer with respect to the nonimprinted material. The more template was present during polymerization, the higher the capacity of the polymer. At a ratio of 1 : 12 the maximum capacity was reached, indicating an optimum saturation of the imprint molecule by the interacting groups. The influence of the degree of cross-linking on the binding capacity of the polymer can provide another indication of the presence of molecularly imprinted binding sites. As shown in Figure 3(b), nonimprinted polymers always bind the same low amount of target molecule which is independent of the degree of cross-linking, whereas binding to a series of MIPs increases with cross-linking. This is expected, as the cross-linking of the material is required in order to preserve the specific conformation of the binding sites.
1.2
The Imprinting Matrix
1.2.1 Organic Polymers
A large majority of the reports on MIPs describe organic polymers synthesized by radical polymerization of functional and cross-linking monomers having vinyl or acrylic groups, and using noncovalent interactions between monomers and template. This can be attributed to the rather straightforward synthesis of these materials, and to the vast choice of available monomers. These can be basic (e.g.,
vinylpyridine) or acid (e.g., methacrylic acid), permanently charged (e.g., 3-acrylamidopropyl trimethylammonium), hydrogen bonding (e.g., hydroxyethyl methacrylate), hydrophobic (e.g., styrene) and others. These rather “simple” monomers normally have association constants with the template that are too low to form a stable complex. Thus, they have to be used in excess to shift the equilibrium toward complex formation. Somewhat more sophisticated monomers are also starting to appear that form stable interactions with the template molecule or substructures thereof, and that can sometimes be used in a stoichiometric ratio.6–8 Two examples of monomers recognizing amino and carboxyl groups are depicted in Figure 4. Another possibility to obtain stronger interactions in the prepolymerization complex, in particular in polar solvents like water, is by using coordination bonds with metal chelate monomers.9 It has also been shown that MIPs can be synthesized without any interacting monomer, if the cross-linker is able to play that role at the same time. For example, good imprinting results have been obtained with the cross-linker N,Obismethacryloyl ethanolamine, a molecule capable of acting as a hydrogen bond donor and acceptor, and thus of interacting with the imprinting template.10 In order to obtain an optimized polymer for a given target analyte, combinatorial approaches to MIP synthesis have been used where the ingredients of the imprinting recipe, in particular the
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
H2N
R
(d)
(a) Cl
Cl
O N
+
H O
N
(c) Cl
H −
R
O
O
O
(b)
Figure 4. Amidine functional monomer (a) binding to a carboxyl group (b);8 tetrachloroquinone monomer (c); complexing an amino group (d).6
kind and molar ratio of the functional monomers, are varied. This is ideally done using automated procedures.11 As an example, a MIP selective for the triazine herbicide terbutylazine was optimized using a combinatorial approach where a number of different MIPs were synthesized in small scale (ca. 55 mg).12 The functional monomer was selected from a library composed of six different molecules (methacrylic acid, methylmethacrylate, hydroxyethyl methacrylate, trifluoromethylacrylic acid, 4-vinylpyridine, and N-vinyl-α-pyrrolidone). An initial screening was performed for the type of functional monomer that retained the template most strongly. Among the six monomers tested, methyl methacrylate, 4-vinylpyridine, and N-vinyl-α-pyrrolidone led to polymers from which the imprint molecule was rapidly and quantitatively extracted, whereas methacrylic acid and trifluoromethylacrylic acid led to polymers that retained the template more strongly. On the basis of these two monomers, secondary screening for selectivity was performed. For that purpose, nonimprinted control polymers were also prepared and analyte binding to the MIPs and control polymers evaluated in batch mode. The polymer showing the highest selectivity was found to be the one based on methacrylic acid. It is important to realize that the morphology of the polymer is largely influenced by the monomers,
the porogenic solvent, and the polymerization conditions. If a good solvent is used that is able to solvate even long polymer chains, a gel-like (though hard) material is obtained, with a pronounced mesoporosity but no macropores. Therefore, access to the binding sites is by diffusion and thus slow. On the other hand, these polymers tend to be transparent. However, if the solvent is a bad one for the growing polymer chains, these will adopt a globular conformation and eventually separate out of solution. The thus formed materials are macroporous resins where light scattering causes opacity. During recent years, other polymers have started to appear that are either better suited for a specific application or easier to synthesize in the desired form. For example, polymers such as polyphenols,13 polyurethanes,14 overoxidized polypyrrole,15 and others have been used. Compared to polymers based on acrylic and vinyl monomers, the use of the above-mentioned polymers seems to be somewhat restricted due to the limited choice of functional monomers. 1.2.2 Solgels
Solgels such as silica and titanium dioxide are now gaining in importance as imprinting matrices, although they have been introduced years
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS
ago. Silica has been used as the imprinting matrix for the imprinting with inorganic ions16 and organic molecules.17–19 Thereby, either the bulk material can be imprinted by the solgel method, thus creating microporous materials with specifically arranged functional groups,16 or an imprinted polysiloxane layer is deposited at the silica surface.17 Recently, Katz and Davis have reported the molecularly imprinting of bulk amorphous silica with single aromatic molecules using a covalent monomer template complex, creating shape-selective catalysts.20 They have also been able to directly observe molecular-imprintgenerated microporosity (additional porosity was created in the silica upon template removal) using physical adsorption experiments. Another material that has been imprinted using the solgel technique is titanium oxide.21,22
1.3
Target Molecules
One of the many attractive features of the molecular-imprinting technique is that it can be applied to a wide range of target molecules. The imprinting of small, organic molecules (e.g., pharmaceuticals, pesticides, amino acids, and peptides, nucleotide bases, steroids, and sugars) is now well established and considered almost routine. Metal and other ions have also been used as templates to induce the specific arrangement of functional groups in the imprinting matrix, allowing these ions to be detected specifically by the MIP.23,24 During the last years, there has been an increasing interest concerning the use of proteins as imprinting templates. This requires the development of specific protocols, since proteins are not compatible with the common imprinting mixtures. Different approaches have been reported, where in most cases the imprinting step is associated with a surface or an interface.25,26 One of the more promising approaches is analogous to protein recognition by antibodies. Not the entire molecule, but only part of it, an epitope, is recognized. Although this concept has been introduced earlier,27 it was only recently that a clear demonstration of the principle was made by Shea’s group.28 Terminal nonapeptides of proteins like cytochrome c, alcohol dehydrogenase, and bovine serum albumin were attached to a flat glass surface and a polyacrylamide-based polymer was
5
cast on the surface. After separation of the two surfaces, imprinted sites were revealed that could now recognize the entire protein. The imprinting of much larger structures is still a challenge. Cells have been imprinted using a lithographic technique29 or a stamping technique in a prepolymer that was subsequently cured.30 Even the surface structure of mineral crystals has been reproduced by imprints.31
2 MIPs AS RECOGNITION ELEMENTS IN SENSORS 2.1
General Considerations
MIPs are synthetic macromolecular receptors that can be used in applications where specific molecular binding events are of interest. Currently the main application area for MIPs is analytical chemistry, for example in enantioseparation and solid-phase extraction,5 although they are also very interesting materials for immunoassays and sensors. In chemical sensors and biosensors, a chemical or physical signal is generated upon the binding of the analyte to the recognition element. A transducer then translates this signal into a quantifiable output signal. Indeed, MIPs have been used as the recognition element in combination with optical, acoustic, and electrochemical transducers. Certain changes in one or more physicochemical parameters of the system (such as, mass accumulation) that occur upon analyte binding are used for detection. This principle is widely applicable and more or less independent of the nature of the analyte. Alternatively, reporter groups may be incorporated into the polymer to generate or enhance the sensor response. In other cases, the analyte may possess a specific property (such as, fluorescence or electrochemical activity) that can be used for detection. The first reported integrated sensor based on a MIP was a capacitance sensor. The device consisted of a field-effect capacitor containing a thin phenylalanine anilide-imprinted polymer membrane. Binding of this model analyte resulted in a change in capacitance of the device, thus allowing for the detection of the analyte in a qualitative manner.32
6
2.2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
Transduction Principles
During the last few years, there has been a big boost in the use of acoustic transducers for the design of MIP-based sensors. These general transducers that do not rely on any specific property of the analyte are either piezoelectric crystals in which the resonance frequency of the bulk material is measured (for frequencies in the lower MHz range), or surface-acoustic wave (SAW) devices that comprise a separate waveguide and piezoelectric transmitter and receiver (for frequencies up to 2.5 GHz).33 SAWs are limited to gas-phase applications due to heavy damping of the acoustic wave in liquids. A variant of SAWs, so-called shear transverse wave (STW) resonators (STW, for frequencies in the higher MHz range) show excellent performance even in aqueous solutions.34,35 In these devices, the oscillation frequency changes in response to mass changes at the transducer surface upon analyte binding to the recognition element. Quartz crystal microbalance (QCM) sensors, which are bulk-acoustic wave devices, have been particularly popular because of their relatively low price, their robustness, and ease of use. They consist of a thin quartz disk with electrode layers on both sides, which can be put into oscillation using the piezoelectric effect. An imprinted polymer is deposited on one side of the disk. Analyte accumulation in the MIP results in a change in mass as well as of the viscoelastic properties of the layer, which in turn causes a change in oscillation frequency that can easily be quantified by frequency counting. Measurements with QCM have been performed both in solution14,36,37 and in the gas phase.38,39 A problem associated with this transducer type, in particular if used in the liquid phase, is that they are sensitive not only to mass changes but also to changes in viscoelasticity close to the surface. Thus, the sample matrix can cause artefacts, and the use of a reference sensor coated with a nonselective polymer of the same type as the MIP has been proposed to eliminate these. Such a reference sensor can be placed on the same quartz crystal as the selective sensor,30 which eliminates temperature effects at the same time. For example, QCM has been used to construct an imprinted polymer-based sensor for glucose.37 The polymer, poly(o-phenylene diamine), was electrosynthesized directly at the sensor surface in the presence of 20 mM glucose.
In that way, a very thin (10 nm) polymer layer was obtained that could rebind glucose with certain selectivity over other compounds such as ascorbic acid, paracetamol, cysteine, and to some extent fructose. In a recent application for the detection of cells,30 imprints of whole yeast cells in polyurethane layers and in solgel layers have been produced at the surface of a QCM crystal using a stamping method. The sensor could be used to quantify yeast cells in suspension at concentrations between 1 × 104 and 1 × 109 cells per ml under flow conditions. Others have relied on common acrylic polymers for the design of MIP-based QCM sensors.36,39 One reason for that was probably the abundance of know-how available on such polymers, and their adaptability to many different template molecules due to the plethora of available functional monomers. With such polymers, it has been demonstrated that the sensor selectivities are similar to those obtained in other applications of acrylic MIPs. For example, a QCM sensor coated with a polymer imprinted with S-propranolol (a β-blocker) was able to discriminate between the R- and S-enantiomers of the drug.36 Similar to acoustic transducers, optical transducers using the surface plasmon resonance (SPR) principle40 measure mass accumulation on the sensor surface. They detect changes in the dielectric constant near metal films on glass substrates. The evanescent wave generated by a totally reflected light beam extends a few hundred nm away from the metal surface and may penetrate a thin MIP layer deposited on it. Indeed, a few reports suggesting to use SPR in combination with MIPs have appeared during recent years.41–43 Unfortunately, SPR sensors do not have much sensitivity for the typically small target molecules that the vast majority of MIPs is intended to detect. Recently, Matsui et al. have developed an approach that increases the sensitivity of a MIP-SPR sensor for dopamine. It relies upon the inclusion of gold nanoparticles in the MIP layer. The sensor signal generated by the swelling of the MIP layer upon analyte binding was amplified by the presence of the gold particles, and analyte concentrations down to the nanomolar range could be detected (Figure 5).44 Other sensors have been designed based on conductometric transducers. These measure the change in conductivity of a selective layer in contact with two electrodes upon its interaction with
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS
7
Shrunken state Binding site “unoccupied”
Au Nanoparticle Au-MIP
COOH
MIP Au film
HOOC
Swollen state Au Nanoparticle
Binding site “occupied” COOH
Au-MIP HO
Greater distance
MIP Au film
NH2
HO
HOOC
Figure 5. Schematic representation of a MIP-coated SPR sensor chip using signal enhancement by embedded gold nanoparticles, for detection of the analyte dopamine. [Reprinted with permission from Matsui et al.44 Copyright 2005, American Chemical Society.]
the analyte. Again, the analyte is not required to exhibit any specific property. Conductometric sensors are often based on field-effect devices. For example, the above-mentioned field-effect capacitor32 belongs to this group. Capacitive detection was also employed in conjunction with imprinted electropolymerized polyphenol layers on gold electrodes.13 The sensitive layer was prepared by electropolymerization of phenol on the electrode in the presence of the template phenylalanine. The insulating properties of the polymer layer were studied by electrochemical impedance spectroscopy. Electrical leakages through the polymer layer were suppressed by deposition of a selfassembled monolayer of mercaptophenol before polymerization and of alkanethiol after polymerization. After that, the template was removed. The multilayer system obtained displayed a decrease in electrical capacitance on addition of phenylalanine. Only a low response was observed toward other amino acids and phenol. The same authors also reported a capacitive creatinine sensor based on a photografted molecularly imprinted polymer.45 Another example for this sensor type is a sensing device for the herbicide atrazine, which
is based on a freestanding atrazine-imprinted acrylic polymer membrane and conductometric measurements.46 The authors optimized the polymer recipe in particular with respect to the kind and molar ratio of cross-linking monomers used, and the relative amount of porogenic solvent in the imprinting mixture. This turned out to be an important factor not only in obtaining flexible and stable membranes, but also because the conductometric response seemed to depend on the ability of the MIP to change its conformation upon analyte binding. Attractive features of this sensor were the comparatively short time required for one measurement (6–10 min), its rather low detection limit of 5 nM, and its good selectivity for atrazine over structurally related triazine herbicides. A very general means of transducing the analyte binding to the recognition element is by measuring the adsorption heat that is produced or taken up upon any adsorption or desorption process. This heat, although small, can be measured using a sensitive calorimetric device. MIP-sensors with calorimetric transducers have not yet been described, but the feasibility of quantifying analyte binding to a MIP by isothermal
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
titration microcalorimetry has recently been demonstrated.47 If the target analyte exhibits a special property such as fluorescence or electrochemical activity, this can be exploited for the design of MIP-based sensors. Optical sensors for the detection of fluorescent analytes belong to this group.48–50 A potential problem that can arise when this detection principle is used is that traces of the imprint molecule can remain entrapped in the polymer, which may cause a high background signal resulting in decreased sensitivity. A remedy could be to imprint the polymer with a structurally related molecule similar to the analyte51,52 but not having that special property, providing that the MIP is still able to bind the target analyte. If the analyte lacks a specific property useful for detection, a competitive or displacement sensor format may be used. A labeled analyte derivative or a nonrelated probe is allowed to compete with the analyte for the binding sites in the MIP.53,54 In one application, a voltammetric sensor for the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) was reported55 where the electroactive compound 2,5dihydroxyphenylacetic acid was used as a probe instead of the labeled analyte. MIP particles were coated as a thin layer onto a disposable screenprinted carbon electrode. The electrode was then incubated with the sample to which the probe was added. In the presence of the analyte, some of the probe was competed out of the imprinted sites, whereas the remaining probe was directly quantified by differential pulse voltammetric measurements. An attractive design of the recognition element/transducer couple is to have the signal generated by the polymer itself. This approach appears promising since it should facilitate the construction of simple integrated sensing devices.56,57 One example for such a format is an optical sensing system where fluorescent reporter groups are incorporated into the MIP, the properties of which are altered upon analyte binding. For example, a fluorescent functional monomer, trans-4-[p-(N, N dimethylamino)styryl]-N -vinylbenzylpyridinium chloride, has been used together with a conventional functional monomer to prepare a polymer imprinted with cyclic adenosine monophosphate.56 Upon binding to the imprinted sites, the analyte interacts with the fluorescent groups, and their
fluorescence is quenched, thus allowing the analyte to be quantified. Others have used a similar system with a fluorescent metalloporphyrin as the reporter group, of which a polymerizable derivative was used as one of the functional monomers.57 Binding of the analyte 9-ethyladenine then resulted in quenching of the fluorescence of the polymer. The signals generated by most of the abovementioned transducer types are two-dimensional and provide only limited information about the composition of the sample. Although this is normally compensated by the high selectivity of MIPs, a different strategy could conceivably be the use of “intelligent” transducer mechanisms, which generate signals with higher inherent information content. One way to achieve that is to exploit the high molecular specificity of absorption spectra in the mid-infrared spectral region (3500–500 cm−1 ). The combination of MIPs and FTIR spectrometry might allow analytical problems to be addressed where the selectivity of the MIP alone is not sufficient, e.g., when samples with complex matrices are to be investigated, or when structurally very similar analytes are present in the sample. A recent report described an approach toward a chemical sensor based on an imprinted polymer and infrared evanescent-wave spectroscopy.58 A polymer molecularly imprinted with 2,4-D was coated in form of a thin film onto a ZnSe attenuated total reflection element, which was mounted in a flow cell. Accumulation of 2,4-D in the MIP layer could be followed on-line and in real time by FTIR spectrophotometric measurements. Analyte binding was concentration dependent and could be quantified by integrating characteristic analyte bands.
2.3
Interfacing Polymer and Transducer
Traditionally MIPs have been prepared as bulk polymer monoliths followed by mechanical grinding to obtain small micrometer-sized particles. Whereas the materials obtained through this somewhat inelegant method still seem to be useful for many applications, others, and in particular sensors require MIPs in defined physical forms such as films or nanoparticles, for which specially adapted synthesis methods are needed. In addition, it is desirable to generate imprinted sites at or near the surface of the material, in order to shorten diffusion distances and response times.
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS
2.3.1 Imprinting at Interphases
Imprinted materials with binding sites situated at or close to the surface of the imprinting matrix have many advantages: the sites are better accessible, mass transfer is and binding kinetics may be faster, target molecules conjugated with bulky labels can still bind, and so on. Thus, during the imprinting step, the template has to be positioned at the boundary between the imprinting (monomer) phase and another phase in order to create surface imprints after polymerization. Whitcombe and coworkers have developed a technique based on emulsion polymerization, i.e., small beads are created in an oil-in-water biphasic system stabilized by a surfactant. The imprint molecule (here: cholesterol) is part of the surfactant (pyridinium 12-(cholesteryloxycarbonyloxy)dodecane sulfate).59 As a result, all binding sites are situated at the particle surface, which was demonstrated by flocculation experiments using polyethyleneglycol-bis-cholesterol. Another protocol for the creation of surface binding sites has been introduced by our group. The imprint molecule is immobilized onto a solid support such as, porous silica beads, prior to polymerization.60 The pores are then filled with the monomer mixture, and the polymerization is initiated. The silica is removed by chemical dissolution, which leaves behind a porous polymeric structure, which is the negative image of the original bead. The binding sites are now all situated at the surface of the polymer, and are uniformly oriented. 2.3.2 Thin Films and Membranes
Sensors normally require MIPs in the form of films or membranes with a thickness of not more than a few hundred nanometers. This is in order to shorten diffusion distances and obtain short response times. Also, the evanescent field used in some optical transducers will usually reach not more than a few hundred nanometers away from the transducer surface. Thus, methods like surfaceinitiated polymerization, spin coating, electropolymerization, and assembly of nanoparticles have been used to generate thin MIP films. Surface-initiated polymerization The basic principle of surface-initiated polymerization (SIP) is the immobilization on a surface
9
of the polymerization initiator, followed by the deposition of monomers, and the initiation of the polymerization process. The commonly used free radical initiators like azo-bis-isobutyronitrile (AIBN) are unstable molecules that decompose into two radicals when energy is provided in the form of ultra violet (UV) light or heat. In the case of azo-initiators, each one of these radicals is active and able to react with a monomer. SIP with an azo-initiators would thus lead to anchored radicals on the surface but also to radicals in solution. The latter is not a favorable condition for obtaining thin polymer films but when proper polymerization conditions are used films can still be obtained. The conditions should be set to avoid potential interactions between growing surface macro-radical species and growing solution macro-radical species. This explains why short time polymerization and diluted monomer mixtures are used for SIP with azo-initiators. For example, Piacham et al. have coupled 2,2 -azobis(2-amidinopropane) onto a gold surface and synthesized a thin MIP film for S-propranolol.61 Similarly, Lotierzo and colleagues have coupled 4,4 -azo-bis(cyanovaleric acid) on a gold surface in order to initiate the synthesis of a MIP with domoic acid as template molecule.42 Both films were successfully used for sensors, with QCM and SPR transducers, respectively. These initiators were coupled to the gold surfaces via self-assembled monolayers (SAMs), which is convenient since homogenous and well-defined surfaces are obtained. A potential problem is that the Au-S bond is quite labile under the influence of UV light or heat.62 The thickness of the obtained films depends on the monomers used, their concentration, the initiator, the surface coverage of the initiator, and the polymerization time. Normally, a thickness of 30 to 100 nm will be desired, although it is possible to synthesize much thinner films of just a few Angstr¨om.63 The presence of the template molecule also influences the film thickness as shown by Piacham et al. Their S-propranololimprinted films were 30 nm thick whereas the nonimprinted control films synthesized under the same condition had a thickness of 6 nm.61 Replacing free radical polymerization with controlled/living radical polymerization should permit a better control of the polymerization process. In controlled/living radical polymerization, only one
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
of the formed radicals is able to initiate the polymerization. The other radical is called dormant and merely acts as a terminating species. So when initiating SIP using controlled/living radicals, there is no formation of radical species in solution and macro-radicals are only growing from the surface. When the polymerization is turned off (e.g., by turning off the UV light source), dormant radicals recombine with the growing macro-radicals. This reaction is reversible and a reinitiation of the polymerization reactivates the growing radicals. This “living” character of the polymer chains makes it possible to graft copolymer blocks by simply reinitiating the polymerization in a new monomer mixture. Despite the above fact, the polymerization conditions still need to be optimized in order to retain control over the process.64 Controlled/living radical SIP can be achieved by atom transfer radical polymerization or by polymerization using iniferters. Both methods are based on the same homolytic cleavage of the initiator with catalysis in the first case and without catalysis in the second. Iniferters can be grafted on different materials used in sensors, such as silicon wafers, glass or gold surfaces. For the coating of glass or silicon wafers, organosilane-terminated iniferters are used, which can be coupled in situ65 or ex situ,66,67 for example by reacting p-(chloromethyl)phenyltrimethoxysilane and sodium N,N-diethyldithiocarbamate. Iniferter SIP for MIP synthesis was first used by Sellergren et al.65 who were able to build two successive MIP layers of 15 nm each on porous silica, using D- and L-phenylalanine anilide as the template. Atom transfer radical polymerization SIP has been described for polymerization on gold surfaces68,69 and silicon wafers.64 Only very few reports indicate the usefulness of this method for MIP synthesis. Husson’s group described imprinting of fluorescent templates such as N,N’didansyl-L-lysine in thin films on gold.69 The thickness of the layers were around 10 nm after 20 h of polymerization. Spin coating One of the standard coating techniques used for example in the microelectronics industry is spin coating. A drop of the film-forming solution or suspension is deposited on a flat surface that is put in rotation, spinning off excess of liquid and leaving a film that can subsequently be cured. We have
recently demonstrated that it is possible to spin coat a monomer mixture on a flat surface followed by in situ photopolymerization in the presence of a template, in order to obtain MIP films with thicknesses between 100 nm and several µm. However, with acrylic and vinyl monomers, polymerization of these films is too fast for phase separation to occur by nucleation, so that nonporous, gellike films with very low binding capacity are obtained. It is possible, thought, to accelerate phase separation by adding a linear polymer such as poly(vinyl acetate) as co-porogen. The porosity of the films can be fine-tuned via the amount and the molecular weight of the linear polymer, and their thickness via the spin rate and monomer concentration. Even surfaces covered with nanoparticles can be obtained (Figure 6).70 We found that in contrast to bulk polymers, in these systems phase separation and pore formation is by spinodal decomposition.71,72 The possible use of such spin-coated MIP films in sensors based on reflectometric interference spectroscopy has recently been demonstrated.73 Spin-coating films with molecular recognition properties have also been reported by Maier et al.74 and Yoshikawa et al.75 They used a different method where the template is entrapped via hydrogen bonding in a preformed soluble polymer (polyamide). The polymer was dissolved in an appropriate solvent in the presence of the template (amino acids or 9-ethyladenine). The spin coating resulted then in the evaporation of the solvent and the formation of films with molecular recognition sites. The films were used to detect 9-ethyladenine by SPR spectroscopy.75 Electropolymerization Electropolymerization was among the first techniques used to grow thin polymer films on surfaces. Electroactive monomers such as pyrrole or aniline are used that can be oxidized at a certain potential. This gives rise to the formation of free radicals and leads to polymerization. The factors affecting the growth of the polymer film are mainly the electrical character of the monomers, the applied electrode potential, and the reaction time. This method is very versatile and permits the coating of all kinds and shapes of conducting surfaces with films of easily controlled thickness. Although the choice of interacting monomers is more limited than with free radical polymerization, the technique has been successfully used for the imprinting
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS
5 µm
11
50 µm 0.5%
2%
4%
7.5%
1%
3%
5%
10%
1 2 3 4
µm
1 2 3 4
µm
r
Figure 6. Contact-mode AFM images of spin-coated MIP film obtained using different concentrations of poly(vinyl acetate) as co-porogen.70,71 [Image reproduced from Pichon and Haupt5 with permission Taylor & Francis, Copyright 2006.]
of templates such as amino acids, phenols, nucleic acids, or sugars. The MIP films were used in combination with electrochemical76,77 acoustic78,79 and SPR43 transducers. Nanoparticles An alternative to the above-described methods where MIPs are synthesized in situ at the transducer surface is the deposition of a preformed MIP. A relatively simple way of achieving that is the coating of the transducer surface with MIP nanoparticles. Several authors reported coating with MIP particles from a suspensions of MIP particles with the help of a second, soluble polymer acting as a glue.80–82 For example, MIP particles obtained by mechanical grinding of a bulk polymer were interfaced with a mass-sensitive transducer by spin-coating a suspension in a polyvinyl chloride solution.81 The resulting thickness of such films is more or less equal to the size of the particles used. Thus, to obtain ultrathin polymer films, the particles have to be downscaled to submicron size. Nanometer size MIP beads can be obtained by various methods, such as precipitation polymerization, or miniemulsion polymerization. Precipitation polymerization can be performed with similar prepolymerization mixtures as for bulk polymers, except that the relative amount of solvent present
in the mixture is much higher. When polymerization progresses, imprinted nano- or microspheres precipitate out of solution but do not polymerize together to form a polymer monolith. The method has the drawback that because of the dilution factor, higher amounts of imprint molecule are needed, although this may be compensated by the typically higher yields. This method has been successfully used by Ye et al. to prepare imprinted particles for binding assays.83 Wulff’s group has used an approach somewhat similar to the precipitation polymerization mentioned in the preceding text;84 however, they have diluted the prepolymerization mixture to below the critical monomer concentration, so that soluble polymer microgels were produced. These had a molecular weight in the range of 106 gmol−1 , which places them close to proteins with respect to molecular size. The same group has later refined the synthesis and been able to obtain even smaller, more compact microgels with a better imprinting efficiency and an average of one binding site per molecule.85 This was achieved via a new polymerization method where polymerization is initiated in a conventional, lowdilution imprinting mixture that is diluted to below the critical monomer concentration with a suitable solvent just before macrogelation occurs. The principle of a miniemulsion polymerization is that the polymerization is conducted in
12
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
stable oil droplets of an aqueous dispersion. The size of the oil droplets ranges from 50 to 200 nm. Miniemulsions have to be stabilized against droplet collisions and Ostwald ripening. This is achieved by using a surfactant. The size of the oil droplets obtained depends on the nature and on the quantity of the surfactant, on the presence or absence of a cosurfactant, and on the nature of the continuous and the dispersion phases. It appears that in water nonionic surfactants (e.g., Lutensol AT50) give better stabilizations than ionic surfactants (e.g., sodium dodecylsulfate (SDS).86 The monomers are mainly dispersed in the oil droplets as their solubility is low in the continuous phase. Depending on their hydrophilic or hydrophobic nature, initiators can initiate the polymerization from the inside of the droplet of from the outside. Initiators able to dissolve in both phases should be avoided. An example for a one-step miniemulsion polymerization of MIPs has been reported by the group of Tovar. The template used was bocphenylalanine, and the size of the obtained beads was 200 nm. Water was used as the continuous phase with SDS as the surfactant. The dispersed phase contained the monomers methacrylic acid and ethyleneglycol dimethacrylate, the template molecule, a cosurfactant (hexadecane) and 2-2 azo(2-methylbutyronitrile) as the initiator.87 The same process can be carried out twice to obtain core-shell nanoparticles as demonstrated by Perez and Mayes.88 Once the first emulsion polymerization finished, the obtained particles are placed in a new emulsion solution and the polymerization is initiated one more time. The particles had a 53 nm core and a shell of 10 to 20 nm depending of the polymerization conditions used. Spherical MIP nanoparticles can then be self-assembled on surfaces via one or more intermediate layers of associative polymers. This permits the creation of ultrathin films, and also allows for surface patterning.89 Layers of atrazine-MIP nanospheres have recently been used in sensors based on reflectometric interference spectroscopy.73
2.3.3 Surface Patterning
For multisensors and biochips, apart from interfacing the MIPs with the transducer in the form of
thin layers, an additional patterning of the surface is often required, for example, to obtain matrices of MIP dots. For that, two different strategies can be considered. The prepolymerization mixture can be deposited in a precise pattern on the surface and then polymerized in situ. Methods such as electropolymerization or SIP can be adapted to this purpose as mentioned in the preceding text. Patterning methods that may be used with MIPs are soft lithography, microspotting techniques, or localized polymerization. Soft lithography The soft lithography technique has been developed by Whitesides and coworkers.90 Threedimensional microchannels are molded onto the surface of a poly(dimethylsiloxane) (PDMS) soft elastomeric stamp. The stamp is placed on the surface, and by capillary action, the microchannels are filled with another material which is subsequently cured. There has been a first report on the use of this technique in combination with molecular imprinting.91 The obtained microchannels had a cross-sectional dimension of 20 × 20 µm2 . The binding properties of the surface were analyzed by using a radioligand. One of the problems is that the current imprinting recipes are not always compatible with the poly(dimethylsiloxane) stamps used for soft lithography, which tend to swell in certain organic solvents. Localized polymerization Localized polymerization can for example be done using laser light of visible or UV wavelengths. Polymerization may be initiated either photochemically or thermally as the laser beam may also cause a localized increase in temperature. Photoinitiation can be achieved by using photoradical initiators such as benzoins (e.g., 2,2dimethoxy-2-phenylacetophenone) when working at 364 nm. For visible wavelengths, quinones such as camphorquinone or eosin in the presence of amines may be used. For thermal initiation, azoinitiators (e.g., 2,2 - azo-bis(2-methylpropionitrile) are suitable. The curing depth (z spatial resolution) obtained by laser polymerization depends mainly on the polymerization time and the intensity of the laser. It has been demonstrated that singlepulse laser polymerization gives smaller curing depths (1–10 µm) than continuous wave polymerization (100 µm).92 These curing depths are well adapted for fluorescent sensing devices. However,
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS
13
was such that thicknesses of between a few micrometers and about 100 µm could be produced, depending on the number of subsequent polymerization cycles.
(a)
(b)
5 µm
200 µm
Figure 7. (a) Contact-mode AFM image of MIP dots deposited using a nanofountain pen (A. Belmont, M. Sokuler, K. Haupt and L. Gheber, Direct writing of molecularly imprinted microstructures using a nanofountain pen. Appl. Phys. Lett. 2007, 90, (in press, DOI: 10.1063/1.2730753)); (b) MIP microstructure fabricated by microstereolithography from an imprinting solution containing trimethylolpropane and trimethacrylate methacrylic acid as monomers using a 364 nm laser. [Reprinted with permission Conrad et al.94 copyright 2003, Wiley VCH.]
if optical multisensing channels are to be created, smaller curing depths are required. This can be achieved by using nonlinear optics like 2 photons polymerization.93 The obtained curing depth by this technique is around 100 nm. There is no report as yet on the use of these methods for the preparation of MIP arrays. However, continuous wave laser polymerization was used by Shea and colleagues for microstereolithography of MIPs.94 Using a 364 nm laser, they were able to draw structures with lateral dimensions in the higher micrometer range (Figure 7) of a polymer based on trimethylolpropane trimethacrylate and methacrylic acid, imprinted with an adenine derivative. They also showed that the special photoinitiator and the UVA absorber used for this process were not affecting the imprinting of their polymer. The curing depth of their system
Microspotting techniques It should be possible to apply standard microspotting techniques such as ink-jetting,95 mechanical microspotting,96 and derivatives thereof, to the deposition of MIP arrays on a surface. For example, arrays of silicon microcantilevers have been used to deposit biomolecules onto glass slides.97 The technique has recently been applied to MIPs for the first time. With fluorescein and 2,4-D as imprinting templates, arrays of MIP dots have been created and the binding of the target molecules in direct or competitive mode was visualised by fluorescence microscopy.98 Depending on the solution to be deposited, the surface and the cantilever, the diameter of the dots can vary but is normally in the higher micrometer range. For smaller dots, techniques like nanofountain pen (NFP) and dippen nanolithography (DPN) can be used. These are scanning probe microscopy techniques that have been shown to be very useful in creating nanoscale pattern of biomolecules due to their high spatial precision. DPN have been pioneered by Mirkin and coworkers. It consists of the dipping of an atomic force microscope (AFM) probe in an “ink”. The “ink” is transferred to the substrate by capillary transport.99 Inks such as solutions of proteins, polymers, or DNA have been used to create nanometric patterns. NFP have been pioneered by Lewis and coworkers.100 In this method, AFM tips are replaced by cantilevered nanopipettes. The pipettes are filled with the solution to be deposited through the back and the liquid is running to the tapered tip by capillary forces. However, it does not flow out on the surface due to its surface tension. When the pipette is placed in contact with the surface, depending on the compatibility of the two, the liquid is flowing out and minute amounts of liquid are deposited, thus creating structures of below micron size. It has been shown that nano and microscale dots and lines of MIPs can be produced with this technique.73
2.4
Outlook
MIPs have already found one application for which they are commercialized, that is, solid-phase
14
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
extraction. Other applications for which they have raised much interest lately are biosensors, and different applications in the biomedical field, such as, controlled drug release. Nevertheless, more work needs to be done to make them a real alternative or complement to biomolecules. In particular, what one hopes to achieve is the development of MIPs that contain a more homogeneous binding site population, have a higher affinity for the target analyte, and that can be routinely used in aqueous solvents. A considerable part of the current research efforts on MIPs is already dealing with these problems. In fact, some of the above-mentioned transduction methods are, apart from their use in sensors, well suited for investigating MIP-analyte interactions. All these efforts are motivated by the attractive properties of MIPs, such as, their outstanding stability, their low price, the fact that they can be tailor-made for analytes for which a biological receptor cannot be found, and that they should be easier to integrate with standard industrial fabrication processes. As far as MIP-based biomimetic sensors are concerned, in terms of sensitivity they are still somewhat inferior to biosensors. This is in part due to the fact that MIP-sensors measure only analyte binding; until now, no MIP-sensor has been described that uses an enzyme reaction for signal amplification as do certain biosensors. Thus, much work is still needed on the optimization of MIPs and their integration with transducers. It appears that the development of imprinted polymer-based sensors is just about to leave the proof-of-principle stage, and researchers are starting to address specific analytical problems and to measure real-world samples.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
REFERENCES 1. R. Arshady and K. Mosbach, Synthesis of substrateselective polymers by host-guest polymerization. Makromolekulare Chemie, 1981, 182, 687. 2. G. Wulff and A. Sarhan, The use of polymers with enzyme-analogous structures for the resolution of racemates. Angewandte Chemie International Edition, 1972, 11, 341. 3. J. U. Klein, M. J. Whitcombe, F. Mulholland, and E. N. Vulfson, Template–mediated synthesis of a polymeric receptor specific to amino acid sequences. Angewandte Chemie International Edition, 1999, 38, 2057. 4. E. Yilmaz, K. Mosbach, and K. Haupt, Influence of functional and cross-linking monomers and the amount of template on the performance of molecularly imprinted
17.
18.
19.
20.
polymers in binding assays. Analytical Communications, 1999, 36, 167. V. Pichon and K. Haupt, Affinity separations on molecularly imprinted polymers with special emphasis on solidphase extraction. Journal of Liquid Chromatography and Related Technologies, 2006, 29, 989–1023. C. L¨ubke, M. L¨ubke, M. J. Whitcombe, and E. N. Vulfson, Imprinted polymers prepared with stoichiometric template-monomer complexes: efficient binding of ampicillin from aqueous solutions. Macromolecules, 2000, 33, 5098. J. H. G. Steinke, I. R. Dunkin, and D. C. Sherrington, A simple polymerisable carboxylic acid receptor: 2-acrylamido pyridine. Trends in Analytical Chemistry, 1999, 18, 159. G. Wulff, T. Gross, and R. Sch¨onfeld, Enzyme models based on molecularly imprinted polymers with strong esterase activity. Angewandte Chemie International Edition, 1997, 36, 1962. S. Mallik, R. D. Johnson, and F. H. Arnold, Selective recognition of bis-imidazoles by complementary bismetal ion complexes. Journal of the American Chemical Society, 1993, 115, 2518. M. Sibrian-Vazquez and D. A. Spivak, Molecular imprinting made easy. Journal of the American Chemical Society, 2004, 126, 7827. T. Takeuchi, D. Fukuma, and J. Matsui, Combinatorial molecular imprinting: an approach to synthetic polymer receptors. Analytical Chemistry, 1999, 71, 285. F. Lanza and B. Sellergren, Method for synthesis and screening of large groups of molecularly imprinted polymers. Analytical Chemistry, 1999, 71, 2092. T. L. Panasyuk, V. M. Mirsky, S. A. Piletsky, and O. S. Wolfbeis, Electropolymerized molecularly imprinted polymers as receptor layers in capacitive chemical sensors. Analytical Chemistry, 1999, 71, 4609. F. L. Dickert, M. Tortschanoff, W. E. Bulst, and G. Fischerauer, Molecularly imprinted sensor layers for the detection of polycyclic aromatic hydrocarbons in water. Analytical Chemistry, 1999, 71, 4559. B. Deore, Z. Chen, and T. Nagaoka, Potential-induced enantioselective uptake of amino acid into molecularly imprinted overoxidized polypyrrole. Analytical Chemistry, 2000, 72, 3989. S. Dai, Y. Shin, C. E. Barnes, and L. M. Toth, Enhancement of uranyl adsorption capacity and selectivity on silica sol-gel glasses via molecular imprinting. Chemistry of Materials, 1997, 9, 2521. M. Glad, O. Norrl¨ow, B. Sellergren, N. Siegbahn, and K. Mosbach, Use of silane monomers for molecular imprinting and enzyme entrapment in polysiloxanecoated porous silica. Journal of Chromatography, 1985, 347, 11. R. Makote and M. M. Collinson, Dopamine recognition in templated silicate films. Chemical Communications, 1998, 3, 425. D. Y. Sasaki and T. M. Alam, Solid-state 31PNMR study of phosphonate binding sites in guanidinefunctionalized, molecular imprinted silica xerogels. Chemistry of Materials, 2000, 12, 1400. A. Katz and M. E. Davis, Molecular imprinting of bulk, microporous silica. Nature, 2000, 403, 286.
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS 21. M. Lahav, A. B. Kharitonov, O. Katz, T. Kunitake, and I. Willner, Tailored chemosensors for chloroaromatic acids using molecular imprinted TiO2 thin films on ionsensitive field-effect transistors. Analytical Chemistry, 2001, 73, 720. 22. S. W. Lee, I. Ichinose, and T. Kunitake, Molecular imprinting of azobenzene carboxylic acid on a TiO2 ultrathin film by the surface sol-gel process. Langmuir, 1998, 14, 2857. 23. H. Chen, M. M. Olmstead, R. L. Albright, J. Devenyi, and R. H. Fish, Metal-ion templated polymers: synthesis and structure of N-(4-vinylbenzyl)-1,4,7-triazcyclonanezinc(II) complexes, their copolymerization with divinylbenzene, and metal-ion selectivity studies of the demetalated resins–evidence for a sandwich complex in the polymer matrix. Angewandte Chemie International Edition, 1997, 36, 642. 24. S. Dai, Y. Shin, L. M. Toth, and C. E. Barnes, Spectroscopic probing of adsorption of uranyl to uranylimprinted silica sol-gel glass via steady-state and timeresolved fluorescence measurement. Journal of Physical Chemistry B, 1997, 101(28), 5521. 25. S. Hjert´en, J. L. Liao, K. Nakazato, Y. Wang, G. Zamaratskaia, and H. X. Zhang, Gels mimicking antibodies in their selective recognition of proteins. Chromatographia, 1997, 44, 227. 26. M. Kempe, M. Glad, and K. Mosbach, An approach towards surface imprinting using the enzyme Ribonuclease A. Journal of Molecular Recognition, 1995, 8, 35. 27. A. Rachkov and N. Minoura, Recognition of oxytocin and oxytocin-related peptides in aqueous media using a molecularly imprinted polymer synthesized by the epitope approach. Journal of Chromatography A, 2000, 889, 111–118. 28. H. Nishino, C.-S. Huang, and K. J. Shea, Selective protein capture by epitope imprinting. Angewandte Chemie International Edition, 2006, 45, 2392–2396. 29. A. Aherne, C. Alexander, M. J. Payne, N. Perez, and E. N. Vulfson, Bacteria–mediated lithography of polymer surfaces. Journal of the American Chemical Society, 1996, 118, 8771. 30. F. L. Dickert and O. Hayden, Bioimprinting of polymers and sol-gel phases. Selective detection of yeasts with imprinted polymers. Analytical Chemistry, 2002, 74, 1302. 31. S. M. D’Souza, C. Alexander, S. W. Carr, A. M. Waller, M. J. Whitcombe, and E. N. Vulfson, Directed nucleation of calcite at a crystal-imprinted polymer surface. Nature, 1999, 398, 312. 32. E. Hedborg, F. Winquist, I. Lundstr¨om, L. I. Andersson, and K. Mosbach, Some studies of molecularly imprinted polymer membranes in combination with field-effect devices. Sensors and Actuators, A, 1993, 36 – 38, 796. 33. E. Benes, M. Groschl, W. Burger, and M. Schmidt, Sensors based on piezoelectric resonators. Sensors and Actuators, A, 1995, 48, 1. 34. F. L. Dickert, O. Hayden, and K. P. Halikias, Synthetic receptors as sensor coatings for molecules and living cells. Analyst, 2001, 126, 766–771. 35. M. Tom-Moy, R. L. Baer, D. Spira-Solomon, and T. P. Doherty, Atrazine measurements using surface transverse wave devices. Analytical Chemistry, 1995, 67, 1510.
15
36. K. Haupt, K. Noworyta, and W. Kutner, Imprinted polymer-based enantioselective acoustic sensor using a quartz crystal microbalance. Analytical Communications, 1999, 36, 391. 37. C. Malitesta, I. Losito, and P. G. Zambonin, Molecularly imprinted electrosynthesized polymers: new materials for biomimetic sensors. Analytical Chemistry, 1999, 71, 1366. 38. F. L.Dickert, P. Forth, P. Lieberzeit, and M. Tortschanoff, Molecular imprinting in chemical sensing–detection of aromatic and halogenated hydrocarbons as well as polar solvent vapors. Fresenius Journal of Analytical Chemistry, 1998, 360, 759. 39. H.-S. Ji, S. McNiven, K. Ikebukuro, and I. Karube, Selective piezoelectric odor sensors using molecularly imprinted polymers. Analytica Chimica Acta, 1999, 390, 93. 40. J. Homola, S. S. Yee, and G. Gauglitz, Surface plasmon resonance sensors: review. Sensors and Actuators, B, 1999, 54, 3–15. 41. A. Kugimiya and T. Takeuchi, Surface plasmon resonance sensor using molecularly imprinted polymer for detection of sialic acid. Biosensors and Bioelectronics, 2001, 16, 1059. 42. M. Lotierzo, O. Y. F. Henry, I. Tothill, D. Cullen, M. Kania, B. Hock, and A. P. F. Turner, Surface plasmon resonance sensor for domoic acid based on grafted imprinted polymer. Biosensors and Bioelectronics, 2004, 20, 145–152. 43. J. C. C. Yu and E. P. C. Lai, Interaction of ochratoxin a with molecularly imprinted polypyrrole film on surface plasmon resonance sensor. Reactive and Functional Polymers, 2005, 63, 171. 44. J. Matsui, K. Akamatsu, N. Hara, D. Miyoshi, H. Nawafune, K. Tamaki, and N. Sugimoto, SPR sensor chip for detection of small molecules using molecularly imprinted polymer with embedded gold nanoparticles. Analytical Chemistry, 2005, 77, 4282. 45. T. Panasyuk-Delaney, V. M. Mirsky, and O. S. Wolfbeis, Capacitive creatinine sensor based on a photografted molecularly imprinted polymer. Electroanalysis, 2002, 14, 221. 46. T. A. Sergeyeva, S. A. Piletsky, A. A. Brovko, E. A. Slinchenko, L. M. Sergeeva, T. L. Panasyuk, and A. V. Elskaya, Conductometric sensor for atrazine detection based on molecularly imprinted polymer membranes. Analyst, 1999, 124, 331. 47. A. Weber, M. Dettling, H. Brunner, and G. E. M. Tovar, Isothermal titration calorimetry of molecularly imprinted polymer nanospheres. Macromolecular Rapid Communications, 2002, 23, 824–828. 48. D. Kriz, O. Ramstr¨om, and K. Mosbach, Molecular imprinting–new possibilities for sensor technology. Analytical Chemistry, 1997, 69, A345. 49. J. F. Fernandez-Sanchez, A. S. Carretero, C. CrucesBlanco, and A. Fernandez-Gutierrez, A sensitive fluorescence optosensor for analysing propranolol in pharmaceutical preparations and a test for its control in urine in sport. Journal of Pharmaceutical and Biomedical Analysis, 2003, 31, 859. 50. Y.-C. Chen, J. J. Brazier, M. Yan, P. R. Bargo, and S. A. Prahl, Fluorescence-based optical sensor design for
16
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS molecularly imprinted polymers. Sensors and Actuators, B, 2004, 102, 107–116. L. I. Andersson, A. Paprica, and T. Arvidsson, A highly selective solid phase extraction sorbent for pre-concentration of sameridine made by molecular imprinting. Chromatographia, 1997, 46, 57. J. Matsui, K. Fujiwara, and T. Takeuchi, Atrazine–selective polymers prepared by molecular imprinting of trialkylmelamines as dummy template species of atrazine. Analytical Chemistry, 2000, 72, 1810. K. Haupt, A. G. Mayes, and K. Mosbach, Herbicide assay using an imprinted polymer based system analogous to competitive fluoroimmunoassays. Analytical Chemistry, 1998, 70, 3936. S. A. Piletsky, E. Terpetschnik, H. S. Andersson, I. A. Nicholls, and O. S. Wolfbeis, Application of non-specific fluorescent dyes for monitoring enantio-selective ligand binding to molecularly imprinted polymers. Fresenius Journal of Analytical Chemistry, 1999, 364, 512. S. Kr¨oger, A. P. F. Turner, K. Mosbach, and K. Haupt, Imprinted polymer-based sensor system for herbicides using differential pulse voltammetry on screen-printed electrodes. Analytical Chemistry, 1999, 71, 3698. P. Turkewitsch, B. Wandelt, G. D. Darling, and W. S. Powell, Fluorescent recognition sites through molecular imprinting. A polymer-based fluorescent chemosensor for aqueous cAMP. Analytical Chemistry, 1998, 70, 2025. J. Matsui, M. Higashi, and T. Takeuchi, Molecularly imprinted polymer as 9-ethyladenine receptor having a porphyrin-based recognition center. Journal of the American Chemical Society, 2000, 122, 5218. M. Jakusch, M. Janotta, B. Mizaikoff, K. Mosbach, and K. Haupt, Molecularly imprinted polymers and infrared evanescent wave spectroscopy. A chemical sensors approach. Analytical Chemistry, 1999, 71, 4786. N. P´erez, M. J. Whitcombe, and E. N. Vulfson, Surface imprinting of cholesterol on submicrometer core-shell emulsion particles. Macromolecules, 2001, 34, 830. E. Yilmaz, K. Haupt, and K. Mosbach, The use of immobilized templates–a new approach in molecular imprinting. Angewandte Chemie International Edition, 2000, 39, 2115. T. Piacham, A. Josell, H. Arwin, V. Prachayasittikul, and L. Ye, Molecularly imprinted polymer thin films on quartz crystal microbalance using a surface bound photo-radical initiator. Analytica Chimica Acta, 2005, 536, 191. W. Huang, G. L. Baker, and M. L. Bruening, Surface–initiated thermal radical polymerization on gold. Langmuir, 2001, 17, 1731. L. K. Ista, S. Mendez, V. H. Perez-Luna, and G. P. Lopez, Synthesis of poly(N-isopropylacrylamide) on initiatormodified self-assembled monolayers. Langmuir, 2001, 17, 2552. A. Ramakrishnan, R. Dhamodharan, and J. Ruhe, Growth of poly(methyl methacrylate) brushes on silicon surfaces by atom transfer radical polymerization. Journal of Polymer Science Part A: Polymer Chemistry, 2006, 44, 1758. B. Sellergren, B. Ruckert, and A. J. Hall, Layer-bylayer grafting of molecularly imprinted polymers via
66.
67.
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
iniferter modified supports. Advanced Materials, 2002, 14, 1204. B. de Boer, H. K. Simon, M. P. L. Werts, E. W. van der Vegte, and G. Hadziioannou, “Living” free radical photopolymerization initiated from surfacegrafted iniferter monolayers. Macromolecules, 2000, 33, 349. T. Kobayashi, S. Takahashi, Y. Nosaka, and N. Fujii, Silane coupling agents for photografting of vinyl monomer. Preparation and properties of (N, N-Diethylamino)– dithiocarbamoylpropyl(trimethoxy)silane. Chemistry Letters, 1992, 21, 1321. J. B. Kim, W. Huang, M. L. Bruening, and G. L. Baker, Synthesis of triblock copolymer brushes by surface-initiated atom transfer radical polymerization. Macromolecules, 2002, 35, 5410. X. Wei, X. Li, and S. M. Husson, Surface molecular imprinting by atom transfer radical polymerization. Biomacromolecules, 2005, 6, 1113. R. H. Schmidt, K. Mosbach, and K. Haupt, A simple method for spin coating molecularly imprinted polymer films of controlled thickness and porosity. Advanced Materials, 2004, 16, 719. R. H. Schmidt and K. Haupt, Molecularly imprinted polymer films with binding properties enhanced by the reaction-induced phase separation of a sacrificial polymeric porogen. Chemistry of Materials, 2005, 17, 1007. R. H. Schmidt, A.-S. Belmont, and K. Haupt, Porogen formulations for obtaining molecularly imprinted polymers with optimized binding properties. Analytica Chimica Acta, 2005, 542, 118–124. A.-S. Belmont, S. Jaeger, D. Knopp, R. Niessner, G. Gauglitz, and H. Haupt, Molecularly imprinted polymer films for reflectometric interference spectroscopic sensors. Biosens. Bioelectron, 2007, (in press, DOI:10.1016/j.bios.2007.01.023). P. Maier, J. Werner-Allen, U. J. Gibson, A. Richter, and J. J. BelBruno, Scanning force microscopy study of the morphology of spin-cast molecular-imprinted nylon thin films. Surface and Interface Analysis, 2004, 36, 1340. M. Yoshikawa, M. D. Guiver, G. P. Robertson, Molecularly imprinted films derived from torlon(R) polyamide-imide. Journal of Molecular Structure, 2005, 739, 41. A. Gomez-Caballero, M. A. Goicolea, and R. J. Barrio, Paracetamol voltametric microsensors based on electrocopolymerized-molecularly imprinted film modified carbon fiber microelectrodes. Analyst, 2005, 130, 1012. H. J. Liang, T. R. Ling, J. F. Rick, and T. C. Chou, Molecularly imprinted electrochemical sensor able to enantroselectivly recognize d and l-tyrosine. Analytica Chimica Acta, 2005, 542, 83. B. S. Ebarvia, S. Cabanilla, and F. Sevilla, Biomimetic properties and surface studies of a piezoelectric caffeine sensor based on electrosynthesized polypyrrole. Talanta, 2005, 66, 145. H. H. Weetall and K. R. Rogers, Preparation and characterization of molecularly imprinted electropolymerized carbon electrodes. Talanta, 2004, 62, 329.
MOLECULARLY IMPRINTED POLYMERS AS RECOGNITION ELEMENTS IN SENSORS 80. I. Surugiu, B. Danielsson, L. Ye, K. Mosbach, and K. Haupt, Chemiluminescence imaging ELISA using an imprinted polymer as the recognition element instead of the antibody. Analytical Chemistry, 2001, 73, 487. 81. C. Liang, H. Peng, L. Nie, and S. Yao, Bulk acoustic wave sensor for herbicide assay based on molecularly imprinted polymer. Fresenius Journal of Analytical Chemistry, 2000, 367, 551. 82. B. S. Ebarvia and F. Sevilla, Piezoelectric quartz sensor for caffeine based on molecularly imprinted polymethacrylic acid. Sensors and Actuators, B: Chemical, 2005, 107, 782. 83. L. Ye, P. A. G. Cormack, and K. Mosbach, Molecularly imprinted monodisperse microspheres for competitive radioassay. Analytical Communications, 1999, 36, 35. 84. A. Biffis, N. B. Graham, G. Siedlaczek, S. Stalberg, and G. Wulff, The synthesis, characterization and molecular recognition properties of imprinted microgels. Macromolecular Chemistry and Physics, 2001, 202, 163–171. 85. G. Wulff, B.-O. Chong, and U. Kolb, Soluble singlemolecule nanogels of controlled structure as a matrix for efficient artificial enzymes. Angewandte Chemie International Edition, 2006, 45, 2955–2958. 86. K. Landfester, M. Willert, and M. Antonietti, Preparation of polymer particles in nonaqueous direct and inverse miniemulsions. Macromolecules, 2000, 33, 2370. 87. D. Vaihinger, K. Landfester, I. Krauter, H. Brunner, and G. E. M. Tovar, Molecularly imprinted polymer nanospheres as synthetic affinity receptors obtained by miniemulsion polymerisation. Macromolecular Chemistry and Physics, 2002, 203, 1965. 88. N. Perez-Moral and A. G. Mayes, Noncovalent imprinted in the shell of core-shell nanoparticles. Langmuir, 2004, 20, 3775. 89. A. Weber, S. Knecht, H. Brunner, and G. E. M. Tovar, Modularer aufbau von biochips durch mikrostrukturierte abscheidung von funktionellen nanopartikeln. Chemie Ingenieur Technik, 2003, 75, 437.
17
90. Y. Xia and G. M. Whitesides, Soft lithography. Angewandte Chemie International Edition, 1998, 37, 550. 91. M. Yan and A. Kapua, Fabrication of molecularly imprinted polymer microstructures. Analytica Chimica Acta, 2001, 435, 163. 92. N. Fang, C. Sun and X. Zhang, Diffusion-linited photopolymerization in scanning micro-stereolithography. Applied Physics A, 2004, 79, 1839–1842. 93. S. Kawata, H.-B. Sun, T. Tanaka, and K. Takada, Finer features for functional microdevices. Nature (London), 2001, 412, 697. 94. P. G. Conrad, P. T. Nishimura, D. Aherne, B. J. Schwartz, D. Wu, N. Fang, X. Zhang, and M. J. Roberts, Functional molecularly imprinted polymer microstructures fabricated using microstereolithography. Advanced Materials, 2003, 15, 1541. 95. A. P. Blanchard, R. J. Kaiser, and L. E. Hood, High-density oligonucleotide arrays. Biosensors and Bioelectronics, 1996, 11, 687. 96. M. Schena, D. Schalon, R. W. Davis, and P. O. Brown, Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270, 467. 97. P. Belaubre, M. Guirardel, G. Garcia, J. B. Pourciel, V. Leberre, A. Dagkessamanskaia, E. Tr´evisiol, J. M. Fran¸cois, and C. Bergaud, Fabrication of biological microarrays using microcantilevers. Applied Physics Letters, 2003, 82, 3122. 98. F. Vandevelde, T. Le¨ıchl´e, C. Ayela, C. Bergaud, L. Nicu, and K. Haupt, Direct patterning of molecularly-imprinted microdot arrays for sensors and biochips. 2007, Langmuir (in press). 99. R. D. Piner, J. Zhu, F. Xu, S. Hong, and C. A. Mirkin, “Dip-Pen” nanolithography. Science, 1999, 283, 661. 100. A. Lewis, Y. Kheifetz, E. Shambrodt, A. Radko, and E. Khatchatryan, Foutain pen naochemistry: atomic force control of chrome etching. Applied Physics Letters, 1999, 75, 2689.
15 Aptameric Biosensors Anat Meir,1 Robert S. Marks2 and Milan N. Stojanovic3 1
Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel 2 Department of Biotechnology Engineering and National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel and 3 Department of Medicine, Columbia University, New York, NY, USA
1 INTRODUCTION
Aptamers, derived from the Latin word “aptus”, meaning “to fit”,1 are synthetic single-stranded DNA or RNA molecules that can bind with high affinity and specificity to their non–nucleic acid target molecules. The artificial nucleic acid ligands can be generated against proteins, small molecules, ions, whole cells, tissues, and organs.2–5 The process to select aptamers, known as in vitro selection and amplification or SELEX (from Systematic Evolution of Ligands by EXponential enrichment), was first reported in 1990 independently by two research teams.1,6 The process of aptamer isolation, their affinity properties and applications thereof are described. In addition, the particular case of how structural changes in aptamers can be used to construct fluorescent molecular sensors coupling both recognition and signaling properties is explained and their use finally as recognition elements in various platforms of biosensors are illustrated.
2 ISOLATION OF APTAMERS
The SELEX process (Figure 1) starts with a singlestranded large library of randomized sequences of oligonucleotides. Each oligonucleotide consists of
a central region of a random sequence (typically between 30 and 80 nucleotides) flanked on each end by a constant sequence, used in PCR amplification. It is impossible to cover all possible sequences in a selection (e.g., for a random region of 40 nucleotides, 440 different sequences are possible), and typical selections use 1013 –1014 unique and amplifiable sequences. This library is exposed to a target for selection (e.g., affinity material containing target proteins or small molecules, or to whole cells or tissues) and selected library members are “fished out” through their binding to the target. The bound nucleic acids are then released and amplified by RT-PCR (for RNA libraries) or PCR (for DNA libraries), to obtain a pool of nucleic acids enriched for those that bind the target. This process can be repeated arbitrarily for a number of cycles, usually, until the large part of a random pool displays satisfactory binding properties. Most often, between 8 and 20 cycles of selection and amplification are required until the target-interacting sequences dominate the population and the desired aptamers can be generated from an initial library. It is often necessary to perform a preselection, or negative selections, in which library members that bind to affinity material in the absence of the target molecule are eliminated. Otherwise, they may dominate the pool.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
5′
T7 promoter Constant region
Random sequence Synthetic DNA poll
3′ Constant region
PCR Transcription
Target
Amplification
RNA poll Incubation of target and RNA Elution of RNA
Parting of binding from non binding species
Figure 1. Scheme of the in vitro selection of an RNA aptamer (SELEX). A library of DNA oligonucleotides containing a portion of randomized sequence is synthesized. The library is then converted into dsDNA by PCR and into RNA by in vitro transcription using the T7 RNA polymerase. After incubation of the target analyte, the nucleic acid pool, the nonspecific or low-affinity binding nucleic acid molecules are removed by washing steps and the captured RNA molecules are eluted, recovered, and amplified by RT-PCR to obtain a newly enriched DNA library. The whole cycle is repeated until a specific population of RNA is obtained, which is finally isolated and characterized. [Reproduced by permission of Elsevier from Tombelli, S., Mascini, M., Biosensors and Bioelectronics, 20, 2424–2434 (2005).]
In the first cycles of selection the nonspecifically bound sequences (i.e., background) dominate the selection. Only after several cycles will specific binders take over the pool. The experimentalist can select various parameters to control both the stringency of selection and the affinity of aptamers. For example, by reducing the amount of target ligand displayed in the column made of affinity materials and by prolonging washing of weak binders, one can increase the affinity of selected library members. However, one has to be balanced. The sequences with higher affinity are rarer in the original pool and can be sometimes missed. Performing low stringency experiments leads to a larger selection and weaker affinities. Interesting variations of the SELEX procedure can be developed to suit targeted applications. To give just one example, in a preclinical evaluation in animals, species
cross-reactivity is required and aptamers targeting both animal and human target proteins are obtained by “Toggle-SELEX”.7 Manual SELEX procedures take weeks to complete. An automated SELEX process can be conducted in days, as first reported in 19988 and later modified9–11 in the high-throughput SELEX automation.12,13 Aptamers obtained through the automated selection have similar properties to those produced through manual in vitro selection,14,15 as described in a report of an automated protocol12 that was designed to mimic a manual in vitro selection. This particular protocol allows the isolation of highaffinity aptamers through on-line monitoring with adjustments of various parameters such as selection conditions (stringency or incubation times), and including on-line monitoring of the amplification step.
3 PROPERTIES OF APTAMERS
Aptamers can bind molecular targets with affinities and specificities that match, and sometimes even exceed, those of antibodies. Some examples of strikingly high-affinity constants include subnanomolar affinities of 2 -aminopyrimidinemodified RNA aptamer targeting a vascular permeability factor/vascular endothelial growth factor16 (Kd = 2.4 ± 0.5 nM), 2 -fluoro-modified RNA aptamer binding the human keratinocyte growth factor17 (Kd = 3 pM), a DNA aptamer for plateletderived growth factor-AB18 (Kd ≈ 10−10 M) as well as D-vasopressin binding aptamer19 (Kd = 560 pM). Aptamer binding to small molecules is, with some exceptions,20 more challenging a task than binding proteins, with affinities rarely exceeding micromolar scales. Judicious choice of selection conditions can yield informationally complex and rare, but extremely tightly binding, aptamers, with tailored kinetic properties. For example, Szostak and colleagues described a systematic study of tightly bound RNA aptamers to GTP, with some having low nanomolar values for Kd .21 Aptamers often excel in binding specificities, with the historic example of the anti-theophylline RNA aptamer22 that displays a 10 000-fold discrimination against caffeine (which differs only by a methyl group), or the anti-L-arginine RNA aptamer that exhibits a 12 000-fold affinity over D-arginine.23
APTAMERIC BIOSENSORS
The aptamers bind their targets by adaptive binding, as discussed in the section on fluorescent sensors. Thus, small molecules usually become an integral part of a three-dimensional structure, which would not even exist without them being incorporated. In the case of proteins, the oligonucleotide combines with the protein into a larger molecular structure.24 Aptamers offer several advantages over antibodies. Polyclonal antibodies are isolated after immunization of animals, while monoclonal antibodies require hybridomal selection. Aptamers are usually isolated through an in vitro procedure, and, because the selection and amplification processes can be uncoupled, they can be easily adapted to completely nonphysiological conditions and against targets that would otherwise be invisible to the immune system. The conditions of their selection process can be adjusted to change their kinetic parameters of aptamers (i.e., kon and koff rates). Other advantages include the ability of aptamers to denature and refold easily, with better shelf life and with ease of attachment of modified functionalities. The advantage of having a recognition region that can refold numerous times has been recently effectively demonstrated in a microarray application,25 where denaturing conditions (e.g., with 7 M urea) were used to regenerate free aptamers that were refolded into their active conformations in the binding buffer after the measurement was completed. Such a procedure allows multiple measurements with the same aptamer. Another advantage with a great promise for the therapeutic application is that an oligonucleotidebased aptamer-specific antidote can be easily designed to reverse the inhibitory activity of a drug. Clearance rates of aptamers are usually much faster than that of antibodies, which, depending on applications, can be considered either beneficial (e.g., in radio imaging) or a drawback (e.g., in the treatment of drug abuse with peripheral blockers). Aptamers share a serious limitation with all other nucleic acid–based tools: degradation by nucleases in biological fluids inactivates them within seconds to minutes.26,27 In order to increase their resistance to degradations and their halflife in biological fluids,28 aptamers can either be modified by postselection29–31 or selections can be performed with modified nucleotides compatible with the enzymes used in the SELEX process.32–34
3
4 MISCELLANEOUS ANALYTICAL APPLICATIONS
Therapeutic applications of aptamers, in which aptamers serve as drugs or as tools for target validation or drug discovery, have been reviewed extensively,4,15 and will not be discussed herein, unless there is an overlap with analytical applications. The use of aptamers in the construction of biosensors relies on their specificity and its coupling to the generation of a measurable signal is discussed.
4.1
Chromatography
Aptamers can be immobilized onto carrier materials and used in separation techniques such as affinity chromatography,35–37 where they may excel in enantiomeric recognition and separations, although the issue of cost-effectiveness of using aptamers in this application seems unresolved.3–5
4.2
Capillary Electrophoresis
Capillary electrophoresis (CE) separates analytes in a capillary manner, using the same mechanism of the standard electrophoresis technique. Aptamers can be separated from the aptamer–analyte complex, as they may undergo structural transition or size/mass changes during the aptamer–target interaction that results in changes in electrophoretic patterns. A fluorescently labeled DNA aptamer was used to detect and quantify human immunoglobulin E (IgE) in affinity probe capillary electrophoresis with laserinduced fluorescence (CE-LIF), and similar conditions were applied for thrombin detection.38 CE can be introduced into in vitro selection and amplification as a separation technique,2,3,5,39 leading potentially to a single-step SELEX.40
4.3
Mass Spectrometry
The selective capture and detection of proteins in affinity matrix–assisted laser desorption/ionization mass spectrometry using aptameric substrates was
4
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
demonstrated.41 This method can be used in proteomic analysis and other affinity-based protein purification processes. The capture and detection of small-molecule ligands using electrospray ionization mass spectrometry has also been reported.42
4.4
Flow Cytometry
Aptamers have strong potential in the field of cytomics, as they can be attached to fluorescent reporters or nanoparticles, allowing simultaneous multiparameter analysis of cells and microsphere particles, including the function and the biological, physical, or chemical characteristics.2,43,44
founded on the basis of arrays of “photoaptamer” (isolated through Photo-SELEX)51 and in this case high degree of multiplexing was achieved.
5 COUPLING OF RECOGNITION PROCESS TO SIGNAL GENERATION IN APTAMERS
In this section we focus on the molecular events that lead to the coupling of recognition events to changes in fluorescent properties, while in the next section, we discuss other common transducing elements including optical, electrochemical, or mass-sensitive devices.
5.1 4.5
ELISA-like Assays
Aptamers can substitute antibodies in analytical and diagnostic ELISA-like assays.45,46 We will not discuss such efforts further, except to mention an original solution-phase variation of sandwich assays known as proximity ligation assay. Binding of two DNA aptamers to a target protein enhances enzymatic ligation of the oligonucleotides attached to these aptamers. The principle behind proximity ligation is general, and any two recognition regions can be used in place of aptamers.47 The ligation products can be selectively PCR-amplified (in real time) and this can lead to zeptomolar concentration detection of proteins (e.g., cytokine platelet-derived growth factor—PDGF).48
4.6
Aptameric Arrays
The aptameric arrays are natural next steps after the widespread adoption of DNA microarrays for genetic analyses and diagnostic assays. One recent demonstration used four aptamers (antilysozyme, antiricin, anti-IgE, and antithrombin), immobilized on coated glass slides,49 achieving effortless multiplex detection. Some microarrays were directly compared to antibody-coated chips with superior results in terms of sensitivity and specificity (e.g., protein detection of IgEs and thrombin in a model system).50 At least one company (Somalogic) was
Stochastic Introduction of Fluorophores
Mere coupling of a fluorophore to an aptamer close to a ligand binding site is by itself not sufficient to yield an aptameric sensor. Despite very detailed knowledge of the solution-phase structures for several aptamers, we are still unable to predict whether the introduction of a fluorophore at a particular site would provide a basis for good signaling or not. Aptamers, particularly those binding small molecules, undergo so-called adaptive binding,24 which means that without their ligand they form poorly defined structures, which rearrange into more rigid structures (“tighten”) upon ligand binding, with ligands becoming an integral part of the whole structure, which would otherwise not even exist without the binding event. This usually means that a stochastic covalent attachment of fluorophores in the vicinity of binding sites is bound to produce some conjugates in which the fluorophore will be able to signal the binding event, by essentially signaling the change in the environment, as first reported by the successful construction of two sensors for ATP based on stochastic probing of corresponding RNA and DNA aptamers with fluorophores.52 The response of these sensors was modest, but they still represented an important breakthrough, and other groups were inspired to attempt similar approaches.53,54 While the mechanism of signaling was not discussed in sufficient detail, at least in the case of a fluorescein derivative of a DNA aptamer (Figure 2a), it seems to be
APTAMERIC BIOSENSORS
F
G A G T A
T G G A 5′ G G C G T G A C C T G A G A T G G A A G (a) 5′
F
G C T A C G G G T A CT C A A G C G C
(b)
F
G
C D A T C GG G T A T C A A G C G C
F C
D
G C T A C G G G T C A T C A A G C G C
(c) Figure 2. (a) ATP aptamer with fluorescein as a linker signals the presence of adenosine in solution. (b) Cocaine-binding three-way junction derivatized with fluorescein signal binding of cocaine, with up to threefold increase in fluorescence. (c) The bis-labeled cocaine-binding three-way junction signals the presence of cocaine with stem formation and decrease in fluorescence.
related to quenching of fluorescence by the G-rich environment of this aptamer.55 A similar approach, with different chemistries of conjugation, was used on a cocaine/steroid-binding three-way junction (Figure 2b).53 Conjugation of fluorescein to virtually any available position surrounding the binding pocket yielded sensors with good signaling properties and up to threefold increase in fluorescence (even in diastereomeric mixtures of sensors obtained by using coupling of 6-iodoaceamido fluorescein with phosphorothioates). Systematic structural studies indicate that contiguous G’s are needed for the strong response. Using BODIPY DIPY rromethene BOron Difluoride dyes and 2 -amino analogs of bases consistently yields sensors for a series of aptamers.54 The introduction of a fluorophore into the vicinity of the binding site is usually intrusive and
5
changes the most stable conformation of a ligandless aptamer to account for the newly acquired functionalities. Such changes almost invariably lead to a weaker binding between ligand and fluorophore-modified aptamer, in comparison to the binding of the original structure. Finally, in order to directly select aptamers for signaling, Ellington and colleagues reported the successful selection and amplification process with uridine substituted with a fluorophore-containing derivative.56 In the final stage of selection they screened library members for changes in fluorescence in the presence of adenosine and analyzed those that showed satisfactory response. The authors hoped that the fluorophore would be incorporated as an essential part of the binding pocket and that the adaptive binding would lead to significant structural changes in the hydrogen bonding networks/hydrophobic interactions of the fluorophore, perhaps leading to excellent signaling and strong binding at the same time. While they were successful in directly generating aptameric sensors for ATP, with better binding and signaling properties than those in the stochastic process, other fluorophores were able to substitute fluorescein, indicating that the fluorophore was not crucial for the binding pocket formation.
5.2
Terminal Introduction of Fluorophores and Quenchers
One can readily assume that the addition of a fluorophore at the 5 end of an aptamer and quenchers on the 3 end would yield successful sensors, for as long as the ends come together in a binding event. Such an approach would be conceptually related to molecular beacons,57 which have terminally positioned fluorophore–quencher couples, and such sensors are often called beacon sensors. We note that ATP and cocaine aptamers have both ends tied into stems, thus they are unlikely to change the spatial arrangement of the fluorophore–quencher couple upon binding, without further modification to their structures (Figure 2c). By shortening the terminal stem of the cocaine aptamer, we destabilized it. End-labeling of this construct with a quencher and a fluorophore resulted in a sensor for cocaine, with fluorescent quenching indicative of cocaine-induced formation of the shortened stem.58 The sensor was selective for cocaine
6
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
over its enzymatic hydrolysis products. Interestingly, the sensor equally accepted the cocaine enantiomer, indicating the carbomethoxy group did not participate in the binding. However, the response of both this aptameric sensor (quenching down to 60% of original fluorescence) and that of a corresponding ATP sensor (only 20% quench) were disappointing. Independent work on a similar design with thrombin59 and PDGF60 aptamers demonstrated that “molecular beacon aptamers” can serve as a real-time detection system with, perhaps, potential to visualize changes in living cells (Figure 3a). In a conceptually different approach,61 an aptamer with two different conformations was designed—one with a stem stable without ligand and the other with this stem broken up by a ligand binding event and alternative stem formation (Figure 3b). This sensor is a true molecular beacon, lighting up in the presence of thrombin, and it is becoming the standard for the field in rational design, with
T 5′
F
T
G
G
T T
D
T
G
G
G G
G
T
T
G
G
T T T G G G F G T G G D T G G T T G T
T
(a)
T
G G
T
T
G
G
T G
5′ F
C G
G
Q
T T GT G GG G G
T
C
A
T
A
C G
A
G
G G
T T T G
A
C
T
extensive use of folding programs for free energy calculation of alternative conformations.
5.3
Bimolecular Formats
The first series of aptameric sensors, based on a combination of aptamers and molecular beacons targeting these aptamers,2,62 showed that addition of a ligand influences the equilibrium between free aptamer, aptamer-bound to beacon, and aptamer bound to ligand (Figure 4). Only the knowledge of the primary sequence is needed to construct them. The response and sensitivity of sensors seem impressive, and the potential for multicolor detection is strong. This method seems to be the most general of all reported methods, and might be particularly suitable for tightly bound protein ligands. A different design, named structure-switching sensors (Figure 5), also relies mostly on the knowledge of the primary sequence for its construction (although knowledge of the secondary structure is obviously helpful).63,64 This design requires an extension of the aptamer sequence in order to accommodate complexes with two additional oligonucleotides (one with a fluorophore and the other with a quencher). With a prudent choice of sequences, and some optimization, the design seems to be general, and the response excellent, such as for both a thrombin and an antiadenosine sensor,63,64 and there is a good potential for multicolor detection with these sensors. The original aptamer and the sensors show visible selectivity for the phosphorylation level of adenosine, with applications for detection of the inhibition of various enzymes using ATP or hydrolyzing phosphate
F
C
Q
C
+
F
(b) Figure 3. (a) Bis-labeled thrombin (F, fluorescein; D, dabcyl quencher) binding G-quartet signals thrombin binding with a decrease in fluorescence. (b) Stanton’s molecular beacon undergoes conformational change upon thrombin binding, leading to an increase in fluorescence.
F Q Q Figure 4. The complex of an open molecular beacon and an aptamer exists in equilibrium with the free aptamer and beacon with closed stem-loop structures. The presence of a ligand (usually protein) shifts this equilibrium toward a closed stem-loop structure, with concomitant decrease in fluorescence.
APTAMERIC BIOSENSORS
7
G A G T A C C T G C C A C G C T C C G C T C A C T G A C C T G G G G T G C G T G G A C G G T G C G A G G C G G T G A C T G G A C C C C G F Q A G G A G A T G Figure 5. The ATP aptamer (bold font) can be engineered into a “structure-switching” tripartite complex. Binding of ATP to the aptamer region shifts the equilibrium toward a bipartite complex without the quencher, leading to an increase in fluorescence.
groups.64 Somewhat similar principles were used to release quenching oligonucleotides from quantum dots.65 The variation on structure-switching aptamers was also adapted to achieve the first general colorimetric sensing, attaching individual components to gold nanoparticles.66 Nutiu and Li introduced an ingenious method for the direct selection of sensors that switch structures. A library of random oligonucleotides is displayed on the column through attachment to the captured oligonucleotide, complementary to the constant region flanked by two random regions. Addition of a ligand causes formation of a binding pocket between two random regions, with the concomitant extrusion of the capture oligonucleotide, and the released aptamer can be collected and amplified. The selected member of the library can be easily modified to achieve sensing. In a proofof-concept demonstration,67 the authors isolated structure-switching aptameric sensors for ATP and GTP, although, interestingly, their procedure did not work for CTP and UTP. This likely does not indicate the limitation of their method, but just the limitation of a library they used in selection, that had short random regions. Interestingly, for the ATP sensor, the authors reported the isolation of a motif corresponding to the previously isolated anti-ATP aptamer. This method represents one of the first potentially general approaches to the selection and amplification of aptamers without the use of affinity material; instead the ligand is used only in solution, and this minimizes chances of artifacts, which are occasionally observed during selection under standard conditions. In the previous two cases we could, in principle, at least, rely mostly on primary structure. Once we have some idea of the secondary structure, we have the option to construct the so-called self-assembling sensors. The first report of this
type of sensors68 (as a matter of fact, first ever report of any aptameric sensors using fluorescent intensity) described a procedure to split an antiTAT aptamer into two shorter oligonucleotides and to incorporate into one of them several more nucleotides, a fluorophore, and a quencher, in order to induce a beaconlike switch. Inspired by reports of antibody-based selfassembling sensors (“open sandwich immunoassay”),69,70 we took aptamers for cocaine, ATP, and thrombin (unpublished) and separated them into two shorter oligonucleotides, one labeled with a fluorophore and the other with a quencher (Figure 6).71 Addition of ligand to these oligonucleotides would cause quenching, apparently due to stabilization of an unstable aptamer structure by ligand binding, a process that brings the fluorophore and quencher into proximity. Multicolor detection of up to three analytes was studied in our system, with some measure of success, although there was some cross talk between channels at the higher concentrations of some ligands, most likely due to nonspecific G A G T A T G G + A T A T A C C T G G A G G C G A A T T G A A T A T G G A A G T T A D A
R
G A G T A T G GA G G C G A A A T A C C T G G T T A AG A A T A T G G A A G T A T T D A
R
Figure 6. In self-assembling sensors, the presence of an analyte stabilizes the bipartite form. [Reproduced by permission of American Chemical Society from Danke Xu, et al. Analytical Chemistry, 77, 5107–5113 (2005).]
8
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
interactions. The major drawback of our system was in reporting binding events by quenching, which reduced its sensitivity.
5.4
Aptamers with External Fluorophores
It would be quite advantageous for intracellular applications to have an approach to expressible aptameric sensors, that is, without covalently attached dyes. While there are many reports of aptamers binding dyes, a malachite green–aptamer72 complex with its aptamer73 is fluorescent, unlike the dye itself. We reasoned that if we could couple binding of malachite green to binding of another aptamer, we could construct aptameric sensors without covalently modifying an aptamer. This could lead to expressible aptameric sensors. Using a design inspired by Breaker’s work on modular nucleic acid catalysts, we constructed a series of sensors by coupling two aptamers through a bridge region74 (Figure 7). Examples of ATP, FMN, Flavin monoucleotide phosphate theophylline, and yet unpublished tobramycin and thrombin sensors show the method is likely general. One drawback of this method is that we do not know mechanistic details of the signal transduction between recognition of analytes and recognition of malachite green and that we are unable to consistently obtain the highest responses. Unfortunately, at least in our hands, malachite green has proved to be unsuitable for routine intracellular fluorescence microscopy applications. While we used the binding of a latent fluorophore to trigger fluorescence, Koide’s group A
A
U
C
G G
G
C
MG
A A U
A
A U
T
G
A G T A G G G C T A G G G G A A
A
G
G
G G C C G C A U
Figure 7. “Modular aptameric sensors” consist of two separate aptamers, one binding an analyte (in this case ATP) and the other binding to malachite green. Binding of an analyte will stabilize the malachite green–aptamer complex, which is fluorescent.
used a completely opposite approach: they constructed an aptamer binding to the quencher portion of a quencher–fluorophore couple, causing stereoelectronic effects that led to the increase in fluorescence.75 With some optimization, we believe that this method has a really strong potential for intracellular applications. Several other approaches have been reported using aptamers and noncovalently attached dyes, such as dyes that bind to cocaine aptamer while being displaced by cocaine, for the construction of the first colorimetric assay based on aptamers76 and ligands77 that displace rhodium complexes that nonspecifically bind aptamers, causing a change in luminescence in the detection of IgE at subnanomolar range. Leclerc’s group used cationic polythiophene to form aggregates with a thrombin aptamer. These aggregates show low fluorescence. The presence of thrombin stabilizes the G-quartet structure of this aptamer, breaking up the aggregates and leading to an increase in fluorescence. At higher concentrations, visual changes in color could be observed as well.78
5.5
Cross-reactive Arrays
Three-way junction-based aptamers bind steroids promiscuously, and they bind other hydrophobic molecules in general. Three-way junctions form a hydrophobic pocket from the unstacked terminal base pairs in stems.53 What possible application can a receptor with no specificity for a particular steroid have? Probably none, if we are using a single sensor. However, we can make a group of sensors with each member of this group with its own selectivity and then organize them in a cross-reactive array that would be able to obtain characteristic response patterns for individual compounds and mixtures. We took three-way junction aptamers and generated sensor analogs, varying mismatch and fluorophore positions. While a single sensor could not clearly distinguish multiple concentrations of cocaine and three steroids, the array of eight sensors in Figure 8 was able to generate characteristic fingerprints for each of the unknown solutions. The successful construction of the cross-reactive arrays raises the question whether this approach could be generalized to other types of analyte–sensor pairs. The hydrophobic analytes are
APTAMERIC BIOSENSORS
F
F
T 33
A
G
C A
32
G
G
T
C
T C
A
A
A
G
C
C
A A
T
T G
T
A C
G
A A
T
G C
A
T
A
A
C
G
G
A
C A
23
34
A
T
T
C
A
A A
G
F
A 7
G
G
T C
A
T A
T
G C
G C
G G
G
C
C
A
24
T
A
C
8
A
A
T G
G T
T C T
G A
29
G
G
T
G
C
C
A
T 25
T T25-32F33
A G
F
T
A
30
G24-32sF33
F
U
F
T
A23-32sF33
31
G
T
G
T
F 32
G
T C
fmtc-32sF33
A
31
9
T
C
A
A A
T G
G
G
T C 22
A
T 23
A
T
F 4.1-31sF32
4.1-34UF
4.1-7sF8
4.1-22sF23
Figure 8. Starting with a three-way junction structure, we can generate a series of cross-reactive sensors by moving the position of fluorophore and mismatch.
particularly suitable for cross-reactive approaches, because interactions between them and nucleic acids are not strongly directional and are based primarily on hydrophobic interactions. In this sense, the three-way junctions are closer to classical hydrophobic receptors, such as cyclodextrans, than to other aptamers. We are not aware of any other set of aptamers that could preserve binding to most of their ligands, despite numerous substitutions so close to the binding site.
5.6
Coupling of Recognition with Catalytic Activity
Another approach to visualize binding events between aptamers and their ligands is to use aptamers as allosteric regulators of nucleic acid enzymes.79–81
6 TRANSDUCING APTAMER RECOGNITION INTO A SIGNAL
In this section we discuss common transducing elements such as optical, electrochemical, and mass-sensitive devices that couple an aptamer as their biorecognition entity.
6.1
Acoustic Biosensors
Aptamers can be immobilized on the surface of quartz crystal microbalances (QCMs), or piezoelectric crystals, which convert an acoustic emission to an electrical signal. The QCM technology allows a label-free detection of molecules and is based on a frequency change of the piezoelectric crystal caused by mass changes on the sensing surface. An example of a biosensor that combines aptamers and QCM is a human IgE detector.82 A DNA aptamer against IgE83 was covalently attached to a gold-coated QCM, with the biotinylated aptamer immobilized in a dense and seemingly oriented manner through DSP (3,3 -dithiodipropionic acid-di(N -succinimidyl ester)-bound streptavidin, allowing the biosensor an extended linear measurement range, in addition to equal sensitivity and selectivity when compared to control experiments using antibodies as recognition entities. Importantly, the aptamer-coated surface could be regenerated more effectively, and it displayed better stability. Similar results were observed with HIV-1 TAT protein84 and thrombin in a flowmeasuring cell.85 Aptamers were also coupled to the surface of Love-wave sensors, which are a special type of surface acoustic wave (SAW) sensors. The
10
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
parallel detection of serine protease thrombin and Rev peptide86,87 was reported using this system, suggesting the future implementation in an array format. The results were comparable to those obtained using a Biacore 3000 system in terms of reproducibility and signal response. The specificity of the system correlated with the specificity of the antithrombin aptamer for its ligand.
6.2
Cantilever-based Biosensors
Micromechanical sensitive detection of proteins in a complex Escherichia coli mixture using a cantilever-based biosensor88 label-free detection method was developed. Aptamers specific for Thermus aquaticus (Taq) DNA polymerase were immobilized on cantilever surfaces that upon aptamer–protein interaction induced a change in surface stress that was followed by differential cantilever bending. Interferometry was used to determine the differential bending between a sensor cantilever functionalized with aptamer and a reference cantilever functionalized with a nonspecific sequence.
6.3
from an aptamer–protein recognition event. When proteins bind to the aptamer-modified electrode (demonstrated with lysozyme and an aptamerfunctionalized ITO indium tin oxide electrode), the redox marker is attracted to the surface, and this leads to a decrease in the electron transfer resistance and thus to sensitive FIS detection. An opposite effect (increase in electron transfer resistance) was used in another reported labelfree detection method, which utilized electrochemical impedance spectroscopy (EIS) and targeted human IgE92 (Figure 9). The aptamer-based system showed higher sensitivity and selectivity than a comparable antibody-based biosensor. An electronic aptamer-based biosensor for the rapid label-free detection of cocaine in complex contaminant-ridden samples was recently reported.93
Electrochemical Biosensors
Electrochemical transduction was used for the detection of thrombin by a beacon aptamer–based biosensor.89 Methylene blue (MB), an aromatic cationic dye that displays both optical and electrochemical properties, was used as an electrochemical marker intercalating in the beacon aptamer sequence. Upon target binding to the aptamer, the beacon sequence undergoes conformational change and releases intercalated MB, which causes changes in the voltammogram and a decrease of the electrical current signal. In another study,90 a sandwich-type sensing system used two aptamers to bind to different epitopes of thrombin (fibrinogen and heparin sites). The secondary aptamer was labeled with pyrroquinoline quinone glucose dehydrogenase ((PQQ)GDH), which, after glucose addition, enabled electric current measurement. An aptameric biosensor for label-free faradaic impedance spectroscopy (FIS) detection of proteins91 is based on reversed surface charge derived
(a)
(b)
(c) Figure 9. AFM images (2 × 2 µm2 ) of (a) the aptamer-modified gold surface, (b) the modified electrode after incubation with 50 nM human IgG, and (c) the modified electrode after incubation with 50 nM human IgE. [Reproduced from92 by permission of American Chemical Society.]
APTAMERIC BIOSENSORS
6.4
Optical Biosensors
Optical biosensors allow one to view target interaction with the recognition element, labeled or unlabeled, by a resultant change in an optical property. Optical biosensing readout usually consists of changes in fluorescence, fluorescence polarization, surface plasmon resonance (SPR), colorimetry (UV/VIS properties), bioluminescence, or chemiluminescence methods. We have discussed various fluorescence mix-and-measure formats in Section 5, however optical transducer-based methods are described here. A biotinylated RNA aptamer was immobilized on a fluorescence-based optic fiber to detect 94 L-adenosine in a competitive assay. In a different and earlier study, a fluorescein-labeled antithrombin aptamer attached to a glass surface was used to detect the target protein by evanescent wave-induced fluorescence anisotropy.95 The aptamer–target binding results in a change in the rotational diffusion rate. The measured fluorescence anisotropy changes as well, thus correlating thrombin concentrations with anisotropy changes. Thrombin was detected through a competitive assay with a fluorescein-labeled thrombin (F-thrombin) in a high-density fiber-optic microarray biosensor.96 An antithrombin aptamer was immobilized on the surface of silica microspheres that were distributed into the microwells of an optical imaging fiber, and its distal end was incubated with F-thrombin. An aptamer-based biosensor array for multiplex analysis of protein targets was developed employing aptamers immobilized on a glass substrate for the detection and quantification of analytes including proteins with relevance to cancer (inosine monophosphate dehydrogenase II, vascular endothelial factor, basic fibroblast growth factor) in complex biological mixtures.97 The binding to targets was measured by fluorescence polarization anisotropy. Solid- and solutionphase aptamer–target interactions were investigated including the dissociation constant, Kd , value which equally compared, proving full functionality of the surface-immobilized aptamer. In a chip-based microsphere array adapted to aptamer receptors,98 beads with immobilized aptamers were introduced into micromachined
11
wells on the “electronic tongue” array. The system consisted of a flow cell connected to a fastperformance liquid chromatograph pump for sample delivery and a fluorescence microscope for observation. Detection of labeled and unlabeled proteins was performed via F-ricin capturing by RNA antiricin aptamers or in a sandwich manner using fluorophore-labeled secondary antibody for interaction with ricin in a sandwich format. Another technique used in optical biosensors for analyzing ligand binding interactions and kinetics of specific molecules within complex mixtures is SPR. Aptamers, as have been reported for targets such as HIV-1 Rev protein, TTF1, and HIV-1 Tat protein,36,99,100 are immobilized on a chip surface. A solution of the analyte molecule flows across this surface and the molecular interaction results in changes in resonance angle. A developed approach based on the automated SELEX protocol, the Photo-SELEX,101,102 leads to the rapid availability of aptamer diagnostic arrays on solid surfaces. Photoaptamers can serve as high-affinity capture agents attached to array surfaces for the simultaneous quantitative measurements of multiple proteins in a complex sample.51 Photoaptamers contain 5 -iodo or 5 -bromo substituted bases and form by UV photoexcitation light-dependent covalent cross-links to their targets. Detection through the addition of a fluorescent dye eventually exhibits a greater sensitivity and specificity. In this diagnostic system, photoaptamers can be reproducibly bound to array substrates and readily renatured in the suitable buffer environment. A fiber-optic biosensor utilizing immobilized aptamers for the detection of ATP was investigated by the authors (unpublished data). In the designed system, previously reported structureswitching DNA aptamers63 were attached to the surface of a silane-coated optical fiber distal tip and the signal was obtained through the chemiluminescence method. A modified oligonucleotide (the aptamer domain) designated for immobilization on the fiber surface and another short complementary biotinylated oligonucleotide were used. In the absence of the target, the two oligonucleotides naturally bind, and biotin interaction with horseradish peroxidase–labeled avidin, Av-HRP (avidin conjugated with an enzyme capable of catalyzing the chemiluminescence oxidation of luminol by an oxidizing
12
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
reagent), allows the formation of a chemiluminescence signal. A signal decrease is expected in the presence of increasing concentrations of the analyte, with release of the biotinylated oligonucleotide, as the aptamer-target binding takes place, resulting in less HRP bound to the immobilized aptamer available for signal formation. The aptamer-based biosensor was examined for target detection range and specificity properties. The results indicated strongly that the aptamer is specific to its analyte and is clearly selective against GTP, CTP, and UTP (Figure 10a). A calibration curve of the aptameric biosensor signal for ATP detection was obtained. The signal intensity decreased upon increasing concentrations of ATP (Figure 10b). The structure-switching mechanism was successfully demonstrated with the immobilized aptamers as well as their specific binding recognition and sensing capabilities. Yet, the sensitivity of the
7
Normalized RLU
6 5 4
While an increasing number of research groups are using aptamers and there is a growing realization that the aptamers have strong potential, we cannot objectively say that biosensors based on aptamers have already revolutionized diagnostics. This is so, in part, because antibody-based technologies are already so well developed and suitable for most applications. However, with at least several unique and major directions of aptameric applications crystallizing, the future actually looks bright. The first track is integration of aptameric approaches with microarray technologies and application of such arrays for diagnostics and metabolomics. Another potential focus, especially after some further improvement, is mix-and-measure assays with the potential for point-of-care applications and continuous monitoring of health. Finally, nascent studies on aptamers with potential to serve as intracellular sensors indicate some potential for competition with established methods to follow intracellular processes.
2
REFERENCES
0 ATP
GTP CTP Target
(a)
UTP
2.5e + 5 2e + 5 RLU
7 PERSPECTIVES IN THE FIELD
3
1
1.5e + 5 1e + 5 5e + 4 0 0
(b)
biosensor did not rise above the solution-based approach.
0.2
0.4
0.6
0.8
1
ATP (mM)
Figure 10. Signaling specificity (a) and target detection range (b) of the ATP aptamer.
1. A. D. Ellington and J. W. Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature, 1990, 346, 818–822. 2. S. D. Jayasena, Aptamers: an emerging class of molecules that rival antibodies in diagnostics. Clinical Chemistry, 1999, 45, 1628–1650. 3. S. L. Clark and V. T. Remcho, Aptamers as analytical reagents. Electrophoresis, 2002, 23, 1335–1340. 4. D. Proske, M. Blank, R. Buhmann, and A. Resch, Aptamers—basic research, drug development, and clinical applications. Applied Microbiology and Biotechnology, 2005, 69, 367–374. 5. S. Tombelli, M. Minunni, and M. Mascini, Analytical applications of aptamers. Biosensors and Bioelectronics, 2005, 20, 2424–2434. 6. C. Tuerk and L. Gold, Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science, 1990, 249, 505–510. 7. R. White, C. Rusconi, E. Scardino, A. Wolberg, J. Lawson, M. Hoffman, and B. Sullenger, Generation of species cross-reactive aptamers using “Toggle” SELEX. Molecular Therapy, 2001, 4, 567–573.
APTAMERIC BIOSENSORS 8. P. Rudolph, J. C. Cox, and A. D. Ellington, Automated RNA selection. Biotechnology Progress, 1998, 14, 845–850. 9. J. C. Cox and A. D. Ellington, Automated selection of anti-protein aptamers. Bioorganic and Medicinal Chemistry, 2001, 9, 2525–2531. 10. J. C. Cox, M. Rajendran, T. Riedel, E. A. Davidson, L. J. Sooter, T. S. Bayer, M. Schmitz-Brown, and A. D. Ellington, Automated acquisition of aptamer sequences. Combinatorial Chemistry and High Throughput Screening, 2002, 5, 289–299. 11. J. C. Cox, A. Hayhurst, J. Hesselberth, T. S. Bayer, G. Georgiou, and A. D. Ellington, Automated selection of aptamers against protein targets translated in vitro: from gene to aptamer. Nucleic Acids Research, 2002, 30, e108. 12. D. Eulberg, K. Buchner, C. Maasch, and S. Klussmann, Development of an automated in vitro selection protocol to obtain RNA-based aptamers: identification of a biostable substance P antagonist. Nucleic Acids Research, 2005, 33, e45. 13. R. D. Jension, D. W. Drolet, D. E. Smith, D. Pratt, and B. J. Hicke, A high throughput platform for systematic evolution of ligands by exponential enrichment (SELEX). Combinatorial Chemistry and High Throughput Screening, 1999, 2, 271–278. 14. M. Blind, D. Faulhammer, and G. Mayer, Speeding up functional genomics by automated selection of intramers. Am Genomics/Proteomics Technologies, 2002, 7/8, 28–33. 15. M. Blank and M. Blind, Aptamers as tools for target validation. Current Opinion in Chemical Biology, 2005, 9, 336–342. 16. D. Jellinek, L. S. Green, C. Bell, L. A. Beebe, B. D. Feistner, S. C. Gill, F. M. Jucker, and N. Janjic, Nucleaseresistant nucleic acid ligands to vascular permeability factor/vascular endothelial growth factor. Chemistry and Biology, 1995, 2, 683–695. 17. N. C. Pagratis, C. Bell, Y. F. Chang, S. Jennings, T. Fitzwater, D. Jellinek, and C. Dang, Potent 2 -amino-, and 2 -fluoro-2 -deoxyribonucleotide RNA inhibitors of keratinocyte growth factor. Nature Biotechnology, 1997, 15, 68–73. 18. D. Jellinek, L. S. Green, R. Jenison, A. Ostman, C. H. Heldin, and N. Janjic, Inhibitory DNA ligands to plateletderived growth factor B-chain. Biochemistry, 1996, 35, 14413–14424. 19. W. G. Purschke, D. Eulberg, K. Buchner, S. Vonhoff, and S. Klussmann, An L-RNA-based aquaretic agent that inhibits vasopressin in vivo. Proceedings of the National Academy of Sciences, 2006, 103, 5173–5178. 20. R. R. Rando and Y. R. Wang, Specific binding of aminoglycoside antibiotics to RNA. Chemistry and Biology, 1995, 2, 281–290. 21. J. M. Carothers, S. C. Oestreich, J. H. Davis, and J. W. Szostak, Informational complexity and functional activity of RNA structures. Journal of the American Chemical Society, 2004, 126, 5130–5137. 22. S. C. Gill, R. D. Jenison, A. Pardi, and B. Polisky, Highresolution molecular discrimination by RNA. Science, 1994, 263, 1425–1429.
13
23. A. Geiger, P. Burgstaller, H. von der Eltz, A. Roeder, and M. Famulok, RNA aptamers that bind L-arginine with sub-micromolar dissociation constants and high enantioselectivity. Nucleic Acids Research, 1996, 24, 1029–1036. 24. T. Hermann and D. J. Patel, Adaptive recognition by nucleic acid aptamers. Science, 2000, 287, 820–825. 25. J. R. Collett, E. J. Cho, and A. D. Ellington, Production and processing of aptamer microarrays. Methods, 2005, 37, 4–15. 26. W. Kusser, Chemically modified nucleic acid aptamers for in vitro selections: evolving evolution. Reviews in Molecular Biotechnology, 2000, 74, 27–38. 27. M. Famulok, G. Mayer, and M. Blind, Nucleic acid aptamers-from selection in vitro to applications in vivo. Accounts of Chemical Research, 2000, 33, 591–599. 28. O. Heidenreich and F. Eckstein, Hammerhead ribozymemediated cleavage of the long terminal repeat RNA of human immunodeficiency virus type 1. Journal of Biological Chemistry, 1992, 267, 1904–1909. 29. P. E. Burmeister, S. D. Lewis, R. F. Silva, J. R. Preiss, L. R. Horwitz, P. S. Pendergrast, T. G. McCauley, J. C. Kurz, D. M. Epstein, C. Wilson, and A. D. Keefe, Direct in vitro selection of a 2 -O-methyl aptamer to VEGF. Chemistry and Biology, 2005, 12, 25–33. 30. L. Beigelman, J. A. McSwiggen, K. G. Draper, C. Gonzalez, K. Jensen, A. M. Karpeisky, A. S. Modak, J. Matulic-Adamic, A. B. DiRenzo, P. Haeberli, D. Sweedler, D. Tracz, S. Grimm, F. E. Wincott, V. G. Thackray, and N. Usman, Chemical Modification of Hammerhead Ribozymes. Journal of Biological Chemistry, 1995, 270, 25702–25708. 31. S. M. Nimjee, C. P. Rusconi, and B. A. Sullenger, APTAMERS: an emerging class of therapeutics. Annual Review of Medicine, 2005, 56, 555–583. 32. M. Kujau and S. Wolfl, Intramolecular derivatization of 2 -amino-pyrimidine modified RNA with functional groups that is compatible with re-amplification. Nucleic Acids Research, 1998, 26, 1851–1853. 33. M. Kubik, C. Bell, T. Fitzwater, S. Watson, and D. Tasset, Isolation and characterization of 2 -fluoro-, 2 -amino-, and 2 -fluoro- /amino-modified RNA ligands to human IFN-gamma that inhibit receptor binding. The Journal of Immunology, 1997, 159, 259–267. 34. L. Gold, B. Polisky, O. Uhlenbeck, and M. Yarus, Diversity of oligonucleotide functions. Annual Review of Biochemistry, 1995, 64, 763–797. 35. T. S. Romig, C. Bell, and D. W. Drolet, Aptamer affinity chromatography: combinatorial chemistry applied to protein purification. Journal of Chromatography B: Biomedical Sciences and Applications, 1999, 731, 275–284. 36. M. B. Murphy, S. T. Fuller, P. M. Richardson, and S. A. Doyle, An improved method for the in vitro evolution of aptamers and applications in protein detection and purification. Nucleic Acids Research, 2003, 31, e110. 37. Q. Deng, C. J. Watson, and R. T. Kennedy, Aptamer affinity chromatography for rapid assay of adenosine in microdialysis samples collected in vivo. Journal of Chromatography A, 2003, 1005, 123–130.
14
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
38. D. Buchanan, I. German, and R. T. Kennedy, Aptamers as ligands in affinity probe capillary electrophoresis. Analytical Chemistry, 1998, 70, 4540–4545. 39. A. Claire, X. Andre, and Y. C. Guillaume, Aptameroligonucleotide binding studied by capillary electrophoresis: cation effect and separation efficiency. Electrophoresis, 2005, 26, 3247–3255. 40. S. D. Mendonsa and M. T. Bowser, In vitro selection of high-affinity DNA ligands for human IgE using capillary electrophoresis. Analytical Chemistry, 2004, 76, 5387–5392. 41. L. W. Dick and L. B. McGown, Aptamer-enhanced laser desorption/ionization for affinity mass spectrometry. Analytical Chemistry, 2004, 76, 3037–3041. 42. M. M. B. Karin, M. Keller, J. Zhang, A. D. Ellington, and J. S. Brodbelt, Electrospray ionization of nucleic acid aptamer/small molecule complexes for screening aptamer selectivity. Journal of Mass Spectrometry, 2005, 40, 1327–1337. 43. A. H. B. M. Henning Ulrich and J. B. Pesquero, RNA and DNA aptamers in cytomics analysis. Cytometry Part A, 2004, 59A, 220–231. 44. H. P. Wendel, K. Guo, L. Scheideler, G. Ziemer, and A. M. Scheule, Aptamer-based capture molecules as a novel coating strategy to promote cell adhesion. Journal of Cellular and Molecular Medicine, 2005, 9, 731–736. 45. D. W. Drolet, L. Moon-McDermott, and T. S. Romig, An enzyme-linked oligonucleotide assay. Nature Biotechnology, 1996, 14, 1021–1025. 46. E. Baldrich, A. Restrepo, and C. K. O’Sullivan, Aptasensor development: elucidation of critical parameters for optimal aptamer performance. Analytical Chemistry, 2004, 76, 7053–7063. 47. S. Pai, A. D. Ellington, and M. Levy, Proximity ligation assays with peptide conjugate ‘burrs’ for the sensitive detection of spores. Nucleic Acids Research, 2005, 33, e162. 48. S. Fredriksson, M. Gullberg, J. Jarvius, C. Olsson, K. Pietras, S. M. Gustafsdottir, A. Ostman, and U. Landegren, Protein detection using proximity-dependent DNA ligation assays. Nature Biotechnology, 2002, 20, 473–477. 49. E. J. Cho, J. R. Collett, A. E. Szafranska, and A. D. Ellington, Optimization of aptamer microarray technology for multiple protein targets. Analytica Chimica Acta, 2006, 564, 82–90. 50. K. Stadtherr, H. Wolf, and P. Lindner, An aptamerbased protein biochip. Analytical Chemistry, 2005, 77, 3437–3443. 51. M. C. Chris Bock, B. Collins, J. Davis, G. Foulds, L. Gold, C. Greef, J. Heil, J. S. Heilig, B. Hicke, M. N. Hurst, G. M. Husar, D. Miller, R. Ostroff, H. Petach, D. Schneider, B. Vant-Hull, S. Waugh, A. Weiss, S. K. Wilcox, and D. Zichi, Photoaptamer arrays applied to multiplexed proteomic analysis. Proteomics, 2004, 4, 609–618. 52. S. D. Jhaveri, R. Kirby, R. Conrad, E. J. Maglott, M. Bowser, R. T. Kennedy, G. Glick, and A. D. Ellington, Designed signaling aptamers that transduce molecular recognition to changes in fluorescence intensity. Journal of the American Chemical Society, 2000, 122, 2469–2473.
53. M. N. Stojanovic, E. G. Green, S. Semova, and D. W. Landry, Cross-reactive arrays based on three-way junctions. Journal of the American Chemical Society, 2003, 125, 6085–6089. 54. E. J. Merino and K. M. Weeks, Facile conversion of aptamers into sensors using a 2 -ribose-linked fluorophore. Journal of the American Chemical Society, 2005, 127, 12766–12767. 55. J. P. Knemayer, N. Marme, and M. Sauer, Probes for detection of specific DNA sequences at the single-molecule level. Analytical Chemistry, 2000, 72, 3717–3724. 56. S. D. Jhaveri, R. Kirby and A. D. Ellington, In vitro selection of signaling aptamers. Nature Biotechnology, 2000, 18, 1293–1297. 57. S. Tyagi and F. R. Kramer, Molecular beacons: probes that fluoresce upon hybridization. Nature Biotechnology, 1996, 14, 303–308. 58. M. N. Stojanovic, P. de Prada, and D. W. Landry, Aptamer-based folding fluorescent sensor for cocaine. Journal of the American Chemical Society, 2001, 123, 4928–4931. 59. X. H. Fang, J. W. J. Li, and W. H. Tan, Molecular aptamer beacons for real-time protein recognition. Biochemical and Biophysical Research Communications, 2002, 292, 31–40. 60. A. Fang, M. Vicens, and W. Tan, Synthetic DNA aptamers to detect protein molecular variants in a highthroughput fluorescence quenching assay. Chembiochem: A European Journal of Chemical Biology, 2003, 4, 829–834. 61. A. Ellington, N. Hamaguchi, and M. Stanton, Aptamer beacons for the direct detection of proteins. Analytical Biochemistry, 2001, 294, 126–131. 62. S. G. Jayasena, L. Sumedha; Gold, Larry. Homogeneous detection of a targetthrough nucleic acid ligand-ligand beacon interaction. PCT Int.Appl. (1999), 76 pp. CODEN: PIXXD2 WO 9931276 A1 19990624 CAN 131:54725 AN 1999:405121 CAPLUS PCT Int. Appl. WO 9931276 A1. 63. R. Nutiu and Y. Li, Structure-switching signaling aptamers. Journal of the American Chemical Society, 2003, 125, 4771–4778. 64. J. M. Yu R. Nutiu and Y. Li, Signaling aptamers for monitoring enzymatic activity and for inhibitor screening. Chembiochem: A European Journal of Chemical Biology, 2004, 5, 1139–1144. 65. S. F. C. Matthew Levy and A. D. Ellington, Quantumdot aptamer beacons for the detection of proteins. Chembiochem: A European Journal of Chemical Biology, 2005, 6, 2163–2166. 66. L. Juewen and Y. Lu, Fast colorimetric sensing of adenosine and cocaine based on a general sensor design involving aptamers and nanoparticles. Angewandte Chemie-International Edition, 2006, 45, 90–94. 67. R. Nutiu and Y. Li, In vitro selection of structureswitching signaling aptamers. Angewandte ChemieInternational Edition, 2005, 44, 1061–1065. 68. R. Yamamoto and P. K. R. Kumar, Molecular beacon aptamer fluoresces in the presence of tat protein of HIV-1. Genes to Cells, 2000, 5, 389–396.
APTAMERIC BIOSENSORS 69. K. Kubota, H. Ueda, Y. Wang, K. Tsumoto, W. Mahoney, I. Kumagai, and T. Nagamune, Homogeneous noncompetitive immunoassay based on the energy transfer between fluorolabeled antibody variable domains (open sandwich fluoroimmunoassay). Biotechniques, 1999, 27, 738–742. 70. H. Ueda, K. Tsumoto, K. Kubota, E. Suzuki, T. Nagamune, H. Nishimura, P. A. Schueler, G. Winter, I. Kumagai, and W. C. Mahoney, Open sandwich ELISA: a novel immunoassay based on the interchain interaction of antibody variable region. Nature Biotechnology, 1996, 14, 1714–1718. 71. M. N. Stojanovic, P. de Prada, and D. W. Landry, Fluorescent sensors based on aptamer self-assembly. Journal of the American Chemical Society, 2000, 122, 11547–11548. 72. J. R. Babendure, S. R. Adams, and R. Y. Tsien, Aptamers switch on fluorescence of triphenylmethane dyes. Journal of the American Chemical Society, 2003, 125, 14716–14717. 73. D. Grate and C. Wilson, Laser-mediated, site-specific inactivation of RNA transcripts. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96, 6131–6136. 74. M. N. Stojanovic and D. M. Kolpashchikov, Modular aptameric sensors. Journal of the American Chemical Society, 2004, 126, 9266–9270. 75. B. A. Sparano and K. Koide, A Strategy for the development of small-molecule-based sensors that strongly fluoresce when bound to a Specific RNA. Journal of the American Chemical Society, 2005, 127, 14954–14955. 76. M. N. Stojanovic and D. W. Landry, Aptamer-based colorimetric probe for cocaine. Journal of the American Chemical Society, 2002, 124, 9678–9679. 77. Y. Jiang, X. Fang, and C. Bai, Signaling aptamer/protein binding by a molecular light switch complex. Analytical Chemistry, 2004, 76, 5230–5235. 78. H.-A. Ho and M. Leclerc, Optical sensors based on hybrid aptamer/conjugated polymer complexes. Journal of the American Chemical Society, 2004, 126, 1384–1387. 79. G. M. Emilsson and R. R. Breaker, Deoxyribozymes: new activities and new applications. Cellular and Molecular Life Sciences (CMLS), 2002, 59, 596–607. 80. S. Seetharaman, M. Zivarts, N. Sudarsan, and R. R. Breaker, Immobilized RNA switches for the analysis of complex chemical and biological mixtures. Nature Biotechnology, 2001, 19, 336–341. 81. J. S. Hartig, S. H. Najafi-Shoushtari, I. Grune, A. Yan, A. D. Ellington, and M. Famulok, Protein-dependent ribozymes report molecular interactions in real time. Nature Biotechnology, 2002, 20, 717–722. 82. B. Petersen, M. Liss, H. Wolf, and E. Prohaska, An aptamer-based quartz crystal protein biosensor. Analytical Chemistry, 2002, 74, 4488–4495. 83. T. Wiegand, P. Williams, S. Dreskin, M. Jouvin, J. Kinet, and D. Tasset, High-affinity oligonucleotide ligands to human IgE inhibit binding to Fc epsilon receptor I. Journal of Immunology, 1996, 157, 221–230. 84. M. Minunni, S. Tombelli, A. Gullotto, E. Luzi, and M. Mascini, Development of biosensors with
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
15
aptamers as bio-recognition element: the case of HIV-1 Tat protein. Biosensors and Bioelectronics, 2004, 20, 1149–1156. T. Hianik, V. Ostatna, Z. Zajacova, E. Stoikova, and G. Evtugyn, Detection of aptamer-protein interactions using QCM and electrochemical indicator methods. Bioorganic and Medicinal Chemistry Letters, 2005, 15, 291–295. M. D. Schlensog, T. M. A. Gronewold, M. Tewes, M. Famulok, and E. Quandt, A love-wave biosensor using nucleic acids as ligands. Sensors and Actuators B: Chemical, 2004, 101, 308–315. T. M. A. Gronewold, S. Glass, E. Quandt, and M. Famulok, Monitoring complex formation in the bloodcoagulation cascade using aptamer-coated SAW sensors. Biosensors and Bioelectronics, 2005, 20, 2044–2052. C. A. Savran, S. M. Knudsen, A. D. Ellington, and S. R. Manalis, Micromechanical detection of proteins using aptamer-based receptor molecules. Analytical Chemistry, 2004, 76, 3194–3198. G. S. Bang, S. Cho, and B.-G. Kim, A novel electrochemical detection method for aptamer biosensors. Biosensors and Bioelectronics, 2005, 21, 863–870. K. Ikebukuro, C. Kiyohara, and K. Sode, Novel electrochemical sensor system for protein using the aptamers in sandwich manner. Biosensors and Bioelectronics, 2005, 20, 2168–2172. Marcela C. Rodriguez, Abdel-Nasser Kawde and Joseph Wang, Aptamer biosensor for label-free impedance spectroscopy detection of proteins based on recognitioninduced switching of the surface charge. Chemical Communications (Cambridge, England), 2005, 34, 4267–4269. D. Xu, X. Yu, Z. Liu, W. He, and Z. Ma, Labelfree electrochemical detection for aptamer-based array electrodes. Analytical Chemistry, 2005, 77, 5107–5113. B. R. Baker, R. Y. Lai, M. S. Wood, E. H. Doctor, A. J. Heeger, and K. W. Plaxco, An electronic, aptamer-based small-molecule sensor for the rapid, label-free detection of cocaine in adulterated samples and biological fluids. Journal of the American Chemical Society, 2006, 128, 3138–3139. F. Kleinjung, S. Klussmann, V. A. Erdmann, F. W. Scheller, J. P. Furste, and F. F. Bier, High-affinity RNA as a recognition element in a biosensor. Analytical Chemistry, 1998, 70, 328–331. R. C. Conrad, R. A. Potyrailo, A. D. Ellington, and G. M. Hieftje, Adapting selected nucleic acid ligands (aptamers) to biosensors. Analytical Chemistry, 1998, 70, 3419–3425. M. Lee and D. R. Walt, A fiber-optic microarray biosensor using aptamers as receptors. Analytical Biochemistry, 2000, 282, 142–146. T. G. McCauley, N. Hamaguchi, and M. Stanton, Aptamer-based biosensor arrays for detection and quantification of biological macromolecules. Analytical Biochemistry, 2003, 319, 244–250. R. Kirby, E. J. Cho, B. Gehrke, T. Bayer, Y. S. Park, D. P. Neikirk, J. T. McDevitt, and A. D. Ellington, Aptamerbased sensor arrays for the detection and quantitation of proteins. Analytical Chemistry, 2004, 76, 4066–4075.
16
BIOLOGICAL AND MOLECULAR RECOGNITION SYSTEMS
99. D. I. Van Ryk and S. Venkatesan, Real-time kinetics of HIV-1 rev-rev response element interactions. Definition of minimal binding sites on RNA and protein and stoichiometric analysis. The Journal of Biological Chemistry, 1999, 274, 17452–17463. 100. M. Minunni, S. Tombelli, E. Luzi, and M. Mascini, Aptamer-based biosensors for the detection of HIV-1 tat protein. Bioelectrochemistry, 2005, 67, 135–141.
101. E. N. Brody and L. Gold, Aptamers as therapeutic and diagnostic agents. Reviews in Molecular Biotechnology, 2000, 74, 5–13. 102. M. C. Golden, B. D. Collins, M. C. Willis, and T. H. Koch, Diagnostic potential of photoSELEX-evolved ssDNA aptamers. Journal of Biotechnology, 2000, 81, 167–178.
16 Immobilization of Biomolecules by Electropolymerized Films Serge Cosnier Institut de Chimie Mol´eculaire, Universit´e Joseph Fourier, Grenoble, France
Deposition of biological macromolecules has been achieved in many different ways such as physical adsorption, cross-linking, covalent binding, and entrapment in gels or membranes. Nevertheless, the stable and reproducible immobilization of biological macromolecules on an electrode surface with complete retention of their biological activity is a crucial problem for the commercial development of biosensors. In particular, the exponential development of biochips and miniaturized biosensors implies the emergence of nonmanual methods that allow the reproducible deposition of biological macromolecules with controlled spatial resolution. Besides photopatterning, screenprinting, and spreading methods, the immobilization of biomolecules in or on electrogenerated polymer films is one of the few methods that have aroused considerable attention because of its electrochemical addressing property. Indeed, electropolymerization leads to the simple and reproducible formation of organic films with precise spatial resolution over surfaces, whatever their size and geometry. In addition, the electropolymerization process that is compatible with bulk manufacturing procedures provides an easy control over the properties of the polymeric coating such as morphology and thickness. Moreover, the polymeric films are stable in aqueous and organic solvents thus allowing biological activities in nonaqueous media. Contrary to the self-assembly method mainly based on the
strong affinity between thiols or disulfides and gold substrates, electropolymerized films can be deposited on a wide variety of electrode materials such as platinum, gold, glassy carbon, indium tin oxide (ITO)-coated surfaces, carbon felt, and so on. Moreover, the introduction of appropriated functionalities through the chemical modification of the monomer can provide polymer films with specific characteristics. Electrogenerated polymers thus constitute a powerful platform for the development of enzyme sensors, immunosensors, and DNA sensors.1–3 Thanks to the bulkiness of biomolecules and their electrostatic charge, the main strategies employed for their immobilization include simple adsorption onto polymeric films, entrapment within the polymer matrix during its electrochemical growth, covalent binding between the biomolecule and functionalized polymers, and attachment of the biomolecule by affinity interactions with the underlying film. Most of the electrochemically deposited polymer films used for biomolecule immobilization are conducting polymers like polyacetylene, polythiophene, polyaniline, polyindole, and polypyrrole (Figure 1). Owing to their conductivity, the thickness of the polymer film can be easily controlled and is not restricted to very thin films contrary to nonconducting organic polymers such as polyphenols, poly(ortho-phenylenediamine), poly
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE H N S
n
n
n
Poly acetylene
Poly aniline
R
R
Poly thiophene
O
n
n n
Poly carbazole
Poly azulene
Poly phenol R
−2e−
2
2
+
N
N
R
R R −e−
N R
N R
R N
+ 2H+
N
H
N
+
N
N
N
R
R
R
+ H
n
+
N
H
R
R + (n + 1) H+
N N R
N n+1
R
Figure 1. Structure of the main electropolymerized films and schematic representation of the electrochemical polymerization of pyrrole monomer.
(dichlorophenolindophenol), and overoxidized polypyrroles. Among the conducting polymers, polypyrrole and its derivatives play the leading role because of their versatile applicability and the wide variety of molecular species covalently linked to a pyrrole group. Initially, the development of biological sensors based on electrogenerated polymers only involved the simple entrapment of biological macromolecules into the polymer during its electrochemical polymerization. From 1986 to 1994, this concept was mainly focused on the development of various approaches of enzyme electrode fabrication, while the emergence of immunosensors remained marginal. In 1994 the first example of a DNA sensor appeared. Since then, there has been a growing interest in the development of affinity sensors such as immunosensors, DNA sensors, and,
very recently, receptor sensors. Table 1 summarizes the chronological appearance of the main concepts of biomolecule immobilization and their evolution as well as those of the transduction of biological phenomena.
1 ADSORPTION ONTO ELECTROPOLYMERIZED FILMS
The easiest way of immobilizing biomolecules is their adsorption on electropolymerized films. Owing to the instability of adsorbed enzymes, this approach was coupled to an electrochemical process of polymer doping. Initially, the electrochemical doping of polyaniline was exploited for the incorporation of negatively or positively charged
IMMOBILIZATION OF BIOMOLECULES BY ELECTROPOLYMERIZED FILMS
3
Table 1. Historical account of the evolution of biosensors based on electropolymerized films
Year
Concept
1986 1987 1988
• • • • • • • • • • • • • • • • • • • • • • •
1990
1991 1992 1994
1995 1997 1998 2000 2002 2003
2005 (a)
Reference
Enzyme entrapment in polypyrrole Electrical connection of an immobilized oxidase by incorporation of redox mediator in polymer Oxidative wiring of an immobilized enzyme by a redox polypyrrole Microbiosensor based on polyaniline (concept of spatial resolution by electrochemical addressing) Enzyme sensor based on an insulating film Entrapment of cell in polymer Covalent binding of enzymes onto functionalized polypyrrole films Entrapment of antibody in polypyrrole film Enzyme entrapment by coadsorption and electropolymerization of amphiphilic pyrrole Electropolymerization of an oligonucleotide functionalized by a pyrrole group DNA sensor elaboration by oligonucleotide adsorption onto polypyrrole films Reductive wiring of an immobilized enzyme by redox polypyrrole films Electropolymerization of peptides substituted by a pyrrole group Organic-phase enzyme electrodes based on polypyrrole films Direct monitoring of a hybridization event via the polypyrrole electroactivity Biotinylated films (polyphenol and polypyrrole) for protein immobilization via biotin–avidin bridges Entrapment of oligonucleotide in polypyrrole film as doping counter—anion Chemical binding of antibody on polypyrrole film Biofunctionalization of an optical fiber via an electropolymerized polypyrrole film Carbon nanotubes modified by oligonucleotide-doped conducting polypyrrole Photografting of enzymes on a photoreactive polypyrrole film Reversible anchoring of histidine-tagged proteins on a poly(pyrrole)-NTA(a) chelator film DNA nanosensor based on electrogenerated polypyrrole nanowire
4, 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20–22 23 24 25 26 27 28 29
NTA: nitrilotriacetic acid.
enzymes such as glucose oxidase, galactose oxidase, and peroxidase during the oxidation or reduction process of the film.30 As an extension of this earlier work, the direct adsorption of DNA probes, antibodies, and antigens onto polymers was investigated for the development of affinity sensors. In particular, recombinant antiatrazine antibody and antihuman α-fetoprotein IgG were adsorbed onto polyaniline films by cyclic voltammetry during the oxidative process. Then, the immunoreactions were detected by impedance spectroscopy or competitive immunoassays.31 Moreover, potentiometric immunosensors were elaborated by the direct adsorption of specific monoclonal antibodies on the polypyrrole surface. The determination of hepatitis B surface antigen, troponin, and digoxin was thus carried out via the formation of an enzyme-labeled immunocomplex, providing very sensitive detection limits, for instance 50 fM for hepatitis B antigen.32 The phenomena of DNA adsorption and desorption on the conducting polypyrrole surface were nicely exploited by Wang’s group for the amperometric detection of DNA and RNA in flowing streams.33 It should be pointed out that very low detection limits have been achieved, namely
3 pM of dsDNA in microliter samples. Moreover, Dong’s group has recently demonstrated that conducting polypyrrole films can be used as convenient support for the deposition of bilayer lipid membranes.34
2 ENTRAPMENT DURING THE ELECTROPOLYMERIZATION PROCESS
Since the pioneering works of Foulds et al.4 and Umana and Waller,6 entrapment in electropolymerized films remains the most popular electrochemical approach to biosensor fabrication. This simple and rapid one-step method involves the application of a suitable potential to the working electrode immersed in the aqueous solution containing both biomolecules and monomer molecules. Biomolecules present in the immediate vicinity of the electrode surface are thus physically incorporated within the growing network of the conducting polymer. It should be noted that the immobilization conditions (pH, temperature, buffer, and monomer nature) can be modulated to offer the maximum biocompatibility to the biomolecule. In addition, biomolecule
4
THE BIOLOGY – MATERIALS INTERFACE
entrapment occurs without any chemical reaction between the monomer and the biomolecule that could affect their activity. Furthermore, this method enables, via the measurement of the electrical charge passed during the polymerization process, the exact control of the thickness of the polymer layer and hence the modulation of the immobilized amount of biomolecules. Moreover, this electrochemical approach is easily applicable to a wide variety of biological macromolecules ranging from coenzymes to cells and biological tissues. In addition, the amount of immobilized biomolecules may be higher than that corresponding to the formation of a compact biomolecule monolayer. Nevertheless, insulating electropolymerized films like polyphenols, polyphenylenediamines, or overoxidized polypyrrole were also successfully used to provide interference-free glucose biosensors. In particular, the electrochemical biomolecule immobilization led to the formation of very thin films because of their self-limiting growth. These films present a restricted permeability conferring improved selectivity and antifouling properties on the enzyme electrode. Among the various polymers involved in biomolecule entrapment, polypyrrole films can be electrosynthesized in biocompatible conditions (low oxidative polymerization potential, neutral pH) and exhibit an intrinsic electronic conductivity owing to their conjugated structure. This conductivity allows the propagation step during the electrodeposition of polymer coatings and hence the successive deposition of different polymeric biolayers. This property was used for the elaboration of multienzyme configurations exhibiting heterogeneous enzyme location in the polymeric structure. For instance, three enzymes (xanthine oxidase, purine nucleoside phosphorylase, and adenosine deaminase) were sequentially entrapped in polypyrrole films generated on a microelectrode. The controlled enzyme ratio and spatial location of each enzyme markedly improve the sensing performance of the microbiosensor in the detection of purines. This method, nevertheless, usually requires, high concentrations of monomer (0.05–0.5 M) and protein (0.2–3.5 mg ml−1 ) during the electropolymerization process. These conditions may limit the applicability of such an approach to biosensor fabrication because of the cost of commercially available biomolecules. In addition, the accurate
amount of biomolecules entrapped within the polymeric network cannot be estimated by a simple difference between the biological concentrations before and after the electropolymerization step. This special feature may constitute a handicap in the optimization of multienzyme electrodes. Two alternatives were developed to overcome these drawbacks. First, small-volume electrochemical cells (0.1 ml) were designed to save significantly the amount of the biomolecule used.35 In addition, the electrodeposition of the polymer–biomolecule coating can be carried out under strict exclusion of oxygen. Another approach involved the immobilization of monomer and biomolecule together, by adsorption, on the electrode surface before the electropolymerization step. This method was based on the unusual adsorption properties of poorly soluble amphiphilic pyrrole derivatives and their capability to polymerize in the adsorbed state. The subsequent electropolymerization of the adsorbed biocoating in an aqueous electrolyte free of biomolecule and monomer, led to the physical entrapment of the adsorbed biomolecules in the “in situ”–generated polypyrrole films.13,36 This original two-step procedure allows the determination of the accurate amount of biomolecule entrapped in the polypyrrole film and, for enzymes, determination of their specific activity. In addition, this concept was extended to the electrical wiring of immobilized enzymes through the use of amphiphilic monomers functionalized by redox groups. Thus, the entrapped enzymes were surrounded by a redox polymer able to establish an electrical communication between the prosthetic site of an enzyme and the electrode surface via the phenomenon of electron hopping. For instance, nitrite and nitrate reductase were efficiently immobilized and wired by polypyrrolic films substituted by 4,4 bipyridinium groups.16 The remarkable properties for entrapping and retaining large biological entities in polypyrrole films were illustrated by the firm immobilization of banana tissue and individual human erythrocyte cells.10 However, it should be noted that the partial hydrophobic character of the host polymers could alter the three-dimensional structure of the entrapped proteins and hence decrease their biological activity. In order to counterbalance this possible detrimental effect, the modification of the organic character of the polymers was
IMMOBILIZATION OF BIOMOLECULES BY ELECTROPOLYMERIZED FILMS
attempted through the introduction of hydrophilic additives within these films. The enhancement of the hydrophilic character of the monomer and hence the polymer biocompatibility was carried out via the functionalization of pyrrole, carbazole, and thiophene derivatives by linear chains bearing ethoxy groups or by oligosaccharides such as glucosyl or lactobiomide groups. These functionalities can develop hydrogen and oxygen interactions that may stabilize the hydration layer of the protein shell. For instance, a marked improvement in biosensor stability was described for the entrapment of glucose oxidase into a poly(gluconyl-pyrrole). Another possibility for conferring a less hydrophobic character to the host polymers is the coentrapment of biomolecules and highly hydrophilic nanoparticles such as inorganic clays.37 Since the immobilized biomolecules are wrapped in a polymeric network, this design, theoretically, should not be adapted to the development of affinity sensors that require excellent accessibility of the immobilized probe. Nevertheless, the formation of antigen–antibody interactions or DNA duplex with one of the biocomponents entrapped in an electropolymerized film was successfully demonstrated by quartz crystal microbalance measurements, amperometric methods, or impedance spectroscopy.12,23,26 Owing to the bulkiness of the target biomolecules such as DNA, antibody, or virus and taking into account the assumed steric hindrances generated by the polymeric chains, it is expected that hybridization or immunoreaction mainly occurrs at the polymer–solution interface. 3 COVALENT COUPLING WITH ELECTROGENERATED POLYMERS
With the aim of improving either the recognition events between macromolecular biomolecules or the specific activity of immobilized enzymes, biomolecule immobilization on the transducer surface was attempted through the formation of a single attachment point with the underlying polymer as an alternative to biomolecule entrapment. This strategy involves the electrogeneration of polymer films bearing adequate functional groups followed by the chemical binding
5
of the biomolecule at the polymer–solution interface.11,19,24 The main advantage of this twostep method lies in the possibility of using optimal conditions for each step. In particular, the initial formation of polymer films can be carried out under conditions (organic solvents, high oxidative, or reductive potentials) that are generally deleterious for biomolecules. In addition, the covalent binding of the biomolecule to the functionalized polymer can be carried out in aqueous buffered solutions containing additives and stabilizers that preserve the catalytic activity or the recognition properties of the biomolecule. In 1991, Schuhmann et al. described for the first time the chemical attachment of an enzyme on an electrode by postfunctionalization of polymer films bearing nitro, amino, or carboxylic groups. The subsequent coupling of biomolecules to the polymer surface was carried out via a watersoluble carbodiimine. However, the presence of additional chemical reagents in the aqueous solution may partly denature the protein and/or lead to incomplete functionalization of the polymer surface. Nevertheless, this procedure, initiated in 1990, is still employed for the development of enzyme electrodes or immunosensors as recently illustrated by the covalent binding of urease or vitellogenin, a biomarker for estrogen, on poly(3aminopropylpyrrole) and poly(terthiophene carboxylic acid), respectively.38,39 DNA sensors were also developed via the covalent binding of oligonucleotides on polymer films. For instance, an electrochemical DNA sensor was elaborated from the following copolymeric film: poly(5-hydroxy-1,4naphthoquinone-co-5 hydroxy-3-thioacetic acid1,4-naphthoquinone), the carboxylic and quinone entities being used for the chemical grafting and the transduction of the hybridization event, respectively.40 With the aim of developing a “reagentless approach” to biomolecule grafting, the electrochemical polymerization of thiophene, pyrrole, and dicarbazole derivatives functionalized by easy leaving groups such as N -hydroxysuccinimide, N -hydroxyphtalimide, or pentafluorophenyl esters has led to attractive precursor polymers.19,41 The latter were efficiently applied to the elaboration of enzyme electrodes and electrochemical immunosensors and DNA sensors. It should be noted nevertheless that enzymes, owing to their bulkiness, could not diffuse into the activated
6
THE BIOLOGY – MATERIALS INTERFACE
polymer films. Thus, only the activated esters located at the polymer–solution interface reacted with the amino groups of the protein shell. Since no deactivation of the ester groups located within the polymer structure took place after soaking in aqueous protein solution, small redox mediators able to permeate through the polymeric coating could thereafter be covalently attached to the ester groups inside the film. The latter may thus bring an additional property to the biopolymer film. For instance, the chemical grafting of polyphenol oxidase (PPO) and thionine, a phenothiazine dye bearing two amino groups, to a poly dicarbazole film functionalized by N -hydroxysuccinimide groups was easily performed by successive immersion into the corresponding aqueous enzyme and dye solutions. PPO, which catalyzes the oxidation of phenols and diphenols into quinone derivatives, has been widely used for the fabrication of biosensors. The latter were mainly based on an amperometric transduction corresponding to the quinone reduction. However, these biosensors are confronted with the electrochemical generation of intermediate radicals that can inactivate the enzyme or form insulating polymer films that induce electrode fouling. The covalently bound thionine mediated the reduction of quinoid products via the simultaneous transfer of two electrons thus preventing the formation of radicals and hence induced an enhancement of the performance of biosensors based on PPO.40 Conducting polypyrrole copolymers functionalized by a redox mediator (ferrocene), itself bearing an N -hydroxyphtalimide, were also applied to the immobilization of amino-terminated oligonucleotide. The subsequent hybridization with the DNA target induced a decrease in the current density of the oxidative signal of the polymerized ferrocene groups.42 The latter may be ascribed to a reduced insertion rate of counter anions into the polypyrrole matrix during the ferrocene electrooxidation owing to steric hindrance and/or electrostatic repulsion resulting from the binding of the negatively charged DNA target. Nevertheless, it should be noted that the chemical coupling of biomolecules onto a precursor film is more time consuming than the direct and very simple procedure of entrapment. Indeed, the reaction time was between 1 and 3.5 h for DNA sensors and between 4 and 32 h for immunosensors.
A new interesting research direction in the covalent binding of biomolecules onto polymer films lies in the photografting of proteins onto electrogenerated photoreactive polymers. Such an innovative approach combines the advantages of the electroaddressing of polymer films with those of photolithography. Actually, immobilization of protein by light is topically addressable and compatible with biological functions. In addition, this reagentless procedure, based on a light-induced reaction between a photoreactive group and C–H bonds, is easily applicable to a wide variety of proteins. The electropolymerization of a pyrrole–benzophenone derivative thus provided the first example of a polymer film allowing upon irradiation (350 nm) the direct grafting of bovine serum albumin and glucose oxidase as the model of proteins.27 Several benzophenone derivatives functionalized by electropolymerizable pyrrole, vinylaniline, or indole groups and differing in the length of the spacer bridging benzophenone and polymerizable groups were synthesized and applied to the photografting of alkaline phosphatase leading to the anchoring of an enzyme monolayer.43 The validity of the photoactivable polypyrrole–benzophenone films for the immobilization of antibody or antigen by irradiation and hence for the fabrication of immunosensors was illustrated via the photochemical grafting of West Nile virus (WNV) phages. The resulting electrodes were applied to the detection of the antibody target using a sandwich assay. After the immunoreaction, the immobilized WNV antibody was recognized by a peroxidase-labeled secondary antibody. The electrochemical detection principle was based on the enzymatic generation of quinone by the peroxidase in the presence of hydrogen peroxide and hydroquinone, followed by the amperometric reduction of quinone. A calibration curve based on different WNV-antibody dilutions ranging from 10 to 106 was elaborated, demonstrating the efficiency of the photografting approach for the design of immunosensors. This procedure was also successfully used for the development of optical immunosensors. For this purpose, a thin layer of ITO was deposited on the silica surface of optical fibers to create an electroconductive surface. Then, the photoactivable polymer electrogenerated on the fiber tip was used to link a biological receptor to the end face of the optical fiber through internal light
IMMOBILIZATION OF BIOMOLECULES BY ELECTROPOLYMERIZED FILMS
irradiation. For instance, a thin layer of hepatitis C virus (HCV) as antigen was covalently bound to the benzophenone-modified surface. The optical detection of the anti-HCV protein antibody was accomplished through an indirect immunoassay configuration.44 After the immunoreaction, the subsequent binding of a marker, peroxidaselabeled IgG antihuman antibody, allowed the catalysis of a chemiluminescence reaction in the presence of luminol and H2 O2 . The target antibody was thus detected at the extremely low titer of 1 : 1 024 000 in real serum tests exhibiting higher sensitivity than Western blot and ELISA tests.
4 BIOMOLECULE ANCHORING BY AFFINITY INTERACTIONS
However, the chemical postfunctionalization mainly based on activated esters may provide nonhomogeneously substituted films with several bounds per biomolecule. In addition, the elaboration of immunosensors, enzyme sensors, or DNA sensors was limited to the anchoring of a biomolecule monolayer. In order to circumvent these drawbacks, an alternative method is replacing the chemical coupling by an affinity binding. The latter does not require additional chemical reagent and provides only a single attachment point thus preserving the activity and accessibility of the immobilized biomolecule. Moreover, biomolecule multilayers may be immobilized on an initial polymer layer bearing affinity tags. On the other hand, the well-known avidin–biotin system based on the extremely specific and high-affinity interactions between four biotins, a vitamin, and the glycoprotein avidin (association constant Ka = 1015 ) was widely used for ELISA assays. The biomolecule coupling can be achieved very easily via the simple formation of avidin bridges between biotinylated biomolecules. These strong associations close to that of covalent binding were thus extensively used for the fabrication of enzyme electrodes by the attachment of biotinylated enzymes to avidin layers previously immobilized by covalent binding or cross-linking on electrode surfaces.45,46 In addition, the immobilized avidin provided a passivation layer over the transducer surface that prevented further nonspecific adsorption of proteins on the surface. However, the reproducibility and accurate formation of
7
protein layers on electrode surfaces requires first the immobilization of a compact and fully active layer of biotin or avidin on the electrode surface. The quality of the latter (absence of manufacturing defects, chemical stability, and storage stability) and the reproducibility of its preparation govern the regularity at the molecular level and the stability of the future layer-by-layer self-assemblies. In this context, an innovative method of biomolecule immobilization elegantly combining the electropolymerization process and affinity interactions involves the electrogeneration of biotinylated polymer films that enable subsequent natural attachment of avidin. The first examples of biotinylated films were reported for the polymerization of biotin derivatives functionalized by a phenol or a pyrrole group.20–22 As expected, the electropolymerization of the phenolic monomer provided nonconductive films that blocked further film growth. Consequently, their formation was restricted to very thin films that could be removed from the electrode surface by protein coupling. In contrast, conducting and redox polymers were successfully electrogenerated from biotin moieties functionalized by a pyrrole group. The continuous growth of biotinylated films was due to the polypyrrole conductivity or the redox conductivity at high anodic potentials afforded by the RuII/III couple via the copolymerization of a polypyridinyl complex of ruthenium (II) functionalized by pyrrole groups. The efficient coupling of an avidin-conjugated enzyme or biotinylated enzyme via an avidin bridge onto these biotinylated films was illustrated by enzymatic, amperometric, and gravimetric measurements demonstrating that such polymer films provided biotin sites that were able to develop specific interactions with avidin.47–49 The binding of compact and active biological macromolecules was thus achieved using avidin–biotin interactions between biotinylated polypyrroles and biotinylated enzymes, antibodies, oligonucleotides, and even biotinylated bacteria.25,50–52 In contrast to the linear structure of biotinylated polypyrrole films, the synthesis of biotin derivatives bearing several electropolymerizable units allowed the emergence of biotinylated films with a cross-linked skeleton. For instance, the electropolymerization of a chiral biotin substituted by two carbazole groups led to a cross-linked film exhibiting stereoselective properties toward the permeation of chiral compounds.53
8
THE BIOLOGY – MATERIALS INTERFACE
These properties were exploited for elaborating enzyme electrodes displaying a better stereoselectivity than the free enzyme (Figure 2). Since biotinylated enzymes were chemically functionalized by several biotin groups, the avidin–biotin interactions were used to build multienzyme layers. Thus, the successive deposition of avidin and biotinylated enzymes on polymer surfaces has led to biosensors exhibiting amperometric performances proportional to the number of enzyme layers. This demonstrates the successive elaboration of reproducible enzyme layers on conventional disk electrodes and microelectrodes such as carbon fiber (diameter 8 µm).54 In addition, the possibility of fabricating complex biological architectures was demonstrated by the step-by-step construction of bienzyme multilayers composed of biotinylated PPO and avidin-labeled alkaline phosphatase, combining their complementary activities.55 The analytical performances of the resulting bienzyme electrodes were easily optimized through the spatially controlled positioning of each enzyme. Since polypyrrole films are mechanically stable in both aqueous and organic media, the use of bioaffine interactions was also tested in organic solvents for developing organic-phase enzyme electrodes. Thus multilayered enzyme assemblies were successfully applied to the detection of catechol in chloroform.56
N O HN H N
N O
N H
NH
S O
E L (a) Electropolymerization E C (b) Affinity anchoring T Carbazole unit R Biotinylated Avidin O monomer Biotinylated D PPO E
Figure 2. Structure of the chiral dicarbazole-biotin monomer and scheme of enzyme electrode fabrication with avidin and biotinylated polyphenol oxidase (PPO).
Besides the development of enzyme electrodes, the biotinylated polymers were also widely exploited for the design of affinity sensors following various original concepts. The biotinylated conducting polypyrroles were thus used for the fabrication of DNA sensors. In particular, the successive immobilization of avidin and biotinylated oligonucleotides on modified quartz crystals allowed the detection of hybridization events by gravimetric measurements.50 However, contrary to multilayered enzyme electrodes, the elaboration of DNA sensors was limited to the anchoring of a monolayer of biotinylated oligonucleotides. With the aim of increasing the density of immobilized oligonucleotide probes, the preparation of supramolecular avidin architectures on biotinylated films was reported through the synthesis of the first biotinylated redox spacer: a tris(bipyridyl)iron(II) complex bearing six preoriented biotin groups.57 In order to develop photochemical and electroluminescent (ECL) transductions for affinity sensors, the first example of a photosensitive biotinylated film was recently described. This biotinylated poly(tris bipyridine ruthenium complex) film allowed both the bioaffine immobilization of biotinylated proteins and the detection of their biological interactions via the change of its photoelectrochemical properties.58 For instance, the photoexcitation of this modified electrode in water, in the presence of an electron acceptor (pentaaminechlorocobalt(III) chloride), induced a cathodic photocurrent. The latter was markedly affected by the immunoreaction between an immobilized biotinylated cholera toxin and the corresponding antibody, thus allowing its quantification (Figure 3). Since specific carbohydrate–protein interactions play main roles in many biological processes, the fabrication of protein sensors via the avidin–biotin system was recently initiated by the synthesis of biotinylated-carbohydrate structures. Monovalent and tetravalent lactoses modified by biotin groups were thus immobilized on biotinylated polypyrrole films and used as recognition elements for the detection of a lectin (Arachis hypogaea agglutinin).59 The lectin binding to immobilized lactose groups was qualitatively demonstrated by impedance spectroscopy measurements, highlighting the beneficial effect brought by the clustered presentation of lactose groups. This constitutes the first example of an electrochemical sensor for the
IMMOBILIZATION OF BIOMOLECULES BY ELECTROPOLYMERIZED FILMS
9
direct detection of carbohydrate–protein interactions (Figure 4). ∆i
RURU RU RU RU RU
5 NEW TRENDS AND CONCLUDING REMARKS Antibody
RURU RU RU RU RU
Among the different concepts of biomolecule immobilization by electropolymerized films, biomolecule entrapment within polymers constitutes a versatile and powerful strategy to fabricate enzyme sensors. In addition, the redox properties of functionalized films can be exploited for the reagentless wiring of the immobilized enzymes. The great success of this electrochemical approach lies mainly in its wide immobilization capabilities: ranging from coenzyme to cell as well as to fullerene and carbon nanotubes. Although this elegant one-step procedure was mainly dedicated to biosensors, electrochemical entrapment is also successfully used for the design of DNA sensors and immunosensors. Nevertheless, biomolecule
Photogenerated current
Figure 3. The functioning principle of antibody detection by an immunosensor based on a photoelectrochemical transduction. The photocurrent is generated upon irradiation of a polypyrrole–ruthenium electrode in the presence of 15 mM [Co(III)Cl(NH3 )5 ]2+ in acetate buffer solution (pH 4.5).
O HN OH OH O HO O HO OH
OH O OH
O
H N
S
NH
S O
OH HO
OH O O HO HO
Lactose
N
N O
O
HO
Lactose
Lactose
OH O
N
N
O
O K
K
O
O S
K
K
G P
O
Lactose
P K
K O O
G O O S
NH
HN
NH
HN
O
Figure 4. Structures of biotin lactose and biotin-clustered lactose used for the detection of lectin.
O
10
THE BIOLOGY – MATERIALS INTERFACE
immobilization by affinity interactions or covalent coupling is attracting continuous and substantial attention due to the exponential emergence of immunosensors and biochips. In particular, the single attachment of the biomolecule at the polymer–solution interface by the avidin–biotin system has opened interesting perspectives in the field of affinity sensors. Moreover, this approach benefits from the commercial availability of a large variety of biotinylated and avidin-conjugated biomolecules. Although the positioning of the biomolecule at the polymer–solution interface seems to constitute a key parameter of the recognition process for affinity sensors, the presence of an intermediate avidin layer as a building block may have a detrimental effect on the sensitivity of the transduction step. Moreover, the chemical modification by biotin groups may lead to protein denaturation. An attractive perspective involves the replacement of the protein bridge by a smaller affinity system mimicking the biological avidin–biotin interactions. Among the various affinity binding systems, the interactions between histidine-tagged proteins and metals ions such as Ni2+ , Zn2+ , or Cu2+ previously complexed by immobilized chelating groups like NTA or iminodiacetic acid (IDA) were widely exploited for protein purification via column chromatography. In contrast to the avidin–biotin system, the coordinated metal ion constitutes a markedly smaller bridge than avidin. In addition, the tethering of the histidine-tagged protein is reversible via the use of stronger coordinating ligands such as imidazole and allows us to control the orientation of the immobilized protein. Cooper et al. described the first attempt at using such an affinity system by investigating the coordination properties of electrogenerated polypyrrole films N-substituted by carboxylate or imidazole groups toward Ni (II) and then histidine-tagged enzymes.60,61 However, the absence of real polymerized NTA groups made the specific immobilization of Ni (II) questionable, the observed enzyme immobilization being ascribable to electrostatic interactions. Nevertheless, the synthesis of a pure pyrrole-NTA and the electrogeneration of the corresponding poly(pyrroleNTA) chelating film allowed more recently a reversible, oriented immobilization of histidinetagged enzymes via chelated Cu2+ (Figure 5).62 Since such a strategy has never been applied to
N N
N N
O O
O O N
O O
N O (CH2)10 N n
Figure 5. Schematic representation of a quartz crystal modified by a poly(pyrrole-NTA) film with a chelated Cu2+ and a coordinated histidine-tagged protein.
the specific anchoring of antibodies or oligonucleotides, it is more likely that the development of poly(pyrrole-NTA) films will open attractive perspectives for the fabrication of affinity sensors. One possible way of combining the simplicity and rapidity of the one-step procedure of entrapment with the accessibility of biomolecule located at the polymer–solution interface may be to confer electropolymerizable properties on the biomolecule itself. Such an approach was initiated more than 10 years ago by Garnier et al. and Livache et al. for the electrogeneration of polypeptide films and poly(pyrrole-oligonucleotide) films, respectively.14,17 Although the concept of biomolecule electropolymerization was used for the development of DNA chips as a prototype of industrial processes, this electrochemical procedure cannot be extended to the immobilization of bulky proteins such as enzymes, antibodies, and antigens. This may be ascribed to the relatively small number (5–10) of pyrrole groups covalently
IMMOBILIZATION OF BIOMOLECULES BY ELECTROPOLYMERIZED FILMS
bound to the protein. A promising alternative may be the design of dendrimers consisting of electropolymerizable units, and their grafting on the protein shell.
REFERENCES 1. M. Gerard, A. Chaubey, and B. D. Malhotra, Application of conducting polymers to biosensors. Biosensors and Bioelectronics, 2002, 17, 345–359. 2. W. Schuhmann, Amperometric enzyme biosensors based on optimized electron-transfer pathways and nonmanual immobilization procedures. Reviews in Molecular Biotechnology, 2002, 82, 425–441. 3. S. Cosnier, Affinity biosensors based on electropolymerized films. Electroanalysis, 2005, 17, 1701–1715. 4. N. C. Foulds and C. R. Lowe, Enzyme entrapment in electrically conducting polymers. Journal of the Chemical Society-Faraday Transactions 1, 1986, 82, 1259–1264. 5. P. N. Bartlett, R. Whitaker, M. J. Green, and J. Frew, Covalent binding of electron relays to glucose oxidase. Journal of the Chemical Society-Chemical Communications, 1987, 1603–1604. 6. M. Umana and J. Waller, Protein-modified electrodes. The glucose oxidase/polypyrrole system. Analytical Chemistry, 1986, 58, 2979–2983. 7. N. C. Foulds and C. R. Lowe, Immobilization of glucose oxidase in ferrocene-modified pyrrole polymers. Analytical Chemistry, 1988, 60, 2473–2478. 8. H. Shinohara, T. Chiba, and M. Aizawa, Simultaneous immobilization of glucose oxidase and a mediator in conducting polymer films. Sensors and Actuators, 1988, 13, 79–86. 9. C. Malitesta, F. Palmisano, L. Torsi, and P. G. Zambonin, Glucose fast-response amperometric sensor based on glucose oxidase immobilized in an electropolymerized poly (o-phenylenediamine) film. Analytical Chemistry, 1990, 62, 2735–2740. 10. M. V. Deshpande and E. A. H. Hall, An electrochemically grown polymer as an immobilisation matrix for whole cells: application in an amperometric dopamine sensor. Biosensors and Bioelectronics, 1990, 5, 431–448. 11. W. Schuhmann, R. Lammert, B. Uhe, and H.-L. Schmidt, Polypyrrole, a new possibility for covalent binding of oxidoreductases to electrode surfaces as a base for stable biosensors. Sensors and Actuators B, 1990, 1, 537–541. 12. R. John, M. Spencer, G. Wallace, and M. R. Smyth, Development of a polypyrrole-based human serum albumin sensor. Analytica Chimica Acta, 1991, 249, 381–385. 13. S. Cosnier and C. Innocent, A novel biosensor elaboration by electropolymerization of an adsorbed amphiphilic pyrrole-tyrosinase enzyme layer. Journal of Electroanalytical Chemistry, 1992, 328, 361–366. 14. T. Livache, A. Roget, E. Dejean, C. Barthet, G. Bidan, and R. T´eoule, Preparation of a DNA matrix via an electrochemically directed copolymerization of pyrrole and oligonucleotides bearing a pyrrole group. Nucleic Acids Research, 1994, 22, 2915–2921.
11
15. D. S. Minehan, K. A. Marx, and S. K. Tripathy, Kinetic of DNA binding to electrically conducting polypyrrole films. Macromolecules, 1994, 27, 777. 16. S. Cosnier, C. Innocent, and Y. Jouanneau, Amperometric detection of nitrate via a nitrate reductase immobilized and electrically wired at the electrode surface. Analytical Chemistry, 1994, 66, 3198–3320. 17. F. Garnier, H. Korri-Youssoufi, P. Srivastava, and A. Yassar, Enzyme recognition by polypyrrole functionalized with bioactive peptides. Journal of the American Chemical Society, 1994, 116, 8813–8814. 18. L. Coche-Gu´erente, S. Cosnier, and C. Innocent, Poly(amphiphilic pyrrole)-PPO electrodes for organicphase enzymatic assay. Analytical Letters, 1995, 28, 1005–1016. 19. H. Korri-Youssoufi, F. Garnier, P. Srivastava, P. Godillot, and A. Yassar, Toward bioelectronics: specific DNA recognition based on an oligonucleotide-functionalized polypyrrole. Journal of the American Chemical Society, 1997, 119, 7388–7389. 20. S. Cosnier, B. Galland, C. Gondran, and A. Le Pellec, Electrogeneration of biotinylated functionalized polypyrroles for the simple immobilization of enzymes. Electroanalysis, 1998, 10, 808–813. 21. S. T. Yang, A. Witkowski, R. S. Hutchins, D. L. Scott, and L. G. Bachas, Biotin-modified surfaces by electrochemical polymerization of biotinyl-tyramide. Electroanalysis, 1998, 10, 58–60. 22. L. M. Torres-Rodriguez, A. Roget, M. Billon, T. Livache, and G. Bidan, Synthesis of a biotin functionalized pyrrole and its electropolymerization: toward a versatile avidin biosensor. Journal of the Chemical Society-Chemical Communications, 1998, 1993–1994. 23. J. Wang and M. Jiang, Towards genoelectronics: nucleic acid doped conducting polymers. Langmuir, 2000, 16, 2269–2274. 24. A. I. Minett, J. N. Barasci, and G. C. Wallace, Immobilisation of anti-Listeria in a polypyrrole film. Reactive and Functional Polymers, 2002, 53, 217–227. 25. T. Konry, A. Novoa, S. Cosnier, and R. S. Marks, The development of an ‘electroptode’ immunosensor: indium tin oxide-coated optical fiber tips conjugated with an electro-polymerized thin film with conjugated cholera toxin B subunit. Analytical Chemistry, 2003, 75, 2633–2639. 26. H. Cai, Y. Xu, P. G. He, and Y. Z. Fang, Indicator free DNA hybridization detection by impedance measurement based on the DNA-doped conducting polymer film formed on the carbon nanotube modified electrode. Electroanalysis, 2003, 15, 1864–1870. 27. S. Cosnier and A. Senillou An electrogenerated poly(pyrrole-benzophenone) film for the photografting of proteins. Journal of the Chemical Society-Chemical Communications, 2003, 414–415. 28. N. Haddour, S. Cosnier, and C. Gondran, Electrogeneration of a poly(pyrrole)-NTA chelator film for a reversible oriented immobilization of histidine-tagged proteins. Journal of the American Chemical Society, 2005, 127, 5752–5753. 29. K. Ramanthan, M. Bangar, M. Yun, W. Chen, N. Myung, and A. Mulchandani, Bioaffinity sensing using biologically
12
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
THE BIOLOGY – MATERIALS INTERFACE functionalized conducting-polymer nanowire. Journal of the American Chemical Society, 2005, 127, 496–497. M. Shaolin, X. Huaiguo, and Q. Bidong, Bioelectrochemical responses of the polyaniline glucose oxidase electrode. Journal of Electroanalytical Chemistry, 1991, 304, 7–16. K. Grennan, G. Strachan, A. J. Porter, A. J. Killard, and M. R. Smyth, Atrazine analysis using an amperometric immunosensor based on single-chain antibody fragments and regeneration-free multi-calibrant measurement. Analytica Chimica Acta, 2003, 500, 287–298. D. Purvis, O. Leonardova, D. Faramkovsky, and V. Cherkassov, An ultrasensitive and stable potentiometric immunosensor. Biosensors and Bioelectronics, 2003, 18, 1385–1390. J. Wang, M. Jiang, and B. Mukherjee, Flow detection of nucleic acids at a conducting polymer-modified electrode. Analytical Chemistry, 1999, 71, 4095–4099. Y. Shao, Y. Jin, J. Wang, L. Wang, F. Zhao, and S. Dong, Conducting polymer polypyrrole supported bilayer lipid membranes. Biosensors and Bioelectronics, 2005, 20, 1373–1379. K. Haberm¨uller and W. Schuhmann, A low-volume electrochemical cell for the deposition of conducting polymers and entrapment of enzymes. Electroanalysis, 1998, 10, 1281–1284. S. Cosnier, Electropolymerization of amphiphilic monomers for designing amperometric biosensors. Electroanalysis, 1997, 9, 894–902. S. Cosnier, M. Fontecave, D. Limosin, and V. Nivi`ere, A poly(amphiphilic pyrrole)-flavin reductase electrode for amperometric determination of flavins. Analytical Chemistry, 1997, 69, 3095–3099. Rajesh, V. Bisht, W. Takashima, and K. Kaneto, An amperometric urea biosensor based on covalent immobilization of urease onto an electrochemically prepared copolymer poly(N-3-aminopropyl pyrrole-copyrrole) film. Biomaterials, 2005, 26, 3683–3690. F. Darain, D. Park, J. S. Park, S. C. Chang, and Y. B. Shim, A separative-free amperometric immunosensor for vitellogenin based on screen-printed carbon arrays modified with a conductive polymer. Biosensors and Bioelectronics, 2005, 20, 1780–1787. B. Piro, J. Haccoun, M. C. Pham, L. D. Tran, A. Rubin, H. Perrot, and C. Gabrielli, Study of the DNA hybridization transduction behavior of a quinonecontaining electroactive polymer by cyclic voltammetry and electrochemical impedance spectroscopy. Journal of Electroanalytical Chemistry, 2005, 557, 155–175. S. Cosnier, D. Fologea, S. Szunerits, and R. S. Marks, Poly(carbazole-N-hydroxysuccinimide) film: a new polymer for the reagentless grafting of enzymes and redox mediator. Electrochemistry Communications, 2000, 2, 827–831. H. Korri-Youssoufi and B. Makrouf, Electrochemical biosensing of DNA hybridization by ferrocenyl groups functionalized polypyrrole. Analytica Chimica Acta, 2002, 469, 85–92. G. Herzog, K. Gorgy, T. Gulon, and S. Cosnier, Electrogeneration and characterization of photoactivable films and their application for enzyme grafting. Electrochemistry Communications, 2005, 7, 808–814.
44. T. Konry, A. Novoa, Y. Shemer-Avni, N. Hanuka, S. Cosnier, A. Lepellec, and R. S. Marks, Optical fiber immunosensor based on a poly(pyrrole-benzophenone) film for the detection of antibodies to viral antigen. Analytical Chemistry, 2005, 77, 1771–1779. 45. P. Pantano andW. G. Kuhr, Dehydrogenase-modified carbon-fiber microelectrodes for the measurement of neurotransmitter dynamics. 2. Covalent modification utilizing avidin-biotin technology. Analytical Chemistry, 1993, 65, 623–630. 46. T. Hoshi, J. Anzai, and T. Osa, Controlled deposition of glucose oxidase on platinum electrode based on an avidin:biotin system for the regulation of output current of glucose sensors. Analytical Chemistry, 1995, 67, 770–774. 47. S. Cosnier, M. Stoytcheva, A. Senillou, H. Perrot, R. P. M. Furriel, and F. A. Leone, A biotinylated conducting polypyrrole for the spatially controlled construction of amperometric biosensor. Analytical Chemistry, 1999, 71, 3692–3693. 48. S. Cosnier, H. Perrot, and R. Wessel, Biotinylated polypyrrole modified quartz-crystal microbalance for the fast and reagentless determination of avidin concentration. Electroanalysis, 2001, 13, 971–974. 49. A. Dupont-Filliard, M. Billon, G. Bidan, and S. Guillerez, Investigation by QCM of the specific and nonspecific avidin interaction onto biotinylated polypyrrole film. Electroanalysis, 2004, 16, 667–673. 50. A. Dupont-Filliard, M. Billon, T. Livache, and S. Guillerez, Biotin/avidin system for the generation of fully renewable DNA sensor based on biotinylated polypyrrole film. Analytica Chimica Acta, 2004, 515, 271–277. 51. S. Da Silva, L. Grosjean, N. Ternan, P. Mailley, T. Livache, and S. Cosnier, Biotinylated polypyrrole films: an easy electrochemical approach for the reagentless immobilization of bacteria on electrode surfaces. Bioelectrochemistry, 2004, 63, 297–301. 52. S. A. G. Evans, K. Brakha, M. Billon, P. Mailley, and G. Denuault, Scanning electrochemical microscopy (SECM): localized glucose oxidase immobilization via direct electrochemical microspotting of polypyrrolebiotin films. Electrochemistry Communications, 2005, 7, 135–140. 53. S. Cosnier, A. Lepellec, R. S. Marks, K. Perie, and J.-P. Lellouche, A permselective biotinylated polydicarbazole film for the fabrication of amperometric enzyme electrodes. Electrochemistry Communications, 2003, 5, 973–977. 54. S. Cosnier, C. Gondran, A. Le Pellec, and A. Senillou, Controlled fabrication of glucose and catechol microbiosensors via electropolymerized biotinylated polypyrrole films. Analytical Letters, 2001, 34, 61–70. 55. C. Mousty, J.-L. Bergamasco, R. Wessel, H. Perrot, and S. Cosnier, Elaboration and characterization of spatially controlled assemblies of complementary polyphenol oxidase-alkaline phosphatase activities on electrodes. Analytical Chemistry, 2001, 73, 2890–2897. 56. C. Mousty, A. Le Pellec, S. Cosnier, A. Novoa, and R. S. Marks, Fabrication of organic phase biosensors based on multilayered polyphenol oxidase protected by an alginate coating. Electrochemistry Communications, 2001, 3, 727–732.
IMMOBILIZATION OF BIOMOLECULES BY ELECTROPOLYMERIZED FILMS 57. N. Haddour, S. Cosnier, and C. Gondran, A new biotinylated tris bipyridinyl iron(II) complex as redox biotin-bridge for the construction of supramolecular biosensing architectures. Journal of the Chemical SocietyChemical Communications, 2004, 2472–2473. 58. N. Haddour, C. Gondran, and S. Cosnier, Electrogeneration of a biotinylated poly (pyrrole-ruthenium(II)) film for the construction of photoelectrochemical immunosensor. Journal of the Chemical Society-Chemical Communications, 2004, 324–325. 59. M.-P. Dubois, C. Gondran, O. Renaudet, P. Dumy, H. Driguez, S. Fort, and S. Cosnier, Electrochemical detection of Arachis hypogaea (peanut) agglutinin binding to monovalent and clustered lactosyl motifs immobilized on a polypyrrole film. Journal of the Chemical SocietyChemical Communications, 2005, 4318–4320.
13
60. J. Davis, A. Glidle, A. E. G. Cass, J. Zhang, and J. M. Cooper, Spectroscopic evaluation of protein affinity binding at polymeric biosensors films. Journal of the American Chemical Society, 1999, 121, 4302–4303. 61. M. C. Halliwell, E. Simon, C. S. Toh, P. N. Bartlett, and A. E. G. Cass, Immobilization of lactate dehydrogenase on poly(aniline)-poly(acrylate) and poly(aniline)-poly(vinyl sulphonate) films for use in a lactate biosensor. Analytica Chimica Acta, 2002, 453, 191–200. 62. N. Haddour, S. Cosnier, and C. Gondran, Electrogeneration of a poly(pyrrole)-NTA chelator film for a reversible oriented immobilization of histidine-tagged proteins. Journal of the American Chemical Society, 2005, 127, 5752–5753.
17 Electrochemical Polymerization for Preparation of Electrochemical Sensors Howard H. Weetall Under Cooperative Agreement with the National Association for Hispanic Elderly Senior Environmental Program Assisting the US Environmental Protection Agency, Las Vegas, NV, USA
There has always been a need for microanalytical devices that operate at low cost and with high selectivity. Sensor technology, which is both low cost and high selectivity, has developed rapidly for the last few years particularly with reference to chemical and biological sensors. Molecular imprinting of synthetic polymers is a recent process where functionalized and crosslinked monomers are copolymerized in the presence of a target analyte. The target analyte acts as a molecular template. Subsequent removal of the template by some extraction process reveals binding sites that are complementary to the target molecule and are capable of rebinding the target molecule with high specificity. The preparation of (MIPs) has generally been accomplished by chemically induced polymerization. More recently, electrochemically induced polymerization has been reported, particularly for the preparation of biosensors whereby biologically active molecules such as antibodies or enzymes have been entrapped. These types of sensors are not considered MIPs and will not be reviewed here in any detail. This chapter will deal with MIPs prepared by electrochemical polymerization. MIPs’ binding sites often have affinities and selectivities approaching those of antibody– antigen systems and have been dubbed antibody binding mimics.1 These antibody mimics were capable of binding many small molecules or
haptens. One of the first-reported antibody mimics bound theophylline and diazepam.1 MIPs have been successfully used as substitutes for antibodies in standard immunoassays.1–3 In addition, MIPs have been shown to work directly in diluted blood plasma.4 Similar systems have been developed for detection of herbicides.5,6 Binding constants for these antibody substitutes generally are in the 10−7 –10−8 M range. Competitive immunoassays for 2,4-dichlorophenoxyacetic acid (2,4-D) based on the use of MIPs were suggested several years ago.7,8 These assays using either fluorescence or electroactive probes were on par with antibody-based assays. However, it should be remembered that all of these reports utilized chemical polymerization. Similarly another major application for MIPs has been for selective solid-phase extraction. For a review of this area see Ref. 9. Most imprinting has been based on covalent and noncovalent bond complexation. Noncovalent approaches appear more flexible. This method was first introduced by Andersson et al.10 This work led to a number of papers covering different aspects of molecular imprinting technology.11,12 Generally, as with the antibody substitutes, the polymerization methods of choice involved chemical activation and cross-linking.13–18 Originally MIPs were employed as stationary phases in high pressure liquid chromatography
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE
Table 1. Examples of Transducers Employed with MIPs
Transducer
Analyte
References
Impedence Amperometry Differential pulse voltametry Potentiometry FET Fluorescence Conductometric Acoustic wave Surface plasmon resonance
Herbicides 2,4-D Clenbuterol
22 23 24
Phenylalanine anilide Odors Chloramphenicol L-Serine Atropine Sialic acid
25 26 27 28 29 30
(HPLC),19 thin-layer chromatography,20 solidphase extraction,21 and immunoassay.1 A wide variety of transducer methods have been employed using MIP sensors. Examples are shown in Table 1. Electropolymerization, as previously mentioned, has been used mostly for the preparation of biosensors that incorporate enzymes or antibodies.31–45 These same methods have been used in a few instances for the preparation of MIPs and chemical sensors specific to small molecules that do not incorporate large biomolecules. Electrochemical entrapment of molecules, both large and small, in organic polymers involves the application of the appropriate potential to the working electrode, generally in an aqueous solution containing the analyte (molecule of interest) and the electropolymerizable monomer or monomers. As the polymer grows on the electrode surface, it traps the analyte into the growing polymer. A major advantage of electropolymerization is that films can be grown in one-step procedures with exact control of the thickness of the polymer produced. In the case of the preparation of nonconducting polymers, the process is self-terminating. Common monomers used include aniline, acetylene, indole, pyrrole, and thiophene. These compounds produce conducting polymers. The synthesis of nonconducting polymers utilizes compounds such as resorcinol and phenylenediamines and under some conditions aniline. Sensors prepared by electropolymerization appear to be of two types. The true MIP, whereby the analyte can be removed after polymerization, leaves a template that can be filled by the analyte, thereby perturbing the electrical equilibrium in some detectable fashion that is proportional to
the quantity of added analyte. A second type of electrochemically produced sensor appears to act as an ion-specific sensor and does not require removal of the analyte before it can be used for detection and quantitation. Piro et al.46 incorporated oligonucleotides into conducting films of poly(3,4-ethylene dioxythiophene) by electrochemical polymerization. The process was in two steps, first coating the electrode with the polymer film and then by electro-oxidation of the formed polymer. Neutral, water-soluble polymers were added to the polymerizing medium to yield high levels of oligonucleotide incorporation. The oligonucleotides could be extracted from the polymer over several days. However, there is no data indicating complete removal of the oligonucleotides from the polymer. A capacitive chemical sensor for fenvalerate47 was prepared by electropolymerization of 2-mercaptobenzimidazole in the presence of fenvalerate and subsequent treatment with n-dodecanethiol. The polymer was washed and subsequently tested against the analyte with a detection limit of 0.36 µg ml−1 . This system was considered to have formed an MIP. However, again there is no direct evidence of complete removal of the target analyte. Glassy carbon electrodes were used for the electropolymerization of poly(Ru(vbpy)3 2+ )48 a derivative of vinylbenzoic acid. These films catalyzed the oxidation of aqueous guanosine5 monophosphate and poly G. This study presents a case of detection using an electrode system produced by electropolymerization of a monomer for the direct detection of an analyte without the previous extraction of the analyte added to the polymerization solution. There is some question as to whether all sensors made from electropolymerization or chemical polymerization in the presence of a target molecule form true MIPs. Work in our laboratory suggests that, in some cases, systems that we believe to be MIPs may indeed be ion-specific electrode systems or use some other related sensor mechanism. An excellent example of an electrochemically prepared sensor that is not an MIP but requires the presence of the imbedded analyte was produced in our laboratories. The monomers resorcinol and o-phenylenediamine49 were polymerized in the presence of 2,4-D on gold disc electrodes.
3
e d c b a 3000 2000 Wave numbers
4000
1000
Figure 1. FTIR of the surface of the resorcinol/phenylenediamine surface electropolymerized in the presence of 2,4dichlorophenoxyacetic acid. (a) The FTIR of 2,4-D on the gold surface prepared in the presence of 100 mg of 2,4-D. (b) The FTIR of the control that lacks the 2,4-D. (c) The FTIR prepared in the presence of 50 mg of 2,4-D. (d) The 2,4-D-containing electrode soaked in 1 M KCl. (e) A similar electrode soaked 1 M KCl in the presence of 2,4-D. (a), (c), (d), and (e) show the presence of 2,4-D in the expected wave number range. (d) and (e) prove that soaking the polymer containing 2,4-D in 1 M KCl does not remove the small molecule from the polymer.
0.5 0.4 ∆ Current (µA)
The resulting nonconducting electrodes have a coating that is approximately 10-nm thick. These electrodes were capable of detecting and quantitating 2,4-D before and after attempts to wash it out of the polymer. Fluorescence internal reflection spectroscopy (FTIR) of the polymer was examined prior to incorporation and after incorporation of 2,4-D. Each of the electrodes prepared in the presence and absence of 2,4-D was examined using FTIR single-point microscopy monitoring the common bands for 2,4-D in the spectral region between 3100 and 2200 cm−1 . In addition, electrodes were examined after soaking in 1 M KCl solution in the presence and absence of added 2,4-D. The data shows that the 2,4-D does not leach out of the polymer film even after 3000 s (the time used for quantitation of 2,4-D electrochemically) at the operating voltage used for detecting the 2.4-D in 1 M KCl solution (Figure 1). Figure 1(a) shows the FTIR of 2,4-D deposited on a Au/mica substrate. The control electrode prepared in the absence of 2,4-D is shown in Figure 1(b). Figure 1(c) shows the FTIR of the electrode prepared in the presence of 50 mg of 2,4-D. Figures 1(d) and (e) show the experimental electrode previously soaked in 1 M KCl in the absence and the presence of 2,4-D, respectively. The results show that the 2,4-D is present in the membrane even after soaking. The mechanism of action for this MnOx electrode appears to be similar to that of an ion-specific electrode. Since the mechanism does not depend on binding the 2,4-D to a template left by previous removal of the analyte from the polymer, the system cannot be called a MIP. The specificity of the electrode was determined by comparing the response of the electrode to 2,4-D and to 2,4-dichlorophenol, which makes up a major portion of the 2,4-D. In addition, the electrode was tested versus benzoic acid as a means of considering the binding capability of the aromatic acid end of the 2,4-D. The electrode showed concentration dependence on 2,4-D, a greatly diminished response to 2,4dichlorophenol, and no response to the addition of benzoic acid (Figure 2). The 2,4-D electrode showed a concentration-dependent response. Similar experiments with the control electrode prepared in the absence of 2,4-D showed no response to 2,4-D, 2,4-dichlorophenol, or benzoic acid.
FTIR Intensity (arb units)
ELECTROCHEMICAL POLYMERIZATION
0.3 0.2 0.1 0 −0.1 −0.2
−1
0
1
2
3
4
5
6
7
8
9
2,4-D analog (µg ml−1)
Figure 2. Change in steady state current response for 2,4-D-doped polymer-coated electrode as a function of (square) 2,4-D, (circle) 2,4-dichlorophenol, and (triangle) benzoic acid. The potential was −1 V, and the solution was stirred. Note that the electrode shows a lower response to 2,4-dichlorophenol and no response to benzoic acid.
A similar system was used to show selectivity for fluorescein, rhodamine, or 2,4-D on a graphite electrode by electropolymerizing resorcinol and o-phenylenediamine in the presence of the
molecule of interest.50 In the case of the dyes, the polymer-coated electrodes showed higher affinity for their “template” molecule than for a “nontemplate” molecule. Since the electrode systems worked just as well before or after extraction of the template molecules, it is difficult to call it a MIP. Complete removal of the dyes from the polymer was not possible, therefore some of the dye molecules must have been in contact with the surface of the polymer. The data described above for the 2,4-D electrode used the same electropolymerized monomers. The FTIR data indicated no loss of the embedded 2,4-D and strongly suggests that this system acts in a similar fashion to the 2,4-D system that appears to be an ion-specific electrode and not an MIP. For the fluorescence studies, two sets of electrodes were prepared by electropolymerization; one set in the presence of fluorescein and the other in the presence of rhodamine. One set of electrodes was soaked in methanol for several days with daily changes until no fluorescence could be detected in the washes. The washed electrodes were allowed to contact a mixture of the two dyes for several hours followed by methanol extractions and examination using fluorimetry. The unwashed set of electrodes was also allowed to contact the dye mixture or challenge solution for several hours. Data from both sets gave similar results. The data presented here is for the washed set of electrodes (Figures 3–7). The electrode prepared in the presence of the dye of interest showed higher affinity for the incorporated dye. The electrodes were washed with three successive aliquots of methanol and each aliquot was examined fluorimetrically. The electrodes were also subjected to a challenge solution diluted from the initial 25 mM to 25 µM. The results were similar to those observed with the more concentrated solution. Control electrodes prepared in the absence of either of the dyes showed no affinity for one dye over the other. These recent data using a nonconducting electropolymerized system suggest that specificity within these systems is not always dependent on removal of the template molecule from the polymer in order to show selectivity. Although we did not examine any conducting polymer systems, it is likely that similar results would be observed. It is obvious that other mechanisms are in play that do not fill spaces but most likely
Fluorescence
THE BIOLOGY – MATERIALS INTERFACE 600 550 500 450 400 350 300 250 200 150 100 50 480 500 520 540 560 580 600 620 640 660 Wavelength (nm)
Figure 3. Fluorescent spectrum of the diluted challenge material containing equal molar quantities of both fluorescein and rhodamine. Excitation was at 450 nm. The peak at approximately 520 nm represents the fluorescein, while the peak at 570 nm represents the rhodamine. [Reprinted from Weetall and Rogers50 with permission from Elsevier.]
100 b
90 80 Fluorescence
4
70 a
60 50 40
c
30 20 10 0 480 500 520 540 560 580 600 620 640 Wavelength (nm)
Figure 4. Fluorescein “imprinted” electrode. Fluorescence spectra from the first (a), second (b), and third (c) 15-ml methanol washes of the fluorescein-prepared electrode that had been exposed to the challenge solution containing 25 mM each of fluorescein and rhodamine. Excitation was at 450 nm. Note that because the ratio of fluorescein to rhodamine is the issue being examined in this discussion, wash-solution dilutions were prepared for the relative comparison of fluorescence spectra. [Reprinted from Weetall and Rogers50 with permission from Elsevier.]
involve some form of hydrogen or ionic binding of the analyte to the target molecule bound to the surface of the polymer. It is likely that many MIP systems described in the literature are not MIPs but
ELECTROCHEMICAL POLYMERIZATION 200
900 a
800
180
700
160
600
140
500 400 c
300 200
Fluorescence
Fluorescence
5
c
120 100 80 60
a
40 b
100
20
0 480 500 520 540 560 580 600 620 640 Wavelength (nm)
Figure 5. Rhodamine “imprinted” electrode. Fluorescence spectra from the first (a), second (b), and third (c) 15-ml methanol washes of the rhodamine-prepared electrode exposed to the challenge solution (see Figure 3). Excitation was at 450 nm. [Reprinted from Weetall and Rogers50 with permission from Elsevier.]
b
0 480 500 520 540 560 580 600 620 640 Wavelength (nm) Figure 7. Rhodamine “imprinted” electrode. Fluorescence spectra from the first (a), second (b), and third (c) 15-ml methanol washes of the rhodamine-prepared electrode that had been exposed to a challenge solution containing 25 µM each of fluorescein and rhodamine. Excitation was at 450 nm. [Reprinted from Weetall and Rogers50 with permission from Elsevier.]
200 180
b
Fluorescence
160 140
be more careful in describing MIP technology and should prove that the template molecule has been totally removed from the polymer when rebinding causes a quantitative detectable response.
120 100
REFERENCES
80
a
60 40
c
20 0 480 500 520 540 560 580 600 620 640 Wavelength (nm) Figure 6. Fluorescein “imprinted” electrode. Fluorescence spectra from the first (a), second (b), and third (c) 15-ml methanol washes of the electrode that had been exposed to the challenge solution containing 25 µM each of fluorescein and rhodamine. Excitation was at 450 nm. Note that because the ratio of fluorescein to rhodamine is the issue being examined, wash-solution dilutions were prepared for the relative comparison of fluorescence spectra. [Reprinted from Weetall and Rogers50 with permission from Elsevier.]
are some form of ion-specific electrodes whereby the analyte binds and equilibrates with the bound species of the same analyte. In the future, one must
1. G. Vlatakis, L. I. Andersson, R. Muller, and K. Mosbach, Drug assay using antibody mimics made by molecular imprinting. Nature, 1993, 361, 645–647. 2. L. I. Andersson, R. Muller, G. Vlatakis, and K. Mosbach, Mimics of the binding sites of opoid receptors obtained by molecular imprinting of enkephalin and morphine. Proceedings of the National Academy of Sciences of the United States of America, 1995, 92, 4788–4792. 3. O. Ramstrom, L. Ye, and K. Mosbach, Artificial antibodies to corticosteroids prepared by molecular imprinting. Chemistry and Biology, 1996, 6, 471–477. 4. P. Manowitz, P. W. Stoecker, and A. M. Yacynych, Galactose biosensing using composite polymers to prevent interferences. Biosensors and Bioelectronics, 1995, 10, 359–370. 5. A. M. Saboori and R. K. Gordon, Selective binding of organophosphate P pesticides using molecular imprinted polymers. Journal FASEB, 2003, 17, 370–376. 6. A. Sasna and P. Skiadal, A four channel electrochemical immunosensor for detection of herbicides based on phenoxyalkanoic acids. International Journal of Environmental Analytical Chemistry, 2003, 83, 101–109. 7. S. Kroger, A. P. Turner, K. Mosbach, and K. Haupt, Inprinted polymer-based sensor system for herbicides
6
8.
9.
10.
11.
12.
13. 14. 15.
16.
17.
18.
19.
20.
21. 22.
23.
24.
THE BIOLOGY – MATERIALS INTERFACE using differential-pulse voltammetry on screen-printed electrodes. Analytical Chemistry, 1999, 71, 3698–3702. K. Haupt, A. Dzgoev, and K. Mosbach, Assay system for the Herbicide 2.4-Dicholorphenoxyacetic Acid using a Molecular Polymer as an Artifical Recognition Element. Analytical Chemistry, 1998, 70, 628–631. C. T. Fleischer, Highly selective solid-phase extraction of biofluids using restricted-access materials in combination with molecular imprinted polymers. American Laboratory, 2001, 33, 20–25. L. I. Anderson, Application of Molecular Imprinting to the Development of aqueous Buffer and Organic Solvent Based Radioligand Binding Assays for (s)-Propranolol. Analytical Chemistry, 1996, 68, 111–117. O. Bruggemann, Molecularly imprinted materials-receptors more durable than nature can provide. Annual Review, 2001, 30, 128–163. V. B. Kandimalla and H. Ju, Molecular imprinting: a dynamic technique for diverse applications in analytical chemistry. 2004, 380, 587–605. M. Yoshikawa, Molecularly imprinted polymeric membranes. Bioseparations, 2002, 10, 277–286. I. A. Nicholls and J. P. Rosengren, Molecular imprinting of surfaces. Bioseparations, 2002, 10, 301–305. T. Takeuchi and J. Haginaka, Separation and sensing based on molecular recognition using molecularly imprinted polymers. Journal of Chromatography B, 1999, 728, 1–20. K. Ulubayram, Molecularly imprinted polymers. Advances in Experimental Medicine and Biology, 2004, 553, 123–138. K. Haupt, Imprinted polymers-tailor-made mimics of antibodies and receptors. Royal Society of Chemistry and Chemical Communications, 2003, 24, 171–178. D. He, A.-J. Tong, and L.-D. Li, Synthesis of steroidbased molecularly imprinted polymers and their molecular recognition study with spectrometric detection. Spectrochimica Acta Part A. Molecular and Biomolecular Spectroscopy, 2003, 59A, 279–284. N. Zheng, Q. Fu, Y.-Z. Li, W.-B. Chang, Z.-M. Wang, and T.-J. Li, Chromatographic characterization of sulfonamide imprinted polymers. Microchemical Journal, 2001, 69, 55–60. N. Hilal, V. Kochkodan, G. Busca, O. Kachdodan, and B. P. Atkin, Tin layer composite molecularly imprinted membranes for selective separation of cAMP. Separation and Purification Technology, 2003, 31, 281–289. J. Matsui, K. Fujiwara, S. Ugata, and T. Takeuchi, Analytical Communication, 1997, 34, 85–89. T. Panasyuk-Delaney, V. M. Mirsky, M. Ulbricht, and O. W. Wolfbeis, Impedimetric herbicide chemosensors based on a molecularly imprinted polymers. Analytica Chimica Acta, 2001, 435, 157–162. K.-C. Ho, W.-M. Yeh, T.-S. Tung, and J.-Y. Liao, Amperometric detection of morphine based on poly(3,4ethylenedioxythiophene) immobilized molecularly imprinted polymer particles prepared by precipitation polymerization. Analytica Chimica Acta, 2005, 440, 176–181. S. Kroger, A. P. F. Turner, K. Mosbach, and K. Hempt, Analytical Chemistry, 1999, 3698–3702.
25. P. Andrea, S. Miroslav, S. Silvia, and M. Stanislav, A solid binding matrix/molecularly imprinted polymerbased sensory system for determination of clenbuterol in bovine liver using differential-pulse voltametry. Sensors and Actuators B, 2001, 76, 286–294. 26. H.-S. Ji, S. McNiven, K. Ikebukuro, and I. Karabe, Selective piezoelectric odor sensors using molecularly imprinted polymers. Analytica Chimica Acta, 1999, 390, 93–100. 27. J. L. Suarez-Rodriguez and M. E. Diaz-Garcia. Fluorescent competitive flow-through assay for chloramphenicol using molecularly imprinted polymers. Biosens. Bioelectronics, 2001, 16, 955–961. 28. D. Kriz, M. Kempe, and K. Mosbach, Introduction of molecularly imprinted polymers as recognition elements in conductometric chemical sensors. Sensor and Actuators B, 1996, 33, 178–181. 29. H. Peng, C. Liang, A. Zhou, Y. Zhang, Q. Xie, and S. Yao, Development of a new atropine sulfate bulk acoustic wave biosensor based on a molecularly imprinted electrosynthesized co-polymer aniline with o-phenylenediamine. Analytica Chimica Acta, 2000, 423, 221–228. 30. A. Kugimiya and T. Takeuchi, Surface plasmon resonance sensor using molecularly imprinted polymer for detection of sialic acid. Biosensors and Bioelectronics, 2001, 16, 1059–1062. 31. A. Charlton, A. Underhill, G. Williams, M. Kalaji, P. J. Murphy, K. M. Abdul Malik, and M. B. Hursthouse, Thiophene-functionalized FFT-Elecron donors as potential precursors to conducting polymers and organic metals: synthesis, properties, structure and electropolymerization studies. Journal of Organic Chemistry, 1997, 62, 3098–3102. 32. S. Thanachasai, Y. Shoichiro, and T. Watanabe, Effect of fabrication parameters on enzyme loading and sensor response of enzyme-carrying conductive polymer electrodes. Analytical Sciences, 2003, 19, 265–269. 33. H. Yang, T. D. Chung, Y. T. Kim, C. A. Choi, C. H. Jun, and H. C. Kim, Glucose sensor using a microfabricated electrode and electropolymerized bilayer film. Biosensors and Bioelectronics, 2002, 17, 251–259. 34. J.-C. Vidal, E. Garcia, and J.-R. Castillo, Electropolymerization of pyrrole and immobilization of glucose oxidase in a flow system: influence of the operating conditions on analytical performance. Biosensors and Bioelectronics, 1998, 13, 371–382. 35. N. Sallacan, M. Zayats, T. Bourenko, A. B. Kharitonov, and I. Willner, Imprinting of nucleotide and monosaccharide recognition sites in acrylamidephenylboronic acid-acrylamide copolymer membranes associated with electronic transducers. Analytical Chemistry, 2002, 74, 702–712. 36. G. Bidan, M. Billon, K. Galasso, T. Livache, G. Mathis, A. Roget, L. Maria Torres-Rodriguez, and E. Vieil, Electropolymerization of a versatile route for immobilizing biological species onto surfaces. Applied Biochemistry and Biotechnology, 2000, 89, 183–193. 37. M. B. Madaras and R. P. Buck, Miniaturized biosensors employing electropolymerized permselective films and their use for creatinine assays in human serum. Analytical Chemistry, 1996, 68, 3832–3839.
ELECTROCHEMICAL POLYMERIZATION 38. N. F. Almeida, L. B. Wingard Jr, and M. K. Malmros, Immobilization of glucose oxidase by electropolymerization of monomers. Annals of the New York Academy of Sciences, 1990, 613, 448–451. 39. G. Arai, T. Noma, H. Habu, and I. Yasumori, Pyruvate sensor based on pyruvate oxidase immobilized in a poly(mercapto-p-benzoquinone) film. Journal of Electroanalytical Chemistry, 1999, 464, 143–148. 40. H. Yang, T. D. Chung, Y. T. Kim, C. A. Choi, C. H. Jun, and H. C. Kim, Glucose sensor using a microfabricated electrode and electropolymerized bilayer films. Biosensors and Bioelectronics, 2002, 17, 251–259. 41. J.-C. Vidal, E. Garcia, and J.-R. Castillo, Electropolymerization of pyrrole and immobilization of glucose oxidase in a flow system: influence of the operating. conditions on analytical performance. Biosensors and Bioelectronics, 1998, 13, 371–382. 42. J.-C. Vidal, E. Garcia, S. Mendez, P. Yarnoz, and J.-R. Castillo, Three approaches to the development of selective bilayer amperometric biosensors for glucose by in situ electropolymerization. The Analyst, 1999, 124, 319–324. 43. J. C. Vidal, E. Garcia-Ruiz, and J.-R. Castillo, Strategies for the improvement of an amperometric cholesterol biosensor based on electropolymerization in flow systems: use of charge-transfer mediators and platinization of the electrode. Journal of Pharmaceutical and Biomedical Analysis, 2000, 24, 51–63.
7
44. X. Chen, N. Matumoto, Y. Hu, and G. S. Wilson, Electrochemically mediated electrodeposition/electropolymerization to yield a glucose microbiosensor with improved characteristics. Analytical Chemistry, 2002, 74, 368–372. 45. Z. Cheng, E. Wang, and X. Yang, Capacitive detection of glucose using molecularly imprinted polymers. Biosensors and Bioelectronics, 2001, 16, 179–185. 46. B. Piro, M.-C. Pham, and T. Ledoan, Electrochemical method for entrapment of oligonucleotides in polymer-coated electrodes. Synthetic Metals, 1999, 129, 566–572. 47. J.-L. Gong, F.-C. Gong, Y. Kuang, G.-M. Zeng, G.-L. Shen, and R.-Q. Yu, Capacitive chemical sensor for fenvalerate assay based on electropolymerized molecularly imprinted polymer as the sensitive layer. Analytical and Bioanalytical Chemistry, 2004, 379, 302–307. 48. A. C. Ontko, P. M. Armistead, S. R. Kirus, and H. H. Thorp, Electrochemical detection of single-stranded DNA using polymer-modified electrodes. Inorganic Chemistry, 1999, 38, 1842–1846. 49. H. H. Weetall, D. W. Hatchett, and K. R. Rogers, Electrochemically deposited. Polymer-coated gold electrodes selective for 2,4-dichlorophenoxyacetic acid. The Analyst, 2005, (submitted). 50. H. H. Weetall and K. R. Rogers, Preparation and characterization of molecularly imprinted electropolymerized carbon electrodes. Talanta, 2004, 62, 329–335.
18 Smart Hydrogel Materials Elizabeth A. Moschou, Leonidas G. Bachas and Sylvia Daunert Department of Chemistry, University of Kentucky, Lexington, KY, USA
1 INTRODUCTION
Smart hydrogels are hydrophilic polymers, which are able to undergo controlled transformations through physical interactions under the application of an external stimulus.1 The external stimuli include the alteration of various physical parameters, such as the change in temperature, pH, electric field, solvent, or light.2 More interestingly, some hydrogels are able to undergo substantial phase transitions in the presence of a specific biochemical agent. In this case, the hydrogel materials are not only able to sense the specific stimulus (the analyte), but also translate this sensing event into a mechanical action. This elaborate mechanism of actuation of smart hydrogel materials can be utilized in a variety of applications, like in bioanalysis for the design of biosensors, in biomedicine for the fabrication of drug delivery systems, or in medical diagnostics for the development of high-throughput screening systems.3–5 Smart hydrogel materials are cross-linked threedimensional polymer networks, which are composed of hydrophilic homo- or hetero-copolymers, that is, single or multiple building blocks.6 These hydrophilic polymers are able to hold a large amount of water, as much as 300% of their weight, while still maintaining a solid state.7 Owing to their ability to adsorb a significant amount of water, smart hydrogel materials are characterized by the properties of softness, elasticity, and flexibility. These properties are crucial in allowing
smart hydrogels to undergo substantial analyteinduced volume changes as well as to mimic natural tissues, thus making them suitable for use in a variety of biomedical applications. Moreover, these materials exhibit high permeation to solvent and small molecules, allowing for homogeneous three-dimensional changes to occur throughout the bulk of their polymeric structure. Additionally, smart hydrogel materials can be easily fabricated by casting the hydrogel precursor solution in a desired mold and initiating the polymerization by a variety of methods, like thermal or UV initiation.8,9 By choosing appropriate dimensions and shapes of the molds, it is possible to fabricate smart materials with any desired geometry. Further, it is also possible to in situ pattern these materials directly onto the desired devices. One of the most important characteristics of analyte-sensitive smart hydrogel materials is their ability to sense a specific analyte, which is provided by the chemical recognition element that is integrated into the material.10 The chemical recognition element binds the target analyte, initiating subsequent abrupt volume changes in the bulk of the polymeric network of the smart hydrogel through uptake of solvent. This mechanism of actuation of the smart hydrogel materials can either be direct or indirect. In the first case, the change in volume of the material can be generated by the binding of analyte to the chemical recognition element of the hydrogel, displacing a previously bound hydrogel component, which results
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE
Free analyte ( )
(a) Recognition element Polymer-bound analyte
Analyte ( )
(b) Recognition element
Analyte ( )
(c) Recognition element Figure 1. Representative mechanisms of actuation of smart hydrogel materials. (a) The binding of the free analyte to the recognition element displaces the polymer-bound analyte, resulting in the release of the affinity cross-links and the swelling of the smart hydrogel material. (b) The chemical recognition element undergoes a conformational change upon binding to the analyte, which results in the swelling of the smart hydrogel material. (c) The interaction of the analyte with the chemical recognition element alters the electrostatic charge of a polymer component (i.e., through a generated local pH change), which affects the volume of the smart hydrogel material.
in a less cross-linked hydrogel state (Figure 1a). Another mechanism incorporates a hinge-motion binding protein as the recognition element within the hydrogel. Upon binding to the target analyte, the hydrogel undergoes a volume change (Figure 1b). As mentioned in the preceding text, the response mechanism of smart hydrogel materials can also be indirect. For instance, the interaction of the chemical recognition element of the hydrogel with the analyte can generate a local pH change, which can then affect the volume of a pHsensitive hydrogel (Figure 1c). The smart hydrogels based on a direct mechanism of actuation are less prone to physical and chemical interferences
when compared to those based on an indirect actuation mechanism. Other properties of smart hydrogel materials that influence their usefulness in everyday applications include their ability to sense and actuate in a fast, reversible, and reproducible manner, as well as to respond to desired concentrations of analyte; their mechanical stability; and their long lifetimes. In the following paragraphs, we discuss representative examples of smart hydrogel materials that can find a series of interesting applications, including the development of biosensors for the detection of different classes of analytes and the fabrication of high-throughput screening systems.
SMART HYDROGEL MATERIALS
2 SMART HYDROGEL MATERIALS AND THEIR APPLICATION IN BIOANALYSIS 2.1
conditions, for example, extreme values of pH or high temperatures. To that end, Kataoka and coworkers employed synthetic recognition systems in the development of a glucose-sensing hydrogel material based on a synthetic phenylboronate derivative (3-acrylamidophenylboronic acid).11,12 Specifically, in basic solutions, the anionic form of the phenylboronate predominates allowing for the formation of a stable complex with compounds containing cis diols, like glucose, through reversible covalent bonds. The introduction of the phenylboronate into an amphiphilic polymeric hydrogel results in the development of a smart hydrogel material that can bind glucose and respond to the binding event through a phase transition manifested by a change in volume (Figure 2). This volume change is driven
Development of Biosensors Based on Synthetic Receptors
Two different strategies have been pursued in the preparation of new smart hydrogel materials: considerable effort has been directed toward the synthesis of new recognition systems using rational design; while the identification, study, and utilization of highly sensitive and selective systems that are already available in nature has been the focus of other studies. The advantages of utilizing synthetic recognition systems include their low cost and, more importantly, their unusual stability in extreme environmental
Glucose
COR NH
3
COR NH - OH B O O
Glucose
- OH B HO OH
Glucose
Glucose Glucose
Glucose
(a) 10
5 g l –1
3 g l –1
9
1 g l –1
8 0.5 g l –1
Vt /Vmin
7 6 5 4 3 2
0.1 g l –1
1 0 (b)
400
800
1200
1600
Time (min)
Figure 2. Smart hydrogel material based on the synthetic receptor 3-acrylamidophenylboronic acid in a PNIPPAm hydrogel that responds to the presence of glucose. (a) Schematic representation of the response mechanism of the smart hydrogel, and (b) induced swelling curves of the smart hydrogel material showing the ratio of the final (Vt ) versus the initial volume (Vmin ) of the hydrogel in the presence of various glucose levels, (♦) 0.1, (∇) 0.5, () 1, () 3, and (O) 5 g l−1 glucose, at 25 ◦ C at pH 9.0 as a function of time. The initial diameter of the gel in the initial collapsed state was 400 µm. [Reprinted with permission from Matsumoto et al.11 Copyright 2004 American Chemical Society.]
4
THE BIOLOGY – MATERIALS INTERFACE
by the change in the osmotic pressure inside the hydrogel resulting from the increase in glucose levels within the polymer network. The smart hydrogel material developed by the introduction of the 3-acrylamidophenylboronic acid moiety into a poly(N -isopropylacrylamide) (PNIPAAm) with a 1 : 9 mole ratio was able to undergo reversible volume changes in the presence of various glucose concentrations, ranging from 0.1 to 5 g l−1 glucose. Asher and coworkers followed a different strategy in the development of smart hydrogel materials for the detection of cations by preparing intelligent polymerized crystalline colloidal arrays (IPCCAs).13 Crystalline colloidal arrays (CCAs) are a series of monodispersed charged colloidal particles that self-assemble, in this case to form face-centered cubic lattices that diffract light in the visible region of the spectrum by following Bragg’s law. The investigators polymerized a hydrogel of acrylamide that contained
Pb2+ chelating moieties, namely, the crown ether 4-acryloylamidobenzo-18-crown-6. In the same hydrogel they entrapped polystyrene CCA. In the presence of Pb2+ , the crown ether moieties bind to the lead analyte cation, and, at low ionic strength solutions, there is a change in the Donnan potential, which subsequently alters the osmotic pressure within the hydrogel. This change results in the swelling of the hydrogel, and as a consequence the periodicity of the CCAs is altered, and the light diffracted by the hydrogel material is red shifted (Figure 3). The IPCCAs were able to detect Pb2+ with a detection limit of 500 nM (100 ppb) Pb2+ and were further utilized in real sample analysis for the detection of lead in body fluids.14 The same group of investigators developed a sophisticated smart hydrogel material for the detection of glucose, which was based on a polyacrylamide-poly(ethylene glycol) (PEG) hydrogel with embedded CCAs. The hydrogel contains phenylboronic acid groups as the glucose
Pb2+
Pb2+ Pb2+ Pb2+
Pb2+
Pb2+ Pb2+
(a)
Pb2+
700
600 Intensity (arbitrary units)
Wavelength (nm)
650
550
500
Pb2+ 0 mM 0.5 mM 1 mM 4 mM 7.5 mM
1 0.8 0.6 0.4 0.2 0
400
450 0 (b)
1
2
3
4
450
500 550 600 650 Wavelength (nm)
5
6
7
700
8
Pb2+ Concentration (mM)
Figure 3. (a) Schematic representation of a smart hydrogel material that utilizes the crown ether 4-acryloylamidobenzo-18-crown-6 incorporated in a IPCCA for the detection of Pb2+ . (b) Dependence of the diffraction spectrum of the IPCCA particles within the smart hydrogel as a function of the concentration of Pb2+ . [Reprinted with permission from Reese et al.13 Copyright 2001 American Chemical Society.]
SMART HYDROGEL MATERIALS
recognition element. During the interaction of the phenylboronate groups on the hydrogel with glucose, PEG also complexes two Na+ ions close to the two boronates and minimizes the electrostatic repulsion between the two boronates. These glucose-induced cross-links decrease the volume of the hydrogel causing a blue shift in the diffraction of the photonic crystals.15 Owing to their mechanism of response, these CCA-embedded smart hydrogel materials can be utilized in the detection of glucose in solutions of physiological ionic strength. In addition, the use of new boronic acids, like 4-amino-3-fluorophenylboronic acid with a lower pKa of 7.8, allowed for the application of this system in the detection of glucose in solutions of physiological pH with a detection limit of 1 µM glucose. The resultant system has been used successfully in the detection of glucose in artificial tear fluid16 and could be suitable for the fabrication of diagnostic contact lenses or ocular inserts for the detection of glucose in diabetic patients.
2.2
Development of Biosensors Based on Natural Recognition Systems
Smart hydrogel materials based on natural recognition systems take advantage of the inherent ability of these systems to recognize their respective ligand analytes with extraordinary selectivity. In that respect, there are several examples of smart hydrogel materials that have been prepared by incorporating enzymes or antibodies as the recognition elements. Examples of these materials include the glucose-responsive hydrogels based on glucose oxidase developed by the groups of Bae17 and Guiseppi-Elie.18 With regard to the materials prepared by Bae and coworkers,17 the hydrogel was made of pH-sensitive polymerizable sulfadimethozine, sucrose particles that played the role of a porogen and the enzymes glucose oxidase and catalase. In contrast, the hydrogels prepared by the group of Guiseppi-Elie,18 employed a pHsensitive monomer, namely, dimethylaminoethyl methacrylate. In the presence of glucose, the glucose oxidase catalyzes the conversion of glucose to gluconic acid and H2 O2 , decreasing the pH of the surrounding environment. During the pH decrease, the volume of the hydrogel increases owing to the change in the protonation state of the pH-sensitive
5
monomer and the electrostatic repulsions arising in the bulk of the hydrogel material (Figure 4). Thus, this mechanism of swelling of the smart hydrogel is directly related to the concentration of the glucose present in the sample solution. The enzyme catalase was employed to remedy the O2 depletion in the bulk of the smart hydrogel material, which could slow down the oxidation of glucose and thus increase the response time of the hydrogel. Catalase converts the generated hydrogen peroxide into molecular oxygen and replenishes it in the bulk of the hydrogel. The glucose-responsive hydrogel developed was able to respond reversibly to glucose levels ranging from 2.7 to 16 mM under simulated physiological conditions by using isotonic phosphate buffer saline (PBS) solutions at 37 ◦ C. Sharma et al. followed a similar approach, and developed a smart hydrogel material responsive to creatinine by incorporating the enzyme creatinine deiminase within the material.19 The acrylamide hydrogel was embedded with CCAs, which were covalently bound to 2-nitrophenol titrating groups. In the presence of creatinine, creatinine deiminase hydrolyzed the target analyte in the bulk of the smart material increasing the pH of the local environment. This resulted in the deprotonation of the 2-nitrophenol groups, which increased their solubility, causing an increase in the volume of the hydrogel and a red shift in the diffraction of the CCA. This creatinine smart hydrogel material showed a detection limit of 0.6 µM for creatinine, and its usefulness was demonstrated by determining the amino acid creatinine in human serum samples. Another approach in the creation of analyteselective smart hydrogel materials was reported by Miyata et al. by employing the glucose-selective lectin concanavalin A (ConA) as part of their materials.20 In their work, ConA was covalently attached to glucosyloxyethyl methacrylate–based hydrogels, which also contained pendant glucose immobilized in the hydrogel network. In this configuration, ConA was bound to pendant glucose creating chemical cross-links within the bulk of the hydrogel network, thus constricting the volume of the hydrogel. Upon the addition of glucose, ConA released the covalently bound glucose with a subsequent increase in the volume of the smart hydrogel. These researchers also demonstrated that the smart hydrogel material was capable of undergoing swelling changes in a reversible
6
THE BIOLOGY – MATERIALS INTERFACE Glucose GOx
O=S=O
N–
N–
Gluconic acid
Glucose
R
R
~
~
O=S=O
~
~
GOx
O=S=O
O=S=O
R-N–
R-N-H
(a) 15
7.45 7.40 pH inside gel
14
Swelling ratio
13 12
7.35 7.30 7.25 7.20 7.15
11
0
50 100 150 200 250 300
Glucose concentration (mg dl–1)
10 9 8 7 0
(b)
50
100
150
200
250
300
350
Glucose concentration (mg dl–1)
Figure 4. (a) Principle of operation of a smart hydrogel material based on the pH-sensitive polymerizable sulfadimethozine (∼SO2 -N− ∼) and the enzyme glucose oxidase (GOx). Upon the addition of glucose, the enzyme catalyzes the conversion of glucose to gluconic acid decreasing the pH in the bulk of the smart material. This results in the neutralization of the charge of the sulfadimethozine, minimizing electrostatic repulsions and shrinking the volume of the smart hydrogel material. (b) Dependence of the swelling ratio of the smart hydrogel in the presence of glucose in isotonic PBS solution at 37 ◦ C. [Reprinted with permission from Kang and Bae.17 Copyright 2003 Elsevier.]
manner in response to stepwise changes in the concentration of glucose present in the sample. In another study, Miyata et al. employed a similar strategy where they took advantage of the selectivity of antigen–antibody binding to develop a new class of highly selective smart hydrogel materials.21,22 These hydrogels were made of acrylamide, and used both an antibody (rabbit immunoglobulin G, rabbit IgG) and an antigen, which were covalently bound onto the polymeric network of the hydrogel. In equilibrium, the hybrid material has a specific volume due to the physical cross-linking of the polymeric chains in the hydrogel network and the additional cross-links provided by the interactions between the bound antibody molecules with the antigens covalently attached on the polymeric network. When free antigen is introduced into the system and allowed to equilibrate, the free antigen competes with the polymer-bound
antigen for the binding sites on the antibody, causing the release of the antigen bound to the hydrogel network. The result is an increase in the volume of the hydrogel that is specifically related to the presence of the target antigen and is also dependent on the concentration of the specific antigen used (Figure 5). These smart hydrogel materials, which are based on the strong antibody–antigen interactions, can find a variety of applications for the development of immunoassay and antigen-sensing systems.
3 SMART HYDROGEL MATERIALS FOR HIGH-THROUGHPUT SCREENING
The need for the rapid analysis of large number of samples has spurred the incorporation of smart
SMART HYDROGEL MATERIALS
7
Free antigen ( )
Antibody Bound antigen
(a)
Equilibrium swelling ratio (m3 m–3)
1.15
1.10
1.05
1 PAAm hydrogel
0.95 (b)
Antigen–antibody hydrogel
0
2 4 6 8 Antigen concentration (mg ml–1)
10
Figure 5. (a) Schematic representation of the principle of operation of smart hydrogel materials based on antibody recognition elements. In general, the antibody (Y) that is immobilized on the smart hydrogel network interacts with the antigen that is covalently bound to the smart hydrogel (o), forming chemical cross-links in the bulk of the material. In the presence of free antigen, the antibody can bind to the free analyte, releasing the bound antigen. The result is the rupture of the chemical cross-links increasing the volume of the smart hydrogel material. (b) Effect of the antigen concentration on the swelling ratio of the smart hydrogel versus that of a control (PAAm) hydrogel that does not contain any antibodies. [Reprinted with permission from Miyata et al.21 Copyright 1999 American Chemical Society.]
hydrogel materials into high-throughput screening platforms. With that goal in mind, Lowe and coworkers developed metabolite-sensitive holographic biosensors based on smart hydrogels,23 which are suitable for use in high-throughput sensing systems, as they combine the high selectivity and sensitivity afforded by enzymes with the reproducibility, low cost, and capability of mass manufacturing. Analogously, the work described previously by Asher’s group on the polymerized colloidal crystal hydrogels should also be suitable for the fabrication of sensing hydrogel materials for high-throughput screening applications.24 Rather recently, our group reported the development of stimuli-responsive hydrogels based on hybrid materials containing genetically engineered
proteins.25 These hydrogels are composed of poly(acrylamide) and incorporate the genetically engineered protein calmodulin (CaM), which was site-directly bound to the hydrogel through its C-terminus. Phenothiazine, a low affinity ligand for CaM, was also covalently bound to the hydrogel network. The result was that CaM bound phenothiazine within the bulk of the hydrogel, creating chemical cross-links with a “handshake”type configuration. In the presence of chlorpromazine, a high affinity CaM ligand, the CaM in the bulk of the hydrogel network releases phenothiazine in order to bind to the free chlorpromazine. The relaxation of the polymer network due to the release of the chemical cross-links increases the volume of the hydrogel material
8
THE BIOLOGY – MATERIALS INTERFACE Phenothiazine Chlorpromazine
CaM protein
(a)
Displacement (µm)
1000 CaM bound to phenothiazine derivative
750
EGTA, CaM unbound
500 250 0
1
2
(i)
3 Cycle
4
5
4
5
750 Displacement (µm)
Competitive binding of CPZ
500
250
0
1
2
(b) (ii)
3 Cycle
Figure 6. (a) Schematic representation of stimuli-sensitive hydrogel microsensors based on genetically engineered calmodulin (CaM), in the absence of chlorpromazine (left), where CaM binds to phenothiazine (cylindrical ligand) that is bound on the hydrogel network, and in the presence of chlorpromazine (right), where CaM releases phenothiazine to bind the free chlorpromazine (spherical ligand), resulting in the swelling of the hydrogel. (b) Reversible swelling of the smart hydrogel material to Ca2+ (i) and chlorpromazine (ii). [Reprinted from Ehrick et al.25 by permission from Macmillan Publishers Ltd: Nature Materials, copyright 2005.]
(Figure 6), creating a swelling. This increase in volume can form the basis for the detection of various analytes that bind specifically to CaM, that is, class-selective detection of antipsychotic drugs. Moreover, this system should be adaptable to a number of other protein–analyte pairs. The miniaturization of these stimuli-sensitive hydrogels into microdomes makes these materials suitable for high-throughput screening by employing a variety of signal transduction methods for example, photomultipliers, photodiodes, or image analysis. These
microdomes can also be conformed as microlenses and be employed as miniaturized biosensing systems by monitoring the lensing effect caused by a target stimulus (analyte) on the surface of the smart hydrogel microdomes.
4 FUTURE FRONTIERS
Smart hydrogel materials show unique physical and chemical properties. Even though their
SMART HYDROGEL MATERIALS
development and utilization is still in its infancy, the prospects for their contribution to the advancement of many areas of science and engineering are limitless. The flexible, soft, and hydrophilic nature of these materials, mimicking natural tissues and avoiding potential tissue irritation, is ideal for their use in a variety of biomedical applications. Further, their selective response toward a specific target analyte confers on them the ability to be key components in the design of highly selective detection systems. To date, smart hydrogel materials have been developed for the detection of a variety of analytes, including ions, carbohydrates, drugs, and proteins. In the near future, it is expected that sensing with smart hydrogels will be expanded with the incorporation of new, natural, or synthetic,26 highly selective recognition systems (examples include those based on molecular imprinting27,28 ). Moreover, methods that allow the precise control of the threedimensional structure of the hydrogel materials are currently being developed and will prove invaluable in the design and preparation of the hydrogels. Two methods that have already emerged as valuable tools in that arena are the synthesis of hydrogel building blocks by genetic engineering methods and the design of associated building blocks that self-assemble into hydrogel structures.29 The evolution in the development of smart hydrogel materials is expected to be followed by advancements in their miniaturization30,31 and patterning32–34 into desired microstructures, thus broadening their analytical applications (e.g., highthroughput analysis systems, microelectromechanical systems (MEMS), and bio microelectromechanical systems (BioMEMS), etc.). For example, the integration of multiple miniature smart hydrogel materials selective to a variety of analytes into micro total analysis systems (µTAS)35,36 will allow the simultaneous analysis of multiple analytes under a single run, significantly improving the time for the analysis of multiple analytes in low-volume samples. In addition, actuators based on smart hydrogel materials that can translate the analyte recognition process into a mechanical action should allow for the fabrication of intelligent responsive systems.37,38 These systems should be capable of initiating autonomously a desired actuation dictated by a sensing mechanism. Potential applications of these materials include a number of biomedical devices such as responsive
9
drug delivery systems. In conclusion, smart hydrogels have emerged as exciting materials that are expected to impact the creation of highly intelligent and sophisticated systems with a plethora of applications in science and technology.
ACKNOWLEDGMENTS
This work was supported by the National Institutes of Health and the National Aeronautics and Space Administration.
REFERENCES 1. E. S. Gil and S. M. Hudson, Stimuli-responsive polymers and their bioconjugates. Progress in Polymer Science, 2004, 29, 1173–1222. 2. H. J. van der Linden, S. Herber, W. Olthuis, and P. Bergveld, Stimulus sensitive hydrogels and their applications in chemical (Micro)analysis. The Analyst, 2003, 128, 325–331. 3. J. Kopecek, Smart and genetically engineered biomaterials and drug delivery systems. European Journal of Pharmaceutical Sciences, 2003, 20, 1–16. 4. I. Y. Galaev and B. Mattiasson, ‘Smart’ polymers and what they could do in biotechnology and medicine. Trends in Biotechnology, 1999, 17, 335–340. 5. S. Brahim, D. Narinesingh, and A. Guiseppi-Elie, Bio-smart hydrogels: Co-joined molecular recognition and signal transduction in biosensor fabrication and drug delivery. Biosensors and Bioelectronics, 2002, 17, 973–981. 6. P. Bahadur and N. V. Sastry, Principles of Polymer Science, Narosa Publishing House, New Delhi, 2002, CRC Press, Boca Raton, FL. 7. J. J. Kim and K. Park, Smart hydrogels for bioseparation. Bioseparation, 1999, 7, 177–184. 8. M. P. Stevens, Polymer Chemistry, Oxford University Press, New York, 1999. 9. A. Ravve, Principles of Polymer Chemistry, Kluwer Academic/Plenum Publishers, New York, 2000. 10. T. Miyata, T. Uragami, and K. Nakamae, Biomoleculesensitive hydrogels. Advanced Drug Delivery Reviews, 2002, 54, 79–98. 11. A. Matsumoto, T. Kurata, D. Shiino, and K. Kataoka, Swelling and shrinking kinetics of totally synthetic glucose-responsive polymer gel bearing phenylborate derivative as a glucose-sensing moiety. Macromolecules, 2004, 37, 1502–1510. 12. K. Kataoka, H. Miyazaki, M. Bunya, T. Okano, and Y. Sakurai, Totally synthetic polymer gels responding to external glucose concentration: their preparation and application to on-off regulation of insulin release. Journal of the American Chemical Society, 1998, 120, 12694–12695.
10
THE BIOLOGY – MATERIALS INTERFACE
13. C. E. Reese, M. E. Baltusavich, J. P. Keim, and S. A. Asher, Development of an intelligent polymerized crystalline colloidal array colorimetric reagent. Analytical Chemistry, 2001, 73, 5038–5042. 14. S. A. Asher, S. F. Peteu, C. E. Reese, M. X. Lin, and D. Finegold, Polymerized crystalline colloidal array chemical-sensing materials for detection of lead in body fluids. Analytical and Bioanalytical Chemistry, 2002, 373, 632–638. 15. V. L. Alexeev, A. C. Sharma, A. V. Goponenko, S. Das, I. K. Lednev, C. S. Wilcox, D. N. Finegold, and S. A. Asher, High ionic strength glucose-sensing photonic crystal. Analytical Chemistry, 2003, 75, 2316–2323. 16. V. L. Alexeev, S. Das, D. N. Finegold, and S. A. Asher, Photonic crystal glucose-sensing material for noninvasive monitoring of glucose in tear fluid. Clinical Chemistry, 2004, 50, 2353–2360. 17. S. I. Kang and Y. H. Bae, A sulfonamide based glucoseresponsive hydrogel with covalently immobilized glucose oxidase and catalase. Journal of Controlled Release, 2003, 86, 115–121. 18. A. Guiseppi-Elie, S. I. Brahim, and D. Narinesingh, A chemically synthesized artificial pancreas: release of insulin from glucose-responsive hydrogels. Advanced Materials, 2002, 14, 743–746. 19. A. C. Sharma, T. Jana, R. Kesavamoorthy, L. Shi, M. A. Virji, D. N. Finegold, and S. A. Asher, A general photonic crystal sensing motif: creatinine in bodily fluids. Journal of the American Chemical Society, 2004, 126, 2971–2977. 20. T. Miyata, A. Jikihara, K. Nakamae, and A. S. Hoffman, Preparation of reversibly glucose-responsive hydrogels by covalent immobilization of lectin in polymer networks having pendant glucose. Journal of Biomaterials Science. Polymer Edition, 2004, 15, 1085–1098. 21. T. Miyata, N. Asami, and T. Uragami, Preparation of an antigen-sensitive hydrogel using antigen-antibody bindings. Macromolecules, 1999, 32, 2081–2084. 22. T. Miyata, N. Asami, and T. Uragami, A reversibly antigen-responsive hydrogel. Nature, 1999, 399, 766–769. 23. A. J. Marshall, D. S. Young, J. Blyth, S. Kabilan, and C. R. Lowe, Metabolite-sensitive holographic biosensors. Analytical Chemistry, 2004, 76, 1518–1523. 24. J. H. Holtz and S. A. Asher, Polymerized colloidal crystal hydrogel films as intelligent chemical sensing materials. Nature, 1997, 389, 829–832. 25. J. D. Ehrick, S. K. Deo, T. W. Browning, L. G. Bachas, M. J. Madou, and S. Daunert, Genetically engineered protein in hydrogels tailors stimuli-responsive characteristics. Nature Materials, 2005, 4, 298–302.
26. N. A. Peppas and Y. Huang, Polymers and gels as molecular recognition agents. Pharmaceutical Research, 2002, 19, 578–587. 27. M. E. Byrne, K. Park, and N. A. Peppas, Molecular imprinting within hydrogels. Advanced Drug Delivery Reviews, 2002, 54, 149–161. 28. J. Z. Hilt and M. E. Byrne, Configurational biomimesis in drug delivery: molecular imprinting of biologically significant molecules. Advanced Drug Delivery Reviews, 2004, 56, 1599–1620. 29. J. Kopecek, Swell gels. Nature, 2002, 417, 388–391. 30. H. van der Linden, W. Olthuis, and P. Bergveld, An efficient method for the fabrication of temperaturesensitive hydrogel microactuators. Lab on a Chip, 2004, 4, 619–624. 31. D. Schmaljohann, M. Nitschke, R. Schulze, A. Eing, C. Werner, and K. J. Eichhorn, In situ study of the thermoresponsive behavior of micropatterned hydrogel films by imaging ellipsometry. Langmuir, 2005, 21, 2317–2322. 32. V. R. Tirumala, R. Divan, L. E. Ocola, and D. C. Mancini, Direct-write e-beam patterning of stimuli-responsive hydrogel nanostructures. Journal of Vacuum Science and Technology B: Microelectronics and Nanometer Structures–Processing, Measurement, and Phenomena, 2005, 23, 3124–3128. 33. M. S. Hahn, L. J. Taite, J. J. Moon, M. C. Rowland, K. A. Ruffino, and J. L. West, Photolithographic patterning of polyethylene glycol hydrogels. Biomaterials, 2006, 27, 2519–2524. 34. M. D. Tang, A. P. Golden, and J. Tien, Molding of three-dimensional microstructures of gels. Journal of the American Chemical Society, 2003, 125, 12988–12989. 35. D. J. Beebe, J. S. Moore, J. M. Bauer, Q. Yu, R. H. Liu, C. Devadoss, and B. H. Jo, Functional hydrogel structures for autonomous flow control inside microfluidic channels. Nature, 2000, 404, 588–590. 36. H. M. Simms, C. M. Brotherton, B. T. Good, R. H. Davis, K. S. Ansethab, and C. N. Bowman, In situ fabrication of macroporous polymer networks within microfluidic devices by living radical photopolymerization and leaching. Lab on a Chip, 2005, 5, 151–157. 37. I. Roy and M. N. Gupta, Smart polymeric materials: review emerging biochemical applications. Chemistry and Biology, 2003, 10, 1161–1171. 38. N. A. Peppas and W. Leobandung, Stimuli-sensitive hydrogels: ideal carriers for chronobiology and chronotherapy. Journal of Biomaterials Science. Polymer Edition, 2004, 15, 125–144.
19 Scanning Electrochemical Microscopy for Biomolecular Immobilization and Imaging Sabine Szunerits Institut National Polytechnique de Grenoble, Domaine Universitaire, Saint Martin d’H`eres, France
1 INTRODUCTION
The localized immobilization of biological recognition elements and the spatial, controlled detection of biological events and activities (e.g., hybridization, enzyme activity, oxidative stress, etc.) are active fields of research, in particular due to an increasing demand for miniaturized bioanalytical devices together with the call for parallel analysis of multiple analytes in small sample volumes. Surface probe microscopy (SPM) techniques have attracted much attention for the site-directed structuring of surfaces because of their simplicity. Consequently, scanning electrochemical microscopy (SECM), an electrochemically based SPM technique introduced in 1989 by Bard,1 is increasingly used next to photochemical and lithographic approaches (e.g., photoimmobilization, laser ablation, photolithography, microcontact printing, dip-PEN lithography) or siteselective supply of biomolecules by microfluidic networks2–6 for locally modifying diverse target surfaces with chemical and biological molecules. SECM is more than just a tool for the reproducible and accurate immobilization of different molecules. One of the main advantages of using SECM is the possibility of mapping surface reactivities allowing the assessment of surface reaction kinetics as well as identifying bioactive sites. The
biological targets imaged at present using SECM include enzymes, antibodies, DNA, proteins, and biological systems as complex as living cells. For a better understanding of SECM, a brief discussion of the basics of SECM is given. However, for a more detailed account the reader is referred to literature, such as, for example Ref. 7.
1.1
Scanning Electrochemical Microscopy (SECM)
Until the early 1980s a typical electrochemical experiment involved the application of a voltage or current perturbation to a millimeter-sized metal electrode. At around that time, the possibility of fabricating electrodes with micrometer size was revealed, which showed a number of specific features associated with their small size.8 In fact, one of the advantages of an ultramicroelectrode (UME) is the establishment of a well-defined steady-state current, which is relatively immune to convection. This allows scanning a UME across an unknown surface to obtain information about its topography and its chemical reactivity.9 Additionally, using a UME allows local surface modification through electrodissolution or electrodeposition processes. There are three ways how SECM can be operated on biological systems: the generator–collector
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE
Reduction Mox
Mox S′
Mred
Mox
S′
S
Mox
S
B
B (a)
Mred
(b)
(c)
Oxidation
Figure 1. Schematic representation of the three operation modes of SECM on biological modified surface: (a) generator–collector mode, (b) feedback mode, and (c) direct mode: Mox /Mred : redox mediator in oxidized or reduced form; B: biological compound; S: reactant specific for B; S : product of S.
mode (G/C), the feedback mode, and the direct mode (Figure 1). In the simplest case (G/C mode) the microelectrode is moved over the immobilized biological molecule B in the presence of S (being a reactant specific for B), detecting the electroactive species S , produced by the immobilized biomolecule (Figure 1a). The UME can be used as a potentiometric or amperometric probe, as well as an electrochemical sensor (e.g., amperometric enzyme electrode).10–12 The G/C detection is highly sensitive as no redox-active species have to be added to the bulk phase of the solution and the background current is effectively zero. The major technical problems with the G/C mode are the need for an independent tip-substrate distance measurement and the absence of a well-defined mass transport rate in some situations. The limitation of the independent tip-substrate distance determination has been overcome these days by using a shear-force-based approach concept as well as by using the impedance of the SECM tip as the distance-dependent signal.11,13–17 The biocatalytic production of S is nevertheless mostly continuous and there is no direct way in the G/C mode to switch the biocatalytic reaction on and off. This situation can lead, in the case of arrays, to the overlap of product diffusion zones from different individual sites not only blurring the SECM image but also degrading the lateral resolution as products are diffusing into regions where no biocatalytic reaction is actually occurring. A much higher lateral resolution can be achieved using the feedback mode. As seen in Figure 1(b), a mediator, being either an electron donor or an acceptor (Mox or Mred ) enables communication between the amperometrically working UME
and the biologically modified surface by shuttling the mediator between the microelectrode and the surface, which can be biased or unbiased. The mediator is converted at the microelectrode and the product of the redox reaction diffuses to the biologically modified substrate where it is subsequently turned over in the presence of a suitable substrate, S. The recycled mediator diffuses back to the UME where it is re-reduced or reoxidized. Depending on the surface, the current detection on the UME in the mediator solution is changing in a distinctive way: if the target is electrically conducting or allows the regeneration of the mediator, an amplification of the UME’s steady-state current is observed because of the redox recycling of the mediator (positive feedback), while a nonconductive interface hinders the back diffusion of the mediator to the tip causing a decrease of the current as the tip approaches the surface of the target (negative feedback). The major advantage of feedback imaging in contrast to the G/C mode is that a higher lateral resolution is obtained as the biocatalytic reaction occurs only in close proximity to the microelectrode. Yet, the immobilized biological target has to be redox active. In the case of enzymes, only a small number are oxidoreductase enzymes. The sensitivity reached with the feedback mode is however limited, as the molecular flux generated by the enzymatic reaction is detected above the background of the hindered mediator diffusion from the bulk phase. As this diffusion may also vary with the sample topography, successful enzyme imaging has been restricted to situations where the enzyme has a very high turnover rate and where a high enzyme load is probed.
b-D-Glucono-d-lactone
Mred
Mox
b-D-Glucose
GOx
(a)
Current (nA)
SCANNING ELECTROCHEMICAL MICROSCOPY
(b)
3.1 3 2.9 2.8 2.7 2.6 2.5 2.4 2.3 100
3
In the presence of glucose In the absence of glucose 80
60 40 20 Distance (µm)
0
Figure 2. (a) Schematic presentation of the enzyme-mediated feedback effect and (b) approach curves in the presence of mediator and glucose (positive feedback) and in the presence of the mediator only (negative feedback). [Reprinted from Kranz et al.20 , with permission from Elsevier.]
The direct mode of SECM (Figure 2c) is not, a priori, used for biological imaging, but, beside the G/C mode, for patterning of surfaces with biomolecules.18–23 The direct mode of SECM can be related to an STM probe used for microfabrication. In this case, the microelectrode serves as counter electrode establishing a highly focused electrical field between the substrate and the UME.
2 IMMOBILIZATION OF BIOMOLECULES USING SECM
The most commonly used method of structuring of surfaces is photolithography but this sometimes poses problems of compatibility with biological substances (organic solvents, strong acids, and strong bases). The principal advantage of SECM as a local immobilization tool is its capacity to induce an immense range of chemical and electrochemical reactions on very varied materials on a micrometric or nanometric scale and is in particular adapted for biological patterning. Efforts to pattern surfaces with biomolecules using the direct mode have been reported by several groups: the local deposition of alkanethiol monolayers,24–26 the fabrication of patterns of conducting polymers bearing functional groups20,27 or oligonucleotide units,22,23,28,29 the fabrication of gold patterns through anodic dissolution of a gold microelectrode to which glucose oxidase (GOx) was covalently bond,30 and the deposition of paramagnetic beads modified with biomolecules.31,32 The direct mode of patterning has, nevertheless, a number of significant limitations. First, the redox process on the UME must
be accompanied by a reverse reaction at the surface. This reaction can be accompanied by water oxidation forming gas bubbles and degrading the pattern formed. Second, the resolution of the pattern is a function of the shape of the UME and the tip–substrate distance. The key for high resolution is a needlelike UME, which can however be easily damaged as a result of their lateral movement or by probe contact.21 Even though feedback-mode approaches for patterning of surfaces with biological structures have been reported, they still lag behind the direct mode in their applications because biological molecules do not have simple redox behavior and are not suitable as redox mediators. Therefore, the biomolecule first has to be attached to the surface and then locally deactivated or activated or desorbed or absorbed through an electrochemical reaction driven by the mediator. The principal advantage of feedback-mode patterning lies in the fact that the substrate does not necessarily have to be conductive, which widens the field of potential surfaces. Matsue et al.33 was able to create micropatterns of diaphorase on glass by locally deactivating the enzyme through bromine or by locally modifying, using hydroxyl radicals, a silane monolayer attached to the glass.34 Kuhr and Wipf attached and detached biotin probes on a glassy carbon electrode by using the UME as an electrochemical pen.35,36 As in any scanning probe technique, the movement of the UME and the kinetics of the reaction to the substrate limit the speed of the patterning process across the substrate. In the case of a fast kinetics, the UME can move at speeds of some micrometers per second. Currently, SECM
4
THE BIOLOGY – MATERIALS INTERFACE
cannot compete in speed with more conventional patterning methods such as photolithography even though with the use of multielectrode probes for parallel patterning and imaging the time taken for the data acquisition process should decrease drastically.37
3 CHEMICAL IMAGING OF BIOLOGICAL SYSTEMS
SECM is not only a tool for the localized immobilization of biomolecules but has become a very valuable technique for the study and imaging of biological samples, being a noncontact SPM technique. The application of SECM to monitor biological targets started in the 1990s and involved topographic images of leaf surfaces as well as the determination of local oxygen concentration changes due to photosynthesis38 and the targets now include enzymes, antibodies, proteins, cells, and DNA. However, with a few exceptions,39–41 in SECM the detection of biomolecular interactions is based on enzyme labeling and, therefore, on the localized measurement of the catalytic activity of enzymes. Indeed, the assessment of enzymatic labeling is important for the optimization of the immobilization and functional parameters of enzyme sensors. In the following, original examples are discussed to demonstrate the usefulness and interest of SECM in bioscience. Table 1 gives further references found in the literature concerning enzyme, protein, cell, and DNA detection based on SECM.
3.1
Enzymes
Imaging the local enzyme activity requires the availability of electrochemically detectable compounds indicative of the biocatalytic reaction. This is an easy task considering the excess of enzyme electrodes developed in the last 40 years.85 In most cases, the biocatalytic activity induces changes in the local concentration of molecules or ions readily accessible by electrochemical means such as oxygen, hydrogen ions, or hydrogen peroxide. In the case of oxidoreductase enzymes, artificial mediators with ideal electrochemical reversibility that enhances the sensitivity of the measurement can be used. If there is no electrochemically detectable species involved in the enzymatic reaction, the natural enzyme can be replaced by synthetic ones enabling the electrochemical monitoring of the biocatalytic reaction.86 Since the first report by Bard et al.45,46 on the use of the feedback mode of SECM to detect biocatalysis using GOx immobilized on diverse insulating surfaces, different oxidoreductase enzymes have been attached to contacting and insulating surfaces and the local enzyme activity has been detected by carefully matching the SECM system to the biocatalytic reaction. GOx is probably the most widely studied of these enzymes as it is robust.10,20,26,27,30,42–51 Both as an immobilized substance and in solution, GOx catalyzes the oxidation of β-D-glucose to β-D-glucono-δ-lactone by a number of one- and two-electron mediator oxidants (equation 1) (Figure 2a). β-D-glucose + O2 + H2 O + (3 − n)Mox
GOx −−−−→
β-D-glucono-δ-lactone + (3 − n)Mred + H2 O2
Table 1. SECM in bioscience
Biological sample GOx Glucose dehydrogenase β-galactosidase HRP(a) Diaphorase (flavoenzyme) Mutarotase, catalase, α-glucosidase, uricase Antigen anticore Cells Proteins DNA (a)
HRP: horseradish peroxidase.
References 10, 32, 54 11, 33, 42,
20, 26, 27, 30, 42–51 52, 53
35, 14, 80, 28,
36, 50, 63–65 66–79 81 39–41, 48, 82–84
24, 55–58 34, 59–62 43
H2 O2 −−−→ 2H+ + O2 + 2e−
(1) (2)
The enzymatic feedback effect using Fe(CN)6 4− as the mediator in solution was employed by Schuhmann et al.20 They could distinguish between a negative-feedback-approach curve in the absence of β-D-glucose and a positive one in the presence of glucose (Figure 2b). One has to bear in mind that the reaction expressed in equation (1) oversimplifies the known mechanism for GOx catalysis, where GOx is believed to be subsequently reduced and reoxidized
SCANNING ELECTROCHEMICAL MICROSCOPY COOH N HOOC N
COOH
+2e−, +2H+ −2e−, −2H+
O
O
5
COOH N N HO
OH
PQQH2
PQQ
corresponding aldehydes or lactones. Proteins containing the cofactor pyrroloquinoline quinone (PQQ) constitute the best-characterized subclass, through which electrons must pass from the reduced PQQ to the redox center in the protein domain.90 Two redox states are relevant in the biocatalytic mechanism of glucose dehydrogenase (GDH). The oxidized quinone state of PQQ can be reversibly converted into the reduced quinol form, PQQH2 , by proton and electron transfer (see above). GDH is the classical example of PQQ-dependent quinoproteins. GDH is extremely interesting as it has a very high catalytic activity. In comparison to GO, 3 mmol β-D-glucose can be oxidized per minute per milligram of GDH, which is 20 times the activity of pure GOx.91 Wittstock et al.32,52 investigated this biocatalytic reaction in depth in the feedback and G/C mode by studying the activity of microbead-immobilized GDH (Figure 3). Briefly, the microbeads used were coated with streptavidin (7 × 105 active molecules/bead) having 2.8 × 106 active sites for biotin, leading to a maximal surface concentration of enz = 1.8 × 10−11 mol cm−2 . In the feedback mode, mediators such as ferrocenemethanol (FcCH2 OH), ferrocenecarboxylic acid (FcCOOH), and p-aminophenol (PAP) were used.
within one catalytic cycle and where β-D-glucose acts to reduce the enzyme while the electrondeficient mediator acts as the oxidant.87 The G/C mode of the biocatalytic reaction involving GOx detects either reductively the decrease of oxygen or oxidatively the formation of hydrogen peroxide. A G/C detection scheme rather than a feedback-mode-based one was proposed by Denuault.27 During the biocatalytic oxidation of β-D-glucose to β-D-glucono-δlactone, hydrogen peroxide is formed (equation 2), which can be oxidized on an appropriate electrode to oxygen. He developed a mesoporous platinum microelectrode for an improved detection of H2 O2 having a sensitivity of 2.8 A M−1 cm−2 .55 This is a real improvement on transition metal hexacyanoferrate- (1.5 A M−1 cm−2 ) and peroxidase-modified electrodes (1.0 A M−1 cm−2 ).88,89 The main drawback of using oxidoreductase enzymes is their dependence on the oxygen concentration in the sample. Significant improvement was achieved when oxidases were replaced by quinoproteins, which catalyze the transfer of electrons from the substrate to an electron acceptor other than oxygen. Quinoproteins are a class of enzymes, which use one of four different quinone-containing prosthetic groups to convert a vast variety of alcohols and amines to their
Fe(CN)63−
Fe(CN)63− b-D-Glucono-d-lactone
Mred
Mox
b-D-Glucose
b-D-Glucono-d-lactone Fe(CN) 4− Fe(CN) 3− b-D-Glucose 6 6
GDH
(a)
COOH
HOOC
GDH
(b)
Figure 3. (a) Schematic of the SECM feedback imaging Mox being ferrocenemethanol (FcCH2 OH), ferrocenecarboxylic acid (FcCOOH), p-aminophenol (PAP) [Reprinted with permission Zhao and Wittstock32 copyright 2005, Elsevier] and (b) generation–collection imaging principle.
6
THE BIOLOGY – MATERIALS INTERFACE 1.6
6
5
4
1.4
i sk (nA)
B
1.3 1.2
A
isk (nA)
1.5
i T / i T∞
6 C C
4
2 0
B
3
0
0.5
1
1.5
2
C *FcCH2OH (mM)
2
1.1
A
1 1 0 0 (a)
1
2
3
4
5
6
d /r T
7
0
2
4
6 d /r T
(b)
8
10
12
Figure 4. (a) Normalized iT –d curves recorded for different mediators in a HEPES buffer (20 mM) with D-glucose (50 mM) and mediator (0.05 mM): (A) FcCH2 OH, (B) FcCOOH, (C) PAP; (b) dependency of kinetically controlled substrate current (is ) on ∗ normalized working distance (d/rT ) and substrate concentration cFcCH . The mediator concentration is (A) 0.05, (B) 0.5, (C) 2 mM; 2 OH ∗ Inset: is —cFcCH curves were the working distance d/a is 0.96 ( ), 2.08 (•), 4.00 (), 6.08 (+), 8.00 (∇); rT = 12.5 µm, Rg = 10, 2 OH rs = 100 µm. [Reprinted with permission Zhao and Wittstock52 copyright 2004, American Chemical Society.]
The choice of the right mediator was proved to be important (Figure 4) as it influences the normalized approaching curves depending on the mediator’s sensitivity to the enzyme. The highest feedback current and thus the most sensitive mediator found was PAP but it showed poor long-time stability. As mentioned in the introduction, the resolution in the feedback mode is generally higher than that of corresponding G/C images. This has been clearly demonstrated by Wittstock et al.32 by comparing a feedback scan across the center of a GDH immobilized microspot (Figure 5a) and a G/C line scan (Figure 5b). The 2 spots can be fully separated in the feedback mode, while in the G/C mode, even when they are about 900 µm apart, an overlap of the peaks can be seen, making the resolution advantage of the G/C mode obvious. When imaging densely packed, patterned enzyme arrays, feedback mode is the first choice even though the sensitivity is limited. These three examples show the use of SECM for the qualitative analysis of biocatalytic reactions. SECM can furthermore provide a detailed quantitative analysis of biocatalysis. When the oxidoreductase enzyme is immobilized on the surface the UME, current (iT ) depends on the mass transport rate and the enzyme kinetics. From the dependence of iT on the distance d, called approach curve, kinetic information can be extracted. If we take the feedback-mode case, when the mediator is fed back under diffusion-controlled conditions, iT − d is identical to that over a conducting surface, while
in the opposite case (the rate of mediator fed back from the sample is less than the rate of mediator diffusion to the UME from the bulk) the approach curve will be identical to that above an insulating surface. Between those limiting cases the iT − d curve contains information on the steady-state rate of the enzymatic reaction. In the feedback mode, the whole family of SECM working curves (IT vs L) can be described by equation (3a).92 IT is the normalized current (IT = iT /i∞ with iT being the current recorded on the tip and i∞ being the steady-state current, recorded when the tip is far away from the surface) and L is the normalized tip–substrate distance (L = d/a; a is the radius of the tip, and d is distance from the surface) IT (L) = IS (L) × 1 −
ITINS (L) ITC (L)
+ ITINS (L)
0.78377 + 0.3315 × exp(−1.0672/L) L 1 (3a) + ITI NS = (0.292 + 1.5151)/L + 0.6553 × exp(−2.4035/L)
ITC (L)
where ITC (L) and ITINS (L) represent the tip currents for the diffusion-controlled regeneration of a redox mediator on a conductive and nonconductive surface, respectively, and IS (L), the finite substrate kinetics. ITC , ITINS , and IS may be represented by
SCANNING ELECTROCHEMICAL MICROSCOPY
80
5.8
70
5.6
60
5.4
50
i (pA)
i (nA)
6
5.2
40 30
5 350 µm
4.8
900 µm
20
4.6
10 0
(a)
7
100
200
300
400
500
600
700
x (µm)
0 (b)
500
1000
1500 x (µm)
2000
2500
Figure 5. Comparison of the resolution ability of feedback and G/C mode. (a) Feedback scan profile across the centers of two GDH immobilized microspots, (b) G/C scan profile across the centers of the galactosidases immobilized microspots. [Reprinted with permission Zhao and Wittstock32 copyright 2005, Elsevier.]
the following analytical approximations:93 0.78377 L + 0.3315 × exp(−1.0672/L) + 0.68 (3b) 1 ITINS (L) = (0.292 + 1.5151/L + 0.6553) −2.4035 (3c) × exp L ITC (L) =
iS (L) (3d) i∞ 0.78377 IS (L) = [L(1 + 1/)] (0.68 + 0.3315) × exp(−1.0672/L) + [1 + F(L, )] (4a) d (4b) = keff × Dred (11/ + 7.3) (4c) F(L, ) = (110–40 L)
IS (L) =
In the case of GDH surface catalysis, SECM feedback experiments were carried out at different mediator concentrations (FcCH2 OH,
50 µM–2.2 mM) keeping the glucose concentration constant at 50 mM (Km,glucose ≤ 24 mM for native GDH in solution).94 Figure 4(b) shows the dependence of kinetically controlled substrate current iS (L) on normalized working distance L for different FcCH2 OH concentrations as well as the change of iS (L) with concentration. As one can see, iS (L) increases at lower working distance and is proportional to the substrate concentrations showing an obvious characteristic of first-order kinetics. This first-order kinetic behavior was attributed to the high catalytic activity of GDH. Following an analytical treatment of first-order enzymatic kinetics (equation 4a) at the sample surface (for 0.1 < L < 1.5)92 where keff is the first-order apparent heterogeneous rate constant (cm s−1 ) apparent rate constants that are in the order of keff = (3.0–37) × 103 cm s−1 could be obtained. The apparent turnover rate for first-order enzymatic kinetics kcat of GDH can be obtained from the limiting expression of the Michaelis–Menten equation (enz and the surface concentration) for small substrate concentrations (equation 5) of kcat = 1811 s−1 , which is rather small compared to native GDH (kcat = 5870 s−1 )94 and may be a result of partially deactivated GDH. Indeed, enz is highly critical for successful feedback detection.
8
THE BIOLOGY – MATERIALS INTERFACE
a radius rs . Equation (7a,b) allows the extraction of a current profile including the highest current value that corresponds to the center of the S bead spot (Figure 6). A surface concentration cred of 1.69 mM was found through fitting and confirms that only a small fraction of the provided enzyme substrate (cred of 10 mM) is converted and the enzyme reaction follows the regime of subS strate saturation. Knowing cred , the total flux ξ of mediator molecules generated at the microspot can be calculated using equation (8), which was in this case 3.14 × 10−13 mol s−1 . Assuming a uniform flux over the entire spot area, this value corresponds to a generation rate related to the projected area of the spot of J = ξ × (πrs2 ) = 1.78 × 10−9 mol s−1 cm−2 . Using equation (6) together with enz = 1.8 × 10−11 mol cm−2 , the maximal apparent turnover number kcat was calculated for a zero-order kinetics as 98 s−1 , which is about 7 times lower than the native membrane-bound GDH (727 s−1 using the same mediator).96 Similar considerations were taken into account for monitoring the β-galactosidase activity.54 Galactosidase, marked by high specificity and activity, is a very important marker for the lacZ gene, which encodes galactosidase and is frequently used as a reporter gene in animals and yeast. However, in contrast to GDH, galactosidase is not a redox enzyme allowing only G/C imaging in the presence of a galactosidase substrate like p-aminophenyl-βD-galactopyranoside (PAPG), which is converted
According to a simple enzymatic detection criteria (equation 6), the enzymatic SECM feedback-mode detection can be improved either by reducing the combined experimentally controllable factor (Dred , cred , a) or by increasing the combined enzyme-dependent factors, kcat , enz , and the surface concentration 46 kcat =
(keff Km ) enz
kcat enz ≥
10−3 Dred cred a
(5) (6)
In the case of G/C mode, quantitative analysis of the GDH catalysis was based on a model developed for diffusion to an isolated, disk-shaped pore.95 The current on the UME is given by S a iT = 4nFDred cred
(7a)
√ 2 arctan{ 2rs /[(r 2 + d 2 − rs2 ) π √ + [(r 2 + d 2 − rs2 )2 + 4d 2 rs2 ]} (7b)
=
S rs ξ = 4Dred cred
(8)
5 4.5 4
iT (nA)
5 4.5 4 3.5 3 2.5 2 1.5 1 900 800 700 600 500 400 300 200 100
3 2 1.5
y(
(a)
3.5 2.5
) mm
iT (nA)
S is the surface concentration of the where cred reduced form of the mediator (in this case Fe(CN)6 4− ), and is a dimensionless factor describing the decrease of the mediator as a function of the lateral distance, r, and the vertical distance, d, from the center of the spot having
1 0
0 900 0 600 700 80 300 400 50 0 100 200 x (µm)
0
200
(b)
400
600
800
x (µm)
Figure 6. (a) SECM G/C image of GDH activity using Fe(CN)6 3− as an electron acceptor in HEPES (20 mM) with D-glucose (50 mM), a = 12.5 µm, d = 30 µm, rs = 75 µm, v = 10 µm s−1 . (b) Profile across the G/C image (◦ ) of GDH activity. The ∗ solid lines are calculated from equation (7a,b) with the following parameters: cFe(CN) 4− = 10 mM, d = 30.45 µm, rs = 74.35 µm, 6
DFe(CN)3− = 6.19 × 10−6 cm s−1 , current offset: 0.91 nA. [Reprinted with permission Zhao and Wittstock32 copyright 2005, Elsevier.] 6
SCANNING ELECTROCHEMICAL MICROSCOPY NH2 OH CH2OH OH O O OH
+ H2O
Galactosidase
CH2OH OH OH O + OH
NH2 OH PAPG
OH
PAP
(a) 80 60 40
4
20
3
2 1
µm
)
1500 1000
y(
into easily detectable PAP where the tip–substrate distance as well as the concentration of PAPG was varied. No obvious loss of enzyme activity as a function of time after spotting was observed (Figure 7). Even though there was some variation in the appearance of the peaks by fitting data, it seemed that fairly uniform total flux values (5.22 ± 0.18 × 10−15 mol s−1 ) could be extracted from the four peaks. However, the flux related to the spot area showed considerable variation (5.2–6.3 × 10−12 mol s−1 cm−2 ), most likely because the appearance of the spots varied within the array. HRP is another enzyme belonging to the family of oxidoreductase. Feedback-mode imaging of HRP immobilized in a hydrogel using 1,4benzoquinone (BQ) as the redox mediator (E = −0.12 VAg/AgCl ) was used by Bard et al.58 to chemically image immobilized enzymes and to estimate the number of enzymes within the site (Figure 8). The reaction of hydrogen peroxide with the formed hydroquinone (HQ) is indeed negligibly slow in the absence of an appropriate catalyst but could be catalytically enhanced with HRP present. The detection of HRP, GOx, and other enzymes is so well established nowadays that the detection of both enzymatic reactions on a multianalytic sensing plate was shown.42,47,97 As one can understand from Figure 9, hydrogen peroxide formed through glucose oxidation can be used as a cosubstrate for the reduction of hydrogen peroxide in the presence of hydroxymethyl ferrocene (FMA)56 and
9
500 0
(b)
0
00 00 25 0 20 0 5 1 1000 x (µm) 500
Figure 7. (a) Reaction scheme for the biocatalytic reaction of PAPG using galactosidase and (b) G/C image of a galactosidase microspot array, cPAPG = 2 mmol, a = 12.5 µm, s v = 10 µm s−1 . Peak 1: d = 71 µm, rs = 145 µm, cPAPP = s 10.1 µmol; peak 2: d = 70 µm, rs = 140 µm, cPAPP = s 9.8 µmol; peak 3: d = 68 µm, rs = 159 µm, cPAPP = 8.6 µmol; s peak 4: d = 67 µm, rs = 162 µm, cPAPG = 9.0 µmol. [Reprinted with permission Zhao et al.54 copyright 2004, Elsevier.]
HRP. The SECM image of a GOx grid detecting the enzymatically generated hydrogen peroxide in the G/C mode is seen in Figure 9 together with the schema of the patterned interface. 0 µm
1.42e-8A
1.11e-8A
8.08e-9A O2 + 2H+
BQ
HQ
H2O2 5.03e-9A
HRP 1.98e-9A (a)
(b)
0 µm
100 µm 100 µm
Figure 8. (a) Reaction scheme of the 1,4-benzoquinone (BQ)/hyroquinone (HQ) reaction on a HRP hydrogel; (b) SECM image of a polycarbonate filter membrane supported by an electrode: ET = −0.4 VAg/AgCl , d = 1 µm, Pt-UME. [Reprinted with permission Zhou et al.58 copyright 2002, American Chemical Society.]
10
THE BIOLOGY – MATERIALS INTERFACE
FMA+ O2
H2O2
Glucose
H2O2
Gluconolactone
FMA
OH− FMA+
FMA
GOx
HRP
(a)
125 µm
−20 pA
SAM a
a
a
X
a
a
a
a
a
X
a
a
a
a
HRP
a GOx
(b)
a
a
a
−10 pA
(c)
Figure 9. (a) Schematic presentation of the SECM G/C-mode multienzymatic experiment having a GOx- and HRP-patterned surface, (b) scheme of the patterned surface after electrochemical desorption and attachment of GOx, (c) experimental results in the presence of D-glucose, O2 , and Ferrocene hydroxymethyl, image frame 500 × 500 µm2 . [Reprinted with permission Serradilla Razola et al.56 copyright 2002, Elsevier.]
A rather different detection scheme was proposed by Matsue et al.57 The oxidation of luminol in the presence of HRP and hydrogen peroxide yields an excited state, which emits luminescence upon degradation into 3-aminophthalate and has allowed optical detection (Figure 10). Hydrogen peroxide can be formed locally through oxygen reduction on the UME. Matsue showed that a combination of SECM and scanning chemiluminescence microscopy (SCLM) allows the imaging of HRP on a glass surface. Indeed, development of combined methods and new techniques to obtain information on spatial and temporal distributions of biomolecules with high sensitivity on a micrometer scale are evoking interest.43,44,98–103 The basic principle of SECM/SCLM is illustrated in Figure 10(b). In short, the microelectrode tip was attached to some micromanipulators placed on an inverted microscope with a photon counter. The photon-counting and current images were obtained
by mapping the photon-counting and current data against the position of the microelectrode tip. This set up was finally used for the imaging of diaphorase immobilized on glass and the generation of CL upon applying a potential pulse (0.0–1.0 VAg/AgCl for 30 s) is seen in Figure 10(c). The CL generation follows the potential pulse quite rapidly and its intensity increases instantaneously upon application of the potential to yield H2 O2 at the tip and stays constant throughout the pulse application. Since the tip is located 10 µm above the substrate and the sampling time is 0.5 s no obvious delay in the CL generation was observed. 3.2
Antigen, Antibody
Beside enzymes, antibodies have been used widely as selective agents in analytical problems because highly specific antibodies can be raised against a
SCANNING ELECTROCHEMICAL MICROSCOPY
hv + 3-Aminophthalate O2
H 2O 2
11
Luminol
HRP (a) XYZ countroller
4
Microelectrode tip
Photon counts
Dual -images computer Photon counter
hv
Dark box
500 I (nA)
Ag/AgCl
(b)
Current 2
0 0
Objective
−2
Mirror
−4 (c)
0
50
100
150
Photon counts (s)
Potentiostat
Counting board
1000
XYZ stage
−500 200
Times (s)
Figure 10. (a) Reaction schematic for the chemiluminescence of luminol in the presence of HRP, (b) schematic diagram illustrating the operating principle, (c) responses of the chemiluminescence intensity and reduction current of oxygen upon pulsed-potential application in a 0.2 M NaH2 PO4 buffer solution (pH 8.7) containing 1.56 mM luminol and 0.1 M KCl, E = 1 VAg/AgCl for 30 s and E = 0 VAg/AgCl for 30 s, sampling time 0.5 s. [Reprinted with permission Zhou et al.57 copyright 2001, Elsevier.]
large variety of substances. The surface immobilization of antibodies is a preferred way of immunosensing, in particular to facilitate the separation of the formed antigen–antibody complexes from the sample. Layers of immobilized immunoglobulins have been investigated with spectroscopic techniques. However, these techniques detect only the presence of proteins on the surface but do not allow one to determine whether the immobilized biomolecules still exhibit their binding functions. In this respect, SECM can add valuable insight to the visualization of an aminated silica glass capillary immobilized oxidized monoclonal anti-dioxygen (antibody) using SECM in the G/C as shown by Heinemann et al.65 The principle is based on the use of first dioxin and then alkaline phosphatase–labeled dioxin (antigen) to cover the remaining active sites. Alkaline phosphatase–labeled dioxin catalyzes the hydrolysis
of the redox-inactive 4-aminophenyl phosphate to the redox-active 4-aminophenol detected on the UME. If the 4-aminophenyl phosphate concentration is high enough to maintain zero-order enzymatic kinetics, the magnitude of the current on the UME represents a measure of the density of active sites on the layer of immobilized antibodies. Matsue64 used the feedback mode to characterize the carcinoembryonic antigen–antibody complex on glass using a HRP-labeled anticarcinoembryonic. The reduction current of the oxidized form of ferrocenylmethanol generated by the HRP reaction was monitored to view SECM images. The same group developed an immunoassay based on this approach for leukocidin, which is a toxic protein produced by methicillin resistant Staphylococcus aureus (MRSA) and causing hospital infection all over the world.63
12
3.3
THE BIOLOGY – MATERIALS INTERFACE
seen can be attributed to nanoparticle tagging. Figure 11(c) shows the same protein spot imaged by SECM. Thought the images are somehow tilted due to different membrane positioning under the microscope or the SECM, the spot shapes are very similar. Much higher currents can be observed on the edges of the spots explained by the well-known “donut effect” in drop spots assays: as the protein solution drop evaporates it becomes more concentrated at its periphery. The choice of the mediator is important; Os(bpy)3 2+ was used because its standard potential (E 0 = 0.631VSCE ) is positive enough so that its oxidized form is able to accept an electron from the silver atoms attached to BSA on the substrate 0 + = 0.558VSCE ). Protein amounts as low (EAg/Ag as 0.1 ng could be detected through a change in feedback from negative on the PVDF membranes without BSA to positive where BSA tagged with silver nanoparticles is present.
Proteins
The work on SECM of proteins is until now limited to only a few reports.80,81 The biochemical detection of protein spots on flat or pseudo two-dimensional surfaces such as gels or polymeric membranes is done mainly through staining techniques. Recently, metallic nanoparticles have received a lot of attention in bioanalysis where they are used as signal-amplification agents or as quantitative tags. Silver nanoparticles also formed the bases of the approach by Girault,81 where they were tagged to bovine serum albumin (BSA) attached to polyvinylidene difluoride (PVDF) membranes through hydrophobic interactions (Figure 11a). Figure 11(b) shows an optical image of a protein spot obtained from a 1.7 nM BSA solution after staining with silver particles and washing. As untagged protein spots are not visible on the membrane, all the morphology
Ag+
Os(bpy)32+
Os(bpy)33+ Ag
BSA (a)
PVDF membrane 0
5.78e-10A
4.60e-10A
Y (µm)
3.42e-10A
2.25e-10A
100 µm (b)
1.07e-10A (c)
400 410
0
X (µm)
Figure 11. (a) Schematic presentation of the protein detection, (b) optical image of a protein spot (1.7 nM protein solution spotted, corresponding to 0.1 ng deposited) after tagging with silver nanoparticles, and (c) SECM image of the same protein spot. [Reprinted from Carano et al.81 , with permission from Elsevier.]
SCANNING ELECTROCHEMICAL MICROSCOPY
Recently, the first report on the imaging of photosystem I (PSI) has been published using the change of surface conductivity.80 PSI is found in nature in cyanobacteria as a 12-unit supramolecular protein complex, while in green plants and algae it has 3–4 additional subunits, yielding a molecular mass of about 300 kDa. PSI contains specialized chlorophyll, a dimer (P700 center) that enables diodelike behavior upon excitation by photons of light. The study is rather qualitative in nature: ferrocenyl-methyltrimethylammonium hexafluorophosphate and hexaammineruthenium (II) chloride were used as mediators in the feedback mode to map the surface reactivity. While positive feedback was observed on the parts where the gold surface was unmodified, gold modified with thiol groups where PSI is attached behaves more like an insulator.
3.4
Cells
After the first demonstrations of SECM on living samples such as grass and Ligustrum sinensis leaves to obtain topographic images and to measure the production of oxygen from an Elodea leaf during photosynthesis, the use of SECM has been broadened to the investigation of phenomena occurring in other living biological systems such as living cells.38 The interest in imaging biological cells is due to the need to uncover their microscopic structural and physiological properties. SECM feedback-mode imaging however cannot be so easily adjusted to cell imaging, because SECM cannot distinguish easily between variations in the tip–sample distance and changes in the local electrochemical activity. As cells are a priori not flat, new considerations have to be made. In order to overcome this limitation, different tip approaches have been considered. Mirkin66,69 and Schuhmann73,104 showed different approaches for the imaging of living cells. Mirkin used classical amperometric feedback and potentiometric G/C modes to image the topography and acid–base activation in single mammalian cells. Negative SECM feedback topographic images of a mammalian cell membrane were obtained using hydrophilic redox mediators (e.g., ferrocyanide), which cannot penetrate into the cell membrane. In contrast, hydrophobic mediators (e.g., menadione or 1,2-naphthoquinone) can enter the cell
13
and be regenerated at a measurable rate. Matsue et al.72 used SECM to study the respiration of a mammalian cells (HeLa cells) as images of the oxygen concentration around a cell directly reflect the respiration activity and can serve as a measure of the cell status. The oxygen concentration was mapped by scanning a Pt electrode over the cell and by mapping the reduction current of oxygen. This group furthermore used an Sb tip in potentiometric mode for acidrelease imaging and could differentiate between normal human breast cells and metastatic breast cells. Schuhmann adapted a shear-force-based constant-distance control of the tip to the biological cells.14 Shear-force-based constant-distance control is based on the vibrating of the UME at its resonance frequency with typical amplitude of only a few nanometers, through the help of a piezopusher. Simultaneously, a laser beam is focused onto the very end of the vibrating tip and the resulting Fresnel diffraction pattern is projected onto a split photodiode. Amplitude and phase information about the vibrating tip is obtained by the diode with respect to the agitation signal using a lock-in amplifier. With decreasing tip–sample distance, increasing shear force leads to a decrease of the vibration amplitude and to a phase shift. Carbon fiber–based electrodes had to be used in combination with the shear-force approach because by using Pt microelectrodes the cells were cut into pieces by the vibration electrode. The interaction force between the tip and the soft sample was too high. These optimized carbon fiber electrodes have been applied for the visualization of the topography of adherently growing PC12 cells, commonly used as a model neuronal cell type (Figure 12a). Moreover, the discrete release of hormones and neurotransmitters from cells during exocytose events has been investigated by placing a small glass capillary, which is connected to a liquid dispensing system, in close proximity to the cell, and provoking exocytose events by application of elevated K+ concentrations. Owing to the small gap between tip and surface, the released neurotransmitters (catecholamines, adrenaline, noradrenalin, dopamine) are consumed at the 700-mV posed electrode with 100% collection efficiency (Figure 12b).
14
THE BIOLOGY – MATERIALS INTERFACE 4.5
z (µm)
4 3.5 3 2.5
60
y(
) µm
40
20
60 40 20
0 (a)
x (µm)
0 120
120 100
100
80
I (pA)
60
80
I (pA)
40 20
80
12.10
40
12.12
12.14
12.16
12.18
12.20
t (s) 20
0
5
10
(b)
15
20
25
30
t (s)
Figure 12. (a) Shear-force-based topographic imaging an individual of PC12 cell, (b) recording of single exocytotic events of a PC12 cell after application of K+ ions. The inset shows the time course of the oxidation current with an expanded timescale of a selected signal event (ET = 700 mVAg/AgCl ). [Reprinted with permission Hengstenberg et al.14 copyright 2001, Wiley VCH.]
PC12 cells were also investigated by SECM before and after exposure to nerve growth factors (NGF) to detect small changes in cell morphology in real time. When exposed to NGF, PC12 cells differentiated into a neuron phenotype by growing narrow neurites that were able to extend 100 µm from the proper cell.67,68
3.5
DNA Hybridization Detection
The tremendous effort toward the fabrication of DNA microarrays and the development of sensitive, selective, and high-throughput DNA microarray chip detectors stems from the potential of
SCANNING ELECTROCHEMICAL MICROSCOPY
the DNA chips for applications in disease diagnosis and gene expression. Thus far, the standard method for the detection of hybridization is confocal fluorescence imaging using fluorescencelabeled target DNA. One of the major drawbacks of fluorescence detection is, beside size and price, the quenching of the fluorescent dyes with time. Electrochemical hybridization methods are an interesting alternative to optical readouts and have been demonstrated as being a sensitive and selective means for the study of DNA oxidative damage, for trace DNA analysis, as well as for the detection of hybridization events.105,106 The use of SECM for imaging hybridization reactions is interesting as this electrochemical scanning probe method is comparatively inexpensive, compact, and sensitive to change in surface conductivity. Additionally, the lateral resolution of the SECM is sufficient for imaging even DNA arrays of high density. Preliminary studies for detecting the DNA hybridization using GOx were reported by Toth et al.10 Electroactive hybridization indicators were used by Takenaka82 for the visualization of DNA microarrays. Zhou et al. showed a different approach for DNA imaging. Guanine residues on the DNA molecules are electroactive, and tip-generated Ru(bpy)3 3+ can induce guanine oxidation and was
15
used for DNA imaging. The same group showed that DNA hybridization can be visualized with SECM using silver enhancement (Figure 13).39 The ODN probes (17-mer) immobilized on the microarray surface were hybridized with a biotinylated complimentary strand and developed by a silver staining process. Because of the staining process, the surface conductivity of the region where hybridization had taken place increased and was selectively detected with a SECM tip and allowed single-base-mismatch DNA analysis. The detection level for a 17-mer was found to be at 30 amol per spot. Schuhmann et al. recently reported an electrochemical detection scheme that was suited for imaging microscopic spots of immobilized nucleic acids.84 The method is based on a modulation of diffusional mass transport of a negatively charged redox mediator (e.g., [Fe(CN)6 ]3−/4− ) that is experiencing electrostatic repelling forces from deprotonated, and thus identically charged, phosphate groups of surface-anchored capture probes (Figure 14). Electrostatic repulsion between An− and the phosphate groups at the backbone of the immobilized DNA strand hinders diffusion of the redox mediator to the gold surface. For ssDNA the flux of An− (Jss ) is higher than for dsDNA (Jds ) due to the increase in negative charges through Au nanoparticle Streptavidine
Ru(NH3)6 3+ Ru(NH3)6 2+
Biotinylated complementary ODN
Ru(NH3)6 3+ Ru(NH3)6 2+ Oligonucleotide (a) I (mA) 2.5
1.4
(b) 500 µm Figure 13. (a) Schematic presentation of SECM imaging of DNA hybridization on a microarray, (b) SECM image of 6 spots with 51 nM of complementary target. [Reprinted with permission Wang et al.39 copyright 2002, American Chemical Society.]
16
THE BIOLOGY – MATERIALS INTERFACE An +
An +
S
An
S
_
An
_
S
S dsDNA
ssDNA
Figure 14. Schematic representation of the influence of coulomb interaction of the diffusion of anions toward DNAmodified chip surface.
formation of aggregates between the probe and the unlabeled target. Szunerits et al.28 added recently to this field by reporting on the use of SECM for the writing of oligonucleotide patterns on thin gold films alongside the imaging of DNA (15-mer) hybridization. Imaging of the deposited polypyrrole oligonucleotides as well as their hybridization with complementary and noncomplementary strands was achieved by means of the feedback mode of SECM using Ru(NH3 )6 3+ as the redox mediator. The detection of the hybridization reaction is possible after subsequent reactions with streptavidin and biotinylated HRP. The HRP-biocatalyzed oxidation of 4-chloro-1-naphthol (1) in the presence of H2 O2 , and the precipitation of the insoluble product 4-chloro-1-naphthon (2) on the hybridized areas on the gold film caused a local alteration of conductivity (Figure 15). Such a change in conductivity (the reverse of the case of silver staining)
can be sensitively detected by the SECM tip and allows the imaging of DNA arrays in a fast and straightforward way.
4 PERSPECTIVES AND CONCLUSION
SECM has proved over the years to be of interest in biotechnological problems such as the detection of the activity of locally immobilized enzymes or the detection of enzymatic products. The use of SECM for the study of living cells constitutes a nondestructive method for the investigation of complex cell reactions. Currently effort is being taken to extend the range of accessible enzymatic reactions and to apply SECM as a research tool for biochemical and physiological studies. As for all the scanning probe techniques, one of the major limitations of SECM is the minimal time of acquisition, which is often too long to study temporal evolutions of the biological activities. Furthermore, in the case of an amperometric probe, the scanning speed limit is imposed by the time necessary to establish a steady-state current at each point, while in the case of a potentiostatic measurement it is limited by the time needed to obtain a constant potential. This characteristic time can be decreased by decreasing the probe size as well as the tip–sample distance. Additionally, scanning in constant height across the sample surface results in a convolution of the electrochemical response and the topographical information. Consequently, any progress toward improved lateral resolution for imaging of biological systems has
E T = −0.5 V
Ru(NH3)64+
(2) + H2O
(1) + H2O2
Ru(NH3)63+
O
OH HRP
HRP
HRP HRP
Precipitation
Cl (1)
Ru(NH3)64+
H2O2
H2O
H
Cl
(2)
Ru(NH3)63+ N N N N N N
Figure 15. Schematic representation of negative feedback SECM imaging of DNA array. [Reprinted from Fortin et al.28 , with permission from Royal Society of Chemistry.]
SCANNING ELECTROCHEMICAL MICROSCOPY
to address current-independent positing systems together with the use of nanometer-sized electrodes. With the integration of nanoelectrodes into AFM probes using focused ion beam milling of metal-coated cantilever tips, an elegant approach combining SECM and AFM has been recently introduced by Kranz.44 SECM/AFM allows us to obtain topographic and electrochemical information with high lateral resolution in a single timeand space-correlated measurement and was already successfully applied to enzymes and soft samples. Demaille et al. has added to this field by attaching flexible polymer chain layers to SECM/AFM probes.107 An alternative is combining SECM with nearfield scanning microscopy (NSOM) surface approaches.14,17,108–110 In NSOM, positioning of the tip (in this case an etched or pulled and metal covered optical fiber) is shear-force based, often based on a tuning fork resonator system.111 As mentioned before, surface shear force increases because of hydrodynamic effects in close proximity to the sample and leads to amplitude damping and phase shift of oscillation. In the case of SECM/NSOM the optical fiber has to be replaced by a nanoelectrode. Different ways of fabricating such tips have been reported but have not been used in combination with biological samples. We are currently developing an electrochemical NSOM based on gold-covered, pulled optical fibers for the construction of DNA chips based on conducting polymer chemistry on boron-doped diamond electrodes.103 An alternative approach is to use the impedance of the SECM tip as a distance-dependent signal. First used by Bard11 and further developed by others,13,15,67 this technique modulates the impedance signal between the tip and the substrate at high frequency so that it can be detected separately from the low-frequency voltammetric signal. For neuron imaging, this approach has some important advantages, such as, it requires no mediator as the ions in solution provide the signal, the faradaic current can be detected simultaneously with the determination of the morphology, and it is instrumentally simpler compared to shear-force approaches. As the theory of SECM and its basic use is very well understood, the future of SECM will be use in more complex environments and configurations. SECM will thus also deal more with the accurate
17
positioning of micro- and nanosensor tips just as recently shown for the amperometric detection of the release of NO from a growing cell after stimulation with a suitable agent.73
REFERENCES 1. A. J. Bard, F.-R. F. Fan, J. Kwak, and O. Lev, Scanning electrochemical microscopy. Introduction and principles. Analytical Chemistry, 1989, 61, 132. 2. N. Dontha, W. B. Nowall, and W. G. Kuhr, Generation of biotin/avidin/enzyme nanostructures with maskless photolithography. Analytical Chemistry, 1997, 69, 2619. 3. E. Delamarche, A. Bernard, H. Schmidt, A. Bietsche, B. Michel, and H. Biebuyck, Microfluidic networks for chemical patterning of substrates: design and application to bioassays. Journal of the American Chemical Society, 1998, 120, 500. 4. Y. Li, B. W. Maynor, and J. Liu, Electrochemical AFM dip pen nanolithography. Journal of the American Chemical Society, 2001, 123, 2105. 5. D. J. Pritchard, Hywel. Morgan, and J. M. Cooper, Micron-scale patterning of biological molecules. Angewandte Chemie International Edition English, 1995, 34, 91. 6. Y. Xia and G. M. Whitesides, Soft lithography. Angewandte Chemie International Edition English, 1998, 37, 550. 7. A. J. Bard and M. V. Mirkin, in Scanning Electrochemical Microscopy, A. J. Bard, M. V. (eds), Marcel Dekker, New York, 2001, p. 1–637. 8. C. Amatore, in Electrochemistry at Ultramicroelectrodes, Vol. Rubinstein ed, Marcel Dekker, New York, 1995, Chapter 4. 9. C. A. Mirkin, High resolution studies of heterogeneous processes with the scanning electrochemical microscope. Mikrochimica Acta, 1999, 130, 127. 10. R. E. Gyurcsanyi, G. Jagerszki, G. Kiss, and K. Toth, Chemical imaging of biological systems with the scanning electrochemical microscope. Bioelectrochemistry, 2004, 63, 207. 11. B. Horrocks, D. Schmidtke, A. Heller, and A. J. Bard, Scanning electrochemical microscopy. 24. Enzyme ultramicroelectrodes for the measurement of hydrogen peroxide at surfaces. Analytical Chemistry, 1993, 15, 3605. 12. B. R. Horrocks, C. A. Mirkin, D. T. Pierce, A. J. Bard, G. Nagy, and K. Toth, Scanning electrochemical microscopy. 19. Ion-selective potentiometric microscopy. Analytical Chemistry, 1993, 65, 1213. 13. C. Gabrielli, F. Huet, M. Keddam, P. Rousseau, and V. Vivier, Scanning electrochemical microscopy imaging by means of high-frequency impedance measurements in feedback mode. Journal of Physical Chemistry B, 2004, 108, 11620. 14. A. Hengstenberg, A. Blochel, I. D. Dietzel, and W. Schuhmann, Spatially resolved detection of neurotransmitter secretion from individual cells by means
18
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
THE BIOLOGY – MATERIALS INTERFACE of scanning electrochemical microscopy. Angewandte Chemie International Edition English, 2001, 40, 905. B. B. Katemann, C. G. Inchauspe, P. A. Castro, A. Schulte, E. J. Calvo, and W. Schuhmann, Precursor sites for localised corrosion on lacquered tinplates visualised by means of alternating current scanning electrochemical microscopy. Electrochimica Acta, 2003, 48, 1115. Y. Lee and A. J. Bard, Fabrication and characterization of probes for combined scanning electrochemical/optical microscopy experiments. Analytical Chemistry, 2002, 74, 3626. Y. Lee, Z. Ding, and A. J. Bard, Combined scanning electrochemical/optical microscopy with shear force and current feedback. Analytical Chemistry, 2002, 74, 3634. C. Kranz, M. Ludwig, H. E. Gaub, and W. Schuhmann, Lateral deposition of polypyrrole lines by means of the SECM. Advanced Materials, 1995, 7, 38. C. Kranz, M. Ludwig, H. E. Gaub, and W. Schuhmann, Lateral deposition of polypyrrole lines over insulating gaps towards the development of polymer-based electronic devices. Advanced Materials, 1995, 7, 568. C. Kranz, G. Wittstock, H. Wohlschlager, and W. Schuhmann, Imaging of microstructured biochemically active surfaces by means of scanning electrochemical microscopy. Electrochimica Acta, 1997, 42, 3105. D. Mandler, in Micro—and Nanopatterning Using Scanning Electrochemical Microscopy, A. J. Bard and M. V. Mirkin (eds), Marcel Dekker, New York, 2001. S. Szunerits, R. Calemczuk, B. Corso, E. Descamps, Y. Defontaine, J.-B. Fiche, E. Fortin, T. Livache, P. Mailley, A. Roget, and E. Vieil, Review: different strategies on DNA chip fabrication and DNA sensing: optical and electrochemical approaches. Electroanalysis, 2005, 17, 2001–2017. S. Szunerits, N. Knorr, R. Calemczuk, and T. Livache, A new approach to writing and simultaneous reading of micropatterns: combining surface plasmon resonance imaging (SPR-i) with scanning electrochemical microscopy (SECM). Langmuir, 2004, 20, 9236. T. Wilhelm and G. Wittstock, Patterns of functional proteins formed by local electrochemical desorption of self assembled monolayers. Electrochimica Acta, 2001, 47, 275. G. Wittstock, R. Hesse, and W. Schuhmann, Patterned self-assembled alkanethiolate monolayers on gold. Patterning and imaging by means of scanning electrochemical microscopy. Electroanalysis, 1997, 9, 746. G. Wittstock and W. Schuhmann, Formation and imaging of microscopic enzymatically active spots on an alkanethiolate-covered gold electrode by scanning electrochemical microscopy. Analytical Chemistry, 1997, 69, 5059. S. A. G. Evans, C. Brakha, M. Billon, P. Mailley, and G. Denuault, SECM: localised. Electrochemistry Communications, 2005, 7, 135. E. Fortin, P. Mailley, L. Lacroix, and S. Szunerits, Imaging of DNA hybridization on microscopic polypyrrole patterns using scanning electrochemical microscopy (SECM): the HRP bio-catalyzed oxidation of 4-chloro-1naphthol. Analyst, 2006, 131, 186.
29. E. Fortin, Y. Defontaine, P. Mailley, T. Livache, and S. Szunerits, Micro-imprinting of oligonucleotides and oligonucleotide gradients on gold surfaces: a new approach based on the combination of scanning electrochemical microscopy and surface plasmon resonance imaging (SECM/ SPR-i). Electroanalysis, 2005, 17, 495. 30. I. Turyan, T. Matsue, and D. Mandler, Patterning and characterisation of surfaces with organic and biological molecules by the SECM. Analytical Chemistry, 2000, 72, 3431. 31. C. A. Wijayawardhana, G. Wittstock, H. B. Halsall, and W. R. Heinemann, Spatially addressed deposition and imaging of biochemically active bead microstructures by scanning electrochemical microscopy. Analytical Chemistry, 2000, 72, 333. 32. C. Zhao and G. Wittstock, Scanning electrochemical microscopy for detection of biosensor and biochip surfaces with immobilized pyrroloquinoline quinone (PQQ)-dependent glucose dehydrogenase as enzyme label. Biosensors and Bioelectronics, 2005, 20, 1277. 33. H. Shiku, T. Takeda, H. Yamada, T. Matsue, and I. Uchida, Microfabrication and characterization of diaphorase-patterned surfaces by scanning electrochemical microscopy. Analytical Chemistry, 1995, 67, 312. 34. H. Shiku, I. Uchida, and T. Matsue, Microfabrication of alkylsilanized glass substrate by electrogenerated hydroxyl radical using scanning electrochemical microscopy. Langmuir, 1997, 13, 7239. 35. W. B. Nowall, N. Dontha, and W. G. Kuhr, Electron transfer kinetics of a biotin/avidin patterned glassy carbon electrode. Biosensors and Bioelectronics, 1998, 13, 1237. 36. W. B. Nowall, W. B. Wipf, and W. G. Kuhr, Localized avidin/biotin derivatization of glassy carbon electrodes using SECM. Analytical Chemistry, 1998, 70, 2601. 37. A. L. Barker, P. Unwin, C. E. Gardner, and H. Rieley, A multi-electrode probe for parallel imaging in scanning electrochemical microscopy. Electrochemistry Communications, 2004, 6, 91. 38. C. M. Lee, J. Y. Kwak, and A. J. Bard, Application of scanning electrochemical microscopy to biological samples. Proceedings of the National Academy of Sciences of the United States of America, 1990, 87, 1740. 39. J. Wang, F. Song, and F. Zhou, Silver-enhanced imaging of DNA hybridization at DNA microarrays with scanning electrochemical microscopy. Langmuir, 2002, 18, 6653. 40. J. Wang and F. Zhou, SECM imaging of surfaceconfined DNA probes and their hybridisation via guanine oxidation. Journal of Electroanalytical Chemistry, 2002, 537, 95. 41. K. Yamashita, M. Takagi, K. Uchida, H. Kondo, and S. Takenaka, Visualization of DNA microarrays by scanning electrohcmial microscopy (SECM). Analyst, 2001, 126, 1210. 42. S. Gaspar, M. Mosbach, L. Wallman, T. Laurell, E. Csoregi, and W. Schuhmann, A method for the design and study of enzyme microstructures formed by means of a flow through microdispenser. Analytical Chemistry, 2001, 73, 4254. 43. S. Kasai, Y. Hirano, N. Motochi, H. Shiku, M. Nishizawa, and T. Matsue, Simultaneous detection of uric acid
SCANNING ELECTROCHEMICAL MICROSCOPY
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
and glucose on a dual enzyme chip using scanning electrochemical microscopy/scanning chemiluminescence microscopy. Analytica Chimica Acta, 2002, 458, 263. A. Kueng, C. Kranz, A. Lugstein, E. Bertagnolli, and B. Mizaikoff, Integration AFM-SECM in tapping mode: simultaneous topographical and electrochemical imaging of enzyme activity. Angewandte Chemie International Edition English, 2003, 42, 3238. D. T. Pierce and A. J. Bard, Scanning electrochemical microsop. 23. Reaction localization of artificially patterned and tissue-bound enzymes. Analytical Chemistry, 1993, 65, 3598. D. T. Pierce, P. R. Unwin, and A. J. Bard, Scanning electrochemical microscopy. 17. Studies of enzymemediator kinetics for membrane and surface immobilized glucose oxidase. Analytical Chemistry, 1992, 64, 1795. M. Mosbach, H. Zimmermann, T. Laurell, J. Nilsson, E. Csoregi, and W. Schuhmann, Picodroplet-deposited of enzymes on functionalized self-assembled monolayers as a basis for miniaturized multi-sensor structures. Biosensors and Bioelectronics, 2001, 16, 827. F.-R. Fan and A. J. Bard, Imaging of biological macromolecules on mica in humid air by scanning electrochemical microscopy. Proceedings of the National Academy of Sciences, 1999, 96, 14222. D. G. Georganopoulou, D. J. Caruana, J. Strutwolf, and D. E. Williams, Electron transfer mediated by glucose oxidase at the liquid/liquid interface. Faraday Discussions, 2000, 116, 109. C. A. Wijayawardhana, G. Wittstock, H. B. Halsall, and W. R. Heineman, Electrochemical immunoassay with microscopic immunomagnetic bead domains and scanning electrochemical microscopy. Electroanalysis, 2000, 12, 640. B. Csoka, B. Kovacs, and G. Nagy, Investigation of concentration profiles inside operating biocatalytic sensors with SECM. Biosensors and Bioelectronics, 2003, 18, 141. C. Zhao and G. Wittstock, Scanning electrochemical microscopy of quinoprotein glucose dehydrogenase. Analytical Chemistry, 2004, 76, 3145. M. Niculescu, S. Gaspar, A. Schulte, E. Csoregi, and W. Schuhmann, Visualization of micropatterned complex biosensor sensing chemistries by means of scanning electrochemical microscopy. Biosensors and Bioelectronics, 2004, 19, 1175. C. Zhao, J. K. Sinha, C. A. Wijayawardhana, and G. Wittstock, Monitoring b-galactosidase activity by means of scanning electrochemical microscopy. Journal of Electroanalytical Chemistry, 2004, 561, 83. S. A. G. Evans, J. M. Elliott, L. M. Andrews, P. N. Bartlett, P. J. Doyle, and G. Denault, Detection of hydrogen peroxide at mesoporous platinum microelectrode. Analytical Chemistry, 2002, 74, 1322. S. Serradilla Razola, B. Lopez Ruiz, N. Mora Diez, H. B. Mark, and J.-M. Kauffmann, Hydrogen peroxide sensitive amperometric biosensor based on horseradish peroxidase entrapped in a polypyrrole electrode. Biosensors and Bioelectronics, 2002, 17, 921. H. Zhou, S. Kasai, and T. Matsue, Imaging localized horseradish peroxidase on a glass surface with scanning
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
19
electrochemical/chemiluminescence microscopy. Analytical Biochemistry, 2001, 290, 83. J. Zhou, C. T. Campbell, A. Heller, and A. J. Bard, Scanning electrochemical microscopy 44. Imaging of horseradish peroxidase immobilized on insulating substrates. Analytical Chemistry, 2002, 74, 4007. H. Yamada, H. Fukumoto, T. Yokoyama, and T. Koike, Immobilized diaphorase surfaces observed by scanning electrochemical microscope with shear force based tipsubstrate positioning. Analytical Chemistry, 2005, 77, 1785. M. Suzuki, T. Yasukawa, Y. Mase, D. Oyamatsu, H. Shiku, and T. Matsue, Dielectrophoretic micropatterning with microparticle monolayer covalently linked to glass surfaces. Langmuir, 2004, 20, 11005. O. Daisuke, Y. Hirano, N. Kanaya, Y. Mase, N. Matsuhiko, and T. Matsue, Imaging of enzyme activity by scanning electrochemical microscopy equipped with a feedback control for substrate-probe distance. Bioelectrochemistry, 2003, 60, 115. K. Wang, J.-J. Xu, D.-C. Sun, H. Wei, and X.-H. Xia, Selective glucose detection based on the concept of electrochemical depletion of electroactive species in diffusion layer. Biosensors and Bioelectronics, 2005, 20, 1366–1372. S. Kasai, A. Yokota, H. Zhou, M. Nishizawa, K. Niwa, T. Onouchi, and T. Matsue, Immunoassay of the MRSA related toxic protein, leukocidin, with scanning electrochemical microscopy. Analytical Chemistry, 2000, 72, 5761. H. Shiku, T. Matsue, and I. Uchida, Detection of microspotted carcinoembryonic antigen on a glass substrate by scanning electrochemical microscopy. Analytical Chemistry, 1996, 68, 1276. G. Wittstock, K.-Y. Yu, H. B. Halsall, T. H. Ridgway, and W. R. Heinemann, Imaging of immobilized antibody layer with scanning electrochemical microscopy. Analytical Chemistry, 1995, 67, 3578. W. Feng, S. A. Rotenber, and C. A. Mirkin, Scanning electrochemical microscopy of living cells. 5. Imaging of fields of normal and metastatic human breast cells. Analytical Chemistry, 2003, 75, 4148. R. T. Kurulugama, W. B. Wipf, S. A. Takacs, S. Pongmayteegul, P. A. Garris, and J. E. Bauer, Scanning electrochemical microscopy of model neurons: constant distance imaging. Analytical Chemistry, 2005, 77, 1111. J. M. Liebetauer, H. M. Miller, J. E. Bauer, S. A. Takacs, V. Anupunpisit, P. A. Garris, and W. B. Wipf, Scanning electrochemical microscopy of model neurons: imaging and real time detection of morphological changes. Analytical Chemistry, 2003, 75, 563. B. Liu, W. Chen, S. A. Rotenber, and C. A. Mirkin, Scanning electrochemical microscopy of living cells, Part 2. Imaging redox and acid/basic reactivities. Journal of Electroanalytical Chemistry, 2001, 500, 590. B. Liu, S. A. Rotenberg, and M. V. Mirkin, Scanning electrochemical microscopy of living cells. Mechanistic study of charge transfer reactions in human breast cells. Analytical Chemistry, 2002, 74, 6340. M. V. Mirkin, B. Liu, and S. A. Rotenberg, Probing redox activity of human breast cells by scanning
20
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
THE BIOLOGY – MATERIALS INTERFACE electrochemical microscopy. Methods in Enzymology, 2002, 352, 112. M. Nishizawa, K. Takoh, and T. Matsue, Micropatterning of HeLa cells on glass substrates and evaluation of respiratory activity using microelectrodes. Langmuir, 2002, 18, 3645. A. Pailleret, J. Oni, S. Reiter, S. Iski, M. Etienne, F. Bedioui, and W. Schuhmann, In situ formation and scanning electrochemical microscopy assisted positioning of NO-sensors above human umbilical vein endothelial cells for the detection of nitric oxide release. Electrochemistry Communications, 2003, 5, 847. H. Shiku, Y. Hara, T. Matsue, I. Uchida, and T. Yamauchi, Dual immunoassay of human chorionic gonadotropin and human placental lactogen at a microfabricated substrate by scanning electrochemical microscopy. Journal of Electroanalytical Chemistry, 1997, 438, 187. K. Takatoshi, T. Yu-suke, O. Daisuke, N. Matsuhiko, and M. Tomokazu, Monitoring the cellular activity of a cultured single cell by scanning electrochemical microscopy (SECM). A comparison with fluorescence viability monitoring. Biosensors and Bioelectronics, 2003, 18, 1379. K. Takoh, A. Takahashi, T. Matsue, and N. Matsuhiko, A porous membrane-base microelectroanalytical technique for evaluating locally stimulated culture cells. Analytica Chimica Acta, 2004, 522, 45. Y. Torisawa, T. Kaya, Y. Takii, D. Oyamatsu, M. Nishizawa, and T. Matsue, Scanning electrochemical microscopy (SECM)-based drug sensitivity test for cell culture integrated in silicon microstructures. Analytical Chemistry, 2003, 75, 2154. T. Yusuke, K. Takatoshi, T. Yuki, O. Daisuke, N. Matsuhiko, and M. Tomokazu, Scanning electrochemical microscopy-based drug sensitivity test for a cell culture integrated in silicon microstructures. Analytical Chemistry, 2003, 75, 2154. T. Yu-suke, H. Shiku, T. Yasukawa, N. Matsuhiko, and T. Matsue, Multi-channel 3-D cell culture device integrated on a silicon chip for anticancer drug sensitivity test. Biomaterials, 2005, 26, 2165. M. Ciobanu, H. A. Kincaid, G. K. Jennings, and D. E. Ciffel, Photosystem I patterning imaged by scanning electrochemical microscopy. Langmuir, 2005, 21, 692. M. Carano, N. Lion, J.-P. Abid, and H. Girault, Detection of proteins on poly(vinylidene difluoride) membranes by scanning electrochemical microscopy. Electrochemistry Communications, 2004, 6, 1217. S. Takenaka, DNA and RNA Binders: From Small Molecules to Drugs, Electrochemical detection of DNA with small Molecules, M. Demeunynck, C. Bailly, and W. D. Wilson (eds), Wiley interscience, Weinheim, 2003, vol. 1, Chapter 9, pp. 224–243. J. Wang, M. Jiang, A. Fortes, and B. Mukherjee, New label free DNA recognition based on doping nucleic acid probes within conducting polymer films. Analytica Chimica Acta, 1999, 402, 7. F. Turcu, A. Schulte, G. Hartwich, and W. Schuhmann, Imaging immobilised ssDNA and detection DNA hybridisation by means of the repelling mode of SECM. Biosensors and Bioelectronics, 2004, 20, 925.
85. E. A. H. Hall, in Biosensors, Vol. Editor, Prentice-Hall, Englewood Cliffs, New York, 1991. 86. R. E. Gyurcsanyi, G. Nagy, L. Nagy, A. Cristalli, M. R. Neuman, E. Lindner, R. P. Buck, H. T. Nagle, and S. Ufer, in Amperometric Microcells for Diagnostic Enzyme Activity Measurements, W. T. Law, N. Usami, and A. M. Usami (eds), Marcel Dekker, New York, 2002. 87. H. J. Bight and D. J. T. Porter, in Electron Transfer(II), Oxygenases, Oxidases(I), Vol. P. D. Boyer (ed), Academic, New York, 1975, Chapter 7, p. 88. T. Ruzgas, E. Csoregi, J. Emneus, L. Gorton, and G. Marko-Varga, Peroxidase-modified electrodes: fundamentals and application. Analytica Chimica Acta, 1996, 330, 123. 89. A. A. Karyakin, Prussian blue and its analogues: electrochemistry and analytical applications. Electroanalysis, 2001, 13, 813. 90. S. A. Salisbury, H. S. Forrester, W. B. T. Cruse, and O. Kennard, A novel coenzyme from bacterial primary alcohol dehydrogenases. Nature, 1979, 280, 843. 91. L. Ye, M. Haemmerle, A. J. J. Olsthoorn, W. Schuhmann, H. L. Schmidt, J. A. Duine, and A. J. Heller, High current density “wired” quinoprotein glucose dehydrogenase electrode. Analytical Chemistry, 1993, 65, 238. 92. C. Wei, A. J. Bard, and C. A. Mirkin, Scanning electrochemical microscopy. 31. Application of SECM to the study of charge transfer processes at the liquid/liquid interface. Journal of Physical Chemistry B, 1995, 99, 16033. 93. C. A. Mirkin, F.-R. F. Fan, and A. J. Bard, Scanning electrochemical microscopy part 13. Evaluation of the tip shapes of nanometer size microelectrodes. Journal of Electroanalytical Chemistry, 1992, 328, 47. 94. K. Matsushita, E. Shinagawa, O. Adachi, and M. Ameyama, Quinoprotein D-glucose dehydrogenase of the acinetobacter calcoaceticus respiratory chain: membranebound and soluble forms are different molecular species. Biochemistry, 1989, 28, 6276. 95. B. D. Bath, Rd. Lee, H. S. White, and E. R. Scott, Imaging molecular transport in porous membranes. observation and analysis of electroosmotic flow in individual pores using the scanning electrochemical microscope. Analytical Chemistry, 1998, 70, 1047. 96. D. Iswantini, K. Kano, and T. Ikeda, Kinetics and thermodynamics of activation of quinoprotein glucose dehydrogenase apoenzyme in vivo and catalytic activity of the activated enzyme in Escherichia coli cells. Biochemical Journal, 2000, 350, 917. 97. T. Wilhelm and G. Wittstock, Analysis of interaction in patterned multienzyme layer by using SECM. Angewandte Chemie International Edition English, 2003, 42, 2248. 98. Y. Hirata, S. Yabuki, and F. Mizutani, Application of integrated SECM ultra-microelectrode and AFM force probe to biosensor surfaces. Bioelectrochemistry, 2004, 63, 217. 99. C. Kranz, A. Kueng, A. Lugstein, E. Bertagnolli, and B. Mizaikoff, Mapping of enzyme activity by detection of enzymatic products during AFM imaging with integrated SECM-AFM probes. Ultramicroscopy, 2005, 100, 127. 100. C. E. Gardner, P. R. Unwin, and J. V. Macpherson, Correlation of membrane structure and transport activity
SCANNING ELECTROCHEMICAL MICROSCOPY
101.
102.
103.
104.
105.
using combined scanning electrochemical-atomic force microscopy. Electrochemistry Communications, 2005, 7, 612. J. V. Macpherson and P. R. Unwin, Noncontact electrochemical imaging with combined scanning electrochemical atomic force microscopy. Analytical Chemistry, 2001, 73, 550. C. M. Lee and A. J. Bard, Fabrication and characterization of probes for combined scanning electrochemical/optical microscopy experiments. Analytical Chemistry, 2002, 74, 3626. P. Actis, M. Manesse, C. Nunes-Kirchner, G. Wittstock, Y. Coffinier, R. Boukherroub and S. Szunerits, Localized electropolymerization on oxidized boron doped diamond electrodes covalent modified with pyrrolyl units. Physical Chemistry Chemical Physics, 2006, 8, 4924–4931. S. Isisk, M. Etienne, J. Oni, A. Blochl, S. Reiter, and W. Schuhmann, Dual microelectrodes for distance control and detection of nitric oxide from endothelial cells by means of scanning electrochemical microscope. Analytical Chemistry, 2004, 76, 6389. E. Paleek, Past, present and future of nucleic acids electrochemistry. Talanta, 2002, 56, 809.
21
106. J. Wang, Electrochemical nucleic acid biosensors. Analytica Chimica Acta, 2002, 469, 63. 107. J. Abbou, C. Demaille, M. Druet, and J. Moiroux, Fabrication of submicrometer-sized gold electrodes of controlled geometry for scanning electrochemical-atomic force microscopy. Analytical Chemistry, 2002, 74, 6355. 108. L. P. Bauermann, W. Schuhmann, and A. Schulte, An advanced biological scanning electrochemical microscope (Bio-SECM) for studying individual living cells. Physical chemistry chemical physics. Physical Chemistry Chemical Physics, 2004, 6, 4003. 109. M. Etienne, A. Schulte, and W. Schuhmann, High resolution constant-distance mode alternating current scanning electrochemical microscopy (AC-SECM). Electrochemistry Communications, 2004, 6, 288. 110. Y. Hirano, D. Oyamatsu, T. Yasukawa, H. Shiku, and T. Matsue, Scanning electrochemical microscopy for protein chip imaging and shear force feedback regulation of substrate-probe distance. Electrochemistry, 2004, 72, 137. 111. K. Karrai and R. D. Grober, Piezo-electric tuning fork tip-sample distance control for near field optical microscopes. Ultramicroscopy, 1995, 61, 197.
20 Modeling of Biosensor Interfaces Michael E. G. Lyons School of Chemistry, University of Dublin, Dublin, Ireland
1 INTRODUCTION
In this chapter we discuss the modeling of biosensor interfaces. Specifically we outline how simple mathematical models may be used to provide insight into the essential physical processes occurring at the biosensor/analyte interface. We recall that a biosensor is a device that recognizes an analyte/reactant (or in biochemical parlance a substrate) in an appropriate sample and interprets its concentration as an electrical signal through a combination of a biological recognition element, which is in intimate contact with a suitable transducer.1–5 In the present chapter we focus attention on biosensors, which utilize surface-immobilized biorecognition elements coupled with amperometric electrochemical transduction.6–13 These systems are termed chemically modified electrodes.14–18 In amperometric detection the target analyte is oxidized or reduced at an electrode surface that has been poised at a suitable detection potential, and the resulting flow of electrons across the electrode/solution interface is measured as a current, which under suitable circumstances (when the reaction is under mass transport control) is directly proportional to the analyte concentration. In principle any species, which can lose or gain electrons can be detected. Therein lies the power of, and possibilities inherent in, amperometric electrochemical detection. A key concept associated with chemically modified electrodes is that of redox mediation (Figure 1). In this process surface-immobilized
sites may be activated electrochemically through the application of a voltage to the support electrode. The latter sites may then oxidize or reduce other redox agents located in the solution phase adjacent to the immobilized layer, for which the direct oxidation or reduction at the electrode surface is inhibited, either because of intrinsically slow heterogeneous electron transfer kinetics or because close approach of the soluble redox species to the electrode is prevented. The idea is presented schematically in Figure 1 where the processes of direct unmediated electron transfer and mediated electron transfer at an electrode are compared. The attractive feature of chemically modified electrodes is the fact that the deposited chemical microstructure or biorecognition element can be the subject of bottom-up rational design and be tailormade to perform a specific task. To achieve this aim, however, we must understand the fundamental principles underlying how the deposited microstructure mediates the oxidation or reduction of the analyte of interest. This is accomplished by formulating very simple mathematical models, which encompass the key happenings in the biosensor operation process namely, the transport of reactant (analyte) to the surface-immobilized biorecognition element and the chemical reaction dynamics between the reactant and the latter. It is usually assumed that substrate transport mechanism can be ascribed to diffusion (transport in a concentration gradient). The rate law governing the interaction between substrate and biocatalyst
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE
S
e−
P
Direct electron transfer
e− A
B
S
P
Mediated electron transfer
Figure 1. Schematic representation of direct and mediated electron transfer at an electrode/solution interface.
can then be specified. Therefore, the modeling procedure involves problem formulation in terms of specifying a particular differential equation that involves diffusion and chemical reaction components. This reaction-diffusion equation may in general be time dependent and may well be nonlinear. It is solved subject to specific initial and boundary conditions to obtain an expression for the current flow and hence the amperometric response. The solution may be analytical or more often, numerical.19 In this chapter we focus attention on the development of simple analytical models, which can be used to describe electrochemical biosensors that utilize enzymes as the biocatalytic recognition element and amperometry as the mode of transduction. The topic of amperometric enzyme biosensors is very broad and space constraints dictate that discussion be confined to a subset of topics of current interest. Consequently, we examine two situations in detail. The first involves modeling the kinetics of direct redox enzyme reaction at the electrode/solution interface. The second is concerned with deriving the amperometric response of biosensors on the basis of redox enzymes adsorbed or otherwise immobilized on well-defined, selfassembled monolayer nanostructures.
2 DIRECT REACTION OF REDOX ENZYMES AT ELECTRODES
The redox centers of many enzymes are electrically insulated by thick protein or glycoprotein shells that serve to prevent direct electrical communication between the redox center of the enzyme and the detector electrode during amperometric
detection. For enzymes such as glucose oxidase with buried redox centers, diffusing redox mediators such as ferrocene/ferricinioum derivatives and the O2 /H2 O2 redox pair have been used to shuttle electrons between the enzyme redox site and the detector electrode. This methodology has received considerable attention. However, the direct nondiffusive mediation between a buried redox site and an electrode is also attractive and is conceptually simpler to mathematically model. Consequently we examine the situation where the redox enzyme is chemically modified by covalent attachment of an electron relay species R to the outer protein sheath (Figure 2) through long and flexible spacer chains. The relay groups are distributed randomly over the outer surface of the protein sheath. In this way the enzyme is made directly electroactive and can communicate electrically with the detector electrode. Substituted ferrocenes have been attached through flexible spacers of various lengths to glucose oxidase,20 and the attached mediator species are believed to act as electronic “stepping stones”, allowing electrons to be transferred from the flavin site to the electrode in several short steps, instead of one large step. It has been shown20 that the length of the spacer chain is of considerable importance in determining the efficiency of electronic communication between relay site and redox site and between the relay site and the detector electrode surface. Communication is effective when the chains are long (>10 bonds) but not when the chains are short (<5 bonds). A peripherally attached redox mediator may accept electrons through either a unimolecular intramolecular or a bimolecular intermolecular process (Figure 2). The unimolecular intramolecular mechanism has been shown to predominate when the relay site is attached to the redox enzyme through long flexible spacer chains. The chemical modification of redox proteins with synthetic electron transfer mediators is always accompanied by the partial degradation of the native biocatalyst. Furthermore, the effectiveness of the electrical contact is enhanced on increasing the mediator loading on the protein surface since electron transfer distances are thereby shortened. For glucose oxidase for example, the optimum electron transfer (ET) mediator loading is 12–13 ferrocene units per enzyme molecule.21 However, the rate constant for ET between the flavin adenine dinucleotide (FAD) site and the nearest electron relay group is approximately 0.9 s−1 , which is
MODELING OF BIOSENSOR INTERFACES
Intramolecular ET
3
Intermolecular ET
Figure 2. Schematic representation of “electro-enzymes” indicating how tethered redox mediators can exchange electrons with the enzyme catalytic site buried within the protein sheath. This electron transfer may occur via unimolecular intramolecular or via bimolecular intermolecular mechanisms as indicated.
much lower than that recorded for ET to the native dioxygen acceptor (typically 5 × 103 s−1 ). We consider the following kinetic model:
1 1 1 1 1 = = + + kU kC /KM k1 K 1 k2 K 1 K 2 k3
kE
Eox + S −−−→ Ered + P
1 1 1 1 = + + kC k2 K 2 k3 k3
kET
Ered −−−→ Eox where the enzyme/substrate reaction occurs in solution and is described in terms of the well known Michaelis–Menten kinetic mechanism involving formation of intermediate adduct species: k1
k2
k3
k−1
k−2
k−3
−−− −− → −−− −− → −−− −− → Eox + S ← −[Eox S] ← −[Ered P ] ← − Ered + P and the pseudo first-order rate constant kE describing the reaction between the substrate and the catalytically active oxidized form of the enzyme is given by:19 kE =
kC s ∞ KM + s ∞
state rate constants for the elementary reaction steps as follows:22–24
(1)
where s ∞ denotes the bulk substrate concentration and the Michaelis constant KM and catalytic rate constant kC are defined in terms of the internal
(2)
where we note that Kj = kj /k−j . Therefore, the kinetics are described in terms of a specific binding interaction between the oxidized form of the redox enzyme Eox and the substrate S to form one or more distinct adduct complexes Eox S and Ered P which subsequently decompose to generate the reduced form of the enzyme Ered and the product P. The significance of these equations have been discussed by Albery and Knowles.25 Note that kC , which has the dimenthe quantity kU = K M sions of a bimolecular rate constant, provides a measure of the rate of capture of the substrate species by the oxidized enzyme Eox to form the adduct Eox S. The terms Michaelis constant and catalytic rate constant are well established in the field of enzyme kinetics.26 The Michaelis constant KM provides a measure of the binding affinity or adduct formation ability of the
4
THE BIOLOGY – MATERIALS INTERFACE
substrate species for the catalytic enzyme. Alternatively, it defines the maximum value of the substrate concentration for which the catalytic kinetics are first order with respect to substrate concentration. The catalytic rate constant kC is a first-order rate constant, quantifying the rate of decomposition of the surface adduct species to form product. We note from equation (2) that both kU and kC are composite quantities and may be considered internal parameters. Both quantities, when expressed in reciprocal format, consist of three separated terms. Considering the kC component terms first, we note that k1 corre2 sponds to slow rate-determining intramolecular electron transfer involving the transformation of the precursor adduct Eox S to the successor adduct Ered P. The K1k term corresponds to the case 2 3 where the precursor/successor adduct transformation is at a preequilibrium followed by a slow rate-determining decomposition of the successor adduct to form products. Finally the k1 term corre3 sponds to slow rate-determining successor adduct
Substrate/mediator binding
decomposition. The smallest of these terms will be the major contributor to the net catalytic rate constant kC . Similarly, if we examine the kU component terms we note that the k1 term reflects 1 rate-determining adduct formation involving the bimolecular reaction between S and Eox . The sec1 involve ond and third terms K1k or K K 1 2 1 2 k3 either single (K1 ) or multiple (K1 K2 ) preequilibria followed by slow intramolecular electron transfer between the adducts Eox S and Ered P within the interface region (k2 ) or slow successor adduct dissociation (k3 ). A schematic free energy profile illustrating the free energy differences associated with each of the possible rate-limiting steps associated with the internal parameters is presented in Figure 3. The distinguishing characteristic of the direct enzyme reaction model is that the reduced form of the enzyme is transformed at the detector electrode back to the catalytically active form. The kinetics of the latter transformation is described by the electrochemical rate constant kET . The latter again
Intramolecular electron transfer TS3
Successor adduct decomposition
TS2 TS1
K 1 K2 K3 K 1 K2 k1 K−1
K2
K2 K3
k3 k−2
k−3
K1
B + S0
K2
[BS]0 [AP]0 1 1 1 1 = + + kC k2 K 2 k3 k 3 1 KM 1 1 1 + + = = kU kC k 1 K 1 k 2 K 1 K 2 k 3
K3 A + P0
Figure 3. Free energy profiles for the Michaelis–Menten adduct formation mechanism where a substrate S binds to a catalytically active oxidized form of the enzyme B (or Eox ) to form a precursor adduct species BS. This binding process is followed by intramolecular electron transfer where the successor adduct species AP is formed, which subsequently decomposes to yield the product and noncatalytically active reduced form of the enzyme A (or Ered ).
MODELING OF BIOSENSOR INTERFACES
is a composite quantity and contains contributions arising from the relay/reduced site reaction (kRE ) and the relay/detector electrode interaction (k ) with 1 = k1 + 1 . kET k RE We assume that the enzyme concentration is much less than the substrate concentration and so we can neglect concentration polarization (i.e., diffusion) of substrate in the solution adjacent to the detector electrode. We set the total enzyme concentration as e = a + b, where a and b denote the concentrations of oxidized and reduced enzyme, respectively. We do, however, need to examine the diffusion of the oxidized form of the enzyme in solution, its reaction with the substrate, and also the heterogeneous ET kinetics of the reduced form of the enzyme at the electrode surface to regenerate the oxidized form of the enzyme. We can envisage two experimental configurations.27 The first we denote the membrane free situation where the enzyme diffuses freely in solution next to the electrode (Figure 4a). The second is designated the membrane bound situation where the enzyme and substrate are located in a thin layer of solution behind a membrane (Figure 4b). We consider each scenario in turn. The net reaction flux f (in units of mol cm−2 −1 s ) is given by: f =
i = kET b0 nF A
(3)
Eox
k′ Ered
Ered
S kE P Solution
(a)
Membrane bounded direct enzyme case
(b)
Electrode
DE Eox
Eox
k′ Ered
Ered
S kE P
Membrane
Free direct enzyme case
Electrode
DE Eox
Solution
Figure 4. Schematic representation of electro-enzyme transport and kinetics. (a) Free semi-infinite enzyme diffusion and reaction. (b) Membrane bounded enzyme reaction and diffusion.
5
We introduce the following nondimensional distance and concentration variables: χ=
x δ
u=
a e
(4)
where δ denotes either the diffusion layer thickness (for the membrane free situation) or the thickness of the solution layer behind the membrane (for the membrane bound system). The transport and kinetics of the reduced enzyme under steady-state conditions is described by the following reaction/diffusion equation: D
d2 a − ka = 0 dx 2
(5)
where we set k = kE s and defines a pseudo firstorder rate constant, and s denotes the substrate concentration. We also set D as the diffusion coefficient of the enzyme and assume that the diffusion coefficients of reduced and oxidized forms of the rate constant are equal. Making use of the definitions provided in equation (4) we can transform equation (5) into nondimensional form as follows: d2 u − γu = 0 (6) dχ 2 where γ = kδ 2 /D is a parameter, which compares the transit time for crossing the diffusion layer with the homogeneous rate constant describing the facility of the enzyme/substrate reaction √ δ k kinetics. We note that γ = δ D = µ where √ the reaction layer thickness µ = D/k provides a measure of how far the oxidized enzyme can travel before it reacts with substrate. The differential equation outlined in equation (6) may be integrated by making use of two boundary conditions. The first concerns the situation at the detector electrode/solution interface at x = 0. Here we may write db da −D =D = −kET b0 (7) dx 0 dx 0 or expressed in nondimensional terms as at χ = 0:
du dχ
=− 0
δ kET (1 − u0 ) = −κ(1 − u0 ) D
(8)
6
THE BIOLOGY – MATERIALS INTERFACE
where we have written κ = kET /kD and the diffusive rate constant kD is given by kD = Dδ. The parameter κ compares the rate of reduced enzyme reaction at the electrode surface to that of reduced enzyme diffusion to the electrode surface. Furthermore, we assume that the substrate S is present in excess in the bulk of solution and so all enzyme is present in its reduced form there and so a = 0 at x = δ. This condition will be valid if oxygen is absent from the solution. Therefore, the boundary condition at the electrode surface is as follows:
χ =1
u=0
(9)
Now, solving equation (5) subject to equations (8) and (9) we obtain the following expression for the normalized concentration of oxidized enzyme adjacent to the electrode surface: √ √ u(χ) = κγ −1/2 (1 − u0 ) tanh γ cosh [ γ χ] √ − sinh [ γ χ] (10) where u0 =
κγ −1/2 κγ −1/2 + coth
√ γ
(12)
and so √ γ
1 √ = √ −1/2 κγ + coth γ 1 + κγ tanh γ (13) This defines the expression for the normalized flux under conditions where semi-infinite diffusion conditions pertain. We can√ consider two limiting cases. The first √ √ is when γ 1. Then, tanh γ ∼ = γ and the normalized flux reduces to: =
coth
−1/2
∼ =
1 1+κ
Therefore, under these circumstances the net flux is first order in enzyme concentration and zero order with respect to substrate concentration. The flux may also depend on applied electrode potential through the kET term. In contrast, when the parameter κ 1, 1 + κ∼ = κ and the flux reduces to ∼ = κ −1 . We label this case II and the net flux is given by:
(11)
From the latter expression we can derive the normalized flux f = 1 − u0 = kET e
Therefore, we note that the parameters γ and κ can be used as defining axes in the construction of a kinetic case diagram. We consider the following limiting situations. First when γ 1, we get two cases depending on the value of the parameter κ = kET /kD = fET /fD , which compares the flux of reduced enzyme oxidation at the electrode/solution interface to the diffusive flux of reduced enzyme to the electrode surface. When γ 1 ∼ = 1/(1 + κ) and when κ 1, 1 + κ ∼ = 1 and ∼ = 1, the situation corresponds to slow rate-determining heterogeneous enzyme oxidation kinetics at the electrode surface. We label this case I, and the net flux is given by: f ∼ e (16) = kET
(14)
√ √ In contrast when γ 1, tanh γ ∼ = 1 and we obtain 1 ∼ (15) = 1 + κγ −1/2
De f ∼ = kD e = δ
(17)
Here the diffusion of the electroactive reduced form of the enzyme to the electrode surface is rate determining. Second, when γ 1, the normalized flux is given by equation (15). Again we have two limiting situations depending on the magnitude of the product κγ −1/2 . Firstly, when κγ −1/2 1 then ∼ = 1 and we regain case I corresponding to rate-determining electrode kinetics of enzyme regeneration. In contrast, when κγ −1/2 1, the normalized flux reduces to ∼ = κ −1 γ 1/2 , which we label case III. Here the flux expression becomes the following: f ∼ =
√ kDe
(18)
s and so Now we recall that k = kE s = K kC+ s M equation (18) reduces to: f =
kC Ds e KM + s
(19)
MODELING OF BIOSENSOR INTERFACES
Returning to equation (20), we note that f2 = 2 kC Dse KM + s and inverting we obtain the following:
In this case we predict that the reaction flux is first order with respect to enzyme concentration. However, the reaction order with respect to substrate concentration depends on the balance between the magnitude of s and the value of the Michaelis constant KM . When s KM we define case IIIA, and equation (19) reduces to: f ∼ = kU Dse = (kC /KM )Dse
e f
(20)
kC De
2 =
1 1 1 KM + s = + · kC Ds kC D D(kC /KM ) s
=
1 1 1 + · kC D kU D s
(22)
and predict that a plot of (e /f )2 versus s −1 should be linear with a slope given by 1/kU D and an intercept given by 1/kC D. The expression represents a modified form of a Lineweaver–Burk plot. An analysis based on the latter equation has been reported by Bartlett and coworkers,28 and their results are illustrated in Figure 5. In this work, glucose oxidase was modified by the covalent attachment of ferrocene-based mediators (ferrocene carboxylic acid, ferrocene acetic acid, and ferrocene butanoic acid). As outlined in Figure 5(a) the mediator-modified enzymes
and the reaction flux will be half order with respect to substrate concentration and first order with respect to enzyme concentration. In contrast, at higher substrate concentrations when s KM then the reaction flux reduces to: f ∼ =
7
(21)
and the flux is independent of substrate concentration and first order in enzyme concentration.
a
i (µA)
30
20 3 / (mg ml−1)2 µA−2
b
0
0.2 E vs SCE (V)
103
0
(a)
1
eΣ iL
c
2
2
10
0.4 (b)
0
0.1
0.2
0.3
([glucose] /mmol dm
0.4
0.5
−3)−1
Figure 5. (a) Typical voltammograms recorded for (a) ferrocene acetic acid–, (b) ferrocene butanoic acid–, and (c) ferrocene carboxylic acid–modified glucose oxidase at a glassy carbon electrode, sweep rate 5 mV s−1 . In all three cases the glucose concentration was sufficient to ensure saturated enzyme kinetics (>80 mM). The enzyme concentration is 1 mg cm−3 . (b) Plot of equation (22) for the ferrocene acetic acid modified enzyme. Three different enzyme concentrations were used in the analysis (0.45, 1.13, and 4.5 mg cm−3 ). [Reprinted with permission Bartlett et al.28 copyright 1987, Royal Society of Chemistry.]
8
THE BIOLOGY – MATERIALS INTERFACE
exhibited clean and well-defined quasi-steadystate electrochemical responses at a glassy carbon detector electrode in dilute oxygen-free aqueous phosphate buffer solution. It is also clear from the latter diagram that the redox mediator thermodynamics (expressed as a half wave potential value) depends markedly on mediator type (typically E1/2 (SCE) = 0.30–0.33 V, ferrocene carboxylic acid; 0.13–0.18 V, ferrocene acetic acid; 0.09–0.11 V) and that for a given substrate concentration and enzyme concentration the optimal reactivity was exhibited by ferrocene acetic acid–modified glucose oxidase. Bartlett and coworkers28 estimated values for kC and KM for each of the modified enzymes from an analysis using equation (22). Their results are presented in Table 1. Note that the catalytic rate constant kC is considerably greater for the ferrocene acetic acid–modified enzyme and this explains the trend in current magnitude observed in the voltammograms. The analysis using equation (22) was replicated over a range of enzyme concentrations and the linearity predicted from the equation confirmed for all modified enzyme systems studied. The largest error was observed for low glucose concentrations, but the linearity exhibited by a typical plot (such as that outlined in Figure 5b) is very good and is supportive of the theory. We now move to the situation where a membrane is used to enclose a thin layer of solution next to the detector electrode and reexamine the reaction-diffusion expression outlined in
equation (6) but now substitute a new boundary condition at the enzyme solution/boundary membrane interface at χ = 1. Therefore, equation (9) is replaced by a zero flux condition, which reads du =0 (23) χ = 1, dχ 1 Therefore, through integration of equation (6) subject to equations (8) and (23) we obtain the following expression for the normalized concentration of oxidized enzyme adjacent to the electrode surface: u(χ) =
κγ −1/2 √ √ cosh[ γ χ] −1/2 κγ + tanh γ √ √ (24) − tanh γ sinh[ γ χ]
The concentration of reduced enzyme is given by v(χ) = 1 − u(χ). Specifically at χ = 0, u = u0 and we write u0 =
κγ −1/2 √ κγ −1/2 + tanh γ
(25)
and can immediately write the expression for the normalized reaction flux by noting √ tanh γ = 1 − u0 = √ κγ −1/2 + tanh γ =
1 1 + κγ
−1/2
coth
√
(26)
γ
Table 1. Experimental data (Ref. 28) obtained for electro-enzyme direct reaction
Enzyme modifier Glucose oxidase E1/2 (V) (vs saturated calomel reference electrode (SCE)) Number of ferrocene per enzyme kC (s−1 ) KM (mM−1 ) kU = kC /KM (dm3 mol−1 s−1 ) (a)
Ferrocene carboxylic acid
Ferrocene acetic acid
Ferrocene butanoic acid
0.3–0.33
0.13–0.18
0.09–0.11
2
13
22
29
800 20 40 × 103
5 1 5 × 103
1100 5 220 × 103
50 2 25 × 103
ca −0.4
(a)
Data obtained in author’s laboratory from analysis of cyclic voltammetry data of GOx adsorbed on carbon electrodes modified with a mesh of single walled carbon nanotubes in phosphate buffer pH 7.
MODELING OF BIOSENSOR INTERFACES
Again, we can deconstruct the latter expression by taking suitable limiting approximations. For instance when√the reaction/diffusion parameter γ √ is small, tanh γ ∼ = γ and equation (26) reduces to: √ γ 1 ∼ (27) = √ = −1/2 κγ + γ 1 + κγ −1 Alternatively when γ is large, tanh equation (26) reduces to: ∼ =
√ ∼ γ = 1 and
1 1 + κγ −1/2
(28)
which is the same as equation (15) obtained for the membrane free case. Again, looking at equation (27), when γ 1 we get two limiting cases depending on whether κγ −1 1 or κγ −1 1. First, if κγ −1 1, then κ γ . We recall that the former parameter compares the flux of reduced enzyme oxidation at the electrode to the diffusive flux of reduced enzyme to the site of reoxidation (κ = kET /kD = fET /fD ); whereas the latter parameter compares the flux for the homogeneous enzyme/substrate kinetics to the transit time for enzyme diffusion across the solution layer (γ = k/kD = fES /fD ). Therefore, the product κγ −1 = (fET /fD )(fD /fES ) = fET /fES compares the flux of reduced enzyme oxidation at the detector electrode surface to the flux arising from the bimolecular homogeneous enzyme/substrate reaction within the diffusion layer. Consequently, when κ γ , fET fES and the regeneration of oxidized enzyme is slow and rate determining. Under such circumstances, the normalized flux reduces to ∼ = 1 or f = kET e
(16)
which again is case I, met previously for the membrane free situation. The current flow depends
9
only on the concentration of enzyme, may exhibit a potential dependence, and will be independent of substrate concentration. Conversely when κγ −1 1, κ γ and fET fES . Here, oxidized enzyme regeneration is fast and the Michaelis–Menten enzyme/substrate kinetics is slow and rate determining. Here the normalized flux reduces to ∼ = 1 = κ −1 γ and the net reaction flux is given by κγ −1 f = ke δ =
kC e sδ KM + s
We label this situation case IV. In this case, the flux depends on substrate concentration according to the Michaelis–Menten rate law but also depends on the thickness of the solution layer trapped behind the membrane. When s KM , we have k f ∼ = KC e δs = kU e δs and we have case IVA M corresponding to unsaturated enzyme kinetics. In contrast, when KM s then f ∼ = kC e δ, we have case IVB, and we have saturated enzyme kinetics. More generally, inversion of equation (29) yields the following: 1 1 1 1 · + = f (kC /KM )e δ s kC e δ
(30)
and a plot of f−1 versus s −1 is linear with a slope given by 1/kU e δ and intercept 1/kC e δ. The situation for large γ yields equation (15), previously obtained for the semi-infinite situation. Again we have two limiting cases depending on the magnitude of the product κγ −1/2 . Firstly, when κγ −1/2 1, ∼ = 1 and we regain case I corresponding to rate-determining electrode kinetics of enzyme regeneration. In contrast, when κγ −1/2 1, the normalized flux reduces to ∼ = κ −1 γ 1/2 , which we have labeled case III. We can summarize the kinetic results obtained to date in Table 2. We can also geometrically represent the analysis in terms of a kinetic case diagram. This
Table 2. Summary of pertinent rate-limiting expressions for direct electro-enzyme reaction
Kinetic case
(29)
Normalized substrate flux
Heterogeneous enzyme oxidation kinetics I Reduced enzyme diffusive transport II
Modified Michaelis–Menten III
Bounded modified Michaelis–Menten IV
∼ =1 ∼ = κ1 γ 1/2 ∼ = κ γ ∼ = κ
Substrate flux f = kET e f = kD e f = KkC Ds + s e M
kC e sδ f = K M +s
10
THE BIOLOGY – MATERIALS INTERFACE Membrane free direct enzyme case −1/2
kg
log k
ψ ≅ k−1
III ψ ≅ k−1g1/2
II
ψ ≅ 1 −1/2 1 + kg
log g
k=1 ψ≅
=1
1 1+ k
I ψ≅1
g=1 1/2
(a)
ψ=
coth g kg−1/2 + coth g1/2
Membrane bounded direct enzyme case log k kg−1/2 = 1 ψ ≅ gk−1
−1 1/2 III ψ ≅ k g
ψ≅
1 −1/2 1 + kg
IV log g
k=1 I ψ≅1
ψ ≅ 1 −1 1 + kg
kg−1 = 1
(b)
ψ=
g=1 tanh g1/2 kg−1/2 + tanh g1/2
Figure 6. Kinetic case diagram (plot of log κ vs log γ ) for (a) membrane free direct reaction and diffusion of electroenzyme and (b) membrane bounded direct reaction and diffusion of electro-enzyme. Note that κ compares the rate of enzyme regeneration at the electrode with that of enzyme diffusion through the solution, whereas γ compares the rate of enzyme diffusion to that of homogeneous reaction between enzyme and substrate. In both cases approximate limiting expressions for the normalized flux and the expressions delineating the boundaries between specific cases are presented.
is presented in Figure 6. The natural axes defining the case diagram are log κ and log γ . The membrane free direct enzyme case is outlined in Figure 6(a), whereas the membrane bound situation is presented in Figure 6(b). Three kinetic sub-cases (I, II, and III) are relevant for the semi-infinite membrane free situation. The bounded membrane situation is well described by the sub-cases labeled I, III, and IV. Common to both are cases I and III. Case II is found only in the semi-infinite membrane free case, whereas case IV is specific to the membrane bound situation. In Figure 6(a) the II/III case boundary lies at γ = 1, the I/II boundary is at κ = 1, and the
I/III boundary is set at κγ −1/2 = 1. In Figure 6(b) we note that the I/III boundary is again defined by the line κγ −1/2 = 1, whereas the I/IV boundary is defined by the line κγ −1 = 1, and the III/IV boundary is γ = 1. We can directly compare the amperometric response obtained for the membrane free situation with that obtained for the membrane bound situation by taking the ratio of the normalized fluxes: √ √ MF coth γ (κγ −1/2 + tanh γ ) = √ √ MB tanh γ (κγ −1/2 + coth γ ) √ 1 + κγ −1/2 coth γ (31) = √ 1 + κγ −1/2 tanh γ This ratio is illustrated schematically in Figure 7 for various values of the parameters κ and γ . We note that for all values of κ, MF /MB → 1 as γ → ∞. Furthermore, the ratio MF /MB increases significantly as γ decreases. The rate of increase in the latter ratio with decreasing γ value is more marked for lower values of the parameter κ. In short the steady-state amperometric response expected for a sensor that does not have a bounding membrane coating is significantly larger than that recorded for a sensor containing a membrane when the homogeneous enzyme/substrate reaction kinetics is slower compared to the rate of diffusive movement of enzyme across the diffusion layer and when the rate of oxidized enzyme regeneration at the electrode surface is much smaller than that of enzyme diffusion.
3 AMPEROMETRIC ENZYME ELECTRODES USING SELF-ASSEMBLED MONOLAYER THIN FILMS
The immobilization of redox enzymes onto the surface of self-assembled monolayers has recently been the subject of considerable interest.29–36 Indeed in a recent review by Wilner and Katz3 it is stated that “Integration of redox enzymes with an electrode support and formation of an electrical contact between the biocatalyst and the electrode is the fundamental subject of bioelectronics and optobioelectronics.” In this section we develop a simple kinetic model to describe the operation of an amperometric
MODELING OF BIOSENSOR INTERFACES ΨMF ΨMF ΨMB
∼ =
1 + k g−1
ΨMB
=
11
1 + k g−1/2 coth g1/2 1 + k g−1/2 tanh g1/2
1+k
1000 ΨMF/ΨMB
k = 0.01 k = 0.1 k=1 k = 10 k = 100
100
ΨMF
10
ΨMB
∼ =1
1
0.1 0.01
0.1
1 g
10
100
Figure 7. The ratio of the amperometric response obtained for the membrane free configuration to that corresponding to the membrane bound situation as a function of the normalized parameter γ that compares the rate of enzyme diffusion in the solution region next to the detector electrode, with the rate describing the reaction between enzyme and substrate in the solution. The flux ratio is presented also for various values of the parameter κ that compares the rate of the reduced enzyme reaction at the detector electrode surface to that of reduced enzyme diffusion to the electrode surface.
enzyme electrode where the enzyme is immobilized within a self-assembled monolayer and where the electronic communication between the enzyme and the electrode is effected by a mobile electronic relay mediator species. This analysis will build on previous work reported by Bourdillon and coworkers,37 Tatsuma and Watanabe,38 Bartlett et al.39 and most recently by Gooding et al.36 and Lyons.40 The simplified model adopted in the present paper is schematically presented in Figure 8. The redox enzyme is assumed to be located within a thin nonconductive layer of thickness L deposited onto the surface of a conducting support electrode. This layer may be an alkane thiol film formed through adsorptive self-assembly from solution. We assume that the enzyme is homogeneously distributed in a plane located at x = L, at the interface between the thiol film and the adjacent solution. We consider the following reaction scheme: k1
kC
S + Eox ES → P + Ered k−1
k
Ered + A → Eox + B k
B→ A
Enzyme layer
a0
Diffusion layer
B
S
a∞
P
A
s∞
aL B B A
sL bL
A
L
d
Bulk solution
Figure 8. Schematic representation of immobilized enzyme electrode using a soluble redox mediator. A denotes the oxidized mediator and B is the reduced mediator. Concentration polarization of substrate S and mediator within the enzyme layer is neglected but a Nernst diffusion layer treatment for substrate and mediator transport in the solution is adopted.
where the oxidized form of the enzyme Eox reacts with the substrate S to form (through an enzyme/substrate complex as intermediate)
12
THE BIOLOGY – MATERIALS INTERFACE
product P and reduced enzyme Ered . The oxidized form of the mediator species A partitions from solution into the enzyme layer and reacts with the reduced enzyme to regenerate the active oxidized enzyme and produce the reduced form of the mediator B. A can subsequently be electrochemically regenerated at the support electrode through the reaction of B, which we assume to occur with kinetic facility. Therefore, the surface concentrations of reduced and oxidized mediator species b0 and a0 are related through the Nernst equation. Of course when measuring the steady-state amperometric response of electrodes of this type in practice, it is usual to hold the electrode at a sufficiently oxidizing potential that the mediator is entirely in its oxidized form at the electrode surface. Under such conditions we can set b0 = 0. In the following analysis this assumption is made. We also assume that the substrate S is electrochemically inert and does not react directly at the support electrode surface. It only interacts with the redox enzyme. We assume that the value of the mediator concentration in the bulk solution is a ∞ and is present only in its oxidized form. Therefore, the concentration of the reduced form of the mediator B is 0 outside the diffusion layer, which is assumed to have a thickness δ. The observed current i is related to the net flux f corresponding to the reaction of mediator B at the electrode surface through the Faraday relationship and is given by i db = f = DB (32) nF A dx 0 where n denotes the number of electrons transferred, F is the Faraday constant, and A represents the geometric area of the electrode, and DB denotes the diffusion coefficient of reduced mediator species in the enzyme layer, which differs from the corresponding diffusion coefficient in the bulk solution. This experimentally measurable flux f must be related to the substrate reaction flux fS within the enzyme layer. We correspondingly show, following an argument initially proposed by Bartlett et al.39 that the required relationship between the fluxes is given by: f = η fS
(33)
where we determine that 1/2 ≤ η ≤ 1. The η parameter reflects the fact that the flux of substrate reacting within the film is not necessarily the same as the flux of reduced mediator detected at the electrode. This is because some reduced mediator can diffuse through the thiol layer away from the electrode and be lost into the adjacent solution. We see that the precise value of η depends on how effectively species B moves away from the electrode. Since the immobilization layer is thin we can neglect diffusive depletion of substrate and mediator within the latter, and so we need only consider the Michaelis–Menten kinetics between the oxidized enzyme Eox and the substrate S and the bimolecular kinetics between the oxidized mediator A and the reduced enzyme Ered . Under steadystate conditions both of these processes are in balance, and we can write fS =
kC eox L κS sL = kLered κA aL κS sL + KM
(34)
where κS , κA denote the partition coefficients for substrate and mediator species respectively and aL , sL denote the oxidized mediator and substrate concentrations at the outer edge of the monolayer at x = L. As previously noted L denotes the thickness of the immobilization layer and eox , ered denote the concentrations of the oxidized and reduced forms of the enzyme. Note also that kC and KM represent the catalytic rate constant and Michaelis constant that are significant parameters, which define the enzyme kinetics, and k denotes the bimolecular rate constant quantifying the kinetics of the reaction between oxidized mediator and reduced enzyme. We let e = eox + ered denote the total enzyme concentration contained within the monolayer. From equation (34) we can show that eox =
(κS sL + KM )kκA aL e kC κS sL + (κS sL + KM )kM κA aL
(35)
The substrate reaction flux within the enzyme layer is then given by kC κS sL Leox κS sL + KM kC κS sL LkκA aL e = kC κS sL + (κS sL + KM )kM κA aL
fS =
(36)
MODELING OF BIOSENSOR INTERFACES
We now need to relate the substrate and mediator concentrations at the outer edge of the monolayer at x = L to the corresponding quantities in the bulk solution. This is done using the Nernst diffusion layer approximation where we note that fS = DS = DA
s ∞ − sL δ
= kDS (s ∞ − sL )
a ∞ − aL δ
= kDA (a ∞ − aL )
DS δ
kDA =
DA δ
(37)
(38)
We can readily show that
fS fS = kDS 1 − sL = s − kDS fDS
fS fS ∞ = kDA 1 − aL = a − kDA fDA ∞
(39)
where fDS and fDA represent the mass transport controlled fluxes of substrate and oxidized mediator in the solution with fDS = kDS s ∞ and fDA = kDA a ∞ . Now we note from equation (39) that if fS fS fDS 1 and fDA 1, then we can neglect the concentration polarization of S and A in the solution and we can set sL ∼ = s ∞ and aL ∼ = a ∞ . This approximation is often used in the literature. If the expressions presented in equation (39) are substituted into equation (36), we can, after quite an amount of algebra, obtain the following cubic equation in substrate flux: AfS3 − BfS2 + CfS − D = 0
(40)
where we can show that A=
kκA κS a ∞ s ∞ fDS fDA
B = kκA κS a ∞ s ∞
1 1 kC e L + + fDS fDA fDS fDA
kC κ S s ∞ kKM κA a ∞ + fDA fDS
C = kC κS s ∞ + kκA a ∞ (KM + κS s ∞ )
1 1 ∞ ∞ + kkC e LκS κA a s + fDS fDA D = kkC e LκS κA a ∞ s ∞
where DS and DA denote the diffusion coefficients of substrate and mediator in the solution phase and we have introduced the mass transport rate constants kDS =
+
13
(41)
In a recent paper dealing with monolayer enzyme electrodes fabricated using self-assembled monolayers of alkanethiols, Gooding and coworkers36 have derived a similar cubic expression for the substrate flux (equation 7 of Ref. 36) and proceeded to solve the cubic equation with a negative discriminant to obtain an expression for fS and hence the observed current i. Indeed they fit their experimental batch amperometry curves to the analytical solution of the cubic equation. This analysis procedure of course is valid, but it must be stated that the direct analytical solution of the cubic equation does not confer any real physical insight into the nature of the system. Instead it is preferable to adopt a different strategy as shown subsequently. Substituting equation (39) into equation (36) results in the following expression for the substrate reaction flux kC κS sL LkκA aL e kC κS sL + (κS sL + KM )kM κA aL fS fS ∞ ∞ 1− 1− kC ke LκS κA s a fDS fDA = fS fS ∞ ∞ kC κ S s 1− f + kκA a 1− f DS
DA fS ∞ K M + κS s 1− f
fS =
DS
(42) This rather ungainly expression may be simplified further if we invert both sides to obtain 1 fS −1 1 1− = fS ke LκA a ∞ fDA fS −1 1 1 1 − + + (kC /KM )e LκS s ∞ fDS kC e L (43) The latter expression is now physically transparent in that the first term is related to the bimolecular reaction between reduced enzyme and oxidized mediator, the second term relates to the
14
THE BIOLOGY – MATERIALS INTERFACE
unsaturated kinetics between substrate and oxidized enzyme, and the third term relates to saturated enzyme kinetics involving decomposition of the enzyme/substrate complex to form product and reduced enzyme. The first two terms on the righthand side (rhs) of equation (43) are modified by transport factors involving substrate and mediator diffusion in the solution. For instance if the substrate reaction flux in the layer becomes close to the limit imposed by either substrate transport in the solution or mediator transport in the solution then both the substrate reaction rate and the mediator reaction rate will be diminished by the transport f f terms TS = 1 − f S or TA = 1 − f S . The effecDS DA tive concentration of substrate and mediator at the layer/solution interface will be considerably lesser than their bulk values s ∞ and a ∞ . We note from equation (43) that the substrate reaction flux may be limited by three possible processes: bimolecular kinetics between oxidized mediator and reduced enzyme, unsaturated kinetics between oxidized enzyme and substrate, or saturated enzyme kinetics involving decomposition of ES intermediate. In the analysis so far we have implicitly assumed that the reaction between the oxidized mediator A and the reduced enzyme Ered can be described in terms of a simple bimolecular expression. Karube and coworkers41,42 have stated that this assumption may not necessarily be valid. It is possible that the mediator/enzyme reaction may also be described in terms of Michaelis–Menten kinetics. In such a situation the mediator may bind to the enzyme and form a complex that will subsequently decompose. In this case, equation (4) must be replaced by: fS =
kC eox L κS sL kLered κA aL = κS sL + KM κA aL + KM
analysis just described and show that the inverse substrate reaction flux is now given by: 1 1 = fS (k/KM )e LκA a ∞
1−
1 + (kC /KM )e LκS s ∞ +
fS fDA
−1
fS 1− fDS
1 1 + kC e L ke L
−1
(45)
The first term on the rhs of equation (45) corresponds to rate-determining unsaturated mediator/ enzyme kinetics modified by a mediator transport term. The unsaturated rate constant is given by kU = k . The second term corresponds to rateKM determining unsaturated enzyme/substrate kinetkC . The third ics, with a rate constant kU = K M term corresponds to saturated enzyme kinetics involving rate-determining decomposition of the enzyme/substrate complex, and the fourth and final term corresponds to the saturated kinetics involving decomposition of the mediator/enzyme complex. It is clear that the development of a general expression for the inverse substrate flux provides much more information pertaining to the reaction mechanism than solving the cubic equation. We now follow the procedure adopted in the previous section and develop a kinetic case diagram for an immobilized enzyme monolayer electrode system. In this analysis we neglect concentration polarization of mediator and substrate in solution. We assume that both the mediator/enzyme reaction and the substrate/enzyme reaction are described by Michaelis–Menten kinetics. Under such circumstances the reaction flux is given by:
(44)
where KM denotes the Michaelis constant for the mediator species. We note that when the mediator concentration in the layer is smaller than the Michaelis constant κA aL KM , the expression outlined in equation (44) reduces to that previously presented in equation (4), but in this case the bimolecular rate constant takes the form k/KM . For the more complicated situation where the mediator/enzyme reaction exhibits Michaelis–Menten kinetics, we can repeat the
kC ke LκS κA s ∞ a ∞ (κS s ∞ +KM )kκA a ∞ +(κA a ∞ + KM )kC κS s ∞ (46) We now introduce a normalized substrate flux given by: fS =
S =
fS fS,max
=
fS kC e L
(47)
where fS,max denotes the maximum enzyme turnover rate. We also introduce saturation parameters
MODELING OF BIOSENSOR INTERFACES
α and β for substrate and mediator as follows: α=
κS s ∞ KM
β=
κA a ∞ KM
(48)
We finally introduce a kinetic competition parameter γ as: )κA a ∞ fME kU κA a ∞ e L (k/KM = = ∞ ∞ (kC /KM )κS s kU κ S s e L fSE (49) Therefore, γ compares the mediator/enzyme reaction flux to the substrate/enzyme reaction flux. When γ 1 then fME fSE and the net flux is limited by the kinetics of the bimolecular reaction between mediator and enzyme. In contrast when γ 1 then fME fSE and the net flux is limited by the kinetics of the reaction between substrate and enzyme. The substrate saturation parameter α compares the value of the substrate concentration in the layer κS s ∞ to the Michaelis constant KM for substrate. When α 1, κS s ∞ KM and we have unsaturated enzyme kinetics. In contrast, when α 1, κS s ∞ KM and saturated enzyme kinetics pertain. The mediator saturation parameter β compares the oxidized mediator concentration within the layer, κA a ∞ , to the Michaelis constant for the mediator KM . When β 1, κA a ∞ KM , and unsaturated mediator kinetics pertain. This is the situation usually considered in the literature. On the other hand when the mediator concentration within the layer is large, κA a ∞ KM , saturated mediator kinetics will apply and β 1. If equations (47–49) are substituted into equation (46), one obtains the following expression for the normalized substrate flux in the layer:
γ =
S =
αγ γ (1 + α) + 1 + β
(50)
This normalized expression is the most general and is valid for all mediator and substrate concentrations. We can now simplify the analysis and assume firstly that the concentration of mediator within the film is low. Under these conditions β 1 and equation (50) reduces to: S ∼ =
αγ 1 + γ (1 + α)
(51)
15
We now can simplify the latter expression further depending on the value of the substrate saturation parameter α. When the substrate concentration in the layer is small, α 1 and equation (51) reduces to: αγ S ∼ (52) = 1+γ This expression is valid for the situation where the mediator and enzyme kinetics are unsaturated. We can simplify still further by examining suitable limiting values of the competition parameter γ . Firstly when γ 1 we recall that the substrate reaction flux is limited by reaction between oxidized mediator and reduced enzyme. Here the normalized flux is given by: S ∼ =αγ
(53)
We label this case IA. Transforming into an expression for the flux we get: k fS ∼ = e LκA a ∞ = kU e LκA a ∞ KM
(54)
Therefore, when the reaction between oxidized mediator and reduced enzyme is rate determining, the flux in the film should exhibit a first-order dependence on the bulk concentration of oxidized mediator, provided the concentration of mediator is not too large. The flux should also be independent of the bulk substrate concentration and exhibit a first-order dependence both on enzyme loading and layer thickness. Secondly, when γ 1 the substrate reaction flux in the layer is limited by the unsaturated reaction kinetics between oxidized enzyme and substrate. In this case the normalized flux takes the form: S ∼ =α
(55)
We label this situation case IB. Retransforming into the usual variables we get kC fS ∼ e LκS s ∞ = kU e LκS s ∞ = KM
(56)
Therefore, we note that the reaction flux should be first order with respect to bulk substrate concentration, independent of mediator concentration, and first order with respect to enzyme loading and
16
THE BIOLOGY – MATERIALS INTERFACE
layer thickness. Therefore, case IA and IB pertain when α 1 and when β 1. We now turn to the situation where α 1 and β 1. Reexamination of equation (51) indicates that the approximate expression for the normalized flux is now given by: S ∼ =
αγ 1+α γ
(57)
Again we get two limiting cases depending on the value of the product αγ . Firstly when αγ 1 equation (57) reduces to S ∼ =αγ
(53)
which was obtained previously, and case IA is obtained again. Secondly, when αγ 1 equation (57) reduces to: S ∼ =1
(58)
We label this case II. Here the reaction flux is given by: fS ∼ (59) = kC e L and corresponds to rate-determining saturated enzyme kinetics. Here the flux is independent both of bulk substrate and mediator concentrations but depends linearly on enzyme loading and layer thickness. We have identified three cases (IA, IB, and II) when the mediator concentration in the layer is low. We now turn to the situation when the opposite pertains. In this case equation (50) reduces to αγ S = γ (1 + α) + β
(60)
Again we can simplify by taking the small α and large α limits. Firstly, when α 1 we get S =
αγ γ +β
(61)
We now compare the magnitudes of the normalized parameters γ and β. When γ β, equation (61) reduces to S =
αγ β
(62)
We label this situation case III. Transforming to the usual expression for the flux we obtain fS ∼ = ke L
(63)
Therefore, case III corresponds to the case of saturated mediator kinetics where the decomposition of the mediator/enzyme complex to form reduced mediator and oxidized enzyme is rate determining. Here the flux is independent of bulk mediator concentration and bulk substrate concentration, but depends in a first-order manner on enzyme concentration and layer thickness. On the other hand, when γ β, we get S ∼ =α
(55)
which again is case IB. Therefore, case IB pertains also when β 1 and so holds for the entire range of the β parameter. Turning again to equation (60), which holds for the case where the mediator concentration in the layer is high, and considering the case α 1, we obtain S =
αγ α γ +β
(64)
Again we can get two possible limits by comparing the magnitudes of αγ and β. Firstly when αγ β we again get case III. S =
αγ β
(62)
Whereas in contrast when αγ β we get S ∼ =1
(58)
which is case II. Therefore, case III is valid when the mediator saturation factor β is large and is valid for the entire range of bulk substrate concentrations or α values. Its region of validity is determined by the conditions γ β and αγ β. Case II corresponding to saturated enzyme kinetics is valid for the entire range of β values, and for large values of α, and subject to the restraints that αγ > β and αγ > 1. Therefore, we have identified three cases (IB, II, III) for the situation where the mediator concentration in the layer is high and all reduced enzyme is bound by mediator. These various mechanistic and kinetic possibilities are presented in terms of a kinetic case
MODELING OF BIOSENSOR INTERFACES
17
log b
log b
III
IB
III
b=g
IB
b >> 1
log g
II
II
b = ag
log g
log a
ag = 1
log a
II
IB IALog
log g II
b << 1
IA IB
Figure 9. Kinetic case diagram for an immobilized enzyme monolayer system.
diagram in Figure 9. The natural axes defining the case diagram are log α, log β, and log γ . Although we indicate the general form of the three dimensional case diagram in Figure 9 it is more instructive to examine two limiting slices of the diagram. The first is a plot of log α versus log γ valid for β 1. This is illustrated in the lower right inset in Figure 9. We see that case IA is located in a block defined by the line αγ = 1 and γ = 1. Case IB is defined by the quadrant bordered by the lines γ = 1 and α = 1. Finally case II is defined in terms of the region bordered by the lines αγ = 1 and α = 1. Cases IA, IB, and II are most often found experimentally since the
mediator concentration in the enzyme layer will usually be low. The second slice of the case diagram is presented in the upper right-hand inset in Figure 9. Here case IB is bounded by the lines β = γ and β = 1. Case II is defined by the lines β = 1 and β = αγ . Finally case III is delineated by the lines β = αγ and β = γ . We summarize the various kinetic possibilities in Table 3, where expressions for the normalized flux and the substrate flux are outlined for the four cases considered. In Table 4 we outline the reaction orders with respect to bulk mediator concentration, bulk substrate concentration, and enzyme surface coverage = e L
Table 3. Summary of pertinent rate-limiting expressions for reaction flux in enzyme monolayer
Kinetic case
Normalized substrate flux
Substrate flux
IA: unsaturated mediator kinetics
S ∼ =αγ
IB: unsaturated enzyme kinetics II: saturated enzyme kinetics III: saturated mediator kinetics
S ∼ =α S ∼ =1 αγ S = β
fS ∼ = k e LκA a ∞ = kU e LκA a ∞ KM k fS ∼ = KC e LκS s ∞ = kU e LκS s ∞ M fS ∼ = k C e L fS ∼ = ke L
18
THE BIOLOGY – MATERIALS INTERFACE
Table 4. Mechanistic indicators for immobilized enzyme monolayer electrodes
Reaction order IA: unsaturated mediator kinetics IB: unsaturated enzyme kinetics II: saturated enzyme kinetics III: saturated mediator kinetics
a∞
s∞
1 0 0 0
0 1 0 0
1 1 1 1
for each of the rate-limiting cases developed in Table 3. We note that is not possible to distinguish between case II and case III by examining the way that the reaction flux varies with enzyme loading, bulk mediator concentration, or bulk substrate concentration since an identical set of mechanistic indicators are predicted for both cases. The implications of the master equation outlined in equation (50) are presented in diagrammatic form in Figures 10–12. In Figure 10 the variation of the normalized substrate flux with the kinetic competition parameter γ is presented in a semilogarithmic format. The plots are computed for different values of the substrate saturation parmeter α. Each set of curves corresponds to a fixed value of the mediator saturation parameter β. The substrate flux is normalized with respect to the maximum enzyme turnover rate. For a given value of β we note that the normalized substrate flux increases with increasing γ value and approaches a limiting value as γ increases. The magnitude of the limiting normalized flux increases with increasing α value. We recall that γ compares the mediator/enzyme reaction flux to the substrate/enzyme reaction flux. When γ 1, fME fSE and the net flux is limited by the kinetics of the bimolecular reaction between mediator and enzyme. In contrast when γ 1, fME fSE and the net flux is limited by the kinetics of the reaction between substrate and enzyme. A maximum normalized flux of unity is attained when the kinetics are limited by the reaction between substrate and enzyme and when the concentration of substrate within the enzyme layer is much larger than the Michaelis constant (large α values). The latter maximum flux is only attained at larger γ values when the concentration of mediator is high (large β values). In Figure 11 the variation of the normalized substrate flux with the mediator saturation parameter β computed from equation (50) is presented. The plots are computed for different values of
the kinetic competiton parmeter γ , which compares the mediator/enzyme reaction flux to the substrate/enzyme reaction flux. Each set of curves corresponds to a fixed value of the substrate saturation parameter α. Here the normalized flux initially set at a constant value the magnitude of which depends on the set value of the substrate saturation parameter α, subsequently decreases with increasing β value. This general trend is observed for all α values examined in the range 0.01–100. In Figure 12 the variation of the normalized substrate flux with substrate saturation parameter α is presented. This is the situation most often illustrated in practice and corresponds to a normalized calibration plot or batch amperometry curve. The plots are computed for a range of γ values and for a series of fixed β values. The normalized substrate flux increases with increasing substrate saturation parameter until a maximum value of unity is attained at large values of the latter. This is characteristic of Michaelis–Menten kinetics. This general behavior is observed independent of the value of the mediator concentration (defined in terms of the parameter β). The dynamic range of the biosensor is also seen to increase when the value of the competition parameter is small, although the sensitivity in the latter regime is not very large. The best dynamic range and sensitivity is obtained when the reaction between mediator and enzyme is rate limiting. We now derive a relationship between the current flowing across the support electrode/enzyme layer interface and the reaction flux within the layer. We have previously noted that the latter quantities are not identical, since some reduced mediator can diffuse through the enzyme layer away from the electrode and be lost into the adjacent solution. To take this fact into account we writef = η fS . We now determine an expression for the parameter η following an argument initially proposed by Bartlett et al.39 We assume that a rotating disc arrangement is used. Within the enzyme layer we note that the reduced mediator species B is generated at a uniform rate given by fS /L. Furthermore, B is lost from the layer through diffusion away from the support electrode toward the outer edge of the enzyme layer. This process is described by the Fick diffusion equation. In the steady state, the rate of mediator diffusion and generation must balance
MODELING OF BIOSENSOR INTERFACES 1.2
1.2 1
b = 0.01
1
ΨS
ΨS
0.6
0.6
0.4
0.4
0.2
0.2
0
0
0.01
0.1
1 g
10
0.01
100
0.1
1 g
10
100
1 g
10
100
1.2
1.2 b = 10
1
b = 100
0.8 ΨS
0.8 ΨS
b=1
0.8
0.8
1
19
0.6
0.6
0.4
0.4
0.2
0.2
0
0
0.01
1 g
0.1
10
0.01
100
a a a a a a
0.1
= 0.01 = 0.1 =1 = 10 = 50 = 100
Figure 10. Variation of the normalized substrate flux with the kinetic competition parameter γ computed from equation (50). The plots are computed for different values of the substrate saturation parmeter α. Each set of curves corresponds to a fixed value of the mediator saturation parameter β.
and we can write DB
d2 b dx 2
+
fS =0 L
(65)
where DB denotes the diffusion coefficient of B in the enzyme layer and b represents the
distance-dependent concentration of mediator species within the layer of thickness L. We can consider two boundary conditions: x = 0 b = b0 = 0, x = L b = bL
f db = dx DB (66)
20
THE BIOLOGY – MATERIALS INTERFACE 0.6
0.010
0.5
0.008
0.4
0.006
0.3 ΨS
ΨS
0.012
0.004
0.2
0.002
0.1
0
0
a = 0.01
0.01
0.1
1 b
10
100
a=1
0.01
1
1.2
0.8
1
0.1
1 b
10
100
1 b
10
100
0.8 0.6 ΨS
ΨS
0.6 0.4
0.4 0.2
0.2
0
0 a = 10
0.01
a = 100 0.1
1 b
10
100
0.01
0.1
g = 0.01 g = 0.1 g=1 g = 10 g = 50 g = 100
Figure 11. Variation of the normalized substrate flux with the mediator saturation parameter β computed from equation (50). The plots are computed for different values of the kinetic competiton parmeter γ that compares the mediator/enzyme reaction flux to the substrate/enzyme reaction flux. Each set of curves corresponds to a fixed value of the substrate saturation parameter α.
The boundary condition at x = 0 corresponds to the situation at the support electrode/enzyme layer interface. The first statement is that the potential of the electrode is set to a value such that the reduced mediator is immediately oxidized at the support electrode and so its surface concentration is 0. The second statement refers to the fact that the observed flux arises from the oxidation of the reduced mediator at the support electrode
surface. The second boundary condition refers to the interface between the enzyme layer and the adjacent solution phase at x = L. Here the reduced mediator concentration has a value bL . We integrate equation (65) between 0 and L to obtain:
db db = −fS DB − (67) dx L dx 0
MODELING OF BIOSENSOR INTERFACES
21
1.2
1.2 b = 0.01
b=1 1
0.8
0.8
0.6
0.6
ΨS
ΨS
1
0.4
0.4
0.2
0.2
0
0
0.01
0.1
1 a
10
100
0.01
1.2
0.1
1 a
10
100
1 a
10
100
1.2 b = 10
b = 100 1
0.8
0.8
0.6
0.6
ΨS
ΨS
1
0.4
0.4
0.2
0.2
0
0
0.01
0.1
1 a
10
100
0.01
0.1
g = 0.01 g = 0.1 g=1 g = 10 g = 50 g = 100
Figure 12. Variation of the normalized substrate flux with the substrate saturation parameter α computed from equation (50). The plots are computed for different values of the kinetic competiton parmeter γ that compares the mediator/enzyme reaction flux to the substrate/enzyme reaction flux. Each set of curves correspond to a fixed value of the mediator saturation parameter β.
db Noting that f = DB dx equation (67) re0 duces to: db DB = −fS + f (68) dx L The flux of B across the enzyme layer/solution interface is now equated with the flux of B across
the diffusion layer in solution and so DB
db dx
= −fS + f = − L
DB ∗ b δ L
(69)
where DB denotes the mediator diffusion coefficient in solution and bL∗ represents the mediator concentration in the solution phase just outside
THE BIOLOGY – MATERIALS INTERFACE
the enzyme layer, and δ denotes the Nernst diffusion layer thickness. The latter concentration term is related to the mediator concentration at x = L by bL = κB bL∗ , where κB denotes the partition coefficient of B. An indefinite integration of equation (65) from 0 to x results in db f fS = x − dx DB DB L
(70)
A second integration of equation (70) results in b(x) = b0 +
f fS 2 x− x DB 2DB L
(71)
Noting that b0 = 0 and when x = L, b = bL we obtain that
L fS bL = f − (72) DB 2 From equation (69) we can readily show that DB bL = fS − f κB δ
(73)
Substituting equation (72) into equation (73) we get
DB L fS f − = fS − f (74) δ κB DB 2 We now introduce a flux ratio given by
=
D L fDB = B fDB δ κB DB
and so we note that the η function is given specifically by
2 η= 1+ 1+
(78)
A plot of η versus is outlined in Figure 13. When 1, η ∼ = 1 and the observed flux corresponding to the oxidation of the reduced mediator species at the electrode surface equals that of the substrate reaction within the enzyme layer. This situation arises when the diffusive flux fDB of mediator species through the diffusion layer is much less than the diffusive flux fDB of mediator species through the enzyme layer to the support electrode surface. In these circumstances very little reduced mediator is lost from the film. In contrast, we note from Figure 10 that when 1 then η → 1/2. Here the reduced mediator species B is lost rapidly from the enzyme layer and diffuses into solution. In Figure 7 we see that η has a maximum value of 1 and a minimum value of 1/2, and η decreases regularly as increases, reflecting the increasing rate of loss of mediator from the layer. Therefore, we can view the η parameter as an efficiency factor that depends on the ratio of diffusive fluxes of mediator through the enzyme layer and through the solution phase. We can now write down an expression for the observed steady-state current response expected for an immobilized enzyme monolayer electrode. If we neglect concentration polarization effects in
(75)
This quantity relates the diffusive flux of mediator in the diffusion layer to the corresponding diffusive flux of mediator within the enzyme layer. Therefore, equation (74) transforms to
fS
f − = fS − f (76) 2 This expression can be readily rearranged to generate a relationship between the flux measured at the support electrode surface and that corresponding to reaction within the enzyme layer as follows:
1+ 2 f =ηf f = (77) S S 1+
1.1 1 h = (1 + Φ/2)/(1 + Φ)
22
0.9 0.8 0.7 0.6 0.5 0.4 0.01
0.1
1 Φ
10
100
Figure 13. Variation of the flux efficiency factor η with the mediator diffusive flux ratio as defined in equation (76).
MODELING OF BIOSENSOR INTERFACES
the solution, then from equation (46) we note that
DB L 1+ 2κB DB δ i= DB L 1+ κB DB δ nF A k ke Lκ κ s ∞ a ∞ C S A × (κS s ∞ + KM )kκA a ∞ +(κA a ∞ + KM )kC κS s ∞
(79)
Since this expression contains the diffusion layer thickness δ, if a rotating disc electrode is used, we would expect that the amperometric response should exhibit a marked rotation speed dependence, because the diffusion layer thickness depends on rotation speed through the Levich relation:43 δ = 0.643D B υ 1/6 ω−1/2 1/3
(80)
where ν denotes the kinematic viscosity of the solution and ω denotes the angular velocity of the rotating disc electrode. We expect that the amperometric response should decrease with increasing rotation speed and attain a limiting value at high rotation speeds. This behavior has been observed experimentally by Bartlett and Whitaker for glucose oxidase immobilized in thin poly-pyrrole films using the O2 /H2 O2 mediator system.44,45 We now refer to the recent paper of Gooding and coworkers36 that presents a detailed experimental analysis of an amperometric enzyme electrode consisting of glucose oxidase immobilized within a carboxylic acid–terminated alkane thiol self-assembled monolayer film. This system used p-benzoquinone as a soluble mediator. Gooding et al.36 noted that it is advisable to use a short-chain alkane thiol since monolayers formed from the latter constituents exhibit less order than monolayer films generated from longer alkane thiol chains. It appears that disordered regions in the monolayer are necessary to enable facile transport of the mobile mediator species through the film to the underlying electrode surface. Films based on 3-mercaptopropionic acid have been shown to exhibit both disordered and ordered domains.46 Very low enzyme loadings were required in the enzyme electrodes prepared by Gooding and coworkers,36 typically 0.7 ± 0.3 pmol cm−2 , to produce an excellent dynamic range
23
to added glucose. Changes in concentration up to 50 mM glucose can be detected. Analysis of the batch amperometry data provided in the work of Gooding et al.36 indicated that the Michaelis constant for the substrate was close to 72 mM, which is considerably higher than that reported for glucose oxidase in solution which is 5 mM. This rather large dynamic range for glucose detection can be attributed either to the presence of partition barriers limiting access of substrate to the enzyme or to an enhanced rate of enzyme turnover due to increased mediation efficiency. Goodring and coworkers have estimated that the enzyme layer thickness L is typically 4 × 10−7 cm whereas the diffusion layer thickness is much larger, typically −4 ∼ 10−3 cm. Hence L δ = 4 × 10 . Therefore, they propose that the concentration gradient of reduced mediator species within the enzyme layer is much higher than that for reduced mediator diffusion into the adjacent solution. This implies that almost all of the reduced mediator is reoxidized at the underlying support electrode surface and that f ∼ = fS since η∼ = 1. At the enzyme/solution interface, the concentration of reduced mediator will be low and that of the oxidized form high, and the response of the biosensor will depend on the ability of the enzyme to turn over the substrate. The effect of enzyme loading on the amperometric current response of the biosensor was also examined, and the response as found to be highly sensitive to the amount of enzyme immobilized. A linear relationship between steady-state current response and enzyme loading was observed, when the surface coverage of enzyme was varied between 0.019 and 0.29 pmol cm−2 . The dynamic range of the sensor was not affected by the variation in enzyme loading. The latter observation could be understood in terms of a ratedetermining enzyme turnover step rather than slow mass transport or enzyme/substrate complex formation. A desirable attribute for a practical biosensor is that the response should be independent of enzyme loading, especially if the activity of the device is to be maintained during storage. Working from the dimensions of the glucose oxidase molecule (308 nm3 ) the maximum enzyme loading possible for a GOx/SAM system is 4 pmol cm−2 , which is considerably lesser than the loading required for the response to be independent of enzyme loading (ca 103 pmol cm−2 ). This therefore is an important limitation for immobilized enzyme monolayer electrodes. Gooding et al.36 also examined the effect
THE BIOLOGY – MATERIALS INTERFACE
of mediator concentration on the amperometric response of the biosensor. An increase in mediator concentration (the range 0.1–5 mM was examined) was found to result in both an increase in sensitivity and dynamic range (Figure 4, Ref. 24). The latter observations were assumed to reflect the fact that the increased concentration of mediator brought about an increased rate of turnover of the reduced enzyme back to its catalytically active oxidized form. Furthermore, the extension in dynamic range with increased mediator concentration was rationalized in terms of the proposal that the sensor was limited by the conversion of the reduced enzyme to the oxidized enzyme rather than by the reaction of the substrate with the oxidized form of the enzyme, or the dissociation of the enzyme/substrate complex. This corresponds to case IA in our terminology. In the latter situation according to the diagnostic parameters outlined in Table 1 the steady-state current should be first order in mediator concentration, first order in enzyme concentration, and zero order in substrate concentration. From Figure 4 in the Gooding paper,36 we note that the batch amperometry profiles indicate only a slight dependence on the current with increasing substrate concentration and a first-order increase in current response with mediator concentration. Gooding et al.36 examined the variation in sensor sensitivity with rotation speed and showed that, relative to a quiescent solution, there is a decrease in sensitivity with stirring; however, the steady-state current level did not subsequently vary very significantly with increasing rotation rate as would be predicted through equations (43) and (44). Again this implies that diffusion of reduced mediator species B to the underlying support electrode surface is greater than the diffusive loss of reduced mediator to the solution and that the observed steady-state current almost fully reflects the kinetic processes occurring at the enzyme surface. Returning to equation (45) we note that the inverse flux, when the mediator/enzyme kinetics are unsaturated, is given by 1 fS −1 1 1 − = fS ke LκA a ∞ fDA fS −1 1 1 + + ∞ 1− (kC /KM )e LκS s fDS kC e L (81)
0.7 0.6 0.5
i (µA cm−2)
24
0.4 0.3 0.2 0.1 0 0
0.05
0.1
0.15 [glucose]
0.2
0.25
0.3
0.35
mM−1
Figure 14. Plot of inverse current versus inverse substrate concentration for a biosensor consisting of glucose oxidase immobilized within an MPA (3-mercaptopropionic acid) self-assembled monolayer using benzoquinone as a soluble mediator. The graph is constructed from batch amperometry data published by Gooding et al.36 Enzyme loading: 0.7 pmol cm−2 ; [benzoquinone]: 1 mM.
and so a plot of inverse flux versus inverse substrate concentration should be linear provided that f f the kinetic terms TS = 1 − f S or TA = 1 − f S DS DA can be neglected. If the latter terms are significant then the inverse flux versus inverse substrate concentration plot should deviate from linearity. We present an analysis of the Goodring batch amperometry data (Figure 2, Ref. 36) in Figure 14. This plot is analogous to a Lineweaver–Burk graph used in enzyme kinetics. We note that the plot deviates significantly from linearity at low substrate concentrations. This arises because of mediator or substrate concentration polarization effects in the solution, as predicted from equation (81).
4 EXTENSION OF MODELING TO MORE COMPLEX SITUATIONS AND SYSTEMS
In this chapter we have concentrated on two particularly simple examples of mathematical modeling applied to the biosensor/solution interface—direct enzyme reaction at surfaces and the kinetics of redox enzymes immobilized on self-assembled monolayer thin films. Much more has been done in the area of mathematical modeling of amperometric enzyme electrodes. However, owing to limitations of space, and indeed owing to the fact that these models are considerably more complex, we
MODELING OF BIOSENSOR INTERFACES
refrain from presenting a detailed account of these activities here but merely constrain our description to a general overview. There has been considerable interest in recent years in the immobilization of enzymes within electronically conducting and redox conducting polymer films. Electrochemical polymerization provides a simple and attractive approach for the immobilization of enzymes at electrode surfaces. The process can be controlled by the choice of electrode potential and will therefore allow accurate control of the polymer film thickness and hence the amount of enzyme entrapped in close proximity to the electrode surface. Progress in this area has been outlined in the recent reviews of Bartlett and Cooper47 and Chaubrey and coworkers.48,49 The kinetics of immobilized enzymes dispersed in polymer films of appreciable thickness has been reported by Mell and Maloy,50 Bartlett and Whittaker,44,45 Gooding and coworkers,51 Marchesiello and Genies,52 Bartlett and Pratt,53 and Karube and coworkers.41 The kinetic analysis of a dispersed enzyme configuration within a porous polymer layer is complex. The reaction scheme envisaged is as
follows: kE
Eox + S → ERed + P kM
B + ERed → A + Eox kET
A→B where A and B denote the reduced and oxidized forms of the mediator (e.g., ferrocene/ferricinium), Eox , Ered denote the oxidized and reduced forms of the redox enzyme, and S, P are the substrate and product. Again kE and kM are rate constants defining the reaction kinetics between substrate/enzyme and mediator/enzyme, respectively. Typical processes to be modeled are outlined schematically in Figure 15. The scheme is based on a redox enzyme such as glucose oxidase, which follows a “ping-pong” reaction mechanism. In the figure, A/B represents the mediator redox couple, Eox and Ered , and S/P represent the substrate and product species, respectively. We assume that the enzyme E is immobilized within the polymer matrix such that its concentration is uniform throughout the thickness L of the polymer layer.
Substrate partition
Substrate/enzyme reaction (MM kinetics)
Electrode
Membrane
Ered
Mediator diffusion e
−
kS
DS P
S
Eox
A
Mediator regeneraion
Substrate diffusion
D ′S S0
S
S∞ Substrate diffusion in membrane
B∞
B kM
DM B
25
B A
A
A
DM
Enzyme regeneration via reaction with mediator
A∞ Solution
Mediator partition
Figure 15. Schematic of a typical enzyme membrane electrode illustrating the various transport and kinetic processes that may serve as rate-determining factors.
26
THE BIOLOGY – MATERIALS INTERFACE
The substrate is free to diffuse through the film with a diffusion coefficient DS . It should be noted that the value of the substrate diffusion coefficient for transport within the porous matrix may differ in magnitude from that exhibited by the substrate in solution. Partitioning of the substrate across the membrane/solution interface occurs and is quantified by a partition coefficient κS . Bartlett and Pratt53 have noted that the redox mediator may be entrapped within the enzyme layer or it may be present in both the enzyme layer and bulk solution. Indeed the redox mediator may be present either in its oxidized form (e.g., dioxygen) or in its reduced form (e.g., ferrocene) in solution. Both situations are found in practice. It is assumed that the mediator can only be regenerated at the electrode surface, giving rise to a current, which can be used to monitor the catalytic sequence of reactions. Bartlett and Pratt53 have considered in detail the former situation where the mediator is trapped within the film. Detailed analysis produces nonlinear reaction-diffusion equations, which may only be subject to an approximate analytical solution. One can readily show that the following reaction/diffusion equations pertain to the situation presented in Figure 15. d2 u dχ 2
−
θ η−1 γM v{u/(1 + αu)} =0 u/(1 + αu) + θ v
γM v{u/(1 + αu)} d2 v =0 − 2 u/(1 + αu) + θ v dχ
(82)
In the latter expressions the normalized substrate and mediator concentrations are given by u = s/κS s ∞ and v = b/c, where b denotes the concentration of oxidized mediator, s is the substrate concentration, and κS is the partition coefficient of substrate. If the mediator is contained within the membrane then c = c , the total mediator concentration in the film. Alternatively, if the mediator is present in solution then c = κM c∞ where c∞ denotes the bulk concentration of mediator in solution and κM is the partition coefficient of mediator. Also the normalized distance is χ = x/L. A number of characteristic parameters are introduced into the kinetic analysis. The first is kM c the competition parameter θ = = (kC /KM )κS s ∞ fMER fSER . Here the parameter θ defines the balance between the mediator/enzyme kinetic flux and the
substrate/enzyme kinetic flux. Since the substrate S reacts with the oxidized enzyme Eox and the mediator with the reduced enzyme Ered , the parameter θ will also define the balance between the oxidized and reduced forms of the enzyme in the film. Therefore, when θ 1 the kinetics will be limited by the reaction between the reduced enzyme and the oxidized mediator species B. Therefore, under such conditions the film will mainly consist of reduced enzyme species. In contrast, when θ 1 the kinetics are limited by the reaction between oxidized enzyme and substrate and the film mainly consists of oxidized enzyme. We can also introduce a reaction/diffusion parameter γM = kM e cL = fMER . This parameter compares the fMD (DM c/L) flux of the mediator/enzyme reaction with that for mediator diffusion across the film. Finally the kM DS DS = and α = parameters η = kkMD (kC /KM )DM U M ∞ κS s KM define a mixed diffusion/reaction term and a saturation parameter, respectively. Furthermore, the flux S due to the turnover of mediator by the substrate is balanced by the difference between the fluxes due to mediator loss at the membrane/solution interface and that due to mediator generation at the electrode/membrane interface: LfS η du S = = DM c θ dχ χ =1 dv dv = − (83) dχ χ =1 dχ χ =0 In contrast, the normalized flux at the electrode/membrane interface is as follows: dv Lfobs 0 = =− (84) DM c dχ χ =0 Note that in general S = 0 and indeed S = dv 0 + dχ . In the latter expressions DM χ =1
denotes the diffusion coefficient of the mediator in the film, L is the membrane thickness, fS , fobs denote the reaction flux arising from the mediator/substrate reaction and that related to the steadystate current flow through the Faraday electrolysis law (fobs = i/nF A) respectively. Note also that c denotes the total mediator concentration. The nonlinear reaction/diffusion equations expressed in
MODELING OF BIOSENSOR INTERFACES
equation (82) are integrated subject to the following boundary conditions: χ = 0,
du =0 dχ
χ = 0, u0 + v0 = 1 χ = 1, u = u1 = 1
(85)
and χ = 1,
dv =0 dχ
χ = 1, v = v1 = 1 χ = 1, v = v1 = 0
(86)
Note that the boundary conditions outlined in equation (86) are of three types depending on the type of biosensor system used. The first corresponds to the case where the redox mediator is contained within the film. The second corresponds to the situation where the oxidized mediator, such as molecular oxygen, is present in the bulk solution. The third corresponds to the situation where the reduced mediator such as ferrocene carboxylic acid is present in the solution bulk. In the latter two cases the mediator partitions into the film from the solution and we have mediator transport across the membrane/solution interface. Finally the mediator concentration at the detector interface at χ = 0 is fixed by the value of the applied electrode potential. If for example, the mediator regeneration reaction at the detector electrode is Nernstian, then we can write 1 v0 = 1 + exp[−ξ ] where the normalized potential nF (E − E 0 ). Under limiting current conis ξ = RT ditions ξ → ∞ and exp[−ξ ] → 0 so v0 → 1. Now the reaction/diffusion equations presented in equation (82) may be solved approximately for various limiting values of θ say (i.e., whether substrate-limited or mediator-limited kinetics). A situation may also be found where one part of the film may exhibit mediator-limited kinetics whereas another part may exhibit substrate limitation. This is the so-called titration situation. Furthermore, the situation when the substrate concentration is uniform across the film may be addressed. This is important when the layer is thin. All of these situations may be subjected to detailed analysis along lines similar to that outlined in previous sections.
27
This has been done by Bartlett and Pratt,53 most particularly for the situation where the mediator is confined to the thin film. Case diagrams may be constructed and limiting analytical expressions for the steady-state flux derived. We defer from making this detailed presentation here for reasons of space and refer the reader to the literature.53 Further theoretical activity associated with amperometric enzyme biosensors may be briefly mentioned here. The model depicted in Figure 15 refers to the situation of heterogeneous mediation. This should be distinguished from homogeneous mediation where the substrate, enzyme, and mediator are all located within the diffusion layer adjacent to a support electrode surface. This situation has been recently discussed by Albery and coworkers54 and by Bartlett and Pratt.55 Again nonlinear reaction/diffusion equations may be proposed and approximately solved to yield kinetic expressions and kinetic case diagrams. The problem is very complex and has been well described in the review by Bartlett et al.21 An interesting analysis of an amperometric enzyme electrode where an artificial electron acceptor competes with oxygen for the reduction of the enzyme has been reported by Hall and Martens.56 The topic of amperometric biosensor amplification57,58 has also been examined. The sensitivity of enzyme electrodes can be increased substantially by incorporation of a substrate recycling scheme.57–60 A possible strategy here involves an electrochemical recycling of enzyme substrate during the transduction step. Therefore, the shuttle analyte is measured not just once but is reconverted to be measured again leading to an amplification in the transduction signal. Finally the modeling of an immobilized oxidase system located in a matrix through which a distribution of conductive mertallic nanoparticles of defined size has been dispersed is reported.61,62 We conclude that the mathematical modeling of amperometric enzyme biosensors offers many and indeed varied problems of considerable challenge, and the results obtained can provide considerable insight into the mechanism of biosensor operation. REFERENCES 1. N. L. Rosi and C. A. Mirkin, Nanostructures in biodiagnostics. Chemical Reviews, 2005, 105, 1547–1562. 2. I. Willner, B. Willner, and E. Katz, Functional biosensor systems via surface nanoengineering of electronic
28
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15. 16.
17.
18.
19.
THE BIOLOGY – MATERIALS INTERFACE elements. Reviews in Molecular Biotechnology, 2002, 82, 325–335. I. Willner and E. Katz, Integration of layered redox proteins and conductive supports for bioelectronic applications. Angewandte Chemie International Edition, 2000, 39, 1180–1218. I. Willner and B. Willner, Biomaterials integrated with electronic elements: en route to bioelectronics. Trends in Biotechnology, 2001, 19, 222–230. J. J. Davis, D. A. Morgan, C. L. Wrathmell, D. N. Axford, J. Zhao, and N. Wang, Molecular bioelectronics. Journal of Materials Chemistry, 2005, 15, 2160–2174. F. W. Scheller, U. Wollenberger, C. Lei, W. Jin, B. Ge, C. Lehmann, F. Lisdat, and V. Fridman, Bioelectrocatalysis by redox enzymes at modified electrodes. Reviews in Molecular Biotechnology, 2002, 82, 411–424. W. Schuhmann, Amperometric enzyme biosensors based on optimized electron transfer pathways and nonmanual immobilization procedures. Reviews in Molecular Biotechnology, 2002, 82, 425–441. K. Habermuller, M. Mosbach, and W. Schuhmann, Electron transfer mechanisms in amperometric biosensors. Fresenius Journal of Analytical Chemistry, 2000, 366, 560–568. H. L. Schmidt and W. Schuhmann, Reagentless oxidoreductase sensors. Biosensors and Bioelectronics, 1996, 11, 127–135. A. Vilkanauskyte, T. Erichsen, L. Marcinkeviciene, V. Laurinavicius, and W. Schuhmann, Biosensors and Bioelectronics, 2002, 17, 1025–1031. J. J. Goodring and D. B. Hibbert, The application of alkanethiol self assembled monolayers to enzyme electrodes. Trends in Analytical Chenistry, 1999, 18, 525–533. K. Busch and R. Tampe, Single molecule research on surfaces: from analytics to construction and back. Reviews in Molecular Biotechnology, 2001, 82, 3–24. R. S. Freire, C. A. Pessoa, L. D. Mello, and L. T. Kubota, Direct electron transfer: an approach for electrochemical biosensors with higher selectivity and sensitivity. Journal of The Brazilian Chemical Society, 2003, 14, 230–243. R. W. Murray, Introduction to the Chemistry of Molecularly Mesigned Electrode Surfaces, in Molecular Design of Electrode Surfaces, Techniques of Chemistry Series, R. M. Murry (ed), Wiley, New York, 1992, Chapter 1, pp. 1–48. R. W. Murray, Chemically modified electrodes. Accounts of Chemical Research, 1980, 13, 135–141. R. W. Murray, Chemically Modified Electrodes, in Electroanalytical Chemistry, A. J. Bard (ed), Marcel Dekker, New York, 1984, Vol. 13, 191–368. R. W. Murray, A. G. Ewing, and R. A. Durst, Chemically modified electrodes: molecular design for electroanalysis. Analytical and Bioanalytical Chemistry, 1987, 59, 379A–390A. W. J Albery and A. R. Hillman, Modified Electrodes, in Annual Reports, Section C: Physical Chemistry, Royal Society of Chemistry, London, 1981, Vol. 78, 377–437. P. N. Bartlett and K. F. E. Pratt, Modelling of processes in enzyme electrodes. Biosensors and Bioelectronics, 1993, 8, 451–462.
20. W. Schuhmann, T. J. Ohara, H-L. Schmidt, and A. Heller, Electron transfer between glucose oxidase and electrodes via redox mediators bound with flexible chains to the enzyme surface. Journal of the American Chemical Society, 1991, 113, 1394–1397. 21. P. N. Bartlett, P. Tebbutt, and R. G. Whitaker, Kinetic aspects of the use of modified electrodes and mediators in bioelectrochemistry. Progress in Reaction Kinetics, 1991, 16, 55–155. 22. M. E. G. Lyons, Electrocatalysis Using Electroactive Polymer Films, Electroactive Polymer Electrochemistry. Part 1. Fundamentals, M. E. G. Lyons (ed), Plenum Press, New York, 1994, Chapter 2, pp. 237–374. 23. M. E. G. Lyons, Mediated electron transfer at redox active monolayers. Part 3. Bimolecular outer sphere, first order koutecky—levich and adduct formation mechanisms. Sensors, 2002, 2, 473–506. 24. M. E. G. Lyons, C. H. Lyons, A. Michas, and P. N. Bartlett, Heterogeneous redox catalysis at hydrated oxide layers. Journal of Electroanalytical Chemistry, 1993, 351, 245–258. 25. W. J. Albery and J. R. Knowles, Evolution of enzyme function and development of catalytic efficiency. Biochemistry, 1976, 15, 5631–5640. 26. D. B. Northrop, On the meaning of KM and v/KM in enzyme kinetics. Journal of Chemical Education, 1998, 75, 1153–1157. 27. W. J. Albery, P. N. Bartlett, D. H. Craston, Amperometric enzyme electrodes. Part 2. Conducting salts as electrode materials for the oxidation of glucose oxidase. Journal of Electroanalytical Chemistry, 1985, 194, 223–235. 28. P. N. Bartlett, R. G. Whitaker, M. J. Green, and J. Frew, Covalent binding of electron relays to glucose oxidase. Journal of the Chemical Society. Chemical Communications, 1987, 1603–1604. 29. H. O. Finklea, Electrochemistry of organized monolayers of thiols and related molecules on electrodes. Electroanalytical Chemistry, A. J. Bard, I. Rubenstein (eds). 1996, 19, 109–335. 30. H. O. Finklea, Self Assembled Monolayers on Electrodes, in Encyclopaedia of Analytical Chemistry, R. A. Meyers (ed), Wiley, Chichester, 2000. 31. D. K. Schwartz, Mechanism and kinetics of self assembled monolayer formation. Annual Review of Biophysics and Biophysical Chemistry, 2001, 52, 107–137. 32. J. C. Hule, Guided molecular self assembly: a review of recent efforts. Smart Materials and Structures, 2003, 12, 264–271. 33. J. J. Gooding, L. Pugliano, D. B. Hibbert, and P. Erokhin, Amperometric biosensor with enzyme amplication fabricated using self assembled monolayers of alkanethiols: the influence of the spatial distribution of enzymes. Electrochemistry Communications, 2000, 2, 217–221. 34. J. J. Gooding and D. B. Hibbert, The application of alkanethiol self assembled monolayers to enzyme electrodes. Trends in Analytical Chenistry, 1999, 18, 525–533. 35. J. J. Gooding, P. Erokhin, D. Losic, W. Yang, V. Policarpio, J. Liu, F. M. Ho, M. Situmorang, D. B. Hibbert, and J. G. Shapter, Parameters important in fabricating enzyme electrodes using self assembled
MODELING OF BIOSENSOR INTERFACES
36.
37.
38.
39.
40.
41.
42.
43. 44.
45.
46.
47.
48.
49. 50.
monolayers of alkanethiols. Analytical Sciences, 2001, 17, 3–9. J. J. Gooding, P. Erokhin, D. B. Hibbert, Parameters important in tuning the response of monolayer enzyme electrodes fabricated using self assembled monolayers of alkanethiols. Biosensors and Bioelectronics, 2000, 15, 229–239. C. Bourdillon, J. P. Bourgeois, and D. Thomas, Covalent linkage of glucose oxidase on modified glassy carbon electrodes. Kinetic phenomena. Journal of the American Chemical Society, 1980, 102, 4231–4235. T. Tatsuma and T. Watanabe, Model analysis of enzyme monolayer and bilayer modified electrodes: the steady state response. Analytical Chemistry, 1992, 64, 625–630. P. N. Bartlett, P. Tebbutt, and C. H. Tyrrell, Electrochemical immobilization of enzymes 3. Immobilization of glucose oxidase in thin films of electrochemically polymerized phenols. Analytical Chemistry, 1992, 64, 138–142. Erratum: Analytical Chemistry, 1992, 64, 1635. M. E. G. Lyons, Mediated electron transfer at redox active monolayers. Part 4. Kinetics of redox enzymes coupled with electron mediators. Sensors, 2003, 3, 19–42. I. Karube, K. Vokoyama, and E. Tamiya, Kinetics of an amperometric glucose sensor with soluble mediator. Journal of Electroanalytical Chemistry, 1989, 273, 107–117. R. Matsumoto, K. Kano, and T. Ikeda, Theory of steady state catalytic currents of mediated bioelectrocatalysis. Journal of Electroanalytical Chemistry, 2002, 535, 37–40. W. J. Albery, Electrode Kinetics, Clarendon Press, Oxford, 1975, Chapter 3, pp. 51–54. P. N. Bartlett and R. G. Whitaker, Electrochemical immobilization of enzymes. Part 1. theory. Journal of Electroanalytical Chemistry, 1987, 224, 27–35. P. N. Bartlett and R. G. Whitaker, Electrochemical immobilization of enzymes. Part 2. Glucose oxidase immobilized in poly–N–methyl pyrrole. Journal of Electroanalytical Chemistry, 1987, 224, 37–48. M. J. Giz, B. Duong, and N. J. Tao, In situ STM study of self assembled mercaptopropionic acid monolayers for electrochemical detection of dopamine. Journal of Electroanalytical Chemistry, 1999, 465, 72–79. P. N. Bartlett and J. M. Cooper, A review of the immobilization of enzymes in electropolymerized films. Journal of Electroanalytical Chemistry, 1993, 362, 1–12. M. Gerard, A. Chaubrey, and B. D. Malhotra, Applications of conducting polymers to biosensors. Biosensors and Bioelectronics, 2002, 17, 345–359. A. Chaubrey and B. D. Malhotra, Mediated biosensors. Biosensors and Bioelectronics. 2002, 17, 441–456. L. D. Mell and J. T. Maloy, A model for the amperometric enzyme electrode obtained through digital simulation
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
29
and applied to the immobilized glucose oxidase system. Analytical Chemistry, 1975, 47, 299–307. J. J. Gooding, E. A. H. Hall, and D. B. Hibbert, From thick films to monolayer recognition layers in amperometric enzyme electrodes. Electroanalysis, 1998, 10, 1130–1136. M. Marchesiello and E. Genies, A theoretical model for an amperometric glucose sensor using polypyrroleas an immobilization matrix. Journal of Electroanalytical Chemistry, 1993, 358, 35–48. P. N. Bartlett and K. F. E. Pratt, Theoretical treatment of diffusion and kinetics in amperometric immobilized enzyme electrodes. Part 1. redox mediator entrapped within the film. Journal of Electroanalytical Chemistry, 1995, 397, 61–78. W. J. Albery, P. N. Bartlett, B. J. Driscoll, and R. B. Lennox, Amperometric enzyme electrodes. Part 5. The homogeneous mediated mechanism. Journal of Electroanalytical Chemistry, 1992, 323, 77–102. P. N. Bartlett and K. F. E. Pratt, A study of the kinetics of the reaction between ferrocene monocarboxylic acid and glucose oxidase using the rotating disc electrode. Journal of Electroanalytical Chemistry, 1995, 397, 53–60. N. Martens and E. A. H. Hall, Model for an immobilized oxidase enzyme electrode in the presence of two oxidants. Analytical Chemistry, 1994, 66, 2763–2770. L. Coche-Guerente, V. Desprez, J. P. Diard, and P. Labbe, Amplification of amperometric biosensor responses by electrochemical substrate recycling. Part 1. theoretical treatment of the catechol—polyphenol oxidase system. Journal of Electroanalytical Chemistry, 1999, 470, 53–60. R. Baronas, J. Kulys, and F. Ivanauskas, Modeling amperometric enzyme electrodes with substrate cyclic conversion. Biosensors and Bioelectronics, 2004, 19, 915–922. V. V. Sorochinskii and B. I. Kurganov, Steady state kinetics of cyclic conversions of substrate in amperometric bienzyme sensors. Biosensors and Bioelectronics, 1996, 11, 225–238. B. Limoges, D. Marchal, F. Mavre, and J. M. Saveant, High amplification rates from the association of two enzymes confined within a nanometric layer immobilized on an electrode: modeling and illustrating example. Journal of the American Chemical Society, 2006, 128, 6014–6015. M. Somasundrum, A. Tongta, M. Tanticharoen, and K. Kirtikara, A kinetic model for the reduction of enzyme generated hydrogen peroxide at a metal dispersed conducting polymer film. Journal of Electroanalytical Chemistry, 1997, 440, 259–264. M. E. G. Lyons, D. E. McCormack, and P. N. Bartlett, Microheterogeneous catalysis in modified electrodes. Journal of Electroanalytical Chemistry, 1989, 261, 51–59.
21 Ion Channel Biosensors Bruce A. Cornell Surgical Diagnostics Pty Ltd., St Leonards, New South Wales, Australia
1 OVERVIEW OF MEMBRANE-BASED BIOSENSORS
Biological sensory systems function by registering changes in the electrical conductivity of specialized cell membranes.1 An important feature of this mechanism is its inherent amplification with a single molecule potentially triggering the passage of up to a million ions per second across an otherwise impermeable membrane. The first reported attempt at developing a practical membrane-based biosensor device was by Ligler et al.2 Aimed at the detection of biological toxins, it comprised alamethicin and a calcium channel complex within a polymerized bilayer lipid membrane (BLM) supported on a porous silicon substrate. The porous silicon provided both a mechanical support for the molecular membrane while also providing a reservoir for the transmembrane flow of ions. The poor stability of the receptor–membrane complex limited the range of applications of the device. The stabilization of the BLM has been a central theme in the development of membrane-based biosensors. Many strategies have been developed, but most focus on physisorbing or chemically attaching a layer of hydrocarbon to a silicon,3 hydrogel,4 polymer,5,6 or metal surface,7 and then fusing a second layer of mobile lipids onto the tethered monolayer to form a tethered BLM. Reviews by Sackman8 and Plant9 describe the literature on BLM stabilization. These approaches have become progressively more sophisticated10 and a key objective is now to employ patterning
techniques to produce membrane arrays possessing different localized functionalities. 2 THE ION CHANNEL SWITCH (ICS ) BIOSENSOR 2.1
Principle of Operation
The low-molecular-weight bacterial ion channel gramicidin11 has been used,12–16 as the basis of a biosensor platform with a range of applications for the detection of low-molecular-weight drugs, large proteins, and microorganisms. The ion channel switch (ICS ) biosensor employs a lipid monolayer tethered via a disulfide group to a gold surface. The membrane is separated from the gold surface by an ethylene glycol spacer which provides a reservoir for ions permeating through the membrane. The transduction mechanism depends on the properties of gramicidin A within a BLM. Gramicidin monomers diffuse within the individual monolayers of the BLM. The flow of ions through gramicidin only occurs when two nonconducting monomers align to form a conducting dimer. The gramicidins within the tethered inner leaflet of the lipid bilayer are also tethered. Also attached to the gold surface as part of the inner leaflet are membrane spanning lipids (MSLs). The arrival of analyte cross-links antibodies attached to the mobile outer layer channels, to those attached to MSL tethers. Because of the low density of tethered channels within the inner-membrane leaflet,
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE
Figure 1. Large analyte transduction mechanism. The binding of analyte (green) to the antibody fragments (Fab) (red) causes the conformation of gramicidin A to shift from conductive dimers to nonconductive monomers. This causes a loss of conduction of ions across the membrane. Scale 5 nm = .
this anchors them distant, on average, from their immobilized inner-layer channel partners. Gramicidin dimer conduction is thus prevented and the admittance of the membrane decreases. Applying a small alternating potential between the gold substrate and a reference electrode in the test solution generates a charge at the gold surface and causes electrons to flow in an external circuit. The membrane stability is primarily enhanced by tethering the inner-membrane leaflet to the gold surface. However additional stability is achieved by substituting a major fraction of the tethered lipids with “archebacterial lipids”. These are lipids modeled on constituents found in bacteria capable of surviving extremes of temperature and hostile chemical environments. Characteristics of these lipids are that the hydrocarbon chains span the entire membrane,17 and that all ester linkages are replaced with ethers.18 BLM films have previously been formed from archebacterial lipids19 and resulted in membranes that are stable to temperatures in excess of 90 ◦ C. A stable membrane incorporating ion channels can be self-assembled20 on a clean, smooth gold surface using a combination of sulfur–gold chemistry and physisorption. Many attempts to
Figure 2. Small analyte transduction mechanism. In the absence of analyte, the mobile channels cross-link to antitarget Fabs anchored at the tether sites. Dimer formation is prevented and the conductance of the membrane falls. The introduction of analyte competes off the hapten (target analog) and increases the membrane conductance.
engineer receptor-based gated ion channels have been reported. Mechanisms range from antichannel antibodies that disrupt ion transport21 to molecular plugs that block the channel entrance.22 These mechanisms require reengineering for each new analyte. Most studies of the ICS biosensor have used antibody Fab fragments as the receptor; however, the approach has been demonstrated to operate using oligonucleotide probes, heavy metal chelates, and cell surface receptors. 2.2
Large and Small Analyte Detection
Large analytes include proteins, hormones, polypeptides, microorganisms, oligonucleotides, DNA segments, and polymers. In the same manner that an ELISA “sandwich” assay may be developed based on a complementary antibody pair, the ICS biosensor may be adapted to the detection of any antigenic target for which a suitable antibody pair is available. The bacterial ion channel gramicidin A is assembled into a tethered lipid membrane and coupled to an antibody targeting a compound of diagnostic interest. The binding of the target molecule causes the conformation of the gramicidin channels to switch from predominantly conducting dimers to predominantly nonconducting monomers as shown in Figure 1. For target analytes with low molecular weights such as therapeutic drugs where the target is too small to use a two-site sandwich assay, a competitive adaptation of the ICS is available. This is shown in Figure 2. 2.3
Biochips and Multianalyte Detection
2.3.1 Biochip Arrays
Sensor arrays have been fabricated using silicon nitride, silicon carbide, and glass substrates. A
ION CHANNEL BIOSENSORS
typical fabrication scheme for a 6-in. crystal silicon wafer is shown in the box below. Using this format a multianalyte detection capability is demonstrated. Multianalyte detection is an advantage as it permits “on board” calibration to correct for systematic variations which can occur across an electrode array and to correct for electrodeto-electrode variation between different sensors. A novel element in the design of these arrays is the use of a titanium oxide ring at the perimeter of the electrode opening. The titanium seal is designed to provide an electrical seal as shown in Figure 3. In addition it retains water during the spotting of biologicals and during the dry down process for storage. A schematic of this design is shown below in Figure 4. Examples of electrode arrays are shown in Figure 5, recorded by both optical and scanning electron microscopy. In Figure 5(a) a 4 × 4, 16 element array of 150µm-diameter electrodes is shown and Figure 5(b) shows a test array of four electrodes ranging from 150 to 20 µm diameter. A consequence of reducing the electrode diameter from 150 to 20 µm is
Hydrophilic
Hydrophobic
Bounds second layer
Seals membrane from leaking at the edge
Figure 3. The combination of the hydrophobic silicon nitride or carbide in combination with the hydrophilic ring of titanium oxide is designed to provide an electrical barrier preventing the leakage of ions at the edge of the membrane. In addition, the hydrophilic ring traps water during the fabrication and drying process. Silicon carbide and nitride permit functional sensors to be made; however, they possess relatively low contact angles to water of 40–60◦ . Higher contact angles nearer to or exceeding 90◦ would achieve better sealing and stability.
3
a reduction of the membrane capacitance and an increase in the membrane resistance. Both measures scale with membrane area, the capacitance linearly and the impedance inversely. In order to test the limits on the lowest-possible electrode diameter, the impedance was measured versus the reciprocal of the electrode area. The membrane in this case was free of ion channels and comprised only a sealing lipid layer. The impedance estimates shown in Figure 6 were compensated for a stray capacitance of approximately 1 pF at each electrode. Gating cross talk between electrodes via this level of capacitance was less than 10% indicating minimal effects from the stray capacitance at the 20-µm-diameter electrode. From Figure 6 it can be seen that a gigaohm seal is achieved at electrode diameters of 50 µm suggesting a high quality seal at the membrane–electrode interface. For the 150µm-diameter electrodes the electrode impedance is 4.7 M in parallel with 120 pF. The interfacial capacitance at the gold surface is 840 pF. Care must be taken in the layout of the contact pads connecting to the electrodes so that capacitative leakage between the test electrode and the substrate of conductive silicon does not exceed the membrane capacitance of the test electrode. This is particularly critical in Figure 5(b) for the 20-µmdiameter electrode where the electrode–membrane capacitance is approximately 2 pF. Although the impedance of these electrodes is dependent on area, the time-dependent responses are independent of area. Such a dependence would only be expected when the spacing of the ion channels or antibodies are comparable to the electrode dimensions. In the present case these spacings are all far smaller than the smallest 20-µm-diameter electrode. One advantage of using an electrode array to measure the target species concentration rather than a single electrode of comparable
100-µm-diameter opening depending on application Titanium oxide 100 nm Silicon nitride 100 nm Titanium barrier 50 nm
Gold 200 nm Single crystal silicon wafer 0.5 mm oxide coated (500 nm)
Figure 4. Cross section of one element in a silicon chip sensor array. The design incorporates five layers: (i) an underlying silicon wafer, (ii) a 50-nm titanium barrier, (iii) a 200-nm gold layer, (iv) a 100-nm silicon nitride layer, and (v) a patterned ring of titanium oxide. The titanium oxide ring is designed to provide a hydrophilic surface at the membrane edge.
4
THE BIOLOGY – MATERIALS INTERFACE
(a)
(b)
(c)
Figure 5. (a) Optical microscopy image of a 16-element sensor array with 150-µm-diameter electrodes. The apparently square geometry of the sensor elements arises from the gold being patterned as rectangles and the silicon nitride openings being round. Because the silicon nitride is only 100 nm thick, it is transparent, allowing the gold to be viewed through the nitride layer. Also visible is the light-gray 2-µm-wide titanium oxide ring. (b) Optical microscopy image of a test array with four electrode elements of 150, 100, 50, and 20 µm diameter. (c) Scanning electron microscopy image of the edge of one of the 150-µm electrode openings showing the titanium oxide ring and the gold to silicon nitride interface. The etch angle at the gold to silicon nitride edge is ∼ 65◦ . Impedence versus reciprocal electrode area
Impedance (Ω)
8.0E+09 6.0E+09 4.0E+09 2.0E+09 0.0E+00 0
0.001
0.002
0.003
0.004
1/(Electrode area) (µm−2)
Figure 6. Impedance in ohms versus the reciprocal of electrode area (compensated for stray capacitance), for 150-, 100-, 50-, and 20-µm electrodes with a non-ion channel containing, sealed membrane applied to each electrode.
area is the improvement in the quality of estimating the response rate. This is shown in Figure 7. An exponential fit to the admittance–decay curve across the 16 electrodes yields coefficient of variations (CV = SD/mean) of well below 10% for a strong response. This indicates that the silicon chip fabrication procedures can provide a highly reproducible electrode geometry and structure. Additional benefits from the distributed sensing array will arise from reduction in the contributions to the CV burden of sample mixing and of course the statistical improvement of 16 independent measures rather than one. 2.3.2 Multianalyte Detection
A further benefit of the sensor arrays is their ability to measure multiple target concentrations from a single addition of sample to the sensor. A key
problem when fabricating an array capable of multianalyte detection is the site-specific decoration of the chip with different antibodies. The approach used here is shown in Figure 8. A fluid handling spotter (sciFlexarrayer leased from Scienion AG, Berlin) was loaded with the appropriate antibody solution and directed to a chip surface that had been partially dried from glycerol, trehalose, or polyvinylpyrolydine (PVP) or their combinations. Total drying was found to damage the membrane surface but drying to approximately 15% relative humidity (RH) achieved a good recovery of the chip function following spotting. The lower size limit of the electrodes was determined by the resolution achievable by the spotter–surface characteristics and not the constraints of the electrode–membrane characteristics. The limiting dimension set by the spotter–surface combination was ∼ 80 µm diameter, whereas the limit set by the electrode–membrane combination was ∼ 10 µm. Figure 9(a,b) shows an example of decorating a chip array with four arbitrary antibody receptors; that is, one quadrant, containing four electrodes, with the pregnancy hormone human chorionic gonadotropin (hCG); two quadrants with antibody receptors for influenza A nuclear protein; and a further quadrant using reference receptor to a target not in the test sample. Figure 9(a) shows the response to four samples containing either 150 mIU l−1 hCG, 100 ng l−1 influenza A nuclear protein virus, or neither. The reference electrode cluster yielded a null result to all three challenges; the hCG cluster yielded a positive response (reduction in admittance read as a negative slope) to the 150 mIU l−1 hCG sample but zero to the influenza A nuclear protein challenge, whereas the influenza
ION CHANNEL BIOSENSORS
A clusters yielded a positive result to challenge with influenza A but zero to hCG. Figure 9(b) shows the layout of the four quadrants. These data
show the ability of the approach to detect the concentration of multiple target species in one sample addition. In this case the sample volumes used
Gold patterning (electrode layout) 1. Starting material 6-in. silicon wafers with LPCVD silicon nitride protection layer 2500 Å thick
Plus
2. PECVD SiN deposition 1000-Å silicon nitride
Plus
3. Metal deposition (a) 200-Å TiW barrier (b) 2500-Å Au metallization (c) 25 Å-Ti metallization (adhesion layer)
Plus Plus Plus
4. Photoresist coating
Plus
5. Lithography stage one: electrode patterning Photoresist exposure using mask
Plus
6. Electrode metal etch (a) Ti etch (1% HF) (b) Au etch (KI) (c) TiW etch (H2O2) 7. Photoresist strip Acetone strip followed by isopropyl alcohol wash
8. Plasma clean O2 plasma clean
Plus
Plus
Plus
Silicon nitride/carbide/oxycarbide deposition (hydrophobic surface)
Plus 9. PECVD nitride/carbide/ oxycarbide depositions 10 000-Å nitride Titanium ring to trap nontethered lipid
10. Ti hydrophilic ring deposition 500-Å Ti metallization
5
Plus
6
THE BIOLOGY – MATERIALS INTERFACE
11. Photoresist coating Standard HPR 506
12. Lithography stage two: Ti ring patterning Photoresist exposure using mask Wafer development using 3% Sodium Hydroxide
Plus
Plus Plus
13. Ti ring metal etch Ti etch (1% HF) procedure
Plus
14. Photoresist strip Acetone strip followed by IPA rinse
Plus
15. HMDS and photoresist coating Prime wafers with HMDS to promote photoresist adhesion
Plus
Plus 16. Lithography stage three: well patterning Photoresist exposure using mask Wafer development using 3% Sodium Hydroxide 17. RIE etching Production RIE etch for nitride or carbide Process gasses: O2, CF4
18. Photoresist strip Acetone strip followed by IPA rinse
Plus
Plus Plus
19. O2 plasma clean Standard O2 plasma clean recipe (10 min) Plus 20. Dicing protect layer Standard HPR 506
ION CHANNEL BIOSENSORS
7
Plus 21. Dicing
22. Dicing protect strip Acetone strip followed by IPA rinse
Plus
Plus 23. O2 plasma clean O2 plasma clean (15 min) Fabrication sequence for silicon chip sensor array Sequence of steps employed to fabricate a silicon chip sensor array. Key steps are (5) Au patterning, (12) Ti ring patterning, (16) well patterning, and (21) dicing. Photolithography contaminates the gold surface and critical step is (23) O2 plasma cleaning. The photolithographic process employed in most commercial chip processing requires that the gold surface is cleaned thoroughly prior to depositing the tethered species. A “gold last’’ process would reduce the criticality of this step. Individual coating layers are depicted as colour-coded stripes.
For example:
UV irradiation to expose photoresist to surface pattern is depicted as arrows.
For example:
Chemical etching following irradiation is depicted as stars.
For example:
Washes with acetone following etching is depicted as circular arrows.
For example:
Plasma cleaning using oxygen plasma is depicted as snowflakes.
For example:
Reactive ion etching depicted as daggers.
For example:
Dicing of the wafer is depicted as sloping bars.
For example:
were 100 µl but these can be reduced to 10–20 µl using a coplanar return electrode. A major problem, as we will see in the next section on scale-up issues, is the insufficient control over the sensor fabrication process to permit quantitative diagnostic analysis without an “on board” calibration of each sensor. An additional use for the multiple targeted arrays is to provide an internal calibrator against which chip-to-chip variation may be corrected. 3 SCALE-UP ISSUES 3.1
Reproducibility
Variation in the sensor performance occurs between test elements within a single chip, between chips, and between chip batch to chip batch. Custom fabricated chips were supplied by Micralyne, Edmonton, Canada. The line resolution of standard silicon foundry techniques well exceeded the requirements of the biochips used here. Silicon
chip fabrication was chosen as a platform for scaling up sensor production since it was viewed as a mature technology that operated within a highly controlled, clean environment. However, an unexpected problem arose in the adaptation of standard photolithographic approaches to the fabrication of patterned surfaces for use in Au–alkanethiolbased sensors. The etch procedures employed to expose the patterned gold seriously contaminates the gold surface in a manner that we have been unable to totally reverse. Cleaning solutions such as Piranha followed by deionized (DI) water and ethanol could achieve a functioning device but the longer-term stability was seriously compromised. High-energy argon ion milling of the surface was necessary immediately prior to coating the thiol or disulfide species regardless of the wet cleaning process employed. The optimal approach is to vary the lithographic process steps to permit a “deposit gold last” sequence which although requiring a final masking step achieves the best results.
8
THE BIOLOGY – MATERIALS INTERFACE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Figure 7. Change of admittance versus time over an array of 16 electrodes. The abscissa (time) axis spans 8 min and the admittance axis spans a full scale deflection (FSD) of 70 nS. The schematic of the array in the center of the trace shows the electrodes from which each trace was recorded. The CVs for the amplitude of the response across the 16 electrodes is 2.8% and to the time constant, τ of an exponential fit to the decay is 2.1%.
Monitoring sensor performance over many batches provides an estimate of the batch-tobatch variation in performance. Figure 10 shows a 1-month record of response to 60 mIU hCG, run without calibrators or any internal corrections. Each day represents a sample of 16 measures from one array and over the month from 16 separate arrays. A batch is actually far more complicated to define as a new batch is initiated
when any of the electrodes, chemistries, or biochemistries is altered. The sample challenge was a standard solution of 60 mIU l−1 hCG. The average daily CV over 16 measures was 12% and the CV of the daily means over the 16 arrays measured during the month was 4.7%. These measures were performed in phosphate buffered saline (PBS) at 30 ◦ C on sensors made that day. Expanded view of electrode clusters showing Fab containing fluid on electrodes
(a)
(b)
(c)
Figure 8. (a) Site-specific coating was achieved by directing a metered volume of biotinylated antibody Fab onto an electrode element (230 µm diameter) in the array. The electrode surface was pretreated with 2–5% trehalose solution and dried prior to spotting the surface. Prior to spotting, the membranes had been assembled to a common structure across all electrodes, including a streptavidin linker to the ion channels and membrane spanning lipids. (b) The sciFlexarrayer (Scienion AG, Berlin) provided a stream of 20-pl-volume drops. Typically 15 drops were applied to each electrode resulting in 12 nl/quadrant of four electrodes. Each quadrant received a different biotinylated antibody fragment. (c) The chip used here was a cluster of four 2 × 2 electrode arrays each 230 µm diameter on either a glass or a silicon substrate.
ION CHANNEL BIOSENSORS
9
Average of cluster slopes 150 mlU ml−1 100 ng L−1 100 ng L−1 hCG Flu A Flu A
N_Slope
0 0.0002 0 −0.0002 −0.0004 −0.0006 −0.0008 −0.001 −0.0012 −0.0014 −0.0016
Flu test
Chip hCG - C
Flu T2
Flu T1
(a)
hCG test
Ref
R
(b)
Figure 9. (a) Response Slope in nanosiemens/s (nS s− 1) to 150 mIU ml−1 , 100 ng ml−1 influenza A nuclear protein or a reference solution free of either analyte applied to the chip. (b) Array geometry and the distribution of antibodies on each of the four clusters.
rate has been normalized to the gating amplitude of each measure. This is equivalent to reporting on the inverse of the time constant of an exponential fit to the response. In Figure 11(b) the same data is processed differently. The calibration data is now used to scale the test data resulting in substantial improvement in reproducibility. The provision of a calibrator channel is probably the most significant benefit brought by simultaneous multianalyte detection.
3.2
Stability and Storage Stability
A key requirement for any diagnostic technology is an ability to store the test element for extended
One month response to 60 mIU l−1 hCG n = 16 each day
04 6/
20 /0 28
26
/0
6/
20
04
04 20
04
6/
20 6/
/0 24
20 22
/0
6/ 20
/0
/0 18
04
04 20
04
6/
20
04 6/ /0 16
/0
6/
20 14
6/ /0
20
04
04 20 12
10
/0
6/
20
04 08
/0
6/
20
04
6/
6/
/0 06
/0 04
04
90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 -
20
Concentration mIU ml−1 hCG
A major step toward achieving a quantitative test is to provide an on board calibrator to correct for daily variation. This is particularly important when measurements are made from serum or blood where matrix variations cause substantial changes to the standard curve. In the absence of a calibrator, the variation essentially eliminates the possibility of all but semiquantitative measurements. Figure 11(a,b) shows an example of the potential improvement in reproducibility that can be achieved by employing a calibrator. The approach depends on a multianalyte capability. Figure 11(a) shows a series of individual chip arrays. The horizontal scale describes particular chip arrays. The vertical scale is a measure of the response rate to a challenge of analyte. In Figure 11(a) the response
Days
Figure 10. The daily means of 16 estimates of 60 mIU ml−1 hCG in PBS at 37 ◦ C over a 1-month period. Similar results were obtained over a 12-month period. These data were obtained from a sensor build based on a plastic substrate.
10
THE BIOLOGY – MATERIALS INTERFACE
31 SA 00 0A 31 SA 00 1B 31 SA 00 4A 38 SA 00 1A 38 SA 00 2B 38 SA 00 5A 38 SA 00 6A 38 SA 00 6B 38 SA 00 7A 38 SA 0 38 07B SA 00 8B 38 SA 01 1A
Response (normalized to Y0)
Uncalibrated chips 0 −0.002 −0.004 −0.006 −0.008 −0.01 −0.012 −0.014
T1
(a)
T2
C
R
31 SA 00 0A 31 SA 00 1B 31 SA 00 4A 38 SA 00 1A 38 SA 00 2B 38 SA 00 5A 38 SA 00 6A 38 SA 00 6B 38 SA 00 7A 38 SA 00 7B 38 SA 00 8B 38 SA 01 1A
Calibrated (mean) response (normalized to Y0)
Calibrated chip 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
(b)
T1
T2
C
R
Figure 11. (a) Uncorrected response rate to a challenge by analyte. T1 and T2 are two tests of the target concentration, C is a calibration measure, and R is a reference channel that permits a differential measure. The latter is particularly useful in blood or serum where matrix artifacts may be minimized through the use of differential reading between the test and reference electrode. The data have been normalized to the gating amplitude only. (b) Response to challenge by analyte in which the calibrator response has been used to normalize the test responses. The effect of normalizing to the calibrator values is to reduce the CVs of T1 and T2 from 27 and 22% to 15 and 14%, respectively.
periods with minimal degradation in performance. A serendipitous observation has permitted a significant insight into some of the mechanisms that cause age-dependent changes in the ICS sensor. Figure 12(a) shows a schematic of a sensor being gated by the multivalent protein, streptavidin (MW ∼ 60 kDa). It was found that if the linker attaching the biotins to the ion channel was reduced in length to a glycine group, then the streptavidin (SA) “on rate” to the biotin was ineffective in achieving gating on the 5–10 min timescale. However, if as shown in Figure 12(b) membrane spanning lipid, MSL4XB, is present a strong, rapid gating occurs. The experimental evidence for this is shown in Figure 13(a,b). This result indicates that SA can bind effectively to the MSL4XB but not to the gaglyB. However, once bound to MSL4XB, the
SA is presented in a way to permit binding to the gaglyB. Even though the details of the mechanism are not understood, the conclusion may be drawn that the gating only results from the gaglyB diffusing to a site where SA has already bound to the MSL4XB. This provides a method of determining the average diffusion distance of the ion channel in the membrane and a means of probing whether this distance alters on storage. By titrating the gating reaction rate to the concentration of the SA challenge, the kon of the SA to the MSL4XB is determined. This may be contrasted with the far slower kon of the SA to the gaglyB. Comparing these kon values with those obtained from directly cross-linking ion channels possessing longer 5XB linkers it is possible to determine the diffusion distance. The
ION CHANNEL BIOSENSORS −MSL
11 +MSL
Streptavidin gaglyB
MSL4XB (a)
(b)
Figure 12. (a) Schematic of a sensor membrane containing gaglyB, the short linker biotinylated gramicidin ion channel, and no biotinylated membrane spanning lipid MSL4XB. (b) The same construct containing MSL4XB.
Table 1. Experimentally determined kon values for the various combinations of ion channel and MSL4XB described above
Configuration ga5XB + std MSL4XB gaglyB + std MSL4XB ga5XB no MSL4XB gaglyB no MSL4XB
Slope = kon M−1 s−1 7.40 × 106 1.19 × 106 6.90 × 106 0.43 × 106
various combinations of kon are given in Table 1. In Table 1 it is evident that when using the longer 5XB linkers the dependence on the MSL4XB is almost eliminated. Taking the ratio of the second and third entries of Table 1 provides a measure of the kon of the mobile channel, ga5XB density to the density of the tethered membrane spanning, MSL4XB sites. The ratio is less than unity at 0.17. This means that the density of mobile channels is greater than the density of the tethered membrane spanning lipid MSL4XB capture sites. This is necessary if streptavidin is used as a linker species linking the channel or the MSL to the biotinylated antibodies. Higher levels of MSL4XB result in too great a cross-linking of the ga5XB to MSL4XB by the streptavidin. This problem is eliminated when using a covalent linkage to the antibody fragment and larger densities of MSL4XB are possible resulting in significantly higher sensitivities. However, in the present study, using the density of channels added in the second mobile layer as 3 × 109 molecules/cm2 , we may determine the MSL4XB density as ∼ 6.7 × 108 molecules/cm2 . Varying the MSL4XB density relative to this estimate now permits a measure of the diffusion
distance of the ion channels. This is seen in Figure 14 in which the MSL4XB density is plotted relative to the value used above. This value is described as the standard (stnd) value. It can be seen that when the sensors are fresh, the gating amplitude rises from a very low value at zero MSL4XB to a maximal value at approximately the standard density of MSL4XB. This indicates a diffusion distance of the channels of approximately (6.7 × 108 )−0.5 = 0.5 µm. This further suggests a complex structure to the membrane surface restricting the diffusion distance. If the diffusion were unrestricted a diffusion distance × 10 of this value would be expected. The alternative explanation that the diffusion coefficient is slowed is not supported by the kinetics of the gating response. When the sensors are dried and stored, also seen in Figure 14, the diffusion distance is reduced by ∼ 40% suggesting the drying and storage have further restricted the average diffusion distance. To maintain a gating response for long periods of storage requires increasing the density of MSL4XB. Figure 15 demonstrates storage times at 20 ◦ C out 28 days. After 3 months at 20 ◦ C the titration response deviates outside acceptable limits. Storage at 4 ◦ C significantly extends the acceptable titration response and some sensors can survive 6 months. The dominant factors causing failure appear to be associated with the diffusion of the mobile species. In all cases the loss of responsiveness is at high target concentrations, leaving the low-concentration region of the standard curve substantially unaltered. This suggests a diffusion mechanism as the cause of the performance loss and more work is required to understand and
12
THE BIOLOGY – MATERIALS INTERFACE −MSL
+MSL 1.4 Normalized response
Normalized response
1.4 1.2 1 0.8 0.6 0.4 0.2
1.2 gly4 × 10S gly4 × 3S gly4 × 1S gly4 × 03S gly4 × 01S gly4 × 0S
1 0.8 0.6 0.4 0.2 0
0 0
500
(a)
1000 Time
1500
2000
0
500
1000 Time
(b)
1500
2000
Figure 13. Experimental gating result for the membrane seen in Figure 12 challenged by 0, 0.1, 0.3, 1, 3, or 10 nM SA. (a) With no MSL4XB, little response is seen at all SA concentrations. (b) With MSL4XB, with 0, 0.1, 0.3, 1, 3, and 10 nM streptavidin causes a progressively larger, faster response gly4 × 10S ⇒ glycine linker gramicidin plus MSL4XB challenged with 10 nMSA.
Absolute response slope (ARS) (nS s−1)
120
Percentage gating
100 80 60 40 20 0 0
8 2 4 6 [MSL4XB] with reference to stnd
10
10 0
0
20
40
60
80
100
120
140
160
−10 −20 −30 −40
Fresh Dry, Day 0 Dry, Day 7 Dry, Day 14 Dry, Day 28
−50
Figure 15. Plot of titration gating rate versus hCG concentration in mIU ml−1 for a sensor stored at 20 ◦ C dry, for up to 1 month.
Fresh After 7day storage After 14 day storage
Figure 14. Plot of gating magnitude versus MSL4XB density relative to the standard density of 6.7 × 108 MSL4XB/cm2 . Drying and storage for 2 weeks at 20 ◦ C causes a need for higher densities of MSL4XB to achieve the same gating magnitude.
control these effects. In particular, the drying procedure plays an important role in storage performance of the sensors. 3.3
Monolayer Membranes
Whether or not the slope of the titration curve is lost, the membrane integrity does not fail. When stored dry, the membrane metrics indicate that the membranes remain sealed or conducting close to
their initial value over extended periods of time. Figure 16 shows the intrinsic stability of the tethered inner monolayer when stored at room temperature. In order to achieve a totally tethered ion channel, a covalently linked bis-gramicidin was synthesized and dispersed with the MSL. Although the conductivity rises over the initial week of storage, after 2 weeks at 20 ◦ C the conduction plateaus and there is no statistical alteration in conduction or in the scatter of conduction across the 16 measures of conductance performed on each day. The data collection is ongoing and is now approaching 6 months with similar performance. These membranes were stored wet in DI water. Note in Figure 16 the absence of any measurable conduction from the membranes not containing bis-gramicidin. The studies presented here direct
ION CHANNEL BIOSENSORS
13
YminP in nanosiemens versus days of storage at 20 °C in DI H2O +/− SD n = 16 measures on each day
80 000 70 000
YminPP (nS)
60 000 50 000 40 000 30 000 20 000 10 000
49
42
35
28
24
22
20
16
14
10
8
6
1
0 Days Plus bis-gramicidin
No bis-gramicidin
Figure 16. Plot of the admittance of membranes containing bis-gramicidin or no bis-gramicidin stored at 20 ◦ C for 51 days. The conductance from the membranes not containing bis-gramicidin is so small it is essentially off scale.
efforts to extend the storage lifetime of these sensors toward modifying the diffusional freedom of the mobile gramicidins during storage and preventing formation of complexes between lipids and biologicals when they are stored assembled on the membranes surface. ACKNOWLEDGMENT
The author wishes to acknowledge the contributions to the work described in this review. In particular, Geoff Drane, Matthew Scaffe, and Shaun Atkinson of Ambri Ltd, Australia for the characterization and spotting of biologicals onto silicon and glass chips; Jog Prashar and Doreen Bali of Ambri Ltd for the underlying chemistry and in particular the novel bis-gramicidin compound quoted in Section 3; Philip Sharp and his team of Ambri Ltd for the underlying biochemistries; Adam Panarello for the engineering interfaces to the chip; Rod Fiddes and Don Smith of Ambri Ltd for the studies of the sensor stability and storage; and Michael Finot of Micralyne Ltd of Edmonton Canada for the fabrication of silicon and glass chips; and Scienion AG, Berlin for access to the sciFlexarrayer spotting printer.
REFERENCES 1. E. Avrone and J. P. Rospars, Modelling insect olfactory neurone signaling by a network utilising disinhibition. Biosystems, 1995, 36, 101. 2. F. S. Ligler, T. L. Fare, E. E. Seib, J. W. Smuda, A. Singh, P. Ahl, M. E. Ayers, A. W. Dalziel, and P. Yager, Fabrication of key components of a receptor-based biosensor. Medical Instrumentation, 1988, 22, 247–256. 3. S. Heysel, H. Vogel, M. Sanger, and H. Sigrist, Covalent attachment of functionalized lipid bilayers to planar wave-guides for measuring protein-binding to biomimetic membranes. Protein Science, 1995, 4, 2532. 4. X. D. Lu, A. L. Ottova, and H. T. Tien, Biophysical aspects of agar-gel supported bilayer lipid nembranes: a new method for forming and studying planar bilayer lipid membranes. Bioelectrochemistry and Bioenergetics, 1996, 39, 285–289. 5. C. A. Naumann, W. Knoll, and C. W. Frank, Hindered diffusion in polymer-tethered membranes: a monolayer study at the air-water interface. Biomacromolecules, 2001(a), 2, 1097. 6. C. A. Naumann, O. Prucker, T. Lehmann, J. R¨uhe, W. Knoll, and C. W. Frank, The polymer-supported phospholipids bilayer: tethering as a new approach to substrate-membrane stabilization. Biomacromolecules, 2002, 3(1), 27–35. 7. C. Steinem, A. Janshoff, W. P. Ulrich, M. Sieber, and H. J. Galla, Impedance analysis of support lipid bilayer membranes: a scrutiny of different preparation techniques. Biochimica et Biophysica Acta, 1996, 1279, 169.
14
THE BIOLOGY – MATERIALS INTERFACE
8. E. Sackmann, Supported membranes: scientific and practical applications. Science, 1996, 271, 43. 9. A. Plant, Self-assembled phospholipid/alkanethiol biomimetic bilayers on gold. Langmuir, 1993, 9, 2764. 10. C. Schmidt, M. Mayer, and H. Vogel, A chip-based biosensor for the functional analysis of single ion channels. Nature, 2000, 39, 3137. 11. B. A. Wallace, Recent advances in the high resolution structures of bacterial channels: gramicidin a (1998). Journal of Structural Biology, 1998, 121, 123. 12. B. A. Cornell, V. L. B. Braach-Maksvytis, L. G. King, P. D. O. Osman, B. Raguse, L. Wieczorek, and R. J. Pace, A biosensor that uses ion-channel switches. Nature, 1997, 387, 580. 13. B. A. Cornell, Optical Biosensors Present and Future, Elsevier Press, 2002, pp. 457–497. 14. G. Woodhouse, L. G. King, and B. A. Cornell, Kinetics of the competitive response of receptors immobilized to ion channels which have been incorporated into a tethered bilayer. Faraday Discussions, 1998, 111, 247–258. 15. G. Woodhouse, L. King, L. Wieczorek, P. Osman, and B. Cornell, The ion channel switch biosensor. Journal of Molecular Recognition, 1999, 12, 323–334. 16. S.-K. Lee, L. G. Casc˜ao-Pereira, R. F. Sala, S. P. Holmes, K. J. Ryan, and T. Becker, Ion channel switch array: A biosensor for detecting multiple pathogens. Industrial Biotechnology, 2005, 1(1), 26–31. 17. S. C. Kushwaha, M. Kates, G. D. Sprott, and I. C. Smith, Novel complex polar lipids from the methanogenic
18.
19.
20.
21.
22.
archaebacterium Methanospirillum hungatei science. Science, 1981, 211, 1163–1164. M. A. De Rosa, B. Gamacorta, B. C. Nicolaus, and P. Albrecht, Isoprenoid ethers: backbone of complex. Lipids of the archaebacterium. Sulfolobus solfataricus. Biochimica et Biophysica Acta, 1983, 753, 249–256. A. Gliozzi, R. Rolandi, M. de Rosa, and A. Gambacort, Monolayer black membranes from bipolar lipids of archaebacteria and their temperature-induced structural changes. Journal of Membrane Biology, 1983, 75, 45–56. D. Philip and J. F. Stoddart, Self-assembly in natural and unnatural systems. Angewandte Chemie International Edition (England), 1996, 35, 1154–1196. J. Bufler, S. Kahlert, S. Tzartos, A. Maelicke, and C. Franke, Activation and blockade of mouse muscle nicotinic channels by antibodies directed against the binding site of the acetylcholine receptor. Journal of Physiology (London), 1996, 492, 107. A. N. Lopatin, E. N. Makhina, and C. G. Nichols, The mechanism of inward rectification of potassium channels—long-pore plugging by cytoplasmic polyamines. Journal of General Physiology, 1995, 106, 923.
FURTHER READING R. Naumann, E. K. Schmidt, A. Jonczyk, K. Fendler, B. Kadenbach, and T. Liebermann, Biomimetic membranes United States Patent 7208089, 2007.
22 Electrochemical Techniques in Biosensors Sunil K. Arya, Surinder P. Singh and Bansi D. Malhotra Biomolecular Electronics and Conducting Polymer Research Group, National Physical Laboratory, New Delhi, India
1 INTRODUCTION
Electrochemistry is known to play an important role in the research and development of biosensors. It is a branch of science, which encompasses chemical and physical processes involving the transfer of charge. Electrochemistry is used to study the loss of electrons (oxidation) or gain of electrons (reduction) that a material undergoes during a reaction. These reduction and oxidation reactions are commonly known as redox reactions and can provide information about the concentration, kinetics, reaction mechanisms, chemical status, and other behavior of a chemical species in solution. Electrochemical techniques can be used to investigate neurotransmitter behavior in biological systems, initiate polymerizations, and test cadmium concentration in natural waters. Electrochemistry offers a perspective different from spectroscopy or other analytical techniques. This difference encourages a researcher to learn and use electrochemistry, since it can often solve research problems that the other approaches cannot. An overview of the development of analytical chemistry demonstrates that electrochemical sensors represent the most rapidly growing class of chemical sensors. A chemical sensor can be defined as a device that yields continuous information about its environment. Ideally, a chemical sensor provides a certain type of response directly related to the quantity of a specific
chemical species. All chemical sensors consist of a transducer, which transforms the response into a detectable signal using modern instrumentation, and a chemically selective layer, which isolates the response of an analyte from its immediate environment. They can be classified according to the property to be determined as electrical, optical, mass, or thermal sensors, and are designed to detect and respond to an analyte in the gaseous, liquid, or solid state. Compared to optical, mass, and thermal sensors, electrochemical sensors are especially attractive because of their remarkable detection limits, experimental simplicity, and low cost. They hold a leading position among the presently available sensors that have reached the commercial stage and which have found a vast range of important applications in the fields of clinical, industrial, environmental, and agricultural analyses. Biosensors have recently attracted much interest and represent a rapidly expanding field of instruments to determine the concentration of substances and other parameters of biological interest. These interesting biodevices have been shown to have applications in clinical diagnostics, environmental monitoring, food freshness, and bioprocess monitoring. Diagnosis and monitoring of various diseases necessitate intensive efforts for routine examination of blood samples and other associated tests. These, however, require specialized analytical techniques, need efficient hands to perform the job, and time for collecting the desired samples
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
for performing clinical tests. Some of the analytes determined are known to be specific for a given disease and hence can be helpful to monitor its progress. The clinical utility of a biochemical test is determined by its sensitivity, its ability to detect a disease with no false negatives, and its specificity, that is, the ability to avoid false positives in a nondiseased person. The development of biosensors and biochips is the result of combined efforts of biologists, physicists, chemists, and engineers. Biosensors use the specificities of biological molecules along with physicochemical transducers to convert a biological signal into an optical or electrochemical signal. A number of biosensors based on metabolites are available for monitoring clinically and industrially important parameters like blood glucose, urea, lactate, cholesterol, uric acid, pesticides, and explosives. A biosensor is an analytical device comprising of a biological element immobilized on a suitable matrix, which in turn is coupled to a transducer that converts the biochemical response into a measurable signal. The performance of a biosensor depends upon many parameters such as sensitivity, selectivity, response time, and specificity. A number of biological molecules such as enzymes, cells, nucleic acids (DNA/PNA), tissues slices, antibodies, or organelles ensure molecular recognition and transform the analytes in some way. Various transducers such as optical, piezoelectrical, thermal, and electrochemical can be used to convert a biochemical response into an observable signal. Electrochemical biosensors are being increasingly used for monitoring synthetic and biological processes. The electrochemical techniques are known to help in the speedy development of biosensors for continuous, real-time, inexpensive, and in vivo monitoring of many components in clinical laboratories and industries. In biosensor fabrication the detection of biomolecular interactions using electrochemical impedance spectroscopy (EIS) gives an advantage in many applications. The interdigitated microarray (IDAs) electrodes are known to be more sensitive than conventional gold electrodes and are compatible with microarray construction of DNA sensors through silicon technology. IDAs have been used as impedimetric sensors. This includes the detection of the cellular behavior, enzyme activity, and antigen–antibody interactions. However, the detection of DNA hybridization without enzyme
labeling on IDAs is still limited to the use of EIS. In the EIS, the label-free affinity binding of target molecules to capture probes on the electrode surface is indicated by a shift in the impedance or a change in the capacitance or admittance of a bulk electrode. But in practice, the separation and detection of an electrical response arising from biomolecular recognition is still limited by the low sensitivity of the EIS technique. Sensitive detection requires more intimate association between the molecular recognition layer and the transduction technique. The present chapter deals with a brief overview of different electrochemical techniques and their potential applications toward the development of biosensors.
2 ELECTROCHEMICAL TECHNIQUES
Electrochemical methods are generally based on electrochemical processes taking place at an electrode surface. Electrochemical detection is based on monitoring changes of an electrical signal due to an electrochemical reaction at an electrode surface, usually as a result of an imposed potential or current. In a solution, the equilibrium concentrations of the reduced and oxidized forms of a redox couple are linked to the potential (E) via the Nernst’s equation. E = E0 +
Cox RT ln nF Cred
(1)
where, E 0 is standard potential, F is Faraday’s constant, T is absolute temperature, and Cox and Cred are concentrations of oxidation and reduction centers. For each redox couple, there exists a potential, known as the standard potential (E 0 ) at which the reduced and oxidized forms are present at equal concentrations. If a potential E with respect to the reference electrode is applied to the working electrode, for example, by the use of a potentiostat, the redox couples present at the electrode respond to this change and adjust their concentration ratios according to equation (1). Electrochemical processes can be studied and can be understood using voltammetry, polarography, chronopotentiometry, cyclic voltammetry (CV), linear sweep techniques, chronoamperometry, pulsed techniques, and others.
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
Voltammetric Methods
Voltammetry refers to the measurement of current resulting from the application of a potential. Unlike potentiometry measurements, which employ only two electrodes, voltammetric measurements utilize a three-electrode electrochemical cell (Figure 1). The use of three electrodes (working, auxiliary, and reference) along with the potentiostat instrument allows accurate application of potential functions and the measurement of the resultant current. The different voltammetric techniques are distinguished from each other primarily by the potential function that is applied to the working electrode to drive the reaction and by the material used as the working electrode. These techniques are used in characterization and quantification of the biosensor electrode. The voltammetric techniques are divided into subclasses based on the different modes of application of potential.
2.1.1 Potential Sweep Techniques
Linear Sweep Voltammetry (LSV) LSV is a general term applied to any voltammetric method in which the potential applied to a working electrode is varied linearly in time. LSV is the simplest potential sweep technique, which involves the sweeping of electrode potential between Ei and Ef at a known sweep rate. The magnitude of the scan rate may be varied from as low as 1 mV s−1 to as high as 1 000 000 V s−1 (attainable when ultramicroelectrodes are used as the working electrode). With a linear potential ramp, the faradaic current is found to increase at higher scan rates. This is due to the increased flux of electroactive material to the electrode at the higher scan rates. The amount of increase in the faradaic current is found to scale with the square root of the
scan rate. This seems to suggest that increasing the scan rate of a linear sweep voltammetric experiment could lead to increased analytical signal to noise ratio. However, the capacitive contribution to the total measured current scales directly with the scan rate giving rise to decreased signal to noise ratio with increasing scan rate. Sljukic et al. have reported the application of electrochemically polymerized composites of multiwalled carbon nanotubes (MWCNTs) with poly(vinylferrocene) (PVF) for glucose sensing.1 The nanocomposite was investigated for glucose determination in aqueous solutions using LSV (Figure 2) and the same was applied for glucose detection in diluted horse blood. Cyclic Voltammetry (CV) CV is a useful and versatile electroanalytical technique for the study of electroactive species. This is an electrolytic method that uses microelectrodes and an unstirred solution so that the measured current is limited by analyte diffusion at the electrode surface. In this case, the waveform is initially the same as in LSV, but on reaching the final potential Ef , the sweep is reversed rather than terminated. On again reaching the initial potential Ei , there are several possibilities. The potential sweep may be halted, reversed again, or alternatively continued further to a value, E. The forward scan produces a current peak for oxidation of any analyte through the range of the potential scan. The current will increase as the potential reaches the oxidation potential of the analyte, but then falls off as the concentration of the analyte is depleted close to the electrode surface. As the applied potential 2.35E−05 1.85E−05 Current (A)
2.1
3
Increasing glucose concentration
1.35E−05 8.50E−06 3.50E−06
Auxiliary electrode N2 flow
Working electrode Ag/AgCl reference electrode
Figure 1. Schematic of an electrochemical cell.
−1.50E−06 −0.2
−0.1
0
0.1
0.2
0.3
0.4
0.5
Potential (V) versus SCE
Figure 2. Linear sweep voltammograms of PVF-MWCNTGC electrode in pH 7.4 phosphate buffer containing 60 mM GOx with increasing glucose concentration in the range 0.5–10 mM.1 [Reprinted from Berbejillo et al.2 , with permission from Royal Society of Chemistry.]
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 25 Peak current (mA)
Peak current (mA)
25 20 15 10 5 0
15 10 5 0
0 (a)
20
5 10 15 20 25 30 Concentration of OCP (ppm)
0 (b)
2 4 6 8 10 12 14 Concentration of 2-AA (ppm)
Figure 3. Amperometric response obtained because of guanine oxidation in DNA/PPY–PVS film as a function of: (a) o-chlorophenol (OCP) and (b) 2-aminoanthracene (2-AA) in phosphate buffer 0.05 M pH 7, scan rate 30 mV s−1 .3 [Reprinted from Arora et al.3 , with permission from Elsevier.]
is reversed, it will reach a potential at which the reduction of product formed during forward scan starts and produces a current of reverse polarity from the forward scan. This reduction peak will usually have a shape similar to that of the oxidation peak in the other direction. The potential difference between the oxidation and reduction peaks is theoretically 59 mV for a reversible reaction. In practice, the difference is typically 70–100 mV. Larger differences or nonsymmetric reduction and oxidation peaks are an indication of a nonreversible reaction. These parameters of cyclic voltammograms make CV most suitable for characterization and mechanistic studies of redox reactions at electrodes. Also, CV is the most popular electrochemical technique for solid electrodes. The ability to obtain reproducible results, at least for subsequent cycles, is invaluable for relatively ill-defined electrode surfaces. Also, the possibility to observe the oxidation peak and the reduction peak simultaneously is quite helpful in the investigation of electrode processes. Several electrode kinetic and electrosorption processes can be studied in detail from the analysis of cyclic voltammograms recorded at various scan rates. In both LSV and CV experiments, the cell current is recorded as a function of applied potential. The important parameters that can be derived from LSV and CV are the magnitude of peak current (Ip ), peak potential (Ep ), number of electrons transferred per reactant molecule (n), rate constant, diffusion coefficient (D), and electrochemical reversibility. The peak current (Ip ) for a reversible system is described by the Randles–Sevcik equation. Ip = 2.69 × 105 An3/2 D 1/2 v 1/2 C
(2)
Here A is the area of electrode, C is the concentration of the species, v is the scan rate (V s−1 ) and according to this equation, Ip is directly proportional to concentration and v 1/2 . In the case of reversibility of the system, the peak current is proportional to the scan rate whereas the peak potential is independent of the scan rate. The peak width is given by Ep − Ep/2 = 59/n mV at 25 ◦ C
(3)
For the reversible electron-transfer processes, the anodic peak current is equal to the cathodic peak current and the peak separation, Ep , is given by an expression Ep = Epa − Epc = 59/n mV at 25 ◦ C
(4)
Berbejillo et al. have used the Randles equation for the topographic calculation of their disposable bismuth- and polyaniline-modified carbon pencil electrode and have shown that these modified electrodes provide good supporting matrices for biomolecule attachment.2 Arora et al. have reported the amperometric DNA biosensor response using CV for the detection of 2aminoanthracene (2-AA, 0.01–20 ppm) and ochlorophenol (OCP, 0.1–30 ppm) concentration, respectively at 25 ◦ C.3 They have shown that the amperometric current arising due to the oxidation of guanine base in the DNA/PPY–PVS electrodes decreased linearly with the increase in the concentration of 2-AA and OCP (Figure 3). Anodic Stripping Voltammetry (ASV) Anodic stripping voltammetry (ASV) is an electrolytic method in which a mercury electrode is
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
held at a negative potential to reduce metal ions in solution and form an amalgam with the electrode. The solution is stirred to carry as much of the analyte metal(s) to the electrode as possible for concentration into the amalgam. After reducing and accumulating an analyte for some time, the potential on the electrode is increased to reoxidize the analyte and to generate a current signal. The ramped potential generally uses a step function, such as in normal pulse polarography (NPP) or differential pulse polarography (DPP). The concentration of an analyte at the Hg electrode, for td (duration of accumulation), nh (number of moles of electrons transferred in the half reaction), il (limiting current during reduction of the metal) and VHg (volume of the electrode), CHg , is given by: CHg =
i1 td nh F VHg
(5)
The expression for current produced by anodic stripping depends on the particular type of Hg electrode but is directly proportional to the concentration of the analyte at the electrode. The main advantage of stripping analysis is the preconcentration of the analyte onto the electrode before making the actual current measurement. Anodic stripping can achieve detection of concentrations as low as 10−10 M. Lu et al. have reported the use of ASV technique for detection of immunochromatographics such as human chorionic gonadotropin (HCG) at built-in single-use screen-printed electrodes (Figure 4).4 Wang et al. have reported the immobilization of single-stranded DNA on gold colloid particles associated with a cysteamine monolayer on gold electrode surface.5 They have studied the hybridization of a silver nanoparticle–oligonucleotide DNA probe, followed by the Sample loading Contact zone with Test zone with Absorbent pad zone labeled Ab the second Ab
Fluid flow
Screen-printed electrode
Figure 4. Schematic of an immunochromatographic electrochemical biosensor.4 [Reproduced from Lu et al.4 with permission from Royal Society of Chemistry.]
5
release of silver metal atoms anchored on the hybrids by oxidative metal dissolution, and the indirect determination of the released solubilized AgI ions by ASV at a carbon fiber microelectrode. The studies show good correlation for DNA detection in the range of 10–800 pmol l−1 and allow a detection level as low as 5 pmol l−1 of the target oligonucleotides.
2.2
Polarography
Polarography is a voltammetric measurement that responds to the combined diffusion/convection mass transport effect. It falls into the general category of LSV where the electrode potential is altered in a linear fashion from the initial potential to the final potential. The use of the dropping mercury electrode (DME) makes polarography different from other LSV measurements. As a linear sweep method controlled by convection/diffusion mass transport, the current versus potential response of a polarographic experiment has the typical sigmoidal shape. In a polarography experiment, the plot of the current versus potential shows the current oscillations corresponding to the drops of Hg falling from a capillary. Polarography experiments result in sigmoidal-shaped curves if one connects the maximum current of each drop. The limiting current (the plateau on the sigmoid), called the diffusion current (id ) (diffusion is the principal contribution to the flux of electroactive material at this point of the Hg drop life), is related to analyte concentration (c) by the Ilkovic equation: id = 708nD 1/2 m2/3 t 1/6 c
(6)
where m is the mass flow rate of Hg through the capillary (mg s−1 ) and t is the drop lifetime in seconds. There are a number of limitations to the polarography experiment for quantitative analytical measurements. Because the current is continuously measured during the growth of the Hg drop, there is a substantial contribution from capacitive current. As the Hg flows from the capillary end, there is initially a large increase in the surface area. As a consequence, the initial current is dominated by the capacitive effects as charging of the rapidly increasing interface occurs. Toward the end of the drop life, there is little
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
change in the surface area, which diminishes the contribution of capacitance changes to the total current. At the same time, any redox process that occurs will result in faradaic current that decays approximately as the square root of time (due to the increasing dimensions of the Nernst diffusion layer). The exponential decay of the capacitive current is much more rapid than the decay of the faradaic current; hence, the faradaic current is proportionally larger at the end of the drop life. Unfortunately, this process is complicated by the continuously changing potential that is applied to the working electrode (the Hg drop) throughout the experiment. Kovacevic et al. have used the polarographic technique for fabrication of an amperometric biosensor containing yeast Saccharomyces cerevisiae.6 The biosensor was used to study the influence of zinc and cobalt on respiratory activity of the yeast S. cerevisiae by measuring oxygen in the solution that was earlier enriched with cobalt or zinc. 2.2.1 Normal Pulse Polarography (NPP)
NPP is one of the pulse polarographic techniques in voltammetry that minimizes the background capacitive contribution to the current by eliminating the continuously varying potential ramp, and replacing it with a series of potential steps of short duration. In NPP, series of potential pulses of increasing amplitude are applied and current measurements are made near the end of each pulse, which allows time for the charging current to decay. It is usually carried out in an unstirred solution. When a Hg drop is dislodged from the capillary (by a drop knocker at accurately timed intervals), the potential is returned to the initial value. For this experiment, the polarogram is obtained by plotting the measured current versus the potential at which the step occurs. As a result, the current is not followed during Hg drop growth, and a normal pulse polarogram has the typical shape of a sigmoid. By using discrete potential steps at the end of the drop lifetime (usually during the last 50–100 ms of the drop life which is typically 2–4 s), the experiment has a constant potential applied to an electrode with nearly constant surface area. After the initial potential step, the capacitive current decays exponentially while the faradaic current decays as the square root of
time. The diffusion current is measured just before the drop is dislodged, allowing excellent discrimination against the background capacitive current. In many respects, this experiment is like conducting a series of chronoamperometry experiments in sequence on the same analyte solution. The NPP method has 1–3 orders of increased analytical sensitivity than normal DC polarography.
2.2.2 Differential Pulse Polarography (DPP)
In DPP a series of discrete potential steps rather than a linear potential ramp are applied to obtain a polarogram. In many ways its experimental parameters for DPP are the same as with NPP such as accurately timed drop lifetimes, potential step duration of 50–100 ms at the end of the drop lifetime, and so on. Unlike NPP, however, each potential step has the same amplitude, and the return potential after each pulse is slightly more negative compared with the potential prior to the step. Hence the total waveform applied to the DME is very much like a combination of a linear ramp with a superimposed square wave. The differential pulse polarogram is obtained by measuring the current immediately before the potential step, and then again just before the end of the drop lifetime. The analytical current in this case is the difference between the current at the end of the step and the current before the step (the differential current). To obtain the differential pulse polarogram the differential current is then plotted against the average of the potential before the step and the step potential. Because this is a differential current, the polarogram in many respects is like the differential of the sigmoidal normal pulse polarogram. As a result, the differential pulse polarogram is peak shaped. DPP has better ability to discriminate against capacitive current because it measures a difference current and helps to subtract any residual capacitive current that remains prior to each step. Limits of detection (LODs) with DPP are 10−8 –10−9 M. Bolger and Lowry have reviewed the experiments involving the use of carbon paste electrodes to monitor and measure brain tissue O2 levels in freely moving animals.7 They reported that mild hypoxia and hyperoxia produced rapid changes in the differential pulse voltammetric (DPV) signal; neuronal activation (tail pinch and stimulated grooming)
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
7
0
−1 A
Current 1c−6A
−2 B
−3
C −4 D −5 E −6 F −7 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05
0
−0.05 −0.1 −0.15 −0.2
Potential (V) versus Ag/AgCl
Figure 5. Differential pulse voltammograms of BH4 at the Mn-doped PbO2 electrode: (A) blank solution, (B) 5 × 10−7 mol l−1 , (C) 1.0 × 10−6 mol l−1 , (D) 1.5 × 10−6 mol l−1 , (E) 2.0 × 10−6 mol l−1 , and (F) 2.5 × 10−6 mol l−1 BH4 . Electrolyte: 0.20 mol l−1 phosphate solution (pH = 5.1). Scan rate: 0.1 V s−1 .8 [Reprinted from Zhang et al.8 , with permission from Vieweg Verlag.]
also produced similar increases in DPV signal. Zhang et al. have reported the use of CV and DPV techniques for characterization of electrochemical behaviors of tetrahydrobiopterin (BH4 ) (Figure 5), monoamine neurotransmitters, and their metabolites at the nanocrystalline Mn-doped lead dioxide film chemically modified electrode (CME).8 Ambrosi et al. have studied the behavior of acidic and neutral pharmaceutical active compounds (PhACs) using the pulse voltammetric technique.9 It has been found that in terms of sensitivity, linearity, and detection limits, DPV technique is well suited for ofloxacin (LOD 5.2 µM)
and clofibric acid (LOD 4.7 µM) whereas normal pulse voltammetry gave better results for diclofenac (LOD 0.8 µM) and propranolol (LOD 0.5 µM). Marques et al.10 have reported a biosensor for methamidophos pesticide detection based on inhibition studies. They have used the DPP technique to characterize the sensor and found a lower detection limit of 1 ppb and sensitivity of 2.2 × 106 mol−1 l min−1 . Table 1 shows the characteristics of some electrochemical biosensors based on various voltammetric and polarographic techniques.
Table 1. Electrochemical biosensors based on voltammetric and polarographic techniques
S. no. 1 2 3 4 5 6 7 8 9
Technique used LSV LSV and CV CV CV CV CV ASV DPP DPV
Analyte Glucose Acetylcholine Oxalate Glucose H 2 O2 Nitrite DNA Methamidophos Tetrahydrobiopterin (BH4 )
Sensitivity −1
0.0095 M A 1.1 mA µM−1 cm−2 43.2 nA M−1 cm−2 11.4 mA M−1 cm−2 24.91 µA mM−1 cm−2 17.21 mA M−1 cm−2 — 2.2 × 106 mol−1 l min−1 —
Detection limit
References
41 µM 0–0.4 µM 0.12 M 0.01 mM 0.01 mM 5.4 µM 5 pmol l−1 1 ppb 5 × 10−10 mol l−1
1 11 12 13 14 15 5 10 8
8
2.3
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Amperometry
Amperometry is a branch of electrochemistry that deals with the addition (reduction) or the removal (oxidation) of electrons from a molecule or atom. In theory, any atom, molecule, or assembly of atoms can be oxidized or reduced if sufficient energy can be provided. However, the range of energies that can be applied is limited by the experimental conditions. Molecules that can be oxidized or reduced in easily available energy ranges are said to be electroactive. The amount of energy required for a redox process is characteristic of the system under examination and is called the redox potential. Oxidation or reduction processes cause a faradaic current to flow in the electrochemical cell when a voltage is applied between the working and reference electrodes. This imposes a potential, encouraging electron-transfer reactions to occur at the working electrode resulting in a current that is directly proportional to the concentration of the electroactive analyte. The electrode reaction produces a measurable current that is a measure of the rate of the electrochemical reaction and is proportional to the concentration of the electroactive species. cO + ne− = cR (7) where n is the number of electrons (e− ) transferred between oxidant (O) and reductant (R). The increasing rate of reduction causes the cell current to increase. The net current in a system is given by the algebraic sum of cathodic and anodic currents: 0 αnF (φ − φ ) co exp − RT 0 i = n Fk 0 −cR exp − (α − 1)nF (φ − φ ) RT (8) where n is the valence of the electroactive specie, k 0 is the kinetic constant, α is the symmetric coefficient, φ is the applied voltage, φ 0 is the reference voltage and R is the universal gas constant. The overall current is limited by the fact that the concentration co is rapidly depleted by the surface reaction and the current is limited by the rate of diffusion of fresh electroactive species from the bulk solution. The value of the diffusionlimited current is obtained from Fick’s first law of
diffusion as: i = nc FDdco /dn
(9)
where nc denotes normal to the cathode surface. In the diffusion limit, the current density is not sensitive to the overpotential and gives rise to the maximum measurable value. The generalized transport equation for ionic species is expressed as ∂c + ∇. (n µE c − D∇c) = 0 ∂t
(10)
where µ is the mobility and E is the electric field vector. To compute the electric field, we need to solve the continuity equation for the current. ∇. j = 0
(11)
Here the flux (j ) can be described by generalized Ohm’s law. The sensitivity of the system depends on the electrode area and the geometry of the electrodes. For example, the change in the edge length of the electrode while keeping the same area can increase the sensitivity by as much as 12%. Besides this, increasing the electrode area also increases the peak current. However, the size and shape of the electrode may be limited by the manufacturing process and the overall system dimension. A designer cannot ignore the Joule heating while developing a sensor. Baronas et al. have applied Fick’s laws for modeling a two-dimensional-in-space mathematical model of biosensors based on an array of enzyme microreactors immobilized on a single electrode.16 They have reported that the modeling system acts under amperometric conditions. Park et al. have calculated the oxygen permeability coefficient pO2 for the polymeric membrane using Fick’s laws for their application in biosensors using enzymeimmobilizable polymeric materials.17 Amperomeric measurements are usually performed by maintaining a constant potential at a Pt-, Au-, or C-based working electrode or an array of electrodes with respect to a reference electrode, which may also serve as the auxiliary electrode, if currents are low (10−9 –10−6 A). The resulting current is directly correlated to the bulk concentration of the electroactive species or its production or consumption rate within the adjacent biocatalytic layer. As biocatalytic reaction rates are often chosen to be first-order dependent on the bulk analyte
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
concentration, such steady-state currents are usually proportional to the bulk analyte concentration. In amperometry if the potential of the electrode is made more negative, the energy of the electrons in the electrode increases and eventually an electron can be transferred from the electrode to the lowest unoccupied energy level of a species in the nearby solution. It is the oxidized form of the redox couple, which gets reduced. Alternatively, by applying a sufficiently high positive potential, the reduced form can be oxidized. The movement of electrons in or out of the electrode can be measured as an oxidation or reduction current. This technique is referred to as amperometry. In this case, the generated current (i) can be expressed by: i=
−AFDnC δ
(12)
where δ is the thickness of diffusion layer. By an appropriate choice of the applied potential, it is possible to discriminate between different redox couples. Setford et al. have reported the screen-printed three-electrode amperometric biosensor for rapid and quantitative measurements of single-protein solution.18 They have used the amperometric detection of signal generated from oxidation of H2 O2 . The fabricated electrode has an LOD of 170 µg ml−1 and linearity up to 1 mg ml−1 for casilan 90 protein. These authors have made an attempt to compare the advantages of amperometric technique over photometric technique such as less sample requirement, less time consuming, low cost, rapid and simple detection procedure, and no additional reagent requirement. 2.4
Potentiometry
Potentiometry is the branch of electroanalytical chemistry in which potential is measured under the conditions of no current flow. The measured potential may then be used to determine the analytical quantity of interest, generally the concentration of some component of the analyte solution. The potential that develops in the electrochemical cell is the result of the free energy change that would occur if the chemical phenomena were to proceed until the equilibrium condition has been satisfied. Grxn = −nFE rxn
(13)
9
This concept is applicable to electrochemical cells that contain an anode and a cathode. For these electrochemical cells, the potential difference between cathode and anode is the potential of the electrochemical cell. Ecell = Ecathode − Eanode
(14)
Under standard conditions, this equation results in the standard cell potential, whereas when the reaction conditions are not standard state, the cell potential is determined using the Nernst equation. Ecell = E 0 −
RT ln(Keq ) nF
(15)
Potential is also generated in physical phenomenon that do not involve explicit redox reactions, but whose initial conditions have a nonzero free energy. An example of this would be ion concentration gradients across a semipermeable membrane. This can also be a potentiometric phenomenon, and is the basis of measurements that use ion-selective electrodes (ISEs). Emem = (constant) −
RT ln(ai ) zi F
(16)
Thus potentiometry is the measurement of a cell potential at zero current. If an interaction between a biological component and an analyte changes the amount of electrons in a cell, potentiometry can be used to quantify the difference between the original potential and the potential after the interaction. Potentiometric measurements involve the determination of the potential difference between either an indicator or a reference electrode or two reference electrodes separated by a permselective membrane, when there is no significant current flowing between them.
2.5
AC Impedance Spectroscopy
Resistance is the ability of a circuit element to resist the flow of electrical current. Ohm’s law defines resistance in terms of the ratio between voltage E and current I . R=
E I
(17)
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
While this is a well-known relationship, its use is limited to only one circuit element as an ideal resistor. An ideal resistor has several simplifying properties: 1. It follows Ohm’s law at all current and voltage levels. 2. Its resistance value is independent of frequency. 3. AC current and voltage signals are in phase with each other. The real world contains circuit elements that exhibit much more complex behavior and the simple concept of resistance no longer works. In its place impedance, which is a more general circuit parameter, is used. Like resistance, impedance is a measure of the ability of a circuit to resist the flow of electrical current. Unlike resistance, impedance is not limited by the simplifying properties listed above. The resistance is given by Ohm’s law: R = E/I , when a DC signal is applied to an interface where E and I are the applied voltage and the resulting current, respectively. When an AC signal is applied to an interface, Ohm’s law is again applicable, but the measured quantity is called the impedance Z and is given by Z = Ep /Ip , where Ep and Ip are the applied peak voltage and the measured peak current, respectively. The AC impedance technique is commonly applied for the investigations of electrode kinetics. The reaction rate is related to the charge-transfer resistance. While choosing the optimal frequency range, one should remember the following: 1. At very low frequencies, the mass transport (diffusion resistance) will dominate the impedance. 2. The electrical double-layer capacitors will short-cut the faradaic impedance at high frequencies. 3. At very high frequencies, the ohmic resistance will become dominant. For slow reaction, the useful frequencies will be located in the lower ranges, while fast reactions require higher frequencies. When the result is not priorly known, it will be useful to scan a wide frequency range for analysis. The measurement can be done under potentiostatic as well as galvanostatic conditions. The (potentiostatic)
amplitude is generally a few millivolts but in situations where media has low conductivity, it is desirable to apply higher amplitudes. For the impedance measurement, it does not matter whether the perturbation is applied as potential or current. In the impedance studies, for stationary electrochemical systems, most parameters are directly related to the DC electrode potential: double-layer capacitance, reaction rates, and so on. It may, therefore, be necessary to evaluate the electrochemical parameters such as potential (E), current (i), charge (Q), and time (t) at fixed values of potential. Most equivalent circuits are based on the constancy of each component during a scan. It is therefore desirable to eliminate time dependence or ensure the “impedance drift”. Electrochemical impedance is usually measured by applying an AC potential to an electrochemical cell and measuring the current through a cell. Normally a sinusoidal potential excitation is applied during the measurement and an AC current signal produced as a response is measured, containing the excitation frequency and its harmonics. This current signal can be analyzed as a sum of sinusoidal functions (a Fourier series). Electrochemical impedance is normally measured using a small excitation signal. This is done so that the cell’s response is pseudolinear. In a linear (or pseudolinear) system, the current response to a sinusoidal potential will be a sinusoid at the same frequency but shifted in phase (Figure 6). E
t
I
t
Phase shift Figure 6. Sinusoidal current response in a linear system.
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
The excitation signal, expressed as a function of time, has the form E(t) = E0 cos(ωt)
(18)
E(t) is the potential at time t, E0 is the amplitude of the signal, and ω is the radial frequency. ω = 2πf
I (t) = I0 cos(ωt − φ)
(20)
An expression analogous to Ohm’s law allows calculating the impedance of the system as: Z=
the accepted method of impedance measurement prior to the availability of lock-in amplifiers and frequency response analyzers. Using Euler’s relationship exp(j φ) = cos φ + j sin φ
E(t) = E0 exp(j ωt)
I
(23)
and the current response as, I (t) = I0 exp(j ωt − j φ)
(24)
The impedance is then represented as a complex number, Z=
E(t) cos(ωt) E0 cos(ωt) = = Z0 I (t) I0 cos(ωt − φ) cos(ωt − φ)
(21) The impedance is therefore expressed in terms of magnitude, Z0 , and phase shift, φ. If we plot the applied sinusoidal signal on the x axis of a graph (Figure 7) and the sinusoidal response signal I (t) on the y axis, an oval shape appears known as Lissajous figure. Analysis of Lissajous figures on an oscilloscope screen was
(22)
to express the impedance as a complex function, the potential is described as,
(19)
In a linear system, the response signal, I is shifted in phase and has different amplitude I0 :
11
E = Z0 exp(j φ) = Z0 (cos φ + j sin φ) I (25)
2.5.1 Impedance Data Presentation
The expression for Z(ω) is composed of a real and an imaginary part. Plotting the real part on the horizontal axis and the imaginary part on the vertical axis results in the “Nyquist plot”. In this plot, the vertical axis is negative and each point on the Nyquist plot is the impedance at one frequency. In Figure 8 low-frequency data are on the right side of the plot and higher frequencies are on the left. This is normally true for EIS data where impedance usually falls as frequency rises but not true for all circuits. The major drawback of Nyquist plots lies in the fact that looking at any data point on the plot, one cannot tell what frequency was used to record that point.
I + dI
−Im Z w E
|Z | w=∞
f
E + dE Figure 7. Origin of Lissajous figure.
w=0 Real Z
Figure 8. Nyquist plot with impedance vector.
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
The Nyquist plot in Figure 8 results from the electrical circuit shown in Figure 9 with Rs = 0. The semicircle is characteristic of a single “time constant”. Electrochemical impedance plots often contain several time constants. Often only a portion of one or more of their semicircles is seen.
EIS data is commonly analyzed by fitting it to an equivalent electrical circuit model. Most of the circuit elements in the model are common electrical elements such as resistors, capacitors, and inductors. To be useful, the elements in the model should have a basis in the physical electrochemistry of the system. As an example, most models contain a resistor that models the cell’s solution resistance.
240
(−Imag)i
2.5.2 Electrical Circuit Elements
300
180
120
60
0
0
60
120
180
240
300
Reali
Figure 10. The Nyquist plot for a typical Randles cell.
Cd1
2.5.3 Randles Cell
Rs
For the measurement of impedance data the Randles cell is one of the simplest and the most common cell model. It includes a solution resistance, a double-layer capacitor, and a charge-transfer or polarization resistance. In addition to being a useful model, the Randles cell model is often the starting point for more complex models. The equivalent circuit for the Randles cell is shown in Figure 9. The double-layer capacity is in parallel with the impedance due to the chargetransfer reaction. The Nyquist plot for a Randles cell is always a semicircle (Figure 10). The intercept at real axis at the high frequencies before the start of the semicircle represents the solution resistance. The real axis value at the other (low frequency) intercept is the sum of the polarization resistance and the solution resistance. The diameter of the
Rct
W
Figure 11. Equivalent circuit with mixed kinetic and chargetransfer control.
semicircle is therefore equal to the polarization resistance. Ghica et al. have used the Randles cell for the impedimetric study of glucose biosensors.19 For the cell circuit (Figure 11), where polarization is due to a combination of kinetic and diffusion processes, the Nyquist plot results in the curve shown in Figure 12. Grant et al. have used the circuit similar to one given in Figure 11 for impedimetric studies to monitor selective and reversible binding of analyte to the electrode fabricated for label-free and reversible immunosensors.20
Cd1 Rs
2.5.4 Parameters Obtained from Impedance Spectra and Their Determination Rct or Rp Figure 9. Schematic diagram of a Randles cell.
The analysis of impedance spectra reveals the information about a number of parameters such as the following:
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
For calculating solution resistance in most of the electrochemical cells precise determination of the current flow path and the geometry of the electrolyte that carries the current is required, as they do not have uniform current distribution through a definite electrolyte area.
500
(−Imag)i
400
300
200
100
0
13
0
100
200
300
400
500
Reali Figure 12. Nyquist diagram for mixed control circuit.
Electrolyte Resistance The analysis of impedance spectra can be utilized to determine the solution resistance, which is often a significant factor in the impedance of an electrochemical cell. A modern three-electrode potentiostat compensates for the solution resistance between the counter and reference electrodes. However, any solution resistance between the reference electrode and the working electrode must be considered when one models a cell. The resistance of an ionic solution, which depends on the ionic concentration, type of ions, temperature, and the geometry of the area in which current is carried, can be defined as follows: R=ρ
l A
(26)
where ρ is the solution resistivity, A is the bounded area, and l is the length carrying a uniform current. The conductivity of the solution, κ, is more commonly used in solution resistance calculations. Its relationship with solution resistance is as follows: R=
1 l l · ⇒κ= κ A RA
(27)
One can calculate κ from the specific ion conductance. The units for κ are siemens per meter (S m−1 ). The siemens is the reciprocal of the ohm, so 1 S = 1 −1 .
Double-layer Capacitance Double-layer capacitance, which exists at the interface between an electrode and its surrounding electrolyte, is another important parameter in impedance spectroscopy and depends on many variables including electrode potential, temperature, ionic concentrations, types of ions, oxide layers, electrode roughness, impurity adsorption, and so on. This double layer is developed by the ions from the solution when they move toward the electrode and stick on the electrode surface. Charges on the electrode are separated from the charges of these ions by a distance of the order of angstroms. Polarization Resistance The measurement of impedance can be carried out with application of external voltage. The externally applied potential to the electrode causes the polarization of the electrode, which can cause current to flow via electrochemical reactions that occur at an electrode surface. The kinetics of the reactions and the diffusion of reactants both toward and away from the electrode control the amount of current flow and the resistance offered by the cell during such measurement is known as the polarizing resistance. Charge-transfer Resistance Charge-transfer resistance is the polarization resistance when the reaction is carried out at equilibrium. Charge-transfer resistance is formed by a single kinetically controlled electrochemical reaction. For example when a metal substrate comes in contact with an electrolyte, the metal (Me) molecules can electrochemically dissolve into the electrolyte, according to: Me ⇔ Men+ + ne−
(28)
or more generally: Red ⇔ Ox + ne−
(29)
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
where Red and Ox refer to the reduced and oxidized species. In the forward reaction equation (28), transfer of charge occurs between the electrode and the electrolyte. This charge-transfer reaction has a certain speed depending on the kind of reaction, the temperature, the concentration of the reaction products, and the potential. The general relation between the potential and the current directly related with the amount of electrons and so the charge transfer via Faraday’s law is given as: i = i0
co e co ∗
αnF η
RT
−
cR e cR ∗
−(1−α)nF η (30)
RT
The overpotential, η, measures the degree of polarization. When the concentration in the bulk is the same as at the electrode surface, co = co ∗ and cR = cR ∗ . The equation (30) simplifies to: nF nF i = i0 eα RT η − e−(1−α) RT η (31) This equation (31) is called the Butler–Volmer equation. It is applicable when the polarization depends only on the charge-transfer kinetics. When the overpotential, η, is very small and the electrochemical system is at equilibrium, the expression for the charge-transfer resistance changes into: RT Rct = (32) nF i0 From this equation (32) the exchange current density can be calculated when Rct (charge-transfer resistance) is known. When the overpotential, η, is high and the electrochemical system is at equilibrium, the expression for the charge-transfer resistance changes into the familiar Tafel equation
η=
RT nF
ln io +
RT nF
ln I
(33)
where io is the exchange current density and η is the overvoltage, equation (33) can be used for kinetic and mechanistic investigation of the electrochemical reaction. Butler–Volmer equations have been utilized by Iyengar et al. to explain the role of impedance spectroscopy as a technique to probe overlapping
Potential (V) versus SCE
14
B
2.25 1.75 1.25 0.75
A
0.25 −0.25 −0.75 −1.25 1.25
1.75
2.25
2.75
log i (µA cm−2)
Figure 13. Tafel plots of different nickel plates in 3% NaCl solution (A) pure nickel plate (B) Ni/Pt alloy plate.11 [Reprinted from Shibli and Beenakumari11 , with permission from Wiley-VCH.]
electrochemical signals by separation in the frequency domain.21 Zebrowska et al. have used the Tafel equation for the electrochemical measurements (Figure 13) of the bilayer lipid membranes tethered to the gold surface.22 Shibli and Beenakumari have utilized the Tafel equation for the characterization of their Ni/Pt alloy modified graphite electrode fabricated for acetylcholine sensor.11 Diffusion Warburg impedance in the impedance measurement comes from the diffusion of analyte toward the electrode. This impedance depends on the frequency of the potential perturbation and has a small value at high frequencies since diffusing reactants do not have to move very far but at low frequencies, where the reactants have to diffuse further, increases the Warburg impedance. The equation for the “infinite” Warburg impedance is as follows: Z = σ (ω)−1/2 (1 − j )
(34)
On a Nyquist plot the infinite Warburg impedance appears as a diagonal line with a slope of 45◦ whereas on a Bode plot, the Warburg impedance exhibits a phase shift of 45◦ . In equation (34), σ is the Warburg coefficient defined as: RT 1 1 σ = 2 2 √ + ∗√ (35) √ cR DR n F A 2 co ∗ DO This form of the Warburg impedance is only valid if the diffusion layer has an infinite thickness.
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
ZO = σ ω
−1/2
j ω 1/2 (1 − j ) tanh δ D
1.5
−(∆Z /Z0)%
Quite often this is not the case. If the diffusion layer is bounded, the impedance at lower frequencies no longer obeys the equation above. Instead, we get the form:
15
1
0.5
(36) 0
Here δ is Nernst diffusion layer thickness and D is an average value of the diffusion coefficients of the diffusing species. This equation is known as finite Warburg impedance. Hou et al. have used the selfassembled multilayer electrode with immobilized rhodopsin and calculated the parameter obtained from impedimetric studies to characterize the fabricated electrode.23 Constant Phase Element Capacitors in impedance measurements experiments often act like a constant phase element (CPE) and the impedance of a capacitor has the form Z = A(j ω)−α (37) For a CPE, the exponent, α is less than one and mostly the “double-layer capacitor” on real cells often behaves like a CPE instead of like a capacitor. Wang et al. have reported the reagentless electrochemical impedance biosensor for glucose.24 They have used the D-glucose/galactose receptor from Escherichia coli for direct glucose detection. They have immobilized the protein on the gold electrode. By using the impedance signal they have detected the extensive ligand-induced domain motion within the protein upon glucose binding (Figure 14) and have shown the applicability of impedance spectroscopy in conjunction with periplasmic binding proteins as a general method for detecting small molecules.
3 CHEMICAL AND BIOCHEMICAL SENSORS
A chemical sensor is a device that transforms chemical information, ranging from the concentration of a specific sample component to total composition analysis, into an analytically useful and measurable signal. Chemical sensors usually contain two basic components connected in series:
0
5
10
15
20
Glucose concentration (µM)
Figure 14. Change in the magnitude of the impedance (|Z|) at 20 Hz as a function of glucose concentration, 30 min after glucose introduction.24 [Reprinted from Wang et al.24 , with permission from ECS - The Electrochemical Society.]
a chemical (molecular) recognition system (receptor) and a physicochemical transducer. Biosensors are chemical sensors in which the recognition system utilizes a biochemical mechanism. The biological recognition system translates information from the biochemical domain, usually an analyte concentration, into a chemical or physical output signal with defined sensitivity. The main purpose of the recognition system is to provide the sensor with a high degree of selectivity for an analyte to be measured. The biosensor selectivity is induced by the immobilization, in the sensitive area of the detector, of the biological component (enzyme, DNA receptor, antibody, antigen, microorganism, cell, etc.) specific to the target analyte. The molecular recognition then corresponds to the association of the biological element and its target molecule (analyte) through an association such as: enzyme–substrate, antibody–antigen, receptor–hormone, complementary DNA sequencing, and so on. These associations maximize the capacity of the biomolecules to recognize a unique substance among various substances. While all biosensors are more or less selective (nonspecific) for a particular analyte, some are, by design and construction, class specific to enzymes. For example whole-cell biosensors are used to measure biological oxygen demand. In sensing systems present in living organisms/systems, such as olfaction and taste, as well as neurotransmission pathways, the actual recognition is performed by a cell receptor. The word receptor or bioreceptor is also often used for the recognition system of a chemical biosensor. The transducer part of a sensor serves to transfer the signal from the output domain of
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
the recognition system to the electrical domain. The general significance of the word transducer provides bidirectional signal transfer (nonelectrical to electrical and vice versa); the transducer part of a sensor is also called a detector, sensor, or electrode. 3.1
Types of Transducers
3.1.1 Photometry
In photometry the light from an indicator molecule is the measured signal. For this method to work, one of the reactants or products of the biorecognition reaction has to be linked to colorimetric, fluorescent, or luminescent indicator molecules. Colorimetric method can be used for the fabrication of biosensor for alcohol determination using alcohol oxidase (AOD). The detection is based on the oxidation and reduction of dyes by generated hydrogen peroxide (H2 O2 ) in the reaction: AOD
RCH2 OH + O2 −−−→ RCHO + H2 O2
(38)
Peroxidase
H2 O2 + o-Dianisidine (reduced) −−−−→ H2 O + o-Dianisidine (oxidized)
(39)
AOD is an oligomeric flavoprotein having a flavin adenine dinucleotide (FAD) molecule as a cofactor. In the reaction of AOD, FAD first reduces to its hydrogenated form that is, FADH2 and then reoxidizes to its native form.25 Morrin et al. have reported the horseradish peroxidase (HRP)-based electrochemical biosensor. The biosensor was characterized by colorimetric technique.26 They have shown that the mass of enzyme immobilized can be determined by colorimetric technique and can be found to be equivalent to the formation of protein monolayer.
A measurement of H , the enthalpy of reaction at different temperatures allows one to calculate S (entropy) and G (Gibbs free energy) for a reaction and therefore collection of basic thermodynamic data forms the basis for a thermometric sensor. Ramanathan and Danielsson have reviewed the principles and applications of thermal biosensors.27 It has been shown that the thermometric method can be used for multianalyte determination, hybrid sensor, and environmental monitoring (e.g., heavy metal and pesticide detection). This technique can be applied for monitoring reactions in nonaqueous medium.
3.1.3 Field-effect Transistors (FET)
As advances are made in biosensors, there is a need for miniaturization and mass production. Field-effect transistors (FET) are used extensively in semiconductor industry in memory chips and logic chips respond to change in electric field (in front of the “gate” of a FET). A FET is thus capable of detecting changes in ion concentration when the gate is exposed to a solution that contains ions. Therefore, pH and ion concentration can be measured with a FET. The advantage of the FET transducer is that it can be incorporated directly to the electronic signal processing circuitry. In fact, a pen-size FET-based pH sensor is being marketed commercially. Zhang et al. have reported the fabrication of a urea biosensor based on FET. They have used the Langmuir–Blodgett (LB) technology for this purpose. The fabricated biosensor shows the detection limit of 0.2 mM and a dynamic range of 0–20 mM.28 Rebriiev and Starodub have reported the fabrication of urea biosensor based on ion-selective field-effect transistor (ISFET) technique. The fabricated electrode shows linear response in the range of 0.05–20 mM.29
3.1.2 Thermometry 3.1.4 Optical
All chemical reactions are accompanied by the absorption (endothermic) or evolution (exothermic) of heat for example, the hydrolysis of ATP is an exothermic reaction. − + ATP− −−→ ADP− 4 + H2 O − 3 + HPO4 + H ;
H298 = −22.2 kJ(pH 7)
(40)
Owing to the number and reliability of optical methods, a vast number of optical transduction techniques can be used for biosensor development. These may employ linear optical phenomena including adsorption, fluorescence, phosphorescence, polarization, rotation, and interference or
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
Advantages of optical techniques involve the speed and reproducibility of the measurement. Optical transducers have been used for affinityand microbial-based biosensors reported for environmental and clinical applications. A variety of optical immunosensors have been configured using direct and indirect formats with and without optical labels. The main drawback of optical measurements is the high cost of the apparatus. Moreover, these instruments are generally larger and not practical for on-site measurements. Among the wide range of reported optical immunosensor applications, atrazine has been measured with SPR through an indirect format. An antibody against atrazine was measured using the SPR system after reaction with water samples. Low concentrations of atrazine (0.1 ppb) can be detected using a relatively simple protocol. Arya et al. have reported a cholesterol biosensor based on the surface plasmon technique. They have reported the detection limit of 50 mg dl−1 and linearity of 50–500 mg dl−1 as shown in Figure 15.30 3.1.5 Acoustic
In acoustic transducers a piezoelectric crystal is used as a mass sensor because of the linear relationship between the change in the mass at the crystal surface and the change in its oscillating state. The vibration of piezoelectric crystals produces an oscillating electric field in which the resonant frequency of the crystal depends on its chemical nature, size, shape, and mass. By placing the crystal in an oscillating circuit, the frequency Anglo change (millideg)
nonlinear phenomena, such as second-harmonic generation. The choice of a particular optical method depends on the nature of the application and the desired sensitivities. In practice, fiber optics can be coupled with all optical techniques, thus increasing their versatility. The optical biosensor formats may involve direct detection of the analyte of interest or indirect detection through optically labeled probes. Total internal reflection fluorescence (TIRF) has been used with planar and fiber-optic waveguides as signal transducers in a number of reported biosensors. In these transducers, light is propagated down a waveguide, which generates an electromagnetic wave (evanescent wave) at the surface of the optically denser medium of the waveguide and the adjacent less optically dense medium. The amplitude of the standing wave decreases exponentially with distance into the lower refractive index material. The fluorescence of a fluorophore (probe) excited within the evanescent field can be collected either outside the waveguide or by coupling the emission frequencies back into the waveguide. In configurations that use TIRF the biological sensing element is immobilized on the side rather than the end of the waveguide. This configuration is particularly useful for measuring binding events at a solid–liquid interface, because the washing steps typically used to separate bound and unbound analyte probes are not required. This technique has been exploited in the widely publicized fluorescence capillary filled devices and resonance mirror device. Surface plasmon resonance (SPR) has recently been used as the basis for signal transduction in biosensors. In a typical experimental setup, incident light is reflected from the internal face of a prism in which the external face has been coated with a thin metal film. At a critical angle, the intensity of the reflected light is lost to the creation of a resonant oscillation in the electrons at the surface of the metal film. Since the critical angle is dependent on the refractive index of the material present on the metal surface, this method has been used to measure the binding of antibodies to antigens immobilized at the sensor surface. This might be visualized as a multilayer configuration consisting of antibody/antigen/metal/quartz (prism surface). The light reflected from the inside surface of the prism does not pass through the sample.
17
400 300 200 100 0 0
100
200
300
400
500
600
Cholesterol concentration (mg dl−1)
Figure 15. The variation in SPR angle with change in concentration of cholesterol.30 [Reprinted from Arya et al.30 , with permission from Elsevier.]
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
can be measured as a function of the mass. When the change in mass (m) is very small compared to the total mass of the crystal, the change in vibrational frequency (f ) relates to m as follows: f =
Cf 2 m A
(41)
In equation (41), C is a constant determined by the crystal material and thickness. One of the applications of piezoelectric crystal is the quartz crystal microbalance (QCM), which is typically made of quartz and operates at frequencies between 1 and 10 MHz. These devices can operate in liquids with a frequency determination limit of 0.1 Hz; the detection limit of mass bound to the electrode surface is about 10−10 –10−11 g. These transducers have been coupled with enzymes and antibodies to detect analytes, including formaldehyde, cocaine, and parathion. Surface acoustic wave (SAW) devices based on piezoelectric effect have been reported to detect vapors which are absorbed onto chemically selective coatings. Although these transducers can operate at higher frequencies (i.e., 250 MHz) than the QCMs yielding higher sensitivities, excessive signal damping prevents them from being used in liquids. Another type of piezoelectric transducer, termed a surface transverse wave (STW), operates at over 250 MHz in liquids. As this transducer is sensitive, stable, and can operate in liquid environments, it has promise for environmental applications. One of the main advantages for acoustic techniques is the detection, in real time, of binding reactions of chemical compounds with the solid surface of the crystal. This feature (similar to SPR) allows kinetic evaluation of affinity interactions (typically between antibodies and antigens). In addition, the cost of the apparatus can be rather low. Limitations for this transduction method involve format and calibration requirements. Each crystal should be calibrated because its frequency depends on the crystal geometry and the immobilization technique used to coat the surface (generally gold-plated quartz) with the antigen or antibody. The main source of variability is the uniformity of the protein immobilized on the surface. Liu et al. have reported the SAW urease sensor system.31 They have reported the detection limit
of 0.5 µg ml−1 for urea. They also found that the result obtained using SAW technique was consistent with the result obtained by conventional colorimetric technique.
3.1.6 Potentiometric
The basic principle behind potentiometric measurements is the development of charge related to the analyte activity (a1 ) in the sample through the Nernst relation: E = E 0 ± (RT /nF )ln a1
(42)
Typically, a reference electrode (inert) and one working electrode both in contact with the sample are required. The most common potentiometric devices are pH electrodes. The potential difference between the indicator and reference electrode is proportional to the logarithm of the ion activity or gas fugacity. This is only the case when: (i) the membrane or layer selectivity is infinite or if there is a constant or low enough concentration of interfering ions and (ii) potential differences at various phase boundaries are either negligible or constant, except at the membrane–sample solution boundary. When a biocatalyst layer is placed adjacent to a potentiometric detector, one has to take into account, as for any biocatalyst sensor, the following: (i) transport of the substrate to be analyzed to the biosensor surface, (ii) analyte diffusion to the reacting layer, (iii) analyte reaction in the presence of a biocatalyst, and (iv) diffusion of the reaction product toward both the detector and the bulk solution. The response of potentiometric biocatalytic sensors is, as for amperometric biosensors, either steady state or transient, but it is never an equilibrium response. The use of ion-selective membranes can make these transducers sensitive to various ions (e.g., H+ , F− , I− , Cl− ) in addition to gases such as CO2 and NH3 , including enzyme systems that change the concentration of any of these ions or gases, can result in biosensors that can measure substrates, inhibitors, or modulators of the enzyme. The pH electrodes have been used to measure the activities of enzymes, such as penicillinase, urease, glucose oxidase (GOx), and acetylcholinesterase, which produce or consume protons
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
as a result of catalysis. This type of configuration has several drawbacks. For example, the change in pH produced by the enzyme is required for detection of activity that affects enzyme catalysis, potentially limiting the dynamic range of the assay. Further, the analyte response curve is dramatically influenced by the buffer capacity of the assay solution, which must be adjusted in the test sample to match the reference standards. The impact of these limitations has been reduced either by measuring initial rates before the pH of the medium is substantially changed or by using a pH-stat configuration which electrochemically compensates for the enzyme-catalyzed pH change. The main advantage of such devices is the wide concentration range for which ions can be detected, generally 10−6 –10−1 mol l−1 . Their continuous measurement capability is also an interesting possibility for environmental applications. The apparatus is inexpensive, portable, and well-suited for in situ measurements. The main disadvantage is that the LOD in some kinds of environmental samples can be rather high (10−5 mol l−1 or 1 ppm) and the selectivity can be rather poor. Most potentiometric biosensors for detection of environmental pollutants use enzymes that catalyze the consumption or production of protons. Phosphoric and carbamic pesticides can be evaluated through the use of a pH electrode that measures the activity of acetylcholinesterase. The activity of the enzyme is affected by the presence of pesticides, and owing to enzymatic amplification, concentrations of these compounds as low as 10−9 M can be measured. In another application, heavy metals have been measured using the enzyme urease coupled to an ammonium ion sensor. Because the activity of urease is sensitive to heavy metal ions, inhibition of enzyme activity can be used to estimate the total concentration of these ions. Basu et al. have reported the fabrication of a potentiometric sensor for the detection and estimation of tributyrin and urea.32 They have used the measurement of change of pH by production of butyric acid and ammonia, respectively, in reactions: C15 H26 O6 3H2 O + (Tributyrin) (Water) +
3C4 H8 O2 (Butyric acid)
Lipase −− −− −− − −
C3 H8 O3 (Glycerol) (43)
3H2 O CO(NH2 )2 + (Water) (Urea) +
19 Urease −−− − −− − −
2NH3 (aq.) (Aqueous ammonia)
H2 CO3 + H2 O (Carbonic acid)
(44)
The fabricated biosensor shows the range of bioanalyte detection from 5 to 15 mM for tributyrin and from 15 to 60 mM for urea and the sensitivity of 55 mV/pH. 3.1.7 Amperometric
Amperometric biosensors typically rely on an enzyme system that catalytically converts electrochemically nonactive analytes into products that can be oxidized or reduced at a working electrode. This electrode is maintained at a specific potential with respect to a reference electrode. The current produced is linearly proportional to the concentration of the electroactive product, which in turn is proportional to the nonelectroactive enzyme substrate. Enzymes typically used in amperometric biosensors are oxidases that catalyze the following class of reactions: Substrate + O2 −−−→ Product + H2 O2
(45)
As a result of the enzyme-catalyzed reaction, the substrate concentration can be determined by amperometric detection of O2 or H2 O2 . An example of this configuration would be an oxygenconsuming enzyme coupled to a Clark electrode. The ambient oxygen concentration is then continuously monitored as it diffuses through a semipermeable membrane and is reduced at a platinum (Pt) electrode. Other common configurations include the use of oxidases specific to various substrates to produce H2 O2 , which is then oxidized at the electrode surface. Although these devices are the most commonly reported class of biosensors, they tend to have a small dynamic range due to saturation kinetics of the enzyme, and a large overpotential is required for oxidation of the analyte; this may lead to oxidation of interfering compounds as well (e.g., ascorbate in the detection of hydrogen peroxide). The advantage of this class of transducers is the use of low-cost and disposable electrodes. The high degree of reproducibility that is possible for these (one-time use) electrodes eliminates the
20
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
cumbersome requirement for repeated calibration. The type of instrument used for these measurements is also very easy to obtain and can be inexpensive and compact allowing for the possibility of on-site measurements. Limitations for this transducer include potential interferences to the response if several electroactive compounds can generate false current values. These effects have been eliminated, for clinical applications, through the use of selective membranes, which carefully control the molecular weight or the charge of compounds that have access to the electrode. Acetylcholinesterase can be coupled to an amperometric sensor used to detect hydrogen peroxide as described in the following reaction: Acetylcholinesterase
Acetylcholine + O2 + H2 O −−−−−−−−−→ Choline + Acetate
(46) Choline oxidase
Choline + 2O2 + H2 O −−−−−−→ Betaine + H2 O2 (47) Consequently, an amperometric biosensor for hydrogen peroxide can be used to measure organophosphate pesticides. In addition to the application in enzyme-based biosensors, amperometric transducers have been used to measure enzymelabeled tracers for immunosensors. Enzymes that are commonly used include HRP and alkaline phosphatase (AP). Compounds of environmental interest, measured using disposable amperometric electrodes include polychlorinated biphenyls (PCBs), triazines, and various toxins. Rahman et al.33 have fabricated an amperometric biosensor for the detection of phosphate ions using pyruvate oxidase whose reaction with pyruvate is phosphate dependent, that is, Pyruvate oxidase (PYO)
Pyruate + Phosphate + O2 −−−−−−−−−−→ Acetylphosphate + H2 O2 + CO2
(48)
Using equation (48) the concentration of the phosphate ions in human serum samples can be estimated and the measurements can be recorded in the form of oxidation current produced from H2 O2 according to equation (49) H2 O2 −−−→ 2H+ + 2e− + O2
(49)
In the determination of phosphate ions they have found the detection limit of 0.3 µM. 3.1.8 Conductometric
Enzyme reactions that produce or consume ionic species depend on the total ionic strength of the media and change the conductance/capacitance of a solution to a greater or lesser extent. Various planar interdigitated electrode configurations have been reported as conductometric transducers for biosensors. These have been used in combination with a variety of possible enzyme systems that can confer specificity on this type of transducer. Enzymes such as urease, which catalyze the production of ionic species, have been used in these devices. Nevertheless, because the conductance is sensitive to temperature, faradaic processes, double-layer charging, and concentration polarization, differential methods with internal controls must be used. Urease-coated electrodes in combination with a control electrode coated with an inactive protein have been used to measure the decomposition of urea to ammonium, bicarbonate, and hydroxyl ions. The advantage of the conductometric technique lies in the use of inexpensive, reproducible, and disposable sensors. The main disadvantage is that ionic species produced must significantly change the total ionic strength to obtain reliable measurement. This requirement increases the detection limit to unacceptable levels and results in potential interferences from variability in the ionic strength of the sample. Heavy metals can be determined by the use of thin-film interdigitated planar conductometric electrodes. GOx, AOD, butyril oxidase, and urease can be immobilized on transducer surfaces and have been used as bioactive elements for the detection of Ag+ , Hg+2 , and Pb2+ . In conductometric sensors electrochemical reactions are based on the surface reactions on electrodes and electrochemical detectors can therefore, in contrast to UV-absorbance detectors, be miniaturized without loss of performance. This enables concentration detection limits down to the nanomolar range to be attained in truly portable battery operated devices. Transduction of binding events at an electrode surface, which results in electrochemical signals, has been the
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
subject of several research efforts. The desired components of such electrochemical transduction systems are affinity for the target analyte, electrochemical activity that is sensitive to changes in the microenvironment, and specificity, that is, inhibition of nonspecific binding. It is important to note that the role of ions as transducers of information messengers has gained widespread acceptance. Since current effects are believed to be regulated initially by ionic control mechanisms, the incorporation of these approaches can be useful for the development of mechanistic models of the action of these currents on cells. The evaluation of the electric and magnetic fields near a cell membrane, due to an external source (electrodes, or capacitive coupling, or magnetic induction, or antenna radiators, or mechanical transduction), is possible. The next step is to consider their effects on the cell processes. The real-time response of living cell membranes to small electromagnetic signals has been quantified using impedance techniques in the frequency domain, linking the theory to the experimental characterization. This has been carried out by first using an electrochemical kinetic approach. It is necessary to recall that the plasma membrane (and other organelle surfaces) exhibits electrical charge separation giving it capacitor-like properties. In addition, this capacitor is “leaky” since transmembrane ion transport occurs, while other ions can be adsorbed at specific membrane sites. Electrochemical detection under hydrodynamically controlled conditions has certain advantages over batch electroanalytical techniques such as 1. The shear forces of the flowing liquid continuously clean the surface of the indicator or working electrode, hence the intense washing at each step becomes less important. 2. High-precision direct measurement can be made as the continuously streaming carrier solution removes reaction products (voltammetric electrodes) and impurities leached from the electrode (potentiometric electrodes), and conditions the working or indicator electrode. Also, the carrier solution flowing through potentiometric detection cells often contains the primary ion at low concentrations resulting in well-defined and stable potential.
21
3. The convective transport of an analyte and/or a reactant helps in reducing response time and in improving the detection limit. 4. Under flow analytical conditions with potentiometric detectors the differences in the response rate for the primary and interfering ions improve the selectivity. 5. Flow analytical conditions give the flexibility to locate the reference electrode downstream with respect to the working or indicator electrode. 6. The use of microelectrodes and microelectrode arrays with the flow measurements brings additional advantages, such as: (a) ability to operate in solutions with very low conductivity; (b) suppressed signal dependence on the liquid flow rate due to high mass transport rate generated by efficient spherical or semispherical, nonlinear diffusion; (c) fast establishment of a steady-state signal which permits the use of rapid-scan voltammetric techniques in combination with flow analytical techniques and generates threedimensional recordings (time/potential/ intensity); and (d) continuous replenishment of the diffusion layer with analytes during the passage of the solution over a microelectrode array which results in an increase in detectability Considering the above-listed properties of electrochemical detectors, one may arrive at the following conclusions: 1. Electrochemical detectors are typical selective detectors whose application range is limited compared to the most common absorption spectrophotometric detectors. However, when the application is judiciously selected, they offer analytical parameters superior to other detection systems including mass spectrometry. The low- and high-frequency conductometric detectors are not selective, but their advantages appear selectively in ion chromatography and capillary electrophoresis, where their analytical parameters for determination of primarily inorganic ions are superior to those of the common spectrophotometric detectors. 2. Electrochemical detectors are simple in design and use and easy to miniaturize.
22
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
3. When properly used, voltammetric detectors provide enhanced measuring sensitivity and LOD values up to 3 orders of magnitude smaller compared to UV–visible spectrophotometric detectors. Noticeably, appreciable precision is maintained even for the lowest analyte concentrations. The advantage of truly coulometric detectors, that is, those featuring 100% electrochemical conversion of the analyte, is that they are absolute detectors. 4. The selectivity of electrochemical detectors is their prominent advantage. The selectivity of electrochemical detectors can be modified or controlled through physico-(bio) chemical modification of the electrode surface. The sensor’s selectivity can be tailored for a particular purpose. Advantageously, voltammetric detectors are sometimes substantially less sensitive to matrices of biological samples than spectroscopic detectors. This favorable feature often simplifies the required sample pretreatment. 5. In some cases, voltammetric and especially potentiometric detectors may suffer from sluggish response compared to spectroscopic detectors. However, this problem is less important when microelectrodes are utilized in electrochemical detectors. 6. Voltammetric detectors offer many possibilities for multianalyte detection using microelectrode arrays and in combination with other detection approaches (e.g., spectroelectrochemistry or simultaneous electrochemistry and piezoelectric microgravimetry with the use of an electrochemical QCM, etc.).
4 ELECTROCHEMICAL BIOSENSOR
An electrochemical biosensor (Figure 16) is a biosensor with an electrochemical transducer. In this, biomolecule is immobilized onto the chemically modified electrode (CME) of electronic conducting, semiconducting, or ionically conducting materials. Electrochemical enzyme-based biosensors are of special interest owing to their practical advantages such as operation simplicity, low expense of fabrication, high selectivity, and suitability for real-time detection.
C
B
B
A
A A
A B
A
C A
B
A A A
Sample
Signal
A/D converter
Biological Transducer component
Figure 16. Schematic of a biosensor.
A biosensor is an integrated receptor–transducer device, which is capable of providing selectivequantitative or semi-quantitative analytical information using a biological recognition element. A biosensor can be used to monitor either biological or nonbiological matrices. Chemical sensors, which incorporate a nonbiological specificity-conferring part or receptor, although used for monitoring biological processes, for example, in vivo pH or oxygen sensors, are not biosensors. Biosensors are also used for the detection and quantification of microorganisms: receptors are bacteria, yeast, or oligonucleotide probes coupled to electrochemical, piezoelectric, optical, or calorimetric transducers. Dynamic voltammetric methods such as CV, DPV, or differential pulse amperometry (DPA) are used to elucidate the chosen biosensor architecture and properties of the immobilized redox proteins. In addition, constant-potential amperometry is frequently used to obtain correlations between substrate concentration and sensor output. The simplest design of an amperometric biosensor is the direct measurement of either an enzymatically generated product or of an electron-transfer mediator naturally involved in the biocatalytic process. A typical example for this design is the basic setup of glucose sensors comprising the enzyme GOx as biorecognition element and recording either the enzymatically produced product H2 O2 or the decrease of the concentration of the cosubstrate O2 for collecting information about the glucose concentration in a sample. The corresponding glucose sensors are typical examples of so-called “first-generation biosensors”. However, since this detection principle may lead to poor reproducibility of the overall sensing process due to varying O2 concentrations in the sample
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
under investigation, the application of artificial redox mediators has been introduced in order to avoid the interference-prone oxygen dependence. Moreover, it is essential to decrease the unfavorable working electrode potential necessary for either the reduction of O2 or the oxidation of H2 O2 . Sensors realizing a design with artificial mediators at known/constant concentration are addressed as “second-generation biosensors”. In second-generation biosensors redox enzymes donate or accept electrons to or from electrochemically active redox mediators having a redox potential adjusted to that of the enzyme’s cofactor. Ideally, the mediator is otherwise inactive, that is, highly specific only for the desired electron-transfer process between the recognition element and the transducer. As a matter of fact, free-diffusing, low-molecular-weight redox mediators are prone to leak from the electrode surface thus imposing overall decreased long-term operation stability to this type of enzyme electrode. This inherent problem, however, does not prevent the successful application of such sensors in one-shot devices, an application field which is especially important for self-monitoring of blood glucose levels. The alternative approach is seen in immobilizing the redox enzyme on a suitable electrode surface in such a way, that the protein-integrated redox site can directly exchange electrons with the electrode avoiding any free-diffusing redox mediator. This sensor design has been named “third-generation biosensors”. On the basis of these considerations, present research is directed toward the development of reagentless amperometric biosensors, which are designed in such a way that all components necessary for complementary biological recognition, biocatalytic reaction, and signal transduction are securely immobilized in specifically designed sensor architecture. In addition, the main work is focused on the development of techniques for specific deposition of matrix, immobilization strategies, transducer selection and on the measurement of complex sensor architectures exclusively on the surface of electrodes. Chemical sensors as well as biosensors are self-contained, all parts being packaged together in the same unit, usually small, the biological recognition element being in direct spatial contact with the transducing element. Electrochemical transduction methods are very popular in
23
sensing biological components. The performance and utility of a sensor lies in its ability to discriminate between different substrates (selectivity), to produce signals for submillimolar up to femtomolar concentration (sensitivity), and to reproduce signals within a reasonable margin of error (accuracy). Besides, the response times are expected to be shorter. Microchip implementation of sensors enables compact size, integrated functions of sample separation and detection (lab-on-a-chip), low cost due to batch production, and potential parallel analysis. Consequently, design, fabrication, and commercialization of these systems require understanding of the fundamental physical mechanisms associated with electrokinetic transport of various analytes, fluid flow, and electrochemical reactions at the sensor surface. In this regard, numerical analysis can provide insight into the interactions between various physical processes so that the system’s performance can be improved and/or optimized. Electrochemical biosensors use electrochemical methods for transduction. They mainly depend upon the type of transducer and molecular receptor used because of the nature of their operational principle. They can be subdivided into three types: 1. Amperometric biosensor where an oxidizing (or reducing) potential is applied between cell electrodes and the cell current is measured. 2. Potentiometric sensors that involve the measurement of the potential of a cell at zero current (the potential proportional to logarithm of the concentration of the substrate being measured). 3. Conductometric biosensors that use the relationship between the conductance and the concentration of the ionic species to measure the concentration of the substrate.
4.1
Amperometric Biosensors
Amperometric sensors exploit the use of a potential applied between a reference and a working electrode, to oxidize or reduce the electroactive species resulting in change of current. This change in current forms the basis of amperometric sensors. Amperometric biosensor alter the concentration of an analyte in their vicinity; these sensors
24
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
may reach a steady state, but they never reach equilibrium. Knowledge of the rate-limiting step of their response, that is, mass transport rate versus reaction rate, is very important for understanding their operational characteristics. In amperometry typically the reaction product is H2 O2 , which can be measured by a pair of electrodes. On applying suitable voltage on one of the electrodes against a reference electrode (Ag/AgCl or calomel), the target species (H2 O2 or O2 ) is reduced or oxidized at the electrode generating electrical current. The simplest amperometric biosensors in common usage involve the Clark oxygen electrode. An amperometric biosensor consists of a platinum cathode at which oxygen is reduced and a silver (Ag)/silver chloride (AgCl) reference electrode. When a potential of −0.6 V, relative to the Ag/AgCl electrode is applied to the platinum cathode, a current proportional to the oxygen concentration is produced. Normally both electrodes are dipped in a solution of saturated potassium chloride and separated from the bulk solution by an oxygen-permeable plastic membrane (e.g., Teflon, polytetrafluoroethylene). The following reactions occur: Ag (anode) 4Ag0 + 4Cl− −−−→ 4AgCl + 4e− (50) Pt (cathode) O2 + 4H+ + 4e− −−−→ 2H2 O (51) The efficient reduction of oxygen at the surface of a cathode causes the oxygen concentration to be effectively zero at cathode surface. The rate of this electrochemical reduction therefore depends on the rate of diffusion of the oxygen from the bulk solution, which is dependent on the concentration gradient and hence the bulk oxygen concentration. It is clear that a small, but significant, proportion of the oxygen present in the bulk is consumed by this process; the oxygen electrode measures the rate of a process which is far from equilibrium, whereas ISEs are used close to equilibrium conditions. This causes the oxygen electrode to be much more sensitive to changes in the temperature than potentiometric sensors. A typical application of this simple type of biosensor is the determination of glucose concentrations by the use of an immobilized GOx membrane. An alternative method for determining the rate of this reaction is to measure the production of hydrogen peroxide directly by applying a potential
of +0.68 V to the platinum electrode, relative to the Ag/AgCl electrode, and causing the reactions: Pt (anode) H2 O2 −−−→ O2 + 2H+ + 2e− (52) Ag (cathode) 2AgCl + 2e− −−−→ 2Ag0 + 2Cl− (53) The major problem with amperometric biosensors is their dependence on the dissolved oxygen concentration. This may be overcome by the use of “mediators” which transfer the electrons directly to the electrode bypassing the reduction of the oxygen cosubstrate. The ferrocenes represent a commonly used family of mediators. Ferrocene and its derivatives present poor solubility in aqueous media; consequently, the functionalization of the monomer, the grafting of the enzyme, or the modification of the electrode surface with ferrocene is required. While a variety of different biological materials (whole cells, antibodies, haptens, oligonucleotides, chemical receptors) are immobilized within or onto conducting polymers, redox enzymes are still the most widely used biomolecules and considered useful from an electrochemical point of view. They are used to catalyze the conversion of the substrate between its oxidized–reduced states, following which some species of enzymatic reactions are detected at the electrode. For oxidase enzymes, oxygen functions as the natural electron acceptor, and for dehydrogenase enzymes, a solubilized physiological nicotinamide cofactor, NAD (P)+ functions as electron acceptor or as electron donor, NAD(P)H. Peroxidases and pyrroloquinoline quinone (PQQ), which are contained in some dehydrogenase enzymes, have recently been of particular interest. PQQ has been increasingly used as an artificial electron-transfer mediator with other types of redox polymers. The sensing of glucose, a physiologically important analyte, has received more attention than any other analyte. The enzyme GOx is well known for its robustness, and this fact has been taken advantage of in fabricating amperometric glucose biosensors containing the enzyme covalently linked to conducting polymers. It has been fueled by the promise of the fabrication of true closedloop delivery systems for better and more accurate diabetes management that will allow for controlled release of insulin in direct response to the output
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
of either an implanted or noninvasive, continuous glucose biosensor. Conducting polymers have been widely used for the fabrication of glucose biosensors of varying formats.34,35 From the simplest fabrication techniques involving entrapment of an enzyme or enzymes within a conducting polymer matrix to the use of composite polymers or polymer multilayers, several amperometric glucose biosensors have been demonstrated. The incorporation of GOx as a counterion during the electrosynthesis of either polypyrrole or polyaniline has been shown to be an elegant strategy to create amperometric glucose biosensors. Polyaniline has been used as an enzyme immobilization matrix for amperometric detection of glucose using a Prussian blue–modified platinum electrode. This particular biosensor construct has been highly effective in countering the influence of common electro-oxidizable interferents. 4.1.1 Unmediated Amperometric Biosensors
These devices measure the current generated by oxidation or reduction of redox species at an electrode surface, which is maintained at an appropriate electrical potential. The current observed has a linear relationship with the concentration of the electroactive species. The electrode is usually constructed of platinum, gold, or carbon. Adjacent to the electrode biomolecule, entrapped by a membrane or directly immobilized, is placed as one of the immunoreactives involved in the competitive immunoassay. Labeled enzymes used on such electrochemical immunoassays are usually oxidoreductases such as HRP or hydrolytic enzymes like AP that yield electroactive species as a product of the enzymatic reaction. Sometimes the substrate or the product of the enzymatic reaction can be monitored amperometrically, without the need of a mediator. These sensors are called unmediated amperometric enzyme electrodes (Figure 17). The direct electron transfer between the redox-active sites of proteins and electrodes is normally prohibited as a consequence of steric insulation by the protein matrix. However, certain enzymes or redox proteins can exhibit electrical communication with electrode supports, and by that process electrically stimulated biocatalytic transformations can be driven close enough to the enzyme active site to make nonmediated electron transfer possible.
25
A number of factors must be taken into account when assessing the suitability of an enzyme substrate for use in an electrochemical detection system: the electrochemistry of the substrate, the electrochemistry of the product of the enzymatic reaction, the medium in which the measurements will be performed, and the electrochemistry of endogenous materials in the test sample. A problem often encountered in unmediated sensors is that other species present in the samples being analyzed are also electroactive at the potential applied. For example, ascorbic acid and uric acid, present in many biological samples, are oxidized at an anodic potential of 0.35 V. Direct electron communication between enzyme active sites and electrodes may also be facilitated by the nanoscale morphology of the electrode, that is, by modification of electrodes with metal nanoparticles. Schuhmann has described the preparation of biosensors whereby GOx is covalently bound to the outer surface of functionalized polypyrrole for the detection of glucose in flow injection manifolds.36 These amperometric sensors show high sensitivity and are effective in screening out electro-oxidizable interferents from solutions containing the analyte along with interfering compounds. Sharma et al. have fabricated an amperometric lactose biosensor by immobilization of lactase and galactose oxidase (GaO) in LB films of poly(3-hexylthiophene) (P3HT)/stearic acid (SA) for estimation of lactose in milk and its products. The fabricated electrode shows linearity 1–6 g dl−1 of lactose and has a shelf life of more than 120 days. 37 Singh et al. have fabricated a cholesterol biosensor by covalent immobilization of cholesterol esterase (ChEt) and cholesterol oxidase (ChOx) on electrochemically prepared polyaniline (PANI) films.38 The bioelectrode has been characterized using UV–visible, Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). Electrochemical behavior of these films has been studied using CV and amperometric techniques, respectively. The PANI/ChEt/ChOx enzyme films show a broad oxidation peak from 0.2 to 0.5 V. These PANI/ChEt/ChOx biosensing electrodes have a response time of about 40 s and linearity from 50 to 500 mg dl−1 of cholesterol oleate concentration. These PANI/ChEt/ChOx films are thermally stable up to 46 ◦ C. These authors have reported a
26
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Transduced current
Transduced current H2O
e−
O2
e−
Substrate
Substrate HRP
Enzyme Product (a)
Oxidase
H2O2
Product
(b)
Figure 17. (a) Direct electron transfer between an electrode and an enzyme molecule, (b) direct electrical “contacting” of HRP for the detection of H2 O2 produced by an oxidase enzyme in direct, nonmediated electrical contacting of enzymes.
sensitivity of 7.5×10−4 nA mg dl−1 and a lifetime of about 6 weeks. Later, these workers fabricated a cholesterol biosensor by coimmobilization of cholesterol oxidase, cholesterol esterase, and peroxidase onto electrochemically prepared polyaniline films. They have reported a response time of about 240 s and an apparent Km value of 75 mg dl−1 , and this electrode can be used to estimate cholesterol concentrations up to 500 mg dl−1 . These polyaniline/cholesterol oxidase/cholesterol esterase films have a detection limit of 25 mg dl−1 with sensitivity of 0.042 µA mg dl−1 . The enzyme films are found to be thermally stable up to 48 ◦ C and have a shelf life of about 6 weeks when stored at 4 ◦ C. The values of the activation energy before and after the critical temperature were reported to be 191 and 95.5 kJ mol−1 , respectively.39 To detect phenolics in aqueous solutions at concentrations in the nanomolar range, Vianello et al. reported the amperometric flow biosensor, using laccase from Rigidoporus lignosus as the bioelement.40 These bioelectrochemical electrodes have characterized the laccase kinetically toward various phenolics both in solution and immobilized to a hydrophilic matrix by carbodiimide chemistry. The electrode has been reported to be successfully used to detect phenolics in waste water from olive oil mills without sample preparation and the sensitivity is reported to be 100 nA µM−1 for some of the substrates, stability for more than 100 working days. Lourenco et al. developed an amperometric biosensor for lactose determination in raw milk through simultaneous immobilization of β-galactosidase and galactose oxidase on a derivatized polyethersulfone membrane.41 The sensitivity and the reproducibility of the biosensors
thus formed are found to be 6.81 and 0.72 nA M−1 , respectively; the biosensors are found to be stable for about 20 days. Freire et al. have described a simple and reliable method for rapid evaluation of mixtures of phenolic compounds (phenol/ chlorophenol, cathecol/phenol, cresol/chlorocresol, and phenol/cresol) using an amperometric device.42 This biosensor uses the difference between the sensitivity of lactase and tyrosinase for detection of different phenolic compounds. They have estimated individual species in the concentration range from 1.0×10−6 to 10.0 × 10−6 mol l−1 with standard deviations of 3.5 and 3.1% for phenol and chlorophenol, respectively. The values of the correlation coefficients for phenol and chlorophenol have been found to be 0.9958 and 0.9981, respectively. Gerard and Malhotra have utilized electrochemically synthesized PANI films for immobilization of GOx and lactate dehydrogenase (LDH) enzymes.43 They have investigated the anion self-exchange in PANI films. They have reported that loading of GOx gets enhanced after self-ion exchange. These researchers have also reported the determination of lactate by photometric detection of NADH formed in the reaction catalyzed by LDH immobilized in PANI films and the results show the response to pyruvate concentration up to 0.45 mM, a response time of 90 s and a shelf life of about 2 weeks. 4.1.2 Mediated Amperometric Biosensors
The electrical contacting of redox enzymes that resist direct electrical communication with electrodes can be established by using synthetic or
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
biologically active charge carriers as intermediates between the redox center and the electrode. These artificial electron donor or acceptor molecules (in the case of reductive or oxidative enzymes, respectively), usually referred to electron-transfer mediators, can be accepted by many redox enzymes in place of their natural oxidants or reductants. They have a wide range of structures, and properties, including a range of redox potentials. Usually the mediator is a lowmolecular-weight species that shuttles electrons between the redox center of an enzyme and a working electrode. These sensors are called mediated amperometric enzyme electrodes. A mediator reacts rapidly with an enzyme, exhibits reversible heterogeneous kinetics, possesses low overpotential for regeneration, and is stable at certain range of pH, temperature, redox state, and dioxygen. Most frequently used mediators are I− [Fe (CN)6 ]−4 , o-phenylenediamine, diaminobenzidine, hydroquinone, 5-aminosalicylic acid (ASA), and so on. In order to be generally applicable these mediators must possess a number of useful properties. 1. They must react rapidly with the reduced form of the enzyme. 2. They must be sufficiently soluble, in both the oxidized and reduced forms, to be able to diffuse rapidly between the active site of the enzyme and the electrode surface. This solubility should, however, not be so great as to cause significant loss of the mediator from the biosensor’s microenvironment to the bulk of the solution. However soluble, the mediator should generally be nontoxic. 3. The overpotential for the regeneration of the oxidized mediator, at the electrode, should be low and independent of the pH. 4. The reduced form of the mediator should not readily react with oxygen. 5. The redox potential of a suitable mediator should provide an appropriate potential gradient for electron transfer between an enzyme active site and an electrode. 6. The mediator should be stable in both the reduced and the oxidized forms and any side reactions between the mediator redox states and the enzyme or the environment should be eliminated.
27
7. To be effective in its role, the mediator must often compete with the enzyme’s natural substrate (e.g., molecular oxygen in the case of oxidases), effectively and efficiently diverting the flow of electrons to and from the electrode. 8. A mediator should exhibit reversible electrochemistry (a large rate constant (ket ) for the interfacial electron transfer at the electrode surface). The efficiency of the electron transport provided by mediators depends not only on the mediator properties but also on the whole system architecture. A mediator that cannot compete with the natural dioxygen electron acceptor that is functioning via a diffusional route can be very efficient when it is included in an organized supramolecular assembly and operates in a nondiffusional mode. Several approaches have been developed and many bioelectrochemical systems have been designed to enhance the electrical contacting of redox enzymes at electrode surfaces by the use of electron mediators. These methodologies range from simple application of soluble enzymes with diffusional electron mediators to systems with sophisticated biomolecular architectures composed of numerous components. Common to all these systems is the application of a multistep mediated electron transfer (MET) process, each step of which proceeds over a short distance. The development of these efficient electrical contacting methodologies has resulted in the construction of numerous amperometric biosensors and bioelectrocatalytic systems including bioreactors and biofuel cells. The contacted enzyme may also be used as part of a more complex assembly—the triggering of any electron-transfer step by an external signal (e.g., light) resulting in the control of the biocatalytic activity. MET is fast and is controlled by the substrate concentration. Hence, the mediator–enzyme assemblies provide a basis for the construction of quantitative analytical biosensors. The continuous monitoring of endogenous compounds or drugs by implantable biosensors enables close surveillance of patients via rapid return of clinical information. Such real-time measurements are highly desired in intensive care units, during surgery, and for the management of diabetes, as they offer an early warning of changes in a patient’s condition, allowing rapid corrective action to be undertaken. The analysis of blood glucose levels in diabetics is
28
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Product
Enzyme (red)
R Fe
+ R
e
Oxidizing voltage
Enzyme (ox)
Electrode
Substrate
Fe
Figure 18. Schematic of mediator facilitated enzyme reaction.
one example where such cheap and continuous monitoring is particularly desirable. MET can be affected by a diffusional mechanism where the electron relay is either an oxidized or reduced species at an electrode surface. Diffusional penetration of the oxidized or reduced relay into the protein yields sufficiently short electron-transfer distance for the electrical activation of the biocatalyst. Penetration of a mediator close to the enzyme active center inside the protein matrix is controlled by the hydrophobic/hydrophilic properties of the mediator and the enzyme, the size and shape of the mediator, and the electrostatic charge interactions between the mediator and the enzyme. Ferrocene derivatives, organic dyes, ferricyanide, Ru-complexes, and other electrochemically active substrates have been employed for diffusional MET and the electrical activation of soluble redox enzymes lacking direct electrical contact with the conductive support. CV allows the assessment of the effectiveness of a particular enzyme/mediator combination using the theory for the catalytic electrochemical processes and the determination of the second-order rate constant for the reaction between the enzyme and the mediator. Soluble redox enzymes electrically contacted by the use of diffusional electron-transfer mediators with various redox potentials provide different rate constants of electron transfer (Figure 18). Comparison of the electron-transfer efficiency provided by different mediators in the presence of the same redox enzyme allows defining important parameters for MET. Mono/multilayer Enzyme Electrodes Activated by Diffusional Mediators Diffusional mediators play an important role when the enzyme content in a monolayer is low.
However, electrical contact in the presence of a diffusional mediator does not usually result in detectable amperometric response. Thus, an increase of the enzyme content is essential to obtain the detectable current when diffusional mediators are applied. The stepwise deposition of a multilayer assembly results in the increase of the enzyme content, resulting in a significantly larger current. The deposition of variable numbers of the enzyme layers allows the “tuning” of the enzyme electrode amperometric output by the control of the number of layers. The enzyme content monolayer assemblies may also be increased by the application of rough electrode surfaces. Polymer or Inorganic Matrix-immobilized Enzymes Activated by Diffusional Mediators Redox enzymes may be electrically contacted with electrode supports by entrapment in an electropolymerized film. One of the original motivations for this approach is the possibility that direct electrical contact of an enzyme linked with a conducting polymer might be possible. Although direct oxidation has been claimed in some conductive polymers (e.g., polypyrrole), the balance of the evidence indicates that if there is any direct electrical contact, the effect is small. It is possible to enhance the electrical communication using diffusional mediators shuttling electrons between the conductive electrode support and the enzymes incorporated into the polymeric film. N methyl phenazinium, benzoquinone, hydroquinone sulfonate, and ferrocene monocarboxylic acid have all been used for this purpose. The polymer porosity is an important issue for this kind of enzyme electrical “wiring” as it provides the route for a mediator to transport the charge. The electrical
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
“wiring” of redox enzymes entrapped in inorganic (e.g., solgel) matrices can also be achieved by the application of solution-state electron relays that can penetrate through the matrix. Tian and Zhu have entrapped GOx in polypyrrole on the outer layer covering of HRP-modified solgel-derived mediated ceramic carbon electrode.44 The electron-transfer mediator, ferrocene carboxylic acid, was incorporated into the system, allowing the electrode to detect glucose at a low potential of +0.16 V. Both enzymes show favorable retention of activities in this polymer configuration. The use of a viologen mediator for covalent tethering of GOx onto polypyrrole has been demonstrated by Liu et al. The viologen, (N -(2-carboxyl-ethyl)-N -(4-vinylbenzyl)4,4 -bipyridinium dichloride, or CVV), is first graft polymerized onto polypyrrole, which then served as covalent anchor to the enzyme through the available carboxylic acid functionalities. The resulting glucose biosensor is capable of linear detection of glucose up to 20 mM, with 40% loss in enzyme activity after storage in buffer for 10 days.45 Xu et al. have constructed the novel hydrogen peroxide biosensor based on the characteristics of the carbon nanotube.46 The MWCNT was used as the coimmobilization matrix to incorporate HRP and electron-transfer mediator methylene blue (MB) onto a glassy carbon electrode surface. CV and amperometric measurements are employed to demonstrate the feasibility of MB as an electron carrier between the immobilized peroxidase and the surface of glassy carbon electrode. The amperometric response of this resulting biosensor to H2 O2 shows linear relation in the range from 4 µM to 2 mM. The detection limit is 1 µM when the signal to noise ratio is 3. The presence of dopamine and ascorbic acid does not affect the estimation of H2 O2 . This biosensor possesses good stability and reproducibility. Vidal et al. have reported an amperometric cholesterol biosensor based on self-assembled monolayers (SAMs) of propanethiol on the platinum (Pt) surface.47 The detection limit and stability for the biosensor are found to be 8 µM and 25 days, respectively. Later, these authors reported an amperometric cholesterol biosensor based on SAM of cystamine on gold. The lifetime of this cholesterol biosensor is about 45–60 days. The biosensor is found to be selective toward electroactive interferents (ascorbic acid and uric acid)
29
and has been tested in serum samples. Further, they have fabricated the amperometric biosensor for determining dichlorvos organophosphate pesticide based on the reversible inhibition of the enzyme (tyrosinase) and the chronocoulometric measurement of the charge due to the chargetransfer mediator 1,2-naphthoquinone-4-sulfonate (NQS). A detection limit of about 0.06 µM was obtained.48,49 An amperometric biosensor for hydrogen peroxide (H2 O2 ) has been developed by Wang et al. via an easy and effective enzyme immobilization method with the “sandwich” configuration: ferrocene–chitosan:HRP:chitosan–glyoxal using a glassy carbon electrode as the basic electrode.50 The biosensor surface is cross-linked with glyoxal to prevent the loss of immobilized HRP. Ferrocene is selected and immobilized on the glassy carbon electrode surface as a mediator. The biosensor has a fast response of less than 10 s to H2 O2 , with a linear range of 3.5 × 10−5 –1.1 × 10−3 M, and a detection limit of 8.0 × 10−6 M. A planar amperometric glucose microsensor based on GOx immobilized on chitosan film with Prussian blue layer has been reported by Zhu et al. The experimental results show that the optimum detection potential is 50 mV (vs Ag/AgCl) and the optimum pH is 6.5. Under the selective conditions the sensor exhibits excellent sensitivity of 98 nA M−1 and a linear range of 0.1–6.0 mM. The apparent Michaelis–Menten constant of the sensor is 21 mM. The response time is less than 60 s with a stability of about 1 month. The interference of ascorbic acid and uric acid can be avoided by the selective permeability of chitosan film and electrocatalysis of Prussian blue layer to H2 O2 . The sensor has been applied to detect glucose in human blood serum.51 A highly stable and sensitive amperometric ethanol bienzyme biosensor was developed by Smutok et al. using AOD isolated from thermotolerant methylotrophic yeast Hansenula polymorpha and HRP as biorecognition elements.52 Enzyme immobilization was performed by means of electrodeposition paints (EDP) with a first layer integrating HRP within an Os-complex-modified EDP in order to assure fast electron transfer between the enzyme and the electrode surface. On top of this layer, AOD was entrapped within an EDP layer thus assuring fast substrate diffusion within
30
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
the hydrogel layer concomitantly with stabilization of the enzyme. A variety of sensor architectures have been investigated to optimize the electrochemical communication between immobilized enzymes and the electrode surface. The immobilized enzyme activities were highly dependent on the applied potential during the electrochemically induced EDP precipitation and on the chemical composition of the used EDP. Bioanalytical properties of the optimized alcohol biosensor such as response time, dynamic range for different analytes (ethanol, methanol, n-propanol, n-butanol, formaldehyde), operational and storage stability were investigated. The developed biosensor was applied for the estimation of ethanol in wine samples. 4.2
Potentiometric Biosensors
For potentiometric sensors, a local equilibrium is established at the sensor interface, where either the electrode or membrane potential is measured, and information about the composition of a sample is obtained from the potential difference between two electrodes. In potentiometry, a glass membrane or other membrane electrode is used for measuring the membrane potential resulting from the difference in the concentrations of H+ or other positive ions across the membrane. Potentiometric biosensors usually operate at or near equilibrium and are not subject to such transport limitations. On the other hand, the magnitude of their apparent equilibrium constant and kinetics, under experimental conditions, defines the continuity of the sensor response and necessitate the reagent introduction. If these sensors operate without requiring reagent addition and are capable of rapid and reproducible regeneration, then they are referred to as multipleuse biosensors. There are three types of ISEs that are of use in biosensors: 1. Glass electrodes for cations (e.g., normal pH electrodes) in which the sensing element is a very thin hydrated glass membrane that generates a transverse electrical potential due to the concentration-dependent competition between the cations for specific binding sites. The selectivity of this membrane is determined by the composition of the glass. The sensitivity to H+ is greater than that achievable for NH4 + .
2. Glass pH electrodes coated with a gaspermeable membrane selective for CO2 , NH3 , or H2 S. The diffusion of the gas through this membrane causes a change in the pH of a sensing solution between the membrane and the electrode, which is then determined. 3. Solid-state electrodes where the glass membrane is replaced by a thin membrane of a specific ion conductor made from a mixture of silver sulfide and a silver halide. The iodide electrode is useful for the determination of I− in the peroxidase reaction and also responds to cyanide ions. Potentiometric biosensors can be fabricated using large numbers of ions (Table 2). Kormos et al. have fabricated a potentiometric glucose biosensor based on SnO2 film.53 The n-type Sb-doped SnO2 semiconductor film properties are characterized using EIS. Measurements on urine samples yield results that are in good agreement with those obtained with the Nylander method and more accurate than those obtained with a test paper. As urine samples do not need pretreatment and the stability period of the biosensor may be prolonged over 8 days by the renewal of the enzyme membrane, it may also be used in continuous flux. Yonekura et al. have studied the potentiometric responses of a Pt wire attached with DNA gel, which is a network of chemically cross-linked DNAs, to three DNA binding substrates, acridine orange, ethidium bromide, and Hoechst.54 The results show that the DNA gel electrode does not respond to ethidium bromide and acridine orange, and Hoechst can be detected selectively using a permeability parameter of the DNA gel. Yang et al. have reported a biosensor for determining Hg2+ using renewable potentiometric urease inhibition.55 For fabricating this sensor, gold nanoparticles were chemically adsorbed on the PVC–NH2 matrix membrane pH electrode surface containing N, N -didecylaminomethylbenzene (DAMAB) as a neutral carrier and urease was then immobilized on the gold nanoparticles. They have reported the linear range of 0.09–1.99 µmol l−1 for Hg2+ detection. Ercole et al. have described the application of an antibody-based biosensor for the determination of E. coli cells in vegetable food using the
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
31
Table 2. A few examples of biochemical reactions involving the release or absorption of ions that may be utilized by potentiometric biosensors
1. H+ cation D-Glucose
H2 O
Glucose oxidase
+ O2 −−−−−−→ D-Glucono-1,5-lactone + H2 O2 −−−−→D-Gluconate + H+ Penicillinase
Penicillin −−−−−→ Penicilloic acid + H+ Urease (pH 6.0)
+
(54) (55)
+
H2 NCONH2 + H2 O + 2H −−−−−−→ 2NH4 + CO2 Urease(pH9.5)
−
H2 NCONH2 + 2H2 O −−−−−−→ 2NH3 + HCO3 + H
(56) +
(57)
Lipase
Neutral lipids + H2 O −−−−→ Glycerol + Fatty acids + H+
(58)
2. NH4 + cation L-Amino
L−Aminoacidoxidase
acid + O2 + H2 O −−−−−−−−−→ Keto acid + NH4 + + H2 O2
(59)
Asparaginase
L-Asparagine
+ H2 O −−−−−→ L-Aspartate + NH4 + +
Urease (pH 7.5)
+
H2 NCONH2 + 2H2 O + H −−−−−−→ 2NH4 + HCO3
(60) −
(61)
3. I− anion Peroxidase
H2 O2 + 2H+ + 2I− −−−−→ I2 + 2H2 O
(62)
4. CN− anion Glucosidase
Amygdalin + 2H2 O −−−−→ 2Glucose + Benzaldehyde + H+ + CN−
potentiometric alternating biosensing (PAB) system based on a light-addressable potentiometric sensor (LAPS) transducing element.56 They have detected the pH variations due to NH3 production by a urease–E. coli antibody conjugate. They have shown that the PAB system is sensitive and fast, in comparison with conventional methods and have a 10–20 times shorter detection time than conventional colony-forming unit (CFU) methods. Langer et al. have reported the fabrication of polyaniline biosensor for choline determination.57 They have immobilized choline oxidase inside nanostructured polyaniline layers of a controlled porosity and micrometer or nanometer thickness. They have used both amperometric and potentiometric techniques for sensor characterization. They have reported the sensitivity of 5 µA mM−1 in amperometric detection and 10 mV mM−1 in potentiometric detection. The linear range of 0–35 mM was reported for choline determination.
4.3
Conductometric Biosensors
Conductometric sensors deal with the measurement of conductivity at a series of frequencies. Originally, in the conductometry and capacitance monitoring solutions, conductance was applied as
(63)
a method of determining reaction rates. Conductometric technique involves the measurement of changes in conductance due to the migration of ions. Many enzyme-linked reactions result in a change in total ion concentration and this would imply that they are suitable for conductometric biosensors. Capacitance measurement is used when the biorecognition reaction causes a change in the dielectric constant of the medium in the vicinity of a bioreceptor. The capacitance measurement method can be used as a transducer. Antigen–antibody reaction is a good example. Suppose antibody molecules are immobilized between two metal electrodes of known area. When an antigen is added and binds with an antibody, the dielectric constant of the medium between the two electrodes is expected to change significantly. This change translates into a change in capacitance. Conductance is directly related to the amount of ions in a cell; conductance measures the presence of ions in a biosensor system as a result of electron exchange between an interacting biological component and an analyte. The operation of conductometric biosensors is based on the ability of a catalytic action of an enzyme or the affinity of antibodies or receptor proteins to modify the electrical impedance of a suitably configured set of electrodes. There are a
32
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
variety of possible enzyme systems that can confer specificity to this type of transducer. Enzyme-based conductometric sensors rely on a change in solution conductivity when the substrate is converted to product. Urease immobilized to the electrode surface catalyzes the hydrolysis of urea, in an overall reaction leading to the formation of ammonium, bicarbonate, and hydroxide (OH− ) ions: Urease
Urea + 3H2 O −−−→ 2NH4 + + HCO3 − + OH− (64) OH− , the charged product of the above reaction, results in the increase of the solution conductivity in the vicinity of the sensor surface. Ureasetagged antibodies have been used to construct a conductometric immunosensor. Standard integrated circuit fabrication methods can be used to manufacture the electrodes, so miniaturized sensors with areas of the order of square millimeters are readily obtained. A sensor is formed by coating the electrode array with thin films responsive to the analyte of interest. To date, the calibration of conductometric sensors has been largely empirical. The relationship between the measured impedance (or a related quantity) and the analyte concentration is determined experimentally. Glutaminase enzyme can be used to fabricate a conductometric biosensor using the detection of ammonium ions generated as: Glutaminase
Glutamine + H2 O −−−−−→ Glutaminate + NH3 (65) when water is used in the biosensor then NH3 + H2 O ←−→ NH4 + + OH−
(66)
when dilute hydrochloric acid is used in biosensor NH3 + H+ −−−→ NH4 +
(67)
Yao et al. have used conductance SAW frequency technique for fabrication of glutamine biosensor.58 They have found the linearity of 6.8 × 10−4 –6.8×10−3 M and the detection limit of 0.05 mg ml−1 . They have also investigated the interference of other amino acids and some neutral substances or salts and reported no interference of such compounds. Formaldehyde biosensors can be fabricated using formaldehyde dehydrogenase (FDH) in the presence of a cofactor NAD+ (oxidized nicotinamide adenine dinucleotide), which
catalyzes the oxidation of formaldehyde to formic acid according to reaction: CH2 O + NAD+ + H2 O −−−→ HCOO− + NADH + 2H+
(68)
The bio-reaction in equation (68) consequently increases the conductivity of the medium, which can be monitored by flow conductivity cell. Lee and Bull have used the ammonium ion– selective electrode for the fabrication of a urea biosensor. They have reported a disposable conductometric biosensor based on sol-gel immobilized urease on a screen-printed IDA electrode for the determination of urea in human urine and serum and they have described the characteristics of urea biosensor for the estimation of heavy metal ions.59 Lee et al. have constructed the urea biosensor based on tetramethoxysilane (TMOS) solgelimmobilized urease on a microfabricated IDA gold electrode.60 They have investigated the controlled performance through the water content in the acidcatalyzed hydrolysis of the solgel stock solution. The resulting biosensor shows wide dynamic range of 0.2±50 mM in 5 mM imidazole–HCl buffer at pH 7.5 and storage stability of about 3 weeks when stored in 5 mM imidazole–HCl buffer at 4 ◦ C. This biosensor can be used to determine the urea concentration in urine sample by employing the differential measurement format consisting of an active IDA conductometric sensor containing solgel-immobilized urease and a reference IDA conductometric sensor containing bovine serum albumin layer instead of the urease. Ilangovan et al. have developed a solgel-immobilized urease conductometric biosensor on a thick-film interdigitated electrode.61 This urea biosensor exhibited response to changes in urea concentration within the range of 1–15 mM. They have used the same electrode for detection of heavy metals such as cadmium, copper, and lead in liquid samples. It is shown that heavy metals ranging from 0.1 to 10 mM can be detected. They have also reported that among the three metals used, the amount of inhibition is found to be more in cadmium, followed by copper, and then lead. Vianello et al. have reported a novel technique to detect atmospheric formaldehyde (CH2 O) under continuous flow conditions by an on-line system comprising of a wet scrubber for continuous transfer of the pollutant to an aqueous solution.62 For this purpose,
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
4.4
Impedimetric Biosensors
Direct impedimetric detection of biological recognition reactions leading to biotransducers were first described by Teasdale and Wallace.64 Sargent and Sadik have investigated the mechanisms of antibody–antigen (Ab-Ag) interactions at conducting polypyrrole electrodes using impedance spectroscopy techniques.65 The theory of charge generation and transport in the heterogeneous polymeric interface has been proposed to explain the current flow during Ab-Ag binding. According to this mechanism, the current obtained at the Ab-immobilized conducting polymer electrodes occurs via the following steps: (i) diffusion of ions to the electrode, (ii) charge transfer at the porous PPy/membrane interface, (iii) migration through the polymer PPy membrane, and (iv) adsorption/desorption of the Ag at the PPy/solution interface. Step (iv) is considered to be the ratedetermining step and could be controlled through the appropriate choice of electrical potential. AbAg reactions are enhanced at positive potentials whereas the application of negative potentials disrupts their association. These findings confirmed that the Ab-Ag interaction is largely influenced by the potential applied to the conducting polymer–modified electrode surface. Thus, the combination of Ab immobilization onto conducting polymer matrices and pulsed potential interrogation waveform is demonstrated to enable direct selective molecular recognition. The use of EIS and the conducting polymer, polypyrrole, as an integrated recognition and transduction system for reagentless biosensor systems has been demonstrated by Geoffrey et al.66
The system incorporated polypyrrole primarily as the immobilizing matrix for the antibody antiluteinizing hormone (anti-LH), entrapped through potentiodynamic electropolymerization from the antibody–monomer solution. The resulting antigenic biosensor shows no apparent change in the Bode impedance parameters (|Z| or θ ) upon exposure to LH. However, following a redox cycle, a significant change emerged with regard to the peak phase angle, θ . The process of redox cycling was thought to result in realignment of the conducting polymer chains following the antibody–antigen interaction. Two charge-transfer processes are observed with these antibody-loaded polypyrrole films, which were assigned to polaronic conduction at low frequencies and electronic conduction at high frequencies. While a full mechanistic understanding of the factors responsible for impedimetric change in conducting polymer membranes at electrode surfaces is unclear at present, there is, however, substantial evidence that indicates that such transduction changes may be employed in truly reagentless biosensing.66 Riul et al. have reported the artificial taste sensor based on conducting polymers.67 They have used impedance spectroscopy for characterization. 3 2.5
−Z ″ (kΩ cm2)
they first made a microreactor containing immobilized FDH and a conductometric transducer. The system can detect atmospheric formaldehyde concentrations in the range 0.05–2 ppm with sensitivity of 20 µS/ppm. Studies show an operational stability of about 3 months, working continuously 10 h/day at room temperature. Guiducci et al. have developed and performed preliminary assessments of an integrable biosensor for the direct detection of DNA sequences through capacitance measurements.63 The device behaves consistently with their proposed electrical model and detects DNA hybridization with high specificity.
33
2 1.5 1 0.5 0 0
0.5
1
1.5
2
2.5
3
Z ′ (kΩ cm2)
Figure 19. Impedance spectra for () bare carbon film electrode, () MV/Nafion-modified electrode and MV/Nafion/ Gox-modified electrode ( ) without and (•) with addition of 5 mM glucose in sodium phosphate buffer saline pH 7.0, 0.1 M at −0.5 V.19 [Reprinted from Ghica and Brett19 , with permission from Elsevier.]
34
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Table 3. Application of electrochemical transducer to some biosensors
S. no.
Transducer
Analyte
1 2 3
Potentiometric Potentiometric Potentiometric and amperometric
BAEE Glucose Choline
4
Potentiometric
Tributyrin and urea
5 6 7 8 9 10 11 12 13 14 15 16
Potentiometric Potentiometric Potentiometric Potentiometric Amperometric Amperometric Amperometric Amperometric Amperometric Amperometric Amperometric Amperometric
17 18 19 20 21 22 23 24 25 26
Amperometric Amperometric Amperometric Amperometric Amperometric Conductometric Conductometric Conductometric Conductometric Conductometric
Urea Creatine Mercury ions Cyanides Lactose Ethanol Phenolics Lactose Cholesterol oleate Cholesterol Cholesterol Dichlorvos organophosphate H 2 O2 H 2 O2 Glucose Glucose Glucose Urea Formaldehyde Urea Urea Urea and heavy metals
27 28 29 30 31
Impedimetric Impedimetric Impedimetric Impedimetric Impedimetric
Glucose BSA Glucose Catechol ODN
Sensitivity
Detection limits −1
0.2 mV µM 50 ± 2 mV pC−1 5 µA mM−1 for amperometry and 10 mV mM−1 for potentiometry 55 mV/pH — 49.2 mV/p[creatine] — 13.4 mV pC−1 6.81 nA M−1 0.2 µA mM−1 100 nA µM−1 — 7.5 × 10−4 nA mg−1 dl−1 441 nA mM−1 cm−2 625.5 nA mM−1 0.09 µM−1 — 172.4 µA mM−1 cm−2 1.11 µA mM−1 98 nA M−1 — — 20 µS/ppm 8.2 µS mM−1 — 1 mM (in spectrophotometric technique) and 5 mM (in electrical method) 2.36 µA mM−1 — — — —
References
0.05–0.5 mM 0–50 mM 0–35 mM
69 53 57
5–15 mM for tributyrin and 15–60 mM for urea 5 × 10−5 –1 × 10−1 M 10−3 –10−5 M 0.09–1.99 µM l−1 20–300 µM 0.0043–0.031 mol dm−3 0–1.75 mM 20–30 nM 1–6 g dl− 1 50–500 mg dl−1 0.025–0.350 mM 0.07–1.25 mM 0.33–5 µM
32
4 µM–2 mM 3.5 × 10−5 –1.1 × 10−3 M 8 × 10−5 –1.3 × 10−3 M 0.1–6.0 mM 0–20 mM 0.03–2.5 mM 0.005–2 ppm 0.2–50 mM 0.05–2.5 mM For urea 1–15 mM
46 50 44 51 45 73 62 60 59 61
For heavy metals 0.1–10 mM 0.020–1.2 mM 0–75 ppm 1–30 mM 10−2 –10−10 M 0.1 µM—0.5 mM
19 20 24 74 68
70 71 55 72 41 52 40 37 38 47 48 49
BAEE: Nα-benzoyl-L-arginine ethyl ester hydrochloride; BSA: bovine serum albumin.
It is seen that the sensor can distinguish commercial beverages without complex analysis, including the discrimination of waters, tastants, and wines. Ghica and Brett have reported a methyl viologen–mediated amperometric enzyme electrode sensitive to glucose using carbon film electrode substrates.19 The electrochemistry of the GOx/methyl viologen–modified electrode was investigated by CV and by EIS (Figure 19).
Dharuman et al. have directly detected the oligodeoxynucleotide (ODN) hybridization using IDA gold (Au) ultramicroelectrodes manufactured by silicon technology using EIS.68 The immobilization of single-stranded oligodeoxynucleotides (ssODNs) is accomplished by self-assembling of thiol-modified ODNs onto an Au-electrode surface. Double-strand formation was identified by decrease of approximately 50% in impedance in
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
the low-frequency region in the presence of K3 [Fe (CN)6 ], compared to the spectrum of ssODNs. It is shown that the impedance spectroscopy at ultramicroelectrodes combined with faradaic redox reactions enhances the impedimetric detection of DNA hybridization on IDA platforms. Table 3 describes the applications of various electrochemical transducers to biosensors.
6.
7.
8.
5 CONCLUSIONS
It has been shown that electrochemical techniques play a predominant role in the design and development of biosensors. As portable, low-cost and simple-to-operate analytical devices, electrochemical biosensors have considerable advantages over conventional analytical instruments including optical, piezoelectric, and thermal biosensors. However, some of the limitations such as effects of electrochemically active interferents and weak long-term stability remain to be overcome before these interesting bioelectronic devices are commercialized.
9.
10.
11.
12.
ACKNOWLEDGMENT
Thanks are due to Dr Pratima Solanki and other members of the group for interesting discussions.
REFERENCES 1. B. Sljukic, C. E. Banks, C. Salter, A. Crossley, and R. G. Compton. Electrochemically polymerised composites of multi-walled carbon nanotubes and poly(vinylferrocene) and their use as modified electrodes: Application to glucose sensing. The Analyst, 2006, 131, 670. 2. J. Berbejillo, J. Laiz, M. F. Cerda, M. E. Martins, and E. Mendez. Topographic characterization of disposable carbon pencil modified electrodes. Portugaliae Electrochimica Acta, 2004, 22, 375. 3. K. Arora, A. Chaubey, R. Singhal, R. P. Singh, M. K. Pandey, S. B. Samanta, B. D. Malhotra, and S. Chand. Application of electrochemically prepared polypyrrolepolyvinyl sulphonate films to DNA biosensor. Biosensors and Bioelectronics, 2006, 21, 1777. 4. F. Lu, K. H. Wang, and Y. Lin. Rapid, quantitative and sensitive immunochromatographic assay based on stripping voltammetric detection of a metal ion label. The Analyst, 2005, 130, 1513. 5. M. Wang, C. Sun, L. Wang, X. Ji, Y. Bai, T. Li, and J. Li. Electrochemical detection of DNA immobilized on
13.
14.
15.
16.
17.
18.
19.
20.
35
gold colloid particles modified self-assembled monolayer electrode with silver nanoparticle label. Journal of Pharmaceutical and Biomedical Analysis, 2003, 33, 1117. Z. F. Kovacevic, M. Miksaj, N. Bercuk, and M. Jukic. Amperometric biosensor for monitoring respiration activity of saccharomyces cerevisiae in the presence of cobalt and zinc. Food Technology and Biotechnology, 2002, 40, 111. F. B. Bolger and J. P. Lowry. Brain tissue oxygen: In vivo monitoring with carbon paste electrodes. Sensors, 2005, 5, 473. W. Zhang, F. Wan, J. Gu, S. Ai, J. Ye, K. Yamamoto, and L. Jin. In vivo determination of tetrahydrobiopterin and monoamine neurotransmitters in rat brain by liquid chromatography with a nano crystalline Mn-doped lead dioxide film modified electrode. Chromatographia, 2004, 59, 677. A. Ambrosi, R. Antiochia, L. Campanella, R. Dragone, and I. Lavagnini. Electrochemical determination of pharmaceuticals in spiked water samples. Journal of Hazardous Materials, 2005, 122, 21. P. R. B. O. Marques, G. S. Nunes, T. C. R. Santos, S. Andreescu, and J. L. Marty. Comparative investigation between acetylcholinesterase obtained from commercial sources and genetically modified drosophila melanogaster application in amperometric biosensors for methamidophos pesticide detection. Biosensors and Bioelectronics, 2004, 20, 825. S. M. A. Shibli and K. S. Beenakumari. Electrodeposited nickel/platinum alloy as a biosensor for acetyl choline. Electroanalysis, 2006, 18, 465. S. Milardovic, Z. Grabaric, and B. S. Gabaric. Sensitive amperometric oxalate biosensor for food analysis. Food Technology and Biotechnology, 2000, 38, 203. D. Pan, J. Chen, S. Yao, W. Tao, and L. Nie. An amperometric glucose biosensor based on glucose oxidase immobilized in electropolymerized poly(o-aminophenol) and carbon nanotubes composite film on a gold electrode. Analytical Sciences, 2005, 21, 367. O. Ngamna, A. Morrin, S. E. Moulton, A. J. Killard, M. R. Smyth, and G. G. Wallace. An HRP based biosensor using sulphonated polyaniline. Synthetic Metals, 2005, 153, 185. S. D. Silva, S. Cosnier, M. G. Almeida, and J. J. G. Moura. An efficient poly(pyrrole-viologen)-nitrite reductase biosensor for the mediated detection of nitrite. Electrochemistry Communications, 2004, 6, 404. R. Baronas, F. Ivanauskas, and J. Kulys. Mathematical modeling of biosensors based on an array of enzyme microreactors. Sensors, 2006, 6, 453. K. Y. Park, H. J. Kim, W. Y. Kim, Y. S. Jeong, and Y. S. L. Bull. Polymer membranes containing 4-trimethylsilylmethylstyrene units. Korean Chemical Society, 2001, 22, 104. S. J. Setford, S. F. White, and J. A. Bolbot. Measurement of protein using an electrochemical bi-enzyme sensor. Biosensors and Bioelectronics, 2002, 17, 79. M. E. Ghica and C. M. A. Brett. A glucose biosensor using methyl viologen redox mediator on carbon film electrodes. Analytica Chimica Acta, 2005, 532, 145. S. Grant, F. Davis, K. A. Law, A. C. Barton, S. D. Collyer, S. P. J. Higson, and T. D. Gibson. Labelfree and reversible immunosensor based upon an ac
36
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS impedance interrogation protocol. Analytica Chimica Acta, 2005, 537, 163. S. Iyengar, E. A. H. Hall, N. G. Skinner, and J. J. Gooding. Frequency domain selection of the peroxide signal for amperometric biosensors electroanalysis. Electroanalysis, 1998, 10, 1040. A. Zebrowska, P. K. Ski, and Z. Aotowski. Electrochemical studies of blocking properties of solid supported tethered lipid membranes on gold. Bioelectrochemistry, 2002, 56, 179. Y. Hou, S. Helali, A. Zhang, N. J. Renault, C. Martelet, J. Minic, T. Gorojankina, M. A. Persuy, E. P. Augy, R. Salesse, F. Bessueille, J. Samitier, A. Errachid, V. Akimov, L. Reggiani, C. Pennetta, and E. Alfinito. Immobilization of rhodopsin on a self-assembled multilayer and its specific detection by electrochemical impedance spectroscopy. Biosensors and Bioelectronics, 2006, 21, 1393. J. Wang, K. S. Carmon, L. A. Luck, and I. I. Sunia. Electrochemical impedance biosensor for glucose detection utilizing a periplasmic E. coli receptor protein. Electrochemical and Solid State Letters, 2005, 8, H61. H. B. Yildiz and L. Toppare. Biosensing approach for alcohol determination using immobilized alcohol oxidase. Biosensors and Bioelectronics, 2006, 21, 2306. A. Morrin, A. Guzman, A. J. Killard, J. M. Pingarron, and M. R. Smyth. Characterization of horseradish peroxidase immobilization on an electrochemical biosensor by colorimetric and amperometric techniques. Biosensors and Bioelectronics, 2003, 18, 715. K. Ramanathan and B. Danielsson. Principles and applications of thermal biosensors. Biosensors and Bioelectronics, 2001, 16, 417. A. Zhang, Y. Hou, N. J. Renault, J. Wan, A. Soldatkin, and J. M. Chovelon. Mixed urease/amphiphile lb films and their application for biosensor development. Biochemistry, 2002, 56, 157. A. V. Rebriiev and N. F. Starodub. Enzymatic biosensor based on the isfet and photopolymeric membrane for the determinaion of urea. Electroanalysis, 2004, 16, 1891. S. K. Arya, P. R. Solanki, R. P. Singh, M. K. Pandey, M. Datta, and B. D. Malhotra. Application of octadecanethiol self-assembled monolayer to cholesterol biosensor based on surface plasmon resonance technique. Talanta, 2006, 69, 918. D. Liu, K. Ge, K. Chen, L. Nie, and S. Yao. Clinical analysis of urea in human blood by coupling a surface acoustic wave sensor with urease extracted from pumpkin seeds. Analytica Chimica Acta, 1995, 307, 61. I. Basu, R. V. Subramanian, A. Mathew, A. M. Kayastha, A. Chadha, and E. Bhattacharya. Solid state potentiometric sensor for the estimation of tributyrin and urea. Sensors and Actuators, B, 2005, 107, 418. Md. A. Rahman, D. S. Park, S. C. Chang, C. J. McNeil, and Y. B. Shim. The biosensor based on the pyruvate oxidase modified conducting polymer for phosphate ions determinations. Biosensors and Bioelectronics, 2006, 21, 1116. B. D. Malhotra, A. Chaubey, and S. P. Singh. Prospects of conducting polymers in biosensors. Analytica Chimica Acta, 2006, 578, 59.
35. B. D. Malhotra, R. Singhal, A. Chaubey, S. K. Sharma, and A. Kumar. Recent trends in biosensors. Current Applied Physics, 2005, 5, 92. 36. W. Schuhmann. Amperometric substrate determination in flow-injection systems with polypyrrole enzyme electrodes. Sensor and Actuators, B, 1991, 4, 41. 37. S. K. Sharma, R. Singhal, B. D. Malhotra, N. Sehgal, and A. Kumar. Lactose biosensor based on langmuirblodgett films of poly(3-hexyl thiophene). Biosensors and Bioelectronics, 2004, 20, 65. 38. S. Singh, P. R. Solanki, M. K. Pandey, and B. D. Malhotra. Covalent immobilization of cholesterol esterase and cholesterol oxidase on polyaniline films for application to cholesterol biosensor. Analytica Chimica Acta, 2006, 568, 126. 39. S. Singh, P. R. Solanki, M. K. Pandey, and B. D. Malhotra. Cholesterol biosensor based on cholesterol esterase, cholesterol oxidase and peroxidase immobilized onto conducting polyaniline films. Sensors and Actuators, B, 2006, 115, 534. 40. F. Vianello, S. Ragusa, M. T. Cambria, and A. Rigo. A high sensitivity amperometric biosensor using laccase as biorecognition element. Biosensors and Bioelectronics, 2006, 21, 2155–2160. 41. R. J. M. Louren¸co, M. L. M. Serralheiro, and M. J. F. Rebeloa. Development of a new amperometric biosensor for lactose determination. Portugaliae Electrochimica Acta, 2003, 21, 171. 42. R. S. Freire, M. M. C. Ferreira, N. Duran, and L. T. Kubota. Dual amperometric biosensor device for analysis of binary mixtures of phenols by multivariate calibration using partial least squares. Analytica Chimica Acta, 2003, 485, 263. 43. M. Gerard and B. D. Malhotra. Application of polyaniline as enzyme based biosensor. Current Applied Physics, 2005, 5, 174. 44. F. Tian and G. Zhu. Bienzymatic amperometric biosensor for glucose based on polypyrrole/ceramic carbon as electrode material. Analytica Chimica Acta, 2002, 451, 251. 45. X. Liu, K. G. Neoh, L. Cen, and E. T. Kang. Enzymatic activity of glucose oxidase covalently wired via viologen to electrically conductive polypyrrole films. Biosensors and Bioelectronics, 2004, 19, 823. 46. J. Z. Xu, J. J. Zhu, Q. Wu, Z. Hu, and H. Y. Chen. An amperometric biosensor based on the coimmobilization of horseradish peroxidase and methylene blue on a carbon nanotubes modified electrode. Electroanalysis, 2003, 15, 3. 47. J. C. Vidal, J. Espuelas, E. G. Ruiz, and J. R. Castillo. Amperometric cholesterol biosensors based on the electropolymerization of pyrrole and the electrocatalytic effect of prussian-blue layers helped with self-assembled monolayers. Talanta, 2004, 64, 655. 48. J. C. Vidal, J. Espuelas, and J. R. Castillo. Amperometric cholesterol biosensor based on in situ reconstituted cholesterol oxidase on an immobilized monolayer of flavin adenine dinucleotide cofactor. Analytical Biochemistry, 2004, 333, 88. 49. J. C. Vidal, S. Esteban, J. R. Gil, and J. R. Castillo. A comparative study of immobilization methods of a tyrosinase enzyme on electrodes and their application to
ELECTROCHEMICAL TECHNIQUES IN BIOSENSORS
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
the detection of dichlorvos organophosphorus insecticide. Talanta, 2006, 68, 791. H. S. Wang, Q. X. Pan, and G. X. Wang. A biosensor based on immobilization of horseradish peroxidase in chitosan matrix cross-linked with glyoxal for amperometric determination of hydrogen peroxide. Sensors, 2005, 5, 266. J. Zhu, Z. Zhu, Z. Lai, R. Wang, X. Guo, X. Wu, G. Zhang, Z. Zhang, Y. Wang, and Z. Chen. Planar amperometric glucose sensor based on glucose oxidase immobilized by chitosan film on prussian blue layer. Sensors, 2002, 2, 127. O. Smutok, B. Ngounou, H. Pavlishko, G. Gayda, M. Gonchar, and W. Schuhmann. A reagentless bienzyme amperometric biosensor based on alcohol oxidase/peroxidase and an Os-complex modified electrodeposition paint. Sensors and Actuators, B, 2006, 113, 590. F. Kormos, L. Sziraki, and I. Tarsiche. Potentiometric biosensor for urinary glucose level monitoring. Laboratory Robotics & Automation, 2000, 12, 291. N. Yonekura, N. Uejoh, and E. Takushi. DNA gel sensor for the detection of DNA binding substrates. Analytical Sciences, 2001, 17, 1695. Y. Yang, Z. Wang, M. Yang, M. Guo, Z. Wu, G. Shen, and R. Yu. Inhibitive determination of mercury ion using a renewable urea biosensor based on self-assembled gold nanoparticles. Sensors and Actuators, B, 2006, 114, 1. C. Ercole, M. D. Gallo, L. Mosiello, S. Baccella, and A. Lepidi. Escherichia coli detection in vegetable food by a potentiometric biosensor. Sensors and Actuators, B, 2003, 91, 163. J. J. Langer, M. Filipiak, J. Kecinska, J. Jasnowska, J. Wlodarczak, and B. Buladowski. Polyaniline biosensor for choline determination. Surface Science, 2004, 573, 14. S. Yao, D. Liu, K. Ge, K. Chen, and L. Nie. A novel glutamine biosensor system based on a conductancesurface acoustic wave frequency response. Enzyme and Microbial Technology, 1995, 17, 413. S. M. Lee and W. Y. L. Bull. Determination of heavy metal ions using conductometric biosensor based on solgel-immobilized urease. Korean Chemical Society, 2002, 23, 116. W. Y. Lee, K. S. Lee, T. H. Kim, M. C. Shin, and J. K. Park. Microfabricated conductometric urea biosensor based on sol-gel immobilized urease. Electroanalysis, 2000, 12, 78. R. Ilangovan, D. Daniel, A. Krastanov, C. Zachariah, and R. Elizabeth. Enzyme based biosensor for heavy metal ions determination. Biotechnology and Biotechnological, 2006, 20, 184. F. Vianello, R. B. Chio, S. Signorini, and A. Rigo. On-line detection of atmospheric formaldehyde by a conductometric biosensor. Biosensors and Bioelectronics, 2007, 22, 920. C. Guiducci, C. Stagni, G. Zuccheri, A. Bogliolo, L. Benini, B. Samori, and B. Ricco, A biosensor
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
74.
37
for direct detection of DNA sequences. In: Proceeding of European Solid-State Device Research Conference. 32th European Solid-State Device Research Conference, Firenze, Italy, 2002, September 24–26, p. 479. P. R. Teasdale and G. G. Wallace. Molecular recognition using conducting polymers: basis of an electrochemical sensing technology-Plenary lecture. The Analyst, 1993, 118, 329. A. Sargent and O. A. Sadik. Monitoring antibody-antigen reactions at conducting polymer-based immunosensors using impedance spectroscopy. Electrochimica Acta, 1999, 44, 4667. L. Geoffrey, P. Peter, and P. Vadgama. Electrochemical impedance spectroscopy as a platform for reagentless bioaffinity sensing. Sensors and Actuators, B, 2001, 78, 249. A. Riul Jr, R. R. Malmegrim, F. J. Fonseca, and L. H. C. Mattoso. An artificial taste sensor based on conducting polymers. Biosensors and Bioelectronics, 2003, 18, 1365. V. Dharuman, T. Grunwald, E. Nebling, J. Albers, L. Blohm, and R. Hintsche. Label-free impedance detection of oligonucleotide hybridisation on interdigitated ultramicroelectrodes using electrochemical redox probes. Biosensors and Bioelectronics, 2005, 21, 645. O. A. Biloivan, S. V. Dzyadevych, N. J. Renault, N. Zine, J. Bausells, J. Samitier, and A. Errachid. Protein detection based on microelectrodes with the PPy[3,3Co(1,2-C2B9H11)]2 solid contact and immobilized proteinases: Preliminary investigations. Materials Science and Engineering C, 2006, 26, 574. F. Kuralay, H. O. Zyoruk, and A. Yldz. Potentiometric enzyme electrode for urea determination using immobilized urease in poly(vinylferrocenium) film. Sensors and Actuators, B, 2005, 109, 19. E. Karakus, S. Pekyardimci, and E. Kilic. Potentiometric bienzymatic biosensor based on PVC membrane containing palmitic acid for determination of creatine. Process Biochemistry, 2006, 41, 1371. M. Keusgen, J. P. Kloock, D. T. Knobbe, M. Junger, I. Krest, M. Goldbach, W. Klein, and M. J. Schoning. Direct determination of cyanides by potentiometric biosensors. Sensors and Actuators, B, 2004, 103, 380. W. Y. Lee, S. R. Kim, T. H. Kim, K. S. Lee, M. C. Shin, and J. K. Park. Sol-gel-derived thick-film conductometric biosensor for urea determination in serum. Analytica Chimica Acta, 2000, 404, 195. V. Zucolotto, A. P. A. Pinto, T. Tumolo, M. L. Moraes, M. S. Baptista, A. Riul Jr, A. P. U. Araujo, and O. N. Oliveira Jr. Catechol biosensing using a nanostructured layer-by-layer film containing Cl-catechol 1,2-dioxygenase. Biosensors and Bioelectronics, 2006, 21, 1320.
23 Conductometric Enzyme Biosensors Sergei V. Dzyadevych,1,2 Valentyna N. Arkhypova,1 Alexey P. Soldatkin,1 Anna V. El’skaya,1 Claude Martelet2 and Nicole Jaffrezic-Renault2 1
Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kiev, Ukraine and 2 CEGELY, Ecole Centrale de Lyon, Ecully Cedex, France
1 INTRODUCTION
The requirements and regulations in the fields of environmental protection, control of biotechnological processes, and certification of food and water quality are becoming more and more drastic. At the same time, stricter requirements regarding human and animal health have led to a rising number of clinical and veterinary tests. This means that highly sensitive, fast, and commercial methods of analyses need to be developed. Analytical devices of the new generation—mainly biosensors—can be useful tools to compete with often tedious, complex, and expensive standard methods. A biosensor converts the modification of the physical or chemical properties of a biomatrix, which occurs as a result of biochemical interactions, into an electric or an optic signal whose amplitude depends on the concentration of defined analytes in the solution. Functionally, the device consists of two parts: a biomatrix, that is, a detecting layer of immobilized material (enzymes, antibodies, receptors, organelles, microorganisms), and a transducer (potentiometric, impedimetric, amperometric, conductometric, acoustic, optic, or colorimetric). Numerous reviews,1–3 books,4–6 as well as a lot of experimental research concerning various
types of biosensors have been published. However, only a few of them are devoted to the development of conductometric biosensors, including those used for chromatography and chemical sensors for determination of air moisture and the concentration of certain gases.7,8 This rather insignificant attention paid to conductometric biosensors in comparison with other transducers can be explained by the fact that the fundamental mechanisms of such devices have not been well studied. Yet conductometric biosensors have important advantages because they do not need the use of a reference electrode; they operate at low-amplitude alternating voltage thus preventing Faraday processes on electrodes, they are insensitive to light, and can be miniaturized and integrated easily by using a cheap thin-film standard technology. Almost all electrochemical analytical methods are based on electrode electrochemical reactions (potentiometry, voltamperometry, amperometry, and coulometry). Conductometry is a method where there are either no electrochemical reactions on the electrodes at all or they are secondary and can be neglected. Therefore in conductometric method, the most important property of an electrolytic solution is its conductivity, which varies in accordance with quite a wide range of enzymatic reactions.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
The liquids analyzed are mostly considered to have significant background conductivity which is easily modified by different factors, therefore the selectivity of this method is presumed to be low and consequently its potential use for different applications, rather doubtful.9 However, in the case of an integral microbiosensor, most of these difficulties can be overcome using a differential measuring scheme which compensates for changes in background conductivity, the influence of temperature variations, and other factors.10,11 In this chapter, the fundamentals of the conductometric measuring technique and its potential application for the control of enzymatic processes are presented. Various conductometric transducers for creating biosensors are described as well as methods of immobilization of an active material on the transducer surface, schemes, and methods of measurement. Some examples of conductometric enzyme-based biosensors are considered, and their advantages and disadvantages together with prospects for further development are discussed.
2 FUNDAMENTALS OF CONDUCTOMETRIC METHOD OF MEASUREMENT
As a rule, an alternating current (ac) is used in conductometric analysis. Therefore, it is at first necessary to describe the processes occurring in an electrolytic cell and at a metal–solution interface, under a sinusoidal ac. Then we will study the parameters influencing the solution conductivity in order to develop experimental measuring schemes.
2.1
Electrochemical Impedance of the Metal – Solution System
In order to understand the basic operating principle of conductometric transducer, the nature of surface impedance of the electrolyte–metal interface must be understood. The key research approach in this system is to interpret the physical and chemical processes like some equivalent electric circuit with electronic elements, capacitors, and resistors, which simulate the real processes in question. Let us describe the electrode process at molecular level. The state of the substrate placed at a
Generator Double electric layer + A− + A− + − C+ A− + A− Electrolysis + − C+ A− A− + + − A + Bulk electrolyte A− + Anode
C+ C+ C+
− − −
− C+ − ` C+ − C+ − Cathode
Figure 1. Ion migration in the solution volume and electrolyte conductivity.
defined distance from the interface is shown in Figure 1. Within a homogeneous phase, the interaction between separate charged or polar particles takes place, the total force affecting any particle being equal to zero. At equilibrium, cations and anions of an electrolyte, as well as molecules of water, are distributed homogeneously. Therefore, the solution is electrically neutral. In the vicinity of the phase interface, the equilibrium of the different forces affecting each particle is violated because of the difference in properties of the molecules placed at opposite sides of the interface (e.g., the molecules at the electrode surface and most of the electrolyte ions and dipole molecules at the opposite surface). This is the same for electrons and atoms of the electrode material. Therefore, just near the phase interface the total vector of the forces affecting each particle is not zero. As a result of this anisotropy, the particles placed at various distances from this surface are oriented or reoriented driven by these forces. In this alternative force field, the particles move toward the lowest energy state. This process takes place at a distance of several ion radii and can cause more or less dipole orientation of the solution molecules in the vicinity of the electrode surface. The oriented dipoles on the electrode surface can be considered as a charged plate capacitor, that is, a double electric layer occurs likewise in the capacitor. Thus, the quantitative meaning is introduced—the capacity of double electric layer Cdl ,12 usually Cdl = 10–20 µF cm−2 .
CONDUCTOMETRIC ENZYME BIOSENSORS
Some of the charged particles can pass through the double layer and cause electrochemical reactions on the electrode surface. This process, called chemical polarization, can be described by a defined resistance, called penetration resistance, Rp .13 It can be estimated from the Buttler–Wolmer equation and, at low-amplitude applied signal, can be expressed as: Rp =
RT nFi o
RT (Dω)−1/2 n2 F 2
Cdl Rsol Rp Zw (a) −XS Low w
(1)
where R is the ideal gas constant; T , the absolute temperature; F , the Faraday constant; n, the number of electrons participating in the electrode reaction; and io , the density of exchange current. In the case of concentration polarization, a sharp decrease of the discharged ion concentration in the presence of electric current is soon revealed in the layer adjacent to the electrode, because of the low speed of supplying particles from the electrolyte bulk toward the electrode surface by diffusion. This results in decreasing current and increasing electrode potential. Therefore the phase shift between periodically changed current and electrode potential is revealed, the potential change always occurring after the current change. In such a system, the concentration polarization due to the ion diffusion from the phase interface into the electrolyte bulk causes an increase in the surface impedance, particularly at low frequencies.14 This diffusion, or “Warburg” impedance Zw , depends on frequency and is described by the equation Zw =
3
(2)
where ω is the ac cyclic frequency, D is the diffusion coefficient. Therefore, the electrochemical impedance of the “metal electrode–solution” system can be simulated by the equivalent scheme as follows (Figure 2a), where Cdl is the double-layer capacity, independent of current frequency; Rp , the penetration resistance simulating chemical polarization and, like Cdl , independent of current frequency; Zw , the diffusion impedance simulating concentration polarization and depending on current frequency; and Rsol , the electrolyte resistance. The corresponding impedance curve is presented in Figure 2(b). At a frequency of measurement
High w
Rsol
Rsol + Rp
Rs
(b)
Figure 2. Classic equivalent circuit (a) and corresponding impedance curve (b) on the metal–electrolyte interface.
higher than 10 Hz, the diffusion impedance can be neglected and the total system impedance consists mainly of the solution resistance, the double-layer capacity, and the penetration resistance. If a metal electrode is placed in the solution for long enough, a nonconductive oxide layer is formed on its surface resulting in an additional capacity, which can be simulated in an equivalent scheme as a capacitance Cox (Figure 3a). This capacitance is bound in series in parallel to the double-layer capacitance and penetration resistance, as well as to the solution resistance. The impedance curve in this case is a straight line with an angle to the real axis (Figure 3b). The electrolyte resistance and interface impedance depend on the solution’s nature and composition and current frequency in different ways. That is why the physicochemical analysis can be based on the measurements of electrolyte resistance, interface impedance, or total electrochemical cell impedance, and, depending on the kind of analytical signal used for low and high frequency, conductometries are distinguished.
2.2
Electrical Conductivity of Solutions
The conductivity of liquids results from dissociation of the dissolved substance, electrolyte, into
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Cdl Cox
Rsol Rp
(a) −XS Low w
High w
Rsol
Rs
(b)
pi = −zi vi ci F grad ψ = −ci ui grad ψ
Figure 3. Equivalent circuit (a) and corresponding impedance curve (b) on the metal–electrolyte interface with additional oxide capacity.
ions and migration of the latter induced by an electrical field. In the presence of electric current, electrolytes dissociate into atoms or atom groups, which are parts of the solvent molecules, namely ions, that is, the electrolyte conductivity has an ion character.15 When the potential difference is applied to the electrode, there is an electrical field within the electrolyte, so the chaotic ion movement is influenced by the ordered, oppositely directed movement of ions (those with negative charge move toward the anode, while positively charged ones move toward the cathode) (Figure 1). Thus, the current in the electrolyte is caused by the ion movement toward the electrodes where the ions are neutralized and isolated as neutral atoms (or molecules). The ion flux, that is, number of ions passing through a unit of electrolyte cross section per unit of time (pi ) can be determined by the formula: pi = ci v − ki ci grad µi − zi vi ci F grad ψ
Thus, the first member in formula (3) corresponds to the contribution of the convectional flow of ions at a concentration of ci ; the second, the contribution of their molecular diffusion; and the third, that of ion migration induced by the supplied potential. Temperature, as a rule, is assumed to be constant (T = const, grad T = 0), so the ion’s thermal diffusion can be ignored. In reality, all three processes usually coexist, but have an initial influence on each other. In any case, some assumption can be made so that only one of them is taken into account. Thus, in case of homogeneous immobile electrolyte, the first and second members of equation (3) can be neglected, and only the ion migration caused by electric field effect be considered. Then,
(3)
where v is the speed of solution flow due to natural or forced convection; ci , the ion concentration; ki , the diffusion coefficient; zi , the charge number; vi , the speed of ion movement caused by applied field; and F , the Faraday number.
(4)
where vi is the speed of ion movement; ci , the ion concentration; and ui = zi vi F , the ion mobility, which is a constant value for the given ion in the infinitely dissolved solution. The current density, that is, the current per unit of the system cross section is an algebraic sum of products of ion fluxes and ion charges: j = F zi pi = F grad ψzi ci ui
(5)
On the other hand, according to the Ohm’s law j = S grad ψ
(6)
where S is the conductivity, that is, the value reciprocal to resistance. Hence, from (5) and (6) S = F zi ci ui
(7)
Thus, the conductivity of an electrolyte solution depends on the ion concentration and mobility. The resistance of electrolyte solution is known to be in direct proportion to the distance L between the immersed electrodes and reciprocal to their area A, therefore, S=χ
A L
where χ is the specific conductivity.
(8)
CONDUCTOMETRIC ENZYME BIOSENSORS
This leads to the following conclusions. Conductometric measurement commonly consists of determining the conductivity of the solution between two parallel electrodes; its value is a sum of conductivities contributed by all ions within the solution tested. Biospecific reactions can cause occurrence of new ions, as well as changes in ion concentration and mobility. This results in changing solution conductivity registered by a conductometric transducer.
2.3
5
between the electrodes immersed in the tested solution is determined. The bridge circuit for measuring electric resistance was first developed by Wheatstone, while Kolrausch has used it for ac (Figure 4a). This bridge circuit consists of four resistances: Rx is the resistance of the analyzed solution; Rm , the set of resistances; Cm , the set of capacities; R1 , R2 , the definite resistances (R1 = R2 ); and n, the zero indicator. According to the bridge circuit theory, the circuit has the highest sensitivity when the resistances of all four arms are equal. Since, as a rule R1 = R2 , the ac bridge circuit balance can be reached only when pure resistances and reactances taken separately are balanced. The minimum zero-indicator value can be obtained by varying active resistances and capacitances. Then the Rm value corresponds to the value Rx of the resistance between
Conductometric Measuring Schemes
It has been stated that conductometric analysis is based on the measurement of conductivity of an electrolyte solution. An active resistance
CM R1 RM n R2
RX
Generator (a)
RX
R1
Generator
Voltmeter
R3
R2
Recorder
Operational amplifier
(b)
SX
R
Generator
Voltmeter Operational amplifier
(c) Figure 4. Diagrams of conductometric devices.
Recorder
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
electrodes. The resistance of an electrolyte solution can be determined with an accuracy of 0.5–1% by means of such a bridge circuit. However, the bridge circuit for measurement supposes constant additional manipulations with a box of active resistances and capacitances that decrease its accuracy. Figure 4(b) demonstrates the modified Wheatstone bridge circuit, which enables direct registration of ac in the cell tested without any subsidiary steps. The measuring scheme shown in Figure 4(c) uses an operational multiplicator of high resistance. In this case, conductivity Sx is in direct proportion to the value of current at the operational multiplier output. This scheme has been used as a basis in the research of enzyme conductometric biosensors.16 The four-electrode scheme is also employed. In it, an ac current is applied to one electrode pair while the voltage drop is measured on the other electrode pair, which is not polarized by the current and thus serves as a probe.17 The schemes described are quite simple and mostly used in experiments. Each of them has its own advantages and drawback, therefore the choice has to be made for each specific case. 3 TRANSDUCERS FOR CONDUCTOMETRIC BIOSENSORS
The conductometric transducer is a miniature twoelectrode device to measure the conductivity of the thin electrolyte layer adjacent to the electrode surface. Most authors agree that the best design for the development of conductometric electrodes is an interdigitated structure.18–20 The physical–chemical processes in the electrochemical cell with a conductometric interdigitated transducer are mostly simulated, as have been mentioned in the preceding text, by equivalent schemes like those shown in Figures 1 and 2. The theoretical calculation of these circuits has been presented.18 For the first case (Figure 1), that is, in the absence of oxide capacitance, Rs = Rsol + Xs = −
Rp 1 + ω2 Cdl2 Rp2
ωCdl Rp2 1 + ω2 Cdl2 Rp2
(9)
In the second case (Figure 2), that is, when the oxide capacity is present, Rs = Rsol + Xs =
Rp 1 + ω2 Cdl2 Rp2
1 + ωCdl Rp2 (Cdl + Cox ) Cox (1 + ω2 Cdl2 Rp2 )
(10)
The impedance curves obtained in accordance with equations (9) and (10) are presented in Figure 5 as well as the changes in curve shape brought about by variations of different circuit parameters. As can be seen, all circuit components (except for Cdl ) influence essentially the curve shapes at low frequency while at high frequency, only change in Rsol causes the displacement of the impedance curve, that is, changes in the real impedance component conductivity. To confirm that the model of electrochemical impedance of a conductometric cell proposed and calculated by us is consistent the thin-film transducers in the measuring scheme were replaced by the equivalent circuit with electronic elements. The experimental impedance curves of the equivalent circuit corresponded with those of real transducers.18 As mentioned in the preceding text, an enzyme reaction is followed by a change in the solution’s
12 6
10 −Xs (kΩ)
6
5
8 6 4 1
2 0
3
2 6
9 Rs (kΩ)
3
4 12
15
Figure 5. Theoretically accounted impedance curves for the model of conductometric cell. Frequency varied from 100 up to 200 kHz. The circuit parameters are as follows: (1) Rp = 5 k, Rsol = 1 k, Cdl = 5 nF; (2) Rp = 10 k, Rsol = 1 k, Cdl = 50 nF; (3) Rp = 10 k, Rsol = 1 k, Cdl = 5 nF, Cox = 1000 µF; (4) Rp = 10 k, Rsol = 1 k, Cdl = 5 nF, Cox = 1000 µF; (5) Rp = 10 k, Rsol = 1 k, Cdl = 5 nF, Cox = 100 µF; (6) Rp = 10 k, Rsol = 1 k, Cdl = 5 nF, Cox = 10 µF.
CONDUCTOMETRIC ENZYME BIOSENSORS
conductivity in the vicinity of electrode, which is recorded by the conductometric transducer. This change can be simulated by the change of background conductivity, which in our experiments was realized by varying the KCl concentration in solution and its temperature.18,21,22 The change in the solution’s background conductivity has been shown to affect mainly the high-frequency part of admittance. Therefore, the transducer is more sensitive at high frequency. Besides, under these experimental conditions, the main contribution to the signal is provided by the real admittance component, conductivity, which is necessary for a conductometric biosensor. Similarly, the admittance was affected by changes in solution temperature. At frequencies higher than 10 kHz, the electrochemical impedance has been shown to be mainly determined by the volume properties of the phases in contact,18 so conductometric transducers can be used for the development of enzyme biosensors. The surface effects of electrodes and their degradation at storage can be neglected. One important aspect in the development of conductometric interdigital transducers is the proper selection of electrode material. Various materials have been tested: platinum,16,20–27 gold,16,18,23,28–30 aluminum,18,31 nickel,18,31 18,26 16,18 18 copper, titanium, chromium, Ta2 O5 ,19 silver,27 and carbon.32 In general, all these materials are suitable, especially when high-frequency ac current is used. However, the electrodes made of precious metals have better characteristics. Titanium, chromium, and aluminum electrodes have been revealed to be undesirable for operation with biological liquids since these electrodes have low sensitivity to changes in ion strength of solution and reach conductivity saturation in a short time. Concerning the dimensional characteristics of electrodes, the investigations of the authors and the data presented in Refs 21 and 23 show that transducer miniaturization does not require the number of electrode fingers increased by a corresponding decrease in their size, as was earlier thought. On the contrary, doing so resulted in lower transducer sensitivity. Miniaturization should be performed by decreasing both the electrode’s working surface and its characteristic dimensions. On the other hand, an electrode with large fingers is not an appropriate design (though the transducer sensitivity can be higher) because, in this case, the thickness of biologically active membrane plays
7
a significant role. The main parameter to determine sensor size is the correlation between the membrane thickness, the electrode’s characteristic dimensions, and their active area. Conductometric transducers are mostly manufactured by microelectronic techniques—photolithography and vacuum spraying—whose advantages are described in detail in Ref. 33. Some authors have used thick-film printing technology.27,34 Its merits are reviewed elsewhere.33 All authors, however, agree that it is much easier to produce conductometric transducers than to produce electrochemical transducers of other type.
4 CONDUCTOMETRY IN ENZYME CATALYSIS
The conductometric measuring method can be used in enzyme catalysis to determine substance concentration and enzyme activity, selectivity in this case being provided just by the enzymes, which catalyze only defined reactions. As a matter of fact, the subject under consideration is not a biosensor as such, but an application of this method in enzymology. In 1961, one of the first researches in this field was published showing how it might be possible to determine urea concentration in solutions.35 This method is based on the difference between electric conductivity of urea solution and that of a solution of ammonium carbon formed as a result of urea hydrolysis by urease. In the experiments, a bridge measuring scheme was used. The urease activity was shown to decrease in the presence of heavy metal (Ag, Hg, etc.) ions in the solution. Electrolytes such as NaCl or KCl do not influence urease activity, but if their concentration in the solution is high, it can lead to the wrong result, especially at low urea concentrations. At low electrolyte concentrations in experiments without buffer solution, during urea hydrolysis, the medium’s pH gradually changed from 7 to 9. However, this causes only an insignificant change in the urease activity while the solution conductivity during the reaction varied substantially. The urea concentration was determined within the 0.1 µM–2 mM range, at optimal pH 7. A comparison of the conductometric method with other methods of urea analysis carried out in that work has shown that the first is characterized by its
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
high accuracy, speed, and simplicity. Besides, in contrast to optical methods, the measurement accuracy of conductometry does not depend on solution color. In 1965, a paper was published on applying the conductometric method to the study of the kinetics of urea enzyme hydrolysis as well as to urease activity determination.36 A differential measuring scheme was used in their experiments. The system consisted of two pairs of platinum plates, each of them placed in its own measuring cell, one with the enzyme, another without. The difference between signals from both cells was registered, thus eliminating any error associated with variations of the parameters outside the cells (temperature, buffer concentration, etc.). The determination range of urea concentration was 1–75 mM, while that of urease activity was 0.04–2.5 activity units/ml. Comparison of the data obtained with the results of classical photometric analysis showed that the conductometric method has all the merits of the classical one and exceeds the latter in accuracy and speed. At the same time in Ref. 37, a research work was presented demonstrating that the changes in conductivity during an enzyme reaction can be considered to be a universal characteristic of the substrate chemical transformation. Even if the conductivity of the products of the reaction and that of the substrate differs a little, the change in the solution’s viscosity and the level of hydration of molecules and ions at the substrate transformation (especially in the presence of other current carriers in the solution) cause noticeable variation in the tested mixture. To prove experimentally the potential of conductometry, the authors chose reactions associated with different mechanisms of conductivity change. It was important to expose the character of conductivity change in the case of evident changes in the solution composition as well as when only solution viscosity and level of molecule hydration vary as a result of the reaction. The enzyme hydrolysis of acetylcholine and starch, on the one hand, and the enzyme depolymerization of gialuronate, on the other, were considered to be the reactions meeting these requirements. Acetylcholine hydrolysis is accompanied by the rupture of the ether-bound complex and the formation of vinegar acid dissociating in protons and CH3 COO− . The proton does not participate in the total conductivity mechanism because the
reaction takes place in a phosphate buffer, pH 7.8, while the appearance of CH3 COO− anions in the solution results in an increase of the solution’s conductivity. For starch hydrolysis, filtered human saliva was added to the starch solution to decrease the solution’s viscosity and increase the level of starch hydrolysis and so increase the solution’s conductivity. When gialuronidase was used, the conductivity increased as a result of reducing the viscosity of the solution due to the depolymerization of gialuronate molecules. The authors have demonstrated that the conductometric method is preferable to the wellknown routine methods of biochemical analysis because of its higher accuracy and lower labor consumption. Using a single device and a single method with no modification, the kinetics of three-enzyme processes with specific features were studied, while three devices based on different principles would be required for classical enzyme analysis. In the next work, the authors modified their conductometric device and used a differential mode to measure the activities of collagenase, trypsin, lactate dehydrogenase, and pseudocholinesterase.38 However, despite demonstrating the potential of the conductometric method to record enzyme processes, the character of all the works mentioned is that of a preliminary or feasibility study. At the beginning of the 1980s a detailed analysis concerning the potentials and limitation of the conductometric method of measurement was performed for the complex study of urease.39 In the first part of the work, the effect on the conductivity of the medium’s pH, urea, urease, and salt concentrations of the studied solution was investigated in the absence of any enzyme reaction. It was shown that the changes in concentrations of the solution compounds cause no substantial variations of its conductivity, which is why these changes can be neglected. The curve of conductivity–pH dependence is bell shaped with a maximum at pH 8.0 for Tris buffer and at pH 6.0 for a citrate buffer. In the second part of the work, the influence of the medium conditions mentioned on urea hydrolysis was investigated. Though pH 7.2 was shown to be optimal for urease in citrate buffer, the substantial dependence of the reaction speed on the solution’s ion strength was revealed at this value—the speed decreased with rising ion strength, while at
CONDUCTOMETRIC ENZYME BIOSENSORS
pH 6.5 it hardly changed. The Michaelis constant for urease in citrate buffer, dI 4.5, was determined to be around 2.5 mM. The linear dependence of the speed of the enzyme reaction on the urease concentration in the solution was also obtained. The successful use of the conductometric method to study the enzyme activity of urease, described in this work, can be considered as a convincing argument of its potentialities due to high sensitivity and good agreement of the kinetic parameters obtained by the conductometric method compared with the results of classical biochemical analysis. In Ref. 40, a six-channel conductometer is used to study different enzymes. The investigation allowed the authors to formulate five factors that bring about, separately or in combination with each other, a change in conductivity, thus ensuring the potential of the conductometric method to record parameters during enzyme reactions (Table 1). In some reactions several factors work simultaneously, namely factors 3 and 5, in reactions with phosphorilase, factors 1, 3–5, in those with apyrase. Factors 1 and 2 influence the conductivity in the most effective way and consequently are the most promising when using conductometry in enzymology. The decrease in size of charged particles does not cause considerable change in conductivity (phosphatase substrates). In the reactions with proton migration, some influence of the buffer type has to be taken into account as an additional factor—an anion buffer decreases conductivity while a cation one increases it due to protoning. Therefore, the choice of the type of buffer is very important. Experiments demonstrated a considerable increase in conductivity in Tris and imidasole buffers in reactions with lipase, and an insignificant change in conductivity of these Table 1. Factors resulting in conductivity changes
Number
Source of changes in conductivity
1 2
Generation of ion groups Separation of different charges
3 4
Ion migration Change in level of ion particles association Change in size of charged groups
5
Enzymes Amidases Dehydrogenases and decarboxylases Esterases Kinases Phosphatases and sulfatases
9
enzymes in phosphate buffer. The conductometric method was also shown to be promising in all the reactions causing a change in pH, which is determined as a rule by pH titration. The sensitivities of both methods are comparable, but conductometry is preferable owing to its lower cost and simplicity of use; besides, titration (unlike conductometry) can be performed only in the direction of pH change and requires more complicated manipulation at operation. In a previous report,32 peptide pyroglutamyl was studied by the conductometric method, the Michaelis constants obtained were 0.34 and 0.47 mM for derivatives of alanine and tyrosine, respectively. However, conductometric methods have some limitations. The ratio between the signal and noise level should not be lower that 2%. For this reason, the concentrations of buffer and some other ingredients, which can be added to the reaction mixture, are important. The method’s sensitivity is reduced in the presence of nonreacting ions in the solution. Buffers with low ion strength can be used, though, to measure low concentration until the signal/noise ratio is of proper value. A disadvantage of conductometry is also its low specificity—it is incapable of distinguishing between reactions that can cause an artifact. The capacity of the double layer and the electrode polarization during reaction can also be sources of the method error. All the investigations reported have become a basis for further development of conductometric biosensors.
5 IMMOBILIZATION OF BIOLOGICAL MATERIAL ON THE SURFACE OF CONDUCTOMETRIC TRANSDUCERS
The choice of the method for immobilizing a biological material on the surface of a transducer is a very important parameter for the design and optimization of a biosensor of any kind. All the principles and methods usually used for the purpose, described in detail in Ref. 33, are well adapted for conductometric transducers. In that case an enzyme was included inside the film of an albumin gel by means of glutaraldehyde.16,26–28,41–44 For example, in Ref. 16 urease was immobilized on the electrode surface by deposition of 10 µl of mixture consisting of the enzyme (100 mg ml−1 ), Bovine serum albumin (BSA) (100 mg ml−1 ), and 2.5%
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
solution of glutaraldehyde at a temperature of 20 ◦ C; the 1.5-mm-thick film of enzyme–albumin gel was formed in 9–10 min. In Refs 41–44 enzymes (glucose oxidase, urease, acetyl-, and butyrylcholinesterase) were immobilized in the glutaraldehyde saturated vapor. A drop (0.1 µl) of the mixture of enzyme (50 mg ml−1 ), BSA (50 mg ml−1 ), and 10% glycerol was deposited on the sensitive surface of the transducer placed in the glutaraldehyde saturated vapor. In Ref. 26, a procedure of covalent binding of urease with the collagen membrane is reported. The collagen film treated in methanol with 0.2 M HCl solution for 48 h at room temperature was washed 3 times in distilled water, placed into 2% aqueous solution of hydrazine monohydrate for 4 h, washed again and placed into freshly prepared mixture of 0.2 M NaNO2 and 0.2 M HCl for 5 min. The film formed was then placed into 10-ml buffer solution of 25-mg urease, and the enzyme-active membrane was thus obtained. A further method for enzyme immobilization, electrochemical polymerization in the presence of polymer, has been presented in Refs 27 and 45. The enzyme was enclosed directly in the polymer matrix carrier during polymerization. The enzyme–polypyrrole film was synthesized on the surface of gold interdigitated electrodes in potentiostatic mode. The 0.1 M phosphate buffer solutions saturated with N2 , pH 7, were prepared. For the urea sensor, the solution consisted of tetraethyammonium-tetrafluorineborate (0.1 M), pyrrole (0.1 M), and urease (4 mg ml−1 ); for the glucose sensor the solution consisted of potassium perchlorate (10 mM), pyrrole (0.1 M), and glucose oxidase (2 mg ml−1 ).45 Electrochemical polymerization is promising due to compatibility with this technology, since it allows selection and ensures appropriate membrane geometry (size, thickness, shape), to control polymerization, to design a universal technological cycle for manufacturing different microbiosensors and multisensors. In the work presented in Ref. 22, urease has been immobilized by the solgel method. A drop of the mixture (5 µl) consisting of urease (50 mg ml−1 in 5 mM imidasole–HCl buffer) mixed with the solgel solution (5-ml tetramethylortosilicate, 1ml H2 O, 50-µl HCl) in the proportion of 1 : 1, was deposited on the transducer’s sensitive surface for polymerization. The polymerization lasted 1–3 min
depending on the tetramethylorthosilicate to water ratio. Naturally, the methods of enzyme immobilization reported are only a few of those used for biosensor design. While selecting a proper method for a particular aim, the common principles have to be taken into consideration, as follows: • An enzyme has to be stable during the reaction. • It is desirable that the reagent forming crosslinking bonds should interact with the chemical groups absent in the active enzyme center, or that this reagent should be as large as possible in order not to reach the active center. • The enzyme’s active center must always be protected in some way. • The washing of unbound enzyme must not negatively affect the immobilized enzyme. • The mechanical properties of a carrier should be taken into account. The immobilization method meeting all these requirements is the appropriate one.
6 CONDUCTOMETRIC ENZYME SENSORS
The first conductometric biosensor for urea determination has been described in Ref. 16. It was a device consisting of a silicium substance with a pair of gold interdigitated and serpentine electrodes. The experiments were carried out in both a laboratory and clinics; the biosensor response to urea was in the range of 0.1–10 mM in imidasole buffer, dI 7.5. The KM of immobilized enzyme was higher than that in the solution; the authors explained it as a result of diffusion limitation. A comparison of the data obtained by the biosensor in the laboratory with the results of conventional clinical tests showed good agreement (the correlation coefficient was higher than 0.99). Similar conductometric biosensors have also been used as a multisensor.28 Urease was immobilized on the surface of the first electrode pair in the gel layer; on the second pair, L-asparaginase; on the third pair, a three-enzyme system “urease–creatinase–creatininase”. This sensor was used for the determination of urea, L-asparagine, and creatinine, respectively. The sensor was tested both separately with each of the substrates, and
CONDUCTOMETRIC ENZYME BIOSENSORS
11
Table 2. The data on development of different conductometric biosensors
Number
Substrate
Enzyme
1 2
Urea Creatinine
3 4 5 6 7
L-asparagine Glucose Hydrogen peroxide D-amino acids Organophosphorous pesticides
8
Acetylcholine
9 10 11 11 12 13 14 15 16
Butyrylcholine Heavy metal ions Penicillin Uric acid Total protein Formaldehyde 4-Chlorophenol Triazine herbicides Carbamate pesticides
Urease Urease–creatinase–creatininase Creatinine deiminase L-asparaginase Glucose oxidase Peroxidase D-amino acid oxidase Acetylcholinesterase, butyrylcholinesterase Acetylcholinesterase, butyrylcholinesterase Butyrylcholinesterase Urease Penicillinase Uricase Trypsin Alcoholoxidase Tyrosinase Tyrosinase Acetylcholinesterase
in multisubstance mode the kinetic and calibration curves were determined. In Table 2, the results of development in the field of conductometric enzyme biosensors during the last decades are presented. It is obvious that conductometric transducers have mainly been used for elaborating biosensors for urea determination. The multisensor described in Ref. 45 consisted of a conductometric biosensor for urea analysis combined with an amperometric biosensor for glucose determination. It was highly selective and simple to operate and was used in clinics. Mikkelsen et al. have characterized conductometric biosensors for urea and D-amino acid determination.26 The enzymes of urease and D-amino acid oxidase were used. The minimum detection limit for urea concentration was 5 µM; the linear dynamic range was of 3 orders. The dependence of response on buffer capacity was studied. While the sensor for D-amino acid analysis was being developed, the enzyme was co-immobilized with catalase, because hydrogen peroxide, being the product of the enzyme reaction, inhibited D-amino acid oxidase. A comparative analysis using copper and platinum electrodes, as well as different buffer solutions showed that the platinum electrodes and glycine buffer were preferable. An optimal pH of the sensor for D-amino acids and its selectivity toward various amino acids were determined.
Source 16, 22, 23, 26–28, 41–43, 45–56 28 34 28 24, 41–43, 46, 55–60 30 26 44, 55, 56, 61–66 46, 55, 56, 61, 62 46, 55, 56, 61, 62 55, 56, 62, 63, 66, 67 55, 56, 68 48 55, 56, 69 55, 56, 70 66, 71 66, 71 66
The sensor showed stable results during its 33-day operation. Two types of thick-film conductometric biosensors for urea determination are the subject of Ref. 27. The first type was manufactured by printing two interdigitated electrodes onto an Al2 O3 substance using platinum paste, while the second, consisted of four silver-palladium electrodes in parallel—by the “green tape” technology. Urease was immobilized by covalent binding in albumin gel. The response time for both biosensors was about 10 min. The dynamic ranges for the first biosensor were: 0.1–50 mM urea, the linear part of 0.1–4 mM, for the second 10 µM–5 mM urea, the linear part of 10–350 µM. These biosensors were shown to suit medical analysis. The conductometric biosensor based on inhibition analysis, first described in Ref. 44, was intended for the determination of organophosphorous pesticides. As a sensitive element, the enzymes acetyl- and butyrylcholinesterase were used. The sensor’s sensitivity to different pesticides (diisopropyl fluorophosphate, paraoxonethyl, paraoxon-methyl, trichlorfon) was investigated, the minimal detection limits for inhibitor concentrations were: 5 × 10−11 M for diisopropyl fluorophosphate, 10−8 M for paraoxon-ethyl, 5 × 10−7 M for paraoxon-methyl, and 5 × 10−7 M for trichlorfon. The dependence of biosensor response on how long the transducer was incubated in the
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
pesticide solution was studied. The possibility of enzyme reactivation in the membrane by means of the reactivator pyridine-2-aldoxime-methiodide was shown. The conclusion was drawn that the biosensors described could be used for the analysis of organophosphorous pesticides in aqueous solutions. The potential of a conductometric urease biosensor for the determination of heavy metal ions was demonstrated in Ref. 67. The sensitivities of heavy metals toward urease varied as follows: Hg2+ > Cu2+ > Cd2+ > Co2+ > Pb2+ > Sr2+ ; reactivation of the inhibited enzyme with Ethylenediaminetetraacetic acid (EDTA) was shown to be probable. Conductometric biosensors applied to analyzing total solution toxicity at parathion-methyl photodegradation were presented in Refs 64 and 65. The results obtained were compared with the data from traditional, highly sensitive method of high performance liquid chromatography (HPLC) and from the Lumistox device (Germany) for toxicity determination. The solution’s toxicity was shown to increase dramatically as pesticide photodegradation began, the toxicity remained once the parathion-methyl dissociation had completed. However, the authors do not oppose the biosensor method, but consider it as an additional, fast way for early screening of numerous samples. The comparative analysis of the operational characteristics of enzyme biosensors for penicillin determination based on conductometric planar electrodes, on the one hand, and pH-sensitive fieldeffect transistors, on the other, demonstrated47 similarity in their analytical parameters: both have short response time and high operational stability. However, planar conductometric electrodes are preferable from the technological aspect, because they are cheaper and easier to manufacture, and therefore promising for practical use. The possibility of selecting the necessary dynamic range of the transducer’s operation by varying the medium’s buffer capacity was also shown.
7 CONCLUSIONS
An application of the conductometric measurement method to continuous recording in the course of enzyme processes is thoroughly examined and analyzed regarding both standard conductometers and
conductometric enzyme biosensors. As compared with conventional methods of biochemical analysis, the method considered is universal, features higher accuracy, and lower labor costs. Conductometric biosensors also have advantages over other types of transducers. First, they can be produced through inexpensive thin-film standard technology. This, along with using an optimized method of immobilization of biological material, results in considerable decrease in both primary cost of devices and the total price of analyses. For integral microbiosensors it is easy to perform a differential measurement mode, thus compensating for external effects and considerably increasing measurement accuracy. The data is convincing evidence of the great potential of conductometric biosensors. However, it is still rather a novel trend in the field of biosensors, which is why the development of commercial devices has a promising future.
REFERENCES 1. P. N. Bartlett and R. G. Whitaker, Strategies for the development of amperometric enzyme electrodes. Biosensors, 1987/88, 3, 359–379. 2. I. Karube and K. Sode, Microbial Sensors for Process and Environmental Control , in Bioinstrumentation and Biosensors, D. L. Wise (ed), Marcel Dekker, New York, 1991, pp. 149–160. 3. S. V. Dzyadevych, A. P. Soldatkin, A. V. El’skaya, C. Martelet, and N. Jaffrezic-Renault, Enzyme biosensors based on ion-selective field-effect transistors. Analytica Chimica Acta, 2005, 568, 248–258. DOI: 10.1016/j.aca.2005.11.057. 4. E. Hall, Biosensors, Open University Press, Cambridge, 1991. 5. C. Tran Minh, Biosensors, Chapman & Hall, London, 1993. 6. E. Kress-Rogers, Handbook of Biosensors and Electronic Noses: Medicine, Food, and Environment, CRC Press, New York, 1997. 7. B. S. Hoffheins, R. J. Lauf, and M. W. Siegel, Intelligent thick-film gas sensor. Hybrid Circuits, 1987, 14, 8–12. 8. J. F. Alder, P. R. Fielden, and A. J. Clark, Simultaneous conductivity and permittivity detector with a single cell for liquid chromatography. Analytical Chemistry, 1984, 56, 985–988. 9. E. N. Dorokhova, G. V. Prokhorova, Analytical Chemistry. Physical-Chemical Methods of Analysis, Vysshaya shkola, Moscow, 1991. 10. W. Gopel, T. A. Jones, M. Kleitz, J. Lundstrom, and T. Seiyama, Conductometry, in Sensors. A Comprehensive Survey, W. Gopel, J. Hesse, and J. N. Zemel (eds), VCH Verlagsgesellschaft, Weinheim, 1991, Vol. 2, Part I, pp. 314–337.
CONDUCTOMETRIC ENZYME BIOSENSORS 11. D. B. Kell, The Principles and Potential of Electrical Admittance Spectroscopy: An Introduction, in Biosensors: Fundamentals and Applications, A. P. F. Turner, I. Karube, and G. S. Wilson (eds), Oxford University Press, Oxford, 1987, pp. 427–468. 12. K. Camman, Working with Ion-Selective Electrodes, Springer-Verlag, New York, 1979. 13. K. J. Vetter, Electrochemical Kinetics, Academic Press, New York, 1967. 14. E. T. McAdams and J. Jossinet, Electrode-electrolyte impedance and polarisation. Innovation et Technologie en Biologie et Medecine, 1991, 12, 11–200. 15. L. I. Antropov, Theoretical Electrochemistry, Mir Publisher, Moscow, 1977. 16. L. D. Watson, P. Maynard, D. C. Cullen, R. S. Sethi, J. Brettle, and C. R. Lowe, A microelectronic conductometric biosensor. Biosensors, 1987/88, 3, 101–115. 17. P. T. Kissinger, W. R. Heineman, Laboratory Techniques in Electroanalytical Chemistry, Marcel Dekker, New York, 1984. 18. S. V. Dzyadevich, A. A. Shul’ga, S. V. Patskovsky, V. N. Arkhipova, A. P. Soldatkin, and V. I. Strikha, Thinfilm conductometric transducers for enzyme biosensors. Russian Journal of Electrochemistry, 1994, 30, 887–891. 19. W. Olthuis, A. Volanschi, J. G. Bomer, and P. Bergveld, A new probe for measuring electrolytic conductance. Sensors and Actuators, B, 1993, 13 – 14, 230–233. 20. U. Weimar and W. Gopel, A.c. measurements on tin oxide sensors to improve selectivities and sensitivities. Sensors and Actuators, B, 1995, 26 – 27, 13–18. 21. N. F. Sheppard, R. C. Tucker, and C. Wu, Electrical conductivity measurements using microfabricated interdigitated electrodes. Analytical Chemistry, 1993, 65, 1199–1202. 22. W. Y. Lee, S. R. Kim, T. H. Kim, K. S. Lee, M. C. Shin, and J. K. Park, Sol-gel-derived thick-film conductometric biosensor for urea determination in serum. Analytica Chimica Acta, 2000, 404, 195–203. 23. P. Jacobs, J. Suls, and W. Sansen, Performance of a planar differential-conductivity sensor for urea. Sensors and Actuators, B, 1994, 20, 193–198. 24. R. Hintsche, B. Moller, I. Dransfeld, U. Wollenberger, F. Scheller, and B. Hoffmann, Chip biosensors on thin-film metal electrodes. Sensors and Actuators B, 1991, 4, 287–291. 25. U. Trebbe, M. Niggemann, K. Cammann, G. C. Fiaccabrino, M. Koudelka-Hep, S. Dzyadevich, and O. Shulga, A new calcium sensor based on ion-selective conductometric microsensors–membranes and features. Fresenius’ Journal of Analytical Chemistry, 2001, 371, 734–739. 26. S. K. Mikkelsen and G. A. Rechnitz, Conductometric transducers for enzyme-based biosensors. Analytical Chemistry, 1989, 61, 1737–1742. 27. U. Bilitewski, W. Drewes, and R. D. Schmid, Thick film biosensors for urea. Sensors and Actuators B, 1992, 7, 321–326. 28. D. C. Cullen, R. S. Sethi, and C. R. Lowe, Multi-analyte miniature conductance biosensor. Analytica Chimica Acta, 1990, 231, 33–40. 29. C. J. McNeil, D. Athey, M. Ball, W. On Ho, S. Krause, R. D. Armstrong, J. D. Wright, and K. Rawson, Electrochemical sensors based on impedance measurement
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
13
of enzyme-catalyzed polymer dissolution: theory and application. Analytical Chemistry, 1995, 67, 3928–3935. T. A. Sergeeva, N. V. Lavrik, A. E. Rachkov, Z. I. Kazantseva, S. A. Piletsky, and A. V. El’skaya, Hydrogen peroxide–sensitive enzyme sensor based on phtalocyanine thin film. Analytica Chimica Acta, 1999, 391, 289–297. H.-E. Endres and S. Drost, Optimization of the geometry of gas-sensitive interdigital capacitors. Sensors and Actuators, B, 1991, 4, 95–98. C. Besson, S. Vessillier, T. Gonzales, J. Saulnier, and J. Wallach, Conductimetric assay of pyroglutamyl peptidase activity. Analytica Chimica Acta, 1994, 294, 305–309. S. V. Dzyadevych, Amperometric biosensors. Modern technologies of creation and commercial analyzers. Biopolymers Cell, 2002, 18, 363–376. W. On Ho, S. Krause, C. J. McNeil, J. A. Pritchard, R. D. Armstrong, D. Athey, and K. Rawson, Electrochemical sensor for measurement of urea and creatinine in serum based on ac impedance measurement of enzyme-catalyzed polymer transformation. Analytical Chemistry, 1999, 71, 1940–1946. W. T. Chin and W. Kroontje, Conductivity method for determination of urea. Analytical Chemistry, 1961, 33, 1757–1760. P. Bourrelly and V. Bourrelly-Durand, Methode d’etude par conductometric differentielle de la cinetique de l’hydrolise enzymatique de l’uree. Journal of Chemical Physics, 1965, 65, 673–677. V. S. Andreev, V. I. Rozengart, and V. A. Torubarov, Registration of kinetics of enzymatic reaction by highfrequency method. Ukrainian Biochemical Journal, 1965, 37, 920–926. V. S. Andreev and A. V. Bashtanov, Differential conductometric device for registration of physicalchemical processes. Zavodskaya laboratoriya, 1968, 34, 1546–1548. M. Hanss and A. Rey, Application de la conductometrie a l’etude des reactions enzymatiques. Systeme uree-urease. Biochimica et Biophysica Acta, 1971, 227, 630–638. A. J. Lawrence and G. R. Moores, Conductimetry in enzyme studies. European Journal of Biochemistry, 1972, 24, 538–546. A. A. Shul’ga, S. V. Dzyadevich, A. P. Soldatkin, S. V. Patskovsky, V. I. Strikha, and A. V. El’skaya, Thinfilm conductometric biosensor for glucose and urea determination. Biosensors and Bioelectronics, 1994, 9, 217–223. A. A. Shul’ga, S. V. Dzyadevich, A. P. Soldatkin, S. V. Patskovsky, V. I. Strikha, Conductometric biosensors for glucose and urea based on microfabricated thinfilm interdigitated array-electrodes. Biologi Italiani, 1993, 23(6), 40–45. A. A. Shul’ga, S. V. Dzyadevich, A. P. Soldatkin, S. V. Patskovsky, N. F. Starodub, V. I. Strikha, and A. V. El’skaya, Thin-film conductometric enzymatic biosensor for glucose and urea determination in blood. Russian Journal of Electrochemistry, 1993, 29, 860–864. S. V. Dzyadevich, A. P. Soldatkin, A. A. Shul’ga, V. I. Strikha, and A. V. El’skaya, Conductometric biosensor for organophosphorus pesticides determination. Journal of Analytical Chemistry, 1994, 49, 789–792.
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
45. B. F. Y. Hin, R. S. Sethi, and C. R. Lowe, Multi-analyte microelectronic biosensor. Sensors and Actuators A, 1990, 1, 550–554. 46. A. M. Nyamsi Hendji, N. Jaffrezic-Renault, C. Martelet, S. V. Dzyadevich, A. A. Shul’ga, A. P. Soldatkin, and A. V. El’skaya, Enzyme biosensor based on micromachined interdigitated conductometric transducer: application to the detection of urea, glucose, acetyl and butyrylcholine chlorides. Sensors and Actuators, B, 1994, 21, 123–129. 47. S. V. Dzyadevich, G. A. Zhylyak, A. P. Soldatkin, and A. V. El’skaya, Conductometric urease microbiosensor based on thin-films interdigitated electrodes for urea determination. Biopolymers Cell, 1996, 12, 53–57. 48. M. M. Castillo-Ortega, D. E. Rodriguez, J. C. Encicas, M. Plascencia, F. A. Mendez-Velarde, and R. Olayo, Conductometric uric acid and urea biosensor prepared from electroconductive polyaniline-poly(n-butyl methacrylate) composites. Sensors and Actuators, B, 2002, 85, 19–25. 49. W. Limbut, P. Thavarungkul, P. Kanatharana, P. Asaawatreratanakul, C. Limsakul, and B. Wongkittisuksa, Comparative study of controlled pore glass, silica gel and Poraver for the immobilization of urease to determine urea in a flow injection conductimetric biosensor system. Biosensors and Bioelectronics, 2004, 8, 813–821. 50. A. Steinschaden, D. Adamovic, G. Jobst, R. Glatz, and G. Urban, Miniaturised thin film conductometric biosensors with high dynamic range and high sensitivity. Sensors and Actuators, B, 1997, 44, 365–369. 51. W.-Y. Lee, K. S. Lee, T.-H. Kim, M.-C. Shin, and J.K. Park, Microfabricated conductometric urea biosensor based on sol-gel immobilized urease. Electroanalysis, 2000, 12, 78–82. 52. N. F. Sheppard, D. J. Mears, and A. Guiseppi-Elie, Model of an immobilized enzyme conductimetric urea biosensor. Biosensors and Bioelectronics, 1996, 11, 967–979. 53. A. M. Gallardo Soto, S. A. Jaffari, and S. Bone, Characterisation and optimisation of AC conductimetric biosensors. Biosensors and Bioelectronics, 2001, 16, 23–29. 54. A. Senillou, N. Jaffrezic, C. Martelet, and S. Cosnier, A laponite clay-poly(pyrrole-pyridinium) matrix for the fabrication of conductometric microbiosensors. Analytica Chimica Acta, 1999, 401, 117–124. 55. A. P. Soldatkin, S. V. Dzyadevich, Y. I. Korpan, V. N. Arkhipova, G. A. Zhylyak, S. A. Piletsky, T. A. Sergeeva, T. L. Panasyuk, and A. V. El’skaya, Biosensors based on conductometric detection. Biopolymers Cell, 1998, 14, 268–277. 56. S. V. Dzyadevych, V. N. Arkhypova, A. V. El’skaya, N. Jaffrezic-Renault, C. Martelet, and A. P. Soldatkin, Conductometric enzyme biosensors for substrates or inhibitors analysis. Current Topics in Analytical Chemistry, 2001, 2, 179–186. 57. P. Jin, A. Yamaguchi, O. F. Asari, S. Matsuo, J. Tan, and H. Misawa, Glucose sensing based on interdigitated array microelectrode. The Analytical Science, 2001, 17, 841–846. 58. A. P. Soldatkin, A. V. El’skaya, A. A. Shul’ga, A. S. Jdanova, S. V. Dzyadevich, N. JaffrezicRenault, C. Martelet, and P. Clechet, Glucose sensitive
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
conductometric biosensor with additional NAFION membrane: reduction of influence of buffer capacity on the sensor response and extension of its dynamic range. Analytica Chimica Acta, 1994, 288, 197–203. S. V. Dzyadevych, O. P. Soldatkin, V. N. Arkhypova, A. A. Shul’ga, G. V. El’ska, Conductometric enzyme glucosensor. Searching the ways of increasing of analytical characteristics. Ukrainian Biochemical Journal, 1995, 67(6), 53–59. S. V. Dzyadevich, V. N. Arkhipova, A. P. Soldatkin, A. V. El’skaya, and A. A. Shul’ga, Glucose conductometric biosensor with potassium hexacyanoferrate (III) as an oxidizing agent. Analytica Chimica Acta, 1998, 374, 11–18. S. V. Dzyadevich, A. A. Shul’ga, A. P. Soldatkin, A. M. Nyamsi Hendji, N. Jaffrezic-Renault, and C. Martelet, Application of conductometric for sensitive detection of pesticides biosensor based on the cholinesterases. Electroanalysis, 1994, 6, 752–758. V. N. Arkhypova, S. V. Dzyadevych, O. N. Schuvaylo, A. P. Soldatkin, A. V. El’skaya, N. JaffrezicRenault, and C. Martelet, Concept of multibiosensors for determination of different toxic compounds based on enzyme inhibitor analysis. Biopolymers Cell, 2001, 17, 70–77. V. N. Arkhypova, S. V. Dzyadevych, A. P. Soldatkin, A. V. El’skaya, N. Jaffrezic-Renault, H. Jaffrezic, and C. Martelet, Multibiosensor based on enzyme inhibition analysis for determination of different toxic substances. Talanta, 2001, 55, 919–927. S. V. Dzyadevych, A. P. Soldatkin, and J.-M. Chovelon, Assessment of the toxicity of parathion and its photodegradation products in water samples using conductometric enzyme biosensors. Analytica Chimica Acta, 2002, 459, 33–41. S. V. Dzyadevych and J.-M. Chovelon, A comparative photodegradation studies of methyl parathion by using Lumistox test and conductometric biosensor technique. Materials Science and Engineering C, 2002, 21, 55–60. S. V. Dzyadevych, A. P. Soldatkin, V. N. Arkhypova, A. V. El’skaya, J.-M. Chovelon, C. Georgiou, C. Martelet, and N. Jaffrezic-Renault, Early-warning electrochemical biosensor system for the environmental monitoring based on enzyme inhibition effect. Sensors and Actuators, B, 2005, 105, 81–87. G. A. Zhylyak, S. V. Dzyadevich, Y. I. Korpan, A. P. Soldatkin, and A. V. El’skaya, Application of urease conductometric biosensor for heavy-metal ion determination. Sensors and Actuators, B, 1995, 24-25, 145–148. V. N. Arkhipova, S. V. Dzyadevich, A. P. Soldatkin, and A. V. El’skaya, Enzyme biosensors for determination of penicillin based on conductometric planar electrodes and pH-sensitive field effect transistors. Ukrainian Biochemical Journal, 1996, 68, 27–32. O. A. Biloivan, S. V. Dzyadevych, O. P. Soldatkin, N. F. Starodub, G. V. El’ska, Enzymosensor based on trypsin and conductometric planar electrodes for determination of bulks and peptid’s substrates in solution. Ukrainian Biochemical Journal, 1997, 69(2), 14–18. S. V. Dzyadevych, V. N. Arkhypova, Y. I. Korpan, A. V. El’skaya, A. P. Soldatkin, N. Jaffrezic-Renault, and C. Martelet, Conductometric formaldehyde sensitive
CONDUCTOMETRIC ENZYME BIOSENSORS biosensor with specifically adapted analytical characteristics. Analytica Chimica Acta, 2001, 445, 47–55. 71. T. Mai Anh, S. V. Dzyadevych, M. Chau Van, N. JaffrezicRenault, N. Duc Chien, and J.-M. Chovelon, Conductometric tyrosinase biosensor for the detection of diuron, atrazine and its main metabolites. Talanta, 2004, 63, 365–370.
15
FURTHER READING A. J. Lawrence, Conductimetric enzyme assays. European Journal of Biochemistry, 1971, 18, 221–225.
24 Chemical and Biological Field-Effect Sensors for Liquids – A Status Report Arshak Poghossian and Michael J. Sch¨oning Institute of Nano- and Biotechnologies and Research Center J¨ulich, Aachen University of Applied Sciences, J¨ulich, Germany
1 INTRODUCTION
Semiconductor-type field-effect devices (FED) based on the electrolyte–insulator–semiconductor (EIS) concept, that is, ISFET (ion-sensitive fieldeffect transistor), capacitive EIS sensor, and LAPS (light-addressable potentiometric sensor) are currently one of the basic structural elements of chemical and biological microsensors with new functional and application possibilities. They provide a lot of potential advantages such as small size and weight, robustness, fast response time, high reliability, batch processing capability, and so on. On the other hand, the possible field of application of these three kinds of FEDs reaches from medicine, biotechnology, and environmental monitoring over food and drug industries up to defense and security purposes including antibioterrorism and biological warfare agents field. The miniaturization of FEDs and their compatibility with advanced microfabrication technology also make them very attractive for the integration into microfluidic platforms in order to build up miniaturized analytical systems such as micro total analysis system (µTAS), “lab on chip”, and electronic tongue devices. This paper gives a status report on research and development of chemical sensors and biosensors
based on ISFET, capacitive EIS, and LAPS structures. In planning this review, we have chosen to mainly focus upon developments occurring during the last 5 years, from the beginning of 2001 to the end of 2005 (for the early works, the interested reader is referred to Refs. 1–5).
2 PRINCIPLE OF FIELD-EFFECT-BASED (BIO-)CHEMICAL SENSORS
Figure 1 shows a typical structure of a capacitive EIS sensor (a), a LAPS (b), and an ISFET (c). These sensor structures are obtained by replacing the metallic gate of the metal–insulator– semiconductor (MIS) capacitance and the insulated-gate field-effect transistor (IGFET), respectively, by an electrolyte solution and a reference electrode. Since (bio-)chemical FEDs are very sensitive for any kind of electrical interaction at or near the gate insulator/electrolyte interface, in general, nearly each (bio-)chemical reaction leading to chemical or electrical changes at this interface can be measured. Therefore, the ISFET, capacitive EIS sensor or LAPS must be coupled with the respective chemical or biological recognition element. Changes in the chemical composition will induce changes in the electrical surface charge of the gate insulator and in the
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Impedance analyzer
RE
V= bias
Analyte
V~
Gate insulator Depletion layer
Capacitance
2
C1
C2
C3
Si Bias voltage
(a) Feedback circuit
Analyte PC Gate insulator Depletion layer
Photocurrent
Potentiostat RE WE
C1
C2
C3
Si Modulated light source
Bias voltage
(b) Chemical or biological recognition element Drain current
VG
RE Analyte
n+ Source
(c)
Gate insulator Channel
n+ Drain p-Si
C1
C2
C3
Id
VDS
Gate voltage
Figure 1. Setup and typical sensor response of a capacitive EIS sensor (a), a LAPS (b), and an ISFET (c); RE: reference electrode; WE: working electrode; PC: computer; c1,2,3 : analyte concentration. For operation, the gate or bias voltage is applied via a reference electrode (e.g., Ag/AgCl liquid-junction electrode), to set the working point of the sensor as well as to provide a stable potential in the solution. In the case of the EIS sensor setup, an additional small alternating voltage V∼ (∼10–50 mV) is applied to the system in order to measure the capacitance of the EIS sensor. To detect the variation of the capacitance of the depletion layer, the LAPS is illuminated with a modulated light beam, which induces an ac photocurrent to be measured as the sensor signal.
potential drop at the electrolyte/insulator interface that consequently modulates the current in the ISFET’s channel, the capacitance of the EIS sensor or the photocurrent of the LAPS (see Figure 1, right). Generally, the following basic mechanisms of potential generation can be
considered: a pH or ion-concentration change, enzymatic reactions, adsorption of charged macromolecules (e.g., polyelectrolytes, deoxyribonucleic acid (DNA)), affinity binding of molecules (e.g., antigen–antibody affinity reaction, DNA hybridization), and potential changes that are
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS
coming from living biological systems as a result of more sophisticated (bio-)chemical processes (e.g., action potentials of nerve cells).
3 FET-BASED (BIO-)CHEMICAL DEVICES 3.1
pH ISFET
Different oxides and nitrides, like SiO2 , Si3 N4 , SiOx Ny (oxynitride), Al2 O3 , Ta2 O5 , ZrO2 , SnO2 , TiO2 , WO3 , PbTiO3 , AlN, TiN, GaN, Al2 O3 – ZrO2 , and Al2 O3 –Ta2 O5 double oxides, hydrogenated diamond, hydrogenated amorphous Si (a-Si:H), and so on, have been proven as pHsensitive material for FEDs.6–25 However, sometimes these results have been “rediscovered” from results that have already been obtained more than 10–30 years ago. At present, Si3 N4 , Al2 O3 , and Ta2 O5 serve as pH-sensitive gate insulator materials in commercial ISFETs. Other more exotic materials such as AlN, TiN, PbTiO3 , WO3 , and so on, sometimes show nearly Nernstian sensitivity, but have been only rarely studied. Ta2 O5 is considered as the best pH-sensitive material for field-effect sensors, combining a practically ideal Nernstian pH sensitivity, minimal drift, and hysteresis.5,6,13 In addition, as discussed in Section 4, it seems that Ta2 O5 is also the best corrosion-resistant pH-sensitive material. pH ISFETs are now a commercial reality: they are available from more than 20 companies such as Honeywell (USA), Orion (USA), Horiba (Japan), Endress + Hausser (Germany), Mettler Toledo (Switzerland), Sentron Europe (The Netherlands), and other producers of electrochemical sensors. Early problems with ISFETs, that is, drift, temperature instability, light sensitivity, encapsulation, and packaging, can be considered as satisfactorily solved, at least by leading companies producing pH-ISFET sensors.25 Today, commercially available ISFET sensors are exceptionally stable (practically drift free), fully temperature compensated, rugged, and reliable, and exhibit performances comparable to those of pH glass electrodes.25 Moreover, different ISFET fabrication technologies with integrated readout interfaces (e.g., constant current–voltage driver, calibration circuitry, electronics for drift and temperature compensation) have been realized using complementary metal-oxide-semiconductor
3
(CMOS) processes.10,26,27 However, to our knowledge, up to now no ISFET with integrated readout interface has been commercialized. Resistance to breakage is the most obvious feature of solid-state field-effect sensors compared to the pH glass electrode. Therefore, nowadays, in many in-line process-monitoring systems in biotechnology, food, pharmaceutical and cosmetic industries, the breakable pH glass electrode is gradually being replaced by nonglass, unbreakable pH sensors based on ISFETs.25 However, the main problem with those applications is the required cleaning-in-place (CIP) suitability of ISFET devices. According to Ref. 25, commercially available pH ISFETs have a limited lifetime in CIP solutions due to the destruction or dissolution of the pH-sensitive layer during the cleaning of the process vessels using highly caustic media and high temperatures. 3.2
Enzyme-modified FETs (EnFET)
Most reported enzyme-modified field-effect transistors (EnFETs) are built-up of pH-sensitive ISFETs, where hydrogen ions are produced or consumed by the enzymatic reaction. A multitude of EnFETs differing in their sensor design or gate material, enzyme–membrane composition, or immobilization method have been reported for the detection of glucose, urea, penicillin, organophosphorus pesticides, creatinine, phenolic compounds, glycoalkaloids, and so on.28–44 Some recently developed EnFETs are summarized in Table 1. For an exact measurement, a pH ISFET/EnFET differential arrangement is often employed (see e.g., Refs. 32 and 39), where the pH ISFET contains a blank enzyme-free membrane and acts as a reference device. Intensive work during the last years focused on the improvement of EnFET characteristics to circumvent problems, which actually prevent the successful commercialization of EnFETs (e.g., dependence of the sensor response on buffer capacity, ionic strength, and pH of the test sample; restricted dynamic range, nonlinearity; relatively slow response and recovery times; operating and storage stability; reproducibility; dependence on enzyme-immobilization method; the incompatibility of most used enzyme-containing layer deposition and patterning methods with silicon technology).
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Table 1. Recently developed EnFETs with enzyme system used and analyte to be detected
Analyte Glucose
Urea Penicillin Creatinine Organophosphate compounds Fluorine-containing organophosphates Phenolic compounds Glycoalkaloids
Enzyme system
References
Glucose oxidase Glucose oxidase/MnO2 powder Glucose oxidase/MnO2 nanoparticles Glucose oxidase/SiO2 nanoparticles Urease Penicillinase Creatinine deiminase Organophosphate hydrolase
28 29 30 31 32–37 12, 13, 38, 39 40 41
Organophophorus acid anhydrolase
42
Tyrosinase Butyryl cholinesterase
43 44
In general, the main disadvantage of field-effect transistor (FET)-based urea and glucose biosensors for biomedical applications is a rather narrow dynamic range (a few millimolars) implying a necessary dilution of the biological sample before the measurement. To extend the dynamic range of a glucose-sensitive EnFET, a glucose-oxidase membrane has been doped with MnO2 powder that catalyzes hydrogen peroxidase (as by-product of the glucose-oxidation reaction).29 As a result, the additional product oxygen is produced, which can be recycled for the glucose-oxidation reaction. In this way, the upper detection limit of the biosensor was extended up to 20 mM. Hence, the developed EnFET can be applied for the glucose detection in undiluted blood samples. A glucose-sensitive EnFET with an extended dynamic range, a good reproducibility, and stability has been realized by the co-immobilization of glucose oxidase and MnO2 nanoparticles, where the MnO2 nanoparticles act as an oxidant rather than a catalyst.30 With the same background, a urea-sensitive EnFET with an extended dynamic range of up to 80 mM was developed taking advantage of a recombinant urease with a genetically modified enzymatic active site.34 The concept of in-situ electrochemical generation of OH− ions in the enzyme membrane was used to improve the recovery time of a glucose-sensitive EnFET.28 A highly sensitive, low detection limit, and long lifetime penicillin-sensitive EnFET was developed in Ref. 39 by adsorptive immobilization of the enzyme penicillinase on a Ta2 O5 -gate ISFET. An extreme low detection limit of 5 µM and a penicillin sensitivity of about 120 mV mM−1 were
achieved by using an optimized buffer solution. The main advantages of the adsorptive immobilization technique are its simplicity, cheapness, and the possibility of a subsequent enzyme (sensor) regeneration. For the fabrication of truly inexpensive and thus, disposable biosensors it is of great interest to integrate the enzyme–membrane preparation in the whole ISFET-fabrication process. A CMOS-compatible, disposable EnFET/ISFET structure with an integrated pseudoreference electrode has been fabricated in Ref. 32. In addition, extended-gate FET structures that are simple in fabricating and packaging have been applied for the development of EnFETs.33 Although EnFETs have a long history and much effort and investment has been done, the transfer of EnFETs from scientific laboratories to real life remains rather slow. Up to now, no EnFET has been commercialized for a wider range of applications. 3.3
DNA-modified FEDs
The possibility of a label-free detection of DNA hybridization utilizing FEDs offers a next generation of DNA chips with direct electrical readout for a fast, simple, and inexpensive real-time analysis of nucleic acid samples. Therefore, in recent years, a considerable research effort has been devoted to the label-free electronic detection of biomolecules (DNA, proteins) by their intrinsic molecular charge using FEDs.45–60 In most cases, the experimentally observed sensor response is interpreted in a way that during the binding event (hybridization of immobilized single-strand DNA (ssDNA)
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS cDNA C
A
T
C
G
G
A
A
ssDNA
n+
A A G C C T T
A
G
G
C
T
A
5
C
A G C C T T
Gate insulator
dsDNA
C A T C G G A A
C A A-T G-C C-G C-G T-A T-A
Hybridization n+
p-Si
n+
C A A-T G-C C-G C-G T-A T-A
Gate insulator
n+
p-Si
Figure 2. Schematic structure of a DNA-modified FET and principle of DNA-hybridization detection (ssDNA: single-stranded DNA; dsDNA: double-stranded DNA; cDNA: complementary DNA).
with its complementary target molecule (cDNA); see Figure 2) the charge associated with the target molecule effectively changes the charge applied to the gate of the FED. As a result, the operating characteristics of the FED, that is, the flat-band voltage and capacitance of the EIS sensor or the threshold voltage and drain current of the FET device, will also change. Although the discussed subject is highly interesting, there are still insufficient correct theoretical models for a clear understanding of both the functioning mechanism of these sensors and the source of the experimentally observed signal generation. Moreover, the reported results are very diverse and controversial (e.g., the observed values of the response signal varies from several millivolts45,51 up to 1.9 V46 ). Furthermore, it is not understandable, why a much higher signal has been observed for a sensor with a less density of immobilized ssDNA (1.45 V with 3.8 × 108 molecules/cm2 49 ) compared to a sensor with a densely packed ssDNA (3 mV with 5 × 1013 molecules/cm2 45 ). Or to give a second example, it is not understandable, what the reason is for the much higher biosensor signals, which are observed when floating-gate transistors47–50 or devices without a necessary reference electrode46,47,49 have been used; or, why a DNA-FET without a reference electrode can deliver a reliable sensor signal? 46,47,49 Field-effect sensors are basically surface-charge (potential) measuring devices and are principally able to measure the charge of adsorbed
macromolecules or the charge change due to a hybridization event. At the same time, however, owing to the so-called counterion screening effect and the nonideality of the molecular layer, the realization of these devices for a direct electrostatic detection of charged macromolecules by their intrinsic molecular charge in relatively high-ionic-strength solutions such as physiological solutions is problematic. This subject has been critically discussed for immunospecies and protein molecules and the DNA-hybridization detection in Refs. 2, 61, and 62, respectively, where the estimated hybridization signals were in the range of several millivolts.62 To enhance the sensor signal, the biosensor must be operated in a very low ionicstrength solution (<1 mM) with a tightly packed probe ssDNA (>1013 ssDNA/cm2 ). Even under these conditions, the theoretical basis of the sometimes experimentally observed large sensor signals still remains unclear. To overcome the described problems, recently, an alternative mechanism based on the detection of the DNA hybridization-induced redistribution of the ion concentration within the intermolecular spaces and/or the alteration of the ion sensitivity of the field-effect device has been proposed.62 Here the theoretical calculations predict a substantial change in the charge redistribution within the intermolecular spaces of the immobilized DNA induced upon the hybridization event that are enough to obtain a detectable signal of about ∼25–35 mV, when using FEDs.62
6
3.4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
‘‘Cell/transistor’’ Hybrid
“Cell/transistor” hybrids are of great interest for a large variety of applications including the monitoring of electrical communication within neuronal networks, transmission paths of ionic channels, or use as biosensor for pharmaceutical agents, toxic substances, or pollutants. The state of a single cell or a cell system can be monitored by means of various methods that can be distinguished into two basic families: 1. The first type utilizes the energic metabolism of cells; signal parameters such as changes in the extracellular acidification rate, concentration of ions, oxygen consumption, CO2 production, and other metabolic products caused by different external stimuli (e.g., by addition of drugs or toxic agents to the medium) can be detected by the various underlying FEDs. The parallel and noninvasive measurement of the different parameters allows a clear interpretation of different effects on living cells, because cells respond to external stimuli with a parallel activation of different signaling pathways. Examples are a cell-monitoring system with different microsensors (array of pH ISFETs and cell-potential FETs with different gate areas63 ), and a completely automated cell-monitoring microsystem (12 spatially distributed ISFETs) with space and time resolution.64 The experiments demonstrate the capability of the developed system for in-vitro toxicity-screening applications by monitoring changes in the extracellular acidification rate after applying the toxic agents. A further approach describes a multisensor silicon needle consisting of two ISFETs and a temperature sensor that has been realized for the simultaneous measurement of the H+− , K+− concentration and temperature of a myocardial tissue.9 2. The second type of methods utilizes specific features of electrogenic cells such as neuronal and muscle cells and refers on extracellular potential measurements. Electrogenic cells generate spontaneous or triggered action potentials that can be measured by coupling them to FEDs. The activity of a neuron leads to ionic and displacement currents flowing through the cell membrane. This results in
an extracellular voltage drop along the narrow cleft between the cell membrane and the gate insulator of the ISFET that finally, modulates the drain current of the ISFET.3,65–67 Different approaches and equivalent electricalcircuit models have been suggested to describe the signal transfer from electrogenic cells to a FET device in order to explain the recorded signal behavior in terms of shape and amplitude (see e.g., Refs. 65–68 and references therein). However, all these models cannot fully explain some kinetic components in the transistor signal.68 Experiments with HEK-293 cells with voltage-gated K+ channels show, for instance, that variations in the ion concentration in the small cleft between the cell and the FET change the surface potential of the underlying gate insulator and, thus, can play a major role in the recorded biosensor signal.68 In addition to neuronal cells, cardiac muscle cells represent an interesting electrically active system. Their beating frequency can be strongly influenced by cardiac stimulants and relaxants. Such a bioelectronic device, built-up of an array of 16 FETs, has been adapted for recording effects of different drugs on cardiac myocytes.69 Further examples are a 16–channel backside contacted FET array,70 a depletionmode floating-gate FET fabricated by 0.5 µm CMOS technology,71 a large array (16 × 16) of floating-gate FETs,72 and an AlGaN/GaN FET with a high signal-to-noise ratio.73 Moreover, an ISFET-based sensor array, which includes both FETs for detecting the action potential and ISFETs coupled with different ion-sensitive membranes for the measurement of concentration of extracellular ions, like Na+ , K+ , and Ca2+ , has been realized for studying the relationship between the membrane potential and the influx/efflux of ions under external stimulation and drug treatment.74 The main advantage of cell-based ISFET biosensors, compared to, for example, patchclamp technique, is the possibility of a real-time, noninvasive, long-term monitoring of the state of living cells. Nonetheless, all these investigations are still in an experimental stage, far from becoming a commercially available product.
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS
(Bio-)chemical Sensor as a Physical Sensor
In multiparameter analysis systems, besides (bio-)chemical parameters it is often necessary to also measure physical parameters of the liquid, like temperature, flow rate, flow direction, and so on. A simple and mostly used way to construct an ISFET-based multiparameter detection system is the integration of an array of ISFETbased (bio-)chemical sensors with different wellestablished single-function physical sensors (see e.g., Refs. 9 and 75). Another concept for multiparameter detection, so-called (bio-)chemical and physical sensors based on an identical transducer principle, has
Four ISFET structures
Eight sensor functions
Multiparameter detection system
K+ ISFET H+ + H+ H Ion generator
Flow-direction sensor
ISFET1
Flow-velocity sensor
pH sensor
K+ sensor
Enzyme sensor
Reference electrode
Liquid-level sensor
Physical sensors
Temperature sensor
(Bio-)chemical sensors
been introduced in Ref. 12. In this approach, the same ISFET, which is well known as a (bio-)chemical sensor, also serves as a physical sensor and thus, the amount of obtained (bio-)chemical and physical information can be significantly higher than the number of sensors present in the system (“high-order” system).76–78 On the basis of this concept, an ISFET-based multiparameter system for the detection of three (bio-)chemical (pH, K+ , and penicillin concentration) and five physical quantities (temperature, flow velocity, flow direction, diffusion coefficient of ions, and liquid level) has been realized using only four ISFET transducers (see Figure 3).13
Diffusion-coefficient sensor
3.5
7
ISFET2 EnFET
Meander-gate
Printed circuit board
Au ion generator
ISFET chips
Figure 3. Schematic of an ISFET-based multiparameter system for detecting three (bio-)chemical (pH, K+ , penicillin) and five physical quantities (temperature, flow velocity, flow direction, diffusion coefficient of ions, liquid level) by using only four ISFET transducers. In this approach, the same ISFET, which is well known as a (bio-)chemical sensor, also serves as a physical sensor; the multifunctionality is achieved by means of different sensor configurations and/or operation modes.
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
4 CAPACITIVE EIS SENSORS
In general, owing to the same functional mechanism, applied materials, and deposition techniques, the sensitive characteristics obtained with EIS and ISFET sensors are quite similar. Therefore, in the following part, we focus on some innovative developments for the fabrication of EIS sensors, like the pulsed laser deposition (PLD) technique, CIP-suitable pH-sensitive materials, porous Si, and the integration of miniaturized EIS sensors with micromachined flow-through microcells. Recently, a capacitive EIS sensor based on PLDprepared Al2 O3 and Ta2 O5 films has been reported as a highly long-term stable pH sensor with nearly Nernstian behavior.79,80 In a further approach, the EIS sensor and a thick-film screen-printed reference electrode have been integrated into a hybrid sensor module.81 These results favor the employment of the PLD process as an alternative deposition method for thin-film pH and chemically sensitive gate insulator materials. Besides its compatibility with silicon planar technology, the main advantage of this method is the controlled deposition of even multicomponent compositions in a defined stoichiometry. As discussed in Section 3.1, commercial pH ISFETs have a limited lifetime in CIP solutions. In order to extend the application area of pH-sensitive FEDs, it is of strong interest to develop insulator materials combining both high corrosion-resistance properties and a high pHsensitive behavior. Therefore, the CIP suitability of EIS sensors with pH-sensitive Ta2 O5 films, prepared by thermal oxidation of Ta layers at an optimized temperature, has been tested under real CIP conditions.82 These experiments have shown, that even after 30 CIP cycles (each CIP cycle includes a cleaning in 4% NaOH solution at 80 ◦ C during 15 min and subsequently in 0.65% HNO3 solution at 80 ◦ C during 5 min), the sensors have a linear calibration curve with a nearly Nernstian sensitivity of 57 ± 1.5 mV/pH. Ellipsometric, video-microscopic, and scanning electron microscopy investigations do not show any visible change in the thickness or degradation of the Ta2 O5 films after the CIP cycles. These experiments could demonstrate the CIP suitability of EIS sensors with Ta2 O5 films, where a nonglass, unbreakable sensor can be placed in direct contact
with food for pH measurements without the risk of broken glass fragments.
4.1
Enzyme-modified EIS Sensor
At present, enzyme-modified capacitive EIS sensors have been realized for the detection of urea,83 penicillin,38,84,85 organophosphorus pesticides (paraoxan, parathion, diazinon, and dichlorvos),86,87 alliin,88 cyanide,89 and other analytes using the respective enzyme. In order to simultaneously detect both the variation of the pH and penicillin content, an EIS sensor array has been developed (see e.g., Ref. 79). In addition, the cross-sensitivity of a EIS penicillin sensor in combination with a diffusion barrier has been investigated with respect to four different kinds of penicillin, namely penicillin G, ampicillin, amoxicillin, and cloxacillin.38 Functioning and, therefore, also the problems related to enzyme-modified capacitive EIS sensors are similar to those of EnFETs, which have been discussed in Section 3.2. In addition, an impedance effect of the enzyme-containing membrane can influence the sensor signal.90 In spite of their very simple structure, generally, enzyme-modified capacitive EIS biosensors are less investigated than EnFETs.
4.2
Capacitive EIS Sensor Based on Porous Si
Capacitive EIS sensors based on porous Si exhibit the advantages of a protected embedment of chemical or biological receptor molecules inside the pores against a fast leaching out, and the enlargement of the effective sensor area due to the porous structure (see Figure 4). Porous pH sensors with an n-Si/SiO2 /Si3 N4 structure have been reported in Refs. 91 and 92: the pH sensitivity (54 mV/pH) is in good agreement with results obtained for nonporous (planar) sensors with the same Si3 N4 layer. Here, the effective sensor surface and thus, the capacitance of the porous pH sensor is larger by a factor of 30 with respect to a comparable nonporous EIS sensor. The possibility to use oxidized porous Si as a transducer material for ion-sensor applications has been demonstrated in Ref. 93. Surprisingly, an unusual super-Nernstian
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS
9
Chemical/biological receptors Si3N4 SiO2 Si SiO2 Contact
Si3N4
50 nm
Figure 4. Schematic and photo of a macroporous EIS sensor; the mean pore diameter varies between 0.5 and 3 µm.
sensitivity toward Na+ and Cu2+ ions has been found, that was interpreted by using a quantumeffect model. Besides the possibility of miniaturization, porous EIS sensors should offer the advantage of fixing biomolecules inside the pores just by means of a physical adsorption process. For example, two porous Si EIS biosensors for the determination of penicillin and triglycerides utilizing the adsorptively immobilized enzymes penicillinase and lipase, respectively, have been investigated.80,94
4.3
Micromachined Flow-through Cell with Wafer-level-integrated Capacitive EIS Sensor
In literature, two platforms have been applied to integrate EIS sensors into a flow-through cell. In a first and most often used approach, the EIS sensor represents a separate component in a homemade flow-through cell. In this way, for example, pHsensitive and penicillinase-modified Ta2 O5 -gate EIS sensors have been integrated into a flowthrough cell with a variable internal volume from 12 to 48 µl that is combined with a commercial flow-injection analysis (FIA) system.84,85 The second platform favors a monolithic waferlevel integration of the flow channel together with the EIS sensor structure. In this case, the sensor represents an integral part of the whole flow-through microcell. Here, a micromachined
flow-through microcell with integrated EIS sensor was realized by combining Si and SU-8 technologies;85,95 the flow-through micro-channel has been formed in a thick SU-8 layer directly onto an already prepared p-Si-SiO2 –Ta2 O5 EIS structure (see Figure 5). In order to extend the functional possibilities of this microcell, two thinfilm Pt microelectrodes have been deposited onto the same chip for additional amperometric and flow-velocity measurements. The EIS structures have been integrated in a pH- and penicillinsensitive configuration in flow-through and FIA mode, respectively, yielding a comparable sensor behavior as for the current single pH- and penicillin-sensitive EIS structures.85
5 LAPS
In contrast to the capacitive EIS sensor, where the measured value of the analyte concentration is an average value over the whole sensing surface in contact with the analyte, the LAPS measurement has the advantage of being spatially resolved. The measured area on the sensing surface is defined by the area of illumination, where the ac photocurrent to be measured has been generated.3,96,97 LAPS devices became popular in many chemical and biological applications such as the detection of bacterial growth, the measurement of cell metabolism, the study of mechanisms of drug action on cell physiology, and so
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Inlet
Outlet
Plexiglass converplate
Passivation layer
Metal electrodes Sensor chip
SU-8 microchannels
(a)
Thin-film ion generator (Pt) Flow channel (~4 µl) EIS sensors
SU-8 Si chip
2 mm
(b)
(c)
Figure 5. Schematic flow-through FIA cell setup of the capacitive EIS sensor (a); micromachined flow-through microcells fabricated by combining Si and SU-8 technologies, where the microchannels have been formed as thick SU-8 layers directly onto the already prepared Si–SiO2 –Ta2 O5 EIS structures: microcell with EIS sensor and Pt ion-generator (b), and microcell with two separate microchannels and EIS sensor for multisensor and/or differential setup applications (c).
on (see e.g., Refs. 97 and 98). The first successfully commercialized system using the LAPS is the Cytometer Microphysiometer system, realized in the 1990s by the company Molecular Devices Corporation (USA).97,98
5.1
Different Types of LAPS
Thanks to the structural similarity between LAPS, capacitive EIS sensor and ISFET, many of the sensitive materials, membrane-deposition techniques, and enzyme-immobilization strategies already developed for ISFETs and EIS sensors are also applicable to LAPS devices. Traditionally, the LAPS is employed for pH recording (see e.g., Refs. 3, 96, and 99–102). Si3 N4 is the most frequently used pH-sensitive material in LAPS devices, although several alternative materials
such as PLD-deposited Ta2 O5 99–101 and Al2 O3 102 have also been proved as alternative pH-sensitive materials. An application of porous silicon for a pH LAPS was demonstrated in Ref. 99. In addition, a LAPS with a submicrometer spatial resolution has been fabricated using amorphous silicon.103,104 A concept for a submicron LAPS is theoretically analyzed in Ref. 105. In contrast to pH-sensitive LAPS, ion-sensitive and enzyme-modified LAPS are studied in less detail. For example, the application of LAPS as an ion sensor for the detection of different cations (Li+ , K+ , Cs+ , Ca2+ , and Mg2+ )106–108 and anions − (NO− 3 and SO4 ) has been demonstrated in Ref. 109. A LAPS for heavy-metal detection using a chalcogenide-glass membrane was developed in Refs. 110 and 111. An enzyme-modified LAPS has been realized for the detection of penicillin,99–101 urea, and butyrylcholine.112
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS
5.2
11
Chemical Imaging and Multilight LAPS
In order to achieve a pH distribution with spatial resolution along the LAPS sensor surface, either the light pointer can be scanned along the surface or multiple light pointers can be used. In the chemical imaging sensor, a map of a twodimensional distribution of the pH value or the ion concentration can be visualized by measuring the amplitude of the photocurrent at each point while the focused laser beam is scanned across the surface of the semiconductor.108,113–118 The detection of the metabolic activity of bacteria (Escherichia coli colonies) immobilized on a p-Si/SiO2 /Si3 N4 LAPS surface113 and the potentiometric imaging of a fluid inside a microchannel108 are two examples of a possible application for the chemical imaging sensor. In contrast to the chemical imaging setup, in the multilight LAPS the sensor surface is illuminated at multiple regions by using many light pointers; each light pointer is modulated at a different frequency.106,114,119 On the basis of the multilight LAPS concept, a novel microphysiometer has been proposed for the simultaneous measurement of several extracellular ion concentrations (H+ , Na+ , K+ , and Ca2+ )106,114 in order to study the influence of drugs on the metabolism of a suckling rat’s nephridium and cardiac muscle cells. An alternative approach is presented in Ref. 120, which allows the simultaneous assessing of the metabolic states of two or more cell populations cocultured on different parts of a single sensor surface. Another setup for a multilight LAPS was realized in Ref. 115. Here, defined positions have been illuminated sequentially by multiple light-emitting diodes (LEDs) using the same modulation frequency. In this way, a pen-shaped miniaturized LAPS device with integrated multisensor functions and sequential readout has been developed (see Figure 6). Such a pen-shaped LAPS can be directly dipped into the test sample to be measured. In further work, the authors have developed a handheld 16-channel pen-shaped LAPS with integrated signal processing unit121 and a LAPS card-based sensor setup.122 The general advantage of the multilight LAPS setup is the short time to take an “image” of the surface-potential distribution (16 sensor spots corresponding to 16 “pixels”). However, the number
Figure 6. Photographs of the portable pen-shaped LAPS device with 16 LEDs for defining the sensor spots (inlet, left) and chamber for the test sample (inlet, right).
of illuminated sensor spots per unit surface area is limited due to the geometrical restrictions of actually commercially available LEDs.
5.3
LAPS for Single-cell Measurements
The number of active measuring sites in ISFETbased cell-monitoring systems is limited by the number of FETs as well as by the fact that typically many cells either do not adhere or only partially adhere on top of the gate of the individual FET. LAPS overcomes the problem of a limited number of active measurement sites. By scanning the light pointer and illuminating the LAPS surface exactly below the cell of interest, it should be possible to record their electric activity.116 Although there are many cells cultured on the chip surface, only that cell illuminated by the focused light beam is interrogated. Therefore, several attempts have been made to record action potentials of single cells by means of a LAPS device.116–118 However, the observed signals were small, typically about 10 µV. Although these experiments have demonstrated the capability of the LAPS for detecting extracellular signals from single cells, its present low signal-to-noise ratio hinders the LAPS to be a competitive technique for extracellular signal recording. Nevertheless, with its conceptual advantage of a free addressability of the measurement point with a
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
spatial resolution of a few tens of micrometers, the LAPS is very attractive for single-cell investigations, especially when improving the potential sensitivity and signal-to-noise ratio. Another area is devoted to the application of LAPS-based systems for the detection of the metabolic activity of single living cells. Here, the main technical problem for extracellular acidification measurements of single cells is the need for a means of confining the produced protons to a small and defined “analyte” volume.
6 CONCLUSIONS AND PERSPECTIVES
A comparative study of an ISFET, a capacitive EIS sensor, and a LAPS100 has shown that, since these three sensor types are based on the same transducer principle and materials, they also have a comparable sensor behavior. Nevertheless, the sensor configuration (i.e., measuring setup) and the sensor preparation (i.e., technology) are specific for each type. For example, capacitive EIS sensors and LAPS are cheaper and easier to prepare due to their simplicity in the layout and the absence of a required encapsulation procedure. An attractive feature of the LAPS, compared to the EIS sensor and ISFET, is its addressability. The main disadvantage of the LAPS is the necessity of a light pointer and the light sensitivity. One common disadvantage of the capacitive EIS sensor and the LAPS is the dependence of the sensor signal on any series impedance in general, and on the electrolyte resistance, in particular. Finally, all three sensor types are suitable for multisensor applications. Despite the intensive research and tremendous amount of published works, generally, it can be concluded that a practical realization of (bio-)chemical FEDs and their transfer from scientific laboratories to real life proceeds still rather slowly. The study of the current state of (bio-)chemical FEDs reveals that some of them, like pH-sensitive, enzyme-modified or cell-based FEDs are at a well-developed stage, whereas others such as DNA-modified FEDs are still in the experimental stage or starting phase. Only very few (bio-)chemical FEDs, namely a pH-sensitive ISFET and a LAPS system for cell-acidification detection have been successfully commercialized
so far. Many improvements have been made in the last few years and it can be expected that (bio-)chemical FEDs sensitive to ions others than hydrogen will become commercially available in the near future. Hence, perspectives for research activities of (bio-)chemical FEDs can be expected in the following directions: • The development of biosensors based on organic FEDs.123 • FED-based DNA chips can be considered as a new tool for a label-free nucleic acid analysis. In this context, the detection of layerby-layer adsorbed polyelectrolytes by means of FEDs51,124,125 could be very useful as a model system for fundamental study effects induced in FEDs by the adsorption and binding of charged macromolecules, in particular, during the DNAhybridization event. • The replacement of the inorganic gate insulator of the FED by a molecular insulator layer directly having the reactive sites for a (bio-)chemical interaction. REFERENCES 1. P. Bergveld and A. Sibbald, Analytical and Biomedical Applications of Ion-Selective Field-Effect Transistors, Elsevier, Amsterdam, 1988. 2. G. F. Blackburn, Chemically Sensitive Field-Effect Transistors, in Biosensors: Fundamentals and Applications, A. P. F. Turner, I. Karube, and G. S. Wilson (eds), Oxford University Press, Oxford, 1987, pp. 481–530. 3. M. Grattarola and G. Massobrio, Bioelectronics Handbook: MOSFETs, Biosensors and Neurons, McGraw-Hill, New York, 1998. 4. M. J. Sch¨oning and A. Poghossian, Recent advances in biologically sensitive field-effect transistors (BioFETs). Analyst, 2002, 127, 1137–1151. 5. P. Bergveld, Thirty years of ISFETOLOGY: what happened in the past 30 years and what may happen in the next 30 years. Sensors and Actuators, B, 2003, 88, 1–20. 6. Y. G. Vlasov, Y. A. Tarantov, and P. V. Bobrov, Analytical characteristics and sensitivity mechanisms of electrolyte-insulator-semiconductor system-based chemical sensors—a critical review. Analytical and Bioanalytical Chemistry, 2003, 376, 788–796. 7. P. K. Shin and T. Mikolajick, Alkali and hydrogen ion sensing properties of LPCVD silicon oxynitride thin films. Thin Solid Films, 2003, 426, 232–237. 8. F. Yan, P. Estrela, Y. Mo, P. Migliorato, H. Maeda, S. Inoue, and T. Shimoda, Polycrystalline silicon ion sensitive field effect transistors. Applied Physics Letters, 2005, 86, 53901–53903.
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS 9. A. Errachid, N. Zine, J. Samitier, and J. Bausells, FETbased chemical sensor systems fabricated with standard technologies. Electroanalysis, 2004, 16, 1843–1851. 10. C. G. Jakobson, U. Dinnar, M. Feinsod, and Y. Nemirovsky, Ion-sensitive field-effect transistors in standard CMOS fabricated by post processing. IEEE Sensor, 2002, 2, 279–287. 11. J. C. Chou, C. Y. Weng, and H. M. Tsai, Study on the temperature effects of Al2 O3 gate pH-ISFET. Sensors and Actuators, B, 2002, 81, 152–157. 12. A. Poghossian, H. L¨uth, J. W. Schultze, and M. J. Sch¨oning, (Bio-)chemical and physical microsensor arrays using an identical transducer principle. Electrochimica Acta, 2001, 47, 243–249. 13. A. Poghossian and M. J. Sch¨oning, Detecting both physical and (bio-)chemical parameters by means of ISFET devices. Electroanalysis, 2004, 16, 1863–1872. 14. S. Yoshida, N. Hara, and K. Sugimoto, Development of a wide range pH sensor based on electrolyte-insulatorsemiconductor structure with corrosion-resistant Al2 O3 Ta2 O5 and Al2 O3 -ZrO2 double-oxide thin films. Journal of the Electrochemical Society, 2004, 151, H53–H58. 15. J. L. Chiang, S. S. Jan, J. C. Chou, and Y. C. Chen, Study on the temperature effect, hysteresis and drift of pH-ISFET devices based on amorphous tungsten oxide. Sensors and Actuators, B, 2001, 76, 624–628. 16. Y. L. Chin, J. C. Chou, T. P. Sun, H. K. Liao, W. Y. Chung, and S. K. Hsiung, A novel SnO2 /Al discrete gate ISFET pH sensor with CMOS standard process. Sensors and Actuators, B, 2001, 75, 36–42. 17. J. C. Chou and L. P. Liao, Study of TiO2 thin films for ion-sensitive field-effect transistor application with RF sputtering deposition. Japanese Journal of Applied Physics, 2004, 43, 61–65. 18. L. T. Yin, J. C. Chou, W. Y. Chung, T. P. Sun, and S. K. Hsiung, Study of indium tin oxide thin film for separative extended gate ISFET. Materials Chemistry and Physics, 2001, 70, 12–16. 19. S. S. Jan, Y. C. Chen, and J. C. Chou, Effect of Mg2+ dopant on the characteristics of lead titanate sensing membrane for ion-sensitive field-effect transistors. Sensors and Actuators, B, 2005, 108, 883–887. 20. J. L. Chiang, Y. C. Chen, J. C. Chou, and C. C. Cheng, Temperature effect on AlN/SiO2 gate pH-ionsensitive field-effect transistor devices. Japanese Journal of Applied Physics, 2002, 41, 541–545. 21. Y. L. Chin, J. C. Chou, Z. C. Lei, T. P. Sun, W. Y. Chung, and S. K. Hsiung, Titanium nitride membrane application to extended gate field effect transistor pH sensor using VLSI technology. Japanese Journal of Applied Physics, 2001, 40, 6311–6315. 22. G. Steinhoff, M. Hermann, W. J. Schaff, L. F. Eastman, M. Stutzmann, and M. Eickhoff, pH response of GaN surfaces and its application for pH-sensitive field-effect transistors. Applied Physics Letters, 2003, 83, 177–179. 23. J. C. Chou and Y. F. Wang, Temperature characteristics of a-Si:H gate ISFET. Materials Chemistry and Physics, 2001, 70, 107–111. 24. J. A. Garrido, A. H¨artl, S. Kuch, M. Stutzmann, O. A. Williams, and R. B. Jackmann, pH sensors based on hydrogenated diamond surfaces. Applied Physics Letters, 2005, 86, 73504–73506.
13
25. W. Oelßner, J. Zosel, U. Guth, T. Pechstein, W. Babel, J. G. Connery, C. Demuth, M. Grote Gansey, and J. B. Verburg, Encapsulation of ISFET sensor chips. Sensors and Actuators, B, 2005, 105, 104–117. 26. W. Y. Chung, C. H. Yang, Y. F. Wang, Y. J. Chan, W. Torbicz, and D. G. Pijanowska, A signal processing ASIC for ISFET-based chemical sensors. Microelectronics Journal, 2004, 35, 667–675. 27. P. A. Hammond and D. R. S. Cumming, Performance and system-on-chip integration of an unmodified CMOS ISFET. Sensors and Actuators, B, 2005, 111 – 112, 254–258. 28. K. Y. Park, S. B. Choi, M. Lee, B. K. Sohn, and S. Y. Choi, ISFET glucose sensor system with fast recovery characteristics by employing electrolysis. Sensors and Actuators, B, 2002, 83, 90–97. 29. L. T. Yin, J. C. Chou, W. Y. Chung, T. P. Sun, K. P. Hsiung, and S. K. Hsiung, Glucose ENFET doped with MnO2 powder. Sensors and Actuators, B, 2001, 76, 187–192. 30. X. L. Luo, J. J. Xu, W. Zhao, and H. Y. Chen, A novel glucose ENFET based on the special reactivity of MnO2 nanoparticles. Biosensors and Bioelectronics, 2004, 19, 1295–1300. 31. X. L. Luo, J. J. Xu, W. Zhao, and H. Y. Chen, Glucose biosensor based on ENFET doped with SiO2 nanoparticles. Sensors and Actuators, B, 2004, 97, 249–255. 32. W. Sant, M. L. Pourciel, J. Launay, T. Do Conto, A. Martinez, and P. Temple-Boyer, Development of chemical field effect transistors for the detection of urea. Sensors and Actuators, B, 2003, 95, 309–314. 33. J. C. Chen, J. C. Chou, T. P. Sun, and S. K. Hsiong, Portable urea biosensor based on the extended-gate field effect transistor. Sensors and Actuators, B, 2003, 91, 180–186. 34. A. P. Soldatkin, J. Montoriol, W. Sant, C. Martelet, and N. Jaffrezic-Renault, A novel urea sensitive biosensor with extended dynamic range based on recombinant urease and ISFETs. Biosensors and Bioelectronics, 2003, 19, 131–135. 35. F. Aouni, R. Mlika, C. Martelet, H. Ben Ouada, N. Jaffrezic-Renault, and A. P. Soldatkin, Modelling of the potentiometric response of ENFETs based on enzymatic multilayer membranes. Electroanalysis, 2004, 16, 1907–1911. 36. A. V. Rebriiev and N. F. Starodub, Enzymatic biosensor based on the ISFET and photopolymeric membrane for the determination of urea. Electroanalysis, 2004, 16, 1891–1895. 37. D. Niwa, K. Omichi, N. Motohashi, T. Homma, and T. Osaka, Organosilane self-assembled monolayermodified field-effect transistors for on-chip ion and biomolecule sensing. Sensors and Actuators, B, 2005, 108, 721–726. 38. A. Poghossian, M. Thust, P. Schroth, A. Steffen, H. L¨uth, and M. J. Sch¨oning, Penicillin detection by means of silicon-based field-effect structures. Sensors and Materials, 2001, 13, 207–223. 39. A. Poghossian, M. J. Sch¨oning, P. Schroth, A. Simonis, and H. L¨uth, An ISFET-based penicillin sensor with high
14
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS sensitivity, low detection limit and long lifetime. Sensors and Actuators, B, 2001, 76, 519–526. W. Sant, M. L. Pourciel-Gouzy, J. Launay, T. Do Conto, R. Colin, A. Martinez, and P. Temple-Boyer, Development of a creatinine-sensitive sensor for medical analysis. Sensors and Actuators, B, 2004, 103, 260–264. A. L. Simonian, A. W. Flounders, and J. R. Wild, FET-based biosensors for the direct detection of organophosphate neurotoxins. Electroanalysis, 2004, 16, 1896–1906. A. L. Simonian, J. K. Grimsley, A. W. Flounders, J. S. Schoeniger, T. C. Cheng, J. J. De Frank, and J. R. Wild, Enzyme-based biosensor for the direct detection of fluorine-containing organophosphates. Analytica Chimica Acta, 2001, 442, 15–23. S. V. Dzyadevych, T. M. Anh, A. P. Soldatkin, N. D. Chien, N. Jaffrezic-Renault, and J. M. Chovelon, Development of enzyme biosensor based on pHsensitive field-effect transistors for detection of phenolic compounds. Bioelectrochemistry, 2002, 55, 79–81. A. P. Soldatkin, V. N. Arkhypova, S. V. Dzyadevych, A. V. El’skaya, J. M. Gravoueille, N. Jaffrezic-Renault, and C. Martelet, Analysis of the potato glycoalkaloids by using of enzyme biosensor based on pH-ISFETs. Talanta, 2005, 66, 28–33. J. Fritz, E. B. Cooper, S. Gaudet, P. K. Sorger, and S. R. Manalis, Electronic detection of DNA by its intrinsic molecular charge. Proceedings of the National Academy of Sciences, 2002, 99, 14142–14146. M. W. Dashiell, A. T. Kalambur, R. Leeson, K. J. Roe, J. F. Rabolt, and J. Kolodzey, The Electrical Effects of DNA as the Gate Electrode of MOS Transistors, In: Proceedings IEEE Lester Eastman conference on High Performance Devices, Delaware, 2002, pp. 259–264. D. S. Kim, Y. T. Jeong, H. K. Lyu, H. J. Park, H. S. Kim, J. K. Shin, P. Choi, J. H. Lee, G. Lim, and M. Ishida, Fabrication and characteristics of a field-effect transistortype charge sensor for detecting deoxyribonucleic acid sequence. Japanese Journal of Applied Physics, 2003, 42, 4111–4115. J. K. Shin, D. S. Kim, H. J. Park, and G. Lim, Detection of DNA and protein molecules using an FETtype biosensor with gold as a gate metal. Electroanalysis, 2004, 16, 1912–1918. D. S. Kim, Y. T. Jeong, H. K. Lyu, H. J. Park, J. K. Shin, P. Choi, J. H. Lee, and G. Lim, An FET-type charge sensor for highly sensitive detection of DNA sequence. Biosensors and Bioelectronics, 2004, 20, 69–74. D. S. Kim, H. J. Park, H. M. Jung, J. K. Shin, Y. T. Jeong, P. Choi, J. H. Lee, and G. Lim, Fieldeffect transistor-based bimolecular sensor employing a Pt reference electrode for the detection of deoxyribonucleic acid sequence. Japanese Journal of Applied Physics, 2004, 43, 3855–3859. F. Uslu, S. Ingebrandt, D. Mayer, S. B¨ocker-Meffert, M. Odenthal, and A. Offenh¨ausser, Label free fully electronic nucleic acid detection system based on a fieldeffect transistor device. Biosensors and Bioelectronics, 2004, 19, 1723–1731. F. Pouthas, C. Gentil, D. Cote, G. Zeck, B. Straub, and U. Bockelmann, Spatially resolved electronic detection of biopolymers. Physical Review E, 2004, 70, 31906–31913.
53. T. Ohtake, C. Hamai, T. Uno, H. Tabata, and T. Kawai, Immobilization of probe DNA on Ta2 O5 thin film and detection of hybridized helix DNA using ISFET. Japanese Journal of Applied Physics, 2004, 43, L1137–L1139. 54. T. Uno, T. Ohtake, H. Tabata, and T. Kawai, Direct deoxyribonucleic acid detection using ion-sensitive fieldeffect transistors based on peptide nucleic acid. Japanese Journal of Applied Physics, 2004, 43, L1584–L1587. 55. T. Sakata, M. Kamahori, and Y. Miyahara, Immobilization of oligonucleotide probes on Si3 N4 surface and its application to genetic field-effect transistor. Materials Science and Engineering, 2004, C 24, 827–832. 56. T. Sakata, M. Kamahori, and Y. Miyahara, DNA analysis chip based on field-effect transistors. Japanese Journal of Applied Physics, 2005, 44, 2854–2859. 57. T. Sakata, S. Matsumoto, Y. Nakajima, and Y. Miyahara, Potential behavior of biochemically modified gold electrode for extended-gate field-effect transistor. Japanese Journal of Applied Physics, 2005, 44, 2860–2863. 58. T. Sakata and Y. Miyahara, Detection of DNA recognition events using multi-well field effect devices. Biosensors and Bioelectronics, 2005, 21, 827–832. 59. K. Y. Park, M. S. Kim, and S. Y. Choi, Fabrication and characteristics of MOSFET protein chip for detection of ribosomal protein. Biosensors and Bioelectronics, 2005, 20, 2111–2115. 60. P. Estrela, P. Migliorato, H. Takiguchi, H. Fukushima, and S. Nebashi, Electrical detection of biomolecular interactions with metal–insulator–semiconductor diodes. Biosensors and Bioelectronics, 2005, 20, 1580–1586. 61. P. Bergveld, A critical evaluation of direct electrical protein detection methods. Biosensors and Bioelectronics, 1991, 6, 55–72. 62. A. Poghossian, A. Cherstvy, S. Ingebrandt, A. Offenh¨ausser, and M. J. Sch¨oning, Possibilities and limitations of label-free detection of DNA hybridization with field-effect devices. Sensors and Actuators, B, 2005, 111 – 112, 470–480. 63. M. Lehmann, W. Baumann, M. Brischwein, H. J. Gahle, I. Freund, R. Ehret, S. Drechsler, H. Palzer, M. Kleintges, U. Sieben, and B. Wolf, Simultaneous measurement of cellular respiration and acidification with a single CMOS ISFET. Biosensors and Bioelectronics, 2001, 16, 195–203. 64. L. Lorenzelli, B. Margesin, S. Martinoia, M. T. Tedesco, and M. Valle, Bioelectrochemical signal monitoring of in-vitro cultured cells by means of an automated microsystem based on solid state sensor-array. Biosensors and Bioelectronics, 2003, 18, 621–626. 65. M. Voelker and P. Fromherz, Signal transmission from individual mammalian nerve cell to field-effect transistor. Small, 2005, 1, 206–210. 66. S. Ingebrandt, C. K. Yeung, M. Krause, and A. Offenh¨ausser, Neuron-transistor coupling: interpretation of individual extracellular recorded signals. European Biophysics Journal, 2005, 34, 144–154. 67. S. Martinoia and P. Massobrio, ISFET-neuron junction: circuit models and extracellular signal simulations. Biosensors and Bioelectronics, 2004, 19, 1487–1496. 68. G. Wrobel, R. Seifert, S. Ingebrandt, J. Enderlein, H. Ecken, A. Baumann, U. B. Kaupp, and
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
A. Offenh¨ausser, Cell-transistor coupling: investigation of potassium currents recorded with p-and n-channel FETs. Biophysical Journal, 2005, 89, 3628–3638. C. K. Yeung, S. Ingebrandt, M. Krause, A. Offenh¨ausser, and W. Knoll, Validation of the use of field effect transistors for extracellular signal recording in pharmacological bioassays. Journal of Pharmacological and Toxicological Methods, 2001, 45, 207–214. S. Ingebrandt, C. K. Yeung, W. Staab, T. Zetterer, and A. Offenh¨ausser, Backside contacted field effect transistor array for extracellular signal recording. Biosensors and Bioelectronics, 2003, 18, 429–435. A. Cohen, M. E. Spira, S. Yitshaik, G. Borghs, O. Shwartzglass, and J. Shappir, Depletion type floating gate p-channel MOS transistor for recording action potentials generated by cultured neurons. Biosensors and Bioelectronics, 2004, 19, 1703–1709. M. J. Milgrew, M. O. Riehle, and D. R. S. Cumming, A large transistor-based sensor array chip for direct extracellular imaging. Sensors and Actuators, B, 2005, 111 – 112, 347–353. G. Steinhoff, B. Baur, G. Wrobel, S. Ingebrandt, A. Offenh¨ausser, A. Krost, M. Stutzmann, and M. Eickhoff, Recording of cell action potentials with AlGaN/GaN field-effect transistors. Applied Physics Letters, 2005, 86, 33901–33903. P. Wang, G. Xu, L. Qin, Y. Xu, Y. Li, and R. Li, Cell-based biosensors and its application in biomedicine. Sensors and Actuators, B, 2005, 108, 576–584. C. Jimenez, L. Moreno, C. de Haro, F. X. Munoz, A. Florido, P. Rivas, A. Bratov, and C. Dominguez, Development of a multiparametric system based on solid-state microsensors for monitoring a nuclear waste repository. Sensors and Actuators, B, 2003, 91, 103–108. A. Poghossian, L. Berndsen, and M. J. Sch¨oning, Chemical sensor as physical sensor: ISFET-based flowvelocity, flow-direction and diffusion-coefficient sensor. Sensors and Actuators, B, 2003, 95, 384–390. A. Poghossian, J. W. Schultze, and M. J. Sch¨oning, Application of a (bio-)chemical sensor (ISFET) for the detection of physical parameters in liquids. Electrochimica Acta, 2003, 48, 3289–3297. A. Poghossian, J. W. Schultze, and M. J. Sch¨oning, Multi-parameter detection of (bio-)chemical and physical quantities using an identical transducer principle. Sensors and Actuators, B, 2003, 91, 83–91. M. J. Sch¨oning, A. Poghossian, T. Yoshinobu, and H. L¨uth, Semiconductor-based field-effect structures for chemical sensing. Proceedings of the SPIE, 2001, 4205, 188–198. M. J. Sch¨oning, “Playing around” with field-effect sensors on the basis of EIS structures, LAPS and ISFETs. Sensors, 2005, 5, 126–138. M. J. Sch¨oning, A. Simonis, T. Krings, H. L¨uth, and J. Wang, Evaluation of a chip-based thin-film /thick-film sensor hybrid for (bio-)chemical analysis. Electroanalysis, 2002, 14, 955–958. M. J. Sch¨oning, D. Brinkman, D. Rolka, C. Demuth, and A. Poghossian, CIP (cleaning-in-place) suitable “nonglass” pH sensor based on a Ta2 O5 -gate EIS structure. Sensors and Actuators, B, 2005, 111 – 112, 423–429.
15
83. H. Barhoumi, A. Maaref, M. Rammah, C. Martelet, N. Jaffrezic-Renault, C. Mousty, S. Cosnier, E. Perez, and I. Rico-Lattes, Insulator semiconductor structures coated with biodegradable latexes as encapsulation matrix for urease. Biosensors and Bioelectronics, 2005, 20, 2318–2323. 84. D. Rolka, A. Poghossian, and M. J. Sch¨oning, Integration of a capacitive EIS sensor into a FIA system for pH and penicillin determination. Sensors, 2004, 4, 84–94. 85. N. N¨ather, D. Rolka, A. Poghossian, M. KoudelkaHep, and M. J. Sch¨oning, Two microcell flow-injection analysis (FIA) platforms for capacitive silicon-based field-effect sensors. Electrochimica Acta, 2005, 51, 924–929. 86. J. Wang, R. Krause, K. Block, M. Musameh, A. Mulchandani, P. Mulchandani, W. Chen, and M. J. Sch¨oning, Dual amperometric-potentiometric biosensor detection system for monitoring organophosphorus neurotoxins. Analytica Chimica Acta, 2002, 469, 197–203. 87. M. J. Sch¨oning, M. Arzdorf, P. Mulchandani, W. Chen, and A. Mulchandani, A capacitive field-effect sensor for the direct determination of organophosphorus pesticides. Sensors and Actuators, B, 2003, 91, 92–97. 88. M. Keusgen, M. J¨unger, I. Krest, and M. J. Sch¨oning, Development of a biosensor specific for cysteine sulfoxides. Biosensors and Bioelectronics, 2003, 18, 805–812. 89. M. Keusgen, J. P. Kloock, D. T. Knobbe, M. J¨unger, I. Krest, M. Goldbach, W. Klein, and M. J. Sch¨oning, Direct determination of cyanides by potentiometric biosensors. Sensors and Actuators, B, 2004, 103, 380–385. 90. A. Poghossian, D. T. Mai, Y. Mourzina, and M. J. Sch¨oning, Impedance effect of an ion-sensitive membrane: characterisation of an EMIS sensor by impedance spectroscopy, capacitance-voltage and constant-capacitance method. Sensors and Actuators, B, 2004, 103, 423–428. 91. M. J. Sch¨oning, A. Simonis, C. Ruge, H. Ecken, M. M¨uller-Veggian, and H. L¨uth, A (bio-) chemical field-effect sensor with macroporous Si as substrate material and a SiO2 / LPCVD-Si3 N4 double layer as pH transducer. Sensors, 2002, 2, 11–22. 92. A. Simonis, C. Ruge, M. M¨uller-Veggian, H. L¨uth, and M. J. Sch¨oning, A long-term stable macroporous-type EIS structure for electrochemical sensor applications. Sensors and Actuators, B, 2003, 91, 21–25. 93. S. Zairi, C. Martelet, N. Jaffrezic-Renault, F. Vocanson, R. Lamartine, R. M’gaieth, H. Maaref, and M. Gamoudi, P-type porous-silicon transducer for cation detection: effect of the porosity, pore morphology, temperature and ion valency on the sensor response and generalisation of the Nernst equation. Applied Physics A, 2001, 73, 585–593. 94. R. R. K. Reddy, I. Basu, E. Bhattacharya, and A. Chadha, Estimation of triglycerides by a porous silicon based potentiometric biosensor. Current Applied Physics, 2003, 3, 155–161. 95. M. J. Sch¨oning, N. N¨ather, V. Auger, A. Poghossian, and M. Koudelka-Hep, Miniaturised flow-through cell with integrated capacitive EIS sensor fabricated at wafer level
16
96.
97.
98.
99.
100.
101.
102.
103.
104.
105. 106.
107.
108.
109.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS using Si and SU-8 technologies. Sens Actuators B, 2005, 108, 986–992. D. G. Hafeman, J. W. Parce, and H. M. McConnell, Light-addressable potentiometric sensor for biochemical systems. Science, 1988, 240, 1182–1185. J. C. Owicki, L. J. Bousse, D. G. Hafeman, G. L. Kirk, J. D. Olson, H. G. Wada, and J. W. Parce, The light-addressable potentiometric sensor: principles and biological applications. Annual Review of Biophysics and Biomolecular Structure, 1994, 23, 87–113. F. Hafner, Cytosensor microphysiometer: technology and recent applications. Biosensors and Bioelectronics, 2000, 15, 149–158. T. Yoshinobu, H. Ecken, A. Poghossian, H. L¨uth, H. Iwasaki, and M. J. Sch¨oning, Alternative sensor materials for light-addressable potentiometric sensors. Sensors and Actuators, B, 2001, 76, 388–392. A. Poghossian, T. Yoshinobu, A. Simonis, H. Ecken, H. L¨uth, and M. J. Sch¨oning, Penicillin detection by means of field-effect based sensors: EnFET, capacitive EIS sensor or LAPS. Sensors and Actuators, B, 2001, 78, 237–242. T. Yoshinobu, H. Ecken, A. Poghossian, A. Simonis, H. Iwasaki, H. L¨uth, and M. J. Sch¨oning, Constantcurrent-mode LAPS (CLAPS) for the detection of penicillin. Electroanalysis, 2001, 13, 733–736. A. B. Md. Ismail, T. Harada, T. Yoshinobu, H. Iwasaki, M. J. Sch¨oning, and H. L¨uth, Investigation of pulsed laser-deposited Al2 O3 as a high pH-sensitive layer for LAPS-based biosensing applications. Sensors and Actuators, B, 2000, 71, 169–172. T. Yoshinobu, M. J. Sch¨oning, F. Finger, W. Moritz, and H. Iwasaki, Fabrication of thin-film LAPS with amorphous silicon. Sensors, 2004, 4, 163–169. W. Moritz, T. Yoshinobu, F. Finger, S. Krause, M. Martin-Fernandez, and M. J. Sch¨oning, High resolution LAPS using amorphous silicon as the semiconductor material. Sensors and Actuators, B, 2004, 103, 436–441. Q. Zhang, Theoretical analysis and design of submicronLAPS. Sensors and Actuators, B, 2005, 105, 304–311. W. Yicong, W. Ping, Y. Xuesong, Z. Qingtao, L. Rong, Y. Weimin, and Z. Xiaoxiang, A novel microphysiometer based on MLAPS for drugs screening. Biosensors and Bioelectronics, 2001, 16, 277–286. Yu. Ermolenko, T. Yoshinobu, Yu. Mourzina, S. Levichev, K. Furuichi, Yu. Vlasov, M. J. Sch¨oning, and H. Iwasaki, Photocurable membranes for ion-selective lightaddressable potentiometric sensor. Sensors and Actuators, B, 2002, 85, 79–85. T. Yoshinobu, H. Iwasaki, Y. Ui, K. Furuichi, Yu. Ermolenko, Yu. Mourzina, T. Wagner, N. N¨ather, and M. J. Sch¨oning, The light-addressable potentiometric sensor for multi-ion sensing and imaging. Methods, 2005, 37, 94–102. Yu. Mourzina, Yu. Ermolenko, T. Yoshinobu, Yu. Vlasov, H. Iwasaki, and M. J. Sch¨oning, Anion-selective light-addressable potentiometric sensors (LAPS) for the determination of nitrate and sulphate ions. Sensors and Actuators, B, 2003, 91, 32–38.
110. Yu. Mourzina, T. Yoshinobu, J. Schubert, H. L¨uth, H. Iwasaki, and M. J. Sch¨oning, Ion-selective lightaddressable potentiometric sensor (LAPS) with chalcogenide thin film prepared by pulsed laser deposition. Sensors and Actuators, B, 2001, 80, 136–140. 111. H. Men, S. Zou, Y. Li, Y. Wang, X. Ye, and P. Wang, A novel electronic tongue combined MLAPS with stripping voltammetry for environmental detection. Sensors and Actuators, B, 2005, 110, 350–357. 112. Yu. G. Mourzina, T. Yoshinobu, Y. E. Ermolenko, Y. G. Vlasov, M. J. Sch¨oning, and H. Iwasaki, Immobilization of urease and cholinesterase on the surface of semiconductor transducer for the development of lightaddressable potentiometric sensors. Microchimica Acta, 2004, 144, 41–50. 113. T. Yoshinobu, H. Ecken, A. B. Md. Ismail, H. Iwasaki, H. L¨uth, and M. J. Sch¨oning, Chemical imaging sensor and its application to biological systems. Electrochimica Acta, 2001, 47, 259–263. 114. W. Yicong, W. Ping, Y. Xuesong, Z. Gaoyan, L. Rong, Y. Weimin, Z. Xiaoxiang, H. Jinghong, and C. Dafu, Drug evaluations using a novel microphysiometer based on cell-based biosensors. Sensors and Actuators, B, 2001, 80, 215–221. 115. T. Yoshinobu, M. J. Sch¨oning, R. Otto, K. Furuichi, Yu. Mourzina, Yu. Ermolenko, and H. Iwasaki, Portable light-addressable potentiometric sensor (LAPS) for multisensor applications. Sensors and Actuators, B, 2003, 95, 352–356. 116. B. Stein, M. George, H. E. Gaub, and W. J. Parak, Extracellular measurements of averaged ionic currents with the light-addressable potentiometric sensor (LAPS). Sensors and Actuators, B, 2004, 98, 299–304. 117. A. B. Md. Ismail, T. Yoshinobu, H. Iwasaki, H. Sugihara, T. Yukimasa, I. Hirata, and H. Iwata, Investigation on light-addressable potentiometric sensor as a possible cell–semiconductor hybrid. Biosensors and Bioelectronics, 2003, 18, 1509–1514. 118. G. Xu, X. Ye, L. Qin, Y. Xu, Y. Li, R. Li, and P. Wang, Cell-based biosensors based on lightaddressable potentiometric sensors for single cell monitoring. Biosensors and Bioelectronics, 2005, 20, 1757–1763. 119. Z. Qintao, W. Ping, W. J. Parak, M. George, and G. Zhang, A novel design of multi-light LAPS based on digital compensation of frequency domain. Sensors and Actuators, B, 2001, 73, 152–156. 120. B. Stein, M. George, H. E. Gaub, J. C. Behrends, and W. J. Parak, Spatially resolved monitoring of cellular metabolic activity with a semiconductor-based biosensor. Biosensors and Bioelectronics, 2003, 18, 31–41. 121. M. J. Sch¨oning, T. Wagner, C. Wang, R. Otto, and T. Yoshinobu, Development of a handheld 16 channel pen-type LAPS for electrochemical sensing. Sensors and Actuators, B, 2005, 108, 808–814. 122. T. Wagner, C. Raoa, J. P. Kloock, T. Yoshinobu, R. Otto, M. Keusgen, and M. J. Sch¨oning, LAPS card—a novel chip card-based light-addressable potentiometric sensor (LAPS). Sensors and Actuators, B, 2006, 118, 33–40. 123. H. E. Katz, Chemically sensitive field-effect transistors and chemiresistors: new materials and device structures. Electroanalysis, 2004, 16, 1837–1842.
CHEMICAL AND BIOLOGICAL FIELD-EFFECT SENSORS FOR LIQUIDS 124. T. Kassab, Y. Han, A. Poghossian, S. Ingebrandt, A. Offenh¨ausser, and M. J. Sch¨oning, Detection of layerby-layer absorbed polyelectrolytes by means of fieldeffect based capacitive EIS structures. Biomedizinische Technik, 2004, 49, 1034–1035.
17
125. G. Maruccio, P. Visconti, A. Biasco, A. Bramanti, A. D. Torre, P. P. Pompa, V. Frascerra, V. Arima, E. D’Amone, R. Cingolani, and R. Rinaldi, Nanoscaled biomolecular field-effect transistors: prototypes and evaluations. Electroanalysis, 2004, 16, 1853–1862.
25 Overview of Optical Biosensing Techniques Ibrahim Abdulhalim,1 Mohammad Zourob2 and Akhlesh Lakhtakia3 1
Department of Electrooptics Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel, 2 Biosensors Division, Biophage Pharma, Montreal, Quebec, Canada and 3 Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, USA
1 INTRODUCTION
The development of optical biosensing technology is an extremely important scientific and technological issue for (i) the diagnosis and monitoring of diseases, (ii) drug discovery, (iii) proteomics, and (iv) the environmental detection of pollutants and/or biological agents. Traditionally, a biosensor is derived from the coupling of a ligand–receptor binding reaction to a transduction mechanism.1 In an optical biosensor, either the reaction product effects a significant change in the response of a transducer to incoming light or the reaction produces an optical signal that is sensed by the transducer, possibly after amplification and/or conversion to some other form (Figure 1). Optical biosensing has a wide scope nowadays: it encompasses optical methods for medical diagnosis2 and imaging, the most well-known of which are a variety of techniques to measure blood glucose concentration noninvasively using optics, such as by analyzing optical scattering from tissue, polarimetric measurement through fluids in the eye, optical coherence tomography, and skin optical imaging. Optical biosensors have seen tremendous advancement during the last two decades due to major developments in optics in general and optoelectronic components in particular, for example,
miniature light sources, optical fibers, materials, and optoelectronic devices.3–11 These advances have been backed by advances in computers and nanotechnology, thereby allowing for smart, miniature, and highly efficient sensors to be developed. The eventual manufacturing of large-scale arrays composed of highly miniaturized biosensing elements that enable the real-time, parallel monitoring of multiple species is an important driving force in biosensor research. Biosensors can be based on a variety of chemical or physical phenomena. Optical sensing has many advantages over nonoptical sensing modalities. Optical sensing schemes are sensitive. Singlemolecule sensing is possible due to the possibility for single-photon detection. Several light signals at different frequencies can be sent over the same optical beam because they do not interfere with one another. By measuring differences in wavelengths, arrival times, or polarization states, optical signals can be readily multiplexed and demultiplexed. Some optical techniques, such as fluorescence, have intrinsic amplification in which a single label can lead to a million photons. Surfaceenhanced techniques such as surface-enhanced Raman scattering (SERS) from molecules located near metallic nanoparticles allow sensing of small concentrations and the ability to recognize specific
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Light source
Analyte (biological, biochemical, or biophysical)
Incident light
Optical transducer
Detector
Output light
Figure 1. Schematic showing the main parts of an optical biosensor.
analytes in the sample. In addition, some optical techniques, such as surface plasmon resonance (SPR) and null ellipsometry, are zero- or blackbackground techniques: the only source of the signal is due to the presence of the analyte species, thereby enabling high-sensitivity measurements. Finally, optical signals travel in an open path; no wires or other transmitting conduits are needed, although the use of optical fibers may be sometimes necessary for nonoptical reasons and may have certain advantages. This attractive feature enables remote measurements to be made. Several optical-sensing mechanisms exist. These mechanisms are identified in Table 1, along with the variables measured. Several variations are possible on each of these mechanisms as well as combination of more than one optical measurement in the same setup. Another classification scheme for optical sensors involves the categories of materials, surfaces, and arrays. For instance, Table 1. Summary of the optical techniques and measured parameters used in biosensing
Technique Ellipsometry and polarimetry Absorption spectroscopy Elastic scattering
SPR Phosphorescence Raman scattering Guided-wave resonance Evanescent wave Interference
in a classification schemes based on materials, we might categorize sensors as based on porous materials, nanoparticles, quantum dots, photonic crystals, and so on. The need to simultaneously measure many analytes is satisfied by multiplexing several sensing elements together. Arrays containing tens of thousands and even hundreds of thousands of sensing elements are commonplace in DNA microarrays. Fluorescence is the main transduction mechanism used in most such microarrays. Indeed, the ability of simultaneously sensing many analytes has revolutionized the thinking of researchers working on biosensing in general and optical biosensing in particular. Single-analyte measurement is no longer considered sufficient for most sensing applications, as it gives only partial information about the sample. A variety of interesting and novel methods for fabricating arrays, coupled with intelligent signal processing, have been developed. Our goal in this chapter is to provide an overview of optical techniques for biosensing. In order to avoid duplication of the subjects in this handbook, the reader is referred to the specific chapters that deal with particular optical techniques in detail; however, details are provided on optical techniques that are not covered elsewhere in this handbook. Additionally, some new enabling technologies such as miniaturized spectrometers, nanomaterials, porous materials, sculptured thin films, and microresonators are reviewed.
2 SPECTROSCOPIC TECHNIQUES
Measured parameters Polarization state Intensity, spectrum, polarization dependence Intensity; angular, wavelength, and polarization dependences; correlation length Intensity, phase, peak position, polarization Intensity, wavelength, polarization state, lifetime Intensity, peak position, polarization state Intensity, resonance frequency Mode profile, intensity, spectrum Intensity, phase
2.1
The Revolution of Parallel Miniature Optical Spectrometers
Miniature optical spectrometers, introduced originally by Ocean Optics, have revolutionized optical spectroscopy with their parallel-processing performance. Diffraction grating-based spectrometers are used along with charge-coupled devices (CCD) or pin-diode arrays (PDAs) for light detection. The early models were just a fraction of the cost of spectrometers then available on the market. Today, tens of companies produce and sell many different models of such spectrometers for a wide variety of applications.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
Combined with fiber-optic technology, these spectrometers continue to be powerful and relatively inexpensive research tools. They are very compact and low in weight. They utilize universal serial bus (USB) technology, making them ideal for field use; for example, marine researchers have their spectrometers in waterproof housings to work with corals in their natural habitats, and other researchers use them for water-pollution measurements and plant-disease diagnostics in the field. The spectrometers have found applications in seas and oceans to measure fluorescence from marine organisms,12 around trees to measure the concentration of oxygen,13 in volcanoes for monitoring sulphur dioxide emissions,14 for analyzing the solar corona, and even to search for signs of life in simulated Mars missions.15,16 The majority of these spectrometers use the popular crossed Czerny–Turner configuration (Figure 2). Diffraction gratings are used to split incoming light into its spectral components. In order to avoid chromatic aberrations, curved mirrors are used to image the slit onto an array of detectors. For further miniaturization, some companies have started using gratings ruled on the curved mirror itself. The diffracted light falls upon the CCD array, and specialized software is then used to analyze and report spectral characteristics. As a grating’s efficiency is dependent on the (free space) wavelength, these spectrometers generally under-report the data at some wavelengths. Some diffraction gratings have their maximum efficiency at 500 nm and less, particularly
Curved mirror
Curved mirror
Diffraction gratings
Input slit
Detectors array
Figure 2. Schematic of the Czerny–Turner configuration commonly used in miniature spectrometers.
3
blue and red wavelengths. Ideally, one would use a reflectance standard along with the software to correct the spectrometer’s measurements, but that is not absolutely necessary. The data are easily exported to a spreadsheet program for further analysis. The use of fiber-optic cords offers advantages in that they can be tightly attached to the aperture (via SMA 905 terminated fibers), thereby protecting the internal parts of the spectrometer from any debris that may enter the spectrometer housing. The fiber-optic cords also offer other advantages. While it is apparent that cords are necessary for connecting optional accessories, the diameter of a cord is also a critical consideration. Very simply, the larger the diameter of the cord, the more light is transmitted. If high-intensity light saturates the CCD array and causes the reported intensity to be above the maximum allowed, a cord of smaller diameter could attenuate the signal sufficiently to allow measurement satisfactorily. Thus, an important consideration is the expected light intensity. In addition to the diameter of the fiber-optic cord acting as an intensity regulator, the diversity of available slit widths (5, 10, 25, 50, 100, and 200 µm) is beneficial. Low-light applications (such as the ones involving fluorescence measurements) require larger slit widths (say, 400 µm), while higher light intensity requires smaller slit widths. Low light-levels can be compensated by changing available integration time of a detector from a few microseconds to few hundreds of microseconds, and some spectrometers offer even up to a few seconds. On the other hand, optical resolution is a function of slit width and the resolving power of the diffraction grating. An optical resolution of just a fraction of a nanometer is possible, and subangstrom resolution maybe achieved almost effortlessly (with a 5-µm-wide slit and a dense diffraction grating) if the available light intensity is sufficient. However, the standard optical resolution is generally between 2 and 10 nm. High-resolution and highly sensitive spectrometers have just emerged for portable Raman spectroscopy, and are ideal for optical sensing in the field. The spectrometers can even be cooled and temperature-controlled for better stability and signal-to-noise ratio. Gratings with maximum efficiency in the near-infrared range are also possible: spectrometers for the 900–2200 nm range are available using CCDs
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
made of InGaAs with prices ranging from US $15K–25K. Biosensing as well as other biomedical applications have benefited significantly from these revolutionary developments in optical spectroscopy. Jobin-Yvon has introduced the only in vivo, fiberoptic spectrofluorometer designed specifically for skin-fluorescence measurements. This device uses a quartz-fiber bundle, which selectively delivers light in the ultraviolet to the near-infrared range to the sample and collects the resulting fluorescence. It is used to measure direct fluorescence from the skin, to evaluate cosmetic and pharmaceuticals, and to quantify drug delivery in photodynamic therapy (PDT).17 As a portable fluorescence spectrometer, it is also used to quantify trace contaminants for environmental monitoring. Multichannel computerized operation is possible, as shown in Figure 3, with each channel monitoring a single sample. An industrial computer system is available from StellarNet (www.stellarnet-inc.com) capable of providing 24-hour, nonstop service for process monitoring. For optical metrology, this spectrometer offers a high speed of processing, thus enabling high-throughput ellipsometry and reflectometry systems for inspection of semiconductor nanoelectronic fabrication processes. With this background, it is clear that miniature fast spectrometers have helped biosensing research and development significantly. But, even though their typical unit cost (few thousands of US dollars
and above) is only a fraction of the typical unit cost of classical bulky spectrometers, they are still too expensive for widespread use in homes, offices, and clinics. However, they are suitable as components in optical sensing systems that are expensive anyway. A further 10-fold reduction of their unit cost would enable the incorporation of these spectrometers in widely used, compact sensing devices. Technologies that can help achieve that goal include microelectromechanical systems (MEMS), nanotechnology, acousto-optics, or highspeed tunable liquid crystal filters, but all of these potential technologies are still too expensive for widespread use. Commercially available small spectrometers for the near-infrared and the visible ranges are often grating-based systems, each with an engine that is a few inches in each dimension. One type of spectrometer uses a linear, variable-band-pass optical filter instead of a grating. Several miniature spectrometers exploiting the technology of MEMS have also been either constructed or proposed, including some Fourier-transform spectrometers. A new design developed by Axsun Technologies18,19 based on MEMS technology uses an optical channel monitor that is commonplace in the telecommunications industry for monitoring dense wavelength-division multiplexing traffic. The spectrometer is a MEMS-based tunable Fabry–Perot filter operating in either a pre- or
Fiber Channel 1 spectrometer
Channel 2 spectrometer
Processor
Channel 3 spectrometer
Channel N spectrometer
Figure 3. Schematic of a multichannel spectrometer system.
Coupling lens
Sample
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
postdispersive mode (i.e., with the wavelengthselective device positioned either before or after the sample).
2.2
Absorption Spectroscopy in Biosensing
Optical absorption-based biosensors exploit many mechanisms ranging from pure resonant absorption of biomolecules to the use of SPR, which is engendered by absorption in thin metal films. Since the middle of the twentieth century, opticalabsorption spectroscopy has been used to detect pollutants in water.20–22 The oxymeter, used for measurement of oxygen saturation in blood hemoglobin,23 was among the first clinical optical absorption-based sensors. Techniques to enhance the effects of absorption have been developed such as the attenuated total internal reflection (ATIR) technique used for evanescent-wave sensing in the cladding of optical fibers and planar waveguides (PWs). Several schemes for absorption spectroscopy exist. The easiest and most widely used is the spectrophotometry, wherein quantitative determination of the absorbing species (chromophores) is done using optical spectroscopy from the ultraviolet to the infrared ranges. Spectrophotometry is used to measure absorption of various enzyme assays, and for the detection of proteins, nucleic acids, and metabolites.24 In spectrophotometry, the reference measurement is taken first using a well-known calibration sample, and then the transmittance through the sample is measured to yield the absorbance. This technique is thus based on the Beer–Lambert law A = ζ CL Incident laser pulse
(1)
where A = − log10 T is the absorbance (a desirable name for A is insertion loss, but that term is not in vogue) and T is the transmittance, ζ is the molar extinction coefficient in cm−1 mol−1 l−1 , C is the concentration in mol−1 l−1 , and L is the optical path length in cm. Since the reflectance from the sample is not very sensitive to the concentration, it can be either ignored or measured just once and then taken into account. The Beer–Lambert law is premised on the assumption of uniform concentration and discounts any dependence on the angle of incidence of light. Variations in concentration can occur, for example, due to dimerization of chromophore molecules at higher concentrations (provided the ζ value for the dimer is different from that for the monomer), thus causing a nonlinear dependence of the absorbance A on the concentration C. Another approach is the cavity ring-down technique25 in which light pulses of duration shorter that the round-trip time inside a cavity are launched into the cavity, and the transmitted pulses after each round trip are monitored with a detector and an oscilloscope (Figure 4). Since each of the injected photons bounces back and forth in the resonant cavity for a certain interval of time before it is absorbed, the transmitted photons are delayed on the average by the ring-down time of the cavity, thereby shifting the phase of the transmitted light. This phase shift is inversely related to the sum of the reflection losses in the cavity, which can be determined to a precision of the order of 100 ppm/round trip. If the cavity is filled with an absorbing medium and the mirror loss is assumed to be negligible, the system becomes an absorption spectrometer. For a cavity length of 1 m, the 100-ppm/round trip precision translates to a minimum detectable absorbance of ≈10−6 cm−1 . The major limitation Transmitted train of pulses
Analyte inside cavity
Mirror
5
Mirror
Figure 4. Schematic of a cavity ring-down absorption spectroscopy setup.
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
on the precision of this technique is the noise in the transmitted beam, which affects the determination of the phase of the transmitted beam; practical limitations on the signal integration time restrict this approach to precision on the order of 50 ppm/pass. For a uniform absorber, the intensity of the transmitted signal decays exponentially with time as −t I = I0 exp (2) τ where I0 is a reference intensity, and τ = l/{c(1 − R + Y + αl)} is the decay constant with R being the cavity mirror’s reflectance, Y the mirror loss, α the absorption coefficient of the analyte, c the speed of light in free space, and l the cavity length supposed to be filled by the analyte. The absorbance is determined as l 1 1 A= (3) − 2.303c τ τe where τe is the decay time when the cavity is without the analyte. Alternatively the absorption coefficient of the analyte can be determined from the ratio between the two decay times if the mirrors losses are neglected or measured separately. The presence of noise in the transmitted beam is intrinsic to the foregoing technique. Fabry–Perot analysis shows that transmission will occur only when one of the laser modes (which occur at integer multiple frequencies of c/2l, where l is the length of the probe laser cavity) matches the frequency of one of the cavity modes. Since the two cavity lengths vibrate independently, the modes of the two cavities match up periodically to permit some transmission, but at random times. Although the phase shifts of the individual transmitted photons are fixed, the phase of the transmitted beam is obscured by the random-intensity noise. Anderson et al.26 addressed this problem by configuring the detection electronics in a triggered mode of operation and waiting for the modes to overlap before starting the data-acquisition procedure. The detector monitoring the transmitted beam triggers on the electronics when longitudinal mode-matching has occurred in one of these coincidences, thereby permitting the intensity to build up in the test cavity so that a signal is observed on transmission. Triggered by the “light is present” observation at the detector, a fast optical switch then shuts off the
probe laser beam, and the ring-down time is measured. The sum of the losses in the test cavity is related to the ring-down time. A precision of about 5 ppm has been demonstrated with this method. Although this reconfiguration of the electronic circuitry reduces the noise, the problem of the random mode-coincidences remains, producing thereby intensity fluctuations, intermittent delays between successive signals, and occasional nonexponential decays. O’Keefe et al.27 proposed a technique which allows measurement of the decay time of the test cavity, but avoids the problems associated with the requirement of longitudinal mode coincidences by using short optical pulses so that every pulse of the probe laser enters the cavity with no additional intensity fluctuation or time delay. This results in improved sensitivity and higher data rate, and also significantly relaxes the requirements on the stability of the system. Another enhancing technique is the ATIR technique or the evanescent-wave absorption technique. Use of ATIR in waveguides and optical fibers increases the interaction length between the evanescent field and the analyte present in the region of evanescence. Fibers made of crystalline silver halide have been used recently, as they are excellent for Fourier spectroscopy in the infrared range.28 This is because the fiber’s surface does not need any protection jacket and the fiber’s transmission range of 4000–600 cm−1 overlaps with the majority of spectral absorption lines of organic molecules. The sensors are based on evanescentwave spectroscopy (the region of evanescence is about 5–10 µm in thickness) wherein resonant absorption of the evanescent light results in dips in the fiber’s transmittance spectrum. The absorption spectral lines are characteristic of the analyte material and have modulation depths corresponding to analyte concentration. One of the major advantages of fiber-based ATIR sensors is that they enable remote chemical analysis in real time. Another significant advantage is that the mechanical robustness of fibers allows their use many times for probing.
2.3
Fluorescence Techniques
Fluorescence is the most widely used technique in analytic instruments. The large number of applications ranges from analytic measurement of metals
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
in aqueous environments to pH measurements in living cells. Fluorescence spectroscopy is also a powerful laboratory tool, both for applied research and for fundamental studies of physical processes in molecules and interactions between biomolecules such as proteins and nucleic acids. In clinical laboratories, the use of fluorescence is dominant for the determination of analyte concentration; indeed, fluorescence immunoassays have largely replaced radioimmunoassays. The high levels of sensitivity and dynamic range are responsible for this dominance, and many laboratories have reported the detection of single molecules. In fluorescence, the incident light is completely absorbed and the molecule is transferred to an excited state from which it can go to various lower states only after a delay quantified by the resonance lifetime.29 Dependence on the polarization state of the incident light is exhibited when the molecules lack spherical symmetry and there is some orientational order. A technique called polarized fluorometry is therefore becoming popular for detecting various analytes. Information on the lifetimes and the dynamic decay of the fluorescence signal provides another important tool, called time-resolved fluorescence, for detection and identification of analytes. Applications of fluorescence in biology and medicine are numerous and significant. Fluorescence techniques play a critical role in the description of biological processes at the molecular and cellular levels. Endogenous and exogenous fluorescent molecules are used as specific markers of metabolic status or disease processes. Fluorescent particles are used as contrast agents for the study of transport phenomena (e.g., blood) in biological media. The successes reported are for transparent media or in tissue when the analyte is located close to the surface. Most biological tissues scatter light so strongly, however, that even special techniques to remove multiply scattered light (such as two-photon and confocal microscopies) fail at depths greater than 0.5 mm below the tissue surface. A complicating factor is the strong attenuation of light as it passes through tissue that degrades the signal-to noise ratio of detected photons. Fortunately, development of fluorescent dyes (such as porphyrin and cyanine) that excite and reemit in the “biological window” at near-infrared wavelengths, where
7
scattering and absorption coefficients are relatively low, has opened new possibilities for deep fluorescence imaging in tissue.30 The instrumentation required is usually not very expensive and can be combined with other instruments such as confocal microscopes and spectrometers. The fluorescence setup consists of a light source, an excitation-wavelength filter, a sample holder, an emission-wavelength filter, and a photodetector that converts any emitted fluorescence photons into an electronic signal. The excitation wavelengths lie usually from the ultraviolet (200 nm) to the visible range (650 nm), corresponding to the electronic energy levels in the outer shells of atoms. Mercury arc lamps are usually satisfactory but can produce only a limited number of wavelengths in the ultraviolet to the visible range (e.g., 253.6, 302.2, 313.2, 365, 404.7, 435.8, and 546.1 nm). Most fluorometers use a high-pressure xenon arc lamp since it has a continuous high intensity spectrum between 200 and 1000 nm wavelength; and pulsed lamps with power of 75 W deliver high-enough peak power to enable high fluorescence signals. Fluorescence parameters that are characteristic of the fluorescent material and its surrounding can be used as signatures that can be correlated with the analyte. Examples include the lifetime and the fluorescence anisotropy. Fluorescence-lifetime imaging (FLIM) is becoming nowadays a popular technique for biological imaging. Time-resolved measurement techniques use pulsed exciting light (usually in the nanosecond range) and then analyze the decay of the emitted pulses. Another possibility is to modulate the exciting light at a certain frequency and then measure the delay time and demodulation of the emitted signal. For fluorescence-anisotropy measurement, linearly polarized excitation light is used while the intensity of emitted signal is measured with the analyzer axis parallel (I|| ) and perpendicular (I⊥ ) to the exciting polarization. The degree of fluorescence anisotropy is defined as a=
I|| − I⊥ I|| + 2I⊥
(4)
wherein the denominator on the right side represents the total fluorescence intensity. The fluorescence anisotropy is a measure of the rotational motion or dynamics of the analyte molecule, which
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
is important in obtaining flexibility parameters of local segments of macromolecules. Another technique is a combination between the polarization anisotropy and time-resolved measurement. This is called the polarized excitation and emission decay technique: the sample is excited using vertically polarized light, and the horizontally as well as the vertically polarized components of the fluorescence decay are separately recorded. The observed decay in the intensity of either of the linearly polarized component is due both to (i) the decrease in size of the population of excited molecules and (ii) the tumbling motion of each molecule, which reorients the transition dipole moment between absorption and emission and so changes the intensity of the light observed using a particular orientation of the emission polarizer. Hence, the polarized fluorescencedecay components contain information about the dynamical motion of the molecules. An interesting way to improve the fluorescence uses the evanescent-field technique relying on total internal reflection (TIR). First described by Hirschfeld31 in 1965, evanescent-field excitation was first used by Kronick and Little32 for fluorescence immunoassays. Total internal reflection fluorescence (TIRF) is a means to selectively excite light emission from fluorophores present near the surface of a waveguide and is relatively immune to the bulk effects. Several studies have been conducted on the use of TIRF for the detection of a single biomolecule. Ligler and coworkers33 investigated multianalyte fluorescence detection using PWs. Plowman et al.34 reported femtomolar sensitivity of fluoro-immunoassay using a dual-channel waveguide. A commercially available product, the Zeptosens reader (Zeptosens, Bayer Tech. Services GmbH) uses the evanescent
field to excite fluorescence in the near-interface region of a microarray chip and has sensitivity down to picomolar concentration (which is equivalent to zeptomoles of captured antibodies).35 There are several advantages to the use of PWs such as independence from the molecular weight of the analyte unlike refractive-index-based techniques, relative ease of preparation, possibility of creating arrays of different recognition molecules using different techniques (e.g., photolithography and ink-jet printing), and integration with fluidic systems. The major disadvantage of using TIRF systems is the requirement of a fluorescent label that should ideally be so selective as to not interfere with the binding interactions of the analyte. Labeling of the analyte with a fluorescent dye is a method for enhancing the signal from the analyte to ensure specific measurements or to ensure both specific detection and amplification of the signal from the specific analyte. Three different major assay formats (direct binding, competitive, and sandwich assays), as shown in Figure 5, have been used. In the direct assay format (Figure 5a), first the recognition molecules are immobilized on the surface of the waveguide and then a fluorescence signal is emitted when analyte molecules with fluorescent labeling bind to the recognition molecules. The competitive assay format (Figure 5b) is normally used in immunoassays for small molecules containing a single epitope (which is the part of a macromolecule that is recognized by the immune system, specifically by antibodies, B cells, or cytotoxic T cells). This format is classified into two subformats. In the first subformat, unlabeled and labeled analytes compete for binding to the immobilized recognition molecules on the waveguide’s surface, and the
Fluorescence-labeled antibody Fluorescence-labeled analyte Analyte Antibody (a)
(b)
(c)
Figure 5. Schematics of the main three formats of solid-phase immunoassays: (a) direct assay between the analyte in solution to the immobilized antibody (recognition molecules), (b) competitive assay between the fluorescently labeled (known concentration) and unlabeled (unknown concentration) antigen for the binding sites of the immobilized antibody, and (c) sandwich assay in which the analyte is put between immobilized antibody and secondary labeled antibodies.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
decrease in the fluorescence signal is proportional to the proportion of the unlabeled analyte. The second requires that the recognition molecules be present in the solution and an analog of the analyte be immobilized on the optical waveguide. The sandwich assay format (Figure 5c) is commonly used for large molecules and requires secondary fluorescent recognition species. This fluorescent secondary recognition molecule is used to detect an analyte that has been captured by immobilized recognition element on the waveguide’s surface. The sandwich and the competitive assay formats are the most commonly used in the immunoassays using PWs. A technique using the evanescent field from a planar waveguide to excite fluorescence near interface region is called waveguide excitation fluorescence microscopy (WEFM ). The use of WEFM to imaging biointerfaces shows a 10-fold improvement in sensitivity in comparison to conventional fluorescence microscopy.36,37 WEFM has been integrated with other techniques such as AFM, SNOM, magnetic tweezers, and optical tweezers for dynamic in situ studies of single molecules at interfaces.
2.4
Raman Spectroscopy for Biosensing
Raman spectroscopy is a form of electronic (more accurately, vibronic) spectroscopy. Classically, the Raman effect arises when a photon incident on a molecule interacts with the molecule’s induced dipole moment, which is proportional to the polarizability change during the molecule’s vibration.38 Quantum mechanically, the interaction is viewed as a scattering event that occurs in 10 fs or less, and the scattering is described as an excitation to a virtual state lower in energy than a real electronic transition with nearly coincident de-excitation and a change in vibrational energy. The energy difference between the initial and final vibrational levels is called the Raman shift −1 ν¯ = λ−1 incident − λscattered
(5)
where λincident and λscattered are the wavelengths (in cm) of the incident and the Raman-scattered photons, respectively. Raman shifts range from a few hundred per centimeter (615–630 cm−1 for
9
ring deformation) to a few thousand per centimeter (3300–3400 cm−1 for bonded antisymmetric NH2 stretch in primary amines). Because only a small fraction of the incident photons is scattered inelastically (1 in 107 photons), the intensity of Raman scattering is low; hence, the accompanying thermal dissipation does not cause a measurable temperature rise in the analyte material. Various Raman techniques have been attempted to analyze blood, water, serum, plasma solutions, skin cancer, and the eye, but many problems remain before tissue diagnosis and blood chemicals analysis in vivo and in real time can be performed.39 Implementation problems include (i) instabilities in the laser wavelength and intensity and (ii) errors due to other chemicals in the tissue sample and long spectral acquisition times. Most importantly, the inherent difficulty of Raman spectroscopy is that its signals are very weak, Raman scattering having an intensity about a 1000th of that of Rayleigh scattering. With the replacement of slow photomultiplier tubes by faster CCD arrays and the manufacture of higher-power near-infrared laser diodes, that inherent difficulty is being alleviated. As mentioned in Section 2.1, miniature fiber-based spectrometers are already commercially available with a reasonable price in the range US $15K–25K. These spectrometers are suitable for Raman measurements. Although their resolution is relatively low (2–4 cm−1 ), they are useful for many biosensing applications because the Raman peaks of molecules in solution or in biological environment are broadened.40 For in vivo tissue studies, an infrared laser is generally used as the excitation source to minimize the background fluorescence. However, the inherent weakness of the Raman signal creates the needs for very high excitation intensity and relatively long signal-collection time; therefore, photothermal damage of the tissue is of great concern for in vivo measurements. Specificity is the most important requirement for an acceptable multicomponent blood analysis: signals from different blood constituents should be distinguishable from each other for independent quantification. Raman spectroscopy is well suited to this requirement. A significant advantage of Raman spectroscopy over near-infrared absorption spectroscopy is that the former’s spectrum
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
has distinct and pronounced peaks, thereby easing the task of separating signals produced by the analytes of interest. In contrast, absorption, scattering and polarimetry techniques in the near-infrared range should be thought of as purely empirical methods that rely heavily on statistical multivariate analysis. Another significant factor to consider is stability, that is, the sensitivity of the technique to disturbances or noises. The most significant noise that has been a problem for near-infrared absorption and scattering methods is the variability of the skin temperature. Raman spectra have been found to be not as sensitive to temperature changes as the near-infrared absorption and scattering spectra. Thus, Raman spectroscopy is one of the most promising techniques for accurate and reliable quantification of the many constituents of blood. The Raman spectra have sharp and distinct peaks, thereby allowing greater discrimination among closely spaced signals and, consequently, more accurate extraction of concentrations from the spectral data. However, Raman spectroscopy is still faced with several critical problems some of which are being overcome by the incorporation of miniature spectrometers and light sources and by using enhancement mechanisms explained in the following subsection. 2.5
Surface-enhanced Optical Phenomena
2.5.1 Nanoenhancement of Surface Plasmon Sensitivity (LSPR Technique)
Several research groups are now exploring alternative strategies for optical biosensing and chemical sensing based on the extraordinary optical properties of nanoparticles made of noble metals. Nanoscale chemosensors and biosensors can be realized through shifts in the localized surface plasmon resonance (LSPR).41–45 A LSPR nanobiosensor, based on LSPR spectroscopy, operates in a manner totally analogous to an SPR sensor by transducing small changes in the refractive index near a noble-metal surface into a measurable wavelength shift as follows46–48 : λmax = m(nadsorbate − nblank ) 2dadsorbate × 1 − exp − ld
(6)
Here, m is the refractive-index sensitivity of the sensor; nadsorbate and nblank are the refractive indices of the adsorbate (i.e., analyte) and the bulk environment prior to the sensing event, respectively; dadsorbate is the effective thickness of the adsorbate layer; and ld is the characteristic electromagnetic field decay length associated with the sensor. While the responses of the LSPR and SPR sensors can be described via the same equation, the sensitivities of the two techniques arise from different experimental parameters.49–52 Flatsurface SPR sensors have a large refractive-index sensitivity (∼2 × 106 nm/RIU, where RIU stands for “refractive index unit”), which is the chief component of their overall sensitivity.53 LSPR nanosensors have modest refractive-index sensitivity (∼2 × 102 nm/RIU),54 in contrast. Nevertheless both types of sensors have approximately equivalent sensitivity for a given adsorbate. In addition to the difference in refractive-index sensitivity, the electromagnetic field decay length ld is also different for SPR and LSPR sensors. SPR sensors have a decay length in the order of ∼200 nm. For LSPR nanosensors using noble-metal nanoparticles, a much shorter electromagnetic field decay length (∼6 nm) has been measured.55 The shorter decay length gives rise to the larger overall sensitivity of LSPR nanosensors. In contrast to the conventional SPR technology, LSPR technology promises multiplexed, high-throughput screening platforms in a highly miniaturized format, requiring small volumes (e.g., attoliters) of analyte solutions. The sensitivity is a few orders of magnitudes better than that of the conventional SPR sensors without metallic nanostructures. In addition, LSPR technology does not require precise controls of the angle of incidence and the ambient temperature, both of which are necessary for the conventional SPR technology. As the measurements are noninvasive in nature, the LSPR platforms are ideal for in vivo quantification of chemical species and the monitoring of dynamic processes inside biological cells. LSPR sensors can be divided into three broad groups: (i) those based on monitoring changes in the relative permittivity of the immediate environment, (ii) those based on changes in SP coupling, and (iii) those exploiting a combination of these two effects.56 The first group of
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
LSPR sensors were implemented for the detection of hexadecanethiol down to zeptomolar sensitivity by monitoring changes in the resonant Rayleigh scattering.57 The second and the third groups were demonstrated for many chemical and biosensing applications by monitoring the changes in LSPR band of metal nanostructures upon analyte binding, using standard spectrophotometric instruments in the transmission mode.58 The advantage of LSPR sensing in the transmission configuration over conventional SPR sensing is a simple experimental procedure that involves measurement just at one wavelength. This simplicity enables the development of disposable LSPR sensors for personal medicine and field applications.
2.5.2 Resonant Raman Effect (RRE) and Surface-enhanced Raman Scattering (SERS)
Four mechanisms are used to enhance the Raman signal59–61 : (i) stimulated Raman scattering due to the excitation of analyte molecules by a high energy pulse (optical electric field of strength ∼109 V cm−1 ); (ii) coherent anti-Stokes Raman scattering (CARS) due to excitation with two strong collinear laser beams having frequency difference equal to the frequency of a Raman peak; (iii) resonant Raman effect (RRE) caused by excitation with photon energies corresponding to resonant energies within the electronic spectrum of the analyte molecules; and (iv) SERS, when the analyte molecules in close proximity (fraction of nanometers) of metallic nanoparticles are excited. The last two mechanisms are the ones that are mostly used for optical biosensing. The RRE increases the intensity of some Raman-active vibrations by a factor of 102 –105 . This effect occurs when the excitation-laser frequency is chosen in such a way that it crosses the frequencies of excited electronic states and resonates with them. The enhancement factor increases when the molecular expansion along its axis of vibration is higher as it absorbs photons. Formally, one can think of the Raman transition probability being proportional to the elements of the polarizability tensor of a bound electron; as the exciting frequency approaches the
11
resonance frequency, these elements are enhanced in a Lorentz model of the bound electron. A common example of this mechanism is furnished by the ring-breathing (in-plane expansion) modes of porphyrins. Another mechanism, called vibronic enhancement, involves vibrations which couple two electronic excited states. In both mechanisms, the enhancement factors are nearly proportional to the intensities in the absorption spectrum of the adsorbate. The enhancement does not begin at a sharply defined wavelength. In fact, enhancement by factor of 5–10 is usually observed if the wave number of the exciting laser is only within a few hundred per centimeter below the electronic-transition wave number of the analyte molecule. SERS is the second relevant enhancement mechanism. The Raman scattering from a compound (or ion) adsorbed on or even within a few angstroms of a structured metal surface can be enhanced by factor of 103 –1014 compared to the case when it is in a solution. SERS is strongest on a silver surface, but is observable on gold and copper surfaces as well, and it is now known that the shape of the nanoparticle plays a crucial role in determining the enhancement factor. So far, the triangular-pyramid shape has been found to give the strongest enhancement. Although a complete understanding of SERS has not been achieved yet, two main mechanisms are widely accepted. The first, called chemical enhancement, involves enhancement of polarizability of the analyte molecule that may occur because of a charge-transfer effect or chemical bond formation between the metal surface and the analyte molecules. The second is due to the enhanced electromagnetic field produced at the surface of the metal when the wavelength of the incident light matches the SPR wavelength of the metal. Molecules adsorbed or in close proximity to the metal surface experience an exceptionally large electric field. Because the Raman effect is proportional to the fourth power of the field amplitude, the efficiency is enhanced by factors as large as 1014 . Molecular vibrational modes normal to the metal surface are most strongly enhanced in comparison to other vibrational modes. Electromagnetic simulations confirm that the electric field can be enhanced62,63 by a factor of 103 and
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
so the Raman signal is enhanced by a factor of 1012 . For a spherical nanoparticle whose radius is much smaller than the wavelength of light, the electric field is uniform across its dimensions, and the electrostatic (Rayleigh) approximation suffices to explain the enhancement. More generally, the field induced at the surface of a spheroidal nanoparticle (with major and minor semi-axes of lengths L and S) is related to the applied external field as ε1 (ω) − ε2 (ω) Einduced = Elaser (7) ε1 (ω) + χε2 (ω) where ε1 (ω) is the complex-valued, frequencydependent, relative permittivity scalar of the metal, ε2 (ω) is that of the ambient material, ω is the angular frequency, and χ is a geometrical factor that depends on the shape of the nanoparticle. The factor χ equals 2 for a sphere, but χ is larger than 2 for prolate spheroids (L > S) and less than 2 for oblate spheroids (L < S). SPR greatly increases the local field experienced by a molecule adsorbed on the surface of the nanoparticle, when Re{ε1 (ω) + χε2 (ω)} = 0. One can visualize this phenomenon by considering the nanoparticle as localizing the electric field of a dipole field centered in the sphere, which then decays with the dipole decay law away from the surface in all directions. In this sense, the nanoparticle acts as an antenna which amplifies the intensity of the scattered light. When χ is greater than 2, the plasmon resonance condition Re{ε1 (ω) + χε2 (ω)} = 0 is satisfied for a wavelength that lies to the red of that for a sphere (due to the fact that the real part of ε1 of metals is, according to equation (7), more negative for longer wavelengths). Of course, this also means that for oblate spheroids, the resonance is blueshifted relative to a sphere. However, the resonance described here refers to an incident field with the electric field polarized parallel to the axis of symmetry of the spheroidal nanoparticle. There is another plasmon resonance associated with the incident electric field polarized perpendicular to the symmetry axis. This resonance is identical in frequency to the parallel resonance for a sphere, but it shifts in the opposite direction for a spheroid, that is, blueshifting for prolate spheroids and redshifting for oblate
spheroids. The parameter χ for the two cases of parallel and perpendicular polarization is given by59 χ|| =
χ⊥ =
2 − 1 (8) ξ +1 −2 (ξ 2 − 1) ξ ln ξ −1 −2 −1 ξ +1 − 2ξ 2 ξ(ξ 2 − 1) ln ξ −1
(9)
where ξ = (1 − S 2 /L2 )−1/2 . The signal enhancement is so dramatic that very weak Raman peaks that are unnoticeable in spontaneous Raman spectra can appear prominently enough in the SERS spectra. Some trace contaminants can also contribute additional peaks. Moreover, because of chemical interactions with metal surfaces, certain peaks that are strong in conventional Raman spectra might not be present in the SERS spectra at all. The nonlinear character of signal intensity as a function of the concentration complicates things even further. Very careful consideration of all physical and chemical factors must be made while interpreting SERS spectra, which makes it extremely impractical. Because of such complications, the surfaceenhanced resonance Raman spectroscopy (SERRS) was developed. As it exploits the best features of both the SERS and the RRE, the resulting enhancement of the Raman signal intensity can be as high as 1014 . Additionally, the SERRS spectra resemble the regular RRE spectra, which make the former much easier to interpret. SERS was discovered with pyridine. Other aromatic nitrogen- or oxygen-containing compounds, such as aromatic amines or phenols, also display strong enhancement due to SERS. The enhancement can also be seen with other electron-rich analytes such as carboxylic acids. Although SERS allows easy observation of Raman spectra from solutions with concentration in the micromolar (10−6 ) range, slow adsorption kinetics and competitive adsorption limit its application in analytical chemistry. The SPR intensity is dependent on many factors, including the wavelength of the incident light and the morphology of the metal surface. The Raman excitation wavelength should match the plasma wavelength of the metal, which is about 382 nm
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
for a 5 µm silver particle but can be as high as 600 nm for larger ellipsoidal silver particles. The plasma wavelength shifts to 650 nm for copper and gold, the other two metals that are used for SERS at wavelengths in the range from 350 to 1000 nm. The best modality for SPR excitation is the use of either a nanoparticle (<100 nm diameter) or an atomically rough surface. SERS is used to study monolayers of materials adsorbed on metal substrates. Although the substrates are often used as electrodes, a wide variety of substrate formats have been found to exhibit SERS: electrochemically modified electrodes,64 colloids, island films, particles grafted on silanized glasses,65–67 and more recently, regular particle arrays.68 Thin films of tilted nanorods of silver, grown by directing silver vapor obliquely at some planar surface, have been applied recently69,70 to virus detection as they exhibited SERS enhancement on the order of 108 . Nanorod assemblies of this type fall into the category of sculptured thin films discussed in Section 3.7. A pH sensor was reported recently71 using SERS spectra of monolayers of para-mercaptobenzoic acid (pMBA) adsorbed on gold nanoshells. The pMBA molecule has a pH-sensitive SERS response. The developed all-optical nanosensor is capable of measuring pH in the vicinity of the molecule continuously over the 5.8–7.6 range at near-infrared wavelengths with an accuracy better than 0.1. Magnetic nanoparticles modulated by a rotating magnetic field were shown recently72 to emit modulated fluorescence signals that may be used to detect analytes dissolved in water. A pH sensing possibility was shown to be possible from the blinking signal.
2.5.3 Surface-enhanced Fluorescence (SEF)
In a similar manner to LSPR and SERS, when fluorophores (fluorescent analyte molecules) are in close proximity to metal nanoparticles,73 the fluorescence intensity is enhanced and the fluorescence lifetime is lowered.74–77 These surface-enhancedfluorescence (SEF) effects occur because the excited fluorophores interact with freely mobile electrons in the metal, thereby resulting in increased rates of radiative decay; similar interactions with the LSPR have been the subject of theoretical analysis and are closely related to the SERS
13
mechanisms.78–80 SEF has been demonstrated on different fluorophores and suggested as a method to enhance in vivo imaging.81 Enhancement of fluorescence has also been reported on nanoscale ZnO platforms.82
2.6
Ellipsometry and Polarimetry
Ellipsometry and polarimetry are techniques for measuring the polarization state of light either reflected off or transmitted through a sample.83,84 Both techniques use similar configurations in which the sample is positioned between a polarizer and analyzer; sometimes compensators and polarization modulators can be added, depending on the setup. Ellipsometry is more widely used to measure the optical properties of thin films, whereas polarimetry is used to measure retardation and Stokes parameters from anisotropic and scattering samples. In ellipsometry, the sample in the form of a slab with two parallel plane faces is characterized by its ellipsometric angles ψ and defined as follows: rp rp tan ψ = = arg (10) rs rs Here, rp,s are the Fresnel reflection coefficients for incident p- and s-polarized light respectively, for a given angle of incidence. Ellipsometric measurements over a range of wavelengths or incident angles allow samples with frequency-dispersion and thickness variations to be investigated. In particular, for a substrate coated with thin films, the relative permittivities of the substrate and the films, and the thicknesses of the films, can be determined accurately and nondestructively. This has many practical applications, particularly in the semiconductor industry, for which accurate characterization of the sample is essential. Since ellipsometry involves the measurement of an intensity ratio, it is free from instabilities of the light source; hence, the signal-to-noise ratio is high, thereby allowing detection of thickness variations of thin films in the subnanometer range and refractiveindex variations on the order of 0.001. Spectroscopic ellipsometry (SE) adds another dimension to the technique: material specificity, in particular when the material is highly dispersive. A theoretical simulation is performed of the
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
sample structure and fitted onto the thickness or refractive index. With variable-angle SE, the spectra of ψ and are measured at many angles of incidence, thus increasing the information gathered on the sample and improving the reliability of the measured data. Ellipsometry has been applied to sense several biochemical analytes.85,86 An ellipsometric image is formed with a CCD camera, thus allowing for simultaneous sensing of multiple biological or biochemical entities. Polarimetry, as opposed to ellipsometry, is widely used for the measurement of the change of the polarization state upon reflection from or transmission through birefringent, optically active, and scattering samples.87 Measurements of retardation and Stokes parameters are carried out using polarimetry. The Stokes parameters are particularly important when the light is partially polarized, such as when the sample depolarizes the incident light. A good use of polarimetry is for skin imaging, which allows diagnosis of cancer in the inner layers of the skin.88 Another example is polarimetric imaging through the eye89,90 for detection of the blood glucose level. For complete characterization of the polarization properties of the scattered light, all the elements of the Mueller matrix need to be determined, which for achiral isotropic materials can be related to some effective values of the ellipsometric parameters ψ and .
3 SENSING TECHNIQUES BASED ON REFRACTIVE-INDEX VARIATION 3.1
Interferometry
Interferometers measure phase variations which can be a result of variations in thickness and/or refractive index.91 Using stabilized interferometers, phase shift interferometry, and heterodyne techniques, one can measure variations in the optical path length of the order of (10−4 − 10−3 )/λ, equivalent to 10−4 − 10−3 variations in the refractive index. Common-path interferometry (i.e., measurement of the phase difference between s- and p- polarized waves in SPR experiments) or the use of Sagnac configuration delivers an improved signal-to-noise ratio, thereby extending the sensitivity limit of interferometry down to 10−8 − 10−7 RIU.
Mach–Zehnder (MZ) interferometers in PWs are being widely used, owing to the large interaction length possible. In addition, a large number of sensors can be fabricated in a chip for multichannel sensing.92 In the interaction region on the sample arm of a PW-MZ interferometer, the characteristics of the evanescent wave are influenced by the analyte, which causes a phase shift due to the variations in the modal effective index neff . Light in the reference arm can be modulated to allow for better signal-to-noise ratio, and the phase shift of the sinusoidal temporal fringes can be measured digitally in real time. Multipass interferometers are another way of improving the sensitivity, as has been demonstrated both in multireflection ATIR93 and in Fabry–Perot94 configurations. By measuring the shift in the Fabry–Perot peaks either in terms of the angle of incidence or the wavelength, one can detect refractive-index variations of the order of 10−8 ; indeed, an improvement of refractive-index sensitivity by a factor of 7 was achieved in water sensing as compared to the SPR.
3.2
Total Internal Reflection and Evanescent Waves
Several sensing configurations based on TIR exist. They rely on the existence of the evanescent field which is modified when the refractive index in the evanescence region is varied. The phenomenon of TIR is well known in optics. If incident light strikes a specularly smooth and planar interface between two different nonabsorbing and uniform materials (with refractive indices ni and nr ) at an angle θi , as shown in Figure 6(a), a fraction of light is reflected and the rest is refracted at an angle θr . If ni > nr , as θi is increased there is a value of θi for which the refracted wave propagates parallel to the interface (and is called a surface wave). As shown in Figure 6(b), then θr = 90◦ and the incidence angle is called the critical angle: −1
θc = sin
nr ni
(11)
When the angle of incidence exceeds the critical angle, no refraction occurs; instead, the light is
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
nr qr
·
ni
qi qi
qc
(a)
(b)
(c)
Figure 6. Illustration of total internal reflection (TIR) at a specularly smooth and planar interface of two different nonabsorbing materials.
reflected back into the medium of incidence. The TIR phenomenon is illustrated in Figure 6(c). No net flow of energy occurs across the interface under the TIR conditions.95 In order to satisfy the boundary conditions, the electromagnetic field must penetrate the optically rarer medium (Figure 7) and an evanescent wave is then generated with exponentially decaying amplitude: −z E = E0 exp (12) dp where z > 0 is the distance from the interface, and dp is the penetration depth: dp =
λ 2πni sin2 θi − (nr /ni )2
(13)
The penetration depth is of the order of few hundred nanometers or less, and can be controlled
Z
Evanescent wave
nr dp ni
15
by an appropriate choice of the ratio of refractive indices of the two materials, the angle of incidence, and the wavelength of the incident light. Another phenomenon important for sensing is frustrated total internal reflection (FTIR). When two materials of higher refractive index are separated by a thin layer of a material having lower refractive index, the energy of the incident light may flow through the gap between the two optically denser materials if the layer is much thinner than a wavelength. Thus, TIR is effectively frustrated, resulting in a partially or fully transmitted beam, depending on the size of the gap. This phenomenon is therefore called FTIR. It is also called optical tunneling, in analogy with the quantummechanical tunneling of a particle through an energy barrier. For angles of incidence much larger than the critical angle, the evanescent field decays very rapidly and a smaller gap is required to achieve significant optical tunneling. Therefore, for a specific angle of incidence, variation in the size of the gap can be used to control the efficiency of power transfer from one high-index material to the other.
3.3
Planar Waveguides
Waveguides are structures that confine and guide electromagnetic radiation (Figure 8). A PW, at its simplest, consists of a thin, transparent, dielectric film deposited on a substrate, and a cover may be put on top of the thin film. In order to achieve a true-guided mode in the thin film, the following condition must be satisfied: nf > max{ns , nc }. If ns = nc then the PW is referred to as being asymmetric; otherwise, it is symmetric. A further requirement is that the incidence angle θi must exceed the critical angle. Thus, the incidence angle must satisfy the following criteria: θi > sin−1 (ns /nf ) and θi > sin−1 (nc /nf ).
E
Cover nc Guiding layer n f
Standing wave
Figure 7. Schematic of the field structure when TIR occurs at a smooth planar interface.
Substrate ns
Figure 8. Schematic showing a standard PW, along with the transverse intensity profile of a guided mode.
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
nc
qi
qi
qi
nf Z
ns (a)
Radiation mode
(b)
Substrate mode
(c)
Guided mode
Figure 9. Ray patterns of (a) a radiation mode, (b) a substrate mode, and (c) a guided mode in a PW, where nf > ns ≥ nc .
Figure 9 illustrates the distinctions between radiation modes (no confinement), substrate modes and guided modes (full confinement). Numerous materials can be used for thin-film PWs, many of which can be spun, dip-coated, or deposited by various techniques on to a substrate. The dielectric film must be of sufficient thickness to support propagation of guided modes and should support a flow of electromagnetic energy only along the guiding structure not perpendicular to it. Light can be led into the thin film using a prism coupler, a grating coupler, an optical fiber, or an end-fire focusing coupler. The basic sensing principle of the PW sensor is to measure changes in the modal effective index neff due to refractiveindex changes in the cover. After propagating through the sensing section of the PW, light is coupled out and its intensity is measured by a detector to generate the sensorgram. A PW can be designed to support many modes propagating along the guide axis, each with a different modal wave number or modal effective index. These modes follow a zig-zag path as the light is totally reflected in the region between the boundary surfaces at angles θi greater than critical angle. However, not all arbitrary beams launched at incidence angles beyond the critical angle can propagate like guided modes. In a guided mode, the incident and reflected light at any position in the guide must be in phase, which requires the magnitude of the total phase change after a complete cycle of TIR to be an integer multiple of 2π . As the ratio λ/df between the wavelength λ and the waveguiding layer’s thickness df increases, the mode becomes more confined to the waveguide layer. This trend affects neff , which at the cutoff is equal to the smaller of the refractive indices of the cover and the substrate
(i.e., min{nc , ns }), and which becomes equal to the refractive index nf of the guiding layer for large λ/df .
3.4
Planar-waveguide Sensing Configurations
The fact that the (evanescent) fields of the guided mode extend into the cover and substrate of the PW makes the device useful for sensing purposes. The cover can be coated with a reagent, such as an indicator or recognition element. A chemical reaction within the region of the evanescent field is sensed due to the changes induced by the analyte on the sensor surface, such as scattering, absorption, fluorescence, or changes in the refractive index. PW sensors are attractive for several reasons. Their small size and flexibility facilitates the miniaturization of analytical instrumentation for in situ measurements. Their availability encouraged the development of remote and real-time continuous sensing in gaseous and liquids without sampling. They are immune to electromagnetic interference and resist hostile and hazardous environments. PW sensors can be fabricated from a variety of materials and can be relatively easily adapted for specific biomedical applications that require biocompatibility, sterilization, disposability, and the capability for in vivo measurements if needed. Light signals in PW sensors can be modulated in several ways to eliminate interference and facilitate the use of internal references. Their adaptability to act as electrodes allows integration with other techniques such as electric-field and magnetic-field techniques to provide more information, reduce nonspecific binding, shorten the analysis time, and improve the sensitivity.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
3.4.1 Asymmetric Waveguides
17
the critical angle on the substrate–spacer interface is coupled into the waveguiding layer via the evanescent field in the spacer, when the propagation constants in the substrate and waveguide match. For monochromatic light, this occurs over a very narrow range of incidence angles, typically spanning considerably less than 1◦ . Alternatively, it can be operated at a fixed incidence angle, and coupling occurs over a narrow range of wavelengths.102
Asymmetric PWs are useful as direct biochemical sensors, as the TIR boundary can be between the chemically selective waveguiding layer and the sample. The basic sensor is a thin waveguiding layer (on which the recognition element is immobilized) that is either deposited or engraved on either a polymer or a glass substrate. Air serves as the cover medium in the simplest case (Figure 10a). This basic device was introduced for sensing purposes by Tiefenthaler and Lukosz,96 who applied it as a humidity and gas sensor by detecting a change in the refractive index of the cover medium. Typical PW sensors use the high-index waveguide formed by depositing silicon nitride (Si3 N4 ),97 indium tin oxide (ITO),98 or tantalum pentoxide (Ta2 PO5 )99 on a glass or polymer substrate. The efficacy of such sensors have been demonstrated for label-free and fluorescence detection. The planar waveguide can be a multilayer and the integrated waveguide SPR biosensor.100 The resonant mirror (RM) was developed for immunosensors (e.g., the commercially available product IAsys from Affinity Sensors, a company in Cambridge, UK), as it is very sensitive to changes in the refractive index of the interfacial layer caused by the binding of macromolecules such as proteins to immobilized biorecognition species such as antibodies.101 In the RM sensor, FTIR is used to couple the light in and out of a high-index waveguiding layer. The RM is effectively a prism coupler where the air gap has been replaced by a low-index dielectric layer. Figure 10(b) shows the RM device structure, consisting of a highindex substrate (n = 1.72), a thin low-index spacer (about 550 nm of silica) and a very thin monomode waveguiding layer (about 80 nm of Si3 N4 ). The high-index resonant layer acts as both a waveguiding and a sensing layer. Light incident above
3.4.2 Grating Couplers
Some PW biosensors are called grating couplers. Either one or two gratings are fabricated on the surface of a PW by conventional lithographic or holographic techniques. Coupling occurs when the propagation vector of a guided mode is matched by the propagation vector of one of the diffracted orders from the grating. This is expressed mathematically as: neff = nc sin α + mλ/, where m is the diffraction order, is the grating period, and α is the propagation angle. In a grating coupler, a reversal of the direction of wave propagation transforms reciprocally the in-coupling into an out-coupling process. Therefore, in some sensor platforms, separate input and output grating couplers are employed. Grating couplers have been fabricated from semiconductors, dielectrics, and polymers. A grating coupler can be an integral part of the sensor. The term integrated optical waveguide (IOW ) sensor refers to a planar waveguide integrated with the grating couplers where the PW can be part of a flow-through cell. Brecht et al.101 concluded that the use of the IOW significantly improves the sensitivity of a sensing system by a factor of 100 compared with waveguides illuminated in discrete spots. The grating waveguide sensors have been demonstrated for single-sensing platforms as in
High-index waveguide Si3N4 Substrate (a)
Substrate (b)
Figure 10. Schematics of (a) a single-layer PW (b) and a multilayer PW that is an RM.
SiO2
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Microvacuum chips (OWLS, Microvacuum, Hungary) and Zeptosens high-throughput screening array platforms (Zeptosens, Bayer, Germany)103 for the detection of different bioanalytes using refractive index and fluorescence. A label-free PW with induced Bragg grating has been used in the detection of protein adsorption. Upon adsorption, the corrugation depth of the grating rises, which causes changes in the reflectance. Resonant grating waveguide structures (GWS) have also been used for biosensing. They are very sensitive to the adsorption/desorption of molecules on the waveguide surface and to any change of refractive index of the medium covering the surface of the sensor chip. When a resonant GWS is illuminated with an incident light beam, the diffracted light matches the guided-mode condition and interference with the m = 0 (specular) diffracted order causing resonant reflection backwards. This happens at a specific wavelength and incidence angle of the incident beam at which the resonance condition is satisfied, whereby the rediffracted beam destructively interferes with the transmitted beam, so that the incident light beam is completely reflected.104,105 The combination of a colorimetric resonant grating and photonic crystal embedded in the plastic surfaces of microtiter plates (96-, 384-, and 1536-well) has been developed by SRU Biosystems as a label-free, high-throughput, screening platform. The sensor can detect a shift in wavelength as low as half a picometer. Binding interactions can be quantified with proteins, cells, and small molecules. Sensitivity is quoted in the 0.05 µg ml−1 to 1 mg ml−1 range with molecular weights <200 Da. Corning has also developed a label-free detection platform that contains resonant GWS in the bottoms of 384-well microtiter plates. When illuminated with broadband light, the optical sensors inside each well reflect only a specific wavelength that is a sensitive function of the index of refraction close to the sensor surface. The platform has a sensitivity of 5 pg mm−2 , which enables the detection of the binding of a 300-Da molecule to a 70-kDa immobilized molecule.106–108 3.4.3 Optoelectrochemical (Electroactive) Transducers
An interesting configuration is in the form of an optoelectrochemical transducer, in which a PW is
overlaid with an electrically conducting ITO film. These types of sensors combine electrochemical control with evanescent-excitation-based detection. This configuration is useful for in situ study of the change in the absorption spectrum with the reduction–oxidation (redox) state of the analyte. In addition, electrochemical control of immunosensor substrates can be used to (i) minimize the crossreactivity (nonspecific adsorption), (ii) regenerate the immunosensor for subsequent use, (iii) control binding, and (iv) shorten the analysis time.109–111
3.4.4 Leaky Waveguides
Leaky waveguides (LWs) are those in which TIR does not occur at one or both of the reflecting boundaries.112–114 The confining mechanism in symmetric LWs is Fresnel reflection at both the low- and high-index boundaries. In asymmetric LWs, the confinement is due to Fresnel reflection at one boundary and TIR at the other. This confinement is short-lived. Loss from the waveguide occurs at a well-defined angle of incidence. This value also defines the maximum in-coupling efficiency, which is found by illumination at the waveguide/substrate interface. The best example of this configuration is the RM, wherein FTIR is used to couple light in and out of a Si3 N4 highindex waveguide via the evanescent field in a silica spacer.106
3.4.5 Long-range Waveguides
Evanescent-field biosensors have proven to be a highly sensitive tool for interactions in the close vicinity of the sensor surface. But, as they generally have penetration depths dp on the order of 100–150 nm, they are mostly suitable for detection of interactions with small targets such as viruses (10–100 nm), proteins (1–10 nm), and DNA. Detection of large targets such as bacterial cells (0.5–5 µm) and eukaryotic cells (5–50 µm) is problematic (Figure 11a). Several researchers have attempted to extend dp up to 1 µm (Figure 11b). These sensors include metalclad leaky waveguides (MCLW) and reversesymmetry waveguides.115 MCLWs have been used for detecting refractive-index changes, scattering,
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
Bacteria
Bacteria Virus
19
Virus
1m Protein
Protein (a)
100 nm (b)
Figure 11. Schematics of (a) the evanescent field of a conventional evanescent-field sensor of 100-nm penetration depth and (b) a long-range evanescent field, in comparison to biologically significant targets to be sensed.
evanescent field arises from the guided mode in the capillary wall (Figure 12b). The latter is favored as it guides light strongly and leads to the excitation of an evanescent field uniformly along the entire length of the capillary. In contrast, the liquid-core waveguide has nonuniform illumination along the capillary due to the weak guiding in the core (n = 1.33 for water), which is lower in refractive index than the cladding (capillary). Light guiding in the liquid core is improved by coating the capillary internally118 or externally119 with materials with refractive index lower than water, for example, fluoropolymers, Teflon, and nanoporous dielectric materials.120 Guiding-wall capillaries have been used mainly for fluorescence sandwich immunoassays with different excitation and emission probing configurations. In one setup, light is introduced at the end of the capillary and propagates on the inner surface as an evanescent wave. To probe fluorescence for example, a portion of the resulting fluorescence tunnels into the guided mode in the capillary wall and is captured at either or both ends of the capillary (Figure 13a). In another setup, which is analogous to a PW, the excitation is evanescent, but the emitted light is collected normal to the capillary axis using a CCD camera (Figure 13b).121 With the second setup, it is possible to detect between 3 and 230 Escherichia coli O157 : H7 cells using Cy5 labeled fluorescent ELISA assay.122 In yet
and fluorescence from bacterial cells captured on an immobilized antibody. Their detection limit is a 1000-fold better than of the conventional evanescent-field sensors based on SPR and RM, because the scattering and fluorescence intensities were increased by several orders of magnitude by the use of MCLWs.103 Long-range PWs have been integrated into different techniques in order to overcome certain problems such as (i) mass transport of the analyte which limits the binding of targets to the immobilized recognition receptors, (ii) nonspecific binding, and (iii) long analysis time. These techniques use the electric field, the magnetic field, or ultrasound standing waves.116,117 The integration improves the detection limit by a few orders of magnitude and shortens the analysis time to a few minutes. 3.4.6 Cylindrical Waveguides
The concept of combining optical detection with capillary device is unique as it achieves dual use of the capillary as a light-guiding and a fluidic channel. There are two possible configurations: (i) liquid-core waveguide, in which, the glass or silica capillary can be illuminated by either direct or partial reflections at the interior (Figure 12a), and (ii) guiding-wall capillary, wherein an indirect
Detector
Light source Evanescent field (a)
(b)
Figure 12. Schematics of (a) a liquid-core waveguide and (b) guiding-wall capillary.
20
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
CCD
Detector
Light source
(a)
(b)
Light source Light source
Detector (c) Figure 13. Schematics of three setups for excitation and collection of fluorescence emission.
another setup, the excitation is produced by a light source normal to the axis of the capillary, and the emitted fluorescence is tunneled into the guided mode of the capillary wall and collected at the end face (Figure 13c). With this setup, it is possible to detect as low as 40 pg ml−1 mouse IgG and 30–50 pg ml−1 staphylococcal enterotoxin B (SEB).123 This setup has been used to probe the capillary at many spots.
3.4.7 Optical Fibers
Optical fibers are cylindrical waveguides. They are small, remarkably strong, and flexible wires made out of glass or a polymer that can transmit light signals with minimal loss over long distances. Optical fibers have several attractive features: (i) very small domains can be probed, (ii) they are immune to interference unlike electrochemical sensors, (iii) they can be used for in vivo monitoring, (iv) they facilitate remote sensing, (v) they offer multiplexed sensing capabilities, and (vi) they are convenient for detection in harsh and hazardous environments. Optical fibers are available in different configurations, shapes, and materials and can transmit light in the visible, nearinfrared, and even the mid-infrared ranges. The most commonly used type of optical fiber for biosensing applications is the multimode stepindex fiber, which has a uniform refractive index in the core region (index n1 ) and in the cladding
(index n2 ). Multimode fibers made of silica and fluoride glasses, with diameter varying from 50 up to 500 µm, are also employed for biosensing. Multimode fibers offer many advantages: bigger domains can be probed, they are easy to use, they have better coupling efficiency, they have lower rate of photobleaching, they transmit well over short and medium distances, and they can be used with a wide range of commercially available optical components. The generated evanescent field near the core is used to sense the analyte surrounding the fiber. This means that the core must be exposed by reducing the thickness of the cladding, which can be adjusted during the production to control the strength of the evanescent field of a sensor. The choice of a suitable fiber material must take into account not only the optical transmission in the desired wavelength range, but also practical limitations such as chemical stability and mechanical flexibility. Silica, fluoride glasses, and plastics are the main materials for commercial optical fibers. Optical fibers are available in different formats. The first format has two designs, either (i) a single fiber to transmit light from the light source to the sample and back to the detector or (ii) one fiber is used for transmitting light from the source to the sample and a second fiber to transmit the light back from the sample to the detector (Figure 14a). The second format that is shown as a bifurcated fiber in Figure 14(b) is more commonly used.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
(a)
(b)
21
(c)
Figure 14. (a) Two fibers, (b) a bifurcated fiber, and (c) a central fiber transmitting the light carries the immobilized reagent and is surrounded by several fibers for collecting the output light and transmitting it to the detector.
Bifurcated fibers are used to excite through one fiber and monitor the altered signal via a different return fiber to separate the excitation light from the return light. The third format consists of a central fiber surrounded by several fibers (Figure 14c). The central fiber carries the immobilized reagent and is connected to the light source, whereas the surrounding fibers collect the output light and transmit it to the detector. Several review articles124,125 on the use of optical fibers in biosensing are recommended. Fiberoptic sensors have been demonstrated for the detection of many analytes, with various recognition molecules, for different applications (e.g., clinical, environmental and industrial), and using different optical techniques such as absorbance, fluorescence (intensity, intensity ratio, quenching, resonant energy transfer lifetime, and polarization), phosphorescence, chemiluminescence, and bioluminescence measurements. Sandwich and competitive assay formats are the most commonly used ones in the fiber-optic immunosensors. Multichannel fiber-optic systems have been commercialized, for example, RAPTOR in which the instrument contains four plastic channels to perform four separate assays simultaneously. This instrument has been used for the detection of different analytes, both biological (bacteria, viruses, toxins) and explosives (TNT, RDX). Walt et al.126,127 have demonstrated the efficacy of the high-density array platform for various biosensing applications using fiber-optic bundles. The fiberoptic bundles comprise hundreds or thousands of identical single fibers each with a diameter of a few micrometers, etched to form microwells at the fiber’s distal end, where the recognition molecules are attached to a microsphere
surface placed for the analysis. Evanescent-fiber probes (40 nm thick) have been used to probe the activation of biomolecules involved in apoptosis (programmed cell death) with specific immobilized peptide sequence and fluorescence resonance energy transfer (FRET) dyes at the probe end.128
3.5
Surface Plasmon Resonance (SPR)
SPR is a quantum optical-electrical phenomenon arising from the interaction of light with the free electrons at the metal surface.129 Under certain conditions the energy carried by photons of light is transferred to collective excitation of electrons, called plasmons, at the interface between a metal and a dielectric. Energy transfer occurs only at a specific resonance wavelength of light when the momentum of the photons and the plasmons are matched. These plasmons are strongly localized electromagnetic waves that propagate along the interface between the metal and the ambient medium, and decay exponentially with penetration distance into an emergent dielectric medium. At the resonance condition, SPR is responsible for a dip in reflectance, which results from the absorption of optical energy in the metal layer. This wave is extremely sensitive to changes in the refractive index near the metal surface within the range of the plasmon field. This change may result in a shift in the resonant wavelength of the incident light,130 change in the intensity of the reflected light,131 or change in the resonant angle of the incident light.132 The magnitude of this shift is quantitatively related to the magnitude of the refractive-index change of the
22
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
medium in contact with the metal surface. SPR has been used for the detection of different analytes including biomedical, environmental, and military defense in different phases: gas, liquid or a solid. Discussions of plasmons and their origin can be found in many books and review articles.133,134 A variety of metals, including silver and gold, copper, aluminum, sodium, indium, titanium, and chromium, can exhibit SPR in the visible range. There are critical limitations on the selection of a metal for SPR-based sensing, such as inertness of the metal, sharpness of the resonance, compatibility with chemicals needed to perform assays, and expense. Gold is the most practical metal as it produces strong SPR dip in the near-infrared region, it is inert, and it can be derivatized easily using mercapto-chemistry for the immobilization of biomolecules. Other metals are not practical; for example, silver is too susceptible to oxidation, indium is very expensive, sodium is violently reactive, and copper and aluminum give broad SPR dips and exhibit less sensitivity to refractive-index changes. SPR was initially exploited for the analysis of gases, liquids and solids. However, to date most of the research and commercial interest in SPR sensors has been in the field of biosensors and biomolecular interaction examinations and kinetic
studies. SPR sensors have been developed and commercialized by several companies including BIAcore, IBIS, Nanofilm, Autolab SPR, Plasmonic, GenOptics, and Spreeta.
3.5.1 SPR Configurations
In order to excite SPR by a light wave at a metaldielectric interface, the incident light’s wavevector must match the SPR wavevector, and the polarization state must be transverse magnetic (TM). To achieve the first condition easily, the incident light’s wave vector can be increased in magnitude either by passing the light through a medium with a refractive index higher than that of the dielectric medium at the boundary at which the surface plasma wave (SPW) is to be excited, or by using diffraction effects.53 Therefore, couplers are needed in SPR sensors. Prism Couplers The prism-based excitation of SPRs was proposed by Kretschmann.135 The Kretschmann configuration (Figure 15a) is the most common geometrical setup as it is the most efficient technique for generating the plasmon. In this configuration, a metal film is deposited directly on top of the prism surface. The metal film is illuminated through the prism at an angle of incidence greater than the
Gold layer Air gap
Grating
Gold layer
(a)
(b)
Gold layer
(c)
Gold layer
Waveguide layer
(d)
Fiber
Gold layer
Ta2O5 layer
(e)
Figure 15. Schematics of (a) the Kretschmann configuration of a prism coupler, (b) the Otto configuration of a prism coupler, (c) grating coupler, (d) waveguide coupler, and (e) fiber-optic coupler.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
critical angle for TIR. The light wave undergoes TIR at the interface between the prism coupler and the metal film, and excites the plasmon at the outer boundary of the metal film by evanescent tunneling. In the Otto configuration136 (Figure 15b), the prism is placed close to a metal surface, so that the photon tunneling occurs through the air gap between the prism and the metal surface. This configuration is useful in the study of SPR with solid media. The Otto configuration is less useful for applications with solutions, since the gap between the metal and the prism is filled with a dielectric, thereby reducing the SPR efficiency. Different approaches have been used in the SPR prism-based sensors: angular, wavelength, intensity, phase, and polarization measurements. The angular- and the wavelength-measurement approaches are the most widely used ones, as they rely on multi-point measurements which yield more robust data, unlike single-point measurements in the intensity- and the phase-measurement approaches. The angular-measurement approach is exploited in several commercial SPR instruments, the best sensitivity (refractive-index resolution) obtained therewith being better than 3 × 10−7 RIU. The wavelength-measurement approach is comparable in performance. Both approaches have been demonstrated in multichannel, high-density (array) formats. In these formats, an SPR is excited in many locations and the light reflected from each location is analyzed to provide information about the analyte in each location. Grating Couplers Another technique to overcome the momentum mismatch is to use a periodically corrugated metal/dielectric interface. The diffracted orders from the corrugation have wave vectors larger in magnitude than the incident light. A light beam is directed towards a medium whose surface has a spatial periodicity comparable to the wavelength of the incident light, for example, a reflection diffraction grating (Figure 15c). The incident beam is diffracted, and the components of the diffracted light whose wave vectors coincide with the SP wavevector get coupled to the SP. Efficient coupling is provided to both air–metal and substrate–metal SP modes of a metal film, if the film thickness and the grating corrugation depth are suitably related.
23
The chief advantage of the grating-coupled SPR sensors is that they can be produced by mass replication technologies such as injection molding and hot embossing. These technologies have opened the door for producing lowcost, high-throughput SPR platforms for label-free monitoring of biomolecular interactions.137 Potential for real-time observation of thousands of interactions on a single sensor chip has been demonstrated.138–140 Waveguide Couplers The process of exciting an SPR using the waveguide is similar to that in the Kretschmann configuration. The light is guided by either a single or multilayer (slab or channel) waveguide to a region with a thin metal overlayer. In that region, the light penetrates evanescently through the metal layer (Figure 15d). If the SP and the guided mode are matched in phase, the incident light excites the SP at the outer interface of the metal layer. The sensitivity of the waveguide-coupled SPR sensor is approximately the same as in the ATIR configuration. The use of optical waveguides in exciting SPR sensors have some attractive features, including the simple control of the optical path in the sensor system, small sizes, and ruggedness.53 Fiber-optic Couplers SPR sensors with fiber-optic couplers operate using either wavelength- or intensity-interrogation141 on a formed SPR active sensing area that is located either at the end of the fiber or in the middle of the fiber where the cladding of optical fiber core is partially removed (Figure 15e). The evanescent field within an optical fiber can excite a standing charge-density wave on the metal (often, gold) surface. The SP on the metal surface is affected by the relative permittivities of the thin metal film and the adsorbate. In the wavelength-interrogation operation, light of a certain wavelength and incident at a certain angle is in resonance with the SP; that light is absorbed to give a minimum in the reflectance spectrum. The wavelength of the light that is absorbed change with the change in the refractive index at the metal surface. In the intensity-interrogation operation, change in intensity due to refractive-index variation adjacent to the metal surface is measured. The reported sensor resolutions are comparable for the two types of operation at 8 × 105 and 5 × 105 RIU, respectively.
24
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
The chief advantage of using fiber-optic couplers is the production of a miniaturized probe with limited interrogation area. That feature allows sensing in inaccessible and harsh conditions, where mechanical flexibility and the ability to transmit signals over long distances is extremely desirable.52 3.5.2 SPR Imaging Systems
SPR imaging systems have great potential for a broad range of applications that require highthroughput analysis of biomolecular interactions, such as proteomic analysis, drug discovery, and pathway elucidation. Numerous studies have been devoted to developing SPR imaging technology, and a handful of instruments are nowadays commercially available. An instrument employing a broadband light source and the Fourier transform algorithm is sold by GWC Technologies.142 HTS Biosystems designed an SPR imaging platform utilizing grating couplers.143 An SPR imaging system used as a microarray reader in combination with fluorescence labeling has been reported to deliver attomolar sensitivity.144 SPR imaging technology has been successfully applied to the screening of bioaffinity interactions with DNA,145 carbohydrates,146 peptides,147 phage display libraries,148 and proteins.149 SPR platforms have been integrated with matrixassisted mass spectrometry (MS) to create a unique approach for protein investigation in array formats. In this approach, SPR is used to quantify interactions between proteins and surface-immobilized ligands, whereas MS is used to identify the captured analyte by desorbing/ionizing the analyte from the interactive surface layer. This combination offers multiprotein analysis and proteincomplex delineation with improved detection limits.150 In the long-range SPR configuration, the evanescent-field region of the SPR on the metal surface is extended by adding a dielectric buffer layer (with a refractive index lower than that of water) between the substrate and the metal film.151–153 This configuration improves the detection limit significantly to 2.5 × 10−8 RIU, which is the highest reported so far. Extension of the sensing region is useful for the detection of large targets such as bacteria and mammalian cells.
3.6
Optical Microresonators
Optical microresonators have attracted interest during the last few years in the biosensing community, due to (i) their small size requiring analyte solutions in nanoliter volumes, (ii) high quality factors, and (iii) unprecedented sensitivity. These tiny optical cavities, whose dimmers may vary from a few to several micrometers, deliver quality factors as large as 3 × 109 and beyond. Such enormously high quality factors represent unique performance characteristics: an extremely narrow resonant line width, long decay time, and a high energy density.154,155 Resonance in a transparent dielectric microresonator occurs when light, confined by TIR along the inside of the resonator surface, orbits near a recognition particle’s surface and returns in phase after each revolution. The sensitivity is improved by several orders of magnitude due to the fact that the light interacts with the same analyte molecule captured by the recognition particle for several thousand times unlike single-pass techniques. The frequencies of the whispering gallery modes (WGMs), characterized by the number of wavelengths within an orbit, are extremely sensitive to added dielectric material on the recognition particle’s surface; just an atomic thickness can lead to a detectable shift of a specific resonance frequency.156 WGMs were originally introduced for sound waves propagating close to a cylindrical wall in St. Paul’s Cathedral, London:157 the mode shape was partially confined due to the suppression of diffraction by reflection from the curved dome walls. The effective volumes and field distributions of WGMs depend on the radius of the resonator.158 Optical microresonators have various types of shapes such as cylindrical, spherical, spheroidal/ toroidal, and ringlike. The underlying principle is the provision of efficient energy transfer to the resonant circular TIR guided wave in the resonator, representing the WGM, through the evanescent field of a guided wave or a TIR spot in the coupler. Efficient coupling occurs upon fulfillment of two main conditions: (i) phase synchronization and (ii) significant overlap of the WGM and the coupler mode. Different techniques have been demonstrated for coupling the light into the microresonators including the prism couplers with
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
FTIR,159–162 side-polished optical fiber-couplers, and “pigtailing” couplers utilizing angle-polished fiber tips in which a core-guided wave undergoes TIR.163,164 In addition, PWs are used to couple to ring and disk microresonators,165,166 and strip-line pedestal antiresonant reflecting waveguides have been proposed for robust coupling to microsphere resonators and microphotonic circuits.167 Sensing relies on the measurement of the resonance shifts (refractive-index change) due to either the adsorption of biomolecules on the surfaces of sensing areas or the presence of a solution surrounding the device. As an alternative, detection is also possible by measuring the output intensity change from the microresonator at a fixed wavelength. Vollmer et al.168 demonstrated the use of WGM microsphere biosensors for the detection of protein adsorption: the adsorption of a single layer of bovine serum albumin (BSA) caused the wavelength to shift by approximately 16 ppm. An optical microsphere resonator used for the detection of thrombin using aptamer as the recognition molecule delivered a detection limit in the order of 1 NIH unit/ml.169 (1 NIH unit of thrombin clots a standard fibrinogen solution in 15 s at 37 ◦ C.) A multiplexed platform for DNA quantification was developed with two microsphere cavities evanescently coupled to the same single optical fiber, the sensitivity of this device being as high as 6 pg mm−2 mass loading.170 Boyd et al.171 described the use of WGM disk microresonators for the detection of pathogens using selective recognition receptors, the devices being capable under optimum conditions of detecting as few as 100 molecules. Microring resonators are compact, integrable with other systems, and can be mass-produced utilizing well-established microfabrication techniques. A polystyrene microring with enhanced resonance using two partially reflecting elements implemented by waveguide offset was shown to produce a sharp Fano-resonant line shape which enhances the sensitivity to the detection of different concentrations of glucose solutions.172 Planar arrays of microtoroidal resonators, evaluated for the detection of D2 O contamination in water, detected as low as 1 ppm (volume/volume) of D2 O in H2 O.173 A liquid-ring resonator (LCR) has been used as a label-free multiplexed detector for capillary electrophoresis (CE). The LCR is unique
25
in that it achieves dual use of the capillary as a resonator and as a CE fluidic channel.174 The combined use of WGMs and SERS has been reported,175–177 when the analyte adsorbed to silver nanoparticles is placed within the evanescent field of a microresonator with a high quality factor. The tremendous advantage of using the microresonator instead of planar surfaces is that the signal is amplified as a result of light circumnavigation on the microresonator surface many thousands of times. Thus each photon has a higher probability of generating Raman photons, unlike the excitation in planar form where the excitation photon has just one opportunity to interact with the target analyte.
3.7
Sensing with Porous Materials and Photonic Crystals
Porous materials provide several modalities for optical biosensing, provided the porosity is on the scale of a wavelength or smaller. A simple modality emerges by way of homogenization theory. If the length scale of porosity is less than a tenth of the wavelength of incident light, a porous material may be thought of in terms of a nonporous homogeneous material with an equivalent refractive index. The equivalent refractive index depends on the refractive index of the skeleton material and the porosity or void fraction. When this porous material is submerged in a liquid or a vapor that does not react chemically with the skeleton material, the equivalent refractive index must change. Thus, the transmission/reflection spectra of a slab of the porous material will be altered by any infiltrant fluid as well as by any solute molecules in that fluid. If the infiltrant molecules chemically react with the skeleton material, the spectra would also be altered. Lin et al.178 were able to optically sense small organic molecules, 16-nucleotide DNA oligomers, and proteins at pico- and femtomolar analyte concentrations in porous silicon. Insertion of the porous silicon between two dielectric mirrors increases the sensitivity.179 If a slab of a porous material possesses a periodic variation of optical constitutive properties, different types of Bragg phenomena can be exhibited by it. The Bragg phenomena could depend on the polarization state and the direction of propagation of the incident light in relation to the
26
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
illuminated surface of the slab. Any infiltration of the voids could shift the center-wavelength and the bandwidth of a Bragg range. Photonic crystals and chiral sculptured thin films are two candidate materials. Although the concept of photonic crystals can be traced back to the 1970s and perhaps even earlier, research literature on these artificially manufactured materials began to grow rapidly after the mid-1990s. This is because photonic crystals are highly suitable for controlling and manipulating the flow of light because of the occurrence of band gaps in their transmission spectra for specific polarization states and propagation directions of the incident light. The one-, twoor three-dimensionally periodic variations in the relative permittivity (scalar or tensor) are often created through a periodic assembly of material cells, the constitutive properties of which determine the center-wavelength and the bandwidth of every band gap (or Bragg range). Some cells in any period need not be made of matter, but be voids instead. The injection of a fluid in the periodic voids of a porous photonic crystal affects the band gaps. Specifically, the edges of a band gap for a certain incident polarization state can be sensitively dependent on the refractive index of the infiltrant fluid. For a refractive-index change of 0.002, Xiao and Mortensen recently calculated that the band-gap edge of 2D photonic crystal can shift on the order of 1 nm.180 Since the refractive index of the infiltrant fluid depends also on any solute molecules present in it, a photonic crystal has potential as an optical biosensor. The insertion of a defect in a photonic crystal creates a hole in a transmission band gap. Typically, the bandwidth of this reflection hole is a small fraction of the bandwidth of the transmission band gap that the former bifurcates. The spectral location of the reflection hole shifts with variations in the refractive index of the infiltrant fluid, as shown experimentally by Chow et al.181 thereby establishing another modality for the potential use of photonic crystals as optical biosensors. Chiral sculptured thin films have one-dimensional periodicity, and are generally grown by physical vapor deposition on rotating substrates. Comprising helical nanowires separated by voids, as shown in Figure 16, a chiral sculptured thin film that is structurally right-/left-handed highly reflects
Magn 8779x
2 µm WD 3.5 3-xxx-xxxx8-0-3
Figure 16. Scanning electron microscope image of a typical sculptured thin film prepared by tilted evaporation. This thin film is structurally chiral.
normally incident light that is right/left circularly polarized but not left/right circularly polarized light, in the Bragg range. The central-wavelength and the bandwidth of the Bragg range depend on the refractive index of any infiltrant fluid, thereby providing a potential modality for optical sensing. The insertion of a central defect layer creates a spectral hole, whose location changes with the infiltrant fluid too, as shown experimentally and theoretically by Lakhtakia et al.182 Just like porous silicon, chiral sculptured thin films and porous photonic crystals provide another modality for optical sensing: the analyte could chemically react with the skeleton material, thereby altering the overall optical transmission characteristics. For instance, the skeleton material could be eroded or transformed either partially or wholly into some other material with very different optical constitutive properties. Special features in the transmission/reflection spectrum would then change. This has been theoretically as well as experimentally demonstrated for chiral sculptured thin films183,184 and underlies a proposal for optical sensing of anaerobic bacteria in compromised environments.185
4 FUTURE TRENDS
Topics for continuing and future research in the area of optical biosensors include: (i) optimization of metal nanoparticles, quantum dots,
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
and nanotubes; (ii) biochips; (iii) noninvasive blood glucose sensors; and (iv) real-time detection of biowarfare agents. Since many research groups are usually focused on certain types of analytes but not on others, there is a need to develop multigroup projects for multianalyte sensing. The development of portable light sources and detectors exploiting nanomaterials would make round-the-clock monitoring possible. Such continuous monitoring biosensors would assist medical researchers in uncovering the factors that indicate the imminent onset of disease, thereby leading to better diagnosis and treatment. Multianalyte biosensors can be used for bioimaging. By introducing nanomaterials into the human body and monitoring the fluorescence signals associated with specific biomolecules, complex biological processes can be monitored and detailed images of tissues can be obtained. The impact of nanotechnologies on biosensing is being felt in the development of biochips. A biochip is a self-contained and integrated array of multiple biosensing elements, electronic and photonic circuitry, a microfluidic system, an electrooptics excitation/detection system, and bioreceptor probes.186 Biochips are already being used in various ways in the agricultural, veterinary, healthcare, and medical sectors. An optical nanobiosensor is an integrated nanoscale device comprising a biorecognition molecular species (e.g., DNA or proteins) coupled to an optical transducing element such as an optical nanofiber, the device being interfaced to a photometric detection system. It should be capable of providing specific quantitative or qualitative analytical information. Insertion of optical nanobiosensors into single living cells, to monitor and measure chemical species of biomedical interest without disrupting normal cellular processes should become possible in the near future, thereby overcoming the challenge of real-time monitoring of molecular signaling processes as well as other processes in living cells.187,188 Nanotechnological developments are expected to enhance optical nanobiosensors in the near future in several different ways. A good example is furnished by plasmonics, which exploits metal nanoparticles for biosensing. Optimization of the shape of the nanoparticles for enhanced LSPR, SERS, and SEF signals and the reliability of
27
results are important topics awaiting finalization. Plasmonics-based nanoprobes are expected to arrive for clinical, lab, or environmental use within a few years. Another example is provided by the use of quantum dots as fluorescent labels with high quantum efficiency. Nanotubes are being viewed with interest due to their possible fluorescence in the near-infrared range; in particular, single-wall nanotubes may possibly be used for in vivo detection of proteins and enzymes, such as β-D-glucose.189 The inherent fluorescence from single-walled carbon nanotubes was shown to have potential in monitoring glucose levels in the blood as well as for imaging biological processes.190,191 However, long-term studies on toxicity need to be conducted before introducing carbon nanotubes and other nanoparticles into the human body. The ability to synthesize or separate nanotubes by their (n, m) chirality indices has the potential to aid the development of an implantable multi-analyte biosensor. In the near term, the fluorescence properties of single-walled nanotubes can be used as imaging markers and biosensors for in vitro studies, particularly in cases where traditional dyes suffer from bleaching, degradation and toxicity problems. A commercial company (http://www.appliednanofluorescence.com) has begun to market a product capable of identifying the individual fluorescence from each (n, m) singlewall nanotube within seconds. The texture of porosity in porous nanomaterials, for biosensing purposes, could be engineered to promote infiltration by certain fluids but not by others, or to promote the binding of certain types of solute molecules but not of others with the skeleton material. An extremely important application shall be in the identification of human cancers. No matter how small, every tumor reveals its identity in tiny amounts of abnormally expressed proteins called oncoproteins. A nanofluidic system developed by Cell Biosciences in Palo Alto (http://www.cellbiosciences.com) measures the levels of three oncoproteins (MYC, BCL2, and AKT) in tiny samples drawn as very fine needle aspirates from hematopoetic tumor cells in preclinical transgenic mice. The nanofluidic system physically separates the oncoproteins in very small capillary tubes and then uses antibodies for protein detection. Another example of the impact of nanotechnology on biosensing is the method developed
28
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
by Zhang et al.192 wherein gold-coated nanocantilevers are used to detect the activity of the 1-8U gene produced by human melanoma cells and controls the tumor growth. The new method detects messenger RNA, produced by active genes, without the need for amplification, relying instead on optical sensors attached to tiny silicon cantilevers that are only 500 nm long, 100 nm wide, and 450 nm thick. A short stretch of single-stranded DNA is attached to the gold coating that binds specifically to messenger RNA produced by the 1-8U gene. An array of eight nanocantilevers is mounted within a microcapillary tube connected to an injection port. The device is capable of distinguishing between messenger RNA coding for a human protein and messenger RNA coding for a similar but not identical rat protein—the two messenger RNAs differed by a mere four bases. Near-field scanning optical microscopy (NSOM) is an emerging nanotechnological technique with its excellent resolving power less than 100-nm domains and its nondestructive nature compared to other scanning-probe microscopic techniques. Nondestructive imaging of biomolecules at the nanoscale is an attractive prospect. At the singlemolecule-level resolution, it is possible to use the NSOM as a critical tool for visualization of cellular components labeled with fluorescent molecules. The NSOM obtains fundamental information about the cellular component’s position and orientation without disturbing them, or the level of interaction with the surface. Several areas of biology and medicine can benefit from studies of this type, especially for molecular imaging, biomedical, and biochip applications. Another emerging field is theranostics (therapeutic and diagnostics), a proposed process of diagnostic therapy for individual patients—to test them for possible reactions to new medications and to tailor subsequent treatments based on the test results.193 Theranostics will require the development of biochips which contain diagnostic sensors (test) and release controlled amounts of drugs. The best example is an insulin delivery system for diabetic people: a sensor for continuous monitoring of blood glucose level with a feedback so that an insulin reservoir releases a specific amount of insulin when there is an unacceptable rise in the blood glucose level. Finally, the field of smart domestic sensors is on the horizon. Sensors can be integrated in homes to
control domestic equipment and ensure safety in combination with “telecare” which makes use of the revolutions in telecommunication and information technologies for remote control.194 A variety of forms for telecare services and smart homes already exists, each ranging from basic systems involving the use of alarms and the ordinary telephone to intelligent monitoring with sensors and interactive communication with cooking, cleaning, and environment-control equipment. Remote patient-care is also part of telecare. Optical sensors (including biosensors) that are cost-effective, easy to integrate, and easy to use are very desirable.
ACKNOWLEDGMENT
This chapter is dedicated to a peaceful and prosperous future for all young people worldwide, one of whom recently decided to grace the life of the second author.
REFERENCES 1. F. S. Ligler and C. A. Rowe Taitt (eds), Optical Biosensors: Present and Future, Elsevier, Amsterdam, The Netherlands, 2002. 2. V. V. Tuchin (ed), Handbook of Optical Biomedical Diagnostics, SPIE Press, Bellingham, WA, USA, 2002. 3. J. B. Jensen, P. E. Hoiby, G. Emiliyanov, O. Bang, L. H. Pedersen, and A. Bjarklev, Selective detection of antibodies in microstructured polymer optical fibers. Optics Express, 2005, 13, 5883–5889. 4. J. Hodgkinson, M. Johnson, and J. P. Dakin, Photothermal detection of trace optical absorption in water using visible light emitting diodes. Applied Optics, 1998, 37, 7320–7326. 5. S. Shalem, A. Tsun, E. Rave, A. Millo, L. Nagli, and A. Katzir, Silver halide single-mode fibers for the middle infrared. Applied Physics Letters, 2005, 87, 091103. 6. J. Tschmelak, G. Proll, J. Riedt, J. Kaiser, P. Kraemmer, L. Barzagas, J. S. Wilkinson, P. Hua, P. J. Hole, R. Nudd, M. Jackson, R. Abuknesha, D. Barcelo, S. Rodriguez-Mozaz, M. J. Lopez de Alda, F. Sacher, J. Stien, J. Slobodnik, P. Oswald, H. Kozmenko, and E. Korenkova, Biosensors for unattended cost-effective and continuous monitoring of environmental pollution: automated water analyser computer supported system (AWACSS) and river analyser (RIANA). International Journal of Environmental Analytical Chemistry, 2005, 85, 837–852. 7. R. W. Waynant, I. K. Ilev, and I. Gannot, Mid-infrared laser applications in medicine and biology. Philosophical Transactions of the Royal Society of London. Series A, 2001, 359, 635–644.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES 8. R. S. Marks, A. Novoa, T. Konry, R. Krais, and S. Cosnier, Indium tin oxide-coated optical fiber tips for affinity electro-polymerization. Materials Science and Engineering C, 2002, 21, 189–194. 9. M. T. Myaing, J. Y. Ye, T. B. Norris, T. Thomas, J. R. Baker Jr, W. J. Wadsworth, G. Bouwmans, J. C. Knight, and P. St. J. Russell, Enhanced two-photon biosensing with double-clad photonic crystal fiber. Optics Letters, 2003, 28, 1224–1226. 10. I. Abdulhalim and G. Moores, Remote temperature and thermal expansion sensing using the time delay mode of position sensors. Sensors and Actuators A, 2004, 111, 245–251. 11. I. Abdulhalim, I. Gannot, and C. N. Pannell, All-fiber and fiber compatible acousto-optic modulators with potential biomedical applications. Proceedings of the SPIE, 2006, 6083, 116–130. 12. C. H. Mazel, Diver-operated instrument for in situ measurement of spectral fluorescence and reflectance of benthic marine organisms and substrates. Optical Engineering, 1997, 36, 2612–2617. 13. D. A. M. Hierro, W. Kronberger, P. Hietz, I. Offenthaler, and H. Richter, A new method to determine the oxygen concentration inside the sapwood of trees. Journal of Experimental Botany, 2002, 53, 559–563. 14. M. Edmonds, R. A. Herd, B. Galle, and C. M. Oppenheimer, Automated, high time-resolution measurements of SO2 flux at Soufriere Hills volcano, Montserrat. Bulletin of Volcanology, 2003, 65, 578–586. 15. E. M. Long and E. Michael, Mars on earth. National Geographic, 1999, 196(1), 34–51. 16. For a detailed list of references on the applications of miniature spectrometers, see the website of ocean optics:, http://www.oceanoptics.com/applications/ references.asp. 2007. 17. I. M. Stefanaki, S. Georgiou, G. C. Themelis, E. M. Vazgiouraki, and A. D. Tosca, In vivo fluorescence kinetics and photodynamic therapy in condylomata acuminate. British Journal of Dermatology, 2003, 149, 972–976. 18. R. A. Crocombe, D. C. Flanders, and W. Atia, Micro-optical instrumentation for process spectroscopy. Proceedings of the SPIE, 2004, 5591, 11–25. 19. E. Botonjic and C. S. Fawcett, Tissue identification using a miniature near-infrared spectrometer. Proceedings of the SPIE, 2006, 6078, 60781Z. 20. D. A. Draegert, N. W. B. Stone, B. Curnutte, and D. Williams, Far-infrared spectrum of liquid water. Journal of the Optical Society of America, 1966, 56, 64–69. 21. C. H. Whitlock, L. R. Poole, J. W. Usry, W. M. Houghton, W. G. Witte, W. D. Morris, and E. A. Gurganus, Comparison of reflectance with backscatter and absorption parameters for turbid waters. Applied Optics, 1981, 20, 517–522. 22. V. Sivaprakasam and D. K. Killinger, Tunable ultraviolet laser-induced fluorescence detection of trace plastics and dissolved organic compounds in water. Applied Optics, 2003, 42, 6739–6746. 23. B. D. Zislin and A. V. Chistyakov, The history of oximetry. Biomedical Engineering, 2006, 40, 53–56.
29
24. M. G. Gore (ed), Spectrophotometry and Spectrofluorimetry, A Practical Approach, Oxford University Press, New York, USA, 2000. 25. G. Berden, R. Peeters, and G. Meijer, Cavity ring-down spectroscopy: experimental schemes and applications. International Reviews in Physical Chemistry, 2000, 19, 565–607. 26. D. Z. Anderson, J. C. Frisch, and C. S. Masser, Mirror reflectometer based on optical cavity decay time. Applied Optics, 1984, 23, 1238–1244. 27. A. O’Keefe and D. A. G. Deacon, Cavity ring-down optical spectrometer for absorption measurements using pulsed laser sources. Review of Scientific Instruments, 1988, 59, 2544–2554. 28. P. Hahn, M. Tacke, M. Jakusch, B. Mizaikoff, O. Spector, and A. Katzir, Detection of hydrocarbons in water by MIR evanescent-wave spectroscopy with flattened silver halide fibers. Applied Spectroscopy, 2001, 55, 39–43. 29. J. R. Lakowicz, Principles of Fluorescence Spectroscopy, Plenum, New York, USA, 2003. 30. F. Wang, W. B. Tan, Y. Zhang, X. Fan, and M. Wang, Luminescent nanomaterials for biological labeling–topical review. Nanotechnology, 2006, 17, R1–R13. 31. T. E. Hirschfeld, Total reflection fluorescence. Canadian Journal of Spectroscopy, 1965, 10, 128–133. 32. M. N. Kronick and W. A. Little, New immunoassay based on fluorescence excitation by total-reflection spectroscopy. Journal of Immunological Methods, 1975, 8, 235–240. 33. C. R. Taitt, G. P. Anderson, and F. S. Ligler, Evanescent wave fluorescence biosensors. Biosensors and Bioelectronics, 2005, 20, 2470–2487. 34. T. E. Plowman, W. M. Reichert, C. R. Peters, H. K. Wang, D. A. Christensen, and J. N. Herron, Femtomolar sensitivity using a channel-etched thing film waveguide fluoroimmunosensor. Biosensors and Bioelectronics, 1996, 11, 149–160. 35. M. Bawlak, E. Schick, M. A. Bopp, M. J. Schneider, P. Oroszlan, and M. Ehrat, Zeptosens protein microarrays: a novel high performance microarray platform for low abundance protein analysis. Proteomics, 2002, 2, 383–393. 36. H. Schneckenburger, Total internal reflection microscopy: technical innovations and novel applications. Current Opinion in Biotechnology, 2005, 16, 13–18. 37. H. M. Grandin, B. Stadler, M. Textor, and J. V¨or¨os, Waveguide excitation fluorescence microscopy: a new tool for sensing and imaging the biointerface. Biosensors and Bioelectronics, 2006, 21, 1476–1482. 38. B. Dorsche (ed), Infrared and Raman Spectroscopy, VCH, New York, USA, 1995. 39. A. B. Myers and R. A. Mathies, Resonance Raman spectra of polyenes and aromatics, in: T. G. Spiro (ed), Biological Applications of Raman Spectrometry, Vol. 2, Wiley, New York, USA, 1987. 40. R. H. Clarke, S. Londhe, W. R. Premasiri, and M. E. Womble, Low resolution Raman spectroscopy instrumentation and applications for chemical analysis. Journal of Raman Spectroscopy, 1999, 30, 827–832. 41. N. Nath and A. Chilkoti, A colorimetric gold nanoparticle sensor to interrogate biomolecular interactions in real
30
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS time on a surface. Analytical Chemistry, 2002, 74, 504–509. A. J. Haes, L. Chang, W. L. Klein, and R. P. Van Duyne, Detection of a biomarker for Alzheimer’s disease from synthetic and clinical samples using a nanoscale optical biosensor. Journal of the American Chemical Society, 2005, 127, 2264–2271. D. Eck, C. A. Helm, N. J. Wagner, and K. A. Vaynberg, Plasmon resonance measurements of the adsorption and adsorption kinetics of a biopolymer onto gold nanocolloids. Langmuir, 2001, 17, 957–960. J. J. Storhoff, A. A. Lazarides, R. C. Mucic, C. A. Mirkin, R. L. Letsinger, and G. C. Schatz, What controls the optical properties of DNA-linked gold nanoparticle assemblies. Journal of the American Chemical Society, 2000, 122, 4640–4650. T. Okamoto, I. Yamaguchi, and T. Kobayashi, Local plasmon sensor with gold colloid monolayers deposited upon glass substrates. Optics Letters, 2000, 25, 372–374. A. J. Haes and R. P. Van Duyne, A nanoscale optical biosensor: sensitivity and selectivity of an approach based on the localized surface plasmon resonance spectroscopy of triangular silver nanoparticles. Journal of the American Chemical Society, 2002, 124, 10596–10604. A. J. Haes and R. P. Van Duyne, A highly sensitive and selective surface-enhanced nanobiosensor. Materials Research Society Symposium Proceeding, 2002, 723, O3.1. L. S. Jung, C. T. Campbell, T. M. Chinowsky, M. N. Mar, and S. S. Yee, Quantitative interpretation of the response of surface plasmon resonance sensors to adsorbed films. Langmuir, 1998, 14, 5636–5648. P. Schuck, Use of surface plasmon resonance to probe the equilibrium and dynamic aspects of interactions between biological macromolecules. Annual Review of Biophysics and Biomolecular Structure, 1997, 26, 541–566. A. Henglein and D. Meisel, Spectrophotometric observations of the adsorption of organosulfur compounds on colloidal silver nanoparticles. Journal of Physical Chemistry B, 1998, 102, 8364–8366. G. Kalyuzhny, A. Vaskevich, G. Ashkenasy, and A. Shanzer, UV/Vis spectroscopy of metalloporphyrin and metallophthalocyanine monolayers self-assembled on ultrathin gold films. Journal of Physical Chemistry B, 2000, 104, 8238–8344. A. Hilger, N. Cuppers, M. Tenfelde, and U. Kreibig, Surface and interface effects in the optical properties of silver nanoparticles. European Physical Journal D, 2000, 10, 115–118. J. Homola, S. S. Yee, and G. Gauglitz, Surface plasmon resonance sensors: review. Sensors and Actuators B, 1999, 54, 3–15. A. J. Haes and R. P. Van Duyne, Nanoscale optical biosensors based on localized surface plasmon resonance spectroscopy. Proceedings of the SPIE, 2003, 5221, 47–58. L. S. Jung, C. T. Campbell, T. M. Chinowsky, M. N. Mar, and S. S. Yee, Quantitative interpretation of the response of surface plasmon resonance sensors to adsorbed films. Langmuir, 1998, 14, 5636–5648.
56. M. Lahav, A. Vaskevich, and I. Rubinstein, Biological sensing using transmission surface plasmon resonance spectroscopy. Langmuir, 2004, 20, 7365–7367. 57. A. D. McFarland and R. P. Van Duyne, Single silver nanoparticles as real-time optical sensors with zeptomole sensitivity. Nano Letters, 2003, 3, 1057–1062. 58. E. Hutter and M.-P. Pileni, Detection of DNA hybridization by gold nanoparticle enhanced transmission surface plasmon resonance spectroscopy. Journal of Physical Chemistry B, 2003, 107, 6497–6499. 59. G. C. Schatz and R. P. Van Duyne, Electromagnetic Mechanism of Surface-Enhanced Spectroscopy, in: M. J. Chalmers, and P. R. Griffiths (eds), Handbook of Vibrational Spectroscopy, Wiley, Chicester, UK, 2002. 60. T. M. Cotton, J.-H. Kim, and G. D. Chumanov, Application of surface-enhanced Raman spectroscopy to biological systems. Journal of Raman Spectroscopy, 2005, 22, 729–742. 61. M. Kerker, Founding fathers of light scattering and surface enhanced Raman scattering. Applied Optics, 1991, 30, 4700–4705. 62. V. M. Shalaev, Nonlinear Optics of Random Media, Springer, Berlin, Germany, 2000. 63. D. A. Genov, A. K. Sarychev, V. M. Shalaev, and A. Wei, Resonant field enhancements from metal nanoparticle arrays. Nano Letters, 2004, 4, 153–158. 64. D. L. Jeanmaire and R. P. Van Duyne, Surface Raman spectroelectrochemistry, part 1: heterocyclic, aromatic, and aliphatic amines adsorbed on the anodized silver electrode. Journal of Electroanalytical Chemistry, 1977, 84, 1–20. 65. K. A. Willets and R. P. Van Duyne, Localized surface plasmon resonance spectroscopy and sensing. Annual Review of Physical Chemistry, 2007, 58, 267–297. 66. T. R. Jensen, R. P. Van Duyne, S. A. Johnson, and V. A. Maroni, Surface-enhanced infrared spectroscopy: a comparison of metal island films with discrete and nondiscrete surface plasmons. Applied Spectroscopy, 2000, 54, 371–377. 67. C. R. Yonzon, D. A. Stuart, X. Zhang, A. D. McFarland, C. L. Haynes, and R. P. Van Duyne, Towards advanced chemical and biological nanosensors: an overview. Talanta, 2005, 67, 438–448. 68. N. F´elidj, J. Aubard, G. L´evi, J. R. Krenn, M. Salerno, G. Schider, B. Lamprecht, A. Leitner, and F. R. Aussenegg, Controlling the optical response of regular arrays of gold particles for surface-enhanced Raman scattering. Physical Review B, 2002, 65, 75419. 69. Y. P. Zhao, S. B. Shanmukh, and R. A. Dluhy, Polarized surface enhanced Raman and absorbance spectra of aligned silver nanorod arrays. Journal of Physical Chemistry B, 2006, 110, 3153–3157. 70. S. Shanmukh, L. Jones, J. Driskell, Y. Zhao, R. Dluhy, and R. A. Tripp, Rapid and sensitive detection of respiratory virus molecular signatures using a silver nanorod array SERS substrate. Nano Letters, 2006, 6, 2630–2636. 71. S. W. Bishnoi, C. J. Rozell, C. S. Levin, M. K. Gheith, B. R. Johnson, D. H. Johnson, and N. J. Halas, All-optical nanoscale pH meter. Nano Letters, 2006, 6, 1687–1692. 72. T. G. Roberts, J. N. Anker, and R. Kopelman, Magnetically modulated optical nanoprobes (MagMOONs) for
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83. 84.
85.
86.
87.
detection and measurement of biologically important ions against the natural background fluorescence of intracellular environments. Journal of Magnetism and Magnetic Materials, 2005, 293, 715–724. I.-Y. S. Lee, H. Suzuki, K. Ito, and Y. Yasuda, Surfaceenhanced fluorescence and reverse saturable absorption on silver nanoparticles. Journal of Physical Chemistry B, 2004, 108, 19368–19372. J. R. Lakowicz, Radiative decay engineering: biophysical and biomedical applications. Analytical Biochemistry, 2001, 298, 1–24. J. R. Lakowicz, Y. Shen, S. D’Auria, J. Malicka, J. Fang, Z. Gryczynski, and I. Gryczynski, Radiative decay engineering 2. effects of silver island films on fluorescence intensity, lifetimes, and resonance energy transfer. Analytical Biochemistry, 2002, 301, 261–277. J. R. Lakowicz, Y. Shen, Z. Gryczynski, S. D’Auria, and I. Gryczynski, Intrinsic fluorescence from DNA can be enhanced by metallic particles. Biochemical and Biophysical Research Communications, 2001, 286, 875–879. I. Gryczynski, J. Malicka, Y. Shen, Z. Gryczynski, and J. R. Lakowicz, Multiphoton excitation of fluorescence near metallic particles: enhanced and localized excitation. Journal of Physical Chemistry B, 2002, 106, 2191–2195. J. Yguerabide and E. E. Yguerabide, Light-scattering submicroscopic particles as highly fluorescent analogs and their use as tracer labels in clinical and biological applications, 1. Theory. Analytical Biochemistry, 1998, 262, 137–156. K. Sokolov, G. Chumanov, and T. M. Cotton, Enhancement of molecular fluorescence near the surface of colloidal metal films. Analytical Chemistry, 1998, 70, 3898–3905. J. Kummerlen, A. Leitner, H. Brunner, F. R. Aussenegg, and A. Wokaun, Enhanced dye fluorescence over silver island films: analysis of the distance dependence. Molecular Physics, 1993, 80, 1031–1046. J. Malicka, I. Gryczynski, C. D. Geddes, and J. R. Lakowicz, Metal-enhanced emission from indocyanine green: a new approach to in vivo imaging. Journal of Biomedical Optics, 2003, 8, 472–478. A. Dorfman, N. Kumar, and J.-I. Hahm, Highly sensitive biomolecular fluorescence detection using nanoscale ZnO platforms. Langmuir, 2006, 22, 4890–4895. H. G. Tompkins, A User’s Guide to Ellipsometry, Academic Press, Boston, MA, USA, 1993. R. M. A. Azzam and N. M. Bashara, Ellipsometry and Polarized Light, North-Holland, Amsterdam, The Netherlands, 1977. H. Arwin and I. Lundstrom, A reflectance method for quantification of immunological reactions on surfaces. Analytical Biochemistry, 1985, 145, 106–112. B. Trotter, G. Moddel, R. Ostroff, and G. R. Bogart, Fixed-polarizer ellipsometry: a simple technique to measure the thickness of very thin films. Optical Engineering, 1999, 38, 902–907. R. A. Chipman, Polarimetry, in: M. Bass, E. W. van Stryland, D. R. Williams, and W. L. Wolfe, Eds., Handbook of Optics, McGraw-Hill, New York, USA, 1994.
31
88. S. L. Jacques, J. C. Ramella-Roman, and K. Lee, Imaging skin pathology with polarized light. Journal of Biomedical Optics, 2002, 7, 329–340. 89. A. Weber, M. C. Cheney, Q. Y. J. Smithwick, and A. E. Elsner, Polarimetric imaging and blood vessel quantification. Optics Express, 2004, 12, 5178–5190. 90. J. M. Bueno and P. Artal, Double-pass imaging polarimetry in the human eye. Optics Letters, 1999, 24, 64–66. 91. P. Hariharan, Optical Interferometry, Academic Press, New York, USA, 2003. 92. P. Hua, J. P. Hole, J. S. Wilkinson, G. Proll, J. Tschmelak, G. Gauglitz, M. A. Jackson, R. Nudd, H. M. T. Griffith, R. A. Abuknesha, J. Kaiser, and P. Kraemmer, Integrated optical fluorescence multisensor for water pollution. Optics Express, 2005, 13, 1124–1130. 93. C. B. Sua, J. Kameoka, B. Ilic, K.-H. Chu, and K.-A. Chang, Properties of an optical multipass surface plasmon resonance technique. Applied Physics Letters, 2006, 89, 071101. 94. X. Liu, Z. Cao, Q. Shen, and S. Huang, Optical sensor based on Fabry-Perot resonance modes. Applied Optics, 2003, 42, 7137–7140. 95. K. Ebling, Integrated Optoelectronics, Springer, Heidelberg, Germany, 1993. 96. K. Tiefenthaler and W. Lukosz, Grating couplers as integrated optical humidity and gas sensors. Thin Solid Films, 1985, 126, 205–211. 97. T. E. Plowman, J. D. Durstchi, H. K. Wang, D. A. Christensen, J. N. Herron, and W. M. Reichert, Multipleanalyte fluoroimmunoassay using an integrated optical waveguide sensor. Analytical Chemistry, 1999, 71, 4344–4352. 98. A. N. Asanov, W. W. Wilson, and P. B. Oldham, Regenerable biosensor platform: a total internal reflection fluorescence cell with electrochemical control. Analytical Chemistry, 1998, 70, 1156–1163. 99. G. L. Duveneck, M. Pawlak, D. Neuschafer, E. Bar, W. Budach, U. Pieles, and M. Ehrat, Novel bioaffinity sensors for trace analysis based on luminescence excitation by planar waveguides. Sensors and Actuators B, 1997, 38, 88–95. ˇ 100. J. Dost´alek, J. Ctyrok´ y, J. Homola, E. Brynda, ˇ ˇ M. Skalsk´y, P. Nekvindov´a, J. Spirkov´ a, J. Skvor, and J. Schr¨ofel, Surface plasmon resonance biosensor based on integrated optical waveguide. Sensors and Actuators B, 2001, 76, 8–12. 101. A. Brecht, A. Klotz, C. Barzen, G. Gauglitz, R. D. Harris, G. R. Quigley, J. S. Wilkinson, P. Sztajnbok, R. Abuknesha, J. Gascon, A. Oubina, and D. Barcelo, Optical immunoprobe development for multiresidue monitoring in water. Analytica Chimica Acta, 1998, 362, 69–79. 102. N. J. Goddard, D. Pollard-Knight, and C. H. Maule, Realtime biomolecular interaction analysis using the resonant mirror sensor. The Analyst, 1994, 119, 583–588. 103. V. A. Dotsenko, A. L. Diikov, and T. A. Vartanyan, Label-free biosensor using an optical waveguide with induced grating of variable strength. Sensors and Actuators B, 2003, 94, 116–121. 104. A. Sharon, D. Rosenblatt, A. A. Friesem, H. G. Weber, H. Engel, and R. Steingrueber, Light modulation with
32
105.
106.
107.
108.
109.
110.
111.
112.
113.
114.
115.
116.
117.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS resonant grating-waveguide structures. Optics Letters, 1996, 21, 1564–1566. I. Abdulhalim, Anisotropic layers in waveguides for tuning and tunable filtering. Proceedings of the SPIE, 2006, 6135, 179–188. B. T. Cunningham, B. Lin, J. Qiu, P. Li, J. Pepper, and B. Hugh, A plastic colorimetric resonant optical biosensor for multiparallel detection of label-free biochemical interactions. Sensors and Actuators B, 2002, 85, 219–226. L. L. Chan, B. T. Cunningham, P. Y. Li, and D. Puff, Self-referenced assay method for photonic crystal biosensors: application to small molecule analytes. Sensors and Actuators B, 2007, 120, 392–398. I. D. Block, L. L. Chan, and B. T. Cunningham, Photonic crystal optical biosensor incorporating structured lowindex porous dielectric. Sensors and Actuators B, 2006, 120, 187–193. Z. Liron, L. M. Tender, J. P. Golden, and F. S. Ligler, Voltage-induced inhibition of antigen-antibody binding at conducting optical waveguides. Biosensors and Bioelectronics, 2002, 17, 489–494. J. P. Bearinger, J. V¨or¨os, J. A. Hubbell, and M. Textor, Electrochemical optical waveguide lightmode spectroscopy (EC-OWLS): a pilot study using evanescentfield optical sensing under voltage control to monitor polycationic polymer adsorption onto indium tin oxide (ITO)-coated waveguide chips. Biotechnology and Bioengineering, 2003, 82, 465–473. D. R. Dunphy, S. B. Mendes, S. S. Saavedra, and N. R. Armstrong, The electroactive integrated optical waveguide (EA-IOW): ultrasensitive spectroelectrochemistry of submonolayer adsorbates. Analytical Chemistry, 1997, 69, 3086–3094. R. Cush, J. M. Cronin, W. J. Stewart, C. H. Maule, J. Molloy, and N. J. Goddard, The resonant mirror: a novel optical biosensor for direct sensing of biomolecular interactions part I: principle of operation and associated instrumentation. Biosensors and Bioelectronics, 1999, 8, 347–354. M. Zourob, S. Mohr, B. J. Treves-Brown, P. R. Fielden, M. B. McDonnell, and N. J. Goddard, An integrated metal clad leaky waveguide sensor for detection of bacteria. Analytical Chemistry, 2005, 77, 232–242. M. Zourob, A. Simonian, J. Wild, S. Mohr, X. Fan, I. Abdulhalim, and N. J. Goddard, Optical leaky waveguide biosensors for the detection of organophosphorus pesticides. The Analyst, 2007, 132, 114–120. R. Horv´ath, H. C. Pedersen, N. Skivesen, D. Selmeczi, and N. B. Larsen, Optical waveguide sensor for online monitoring of bacteria. Optics Letters, 2003, 28, 1233–1235. M. Zourob, J. J. Hawkes, W. T. Coakley, B. J. TrevesBrown, P. R. Fielden, M. B. McDonnell, and N. J. Goddard, Optical leaky waveguide sensor for detection of bacteria with ultrasound attractor force. Analytical Chemistry, 2005, 77, 6163–6168. M. Zourob, S. Mohr, B. J. Treves-Brown, P. R. Fielden, M. B. McDonnell, and N. J. Goddard, An integrated optical leaky waveguide sensor with electrically induced concentration system for the detection of bacteria. Lab on a Chip, 2005, 5, 1360–1365.
118. P. Dress and H. Franke, Increasing the accuracy of liquid analysis and pH-value control using a liquid-core waveguide. Review of Scientific Instruments, 1997, 68, 2167–2171. 119. P. Dasgupta, G. Zhang, J. Li, C. Boring, S. Jambunathan, and R. Al-Horr, Luminescence detection with a liquid core waveguide. Analytical Chemistry, 1999, 71, 1400–1407. 120. W. P. Risk, H.-C. Kim, R. D. Miller, H. Temkin, and S. Gangopadhyay, Optical waveguides with an aqueous core and a low-index nanoporous cladding. Optics Express, 2004, 12, 6446–6455. 121. J. Myong-Song and T. Vo-Dinh, Miniature biochip system for detection of Escherichia coli O157:H7 based on antibody-immobilized capillary reactors and enzymelinked immunosorbent assay. Analytica Chimica Acta, 2004, 507, 115–121. 122. B. H. Weigl and O. S. Wolfbeis, Capillary optical sensors. Analytical Chemistry, 1994, 66, 3323–3327. 123. F. S. Ligler, M. Breimer, J. P. Golden, D. A. Nivens, J. P. Dodson, T. M. Green, D. P. Haders, and O. A. Sadik, Integrating waveguide biosensor. Analytical Chemistry, 2002, 74, 713–719. 124. O. S. Wolfbeis, Fiber-optic chemical and biosensors. Analytical Chemistry, 2006, 78, 3859–3874. 125. B. Kuswandi, R. Andres, and R. Narayanaswamy, Optical fiber biosensors based on immobilised enzymes. The Analyst, 2001, 126, 1469–1491. 126. D. Monk and D. R. Walt, Optical fiber-based biosensors. Analytical and Bioanalytical Chemistry, 2004, 379, 931–945. 127. D. R. Walt and J. Epstein, Fluorescence-based fiber optic arrays: a universal platform for sensing. Chemical Society Reviews, 2003, 32, 203–214. 128. P. M. Kasili, J. M. Song, and T. Vo-Dinh, Optical sensor for the detection of Caspase-9 activity in a single cell. Journal of the American Chemical Society, 2004, 126, 2799–2806. 129. J. M. Pitarke, V. M. Silkin, E. V. Chulkov, and P. M. Echenique, Theory of surface plasmons and surfaceplasmon polaritons. Reports on Progress in Physics, 2007, 70, 1–87. 130. J. Homola, G. Schwotzer, R. Willsch, W. Ecke, and H. Bartelt, Fiber optic sensor for adsorption studies using surface plasmon resonance. Proceedings of the SPIE, 1995, 2508, 324–333. 131. M. M. B. Vidal, R. Lopez, S. Aleggret, J. AlonsoChamarro, I. Arces, and J. Mateo, Determination of probable alcohol yield in musts by means of an SPR optical sensor. Sensors and Actuators B, 1993, 11, 455–459. 132. B. Liedberg, I. Lundstrom, and E. Stenberg, Principles of biosensing with an extended coupling matrix and surface plasmon resonance. Sensors and Actuators B, 1993, 11, 63–72. 133. H. Raether, Surface Plasmons on Smooth and Rough Surfaces and on Gratings, Springer, Berlin, Germany, 1988. 134. G. Hass, M. Francombe, and R. W. Hoffman (eds), Physics of Thin Films, Vol 9, Academic Press, New York, USA, 1977.
OVERVIEW OF OPTICAL BIOSENSING TECHNIQUES 135. E. Kretschmann and H. Raether, Radiative decay of nonradiative surface plasmons excited by light. Zeitschrift f¨ur Naturforschung A, 1968, 23, 2135–2136. 136. A. Otto, Excitation of nonradiative surface plasma waves in silver by the method of frustrated total reflection. Zeitschrift f¨ur Physik, 1968, 216, 398–410. 137. C. Thirsturp, W. Zong, M. Borre, H. Neff, H. C. Pedersen, and G. Holzhueter, Diffractive optical coupling elements for surface plasmon resonance sensors. Sensors and Actuators B, 2004, 100, 298–308. 138. M. Piliarik, H. Vaisocherov´a, and J. Homola, Towards parallelized surface plasmon resonance sensor platform for sensitive detection of oligonucleotides. Sensors and Actuators B, 2007, 121, 187–193. 139. P. Adam, J. Dost´alek, and J. Homola, Multiple surface plasmon spectroscopy for study of biomolecular systems. Sensors and Actuators B, 2006, 113, 774–781. 140. J. Dost´alek, J. Homola, and M. Miler, Rich information format surface plasmon resonance biosensor based on array of diffraction gratings. Sensors and Actuators B, 2005, 107, 154–161. 141. R. C. Jorgensen and S. S. Yee, A fiber-optic chemical sensor based on surface plasmon resonance. Sensors and Actuators B, 1993, 12, 213–220. 142. V. Kanda, P. Kitov, D. R. Budle, and M. T. McDermott, Surface plasmon resonance imaging measurements of the inhibition of Shiga-like toxin by synthetic multivalent inhibitors. Analytical Chemistry, 2005, 77, 7497–7504. 143. U. Aoki, K. Shimada, M. Nagano, M. Kawai, and H. Koga, A novel approach to protein expression profiling using antibody microarrays combined with surface plasmon resonance technology. Proteomics, 2005, 5, 2396–2401. 144. F. Yu, D. F. Yao, and W. Knoll, Surface plasmon field-enhanced fluorescence spectroscopy studies of the interaction between an antibody and its surface-coupled antigen. Analytical Chemistry, 2003, 75, 2610–2617. 145. B. P. Nelson, M. R. Liles, K. B. Frederick, R. M. Corn, and R. M. Goodman, Label-free detection of 16S ribosomal RNA hybridization on reusable DNA arrays using surface plasmon resonance imaging. Environmental Microbiology, 2002, 4, 735–743. 146. E. A. Smith, W. D. Thomas, L. L. Kiessling, and R. M. Corn, Surface plasmon resonance imaging studies of protein-carbohydrate interactions. Journal of the American Chemical Society, 2003, 125, 6140–6148. 147. G. J. Wineger, A. W. Wark, H. J. Lee, E. Conder, T. Saeki, S. Fang, and R. M. Corn, Real-time surface plasmon resonance imaging measurements for the multiplexed determination of protein adsorption/desorption kinetics and surface enzymatic reactions on peptide microarrays. Analytical Chemistry, 2004, 76, 5677–5684. 148. D. Wassaf, G. Kuang, K. Kopacz, Q.-L. Wu, Q. Nguyen, M. Toews, J. Cosic, J. Jacques, S. Wiltshire, J. Lambert, C. C. Pazmany, S. Hogan, R. C. Ladner, A. E. Nixon, and D. J. Sexton, High-throughput affinity ranking of antibodies using surface plasmon resonance microarrays. Analytical Biochemistry, 2006, 351, 241–253. 149. J.-S. Yuk, M.-J. Lee, U.-R. Kim, and K.-S. Ha, Analysis of blood proteins on protein arrays with a spectral surface plasmon resonance biosensor. Current Applied Physics, 2007, 7, 102–107.
33
150. D. Nedelkov and R. W. Nelson, Surface plasmon resonance mass spectrometry: recent progress and outlooks. Trends in Biotechnology, 2003, 21, 301–305. 151. F. Kou and T. Tamir, Range extension of surface plasmons by dielectric layers. Optics Letters, 1987, 12, 367–369. 152. G. G. Nenninger, P. Tobika, J. Homola, and S. S. Yee, Long-range surface plasmons for high-resolution surface plasmon resonance sensors. Sensors and Actuators B, 2001, 74, 145–151. 153. R. Slav´ık and J. Homola, Ultrahigh resolution long range surface plasmon-based sensor. Sensors and Actuators B, 2007, 123, 10–12. 154. A. B. Matsko, A. A. Savchenkov, D. Strekalov, V. S. Ilchenko, and L. Maleki, Review of Applications of Whispering-Gallery Mode Resonators in Photonics and Nonlinear Optics, IPN Progress Report 42–162, August 15, 2005, The Interplanetary Network Progress Report, Jet Propulsion Laboratory, California institute of Technology. 155. K. Vahala (ed), Optical Microcavities, World Scientific, Singapore, 2004. 156. A. Serpenguezel, S. Arnold, and G. Griffel, Excitation of resonances of microspheres on an optical fiber. Optics Letters, 1994, 20, 654–656. 157. J. W. Strutt, The Theory of Sound, Dover, New York, USA, 1945. 158. Lord Rayleigh, Further applications of Bessel’s functions of high order to the whispering gallery and allied problems. Philosophical Magazine, 1914, 27, 100–109. 159. R. Ulrich, Theory of the prism-film coupler by plane wave analysis. Journal of the Optical Society of America, 1970, 60, 1337–1350. 160. P. K. Tien and R. Ulrich, Theory of prism-film coupler and thin film light guides. Journal of the Optical Society of America, 1970, 60, 1325–1336. 161. A. V. Chelnokov and J.-M. Lourtioz, Optimized coupling into planar waveguides with cylindrical prisms. Electronics Letters, 1995, 31, 269–271. 162. D. Sarid, P. J. Cressman, and R. L. Holman, Highefficiency prism coupler for optical waveguides. Applied Physics Letters, 1978, 33, 514–515. 163. V. S. Ilchenko, X. S. Yao, and L. Maleki, Pigtailing the high-Q microsphere cavity: a simple fiber coupler for optical whispering-gallery modes. Optics Letters, 1999, 24, 723–725. 164. V. S. Ilchenko, X. S. Yao, and L. Maleki, Microsphere integration in active and passive photonics devices. Proceedings of the SPIE, 2000, 3930, 154–162. 165. A. Yalcin, K. C. Popat, J. C. Aldridge, T. A. Desai, J. Hryniewicz, N. Chbouki, B. E. Little, O. King, V. Van, ¨ u, and S. Chu, D. Gill, M. F. Anthes-Washburn, M. S. Unl¨ B. B. Goldberg, Optical sensing of biomolecules using microring resonators. IEEE Journal of Selected Topics in Quantum Electronics, 2006, 12, 148–155. 166. C.-Y. Chao and L. J. Guo, Biochemical sensors based on polymer microrings with sharp asymmetrical resonances. Applied Physics Letters, 2003, 83, 1527–1529. 167. B. E. Little, J.-P. Laine, D. R. Lim, H. A. Haus, L. C. Kimerling, and S. T. Chu, Pedestal antiresonant reflecting waveguides for robust coupling to microsphere resonators
34
168.
169.
170.
171.
172.
173.
174.
175.
176.
177.
178.
179.
180.
181.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS and for microphotonic circuits. Optics Letters, 2000, 25, 73–75. F. Vollmer, D. Braun, A. Libchaber, M. Khoshsima, I. Teraoka, and S. Arnold, Protein detection by optical shift of a resonant microcavity. Applied Physics Letters, 2002, 80, 4057–4059. H. Zhu, J. D. Suter, I. M. White, and X. Fan, Aptamer based microsphere biosensor for thrombin detection. Sensors, 2006, 6, 785–795. F. Vollmer, S. Arnold, D. Braun, I. Teraoka, and A. Libchaber, Multiplexed DNA quantification by spectroscopic shift of two microsphere cavities. Biophysical Journal, 2003, 85, 1974–1979. R. W. Boyd and J. E. Heebner, Sensitive disk resonator photonic biosensor. Applied Optics, 2001, 40, 5742–5747. C.-Y. Chao and L. J. Guo, Biochemical sensors based on polymer microrings with sharp asymmetrical resonance. Applied Physics Letters, 2003, 83, 1527–1529. A. M. Armani and K. J. Vahala, Heavy water detection using ultra-high-Q microcavities. Optics Letters, 2006, 31, 1896–1898. H. Zhu, I. M. White, J. D. Suter, M. Zourob, and X. Fan, Integrated refractive index optical ring resonator detector for capillary electrophoresis. Analytical Chemistry, 2007, 79, 930–937. W. Kim, V. P. Safonov, V. M. Shalaev, and R. L. Armstrong, Fractals in microcavities: giant coupled, multiplicative enhancement of optical responses. Physical Review Letters, 1999, 82, 4811–4814. S. Blair and K. Zheng, Microresonator-enhanced Raman amplification. Journal of the Optical Society of America B, 2006, 23, 1117–1123. I. M. White and X. Fan, Demonstration of composite microsphere cavity and surface enhanced Raman spectroscopy for improved sensitivity. Proceedings of the SPIE, 2005, 5994, 59940G. V. S.-Y. Lin, K. Motesharei, K.-P. S. Dancil, M. J. Sailor, and M. R. Ghadiri, A porous silicon-based optical interferometric biosensor. Science, 1997, 278, 840–843. S. Chan, P. M. Fauchet, Y. Li, L. J. Rothberg, and B. L. Miller, Porous silicon microcavities for biosensing applications. Physica Status Solidi A, 2000, 182, 541–546. S. Xiao and N. A. Mortensen, Highly dispersive photonic band-gap-edge optofluidic sensors. Journal of European Optical Society, 2006, 1, 06026. E. Chow, A. Grot, L. W. Mirkarimi, M. Sigalas, and G. Girolami, Ultracompact biochemical sensor built with
182.
183.
184.
185.
186.
187.
188.
189.
190.
191.
192.
193.
194.
two-dimensional photonic crystal microcavity. Optics Letters, 2004, 29, 1093–1095. A. Lakhtakia, M. W. McCall, J. A. Sherwin, Q. H. Wu, and I. J. Hodgkinson, Sculptured-thin-film spectral holes for optical sensing of fluids. Optics Communications, 2001, 194, 33–46. A. Lakhtakia and M. W. Horn, Bragg-regime engineering by columnar thinning of chiral sculptured thin films. Optik, 2003, 114, 556–560. S. M. Pursel, M. W. Horn, and A. Lakhtakia, Tuning of sculptured-thin-film spectral-hole filters by postdeposition etching. Optical Engineering 2007, 46, 040507. H. Tan, O. Ezekoye, J. van der Schalie, M. W. Horn, A. Lakhtakia, J. Xu, and W. D. Burgos, Biological reduction of nano-engineered iron(III) oxide sculptured thin films. Environmental Science and Technology, 2006, 40, 5490–5495. T. Vo-Dinh and B. M. Cullum, Biosensors and biochips: advances in biological and medical diagnostics. Fresenius Journal of Analytical Chemistry, 2000, 366, 540–551. T. Vo-Dinh, B. M. Cullum, and D. L. Stokes, Nanosensors and biochips: frontiers in biomolecular diagnostics. Sensors and Actuators B, 2001, 74, 2–11. T. Vo-Dinh, J. P. Alarie, B. M. Cullum, and G. D. Griffin, Antibody-based nanoprobe for measurements in a single cell. Nature Biotechnology, 2000, 18, 764–767. P. W. Barone, S. Baik, D. A. Heller, and M. S. Strano, Near-infrared optical sensors based on single-walled carbon nanotubes. Nature Materials, 2005, 4, 86–92. S. M. Bachilo, M. S. Strano, C. Kittrell, R. H. Hauge, and R. E. Smalley, Structure-assigned optical spectra of single-walled carbon nanotubes. Science, 2002, 298, 2361–2366. P. Cherukuri, S. M. Bachilo, S. H. Litovsky, and R. B. Weisman, Near-infrared fluorescence microscopy of single-walled carbon nanotubes in phagocytic cells. Journal of the American Chemical Society, 2004, 126, 15638–15639. J. Zhang, H. P. Lang, F. Huber, A. Bietsch, W. Grange, U. Certa, R. Mckendry, H.-J. G¨untherodt, M. Hegner, and Ch. Gerber, Rapid and label-free nanomechanical detection of biomarker transcripts in human RNA. Nature Nanotechnology, 2006, 1, 214–220. F. J. Picard and M. G. Bergeron, Rapid molecular theranostics in infectious diseases. Drug Discovery Today, 2002, 7, 1092–1101. P. Tang and T. Venables, ‘Smart’ homes and telecare for independent living. Journal of Telemedicine and Telecare, 2000, 6, 8–14.
26 Localized Surface Plasmon Resonance (LSPR) Spectroscopy in Biosensing Alexander Vaskevich and Israel Rubinstein Department of Materials and Interfaces, Weizmann Institute of Sciences, Rehovot, Israel
1 INTRODUCTION
Interaction of electromagnetic waves with the interface between a metal and a dielectric medium can result in excitation of electron density oscillations called surface plasmon (SP) polaritons. In the case of a planar interface the SP propagates along the surface. At interfaces with a sharp roughness on the nanometer scale, as well as in dispersed metal structures, these oscillations are confined to high-curvature areas. These two types of electronic excitations are known as propagating and localized SPs, respectively, and can be monitored using an appropriate experimental setup. Propagating SPs are usually excited in the total internal reflection mode (Kretschmann configuration) using a complicated experimental setup. Observation of localized SPs is considerably simpler and can be done with standard spectrophotometric equipment in the transmission (or reflection) configuration. The conditions for excitation of SPs and light absorption are sensitive to the dielectric properties of the medium adjacent to the metal–dielectric interface. A major advantage of SP spectroscopy with respect to other detection methods is its inherent label-free nature: the measured quantity is the optical response of the metal nanostructures, which is sensitive to changes in the dielectric constant of the medium. The analytical capabilities of propagating surface plasmon resonance (SPR)
spectroscopy have been widely recognized, and since 1990 several commercial instruments have become available.1 For more than two decades, starting from the late 1970s, sensing applications based on localized SPs have been focused on surface-enhanced Raman spectroscopy (SERS).2 Development of biosensor applications of localized surface plasmon resonance (LSPR) has gained momentum only recently, in relation with the rapid progress in nanotechnology.3 The sensitivity of the localized SP absorbance to changes in the dielectric properties of the immediate environment has been well understood since the theory describing light scattering of small, isolated spherical metal particles was development by Mie in 1908. Assuming that the metal particles with their immediate surrounding medium are noninteracting and homogeneous, solution of Maxwell equations gives the dependence of the absorbance on bulk optical dielectric functions and geometric factors3 : ε2 (ω) ω 3/2 σext (ω) = 9 εm V0 c [ε1 (ω) + 2εm ]2 + ε2 (ω)2 (1) where σext is the extinction cross-section at angular frequency ω; ε1 and ε2 are the real and imaginary parts of the metal dielectric function at angular frequency ω, respectively; εm is the dielectric constant of the medium; V0 is the particle volume; and c is the velocity of light. According to the
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 1.2
Extinction
1.0
0.8
3 2 1
0.6
0.4 400
(a)
500 600 700 Wavelength (nm)
(b)
(c)
Figure 1. Transmission spectra (a) and AFM images (b,c) (600 × 600 nm2 ) of Au nanoparticulate systems. Part (a) shows (1) citrate-stabilized Au NPs (mean diameter, 14 ± 2 nm) in water; (2) a monolayer of citrate-stabilized Au NPs immobilized on mercaptosilane-modified glass; an image of the monolayer is shown in (b); (3) Au island film (nominal thickness, 5.0 nm) evaporated on aminosilane-modified glass; an image of the island film is shown in (c). Spectra 2 and 3 were taken in air; all spectra are normalized to maximum extinction. Details on the preparation and immobilization of Au NPs are given in Ref. 5 and on evaporated Au film in Ref. 6. [Reprinted with permission from Doron-Mor et al.6 Copyright 2004, American Chemical society.]
theory, a SP band appears when ε1 (ω) = −2εm if ε2 (ω) is small or only weakly depends on ω. Figure 1(a) presents a transmission spectrum of 14 ± 2 nm Au nanoparticles (NPs) in water, showing a LSPR band at ∼ 520 nm. The value for the SP absorption maximum predicted by the Mie equation is 516 nm (water refractive index is n1 = 1.33, therefore the condition for maximum extinction is ε1 = −2 × 1.332 = −3.54, which is the value of ε1 at 516 nm according to classical data4 ), in good agreement with the experimental value. The SP bands of Au and Ag nanostructures are positioned in the visible-to-NIR part of the optical spectrum. The chemical inertness of Au and the relative stability of Ag make them the metals-of-choice for LSPR-based sensors. The sensitivity of LSPR to the immediate dielectric environment is seen in the spectra of Au NPs in solution and in air (Figure 1a, spectra 1 and 2). The increase in the dielectric constant from air (ε1 = 1) to aqueous solution (ε1 ≈ 1.332 ) causes a red shift of the maximum of the LSPR band from 514 to 520 nm, in accordance with the Mie theory, although the influence of the solid substrate on the resonance conditions7 should be taken into account for Au NPs immobilized on glass. In most cases the optical properties of metal nanostructures are considerably more complex than those of isolated metal spheres described quantitatively by the original Mie theory. Hence, the LSPR band
depends not only on the dielectric properties of the metal and the adjacent medium, but also on geometric factors, namely, shape of the NPs or islands and the lateral separation between individual nanostructures. Interaction between charge oscillations in the individual particles results in strong coupling of the SPs and shift of the resonance wavelength. Comparison of the images in Figure 1(b,c) shows that evaporated metal islands are irregularly shaped and less separated compared to the Au NP film. These differences in morphology influence the transmission spectrum, that is, SP coupling in the island film due to the relatively small interisland separation and nonsymmetric island shape effect a red shift of the extinction band compared to the solution-based and immobilized Au NPs (Figure 1a). Various types of subwavelength metal nanostructures supporting localized SPs have been used successfully in biosensing. These include solution-based8–11 and immobilized12 NPs, evaporated metal island films,13–17 continuous semitransparent films with nanoholes,18 and sandwich structures.19–22 A particular class among these biosensors comprises systems based on monitoring optical changes induced by spatial rearrangement/aggregation of NP–biomolecule conjugates. This kind of biosensors, most commonly used in solution and particularly effective in DNA
LSPR SPECTROSCOPY IN BIOSENSING
recognition,22–24 is outside the scope of this chapter. Here we focus on systems where the spatial distribution of the metal nanostructures is assumed to remain unchanged. Development of LSPR sensors has been stimulated by the desire to simplify the experimental system and the possibility to use common spectrophotometric equipment. Indeed LSPR experimental setups have demonstrated substantial simplification compared to those used in propagating SPR measurements. In comparing the two approaches one should take into account, however, that engineering of a high-throughput system based on LSPR would necessarily include complex sample handling technology similar to that used in commercial SPR instruments. It therefore seems that practical LSPR biosensors may be more successful in applications where propagating SPR systems are difficult to apply, such as remote control or disposable chips. 2 METAL NANOSTRUCTURES IN LSPR SENSING 2.1
Solution-based and Immobilized Metal Nanoparticles (NPs)
In the context of this chapter, LSPR biosensing using metal NPs in solution is based on formation of NP–biomolecule conjugates without aggregation; systems based on bioinduced NP aggregation are beyond the scope of this text. Although both Au and Ag NPs have been widely used as markers in biological systems, Au NPs have been the system-of-choice in the preparation of LSPR biosensors. Water-soluble citrate-stabilized Au NPs have been almost exclusively used in solution-based LSPR biosensing, as they allow adjustment to the particular system requirements as well as tuning of the average size between ca. 5 and 50 nm. Preparation procedures for citratestabilized Au NPs are well established and available in the literature (see a recent comprehensive review25 ), providing NPs with a narrow size distribution (size dispersion of ca. 10%). Immobilization of receptor molecules on the NP surfaces is performed by exploiting either electrostatic interactions11,26 or exchange of the citrate stabilizer with sulfur-containing receptor molecules.27 Immobilization of NPs on oxide substrates (planar or fiber-shaped glass and quartz; mica;
3
native silicon oxide on silicon wafers; ITO) almost always follows the general protocol of binding negatively-charged citrate-stabilized Au NPs to surfaces modified with an amino- or mercaptosilane layer5,28,29 or with a positively charged polyelectrolyte.30 The negatively charged immobilized NPs are well separated due to electrostatic repulsion,5 and the interparticle distance can be tuned by variation of the ionic strength31 and NP concentration in solution.12 This approach leads to formation of NP monolayers with surface densities up to ca. 30% (with respect to hexagonal close-packing); the SP band position does not vary with surface coverage, indicating absence of NP aggregation. Electroless deposition of Au on immobilized NPs promotes increase of the SP band intensity and was applied to the preparation of biosensors.32,33 NPs can also be easily immobilized on curved surfaces including optical fibers and microfluidic channels, making this method versatile and attractive for various applications. A noted problem in electrostatic immobilization of Au NPs on solid substrates is its sensitivity to changes in solution composition and particularly to drying, which causes aggregation and a large change in the optical properties.5,12
2.2
Nanostructured Films Prepared by Metal Evaporation
Vacuum evaporation of metal island films on transparent substrates (glass, quartz, mica, polymers) presents a convenient approach to the preparation of LSPR transducers. Both metal island films and arrays of nanoholes in continuous metal films have been prepared by vacuum evaporation. Specific issues related to sensor optimization include control over the shape and surface density of the metal islands or holes, adhesion between the metal and the substrate, stability of the optical properties, and shelf life. The weak adhesion of evaporated films of Au and Ag to oxide substrates such as glass or mica is well known and results in uncontrolled detachment of metal islands upon interaction with solvents.34–36 Note that improved adhesion of sputtered Au island films (15 nm nominal thickness) to bare glass was found after high-temperature annealing at 450 ◦ C,34 but this type of island films
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
was not used for biosensing. Thin (ca. 5–10 nm) evaporated Cr and Ti underlayers, widely used as adhesion promoters for thick Au films, were applied in the preparation of nanohole structures supporting LSPR.18,37 Drawbacks associated with the use of metallic adhesion promoters for Ag and Au island films include (i) the good wetting between the two metal layer hampers island formation38 and (ii) substantial decrease of the total transmittance of the films.33 Use of an organic adhesion layer presents a viable alternative to evaporated metal underlayers. Hence, excellent adhesion of Au island films was achieved by metal evaporation on either a mercaptosilane6,38,39 or aminosilane40,41 layer on glass or quartz substrates. In another study, pretreatment of mica with Triton X-100 prior to evaporation of Ag islands furnished almost 10-fold increase in the force needed to peel metal islands from the surface by an AFM tip.35 Control over the morphology and optical properties of metal island films evaporated on homogeneous substrates can be achieved by variation of the evaporation rate and by postdeposition treatment. We have studied systematically the morphology evolution in Au island films on mica, quartz, and (bare and silanized) glass, as a function of film thickness up to the formation of a percolated layer.6,14,15,42,43 Evaporation at low rates of 0.005–0.01 nm s−1 enabled sufficient coalescence of small islands into larger aggregates. This corroborates well with earlier studies on the preparation of SERS-active Ag island films by metal evaporation onto bare glass.44 Evaporation of metal island films on amino- and mercaptosilane-modified oxide surfaces provides good adhesion, as shown in the case of continuous Au films.39 Postdeposition annealing, used for improvement of the optical properties of metal island films (see Section 3.1), may be incompatible with the organic adhesion layer, as the latter may not survive the thermal treatment. However, we found that when the annealing temperature does not exceed ca. 200 ◦ C, strong adhesion of Au islands to the substrate is preserved. The morphology of island films was characterized by AFM, high-resolution scanning electron microscope (HRSEM)6 and cross-sectional TEM. The latter two techniques provide complementary quantitative information on the 3D topography and projection area of the metal islands. Representative images of as-prepared and
annealed 5.0-nm Au island films evaporated on silanized glass are shown in Figure 2. In the unannealed film, reorganization of the shape is not complete; hence the HRSEM image shows a large fraction of elongated structures (Figure 2b). After annealing, the 2D projection of the islands becomes much more regular (Figure 2d) while cross-sectional TEM shows substantial increase in island height and interisland spacing compared to the unannealed film. The general shape of the islands after annealing is close to oblate ellipsoid, supporting an earlier suggestion45 not verified by cross-sectional imaging. Transmission UV–vis spectra of unannealed and annealed films of varied thicknesses are shown in Figure 3. The gradual red shift of the SP band maximum with increase of the film thickness reflects enhanced interisland coupling. Annealing of the films in air increases the average separation between islands, as shown in Figure 2 for a 5.0-nm-thick film. This results in a substantial blue
50 nm
(a) 50 nm
(c)
100 nm
(b) 100 nm
(d)
Figure 2. Cross-sectional TEM (a,c) and HRSEM (b,d) images of 5.0-nm (nominal thickness) gold island films on silanized glass. (a,b) Before annealing, (c,d) after annealing, 20 h at 200 ◦ C. Solid straight lines in (a) and (c) serve as a guide to the eye, representing the (removed) glass substrate and showing that islands were not displaced during the multistep sample preparation (embedding in epoxy, removing the glass substrate, cutting a ca. 50-nm slice). [Adapted from Karakouz et al.43 ]
LSPR SPECTROSCOPY IN BIOSENSING 0.8
0.5
15 nm
7.5 nm
0.5
5.0 nm 2.5 nm
7.5 nm Extinction
Extinction
0.4
10 nm
0.6
0.3
0.3
(a)
5.0 nm
0.2 2.5 nm
0.2 0.1
15 nm 10 nm
0.7
0.4
5
0.1
1.0 nm
0 300 400 500 600 700 800 900 1000 (b) Wavelength (nm)
1.0 nm
0 300 400 500 600 700 800 900 1000 Wavelength (nm)
Figure 3. Transmission UV–vis spectra of ultrathin gold island films on silanized glass, (a) unannealed and (b) annealed for 20 h at 200 ◦ C. Nominal thicknesses are indicated. [Reprinted with permission from Doron-Mor et al.6 Copyright 2004, American Chemical Society.]
shift of the SP band maximum and a much sharper extinction peak. Up to a nominal thickness of ca. 10 nm the SP band is well-defined for films prepared under these conditions (Figure 3). Hence, evaporation on silanized glass followed by thermal annealing presents a simple and convenient preparation scheme for Au island films displaying well-defined SP absorbance.6,14,15,42 Another approach used for preparation of nanostructured Ag and Au films is nanosphere lithography (NSL), based on patterning of a substrate with densely-packed polymeric or glass microspheres serving as a mask for metal evaporation.46–48 After removal of the mask, an array of triangular metal nanostructures remains on the surface. This patterning method allows preparation of monodisperse metal nanostructures on the centimeter scale; however, lateral inhomogeneity on the millimeter scale remains an unresolved problem in the colloid mask approach. Relatively small areas are homogeneous, thus the optical properties vary substantially between different locations on the sample.49,50 The general scheme for the preparation of a metal island film using evaporation through a mask of densely-packed microspheres is shown in Figure 4. Variation of the sphere size and the nominal thickness of the evaporated metal allows control of the metal NP shape and size, as depicted in Figure 4. The LSPR band position can be tuned in a rather large wavelength range. The triangle footprint and large interisland
separation are thought to be advantageous in sensing applications.51 As in the case described above of metal evaporation on unpatterned surfaces, thermal annealing is a simple way to affect NP shape. In the case of metal deposition through a microsphere mask the NPs are hundreds of nanometers in size and annealing effects island reshaping with no substantial island displacement. Upon annealing the well-defined crystallographic habit seen in Figure 4(a) disappears and the NPs become roundshaped,52 while the SP band maximum is shifted to shorter wavelengths by as much as 200 nm. These rather dramatic changes in LSPR spectra, as well as those described above for the random evaporated metal island films, illustrate the sensitivity of the LSPR extinction spectra to change in metal island shape, presenting a potential difficulty in sensing applications. Several sandwich-type structures combining a flat, continuous metal film and an island53 or a rough metal47 film, as well as a combination of a metal island film and bound NPs,22 were used as LSPR biosensors. An example of the preparation of a sandwich-type LSPR transducer based on encapsulation of silica beads in Au21 is shown in Figure 5. Recently nanostructured metal substrates consisting of nanosize holes in thin, continuous metal films have been developed.54 Polystyrene nanospheres are deposited on a transparent substrate below full coverage, while the average distance between the charged nanospheres is
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
3. Dry
2. Drop coat
1. Clean substrate
Glass
6. AFM
4. Ag, q = 0°
5. Liftoff
125 nm Ag
Normalized extintion
(a) A
B
C
D
E
F
G
120
150
150
95
120
145
145
145 (a)
42
70
62
48
46
59
55
50
747
(shape) 782 (lmax)
426
400 (b)
446
497
500
565
638
600
720
700
H
800
(b)
900
Wavelength (nm)
Figure 4. (a) Schematic representation of the nanosphere lithography (NSL) fabrication process. Glass and mica were used as substrates. The AFM image in step 3 is 5 × 5 µm2 . (b) Size- and shape-tunable LSPR spectra of various Ag nanoparticles on mica (labeled A–H). The extinction oscillation is caused by light interference in the thin mica substrates.51 The wavelength of maximum extinction, λmax , changes by varying the in-plane width (a) and out-of-plane height (b) of the nanoparticles. [Reproduced by permission of the Materials Research Society from Haes et al.17 ]
controlled by the solution ionic strength. The nanospheres are immobilized on the surface by brief heating in boiling water, thus preventing
formation of aggregates during the drying step. This is followed by evaporation of an Au overlayer and removal of the nanospheres by tape, providing
LSPR SPECTROSCOPY IN BIOSENSING
7
Reflectance (absorption units)
1.5
4 4 Gold-capped nanoparticle layer substrate
1
200 (nm)
3
0.4 0.8 1.2
0 3 Nanoparticle layer substrate
0.5
2 Gold deposited glass substrate
0.4 0.8 1.2
2
1.6
1.6 2 (µm)
1 Glass substrate
1 0 400 (a)
450
500
550 600 650 700 Wavelength (nm)
750 800 (b)
Figure 5. (a) Reflectance spectra for the different steps in the preparation of a gold-capped silica nanoparticle layer on a gold substrate. (b) AFM image of the gold-capped nanoparticle layer. [Reprinted with permission from Endo et al.21 Copyright 2005, American Chemical Society.]
2.3
Stability of LSPR Nanostructures
A major concern in the realization of LSPR biosensing devices is stability of the metal nanostructures. A basic requirement in sensing applications is assuring that changes in the optical response of the nanostructured metal film originate exclusively from binding of a target analyte and not from other factors. This is a central issue in any nanoparticulate metal structure on solid substrate, i.e., both immobilized NPs and evaporated island films are susceptible to environmentally-induced shape and optical changes. The two major factors influencing nanostructured metal film structure are (i) change of the shape of metal islands or NPs upon interaction with solvents and (ii) shape modification and possible aggregation induced by drying. Both are difficult to overcome for bare islands or NPs, but the systems are frequently stabilized after application of a biorecognition interface on the nanostructured metal surface.56,57
0.6 e (Abs)
a surface with randomly distributed optical holes (Figure 6). These substrates exhibit a well-defined localized SP band similar to that of nanoparticulate metal films and have been used successfully for optical biosensing.
15 nm 20 nm 25 nm
1 µm
0.5 0.4 Au
0.3 500
600
700 l (nm)
15–25 nm 140 nm SiO2
Au
800
900
Figure 6. Extinction spectra of 140-nm-wide nanoholes with the same surface density (≈ 9 µm−2 ) and different depths. (Similar changes in the peak were also observed for holes with other diameters and surface densities when varying hole depth; data not shown.) Spectra were acquired with the nanostructures immersed in water. A representative SEM image (20-nm-deep holes) is shown in the inset. A few percent of pairwise aggregated holes were present on all samples due to colloid aggregation during drying. [Reprinted with permission from Dahlin et al.55 Copyright 2006, American Chemical Society.]
Evaporated metal islands undergo shape changes induced by interaction with solvents, which may strongly influence their spectrum following exposure to liquid environments.6,49,58 It was found that the mean height of islands measured by AFM increases after exposure to solvents,58 but no
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
detailed characterization of changes in island shape for relatively small (≤10 nm) metal islands can be found. Clear, solvent-induced island reshaping was observed by AFM imaging of large (ca. 100 nm) Ag triangles, showing disappearance of sharp tips at the corners of the metal NPs (Figure 7).49 The morphology-related shift of the LSPR band maximum in this case was on the order of 200 nm. A similar process of edge smoothing is likely to be operative in smaller islands. A possible approach to LSPR system stabilization is preconditioning of the metal island film by exposure to a solvent and drying, which may result in stabilization of the optical properties.6,13,16,49 Changes in the transmission spectrum accompanying analyte adsorption are then attributed exclusively to response of the LSPR system to the
dielectric environment. This procedure is quite effective in common organic solvents, but is less effective in phosphate buffer saline (PBS) solutions—the usual medium for biosensing—i.e., the optical properties of metal island films do not stabilize after several equilibration cycles. Recently a more general approach to stabilization of the optical response of Au island films was presented, based on encapsulation of the metal islands in an ultrathin (ca. 1.5 nm) silica shell.59,60 UV–vis spectra of silica-coated Au island films measured before and after immersion in organic and aqueous solvents, including PBS, do not show any change in the SP band within the accuracy of the measurement (Figure 8). This result establishes
4
0.30
2
Extinction
0.25 1 0.20 3 0.15 0.10 (a) 0.30
(a)
1–4
Extinction
0.25
0.20
0.15
0.10
400 (b)
500 600 700 Wavelength (nm)
800
(b) Figure 7. Tapping-mode AFM images (1 × 1 µm2 ) of Ag nanoparticle arrays on glass substrates, prepared by NSL. (a) Nanoparticles not exposed to any solvent after nanosphere mask removal (average particle height, 47.3±1 nm); (b) similar nanoparticles after incubation in H2 O for 24 h (average particle height, 51.3 ± 2 nm). [Reprinted with permission from Malinsky et al.49 Copyright 2001, American Chemical Society.]
Figure 8. Transmission spectra (measured in air) of (a) bare Au island films (5 nm, evaporated on silanized glass and annealed) and (b) coated with a ca. 1.5-nm silica layer, before and after 20-min immersion in various solvents followed by washing in water and drying: (1) before immersion, (2) after EtOH or MeOH, (3) after water, (4) after PBS. [Reprinted with permission from Ruach-Nir et al.60 Copyright 2007, American Chemical Society.]
LSPR SPECTROSCOPY IN BIOSENSING
the feasibility of silica-coated Au island films as transducers for biological sensing, ensuring that changes in the recorded spectra reflect solely binding/release of target analytes. Encapsulation of Ag island films using a silica layer prepared by the sonogel method did not lead to complete stabilization of the system toward interaction with solvents.36 Recently dense and uniform alumina coatings were prepared by CVD on Ag island films,61 but their use as a stabilizing shell was not reported. The long-term stability of LSPR transducers remains largely unexplored. Our experience, as well as literature data,62 have shown the applicability of evaporated Au island films after months and even years of storage in laboratory ambient. Evaporated Ag island films are less stable and the reported storage results vary substantially: both stability of the optical properties17 and rapid tarnishing of Ag NP films in ambient air with 1.8 nm h−1 shift of the SP band63 have been reported. This may introduce difficulties in obtaining stable Ag LSPR transducers for longterm applications.
3 LSPR TRANSDUCERS 3.1
General Properties and Sensitivity of LSPR Transducers
Development of optical transducers based on LSPR spectroscopy involves several general issues, such as sensitivity to analyte binding and choice of the measured parameters. In LSPR sensing analyte molecules accumulate on the transducer surface, changing the dielectric properties (i.e., the effective refractive index) of the surrounding medium and, as a result, the conditions for excitation of SPs (the simplest case is given by the Mie relationship, equation (1)). However, calculation of the intensity of the evanescent wave for metal island systems, taking into account the island size and shape, size distribution, influence of the solid support, and interactions between islands, makes quantitative prediction almost impossible. Adjustable parameters are commonly used in model calculations and only a partial set of parameters (most frequently the wavelength of maximum SP absorbance) is used
9
for comparison between model calculations and experimental data,7,17,64 while other parameters, such as band intensity and peak shape, are usually not considered. In the case of propagating SPR, a semiempirical approach to quantitative analysis of the sensitivity was presented and validated.65 It is based on experimental determination of the optical response of the SPR interface to change of the dielectric constant of an infinite, homogeneous surrounding medium, and use of these data for prediction of the response to accumulation of an adsorbate layer of a finite thickness. Over a narrow range of refractive index change, the SPR response R can be approximated as a linear function of the change in bulk refractive index: R = m(η) = m(ηfinal − ηinitial )
(2)
where m is the bulk refractive index sensitivity (see below) and η is the refractive index of the surrounding medium. The bulk refractive index sensitivity m serves as an upper limit to the sensitivity of nanostructures supporting SP excitation to local refractive index changes,66 such as those associated with biomolecule sensing. In the case of an adsorbed layer with a finite thickness d the sensor response also depends on a characteristic length ld of the exponential decay of the evanescent field: 2d (3) R = m(ηa − ηs ) 1 − exp − ld where ηa and ηs are the refractive indexes of the adsorbate and the bulk solution, respectively. Equation (3), developed for propagating SPR, was successfully applied to the response of LSPR systems.52,67 The experimental value of ld is typically approximately an order-of-magnitude smaller for LSPR compared to propagating SPR.52 The experimental value of m in LSPR is influenced by geometric factors and physical parameters of the real system. The value of m for a particular transducer can be determined by measuring the change in the optical response upon systematic variation of the refractive index of the bulk contacting medium (see below). Determination of the decay length ld can be done using model systems with well-defined and variable overlayer thickness
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
0.3 PIC 0.2 0.1
Scaled ×2
Wavelength of maximum extinction (nm)
Extinction
0.4
Maximum extinction and PIC
568
0.5
566 564 562 560
0.0 500 (a)
600 700 Wavelength (nm)
1.35 (b)
1.40
Refractive index
0.52 0.50 0.48 0.46 0.44 0.42
1.45 (c)
Offset 0.4
1.35
1.40
1.45
Refractive index
Figure 9. Refractive index sensitivity measurement for a 7.5-nm (nominal thickness) Au island film evaporated on bare glass, annealed 30 min at 500 ◦ C. (a) Transmission spectra measured in CH3 OH–CHCl3 mixture, from pure CH3 OH (lower spectrum) to pure CHCl3 (upper spectrum). Difference spectra (lower group of spectra, scaled) were calculated by subtracting the spectrum in pure CH3 OH from the other spectra. The plasmon intensity change (PIC), determined at a constant wavelength, is indicated by the dashed vertical line. Inset: HRSEM image of the island film (1.0 × 1.0 µm2 ). (b) Dependence of the wavelength of maximum SP extinction on the solvent refractive index. Data obtained upon increase and decrease of the refractive index (upward and downward pointing triangles, respectively), the latter determined using an Abbe refractometer. (c) Dependence of the maximum SP extinction (upper line) and the PIC (lower line) on the refractive index; experimental condition as in (b). [Adapted from Karakouz et al.43 ]
(see below). Once the values of m and ld have been determined, solving equation (3) for d allows determination of the optical response to analyte binding in terms of effective thickness of an adsorbate layer. Such quantification may allow determination of analyte surface coverage directly from the response of an LSPR sensor. An example of the response of a transmission localized surface plasmon resonance (TLSPR) transducer to variation of the bulk refractive index is shown in Figure 9. To eliminate possible influence of island shape change on the signal, the Au island film was exposed to the series of solvent media until stabilization of the response was achieved (usually one solvent cycle), evidenced by remeasuring in the first solvent. The increase of the refractive index causes a red shift and an increase of the maximum SP absorption (Figure 9a). Figure 9(b,c) presents experimental data of several solvent cycles, showing overlap within experimental error, indicating stabilization of the island morphology. The shift of the wavelength of the SP band maximum and the change in the extinction have both been used previously in the quantification of LSPR response. Deviation from linearity for measurements performed in air was reported and
treated by applying a polynomial approximation.65 In the present case, the linear dependence of the two parameters on the refractive index of the bulk medium (Figure 9b,c) shows that the linear approximation (equation 2) holds well for Au island film transducers in solution. As seen in Figure 9(a), the maximum of the SP band shifts between 560 and 570 nm, while the difference spectra pass through a maximum at ca. 590 nm. Hence, the maximal change in the SP intensity occurs at a wavelength close to the inflection point in the red wing of the SP band, as observed by several groups.12,15,16,68 The maximum of the differential extinction (Figure 9a, lower group of spectra), denoted Plasmon Intensity Change (PIC) by us, is located at nearly the same wavelength in the studied range of refractive indexes (see dashed vertical line in Figure 9a).15,16 Hence, measurements in the vicinity of the differential extinction maximum provide optimal sensitivity when the extinction intensity is chosen for quantification of analyte binding16 (see the difference in the slopes in Figure 9c). Measurement of extinction change at a single wavelength (or in a narrow wavelength range using a white-light source and a band-pass filter) in the vicinity of the PIC requires an exceedingly
LSPR SPECTROSCOPY IN BIOSENSING
11
Table 1. Bulk refractive index sensitivity of nanostructures supporting LSPR
Sensitivity Configuration of LSPR transducer
Nanostructure characteristic Shift of SP Extinction change dimension (nm) wavelength (nm/RIU) (abs units/RIU) Au nanostructures
70
NPs in solution NPs in solution71 NPs immobilized on silanized glass12,72 NPs immobilized on polyelectrolyte layer30 NPs immobilized on silanized glass73 NPs immobilized on silanized glass74 Nanoshells immobilized on silanized glass74 NPs immobilized on unclad silanized optical fiber75 Island films evaporated on glass and annealed at 450 ◦ C 34 Island films evaporated on unclad silica optical fiber and annealed at 600 ◦ C76 Island films evaporated on unclad silica optical fiber three times and annealed at 600 ◦ C after each step77 Island films evaporated on silanized glass and annealed at 200 ◦ C6,43 Island films evaporated on bare glass and annealed at 500–550 ◦ C43 Island films evaporated on silanized glass, annealed at 200 ◦ C and covered with a 1.5-nm silica layer43,60 Random holes in a continuous metal layer18,67
Sandwich structure: metal film evaporated on polystyrene NSL mask on evaporated metal film20,47
D 16 D 5.2 D 13 D 39 D7 D 20 D 30 D 50 D 50 wall thickness 4.5 D 8.4 NT 15
85 50 75 70 70 75 70 60 410 160 –
– – PIC 0.46 PIC 1.2 0.09 0.12 –
NT 4
90
–
NT 4 per step
290
–
NT 2.5 NT 5.0 NT 7.5 NT 5.0 NT 10.0 NT 2.5 NT 5.0
70 80 120 100 140–160 50 60
PIC 0.2 PIC 0.6 PIC 0.5 PIC 0.8 PIC 0.8 PIC 0.16 PIC 0.25
Layer thickness 20; Multiple holes D 110 Single holes D 60 Layers thickness 20 Polystyrene NPs D 110
180 90 60
PIC ≈ 1 – –
150 190
– –
– 4.2 PIC ≈ 1
Ag nanostructures NPs immobilized on silanized glass28 Island films prepared by NSL49
D 90 Triangles, D ≈ 100 Height 50 Separation ca. 150
D: characteristic lateral dimension; NT: nominal thickness; PIC: plasmon intensity change; RIU: refractive index unit.
simple and inexpensive experimental setup. The applicability of extinction measurements to highthroughput biosensing using standard equipment was demonstrated recently.69 In comparison, determination of the wavelength shift of the SP band maximum requires more elaborate analysis and specialized software. Fast accumulation of spectra with digital processing, considering changes in both peak position and intensity, can
substantially improve the signal-to-noise ratio of LSPR transducers.55 The bulk refractive index sensitivity, commonly expressed as change in the LSPR parameter per refractive index unit (RIU), can serve as a valid criterion for comparing the sensing capability of different LSPR platforms. Table 1 summarizes data for various LSPR systems, both in solution and on solid substrates. As seen in Table 1, the
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 590
0.2
0.4
0.16 0.12 0.08
(b)
0.2 0.1
PIC
0.1 0.08
0.3
2.5 nm
0.06 0.04 0.02 0 400 500 600 700 800 900 Wavelength (nm)
(c)
(d)
0.25 0.2
5.0 nm 580 570
2.5 nm
560 550
PIC
(e) 0.25
0.15
0.15
0.1
0.1
0.05
0.05
0 400 500 600 700 800 900 Wavelength (nm)
5.0 nm
0.2
5.0 nm PIC
0.04 0.12
Extinction difference
Extinction difference
(a)
5.0 nm
Wavelength (nm)
2.5 nm Extinction
Extinction
0.24
2.5 nm
0 0 (f)
2 4 6 8 10 12 Number of layers
Figure 10. Transmission UV–vis spectra of Au island films (annealed at 200 ◦ C; nominal thickness indicated) recorded during LbL preparation of coordination-based multilayer films. The thickness of the layer deposited on the Au islands increases by ca. 1.4 nm/layer. All spectra were taken in air. Transmission spectra (a,c) and corresponding difference spectra (b,d) are shown. (e,f) Wavelength of maximum extinction and the PIC obtained during film preparation. [Reprinted with permission from Doron-Mor et al.16 Copyright 2005, Wiley VCH.]
bulk sensitivity of nanostructures depends primarily on geometric parameters. In general, the SP wavelength shift and maximum intensity show a similar trend. Au nanostructures are less sensitive to refractive index change than Ag; however, the difference is by a factor of 2, much less than in SERS. It is evident from Table 1 that nanostructures comprising evaporated metal island films and NPs on unpatterned, flat substrates have roughly similar refractive index sensitivity reaching ca. 100 nm/RIU for wavelength shift and ca. 1 au/RIU for PIC. In general, larger nanostructures show higher sensitivity, with a maximum reported sensitivity of 160 nm/RIU for 10-nm Au films evaporated on glass and annealed, and 150 nm/RIU for 90-nm Ag NPs immobilized on glass. Application of multiple-reflection schemes based on modified unclad surfaces of optical fibers increases the sensitivity of this type of structures to 290 nm/RIU for a relatively thick (15 nm) film. Substrates patterned using an NSL mask show a sensitivity of up to ca. 200 nm/RIU. Nanoholes in continuous Au films show sensitivities similar to those of Au island films, while nanohole structures
in Ag films may show a higher sensitivity. The highest wavelength sensitivity (ca. 400 nm/RIU) has been reported for Au nanoshells immobilized on glass, where both the interior and exterior space of the nanoshell was filled with solvent. The distance sensitivity of LSPR systems is particularly crucial in biosensing. It is expressed as the characteristic decay length ld (equation 3). The distance dependence of the response of LSPR structures was determined experimentally using overlayers with a variable thickness controlled on the nanometer scale, including self-assembled monolayers (SAMs) of alkanethiols,49,67 metal– organic coordination-based multilayers,16,78 polyelectrolyte multilayers,30,79 sol-gel60 and chemical vapor deposition (CVD) deposited61 oxides. Figure 10 shows the optical response of an LSPR transducer to layer-by-layer (LbL) construction of a self-assembled multilayer on Au island films using metal–organic coordination.16 Evolution of the transmission spectra during incremental increase in the thickness of a thin uniform layer on Au islands (Figure 10a,c) is qualitatively similar to that observed for change of the bulk refractive index (Figure 9). The differential
LSPR SPECTROSCOPY IN BIOSENSING
extinction spectra (Figure 10b,d) show a maximum sensitivity at nearly constant wavelengths red shifted with respect to the maximum of the SP band, as also seen in Figure 9. The decrease in sensitivity due to distance dependence of the evanescent field for the 2.5-nm film is evident as saturation after 7–8 layers, corresponding to an overlayer thickness of ca. 11 nm. The decrease in sensitivity for the 5.0-nm films is much less pronounced, extending the response to > 15 nm, with a near-linear region resembling the response to SAMs with variable thickness.49 Since biorecognition interfaces usually comprise several layers, generally including biomolecules,60 thicker metal films with better-defined islands—providing higher distance sensitivity—should be preferred as platforms for LSPR biosensors. The possibility of spatial distribution of different analyte binding sites on the LSPR transducer should be considered. This is related to inhomogeneity of the LSPR transducer surface on the nanometer scale and the existence of regions with different local refractive index sensitivity.80 Different optical sensitivity for binding to the metal nanostructures and to the exposed hole bottom was demonstrated for nanohole arrays.18,67 Hence, in the application of equations (2) and (3) to the analysis of the response of heterogeneous LSPR substrates, the bulk refractive index sensitivity m represents a local value or a weighted average, depending on the particular spatial distribution of bound analyte. A basic question in LSPR spectroscopy concerns the quantitative relationship between surface coverage by the analyte (in the submonolayer regime) and the LSPR response. We addressed this issue by studying the sensitivity of the SP band to change in the fractional coverage of a self-assembled chromophoric monolayer on an Au island film up to a full monolayer coverage.14,15 Au island films similar to the one presented in Figure 2(c,d) were used as LSPR transducers, and the disulfide chromophoric molecule 1 (Figure 11b)15 or Co-tetraphenylporphyrin (CoTPP)14 (not shown) served as a target analyte. The spectral separation between the molecular absorption band and the Au SP band allowed independent determination of the fractional surface coverage and the SP change during formation of a SAM. The results in Figure 11(a,b) show a clear correlation between the two absorption
13
bands, increasing simultaneously during formation of a SAM of 1. As in the previous examples, the maximum change in SP extinction (the PIC) is red-shifted with respect to the maximum SP absorbance. The kinetics of the shift of both the wavelength of the SP band and the PIC are similar (Figure 11c), showing saturation upon completion of monolayer adsorption. The PIC and the chromophore absorption, the latter directly proportional to the fractional coverage by the SAM, are linearly correlated over the entire range of surface coverage (Figure 11d). The same linearity applies to the shift of the wavelength of the SP band (not shown). In biological sensing, the target analyte usually does not bind directly to the surface of the LSPR transducer (as in the previous example), but rather binds to specific receptors preassembled on the surface. Binding of an analyte to a receptor layer on an LSPR transducer was modeled by binding of Co-TPP to an imidazole-functionalized SAM on an Au island film.14,42 As in the corresponding case of formation of a SAM of 1 (Figure 11), a linear correlation was observed between the fractional surface coverage by the analyte, bound at a finite distance form the island surface via the imidazole receptor, and the optical response (PIC or shift of the wavelength of the SP band), up to a monolayer coverage. Similar detection of analyte binding at a distance from a metal island surface was reported for protoporphyrin IX binding to a silica coating on an Au island film.60 These examples provide experimental basis for application of LSPR transducers in quantitative analysis of analyte binding. The linear dependence of the optical signal on surface coverage by the analyte allows quantification of kinetic data and calculation of binding constants, either to the metal or to a receptor layer, using experimental schemes similar to those applied in the well-developed propagating SPR technique.
3.2
LSPR Biosensing: Case Studies
Biosensing applications have been realized for almost all the configurations of LSPR transducers described above. Such applications require preparation of a biorecognition interface exposing specific receptors to target analytes. In general, immobilization of receptors follows established
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 0.06 49 min
0.18
49 min
225 s
0.05
Absorbance
Absorbance difference
45 s
0.16
15 s 0s
0.14
0.12
1 225 s
0.04 O
O
O
O
0.03
45 s S−S
0.02 15 s
0.01 0.1 400 500 600 Wavelength (nm)
300 (a)
Absorbance at 365 nm
Normalized signal
0.8 0.6 0.4 0.2 0 0
10
20
30
40
300
(b)
1
(c)
0
700
Adsorption time (min)
(d)
700
0.016 0.012 0.008 0.004 0
50
400 500 600 Wavelength (nm)
0
0.02
0.04
0.06
Plasmon intensity change
Figure 11. Transmission UV–vis spectroscopy for the formation of a monolayer of 1 (inset in b) on an Au island substrate (2.5 nm nominal thickness, evaporated on quartz, unannealed), adsorbed from 2 mM solution of 1 in chloroform. (a) Absolute spectra. (b) Difference spectra (obtained by subtraction of the 0-s spectrum from the other spectra in a); dashed line corresponds to the spectrum of a thick layer of 1, obtained by evaporation of a drop on quartz (original spectrum divided by 6). (c) Normalized quantities of the plasmon absorbance versus adsorption time: squares—shift of the wavelength of maximum absorbance (from a); circles—intensity of the maximum difference peak (plasmon intensity change, PIC) (from b). (d) Correlation between the PIC and the maximum absorbance of 1 at 365 nm (both from b). All UV–vis spectra were taken ex situ, after rinsing the sample with chloroform and ethanol and drying under a nitrogen stream. [Reprinted with permission from Kalyuzhny et al.15 Copyright 2001 American Chemical Society.]
schemes developed for the preparation of biorecognition interfaces (see e.g., a recent review81 ). Biotin–avidin interactions have been exploited extensively both for immobilization of specific receptors and as a model system for protein recognition. A popular scheme includes preparation of a carboxylate- or amine-terminated SAM on the surface of metal NPs or islands, followed by covalent coupling of biotin through an amide bond.13,35,72 An example of this type of experimental scheme is shown in Figure 12, where both the peak intensity and wavelength are sensitive to binding of avidin (see also data in Table 2). Immobilization of biological receptors on oxide surfaces can be carried out by converting an
amine-terminated siloxane SAM to a carboxylateterminated surface followed by coupling of a biomolecular receptor through an amide bond. This scheme and corresponding transmission spectra are shown in Figure 13 for the preparation of an immunoglobulin (IgG) protein recognition interface57 on silica-stabilized Au islands on glass.60 Specific recognition was demonstrated in experiments where bound mouse-IgG and rabbitIgG antigens were exposed to the corresponding specific and nonspecific IgG antibodies, showing highly specific protein recognition (Figure 14). In LSPR systems analyte binding can be detected by measurements in solution (in situ) as shown in Figure 12(b), or in air or nitrogen
LSPR SPECTROSCOPY IN BIOSENSING
15
Fabrication protocol 3
2
1
Glass
Silane SAM
AuCM – MPA
AuCM
Biotin - functionalized AuCM – MPA O
O
(1) (CH3CH2O)3Si
NH2 (2) HS
OH
(3) H2N
O
O
O
HN NH H H S
H N
(a)
O
Detection protocol Absorbance
0.20
Light
After protein binding Befor protein binding
0.15 0.10 0.05 0.00
Biomolecular binding event on sensor chip detected by absorbance change
(b)
300 400 500 600 700 800 900 Wavelength (nm)
Figure 12. (a) Schematic presentation of the steps involved in the fabrication of an immobilized colloidal Au sensor chip on glass. The glass substrate was functionalized with 3-aminopropyl trimethoxysilane (1) to provide an amine-terminated surface for binding of a monolayer of citrate-stabilized Au NPs (AuCM ). A SAM of mercaptopropionic acid (MPA) (2) on the Au NPs provides reactive carboxylic groups that can be further modified by biotin (3) to study specific binding of streptavidin. (b) Protein binding to the biotinylated transducer results in increase and red shift of the SP band. [Reprinted with permission from Nath and Chilkoti.72 Copyright 2002, American Chemical Society.] Au Glass
0.45
Binding of Anti-rabbit IgG
0.40
Immobilization of Rabbit IgG
0.35 OMe Si OMe
SH OH HO OH HO OH HO OH Si OH Si O Si OH Si OH
S
S
S
0.30 Extinction
MeO
MPTS
Anti-rabbit IgG
Functionalization of interface
0.25 0.20 0.15
S
0.10 0.05
Na2SiO3
Rabbit IgG 400
S
S
S
700
800
900 1000 O C
HO OH HO OH HO OH HO OH Si OH Si OH Si OH Si OH S
600
Wavelength (nm)
~ ~1.5-nm silica HO OH Si OH
500
O OH OH O OHO OH O OH C C C C
Modification of silica surface
S
Figure 13. Schematic chart showing the preparation of a protein recognition interface using a T-LSPR transducer based on a silica-encapsulated, 5.0-nm Au island film evaporated on silanized glass and annealed, followed by specific protein recognition. Inset: actual transmission UV–vis measurements, carried out ex situ. Conditions of silica coating as in Ref. 60. [Adapted from Bendikov et al.57 ]
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Table 2. Selected biorecognition systems based on LSPR detection
Configuration of LSPR sensor
Preparation of recognition interface
Experimental details
Au NPs (40 nm) in solution68
Au NPs covered with monoclonal anti-hFABP. Detection of binding of hFABP
Incubation of Au NP bioconjugate with analyte
Au NPs immobilized on silanized glass, NPs enlarged by electroless deposition33 Au NPs (13–50 nm) immobilized on silanized glass12,72
Au NPs functionalized with HSA or anti-HSA. Detection of binding of anti-HSA or HSA, respectively Au NPs functionalized with MPA followed by chemical coupling of biotin. Detection of streptavidin and anti-biotin monoclonal antibodies Au NPs functionalized with disulfide polymer carrying receptor (glucose, pepstatin fragment, phenylboronic acid). Binding of ConA, HIV-1 protease, glycoprotein Au NPs functionalized with BSA or HSA
Difference in extinction after binding of analyte in stagnant solution
Au NPs (40 nm) immobilized on silanized glass82–84
Au NPs (40 nm) immobilized on silanized glass85
Detection of binding of anti-BSA (pig) or anti-HSA (goat, vector) Au NP (9 nm) film Au NPs functionalized with immobilized on fiber cystamine followed by coupling after removal of normal of biotin or immobilization of cladding86 anti-SEB Au NPs immobilized on Binding of streptavidin to unclad silanized silica immobilized biotin fiber75 Au NPs immobilized on Binding of streptavidin to the end face of a fiber87 immobilized biotin Continuous 20-nm-thick Biotin–NA Au film with 110-nm Ganglioside (GM1 ) holes18 glycolipid—CT hybridization of oligo-DNA (15 mer)
Evaporated Au island film, 2.5–5.0 nm13,57 Au NPs (40 nm) immobilized on glass88
Binding of streptavidin to immobilized biotin; specific recognition of IgG proteins Streptavidin binding to biotinylated BSA immobilized on Au NPs.
Au NPs (40 nm) immobilized on glass89
SZ-BSA immobilized on Au NPs followed by exposure to anti-SZ
Ag film evaporated through an NSL mask on mica35,50
Ag islands functionalized with mixed MUA-C8 SAM followed by coupling of biotin. Anti-biotin recognized by surface-bound biotin
Sensitivity Ca. 20 ng ml−1 hFABP. Determination of affinity constants in the range 109 –1011 mol−1 Minimum detected concentration 100 µg ml−1 of HSA
Kinetics of extinction change during analyte binding in a stirred solution
Detection limit of streptavidin ca. 20 nM for 13-nm NPs and 1 nM for 39-nm NPs
Kinetics of extinction change during analyte binding and release
Detection limit of ConA, 1.9 nM; HIV-1, protease, 50 nM; glycoprotein (OVA), 100 nM
Measurements of transmission spectra in solution
Detection limit ca. 30 nM for anti-HSA
Laser intensity attenuation, measured using lock-in technique
Detection limit (S/N ratio of 3) 1 nM for streptavidin and 1.4 pM for anti-SEB
Binding of analytes in a flow cell
Detection limit (S/N ratio of 3) of streptavidin 0.1 nM; raw data not shown Optical response measured at 20 µg ml−1 Kinetics of analyte binding followed at a constant wavelength with collection of spectra. Concentration of analytes: 0.3 µM NA; 0.5 µM CT; 0.2 µM DNA Minimum detected concentration 10 nM for antirabbit IgG binding 5.0 meV shift of SP band upon exposure to 2 µM streptavidin in solution
Binding of analyte in stagnant solution Binding of analyte in stagnant solution. Measurements performed in situ
Binding of analyte in stagnant solution. Measurements performed ex situ in air Light scattering from single epiluminescent Au NPs immersed in stagnant solution. Light scattering from epiluminescent Au NPs immersed in stagnant solution Binding of analyte in liquid-displacement cell. Measurements in N2 and in PBS solution. Spectra smoothed due to mica interference
Detection limit 20 nM for Sz
Detection limit 1 pM for streptavidin
LSPR SPECTROSCOPY IN BIOSENSING
17
Table 2. (continued)
Configuration of LSPR sensor
Preparation of recognition interface
Experimental details
Ag film evaporated Ag islands functionalize with through a NSL mask on mannose-terminated SAM. mica90 ConA served as analyte Ag triangle NPs (25 nm Ag islands functionalized with thick) evaporated mixed MUA-C8 SAM followed through an NSL mask by coupling with anti-ADDL. onto mica91 ADDL binding measured directly and in sandwich configuration after binding of second anti-ADDL antibody
Sensitivity
Kinetics of binding and release Specific binding of ConA in solution (9 µM) in the presence of interfering BSA (15 µM) Binding of analyte in stagnant Detection limit for ADDL solution for 30 min. Spectra binding 10 pM (directly) and measured in N2 after drying 100 fM (sandwich configuration)
MPA: mercaptopropionic acid; HSA: human serum albumin; OVA: ovalbumin; BSA: bovine serum albumin; SEB: staphylococcal enterotoxin B; NA: neutroavidin; CT: cholera toxin; IgG: immunoglobulin G; ADDL: amyloid-β-derived diffusible ligand.
(ex situ) after drying13,35,55 as shown in Figures 13 and 14. The change in refractive index upon analyte binding is substantially higher in ex situ measurements, as the reference signal before binding is taken in air (nair = 1) compared to aqueous solution (nsol ≈ 1.33). Ex situ measurements are also well suited to disposable kits. On the other hand, affinity measurements and quantitative analysis of analyte adsorption and desorption kinetics can only be carried out in situ.
LSPR sensing covers a wide range of systems, from simple chips capable of detecting a target analyte, to sophisticated instrumental schemes allowing observation of analyte binding to single nanostructures. A representative selection of LSPR biorecognition systems is summarized in Table 2. Analysis of the data in Table 2 shows that detection limits reported by different groups vary by 3 orders-of-magnitude for similar model systems. The highest reported sensitivity was obtained using
Rabbit–anti-rabbit 0.4
Anti-rab Rabbit Extinction
Extinction
0.4
Rabbit–anti-mouse
0.3 0.2 0.1
Anti-mouse Rabbit
0.3 0.2 0.1
400
600
800
1000
400
Wavelength (nm)
0.4
Anti-mouse Mouse
0.3
Extinction
Extinction
800
1000
Mouse–anti-rabbit
Mouse–anti-mouse 0.4
600
Wavelength (nm)
0.2
Anti-rab Mouse
0.3 0.2 0.1
0.1 400
600 800 Wavelength (nm)
1000
400
600 800 Wavelength (nm)
1000
Figure 14. Specific recognition of IgG antibodies using an array configuration of T-LSPR sensors with bound IgG antigens. Preparation of the biorecognition interfaces and experimental conditions as in Figure 13. [Adapted from Bendikov et al.57 ]
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
an LSPR transducer based on multiple attenuated total reflection from an unclad optical fiber.86 This result corroborates with the high refractive index sensitivity of this special type of LSPR transducer (see Table 1, Ref. 75). Results showing extremely high sensitivity with LSPR transducers should be treated with caution, as the valid test for the maximum sensitivity is the bulk refractive index sensitivity, which does not vary dramatically (see Table 1). Let us consider as an example the detection limit of 100 pg ml−1 , reported for specific recognition of immunoglobulin proteins in a reflection LSPR sensing scheme (Figure 5).92 The experimental protocol consisted of placing a 100-nl drop with analyte on a ca. 1-mm2 spot of LSPR transducer with the immobilized receptor for 30 min, followed by washing to remove nonspecifically adsorbed molecules and measurement of reflectance changes. If we assume that all the analyte molecules in the drop were adsorbed and there was no desorption during washing before the optical measurements, one calculates that 10−14 g protein was adsorbed on the transducer spot. Taking the density of the protein as 1.35 g cm−3 ,93 gives a mean thickness of the analyte film of ca. 10−5 nm. Calculation of the expected response using equation (3) and data from Table 1 for refractive index sensitivity shows that detection of such a minute amount is below the instrument resolution. Other reports of extraordinary LSPR biosensitivity may be questioned for similar reasons. Table 2 shows a variety of schemes for the preparation of biorecognition interfaces and for analyte binding that have been successfully adapted to various LSPR sensing platforms. To date only one system, i.e., bioconjugated Au NPs in solution,68,94,95 has been tested with sufficient statistics (hundreds of samples) using standard protocols and equipment applied in quantitative bioanalysis. High-throughput screening (144 samples/h) was applied to the study of affinity constants for a variety of monoclonal antigen–antibody pairs95 and the results were validated by comparison with common SPR measurements. Results obtained with other LSPR biosensor systems at the current stage of development should be considered as proof-of-concept demonstrations. Intriguing results were reported with sandwich structures comprising avidin-functionalized Au NPs conjugated to a biotin-functionalized lipid
bilayer formed on a planar quartz surface.96 Avidin receptors on the immobilized NPs allow further binding of biotinylated biomolecules. The kinetics of hybridization of single-stranded 15-mer DNA with the immobilized complementary strand were measured with close to 1:1 hybridization efficiency. Of particular interest is the use of biorecognition systems comprising a small number of or even single NPs as the optical transducer. Monitoring the SP of an individual NP can push to the lower Streptavidin (analyte)
Biotin (acceptor) Biotinylated BSA
AU
AU
(a) Scattering intensity (arb units)
18
(b)
1.00 0.95 0.90 2.22 2.24 2.26 2.28 2.30 2.32 2.34 Photon energy (eV) Objective lens
(c)
Figure 15. Schematic representation of a biosensor based on light scattering from single Au NPs. (a) Au NPs are functionalized with biotinylated BSA which subsequently binds streptavidin. (b) Mie-type calculations for the three situations shown in (a). (c) Left: true-color photograph of a sample comprising functionalized Au NPs, obtained using dark-field illumination. Right: experimental setup enabling dark-field microscopy of single Au NPs immersed in a liquid. [Reprinted with permission from Raschke et al.88 Copyright 2003 American Chemical Society.]
Plasmon shift (meV)
LSPR SPECTROSCOPY IN BIOSENSING
0 −2
C = 1 × 10−6 mol l−1 −4 −6
C = 2 × 10−6 mol l−1 −10
0
10 20 30 40 Incubation time (min)
50
60
Figure 16. LSPR single-NP experiments: shift of the SP band versus incubation time for different streptavidin concentrations and control experiments. Upon addition of streptavidin at time t = 0 the NP resonance starts to red shift (green triangles and orange circles), while addition of potassium phosphate buffer leaves the resonance position unchanged (red squares). The streptavidin concentration was 1 × 10−6 and 2 × 10−6 mol l−1 for triangles and circles, respectively. Addition of 1 × 10−6 mol l−1 streptavidin to an NP coated with nonbiotinylated proteins shows no evidence of unspecific binding (blue asterisks). [Reprinted with permission from Raschke et al.88 Copyright 2003 American Chemical Society.]
limit the number of detected analyte molecules. Several groups have explored LSPR sensing using individual metal NPs.88,97–99 An example of a biorecognition experiment using single NPs as LSPR transducers is shown in Figure 15.88 Au NPs (40 nm diameter) were functionalized with biotinylated bovine serum albumin (BSA) and the sample was exposed to a solution of streptavidin. The kinetics of binding were measurable using the spectral shift of the SP maximum, while no change was observed in control experiments (Figure 16). This demonstration indicates that, in principle, LSPR spectroscopy can be performed on the single-NP level.
4 CONCLUSIONS
The current status of LSPR biosensing based on noble metal nanostructures was examined. Several classes of optical transducers supporting LSPR in the visible spectral region were discussed as potential biosensors. The general sensing scheme includes immobilization of a
19
biorecognition interface (specific receptors) on the LSPR transducer and measurement of changes in the SP band (intensity or wavelength) accompanying specific analyte binding. The reported results indicate that quantitative comparison of the sensitivity of different LSPR systems requires further experimental verification. Reduction of LSPR biological transducers to practice needs additional engineering and optimization; however, the relatively low cost of most LSPR transducers and corresponding experimental setups, and the relative simplicity of the measurements, point to possible applications such as disposable chips. The possibility of measuring single nanostructures may enable significant miniaturization.
ACKNOWLEDGMENTS
The authors gratefully acknowledge financial support from the Israel Science Foundation, Grant No. 307/03, and EU Project No. 028331 (PROSURF). REFERENCES 1. J. Homola, Present and future of surface plasmon resonance biosensors. Analytical and Bioanalytical Chemistry, 2003, 377, 528–539. 2. M. Moskovits, Surface-enhanced Raman spectroscopy: a brief retrospective. Journal of Raman Spectroscopy, 2005, 36, 485–496. 3. E. Hutter and J. H. Fendler, Exploitation of localized surface plasmon resonance. Advanced Materials, 2004, 16, 1685–1706. 4. P. B. Johnson and R. W. Christy, Optical constants of the noble metals. Physical Review B, 1972, 6, 4370–4379. 5. K. C. Grabar, R. G. Freeman, M. B. Hommer, and M. J. Natan, Preparation and characterization of Au colloid monolayers. Analytical Chemistry, 1995, 67, 735–743. 6. I. Doron-Mor, Z. Barkay, N. Filip-Granit, A. Vaskevich, and I. Rubinstein, Ultrathin gold island films on silanized glass. Morphology and optical properties. Chemistry of Materials, 2004, 16, 3476–3483. 7. H. X. Xu and M. Kall, Modeling the optical response of nanoparticle-based surface plasmon resonance sensors. Sensors and Actuators B: Chemical, 2002, 87, 244–249. 8. N. G. Khlebtsov, V. A. Bogatyrev, B. N. Khlebtsov, L. A. Dykman, and P. Englebienne, A multilayer model for gold nanoparticle bioconjugates: application to study of gelatin and human IgG adsorption using extinction and light scattering spectra and the dynamic light scattering method. Colloid Journal, 2003, 65, 622–635. 9. N. G. Khlebtsov, V. A. Bogatyrev, L. A. Dykman, and A. G. Melnikov, Spectral extinction of colloidal gold
20
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS and its biospecific conjugates. Journal of Colloid and Interface Science, 1996, 180, 436–445. P. Englebienne, A. Van Hoonacker, and M. Verhas, Surface plasmon resonance: principles, methods and applications in biomedical sciences. Spectroscopy: An International Journal, 2003, 17, 255–273. D. Eck, C. A. Helm, N. J. Wagner, and K. A. Vaynberg, Plasmon resonance measurements of the adsorption and adsorption kinetics of a biopolymer onto gold nanocolloids. Langmuir, 2001, 17, 957–960. N. Nath and A. Chilkoti, Label-free biosensing by surface plasmon resonance of nanoparticles on glass: optimization of nanoparticle size. Analytical Chemistry, 2004, 76, 5370–5378. M. Lahav, A. Vaskevich, and I. Rubinstein, Biological sensing using transmission surface plasmon resonance spectroscopy. Langmuir, 2004, 20, 7365–7367. G. Kalyuzhny, A. Vaskevich, G. Ashkenasy, A. Shanzer, and I. Rubinstein, UV/vis spectroscopy of metalloporphyrin and metallophthalocyanine monolayers selfassembled on ultrathin gold films. The Journal of Physical Chemistry B, 2000, 104, 8238–8244. G. Kalyuzhny, M. A. Schneeweiss, A. Shanzer, A. Vaskevich, and I. Rubinstein, Differential plasmon spectroscopy as a tool for monitoring molecular binding to ultrathin gold films. Journal of the American Chemical Society, 2001, 123, 3177–3178. I. Doron-Mor, H. Cohen, Z. Barkay, A. Shanzer, A. Vaskevich, and I. Rubinstein, Sensitivity of transmission surface plasmon resonance (T-SPR) spectroscopy: self-assembled multilayers on evaporated gold island films. Chemistry: A European Journal, 2005, 11, 5555–5562. A. J. Haes, C. L. Haynes, A. D. McFarland, G. C. Schatz, R. P. Van Duyne, and S. L. Zou, Plasmonic materials for surface-enhanced sensing and spectroscopy. MRS Bulletin, 2005, 30, 368–375. A. Dahlin, M. Zach, T. Rindzevicius, M. Kall, D. S. Sutherland, and F. Hook, Localized surface plasmon resonance sensing of lipid-membrane-mediated biorecognition events. Journal of the American Chemical Society, 2005, 127, 5043–5048. G. Bauer, F. Pittner, and T. Schalkhammer, Metal nano-cluster biosensors. Mikrochimica Acta, 1999, 131, 107–114. M. Himmelhaus and H. Takei, Cap-shaped gold nanoparticles for an optical biosensor. Sensors and Actuators B: Chemical, 2000, 63, 24–30. T. Endo, K. Kerman, N. Nagatani, Y. Takamura, and E. Tamiya, Label-free detection of peptide nucleic acid-DNA hybridization using localized surface plasmon resonance based optical biosensor. Analytical Chemistry, 2005, 77, 6976–6984. E. Hutter and M. P. Pileni, Detection of DNA hybridization by gold nanoparticle enhanced transmission surface plasmon resonance spectroscopy. The Journal of Physical Chemistry B, 2003, 107, 6497–6499. T. Schalkhammer, C. Lobmaier, F. Pittner, A. Leitner, H. Brunner, and F. R. Aussenegg, The use of metalisland-coated pH-sensitive swelling polymers for biosensor applications. Sensors and Actuators B: Chemical, 1995, 24, 166–172.
24. N. L. Rosi and C. A. Mirkin, Nanostructures in biodiagnostics. Chemical Reviews, 2005, 105, 1547–1562. 25. M. C. Daniel and D. Astruc, Gold nanoparticles: assembly, supramolecular chemistry, quantum-size-related properties, and applications toward biology, catalysis, and nanotechnology. Chemical Reviews, 2004, 104, 293–346. 26. W. D. Geoghegan, Immunoassays at the microscopic level–solid-phase colloidal gold methods. Journal of Clinical Immunoassay, 1988, 11, 11–23. 27. V. A. Bogatyrev, L. A. Dykman, B. N. Khlebtsov, V. K. Plotnikov, and N. G. Khlebtsov, Optical properties of colloidal gold-oligothymidine conjugates and their variations on hybridization with polyadenylic acid. Colloid Journal, 2005, 67, 413–421. 28. G. Chumanov, K. Sokolov, B. W. Gregory, and T. M. Cotton, Colloidal metal-films as a substrate for surfaceenhanced spectroscopy. The Journal of Physical Chemistry, 1995, 99, 9466–9471. 29. A. Doron, E. Katz, and I. Willner, Organization of au colloids as monolayer films onto ito glass surfaces–application of the metal colloid films as base interfaces to construct redox-active monolayers. Langmuir, 1995, 11, 1313–1317. 30. J. Schmitt, P. Machtle, D. Eck, H. Mohwald, and C. A. Helm, Preparation and optical properties of colloidal gold monolayers. Langmuir, 1999, 15, 3256–3266. 31. P. Hanarp, D. S. Sutherland, J. Gold, and B. Kasemo, Control of nanoparticle film structure for colloidal lithography. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2003, 214, 23–36. 32. Y. D. Jin, X. F. Kang, Y. H. Song, B. L. Zhang, G. J. Cheng, and S. J. Dong, Controlled nucleation and growth of surface-confined gold nanoparticles on a (3-aminopropyl)trimethoxysilane-modified class slide: a strategy for SPR substrates. Analytical Chemistry, 2001, 73, 2843–2849. 33. F. Frederix, J. M. Friedt, K. H. Choi, W. Laureyn, A. Campitelli, D. Mondelaers, G. Maes, and G. Borghs, Biosensing based on light absorption of nanoscaled gold and silver particles. Analytical Chemistry, 2003, 75, 6894–6900. 34. M. Gluodenis, C. Manley, and C. A. Foss, In situ monitoring of the change in extinction of stabilized nanoscopic gold particles in contact with aqueous phenol solutions. Analytical Chemistry, 1999, 71, 4554–4558. 35. J. C. Riboh, A. J. Haes, A. D. McFarland, C. R. Yonzon, and R. P. Van Duyne, A nanoscale optical biosensor: real-time immunoassay in physiological buffer enabled by improved nanoparticle adhesion. The Journal of Physical Chemistry B, 2003, 107, 1772–1780. 36. N. Hashimoto, T. Hashimoto, T. Teranishi, H. Nasu, and K. Kamiya, Cycle performance of sol-gel optical sensor based on localized surface plasmon resonance of silver particles. Sensors and Actuators B: Chemical, 2006, 113, 382–388. 37. A. G. Brolo, R. Gordon, B. Leathem, and K. L. Kavanagh, Surface plasmon sensor based on the enhanced light transmission through arrays of nanoholes in gold films. Langmuir, 2004, 20, 4813–4815. 38. P. A. Mosier-Boss and S. H. Lieberman, Comparison of three methods to improve adherence of thin gold films to
LSPR SPECTROSCOPY IN BIOSENSING
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
glass substrates and their effect on the SERS response. Applied Spectroscopy, 1999, 53, 862–873. C. A. Goss, D. H. Charych, and M. Majda, Application of (3-Mercaptopropyl)trimethoxysilane as a molecular adhesive in the fabrication of vapor-deposited gold electrodes on glass substrates. Analytical Chemistry, 1991, 63, 85–88. M. Wanunu, A. Vaskevich, and I. Rubinstein, Widelyapplicable gold substrate for the study of ultrathin overlayers. Journal of the American Chemical Society, 2004, 126, 5569–5576. M. Wanunu, A. Vaskevich, A. Shanzer, and I. Rubinstein, Divergent growth of coordination dendrimers on surfaces. Journal of the American Chemical Society, 2006, 128, 8341–8349. G. Kalyuzhny, A. Vaskevich, M. A. Schneeweiss, and I. Rubinstein, Transmission surface-plasmon resonance (T-SPR) measurements for monitoring adsorption on ultrathin gold island films. Chemistry: A European Journal, 2002, 8, 3850–3857. T. Karakouz, A. Tesler, M. Idelson, R. PopovitzBiro, A. Vaskevich, and I. Rubinstein, Refractive index sensitivity of the localized plasmon absorbance in gold island films. In preparation. V. L. Schlegel and T. M. Cotton, Silver-island films as substrates for enhanced Raman-scattering–effect of deposition rate on intensity. Analytical Chemistry, 1991, 63, 241–247. S. Norrman, T. Andersson, C. G. Granqvist, and O. Hunderi, Optical-properties of discontinuous gold-films. Physical Review B, 1978, 18, 674–695. J. C. Hulteen and R. P. Van Duyne, Nanosphere lithography–a materials general fabrication process for periodic particle array surfaces. Journal of Vacuum Science and Technology A: Vacuum, Surfaces, and Films, 1995, 13, 1553–1558. H. Takei, Surface-adsorbed polystyrene spheres as a template for nanosized metal particle formation: optical properties of nanosized Au particle. Journal of Vacuum Science and Technology B, 1999, 17, 1906–1911. F. A. Denis, P. Hanarp, D. S. Sutherland, and Y. F. Dufrene, Nanoscale chemical patterns fabricated by using colloidal lithography and self-assembled monolayers. Langmuir, 2004, 20, 9335–9339. M. D. Malinsky, K. L. Kelly, G. C. Schatz, and R. P. Van Duyne, Chain length dependence and sensing capabilities of the localized surface plasmon resonance of silver nanoparticles chemically modified with alkanethiol selfassembled monolayers. Journal of the American Chemical Society, 2001, 123, 1471–1482. A. J. Haes and R. P. Van Duyne, A nanoscale optical biosensor: sensitivity and selectivity of an approach based on the localized surface plasmon resonance spectroscopy of triangular silver nanoparticles. Journal of the American Chemical Society, 2002, 124, 10596–10604. T. R. Jensen, M. D. Malinsky, C. L. Haynes, and R. P. Van Duyne, Nanosphere lithography: tunable localized surface plasmon resonance spectra of silver nanoparticles. The Journal of Physical Chemistry B, 2000, 104, 10549–10556. A. J. Haes and R. P. Van Duyne, A unified view of propagating and localized surface plasmon resonance
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
21
biosensors. Analytical and Bioanalytical Chemistry, 2004, 379, 920–930. F. R. Aussenegg, H. Brunner, A. Leitner, C. Lobmaier, T. Schalkhammer, and F. Pittner, The metal island coated swelling polymer over mirror system (MICSPOMS)–a new principle for measuring ionic-strength. Sensors and Actuators B: Chemical, 1995, 29, 204–209. J. Prikulis, P. Hanarp, L. Olofsson, D. Sutherland, and M. Kall, Optical spectroscopy of nanometric holes in thin gold films. Nano Letters, 2004, 4, 1003–1007. A. B. Dahlin, J. O. Tegenfeldt, and F. Hook, Improving the instrumental resolution of sensors based on localized surface plasmon resonance. Analytical Chemistry, 2006, 78, 4416–4423. V. P. Drachev, V. C. Nashine, M. D. Thoreson, D. BenAmotz, V. J. Davisson, and V. M. Shalaev, Adaptive silver films for detection of antibody-antigen binding. Langmuir, 2005, 21, 8368–8373. T. A. Bendikov, A. Rabinkov, T. Karakouz, A. Vaskevich, and I. Rubinstein, Specific Recognition of IgG Proteins Using Transmission Localized Surface Plasmon Resonance (T-LSPR) Spectroscopy. In preparation. S. E. Roark and K. L. Rowlen, Thin Ag films—influence of substrate and postdeposition treatment on morphology and optical-properties. Analytical Chemistry, 1994, 66, 261–270. L. M. Liz-Marzan, M. Giersig, and P. Mulvaney, Synthesis of nanosized gold-silica core-shell particles. Langmuir, 1996, 12, 4329–4335. I. Ruach-Nir, T. A. Bendikov, I. Doron-Mor, Z. Barkay, A. Vaskevich, and I. Rubinstein, Silica-stabilized gold island films for transmission localized surface plasmon sensing. Journal of the American Chemical Society, 2007, 129, 84–92. A. V. Whitney, J. W. Elam, S. Zou, A. V. Zinovev, P. C. Stair, G. C. Schatz, and R. P. Van Duyne, Localized surface plasmon resonance nanosensor: a high-resolution distance-dependence study using atomic layer deposition. The Journal of Physical Chemistry B, 2005, 109, 20522–20528. G. D. Sockalingum, A. Beljebbar, H. Morjani, J. F. Angiboust, and M. Manfait, Characterization of island films as surface-enhanced Raman spectroscopy substrates for detecting low antitumor drug concentrations at single cell level. Biospectroscopy, 1998, 4, S71–S78. M. McMahon, R. Lopez, H. M. Meyer, L. C. Feldman, and R. F. Haglund, Rapid tarnishing of silver nanoparticles in ambient laboratory air. Applied Physics B: Lasers and Optics, 2005, 80, 915–921. T. Okamoto and I. Yamaguchi, Field enhancement by a metallic sphere on dielectric substrates. Optical Review, 1999, 6, 211–214. L. S. Jung, C. T. Campbell, T. M. Chinowsky, M. N. Mar, and S. S. Yee, Quantitative interpretation of the response of surface plasmon resonance sensors to adsorbed films. Langmuir, 1998, 14, 5636–5648. M. M. Miller and A. A. Lazarides, Sensitivity of metal nanoparticle surface plasmon resonance to the dielectric environment. The Journal of Physical Chemistry B, 2005, 109, 21556–21565. T. Rindzevicius, Y. Alaverdyan, A. Dahlin, F. Hook, D. S. Sutherland, and M. Kall, Plasmonic sensing characteristics
22
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS of single nanometric holes. Nano Letters, 2005, 5, 2335–2339. P. Englebienne, Use of colloidal gold surface plasmon resonance peak shift to infer affinity constants from the interactions between protein antigens and antibodies specific for single or multiple epitopes. The Analyst, 1998, 123, 1599–1603. P. Englebienne, A. Van Hoonacker, M. Verhas, and N. G. Khlebtsov, Advances in high-throughput screening: biomolecular interaction monitoring in real-time with colloidal metal nanoparticles. Combinatorial Chemistry and High Throughput Screening, 2003, 6, 777–787. S. Underwood and P. Mulvaney, Effect of the solution refractive-index on the color of gold colloids. Langmuir, 1994, 10, 3427–3430. A. C. Templeton, J. J. Pietron, R. W. Murray, and P. Mulvaney, Solvent refractive index and core charge influences on the surface plasmon absorbance of alkanethiolate monolayer-protected gold clusters. The Journal of Physical Chemistry B, 2000, 104, 564–570. N. Nath and A. Chilkoti, A colorimetric gold nanoparticle sensor to interrogate biomolecular interactions in real time on a surface. Analytical Chemistry, 2002, 74, 504–509. T. Okamoto, I. Yamaguchi, and T. Kobayashi, Local plasmon sensor with gold colloid monolayers deposited upon glass substrates. Optics Letters, 2000, 25, 372–374. Y. G. Sun and Y. N. Xia, Increased sensitivity of surface plasmon resonance of gold nanoshells compared to that of gold solid colloids in response to environmental changes. Analytical Chemistry, 2002, 74, 5297–5305. S. F. Cheng and L. K. Chau, Colloidal gold-modified optical fiber for chemical and biochemical sensing. Analytical Chemistry, 2003, 75, 16–21. F. Meriaudeau, T. Downey, A. Wig, A. Passian, M. Buncick, and T. L. Ferrell, Fiber optic sensor based on gold island plasmon resonance. Sensors and Actuators B: Chemical, 1999, 54, 106–117. F. Meriaudeau, A. Wig, A. Passian, J. P. Lauret, and T. L. Ferrell, Multiple gold island layers on a fiber core: a promising sensing device. Optical Engineering, 2001, 40, 658–660. A. J. Haes, S. L. Zou, G. C. Schatz, and R. P. Van Duyne, A nanoscale optical biosensor: the long range distance dependence of the localized surface plasmon resonance of noble metal nanoparticles. The Journal of Physical Chemistry B, 2004, 108, 109–116. N. Nath and A. Chilkoti, Label free colorimetric biosensing using nanoparticles. Journal of Fluorescence, 2004, 14, 377–389. A. J. Haes, S. L. Zou, G. C. Schatz, and R. P. Van Duyne, Nanoscale optical biosensor: short range distance dependence of the localized surface plasmon resonance of noble metal nanoparticles. The Journal of Physical Chemistry B, 2004, 108, 6961–6968. D. Chen, G. Wang, and J. Li, Interfacial bioelectrochemistry: fabrication, properties and applications of functional nanostructured biointerfaces. The Journal of Physical Chemistry C, 2007, 111, 2351–2367. S. Morokoshi, K. Ohhori, K. Mizukami, and H. Kitano, Sensing capabilities of colloidal gold modified with a selfassembled monolayer of a glucose-carrying polymer chain on a glass substrate. Langmuir, 2004, 20, 8897–8902.
83. H. Kitano, Y. Makino, H. Kawasaki, and Y. Sumi, Selfassembled monolayer of a pepstatin fragment as a sensing element for aspartyl proteases. Analytical Chemistry, 2005, 77, 1588–1595. 84. H. Kitano, Y. Anraku, and H. Shinohara, Sensing capabilities of colloidal gold monolayer modified with a phenylboronic acid-carrying polymer brush. Biomacromolecules, 2006, 7, 1065–1071. 85. K. Fujiwara, H. Watarai, H. Itoh, E. Nakahama, and N. Ogawa, Measurement of antibody binding to protein immobilized on gold nanoparticles by localized surface plasmon spectroscopy. Analytical and Bioanalytical Chemistry, 2006, 386, 639–644. 86. L. K. Chau, Y. F. Lin, S. F. Cheng, and T. J. Lin, Fiberoptic chemical and biochemical probes based on localized surface plasmon resonance. Sensors and Actuators B: Chemical, 2006, 113, 100–105. 87. K. Mitsui, Y. Handa, and K. Kajikawa, Optical fiber affinity biosensor based on localized surface plasmon resonance. Applied Physics Letters, 2004, 85, 4231–4233. 88. G. Raschke, S. Kowarik, T. Franzl, C. Sonnichsen, T. A. Klar, J. Feldmann, A. Nichtl, and K. Kurzinger, Biomolecular recognition based on single gold nanoparticle light scattering. Nano Letters, 2003, 3, 935–938. 89. M. P. Kreuzer, R. Quidant, G. Badenes, and M. P. Marco, Quantitative detection of doping substances by a localised surface plasmon sensor. Biosensors & Bioelectronics, 2006, 21, 1345–1349. 90. C. R. Yonzon, E. Jeoung, S. Zou, G. C. Schatz, M. Mrksich, and R. P. Duyne, A comparative analysis of localized and propagating surface plasmon resonance sensors: the binding of concanavalin A to a monosaccharide functionalized self-assembled monolayer. Journal of the American Chemical Society, 2004, 1326, 12669–12676. 91. A. J. Haes, L. Chang, W. L. Klein, and R. P. Van Duyne, Detection of a biomarker for Alzheimer’s disease from synthetic and clinical samples using a nanoscale optical biosensor. Journal of the American Chemical Society, 2005, 127, 2264–2271. 92. T. Endo, K. Kerman, N. Nagatani, H. M. Hiepa, D. K. Kim, Y. Yonezawa, K. Nakano, and E. Tamiya, Multiple label-free detection of antigen-antibody reaction using localized surface plasmon resonance-based coreshell structured nanoparticle layer nanochip. Analytical Chemistry, 2006, 78, 6465–6475. 93. H. Fischer, I. Polikarpov, and A. F. Craievich, Average protein density is a molecular-weight-dependent function. Protein Science, 2004, 13, 2825–2828. 94. P. Englebienne, A. Van Hoonacker, and J. Valsamis, Rapid homogeneous immunoassay for human ferritin in the Cobas Mira using colloidal gold as the reporter reagent. Clinical Chemistry, 2000, 46, 2000–2003. 95. P. Englebienne, A. Van Hoonacker, and M. Verhas, Highthroughput screening using the surface plasmon resonance effect of colloidal gold nanoparticles. The Analyst, 2001, 126, 1645–1651. 96. L. Olofsson, T. Rindzevicius, I. Pfeiffer, M. Kall, and F. Hook, Surface-based gold-nanoparticle sensor for specific and quantitative DNA hybridization detection. Langmuir, 2003, 19, 10414–10419.
LSPR SPECTROSCOPY IN BIOSENSING 97. J. J. Mock, D. R. Smith, and S. Schultz, Local refractive index dependence of plasmon resonance spectra from individual nanoparticles. Nano Letters, 2003, 3, 485–491. 98. A. D. McFarland and R. P. Van Duyne, Single silver nanoparticles as real-time optical sensors with zeptomole sensitivity. Nano Letters, 2003, 3, 1057–1062.
23
99. A. Curry, G. Nusz, A. Chilkoti, and A. Wax, Substrate effect on refractive index dependence of plasmon resonance for individual silver nanoparticles observed using darkfield micro-spectroscopy. Optics Express, 2005, 13, 2668–2677.
27 Picoscopes, New Label-Free Biosensors Petr I. Nikitin Natural Science Center of General Physics Institute, Russian Academy of Sciences, Moscow, Russia
1 INTRODUCTION
Optical biosensors and biochips are widely used in many areas of science, technology, and medicine.1 Label-free or “reagentless” optical methods for detecting bio- and chemical interactions have a number of advantages such as ability to monitor reactions in real time and good reliability of results obtained using fewer operations. Among such methods, one can mention those based on the surface plasmon resonance (SPR),2 whose sensitivity and/or signal-to-noise ratio can be substantially improved by using phase peculiarities of light reflected under SPR,3–7 the reflection interference spectroscopy,8 and a variety of waveguide methods (“resonance mirror”,9 grating coupler,10 planar Mach-Zehnder interferometer,11 etc.). The phase SPR methods can be used not only for enhancement of assay sensitivity,3,4 but also for label-free readout of microarrays or biochips. For example, methods such as phasepolarization contrast with spectral SPR,5 dark-field SPR microscopy,6 and SPR interferometry7 can be used in multichannel sensor systems designated for high-throughput screening or simultaneous detection of several analytes. Although the phase detection SPR methods for gas measurements3 may yield very high threshold sensitivity, for example, relative change of refractive index n/n ≈ 4 × 10−8 , the resolution of SRP and other refractometric biosensors in studies of liquids is restricted. This is due to the
strong dependence of the refractive index of liquids upon temperature (10−4 per 1 ◦ C). The thermal drift can be partially compensated by the differentiation of the biosensing schemes or by a reference channel in two- or multichannel detection schemes.7 The sensitivity to bulk refractive index also limits the dynamic range of the sensors and the type of reagents to be used. Typically, changing of buffers and reagents brings n ≈ 0.02, whereas biochemical reactions yield only n ≈ 10−5 –10−7 . Besides, it is difficult to provide simultaneously high sensitivity and wide dynamic range of the measurements with the use of compact and affordable refractometric sensors. All the above-mentioned label-free methods employ thin-film structures with precisely deposited metal films (gold or silver) or dielectric films. Such structures and related biochips are rather expensive to be single used. Regeneration of the biochips increases maintenance cost of the equipment, which, in practice, is not lower than that of many label-based biosensing instruments. For medical diagnostics, biochip regeneration is practically unacceptable because of contamination issues. Preferably, in order to compete in medical applications with nitrocellulose immunochromatographic strips, the biochips should be comparable with them in cost. The goal of our research was the development of a new type of label-free biosensors that would be free from the above-mentioned drawbacks of this class of instruments.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
2 GLASS SLIP AS A BIOCHIP
R 0.06
For the first time, we proposed the use of simple microscopic glass slips without deposition of any metal or dielectric films as the labelfree biochips.12–15 A sufficiently thick (tens or hundreds of micrometers) slip is an acceptable Fabry–Perot interferometer provided that a small area on its surface is used for each biosensor channel. The developed technology employs interference between two beams reflected from the biochip as shown in Figure 1: the beam 5 reflected from the bottom surface of the glass slip 2 and the beam 6 reflected from the upper surface with the biological recognition layer 3. The result of the interference naturally depends on the phase thickness of the slip with the recognition layer. The calculated reflection spectrum of the glass plate with thickness d = 50 µm and refractive index n = 1.5 for radiation of a superluminescent light emitting diode (SLD) with the central wavelength λ = 850 nm and spectral width 30 nm is shown in Figure 2. The spectrum is a periodic function with maxima (minima) separated by spectral intervals that are equal to ν = c/2nd, where c is the speed of light. During a biological reaction, some components of the solution adhere to the surface of the biomolecular layer (or separate recognition spots), whereas others detach from it. This causes a change of the phase difference between the interfering waves 5 and 6 (Figure 1) and, accordingly, a change of the reflection spectrum (Figure 2). These changes are measured to judge about the binding reaction. As seen in Figure 2, the reflection from a transparent glass slip is small (only 6% at maxima and 2% at minima). So, to make an affordable disposable biochip
4
3 2 1
5
6
Figure 1. Scheme of interference pattern formation: 1: air; 2: glass slip; 3: recognition layer; 4: biological solution; 5 and 6: reflected beams.
0.04
0.02
0
830
850
870
l (nm)
Figure 2. Reflection spectrum of a glass slip of 50 µm thickness irradiated by SLD (λ = 850 nm, spectral width = 30 nm).
of a simple glass slip, we developed new low-noise methods and readout devices.
3 SPECTRAL CORRELATION METHODS
Label-free biosensors named Picoscope were developed for simultaneous real-time detection of several biological agents by measuring picometerrange changes of the thickness of different recognition spots or channels on the biochip surface. The sensors are based on spectral correlation (SC) methods, which use correlation signals between two coupled interferometers.13–15 A Picoscope optical scheme is shown in Figure 3. The first interferometer 4 is the above-mentioned glass slip (biochip) with recognition spots 8 or flow channels, or wells. The second one is a scanned interferometer 2 that employs periodical modulation of path difference of the interfering beams. For example, this could be a scanned Fabry–Perot interferometer, whose base (i.e., distance L between its two mirrors) is periodically changed by a piezoelectric driver. Other interferometers, for example, Michelson, Mach-Zahnder, including planar or fiber-optical interferometers can also be used. These interferometers are scanned by variation of the path difference of interfering beams (or arms) of the interferometers. As shown in Figure 3, the radiation from SLD 1 passes through the scanned interferometer 2, then through a semitransparent mirror 3 and is incident onto a glass plate 4. The radiation reflected from the plate is directed by the
PICOSCOPES, NEW LABEL-FREE BIOSENSORS I (ru) 6
8
7
3
4 5 6
4
2
3
9
2
1 Figure 3. Scheme of the Picoscope : 1: SLD; 2: scanned interferometer; 3: semitransparent mirror; 4: glass slip; 5: optics; 6: CCD camera; 7: fluidic system; 8: recognition spots or wells; 9: computer.
0
830
850
870
l (nm)
Figure 4. Spectra of radiation recorded by each pixel of the CCD camera for two bases of the Fabry–Perot interferometer L1 = 75 µm (low curve) and L2 = 75.212 µm (upper curve).
U (ru) 5 4
semitransparent mirror to photodetectors or a CCD camera 6. For the scanned Fabry-Perot interferometer, the initial base L is adjusted to optical thickness of the biochip L ≈ n · d. Then a scanned piezodriver periodically modulates L by a linear law with amplitude of a few micrometers. Figure 4 shows the calculated spectral distribution of the radiation incident on the photodetector or each pixel of the CCD camera for two bases L1 = 75 µm and L2 = 75.212 µm while using a 50-µm glass slip as the biochip. In the second case, the total light intensity incident to each photodetector integrated over the spectrum of the radiation source is much higher than that in the first case. The situation repeats with further increase of the base of the scanned interferometer by a half of wavelength, and so on. Precise calculations for scanning the base L between 72 and 78 µm give the resulting output signal U from each photodetector shown in Figure 5. The relative phase shift of this sinusoidal correlation dependence U (L) is used to calculate the change of thickness d of the biochip due to the biochemical reaction and sensogram generation. To realize the method, we developed hardware and software. Under the control of the software, the hardware generated different voltages
3 2 1 0
73
74
75
76
77 L (µm)
Figure 5. Dependence of correlation signal from each photodetector on the interferometer base.
applied to the piezodriver of the scanned interferometer. The resulting images from the CCD camera or signals from several photodiodes were processed by the software. In some software versions, the signals from the CCD pixels corresponding to each spot with the recognition layer were averaged over the spot area to minimize the electronic noise. In other versions, the software provided spatially resolved measurements within each spot. The area between the spots (or biological channels) was used for the reference measurements of the glass thickness changes due to, for example, temperature variations while changing the solutions to eliminate temperature drifts.
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
4 TWO-CHANNEL BIOSENSORS
1.4 PBS
1.2
Second Ab
1 ∆d (nm)
Several different types of biosensing instruments were designed based on the SC methods. They were tested for various biochemical applications. One type of the devices is designated for twochannel detection of biochemical reactions in flow mode.14 It has one additional reference channel for elimination of temperature drifts. Three separate photodiodes are used to record intensity of the light reflected from each channel. This type of the device, named Affinoscope , is intended for testing affinity between various biological and chemical agents (Figure 6). It uses a microscopic glass slip of 100 µm thickness as the biochip. A special cuvette forms two flow channels with sensing areas 1 mm in diameter. By immobilization of antibodies (Ab) on the biochip surface using different interface chemistry, for example, via biotin–streptavidin bridge,12 various proteins,14 and food pathogen15 were detected by Affinoscope . An example of detection of Listeria monocytogenes by biotinylated first Ab is given in Figure 7. The antigen (Ag) was in the form of cell suspension at concentration of C = 107 cells/ml. The Ag layer thickness averaged over the sensor’s surface of d ∼ 80 pm was surely detectable. The sensor’s response increased significantly by d = 400 pm by binding of the second native Ab. Control experiments with different combinations of nonand specific Abs and Ags showed very low (∼1%) nonspecific binding (NSB) for the used interface chemistry and reagents. The biochips were regenerated by glycine buffer (GB) with pH 2.2.
PBS
Ag
PBS
First Ab
0.8 0.6
GB
PBS Streptavidin
0.4 0.2 0 −0.2
0
1000 2000 3000 4000 5000 6000 7000
t (s)
Figure 7. Sensogram of detection of Listeria monocytogenes at concentration 107 cell/ml.
The detailed investigations showed that in the flow mode the used Ab mainly captured smallscale Ag in the form of soluble protein and fragments of cell membrane rather than whole bacteria. To increase the sensor’s response, the cell culture was heat-treated and ultrasonically processed for cell lysis. Besides, the surface density of the Ab was varied by changing the density of the biotin and streptavidin molecules to optimize specific capturing of the whole cells and soluble proteins. As a result, the cell concentration as low as 104 cells/ml was surely detected by the second Ab by recording of d = 90 pm (Figure 8). This detection limit is 2 orders of magnitude better than that of the standard enzyme-linked immunosorbent assay (ELISA) with the same Abs. The observed detection limit for bacteria is much lower than that measured by the high-end “BIAcore 2000” SPR instrument.16 Employment of the second Ab permits one to confirm specificity 2.5 2
PBS
Ag PBS
∆d (nm)
1.5
Second PBS Ab
PBS First Ab
1 0.5 0
−0.5
Figure 6. Photo of two-channel Affinoscope .
0
1000
2000
3000
4000
5000
6000
7000
Streptavidin
t (s)
Figure 8. Sensogram of detection of Listeria monocytogenes at concentration 104 cell/ml by second antibody.
PICOSCOPES, NEW LABEL-FREE BIOSENSORS
5
of reactions and to achieve the detection limit for food pathogens, which is 3–2 orders of magnitude better than that reported for the SPR devices.16,17
5 MACRO- AND MICROARRAYS
Another attractive application of the technology is label-free readout of macro- and microarrays for high-throughput screening and for biomedical diagnostics. First of all, we tested less favorable case for readout of macroarrays with very large surface area, namely, for detection of parallel reactions in 96 separate wells in a standard ELISA plate format of 127 × 85 mm2 .13,14 A photo of the Picoscope prototype for this format is shown in Figure 9. A glass plate of 50 µm thickness was used as the bottom of the ELISA frame. A special design of the frame was tested to avoid deflection of the plate while pouring and removing the solutions and to prevent vaporization of the solutions to minimize temperature drifts. The large surface area of the ELISA plate was illuminated by a low-power SLD (<0.1 mW) using parabolic optics.13 A sensitive CCD camera (Apogee Instruments Inc., Auburn, CA) was used to record an image of 96 wells simultaneously. The camera had 512 × 512 pixels and 14-bit digital output. The images were processed by a computer, which also controlled the scanned Fabry–Perot interferometer. The example of image of ELISA plate with computer-generated layout is shown in Figure 10. The software automatically found
Figure 10. Image of ELISA plate with computer-generated layout.
position of each well by correlation response, so the exact position of the plate in the device holder was not important. The signals were averaged over the area of each well. The phase changes of the correlation dependencies on L were used for calculation of the change of thickness of the biological layer in each well. A sensogram of the binding to biotinylated glass bottom of such macroarray of streptavidin and biotinylated goat Ab specific to human immunoglobulin hIgG is shown in Figure 11. Different wells were used to detect immunoglobulin hIgG at concentrations of 1, 3, and 10 µg ml−1 3.5 3 PBS
2.5 ∆d (nm)
TM
e
scop
Pico
PBS
Ab
2 1.5 Streptavidin 1 0.5 0 −0.5
Figure 9. Photo of the Picoscope for ELISA format.
0
10
20
30
40
50
60
70
80
90 100
Time (min)
Figure 11. Sensogram of binding of streptavidin molecules (at 10 µg ml−1 ) and biotinylated goat anti-hIgG antibody (at 50 µg ml−1 ) to the glass surface of ELISA wells.
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 0.5 0.4
∆d (nm)
0.3 3
0.2 2
0.1 1
0 0
−0.1
10
20
30
40
50
Time (min)
Figure 12. Detection of hIgG at concentrations of 1, 3, and 10 µg ml−1 (sensograms 1, 2, 3, respectively) by the Picoscope for ELISA format.
(Figure 12), which gave increase in thickness up to 400 pm according to kinetics of the reactions. The noise level of the 96-well reader was higher than that of two-channel biosensor14 due to illumination of a large surface area by a lowpower SLD. The long-term drift of the 96-well reader was equal to 40 pm h−1 . The Picoscope based on modern high-power SLD can be used to readout reactions in 1536-well ELISA format and for high-throughput screening. More favorable experimental conditions were realized for readout of microarrays or small biochips up to 20 × 20 mm2 with separate recognition spots on a glass slip.15 The smaller surface of such biochip permitted simplification of optical elements, decreased amount of reagents, provided higher signal-to-noise ratio for moderate power SLD as well as better fit to modern biodiagnostics trends. For testing the multispot biochips, we modified the covalent immobilization of Ab via the biotin–streptavidin bridge.15 The biotinylated Abs were spotted on the biochip located on a Peltier cooler by a capillary pipette system with a computer-controlled driver. In some cases, the spots with Ab were covered by sugar derivatives for better storage of the dried biochips. An image of several Ab spots 280 µm in diameter visualized by the Picoscope is shown in Figure 13. For the visualization, the sandwich assay similar to that used for L. monocytogenes detection (Figure 7) was realized. The size, shape, and position of the Ab spots had the required regularity for multiagent analysis by the Picoscope .
Figure 13. Image with visualized spots of antibodies on the biochip surface.
6 SPECTRAL-PHASE INTERFERENCE METHOD
For biosensors with small number of channels on a glass slip, we developed a spectral-phase interference (SPI) method.12,13 The method includes digital recording of spectrum of the glass slip with biological layers (Figure 2), determination of main harmonic of such spectrum and monitoring of the phase ϕ shift of such harmonic due to a reaction. Figure 14 shows the scheme of a singlechannel SPI biosensor.12 The cell for reagents is used either in a continuous flow or batch modes. For the sensogram, the thickness increase due to the biochemical reaction was calculated as d = (ϕ − ϕ0 )λ/(4πn), where ϕ0 is the initial phase of main harmonic of the spectrum.
4
9
3 2
8
7
5
1 6
Figure 14. Scheme of the SPI Affinoscope : 1: SLD; 2: beamsplitter cube; 3: glass slip; 4: batch or flow cell; 5: fiber; 6: diffraction grating; 7: CCD array; 8: analog-to-digital converter; 9: computer.
PICOSCOPES, NEW LABEL-FREE BIOSENSORS 2.5 GB
2 PBS
F10 PBS
∆d (nm)
Both SPI and SC methods were used for various designs of Picoscope and Affinoscope , which were successfully tested for different protein detection,12–15 epitope mapping and immunotherapy research, screening on lectins,18 bacterial pathogen detection,15 development of interface chemistry and optimization of magnetic immunoassays,19–22 for monitoring of bacteriocin production, and so on. Some of these applications are discussed below.
7
PBS
1.5 Di62
PBS
1
E7H2
TNF
0.5 0 0
2000
4000
6000
t (s)
7 APPLICATIONS EXAMPLES
Figure 16. Sensogram of TNF epitope mapping by F10, Di62, and E7H2 monoclonal antibodies.
One of the first SPI devices was used for fast characterization of binding properties of different immunoreagents. Figure 15 demonstrates binding of streptavidin, biotinylated Ab F10 specific to human tumor necrosis factor (TNF) and capturing TNF itself as well as regeneration of the biochip by GB.12 These experiments were continued (in collaboration with B.V. Radko, S.I. Rogov, L.N. Shindarova and V.G. Korobko, Institute of Bioorganic Chemistry of RAS, Moscow) for TNF epitope mapping by different monoclonal antibodies (MAbs). The related sensogram (Figure 16) starts with binding of TNF to already immobilized F10 Ab. Then, the same second Ab F10 showed fast binding to TNF with thickness increase by 850 pm. However, no binding was observed for the third Ab Di62, whereas strong signal was recorded
for the fourth Ab E7H2 at the same concentration C = 10−6 M: the thickness increased by 700 pm. For the next sensogram shown in Figure 17, the order of the second and third Abs was changed. So, the second Ab Di62 bonded well with the thickness increase of 800 pm with no detectable signal observed for the third Ab F10. The fourth Ab E7H2 also bonded very well with a smaller affinity constant defined from the slope of the sensogram. Such experiments have revealed that Abs F10 and Di62 compete for the same epitope of TNF while Ab E7H2 binds to the other site. The results demonstrate that the Picoscope can be used for fast epitope mapping. The Picoscope are also efficient auxiliary instruments for immunotherapy and related studies. They can be used for fast selection of Abs specific to certain surface proteins of pathogenic bacteria, that is, Abs that are most effective for
4 TNF PBS PBS
GB
PBS
2.5
GB
Ab 2 PBS
2
PBS
PBS
1.5 ∆d (nm)
∆d (nm)
3
PBS
1
Streptavidin
1
PBS
Di62
0
500
1000 t (s)
E7H2
0.5
0
0
F10
TNF
1500
2000
Figure 15. Sensogram of TNF binding to biotinylated antibody on the glass slip.
−0.5
0
2000
4000
6000
t (s)
Figure 17. Sensogram of TNF epitope mapping by Di62, F10, and E7H2 monoclonal antibodies.
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
therapy of the respective disease. For example, it is known that several MAbs can be used for treatment against Yersinia pestis or plague, the efficiency of such treatment being different for various MAbs or their combination.23 The Abs will neutralize activity of microorganisms only when they are directed against F 1 and LcrV Ags of Y. pestis, which are responsible for microbe pathogenicity and virulence. Moreover, only a certain region of LcrV appears to be a good target for plague-protective Abs.23 In the experiments, we investigated interactions of V Ags of Y. pestis and specific MAb (produced in the State Research Institute of Highly Pure Biopreparations, St. Petersburg, Russia). One of the Ags was commonly used V-aG Ag with molecular weight of 37 kD while the second modified LcrV Ag was only slightly smaller with weight of about 30 kD. For comparative measurements, the two-channel Picoscope was used and same biotinylated MAb were immobilized in both channels (Figure 18). The observed bindings of two Ags V-aG and modified LcrV to that Ab were quite different. The first Ag yielded the thickness increase of 700 pm. Binding of the second Ag d ≈ 85 pm was much lower (Figure 18). These results indicate that the second modified Ag practically had no target region specific for the used Mab. Picoscope can be similarly employed for fast screening of immunoreagents for therapy, for research on target identification for Ab intervention or on selection of Abs suitable for clinical use as a fast-acting pretreatment or postexposure therapy for highly dangerous infections, including plague. 2.5 Ag: Y. pestis V–aG
2.2
4
PBS
3.5
Streptavidin PBS Ab−biotin PBS
1.9
100 µg ml−1
3
1.3 Ag: Y. pestis Lcrv
1
PBS
25 µg ml−1 15 µg ml−1
−1
l
gm
µ 75
2.5
1.6
∆d (nm)
∆d (nm)
One of our initial prototypes of the SPI biosensor12 was tested for screening of lectins.18 Lectins are proteins or glycoproteins from plants, animals or microorganisms, which typically bind specifically to sugar residues, for example, located in cell walls or membranes. This reaction may change the physiology of the cell wall and influences metabolism inside the cell. Some lectins of plants stimulate the immune system by unspecific activation of T cells or influence cell division; others cause agglutination of cells (e.g., erythrocytes) and are therefore from therapeutic interest. For screening of lectins, glass slips with different types of sugar surfaces were applied: glucose, starch, glucan and mannan from Saccharomyces cerevisiae, fucoidan from Fucus vesiculosus, hyaluronic acid from Streptococcus equi and sialic acid. Dependencies of binding of Concanavalin A at different concentrations on a mannan coated glass slip, which allowed one to calculate the association and dissociation rate constants,18 are presented in Figure 19. The SPI prototype was used to study binding of six different lectins on five different carbohydrate surfaces (Figure 20). Concanavalin A proved to have the highest affinity to the polysaccharide mannan followed by fucoidan, starch, hyaluronic acid, and sialic acid.18 Lectins are from interest for cancer therapy, and the described method can contribute to discovery of new anticancer drugs. The Picoscope application for detection of food pathogens was mentioned above (Figures 7 and 8). It also was used for Salmonella detection. As the capture Abs, we used either highly purified rabbit Ab specific to Salmonella enteritidis
10 µg ml−1
2
5 µg ml−1
1.5 1
0.7
0.5
0.4
0
1 µg ml−1
0.25 µg ml−1 Baseline
−0.5
0.1 0
500
1000
1500
2000
t (s)
Figure 18. Sensogram of binding of two different V antigens to anti Y. pestis antibody.
2.5 µg ml−1 0.50 µg ml−1
0
500
1000
1500
2000
2500
t (s)
Figure 19. Dependence of thickness increase from Concanavalin A concentration on a mannan coated biochip.
PICOSCOPES, NEW LABEL-FREE BIOSENSORS
9
3 2.5
2.5
2 ∆d (nm)
3
∆d (nm)
2
1.5 Streptavidin
BSA
Ag
Second Ab Substrate
First Ab
1
1.5
TBS–Tween
TBS–Tween
0.5
1
PBS
PBS
200
400
0
0.5
0
e c
0 1
2
b 3
4
5
600
a 6
1000
1200
1400
Figure 21. Sensogram of detection of Salmonella antigen (“SLM Positive Control”).
Figure 20. Binding of selected lectins to different types of carbohydrate surfaces: 1: Canavalia ensiformis; 2: Triticum vulgaris; 3: Helix pomatia; 4: Ulex europaeus I; 5: Viscum album I; 6: Lens culinaris; a: mannan, b: starch, c: fucoidan, d: hyaluronic acid, e: sialic acid.
4 3.5 TBS–Tween
BSA
3 2.5 ∆d (nm)
(State Research Center of Applied Microbiology and Biotechnology, Obolensk, Russia) or goat Ab to different strains of Salmonella (Kirkegaard & Perry Laboratories Inc., Gaithersburg, MD, USA). Other reagents were from commercially available set “30702 Vidas Salmonella SLM”, designated for the enzyme-linked fluorescent assay carried out by miniVidas instrument produced by bioM´erieux . The Salmonella Ag (“SLM Positive Control” of the mentioned set) detected by the biotinylated Ab gave a very high response of about 2 nm as shown in Figure 21. Even being diluted in 128 times, the Salmonella Ag produced a well-detectable signal of 400 pm (Figure 22). The responses represent the result in the “reagentless” mode of the Picoscope . The estimated detectable concentration of Salmonella was less than 104 cell/ml. Another important feature was observed in these experiments. The signals substantially increased when the second polyclonal Ab labeled by alkaline phosphatase and the substrate (4-methyl-umbelliferyl phosphate, 0.6 mmol, and diethanolamine, 0.62 mol l−1 or 6.6%, pH 9.2) from the set were passed through the cuvette with our biochip (Figure 21). The conjugate enzyme catalyzed the hydrolysis of this substrate into a fluorescent product, 4-methylumbelliferone. This product was collected after passing of our cuvette and its fluorescence was well recorded at
800
t (s)
d
Streptavidin PBS First Ab
2
PBS
1.5
Ag
Second Ab
1 0.5 0 −0.5
0
200
400
600
800
1000
1200
t (s)
Figure 22. Sensogram of detection of Salmonella antigen diluted in 128 times.
450 nm. Similar comparison of both Picoscope sensograms and fluorescent signals of the product for different nonspecific immunoreagents (including using “Negative Control” from the set) confirms high specificity of the studied reactions and good correlation of both techniques. What is important is that the Picoscope sensograms can show dynamics of each step of an enzyme-based assay (as in Figure 21). So the device can be used not only in label-free mode, but it can record as many additional steps of the assay (e.g., binding of the second Ab, enzyme labels, etc.) as necessary to reach the required sensitivity or to confirm the specificity. The next application of the developed devices is devoted to fast selection of Ab pairs (“capture” and “tracer”) and buffers or to optimization of interface chemistry for other types of the sandwich assays. Development of assays based on
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
labels (enzyme, fluorescent, magnetic, etc.) is time consuming and requires a lot of combinatorial efforts to reveal a wrong interim step if the final label readout result is not acceptable. In particular, the Picoscope and Affinoscope were used for optimization of Magnetic ImmunoAssay technology (MIAtek ) based on superparamagnetic nanoparticles or magnetic bead (MB) labels.19–22 Such particles or MB were detected by our original highly sensitive method by MB nonlinear magnetization.19 The method consists in exposing of MB to magnetic field at two frequencies f1 and f2 and measuring response at combinatorial frequencies fi = m · f1 + n · f2 , where m and n are integers (one of them can be zero).19 The integers can be varied to get the best signalto-noise ratio, for example, fi = f1 ± 2f2 .19,21,22 The method allows measuring a relative change of magnetic susceptibility at the level of up to 10−8 and counting MB in wide liner dynamic range of about 5 orders of magnitude.20 Various readout devices were designed based on this method, their parameters and initial results of immunoassays were published.20 As the solid phase for MIA, the porous filters and multicapillary glass structures (photonic crystals) were used for fast immunoconcentration of the Ags.21 The MIA sensitivity is 1–2 orders of magnitude better than that of the standard ELISA assay with much shorter assay time.21,22 However, using commercially available MB mainly designated for magnetic separation of biological agents gave relatively high NSB of MB, which was 2 orders of magnitude higher than the electronic noise of our magnetic readers.20,21 So, in order to employ the high sensitivity of the magnetic readers in full, to select optimal MB and chemical interfaces on glass surfaces, and to investigate ways of decreasing NSB of MB, we used two-channel Picoscope . We recorded and compared assays on hydrophobic, coated by protein A or by streptavidin surfaces.21,22 For testing of Ab sorption on the hydrophobic glass, we pretreated the surface by different silanes.15 However, with the Picoscope , we very clearly observed the Ab and other proteins leaching.15 The binding of Ab was much stronger with using of protein A on activated glass surface and borate buffer (BB) with pH 8.2. Besides, such Ab immobilization on protein A occurred through Fc fragments, which provided proper orientation of Ab for effective capturing of the Ags.
10 8 Second Ab
6 ∆d (nm)
10
BB
BB
BB
Protein A
4
First Ab Ag
BB
MB–Dynal
2 BSA
0 0
500
1000
1500
2000
−2
t (s)
Figure 23. Sensogram of development of the magnetic immunoassay for Salmonella detection by streptavidin-coated MBs.
An example of a sensogram of the magnetic immunoassay development for Salmonella detection using Ab on protein A coated glass is presented in Figure 23. For the Salmonella Ag (“SLM Positive Control”), a strong response of 1.5 nm was observed. After binding of the second biotinylated Ab, the response of the streptavidin-coated MB (Dynabeads MyOne , Invitrogen, Norway) was much higher and reached 6 nm. The Picoscope allowed one to define the flow rate of washing buffers, which removes nonspecific and keeps specific bonded MBs. Besides, a comparison of sensograms from two channels for different nonand specific reagents was used for optimization of MIA on glass surfaces. The experiments show that Ab immobilized by Fc fragments to protein A has higher efficiency for capturing whole bacteria as compared with immobilization through the biotin–streptavidin bridge. A sensogram of detection of inactivated Legionella pneumophila cells at C = 107 cell/ml by the Ab on protein A is given in Figure 24. The signal increased for second biotinylated Ab and for streptavidin-coated MB, which had smaller diameter of about 190 nm (Figure 24). These MB and immunoreagents were also selected for fast MIA. An example of assay development for detection of Salmonella typhimurium inactivated cells using streptavidin-coated glass and protein A coated MB is presented in Figure 25. This sensogram also demonstrates proper binding of each reagent for magnetic assay. However, it shows much slower kinetics of binding of such MB to the second native Ab (Figure 25). This is, probably, due to
PICOSCOPES, NEW LABEL-FREE BIOSENSORS 6 5
∆d (nm)
4 Ag Legionella
BB
Ab–biotin
3 BB
2
MB–streptavidin
Protein A BB
BSA
1 Ab
0
200
0
400
600
800
1000
1200
1400
t (s)
Figure 24. Sensogram of development of the magnetic immunoassay for Legionella detection.
the Picoscope or diameter of capillaries of glass structures for magnetic assays. Such optimization was defined by minimization of the gap to restrict the Ag flow close to the Ab layer, on the one hand, and by increasing the gap not to clog the channel or capillaries by matrix components of tested liquids, on the other hand. Besides, active efforts were applied to direct the Ags to the Ab layer by ultrasound waves and electric field. For the Ag concentrated by magnetic separation, when it is bonded with Ab coupled with MB, the proper application of magnetic field was also used. The results show much higher efficiency of capturing the whole bacteria in such configurations.
8 DISCUSSION
1.4 1.2
PBS
PBS PBS
1 ∆d (nm)
11
Ab–biotin BSA
0.8 MB–protein A
0.6
PBS Ag
Second Ab
0.4 0.2 0 0
1000
2000
3000 4000 t (s)
5000
6000
Figure 25. Sensogram of reagent testing for Salmonella typhimurium detection by MB coated by protein A.
lower affinity constants between Ab and protein A compared with covalent binding of biotin (on second Ab) to streptavidin on MB coating in the previous case (Figure 24). So, the protocol is considered less favorable for fast MIA. Thus, the developed optical devices are efficient tools for rapid selection of protocols and reagents for labelbased assays. The experiments showed that the efficiency of capturing bacterial Ags from the flow of tested liquids also increased while using long flexiblechain spacers for immobilization of the Abs to the glass surface. This provides flexibility for active site of Ab and is useful for label-free assays. However, the tested spacers for MIA increased NSB of MB and should be modified for such applications. Alternative approaches were also tested for this task. One of them was based on optimal width of the gap of flow channels of
The experiments showed that the root-mean-square noise of the used versions of the Picoscope expressed in thickness averaged over the irradiation area was 3 pm.12–15 The value shows that a reaction can be detected when only 0.1% of the surface during the reaction is covered by protein molecules or 1% for small molecules. So, the device can be used as an analytical “molecular balance”. The drifts were 20 and 40 pm h−1 for two-channel and 96-wells readers, respectively.14 Another important feature is that variation of refractive index of the solutions leads to changes of amplitudes of maxima and minima in the spectrum of the glass slip, not their spectral positions (Figure 2). The fact allows avoiding parasitic sensitivity to the bulk refractive index of the solution. Thus, the Picoscope technology is a true direct biosensing method. It should be noted that refractive index of the proteins is slightly lower than that of the used glass slip. So, a third weak beam also reflects from the glass-protein layer interface. This beam can be eliminated by using a fused silica plate with lower refractive index. Such beam does not contribute to our algorithm of the sensogram generation, which considers only reflection from the moving boundary of the biological layer due to affinity reactions. The reflections from both boundaries of the glass slip are used only for reference measurements to compensate possible thermal expansion of the glass and related drifts. An interesting fact was observed for some porous molecular structures, namely: when a layer
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
with the refractive index lower than that of water (n = 1.33) grows on a glass slip, the sensogram gives “negative” signals. This is due to phase changes of light reflected from this layer. Such layer should cause similar “negative” signals in the SPR sensors. Several other types of biochips for the developed technology were tested (Figure 26). Figure 26(a) demonstrates a biosensor that uses a layer of the tested medium (gas or liquid with thickness dm ) or a gap 4 between two surfaces of an optical material 8 filled with the tested medium. In this case, the recognition layer 3 is deposited on at least one of such surfaces. The interference between two beams 6 and 7 reflected from surfaces with the recognition layers is used for measurements of optical thickness nm · dm of the medium in the gap. There are two differences for the gap-based variant of Affinoscope : (i) binding of a component from the medium to the recognition layer is measured as the decrease of optical thickness nm · dm , while detaching the components increases it; (ii) a change of the refractive index nm of the medium also contributes to the recorded signals. So, this is also the refractometric sensor. It can be easily used for analysis of gas media. For water in 100 µm gap, the optical thickness nm · dm changes
8 4
8
3
3
4 8
9
1
6
(a)
7
(c) 4
8 4
3
3 2
10
2
9 (b)
1 5
6
7
(d)
Figure 26. Modifications of the biochip for: (a) refractometric version of Affinoscope , (b) combined biosensor, (c) fiber-optical refractometric version of Affinoscope , (d) fiber-optical Picoscope : 1: air; 2: thin transparent plate; 3: recognition layer; 4: gas or liquid medium, 5, 6, 7: reflected beams; 8: optical material; 9: end of optical fiber or selfoc lens; 10: partially reflecting interface or coating.
by 18 nm per 1 ◦ C. The sensitivity to temperature variations in this case is 60 times higher than that borosilicate glass plate. However, a special material can be chosen for insertion into the gap so that its thermal extension compensates the change of the refractive index of the liquid under test. On the other hand, considering the temperature dependence of the reflection spectra of water layers and solid materials (plastics, semiconductors, etc.) as a beneficial feature, we developed optical temperature sensors and instruments for precise measurement of energy dissipation. The combined biochip for the Affinoscope shown in Figure 26(b) has both options, namely: both partially transparent plate 2 and gap 4 may be used simultaneously. Here two interference spectra can be analyzed: of beams 5 and 6 reflected from the plate 2 (as in Figure 1) and of beams 6 and 7 reflected from gap 4 with recognition layers 3. We successfully used thin-wall capillary tubes, especially flat capillary, as a combined biochip naturally integrated with the flow-through cuvette. The fiber-optical variants of the miniature biosensors are presented in Figure 26(c) and (d). They use the end of the optical fiber 9 (or selfoc lens on the fiber) connected with the measuring units. The refractometric biosensor (Figure 26c) is similar to that shown in Figure 26(a) and employs interference of the beams reflected from the selfoc or fiber-medium interface and from the surface of optical material 8 with recognition layer 3. Next miniature biosensor at the end of the optical fiber (Figure 26d) has reflecting interface or coating 10 between the end of the optical fiber 9 (or selfoc lens on the fiber) and partially transparent plate 2. It is based on interference between the beams reflected from interface 10 and from the top of the plate with recognition layers 3, which is similar to that demonstrated in Figure 1. So we named it fiber-optical picoscope (FOP). Due to small size of optical fiber or selfoc lens, the FOP can be used for biomedical diagnostic in vivo, for example, for recording immunochemical reactions directly during surgery intervention, or for control of hyperthermia of tumors together with discussed fiber-optical temperature sensors, and so on. These options of the bio-, chemical, and temperature sensors could be useful for online monitoring of different technological processes or medical treatments, for measurements in chromatography, during electrophoresis and other research, biomedical,
PICOSCOPES, NEW LABEL-FREE BIOSENSORS
and technological processes. The application of the Picoscope and Affinoscopes can be as wide as that of optical microscopes because they can provide standard optical lateral resolution and, in addition, offer much more comprehensive information with outstanding real-time resolution in depth, for example, for measuring molecular binding kinetics, monitoring of assembling and detaching in molecular structures, and so on.
12.
ACKNOWLEDGMENT
13.
The author thanks B.G. Gorskov, M.V. Valeiko, T.I. Ksenivich, M.P. Nikitin, N.M. Lyndin, I.E. Svetoch and I.L. Nikitina for their help in the study and useful discussions. The described research was supported in part by RFBR grant.
10.
11.
14.
15.
16.
REFERENCES 1. F. S. Ligler and C. A. R. Taitt, Optical Biosensors: Present and Future, Elsevier, Amsterdam, 2002. 2. B. Liedberg, C. Nylander, and I. Lundstr¨om, Biosensing with surface plasmon resonance–how it all started. Biosensors and Bioelectronics, 1995, 10, 1–9. 3. A. V. Kabashin and P. I. Nikitin, Interferometer utilising a surface-plasmon resonance in sensor applications. Quantum Electronics, 1997, 27, 653–654. 4. P. I. Nikitin, A. A. Beloglazov, V. E. Kochergin, M. V. Valeiko, and T. I. Ksenevich, Surface plasmon resonance interferometry for biological and chemical sensing. Sensors and Actuators B, 1999, 54, 43–50. 5. A. V. Kabashin, V. E. Kochergin, A. A. Beloglazov, and P. I. Nikitin, Phase-polarisation contrast for surface plasmon resonance biosensors. Biosensors and Bioelectronics, 1998, 13, 1263–1269. 6. A. N. Grigorenko, A. A. Beloglazov, P. I. Nikitin, C. Kuhne, G. Steiner, and R. Salzer, Dark-field surface plasmon resonance microscopy. Optics Communications, 2000, 174, 151–155. 7. P. I. Nikitin, A. N. Grigorenko, A. A. Beloglazov, M. V. Valeiko, A. I. Savchuk, O. A. Savchuk, G. Steiner, C. Kuhne, A. Huebner, and R. Salzer, Surface plasmon resonance interferometry for micro-array biosensing. Sensors and Actuators A, 2000, 85, 189–193. 8. G. Gauglitz, A. Brecht, G. Kraus, and W. Nahm, Chemical and biochemical sensors based on interferometry at thin (multi-) layers. Sensors and Actuators B, 1993, 11, 21–27. 9. R. Cush, J. M. Cronin, W. J. Stewart, C. H. Maule, J. O. Molloy, and N. J. Goddard, The resonant mirror–a novel optical biosensor for direct sensing of biomolecular interactions: principle of operation and
17.
18.
19.
20.
21.
22.
23.
13
associated instrumentation. Biosensors and Bioelectronics, 1993, 8, 347–353. W. Lukosz and C. Stamm, Integrated optical interferometer as relative humidity sensor and differential refractometer. Sensors and Actuators A, 1991, 25 – 27, 185–188. R. G. Heideman, and P. V. Lambeck, Remote optochemical sensing with extreme sensitivity: design, fabrication and performance of a pigtailed integrated optical phase-modulated Mach-Zehnder interferometer system. Sensors and Actuators B, 1999, 61, 100–127. P. I. Nikitin, B. G. Gorshkov, M. V. Valeiko, and S. I. Rogov, Spectral-phase interference method for detecting biochemical reactions on a surface. Quantum Electronics, 2000, 30, 1099–1104. P. I. Nikitin, B. G. Gorshkov, M. V. Valeiko, and S. I. Nikitin, Multichannel optical biosensors for label free high-throughput screening. Proceedings of SPIE, 2001, 4578, 126–135. P. I. Nikitin, M. V. Valeiko, and B. G. Gorshkov, New direct optical biosensors for multi-analyte detection. Sensors and Actuators B, 2003, 90, 46–51. P. I. Nikitin, B. G. Gorshkov, E. P. Nikitin, and T. I. Ksenevich, Picoscope, a new label-free biosensor. Sensors and Actuators B, 2005, 111 – 112, 500–504. E. A. Perkins and D. J. Squirrell, Development of instrumentation to allow the detection of microorganisms using light scattering in combination with surface plasmon resonance. Biosensors and Bioelectronics, 2000, 14, 853–859. V. Koubova, E. Brynda, L. Karasova, J. Skvor, J. Homola, J. Dostalek, P. Tobinska, and J. Rosicky, Detection of foodborne pathogens using surface plasmon resonance biosensors. Sensors and Actuators B, 2001, 74, 100–105. M. Hartmann, P. Nikitin, and M. Keusgen, Innovative analytical system for screening on lectins. Biosensors and Bioelectronics, 2006, 22, 28–34. P. I. Nikitin and P. M. Vetoshko, Process of Analysis of Mixture of Biological and/or Chemical Components with Use of Magnetic Particles and Device for its Implementation, Patent of Russian Federation RU 2166751, 2000, European Patent Application EP1262766 publication, 2001. P. I. Nikitin, P. M. Vetoshko, and M. V. Valeiko, New Type of Biosensors Based on Detection of Superparamagnetic Nanoparticles, Book of Abstracts of Eurosensors XVII Conference, Guimaraes, Portugal, September 21–24, 2003, 140–141, Available on-line at: https://repositorium.sdum.uminho.pt/handle/1822/4837. P. I. Nikitin, P. M. Vetoshko, and T. I. Ksenevich, Magnetic immunoassays. Sensor Letters, 2007, 5, 296–299. P. Nikitin, P. Vetoshko, and T. Ksenevich. New type of biosensors based on magnetic nanoparticle detection. Journal of Magnetism and Magnetic Materials, 2007, 311, 445–449. J. Hill, C. Copse, S. Leary, A. J. Stagg, E. D. Williamson, and R. W. Titball, Synergistic protection of mice against plague with monoclonal antibodies specific for the f1 and v antigens of yersinia pestis. Infection and Immunity, 2003, 71, 2234–2238.
28 Chemiluminescent Optical Fiber Immunosensor Sebastien Herrmann1 and Robert S. Marks1,2 1
Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel and 2 National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
1 INTRODUCTION TO CHEMILUMINESCENCE 1.1
Definition
Luminescence is a term used to describe the light emission that occurs when a molecule in an excited state relaxes to its ground state.1 The various types of luminescence differ from the source of energy to obtain the excited state. In chemiluminescence, the energy is produced by a chemical reaction. Since excitation is not required for sample radiation, problems frequently encountered in photoluminescence as light scattering or source instability are absent in chemiluminescence. High backgrounds due to unselective photoexcitation are absent too: there is no need for time resolved detection. The main advantages of chemiluminescence labeling and detection in bioassays are: a large linear response reaching up to six orders of magnitude, the fast emission of light, the high stability of the reagents and conjugates, and the low consumption of expensive reagents. Moreover there are only short incubation times owing to the high sensitivity generally achieved.2 Although various sensors based on chemiluminescence were built for analytical applications,3 this chapter will focus on the bioassays based on optical fibers.
1.2
Optical Parameters
Chemiluminescence, which is the phenomenon observed when the vibronically excited product of an exoergic reaction relaxes to its ground state with emission of photons, can be defined in simplistic terms: chemical reactions that emit light.4 The chemical reaction produces energy in sufficient amount to induce the transition of an electron from its ground state to an excited electronic state. This electronic transition is often accompanied by vibrational and rotational changes in the molecule. Return of the electron to the ground state with emission of a photon is thus called chemiluminescence. The excited molecule can also lose energy by undergoing chemical reactions, by collisional deactivation, internal conversion or inter-system crossing. These radiationless processes are undesirable from an analytical point of view when they compete with chemiluminescence. The fraction of molecules emitting a photon on return to the ground state is the quantum yield (cl ). It is the product of three ratios: cl = c × e × f where c is the fraction of reacting molecules giving an excitable molecule and accounts for the yield of the chemical reaction; e is the fraction of such molecules in an electronically excited state and relates to the efficiency of the
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
energy transfer and f is the fraction of these excited molecules that return to the ground state by emitting a photon (Figure 1). A lot of organic molecules are chemiluminogenic but the quantum yields are generally very low, typically less or far less than 1%. This inefficiency, in most cases, is due to low yield of the chemical reaction or poor energy transfer but, in some instances, the excited molecule is a poor emitter. The addition to the system of a more efficient fluorophore results in a non-radiative energy transfer to that fluorophore which emits intense light. 1.3
as little as 0.6 picograms of adenosine triphosphate (ATP) or 0.1 femtograms of luciferase, two common luminescent analytes. In luminescence, there are two components of light that reach the detector. The first component is proportional to the concentration of the limiting reactant in the chemiluminescent reaction. The second component, known as background, is an approximately constant light level due to various factors such as the phosphorescence of plastics, impurities in the reagents. This background light component is much lower in luminometry than in other analytical techniques such as spectrophotometry and fluorometry. Wide dynamic range and low instrument cost are also distinct advantages of luminometry. Samples can be measured across decades of concentration without dilution or modification of the sample cell.
The Advantages of Luminometry
Luminometry, the analytical technique used to measure chemiluminescent reactions, has several advantages over other analytical techniques. Extraordinary sensitivity, a wide dynamic range, inexpensive instrumentation, and the emergence of novel luminescent assays make this technique very popular. Superior sensitivity and low background distinguish luminometry from other analytical methods. Luminometry is up to 100 000 times more sensitive than absorption spectroscopy and is at least 1000 times more sensitive than fluorometry.5 A well-designed luminometer can detect
2 THE BIOCHEMISTRY OF CHEMILUMINESCENCE 2.1
Substrates Used in Chemiluminescent Reactions
Numerous substrates have been already used in the field of chemiluminescence. Luminous animals Collisional deactivation
Chemiexcitation X
Y∗
S1
Inter system crossing T2
1. Chemireaction (Φc) (150–300 kJ mole−1)
Internal conversion
2. Energy transfer (Φe)
T1
Fluorescence (Φf)
Photoexcitation
Phosphorescence
Non-radiative processes S0
S0
Y
Y
Figure 1. Diagram placing chemiluminescence among the most typical photophysical processes. The radiationless processes are undesirable from an analytical point of view when they compete with chemiluminescence. [Reprinted with permission Dodeigne et al.1 copyright 2000, Elsevier.]
CHEMILUMINESCENT OPTICAL FIBER IMMUNOSENSOR
are known since the ancient Greek civilization but ‘artificial’ chemiluminescence was only described in 1877 by Radziszewski who observed the yellow light emission when oxygen was bubbled into an alkaline ethanolic solution of 2,4,5triphenylimidazole (lophine).6 Fifty years later, Albrecht reported the luminescent properties of 5amino-2,3-dihydrophtalazine-1,4-dione (luminol)7 Acridinium derivatives were known as chemiluminogenic molecules since Gleu and Petsch, in 1935, described the blue or green light emission of bis(N -methylacridinium) nitrate (lucigenin).8 After McCapra, in 1964, has proposed a mechanism based on the formation of a dioxetanone cycle for explaining the chemiluminescence of acridinium salts,9 derivatives of dioxetane and dioxetanedione (peroxyoxalate) have been prepared and experimented on.10,11 Most of the chemiluminescent bioassays are currently based on luminol and its derivatives, alone or coupled to light enhancers (Figure 2). 2.2
Enzymes Used in Chemiluminescent Reactions
In aprotic media (dimethylsulphoxide or dimethylformamide), only oxygen and a strong base are required for chemiluminescence.13 In protic solvents (water, water solvent mixtures or lower alcohols), various oxygen derivatives (molecular oxygen, peroxides, superoxide anion) can oxidize luminol derivatives but catalysis either by enzymes or by mineral catalysts is required.14 Since the beginning, many catalysts have been proposed13,15,16 : enzymes such
3
as microperoxidase, myeloperoxidase, horseradish peroxidase, catalase, xanthine oxidase,17–19 metalloproteins as cytochrome c,20 haemoglobin especially haptoglobin,21 deuterohemin or mineral catalysts such as molecular ozone and halogens or persulphate anion or Fe(III), Co(II) and Cu(II) cations as well as their complexes. More recently, the bacterial peroxidase from Arthromyces ramosus characterized by a very high turn-over has been proposed and a hundred times increase in sensitivity was claimed.22,23 Moreover, many enzymes or enzyme mixtures that produce oxygen derivatives as by-products have been involved in chemiluminescent detection. Alkaline phosphatase, b-D-galactosidase and b-glucosidase in the presence of indoxyl conjugates as substrates,24 lactate oxidase,25 acylCoA synthetase and acylCoA oxidase26 or diamine oxidase27 produce hydrogen peroxide; 3-a hydroxysteroid deshydrogenase28 or glucose-6-phosphate deshydrogenase release nicotinamide adenine dinucleotide hydrogen (NADH) which reduces, in the presence of 1-methoxy-5-methylphenazinium methylsulphate, molecular oxygen to hydrogen peroxide which generates light in the luminol microperoxidase system. 3 DETECTION OF CHEMILUMINESCENCE: PHOTON-COUNTING SYSTEMS 3.1
Charged-coupled Device
Sometimes an array of tiny detectors is not sufficient but a two-dimensional matrix of detectors is needed. Charge-coupled device (CCD) sensors and
NH2 O − N− + H2O2 + HO NH
Peroxidase
O NH2 O
O
NH2 O O*− + N2 + 3H2O
O− + Light (λmax = 430 nm)
O−
O− O
Figure 2. Chemiluminescent reaction produced by the catalysis of hydrogen peroxide by horseradish peroxidase (HRP) and the charge transfer to luminol. [From Konry et al.12 ]
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
cameras are available for both of these purposes. CCD cameras are useful, e.g. in the areas of high temperature superconductors (HTSs) and astronomy. CCD-detection is also used in atomic emission spectrometry,29 and in fact it has also been predicted that in atomic absorption spectrometry the Charge-coupled array detector together with a high intensity continuum light source would be in the future the choice number one.30 A CCD is best described as a semiconductor chip, one face of which is sensitive to light. Typically, it is fabricated from a p-doped silicon layer on an n-doped substrate. This structure is then capped with an insulating layer of SiO2 (easily obtainable by thermal oxidation), on top of which is placed a pattern of highly doped and strongly conducting silicon electrodes. The light sensitive face is rectangular in shape and subdivided into a grid of discrete rectangular areas, called pixels. The arrival of a photon on a pixel generates a small electrical charge, which is stored for later read-out. The size of the charge increases cumulatively as more photons strike the surface. By using a few clocking circuits, an amplifier and a fast analogue-to-digital converter (ADC), it is possible to evaluate the amount of light that has fallen onto each pixel by examining the amount of charge it has stored. The chip will usually be cooled to reduce the noise level. The whole instrument is often referred to as a CCD camera. The electronics controlling the CCD chip are interfaced to a computer, which in turn controls them. Thus, the images observed by the CCD are transferred directly to a computer memory without an analogue stage, hence they can be plotted on an image display device or written to a magnetic disk. The principal advantages of CCDs are their high sensitivity, dynamic range and linearity.
3.2
Photomultiplier Tube
An efficient and accurate light detection is a common need to all analytical luminescence methods.31 The size of the required photosensitive area of the detector varies depending on the application. In photo-cathode devices, the photons are incident on the active region of the material forming the detector. The surface material of the photo-cathode plays a key role in the functioning
of a photo-emissive light detector and the wavelength range of sensitivity is dictated primarily by the absorption band of the cathode material and to some extent the work function of the surface.32 One of the strengths of the devices based on the photo-cathodes is their very low noise level. In all semiconductor photo-detectors, one or more semiconductor layers are typically grown on a suitable substrate. The simplest of semiconductor photo-detectors, the photo-conductive types, are not very usable in analytical applications. The other type requires a junction, either of the p–n junction variety or of the Schottky barrier variety. In both cases, the light must be allowed to penetrate to the region designed for absorption. When the energy of the absorbed photon is large enough to raise an electron from the valence band to the conduction band, they create holes in the valence band. The existing electric field separates then the electrons and holes and causes the terminal current to flow in proportion to the photon flux. When low light intensities need to be detected and measured, single-photon counting using photocathode devices or photomultiplier tubes (PMT), has for long been the first choice. However, the traditional way of measuring just the photocurrent of the PMT is often perfectly satisfactory. If high magnetic fields are problematic for vacuum PMTs the gas-filled PMTs can be a solution.33
3.3
Single Photon Avalanche Diodes
The economically most promising area of the rapidly developing analytical chemistry lies in the area of analysis made outside of big central laboratories, in the actual place needing the analysis: in the points of environmental problems, at home, at the site of a chemical production processes, etc. Most often these applications would require a very inexpensive apparatus, and often the methods utilized should preferably allow for reliable use by untrained personnel or final end users. The apparatus should normally also be small in size and optionally battery operated. Fortunately, new emerging technologies seem to fulfill these needs. Silicon photodiodes with effective areas of a few square millimetres have proven to be inexpensive and useful in some applications of steady state fluorometry. These are based
CHEMILUMINESCENT OPTICAL FIBER IMMUNOSENSOR
on a reverse biased p–n junction. The reverse bias voltage has the effect of increasing the voltage across the depletion layer compared with a forward bias voltage so that any photo-induced electron–hole pairs are swept rapidly across the junction to create a current pulse. However, these diodes are not suitable for single-photon counting purposes. Avalanche photodiodes (APDs) have been developed for photon counting purposes and are thus called single-photon avalanche diode (SPADs).34,35 These devices consist of a reverse biased p–i–n junction and operate in a non-proportional multiplication mode analogous to a Geiger M¨uller tube. The reverse bias is held slightly above rather than below the breakdown voltage for the junction. The electric field is sufficiently high to sustain an avalanche of carrier multiplication via secondary ionisation once a primary electron–hole pair has been photo-induced by absorption in the depletion layer. The diode current is either turned off passively by limiting the current flowing with a suitable resistor, or actively by lowering the bias voltage after the onset of the avalanche.36,37 In the PMT the primary photo electron is emitted from the photo cathode into vacuum and then multiplied by secondary electron emission. The shower of secondary electrons is collected by the anode and produces a current impulse at the output. To operate a PMT as a single photon detector, the gain (controlled by the operating voltage) must be set to a level to produce output pulses (from single primary electrons) in excess of the threshold of the timing device. In the SPAD a conduction electron is excited internally, which triggers an avalanche breakdown. A characteristic feature of a SPAD is the extremely small variance of the amplitude of the output pulses even if more than one primary photo electron was to be excited by the light pulse. The PMT produces, on the other hand, output pulses with high variance (depending on the type) and the mean amplitude is proportional to the number of primary photo-electrons. An important parameter of all detectors is the percentage of photo-electrons produced per photon, the quantum efficiency. It ranges from a few percent to more than 50%. The spectral response of a SPAD is determined on the long wavelength side by the band gap of the semiconductor employed. Presently, photon counting using PMTs still seems to be the most cost-effective way to detect
5
very low light levels and they have quite large photo-cathode areas, if such are needed by the application. SPAD-detectors will surely become more and more attractive as time goes by and their development proceeds further and the prices decrease. Also, CCD detectors surely will find their way to the relatively low-cost instruments in the future.
4 OPTICAL FIBER BIOSENSOR 4.1
Use of Fiber-optic Systems
Biosensors couple an immobilized biospecific recognition entity to the surface of a transducer, which “transduces” a molecular recognition event into a measurable electrical signal, pinpointing the presence of the target. Chemiluminescent optical fiber biosensors use the fiber to transduce the photons emitted during the chemiluminescent reaction. All optical fibers operate by “total internal reflection.” If a ray of light in a medium of refractive index n1 strikes the interface with another medium of refractive index n2 (n2 < n1), at an angle θ , and θ is greater than θC , the ray is totally reflected back into the first medium. θC = sin−1 (n2/n1) and is called the critical angle. An optical fiber exploits total internal reflection by having an inner region of high refractive index and a cladding of lower index. Light is confined by repeated reflections. Single strands of transparent material such as glass or fused silica can pipe-trapped light over long distances with very low loss. Light entering the fiber within the acceptance cone is totally reflected at the core-cladding interface. Optical fiber sensors are ideal transducers governed by Snell’s law. They have the following advantages38 : (1) geometric convenience and flexibility; (2) low cost of production; (3) they are inert and therefore non-hazardous; (4) they are free of electric interference; (5) being dielectric, they are protected against atmospheric disturbances; (6) their small volume economizes reagents and enables portability as well as access to difficult areas; (7) they are robust with high tensile strength; (8) their silica composition enables macromolecular conjugation via silanization; (9) they enable solid-phase characterization of the analyte; (10) their potentially long interaction lengths
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
enable remote signal transmission; (11) light transmission is done with minimal loss; (12) high efficiency coupling occurs in the blue region which is ideal for chemiluminescence; (13) optical multiplicity; (14) polyvalence, as an optrode system, they can be easily adapted from one antigen–antibody system to another; (15) they are amenable to mass production; (16) they enable multiple antigen detection via fiber bundles. Numerous groups have worked on the key issue of the optimization of the coupling of light, so as to increase sensitivity of the system. Methods developed include physical modification of the endface geometry of the optical fiber, using step-etch, continuous, combination tapers39 or using inwardly, adiabatically tapered loops to a waist diameter typically about that of the original core, then outwardly back to the original core-cladding diameter.40 These methods provide sufficiently large optically active areas. Another method is the construction of an organic waveguide at the core-biochemical layer interface, at a certain optimal index of refraction and key layer thickness.41 4.2
Surface Activation and Immobilization of the Bioreceptor
Optical fibers used in chemiluminescent measurement are mostly based on a silica surface that has to be activated in order to bind the bioreceptor. Immobilization of the biological receptor onto the fiber surface is usually achieved by silanization of a bi-functional silane (general structure (MeO)3Si(CH2)nX) that allows for the covalent attachment of the biomolecule with an appropriate cross-linker or by direct chemical modification of the reactive X group.38 However, liquid-phase silanization often provides low reproducibility of the silane layer configuration and gas phase preparation, whereas producing better quality surfaces, usually requires vacuum conditions and high temperature to obtain high surface coverage. A recent study showed the possibility of performing a gasphase silanization procedure at room temperature and atmospheric pressure on silicon oxide,42 which has been adapted on fiber,43 Other chemistries have been used involving cyanogen bromide,44 photoactivable silane,45 electrochemical polymerization of derived pyrrole monomers12 or via an avidin/biotin bridge.46
4.3
Applications
The first mention of a fiber-optic biosensor based on luminescence was made by Gautier et al. in 1989, for the microdetermination of NADH.47 Later, Arenkov et al. has created the first chemiluminescent fiber-optic immunosensor for detecting antibodies to the influenza virus.48 Using this kind of sensor compared to conventional solid-phase immunoassay they proved an important decrease in the response time and a significant improvement in sensitivity. In 1993, Coulet et al. built another application by using co-immobilized enzymes. They also emphasized the simplicity of the optical system based on luminescence since no light source or monochromator were necessary while they kept sensitivity, selectivity and polyvalence.49 Later on, these fiber based biosensors were used for the detection of organophosphorus pesticides. Based on the grafting of multiple phosphatase layers, this system, was able to detect ppb level of toxic material in less than 30s.50 Nowadays, numerous chemiluminescent optical fiber immunosensors have been developed to diagnose infection of viral pathogens like Hepatitis C virus,51 West Nile virus (Figure 3),43 Ebola virus52 and but also bacterial targets, such as Vibrio cholera 45 and even tumor markers.53 Some of the latest innovations in this field were brought by D. Walt and coworkers who were using imaging fiber bundles in the field of molecular biology.54 These bundles comprise thousands of individual fibers melted and drawn together in a coherent way so that an image can be carried and maintained from one end to the other allowing multiple reading at one time. Very preliminary studies showed also the possibility of modifying covalently a polymer-based optical fiber and build a chemiluminescent immunosensor at very low cost using phage display epitopes. In summary, the advantages of using chemiluminescent optical fiber immunosensors are their high sensitivity, specificity, robustness and portability. Those unique aspects make this technology a very promising candidate for new all-in-one devices incorporating both the sensors and the microfluidics necessary to the biological tests. An example of such unique project is the BioPen—presented as the first lab-in-a-pen - lead by Dr Robert Marks’ team.
CHEMILUMINESCENT OPTICAL FIBER IMMUNOSENSOR
Step 1
7
−
Si
O
Si
OH
Si
O
Si
OH
Si
O
Optical-fiber core OMe
−
MeO
Si
(3-Mercapiopropyl) trimethoxysllane
SH
OMe O
O O N CH2(CH2)3CH3 C O N
−
O
6-Maleimidohexanoic acid N hydroxysuccinimide ester
O
OMe Si
Step 2
O
Si
Si
OH
O
Si
O
Si
Si
OH
O
Si
O
Si
West nile virus (WNV) inactivated virions
SH SH
Step 5
Blocking reagents
SH
Mouse anti-WNV IgG (analyte)
OMe O
O O N CH2(CH2)3CH3 C O N
OMe Si
O
Si
OH O
Si
S O
Step 3
Si
O
Si
OH O
Si
O
Rabbit antimouse IgG HRP-labelled
O
O
O O N CH2(CH2)3CH3 C O N
S
Si
O
Step 6
O
O
O O N CH2(CH2)3CH3 C O N
S
Si OMe
O
H2O2 + Luminol
O
O OMe Si O
Si
O N CH2(CH2)3CH3 C O NH S O
Si OH O
Step 4
Si O
Si
O S
O N CH2(CH2)3CH3 C O
Step 7
O
Si OH O
O Si O
Si OMe
S
O N CH2(CH2)3CH3 C O NH O
3-Aminophthalate*
(a) Step 8 Light
3-Aminophthalate
(b)
Figure 3. Optical fiber modification and immunoassay rationale for the detection of anti West Nile virus Immunoglobulin G. [Reprinted with permission Herrmann et al.43 copyright 2005, Elsevier.]
REFERENCES 1. C. Dodeigne, L. Thunus, and R. Lejeune, Chemiluminescence as diagnostic tool. A review. Talanta, 2000, 51(3), 415–439. 2. N. F. Starodub, P. J Arenkov, A. N Starodub, and V. A Berezin, Fiber optic immunosensors based on enhanced chemiluminescence and their application to determine different antigens. Sensors and Actuators B-Chemical, 1994, 18(1–3), 161–165. 3. Z. Zhang, S. Zhang, and X. Zhang, Recent developments and applications of chemiluminescence sensors. Analytica Chimica Acta, 2005, 541(1–2), 37–46. 4. I. Weeks, Chemiluminescence immunoassay. Wilson and Wilson’s Comprehensive Analytical Chemistry, 1992, 29, 91–97. 5. G. K. Turner, Measurement of Light from Chemical or Biochemical Reactions, Bioluminescence and Chemiluminescence: Instruments and Applications, K. Van Dyke (ed), Vol. 1,1985, CRC Press: pp. 43–78. 6. B. Radziszewski, Untersuchungen u¨ ber hydrobenzamid, amarin und lophin. Chemische Berichte, 1877, 10(1877), 70–75.
7. H. O. Albrecht, Chemiluminescence of aminophthalic hydrazide. Zeitschrift fur Physikalische Chemie, 1928, 136, 321–330. 8. K. Gleu and W. Petsch, Die chemiluminescenz der dimethyldiacridyliumsalze. Angewandte Chemie, 1935, 48, 57–59. 9. F. McCapra and D. G. Richardson, The mechanism of chemiluminescence: a new chemiluminescent reaction. Tetrahedron Letters, 1964, 43, 3167–3172. 10. M. M. Rauhut, L. J. Bollyky, B. G. Roberts, M. Loy, R. H. Whitman, A. V. Iannotta, A. M. Semsel, and R. A. Clarke. Chemiluminescence from reactions of electronegatively substituted aryl oxalates with hydrogen peroxide and fluorescent compounds. Journal of the American Chemical Society, 1967, 89, 6515–6522. 11. K. R. Kopecky and C. Mumford, Luminescence in the thermal decomposition of 3,3,4-trimethyl-1,2-dioxetane. Canadian Journal of Chemistry, 1969, 47, 709–711. 12. T. Konry, A. Novoa, S. Cosnier, and R. S. Marks, Development of an “electroptode” immunosensor: indium tin oxide-coated optical fiber tips conjugated with an electropolymerized thin film with conjugated cholera toxin B subunit. Analytical Chemistry, 2003, 75(11), 2633–2639.
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
13. H. R. Schroeder and F. M. Yeager, Chemiluminescence yields and detection limits of some isoluminol derivatives in various oxidation systems. Analytical Chemistry, 1978, 50, 1114–1120. 14. D. F. Roswell and E. H. White, The chemiluminescence of luminol and related hydrazides. Methods in Enzymology, 1978, 57, 409–423. 15. K. Van Dyke, Bioluminescence and Chemiluminescence: Instruments and Applications, CRC Press: Boca Raton, FL, 1985. 16. H. A. H. Rongen, R. M. W. Hoetelmans, A. Bult, and W. P. Van Bennekom, Chemiluminescence and immunoassays. Journal of Pharmaceutical and Biomedical Analysis, 1994, 12, 433–462. 17. E. H. Jansen, R. H. van den Berg, and G. Zomer, Characteristics and detection principles of a new enzyme label producing a long-term chemiluminescent signal. Journal of Bioluminescence and Chemiluminescence, 4, 1989, 129–135. 18. R. A. Radi, H. Rubbo, and E. Prodanov, Comparison of the effects of superoxide dismutase and cytochrome c on luminol chemiluminescence produced by xanthine oxidase-catalyzed reactions. Biochimica Et Biophysica Acta-Protein Structure and Molecular Enzymology, 1989, 994, 89–93. 19. R. Radi, H. Rubbo, L. Thomson, and E. Prodanov, Luminol chemiluminescence using xanthine and hypoxanthine as xanthine oxidase substrates. Free Radical Biology and Medicine, 1990, 8, 121–126. 20. A. A. Akhrem, G. N. Semenkova, S. N. Cherenkevich, Y. M. Popova, and P. A. Kiselev, Chemiluminescence of luminol caused by interaction of cytochrome P-450 and cytochrome C with cumene hydroperoxide: comparative studies. Biomedica Biochimica Acta, 1985, 44, 1591–1597. 21. A. V. Kozlov, A. N. Osipov, and Yu. A. Vladimirov, Mechanism of luminole-dependent chemiluminescence of human blood serum in the presence of hydrogen peroxide. Biofizika, 1990, 35, 347–349. 22. B. B. Kim, V. V. Pisarev, and A. M. Egorov, A comparative study of peroxidases from horse radish and arthromyces ramosus as labels in luminol-mediated chemiluminescent assays. Analytical Biochemistry, 1991, 199, 1–6. 23. K. Akimoto, Y. Shinmen, M. Sumida, S. Asami, T. Amachi, H. Yoshizumi, Y. Saeki, S. Shimizu, and H. Yamada, Luminol chemiluminescence reaction catalyzed by a microbial peroxidase. Analytical Biochemistry, 1990, 189, 182–185. 24. H. Arakawa, M. Maeda, and A. Tsuji, Chemiluminescent assay of various enzymes using indoxyl derivatives as substrate and its applications to enzyme immunoassay and DNA probe assay. Analytical Biochemistry, 1991, 199, 238–242. 25. M. Tabata, M. Totani, and T. Murachi, Determinations of lactate and lactate dehydrogenase activity in serum with the flow injection analysis system involving immobilized enzyme column and chemiluminescence. Analytical Biochemistry, 1991, 193, 112–117. 26. B. M. Naslund, K. Bernstrom, A. Lundin, and P. Arner, Free fatty acid determination by peroxidase catalysed luminol chemiluminescence. Journal of Bioluminescence and Chemiluminescence, 1989, 3, 115–124.
27. L. Bruun and G. Houen, In situ detection of diamine oxidase activity using enhanced chemiluminescence. Analytical Biochemistry, 1996, 233, 130–136. 28. S. Ikegawa, N. Hirabayashi, T. Yoshimura, M. Tohma, M. Maeda, and A. Tsuji, Determination of conjugated bile acids in human urine by high-performance liquid chromatography with chemiluminescence detection. Journal of Chromatography-Biomedical Applications, 1992, 577, 229–238. 29. F. M. Pennebaker, D. A. Jones, C. A. Gresham, R. H. Williams, R. E. Simon, and M. F. Schappert, Spectroscopic instrumentation in the 21st century: excitement at the horizon: plenary lecture. Journal of Analytical Atomic Spectrometry, 1998, 13, 821–827. 30. J. M. Harnly, The future of atomic absorption spectrometry: a continuum source with a charge coupled array detector. Journal of Analytical Atomic Spectrometry, 1999, 14, 137–146. 31. S. Kulmala and J. Suomi, Current status of modern analytical luminescence methods. Analytica Chimica Acta, Analytical Horizons–An International Symposium Celebrating the Publication of Volume 500 of 2003, 500(1–2), 21–69. 32. H. Markoc, A. Di Carlo, and R. Cingolani, GaN-based modulation doped FETs and UV detectors. Solid-State Electronics, 2002, 46, 157–202. 33. A. Breskin, T. Boutboul, A. Buzulutskov, R. Chechik, G. Garty, E. Shefer, and B. K. Singh, Advances in gas avalanche photomultipliers. Nuclear Instruments and Methods in Physics Research Section A-Accelerators Spectrometers Detectors and Associated Equipment, 2000, 442, 58–67. 34. F. Zappa, A. L. Lacaita, S. D. Cova, and P. Lovati, Solidstate single-photon detectors. Optical Engineering, 1996, 35, 938–945. 35. D. Robinson and B. Metscher, Photon detection with cooled avalanche photodiodes. Applied Physics Letters, 1987, 51, 1493. 36. S. Cova, A. Longoni, and G. Ripamonti, Active-quenching and gating circuits for single-photon avalanche diodes (SPAPDs). IEEE Transactions on Nuclear Science, 1982, NS29, 599–601. 37. M. Ghioni, S. Cova, F. Zappa, and C. Samori, Compact active quenching circuit for fast photon counting with avalanche photodiodes. Review of Scientific Instruments, 1996, 67, 3440–3448. 38. R. S. Marks, E. Bassis, A. Bychenko, and M. M. Levine, Chemiluminescent optical fiber immunosensor for detecting cholera antitoxin. Optical Engineering, 1997, 36(12), 3258–3264. 39. G. P. Anderson, J. P. Golden, and F. S. Ligler, A fiber optic biosensor: combination tapered fibers designed for improved signal acquisition. Biosensors and Bioelectronics, 1993, 8(5), 249–256. 40. Z. M. Hale and R. Marks, Optical Waveguide Chemical and Biological Sensor, United States Department of the Air Force, USA 1996, 10. 41. Z. M. Hale, F. P. Payne, R. S. Marks, C. R. Lowe, and M. M. Levine, The single mode tapered optical fiber loop immunosensor. Biosensors and Bioelectronics, 1996, 11(1/2), 137–148.
CHEMILUMINESCENT OPTICAL FIBER IMMUNOSENSOR 42. E. Pavlovic A. P. Quist, U. Gelius, and S. Oscarsson, Surface functionalization of silicon oxide at room temperature and atmospheric pressure. Journal of Colloid and Interface Science, 2002, 254(1), 200–203. 43. S. Herrmann, B. Leshem, S. Landes, B. Rager-Zisman, and R. S. Marks, Chemiluminescent optical fiber immunosensor for the detection of anti-West Nile virus IgG. Talanta, 2005, 66(1), 6–14. 44. N. Strashnikova, V. Papper, P. Parkhomyuk, G. I. Likhtenshtein, V. Ratner, and R. Marks, Local medium effects in the photochemical behavior of substituted stilbenes immobilized on quartz surfaces. Journal of Photochemistry and Photobiology A-Chemistry, 1999, 122(2), 133–142. 45. B. Leshem, G. Sarfati, A. Novoa, I. Breslav, and R. S. Marks, Photochemical attachment of biomolecules onto fibre-optics for construction of a chemiluminescent immunosensor. Luminescence, 2004, 19(2), 69–77. 46. B. Polyak, S. Geresh, and R. S. Marks, Synthesis and characterization of a biotin-alginate conjugate and its application in a biosensor construction. Biomacromolecules, 2004, 5(2), 389–396. 47. S. M. Gautier, L. J. Blum, and P. R. Coulet, Fibreoptic biosensor based on luminescence and immobilized enzymes: microdetermination of sorbitol, ethanol and oxaloacetate. Journal of Bioluminescence and Chemiluminescence, 1990, 5(1), 57–63. 48. P. Arenkov, V. A. Berezin, and N. F. Starodub, Chemiluminescence fiber optic immunosensor for detecting
49.
50.
51.
52.
53.
54.
9
antibodies to the influenza virus. Ukrainskii Biokhimichnii Zhurnal, 1991, 63(4), 99–103. P. R. Coulet, L. J. Blum, and S. M. Gautier, Luminescencebased fibre-optic probes. Sensors and Actuators BChemical, 1993, 11(1–3), 57–61. Z. Chen, D. L. Kaplan, H. Gao, J. Kumar, K. A. Marx, and S. K. Tripathy, Molecular assembly of multilayer enzyme: toward the development of a chemiluminescencebased fiber optic biosensor. Materials Science and Engineering C, 1996, 4(3), 155–159. T. Konry A. Novoa, Y. Shemer-Avni, N. Hanuka, S. Cosnier, A. Lepellec, and R. S. Marks, Optical fiber immunosensor based on a poly(pyrrole-benzophenone) film for the detection of antibodies to viral antigen. Analytical Chemistry, 2005, 77(6), 1771–1779. A. Petrosova, T. Konry, S. Cosnier, I. Trakht, J. Lutwama, E. Rwaguma, A. Chepurnov, E. Muhlberger, L. Lobel, and R. S. Marks, Development of a highly sensitive, field operable biosensor for serological studies of Ebola virus in central Africa. Sensors and Actuators B: Chemical, 2007, 122, 578–586. O. Salama, S. Herrmann, A. Tziknovsky, B. Piura, M. Meirovich, I. Trakht, B. Reed, L. I. Lobel, and R. S. Marks, Chemiluminescent optical fiber immunosensor for detection of autoantibodies to ovarian and breast cancerassociated antigens. Biosensors and Bioelectronics, 2007, 22, 1508–1516. S. Szunerits and D. R. Walt, The use of optical fiber bundles combined with electrochemistry for chemical imaging. ChemPhysChem, 2003, 4(2), 186–192.
29 Bioluminescent Whole-Cell Optical Fiber Sensors Boris Polyak1 and Robert S. Marks2 1
Department of Cardiology Research, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA and 2 Department of Biotechnology Engineering and National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
1 INTRODUCTION
In parallel to the continuous development of increasingly more sophisticated physical and chemical analytical technologies for the detection of environmental pollutants, there is also need for bioassays which report not only on the presence of a chemical but also on its bioavailability and its putative biological effects. As a partial fulfillment of that need, there has been a rapid development of biosensors based on genetically engineered bacteria. Such microorganisms typically combine a promoter operator, which acts as the sensing element, with a reporter gene(s) coding for easily detectable proteins. These sensors have the ability to detect global parameters such as stress conditions, toxicity, or DNA damaging agents, as well as specific organic and inorganic compounds. The first bacterial assays were based either on auxotroph bacteria to histidine (Salmonella typhimurium in the Ames test1 ) or “dark” mutants of natural bacteria (Vibrio fischeri in the bioluminescence test for genotoxic compounds (BLT) test or Photobacterium leioghnati in Mutatox 2 ), where mutagenicity was measured either as the rate of reversion of His− to His+ mutants capable to grow on histidine-deficient medium in the Ames test or as the rate in
restoring luminescence (in BLT and Mutatox tests). Later, a Microtox test3,4 was developed, in which short-term effects on light production of the luminescent bacterium Photobacterium phosphoreum serve to estimate the acute toxicity of the studied sample. In recent years, other microbial tests were commercialized such as, SOS chromotest (SOS-colorimetric Escherichia coli test harboring the sfiA::lacZ fusion5,6 ), Umu test (SOS-colorimetric S. typhimurium test harboring the umuC::lacZ fusion7 ), and Vitotox (SOSbioluminescence S. typhimurium test harboring the Rec-N::luxCDABE fusion for genotoxicity and the Pr1::luxCDABE fusion for cytotoxicity8,9 ) that provides detection within 3–4 h. All the aforementioned methods use the test bacteria in a liquid suspension. This requires laboratory preparation of fresh bacterial suspensions for each test and some of the assays require complex pretest procedures. In addition, these methods are not easily amenable to field measurements. The present chapter will focus on approaches to overcome some limitations of bacterial sensors in suspension. More specifically, we will discuss the preparation, performance, and storage ability of the so-called “built-in” or “self-contained” optrodes for a one-step-assay, in which the reporter cells are an integral part of the disposable fiber, and
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
measurements will not require additional reagents. In order to be an integral and storable part of an operational biosensor, the bacterial cells, which will sense the presence of the target compound and emit the required signal, will need to be immobilized. Immobilization not only helps in forming the required close proximity between the biomaterial and the transducer but also helps in stabilizing it for reuse. The biological material has been immobilized directly on the transducer or as in most cases, in membranes, which can subsequently be mounted on the transducer. Biomaterials can be immobilized either through adsorption, entrapment, covalent binding, cross-linking, or a combination of all these techniques.10,11 To construct bioluminescent whole-cell optical fiber–based sensors, immobilization of reporter bacteria was achieved as reported in literature by three different approaches: (i) physical adsorption of alginates as films containing the reporter cells onto the tip end of optical fibers,12–16 (ii) the incorporation of reporter cells into microspheres of biotin modified alginate followed by their attachment to avidin-coated optical fibers,17 and (iii) antibody-based immobilization of bioluminescent bacterial sensor cells.18 2 DESCRIPTION OF BACTERIAL STRAINS USED IN CONSTRUCTION OF OPTRODES
E. coli strains used in the construction of the optical fiber–based sensors mostly contain a multicopy plasmid in which a different gene promoter was fused to the V . fischeri or Photorhabdus luminescence lux genes. Construction of different plasmids has been described in detail in the past in their respective references (Table 1). The
mechanisms of action of reporter bacteria are discussed elsewhere in this handbook. 3 PHYSICAL ADSORPTION OF ALGINATE FILM LAYERS ON OPTICAL FIBER TIP
As a first approach, calcium alginate was used to immobilize reporter cells onto optical fibers12,13,26 by means of physical adsorption. Using a natural polymer, bioencapsulation of cells enabled the concentration of bioluminescent cells at the end face region of an optical fiber, thus creating a highly localized density at the measurement site. The confinement to a small volume by physical adsorption or as in subsequent cases (microspheres and antibodies approaches) by covalent bonding adjacent to the optical fiber allows a higher coupling of the pollutant-induced light into the optical waveguide. An optimal concentration of cells may be specified if one learns to control their multiplication within the matrix. In addition, the procedure of producing gels from alginates is simple, involving nonhazardous chemicals. The formed gels are translucent, provide a hydrated environment, and are biocompatible with biological organisms. Also, the highly polar properties of alginates enable very good physical adsorption on the polar surface of the optical fibers. In this physical adsorption approach, optrodes were prepared in the following method: reporter cells mixed 1 : 1 with a 2% (w/v) low viscosity sodium alginate solution. The 1-cm optical fiber tip was first exposed (for a few seconds) to the bacterial alginate suspension, and then dipped (for a few seconds) into a sterile 0.5 M calcium chloride solution, thus entrapping the bacteria onto the
Table 1. Bioluminescent bacterial strains used in construction of optical fiber based biosensors (optrodes)
Strain
Plasmid/host
TV 1061 DPD2794 DPD1718 DPD2511 DPD2543 DPD2191 MC1061
pgrpElux5 /RFM443 precAlux6 /RFM443 lacZ::recA::luxCDABE/DPD1692 (a) pkatGlux2 /RFM443 pfabAlux6 /DE112 pmicFlux1 /GC4468 pmerRluxCDABE/ MC1061
Origin of lux genes Vf Vf Pl Vf Vf Vf Pl
Stress
Inducer used in this study
Protein folding DNA damage DNA damage Oxidative Fatty Acid synthesis Superoxide Heavy metals
Ethanol NA NA, MMC H2 O 2 Phenol MV Hg, Cd
Vf : Vibrio fischeri ; Pl: Photorhabdus luminescence; NA: nalidixic acid; MMC: mitomycin C; MV: methyl viologen. (a) Chromosomal integration.
References 19 20 21 22 23 24 25
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS
fiber within a hardened calcium alginate matrix. Repeating these steps thickened the adlayer, thus increasing the number of bacterial sensor cells attached to the optical fiber transducer.12,13 The polymer/bacteria adlayers with the thickness of 80–100 µm are shown in Figure 1. To allow a high-throughput mode preparation and measurement of the optrodes, two devices were developed. The first is a multiple fiber preparation device (Figure 2a–d), which consists of a matrix holder for 121 fibers that can move up and down along the z axis. Solutions with an alginate/bacteria mixture and cross linker (CaCl2 ) move in the perpendicular direction (Y). Alternate dipping of all 121 fibers into the bacterial/alginate and cross linker solutions facilitates the creation of polymer layers containing bacteria on the tips of optical fibers. After probe preparation, the matrix holder with its 121 fibers is inserted into the 121-position rack with 121 Eppendorf tubes containing the solutions to be tested (Figure 2c and d). The second device is an optical fiber–based luminometer for the simultaneous reading of 121 fiber probes (Figure 2e and f). Optrodes prepared by this method were optimized in respect to various system parameters as: number of adlayers (a six-adlayer probe), an optimal fiber core diameter (270 µm), incubation temperature (37 ◦ C) and a reporter cell density (1.5–3.0 × 107 cells/probe). Optimized optrodes tested with a range of mitomycin C (a model genotoxic compound) concentrations from 0 to 6400 µg l−1 .
(a)
(b) 100 µm
Figure 1. Micrograph of probe adlayers set onto the optical fiber core. (a) The fiber-probe interface. (b) The polymer layers with the approximate thickness at around 80–100 µm. [Reprinted from Water Science & Technology, 42(1–2), 305–311, with permission from the copyright holders, IWA.]
3
Light-kinetic profiles of these responses show that following a 30 min lag phase a clear dose-dependent induction may be observed (Figure 3).13
4 BLIND CONTROL TESTS OF DEFINED CHEMICALS AND ENVIRONMENTAL SAMPLES
Since calcium alginate is sensitive to chelator agents (e.g., citrate, ethylenediaminetetraacetic acid (EDTA), phosphates, etc.), the matrix could undergo degradation. This issue can become sensitive with the testing of real environmental samples. Therefore, one may need to make sure that there will always be sufficient calcium during measurement in order to prevent the calcium alginate matrix from dissolving. Polyak and coworkers participated in blind controlled studies in May 2000 in Mol, Belgium (TECHNOTOX)27 and in September 2002 in Corvallis, Oregon, US (EILATOX), where real-life samples were measured with the optrodes described herein, and there was no need to add any extra calcium ions.14 In these studies, a field-operable fiber-optic detector device enabled the measurement of 22 fibers measured one at a time (Figure 4). At the TECHNOTOX technical workshop, our technology showed a high degree of toxicity for samples containing well-known genotoxic compound N -Methyl-N -nitro-N -nitrosoguanidine (MNNG) and the intermediate-low degree of toxicity for samples containing 4-nitroquinoline-N -oxide (4NQO). The toxicity of 2-aminoanthracene (2-AA) could not be determined without the use of a metabolic activator. Determination of environmental samples was consistent with the expected results. Results at the EILATOX technical workshop showed that out of 14 toxic samples tested, nonimmobilized bacteria correctly detected 9 samples and the immobilized bacteria (optrodes) correctly detected 7 toxic substances, leaving 5 and 7 toxic samples undetected, respectively. All three nontoxic control samples were correctly identified as such. Substances such as parachlorophenol, MNNG, paraquat, sodium cyanide, and chlordimeform caused an induction of stress promoters, with variations in the number of induced promoters and the strength of the induction. For example, while parachlorophenol and MNNG induced many of
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Z Y (a)
(b)
(c)
(d)
(e)
(f)
Figure 2. The device for preparation of large number of optical fiber sensors in one batch. One hundred and twenty-one fibers can be prepared simultaneously within a few minutes: (a–d) are different steps in optrode preparation, (e and f) are front and side views of the high-throughput optical fiber luminometer.
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS
Photon counts/107 cell
6000
(µg l−1) 0 10 25 50 100 200 400 800 1,600 3,200 6,400
5000 4000 3000 2000 1000 0 0
50 100 150 200 250 300 350 400 Time (min)
Figure 3. Light kinetics at different analyte (mitomycin C) concentrations of an optimized optrode probe. These involve various parameters such as temperature (37 ◦ C), 6 calcium alginate adlayers, 1.5–3.0 × 107 cells/probe, and 270-µm optical fiber core diameter. [Reprinted from Sens. Actuators, B B74, 18–26. B. Polyak, et al., ‘R.S. Bioluminescent whole cell optical fiber sensor to genotoxicants: system optimization.’ Copyright (2001), with permission from Elsevier.]
Figure 4. Field-operable photodetector device. [K. Hakkila, et al. ‘Detection of bioavailable heavy metals in EILATox-Oregon samples using whole-cell luminescent bacterial sensors in suspension or immobilized onto fibre-optic tips.’ Journal of Applied Toxicology 24, 333–342. Copyright (2004). John Wiley & Sons Limited. Reproduced with permission.]
the tested promoters, substances such as paraquat, phosdrin, and sodium cyanide induced a smaller number, suggesting more specific cellular effects. Other toxic chemicals (sodium arsenite, mercuric chloride, and metham sodium) did not induce any
5
of the tested stress promoters but exerted measurable general cytotoxic “lights off” effects on background luminescence. Of the undetected substances, it is possible that the Ni and selenite ions were neutralized by sequestration in the organics-rich test medium Luria-Bertrani (LB). The inability to detect colchicine and trimethylolpropane phosphate, however, indicates an insufficient detection range of the bacterial panel, and may point at a more fundamental problem of the detection capabilities of the experimental system. A quantitative representation of the performance of the bacterial sensor strains is given in Table 2, which includes the calculated ranges of threshold toxicity values for all the tested promoters in terms of effective concentration (EC)50 or EC200 , along with rat oral LD50 values. EC200 and EC50 values represent the effective sample concentrations causing a two-fold increase or decrease in luminescence, respectively, relative to untreated controls. These values were calculated as previously described.21,28 An LD50 value is the amount of a solid or liquid material that will kill 50% of the test animals. Lacking appropriate human toxicological data, the latter may be used as a comparative reference for assay sensitivity. They may also be used as general, rough indicative estimates of the possible effective concentrations for human exposure based on oral exposure of average daily water consumption. As may be observed from the data in Table 2, the detection limits for different chemicals varied significantly in both types of assays. The bacterial strains exhibited a relatively high sensitivity for MNNG, parachlorophenol, paraquat, and mercuric chloride (0.01–5.0 mg l−1 ), while for others (phosdrin, sodium arsenite, metham sodium, and sodium cyanide) the detection thresholds were higher. In general, it appears that substances that induced stress promoters were detected at lower concentrations than those that were detected by their general toxic effects. The overall sensitivity of immobilized bacteria (optrodes), as judged by the EC values in Table 2, is generally similar to that of suspensions of bacteria. Differences in performance may be attributed to the different physiological conditions of the immobilized or the nonimmobilized cells, or to the number of cells present per reaction assay. In the case of the recA::lux CDABE strains, the
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Table 2. Comparative sensitivity of bacterial constructs to toxic substances comprising the unknown water samples
EC (mg l−1 )(a) Substance Chlordimeform Phosdrin Mercuric chloride Sodium arsenite Metham sodium Sodium cyanide Parachlorophenol Paraquat MNNG
Liquid culture
Immobilized bacteria (optrode)
LD50 (mg kg−1 )(b)
5–30 10–120 1–9 5–30 4–40 2–40 0.015–1.65 2.5–8 0.01–0.5
— 40 0.15 10 10 20 30 — 0.31
340 3.7–6.1 18 41 450 6.4 500 110–150 90
[Pedahzur, et al. ‘Water toxicity detection by a panel of stress-responsive luminescent bacteria.’ Journal of Applied Toxicology 24, 343–348. (2004) John Wiley & Sons Ltd. Reproduced with permission.] (a) Effective concentration (EC200 or EC50 ) values. (b) LD50 : oral exposure for rats (manufacturers’ data).
differences can also be related to the source of the lux reporter genes (V. fischeri or Photorhabdus luminescens) or to the presence of a single copy of the recA::lux fusion in the strain (DPD1718) used in the optic fiber configuration.
5 OPTRODE PREPARATION USING A MICROSPHERE METHOD
The general major limitation of entrapment techniques is the additional diffusional barrier offered by the entrapment materials. To minimize this limitation and also to achieve other advantages, the entrapment of bioreporter cells into calcium alginate microspheres with small dimensions (700–900 µm) and with their subsequent conjugation onto the optical fiber surface was successfully undertaken.17 Conjugation of the microspheres to the optical fibers was achieved using a very wellknown avidin–biotin affinity system (Figure 5). The avidin–biotin interaction is an extremely specific and strong noncovalent binding method (association constants, Ka , of the glycoprotein avidin for biotin in solution or immobilized on the surface are ∼1015 or 1010 mol−1 l, respectively).29 The bond between biotin and avidin is established very rapidly and, once formed, is essentially undisturbed by extreme pH values or exposure to organic solvents or other denaturating agents.30 For the construction of this sensor configuration, there was a need to first modify alginate by biotin.
Biotin was covalently coupled with alginate in an aqueous-phase reaction by means of carbodiimidemediated activation chemistry (Figure 6) and the biotin–alginate conjugate was then fully characterized. The use of biotin–alginate conjugate enabled to entrap reporter cells in a spherical geometry and to couple those microspheres onto the optical transducer surface modified by avidin/streptavidin. The covalent attachment of avidin/streptavidin to the silica surface was then carried out by means of previously described silanization methods.31,32 The microsphere-based method has a variety of advantages over the physical adsorption-based layered configuration: well-defined geometrical shape and uniformity of the beads; simplicity of preparation; improvement of diffusion properties (due to greater porosity caused by the reduction (13%) of cross-linkable COOH groups as a result of their chemical modification to link biotin); ability to store beads separately from the optical fibers; and, finally, the possibility of placing a mixture of microspheres containing different biospecificities onto the same fiber, thus facilitating the creation of nonspecific probes with a triggering system sensitive to a wider range of toxicants. Biotinylated alginate microspheres with previously entrapped reporter cells were conjugated to the optic fiber by different configurations. As shown in Figure 7(a), it was possible to attach a lone bead to the end face of the fiber or, alternatively, to coat the fiber with a number of microspheres (see Figure 7b). Conjugation of beads was achieved using either avidin or streptavidin. However, the use of streptavidin, the
7
Fiber surface
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS
(Ka) Association constant + Biotin
Avidin/streptavidin
1015 M−1 (in solution) 1010 M−1 (immobilized)
Avidin–biotin complex
Figure 5. Hypothetical approach for conjugation of biotinylated alginate microspheres to the (strep) avidin-coated optical fibers (not to scale).
nonglycosylated and hydrophobic bacterial analog of the egg-white glycoprotein avidin, produced more satisfactory results in the conjugation process. Figure 8 shows the bioluminescent response of E. coli strain DPD1718 entrapped within biotin–alginate microspheres (lone bead configuration) that had been conjugated to the optical fibers and exposed to various concentrations of mitomycin C. An approximately 1-h lag phase was followed by a dose-dependent increase in bioluminescence. A calibration curve obtained at 180 min of incubation with the analyte showed very good linear behavior in the range of mitomycin C concentrations from 800–100 µg l−1 . 6 COMPARISON OF REPORTER CELL PERFORMANCE IN BIOTIN – ALGINATE AND THE ORIGINAL ALGINATE MATRIX
Figure 9 shows differences between biotin–alginate and original alginate matrices, when luminescence of entrapped cells was measured. In all three
tested inducer concentrations, a better response was observed for the biotin–alginate immobilization matrix. This result suggests that probably biotin–alginate conjugate provides the sensor with better diffusion properties due to the larger pores in biotin–alginate hydrogel matrix. Scanning electron microscopy (SEM) studies of both biotin–alginate and the original matrices, shown in Figure 10, indicate that the biotin–alginate matrix has a more developed surface morphology than the original alginate, which shows a smoother surface. This could probably indirectly suggest that biotin–alginate has a more porous structure, compared to the original alginate.
7 ANTIBODY-BASED IMMOBILIZATION OF BIOLUMINESCENT BACTERIAL SENSOR CELLS
An alternative method to the natural polymer entrapment is the antibody-based conjugation of the reporter cells to optical fibers, glass slides, and gold-coated glass slides.18 The technology for
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS (H3C)2N(H2C)3HN N
O
C2H5
O OOC O
HO O OOC
C
OH O
EDAC
HO
O OH
HO O OOC
O
Alginate
O O OH
OH O
HO
O
O-Acylisourea intermediate
NHSS SO3 O
O
N
O O C OH O O HO HO O O O OOC OH Alginate-NHSS ester stabilization
S
H N
NH
3 h, RT
H2N N H
O
O
Biotin hydrazide
S
H N
NH
HN O HO O OOC
O O OH
HO
N H
OH O O
O
O Biotin alginate
Figure 6. Biotin coupling to alginate via carbodiimide chemistry. NHSS: N -hydroxysulfosuccinimide; EDAC: 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide; RT: room temperature.
bonding antibodies on different flat or porous substrates is very versatile and well developed and it is often used as a first step in the construction of complex sensing elements. The successful combination of this generic approach with reporting microorganisms could pave the way for their incorporation on or in virtually any substrate. The advantages of antibody-based methods lie in the fact that conjugation of reporter cells occurs in very close proximity to the transducer,
without having any diffusion barriers, except for the cell wall. This condition offers a faster time response for the biosensor, which allows the use of this sensor configuration in a continuous mode of operation. However, an antibody-based approach may have also a number of drawbacks: (i) the exposed reporter cells are less protected from the drag stress in a flow system which may lead to the detachment of the cell from the sensor surface, (ii) leaching of cells may enhance contamination of media, important when
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS
9
(b)
(a)
Figure 7. Experimental conjugation of biotin–alginate microspheres to an optical fiber via avidin-biotin affinity interactions: (a) attachment of a lone bead to the end face of the fiber, (b) coating of the fiber with a number of microspheres. Diameter of the optical fibers is in both cases 1000 µm. [Reprinted with permission from B. Polyak, S. Geresh, and R.S. Marks, Synthesis and characterization of a biotin-alginate conjugate and its application in a biosensor construction. Biomacromolecules 5, 389–396. Copyright (2004) American Chemical Society.]
7000 Photon (counts/s at 180 min)
7000 6000
Photon (counts/s)
5000
4000
6000 5000 4000 3000 2000 1000 0
3000
0
200 400 600 Mitomycin C (µg l−1)
800
2000
1000
0 0
20
40
60
80
100
120
140
160
180
200
Time (min)
Figure 8. Bioluminescence response curves obtained from reporter cells encapsulated within biotin–alginate beads and conjugated to the optical fiber surface using the streptavidin/biotin affinity interaction. The main figure shows the response at a mitomycin C concentration range of 800–100 µg l−1 ; the inset shows the linear range of the calibration curve based on the light signal measured at 180 min of incubation with the mitomycin C. ()—800 µg l−1 , (•)—400 µg l−1 , ()—200 µg l−1 , ()—100 µg l−1 , ()—blank (water). [Reprinted with permission from B. Polyak, S. Geresh, and R.S. Marks, Synthesis and characterization of a biotin-alginate conjugate and its application in a biosensor construction. Biomacromolecules 5, 389–396. Copyright (2004) American Chemical Society.]
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 1.8
Biotin alginate (BA) 3.2 mg l−1 Alginate (A) 3.2 mg l−1
Luminescence (rlu)
1.5 1.2
(BA) 0.8 mg l−1
0.9
(A) 0.8 mg l−1
0.6 (BA) 0.2 mg l−1 (A) 0.2 mg l−1 A control
0.3
BA control
0 0
50
100
150 200 Time (min)
250
300
Figure 9. Comparison of reporter cells performance in biotin–alginate and original alginate matrix. Biotin–alginate bead immobilized cells and original alginate bead immobilized cells were exposed to a three mitomycin C concentrations. rlu: relative luminescence units.
genetically engineered organisms are used, and (iii) lack of homogeneous surface coverage by cells that stems from sometimes inefficient surface functionalization procedures. In addition, their multiplication may not be confined, but released into the environment. One of the most important advantages of solid sensing elements compared to suspended bacterial cultures is their compatibility with continuous monitoring schemes. Figure 11(a) and (b) demonstrates the ability to monitor toxicity (heat shock) stress under continuous flow conditions. Figure 11(a) presents the response of a coated optical fiber that was exposed to 2% (v/v) alcohol feed at the times indicated by the upward arrows in the figure. The downward arrows indicate a switch to alcohol-free feed. The figure demonstrates that the sensor can sense heat shock evolution (see Figure 11a) continuously.18
Biotin alginate
Original alginate
Figure 10. Scanning electron microscopy (SEM) studies of hydrogel surface of biotin–alginate and original alginate matrices.
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS 8
Luminescence (rlu) × 10−3
4
0 0
10
(a)
20
30
Time (min)
5
2.5
also demonstrated their ability for reuse.18 However, the polymer-based biosensors, because of their protective polymer environment, could be frozen using glycerol as a cryoprotectant and therefore stored for much longer time periods than sensors stored at 4 ◦ C. Freezing the polymer-based sensors at −80 ◦ C utilizing glycerol at the concentration of 20% (v/v) offers a very good shelf life for the sensors, keeping about 75% of the initial activity for at least half a year.33 In addition, the fine geometrical shape of the probes was preserved in glycerol without any deformation, thus allowing reconstitution of the sensor in its original form.
9 COMPARISON BETWEEN BIOLUMINESCENCE AND FLUORESCENCE REPORTER FUNCTIONS IN GENETICALLY MODIFIED BACTERIAL SENSORS
0 0 (b)
11
10
20
30
Time (min)
Figure 11. (a) Luminescence time course of TV1061 modified optical fiber sensor under continuous flow of LB medium (flow rate, 1 ml min−1 ). (b) Luminescence time course of a glass-based sensor with optical fiber signal transduction under continuous flow of LB medium (flow rate, 1 ml min−1 ). Upward arrows indicate the introduction of 2% (v/v) alcohol in LB medium and downward arrows indicate pure LB medium feed. [Reprinted from Talanta 55, 1029–1038. J.R. Premkumar, et al. ‘Antibody-based immobilization of bioluminescent bacterial sensor cells.’ Copyright (2001), with permission from Elsevier.]
8 BACTERIAL VIABILITY IN ANTIBODY-BASED ATTACHMENT VERSUS ALGINATE ENTRAPMENT
Both polymer entrapment and antibody-based methods showed good viability of the immobilized reporter cells. Preservation of calcium alginate immobilized sensors in solutions demonstrated that these systems could be stored in LB medium at 4 ◦ C keeping their sensor functionality up to 85–90% relative to the fresh sensor during the first month, up to 75–80% during the second month, and up to 50–60% during the next two months.33 The antibody-based sensors showed not only excellent preservation of their functionality up to 4–5 months under the same conditions but
Recent studies attempted to compare the performances of different reporter systems (luxCDABE, lacZ, and gfp).34 However, in these studies the growth conditions or the genetic constructs were not identical, which makes direct comparison of the reporter impossible. Later reports compared bioluminescent and fluorescent reporter systems controlled under the same promoter element and also using a consistent growth conditions. Hakkila et al. compared the performance of two bioluminescence reporter genes, the firefly luciferase (Photinus pyralis lucFF ) and the bacterial luciferase operon (P. luminescence luxCDABE ), and two fluorescence proteins (GFP) green fluorescent protein (Aequora victoria gfp) and (RFP) red fluorescent protein (Discosoma sp. dsred ) in identical constructs controlled under mercury- (mer) and arsenite- (ars) responsive regulatory units.25 Another group compared three fluorescent reporters: GFP (EGFP-enhanced green fluorescent protein mutant and GFPuv a blue excitation shifted mutant with λex : 395 nm as opposed to common GFP excitation at λex : 488 nm), DsRed (Discosoma sp. dsred ) and one bioluminescent reporter (V. fischeri luxCDABE ) under the control either SOS (recA) or heat shock (grpE) promoters.35 Both groups drew similar conclusions that bacterial bioluminescence has two major advantages for gene activation monitoring: faster response times and higher short-term sensitivities.
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Both advantages stem from the catalytic nature of the enzymatic reporter, allowing a relatively small number of reporter molecules to generate a sufficiently strong signal. The main advantage of fluorescent sensing is reporter stability. Once induced, produced, and matured (folded), the fluorescent protein keeps accumulating and may be detected for many hours. In fact, fluorescent proteins such as GFP may be detected even after cell death. In contrast, bacterial bioluminescent activity is relatively short lived. For example, in the bacterial reporter system, five lux genes were used as a unified reporter: two of them (luxAB) code for the luciferase enzyme and three (luxCDE ) for other enzymes in charge of supplying the substrate for the luciferase, a long-chain aldehyde. The combined half-life of the overall activity is thus short. Another common limitation encountered when using fluorescence detection in a real samples analysis is that the matrix may contain compounds that autofluoresce or that can be exited at the wavelength of commonly employed fluorescent molecules. This causes an increase in background fluorescence, which in turn tends to compromise the detection limits of the system. To address this issue, an RFP reporter system (DsRed) was investigated in the same previously mentioned studies.25,35 In that work, Hakkila et al. reported that DsRed reporter showed even slower response than GFP. One possible reason for that evidence was attributed by the authors to the slow folding process of the DsRed protein. DsRed requires days at room temperature to reach maximal red fluorescence.36 Similarly, Sagi et al. reported that the plasmid-born recA::DsRed2 fusion was unstable, and unexplainable variations were observed between individual experiments.35 A different approach in using red fluorescence for reduction of the background fluorescence was published very recently.37 In these studies, the authors investigated the use of a reporter enzyme that produces fluorescent compounds, which can be exited at wavelengths that are not commonly encountered in compounds present in real samples. More specifically, a fusion of arsenite sensitive promoter (ars) and cobA gene was investigated for sensing purposes. The CobA gene codes for uroporphyrinogen III methyltransferase that converts the substrate uroporphyrinogen (urogen) III into two fluorescent compounds sirohydrochlorin
and trimethylpyrrocorphin. Urogen III is ubiquitous within the cell, however, because the cells use it for vitamin B12 and siroheme biosynthesis. This sensing system is limited by substrate availability. By supplementing the media with ALA (δ-aminolevulinic acid), a precursor of urogenIII, a more stable and reproducible response was obtained. Although this innovative approach has its own advantages in reducing the background fluorescence, it does not lead to the generation of the direct genetic fluorescence product and requires an external supplementation of the substrate precursor, which in combination will prolong the overall sensor response time. The choice of reporter for any application has, therefore, to be case-specific. Bioluminescence is more suitable for rapid and sensitive detection, possibly even in on-line configuration (e.g., using optical fiber probes), while fluorescent reporter proteins are advantageous for long exposures and cumulative signal detection. One potential means by which the advantages of both sensor types may be combined is a dual-function whole-cell sensor system, in which two (or more) cell types could be encapsulated in a solid matrix.35 The cells could represent either different sensing mechanisms (i.e., different target analyte) or different reporter systems, and potentially serve to monitor multiple parameters in a single device.
10 CONCLUDING REMARKS AND FUTURE PERSPECTIVES
Among microbiologists, the term biosensor or microbial biosensor is often used to describe only the responsive microbial organism. In biosensor literature, however, it is claimed that to be considered a true biosensor the biological entity needs to be integrated into an appropriate transducer-based hardware. Although the isolated bacterial strain might serve as an excellent reagent in the laboratory, to be taken outside its boundaries it needs to be incorporated into a device that will allow storage and maintenance of the live cells, access to the sample, and signal capture. In this chapter, we have surveyed new and original techniques that offer some potential solutions for the creation of hardware devices named microbial biosensors that can be used in the
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS
environmental field. We believe that such bioluminescent microbial optrode sensors can be prepared with different configurations and stored under appropriate conditions that would provide sufficient shelf life. The techniques of reporter cell immobilization on the end tip of optical fibers,12,13,17,18 entrapment at the bottom of microtiter plate wells,38 fixation in agar-gel membrane,39 encapsulation in solgel matrices,40 and random embedding into a highdensity microwell array41,42 followed by optical decoding contributed significantly to the field of biosensors and could serve as a fundamental basis for further development of such analytical devices. The new trend today in the biosensor’s field is miniaturization of these detection systems, placing them on chips. A chip-based system was developed by Simpson and coworkers, who used a complementary metal-oxide semiconductor (CMOS) imager for very low-level detection of the bioluminescent signal of a Pseudomonas fluorescens strain induced by naphthalene or salicylate.43 Their device, termed bioluminescent bioreporter integrated circuit (BIBIC ), is probably the first integrated whole-cell biochip. Another approach in whole-cell arrays was recently reported by Van Dyk and coworkers44 who described the LuxArray: a collection of 689 nonredundant functional promoter fusions to P. luminescens luxCDABE in live E. coli strains, representing close to 30% of the predicted transcriptional units in this bacterium. High-density printing of the reporter strains to membranes on agar plates was used for simultaneous assays of gene expression with impressive results. Another pioneering approach toward the production of a whole-cell lab-on-chip integrated system was demonstrated by Rabner and coworkers.45 Their sensor relies on a disposable plastic biochip prepared with a 4 × 4 micro-lab (mLab) chambers array of bioluminescent E. coli reporter cells that responds to a predetermined class of chemical agents and microfluidic channels for liquids translocation. The device integrates an electro-optics for signal acquisition with motorized readout calibration accessories, hydropneumatics modules for water sample translocation into biochip mLabs and electronics for overall control and communication with the host computer. This prototype has a demonstrated sensitivity for broad classes of water-borne toxic
13
chemicals including naladixic acid (a model genotoxic agent), botulinum toxin, and acetylcholine esterase inhibitors. A decade of genetically engineered microorganisms for the detection of either toxic effects or of specific classes of chemicals has set the ground for a new and exciting era. The potential incorporation of such cells into numerous array formats on biochips, optic fibers, or other suitable surfaces, will allow a mode of bioanalysis previously considered impossible. A positive response of a live-cell optic fiber or chip array will indicate the existence of the probed effect, the response pattern will indicate the identity of the chemicals in the sample, and the intensity of the response will quantify their concentrations. In other configurations, such arrays can serve for high-throughput screening of chemicals and drugs, simultaneously monitoring both for desired and negative effects.
REFERENCES 1. B. N. Ames, F. D. Lee, and W. E. Durston, Improved bacterial test system for the detection and classification of mutagens and carcinogens. Proceedings of the National Academy of Sciences of the United States of America, 1973, 70, 782–786. 2. K. K. Kwan, B. J. Dutka, S. S. Rao, and D. Liu, Mutatox test: a new test for monitoring environmental genotoxic agents. Environmental Pollution (Oxford, United Kingdom), 1990, 65, 323–332. 3. A. A. Qureshi, A. A. Bulich, and D. L. Isenberg, Microtox toxicity test systems—where they stand today, Microscale Testing in Aquatic Toxicology, CRC, Boca Raton, FL, Chapter 13 1998, pp. 185–199. 4. A. A. Bulich, Utility of the Microtox Luminescent Bacterial Assay for the Rapid Assessment of Aquatic Pollution, 2nd Interagency Workshop on In-Situ WaterQuality Sensing: Biological Sensors, NTIS, Springfield, VA. 1980, pp. 173–184. 5. P. Quillardet and M. Hofnung, The SOS chromotest: A review. Mutation Research, 1993, 297, 235–279. 6. P. Quillardet, O. Huisman, R. D’Ari, and M. Hofnung, SOS chromotest, a direct assay of induction of an SOS function in Escherichia coli K-12 to measure genotoxicity. Proceedings of the National Academy of Sciences of the United States of America, 1982, 79, 5971–5975. 7. Y. Oda, S. Nakamura, I. Oki, T. Kato, and H. Shinagawa, Evaluation of the new system (umu-test) for the detection of environmental mutagens and carcinogens. Mutation Research, 1985, 147, 219–229. 8. L. Verschaeve, J. Van Gompel, L. Thilemans, L. Regniers, P. Vanparys, and D. Van der Lelie, VITOTOX bacterial genotoxicity and toxicity test for the rapid screening of chemicals. Environmental and Molecular Mutagenesis, 1999, 33, 240–248.
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
9. D. van der Lelie, L. Regniers, B. Borremans, A. Provoost, and L. Verschaeve, The VITOTOX test, an SOS bioluminescence Salmonella typhimurium test to measure genotoxicity kinetics. Mutation Research, 1997, 389, 279–290. 10. G. F. Bickerstaff, Immobilization of enzymes and cells: some practical considerations. Methods in Biotechnology, 1997, 1, 1–11. 11. S. F. D’Souza, Microbial biosensors. Biosensors and Bioelectronics, 2001, 16, 337–353. 12. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Optical fiber bioluminescent whole-cell microbial biosensors to genotoxicants. Water Science and Technology, 2000, 42, 305–311. 13. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Bioluminescent whole cell optical fiber sensor to genotoxicants: system optimization. Sensors and Actuators, B, 2001, B74, 18–26. 14. R. Pedahzur, B. Polyak, R. S. Marks, and S. Belkin, Water toxicity detection by a panel of stress-responsive luminescent bacteria. Journal of Applied Toxicology, 2004, 24, 343–348. 15. K. Hakkila, J. Lappalainen, and M. Virta, Toxicity detection from EILATox-Oregon workshop samples by using kinetic photobacteria measurement: The Flash method. Journal of Applied Toxicology, 2004, 24, 349–353. 16. T. Fine, P. Leskinen, T. Isobe, H. Shiraishi, M. Morita, R. S. Marks, and M. Virta, Luminescent yeast cells entrapped in hydrogels for estrogenic endocrine disrupting chemical biodetection. Biosensors and Bioelectronics, 2005, 21, 2263–2269. 17. B. Polyak, S. Geresh, and R. S. Marks, Synthesis and characterization of a biotin-alginate conjugate and its application in a biosensor construction. Biomacromolecules, 2004, 5, 389–396. 18. J. R. Premkumar, O. Lev, R. S. Marks, B. Polyak, R. Rosen, and S. Belkin, Antibody-based immobilization of bioluminescent bacterial sensor cells. Talanta, 2001, 55, 1029–1038. 19. T. K. Van Dyk, W. R. Majarian, K. B. Konstantinov, R. M. Young, P. S. Dhurjati, and R. A. LaRossa, Rapid and sensitive pollutant detection by induction of heat shock gene-bioluminescence gene fusions. Applied and Environmental Microbiology, 1994, 60, 1414–1420. 20. A. C. Vollmer, S. Belkin, D. R. Smulski, T. K. Van Dyk, and R. A. LaRossa, Detection of DNA damage by use of Escherichia coli carrying recA ::lux, uvrA ::lux, or alkA ::lux reporter plasmids. Applied and Environmental Microbiology, 1997, 63, 2566–2571. 21. Y. Davidov, R. Rozen, D. R. Smulski, T. K. Van Dyk, A. C. Vollmer, D. A. Elsemore, R. A. LaRossa, and S. Belkin, Improved bacterial SOS promoter::lux fusions for genotoxicity detection. Mutation Research, 2000, 466, 97–107. 22. S. Belkin, D. R. Smulski, A. C. Vollmer, T. K. Van Dyk, and R. A. LaRossa, Oxidative stress detection with Escherichia coli harboring a katG’::lux fusion. Applied and Environmental Microbiology, 1996, 62, 2252–2256. 23. O. Bechor, D. R. Smulski, T. K. Van Dyk, R. A. LaRossa, and S. Belkin, Recombinant microorganisms as environmental biosensors: pollutants detection by Escherichia coli bearing fabA ::lux fusions. Journal of Biotechnology, 2002, 94, 125–132.
24. J. T. Oh, Y. Cajal, E. M. Skowronska, S. Belkin, J. Chen, T. K. Van Dyk, M. Sasser, and M. K. Jain, Cationic peptide antimicrobials induce selective transcription of micF and osmY in Escherichia coli. Biochimica et Biophysica Acta, 2000, 1463, 43–54. 25. K. Hakkila, M. Maksimow, M. Karp, and M. Virta, Reporter Genes lucFF, luxCDABE, gfp, and dsred Have Different Characteristics in Whole-Cell Bacterial Sensors. Analytical Biochemistry, 2002, 301, 235–242. 26. T. Matsunaga, H. Sudo, H. Takemasa, Y. Wachi, and N. Nakamura, Sulfated extracellular polysaccharide production by the halophilic cyanobacterium Aphanocapsa halophyta immobilized on light-diffusing optical fibers. Applied Microbiology and Biotechnology, 1996, 45, 24–27. 27. B. Polyak and R. S. Marks, Fiber optic RecA lux sensor, TECHNOTOX Technical Workshop on Genotoxicity Biosensing, 2000, http://www.vito.be/english/environment/ environmentaltox5.htm. 28. S. Belkin, D. R. Smulski, S. Dadon, A. C. Vollmer, T. K. Van Dyk, and R. A. Larossa, Panel of stress-responsive luminous bacteria for the detection of selected classes of toxicants. Water Research, 1997, 31, 3009–3016. 29. M. Wilchek and E. A. Bayer, The avidin-biotin complex in bioanalytical applications. Analytical Biochemistry, 1988, 171, 1–32. 30. N. M. Green, Avidin. Advances in Protein Chemistry, 1975, 29, 85–133. 31. K. Ernst-Cabrera and M. Wilchek, High-performance affinity chromatography. TRAC Trends in Analytical Chemistry (Personal Edition), 1988, 7, 58–63. 32. G. T. Hermanson, (ed), Bioconjugate Techniques, Academic Press, San Diego, CA, 1995, p. 786, 218. 33. B. Polyak, Development of Microbial Bioluminescent Optical Fiber Sensors to Detect Toxic Compounds. Ph.D. dissertation. Ben-Gurion University of the Negev, BeerSheva, Israel. 2006. 34. L. H. Hansen and S. J. Sorensen, Versatile biosensor vectors for detection and quantification of mercury. FEMS Microbiology Letters, 2000, 193, 123–127. 35. E. Sagi, N. Hever, R. Rosen, A. J. Bartolome, J. Rajan Premkumar, R. Ulber, O. Lev, T. Scheper, and S. Belkin, Fluorescence and bioluminescence reporter functions in genetically modified bacterial sensor strains. Sensors and Actuators, B: Chemical, 2003, B90, 2–8. 36. G. S. Baird, D. A. Zacharias, and R. Y. Tsien, Biochemistry, mutagenesis, and oligomerization of DsRed, a red fluorescent protein from coral. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97, 11984–11989. 37. J. Feliciano, Y. Liu, and S. Daunert, Novel reporter gene in a fluorescent-based whole cell sensing system. Biotechnology and Bioengineering, 2006, 93, 989–997. 38. F. Mbeunkui, C. Richaud, A. L. Etienne, R. D. Schmid, and T. T. Bachmann, Bioavailable nitrate detection in water by an immobilized luminescent cyanobacterial reporter strain. Applied Microbiology and Biotechnology, 2002, 60, 306–312. 39. Y. Sun, T. Zhou, J. Guo, and Y. Li, Dark variants of luminous bacteria whole cell bioluminescent optical fiber sensor to genotoxicants. Journal of Huazhong University of Science and Technology, Medical Sciences, 2004, 24, 507–509.
BIOLUMINESCENT WHOLE-CELL OPTICAL FIBER SENSORS 40. J. Rajan Premkumar, R. Rosen, S. Belkin, and O. Lev, Sol-gel luminescence biosensors: Encapsulation of recombinant E. coli reporters in thick silicate films. Analytica Chimica Acta, 2002, 462, 11–23. 41. I. Biran and D. R. Walt, Optical imaging fiber-based single live cell arrays: A high-density cell assay platform. Analytical Chemistry, 2002, 74, 3046–3054. 42. Y. Kuang, I. Biran, and D. R. Walt, Simultaneously Monitoring Gene Expression Kinetics and Genetic Noise in Single Cells by Optical Well Arrays. Analytical Chemistry, 2004, 76, 6282–6286. 43. E. K. Bolton, G. S. Sayler, D. E. Nivens, J. M. Rochelle, S. Ripp, and M. L. Simpson, Integrated CMOS
15
photodetectors and signal processing for very low-level chemical sensing with the bioluminescent bioreporter integrated circuit. Sensors and Actuators, B: Chemical, 2002, B85, 179–185. 44. T. K. Van Dyk, E. J. DeRose, and G. E. Gonye, LuxArray, a high-density, genomewide transcription analysis of Escherichia coli using bioluminescent reporter strains. Journal of Bacteriology, 2001, 183, 5496–5505. 45. A. Rabner, S. Belkin, R. Rozen, and Y. Shacham, Wholecell luminescence biosensor-based lab-on-chip integrated system for water toxicity analysis. Proceedings of the SPIE-The International Society for Optical Engineering, 2006, 6112, 611205/611201–611205/611210.
30 Phagocyte Luminescent Sensor Moni Magrisso1 and Robert S. Marks1,2 1
National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel and 2 Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
1 INNATE IMMUNE SYSTEM AND PHAGOCYTOSIS
The innate immune response represents a “first line” of defense, which uses a panoply of defense mechanisms that are triggered by infection to protect the host by destroying the invading microbes and neutralizing their virulence factors. In general, innate immunity is a nonspecific, inducible response to pathogens. It is designed to recognize a few highly conserved structures present in many different microorganisms. The structures recognized are called pathogen-associated molecular patterns and include lipopolysaccharide (LPS) from the gram-negative cell wall,22 peptidoglycan, lipoteichoic acids from the grampositive cell wall,46 the sugar mannose (common in microbial glycolipids and glycoproteins but rare in those of humans), bacterial DNA, N -formylmethionine found in bacterial proteins, double-stranded RNA from viruses,33 and glucans from fungal cell walls.32 Most body defense cells have pattern-recognition receptors35 for these common pathogen-associated molecular patterns and so there is an immediate response against the invading microorganism. Pathogen-associated molecular patterns can also be recognized by a series of soluble pattern-recognition receptors in the blood that function as opsonins and initiate the complement pathways. In all, the innate immune system is thought to recognize approximately 103
molecular patterns. The innate immune responses involve phagocytosis (neutrophils, monocytes, and macrophages), the release of inflammatory mediators (basophils, mast cells, and eosinophils), natural killer cells and molecules such as complement proteins, acute phase proteins, and cytokines. Different immune deficiency diseases (involving, e.g., immunoglobulins, complement, or T cells) may shorten life expectancy; however, a drastic decrease in the number of circulating phagocytes can result in death within days or weeks through intractable bacterial infections, against which antibiotics are of little avail. In such infections, the bacteria involved often are of a variety that normally would not be considered pathogenic. Thus the ultimate disposal of all infectious agents and other unwanted particles, which have been detected and processed with the help of other branches of the immune system, occurs through phagocytosis, so that phagocytosis represents an indispensable step in our immunological defense system.75
2 MECHANISMS, LOCALIZATION, AND FACTORS OF OXIDATIVE PHAGOCYTE ACTIVITY
Professional phagocytes are equipped with a large number of microbicidal systems, of which
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
one is the oxygen radical-generating NADPH oxidase. Thus, activation of neutrophil granulocytes, induced by particulate or soluble agonists, results in the production of various reactive oxygen metabolites, including superoxide anion, hydrogen peroxide, hypochlorous acid, and hydroxyl radical.7,60,62 It is generally accepted that the chemiluminescence (CL) reaction is dependent on the cellular metabolism of molecular oxygen. However, other factors also influence the CL which is measured, and results obtained with the technique cannot be correctly interpreted until the precise mechanism(s) responsible for the reaction have been established. A number of publications dealing with the mechanisms of light emission have shown that the CL reaction is dependent on myeloperoxidase (MPO), a protein located in the azurophilic granules of the cells. Furthermore, much of the CL activity may have an intracellular origin.20 Upon stimulation with both soluble and particulate matter, the granulocyte oxidative metabolism is activated resulting in a respiratory burst.38,55 The respiratory burst is accompanied by an activation of an NADPH oxidizing enzyme.62 This enzyme catalyzes the reduction of oxygen to superoxide anion, which is paralleled by the consumption of O2 . The superoxide anion is a short-lived metabolite due to its strong tendency to dismutate spontaneously, thereby generating hydrogen peroxide.59 Both superoxide and hydrogen peroxide have been proposed to directly participate in bacterial killing, but since the microbicidal effect of both is weak, the main task of these initial oxygen species is probably to participate in the generation of more reactive and toxic species such as hydroxyl radicals, hypochlorous acid, and singlet oxygen.59 The respiratory burst is also associated with the emission of light (generated from reactive species which generate luminol with a high energy state when they revert to the basal energy level), which can be amplified and detected as luminol-dependent chemiluminescence (LCL).2,1 The precise origin of the light seen in luminol-amplified CL is not known, but the requirement for reactive oxygen species is demonstrated by the absence of light emission in an anaerobic environment and the lack of CL from granulocytes isolated from patients suffering from chronic granulomatous disease (CGD). The disease is related to an absence of the respiratory burst and is associated with a defect
of the NADPH oxidase system followed by a failure to produce reactive oxygen species and CL. LCL of peripheral blood–derived phagocytes depends on both MPO activity and superoxide generation.23,28,37 Other suggestions are singlet oxygen involvement3 and cooxidation of luminol by hypohalite and H2 O2 .10 A further complication is that an LCL reaction may occur both intracellularly and extracellularly.8,11 An interpretation of a CL response must take into consideration that both extracellular and intracellular activity will contribute to the response and that the relative importance of oxygen radical production and MPO availability, respectively, will differ depending on the experimental conditions. This is of utmost importance not only in the many studies on the effect of different pharmaceuticals on leukocyte oxidative metabolism that use the CL technique but also in studies using different scavengers/inhibitors to determine the molecular mechanisms behind the CL reaction.20 An extracellular production of oxygen metabolites is very important for the killing of nonphagocytized bacteria, but to perform a killing process with minimum destruction of the surrounding tissue components, the cellularly produced metabolites should preferentially be formed within the phagocytic vacuoles. Besides the status of phagocytes, the proportion of extra- and intracellularly generated reactive oxygen species (ROS) is determined by a number of factors. Such factors can be the type of the stimulant, its amount, or various physical characteristics of the CL system (volume, mixing, temperature). In summary, CL kinetics depends on a number of factors determined in turn by complex relationships such as blood components (polymorphonuclear leukocyte (PMN), RBC, serum, etc.), constituents of the CL system (zymosan, luminol), and measurement conditions (temperature, pH, mixing, phagocyte aging during storage, sample volume). However, maximal emission appears randomly for the particular cells after stimulation. The usual CL kinetics curve reflects the integral oxidative activity of every cell, but their individual contribution is not the same. Many cells remain indifferent even when in contact with a stimulating zymosan. Obviously, their ability to respond is different.49,67
PHAGOCYTE LUMINESCENT SENSOR
3 TECHNIQUES USED TO DETECT RESPIRATORY BURST AND LOCALIZATION
A number of different techniques are currently employed to monitor NADPH oxidase activity in phagocytic cells.53,36,14,57,56,25,24,68
3.1
Microscopy
Traditionally, NADPH oxidase activity has been evaluated with a microscopic method by nitroblue tetrazolium (NBT) salt reduction to blue–black insoluble formazan granules identified in positive neutrophils by microscopy.58 Also, the respiratory burst was detected using a covalently bound rosamine stain.54 This method allows the visualization of intracellular oxidant production in fixed cells using attenuated illumination with a laser. As expected, extracellular superoxide production measured by the cytochrome c test did not correlate with the intracellular rosamine oxidation.
3.2
Spectrophotometry
Cytochrome c reduction test —reduction of ferricytochrome c has been used to measure rates of formation of superoxide: Fe3+ cyt c + Fe2+ cyt c + O2 . O•−→ 2 The reaction is followed spectrophotometrically at 550 nm. NBT test —nitro-substituted aromatics, such as NBT, can be reduced by superoxide via one-electron transfer reactions. Superoxide anion production measured with NBT reduction using a photometric method at 490 nm is a simple, quantitative method and has recently been adapted to automated measurements.70
3.3
Fluorimetry
Dihydrorhodamine 123 is an intracellular dye that turns fluorescent after exposure to hydrogen peroxide (H2 O2 ), which is released during a respiratory burst. The difference between the relative fluorescence intensity in activated and nonactivated cells was measured by flow cytometry27
3
Bass et al. developed a method for quantifying intracellular respiratory burst activity at a single cell level.6 They used 2,7-dichlorofluoresceindiacetate (DCFH-DA), which readily diffuses through an intact plasma membrane. Intracellularly the substrate is hydrolyzed to impermeable and nonfluorescent 2,7-dichlorofluorescein (DCFH). Upon oxidation by hydrogen peroxide, DCFH is turned into strongly fluorescent 2,7dichlorofluorescein (DCF), a fluorochrome applicable to quantification by flow cytometry.
3.4
Chemiluminescence
The luminol-amplified CL technique is very sensitive and simple to perform and, as a consequence, it is widely and increasingly used to study respiratory burst activity induced in phagocytic cells.1,3,21 PMNs can circulate in a “priming” state, which is a state reflecting the organism’s readiness for defense.45,77 Moreover, attempts have been made to correlate the primed activity of circulating PMNs with the severity of disease and its outcome,73 as well as to measure intracellular and extracellular production of ROS.8,11,16,18,34,42 The extracellular CL response can be separated from the intracellular one17,19,43 on the basis that: (i) the CL reaction is peroxidase dependent and is totally inhibited by the MPO inhibitor azide23,65,26 and (ii) H2 O2 scavenger catalase and azide-insensitive horseradish peroxidase (HRP) are both large proteins that have no access to intracellular sites.
3.5
Advantages and Disadvantages of these Techniques
Ideally, a method for measuring the generation of reactive oxygen metabolites should: (i) not interfere with cellular function,29 (ii) be specific for a particular mechanism and/or metabolite, (iii) be sensitive, and (iv) be capable of measuring both extracellularly and intracellularly released reactive oxygen metabolites. Luminometry has several advantages over other analytical techniques. Luminometry is up to 100 000 times more sensitive than absorption spectroscopy and is at least 1000 times more sensitive than fluorimetry. The techniques commonly used to measure
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
the production of reactive oxygen metabolites usually involve some large detector molecule that cannot reach the intracellular site.53 Thus, with the use of these techniques, only oxidative metabolites released extracellularly are quantified. The luminol-enhanced chemiluminescent system allows us to measure intracellular as well as extracellular production of ROS. Usually, CL systems used for the quantitative estimation of intracellular ROS production are different from those used for extracellular production. That is why no direct comparison in quantitative terms can be made between the amounts of ROS released extracellularly and those produced intracellularly. As was reported, a new component approach of analyzing CL kinetics is appropriate for an estimation of the respiratory burst and therefore for characterization of the functional state of PMNs48,49 (Table 1).
4 THE FIBER-PHAGO LUMINOMETER AS A DETECTOR DEDICATED TO THE SENSITIVE ASSESSMENT OF PHAGOCYTE ACTIVITY IN BIOLOGICAL FLUIDS 4.1
Blood Chemiluminescence, Components of Chemiluminescent Kinetics and Phagocyte States
The most productive way to work with living phagocytes is to keep them in their whole
blood environment. This minimizes the need for laborious work and helps prevent the introduction of artifacts when using cell purification methodologies.31 In addition, it reduces the time required for each test and maintains conditions that are close to the in vivo cellular environment. The chemiluminescent system allows us to measure intracellular as well as extracellular reactions,11 and when using a previously described component analysis,48 it is possible to simultaneously assess the contribution of both the extracellular and the intracellular CL emitted from the same cellular system. The cellular–biochemical characteristics of these three components were previously described49 and are summarized as follows (Figure 1): The first component represents processes that take place near the plasma membrane. They are connected with phagocytosis and cause extracellular CL. The second component represents processes located inside the cell. They are connected with phagocytosis and cause intracellular CL. The third component represents mainly processes that lead to intracellular CL. However, they are not directly connected with phagocytosis. We used these components and a previously described methodology50 to derive CL kinetic parameters of a single emitting system that allows for the quantitative comparison of the dynamic functional state of circulating blood PMNs. The general idea of dynamic assessment of phagocyte respiratory burst is illustrated in Figure 2. The existing parameters of CL kinetics can be
Table 1. Basic characteristics of methods used for phagocyte respiratory burst assessment
Method characteristics Interference with cell activity Specific Sensitive Separation of extra- and intracellular activities
(a) (b)
100 × photometry. 1000 × fluorimetry.
Microscopy
Photometry
Fluorimetry
Amplified CL
Yes
Yes
Yes
No
No No Intracellular only
No No Different systems used
Yes Yes(a) Intracellular only
Yes/No Yes(b) Different systems used for intra-, extracellular activities Same activity system—but component approach used
PHAGOCYTE LUMINESCENT SENSOR Model CL kinetic tot 1 2 3
2000 CL (cps)
1
2
1500
Model CL kinetics
2500
Total CL First component Second component Third component
Total Phagocytosis related Nonphgocytosis related
2000 1500
CL (cps)
2500
5
1000
1000
tot 500
500
3 0 0
10
20 Time (min)
(a)
30
0
40
0
10
(b)
20 Time (min)
30
40
Figure 1. (a) CL kinetics broken down into its components.48 (b) CL kinetics resulting from processes directly connected with phagocytosis (sum of first and second component) as well as CL produced as a result of processes not directly related to phagocytosis (third component). [Magrisso M, et al. ‘Model Components of Luminol Chemiluminescence Generated by PMNL.’ Journal of Biochemical and Biophysical Methods, (1995) 30, 257–269. Reprinted with permission from Elsevier.]
Innate system status
CL2 (P1)
∆CL2 > 0 S 1′
S 2′ ∆CL2 < 0 S0
S1
S2
∆CL1 > 0 CL1 (P1)
Figure 2. Momentary and dynamic innate immune system status. Here CL1 and CL2 are imaginary parameters of respiratory burst based on CL kinetics information (set of CL parameters characteristic for the case). The points denoted as S1, S1 , S0, S2, S2 depict different momentary innate immune status; CL1 and CL2 are measures of its dynamic change in case of two different scenarios.
classified into three groups: physical, biological, and temporal. The physical parameters consist of cell numbers (phagocytes, erythrocytes), stimulant concentration (particle/cell ratio), volume-tosurface ratio, mixing (sample oxygenation and phagocytosis synchronization), pH of the buffer used, and temperature. These parameters allow for calibration and the investigator must keep them constant at some predetermined value to avoid a multiparametric interpretation. The other two groups form a “phagocytosis-inherent space”
(cell reserve of reagents participating in respiratory burst-related chain of reactions as well as the existing primed status of phagocytes) and cannot be controlled. Instead, we propose that the change in the phagocyte respiratory burst caused by some well-controlled shift of these parameters can be measured.50 Briefly, having in mind the limited capacity of the phagocyte to restore its ability to generate ROS (inherent irreversibility of phagocytes), it is not the same if the phagocyte respiratory burst follows the S1–S0–S2 or S1 –S0–S2 trajectory (both from an estimative and prognostic point of view). It would also be important to have blood samples under properly controlled assay conditions in order to correlate their experimentally or clinically defined functional states with those obtained by the component analysis of CL kinetics.
4.2
CL Probes
The most common lumigenic substances are luminol (5-amino-2, 3-dihydro-1,4-phthalazinedione) and lucigenin (bis-N -methylacridinium nitrate), with emission at 460 and 510 nm, respectively. There are three main characteristics of the luminolamplified CL reaction in neutrophils: (i) a peroxidase (usually MPO originating from azurophil granules) is required, (ii) oxygen metabolites produced by the NADPH oxidase are needed, and
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
(iii) both intracellular and extracellular reactions are measured.44 Lucigenin-dependent chemiluminescence (LDCL), in contrast to LCL, is independent of MPO and is postulated to be the consequence of superoxide production by an NADPH oxidase located in the plasma membrane of PMN.
4.3
Stimulants, Mechanisms
The stimulants can be divided into different groups depending upon their solubility and interaction with the membrane receptors. Most of the used soluble receptor stimulants (n-formylmethionyl-leucyl-phenylalanine [nFMLP], phorbol 12-myristate 13-acetate [PMA], conA, plateletactivating factor PAF, Ca-ionophore A23187) interact with the PMN membrane by a nonreceptor mechanism. Arachidonic acid (AA) can also stimulate without interaction with receptors. Zymosan and latex beads belong to the group of particle stimulants. When luminol is used as a CL probe, the PMN CL response is highly dependent on the type of stimulus employed. Contact with opsonified particles results in recognition via complement and/or immunoglobulin G (IgG) Fc receptors of the phagocyte, activation of redox metabolism, phagocytosis, specific and azurophilic degranulation, and formation of phagolysosomes. On the other hand, the liquid stimulant PMA causes specific degranulation with full activation of granulocyte redox metabolism, but little or no azurophilic degranulation, and no formation of phagolysosome.3 Depending on the mutual correlation between these processes, different phases of LCL kinetics are formed, which are clearly visible in some cases or may remain invisible, which makes the LCL test difficult for clinical use (Table 2).
4.4
Requirements for a Dedicated Luminescent Sensor of the Phagocyte Respiratory Burst
A typical chemiluminescent instrument71,72,64,9 consists of a sample compartment and a measuring section, which are functionally connected and operate under computer control. The correct interpretation of data, as well as data reproducibility, depends on many requirements that need to be satisfied by the instrument design. First, in order to achieve precise, repeatable, and comparable results, the measurement of biological samples must be performed at equivalent conditions regarding both the device and the samples. Such a measurement is better realized if the samples are tested simultaneously, in a multichannel mode.9 Of course, data is also acquired “simultaneously” just in case the maximal time shift inside the cycle of measurement is sufficiently lower than the time interval for a significant chemiluminescent intensity change. Second, high-sensitivity measurements allow for routine work at lower reagent concentrations. Since common CL measurements occur in the visible portion of the spectrum, the detector of choice is usually a photomultiplier tube (PMT). The most important characteristic of the PMT is the quantum efficiency of the photocathode (the ratio between the number of electrons emitted by the photocathode to the number of incident photons). However, the photomultiplier noise (dark current) is the ultimate limiting factor in determining sensitivity. Because photon-counting offers 100 times better signal-to-noise ratio in comparison to DC registration and thus higher sensitivity, it is probably the most widely used form of detection in CL. Third, as in all cell activities, the emitted CL is strongly temperature dependent,3 requiring the samples to have precise temperature control.
Table 2. Multiphase CL response of CL probes and its correlation to extracellular and intracellular ROS production
fMLP Lum-NADPH and MPO-dep (H2 O2 ; O2 − ) Luc-NADPH-dep (O2 − )
2 peaks first extracellular second intracellular 1 peak extracellular
PMA
Zymosan
1 peak extracellular + intracellular(predominant part)
1 peak extracellular + intracellular
1 peak 50% extracellular + ?
1 peak ?% extracellular
PHAGOCYTE LUMINESCENT SENSOR
4.5
Sensor Design, Block Diagram
The chemiluminescent system allows us to measure intracellular as well as extracellular reactions,11 and when using a previously described component analysis,48 it is possible to simultaneously assess the contribution of both the extracellular and the intracellular CL emitted from the same cellular system. On the other hand, optical-fiberbased biosensors have demonstrated their ability to detect biological entities with high sensitivity due to the intimacy between the specific biological interactions and the fiber core coupling with minimal signal losses.5,12,51,52,41,39 Moreover, it has also been shown that a silica surface stimulates circulating blood phagocytes, which then produce a CL pattern similar to the first extracellular phase of the well-known nFMLP pattern.69 By applying the drop of blood on the end face of an optical fiber, an increased surface-to-volume ratio is obtained, improving phagocytosis and light-capturing conditions. The instrument design described here allows for the assessment of both the extracellular and intracellular parts of the CL response simultaneously. This fiber-based chemiluminescent sensor will provide timely and clinically relevant diagnostic and management information for patients undergoing an infection. A new proprietary fiber-based luminometer dedicated to phagocyte activity assessment has been evaluated as a putative tool for rapid, sensitive, reproducible, and inexpensive
7
measurement of the in vivo inflammation state of circulating phagocytes, and the evaluation of the patient status during infection and is described here.
4.6
Detectors, Signal Capturing and Transduction: a Dual Role of Optical Fibers
A luminometer was designed with the following basic characteristics: (i) computerized control of photodetection, (ii) photon-counting mode measurement of a six-fiber sample module, (iii) simultaneous transfer of the measured data to a serial port (allowing for data acquisition by an external computer), (iv) direct data recording into the computer memory while placing the graphs in parallel on the computer screen, and (v) printing of collected data. To realize all of the aforementioned characteristics, a specific driver was developed using LabWindows. A block diagram of the six-channel luminometer is shown in Figure 3. It consists of a thermostated fiber holder module (1) containing six fibers (2); a photon-counting PMT detector (3); a DC power supply (4); a stepper driver (5); a programmable logic controller (PLC) (6); a personal computer (7); a step motor (8); a position sensor (9); a thermocontroller (10); and a rotating diskshutter (11). The rotating disk-shutter contains a 2 4
1
10
4
8
5
6
9
3
12 11
7 4
(a)
(b)
Figure 3. External view (a) and block diagram (b) of the luminometer. 1: thermocontrolled fiber holder; 2: fibers; 3: photon-counting PMT detector; 4: power supply; 5: interface; 6: PLC; 7: computer; 8: step motor; 9: position sensor; 10: thermocontroller; 11: rotating disk-shutter with a hole 12. [Courtesy of Elsevier Science.]
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
hole that is positioned under the sample fiber at the moment it is under measurement, thus exposing only one fiber at a time. The fiber holder (sample compartment) was designed to offer optimal conditions for the adequate measurement of CL emitted by the phagocytes lying at the fiber end-face surface. The latter takes place in a sample cuvette or well (Figure 1d). The disk-shutter located in a light-tight space, can be rotated 60◦ around its axis by the step motor and by a worm gear (not shown) with a preciseness of 0.025◦ . When the orifice of the rotating shutter is positioned under one of the six fibers, it is then in optical contact with the naked PMT head of the photon-counting detector and the emitted photons are transmitted to the PMT surface and counted for a predetermined time interval. The subsequent turn of the shutter by a 60◦ angle positions the next fiber for measurement and the cycle is thus repeated. The position sensor’s feedback is used to ensure the correct function of the shutter positioning. Neither the samples nor the detector change their position during the measurement. Such an arrangement is space thrifty, ensures constant thermoregulation with the fiber holder, and provides a minimal optical path between the light-emitting samples and the light detector thus allowing optimum light collection. The measuring section consists of a photon-counting PMT detector that responds to light emission with electric impulses, the number of which correlates with the number of photons emitted, that is, light intensity.
of the buffers, and so on. This is why investigators must keep them constant at some predetermined value to avoid a multiparametric interpretation. However, the expected change in the CL pattern with the change of a known and described parameter validates the dynamic properties of the instrument and also provides an additional option to compare it with the competing instruments and protocols.
5 FEATURES OF THE PHAGOLUM DEVICE
5.2
A number of experiments show the instrument’s ability to provide relevant data of the phagocyte functional status, as well as check the extent of the recorded kinetic data that helps analyze the extra- to intracellular proportion of the phagocytereleased ROS when using the same emitting system during phagocytosis. Phagocyte CL kinetics is known to depend on many parameters3,40,50,30 : the PMNs’ functional status, the stimulating agent, the dilution of the blood, the stimulating particle/cell ratio, temperature, mixing, surface-to-volume ratio, storage duration, hydrophilic/hydrophobic properties of the sample surface, pH, metal content
It has been reported that the storage temperature47 as well as the temperature change that occurs in vitro, greatly affects the shape of the CL kinetics.4 Moreover, thermal shock or feverassociated temperatures enhance the neutrophils’ ROS production.61 That is why most of the luminometers designed to measure phagocyte ROS production are temperature controlled. Figure 5 shows two representative CL kinetics recorded at 20 and 37 ◦ C after 2-h blood preincubation at room temperature. A two-phase pattern is visible in both curves. The first peak appears at the
5.1
Zymosan Concentration as a CL Kinetics Parameter
Zymosan concentration (cell/particle ratio) may be misleading if not considered as a factor of CL patterns. Figure 4 shows the effect of zymosan concentration on the recorded CL pattern, demonstrating one of the known parameters that affects phagocyte activity assessment (and therefore needs a proper use depending on the goal). The samples are identical regarding both the volume and the concentration of the cells and the rest of the reagents used. The only difference is in the zymosan concentration, and therefore, in the amount of collisions and attempts of phagolysosomes forming. That in turn changes the amount and ratio of the ROS produced extra- and intracellularly during phagocytosis, thus causing clear difference in the observed CL kinetics pattern (Figure 4). The component analysis shows that the most significant change is increased emission of extracellular ROS with the increase of zymosan concentration. CL Kinetics at Room and Physiological Temperatures
Capacity (counts)
PHAGOCYTE LUMINESCENT SENSOR
1e + 6
9
PMN 250000 ml−1 PMN 25000 ml−1 PMN 2500 ml−1
1e + 5
1e + 4 0
3 4 2 Zymosan (mg ml−1)
1
(a) 2000
1.8
1800
1.6
1600
Relative units
CL (cps)
1.4
0.5 mg ml−1 4.0 mg ml−1
1400 1200 1000 800
1.2
400
0.4
200
0.2 5
10
(b)
15 Time (min)
20
25
0
30
Relative phagocapacity Velocity
0.8 0.6
0
6
1
600
0
5
0.5 mg ml−1
4 mg ml−1
(c)
Figure 4. CL kinetics pattern dependence on standard and extracellularly forced emitting system. Sample content: luminol E-4M: 10 µl; blood 1/30: 10 µl; opsonized zymosan (OZ): 12/1.5 mg ml−1 , correspondingly, 10 µl. (a) CL capacity dependence on zymosan concentration—some saturation is observed at 2 mg ml−1 zymosan. (b) CL patterns recorded after stimulation with low and high zymosan concentrations. (c) Derived CL information.
1100 1000 20 °C 37 °C
CL intensity (cps)
900 800 700 600 500 400 300 200 100 0
0
10
20
30
40 50 Time (min)
60
70
80
90
Figure 5. Representative CL kinetics recorded at room temperature (20 ◦ C, filled circle) and mammalian physiological temperature (37 ◦ C, empty circle). Both kinetics show a two-phase pattern CL. Sample content: luminol E-4M: 10 µl; blood 1/30: 10 µl; OZ: 12 mg ml−1 , correspondingly, 10 µl.
same time—approximately 3 min after the stimulation of the phagocytes in both kinetics (see the arrows). As for the second visible peak, it appears 10 and 45 min after stimulation for the kinetics recorded at 37 and 20 ◦ C respectively. Some stimulants are known to show two-phase CL patterns, but it is not characteristic in the case of zymosan-induced CL kinetics. In fact, there is one exceptional CL pattern at physiological conditions—the “frustrated state” of the phagocytes (see Ref. 50) featuring two peaks in its CL kinetics. It has been demonstrated by others that the presence of silica in the sample compartment causes an additional stimulation to PMNs.69 As mentioned in the preceding text, the front-end surface of the silica optical fibers in our system also serves as our cuvette bottom. Indeed,
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
both the size of the target to be phagocytized and the silica material lead to one very important feature of the use of this biosensor, the clear indication of the extracellularly produced light and the time of its appearance. This is intended to simplify the analysis and understanding of the mechanisms of PMNs activation, as well as the assessment of the extra- and intracellularly generated ROS using the same light-emitting system as was described in our earlier works (see CL assay). Note also the initial CL peak presence as well as the time of its appearance in all experiments in this article. Another contributor to the increased relative CL participation of the earlier stage processes (mainly extracellularly generated ROS) is the high quantity of zymosan used in the experiment.50 5.3
Assessment of Primed Phagocytes – Blood Storage (Aging of Blood) as a Priming Factor
The exposure of human neutrophils to low concentrations of chemotactic agents and other biologically active substances shows an increased response when stimulated again with the same or another agent (priming—see e.g., Ref. 15). Moreover, attempts have been made to correlate the primed activity of circulating PMNs with the severity of disease and outcome.66,73 That is why it was essential to check the sensitivity of our system and approach to assess
the priming by the functional status of phagocytes as reflecting the organism’s readiness for defense, therefore providing a high predictive value.45 Representative changes in CL pattern are shown in Figure 6 after different durations of blood post-venipuncture storage. The data, measured in a time interval of several hours, describes the aging of the same blood sample. It illustrates the potential of the computerized multisample temperature controlled luminometer for a fiber array–based biosensor as a rapid and sensitive measuring tool for the in vivo state of inflammation of circulating phagocytes. It is commonly accepted that aging of blood leads to the priming of phagocytes; therefore, it is a useful model for the investigation of the functional status of the phagocyte.76 Indeed, the analysis of the kinetics shows that the noticeable decrease in the peak time of the observed CL pattern can be represented as a continuous shift of the derived CL parameter’s effectiveness and velocity. As defined earlier,50 the effectiveness is calculated as the ratio of intracellular CL to extracellular CL due to phagocytosis (Figure 1b). As for the velocity, it is derived as the ratio of the total CL emitted due to phagocytosis to the light emitted during processes not directly related to phagocytosis. Figure 6(b) shows the quantitative estimation of both the effectiveness and the velocity of the emitted during respiratory burst ROS after storage at room temperature for 0, 1, 2, 3
600
Relative units
CL (cps)
400
Effectiveness Velocity
2.5
After 0 h After 1 h After 2 h After 4 h
500
300
2 1.5 1
200 0.5 100 0 0 (a)
10
20 Time (min)
30
After 0 h
40
After 1 h
After 2 h
After 4 h
(b)
Figure 6. (a) CL patterns recorded with the aging of same blood as a model for primed phagocyte activation. (b) Effect of aging on derived CL kinetic parameters. Sample content: luminol: E-4M: 10 µl; blood 1/30: 10 µl; OZ: 12 mg ml−1 , correspondingly, 10 µl.
PHAGOCYTE LUMINESCENT SENSOR
and 4 h, respectively. Indeed, the proper oxidative action of phagocytes is expected to be fast and efficient because of ROS created mostly during the phagocytosis timeframe and inside the cell. Because of the priming that takes place during the aging of blood, the phagocyte functional status undergoes continuous transition from “resting”50,76 state (high efficiency, low velocity) to “standby” state (decreased efficiency, higher velocity). Thus, the aging model illustrates the device potential to monitor the phagocyte functional status change with the changes in humoral-immune modulators.
5.4
fMLP priming
Figure 7(a) shows a representative change in CL pattern caused by a prior storage of tested blood with low concentration (3 nmol) of chemoattractant fMLP. Next, Figure 7(b) compares the quantitative estimation of both the effectiveness and the velocity of respiratory burst after fMLP priming recorded in parallel with a nonprimed sample from the same blood. It is interesting to see that at these conditions, fMLP priming causes an increase in velocity and some decrease in the effectiveness of respiratory burst owing to the changes in phagocytosis-related components of the CL (the
amount of extracellularly produced ROS is more significantly increased).
5.5
Glucose Level as a Priming Agent
It is known that the lack of glucose leads to exhausting of phagocytosis. Part of zymosanstimulated CL kinetics is glucose dependent, and the other part is not dependent on the glucose content. The glucose-independent part is considered to be directly connected to AA metabolism.13 The same work shows a 30–40% decrease of CL in the case of glucose lack for 2 h, without influence on the cell’s vitality. In other words, a change of glucose level during phagocyte stimulation is a priming factor and could provide additional information for the connection between CL and phagocytosis. Data shown in Figure 8 demonstrate CL kinetics of samples incubated with presence/absence of glucose (5.56 mmol l−1 ) for 3 h and after stimulation with relatively low zymosan concentration in the presence/absence of glucose in the standard CL system. In general, the phagocytosis-related part of CL kinetics shows a clear dependence on glucose concentration. The decrease of glucose level in the phagocyte media both prior and during the stimulation primes phagocyte respiratory burst readiness (Figures 8a and b).
Dependence of CL pattern on prior storage of phagocytes with fMLP
Dependence of derived CL parameters on prior storage of phagocytes with fMLP 7
4000
6
Without fMLP With 3 nmol l−1 fMLP
2000
Without fMLP 3 nmol l−1 fMLP
5 Relative units
3000 CL (cps)
11
4 3 2
1000
1 0
0 0 (a)
2
4
6 8 Time (min)
10
12
Effectiveness
Velocity
(b)
Figure 7. (a) Chemiluminescence response after incubation of diluted whole blood samples in vitro for 5 min at 37 ◦ C in the presence (•) and absence (o) of 3 nmol l−1 of fMLP. (b) Effect of fMLP on derived CL kinetic parameters. Sample content: luminol E-4M: 10 µl; blood 1/30: 10 µl; OZ: 12 mg ml−1 , correspondingly, 10 µl.
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Dependence of CL component capacity on the presense of glucose in CL system
Effect of the glucose on phagocyte activity 3000
18 000 16 000
2500
Gi+Gp+ Gi+Gp− Gi−Gp+ Gi−Gp−
Capacity (cps)
CL (cps)
2000
14 000
1500 1000
12 000
Gi+Gp+ Gi+Gp− Gi−Gp+ Gi−Gp−
10 000 8000 6000 4000
500
2000
0
0 0
10
(a)
20 Time (min)
30
40
1+2
3
(b)
Figure 8. Comparison of the in vivo relative contribution of phagocytosis-related and nonrelated reactive oxygen species produced after incubation of diluted whole blood samples in vitro with D-glucose (priming of phagocytes). (a) Chemiluminescence pattern after incubation of diluted whole blood samples in vitro in the presence (+) or absence (−) of 5.56 mmol l−1 of D-glucose during the incubation (Gi) or during the measurement (Gp). (b) Comparison of the in vivo relative contribution of phagocyte extracellularly and intracellularly produced reactive oxygen species produced after incubation of diluted whole blood samples in vitro in the presence (+) or absence (−) of 5.56 mmol l−1 of D-glucose during the incubation (Gi) or during the measurement (Gp).
5.6
Circulating Phagocyte Activation
During the respiratory burst, upon stimulation with either soluble or particulate matter, PMNs generate reactive oxygen species and emit CL as a result of metabolic activation. The measurement of
CL has been demonstrated to be a useful tool for the in vitro assessment of the opsonophagocytic function of PMNs. Furthermore, the analysis of CL kinetics can be used to characterize the functional state of the PMNs.76,50 Figure 9(a) shows a typical pattern of a healthy “resting” state and
Derived respiratory burst parameters Infected (versus) healthy response 2000
4
Relative units
1500 CL (cps)
Effectiveness Velocity
Infected Control
1000
500
2
1
0 0 (a)
3
10
20 Time (min)
30
0
40
Candida
Control
(b)
Figure 9. (a) Simultaneously recorded representative CL responses ± CV of healthy (control) and infected patient blood (Candida albicans). According to their phagocyte functional status the healthy and infected responses can be classified50 as “resting” and “activated” correspondingly. Sample content: luminol E-4M: 10 µl; blood 1/30: 10 µl; OZ: 12 mg ml−1 , correspondingly, 10 µl. (b) Effect of circulating phagocyte status on derived CL kinetic parameters.
PHAGOCYTE LUMINESCENT SENSOR
an infected “activated” one, recorded while using operator-blinded blood samples obtained from two patients, one of whom was a patient suffering from a urinary tract infection. Both patterns were recorded after a 2-h preincubation of the blood. The healthy blood possesses, in general, a higher capacity for in vitro priming as compared to the blood of an infected patient, which had already undergone priming. This is why a relative prolongation of storage time could result in bringing both patterns of CL kinetics closer. However, Figure 9 shows that even at such a condition, the observed CL patterns differ sufficiently. It is clear from the very different CL patterns that this device is useful in distinguishing healthy from infected blood. Further analysis emphasizes this by showing the differences in the patient respiratory burst depicted in Figure 9(b). The data implies that during development of any phagocyte-related disease it will be possible to monitor the overall change in the patient’s humoral-immune-modulated phagocyte functional status. Our preliminary data (not shown), also depict unique CL kinetic patterns of PMNs obtained from patients infected by different types of organisms. Thus, this instrument has the potential of elucidating the nature of an infecting agent at a stage where definite characterization by bacteriological and/or serological methods is still unavailable. This valuable information could assist decision making regarding early resumption of antibiotic treatment and the type of chemotherapeutic agent used.
5.7
5.8
Derived respiratory burst parameters 8
Follow-up CAPD Follow-up CAPD+Diabetes
Relative units
CL (cps)
6
1500 1000
Priming in Biological Space II: Priming of the Surrounding Media
Of course, the approach is applicable not only to blood samples. For many disorders interfering with the innate immune system, other phagocyte-containing liquids could be relevant. The chemical composition of human cerebrospinal fluid is considered to reflect brain metabolism and
3000
2000
Priming in Biological Space I: Diabetes as a Glucose-level Priming Agent during Recurrent Therapeutic Procedures
One of the major causes of diabetic complication is hyperglycemia, but the exact mechanism of its detrimental effect is not clear. An impaired production of oxygen-derived free radicals (e.g., superoxide anion (O2 − ) and hydrogen peroxide-myeloperoxidase-halide (H2 O2 -MPO-Cl− ) antimicrobial system) by neutrophils from poorly controlled diabetic patients was demonstrated recently.63 This was supported by our observations of continuous ambulatory peritoneal dialysis (CAPD) patients. Some of these patients show an elevated glucose level, which in turn acts as an additional priming parameter (Figure 10). Figure 10(a) demonstrates different CL patterns between two groups of follow-up CAPD patients due to different levels of glucose in their blood. More detailed analysis shows (Figure 10b) an impaired phagocytosis-related part of respiratory burst.
CL kinetics patterns of CAPD patients
2500
13
Effectiveness Velocity
4
2 500 0
0 0 (a)
10
20 30 Time (min)
40
50
FUP
FUP+Diabetes
(b)
Figure 10. (a) Comparison between representative CL kinetics of two groups of CAPD follow-up patient with different blood glucose levels. (b) Derived CL information demonstrates impaired phagocytosis in the case of elevated glucose levels.
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
there is experimental evidence78 of a decrease in sulfhydryl groups and increased content of products of lipid peroxidation—both affecting the oxidative stress—this implies that cerebrospinal fluid also can be a parallel sample source for CL assessment in some autoimmune disorders like multiple sclerosis, stroke, Parkinson’s disease, Alzehimer’s disease, and physiological aging. Figure 11(a) compare simultaneously the activation level of whole blood and peritoneal liquid phagocytes. The striking difference in the phagocytosis-related part of demonstrated CL patterns suggests possible existence of some factor in the peritoneal liquid that is blocking this part of CL emission. Such a thesis is supported by the data reported in.79 Next, Figure 11(b) shows consecutive daily CL records of phagocyte activity in blood and peritoneal liquid taken from patient with peritonitis which illustrates the ability of the approach to monitor the innate immune system change with the patient treatment during the course of particular infection, in that case—peritonitis.
5.9
Priming in Temporal Space: CAPD Follow-up and Suppressed Patients Demonstrate Different Aging of Circulating Phagocytes
As reported earlier,76 the storage of blood interferes with the phagocyte level of dynamic
activation in many pathologies. Indeed, the initial phagocyte functional status, their transitional direction characteristics, in particular, clinical picture, taken together with the limited potential of phagocyte to restore its oxidative functionality, change the phagocyte functionality to a different extent and balance over time. Figure 12 shows different patterns of phagocyte response change after 2-h blood storage of CAPD follow-up patients and the response obtained from patients with suppressed phagocyte activity after surgical intervention.
5.10
Case Separation and Monitoring
All the analytical and technological steps mentioned earlier can be used for better diagnostic and prognostic evaluation during patient hospitalization and medical treatment. Figure 13 summarizes our results for phagocyte activity of CAPD patients. The method uses internal reference and comparison between primed and nonprimed phagocytes. Standard parameters (area under the CL kinetics, initial slope, time to peak), as well as CL kinetics component information were used to assess the normalized (by cell count) phagocyte activity. Component analysis was performed to derive more phagocytosis-related information. CL1 and CL2 are linear combinations made by the best-distinguishing CL parameters
Peritonitis—parallel CL data from peripheral blood and peritoneal liquid phagocytes
Peritoneal liquid: consecutive measurements
1600
1 Peritonitis blood Peritonitis liquid
1400
CL (relative units)
CL (cps)
1200 1000 800 600 400
PL Run 1 PL Run 2 PL Run 3 PL Run 4
0.8 0.6 0.4 0.2
200 0 0 (a)
10
20 30 Time (min)
40
0 50
0 (b)
10
20 30 Time (min)
40
50
Figure 11. Peritonitis blood versus peritoneal liquid—direct comparison between the local and overall state of phagocyte activation. (a) Different pattern of CL kinetics due to significant decrease of phagocytosis-related part of the respiratory burst. (b) Consecutive daily CL records of phagocyte activity in peritoneal liquid taken from patient with peritonitis.
PHAGOCYTE LUMINESCENT SENSOR Follow-up and suppressed CL patterns recorded without and after 2 h aging
Derived CL parameters 5
1600 1400
Follow-up Follow-up + 2 h Suppressed Suppressed + 2 h
1000
Effectiveness Velocity
4 Relative units
CL (cps)
1200
15
800 600 400
3 2 1
200 0
0 0
(a)
10
20 30 Time (min)
40
50
FUP
FUP+2h
Supp
Supp+2h
(b)
Figure 12. (a) CL patterns recorded with the aging of follow-up (FUP) and suppressed blood as a model for primed phagocyte activation. (b) Effect of aging on derived CL kinetic parameters. Sample content: luminol E-4M: 10 µl; blood 1/30: 10 µl; OZ: 12 mg ml−1 , correspondingly, 10 µl.
(Table 3 the list of parameters used for data separation shown on Figure 13). Standard statistical procedure was used to select the parameters and determine CL1 and CL2. As a result there is no overlapping between the groups shown in Figure 13. Moreover, Figure 13 illustrates the ability of the approach to monitor changes in the innate immune system with the patient treatment during the course of a particular infection, in this case—peritonitis. Daily measurements were preformed several times and CL information was used to characterize the innate immune status. 5.11
Effect of Pharmaceutical Substances on Respiratory Burst of Circulating Phagocytes
As shown earlier, the phagocyte luminescent concept can be applied to follow disease activity or early infection—before antibodies are detectable—and provide diagnostic and prognostic information during the course of patient treatment. It can be easily adapted to provide toxicology information about interaction between phagocytes and allergens, microbial and industrial pollutants, as well as for assessment of immunomodulating activity of pharmacological products. Figure 14 demonstrates the in vitro effect of IgE and aspirin on phagocyte respiratory burst activity.
Table 3. List of some parameters for group separation and case monitoring
Parameter nonPhagoSA RelCapSP RelPtimeSP
VelSP ExtraS RelNoPhagoSA
ExtraSA BkgSP NoPhagoS VelSA BkgSA RelPtimeSA
ExtraSP EffS SlopeS SlopeSP
Definition Nonphago-related CL of aged sample Capacity of primed sample divided by capacity of standard sample Peak time of primed sample divided by peak time of standard sample Velocity of primed sample Extracellular phagocytosis-related emission of standard sample Nonphago-related CL of aged sample divided by nonphago-related CL of standard sample Extracellular phagocytosis-related emission of primed sample Background CL of primed sample Nonphago-related CL of standard sample Velocity of aged sample Background CL of aged sample Peak time of primed sample divided by peak time of aged sample Extracellular phagocytosis-related emission of primed sample Effectiveness of standard sample Peak of standard sample divided by time to reach it Peak of primed sample divided by time to reach it
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Infection—case monitoring 4
2 Run 1 Run 2 CL2
0
−2
FUP TINF PER SUPR DIAB TRANS
Run 3 −4
−6
−6
−4
−2
0
2 CL1
4
6
8
10
Figure 13. Group separation and case monitoring by discriminant analysis. Every case is shown by a small circle. Large circles depict mean canonical group coordinates. For case monitoring see text. FUP: follow-up case; TINF: case of tunnel infection; PER: case peritonitis; SUP: case of patient suppressed after transplantation; DIAB: case of diabetes mellitus; TRANS: case during treatment.
Effect of IgE on phagocyte activity
1600
Effect of aspirin on phagocyte activity
4000
1400 Control IgE-1U IgE-5U
1000
Control Aspirin 1.5 mmol
3000 CL (cps)
CL (cps)
1200
800 600 400
2000
1000
200 0 0 (a)
10
20 Time (min)
30
0
40 (b)
0
5
10
15 20 Time (min)
25
30
35
Figure 14. Examples of pharmaceutical agents testing—aspirin and IgE.
6 PROSPECTS
The PhagoLum biosensor system is based on an approach and a device with the potential to be an automated system for the assessment of circulating phagocyte functional status by the luminescence emitted during stimulated respiratory burst. Of course, to become efficient such an automated system will require relevant associated
databases. Several directions for applications seem to be very promising: (i) to follow disease activity or early infection in hospitals (before antibodies are detectable) in humans for both medical diagnosis and prognosis; (ii) to study the effects of pharmacological agents on the metabolism of granulocytes; (iii) to provide information about toxic interaction between phagocytes and new biomaterials.
PHAGOCYTE LUMINESCENT SENSOR
REFERENCES 1. R. C. Allen and L. D. Loose, Phagocytic activation of a luminol-dependent chemiluminescence in rabbit alveolar and peritoneal macrophages. Biochemical and Biophysical Research Communications, 1976, 69, 245–252. 2. R. C. Allen, R. L. Stjemholm, and R. H. Sieel, Evidence for the generation of electronic excitation state(s) in human polymorphonuclear leukocytes and its participation in bactericidal activity. Biochemical and Biophysical Research Communications, 1972, 47, 679–684. 3. R. C. Allen, Phagocytic leukocyte oxygenation activities and chemiluminescence: a kinetic approach to analysis. Methods in Enzymology, 1986, 133, 449–493. 4. B. Andersen and A. Brendzel, Use of a unique chemiluminescence spectrometer in a study of factors influencing granulocyte light emission. Journal of Immunological Methods, 1978, 19, 279–287. 5. P. Arenkov, V. Berezin, and N. Starodub, Chemiluminescence fiber optic immunosensor for detecting antibodies to the influenza virus. Ukra¨ıns’ky˘ı biokhimichny˘ı zhurnal, 1991, 63(4), 99–103. 6. D. A. Bass, J. W. Parce, L. R. DeChatelet, I. Szejda, M. C. Seeds, and M. Thomas, Flow cytometric studies of oxidative product formation by neutrophils: a graded response to membrane stimulation. Journal of Immunology, 1983, 130, 1910–1917. 7. P. Bellavite, The superoxide-forming enzymatic system of phagocytes. Free Radical Biology and Medicine, 1988, 4, 225–221. 8. J. G. Bender and D. E. Van Epps, Analysis of the bimodal chemiluminescence pattern stimulated in human neutrophils by chemotactic factors. Infection and Immunity, 1983, 41, 1062–1070. 9. P. Bochev, B. Bechev, and M. Magrisso, Six-sample multiplexing computerized analyzer for integral and spectral luminescence measurements. Analytica Chimica Acta, 1992, 256, 29–32. 10. E. P. Brestel, Co-oxidation by hypochlorite and hydrogen peroxide—implications for neutrophil chemiluminescence. Biochemical and Biophysical Research Communications, 1985, 126, 482–488. 11. G. Briheim, O. Stendahl, and C. Dahlgren, Intra- and extracellular events in luminol-dependent chemiluminescence of polymorphonuclear leukocytes. Infection and Immunity, 1984, 45, 1–5. 12. M. Cattaneo, K. Male, and J. Luong, A chemiluminescence fiber-optic biosensor system for the determination of glutamine in mammalian cell cultures. Biosensors and Bioelectronics, 1992, 7(8), 569–574. 13. K. Cheung, A. Archibald, and M. Robinson, The origin of chemiluminescence produced by neutrophils stimulated by opsonized zymosan. Journal of Immunology, 1983, 130, 2324–2329. 14. H. J. Cohen and M. E. Chovaniec, Superoxide generation bydigitonin-stimulated guinea pig granulocytes. A basis for acontinuous assay for monitoring superoxide production and for the study of the activation of the generating system. Journal of Clinical Investigation, 1978, 61, 1081–1087. 15. A. M. Condliffe, E. Kitchen, and E. R. Chilvers, Neutrophil priming: pathophysiological consequences and
16.
17.
18.
19.
20.
21.
22.
23.
24. 25.
26.
27.
28.
29.
30.
17
underlying mechanisms. Clinical Science, 1998, 94, 461–471. C. Dahlgren and O. Stendahl, Role of myeloperoxidase in luminol-dependent chemiluminescence of polymorphonuclear leukocytes. Infection and Immunity, 1983, 39, 736–741. C. Dahlgren, Difference in extracellular radical release after chemotactic factor and calcium ionophore activation of the oxygen radical generating system in human neutrophils. Biochimica et Biophysica Acta, 1987, 930, 33–38. C. Dahlgren, Analysis of luminol-dependent chemiluminescence from granule depleted neutrophil cytoplast reveals two different light emitting mechanisms. Journal of Bioluminescence and Chemiluminescence, 1988a, 2, 25–33. C. Dahlgren, Effects on extra- and intracellular localized, chemotactic induced, oxygen radical production in neutrophils following modulation for ligand-receptor interaction. Inflammation, 1988b, 12, 335–349. C. Dahlgren, Is lysosomal fusion required for the granulocyte chemiluminescence reaction? Journal of Free Radicals in Biology and Medicine, 1989, 6, 399–403. C. Dahlgren, P. Follin, A. Johansson, R. Lock, H. Lundqvist, and A. Walan, Chemiluminescence as a means of following the function of phagocytic cells. Trends Photochemistry And Photobiology, 1991, 2, 427–443. S. M. Dauphinee and A. Karsan, Lipopolysaccharide signaling in endothelial cells. Laboratory Investigation, 2006, 86(1), 9–22. L. R. DeChatelet, G. D. Long, P. S. Shirley, D. A. Bass, M. J. Thomas, F. W. Henderson, and M. S. Cohen, Mechanism of the luminol-dependent chemiluminescence of human neutrophils. Journal of Immunology, 1982, 129, 1589–1593. M. A. DeLuca (ed), Methods in Enzymology, Academic Press, New York, 1978, Vol. LVII. M. A. DeLuca and W. D. McElroy (eds), Methods in Enzymology, Academic Press, Orlando FL, 1986,Vol. 133, Part B. S. W. Edwards, Luminol and lucigenin-dependent chemiluminescence of neutrophils: role of degranulation. Journal of Clinical and Laboratory Immunology, 1987, 22, 35–39. A. Emmend¨orffer, M. Hecht, M. L. Lohmann-Matthes, and J. Roesler, A fast and easy method to determine the production of reactive oxygen intermediates by human and murine phagocytes using dihydrorhodamine 123. Journal of Immunological Methods, 1990, 131, 269–275. H. Faden and N. Maciejewski, Whole blood luminoldependent chemiluminescence. Journal of the Reticuloendothelial Society, 1981, 30, 219–226. J. Faldt, M. Ridell, A. Anna Karlsson, and C. Dahlgren, The phagocyte chemiluminescence paradox: luminal can act as an inhibitor of neutrophil NADPH-oxidase activity. Luminescence, 1999, 14, 153–160. I. Ginsburg, R. Misgav, D. F. Gibbs, J. Varani, and R. Kohen, Chemiluminescence in activated human neutrophils: role of buffers and scavengers. Inflammation, 1993, 1(3), 227–243.
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
31. L. Glasser and R.L. Fiederlein, The effect of various cell separation procedures on assays of neutrophil function. A critical appraisal. American Journal of Clinical Pathology, 1990, 93, 662–669. 32. B. L. Granger, M. L. Flenniken, D. A. Davis, A. P. Mitchell, and J. E. Cutler, Yeast wall protein 1 of Candida albicans. Microbiology, 2005, 151(Pt 5), 1631–1644. 33. O. Haller, G. Kochs, and F. Weber, The interferon response circuit: induction and suppression by pathogenic viruses. Virology, 2006, 344(1), 119–130. 34. M. B. Hallet and A. K. Campbell, Two distinct mechanisms for stimulation of oxygen-radical production by polymorphonuclear leukocytes. The Biochemical Journal, 1983, 216, 459–465. 35. D. C. Hargreaves and R. Medzhitov, Innate sensors of microbial infection. Journal of Clinical Immunology, 2005, 25(6), 503–510. 36. P. A. Hyslop and L. A. Sklar, A quantitative fluorimetric assay for the detection of oxidant production by polymorphonuclear leukocytes: its use in the simultaneous fluorimetric assay of cellular activation processes. Analytical Biochemistry, 1984, 141, 280–286. 37. T. W. Jungi and E. Peterhans, Change in die chemiluminescence reactivity pattern during in vitro differentiation ol human monocytes to macrophages. Blut, 1988, 56, 213–220. 38. S. J. Klebanoff and R. A. Clark, The Neutrophil: Function and Clinical Disorders, Amsterdam, Elsevier, Biomedical Press, 1978. 39. T. Konry, A. Novoa, S. Cosnier, and R.S. Marks, Development of an ‘electroptrode’ immunosensor: indium–tin– oxide–coated optical fiber tips with an electropolymerized thin film with conjugated cholera toxin B subunit. Analytical Chemistry, 2003, 75, 2633–2639. 40. L. Liu, H. Elwing, A. Karlsson, G. Nimeri, and C. Dahlgren, Surface-related triggering of the neutrophil respiratory burst. Characterization of the response induced by IgG adsorbed to hydrophilic and hydrophobic glass surfaces. Clinical and Experimental Immunology, 1997, 109(1), 204–210. 41. Y. Liu, J. Ye, and Y. Li, Rapid detection of Esherichia coli O157:H7 inoculated in ground beef, chicken carcass, and lettuce samples with an immunomagnetic chemiluminescence fiber-optic biosensor. Journal of Food Protection, 2003, 66, 512–517. 42. R. Lock and C. Dahlgren, Characteristics of the granule chemiluminescence reaction following an interaction between human neutrophils and Salmonella typhimurium bacteria. APMIS Acta Pathologica, Microbiologica, et Immunologica Scandinavica, 1988, 96, 299–305. 43. R. Lock, A. Johansson, K. Orselius and C. Dahlgren, Analysis of horseradish peroxidase-amplified chemiluminescence produced by human neutrophils reveals a role for the superoxide anion in the light emitting reaction. Analytical Biochemistry, 1988, 173, 450–455. 44. H. Lundqvist and C. Dahlgren, Isoluminol-enhanced chemiluminescence: sensitive method to study the release of superoxide anion from human neutrophils. Free Radical Biology and Medicine, 1996, 20(6), 785–792. 45. E. G. Maderazo, C. L. Woronick, S. D. Albano, S. P. Breaux, and R. M. Pock, Inappropriate activation deactivation and probable autooxidative damage as a
46.
47.
48.
49.
50.
51.
52.
53.
54.
55. 56. 57. 58.
59.
60.
61.
mechanism of neutrophil locomotory defect in trauma. Journal of Infectious Diseases, 1986, 154, 471–477. P. N. Madianos, Y. A. Bobetsis, D. F. Kinane, Generation of inflammatory stimuli: how bacteria set up inflammatory responses in the gingiva. Journal of Clinical Periodontology, 2005, 32(Suppl 6), 57–71. U. Magnusson and H. Holst, Assaying granulocyte phagocytosis by chemiluminescence: effect of storage time and temperature of blood samples. Zentralblatt fur Veterinarmedizin. Reihe B, 1998, 45(4), 217–222. M. Magrisso, M. Alexandrova, P. Bochev, B. Bechev, V. Markova, and I. Benchev, Model components of luminol chemiluminescence generated by PMNL. Journal of Biochemical and Biophysical Methods, 1995a, 30, 257–269. M. Magrisso, B. Bechev, P. Bochev, V. Markova, and M. Alexandrova, A new approach for analysis of chemiluminescent kinetics of activated phagocytes in blood. Journal of Bioluminescence and Chemiluminescence, 1995b, 10, 77–84. M. Magrisso, M. Alexandrova M. Markova, B. Bechev, and P. Bochev, Functional States of Polymorphonuclear Leukocytes Determined by Chemiluminescent Kinetic Analysis. Luminescence, 2000, 15, 143–151. R.S. Marks, E. Bassis, A. Bychenko, and M.M. Levine, Chemiluminescent optical fiber immunosensor to cholera antitoxin. Optical Engineering, 1997, 36(12), 3258–3264. R. Marks, A. Margalit, A. Bychenko, E. Bassis, N. Porat, and R. Dagan, Development of a chemiluminescent optical fiber immunosensor to detect Streptococcus pneumoniae antipolysaccharide antibodies. Applied Biochemistry and Biotechnology, 2000, 89(2–3), 117–126. J. A. Metcalf, J. I. Gallin, W. M. Nausseef, R. K. Root, Laboratory Manual of Neutrophil Function. Raven Press, New York, 1986. M. A. Model, L. S. Ganelina, and R. F. Todd III, A microscopic study of Fc gamma RIII-mediated respiratory burst in neutrophils. Immunobiology, 1998, 199(1), 39–50. H. Z. Movat, The Inflammatory Reaction, Amsterdam, Elsevier, 1985. L. Packer (ed), Methods in Enzymology, Academic Press, Orlando, FL, 1984, Vol. 105. L. Packer (ed), Methods in Enzymology, Academic Press, New York, 1994, Vol. 233. E. Piva, S. De Toni, A. Caenazzo, M. Pradella, F. Pietrogrande, and M. Plebani, Neutrophil NADPH oxidase activity in chronic myeloproliferative and myelodysplastic diseases by microscopic and photometric assays. Acta Haematologica, 1996, 96(4), 264–265. R. K. Root and M. S. Cohen, The microbicidal mechanisms of human neutrophils and eosinophils. Reviews of Infectious Diseases, 1981, 3, 565–598. G. M. Rosen, S. Pou, C. L. Ramos, M. S. Cohen, and B. E. Britigan, Free radicals and phagocytic cells. FASEB Journal, 1995, 9, 200–209. A. J. Rosenspire, A. L. Kindzelskii, and H. R. Petty, Cutting edge: fever associated temperatures enhance neutrophil responses to lipopolysaccharide: a potential mechanism involving cell metabolism. Journal of Immunology, 2002, 169(10), 5396–5400.
PHAGOCYTE LUMINESCENT SENSOR 62. F. Rossi, The O2¨y-forming NADPH oxidase of the phagocytes: nature, mechanisms of activation and function. Biochimica et Biophysica Acta, 1986, 853, 65–89. 63. N. Sato, H. Shimizu, K. Suwa, Y. Shimomura, M. Mori, and I. Kobayashi, Myeloperoxidase activity and generation of active oxygen species in leukocytes from poorly controlled diabetic patients. Diabetes Care, 1992, 15, 1050–1052. 64. P. E. Stanley, Commercially available luminometers and imaging devices for low-light level measurements and kits and reagents utilizing bioluminescence or chemiluminescence: survey update 5. Journal of Bioluminescence and Chemiluminescence, 1997, 12(2), 61–78. 65. P. Stevens, D. J. Winston, and K. Van Dyke, In vitro evaluation of opsonic and cellular granulocyte function by luminol-dependent chemiluminescence: utility in patients with severe neutropenia and cellular deficiency states. Infection and Immunity, 1978, 22, 41–51. 66. D. L. Stevens, A. E. Bryant, J. Huffman, K. Thompson, and R. C. Allen, Analysis of circulating phagocyte activity measured by whole blood luminescence: correlations with clinical status. Journal of Infectious Diseases, 1994, 170(6), 1463–1472. 67. M. Suematsu, C. Oshio, S. Miura, and M. Tsuchiya, Real-time visualization of oxyradical burst from single neutrophil by using ultrasensitive video intensifier microscopy. Biochemical and Biophysical Research Communications, 1987, 149, 1106–1110. 68. M. Tarpey and I. Fridovich, Methods of detection of vascular reactive species: nitric oxide, superoxide, hydrogen peroxide, and peroxynitrite, Circulation Research, 2001, 89, 224–236. 69. M. Tuomala, M. R. Hirvonen, M. Holopainen, and K. Savolainen, Stimulation of human polymorphonuclear leukocytes by consecutive doses of quartz and interactions of quartz with fMLP. Toxicology and Applied Pharmacology, 1993, 118(2), 224–232. 70. P. van der Valk and C. J. Herman, Leukocyte functions. Laboratory Investigation, 1987, 56(2), 127–137.
19
71. K. Van Dyke (ed), Bioluminescence and Chemiluminescence: Instruments and Applications, CRC, Boca Raton, Florida, 1986, Vol. 1. 72. K. Van Dyke and V. Kastranova (eds), Cellular Chemiluminescence, CRC, Boca Raton, Florida, 1987, Vol. 1. 73. C. H. Wakefield, P. D. Carey, S. Foulds, J. R. Monson, P. J. Guillou, Polymorphonuclear leukocyte activation. An early marker of the postsurgical sepsis response. Archives of Surgery, 1993, 128(4), 390–395. 74. K. H. Western and V. Videm, Donor neutrophil function after plateletpheresis, Transfusion, 2000, 40(11), 1414–1418. 75. E. Wiener, Impaired phagocyte antibacterial effector functions in beta-thalassemia: a likely factor in the increased susceptibility to bacterial infections. Hematology, 2003, 8(1), 35–40. 76. J. M. Zgliczynski, E. Kwasnowska, T. Stelmaszynska, E. Olszowska, S. Olszowski, and J. M. Knapik, Functional states of neutrophils as suggested by whole blood chemiluminescence. Acta Biochimica Polonica, 1988, 35, 330–342. 77. G. A. Zimmerman, A. D. Renzetti, and H. R. Hill, Functional and metabolic activity of granulocytes from patients with adult respiratory distress syndrome. Evidence for activated neutrophils in the pulmonary circulation. The American Review of Respiratory Disease, 1983, 127, 290–300. 78. V. Calabrese, R. Bella, D. Testa, F. Spadaro, A. Scrofani, V. Rizza, and G. Pennisi, Increased cerebrospinal fluid and plasma levels of ultraweak chemiluminescence are associated with changes in the thiol pool and lipidsoluble fluorescence in multiple sclerosis: the pathogenic role of oxidative stress. Drugs under Experimental and Clinical Research, 1998, 24(3), 125–131. 79. I. Daniels, K. S. S. Bhatia, C. J. Porter, M. A. Lindsay, A. G. Morgan, R. P. Burden, and J. Fletcher, Hydrogen peroxide generation by polymorphonuclear leukocytes exposed to peritoneal dialysis effluent. Clinical And Diagnostic Laboratory Immunology, 1996, 3(6), 682–688.
31 Applications of the Electrogenerated Luminescent Reactions in Biosensor and Biochip Developments Christophe A. Marquette and Lo¨ıc J. Blum Laboratoire de G´enie Enzymatique et Biomol´eculaire, Universit´e Claude Bernard Lyon 1, Villeurbanne Cedex, France
Luminescent transitions of excited molecules or atoms to a state of lower energy are characterized by electromagnetic radiations dissipated as photons in the ultraviolet, visible, or near-infrared regions. These luminescent reactions are classified according to the energy source involved during the excitation step. Thus, the most classical lightemission reactions are referred to as bioluminescence (from in vivo systems), chemiluminescence (from a chemical reaction), electrogenerated luminescence (from an electrochemical reaction), and photoluminescence (from UV, visible, or nearIR radiations). More trivial reactions were also described as pyroluminescence (from flameexcited metal atoms), radioluminescence (from irradiation by x rays or γ rays), sonoluminescence (from ultrasonication of dissolved substance), and thermoluminescence (from solids subjected to mild heating). Luminescence measurements consist in monitoring the rate of production of photons and, thus, the light intensity depends on the rate of the luminescent reaction. Consequently, light intensity is directly proportional to the concentration of a limiting reactant involved in a luminescence reaction. With modern instrumentation, light can be measured at a very low level, and this allows the
development of very sensitive analytical methods based on these light-emitting reactions. Electrogenerated luminescence sensors have been developed with the aim of combining the sensitivity of light-emitting reactions with the convenience of sensors. Fiber optics associated with a sensitive light detector appeared to be convenient transducers for designing biosensors. In addition to these fiber optics–based sensors several luminescence analytical systems, including imaging systems and on-chip biosensing, have been described and are reported hereafter.
1 ELECTROGENERATED LUMINESCENT REACTIONS 1.1
Electrochemiluminescent (ECL) Reaction
Chemiluminescence reactions are generally oxidoreduction processes and the excited compound that is the reaction product, has a different chemical structure from the initial reactant. Several hundreds of organic and inorganic compounds are at the origin of chemiluminescence reactions, which can occur in liquid or solid phases, or at solid–liquid or solid–gas interfaces.1–3
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Here, electrochemiluminescence (ECL) refers to liquid phase light-emitting reactions based on the oxidation of 5-amino-2,3-dihydrophthalazine-1,4dione (luminol).4 Figure 1(a) shows the overall reactions in aqueous medium. The luminol oxidation leads to the formation of an aminophthalate ion in an excited state, which emits light when returning to the ground state. The quantum yield of the reaction is low (≈0.01) and the emission spectrum shows a maximum at 425 nm.5 The electrochemical oxidation of luminol is usually considered as the second most efficient way of triggering the reaction, behind the horseradish peroxidase (HRP) biocatalyzed one. In a mechanistic study of this ECL reaction, Sakura6 had proposed that luminol was first oxidized at the electrode surface and then reacted, mole to mole, with hydrogen peroxide (Figure 1a). The theoretical ratio:
H+, e–
Diazaquinone Luminol (LH–) + 425 mV vs Pt pH 8–9
Oxidant
Luminol endoperoxide
h n 425 nm N2 [3-Aminophthalate]
[3-Aminophthalate]*
I (µA)
(a) 3.5 3 2.5 2 1.5 1 0.5 0 −0.5 −1 0 (b)
0.2
0.4 0.6 E (V)
0.8
1
Figure 1. (a) Schematic representation of the electrocatalyzed chemiluminescent reaction and (b) a typical cyclic voltammogram of luminol in aqueous solution.
(photon produced)/(H2 O2 consumed) is then 1, while it is only 0.5 for the peroxidase-catalyzed reaction.
1.2
Electroluminescent (EL) Reactions
Electroluminescent (EL), here, refers to the electrogenerated oxidoreduction reactions of compounds, different from the luminol or luminol derivatives, leading to a photon emission. The main competitors to luminol ECL in the field of analytical chemistry are the ruthenium complexes7,8 and more generally the metal chelate systems. Nevertheless, other molecules such as 9,10-diphenylanthracene,9 phenothiazine,10 and pyrene11 were demonstrated as EL. One of the most attractive characteristics of these metal chelate complexes is their ability to be regenerated in their native form after having completed the light-emission reaction sequence. A single molecule could then theoretically generate more photons than the luminol in the destructive ECL. The most widely used and studied of these metal chelate complexes is the tris(2,2 bipyridyl)-ruthenium (II) also named Ru(bpy)3 2+ (Figure 2a). Indeed, since it was first reported as an EL compound in 1972,12 Ru(bpy)3 2+ has become the most thoroughly studied ELactive molecule.7,13 This domination of the field is mainly due to its strong luminescence, its solubility in both aqueous and nonaqueous media at room temperature, and of course its ability to undergo, as mentioned in the preceding text, reversible one-electron transfer reaction (Figure 2b). Figure 2(c) presents the most widely used system for triggering EL of Ru(bpy)3 2+ in aqueous solution. First, the ruthenium complex is electrooxidized in a one-electron reaction at the electrode surface (polarized at a potential between +1 and +1.5 V). Concomitantly, the classical coreagent tripropylamine (TPA)14 is also oxidized and deprotonated to generate a radical species that will reduce the oxidized metal complex (Ru(III)(bpy)3 3+ ), leading to an excited state of the reduced ruthenium complex that emits a photon (617 nm) while returning to the ground state.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS
3
0.8 0.6 2+ N N
N
2Cl−
I (µA)
0.4
Rh N
N
0.2 0 −0.2 −0.4
6H2O
−0.6
N
−0.8 0.5
0.7
(b)
(a)
0.9
1.1 E (V)
1.3
1.5
h ν 617 nm
Ru(II)(bpy)32+*
Ru(II)(bpy)32+
e− +1000∼1500 mV pH 7
e−
Ru(III)(bpy)33+ TPA
TPA.
TPA+
(c)
H+
Figure 2. (a) Structure of the tris(2,2 -bipyridyl)-ruthenium (II) also named Ru(bpy)3 2+ , (b) a typical cyclic voltammogram of the Ru(bpy)3 2+ in aqueous solution, and (c) schematic representation of the electroluminescent reaction of Ru(bpy)3 2+ with tripropylamine (TPA).
2 BIOSENSOR APPLICATIONS
The main interest of luminol ECL in biochemical and clinical analysis is the possibility of coupling this light-emitting reaction with enzyme-catalyzed reactions generating hydrogen peroxide. Simple auxiliary H2 O2 -generating reactions as well as multienzymatic systems leading to the production of hydrogen peroxide can then be used for the specific detection of different metabolites. Moreover, avoiding the use of fragile enzymes for the catalysis of the chemiluminescent reaction could lead to more stable and reproducible sensors. Consequently, regarding the sensitivity of hydrogen
peroxide detection, the electrogenerated chemiluminescence of luminol will be more efficient than the peroxidase-catalyzed reaction.15 Because of this high sensitivity for hydrogen peroxide, most of the applications of ECL will be dedicated to the detection of hydrogen peroxide-generating label enzymes and hydrogen peroxide enzymatic precursors. Less often, this electrogenerated reaction will be used for the detection of luminol-labeled molecules. On the contrary, the majority of the bioanalytical applications of the metal chelate complexes are based on the labeling of biomolecules with the complex itself. Indeed, by attachment of a suitable group to the bipyridine moieties, Ru(bpy)3 2+ can
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
be linked to biologically interesting molecules such as proteins or nucleic acids. The structures of three of these modified complexes are presented in Figure 3.
O
2+
OH OH O
N N
N Ru N
N N
(a) O
P
N(iPr)2 2+ CN
2.1
Enzyme-based Biosensors
2.1.1 Luminol-based Systems
As mentioned in the preceding text, an original and unusual way to obtain highly sensitive hydrogen peroxide detection is the ECL of luminol. On the basis of this electro-optical process, flow-injection analysis (FIA) H2 O2 sensors was developed.15–17 ECL was generated using a polarized glassy carbon electrode (GCE) versus a platinum pseudoreference electrode and integrated in a FIA system that could take advantage of the use of optical fibers to separate the detector and the flow system15,18–20 (Figure 4). The optimization of the reaction conditions showed that an applied potential of +425 mV versus a platinum pseudoreference electrode enabled the realization of a sensitive H2 O2 sensor while avoiding fouling of the working electrode. An optimum pH measurement of 9 was found and, moreover, the pH dependence of the ECL sensor
CH3
N
Detection system
N
N Ru N
N N
FO (b) 2+
O O O
FC
N
SL
O R
N N
N Ru
N
N N
(c)
Figure 3. Structures of (a) bifunctional Ru(bpy)3 2+ derivative, (b) TrisBipyidyl Ruthenium (TBR)-label used by Perkin– Elmer, and (c) label used by Igen (R=CH3 , Origen TAG-NHS Ester ) and Boehringer Mannheim (R=H).
Applied potential
GCE
Figure 4. Flow cell for electrochemiluminescence measurements. GCE: glassy carbon electrode; SL: sensing layer; FO: liquid-core single optical fiber.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS
appeared less pronounced than when using immobilized HRP as the sensing layer (SL). Under optimum conditions, hydrogen peroxide measurements could be performed in the range 1.5 pmol–30 nmol. This ECL H2 O2 sensor then exhibited slightly higher performances than membranebased HRP chemiluminescent FIA biosensors.21 For the development of glucose and lactate ECL FIA biosensors,15 the hydrogen peroxide ECL sensor could be associated with the catalytic action of glucose oxidase and lactate oxidase. The oxidases were immobilized on synthetic preactivated membranes brought into contact with the GCE. The glucose or lactate electro-optical biosensor was then able to detect the target analyte with detection limits of 150 and 60 pmol, respectively. In each case, glucose and lactate measurements could be performed over 4 decades of concentration. These biosensors were tested for glucose and lactate measurements in sera, and for lactate measurements in whey solutions. The agreement between the results of the present method and those of reference methods was good. For glucose analysis in serum, the coefficient of variation for 53 repeated measurements performed over a 10-h period was 4.8% while for lactate analysis, 80 assays performed over a 15-h period gave a coefficient of variation of 6.7%. Thus, the ECL-based biosensors gave the possibility to sensitively detect glucose and lactate in complex matrices without pretreatment of the samples. A flow-injection fiber-optic ECL biosensor for choline was also developed.19,20 Choline oxidase was immobilized by physical entrapment in a photo-cross-linkable poly(vinyl alcohol) polymer (PVA-SbQ) after adsorption on weak anionexchanger beads (diethylaminoethyl (DEAE)-Sepharose). In this way, the SL was directly created at the surface of the working GCE. The optimization of the reaction conditions and of the physicochemical parameters influencing the FIA biosensor response allows the measurement of choline concentration with a detection limit of 10 pmol. The DEAE-based system also exhibited a good operational stability since 160 repeated measurements of 3 nmol of choline could be performed with a variation coefficient of 4.5%. A cholesterol FIA biosensor has also been described as an application of the H2 O2 ECL sensor.18 In that work, the luminol ECL, previously studied in aqueous media, was implemented in
5
Veronal buffer added with 0.3% triton X-100 (v/v), 0.3% PEG, and 0.4% cholate to enable the solubilization of the cholesterol and then its efficient oxidation catalyzed by the immobilized cholesterol oxidase. The ECL reaction occurred, thus, in a micellar medium and the performances of the H2 O2 ECL sensor were investigated. The calibration curve obtained for hydrogen peroxide exhibited a detection limit of 30 pmol and ranged over 3 decades at least. These performances compared well with those previously obtained in nonmicellar media.16 The presence of surfactant compounds in the ECL measurement buffer appeared, thus, to have little effect on the H2 O2 ECL sensor performances. In optimized conditions, the determination of free cholesterol could be performed with a detection limit of 0.6 nmol and a calibration curve ranging over 2 decades of concentration at least.
2.1.2 Ru(bpy)3 2+ -based Systems
Most of the Ru(bpy)3 2+ applications in enzymebased biosensors involve dehydrogenase-type enzymes.22,23 A FIA detection method for glucose was presented which was based on oxidation of glucose by glucose dehydrogenase with concomitant conversion of NAD+ to nicotinamide adenine dinucleotide (NADH) followed by EL detection of NADH as a coreactant (Figure 5).22 Here, because the reduced form of NADH contains a tertiary amine, NADH can be used as a coreactant for Ru(bpy)3 2+ . The mechanism of the reaction of NADH with the ruthenium complex is then similar to that of the TPA/Ru(bpy)3 2+ mentioned in the preceding text. In a work from Martin et al., glucose dehydrogenase was immobilized via glutaraldehyde cross-linking to controlled pore glass beads bearing aminogroups to form an immobilized enzyme reactor used upstream to a platinum working electrode modified with Nafion film entrapping the EL reagent. Conditions for optimum enzyme reactor efficiency and EL detection were determined and reported for pH (about 6.51) and NAD+ concentration (l–2.5 mM). At the optimum conditions, a working curve was constructed where the upper limit for glucose detection was dependent on
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Substrate + NAD+
hn 617 nm
[Ru(bpy)32+]*
dehydrogenase
Product + NADH + H+
H+
NAD+ NAD•
Ru(bpy)32+
Ru(bpy)33+
NADH•+
e−
NADH
e− +1.5 V vs Ag/AgCl
Figure 5. Electroluminescence-based reaction mechanism for the detection of NAD+ dehydrogenase substrates. [Reprinted from Martin and Nieman22 , with permission from Elsevier.]
NAD+ concentration and the lower detection limit was 10 µM glucose. On the basis of a principle equivalent to the glucose EL biosensor presented in the preceding text, an FIA system was developed for ethanol.24 The electrogenerated luminescence of ruthenium tris(2,2 -bipyridine) was then used to detect a reduced form of NADH produced following the action of an immobilized alcohol dehydrogenase (ADH). The enzyme was used immobilized onto aminosilane modified glass beads packed in a column separated from the measurement flow cell. This latter was composed of a glassy carbon working electrode and a specially design stainless steel counterelectrode. The NADH determination was optimum under a flow rate of 1.5–2.0 ml min−1 and an applied voltage of +1.6 V. The NADH calibration plot showed a linear behavior in the concentration range from 10 to 250 µM, and the lower detection limit was 10 µM. Thus, using these optimized conditions, ethanol was detected in the FIA system as 0.01% (v/v) in buffer and with a detection ranging over 2 decades at least. Another interesting EL reaction based on Ru(bpy)3 2+ is described in Figure 6, where the coreactant of the metal complex is the oxalate (C2 O4 2− ).25 In this EL reaction, the oxalate is oxidized to form a strongly reducing carbon dioxide anion radical, which promotes Ru(bpy)3 2+ EL. In this case, the reaction occurring between oxalate
and hydrogen peroxide, leading to the production of water and CO2 , could be used to detect the presence of H2 O2 . Thus, this ability of the H2 O2 to diminish the oxalate-promoted EL was shown to be a possible basis for glucose detection using glucose oxidase.23 An inverse relationship was observed between glucose concentration and EL intensity but on a very narrow range, from 1 to 12 mM. Moreover, this system was not set up as a real biosensor, that is, including immobilized enzyme, and then consumed large quantities of reagent. Similar to the work presented above for the detection of glucose through oxalate/Ru(bpy)3 2+ EL, cholesterol has been detected using cholesterol oxidase.23 Again, a correlation between the EL intensity decrease and the cholesterol concentration was found on a limited range, from 2 to 10 mM.
2.2
Immunosensors
2.2.1 Luminol-based Systems
Luminol- and luminol-derivative-labeled antibodies16 are possible reagents for ECL immunosensors. Nevertheless, only few works were published with such labels,16,26 mainly because of the difficulties encountered when attempting to
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS Substrate + O2
oxidase
7
Product + H2O2
H2O + CO2
H2O2 + C2O42−
hn 617 nm CO2 C2O4• −
C2O42−
Ru(bpy)32+
CO2• − [Ru(bpy)32+]*
Ru(bpy)33+
Ru(bpy)33+
e−
Ru(bpy)32+
e− +1.5 V vs Ag/AgCl
Figure 6. Electroluminescence-based reaction mechanism for the detection of oxidase substrates through EL inhibition.
achieve their attachment through standard chemical reactions that retain the integrity of the protein. Indeed, the luminol molecule possesses only an aromatic amine as an available functional group, which is not easily covalently linked to biomolecules. Luminol derivatives having more reactive functions, such as N -(4-aminobutyl)N -ethylisoluminol (ABEI), were then tested as labels27 but were found to exhibit lower lightemission properties when grafted directly to proteins. Luminol-labeled antibodies were prepared using glutaraldehyde as a cross-linking agent and used in a 2,4-dichlorophenoxyacetic acid (2,4-D) competitive ECL immunosensor (Figure 7). 2,4-D was covalently immobilized at a GCE surface, via a 6-carbon spacer arm, by a procedure allowing to obtain stable immobilized antigens that could be then stored dry, used, and regenerated 50 times without loss of binding capacity. The luminol ECL detection was performed in an FIA system. The optimum conditions were found to be an oxidation potential of +500 mV versus a platinum
Glassy carbon electrode e− H2O2 Lu
hn 425 nm
O=C NH CH2
H2C H2C H2C NH H2C
CH2 CH2 C-O O Cl
Cl
Figure 7. Electrochemiluminescence-based immunosensor for 2,4-D using luminol-labeled antibodies and direct immobilization of the antigen at a glassy carbon electrode surface.
pseudoreference electrode, in the presence of 600 µM H2 O2 . Under these conditions, luminol could be detected in the range 5.5 fmol–55 nmol. Luminol-labeled anti-2,4-D antibodies were tested
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
for 2,4-D immunodetection. The corresponding ECL immunoassays exhibit a detection limit of 0.2 µg l−1 of free 2,4-D. The overall time taken for the experiment was 50 min and a linear range from 0.2 to 200 µg l−1 was obtained. Numerous works by Wilson et al.28–30 were published about the use of the ECL reaction of luminol for the achievement of immunosensors. These works were based on glucose oxidase–labeled antibodies used to locally generate the hydrogen peroxide required for the ECL reaction (Figure 8). Thus, antibodies to atrazine were labeled with glucose oxidase and used in enzyme-linked immunoassays.28 Transparent aminosilanized indium tin oxide (ITO)-coated glass electrodes were derivatized with aminodextran covalently modified with atrazine caproic acid. The labeled antibodies were used to investigate the derivatized electrodes in an ECL flow-injection analyzer. ECL immunoassay for atrazine in the range 0–1 µg l−1 showed that it was possible to detect the target molecule at concentrations as low as 0.1 µg l−1 . In a similar way, an ECL enzyme immunoassay for 2,4,6-trinitrotoluene (TNT) was reported.29 The deposition of a reusable immunosorbent dextran surface anchored to a gold surface in the flow cell by chemiadsorbed thiol groups was described as an SL. Antibodies were again labeled with the enzyme glucose oxidase and used in competitive immunoassays in which the separation step was carried out by concentrating unbound antibodies
H2O2
on the immunosorbent surface. Hydrogen peroxide generated by the enzyme label when glucose was pumped through the flow cell was then subsequently detected using luminol ECL. The light intensities obtained were inversely proportional to the concentration of TNT in the sample in the range 2.3–100 µg l−1 . More trivial electroassisted chemiluminescence enzyme immunoassays for TNT and pentaerythritol tetranitrate (PETN) were described.30 Haptens corresponding to these explosives were covalently attached to high-affinity dextran-coated paramagnetic beads. The beads were mixed with the corresponding Fab antibodies fragments and the sample. After adding HRP-labeled antispecies-specific antibody, the mixture was pumped into an electrochemiluminometer where beads were magnetically concentrated on the working electrode. The amount of analyte in the sample was determined by measuring light emission when H2 O2 was generated electrochemically in the presence of luminol and p-iodophenol (Figure 9). The detection limits obtained here for TNT and PETN were 0.11 and 19.8 µg l−1 , respectively.
hn 425 nm
Luminol
Horseradish peroxidase
Glucose
Glucose oxidase
O2
Magnetic bead
H2O2
hn 425 nm
Antigen coating
Luminol Antigen coating e−
ITO electrode
Figure 8. Electrochemiluminescence-based immunosensor for TNT using glucose oxidase as label and antigen-coated dextran-modified ITO.
Electrode Magnet
Figure 9. Electroassisted chemiluminescence-based immunosensor for TNT using horseradish peroxidase as a label and antigen-coated dextran-modified magnetic beads.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS
2.2.2 Ru(bpy)3 2+ -based Systems
Electroluminescence-based immunoassays use, in most cases, Ru(bpy)3 2+ as a label, which allows measurements in aqueous solutions at a pH optimal for immunoreactions. The nondestructive mechanism of the Ru(bpy)3 2+ ECL also enhances theoretically the signal intensity by producing more than one photon per label. A variety of different Ru(bpy)3 2+ -based labels were published and used for basic research or commercial applications. N-hydroxysuccinimide (NHS) esters of Ru(bpy)3 2+ are used as monofunctional31,32 and bifunctional derivatives (Figure 3).33–35 Monofunctional NHS esters are used in commercial analyzers such as Elecsys and Origen (Origen TAG-NHS Ester ). These particular derivatives offer the advantage of a spacer between the biomolecule and the label. They also have no tendency to cross-link the biomolecules compared with the bifunctional NHS ester. The large majority of the studies performed using Ru(bpy)3 2+ as a label were conducted with magnetic beads as the solid support, brought into contact with the necessary electrode only during the EL-triggering step (Figure 10). Indeed, EL instrumentations were developed on the basis of the use of photomultiplier tube, particularly by ORIGEN , to measure EL labels present at the surface of magnetically responsive beads. The beads were designed to be easily coated with either antibodies or antigen and act as a binding solid phase.36 Thus, sensitive detections of various biotoxins and bacterial spores using the commercial ORIGEN analyzer were achieved by capture Introduce the magnetic beads Capture of the beads bearing and the assay components the reacted components
9
on antibody-conjugated micron sized magnetic beads followed by binding of Ru(bpy)3 2+ -labeled secondary antibodies.31 Femtogram sensitivity levels were obtained for all biotoxins tested including botulinus A, cholera β subunit, ricin, and staphylococcal enterotoxoid B when using this immunomagnetic ECL approach. Assays for Bacillus anthracis spores were also successfully performed with a detection limit of at least 100 spores. Sensitive immunoassays for digoxin, thyrotropin, carcinoembryonic antigen, and α-fetoprotein were also developed using a similar system.37,38 ECL assays with Ru(bpy)3 2+ -derivatized antibodies or antigens were also achieved by performing the assay directly on an electrode surface.39 Biomolecules were immobilized onto disposable screen-printed (SP) gold electrodes via selfassembled monolayers of thiols or Fc-specific binding protein G. Finally, an alternative to the classical Ru(bpy)3 2+ EL reaction-triggering via TPA was proposed by Michel et al.40 The use of carbon interdigidated microelectrode arrays allowed a coreactant-free detection of labeled proteins via the annihilation reaction of Ru(bpy)3 + and Ru(bpy)3 3+ by redox-cycling. Nevertheless, up to now no specific applications were developed on the basis of such an electrochemical triggering system. 2.3
DNA Sensors
2.3.1 Luminol-based Systems
The luminol derivative ABEI was used to label a known oligonucleotide sequence, subsequently Applying the potential and measuring the EL signal
Photodetector
Electrode Magnet
Figure 10. Illustration of the process involved in EL analytical systems based on magnetic beads.
Release of the beads and wash out
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
used as a DNA probe for identifying a target single-stranded DNA.41 The developed system consisted of a platinum working electrode modified with electropolymerized polypyrrole. This electrogenerated polymer was used to immobilize the probe nucleic acid sequence, subsequently involved in the specific hybridization reaction. The hybridization events were evaluated by the ECL measurements of the ABEI-labeled, hybridized target sequence. The results showed that only a complementary sequence could form a double-stranded DNA with the DNA probe and give a strong ECL response, while a threebase mismatch sequence and a noncomplementary sequence gave no ECL signal. The intensity of the ECL was linearly related to the concentration of the complementary sequence in the range 9.6 × 10−11 –9.6 × 10−8 mol l−1 . Figure 11 depicts the configuration of a DNA detection system42 close to the system described above for the immunodetection of explosives by Wilson et al.—that is, based on electroassisted chemiluminescence. Nucleic acid probes were assembled on an Au-electrode using thiol-derivate sequences. The resulting monolayer-functionalized electrode was
hn 425 nm
Luminol
O2
H2 O2
e−
Gold electrode
Figure 11. Schematic representation of the detection of nucleic acid sequence through the electroassisted chemiluminescence. The red sphere represents the doxorubicin intercalator.
then treated with the complementary target sequence, leading to the double-stranded DNA assembly on the electrode surface. This hybridized system was further treated with doxorubicin, a well-known specific intercalator of doublestranded CG base-pair-containing DNA sequences.43 The electrochemical reduction of the intercalator led to the electrocatalyzed reduction of O2 to H2 O2 , which in the presence of luminol enabled the catalysis of the chemiluminescent reaction by the free HRP. This electroassisted chemiluminescent reaction then enabled the detection, down to picomolar levels, of the target nucleic acid sequence.
2.3.2 Ru(bpy)3 2+ -based Systems
Likewise for immunoassays based on the EL of ruthenium complexes, commercial instrumentation is available for the detection of DNA or messenger RNA by reverse transcription polymerase chain reaction (PCR) (QPCR System 5000 from Perkin–Elmer44,45 and the Origen Analyzer from Igen46 ). The PCR products are usually immobilized on a solid support (magnetic beads) using biotin–streptavidin chemistry and the DNA (RNA) targets are detected with a Ru(bpy)3 2+ label down to attomolar levels. In a recent publication, m-RNA isolated and amplified from as low as 10 melanoma cells, were detected in a background media composed of 107 cells.46 Other target genes were evaluated such as the human immunodeficiency virus 1 (HIV-1) gag gene31,47 and the cystic fibrosis F-508 deletion mutation.47,48 The results obtained from these assays demonstrated the possibility to detect 10 copies of the HIV-1 gag genes or cystic fibrosis F-508 mutations in 1 ng of human DNA. A more integrated approach for DNA detection was proposed by Xu et al.49,50 Here, singlestranded DNA were immobilized directly on aluminum(III) alkanebiphosphate–modified electrodes and used as a probe sequence for the hybridization of an Ru(bpy)2 2+ -labeled target. In this case, only simple poly(dT) sequences were used and detected specifically, as proof of concept.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS
(IDA) chelating beads (glucose oxidase only) or on DEAE anion-exchanger beads, and spotted on the surface of a glassy carbon foil (25 mm2 ) entrapped in PVA-SbQ photopolymer. The chip measurement was achieved by applying a +850 mV potential between the GCE and a platinum pseudoreference for 3 min, while capturing a numeric image of the multifunctional biosensing chip with a chargedcoupled device (CCD) camera. The use of luminol supporting beads (DEAESepharose) included in the SL was shown to enable the achievement of spatially well-defined signals and to solve the hydrogen peroxide parasite signal that appeared between contiguous spots using the free luminol found in the solution.51,52 The detection limits of the different biosensor were found to be 1 µM for glutamate, lysine, and uric acid, 20 µM for glucose, and 2 µM for choline and lactate. The detection ranges were 1–25 µM (uric acid), 1–0.5 µM (glutamate and lysine), 20–2 µM (glucose), and 2–0.2 µM (choline and lactate).
3 BIOCHIP APPLICATIONS
ECL and EL biochips presented here are either arrays of ECL or EL biosensors, or miniaturized biosensors integrating detector and/or microfluidics systems. The basis of the recognition and the biomolecules labeling are then equivalent to the methods described in the preceding text, and certain redundancies might appear.
3.1
11
Enzyme-based Biochips
3.1.1 Luminol-based Systems
A multifunctional biosensing chip was designed on the basis of the ECL detection of enzymatically produced hydrogen peroxide (Figure 12). Six different oxidases specific for choline, glucose, glutamate, lactate, lysine, and urate were noncovalently immobilized on iminodiacetic acid Sample Injection
Pt
W
S
Platinum pseudo-reference Analyte 1
hh n
Analyte 6
hhn Applied potential
GCE
H2O2 e−
H2O2
e−
Glassy carbon (a)
(b)
Figure 12. (a) Schematic representation of the sensing layer organization and reaction. The green sphere represents the luminol supporting beads. (b) Organization of the electrochemiluminescent multifunctional biosensing chip. GCE: glassy carbon electrode; Pt: platinum pseudoreference electrode; S: silicone spacer; W: Plexiglas window.
The ECL chip was used for the detection of glucose, lactate, and uric acid in human serum matrix. Good correlations between measured and expected values were found without the need of internal calibration of the sample, demonstrating the potential of the ECL multifunctional biosensing chip. This electrochemiluminescent biochip was extended to trienzymatic SL based on kinase-oxidase activities for the detection of acetate. A reaction sequence using acetate kinase, pyruvate kinase, and pyruvate oxidase was shown to enable the production of H2 O2 in response to acetate injection in the range of 10 µM–100 mM.53 On the basis of a similar entrapment concept of enzyme and luminol in PVA-SbQ photopolymer, a microarray of nine SP graphite electrodes (Figure 13a) was used to develop multiparametric ECL biochips.54 ECL cyclic-voltametric experiments were performed to characterize the ECL reaction triggered at the surface of the SP carbon electrode array and an optimum luminol oxidation potential of +650 mV versus platinum pseudoreference was found with a reproducibility of 4.4%. The different SLs were obtained through the entrapment of glucose oxidase, lactate oxidase, and choline oxidase in PVA-SbQ (poly(vinyl alcohol)-bearing styrylpyridinium groups) photopolymer deposited at the surface of three from the nine electrode arrays (Figure 13c). Therefore, ECL measurements were performed to establish calibration curves by using a CCD camera. In the present case, the achieved biosensor arrays
8, 4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
1
12
(a)
22, 3 Pseudoreference hn 425 nm
Analyte
Enzyme
Applied potential H2O2
Luminol
e−
(b)
Lox Gox Chox (c)
Glucose
Lactate
Choline
1 cm
Figure 13. (a) Schematic representation of an electrochemiluminescent active biochip based on screen-printed electrodes array, (b) principle of the electrochemiluminescent enzyme-based biochip, and (c) distribution of the different sensing layers at the biochip surface and electrochemiluminescent images of the biochip in the presence of either glucose, lactate, or choline. Chox: choline oxidase; Gox: glucose oxidase; Lox: lactate oxidase; Lu: luminol.
allowed the simultaneous detection and quantification of L-lactate, D-glucose, and choline with detection limits between 3 and 10 µM.
Working electrode Plexiglass Outlet
Inlet
SU-8 spacer
Silicon chip
Encapsulation epoxy Photodiodes
Printed-circuit board
Figure 14. Schematic representation of an integrated microfluidic electroluminescent silicon chip.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS
3.1.2 Ru(bpy)3 2+ -based Systems
The fabrication of a miniaturized silicon device integrating both the electrode and the photodetector was presented by Fiaccabrino et al.55 Thus, a 5 × 6 mm chip composed of two identical cells (one active and one reference) and two photodiodes for the differential measurements of the EL reaction was developed. An interdigidated gold electrode rested on each photodiode, only separated by a reflective layer. This device could detect the ruthenium complex with a detection limit of 0.5 µM. The same cell using a platinum interdigidated electrode instead of a gold electrode was used to detect codeine with immobilized Ru(bpy)3 2+ .56 Using SU-8 technology, the silicon device could be modified to create a flow cell57 (Figure 14). A polymer thickness of 300 µm resulted in a cell volume of about 2.25 µl and allowed the detection of ruthenium complex concentrations as low as 50 µM in FIA. In a modified system, glucose could be detected by coupling the EL flow cell with a microenzymatic reactor with a detection limit of 50 µM.58 A submicrolitre EL detector was also described by Arora et al.59 A flow cell with an effective volume of 100 nl containing two platinum thinfilm electrodes was produced with poly(methyl methacrylate) (PMMA) and placed directly on the window of a photomultiplier tube. A very low detection limit of 5 × 10−13 M was achieved for Ru(bpy)3 2+ but no biosensing applications were proposed.
3.2
Immunochips and DNA Chips
3.2.1 Luminol-based Systems
A new active support for ECL biochip preparation has been developed on the basis of graphitemodified polydimethyl siloxane elastomer (PDMS).60 The addressed inclusion of Sepharose beads at the surface of the obtained elastomeric electrode generated local highly specific surfaces. This electrode structure was characterized by electrochemical and imaging methods and an increase factor of the surface area equal to 50 was found. This was due to the texturing of the surface
Glucose
13
H2O2
Glucose oxidase
hn 425 nm
Luminol
Conducting elastomer
(a) Glucose
H 2O 2
Glucose oxidase
hn 425 nm
Luminol
Conducting elastomer
(b)
Figure 15. The different electrochemiluminescent biochip formats based on conducting elastomer. (a) Nucleic acid–based biochip and (b) immunobiochip.
generated by the presence of the Sepharose beads (Figure 15). This new material was used to design biochips based on the ECL reaction of luminol in the presence of enzymatically produced H2 O2 . Using beads bearing biomolecules such as oligonucleotides or antigen in conjunction with glucose oxidase–labeled DNA or antibody, sensitive
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
biochips could be obtained with detection limits of 1011 and 1010 molecules, respectively.
3.2.2 Ru(bpy)3 2+ -based Systems
The only real EL biochip platform based on the Ru(bpy)3 2+ electroluminescence was developed by Meso Scale Diagnostics. It is based on disposable electrodes, on which the assays are carried out, made of SP carbon ink and placed within
the wells of multiwell plates.61 A variety of plate formats are available (96, 384, and 1536) and particularly, the 96-well format could be obtained as multispot with a patterned microarray within each well (Figure 16). Thus, 4, 7, or 10 differentiated spots could be present at the same time at the bottom of a single well. The electroluminescence of the labeled proteins or nucleic acids is then triggered by the well-bottom graphite electrode and collected with either a CCD camera or a series of photodiodes. An example of multiple simultaneous
CCD imaging camera
hn 617 nm
hn 617 nm
e−
Rubpy
Antigen 1 coating
e−
Rubpy
Antigen 2 coating
hn 617 nm
e−
Rubpy
Antigen 3 coating
Screen-printed electrode (a)
(b)
96 wells: 4, 7, and 10 spots/well
Figure 16. Surface organization (a) of one of the Meso Scale Diagnostics plate well bottom for the EL detection of protein or DNA. Electroluminescent images (b) obtained with 4, 7, or 10 multiwalled 96-well plates.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS
assays within one well is show in Figure 16(a). Different antigens are immobilized in the different subwells and are subsequently recognized by different Ru(bpy)3 2+ -labeled antibodies from the sample. A large number of assays were performed on this platform, from ligand–receptor binding assays to kinase assays and DNA–protein binding assays. For example, multiplexed cytokine immunoassays were used to simultaneously detect four human cytokines (IL-1β, IL-6, TNF-α, and INF-γ ) with detection limits in the 1–10 pg ml−1 range. Peptide arrays were also developed with SH2 domains of EGF receptor to precisely determine the binding site of the protein on its receptor.
REFERENCES 1. U. Isacsson and G. Wettermark, Chemiluminescence in analytical chemistry. Analytica Chimica Acta, 1974, 68(2), 339–362. 2. D. H. Stedman and M. E. Fraser, Analytical Applications of Gas Phase Chemiluminescence, in Chemi-and Bioluminescence, J. G. Burr (ed), Marcel Dekker, New York, 1985, pp. 439–468. 3. L. J. Blum, Bio-,Chemi-Luminescent Sensors, World Scientific, Singapore, 1997. 4. G. P. Jirka, A. F. Martin, and T. A. Nieman, pH and concentration response surfaces for the luminol–H2 O2 electrogenerated chemiluminescence reaction. Analytica Chimica Acta, 1993, 284(2), 345–349. 5. D. F. Roswell and E. H. White, The Chemiluminescence of Luminol and Related Hydrazides, in Methods in Enzymology, S. Fleischer and B. Fleischer (eds), Academic Press, London, 1978, pp. 409–423. 6. S. Sakura, Electrochemiluminescence of hydrogen peroxide-luminol at a carbon electrode. Analytica Chimica Acta, 1992, 262(1), 49–57. 7. W.-Y. Lee, Tris(2,2-bipyridyl) ruthenium (II) electrogenerated chemiluminescence in analytical science. Mikrochimica Acta, 1997, 127(1–2), 19–39. 8. A. W. Knight and G. M. Greenway, Occurrence, mechanisms and analytical applications of electrogenerated chemiluminescence. A review. The Analyst, 1994, 119(5), 879–890. 9. F. E. Beideman and D. M. Hercules, Electrogenerated chemiluminescence from 9,10-diphenylanthracene cations reacting with radical anions. Journal of Physical Chemistry, 1979, 83(17), 2203–2209. 10. A. Kakhr, Y. Mugnier, and E. Laviron, Electrochemical reduction of phenothiazine and fluorobenzene at low temperature. Electrochimica Acta, 1983, 28(12), 1897–1898. 11. A. J. Bard, Electrogenerated Chemiluminescence, Marcel Dekker, New York, 2004.
15
12. N. E. Tokel and A. J. Bard, Electrogenerated chemiluminescence. IX. Electrochemistry and emission from systems containing tris(2,2 -bipyridine)ruthenium(II) dichloride. Journal of the American Chemical Society, 1972, 94(8), 2862–2863. 13. R. Wilson, H. Akhavan-Tafti, R. de Silva, and A. P. Schaap, Comparison between acridan ester, luminol, and ruthenium chelate electrochemiluminescence. Electroanalysis, 2001, 13(13), 1083–1092. 14. J. K. Leland and M. J. Powell, Electrogenerated chemiluminescence: an oxidative-reduction type ECL reaction sequence using tripropyl amine. Journal of the Electrochemical Society, 1990, 137(10), 3127–3131. 15. C. A. Marquette and L. J. Blum, Luminol electrochemiluminescence-based fibre optic biosensors for flow injection analysis of glucose and lactate in natural samples. Analytica Chimica Acta, 1999, 381, 1–10. 16. C. A. Marquette and L. J. Blum, Electrochemiluminescence of luminol for 2,4-D optical immunosensing in a flow injection analysis system. Sensors and Actuators, B: Chemical, 1998, 51, 100–106. 17. M. F. Laespada, J. P. Pavon, and B. M. Cordero, Electroluminescent detection of enzymatically generated hydrogen peroxide. Analytica Chimica Acta, 1996, 327(3), 253–260. 18. C. A. Marquette, S. Ravaud, and L. J. Blum, Luminol electrochemiluminescence-based biosensor for total cholesterol determination in natural samples. Analytical Letters, 2000, 33(9), 1779–1796. 19. V. C. Tsafack, C. A. Marquette, B. Leca, L. J. Blum, and V. C. Tsafack, An electrochemiluminescence-based fibre optic biosensor for choline flow injection analysis. The Analyst, 2000, 125(1), 151–155. 20. C. A. Marquette, B. D. Leca, and L. J. Blum, Electrogenerated chemiluminescence of luminol for oxidase-based fibre-optic biosensors. Luminescence, 2001, 16(2), 159–165. 21. L. J. Blum, Chemiluminescent flow injection analysis of glucose in drinks with a bienzyme fiberoptic biosensor. Enzyme and Microbial Technology, 1993, 15(5), 407–411. 22. A. F. Martin and T. A. Nieman, Glucose quantitation using an immobilized glucose dehydrogenase enzyme reactor and a tris(2,2 -bipyridyl) ruthenium(II) chemiluminescent sensor. Analytica Chimica Acta, 1993, 281(3), 475–481. 23. F. Jameison, R. I. Sanchez, L. Dong, J. K. Leland, D. Yost, and M. T. Martin, Electrochemiluminescencebased quantitation of classical clinical chemistry analytes. Analytical Chemistry, 1996, 68(8), 1298–1302. 24. I. Rubinstein, C. R. Martin, and A. J. Bard, Electrogenerated chemiluminescent determination of oxalate. Analytical Chemistry, 1983, 55(9), 1580–1582. 25. K. Yokoyama, S. Sasaki, K. Ikebukuro, T. Takeuchi, I. Karube, Y. Tokitsu, and Y. Masuda, Biosensing based on NADH detection coupled to electrogenerated chemiluminescence from ruthenium tris(2,2 -bipyridine). Talanta, 1994, 41(6), 1035–1040. 26. L. Dong and M. T. Martin, Enzyme-triggered formation of electrochemiluminescent ruthenium complexes. Analytical Biochemistry, 1996, 236(2), 344–347. 27. L. S. Hersh, W. P. Vann, and S. A. Wilheim, A luminol assisted competitive binding immunoassay of human
16
28.
29.
30.
31.
32.
33.
34.
35.
36.
37. 38.
39.
40.
41.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS immunoglobulinG. Analytical Biochemistry, 1979, 93, 267–271. R. Wilson, M. H. Barker, D. J. Schiffrin, and R. Abuknesha, Electrochemiluminescence flow injection immunoassay for atrazine. Biosensors and Bioelectronics, 1997, 12(4), 277–286. R. Wilson, C. Clavering, and A. Hutchinson, Electrochemiluminescence enzyme immunoassay for TNT. The Analyst, 2003, 128(5), 480–485. R. Wilson, C. Clavering, and A. Hutchinson, Electrochemiluminescence enzyme immunoassays for TNT and pentaerythritol tetranitrate. Analytical Chemistry, 2003, 75, 4244–4249. G. F. Blackburn, H. P. Shah, J. H. Kenten, J. Leland, R. A. Kamin, J. Link, J. Peterman, M. J. Powell, A. Shah, and D. B. Talley, Electrochemiluminescence detection for development of immunoassays and DNA probe assays for clinical diagnostics. Clinical Chemistry, 1991, 37(9), 1534–1539. J. H. Kenten, J. Casadei, J. Link, S. Lupold, J. Willey, M. Powell, A. Rees, and R. Massey, Rapid electrochemiluminescence assays of polymerase chain reaction products. Clinical Chemistry, 1991, 37(9), 1626–1632. A. W. Knight and G. M. Greenway, Relationship between structural attributes and observed electrogenerated chemiluminescence (ECL) activity of tertiary amines as potential analytes for the tris(2,2-bipyridine)ruthenium(II) ECL reaction: a review. The Analyst, 1996, 121(11), 101R–106R. E. Terpetschnig, H. Szmacinski, and J. R. Lakowicz, Fluorescence polarization immunoassay of a highmolecular-weight antigen based on a long-lifetime RuLigand complex. Analytical Biochemistry, 1995, 227(1), 140–147. E. Terpetschnig, H. Szmacinski, H. Malak, and J. R. Lakowicz, Metal-ligand complexes as a new class of longlived fluorophores for protein hydrodynamics. Biophysical Journal, 1995, 68(1), 342–350. M. C. Kibbey, D. MacAllan, and J. W. Karaszkiewicz, Novel electrochemiluminescent assays for drug discovery. Journal of the Association for Laboratory Automation, 2000, 5(1), 45–48. D. R. Deaver, A new non-isotopic detection system for immunoassays. Nature, 1995, 377(6551), 758–760. D. L. Gatto-Menking, H. Yu, J. G. Bruno, M. T. Goode, M. Miller, and A. W. Zulich, Sensitive detection of biotoxoids and bacterial spores using an immunomagnetic electrocheminescence sensor. Biosensors and Bioelectronics, 1995, 10(6–7), 501–507. K. F¨ahnrich, C. K. O’Sullivan, and G. G. Guilbault, Disposable Biosensor Based on Electrogenerated Chemiluminescence (ECL), In: Europt(r)ode V , Lyon, 2000, p. 149, 2000 April 16–19. P. E. Michel, N. F. de Rooij, M. Koudelka-Hep, K. A. Fahnrich, C. K. O’Sullivan, and G. G. Guilbault, Redox-cycling type electrochemiluminescence in aqueous medium. A new principle for the detection of proteins labeled with a ruthenium chelate. Journal of Electroanalytical Chemistry, 1999, 474(2), 192–194. M. Yang, C. Liu, K. Qian, P. He, and Y. Fang, Study on the electrochemiluminescence behavior of ABEI and its
42.
43. 44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
application in DNA hybridization analysis. The Analyst, 2002, 127(9), 1267–1271. F. Patolsky, E. Katz, and I. Willner, Amplified DNA Detection by electrogenerated biochemiluminescence and by the catalyzed precipitation of an insoluble product on electrodes in the presence of the doxorubicin intercalator. Angewandte Chemie International Edition, 2002, 41(18), 3398–3402. F. Arcamone, Doxorubicin: Anticancer Antibiotics, Academic Press, New York, 1983. A. M. Siddiqi, V. M. Jennings, M. R. Kidd, J. K. Actor, and R. L. Hunter, Evaluation of electrochemiluminescence-and bioluminescence-based assays for quantitating specific DNA. Journal of Clinical Laboratory Analysis, 1996, 10(6), 423–431. K. Motmans, J. Raus, and C. Vandevyver, Quantification of cytokine messenger RNA in transfected human T cells by RT-PCR and an automated electrochemiluminescencebased post-PCR detection system. Journal of Immunological Methods, 1996, 190(1), 107–116. C. D. O’Connell, A. Juhasz, C. Kuo, D. J. Reeder, and D. S. B. Hoon, Detection of tyrosinase mRNA in melanoma by reverse transcription-PCR and electrochemiluminescence. Clinical Chemistry, 1998, 44(6), 1161–1669. S. R. Gudibande, J. H. Kenten, J. Link, K. Friedman, and R. J. Massey, Rapid, non-separation electrochemiluminescent DNA hybridization assays for PCR products, using 3 -labelled oligonucleotide probes. Molecular and Cellular Probes, 1992, 6(6), 495–503. J. DiCesare, B. Grossman, E. Katz, E. Picozza, R. Ragusa, and T. Woudenberg, A high-sensitivity electrochemiluminescence-based detection system for automated PCR product quantitation. Biotechniques, 1993, 15(1), 152–157. X. Xu and A. J. Bard, Immobilization and hybridization of DNA on an aluminum(III) alkanebisphosphonate thin film with electrogenerated chemiluminescent detection. Journal of the American Chemical Society, 1995, 117(9), 2627–2631. X. Xu, H. C. Yang, T. E. Mallouk, and A. J. Bard, Immobilization of DNA on an aluminum(III) alkanebisphosphonate thin film with electrogenerated chemiluminescent detection. Journal of the American Chemical Society, 1994, 116(18), 8386–8387. C. A. Marquette and L. J. Blum, Self-containing reactant biochips for the electrochemiluminescent determination of glucose, lactate and choline. Sensors and Actuators, B: Chemical, 2003, 90(1–3), 112–117. C. A. Marquette, A. Degiuli, and L. J. Blum, Electrochemiluminescent biosensors array for the concomitant detection of choline, glucose, glutamate, lactate, lysine and urate. Biosensors and Bioelectronics, 2003, 19(5), 433–439. C. A. Marquette, D. Thomas, A. Degiuli, and L. J. Blum, Design of luminescent biochips based on enzyme, antibody, or DNA composite layers. Analytical and Bioanalytical Chemistry, 2003, 377(5), 922–928. B. P. Corgier, C. A. Marquette, and L. J. Blum, Screenprinted electrode microarray for electrochemiluminescent measurements. Analytica Chimica Acta, 2005, 538(1–2), 1–7.
APPLICATIONS OF THE ELECTROGENERATED LUMINESCENT REACTIONS 55. G. C. Fiaccabrino, N. F. de Rooij, and M. Koudelka-Hep, On-chip generation and detection of electrochemiluminescence. Analytica Chimica Acta, 1998, 359(3), 263–267. 56. P. E. Michel, P. D. van der Wal, G. C. Fiaccabrino, N. F. de Rooij, and M. Koudelka-Hep, Reagentless sensor integrating electrodes, photodetector, and immobilized Co-substrate for electrochemiluminescence-based assays. Electroanalysis, 1999, 11(18), 1361–1367. 57. P. E. Michel, G. C. Fiaccabrino, N. F. de Rooij, and M. Koudelka-Hep, Integrated sensor for continuous flow electrochemiluminescent measurements of codeine with different ruthenium complexes. Analytica Chimica Acta, 1999, 392(2–3), 95–103. 58. E. L’Hostis, P. E. Michel, G. C. Fiaccabrino, D. J. Strike, N. F. de Rooij, and M. Koudelka-Hep, Microreactor and electrochemical detectors fabricated using Si and EPON SU-8. Sensors and Actuators, B: Chemical, 2000, 64(1–3), 156–162. 59. A. Arora, A. J. de Mello, and A. Manz, Sub-microliter electrochemiluminescence detector—a model for small volume analysis systems. Analytical Communications, 1997, 34, 393–395. 60. C. A. Marquette and L. J. Blum, Conducting elastomer surface texturing: a path to electrode spotting: application
17
to the biochip production. Biosensors and Bioelectronics, 2004, 20(2), 197–203. 61. E. N. Glezer, K. Jonhson, J. D. Debad, M. Tsionsky, B. Jeffrey-Coker, C. Clinton, A. Kinshbaugh, J. K. Leland, M. Billadeau, S. Leytner, S. Altunata, G. B. Sigal, J. L. Wilbur, H. A. Biebuyck, and J. N. Wholstader, Electrochemiluminescent Microarrays: A New Tool for Drug Discovery and Life Science Research, In: 224th ACS National Meeting, Boston, 2002 August 18–22.
FURTHER READING M. L. Calvo-Munoz, A. Dupont-Filliard, M. Billon, S. Guillerez, G. Bidan, C. Marquette, and L. Blum, Detection of DNA hybridization by ABEI electrochemiluminescence in DNA-chip compatible assembly. Bioelectrochemistry, 2005, 66(1–2), 139–143. F. Patolsky, Y. Weizmann, and I. Willner, Redox-active nucleic-acid replica for the amplified bioelectrocatalytic detection of viral DNA. Journal of the American Chemical Society, 2002, 124(5), 770–772.
32 Dual Polarization Interferometry: A Real-Time Optical Technique for Measuring (Bio)molecular Orientation, Structure and Function at the Solid/Liquid Interface Graham H. Cross,1 Neville J. Freeman2 and Marcus J. Swann2 1
Department of Physics, Durham University, Durham, UK and 2 Farfield Scientific Ltd., Crewe, UK
1 INTRODUCTION
The challenging task of understanding and measuring the function of proteins and other biological molecules in all their structural and environmental complexity is one that has spawned a myriad of different techniques in the field of biological sciences. These span those providing exquisite detail in terms of molecular structure of a static system, such as X-ray crystallography or neutron reflection, to those providing dynamic measurements of protein function such as protein–protein interaction kinetics measured by some of the biosensing techniques covered in this handbook. Such measurements provide pieces of a jigsaw puzzle which need to be combined with others to provide a full picture. Of course, the function of any (bio)molecule is critically dependent on its environment, structure, and molecular arrangement. As such the ability to provide information linking these different areas is of fundamental interest.
Here we look at one such technique, dual polarization interferometry (DPI). This optical, surface analytical technique provides a multiparametric measurement of molecules at a surface to give information on molecular dimension (layer thickness) and packing (layer refractive index (RI), density) and surface loading and stoichiometry (mass). This combines the analytical nature of neutron reflection with the real-time, bench-top accessibility associated with biosensors and can be used to provide a link between a molecule’s structure and its function. This chapter puts DPI in the context of other multiparametric optical techniques, outlines the principles behind the technology and its implementation together with some simple examples to provide validation of the measurement. The basic experimental and data analysis methods are covered together with examples of areas of application of the technology specifically where structural information complements more conventional “mass” dependent measurement.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
The growth, metabolism, and replication of cells, the basic building blocks of life, depend very heavily on proteins. Proteins, while expressed within the cells themselves, perform a vast range of functions of both an intracellular and intercellular nature. The profile of expressed proteins within a cell depends upon the metabolic status of the cell, its age, and its local environment. Understanding the role that proteins play in the status of the cell is crucial to the understanding of the diseased state and is therefore of great importance within medical and pharmaceutical studies of disease. In order to understand the complex nature of protein function and the many different roles a protein may have, real-time measurements of proteins and their behavior is required. The structure of a protein is determined by its primary, secondary, and tertiary structures, the latter two being noncovalent in nature and a range of interactions contribute to the final structure such as hydrogen bonding, electrostatic interactions, and dispersion forces. These interactions occur between adjacent amino acid groups and may be mediated or altered by solvation, the ionic strength of the solution, and a range of other environmental factors such as pH or temperature. Measurement of the dimensions of a protein layer as a function of these variables can probe these factors, and a particular protein’s sensitivity. The dynamic nature of the secondary and tertiary structures of proteins enables them to undergo structural changes in response to stimuli which are often related to their functional roles. Structurally distinct regions within a protein are often associated with specific functions and these structures may be conserved to undertake similar functions across a range of different proteins. Finally, these individual peptides often interact with other peptides to perform specific functions or to provide structural integrity and this final structure of the protein is known as the quaternary structure. The shape of the protein, especially its external surface often provides pockets or clefts, which offer specific binding sites for small molecules or other proteins. Interaction with these sites is often described as “specific binding” and is associated with the activation or regulation of the activity of the protein. Probing the dimensional aspects of these interactions with other proteins, peptides, and other
ligands and small molecules can provide information about the specific nature of the interactions. For example, determining how the layer structure of an oriented immobilized protein changes on binding its partner can indicate the location on the protein at which the binding site resides. Indeed for protein–small molecule complexes, interactions can be dominated by structural or conformational changes. This is particularly relevant to the pharmaceutical industry. Small molecules may interact in a range of ways with a protein, dependent on the nature and number of the binding sites. Determining a structural signature for a small molecule binding can differentiate between different modes of interaction. These may include molecules binding to the same site with different degrees of specificity, whether they promote a specific conformational change or not and those binding to unrelated sites. The behavior of proteins at interfaces (e.g., surfaces) is of particular relevance. The first aspect of this, is that many biologically important processes are interfacial in nature, with for example, the interaction of molecules at membrane surfaces whether above, within, or across the membrane bilayer. Lipid layers and vesicles can be immobilized and quantified and their interactions then probed through both mass and structural changes. The second aspect relates to the many of the ways we use proteins, many of which require us either to immobilize them or to prevent them from being immobilized at a surface. So following the structural evolution during the construction of a protein surface to be used for example, as a diagnostic test can help understand the factors influencing the functioning or otherwise of the proteins within the immobilized assembly. Alternatively, the detailed characterization of a surface and its interaction with proteins can be a valuable tool to understand the mechanisms of biofouling or protein resistant surfaces. 2 TECHNOLOGY 2.1
Overview of Optical Techniques
Spectroscopic ellipsometry is the most familiar method by which the optogeometrical properties of thin films may be deduced.1,2 This technique analyzes the state of polarization of light reflecting from multilayer reflective samples and
DUAL POLARIZATION INTERFEROMETRY
uses the laws of electromagnetism (formulated as Maxwell’s equations applied to reflection and refraction at the layer interfaces) to resolve the layer thicknesses and RIs of the layers. The analysis requires the experimenter to choose a specific structural model from which the corresponding expected data may be calculated and to which the observed data may be compared via an error minimization process. There is, alongside this, an increasing interest in optical-guided wave techniques that are able to determine the average thickness and density of ultrathin layers that bind to an optical waveguide surface.3–6 In any optical waveguide structure, the light field is not wholly confined within the physical boundaries of the guiding medium but, rather, decays exponentially away from the boundaries. This part of the optical field is known as the evanescent (vanishing) field. If a layer is added to or removed from the original waveguide surface or an existing layer changes its thickness or density the position of the boundary at which the light begins this exponential decay is altered. Such changes alter the speed of propagation (“phase velocity”) of the whole field. Here, the measured changes to the phase velocity of optical fields probing the layers are interpreted through application of Maxwell’s equations to guided optical fields in multilayer samples. These developments follow on from the widely used and commercialized evanescent wave methods, notably surface plasmon resonance (SPR) spectroscopy,7,8 where the information provided is limited to the change in a mass-related parameter (resonance angle shift) at the optical surface as a function of time. Thus the measurement of the kinetics of molecular binding events (association and dissociation constants) and concentration measurements have been the two main applications for evanescent wave sensors until recently. While there is still a great need for such simple information obtained with the speed and sensitivity that evanescent wave methods offer, the variety of examples given in the preceding text require a greater degree of information to distinguish different possible behavior of the proteins being studied. Structural changes have been inferred from single parameter measurements, as for example, the observed “mass” response will be enhanced or suppressed by the effect of the conformational change. This can only be interpreted however
3
with a view to what the expected mass change should have been and there are too many potential contributions from other factors to make this a viable approach in general. Most instances can be attributed to effects such as binding-promoted surfactant adsorption/desorption or ion motion due to pI changes of the protein or related immobilization matrix effects. In short, a single measurement by evanescent wave techniques cannot be interpreted for layer structure with any confidence without some additional information. With low noise instrumentation, evanescent wave techniques have the capability to resolve layer dimensional changes at the sub-angstrom level and RI increments of 10−6 . Here we describe methods that use an additional independent evanescent wave measurement to remove these ambiguities (dual mode evanescent wave spectroscopy (DMEWS)). With dual mode evanescent wave methods, the capability inherent in spectroscopic ellipsometry is shared by the guided wave techniques, the layer model assumptions are similar but the methods of data analysis are distinctly different. While in ellipsometry the data is analyzed using a multiparameter model fit using the χ 2 statistic and its minimization, in guided wave methods the phase velocity change data is carried through directly to the layer parameters required to produce such a change. It will be important to remember however that all methods require the correct choice of model in order to be successful. We will concentrate on the experimental determination of the two optogeometrical parameters (average RI and thickness) of a uniform, isotropic thin film: In ellipsometry, the corresponding model system is a “three-phase” model.1,2 In an optical waveguide measurement we need two independent sources of experimental data. These might comprise a data pair taken from two evanescent fields at different optical wavelengths or, to reduce the uncertainty that optical dispersion might introduce two orthogonally polarized fields at a fixed wavelength. Although there are developments possible with the former, we will concentrate on the application of the latter method. Here one can distinguish between methods that rely on the measurement of modal phase matching conditions (resonance techniques) and reflectometry, and that implemented in DPI which relies on the interferometric detection of optical field phase changes.
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
In the coupled plasmon waveguide resonance (CPWR) technique9 the waveguide structure comprises a Kretschman-type SPR arrangement10 but with the addition of a thin low RI dielectric film (silicon dioxide) above the silver film. As in conventional SPR the interface between the metal and the emergent dielectric confines an optical field with transverse magnetic (TM) polarization. Light incident through the coupling prism is therefore polarized in the plane of incidence (“p” polarized.) However, this simple layer addition allows the combined system to also confine a transverse electric (TE) field which can be coupled to by incident light polarized orthogonal to the plane of incidence (“s” polarized). Each of the two modes has an electric field component (the evanescent field) whose amplitude decays exponentially, but at different rates, beyond the dielectric layer into the medium of interest. In experiments the incidence angle is scanned with high angular resolution and the reflected light intensity is measured around a range of angles spanning the angles of minimum reflection. At these coupling angles, the tangential phase velocity of light in the prism matches that of the waveguide field and the real part of the effective index of the structure may be related to the angle. Thus as layers are added to the system this “phase matching” condition changes and the resonance angle changes. From a full analysis of data taken from the reflection spectrum it is, in principle, possible to use transfer matrix methods11 and multiparameter fitting procedures to give the layer thickness and the RI and extinction coefficient for each of the two polarizations. One important example where this has been applied is to lipid bilayer systems where the optical properties normal to the bilayer are distinctly different to those in the layer plane.5 In optical waveguide light mode spectroscopy12,13 (OWLS), the waveguide structure is a simple slab waveguide into which light may be coupled using a grating to achieve phase matching. As in all such coupling methods, light entering the structure must have a tangential phase velocity (determined by coupling angle) equal to that of the optical waveguide field. The dielectric slab waveguide is designed to support fields (or “modes” from hereon) of each polarization, TE, and TM. At an appropriate angle of incident light when the phase matching condition is achieved,
the waveguide mode is excited and propagates light along to the waveguide end facet where it is collected by a photodiode and recorded. These angles will change according to changes above the original surface as described earlier. Since the TE and TM resonance angles are separated from each other, it is difficult to implement a system that can track the resonance minima of two such modes in real time. Thus for real-time studies the technique works by following the shift in resonance angle for a single polarization. Kinetic studies are therefore possible. The layer optogeometrical properties can however be extracted after the layer has bound by measuring the resonance shifts for both polarizations individually. These will provide the effective index changes for TE and TM polarized modes and using numerical solution of the eigenvalue equations for the waveguide system and making the assumption that the only unknown layer is uniform and isotropic its thickness and index can be found. In cases where this assumption is not strictly valid the thickness and RI data will have inaccuracies and the extent to which these might be introduced in OWLS and other studies has been examined by Mann.14
2.2
Dual Polarization Interferometry (DPI)
Interferometers comprise devices with two optical paths that detect the change in optical path length experienced by an optical field passing through the sensing path of the interferometer. Sensitivity is governed by, among other things, the interaction length and the signal-to-noise ratio of the detection scheme. Typically, integrated optical interferometers are configured in the Mach–Zehnder format15 by creating channel waveguiding regions in the top surface of an optical dielectric stack. DPI uses a much-simplified interferometer based on slab waveguides, with the reference slab waveguide buried beneath the sensing waveguide simply as part of the multilayer fabrication process (see Figure 1a). Coherent light broadly illuminates the stack end facet, exciting all possible modes (guided and radiation) in the structure but only the guided modes propagate more than 50 µm or so along the path.16 Upon exiting the structure (after 20 mm or so depending on sample length) the light from the two modes diffracts into free space. Because the
DUAL POLARIZATION INTERFEROMETRY
waveguides are so close together (only ∼4 µm apart) the diffracted wavefront generates the wellknown pattern of Young’s interference fringes in the far-field only a few millimeters from the end facet. Changes in the optical properties of the sensing waveguide (e.g., layer changes) translate into variations in the phase of the sensing mode field and then into interference pattern intensity shifts, as captured by a high-resolution camera. The optical tolerances are so forgiving that macroscopic movements of the input coupling beam on the order of hundreds of micrometers cause no change in the interference pattern. These loose tolerances
5
allow the stack to be inserted and removed from the optical train without precision alignment, an essential characteristic for a disposable measurement platform. The waveguide stack is designed so that both measurement and reference arm support single modes in both TE and TM polarizations, enabling two optical phase change measurements to be made and the polarization of the light is alternately switched on a 2-ms cycle using a ferroelectric liquid crystal rotator. Direct measurement of the phase change is obtained by continuously monitoring the relative phase position of the fringe pattern by performing Camera
Biological layer Fringe positions move as the biological layer is modified or altered
Sensing waveguide
Laser (light source)
Reference waveguide Output from both waveguides combine to generate interference fringes in the far field
(a) Response
Sensor response
Time
x
Polarization 1
x
Polarization 2
t Maxwell’s equations
Equivalent homogeneous layer Thickness
Polarization 2 Polarization 1 (b)
Absolute RI (density)
Figure 1. (a) Schematic diagram of a laser illuminated measurement chip, with fringes produced on the camera as the propagated light diffracts out of the end of the waveguides and interferes. [Reprinted with permission M J Swann et al., copyright 2004, Elsevier.] (b) Schematic diagram of the process of conversion of measured phase data to calculated layer thickness and refractive-index values. [Reprinted with permission from Farfield Scientific Ltd.]
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
a Fourier transformation relating intensity to position. The application of a standard transfer matrix approach provides evaluation of the guided modes for the structure. This allows inclusion of an arbitrary number of layers in a model, each of which is represented by its own layer matrix. Calibration of the bare chip using two liquids of known RIs as upper layers to generate TE and TM phase changes provides an initial structure (waveguide layer thicknesses and indices.) A successive approximation method provides the optimum refractive-index value and the thickness of the waveguide layer. Subsequent phase changes are analyzed similarly by including a model uniform isotropic thin layer on the surface of the waveguide (see Figure 1b) and resolving its properties (index and thickness). This calculated layer corresponds to the single homogeneous layer equivalent to the layer deposited experimentally. The layer density can be determined from the RI (see subsequent text) and knowing size and density, one can also trivially calculate the total mass, surface concentration, number of protein molecules, molecular footprint, and other useful parameters. Because experimentally, layers of different proteins or other materials can be deposited sequentially, it can sometimes be the case that a layer has been deposited which is not expected to change during the ongoing course of the experiment. This layer can then be incorporated as a fixed layer in the optical multilayer structure, and subsequent changes calculated as a new layer on top. Where this analysis does not produce realistic results, this can indicate the subsequent layer is either penetrating or expanding the sublayer. Where the assumption of a uniform isotropic layer is not valid alternative approaches can be used and have been applied successfully, for example, to lipid bilayer systems.
2.3
Experimental Setup
The measurement chip is located on a thermal block which is held at the preset temperature of between 10 and 40 ◦ C with a stability of ±2 mK. The illumination is provided by a 632.8 nm He–Ne laser. Running buffer or samples are exposed to the two fluidic channels of the measurement chip via a
fluidic manifold supplied by an high pressure liquid chromatography (HPLC)-type sample injection system driven by a syringe pump. The fluidics can be configured to allow a variety of sample volumes and viscosities to be introduced, and the sample flow may be maintained or stopped to allow samples to incubate on the chip surface. While experiments are generally undertaken in aqueous phase, most water miscible solvents can be used. The RI range for the running buffer is 1–1.49. For thin layers however there is no upper limit on the layer RI. Measurement chips are calibrated at the beginning of a measurement with solutions of known RI, typically 80% ethanol/water and pure water. This allows the sensitivity of the phase response and hence waveguide parameters to be calculated. Measurement of the phase change between the water and the running buffer also allows the RI of the buffer to be checked. These values are then used for the chip structure in the subsequent data analysis.
2.3.1 Typical Experimental Approach
Experiments usually start from either an unmodified silicon oxynitride chip, or using one that has been chemically modified with an alkoxysilane (mono)layer. Typical surface functionalities are amine, thiol, or hydrophobic—either trimethylsilane or octadecylsilane, from which a variety of immobilization methodologies may be employed. Proteins may be physisorbed, either via hydrophobic, hydrophilic, or electrostatic interaction, or can be coupled to the surface with a cross-linker. This may be direct covalent coupling with a bifunctional cross-linker, or via an intermediate coupling layer, such as via biotinylation of an amine chip, coupling of streptavidin followed by binding of a biotinylated protein. As much of the protein layer immobilization as possible is generally undertaken on the instrument this ensures that all layers can be properly quantified and the final surface structure can be accurately calculated from the measured phase shift starting from the initial bare or modified surface. Once the layer thickness and RI have been measured, values for the protein layer density, mass, molecular footprint and so on, can be calculated.
DUAL POLARIZATION INTERFEROMETRY
2.3.2 Typical System Performance
Experimentally observed errors are somewhat dependent on the nature of the layers being measured. For a typical protein monolayer the errors are shown in Table 1. In thickness the resolution equates to less than one-tenth of an atomic bond length. Where layers are very diffuse, or the layer thickness approaches the 1/e2 extent of the original evanescent field (∼100 nm for an aqueous system with layer RI < 1.40) these may be larger.
2.4
Data Analysis
The RI increments of proteins are quite consistent1,17,18 with typical values in the region of 0.186 g cm−3 and it is therefore possible to determine the mass of material deposited on the sensor surface in a similar way to that of de Feijter19 using equations (1) and (2) ρL =
ρp (nL − ns ) (np − ns )
mL = ρ L τ L
(1) (2)
where ρL is the adsorbed layer density, ρp is the protein density, nL is the adsorbed layer RI, np is the protein RI, ns is the solution (bulk) RI, mL is the mass loading per unit area, and τL is the adsorbed layer thickness. From the mass loading it is straightforward to calculate the area per molecule according to equation (3) Mw A= (3) N a mL where A is the area per molecule, Mw is the protein molecular weight, and Na is Avogadro’s number.
7
By using the measured values for the RI of the bulk solution the volume fraction of the layer occupied by protein (φp ) can also be calculated using equation (4): φp =
(n2L − n2s ) (n2p − n2s )
After calculation of the parameters described in the preceding text, it is possible to draw inferences not only regarding the gross structures of the deposited protein layers but also the likely orientation of the protein molecules within the layers.
2.5
Measurement Validation and Model Examples
Validation of the measurements has been made using a variety of methods, generally however the use of measurements of protein dimensions as a validation methodology should be used with caution, as proteins may conform significantly onto solid surfaces and this degree of deformation can itself be a function of protein surface loading. Comparative measurements of protein systems against other techniques have been made. cf. C receptor protein as a comparison with atomic force microscopy (AFM),20 bovine serum albumin (BSA) structures as compared with neutron reflection21 or streptavidin immobilized on a biotinylated surface22 and an antibody oriented on a protein G surface (shown subsequent text) compared with its X-ray crystallographic dimensions. In the two latter cases, where the comparative technique (X-ray crystallography) is not a surface method, the proteins are captured via a specific interaction which means that both are specifically
Table 1. Typical percentage CV in phase, temperature, and “resolved” layer values from DPI measurements
Parameter TM phase measurement Mass (ng mm−2 ) Thickness Density Temperature
Typical layer value
Accuracy (±)
8 rad 2 ng mm−2 5 nm 0.4 g cm−3 20 ◦ C
0.25% <1% 5% 5% 0.1 K
[Reprinted with permission from Farfield Scientific Ltd.]
(4)
Resolution (±) 0.8 mrad (0.01%) 0.2 pg mm−2 (0.01%) 0.01 nm (0.2%) 0.0004 g cm−3 (0.2%) 2 mK
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
oriented and also reduces the likelihood of deformation of the protein at the surface. Verification using well-defined nonprotein systems has used polymer layers or particulate adsorption. Comparisons using polymer multilayer deposition has been made to good effect, with dimensional measurements providing reasonable values from the very first layers at the nanometer level (where ellipsometry is not so reliable) to much thicker layers in the tens of nm and beyond, which agree very closely with values measured via ellipsometry.23
distinct regions where a sphere is adsorbed, and regions where no spheres are adsorbed. Above ∼17% coverage however a consistent value of the sphere layer thickness is obtained. In this case this is 29.9 ± 0.7 nm (n = 6), which compares with the manufacturer quoted sphere dimensions of 24 ± 4 nm for the batch, or 32.4 nm for the volume average measured by dynamic light scattering (DLS), with a number distribution peak at 24.4 ± 2 nm.
3 APPLICATIONS
2.5.1 Nanospheres
3.1
One example of measurements of a nonconformable particle is that of carboxylated polystyrene nanospheres. The spheres are available in a range of sizes (Invitrogen, Molecular Probes) and are negatively charged, and so physisorb via electrostatic interaction onto an amine functionalized chip surface in phosphate buffered saline solution (PBS). The packing density of the spheres can be varied by changing the pH of the experiment. The high charge on the spheres means that at pH 7.4 sphere–sphere repulsion limits the surface coverage, which increases as the pH is lowered. Figure 2 shows a plot of measured layer thickness versus coverage. There are two distinct regions to the plot. At very low coverage the thickness value is lower than expected. This is due to the layer being effectively inhomogeneous, with the light propagating in the waveguide between
Many biosensing technologies have been developed for the characterization of biomolecular interactions. The focus being almost exclusively that of determining interaction affinities and binding kinetics, as well as in some more limited cases thermodynamic aspects of the binding interaction. For these, a single binding related response is required. In the interests of brevity we do not focus on these aspects here, but give a few examples where structural measurements provide additional and complimentary information24 to that which might also be obtained by more conventional biosensor techniques such as SPR.
40 Thickness (nm)
35 30 25 20 15 10 5 0 0
2
4 6 Mass (ng mm−2)
8
10
Figure 2. Thickness versus mass (surface excess) of nominally 24-nm polystyrene nanospheres, physisorbed onto an amine chip in PBS, with pH adjusted between pH 2.8 and 4. [Reprinted with permission from Farfield Scientific Ltd.]
Biomolecular Interactions
3.1.1 Molecular Orientation
One structural aspect that can be determined as part of an interaction analysis is molecular orientation. Where the dimensions of a molecule are known, the layer thickness changes measured as part of an analysis can provide information on the orientation and binding site location on a protein. A model example is the binding of the Fc region of an antibody to protein G. Figure 3 shows the binding response for an IgG3 antibody onto an immobilized protein G layer. The final layer thickness for the antibody of 15.1 nm (when “resolved” to a fixed protein G layer) shows that the antibody is oriented vertically. This is close to the expected antibody dimension for the antibody being captured via the terminus of the Fc domain. DPI has been used to measure homopolyvalent antibody–antigen interaction kinetics25 as well as
DUAL POLARIZATION INTERFEROMETRY
9
12
1
0.8 0.7
8
0.6 6
0.5 0.4
4
0.3 0.2
2
0 1000
Density (g cm−3)
Mass (ng mm−2) and thickness (nm)
0.9 10
Mass Thickness Density
2000
3000
4000
5000
0.1
0 6000
Time (s) Figure 3. Mass, thickness, and density plot for an oriented IgG3 antibody immobilization. The data was calculated as a single homogeneous layer. The chip is thiol modified, in PBS running buffer. The sequence of sample injections are s-GMBS (1500 s), Protein G (2000 s), and IgG3 antibody (3250 s). [Reprinted with permission from Farfield Scientific Ltd.]
structural changes in polyclonal antibody layers on antigen binding26,27 where specific and nonspecific interactions can be discriminated on the basis of structural changes. A demonstration of the ability to use structural measurements to discriminate protein–protein interactions at different binding sites is the interaction of the cell surface protein CD6 with two antibodies specific to different domains on the CD6 molecule. CD6 is involved in regulating T lymphocytes and hence immune regulation. CD6 is a linear molecule containing three scavenger receptor cysteine rich (SRCR) domains, each one approximately 3.5 nm long. The antibodies antiCD6-D1 and anti-CD6-D3 bind to the first and third domains of CD6 respectively. In this experiment the CD6 is immobilized via a biotinylated two domain spacer (forming a molecule 17 nm long) to a streptavidin surface. The experimentally determined dimensions of the CD6 layer above the streptavidin (14–17 nm) shows that the molecule is oriented predominantly vertically. The structural responses of the two antibodies are very different and summarized subsequently in Figure 4. The antibody binding domain 1 causes a thickness increase and density decrease as it binds to the top
of the linear protein array. The antibody to domain 3 however causes the density to increase and the average layer thickness to decrease slightly. The measured antibody binding results using DPI are fully consistent with the expected binding of the antibody to the CD6 molecule with an orientation also confirmed by DPI. These results show clearly how structural data obtained as part of a functional measurement can discriminate the interaction of the antibodies with different binding sites on a protein: This data being fully additional to any affinity or kinetic type measurements that might be made, which provide qualitatively different data about the system. A literature example of the value of structural contributions to biomolecular interactions is the Apolipoprotein E (ApoE) isoprotein-specific interaction with tissue plasminogen activator (tPA), a protein that it modulates as part of the blood clotting cascade.28 ApoE is an important genetic risk factor for multiple neurological, vascular, and cardiovascular diseases. In this case while the mass of ApoE bound is similar, the thickness of the protein layer is substantially greater for the ApoE3 isoform than either E2 or E4. The protein layer density is also increased considerably after the
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Anti-CD6-D3
∆ Mass (ng mm−2) and density × 10 (g cm−3)
CD6 17-nm multidomain linear protein array
0.10 2.5 0.05
−0.05
∆ Mass (ng mm−2) and density × 10 (g cm−3)
0.15
Anti-CD6-D1
−2.5
−0.10 −0.15
(Biotin–steptavidin coupled)
0
0
Mass Density Thickness
−5
5
0.10 2.5 0.05 0 −0.05 −0.10 −0.15
∆ Thickness (nm)
5
0.15
0 −2.5
∆ Thickness (nm)
10
−5
Figure 4. Thickness mass and density changes for CD6 complex–antibody interactions and schematic representation of the binding event. [Reprinted with permission from Farfield Scientific Ltd.]
addition of ApoE2 whereas density was decreased with addition of ApoE3 or E4. These measured differences also reflect physiologically observed differences between the different phenotypes. ApoE has been linked to outcome and survival following acute injury of the central nervous system as well as the cardiovascular system.
3.2
Lipid and Membrane Studies
3.2.1 Introduction
Many important biological processes such as intraand intercellular signaling occur at membrane interfaces. Given that such processes are involved in many disease mechanisms, including cancer, the study of active components in the membrane is an area of intense research activity in both the academic sector and the biotechnology and pharmaceutical industries.29 Cellular membranes are complex, the bulk of the membrane “matrix” being made up of phospholipids assembled into a bilayer structure. The membrane contains a range of additional components such as cholesterol and proteins. The latter provide specific functions such
as transporting molecules across the membrane (e.g., signaling).30 The amphiphilic nature of phospholipids drives them to self assemble into structures which minimize hydrophobic–hydrophilic interactions. Thus in the cell membrane the lipids form a bilayer in which the tails of the lipid molecules are adjacent to each other leaving the hydrophilic head groups facing out on either side of the layer. Lying within this layer are the cholesterol and other components of the membrane. A wide range of studies have been carried out using biomimetic systems using single or mixed lipid systems with and without additional components such as cholesterol. The preparation of lipid structures is far from straightforward31–33 as a wide range of structural variation has been observed in the preparation of in vitro lipid systems. Depending upon the exact conditions of preparation, lipid cakes, rods, and/or vesicles may be formed in addition to supported bilayer structures. It is often difficult to assign, without ambiguity, the particular structures which have been generated in a given experiment. The ability to probe both the dimensions and the density of layer structures obtained using DPI can help to reduce this ambiguity.
DUAL POLARIZATION INTERFEROMETRY
Using simple geometric modeling it is possible to predict the likely surface characteristics that will be obtained when, for example, single bilayer wall (unilamellar) vesicles are deposited on a surface as opposed to double bilayer wall (bilamellar) vesicles are deposited on the waveguide surface. Thus the most likely lipid structures formed on the surface of the waveguide can be readily identified. Typical experimental protocols involve the hydration of the appropriate lipid/s followed by the formation of vesicles by sonication/surfactant depletion or extrusion. The resultant solutions are then flowed over the waveguide surface and the resultant surface layers measured. The waveguide surface was either used as is or modified as required. Hybrid bilayer membranes (HBM) can also be produced by flowing solutions of vesicles over waveguide surfaces which have been modified with for example, octadecylsilanes or decanoic acid surface.34 Whatever the selected method, the multiparametric measurement of the layers formed can be monitored in real time and related to the most likely structures obtained.
11
to investigate lipid structures. Free standing lipid vesicles can be simply constructed on a waveguide surface by perfusing lipid vesicle solutions and an example is given in Figure 5. Lipid vesicles may be formed from multiple bilayer structures, being unilamellar, bilamellar, trilamellar, or greater. It is however difficult to elucidate the number of lamellae within the vesicle, often requiring the use of cryotransmission electron microscopy to unambiguously determine the structure. The dimensions and density of the layers formed provides information on the likely structures obtained. Taking the example of DSPA, the layer characteristics can be compared with calculated layer characteristics in order to elucidate the likely vesicle structures can be demonstrated. In Table 2 the observed characteristics of the DSPA lipid vesicle layer are compared with the predicted characteristics. It is clear that the layer characteristics are most consistent with a multilamellar vesicle which is effectively a “solid onion” structure. 3.2.3 Liposome–Peptide Interactions
3.2.2 Structures – Lipid Vesicle Structures
DPI has been used to study a number of peptides associating with membranes, including antimicrobial peptide V4, and duramycin. Taking the example of melittin, a small peptide which is a component of bee venom. It is known to disrupt certain
90
1.45
80
1.44
70
1.43 1.42
60
1.41
50
Thickness
40
1.4
Mass Refractive index
30
1.39 1.38
20
1.37
10
1.36
0
Refractive index
Thickness (nm) and mass (ng mm−2)
DPI has been used to study a wide range of phospolipids. 1,2-distearoyl-sn-glycerol-3-phosphatidic acid (DSPA) will be used to demonstrate the utility of DPI and simple modeling
1.35 0
240
480
720
960 1200 1440 1680 1920 2160 2400 2640 2880 Times (s)
Figure 5. Thickness, refractive index, and mass of a layer of DSPA liposomes added to an unmodified, silicon oxynitride surface at a flow rate of 25 µl m−1 in PBS. [Reproduced from Popplewell et al.35 . BBA Membranes.]
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Table 2. Calculated and observed thickness and refractive-index values for a spherical DSPA multilamellar liposome (in this case the lamellae exceed six in number and there is no distortion)
Observed (DLS) Observed (DPI) Calculated
Number of lamellae(a)
Thickness (nm)
Refractive index
Longitudinal axis (nm)
Equatorial axis (nm)
1 3 6 Solid
79 (±20) 87 (±9) 87 87 87 87
n/a 1.405 1.355 1.384 1.396 1.404
87 87 87 87 87 87
n/a n/a 87 87 87 87
(a)
Assuming 100% layer coverage. [Reprinted with permission from Farfield Scientific Ltd.]
classes of lipid structure. The mechanism by which this disruption occurs is still a matter of debate and DPI has been used to examine aspects of melittin–lipid bilayer interactions. Melittin is amphipathetic, the n-terminus carrying hydrophobic amino acid residues while the c-terminus carries predominantly hydrophilic residues and is highly positively charged (carrying 6 positive charges). The influence of melittin on a 1,2-dioleoyl-snglycero-3-phosphocholine (DOPC) lipid vesicle layer is shown in Figure 6. Melittin was perfused over the stable vesicle layer commencing at 19 760 s. Initially the layer is seen to increase in
mass, density, and dimensions as melittin binds to the external surface of the vesicles. During the initial 30 s the layer dimension holds at circa 20 nm which is consistent with the maintained integrity of the vesicles. However after 30 s there is a rapid decrease in the dimensions and mass of the layer and a concomitant increase in the density. The final dimensions of the layer are consistent with a single supported bilayer on the surface of the waveguide. Further insights into the mechanism of action were elucidated by examining layer structure change obtained with lipid vesicles constituted with different lipids (varying the charge and TM) 1.45
24
1.44
20 1.43
18
1.42
16 14
Thickness Mass
12
RI
10
1.41 1.4 1.39
8 6
Refractive index
Thickness (nm) and mass (ng mm−2)
22
1.38
4 1.37
2
1.36
0
19 700 19 730 19 760 19 790 19 820 19 850 19 880 19 910 19 940 19 970 20 000 Time (s)
Figure 6. The effect of an injection of melittin (0.5 mg ml−1 ) on the dimensions of an immobilized layer of DOPC liposomes. On addition of melittin there is an initial increase in refractive index, mass, and thickness as the melittin associates with DOPC, followed by a rapid decrease in both mass and thickness as the liposome ruptures. [Reproduced from Popplewell et al.35 . BBA Membranes.]
DUAL POLARIZATION INTERFEROMETRY
and examining the stoichiometry which leads to vesicle rupture (found to be approximately 1 melittin:6 outer hemilayer lipid molecules).35
3.3
Protein – Small Molecule Interactions
3.3.1 Introduction
The measurement of interactions of proteins with small molecules (compounds and small peptides under 1000 Da) is an area that is both challenging and of significant commercial interest. The main driving force is from the drug discovery process, where measurements can support many areas from target identification, ligand fishing, assay development, and lead selection through to early absorption, distribution, metabolism, excretion (ADME) and manufacturing quality control.36 Measurements in these areas require a high degree of sensitivity and can be greatly affected by changes in buffer condition (drug compounds often being stored in dimethyl sulfoxide (DMSO)). There are two aspects in which structural measurement in conjunction with probes of molecular function can be obtained with DPI measurements. This is in the direct measurement of conformational change related to a binding process, and the other is a structurally significant binding event. The first of these may be demonstrated with the model system streptavidin–biotin,26 while the second is exemplified by the binding of cortisol by anticortisol. In both cases, changes in the average layer structure (thickness and RI) can be related to a particular binding event. This provides a method for the characterization of small (drug) molecule interactions, where a plot of the percentage density change in the protein molecule versus the percentage thickness change can act as a classification method for a particular binding mode that uses the structural changes that a molecule elicits rather than (or as well as) the more conventional extent versus affinity plot (cf. Figure 4 in Ref. 36). 3.3.2 Antihydrocortisone – Hydrocortisone Interaction
The affinity plot for a hydrocortisone antibody based on thickness change is shown in Figure 7(a).
13
These can be plotted from RI or density as well as mass changes. The antibody layer had been immobilized in an oriented manner using protein G, and the dimensional measurements confirmed this (Antibody layer Th = 15.1 nm). The size/density plot for this interaction is shown in Figure 7(b). Here the thickness increases and the density decreases. This is a structurally significant response giving a large structural change. The antibody is immobilized in an oriented fashion on protein G, and the response reflects the hydrocortisone binding at the terminal binding sites on the Fab fragments at the top of the oriented antibody. The figure shows all the concentration data, which lie on the same radial line. This shows that in principle the structural effect of a small molecule can be determined from a single concentration sample. For comparison note the response of streptavidin to biotin, Figure 7(c), where the tight binding results in a conformational tightening which is also born out by X-ray data.26 3.4
Metal Ion Interactions
3.4.1 Introduction
Many proteins have their function mediated by concentrations of cations in solution; so the body controls levels of protons, sodium, and potassium across cell membranes. Similarly, divalent cations such as calcium modulate the activity of many different proteins. Measuring the interactions of specific ions with proteins is a challenging task, as the mass changes are often vanishingly small. Often, structural changes are more significant, but again prove difficult to identify. DPI has been used to measure the structural and mass changes of a number of proteins as a function of metal ion concentration. These include calmodulin (Ca2+ ), prion protein (Cu2+ , Mn2+ , Zn2+ , Fe2+ , Mg2+ , Ni2+ ), human serum albumin, HSA (Cu2+ , Ni2+ ), BSA (Ni2+ ), β-Amyloid (Cu2+ , Mg2+ ). Here as an example we show the response of tissue transglutaminase, which binds calcium ions.37 3.4.2 Transglutaminase – Calcium Ion Binding
Transglutaminases are catalysts involved in the post-translational modification of proteins, forming isopeptide bonds at glutamine residues. This
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 2 Hydrocortisone Structure axis Mass axis Linear (hydrocortisone)
1.5 2 1
1.6
% Thickness change
% Thickness change (nm)
1.8 1.4 1.2 1 0.8 0.6 0.4
0.5
−2
−1.5
−1
−0.5
0
0.5
1
1.5
2
−0.5
Data (-bulk) Fit
0.2
0
−1
0 0
5
10
15
20
25
−1.5
Hydrocortisone concentration (µM) −2 (a)
% Density change
(b)
2.5
1.5
% Density change −3.5
−2.5
−1.5
% Thickness change
3.5 Structure axis
Mass axis
0.5 −0.5 −0.5
0.5
1.5
2.5
3.5
Conformational change
−1.5 −2.5
Mass change
−3.5 (c)
Figure 7. (a) Binding curve for hydrocortisone and antihydrocortisone. Affinity fit 0.28 µM. The antibody was immobilized on a thiol chip via s-GMBS and protein G. The hydrocortisone was diluted from a stock DMSO solution, and the response corrected for the bulk RI contribution from the DMSO. (b) Size/density plot for hydrocortisone/antihydrocortisone interaction. The individual points correspond to concentration injections of 0.1–22.5 µM hydrocortisone. (c) Size/density matrix plot of the conformational change for streptavidin binding biotin (SA immobilized on a biotinylated amine chip). [Reprinted with permission from Farfield Scientific Ltd.]
activity has been shown to be modulated by calcium and guanosine 5 -triphosphate (GTP). This modulation is thought to be related to putative conformational changes induced by the modulators. Indirect analysis using shallow angle neutron scattering (SANS) and shallow angle X-ray scattering (SAXS) and circular dichroism spectroscopy have suggested that there is a significant
increase of 0.8 nm in the gyration radius of the protein on binding calcium suggesting a significant broadening of the protein structure on binding. Efforts to elucidate conformational changes directly from crystallographic data have not been successful. Reports on optical measurements of transglutaminase on the addition of calcium have also been reported in which anomalies in the
DUAL POLARIZATION INTERFEROMETRY
RI change
expected responses have been attributed to likely conformational changes in the protein on binding calcium. Using DPI it has been possible to measure the conformational changes associated with calcium binding directly. The protein was immobilized to an amine functionalized sensor surface via free external amine groups using BS3 . A thickness increase of 5 nm was observed which demonstrates that the disc shaped molecule (approximately 15 nm in diameter and 5 nm thick) had been immobilized face parallel to the chip surface as might be expected. Once the protein surface had been created, it was challenged with different concentrations of calcium chloride and chloride mol equivalents of sodium chloride. On binding calcium, the transglutaminase undergoes significant conformational changes with a thickness contraction of 0.4 nm. The RI changes as a function of calcium concentration are shown in Figure 8. The experiment can be performed and analyzed in a number of ways. The data in Figure 8 is obtained by analyzing a single channel, and using the sodium injections as a control for changes due to ionic strength and bulk RI. The affinity constant has been calculated to be 1.16 mM which compares well with the range of literature values for the interaction which span the range 0.2–3.0 mM. An alternative method of data analysis uses the data obtained on the control channel (a surface treated in the same way, but without the protein) as a control subtraction.37 This produces a very similar result with affinity calculated at 0.95 mM.
15
This clearly suggests that the structural changes observed are directly related to the binding of calcium.
3.5
Biomolecular Stability and Structure
3.5.1 Introduction
Understanding biomolecular structure and stability at surfaces is important in a wide range of applications from the optimization and quality control of diagnostic devices to the functionalization of surfaces of materials such as contact lenses which are prone to biofouling to the preparation of medical implants which are in contact with the body for extended periods of time. For biocompatible devices, the fate of protein structure at the surface is critical in terms of the viability of medical devices and their ability to function normally. In many cases the forces which proteins are exposed to at surfaces are sufficient to disrupt the tertiary and quaternary structure leading to compromised functional capability, the mobilization of the immune system, and ultimately to rejection. In the case of diagnostic or sensing devices, the structure of proteins and other molecules at a surface will have a significant effect on the device’s functionality. DPI has been used to examine a number of key aspects in the determination of the fate of protein at surfaces under different environmental conditions. 3.5.2 Surface Development/immobilization
0.0045 0.004 0.0035 0.003 0.0025 0.002 0.0015 0.001 0.0005 0
Data (ca–Na) Fit
0
5
10
15
20
25
30
35
Calcium ion concentration (mM)
Figure 8. Plot of RI change as a function of calcium ion concentration. The data has been corrected for ion charging and bulk refractive-index effects by subtraction of the response from NaCl injections at the same ionic strength. Calcium ion affinity 1.16 mM. [Reprinted with permission from Farfield Scientific Ltd.]
The orientation of antibodies on a solid surface has a significant effect on the overall activity of the molecule. Antibodies have two “arms” (see Figure 9a) which are implicated in the capture of antigens and if these are too restricted either as a consequence of lying on the surface or due to steric crowding of neighboring molecules the activity of the antibody will be compromised or extinguished altogether. Therefore obtaining information on the orientation of immobilized antibodies and factors effecting the orientation during the immobilization process are of great interest. A study of such processes has been undertaken using DPI. A range of immobilization strategies were employed and the resulting structures
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 7 nm
5 nm 3 – 6 nm
(b) 15 nm
9 –15 nm
(a)
(c)
Figure 9. (a) Molecular structure of an IgG3 antibody with approximate dimensions; (b) Typical surface obtained when using amine coupling chemistry (inactive); (c) Typical surface obtained when using protein G coupling strategy (active). [Reprinted with permission from Farfield Scientific Ltd.]
and activities measured. Typically, when crude immobilization strategies are used layer dimensions of 7 nm or less are observed. Antibody layers which are 6 nm or less are on the whole inactive or severely compromised. Generally when antibody layers have dimensions which are greater than 7 nm (and from mass calculations have an appropriate area per molecule to indicate a monolayer) the antibody is likely to be active. Examples of antibody layers obtained and their activities post immobilization are provided in Table 3.
Similarly, DPI has also been used for assessing immobilization strategies for DNA sensing surfaces.38,39 This is a particularly challenging area due to the high charge on the DNA backbone making accessible orientation of the DNA molecule difficult to achieve.
3.5.3 Environmental Effects
Proteins undergo substantial structural changes as a consequence of their local environment. Some
Table 3. Examples of antibody immobilization strategies, dimensions of layers obtained, and resulting activities to respective antigens
Antibody
Type
Ovalbumin HSA Bi-ProBNP
IgG1 Poly
BSA
IgG1
Cortisol (1)
IgG3
Cortisol (2)
IgG3
PrP
IgG2a
Immobilization −NH2 , BS3 −NH2 , BS3 −NH2 , SA, s-NHS-LC Biotin, −NH2 , BS3 , Protein G −NH2 , BS3 , Protein G −SH, s-GMBS, Protein G −SH, s-GMBS, Protein G
Antibody layer (nm)
Activity
Antigen (MWt)
Thickness (nm)
3.3 6.4 6.7
Inactive Active 1:1 Active 1:1
5000 67 000 8000
None Positive Negative
6.0
Inactive
66 000
None
9.0
Active 2:1
362
Positive
15.1
Active 2:1
362
Positive
11.2
Active 1:6
24 000
Positive/none
HSA: human serum albumin; BSA: bovine serum albumin; BS3 :bis(sulphosuccinimydyl) suberate; ProBNP: precursor of brain natriuretic peptide; PrP: prion protein. [Reprinted with permission from Farfield Scientific Ltd.]
DUAL POLARIZATION INTERFEROMETRY
17
Table 4. pH cycling profile low-high-low with lysozyme concentration fixed at 1.0 g dm−3
pH
Layer thickness ˚ ± 1) (A
Refractive index (±0.001)
Mass loading (mg m−2 ± 0.05)
Area per molecule ˚ 2) (A
Protein volume fraction (±0.001)
4 7 4
25 49 37
1.401 1.443 1.431
0.89 2.91 2.01
2733 ± 100 832 ± 50 1208 ± 60
0.343 ± 0.001 0.568 ± 0.001 0.520 ± 0.001
[Reprinted with permission Freeman et al.41 2004 American Chemical Society.]
changes will be in order to render the protein active/inactive such as the binding of specific metal ions, changes in pH and so on, while other changes will be irreversible (denaturation) typically as a consequence of excessive heat. Studies of structural changes as a consequence of environmental changes have been undertaken using DPI, such as the pH dependent adsorption of BSA.21
reorient themselves long axis normal to the waveguide surface. This change in behavior is probably due to the reduced electrostatic repulsions at higher pH between neighboring lysozyme molecules on the waveguide surface. Changes in the adlayer structure when the pH is cycled between pH 4 and 7 are shown in Table 4.
3.5.5 Protein Surfactant Structures
Lysozyme adsorption at the silica water interface is another extensively investigated model system. The behavior of the protein at the interface has been studied primarily using neutron reflection techniques and ellipsometry. These studies were, in the main carried out using pure silicon dioxide surfaces40 whereas the waveguide surfaces used in typical DPI experiments are lightly doped with nitride. In addition DPI experiments were carried out using a flow through cell arrangement rather than the static fluidic systems preferred by previous experimenters. Despite these differences, correlations between data from these analytical techniques are extremely good.41 The lysozyme was prepared in two pH buffer solutions and at the desired concentrations and flowed over the waveguide surface at a constant flow rate (50 µl min−1 per channel). The layer characteristics obtained were measured using DPI in real time (measurement frequency 0.1 s) and compared with available published data. At pH 4 there is a considerable amount of positive charge on the lysozyme molecules and the adlayers obtained are relatively sparse, the molecules probably lying with their short axes normal to the mildly negatively charged waveguide surface. At pH 7 the layers obtained at low concentration also appear go down on to the surface short axis normal but at higher concentrations appear to
The behavior of surfactants used to prevent protein aggregation (Tween ) have been studied at the waveguide surface. Comparing the properties of the Tween series we find that the head groups are large relative to the hydrophobic tail groups and are of a similar size. Moving from Tween 20 through 60 the saturated alkyl tails extend in length while Tween 80 has a single carbon–carbon double bond in it (increasing the molecular fluidity).42 It can be seen from Figure 10 that the thickness of the adlayer is directly proportional to the hydrophilicity of the molecules involved. Thus, regardless of the size of the molecule involved, 3
Tw20
[C] / CMC = 2.0
2.5 Thickness
3.5.4 Lysozyme
2 Tw40
1.5 Tw60
Tw80
1 0.5 0 14.5
15
15.5
16
16.5
17
Hydrophilic lipophilic balance Figure 10. Thickness versus hydrophilic lipophilic balance (HLB) for the series of Tween 20–80 surfactants at [C]/CMC of 2.0. [Reprinted with permission from Farfield Scientific Ltd.]
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
it appears to be the energetics of solvation in water that ultimately determine the structures of the adlayers on the surface of the waveguide. Thus the most hydrophilic molecule Tween 20 forms the thickest and most diffuse adlayer while Tween 80 forms the thinnest densest adlayer. 4 FUTURE DEVELOPMENTS
The optical waveguide device can be considered to be an optical bench. As such, a wide variety of optical experiments can, in principle, be carried out either sequentially or, preferentially, simultaneously. Rather than listing the variety of such experiments, for the sake of brevity, just one extension to the DPI technique will be briefly discussed here. 4.1
Waveguide Extinction Coefficients
All of the data discussed to date has related to the measurement of changes in phase of light propagating through the sensing waveguide relative to the underlying reference waveguide as measured by changes in the position of interference fringes. A relative measure of the light lost from the sensing waveguide can be made quite simply by measuring the contrast of the interference fringe image (the losses). The contrast provides a relative measurement of the amount of light transmitted through the sensing waveguide compared to that transmitted through the reference waveguide. Information on losses enables inferences to be made regarding the nature of structures within the layer such as nucleated versus stochastic packing of bodies within the layer. The measurement of extinction coefficients and their interpretation is actively being developed and a full analytical solution for waveguide losses has been developed which it is anticipated will provide yet further information on the structure and arrangement of proteins and other biologically relevant molecules on the surface. During this development a special case was identified with respect to waveguide losses. It has been observed that losses from the waveguide structure increase substantially when crystallization occurs. This is distinct from aggregation, precipitation, and other nonordered solid-state phases which do not lead to the same dramatic losses.
Early experimental data was obtained using the model protein lysozyme. During the early stages of the crystallization process it was possible to measure the characteristics of the layer structure formed on the waveguide surface. These experiments suggested that, assuming expitaxial growth, that the crystallization could be detected when groups of around 30 molecules or so were present. This would suggest that this approach is capable of identifying the very early stages of crystallization and possibly to nucleation event itself. Given the insensitivity to other solid-state phases, it has been possible to determine crystallization even in the presence of precipitates. A range of proteins have been studied and while the initial conditions for crystallization vary considerably all have shown similar characteristics during the course of crystallization. Preliminary studies using nondiffracting crystals and salt crystals suggest that it might be possible to elucidate between these classes using such waveguide techniques. If this proves to be the case then it should be possible to substantially enhance the productivity of protein structure determination for which the production of diffraction quality protein crystals is the bottleneck. 4.2
Chip Functionalization
Chip functionalization is a critical area for tagless biosensor systems. The immobilization of proteins on surfaces in a manner which it is both biologically relevant and does not result in excessive nonspecific binding is important in the reduction of ambiguity of experimental results. One approach to this problem is to use biomimetic surfaces such as carbohydrates. 4.2.1 Carbohydrate Chips
Preliminary work attaching keratin sulfate (KS), a 7 kDa oligosaccharide to waveguide surface has demonstrated high specificity to proteins binding KS sequences compared to those which do not (e.g., lactoferin binds strongly while concanavalin A does not). Similarly encouraging results have been obtained using condroitin sulfate (CS) and heparin sulfate (HS). These surfaces show a high level of nonspecific binding which appear to resist the physisorption of BSA even at relatively high
DUAL POLARIZATION INTERFEROMETRY
concentrations (0–2 mg ml−1 ). The flexibility of the chemistries which can be deployed and their relatively high activities on waveguide surfaces suggest that in the future these surfaces may offer very high level of performance for tagless biosensor systems.
5 CONCLUSIONS
Dual polarization interferometry is a highly sensitive surface analytical technique that has been used for measuring the structure, orientation, and functionality of biological and other layers at the liquid–solid interface. The potential areas of application are many and varied; however they share the common theme of providing a greater level of understanding of the complex processes of molecular arrangement and interactions. The technique relies on classical optics which is well understood and provides dimensional information to a very high resolution (typically better than 0.01 nm) and mass loadings to a resolution of around 100 fg mm−2 . It is possible not only to detect interactions between large proteins and small molecules but also to quantify them and to determine stoichiometries. Furthermore the technique shows promise for further development to provide information beyond that obtained from layer thickness and RI.
ACKNOWLEDGMENTS
The authors would like to thank Prof. David Fernig (Liverpool University), Dr David Cullen, Dr Kal Karim, and Dr Judith Taylor (Cranfield University), Prof. Jian Lu (Manchester University), and Prof. Neil Barclay (Oxford University) for their experimental expertise and advice. We also gratefully acknowledge the experimental skills and diligence of Dr Jonathan Popplewell, Dr Louise Peel, Dr Mark Gostock (Farfield Scientific Ltd.) who undertook much of the experimental work described. We would also like to thank Dr Gerry Ronan, Dr Simon Carrington, and Dr Kathryn Chapman (Farfield Scientific Ltd.) for helpful discussions on the most appropriate ways to describe some of the physical concepts utilized by DPI and the BBSRC for research funding.
19
REFERENCES 1. H. Arwin, Ellipsometry on thin organic layers of biological interest: characterization and applications. Thin Solid Films, 2000, 48, 377–378. 2. R. M. A. Azzam and N. M. Bashara, Ellipsometry and Polarised Light, North Holland, Amsterdam, 1977. 3. P. M. Nellen, K. Tiefenthaler, and W. Lukosz, Input grating couplers as biochemical sensors. Sensors and Actuators, 1988, 15, 285. 4. L. Guemouri, J. Ogier, and J. J. Ramsden, Optical properties of protein monolayers during assembly. Journal of Chemical Physics, 1998, 109, 3265. 5. Z. Salamon and G. Tollin, Optical anisotropy in lipid bilayer membranes: coupled plasmon-waveguide resonance measurements of molecular orientation, polarizability, and shape. Biophysical Journal, 2001, 80, 1557. 6. G. H. Cross, A. A. Reeves, S. Brand, M. J. Swann, L. L. Peel, N. J. Freeman, and J. R. Lu, The metrics of surface adsorbed small molecules on the Young’s fringe dual-slab waveguide interferometer. Journal of Physics D: Applied Physics, 2004, 36, 74. 7. B. Liedberg, C. Nylander, and I. Lundstrom, Surface plasmon resonance for gas detection and biosensing. Sensors and Actuators, 1983, 4, 299. 8. G. Ramsay, Commercial Biosensors, John Wiley & Sons, 1998. 9. Z. Salamon, H. A. Macleod, and G. Tollin, Coupled plasmon-waveguide resonators: a new spectroscopic tool of probing film structure and properties. Biophysical Journal, 1997, 73, 2791. 10. E. Kretschmann, Die Bestimmung optischer Konstanten von Metallen durch Anregung von Oberflachenplasmaschwingungen. Zeitschrift fur Physik, 1971, 241, 313. 11. Z. Salamon, H. A. Macleod, and G. Tollin, Surface plasmon resonance spectroscopy as a tool for investigating the biochemical and biophysical properties of membrane protein systems. I: Theoretical principles. Biochimica Et Biophysica Acta, 1997, 1331, 117. 12. J. Voros, J. J. Ramsden, G. Csucs, I. Szendro, S. M. DePaul, M. Textor, and N. D. Spencer, Optical grating coupler biosensors. Biomaterials, 2002, 23, 3699. 13. W. Lukosz and K. Tiefenthaler, Sensitivity of integrated optical grating and prism couplers as (bio)-chemical sensors. Sensors and Actuators, 1988, 15, 273. 14. E. K. Mann, Evaluating optical techniques for determining film structure: optical invariants for anisotropic dielectric thin films. Langmuir, 2001, 17, 5872. 15. R. G. Heideman and P. V. Lambeck, Remote optochemical sensing with extreme sensitivity: design, fabrication and performance of a pigtailed integrated optical phase-modulated Mach–Zehnder interferometer system. Sensors and Actuators, 1999, B61, 100–127. 16. G. H. Cross, Y. T. Ren, and N. J. Freeman, Young’s fringes from vertically integrated slab waveguides: applications to humidity sensing. Journal of Applied Physics, 1999, 86, 6483–6488. 17. M. B. Huglin, Light Scattering from Polymer Solutions, Academic Press, New York, 1972. 18. J. Wen and T. Arakawa, Refractive index of proteins in aqueous sodium chloride. Analytical Biochemistry, 2000, 280, 327–329.
20
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
19. J. A. de Feijter, J. Benjamins, and F. A. Veer, Ellipsometry as a tool to study the ad-sorption of synthetic and biopolymers at the air-water interface. Biopolymers, 1978, 17, 1759–1772. 20. S. Lin, C.-K. Lee, Y.-M. Wang, L.-S. Huang, Y.-H. Lin, S.-Y. Lee, B.-C. Sheu, and S.-M. Hsu, Measurement of dimensions of pentagonal doughnut-shaped C-reactive protein using an atomic force microscope and a dual polarisation interferometric biosensor. Biosensors and Bioelectronics, 2006, 22(2), 323–327. 21. N. J. Freeman, L. L. Peel, M. J. Swann, G. H. Cross, A. Reeves, S. Brand, and J. R. Lu, Real time, high resolution studies of protein adsorption and structure at the solid-liquid interface using dual polarisation interferometry. Journal of Physics: Condensed Matter, 2004, 16, S2493–S2496. 22. G. H. Cross, A. Reeves, S. Brand, J. F. Popplewell, L. L. Peel, M. J. Swann, and N. J. Freeman, A new quantitative optical biosensor for protein characterisation. Biosensors and Bioelectronics, 2003, 19, 383–390. 23. T. Halthur, P. Claessen, and U. Elofsson, Immobilization of enamel matrix derivate protein onto polypeptide multilayers. Comparative in situ measurements using ellipsometry, quartz crystal microbalance with dissipation, and dual-polarization interferometry. Langmuir, 2006, 22(26), 11065–11071. 24. G. Thibault, J. Yudin, P. Wong, V. Tsitrin, R. Sprangers, R. Zhao, and W. A. Houry, Specificity in substrate and cofactor recognition by the N-terminal domain of the chaperone ClpX. Proceedings of the National Academy of Sciences of the United States of America, 2006, 103(47), 17724–17729. 25. S. Lin, C.-K. Lee, Y.-H. Lin, S.-Y. Lee, B.-C. Sheu, J.-C. Tsai, and S.-M. Hsu, Homopolyvalent antibodyantigen interaction kinetic studies with the use of a dual polarisation interferometric biosensor. Biosensors and Bioelectronics, 2006, 22(5), 715–721. 26. M. Swann, L. Peel, S. Carrington, and N. Freeman, Dual polarisation interferometry: an analytical technique to measure changes in protein structure in real time, to determine the stoichiometry of binding events and to differentiate between specific and non-specific interactions. Analytical Biochemistry, 2004, 329, 190–198. 27. M. Swann, N. Freeman, S. Carrington, G. Ronan, and P. Barrett, Quantifying structural changes and stoichiometry of protein interactions using size and density profiling. Letters in Peptide Science, 2003, 10, 487–494. 28. S. Biehle, J. Carrozzella, R. Shukla, J. Popplewell, M. Swann, N. Freeman, and J. Clark, Apolipoprotein E isoprotein specific interactions with tissue plasminogen activator. Biochimica Et Biophysica Acta-Molecular Basis of Disease, 2004, 1689, 244–251.
29. G. C. Terstappen and R. Angelo, In silico research in drug discovery. Trends in Pharmacological Sciences, 2001, 22, 23–26. 30. M. Cascio and R. S. Rapaka, Structural biology and structural genomics/proteomics. Journal of Peptide Research, 2002, 60, 307–311. 31. B. A. Lewis and D. M. Engelman, Surface areas and volumes of DPPC by X-ray scattering. Journal of Molecular Biology, 1983, 166, 211–217. 32. M. Seitz, E. Ter-Ovanesyan, M. Hausch, C. K. Park, J. A. Zasadzinki, R. Zentel, and J. N. Israellachvili, Formation of tethered supported bilayers by liposome fusion onto lipopolymer monolayers promoted by osmotic stress. Langmuir, 2000, 16, 6067–6070. 33. J. Majewski, J. Y. Wong, C. K. Park, M. Seitz, J. N. Israelachvili, and G. S. Smith, Structural studies of polymer-cushioned lipid bilayers. Biophysical Journal, 1998, 75, 2363–2367. 34. C. Terry, J. Popplewell, M. Swann, N. Freeman, and D. Fernig, Characterisation of membrane mimetics on a dual polarisation interferometer. Biosensors and Bioelectronics, 2006, 22(5), 627–632. 35. J. F. Popplewell, M. J. Swann, N. J. Freeman, C. McDonnell, and R. Ford, Quantifying the effects of melittin on liposomes. Biochimica Et Biophysica Acta-Biomembranes, 2007, 1768(1), 13–20. 36. M. A. Cooper, Optical biosensors in drug discovery. Nature Reviews Drug Discovery, 2002, 1, 515–528. 37. K. Karim, J. D. Taylor, D. C. Cullen, M. J. Swann, and N. J. Freeman, Measurement of conformational changes in the structure of transglutaminase on binding calcium ions using optical evanescent dual polarisation interferometry. Analytical Chemistry, 2007, 79(8), 3023–3031. 38. H. Berney and K. Oliver, Dual polarization interferometry size and density characterisation of DNA immobilisation and hybridisation. Biosensors and Bioelectronics, 2005, 21, 618–626. 39. B. Lillis, M. Manning, H. Berney, E. Hurley, A. Mathewson, and M. Sheehan, Dual polarisation interferometry characterisation of DNA immobilisation and hybridisation on a silanised support. Biosensors and Bioelectronics, 2006, 21, 1459–1467. 40. J. R. Lu and R. K. Thomas, Nuetron of reflection from wet interfaces. Journal of the Chemical Society, Faraday Transactions, 1998, 94(8), 995. 41. N. J. Freeman, L. L. Peel, M. J. Swann, and J. R. Lu, Lysozyme adsorption studies at the silica-water interface using dual polarisation interferometry. Langmuir, 2004, 20, 1827–1832. 42. L. Stryer, Biochemistry, 4th Edn, W. H. Freeman, New York, 1995.
33 Grating-Based Optical Biosensors Katalin Erd´elyi,1 Anthony G. Frutos,2 Jeremy J. Ramsden,3 Istv´an Szendro1 and Guy Voirin4 1
MicroVacuum Ltd., Budapest, Hungary, 2 Corning Life Sciences, Corning Incorporated, Corning, NY, USA, 3 Department of Materials, Cranfield University, Cranfield, UK, and 4 CSEM Centre Suisse d’Electronique et de Microtechnique SA, Neuchˆatel, Switzerland
1 INTRODUCTION
Optical waveguides interact with their environment through their evanescent fields, regardless of how this interaction is monitored (coupling with a grating or prism, Mach–Zehnder or slab interferometry, etc.), and as such they are sensitive to changes in the electronic polarization distribution within the evanescent fields. These changes could arise in several different ways: new atoms could replace existing atoms, the new atoms having a higher or lower polarizability than the existing ones; the density of the material within the evanescent field could increase or decrease; an adlayer of particles with a polarizability different from that of the medium surrounding them could be built up (or removed) at the interface between the waveguide and the medium. The evanescent field decays exponentially from the boundary of the waveguide into the external medium.1 The most common waveguide design consists of an optically dense slab whose refractive index is higher than that of any other part of the system. Typically the system thus consists of a thin high refractive index slab made from, for example, titanium dioxide (n ∼ 2), supported on optical glass (n ∼ 1.5), and in contact with an aqueous cover medium (n ∼ 1.4). With such an arrangement, the evanescent field of red or
green light guided within the waveguide typically extends from 100–200 nm into the cover medium. This arrangement far from exhausts the possibilities however; in the so-called reverse symmetry configuration, the support has a very low refractive index (e.g., n ∼ 1.2), thereby driving the guided modes into the cover medium.2 With this arrangement, very large evanescent fields can be achieved, extending from tens to hundreds of micrometers away from the waveguide. This basic physics defines the fields of application, which are, as such, shared by any evanescent wave technique. Nevertheless, the grating coupler has several unique features, which makes it very powerful and versatile optical evanescent wave techniques. In particular, both the transverse magnetic (TM) and transverse electric (TE) modes can be measured, and by tuning the waveguide parameters (e.g., the thickness and/or the refractive index of the high refractive index slab), the number of excitable modes can be selected. Furthermore, the structure of the mode equations governing propagation of light within the waveguide allows a rather direct link to be made between the measured waveguiding parameters (the propagation constants in one form or another) and the optogeometric parameters of the structures within the evanescent field, which are usually the object of the measurement. Thus one may note that surface
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
plasmon resonance (SPR) is limited by only the TM mode being excitable; waveguide interferometry in its various forms is limited by only one mode being practically available for measurements; ellipsometry is limited by the structure of the equivalent to the mode equations, which makes the measured parameters rather insensitive to the thickness and refractive index of adlayers, and so on. This list could be continued and extended both in breadth and depth, but it is not the purpose of this section to give a detailed comparison of the various realizations of the evanescent wave technique. The grating coupler is therefore advantageous whenever interpretable information is required from the measurement, rather than merely evidence of a change in the system. As will become clearer in the subsections in the subsequent text, this interpretable information could be molecular orientation within an adlayer, the number of particles per unit area adsorbed at the solid/liquid interface, the thickness of an adlayer, and so on. The intrinsic sensitivity of the grating coupler optical waveguide is also very high, about 10 times better than that of SPR, for example.3 When the incoupling angles are measured through mechanical goniometry in the incoupling configuration, the achievable precision of the angular measurement is commensurate with the precisions of the monochromaticity of the light source, the thermal stability of the waveguiding material, practically achievable temperature stability, and so on. Clearly higher precision of measurement can be achieved using interferometry simply by extending the length of the interferometer; but this requires a commensurate increase in the temperature stability. Grating couplers with microradian resolution require aqueous cover media to be thermostated to a few tenths of a degree celsius; a meter-long interferometer would have to be thermostated to better than one millikelvin. The grating coupler is above all a device for interrogating interfacial processes. Bulk processes may also be investigated, but in this case they are being sampled by inserting an interface into the system, and it must always be carefully considered whether the system is being perturbed thereby. Another general point that should be made is that the grating coupler is very well adapted to making kinetic measurements with high resolution. This is not only important for fast sensor response
but also for elucidating the mechanisms of adlayer formation, living cell physiological response, and so on. 1.1
The Physical Objects Measurable with Grating-based Optical Sensors
The kinds of objects that are measurable may be put into three classes: individual particles, including molecules, macromolecules, colloidal particles, and other nano-objects; thin and thick films deposited on solid and living cells, either individually or in a mass.
1.1.1 Particles
The simplest way in which particles are measured is simply to allow them to accumulate at the waveguide surface. Provided their refractive index is different from that of the medium in which they are suspended in the bulk (liquid or gas), a condition which is almost invariably fulfilled, the polarizability distribution within the evanescent field will change, resulting in measurable changes in the waveguide propagation constants. Very often the addition of the particles results in the formation of a thin (or thick) film, whose structural elucidation is covered in the subsequent text. In sensing, it is frequently desired to determine the presence of small molecules, for example drugs, whose relative molecular weight may only be a few hundred. The sensitivity of the grating coupler is not generally adequate to be able to measure the presence of one monolayer of such small molecules adsorbed at the planar waveguide surface. Hence, recourse must be made to capturing and concentrating the molecules within the evanescent field. A variety of ways for achieving this has been reported in the literature, including ultrarough (quasifractal) surfaces, with which the capacity may be very considerably increased; making the near-surface zone or all of the waveguiding film porous, such that the inner surfaces of the pores become the adsorbing surface; coating the waveguiding film with a hydrogel such as dextran, typically several hundred nanometers thick; coating the waveguiding film with a lipid bilayer or multilayer. This last one is particularly useful when the concentration of lipophilic drugs is to be detected;
GRATING-BASED OPTICAL BIOSENSORS
concentration factors in excess of 10 000 can be achieved. With some of these ways, especially the porous waveguiding layer and the dextran hydrogel, the capture and concentration is achieved only at the expense of a great retardation of transport of the molecule to be detected (the analyte) to within the evanescent field, with a corresponding lengthening of the response time of the sensor. Since association and dissociation constants may suffer different perturbations as a result, hydrogels in particular should be avoided if the deduction of thermodynamic ligand receptor (the receptor typically being immobilized by attachment is the hydrogel) binding constants using the kinetic mass action law is the goal of the measurement.
3
an arbitrarily large number of parameters may be needed to describe the profile. In certain cases, however, the profile follows a simple law, as in de Gennes’ scaling theory of polymer adsorption at interfaces, for example, whose parameter (in that case the exponent of a power law) can be extracted from the waveguide measurements. Another approach is to extract Mann’s F parameter, which gives information about whether the profile is decreasing, uniform, or increasing and then decreasing as one moves from the waveguide surface out into the bulk medium. It should however be noted that with conventional waveguides, the sensitivity of the propagation constants to changes in the refractive index profile falls off sharply as the penetration depth of the evanescent field is reached.
1.1.2 Thin Films
The solution of Maxwell’s equations for stratified media, albeit algebraically tedious, is a straightforward procedure and allows the relationship (a set of mode equations) between the optogeometric parameters of any number of adlayers and the propagation constants of the guided modes in the waveguide to be derived. The limitations are the number of modes that can propagate in the waveguide, the noise level of the measurement, and the sensitivity of the mode equations. Even if only two or four parameters (propagation constants) can be measured, it is already possible to derive film thickness and refractive indices, from which many useful and important inferences, including orientation of the molecules constituting the thin film, and so on, can be made. Very often, one wishes to observe changes in the optogeometric parameters of the film during the application of some perturbation, for example, addition of a substance able to intercalate into the film. If the films are constituted from particles whose size is less than about 1/10th of the wavelength of the guided light, the uniform thin film approximation (UTFA) may be applied and the film characterized by mean thickness and refractive indices. For larger particles, scattering from individual particles needs to be explicitly taken into account. Until now, relatively little work has been done on characterizing films with nonuniform refractive index profiles perpendicular to the plane of the film, which of course coincides with that of the waveguide. That is because in the general case
1.1.3 Living Cells
Formally speaking, individual cells constitute particles and confluent monolayers or multilayers constitute thick films, but they deserve separate mention because of their peculiarities compared with inanimate matter. Cells in culture, suspended in aqueous medium, are spherical. The most typical reaction undergone by cells when they arrive at the solid surface is to spread out and adopt the shape of a segment. This implies a vast redistribution of material in the vicinity of the waveguide surface. Hence even with conventional waveguides, with a penetration depth of the order of 100 nm, the spreading of eukaryotic cells, which have a diameter of 10–20 µm as spheres, can be monitored with excellent resolution.4 The spreading reaction is typically rather slow, taking place over tens of minutes or even hours, and thus can be monitored very easily.
1.2
Applications to Areas of Human Activity
1.2.1 Medicine
The three broad categories of applications in the medical field are (i) physiology, (ii) clinical diagnosis, and (iii) biomedicine. In physiology, the importance of being able to detect molecules without labeling them is of inestimable advantage, given the often significant, but equally often hard
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
to quantify, perturbations made by the label on the system under investigation. That is the great disadvantage of fluorescence-based methods. On the other hand, in the absence of labeling it is much more difficult to identify the molecules entering the evanescent field, and in physiology one is often working with very complex mixtures of hundreds or even thousands of different molecules, and in the absence of labeling careful and ingenious experimentation is needed to infer the identity of what is causing a particular change. Typical questions that one might wish to investigate using grating couplers are the modes of action of the P450 enzyme complex, the aggregation of platelets, and so on. These are typical interfacial processes; indeed most physiological processes take place at a solid/liquid interface. If one wishes to investigate homogeneous processes, either the interface is used to sample the bulk volume, or else one can attempt to mimic the homogeneous reaction volume, for example, by coating the waveguide with a thick hydrogel, but this is both chemically and morphologically somewhat different from unstructured bulk liquid and due regard must be taken of the differences. The typical problem in clinical diagnosis is to detect the presence of one particular biomarker molecule in a biofluid. If the fluid is blood, there will be hundreds of other molecules present, many at much higher concentrations. Therefore, extraordinarily high selectivity of detection is needed, that is, extremely high affinity of the capture layer coating the waveguide for the analyte of interest, and weak reversible affinity for everything else. These are sometimes referred to as specific and nonspecific binding respectively. The grating coupler is uniquely useful for optimizing the design of such capture layers since not only can one directly measure their performance, but there is enough additional detail available from the experimental measurements to give insight into the mechanisms of specific and nonspecific binding. Biomedicine here refers to the introduction of artificial objects into the body. In the case of implants in the bloodstream, such as stents, heart valves, and so on, it is very important that the surfaces of the implants do not become coated with blood proteins, which risk becoming denatured and hence invoking inflammatory responses. The grating coupler is invaluable tool both for screening candidate surface coatings, and for elaborating the
mechanism of undesirable binding, which is very important for guiding the improved design of surfaces. The other main class of implants is the artificial prostheses used, for example, in bone replacement. In this case the requirement is the opposite from that applicable to the stent: one wishes to maximize protein adsorption as a precursor to fully assimilating the implant with the surrounding cells of the body. 1.2.2 Environment
Environmental monitoring comprises the observation of the purity of air, water, and so on. In these applications, the waveguide is exposed to the environment and impurities are allowed to accumulate on the surface. The technology is essentially the same as that of the medical applications, the main difference being that the media in which the impurities are suspended are usually much simpler than the biofluids of medical samples. Grating couplers have been applied to monitoring dust in the air, viruses in riverwater, and so on.5 In one class of applications, one is looking for a specific pollutant (e.g., a pesticide, or a particular bacterium), and this problem is the most similar to the medical ones. In another class of applications one does not know all that is present in a contaminated water sample for example, and it is useful to measure the accumulation of all impurities as an indicator of global purity. In environmental applications, the grating coupler is also useful for developing sensors, based on a broad palette of technologies that can be used for online, unsupervised monitoring over long periods. 1.2.3 Process Monitoring
Again, the principles are essentially the same as those applicable to medicine and the environment. One wishes to monitor the state of a chemical reactor or a bioreactor either by monitoring a few key substances, or by monitoring a complex of accumulants indicative of the overall state of the contents of the reactor. Some of the applications that could be included here could equally well fall under medicine or environment, for example, monitoring of pharmaceutical preparations (purity and stability of drug solution for example) and the monitoring of factory effluent.
GRATING-BASED OPTICAL BIOSENSORS
Biofouling could well be included here as an application. The main contribution of the grating coupler is in the development of surfaces able to resist the initial adsorption events that lead to the facilitation of cell and then organism attachment. 1.2.4 Military
Military applications of grating coupler sensors tend to be of the environmental type applied to analytes of medical interest, for example, the detection of nerve gases and airborne bacterial spores, or toxins in drinking water. The sensors are used either to develop specific capture and concentration coatings for use on a variety of sensing platforms, or as convenient field devices usable by soldiers. 1.2.5 Space
The final application, sensors for spacecraft and extra terrestrial planetary landing craft, exploits all the preceding elements, particularly emphasizing the potential of the grating coupler to be a universal, miniature sensor platform able to respond to a huge variety of different analytes in both gaseous and fluids environments.6
2 INCOUPLING MODE SENSORS 2.1
The Optical Theory of OWLS (Optical Waveguide Lightmode Spectroscopy)
Planar waveguides are films made of high refractive index material embedded between lower index materials. If the light wave introduced into the high index film arrives at the boundary at an angle that is greater than the critical angle of total internal reflection the light wave is confined inside the waveguide. The multiple reflected wave components interfere with each other. The interference is constructive, if the phase change during traveling across the film plus those due to reflectance from both boundaries of a planar waveguide is an integer multiple of 2π. In optical waveguide lightmode spectroscopy (OWLS) sensors monomode waveguides are most commonly used. This means the phase shift during one total internal reflection equals zero. In this case, a stationary wave results
5
that travels along the length of the waveguide with a certain propagation velocity and the amplitude of the electromagnetic field varying along the cross section of the waveguide (Figure 1). We define the effective refractive index of the guided mode N as the ratio of the speed of light in vacuum and the phase velocity in the waveguide. N is different for the different modes and depends not only on the refractive index and thickness of the waveguiding film but also on the surroundings. To excite the guided mode the light should be coupled into the waveguide either at the cross section (butt coupling) or from the surface with a prism or grating. Detecting the guided modes we get either information about the refractive index of the material that covers the waveguide film, or the refractive index and thickness of a deposited thin layer can be determined. In the first case the optical grating coupler waveguide is used as refractometer. In the second case, it can be used as a sensor for a specific molecule if the sensor surface is coated with a monomolecular chemoresponsive layer that makes the target molecule selectively adsorb on the surface. Both the refractive index and the thickness of the adsorbed layer can be determined and the process of adsorption monitored in situ. In order to excite the guided mode, light with an appropriate propagation vector should be introduced into the waveguide, that means kx = k0 nf sin(γ ) = k0 N . The coupling may be accomplished by a grating. Figure 2 shows the waveguide film equipped with a grating of period D. The light beam entering into the film makes an angle β with the normal of the layer. The propagation vector is k, with horizontal component kx = k0 nf sin(β). The incident light beam arrives at and is diffracted by the grating. The diffracted light wave of wave vector k, is most intense in those directions where the optical path difference between the rays emerging from neighboring grooves of the grating is an integer multiple of the wavelength λ0 nf D(sin(γ ) − sin(β)) = l λ0
(1)
To obtain the guided mode from the diffracted beam, k0 nf sin(γ ) = k0 N should hold for the x component of its wave vector, so we arrive to the incoupling condition N − nf sin(β) = l λ0 /D
(2)
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Cover medium
nc
Adsorbed layer waveguide film
g
na, na nf, nf
Grating
b To detector 1
To detector 2
ns
Substrate
z a0
y
Incident laser beam l0
x
Figure 1. Principle of the waveguide sensor. At certain angles of incidence α, modes are excited and detected. Either nc or nf and df and na , da can be determined by detecting the angles αTE and αTM where the transverse electrical (TE) and the TM modes, respectively are excited.
Notations: nc is the refractive index of the covering medium, na is the refractive index of the adsorbed layer, da is its thickness; nf is the refractive index of the waveguide, df is its thickness; N is the effective refractive index of the waveguide; λ0 is the vacuum wavelength of the laser light incident upon the sensor chip and exciting the guided mode by the grating, of grating period D; α is the angle of incidence of the laser beam (in air), β is the angle of incidence at the grating, γ is the angle between the diffracted beam and the normal of the waveguide film: this is the direction of propagation of the plane waves, which are internally totally reflected at the boundaries.
According to Snell’s law n0 sin(α0 ) = nf sin(β), that means a guided wave exists and a maximum signal is detected if
Grating period D D
A
Grating
b
g
B
k′
b′ Diffracted wave
C g
c′ a′
a k
kf
b b Incident wave
Guided wave
a0
Figure 2. Coupling linearly polarized laser light into the waveguide by a grating. Note that D is defined as the length between successive grating peaks.
The light wave arrives from the air through the substrate into the waveguide. In air, the angle of incidence is α0 . That is the angle we can measure.
n0 sin(α0 ) = N − l λ0 /D
(3)
As there are two independent modes of the electromagnetic field in the system, TE mode and TM mode, the monomode waveguide is represented by two effective refractive indices NTE and NTM . From the incoupling angles, αTE and αTM , the effective refractive indices NTE and NTM can be determined for both modes; if m = 0, NTE = n0 sin(αTE ), and NTM = n0 sin(αTM ). Measuring with the waveguide surface covered with a solvent of known refractive index, we get both the thickness and refractive index of the waveguide layer from the three-medium waveguide mode equations. These data are then used in the fourlayer formulas to evaluate the measurements when an adsorbed layer is present.7 More details about incoupling theory can be found elsewhere.8–10
GRATING-BASED OPTICAL BIOSENSORS
2.2
The Structure of the Planar Grating Coupler Sensor Chip
In a typical grating coupler waveguide technique the sensor chip consists of a high refractive index waveguide film deposited on a lower index substrate and having an optical grating for in- or out-coupling light to or from the waveguide. A cuvette is attached to the top of the sensor surface that allows a cover material to be brought into contact with the waveguide. This cover material can be a solvent from which adsorption takes place and an adsorbed layer is built up on the waveguide surface. More details are given in Ref. 3.
2.3
Instrumentation
Based on the pioneering work of W. Lukosz and his group at the Quantum Optics Laboratory, Swiss Federal Institute of Technology, Zurich, instruments are now commercially available based on the incoupler grating waveguide sensor principle. Lukosz8 and Ramsden11 have both reviewed various types of optical grating coupler biosensors. These reviews have outlined the advantages of the grating coupler biosensor compared to other optical biosensors (including the fact that the OWLS Grating C (cover medium) A (adsorbed layer) F (waveguide film)
7
technique is theoretically an order of magnitude more sensitive than the SPR3 ) and have highlighted that by measuring two incoupling angles corresponding to the TM and TE polarizations, one can determine two independent parameters of the thin adlayer of the captured analyte. The optical setup of the OWLS instrument is illustrated in Figure 3. A computer-controlled high-precision goniometer rotates a sensor holder with high accuracy and reproducibility. Linearly polarized light (He-Ne laser) is incoupled by a diffraction grating into the waveguide layer, provided that the incoupling condition is fulfilled. In the waveguide layer the light is guided by total internal reflection to the ends where it is detected by photodiodes. In commercially available equipment (OWLS120) the angular resolution is better than 10−4 degrees and in continuous measurement mode, when only one incoupling angle change is monitored, the temporal resolution is better than 3 s. The instrumental resolution in terms of effective refractive index change is N ≈ 10−6 . The main drawback of the input coupler is that the rotating sensor configuration is not suitable for miniaturization and/or for multichannel/array configuration. However, the flexibility and the quality and quantity of the basic information delivered make this method a perfect tool for
Rotation Evanescent electromagnetic field Flow cell
S (substrate) Waveguide Air
a
Substrate
Grating
Photodiode
Laser light Incoupling angle
Shutter Beam mirror
Figure 3. Typical optical setup of the OWLS instrument.
Laser
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
300
Protein solution
Shift of the incoupling angle
200
Light intensity
Adsorbed mass of proteins (ng cm−2)
Buffer solution
100
TM peak
TE peak
Angle of incidence (°) 0 0 Baseline in buffer solution
30
60
90
Time (min)
Figure 4. Typical biomolecular binding measured by an OWLS instrument.
R&D applications. A typical biomolecular binding measured by OWLS technique is presented in Figure 4.
2.4
Sensor Fabrication
Fabricating a cheap, reliable, reproducible grating coupler waveguide sensor needs two main manufacturing processes to be mastered: depositing a low loss optical waveguiding layer and producing a high period grating. Good optical waveguiding films on glass supports are usually made from transparent metal oxides. The requirement to deposit thin (in the range of 100 nm) and low loss (≤1 dB cm−1 ) waveguide layers on glass or polymer surfaces with high reproducibility is a serious budgetary problem. Commercially available vacuum evaporators, sputtering or CVD equipment can do the job but are too expensive for medium volume sensor production. An elegant, and economical method for waveguide fabrication is the solgel technique, in which solid, glassy layers are produced from metal-alkoxide or colloidal solutions after heat treatment at high temperature. The thickness uniformity, the waveguide properties and the smoothness of these films are excellent, to obtain adequate incoupling efficiency into the waveguide a low modulation (typically 10 nm), high-frequency (typically 2000 to 3000 lines per mm) optical grating is needed.
Conventional photolithography with dry etching techniques, or holographic exposure of photosensitive layers, or direct ablation of the solid surface are suitable methods, but all require expensive equipment and a clean room environment. An elegant and economical method to produce high frequency gratings is to emboss a solgelcoated substrate with a master grating. Although embossing technology is a straightforward choice, to produce gratings with high reproducibility the technological processes must be controlled with high precision. The method is based on the fact that the solgel layer, after application as a thin film onto the surface of the substrate, will harden spontaneously. If the semihardened solgel layer is embossed in the appropriate time window to a master grating the solgel layer will be deformed in the right way without sticking to the master grating. After appropriate heat treatment a solid surface with a grating depth of 5–20 mm is obtained. High refractive index, metaloxide-based solgel materials that can be used for grating embossing are available, so the fabrication of a grating coupler waveguide sensor becomes quite simple by using the same material as the waveguide layer in which the grating can be embossed. Grating coupler sensors from TiO2 , Ta2 O5 , SiO2 /TiO2 , ITO, and so on are commercially available. Building on the art and practice of embossing gratings in solgel materials, one can develop and produce grating
GRATING-BASED OPTICAL BIOSENSORS
coupler waveguide structures with more than one grating, with chirped gratings, with stacked gratings and with stacked waveguides with gratings in each waveguide, and so on.12
2.5
9
Immobilizing anti-E. coli IgG onto the aminosilanised sensor of OWLS by covalent coupling, a calibration curve between 3 × 104 and 3 × 107 CFU ml−1 was obtainable.15 2.6
Immunosensors Based on OWLS Detection
OWLS Assays on Living Cells
In terms of cells, OWLS assays—which can quantify the deposition of material in a thin (usually <150 nm) layer above the solid sensor surface—can provide data on focal contacts and adhesion sites, while the rest of the cellular mass remains out of the field of detection. Living cells produce and release molecules. Physical sedimentation of living cells and molecules secreted by them will result in a rapid, (mixed cellular and molecular) material deposition. The saturationlike kinetics of “cell-attachment” observed in OWLS measurements is composed by both, the deposition of secreted molecules and the physical contacts of cells with the sensor surface.16 Upon adhesion, different types of cells display different patterns of cytoskeletal changes, extracellular matrix production and motility. The rapid expansion of some epithelial cells with wide lamellipodia (arrows on the left in Figure 5) and the exploring outgrowth-withdrawal moves of minor processes (arrows on the right in Figure 5) in initial
In the past years several immunosensor protocols were developed, based on the OWLS technique. Using various immobilization protocols, each component of the antibody–antigen complex can be covalently immobilized on the sensor surface, allowing noncompetitive or competitive detection of the analytes. A competitive or binding inhibition (immobilized antigen based) OWLS immunosensor has been developed and optimized for the detection of trifluralin.13 The OWLS technique has been applied to the detection of the toxins aflatoxin and ochratoxin in both direct and competitive immunoassays. A competitive immunosensor based on OWLS detection could be suitable for the quick determination of Ochratoxin and Aflatoxin contamination in grain samples.14 OWLS technique was investigated for detecting Escherichia coli, which is an indicator microorganism for contamination in the food industry. MDCK
Deposited material (arb units)
350
MDCK
300 NE-4C 250
Injection
200 150 100 NE-4C
50 0 0
10
20
30
40
50
Time (min)
Figure 5. Kinetics of “cell-attachment” observed in OWLS measurements.
60
70
80
90
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
attachment of neuronal precursor cells represent two extremities in the scale of possible moves of adhering tissue cells. OWLS signals recorded during the attachment of Madin–Darby canine kidney (MDCK) (kidney epithelium) cells and the neuroectodermal NE-4C cells reflect some of these basic differences (Figure 5). The steplike versus monotonically saturating deposition curves in the cases of NE-4C and MDCK cells respectively indicate the different kinetics of both adhesion and secretion by the two types of cells. Cell physiological interventions that block active cell metabolic processes, such as cooling (assays at 4–10 ◦ C), blocking cytoskeletal activation (treatment with Cytochalasin B), or assaying cells after fixation result in altered OWLS signals. Such treatments help to make distinctions between passive sedimentation and active cell responses. By OWLS assays, clear-cut differences can be detected in the initial “adhesive” reactions of the same cells on different substrates.
2.7
This kind of experiments can be performed using commercial incoupling mode grating sensors and instrumentation.21 The grating coupler waveguide structure can be used also to excite fluorescent molecules with high signal to noise ratio in the vicinity (typically 200 nm) of the solid sensor surface and study with a microscope the interaction of cells with the sensor surface. This measuring possibility opens a new field of application of the grating coupler waveguide structure, as an evanescent wave excitation fluorescence microscopy system.22
3 OUTCOUPLING MODE SENSORS
The objective of most of the integrated schemes is to perform the measurements mechanical movement in order to be manufacture a compact reading system. following detection schemes are based grating equation Ne (t) =
Electrochemical-OWLS, Fluoro-OWLS
Label-free optical biosensing methods like the OWLS technique can be combined with electrochemical measurements. The combination of these measurement methods results in a system, in which surface processes can be studied by optical methods while electrical fields are applied. Electrical fields have an effect not only on the light incoupling mechanism17 but can drastically modify the adsorption/desorption kinetics of biological molecules onto the sensor surface as well as association/dissociation of biological macromolecules.18,19 Beside the studies with the electrochemical-optical waveguide lightmode spectroscopy (EC-OWLS) method in the field of basic molecular research, it’s a challenging new area of application to study the behavior of living cells with EC-OWLS.20 The robust easy to perform and highly reproducible incoupling of the light into a planar waveguide with the help of a grating opens new ways to study fluorescently labeled molecules and processes. The possibility of measuring label-free optical and fluorescently labeled reactions simultaneously allows one to better understand complex biological processes occurring on solid surfaces.
sensing without able to All the on the
l·λ D − na sin(θ )
(4)
where λ is the wavelength, D is the grating period, θ is the angle of incidence of the plane wave, Ne (t) is the effective refractive index of the waveguide, l is the diffraction order, and na the refractive index of the ambient medium. In this equation, there are three parameters that can be used to monitor the change of the effective refractive index: the coupling angle, the grating period and the wavelength. In this section examples are presented on the use of the grating period in the “light pointer” system and on the use of the wavelength in the wavelength-interrogated optical sensing system (WIOS).
3.1
Chirped Grating Couplers (CGS) Light Pointer
This system measures refractive index changes at the surface of a waveguide chip using an optical arrangement called a light pointer. The key role is played by chirped grating couplers (CGC): grating couplers with a grating periodicity D(y) linearly varying with the position along the line grating (perpendicular to the propagation direction and
GRATING-BASED OPTICAL BIOSENSORS
11
Side view
(a)
qout
qin Top view
z
yr Light pointer
(b)
y
Figure 6. “Light pointer” sensor chip based on two chirped grating couplers: (a) side view and (b) top view.
plane of incidence). The CGC are used to couple light into and out of the waveguides (Figure 6). A large area input grating is uniformly illuminated at a fixed angle. Light couples into the waveguide at one specific position on the grating and defines a fine line of guided light (light pointer). The output grating couples out the light at one position and directs it on a CCD camera or a position-sensitive detector. In the case of an infinite sensing layer on the input grating coupler, the effective waveguide refractive index will only be dependent on the sensing layer refractive index if we assume that the thickness of the waveguide layer is constant. For a linear chirp with a varying periodicity D(y) = D(0) + sD· y (D(0) periodicity at y = 0; sD slope of the chirp), the light pointer position yr corresponding to the resonant periodicity D(yr ) can be expressed as: λ − D(0) n (t) − sin θ yr = c sD
(5)
The position of the beam detected by the camera is used to calculate the effective refractive index of the waveguide. Additional details can be found elsewhere.23–26 Each optical chip has two measurement pads or gratings (Figure 7). These may be used for separate experiments or may be chemically modified separately and then used in parallel. One pad is used to monitor a binding reaction, while the other pad is used as a reference to eliminate external influences such as temperature and refractive index fluctuations. The chips are realized using replication technologies: the grating structures are fabricated by injection molding followed by a deposition of a TiO2 layer to form the waveguiding film. Addition or loss of mass at the surface of the waveguide (due to molecular interactions) results in a change of the coupling position. By monitoring the beam position on the camera, biochemical interactions at the waveguide grating surface can be followed in real time (Figure 8).
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Reference
Source Signal
Figure 7. Replicated grating chip with two measurement channels and images of the light pointers obtained with a camera.
3.2
Detector
I
l
Wavelength-interrogated Optical Sensing (WIOS)
With the WIOS system, the resonance condition of the grating coupler is interrogated with a tunable laser (Figure 9). WIOS detects the refractive index changes in the evanescent wave of a straight waveguide grating using a wavelength sweep. Light from a vertical cavity surface-emitting laser (VCSEL), emitting at around 763 nm, is incident on the first grating. The waveguide mode is excited and propagates into the waveguiding layer. The
t
t/l
Figure 9. Scheme of the WIOS configuration at the resonance condition.
second grating couples out the guided light (at a different angle) and directs it on the detector. The resonant coupling occurring on the first grating is governed by the grating equation: λr (t) = D(Ne (t) − sin(θ ))
(6)
with λr the resonance wavelength for which coupling occurs, the grating period, θ the incidence angle, Ne (t) the effective index of the waveguide mode. Reference pad Sensing pad
Binding of antimouse IgG on mouse IgG 1.4 Buffer
Buffer
Antimouse IgG in buffer
Spot position on camera (au)
1.2 1 0.8 0.6 0.4 0.2 0 0
500
1000
1500
2000
2500
3000
3500
4000
−0.2 Time (s)
Figure 8. Analysis of the image of the output grating on a camera in real time allows the monitoring of biochemical reactions occurring at the sensing layer: example of one channel with binding of anti-mouse IgG on mouse IgG and a reference channel blocked with BSA.
GRATING-BASED OPTICAL BIOSENSORS
For a given optical configuration (θ , D fixed), the monitoring of λr will give access to effective index variations of the waveguide Ne (t). Consequently this gives access to refractive index variations introduced by the biochemical reaction. The size of one measurement channel being 0.8 × 2 mm2 , it is easy to implement several channels on the same chip. A system was developed with the possibility to detect eight channels simultaneously. This can be extended to 16 or 24 using a chip with several columns of 8 pads and a translation table. An example of a measurement is given in Figure 10 where measurements from three different channels are reported—the binding of an antibody on two different antigens and on a reference channel blocked with bovin serum albumin (BSA); the antibody is specific for antigen B and has no cross reaction with antigen A. Further details can be found elsewhere.27,28 3.3
Combination of Wavelength-interrogated Optical Sensing and Fluorescence Detection
One advantage of the grating waveguide technology is the possibility to perform label-free and
13
fluorescence measurements simultaneously on the same sensor pad. In the WIOS configuration, if fluorescent labels excited at the laser wavelength are used, the evanescent wave excites fluorescent light that is partially coupled back into the waveguide. The fluorescent light is also out coupled with the second grating. Using a beam splitter and a wavelength filter, it is separated from the excitation light and collected on a detector. This feature is demonstrated by Figure 11 showing two signal curves recorded at exactly the same time on a single sensor pad. The most conspicuous advantage of reading out both types of signals at the same time is that processes involving labeled molecules can be clearly separated from processes with nonlabeled molecules occurring on the same measuring spot. The “label-free” curve always keeps track of the changes in surface mass density on the sensor pad, irrespective of labeling or nonlabeling of the molecules. In case of disturbing effects, for example, by various kinds of bleaching, the fluorescence signal can be appropriately corrected. Processes involving extremely small molecules can be detected by fluorescence and/or mass labeling.
14 XX 1 Antigen A 3 Antigen B 5 Reference 7 8
12
WIOS signal (W.U.)
10
8
Reaction with antigen A Reaction with antigen B Reference
6
4
2
0 PBS −2
200
400
Introduction solution PBS with antibody B
600
800
1000 Rinsing with PBS
1200
Time (sec)
Figure 10. Example of multisensing measurement with two different immobilized antigens.
1400 PBS
1600
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 0.7
290 m lgG
PBS
PBS
Alexa 750 a–m lgG
PBS
PBS 0.6
Label-free signal (au)
270
0.5 250 0.4 Label free Fluorescence
230 1
0.3
210
0.2
2 190
Fluorescence signal (au)
PBS
0.1
170
0 0
10
20
30
40
50
Time (min)
Figure 11. Experimental demonstration of simultaneous detection of adsorption processes by label-free (WIOS, curve 1) and fluorescence-based (curve 2) chip readout.
4 ARRAY SENSORS 4.1
Resonant Waveguide Grating (RWG) Sensors
Optical biosensors based on sensing changes in index of refraction have been used for many years for the study of biomolecular interactions. These sensors have been chip based and, as a result, have been limited in throughput. Of recent interest is the application of label-free detection technologies for drug discovery applications.29,30 The Corning Epic System is a high-throughput, microplatebased label-free detection platform that has been developed to address this need. Figure 12(a) shows a picture of a Corning 384well Epic microplate. The optical sensors in each well of the microplate are resonant waveguide grating (RWG) sensors and consist of a substrate with an optical grating and a high index of refraction waveguide coating (see Figure 12b). When illuminated with broadband light at a fixed angle of incidence, these sensors reflect only a narrow band of wavelengths, which is a sensitive function of the effective index of refraction of the sensor and is governed by the following equation: sin θ =
Ne − λ D
(7)
where θ is the angle of incidence, Ne is the effective index of refraction of the waveguide, λ is the
resonant wavelength, and D is the grating period. The light that is coupled into the waveguide film propagates parallel to the surface in the plane of the waveguide film and creates an electromagnetic field (an evanescent wave, that is, decaying exponentially with increasing distance from the interface) in the liquid adjacent to the interface. The distance from the sensor surface at which the electric field strength has decreased to 1/e of its initial value is the penetration depth; for the RWG sensors described here, the penetration depth is ∼150 nm. The sensors are coated with a chemically modified surface layer that enables covalent attachment of protein targets or other biomolecules. Binding of compounds to the immobilized target induces a change in the effective index of refraction of the waveguide, and this is manifest as a shift in the wavelength of light reflected from the sensor. The magnitude of this wavelength shift is proportional to the amount of analyte that binds to the immobilized target. Wavelength shifts in the picometer range can be measured with noise levels on the order of 0.1 pm (∼7 × 10−7 refractive index units).
4.2
Referencing
RWG sensors are sensitive to small changes in temperature and changes in the bulk index of refraction of the solvent. For high-sensitivity
GRATING-BASED OPTICAL BIOSENSORS
YYYY Y Y Y
Chemistry Waveguide substrate
(a)
Broadband source Well bottom
Non Binding surface
15
Target molecules
Reflected wavelength
(b)
Binding surface
(c)
Figure 12. (a) Picture of a Corning 384-well Epic microplate. (b) Resonant waveguide grating (RWG) sensors consisting of a substrate with an optical grating and a high index of refraction waveguide coating. (c) Self-referencing scheme employed by the Corning Epic System.
measurements, it is critical that these effects be controlled or referenced out. The Corning Epic System employs a self-referencing scheme to address this issue in which each well in the microplate has a reference region that is used to reference out the aforementioned factors (see Figure 12c). This is enabled by a patent-pending process that provides protein binding chemistry on only half of the sensor surface so that when a solution of protein target is added to the well, it only binds to half of the sensor surface, leaving the other half as an in-well reference.
the master is released. Hot embossing employs a similar strategy, but the master is pressed into a thermoplastic material above its softening point and then cooled before release. The waveguide coating material is typically a high index of refraction metal oxide (e.g., TiO2 , Ta2 O5 , Nb2 O5 , or ZrO2 ) that can be deposited using a variety of techniques including vacuum evaporation, sputtering, chemical vapor deposition, and solgel processes.
4.4 4.3
Sensor Fabrication
Many different technologies have been used for the fabrication of grating structures in substrates, such as solgel techniques,12 UV embossing, nanoimprint lithography, electropolymerization, micromolding, laser induced isomerization of azobenzene films, hot embossing, and injection molding.31–40 For example, in the UV embossing process, a negative grating master is fabricated using a technique such as e-beam lithography. A UV-curable monomer is applied to the surface of a substrate and the grating master is pressed into the monomer to mold a positive replica of the grating structure onto the substrate. While the master and substrate are in contact, the monomer is cured (polymerized) under a UV source, after which
Applications
In their most basic format, biochemical assays performed on RWG sensors consist of the immobilization of a target protein on the sensor surface followed by a wash free binding assay using potential drug candidates. Some examples of application include small molecule (drug)/protein assays, protein/DNA interactions, antibody profiling, enzyme (e.g., kinase, protease) direct bind and functional assays, and cytokine/cytokine receptor assays. A major advantage of these label-free, direct bind assays is the ability to screen certain “orphan” receptors (receptors in which the natural ligand is not known) or other targets that are difficult to screen due to problems with the use of fluorescent labels. To demonstrate the sensitivity of RWG sensors for small molecule(drug)/protein interactions,
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 8 Response (pm)
Response (pm)
10 7.5 5
KD(Epic™) = 795 nM
2.5
6 4
KD(Epic™) = 53 nM
2
KD(Literature) = 760 nM
KD(Literature) = 19 nM
0
0 0
1000 2000 3000 4000 5000 6000 [Dansylamide] (nM)
0
500 1000 1500 2000 2500 3000 [Acetazolamide] (nM)
Figure 13. Demonstration of the sensitivity of RWG sensors for small molecule(drug)/protein interactions.
a model assay system was developed based on the binding of benzenesulfonamides to the enzyme carbonic anhydrase (∼30 kDa). In these experiments, carbonic anhydrase was immobilized in the wells of an Epic microplate and was assayed with a titration series of the drugs dansylamide (250 Da) and acetazolamide (222 Da). Figure 13 shows the results of these experiments. The binding signal of both drugs is dose dependent and saturable, with estimated affinities that are in good agreement with literature values.41 It has recently been demonstrated that RWG sensors have applications in cell assays.42,43 In these assays, whole cells are cultured directly on the sensor surface and exposed to various compounds (agonist, antagonists, etc.). The detection principles for performing whole cell assays are similar to those for biochemical assays: changes in local index of refraction are manifest by a shift Gq-coupled receptor: PAR1
Gs-coupled receptor: b2-AR
Gi-coupled receptor: MC receptors
Response (pm)
200 100 0
200 Response (pm)
100
300 Response (pm)
in response of the sensor. The surface sensitivity of RWGs means that only the bottom portion of whole cells cultured on the sensor are monitored during an assay. Because the amplitude of the evanescent wave decays exponentially from the sensor surface, an object contributes more to the overall response when the object is closer to the sensor surface as compared to when it is farther away. Thus, when endogenous macromolecules within the cytoplasm of mammalian cells move into or out of the sensing volume, a change in the local index of refraction is induced which leads to a shift in sensor response. Moreover, if in response to a stimulus, the cell changes shape, or the endogenous material within the cell that is in close proximity to the sensor reorganizes, a shift in sensor response results. This means that RWGs are sensitive to whole cell movement and mass redistribution within a cell due to protein trafficking.
50 0.0 −50
Add thrombin −100 10 20 30 40 50 60 70 Time (min)
100 50 Add a-MSH
Add epinephrine −100
0
150
0 0
10 20 30 40 50 60 70 Time (min)
0
10 20 30 40 50 60 70 Time (min)
Figure 14. Characteristic response signatures for assays performed on the Corning Epic System for three different GPCRs in A431 cells.
GRATING-BASED OPTICAL BIOSENSORS
Figure 14 shows characteristic response signatures for assays performed on the Corning Epic System for three different G protein coupled receptors (GPCRs) in A431 cells. The GPCRs tested were the PAR1 receptor (a Gq-coupled receptor), the β2 adrenergic receptor (a Gs-coupled receptor), and the MC receptor (a Gi-coupled receptor). Addition of the corresponding agonist (thrombin (PAR1), epinephrine (B2), α-MSH (MC receptor) induces a characteristic response profile. The data show that the Epic System can distinguish between the different classes of GPCRs.
REFERENCES 1. J. J. Ramsden, Review of new experimental methods for investigating random sequential adsorption. Journal of Statistical Physics, 1993, 73, 853–877. 2. R. Horvath, N. Skivesen, N. B. Larsen, and H. C. Pedersen, Reverse symmetry waveguide for optical biosensing., in Frontiers in Chemical Sensors. Novel Principles and Techniques, Springer Series on Chemical Sensors and Biosensors, G. Orellana, M. C. Moreno-Bondi (eds), Springer, Berlin, 2005, Vol. 3, pp. 279–301. 3. W. Lukosz, Principles and sensitivities of integrated optical and surface plasmon sensors for direct affinity and immunosensing. Biosensors and Bioelectronics, 1991, 6, 215–225. 4. S.-Y. Li, J. J. Ramsden, J. E. Prenosil, and E. Heinzle, Measurement of adhesion and spreading kinetics of baby hamster kidney and hybridoma cells using an integrated optical method. Biotechnology Progress, 1994, 10, 520–524. 5. J. J. Ramsden, A sum parameter sensor for water quality. Water Research, 1999, 33, 1147–1150. 6. J. J. Ramsden, Y. P. Sherkan, N. B. Zhitov, and S. O. Korposh, Sensors for spacecraft cabin environment monitoring. Acta Astronautica, in press. 7. J. V¨or¨os, J. J. Ramsden, G. Cs´ucs, I. Szendro, S. M. De Paul, M. Textor, and N. D. Spencer, Optical grating coupler biosensors. Biomaterials, 2002, 23, 3699–3710. 8. W. Lukosz, Integrated optical chemical and direct biochemical sensors. Sensors and Actuators, 1995, B29, 37–50. 9. E. Hild, Planar waveguides as chemical and biochemical sensors, www.owls-sensors.com/pdf/products/biosensor /theory.pdf. 10. K. Tiefenthaler, Integrated optical couplers as chemical waveguide sensors, Advances in Biosensors, JAI Press Ltd, 1992, Vol. 2, 261–289. 11. J. J. Ramsden, Optical Biosensors. Journal of Molecular Recognition, 1997, 10, 109–120. 12. I. Szendro, Art and Practice to Emboss Gratings into Sol-Gel Waveguides, SPIE’s Symposium on Integrated Optics, Functional Integration of Opto-Electro-Mechanical Devices and Systems, In Proceedings of SPIE Vol. 4284 (2001), 80–87. San Jose, CA. USA.
17
13. A. Sz´ek´acs, N. Trummer, N. Ad´anyi, M. V´aradi, and I. Szendro, Development of a non-labeled immunosensor for the herbicide trifluralin via OWLS detection. Analytica Chimica Acta, 2003, 487, 31–42. 14. N. Ad´anyi, I. A. Levkovets, S. Rodriguez-Gil, A. Ronald, M. V´aradi, and I. Szendro, Development of immunosensor based on OWLS technique for determining Aflatoxin B1 and Ochratoxin A. Biosensors and Bioelectronics, 2007, 22, 797–802. 15. N. Ad´anyi, M. V´aradi, N. Kim, and I. Szendro, Development of new immunosensors for determination of contaminants in food. Current Applied Physics, 2006, 2, 279–286. 16. E. Madarasz, I. Lefkovets, K. Erdelyi, and I. Szendro, Label-free OWLS assays on the kinetics of cellattachment: Quantification of cell adhesivity, In: SBS 12th . Annual Conference, Seattle, WA. USA, 2006 September 17–21. 17. S. Stankowski and J. J. Ramsden, Voltage—dependent coupling of light into ITO-covered Waveguides. Journal of Physics D: Applied Physics, 2002, 35, 299–302. 18. M. A. Brusatori and P. R. Van Tassel, Biosensing under an applied voltage using optical waveguide lightmode spectroscopy. Biosensors and Bioelectronics, 2003, 18, 1269–1277. 19. J. P. Bearinger, J. V¨or¨os, J. A. Hubbell, and M. Textor, Electrochemical optical waveguide lightmode spectroscopy (EC-OWLS): a pilot study using evenescent-field optical sensing under voltage control to monitor plycationic polymer adsorption onto indium tin oxide (ITO)coated waveguide chips. Biotechnology and Bioengineering, 2003, 82(4), 465–473. 20. N. Ad´anyi, E. N´emeth, A. Hal´asz, I. Szendro, and M. V´aradi, Application of electrochemical optical waveguide lightmode spectroscopy (EC-OWLS) for studying the effect of different stress factors on lactic acid bacteria. Analytica Chimica Acta, 2006, 573 – 574, 41–47. 21. M. Halter, M. Gabi, M. Textor, J. V¨or¨os, and H. M. Grandin, Enhanced optical waveguide lightmode spectroscopy via detection of fluorophore absorbance. Review of Scientific Instruments, 2006, 77, 103–105. 22. H. M. Grandin, B. St¨adler, M. Textor, and J. V¨or¨os, Waveguide excitation fluorescence microscopy: a new tool for sensing and imaging the biointerface. Biosensors and Bioelectronics, 2006, 21, 1476–1482. 23. R. E. Kunz and L. U. Kempen, Miniature integrated optical sensors. Proceedings of the SPIE, 1994, 2068, 69–86. 24. R. E. Kunz, G. Duvenek, and M. Ehrat, Sensing pads for hybrid and monolithic integrated optical Immunosensors. Proceedings of the SPIE, 1994, 2331, 2–17. 25. R. E. Kunz, J. Edlinger, B. J. Curtis, M. T. Gale, L. U. Kempen, H. Rudigier, and H. Sch¨utz, Grating couplers in tapered waveguides for integrated optical sensing. Proceedings of the SPIE, 1994, 2068, 313–325. 26. J. D¨ubendorfer and R. E. Kunz, Reference pads for miniature integrated optical sensors. Sensors and Actuators, 1997, B38 – 39, 116–121. 27. G. Voirin, R. E. Kunz, H. Chai-Gao, K. Cottier, F. Crevoisier, E. Bernard, R. Ischer, and M. Wiki, New instrument based on evanescent wave for affinity sensing European. Cells and Materials, 2(Suppl. 1), 2001, 32.
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
28. K. Cottier, M. Wiki, G. Voirin, H. Gao, and R. E. Kunz, Label-free highly sensitive detection of (small) molecules by wavelength interrogation of integrated optical chips. Sensors and Actuators, 2003, B9, 1241–1251. 29. B. Cunningham, P. Li, B. Lin, and J. Pepper, Colorimetric resonant reflection as a direct biochemical assay technique. Sensors and Actuators B, 2002, 81, 316–328. 30. J. Comley, Label-free detection: New biosensors facilitate broader range of drug discovery applications. Drug Discovery World, 2005, Winter 2004/5, 63–74. 31. M. Fardad, H. Luo, Y. Beregovski, and M. Fallahi, Solgel grating waveguides for distributed Bragg reflector lasers. Optics Letters, 1999, 24, 460–462. 32. B. Daniezik, W. Ehrfeld, C. Fattinger, M. Heming, H. Lowe, A. Michel, F. Michel, N. Oranth, and J. Spinke, A Universal Transducer for Optical Interface Analytics: Transducer Design and Concepts for an Economical Mass Production, in Thin Films on Glass (Schott Series on Glass and Glass Ceramics), H. Bach and D. Krause (eds), Springer-Verlag Telos, 1997, 323–335. 33. L. J. Guo, Recent progress in nanoimprint technology and its applications. J. Physics. D: Applied. Physics, 2004, 37, R123–R141. 34. S. Tian, N. Armstrong, and W. Knoll, Electrochemically tunable surface-plasmon-enhanced diffraction gratings and their (bio-) sensing applications. Langmuir, 2005, 21, 4656–4660. 35. P. Rochon, E. Batalla, and A. Natansohn, Optically induced surface gratings on azoaromatic polymer films. Applied Physics Letters, 1995, 66, 136–138.
36. D. Kim, S. Tripathy, L. Li, and J. Kumar, Laserinduced holographic surface relief gratings on nonlinear optical polymer films. Applied Physics Letters, 1995, 66, 1166–1168. 37. R. Kunz, M. Gale, J. Edlinger, and P. Sixt, Replicated chirped waveguide gratings for optical sensing applications. Sensors and Actuators A, 1995, 46 – 47, 482–486. 38. J. Soechtig, H. Schift, B. Patterson, D. Bruce, and S. Westenhoefer, Replicated diffractive optical lens components for laser diode to fiber coupling in optical bench arrangements. Proceedings of the SPIE, 1997, 3226, 44–55. 39. F. P. Shvartsman, Replication of diffractive optics, in Diffractive and Miniaturized Optics, Vol. CR49 of SPIE Critical Reviews Series ∼Society of Photo-Optical Instrumentation Engineering, S. H. Lee, ed., Bellingham, WA., 1993, pp. 165–186. 40. M. Heckele and W. Schomburg, Review on micromolding of thermoplastic polymers. Journal of Micromechanics and Microengineering, 2004, 14, R1–R14. 41. D. Myszka, Analysis of small-molecule interactions using Biacore S51 technology. Analytical Biochemistry, 2004, 329, 316–323. 42. G. Li Fang and J. Peng, Optical biosensor provides insights for bradykinin B2 receptor signaling in A431 cells. FEBS Letters, 2005, 579, 6365–6374. 43. A. Ferrie Fang, N. Fontaine, and P. Yuen, Characteristics of dynamic mass redistribution of EGF receptor signaling in living cells measured with label free optical biosensors. Analytical Chemistry, 2005, 77, 5720–5725.
34 Holographic Sensors Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
1 INTRODUCTION
The cherished and long held perception that biosensors exploiting specific biological recognition phenomena coupled to appropriate physicochemical transducers will eventually displace all other analytical technologies within the consumer, food and beverage, environmental, military, healthcare, biotechnology, and biomedical industries has yet to be realized. After over two decades of research into biosensors, the majority of the $22.3 billion in vitro diagnostics market in 2003 could be accounted for by clinical chemistry ($7 billion), immunochemistry ($6.4 billion), and microbiology ($1 billion), with only $3.8 billion being attributable to biosensors, and with almost all of that market relating to a single analyte, glucose. The original attraction of biosensors, that is, their small size, ruggedness, inexpensiveness, fast and real-time response, ready interface with computers, facile use by lay personnel, and biocompatibility has, with the notable exception of the glucose sensor, eluded translation into reality. The commercial realization and up-take of these devices has been painfully slow, mainly because early biosensor embodiments were expensive, not sufficiently durable, and unsuited to large-scale manufacture. In addition, the key criteria for success in the sensor marketplace is that such devices should have a performance/price ratio substantially above that of existing diagnostic tests and/or they should allow important new measurements to be made. These issues are now
being addressed by coupling novel biorecognition systems to transducer technologies amenable to mass-production techniques developed for the microelectronics, printing and photography industries. Our approach relies on the concept of using a reflection hologram as the interactive element in a truly mass-producible sensor. This concept is unique in the field of chemical and biological sensors in that that the holographic element itself provides both the analyte-sensitive matrix and the optical interrogation and reporting transducer.1,2
2 HOLOGRAPHIC TRANSDUCTION
The principle of holography was established in 1948 by the Hungarian physicist Dennis Gabor (1900–1979), for which he received the Nobel Prize in physics in 1971. Gabor coined the term hologram from the Greek words holos, meaning “whole,” and gramma, meaning “message”.3 The discovery was an unexpected result of research into improving electron microscopes at the British Thomson-Houston Company in Rugby, although further development in the field was stymied during the next decade because light sources available at the time were not truly “coherent” and had to await the discovery of the laser in 1960. The first holograms which recorded threedimensional (3-D) objects were fabricated by Leith and Upatnieks in the USA and by Denisyuk in the Soviet Union in 1963. There are several types of
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
holograms: The first holograms were “transmission holograms”, which were viewed by shining laser light through them, while a later refinement, the “rainbow transmission” hologram, allowed viewing by white light and is commonly used on credit cards and product packaging as a security feature. These versions of the rainbow transmission holograms are formed as surface relief patterns in a plastic film coated on a reflective aluminium backing that provides the light from “behind” to reconstruct the imagery. Another type of common hologram, a Denisyuk hologram, is the true “white-light reflection” hologram, which is made in such a way that the image is reconstructed naturally using light on the same side of the hologram as the viewer. Holographic technology is of considerable interest in a wide variety of fields such as artistic displays, security devices, smart labels, analytical engineering, authenticity, and holographic optical elements. We have developed a deceptively simple, generic approach for the fabrication of chemical sensors based on reflection holograms embedded within “smart” hydrogel films. These sensors are based on a particular type of holographic grating known as a single-beam reflection hologram, or more commonly, a “Denisyuk” hologram.4 Conventionally, Denisyuk gratings comprise silver halide-gelatine photographic emulsions coated onto glass or plastic substrates, and are fabricated
by passing a single, collimated laser beam through the film, which is backed by a mirror.5 Interference between the incident and reflected beams creates a standing wave interference pattern,6 which after development and fixing, is observed as a threedimensional pattern comprising lines of ultrafine grains of metallic silver (∼20 nm diameter) distributed within the thickness (∼5–10 µm) of the gelatine film (Figure 1). The silver grains lie in parallel planes, known as fringes, and are separated by a distance of approximately half the wavelength (1/2λ) of the laser light used in their construction. The interference planes or fringes are parallel to the substrate surface, much like the pages of a book, and together act as a Bragg diffraction grating. Under white-light illumination, the interference fringes reflect a specific narrow band of wavelengths, which recreates a monochromatic image of the original mirror used during hologram recording. Constructive interference between partial reflections from each fringe plane gives a characteristic spectral peak with a wavelength approximately governed by Bragg’s law and determined by the spacing of the holographic fringes: mλ = 2n∂sinθ
(1)
where m is the diffraction order, λ is the wavelength of light in vacuo, n is the average refractive index of the system, ∂ is the spacing of
~51–0 µm White light illumination
~22 nm diameter Ag0 grains
∂
‘‘Smart ’’ polymer
Diffracted light (lmax)
∂ Figure 1. Cross-section of a holographic diffraction grating of thickness ∼5–10 µm and fringe spacing ∂ illuminated with white light at an angle of θ and showing diffracted light at λmax .
HOLOGRAPHIC SENSORS
the diffracting plane and θ is the glancing angle between the incident light propagation direction and the diffracting planes. Any physical, chemical, or biological mechanism that changes the spacing of the fringes (∂), the average refractive index (n) of the film or the total number of the fringes contained within the film thickness will generate observable changes in the wavelength (color) or intensity (brightness) of the reflection hologram. For example, swelling of the holographic film results in an increase in the distance between the fringes leading to a red-shift in the wavelength of reflected light. Conversely, contraction of the polymer film causes a decrease in fringe separation and thus the diffracted light is blueshifted.1 The peak reflectivity is dependent on the number of fringe planes and the modulation depth of the refractive index. In addition, any compromise of the integrity of the supporting film in such a way that it disrupts the fringe structure, results in a decrease in the intensity or brightness of the diffracted light.7,8 The interference fringe structure of the holographic grating thus acts as a reporter, whose optical characteristics are determined by the physicochemical properties of the supporting polymer film. Changes in the wavelength or intensity of the diffracted light can easily be quantified using a spectrometer and a white-light source. Other common types of hologram, for example, transmission or embossed holograms, do not behave like this as they possess an interference fringe structure, which is perpendicular to the plane of the substrate surface and this makes them insensitive to changes in the thickness of the supporting polymer film.5 The interference fringe structure of the sensor holograms are not permanently altered during such tests since the holograms can undergo many cycles of swelling and contraction and usually return to the same peak wavelength and reflectivity. It is possible to tune the reflection hologram to respond optically to the presence of specific target analytes by incorporating holograms into “smart” hydrogel films that contain appropriate receptor systems complementary to the target analytes. 3 HOLOGRAPHIC RECORDING MATERIALS
The first recorded use of a holographic system described monitoring the relative humidity in air using a conventional gelatine hologram.9 Since
3
then, gelatine-based holographic matrices have also been used for measuring the water content of organic solvents,1 and for monitoring the activity of trypsin through cleavage of peptide bonds within the gelatine film.7,8 At this point in time, the scope of sensor fabrication was limited to the range of matrices commonly available for holographic recording. Gelatinous matrices exhibit complex responses to pH and ions and are therefore inappropriate for sensing applications in biological samples of variable composition. Mayes et al.10 circumvented this problem by using poly(vinyl alcohol) (PVA) as an alternative holographic matrix, and showed that holograms fabricated in this material cross-linked with Cr(III) ions exhibited superior properties as a sensor matrix, since they were largely insensitive to interference from pH, ions, and other small molecules found in biological fluids. Functional modifications to this base matrix also allowed develoment of pH and trypsin-sensitive holograms.10 The desire for alternative holographic recording materials with other functional attributes led to the development of a novel diffusion method for generating diffraction gratings by distributing ultrafine silver bromide grains into prefabricated polymer films.11 This so-called diffusion technique involved coating a thin layer (∼10 µm thick) of unsensitized polymer film on a silanized glass slide and then immersing the slide sequentially in solutions of a silver salt and a bromide salt containing a photosensitizing dye, 1,1 ’-diethyl-2,2 ’-cyanine iodide. In this way, ultrafine grains of photosensitive silver bromide (<20 nm diameter) were precipitated within the matrix of the film and thereby transforming it into a holographic recording material. It is worth noting that the finished holograms consist only of metallic silver (Ag0 ) suspended in the polymer film and are “absorption” rather than “phase” gratings. Consequently, they rely on diffractive reflection from the silver grains and not on the refractive index difference between two transparent phases. The holograms are typically recorded in these films with a single 10 ns pulse from a frequency doubled Nd:YAG laser (532 nm). The films are positioned over a front surface mirror prior to exposure with a spacer positioned at one end to hold the film at an angle of approximately 4◦ in relation to its surface.1 This small displacement from the horizontal position prevents the fabricated
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
hologram from diffracting the incident light at the same angle as light specularly reflected from its surface. After a conventional photographic development step, illumination of the grating under white light recreates the monochromatic image of the plane mirror used in its construction with the constructive interference at each fringe plane resulting in a characteristic spectral peak with a wavelength governed by the Bragg equation. Reflection holograms created using this technique were found to have similar brightness under the same exposure and processing conditions to those made from commercially available holographic recording materials.1 The significance of this technique to the field of holography should not be underestimated, since the diffusion method circumvents the traditional laborious, emulsion-forming methods that are currently used to construct holographic recording materials.12 Significantly, for the fabrication of sensor holograms, the diffusion method makes it possible to record silver halide volume holograms in a wide range of previously inaccessible natural and synthetic polymer films, even those that are somewhat hydrophobic13 or would otherwise encourage very rapid grain-growth of the colloidal silver particles.14 The finished holograms are robust and relatively unresponsive to changes in the physical environment. For example, the holograms are not light sensitive, since the grating consists only of Ag0 metal and, with a suitable choice of polymeric base matrix, do not change color with temperature. Nevertheless, it is advisable to thermostat the temperature of the medium in which the analysis is performed to ±1 ◦ C. The simplicity and rapidity of this technique, combined with the sensing capability of “smart” hydrogels, offers the possibility to construct a range of inexpensive optical sensors selective for many putative analytes. The base materials selected for the fabrication of the holographic diffraction gratings usually belong to a category of polymers termed “hydrogels”. These polymers comprise 3-D networks characterized by their pronounced capacity to absorb large amounts of water, which can range from being mildly absorbing retaining approximately 30% (w/w) within their structure, to strongly absorbing where they can swell up to 1000% their original volume.15 Hydration of these materials is encouraged by the hydrophilic nature of
the polymer chains but is restricted both by their cross-linking through covalent or ionic bonding and by secondary forces such as hydrogen bonding or hydrophobic interactions.16,17 Hydrogels may be tailored to undergo macroscopic volumetric changes in response to relatively small changes in environmental conditions,18 induced by numerous physical and chemical stimuli including pH,19 temperature,20,21 solvents,13 ions22,23 and specific chemical24 and biological analytes.25 Such analyte-sensitive hydrogels are known as smart polymers.18 Incorporation of a reflection hologram throughout the volume of a smarthydrogel, results in a holographic sensor whose diffraction characteristics are dependent upon interaction with the analyte of interest. Holograms have been fabricated within a broad range of natural and synthetic polymer matrices such as cross-linked poly (hydroxyethyl methacrylate) HEMA, PVA, poly (acrylamide) and various starch and proteinaceous materials to generate sensors that respond to a variety of putative analytes.
4 ANALYTE-RESPONSIVE HOLOGRAPHIC SENSORS 4.1
Gases
Holographic gratings that respond to aerial or dissolved gases have yet to be reported in the literature. Preliminary work in the author’s laboratory has suggested that holographic sensors responsive to O2 and CO2 can be constructed, albeit to date with limited sensitivity and selectivity. For example, four separate species of carbon dioxide (CO2 ) exist in aqueous solution: dissolved carbon dioxide (CO2(aq) ), carbonic acid (H2 CO3(aq) ), bicarbonate 2− (HCO− 3 (aq) ) and carbonate (CO3 (aq) ) and all contribute to the mass of aqueous carbon dioxide: [aqCO2 ] = [CO2(aq) ] + (H2 CO3(aq) ] 2– + [HCO− 3 (aq) ] + [CO3 (aq) ]
(2)
A poly-HEMA based hologram comprising poly (2hydroxyethyl methacrylate-co-2-aminoethyl methacrylate-co-ethylene dimethacrylate) (pAEMA) contracts in the presence of aqCO2 at pH < 7 and swells at higher pH values. At pH > 9, the primary
HOLOGRAPHIC SENSORS
amine functions within the gel are deprotonated and are free to form carbamates with the aqCO2 :
5
was monitored through the rear of the device, which was not in contact with the test solution.
Polymer ∼ NH 2 + HOCO− 2 ←−→ Polymer ∼ NHCO− 2
(3)
The pAEMA hologram swells by up to 15% in response to 100 mM aqCO2 at pH 9.0, while the base poly-HEMA polymer does not respond to aqCO2 at any pH value. These studies are the subject of ongoing research into gas-sensitive holographic sensors.
4.2
Water and Solvents
Holographic gratings have been fabricated for the direct measurement of water activity in apolar liquids.1 Immersion of gelatine-based holograms in “wet” hydrophobic solvents results in preferential partition of water into the holographic phase from the bulk solution. The resultant swelling and consequent red-shift in the diffraction wavelength is directly proportional to the water activity (aw ) of the liquid sample. The holographic sensors generate a visual color change within the visible spectrum and offer the prospect of use in a semiquantitative format without the need for additional instrumentation. The holographic water sensors are likely to find widespread application as power-free water activity sensors in the petrochemical, food, textiles, electronics, and pharmaceutical industries. It is possible to tailor the response of the holographic sensors to detect different solvents in aqueous solutions by varying the hydrophobicity of the film in order to modulate the partition coefficient of the solvent. For example, a series of sensor holograms have been constructed in a range of synthetic polymeric materials and tested for their use as an alcohol sensor.13 Sensor holograms prepared in cross-linked poly-HEMA displayed a redshift in diffraction wavelength, which was directly proportional to alcohol content across a wide concentration range. This alcohol-sensitive hologram was used to measure the ethanol content of a range of commercial alcoholic beverages such as wines, beers, and spirits to within ±0.3% (v/v) of their stated value.12 The optical signal from the sensor hologram was unaffected by highly colored and/or turbid alcohol samples since the reflected signal
4.3
pH
The determination of pH and many ionic species is essential within the biomedical, environmental, food, beverage, security, agricultural, and biotechnology industries. In order to create pH-sensitive holograms, the Bragg gratings are recorded within hydrogels containing acidic or basic monomers copolymerized within the polymeric backbone.25 Ionization of the pendant functional groups causes the grating to swell or contract as a result of electrostatic and osmotic forces that draw in, or expel, counterions and water into or out of the gel phase. This movement of counterions and water changes the fringe separation and causes longer or shorter wavelengths to be selected for reflection from the holographic mirror; thus, the diffraction wavelength of the sensor hologram is dependent on the pH of the bulk medium. Holographic sensors for monitoring H+ (pH) have been fabricated from two different hydrogel systems based on poly-HEMA and poly-(acrylamide). Copolymerization with monomers bearing ionizable groups and suitable cross-linkers has been shown to confer a characteristic pH-sensitivity dependent on the individual functional monomer incorporated. Reversible and visually perceptible color changes occur either side of an apparent dissociation constant (pKa ) and are governed by the nature of the ionizable monomer incorporated into the holographic matrix. It is possible to tune the response of the resultant sensor hologram to the pH range of interest for a particular application through selection of acidic or basic monomers with appropriate pKa values. Unlike other optical pH sensors, it is possible to tailor the operational replay wavelength of the holographic sensor by careful control of the exposure conditions. The effects of hydrogel composition, ionic strength, temperature, and factors influencing reversibility and response time have been evaluated. Optimized holographic pH sensors show milli-pH resolution. The pHsensing range of the holograms can be controlled through variation of the nature of the ionizable comonomer used in polymer film construction; a series of holographic sensors displaying visually perceptible, fully reversible color changes over
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
different pH ranges are demonstrated (Figure 2). A poly(hydroxyethyl methacrylate-co-methacrylicacid) holographic sensor was shown to be able to quantify the change in H+ concentrations in real time in a sample of milk undergoing homolactic fermentation in the presence of Lactobacillus casei.26
4.4
Ions
The rational modification of poly-HEMA with crown ethers was investigated to develop sensor holograms for K+ and Na+ .27 Crown ethers are well-known to form strong complexes with metal ions in solution.28 Methacrylated crown ethers were incorporated into the poly-HEMA film during photopolymerization and holograms containing 0–97 mol% either 12-crown-4, 15-crown-5, or 18crown-6 were shown to respond to alkali and alkaline earth ions with varying magnitudes and specificity. Optimized compositions containing 50 mol% crown ether showed λ responses ≤200 nm within 30 s at ion concentrations ≤30 mM. Holograms constructed with 18-crown6 were shown to respond linearly over the physiological K+ concentration range (Figure 3). Furthermore, the sensor was virtually unaffected by normal physiological variations in background Na+ levels (∼130–150 mM), highlighting its potential for use as a blood potassium sensor.27 Further work has investigated the use of holograms for the detection of divalent metal ions, such (a)
(b)
Figure 3. The effect of 20 mM K+ on an 18-crown-6 containing poly-HEMA hologram in the presence of 150 mM Na+ .
Figure 2. Visual appearance of a poly-HEMA-co-methacrylic acid hologram at three pH values demonstrating replay wavelengths in the visible range.
as Ca2+ , Mg2+ , Ni2+ , Co2+ and Zn2+ , by incorporating chelating monomers into the holographic matrix. A methacrylated analogue of iminodiacetic acid (IDA) was successfully incorporated into a poly-HEMA hologram cross-linked with ethylene glycol dimethacrylate (EDMA) to confer sensitivity to the presence of Ca2+ , Mg2+ , Co2+ and Zn2+ ions.29 The effects of active monomer and cross-linker concentration, pH, and ionic strength on the swelling of the holographic matrix and on the sensitivity to various metal ions were studied.
HOLOGRAPHIC SENSORS
The sensor showed reversible responses to divalent metal ions and was used for the real-time monitoring of Ca2+ ion efflux during the early stages of germination of Bacillus megaterium spores.29
4.5
Ionic Strength
Holograms for monitoring ionic strength have been fabricated from charged sulphonate and quaternary ammonium monomers incorporated into the holographic sensor matrix.30 The reflected color of the holograms was used to follow their swelling or contraction as a function of ionic strength in various media. The effects of comonomer structure, buffer composition, ion composition, pH and temperature were assessed as a function of the reversibility and reproducibility of the sensor. The sensor was freely reversible with no sign of hysteresis and exhibited little response to pH within the range 3–9 and temperature within the range 20–45 ◦ C. In contrast to sensors that rely on monomers of a single polarity, the sensors could quantify ionic strength independent of the identity of the ionic species present in the test solution. This system was used to quantify the ionic strength of milk solutions, which contain a complex mixture of ions and biological components.30
4.6
Enzymes and Enzymatic Reactions
Holographic Bragg gratings can also be exploited to measure enzyme activity7,8,10,15 or substrate concentrations.31 The simplest example is the use of holographic sensors to measure lytic enzymes such as proteases, carbohydrases, or lipases. For example, if an enzyme cleaves bonds in the holographic matrix backbone or pendant functionality, the matrix may swell and a red-shift in diffraction wavelength occurs. The holographic sensor swells as the effective cross-linking density of the polymeric network is decreased by the catalytic action of the enzyme. This approach has been exemplified with a gelatine-based Bragg reflector, which was used to quantitate the activity of the serine protease trypsin, which cleaves peptide bonds within the gelatine film.7,8 The holographic element constructed in gelatine and designed to
7
replay in a narrow range of peak wavelengths (665–696 nm) was responded to a range of trypsin concentrations as low as 25 nM with a response time of ∼20 min. Subsequent work involved constructing PVA holograms modified with the trypsin substrate, poly-(L-lysine). The incorporation of poly-(L-Lysine) rendered the otherwise unresponsive hologram, sensitive to the protease trypsin, while remaining unresponsive to other proteases such as chymotrypsin.15 A control hologram comprising a poly-(D-Lysine) modified PVA matrix also proved unresponsive to trypsin. A similar approach has been used to quantify α-amylase activity, although in this case a starch- or starchpolyacrylamide Bragg grating7 was used. The enzyme α-amylase degrades the starch base and results in a decrease in both diffraction efficiency and wavelength. This behavior demonstrates the potential of the sensor technology to detect abnormal levels of trypsin or α-amylase in pancreatic or salivary extracts and thus provide a marker for pancreatic disorders.
4.7
Metabolite Sensors
The sensor hologram is also able to detect the products of enzymatic reactions. The concept of utilizing enzyme-linked holographic sensors was demonstrated for the clinically and industrially relevant metabolites urea and penicillin G.31 The action of the enzymes urease (EC 3.5.1.5) and penicillinase (EC 3.5.2.6) on their respective substrates, urea, and penicillin G, is known to cause acidification or alkalization of a test solution. Each enzyme was immobilized to an appropriate holographic pH sensor and the pH changes resulting from the enzymatic reactions were sensitively measured and correlated with the original levels of urea and penicillin. For example, an abnormally high level of urea in blood is a strong indication of kidney dysfunction, with the normal range being 1–10 mM and the abnormal range being up to 100 mM. Urease catalyzes the hydrolysis of urea into ammonium and bicarbonate ions: − (NH2 )2 CO + 2H2 O + H+ −−−→ 2 NH+ 4 + HCO3 (4) and was used to monitor urea by immobilizing the enzyme on a 6 mol% dimethylaminoethyl methacrylate (DMAEM) pH-sensitive hologram.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
A linear response up to about 20 mM urea was obtained. These devices are representative of a generic system whereby individual enzymes or a series of linked enzymes can be integrated with holograms to generate a family of inexpensive/disposable sensors for a wide range of biochemical metabolites. Alternatively, coentrapment Pf enzymes within the holographic matrix can be used to eliminate potential interferences or amplify weak responses to other analytes.
4.8
Glucose
Diabetes represents one of the largest health concerns of the twenty-first century since it currently afflicts approximately 6% of the global population and is expected to double by 2025 to 300 million.32 Holograms that detect glucose have been fabricated from hydrogel films containing a base matrix modified with chemical ligands based on phenylboronic acid. The ability of boronic acids to bind reversibly compounds containing cis-diols such as glucose has long been known.33,34 However, at low pH, boronic acids exist in an uncharged trigonal planar configuration, while at higher pH values (pH > pKa ; >8.8) the trigonal form can react with OH− to form the more stable negatively charged tetrahedral state, which binds cis-diols more readily. Consequently, the requirement of conventional boronates for pH values >8.8 to effect binding of glucose presents a challenge for monitoring this metabolite in biological samples. However, more recently, new boronic acid derivatives that bind glucose at physiological pH values have been developed and these have been used in sensor hologram fabrication. Acrylamide-based hydrogels containing the monomer 3-acrylamidophenylboronic acid (3APB) have been fabricated and the chemical composition of the films optimized for glucose detection using embedded reflection holograms.35,36 Maximum sensitivity was observed at a functional monomer concentration of 20 mol%. The sensor holograms display a monotonic redshift in diffraction wavelength as a function of glucose concentration across the normal glucose concentration range (2–10 mM) at physiological pH and ionic strength values. It is believed that glucose diffuses into the holographic matrix from
the bulk medium and binds to the pendant boronic acid groups. This effectively decreases the pKa of the boronic acid–glucose complex by stabilizing the charged tetrahedral phenylboronate anion and the presence of these charged groups within the polymer generates a Donnan potential resulting in an osmotic pressure that causes the hologram to imbibe more water, swelling and thereby shifting the diffraction wavelength toward the red end of the spectrum. The reaction of glucose with boronic acids is unusual since the covalent bond formed between the two molecules is reversible in aqueous media and when the glucose is removed from the bathing medium, the hologram contracts and returns to its original diffraction wavelength.37 These observations suggest that the sensor is suitable for continuous real-time sensing of dynamic changes in glucose concentration. Current work in glucose detection is focused on assessing the performance of these sensor holograms for the detection of glucose in complex biological media and their incorporation into a suitable sensor format for continuous glucose monitoring in human subjects.38 The sensor responds to glucose in the presence of lactate (Figure 4).
4.9
Lactate
L-lactate is a metabolite generated during anaerobic metabolism and is a useful indicator in the food industry, fermentation, clinical diagnostics, and exercise performance in sports medicine. The synthetic receptors based on phenylboronates are
20 10 ∆lmax (nm)
8
Lactate
0 −10 −20 −30 −40 −50
2
4
6 mM
8
10
12
Glucose/4mM Lactate Glucose
Figure 4. Response of a 11.9 mol% 3-APB (3-acrylamidophenylboronate)/ 9.2 mol% DAPA (N -[3-(dimethylamino)propyl]acrylamide)/ 2.9 mol% MBA (N ,N -Methylenebisacrylamide)/acrylamide copolymer hologram to glucose and lactate on PBS buffer pH 7.4 at 30 ◦ C.
HOLOGRAPHIC SENSORS
known to bind with bidentate chelating ligands to form 5- and 6-membered cyclic esters.38 The boronates bind saccharides and other carbohydrates as well as o-diphenols, o-hydroxy acids, dicarboxylic acids, and α-hydroxy acids such as L-lactate. Consequently, a significant challenge has been to devise a boronate analogue, which selectively binds lactate compared to glucose. Preliminary studies have demonstrated that a hologram containing a reduced concentration (5 mol%) of 3-acrylamidophenylboronate (3-APB) shows an improved sensitivity for L-lactate over glucose.39
4.10
Bacteria
There is substantial interest in use of small-scale bioprocesses (∼nanoliter to microliter volumes) for fast, reliable, and inexpensive high-throughput biology to enable both early process development studies and the screening of drug candidates for drug discovery. However, in such small volumes and in a parallel format, it is impossible to use standard industrial sensors because of their relatively large dimensions. The sensor holograms have been successfully used to monitor the metabolic products of small-scale (<1 µl) microbial fermentations since they are readily miniaturized and can be sterilized in situ by autoclaving. For example, sensor holograms have been used to monitor the homolactic fermentation of milk by Lactobacillus casei thorough the change in pH generated during the fermentation process.15 In other work, the depletion of glucose during the growth of Bacillus subtilis has been monitored holographically using glucose sensor holograms.30 In this case, the sensor holograms offer the considerable advantages over conventional enzymebased alternatives since they do not consume glucose, and thereby do not reduce substrate levels in small volume bioreactors that can lead to alterations in the metabolism of the living cells being monitored. Calcium ion sensor holograms have been applied to monitor the germination of Bacillus megaterium spores by measuring the efflux of calcium into the medium in real time.20 The organism is a model for Bacillus anthracis, and current work is focused on further characterizing this approach and assessing its potential for deployment as a rapid anthrax detection and identification system.
9
5 SUMMARY
The combination of “smart” responsive polymeric matrices, which incorporate selective recognition elements for target analytes, with holographic gratings provides an inexpensive and generic sensor technology. The Bragg diffraction gratings act as an optically interrogatable reporting system that enables analyte-induced changes in the swellability of the supporting polymer layer to be accurately and rapidly determined in real time. A wide range of natural, synthetic, or rationally designed films that would not ordinarily be suitable for use as holographic recording materials may be used for the fabrication of these “smart” holograms. The resultant sensors have proven suitable for use in opaque and very turbid samples and are very stable with respect to calibration, as, unlike optical sensing methodologies involving fluorescent dyes, the gratings do not suffer problems associated with quenching or photobleaching. These characteristics suggest that these sensor holograms may be highly suitable for the construction of simple, inexpensive, and robust (bio)chemical sensors that can be readily deployed in the field for use at the point-of-need. Furthermore, their relatively rapid response times suggest their application in real-time monitoring of clinical analysis in vivo.
REFERENCES 1. J. Blyth, A. G. Mayes, E. R. Frears, R. B. Millington, and C. R. Lowe, A holographic sensor for water in solvents. Analytical Chemistry, 1996, 68, 1089–1094. 2. C. R. Lowe, Chemoselective biosensors. Current Opinion in Chemical Biology, 1999, 3, 106–111. 3. D. Gabor, A new microscopic principle. Nature, 1948, 161, 777–778. 4. Y. N. Denisyuk, On reproduction of optical properties of an object by wave field of its scattered radiation. Optics and Spectroscopy-USSR, 1965, 18, 152–15-. 5. G. Saxby, Practical Holography, 2nd Edn, Prentice Hall, Englewood Cliffs, 1994. 6. G. Saxby Manual of Practical Holography, 1st Edn, Butterworth-Heinemann Ltd, 1991. 7. R. B. Millington, A. G. Mayes, J. Blyth, and C. R. Lowe, A holographic sensor for proteases. Analytical Chemistry, 1995, 67, 4229–4233. 8. R. B. Millington, A. G. Mayes, J. Blyth, and C. R. Lowe, A holographic biosensor for proteases. Sensors and Actuators, 1996, B33, 55–59.
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
9. R. C. Spooncer, F. A. S. Al-Ramadhan, and B. E. Jones, A humidity sensor using a wavelength-dependent holographic filter with fibre optic links. International Journal of Optoelectronics, 1992, 7, 449–452. 10. A. G. Mayes, J. Blyth, R. B. Millington, and C. R. Lowe, Metal ion-sensitive holographic sensors. Journal of Molecular Recognition, 1998, 11, 168–174. 11. J. Blyth, R. B. Millington, A. G. Mayes, and C. R. Lowe, A diffusion method for making silver bromide based holographic recording material. Imaging Science Journal, 1999, 47, 87–91. 12. I. Leubner, R. Jagannathan, and J. Wey, Formation of silver bromide crystals in double-jet precipitation. Photographic Science and Engineering, 1980, 24, 268–272. 13. A. G. Mayes, J. Blyth, M. Kyrolainen-Reay, R. B. Millington, and C. R. Lowe, A holographic alcohol sensor. Analytical Chemistry, 1999, 71, 3390–3396. 14. C. R. Lowe, J. Blyth, A. J. Marshall, A. James, S. Kabilan, M. C. Lee, B. Madrigal-Gonzalez, X.-P. Yang, and C. A. B. Davidson, Holographic biosensors. SPIE Optical Engineering Magazine, 2003, 20–23. 15. J. M. Seidel and S. M. Malmonge, PolyHEMA hydrogels for using as biomaterials. Materials Research, 2000, 3, 79–83. 16. P. J. Flory, Principles of polymer Chemistry, Cornell University Press, Ithaca, 1953. 17. X. Qu, A. Wirsen, and A. C. Albertsson, Synthesis and characterisation of pH-sensitive hydrogels based on chitosan and D,L-lactic acid. Journal of Applied Polymer Science, 1999, 74, 3193–3202. 18. A. S. Hoffman, Molecular bioengineering of biomaterials in the 1990s and beyond: a growing liaison of polymers with molecular biology. Artificial Organs, 1992, 16, 43–49. ˇ 19. J. KopeSek, Polymer chemistry: swell gels. Nature, 2002, 417, 388–391. 20. M. Marchetti, S. Prager, and E. Cussler, Thermodynamic predictions of volume changes in temperature-sensitive gels. I.2.10 theory. Macromolecules, 1990, 23, 1760–1765. 21. W. F. Lee and W. F. Yuan, Thermoreversible hydrogels XV swelling behaviours and drug release for thermoreversible hydrogels containing silane monomers. Journal of Applied Polymer Science, 2002, 84, 2523. 22. D. Hariharan and N. Peppas, Modelling of water transport and solute release in physiologically sensitive gels. Journal of Controlled Release, 1993, 23, 123–136. 23. P. Markland, Y. Zhang, G. L. Amidon, and V. C. Yang, A pH- and ionic-strength responsive polypeptide hydrogel: synthesis, characterisation and preliminary protein release studies. Journal of Biomedical Materials Research, 1999, 47, 595–602. 24. T. Chandy and C. P. Sharma, Glucose-responsive insulin release from poly(vinyl alcohol)-blended polyacrylamide
25. 26.
27.
28. 29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
membranes containing glucose oxidase. Journal of Applied Polymer Science, 1992, 46, 1159–1167. T. Miyata, N. Asami, and T. Uragami, A reversibly antigen-responsive hydrogel. Nature, 1999, 399, 766–769. A. Marshall, J. Blyth, C. A. B. Davidson, and C. R. Lowe, pH-sensitive holographic sensors. Analytical Chemistry, 2003, 75, 4423–4431. A. G. Mayes, J. Blyth, R. B. Millington, and C. R. Lowe, Metal ion-sensitive holographic sensors. Analytical Chemistry, 2002, 74, 3649–3657. P. Groth, Acta Chemica Scandinavica Series A, 1981, 35, 463. B. Madrigal-Gonzalez, G. Christie, C. A. B. Davidson, J. Blyth, and C. R. Lowe, Bivalent metal ion-sensitive holographic sensors. Analytica Chimica Acta, 2004, 527, 13–20. A. J. Marshall, D. Young, S. Kabilan, A. Hussain, J. Blyth, and C. R. Lowe, Holographic sensors for the determination of ionic strength. Analytica Chimica Acta, 2005, 527, 13–20. A. J. Marshall, D. Young, J. Blyth, S. Kabilan, and C. R. Lowe, Metabolite-sensitive holographic sensors. Analytical Chemistry, 2004, 76, 1518–1523. H. King, R. E. Aubert, and W. H. Herman, Global burden of diabetes, 1995–2025. Prevalence, numerical estimates and projections. Diabetes Care, 1998, 21, 1414–1431. J. P. Lorand and J. O. Edwards, Polyol complexes and structure of the benzeneboronate ion. Journal of Organic Chemistry, 1959, 24, 769–774. M. C. Lee, S. Kabilan, A. Hussain, X.-P. Yang, J. Blyth, C. A. B. Davidson, and C. R. Lowe, Glucose-sensitive holographic sensors. Journal of Molecular Recognition, 2004, 17, 162–166. S. Kabilan, A. J. Marshall, F. K. Sartain, M. C. Lee, A. Hussain, X. P. Yang, J. Blyth, N. Karangu, K. James, J. Zeng, D. Smith, A. Domschke, and C. R. Lowe, Holographic glucose sensors. Biosensors and Bioelectronics, 2005, 20, 1602. M. C. Lee, S. Kabilan, A. Hussain, X.-P. Yang, J. Blyth, and C. R. Lowe, Glucose-sensitive holographic sensors for monitoring bacterial growth. Analytical Chemistry, 2004, 76, 5748–5755. A. P. Davis and R. S. Wareham, Carbohydrate recognition through non-covalent interactions: a challenge for biomimetic and supramolecular chemistry. Angewandte Chemie International Edition, 1999, 38, 2978–2996. A. Domschke, W. F. March, S. Kabilan, and C. R. Lowe, Initial clinical testing of a holographic non-invasive contact lens glucose sensor. Diabetes Technology and Therapeutics, 2006, 8, 89–93. F. K. Sartain, X.-P. Yang, and C. R. Lowe, A holographic lactate sensor. Analytical Chemistry, 2006, In Press.
35 Introduction to Acoustic Technologies Bernardita Araya-Kleinsteuber and Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
1 INTRODUCTION
Acoustic sensors are a relatively new concept in biosensing applications, as only in the last 50 years they have been in active use in chemical analysis. However, acoustic wave (AW) devices have been in active use for more than 60 years, especially in the telecommunications industry, where piezoelectric elements can be found in all kinds of electronic devices, such as radar, computers, mobile phones, and so on. In general, the principle is based on a mechanical wave propagating through piezoelectric or other materials, in which any material changes at the material surface will modify the propagation path of the wave, which in turn will alter the electrical response of the sensor. The latter can be easily tracked down and correlated to changes in the material being measured.1–5 The feature of high sensitivity to surface changes has opened a whole new approach for biosensing applications, where acoustic sensors have proven to be a useful tool for the analysis of interactions of biomolecules with surfaces.1,5–9 In the simplest cases, these devices act as gravimetric sensors, responding to mass accumulation on the sensors. Since all analytes possess mass, any species that can be immobilized on the device surface can, in principle, be sensed. In this context, all acoustic sensors are sensitive, to varying degrees, to perturbation to changes in many physical or chemical parameters, like force, film thickness, mass, concentration,
viscosity, etc.,2,10–14 and have been actively used for understanding the mechanical properties of films.1,15,16 More recently, acoustic sensors have been used for the analysis of interfacial phenomena, such as surface roughness, stress, and slip.17 However, the main difficulty for biosensing applications is achieving selectivity, which can be partially overcome through the design of the sensor system. The range of phenomena that can be detected by AW devices can be greatly expanded by coating the devices with materials that undergo changes in their mass, elasticity, or conductivity upon exposure to a particular physical or chemical stimulus, with the most common approach being the attachment of an analyteselective film. One of the main advantages of acoustic sensing is that can offer real-time measurement of surface interactions, which is of particular interest in the study of protein binding events and immunochemical reactions. Some of the more common techniques used for those purposes, such as radiochemical and fluorescent tagging, X-ray photoelectron spectroscopy and atomic force microscopy provide no dynamic information regarding the kinetics of adsorption or ligand–ligand binding processes. Therefore, acoustic devices as biosensors provide an alternative to optical techniques such as surface plasmon resonance or optical waveguides, which can also offer real-time study of interfacial protein chemistry.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Newer prospects include automotive (torque and tire pressure sensors), and industrial and commercial applications (vapor, humidity, temperature, and mass sensors). In general, AW sensors are competitively priced, very sensitive, and reliable. Some are also capable of being passively and wirelessly interrogated. This chapter will give a general overview of acoustic sensing, beginning on how AWs are created in crystals, followed by the basis for construction of acoustic sensors, including materials and electrodes configuration. Finally, a description of the modes of vibration possible in an acoustic sensor is included. The next section focuses on the different types of acoustic sensing devices: the thickness shear mode (TSM) resonators, the acoustic plate mode (APM) device, the surface acoustic wave (SAW) sensor, and the flexural plate wave (FPW) device. For each of the devices, general considerations of construction are given, including a description of the acoustic response dependence on mass. To conclude, an overview of the common applications of acoustic sensors is given.
2 ACOUSTIC WAVE GENERATION IN PIEZOELECTRIC CRYSTALS
For acoustic sensing purposes, a key aspect is the conversion between mechanical vibrations and electrical energy, which is possible due to the piezoelectric properties of the sensing element. Piezoelectricity, which was first discovered by the Curie brothers in 1880,18 occurs in crystals having one or more polar axes or in the absence of a center of symmetry. The piezoelectric effect arises when pressure applied to a dielectric material deforms its crystal lattice, which in turn causes a change in the distribution of charges in the atoms and bonds, generating a net macroscopic electrical polarization of the crystal.19 If electrical contacts (electrodes, electronic conducting films) are applied to the sides of a thin slab or rod of a piezoelectric material, current will flow through an external circuit when stress is applied to the crystal. When the stress is released, then the current flows in the opposite direction. The converse piezoelectric effect is experienced when a crystal is strained by an electric field, normally through an alternating voltage applied
to the attached electrodes, which in turn causes electronic displacement of the lattice, and consequently mechanical oscillations occur within the crystal lattice. Under these conditions, oscillating electric fields produce mechanical oscillations in the crystal.1,8 In this context, piezoelectric acoustic sensors make use of oscillatory coupling between strain and electrical polarization that allows the electrical generation of AWs in a crystal.1,3 These oscillations are stable only at the natural resonant frequency of the crystal. At that frequency, impedance of the crystal to the exciting voltage is low. If the crystal is incorporated into the feedback loop of an an acoustic sensor oscillator circuit, it becomes the frequency determining element of the circuit, as its quality factor, Q, is very high. When analyzing resonant systems, a crucial definition is the Q factor of the resonant peak. Q refers to a measure of the “quality” of a particular resonance, and represents the ratio of acoustic energy storage and dissipation. In general, Q is a measure of the sharpness of the resonant peak in the frequency response of the system and is inversely proportional to the energy dissipation or damping in the system.5,18,20 It can be written as Q ≡ fR /BW, where fR is the resonant frequency and BW is the bandwidth; it can be equally presented as ω Up /Pd , where ω is the angular frequency, Up is peak total energy present in the device, and Pd is the power dissipated by the device.1 As explained before, when a voltage is applied to a quartz crystal, piezoelectric properties lead to a mechanical strain, where atomic positions move accordingly to the attraction and repulsion of the charge center. The application of an alternating voltage causes the displaced lattice to store energy in electrostatic bonds, which can propagate through the material. Displaced atomic positions also transfer forces to neighboring atomic planes such that the energy is transmitted as a wave. Near the resonant frequency, this storage and reflection of energy creates a standing wave in the material, known as an acoustic resonance.2,3,21 Resonance can be defined as an increase in the oscillatory energy absorbed by a system when the frequency of the oscillations matches the system’s natural frequency of vibration, which is the resonant frequency. In general, a resonant object, whether mechanical, acoustic, or electromagnetic, will probably have more than one
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
resonant frequency. When a stimulus is applied, the system will select its resonant frequency while it is filtering out all frequencies other than its resonance. All frequencies at which the system resonates are known as the harmonic series, while the fundamental frequency corresponds to the lowest resonant frequency of a harmonic series. The resonant frequency depends on the physical dimensions of the crystal and will change if material is placed on the surface.5,22 This occurs because an oscillating piezoelectric crystal will also transfer its vibratory energy to the medium that surrounds it. If the medium is a fluid, the acoustic energy dissipates through frictional losses that occur near to the solid–liquid interface, according to the mechanical properties of the region. For this reason, an acoustic sensor will sense only the mass or liquid within the penetration depth of the wave into the fluid.23 This scenario is the basis for piezoelectric crystals operating as sensors, where acoustic changes in amplitude or frequency are detected when the device interacts with its environment.
3 ACOUSTIC DEVICES
The typical acoustic device consists of a piezoelectric material with one or more metal transducers on its surface(s). These transducers launch AWs into the material at ultrasonic frequencies, which may range from one to hundreds of megahertz. The transducer metal is usually selected for either chemical inertness (e.g., gold) or for its acoustic match to the piezoelectric material (e.g., aluminium on quartz). The piezoelectric material may consist of a polished plate or an oriented thin film. Among piezoelectric materials, quartz is the most frequently used matrix because of its high Q factor, its stability with respect to temperature, its small size and low cost, which leads to a highly versatile material for sensing purposes.3,4,8,24 There are several other piezoelectric materials used for acoustic sensing, for example, lithium niobate has higher acoustoelectric coupling and is a good candidate for high temperature applications due to its higher Curie temperature. The Curie temperature refers to the temperature above which the material loses its the piezoelectric properties.25 Following the work of the
3
Curie brothers, Rochelle salts (sodium potassium tartrate tetrahydrate NaKC4 H4 O6 · 4H2 O) were widely used for its piezoelectric properties, however, it has several disadvantages as a practical material as it must be stored under conditions of 40–85% humidity, decomposes at 328.8 K and is extremely soluble in water.26 Thin films of zinc oxide, applied by sputtering techniques, are used when very thin plates are desired or when the device must be created entirely by microfabrication or micromachining methods on a nonpiezoelectric substrate such as silicon.19 Table 1 presents some properties of piezoelectric materials commonly used for acoustic sensors fabrication. The design of quartz crystal resonators is strongly dependent on the orientation of the crystal with respect to its reflective faces. Quartz is an anisotropic material, so most of its physical properties depend crucially on direction, such as the elastic and electrical properties, which in turn affect the temperature coefficient.3,24 For this reason it is necessary to consider the crystal Cartesian axes and the orientation of the different cuts when designing an acoustic sensor. Figure 1 presents the Cartesian axes for a quartz crystal, where the X axis passes through a vertex and the Y axis at right angles of a face. The Z axis is considered to be the optic axis, as the crystal is not piezoelectric in that direction and presents unique optical properties, associated with a complex refractive index. X and Y axes are piezoelectrically active; therefore, if a field is applied to the crystal parallel to the X axis, the thickness in the X direction increases. On the other hand, when the field is aligned with the Y axis, there is shear deformation along the Z axis.3,24,32 One of the most common cuts for resonator applications is the AT cut. This is made by cutting the quartz normal to the Y axis (parallel to X) and rotated 35◦ 15 from the Z axis,33,34 where an applied voltage across the crystal faces produces oscillation in shear mode, with no thickness extension. One of the key characteristics of an AT-cut quartz crystal is a zero temperature coefficient near room temperature, allowing a great variety of applications, particularly in frequency control.3,24,33 Other commonly used cut of quartz is the ST. The ST-cut quartz is basically an AT-cut plate with the surface normal rotated 42.75◦ from the Y axis. Rotated Y cuts of quartz in this region
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Table 1. Properties of some piezoelectric materials. The range for the piezoelectric coefficient corresponds to the different strains possible in the crystal axis
Density (103 kg m−3 )
Material
Formula
Form
Quartz Rochelle salts Lithium tetraborate Lithium niobate Lithium tantalite Gallium arsenide Zinc oxide Lead zirconate titanate
SiO2 NaKC4 H4 O6 · 4H2 O Li2 B4 O7
Single crystal Single crystal Single crystal
LiNbO3 LiTaO3 GaAs ZnO PbZr0.6 Ti0.4 O3
Single crystal Single crystal Single crystal Single crystal Polycrystalline ceramic
d piezoelectric coefficient (10−12 C/N)
Upper temperature limit (Curie) (C)
2.695(a) 1.77(b) 2.45(d)
2.3(a) 27–290(a) 8–19(b)
550(b) 45(b) Melt 917(c)
4.628(d) 7.454(d) 5.316(d) 5.665(a) 7.5(b)
6–69(e) 5–20(e) 11.5(e) 80–320(c) 57–140(b)
1133(e) 604(e) 25(h) 7–27(f)(g) 300(b)
(a)
Ref. 1. Ref. 27. Ref. 20. (d) Ref. 28. (e) Ref. 29. (f) Ref. 30. (g) ZnO:(Co, Mn, Cr, or Ni) ZnO coupled with Cobalt, Manganese, Chromium or Nickel. (h) Ref. 31. (b) (c)
Z
Y′
X
Z
X
Y
X′
Y
Z′
Figure 1. Cartesian axes for a quartz crystal.
give parabolic frequency temperature characteristics, and hence provide excellent temperature stability. The turnover temperature may be varied by adjusting the cut angle.1 A summary of the AW sensor fabrication process is shown in Figure 2. The type of acoustic device and the selection of the substrate determines which process module is implemented. The key is the deposition of the electrodes, normally called interdigitated transducers (IDT) or interdigitated electrodes (IDE), on the surface of the acoustic device. This is normally achieved through photolithographic and etching
processes. Manufacturing begins by carefully polishing and cleaning the piezoelectric substrate. A metal, usually aluminium, is then deposited uniformly onto the substrate. The device is spincoated with a photoresist and baked to harden it. It is then exposed to UV light through a mask with opaque areas corresponding to the areas to be metalized on the final device. The exposed areas undergo a chemical change that allows them to be removed with a developing solution. Finally, the remaining photoresist is removed. The pattern of metal remaining on the device corresponds to the IDT. By changing the length, width, position, and thickness of the IDT, the performance of the sensor can be maximized.35,36 Generally, resonators can be distinguished as two-port delay lines and one-port resonators.37 Two-port delay lines work with one IDT as a transmitter and one as a receiver. The separation between them determines the delay between the transmission and receiving of the surface wave. One-port resonators consist of one IDT structure in between two reflectors thus producing a standing wave in both directions.1,34,37
4 MODES OF VIBRATION
The crystal symmetry, its thickness, the angle of cut of the crystal substrate, and the configuration of
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
5
Clean substrate
Metallization
Formation of SiO2 layer
Photolithography
Photolithography
Oxidation
Metallization
Etching
Formation of zinc oxide layer
Liftoff
Wafer dicing
Sample cleaning
Transducer mounting and electrical testing
Biochemical deposition
Figure 2. Overview of acoustic wave sensor fabrication process. [Reprinted with permission Hoummady et al.36 , copyright 1997, Institute of Physics.]
the excitation electrodes determine the electromechanical coupling and stresses resulting from an applied electric field, in turn defining the different types of AWs and its wavelength generated in the crystal.38,39 The velocity of the sound wave is a constant for a particular crystal, under a given set of conditions. With wavelength and velocity fixed, the wave equation, ν =λ·f
(1)
where λ is wavelength, f , frequency, and ν, velocity of the wave, indicates that frequency will
also be fixed. The powerful implication is, by controlling the dimension of the electrodes and choosing a crystal that has the velocity needed, the electrodes can be designed to select, to filter out, a certain frequency. The system will, therefore, resonate at that particular frequency and will select that frequency component from a complex signal. AW devices are described by the mode of wave propagation through or on a piezoelectric substrate. AWs are distinguished primarily by their velocities and displacement directions; many combinations are possible, depending on the material and boundary conditions. The IDT of each sensor
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
TSM
SAW
FPW
SH-APM
Name
Thickness shear mode resonator
Surface acoustic wave resonator
Flexural plate wave
Shear horizontal acoustic plate mode
Wave type
Bulk, transverse
Surface, vertical
Plate, vertical
Plate, horizontal
Particle displacement relative to wave propagation direction
Normal
Transverse, parallel
Transverse, parallel
Transverse
Media used
Gas, liquid
Gas
Gas, liquid
Gas, liquid
Frequencydetermining parameter
Thickness d
Spacing of IDE
Typical operation frequency (MHz)
5–20
30–500
2–7
25–200
∆m equivalent to 1 Hz of ∆f for a defined resonant frequency
12 ng cm2 (6 MHz) 2 ng cm2 (27 MHz)
0.01 ng cm2 (200 MHz)
0.4 ng cm2 (5.5 MHz)
0.5 ng cm2 (104 MHz)
Spacing of IDE, plate Spacing of IDE, plate thickness d thickness d
Top view
Side view
Acoustic wave propagation modes
Figure 3. Common acoustic devices, characteristics, and mode of acoustic wave propagation. White arrows indicate wave propagation direction, black arrows indicate particle displacement.1,3,5,20,40,42
provides the electric field necessary to displace the substrate and thus form an AW. The wave propagates through the substrate, where it is converted back to an electric field at the IDT on the other side. Figure 3 shows the configuration of typical AW devices.
A wave propagating through the substrate is called a bulk wave. The most commonly used bulk acoustic wave (BAW) devices are the TSM resonator and the shear-horizontal acoustic plate mode (SH-APM) sensor (Figure 3).3,5,38 Transverse, or shear, waves have particle displacements
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
that are normal to the direction of wave propagation and which can be polarized so that the particle displacements are either parallel to or normal to the sensing surface. Shear horizontal (SH) wave motion signifies transverse displacements polarized parallel to the sensing surface; shear vertical motion indicates transverse displacements normal to the surface.40 If the wave propagates on the surface of the substrate, it is known as a surface wave. The most widely used surface wave devices are the SAW sensor and the shear-horizontal surface acoustic wave (SH-SAW) sensor, also known as the surface transverse wave (STW) sensor.
4.1
Common Acoustic Sensors
All AW devices are sensors as they are sensitive to perturbations of many different physical parameters. Any change in the characteristics of the path over which the AW propagates will result in a change in output. Thus, when a crystal surface is loaded with additional mass, or liquid, the resonant frequency will vary as a consequence of the acoustic energy lost from the vibrational mode. This transfer of energy results in a drop in resonant frequency, and in the case of liquids, severe and sometimes catastrophic damping of the AWs, thereby causing a decrease in the Q factor.41 In general, the sensitivity of the sensor is proportional to the amount of energy in the propagation path being disturbed. Initially, all the sensors will function in gaseous or vacuum environments, but only a subset of them will operate efficiently when they are in contact with liquids. Bulk AW sensors typically disperse the energy from the surface through the bulk material to the other surface, this distribution minimizes the energy density on the surface, which is where the sensing is performed. The TSM, SH-APM, and SH-SAW all generate waves that propagate primarily in the SH motion. The SH wave does not radiate appreciable energy into liquids, allowing liquid operation without excessive damping.3,5,8 Conversely, SAW sensors focus their energy on the surface, tending to make them more sensitive, however, the substantial surface-normal displacement that radiates compression waves into the liquid also causes excessive damping.40
7
An acoustic device is thus sensitive mainly to physical parameters which may interact with (perturb) mechanical properties of the wave and/or its associated electrical field. However, for chemical sensors or biosensors some transduction layers should be used to convert the value of the desired parameter (chemical agent concentration, etc.) into a mechanical or electrical perturbation that can disturb the AW properties.36 Each device is characterized according to their AW propagation, in terms of the substrate material and the particle displacements relative to the direction of the wave propagation and to the sensitive surface. As explained earlier, these devices can operate in either gas or liquid medium, depending upon physical properties. The sensing mechanism is generally a function of parameter perturbation affecting the propagating AW in the surface of the sensor. In this way, the most common acoustic sensors can be uniquely identified by the vibrational mode and polarization, which in turn have a direct link to the position of the driving electrodes (Figure 3).
Electrode
Electrode (a)
(c)
(b)
(d)
Figure 4. Quartz crystal microbalance (a), (b) front view (c), (d) side view.
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
5 QUARTZ CRYSTAL MICROBALANCE
The TSM sensor is widely referred to as the quartz crystal microbalance, QCM, and is undoubtedly the oldest and the most recognized acoustic sensor. It consists of a thin disc of AT-cut quartz, with parallel circular electrodes on both sides normally gold over chromium, acting as a one-port resonator (Figure 4). The application of a voltage between these electrodes produces a shear deformation of the crystal, where the AWs generated in TSM devices are bulk transverse waves that travel in a direction perpendicular to the plate surfaces (Figure 5). As a result of the field, both surfaces move in parallel but in opposite directions (Figure 5) to generate bulk transverse shear waves that propagate through the thickness of the plate, parallel to the electric field. Under these conditions, the crystal produces electromechanical standing wave resonances. The displacement is greatest at the faces of the crystal, making it very sensitive to surface chemical interactions and mass accumulation. Particle motion parallel to the sensor surface conveniently provides compatibility with contacting liquids. In a TSM resonator, particle displacements at these surfaces are parallel to the surface. The plate thickness d determines the wavelength λ of the fundamental (n = 1) and harmonic (n = 3, 5, 7 . . .) and resonances according to λ = 2d/n. The resonant frequency of the fundamental mode
Z
is typically 5 or 10 MHz, and the frequency increases as the plate thickness decreases. For a TSM wave, the device thickness must be odd multiples of half-wavelengths, so that the wave can reflect back on itself and cause resonance.2,4,5,21 Under these conditions, the velocity of the shear wave is given by: 1/2 µ ν= ρ
Where ν is the acoustic-shear wave velocity, ρ is the density of quartz and µ is the shear stiffness calculated for the direction of motion and the disc cut angle. For AT cut quartz crystals, µ is 2.947 · 1010 Nm−2 and ρ 2.651 · 103 Kg m−3 . As a result, the shear wave velocity is 3334.15 ms−1 . The resonant frequency is given by: f0 =
Liquid
Quartz Quartz particle displacement
X Air (free surface of the quartz disc)
Figure 5. Wave propagation direction and particle displacement in a thickness shear mode device.
nν 2dQ
(3)
Where f0 is the resonant frequency in Hertz, n is an odd integer, and dQ is the disc thickness. This behavior is valid when the QCM is used in vacuo, but represents only an approximation in fluids. With respect to the sensor applications, the simplest case is when a mass is attached to the crystal to change the resonance behavior. This was modeled by Sauerbrey in 1959, who using QCM, presented the real breakthrough in the acoustic sensors field, with the first quantitative investigation that relates the mass of deposited material to the decrease in frequency.8,22,43,44: f = − √
Liquid particle displacement
(2)
2f0 m · µQ ρQ A
(4)
Here f is the resonant frequency shift due to the added mass and m is the added mass. The fundamental resonance frequency of the unloaded device is f0 ; µQ is the shear stiffness, ρQ the density of the crystal and A is the surface area of the crystal. Thus, considering that the properties of quartz do not change, there is a linear relationship between the change in frequency and the loading of mass; therefore, the fundamental frequency decreases with increasing mass.3,5,8
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
Basically, the model assumes that when mass is added to the top surface of the crystal, the resonant frequency drops because the wave must travel a longer distance and the crystal must expend more energy to move the added mass. The wavelength is then increased due to the increase in thickness. At resonance, the thickness is equal to an odd multiple of half-wavelengths, so the increased wave path distance results in a longer wavelength at resonance. If the thickness of the film is small relative to the thickness of the quartz, the wave velocity will remain constant. Since the wavelength varies inversely with frequency at constant velocity, the increase in wavelength due to the film results in a decrease in frequency. As the film is assumed to have the same stiffness and density as quartz, the model is valid only for small masses or films with similar properties to quartz, such as metals, and it has been verified
9
for the application of “rigid” overlayers up to a mass load of m/m = 2%.45 However, the model overestimates the results for polymers or biological films. In addition, it is not physically valid for liquids whose stiffness, viscosity, and density are largely different than quartz. In this context, several attempts (Table 2) have been made to expand Sauerbrey’s theory by including a number of other parameters associated with deposited thin films such as the propagation of the AW into the deposited film,46,47 the change in period,48 the acoustic impedance of the film,49,50 the effects of electrode, film, and quartz diameters on the sensitivity,51 or the bulk modulus viscosity, density, and film thickness are also considered.52 Up to 1985, there was a general impression that the TSM devices could not be operated in liquid phase due to viscous damping effects that
Table 2. Summary of theories for acoustic response to solid films of TSM resonators
Authors Sauerbrey44
Model f = − √
Lu and Lewis49 and Lu50 Glassford40 Mecea and Bucur51
Crane and Fisher52 A b D f0 f fl fs fc ff fq k l lf lq m
2f0 · m A µQ ρ Q
Film is considered as extension of disc thickness, pure mass effect
2f 2 f = − ρ ν0 m Q Q A
Mille and Bolef46,47
Behrndt48
Considerations
Small acoustic losses in quartz and film. Propagation of the acoustic wave into deposited film considered Consideration of change of period
τ = Nρ1 A mf Q Z πf πf tan f c = − Zf tan f c Q Q f f b fl = b S 0 (D cos φ)2 dz fq2 2ρ l {1 − exp[−r0 re ]2 } =1+ f f fc2 ρq lq {1 − exp[−r re ]2 }
Consideration of acoustic impedance of film Consideration of mass loading of liquid film Effects of electrode, film and quartz diameters on the sensitivity of a crystal coated with a thin or nondissipating film are considered
f α tan lb(1 − tanh2 kb) + β tanh kb(1 + tan2 lb) fq = πρQ νq (1 + tanh2 kb tan2 lb)
Area of the quartz plate Liquid film thickness Ratio of velocity amplitude at z and velocity amplitude at crystal surface, Z=0 Fundamental frequency Frequency change due to film Frequency change due to liquid film Frequency change due to solid film Resonant frequency of the quartz crystal with the film Resonant frequency of the film Resonant frequency of the quartz crystal without the film Real part of the propagation coefficient if the film Imaginary part of the propagation coefficient of the film Film thickness Quartz crystal thickness Change in mass due to a solid film
mf N ro re r νq z Zf ZQ α β µq ρf ρq φ τ
Bulk modulus viscosity density and film thickness are considered
Mass of the film Frequency constant of the specific crystal cut Radius of the film Radius of the electrode Radius of the quartz crystal Phase velocity of shear wave in quartz Direction in rectangular system Acoustic impedance of the film Acoustic impedance of the quartz Real part of the characteristic impedance of the film Imaginary part of the characteristic impedance of the film Shear modulus of quartz Density of the film Density of quartz Phase angle by which the acoustic response wave at z lags that at the crystal surface, z=0 Period change due to a solid film
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
will cause oscillation suppression.45 Glassford40 presented the first attempt to infer the response of liquid over the quartz resonator, considering that the frequency shift is proportional to the ratio of the kinetic energy of the deposit to that of the bare crystal. In his model, he showed that an oscillating solid deposit will have the same velocity as the crystal surface throughout, but for a liquid deposit a velocity gradient must be established in order to transmit the shear forces necessary to sustain the oscillation. The kinetic energy of a liquid deposit and the induced change in the resonator frequency will therefore always be less than that of a solid deposit of the same mass because of lower mean velocity in the deposit. After this work, several studies demonstrated that a quartz crystal can oscillate in contact with liquid. In addition, they showed that the liquid causes a significant shift in the resonant frequency. Basically, when the crystal is operated in liquid, acoustic energy is transferred to the fluid through viscous coupling of the quartz surface to the fluid particles. This energy transfer results in a drop in resonant frequency and damping of the resonance amplitude, because fewer oscillations can be supported due to the fall in energy stored. This can be equated to the loss in energy through viscous damping of the fluid. This phenomenon was explained in the beginning of 1980s by Kanazawa and Gordon,53 who modeled the resonant frequency shift of a quartz resonator by coupling the properties of the fluid and the quartz through a boundary condition. The decay is exponential and declines with a characteristic decay length δ. This is the no-slip boundary condition, where the velocity of quartz at the interface is equal to that of the liquid layer.3,8,21,43,54 In this model, the velocity of the quartz is assumed to be equal to the velocity of the liquid at the solid–liquid interface, but decays rapidly as the wave propagates into the fluid. 3/2
f = − √
f0 √ · η L ρL πµQ ρQ
(5)
where f is the resonant frequency shift, f0 is the fundamental resonance frequency of the unloaded crystal, ρL and ηL are the density and viscosity of liquid in contact with the crystal, µQ and ρQ are the shear stiffness and the density respectively of the crystal.
Physically this model predicts that only a thin layer of liquid will undergo displacement at the surface of the bulk wave device, and the device response will be a function of the mass of this layer. It is comparable to the Sauerbrey equation, but produces a square root relation to the sensor variables instead of a linear relation. Apart from the work of Kanazawa and Gordon,53 several other theories have been formulated to explain the coupling of the crystal to the liquid medium (Table 3). Basically all of them consider viscosity and density as being the key parameters defining the frequency shift for liquid loading.55–57 However, other theories also include surface roughness as trapped liquid in the surface increases the effective mass,58 surface stress,59 or electric properties.60–63 In general, the TSM features simplicity of manufacture, temperature stability, and good sensitivity to additional mass deposited on the crystal surface. Typical TSM resonators operate between 5 and 20 MHz as fundamental frequency, with the possibility of a few overtones. Making very thin devices that operate at higher frequencies can increase the mass sensitivity, but thinning the sensors may result in fragile devices that are difficult to manufacture and handle. Recent work has been performed to generate TSM resonators without the presence of electrodes, known as the magnetic acoustic resonator sensor, MARS,64,65 which offers a whole new approach to acoustic sensing, as it does not rely on electrodes for performing the sensing, and allows all the resonant frequencies of the crystal to be excited. Commercial QCM can have many different coatings, according to the application needed, for example, the most commonly used sensor surface is pure gold (Au), as Au is chemically stable and easy to modify in different ways. Silicon dioxide is also used as lipid bilayers can form easily on top, which act as a platform for further immobilization of molecules. Stainless steel surfaces may be used for studies of biofilm formation in process industry. Many polymers can be spin-coated if a polymer substrate is required, with polystyrene being the most common. Titanium coated surfaces are mainly used for implant research such as the adsorption of proteins or formation of calcium phosphate coatings. Some metal oxides coatings include aluminium trioxide, platinum, tantalum,
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
11
Table 3. Summary of theories for acoustic response to liquid loading of TSM resonators
Author Nomura and Minemura56
Model f =
Considerations
− B1 (dL − 1)
A1 κL0.611
1.02
Nomura and Okuhara57
f = Aa ηL0.5 − B2 ρL0.5 − C
Kanazawa and Gordon53
f = −fq
Bruckenstein and Shay25
3/2
Yao and Zhou63 Shana et al.62 A A1 A2 A3 B1 B2 C0 C1 C2 C3 C66 dL f fq h
1/2
3/2
2fq2 mL (µq ρq )1/2 ρ ε mL = 2L fq − fm = A3 (p − pm )2 f = −
Heusler et al.59
Muramatsu et al.61
ηL ρL π µq ρ q
f = −2.26x10−6 nfq (ηL ρL )1/2
Schumacher et al.58
Hager60
Empirical formulation for aqueous solution, frequency depends on density and conductivity of the solution Empirical formulation for organic liquids. If no electrolyte is present, frequency shift dependent of viscosity and density
Surface roughness is considered. Liquid trapped in surface increases effective mass
f = −k1 (ηL ρL )1/2 + k2 εL 3/2 R1 = kA − 2.26 × 10−6 nfq (ηL ρL )1/2 3 1/2
f = C0 + C1 ρL − C2 ηL1 − C3 εL f fq
=−
fq ρL ηL πρq C66
1/2
|tanh(k3 h)|
Area of the quartz plate Numerical constant Numerical constant Numerical constant Numerical constant Numerical constant Numerical constant Numerical constant Numerical constant Numerical constant Stiffened elastic constant due to intrinsic velocity of the quartz crystal Specific gravity of liquid Frequency change due to film Resonant frequency of the quartz crystal without the film Height of liquid layer
tantalum nitride, tungsten, copper, chromium, iridium, iron, silicone carbide, iron carbide, silver, and cobalt.66 In recent years, there has been increasing interest in measuring not only changes in the resonant frequency but also the dissipation, which is used as complementary information to the frequency shift.34,67,68 The dissipation gives information about the rigidity of the film, therefore it is possible to obtain information not only of mass changes but also structural changes occurring at the sensor surface.67 This technology is commercially available and increasingly used in labs around the world.66
Approach similar to Glassford.40 Viscosity and density are considered, no-slip assumption, interfacial effects ignored Viscosity and density are considered, no-slip assumption, interfacial effects ignored
Influence of surface stress and pressure are considered Hydrodynamic coupling analysis, liquid dielectric constant is considered Resistance of electrical equivalent circuit is considered Similar to Nomura and Okuhara model but considering dielectric constant Piezoelectric effects are considered
k1 k2 k3 mL m N p − pm Rl ε εL ηL κL µq ρL ρq
Numerical constant Numerical constant Electromechanical coupling constant Mass per unit area of equivalent liquid layer Change in mass due to a solid film Number of sides of crystal in contact with the liquid (n=1 or 2) Pressure difference between the two sides of the quartz crystal Resistance of equivalent circuit of quartz crystal Mean diameter of hemicylinders Dielectric constant of a liquid Dynamic viscosity of a liquid Specific conductivity of a liquid Shear modulus of quartz Density of liquid Density of quartz
QCM-D is a technique for measuring the mass of material/molecules attached to the surface of the quartz crystal through changes in the resonant frequency, f, while also getting information about the viscoelasticity of the layer by measuring the dissipation factor, D. The f-shift of the QCM-D is due to the change in the total coupled mass, including the water coupled to the layer.67,68 In a humid environment, an adsorbed film may consist of a considerably high amount of water, which is sensed as a mass uptake by the QCM. However, by measuring, simultaneously, resonant frequencies and
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Table 4. Recent publications on acoustic sensors in biosensing
Analyte
Bioselective layer
Immobilization
Acoustic technique
Antihemoglobin
Fullerenehemoglobin HAS
Au/C60 /hemoglobin
SAW
69
Au/11 MUA/HSA
QCM (9 MHz) SH-SAW
70
Warfarin E. coli O157:H7 Albumin
Rabbit polyclonal IgG Ab MIP
BMP-2
Protein A
Paclitaxel
Anti-taxane-IgG
Mesothelin Salmonella typhimurium Annexin
Mouse antimesothelin Antisalmonella CSA-1 POPC:POPS 4:1
Lectin
Conc A
IgG
Histidine
Borrelia burgdorferi
Anti-OspA
Au/MEA/NHSPEG-biotin/neutravidin/Ab Au–NH2 , Au–OH, Au–COOH/DMAPMAAlbumin Au/protein A Au/PDDA/PSS/anti-taxane IgG Au/EDC/HS/Ab Au/protein A/antisalmonella Ab Au/octanethiol/POPA-POPS Au/polystryrene/yeast mannan/BSA/conc A Au/DTT/histidine Au/2-AET/glutaraldehide/ avidin/ biotinhuman IgG/anti-OspA
References
71
QCM (9 MHz)
72
QCM (20 MHz) QCM (10 MHz) QCM
73
QCM (7.99 MHz) QCM (5 MHz) QCM (10 MHz) QCM (10 MHz) FPW (25 MHz)
76
74 75
85 86 87 88
HSA: human serum albumin; MUA: mercaptoundecanoic acid; Ab; antibody; MEA: mercaptoethylamine; NHS-PEG-biotin: N-hydroxysuccinide poly(ethylene glycol)-5000 biotin; MIP: molecular imprinted polymer; DMAPMA: 3-dimethylaminopropyl methacrylamide; BMP-2: human bone morphogenetic protein; PDDA: poly(dimethyldiallyl ammonium chloride); PSS: poly(styrenesulfonate); EDC: 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide; NHS: N-hydroxysuccinimide; POPC: 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine; POPS: 1-palmitoyl-2-oleoyl-sn-glycero-3phosphoserine; Conc A: concavalin A; BSA: bovine serum albumin; DTT: 1,4-dithiothreitol; OspA: outer surface protein A; AET: aminoethanethiol.
dissipations at multiple harmonics, it becomes possible to judge if the adsorbed film is rigid or water rich (soft) which is not possible by looking only at the frequency response. The resonant frequency of the crystal depends on the total oscillating mass, including water, coupled to the oscillation.67,68 Some recent applications of QCM resonators for biosensing are presented in the next section, Table 4.
6 ACOUSTIC PLATE MODE (APM) DEVICES
APM devices are another type of bulk wave acoustic device, which, unlike the QCM, is a two-port device in which the wave propagates many wavelengths between input and output transducers; consequences of this include differences in
the instrumentation and analysis of wave propagation characteristics. APM devices use a thin piezoelectric substrate, or plate, functioning as an acoustic waveguide that confines the energy between the upper and lower surfaces of the plate (Figure 6), generating SH waves.1,34,40 SH modes have particle displacement predominantly parallel to the device surface and normal to the direction of propagation. Therefore, the absence of a surface-normal component of displacement reduces drastically the loss of acoustic energy from interaction with the environment. As a result, both surfaces undergo displacement, as the waves travel between the top and bottom surfaces of the plate, such that detection can occur on either side. This is an important advantage, as all electrical connections can be made to the face of the crystal that is not immersed in solution. When mass is bound strongly to the surface,
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
13
Output transducer
Mass sensing surface
n
tio
a ag
op
ve
pr
a
W
Input transducer
Cross-sectional displacement Figure 6. Shear-horizontal acoustic plate mode sensor. The cross sectional displacement corresponds to the first mode, blue arrows show particle displacement.
the layer moves synchronously with the quartz surface. In SH-APM devices, AWs can be excited and detected by lithographically patterned IDT structures, where the nth order SH plate mode will be generated according to Martin et al. (1989) 2 1/2 nb vo 1+ fn = b 2d
(6)
with the input transducer with periodicity b and thickness d, and vo the wave velocity of the unloaded device. The accumulation of mass on the surface of the device disturbs the balance between kinetic and potential energy that exists in a mechanical resonator. A layer of ideal mass (having no thickness or elasticity) deposited at the surface results in increased kinetic energy, which is offset by a decrease in oscillation frequency. The perturbation of an SH plate mode oscillator by surface mass is approximated by34,77 : f v = −cf ρs = f v0
(7)
in which cf is the frequency sensitivity to surface mass, ρs is the surface mass density (mass/area on surface). The equation predicts that the frequency will decrease linearly with accumulated mass density, and the sensitivity is predicted to depend inversely on plate thickness.1 Although more sensitive to mass loading than the TSM resonator, SH-APM sensors are less sensitive than surface wave sensors. There are two reasons for this: the first is that the sensitivity to mass loading and other perturbations depends on the thickness of the substrate, with sensitivity increasing as the device is thinned. The minimum thickness is constrained by manufacturing processes. Second, the energy of the wave is not maximized at the surface, which reduces sensitivity.1,34,40
7 SURFACE WAVE SENSORS
In 1887, Lord Raleigh was the first to discover this mode of acoustic oscillation known as a SAW, where the stress free boundary imposed by the surface of a solid gives rise to AWs confined to the surface with both shear and compressional components that can couple with the medium in contact
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Particle displacement Coating Transmitter
v1
Receiver
l1
Figure 7. Design of a typical surface acoustic wave sensor.
with the device’s surface.1,3,34 With few exceptions, all SAW devices consist of thin-film metal structures fabricated on the surface of a piezoelectric substrate. The substrate material is usually a single crystal of ST-quartz, lithium niobate, or lithium tantalate with finger type IDTs that generate the Raleigh waves propagating in both directions away from the IDT (Figure 7). The surface particles move elliptically, and the displacement decays exponentially within the solid, such that the surface acts as an acoustic waveguide. Each IDT is the origin of the AW, whose velocity ν0 is determined by the plate material and the crystal cut; the wavelength, d, is equal to the finger spacing between the IDTs, or periodicity and the frequency corresponds to f = v0 /d.1,34,40 In sensor applications, the propagation path between the two IDTs of a two-port delay line, SAW is used as the sensitive area, which is usually coated with an analyte-sensitive coating.37 A basic advantage is that AWs travel very slow (typically 3000 m s−1 ), so that large delays are obtainable. The IDT geometry is capable of almost endless variation, leading to a wide variety of devices. Starting around 1970, SAW devices were developed for pulse compression radar, oscillators, and band-pass filters for domestic TV and professional radio. In the 1980s the rise of mobile radio, particularly for cellular telephones, caused a dramatic increase in demand for filters. New high-performance SAW filters emerged and vast numbers are now produced, around 3 billion annually.35 In recent years, wireless SAW sensors have been developed, where a radio frequency (RF) request signal transmitted by a local radar transceiver is picked up an antenna connected to the IDT, which converts the received signal into a SAW.70
The operating frequency of SAW is determined not by the wafer thickness but by the transducer periodicity:f = v/λ, where v is the SAW propagation velocity and λ the transducer periodicity.77 Typical SAW sensors operate from 25 to 500 MHz. One disadvantage of these devices is that Rayleigh waves are surface-normal waves, making them poorly suited for liquid sensing. When a SAW sensor is contacted by a liquid, the resulting compressional waves cause an excessive attenuation of the surface wave. Also, the quality factor Q of SAW devices is between 6000 and 12 000, considerably lower than for TSM devices operating in air.34 When mass is deposited on top of the device as a thin and rigid film, the frequency change depends on the mass load as well as on several elastic constants, also, there is an influence of the electric conductivity and the dielectric constant of the film. In general, the kinetic energy increases with no energy loss due to viscous coupling, which in turn leads to a decrease in the propagation velocity34,77 : v f = −cf fρs = f v0
(8)
Where cf is a substrate-dependent constant (1.29 × 10−6 cm2 s g−1 for ST-cut quartz) and f the operating frequency. Again, the mass sensitivity increases with the square of the fundamental frequency, as for TSM sensors, but as the fundamental frequency is much higher for SAW devices, the latter present much higher sensitivity in vacuo.1 However, in the liquid phase SAW devices present high dissipation and are less suitable than TSM due to high energy loss to the liquid media. There are other mechanisms, apart from mass loading that can give a sensor response,
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
such as changes viscoelastic properties and electrical conductivity of the adsorbed species.77 If the cut of the piezoelectric material is rotated appropriately, the wave propagation changes from vertical shear SAW to SH-SAW, which considerably reduces the energy losses when used in liquid media. Common piezoelectric materials used to produce SAW devices do not produce a pure shear wave, so part of the energy is lost to a bulk AW that propagates normal to the surface. To correct this issue, acoustic waveguides can be used. Such waveguides correspond to a material attached to the surface that has a lower acoustic velocity, such that the energy is trapped near the surface. Normally, SAW devices with guiding layers are called Love Wave devices. One of the disadvantages of SAW devices is that, although lithium niobate and lithium tantalate have a larger coupling efficiency than quartz, they do not possess a zero temperature coefficient, and thus careful control of temperature is needed. Additionally, because many parameters may contribute to the frequency change of a SAW device, it is required that the SAW devices work in pairs where only one of them will be subjected to the analyte and the other is used as the reference.37 In general, SAW devices are regarded as more of a very sensitive monitor sensor than an accurate measuring device.37 8 FLEXURAL PLATE WAVE (FPW) DEVICES
In a FPW resonator, an AW is excited in a thin, rectangular membrane, normally made of silicon nitride embedded in a frame of silicon, where IDTs are patterned onto the surface, and then the silicon nitride wafer is backside etched to release the membrane. Other piezoelectric materials that can be used for the membrane are silicon dioxide, oxy-nitride, aluminium nitride, zinc oxide and diamond.1,77 A schematic representation of a Flexural Plate Wave device is presented in Figure 8, with a cross section showing the position of the IDTs, the silicon nitride membrane and the zinc oxide layer. The oscillation in these membranes, usually a few microns thick, is conventionally obtained electrostatically, using the IDTs as in the SAW devices; magnetic excitation has also been reported.77 The
15
AWs propagate from one IDT to the other in a delay-line fashion, and can move normal to the surface or can propagate a shear wave, as in the SH-SAW sensors. As for all other acoustic sensors, any perturbation of the surface will change the velocity of propagation of the wave and will damp the acoustic oscillation.77,79 AWs generated in a FPW mode are commonly known as Lamb waves, and correspond to acoustic modes that propagate in a thin layer of deposited substrate.42,79 Lamb waves can have both symmetric and antisymmetric modes.3,34 Antisymmetric Lamb waves exhibit flexural character and their velocities decrease with decreasing plate thickness. Lamb waves have elliptical particle motion, like Raleigh waves, and therefore contain both shear and compressional components. However, due to the minimal thickness of the FPW, the wave velocity in a membrane is much lower than in a solid substrate, giving in turn, a much lower frequency of operation, typically 2–7 MHz. This lower velocity also means that the generated waves do not excite compressional waves, making it suitable for liquid applications. Due to this characteristic, FPW resonators have a high Q factor and low energy losses in fluid environments.34,42,77,79 The asymmetric wave propagation velocity in FPW devices changes with rigid surface mass according to77 : v ρs f = =− f v0 2M
(9)
where 1/2M, the integral mass sensitivity can be increased by using thinner plates, which in turn will reduce the resonant frequency and the phase velocity. As the device is normally fabricated on silicon, it can be easily integrated with on-chip electronics, offering a cheaper alternative to TSM resonators.34,77 However, an interface has to be attached to the guiding layer to enhance specificity and sensitivity.
9 APPLICATIONS OF ACOUSTIC WAVE SENSORS
The range of phenomena that can be detected by AW devices is strongly dependent on the interaction of the changing medium with the acoustic
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
A′
A
IDTs
Cross section A–A′ Silicon nitride
Zinc oxide layer Si substrate
Figure 8. Schematic diagram of a flexural plate wave (FPW) sensor.
material, and consequently by how AW propagation is affected. The applications can be greatly expanded by coating the devices with materials that are particularly sensitive to the parameter being measured. Resultant changes in physical and/or chemical properties of the coating in turn perturb the underlying AW device. The ultimate performance of the sensor depends on both the device configuration, that is, substrate material, acoustic mode, operating frequency; and the nature and extent of the coating-analyte interactions.1 For example, acoustic sensors become force, pressure, and torque sensors when something affects the dynamics of propagating medium. They can be gravimetric sensors when particles contact the propagating surface. Additionally, if the propagating medium changes with temperature, changing the output, they become very sensitive temperature sensors. Acoustic sensors have also become very useful in the field of materials characterization, as they are extremely sensitive to thin-film properties. The sensitivity of AW devices to a variety of film properties, such as mass density, viscoelasticity, and conductivity makes them versatile characterization tools.1
Probably the most commonly known application is in the field of biosensors, as if the device is selectively coated, from the mass sensitivity of the sensor it is possible to measure the amount of species bound. Obtaining adequate sensitivity and selectivity for the measurement of a given analyte requires a chemical or biochemical interface. The coating, which should be physically of chemically bound to the surface, may consist of a solid adsorbent, a chemical reagent, or a sorptive liquid or polymer. The coating then acts as a selective element that immobilizes a finite mass of some species of the environment.1 9.1
Temperature Sensors
Normally, temperature sensors are based on SAW delay line oscillators, as surface wave velocities are temperature dependent and are determined by the orientation and the type of material used to fabricate the sensor.80 The high linearity of the frequency shift with temperature makes it possible to achieve a high resolution and a high stability with a simple oscillator circuit.81 With these temperature sensors it is possible to achieve a resolution of 0.1 K.78
INTRODUCTION TO ACOUSTIC TECHNOLOGIES
Lithium niobate, LiNbO3 , is an ideal material for temperature sensors because its large temperature coefficient delay (TCD) of approximately −85 ppm/ ◦ C and its high electro acoustic coupling factor.1,78 However, an accelerated decomposition of lithium niobate can be observed above 300◦ . Noble metals with a high melting point, such as Pt, Rh, or Ir are best suited for electrodes for hightemperature applications.80 9.2
Pressure Sensors
Cullen and Reeder where the first ones to report the use of SAW technology for a pressure sensor.82 In this case, the physical effect is a variation of the elastic constants and in turn the change of the SAW velocities.78,80 Basically, a SAW pressure sensor is created by making the SAW device into a diaphragm, which will bend under hydrostatic pressure. For this to work, a constant reference pressure must be applied to the other side of the diaphragm.35,80 The pressure sensors are normally constructed as an “all quartz” package, where the delay line and the lid are made of the same material, thus avoiding thermal stresses and reducing the cross sensitivity to temperature.78 The resolution of SAW pressure sensors are normally 1% of full scale.78 9.3
Torque Sensors
If a SAW device is rigidly mounted to a flat spot on a shaft, and the shaft experiences torque, this torque will stress the sensor and a change in the signal will be observed. If the shaft is rotated one way, the SAW torque sensor experiences tension, if rotated the other way, it experiences compression.83 Normally, for practical applications two torque sensors are needed, such that their centrelines are at right angles. In this way, when one sensor is in compression, the other is in tension. Also, by comparing the two sensors, it is also possible to avoid any temperature drift effects.35,83
10
BIOSENSOR APPLICATIONS
The development of biosensors based on piezoelectric transducers is widely investigated due to
17
their intrinsic mass sensitivity. The most classical transducers used for biosensing are the QCM, and in minor extent the SAW, since both give a direct response signal that can be correlated to the binding event between the sensitive layers attached to the transducer, and the analyte. This type of transducers offers a wide range of applications, where any analyte of interest can, in principle, be detected, as long as a suitable binding layer is used. In fact, there have been many applications for acoustic sensors that include antibody-based, nucleic acid-based, enzyme-based and cell-based acoustic biosensors.84 The most interesting feature of acoustic sensors is that they allow in situ mass detection in a label-free fashion34,39 due to the correspondence of frequency change to adsorbed mass.34,84,85 Additionally, with the appropriate flow injection analysis (FIA) system the elucidation of thermodynamic and kinetic parameters of binding events occurring at the sensor surface–liquid interface is possible.3 The typical response of an acoustic sensor for an immobilization/adsorption occurring on the surface is presented in Figure 9; where in the top diagram can be clearly seen that upon the addition of the analyte the frequency gradually decreases from its original value f0 , until a reasonable stable signal is obtained. Then, a washing solution is normally added to remove any unbound analyte. This causes a slight increase in the frequency, which correlates to the remnant material being removed from the surface, until a stable response is obtained again. From the frequency difference between f0 and f1 it is possible to calculate the mass according to the Sauerbrey model.44 The bottom diagram presents the energy dissipation changes after the same binding event. Following the addition of the binding analyte, the dissipation increases as adsorption is occurring at the surface and the resonator needs more energy to move the added mass. After the washing, any unbound material is removed; therefore, the dissipation of energy related to the attachment of the analyte can be calculated from D0 and D1 . The extent of energy dissipation or signal attenuation can be related with the rigidity of the film and water entrapment,34,67,68 and it has been shown that the adsorption of smaller proteins, such as albumin and myoglobin, result in less dissipation shifts than larger proteins (fibrinogen, ferritin).89
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Resonant frequency (Hz)
Analyte
f0
Wash
f1
(a)
Time
∆ D/A
Wash
REFERENCES
Analyte
D1 D0
(b)
still being developed in research centers around the world, that have not been transferred yet into routine use in R&D applications. There are several reasons that could cause this delay in reaching the market: First, the need for temperature stabilization for certain piezoelectric substrates; secondly, the manufacturing costs, considering the small size and high precision required for the electrodes, as they will largely define the frequency of operation; thirdly, simpler, integrated and miniaturized electronics would make them easier to use; and finally, there is an increasing need for operation at higher frequencies, as that is known to improve the response and sensitivity of existing sensors. Overall, it seems that new sensors do not yet offer clear advantages over existing products, as most research is focused on the development of specific biochemical sensors, rather than on the improvement of the transducer engineering.
Time
Figure 9. Schematic diagram of a typical immobilization/ adsorption event response on a QCM surface at a particular frequency. (a) Resonant frequency variation over time. (b) Dissipation factor variation or signal attenuation over time. Analyte and wash actions are presented by arrows. In (a), f0 represents the frequency before immobilization, f1 frequency after the event, in (b), D0 and D1 represent the dissipation or signal attenuation before and after the adsorption event.
In this way, many applications of acoustic sensors in biosensing have been developed. Table 4 gives an overview of studies published in the last 5 years. Previous work can has been reviewed by Bizet20 and Kaspar.5 In conclusion, it should be noted that the field of acoustic biosensing is an ongoing development. Although there are some commercial systems already in the market, such as the QCM and some SAW devices, there are many acoustic sensors
1. D. S. Ballantine, R. M. White, S. J. Martin, A. J. Ricco, and G. C. Frye, ’Acoustic Wave Sensors: Theory, Design, and Physico-Chemical Applications, Academic Press, New York, 1997. 2. C. Behling, R. Lucklum, and P. Hauptmann, Response of quartz-crystal resonators to gas and liquid analyte exposure. Sensors and Actuators A: Physical, 1998, 68(1–3), 388–398. 3. B. A. Cavic, G. L. Hayward, and M. Thompson, Acoustic waves and the study of biochemical macromolecules and cells at the sensor-liquid interface. The Analyst, 1999, 124(10), 1405–1420. 4. R. C. Holt and G. J. Gouws, The use of bulk acoustic wave devices as probes of material properties. Current Applied Physics, 2004, 4(2–4), 296–299. 5. M. Kaspar, H. Stadler, T. Weiss, and C. Ziegler, Thickness shear mode resonators (“mass-sensitive devices”) in bioanalysis. Fresenius Journal of Analytical Chemistry, 2000, 366(6–7), 602–610. 6. S. Kurosawa, H. Aizawa, M. Nakamura, and J.-W. Park, Immunosensors using a quartz crystal microbalance. Measurement Science and Technology, 2003, 14, 1882–1887. 7. S. L. Snellings, J. Fuller, and D. W. Paul, Response of a thickness-shear-mode acoustic wave sensor to the adsorption of lipoprotein particles. Langmuir, 2001, 17, 2521–2527. 8. M. Thompson and D. C. Stone, Surface-Launched Acoustic Wave sensors, Wiley-Interscience, 1997. 9. M. Weiss, W. Welsch, M. V. Schickfus, and S. Hunklinger, Viscoelastic behaviour of antibody films on a shear horizontal acoustic surface sensor. Analytical Chemistry, 1998, 70(14), 2881–2887.
INTRODUCTION TO ACOUSTIC TECHNOLOGIES 10. B. A. Cavic, F. L. Chu, L. M. Furtado, S. Ghafouri, G. L. Hayward, D. P. Mack, M. E. McGovern, H. Su, and M. Thompson, Acoustic waves and the real-time study of biochemical macromolecules at the liquid/solid interface. Faraday Discuss, 1997, 107, 159–176. 11. B. A. Cavic and M. Thompson, Protein adsorption to organosiloxane surfaces studied by acoustic wave sensor. The Analyst, 1998, 123(10), 2191. 12. D. Johannsmann, Viscoelastic analysis of organic thin films on quartz resonators. Macromolecular Chemistry and Physics, 1999, 200(3), 501–516. 13. G. McHale, R. Lucklum, M. I. Newton, and J. A. Cowen, Influence of viscoelasticity and interfacial slip on acoustic wave sensors. Journal of Applied Physics, 2000a, 88(12), 7304–7312. 14. G. McHale, M. I. Newton, M. K. Banerjee, and J. A. Cowen, Acoustic wave-liquid interactions. Materials Science and Engineering, 2000b, C12, 17–22. 15. R. Lucklum and P. Hauptmann, Transduction mechanism of acoustic-wave based chemical and biochemical sensors. Measurement Science and Technology, 2003, 14(11), 1854–1864. 16. H. S. Sindi, A. C. Stevenson, and C. R. Lowe, A strategy for chemical sensing based on frequency tunable acoustic devices. Analytical Chemistry, 2001, 73, 1577–1586. 17. L. A. Theisen and S. J. Martin, A model for the quartz crystal microbalance frequency response to wetting characteristics of corrugated surfaces. Analytical Chemistry, 2004, 76, 796–804. 18. J. Curie and P. Curie, Developpement, par pression, de l’electricit polaire dans les cristaux hemiedres faces inclinees. Comptes Rendus de l’ Academie des Sciences Paris, 1880, 91, 294–295. 19. R. P. Buck, E. Lindner, W. Kutner, and G. Inzelt, Piezoelectric chemical sensors. Pure and Applied Chemistry, 2004, 76(6), 1139–1160. 20. K. Bizet, C. Gabrielli, and H. Perrot, Response of quartzcrystal resonators to gas and liquid analyte exposure. Analusis, 1999, 27(7), 609–616. 21. S. J. Martin, V. E. Granstaff, and G. C. Frye, Characterization of a quartz crystal microbalance with simultaneous mass and liquid loading. Analytical Chemistry, 1991, 63(20), 2272–2281. 22. R.W. Cattrall, Chemical Sensors, Oxford University Press, 1997. 23. H. Sota, H. Yoshimine, R. F. Whittier, M. Gotoh, Y. Shirohara, and Y. Hasegawa, A versatile planar QCMbased sensor design for nonlabeling biomolecule detection. Analytical Chemistry, 2002, 74, 3592–3598. 24. B. R. Long, Quartz Crystals and Oscillators A Technical Paper. Corning Frequency Control: IEEE, Frequency Control Reference and Tutorial Information website (first presented at the RF Expo East, 1990), 2002. 25. J. Blitz, Fundamentals of Ultrasonics, 2nd Edn, Butterworths, London, 1967. 26. P. E. Donovan, An investigation of the ferroelectric properties of Rochelle salt. Physics Education, 1979, 14(2), 100. 27. Piezoelectricity, Morgan Electroceramics Technical Publications TP238, Accessible at http://www. morganelectroceramics.com/techpub1.html, 2004.
19
28. J. Gualtieri, J. A. Kosinski, and A. Ballato, Piezoelectric materials for Acoustic Wave Applications. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 1994, 41(1), 53–59. 29. POLECER. Guide on the Best Piezoelectric Properties of Lead-Free Single Crystals. Prepared for POLECER Thematic Network Workpackage 9, 2004. 30. T. Fukumura, Y. Yamada, H. Toyosaki, T. Hasegawa, H. Koinuma, and M. Kawasaki, Exploration of oxidebased diluted magnetic semiconductors toward transparent spintronics. Applied Surface Science Proceedings of the Second Japan-US Workshop on Combinatorial Materials Science and Technology, 2004, 223(1–3), 62–67. 31. K. L. Kavanagh, Atomic interface structure-property investigations. Canadian Journal of Physics, 2000, 78, 201–210. 32. D. Fairweather and R. C. Richards, Quartz Crystals as Oscillators and Resonators, Essex, Chelmsford, 1957. 33. D. Lee and S. Lee, Electric-field measurement near a ring antenna by a new field sensor using piezoelectric resonance. Review of Scientific Instruments, 1996, 67, 9 3320–3324. 34. C. Steinem, A. Janshoff, and H.-J. Galla, Piezoelectric mass-sensing devices as biosensors—an alternative to optical biosensors? Angewandte Chemie, 2000, 39(22), 4004–4032. 35. B. Drafts, Acoustic Wave Technology Sensor, Sensors Magazine, 2001. 36. M. Hoummady, A. Campitelli, and W. Wlodarski, Acoustic wave sensors: design, sensing mechanisms and applications. Smart Material Structure, 1997, 6, 647–657. 37. E. Benes, M. Groschl, W. Burger, and M. Schmid, Sensors based on piezoelectric resonators. Sensors and Actuators A: Physical, 1995, 48(1), 1–21. 38. J. W. Grate, S. J. Martin, and R. M. White, Acoustic wave microsensors: part I. Analytical Chemistry, 1993, 65(21), 940-A–948. 39. M. D. Ward and D. A. Buttry, In situ interfacial mass detection with piezoelectric transducers. Science, 1990, 249(4972), 1000–1007. 40. A. P. M. Glassford, Response of quartz crystal microbalance to a liquid deposit. Journal of Vacuum Science and Technology, 1978, 15(6), 1836–1843. 41. L. Tessier, N. Schmitt, H. Watier, V. Brumas, and F. Patat, Potential of the thickness shear mode acoustic immunosensors for biological analysis. Analytica Chimica Acta, 1997, 347(1–2), 207–217. 42. M. J. Vellekoop, Acoustic wave sensors and their technology. Ultrasonics, 1998, 36(1–5), 7–14. 43. G. L. Hayward and M. Thompson, A transverse shear model of a piezoelectric chemical sensor. Journal of Applied Physics, 1998, 83(4), 2194–2201. 44. G. Sauerbrey, Use of quartz vibration for weighing thin films on a microbalance/Verwendung von Schwingquarzen zur Wagung dunner Schichten und zur Mikrowagung. Zeitschrift fur Medizinische Physik, 1959, 155, 206. 45. C. Lu and A. W. Czanderna, Applications of Piezoelectric Quartz Crystal Microbalances, Elsevier, New York, 1984. 46. J. G. Miller and D. I. Bolef, Sensitivity enhancement by the use of acoustic resonators in cw ultrasonic spectroscopy. Journal of Applied Physics, 1968a, 39(10), 4589–4593.
20
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
47. J. G. Miller and D. I. Bolef, Acoustic wave analysis of the operation of quartz-crystal film-thickness monitors. Journal of Applied Physics, 1968b, 39(12), 5815–5816. 48. K. H. Behrndt, Long-term operation of crystal oscillators in thin-film deposition. Journal of Vacuum Science and Technology, 1971, 8(5), 622–625. 49. C.-S. Lu and O. Lewis, Investigation of film-thickness determination by oscillating quartz resonators with large mass load. Journal of Applied Physics, 1972, 43(11), 4385–4390. 50. C.-S. Lu, Mass determination with piezoelectric quartz crystal resonators. Journal of Vacuum Science and Technology, 1975, 12(1), 578–583. 51. V. Mecea and R. V. Bucur, The mechanism of the interaction of thin films with resonating quartz crystal substrates: the energy transfer model. Thin Solid Films, 1979, 60(1), 73–84. 52. R. A. Crane and G. Fisher, Analysis of a quartz crystal of microbalance with coatings of finite viscosity. Journal of Physics D: Applied Physics, 1979, 12, 2019–2026. 53. K. K. Kanazawa and J. G. Gordon, The oscillation of a quartz resonator in contact with a liquid. Analytica Chimica Acta, 1985, 175, 99–105. 54. M. V. Voinova, M. Jonson, and B. Kasemo, ‘Missing mass’ effect in biosensor’s QCM applications. Biosensors and Bioelectronics, 2002, 17(10), 835–841. 55. S. Bruckenstein and M. Shay, Experimental aspects of use of the quartz crystal microbalance in solution. Electrochimica Acta, 1985, 30(10), 1295–1300. 56. T. Nomura and A. Minemura, Behavior of a piezoelectric quartz crystal in an aqueous solution and the application to the determination of minute amounts of cyanide. Nippon Kagaku Kaishi, 1980, 1980, 1621–1625. 57. T. Nomura and M. Okuhara, Frequency shifts of piezoelectric quartz crystals immersed in organic liquids. Analytica Chimica Acta, 1982, 142, 281–284. 58. R. Schumacher, G. Borges, and K. K. Kanazawa, The quartz microbalance: a sensitive tool to probe surface reconstructions on gold electrodes in liquid. Surface Science, 1985, 163(1), L621–L626. 59. K. E. Heusler, A. Grzegorzewski, L. Jackel, and J. Pietrucha, Measurement of mass and surface stress at one electrode of a quartz oscillator. Berichte Der BunsenGesellschaft-Physical Chemistry Chemical Physics, 1988, 92(11), 1218–1225. 60. H. E. Hager, Fluid property evaluation by piezoelectric crystals operating in the thickness shear mode. Chemical Engineering Communications, 1986, 43(1–3), 25–38. 61. H. Muramatsu, E. Tamiya, and I. Karube, Computation of equivalent circuit parameters of quartz crystals in contact with liquids and study of liquid properties. Analytical Chemistry, 1988, 60(19), 2142. 62. Z. A. Shana, D. E. Radtke, U. R. Kelkar, F. Josse, and D. T. Haworth, Theory and application of a quartz resonator as a sensor for viscous liquids. Analytica Chimica Acta, 1990, 231, 317–320. 63. S.-Z. Yao and T.-A. Zhou, Dependence of the oscillation frequency of a piezoelectric crystal on the physical parameters of liquids. Analytica Chimica Acta, 1988, 212, 61–72.
64. A. C. Stevenson and C. R. Lowe, Magnetic-acousticresonator sensors (MARS): a new sensing methodology. Sensors and Actuators A: Physical, 1999, 72(1), 32–37. 65. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Mehta, and C. R. Lowe, The acoustic spectrophonometer: a novel bioanalytical technique based on multifrequency acoustic devices. Analyst, 2003, 128(10), 1222–1227. 66. Q Sense. www.q-sense.com, 2006. 67. M. Rodahl, F. Hook, A. Krozer, P. Brzezinski, and B. Kasemo, Quartz crystal microbalance setup for frequency and Q-factor measurements in gaseous and liquid environments. Review of Scientific Instruments, 1995, 66(7), 3924–3930. 68. M. Rodahl and B. Kasemo, A simple setup to simultaneously measure the resonant frequency and the absolute dissipation factor of a quartz crystal microbalance. Review of Scientific Instruments, 1996, 67(9), 3238–3241. 69. H.-W. Chang and J.-S. Shih, Surface acoustic wave immunosensors based on immobilized C60-proteins. Sensors and Actuators B: Chemical, 2006, 121(2), 522–529. 70. E.-L. Lyle, G. L. Hayward, and M. Thompson, Acoustic coupling of transverse waves as a mechanism for the label-free detection of protein-small molecule interactions. Analyst, 2002, 127, 1596–1600. 71. E. Berkenpas, P. Millard, and M. Pereira da Cunha, Detection of Escherichia coli O157:H7 with langasite pure shear horizontal surface acoustic wave sensors. Biosensors and Bioelectronics, 2006, 21(12), 2255–2262. 72. T.-Y. Lin, C.-H. Hu, and T.-C. Chou, Determination of albumin concentration by MIP-QCM sensor. Biosensors and Bioelectronics, 2004, 20(1), 75–81. 73. M. Michalzik, J. Wendler, J. Rabe, S. Buttgenbach, and U. Bilitewski, Development and application of a miniaturised quartz crystal microbalance (QCM) as immunosensor for bone morphogenetic protein-2. Sensors and Actuators B: Chemical, 2005, 105(2), 508–515. 74. L. Pastorino, F. Caneva Soumetz, M. Giacomini, and C. Ruggiero, Development of a piezoelectric immunosensor for the measurement of paclitaxel. Journal of Immunological Methods, 2006, 313(1–2), 191–198. 75. C. D. Corso, D. D. Stubbs, S.-H. Lee, M. Goggins, R. H. Hruban, and W. D. Hunt, Real-time detection of mesothelin in pancreatic cancer cell line supernatant using an acoustic wave immunosensor. Cancer Detection and Prevention, 2006, 30(2), 180–187. 76. X.-L. Su and Y. Li, A QCM immunosensor for Salmonella detection with simultaneous measurements of resonant frequency and motional resistance. Biosensors and Bioelectronics, 2005, 21(6), 840–848. 77. S. J. Martin, G. C. Frye, J. J. Spates, and M. A. Butler, Gas Sensing with Acoustic Devices, Ultrasonics Symposium, San Antonio, 1996. 78. L. M. Reindl, A. Pohl, G. Scholl, and R. Weigel, SAWbased radio sensor systems. Sensors Journal, IEEE, 2001, 1(1), 69–78. 79. B. Jakoby and M. J. Vellekoop, Properties of love waves: applications in sensors. Smart Material Structure, 1997, 6, 668–679.
INTRODUCTION TO ACOUSTIC TECHNOLOGIES 80. G. Scholl, F. Schmidt, and U. Wolff, Surface acoustic wave devices for sensor applications. Physica Status Solidi (a), 2001, 185(1), 47–58. 81. F. Moeller and J. Kuhn, SAW resonator temperature sensor. Sensors and Actuators, 1992, A30(1–2), 73–75. 82. D. E. Cullen and T. M. Reeder, Measurement of SAW Velocity Versus Strain for YX and ST Quartz, Ultrasonics Symposium, 1975, pp. 519–522. 83. J. Beckley, V. Kalinin, M. Lee, and K. Voliansky, NonContact Torque Sensors Based on SAW Resonators, IEEE International Frequency Control Symposium and PDA Exhibition, 2002, pp. 202–213. 84. R. M. Lec, Piezelectric Biosensors: Recent Advances and Applications, In: Proceedings of the 2001 IEEE International Frequency Control Symposium & PDA Exhibition, Seattle, Washington, USA, June 5–8, 2001, pp. 419–429. 85. K. Kastl, M. Ross, V. Gerke, and C. Steinem, Kinetics and thermodynamics of annexin A1 binding to solid-supported membranes: a QCM study. Biochemistry, 2002, 41(31), 10087–10094.
21
86. Z. Pei, H. Anderson, T. Aastrup, and O. Ramstrom, Study of real-time lectin-carbohydrate interactions on the surface of a quartz crystal microbalance. Biosensors and Bioelectronics, 2005, 21(1), 60–66. 87. Y. Liu, X. Yu, R. Zhao, D.-H. Shangguan, Z. Bo, and G. Liu, Real time kinetic analysis of the interaction between immunoglobulin G and histidine using quartz crystal microbalance biosensor in solution. Biosensors and Bioelectronics, 2003, 18(11), 1419–1427. 88. J. Pepper, R. Noring, M. Klempner, B. Cunningham, A. Petrovich, R. Bousquet, C. Clapp, J. Brady, and B. Hugh, Detection of proteins and intact microorganisms using microfabricated flexural plate silicon resonator arrays. Sensors and Actuators B: Chemical, 2003, 96(3), 565–575. 89. M. Rodahl, F. Hook, C. Fredriksson, C. A. Keller, A. Krozer, P. Brzezinski, M. Voinova, and B. Kasemo, Simultaneous frequency and dissipation factor QCM measurements of biomolecular adsorption and cell adhesion. Faraday Discuss, 1997, 107, 229–246.
36 Love Wave Biosensors Kathryn A. Melzak1 and Electra Gizeli1,2 1
Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Crete, Greece and 2 Department of Biology, University of Crete, Crete, Greece
1 INTRODUCTION
Love wave sensors are acoustic devices that employ Love waves, propagating shear-horizontal acoustic waves that are confined to the surface region of a substrate by applying a thin overlayer that acts as a waveguide. In common with many other acoustic sensors, the principle of measurement is that the propagation of the acoustic wave through the solid medium of the sensor is affected by changes in the adjacent medium that contains the analyte of interest. The fundamental physical questions associated with Love wave sensor measurements concern are about the manner in which the wave propagates and the manner in which this propagation is affected by changes in the medium adjacent to the sensor. Although the former point has been addressed thoroughly over the last century since Love waves were first described in seismological studies, the latter point remains under investigation, particularly for biological samples where the interaction with the sensor surface can be complex. There are additional practical considerations associated with acoustic sensor measurements: the acoustic wave must be generated with suitably designed acoustic devices, the wave propagation must be measured, and the device surface must be made specific for the analyte of interest. Love wave sensors respond to analyte interaction with
the exposed surface of the waveguide layer, and hence this is the surface that must be modified to confer specificity on the sensor. The variety of waveguide materials that is available leads to requirements for a variety of surface modification procedures.
2 DESCRIPTION OF LOVE WAVES
Love waves are produced in acoustic sensors when a waveguide layer is added to a substrate that supports a shear wave such as a surface skimming bulk wave, an acoustic plate mode, or a leaky surface acoustic wave. Addition of a waveguide layer has the effect of confining the acoustic energy close to the sensing surface that is exposed to the analyte, thus increasing the device sensitivity; the mass sensitivity of acoustic devices with shear-horizontal waves can be increased by a factor of up to 20 by the addition of an appropriate waveguide.1 Experimental results have shown that Love wave sensors have the highest mass sensitivity2–4 and viscosity sensitivity5 of acoustic sensors. A schematic representation of the Love wave device is shown in Figure 1. The waveguide layer must be a dielectric material with a lower shear acoustic velocity (Vshear ) than that of the substrate in order to satisfy the criteria for generating a Love wave. In addition, the
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Waveguide layer
h z
Source
Piezoelectric substrate (quartz) Interdigitated transducers Figure 1. Schematic representation of the Love wave device, with a waveguide thickness h. Note that the bars of the transducers and the waveguide thickness are not drawn to scale.
thickness (h) of the layer is critical for achieving maximum surface sensitivity. Waveguide layers with a high shear velocity give maximum sensitivity when thick layers are applied; for a device operating at 110 MHz, the optimum thickness for a silica waveguide layer with Vshear = 2560 m s−1 is h = 15 µm.6 In contrast, waveguide layers with a low shear velocity give maximum sensitivity when thin films are used; for example, for the 110 MHz device, the optimum thickness of a polymer layer with Vshear = 1000 m s−1 is h = 1.3 µm.7 Increasing the operating frequency of the device will result in a reduction of the optimum guiding layer thickness.
3 SENSING MECHANISM
Love wave sensors respond to perturbations that affect the mechanical properties of the region adjacent to the device surface. In addition, because of the piezoelectric nature of the substrate, changes in the electric properties at the surface can also be detected. However, the latter sensing mechanism can be eliminated by careful device and set-up design and for this reason is not considered during biosensing applications. Love wave sensors respond to mass that is adsorbed to the exposed surface of the waveguide layer. The mass sensitivity Sm of the Love wave sensor has been described theoretically by several investigators.1,2,8–12 Perturbation theory has been used to derive more complex equations relating Sm to the density, shear velocity, and thickness of the mass loaded on the surface as well as the
average stored energy in the waveguide.1,10 In the preceding analysis, it is assumed that the thickness of the deposited mass layer is much smaller than the wavelength and therefore does not have the characteristics of a waveguide layer. In general, the mass sensitivity Sm of the sensor is measured empirically as a change in a measured acoustic parameter, typically frequency or velocity, as a result of mass adsorption and is given by a formula with the following format: v/v0 h→0 h→0 m/A (1) The terms f and v represent the change in frequency and velocity, respectively, occurring as a result of the deposition of mass m in an area A and f0 and v0 are the frequency and velocity of the waveguide device prior to mass deposition. Values of Sm derived from equation (1) are expressed in cm2 g−1 and are independent of the area over which mass is loaded and the device operating frequency. Love wave devices operate in liquid without excessive damping of the wave, making them suitable for analysis of biomolecular samples in an aqueous environment. Liquid in contact with the acoustic device will couple with the oscillating surface of the device. The thickness δ of the coupled liquid layer depends on the angular frequency ω (where ω = 2πf ) and the liquid’s shear viscosity ηl and density ρl according to: 2ηl δ= (2) ρl ω Sm = − Lim
f/f0 m/A
or
Sm = − Lim
LOVE WAVE BIOSENSORS
The outer boundary of the layer is taken to be the point where the wave amplitude has decayed to 1/e of its initial value. For a 100 MHz wave operating in water, δ is calculated to be 56 nm. If the liquid above the acoustic sensor behaves as a Newtonian fluid, then the relative change in velocity v/v and the attenuation α of the acoustic wave are proportional to (ηρ)1/2 , where η is the dynamic viscosity and ρ is the solution density. At higher viscosities, the relaxation time of the liquid becomes significant. The relaxation time is also significant at low viscosities for solutes with high molecular weight.13 In order to model the response of Love wave sensors in liquid, the displacement associated with the acoustic wave must be determined simultaneously in the substrate, the waveguide layer, and the liquid layer. This is done by solving the wave equation for the three layers, while making assumptions such as nonslip conditions regarding the boundaries between the layers. These results can be combined with an equation analogous to equation (1) in order to obtain the sensitivity as a function of layer properties such as waveguide layer thickness or solution viscosity.8–10 One limitation encountered with models of acoustic waves is the requirement for a value for the shear velocity and modulus of adsorbed layers at the operating frequency of the device; theoretical predictions of adsorbed mass must account for the difference in shear modulus with frequency14 in order to obtain accurate results. Models of the response for shear acoustic sensors can also be limited by the assumptions that are made regarding the boundary conditions. The non-slip boundary condition that is often made for sensors operating in liquids states that the velocity of fluid moving parallel to a surface reduces to zero with respect to the surface. If the surface of the sensor moves because of the acoustic wave, the nonslip boundary condition assumes that the displacements in the liquid layer immediately adjacent to the surface will be the same as those at the surface of the solid. The non-slip boundary condition may not be a valid assumption15,16 for shear-mode acoustic sensors that operate with high surface accelerations. Modeling of the response of acoustic sensors remains an active area of research. In general, the sensor response can be modeled accurately for mass that is firmly attached to the surface, such as a deposited metal layer; the response can also be
3
modeled accurately for solutions. Interpretation of acoustic sensor data becomes more complicated when there are large molecules or whole cells adsorbed to the sensor surface and the response is associated with changes in mass and simultaneous changes in conformation.
4 PRACTICAL CONSIDERATIONS: DEVICES, WAVEGUIDES, SURFACE MODIFICATIONS, AND MEASUREMENTS
Acoustic waves can be generated via the piezoelectric effect, by application of an alternating current to suitably placed interdigital electrodes (IDTs) on the surface of a piezoelectric substrate (see Figure 1). The IDTs consist of a pair of contact pads and a number of repeating parallel bars. Each contact pad is electrically connected to alternating bars but the contact pads with their respective sets of bars are not connected to each other. A voltage is applied to produce a difference in potential between two contact pads. If the underlying substrate is piezoelectric, it will be deformed in a direction determined by the orientation of the piezoelectric crystal. Application of an alternating current results in an oscillating stress that is applied to the piezoelectric crystal, thus generating the acoustic wave. The waves generated at each pair of oppositely polarized bars will move outward in both directions and will add constructively if the distance between the repeating pairs is appropriate. In practice, the distance between the pairs is fixed, thus determining the acoustic wavelength, and the acoustic velocity is determined by the piezoelectric crystal, through which the wave travels; these factors combine to determine the frequency of alternating current that can be used to generate acoustic waves efficiently. The nature of the acoustic wave generated will be a function of the orientation and thickness of the piezoelectric substrate. The acoustic devices used to generate Love waves consist of a pattern of interdigital electrodes on a section cut from a wafer of piezoelectric substrate. The electrodes are typically prepared by photolithography. Design features that can be changed include the nature of the substrate, the metal of the IDTs,17 and the choice of a delay line or a resonator configuration.
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
For delay line devices, many details of the IDT pattern will affect the device performance. The repeat distance of the IDTs determines the wavelength of the acoustic wave that is generated. Thinner metal layers in the IDTs lead to the appearance of harmonic peaks; this is an additional way to vary the acoustic wavelength and the operating frequency of the device. Increasing the number of repeat units of the IDTs will decrease the bandwidth but increase the maximum transmitted power. The repeat distance between the input and output IDTs is typically 100–300 wavelengths; increasing the separation distance will decrease the transmitted signal but increase the pathlength through the sample to be measured, since the sample is generally placed between the IDTs. Split fingers are used to minimize reflections at the IDTs by causing destructive interference of the reflected waves. The ends of the devices can be cut at an angle to minimize the effect of reflections of the acoustic wave off the ends of the device, thus leading to a smoother transfer function. This can be done either by modifying the shape of the device when seen from the top surface (the ends can be cut at an angle with respect to the IDTs, to produce a parallelogram shape) or by changing the shape of the device when viewed in profile; again, the ends of the device near the IDTs can be polished with sandpaper to a 45◦ angle. Addition of the waveguide layer also decreases the effect of the reflections of the acoustic wave off the ends of the device. The waveguide must be dielectric material with a low density and a lower acoustic velocity than that of the substrate in order to satisfy the criteria for generating a Love wave; in addition, it must be elastic to minimize dissipation of the acoustic energy. Silica8,18–23 and organic polymer layers are the most commonly used waveguide materials; ZnO has also been investigated and has been shown to confer better sensitivity than SiO2 .24,25 Silica is chemically resistant and has good elastic properties; the limitations of silica as a waveguide material lie in the difficulty and expense of preparing a suitable and reproducible layer on the surface of the acoustic device. Waveguides can be readily prepared from organic polymers by spin-coating and also by vapor deposition on the substrate.26 Poly(methyl methacrylate) (PMMA),27–31 parylene,26 polystyrene,32 polyimide32 and Novolac photoresist,31,33,34 in addition
to polymers that are chemically selective with regard to analytes,35 have been employed as waveguide layers. Novolac is more resistant to solvents than is PMMA, possibly because of crosslinking; this has some advantages, but this does not appear to affect the mass sensitivity of the devices.31 Polymer waveguide layers can often be cleaned off to permit the acoustic device to be reused. The optimum waveguide thickness will be a function of the acoustic velocities in the waveguide and the substrate;10 in practice, this is best determined empirically by depositing a nonconducting, acoustically thin (<10 nm) mass layer on the device; mass layers have been built by sequential additions of Langmuir–Blodgett films2 and by deposition of metal films24,36 or silica.4 Typical values of Sm reported in literature vary from 380 cm2 g−1 for an optimized silica guiding layer18 to 430 cm2 g−1 for an optimized PMMA guiding layer.30 The highest Sm ever measured has been for a trilayer waveguide system comprising quartz overlaid by an SiO2 and a PMMA guiding layer, and was 640 cm2 g−1 .4 The response of Love devices to changes in viscosity has been determined with different solutions37 and with solutions of polymers of increasing molecular weight to characterize the solute rotation time.13 In some cases, waveguides can be used to screen the IDTs, so that the IDTs can be exposed to liquids. For quartz devices, organic polymer waveguide layers are not sufficiently thick to act as electrical insulators; the IDTs must therefore be protected from the aqueous sample. On delay line devices, the sample solution can be contained to a region between the IDTs by a flow cell and gasket that are pressed against the device surface. Pressure on the device will decrease the efficiency of transmission of the acoustic wave and should therefore be minimized. Silica waveguides have been shown to permit measurements with the IDTs exposed to buffer,23 although sputtered silica may be sufficiently permeable to permit solution electrolyte to reach the IDTs.26 The IDTs on lithium tantalate substrates may be exposed to aqueous buffer when coated with polymer waveguides, because of the higher electromechanical coupling coefficient.38 The waveguide layer is the surface that is exposed to the sample, and therefore is the surface that must be modified in order to ensure the
LOVE WAVE BIOSENSORS
appropriate specificity with regard to the analyte. Silica layers have been modified by structuring of the surface to separate the viscosity and density effects of solutions,39,40 by silanation to produce a hydrophobic surface for protein adsorption,18,23 by addition of a bifunctional cross-linker to react with proteins22 and by deposition of lipid vesicles to form a supported lipid bilayer (SLB).21 Waveguides composed of organic polymers have been modified by addition of a thin gold layer suitable for subsequent deposition of proteins33,38 or for modification with alkylthiols;25 PMMA layers have also been modified with a silicate gel to promote formation of SLBs28 and have been used directly for protein adsorption.27 Immunosensors can be prepared by the nonspecific adsorption of protein G to a hydrophobic surface such as an exposed gold layer, followed by interaction of the protein G with the antibody of interest; an analogous procedure can be carried out with an initial nonspecific adsorption of neutravidin or streptavidin followed by a specific binding to a biotinylated molecule of interest.41 The response of Love wave devices can be measured with oscillator circuits and frequency counters,18,19,22–24 network analyzers,20–22,26,33,34,36 vector voltmeters,27 and other systems.42
5 LOVE WAVE DEVICES AS BIOSENSORS
Love wave devices are suitable for measuring adsorbed mass in liquid, solution viscosity, and for the analysis of the viscoelastic properties of thin adsorbed layers; examples of these and other more specific applications are listed in Table 1. The mass sensitivity of acoustic sensors may be exploited to produce biosensors for analyzing many biologically important binding interactions. These include antibody–antigen interactions, other protein binding events, and protein interaction with SLBs that mimic the lipid bilayer of cell membranes. If one of the binding partners in any of these interactions is attached to the surface of an acoustic device, then the binding events can be monitored by recording the increase in mass adsorbed to the surface. Love wave devices have been used to measure antibody–antigen interactions,6,27,32,47 including assays where the antigens are associated
5
Table 1. Examples of applications
General applications: • Detection of adsorbed mass1,18,24,43 • Detection of adsorbed mass in liquid7,8,10,11 • Measurement of viscosity-density product in liquids12,37 • Measurement of viscosity and density separately, with a structured surface5,39,40 • Measurement of thin-film viscoelastic properties and density separately, by comparison with reference solutions33 Specific applications: • Measurements of protein adsorption19,33,38 • Measurement of protein layer water content, in combination with optical measurements20,44 • Analysis of protein interactions: binding and rate constants34,45 • Immunoassays6,27,46–48 • Aptamer–protein interactions45,49 • Formation of supported lipid bilayers21,28,50 • Analysis of membrane proteins, with supported lipid bilayers29 • Assays with whole viruses and cells22,23,32
with whole cells,23 viruses22 or spores,32 those where the antibody is associated with air-filled microbeads that act as ultrasound contrast agents48 and those where the antigen is associated with an SLB that can be rinsed off to regenerate the sensor surface.47 Other interactions that have been measured with Love wave sensors include binding of antibodies to protein A and protein G,34 the binding of anticoagulants to the blood clotting factor thrombin,45 and the interaction of membrane proteins with an SLB.29 Love wave devices have been used to obtain simultaneous information about the viscoelasticity and adsorbed mass for layers of proteins33 and have been combined with optical measurements to determine the water content of protein layers.20 Love wave devices have also been used28 to monitor the transition from adsorbed vesicle layers to bilayers during formation of SLBs by vesicle fusion. Although Love wave sensors perform well in the previously mentioned applications, similar results can often be obtained with other label-free, realtime acoustic or optical techniques. The closest equivalent sensor in common use is the transverse shear mode resonator (TSMR) acoustic device, commercially available through Q-Sense and other companies.51 TSMR is an alternative term for the device known as a quartz crystal microbalance (QCM), due to the device’s sensitivity to factors other than mass. The little information that
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
is available on direct comparisons between Love wave sensors and TSMR devices suggests that they can provide complementary information, in combination with optical measurements, that helps to resolve the viscoelastic effects that can contribute to ambiguities in TSMR determinations of adsorbed protein mass.20 Love wave sensors for bacteriophage detection have been shown by indirect comparison to operate over a greater range of sample concentration than a TSMR, although similar relative frequency shifts were observed.52 The main difference between the two devices is the operating frequency: in the TSMR configuration the f0 is restricted by the thickness of the oscillating plate resulting in a typical fundamental frequency of 5 MHz, which can go up to 65 MHz if harmonics up to the 13th mode are probed. In contrast, the operating frequency of the Love wave device can vary from few tenths up to several thousand MHz (i.e., from 50 up to 500 MHz). This difference affects the penetration depth δ which will be approximately 180 nm for the 10-MHz TSMR, compared to 56 nm for a 100-MHz device; additionally, sensors with the same sensitivity as measured by the relative frequency change will have a greater absolute frequency change with a higher operating frequency. The sensitivity and detection limit are both points of interest when comparing various biosensors. For a strict comparison of these parameters between various sensors, one should compare the performance of the systems during the binding of the same analyte under identical conditions such as surface properties, biorecognition chemistry, pH, flow, and temperature. Such experiments have not been performed; however, quoted values in literature give a detection limit of ∼74 pg cm−2 for the Love wave biosensor, based on the direct measurement of bound mass of fluorescently labeled protein (human α-thrombin) and aptamer (HIV-1Rev peptide) on the device surface.49 The detection limit of the commercially available Q-Sense E4 TSMR device is quoted as 500 pg cm−2 in the product information brochure, but this value has been determined using the Sauerbrey equation rather than being experimentally measured (the mass sensitivity Sm for the QCM is given 2f 2 f by the Sauerbrey equation:Sm = ρ = − √ 0 , m µq ρq where µq and ρq are the shear stiffness and density of quartz). The reported detection limit of surface
plasmon resonance (SPR) devices to protein binding is 100–1000 pg mm−2 .53 In the future, the widespread use of Love wave sensors for measurements of mass deposition would depend on the availability of the acoustic devices, the cost of the other components required in the analysis, and on the availability of complete detection systems; lower cost acoustic devices are therefore an area of interest and have been investigated.19 One potential advantage of Love wave sensors in this regard is that techniques have been developed for large-scale manufacture due to the extensive use of analogous devices as electronic components. Additionally, it has been demonstrated that the Love wave sensor response may be determined with relatively inexpensive oscillator circuits and frequency counters; another potentially advantageous feature of Love wave sensors is that multiple channels can be prepared on one device. The strength of acoustic sensors is their sensitivity to solution viscosity and to the viscoelastic properties of thin layers; the latter feature means that acoustic sensors are able to provide more information about adsorbed layers than the amount of adsorbed mass. The viscoelastic properties of adsorbed layers of biomolecules are of interest because of their relation to the structural features within the layer. Changes in the viscoelastic properties can indicate conformational changes that are not associated with adsorption or desorption of mass. The difficulty here lies in the interpretation of the data; relatively few experiments have been carried out in this area. It is anticipated that the development of better models to quantify mass and viscoelastic changes together with the Love wave devices’ inherent high sensitivity will, in the future, lead to a new generation of acoustic wave biosensors.
REFERENCES 1. Z. Wang, J. D. N. Cheeke, and C. K. Jen, Sensitivity analysis for love mode acoustic gravimetric sensors. Applied Physics Letters, 1994, 64, 2940–2942. DOI: 10.1063/1.111976. 2. E. Gizeli, N. J. Goddard, C. R. Lowe, and A. C. Stevenson, A love plate biosensor utilising a polymer layer. Sensors and Actuators B-Chemical, 1992, 6, 131–137. DOI: 10.1016/0925-4005(92)80044-X. 3. J. Du, G. L. Harding, J. A. Ogilvy, P. R. Dencher, and M. Lake, A study of love-wave acoustic sensors.
LOVE WAVE BIOSENSORS
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
Sensors And Actuators A-Physical, 1996, 56, 211–219. DOI: 10.1016/S0924-4247(96)01311-8. J. Du and G. L. Harding, A multilayer structure for love-mode acoustic sensors. Sensors and Actuators A-Physical, 1998, 65, 152–159. DOI: 10.1016/S09244247(97)01698-1. A. Turton, D. Bhattacharyya, and D. Wood, Liquid density analysis of sucrose and alcoholic beverages using polyimide guided love-mode acoustic sensors. Measurement Science and Technology, 2006, 17, 257–263. DOI: 10.1088/0957-0233/17/2/005. G. L. Harding, J. Du, P. R. Dencher, D. Barnett, and E. Howe, Love wave acoustic immunosensor operating in liquid. Sensors and Actuators A-Physical, 1997, 61, 279–286. DOI: 10.1016/S0924-4247(97)80275-0. E. Gizeli, Study of the sensitivity of the acoustic waveguide sensor. Analytical Chemistry, 2000, 72, 5967–5972. DOI: 10.1021/ac000694u. C. McMullan, H. Mehta, E. Gizeli, and C. R. Lowe, Modelling of the mass sensitivity of the love wave device in the presence of a viscous liquid. Journal of Physics D-Applied Physics, 2000, 33, 3053–3059. DOI: 10.1088/0022-3727/33/23/307. B. Jakoby and M. J. Vellekoop, Properties of love waves: applications in sensors. Smart Materials and Structures, 1997, 6, 668–679. DOI: 10.1088/0964-1726/6/6/003. G. McHale, M. I. Newton, and F. Martin, Theoretical mass sensitivity of love wave and layer guided acoustic plate mode sensors. Journal of Applied Physics, 2002, 91, 9701–9710. DOI: 10.1063/1.1477603. G. Kovacs and A. Venema, Theoretical comparison of sensitivities of acoustic shear wave modes for (bio)chemical sensing in liquids. Applied Physics Letters, 1992, 61, 639–641. DOI: 10.1063/1.107807. G. Kovacs, M. J. Vellekoop, G. W. Lubking, and A. Venema, A love wave sensor for (bio)chemical sensing in liquids. Sensors and Actuators A-Physical, 1994, 43, 38–43. DOI: 10.1016/0924-4247(93)00660-V. K. A. Melzak, F. Martin, M. I. Newton, G. McHale, and E. Gizeli, Acoustic determination of polymer molecular weights and rotation times. Journal of Polymer Science Part B: Polymer Physics, 2002, 40, 1490–1495. DOI: 10.1002/polb.10206. L. Fadel, C. Zimmermann, I. Dufour, D. Rebi`ere, C. D´ejous, and J. Pistr´e, Coupled determination of gravimetric and elastic effects on two resonant chemical sensors: love wave and microcantilever platforms. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, 2005, 52, 297–303. DOI: 10.1109/TUFFC.2005.1406555. W. C. Duncan-Hewitt and M. Thompson, Fourlayer theory for the acoustic shear-wave sensor in liquids incorporating interfacial slip and liquid structure. Analytical Chemistry, 1992, 64, 94–105. DOI: 10.1021/ac00025a017. E. T. Watts, J. Krim, and A. Widom, Experimental observation of interfacial slippage at the boundary of molecularly thin films with gold substrates. Physical Review B, 1990, 41, 3466–3472. DOI: 10.1103/PhysRevB.41.3466. F. Hermann, B. Jakoby, J. Rabe, and S. B¨uttgenbach, Micoacoustic Sensors for Liquid Monitoring, in Sensors Update, H. Baltes, J. Hesse, and J. Korvink (eds),
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
7
Wiley-VCH, Weinheim, 2001, Vol. 9, pp. 105–160. DOI: 10.1002/1616-8984(200105)9:1<105::AID-SEUP105>3. 0.CO;2-I. G. L. Harding, Mass sensitivity of love-mode acoustic sensors incorporating silicon dioxide and silicon-oxyfluoride guiding layers. Sensors and Actuators A-Physical, 2001, 88, 20–28. DOI:10.1016/S0924-4247(00)00491-X. N. Bari´e, T. Wessa, M. Bruns, and M. Rapp, Love waves in SiO2 layers on STW-resonators based on LiTaO3 . Talanta, 2004, 62, 71–79. DOI: 10.1016/S0039-9140(03)00407-7. C. Zhou, J. M. Friedt, A. Angelova, K. H. Choi, W. Laureyn, F. Frederix, L. A. Francis, A. Campitelli, Y. Engelborghs, and G. Borghs, Human immunoglobulin adsorption investigated by means of quartz crystal microbalance dissipation, atomic force microscopy, surface acoustic wave, and surface plasmon resonance techniques. Langmuir, 2004, 20, 5870–5878. DOI: 10.1021/la036251d. E. Gizeli and J. Glad, Single-step formation of a biorecognition layer for assaying histidine-tagged proteins. Analytical Chemistry, 2004, 76, 3995–4001. DOI: 10.1021/ac034855g. O. Tamarin, C. D´ejous, D. Rebi`ere, J. Pistr´e, S. Comeau, D. Moynet, and J. Bezian, Study of acoustic love wave devices for real time bacteriophage detection. Sensors and Actuators B-Chemical, 2003, 91, 275–284. DOI: 10.1016/S0925-4005(03)00106-0. E. Howe and G. Harding, A comparison of protocols for the optimisation of detection of bacteria using a Surface Acoustic Wave (SAW) biosensor. Biosensors and Bioelectronics, 2000, 15, 641–649. DOI: 10.1016/S09565663(00)00116-0. D. A. Powell, K. Kalantar-zadeh, and W. Wlodarski, Numerical calculation of SAW sensitivity: application to ZnO/LiTaO3 transducers. Sensors and Actuators A-Physical, 2004, 115, 456–461. DOI:10.1016/j.sna. 2004.05.031. K. Kalantar-zadeh, W. Wlodarski, Y. Y. Chen, B. N. Fry, and K. Galatsis, Novel love mode surface acoustic wave based immunosensors. Sensors and Actuators BChemical, 2003, 91, 143–147. DOI: 10.1016/S09254005(03)00079-0. F. Bender, K. Lange, N. Bari´e, J. Kondoh, and M. Rapp, On-line monitoring of polymer deposition for tailoring the waveguide characteristics of love-wave biosensors. Langmuir, 2004, 20, 2315–2319. DOI: 10.1021/la035674c. F. Bender, R. W. Cernosek, and F. Josse, Lovewave biosensors using cross-linked polymer waveguides on LiTaO3 substrates. Electronics Letters, 2000, 36, 1672–1673. DOI: 10.1049/el:20001137. K. A. Melzak and E. Gizeli, A silicate gel for promoting deposition of lipid bilayers. Journal of Colloid and Interface Science, 2002, 246, 21–28. DOI: 10.1006/jcis.2001.8054. K. A. Melzak, D. J. Ellar, and E. Gizeli, Interaction of cytolytic toxin CytB with a supported lipid bilayer: study using an acoustic wave device. Langmuir, 2004, 20, 1386–1392. DOI: 10.1021/la035469x. E. Gizeli, Design considerations for the acoustic waveguide biosensor. Smart Materials and Structures, 1997, 6, 700–706. DOI: 10.1088/0964-1726/6/6/006.
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
31. A. Rasmusson and E. Gizeli, Comparison of poly(methylmethacrylate) and Novolak waveguide coatings for an acoustic biosensor. Journal of Applied Physics, 2001, 90, 5911–5914. DOI: 10.1063/1.1405142. 32. D. W. Branch and S. M. Brozik, Low-level detection of a bacillus anthracis simulant using love-wave biosensors on 36 YX LiTaO3 . Biosensors and Bioelectronics, 2004, 19, 849–859. DOI: 10.1016/j.bios.2003.08.020. 33. K. Saha, F. Bender, A. Rasmusson, and E. Gizeli, Probing the viscoelasticity and mass of a surface-bound protein layer with an acoustic waveguide device. Langmuir, 2003, 19, 1304–1311. DOI: 10.1021/la026806p. 34. K. Saha, F. Bender, and E. Gizeli, Comparative study of IgG binding to proteins G and A: Nonequilibrium kinetic and binding constant determination with the acoustic waveguide device. Analytical Chemistry, 2003, 75, 835–842. DOI: 10.1021/ac0204911. 35. F. Bender, N. Bari´e, G. Romoudis, A. Voigt, and M. Rapp, Development of a preconcentration unit for a SAW sensor micro array and its use for indoor air quality monitoring. Sensors and Actuators B-Chemical, 2003, 93, 135–141. DOI: 10.1016/S0925-4005(03)00239-9. 36. M. I. Newton, G. McHale, and F. Martin, Experimental study of love wave devices with thick guiding layers. Sensors and Actuators A-Physical, 2004, 109, 180–185. DOI: 10.1016/j.sna.2003.10.034. 37. B. Jakoby and M. J. Vellekoop, Viscosity sensing using a love-wave device. Sensors and Actuators APhysical, 1998, 68, 275–281. DOI: 10.1016/S09244247(98)00017-X. 38. E. Gizeli, F. Bender, A. Rasmusson, K. Saha, F. Josse, and R. Cernosek, Sensitivity of the acoustic waveguide biosensor to protein binding as a function of the waveguide properties. Biosensors and Bioelectronics, 2004, 18, 1399–1406. DOI: 10.1016/S0956-5663(03)00080-0. 39. F. Herrmann, D. Hahn, and S. B¨uttgenbach, Separate determination of liquid density and viscosity with sagittally corrugated Love-mode sensors. Sensors and Actuators A-Physical, 1999, 78, 99–107. DOI: 10.1016/S09244247(99)00224-1. 40. F. Herrmann, D. Hahn, and S. B¨uttgenbach, Separation of density and viscosity influence on liquid-loaded surface acoustic wave devices. Applied Physics Letters, 1999, 74, 3410–3412. DOI: 10.1063/1.123361. 41. H. Morgan and D. M. Taylor, A surface plasmon resonance immunosensor based on the streptavidin biotin complex. Biosensors and Bioelectronics, 1992, 7, 405–410. DOI: 10.1016/0956-5663(92)85039-D. 42. M. I. Newton, G. McHale, F. Martin, E. Gizeli, and K. A. Melzak, Pulse mode operation of love wave devices for biosensing applications. Analyst, 2001, 126, 2107–2109. DOI: 10.1039/b109259f.
43. J. A. Ogilvy, The mass-loading sensitivity of acoustic love wave biosensors in air. Journal of Physics D-Applied Physics, 1997, 30, 2497–2501. DOI: 10.1088/00223727/30/17/017. 44. J. M. Friedt, L. Francis, G. G. Reekmans, R. De Palma, A. Campitelli, and U. B. Sleytr, Simultaneous surface acoustic wave and surface plasmon resonance measurements: electrodeposition and biological interactions monitoring. Journal of Applied Physics, 2004, 95, 1677–1680. DOI: 10.1063/1.1625420. 45. T. M. A. Gronewold, S. Glass, E. Quandt, and M. Famulok, Monitoring complex formation in the bloodcoagulation cascade using aptamer-coated SAW sensors. Biosensors and Bioelectronics, 2005, 20, 2044–2052. DOI: 10.1016/j.bios.2004.09.007. 46. F. Josse, F. Bender, and R. W. Cernosek, Guided shear horizontal surface acoustic wave sensors for chemical and biochemical detection in liquids. Analytical Chemistry, 2001, 73, 5937–5944. DOI: 10.1021/ac010859e. 47. E. Gizeli, M. Liley, C. R. Lowe, and H. Vogel, Antibody binding to a functionalized supported lipid layer: a direct acoustic immunosensor. Analytical Chemistry, 1997, 69, 4808–4813. DOI: 10.1021/ac970519m. 48. S. Joseph, T. M. A. Gronewold, M. D. Schlensog, C. Olbrich, E. Quandt, M. Famulok, and M. Schirner, Specific targeting of ultrasound contrast agent (USCA) for diagnostic application: an in vitro feasibility study based on SAW biosensor. Biosensors and Bioelectronics, 2005, 20, 1829–1835. DOI: 10.1016/j.bios.2004.07.014. 49. M. D. Schlensog, T. M. A. Gronewold, M. Tewes, M. Famulok, and E. Quandt, A love-wave biosensor using nucleic acids as ligands. Sensors and Actuators B-Chemical, 2004, 101, 308–315. DOI: 10.1016/j.snb.2004.03.015. 50. K. Melzak, E. Ralph, and E. Gizeli, Effect of the surface hydrophilicity on the formation of a membrane-type interface: study using an acoustic wave device. Langmuir, 2001, 17, 1594–1598. DOI: 10.1021/la001443j. 51. C. K. O’Sullivan and G. G. Guilbault, Commercial quartz crystal microbalances - theory and applications. Biosensors and Bioelectronics, 1999, 14, 663–670. DOI: 10.1016/S0956-5663(99)00040-8. 52. O. Tamarin, S. Comeau, C. D´ejous, D. Moynet, D. Rebi`ere, J. Bezian, and J. Pistr´e, Real time device for biosensing: design of a bacteriophage model using love acoustic waves. Biosensors and Bioelectronics, 2003, 18, 755–763. DOI: 10.1016/S0956-5663(03)00022-8. 53. F.-C. Chien and S.-J. Chen, A sensitivity comparison of optical biosensors based on four different surface plasmon resonance modes. Biosensors and Bioelectronics, 2004, 20, 633–642. DOI: 10.1016/j.bios.2004.03.014.
37 Magnetic Acoustic Resonator Sensor (MARS) Bernardita Araya-Kleinsteuber, Adrian C. Stevenson and Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
The successful performance of acoustic sensors has always been related to the ability to attach electrodes or metal films to piezoelectric crystals, together with appropriate wire connections to these metal films. The disadvantage is that the electrical connections to the electrode tend to be fragile, are liable to break, and restrict the device to a single operating frequency. They also have a fundamental incompatibility with aqueous systems due to the electrical components intended for air operation, as well as the unregulated affect of the conductivity and dielectric properties on the electrical crystal resonance.1,2 Consideration of these characteristics has led to several innovations in the configuration and electronics to improve the sensitivity, operating frequency, and the performance of acoustic devices. The resulting magnetic acoustic resonator sensor (MARS) is a new acoustic wave sensor geometry that produces a similar response to the thickness shear mode (TSM) device, but it avoids wiring the electrodes to the crystal surfaces, leading to a simple and versatile acoustic element. In the current MARS device (Figure 1), acoustic generation is achieved in freestanding sensor plates by connecting a planar spiral coil to a radio frequency signal generator, an AM detector, and a lock-in amplifier and positioning it adjacent to the lower surface of the plate. In this way, radial
or linear shear acoustic waves from megahertz to gigahertz frequencies can be induced from the coil’s electromagnetic field via magnetic direct generation (MDG),1–4 magnetostriction,5 or converse piezoelectricity6–8 depending on the material of the substrate element. Here, the current generated in the coil emits a field, which interacts with the acoustic element to produce a driving force and resonance in the plate, which is detected by the coil and passed to the detector. The acoustic element can be made from different materials, so the limited configuration of traditional acoustic sensors can be improved considerably. The advantages of the MARS device over traditional piezoelectric transducer such as the quartz crystal microbalance (QCM) are (i) absence of direct electric contacts to the resonator, (ii) no pressure points, (iii) simplified fluidics, (iv) easy size reduction, (v) choice of a variety of materials, (vi) integration into lab-on-a-chip technology, and (vii) multifrequency operation.
1 WIRELESS ACOUSTIC WAVE GENERATION 1.1
Magnetic Direct Generation
The scientific development of MARS is based on the discovery of the MDG principle by Houck in the 1960s.3
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
FM modulation
In
Out Lock-in amplifier
FM signal generator
Out
In
AM amplifier
Terminals 5 mm
Evanescent wave 10–200 nm (sensing region) Solid–liquid interface AT cut piezoelectric crystal Planar coil (a) Liquid sample
Resonant disc: silica Al underlayer Planar coil
NdFeB magnet (b) Figure 1. Assembled magnetic acoustic resonator sensor configuration, and position of resonant device relative to coil for (a) converse piezoelectric or (b) MDG transduction, respectively.
MDG refers to the process of generating acoustic waves with electromagnetic and magnetic fields at room temperature without physical contact, and results from conduction electrons colliding with a metal lattice. Randall was the first to observe this new coupling mechanism between electromagnetic and acoustic waves,9 but the process was demonstrated experimentally by Houck et al.3 Later, Betjemann,10 Meredith et al.,11 and then Gaerttner et al.12 confirmed the presence of the phenomena at room temperature, including generation in other materials such as semimetals and semiconductors.
One of the first steps undertaken for the development of MARS was to establish a noncontact geometry for biosensing. To optimize electromagnetic-to-acoustic efficiency, spiral coils were used as a starting point: initially, a traveling acoustic wave format was investigated, where input and output transducers made from spiral coils are positioned at either end of an acoustic waveguide. This work demonstrated that noncontact surface acoustic wave (SAW) equivalents, based on MDG, were unlikely to be realized; whereas the QCM equivalent, with the spiral coil positioned beneath a resonant plate, was more successful in
MAGNETIC ACOUSTIC RESONATOR SENSOR (MARS)
offering a substantial improvement in transduction efficiency of 4 orders of magnitude. Nevertheless, for conventional MDG to occur, a metal plate in which the acoustic waves are to be generated, a magnet, and a very intense source of electromagnetic waves, such as a coil connected to an RF pulse generator, are required. A similar response can be obtained with a glass plate covered by a thin metal film. This format has been termed enhanced magnetic direct generation (EMDG).4 The problem with metal substrates, like aluminum elements, is that they are a low-value material for immunologist or biochemists, as they are not the most amenable to chemical modification. Furthermore aluminum expands and contracts with temperature, which is exacerbated by acoustic velocity changes. The solution is a glass element coated with aluminum (250-µm-thick glass plate, 1-µm-thick aluminum layer), so only the glass element remains in contact with the test fluid. Benefits include reduced temperature related drifts, enhanced efficiency and Q factor, and easy chemical modification of the upper surface. Table 1 lists some materials that have been excited with EMDG using the MARS. Many other materials are suitable for EMDG, including silicon,13 which presents significant fabrication advantages. As explained in the Introduction to Acoustic Technologies section, if piezoelectric materials are used as resonant elements, transduction occurs via the converse piezoelectric effect, with similar acoustic resonance behavior to that obtained with EMDG. In summary, electromagnetic-to-acoustic transduction can occur in a variety of electronic materials with either polarizable atomic structures or conductivity sufficient for electron momentum to move the lattice. The most common substrate used in the MARS is single AT-cut quartz disks, and it has already
3
been demonstrated that the MARS system is capable of inducing shear resonances in quartz disk of 0.25-, 0.5-, 1-, and 2-mm thicknesses.14 However, as for TSM sensors, the resonant frequency depends on the thickness of the resonator, and in general, for the MARS device the signal amplitude decreases with thicker disks, thus thinner disks are preferred. Nowadays, the standard device used is of 12-mm diameter and 0.25-mm thickness (Figure 2). 1.1.1 Spiral Coil
The basis of the wireless connection to the quartz crystals is the electric field of the spiral coil antenna (Figure 3). Here, inductive and capacitive electric field components that are perpendicular and parallel to the turn density of the coil4 interact with the lattice via the converse piezoelectric effect, displacing positive and negative charge centers and generating an acoustic wave within the crystal. The driving electric field is located near the surface of the spiral, and between each of its turns, with the field decaying significantly for distances exceeding the turn gap (Figure 3). For a material to be driven effectively by the field, it must be placed in this region, approximately 0.2–2 mm away from the coil. The main characteristic of the coil approach used in the MARS technology is that it allows acoustic generation in crystals without electrodes. Therefore, the crystal is free to vibrate at all its harmonic resonances. The coil consists of a conductive spiral track that circulates from connections at its center and at its outer edge. Two types of coils can be constructed, one made from enameled copper wire wound onto an insulating plate and the other from an etched,
Table 1. Examples of materials excited with enhanced magnetic direct generation (EMDG)
Acoustic shear velocity (m s−1 ) Material Stainless steel Aluminum Silica glass Fused quartz Sapphire Diamond
Plate thickness (mm)
Fundamental frequency (MHz)
MARS
Literature
0.485 0.915 0.503 0.55 0.998 0.2
3.2598 1.7537 3.589 3.454 2.954 31.716
3162 3209 3610 3799 5896 12686
3297 3111 N/A 3764 6163 N/A
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
0.25 mm
12 mm
(a)
(b)
Figure 2. (a) Typical dimensions of a sensing disk and (b) image of actual quartz resonator.
20 1.70 1.60 1.50 1.40 1.30 1.20 1.10 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0
Distance (mm)
10
0
−10
Scale = 103 V m−1
−20
−20
−10
0 Distance (mm)
10
Figure 3. Electric field distribution, proximal to the spiral coil antennae.
20
MAGNETIC ACOUSTIC RESONATOR SENSOR (MARS)
(a)
5
(b)
Figure 4. Spiral coil antennae (a) etched, copper-clad circuit board and (b) wound from enameled copper wire.
copper-clad circuit board (Figure 4). A high turn density is easier to achieve with copper wire, while a printed circuit is far more reproducible. More details of spiral coil construction are given in Refs 1 and 8. The operating distance range of the spiral coil is the most significant limitation, which could be improved with alternate forms. For example, a toroidal form has been used to achieve a 10-cm separation between the coil and the material.15 The acoustic detection is achieved by connecting the spiral coil with a signal generator as a signal source and using an oscilloscope as a detector. The signal generator is set up to drive RF current through a resistance and a spiral coil and capacitor are connected in parallel. To improve signal levels, a differential amplifier can be inserted between the coil and the oscilloscope. A lock-in amplifier stage, following the differential amplifier, can be used to significantly enhance signal recovery. A computercontrolled system, which tunes the signal generator, but maintains a mechanically fixed cable element, is preferred for multifrequency operation. This system works by combining the impedance of a coaxial line and a spiral coil to support multiple matching frequencies.
2 MARS APPLICATIONS
As described before, the sensor plates can be aluminized silica disks, quartz, or any other element
that can interact with the electromagnetic field to produce acoustic waves.2 Resonant shear transverse acoustic waves are generated by this process, so, as for electroded acoustic sensors, the detection mechanism is based on the propagation of these transverse acoustic waves through the plate, according to changes in the characteristics of the propagation path. In this manner, changes in frequency and/or amplitude can be correlated to physicochemical parameters of the contacting sample. This noncontact configuration of the MARS technique offers the additional advantage of operating over multiple harmonic frequencies, from 6 MHz to 1.1 GHz (Figure 5), and thus it is possible to collect new data that other acoustic sensors cannot obtain, since their on-sensor electrodes constrain the frequency to single measurements, over a few overtones of the fundamental. The multifrequency operation in turn offers another key advantage of the√MARS: the control of the evanescent wave, δ = 2η/ρω. 16 This means that increasing operating frequency will vary the thickness of the fluid layer from 200 nm at 6.6 MHz to 10 nm at 1 GHz (Figure 6). This multifrequency characteristic has been considered as the first step toward “acoustic fingerprinting”.6,7,17 This unique ability to focus the acoustic wave down onto the chemical recognition layer through variable-thickness evanescent waves allows bulk fluid events to be excluded, and the analysis to be focused only
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 600
400
Amplitude (mV)
200
0
−200
−400
−600 0
100
200
300
400
500 600 Frequency (MHz)
700
800
900
1000
1100
Figure 5. Multiple frequency shear wave resonance of a single quartz disk.
250
Decay of the acoustic shear wave
6.6 MHz 219 nm 20 MHz 126 nm
200
1.1 GHz 10 nm Pen depth (nm)
AT quartz 150
RF signal 5 mm Planar coil
100
50
0 0
100
200
300
400
500 600 Frequency (MHz)
700
800
900
1000
Figure 6. Penetration depth of the evanescent wave across the frequency range 0–1100 MHz. Calculated from δ = considering water viscosity and density values (ηw = 0.001 kg m−1 s−2 , ρw = 1000 kg m−3 ).
1100
√
2η/ρω,
MAGNETIC ACOUSTIC RESONATOR SENSOR (MARS)
on interfacial processes associated with viscosity, elasticity, and slippage.2,7,17 In general, a decrease in the signal amplitude over 600 MHz is observed (Figure 5); however, the signal-to-noise ratio of the spectral measurements is still in excess of 104 , and thus the reduced amplitude is not related to poor signal recovery.14 This observation is confirmed from Q factor measurements of the device in contact with fluids, because, contrary to what may be expected, the Q factor does not fall with frequency, instead, exceeds 104 at 1 GHz,6,14 which is 10 times higher than conventional TSM resonators at 10 MHz.18 In fact, the fall of signal amplitude at 600 MHz is related to impedance mismatching between the coil and the circuit. As for standard acoustic sensors, any changes in the propagation path of the acoustic wave, due to adsorption of mass to the surface or interaction with viscoelastic fluids, will alter the frequency and amplitude of the resonant peak. For adsorbed mass, the response can, in part, be interpreted using the Sauerbrey model19 that relates the changes in frequency to the extra mass, but it can be reformulated for the multifrequency operation of the MARS sensor in terms of a linear relation: mf f (1) f = MR
7
Where mf /MR is the ratio of the film and resonator mass, and f is the operating frequency. With respect to amplitude, an electroded device has its peak at the fundamental frequency, whereas the coil approach of the MARS configuration has the benefit of accessing 80 harmonic frequencies (Figure 5). In this way, it is possible to extract frequency and amplitude change information from all peaks in the desired frequency range, to evaluate frequency dependent behavior. For example, Figure 7 presents the response for glucose loading at a given harmonic. In the same way, the response for an immunoassay performed on top of the MARS device is given in Figure 8. Comparing these figures, in both there is a clear shift in the resonant frequency, but from this single peak information it is not possible to identify whether the analyte is attached to the surface or only lying on top of it. However, from the multifrequency analysis, it has been shown that protein adsorption leads to a linear relationship between frequency shift and operating frequency (Figure 9) that correlates with the Sauerbrey model.7,8,20 Additionally, when recognition events take place over the device, each analyte, for example, immunoglobulin G (IgG), bovine serum albumin (BSA), anti-IgG, present linearly increasing frequency shifts (Figure 10),20 where clearly, higher harmonics show larger shifts,
200
Amplitude (mV)
100
0 Water −100
Glucose 7% (w/w) Glucose 24.3% (w/w) Glucose 39% (w/w)
−200 231.15
231.17
231.19
231.21
231.23 231.25 Frequency (MHz)
Figure 7. Glucose loading response for a quartz device at 231.2 MHz.
231.27
231.29
231.31
231.33
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS 800 PBS
600
Goat IgG 400 Amplitude (mV)
BSA 200 Antigoat IgG 0 −200 −400 −600 −800 181.23
181.25
181.27
181.29 Frequency (MHz)
181.31
181.33
181.35
Figure 8. Immunoassay response for a quartz device at 181 MHz. Goat IgG concentration 10 µg ml−1 , BSA 1%, antigoat IgG 10 µg ml−1 .
Frequency reduction (kHz)
8
6 R2 = 0.97 4
2
0
0
50
100
150
200 250 Frequency (MHz)
300
350
400
Figure 9. Frequency shift spectrum following IgG exposure of 850 µg ml−1 .
which in turn can be correlated to the amount of mass in the surface. In contrast, for viscoelastic loading, an increase in viscosity reduces the frequency and increases the width of the resonant peak (Figure 7).
However, inspection of the multifrequency spectra, shows that, in general, the shape of the f versus f plot is nonlinear across the frequency range 6–1100 MHz.2,14,17 Unfortunately, there is no comparable data for QCM devices with which
MAGNETIC ACOUSTIC RESONATOR SENSOR (MARS)
9
14
Frequency shift (kHz)
12 10
Goat IgG
8
BSA
6
Antigoat IgG
4 2 0 0
50
100
150
200 250 Frequency (MHz)
300
350
400
Figure 10. Typical frequency shift response for an immunoassay performed on a quartz device. Goat IgG concentration 10 µg ml−1 , BSA 1%, antigoat IgG 10 µg ml−1 . [Reprinted from Araya-Kleinsteuber, B. et al., Magnetic acoustic resonance immunoassay (MARIA): a multifrequency acoustic approach for the non-labelled detection of biomolecular interactions. Journal of Molecular Recognition, 19(4), 379–385, (2006) with permission from Wiley.]
to compare. Nevertheless, while it is possible to fit low-molecular-weight molecules to the Kanazawa model, the fit across frequency is generally poor, with complex patterns that still indicate a consistent trend. This behavior observed for frequency shift can be related to the adsorption process that occurs at the surface in immunoassay experiments. As proteins are adsorbed to the surface, they form a film that moves synchronously with the resonator,
acting as an extension of the disk and, therefore, behaving as expected according to the Sauerbrey model. This is confirmed considering the minor amplitude reduction observed for those types of assays, as a rigidly attached film prevents dissipation. In contrast, for viscoelastic loading, the amplitude reduction is notorious (Figures 7 and 8). Another interesting feature of the multifrequency analysis of the MARS system is that from the dissipation is possible to identify the
% Amplitude change
Frequency (MHz)
Increasing concentration
Figure 11. Typical amplitude change response for viscoelastic loading.
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
viscoelastic relaxation,21 together with two clear regions (Figure 11): at low frequencies the liquid flows in an oscillatory fashion in response to the oscillatory shear strain. All of the driving energy is dissipated in viscous flow of the liquid, and no energy is stored elastically, and the laminar movement leads to increasing dissipation by friction. Basically, the period of the oscillation is much greater than the time between diffusive jumps of the liquid molecules, so liquid flow occurs as a small directional drift superimposed on the random, thermal, molecular motion. When the frequency is increased, the movement of the resonator is too fast and the fluid cannot slide fast enough to move in phase with the surface. Instead, this energy is stored elastically, and the liquid is behaving as an amorphous “solid” with a rigidity modulus comparable to that of a normal crystalline solid. At some intermediate frequency where the period of the applied oscillatory strain is comparable to the diffusive jump time, the liquid will show both viscous and elastic properties. This change from viscous to elastic behavior with increasing frequency is called viscoelastic relaxation, and the identification of this point is easily done with the MARS system. This behavior has been observed for several polyol solutions and protein films, and in general, adsorbed films show a more elastic behavior (relaxation point at higher frequencies) whereas polyols show a much sharper inflection point at low frequencies, corroborating the viscous nature of the solution.14 Finally, the multifrequency approach of the MARS system, provides not only selective access to the events occurring at the solid–liquid interface with the control of the penetration depth of the evanescent wave at the different frequencies, but also offers versatile remote connection, such that the disk can be easily derivatized and placed adjacent to the planar coil for measurement, simplifies acoustic sensor usage,7 and supports miniaturization of the acoustic elements leading to enhanced sensitivity.
REFERENCES 1. A. C. Stevenson and C. R. Lowe, Magnetic-acousticresonator sensors (MARS): a new sensing methodology. Sensors and Actuators A: Physical, 1999, 72(1), 32–37.
2. H. S. Sindi, A. C. Stevenson, and C. R. Lowe, A strategy for chemical sensing based on frequency tunable acoustic devices. Analytical Chemistry, 2001, 73, 1577–1586. 3. J. R. Houck, H. V. Bohm, B. W. Maxfield, and J. W. Wilkins, Direct electromagnetic generation of acoustic waves. Physical Review Letters, 1967, 19(5), 224–227. 4. A. C. Stevenson and C. R. Lowe, Noncontact excitation of high Q acoustic resonances in glass plates. Applied Physics Letters, 1998, 73(4), 447–449. 5. T. D. Lacheisserie, Magnetostriction: Theory and Applications of Magnetoelasticity, CRC Press, Boca Raton, 1993. 6. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Mehta, and C. R. Lowe, Hypersonic evanescent waves generated with a planar spiral coil. The Analyst, 2003, 128(9), 1175–1180. 7. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Mehta, and C. R. Lowe, The application of the acoustic spectrophonometer to biomolecular spectrometry: a step towards acoustic fingerprinting. Journal of Molecular Recognition, 2004, 17(3), 174–179. 8. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Mehta, and C. R. Lowe, Planar coil excitation of multifrequency shear wave transducers. Biosensors and Bioelectronics, 2005, 20(7), 1298–1304. 9. R. H. Randall, F. C. Rose, and C. Zener, Intercrystalline thermal currents as a source of internal friction. Physical Review, 1939, 56(4), 343LP–348. 10. A. G. Betjemann, H. V. Bohm, D. J. Meredith, and E. R. Dobbs, R. F. - ultrasonic wave generation in metals. Physics Letters A, 1967, 25(10), 753–754. 11. D. J. Meredith, R. J. W. Tobin, and E. R. Dobbs, Electromagnetic generation of ultrasound waves in metals. The Journal of the Acoustical Society of America, 1968, 45, 1393–1401. 12. M. R. Gaerttner, W. D. Wallace, and B. W. Maxfield, Experiments relating to the magnetic direct generation of ultrasound in metals. Physical Review, 1969, 184, 702–704. 13. F. Lucklum, P. Hauptmann, and N. Fd. Rooij, Magnetic direct generation of acoustic resonances in silicon membranes. Measurement Science and Technology, 17(4), 719–726. 14. B. Araya-Kleinsteuber, Characterization of the Magnetic Acoustic Resonator Sensor, MPhil Thesis, University of Cambridge, 2004. 15. A. C. Stevenson, A. C. A. Roque, B. ArayaKleinsteuber, E. Kioupritzi, and C. R. Lowe, Wireless excitation of quartz crystals immersed in an aqueous fluid. The Analyst, 2006, 131(1), 474–476. 16. K. K. Kanazawa and J. G. Gordon, The oscillation of a quartz resonator in contact with a liquid. Analytica Chimica Acta, 1985, 175, 99–105. 17. A. C. Stevenson, B. Araya-Kleinsteuber, R. S. Sethi, H. M. Mehta, and C. R. Lowe, The acoustic spectrophonometer: a novel bioanalytical technique based on multifrequency acoustic devices. The Analyst, 2003, 128(10), 1222–1227. 18. H. Sota, H. Yoshimine, R. F. Whittier, M. Gotoh, Y. Shirohara, and Y. Hasegawa, A versatile planar QCM-based sensor design for nonlabeling biomolecule detection. Analytical Chemistry, 2002, 74, 3592–3598. 19. G. Sauerbrey, Use of quartz vibration for weighing thin films on a microbalance/Verwendung von Schwingquarzen
MAGNETIC ACOUSTIC RESONATOR SENSOR (MARS) zur Wagung dunner Schichten und zur Mikrowagung. Zeitschrift Fur Physik, 1959, 155, 206. 20. B. Araya-Kleinsteuber, A. C. A. Roque, E. Kioupritzi, A. C. Stevenson, and C. R. Lowe, Magnetic acoustic resonance immunoassay (MARIA): a multifrequency acoustic
11
approach for the non-labelled detection of biomolecular interactions. Journal of Molecular Recognition, 2006, 19(4), 379–385. DOI:10.1002/jmr.790. 21. A. J. Matheson, Molecular Acoustics, Wiley-Interscience, 1970.
38 Thermal Biosensor and Microbiosensor Techniques Bin Xie and Bengt Danielsson Department of Pure and Applied Biochemistry, Lund University, Lund, Sweden
1 INTRODUCTION
Biosensor technology is experiencing a renaissance because of advancements in microfluidics, microelectronics, and proteomics. Application of these advancements to biosensor technology provides unprecedented possibilities for improvement that far exceeds those of conventional bioanalytical techniques.1–8 The advantages include automated analysis, miniaturization, decentralized bioanalysis, implantation, multianalyte determination, reusable enzyme reactors, multienzyme reactions, minute samples, reduced reagent consumption, and most importantly, it provides a pathway for systems integration, that is, biosensor-on-a chip technology. Systems integration is needed to develop implantable sensing devices, for multianalyte analysis, in the development of decentralized, point of care, instrumentation. Although the biosensors are generally classified by their measurement principles, such as electrochemical, thermometric, photometric, and so on, they share numerous features both with respect to their construction, biorecognition interfaces, and signal conversion processes. The biochemical reactions commonly involve enzymes specific for a specific substrate, and, in general, these bioreactions are exothermic and having rapid turnover rates. The availability of numerous enzymes with well-defined enzymatic specificity, combined with the exothermic
nature of many reactions, makes it possible to develop thermal- or calorimetry-based biosensors for detecting a wide range of biomolecules. In the case of thermal biosensors, these reactions are detected by measuring enthalpy changes. These measurements are then used to prepare calibration curves. The thermal measurement scheme provides unique opportunities for detecting a wide range of biomolecules and serves as an important complement to other biosensor detection schemes. Typically thermal biosensors employ a flow injection analysis scheme using an immobilized enzyme reactor, together with a differential temperature measurement scheme. The configuration usually involves a pair of thermal transducers, such as thermistors or thermopiles, positioned across the enzyme column. This differential measurement system generates a high common-mode-rejection ratio that greatly reduces the effects of ambient temperature fluctuations, allowing the specific measurement of the enzyme catalysis. The thermal signal becomes proportional to the concentration of the substrate. The scheme has a number of advantages over indirect electrical and optical detection schemes. The demand for biosensing technology with ever higher sensitivities, improved reproducibility, and increased dynamic range will continue to drive the development of biosensor technology. Like other types of biosensors, thermal biosensors have also been extensively applied in
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
a variety of areas including clinical analysis,9–13 environmental monitoring and control,14,15 bioprocess monitoring,16,17 biochemical studies,18–21 and organic solvent reactions.22,23 Currently thermal biosensors are constructed in a wide range of formats and sizes using a number of fabrication technologies that make the technology easily accessible. These features and properties are described in detail in the following sections.
(Cp ) of the system. This includes the heat capacity of the solvent that is defined by: Q = Cp (T ) The change in temperature recorded by the thermal biosensors (T ) is directly proportional to the enthalpy change. This value is inversely proportional to the heat capacity of the reaction, as defined by: T =
2 PRINCIPLES AND FEATURES OF THERMAL BIOSENSORS
−(np H ) Cp
Enzymes are the most common and extensively used biorecognition elements in biosensors. The ease with which enzymes can be immobilized and their ability to cycle coenzymes or substrates makes them ideally suited for thermal measurements using recycling systems. Furthermore, the high substrate specificity that enzymes, particularly oxidases, exhibit makes them especially well suited for bioanalytical determinations, where samples often contain a variety of structurally related compounds. In addition, expanding interest in biodiversity will most certainly lead to the identification of numerous enzymes with both new and variable substrate specificities that will spur the development of a never-ending cascade of new biosensors.
The enthalpy changes for enzymatic catalysis is around −10 to −200 kJ mol−1 (see Table 1), which is adequate for determination of the substrate concentrations at clinically interesting levels for a range of metabolites. A partial list of enzymes, their target metabolites and molar enthalpies is shown in Table 1. Thermometric detection is especially advantageous when multiple reactions are involved, since it is the sum of all the reaction enthalpies that determines the sensitivity of the assay. Thus, in the case of oxidases, it is advantageous to co-immobilize catalase, which consumes the hydrogen peroxide produced in oxidase reaction. The highly exothermic reaction doubles the sensitivity and reduces the deleterious effects that hydrogen peroxide has on enzyme activity. Furthermore, it reduces oxygen consumption thereby increasing the linear range of the oxidase reaction. As seen in Table 1, the high protonation enthalpy of a buffer, like Tris, can also be utilized
2.2
Table 1. Molar enthalpy changes for some enzyme-catalyzed reactions
2.1
Specificity of Enzymatic Catalysis
Universal Enthalpy Determination of Biochemical Reactions
The evolution of heat is a general property accompanying biochemical transformations. The total heat evolution is proportional to the molar enthalpy change and to the total number of moles of product molecules created in the reaction: Q = −np (H ) where Q is the total heat, np is the number of moles of product, and H is the molar enthalpy change. It is also dependent on the heat capacity
Enzyme
Substrate
Catalase Cholesterol oxidase Glucose oxidase Hexokinase LDH NADH dehydrogenase β-Lactamase Trypsin
Hydrogen peroxide Cholesterol Glucose Glucose Sodium pyruvate NADH Penicillin G BenzoylL-arginineamide Urea (phosphate buffer, pH 7.5) Urate
Urease Uricase
LDH: lactate dehydrogenase. (a) In Tris buffer.
−H (kJ mol−1 ) 100 53 80 28 (75)(a) 62 225 67 (115)(a) 29 61 49
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
to enhance the total enthalpy of proton-producing reactions. An inherent disadvantage of calorimetry is the lack of specificity. All enthalpy changes in the reaction mixture contribute to the final measurement. It is therefore essential to avoid nonspecific enthalpy changes due to dilution or solvation effects. In most cases, these effects can be minimized by judiciously diluting the sample. This requires the development of sample specific procedures, which reduces the utility of the technique. In order to overcome this limitation a “blank” reference column has been incorporated, thus allowing differential determinations to be made. This eliminates these types of nonspecific thermal effects, which reduces problems associated with platform migration as well as improving assay sensitivity and reproducibility. Generally, however, the nonspecific effects do not present such large practical problems that a reference column has to be employed.
2.3
Flexible Control of Flow Injection Analysis
Thermometric detection usually employs a differential measurement scheme of temperature across the enzyme reactor in order to increase the common-mode-rejection ratio. As a result, thermal biosensors typically use flow injection-based analysis. In addition, control of the carrier solutions and samples is straightforward using this continuous analysis scheme. Furthermore, flow injection analysis has particular added value when dealing with microliter-sized samples in thermal bioanalysis since dispersion of the sample during the transportation process leads to dilution of the sample solution, which results in an extension of the linear detection range in oxidase catalyzed reactions, such as glucose. This is presumably due to the fact that the immobilized enzyme never reaches catalytic saturation levels.
2.4
Transducer-sample Isolation
One of the main advantages that thermal detection has over the other detection methods is the possibility of isolating the thermal transducers from
3
the sample solution. This is achieved by placing the transducers outside the enzyme reactors or columns. This unique sensing scheme is particularly advantageous when analyzing “real” samples, such as whole blood. However, the isolation and heat transduction results in reduced efficiency. In order to compensate for these limitations, the thermistors are mounted on gold tubing using heatconductive glue. These are positioned in close proximity to the inlet (reference) and outlet (measurement) of the enzyme column. The integrated thermistors or thermopiles used on lab-on-a-chip designs are embedded in a wafer containing micro flow channels with an insulating dielectric layer predominantly consisting of silicon dioxide or silicon nitride. This submicron-thick layer maximizes heat transfer while protecting the transducer from the sample.
3 THERMAL TRANSDUCERS
According to the working principle, most thermal transducers can be divided into thermomechanical, thermoresistive, thermocouple, junction-based, acoustic, and quartz-resonant sensing devices. However, the most commonly employed transducers in the thermal biosensor studies are thermistors and thermocouples, or thermopiles. 3.1
Thermistors
Thermistors are a type of resistor that detects resistance changes as a function of the ambient temperature. Thermistors detect temperature fluctuations by measuring changes in the resistance of metal oxides. There are two types of thermistors, positive (PTC) and negative (NTC) thermistors. The resistance of PTC thermistors increases as the temperature increases, while the resistance of NTC thermistors decreases as the temperature increases. By altering the composition of the metal oxide and the manufacturing parameters, thermistors with a variety of resistances and in a wide range of sizes (down to 0.1–0.3-mm beads) can be made. The most accurate empirical expression describing the resistance-temperature relationship of thermistors is the Steinhart–Hart equation: 1 = A + B(ln R) + C(ln R)3 T
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
where T is the temperature (K); ln R is the natural logarithm of the resistance; and A, B, and C are derived coefficients. For narrow temperature ranges the above relationship can be approximated by the equation: RT = RTo eβ(1/T −1/To ) where RT and RTo are the zero-power resistances at the absolute temperatures T and To , respectively, and β is a material constant that ranges between 4000 and 5000 K for most thermistor materials. The typical temperature coefficient of a metal oxide-based thermistor (NTC) is between −3.3 and −4.9% per ◦ C at 25 ◦ C. This is more than 10 times the sensitivity of a platinum resistance thermometer of the same nominal resistance. When compared with the metal oxide-based thermistors, thin-film thermistors generally have lower temperature coefficients. For example, metal oxide-based amorphous germanium thermistors have a sensitivity of −2% per ◦ C, while thinfilm polysilicon thermistors have a sensitivity of 0.34% per ◦ C. Despite this, there is an increasing interest in thin-film thermistors because the production processes are compatible with standard microelectronics manufacturing. This greatly simplifies the integration of chip-based biosensors at the manufacturing level. In an effort to improve the sensitivity of polysilicon thermistors, we have optimized our system design and have been able to improve the sensitivity of polysilicon thermistors to −1.7% per ◦ C at 25 ◦ C.24
of a pair of dissimilar metals, A and B, and whose two junctions are held at different temperatures, is directly proportional to the difference of the hot and cold junction temperatures, Kh − Kc . The SAB term is the Seebeck coefficient. Because this coefficient does not depend in any way on the distribution of temperature along the metals between the junctions, it provides a very accurate way of the detection. A thermocouple made from dissimilar metals can generate a voltage output from a few microvolts per kelvin to hundreds of microvolts per kelvin. Serially connected thermocouples, called thermopiles, make it possible to amplify thermal signals. The voltage generated over a thermopile is proportional to the number of thermocouples in the thermopile. Thus if a thermopile consists of 100 thermocouples, the potential output is 100 times as much as the single thermocouple. The hot junction of a thermopile is normally used as the measurement point while the cold junction is used as the reference (which is kept at a constant temperature). In addition, the thermopile bears a high commonmode-rejection ratio to the ambient temperature fluctuation as compared with the thermistors. This eliminates the need for complicated thermal insulation as is required for thermistor-based systems. Moreover, the continuous advancements in microfabrication technology have made it possible to increase the sensitivity of thermocouples at ever lower production costs.
3.3 3.2
Thermopiles
Thermocouples use the Seebeck effect to detect temperature changes. This effect is based on the fact that when two dissimilar metals are joined together, a predictable voltage will be generated over the junction. Temperature variations are detected by measuring the differential temperatures between the measurement junction and the reference junction. The relationship can be described as: dV = SAB · (Kh − Kc ) The voltage difference, dV , that is produced across the terminals of an open circuit made up
Diodes
Another type of thermal transducers is the diode, which is based on the fact that the forward voltage drop across the diode is temperature dependent. This temperature dependence follows from the Schottky ideal diode equation given below. The thermal voltage VT is approximately 26 mV at room temperature (approximately 25 ◦ C or 298 K) and is a known constant. It is defined by: VT =
kT q
where q is the charge on an electron (the elementary charge), k is Boltzmann’s constant, T is the absolute temperature of the p-n junction.
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
4 THE CONVENTIONAL THERMAL BIOSENSOR – ENZYME THERMISTOR 4.1
Original Concept
The enzyme thermistor (ET) instrument used in many of the studies cited herein has been previously described by Danielsson.25 In brief, it consists of a thermostated thick-walled aluminum jacket, 80 mm in diameter and 250 mm in length. This unit is contained in a cylindrical aluminum heat sink with heat exchangers with two column positions (Figure 1). The two positions can either be fitted with two different enzyme columns, for two different assays or with one assay column and use the other column as a reference, that is, split flow. The columns are connected proximally to the thermistor probes and are easily exchanged. The thermistors are connected to a Wheatstone bridge with a maximum sensitivity of 100 mV (m ◦ C)−1 . Commonly used full-scale sensitivities are in the 10–50 m ◦ C range. This permits determinations in the 0.01–100 mM range for most
reactions (Table 2). A large excess of enzyme (10–100 units for a 1-ml column) is bound to a mechanically stable, highly porous support, such as controlled pore glass (CPG) or Eupergit C. The enzymes and supports show excellent long-term operational stability. A suitable flow rate for flow injection analysis is 0.5–2 ml min−1 with a sample volume of 0.1–1 ml or smaller. Using these sample volumes, a thermal steady state is not achieved. However, numerous studies have shown that the temperature peaks result in linear standard curves indicating that the thermal signal is proportional to the substrate concentration.
4.2
Semicommercial Products
A number of instruments of this type have been built at our institute. Prototypes of the instrument have been made available to various laboratories around the world on an “at cost” basis (Figure 2). The universal nature of the detection scheme
Wheatstone bridge amplifier
ET
Pump
Sample valve
Aluminum cylinder
Heat exchangers Buffer
Figure 1. Schematic of an enzyme thermistor.
5
Thermistors Enzyme columns
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Table 2. Linear concentration ranges of substances measured by thermometric biosensors with immobilized enzymes
Analyte
Enzymes
Linear range (mM)
Ascorbic acid ATP (or ADP) Cellobiose Cephalosporins Creatinine Ethanol Glucose Glucose L-Lactate L-Lactate L-Lactate (or pyruvate) Oxalate Penicillin
Ascorbate oxidase Pyruvate kinase + hexokinase ß-Glucosidase + glucose + oxidase/catalase Cephalosporinase (ß-lactamase) Creatinine iminohydrolase Alcohol oxidase Hexokinase Glucose oxidase/catalase Lactate-2-monooxygenase Lactate oxidase/catalase Lactate oxidase/catalase + LDH Oxalate oxidase ß-Lactamase Penicillin acylase Invertase Urease
0.01–0.6 10 nM(a) 0.05–5 0.005–10 0.01–10 0.0005–1 0.01–25 0.0002–1 (75(b) ) 0.0005–2 0.002–1 10 nM(a) 0.005–0.5 0.005–200 0.02–200 0.05–100 0.005–200
Sucrose Urea (a) (b)
With substrate recycling. With benzoquinone as electron acceptor.
enzyme reactions, and automatic baseline compensation. The data is collected and analyzed using information management software. However, at present, the systems are not commercially available, despite considerable efforts to commercialize the technology.
5 MINIATURIZED BIOSENSORS
Figure 2. Integrated dual-channel enzyme thermistor system.
makes the technology particularly appealing for both industrial and clinical applications. Currently, computer assisted control and monitoring of the performance for up to 10 different data parameters has been achieved using lab-view-based software. The parameters include: pump flow rates, sample valve switching, simultaneous thermal signals analysis of the various
During the last few years miniaturization of biosensors has accelerated as a result of developments in injection molding, micromachining, and semiconductor technologies. Miniaturized thermal biosensors have increased the potential of this technology, particularly in the areas of clinical biochemical analysis, decentralized health care and bioprocess control. The synergy between miniaturization and systems integration has made it possible to develop thermal biosensor arrays. The advantages of this approach include simple, stable, and reliable detection, as well as the ability to analyze multiple analytes simultaneously.
5.1
Portable Systems
In order to test the feasibility, a miniaturized device 50 mm in length and 20 mm in diameter was designed and constructed (Figure 3). The enzyme
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES Adiabatic layer
Enzyme column
Bead thermistors
Aluminum cylinder
Inlet and outlet gold tubings
Figure 3. A schematic diagram of the miniaturized flow injection thermal biosensor. Arrows indicate the flow direction.
column itself was constructed out of stainless steel tubing. Microbead thermistors were mounted at the inlet and outlet ports. The other components are labeled appropriately. The enzyme column is 1.5/1.7 mm (ID/OD) and 15 mm in length. The highly insulated column, combined with accurate flow rates, provides excellent operational stability. While the small column dimensions reduce buffer and sample consumption. These portable devices are suitable for home monitoring of glucose in diabetes. In order to allow direct analysis using whole-blood samples three different approaches have been tested. Whole blood is a particularly difficult sample because of the viscosity and the presence of cells, both of which lead to clogging and high backgrounds in many systems. In the first series of studies a superporous agarose support material (developed at our department) was used for immobilization of glucose oxidase and catalase. The superporous agarose has pores large enough to allow cells to pass freely through them. After injection of numerous whole-blood samples, the enzyme column did not show any sign of clogging. The calibration curve obtained using 20-µl samples injected in a flow of 100 µl min−1 was linear up to 25 mM glucose. These whole-blood samples were diluted 10-fold prior to injection.11 Thus the actual amount of whole blood needed was only 2 µl. The second approach used a minicolumn (0.6 × 10 mm) containing spherical 125–175 µm CPGparticles as the support material for glucose oxidase/catalase immobilization. This support material provides spaces between the particles that are large enough to allow the cells to pass through without being trapped. A blood sample volume of as little as 1 µl was adequate to make glucose determinations in the 1–25 mM range. The
7
system was used to make over 100 blood sample determinations without showing any deterioration in performance.9 Using this device, assays were also developed for urea (0.2–50 mM) and lactate (0.2–14 mM) using 1µl blood samples.10 In a third approach, the blood cells are removed by dialysis or filtration using small coaxial dialysis units constructed by attaching a 25 mm-long, 0.2-mm (ID) cuprophan (cellulose) hollow fiber inside 0.5-mm PVC tubing. These devices resulted in about a 5% glucose yield (as compared to the original sample) and had a linear range of up to 25 mM glucose using a 1.5 × 15-mm glucose oxidase/catalase column. This range is adequate for diabetes monitoring. Alternatively, it is possible to use a commercially available microdialysis probe (CMA/Microdialysis, Stockholm, Sweden). This probe consists of a thin needle (0.6-mm diameter) surrounded by dialysis tubing (4–30-mm long), which can be inserted in a vein or under the skin. Low-molecular-weight compounds are transported to the sample valve of the analytical device by a slow buffer stream (typically <5 µl min−1 ). Using the device, a linear range for glucose between 1–25 mM was obtained. These studies showed that the scheme provided a reliable method for ex vivo monitoring of glucose.12
5.2
Microfabricated Systems
Integration of the microfluidic reactor with thermal transducers, such as thin-film thermistors and thermopiles fabricated on quartz chips, has been studied using various sensing formats. These formats include one pair of thermistor sensors for determining one analyte, an array of thermistor sensors for multianalyte determination, and a combination of thermistors and thermopiles on the same chip. The combined format was developed to compare the thermal signal generation between the two types of transducers. The sensing devices were manufactured on 525-µm-thick quartz wafers on which a layer of polysilicon had been deposited for fabrication of the thermistors. Boron was ionimplanted into the polysilicon layer in doses of 5 × 1014 cm−2 , 5 × 1013 cm−2 , and 2 × 1013 cm−2 in order to achieve resistivity values of 0.1, 100, and 1000 cm, respectively. A 1-µm oxide layer (low-temperature oxide) was then deposited by low-pressure chemical vapor deposition (LPCVD)
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
as passivation over the thermistors. Finally, the polyimide distance layer, which defines the horizontal slit of the bead filter, was deposited by spin-coating, and finally lithographically patterned. The polyimide thickness was targeted to about 8 µm. A similar process was used for the fabrication of the integrated thermopiles. The thin-film thermal transducer-based devices (thermistors or thermopiles) were composed of a transducer chip, a spacer, and electrical and liquid flow connections. The transducers were electrically insulated from the microfluidic stream in order to eliminate direct electrical contact between the solution and the transducers. Well-matched thin-film thermistors or cold and hot junctions of the thermopile were placed along the enzyme channel to differentially detect the temperature changes resulting from the enzyme reactions. The measurement thermistor or hot junction was placed downstream from the enzyme regions, while the reference thermistor or cold junction was placed upstream. The optimal positioning of the transducers was determined empirically. Integrated thermal biosensor systems have been applied to study immobilization, enzymatic reactions, and microfluidics. In brief, the microfluidic channel for the flow injection control and the enzyme reaction channel were microfabricated on silicon chip, in proximity to the bead thermistors (Figure 4).26 In this device, the flow and enzyme reaction chambers consisted of 33 parallel V-shaped microfluidic channels, 50 µm in depth. This increases the surface area of the enzyme reactor, which allows more of Enzyme reactor with multiple microfluidic channels
Bead thermistors
Silicon chip
Inlet and outlet gold tubings
Figure 4. A microfluidic thermal biosensor fabricated on a silicon chip. [Reprinted from Xie et al.26 , with permission from Elsevier.]
the enzyme to be immobilized. These channels were fabricated on the surface of a silicon chip using anisotropic etching techniques. The bead thermistors were mounted outside the inlet and outlet. The system showed a significant increase in signal when tested with the penicillin/penicillinase assay. The integration of this microfluidic system with multiple thin-film thermistors for multianalyte determinations is described in Section 5.3. A microbiosensor based on an integrated thermopile has been designed and fabricated on a quartz chip.27 The thermopile, which was manufactured in polysilicon together with aluminum, provided a potential output of ca 2 mV K−1 . A silicone rubber membrane was used to form and seal the microchannel. The system was used to perform glucose determinations.27 In these studies, the enzyme reactor chamber was 20 µl, and 1-µl sample volumes were used. A linear range of 2–25 mM glucose was obtained at a flow rate of 105 µl min−1 . The relative standard deviation (RSD) for 100 glucose samples (10 mM) was 5%.
5.3
Thermal Biosensor Arrays
An area of ever-increasing demand in clinical diagnosis is the simultaneous determination of multiple analytes extending to personal health care, bioprocess control, and sequential enzyme reactions. It is essential in a personal health care system, as the information from multiple metabolites improves the reliability of the clinical diagnosis. Serious efforts are being made toward a multianalyte biosensor. Many of these employ multichannel or split-flow systems and combination with electrochemical detection is also possible.28,29 A prerequisite of the multichannel scheme is avoiding interference from previous reactions. Uniform flow rates in these systems are important. In applications involving electrochemical and optical detection, the system must be suitably controlled in order to minimize the interferences.30,31 In addition, the specificity is dependent on the applied potential or the wavelength. The number of analytes being measured governs the detection conditions. Recently, development of thermal biosensors for simultaneous multianalyte determination in a sample mixture has been demonstrated using an integrated thin-film thermistor array in a single
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
9
Responses
Microchannel
Spacer
Flow direction
Quartz
Thermistor array
Glucose oxidase
Lactate oxidase
Urease
Figure 5. Schematic diagram of the flow injection thermal biosensor array for simultaneous determination of lactate, glucose, and urea.
flow channel (Figure 5). The technique relies on the specificity of the enzyme catalysis and the universality of thermal detection. Here, a single microchannel column is serially partitioned into several discrete detection regions. Each region has one enzyme preparation corresponding to the specific analyte and a pair of film thermistors. One of them is placed after, and one before the enzyme matrix. On injection of a substrate mixture, multiple thermal signals generated are detected simultaneously. A unique advantage of this design is that all determinations are performed under essentially identical conditions. In addition, application of micromachining and IC technologies is of benefit for the manufacture of uniform and cheap thermal transducers with flexible shape, size, resistance, as well as delicate microstructure on the chips. The good chemical insulation of the transducers from the flow stream eliminates interference from the reactants on the transducers, and the intrinsic stability of the transducers obliterates the need for frequent recalibration of the sensors. In order to simultaneously determine several analytes, such as glucose, lactate, and urea, the enzyme regions were in series charged with glucose oxidase, lactate oxidase, and urease, which were individually immobilized on N -hydroxy succinimide (NHS)-activated agarose beads (13 µm in diameter). The regions between the adjacent two enzymes were charged with similar beads without any enzymes in order to damp the thermal carryover downstream of the reactive enzymes. However, because of the differential measurement
scheme, the carryover effect will be minimized. The feasibility of the system for simultaneous multianalyte determination has been exemplified by glucose and urea or penicillin and urea measurement with a linear range of up to 20 mM for urea, 8 mM for glucose, and 40 mM for penicillin.24 Determinations of three analytes (glucose, urea, and penicillin) and four different analytes (glucose, lactate, urea, and penicillin) in sample mixtures were also demonstrated using similar thermal biosensor arrays.32,33
6 HYBRID BIOSENSORS 6.1
Extension of Thermal Glucose Linear Range with Electrochemical Regeneration
Another field under current investigation is hybrid sensors, which combine two different measurement technologies into a hybrid (Figure 6). Conventional biosensors are usually classified into categories, such as electrochemical, optical, and thermal sensors according to the detection principle. Each type of sensor has its own merits and drawbacks. Creating hybrid biosensors by combining different detection principles could possibly retain the original advantages and avoid the disadvantages of the respective type of sensor. Furthermore, hybridization of biosensors could also create unique properties.
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Glucose
GODox
2Fe(cp)
GODred
2Fe(cp)+
Pt column
∆q Gluconolactone
2e−
Figure 6. Hybrid biosensor principle: a combination of two sensing principles of thermal and electrochemical measurement.
One example of a hybrid biosensor was fabricated and demonstrated by Xie and coworkers (Figure 7).34 This biosensor combined electrochemical regeneration of an electron mediator, such as ferrocene, with flow injection biocalorimetry. The enzyme column that was constructed of electrically conducting materials—platinum and reticulated vitreous carbon (RVC)—functioned as working electrode and enzyme catalytic reactor, and together with a thermistor as a thermally sensitive element. RVC was used as a support onto which the enzymes and electron mediators (ferrocene) were immobilized/adsorbed and packed into a platinum column. The column and a platinum counterelectrode were connected to a simple potentiostat to carry out the electrochemical regeneration of the mediators. Simultaneously, the temperature changes in association with the enzyme reactions were differentially detected by a pair of thermistors which were mounted at the inlet and outlet of the column, respectively. This bioelectrochemical-calorimetric device was tested for glucose determination using glucose oxidase with ferrocene as mediator. This sensor was less susceptible to interferences than a conventional Reference thermistor
Filter
electrochemical device and the linear range was independent of the oxygen concentration in contrast to a normal thermal biosensor, which is limited by the oxygen concentration in buffer.
6.2
Thermal Signal Amplification by Electrochemical Recycling
In a following study a hybrid biosensor was constructed based on tyrosinase-catalyzed catechol reactions (Figure 8).35 Catechol was electrochemically regenerated from 1,2-benzoquinone, which was produced by oxidation of catechol by tyrosinase. The current and temperature changes in relation to the reactions were simultaneously detected. The results indicated that by using electrocatalytic recycling the thermal signal could be improved in sensitivity and linear range. The thermal signal, on the other hand, could be used as a reference for the electrical signal, for example for the calculation of the recycling factor, provided there is no contribution to the temperature signal from the electrochemical catalysis. In our experiment we could not demonstrate any significant difference
Crushed Pt column RVC
Measurement thermistor
Inlet Outlet V
Silicone tubing Pt wire
Gold tubing Pt wire
5 mm Figure 7. A schematic diagram of a ferrocene-mediated hybrid glucose biosensor.
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
11
∆I A
Platinum working electrode ∆T
Reference thermistor Catechol
Analyte
e−
O2
Measurement thermistor
Tyrosinase Benzoquinone H2O +∆q
Product
Reference electrode Electrically conductive RVC matrix coated with polypyrrole and tyrosinase
Figure 8. A dual-signal hybrid biosensor for simultaneous thermal and electrical determination of tyrosinase-catalyzed reaction. [Reproduced from Kiba et al.36 Copyright 1984, with permission from Elsevier.]
between the thermal signals obtained with and without applying the electrochemical catalysis.
7 APPLICATIONS 7.1
Determination of Metabolites
A large number of thermistor-based biosensor assays using immobilized enzyme reactors have been proposed for use in biotechnology, clinical chemistry, and food analysis (Table 1). In the following examples, the concentration ranges given have in general been obtained with 0.5-ml samples at a flow rate of 1 ml min−1 . The sensitivity can be adapted to higher concentrations by dilution and use of smaller sample volumes. Oxidases generally offer higher sensitivity than dehydrogenases because of higher heat of reaction (−H = 75–100 kJ mol−1 ) and have no extra cofactor requirement. Co-immobilization of oxidases with catalase has three additive effects: doubling the total reaction heat by adding the enthalpy change of the catalase reaction (−100 kJ mol−1 ), removal of the hydrogen peroxide formed in the oxidase reaction avoiding protein damage by the hydrogen peroxide, and 50% improvement of the use of the oxygen available which extends the linear range to about 1 mM. The low solubility of oxygen in aqueous solutions is a serious drawback for use of oxidases. A solution
to this problem, although not ideal, is to use an electron acceptor with higher solubility, such as benzoquinone.36 Hydrolytic enzymes, such as disaccharidases, are usually associated with low enthalpy changes and have to be supplemented with secondary enzymes for practically useful assays. Cellobiose, for instance, can be determined with β-glucosidase in combination with glucose oxidase and catalase. Another common way to increase the sensitivity of calorimetric measurements is to use buffers with high protonation enthalpy (such as Tris buffer), if a proteolytic reaction is connected with the enzymic reaction. Substrate and coenzyme recycling is another way to increase the sensitivity, in favorable cases up to several 1000-fold. As an example 5000-fold amplification was observed using co-immobilized lactate oxidase (oxidizing lactate to pyruvate), LDH (reducing pyruvate to lactate), and catalase.37 Lactate (or pyruvate) concentrations as low as 10 nM could be determined with this arrangement. Similar sensitivities for ATP (alternatively ADP) were obtained with the enzyme couple pyruvate kinase and hexokinase.38 Highly sensitive detection of ATP/ADP, the same as with bioluminescence, can be accomplished by coupling the two cycles so that the pyruvate formed in the pyruvate kinase/hexokinase is recycled in the LDH/LOD cycle.39 The practicality of this approach is unfortunately limited since it is directly influenced by the actual activity of
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
all enzymes involved. This is in contrast with direct assays using immobilized enzyme reactors where the sensitivity is virtually unchanged as long as there is excess enzyme activity. The enzymes involved in the LDH/LOD system are, however, stable enough to make it practically useful, for instance as detecting mechanism in enzyme immunoassays. The most common enzyme support in our work has been propylamino-derivatized CPG (from Corning) with a pore size in the range of 50–200 nm and a particle size up to 80 mesh (0.18 mm), loaded with a large excess of enzyme, often 100 units or more, immobilized with glutardialdehyde.14 In more recent work, we have been using a spherical CPG from Schuller GmbH (Steinach, Germany) with a particle size in the range of 125–140 µm and a pore size of 50 nm. In contrast to crushed CPG, this beaded support material produces enzyme columns with remarkable resistance to clogging by particles in the sample. Even whole-blood samples can be used.9 CPG offers high binding capacity, good mechanical, chemical as well as microbial stability, and relatively simple coupling procedures, but Eupergit C (oxirane acrylic beads from R¨ohm Pharma, Weiterstadt, Germany) and VA-Epoxy Biosynth (Riedel-de Ha¨en, Seelze, Germany) are good alternative support materials. The major limiting factor for column life is usually mechanical obstruction. If, however, the solutions used, as well as the samples, are filtered through at least a 1–5-µm filter and if microbial growth in the solutions and the flow lines is prevented, good operational stability with unchanged performance for large series of samples (thousands) can be obtained and the column may be functional for several months. Alcohols can be measured with alcohol oxidase (EC 1.1.3.13) from Candida boidinii or Pichia pastoris. The latter enzyme has higher specific activity and a somewhat different substrate specificity. Co-immobilization with catalase increases the stability of the enzyme column to several months with an operating range of 0.005–1 mM (0.5-ml samples) using 0.1 M sodium phosphate, pH 7.0, as buffer. This assay is useful for the determination of ethanol in samples from beverages and blood and for the monitoring of fermentations.40
7.1.1 Cellobiose
As already mentioned, the heat produced by the hydrolysis of cellobiose with β-glucosidase is too low to give sufficient sensitivity. By measuring the glucose formed in a precolumn containing β-glucosidase with a glucose oxidase/catalaseloaded ET a typical operating range of about 0.05–5 mM can be obtained.41 7.1.2 Cholesterol and Cholesterol Esters
Cholesterol has been determined in 0.16 M phosphate buffer, pH 6.5, containing 12% (v/v) ethanol and 8% (v/v) Triton X-100 using cholesterol oxidase (EC 1.1.3.6) from Nocardia erythropolis. Cholesterol esters can be measured by including a precolumn with cholesterol esterase (EC 3.1.1.13). The measuring ranges are adequate for clinical use.42 7.1.3 Glucose
This is one of the most-used assays based on calorimetry for various bioanalytical applications. It is usually carried out with glucose oxidase co-immobilized with catalase as mentioned above.14 This procedure provides high sensitivity and specificity, it has no cofactor requirement and the enzyme columns are very stable. Alternatively, the enzyme hexokinase can be used.43 The enzyme, however, requires the cofactor ATP, but a linear range of up to 25 mM can be obtained. Hexokinase can also be used in an indirect assay for ATP, if the sample solution contains an excess of glucose. Micromolar sensitivity can be obtained by this technique. In an analogous way NADH can be measured with the same sensitivity using an LDH column and excess of pyruvate. 7.1.4
L-Lactate
L-Lactate can be determined down to micromolar concentrations with two different enzyme systems: the lactate-2-monooxygenase (EC 1.13.12.4) from Mycobacterium smegmatis and the lactate oxidase from Pediococcus pseudomonas (EC 1.1.3.2) together with catalase.14 The latter enzyme is currently preferred because of lower price, but the
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
monooxygenase could be interesting for removal and simultaneous determination of lactate in combination with the previously described recycling arrangement for lactate/pyruvate.37 Since the end product of the monooxygenase reaction is acetate and not pyruvate, both metabolites could be determined in the same sample. 7.1.5 Oxalate
Oxalate was measured with oxalate oxidase (EC 1.2.3.4) from barley seedlings. A linear concentration range of 0.005–0.5 mM was observed in 0.1 M sodium citrate buffer, pH 3.5, containing 2 mM EDTA and 0.8 mM 8-hydroxyquinoline.37 The assay was found to be suitable for the determination of oxalate in urine, beverages, and food samples. Urine samples had to be diluted 10-fold and passed through a C18-cartridge to remove interfering substances. 7.1.6 Penicillins
The procedures designed for the assay of ß-lactams (for instance penicillin G and V) using ß-lactamases, such as penicillinase type I from Bacillus cereus (EC 3.5.2.6) have been particularly successful.44 The useful linear range is about 0.005–200 mM. Several industrial applications have been developed using both discrete samples and continuous monitoring on pilot-plant and production-scale fermentors. Alternatively, the more specific penicillin amidase (EC 3.5.1.11) can be used, especially in fermentation broths.16 The sensitivity is, however, lower although sufficient for process monitoring. In both cases the enzyme columns are very stable and can be used for several months or for thousands of samples provided they are sterile and filtered.
7.1.7 Sucrose
In contrast to most other disaccharide-splitting enzymes, invertase (EC 3.2.1.26) produces enough heat to allow direct determinations of sucrose in the range of 0.05–100 mM.45 An important advantage of this procedure, compared to other biosensor assays, is that it is not disturbed by
13
the presence of glucose. Invertase columns are extremely stable and useful in food and bioprocess analysis.
7.1.8 Triglycerides
Practical routine methods for the determination of all the main blood lipid classes, cholesterol and cholesterol esters, phospholipids, and triglycerides using thermistor-based biosensors have been proposed.42 Thus, triglycerides have been determined with lipoprotein lipase (EC 3.1.1.34) immo˚ The bilized on CPG with a pore size of 2000 A. assay buffer was 0.1 M Tris buffer, pH 8.0, containing 0.5% Triton X-100. The linear response was 0.05–10 mM for tributyrin and 0.1–5 mM for triolein.46 7.1.9 Urea
Urease gives a linear range of at least 0.01–200 mM and offers a clinically useful assay that is independent of the ammonium concentration in the sample.43 Urease is very sensitive to inhibition by heavy metals, a fact that has been exploited in the design of a reversible procedure for heavy-metal determination. Addition of 1 mM EDTA and 1 mM reduced glutathione to the buffer, on the other hand, protects the urease, leading to a very stable enzyme column. Acid urease from Lactobacillus fermentum has lower pH optimum and somewhat different properties than Jack bean urease and has been studied in reactors capable of removing urea from alcoholic beverages. This has attracted some interest, especially in Japan, since urea and ethanol upon standing or heating form ethylcarbamate, a carcinogenic compound. In this context, acid urease has been shown suitable for urea determination.47 Other metabolites that have been measured with thermistor-based biosensors include ascorbic acid, cephalosporins, creatinine, galactose, hydrogen peroxide, lactose, malate, phospholipids, uric acid, xanthine, and hypoxanthine. The lifetime of an enzyme column depends to a large extent on the enzyme and the nature of the sample. With stable enzymes, such as invertase and glucose oxidase, and clean samples the
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
column may last for several thousands of samples before a change in performance can be noticed. As mentioned above, a large excess of enzyme is normally applied which results in a constant response for a given concentration until maybe 90% of the original activity is lost. For a long column life, crude samples, such as fermentation broth, milk, or blood, should be dialyzed or at least microfiltered. It is important that the sample is free from microorganisms that may otherwise be trapped in the flow system and consume the analyte or give a nonspecific contribution to the heat developed in the enzyme column. It was shown that β-lactamase columns used for determination of penicillin could last for well over 1000 samples if the broth samples were centrifuged and filtered (2 µm) before analysis.44 If possible, the enzyme should also be protected from inhibitors in the buffer or in the sample. Loss of urease activity is clearly prevented by addition of EDTA and reduced glutathione or DTT to protect from heavy metals and oxidation.14 Co-immobilization of catalase with oxidases prolongs the column lifetime considerably by removing the hydrogen peroxide formed in the oxidase reaction.40 Approximately doubled heat production and increased linearity are additional bonus effects.
7.2
Blood Analysis
A miniaturized thermal biosensor has been evaluated as part of a flow injection analysis system for the determination of glucose in whole blood. The sensor employed a small enzyme column constructed of stainless steel tubing and microbead thermistors (Figure 3). In the first trial, the sensor was applied for determination of blood glucose in dilution.11 The study employed superporous agarose beads as supporting materials for coimmobilization of glucose oxidase together with catalase. The whole human blood (containing an anticoagulant and sodium fluoride) was diluted 10-fold with PBS buffer, and analyzed in 20-µl sample volume and a flow rate of 50 µl min−1 . The results were compared with those from the Boehringer Mannheim Reflolux glucose meter and showed a good correlation. Direct determination of whole blood without any pretreatment has also been demonstrated with
the miniaturized thermal biosensors.9,10 In particular, fast determination of whole-blood glucose without any pretreatment was achieved with a sampling rate of 90 samples/h using a sample volume of 1 µl. GOD and catalase were co-immobilized onto CPG and packed into a microcolumn. Using a 1-µl sample volume an extended linear range of 0.5–20 mM glucose was obtained. The correlation coefficient of 0.98 between the thermal biosensor, Reflolux-S meter (Boehringer Mannheim), Granutest 100 glucose test kit (Merck Diagnostics) and the Ektachem (Kodak) instrument was evaluated with an RSD of 3.7% (n = 100). The influence of the hematocrit value and of possible interferences was also reported. There was no influence on the glucose determination for hematocrit values between 13 and 53%. This technique has been further applied to other metabolite determinations in whole blood, such as lactate and urea.10 Urease and lactate oxidase/catalase were separately immobilized onto CPG and charged into the enzyme columns. At a flow rate of 70 µl min−1 , linear analytical ranges from 0.2 to at least 50 mM and 0.2 to 14 mM were obtained for urea and lactate, respectively. The RSD (CV) for measurements of the analyte in buffer was 0.91% for urea and 1.84% for lactate. For urea in whole blood, the CV for 50 determinations was 4.1%. The results were compared with spectrophotometric methods. Correlation coefficients of 0.989 and 0.984 for blood urea and lactate (30 samples each) and in concentrations ranging from 4 to 20.9 mM and from 1.7 to 12.7 mM, respectively, were obtained.
7.3
In vivo Monitoring of Diabetes
The coupling of a miniaturized thermal flow injection analysis biosensor to a microdialysis probe for continuous subcutaneous glucose monitoring has also been reported.12 Co-immobilized GOD and catalase with a buffer flow rate of 60 µl min−1 via a 1-µl sample loop connected to a microdialysis probe were employed. In vitro results showed that the response time was 85 s and the sampling rate, 42 samples/h. During the experiment, the glucose profile in a healthy volunteer was followed both in the subcutaneous tissue and in the blood using the microdialysis setup proposed. The results were compared to other blood glucose analyzers.
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
7.4
Multianalyte Determination
A flow injection thermal microbiosensor has also been designed for the simultaneous determination of multiple analytes.24,32 The biosensor consisted of a number of thin-film thermistors, which were located along a single microchannel in array format (Figure 5). This allows the determination of multiple analytes nearly simultaneously under equal conditions. For instance, for the determination of glucose, urea, and penicillin, a single microchannel was serially partitioned into three distinct detection regions. Each region contained one immobilized enzyme matrix and a pair of thermistors for differential measurement of temperature changes. The feasibility was demonstrated using agarose immobilized with GOD/CAT, urease, and penicillinase. Using this method, samples containing urea mixed with penicillin V and glucose were simultaneously analyzed. Linear ranges of up to 20 mM urea, 40 mM penicillin V, and 8 mM glucose (saturated with O2 ) were obtained using a flow rate of 30 µl min−1 and a sample volume of 20 µl. This system has been evaluated for the simultaneous determination of up to four different analytes, namely, glucose, lactate, urea, and penicillin.33
7.5
Recycling-amplified TELISA
In the competitive thermometric enzyme-linked immunosorbent assay (TELISA) method the ET column contains an immunosorbent. The sample is mixed with enzyme-labelled antigen and the concentration of bound antigen is determined by the introduction of a substrate pulse, after which the column is regenerated by a pulse of glycine at low pH. The whole cycle takes only 13 min or less in the arrangement described by Birnbaum and coworkers.18 The sensitivity is adequate for at-line determination of hormones, antibodies, and other biomolecules produced by fermentation. The use of alkaline phosphatase as an enzyme label allows enhancement of the sensitivity by using phosphoenolpyruvate as substrate and the utilization of a separate detection column in the ET unit for the determination of the product (pyruvate) by substrate recycling. This is accomplished by using the substrate recycling system described above, consisting of co-immobilized
15
LDH (reduces pyruvate to lactate under the consumption of NADH), lactate oxidase (oxidizes lactate to pyruvate), and catalase. In addition, genetically engineered enzyme conjugates have been used in immunoassays. Thus a human proinsulin–Escherichia coli alkaline phosphatase conjugate was used by Mecklenburg et al.19 for the determination of insulin or proinsulin. Concentrations lower than 1 µg ml−1 could be determined in less than 15 min.
7.6
On-line Monitoring of Bioprocesses
For on-line monitoring of bioprocesses using thermistor-based biosensors at a fermentation pilot plant and at a production plant, the equipment was placed inside a steel cabinet flushed with cool, filtered air to keep the temperature sufficiently constant. The ET was automated and equipped with a pneumatic sampling valve and a sample selector. A sample stream of 0.5–2 ml min−1 was taken from an autoclavable 0.2-µm polypropylene hollow fiber filtration probe (Advanced Biotechnology Corp., Puchheim, Germany). In order to follow penicillin production 0.1-ml samples were injected every 10–30 min over the duration of the fermentation (1–2 weeks). The flow through the ET unit (0.9 ml min−1 ) was equally split between the enzyme column (ß-lactamase or penicillin amidase bound to CPG) and an inactive reference column containing immobilized bovine serum albumin.16 The column was protected against microbial growth by adding 1 mM sodium azide to the buffer solution. With this setup, penicillin V could be measured during the entire fermentation run with the same enzyme column without serious problems in spite of rapid ambient temperature variations between 20 and 40 ◦ C, high humidity and vibrations. The linear concentration range of penicillin V can be as large as 0.05–500 mM for 0.1-ml samples. The reference column efficiently compensates for nonspecific heat effects. Besides penicillin, measurements have been performed on Saccharomyces fermentations by Rank and coworkers16 using alcohol oxidase for ethanol, glucose oxidase for glucose, and lactate oxidase for lactate. In all cases, catalase was co-immobilized to increase sensitivity and linear range. In a recent study17 Rank et al. demonstrated on-line monitoring of
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
ethanol, acetaldehyde, and glycerol during industrial fermentations with Saccharomyces cerevisiae. Larger variations in the concentration registered could occasionally be seen, especially at the end of penicillin fermentations, when the viscosity of the broth was high due to very high cell mass, which may cause improper function of the filtration unit. The general impression is, however, that the ABC filtration probe works better than a tangential flow unit at higher viscosities in smaller fermentors as well as in larger, production-scale fermentors.
7.7
Measurements in Organic Solvents
Measurements in organic media using biosensors have attracted much interest in recent years. Thermistor-based biosensors, such as the ET, are of special interest since the temperature response depends on the heat capacity of the system and the specific heat is up to three times lower in some organic solvents than in water. In addition the solubility of some enzyme substrates (cholesterol and triglycerides for instance) is higher in organic solvents than in water. It has been possible to design potentially useful procedures for enzyme analysis in organic solvents, especially since the enzymes involved may become stabilized by the immobilization. It could happen that the enzymic activity is lost after some time, but it is often possible to restore it fully by treatment with aqueous buffer. The enthalpy change is likely to be different in organic solvents or solvent–water mixtures than in pure buffer, which makes it difficult to predict the temperature response. In a comparison of the temperature responses obtained for tributyrin in a buffer–detergent system and in cyclohexane with lipoprotein lipase immobilized on celite the response was about 2.5 times higher in the latter case (as would be expected from the actual specific heats) and linear up to higher concentrations. In other experiments, however, the increase in sensitivity was found to be much higher. The usefulness of calorimetric sensors for work in different media was demonstrated by Stasinska et al.23 in a study on immobilized α-chymotrypsin which was used for hydrolysis of peptide bonds in 0.05 M Tris HCl, pH 7.8, containing 10% dimethyl formamide (DMF) and for syntheses
of peptide bonds in 50% DMF + 50% 0.1 M sodium borate, pH 10.0. With the α-chymotrypsin immobilized in the ET column both reactions could be followed, with the hydrolysis giving an exothermic response while the synthetic route was endothermic.
7.8
Environmental Control
The effect of pollutants on biological reactions is clearly measurable,14 but only a few routine applications of calorimetry have been described to date. One reason for this is the lack of suitable instrumentation. The inhibitory effect of pollutants such as pesticides on biological systems is usually irreversible, which means that the column with immobilized enzyme or cells must be replaced after one positive sample, resulting in an analysis speed of maybe only 1–2 samples/h. Instruments with a magazine of columns or with several parallel columns could overcome this drawback. Metal detection with thermistor-based biosensors has mostly been performed in two ways: by measuring the inhibition of enzymic activity or by measuring the activation of apoenzymes by metal ions. In both cases, a certain specificity can be obtained. An example of the first alternative is given by the very efficient inhibition of urease activity by heavy-metal ions (Hg2+ , Cu2+ , and Ag+ ). By using enzyme columns with comparatively low activity, very sensitive determinations in the parts per billion range or lower can be made. The original activity of the urease column can be restored by washing with iodide and EDTA. The sampling frequency is 3–4 samples per/h.14 Many enzymes require a certain metal in their active site to be active. It is often possible to remove this metal with strong chelating agents, which results in an inactive apoenzyme. Upon exposure to a sample containing the same (or related) metal ion, the activity is restored to an extent that is related to the concentration of the metal ion. This procedure can be repeated up to a couple of times per hour. Examples of this technique including determination of Co2+ , Cu2+ , and Zn2+ at nanomolar concentrations have been given by Satoh.15
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES
7.9
Thermometric Monitoring of Soluble Enzymes
On-line monitoring of chromatographic enzyme separations is usually restricted to registration of the UV absorption and determination of the pH or conductivity of the mobile phase. The normal procedure is to assay for the component of interest fraction-wise, collecting the fractions with the highest concentrations for further purification or concentration. This is time and labor consuming and may be damaging to labile components. Specific monitoring of proteins, for instance direct identification of a special enzyme, would greatly facilitate and speed up purification, since it would allow for an eluted enzyme fraction to be taken directly (on line) to a subsequent purification step. It has been shown that the ET has definite advantages as a detector of enzymic activities. For chromatographic monitoring, the effluent or a suitable aliquot of the effluent from a chromatographic column is mixed with a stream of substrate to the enzyme of interest. The heat registered upon passing the mixture through an empty inert column in the ET unit is proportional to the enzymic activity. Furthermore, it has been demonstrated that the ET can be utilized in automated, rapid (10–15 min/sample) TELISA monitoring of biomolecules other than enzymes.20 Another study demonstrated the control of an affinity-adsorption procedure by the specific enzyme activity signal from an ET.21 LDH was recovered from a solution by affinity binding to an N 6 -(6-aminohexyl)-AMP-sepharose gel. The LDH activity signal from the ET was used in a PID controller (equipped with proportional, integrating, and derivating control functions) or a computer to regulate the addition of AMP-sepharose suspension to the LDH solution. The rapid and precise control of the addition of adsorbent in our model experiments suggests that this technique should be attractive in pilot-plant and industrial-scale purifications of enzymes.
7.10
Characterization of Immobilized Biocatalysts
The usefulness of thermistor-based biosensors for the characterization of an immobilized enzyme
17
(invertase) was demonstrated in a study in which the kinetic constants were directly determined without the need for postcolumn analysis.48 An extension of this work allowed for the direct determination of the catalytic activity of immobilized cells as well.49 Trigonopsis variabilis strains selected by mutagenesis for high cephalosporintransforming activity were used in a model system in which the yeast cells were immobilized by cross-linking with homobifunctional reagents or by physical entrapment in gels. The thermometric signal arising from the activity of one specific, dominating enzymic step in the cells can be identified by comparative HPLC analysis of the reaction mixture. The cephalosporin-transforming activity of D-amino acid oxidase isolated from selected yeast strains and immobilized by gel entrapment was identified in the same way. The thermometric signal was found to be proportional to the number of cells as well as to the amount of enzyme D-amino acid oxidase (DAAO) immobilized in the ET minicolumn.
REFERENCES 1. A. P. F. Turner, New trends in biosensor development. Biosensors and Bioelectronics, 1999, 14, 243–245. 2. I. Karube, Recent trends in biosensor research and development. International Congress Series, 1995, 1100, 37–38. 3. C. R. Lowe, Biosensors. BCPC Symposium Proceedings, 1996, 65, 369–374. 4. H. Nakamura and I. Karube, Current research activity in biosensors. Analytical and Bioanalytical Chemistry, 2003, 377, 446–468. 5. C. Ziegler, and W. G¨opel, Biosensor development. Current Opinion in Biotechnology, 1998, 2, 585–591. 6. T. Natsume, Interaction proteomics using biosensor. Jikken Igaku, 2002, 20, 2015–2019. 7. G. Urban, Biosensor microsystems. Sensors Update, 2001, 8, 189–214. 8. T. Louis and P. Celestino. Micro- and nanotechnology in biosensor research. Chimia, 1999, 53(3), 62–66. 9. B. Xie, U. Hedberg, M. Mecklenburg, and B. Danielsson, Fast determination of whole blood glucose with a calorimetric micro-biosensor. Sensors and Actuators B, 1993, 15 – 16, 141–144. 10. B. Xie, U. Harborn, M. Mecklenburg, and B. Danielsson, Urea and lactate determined in 1-µL whole blood with a miniaturized thermal biosensor. Clinical Chemistry, 1994, 40, 2282–2287. 11. U. Harborn, B. Xie, and B. Danielsson, Determination of glucose in diluted blood with a thermal flow injection analysis biosensor. Analytical Letters, 1994, 27, 2639–2645.
18
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
12. A. Amine, B. Xie, and B. Danielsson, A microdialysis probe coupled with a miniaturized thermal glucose sensor for in vivo monitoring. Analytical Letters, 1995, 28, 2275–2286. 13. U. Harborn, B. Xie, R. Venkatesh, and B. Danielsson, Evaluation of a miniaturized thermal biosensor for the determination of glucose in whole blood. Clinica Chimica Acta, 1997, 267, 225–237. 14. B. Danielsson and K. Mosbach, Enzyme thermistors. Methods in Enzymology, 1988, 137, 181–197. 15. I. Satoh, Continuous biosensing of heavy metal ions with use of immobilized enzyme reactors as recognition elements. Materials Research Society. International Meeting on Advanced Materials, 1989, 14, 45. 16. M. Rank, J. Gram, and B. Danielsson, Industrial on-line monitoring of penicillin V, glucose and ethanol using a split-flow modified thermal biosensor. Analytica Chimica Acta, 1993, 281, 521–526. 17. M. Rank, J. Gram, K. Stern-Nielsen, and B. Danielsson, On-line monitoring of ethanol, acetaldehyde and glycerol during industrial fermentations with Saccharomyces cerevisiae. Applied Microbiology and Biotechnology, 1995, 42, 813–817. 18. S. Birnbaum, L. B¨ulow, K. Hardy, B. Danielsson, and K. Mosbach, Rapid automated analysis of human proinsulin produced by Escherichia coli . Analytical Biochemistry, 1986, 158, 12–19. 19. M. Mecklenburg, C. Lindbladh, H. Li, K. Mosbach, and B. Danielsson, Enzymatic amplification of a flow-injected thermometric enzyme-linked immunoassay for human insulin. Analytical Biochemistry, 1993, 212, 388–393. 20. B. Danielsson and P.-O. Larsson, Specific monitoring of chromatographic procedures. Trends in Analytical Chemistry, 1990, 9, 223–227. 21. L. Flygare, P.-O. Larsson, and B. Danielsson, Control of an affinity purification using a thermal biosensor. Biotechnology and Bioengineering, 1990, 36, 723–726. 22. B. Danielsson, L. Flygare, and T. Velev, Biothermal analysis performed in organic solvents. Analytical Letters, 1989, 22, 1417–1428. 23. B. Stasinska, B. Danielsson, and K. Mosbach, The use of biosensors in bioorganic synthesis: peptide synthesis by immobilized α-chymotrypsin assessed with an enzyme thermistor. Biotechnology Techniques, 1989, 3, 281–288. ¨ 24. B. Xie, M. Mecklenburg, B. Danielsson, O. Ohman, P. Norlin, and F. Winquist, Development of an integrated thermal biosensor for the simultaneous determination of multiple analytes. Analyst, 1995, 120, 155–160. 25. B. Danielsson, Calorimetric biosensors. Journal of Biotechnology, 1990, 15, 187–200. 26. B. Xie, B. Danielsson, P. Norberg, F. Winquist, and I. Lundstr¨om, Development of a thermal micro-biosensor fabricated on a silicon chip. Sensors and Actuators B, 1992, 6, 127–130. ¨ 27. B. Xie, M. Mecklenburg, O. Ohman, F. Winquist, and B. Danielsson, Microbiosensor based on an integrated thermopile. Analytica Chimica Acta, 1994, 209, 165–170. 28. G. Jobst, M. Varahram, I. Moser, P. Svasek, E. Aschauer, Z. Trajanoski, P. Wach, P. Kotanko, F. Skrabal, and G. Urban, Thin-film microbiosensors for glucose-lactate monitoring. Analytical Chemistry, 1996, 68, 3173–3179.
29. H. Frebel, G.-C. Chemnitius, K. Cammann, R. Kakerow, M. Rospert, and W. Mokwa, Multianalyte sensor for the simultaneous determination of glucose, L-lactate and uric acid based on a microelectrode array. Sensors and Actuators B-Chemical, 1997, B43, 87–93. 30. P. Yu and G. S. Wilson, An independently addressable microbiosensor array: What are the limits of sensing element density? Faraday Discussions, 2000, 116, 305–317. 31. B. G. Healey, L. Li, and D. R. Walt, Multianalyte biosensors on optical imaging bundles. Biosensors and Bioelectronics, 1997, 12, 521–529. 32. B. Xie and B. Danielsson, An integrated thermal biosensor array for multianalyte determination demonstrated with glucose, urea and penicillin. Analytical Letters, 1996, 29, 1921–1932. 33. B. Xie, M. Mecklenburg, A. Dzgoev, and B. Danielsson, Simultaneous determination of glucose, lactate, urea and penicillin in mixed samples using an integrated thermal biosensor array. Analytical Methods and Instrumentation, 1996, Special issue µTAS 96, 95–99. 34. B. Xie, M. Khayyami, T. N. Nwosu, P.-O. Larsson, and B. Danielsson, Ferrocene-mediated thermal biosensor. Analyst, 1993, 118, 845–848. 35. B. Xie, X. Tang, U. Wollenberger, G. Johansson, L. Gorton, F. Scheller, and B. Danielsson, Hybrid biosensor for simultaneous electrochemical and thermometric detection. Analytical Letters, 1997, 30, 2141–2158. 36. N. Kiba, T. Tomiyasu, and M. Furusawa, Flow enthalpimetric determination of glucose based on oxidation of 1,4-benzoquinone with use of immobilized glucose oxidase column. Talanta, 1984, 31, 131–132. 37. F. Scheller, N. Siegbahn, B. Danielsson, and K. Mosbach, High-sensitivity enzyme thermistor assay of L-lactate by substrate recycling. Analytical Chemistry, 1985, 57, 1740–1743. 38. D. Kirstein, B. Danielsson, F. Scheller, and K. Mosbach, Highly sensitive enzyme thermistor determination of ADP and ATP by multiple recycling enzyme systems. Biosensors, 1989, 4, 231–239. 39. B. Danielsson, B. Mattiasson, and K. Mosbach, Enzyme thermistor analysis in clinical chemistry and biotechnology. Pure and Applied Chemistry, 1979, 51, 1443–1457. 40. G. G. Guilbault, B. Danielsson, C. F. Mandenius, and K. Mosbach, Enzyme electrode and thermistor probes for determination of alcohols with alcohol oxidase. Analytical Chemistry, 1983, 55, 1582–1585. 41. B. Danielsson, E. Rieke, B. Mattiasson, F. Winquist, and K. Mosbach, Determination by the enzyme thermistor of cellobiose formed on the degradation of cellulose. Applied Biochemistry and Biotechnology, 1981, 6, 207–222. 42. I. Satoh, Biomedical applications of the enzyme thermistor in lipid determination. Methods in Enzymology, 1988, 137, 217–225. 43. L. D. Bowers and P. W. Carr, Immobilized-enzyme flow-enthalpimetric analyzer: application to glucose determination by direct phosphorylation catalyzed by catalase. Clinical Chemistry, 1976, 22, 1427–1433. 44. G. Decristoforo and B. Danielsson, Flow injection analysis with enzyme thermistor detector for automated detection of β-lactams. Analytical Chemistry, 1984, 56, 263–268.
THERMAL BIOSENSOR AND MICROBIOSENSOR TECHNIQUES 45. B. Mattiasson and B. Danielsson, Calorimetric analysis of sugars and sugar derivatives with aid of an enzyme thermistor. Carbohydrate Research, 1982, 102, 273–282. 46. I. Satoh, B. Danielsson, and K. Mosbach, Triglyceride determination with use of an enzyme thermistor. Analytica Chimica Acta, 1981, 131, 255–262. 47. I. Satoh, M. Akahane, and K. Matsumoto, Analytical application of immobilized acid urease for urea in flow streams. Sensors and Actuators, B: Chemical, 1991, B5, 241–243.
19
48. V. Stefuca, P. Gemeiner, L. Kurillov´a, B. Danielsson, and V. B´ales, Application of the enzyme thermistor to the direct estimation of intrinsic kinetics using the saccharoseimmobilized invertase system. Enzyme and Microbial Technology, 1990, 12, 830–835. 49. P. Gemeiner, V. Stefuca, A. Welwardov´a, E. Michalkov´a, L. Welward, L. Kurillov´a, and B. Danielsson, Direct determination of the cephalosporin transforming activity of immobilized cells with use of an enzyme thermistor. 1. Verification of the mathematical model. Enzyme and Microbial Technology, 1993, 15, 50–56.
39 Microcalorimetry and Related Techniques Alan Cooper WestChem Department of Chemistry, University of Glasgow, Glasgow, Scotland
Almost all physical and chemical processes or interactions involve changes in heat energy, and the direct measurement of thermal effects is potentially attractive for a wide range of analytical or sensor applications. Heat effects are usually intrinsic to the process under investigation and thus require no additional chemical or physical modifications of the sample material. Moreover, thermal effects should be measurable whatever the state of the sample material, so may in principle be used on solids, suspensions or other heterogeneous phases where turbidity or light scattering might otherwise frustrate optical and other techniques. Consequently, calorimetric methods have gained popularity as potentially noninvasive and nondestructive analytical techniques for sensing or monitoring a wide range of processes, as well as giving direct access to the underlying thermodynamics. This is particularly true for the study of biological and biomolecular systems, where recent developments in microcalorimetry and related technologies have led to the availability of commercial instruments that are simple to use and have become part of the standard repertoire of techniques in many research laboratories. There are also numerous on-going trials aimed at exploiting thermal methods for more rapid general-purpose screening procedures, requiring no labeling, attachment, or other potentially disruptive chemical modifications. This chapter will give an overview of currently available methods applicable to biological and biomolecular samples, together with a
summary of developing techniques aimed at more rapid throughput applications. The use of direct calorimetric methods for the study of biological and biomolecular processes is not new. Indeed, some of the earliest investigations on the nature of heat by Lavoisier in the late eighteenth century involved the measurement of heat output by guinea pigs enclosed in an ice calorimeter, where the animal’s body heat was measured by the increased melting of ice. Combustion calorimetry developed quickly, and remains as the standard procedure for determining the absolute calorific value of foodstuffs and related materials central to metabolic energetics. However, biological microcalorimetry as we now know it probably begins in the early twentieth century with the pioneering work of A.V. Hill (UK), who devised sensitive thermocouple techniques to detect heat changes in contracting muscle fibers. He was awarded the 1922 Nobel Prize in Physiology or Medicine “for his discovery relating to the production of heat in muscle”. Subsequent developments, both in instrumental techniques and their applications to biomolecular systems, comes from the work of Edouard Calvet (France), Julian Sturtevant (USA), T.H. Benzinger (USA), Peter Privalov and Valerian Plotnikov (former USSR), John Brandts (USA), and Ingemar Wads¨o (Sweden), amongst others. Here, we concentrate on currently available microcalorimetry technologies and their applications (both actual and potential) to biological materials and their interactions.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
1 CALORIMETRIC PRINCIPLES
Although calorimetry is a widely established procedure across a wide range of chemistry, physics, and materials sciences,1 and the underlying thermodynamic principles are common to all applications, the study of biological systems presents additional challenges. In particular, the heat effects normally encountered with biological samples are generally quite small—both because of the generally small enthalpy changes associated with the underlying biomolecular interactions, often involving just noncovalent interactions, and because of the small sample size and low concentrations normally available. A note about units: Despite the introduction of SI units, and the best efforts of IUPAC and other international bodies, it is still common (especially in the USA) to use the calorie as unit of heat, rather than the recommended SI unit, the joule. The calorie is a useful quantity to bear in mind, especially in aqueous systems, since it takes 1 calorie to raise the temperature of 1 g of water by 1 ◦ C. Conversion: 1 calorie = 4.184 J. A further cautionary note: Although the majority of physical and chemical processes will have an associated heat effect, there are some cases, under some conditions, where the enthalpy change of the process is zero. A striking example of this arises in the thermodynamics of protein–protein interactions in solution, where the heat of association depends strongly on temperature, and can be 0 at ambient temperatures.2 More generally, thermodynamic phase changes higher than first order can take place without change in enthalpy. However, such situations are relatively rare. So, with this caveat, typical heat effects may be estimated as follows. Cells and tissues: A resting 75 kg male generates a metabolic heat output of about 150 W (1 W = 1 J s−1 ), which corresponds to an average of around 2 mW g−1 of tissue. Since the bulk of biological tissue is water, in the absence of heat losses this would give a temperature change of about 5 × 10−4 ◦ C s−1 . This is the typical heat flux one might expect for biological tissues, though obviously individual cells and tissues are likely to vary enormously depending on their function and metabolic state. For comparison, A.V. Hill in his original experiments circa 1913 detected temperature changes of up to 0.003 ◦ C during twitching
of the frog sartorius muscle. Heat flux from individual cells, either in tissue or cell culture suspensions, is normally around 20–50 pW (2–5 × 10−11 W) per cell, though this can range from as low as 0.01 pW for relatively inert red blood cells, and up to 300 pW or more for metabolically active mammalian hepatocytes (liver cells).3,4 Biomolecular interactions: When working with biological macromolecules, scarcity of material and poor solubility/aggregation problems mean that concentrations in solution rarely exceed 10 µM (corresponding to around 0.25 mg ml−1 for a 25 kDa macromolecule). For noncovalent interactions such as protein-inhibitor or drug-receptor binding, the binding enthalpies are typically of order ±10 kJ mol−1 . Consequently, for 1 ml of a 10 µM solution (10 nmol of receptor), the heat energy liberated (or absorbed) upon ligand binding is of order 1 × 10−4 J for complete saturation of binding sites. For binding isotherm investigations involving thermal titration (see isothermal titration calorimetry, ITC, in the subsequent text), detection levels of 1 × 10−6 J ml−1 , or lower, are required—hence the term “micro”-calorimeter. This translates to temperature changes in aqueous samples of less than 0.25 × 10−6 ◦ C per binding event. Such relatively small heat effects put severe limitations on the measurements and demand careful controls to eliminate heat artefacts from other sources. Heat due to mixing and evaporation can give rise to heat effects many orders of magnitude greater than that of the target experiment. Temperature control is vital, and systematic effects arising from environmental temperature gradients and fluctuations are generally minimized by adopting a differential, dual-cell configuration, in which identical “sample” and “reference” calorimetric vessels (or cells) are mounted back-to-back, with only the difference in thermal response between the cells being measured. Ideally, such an arrangement eliminates artefacts due to extraneous heat effects. Simple calorimeters measure just the (differential) temperature change in the sample, converted into absolute thermal energy using the known (or assumed) heat capacity of the instrument. However, this is rarely satisfactory for biological calorimetry because of the very small temperature changes involved and the underlying uncertainties in detection and calibration. Two different approaches have been adopted in order to give
MICROCALORIMETRY AND RELATED TECHNIQUES
more direct thermal energy measurement appropriate for these circumstances. Heat flux (or “heat leak” or “heat burst”) calorimetry is a passive method that relies on the coupled thermal and electrical properties of thermoelectric devices. The calorimetric sample (and reference) cells are placed in intimate contact with thermopiles—multiple thermocouples connected in series—whose opposing junctions are in good thermal contact with a relatively massive heat sink (see Figure 1). No attempt is made to contain the heat within the sample cell. Rather, any heat generated within the calorimetric vessel is allowed to flow across the thermopile to the heat sink. The voltage (V ) generated by the thermopile at any one time is proportional to the temperature difference (δT ) between the sample and the surrounding heat sink: V = k1 · δT
(1)
For small temperature differences, the rate of heat energy dissipation across the thermopile (dQ/dt) is also proportional to δT : dQ = k2 · δT dt
(2)
Consequently, the (differential) voltage generated by the thermopiles is a direct measure of the heat flux in or out of the calorimetric vessel: dQ = k · V (where the ks are instrumental dt constants) (3) Insulation
Thermal shield
S
Reference
Sample
Integration of the voltage (V ) over time gives, after appropriate calibration, the total heat energy change, Q. This is the basis of modern “thermal activity monitor” (TAM) instruments, based on the original principle devised by Calvet,5 subsequently developed by Benzinger and Wads¨o groups.6,7 Current systems rely on the use of solid-state, semiconductor Peltier thermocouple devices, which combine good thermoelectric response and good thermal conductivity with a low electrical impedance that minimizes electrical noise in the measured voltages (which are typically in the submicrovolt range). Connection of the sample and reference thermopiles back-to-back in series (see Figure 1) means that only differential effects are detected. These systems have very good long-term thermal stability, but relatively slow response times. Heat compensation calorimetry, by contrast, relies on the active response to temperature differentials between sample and reference cells, supplying electrical heat energy directly to one cell or the other in order to restore thermal balance (see Figure 2). The calorimetric cells are suspended in an adiabatic shield, thermally isolated from each other, but with sensitive thermocouples to sense any temperature difference (T1 ) between them. The thermocouple voltage (corresponding to T1 )
Thermostat
Thermopiles
Heat sink
3
∆T1
R
Computer Nano voltmeter Feedback heaters
Figure 1. Principles calorimetry.
of
heat
flux/heat
leak/heat
burst Figure 2. Principles of heat compensation calorimetry.
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
is amplified and, using electronic feedback circuitry, electrical current is supplied to the feedback heaters of the appropriate cell to restore T1 to zero. This electrical heat energy is a direct measure of the differential thermal output from whatever process is taking place within the sample cell. These two approaches have so far proved the most successful and reliable for biological and biomolecular studies. The main differences between competing instruments lies in the nature of the samples and processes to be studied, and in the ways in which these reactions or processes may be initiated.
2 THERMAL ACTIVITY MONITOR (TAM)
The TAM is an isothermal microcalorimeter system utilizing the heat leak principle and based on original designs by Wads¨o.7 Its high sensitivity and good thermal stability makes it suitable for monitoring heat flux from very slow processes such as seed maturation,8 or degradation of pharmaceutical products.9,10 Sample and reference cells, with a typical capacity of a few ml, are mounted directly into the thermopile block. The versatility of the demountable cell configuration allows for a variety of sample handling options including ampoule breaking for bulk dissolution and reaction studies, liquid flow for adsorption and in-line process monitoring, gas flow systems for aeration of microbial cultures, and so forth (though precautions must be taken to minimize evaporation losses and consequent heat artefacts in gas flow experiments).11 Although primarily an isothermal reaction calorimeter, modification using two different temperature regions (“heat drop calorimeter”) allows direct measurement of absolute heat capacities on bulk samples.12 The good thermal stability and sensitivity of the TAM and related instruments comes at the cost of sampling speed. The larger thermal inertia of the system and the passive nature of the heat leak principle means that instrumental response times are quite slow. Consequently, although isothermal titration reaction studies are possible using cells equipped with microinjection and stirring facilities, such experiments are relatively time consuming compared to more dedicated ITC methods (see subsequent text), although in some cases speeds can be enhanced by software deconvolution techniques.13
3 ISOTHERMAL TITRATION CALORIMETRY (ITC)
Reactions and interactions in solution or suspension are currently best measured using a dedicated ITC approach based on the heat compensation method.14–16 In a typical configuration (Figure 3) the sample cell (capacity 1–2 ml, total fill) is fitted with a combined microliter injection syringe and stirrer, through which small volumes of one reagent (the “ligand”) may be injected into the sample solution (the “macromolecule”). Any heat liberated or absorbed by the subsequent reaction that generates a small change in the temperature difference (T1 ) between sample and reference cells is nullified by electrical heat energy to the appropriate cell feedback heaters. A typical experiment for binding studies comprises a sequence of injections (5–50 µl each) of ligand into the macromolecule solution, each separated by an interval of 3–4 min (or longer for slow reactions), giving a series of heat pulses that eventually diminish to baseline levels as all the binding sites are titrated (Figure 4). Integration of the heat flux from each injection
Injection syringe and stirrer motor L
Thermal shield
∆T2 ∆T1
R Jacket (∆T2) heater/cooler
Feedback heaters
Figure 3. Isothermal titration calorimeter (ITC). [Reproduced from Johannessen et al.33 by permission of the Royal Society of Chemistry.]
MICROCALORIMETRY AND RELATED TECHNIQUES Time (min) 0
20
40
60
80
100
120
0.0
0.5
1.0 1.5 2.0 Molar ratio
2.5
3.0
0
µW
−2 −4 −6 (a) kJ mol−1 of injectant
0 −10 −20 −30 −40 −50
(b)
Figure 4. Typical ITC data for binding of a trisaccharide inhibitor (tri-N -acetyl-glucosamine; tri-NAG) to hen egg-white lysozyme, in 0.1 M acetate buffer, pH 5. Each exothermic heat pulse (a) corresponds to injection of 10 µl of tri-NAG (0.45 mM) into the protein solution (36 µM). Integrated heat data (b) constitute a differential binding curve that may be fit to a standard single-site binding model to give, in this instance, the stoichiometry of binding, N = 0.99, binding affinity, Kass = 3.9 × 105 M−1 (Kdiss = 2.6 µM), and enthalpy of binding, H = −51.7 kJ mol−1 . [Adapted from Cooper et al.17 with permission from Elsevier.]
event gives a differential thermal titration curve that may be analyzed in terms of an appropriate binding isotherm to give quantities such as the number of binding sites (N ), binding affinity (K), and binding enthalpy (H ) for the system under investigation. Repeat measurements over a range of temperatures (typically in the range 5–50 ◦ C) can be used to determine the variation in H with temperature or heat capacity difference (Cp = dH /dT ) that is commonly observed in biomolecular systems.2,17 Sample preparation is key to successful ITC operation and particular attention must be paid to matching the sample and ligand buffer (solvent) to avoid the large spurious heat effects that
5
will arise from mixing different buffers. This is best achieved by extensive dialysis of the macromolecule against the appropriate buffer, taking an aliquot of the final equilibration buffer for preparation of the ligand solution and for dilution control experiments. Alternative equilibration methods include buffer exchange by gel filtration or centrifugal membrane concentrators. Although primarily designed for the measurement of interactions in solution, ITC can be used to study interactions in suspensions and dispersions such as colloids or lipid bilayer/membrane vesicles. The main limitation, at least for noncovalent ligand binding studies, is that the concentration of binding sites in the sample cell should be in excess of 1 µM. This can be difficult to achieve in, for example, cell suspensions, where the effective concentration of cell surface receptors is too low. High concentrations of (packed) cells, viscous solutions, or excessive particulate matter in the sample suspension give rise to additional heat effects from the mechanical stirring that can mask the desired observation. ITC methods can also be used to monitor slower processes such as enzyme kinetics or changes in cell metabolism after injection of substrates or metabolites. This can be useful in circumstances where alternative assays are not available, since the heat flux generated by reactions does not require any additional components such as might be required in coupledenzyme assays for example. Sample requirements in this case can be more modest, since the heat of covalent reactions are generally much larger.
4 DILUTION ITC
Dissociation of (macro)molecular complexes can be studied in the ITC by dilution. Injection of sample into a large excess of solvent gives (usually) endothermic heat pulses as the complexes dissociate. With appropriate choice of concentrations, such heat pulses get progressively smaller with subsequent injections as the concentration in the sample cell increases. This has been used, for example, to characterize monomer–dimer interactions in proteins,19 and to determine critical micelle concentrations (Figure 5).20
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Time (min) 0
20
40
60
80
60
µJ s−1
40
20
0
kJ mol−1 of injectant
(a)
2
cmc 0
0 (b)
5
10
15
20
25
Injection number
Figure 5. Dilution ITC for determining dissociation thermodynamics. This example shows the series of endothermic heat pulses (a) obtained from sequential injections of detergent micelles into water. (b) shows the integrated heat data (symbols) and the first derivative (line) from which the critical micelle concentration (cmc) can be inferred. [Adapted from Lovatt et al.19 with permission. Copyright 1998, American Chemical Society.]
or the phase transitions that can take place in biological membranes. Figure 6 shows the typical layout of a DSC instrument.21 Sample and reference solutions are contained in identical calorimetric vessels (labeled S and R), typically around 0.5–1 cm3 in volume. In a DSC experiment the sample solution, S (typically a protein at a concentration of 1 mg cm−3 or less) is heated at constant rate in the calorimeter cell alongside an identical reference cell (R) containing buffer. Both sample and reference solutions are kept under a small positive inert gas pressure, P (1–2 atm), to inhibit bubble formation from dissolved gases as the temperature is increased. Following the heat compensation principle, temperature differences between S and R (T1 ) and the surrounding jacket (T2 ) are measured by sensitive thermocouples which provide a voltage, proportional to the temperature difference, that may be sensed and amplified by external electronics. The entire system is heated at constant rate by the jacket and main heaters, and each cell (R and S) may be heated separately using feedback heaters. The power supplied to these heaters (voltage and current) is measured and recorded. Initially during a temperature scan, if both sample and reference behave the same, there will be no temperature difference between them. However, at some temperature the protein molecules in the sample solution for example, may begin to thermally unfold, and some of the heat energy P
5 DIFFERENTIAL SCANNING CALORIMETRY (DSC)
Differential scanning calorimetry (DSC) is an experimental technique to measure directly the heat energy uptake that takes place in a sample during controlled increase (or decrease) in temperature. At the simplest level it may be used to determine thermal transition (“melting”) temperatures for samples in solution, solid, or mixed phases (e.g., suspensions). But with more sensitive apparatus and more careful experimentation it may be used to determine absolute thermodynamic data for thermally-induced transitions of various kinds. It is particularly useful in studying the thermodynamics of unfolding transitions in dilute solutions of proteins and nucleic acids,
Thermal shield
∆T2 S
∆T1
R
Jacket (∆T2) heater/cooler
Main heaters
Feedback heaters (∆CP) Figure 6. A differential scanning calorimeter for measuring thermal transitions in dilute solution. [Reproduced from Johannessen et al.33 by permission of the Royal Society of Chemistry.]
from the main heaters will be used to bring about this endothermic transition, rather than in raising the temperature. Consequently, there will be a temperature lag (T1 ) between the sample and reference cells. This is detected by the external electronics, and additional heat is supplied to S (using the feedback heater) to correct this imbalance. The electrical heat energy supplied to the sample, in this case, is a direct measure of the enthalpy change in the sample due to the temperature change, and the instrumental output is the differential excess heat capacity of the sample with respect to solvent (e.g., see Figure 7). The mid-point temperature of the thermal transition (Tm ) is frequently adequate for simple qualitative stability studies, but more detailed analysis of the thermogram shapes can yield full thermodynamic information for the transition, its cooperativeness and reversibility. The binding of ligands stabilizes the native state of a protein that results pH 1 2 3 4 5
pH 3.8
80
60 pH 2.5
60
40 40 pH 1.2
CP (kJ K−1 mol−1)
Tm (°C)
80
Excess heat capacity Cp (mJ K−1)
MICROCALORIMETRY AND RELATED TECHNIQUES
40
60
80
Temperature (°C) Figure 7. Typical DSC data for the unfolding of a small globular protein (lysozyme) in solution at various pH values. The insert shows the variation in midpoint unfolding temperature (Tm ) as a function of pH. The increase in area under each endotherm with higher Tm , and the higher heat capacity baselines after the unfolding transitions, are both indications of the significant positive Cp commonly associated with such processes. [Adapted from Cooper et al.17 with permission from Elsevier.]
+ ADP
4
+ Shikimate 2
Enzyme alone
0 20
30
40 50 Temperature (°C)
60
70
in an increase in Tm of the protein (see Figure 8). This thermal shift effect can be used for qualitative screening assays for potential drugs or inhibitors when the target protein is known and available in sufficient quantities. One factor that must be borne in mind, particularly with biomolecular systems, is that thermal transitions are frequently irreversible and DSC thermograms often exhibit complex patterns that depend on kinetic and other factors such as the temperature scan rate or the geometry of the calorimetric cell. An example is shown in Figure 9.
0.002
Cp (cal °C −1)
20
+ ATP
Figure 8. Raw DSC data illustrating the heat uptake associated with thermal unfolding of shikimate kinase (1 mg ml−1 ) in the presence and absence of substrate molecules (2 mM shikimate, ADP or ATP). The increase in Tm in the presence of each substrate is consistent with specific ligand binding to the native state of the enzyme. [Adapted from Chancellor et al.34 with permission from Cold Spring Harbor Press.]
20
0
7
0.000 −0.002 −0.004
pH 7.1 pH 6.0 pH 5.0 pH 4.0 pH 3.0
−0.006 30
40
50
60
70
80
90
Temperature (°C) Figure 9. DSC thermograms for the thermal unfolding and subsequent aggregation of a monoclonal antibody in dilute solution at different pH levels. [Andrew Heron, Ph.D. thesis, Glasgow University, 1999—unpublished.]
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
The erratic exothermic responses at near-neutral pH correspond to the irreversible aggregation of unfolded protein, under these conditions. The shapes of these high temperature transients depend on scan rates and concentrations in an unpredictable fashion, and can vary from one instrument to another. The response arises from a number of effects including erratic thermal convection of aggregated material in the calorimetric cell. These artefacts can sometimes be minimized by using instruments with different cell geometries (e.g., capillary cells), but this does not eliminate the underlying causes of the effects.
6 PRESSURE PERTURBATION CALORIMETRY (PPC)
Pressure perturbation calorimetry (PPC) is a recently introduced modification to DSC that allows the determination of differential volumetric properties of molecules in solution.23 The equipment consists of a standard DSC (Figure 6), run in isothermal mode, with the additional facility to apply inert gas pressure pulses (compression and decompression, ±3–5 atm) simultaneously to the sample and reference cells. Pressure-volume (PV) work on the system generates heat pulses (Q) that are related to the differences in thermal expansibility of the solute compared to the solvent that it has displaced. Typical data are illustrated in Figure 10 for a solution of carbohydrate in water.
4 Decompression ∆P = −75 psi
µcal s−1
2
0 −2 −4
Compression ∆P = +75 psi 0
20
40
60
80
100
120
140
Time (s)
Figure 10. Raw PPC data obtained upon pressure perturbation (±75 psi) of an aqueous solution of β-cyclodextrin at 25 ◦ C. [Diane Cameron & Alan Cooper—unpublished.]
The magnitude of the integrated heat effect (Qrev ) in response to a pressure pulse (P ) depends on a number of factors, expressed in the following equations: Thermal expansivity : E ◦ = ∂V ◦ /∂T = α ◦ V ◦ (4) Thermal expansion coefficient of solute: αS◦ = α0 −
Qrev T Pg s Vs◦
(5)
where α0 is the thermal expansion coefficient of the solvent, T is the absolute temperature, and gs and Vs◦ are the mass and partial specific volume of the solute, respectively. This technique has been applied to the study of volumetric changes during protein unfolding and aggregation,23,24 and more recently to protein-ligand and related interactions (Cooper & Cameron—unpublished).
7 PHOTOCALORIMETRY
The energetics of light-induced processes can be studied using simple modifications of the calorimetric devices described in the preceding text. This was first used to study the energetics of the various stages in the rhodopsin/photoreceptor membrane photocycle of visual excitation, including processes at liquid nitrogen temperatures,25–27 and has since been applied to other photosynthetic and photodegradation processes.28 Fiberoptic light guides are used to illuminate the sample (and reference) in situ in the calorimeter cells using an appropriately stable light source and monochromator. Even in the absence of any photoreaction, all the light energy entering the calorimeter is converted into heat, which gives a background/baseline level of heat flux against which any additional effects of the photoreaction must be measured. This means that the method is in practice applicable successfully only to photochemical processes with relatively high quantum efficiencies.
MICROCALORIMETRY AND RELATED TECHNIQUES
8 SCREENING METHODS
Given the ubiquity of heat effects and the potentially label-free and noninvasive nature of microcalorimetry, it is not surprising that attempts have been made to use this for various screening procedures, especially in the pharmaceutical/drug discovery context. However, calorimetric methods as currently implemented are relatively slow, with a typical average turnaround time of 2–3 h per sample for conventional ITC or DSC experiments, including time for appropriate controls, cell cleaning, and equilibration. Automatic sample handling techniques can be used for routine procedures, allowing unattended instrument operation and increased sample throughput to approximately 10 compounds per day—a fairly modest throughput compared to the needs of the pharmaceutical industry. This, together with the relatively large sample requirement (by biochemical standards), means that calorimetric methods do not yet have sufficient capacity for primary screens involving large compound libraries. However, they are finding increasing application in more detailed characterization of selected compound families (e.g., see Ref. 29). One step toward addressing this problem has been the development of more rapid, automated DSC technology, using capillary cells and increased scan rates to screen for ligand binding using the thermal shift approach described in the preceding text.30 Running unattended, this can allow up to 50 scans per day, albeit with slightly reduced sensitivity.
9 THERMAL IMAGING METHODS
Although not strictly calorimetry, another thermal method worth mentioning in this context exploits sensitive thermal imaging technology to detect the changes in infrared emission arising from small temperature changes.31 This has been used to image drug-induced variations in thermogenesis from cell cultures in multiwell microtiter plates, and consequently appears potentially attractive for screening purposes. Success in this case depends on very careful control of temperature uniformity across the sample plate, and this does appear to impose some limitations on possible applications. As currently implemented, this method has
9
a reported temperature sensitivity of the order of 10−3 ◦ C, compared to about 10−5 ◦ C for thermoelectric detectors, or better than 10−6 ◦ C for heat conduction calorimeters.3
10
CALORIMETERS-ON-CHIPS
Given the high sample demand and speed limitations of current microcalorimeter instruments it is not surprising that numerous efforts are under way to utilize microfabrication/nanotechnology approaches to miniaturize the process. In principle, reduction in sample volume to microliter proportions (or less) would allow more economic use of precious biological materials as well as enhancing thermal response times, which together with multiple sample processing in parallel on array-like devices, would give orders-of-magnitude improvements in sample throughput capability. Fabrication of submillimeter thermometer or other calorimetric detectors with millidegree (0.001 ◦ C) sensitivity, or equivalent, is relatively straightforward using modern semiconductor/vapor-deposition technologies, and can in principle be used to generate devices with multiple detectors on a single chip. But there are major technical issues relating to thermal stability, sample delivery and mixing that have to be addressed when using such devices for real applications. Extraneous heat effects arising from sample evaporation and surface wetting/adsorption processes can be significantly larger than the heat of reaction under investigation, and the basic (fluid) mechanics of sample positioning and mixing can lead to large thermal artefacts. One innovative approach to the sample mixing problem has been to use on-chip electrostatic forces to merge submicroliter liquid droplets, as in the “enthalpy array” devices of Torres et al.32 that are capable of detecting heat effects associated with standard enzyme-catalyzed reactions, ligand binding, and mitochondrial respiration processes on a standard 96-fold array format, with thermal response times of around 1 s per detector. Micromachined nanocalorimeter devices capable of monitoring heat flux from single cells or other subnanoliter samples have been described.33,34 Despite such innovations, there are still major hurdles being faced by calorimetry-on-chip development, and no widespread uptake or significant
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
applications have yet been reported as of this date (May 2006).
REFERENCES 1. M. Sorai (ed), Comprehensive Handbook of Calorimetry and Thermal Analysis, John Wiley & Sons, 2004, ISBN: 0-470-85152-X. 2. A. Cooper, Heat capacity effects in protein folding and ligand binding: a re-evaluation of the role of water in biomolecular thermodynamics. Biophysical Chemistry, 2005, 115, 89–97. 3. R. B. Kemp, The application of heat conduction microcalorimetry to study the metabolism and pharmaceutical modulation of cultured mammalian cells. Thermochimica Acta, 2001, 380, 229–244. 4. R. B. Kemp and I. Lamprecht, La vie est donc un feu pour la calorimetrie: half a century of calorimetry - ingemar Wads¨o at 70. Thermochimica Acta, 2000, 348, 1–17. 5. M. Calvet and H. Prat, Microcalorim´etrie, Masson, Paris, 1956. 6. C. Kitzinger and J. H. Benzinger, Methods of Biochemical Analysis, 1960, 8, 309. 7. I. Wads¨o, Design and testing of a micro reaction calorimeter. Acta Chemica Scandinavica, 1968, 22, 927–937. 8. F. R. Hay, M. A. A. ONeill, A. E. Beezer, and S. Gaisford, Isothermal microcalorimetry: a tool to predict seed longevity? Seed Science Research, 2006, 16, 89–96. 9. A. E. Beezer, M. A. A. O’Neill, K. Urakami, J. A. Connor, and J. Tetteh, Pharmaceutical microcalorimetry: recent advances in the study of solid state materials. Thermochimica Acta, 2004, 420, 19–22. 10. C. V. Skaria, S. Gaisford, M. A. A. O’Neill, G. Buckton, and A. E. Beezer, Stability assessment of pharmaceuticals by isothermal calorimetry: two component systems. International Journal of Pharmaceutics, 2005, 292, 127–135. 11. I. Wads¨o and L. Wads¨o, A new method for determination of vapour sorption isotherms using a twin double microcalorimeter. Thermochimica Acta, 1996, 271, 179–187. 12. J. Suurkuusk and I. Wads¨o, Design and testing of an improved precise drop calorimeter for measurement of heat-capacity of small samples. Journal of Chemical Thermodynamics, 1974, 6, 667–679. 13. M. Bastos, S. Hagg, P. Lonnbro, and I. Wads¨o, Fast titration experiments using heat conduction microcalorimeters. Journal of Biochemical and Biophysical Methods, 1991, 23, 255–258. 14. T. Wiseman, S. Williston, J. F. Brandts, and L. N. Lin, Rapid measurement of binding constants and heats of binding using a new titration calorimeter. Analytical Biochemistry, 1989, 179, 131–137. 15. A. Cooper and C. M. Johnson, Isothermal Titration Microcalorimetry, in Microscopy, Optical Spectroscopy, and Macroscopic Techniques, C. Jones, B. Mulloy, and A. H. Thomas (eds), Humana Press, Totowa, 1994, pp. 137–150.
16. A. Cooper, Microcalorimetry of Protein-Protein Interactions, in Biocalorimetry: The Applications of Calorimetry in the Biological Sciences, J. E. Ladbury and B. Z. Chowdhry (eds), John Wiley & Sons, 1998, pp. 103–111. 17. A. Cooper, C. M. Johnson, J. H. Lakey, and M. Nollmann, Heat does not come in different colours: entropyenthalpy compensation, free energy windows, quantum confinement, pressure perturbation calorimetry, solvation and the multiple causes of heat capacity effects in biomolecular interactions. Biophysical Chemistry, 2001, 93, 215–230. 18. A. Cooper, Biophysical Chemistry, Royal Society of Chemistry, Cambridge, 2004. 19. M. Lovatt, A. Cooper, and P. Camilleri, Energetics of cyclodextrin-induced dissociation of insulin. European Biophysics Journal, 1996, 24, 354–357. 20. A. Cooper, M. A. Nutley, and P. Camilleri, Microcalorimetry of chiral surfactant-cyclodextrin interactions. Analytical Chemistry, 1998, 70, 5024–5028. 21. V. V. Plotnikov, J. M. Brandts, L.-N. Lin, and J. F. Brandts, A new ultrasensitive scanning calorimeter. Analytical Biochemistry, 1997, 250, 237–244. 22. T. Krell, J. Maclean, D. J. Boam, A. Cooper, M. Resmini, K. Brocklehurst, S. M. Kelly, N. C. Price, A. J. Lapthorn, and J. R. Coggins, Biochemical and X-ray crystallographic studies on shikimate kinase: the important structural role of the P-loop lysine. Protein Science, 2001, 10, 1137–1149. 23. L.-N. Lin, J. F. Brandts, J. M. Brandts, and V. Plotnikov, Determination of the volumetric properties of proteins and other solutes using pressure perturbation calorimetry. Analytical Biochemistry, 2002, 302, 144–160. 24. L. Mitra, N. Smolin, R. Ravindra, C. Royer, and R. Winter, Pressure perturbation calorimetric studies of the solvation properties and the thermal unfolding of proteins in solution - experiments and theoretical interpretation. Physical Chemistry Chemical Physics, 2006, 8, 1249–1265. 25. A. Cooper and C. A. Converse, Energetics of primary processes in visual excitation: photocalorimetry of rhodopsin in rod outer segment membranes. Biochemistry, 1976, 15, 2970–2978. 26. A. Cooper, Calorimetric measurements of light-induced processes. Methods in Enzymology, 1982, 88, 667–673. 27. A. Cooper, Energy uptake in the first step of visual excitation. Nature, 1979, 282, 531–533. 28. P. Johansson and I. Wads¨o, A photo microcalorimetric system for studies of plant tissue. Journal of Biochemical and Biophysical Methods, 1997, 35, 103–114. 29. K. S. Cameron, J. K. Clark, A. Cooper, L. Fielding, R. Palin, S. J. Rutherford, and M. Q. Zhang, Modified gamma-cyclodextrins and their rocuronium complexes. Organic Letters, 2002, 4, 3403–3406. 30. V. Plotnikov, A. Rochalski, M. Brandts, J. F. Brandts, S. Williston, V. Frasca, and L. N. Lin, An autosampling differential scanning calorimeter instrument for studying molecular interactions. Assay and Drug Development Technologies, 2002, 1, 83–90. 31. M. A. Paulik, R. G. Buckholz, M. E. Lancaster, W. S. Dallas, E. A. Hull-Ryde, J. E. Weiel, and J. M. Lenhard, Development of infrared imaging to measure thermogenesis in cell culture: thermogenic effects of uncoupling protein-2, troglitazone, and beta-adrenoceptor agonists. Pharmaceutical Research, 1998, 15, 944–949.
MICROCALORIMETRY AND RELATED TECHNIQUES 32. F. E. Torres, P. Kuhn, D. De Bruyker, A. G. Bell, M. V. Wolkin, E. Peeters, J. R. Williamson, G. B. Anderson, G. P. Schmitz, M. I. Recht, S. Schweizer, L. G. Scott, J. H. Ho, S. A. Elrod, P. G. Schultz, R. A. Lerner, and R. H. Bruce, Enthalpy arrays. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101, 9517–9522. 33. E. A. Johannessen, J. M. R. Weaver, L. Bourova, P. Svoboda, P. H. Cobbold, and J. M. Cooper, Micromachined
11
nanocalorimetric sensor for ultra-low-volume cell-based assays. Analytical Chemistry, 2002, 74, 2190–2197. 34. E. B. Chancellor, J. P. Wikswo, F. Baudenbacher, M. Radparvar, and D. Osterman, Heat conduction calorimeter for massively parallel high throughput measurements with picoliter sample volumes. Applied Physics Letters, 2004, 85, 2408–2410.
40 Magnetic Biosensor Techniques Christopher H. Marrows School of Physics and Astronomy, University of Leeds, Leeds, UK
1 INTRODUCTION
Typical biosensor schemes involve the attachment of some sort of labeling moiety to the biomolecule in question via a specific biochemical binding event. The label possesses some physical property that can then be detected by an appropriate sensor technology, for instance, radioisotopes, enzymes, and fluorescent or charged molecules have been used in the past.1 Magnetism is an excellent means to interact with the biological system of interest, as magnetic fields will not interfere with or perturb the biochemistry in question at all. Moreover, they can penetrate turbid media (e.g., within cells) without attenuation or susceptibility to interference associated with optical probes. Magnetic tags have very stable properties over time as they are unaffected by any reagent chemistry and do not suffer from photobleaching. Moreover, they are straightforward to detect, since there is negligible magnetic background signal in biological samples of interest. The use of magnetic tagging of biological objects (e.g., DNA,2 proteins,3 or bacteria4 ) with microspheres containing magnetic materials has found several uses: for instance, in cell separation; to sort, detect, and remove cancer cells;5 or separate and collect particular molecules of interest.6 DNA was extracted from cells using immunomagnetic separation in the human genome project, following the use of antibodies to provide selective linkages. Here some current biosensor schemes based on the detection of magnetic microbeads and
nanoparticles are reviewed. All rely on the analyte binding to a suitably functionalized magnetic label or tag, which then transforms the task from detecting a particular biochemical entity to that of detecting the magnetic moment of the label. A schematic of this scheme is shown in Figure 1. A variety of micro- and nanoscale magnetometers are available that can be used for this purpose. In particular, magnetoresistive sensors, used in the hard disk industry as playback heads, are convenient to fabricate into an integrated lab-on-chip geometry, and these will be discussed at some length. It is also possible to apply forces to the magnetic labels with field gradients, allowing biochemical cargoes to be transported around the chip surface. First, however, we will look at a selection of the labeling methods that have been used to date.
2 MAGNETIC LABELS
There are demanding requirements for the magnetic tags themselves: the force that can be applied to them and the field that they generate are proportional to the magnetic moment, which scales with the particle volume. High-moment-density (magnetization) materials are therefore needed to operate effectively at the nanoscale. All studies so far where tags have been successfully sensed have used large numbers of magnetic nanoparticles encapsulated in a polymer microbead—this also provides a density similar to that of water
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
Beads
Analyte
Sensor A
Sensor B
Sensor C
Figure 1. Principle of a common scheme for biosensor operation. An array of individually addressable magnetic field sensors are fabricated on a chip surface, and each is functionalized with a receptor molecule (e.g., a strand of complementary DNA or a suitable antibody) for a particular analyte. The sample is then washed over the sensors, and binding will occur over any sensor functionalized with a suitable receptor. Magnetic microbeads are then washed over the chip, suitably functionalized to bind to any analyte: in the case of DNA detection, it is common to prepare a sample in which the analyte DNA is suitably biotinylated and use microbeads that are coated in streptavidin. After a final wash, beads will be immobilized only over the appropriate sensor. In the example shown here, only analyte B is detected in the sample, whereas analytes A and C are not found.
allowing suspension in solution, although in a suitable field gradient any magnetic particle can be given positive, negative, or neutral buoyancy. The material must also be biocompatible: core–shell structures (e.g., Fe/Au7 or Co embedded in polymers8 ) have also been studied, although magnetite9 satisfies this requirement and is therefore a popular choice for study. Particles of 30 nm diameter (intermediate between Fe3 O4 and γ -Fe2 O3 ) have been formed at 3–20 ◦ C and neutral pH allowing immobilization of biomolecules on the surface during synthesis,10 and particles as small as 7 nm have been shown to be chemically and magnetically stable over many months.11 Particles as small as 10 nm have been previously demonstrated with immobilized trypsin on the surface,3 but these are too small to be magnetically separable given the low magnetization of magnetite. More novel structures are multicomponent magnetic nanowires,12 synthesized by electrodeposition into a narrow pore. These have proved effective for cell separation,13 and form the basis of a novel cell positioning system.14 The multicomponent nature of the nanowires means that different regions can be
selectively functionalized.15 A nonviral, versatile gene delivery system with a high transfection ratio has been demonstrated based on this technology.16 A review of magnetic carriers for various biochemical and biomedical applications has been given by Hafeli et al.17 Commercial suppliers of these particles include Invitrogen,18 Bangs Laboratories,19 and Micromod.20 Micromer-M 2µm particles manufactured by Micromod are shown in Figure 2. It is worth noting a point of basic magnetism here. Magnetic particles will naturally tend to be attracted to one another and form aggregates. One way to prevent this is to surround the particle with a suitable coating to ensure that surface forces provide a proper dispersion in solution, for example, triblock copolymers with hydrophilic tail groups were used to perform this task for the magnetite nanoparticles prepared by Harris et al.9 However, very small magnetic entities often do not possess a large enough energy barrier against magnetization reversal by random thermal fluctuations of the moment direction. Such particles are said to be superparamagnetic and do not possess a permanent magnetic moment as it is fluctuating randomly in direction at, roughly, gigahertz frequencies. There are hence no magnetic forces between such particles. The obvious drawback to this is that there is now no magnetic moment to detect in a biosensor. This is restored by applying an external field to the
7
2 µm
Magnetic moment per particle (Am2)
2
10−12 10−14 Measured Datasheets Nickel Cobalt Iron Iron oxide
10−16 10−18 0
(a)
(b)
0.4 0.8 1.2 1.6 Size label (µm)
2
Figure 2. Magnetic particles used for labeling. (a) Scanning electron micrograph of 2-µm magnetic microspheres. (b) Magnetic moment per bead for commercial particles containing iron oxide (filled dots are values derived from datasheets, hollow dots are measurements) and Co, Fe, Ni particles (lines are calculated from bulk magnetization values). [Reprinted with permission Lagae et al.84 Institution of Engineering and Technology.]
MAGNETIC BIOSENSOR TECHNIQUES
particles, which partially overcomes the fluctuations and produces a definite moment along the field direction—this can be tuned to be of an appropriate size as it will be proportional to the applied field. If this field is uniform, it will not apply any force to the particles, since they possess magnetic dipoles—a gradient is necessary to do this. In many of the studies, we mention in the subsequent text, superparamagnetic labels have been used that are rendered detectable by applying a uniform field when sensing.
3 LABEL MANIPULATION
Before moving on to a discussion of sensing the particles, it is worthwhile to pause and consider how forces may be applied to them so that the magnetic tag may be used as a handle as well as a label. This would be important in developing a fully magnetically driven lab-on-achip technology, and we shall see below that this
3
can be used in many ways in conjunction with sensors to enhance their utility and functionality. We deal with these cases in the appropriate section on sensors. Here we discuss purely manipulative techniques that make use of magnetism. One of the best known of these are the magnetic tweezers that have been developed to apply forces in the nanonewton regime to bind magnetic particles.21 In this particular example, cell stiffness in single vinculin-deficient mouse cells was measured. A schematic of the instrument used is shown in Figure 3. Cell mechanics have also been studied through the technique of microrheology using magnetic beads, one of the techniques reviewed by Mackintosh and Schmidt.22 The mechanics of a single DNA molecule were investigated with this technique as long ago as 1995 by Wirtz,23 with the motion being detected via a fluorescent label attached to the DNA strand. Measurements of ligand–receptor (streptavidin–biotin and avidin–biotin) bond forces have been carried out by magnetic means using nanoparticles.24 A force differentiation immunoassay that operates
Magnet positioned with micromanipulator M Beads
37 °C incubator
CCD camera
Microscope
Water
0 −15 V variable power supply
Pe ri pu stal m tic p
Cold water bath
Figure 3. Diagram of a magnetic tweezer. The goal of the magnetic tweezer technique is to arrange a small “tug-of-war” between the electromagnet and the cell. The magnet is mounted on a micromanipulator secured to a light microscope, with the entire working area heated to 37 ◦ C and cold water circulating through the brass housing of the magnet to prevent overheating of the wire as high current passes through it. A microscopic view (inset) of the area on the coverslip shows the beads (4.5 µm diameter) bound to the surfaces of cultured cells relative to the position of the tip of the magnet. [Reprinted from Alenghat et al.21 with permission from Elsevier (copyright 2000).]
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
by selectively binding the analyte in question to magnetic microbeads and then to a surface25 is a direct precursor of the techniques below. In this experiment, the bound particles are detected and counted using an optical microscope; it is a natural extension of the method to use the same magnetic particles that provide the force selectivity in the assay to provide the readout as well by magnetic means. In all these cases, the field and field gradient were generated using external coils surrounding the sample. More recently, conducting wire arrays have been developed to move magnetic microspheres around in arbitrary ways on the surfaces of biochips.26 A ring trap has been developed to localize the particles in a particular spot on the surface, while a two-dimensional array of wires allows a magnetic potential well to be formed and moved around arbitrarily on the surface: this functionality is demonstrated in Figure 4. Biological cargoes attached to magnetic nanoparticles will be transported across the chip surface as the well is moved. More than one well can be combined, allowing different biochemical reagents to be brought together for reaction at a specific location on the chip, facilitating a nanoscale biochemical assembly line. These methods have been applied to the manipulation of magnetotactic bacteria to assemble arrays of magnetic nanoparticles.27 It has been shown that a similar system, albeit on a much larger scale, can be fabricated using so-called soft lithography methods.28 The combination of magnetic control and drive with microfluidics also offers interesting opportunities. It has been shown that directed transport will be needed to realize optimal sensitivity to biomolecules in solution.29 Microfabricated tools for positioning and sensing magnetic microcarriers have been developed by Tondra et al.30 which incorporate giant magnetoresistance (GMR) sensors of the type discussed in the subsequent text. A magnetic microcarrier diverter, based on these principles, was reported by this group.31 Magnetic labels reaching a Y-shaped junction in a microfluidic channel can be directed to flow into only one or other branch of the junction with very high fidelity. Other examples of magnetically driven actuation for microbeads include a filterless magnetic separator,32 a microfluidic pump without moving parts,33 and a complex manipulation system
10 µm
(a)
20 µm
(b)
10 µm
(c)
Figure 4. (a) Demonstration of the movement of a group of superparamagnetic particles over two wires of a microelectromagnet matrix. The wire currents were adjusted so they continuously move particles by increments that are less than the wire spacing. The size of the particle group is broader above the wire. (b) A group of particles is moved vertically by the matrix over a longer range of five wire spacings. (c) Two groups of particles are moved diagonally to join them together at a single location. Particles can be moved diagonally at any angle. Current was passed through all 14 wires for the demonstrations shown. [Reused from Lee et al.26 copyright 2001, American Institute of Physics.]
incorporating valves, flow sensors, biofilters, and electrochemical immunosensors.34 We now turn to the various magnetic sensors that can provide readout in a magnetically driven lab-on-a-chip system.
4 BIOSENSOR TECHNOLOGIES 4.1
Magnetic Biosensors
It is of course necessary to be able to sense these particles, and a high-performance sensor is required to be able to detect such a small magnetic moment reliably and in an acceptably short time. In almost all cases described in the subsequent text, the standard sensing technique is a form of
MAGNETIC BIOSENSOR TECHNIQUES
maximum. The method was subsequently refined using a gradiometer scheme which resulted in a two-order-of-magnitude improvement in detection sensitivity.36 Although not necessary to use a SQUID, this particular measurement protocol has a one-shot character and cannot be used to acquire continuous time series of data. A similar technique was reported by Kotitz et al.37 A similar SQUID method was reported by Katsura et al. who anchored magnetite nanoparticles to a glass coverslip using a selective DNA-based binding technique.38 This was then scanned over the high-TC SQUID, which was held at 77 K behind a quartz window. The pattern of DNA bound to the coverslip was reproduced by the sensor: typical SQUID time traces and a schematic of the measurement arrangement are shown in Figure 5. Other groups have also explored SQUID-based microscopy39 for biological measurements as well as biosensing.40–42 However, the fact that SQUIDs must operate at cryogenic temperatures means that they cannot be integrated into lab-on-a-chip designs or otherwise made easily portable, a significant disadvantage to use in the field, and this seems destined to remain a laboratory-based technique. Room-temperature sensors are obviously much more attractive on these grounds. A tried and 1
Si chip
Sample 293 K
Flux (mF0)
noncompetitive immunoassay and is as follows. The magnetic labels are functionalized and hence attached to the analyte in question. An area on the sensor is then functionalized in a complementary way, so that when a labeled analyte passes over the sensor, a ligand–receptor binding event will take place. The magnetic moment of the labels bound to the sensor will be proportional to the quantity of analyte to be measured, and can hence be determined by magnetometry. The essential feature of this is that the analyte must bind to both the label and the sensor, and the system will work equally well if this takes place in the opposite order to that given above. This was the scheme outlined in Figure 1. One of the most sensitive magnetometers of all is the superconducting quantum interference device (SQUID), which operates on the basis of the Josephson effect. This converts a magnetic flux into an electrical current, and hence a measurable voltage signal. A recent demonstration of the use of a SQUID as a biosensor was reported by Chemla et al.35 who used a dc SQUID fabricated from the high-temperature superconductor YBa2 Cu3 O7–x to detect ∼35-nm-diameter magnetite nanoparticles. The SQUID was contained within a vacuum cavity and held at 77 K using liquid nitrogen, 40 µm from a silicon nitride membrane. The sample is at room temperature and pressure outside the membrane, and for this demonstration, consisted of a Mylar membrane which has been coated in liposomes carrying the FLAG epitope, immersed in a solution of the magnetite nanoparticles bound to the appropriate antibody. Given an appropriate period of time, the antibodies will bind to available receptors on the liposomes. The operating principle is that the antibody concentration can be measured by applying a field pulse, which will magnetize the nanoparticles, which will then relax. The superparamagnetic N´eel relaxation takes place on a timescale τN that is much longer than that due to Brownian motion τB . Since the unbound particles will undergo the Brownian relaxation, they rapidly lose their moment, on a timescale of microseconds in this case. Meanwhile the bound ones remain magnetized for much longer (up to 1 s in this example), and their remanent moment can then be measured by the SQUID magnetometer. An ultimate sensitivity of around 104 nanoparticle labels was achieved with this particular sensor scheme, in close accord with the theoretical
5
SiN window
0.5
Sapphire rod
77 K SQUID
0 0 0
0.1
0.2 Time (s)
0.3
0.4
Figure 5. Upper trace: Magnetic background detected by the magnetometer in response to a 0.3-mT field, fitted to (t) = offset + s e−t/τ (dotted line); lower trace: background detected by the gradiometer in response to a 1.2-mT field. The field applied was pulsed on for 1 s and off for 1 s, and data were recorded each time the field was turned off; 100 averages were taken. Inset: Configuration of the SQUID microscope. The sample, at room temperature and atmospheric pressure, is 100 µm above the SQUID, which is at 77 K and in vacuum. [Reused from Lee et al.36 copyright 2002, American Institute of Physics.]
6
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
tested magnetic sensor technology is the Hall effect, which has been widely deployed in a variety of applications for decades. Biosensor designs based on microscale Hall crosses have been put forward. For instance, Besse et al. have demonstrated the detection of a 2.8-µm-diameter magnetic microbead using a Si Hall sensor fabricated using standard CMOS processing techniques,43 as shown in Figure 6. Two different detection protocols were used: an apparent susceptibility measurement and one based on second harmonic measurement that overcomes the offset problem of the previous technique. By functionalizing both the bead and the sensor surface, full biosensing activity may be brought about using this scheme. Magnetoresistive devices are also attractive prospects, and the most technologically straightforward scheme, at least in terms of sensor construction, is to exploit the anisotropic magnetoresistance (AMR).44
This is because the sensor consists of a single microfabricated element of magnetic material, most often permalloy (Ni80 Fe20 ), the resistance of which depends on the relative directions of the element’s magnetization M and the current density J flowing through it in proportion to (M·J)2 . Such devices were successfully implemented as the first generation of playback heads in hard disk drives owing to the simplicity of fabrication and the fact that they could be easily biased to give a linear output.45 However, the fractional change in resistance (the magnetoresistance ratio) is limited to ∼1–2% for this effect, meaning that high signal-to-noise ratios are difficult to achieve. However, the angular dependence of the effect was cleverly exploited by Miller et al. who built ring-shaped sensor devices from permalloy,46 connected with two wires on either side of the sensor so that the two halves of the ring form parallel conduction paths. In equilibrium, the
H0+H2
Ib
Z (a)
H1
VH
Y X
Superparamagnetic bead
ac current source
H2
Reference lock-in amplifier
H1 dc current source
(b)
dc current source
H0
Figure 6. Schematic view of the Hall effect measurement setup. A single superparamagnetic bead is centered on a Hall sensor, biased with the current Ib . A dc magnetic field H0 is applied perpendicular to the sensor. An ac field is added either in the z direction (H2 ) or in the x direction (∼H1 ). The Hall voltage VH , containing a component proportional to the magnetic induction produced by the bead, is measured with a lock-in amplifier. [Reused from Besse et al.43 copyright 2002, American Institute of Physics.]
MAGNETIC BIOSENSOR TECHNIQUES
magnetization of the ring forms a flux-closed loop, which is an extremely stable state. Moreover, even if the device enters the metastable so-called onion state47 with two halves of the ring magnetized with opposite chirality, the resistance from one side of the ring to the other will be unchanged since the magnetization is still essentially circumferential and hence parallel to the current flow. A vertical field was applied that was strong enough to magnetize the superparamagnetic label particle to be detected, but too weak to perturb the magnetic state of the sensor other than by causing a weak out-of-plane canting of the moments. However, when such a magnetized label was placed over the sensor—in this case using an antiferromagnetic atomic force microscope (AFM) tip—the radial field components that it generated splayed out the magnetization of the ring (as shown in Figure 7) so that it was now orthogonal to the current everywhere around the ring, causing a drop in resistance that was measured using phasesensitive detection—signal-to-noise ratios of better than 102 were claimed during the detection of a
4.3-µm-diameter Ni70 Fe30 sphere. A useful feature of this design is that the ring can be matched in size to the diameter of the sphere to be measured, so that single-label sensitivity can be ensured. This feature does prevent convenient label counting, however. Another physical consequence of the AMR is that small transverse voltages are generated across the sides of a conductor when it is magnetized in plane, known as the planar Hall effect. This was exploited by Ejsing et al. who patterned sensor devices consisting of a Hall cross of active area 10 × 10 µm2 from IrMn/NiFe bilayers.48 The antiferromagnetic IrMn layer is there to provide an exchange bias and keep the NiFe in a well-defined single-domain state in small applied fields. When drops of solution were placed on the sensor under weak magnetizing fields, easily resolved voltage changes were observed without difficulty using simple dc measuring techniques, allowing measurements to be made at the few-label level. Single 250-nm-diameter label detection is projected using this method.
4.2
(a)
I M
(b)
Figure 7. Schematic diagram of the function of the AMR ring sensor. The hatched areas represent the contact fingers. (a) Maximum resistance state in which the current I is mostly parallel or antiparallel to the circumferential magnetization M. (b) Minimum resistance state in which I is mostly normal to M. [Reused from Miller et al.46 copyright 2002, American Institute of Physics.]
7
Spintronic Biosensors
A more sensitive technology is the GMR,49 now ubiquitous as the means by which the playback head of all high-density hard disk drives operate—AMR has been entirely superseded by this new technology for a few years at the time of writing. This technology is being adopted to design improved biosensors.50 The field has recently been reviewed by Graham, Ferreira, and Freitas.51 To briefly summarize the principles of operation of a GMR device, it consists at its core a pair of ferromagnetic layers that can have their moments arranged in a mutually parallel (P) or antiparallel (AP) fashion by the application of a small field to be sensed. The layers are separated by the thin spacer layer, usually only ∼2 nm thick. Such a device is known as a spin valve and operates as a spin polarizer–analyzer experiment. The first magnetic layer spin polarizes the electrical current, so that it is predominantly carried by electrons of only one spin; this current is then analyzed by the second magnetic layer which allows it to pass relatively unimpeded if its magnetization direction matches the spin polarization of the current (P state): the overall resistance is low. On the other hand, if the magnetization is oppositely
8
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
directed (AP state), then the spin-polarized current will be scattered more strongly and the resistance will rise. Since the electrical conduction of a current in a GMR device depends on the spin polarization of that current, it is a member of the larger class of spintronic devices.52 A typical layer stack is shown in Figure 8. Usually a fixed sense current is used and as the field to be sensed is varied and the device switches between the P and AP states, the resistance of the device, and hence the voltage dropped across it, will vary. In comparison to the AMR sensor, the available magnetoresistance ratios are much higher, in the range of 5–20% at room temperature. Typically the spacer layer is Cu, while the ferromagnetic layers are alloys of Co, Ni, and Fe, often laminated to provide high spin-dependent scattering at the interfaces with the spacer, while another material is used to give low magnetostriction and proper magnetic switching behavior. With appropriate biasing, this can be a linear response to field within some dynamic range set by the saturation field. As an alternative to a two-magnetic-layer spin-valve device, a multilayer of many repeats of ferromagnet and spacer layer can be used, with
Ta (45 Å) IrMn (75 Å)
Pinne d GMR
NiFe (35 Å) Co (5 Å)
active
Cu (25 Å)
region
Co (5 Å)
Free
NiFe (35 Å) Ta (45 Å) Si
Figure 8. A spin-valve layer stack, with examples of typical layer materials and thicknesses. At its heart is a ferromagnet–spacer–ferromagnet sandwich (labeled GMR active region), where the two layers can be arranged in parallel or antiparallel states by switching the magnetization direction of the so-called free layer with a small applied field. The magnetization direction of the pinned layer is held fixed in these fields by the adjacent antiferromagnetic IrMn layer. The electrical resistance of the spin valve changes when the reorientation of the free layer occurs. In this example, the ferromagnetic layers are laminated bilayers: the permalloy (NiFe) provides low magnetostriction and a soft magnetic response, while Co acts as a diffusion barrier and boosts the GMR ratio.
the spacer-layer thickness tuned to provide an AP alignment in small fields. Such multilayers can have a GMR ratio of up to 75% at room temperature, but the fields required to provide a P alignment are many orders of magnitude larger than in the spin valve, decreasing the overall sensitivity. As with an AMR or planar Hall sensor, a GMR device is sensitive to in-plane components of the magnetic field, unlike a conventional Hall effect sensor or a SQUID. One of the pioneering groups in the field is based at the Naval Research Laboratory in Washington DC. They have demonstrated their bead array counter (BARC) technology in a series of papers.53–56 It is a portable, briefcase-sized immunoassay system that can screen for many different pathogens in minutes—up to 64 in the implementation described in Ref. 54. This system is based on magnetic multilayer technology, which offers a high GMR ratio but only over a wide field range, giving a low overall sensitivity for the device. The principle is that a sample flows through a liquid cell that contains a chip with an array of GMR sensors which are passivated below a layer of silicon nitride, followed by a layer of silicon oxide, on top of which regions may be functionalized with an appropriate biochemical binding site. Photographs of such a biochip, as well as the complete portable system are shown in Figure 9. Initial development of the BARC used a DNA hybridization assay, rather than an immunoassay, as arrays containing thousands of DNA probes are, compared to the large number of antibodies needed for immunoassay, relatively straightforward to synthesize and are already commercially available.57 Suitable DNA probes may be covalently immobilized by any technique suitable for galls or silica surfaces, for example, the aminosilane method of Chrisey et al.58 These passivation layers mean that the chip can be operated in saline solution. For each DNA sequence to be detected in the sample, an oligomer probe that is complementary to that sequence is immobilized over a particular GMR sensor (or group of sensors). One performs a polymerase chain reaction (PCR) on the sample, which is then biotinylated and flowed over the sensor array. Any DNA targets present in the sample will bind to the sites above the appropriate sensor. Streptavidin-funtionalized magnetic microbeads are then introduced and will bind
MAGNETIC BIOSENSOR TECHNIQUES
9
Sensor chip, quartz flow cell, and carrier board Close up of sensor and flow cell
1 mm (a)
(b)
Data aquisition and analysis computer
Assay cartridge Magnetics and electronics (c)
Figure 9. Different aspects of the BARC sensor prototype. (a) The BARC chip with flow cell mounted on the chip carrier board, which is mounted in the assay cartridge. (b) Magnified view of the 5 × 5 mm2 BARC chip with flow cell. (c) The tabletop unit containing all electronics, electromagnet, assay cartridge (with BARC chip, flow cell, etc.), and computer. [Reprinted from Miller et al.55 with permission from Elsevier (copyright 2001).]
to any biotin available on the analyte. Following a wash or application of a magnetic force to remove any unbound magnetic labels, a measurement of the resistance of each sensor will reveal the presence of that particular DNA target in the sample. To optimize signal-to-noise ratio, a Wheatstone bridge is used for each sensor, where one arm is the active sensor and another is a nonfunctionalized reference GMR element. The superparamagnetic labels are magnetized by an ac field that is applied perpendicular to the chip surface and so does not affect the sensors, as GMR devices have excellent off-axis signal rejection. However, a perpendicularly magnetized bead will generate in-plane field components that will modify the GMR device resistance, and the voltage across the bridge is measured using a lock-in amplifier. Increasing the modulation frequency allows one to improve the signal-to-noise ratio by reducing 1/f noise, so that the overall noise
can be lowered to the Johnson noise floor of the GMR element and associated wiring. The BARC chip and its successors (BARC-II and BARC-III, which feature larger, serpentine-pattern sensors) are designed to operate with M-280 “Dynabeads”, 2.8-µm-diameter polystyrene spheres embedded with, about 6% by volume, ∼15-nm-diameter γ -Fe2 O3 nanoparticles. An important advantage of this approach is that with a large array of small sensors, groups can be devoted to particular analytes, allowing the beads to be counted and a quantitative measure of the concentration of a particular analyte to be obtained. Although fabricating large arrays of GMR devices with all the appropriate wiring and detection electronics, including the passive reference devices, is taxing, this technology has been developed exactly for the construction of a magnetic random access memory (MRAM)59 by several different companies. An array containing
10
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
16 million devices for this purpose has been demonstrated recently,60 and still larger arrays are being planned. With this type of technology available, the scope for detecting a wide variety of different pathogens is limited by the biochemical functionalization rather than by the magnetic sensor technology. A similar sensor scheme, based on a GMR multilayer patterned into a spiral design, was recently reported by the Bielefeld group.61 This system made use of magnetic microspheres of 0.86 or 0.35 µm diameter from Bangs Laboratories, with a magnetite mass content of 46%. The spiral pattern is about 70 µm in diameter and is designed to fit within a pin spot of DNA probe material, which is about 100 µm in diameter. In this particular implementation, 15 different DNA sequences could be probed for. The principle of operation is very similar to the BARC scheme—biotinylated PCR product obtained from the sample is washed over the chip followed by streptavidin-coated magnetic microspheres. As more microspheres bind to the probe spot above the sensor, its resistance decreases and a signal for the concentration of that particular DNA sequence in the sample is obtained within minutes when a vertical field is applied to the chip to magnetize the labels. The estimated sensitivity of this scheme is about 400 molecules per probe spot for 100% binding. This was reckoned to be about a factor of 102 more sensitive than fluorescent detection. This comparison was made explicitly in a follow-up paper,62 where a larger, 206-element array of spirals was used, covered with appropriate DNA probe spots of varying concentration. An identical array of spots was placed on a polymer-coated glass slide for fluorescence measurements. Both chips were then washed in biotinlabeled complementary DNA analyte, and then different labels were applied to each chip: either streptavidin-coated 0.35-µm microspheres for the magnetic biochip or Cy3 streptavidin markers for the fluorescence experiment. The sensitivity of the magnetic scheme was found to be about three times higher for low probe DNA concentrations, corresponding to about 8% of probe DNA strands successfully hybridizing. Two schemes are proposed that could improve this: these arrays are hand spotted and a piezo electric spotter leads to better spot homogeneity. Smaller labels will reduce steric effects and allow better binding—as
the probe concentration increases, the fraction of successful binding events dropped as saturation was approached. The magnetic behavior of these multilayer sensors was reproduced accurately by modeling of the application of in-plane and out-ofplane fields.63 This group has also performed the first (and perhaps so far the only) detailed micromagnetic simulations of the interactions between a magnetic bead and the sensor multilayer stack.64 This included both coupled multilayers of the types used in the experiments described in the preceding text and also magnetic tunnel junction (MTJ) stacks. MTJs are similar to the GMR spin-valve sensors, described in the preceding text, in design, but have an ultrathin insulating layer instead of the Cu spacer.65 In most junctions, to date, this has been an amorphous Al2 O3 layer owing to the relative ease of fabrication, but other materials that offer higher performance are now under investigation.66 Although the underlying physics of their operation is entirely different because they operate in the tunneling rather than the diffusive transport regime, their use as a sensor is identical—the resistance is much higher when the two ferromagnetic electrodes are in an AP state as compared to a P state, referred to as tunneling magnetoresistance (TMR). High-quality aluminabased junctions show a magnetoresistance ratio of 50–70%. However, the greater resistance of a tunnel junction means that the Johnson noise floor is proportionately higher, potentially reducing the signal-to–noise ratio. The comparison of a GMR multilayer with an MTJ was also performed experimentally by this group, with the aim of designing a sensor capable of detecting a single magnetic tag.67 The TMR sensor was shown to be about four times more sensitive than the GMR multilayer. Single-marker sensitivity was tested by scanning a magnetic force microscope tip over an MTJ sensor. Suitable magnetic tags of an appropriate size have not yet been fabricated by any group, but the tip possesses a dipole moment comparable to that of a single label, showing that measurements at this level of sensitivity are, in principle, possible. A similar demonstration was carried out using lithographically patterned permalloy elements as test markers.68 The major commercial application of GMR devices is the read heads of hard disks, which are
MAGNETIC BIOSENSOR TECHNIQUES
based not on multilayers but more on the advanced structures described in the preceding text called spin valves that offer far superior sensitivity—as stated earlier. This is due to the switching into the P state in a very small magnetic field, which can be less than 1 Oe. Micron scale spin-valve sensor devices have been used at Stanford to detect a single 2.8-µm bead at a signal–noise ratio of 10:1.69 These sensors were also tested with 11-nmdiameter Co nanoparticles,70 and the capability of detecting less than 10 of these, perhaps as few as one, was projected, opening up the possibility of detecting single DNA fragments. The combination of high-performance spinvalve sensors with on-chip current lines to move magnetic labels to the sensing position is potentially a very powerful one. Tapering the lines is necessary in order to generate a field gradient that will be able to apply a force to the dipolar particles. Lagae et al. used this approach to both manipulate and magnetize the beads used as markers in their collaborative experiment between IMEC and INESC-MN,71 obviating the need for an external field to be applied. Indeed, in many cases the Oersted magnetic field generated by the sense current in the spin valve will be enough to magnetize the markers sufficiently well to provide a useful signal.72 In this case, 300-nm-diameter magnetite particles, most probably forming clusters, were used. The group of Freitas at INESCMN in Lisbon went on to use spin-valve sensors to perform single-label detection,73 sensing 2-µm iron oxide and 400-nm Fe-dextran particles undergoing streptavidin–biotin binding events at the single-marker level.74 Most recently, biomolecular recognition using a single 250-nm Nanomag-D label was achieved, with nearby on-chip tapered current lines used to direct the markers over the 2 × 6 µm2 sensor, as shown in Figure 10.75 These results were achieved without resorting to lock-in detection, although the differential sensor scheme, with a passive reference spin valve, was used. Since it is possible, in principle, to immobilize one biomolecule on a single label, this system shows the capability of performing single biomolecule detection.76 Such exquisite sensitivity is possible with GMR spin valves since they possess a superior signal-to-noise ratio to a TMR sensor and a far higher sensitivity than a GMR multilayer. Spin-valve GMR sensors have also been used to monitor microfluidic flows of oil by including
11
(a)
(b)
Figure 10. (a) Design including a spin-valve sensor (in the center of the micrograph between the contact leads) and adjacent tapered current lines for controlled placement and movement of the labels. (b) Current flows through the bottom current line attracting particles to the thinner region of the line. [Reused from Ferreira et al.75 copyright 2003, American Institute of Physics.]
picoliter ferrofluid droplets at regular intervals.77 INESC-MN also have a magnetoresistive flow meter based on spin-valve technology,78 intended for measuring flow velocities of biological fluids such as blood or plant sap through a microfluidic channel by incorporating superparamagnetic microbeads into the flow. As yet, there has not been a great deal of effort to build similar devices using TMR sensors, although these devices are now finding use in playback heads of high-density laptop disk drives after some years of speculation. As noted in the preceding text, since they are based on tunnel junctions, the high resistance of these sensors means that signal-tonoise ratios can be rather poor. High-sensitivity
12
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS Double-stranded DNA with biotin tag Magnetic particle stretavidin modified Silane SAM 400 s
Streptavidin
MFG Au SiO2
Passivating layer
SV
900 s
(a)
(b)
4
Sensor output (mV)
3
8. Sensor washed
4. Sensor washed 7. MFG lines switched off
3. MFG lines switched off 2
1
2. Add magnetically labeled target
5. Binding signal ~0.85 mV
0
6. MFG lines switched on and addition of labels
1. MFG lines switched on
0
9. Increased binding signal ~1.65 mV
400
(c)
800 Time (s)
1200
1600
Figure 11. Real-time experiment to detect cystic fibrosis genes. (a) Schematic principle for real-time detection of a CFTR gene sequence: DNA probe material is first immobilized on the chip surface; 250-nm particles functionalized with complementary and noncomplementary DNA targets are focused near the probe using the magnetic field generating (MFG) lines; unbound particles are washed away; only the particles bound to hybridized DNA targets are detected by the spin valve (SV). (b) Still images depicting the sensing region of the sensor during the real-time experiment. Images were taken during attraction to the MFG line (after 400 s), and after washing (after 900 s). (c) Real-time recorded sensor signal during the CFTR detection. In the case where the target is complementary to the probe, hybridization occurs and a residual signal of 0.85 mV remains after washing (case shown). In the case where target is noncomplementary (control sample), the sensor signal returned to the baseline in steps 5 and 9 (not shown). [Reproduced with permission from Lagae et al.84 Copyright 2005, Institution of Engineering and Technology.]
general-purpose TMR sensors have been demonstrated using alternating biasing scheme,79 which has also been used for GMR sensors.80 It is possible that efforts to make deep submicron sensors for single-molecule biosensor applications will require
a shift to TMR technology, since the resistance of a conventional current-in-plane GMR device will become too small to give a useful voltage signal for the levels of sense current that the device can tolerate without excessive heating.
MAGNETIC BIOSENSOR TECHNIQUES
5 CONCLUDING REMARKS
A variety of different sensor technologies have been reviewed in the preceding text, with some emphasis on GMR-based sensors since most of the relevant literature describes this approach. Each has its own advantages: for superior signal-tonoise ratio, a spin-valve sensor is superior; while for high dynamic range, a GMR multilayer sensor is better. The simplest to fabricate are planar Hall sensors, while AMR rings are a natural geometry for single microsphere detection. All are capable of being fabricated using standard planar technologies into useful lab-on-a-chip structures. The past few years have seen a large number of reports in the literature describing the way in which such devices could be most usefully engineered. In most of the work reviewed in the preceding text, the sensor performance was demonstrated using a well-known biochemical binding event such as avitin–biotin or streptavidin–biotin binding. There is now a trend among those groups who have a working sensor technology to try useful biochemical experiments using the new apparatus they have designed and refined. For instance, rapid DNA–DNA hybridization has been accomplished by the INESC-MN group in Lisbon using an ac magnetic field focusing method81 that is easily combined with a spin-valve sensor.82 This technology has now been used for genetic analysis to detect cystic fibrosis–related DNA targets (shown in Figure 11).83,84 The promise of portable bedside pathology units that are capable of providing results in minutes or even seconds on samples of a few microliters or less does not seem unrealistic with further developments in this field. In the future, a shift from DNA to protein chips for immunoassay seems likely, although the additional complications due to the secondary and tertiary structure of the proteins means that greater precision in biomolecular recognition will be required. There remains obvious promise in the field for new applications and technological breakthroughs. In particular, there remains enormous scope for developing lab-on-a-chip designs where magnetic actuation and sensing are combined to provide a selective protocol for carrying out a full biochemical process of arbitrary complexity at the picoliter level that could be capable of self-monitoring and handling conditional events such as automatic error correction. There is also a whole range of
13
interesting new possibilities that could arise if the magnetic labels could be shrunk below the size at which they could pass through a cell membrane without rupturing it—about 100 nm. This would allow manipulation and sensing of the internal structure of a living cell tethered to a chip surface.
REFERENCES 1. D. Ivnitski, I. Abdel-Hamid, P. Atanasov, and E. Wilkins, Biosensors for detection of pathogenic bacteria (Review). Biosensors and Bioelectronics, 1999, 14, 599. 2. Z. H. Fan, S. Mangru, R. Granzow, P. Heaney, W. Ho, Q. Dong, and R. Kumar, Dynamic DNA hybridization on a chip using paramagnetic beads. Analytical Chemistry, 1999, 71, 4851. 3. K. Nishimura, M. Hasegawa, Y. Ogura, T. Nishi, K. Kataoka, H. Handa, and M. Abe, 4◦ preparation of ferrite nanoparticles having protein molecules immobilized on their surfaces. Journal of Applied Physics, 2002, 91, 8555. 4. N. Nakmura, J. G. Burgess, K. Yaguida, S. Kudo, T. Sakaguchi, and T. Matsunaga, Detection and removal of escherichia coli using fluorescein isothiocyanate conjugated monoclonal antibody immobilized on bacterial magnetic particles. Analytical Chemistry, 1993, 65, 2036. 5. S. Sieben, C. Bergemann, A. L¨ubbe, B. Brockmann, and D. Rescheleit, Comparison of different particles and methods for magnetic isolation of circulating tumor cells. Journal of Magnetism and Magnetic Materials, 2001, 225, 175. ˇ ˇ 6. I. Safao´ ık and M. Safao´ ıkov´a, Use of magnetic techniques for the isolation of cells. Journal of Chromatography B, 1999, 722, 33. 7. B. Ravel, E. E. Carpenter, and V. G. Harris, Local structure of Core/Shell Fe/Au nanoparticles: Evidence for oxidized cores. Journal of Applied Physics, 2002, 91, 8195. 8. M. Rutnakornpituk, M. S. Thompson, L. A. Harris, K. E. Farmer, A. R. Esker, J. S. Riffle, J. Connolly, and T. G. St Pierre, Formation of cobalt nanoparticle dispersions in the presence of polysiloxane block copolymers. Polymer, 2002, 43, 2337. 9. L. A. Harris, J. D. Goff, A. Y. Carmichael, J. S. Riffle, J. J. Harburn, T. G. St Pierre, and M. Saunders, Magnetite nanoparticle dispersions stabilized with triblock copolymers. Chemistry of Materials, 2003, 15, 1367. 10. M. Tada, S. Hatanaka, H. Sanbonsugi, N. Matsushita, and M. Abe, Method for synthesizing ferrite nanoparticles? 30 nm in diameter on neutral pH condition for biomedical applications. Journal of Applied Physics, 2003, 93, 7566. 11. S. H. Gee, Y. K. Hong, D. W. Erickson, M. H. Park, and J. C. Sur, Synthesis and aging effect of spherical magnetite (Fe3 O4 ) nanoparticles for biosensor applications. Journal of Applied Physics, 2003, 93, 7560. 12. M. Chen, L. Sun, J. E. Bonevich, D. H. Reich, C. L. Chein, and P. C. Searson, Tuning the response of magnetic suspensions. Applied Physics Letters, 2003, 82, 3310.
14
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
13. A. Hultgren, M. Tanase, C. S. Chen, G. J. Meyer, and D. H. Reich, Cell manipulation using magnetic nanowires. Journal of Applied Physics, 2003, 93, 7554. 14. M. Tanase, D. M. Silevitch, A. Hultgren, L. A. Bauer, P. C. Searson, G. J. Meyer, and D. H. Reich, Magnetic trapping and self-assembly of multicomponent nanowires. Journal of Applied Physics, 2002, 91, 8549. 15. L. A. Bauer, D. H. Reich, and G. J. Meyer, Selective functionalization of two-component magnetic nanowires. Langmuir, 2003, 19, 7043. 16. A. Salem, P. C. Searson, and K. W. Leong, Multifunctional nanorods for gene delivery. Nature Materials, 2003, 2, 668. 17. U. Hafeli, W. Schutt, J. Teller, and M. Zborozski (eds), Scientific and Clinical Applications of Magnetic Carriers, Plenum, New York, 1997. 18. http://www.invitrogen.com/dynal, 2006. 19. http://www.bangslabs.com/, 2006. 20. http://www.micromod.de/, 2006. 21. F. J. Alenghat, B. Fabry, K. Y. Tsai, W. H. Goldmann, and D. E. Ingber, Analysis of cell mechanics in single vinculin-deficient cells using a magnetic tweezer. Biochemical and Biophysical Research Communications, 2000, 277, 93. 22. F. C. MacKintosh and C. F. Schmidt, Microrheology. Current Opinion in Colloid and Interface Science, 1999, 4, 300. 23. D. Wirtz, Direct measurement of the transport properties of a single DNA molecule. Physical Review Letters, 1995, 75, 2436. 24. M. Panhorst, P.-B. Kamp, G. Reiss, and H. Br¨uckl, Sensitive bondforce measurements of ligand-receptor pairs with magnetic beads. Biosensors and Bioelectronics, 2005, 20, 1685. 25. G. U. Lee, S. Metzger, M. Natesan, C. Yanavich, and Y. F. Dufrˆene, Implementation of force differentiation in the immunoassay. Analytical Biochemistry, 2000, 287, 261. 26. C. S. Lee, H. Lee, and R. M. Westervelt, Microelectromagnets for the control of magnetic nanoparticles. Applied Physics Letters, 2001, 79, 3308. 27. H. Lee, A. M. Purdon, V. Chu, and R. M. Westervelt, Controlled assembly of magnetic nanoparticles from magnetotactic bacteria using microelectromagnets arrays. Nano Letters, 2004, 4, 995. 28. T. Deng, G. Whitesides, M. Radhakrishnan, G. Zabow, and M. Prentiss, Manipulation of magnetic microbeads in suspension using micromagnetic systems fabricated with soft lithography. Applied Physics Letters, 2001, 78, 1775. 29. P. E. Sheehan and L. J. Whitman, Detection limits for nanoscale biosensors. Nano Letters, 2005, 5, 803. 30. M. Tondra, A. Popple, A. Jander, R. L. Mille, N. Pekas, and M. D. Porter, Microfabricated tools for manipulation and analysis of magnetic microcarriers. Journal of Magnetism and Magnetic Materials, 2005, 293(1), 725–730. 31. N. Pekas, M. Granger, M. Tondra, A. Popple, and M. D. Porter, Magnetic particle diverter in an integrated microfluidic format. Journal of Magnetism and Magnetic Materials, 2005, 293, 584. 32. J.-W. Choi, C. H. Ahn, S. Bhansali, and H. T. Henderson, A new magnetic bead-based, filterless bio-separator with planar electromagnet surfaces for integrated bio-detection systems. Sensors and Actuators, B, 2000, 68, 34.
33. J. Juong, J. Shen, and P. Grodzinski, Micropumps based on alternating high-gradient magnetic fields. IEEE Transactions on Magnetics, 2000, 36, 2012. 34. J.-W. Choi, K. W. Oh, A. Han, N. Okulan, C. A. Wijayawardhana, C. Lannes, S. Bhansali, K. T. Schlueter, W. R. Heinemann, H. B. Halsall, J. H. Nevin, A. J. Helmicki, H. T. Henderson, and C. H. Ahn, Development and characterization of microfluidic devices and systems for magnetic bead-based biochemical detection. Biomedical Microdevices, 2001, 3, 191. 35. Y. R. Chemla, H. L. Grossman, Y. Poon, R. McDermott, R. Stevens, M. D. Alper, and J. Clarke, Ultrasensitive magnetic biosensor for homogeneous immunoassay. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97, 14268. 36. S. Lee, W. R. Myers, H. L. Grossman, H.-M. Cho, Y. R. Chemla, and J. Clarke, Magnetic gradiometer based on a high-transition temperature superconducting quantum interference device for improved sensitivity of a biosensor. Applied Physics Letters, 2002, 81, 3094. 37. R. Kotitz, H. Matz, L. Trahms, H. Koch, W. Weitschies, T. Rheinlander, W. Semmler, and T. Bunte, SQUID based remanence measurements for immunoassays. IEEE Transactions on Applied Superconductivity, 1997, 7, 3678. 38. S. Katsura, T. Yasuda, K. Hirano, A. Mizuno, and S. Tanaka, Development of a new detection method for DNA molecules. Superconductor Science and Technology, 2001, 14, 1131. 39. F. Baudenbacher, N. T. Peters, and J. P. Wikswo Jr, High resolution low-temperature superconductivity SQUID microscopes for imaging magnetic fields of samples at room temperature. Review of Scientific Instruments, 2002, 73, 1247. 40. K. Enpuku, T. Minotani, T. Gima, Y. Kuroki, Y. Itoh, M. Yamashita, Y. Katakura, and S. Kuhara, Detection of magnetic nanoparticles with superconducting quantum interference device (SQUID) magnetometer and application to immunoassays. Japanese Journal of Applied Physics Part 2, 1999, 38, L1102. 41. K. Enpuku, T. Minotani, M. Hotta, and A. Nakahodo, Application of high Tc SQUID magnetometer to biological immunoassays. IEEE Transactions on Applied Superconductivity, 2001, 11, 661. 42. K. Enpuku, M. Hotta, and A. Nakahodo, High-Tc SQUID system for biological immunoassays. Physica C, 2001, 357, 1462. 43. P. A. Besse, G. Boero, M. Demierre, V. Pott, and R. Popovic, Detection of a single magnetic microbead using a miniaturized silicon Hall sensor. Applied Physics Letters, 2000, 80, 4199. 44. T. R. McGuire and R. I. Potter, Anisotropic magnetoresistance in ferromagnetic 3d alloys. IEEE Transactions on Magnetics, 1975, 11, 1081. 45. J. C. Mallinson, Magneto-Resistive Heads: Fundamentals and Applications, Academic Press, San Diego, 1996. 46. M. M. Miller, G. A. Prinz, S.-F. Cheng, and S. Bounnak, Detection of a micron-sized magnetic sphere using a ring-shaped anisotropic magnetoresistance-based sensor: A model for a magnetoresistance-based biosensor. Applied Physics Letters, 2002, 81, 2211. 47. J. Rothman, M. Kl¨aui, L. Lopez-Diaz, C. A. F. Vaz, A. Bleloch, J. A. C. Bland, Z. Cui, and R. Speaks,
MAGNETIC BIOSENSOR TECHNIQUES
48.
49. 50.
51.
52.
53.
54.
55.
56.
57.
58.
59. 60. 61.
62.
63.
64.
Observation of a bi-domain state and nucleation free switching in Mesoscopic Ring Magnets. Physical Review Letters, 2001, 86, 1098. L. Ejsing, M. F. Hansen, A. K. Menon, H. A. Ferreira, D. L. Graham, and P. P. Freitas, Planar Hall effect sensor for magnetic micro- and nanobead detection. Applied Physics Letters, 2004, 84, 4729. E. Yu. Tsymbal and D. G. Pettifor, Perspectives of giant magnetoresistance. Solid State Physics, 2001, 56, 113. M. Tondra, M. Porter, and R. J. Lipert, Model for detection of immobilized superparamagnetic nanosphere assay labels using giant magnetoresistive sensors. Journal of Vacuum Science and Technology A, 2000, 18, 1125. D. L. Graham, H. A. Ferreira, and P. P. Freitas, Magnetoresistive-based biosensors and biochips. Trends in Biotechnology, 2004, 22, 455. ˇ c, J. Fabian, and S. Das Sarma, Spintronics: funI. Zuti´ damentals and applications. Reviews of Modern Physics, 2004, 76, 323. D. R. Baselt, G. U. Lee, M. Natesan, S. W. Metzger, P. E. Sheehan, and R. J. Colton, A biosensor based on magnetoresistance technology. Biosensors and Bioelectronics, 1998, 13, 731. R. L. Edelstein, C. R. Tamanaha, P. E. Sheehan, M. M. Miller, D. R. Baselt, L. J. Whitman, and R. J. Colton, The BARC biosensor applied to the detection of biological warfare agents. Biosensors and Bioelectronics, 2000, 14, 805. M. M. Miller, P. E. Sheehan, R. L. Edelstein, C. R. Tamanaha, L. Zhong, S. Bounak, L. J. Whitman, and R. J. Colton, A DNA array sensor utilizing magnetic microbeads and magnetoelectronic detection. Journal of Magnetism and Magnetic Materials, 2001, 225, 138. J. C. Rife, M. M. Miller, P. E. Sheehan, C. R. Tamanaha, M. Tondra, and L. J. Whitman, Design and performance of GMR sensors for the detection of magnetic microbeads in biosensors. Sensors and Actuators, A, 2003, 107, 209. M. J. O’Donnell-Maloney and D. P. Little, Microfabrication and array technologies for DNA sequencing and diagnostics. Genetic Analysis, 1996, 13, 151. L. A. Chrisey, G. U. Lee, and C. E. O’Ferrall, Covalent attachment of synthetic DNA to self-assembled monolayer films. Nucleic Acids Research, 1996, 24, 3031. http://www.mram-info.com, 2006. http://www.nec.co.jp/press/en/0602/0702.html, 2006. J. Schotter, P. B. Kamp, A. Becker, A. P¨uhler, D. Brinkmann, W. Schepper, H. Br¨uckl, and G. Reiss, A biochip based on magnetoresistive sensors. IEEE Transactions on Magnetics, 2002, 38, 3365. J. Schotter, P. B. Kamp, A. Becker, A. P¨uhler, G. Reiss, and H. Br¨uckl, Comparison of a prototype magnetoresistive biosensor to standard fluorescent DNA detection. Biosensors and Bioelectronics, 2004, 19, 1149. W. Schepper, J. Schotter, H. Br¨uckl, and G. Reiss, A magnetic molecule detection system - a comparison of different setups by computer simulation. Physica B, 2006, 372, 337. W. Schepper, J. Schotter, H. Br¨uckl, and G. Reiss, Analysing a magnetic molecule detection system - computer simulation. Journal of Biotechnology, 2004, 112, 35.
15
65. E. Yu. Tsymbal, O. N. Mryasov, and P. R. Le Clair, Spindependent tunnelling in magnetic tunnel junctions. Journal of Physics: Condensed Matter, 2003, 15, R109. 66. S. S. P. Parkin, C. Kaiser, A. Panchula, P. M. Rice, B. Hughes, M. Samant, and S. H. Yang, Giant Tunneling Magnetoresistance at Room Temperature with MgO(100) Tunnel Barriers. Nature Materials, 2004, 3, 862. 67. M. Brzeska, M. Panhorst, P. B. Kamp, J. Schotter, G. Reiss, A. P¨uhler, A. Becker, and H. Br¨uckl, Detection and manipulation of biomolecules by magnetic carriers. Journal of Biotechnology, 2004, 112, 25. 68. H. Br¨uckl, M. Brzeska, D. Brinkmann, J. Schotter, G. Reiss, W. Schepper, P.-B. Kamp, and A. Becker, Magnetoresistive logic and biochip. Journal of Magnetism and Magnetic Materials, 2004, 282, 219. 69. G. Li, V. Joshi, R. L. White, S. X. Wang, J. T. Kemp, C. Webb, R. W. Davis, and S. Sun, Detection of single micron-sized magnetic bead and magnetic nanoparticle using spin valve sensors for biological applications. Journal of Applied Physics, 2003, 93, 7557. 70. S. Sun and C. B. Murray, Synthesis of monodisperse cobalt nanocrystals and their assembly into magnetic superlattices. Journal of Applied Physics, 1999, 85, 4325. 71. L. Lagae, R. Wirix-Speetjens, J. Das, D. Graham, H. Ferreira, P. P. Freitas, G. Borghs, and J. de Boeck, On-chip manipulation and magnetization assessment of magnetic bead ensembles by integrated spin-valve sensors. Journal of Applied Physics, 2002, 91, 7445. 72. H. A. Ferreira, N. Feliciano, D. L. Graham, and P. P. Freitas, Effect of spin-valve sensor magnetostatic fields on nanobead detection for biochip applications. Journal of Applied Physics, 2005, 97, 10Q904. 73. D. L. Graham, H. A. Ferreira, P. P. Freitas, and J. M. S. Cabral, High sensitivity detection of molecular recognition using magnetically labelled biomolecules and magnetoresistive sensors. Biosensors and Bioelectronics, 2003, 18, 483. 74. D. L. Graham, H. Ferreira, J. Bernado, P. P. Freitas, and J. M. S. Cabral, Single magnetic microsphere placement and detection on-chip using current line designs with integrated spin valve sensors: Biotechnological applications. Journal of Applied Physics, 2002, 91, 7786. 75. H. A. Ferreira, D. L. Graham, P. P. Freitas, and J. M. S. Cabral, Bio detection using magnetically labeled biomolecules and arrays of spin valve sensors. Journal of Applied Physics, 2003, 93, 7281. 76. M. A. Osbourne, W. S. Furey, D. Klenerman, and S. Balasubramanian, Single Molecule Analysis of DNA Immobilised on Microspheres. Analytical Chemistry, 2000, 72, 3678. 77. N. Pekas, M. D. Porter, M. Tondra, A. Popple, and A. Jander, Giant magnetoresistance monitoring of magnetic picodroplets in an integrated microfluidic system. Applied Physics Letters, 2004, 85, 4783. 78. H. A. Ferreira, D. L. Graham, P. Parracho, V. Soares, and P. P. Freitas, Flow velocity measurement in microchannels using magnetoresistive chips. IEEE Transactions on Magnetics, 2004, 40, 2652. 79. M. Vop´alensk´y, P. Ripka, J. Kub´ık, and M. Tondra, Alternating biasing of SDT sensors. Sensors and Actuators, A, 2004, 110, 182.
16
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
80. M. Vop´alensk´y, P. Ripka, J. Kub´ık, and M. Tondra, Improved GMR sensor biasing design. Sensors and Actuators, A, 2004, 110, 254. 81. H. A. Ferreira, N. Feliciano, D. L. Graham, L. A. Clarke, M. D. Amaral, and P. P. Freitas, Rapid DNA hybridization based on ac field focusing of magnetically labelled target DNA. Applied Physics Letters, 2005, 87, 013901. 82. D. L. Graham, H. A. Ferreira, N. Feliciano, P. P. Freitas, L. A. Clarke, and M. D. Amaral, Magnetic-field assisted DNA hybridisation and simultaneous detection using micron-sized spin-valve sensors and magnetic nanoparticles. Sensors and Actuators, B, 2005, 107, 936.
83. H. A. Ferreira, D. L. Graham, N. Feliciano, L. A. Clarke, M. D. Amaral, and P. P. Freitas, Detection of cystic fibrosis related DNA targets using ac field focusing of magnetic labels and spin-valve sensors. IEEE Transactions on Magnetics, 2005, 41, 4140. 84. L. Lagae, R. Wirix-Speetjens, C.-X. Liu, W. Laureyn, G. Borghs, S. Harvey, P. Galvin, H. A. Ferreira, D. L. Graham, P. P. Freitas, L. A. Clarke, and M. D. Amaral, Magnetic biosensors for genetic screening of cystic fibrosis. IEE Proceedings—Circuits Devices and Systems, 2005, 152, 393.
41 Introduction to Microfluidic Techniques Bernhard H. Weigl,1 Ron L. Bardell2 and Catherine Cabrera3 1
Department of Bioengineering, University of Washington, Seattle, WA, USA, 2 MicroPlumbers Microsciences LLC, Seattle, WA and Minneapolis, MN, USA and 3 Biosensor and Molecular Technologies, MIT Lincoln Laboratory, Lexington, MA, USA
1 INTRODUCTION
Microfluidics is the science of fluid flow in structures that have at least one dimension in the microscale (between 1 µm and 1 mm). According to this very broad definition, capillary electrophoresis (CE), flow injection analysis (FIA), small-diameter versions of high-pressure liquid chromatography (HPLC), and many other techniques would fall under the microfluidics umbrella. Therefore, a device is more commonly considered to be microfluidic if it has two or more of the characteristics listed below: • It comprises a channel network wherein the channels have microdimensions. • It is microfabricated into or from a solid substrate. • It integrates two or more discrete laboratory functions on a single chip. • Fluid flow in a microstructure is a required element of the analytical or preparative function of the device. This excludes microarrays, microtiter plates, and so on, from this more narrow definition. Other definitions related to microfluidics are also in common use. For example, a “lab on a chip” integrates several laboratory processes on a single chip. A “micro–total analysis systems
(µTAS)” integrates all laboratory processes required for an analysis on a single chip.1 However, in reality, many microfluidics researchers use the terms microfluidics, microfluidic devices, lab on a chip, and µTAS interchangeably. Furthermore, conferences under the microfluidics heading will usually feature talks on microarrays, and vice versa. In this chapter, we will therefore use a more practical approach to delineate microfluidics: microfluidics is what the literature and the researchers in the field call microfluidics. Many of today’s microfluidics researchers started their careers in optical or electrochemical microsensors. This is no coincidence. Microsensors hold much of the same promise that is now expected from microfluidic circuits—the possibility of designing a small, easy-to-use, fully integrated, chemical–analytical device. Microsensors do not only, to some extent, compete with microfluidic systems as tools for chemical and biological analysis, but they also frequently play an important part either during the development of microfluidics devices (e.g., pressure, flow, and temperature sensors) or as detector components in microfluidic systems. And conversely, microfluidic systems can provide an environment that enhances the performance characteristics of microsensors (e.g., by providing a constant and laminar flow past the sensor head).
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Microsensors can be physically placed in contact with microfluidic flow in a number of different ways. For example, both optical and electrochemical sensors can form one wall of a channel. True microdiameter sensors can also be placed in the center of a channel, although this has rarely proved beneficial, frequently causing the sensor to be less stable and prone to mechanical damage from dispersed particles and cells. Pressure and flow sensors are used to verify actual flow rates in microfluidic systems, and to calibrate micropumps. Honeywell, Inc. has developed a microflow sensor based on a differential heat-loss measurement2,3 that has been used in the development of microfluidic flow-cytometer circuits.4 Temperature probes are typically used as feedback systems for temperature-controlled microfluidic chambers, for example for polymerase chain reaction (PCR) heat-cycling applications.5 Many microsensors have also been used as detector elements in microfluidic circuits. Electrochemical and optical sensors are frequently used for detection of chemical species in small-diameter and microfluidic channels, such as in glucose monitors6 as well as in biotechnical process monitoring applications.7 Microfluidic devices are often described as miniature versions of their macroscale counterparts. While this analogy is true for some aspects of microfluidic devices, many phenomena do not simply scale linearly from large to small implementations. Examples include the following: increased surface area-to-volume ratio (actually this does scale linearly, but what it affects may not) and the omnipresence of laminar flow. The first commercial microfluidic lab-on-a-chipbased systems were introduced for life science applications less than 3 years ago. Since that time the field has also seen the formation of a number of diverse microfluidics companies, the publication of more than 3000 scientific papers on microfluidics, and development of several additional microfluidics-based products.8,9 The MIT Technology Review named microfluidics 1 of 10 technologies that will change the world and one of the many areas in which this will be seen is in the life sciences sector.10 In 2001, Larry Kricka surveyed the range of microanalytical devices, from microchips and gene chips to bioelectronics chips, and their impact on diagnostic testing.11 He predicted a move of clinical testing
from central laboratory to nonlaboratory settings with a positive impact on healthcare costs. During the bubble years of the late 1990s and early 2000s, the market growth for microfluidicsbased products was forecast to be several billion US dollars by 2004. Now, as with other markets, current growth forecasts are a much more modest, yet healthy, increase from US $127.8 million (2002) to $709.9 million by 2008.12 To date, several lab-on-a-chip companies, including Aclara (Mountain View, CA), Caliper (Mountain View, CA), Gyros AB (Uppsala, Sweden), and Orchid Biosciences (Princeton, NJ), have developed microfluidic technologies that work for highly predictable and homogeneous samples that are common in the drug discovery process, whether in compound screening, genomic analysis, or proteomics.13–19 The first generations of many of these systems address the non-FDAregulated life sciences research market. One of the primary challenges for homogenous samplebased lab chip providers, however, is their inability to perform analysis on-chip directly from normal, complex, and heterogeneous clinical samples, such as whole blood. Other companies active in the microfluidics area (e.g., Micronics, Redmond, WA; Cepheid, Sunnyvale, CA; MicroPlumbers Microsciences, Seattle, WA; and Fluidigm, San Francisco, CA) have tried to address this issue by their choice of chip materials, structure, and dimensions, by selecting a fluid transport method that is compatible with biological fluids, by employing various novel methods for sample preparation upstream of analysis, and by constructively allowing for the handling of blood and cell-laden streams on microchips.5,20–26
2 CHARACTERISTICS OF FLUID FLOW IN MICROCHANNELS
The behavior of fluids in the microscale is quite different from the macroscale behavior we are familiar with in our everyday lives, for example, water flowing from the tap into the kitchen sink or a spoon stirring cream and coffee in a cup. It is the interplay between fluid properties, flow properties, and the scale of the fluid passage that determines the way fluids behave. In this section we discuss how fluid passage dimensions affect both fluid properties and flow properties.
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
The term fluids includes both liquids and gases. We can utilize the kinetic theory of gases (there is no corresponding theory for liquids) to conceptualize important fluid properties. By this theory gas consists of molecules in constant motion, frequently colliding with walls and with each other. Pressure is the force per unit area imparted by the number of collisions between molecules and a unit area of surface. Temperature relates to the speed with which the molecules are traveling; higher temperature gives higher speed. Density is the product of molecular mass and the number of molecules per unit volume. The ideal gas law states that pressure is linearly proportional to the product of temperature and density. From the kinetic theory perspective it is easy to see how an increase in temperature or density would increase pressure. Unlike the molecules in gases, which have a nonzero mean free path (the average distance a molecule can travel between collisions), the molecules in liquids are so close together they are always exchanging momentum. However, liquids do not have the rigid structure of a solid and thus are able to deform when the physical shape of their container changes or a physical object moves through them (e.g., a spoon in a cup of coffee). Viscosity is the measure of the effort required to deform a fluid. Compare the effort required in walking on land (in air) with walking in neck-deep water. Viscosity is often introduced by discussing Couette flow, in which fluid is contained between a moving wall and a parallel stationary wall that are
a distance y apart (see Figure 1). In a macroscale Couette flow device, the fluid velocity immediately next to the wall will equal the wall velocity. This is referred to as zero slip. If the fluid is a Newtonian fluid, such as water, the fluid velocity will change smoothly from zero at the stationary wall to the velocity vwall at the moving wall. We can say the spatial gradient of the fluid velocity dv/dy is a constant. The viscosity µ is simply the proportionality constant between the shear stress τ applied to the fluid and the resulting velocity gradient, and thus τ = µ dv/dy. Shear stress is what you apply to lotion when you rub it between your hands (i.e., the lotion is experiencing Couette flow). But many fluids, particularly biological fluids, are not Newtonian. They may be shear thinning, shear thickening, dependent on shear history, or may require an initial shear stress that must be applied before they begin flowing, for example, blood. It is often helpful to use a consistent set of units that is tailored for the physical scale in which the processes of interest occur. We prefer the system shown in Table 1 that is based on grams, millimeters, and seconds. The flow behavior in a microdevice can be understood through dimensionless parameters such as the Knudsen, Peclet, Reynolds, and Bond numbers. Their definition includes a length scale, a characteristic dimension L, that varies with the geometrical shape of the fluid. In a droplet or round pipe, the diameter is appropriate. In other shapes, the “hydraulic diameter” concept of DH = 4 × area/wetted perimeter is useful. In a rectangular cross section, DH = 2/(1/height + 1/width). 2.1
dn dy
n(y )
Figure 1. Couette flow is the motion of fluid between two parallel plates, one stationary plate (on the left) and one moving. A Newtonian fluid exhibits a constant spatial gradient of its velocity.
3
The Knudsen Number – Fluid Continuum or Discrete Fluid Particles?
Though fluids are collections of discrete molecules, each with individual properties, it is mathematically simpler to define velocity, temperature, density, and pressure as statistically based properties in a continuum approximation. For the continuum concept to be valid, the smallest region of the flow field to which we assign averaged property values must contain a statistically significant number of molecules. At standard temperature and pressure, a 1-µm-sided cube contains 25 million air molecules or 34 billion water molecules. The continuum approximation can become invalid for
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS Table 1. Microfluidic units
Property
Unit
Name
Definition
Mass Length Time Volume Force Pressure Energy Power
g mm s µl µN Pa nJ nW
Gram Millimeter Second Microliter Micronewton Pascal Nanojoule Nanowatt
Base unit Base unit Base unit mm3 g mm s−2 µN mm−2 µN mm nJ s−1
a gas flow but still be acceptable in a liquid-filled passage that is 100 times smaller. When it becomes invalid, a kinetic theory–based analysis is needed. When the physical dimensions of a microdevice become so small that there are few molecules near the wall, the assumption of zero slip between fluid and wall can no longer be made. The Knudsen number, Kn = Lmfp /L, compares intermolecular spacing to the characteristic dimension. √For gases, the mean free path is Lmfp = kT /( 2πP d 2 ) in which k is the Boltzmann constant, T is absolute temperature, P is absolute pressure, and d is molecular diameter. For Kn < 0.001, the continuum approximation holds and zero slip boundary conditions are appropriate; for 0.001 < Kn < 0.1, the continuum approximation holds, but there is finite slip; for 0.1 < Kn < 10, the continuum approximation is invalid and a particle-based method (e.g., direct simulation Monte Carlo) should be used for flow characterization; for Kn > 10, free molecular flow requires Boltzmann equation modeling or another method also based on kinetic theory.27 The situation is less clear cut for liquid flows. Since the molecules are always in collision state, the mean free path is roughly equivalent to the molecular diameter. From experimental results, it appears that 10–20 molecular layers is the minimum height without invalidating the continuum approach or the zero slip boundary condition. For most liquids, minimum flow passage dimensions as small as 1–2 µm will meet the molecular layer requirement. For even smaller channels, molecular dynamics simulations may be the appropriate analysis method. 2.2
The Peclet Number – Which Transport Mechanism?
The constant motion of molecules in fluids ensures that they will intermingle. When we employ the
continuum concept, it is convenient to separate the actual mixing process into two conceptual transport mechanisms: diffusion, a molecular process modeled as a statistical random walk that is proportional to the degree of kinetic energy in the system, and advection (convection if heat is being transferred), in which molecules are carried along by the local velocity of the fluid. The relative importance of these two conceptual transport mechanisms is the Peclet number, the ratio of advection and diffusion, P e = vL/D, in which v is the fluid velocity and D is the diffusion coefficient of the solute in the solvent. When P e < 1000, molecular diffusion becomes more effective than stirring for mixing.
2.3
The Reynolds Number – Laminar or Turbulent?
The relative importance of the inertial versus viscous forces in the flow, (i.e., the ratio of the momentum of the fluid to the friction force imparted on the fluid by the walls), is described by the Reynolds number Re = ρvL/µ, originally proposed by Osborne Reynolds in 1883,28 in which v is bulk velocity of the flow, ρ is fluid density, and µ is fluid viscosity. A low Reynolds number flow is a laminar, or layered, flow in which fluid streams flow parallel to each other and mix only through advective and molecular diffusion (see Figure 2). Laminar flow is dominated by viscous forces and has fluid velocity at all locations invariant with time when boundary conditions are constant. There is advective mass transport only in the direction of fluid flow. Laminar flow is rarely observed in everyday life unless the fluid is very viscous, for example, pouring honey or squeezing toothpaste from a tube. In contrast, a high Reynolds number flow is a turbulent flow in which inertial forces dominate and various-size parcels of fluid exhibit motions that are simultaneously random in both space and time. Significant advective mass transport occurs in all directions. We are familiar with this regime from watching water fill a sink or stirring cream in our coffee. The transition between laminar and turbulent flow typically occurs above Re = 2000, though some experiments suggest transition in gas flows in microchannels may occur at Re as low as
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
5
Figure 2. A glacier illustrates laminar flow. No mixing occurs between the two side-by-side streams of ice.
400.29 A flow is identified as laminar or turbulent by either experimental or computational methods. Using experimental data, a laminar flow is identified by a linear proportionality between the log of the pressure loss in the channel and the log of the volume flow rate. If the flow transitions to turbulence, the proportionality constant would change at that flow rate. Transition to turbulence can also be identified using numerical techniques like the finite element or finite volume methods to simulate the flow, because as Hinze30 states, turbulence is defined as irregular flow with random variation of flow properties (e.g., velocity, pressure, etc.) in both time and space coordinates simultaneously. A numerical simulation based on solving the appropriate conservation of mass and momentum equations will not converge to a steady solution if the flow is randomly varying. Time averaging of the flow properties or some other technique must be used to mathematically model a turbulent flow. Flow in microchannels is virtually always laminar, unless the fluid is driven at very high velocity.
2.4
The Bond Number – How Critical is Surface Tension?
Another flow characteristic that becomes important in microscale passages is the interfacial tension between gas and liquid phases or between immiscible fluids. In flow in porous media, the Capillary number, the ratio of viscous forces to interfacial tension forces, is important. For droplet breakup,
the Weber number, the ratio of inertial and interfacial tension forces is a useful parameter. For microfluidic circuits with changes in elevation, the Bond number, is given by Bo = ρgL2 /σ , the ratio of gravity to interfacial tension forces, in which g is the acceleration of gravity and σ is surface tension. A low Bond number flow responds more to change in surface energy than to change in elevation of the free surface between the phases. Thus, the liquid rises in a capillary tube in spite of gravitational force.
2.5
Example of Flow Characterization
As an example of using nondimensional parameters to predict flow behavior, we investigate a flow rate of 0.05 µl s−1 in a microchannel that is 1 mm in width and 0.050 mm in height. First, we imagine the channel is filled with water vapor and compute the Knudsen number. The Boltzmann constant in microfluidic units is k = 1.3806 × 10−14 nJ K−1 and the diameter of a water molecule is d = 0.25 × 10−6 mm. If absolute pressure is P = 101325 Pa and temperature is T = 293 K, the mean free path is Lmfp = 0.000144 mm. Basing the Knudsen number on the smallest dimension, the channel height, gives Kn = 0.0029. According to the Knudsen number ranges discussed above, we can utilize the continuum approximation in this case, but would need to calculate the finite slip between the fluid and the channel walls. Now imagine our fluid passage is filled instead with a dilute saline solution at 20 ◦ C. As a liquid,
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
we replace Lmfp with d giving Kn = 0.00025, which allows both the continuum approximation and zero slip boundary conditions. The diffusion coefficient for NaCl in water is D = 1.74 × 10−3 mm2 s−1 . Since the width is an order-ofmagnitude larger than the height, the hydraulic diameter concept suggests a characteristic length that is approximately twice the smaller dimension, or L = 0.1 mm. From the ratio of the flow rate and the flow area, we calculate the bulk fluid velocity as u = 1 mm s−1 . Thus, the Peclet number is P e = 57, suggesting that diffusion is an effective mass transport mechanism in this case. (Indeed, a diffusion front of NaCl would cross the channel height in less than 2 s.) Assuming essentially water properties, the fluid density is ρ = 0.001 g µl−1 and dynamic viscosity is µ = 0.001 Pa s. Thus, Re = 0.1, a very laminar flow. Two streams carrying different solutes would flow side by side in this channel with their components mixing only by diffusion. The Bond number depends on gravity (g = 9810 mm s−2 ) and surface tension, which for water is σ = 72 µN mm−1 , giving Bo = 0.0014. Gravity will be a weak mechanism compared to the capillary effect. Determining dimensionless parameters is a good way to start the initial design of a microfluidic circuit. This microchannel contains a highly laminar flow in which solutes mix only by diffusion and channel wetout will depend on surface energy, not elevation change. In addition, we also know how changing channel dimensions or fluid properties will impact this flow behavior. 3 USING MICROSCALE EFFECTS TO DESIGN FASTER, MORE ACCURATE, AND LESS EXPENSIVE DEVICES
Researchers developing microfluidic devices frequently face obstacles that are directly related to the fundamental physics of microscale flow. Here are a few practical examples: • Fluids that are joined in a microfluidic circuit do not mix easily. • Sample particles that are heavier than the surrounding fluid settle to the channel bottom very quickly. • Microfluidic devices tend to have a very large surface-to-volume ratio, thus providing much
wall space for particles to stick to for a given volume. • A small drop of fluid placed in the inlet of a microfluidic device can evaporate very rapidly. • In microdevices, capillary force and surface energy effects are large forces compared to gravity. Depending on their direction and nature, they may move fluids upward and sideways, or block fluid movement, even downward. • Small fluid volumes will almost immediately take on the temperature of the environment, and cool down or heat up very quickly. However, those superficially unfortunate effects can be turned into extremely powerful tools in microfluidic devices: • Flow is usually laminar, allowing the parallel flow of several layers of fluid, thus enabling the design of separation and detection devices based on laminar fluid diffusion interfaces, which will be discussed later. • At micrometer dimensions, diffusion becomes a viable approach to move particles, mix fluids, and control reaction rates. Typical small drug molecules (e.g., cephradine with a MW of 349) diffuse about 14.3 mm s−1 at 25 ◦ C in aqueous solutions. This allows the establishment of controlled concentration gradients in flowing systems, as well as complete equilibration of the molecule across a 100 µm channel in less than one minute. • Unaided by centrifugation, sedimentation becomes a viable means to separate dispersed particles by density across small channel dimensions. For example, red blood cells sediment in a 100-µm-deep channel in about 1 min and generate a 50-µm layer of plasma in the process. • In microchannels, the reactor size (and thus the diffusion distance) can be made extremely small, particularly if fluid streams are hydrodynamically focused. Thus, diffusion-controlled chemical reactions occur more rapidly than in comparable macroscopic reaction vessels. For example, Hatch et al.31 have shown a microfluidic immunoassay that was completed in less than 25 s, as opposed to more typical immunoassay reaction times of 10 min or more. • Evaporation of small quantities of fluids can be extremely rapid because of a typically large surface-to-volume ratio. This effect can be use both for concentration of sample particles, as
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
well as for the movement of fluids through a disposable “evaporation pump”.32 • Active particle transportation and separation methods, such as CE, show greatly enhanced separation performance in small channels. Other positive characteristics of microfluidic devices that are derived from economics, convenience, and safety include the following: • Plastic microfluidic structures can be massproduced at very low unit cost, allowing them to be made disposable. • Microfluidic devices are somewhat amenable to high throughput by processing multiple samples and assays in parallel. • Microdevices require only small volumes of sample and reagents, and produce only small amounts of waste, which can often be contained within the disposable device. • The small scale of the various components of microfluidic systems allows them to be integrated into total analysis systems (µTAS) capable of handling all the steps of the analysis on-chip, from sampling, sample processing, separation and detection to waste handling. This integration also makes complex analyses potentially simpler and safer to perform. • It is possible to design passive fluidic devices that utilize inherent properties of the fluid and its microenvironment (capillary force, evaporation, wicking, heat transfer, diffusion, etc.) for fluid movement, mixing, heating, cooling, and catalyzing chemical reactions. Thus, disposable stand-alone devices can be designed that require no external power source or instrumentation, yet still perform many, if not all, of the functions typically associated with full-scale automated chemical analysis devices containing pumps, mixers, heat elements, readout electronics, and so on. • Passive microfluidic devices with integrated detection have the potential to be compatible with very small amounts of fluid, thus allowing ultralow-pain (yield low-volume) blood extraction methods to be used in an integrated fashion. This potentially opens up the regular home use of medical diagnostic assays such as cholesterol, antibodies for sexually transmitted diseases (STDs), and other tests that are currently only performed in laboratories.
7
4 THE PREFERRED SCALE FOR BIOSCIENCE APPLICATIONS
There is quite a bit of confusion in the microfluidics world about the use and applicability of the various dimensional prefixes such as macro, meso, micro, nano, and pico. The problem stems in part from their use for both dimensional parameters (length, width, and diameter) as well as for volume parameters (i.e., the volume pumped by a micropump per second). Thus, what is considered a microvolume (e.g., a few microliters) can be contained in a device with dimensional parameters in the millimeters. Further, many authors use a more colloquial definition of macro, micro, and mesoscale. For example, the macroscale sometimes is defined as “human dimension”, the microscale as “atomic dimensions”, and the mesoscale as bridging these two regimes.33 The authors prefer a definition that refers to the smallest dimensional parameter within a particular microfluidic flow structure since that dimensional parameter typically controls the physical behavior of the fluid. Therefore, in a macroscale fluidic device, no part of the flow structure (channel diameter, height, width, or, conceivably though unlikely, length) has a dimension of less than 1 mm. A microfluidic device has a smallest dimension of somewhere between 1 and 999 µm, and nanoand picofluidic devices have equivalent definitions. The authors also accept the use of the term mesoscale structure for a subset of microscale devices that have a smallest dimension of between 100 and 999 µm. On the basis of these definitions, we now explore some dimensions relevant to biosciences and list appropriate device dimensions for fluidic applications. Bioanalytical methods generally analyze and manipulate biological particles ranging from tissues (greater than 1 mm in diameter), cells (typically ranging from 0.1 to 30 µm in diameter), and molecules (ranging from a few nanometers for small molecules such as drugs and hormones to hundreds of micrometers for large proteins and nucleic acids). A number of research groups34 have used microfluidic devices to expose immobilized tissues to various concentrations of agents. While the channels leading up to the tissue, as well
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
as any mixing or diluting structures present in such devices frequently are microfluidic, the actual chamber that holds the tissue typically is not strictly microfluidic. Cells, on the other hand, have long been manipulated using microscale structures. For example, most conventional flow cytometers use a microscale nozzle that focuses cells in a single line inside a fluid jet. More recently, several researchers have developed microfluidic flow cytometers that either simulate such a jet inside a mesoscale microfluidic structure,20 or align cells by squeezing them through smaller, cell-sized microstructures.35–37 Large to midsize proteins such as proteins and nucleic acids are generally, for the purposes of separating, mixing, reacting, or detecting them, handled in bulk solution in microfluidic circuits, and not manipulated individually. However, some researchers have designed devices with dimensions in the very low microscale range (1–10 µm, P = 5.5 Torr
thus still considered microfluidic) in order to manipulate those molecules individually.38 For example, the folding of individual proteins can be studied in such devices,39 and DNA can be stretched out,40 for example for the purposes of analyzing its code using an atomic force microscope. Small molecules and ions are practically always manipulated in bulk within microfluidic devices. Many papers have recently been published claiming that their device is “nanofluidic”, or uses nanostructured materials. In many cases this does not mean that their devices have a manufactured dimension in the nanoscale, but simply refers to the use of, for example, molecular monolayers of a material inside the structure, or the immobilization of individual molecules (proteins, DNA) inside the channels.41 In other cases, researchers use the term nanofluidic or even picofluidic for devices (e.g., ink-jet heads) that generate or manipulate nano- or picoliter volumes of a fluid. Again,
P = 5.8 Torr
Liquid
Vapor
200 nm
200 nm
(a)
(b)
P = 6 Torr
P = 5.8 Torr
200 nm (c)
200 nm (d)
Figure 3. Sequence of environmental scanning electron microscopy (ESEM) images obtained when partial pressure of water in the ESEM chamber was gradually raised in a controlled manner, while observing a single open carbon nanotube filled with water (a–c). Note the liquid-volume recovery during subsequent pressure decrease (c–d).
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
this usually does not mean that any fabricated part of the device has nano- or picometer dimensions.42 Also, some researchers claim devices as being nanofluidic if they use, for example, nanoporous materials as filters or immobilization matrices. While true in the strictest sense of our definition, we are somewhat hesitant to accept this reading. Nanoporous materials are generally generated using a statistical process (γ ray irradiation, chemical etching), and not a linear design process. However, there are indeed a few microfabricated fluidic devices that have dimensions of less than 1 µm, for example, the carbon nanotube shown in Figure 3.43 These devices, however impressive in their complexity of manufacturing, have found only limited application in biosciences so far.44 In summary, the microfluidic (1–999 µm) scale is uniquely suited for most, if not all, processes and devices needed for biosciences applications. Manufacturing at this scale is now routine, at least for research devices, and within the next 5 years will be routine for low-cost mass manufactured devices as well. The authors believe that further advances on the nanoscale may bring great insights on specific problems such as single-molecule detection, but the vast majority of all devices used in biosciences will migrate from the macroscale to the microscale within the next decades, and remain there for the foreseeable future. 5 THEORIES OF MICROFLUIDIC PUMPING AND FLUID MOVEMENT 5.1
Pressure-driven Flow
Fluids, by definition, cannot sustain shear and will flow in response to a sufficient difference in pressure between the inlet and outlet of a fluid passage to accelerate the fluid mass and counter fluid friction with the walls. The pressure can be applied by an external source, by the weight of the fluid itself (hydrostatic head), or even by an expanding air bubble in the passage. To determine the fluid velocity, it might be tempting to use Bernoulli’s equation, 1 1 (P + ρU 2 + ρgh)inlet = (P + ρU 2 2 2 + ρgh)outlet
(1)
9
in which ρ is fluid density, U is mean velocity of the cross section, g is the acceleration of gravity, and h is fluid height. Bernoulli’s equation states that the sum of the three pressure terms: the thermodynamic pressure P , the velocity pressure (1/2 ρU 2 ), and the hydrostatic pressure (ρgh) is the same at any cross section of the fluid passage. It is derived from a conservation of energy statement by assuming the fluid has no viscosity and energy dissipation due to shear stresses in the fluid is negligible, both inappropriate assumptions for low Reynolds number flows. Instead of using energy conservation to determine a low Reynolds number flow response to applied pressure, it is more accurate to use momentum conservation, which leads to the Stokes or Navier–Stokes equations.45 ∂ ρu + u · ∇ρu + ∇P − µ∇ 2 u = 0 ∂t
(2)
This is a general equation for an incompressible Newtonian fluid and can be used for complex three-dimensional flow fields with vector velocity u = (u1 , u2 , u3 ). The z-direction component, for example, is ∂ ∂ ∂ ∂ ρu3 + u1 ρu3 + u2 ρu3 + u3 ρu3 ∂t ∂x ∂y ∂z 2 ∂ u3 ∂P ∂ 2 u3 ∂ 2 u3 (3) +µ =− + + ∂z ∂x 2 ∂y 2 ∂z2 The Navier–Stokes equation is typically simplified to suit the particular case of fluid flow. For example, when the Reynolds number Re 1, the inertial force term u · ∇ρu is so small compared to the viscous force term µ∇ 2 u that it can be neglected. This is termed Stokes flow. The flow in a straight fluid passage of constant cross section is unidirectional. If we use Cartesian coordinates (x, y, z) and take z to be the direction of fluid motion, the fluid velocity components are u = (0, 0, u). If we choose an incompressible fluid, then, by conservation of mass in the constant cross-section passage, the fluid cannot be changing speed as it travels down the passage. Thus, ∂u/∂z = 0 and u may be a function of x and y, but not z. The three components of the Navier–Stokes equation simplify to ∂P /∂x = 0, ∂P /∂y = 0, and 2 ∂u ∂P ∂ u ∂ 2u ρ (4) + =µ + ∂t ∂z ∂x 2 ∂y 2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
in which the passage height is 0 < y < d. This solution reveals the parabolic velocity profile of steady laminar flow (recall that a parabola is u = aδ 2 + bδ + c) as a natural consequence of viscous shear and momentum conservation in a straight channel. Figure 4 illustrates that the velocity profile is indeed unchanging across the width of the channel, except near the endwalls. If the x and y dimensions of a rectangular crosssection channel are comparable in size, the exact analytical solution for velocity can be defined as an infinite series.46 A good approximation of the ratio between mean velocity U and the maximum velocity Umax at the center of the channel is U 1 h 2 1− (6) = Umax 3 3 w in which height h and width w are chosen so that h < w. This ratio is always 4/9 ≤ U/Umax ≤ 2/3. Also, if the Knudsen number Kn < 0.001, the continuum approximation holds and there is no slip velocity at the walls, uslip = 0. If 0.001 < Kn < 0.1, the continuum approximation holds, but a nonzero value of uslip would need to be calculated. For higher Kn, these equations would be inappropriate, as the flow could not be modeled as a continuum. 5.2
Calculating Volume Flow Rate or Pressure Difference in Straight Channels
An efficient method to determine the flow rates in a microfluidic device is to calculate the flow resistance of each passage and then combine them via a circuit diagram and the electric–hydraulic circuit analogies: current ↔ volume flow rate and voltage ↔ pressure difference between inlet and outlet. Thus, analogous to electrical resistance = voltage/current, we have f low resistance = pressure diff erence/f lowrate.
1 0.9 0.8 Fluid velocity
If the flow is steady, laminar, and the y dimension of the passage is at least an orderof-magnitude smaller than the x dimension, then the two-dimensional solution for the velocity in the fluid passage is a good approximation and is simply 2 dP d 2 y y u= + uslip − (5) dz 2µ d2 d
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
(a)
–1 –0.8 –0.6 –0.4 –0.2 0 0.2 0.4 0.6 0.8 Distance from centerline
Velocity
10
C
ne han
l wi
1
dth
Heig
ht
(b)
Figure 4. Parabolic velocity profiles. (a) Velocity varies parabolically between the two parallel walls. (b) Velocity map in a rectangular channel shows the flow is really two-dimensional anywhere along the width except within a distance of height/2 from the endwalls.
The flow resistance in a straight channel can be derived from the Darcy friction factor, f =
(DH P /L) (1/2ρU 2 )
(7)
which is a ratio of the energy dissipated in shear to the kinetic energy of the fluid. The hydraulic diameter DH was introduced previously, the pressure gradient is the ratio of the pressure difference P over the channel length L, and U is the mean fluid velocity of the cross section. Experiments over many years have shown that for laminar flow in straight channels, f = 64/(ϕRe), in which the aspect ratio factor is ϕ = 1 for
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
circular pipes or ϕ≈
5.4
2 11 + AR(2 − AR) 3 24
(8)
for passages with rectangular cross sections.47 The aspect ratio AR is the ratio of the channel height and width, or its reciprocal, so that AR ≤ 1. Combining these to eliminate f gives a general equation for flow resistance R=
128 µL (4 Area ϕDH2 )
(9)
When AR 1, the hydraulic diameter of a rectangular channel depends mainly on the smaller dimension and the flow resistance is inversely proportional to the third power of the smaller dimension. It is a simple matter to add up the resistances of each section of fluid path, analogous to an electric circuit, and calculate the necessary pressure difference P between inlet and outlet to obtain a required volume flow rate Q. For example, for two different channels connected in series, we use P = (R1 + R2 )Q (10) When the flow is unsteady, for example, starting, stopping, or oscillatory, additional fluid circuit elements modeling inertance and capacitance must be added to the fluid circuit model.
5.3
Gravity-driven Flow
The driving pressure P can be produced by a variety of different sources: syringe pump, handheld syringe, tank pressurized by gas, or simply gravity, also called hydrostatic head. In this last case the driving pressure is P = ρgh
(11)
where ρ is the density of the fluid, g is acceleration of gravity, and h is the elevation difference between the inlet and outlet of the fluid passage. Other elevation changes completely within the passage are immaterial.
11
Examples of Pressure-driven Flow
Regardless of how the driving pressure is created, whether by pump, gravity, or compressed air cylinder, the amount of pressure needed to produce a required flow rate is calculated in the same way. Utilizing the previous equations in this section, we determine the driving pressure needed to generate a flow of Q = 1 µl s−1 of water at 25 ◦ C. in a w = 1-mm-wide by h = 0.1mm-high by L = 100-mm-long rectangular channel. The channel aspect ratio is AR = h/w = 0.1 so the aspect ratio factor is calculated as ϕ ≈ 0.75. Taking the viscosity of water as µ = 0.001 Pa s and calculating the hydraulic diameter (see Section 2) as DH = 2/(1/ h + 1/ w) = 0.182, gives the resistance to flow in the channel as R = 1290 Pa s µl−1 . To achieve the required flow rate requires a driving pressure of P = 1290 Pa. If we supply this by the hydrostatic pressure of a column of water, it would need to be h = P /(ρg) = 131 mm high, (assuming density ρ = 0.001 g µl−1 and g = 9810 mm s−2 ). Clearly, not much pressure is needed to drive this flow rate in this microfluidic channel. Here we assumed that surface tension forces at the inlet and outlet are either equal or insignificant, but they should be included in modeling a low Bond number flow.
5.5
Forced Flow through Packed Bed
There are applications, such as affinity chromatography48 or enzyme kinetics,49 in which the microcircuit designer may wish to capture a component of the solution on solid support. Columns with packed media can be implemented in a microdevice by filling a channel with microbeads or silica. The pressure required to drive the solution at the desired flow rate Q through porous media is often the largest pressure drop in the system and should be calculated before the fluid circuit is built to avoid an unreasonably high back pressure. A packed bed can be characterized by the following parameters: Abed , the cross-sectional flow area of the packed bed; Lbed , the flow-direction length of the bed; Dp , the diameter of its particles; ε, the void fraction (volume fraction of the empty space between particles through which fluid can flow); and φ, the sphericity of the particles. For
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
spherical particles, φ = 1. For nonspherical particles: Dp is the diameter of an equivalent sphere that has the same volume as the actual particle, and φ = 6vp /(Dp Sp ), the ratio of surface areas of the equivalent sphere and the actual particle Sp , where vp is the volume of particle. A packedmedia Reynolds number is defined as RePM = ρubed Dp /µ, where ubed = Q/(Abed (1 − ε)). The pressure drop in the packed bed is determined from the Ergun equation, which is appropriate for both creeping (Stokes) flow (RePM < 10) and laminar flow (RePM < 1, 000). 150 1.75 + PPM = φ 2 RePM φ ρ(1 − ε)/ε 3 Lbed Q2 (12) × Dp /A2bed A slightly different approach is useful when more than one size of microbeds are used.50 Channeling due to irregular packing and nonuniformly sized media can be problematic and greatly lower the effectiveness of a packed bed. Some consideration should be applied to the fact that microchannels can have a large surface-to-volume ratio. If the volume of fluid to be processed is very small and the height of the channel can be decreased sufficiently, the walls of the channel may perform as the solid support.
5.6
Example of Flow in Packed Media
Let us revisit the previous pressure-driven flow example to see how much additional pressure is required if the channel is filled with media. We assume spherical particles (so φ = 1) of diameter Dp = 0.003 mm and a bed void fraction of ε = 0.35, for a tightly packed bed. The area of the bed is the cross-sectional area of the channel, Abed = 0.1 mm2 . Using the same flow rate as the previous example, Q = 1 µl s−1 , gives a bed velocity of ubed = 15.4 mm s−1 and a packed-media Reynolds number of RePM = 0.046. If we take the same density and viscosity as the previous example, the required driving pressure is PPM = 5750 Pa, or 4.5 times larger because of the addition of the media. To drive this flow hydrostatically would require a 586-mm-high column of water. Also note that the packed-media driving pressure is a
function of the square of the flow rate, unlike the linear relationship in a channel without media. Thus, increasing the flow rate by a factor of 10 would increase the packed-media driving pressure by a factor of 100.
5.7
Electroosmotic Flow (EOF)
Electroosmotic flow (EOF) occurs when the channel walls of a microfluidic device are charged at the local buffer pH. The fluid proximal to the channel walls will not be neutral but rather will contain a higher-than-bulk concentration of counterions (balancing the opposing charge of the channel wall). When an electric field is applied parallel to the surface, the charged fluid will move in bulk toward the complimentary electrode, resulting in convective fluid flow (see Figure 5).51 In the case of a negatively charged surface the fluid will have a net positive charge and will migrate toward the cathode (negative electrode). Initially only a thin layer of fluid begins to migrate, creating a velocity gradient that results in momentum transfer to the adjacent fluid through viscous shear forces, which then begins to move. In other words, the charged fluid layer “drags” the adjacent fluid layer along, until finally the entire channel moves at a uniform velocity.51 Essentially, one creates the “one fixed wall, one moving wall” situation described during the discussion of viscosity. Note that this uniform velocity occurs if the channel characteristic diameter is at least seven times that of the electric double layer proximal to the channel walls52 and if other sources of fluid acceleration, such as convective currents due to Joule heating, are negligible. This velocity profile is very different from that of pressure-driven flow, which has a nonuniform, parabolic profile. The effective charge of a surface, called zeta potential (ζ ), is defined as the potential difference at the interface between the tightly held layer of counterions immediately proximal to the surface and the bulk solution (this interface is called the surface of shear).53 In addition to the surface charge of the material, three fluid parameters influence the ζ potential: pH, dielectric constant, and ionic strength.54 The velocity of fluid undergoing EOF is a function of the ζ potential of the walls,
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
+
(a)
+
Before applying field
Driven by shear forces
Driven by electrostatic attraction
13
–
(b) Immediately after applying field
–
(c) Shear forces accelerate neighboring fluid lamina
+
–
(d) Steady-state reached; all fluid lamina move at uniform velocity
Figure 5. Schematic of electroosmotic flow in a microfluidic channel. White = positive, dark gray = negative, light gray = neutral. The channel walls are negatively charged; the bulk fluid is neutral. Arrow size corresponds to fluid velocity.
the electric field strength, and the fluid properties themselves, as νEOF =
ζ DF µ
(13)
in which νEOF is the velocity of the fluid due to EOF in a circular capillary, ζ is the zeta potential of the charged wall, D is the dielectric constant of the fluid, and µ is the viscosity of the fluid. EOF velocity depends on characteristics of both the fluid undergoing transport and the channel wall material. The dielectric constant and the viscosity of the fluid undergoing transport directly affect EOF. In addition, other fluid characteristics (pH, ionic strength, composition) can have additive or opposing effects. For example, in a bare glass capillary, the surface charge increases with pH. But if the pH is increased through addition of high concentrations of a metallic salt, then the ionic strength will increase, which acts to decrease EOF. Up until fairly recently, the vast majority of microfluidic devices were made from glass, which has a well-characterized surface charge that varies in a predictable way with changes in the fluid.
Under physiologic conditions, glass and silica have a negative ζ potential; as the local pH drops the silanol groups on the glass surface become protonated and the ζ potential drops in magnitude. Many different surface modification techniques have been developed for glass, which allow the user to change the surface charge and/or apply a nonfouling coating. EOF in glass capillaries is therefore a fairly straightforward technique, commonly used in many microfluidic devices, particularly those used for CE. As newer devices begin to incorporate less expensive materials, particularly polymeric components such as Mylar and silicone, the associated EOF behavior becomes more difficult to predict. In fact, a major obstacle to the use of materials other than glass for microfluidic devices has been the lack of information on the surface properties of these materials.55 Compared to glass and silica, there are significantly fewer established techniques for surface modifications of polymers. One should rely on empirical data specific to the material of interest when designing polymeric devices to work with EOF.
14
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Owing to increasing interest in the use of polymeric materials for microfluidic devices, new surface modification techniques are continually being developed56 as are methods for dynamic coatings,57 for example, some researchers suggest that oxidation of polydimethylsiloxane (PDMS) increases its ζ potential and therefore the EOF velocity.58 Certain fabrication techniques can alter the surface properties of some areas of the device, which creates a nonuniform surface and can lead to nonplug flow.59 The use and treatment history of the device also influence EOF velocity. Fluid components, particularly protein, can adsorb onto the channel walls, thus altering their charge and therefore changing the associated double layer. For EOF to operate consistently over time, this surface fouling must be avoided, either through treating the channel walls to minimize adsorption and/or through addition of materials to the fluid itself that prevent adsorption. Alternately, if the degree of fouling is well known, the device can be operated for a fixed period of time and then flushed with a cleaning solution that returns the walls to a pristine state. Biological fluids, in particular, create significant fouling concerns, primarily due to the relatively high concentration of proteins in solution. If the device is single use, fouling concerns are reduced but not eliminated, since EOF could be affected by fouling during a single assay.
5.8
Advantages and Disadvantages of EOF
There are three main advantages to using EOF to drive fluids: uniform flow profile, no-movingpart pumping, and a simplified fluidic interface. Uniform velocities result in uniform retention times for all particles in a given section of the device, which can greatly simplify calculations and analysis. Because fluids undergoing EOF move as a bolus, the leading and trailing edges of materials are minimized, which reduces the time and material required to change solutions in a device. Unlike pressure-driven flow, EOF does not require a leak-tight interface between the source of the hydraulic driving force (electrodes in this case) and the fluid being driven. Therefore, the interface between the source of pumping and the fluid being pumped can be as
simple as two wires placed into holes in the device. A disadvantage of EOF is its strong dependence on the electrochemical properties of both channel walls and the fluid. If a device is expected to process a variety of fluids or a fluid of unknown pH/ionic strength, the EOF velocity will be unpredictable. Since EOF depends on the material properties of the channel wall, any changes in device manufacture must be analyzed for potential effects on EOF. In addition, EOF often requires high voltages (typically in the kilovolt to megavolt range), which requires isolation of the electrodes from the sample fluid to avoid the products of electrolysis (bubbles, acid/base) from entering the sample, while also retaining electrical connectivity. Heat produced by the high electric field may also have to be dissipated. Finally, if a microfluidic device will be incorporating an applied voltage, the possibility of EOF, intentional or not, must be considered during the design stage. This concern is particularly important when applying an electric field perpendicular to the direction of fluid flow, since the induced EOF will itself be perpendicular to the direction of fluid flow, at least initially. If one observes unusual flow patterns in a microfluidic device to which electricity is being applied, particularly recirculating flows, one should consider EOF as a likely cause of the phenomenon. Because of the utility and ubiquity of EOF in the microfluidic community, a significant amount of research has been done on many aspects of EOF. A full review is beyond the scope of this text; for good starting points into the related scientific literature, see the excellent review by Manz and colleagues.51
5.9
Capillary Flow
Molecules at a liquid–gas interface experience molecular attraction only from the liquid side. In response to this imbalance, the liquid surface contracts like a stretched membrane in tension; this is surface tension σ , a force per unit length. An analogous argument can be made on the basis of energy instead of force.60 Organic compounds with hydrophilic heads and hydrophobic hydrocarbon tails, such as detergents, are strongly adsorbed at the liquid–gas interface and tend to form a
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
monolayer on the liquid surface. Even a very low concentration of these “surface-active” molecules, surfactants, (e.g., 0.004 M sodium dodecyl sulfate) interferes with hydrogen bonding and can lower the surface tension of water from 72.9 µN mm−1 (at 20 ◦ C) to 40–50 µN mm−1 . A drop of liquid placed on a solid surface may spread out and wet the surface or form a static contact angle at the three-phase boundary between the wetted solid and the liquid–gas interface. The pressure rise due to surface tension in the general case of an aspherical drop with principal radii of curvature, r1 and r2 , (i.e., the radii of curvature along any two orthogonal tangents) is P = σ = 1/r1 + 1/r2 ), the Young–Laplace equation. The contact angle is a sensitive measure of surface energy and depends, not only on the chemical composition of the fluid (e.g., its pH), but also on the surface condition of the material (Figure 6). The same material will result in different contact angle measurements depending on its cleanliness, its previous contact with hydrophobic materials that can alter the surface (e.g., Teflon and silicone oil), whether it is already wetted, and even the humidity of the surrounding gas. An advancing contact angle (e.g., an expanding drop during condensation) is typically significantly larger than a receding contact angle and both change with time as the precursor film61,62 that extends out beyond the drop is spreading or retracting. Table 2 lists advancing contact angles for a water drop on various materials. The capillary pressure in a rectangular channel with height h and width w (see Figure 7) can be determined from a force balance, −P hw = 2(h + w)σ cos θ , which can be simplified to P = −2σ cos θ (1/ h + 1/w)
q
(14)
q
Figure 6. Contact angles, θ , for liquid water drops on solid surfaces. The solid on the left is hydrophilic (i.e., θ < 90◦ ), while that on the right is hydrophobic.
15
Table 2. Approximate advancing contact angles of a water drop. Glass, polyethylene terephthalate (PET), and polymethyl methacrylate (PMMA) are hydrophilic and should be naturally wetting, while Teflon and polydimethylsiloxane (PDMS) would require addition of surfactants to the aqueous solution or a surface-energyincreasing treatment to lower the contact angle
Contact angle (◦ )
Solid Glass, borosilicate (Pyrex) PET Acrylic (PMMA) PS Paraffin Poly(tetrafluoroethylene) (Teflon) PDMS
14 50 75 86 109 112 115
PS: polystyrene.
q
Figure 7. Liquid filling a channel. The small contact angle means the surface tension is pulling the liquid to accomplish the wetout.
Why is the minus sign needed here? When the contact angle is small, the fluid is being pulled into the channel by surface tension and the pressure in the liquid is actually lower than in the downstream gas. Conversely, when the contact angle is θ > 90◦ , a positive pressure difference would be required to force liquid into the channel against surface tension. Compare capillary behavior in the same rectangular channel in two different materials using the contact angle values from Table 2. The capillary pressure in water in a 1-mm-wide by 0.1mm-high channel fabricated of PET is P = −2(72.9) cos 50◦ (1/0.1 + 1/1) = −1031 Pa with respect to the gas pressure downstream of the meniscus. If the water at the upstream end of the channel is at ambient pressure (i.e., 0 Pa) and the channel elevation is constant, the pressure difference in the liquid between the upstream and downstream end at the meniscus will push the liquid into the channel. On the other hand, if the channel is fabricated of PDMS, the capillary pressure is 678 Pa, which would oppose liquid flow
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
PL
PG
Figure 8. Area discontinuity can create an unstable “surface tension stop” that sustains a small pressure difference, PL > PG .
into the channel. This positive capillary pressure would not be likely to push the liquid out of the PDMS channel however, because the receding contact angle would likely be less than 90◦ . Another interaction between surface tension and channel geometry is a surface tension stop as shown in Figure 8. A desirable (or unintentional) pressure difference can be sustained by an area discontinuity.
5.10
Absorptive and Wicking-driven Flow
Uptake of fluid by capillary pumping of a hydrophilic polymer is the mechanism for fluid movement in the lateral flow strip, a qualitative immunological assay in a passive handheld format, such as a home pregnancy test. Most current lateral flow strip assays are based on membranes composed of cellulose nitrate or cellulose acetate depending on the degree of protein binding desired. A similar functionality is obtainable from hydrogels, cross-linked polymer networks surrounded by an aqueous solution. When wetted by a solvent, the chains in the network are solvated, but do not mix due to the cross-linking, which provides an elastic restoring force to counter swelling. Hydrophilic polymers can be divided into categories based on the relaxation time of the polymer and the diffusion time of the solvent. One parameter is the Deborah number, the ratio of the rates of solvent penetration and polymer relaxation, De = λD/δ 2 , in which λ is the characteristic polymer relaxation time from swelling stresses, D is the diffusion coefficient of the solvent, and δ is the diffusional distance at time = λ.63 Case I transport (De 1) occurs when the diffusion time is much slower than the polymer relaxation time, leaving diffusion as the controlling mechanism. This is typical in nonswelling systems. In case II transport (De 1), the rate limiting process is polymer relaxation. In other hydrogels,
De is on the order of 1 and the two processes occur on the same time scale, leading to anomalous transport behavior. When De is very large, this is sometimes referred to as super case II behavior. A simple description of the time-dependent swelling of a polymer is Mt /M∞ = kt n , in which Mt /M∞ is the fractional uptake (or release) of solvent normalized by the equilibrium conditions and k and n are constants dependent on solvent diffusion coefficient and type of transport process.64–66 Figure 9 plots the fractional uptake of solvent for various transport types. For diffusion-controlled (type 1) transport, n = 0.5, while for polymer relaxation controlled (type II) transport, n = 1. Anomalous transport has 0.5 < n < 1, and super type II has n > 1. The uptake of solvent and solute in swelling polymeric systems can be numerically modeled by the species conservation equation67,68 if the solvent velocity u is known from the solution of the momentum conservation equations, from Darcy’s equation for fluid flow through a porous medium and the permeability and porosity of the medium, or from experimental data to determine the constants. For example, data from experiment with 5 µm pore size nitrocellulose polyether sulfone exhibits Type I transport behavior69 in which wetting speed is proportional to the square root of wetting time. Wetting time data for a typical lateral flow strip based on Whatman nitrocellulose “Purabind” is shown in Figure 10.
n > 1, Super II n = 1, Type II 0.5 < n < 1, Anomalous n = 0.5, Type I
5 4.5 4 3.5
Wt /W∞
16
3 2.5 2 1.5 1 0.5 0 0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Time
Figure 9. Fractional uptake of solvent versus time for various transport types.
INTRODUCTION TO MICROFLUIDIC TECHNIQUES
Plasma Water
400
Wetting time (s)
350 300 250 200 150 100 50 0 0
2.5
5
7.5
10
12.5
Nominal pore size (µm)
Figure 10. Wetting times for 45-mm-long lateral flow strip of Whatcom nitrocellulose “Purabind” for water at 25 ◦ C. The data is also scaled by viscosity ratio to predict behavior with blood plasma as solvent.
6 USING APPROPRIATE STRATEGIES FOR DEVELOPMENT OF MICROFLUIDIC DEVICES
Microfluidics brings unique capabilities to assays and sensors in bioscience applications, such as: lower cost assays, more rapid results, smaller reagent volumes, and less hazardous waste. But fluids in the microscale do not display the familiar behavior of fluids in the human-scale world. Understanding the physics of microfluidics is one key to successful development of microdevices. It is a nearly impossible task to replicate macroscale fluid-management strategies in the microscale and far more fruitful instead to leverage its unique behaviors and inherent capabilities. In the microscale, inertial and gravitational forces are often much less important than surface tension and viscous forces. Alternatives to pressure-driven flows exist and are robust and reliable, such as electrokinetics and wicking. Dimensionless parameters can be utilized to show which physics will be dominant in your device. Then mathematical modeling becomes an effective way to estimate performance in the deterministic world of microfluidics. In this way, a new microfluidic device has the potential to become a novel solution in its application area.
17
REFERENCES 1. B. H. Weigl, R. L. Bardell, and C. R. Cabrera, Lab-ona-chip for drug development. Advanced Drug Delivery Reviews (invited review article), 2003, 55(3), 349–377. 2. E. Cabuz, J. Schwichtenberg, B. DeMers, E. Satren, A. Padmanabhan, and C. Cabuz, MEMS-Based Flow Controller for Flow Cytometry Honeywell International , 2002 http://content.honeywell.com/sensing/solutions/markets/ medical/88PAD HH 2002 twopage fullpaper.pdf. 3. U. Bonne et al., Microsensor Housing, US Patent 6,322,24, Issued November 27, 2001. 4. http://www.darpa.mil/MTO/bioflips/presentations/2001-1/ index.html, (DARPA BioFlip Program), 2001. 5. P. Belgrader, M. Okuzumi, F. Pourahmadi, D. Borkholder, and M. A. Northrup, A microfluidic cartridge to prepare spores for PCR analysis. Biosensors and Bioelectronics, 2000, 14, 849–852. 6. B. H. Weigl, R. L. Bardell, T. Schulte, D. C. Cullen, and J. Demas, Modeling of microscale processes speeds development and enhances performance of medical diagnostic product. In Vitro Diagnostics Technology, 10, June 2004, 41–49, invited. 7. B. H. Weigl, A. Holobar, W. Trettnak, and O. S. Wolfbeis, Optical triple sensor for measuring pH, oxygen and carbon dioxide. Journal of Biotechnology, 1994, 32, 127–138. 8. B. H. Weigl, New Assays and Separations Based on Laminar Fluid Diffusion Interfaces—Results From Field Trials for Cell Analysis, HTP Screening, and Medical Diagnostics, in Micro Total Analysis Systems 2002, D. J. Harrison and A. Van den Berg (eds), Kluwer Academic Publishers, Dordrecht, 2002. 9. P. Mitchell, Microfluidics—downsizing large-scale biology. Nature Biotechnology, 2001, 19, 717–721. 10. J. Benditt, Ten Emerging Technologies that will Change the World, MIT Technology Review: January/February, 2001. 11. L. J. Kricka, Microchips, microarrays, biochips and nanochips: personal laboratories for the 21st century. Clinica Chimica Acta, 2001, 307(1–2), 219–223. 12. Frost and Sullivan, U.S. Point-Of-Care Retail Diagnostics Markets, 3/15/2003, available from hyperlink http://www.marketresearch.com (this is a market research report), 2003. 13. R. L. Chien and J. W. Parce, Multiport flow-control system for lab-on-a-chip microfluidic devices. Fresenius Journal of Analytical Chemistry, 2001, 371(2), 106–111, (eng). 14. L. Bousse, C. Cohen, T. Nikiforov, A. Chow, A. R. Kopf-Sill, R. Dubrow, and J. W. Parce, Electrokinetically controlled microfluidic analysis systems. Annual Review of Biophysics and Biomolecular Structure, 2000, 29, 155–181. 15. M. T. Cronin, T. Boone, A. P. Sassi, H. Tan, Q. Xue, S. J. Williams, A. J. Ricco, and H. H. Hooper, Plastic microfluidic systems for high throughput genomic analysis and drug screening. Journal of the Association for Laboratory Automation, 2001, 6(1), 74–78. 16. M. T. Cronin, M. Pho, D. Dutta, F. Frueh, L. Schwarcz, and T. Brennan, Utilization of new technologies in drug trials and discovery. Drug Metabolism and Disposition, 2001, 29(4), 586–590.
18
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
17. A. J. Ricco, T. D. Boone, Z. H. Fan, I. Gibbons, T. Matray, S. Singh, H. Tan, T. Tian, and S. J. Williams, Application of disposable plastic microfluidic device arrays with customized chemistries to multiplexed biochemical assays. Biochemical Society Transactions, 2002 30(2), 73–78. 18. W. W. Weber and M. T. Cronin, Pharmacogenetic Testing, in Encyclopedia of Analytical Chemistry, R. A. Meyers (ed), John Wiley & Sons, Sussex, 2000, pp. 1506–1531. 19. M. T. Boyce-Jacino, J. E. Reynolds, T. T. Nikiforov, Y. H. Rogers, C. Saville, T. C. McIntosh, P. Goelet, and M. R. Knapp, High volume molecular genetic identification of single nucleotide polymorphisms using genetic bit analysis: application to human genetic disease. American Journal of Human Genetics, 1994, 55(3), 18–22. 20. B. H. Weigl, R. L. Bardell, N. Kesler, and C. J. Morris, Lab-on-a-chip sample preparation using laminar fluid diffusion interfaces—computational fluid dynamics model results and fluidic verification experiments. Fresenius Journal of Analytical Chemistry, 2001, 371(2), 97–105. 21. A. Y. Fu, C. Spence, A. Scherer, F. H. Arnold, and S. R. Quake, A microfabricated fluorescence-activated cell sorter. Nature Biotechnology, 1999, 17, 1109–1111. 22. J. W. Hong and S. R. Quake, Integrated nanoliter systems. Nature Biotechnology, 2003, 21, 1179–1183. 23. M. T. Taylor, P. Belgrader, R. Joshi, G. A. Kintz, and M. A. Northrup, Fully automated sample preparation for pathogen detection performed in a microfluidic cassette. Micro Total Analysis Systems, 2001, 670–672. 24. M. A. Northrup, L. Christel, W. A. McMillan, K. Petersen, F. Pourahmadi, L. Western, and S. Young. A New Generation of PCR Instruments and Nucleic Acid Concentration Systems, PCR Applications—Protocols for Functional Genomics, 1999, 105–125. 25. T. Thorsen, S. J. Maerkl, and S. R. Quake, Microfluidic large scale integration. Science, 2002, 298, 580–584. 26. P. Jandik, B. H. Weigl, N. Kesler, J. Cheng, C. J. Morris, T. Schulte, and N. Avdalovic, Initial study of using laminar fluid diffusion interface for sample preparation in HPLC. Journal of Chromatography A, 2002, 954, 33–40. 27. M. Gad-el-Hak, The fluid mechanics of microdevices—the freeman scholar lecture. Journal of Fluids EngineeringTransactions of the ASME, 1999, 121, 5–33. 28. O. Reynolds, An experimental investigation of the circumstances which determine whether the motion of water in parallel channels shall be direct or sinuous and of the law of resistance in parallel channels. Philosophical Transactions of the Royal Society of London, 1883, 174, 935–982. 29. P. Wu and W. A. Little, Measurement of friction factors for the flow of gases in very fine channels used for microminiature Joule-Thomson refrigerators. Cryogenics, 1983, 23, 273–277. 30. J. O. Hinze, Turbulence, 2nd Edn, McGraw-Hill, 1987, pp. 1–4. 31. A. Hatch, A. E. Kamholz, K. R. Hawkins, M. S. Munson, E. A. Schilling, B. H. Weigl, and P. Yager, A rapid diffusion immunoassay in a t-sensor. Nature Biotechnology, 2001, 19(5), 461–465. 32. D. J. Beebe and G. M. Walker, An evaporation-based microfluidic sample concentration method. Lab on a Chip, 2002, 2, 57–61.
33. National Academy of Science, Summary, the Impact of Materials—from Research to Manufacturing, http://www. national-academies.org. 2002. 34. A. Folch and M. Toner, Microengineering of cellular interactions. Annual Review of Biomedical Engineering, 2000, 2, 227. 35. J. P. Brody, P. Yager, R. Goldstein, and R. H. Austin, Biotechnology at low Reynolds numbers. Biophysical Journal, 1996, 71, 3430–3441. 36. R. H. Carlson, J. P. Brody, S. Chan, C. Gabel, J. Winkleman, and R. H. Austin, Self-sorting of white blood cells in a lattice. Physical Review Letters, 1997, 79, 2149–2152. 37. E. Altendorf, E. Iverson, D. Schutte, B. H. Weigl, T. Osborn, R. Sabeti, and P. Yager, Optical Flow Cytometry Utilizing Microfabricated Silicon Flow Channels, in Advanced Techniques in Analytic Cytology (BIOS 96) SPIE Proceedings, SPIE (formerly the International Society for Optical Engineering), Vol. 2678. 38. T. A. J. Duke and R. H. Austin, Microfabricated sieve for the continuous sorting of macromolecules. Physical Review Letters, 1998, 80, 1552–1555. 39. J. B. Knight, A. Vishwanath, J. P. Brody, and R. H. Austin, Hydrodynamic focusing on a silicon chip: mixing nanoliters in microseconds. Physical Review Letters, 1998, 80, 3863–3866. 40. R. H. Austin, J. P. Brody, E. C. Cox, T. Duke, and W. Volkmuth, Stretch genes: aligning single molecules of DNA. Physics Today, 1997, 32–36. 41. J. S. Kuo, Interfacing Chip-Based Nanofluidic-Systems to Surface Desorption Mass Spectrometry, JIN Reports, Pacific Northwest National Laboratory, 2003, http://www. pnl.gov/nano/institute/2003reports/. 42. T.-C. Kuo, D. M. Cannon Jr, M. A. Shannon, J. V. Sweedler, and P. W. Bohn, Hybrid three-dimensional nanofluidic/microfluidic devices using molecular gates. Sensors and Actuators A, 2003, 102/3, 223–233. 43. Y. Gogotsi, C. M. Megaridis, H. Bau, J.-C. Bradley and P. Koumoutsakos, Carbon Nanopipes for Nanofluidic Devices and In-situ Fluid Studies, In: NSF Nanoscale Science and Engineering Grantees Conference, National Science Foundation, Arlington, Virginia, 2003, Dec 16–18. 44. L. Wanli, J. O. Tegenfeldt, L. Chen, R. H. Austin, S. Y. Chou, P. A. Kohl, J. Krotine, and J. C. Sturm, Sacrificial polymers for nanofluidic channels in biological applications. Nanotechnology, 2003, 14, 578–583. 45. R. L., Panton, Incompressible Flow, John Wiley & Sons, 1984, p. 154. 46. F. M. White, Viscous Fluid Flow, 2nd Edn, John Wiley & Sons, 1991, p. 120. 47. O. C. Jones Jr, An improvement in the calculation of turbulent friction in rectangular ducts. Journal of Fluids Engineering-Transactions of the ASME, 1976, 98, 173–181. 48. N. Malmstadt, P. Yager, A. S. Hoffman, and P. S. Stayton, A smart microfluidic affinity chromatography matrix composed of poly(N-isopropylacrylamide)—coated beads. Analytical Chemistry, 2003, 75, 2943–2949. 49. G. H. Seong, J. Heo, and R. M. Crooks, Measurement of enzyme kinetics using a continuous-flow microfluidic system. Analytical Chemistry, 2003, 75, 3161–3167.
INTRODUCTION TO MICROFLUIDIC TECHNIQUES 50. M. J. MacDonald, C. F. Chu, P. P. Guilloit, and K. M. Ng, A generalized Blake-Kozeny equation for multisized spherical particles. AIChE Journal, 1991, 37, 1583–1588. 51. A. Manz, C. S. Effenhauser, N. Burggraf, D. J. Harrison, K. Seiler, and K. Fluri, Electroosmotic pumping and electrophoretic separations for miniaturized chemical analysis systems. Journal of Micromechanics and Microengineering, 1994, 4, 257–265. 52. T. S. Stevens and H. J. Cortes, Electroosmotic propulsion of eluent through silica-based chromatographic media. Analytical Chemistry, 1983, 55, 1365. 53. G. V. Sherbert, The Biophysical Characterisation of the Cell Surface, Academic Press, 1978. 54. R. C. Boltz and T. Y. Miller, A Citrate Buffer System for Isoelectric Focusing and Electrophoresis of Living Mammalian Cells, in Electrophoresis ’78, N. Catsimpoolas (ed), Elsevier North Holland Biomedical Press (New York), 1978, 345–355. 55. L. E. Locascio, C. E. Perso, and C. S. Lee, Measurement of electroosmotic flow in plastic imprinted microfluid devices and the effect of protein adsorption on flow rate. Journal of Chromatography A, 1999, 857, 275–284. 56. S. L. R. Barker, D. Ross, M. J. Tarlov, M. Gaitan, and L. E. Locascio, Control of flow direction in microfluidic devices with polyelectrolyte multilayers. Analytical Chemistry, 2000, 99A, 5925–5929. 57. Y. Liu, J. C. Fanguy, J. M. Bledsoe, and C. S. Henry, Dynamic coating using polyelectrolyte multilayers for chemical control of electroosmotic flow in capillary electrophoresis microchips. Analytical Chemistry, 2000, 72, 5939–5944. 58. S. Wang, C. E. Perso, and M. D. Morris, Effects of alkaline hydrolysis and dynamic coating on the electroosmotic flow in polymeric microfabricated channels. Analytical Chemistry, 2000, 72, 1704–1706.
19
59. F. Bianchi, F. Wagner, P. Hoffmann, and H. H. Girault, Electroosmotic flow in composite microchannels and implications in microcapillary electrophoresis systems. Analytical Chemistry, 2001, 73, 829–836. 60. R. F. Probstein, Physicochemical Hydrodynamics, 2nd Edn, Wiley-Interscience, 2003, 305–306. 61. P. M. Ball, Spreading it about. Nature (London), 1989, 338, 624. 62. K. Kaski, Europhysics News, 1995, 26, 23. 63. C. S. Brazel and N. A. Peppas, Dimensionless analysis of swelling of hydrophilic glassy polymers with subsequent drug release from relaxing structures. Biomaterials, 1999, 20, 721–732. 64. N. A. Peppas and R. W. Korsmeyer, Dynamically Swelling Hydrogels in Controlled Release Applications, in Hydrogels in Medicine and Pharmacy, N. A. Peppas (ed), CRC Press Boca Raton, 1987, Vol 3. 65. A. R. Berens and H. B. Hopfenberg, Diffusion and relaxation in glassy polymer powders: 2. Separation of diffusion and relaxation parameters. Polymer, 1978, 19(5), 489–496. 66. S. J. Kim, K. J. Lee, I. Y. Kim, and S. I. Kim, Swelling kinetics of interpenetrating polymer hydrogels composed of poly(vinyl alcohol)/chitosan. Macromolecular Science, 2003, A40(5), 501–510. 67. D. Berger and D. C. T. Pei, Drying of hygroscopic capillary porous solids: a theoretical approach. International Journal of Heat and Mass Transfer, 1973, 16, 293–302. 68. H. B. Hopfenberg and H. L. Frisch, Transport of organic micromolecules in amorphous polymers. Polymer Letters, 1969, 7, 405–409. 69. S. Krishnamoorthy, V. B. Makhijani, M. Lei, M. G. Giridharan, and T. Tisone, Computational Studies of MembraneBased Test Formats. In: Technical Proceedings 2000 International Conference on Modeling and Simulation of Microsystems, MSM , San Diego, CA, 2000, 590–593.
42 Practical Aspects of Microfluidic Devices: Moving Fluids and Building Devices Bernhard H. Weigl,1 Ron L. Bardell2 and Catherine Cabrera3 1
Department of Bioengineering, University of Washington, Seattle, WA, USA, 2 MicroPlumbers Microsciences LLC, Seattle, WA and Minneapolis, MN, USA and 3 Biosensor and Molecular Technologies, MIT Lincoln Laboratory, Lexington, MA, USA
1 MOVING FLUIDS IN A MICROFLUIDIC DEVICE
“Fluid” and “fluid movement” lie at the heart of microfluidics. Various types of fluid motion are required, including moving fluids in a continuous stream, dispensing a controlled bolus of liquid, and getting the fluid into the device from the macroscopic world in the first place. Each of these topics is discussed below. Techniques for controlling the motion of fluids in microfluidic devices can be as simple as harnessing the hydrostatic pressure of a column of liquid in a tube placed above a port in the device or as complicated as a microfabricated multistage pump. A discussion of laminar flow in general and the theoretical basis for several means of generating laminar flow in a microfluidic device can be found in Chapter 41, Introduction to Microfluidic Techniques.
1.1
be used to perform “valveless” switching to inject fixed amounts of a fluid into a flow stream.1 By controlling the voltage and duration of the applied field, the fluid volume dispensed can be precisely and reproducibly controlled (see Figure 1). Alternate approaches rely on pressure-driven flow to actuate fluid dispensation. Microscale fluid movers are small enough to be included on-chip in a microfluidic device, though the additional cost may not be justified in a single-use chip. They can be fabricated from a number of different materials, including silicon, brass, glass, and polymers, and usually function by changing volume, usually by flexing a wall. They typically have some type of valving to direct the fluid flow and are driven by electrical energy. They can be categorized in a number of different ways, by: purpose, output type, working fluid, and physical mechanism. We may call them micropumps, though not all of them conform to the usual concept of a machine, especially those in which the physical mechanism has no moving parts whatsoever.
Dispensing Discrete Volumes
Many biomedical microfluidic applications require dispensing precise volumes of fluids, perhaps to another fluid, a dried reagent pellet, or to or from the outside world. Electroosmotic flow (EOF) can
1.2
Micropumps
Depending on their purpose, micropumps can be divided into continuous-flow pumps and batchflow pumps. We can categorize micropumps by
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS + Source +
Injection bolus
Injection bolus
Source
Waste −
Waste
Analysis (a)
Analysis (b)
−
Figure 1. Electrokinetic injection of fluid sample. (a) Formation of injection bolus. (b) Switch voltage and direct bolus to analysis region.
output type, either as a displacement source or as a pressure source. A displacement source changes the volume of the pump to “displace” a chosen amount of fluid; pressure is not controlled. For accurate delivery in an open-loop control system, the pump should be paused after fluid displacement until fluidic compliances (e.g., bubbles, flexible membranes) discharge and fluid motion ceases. A pressure source can provide continuous flow in an open-loop control system, but needs an integrated flow sensor in a closed-loop feedback system to deliver a precise volume of fluid. Flow-rate sensors (as shown in Figure 2) can be fluid-resistance based (viscosity dependent) or calorimetric (specific-heat dependent) and are calibrated for the particular fluid, but can self-adjust to temperature variation if temperature sensing is integrated. If the sample is of unknown or variable composition (e.g., blood), one approach to achieve dispensed volume accuracy is to avoid pumping the actual fluid and instead pump a “pusher” fluid, such as water or FluorinertTM . Disadvantages include contamination and/or dilution of the sample as the sample/pusher interface is stretched by the parabolic velocity profile of pressure-based flow and interchange by diffusion occurs. This is ameliorated if the pusher fluid and sample are immiscible. Air can be used as a pusher fluid or as a small bubble separating pusher and sample fluids, but its compliance lengthens time constants for starting/stopping flow and, if dispensing pressure is low enough, surface tension effects (e.g., variation in capillary pressure at the liquid meniscus) may make control of fluid position difficult. Micropumps can be separated into several categories by their physical mechanism: electromechanical, pneumatic, capillary, and osmotic. Most
(a)
(b)
Figure 2. Liquid mass flow meter (a) for flow rates from 50 nl s−1 to 40 µ l s−1 based on calorimetric sensing. Sensor body with control electronics is 35 × 70 mm (Sensirion AG, Z¨urich, CH). (b) A differential pressure sensor for resistance-based flow metering. Sensor body is 6 × 7 × 8 mm (Honeywell Sensing and Control, Freeport, IL).
of these are pressure sources, but electromechanical micropumps can be designed as displacement sources and pneumatic or capillary micropumps can function as displacement sources if the backpressure opposing fluid motion is very small. Electromechanical micropumps form the most varied category, but in shear number of units the capillary type is most common due to the ubiquity of lateral flow strips.
1.3
Continuous-flow Micropumps
Electromechanical micropumps typically use electrical energy to expand and/or contract the pump body and use check valves to direct the resulting flow downstream. There are three types of check valves: fixed, passive, and active. Fixed valves have no moving parts. Their inner channel is shaped to dissipate more viscous energy in
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
upstream than in downstream flow. Turning off a fixed-valve micropump does not stop the flow; a separate valve must be actuated. A major advantage is that they can pass particles nearly the size of their throat (typically> 50 µm) without wear. Passive and active valves typically employ moving flaps that seal against the valve seat. The clearance between the seat and the flap is generally quite small and the seat and flap can be damaged by particles. The hydrodynamic forces moving the flap of a passive valve are small and can be overwhelmed by high fluid viscosity or surface tension, especially once the valve seat is wetted but the pump body contains air. An active valve can overcome surface tension at the expense of mechanical and control complexity. A robust micropump is self-priming and bubble tolerant. Its compression ratio should be large enough to pump air against the upstream pressure drop. The most common actuator for electromechanical micropumps is a piezoelectric disk bonded to the flexible wall(s) of the pump body.2–7 These are often referred to as membrane pumps. Figures 3 and 4 show examples of electromechanical micropumps using fixed valves and actuated by piezoelectric disks. Some designs indirectly couple the piezoelectric actuator to the flexible wall by means of a lever to produce proportionally larger motion8,9 (Figure 5).
3
(a)
(b) Figure 4. (a) Prototype piezoelectric-disk fixed-valve micropump in plastic with 12-mm-diameter chamber by Bartels Mikrotechnik GmbH, Dortmund. (b) Piezoelectrically activated diaphragm micropump for liquids and gases by thinXXS Microtechnology AG, Zweibruecken.
Figure 3. Piezoelectric-disk fixed-valve micropump with a 3-mm-diameter chamber and 0.114-mm-wide curly channels that operate as leaky check valves, providing a higher pressure drop in the reverse (left-to-right) than in the forward direction. Highest efficiency is achieved when the actuation frequency is set at the system resonance of the pump. [Reprinted with permission Morris and Forster14 copyright 2003, IEEE.]
Another actuation method for electromechanical micropumps is electrostatic force obtained by applying opposite charges on parallel conducting plates, one of which is rigid and the other is a flexible wall of the pump body.10,11 This electric field can cause electrokinesis of particles in the fluid being pumped, which may be an undesirable effect. Electromechanical pumps that utilize electromagnetic actuators, similar to audio speaker technology, have also been developed.12,13 Though bulkier than an electrostatic actuator or piezoelectric disk, this design offers low voltage–high current operation, which may be more appropriate for in vivo use.
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS 5 6
2 3
4 8
1
7
Figure 5. Piezoelectric-lever micropump with passive valves. Illustrated are pump membrane (1), chamber (2), inlet (3) and outlet (4) check valves, membrane stiffener block (5), top (6) and bottom (7) glass cover plates, and membrane-motion limiters (8). During operation, the membrane is pushed up against the top glass cover plate by a piezoelectric lever actuator (not shown) that pokes through the center hole and pushes against the membrane stiffener block, which is bonded to the membrane. [Reprinted with permission Maillefer et al.9 copyright 1999, IEEE.]
Acrylic pump chambers
Glass backplate
Figure 6. Illustration of actuation of electrothermal peristaltic pump. [After Grosjean.15 ] The working fluid (e.g., air) is contained in the crosshatched volumes below the membrane. Heaters in each volume operate in sequence to heat and expand the working fluid, pressing and sealing the membrane against the upper chamber surface and moving the pumped fluid from chamber to chamber. Arrows show pumped fluid direction.
Other novel electromechanical pumps have been developed, including an electrothermal peristaltic pump.15 In this design, three sequential chambers are sequentially compressed by a flexible membrane as illustrated in Figure 6. Each chamber has its own heater. The movement of the membrane is accomplished by heating air to lower its density and increase its volume. The actuation frequency is low, but it can be operated as a self-priming pump.
1.4
Batch-flow Micropumps
All the electromechanical micropumps described thus far have been continuous-flow pumps. However, it is possible to develop batch-flow pumps, based on a chamber with one fluid connection and flexible walls that are actuated by any of the
electromechanical methods described above. They can be operated reversibly with fluid intake on volume expansion and fluid output during contraction. A ubiquitous form of batch pump is the printhead of ink-jet printers (e.g., Bio-DotTM ), which are excellent at placing precise drops a sample solution on a solid or liquid surface. Not all micropumps are electromechanical. Some examples include thermally induced bubbles.16 For example, Liu et al. have developed batch-flow pneumatic micropumps,17 which use electrothermal actuation. A second design is an electrochemical pump that produces gas by electrolysis. It is more efficient, but cannot be operated reversibly. A third design uses phase-change actuation, essentially boiling the working fluid. A capillary micropump is a batch-flow, nonreversible device usually implemented as an absorbent pad of nitrocellulose as in a lateral flow strip. The fluid flow rate is controlled by the cross section of the pad, the duration of flow by its length. When a single, very-low, flow rate (e.g., 1 ml h−1 ) is desired, an osmotic pump may be appropriate (e.g., ALZET 1003D). These are essentially fluid-displacement pumps driven by chemical potential. They consist of an inner chamber containing the fluid to be pumped and an outer chamber with a rigid semipermeable outer wall and a flexible impermeable inner wall. On exposure to water, the concentrated salt solution in the outer chamber expands and the inner chamber is compressed, forcing out the pumped fluid.
1.5
Macro-to-micro Interface for Transferring Fluids
The interface between the macroscopic and microscopic worlds is a major design challenge of microfluidic devices.18,19 The simplest solution is the open reservoir with pipette access to introduce or remove sample. Examples include microarrays and the Agilent LabChip and 2100 Bioanalyzer system. Another approach is to epoxy plastic or glass tubing directly to the device, but machining holes in glass or silicon, positioning the tube over the hole, or selecting an epoxy that will bond to a silicone polymer without clogging the hole make this approach nonoptimal. A better approach is to insert the microfluidic chip into a void within a
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
5
Figure 8. Manual microsyringe pump (Stoelting Co., Wood Dale, IL). (a)
A more automated fluid delivery system would load only the sample fluid by pipette and load all reagents from off-card syringe pumps through small-bore rigid tubing. Figure 8 shows a syringe pump that, while manual, is inexpensive and accurate. Automatic computercontrolled dispensing from multiple syringe pumps is available with pump modules like those shown in Figures 9 and 10. (b)
Figure 7. (a) An illustration of a combined electromicrofluidic packaging architecture. The fluidic printed wiring board (FPWB), the largest object, has fluidic connections (the black holes) as well as electrical connections. The electromicrofluidic dual in-line package plugs into the FPWB. The microfluidic integrated circuit (MIC) is the smallest object shown.20 (b) A pneumatic–microfluidic manifold that connects air and liquid lines to inlet/outlet ports on the edge of a clear plastic laminate microfluidic card that is held along that edge by a spring-loaded clamp. The air lines operate pneumatically actuated valves on the card to direct the fluid flow (Micronics, Inc., Redmond, WA).
soft lithography or plastic laminate structure that provides a macro–micro interface, such as wells that align with access holes in the chip. Once the fluid connection positions become fixed in a final microdevice design, a standardized layout fixture that supplies multiple interfaces: fluidic, electrical, vacuum, and hydraulic connections between microchip and reader instrument is advantageous. An example is the Caliper sipper chip that has a glass capillary attached to the single fluid inlet port. Figure 7 shows two more examples.
2 MICROCONSTRUCTION TECHNIQUES AND DEVICE EXAMPLES
Fabrication of prototype microdevices is more like watchmaking than like automobile engine repair. Features that are 10 µm wide are barely visible to the unaided eye; they look like scratches. Electrical and fluid inlet and outlet connections are often susceptible to damage. Dust control is essential, usually by deploying ionizers at the assembly bench; it is generally impossible to remove dust from a completed structure, even with compressed air. Achieving uniform surface energy throughout the internal passages of the microdevice is often critical to proper filling of the channels with a polar liquid or aqueous solution. Care must be taken to avoid resting microdevice parts on any surface that has molecules eager to migrate to the higher-energy surfaces of your microdevice, thus lowering the surface energy and making wetting more difficult. There is a wide range of technologies available for constructing microdevices: traditional lithography, soft lithography, or machining of plastics,
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
(a)
(a)
(b)
Figure 9. Syringe pump modules that can deliver microliter fluid volumes. (Kloehn, Ltd, Las Vegas, NV (a), Harvard Apparatus, Inc., Holliston, MA (b).)
metals, or glass by laser ablation or computernumerical-control (CNC) mill to produce finished parts or primary molds. Polymer films can be laser-cut, knife-cut, or stamp-cut with patterns that when stacked, aligned, and bonded together create a three-dimensional laminate structure that can contain fluidic channels, pneumatically activated valves, flex circuits to support sensors, porous membranes, and so on. Almost any object can be positioned within a molded part or a laminate. (b)
2.1
Traditional Lithographic Techniques
Microelectromechanical systems (MEMS), of which microfluidics is a subcategory, began as a offshoot of the computer chip processing industry, in which hard substrates, most commonly silicon, are the primary construction material. The basic paradigm of standard lithographic techniques involves the use of electromagnetic radiation, typically ultraviolet (UV) light, to transfer a pattern to a light-sensitive polymer (also known as photoresist), which undergoes a chemical response upon exposure to the radiation (see Figures 11–13). The exposed areas are defined by means of a photomask, usually consisting
Figure 10. Complete microsyringe pump systems. If multiple fluids can be injected simultaneously at the same flow rate into your microfluidic device, the system in (a) offers complete control of flow rates and volumes (Harvard Apparatus, Inc., Holliston, MA). If up to four fluids need to be controlled independently, the device in (b) controls flow rates, volumes, and timing, as well as automatic reloading of the syringes from supply bottles (Micronics, Inc., Redmond, WA). It also offers multiple pneumatic lines that can be switched independently between positive, negative, and ambient pressure. These are used to control the pneumatic liquid-control valves on the disposable plastic laminate cards that fit in the manifold (foreground).
of a patterned thin chromium film on a quartz plate; areas to be exposed are defined by open areas in the mask plate. After light exposure, the
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
polymer-coated disk must be developed, similar to developing a photograph, such that the areas exposed to the electromagnetic radiation behave in an opposite manner to unexposed areas; one set of areas polymerizes and remains on the surface while the other set is washed away. The item being machined then undergoes either material removal (e.g., etching of exposed substrate) or material addition (e.g., metal deposition) Finally, the remaining photoresist is removed, typically with a solvent, and the substrate is ready for the next round of machining. Traditional lithography methods are amenable to parallel processing and can produce mechanically strong and chemically resistant devices, with feature sizes as small as 0.1 µm. However, these methods are also expensive, require significant chemical processing equipment outlays, and often require toxic chemicals. In addition, the processes are often time consuming and not amenable to rapid design iterations. New methods of MEMS fabrication, categorized as “soft lithography”, address many of these concerns. For many BioMEMS applications, traditional lithographic techniques may be most applicable for creating a stamp or mold that is then used to produce large numbers of devices via soft lithography.
7
Apply or grow resist Expose to radiation
Add layer (optional)
Develop resist
Substrate (silicon or silicon oxide)
Traditional lithography process
Etch or deposit material
Remove remaining resist
Figure 11. General process of traditional lithography.
In that context, there are several common modifications to traditional lithography when used for bioMEMS applications. Given the relatively large feature size required for bioMEMS devices, the mask that contains the pattern can be as simple as an overhead transparency on which the design has been drawn by hand. The desired feature size is the single most important consideration in selecting a mask and illumination source, with budget and time Light Mask
Add photoresist
Bare substrate (silicon wafer)
Expose
Develop
Etch Remove photoresist
Figure 12. The photolithographic process, using positive photoresist followed by an etch step, is shown.
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS Anisotropic etch
(100) Surface orientation
Isotropic etch
Any orientation
(110) Surface orientation Figure 13. Etch patterns based on silicon type.
considerations coming a close second. Typically ultraviolet (UV) light is used, although electromagnetic waves with narrower wavelengths, such as X rays, have been used to achieve a finer resolution. In traditional photolithography, the photoresist layer thickness is typically on the order of 1 µm and is completely removed by the end of a micromachining cycle. In contrast, by using special photoresists at a thickness on the order of hundreds of microns, the photoresist itself can be patterned and used as a mold. For example, SU-8 photoresist can be layered up to 450 µm thickness and can be used to achieve aspect ratios of 15:1.21 SU-8 components can be used as molds for soft lithography or assembled together to form a microfluidic device. A complete integrated microfluidic system for mass spectrometry has been constructed using SU-8 to form multiple layers of channels sandwiched between silicon and Pyrex wafers.22 Two excellent sources of additional information on traditional lithography are VLSI Technology 23 and Introduction to Microelectronic Fabrication.24
2.2
lithography as “an elastomeric stamp with patterned relief structures on its surface that is used to generate patterns” and claim reproduction of feature sizes as small as 30 nm and up to 500 µm. A commonly used elastomer is a silicone rubber, polydimethylsiloxane (PDMS), but other elastomers are available, such as polyurethanes, polyimides, and phenol formaldehyde polymers. They describe a variety of soft lithography techniques: cast molding, replica molding (REM), microcontact printing (µCP), microtransfer molding (µTM), micromolding in capillaries (MIMIC), and solventassisted micromolding (SAMIM), but the most commonly used techniques are injection molding and embossing. In hot embossing (see Figure 14) a hard negative mold is pressed into a heat-softened thermoplastic polymer, which on cooling retains the pattern. In soft embossing a flexible rubber mold is filled with hot polymer under pressure (see Figure 15). Unlike hard polymers, the deformability (elasticity) of soft polymers like PDMS can be problematic for accurate registration between parts and limits the aspect ratio of features to between 0.2 and 2.0 to ensure structural integrity. A useful reference for practical tips is My Little Guide to Soft Lithography (or Soft Lithography for 27 ˚ Dummies) from Krogh and Asberg. Commonly used materials for primary molds are SU-8, a negative photoresist, which can be patterned using the standard lithographic processes21
Soft Lithography
Though well-developed, traditional lithographic techniques are expensive and require a relatively elaborate fabrication facility. Soft lithography attempts to address these concerns and offer additional flexibility, such as the ability to work with nonplanar surfaces and to use primary molds that are either positive (i.e., the mold is the same shape as the final part) or negative (i.e., the void in the mold is the same shape as the final part). A foundation paper with many useful references is from Xia and Whitesides.25 They define soft
Figure 14. SEM image of pyramids with a 30-µm base width fabricated in PMMA by hot embossing with a silicon mask formed by standard lithography with wet-chemical etching.26 [Reprinted with permission Lin et al.26 copyright 1998, Springer Verlag.]
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES 200 µm
and used as the primary mold in any of the soft lithography processes; and high-temperature epoxy, which can be used as a stamp for hot embossing.28 Mold wear can be reduced by making parts from negative secondary molds that were formed from a primary positive mold.
2.3
(a) 2 mm
(b)
(c)
5 mm
Figure 15. (a) Soft embossing of heated plastic resins in a hard rubber mold can produce high aspect ratio (height/width) features, such as these micropillars; (b) vertical features such as these posts do not need the draft angle that is required in injection molding since the mold can flex when pulling the part; (c) features can be placed on both sides of the part. [Photos courtesy of Edge Embossing LLC, Medford, MA.]
9
Machining, Cutting, and Laser Ablation
Tools for direct shaping of materials for microdevice constructions include lasers, knife plotters, and miniature CNC milling machines. All use a software “mask” that can be easily altered. Miniature CNC mills (e.g., Sherline 5400 CNC Mill with tolerance ∼25µm, Taig CNC Mill with tolerance ∼15µm) are low-cost (US $2000) means to shape metals, glass, silicon, polymers, and plastic sheets with small-diameter diamond-tipped bits (e.g., 50, 75, 100, 125 µm diameter). Figure 16 shows an example of machined acrylic sheet. Small knife plotters (e.g., SummaCut D60 vinyl cutter with tolerance ∼25 µm) are available for a similar price to cut plastic films up to 0.030 in. (30 mils, 800 µm) thick. There are several types of lasers capable of shaping parts for microdevices. Lasers operating at IR or visible light wavelengths provide lower resolution and remove material by melting, vaporization, and pyrolysis (thermal decomposition of chemical bonds). Lasers that operate in the UV range provide high-resolution photolytic (direct decomposition of chemical bonds due to absorption of single or multiple photons) micromachining. At high power density, both pyrolytic and photolytic decomposition create a rapid rise in pressure and temperature that ejects material in a process called ablation. The energy is absorbed into a depth of the material, depending on the first-order absorption cross section of the material. The absorbed energy is converted to heat with a temperature profile that decays exponentially into the surrounding material. The material directly exposed to the radiation heats and vaporizes rapidly, ejecting gas and particles while cooling the surrounding material. As the laser is pulsed, it moves in steps to adjacent uncut material, and the laser is pulsed again. The laser repetition rate, the pulse width, and the pulses per inch all affect the quality of the cut. (L. Levine, private communication.30 ) Figure 17 compares cut quality
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Figure 16. Close-up of CNC-machined fluidic prototype device.29 Machining is typically a more time-intensive process than laser ablation, but the edges of the machined features are sharper and the substrate material properties have not been altered by the high temperature characteristic of the ablation process.
Laser type
CO2
Tripled YAG
KrF excimer
18
>4000
Cut quality
Cutting time (s)
0.7
Figure 17. Trade-off between cut quality (a function of laser type, power, and spot size) and cutting time with Mylar as the substrate. [From Photomachining Inc.] Table 1. Comparison of wavelengths and spot sizes of various lasers. The smaller spot sizes give increased precision, but also require increased processing time
Laser type
CO2
YAG
Tripled YAG
KrF excimer
Color Wavelength (µm) Approximate spot size (µm)
IR 10.6 120
Near IR 1.06 12
Near UV 0.36 4
UV 0.25 3
From Laserod Inc.
and cutting time of different laser types when set up for high speed cutting. Table 1 compares the wavelengths and spot sizes of different types of lasers. CO2 lasers (e.g., Universal Laser M-360) can cut or engrave any of a wide variety of materials, such as: aluminum, brass, titanium, stainless steel, glass, silicon, and polymer or plastic sheet. The Nd:YAG (neodymium:yttrium–aluminum–garnet) laser is typically used to cut or weld metals. The tripled YAG can also cut some polymers, such as: Kapton, polycarbonate, and polyimide. An excimer laser is compatible with many polymers, including: fluorinated ethylene propylene (FEP), Kapton, parylene, polyethylene terephthalate (PET, Mylar),
polymethyl methacrylate (PMMA, acrylic), polycarbonate, polyester, polyethylene, polyimide, polyurethane, polyvinyl alcohol (PVA), and Teflon. Table 2 lists the preferred sizes and unique properties of the most commonly used materials. Cut edge quality depends on laser type. The ablation process of the UV lasers can produce a very clean edge, while the IR lasers tend to melt, instead of vaporize, the material.
2.4
Laminate Technologies
A very useful and adaptable construction technique for microfluidic devices is the concept of building
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
11
Table 2. Commonly available plastic sheet and film stock from suppliers/distributors: McMaster-Carr, CS Hyde Industries, and Sheffield Plastics
Material Polyester (PET or Mylar)
Available thickness (µm)
Polycarbonate Acrylic, clear (cast)
12.5, 25, 50, 75, 100, 125, 250 75, 125, 250 500, 1000, 1250, 1500
Acrylic, clear (extruded)
1000, 1500
Acrylic, black (extruded) Polyimide
250, 500, 1000, 1500 25, 50, 75
COP Silicone
50, 125, 250 125, 250, 500, 1000
Polypropylene (clear) Polypropylene (hazy) Polyethylene (LMW, HMW, or UHMW) PVDF (clear) FEP (clear) Urethane Acetal (white, black)
45 250, 500, 1500
Unique properties Okay optical properties, autofluorescence, most widely available in a variety of film stocks Good optical quality, low fluorescence Good optical quality, thickness highly variable, can come in UV grade transparent to 350 nm Good optical quality, grazes readily with exposure to even dilute alcohol Orange color, often thermally bonded at high temperature, not very suitable for CO2 laser Thickness variability around 20% Makes dust when cutting, requires air—assist to avoid flaming Usually low-quality material Readily available in food grade
50, 75 50, 75 50, 75+ 250, 500, 1000, 1500
COP: cyclic olefin polymer. LMW: low molecular weight. HMW: high molecular weight. UHMW: ultrahigh molecular weight. PVDF: polyvinylidene fluoride.
up a device by stacking layers, each of which has its own planar pattern of channels and chambers to hold fluids or simply holes (vias) to allow fluid communication between neighboring layers. (This stacking technique was intensively developed by engineers in the 1950s and 1960s for fluidic amplifiers in the flight control circuits of jet aircraft.) A basic microfluidic device can comprise a primary layer into which a pattern defining the fluid channels has been etched, machined, cast, or embossed and a second layer that serves as a cap to close off the channels. The layer materials can be any combination of silicon, glass, metals, polymers, or plastic films. If the pattern passes completely through the primary layer, then a third layer is needed as a capping layer. The choice of two-layer or three-layer construction depends mainly on the choice of pattern-making method. Adding additional layers allows overlapping channels and complex features like valves, mixing structures, and pumps, or the opportunity for easy parallelization.
2.5
Plastic Film and Sheet Stock (L. Levine, private communication)
Thinner materials are classified as films; those thicker than 0.010 in. are generally considered sheets. Other than custom stock, few materials are available in thicknesses between 0.010 and 0.015 in. Sheet materials up to 0.080 in. thick can be readily handled for laser cutting and lamination. Film thickness can be defined either by gauge (i.e., the thickness in inches multiplied by 100), or by “mil” thickness (i.e., 1 mil is equivalent to 0.001 in. = 25.4 µm and 40 mils (0.040 in.) = 1 mm). The thickness tolerance of film stock is generally 5–10%. Extruded sheet stock is similar, but the thickness tolerance of cast sheet stock can be as much as 25% of material thickness (e.g., cast acrylic). Other material characteristics of potential importance are the addition of flame retardants, typically brominated compounds, that may become chemical interferents in an assay and the autofluorescence of the material that may interfere with
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
high-sensitivity fluorescence detection. Materials specified as medical or food grade are often the better choice. The most widely available material is polyester film (i.e., PET, Mylar ). Widely used in the graphics industry, it can be purchased with surface treatments that enhance the adhesion of aqueousbased inks (usually corona treated), and is available in heat-sealable grades with a thin layer of low molecular weight (MW) polymer, usually a polyolefin or a polyvinylidene dichloride/PVA, or oligomers of PET itself.
2.6
Layer Bonding
The appropriate bonding method depends on the type of bond (permanent or reversible), the tolerance of the material to high temperatures, the deformability of the material, and solubility of the bonding agent to the fluids of interest (e.g., water, solvents). Some fabrication technologies, such as injection molding, plastic-film laminates, and soft lithography, have their own native bonding methods. Plastic-film laminates are typically fabricated by alternating layers of plastic film or rigid sheet with pressure-sensitive adhesive (PSA) film. For increased durability during assembly, the adhesive film is often a composite structure of a polyester carrier film coated with PSA on both sides, essentially double-sided sticky tape. One drawback is that, if fluid channels are cut in one of the layers to be bonded, or in the PSA film itself, the adhesive will be exposed to the fluid, which introduces a potential incompatibility to the use of organic solvents or the long-term storage of aqueous solution. Figure 18 shows a stack-up of layers to form a microfluidic card. Injection-molded parts are usually assembled by solvent bonding, diffusion bonding, ultrasonic bonding, or laser bonding, though PSA can be used as well. For devices implemented in PDMS by soft lithography, a low-temperature permanent bond is obtained by treating the bonding surfaces with an oxygen plasma to raise their surface energy. If the surfaces are placed in contact with each other within 3 min, a permanent bond is formed between the layers of PDMS (a rubbery transparent polymer) and glass, silicon, or itself. If a reversible
bond to glass is desired, the glass surface should be cleaned with isopropyl alcohol (IPA) to improve adhesion. A PSA film or double-stick tape (e.g., Adhesives Research, ARcare 7841) can also be used to bond PDMS to many materials, such as metals or printed-circuit boards. A reversible bond can be created between rigid materials that can tolerate a temperature of 100 ◦ C, including metal, glass, and ceramic, by using a wafer-mounting wax, such as Crystalbond 509, which is transparent in thin sections, dissolves in acetone, and, though it has a flow point at 120 ◦ C, is workable at 100 ◦ C. No bonding agent at all is necessary if the layers have optically smooth surfaces; they can be pressed together mechanically in a jig to form a watertight seal if they are completely dry when assembled. Permanent bonds can be formed with a lowviscosity epoxy (e.g., µ < 100 cP), which will wick over the smooth surface between parts, but be prevented from filling wider gaps by surface tension. Silicon and glass can be permanently bonded by anodic bonding, in which a high temperature (∼400 ◦ C) and a DC electrical potential (250 < V < 1000) cause sodium ions to migrate across the boundary from the glass to create a permanent electrostatic bond. Silicon can be bonded to silicon at lower temperatures by using an intermediate layer of sputtered lithium borosilicate.31
2.7
Surface Modification
In materials with naturally hydrophilic surfaces, channels that are designed to carry liquids are easily wetted if their width-to-height aspect ratio is near unity. Variations in surface energy will affect the wetting speed as the liquid proceeds through the channel, but the channel will wet as long as the meniscus contact angle remains less than 90◦ . However, even slight variations in surface energy between different locations along the wall can make wetting of channels with aspect ratios greater than 5 quite difficult (see Figure 19). There are several ways to achieve uniform surface energy. Sheet PET can be purchased with a hydrophilic surface coating, but manufacturing procedures are needed to ensure that the material does not contact any surface that will change its surface energy, such as a surface shedding hydrophobic particles or contaminated with skin
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
Glass (Pyrex) Layer 1: cover slip insert 0.125-mm PET
Layer 2: Layer 3: 0.025-mm adhesive 3.175-mm PMMA
Layer4: 0.100-mm ACA
13
Layer5: 0.125-mm PET
Figure 18. Layout of a microdevice built up from five plastic laminate layers and a glass insert. Layers 1 and 5 are polyethylene terephthalate (PET), layer 2 is a pressure-sensitive adhesive (PSA), layer 3 is polymethyl methacrylate (PMMA), and layer 4 is a sandwich of PSA with a PET center layer.
oils. These cautions should also be followed during assembly of parts that have undergone plasma treatment. Both oxygen and fluorine plasmas can create a temporary uniform hydrophilic surface. A direct-current corona torch forms hydroxyl groups on the surface of PET that, even after several days, can halve the contact angle of aqueous solutions. Another method to achieve uniform hydrophilic surfaces is to use stable coatings of hydrophilic polymers (e.g., AST HydroLast) of the channel walls after device assembly.
2.8
Integration of Heterogeneous Materials
It is possible to integrate a wide variety of materials as inserts into engineered voids in microdevices. Calculated tolerance stackups of inserts and part thicknesses should ensure that the insert is thinner than the void into which it fits. Any fluid inlet and outlet ports to the insert should be located on one side of the insert and pressed against or bonded to a mating surface of the surrounding part.
(a)
(b)
Figure 19. Wetting of two high width-to-height aspect ratio channels with hydrophilic walls. Channel walls in (a) have uniform surface energy; channel walls in (b) have variation in surface energy and, even though they are hydrophilic, air pockets are likely to form.
Thin-film membranes, proton-exchange membranes, and membranes for ultrafiltration, nanofiltration, and microfiltration can be integrated into a plastic-laminate or soft lithography system (see Figure 20). Applications such as ligand assays, enzymatic processes sensitive to trace metals, electrophoresis, degassing of aqueous solutions, and fluorometry are enabled in this way. Microdevices, such as lab-on-a-chip type devices, typically employ optically clear materials, but the feature size is small. Spherical or cylindrical lenses can be integrated to enable visual inspection with the unaided eye. Electronics can be integrated as polymer thickfilm (PTF) flexible circuits (i.e., flex circuits), which are screen-printed thick-film conductive inks on a low-cost polyester dielectric substrate. Multilayer circuits are produced with dielectric materials as insulating layers, and double-sided circuits with printed through-hole technologies. Lead-free, silver-loaded isotropic conductive adhesive provides both electrical and mechanical connection of active and passive surface-mounted components for applications such as optoelectronics, electrokinetics, and liquid crystal displays. Nanogen has been a leader in the field of integrating polymeric materials and IC chips for biological applications. In a collaboration with Genoptix and UC Irvine, researchers developed a microfluidic device that successfully isolated bacteria from a spiked blood sample and provides an excellent example of a heterogeneous microfluidic device, consisting of a variety of materials each machined in a different way (see Figure 21).32 The bottom layer, made of polycarbonate, contains
14
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Glass cover plate
PSA with microfluidic channel
Kapton with flip-chip bonded DEP chip
(a)
PSA Fluidic inlet/outlet
Polycarbonate substrate Figure 21. Schematic of a heterogeneous microfluidic device used to extract bacteria from a blood sample. [Reprinted with permission Huang et al.32 copyright 2003, Springer Science and Business media.]
(b) Antibody–dye conjugate
Test zone
Control zone Cylindrical lens
Vent Injection port Sample receiver (c)
1 cm
Evaporation port Vent or absorbent pad
Figure 20. A wide variety of materials can be integrated into microdevices: (a) porous membranes (the white circles) can sequester live bacteria in neighboring wells (NASA GeneSat card); (b) elastomers (the gray disks) can form the flexible membranes of pneumatically actuated valves (ALine, Inc., Redondo Beach, CA); (c) a cylindrical lens inserted in a micro lateral flow strip device to magnify test and control zones for viewing with the unaided eye (MicroPlumbers Microsciences LLC, Seattle, WA).
machined fluidic channels. The next layer, a PSA, adheres the bottom layer to the heart of the device, a dielectrophoresis (DEP) chip. The DEP layer is itself heterogeneous, consisting of a flexible polyimide layer patterned with electrical circuits and a silicon chip with electrodes fabricated using repeated cycles of traditional UV photolithography
and sputtered deposition of a titanium–tungsten adhesion layer followed by deposition of a platinum layer. The electrodes are 50 µm squares, spaced 50 µm apart. The DEP chip is attached to the polyimide layer via “bump” bonding with silver epoxy. To complete the device, a glass cover plate is sealed to the top by a second PSA layer with cutouts for fluidic channels. 2.9
Immobilization of Biological Material
There are a number of ways to immobilize bioactive molecules on solid substrates in microdevices. Proteins can be directly adsorbed on a surface, but surface hydrophobicity, charge, and chemical makeup can affect both their stability and orientation. Protein–material interactions may result in decreased protein activity and nonspecific protein adsorption can change the intended biological activity. Another approach, in addition to adsorption and covalent coupling, is tethering with an intermediate linker molecule such as polyethylene
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
oxide (PEO) chains that reduce nonspecific protein adsorption and denaturing of the target protein that is caused by interactions with the substrate. Compared to direct adsorption, tethered proteins have greater mobility, which avoids steric hindrance of binding processes and allows clustering of ligand-bound receptors within the cell membrane, which is known to be a requirement for activation of some intracellular signaling pathways. Substrate materials include polystyrene, PMMA, polyurethane, polyamide, and hydrophobized glass. Mesoporous silica can be integrated into a plastic-laminate or soft lithography structure. With negatively charged functional groups on its surface, a favorable chemical environment is created for proteins. The Pacific Northwest National Laboratory (PNNL) has demonstrated that high concentrations of an active enzyme can be immobilized in a mesoporous, functionalized silica structure while exhibiting higher activity than they would in aqueous solution. DNA can also be immobilized onto a surface, most commonly in the form of a DNA chip used for hybridization microarray assays. DNA chips can be functionalized in two different ways. Various DNA probes can be synthesized off-chip and applied to the chip surface using a linker chemistry to immobilize the DNA. Alternatively, the DNA can be synthesized in situ, base pair by base pair, an approach commercialized by Affymetrix. Photolithographic techniques are used to selectively protect and expose different regions of the chip, typically 18- to 20-µm squares. A solution containing a single deoxynucleotide (A, C, T, or G) linked to a removable protection group is then washed over the entire chip. Exposed squares participate in linking reactions, thus extending one base pair, while the rest of the chip remains unmodified.
2.10
Separation Matrices
Hydrogels can be cast into wells in plasticlaminate and soft lithography structures. This includes agarose gel separation matrix designed for the separation of nucleic acid (NA) fragments. Applications include separation of base pairs ranging in length from 100 to 1200 and separation of polymerase chain reaction (PCR) products.
15
3 PUTTING IT ALL TOGETHER – AN EXAMPLE OF THE DEVELOPMENT OF A FULLY INTEGRATED MICROFLUIDIC DEVICE
One of us (Weigl), with collaborators (collaborators are Micronics, Inc, for microfluidic card development, Yager Group, University of Washington, for dry-down reagent development, and Dr. Tarr, Washington University, for clinical validation and support), is developing a lab-on-a-card platform to identify enteric bacterial pathogens in patients presenting with acute diarrhea, with special reference to infections that might be encountered in developing countries.33,34 Component functions that are integrated on this platform include on-chip capture and lysing of pathogens, multiplexed NA amplification and on-chip detection, sample processing to support direct use of clinical specimens, and dry reagent storage and handling. All microfluidic functions are contained on the lab card. This new diagnostic test will be able to rapidly identify and differentiate Shigella dysenteriae serotype 1, Shigella toxin–producing Escherichia coli, E. coli 0157, Campylobacter jejuni, and Salmonella and Shigella species. The multiplex disposable enteric card (DEC) test (see schematic in Figure 22) will be an automated, rapid, easy-to-use, point-of-care platform to simultaneously detect multiple enteric pathogens causing disease with similar symptoms. It will provide a mechanism for accurate, point-of-care diagnosis with a rapid turnaround time for results. The method is based on laminate microfluidic lab card technology developed at Micronics and the University of Washington. This technology has been used in many different applications ranging from diffusion-based separation and detection to projects involving flow cytometry on a chip and NA–based amplification and detection techniques. The individual microfluidic subcircuits of the DEC card were initially designed and validated with both pathogen isolates as well as stool samples before integration of the subcircuits into a single disposable unit. The subcircuits are (i) capture and lysis of pathogens, (ii) NA extraction, (iii) NA amplification, and (iv) visual detection of amplified NA. A subcircuit card that can purify NAs from lysed leukocytes or bacteria (Figure 23) is loaded with specimen in a lysis solution, which allows RNA
16
MINIATURIZED, MICRO AND PARTICLE SYSTEMS Feces extract
Salmonella Shigella STEC
Campylobacter E. coll O157:H7 Positive control Immunocapture NA amplification NA LFS detection
Figure 22. Schematic of DEC approach showing a combination of pathogen capture and lysis, nucleic acid extraction, PCR, and visual detection of amplicons.
•
DNA/RNA capture from lysate sample
Lot no. NCI – 25
Micronic
Wash Air
Wash
Lyse
Purified sample
Capture filter •
Washing of DNA/RNA
Raw sample
To waste
•
Removal of DNA/RNA from card
Elute
Figure 23. Credit-card-sized microfluidic lab card that automates NA extraction.
xxx
xxx
xxx
xxx
xxx
xxx
xxx
xxx
xxx
xxx
xxx
xxx
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
17
Rapid PCR amplification breadboard and lab card 8 min for 35 cycles (nonoptimized)
(a)
(b)
(c)
Figure 24. Microfluidics-enabled rapid PCR amplification lab card and breadboard designed by Micronics, Inc. Prototype Thermal Electric Cooler (a), lab card with PCR reaction chambers (b), and thermal couple trace showing 60-s reverse 60 ◦ C reverse transcription followed by 16-s PCR cycles (c).
5′
3′
5′ B
B 5′
1
2
3
1
2
3
4
5
6
7
8
F 3′
3′ I F
E
ssDNA is captured by labeled probes
SA–MPs bind biotinlabeled probe
DNA-bound SA–MP complexes migrate through membrane. Anti-FITC IgG binds complexes
Absorbent pad facilitates wicking
5′
3′
ssDNA, amplified product
Capture probes
B
F
SA-coated microparticle
Anti-FITC antibody
Figure 25. Visual lateral flow-based amplicon detection process developed by Micronics Inc.
4
5
6
7
8
18
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
from the sample to bind to silica. An on-card silica filter and microfluidic valves provide fluid control to automate the RNA binding, washing, drying, and elution steps. The card was initially validated in experiments in which 106 white blood cells were processed using commercial kits or suspended in lysis buffer prior to loading on the lab card. Realtime PCR assays determined that the microfluidic card solutions were detected a few cycles earlier than the control RNeasy solutions. This card has also been validated for lysis and detection of gramnegative bacteria isolated from feces. Similarly, the NA amplification subcircuit has been designed (Figure 24) and tested for each of the pathogens. The PCR product generated by the subcircuit shown in Figure 24 is detected using a microfluidic visual amplicon detection method. Analogous to immunochromatographic strip tests, this method allows multiplexed detection of PCR-amplified products without instrumentation or software. As amplicons bound to colored microparticles accumulate on an antibody stripe immobilized in the microchannel, a colored line becomes visually apparent, indicating successful NA amplification and the presence of target (Figure 25). Procedural control lines have been included and results are available in a few minutes. This example demonstrates typical subcomponents that have to be integrated to form a fully functional microfluidic device. Further, this example is quite representative of the status of integrated microfluidic analysis devices today—many are in development in both corporate and academic settings, but few, if any, are currently in production or use. Given the enormous progress that has been made in the microfluidics and lab-on-a-chip fields over the 15 years since its inception, and the enormous and broad efforts that currently go into microfluidics research, the authors believe that fully integrated microfluidic devices will indeed become mainstream analytical tools within the decade.
REFERENCES 1. A. Manz, C. S. Effenhauser, N. Burggraf, D. J. Harrison, K. Seiler, and K. Fluri, Electroosmotic pumping and electrophoretic separations for miniaturized chemical analysis systems. Journal of Micromechanics and Microengineering, 1994, 4, 257–265.
2. F. Forster, R. Bardell, M. Afromowitz, and N. Sharma, Design, Fabrication and Testing of Fixed-valve Micropumps, In: Proceedings of the ASME Fluids Engineering Division, 1995 IMECE , San Francisco in November 1995, Vol. 234 pp. 39–44. 3. A. Olsson, P. Enoksson, G. Stemme, and E. Stemme, A Valve-less Planar Pump in Silicon, In: The 8th International Conference on Solid-state Sensors and Actuators, and Eurosensors IX , Stockholm, Sweden, 1995 June 25–29, pp. 291–294. 4. T. Gerlach and H. Wurmus, Working principle and performance of the dynamic micropump. Sensors and Actuators A (Physical), 1995, 50(1–2), 135–140. 5. Y. H. Mu, N. P. Hung, and K. A. Ngoi, Simulation and Optimization of a Piezoelectric Micro-pump, In: International Conference of ASME , Anaheim, California, 1998, November 15–20. 6. R. Linnemann, M. Richter, A. Leistner, and P. Woias, A Full Wafer Mounted Self-priming and Bubble-tolerant Piezoelectric Silicon Micropump, In: Proceedings of the Actuator ’98 Conference, Bremen, Germany, 1998, June 17–19, pp. 78–81. 7. P. Woias, R. Linnemann, M. Richter, A. Leistner, and B. Hillerich, A Silicon Micropump with a High Bubble Tolerance and Self-priming Capability, in Micro Total Analysis Systems, J. Harrison and A. Van den Berg (eds), Kluwer Academic Publishers, Dordrecht, 1998, pp. 383–386. 8. C. R. Tamanaha, L. J. Whitman, and R. J. Colton, Hybrid macro-micro fluidics system for a chip-based biosensor. Journal of Micromechanics and Microengineering, 2002, 12, N7–N17. 9. D. Maillefer, S. Gamper, B. Frehner, P. Balmer, H. van Lintel, and P. Renaud, A High Performance Silicon Micropump for an Implantable Drug Delivery System Technical Digest MEMS’99 , 1999, pp. 541–546. 10. A. Richter and R. Zengerle, Properties and Applications of a Micro Membrane Pump with Electrostatic Drive, In: 3rd International Conference of New Actuators (ACTUATOR ’92), Bremen, Germany, 1992, pp. 28–33. 11. M. T. A. Saif, E. Alaca, and H. Sehitoglu, Analytical modeling of electrostatic membrane actuator for micro pumps. Journal of Microelectromechanical Systems, 1999, 8(3), 335–345. 12. C. Yamahata and G. Gijs, Integrated Plastic Micropumps with Magnetic Actuation, In: NanoTech 2003, 7th Annual European Conference on Micro & Nanoscale Technologies for the Biosciences, Montreux, Switzerland, 2003 November 25–27. 13. H. J. Yoon, J. M. Jung, J. S. Jeong, and S. S. Yang, Micro devices for a cerebrospinal fluid (CSF) shunt system. Sensors and Actuators A, 2004, 110, 68–76. 14. C. J. Morris and F. K. Forster, Low-order modeling of resonance for fixed-valve micropumps based on first principles. Journal of Microelectromechanical Systems, 2003, 12, 325–334. 15. C. Grosjean and Y. C. Tai, A Thermopneumatic Peristaltic Micropump, In: 1999 International Conference on Solidstate Sensors and Actuators (Transducers ’99), Sendai, Japan, 1999 June, pp. 1776–1779. 16. J. H. Tsai and L. W. Lin, Micro-to-macro fluidic interconnectors with an integrated polymer sealant.
PRACTICAL ASPECTS OF MICROFLUIDIC DEVICES
17.
18. 19.
20.
21.
22.
23. 24. 25.
26.
Journal of Micromechanics and Microengineering, 2001, 11, 577–581. R. H. Liu, J. Yang, R. Lenigk, J. Bonanno, and P. Grodzinski, Self-contained, fully integrated biochip for sample preparation, polymerase chain reaction amplification, and DNA microarray detection. Analytical Chemistry, 2004, 76, 1824–1831. D. Ross and L. E. Locasio, Rapid microfluidic mixing. Analytical Chemistry, 2002, 74, 45–51. J. Liu, C. Hansen, and S. R. Quake, Solving the “Worldto-Chip” interface problem with a microfluidic matrix. Analytical Chemistry, 2003, 75, 4718–4723. P. Galambos and G. Benavides, Electrical and Fluidic Packaging of Surface Micromachined Electro-microfluidic Devices, In: SPIE Micromachining and Microfabrication Conference, San Jose, California, 2000 September. H. Lorenz, M. Despont, N. Fahmi, N. LaBianca, P. Renaud, and P. Vettiger, SU-8: a low-cost negative resist for MEMS. Journal of Micromechanics and Microengineering, 1997, 7, 121–124. J. Carlier, S. Arscott, V. Thomy, J. C. Fourrier, F. Caron, J. C. Camart, C. Druon, and P. Tabourier, Integrated microfluidics based on multi-layered SU-8 for mass spectrometry analysis. Journal of Micromechanics and Microengineering, 2004, 14, 619–624. S. M. Sze, VLSI Technology, McGraw-Hill Science/ Engineering/Math, 1988. R. C. Jaeger, Introduction to Microelectronic Fabrication, 2nd Edn, Prentice Hall, 2001, p. 232. Y. Xia and G. M. Whitesides, Soft lithography. Angewandte Chemie International Edition, 1998, 37, 550–575. L. Lin, Y. T. Cheng, and C. J. Chiu, Comparative study of hot embossed micro structures fabricated by laboratory
27.
28.
29. 30. 31.
32.
33.
34.
19
and commercial environments. Microsystem Technologies, 1998, 4, 113–116. ˚ L. Krogh and P. Asberg, My Little Guide to Soft Lithography (or Soft Lithography for Dummies), Link¨oping University, website, http://www.ifm.liu.se/∼petas/mikrosystem/Links/Material− files/Soft− Lithography− for− Dummies.pdf, 2003. T. Koerner, L. Brown, and R. D. Oleschuk, Prototyping of Polymeric Microfluidic Devices with Hot Embossing, In: Third Canadian Workshop on MEMS , Ottawa, Canada, 2003 August 22. Photo Courtesy of MicroPlumbers Microsciences LLC , http://www.microplumbers.com, 2007. Private communication from L. Levine, ALine Inc, Redondo Beach, CA, Hyperlink http://www.alineinc.com/. A. Gerlach, D. Maas, D. Seidel, H. Bartuch, S. Schundau, and K. Kaschlik, Low-temperature anodic bonding of silicon to silicon wafers by means of intermediate glass layers. Microsystem Technologies, 1999, 5, 144–149. Y. Huang, J. M. Yang, P.J. Hopkins, S. Kassegne, M. Tirado, A. H. Forster, and H. Reese, Separation of simulants of biological warfare agents from blood by a miniaturized dielectrophoresis device. Biomedical Devices, 2003, 5(3), 217–225. P. Yager, T. Edwards, E. Fu, K. Helton, K. Nelson, M. R. Tam, and B. H. Weigl, Microfluidic diagnostic technologies for global public health. Nature, 2006, 442(7101), 412–418. B. H. Weigl, J. Gerdes, P. Tarr, P. Yager, L. Dillman, R. Peck, S. Ramachandran, M. Lemba, M. Kokoris, M. Nabavi, F. Battrell, D. Hoekstra, E. J. Klein, and D. M. Denno, Fully integrated multiplexed Lab-on-achip assay for enteric pathogens. Proceedings of the SPIE, 2006, 6112, 1–11.
43 Polymer-Based Microsystem Techniques Matthias Schuenemann1 and Erol C. Harvey1,2 1
MiniFab (Aust) Pty. Ltd., Scoresby, Victoria, Australia and 2 Faculty of Engineering and Industrial Science, Swinburne University of Technology, Hawthorn, Victoria, Australia
1 INTRODUCTION
The need for point-of-care or point-of-use biosensors and bioanalytical devices in health care, in the food industry as well as for environmental testing has been a major factor in the development of low-cost microfluidic devices. The advantages of miniaturization (e.g., rapid analysis times, higher achievable analytical performance facilitated by changed fluid dynamics, low sample/reagent volumes, cost-effective reagent usage, reduced sample wastage, and reduced contamination and crosscontamination) have been attracting increasing attention from research groups as well as from commercial device manufacturers.1–3 Point-of-care devices enable diagnostic procedures at or close to the actual point of application (point-of-care, point-of-test). Extensive cleaning and test preparation procedures for setting up point-of-care tests are neither acceptable nor practical. For this reason, disposable devices are favored by the end user. On the other hand, it is very rarely economically feasible to integrate all technical components and subsystems required for complex sophisticated tests into disposable products. Therefore, biosensor systems tend to be divided into disposable chips or cartridges (or similar technical solutions) and a nondisposable host device (or instrument). The very essence of a successful design of a commercially viable pointof-care analysis system lies in the smart division
between the disposable cartridge and the reusable instrument, and the careful design of the interface between the two. Figure 1 shows a microscope slide-sized disposable biosensor chip with integrated micromixers, delay lines, passive valves, and electrochemical sensors. Economical restrictions dictate cost-efficient materials and technologies for the manufacturing of disposable cartridges. Many of the already published approaches to highly miniaturized bioanalytical systems are realized either in silicon4,5 or in glass,6,7 mostly relying on adapted silicon micromachining technologies and resulting in highly integrated miniaturized devices. Unfortunately, the respective manufacturing technologies as well as the utilized materials are rather expensive. For many potential applications of miniaturized bioanalytical devices, such high production costs cannot be justified. Polymer materials have been demonstrated to be a very versatile and cost-effective material choice, and the use of polymer-based microsystem techniques leads to bioanalytical devices with a very competitive cost of ownership per test.
2 MANUFACTURING OF LOW-COST POLYMER MICROFLUIDIC BIOCHIPS
One of the greatest challenges in developing lowcost disposable polymer microfluidic biosensors
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Figure 1. Disposable biosensor chip with integrated micromixers, delay lines, passive valves, and electrochemical sensors.
is to select a set of manufacturing processes that can be readily scaled in volume for each of the development stages, and that from the start, uses materials that will form the final device. This is essential in order to make cost effective the process of developing a biosensor that will pass regulatory compliance to become a commercial product. Assuming that the bioassay has already been demonstrated at the laboratory scale, and that the appropriate reporting mechanism has been chosen (e.g., electrochemical, fluorescence, gravimetric), the first stage is to demonstrate the incorporation of these processes within a microfluidic system. The fabrication processes used for this stage must allow rapid iteration of design. Only a few working units, typically fewer than 10, are required to demonstrate the proof-of-concept. If the assay involves several discrete processing steps requiring specialist fluidic solutions, for example, passive valving, filtering, or metering, these steps may be demonstrated separately to show proof-of-principle. We generally refer to this as a Stage 0 development and use it to give confidence that the assay can be transferred to a disposable biosensor. Although desirable that the materials used to fabricate the proof-of-concept devices are the same as those to be used in the final manufacture, this becomes an essential requirement for the next stage. In Stage 1 each of the individual components of the disposable biosensor are brought together to demonstrate a working assay and explore its performance in terms of sensitivity,
selectivity, specificity, and performance variation. This information is compared to the performance of the assay at the laboratory bench if the design requirement was set on the basis of the benchscale performance. Often the microfluidic design must be further improved as sources of manufacturing variation are identified. These might include variation in channel dimensions, electrode surface areas, optical interference, or variation in component adhesion. The manufacturing process typically produces batches of 10–100 units for this stage and could be considered “prototyping” since the devices are manufactured either individually or, perhaps using thermal embossing techniques in small batches of 10–50 per sheet.8 For Stage 2 the manufacturing process must incorporate some element of batch or volume manufacturing as the biosensor testing process should now obtain statistically significant performance variation data on several thousand devices. Clearly there is less opportunity, and hopefully less need, for design change; and high-speed replication processes such as injection molding can be used. The tooling for this replication step must be robust enough to produce repeatable results and can be created in a number of ways including nickel electroforming from a master, electrodischarge machining, or diamond-tipped precision milling.9 Stage 2 development is used to eliminate sources of variation in the manufacturing process such as polymer shrinkage, warpage, component misalignment during assembly, or irreproducible bonding.
POLYMER-BASED MICROSYSTEM TECHNIQUES
After this stage the biosensors may be ready for early stage field trials so that Stage 3 must be able to produce runs of up to 10 000 devices in a few months. If the developer aims for a lowcost disposable polymer biosensor there should be a clear manufacturing path to achieve production volumes of 105 –107 devices per year; clearly only achievable with high-speed replication, minimal assembly, and considerable process automation. This is best achieved using highly integrated polymer devices.
3 POLYMER MATERIALS
The selection of a suitable polymer material for a disposable biosensor cartridge is highly dependent on the intended application, the sample preparation, amplification, and detection process as well as the design complexity of the device. Almost every bioanalytical application will introduce specific technical demands for the chosen polymer material. Nonetheless, many applications share a common set of general requirements.10 Most polymer-based microfluidic chips and cartridges are manufactured from thermoplastic polymers. Thermoplastic polymers are characterized by first- and second-order thermal transitions. Whereas the first-order transition temperature usually corresponds to melting and allotropic transformation and is usually well outside the thermal working range for most materials, the secondorder transition temperature characterizes the point above which the fixed molecular structure of the material is partially broken down by a combination of thermal expansion and thermal agitation.11 Most thermoplastic polymers soften above this glass transition temperature, Tg , and exhibit a rubberlike behavior. Only when a material is highly crystalline are mechanical properties maintained above the glass transition temperature. Certain biological processes such as polymerase chain reaction (PCR) are performed at temperatures as high as 96 ◦ C, while other devices potentially need to survive hostile storage temperatures. The polymer material has to be selected so that the fabricated device does not deform or disintegrate at the maximum specified temperatures. Microfluidic structures and highly miniaturized fluidic devices are characterized by a surface-tovolume ratio that is at least 1 or 2 orders of
3
magnitude higher than in conventional laboratory equipment. The large surface-to-volume ratio leads to a much stronger interaction of sample material and reagents with the substrate material, compared with standard laboratory equipment. The diagnostic integrity of a device is therefore heavily influenced by biocompatibility of the polymer material as well as by material properties such as water vapor permeability, gas permeability, and water absorption. Biocompatibility of the substrate materials with the assay is an especially important requirement for a good analytical performance. Protein adsorption and cell adhesion are common phenomena interfering with bioanalytical processes. Protein adsorption is affected by factors such as surface energy/tension, surface charge, roughness, crystallinity, and entropy. Additionally, additives embedded in the polymer material such as plasticizers or UV stabilizers might lyse from the substrate material when subjected to elevated temperatures or contact with fluidic samples and reagents and inhibit biochemical reactions. The increased surface-to-volume ratios as well as the small amounts of target molecules characteristic of microfluidic systems make them particularly susceptible to these processes.12 A major drawback of polymers is their relatively high water vapor permeability rates, making polymers more difficult to use in bioanalytical devices compared to glass and metals. Any loss of water or water vapor from a sample or reagent may lead to a drift in pH or osmolarity and interfere with the analytical process on the device. Again, the large surface-to-volume ratio in miniaturized bioanalytical devices increases their susceptibility to this. The rate of potential fluid loss depends upon material properties such as water vapor permeability and water absorption rates as well as on design factors such as the diffusion path length from the microfluidic structure to the external environment. Detection of reaction products forms a fundamental part of the bioanalytical device. Many detection methods rely on optical techniques, such as detecting fluorescent dyes attached to proteins or optical measurement of spots on microarrays.1,13 An optically transparent material is essential for devices that depend on such detection techniques. However, many polymer materials are characterized by background fluorescence
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
(or autofluorescence), resulting either from fluorescence intrinsic to the bulk polymer or from additives, impurities, or degradation products. The small sample and reagent volumes in miniaturized biosensors as well as the comparatively small amounts of fluorophores attached to the respective targets will result in small fluorescence signals. Background fluorescence decreases the signal-tonoise ratio significantly. It is therefore important to analyze, understand, and consider autofluorescence properties for successful system design as well as for suitable material selection.14 A well-informed selection of a suitable polymer material is critical not only to the performance but also to the manufacturability of the biosensor or biochip. During development and prototyping, significant research efforts have to be invested to overcome technical challenges resulting from imperfect material behavior. Having to change materials en route from Stage 1 to Stage 3 is likely to impose considerable cost as well as significant time delays in any development project. Manufacturing-related material requirements may include laser machinability, low shrinkage during injection molding, and sufficient resistance to cleaning agents. The material should be commercially available and reasonably well introduced into the market. A material with only a single supplier can potentially become temporarily or permanently unavailable, putting the commercial prospects of a device in a highly dangerous position. The selection of a rarely used material may also delay regulatory approval processes. Polymeric materials like polycarbonate (PC),15 polydimethylsiloxane (PDMS),16 polyethylene terephthalate (PET),17 polymethyl methacrylate (PMMA),18 cyclic olefin copolymer (COC),19 and polyimide (PI)20 have commonly been used to fabricate prototypes of microfluidic bioanalytical devices. Less frequently, other standard organic polymeric materials such as polyethylene (PE), polyetheretherketone (PEEK), polystyrene (PS), polyamide (PA), polyetherimide (PEI), liquid crystal polymer (LCP), polypropylene (PP), polybutylene terephthalate (PBT), polyoxymethylene (POM), polyphenylene ether (PPE), and polysulfone (PSU) have successfully been used in microtechnology, mainly in a research environment outside the miniaturized biosensor domain.8 PMMA and PC meet the basic material requirements for miniaturized biosensors, are widely
available and comparatively easy to machine and are therefore favored by the research community.10,12 Another material receiving increasing attention is PET,17,21,22 its main advantages being its widespread use in the packaging and printing industry and the extensive fabrication and processing knowledge base. PDMS is another transparent, elastomeric material that is used in soft lithography and molding processes for prototyping.23 Although quite suitable for the fabrication of prototypes, its disadvantages include limited mechanical strength, limited ability to bond to other polymer materials, and very high water vapor permeability. A newer group of materials, COC, has great potential in microanalytical processes for its high chemical stability, low permeability rates, and very good optical properties,24 but suffers from high costs and limited availability. Table 1 shows a qualitative overview of the suitability of selected polymer materials for biochip manufacturing. The analysis shows that there is no one ideal polymer able to meet all requirements. Rather, the device or package designer has to find a technically and economically valid compromise for his specific application, taking into account such factors as the temperature regime of the analytical process, the storage conditions for the disposables prior to their use, the emission wavelength of the utilized fluorophores, the design complexity, and the fabrication technology most suitable for the expected production volumes.12
4 MICROSTRUCTURING OF POLYMERIC MATERIALS
One of the greatest challenges in developing lowcost disposable polymer microfluidic biosensors is to select a set of manufacturing processes that can be readily scaled in volume for each of the development stages. For this reason direct machining, laser cutting, and thermal embossing are attractive methods for development since each is able to structure a bulk polymer sheet that is available in high volume with excellent uniformity. Also, in the case of thermoplastics, the sheet form of the polymer can be considered to have properties similar to that achieved by injection molding (although in some specific details this may not be a valid assumption as UV laser cutting can leave
Water absorption
Thermal stability
Autofluorescence n/a n/a n/a n/a
n/a n/a n/a
n/a
Machinability
Cost
Cutting/blanking Micromilling
Injection molding
Laser excimer (λ = 248 nm)
Laser 3 ω Nd:YAG (λ = 355 nm)
Laser CO2 (λ = 10.6 µm)
Optical transparency
Material characteristics and machinability of polymer materials can vary significantly depending on manufacturer and material grade, due to the influence of additives such as plasticizers or UV stabilizers. Especially laser micromachining processes are highly sensitive to the presence of such additives. Figures in the table are therefore given for base polymers/most common polymer grades. Most favorable material least favorable material.
COC PC PDMS PEEK PET High-density PE Low-density PE PI PMMA PS Polytetrafluoroethylene Polyvinylchloride PVDC Polyvinylidene fluoride
Material
Water vapor permeability
Properties
Hot embossing
Table 1. Suitability of selected polymer materials for biochip manufacturing
POLYMER-BASED MICROSYSTEM TECHNIQUES 5
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
a temporary surface activation not produced by molding techniques).25
4.1
Laser Fabrication
A wide range of lasers able to cut and pattern an even wider range of materials suitable for polymer biosensor packaging is now available.26 Laser micromachining systems have the advantage of being noncontact tools that can be rapidly reprogrammed to produce varied patterns, making them particularly suitable for the design and development phase of the microfluidic biosensor. Lasers are available that produce either pulsed or continuous radiation and are characterized by the wavelength of the light they produce. For micromachining applications pulsed lasers are essential since they allow greater control of the molten, or heat-affected zone in comparison to continuous systems. Generally the shorter the pulse length, the smaller the heat-affected zone. Table 2 shows a range of the popular pulsed lasers used for microfabrication and their operating characteristics. It should be obvious that for any material to be able to be laser machined it should absorb light at the wavelength of the laser to be used. For this reason, many infrared laser sources (e.g., carbon dioxide lasers (10.6 µm) or fiber lasers (1.09–1.55 µm depending upon type)) will produce wildly varying results depending on the nature of the polymer used or the precise detail of
additives in the polymer. Unfortunately the buyer of the bulk polymer often is unable to know what these additives are and in what concentration they are present, therefore much laser work tends to be by trial and error. The most popular pulsed visible lasers are specially modified Nd:YAG (neodymium–yttrium–aluminum–garnet) lasers that can produce powerful pulses of green (533 nm) or ultraviolet (256 nm) light at high repetition rates. The alternate wavelengths are produced by placing wavelength doubling or tripling crystals in the beam, a technique that can be applied to some other lasers, for example the infrared fiber laser or the green copper vapor laser (CVL), enabling each to produce ultraviolet pulses. Ultraviolet pulses are the most useful wavelength for micromachining applications since they produce the least thermal damage and, since most polymers strongly absorb ultraviolet radiation, can provide control of the depth of laser machining. Excimer lasers are pulsed gas lasers that produce ultraviolet light without the aid of doubling crystals. Another major difference from other laser sources is the large rectangular beam produced by excimer lasers. Hence rather than being used as a focused spot, excimer lasers are generally used as an illumination source for a stencil or mask that is imaged onto the polymer workpiece. If an image-reducing lens is used, the features produced at the workpiece can be of submicron size, and for most polymer materials the machined depth is typically less than a micron per laser pulse.
Table 2. Pulsed laser types and their operating characteristics
Pulsed laser source
Type
Frequency multiplied
Wavelength
Carbon dioxide (CO2 ) Ti:Sapphire Nd:YAG Nd:YAG 2 ω Nd:YAG 3 ω Nd:YAG 4 ω Copper Vapor (CVL)
Infrared Infrared Infrared Visible Ultraviolet Ultraviolet Visible Visible Ultraviolet Ultraviolet Ultraviolet Ultraviolet Ultraviolet Ultraviolet
Fundamental Fundamental (tunable) Fundamental Doubled Tripled Quadrupled Fundamental Fundamental Doubled Doubled Fundamental Fundamental Fundamental Fundamental
9.24–10.64 µm 700–1080 nm 1.064 µm 532 nm 355 nm 266 nm 511 nm 578 nm 255 nm 271 nm 308 nm 248 nm 193 nm 157 nm
Copper Vapor 2 ω (CVL 2 ω) Excimer Excimer Excimer Excimer (a)
(XeCl) (KrF) (ArF) (F2)
Typical specifications. Values will vary depending upon configuration and operating conditions.
Pulse width(a)
Repetition rate(a)
25 µs–1 ms 20–100 fs 10–300 ns
20 kHz 75–120 MHz 2–100 kHz
20 ns
10–20 kHz
20 ns
100 Hz–6 kHz
POLYMER-BASED MICROSYSTEM TECHNIQUES
Hence by computer-controlled manipulation of the number of pulses and the mask shape, complex three-dimensional shapes such as channels, ports, weirs, wells, mixers, and bifurcators can be rapidly fabricated in polymers.27 It is necessary to implement some form of polymer replication process once increasing manufacturing volumes are required. A range of microreplication processes for thermoplastic polymers are available that are generally smaller-scale implementations of their macroworld counterparts. These include hot embossing, injection molding, reaction injection molding, injection compression molding, and thermoforming.28
4.2
Hot Embossing
Hot embossing is a popular replication process since it is relatively easy to tool-up for and is a comparatively easy process to execute. It is able to achieve excellent replication of high-aspect-ratio microstructures, for example 8-µm-wide beams 150 µm tall in PMMA,8 but has the disadvantage of a slow cycle time that can be up to 20–30 min. In the hot-embossing process a mold tool is created that has the inverse features of the desired shape. This can be done by direct precision machining of metals or can be a nickel electroform grown from a previously microfabricated master. This master could be made in a number of ways including laser ablation of polymers, wet or dry lithographic etching in silicon,29 UV lithography in thick SU-8 photoresist, or synchrotron exposure using the LIGA process (a German acronym for lithography, electroplating and replication). In some cases the polymer or silicon master can itself be used as the embossing tool.29–31 The tool is mounted into a press and heated to a temperature slightly above the glass transition temperature, Tg of the polymer to be embossed (PMMA 106 ◦ C, PC 150 ◦ C). Polymer sheet is introduced into the press, which is closed, and a force of between 20–30 kN over a 4-in.-diameter area is applied under a vacuum of around 10−1 mbar. After a hold time of a few minutes and with the force still applied, the tool is then cooled to below Tg to stabilize the polymer before opening and demolding. Optimization of the process will reduce the thermal stresses in the part realizing improved replication, but usually at the cost of increased cycle time.
7
Nanosized features are readily reproduced by hot embossing. While this may be useful it also means that imperfections and roughness in the tool are also readily reproduced.
4.3
Injection Molding
Injection molding is a highly developed process for macroreplication and is now increasingly available for microscale thermoplastic replication.28 The process has the advantage of extremely fast cycle times, of the order of a few seconds per cycle, but at the cost of a considerably more complex molding tools. In this process, a microstructured mold insert is placed within a specially formed mold cavity within the injection-molding machine. Polymer beads are heated above Tg and forced to flow into the mold cavity at high pressure where they rapidly cool to form a solid component that is ejected from the tool. This cyclic temperature control is called variotherm (variothermal ). The resulting parts can have high degrees of internal stress and variable rates of shrinkage due to the rapid cooling of the polymer in the tool. Minimizing these effects as well as creating an effective ejection system for removing the part from the tool becomes part of the skill in designing good injection-molding systems. The ability to produce many millions of parts per year at relatively low cost makes this an important part of the industrial manufacturing process. Table 3 compares selected manufacturing technologies for polymer biochips and rates them according to their suitability for tool making, prototyping, and volume production. Having created the polymer components of the microfluidic system they must then be assembled and bonded together to form complete units. 5 SURFACE MODIFICATION OF POLYMER MATERIALS
Surface modification techniques change the surface characteristics of a material for a specific application without severely affecting the bulk properties of the polymer substrate. A range of biological, physical, and chemical methods are employed to modify surface properties such as wettability, permeability, biocompatibility,
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
LIGA Silicon bulk micromachining Laser micromachining (CO2 , λ = 10 µm) Laser machining (Nd:YAG, λ = 355 nm) Laser machining (Excimer, λ = 248 nm) Micromilling µEDM Plasma etching Hot embossing Injection molding Roto-cutting blanking Stereolithography
Investment costs/ operational costs
Process time/throughput
Process flexibility
3D capabilities
Precision
Technology
Minimum structure width
Table 3. Selected manufacturing technologies for polymer biochips
/ / / / / / / / / / / /
Application Toolmaking Toolmaking Prototyping production Prototyping toolmaking Prototyping toolmaking Prototyping toolmaking Toolmaking Prototyping production Toolmaking production Production Production Prototyping toolmaking
µEDM: microelectrodischarge machining. Most favorable process least favorable process.
chemical inertness, bondability, electrical characteristics, or optical properties.32 The majority of polymer packaging technologies use surface modification techniques in order to condition the polymer surfaces for the bonding process. Most polymer surfaces are hydrophobic, leading to poor wetting of the surface and therefore a poor spreading of adhesives or poor adhesion during bonding. One commonly used surface modification method is the use of a corona discharge to oxidize the polymer surface by ionized particles.33 Although corona treatment is very cost effective compared with other surface modification methods, its short shelf-life and limitations in the treatable thickness of polymer sheets (up to 250 µm) restrict its applicability. An alternative to corona discharge is gas plasma treatment. Typically, gas plasma treatment of polymers are utilized to ablate surface contamination, introduce chemically functional groups to the surface, and/or to introduce cross-linking.34 Common gases utilized in this process include oxygen, nitrogen, and argon. One of the most widely used applications of gas plasma treatment is the oxygen plasma modification of PDMS utilized to convert hydrophobic Si–C siloxane groups to hydrophilic
SiOx groups.35 Similar to the corona discharge process, the surface modification can be short lived due to polymer chain mobility. Another major disadvantage of gas plasma treatment is the requirement for an evacuated environment. In an atmospheric plasma treatment process a polymer film can be passed through the plasma beam without the need for a vacuum, allowing for continuous in-line processing.36 Many surface modification methods combine a chemical surface treatment with physical changes to surface properties. Polymer surfaces can be grafted with chemicals that provide excellent adhesion to a large range of materials. This process starts with a surface activation step, followed by the deposition of chemicals dissolved in a water solution (e.g., silanes) which bond to the activated polymer.37 In another surface modification approach, PET surfaces have been modified using a saponification reaction, in which polymer substrates were immersed in a bath of highly concentrated NaOH to etch the surface immediately before bonding.21 The effect of photodegradation has been utilized to modify the surface of PMMA by exposing the polymer film to UV light to soften the top surface of the substrate.38
POLYMER-BASED MICROSYSTEM TECHNIQUES
The nonspecific adsorption of proteins to polymer surfaces (and surfaces of other materials) is a significant problem encountered in a variety of biotechnological and bioanalytical applications. The behavior of hydrophilic polymer surfaces can vary considerably from nonfouling to selectively binding to high binding, depending on their respective physical and chemical surface characteristics. Proteins also adsorb to hydrophobic surfaces, but tend to denature, resulting in a thin, denatured, but persistently attached protein film preventing subsequent protein adsorption. This behavior may lead to a depletion of available target proteins and may significantly distort the measurements. For processes such as PCR, the use of different additives, for example, polyethylene glycol (PEG) or bovine serum albumin (BSA) in the PCR buffer has been shown to reduce nonspecific binding of key assay components to polymer surfaces and to improve process yield.15,39–41 The grafting of polyethylene oxide (PEO) has also been demonstrated to reduce nonspecific binding.42 Permeability of the substrate material is another essential property to control. Microsized bioassays
9
only handle small amount of fluids and reagents. It is therefore essential to maintain the volume of these fluids. A small fluid reduction caused by permeable materials affects the integrity of the process. Modifying the surface to become less permeable assists in avoiding this problem. Barrier layers on flexible polymer substrates are usually formed by depositing a thin layer of inorganic material like aluminum or silicon oxide on commodity polymers, such as PE or PET.43 A major disadvantage of this method is the loss of optical transparency preventing the use of optical detection techniques. In another approach, high barrier polymers are formed by co-extruding commodity polymers with polymer barrier layers, such as polyvinylidene chloride (PVDC). A very promising approach to surface modification is surface coating with parylene, a conformable, transparent coating based on polymerized para-xylylene. Parylene is deposited via chemical vapor deposition. In addition to preventing fluid losses through substrate materials, parylene reduces protein adsorption and cell adhesion.44 Since the process requires vacuum
Investment/operational costs
Process compatibility
Option for selective treatment
Surface treatment
Sustainability of effect
Strength of effect
Table 4. Surface modification of polymer materials for biochip manufacturing
Surface modification techniques for adhesion promotion Saponification Photodegradiation (UV) Corona treatment Plasma treatment Polymer grafting Primer deposition
/ / / / / /
Surface modification techniques for biocompatibility PEO PEG BSA Parylene deposition
/ / / /
Surface modification techniques for water vapor permeability reduction Barrier layer deposition Parylene deposition Barrier layer co-extrusion Most favorable process
/ / /
least favorable process.
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
conditions, it is difficult to integrate into continuous productions systems. Surface modification techniques are usually applied before bonding the prefabricated polymer layers or parts together. Unfortunately, surface requirements for bondability, biocompatibility, and permeability are usually contradictory and potentially conflicting. Surface modifications to condition the polymer surfaces for the bonding process often leave reactive functional chemical groups on the surface, which may inhibit bioanalytical processes. The same inhibition can occur when treating a surface to minimize loss of reagent. Again, the consequences of these contradictions are amplified by the large surface-tovolume ratio typical for miniaturized microfluidic devices. Each surface modification addressing one requirement therefore needs cross-checking to ensure compatibility with other requirements. Table 4 shows a qualitative assessment of selected surface modification techniques of polymer materials for biochip manufacturing.
6 ASSEMBLY AND PACKAGING OF POLYMER-BASED MICRODEVICES
Almost all microfluidic devices are based at least partly on fully enclosed and sealed microfluidic structures (i.e., channels, reservoirs, process chambers). Polymer microfabrication techniques, however, are usually only capable of generating open fluidic structures, and rely on bonding and sealing technology for the completion of the microfluidic device. The simplest way to bond and seal a microfluidic structure is to cap a single planar microstructured polymer substrate on one or both sides with an unstructured cover layer. More sophisticated devices may be assembled from several stacked layers of microstructured polymer films or substrates, creating true three-dimensional microfluidic systems. The number of layers that can be bonded together is only limited by the applied bonding technique, the complexity of the design, and the feature size of the microfluidic structures. As an example, Figure 2 shows a PCR cartridge, driven by pneumatically actuated peristaltic on-chip pumps and controlled by pneumatically actuated on-chip valves. The device is fabricated from seven vertically assembled polymer layers.
The actual microfluidic reactor consists of three microstructured layers. The pneumatic control circuit is realized by another three microstructured layers, and an elastomeric membrane layer joins and separates the two three-layer prefabricates. Primary functions for assembly, bonding, and sealing are to realize fully functional microfluidic devices by joining microstructured prefabricates, to prevent leakage from microfluidic features and to provide sufficient structural integrity within the assembled device. Several bonding technologies can be used for assembly, bonding, and sealing of prestructured polymer layers (see Table 5). Most of these are adapted from standard polymer manufacturing technologies. For microfluidic circuits, bonding technologies that enable a selective bonding and sealing only at preselected areas (e.g., around the channel walls) are especially interesting. Although these technologies are usually more costly than bulk bonding techniques, many of them reduce the risk of involuntarily blocking channels and microfluidic structures and/or avoid accidental exposure of biological fluids to potentially nonbiocompatible auxiliary materials (e.g., adhesives, solvents). The joining of polymer substrates using adhesives is widely used during prototyping of polymer microfluidic devices. Adhesives are capable of bonding between dissimilar polymers as well as bonding polymers to metal layers or polymer prefabricates with large metallization areas. Additionally, adhesive bonding processes do not require extensive capital investment. The direct application of an adhesive layer onto the surface of the polymer substrate carries a high risk of channel blocking. More commonly, adhesives (i.e., ultraviolet curable adhesives) are selectively applied to the bond surface using screen-printing techniques.45 However, adhesives spread after application and clamping, potentially entering microsized features and clogging channels, mixers, or fluidic junctions. A voidless adhesive joint with liquid or thixotropic adhesives and screen printing is difficult to realize around complex or densely packed microstructures. The use of adhesive films instead of liquid adhesives prevents the undesired flow of adhesives into microfeatures, but necessitates prestructuring of adhesive film to create the required microfluidic vias between the polymer layers and careful alignment of the
POLYMER-BASED MICROSYSTEM TECHNIQUES
11
(a)
(b) Figure 2. (a) Design for a polymer biochip fabricated from vertically assembled microstructured polymer layers. (b) Polymer biochip fabricated from vertically assembled microstructured polymer layers—manufactured layers and completed device.
Table 5. Systematization of polymer bonding techniques
Bulk bonding
Direct bond between structural layers
Bond mediated by auxiliary materials
Lamination Thermal diffusion bonding UV-assisted thermal diffusion bonding Plasma-assisted thermal diffusion bonding
Adhesive bonding Adhesive tape bonding Solvent bonding Chemical etching–assisted thermal diffusion bonding Screen-printed adhesives and adhesive bonding Prestructured adhesive tape and adhesive bonding Light-absorbing dyes laser welding Microwave absorber Microwave welding
Ultrasonic welding Selective bonding Transmission laser welding Reverse conductive laser welding
adhesive film relative to the structures on the polymer substrates, thus increasing manufacturing costs significantly. Additionally, adhesives have to be selected carefully as there is a high risk of undesired molecular interaction of the biological assay with the surface chemistry of the adhesive layer,
which may influence or even inhibit the biochemical processes on the device.12 Thermal lamination is a simple, effective method to cap single planar layers that contain microfluidic structures. A very common laminate consists of a thin PE/PET film thermally bonded
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
to PET substrates using a hot laminator.22,46,47 Thermal lamination is especially suited to seal simple devices consisting of only one microstructured layer, but it has considerable limitations in sealing large, shallow features (reservoirs, reaction chambers) without any additional structural support, as the laminating film sags into these structures during lamination and potentially interferes with their intended function. Additionally, multilayer devices usually cannot as easily be sealed with thermal lamination since the laminating film isolates microfluidic layers from each other by blocking microfluidic vias between layers. One approach to realize vertically integrated microfluidic multilayer devices via lamination is to microstructure (relatively thick) PE/PET/PE films (i.e., by laser manufacturing or roto-cutting) and laminate them together (i.e., in a reel-to-reel system). For prototype or small series production, thermal diffusion bonding, realized by applying heat and pressure over a given time to preassembled polymer slides, is a suitable method to bond prestructured polymer layers to each other. As no auxiliary materials such as adhesives are required, potential channel blocking is avoided, and biocompatibility is maintained. The bonding success depends heavily on the mobility of molecular chains in the polymer. Thus, only very similar materials with identical glass transition temperature can be bonded together. Successful thermal diffusion bonding has been reported for PC, PET, PMMA, and COC.12,48,49 Bonding temperature and applied pressure are critical as an unsuitable parameter combination will deform the material and collapse the channels. For the device in Figure 2, two three-layer PC prefabricates were manufactured separately by thermal diffusion bonding. The laser-machined PC layers, which had alignment features incorporated into the design, were placed into an in-house developed hot embossing tool. A temperature of 135 ◦ C and a pressure of 4.2–4.5 MPa were applied for 20 min.12 A major disadvantage of thermal diffusion bonding is the required process time of up to 30 min for a bond with sufficient strength. UV treatment prior to bonding allows for bonds to form at a significantly faster rate compared to thermal diffusion bonding of untreated surfaces.38 The number of layers that can be bonded together by this technology is limited by the complexity of the design
and the feature size of the cut-out structures. The pressure distribution to any bond area situated above or below a void in the structure (e.g., a channel or a process chamber) is very uneven and might locally prevent successful bonding. Strict observation of design rules is required. Solvent bonding involves the exposure of a polymer surface to a suitable solvent. Upon joining two solvent-exposed surfaces, the interfaces of both substrates diffuse in one another and form a bond after the solvent evaporates from the assembly. Although solvent bonding is a common joining method for the assembly of polymer parts with many material/solvent combinations being available, it has rarely been used for bioanalytical devices. One approach is to deposit a thin layer of COC with a lower glass transition temperature on a thick layer of COC with a higher glass transition temperature by dissolving it in toluene and spin-coating it on the thicker substrate. The solvent-bonded parts were subsequently thermal diffusion bonded to each other.50 The optical transparency of many polymer materials has been used for a number of selective bonding techniques. A common bonding technique is through-transmission laser welding used to bond two polymer parts with different optical transmission characteristics. A laser transmits energy through the transparent layer. The laser energy is absorbed by the subjacent opaque polymer, causing the material to heat past its melting temperature. As a result, the two substrates will locally join. Scanning a focused laser beam around microsized features enables selective sealing and bonding. In reverse conductive welding, the energy-absorbing layer is not part of the device, but forms a workbench that heats up during energy absorption. From there, the thermal energy is conducted back to the interface between the polymer layers. This process creates a large heat-affected zone, which leads to distortion of microsized features in the vicinity of the bond. Another way to weld polymer layers together is based on an energy-absorbing dye. The dye is deposited onto at least one of the surfaces to be bonded and subsequently heated by a laser source with a wavelength corresponding to the absorption wavelength of the dye.51 In ultrasonic welding, high frequency mechanical energy is applied via an acoustic horn to
POLYMER-BASED MICROSYSTEM TECHNIQUES
13
Cost
Process time and throughput
Technical flexibility
Biocompatibility
Transparency
Compatibility with metallization
Channel clogging / distortion
Structural complexity
Geometrical resolution
Technical maturity
Table 6. Process performance of selected polymer bonding techniques
Adhesive bonding (bulk) Adhesive bonding (screen-printed adhesive) Adhesive tape bonding (bulk) Adhesive tape bonding (prestructured tape) Lamination Thermal diffusion bonding Thermal diffusion bonding (UV-assisted) Thermal diffusion bonding (O2 plasma-assisted) Thermal diffusion bonding (chemical etch–assisted) Solvent bonding Laser welding (transmission) Laser welding (reverse conductive) Laser welding (absorbent dye) Ultrasonic welding Microwave welding (microwave absorber) Most favorable process
least favorable process.
the polymer assembly creating frictional heat between molecules and causing the polymer to melt and join.52 Another bonding technique utilizes microwave technology to join polymer layers in microfluidic devices. Most polymers are transparent to microwave radiation. If a microwave absorber such as a conductive polymer or a metal film is added to the joint interface between two polymer layers, it will selectively absorb the microwave energy. This interaction results in a local heat generation at the interface, leading to bulk polymer flow across the joint and formation of a weld.12,53 Table 6 qualitatively assesses the process performance of selected polymer bonding techniques. The analysis shows that again, owing to the strengths and weaknesses of each of the discussed bonding techniques, a single preferred bonding technique cannot be identified. The selection of a suitable bonding technique depends heavily on the complexity of the design, the utilized materials, and the fabrication technology most suitable for the respective production volumes. A
more detailed discussion of polymer bonding techniques is available in the literature.54–56
7 SUMMARY
Polymer microfabrication offers a wide variety of techniques for fabricating microdevices. Some of the techniques are relatively new and are borrowed from other microfabrication processes while the vast majority are adaptations of techniques already established in the macromanufacturing environment. We can expect to see even more innovations arising from the combination of other traditional manufacturing processes, for example printing processes, that when combined with polymer fabrication will produce increasingly integrated microsystems. The development of new polymer materials will further accelerate this development. The low material cost and great structural resolution possible with polymers makes for a highly cost-effective approach to designing and fabricating complex devices. As with all
14
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
product development, careful attention must be paid to the way the manufacturing process is scaled in volume. However, low cost, great design flexibility, and the ability to cost-effectively achieve high production volumes mean that we are seeing an increasing introduction of innovative and commercially successful disposable biosensor systems into the market.
REFERENCES 1. D. R. Reyes, D. Iossifidis, P.-A. Auroux, and A. Manz, Micro total analysis systems. 1. Introduction, theory, and technology. Analytical Chemistry, 2002, 74, 2623–2636. 2. P.-A. Auroux, D. Iossifidis, D. R. Reyes, and A. Manz, Micro total analysis systems. 2. Analytical standard operations and applications. Analytical Chemistry, 2002, 74, 2637–2652. 3. L. J. Kricka, Miniaturization of analytical systems. Clinical Chemistry, 1998, 44, 2008–2014. 4. M. A. Northrup, M. T. Ching, R. M. White, and R. T. Watson, DNA Amplification in a Microfabricated Reaction Chamber, In: Digest of Technical Papers: Transducers ‘93 , Yokohama, 1993, pp. 924–926. 5. M. A. Northrup, B. Bennett, D. Hadley, P. Landre, S. Lehew, J. Richards, and P. Stratton, A miniature analytical instrument for nucleic acid based on micromachined silicon reaction chambers. Analytical Chemistry, 1998, 70, 918–922. 6. E. T. Lagally, P. C. Simpson, and R. A. Mathies, Monolithic integrated microfluidic DNA amplification and capillary electrophoresis analysis system. Sensors and Actuators. B, 2000, 63, 138–146. 7. E. T. Lagally, C. A. Emrich, and R. A. Mathies, Fully integrated PCR-capillary electrophoresis microsystem for DNA analysis. Lab on a Chip, 2001, 1, 102–107. 8. H. Becker and U. Heim, Hot embossing as a method for the fabrication of polymer high aspect ratio structures. Sensors and Actuators. A, 2000, 83, 130–135. 9. W. Schomburg, Review of micro moulding of thermoplastic polymers. Journal of Micromechanics and Microengineering, 2004, 14, R1–R14. 10. M. L. Hupert, M. A. Witek, Y. Wang, M. W. Mitchell, Y. Liu, Y. Bejat, D. E. Nikitopoulos, J. Goettert, M. C. Murphy, and S. A. Soper, Polymer-Based Microfluidic Devices for Biomedical Applications, in Microfluidics, BioMEMS, and Medical Microsystems, H. Becker and P. Woias (eds), SPIE, Bellingham, 2003, SPIE Vol. 4982, pp. 52–64. 11. M. Chanda and S. K. Roy, Plastics Technology Handbook, 4th Edn, CRC Press, Boca Raton, 2007. 12. M. Schuenemann, D. Thomson, M. Atkin, S. Garst, A. Yussuf, M. Solomon, J. Hayes, and E. Harvey, Packaging of Disposable Chips for Bioanalytical Applications, in Proceedings of the IEEE 54th Electrical Components and Technology Conference, P. Thompson (ed), IEEE Press, Piscataway, 2004, pp. 853–861.
13. M. A. Burns, B. N. Johnson, S. N. Brahmasandra, K. Handique, J. R. Webster, K. Madhavi, T. S. Sammarco, P. M. Man, D. Jones, D. Heldsinger, C. H. Mastrangelo, and D. T. Burke, An integrated nanoliter DNA analysis device. Science, 1998, 282, 484–487. 14. K. R. Hawkins and P. Yager, Nonlinear decrease of background fluorescence in polymer thin-films—a survey of materials and how they can complicate fluorescence detection in µTAS. Lab on a Chip, 2003, 3, 248–252. 15. J. Yang, Y. Liu, C. B. Rauch, R. L. Stevens, R. H. Liu, R. Lenigk, and P. Grodzinski, High sensitive PCR assay in plastic micro reactors. Lab on a Chip, 2002, 2, 179–187. 16. X. Yu, D. Zhang, T. Li, L. Hao, and X. Li, 3D microarrays biochip for DNA amplification in polydimethylsiloxane (PDMS) elastomer. Sensors and Actuators. A, 2003, 108, 103–107. 17. J. S. Rossier, M. A. Roberts, R. Ferrigno, and H. H. Girault, Electrochemical detection in polymer microchannels. Analytical Chemistry, 1999, 71, 4294–4299. 18. S. Qi, X. Liu, S. Ford, J. Barrows, G. Thomas, K. Kelly, A. McCandless, K. Lian, J. Goettert, and S. A. Soper, Microfluidic devices fabricated in poly (methyl methacrylate) using hot-embossing with integrated sampling capillary and fiber optics for fluorescence detection. Lab on a Chip, 2002, 2, 88–95. 19. J. Steigert, S. Haeberle, T. Brenner, C. M¨uller, C. P. Steinert, P. Koltay, N. Gottschlich, H. Reinecke, J. R¨uhe, R. Zengerle, and J. Ducr´ee, Rapid prototyping of microfluidic chips in COC. Journal of Micromechanics and Microengineering, 2007, 17, 333–341. 20. S. Metz, R. Holzer, and P. Renaud, Polyimide-based microfluidic devices. Lab on a Chip, 2001, 1, 29–34. 21. M. Atkin, J. P. Hayes, N. Brack, K. Poetter, R. Cattrall, and E. Harvey, Disposable Microchip Fabrication for DNA Diagnostics, in Biomedical Applications of Micro- and Nanoengineering, D. V. Nicolau (ed), SPIE, Bellingham, 2002, SPIE Vol. 4937, pp. 125–135. 22. J. Rossier, F. Reymond, and P. E. Michel, Polymer microfluidic chips for electrochemical and biochemical analyses. Electrophoresis, 2002, 23, 858–867. 23. C. S. Effenhauser, G. J. M. Bruin, A. Paulus, and M. Ehrat, Integrated capillary electrophoresis on flexible silicone microdevices: analysis of DNA restriction fragments and detection of single DNA molecules on microchips. Analytical Chemistry, 1997, 69, 3451–3457. 24. C. H. Ahn, J. W. Choi, G. Beaucage, J. H. Nevin, J. B. Lee, A. Puntambekar, and J. Y. Lee, Disposable smart lab on a chip for point-of-care clinical diagnostics. Proceedings of the IEEE, 2004, 92, 154–173. 25. M. A. Roberts, J. S. Rossier, P. Bercier, and H. Girault, UV laser machined polymer substrates for the development of microdiagnostic systems. Analytical Chemistry, 1997, 69, 2035–2042. 26. C. Khan Malek, Laser processing for bio-microfluidics applications (Part 1). Analytical and Bioanalytical Chemistry, 2006, 385, 1351–1361. 27. E. C. Harvey, P. T. Rumsby, M. C. Gower, and J. L. Remnant, Microstructuring by Excimer Laser, in Micromachining and Microfabrication Technology, K. W. Markus (ed), SPIE, Bellingham, 1995, SPIE Vol. 2639, pp. 266–277.
POLYMER-BASED MICROSYSTEM TECHNIQUES 28. M. Heckele and W. K. Schomburg, Review on micro moulding of thermoplastic polymers. Journal of Micromechanics and Microengineering, 2004, 14, R1–R14. 29. J. Elders, H. V. Jansen, M. Elwenspoek, and W. Ehrfeld, DEEMO: A New Technology for the Fabrication of Microstructures, in Proceedings of the IEEE Micro Electro Mechanical Systems, IEEE Press, Piscataway, 1995, pp. 238–243. 30. J. Narashimhan and I. Papautsky, Polymer embossing tools for rapid prototyping of plastic microfluidic devices. Journal of Micromechanics and Microengineering, 2004, 14, 96–103. 31. C. Khan Malek and R. Duffait, Packaging using hotembossing with a polymeric intermediate mould. International Journal of Advanced Manufacturing Technology, 2006. DOI 10.1007/s00170-006-0595-2. 32. S. L. McArthur and K. M. McLean, Surface Modification, in Encyclopedia of Biomaterials and Biomedical Engineering, G. E. Wnek and G. L. Bowlin (eds), Marcel Dekker, New York, 2004. 33. C. M. Chan, T. M. Ko, and H. Hiraoka, Polymer surface modification by plasmas and photons. Surface Science Reports, 1996, 24, 3–54. 34. P. K. Chu, J. Y. Chen, L. P. Wang, and N. Huang, Plasmasurface modification of biomaterials. Materials Science and Engineering R, 2002, 36, 143–206. 35. D. C. Duffy, J. C. McDonald, O. J. A. Schueller, and G. M. Whitesides, Rapid prototyping of microfluidic systems in poly(dimethylsiloxane). Analytical Chemistry, 1998, 70, 4974–4984. 36. M. J. Shenton and G. G. Stevens, Surface modification of polymer surfaces: atmospheric plasma versus vacuum plasma treatments. Journal of Physics D: Applied Physics, 2001, 34, 2761–2768. 37. W. S. Gutowski, S. Li, C. Filippou, P. Hoobin, and S. Petinakis, Interface-interphase engineering of polymers for adhesion enhancement: Part II. Theoretical and technological aspects of surface-engineered interphaseinterface systems for adhesion enhancement. Journal of Adhesion, 2003, 79, 483–519. 38. R. Truckenm¨uller, P. Henzi, D. Herrmann, V. Saile, and W. K. Schomburg, Bonding of polymer microstructures by UV irradiation and subsequent welding at low temperatures. Microsystem Technologies, 2003, 10, 372–374. 39. E. Kiss, J. Samu, A. Toth, and I. Bertoti, Novel ways of covalent attachment of poly(ethylene oxide) onto polyethylene: surface modification and characterization by XPS and contact angle measurements. Langmuir, 1996, 12, 1651–1657. 40. M. Zhang, T. Desai, and M. Ferrari, Proteins and cells on PEG immobilized silicon surface. Biomaterials, 1998, 19, 953–960. 41. B. C. Giordano, E. R. Copeland, and J. P. Landers, Towards dynamic coating of glass microchip chambers for amplifying DNA via the polymerase chain reaction. Electrophoresis, 2001, 22, 334–340. 42. P. Kingshott and H. J. Griesser, Surfaces that resist bioadhesion. Current Opinion in Solid State and Material Science, 1999, 4, 403–412. 43. M. Hanika, H.-C. Langowski, U. Moosheimer, and W. Peukert, Inorganic layers on polymeric films—
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
15
influence of defects and morphology on barrier properties. Chemical Engineering and Technology, 2003, 26, 605–614. Y. S. Shin, K. Cho, S. H. Lim, S. Chung, S. Park, C. Chung, D. Han, and J. K. Chang, PDMSbased micro PCR chip with Parylene coating. Journal of Micromechanics and Microengineering, 2003, 13, 768–774. J. Han, S. Lee, A. Puntambekar, S. Murugesan, J.-W. Choi, G. Beaucage, and C. H. Ahn, UV Adhesive Bonding Techniques in Room Temperature for Plastic Lab-on-aChips, in Proceedings of Micro Total Analysis Systems 2003, M. A. Northrup, K. F. Jensen, and D. J. Harrison (eds), Transducers Research Foundation, San Diego, 2003, pp. 1113–1116. M. A. Roberts, J. S. Rossier, P. Bercier, and H. H. Girault, UV laser machined polymer substrates for the development of microdiagnostic systems. Analytical Chemical, 1997, 69, 2035–2042. J. S. Rossier, G. Gokulrangan, S. Svojanovsky, G. S. Wilson, and H. H. Girault, Characterization of protein adsorption and immunosorption kinetics in photoablated polymer microchannels. Langmuir, 2000, 16, 8489–8494. J. Yang, Y. Liu, C. B. Rauch, R. L. Stevens, R. H. Liu, R. Lenigk, and P. Grodzinski, High sensitivity PCR assay in plastic micro reactors. Lab on a Chip, 2002, 2, 179–187. X. Zhu, G. Liu, Y. Guo, and Y. Tian, Study of PMMA thermal bonding. Microsystem Technologies, 2007, 13, 403–407. F. Bundgaard, T. Nielsen, D. Nilsson, P. Shi, and G. Perozziello, Cyclic Olefin Copolymer (COC/Topas )— an Exceptional Material for Exceptional Lab-on-a-chip Systems, in Proceedings of Micro Total Analysis Systems 2004, T. Laurell, J. Nilsson, K. Jensen, D. J. Harrison, and J. P. Kutter (eds), Royal Society of Chemistry, Cambridge, 2004, Vol. 2, pp. 372–377. L. Dosser, K. Hix, K. Hartke, R. Vaia, and M. Li, Transmission Welding of Carbon Nanocomposites with Direct-diode and Nd:YAG Solid State Lasers, in Photon Processing in Microelectronics and Photonics III, P. R. Herman, J. Fieret, A. Pique, T. Okada, F. G. Bachmann, W. Hoving, K. Washio, X. Xu, J. J. Dubowski, D. B. Geohegan, and F. Traege (eds), SPIE, Bellingham, 2004, SPIE Vol. 5339, pp. 465–474. R. Truckenm¨uller, Y. Cheng, R. Ahrens, H. Bahrs, G. Fischer, and J. Lehmann, Micro ultrasonic welding: joining of chemically inert polymer microparts for single material fluidic components and systems. Microsystem Technologies, 2007, 12, 1027–1029. A. A. Yussuf, I. Sbarski, J. P. Hayes, M. Solomon, and N. Tran, Microwave welding of polymeric microfluidic devices. Journal of Micromechanics and Microengineering, 2005, 15, 1692–1699. C. A. Harper, Plastics Joining, in Handbook of Plastics, Elastomers, and Composites, 4th Edn, C. A. Harper (ed), McGraw-Hill, New York, 2002, pp. 507–560. T. Velten, H. H. Ruf, D. Barrow, N. Aspragathos, P. Lazarou, E. Jung, C. Khan Malek, M. Richter,
16
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
J. Kruckow, and M. W¨ackerle, Packaging of BioMEMS: strategies, technologies and applications. IEEE Transactions on Advanced Packaging, 2005, 28, 533–546. 56. S. Garst, M. Schuenemann, M. Solomon, M. Atkin, and E. Harvey, Fabrication of Multilayered Microfluidic Packages, in Proceedings of the IEEE 55th Electrical Components and Technology Conference, P. Thompson (ed), IEEE Press, Piscataway, 2005, pp. 853–861.
FURTHER READING H. Becker and C. Gartner, Polymer microfabrication methods for microfluidic analytical applications. Electrophoresis, 2000, 21, 12–26. D. Thomson, J. P. Hayes, and H. Thissen, Protein Patterning in Polycarbonate Microfluidic Channels, in BioMEMS and Nanotechnology, D. V. Nicolau (ed), SPIE, Bellingham, 2004, SPIE Vol. 5275, pp. 161–167.
44 Microelectrochemical Systems Stuart A. G. Evans and Lindy J. Murphy Oxford Biosensors Ltd., Yarnton, UK
1 INTRODUCTION
The use of microelectrodes in the field of biosensors has led to increasingly lower detection limits and sample volumes, due to their small dimensions and high sensitivity of measurement. Detection limits as low as femtomolar concentrations of DNA or zeptomolar concentrations of analytes, and sample volumes as low as picoliters have been reported. In addition, advances in microfabrication techniques have resulted in increasing numbers of lab-on-a-chip-type devices with inbuilt electrochemical detection being reported, some of which are commercially available. Microelectrodes have also been fundamental to the development of the technique of scanning electrochemical microscopy (SECM), which allows investigation of redox processes at electrode surfaces with high resolution. This article describes the electrochemical response and methods of fabrication of microelectrodes, and outlines some of the recent applications of microelectrodes in the field of bioelectrochemistry.
2 MICROELECTRODES: DEFINITION AND PROPERTIES
Microelectrodes, as their name suggests, differ from conventional electrodes (macroelectrodes) with respect to their size. Macroelectrodes typically have dimensions in the meters to millimeters scale, depending on their application,
whereas microelectrodes (which are also known as ultramicroelectrodes or UME s) are regarded as having at least one dimension in the micrometer range. The question of how small an electrode must be in order to be defined as a microelectrode has been discussed in great detail, but with no clear resolution. Part of the reason being that the term microelectrode was initially used in the 1940s for electrodes with dimensions in the millimeter range, but in the late 1970s it was used for smaller electrodes with dimensions in the micrometer range. It is generally accepted that for an electrode to be considered a microelectrode it must have at least one dimension, the critical dimension, smaller than the diffusion layer thickness, under the experimental conditions employed.1 For the purpose of this review, a microelectrode is defined as an electrode having at least one dimension smaller than 25 µm but greater than 10 nm. It will therefore not include the so-called nanodes,2 with critical dimensions that reside in the nanometer range. For clarity, the critical dimension can be the thickness of the electrode for microring, microband, or tubular microband electrodes, or the radius of the electrode for microdisc, hemisphere, or spherical microelectrodes. When one electrode dimension is below the critical size, the electrode response has been shown to deviate from the standard theory for macroelectrodes and to exhibit some unique properties. Under appropriate experimental conditions, for example during slow scan voltammetry, the voltammetric response of microelectrodes is very
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
different to that observed at electrodes of conventional size because the diffusion layer thickness can greatly exceed the dimensions of the microelectrode (see Figure 1).3 When this occurs, the microelectrode attains a time-independent steadystate response, characterized by a sigmoidalshaped voltammogram. This is similar to the polarograms obtained with a dropping mercury electrode or the current-voltage curves obtained with a rotating disc electrode, but in this case it is due to high diffusion rates under quiescent conditions. To explain this phenomenon fully, a simple model will be described where a microelectrode is immersed in a solution of an oxidizable redox species, with the microelectrode poised at a potential sufficient to oxidize the redox species at a diffusion-controlled rate. Initially, after application of the potential, the electrode perturbs the solution and causes the formation of a diffusion layer that moves out from the electrode into solution. At short times, the diffusion layer thickness, δ, is very thin and so the electrode is much larger than the diffusion layer thickness. Consequently, the nonuniform current distribution resulting from high mass transport of redox species to the edge of the microelectrode (the edge effect) has little contribution to the measured current and the electrode response is described by that of an infinitely large planar electrode (see Figure 2a and b). As time progresses, the diffusion layer thickness increases and eventually exceeds the dimensions of the microelectrode. Under these conditions, the edge effect becomes dominant and results in the 20
i (mA)
10
(a)
(b)
(c)
Figure 2. Illustration depicting the diffusion fields to (a) a macroelectrode (planar diffusion), (b) a microelectrode at short time after application of a potential step (planar diffusion), and (c) a microelectrode at long times after a potential step (radial diffusion).
formation of a spherical diffusion field and the attainment of a steady-state response with high current density (Figure 2c). Conversely, for short timescale experiments, for example with cyclic voltammetry recorded at high scan rate, the diffusion layer thickness is smaller than the size of the microelectrode, semi-infinite planar diffusion is dominant and the voltammetry reverts to the peak-shaped behavior seen at electrodes of conventional size. Figure 3 compares cyclic voltammograms recorded using a 14-µm thick carbon microband electrode in a 10-mM Ru(NH3 )6 Cl3 solution recorded with fast and slow scan rates. The slow scan rate voltammogram displays the characteristic sigmoidal shape consistent with radial diffusion to a microelectrode, while the fast scan voltammetry (FSV) has peaks consistent with planar diffusion.
0 −0.5
−0.25
0
0.25
−10 −20 −30 E vs Ag/AgCl (V) Figure 1. Cyclic voltammograms for a 14-µm-thick screen printed carbon microband electrode in 10 mM Ru(NH3 )6 Cl3 , recorded with scan rates of 10 mV s−1 (black line) and 100 mV s−1 (gray line).
3 ADVANTAGES OF MICROELECTRODES
Microelectrodes, because of their small size, have several advantages compared with macroelectrodes and, as a result they have been the focus of several comprehensive review articles.4–6 As the electrolysis currents recorded during microelectrode experiments are typically small, the impact of ohmic phenomena (iR drop) is greatly reduced making microelectrodes amenable to undertaking electrochemistry in a wide variety
MICROELECTROCHEMICAL SYSTEMS
3
4 TYPES OF MICROELECTRODES AND THEIR FABRICATION
(a)
(b)
(d)
(e)
(g)
(h)
(c)
(f)
(i)
Figure 3. Showing the most commonly used geometries of microelectrodes and microelectrode arrays; (a) microdisc, (b) microring, (c) microband, (d) microcylinder, (e) microsphere, (f) microhemisphere, (g) interdigitated array, (h) microdisc array, (i) random array of microdiscs.
of chemical media including nonaqueous solvents, gas, ice, polymer films, and in low-conductivity aqueous solutions with little or no supporting electrolyte.7 The minimal distortion from iR drop also enables the use of microelectrodes for fast scan rate voltammetry with scan rates of over 1 × 106 V s−1 .8 In addition to this, the response time is reduced since the capacitive (nonfaradaic) response of an electrode decreases with electrode radius, so more information can be gained in the early part of chronoamperometric transient responses and in fast scan rate voltammetry for the investigation of high-speed electron transfer reactions that were previously inaccessible with macroelectrodes. The small physical size also makes them ideally suitable for experimental conditions where either space or sample volume is at a premium, for example during single cell studies in nanoliter volumes.9 Finally, the steady-state response obtained with microelectrodes makes them ideally suitable for electroanalytical applications, since the limiting current is directly proportional to the analyte concentration giving an excellent signalto-noise ratio and as low as zeptomole detection limits.10
Microelectrodes fall into one of two main categories; single or array microelectrodes. Figure 3 shows the most common geometries of microelectrode, which have been fabricated and utilized in the literature. Of these, the most commonly used microelectrode geometry, accounting for approximately 50% of all microelectrode studies,11 is the microdisc electrode (also known as inlaid microdisc). Of the other common geometries, the microcylinder accounts for 20%, microarray electrodes (both random and uniform) account for a further 20%, while the remaining 10% is split mainly between the microband and microring, with a small percentage attributable to the microsphere and microhemisphere electrodes. Fabrication of the single microelectrodes is typically undertaken by sealing a microwire, thin foil, or fine fiber into an insulating material such as glass or epoxy resin. The reviews by Zoski and Murray and coworkers provide highly detailed and comprehensive discussion of the topic including the design, fabrication, and characterization of microelectrodes.12,13 Briefly, microdisc electrodes are fabricated by either heat sealing a microwire into a glass capillary (under vacuum) and then polishing the end of the capillary to yield a microdisc electrode or by inserting the microwire into the capillary and then pulling the metal/glass assembly using a pipette puller. To prepare microcylinder electrodes, the microwire is again inserted into the glass capillary, but in this case a small length of microwire (<1 mm) is left to protrude from the end of the glass thereby forming a microcylinder of exposed wire. Microband electrodes are most commonly fabricated by sandwiching metal foils (or thin metal films) between glass or epoxy insulating layers. Spherical and hemispherical microelectrodes are typically fabricated by electrodeposition of mercury films onto platinum microdisc supports, the radius of the sphere or hemisphere being determined by the amount of mercury deposited. Finally, in order to fabricate microring microelectrodes (also known as inlaid ring microelectrodes), the interior or exterior walls of a pulled glass capillary (or rod) is coated, either by painting with an organometallic compound or by vapor deposition of a thin film of conducting material, for example Au, Pt,
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
or C. The coated capillary (or rod) is then sealed into a larger glass tube with epoxy resin. Polishing the end of the capillary exposes the microring electrode. Arrays of microelectrodes fall into one of two groups; regular arrays, where identically sized electrodes are positioned periodically with uniform separation or random arrays, where either the electrodes are of uniform size but spaced randomly or alternatively where both the size and spacing of the electrodes are random. Regular arrays with well controlled electrode size and distribution are generally constructed using standard photolithographic techniques,14 whereas random arrays are generally prepared by sealing small conducting particles (e.g., graphite powder) or a large number of microwires (or fibers) into a nonconducting support. Polishing the surface exposes the random array of disc electrodes.
5 CHARACTERIZATION OF MICROELECTRODES
A number of methods have been devised to characterize the size, shape, and quality of microelectrodes after fabrication. The electrodes are typically inspected using scanning electron microscopy (SEM) to determine the quality of the seal between the conducting and insulating materials and to approximate the dimensions of the microelectrode. In order to characterize the electrochemical response of the microelectrodes, steady-state voltammetry is undertaken in an aqueous solution containing a well-characterized reversible redox couple possessing a fast heterogeneous electron transfer rate, for example, 1 mM Ru(NH3 )6 Cl3 .15 The voltammogram obtained with a slow scan rate (typically <10 mV s−1 ) should be sigmoidal in shape with the reverse scan retracing the forward sweep. A separation between the forward and reverse scans indicates that either the scan rate is too fast, or that the seal between the conducting and insulating materials is poor. The magnitude of the diffusion limiting current will depend on the geometry and size of the microelectrode used and the diffusion coefficient of the redox species.
6 EXPERIMENTAL SETUP FOR SCANNING ELECTROCHEMICAL MICROSCOPY (SECM)
SECM is a scanning probe microscopy (SPM) technique where a microelectrode probe (typically a microdisc electrode) is scanned in close proximity to a sample (the substrate) immersed in an electrolyte solution. The technique differs from other SPM techniques because it relies on the electrochemical response of the microelectrode probe. SECM can therefore be used to perform almost any type of electrochemical experiment with the electrochemical probe above a micrometer size area of the sample. AC voltammetry, amperometry, potentiometry, and microfabrication can be undertaken using SECM. The technique was originally devised by Engstrom (in 1986) to probe the diffusion layer of a large electrode,16 although it was not until later that year that Bard and coworkers named the technique scanning electrochemical microscopy (SECM ).17 Since then, over 700 research articles, several comprehensive reviews, and one book have been written about the technique.18,19
6.1
The Feedback Mode of SECM Operation
The most popular operation of SECM is in the amperometric mode where the microelectrode tip acts as an active probe for oxidizing or reducing redox active species in solution. The interaction of the microelectrode diffusion layer and the sample surface forms the basis of the so-called feedback mode. When a microdisc electrode is immersed in a solution containing an oxidizable species (R) and poised at a potential sufficient to oxidize the redox species at a diffusion-controlled rate, a quasihemispherical diffusion layer builds up around the tip of the microelectrode. After a short time (of the order of tens of a 2 /D, where a is the radius of the microdisc and D is the diffusion coefficient of the species of interest), the size of this diffusion layer becomes constant (at approximately 7 × a) and the steady-state current, iT ∞ , is obtained as depicted by Figure 4(a). In this situation, the current attained at the tip is proportional to the concentration of R, CR , and
MICROELECTROCHEMICAL SYSTEMS
iT/ iT⬁
R O
A
R O
R O
Insulating
Conducting
B
C
C A
B
⬁
0
d /a Figure 4. Basic principles of the feedback mode of SECM and the corresponding approach curves for each limiting case where (A) shows the response of the microelectrode in the bulk solution, where diffusion leads to a steady-state current, iT ∞ ; (B) when the microelectrode is moved nearer to an insulating substrate, hindered diffusion leads to iT < iT ∞ ; (C) when the microelectrode is moved closer to a conductive substrate, positive feedback leads to iT > iT ∞ .
diffusion coefficient, DR , of the oxidizable species in the solution. The faradaic current recorded at the microelectrode can therefore be given by equation (1): iT ∞ = 4nFD R CR∞ a
(1)
where n is the number of electrons transferred in the reaction and F the Faraday constant. This current, iT ∞ , assumes that the microelectrode is located in the bulk far away from the substrate and that the rate of mass transport is diffusion controlled. If the tip of the microdisc electrode is then moved closer to the substrate surface, so that the diffusion layer of the microelectrode interacts with the substrate surface, the tip current becomes dependent on the conductivity or reactivity of the substrate. The resulting response forms the basis of the most commonly used mode of SECM operation—the feedback mode. For example, when the tip approaches an insulating substrate, the steady-state current (iT ) flowing through the microelectrode becomes less than iT ∞ . The decrease in current is attributable to the insulating surface blocking the diffusion of R to the tip and causing the tip to see a decreased concentration of the reduced species; an effect
5
called negative feedback or hindered diffusion (Figure 4B). A typical hindered diffusion approach curve is depicted in Figure 4(B) and shows that as the tip/substrate distance decreases, iT ∞ tends to zero. If the tip is approached toward a very reactive substrate, the steady-state current (iT ) flowing through the tip becomes greater than iT ∞ . The increased current is attributable to the substrate converting the oxidized species back into R, which then diffuses back to the tip. The flux of R from the substrate, combined with the flux of R from the solution around the tip causes the tip to see an increased concentration of reduced species and results in iT being greater than iT ∞ , an effect called positive feedback (Figure 4C). A typical positive feedback approach curve is shown in Figure 4(C). The actual feedback current can be more complicated than the two limiting cases described in the preceding text. For example, if electron transfer reaction from O → R at the substrate surface is kinetically controlled rather than diffusion controlled, then the tip current not only reflects the tip substrate distance but also the rate of regeneration of R at the substrate surface. This can therefore be used to determine the heterogeneous kinetics of reaction at the substrate. When operated in the amperometric mode, the SECM can be used to study homogenous electrochemical reactions, electrochemical processes within films, as a tool for microfabrication (etching and deposition of metals, polymers, or biological systems), and to image maps of surface reactivity in both biological (single cell, enzyme, and antibody) and chemical systems. The versatility of SECM also makes it amenable to the study of a range of different samples including the liquid/liquid, gas/liquid and liquid/ice interfaces.
7 APPLICATIONS OF MICROELECTRODES TO BIOELECTROCHEMISTRY
One of the main applications of microelectrodes for biosensing arises from the small electrode size, permitting electrochemical detection in very small volumes such as single cells or in microanalytical devices. The small size also allows high spatial resolution of the response, which is directly of use in SECM and in vivo monitoring. Another feature of microelectrodes, the high sensitivity of measurement, allows detection of very low
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
currents and hence very low detection limits. These applications are discussed in more detail in the subsequent text.
7.1
Low Detection Limit
The low detection limit of microelectrodes is one intrinsic feature of their response characteristics. Detection at the picomolar and femtomolar range in µl size droplets is possible. One example of this is the highly sensitive detection of 3000 copies of DNA in a 10-µl droplet at 0.5 fM concentration, using a 10-µm-diameter glassy carbon electrode.20 The microelectrode was coated with redox polymer onto which was immobilized a DNA capture sequence, which after hybridization with the target DNA was exposed to a detection sequence labeled with horse radish peroxidase. Although this is a multistage measurement, the technique could lend itself to a miniaturized device. This methodology can also be extended to the detection of immunoreactions with high sensitivity and low detection limits. Also of interest is the electrochemical monitoring of a single cell with a 3-µm radius carbon fiber electrode in a vial of 100–200 picoliters.21 A layer of mineral oil was used to reduce evaporation and permitted measurements for several minutes. Although the small volume allowed complete electrochemical exhaustion of the redox species within 60 s, FSV allowed continuous measurement without depletion.
7.2
In Vivo Sensing
Microelectrodes have been used in individual cells, in tissue samples, and in vivo to directly measure a variety of target analytes, including pH change, O2 , CO2 , superoxides, NO, and chemical messengers such as catecholamines (dopamine, epinephrine and norepinephrine), serotonin and histamine. Peptides with a tryptophan or tyrosine reside are also electroactive and can be monitored. Microbiosensors modified with enzymes such as glucose oxidase have also been used. Monitoring the analytes themselves can be of interest, or they may be measured to determine the effect of an external stimulant such as application of a
therapeutic or recreational drug or a physiological event such as a tail pinch.22 In vivo sensing of glucose for the monitoring and control of glucose levels in diabetic patients is an active area of research, because of the potential benefits of improved control of glucose levels and the possible incorporation in a feedback system with an artificial pancreas. However, this method typically uses sensors with dimensions of tens of micrometers in conjunction with immobilized enzyme and an outer protective layer, so that the potential advantages of microelectrodes of fast response time and high spatial resolution of the response are not fully exploited. In vivo glucose sensing has recently been covered in an excellent review by Wilson.23 The investigation of neurochemical processes is the most active area of in vivo microelectrode research. Neurochemistry has been investigated using enzyme modified microelectrodes to detect analytes, in particular ATP.24 An ATPsensing microelectrode developed by Dale’s group is now commercially available from world precision instruments (WPI). Use of microelectrodes for the real-time direct detection of neurochemicals has been reviewed by Wightman.25 Also of interest is the detection of exocytosis events at the single cell and single vesicle level which has been made possible by microelectrodes. This has been applied to the monitoring of the neurotoxic effects of environmental pollutants and drugs of abuse on vesicular catecholamine release.26 Wightman has pioneered the use of FSV to increase the temporal resolution of in vivo microelectrode responses, in addition to the high spatial resolution of the microelectrode signal. In vivo sensors for direct electrochemical detection often have a protective polymer coat to reduce the amount of interferent species reaching the electrode. However in FSV, higher temporal resolution is obtained for uncoated electrodes due to faster diffusion of electroactive species to the electrode surface.27 In vivo measurement of NO with microelectrodes also merits discussion. The biological role of NO as a physiological messenger molecule was first discovered in the 1980s, and subsequently several methods of preparation of microelectrochemical sensors with modified surfaces for in vivo determination of NO have been reported. Electrochemistry with microelectrodes is the only
MICROELECTROCHEMICAL SYSTEMS
technique currently available for the quantitative detection of in vivo NO levels, which are in the nanomolar concentration range. NO sensors must be able to measure the low levels of NO in a background of other electroactive species such as ascorbate, and the small size and hydrophobic nature of NO naturally lends itself to direct electrochemical detection at microelectrodes modified by use of size exclusion and/or hydrophobic coatings. Alternatively, NO can be detected catalytically at chemically modified sensors. The preparation and use of in vivo NO sensors has been reviewed by Bedioui.28
8 MICROFABRICATED DEVICES
The technique of electrochemistry can be readily applied to miniaturized devices, since fabrication of microelectrodes and cheap and small-scale integrated instrumentation for detection of electrochemical responses is relatively facile. This compares favorably with other detection techniques such as optical or mass spectrometry. Although these techniques can use miniaturized chips to perform measurements with very low detection limits, sometimes at the single molecule level, the instrumentation required to perform the techniques themselves are not easily miniaturized. The use of microelectrodes in microelectromechanical systems (MEMS) (also known as miniaturized total analytical systems (µTAS)) extends beyond electrochemical detection to methods of manipulating cellular material. The techniques of electroporation and dielectrophoresis have been extended to the individual cellular level by the use of microelectrodes, and can be used as part of a µTAS. In electroporation, a strong electric field (hundreds to thousands of volts) is applied between two electrodes, in between which is placed a population of cells. The electric field causes part of the cell membrane to break down so that exogenous chemicals such as fluorescent markers can be incorporated into the cells and the functioning of the cell compartment investigated. To investigate a single cell without a microelectrode, either a single cell needs to be isolated and placed between the macro electrodes, or focusing of the electric field is required. Microelectrodes have enabled individual cells or even parts of the cell membrane to be electroporated.29
7
Dielectrophoresis is the motion of particles caused by dielectric polarization in a nonuniform electric field. The degree of motion is determined by the magnitude and polarity of the charges induced in a particle in an electric field, where the particle can be a cell, microorganism or other bioparticle. The induced charges impart an electric dipole to the particle, equivalent to approximately 0.1% of the net surface charge usually carried by the particle. Dielectrophoresis can be used to manipulate cells and particles in microfluidic devices, and use of microelectrodes to apply the electric field can allow individual cells or particles to be manipulated.30 Microelectrodes have also been used to monitor extracellular species in the region of a single cell, using very low volume “petri dishes”. By sampling the microelectrode response at shorter times, high temporal resolution of cellular processes can be achieved.31 Microelectrode arrays (MEAs) have also been used to interrogate tissue slices and the intra and extracellular biochemistry of cells. MEAs are commercially available from Multichannel Systems (Reutligen, Germany) and Panasonic (Tokyo). The use of MEAs to interrogate neuronal cell activity and the effect of drugs and toxins on tissue slices has recently been reviewed.32 MEAs can be used extensively for pharmaceutical applications, allowing screening of prospective therapeutic agents and monitoring of potentially adverse tissue reactions, for example, the potential effect of novel drugs on cardiac function. DiagnoSwiss have developed disposable microtiter plates for electrochemical immunoassays, using a plasma etching process to make microchannels in which conventional immunoassay reagents are placed. Microelectrodes in the channel detect the immunoreactions within 15 min, because of the small volume of sample in the microchannels resulting in fast equilibration between the sample and the reagents.33,34 Microelectrodes also enable the technique of CE-EC (capillary electrophoresis with electrochemical detection) to be extended to miniaturized systems. Use of individually addressable MEAs combined with electrophoretic separation can allow detection of multiple products in a sample.35 Portable DNA detectors using microelectrodes in microsystems and biochips has been reviewed
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
by Lee and Hsing.36 Electrochemical detection of DNA can be achieved by direct or catalyzed oxidation of DNA bases, or by the electrochemical response generated by enzyme or other redox markers by a specific binding event with the target DNA. There have recently been several excellent articles reviewing the electrochemical detection of DNA, including the use of nanoparticles that can increase the sensitivity of detection.37–39
for the assembly of biochips and micro sensing arrays. Electrochemical treatment of small, precise areas of an electrode surface by the probe can alter the surface properties to promote attachment of biomolecules. Electropolymerization of redox monomers such as pyrrole can also be patterned onto an electrode surface, and can then be used for attachment of biomolecules.
10 CONCLUSIONS 9 SECM
The main application of SECM to biosensors has been to probe the surface activity, and hence the surface reaction kinetics, of immobilized biological systems, in particular immobilized enzymes. Readers are referred to the large series of papers by Bard, one of the originators of SECM, which explore and expand the possibilities of the technique. Enzyme reactions can be measured by electrochemical detection of a substrate or product of an enzyme reaction, for example hydrogen peroxide, or alternatively a redox mediator can be used. Measurements with the probe can be made amperometrically or potentiometrically. Two modes of SECM can be used to image enzyme activity, the enzyme-mediated feedback mode first utilized by Pierce and coworkers,40 or the generator/collector mode.41 The generator/collector mode is used most frequently with enzyme samples as the enzyme reaction rates are often too slow for the feedback mode, though the spatial resolution of this technique somewhat worse. Electrochemical reactions at the probe can also be used to alter the solution composition at precisely defined areas of the sample, such as by generation of hydroxide ions to alter the local pH. The probe can then be used to monitor any change in biochemical activity. Detection of immuno or protein-binding events such as DNA hybridization can also be made by the use of enzyme labeling of a relevant protein species.42,43 Individual cells can also be investigated. SECM is also used to electrochemically pattern the electrode surface at the micrometer scale and to investigate the biochemical activity of miniaturized sensor arrays, including cross talk between neighboring immobilized species.44 Micropatterning of biomolecules is a necessary requirement
The field of biosensors and biochips continues to be an exciting and rapidly expanding area of research and the potential for miniaturization of multiparametric sensing systems is very attractive. The combination of microelectrodes with the technologies of microfluidics and MEMS will lead to a range of novel and multistep electrochemical assays such as the production of cheap and disposable DNA chips, immunoassays, and µTAS for an array of different analytes. These chips will have several advantages over current technologies because they will not only require small sample volumes, but also provide high sensitivity and low detection limits.
ACKNOWLEDGMENT
The authors would like to thank Professor Allen Hill for helpful discussions and suggestions.
REFERENCES ˇ 1. K. Stulik, C. Amatore, K. Holub, V. MareSek, and W. Kutner, Microelectrodes. Definitions, characterization, and applications. Pure and Applied Chemistry, 2000, 72, 1483–1492. 2. R. M. Penner, M. J. Heben, T. L. Longin, and N. S. Lewis, Fabrication and use of nanometer-sized electrodes in electrochemistry. Science, 1990, 250, 1118–1121. 3. M. A. Dayton, J. C. Brown, K. J. Stutts, and R. M. Wightman, Faradaic electrochemistry at microvoltammetric electrodes. Analytical Chemistry, 1980, 52, 946–950. 4. J. Heinze, Ultramicroelectrodes in electrochemistry. Angewandte Chemie International Edition in English, 1993, 32, 1268–1288. 5. C. Amatore, Electrochemistry at Ultramicroelectrodes, in Physical Electrochemistry—Principles, Methods and Applications, I. Rubinstein (ed), Marcel Dekker, New York, 1995, pp. 131–208.
MICROELECTROCHEMICAL SYSTEMS 6. J. Wang, Analytical Electrochemistry, 2nd Edn, WileyVCH, New York, 2000, pp. 128–134. 7. A. M. Bond, Past, present and future contributions of microelectrodes to analytical studies employing voltammetric detection, a review. Analyst, 1994, 119, R1–R21. 8. C. P. Andrieux, D. Garreau, P. Hapiot, and J. M. Saveant, Ultramicroelectrodes: cyclic voltammetry above one million V s−1 . Journal of Electroanalytical Chemistry, 1988, 248, 447–450. 9. N. Gao, M. Zhao, X. Zhang, and W. Jin, Measurement of enzyme activity in single cells by voltammetry using a microcell with a positionable dual electrode. Analytical Chemistry, 2006, 78, 231–238. 10. S. E. Hochstetler, M. Puopolo, S. Gustincich, E. Raviola, and R. M. Wightman, Real-time amperometric measurements of zeptomole quantities of dopamine released from neurons. Analytical Chemistry, 2000, 72, 489–496. 11. R. J. Forster, Microelectrodes: new dimensions in electrochemistry. Chemical Society Reviews, 1994, 23, 289–297. 12. C. G. Zoski, Ultramicroelectrodes: design, fabrication, and characterization. Electroanalysis, 2002, 14, 1041–1051. 13. R. L. McCarley, M. G. Sullivan, S. Ching, Y. Zhang, and R. W. Murray, Lithographic and Related Microelectrode Fabrication Techniques, in Microelectrodes: Theory and Applications, M. I. Montenegro, M. A. Queiros, and J. L. Daschbach (eds), Kluwer Academic Publishers, Dordrecht, 1991. 14. R. Feeney and P. Kounaves, Microfabricated ultramicroelectrode arrays: developments, advances, and applications in environmental analysis. Electroanalysis, 2000, 12, 677–684. 15. R. M. Wightman and D. O. Wipf, in Electroanalytical Chemistry, A. J. Bard (ed), Marcel Dekker, New York, 1989, Vol. 15, p. 267. 16. R. C. Engstrom, M. Weber, D. J. Wunder, R. Burgess, and S. Winquist, Measurements within the diffusion layer using a microelectrode probe. Analytical Chemistry, 1986, 58, 844–848. 17. H. Y. Liu, F. R. F. Fan, C. W. Lin, and A. J. Bard, Scanning electrochemical and tunneling ultramicroelectrode microscope for high-resolution examination of electrode surfaces in solution. Journal of the American Chemical Society, 1986, 108, 3838–3839. 18. A. J. Bard, F. R. Fan, and M. V. Mirkin, Scanning Electrochemical Microscopy, in Electroanalytical Chemistry, A. J. Bard (ed), Marcel Dekker, New York, 1994, Vol. 18, pp. 242–373. 19. M. V. Mirkin and A. J. Bard (eds), Scanning Electrochemical Microscopy, Marcel Dekker, New York, 2001. 20. Y. Zhang, H.-H. Kim, and A. Heller, Enzyme-amplified amperometric detection of 3000 copies of DNA in a 10-µL droplet at 0.5 fM concentration. Analytical Chemistry, 2003, 75, 3267–3269. 21. K. P. Troyer and R. M. Wightman, Dopamine transport into a single cell in a picoliter vial. Analytical Chemistry, 2002, 74, 5370–5375. 22. R. M. Wightman, Probing cellular chemistry in biological systems with microelectrodes. Science, 2006, 311, 570–574.
9
23. G. S. Wilson and R. Gifford, Biosensors for real-time in vivo measurements. Biosensors and Bioelectronics, 2005, 20, 2388–2403. 24. N. Dale, S. Hatz, F. Tian, and E. Llaudet, Listening to the brain: microelectrode biosensors for neurochemicals. Trends in Biotechnology, 2005, 23, 420–428. 25. K. P. Troyer, M. L. A. V. Heien, B. J. Venton, and R. M. Wightman, Neurochemistry and electroanalytical probes. Current Opinion in Chemical Biology, 2002, 6, 696–703. 26. R. H. S. Westerink, Exocytosis: using amperometry to study presynaptic mechanism of neurotoxicity. Neurotoxicology, 2004, 25, 461–470. 27. B. J. Venton and R. M. Wightman, Psychoanalytical electrochemistry: dopamine and behaviour. Analytical Chemistry, 2003, 75, 414A–421A. 28. F. Bedioui and N. Villeneuve, Electrochemical nitric oxide sensors for biological samples—principle, selected examples and applications. Electroanalysis, 2003, 15, 5–18. 29. J. Olofsson, K. Nolkrantz, F. Ryttsen, B. A. Lambie, S. G. Weber, and O. Orwar, Single-cell electroporation. Current Opinion in Biotechnology, 2003, 14, 29–34. 30. R. Pethig and G. H. Markx, Applications of dielectrophoresis in biotechnology. Trends in Biotechnology, 1997, 15, 426–432. 31. J. M. Cooper, Towards electronic petri dishes and picolitrescale single-cell technologies. Trends in Biotechnology, 1999, 17, 226–230. 32. A. Stett, U. Egert, E. Guenther, F. Hofmann, T. Meyer, W. Nisch, and H. Haemmerle, Biological application of microelectrode arrays in drug discovery and basic research. Analytical and Bioanalytical Chemistry, 2003, 377, 486–495. 33. J. Rossier, F. Reymond, and P. E. Michel, Polymer microfluidic chips for electrochemical and biochemical analyses. Electrophoresis, 2002, 23, 858–867. 34. J. S. Rossier, C. Vollet, A. Carnal, G. Lagger, V. Gobry, H. H. Girault, P. Michel, and F. Reymond, Plasma etched polymer microelectrochemical systems. Lab on a Chip, 2002, 2, 145–150. 35. J. Wang, Electrochemical detection for capillary electrophoresis microchips: a review. Electroanalysis, 2005, 17, 1133–1140. 36. T. M.-H. Lee and I.-M. Hsing, DNA-based bioanalytical microsystems for handheld device applications. Analytica Chimica Acta, 2006, 556, 26–37. 37. T. G. Drummond, M. G. Hill, and J. K. Barton, Electrochemical DNA sensors. Nature Biotechnology, 2003, 21, 1192–1199. 38. J. Wang, Nanoparticle-based electrochemical DNA detection. Analytica Chimica Acta, 2003, 500, 247–257. 39. A. Markoci, M. Aldavert, S. Marin, and S. Alegret, New materials for electrochemical sensing V: nanoparticles for DNA labeling. Trends in Analytical Chemistry, 2005, 24, 341–349. 40. D. T. Pierce, P. R. Unwin, and A. J. Bard, Scanning electrochemical microscopy. 17. Studies of enzyme-mediator kinetics for membrane- and surfaceimmobilized glucose oxidase. Analytical Chemistry, 1992, 64, 1795–1804. 41. G. Wittstock, R. Hesse, and W. Schuhmann, Patterned selfassembled alkanethiolate monolayers on gold patterning
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
and imaging by means of scanning electrochemical microscopy. Electroanalysis, 1997, 9, 746–750. 42. M. V. Mirkin and B. J. Horrocks, Electroanalytical measurements using the scanning electrochemical microscope. Analytica Chimica Acta, 2000, 406, 119–146. 43. G. Wittstock, Modification and characterization of artificially patterned enzymatically active surfaces by
scanning electrochemical microscopy. Fresenius Journal of Analytical Chemistry, 2001, 370, 303–315. 44. R. E. Gyurcsanyi, G. Jagerszki, G. Kiss, and K. Toth, Chemical imaging of biological systems with the scanning electrochemical microscope. Bioelectrochemistry, 2004, 63, 207–215.
45 Micro- and Nanoelectromechanical Sensors Keith L. Aubin,1 Bojan Ilic1,2 and Harold G. Craighead1 1
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA and 2 Cornell Nanoscale Science and Technology Facility, Cornell University, Ithaca, NY, USA
1 INTRODUCTION
In general, biosensors consist of certain elements regardless of the interrogation method employed. Specifically, the recognition of specific analytes out of many that may exist in the medium of interest, be it blood, air, or water, or any other substance from which knowledge of its constituents is desired, is for the most part dependent upon nature herself, that is to say, the biochemistry of life. Indeed, one of the most heralded biosensors known is right in front of the reader. As she/he is undoubtedly well acquainted with this organ, it still does some justice to point out here the great sensitivity of the human olfactory gland. Researchers across the globe seek an artificial scheme to replicate such sensitivity to the myriad of delights and repugnances that we experience every day and with every whiff. However, for simpler schemes of detection, say for the sensing of a single analyte of interest, it is quite adequate to borrow from the diversity of recognition that arises from the immune system, whose abilities are equally impressive, if not more so. Biosensors in general (artificial ones that is) require at the very least sensing and signal elements. The former usually relies upon this biochemistry existent in nature to specifically detect
the analyte of interest. For example, antibodies, which are proteins used in the immune system to recognize unwanted entities, or antigens, can be manufactured and used to coat the surface of a biosensor so as to make that surface receptive to a very specific target. Once (and if) that target analyte is present on the surface of this sensor, there must be a scheme in place to sense its presence. There are many ways presently in practice to accomplish this. One popular method is to use fluorescently labeled secondary antibodies that will also specifically bind to the analyte of interest. At a later step, this so-called “tagged” antibody is introduced and its incandescent properties are interrogated to reveal the presence of the analyte being sought. Although this method is quite useful, it does suffer from several difficulties. Arguably, the worst among these is the time required to incubate the sample so that a detectable amount of analyte adheres to the functionalized sensor surface. This time could be many hours, depending on the concentrations and analytes in question. If a method existed that could detect a smaller number or even single binding events, this would be a marked improvement over methods currently employed. Moreover, if such a method could be miniaturized and made
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
at such a cost so as to be relatively expendable, the frequency, and availability of these tests would benefit society in ways too numerous to state. Among the sensors being developed, the emerging field of microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS) has demonstrated a number of recent significant scientific advancements, translating into a wide range of potential chemical and biological sensing applications.1–18 Two alternate detection methods of note are outlined below. Briefly stated, these work by either detecting added mass through a shift in a natural resonance or detecting surface stresses brought about through receptor–ligand interaction. These devices, made by lithographic techniques, can be formed in highly uniform arrays in a form that can be readily integrated with motion transduction and microfluidic systems.19 In the case of oscillators, the types of materials that can be structured in this way have low mechanical losses providing a high mechanical quality factor and therefore well-defined resonant frequencies. The very specific resonant frequencies coupled with the low mass of the oscillator enable the detection of small amounts of additional bound mass. Experimental investigations illustrate that the ability to engineer nanoscale features on the surface of NEMS devices, combined with localized chemical functionalization, allows for specificity and calibration of these devices as detectors.20,21 For deflection devices, materials can be selected and layered in such a way as to maximize the binding and measured surface stresses. Although the nature of this detection method makes measuring single molecules impossible, they have been shown to be quite effective in measuring low concentrations of relevant analytes.22,23 They have the added advantage of having the ability to operate in liquid and thus measure analytes in real time.
2 RESONANCE DETECTION OF BIOLOGICAL ANALYTES 2.1
Introduction
The frequency of vibration of any resonating body obeys precisely known mathematics, which depend upon many factors, such as the material of
the structure, its shape, its mass, and so on. This is clearly seen in the example of a violin, whose strings, although of the same material, of the same length, and under similar tension, emit very different tones on account of the differing densities between the strings. This analogy can be generalized by saying structures of different masses, with all other parameters similar, will resonate at different frequencies (with some exceptions, of course, most notably the simple pendulum). It is this effect that is currently being investigated at the micro- and nanoscale. The motivation behind this is simple. All biosensors detect the presence of a mass, generally through secondary effects due to the presence of that mass. If one could detect this mass directly, it would simplify the system through the absence of this secondary “probe”. One possible way of doing this is to measure the frequency of a vibrating structure that is functionalized against an analyte of interest. As the analyte binds to the sensor, its frequency changes by virtue of the finite added mass of that analyte. The sensitivity to this mass change can be seen both mathematically and intuitively to be largely dependent upon the mass of the sensor itself, that is, the less massive the sensor, the smaller the detectable bound mass. Since the masses of biological analytes are exceedingly small, to detect them, one would need a very small vibrating device, indeed. This effect has therefore been investigated using micro- and nanoelectromechanical resonating systems. Most popular among these types of resonating sensors is a cantilever (or diving board–like) shape. To perform their specialized functions, resonant sensors and actuators must reliably store and convert different forms of energy, transduce signals, and respond in a repeatable manner to external chemical and biological environments. For instance, biomolecular adsorption of target analytes to treated regions of a cantilever-based sensor can alter mechanical stress within the oscillator as well as its total mass and thus influence both the bending and the natural frequency of the cantilever, respectively. Since both the deflection and resonant frequency shift are highly dependent upon the position of the adsorbed material, it is difficult to determine the exact amount of additional mass present without microscopic inspection.24–34
MICRO- AND NANOELECTROMECHANICAL SENSORS
To circumvent these limitations, one can construct arrays of surface micromachined oscillators with precisely positioned chemically functionalized anchors. In this scenario, binding events are confined to a particular portion of the device and do not occur anywhere else on the surface. Although many other methods for signal transduction exist (such as piezoresistive, capacitive, and magnetomotive), for the cases described
below, signal transduction was achieved by employing an optical-deflection or interferometric system to measure the mechanical bending or the frequency change in the out-of-plane translational vibrations resulting from additional loading by the specifically adsorbed mass.11–13,20,21,35–40 Within such a configuration, a collimated laser beam is focused onto the free end of the cantilever and is reflected onto a split photodiode. The difference signal between the two cells of the position-sensitive detector determines the cantilever bending while the AC signal corresponds to vibrations of the cantilever (see Figure 1a). In the case of interferometric detection, reflectance variations from the incident He–Ne laser are measured using a single-cell photodetector (see Figure 1b). The measured vibrations are induced through electrostatic, magnetic, piezoelectric, or optical actuation.18,40–49
e –N He aser L
Spectrum Photodetector analyzer Mirror
(a)
3
Sample
2.2
He–Ne laser
In order to estimate the lower detectable mass limit, surface-machined NEMS oscillators with integrated circular Au contacts and sub-attogram mass detection sensitivity were used in a study by researchers at Cornell University (see Figure 2).20 In order to maximize the sensitivity, the Au dots were placed in close proximity to the free end of the oscillator, where the amplitude of the oscillation is maximized (see equation 1). Mass loading effects were illustrated through selective immobilization of dinitrophenyl poly(ethylene
Spectrum analyzer
RF out Photodetector
(b)
Mass Sensitivity of Resonant Detection
Figure 1. Schematic of (a) deflection and (b) interferometric optical measurement apparatus.
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
Figure 2. Scanning electron micrograph (SEM) micrographs of cantilever (a–d) and bridge (e–h) type oscillators where the scale bars correspond to 5 µm and 2 µm, respectively. The diameters of the Au pads were 50, 100, 200, and 400 nm, from left to right. [Reprinted from Ilic et al.,20 with permission from American Institute of Physics.]
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
glycol) undecanthiol (DNP-PEG4-C11thiol)-based molecules to prefabricated Au contacts on the surface of the NEMS resonator. Following measurement of baseline frequencies, the gold dot was then removed using a wet gold etch. Subsequent measurements provided calibration data of corresponding frequency shifts that depended on the size of the original gold dot (Figure 3). Similar devices were immersed in a thiol solution to facilitate the selective binding of
DNP-PEG4-C11thiol self-assembled monolayers to the gold nanodots. Frequency shifts due to this additional mass loading were measured. For the frequency shifts of 125 Hz and 1.10 kHz demonstrated in Figure 4(a) and (b), the corresponding additional mass loading, calculated using Equation (1), was 6.3 and 213.1 ag, respectively. Within the linear elastic limit, the resonant frequency shift due to additional mass loading, assuming the bound mass is much less than the mass of the
Optical detector output (arb units)
1
0.8
0.6
0.4
0.2
0 2.465 2.470 2.475 2.480 2.485 (a)
Frequency (MHz)
2.465 2.470 2.475 2.480 2.485 (b)
Frequency (MHz)
Optical detector output (arb unit)
1
0.8
0.6
0.4
0.2
0 2.46 (c)
2.47
2.48
Frequency (MHz)
2.45 (d)
2.46
2.47
2.48
Frequency (MHz)
Figure 3. Calibration frequency spectra of 10-µm-long rectangular cantilevers before (dashed line) and after (solid line) the removal of the (a) 50-, (b) 100-, (c) 200-, and (d) 400-nm-diameter gold dots. [Reprinted from Ilic et al.,20 with permission from American Institute of Physics.]
MICRO- AND NANOELECTROMECHANICAL SENSORS
Optical detector output (arb units)
1
0.5
0 3.3525 (a)
3.3575
3.3550
1
0.5
0 3.3275
3.3250 (b)
Frequency (MHz)
Figure 4. Experimentally measured frequency spectra before (solid line) and after (dashed line) the adsorption of the thiolate on (a) 50- and (b) 400-nm-diameter gold dot. [Reprinted from Ilic et al.,20 with permission from American Institute of Physics.]
5
cantilever, x is the position of the bound mass measured from the base of the cantilever, l is the total length of the cantilever, and mo is the mass of the cantilever without bound mass. The same researchers, in a different study, set about to show how this exquisite sensitivity could be used to detect a single bound biological analyte using similar devices.21 Figure 5(a–c) shows cantilever devices fabricated from 90-nm-thick, lowstress silicon nitride with a 40-nm Au dot near the free end. Thiolate functionalized double-stranded 1587-bp DNA (dsDNA) molecules were used to illustrate the ability of single-molecule detection (see Figure 6). The resonant frequency of individual oscillators in an array of resonator devices was measured by thermo-optically driving the individual devices and detecting their motion by optical interference. The number of bound molecules was quantified from the measured frequency shift of the oscillator. Figure 7 illustrates the frequency shift due to a single dsDNA molecule bound to the catalyzing Au dot.
oscillator, is given by f = 0.279meff
2.3
EI l 3 m3o
(1)
where I is the moment of inertia of the cantilever, E is the Young’s modulus of low-stress silicon nitride (Emeasured ∼ 110 GPa assuming a silicon nitride density of 3.4 g cm−3 ), meff = mbound (x/ l) is the effective mass of the mass bound to the
(a)
(b)
Measurement of Biological Analytes
As a proof of principle, different types of biological analytes were detected using resonant NEMS/MEMS structures. These analytes included cells and viruses. The importance of detecting these types of analytes is clear when applied to areas of public health. Although the specific species detected in the studies described subsequently were not necessarily harmful to humans
(c)
Figure 5. (a) Optical and (b) and (c) scanning electron micrographs highlighting cantilevers of various length with 40-nm Au dots centered 300 nm away from the free end of the cantilever. [Reprinted with permission Ilic et al.21 copyright 2005, American Chemical Society.]
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
S
S
S Au
NEMS
bulk micromachined silicon nitride cantilevers, the presence of a single bacterium of Escherichia coli O157 : H7 was detected.30 This type of bacteria is known to cause severe illness through the ingestion of undercooked meat. The cantilevers were coated with antibodies reactive against E. coli and then immersed into solutions containing the cells at concentrations varying from 105 to 109 colonyforming units/ml. Resonant frequency spectra were taken before and after antibody coating and after exposure to cells. The measured vibrational mode was actuated entirely because of thermal noise and ambient vibrations in air. A single E. coli cell bound to a cantilever is shown in Figure 8(a). The measured frequency
1 0.8
(a)
0.6 0.4
1 Output (arb units)
Optical detector output (arb units)
Figure 6. Schematic of the optically driven interferometric setup employing a red He–Ne laser and a modulated blue diode laser for motion detection and excitation, respectively. Zoomed-in schematic shows the binding dynamics of the thiolated dsDNA molecules to the Au dots. [Reprinted with permission Ilic et al.21 copyright 2005, American Chemical Society.]
0.2 0 11.435
11.440 Frequency (MHz)
0.5
0
Figure 7. Measured frequency spectra for a NEMS resonator before (black) and after (red) the binding of a single DNA molecule. The blue lines are Lorentzian curve fits. [Reprinted with permission Ilic et al.21 copyright 2005, American Chemical Society.]
in their measured state, the detection methods used could be adapted through different biochemistry to detect analytes of more relevance. Using an array of relatively large (15–500-µm long)
1.04 (b)
1.08 f (MHz)
1.12
Figure 8. (a) Scanning electron micrograph (SEM) of a single E. coli O157:H7 cell bound to the immobilized antibody layer near the free end of the oscillator. Scale bar corresponds to 5 µm. (b) The corresponding thermal and ambient noise spectra due to the transverse vibrations of the cantilever before (black) and after (red) antibody immobilization and single cell attachment. [Reprinted from Ilic et al.,31 with permission from AVS The Science & Technology Society.]
MICRO- AND NANOELECTROMECHANICAL SENSORS
1 0.8 0.6 0.4 0.2
10.15 10.20 Frequency (MHz)
(a)
Optical detector output (arb units)
105
0 10.10
104
10.25
105 (b)
106 CFU (ml)
107
1 0.8 0.6 0.4 0.2 0 5.80
(c)
shift of 4.6 kHz due to the immobilization of a single cell corresponds to a mass of 665 fg, which is consistent with other reports and the estimated volume of this cell. The measured resonant frequency spectra of the cantilever, in air, before and after antibody and cell attachment, are plotted in Figure 8(b). A similar experiment requiring more sensitive devices was performed to detect the presence of a single virus. As a nonpathogenic model the group used the insect phage baculovirus.32 In this case, sensitivity enhancement was accomplished by employing smaller, surfacemachined polycrystalline silicon NEMS devices
Frequency shift (Hz)
Optical detector output (arb units)
Figure 9. A cantilever beam with a 1 × 1 µm2 paddle, defined using electron beam lithography. The scale bar represents 2 µm. [Reprinted from Ilic et al.,32 with permission from AVS The Science & Technology Society.]
7
5.85
5.90 5.95 6.00 Frequency (MHz)
6.05
6.10
Figure 10. Data showing detection of baculovirus. (a) Frequency spectra. The baseline frequency measurement is shown as the black peak. Subsequent frequency measurements following antibody (green) and virus binding (red) show easily measurable frequency shifts. The insets are cartoon schematics of the antibody–surface and virus–antibody–surface interactions (from right to left). (b) Frequency shifts of 6 (black), 8 (red), and 10 (blue) µm long cantilevers as a function of virus concentration in solution. (c) Frequency shift due to the control experiment using a buffer solution without baculovirus (blue). [Reprinted from Ilic et al.,32 with permission from AVS The Science & Technology Society.]
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
(see Figure 9). Following baseline frequency measurements in vacuum (10−6 Torr, in order to remove viscous damping effects), the devices were first functionalized by submersion in an antibody solution (AcV1 antibody against baculovirus gp64 envelope protein). Their frequency shift due to antibody binding was then measured. Similar steps using a baculovirus solution showed additional frequency shift, thereby sensing the specific binding of virus particles to the functionalized cantilever (see Figure 10a). Figure 10(b) shows the frequency shift variation with the baculovirus concentration for three different cantilever lengths. Nonspecificity of the binding was evaluated using a buffer solution without baculovirus. The frequency shifts from the control experiments were negligible compared to a shift from the binding of the baculovirus.
3 STATIC-DEFLECTION-BASED DETECTION 3.1
A notable difficulty with this method is the tendency for an uncoated cantilever, otherwise resting at its equilibrium position, to succumb to thermal effects and deflect without the stress of bound species. The deflection method in general is especially prone to this problem mainly because coating one side of the cantilever, designed to secure only the receptor of interest, by definition means that the cantilever will be a bilayer structure. Unless by some fortunate chance that the two layers share in common a near exact coefficient of thermal expansion, any temperature change will incite bending of the cantilever and be a frustrating source of noise. Several solutions to this problem have been implemented in the literature. These involve either controlling the temperature of the system or incorporating a reference device into the sensor.22,23 The latter method would also help minimize false signals due to nonspecific binding of nontarget material.
Introduction
Most surface-stress-based MEMS detection systems work by functionalizing a single side of a cantilevered beam. As the target ligand binds to an immobilized receptor on this surface, a stress develops across that face of the beam. Since only one side of the beam experiences this effect, the differential stress between the top and bottom faces of the beam cause a measurable bending of the cantilever. This slight bending is governed by Stoney’s equation: z = 3
(1 − v) L2 σ E t2
(2)
Here, z is the deflection of the cantilever tip, ν is Poisson’s ratio of the device material, t is its thickness, L its length, and σ is the differential change in surface stress (in J m−2 ) between the top and bottom surfaces of the cantilever. Generally, this slight bending is interrogated through the use of optical methods, similar to those used in atomic force microscopy (AFM), where a laser, impinging upon the cantilever with oblique incidence, is deflected into a split photodiode. The translated signal is thereby the difference in potential between the two adjacent photodiodes.
3.2
Detection of DNA Hybridization
By exploiting the effect outlined in the preceding text, the detection of hybridization events between probe and sample single-stranded DNA (ssDNA) was accomplished using 500-µm-long by 100-µm-wide by 1-µm-thick silicon cantilever devices (Figure 11).23 DNA hybridization is normally detected using fluorescent tags for the measurement of gene expression. The cantilever beams used in this study were purposely made long and thin (see equation 2) and consequently, to avoid stiction (i.e., the permanent and catastrophic attachment of the cantilever to an underlying substrate) these devices were made using bulk micromachining methods, thereby removing the substrate beneath the device altogether. Not only were hybridization events detected, but two separate types of DNA were detected in solution by functionalizing neighboring cantilevers with different probe capture strands of ssDNA. In serial measurements, these neighboring devices served as reference devices in order to minimize false signals due to thermal effects or nonspecific binding (Figure 12).
MICRO- AND NANOELECTROMECHANICAL SENSORS
9
Deflection (nm)
100 50
Ι
ΙΙ
ΙΙΙ
0 −50
100 µm
−100
3.3
Protein Detection (Prostate Specific Antigen)
The importance of the detection of small quantities of proteins in biological fluids is showcased by the example of prostate specific antigen (PSA). Blood levels of PSA have been shown to be elevated for people with prostate cancer. Such levels have been used to help diagnose the presence of this disease before the onset of symptoms. Indeed it is also known that such marker proteins exist for other types of cancer. As a competitive technology to enzyme-linked immunosorbent assays (ELISA) for protein detection, the deflection method of detection holds several advantages. First, where the former requires many twofold binding events for a successful detection (antigen to capture antibody and labeled probe antibody to antigen), the latter is a label-free method. Furthermore, since the cantilever devices are fabricated using wellestablished methods from the microelectronics industry, an array of such devices would be quite smaller than the 96-well microtiter plates used in ELISA, thus allowing for a high density of tests in a small area. An impressive example of protein detection using microfabricated cantilevers was that of the prostate cancer marker PSA. This small protein was detected using a commercially available AFM cantilever (Figure 13) functionalized with a coating of monoclonal antibodies specific to PSA. This cantilever was placed in a temperaturestabilized flow cell and was shown to detect PSA concentrations down to 0.2 ng ml−1 in simulated
0
20
(a)
40 60 Time (min)
80
100
80
100
30 Differential signal (nm)
Figure 11. Scanning electron micrograph of an array of microfabricated silicon cantilevers (1-µm thick, 500-µm long, and 100-µm wide; Micro- and Nanomechanics Group, IBM Zurich Research Laboratory, Switzerland). [Reprinted with permission from J. Fritz, et al. Science, 2000, 288, 316. Copyright 2000 AAAS.]
20 Ι
10
ΙΙ
ΙΙΙ
0 −10 −20 −30 0
(b)
20
40
60
Time (min)
Figure 12. Hybridization experiment using two cantilevers functionalized with different sequences. Interval I is a baseline measurement followed by injection of a complementary sequence to one of the cantilevers (interval II). After purging, the second complementary sequence was injected (interval III), followed 20 min later by another purge. (a) Absolute deflection versus time of two individual cantilevers covered with two different oligonucleotides (red and blue). (b) Corresponding differential signal. [Reprinted with permission from J. Fritz, et al. Science, 2000, 288, 316. Copyright 2000 AAAS.]
human serum (Figure 14).22 This concentration is within the range of clinical interest and its successful detection makes this method competitive to those presently used.
4 FLUIDIC NEMS AND MEMS
As described earlier in the chapter, resonant NEMS systems have been demonstrated as sensitive mass detectors with sub-attogram and even single-molecule sensitivity. Sample delivery is generally difficult in such cases requiring the entire
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Figure 13. Schematic diagram of the experimental setup where a microcantilever is mounted in a temperature-controlled fluid cell. The scanning electron micrograph on the right shows the geometry of a gold-coated silicon nitride cantilever beam (200-µm long, 0.5-µm thick, and with each leg 40-µm wide). Deflection measurements were made using a laser beam that was reflected off the back of the cantilever and focused onto a position-sensitive detector. [Reprinted with permission Wu et al.22 copyright 2001, Nature Publishing Group.]
200
Steady-state deflection, ∆hs (nm)
[BSA] = 1 mg ml−1 fPSA
150 Cantilever: 600-µm long, 0.65-µm thick
Clinical threshold fPSA concentration (4 ng ml−1) fPSA
Cantilever: 366-µm long, 0.65-µm thick
cPSA
100
fPSA
50 Cantilever: 200-µm long 0.5-µm thick 0 10−2
10−1
100
101
102
PSA concentration (ng
103
104
105
ml−1)
Figure 14. Steady-state cantilever deflections as a function of fPSA and cPSA concentrations for three different cantilever geometries. Note that longer cantilevers produce larger deflections for the same PSA concentration, thereby providing higher sensitivity. Each point represents an average of cantilever deflections obtained in multiple experiments done with different cantilevers. The error bars represent the range of deflections obtained from these experiments. The data (green diamonds) for fPSA detection, however, is from multiple experiments at a given concentration and is shown as a cluster plot. The error bar in each of these data points represents the fluctuation of the cantilever during the particular measurement. [Reprinted with permission Wu et al.22 copyright 2001, Nature Publishing Group.]
MICRO- AND NANOELECTROMECHANICAL SENSORS
Figure 15. Optical micrograph of encapsulated devices. The scale bars are 50 µm. The inset shows 12 NEMS devices which are part of a larger array.
2500 2000 Quality factor
device chip to be submersed into an analytecontaining mixture. Additionally, high vacuum is required to remove viscous damping to improve sensitivity. Recently, researchers at Cornell University have made progress showing that these devices can be a useful part of an on-chip analysis system by demonstrating the ability to encapsulate resonant NEMS in part of a microfluidic network (Figure 15). On-chip implementation of these systems and other microscale systems is a highly sought after solution to the bulky laboratory apparatus that is presently required to perform bioassays. Since chips in the microelectronics industry are mass produced in a highly reproducible and low-cost fashion, the advantages of placing highly sensitive bioanalysis systems in this format are clear. For the NEMS system described here, microchannels were used for delivery of liquids and nitrogen (for drying) and the channels could be pumped down to pressures where viscous damping effects are negligible (Figure 16). The devices were successfully operated under vacuum conditions while encapsulated within the microfluidic channels. Low operating pressures inside the channels eliminated viscous damping effects that would degrade the quality factor of resonance and thus reduce the mass sensitivity of the sensor if operated in air. This was confirmed by measuring the quality factor of a resonating structure while monitoring the pressure at the vacuum pump while the system was allowed to slowly leak
11
1500 1000 500
0.001 0.01
0.1
1
10
100
1000
Pressure (Torr) Figure 16. Quality factor as a function of pressure.
to atmospheric pressure (see Figure 16). These leaks were mostly from the external plumbing network, as the leak rate was not significantly different with or without the channels attached. The encapsulated devices were shown to detect baculovirus using a method similar to those described earlier in the chapter with the exception that the fluids containing antibodies for device functionalization and virus particles for detection were delivered via the microfluidic network. Washing agents, nitrogen (for drying), and vacuum were also applied via microfluidics to achieve desirable measurement conditions. Other advances in microfluidics have shown that it is possible to create on-chip sample preparation methods including preconcentration, filtration, solid phase extraction, and cell manipulation.50–52 Microfluidic on-chip pumps and flow sensors have also been demonstrated, with the latter consisting of an encapsulated MEMS.19 Such systems could be incorporated into a microfluidic network, part of which would encapsulate NEMS resonators for mass sensing applications. Researchers at MIT were successful at doing the converse of what is described in the preceding text. By creating a microscale cantilevered resonator constructed out of a microfluidic channel, researchers under the direction of S. Manalis were able to perform real-time resonant detection of binding events.53 Keeping biological molecules in solution is crucial in preserving their maximum function so that processes such as receptor–ligand binding
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Figure 17. Cantilevered microfluidic channel. [Reprinted from Burg and Manalis53 , with permission from American Institute of Physics.]
1 µm
100 µm
(a)
the creation of reasonably high vacuum in the vicinity of the resonator is necessitated. Such an environment would be prohibitive to the retention of liquid on the sensor’s surface, meaning that any biological molecules fixed there would be left dry, without the benefit of the ionic solution that would otherwise help it retain its very particular folded shape. Therefore, it is hypothesized that the drying of such molecules is detrimental to their function and may reduce the effectiveness of a sensor employing these techniques. The advantage that the Manalis system holds is that since the liquid runs through the resonator, and not over it, resonant motion of the device can take place in vacuum, thereby allowing for the resonant detection of binding events as they occur inside the cantilever. With this system, such protein interactions as streptavidin–biotin binding were measured. Figures 17 and 18 show schematics and images of the device.
(b) Figure 18. Cantilevered microfluidic channel. [Reprinted from Burg and Manalis53 , with permission from American Institute of Physics.]
can take place with an effectiveness close to that which occurs inside the body. This is problematic with the majority of resonant detection systems employing MEMS or NEMS oscillators since they require the removal of viscous damping forces to operate at peak sensitivity. Such can only be accomplished by the reduction of the scores of impinging molecules that would pelt the surface of the oscillator in a fluid environment. Thus,
5 CONCLUSION
As the above examples illustrate, there exists a considerable effort underway in providing miniaturized, highly sensitive biological sensors. It should be noted that many other efforts exist, not listed here, and were omitted mainly for the sake of brevity. Progress has been made in the ability to detect low analyte concentrations or even single molecules. To achieve this ever-increasing sensitivity, more complicated design, fabrication, transduction methods, and/or environmental control was necessary. Such requirements may seem daunting when thinking of real-world consumer
MICRO- AND NANOELECTROMECHANICAL SENSORS
applications for the detection of such analytes as disease protein markers, pathogenic contaminates, or biological warfare agents. However these engineering issues will undoubtedly be overcome. Research and commercial tools based on this technology may be soon realized.
REFERENCES 1. W. E. Newell, Miniaturization of tuning forks. Science, 1964, 161, 1320–1326. 2. H. C. Nathanson and R. A. Wickstrom, A resonant-gate silicon surface transistor with high-q band-pass properties. Applied Physics Letters, 1965, 7, 84–86. 3. H. C. Nathanson, W. E. Newell, R. A. Wickstrom, and J. R. Davis, The resonant gate transistor. IEEE Transactions on Electron Devices, 1967, 14, 117. 4. K. E. Peterson, Micromechanical light modulator array fabricated on silicon. Applied Physics Letters, 1977, 31, 521–523. 5. K. E. Peterson, Silicon torsional scanning mirror. IBM Journal of Research and Development, 1980, 24, 631–637. 6. K. E. Peterson, Silicon as a mechanical material. Proceedings of the IEEE, 1982, 70, 420–457. 7. R. A. Buser and N. F. de Rooij, Resonant silicon structures. Sensors and Actuators A, 1989, 17, 145–154. 8. N. V. Lavrik, M. J. Sepaniak, and P. G. Datskos, Cantilever transducers as a platform for chemical and biological sensors. Review of Scientific Instruments, 2004, 75, 2229–2253. 9. H. G. Craighead, Nanoelectromechanical systems. Science, 2000, 290, 1532–1535. 10. A. N. Cleland and M. L. Roukes, Fabrication of high frequency nanometer scale mechanical resonators from bulk Si crystals. Applied Physics Letters, 1996, 69, 2653–2655. 11. D. W. Carr and H. G. Craighead, Fabrication of nanoelectromechanical systems in single crystal silicon using silicon on insulator substrates and electron beam lithography. Journal of Vacuum Science and Technology B, 1997, 15, 2760–2763. 12. D. W. Carr, L. Sekaric, and H. G. Craighead, Measurement of nanomechanical resonant structures in single-crystal silicon. Journal of Vacuum Science and Technology B, 1998, 16, 3821–3824. 13. D. W. Carr, S. Evoy, L. Sekaric, H. G. Craighead, and J. M. Parpia, Measurement of mechanical resonance and losses in nanometer scale silicon wires. Applied Physics Letters, 1999, 75, 920–922. 14. X. M. H. Huang, C. A. Zorman, M. Mehregany, and M. L. Roukes, Nanoelectromechanical systems: nanodevice motion at microwave frequencies. Nature, 2003, 421, 496. 15. P. A. Williams, S. J. Papadakis, A. M. Patel, M. R. Falvo, S. Washburn, and R. Superfine, Torsional response and stiffening of individual multiwalled carbon nanotubes. Physical Review Letters, 2002, 89, 255502.
13
16. D. Qian, G. J. Wagner, W. K. Liu, M.-F. Yu, and R. S. Ruoff, Mechanics of carbon nanotubes. Applied Mechanics Reviews, 2002, 55, 495. 17. S. J. Papadakis, A. R. Hall, P. A. Williams, L. Vicci, M. R. Falvo, R. Superfine, and S. Washburn, Resonant oscillators with carbon-nanotube torsion springs. Physical Review Letters, 2004, 93, 146101. ¨ unel, D. Roundy, T. A. 18. V. Sazonova, Y. Yaish, H. Ust¨ Arias, and P. L. McEuen, A tunable carbon nanotube electromechanical oscillator. Nature, 2004, 431, 284–287. 19. D. Czaplewski, B. R. Ilic, M. Zalalutdinov, W. L. Olbricht, A. T. Zehnder, H. G. Craighead, and T. A. Michalske, A micromechanical flow sensor for microfluidic applications. Journal of Microelectromechanical Systems, 2004, 13, 576. 20. B. Ilic, H. G. Craighead, S. Krylov, W. Senaratne, C. Ober, and P. Neuzil, Attogram detection using nanoelectromechanical oscillators. Journal of Applied Physics, 2004, 95, 3694–3703. 21. B. Ilic, Y. Yang, K. Aubin, R. Reichenbach, S. Krylov, and H. G. Craighead, Enumeration of DNA molecules bound to a nanomechanical oscillator. Nano Letters, 2005, 5, 925–929. 22. G. Wu, R. H. Datar, K. M. Hansen, T. Thundat, R. J. Cote, and A. Majumdar, Bioassay of ProstateSpecific Antigen (PSA) using microcantilevers. Nature Biotechnology, 2001, 19, 856–860. 23. J. Fritz, M. K. Baller, H. P. Lang, H. Rothuizen, P. Vettiger, E. Meyer, H.-J. Guntherodt, Ch. Gerber, and J. K. Gimzewski, Translating biomolecular recognition into nanomechanics. Science, 2000, 288, 316–318. 24. H. P. Lang, R. Berger, C. Andreoli, J. Brugger, M. Despont, P. Vettiger, Ch. Gerber, J. K. Gimzewski, J. P. Ramseyer, E. Meyer, and H.-J. Guntherodt, Sequential position readout from arrays of micromechanical cantilever sensors. Applied Physics Letters, 1998, 72, 383–385. 25. Z. Hu, T. Thundat, and R. J. Warmack, Investigation of adsorption and absorption-induced stresses using microcantilever sensors. Journal of Applied Physics, 2001, 90, 427–431. 26. L. A. Pinnaduwage, V. Boiadjiev, J. E. Hawk, and T. Thundat, Sensitive detection of plastic explosives with self-assembled monolayer-coated microcantilevers. Applied Physics Letters, 2003, 83, 1471–1473. 27. D. R. Baselt, G. U. Lee, and R. J. Colton, Biosensor based on force microscope technology. Journal of Vacuum Science and Technology B, 1996, 14, 789–793. 28. G. Wu, H. Ji, K. Hansen, T. Thundat, R. Datar, R. Cote, M. F. Hagan, A. K. Chakraborty, and A. Majumdar, Origin of nanomechanical cantilever motion generated from biomolecular interactions. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98, 1560. 29. C. A. Savran, S. M. Knudsen, A. D. Ellington, and S. R. Manalis, Micromechanical detection of proteins using aptamer-based receptor molecules. Analytical Chemistry, 2004, 96, 3194–3198. 30. B. Ilic, D. Czaplewski, H. G. Craighead, P. Neuzil, C. Campagnolo, and C. Batt, Mechanical resonant immunospecific biological detector. Applied Physics Letters, 2000, 77, 450–452.
14
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
31. B. Ilic, D. Czaplewski, M. Zalalutdinov, H. G. Craighead, P. Neuzil, C. Campagnolo, and C. Batt, Single cell detection with micromechanical oscillators. Journal of Vacuum Science and Technology B, 2001, 19, 2825–2828. 32. B. Ilic, Y. Yang, and H. G. Craighead, Virus detection using nanoelectromechanical devices. Applied Physics Letters, 2004, 85, 2404–2406. 33. N. V. Lavrik and P. G. Datskos, Femtogram mass detection using photothermally actuated nanomechanical resonators. Applied Physics Letters, 2003, 82, 2697. 34. A. Gupta, D. Akin, and R. Bashir, Single virus particle mass detection using microresonators with nanoscale thickness. Applied Physics Letters, 2004, 84, 1976–1978. 35. G. Meyer and N. M. Amer, Novel optical approach to atomic force microscopy. Applied Physics Letters, 1988, 53, 1045–1047. 36. S. Alexander, L. Hellemans, O. Marti, J. Schneir, V. Ellings, P. K. Hansma, M. Longmire, and J. Gurley, An atomic-resolution atomic-force microscope implemented using an optical lever. Journal of Applied Physics, 1989, 65, 164–167. 37. D. Rugar, H. J. Mamin, and P. Guethner, Improved fiberoptic interferometer for atomic force microscopy. Applied Physics Letters, 1989, 55, 2588–2590. 38. P. K. Hansma, B. Drake, D. Grigg, C. B. Prater, F. Yashar, G. Gurley, V. Ellings, S. Feinstein, and R. Lal, A new optical-lever based atomic force microscope. Journal of Applied Physics, 1996, 76, 796–799. 39. D. W. Burns, J. D. Zook, R. D. Horning, W. R. Herb, and H. Guckel, Sealed-cavity resonant microbeam pressure sensor. Sensors and Actuators, A, 1995, 48, 179–186. 40. B. Ilic, S. Krylov, K. Aubin, R. Reichenbach, and H. G. Craighead, Optical excitation of nanoelectromechanical oscillators. Applied Physics Letters, 2005, 86, 193114. 41. D. Rugar, R. Budakian, H. J. Mamin, and B. W. Chui, Single spin detection by magnetic resonance force microscopy. Nature, 2004, 430, 329–332. 42. T. C. Nguyen, Micromechanical filters for miniaturized low-power communications. Proceedings of SPIE, 1999, 3673, 55. 43. S. Evoy, D. W. Carr, L. Sekaric, A. Olkhovets, J. M. Parpia, and H. G. Craighead, Nanofabrication
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
and electrostatic operation of single-crystal silicon paddle oscillators. Journal of Applied Physics, 1999, 86, 6072–6077. C. W. Yuan, E. Batalla, M. Zacher, A. L. de Lozanne, M. D. Kirk, and M. Tortonese, Low temperature magnetic force microscope utilizing a piezoresistive cantilever. Applied Physics Letters, 1994, 65, 1308. V. Kaajakari and A. Lal, Parametric excitation of circular micromachined polycrystalline silicon disks. Applied Physics Letters, 2004, 85, 3923–3925. M. Zalalutdinov, K. L. Aubin, R. B. Reichenbach, A. T. Zehnder, B. Houston, J. M. Parpia, and H. G. Craighead, Frequency entrainment for micromechanical oscillator. Applied Physics Letters, 2003, 83, 3815. R. B. Reichenbach, M. K. Zalaludinov, K. L. Aubin, D. A. Czaplewski, B. Ilic, B. H. Houston, H. G. Craighead, and J. M. Parpia, Resistively actuated micromechanical dome resonators. Proceedings of SPIE, 2004, 5344, 51. M. Zalalutdinov, A. Zehnder, A. Olkhovets, S. Turner, L. Sekaric, B. Ilic, D. Czaplewski, J. M. Parpia, and H. G. Craighead, Autoparametric optical drive for micromechanical oscillators. Applied Physics Letters, 2001, 79, 695. K. L. Aubin, M. Zalalutdinov, T. Alan, R. B. Reichenbach, R. Rand, A. Zehnder, J. Parpia, and H. G. Craighead, Limit cycle oscillations in CW laser-driven NEMS. Journal of Microelectromechanical Systems, 2004, 13, 1018. S. Song, A. K. Singh, and B. J. Kirby, Electrophoretic concentration of proteins at laser-patterned nanoporous membranes in microchips. Analytical Chemistry, 2004, 76, 4589–4592. Y. Yang, C. Li, K. H. Lee, and H. G. Craighead, Coupling on-chip solid-phase extraction to electrospray mass spectrometry through an integrated electrospray tip. Electrophoresis, 2005, 26, 3622–3630. B. J. Kirby, A. R. Wheeler, R. N. Zare, J. A. Fruetel, and T. J. Shepodd, Programmable modification of cell adhesion and zeta potential in silica microchips. Lab on a Chip, 2003, 3, 5–10. T. P. Burg and S. R. Manalis, Suspended microchannel resonators for biomolecular detection. Applied Physics Letters, 2003, 83, 2698–2700.
46 Nanobiolithography of Biochips Levi A. Gheber Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
1 WHY GO NANO?
The introduction of the arrayed biosensor, the so-called DNA chips and variations, has brought tremendous advances in the field of genomics, proteomics, diagnosis, and drug development during the last decade. Currently, more and more pharmaceutical companies are using this technology for developing new drugs, more and more hospitals are using them for diagnostic purposes. However, the present technology limits the use of these valuable tools to large research laboratories, major pharmaceutical companies, or advanced hospitals. In order for these instruments to provide maximum societal benefit, there is a pressing need to make them portable, point-of-care devices. In order to realize this transition, it is important to realize what precisely the limitations of the present technology are and to devise ways of overcoming them.
1.1
a high numerical aperture (NA) is required, which leads to a large magnification and a small view field. For example, a 20× objective on a typical microscope will provide a ∼1-mm-diameter viewfield, so it will image approximately nine spots at once, at best. In order to image the whole array, it is necessary to mechanically scan the sample across the objective. Scanning requires complex mechanics; in fact a chip scanner includes sophisticated robotics, which leads to large size and heavy weight of the instrument. This renders the chip nonportable, despite the relatively small size and light weight of the microscope slide on which the array is printed. Miniaturization serves the purpose of portability in a number of ways, beyond the obvious advantages of smaller size and lighter weight. As explained in the preceding text, the bottleneck in achieving true portability of chips is not the size of the chips per se, but the implications for reading that are imposed by this size. Reducing the size of the arrays themselves offers several advantages, as described in the subsequent text.
Limitations of Current Techniques
The array spots are large, ∼100 µm in width, placed at a spacing of ∼300 µm. In principle such separations can be resolved with the naked eye (which can easily resolve 0.3 mm). An objective is needed in a scanner because the emitted light levels are very low, so high light-collection power is needed. To achieve a high light-collection power,
1.2
Foreseen Advantages of Future Nanobiochips
1.2.1 Optical Advantage (No Scanning)
Smaller spots, ∼100-nm diameter at a spacing of ∼400 nm, are resolvable with conventional optical
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
microscopy (diffraction limit for high-NA objectives is ∼250 nm). The same 20× objective mentioned in the preceding text, providing a viewfield with a diameter of ∼1 mm can image 2500 spots at once, at this spacing. This means that there is no need to scan the sample; the whole array can be read at once for spots with these dimensions. 1.2.2 Light-collection Advantage (High NA Possible Due to No Scanning)
Oil objectives are not used with current scanners because their typical working distance is ∼170 µm with a depth of field of ∼1 µm, which makes it extremely difficult to avoid collisions of the sample with the objective while scanning, and movement of the array out of the focal plane of such objectives is practically inevitable. If scanning is not required, the use of high-NA, immersion oil objectives is possible. The great advantage in using high-NA objectives is their light-collection power. In epifluorescence, where excitation light is delivered through the objective that is also collecting the emitted fluorescence light, brightness of collected image is proportional to NA4 and inversely proportional to M 2 (M: magnification). For example: a 20× objective, NA = 0.6 collects ∼7.7 times less light than a 40× objective, NA = 1.4 (oil), despite the higher magnification of the 40×. Reduction of the size of spots and the spacing between them makes scanning unnecessary, opening the way to portability. In addition, the decrease in fluorescence signal following the reduction of spot size can be compensated to some extent by the use of high-NA oil objectives, which is possible once scanning is not required. Obviously, if an objective is implemented in the reading device, the portability is still limited, although much improved in comparison with the current technology (a scanner weighs somewhere between 8 and 15 kg, measures some 0.5 m in length and costs ∼¤50 000, an oil objective is ∼5 cm in length and diameter, weighs a few hundreds of grams and costs ∼¤1000). 1.2.3 Speed Advantage
Reactions on a smaller chip are faster, because mass transfer (governed by diffusion of target
molecules) and heat exchange (dissipation of heat generated by exothermic reactions) are faster.
1.2.4 Weight Advantage
Reduction in the linear dimensions of spots by 3 orders of magnitude leads to reduction in surface area by 106 . An additional reduction of ∼10× in thickness (from a standard ∼1-mm thick microscope slide to ∼0.15 mm of a cover glass) leads to an expected reduction in the weight of the carrier glass of ∼107 . Although the weight of one microscope slide is not a problem in its own, these firstprinciple calculations make the point that within the same light weight, one could accommodate at least 1 million miniaturized nanoarrays.
1.2.5 Cost Advantage
The biological components of an array represent a disproportionately large fraction of the materials costs. Miniaturization would enable the consumption of as much as 106 times less biological probe molecules, yielding a substantial cost saving to offset the increased cost of more sophisticated processing methods.
1.3
The ‘‘Lab-on-a-Chip’’ Concept and Nanobiolithography
The current biochip technology requires, in fact, a fully equipped laboratory and trained personnel in order to use the microarrays. The operations required typically include separation and purification of the sample, amplification (PCR in the case of DNA), blocking, hybridization, and washing. True portability of biochips would not be achieved even if the chip-reading equipment is portable (as explained in the preceding text), owing to this fact. This realization constitutes the main reasoning for the need to include a whole laboratory on a chip, able to perform the various tasks that are nowadays performed in the laboratory surrounding the microarray scanner. Such a lab-on-a-chip should include fluidic systems, like channels, pumps, and valves, able to perform tasks of separation, transfer of liquids, purification, amplification, and so on,
NANOBIOLITHOGRAPHY OF BIOCHIPS
2 HOW TO GO NANO? 2.1
Nanobiolithography Techniques
2.1.1 Nanografting
This approach is based on “nanoshaving” a selfassembled monolayer (SAM)1 on the surface of the sample, thus dislocating molecules of the SAM and exposing the substrate for adsorption of other molecules from solution (Figure 1). It is not a “direct-write” technique, and the quality of the protein nanostructures depends on the spatial precision of SAM nanopatterns and on the selectivity of protein adsorption. The adsorption of a biomolecule is performed in a second step and is based on the interaction between the inserted molecule (Z in Figure 1) and the biomolecule. The advantage of the technique is the simplicity of the SPM tools needed, basically just a simple Atomic Force Microscope (AFM) probe is needed in order to create the negative patterns in the SAM. The chemical details, however, render it less widely used. 2.1.2 Dip-pen Nanolithography (DPN)
Dip-pen nanolithography (DPN) has been historically the first demonstrated technique to use SPM in order to directly write nanoscale patterns of molecules.2 It uses an AFM probe that is dipped into an “ink” and is then precisely positioned on a surface onto which it writes the molecules, much
AFM tip
Scan
XXXXXXXXXXXXXXXX Au (111)
Z
XXX
ZZZ
Z
Z
Biolithography differs from the lithography employed in micro- and nanoelectronics in the fact that it aims at producing the same kind of features with biomolecules, on biomolecules, or in biomolecules. Since biomolecules are much more sensitive to their environment than inorganic materials (such as semiconductors and noble metals), most of the lithography technologies used in micro- and nanoelectronics are unsuitable for biolithography. High or ultrahigh vacuum is unacceptable, evaporation/sputtering is inapplicable, etching with strong acids would damage biomolecules, and irradiation with UV light would destroy DNA and proteins. Biolithography techniques, therefore, must operate in close to ambient atmosphere and/or in liquid, close to room temperature and moderate pH. Nanobiolithography techniques have to comply with all the preceding conditions and provide nanometer precision of positioning and nanometer-size dimensions of features. This is the reason that the most natural candidate for nanobiolithography is the scanning probe microscope (SPM), which enjoys all these abilities. This chapter therefore concentrates on SPM-based techniques. Several SPM-based methods have been demonstrated during the last decade. We shortly describe
them in the subsequent text, accompanied by representative examples, and discuss the advantages and disadvantages of each.
Z
in addition to bioarrays (perhaps several, perhaps some DNA arrays and some protein arrays) and the array-reading systems (light sources, filters, light sensors, etc.). Current microfluidic devices have typical dimensions of millimeters to centimeters, with microchannels of micrometer-scale diameters. Pumps, valves, and other mechanical devices are manufactured using the so-called microelectromechanical systems (MEMS) techniques, which are basically borrowed from microelectronics technology. Their dimensions, as the name indicates, are of tens of micrometers. Clearly, in order to tackle the concept of a portable lab-on-a-chip there is a pressing need to move from microfluidics to nanofluidics and from MEMS to NEMS (nanoelectromechanical systems), and this constitutes yet another significant reason to “go nano”.
3
Z
XXXX
Figure 1. Basic principle of nanografting. [Reproduced with permission Wadu-Mesthrige et al.1 copyright 1999, American Chemical Society.]
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS AFM tip
Writing direction Molecular transport Water meniscus
Au substrate Figure 2. Schematic process of DPN writing. [Reprinted with permission from Piner et al.2 Copyright 1999 AAAS.]
like a conventional dip pen, with a nanometer resolution, hence the name of the technique. The writing process is mediated by the (spontaneous) formation of a narrow capillary “neck” of water that is formed between the AFM probe tip and the sample, when the experiment is conducted in ambient atmosphere (in air). This capillary bridge allows the transport of molecules from the tip to the sample (and vice versa) and in the case where the molecules attach themselves to the surface, stable surface structures are formed on the surface, with nanometric dimensions (Figure 2). The choice of an “ink” designed to react with the surface on which it is written is very important, since it provides the chemical driving force that favors the transport of molecules from the tip to the surface.3 Another important aspect of DPN is that the humidity and temperature control provide a means of controlling the basic writing process and size of printed features. On the other hand, the need for controlled-environment chambers imposes some limitations on the technique. DPN can be extended in principle to a parallel lithography process,4,5 by using arrays of AFM cantilevers. Owing to the fact that AFM cantilevers are manufactured using conventional lithographic methods borrowed from the microelectronics industry, it is relatively easy to manufacture such arrays.
aperture ranging between a few tens of nanometers up to a few hundreds of nanometers (Figure 3). This nanopipette is mounted as the probe of an SPM and precisely controlled, to deliver a liquid filled in the capillary to the surface. In contrast to DPN, the probe is not dipped into an ink vessel and can in principle write continuously, similar to the differences between the macro dip pen and fountain pen. The use of micropipettes as probes for SPMs had been originally developed for near-field scanning optical microscopy (NSOM, or SNOM) as early as 1993,6 however, originally their purpose was to serve as light waveguides with subwavelength apertures. It was later that these nanopipettes were used for delivery of liquids to a surface,7,8 however not in a biological context. The demonstration of the ability to print patterns of proteins of submicrometer dimensions followed in 20029 and 2003.10 A nanopipette is filled with the liquid of choice, which is drawn to the tip of the probe by capillary
2.1.3 Nano Fountain Pen Nanolithography (NFP) 100 nm
The “fountain pen” technique typically use a glass or quartz capillary drawn into a sharp tip, with an
Figure 3. A nanopipette with a 200-nm-diameter aperture.
NANOBIOLITHOGRAPHY OF BIOCHIPS
forces. Typically the liquid does not flow out of the pipette on its own because of the surface tension of the droplet that forms at its end. Flow occurs only upon contacting the pipette with a surface (Figure 4). Two basic types of nanopipettes exist: the straight nanopipette and the cantilevered nanopipette. The straight probes are controlled, just like in NSOM, using a “shear-force” detection mechanism. The other type can use all modes employed in AFM, that is, contact, tapping, and noncontact, owing to the fact that it is a bent, cantilevered probe. With the straight probe, though, it is difficult to write lines, because once in contact with the surface, the feedback signal vanishes (the oscillation amplitude is zero) and it is not possible to keep a constant force while translating the sample. The bent probe, however can easily write lines. One more aspect of nano fountain pen nanolithography (NFP) that is worth mentioning is that flow of the liquid out of the pipette to the surface is governed, among other parameters, by the wettability of the liquid-substrate system. One advantage of NFP over DPN is its ability to print solutions of many types of molecules on many types of substrates (practically anything on anything), as we show in the subsequent text. Another, conceptual advantage (that has still to be demonstrated), is its ability to write “without pen lifting”, assuming one can load the pipette with a train of various molecules that are written as they come out of the tip of the pipette. The manufacture of nanopipettes is difficult, and they are apparently not amenable for either mass production or manufacture in arrays. However, work is under way in several groups, trying to combine the advantages of a fountain pen with
5
the advantages of microfabrication, to end up with cheaper, parallel arrays of probes.
2.1.4 Scanning Near-field Photolithography (SNP)
Scanning near-field photolithography (SNP) uses the light emanating from an NSOM to induce light-assisted chemical reactions on a surface. Owing to the fact that NSOM illuminates an area with dimensions well under the wavelength of the light it uses, the chemical reactions are limited to that nanometer-sized region (Figure 5). In the context of bionanolithography, this method has been applied to immobilize proteins11 and very recently DNA12 with very high resolution. Although not purely “direct write”, SNP is a very promising approach to bionanolithography.
2.1.5 Combinations and Variations
NPRW Nanopen reader and writer (NPRW) is a combination of the nanografting technique and DPN technique.14 Here a SAM monolayer is used as the “resist”, like in nanografting, which is removed locally with the tip of an AFM probe. The AFM probe is precoated with a different molecule, thus it simultaneously “shaves” the resist SAM and deposits a new adsorbate. The same probe is then used to image the features produced this way (Figure 6). NPRW presents an advantage over DPN in that the resolution does not depend on the
λ = 244 nm
Figure 4. Schematic process of NFP writing.
Figure 5. Schematic process of SNP. [Reproduced with permission Sun and Leggett13 copyright 2002, American Chemical Society.]
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS NPRW
Film/AFM contact line AFM tip Writting direction
Air Surface tension force
(a)
Au substrate
Film of patterning molecules Molecular resist
Au substrate
(b)
Au substrate Molecular resist
Au substrate
Figure 7. MFN principle. [Reprinted with permission Schwartz15 copyright 2001, American Chemical Society.]
(c)
Au substrate
Figure 6. Schematic diagram of NPRW illustrating the three basic steps to produce and characterize a pattern under ambient laboratory conditions. [Reproduced with permission Amro et al.14 copyright 2000, American Chemical Society.]
(a)
bare substrate or the humidity of the environment but on the tip–substrate contact force. MFN Unlike NPWR, in meniscus force nanolithography (MFN) the AFM probe is not coated with a SAM. Instead, it “swims” in a drop of solution containing the molecules to be written.15 The surface tension of the drop is pressing the tip with high force on the substrate. This allows the feedback loop of the AFM to be disconnected and, furthermore, the high force flattens the underlying polycrystalline gold and strips it of the resist monolayer. Thus, MFN can proceed at very high writing speeds (Figure 7). MFP Micromachined fountain pen (MFP) is a modified AFM probe with integrated fluidic channels running over the cantilever beams (Figure 8), which can replace the pulled glass capillaries used in NFP.16 The advantage it offers is the possibility of mass production of such probes, using standard technologies common in microelectronics. Another variant of the AFM-based fountain pen probe is termed nano fountain probe (as opposed
200 µm
(b)
(c)
Figure 8. Micromachined fountain pen for AFM-based nanopatterning. [Reprinted with permission Deladi et al.16 copyright 2004, American Institute of Physics.]
to nano fountain pen), and uses a “volcano”shaped AFM probe (Figure 9). This development has apparently the capability of both writing sub100-nm features and avoids the need for dipping the probe repetitively.17 E-DPN Electrochemical AFM dip-pen nanolithography (E-DPN) is an extension of DPN, which makes use of the minuscule water meniscus formed between the AFM probe and the surface as a nanometersized electrochemical cell, in which metal salts can be dissolved, reduced into metals electrochemically, and deposited on the surface.18 This is
NANOBIOLITHOGRAPHY OF BIOCHIPS
7
Shell Reservoir Core tip Microchannel Ink Liquid–air interface Water meniscus
(a)
Volcano tip
(b)
Reservoir
Cantilevers 2 µm (c)
500 µm (d)
Figure 9. Writing mechanism of the volcano tip. [Reprinted with permission Kim et al.17 copyright 2005, Wiley VCH.]
achieved by applying a voltage between the AFM tip and the substrate (Figure 10). This technique was used to write nanowires of metal, however it could conceivably be extended to biomolecules immobilized to these metallic features in a subsequent step.
U Ag/Agcl
Nanopipette
E-NFP Electrochemical nano fountain pen (E-NFP) uses a nanopipette, like NFP, but applies an electric field between two electrodes, one inserted into the nanopipette, and one inserted in the bath of ionic solution in which the pipette is immersed (Figure 11). The method offers the fine control
Figure 11. Schematic of the writing experiment. A voltage is applied between two Ag/AgCl electrodes, one inside the nanopipette, and one inserted into the bath of ionic solution. [Reprinted with permission Bruckbauer et al.9 copyright 2002, American Chemical Society.]
of the delivery potentially down to the singlemolecule level.9 2.2 Figure 10. Schematic sketch of the E-DPN experimental setup. [Reprinted with permission Li et al.18 copyright 2001, American Chemical Society.]
Positive Nanobiolithography (Deposition of Material)
It is important to make a few distinctions before describing specific results.
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
Direct write versus indirect write: By directwrite processes one means directly depositing the molecules of interest onto the substrate. For example, nanografting, as described in the preceding text, is not a direct-write technique. DPN, on the other hand, is a direct-write technique in some cases, and an indirect writing process in others, depending on the molecule to be patterned: if the directly written molecule is an intermediate stage, followed by additional steps to link the final molecule, then it is not considered “direct write”. At this point, however, it is important to make the other distinction: immobilization of the patterned molecules on the substrate. The step of immobilization is important in order to achieve the goal of a functional biochip, and depending on the approach, may contribute to the definition of a lithography method as a direct or indirect one. If, for example, a technique is used to directly
pattern a molecule that serves as the linker of the biomolecule to the substrate, then the technique is “direct write” as far as the linker is concerned, but indirect as far as the biomolecule is concerned. However, directly patterning the biomolecule on the substrate, even if possible, would not attain the goal of immobilization. Therefore, these definitions, if at all, should be used carefully and in the correct context. One more point to make is that in some cases, fully operational nanoarrays (although very simplified, compared with microarrays) have been demonstrated, while in other cases only the patterning of the probe molecules has been presented. This is indicated in the brief description of the reported achievements in the subsequent text. Several examples are described, grouped according to the nanopatterned biomolecules. These are also summarized in Table 1.
Table 1. A summary of biomolecules that have been patterned using nanobiolithography techniques
Molecule
Details
Method
Lysozyme, IgG IgG Lysozyme Collagen BSA Streptavidin, BSA Protein G Lysozyme Lysozyme, IgG IgG, DNA His-tagged peptides IgG Enzyme: staphylococcal serine V8 protease Protein G, GFP Enzyme: trypsin IgG in nanowells Enzyme: DNase I IgG His6-ubiquitin, thioredoxin Avidin, BSA Avidin CPMV TMV Escherichia coli Photoresist PDMS TRIM
MFN E-NFP Nanografting DPN SNP Nanografting Nanografting Nanografting DPN SNP DPN E-NFP DPN DPN E-NFP E-DPN DPN Immobilized DPN NFP NFP E-NFP DPN DPN DPN c-AFM DPN DPN, nanografting DPN DPN NFP DPN NFP
DNA
Proteins
Virus Single cell Polymers
CPMV: cowpea mosaic virus; TMV: tobacco mosaic virus; PDMS: Polydimethylsiloxane; TRIM: trimethylolpropane trimethacrylate.
References 15 9 19 20 12 1 21 22 23 11 24 9 25 26 27 28 29 30 10 31, 32 33 34 35 36 37 38 39 40 41 7 42 43
NANOBIOLITHOGRAPHY OF BIOCHIPS
2.2.1 DNA
Patterning of DNA has been demonstrated with most of the techniques mentioned here. Nanografting,19 MFN,15 E-NFP,9 DPN,20 and recently SNP.12 Importantly, ssDNA nanostructures have been proved to be amenable for hybridization with target complementary DNA fragments, in multifunctional arrays20,27,44 (Figures 12 and 13). 2.2.2 Proteins
A large variety of proteins has been printed on submicrometer scale by virtually all the techniques discussed in the preceding text. Lysozyme was printed using Nanografting 1,22 and DPN.25,26
9
Immunoglobulin G (IgG) antibodies from various sources have been patterned using Nanografting,1 for rabbit IgG21 their function was proved with goat antirabbit IgG, DPN 26 where direct writing of rabbit IgG was demonstrated on a multicomponent (lysozyme) array and probed with anti-IgG, and antirabbit and antihuman IgG (Figure 14), probed with rabbit and human IgG, respectively29 and anti-p24(human immunodeficiency virus (HIV)).35 Rabbit IgG was also patterned using E-NFP, and was proved functional by probing with antiIgG.27,33 Bovine serum albumin (BSA) has been patterned using SNP,11 DPN,24 and conductive AFM (c-AFM ).37 Another important protein, avidin/streptavidin has been patterned with various techniques: DPN,24,38 c-AFM.37 Protein G has been patterned with E-NFP 9 and NFP.10 Other
4 µm
12 µm
Figure 12. Combined red–green epifluorescence image of two different fluorophore-labeled sequences simultaneously hybridized to a two-sequence array deposited on an SiOx substrate by DPN. [Reprinted with permission Demers et al.20 copyright 2002, AAAS.]
5 µm
Figure 14. Array of dots consisting of antirabbit IgG (labeled with Alexa 594) on a negatively charged SiO2 surface. [Reprinted with permission Lim et al.29 copyright 2003, Wiley VCH.]
5 µm
5 µm
Figure 13. Spots of ssDNA labeled with biotin and Alexa Fluor 647 (Alexa 647 DNA, 35 mer) delivered by the nanopipette onto a streptavidin surface. Fluorescence images spotted DNA (red), hybridized complementary DNA (green), and combined image (yellow). The second oligonucleotide hybridizes selectively to the initial spotted oligonucleotide. [Reprinted with permission Bruckbauer et al.27 copyright 2003, American Chemical Society.]
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
examples of proteins include his-tagged peptides with E-DPN,28 his-tagged ubiquitin and thioredoxin with DPN 36 and GFP printed with NFP.10 Also collagen was patterned using DPN.23 Enzymes have also been delivered to surfaces in one way or another, however they will be discussed subsequently in the context of enzymebased negative lithography.
2.2.3 Virus
Entire viruses have been patterned using SPMbased nanobiolithography techniques. Two examples are (genetically modified) cowpea mosaic virus (CPMV) that has been patterned using nanografting and DPN39 and tobacco mosaic virus (TMV), patterned using DPN.40
2.2.4 Polymers
Although polymers are not biological molecules, the ability to nanopattern them may find important applications in future nanobiochips. We mention here three examples: photoresist (a form of Poly(methyl methacrylate) (PMMA)) printed with NFP,7 PDMS printed with DPN,42 and trimethylolpropane trimethacrylate (TRIM) printed with NFP43 (Figure 15).
2.3
Negative Nanobiolithography (Removal of Material)
Negative lithography, as opposed to positive lithography, is a process by which material is removed from surfaces in desired areas. Many nonbiological methods exist to perform negative lithography in general and nanolithography in particular. The methods can basically be divided into two groups: mechanical (such as indentation, scraping, etc.) and chemical (involving some type of etching agent). The key element in biological negative lithography is the use of biological molecules that possess specificity. Unlike an acid attacking silicon, a metal, and so on, an enzyme will only recognize with high affinity a specific substrate. Enzyme-based nanolithography uses the tools employed for positive nanolithography, to pattern enzymes on surfaces covered with the substrate of the enzyme. So far three such examples have been demonstrated. Staphylococcal serine V8 protease was immobilized to an AFM tip and scanned on a surface consisting of peptides immobilized on mica.30 The protease recognizes either glutamic or aspartic acid residues in the peptide and digests the peptide’s C
3.5 µm 32.
5µ
m
s 60
12
0
s
s 20
32 .5
µm
10 µm
Figure 15. Dots of trimethylolpropane trimethacrylate (TRIM) deposited with NFP. [Reprinted with permission Sokuler and Gheber43 copyright 2006, American Chemical Society.]
Figure 16. Nanowells created by delivering trypsin with NFP on a BSA-covered surface. [Reprinted with permission Ionescu et al.31 copyright 2003 American Chemical Society.]
NANOBIOLITHOGRAPHY OF BIOCHIPS
11
efforts are currently being invested by the scientific community to find solutions to this problem. For example, polymer microlenses that could significantly enhance the emitted light.43
3.2
Figure 17. Nanotrenches in DNA surface using DNAse I and DPN. [Reprinted with permission Hyun et al.34 copyright 2004, American Chemical society.]
terminus. It was demonstrated that the peptide containing glutamic acid was “etched” by the enzyme. Trypsin, another protease, has been patterned using NFP on a BSA-covered surface, to create depressions. Trypsin recognizes lysine and/or arginine and hydrolyzes the peptide bond at these locations. BSA contains 86 lysine and arginine amino acids, therefore the cleavage by trypsin causes the collapse of the protein structure31 (Figure 16). The same approach was used to create nanochannels in a BSA substrate.32 DNase I, a nonspecific endonuclease that digests double-stranded and single-stranded DNA into nucleotide fragments was patterned using DPN, onto a surface functionalized with an oligonucleotide SAM.34 The enzyme digested the oligonucleotide substrate, leading to the creation of nanochannels (Figure 17).
3 OBSTACLES TO OVERCOME 3.1
Low Signal Intensity
Reduction of spot size by ∼103 is expected to reduce fluorescence emission intensity by ∼106 (like the reduction of the area) compared with signal intensities presently available in microarray technology, but hopefully less, due to improvement of surfaces and their binding capacity. This reduction in signal has to be compensated by more than just the transition to a high-NA objective, and
Expensive Manufacture Methods
All the techniques described in the preceding text, based on SPM methods, are inherently expensive. The high price is due to the systems, the probes, and the fact that scanning techniques are serial, and thus slow. Several proof-of-concept demonstrations show that DPN is in principle extendable to a parallel process,5,45,46 which should speed up nanobiolithography processes.
3.3
Multiplicity of Molecules
Nanobioarrays demonstrated so far have been composed of two different molecules, to the best. These are obviously only the first steps, proofs of concept, however it is clear that if and when the previous problems are solved, the ability to nanopattern hundreds, if not thousands, of different biomolecules, will become a limiting step.
3.4
Label-free and Time-resolved Detection
One of the goals of nanobiolithography is to greatly improve the portability of biochips. Portable biochips can potentially be used for monitoring the quality of food, water, and the environment in general. However, the present biochip technology, based almost entirely on fluorescent labeling of the target, is incompatible with continuous monitoring. Therefore, label-free detection methods need to be developed, compatible with microarray and future nanoarray technology.
REFERENCES 1. K. Wadu-Mesthrige, S. Xu, N. A. Amro, and G. Y. Liu, Fabrication and imaging of nanometer-sized protein patterns. Langmuir, 1999, 15, 8580–8583. 2. R. D. Piner, J. Zhu, F. Xu, S. H. Hong, and C. A. Mirkin, “Dip-pen” nanolithography. Science, 1999, 283, 661–663.
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
3. C. A. Mirkin, S. H. Hong, and L. Demers, Dip-pen nanolithography: Controlling surface architecture on the sub-100 nanometer length scale. Chemphyschem, 2001, 2, 37–39. 4. S. H. Hong, J. Zhu, and C. A. Mirkin, Multiple ink nanolithography: Toward a multiple-pen nano-plotter. Science, 1999, 286, 523–525. 5. K. Salaita, S. W. Lee, X. F. Wang, L. Huang, T. M. Dellinger, C. Liu, and C. A. Mirkin, Sub-100 nm, centimeter-scale, parallel dip-pen nanolithography. Small, 2005, 1, 940–945. 6. K. Lieberman and A. Lewis, Simultaneous scanning tunneling and optical near-field imaging with a micropipette. Applied Physics Letters, 1993, 62, 1335–1357. 7. M. H. Hong, K. H. Kim, J. Bae, and W. Jhe, Scanning nanolithography using a material-filled nanopipette. Applied Physics Letters, 2000, 77, 2604–2606. 8. A. Lewis, Y. Kheifetz, E. Shambrodt, A. Radko, E. Khatchatryan, and C. Sukenik, Fountain pen nanochemistry: Atomic force control of chrome etching. Applied Physics Letters, 1999, 75, 2689–2691. 9. A. Bruckbauer, L. M. Ying, A. M. Rothery, D. J. Zhou, A. I. Shevchuk, C. Abell, Y. E. Korchev, and D. Klenerman, Writing with DNA and protein using a nanopipet for controlled delivery. Journal of the American Chemical Society, 2002, 124, 8810–8811. 10. H. Taha, R. S. Marks, L. A. Gheber, I. Rousso, J. Newman, C. Sukenik, and A. Lewis, Protein printing with an atomic force sensing nanofountainpen. Applied Physics Letters, 2003, 83, 1041–1043. 11. C. Philipona, Y. Chevolot, D. Leonard, H. J. Mathieu, H. Sigrist, and F. Marquis-Weible, A scanning near-field optical microscope approach to biomolecule patterning. Bioconjugate Chemistry, 2001, 12, 332–336. 12. S. Q. Sun, M. Montague, K. Critchley, M. S. Chen, W. J. Dressick, S. D. Evans, and G. J. Leggett, Fabrication of biological nanostructures by scanning nearfield photolithography of chloromethylphenyisiloxane monolayers. Nano Letters, 2006, 6, 29–33. 13. S. Q. Sun and G. J. Leggett, Generation of nanostructures by scanning near-field photolithography of self-assembled monolayers and wet chemical etching. Nano Letters, 2002, 2, 1223–1227. 14. N. A. Amro, S. Xu, and G. Y. Liu, Patterning surfaces using tip-directed displacement and selfassembly. Langmuir, 2000, 16, 3006–3009. 15. P. V. Schwartz, Meniscus force nanografting: Nanoscopic patterning of DNA. Langmuir, 2001, 17, 5971–5977. 16. S. Deladi, N. R. Tas, J. W. Berenschot, G. J. M. Krijnen, M. J. de Boer, J. H. de Boer, M. Peter, and M. C. Elwenspoek, Micromachined fountain pen for atomic force microscope-based nanopatterning. Applied Physics Letters, 2004, 85, 5361–5363. 17. K. H. Kim, N. Moldovan, and H. D. Espinosa, A nanofountain probe with sub-100 nm molecular writing resolution. Small, 2005, 1, 632–635. 18. Y. Li, B. W. Maynor, and J. Liu, Electrochemical AFM “Dip-Pen” nanolithography. Journal of the American Chemical Society, 2001, 123, 2105–2106. 19. M. Z. Liu, N. A. Amro, C. S. Chow, and G. Y. Liu, Production of nanostructures of DNA on surfaces. Nano Letters, 2002, 2, 863–867.
20. L. M. Demers, D. S. Ginger, S. J. Park, Z. Li, S. W. Chung, and C. A. Mirkin, Direct patterning of modified oligonucleotides on metals and insulators by dip-pen nanolithography. Science, 2002, 296, 1836–1838. 21. J. R. Kenseth, J. A. Harnisch, V. W. Jones, and M. D. Porter, Investigation of approaches for the fabrication of protein patterns by scanning probe lithography. Langmuir, 2001, 17, 4105–4112. 22. K. Wadu-Mesthrige, N. A. Amro, J. C. Garno, S. Xu, and G. Y. Liu, Fabrication of nanometer-sized protein patterns using atomic force microscopy and selective immobilization. Biophysical Journal, 2001, 80, 1891–1899. 23. D. L. Wilson, R. Martin, S. Hong, M. Cronin-Golomb, C. A. Mirkin, and D. L. Kaplan, Surface organization and nanopatterning of collagen by dip-pen nanolithography. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98, 13660–13664. 24. J. Hyun, S. J. Ahn, W. K. Lee, A. Chilkoti, and S. Zauscher, Molecular recognition-mediated fabrication of protein nanostructures by dip-pen lithography. Nano Letters, 2002, 2, 1203–1207. 25. K. B. Lee, S. J. Park, C. A. Mirkin, J. C. Smith, and M. Mrksich, Protein nanoarrays generated by dip-pen nanolithography. Science, 2002, 295, 1702–1705. 26. K. B. Lee, J. H. Lim, and C. A. Mirkin, Protein nanostructures formed via direct-write dip-pen nanolithography. Journal of the American Chemical Society, 2003, 125, 5588–5589. 27. A. Bruckbauer, D. J. Zhou, L. M. Ying, Y. E. Korchev, C. Abell, and D. Klenerman, Multicomponent submicron features of biomolecules created by voltage controlled deposition from a nanopipet. Journal of the American Chemical Society, 2003, 125, 9834–9839. 28. G. Agarwal, R. R. Naik, and M. O. Stone, Immobilization of histidine-tagged proteins on nickel by electrochemical dip pen nanolithography. Journal of the American Chemical Society, 2003, 125, 7408–7412. 29. J. H. Lim, D. S. Ginger, K. B. Lee, J. Heo, J. M. Nam, and C. A. Mirkin, Direct-write dip-pen nanolithography of proteins on modified silicon oxide surfaces. Angewandte Chemie International Edition, 2003, 42, 2309–2312. 30. S. Takeda, C. Nakamura, C. Miyamoto, N. Nakamura, M. Kageshima, H. Tokumoto, and J. Miyake, Lithographing of biomolecules on a substrate surface using an enzyme-immobilized AFM tip. Nano Letters, 2003, 3, 1471–1474. 31. R. E. Ionescu, R. S. Marks, and L. A. Gheber, Nanolithography using protease etching of protein surfaces. Nano Letters, 2003, 3, 1639–1642. 32. R. E. Ionescu, R. S. Marks, and L. A. Gheber, Manufacturing of nanochannels with controlled dimensions using protease nanolithography. Nano Letters, 2005, 5, 821–827. 33. A. Bruckbauer, D. J. Zhou, D. J. Kang, Y. E. Korchev, C. Abell, and D. Klenerman, An addressable antibody nanoarray produced on a nanostructured surface. Journal of the American Chemical Society, 2004, 126, 6508–6509. 34. J. Hyun, J. Kim, S. L. Craig, and A. Chilkoti, Enzymatic nanolithography of a self-assembled oligonucleotide monolayer on gold. Journal of the American Chemical Society, 2004, 126, 4770–4771.
NANOBIOLITHOGRAPHY OF BIOCHIPS 35. K. B. Lee, E. Y. Kim, C. A. Mirkin, and S. M. Wolinsky, The use of nanoarrays for highly sensitive and selective detection of human immunodeficiency virus type 1 in plasma. Nano Letters, 2004, 4, 1869–1872. 36. J. M. Nam, S. W. Han, K. B. Lee, X. G. Liu, M. A. Ratner, and C. A. Mirkin, Bioactive protein nanoarrays on nickel oxide surfaces formed by dip-pen nanolithography. Angewandte Chemie International Edition, 2004, 43, 1246–1249. 37. J. H. Gu, C. M. Yam, S. Li, and C. Z. Cai, Nanometric protein arrays on protein-resistant monolayers on silicon surfaces. Journal of the American Chemical Society, 2004, 126, 8098–8099. 38. Q. L. Tang, Y. X. Zhang, L. H. Chen, F. N. Yan, and R. Wang, Protein delivery with nanoscale precision. Nanotechnology, 2005, 16, 1062–1068. 39. C. L. Cheung, J. A. Camarero, B. W. Woods, T. W. Lin, J. E. Johnson, and J. J. De Yoreo, Fabrication of assembled virus nanostructures on templates of chemoselective linkers formed by scanning probe nanolithography. Journal of the American Chemical Society, 2003, 125, 6848–6849.
13
40. R. A. Vega, D. Maspoch, K. Salaita, and C. A. Mirkin, Nanoarrays of single virus particles. Angewandte Chemie International Edition, 2005, 44, 6013–6015. 41. S. Rozhok, C. K. F. Shen, P. L. H. Littler, Z. F. Fan, C. Liu, C. A. Mirkin, and R. C. Holz, Methods for fabricating microarrays of motile bacteria. Small, 2005, 1, 445–451. 42. D. L. Malotky and M. K. Chaudhury, Investigation of capillary forces using atomic force microscopy. Langmuir, 2001, 17, 7823–7829. 43. M. Sokuler and L. A. Gheber, Nano fountain pen manufacture of polymer lenses for nano-biochip applications. Nano Letters, 2006, 6, 848–853. 44. M. Z. Liu and G. Y. Liu, Hybridization with nanostructures of single-stranded DNA. Langmuir, 2005, 21, 1972–1978. 45. S. H. Hang and C. A. Mirkin, A nanoplotter with both parallel and serial writing capabilities. Science, 2000, 288, 1808–1811. 46. M. Zhang, D. Bullen, S. W. Chung, S. Hong, K. S. Ryu, Z. F. Fan, C. A. Mirkin, and C. Liu, A MEMS nanoplotter with high-density parallel dip-pen manolithography probe arrays. Nanotechnology, 2002, 13, 212–217.
47 Nanosphere Lithography-Based Chemical Nanopatterns for Biosensor Design Pascal Colpo, Andrea Valsesia, Patricia Lisboa and Fran¸cois Rossi Institute for Health and Consumer Protection, Joint Research Centre, Ispra, Italy
1 INTRODUCTION
Patterning biomolecules on surfaces is a fundamental issue for many biosensor applications such as medical diagnostics, environment monitoring, food safety, or security applications.1 For instance in genomics and proteomics areas, DNA and proteins are patterned in hundreds of micrometer spots, enabling thousands of analysis to be performed simultaneously on a small area. The step forward in terms of miniaturization leads naturally to submicron patterning. Nanoarrays represent a radical technology breakthrough that would provide an enormous performance enhancement compared to conventional technologies. They are intended to increase by several orders of magnitude the number of analyses in the same area and to lower the detection limits. Nanoarrays will be the technological basement of a new generation of miniaturized biochips for molecular diagnostics. Many experiments are being performed worldwide to develop advanced sensing platforms having controlled surface chemistry with welldefined nanopatterns. The goal is to immobilize biomolecules on a surface in an active state, avoiding nonspecific adsorption. The main trends are to structure the surface in adhesive and nonadhesive zones to control the protein binding at the nanoscale. The surface densification of the recognition element results in an amplification of the
recognition activity of the sensing surface, leading to an enhancement of the sensitivity and the specificity of the sensor. Another important consequence is the reduction of the analyte volume needed for the detection. Many approaches are used to create chemical surface nanostructuring: for instance nanosoft lithography,2,3 dip-pen lithography,4–6 and nanofountain pen lithography.7 These techniques allow the production of nanofeatures with typical dimensions of a few hundred nanometers. The approaches are based on the sequential dispensing of small (nano) quantities of functional molecules (polypeptides, oligonucleic acids, thiols) in specific locations, followed by the passivation of the remaining area using antiadhesion layers. An alternative nanopatterning technique to fabricate nanofeatures is the so-called nanosphere lithography. This technique relies on the selfassembly of monodisperse nanoparticles that are used as a 2D nanomask during etching and deposition operations. This technique presents the advantage of being inexpensive and enables the production of nanotopography over large surfaces.8 This chapter describes a reliable technique to directly create a chemical nanopatterned surface using nanosphere lithography. The first part of the chapter provides some background information on colloidal lithography including techniques of deposition and phenomena involved in the
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
colloidal mask formation. Then, two different strategies for surface chemical nanopatterning are presented: the first based on plasma deposited polymers and the second based on self-assembled monolayers (SAM).
2 NANOSPHERE LITHOGRAPHY
Colloidal-particle films have several technological and fundamental applications. They are employed as nanomasks for etching or deposition processes and as nanobuilding blocks for the nanostructuring of a surface. Whenever ordered in regular arrays (2D or 3D colloidal crystals), they can provide special optical properties (photonic crystal, enhanced plasmonic surface resonance, or surface-enhanced Raman scattering effects).9 Methods of nanosphere lithography used for nanofabrication differ as a function of the desired products. Metallic nanodots and nanoholes are, for instance, fabricated for localized surface plasmon resonance based sensors10,11 and functional polymeric patterns, to create bioactive material with nanoscale resolution.8 The ultimate challenge is to set up a reliable method to control the organization of colloidalparticle films on a surface, which is driven by the particle–particle and particles–surface interactions. In some applications, the interdistance between nanoparticles must be controlled.12,13 The absorption of colloidal particles on surfaces is performed by means of electrostatic or specific chemical forces. If needed, the surface electrostatic charge is modified chemically by a positively charged layer, and the organization of colloidal layers (i.e., the density and interdistance of nanobeads) depends upon the concentration of the particles in the colloidal suspension and the ionic strength of the electrolytic solution.14 When a well-ordered 2D crystal is used as a template for metal deposition over large areas, the efficiency of nanoparticle organization is often enhanced by using a surfactant to increase the wettability of the surface. For both types of organization, deposition techniques such as dip-coating, Langmuir–Blodgett, or spin-coating can be used and optimized deposition parameters are needed to accurately control the number of particle layers created in the film.
To create nanobioactive surfaces, that is, surfaces with chemical contrast at the nanoscale, the nanoparticles are usually deposited on a polymeric layer that already has the functionality needed in the final product. The first functional layer used as a contact surface during the nanobead depositions is preferably used as deposited. Indeed, any additional surfactant that could alter its chemical function must be avoided. The spin-coating technique is widely used for colloidal film formation because of the simplicity of its implementation. A microdrop of polystyrene (PS) colloidal particles suspension is deposited on the hydrophilic surface with the spin-coater off (contact angle with pristine PS beads suspension <40◦ ). The bulk volume of the drop is usually removed by a micropipette, in order to obtain a very thin layer of PS beads suspension on the surface. The sample is then spun at a determined speed in order to accumulate the liquid and the PS beads at the boundary of the drop, leaving a monolayer of PS beads in the center. The evaporation rate of the liquid has to be maintained low enough to allow the organization of the PS beads in a hexagonal crystal lattice. In this way, a large area in the range 500 × 500 µm2 of homogenous PS beads crystal can be deposited on the surface.
3 CHEMICAL NANOPATTERNS
The surface chemical nanopatterning strategy combines colloidal lithography with surface functionalization techniques. The steps involved in the process are illustrated in Figure 1. First a layer rich in carboxylic functionalities is deposited on the substrate and is then covered by a monolayer of crystalline PS nanosphere (Figure 1a); the use of PS nanospheres is recommended since they have a good monodispersity factor (<10%) and they can be easily chemically etched by an O2 plasma discharge. Moreover their surface chemistry can be adapted to the chemical properties of the surface in order to avoid the specific absorption of the spheres onto the surface. The postprocessing lift-off of the spheres can be done without using aggressive solvents, which could affect the stability of the carboxylic groups of the surface. The nanomask pattern is then transferred to the carboxylic surface by means of O2 plasma
CHEMICAL NANOPATTERNS FOR BIOSENSOR DESIGN
Antifouling deposition
O2 plasma
COOH
COOH COOH
3
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
(b)
(a)
Ultrasonic bath
COOH
COOH
COOH
(c)
(d)
Figure 1. Scheme of the nanopatterning technique: (a) Plasma etching of PS-nano mask and creation of COOH nanostructures. (b) Deposition of antifouling (passivation) layer. (c) Residual PS beads are removed by ultrasonic bath. (d) Final nanostructured surface.
etching (Figure 1b). In this way, the PS spheres are reduced in diameter and the uncovered carboxylic groups of the surface are etched away. The etching time is accurately controlled in order to avoid the complete etching of the spheres protecting certain areas covered by the carboxylic functionalities. The residual etched nanospheres are used as a mask for the passivation (antifouling) of the remaining area (Figure 1c). The final step involves the lift-off of the residual nanosphere mask by an ultrasonic treatment of the surfaces in ultrapure water. The spheres are easily stripped by the mechanical forces induced by the ultrasound because of their weak interaction with the surface, leaving some nanoareas of carboxylic
functionalities surrounded by the antifouling layer (Figure 1d). One of the advantages of this method is the compatibility with different surface functionalization techniques: both the carboxylic functionalized layer and the antifouling layer can be fabricated by plasma-enhanced chemical vapor deposition15,16 (PE-CVD) or by classical wet chemistry (SAMs). Such a high flexibility allows the creation of chemical nanopatterns on different substrates and with different morphological properties, for example, 3D or 2D chemical nanopatterns.a Two representative examples are shown in Figure 2: Figure 2(a) shows the 3D structured morphology of polyacrylic acid (PAA) nanodomes (carboxylic
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
100 nm 100 nm 400 nm
200 nm (a)
200 nm
(b)
Figure 2. (a) AFM picture of the 3D nanopatterned surface obtained by the combination of the nanosphere lithography and PE-CVD surface functionalization. (b) AFM picture of the 2D nanopatterned surface obtained by the combination of nanosphere lithography and SAM. The hexagonal 2D pattern is not clearly visible from the picture but it is clearly seen if we look at the Fourier Transform of the picture (inset). This pattern arises from the different heights of the MHD and the HDT molecules.
functional) surrounded by a polyethylene glycol–like (antifouling) matrix,8,17 while Figure 2(b) shows a SAM 2D patterned surface on gold constituted by 16-mercaptohexadodecanoic acid (MHD) nanospots surrounded by a hexadecanethiol (HDT) matrix.18 . In the first example, the functional polymer films are deposited from a monomer vapor fragmented using a glow discharge (PE-CVD). The plasma reactors used are generally capacitively coupled, owing to their simplicity, the low cost of fabrication, and the mild conditions produced, avoiding excessive precursor fragmentation.19 Plasma process parameters such as the working pressure, monomer flow, and the power forwarded to the discharge have to be controlled and optimized in order to minimize the monomer fragmentation in the plasma and to maintain high density of monomer functionality in the deposited films. In the second example, the most delicate step is the preparation of the gold surface for the HDT (or any other passivation layer) self-assembly: in this case the O2 plasma has the double role of removing the unmasked MHD SAM and preparing the surface for the HDT absorption. As proof of the concept, labeled bovine serum albumin (BSA) proteins were incubated on a 3D nanopatterned surface where the carboxylic groups of the acrylic acid were activated using classical 1-ethyl-3-(3-dimethylaminopropil) carbodiimide/ N-hydroxysuccinimide (EDC/NHS) chemistry. Fluorescence contrast is clearly observed in Figure 3, consistent with the selective immobilization of BSA on the COOH-terminated nanoareas
(Figure 3c). The size of the fluorescence spots is diffraction limited to ∼ 300 nm, indicating that the real size of the fluorescence features is smaller than this value, while the periodicity of the patterns is ∼ 500 nm; moreover the same hexagonal surface pattern is confirmed from the fast Fourier transform (FFT) of the fluorescent image (inset of Figure 3c). These results confirm the selective immobilization of biomolecules on the activated COOH nanoareas with respect to the antifouling matrix. As explained in the introduction of this chapter, the objective of the creation of such precise chemical nanopatterns is the surface densification of the recognition agents in the case of biosensing devices; one illustrative example is represented by the immunosensor, where the antibody is immobilized on a surface enabling the recognition of its antigen via the specific antibody–antigen reaction. In this case, the surface density of active “probes” is the surface density of antibodies immobilized with the antigen recognition sites available for the specific reaction (i.e., nondenatured). In order to compare the number of active antibodies immobilized on a nonstructured, COOHfunctionalized surface with respect to a 2D nanopatterned, COOH-functionalized surface,b a parallel enzyme-linked immunosorbent assay (ELISA) test has been performed. First a monoclonal antibody is immobilized on the surface. BSA is used in this case as a blocking agent for nonspecific absorption. Then, the sample is exposed to the antigen solution: only the antibodies correctly immobilized on the surface could recognize their antigen. A
CHEMICAL NANOPATTERNS FOR BIOSENSOR DESIGN
5
f-BSA
O
N
O
O
N
O
C O
C O
O
N
O
C
O
(a)
N
H
C O
(b)
300
200
100 (c)
(arb units)
Figure 3. (a) COOH activation by EDC/NHS protocol. (b) Fluorescently labeled BSA (f-BSA) is covalently bound to the surface via its amino groups. (c) Typical fluorescence map of f-BSA immobilized on PAA nanocraters, in the inset, the FFT of the image: the hexagonal crystalline structure is clearly visible.
biotinated antibody then serves as a specific linker to the avidinated enzyme that catalyzes the chemiluminescent reaction with trifluorobenzene (TFB). The signal intensity of the final blue color (at 670 nm) of the solution is proportional to the “recognized” antigens, and hence to the amount of reactive antibodies. The transmittance spectra for the ELISA test for the nonpatterned and the nanopatterned surfaces are shown in Figure 4(a). The 670-nm blue signal of the ELISA-exposed nanopatterned sample was four times larger than the nonpatterned one, evidencing a significant increase of the number of recognition agents. The morphology of the ELISA-exposed nanopatterns (Figure 4b) has a clear crystalline nature similar to the original chemical patterns as demonstrated by the FFT of the height function of the sample (Figure 4b inset). The height distribution of the clusters as measured by atomic force microscopy (AFM) is 54 ± 3 nm (n = 63) and is
consistent with a theoretical value for the sum of the heights of the proteins involved in the ELISA test. As an example, a height profile along a crystalline spots line is shown in Figure 4(c). The combination of the spectrometry results with the surface analysis on the ELISA test– exposed surfaces allows us to conclude that the nanopatterned surfaces are able to induce the immobilization of the antibodies (first step of the ELISA test) in such a way that the antibody–antigen reaction is more favorable than in the case of the nonpatterned ones.
4 OUTLOOK
Nanopatterning a surface at the nanoscale is a challenging task and is very promising for many fields of applications. Improving the capability of the functional surfaces to bind biomolecules
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS 350 nm
670 nm
100
MHD or HDT
Transmittance (%)
R R R R R R R R R R R R R
80 60 Nano MHD/HDT
40
R
R H H
H H H H
R H H H H
H H
20 0 300
(a)
400
500 600 Wavelength (nm)
700
800
1000
2000
70
Height (nm)
60 50 40 30 20 10 400 nm
0 0
(b)
(c)
3000
4000
5000
Position along the line (nm)
Figure 4. (a) Transmittance spectra for the solutions reacted with TFB for the nonpatterned and the nanopatterned samples. (b) AFM picture of the nanopatterned (COOH/antifouling) sample after the ELISA procedure (vertical scale: [0;106 nm]). The inset shows the FFT of the h(x, y) functions. (c) Height profile along the red line in Figure 3(a). The height of the spot (marked by red triangles) is calculated from the blue baseline.
in the active state, with a very low level of nonspecific absorption, is an enabling feature for the development of very sensitive devices that can be used as prescreening and early diagnostic tools. While nanopatterned biosensor surfaces are still the object of fundamental studies, interesting results are obtained in terms of selectivity and sensitivity of detection. Colloidal lithography is one of the techniques that can be implemented to produce these surfaces. It has many advantages such as low cost and parallel fabrication capability. Furthermore, this technique is compatible with classical surface functionalization techniques such as SAM and plasma deposition or functionalization. Nevertheless, compatibility with classical
sample preparation and handling systems still has to be implemented to realize the full potential of such nanodevices.
ACKNOWLEDGMENTS
This work has been supported by the NanoBioTech action of the Sixth Framework Program of the European Commission. The authors would like to acknowledge all the people involved in the NANOBIOTECH action, in particular: G. Ceccone, T. Sasaki, F. Bretagnol, and M. Lejeune, T. Meziani.
CHEMICAL NANOPATTERNS FOR BIOSENSOR DESIGN
The authors are especially grateful to M. GarciaParajo and A. Bouma (MESA+ Institute, The Netherlands) for the confocal microscopy measurements.
END NOTES a.
The pattern is considered 2D when the typical size of patterning in the plane of the surface is much greater than the height of the nanostructures. b. These experiments have been performed on the 2D chemical nanopatterns.
REFERENCES 1. N. L. Rosi and C. A. Mirkin, Nanostructures in biodiagnostics. Chemical Reviews, 2005, 105, 1547–1562. 2. J. P. Renault, A. Bernard, A. Bietsch, B. Michel, H. R. Bosshard, E. Delamarche, M. Kreiter, B. Hecht, and U. P. Wild, Fabricating arrays of single protein molecules on glass using microcontact printing. The Journal of Physical Chemistry. B, 2003, 107(3), 703–711. 3. D. Falconnet, D. Pasqui, S. Park, R. Eckert, H. Schift, J. Gobrecht, R. Barbucci, and M. Textor, A novel approach to produce protein nanopatterns by combining nanoimprint lithography and molecular self-assembly. Nano Letters, 2004, 4, 1909–1914. 4. K. B. Lee, S. J. Park, C. A. Mirkin, J. C. Smith, and M. Mrksich, Protein nanoarrays generated by dip-pen nanotithography. Science, 2002, 295, 1702–1705. 5. K. B. Lee, E. Y. Kim, C. A. Mirkin, and S. M. Wolinsky, The use of nanoarrays for highly sensitive and selective detection of human immunodeficiency virus type 1 in plasma. Nano Letters, 2004, 4, 1869–1872. 6. Y. S. Lee and M. Mrksich, Protein chips: from concept to practice. Trends in Biotechnology, 2002, 20, S14–S18. 7. H. Taha, R. S. Marks, L. A. Gheber, I. Rousso, J. Newman, C. Sukenik, and A. Lewis, Protein printing with an atomic force sensing nanofountainpen. Applied Physics Letters, 2003, 83, 1041–1043.
7
8. A. Valsesia, P. Colpo, M. M. Silvan, T. Meziani, G. Ceccone, and F. Rossi, Fabrication of nanostructured polymeric surfaces for biosensing devices. Nano Letters, 2004, 4, 1047–1050. 9. B. G. Prevo and O. D. Velev, Controlled, Rapid Deposition of Structured Coatings from Micro- and Nanoparticle Suspensions. Langmuir, 2004, 20, 2099–2107. 10. A. J. Haes, S. Zou, G. C. Schatz, and R. P. V. Duyne, Nanoscale optical biosensor: Short range distance dependence of the localized surface plasmon resonance of noble metal nanoparticles. Journal of Physical Chemistry B, 2004, 108, 6961–6968. 11. T. Rindzevicius, Y. Alaverdyan, A. Dahlin, F. Hook, D. S. Sutherland, and M. Kall, Plasmonic sensing characteristics of single nanometric holes. Nano Letters, 2005, 5(11), 2335–2339. 12. B. Kasemo, Biological surface science. Surface Science, 2002, 500, 656–677. 13. M. Arnold, E. A. Cavalcanti-Adam, R. Glass, J. Blummel, W. Eck, M. Kantlehner, H. Kessler, and J. P. Spatz, Activation of integrin function by nanopatterned adhesive interfaces. ChemPhysChem, 2004, 5, 383–388. 14. P. Hanarp, D. S. Sutherland, J. Gold, and B. Kasemo, Control of nanoparticle film structure for colloidal lithography. Colloids and Surfaces A, 2003, 214, 23–36. 15. F. Bretagnol, L. Ceriotti, M. Lejeune, A. PapadopoulouBouraoui, M. Hasiwa, D. Gilliland, G. Ceccone, P. Colpo, and F. Rossi, Functional micropatterned surfaces by combination of plasma polymerization and lift-off processes. Plasma Processes and Polymers, 2006, 3, 30–38. 16. A. Valsesia, M. M. Silvan, G. Ceccone, D. Gilliland, P. Colpo, and F. Rossi, Acid/base micropatterned devices for pH-dependent biosensors. Plasma Processes and Polymers, 2005, 2, 334–339. 17. A. Valsesia, P. Colpo, T. Meziani, F. Bretagnol, M. Lejeune, T. Meziani, F. Rossi, A. Bouma, and M. Garcia-Parajo, Selective immobilization of protein clusters on polymeric nanocraters. Advanced Functional Materials, 2006, 16(9), 1242–1246. 18. A. Valsesia, P. Colpo, P. Lisboa, M. Lejeune, T. Meziani, and F. Rossi, Immobilization of antibodies on biosensing devices by nanoarrayed self-assembled monolayers. Langmuir, 2006, 22(4), 1763–1767. 19. H. K. Yasuda. Plasma Polymerization, Academic Press, London, 1985.
48 Quantum Dots: Their Use in Biomedical Research and Clinical Diagnostics Stanley Abramowitz Advanced Technology Group, Silver Spring, MD, USA
1 INTRODUCTION
Quantum dots are most useful in both biomedical research and for in vitro and in vivo clinical diagnostics. Quantum dots are semiconductor nanocrystals with dimensions varying from 1 to 10 nm. Because of the small dimensions, the physicochemical properties of quantum dots are dependent on their size. This is because of a phenomenon known as quantum confinement. Briefly the energy levels for nanocrystals are a function of the size of the quantum dot. This results in the emission of photons with small bandwidth, relatively long lifetime (about 10 ns) and, equally important, symmetric bandwidth. This is a potentially large advantage over the use of organic fluorophore dyes, which typically have fluorescence bands with a red tail emission and short lifetimes relative to quantum dots. Also, properly coated quantum dots are much more photostable even in biological systems than the commonly available fluorophores. A complete discussion of the electrical, optical, and magnetic properties of quantum dots together with the theory that predicts these properties can be found in several articles.1–3 The wide use of quantum dots especially in research applications has been facilitated by the introduction of reliable and widely available technologies for the synthesis of quantum dots of reproducible size.4 The bulk of the use of
quantum dots in medical research and diagnostics is based on their optical properties. Other advantages of quantum dots in comparison with the more commonly available organic fluorophores include their large quantum yields; ability to excite a wide variety of sizes of quantum dots, with emission ranging from the visible to the near infrared with one laser frequency or light source; the symmetric and narrow emission band width; and longer fluorescence lifetimes.5 This obviates the need for fluorescence resonance enhancement transfer (FRET) dyes for multicolor labeling methodologies, as is used for labeling different parts of a cell and the four-color technology utilized in DNA analysis. The longer fluorescence lifetime permits the use of “gated detection technologies”, thereby helping to avoid the natural short-time fluorescence present in biomaterials including tissue.6 There are significant toxicology concerns when quantum dots are utilized for in vivo applications. There is a general concern for the toxicology of nanomaterials including quantum dots.7 The toxicology of particular quantum dots are determined by their chemical make up, the stability of the chemical coatings that provide the means to solubilize the quantum dots into a colloidal solution, and the functionalization provided for interfacing with the biological moieties to be measured.8 Typically a moiety is attached to the quantum dots for bonding to a variety of biological entities including DNA, proteins, antibodies, and so on. The toxicity
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
is dependent upon several factors including the metals comprising the quantum dot, the chemical in vivo stability of the coating, and functionalization. The quantum dot and its higher-band-gap covering and the chemical species attached for solubilization into a colloidal suspension and functionalization in order to target biospecies is often referred to as the quantum-dot conjugate. In this chapter we use the term quantum dot to refer to this species that is utilized in biomedical research and clinical diagnostics.
2 PREPARATION AND SOURCES OF QUANTUM DOTS
Quantum dots have many applications. This chapter is limited to the preparation and sources of quantum dots for biology research and clinical diagnostics. Quantum dots are typically made up of semiconductor metals such as cadmium, selenium, indium, and so on. These metals can be extremely toxic and it is necessary to coat the quantum dot with another higher-band-gap material such as ZnS in order to minimize the phenomenon called blinking. A typical quantum dot will have a core of CdSe and a coating of a few molecules of ZnS. This coating will mitigate a blinking phenomenon that occurs because of a loss of energy through crystal imperfections and thereby increase the quantum yield. The quantum dot will then be coated with a layer that will enable its functionalization for biological uses and will permit the “solubilization” of the quantum dots into a colloidal solution or suspension. Quantum dots can be synthesized by heating pyrophoric materials including Cd(CH3 )2 and elemental Se in trioctylphosphine oxide at temperatures of 250–350 ◦ C for 24 h followed by a precipitation step that is size selective. It has been recently shown that less onerous Cd-containing species can be used including CdO, Cd(OAc)2 , and CdCO3 . A more convenient sonically driven synthesis that yields quantum dots of similar optical and magnetic properties has been published.4 A summary of synthesis methodologies and citations to the thermally driven technologies can also be found in Ref. 4. This synthesis technology that utilizes sonic energy is more straightforward and simpler than the thermally driven methodologies and should be available to more laboratories.
The synthesized quantum dots are then coated with materials that enable its functionalization for biological use. These coatings include silica and other materials that can then be derivatized for attaching proteins, DNA, antibodies, and so on. Quantum dots that are coated and ready for biological use can be obtained from several companies including Invitrogen,9 Evident Technologies,10 and Crystalplex.11 Much information concerning the use of quantum dots for biological research and the development of diagnostics can be found at the websites of these companies.
3 PHYSICOCHEMICAL PROPERTIES OF QUANTUM DOTS
Quantum dots are nanocrystals of semiconductor materials in the size range of 1–10 nm. The optical properties of quantum dots are of particular interest to biological and medical research. Colloidal semiconductor quantum dots are single crystals whose size can be controlled by the synthesis conditions. The various processes used yield quantum dots of a particular size that have distinctive absorption and emission spectra. The emission spectrum of a particular quantum dot is size dependent and varies from the near-infrared through the visible spectrum. Basically the absorption of a photon with energy above the semiconductor band gap results in an exciton or electron–hole pair. Unlike the commonly used organic fluorophores, the emission has a narrow bandwidth, often about 20–25 nm; is symmetric; has longer lifetimes, greater than 10 ns; can be excited by a single laser wavelength or other light source; and does not require the use of FRET dyes. This is shown in Figures 1 and 2 that are taken from Ref. 5. The longer lifetime permits the use of timegated detection technologies. These properties have advantages over the commonly used fluorophores particularly with multicolor detection requirements, as is the case with some commonly utilized DNA sequence and resequencing applications. The nanocrystals are smaller than the Bohr exciton radius, which is typically about a few nanometers, and therefore the energy levels are quantized and related directly to the nanocrystal size, an effect commonly referred to as quantum containment. Surface defects in the quantum dot may lead to a blinking phenomenon and thereby,
QUANTUM DOTS IN BIOMEDICAL RESEARCH AND CLINICAL DIAGNOSTICS
3
Normal fluorescence
Normalized intensity
1 0.8 0.6 0.4
1771 400
(a)
500
600
700
1033
729 Wavelength (nm)
564
460
Figure 2. (a) Size- and material-dependent emission spectra of several surfactant-coated semiconductor nanocrystals in a variety of sizes. The blue series represents different sizes of CdSe nanocrystals (16) with diameters of 2.1, 2.4, 3.1, 3.6, and 4.6 nm (from right to left). The green series is of InP nanocrystals (26) with diameters of 3.0, 3.5, and 4.6 nm. The red series is of InAs nanocrystals (16) with diameters of 2.8, 3.6, 4.6, and 6.0 nm. (b) A true-color image of a series of silica-coated core (CdSe)-shell (ZnS or CdS) nanocrystal probes in aqueous buffer, all illuminated simultaneously with a handheld ultraviolet lamp.
1 Normalized intensity
(b)
0.2 0
0.8 0.6 0.4 0.2 0 400
(b)
(a)
500
600
700
dots and their useful lifetime in real biological systems including cells, cultures, and animals.
Wavelength (nm)
Figure 1. Excitation (dashed) and fluorescence (solid) spectra of (a) fluorescein and (b) a typical water-soluble nanocrystal (NC) sample in PBS. The fluorescein was excited at 476 nm and the NC at 355 nm. Excitation spectra were collected with detection at 550 nm (fluorescein) and 533 nm (NC) because of the difference in emission spectra. The nanocrystals have a much narrower emission (32 nm compared with 45 nm at half maximum and 67 nm compared with 100 nm at 10% maximum), no red tail, and a broad, continuous excitation spectrum. [Reprinted with permission from M. Bruchez Jr, et al., Semiconductor nanocrystals as fluorescent biological labels, Science, 1998, 281, 2013–2016. Copyright 1998 AAAS.]
a loss of quantum yield. Basically the absorption of a photon with energy above the semiconductor band gap results in an exciton or electron–hole pair. Blinking can be mitigated by covering the quantum dot with a few atomic layers of a material with a higher band gap. Hence the covering of CdSe with ZnS, and the common description of this quantum dot as CdSe/ZnS. It is possible, with suitable covering, to obtain quantum yields approaching 90%. This covering and the functionalization of the quantum dot for biological use markedly increase the photostability of quantum
4 TOXICOLOGY
Nanomaterials are being used as constituents of many commercial products including filters, catalysts, paints, cosmetics, microelectronics, drug delivery vehicles, and for biological and medical research as discussed in this chapter. Therefore there is a general concern for their toxic potential though their interaction with the environment and biological systems. This chapter is only be concerned with the toxicity of quantum dots as they pertain to biological research, clinical studies, and in vivo and in vitro diagnostics. There have been several studies concerning the toxicology of quantum dots as they pertain to living systems. This is not surprising since some of the more common constituents of quantum dots, for instance, cadmium and selenium, are quite poisonous and readily dissolve in biological fluids. When quantum dots are covered with a layer of a higher-energy-gap material and then covered with a suitable chemical to allow functionalization and solubilization of the quantum dot into a colloidal
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
suspension, they are not generally toxic as long as the coverings remain intact and do not allow bodily or biological fluids into the quantum-dot core. Also, as noted in the preceding text, the lifetimes of the quantum dots in biological media are sufficiently long to allow kinetic studies and the flow of at least the smaller quantum dots through the biological system studied. A summary of some of the more common methodologies for quantumdot solubilization and functionalization is given in Ref. 12. A recent, complete study of the effects of high doses of CdSe/ZnS polyethylene glycol silanized quantum dots has indicated that they have a minimal impact on cells and are very promising for in vivo applications.13
5 IMAGING
A review of the use of nanocrystals including quantum dots for biological detection is a very useful primer to the use of nanocrystals for a wide variety of biological applications.14 The breadth of the use of quantum dots for imaging can be illustrated by the following examples. Quantum dots are utilized for imaging in cells, tissues, and in living subjects. They have longer fluorescence life times in living subjects than the traditional fluorophores. A recent study of the fluorescence of quantum dots that have been designed to bind to the vasculature of human tumors in mice showed that the quantum dots were visible 20 min after injection and the fluorescence peaked at 6 h after injection, and the optical images clearly outlined the tumors showing that the quantum dots attached to the blood vessels growing in and around the tumors.15 Another recent paper describes a methodology that allows for the fabrication of self-illuminating quantum dots, thereby alleviating the need for separate light sources for stimulating fluorescence. The quantum-dot conjugates are prepared with a mutant of the bioluminescent protein Renilla reniformis luciferase. The conjugates emit long-wavelength bioluminescent light in cells, animals, and tissues and are suitable for in vivo imaging. The system has been demonstrated in mice, tissue in living mice, and cells.16 The use of quantum dots with suitable hydrodynamic diameters allows the passage of these quantum dots through the blood and lymphatic systems and they
can then be targeted to the moieties of interest. Recently quantum dots have been shown to be able to pass through the sequential lymph nodes and map the excavation (passing out of a fluid into the surrounding tissue) from the vasculature in a rat model. An InAs quantum dot with a ZnSe covering that was then coated with suitable coating for attachment to biological species of interest was utilized in this study. This quantum dot emits in the red region of the spectrum (750–920 nm), depending on the size of the InAs core.17 When injected into Xenopus embryos, the quantum dots were stable, nontoxic, cell autonomous, and slow to photobleach. These properties allowed the fluorescence to be followed through animal development to the tadpole stage allowing the study of embryogenesis.18 Semiconductor quantum dots have been used to label cancer markers such as Her2 and other cellular targets in living cells and pathology specimens. All the signals are specific for the intended targets and are reported to be brighter and considerably more photostable than the commonly available organic fluorophores. The use of quantum dots with different emission wavelengths targeted to different moieties in the cell has also been demonstrated.19 Quantum dots are also being utilized for immunolabeling of membrane proteins and cells.20
6 DIAGNOSTICS
Quantum dots have been used for in vitro diagnostics. Their use has several potential advantages for fluorescence technologies, including the possibility of exciting many emission wavelengths, depending on the size of the quantum dot, with one laser excitation frequency, narrow, and symmetric emission bands that may make analysis simpler in the case of multicolor analyses, photostability, and high quantum yield. Quantum dots are being utilized in Fluorescence In Situ Hybridization (FISH), DNA analysis, targeting a variety of components of cells, and so on. A recent review outlining the utility of quantum dots in the probing of human chromosomes and DNA discusses the advantages of quantum dots and the challenges that need to be overcome to make them commercially viable.21 Quantum dots have been used for FISH and molecular cytogenetics. They have been
QUANTUM DOTS IN BIOMEDICAL RESEARCH AND CLINICAL DIAGNOSTICS
applied to karyotyping and to spectral karyotyping. They have also been used to determine the number of gene copies and their distribution among the chromosomes. A recent paper compares the fluorescence from quantum dots and conventional organic fluorophores when utilized for these applications. These researchers found the quantum dots to be brighter and more photo stabile than the organic fluorophores.22 By using 10 intensity level and 6 colors, one can in principle encode for 1 million DNA or protein sequences. The quantum dots are embedded in beads and can be analyzed using flow cytometry.23 Another study showed the use of multiplexed single nuclear polymorphism (SNP) genotyping using Qbead semiconductor quantum dots to code microspheres that are utilized in multiplex assays. By the use of combination mixtures of quantum dots with varying emission wavelengths, one can create useful spectral bar codes for complex DNA analysis.24 There are several diagnostic companies, including Ventana, that are investigating the possibility of incorporating quantum-dot technology into their diagnostic platforms for anatomic pathology and cytology applications.25 Quantum dots are especially useful where multicolor emission from several sites either within a tissue cell or diagnostic such as four-color DNA analysis are required. They have been used in the ParAllele analysis for phenotyping. Over 20 000 SNPs can be determined within a single assay. This is an inventive and efficient technology for the determination of a large number, up to 20 000, of SNPs in a single tube assay. The last step of the assay is the identification of a single DNA base that is assayed via a four-color assay. The targets are analyzed on an Affymetrix DNA array using quantum dots for the four-color assay. The advantages of this are the ability to efficiently excite the four colors corresponding to the four nucleotides with one laser frequency and the resultant emissions from the four bases to which the quantum dots are attached. The resultant emission bands are narrow and symmetric. This technology is scalable. At present 20 000 SNPs are analyzed via 4 probes for each of the DNA bases. (While it is in principle possible to analyze the SNPs using two probes, Affymetrix has decided to analyze for all four bases.) There is still much more room on the DNA chip for more probes to afford analysis of more than 20 000 SNPs. A discussion of this technology can be found at the Affymetrix
5
website26 and in recent archival publications.27,28 Affymetrix, which is marketing this assay, is also working collaboratively with others on other DNA assays that may eventually be available as “offthe-shelf” DNA arrays that utilize quantum dots because of the advantages previously discussed. To my knowledge, the ParAllele DNA array that is available from Affymetrix is the only “offthe-shelf” commercial product utilizing quantum dots for in vitro clinical diagnostics. One can obtain quantum dots that are suitable for many of the applications discussed from quantum-dot suppliers.9–11
7 CONCLUSIONS
Quantum dots have great utility in the areas of biomedical research and clinical diagnostics. They are also being utilized for biosensors that can monitor REDOX reactions for both in vivo and in vitro applications.29 This discussion of nanocrystals has been limited to quantum dots that have been functionalized for use in biomedical and diagnostic applications. It should be noted that other nanocrystals are also finding utility in these areas as well as other biomedical applications including drug delivery. Of special interest is a colloidal suspension of nanocrystal gold that has been utilized for several applications including DNA detection and imaging.14,30 The National Cancer Institute of NIH maintains an excellent website that monitors the current literature in the biomedical and clinical uses of nanocrystals including quantum dots.31 This website has abstracts of articles on the biomedical research and clinical uses of nanocrystals. Reports are posted weekly, and archives dating back to 2004 can be accessed. An excellent review of the potential and realized uses of nanocrystals, including quantum dots, can be found in Refs 12 and 14.
REFERENCES 1. A. P. Alivisatos, Semiconductor clusters, nanocrystals, and quantum dots. Science, 1996, 271, 933–937. 2. Al. L. Efros and M. Rosen, The electronic structure of semiconductor nanocrystals. Annual Review of Materials Science, 2000, 30, 475–421.
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
3. M. Nirmal and L. Brus, Luminescence photophysics in semiconductor nanocrystals. Accounts of Chemical Research, 1999, 32, 407–414. 4. M. J. Murcia, D. L. Shaw, H. Woodruff, C. A. Naumann, B. A. Young, and E. C. Long, Facile sonochemical synthesis of highly luminescent ZnS-shelled CdSe quantum dots. Chemistry of Materials, 2006, 18, 2219–2225. 5. M. Bruchez Jr, M. Moronne, P. Gin, S. Weiss, and A. P. Alivisatos, Semiconductor nanocrystals as fluorescent biological labels, Science, 1998, 281, 2013–2016. 6. M. Dahan, T. Laurence, F. Pinaud, D. S. Chemla, A. P. Alivisatos, M. Sauer, and S. Weiss, Time gated biological imaging by use of colloidal quantum dots. Optics Letters, 2001, 26, 825–827. 7. A. Nei, T. Xia, L. Madler, and N. Li, Toxic potential of materials at the nanolevel. Science, 2006, 311, 622–627. 8. R. Hardman, A toxicologic review of quantum dots: toxicity depends on physicochemical and environmental factors. Environmental Health Perspectives, 2006, 114, 165–172. 9. www.invitrogen.com/products/qdot/. 10. www.evident.tech.com. 11. www.crystalplex.com. 12. X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, Quantum dots for live cells, in vivo imaging, and diagnostics. Science, 2005, 307, 538–544. 13. T. Zhang, J. L. Stilwell, D. Gerion, L. Ding, O. Elboudwarej, P. A. Cooke, J. W. Gray, A. P. Alivisatos, and F. F. Chen, Cellular effect of high doses of silica-coated quantum dot profiled with high throughput gene expression analysis and high content cellomics measurements. Nano Letters, 2006, 6, 800–808. 14. A. P. Alivisatos, The use of nanocrystals in biological detection. Nature Biotechnology, 2004, 22, 46–52. 15. W. Cai, D.-W. Shin, K. Chen, O. Gheysens, Q. Cao, S. X. Wang, S. S. Gambhir, and X. Chen, Peptide-labeled nearinfrared quantum dots for imaging tumor vasculature in living subjects. Nano Letters, 2006, 6, 669–676. 16. M.-K. So, C. Xu, A. M. Loening, S. S. Gambhir, and J. Rao, Self-illuminating quantum dot conjugates for In vivo imaging. Nature Biotechnology, 2006, 24, 339–343. 17. J. P. Zimmer, S. W. Kim, S. Ohnishi, E. Tanaka, J. V. Frangioni, and M. G. Bawendi, Size series of small indium arsenide-zinc selenide core-shell nanocrystals and their application to in vivo imaging. Journal of the American Chemical Society, 2006, 128, 2526–2527. 18. B. Dubertret, P. Skourides, D. J. Norris, V. Noireaux, A. H. Brivanlou, and A. Libchaber, In vivo imaging of quantum dots encapsulated in phospholipid micelles. Science, 2002, 298, 1759–1762.
19. X. Wu, H. Liu, J. Liu, K. N. Haley, J. A. Treadway, J. P. Larson, N. Ge, F. Peale, and M. P. Bruchez, Immunofluorescent labeling of cancer marker Her2 and other cellular targets with semiconductor quantum dots. Nature Biotechnology, 2003, 21, 41–46. 20. A. Sukhanova, J. Devy, L. Venteo, H. Kaplan, M. Artemyev, V. Oleinikov, D. Klinov, M. Pluot, H. M. Cohen, and I. Nabiev, Biocompatible fluorescent nanocrystals for immunolabeling of membrane protein and cells. Analytical Biochemistry, 2004, 324, 60–67. 21. Y. Xia and P. E. Barker, Semiconductor nanocrystal probes for human chromosomes and DNA. Minerva Biotecnologica, 2006, 16, 281–288. 22. Y. Xiao and P. E. Barker, Semiconductor nanocrystal probes for human metaphase chromosomes. Nucleic Acids Research, 2004, 32, e28. 23. M. Han, X. Gao, J. Z. Su, and S. Nie, Quantum dot tagged microbeads for multiplexed optical coding of biomolecules. Nature Biotechnology, 2001, 19, 631–635. 24. H. Xu, M. Y. Sha, E. Y. Wong, J. Uphoff, Y. Xu, J. A. Treadway, A. Truong, E. O’Brien, S. Asquith, M. Stubbins, N. K. Spurr, E. H. Lai, and W. Mahoney, Multiplexed SNP genotyping using Qbead system: a quantum dot-encoded microsphere-based assay. Nucleic Acids Research, 2003, 31, e43. 25. www.ventanamed.com. 26. www.affymetrix.com/technology/mip technology.affx. 27. P. Hardenbol, J. Baner, M. Jain, M. Nilsson, E. A. Namsaraev, G. A. Karlin-Neumann, H. H. Fakrai-Rad, M. Ronaghi, T. D. Willis, U. Landegren, and R. W. Davis, Multiplexed genotyping with sequence-tagged molecular inversion probes. Nature Biotechnology, 2003, 21, 673–678. 28. P. Hardenbol, F. Yu, J. Belmont, J. MacKenzie, C. Bruckner, T. Brudage, A. Boudreau, S. Chow, J. Eberle, A. Erbilgin, M. Falkowski, R. Fitzgerald, S. Ghose, O. Lartchouk, M. Jain, G. Karlin-Neumann, X. Lu, X. Miao, B. Moore, M. Moorhead, E. Namsaraev, S. Paternak, E. Prakash, K. Tran, Z. Wang, H. B. Jones, R. W. Davis, T. D. Willis, and R. A. Gibbs, Highly multiplexed molecular inversion probe genotyping: over 10,000 SNPs genotyped in a single tube assay. Genome Research, 2005, 15, 269–275. 29. S. J. Clarke, C. A. Hollman, Z. Zhang, S. E. Bradford, N. M. Dimitrijevic, W. G. Minarik, and J. L. Naudeau, Photophysics of dopamine-modified quantum dots and effects on biological systems. Nature Materials, 2006, 5, 409–417. 30. R. Elghanian, J. J. Storhoff, R. C. Mucic, R. L. Letsinger, and C. A. Mirkin, Selective colorimetric detection of polynucleotides based on the distance-dependent optical properties of gold nanoparticles. Science, 1997, 277, 1078–1081. 31. http:nano.cancer.gov/news center/anaotech news.asp.
49 Manipulation and Detection of Magnetic Nanoparticles for Diagnostic Applications Benjamin B. Yellen and Randall M. Erb Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA
1 INTRODUCTION
Over the last few decades, the field of biosensors and biochips has flourished due to increasing applications in DNA and pathogen detection, clinical diagnostics, and the analysis of various biological and chemical materials.1,2 Developing these micro total analysis systems (µTAS)3 has required multidisciplinary collaboration between physicists, chemists, biologists, and engineers to accomplish various tasks; including integrating the microfluidics, immobilizing molecules on various surfaces, and detecting and manipulating desired components inside the fluid. A great deal of work has already been done on the microfluidics, leading to a diverse array of technologies4,5 related to sample preparation, sample injection, reaction, separation, and detection.6,7 In tandem, significant advances in material science has allowed for the development of stable monodisperse colloidal particles, which serve as an ideal candidate for loading sensor molecules onto mobile supports due to their high surface area-to-volume ratio. Strategies for the preparation of polymer and metal-based colloidal particles are provided in several recent review papers.8–11 Significant work has also been conducted on synthesizing particles that emit a detectable signal through the incorporation of an optical, electrical, or magnetic material into the
particles.8,10–14 This feature allows for the positions of the particle to be detected by an array of sensors. In comparison with optical and electrical detection schemes, magnetic detection systems tend to be highly sensitive, inexpensive, and compatible with most lab-on-a-chip applications.15–22 Magnetic particles offer an additional advantage in that they can be manipulated by external magnets and transported to desired locations independently of other species inside the fluid. Although other approaches based on optical and electrical field manipulation also have the potential for dual functionality, the relative transparency of most biological materials to magnetic fields makes magnetism uniquely adapted for diagnostic and biomedical applications. Here, the focus is to review recent work on magnetic detection and manipulation systems, and the mention of alternative approaches based on electric or optical fields is used only for comparison purposes. This paper is organized as follows. First, we review the basic principles governing magnetization in nanostructures and outline the types of magnetic materials used in biomedical applications. On the basis of this discussion, the criteria for manipulating magnetic particles in a fluidic system and its general scaling principles are outlined. Next, we present recent work on magnetic
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
as the coercive field, Hc , also frequently called the coercivity. There are several classes of magnetic materials, each of which is defined by common hysteretic traits. For the sake of simplicity, this discussion covers only the three most prominent groups, namely ferromagnetic, superparamagnetic, and diamagnetic materials. Ferromagnetism is a state describing materials that have some remaining magnetization after the external field is removed (i.e., they have magnetic remanence). This class of materials is known to exhibit hysteresis, which is a term implying that the material’s magnetization is not uniquely defined by the strength and direction of the applied field, but it also depends on the history of past exposure to a magnetic field. A typical hysteresis curve for ferromagnetic materials is provided in Figure 1(a). A second class of materials, known as superparamagnetic, retains zero magnetization in the absence of external fields (i.e., no hysteresis). Owing to this behavior, the magnetization within superparamagnetic materials traces and retraces the same path on the hysteresis loop, which implies that its magnetization is not history dependent and is based solely on the strength and direction of the present external field, as shown in Figure 1(b). A third class of materials, known as diamagnetic, exhibits peculiar behavior in that the material’s magnetization opposes the applied field. An example of a diamagnetic hysteresis loop is shown in Figure 1(c). Although the vast majority of biological materials (water, proteins, etc.) display slightly diamagnetic
sensors used in biological detection, and outline the basic types of sensors used in magnetic assays as well as the principle of operation for the most commonly used variety, known as spin valves. Finally, this paper concludes with a discussion on the future outlook in the field of magnetic biosensors and biochips and a general comparison of magnetic versus optical and electrical strategies for manipulating and detecting biological materials.
2 MAGNETIZATION BEHAVIOR OF NANOSTRUCTURED MAGNETIC MATERIALS
To familiarize the reader with terms commonly found in magnetic material descriptions, this section begins with a discussion of how the magnetization M of a material relates to the external magnetic field, H . The magnetization behavior is typically depicted by a hysteresis loop, like those shown in Figure 1. Magnetic saturation, Ms , is a parameter, which characterizes the strength of a material’s magnetization when all of its atomic spins are aligned with an external field. In this state, the material is magnetized to the point of saturation. When the external field is removed, any remaining magnetization is defined as the magnetic remanence, Mr . In materials that have magnetic remanence, opposing fields must be applied to decrease the material’s remanent magnetization to zero. The critical field strength required to reverse the material’s magnetization is defined
M Mr
M
M
Ms
Hc H
(a)
H
(b)
H
(c)
Figure 1. Characteristic hysteresis loops for (a) ferromagnetic, (b) superparamagnetic, and (c) diamagnetic materials.
MAGNETIC NANOPARTICLES FOR DIAGNOSTIC APPLICATIONS
properties, this effect is considered to be weak compared with ferromagnetic and superparamagnetic behavior of magnetic materials (i.e., Fe, Co, Ni, rare earth materials, and various alloys), and hence diamagnetic effects are often ignored in theoretical treatment. With sufficient time, the magnetization within all magnetic materials will eventually relax to zero under the influence of randomizing thermal fluctuations. The rate at which the particle’s magnetization relaxes is related to an energy barrier, E, with respect to its equilibrium state, as given by: τ −1 = f0 e−E/kB T , where τ is the corresponding relaxation time constant. For materials displaying uniaxial anisotropy, the energy barrier is simply the product of the material’s volume with its magnetic anisotropy constant: E = KV . The valuef0 has been determined experimentally to vary between 109 and 1013 s−1 ;23 however, exact knowledge of the matching constant is not so crucial, since the exponential function dominates the behavior of the time constant. As an example, consider the behavior of a spherical iron nanoparticle with an anisotropy constant 10−6 erg cm−3 and with the following parameters (f0 = 109 s−1 , T = 298 K), the magnetization within the material is predicted to survive for 0.1 ms for a particle with 10-nm diameter as compared to 109 s for a particle with 15-nm diameter. This analysis explains why <10-nm magnetic nanoparticles are the preferred magnetic material for biomedical applications. Below this critical size of roughly 10 nm, the particles become effectively superparamagnetic. The advantage of using superparamagnetic particles is that they readily respond to an applied magnetic field, yet the particles can be turned off when the external field is removed (i.e., they do not irreversibly agglomerate because they lack remanent magnetization). In practice, the material is considered to be ferromagnetic if the remnant magnetization lasts longer than the experiment time (i.e., on the order of a few seconds). Magnetizations that relax more quickly are considered to be superparamagnetic because of the fact that their magnetization behaves more like a “super” large paramagnetic spin. Most often, the threshold of E = KV ≈ 25kB T is taken as the limit for superparamagnetism.24 Below this limit, the timeaveraged magnetization within an individual particle is described by the well-known Langevin’s
3
function: H ) M(
µ0 Ms V H H kB T |H | µ0 Ms V H kB T H − = Ms coth kB T µ0 Ms V H |H |
= Ms L
(1) An approximation can be obtained in the lowfield regime (µ0 Ms V H kB T ) by using the Taylor series expansion of coth(η) ≈ (1)/(η) + (η)/(3) + . . ., which results in the particle’s magnetization reducing to a linear relationship with the H ) = (µ0 Ms 2 V )/(3kB T )H = applied field as: M( χ H , where the magnetic susceptibility χ = (µ0 V Ms 2 )/(3kB T ) is an experimentally determined parameter. In the high-field regime (µ0 Ms V H kB T ), the particle’s magnetization saturates according to the relationship: 1 − (kB T )/(µ0 Ms V H ). However, this circumstance is only reached in magnetic fields approaching 0.1 T.
3 MAGNETIC PARTICLES USED IN DIAGNOSTIC APPLICATIONS
Biomedical devices commonly employ magnetic particles for both in vivo and in vitro applications. In vivo applications encompass drug targeting, hyperthermia, and magnetic resonance imaging, while in vitro applications include separation/manipulation, detection, and magnetorelaxometry.25 For these various applications, care should be taken to select the proper type of magnetic particles. Superparamagnetic particles come in two varieties: surfactant-stabilized ferrofluid and polymer-based micro/nanospheres. The key ingredient in both types of particles is nanoscale magnetic grains having dimensions tailored to promote a superparamagnetic response. Ferrofluid is a stabilized dispersion of superparamagnetic grains inside carrier fluids, such as water or hydrocarbonbased liquids.26,27 The method for stabilizing these particles involves attaching long polymer chains or charge carrying molecules to the particle surfaces. These molecules induce repulsive electrostatic or steric interactions, which are used to overcome
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
short-range attractive forces as well as attractive magnetic interactions, thereby allowing the particles to remain colloidally stable. Polymer-based magnetic micro/nanospheres are formed by incorporating superparamagnetic grains into the particle matrix during microsphere formation. A number of techniques have already been developed for synthesizing microspheres from various biodegradable and nonbiodegradable polymers.28,29 In most cases, the loading fraction of magnetic material within the microspheres is kept below 30% in order to preserve its superparamagnetic behavior by reducing magnetic interactions between the grains. Using straightforward surface modification techniques, functional groups can be attached to the particle’s surface. These functional groups can be tailored to recognize specific proteins, DNA, and other biological substances through molecular affinity binding. The advantage of using magnetic microspheres is that the collective magnetic moment of the particle can be substantially increased due to the presence of a large number of encapsulated magnetic grains. Since magnetic force is proportional to the particle’s magnetic moment, which in turn is dependent on the particle’s volume, >100-nm magnetic particles are the preferred choice for biological separation.
4 MAGNETIC MANIPULATION SYSTEMS AND GENERAL SCALING PRINCIPLES
The aim of this section is to review recent progress on techniques used to manipulate superparamagnetic particles. First, the physical origin of magnetic forces on colloidal particles is provided, and it is followed by an overview of the types of magnetic field sources commonly employed in microsystems. The purpose of this discussion is to provide general design criteria for when a particle’s motion is dominated by magnetic force as opposed to random Brownian motion. Similar to the electrostatic treatment of polarizable materials, the net force on a superparamagnetic particle can be viewed as the force acting on equivalent magnetic charges distributed on the particle’s surface. These charges arise because of p the difference in the particle’s magnetization M with respect to the magnetization of the surround f . The equivalent surface charge density ing fluid M
f ), where p − M n is a is represented by: σ = n · (M unit vector normal to the particle surface, leading to an expression for the net magnetic force as: F = µ0 σ H · dS Sp
p − M f )H · ndS = µ0 (M
(2)
Sp
where H is the magnetic field at the location of the particle’s surface, Sp . In applying Gauss’s divergence theorem, (1) can be rewritten as: p − M f ) · ∇)H dV ((M F = µ0 Vp
p − m f ) · ∇)H = µ0 ((m
(3)
where m p and m f are the magnetic moments of the particle and of the fluid volume that the particle displaces. The most important conclusion that can be reached on the basis of the above expression is that the force is proportional to the field gradient, and it is simple to show that uniform magnetic fields will apply zero net magnetic force on a magnetic particle. Another conclusion that can be drawn from expression (3) is that both magnetic and nonmagnetic materials can be manipulated by magnetic force if a fluid of suitable magnetic susceptibility is chosen. Take, for example, a magnetic particle p = 0) that is situated inside a nonmagnetic car(M f ≈ 0). In this case, the rier fluid, such as water (M force on the particle is simply a product of the particle’s moment and the field gradient. A variety of systems currently employ this methodology in the field of magnetic separation.30,31 If, on the other hand, the fluid contains a suspension of magnetic nanoparticles (i.e., ferrofluid), which are magnetized by an external field, then the average fluid f = 0), thereby magnetization becomes nonzero (M p = 0), allowing even a nonmagnetic particle (M which is placed inside the fluid, to acquire an effective net magnetic moment and be manipulated by field gradients. The latter phenomenon can be thought of as “negative magnetophoresis” as a corollary to the phenomenon of “negative dielectrophoresis”, which occurs when electric fields are
MAGNETIC NANOPARTICLES FOR DIAGNOSTIC APPLICATIONS
applied to manipulate weakly polar materials (e.g., plastic particles) immersed inside strongly polarized fluids (e.g., water). In the literature, this class of fluids is often called inverse ferrofluids, and work is ongoing on the design of manipulation systems around this effect.32,33 In the following analysis, it will be assumed that the particles are spherical and superparamagnetic, so that its magnetic dipole moment can be related linearly with the applied magnetic field. The dipole moment is given by: m = χ¯ Vp H , where χ¯ = (3(χp − χf ))/(3 + χp + 2χf ) is a term denoting the effective susceptibility of the particle, and it includes both a shape factor, which accounts for demagnetizing fields within the spherical particle,34 as well as the difference in the particle’s susceptibility χp with respect to the susceptibility of the surrounding fluid χf . It is worth mentioning that if the particle’s susceptibility is larger than that of the fluid (i.e., χp > χf ), then the particle’s moment is aligned parallel to the field and it will migrate toward the regions of magnetic field maxima. On the other hand, if the particle’s susceptibility is less than that of the fluid (i.e., χp < χf ), then the particle’s moment is aligned antiparallel with the field and it will migrate toward the regions of magnetic field minima. It is a simple matter to demonstrate that the effective magnetic susceptibility for a spherical particle ranges within −3/2 ≤ χ ≤ 3. A variety of different magnetic field sources have been used to manipulate colloidal particles. Some are based on current sources, while others are based on the fields produced by magnetic materials, such as permanent or magnetizable magnets. It turns out that the most important feature for manipulating colloidal particles is not the type of source but rather its geometry. As a general rule, the field gradient varies inversely with the smallest dimension of the field producing structure. However, both large and small magnetic sources can play a significant role in microfluidic manipulation. Small magnetic sources have the advantage of producing stronger magnetic field gradients, but the field gradients are highly localized and, thus, can only manipulate particles in close proximity to the source. On the other hand, large magnetic structures produce weaker magnetic field gradients; however their fields and field gradients have the advantage of extending further into the fluid.
5
With this concept in mind, the following discussion attempts to outline the types of magnetic field sources used in micromanipulation and how their fields and field gradients decay with distance from the source. Magnetic field–versus-distance relationships can be obtained for several different field producing geometries. For example, a semi-infinite current line produces fields that decay inversely with the first power of distance from the source (i.e., H (r ) ∝ r −1 , (∂/(∂r)H (r ) ∝ r −2 ). This geometry has previously been used by several authors for manipulating magnetic particles, cells, and other materials suspended in fluids.35,36 The edges of a large domain wall within a magnetic thin film, such as in iron garnet films,37 also produce magnetic fields that decay inversely with the first power of distance from the source. The field produced by long wires magnetized perpendicularly to their long axes decays inversely with the square of distance away from the wire center (i.e., H (r ) ∝ r −2 , ∂/∂rH (r ) ∝ r −3 ). This type of structure has found applications in magnetic separation38 and drug delivery.39 The magnetic field also decays inversely with the square of distance away from one pole of a long-axially magnetized wire. Tightly wound current loops produce a magnetic field that decays inversely with the cube of distance from the source (i.e., H (r ) ∝ r −3 , (∂)/(∂r)H (r ) ∝ r −4 ). A similar type of field is produced by neighboring magnetic particles inside the fluid or by lithographically patterned small magnetic dots.40,41 Taking cues from the high-gradient magnetic separation (HGMS) community, multiple magnetic field sources are commonly used in magnetic manipulation systems.38,39 This approach is taken because fundamental physics indicates that a single source of magnetic field cannot simultaneously produce strong fields and strong field gradients everywhere in space. The reason strong fields are also needed is that the moment of a superparamagnetic particle is proportional to the strength of the applied field. Since the field effectively contributes twice in the force equation (i.e., the force is the product of the magnetic moment and the field gradient), a common practice is to use at least two different types of magnetic field sources in colloidal manipulation: one source is typically a large magnet, which produces long-range fields for saturating the moments of all the particles in the fluid, while the other source is typically a small
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
structure, which is used to supply strong local field gradients for attracting the particles. By combining the two types of sources, the particle moments and the field gradients are maximized and the effective reach of the magnetic manipulation system can be extended much further into the fluid. An additional advantage to the two-source method is that programmable operations can be performed on particles inside the fluid when used in combination with programmable magnets such as those found in magnetic data storage substrates. In this approach, long-range fields can be used to bias the moment of the particle in either repulsive or attractive configurations with respect to the underlying magnetization pattern of the substrate. This phenomenon has been used to program the fluidic deposition of colloidal materials onto preselected sites on a substrate.40 Fluid drag and magnetic force are the basis for a class of magnetic manipulation models that are founded on modeling particle trajectories. The most typical approach is to ignore particle inertia (any particle acceleration happens over timescales that are minuscule compared to the timescale of particle movement) and to obtain particle velocity by equating the magnetic force in (3) with the Stoke’s drag force: Fdrag = 3πηd · v, where d is the diameter of the particle, v is the particle’s velocity, and η is the viscosity of the fluid. The time for a particle to reach the surface of the magnet Smag from a given starting position X, therefore becomes: Fmag ∂x v = = ∂t 3πηd
X t=
3πηd ∂x Fmag
(4)
Smag
In the literature, one often finds statements that Brownian motion becomes an important concern for particles smaller than about 100 nm. Strictly speaking, such a general statement is invalid. A more accurate, although still approximate, criterion can be derived for when particle movement can be described in terms of deterministic trajectories as opposed to those based on random Brownian motion. This criterion is based on the idea that random deviation from a point on the trajectory by more than one particle diameter d should be unlikely. For magnetic manipulation, the likelihood of such deviation is small if the corresponding change of the particle’s magnetic energy
during movement exceeds kB T . Assuming that the magnetic force on the particle does not change appreciably as the particle moves within a sphere of diameter d, the change in magnetic energy is approximately equal to the magnetic force times d. To get a feeling for the criteria mentioned in the preceding text, suppose that the force on a particle is being applied by a spherical magnet of diameter D, with magnetization M0 . If we assume the particle is magnetized by an externally applied field, H0 , then the force on the particle is given by the expression: Fmag · d =
¯ 0 M0 4 D 4 6µ0 π 2 χH d 4 ≈ kB T (5) 4π 6 D R
From the above expression, it is clear that when the particle is located very far from the magnet (i.e., R D), it experiences little magnetic force, and therefore random Brownian motion will certainly dominate. Let us, therefore, concentrate on some critical region surrounding the magnet, say R = 10D, where D is again the characteristic dimension of the permanent magnet. In the following analysis, we will use the magnetic particle properties (χ¯ ≈ 1), an applied bias field of H0 ≈ 1 kOe, and assume that the magnetization of the spherical magnet is M0 ≈ 10 kOe, all of which are common parameters in magnetic manipulation systems. When the characteristic size of the magnet is of the order of 1 µm, the above criterion implies that particles greater than 250 nm move along reasonably well-defined trajectories when they are closer than about 10 µm away from the magnet. Brownian motion dominates the trajectory for particles below this size or when the distance from the magnet is greater. In these cases, it is better to describe particle motion in terms of distribution functions, such as particle concentration. Clearly, 100-nm particle diameter is not some magical size below which particles cannot be manipulated. In fact, it is not difficult to show that even 50-nm particles can be manipulated along well-defined trajectories when they are within with about 2 diameters of the gradient-producing spherical magnet (i.e., R = 2D). This analysis implies that it is the size ratio between the particle and the magnetic manipulator that is the important criteria. Smaller particles can be manipulated without much regard for Brownian motion when the characteristic size of the gradient-producing magnet
MAGNETIC NANOPARTICLES FOR DIAGNOSTIC APPLICATIONS
is also reduced. This finding provides additional motivation for using microfabrication technology, typically employed to create integrated circuits and microelectromechanical systems (MEMS), to miniaturize particle handling systems. For particles below the critical threshold, detailed trajectory analysis is no longer meaningful and random Brownian motion dominates particle movement. Problems of this type occur in many other areas of fluid physics. The common feature of all these approaches is the use of particle distribution functions, which are usually interpreted in term of the probability of finding a particle within some finite region of space–time. The effect of Brownian motion on concentration is usually described by the diffusion flux density: Jdiff = −D∇C(r , t) where D is the diffusion coefficient and C(r , t) is the particle concentration. The effects of nonrandom particle motion can be incorporated through the average particle velocity vp and the resulting drift flux density of particles is: Jdrift = vp C(r , t). The sum of the diffusion and drift flux densities constitutes the total particle flux density: J = Jdrift + Jdiff . Evolution of the concentration can now be obtained through the conservation law: ∂C ∂C + ∇ · J = 0 or ∂t ∂t = −∇ · (Jdiff + Jdrift ) = ∇ · (D∇C(r , t)) − ∇ · ( vp C(r , t)) (6) Initial work along this direction was performed recently42 and relatively simple analytical solutions were obtained for simple problems concerning the magnetic manipulation of ferrofluids.
5 MAGNETIC DETECTION SYSTEMS USED IN BIOSENSORS
Progress in magnetic biosensors has been driven by recent advances in techniques for fabricating and retrieving signals from miniature magnetic field sensors, which is a topic of great interest in magnetic disk drive technology. Leveraging past work in this field, magnetic field sensors have recently been adapted to detect binding
7
of molecules onto a substrate. The basic sensing device consists of a magnetic field sensor, whose surface is chemically functionalized with probe molecules for recognizing target molecules of interest (i.e., bacteria, nucleic acids, proteins, viruses, cells, etc.). In the simplest case, the biomolecules to be detected (i.e., target molecules) are immobilized onto magnetic particles and they are subsequently exposed to an array of magnetic sensors, which are functionalized with either complementary or noncomplementary probe molecules. After sufficient time is provided for the magnetic labels to interact with the sensors through specific molecular recognition, the remaining magnetic labels are rinsed from the solution. Because magnetic labels are superparamagnetic, an external magnetic field is needed to magnetize the particles. A positive binding signal is therefore indicated by the perturbation of the external field signal by the stray dipole fields emanating from the magnetic label. An illustration of the general sensing mechanism is provided in Figure 2. A variety of different sensors have been employed in biological detection. Low-field magnetic sensors, such as superconducting quantum interference devices (SQUID),43 fluxgate magnetometers,44 and induction coils, have previously been used in medical imaging, however owing to their large size they are not often employed in magnetic biosensors. Instead, the focus has been on solid-state magnetic field sensors which are amenable to batch fabrication techniques. The most common solid-state sensors used in magnetic biodetection are based on the Hall effect15 or on the magnetoresistive effect, such as anisotropic magnetoresistance (AMR),16 giant magnetoresistance (GMR)17–20,22 or the planar Hall effect (PHE).21 Although work is ongoing on the development of more sensitive cantilever-based sensors45 and atomic magnetometers,46 these developments will not be discussed in detail since the aim of this section is simply to outline the basic sensing mechanism used in magnetic biosensors. For this reason, the rest of this section is devoted to a discussion of GMR-based sensors, which to date are the most popularly employed device in magnetic biosensors. GMR sensors, often called spin valves, consist of two layers of ferromagnetic material separated by a nonmagnetic spacer layer. The sensors are
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS Target molecule
Magnetic label
Stray fields Uniform field
Substrate
Magnetic field sensor
Sensor probe molecules
Figure 2. Magnetic labels immobilized with target molecules are exposed to a magnetic field sensor. Through specific molecular recognition, the magnetic label binds selectively to the probe molecules on the surface of the magnetic field sensor. The target molecule’s presence is therefore detected by the stray fields the magnetic label produces in response to the uniform magnetizing field.
designed such that the magnetization of one layer is pinned by an antiferromagnetic layer, while the other layer’s magnetization is free to rotate in response to an external field. In the typical design, the pinned layer is initially set such that its magnetization makes a 90◦ angle with the free layer’s magnetization in the absence of external fields. The signal from the GMR sensor is sensitive to the sine of the angle between the pinned layer with respect to the free layer, and it is interpreted as a change in electrical resistance, R, through the sensor material. Hence, the key to predicting the sensor signal is in determining the relative angle between the two layers, which is accomplished by modeling the magnetic energy within the free layer47 as: U=
1 HK MF sin2 (φ) − H⊥ MF cos(φ) 2 − H MF sin(φ)
(7)
where MF is the magnetization of the free layer, 90◦ − φ is the relative angle between the magnetization of the free and pinned layers, and HK is the total anisotropy field in the free layer, which includes effects due to shape anisotropy and crystalline anisotropy; while H and H⊥ are the external fields acting on the free layer, oriented either parallel or perpendicular to the pinned layer,
respectively. These external fields may result from bias fields, the field from the magnetic particles, and any other intrinsic fields in the sensor, associated with the sense current, interlayer coupling, and magnetostatic fields due to the pinned layer. The equilibrium magnetization orientation within the spin valve is determined by minimizing the magnetostatic energy U of the free layer with respect to φ, which results in an approximate expression through the use of small angle approximation (φ < 25◦ ) as: sin(φ) ∼ = tanh
H H⊥ + HK
(8)
This approximation is reasonable because the tilting angle of the free layer is often less than 10◦ .48 The resistance in the spin valve can therefore be written as: R = R0 + (1)/(2)δR sin(φ), where R0 , is the resistance when the magnetizations of the free and pinned layers are perpendicular (i.e., φ = 0), while δR is the maximum possible change in resistance of the spin valve when the magnetization of the free and pinned layers are oriented antiparallel. The magnetoresistance ratio is defined as MR ≈ (δR)/(R0 ), and for a typical spin-valve sensor this ratio is of the order of 10%. Using (8), it is possible to write the change in resistance R due to the presence of a magnetic
MAGNETIC NANOPARTICLES FOR DIAGNOSTIC APPLICATIONS
particle as: R = Rwith − Rwithout =
H ∗ 1 δR tanh 2 H⊥∗ + HK H − tanh H⊥ + HK
(9) where H ∗ , H⊥∗ denotes the fields produced in the presence of a magnetic particle and includes its contribution to magnetizing the free layer, whereas H , H⊥ denotes the fields produced in the particle’s absence when only the external fields and intrinsic sensor fields contribute to magnetizing the free layer. While GMR sensors have been designed in a variety of shapes, the most common GMR sensor design is the rectangular spin-valve structure in which the pinned layer’s magnetization is set along the sensor’s minor axis by crystalline anisotropy, while the free layer is dominated by shape anisotropy and aligns along the sensor’s major axis. A DC bias field is typically applied along the sensor’s major axis, and a small-signal AC magnetic field is applied along the sensor’s minor axis to generate a signal which can be easily detected with the use of a lock-in amplifier. On the basis of this design, it is possible to produce a voltage signal in the range of millivolts using modest external magnetic fields of <100 Oe, and a small sense current of only a few milliamperes.15–22 Magnetic biosensors are an ideal detection platform when only the presence or absence of a target molecule needs to be ascertained. However, quantitative comparison between different magnetic biosensor platforms has remained a difficult challenge due to the high nonlinearity of the field from magnetic labels. The sensor signal can be modeled to a first approximation as being proportional to the average of the magnetic particle’s field across the sensor. Since the fields from magnetic particles are dipolar, the sensor signal depends strongly on the direction of the external field, the position of the particle, and the orientation of the sensor axis. Because of symmetry considerations, there are situations when a particle’s signal is maximized; however, other situations permit a particle to be located on the sensor with no signal being obtained. Wherever possible, one must design the system to prevent these scenarios from occurring, since they lead to false-negative test
9
results. Another problem encountered in magnetic biosensors, is that the particle’s field can point in opposite directions at different points of the sensor, in effect destructively interfering with the sensor signal. This effect is more pronounced when the particle is much smaller than the sensor; however, this effect can be reduced by designing the sensor to be commensurate with the size of the magnetic label. In doing so, the particle’s field becomes substantially more uniform across the sensor, thereby allowing a maximal signal to be obtained while simultaneously reducing its sensitivity to the particle’s position above the sensor.
6 CONCLUSIONS AND OPEN QUESTIONS
Compared to competing technologies based on optical and electrical fields, the use of magnetic nanoparticles in biosensors and biochips has a number of advantages, which makes it uniquely suited for diagnostic applications. The advantage of using magnetic detection systems is that the sensor output is an electronic signal, which enables the entire sensor platform to be miniaturized without having to accommodate bulky optical sources. For this reason, magnetic biochips are ideally suited for portable applications used in the military and in health diagnostics. In addition, magnetic materials are more stable than their fluorescent counterparts (magnetic signals do not bleach), and if designed properly, magnetic biosensors can be used to quantitatively compare data between different biosensor experiments. Magnetic signals also benefit from a lower external noise level than their fluorescent counterparts. Furthermore, magnetic manipulation systems allow for straightforward and potentially programmable handling of colloidal particles in fluids. This capability can be used to separate molecules, mix fluids, or effectively concentrate target molecules onto sensor devices. Compared with dielectrophoresis, which is the basis of optical or electrical techniques for manipulating neutrally charged particles, magnetophoresis has a number of advantages. For one, most biological materials are transparent to magnetic fields, which enables only the materials of interest to be manipulated without concern for heating or inducing chemical
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
reactions. Moreover, basic physics indicates that magnetic forces are likely to be orders of magnitude stronger than forces produced by electrical or optical fields. The basis for this argument is that substantially higher spatial energy densities can be stored in magnetic fields than in electrical fields, which are limited by dielectric breakdown of roughly 106 V m−1 in most fluids. The energy density stored in a 1 T magnetic field, for example, is 3–4 orders of magnitude higher than the energy density stored in a corresponding 106 V m−1 electrical field. This analysis motivates future use of magnetic systems for manipulation of particles much smaller than is possible by electrical or optical fields. Despite its recent success, several issues have limited the use of magnetic sensors more broadly in diagnostics. Compared with fluorescent sensors, which acquire signal through line of sight, the limitation in magnetic sensing is the highly nonlinear dipolar field produced by magnetic labels. As a result, magnetic signals are more sensitive to both the size and position of the label on the sensor than are fluorescent signals. This problem may be largely a technical issue, and one way to overcome this problem is to use sensors that are commensurate in size with the magnetic labels. Additionally, techniques can be devised to control the label’s position on the sensor by magnetic force, thereby providing a more repeatable signal. In conclusion, there is a bright future for magnetic biosensors. With increasing control over magnetic particle synthesis and with future advances in the design of smaller and more sensitive magnetic field sensors, magnetic biosensors may one day rival conventional methods and become more broadly adopted in the field of biosensors and biochips.
REFERENCES 1. D. H. Blohm and A. Guiseppi-Elie, New developments in microarray technology. Current Opinion in Biotechnology, 2001, 12, 41–47. 2. J. Marx, DNA arrays reveal cancer in its many forms. Science, 2000, 289, 1670–1672. 3. A. Manz, N. Graber, and H. M. Widmer, Miniaturized total chemical analysis systems: a novel concept for chemical sensing. Sensors and Actuators, B Chemistry, 1990, 1(1–6), 244–248.
4. M. J. Madou, Fundamentals of Microfabrication: The Science of Miniaturization, 2nd Edn, CRC Press, Boca Raton, 2002. 5. D. R. Reyes, D. Iossifidis, P. A. Auroux, and A. Manz, Micro total analysis systems. 1. Introduction, theory, and technology. Analytical Chemistry, 2002, 74(12), 2623– 2636. 6. P. A. Auroux, D. Iossifidis, D. R. Reyes, and A. Manz, Micro total analysis systems. 2. analytical standard operations and applications. Analytical Chemistry, 2002, 74(12), 2637–2652. 7. T. Vilkner, D. Janasek, and A. Manz, Micro total analysis systems. Recent developments. Analytical Chemistry, 2004, 76(12), 3373–3385. 8. F. E. Kruis, H. Fissan, and A. Peled, Synthesis of nanoparticles in the gas phase for electronic, optical and magnetic applications-a review. Journal of Aerosol Science, 1998, 29(5–6), 511–535. 9. H. Kawaguchi, Functional polymer microspheres. Progress in Polymer Science, 2000, 25(8), 1171–1210. 10. S. Sun, H. Zeng, D. B. Robinson, S. Raoux, P. M. Rice, S. X. Wang, and G. Li, Monodisperse MFe2O4 (M = Fe, Co, Mn) Nanoparticles. Journal of the American Chemical Society, 2004, 126, 273. 11. N. Nath and A. Chilkoti, Label free colorimetric biosensing using nanoparticles. Journal of Fluorescence, 2004, 14(4), 377–389. 12. S. R. Nicewarner-Pe˜na, R. G. Freeman, B. D. Reiss, L. He, D. J. Pe˜na, I. D. Walton, R. Cromer, C. D. Keating, and M. J. Natan, Submicrometer metallic barcodes. Science, 2001, 294, 137–141. 13. M. Han, X. Gao, J. Su, and S. Nie, Quantum-dottagged microbeads for multiplexed optical coding of biomolecules. Nature Biotechnology, 2001, 19, 631–635. 14. D. H. Reich, M. Tanase, A. Hultgren, L. A. Bauer, C. S. Chen, and G. J. Meyer, Biological applications of multifunctional magnetic nanowires. Journal of Applied Physics, 2003, 93, 7275–7280. 15. P. A. Besse, G. Boero, M. Demierre, V. Pott, R. Popovic, Detection of a single magnetic microbead using a miniaturized silicon Hall sensor. Applied Physics Letters, 2002, 80, 4199–4201. 16. M. M. Miller, G. A. Prinz, S. F. Cheng, and S. Bounnak, Detection of a micron-sized magnetic sphere using a ring-shaped anisotropic magnetoresistance-based sensor: A model for a magnetoresistance-based biosensor. Applied Physics Letters, 2002, 81(12), 2211–2213. 17. D. L. Graham, H. A. Ferreira, P. P. Freitas, and J. M. S. Cabral, High sensitivity detection of molecular recognition using magnetically labelled biomolecules and magnetoresistive sensors. Biosensors and Bioelectronics, 2003, 18, 483–488. 18. D. L. Graham, H. A. Ferreira, and P. P. Freitas, Magnetoresistive-based biosensors and biochips. Trends in Biotechnology, 2004, 22(9), 455–462. 19. M. Tondra, M. Porter, and R. J. Lipert, Model for detection of immobilized superparamagnetic nanosphere assay labels using giant magnetoresistive sensors. Journal of Vacuum Science and Technology A, 2000, 18(4), 1125–1129. 20. G. Li, S. X. Wang, and S. Sun, Model and experiment of detecting multiple magnetic nanoparticles as biomolecular
MAGNETIC NANOPARTICLES FOR DIAGNOSTIC APPLICATIONS
21.
22.
23.
24.
25.
26.
27.
28.
29.
30. 31.
32.
33.
34. 35.
labels by spin valve sensors. IEEE Transactions on Magnetics, 2004, 40(4), 3000–3002. L. Ejsing, M. F. Hansen, A. K. Menon, H. A. Ferreira, D. L. Graham, and P. P. Freitas, Planar Hall effect sensor for magnetic micro- and anobead detection. Applied Physics Letters, 2004, 84(23), 4729–4731. D. K. Wood, K. K. Ni, D. R. Schmidt, and A. N. Cleland, Submicron giant magnetoresistive sensors for biological applications. Sensors and Actuators A, 2005, 120(1), 1201–1206. D. P. E. Dickson, N. M. K. Reid, C. Hunt, H. D. Williams, M. El- Hilo, and K. O’Grady, Determination of f0 for fine magnetic particles. Journal of Magnetism and Magnetic Materials, 1993, 125(3), 345–350. L. C. R. N´eel, Influence of thermal fluctuations on the magnetization of ferromagnetic small particles. Academy of Sciences, 1949, 228, 664–668. P. Tartaj, M. D. P. Morales, S. Veintemillas-Verdauger, T. Gonzalez-Carreno, and C. J. Serna, The preparation of magnetic nanoparticles for applications in biomedicine. Journal of Physics D: Applied Physics, 2003, 36, R182–R197. R. Massart, Preparation of aqueous magnetic liquids in alkaline and acidic media. IEEE Transactions on Magnetics, 1981, 17(2), 1247–1248. S. W. Charles, Magnetic Fluids (Ferrofluids), J. L. Dormann and D. Fiorani (eds), Elsevier Science Publishers, Amsterdam, 1992, pp. 267–276. X. Li and Z. Sun, Synthesis of magnetic polymer microspheres and application for Immobilization of proteinase of balillus sublitis. Journal of Applied Polymer Science, 1995, 58(11), 1991–1997. H. P. Khng, D. Cunliffe, S. Davies, N. A. Turner, and E. N. Vulfson, The synthesis of sub-micron magnetic particles and their use for preparative purification of proteins. Biotechnology and Bioengineering, 1998, 60(4), 419–424. M. Uhlen, Magnetic separation of DNA. Nature, 1989, 340(6236), 733–734. C. H. Setchell, Magnetic separations in biotechnology-a review. Journal of Chemical Technology and Biotechnology, 1985, 35(B), 175–182. G. Helgesen, P. Pieranski, and A. T. Skjeltorp, Dynamic behavior of simple magnetic hole systems. Physical Review A, 1990, 42, 7271–7280. B. B. Yellen, O. Hovorka, and G. Friedman, Arranging matter by magnetic nanoparticle assemblers. Proceedings of the National Academy of Sciences, 2005, 102, 8860–8864. W. K. H. Panofsky and M. Phillips, Classical Electricity and Magnetism, 2nd Edn, Addison-Wesley, 1962. C. S. Lee, H. Lee, and R. M. Westervelt, Microelectromagnets for the control of magnetic nanoparticles. Applied Physics Letters, 2001, 79(20), 3308–3310.
11
36. D. L. Graham, H. Ferreira, J. Bernardo, P. P. Freitas, and J. M. S. Cabral, Single magnetic microsphere placement and detection on-chip using current line designs with integrated spin valve sensors: Biotechnological applications. Journal of Applied Physics, 2002, 91(10), 7786. 37. L. E. Helseth, H. Z. Wen, R. W. Hansen, T. H. Johansen, P. Heinig, and T. M. Fischer, Assembling and Manipulating Two-Dimensional Colloidal Crystals with Movable Nanomagnets. Langmuir, 2004, 20, 7323–7332. 38. F. J. Friedlaender, M. Takayasu, J. B. Rettig, and C. P. Kentzer, Particle flow and collection process in single wire HGMS studies. IEEE Transactions on Magnetics, 1978, 14(6), 1158–1164. 39. B. B. Yellen, Z. G. Forbes, D. S. Halverson, G. Fridman, K. A. Barbee, M. Chorny, R. J. Levy, and G. Friedman, Targeted drug delivery to magnetic implants for therapeutic applications. Journal of Magnetism and Magnetic Materials, 2005, 293(1), 647–654. 40. B. B. Yellen and G. Friedman, Programmable Assembly of Heterogeneous Colloidal Particle Arrays. Advanced Materials, 2004, 16(2), 111–115. 41. B. B. Yellen, G. Fridman, and G. Friedman, Ferrofluid lithography. Nanotechnology, 2004, 15, S562–S565. 42. O. Hovorka, B. B. Yellen, N. Dan, and G. Friedman, Self-consistent model of field gradient driven particle aggregation in magnetic fluids. Journal of Applied Physics, 2005, 97, 10Q306. 43. S. H. Liao, S. C. Hsu, C. C. Lin, H. E. Horng, J. C. Chen, M. J. Chen, C. H. Wu, and H. C. Yang, High-Tc SQUID gradiometer system for magnetocardiography in an unshielded environment. Superconductor Science and Technology, 2003, 16, 1426–1429. 44. P. Ripka, Review of fluxgate sensors. Sensors and Actuators, A, 1992, 33, 129–141. 45. N. E. Jenkins, L. P. DeFlores, J. Allen, T. N. Ng, S. R. Garner, S. Kuehn, J. M. Dawlaty, and J. A. Marohn, Batch fabrication and characterization of ultrasensitive cantilevers with submicron magnetic tips. Journal of Vacuum Science and Technology B, 2004, 22(3), 909–915. 46. P. D. D. Schwindt, S. Knappe, V. Shah, L. Hollberg, J. Kitching, L. A. Liew, and J. Moreland, Chipscale atomic magnetometer. Applied Physics Letters, 2004, 85(26), 6409–6411. 47. G. Li and S. X. Wang, Analytical and micromagnetic modeling for detection of a single magnetic microbead or nanobead by spin valve sensors. IEEE Transactions on Magnetics, 2003, 39, 3313–3315. 48. Y. W. Tahk, K. J. Lee, and T. D. Lee, Spin tilting phenomenon in strongly coupled AFC media. IEEE Transactions on Magnetics, 2002, 38(5), 2087–2089.
50 The Detection and Characterization of Ions, DNA, and Proteins Using Nanometer-Scale Pores John J. Kasianowicz,1 Sarah E. Henrickson,1 Jeffery C. Lerman,1 Martin Misakian,1 Rekha G. Panchal,2 Tam Nguyen,2 Rick Gussio,2 Kelly M. Halverson,3 Sina Bavari,3 Devanand K. Shenoy4 and Vincent M. Stanford5 1
Electronics and Electrical Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA, 2 Target Structure Based Drug Discovery Group, National Cancer Institute–SAIC, Frederick, MD, USA, 3 United States Army Medical Research Institute of Infectious Diseases, Frederick, MD, USA, 4 Naval Research Laboratory, Center for Bio/Molecular Science and Engineering, Washington, DC, USA and 5 Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
1 INTRODUCTION
Biology is controlled by interactions between different types of soft condensed matter including DNA, RNA, proteins, lipids, and carbohydrates.1 Hydrogen bonding and other atom–atom interactions permit biological macromolecules to adopt three-dimensional structures that are robust over long enough timescales to perform useful work (e.g., the storage, transcription, transmission, and translation of information critical for the development, maintenance and propagation of life). In addition, they catalyze chemical reactions (e.g., the synthesis and degradation of other molecules) and act as inter- and intracellular transport machines. Here, we focus on the latter category of macromolecules because they have demonstrated potential for use in biosensor applications.
Ion channels are nanometer-scale pores formed by membrane-spanning proteins2 that can catalyze the flow of up to ∼109 ions/s. More than 50 years of research into the structure and function of ion channels demonstrates that a seemingly simple motif, a nanopore, performs many different tasks in cells and organelles. These include neuronal signal transmission,3 antibiotic activity,4 the transduction of signals within and between cells,5 and the selective transport of ions and macromolecules. Failure of ion channels in vivo often leads to debilitating disease. For example, a defect in a chloride-selective ion channel is the molecular basis for cystic fibrosis.6 Biological nanopores also facilitate the transport of macromolecules in a wide variety of processes including protein translocation across membranes,7 gene transduction between bacteria, and the transfer of genetic information from some viruses and bacteriophages to cells.8 With the
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. Published in 2007 by John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4. This chapter is in the public domain in the United States but is copyright John Wiley & Sons Ltd. in the rest of the world.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
a-Hemolysin
PA63
relatively large ion channel12 from seven identical monomers.9 The crystal structure of the channel shows a massive cap domain that extends beyond one of the membrane–solution interfaces and a relatively short β-barrel stem region that spans the membrane (Figures 1 and 2). The αHL channel has several properties that make it ideal for use in biosensor systems. Like many other protein ion channels, the αHL nanopore gates (i.e., switches) between different conducting states.13 Over 15 years ago, we found that the αHL channel can remain fully open for tens of minutes.14 This permitted the development of the αHL channel as a fully open nanometerscale test tube to study the reaction dynamics of ions binding to the pore,15–17 of polymers partitioning into and binding to it,18 and the transport of individual DNA molecules through it.19 The results of these experiments are described below because they opened the possibility of using single nanopores for the detection and characterization of analytes. Nanometer-scale pores are ideal for use in sensor applications for several reasons. First, they
Figure 1. Structures of two protein nanopores formed by protein toxins used in the development of nanometer-scale biosensors. (Left) A crystal structure of the Staphylococcus aureus alpha-hemolysin (αHL) ion channel.9 (Right) A model for the channel formed by B. anthracis protective antigen 63 (PA63 )7 is shown.10 The αHL channel is approximately 10.5-nm tall.
goal of adapting protein nanopores for biosensor applications, we are studying how ions, DNA, and proteins bind to and alter the ionic current through two different channels formed by the bacterial toxins, Staphylococcus aureus alphahemolysin (αHL)9 and Bacillus anthracis protective antigen 63 (PA63 )10 (Figure 1).
aHL
4 nm
(a)
Rf Zpore − +
V
2 ION TRANSPORT THROUGH FULLY OPEN NANOSCALE PORES 2.1
Properties of S . aureus αHL, a Model Nanopore for Biosensing
α-Hemolysin is one of several toxins secreted by the bacteria S. aureus.11 The 293–amino acid protein monomer has a molecular mass of 33.1 kDa, is water soluble, binds spontaneously to phospholipid membranes, and forms a
Zm
(b) Figure 2. Experimental setup for measuring the ionic current through protein nanometer-scale pores. (a) A lipid membrane (∼4-nm thick) is formed on a 100-µm diameter hole in a Teflon film that separates two identical Teflon chambers that each hold ∼2 ml of aqueous electrolyte solution. Ion channels are reconstituted into the membrane by adding protein to one chamber while stirring. (b) The impedance of the membrane and nanopore are measured using a low-noise voltage source and a high-impedance, high-bandwidth operational amplifier.
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
are commensurate with the size of the analytes of interest. Second, they are sufficiently small so that analytes can create a signal by a steric blockade of the pore or by changing the electrostatic potential near or inside the pore (i.e., the pore size is on the order of the Debye length in a typical electrolyte solution).20 Third, the analyte does not necessarily need to be labeled (e.g., with a fluorescent probe) to be detected as a single entity. Fourth, the method is sufficiently sensitive (better than 1 nM).
Thus d = (4gl/σ π)1/2 . For the αHL channel (l ∼ 10 nm) in 1 M KCl (σ ∼ 0.1 S cm−1 ) at pH 7.5, the single-channel conductance is g ∼ 1 nS and the estimated diameter is d ∼ 1.12 nm, slightly smaller than the limiting aperture obtained from the channel crystal structure (1.56 nm). Although naive, this simple calculation underscores the fact that ion channels are indeed nanometer-scale objects.
2.3 2.2
Measurement of the Ionic Current through Protein Nanopores
Details of the experimental methods for reconstituting channels formed by αHL and similar proteins into planar lipid bilayer membranes are described elsewhere.16 Briefly, a solvent-free diphytanoyl phosphatidylcholine lipid membrane is formed on a 20–100-µm diameter opening in a 25-µm thick polytetrafluoroethylene (PTFE, Teflon) partition that separates two halves of a Teflon chamber (Figure 2a). The two compartments contain identical aqueous solutions (e.g., 1 M KCl buffered to a constant pH value). The pore-forming protein is added to the aqueous phase in one compartment, herein called cis, which is stirred vigorously for ∼10 s. After the desired number of channels is formed, excess protein is removed from the chamber. An electric field is applied across the membrane by a matched pair of Ag–AgCl electrodes. The ionic current is converted to a voltage using a high-bandwidth amplifier (Figure 2b) after which the signal is passed through an analog low-pass filter and then digitized by an A/D converter. A negative applied potential drives anions from the cis side to the trans side. If we assume the pore can be represented by a smooth circular cylinder filled with an electrolyte solution that has a conductivity equal to that of the bulk, σbulk , and that for small applied potentials Ohm’s law is valid (i.e., g = I /V , where g is the single-channel conductance), a crude estimate for the diameter, d, of an ion channel can be obtained. If we also assume that the access resistance of the solution outside the pore2 is zero, then the channel conductance is g = σ A/ l, where A and l are the cross-sectional area and length of the pore, respectively, and σ is the conductivity of the solution inside the pore.
3
Effect of Electrostatics on the Current Flow in a Fully Open Channel
Figure 3(a) illustrates typical ionic current recordings for a single αHL channel that occur in response to different values of the applied potential.21 Figure 3(b) shows the mean value of the current at each voltage, in the form of a current–voltage (I –V ) relationship, for solutions with two different pH values. At low pH (pH 4.5), the I –V relationship is nearly ohmic. At higher pH (pH 7.5), the I –V relationship becomes slightly nonlinear and rectifying.15,16,21 The difference in the I –V relationships at these two pH values is more striking at lower values of the ionic strength (not shown). In principle, the binding of protons to amino acid side chains in the αHL channel could cause the I –V relationship to change by either altering the pore’s geometry or the electrostatic potential profile along the pore axis. The latter effect can be described by a one-dimensional electrostatic model for the control of ion flow through the channel.2,21 Figure 3(c) shows how the αHL channel is most likely situated in a 4-nm thick lipid bilayer membrane.17 Figure 3(d) presents a simplified one-dimensional potential profile that identifies charged amino acid side chains inside the pore or near the pore entrances. The applied potential, V , is assumed to drop linearly along the channel length as in the Goldman–Hodgkin–Katz equation.22,23 The well amplitudes change as the pH value of the electrolyte solution is varied (the positive barrier amplitudes remains fixed because of lysine’s high pK value; the lysines are at positions 8, 131, and 147). Physically reasonable adjustments to the values of the well depths made it possible to obtain a good fit to the shape of the I –V relationships for pH 4.5 and 7.5. The change in the I –V relationship
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
cis
trans
100
I (pA)
50 0 1.5 to −50
4.6 nm
−100 −150 0
100 Time (ms)
(a)
200 (c) 10 nm
K8 pH 4.5
150
I (pA) 100
D13 K147 pH 7.5
50
E111 −200
−100
100
200
K131
−50
V (mV)
D127
−100
D128
−150
x=0 (b)
x=l
(d)
Figure 3. Experimental and theoretical description for ion flow through the fully open αHL channel. (a) Single-channel currents for applied potentials ranging from −200 mV to +200 mV in 10-mV increments. (b) Current–voltage relationship estimated from data similar to that in (a). The current is generally nonlinear in the applied potential, slightly rectifying, and pH dependent. (c) Cartoon illustration of the αHL channel in a lipid membrane. (d) A simplified one-dimensional electrical potential profile that includes the applied transmembrane voltage, and the barriers and wells caused by fixed charges inside the nanopore. Changes in the solution pH cause an asymmetric change in the amount of fixed charge in the αHL pore.21 This property was used to demonstrate that single αHL channels could act as sensors for ions. [Reprinted from M. Misakian and J.J. Kasianowicz, Electrostatic influence on ionic current through the α-HL ion channel. J. Membrane Biology, 2003, 195, 137–146, with permission from Springer.]
from nearly linear to nonlinear and rectifying most likely reflects the fact that ionizable side chains (e.g., D13, E111, D127, and D128) that reversibly bind protons under these conditions are asymmetrically distributed along the pore axis. Also, the pore diameter is commensurate with the Debye length.20
2.4
Single Nanopore-based Sensors: Analyte Detection Based on Reaction Dynamics
The results in Figure 3, and the simplified theoretical models that describe them, demonstrate how an ion can bind to a channel and leverage the flow of other ions through a nanometer-scale
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
pore (i.e., much like the field-effect process in a transistor). Because ion binding to sites within the pore is generally a reversible process, one might expect that the channel conductance will fluctuate between two states as the ion associates with, and dissociates from the site. Moreover, because reaction kinetics are characteristic of the interaction between the analyte and the binding site, the dynamics of the current fluctuations will contain information about the analyte concentration and type.24 Furthermore, the type of blockade (e.g., electrostatic control, steric blockade of the pore by analyte, etc.) provides additional details about the process. Therefore, the binding of the analyte to the channel could either cause the conductance to increase or decrease. Let us suppose the pore has two conductance states that are characteristic of the binding site when it is never, or always, occupied (Figure 4, states 1 and 2). These two conditions could correspond to analyte concentrations that are much less than or much greater than the binding constant K in mol l−1 . K is defined by K = koff /kon where kon and koff are the rate constants for the association and dissociation of the analyte to the binding site on the nanopore, and 1/koff is the mean time that the analyte is bound to the site on the pore. When the analyte concentration is equal to the binding constant (i.e., [A] = K), the channel spends on average half the time in each of the two conductance states. [A] << K
[A] ≈ K
[A] >> K
State 1
I (t ) State 2
Apply voltage
Zero current
Figure 4. Schematic of nanopore-based method for analyte detection. Ionic current versus time for a pore challenged with three different analyte concentrations. First, in the absence of analyte ([A] K), where K is the association constant for the binding of analyte to the pore, the current is in state 1. Second, for analyte concentration [A] ≈ K, the pore conductance will fluctuate between two states (bound and unbound with analyte). Third, for high analyte concentration (i.e., [A] K), the pore will be virtually always occupied with analyte and therefore be in state 2.
5
Figure 5(a) illustrates schematically how the ionic current appears as the analyte concentration varies. Figure 5(b) shows the mean ionic current variation if there is either only one analyte binding site on the channel or many independent binding sites with identical binding constants. Calibrating a given nanopore with known concentrations of a particular analyte allows the unique determination of the analyte concentration in a test solution by measuring the value of the mean ionic current. The dynamic information in current fluctuations provides additional information that aids the estimation of the concentration and identification of the analyte species.15,16,24 Spectral analysis is used to determine the frequency content of a time series.25 For a random telegraph, two-state system, the spectral density of the current noise is described by: S(f ) = S(f ) =
4(i1,2 )2 τ 2 ((τ1 + τ2 )(1 + (2πf τ )2 ))
or
S(0) (1 + (f/fc )2 )
where τ1 and τ2 are the mean times spent in states 1 and 2, respectively; 1/τ = 1/τ1 + 1/τ2 or τ = τ1 τ2 /(τ1 + τ2 ) (in seconds); f is the frequency (in Hz); and i1,2 is the difference in current between states 1 and 2.15,26 Figure 5(c) is a theoretical plot of the spectral density as a function of frequency for a given analyte type and concentration (given values for kon and koff ). At low frequencies, S(f ) approaches a constant value, S(0). At greater frequencies, S(f ) decreases as 1/f 2 . At the characteristic corner frequency fc = 1/(2πτ ), the spectral density drops twofold from its value at f = 0 (i.e., S(fc ) = S(0)/2). A least-squares fit of the expression above for S(f ) to the experimental ion current spectral density data provides estimates for S(0) and τ . Figure 5(d) illustrates how these two parameters vary with analyte concentration. At both extremes of the concentration, the current fluctuations, and therefore S(0) (solid line), are virtually nil because the binding site is either always unoccupied or fully occupied. S(0) rises to a maximum value near the analyte concentration [A] ∼ K, because the site is occupied or unoccupied about half the time.
MINIATURIZED, MICRO AND PARTICLE SYSTEMS IMAX
Mean ionic current
6
[A] << K
[A] ≈ K [A] >> K
IMIN
IMAX
IMIN pK + 2
(a)
(b)
pK, Nkoff
0.1
∼1/f
2
0.5
0.5
t
fc 0
0 (c)
1
1/koff S(0)
S(f )
1
0.01
pK − 2
log10 [A] 1
S(0)
pK
100 1000 log10 (f )
pK + 2
10000 (d)
pK − 2 pK log10 [A]
Figure 5. Spectral analysis of analyte-induced current fluctuations provides estimates for the binding constant and kinetic rate constants for the reactions. (a) Hypothetical ionic current versus time recordings for three different analyte concentrations. The fluctuations in the ionic current about the mean value are caused by the reversible reaction between the analyte and a site or sites on a single nanopore. They are minimal at the extremes of analyte concentration and maximal at [A] ≈ K. (b) For increasing analyte concentration, the mean ionic current decreases monotonically from the maximum to the minimum current values. (c) Relative power spectral density (PSD) for the ionic current fluctuations. The low-frequency PSD value, S(0), and the corner frequency, fc , provide information about the binding constant and kinetic rate constants. For reactions that are Markovian, the PSD decreases as 1/f 2 for f > fc . (d) At the extreme values of analyte concentration, S(0) (black line) is minimal; for analyte concentrations [A] ≈ K, it rises to a maximal value. The characteristic relaxation time for the interaction between the analyte and the nanopore, τ = 1/2πfc , decreases monotonically with increasing analyte concentration (dashed line). In the limit of zero analyte concentration, τ ∼ 1/koff .
The plot in Figure 5(d) also illustrates that at low analyte concentration, the characteristic lifetime τ (dashed line) equals 1/koff because the dominant timescale is the mean time the analyte is bound to a site on the channel. As the analyte concentration increases, a second timescale, the time it takes the analyte to bind and react with the site, contributes and τ decreases monotonically to zero. The variation of S(0) with analyte concentration depends on both the pK, the product of the number of binding sites, N, and koff . Thus, if the pK and koff are determined from a calibration of the mean current (Figure 5b) and τ (Figure 5d), the number of binding sites can be estimated from the values of S(0).15 This method discriminates particularly well between different analytes that bind to the nanopore
because it makes use of both the thermodynamic (pK) and kinetic (kon and koff ) information. For example, it was demonstrated that a single αHL channel can distinguish between isotopic ion species (i.e., aqueous hydronium and deuterium ions).15,16 The spectral method was subsequently applied to genetically engineered versions of the αHL channel tuned to bind divalent cations.17 3 NEUTRAL POLYMER AND DNA TRANSPORT IN A SINGLE NANOPORE 3.1
Neutral Polymer Probes of Channel Structure Interact with the Pore
Krasilnikov and colleagues developed a method to use nonelectrolyte polymers of poly(ethylene
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
glycol) (PEG) to estimate the diameter of ion channels.27,28 It is well known that PEG decreases the bulk conductivity of ionic solutions. Thus, PEGs that are sufficiently small enter the pore and decrease the channel conductance. Polymers larger than the diameters of the two channel mouths rarely partition into the pore and therefore have little or no effect on the conductance. The dependence of channel conductance on the PEG molecular weight determines the pore’s PEG molecular mass cutoff, and by inference, the pore diameter. The single-channel recordings in Figure 6(a) illustrate the effect of different molecular mass PEGs on the αHL channel conductance. Note that the relatively large PEG 8000 rarely decreases the conductance. In contrast, PEG 200 significantly reduces the mean current. The ratio of the conductance in the presence of PEG to that in the absence of the polymer demonstrate that PEGs with molecular mass less than 3000 partition into the channel (Figure 6b). The diameter of the αHL channel is estimated from these data and the measured values of PEG hydrodynamic radii29 are indicated on the plot. The single-channel current recordings in the presence of PEG 2000 (Figure 6a) are noisy. Ion current fluctuations should indeed occur when the
polymer randomly partitions into and out of the pore. However, the observed noise is orders of magnitude greater than expected based on the calculated residence time for the polymer diffusion inside the pore. Specifically, the one-dimensional diffusion equation x2 = 2DτD 30 suggests the polymer should diffuse the length of the channel in a time τD ∼ 10 ns. However, the current recordings shown in Figure 6(a), which were filtered to 1-kHz bandwidth, indicate otherwise. Indeed, the mean residence time for PEG in the αHL pore, deduced from the excess current noise, was ∼100 µs.18
3.2
Detecting Individual Polynucleotides that Thread through a Single αHL Channel
The previous result (Figure 6a) indicated that the αHL nanopore can interrogate a polymer for a time much greater than the time taken for the polymer to diffuse through the channel. Because of this property and because the αHL channel can remain fully open for long times, an opportunity is provided to study the details of DNA transport in a highly confined space. Specifically, we demonstrated that individual molecules of single-stranded DNA are
Channel conductance ratio
Hydrodynamic radius (nm) 0.5 1 2
30 pA
1s
(a)
PEG 200
PEG 2000
PEG 8000
1.0
0.8
0.6
Hard spheres Scaling theory
100 (b)
4
1.2
w 3 law
No PEG
7
Ratio of bulk conductivities
10000 1000 PEG molecular weight
Figure 6. Estimating the size of the αHL channel with nonelectrolyte polymers. Polymers of poly(ethylene glycol), PEG, reduce the bulk conductivity of an electrolyte solution. (a) Sufficiently small PEGs partition into the solitary channel and reduce the current of spontaneously forming channels. (b) The dependence of the single-channel conductance on the polymer Molecular Weight (MW) is used to estimate the PEG MW cutoff, and thus provides an estimate for the diameter of the aqueous-filled channel pore.
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS +poly[U] cis
Lifetime (µs)
3000
50 pA
−120 mV
300 µs
0
1300 µs
(a)
ssDNA
1500
(b)
+
+++++ + + +
+ ++
400 200 Mean poly[U] length (nt)
dsDNA trans (c)
cis
Figure 7. Polynucleotides are driven into a single αHL channel by a transmembrane potential difference. (a) Single-channel recordings in the absence and presence of single-stranded RNA show transient blockades. (b) Polymer-induced blockade lifetimes (inset: histogram of blockade lifetimes for a given length poly[U] RNA show 3 characteristic lifetime values). The polynucleotide-induced lifetimes for the two slowest blockade types are proportional to the polymer length, which suggests the polynucleotide threads completely through the nanopore. (c) PCR demonstrates that single-, but not double-stranded DNA is transported through the αHL channel from the cis to the trans side.
driven electrophoretically into and through a single αHL ion channel.19,31 Because the mobility of negatively charged polynucleotides is less than that of monovalent ions and the polymer occupies space that small mobile ions normally would, polynucleotides decrease the channel conductance when they are inside the pore (Figure 7a). The lifetime of the polymer-induced current blockades is proportional to the contour length for polynucleotides comparable to or longer than the pore length, (Figure 7b). Polymerase chain reaction technology (PCR) confirmed that singlestranded, but not blunt-ended double-stranded, DNA was transported through the pore. The latter two results strongly suggest that the polymer threads through the pore as a linear rod.19 In that report, we hypothesized that a single nanopore could rapidly sequence DNA if each base caused a unique current blockade level. We subsequently demonstrated that different homopolymers cause distinctly different ion current blockade signatures.32,33 Because DNA sequencing with a single nanopore is yet to be realized, intense investigation continues.34–41 3.3
Sensor Technologies Based on DNA – Nanopore Interactions
For relatively short polynucleotides that interact with the αHL channel, the time-averaged
t Blockade rate ~[polymer]free
Complex cannot enter pore
Complex blocks pore for t ~1/koff
Figure 8. Sensor models based on the interaction between a single nanopore and polymers. It is assumed that polymers with binding sites for analytes have unfettered access to the nanopore. The entry or transport of individual polymers causes a transient decrease in the ionic current (left). Addition of analytes that bind to the polymer change the ability of the latter to partition into (center) and/or transport through the pore (right). In the latter model, the analyte : polymer complex blocks the pore for a time that corresponds to the mean lifetime of the complex (i.e., τ ∼ 1/koff ). [Adapted from Kasianowicz, et al.,42 2001.]
blockade rate increases linearly with the polymer concentration.31 This, in part, permitted simultaneous multiple analyte detection with polymers and a single nanopore (Figure 8a–c).42 Briefly, a binding site for a specific analyte is attached to an αHL channel–permeant polymer. Analyte
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
binding to this site alters the ability of the polymer to thread through the pore. In the first case, the analyte concentration is deduced from the decrease in the mean number of blockades per unit time (Figure 8b). For the second detection scheme (Figure 8c), the analyte concentration is estimated from the mean time for nanopore occlusion by the analyte/polymer complex after the electric field is applied. Because different polymer types cause different current blockade patterns (see below), a single nanopore can be used to simultaneously detect different analytes. This method is particularly useful because it does not require the analytes to be labeled. In addition, changing the applied potential permits the force on the bond between the analyte and polymer to be varied, which may help identify a particular analyte in the presence of molecules with similar, but not identical properties.
4 ADVANCED SIGNAL PROCESSING METHODS: READING INFORMATION ENCODED IN POLYMERS 4.1
Polynucleotide-induced Current Blockades Characteristic of Polymer Type
As shown in Figure 7, the transport of individual polynucleotides through a single ion channel is easily observed electronically because the polymers occlude the channel and thereby reduce the flow of ions through the nanopore. The length of a polymer can be estimated from the mean current blockade lifetime (Figure 7b). Can information encoded in the polymer be read from the electronic signals? The current recordings in Figure 9(a) illustrate the blockades caused by identical length poly[dT], poly[dA], and poly[dC] molecules. Note that the lifetime and substate patterns for a given homopolynucleotide are clearly distinguishable from those caused by the others. Nevertheless, the variation in individual blockade patterns for a given polymer type requires a stochastic analysis of the signals. The current blockades depend on the characteristics of the polynucleotide (e.g., base composition, secondary structure, and interactions between polymer subunits) and the nanopore (e.g., pore geometry and local electric field in the lumen). The
Fully open
I=0
poly[dT]
poly[dC]
9 poly[dA]
25 pA 2 ms
(a) Open
I=0 Open 50 pA
I=0 5 ms
(b)
Figure 9. Polynucleotides threading through a single αHL channel cause transient ionic current blockades that are characteristic of the polymer. (a) Blockades caused by individual 100-nt long poly[thymine] (poly[dT]), poly[cytosine] (poly[dC]), and poly(adenosine) (poly[dA]). (b) The blockade patterns for poly[dT] depend upon the side to which the polymer is added.
signals caused by 100-base-long homopolymers of thymine (i.e., poly[dT]100 ) are discussed in greater detail because their rich state structure reveals characteristics of the pore geometry. Additionally, the signals provide an example of how information encoded in a polymer might be read electronically via a nanopore. The current blockades shown in Figure 9(b) for poly[dT]100 entering the cis entrance of the αHL channel, as indicated by the cartoon inset, often show a characteristic shallow-then-deep blockade pattern. In contrast, when the polymer is driven from the opposite direction (i.e., trans side), the blockade pattern is reversed (i.e., a deep-thenshallow pattern prevails). Figure 10 illustrates many blockades induced by poly[dT]100 . This “forest from the trees” representation obscures the details of any individual blockades (Figure 9b) but it aids the visual identification of the most probable occluded current states. For example, the three darkest bands in the current recording (Figure 10a, left) and the largest peaks in the current amplitude histogram for ∼104 blockades (Figure 10a, right) correspond to the fully open state and two most probable occluded current
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS 150
State Open
I (pA)
100
1
50
2 2a 3
0 0 (a)
1000 Time (ms)
2000 Current amplitude histogram
State 100
I (pA)
Open 50
1′
2′ 0
3′ 0
(b)
300
600
Time (ms)
Current amplitude histogram
Figure 10. Ionic current time series for poly[dT]100 transit events with lifetimes between 40 µs and 2 ms (left) and current amplitude distribution (right) for polymers entering the pore from either the (a) cis or (b) trans pore entrances for applied potentials of V = −120 or +120 mV, respectively. The two time series depict the open channel current band and bands corresponding to the three most probable occluded states. The limited number of occluded states may represent the negotiation of the polymer through the various-diameter segments of the pore.
states (states 1 and 3). The speckle between the lower two dark bands (Figure 10b, left) represents a less frequently occurring, but statistically significant state (state 2) and an even less probable state (state 2a). We ignore the latter state in subsequent discussion. The technique for determining the state sequences of individual events relies on Viterbi decoding43 of the dwell times within states of Gaussian mixtures fit to the observed amplitude densities. For the range of event lifetimes under consideration (≤ 2 ms), three blockade states and one open channel state are statistically adequate to describe the amplitude distribution. Using these population distributions, the state sequences in current flow levels from individual molecules as they entered the ∼1.5-nm diameter
opening in the channel were decoded. Under these experimental conditions only hundreds of ions per microsecond flow through the pore when it is partially occluded by a polynucleotide. Thus, statistical techniques are fundamental to characterizing the blockade states. For relatively short lifetime current blockades, the states and state sequences suggest that the polymer–pore interaction is simple. Moreover, it can be demonstrated that the state parameters and their sequence depend on the direction of transit, and how long the polymer and pore interact with each other. A statistical analysis of the current amplitude histogram in Figure 10(a, right), shows that three occluded states result in a good fit to the data. The cis open channel state mean current
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
4.2
Fully open
1 2 3
I=0
.
.
.
Figure 11. A cartoon that illustrates a possible mechanism for the three most probable transient current blockades caused by poly[dT]100 .
(∼120 pA), and the occluded state mean current values (∼70, ∼46, and ∼17 pA), have probability weights of 0.62, 0.2, 0.03, and 0.15 respectively. Similar results are obtained for events caused by poly[dT]100 molecules entering the trans entrance (Figure 10b). In that case, the trans fully open single-channel current average (∼88 pA), and the three most probable occluded states (∼53, ∼26, and ∼8 pA) occur with probability weights 0.53, 0.04, 0.19, and 0.24, respectively. Interestingly, the ratios of mean current values for each of the three most probable occluded states to the respective mean open channel current for poly[dT]100 entering the pore from the cis side (Figure 10a) do not appear to correspond to those for the three most likely occluded states for polymers threading the pore in the opposite direction (Figure 10b). One interpretation of the latter result, illustrated in Figure 11, suggests that the degree of ionic current blockade correlates with the amount of poly[dT] mass in either the pore vestibule (shallow blockade), or the smallest channel aperture (deeper blockade). This simple hypothesis is consistent with the blockade patterns caused by poly[dT] transport in either direction and the lifetime distributions of poly[dT]-induced blockades. These results, and others shown here, demonstrate that DNA can be used to probe the geometry of αHL channel. By inference, this technique may prove useful for probing the structures of other nanometer-scale pores, including those made in solid-state materials.
11
Blockade State Sequences Evolve with the Event Lifetime
Because the physical length of the homopolymer is constant for the poly[dT]100 experiment, differences in the blockade event lifetime and the state sequences allow us to characterize the physical properties of the nanopore. Figure 12 illustrates how the morphology of poly[dT]100 -induced current blockades evolves with increasing event lifetime over the range from 60 ≤ τcis ≤ 600 µs (i.e., for polymer added to the cis side). Here, the single-channel current time series for ensembles of events at three representative lifetimes (i.e., τcis = 60, 140, and 600 µs) are aligned at the onset of each channel blockade. The colors indicate the frequency of current values; that is, the closer to red end of the spectrum, the greater the number of occurrences. Because few 60-µs events exhibit the deep blockade state (state 3), the polymer most likely only entered the pore vestibule and did not thread completely through the pore. The 140-µs ensemble shows a bifurcation of the event set into shallow blockades, which are qualitatively similar to the 60-µs events, and deep blockades in which the homopolymer most likely was driven past the narrowest diameter of the channel and
∆tcis 60 µs
States 1
140 µs
600 µs
1,3
1,3,1→3
Figure 12. Event time-amplitude histograms showing characteristic ionic current signatures for increasing blockade duration. Poly[dT]100 -induced current blockades stratified by duration show that the event structure evolves in a simple manner. Sixty microsecond long events show a state 1 conductance level; 140 µs long events show a bimodal conductance morphology (state 1 and state 3); 600 µs long events show state 1 and increasingly frequent state 3 blockades. The 600 µs blockades also show the emergence of state 1 to state 3 transitions within the events. These signatures most likely represent the progress of the polymer through the various limiting apertures of the nanopore. In these experiments, the polynucleotide entered the αHL channel from the cis pore mouth. The color scale is adjusted to the declining frequency of longer events to best visualize the common event morphologies.
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
threaded through the pore (see Figure 11 center). The 600-µs event ensemble shows a third event morphology, a shallow-then-deep blockade, that is composed of three event types: shallow blockades, deep blockades, and shallow-then-full blockades. Figure 9(a, left) shows three such individual events. 4.3
Extracting Information Encoded in Polymers
Figure 13 illustrates typical single-channel current blockades for poly[dT]100 entering from the cis entrance of the channel, and the Maximum A Posteriori probability estimate of the state sequence (black), subject to the constraint imposed by a persistent Hidden Markov Model (HMM), which applies a penalty for state transitions, superimposed on the actual time series data (gray). For polymers entering the pore from the cis side (Figure 13a), the blockades show the three common patterns of Figure 12; i.e., state 1 only, state 3 only, and the intra-event transition from state 1 to state 3. Also included is an example of a relatively rare event comprised of a transition from state 2 to state 3. A corresponding class of events is observed when the polymer enters the trans side (Figure 13b). However, note that the transitions are from a more occluded state to a less occluded one, with the opposite two-step pattern observed when the polymer enters the pore from the cis entrance. The relatively small number of current blockade states and patterns also
suggests that a simple description of the blockade mechanism at these short event lifetimes may be valid. Figure 13(b) shows individual events illustrating shallow blockades, deep-then-shallow blockades, and events proceeding directly to a deep blockade. A mirror symmetrical morphology is observed in trans-to-cis event ensembles of this duration range: the deep-then-partial blockade. These results most likely reflect the fact that the channel cross section is asymmetric: the narrower segments are closer to the trans pore entrance. Analysis of a large number (∼2 × 105 ) of poly[dT]100 -induced blockade events, from both the cis and trans directions suggest an interesting and potentially important use of polymers as molecular rulers for the ion channel. The wide range of blockade durations, from 20 µs to over 2 full seconds, also suggests that the very long events may represent ssDNA that are folded in ways requiring substantial time periods to unfold and thereby access states that allow transit. The state structure of the amplitude distribution for longer events, characterized by components of a Gaussian mixture, evolves substantially over logarithmic increments of event duration beyond the 60–600-µs range just discussed, and is shown in Figure 14. Progressively greater proportions of long-duration events are spent in deep blockade states and require many more Gaussian mixture components to model adequately than do the deep blockade portions of the short-duration events. We have resolved up to 39 states with the aid of digital
150 cis
trans
100
1
I (pA)
I (pA)
100 1'
50
2
50
3
2' 3'
0
0 0
6 Time (ms)
12
0
6 Time (ms)
12
Figure 13. Typical single-channel current blockades for poly[dT]100 entering from the cis entrance (a) or trans entrance (b) and the maximum-likelihood estimate of the amplitude state sequence (black) superimposed on the data (gray). The technique for determining the state sequences from the data relies on Viterbi decoding of the dwell times.
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS 40 µs–2 ms
0
50
100
2.02–20 ms
150
0
50
100
20.02–200 ms
0 150 I (pA)
50
100
13
200.02 ms–2 s
150
0
50
100
150
Figure 14. Blockade event lifetime histograms for poly[dT]100 molecules that enter the cis side of a single αHL nanopore. For blockade lifetimes over a wide range (40 µs–2 s), virtually all of the events (99%) have lifetimes <5.5 ms. The lifetimes for each order of magnitude have clearly defined and differing Gaussian amplitude states. This representation of the data provides a fingerprint of the molecule as it interacts with the nanopore. We suggest that the ability to unambiguously decode the many Gaussian states caused by polymer–nanopore interactions provides an “electronic spectrogram” that could be used to uniquely identify polymers of interest.
filtering techniques and were able to estimate the required parameters. Clarification of the actual nanopore cross section and its functional interaction with polymers in transit suggests that the most fully blocked states will provide the best coign of vantage for higherresolution measurements of the ssDNA molecules themselves. Possibly, this is because the more complete blockade levels represent the interaction of the polymer with the narrowest point of constriction in the nanopore channel. If true, our state decoding technique, or an equivalent one, will be needed to extract information encoded in polymers.
4.4
Statistical Methods
It was previously demonstrated that statistical signal processing could be used to estimate and measure substates and their lifetimes in the DNA-induced current blockades.19,33,44 In many blockade events, the single-channel current is piecewise stationary, with states that overlap in amplitude but not in time. This signal structure prompted modification of the classical HMM of Baum45 to make a maximum a posteriori state sequence estimate. Statistical characterizations of the DNA-induced αHL channel current blockade states were based on Gaussian mixture models (GMMs) estimated using an expectation maximization (EM) procedure46 rather than the classical supervised forward–backward iteration.
This provides a set of Gaussian components and mixture weights from a large population of events. The amplitudes of individual piecewise stationary segments, and their lifetimes, can then be estimated using Viterbi decoding,43 which provides a MAP state sequence as the most probable generating function for the observed time series. While the maximum a posteriori state sequences are globally optimal, given the correct output distributions, it is well known that the EM/GMM estimator can arrive at local likelihood maxima that are globally suboptimal. However, a good statistical criterion can mitigate the practical impact of this limitation, with random initial conditions being explored until no further improvements in the likelihood or goodness-of-fit criteria are forthcoming. The well-known Kolmogorov–Smirnov (KS) statistic offers such a stopping criterion. The KS statistic is computed for each candidate amplitude mixture model, and additional components added if the p-value of the model fit could be rejected at the 0.05 level. Because the GMM components usually overlap, simply assigning each point to the highestlikelihood component results in many physically implausible transitions between states that overlap in amplitude. To model the time coherence in the signal implied by the passage of polynucleotides through the pore, the GMM components were employed as the output distributions of an ergodic HMM with a transition matrix favoring state persistence, meaning it has a dominant
14
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
diagonal with much smaller nonzero probabilities off the main diagonal. Also, an unconstrained maximum-likelihood GMM can result in distribution states that are highly heteroscedastic, which can therefore result in unrealistic decoding of the state sequences. A solution was to constrain the variances to equality during the GMM/EM estimation procedure. This offers a better approximation to the actual physical phenomenon of a nanometerscale pore that is occluded by a comparable-sized polymer than does unconstrained variances for the states. In the pioneering work applying HMM processing to channel conductance data described by Chung and colleagues,47,48 they state “Perhaps the most subjective part of the HMM processing method, like any parameter estimation scheme, is finding the state dimension—or the number of conductance states in our example—in hidden Markov chain processes.” In contrast, the stateidentification technique described above for quantifying current blockades44 is fully adaptive to the number of channel current states, and results in maximum a posteriori estimates of the state parameters and state sequences within the events.33,44 This newer method uses the KS goodness-of-fit criterion as a stopping rule for signal-amplitude states. It stops when the model cannot be rejected at the p value of 0.05, rather than using an ad hoc estimate of the point of diminishing returns. Once an adequate channel amplitude state model has been estimated using the EM algorithm for mixtures, a maximum a posteriori Viterbi algorithm decodes the entire event. The state sequences, like those shown in Figure 13, also provide lifetime and amplitude measurements for further analyses, such as discriminators for molecule types or automated extraction of structural information from individual molecules, and for analysis of the kinetics of encounters between the αHL nanopore and single DNA molecules. To summarize, the measurement algorithm discussed above estimates the number of states, the mixture weights, state means, a pooled estimate of the state variance, and a state sequence for the entire ensemble blockade events. Thus, it can be reasonably characterized as being fully datadriven or unsupervised, in contrast to other systems, which require supervised training or enforce
arbitrary assumptions on the number of states, state means, and state variances. 5 DETECTING ANTHRAX TOXINS WITH A SINGLE NANOPORE 5.1
Properties of the B . anthracis PA63 Ion Channel
The bacterium Bacillus anthracis secretes three proteins that cause late-stage anthrax infection. The properties of these toxins, and the steps leading to cell intoxication by them, have been outlined elsewhere.49 Protective antigen 83 (PA83 , 83 kDa) binds to target cells, is cleaved by furinlike proteases, and the 63-kDa fragment that remains associated with the membrane surface (PA63 ) oligomerizes into a heptameric prepore (PA63 )7 . Lethal factor (LF, 90 kDa) and edema factor (EF, 89 kDa) subsequently bind to (PA63 )7 , and the complexes LF:(PA63 )7 and EF:(PA63 )7 become associated with endocytotic vesicle membranes. Acidification of the endosome interior occurs and is believed to cause the heptameric (PA63 )7 prepore to form a fully functional transmembrane ion channel that facilitates the entry of LF and EF into the cytoplasm. Once inside the cell, LF and EF interfere with MAPKK signaling proteins and increase cAMP production, respectively, leading to cell death by two different mechanisms.
5.2
Nanopore-based Assay for Toxin Detection and Characterization
Figures 15(a–d) demonstrate that full-length LF and EF convert the (PA63 )7 channel I–V relationship from slightly nonlinear to highly rectifying.50 The data in Figure 15(d) show that the extent to which LF blocks the channels depends on the LF concentration. The ratio of the current in the presence of LF to that in the absence of the LF is shown in Figure 15(e). A simple analysis of this data suggests that LF binds with high affinity to the (PA63 )7 channel (K ∼ 50 pM). Similar results were obtained with EF. The ability to detect LF and EF in trace quantities with the (PA63 )7 channel provides a significant advantage for biosensor applications (e.g., the sensitive detection of LF and EF). Unlike surface plasmon resonance technique,
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS 1000
1000
−EF
+EF
500
I (pA)
0 −500
0 −500
−1000
−1000 150 Time (ms)
0 (a)
200
I (pA)
300
150 Time (ms)
0 (b)
300 −EF
300
[LF] = 0
I (pA) 150
100 +EF −120
−60 −100
−150
120 60 V (mV)
−300
−200
(c)
−120 −60
60 120 V (mV)
Increasing [LF]
I (pA)
500
15
(d)
1
I([LF])/I([LF] = 0)
2
I (nA) 1 0.5
−120
−60 −1 −2
0 (e)
0
50
100
60 120 V (mV) PA63 PA63 + mAb PA63 + mAb + LF
150 2500
[LF] (pM)
(f)
Figure 15. The binding of edema factor (EF) and lethal factor (LF) to the PA63 channel provides a novel method for anthrax toxin detection and anthrax therapeutic screening applications. (a) and (b) The current recordings for PA63 ion channels without and with EF present, respectively. (c) The instantaneous I–V relationship of PA63 channels in the absence (filled squares) and presence of EF. (d) LF also affects the I–V relationship of PA63 channels in an asymmetric manner. The concentration of LF was increased from zero to 160 pM. (e) The ratio of the ionic current in the presence of LF to that in its absence as a function of LF concentration for three different values of the applied potential. The solid line through the data is the result of a least-squares fit of an equation to the data that assumes 1 : 1 binding between LF and a PA63 channel and a 40 pM binding constant. (f) The I–V relationships of PA63 channels alone and in the presence of either a monoclonal antibody (1G3-1-1) or the mAb with and 3 nM LF are virtually identical.
which is also used to characterize the binding of LF and EF to PA63 , the electronic method provides a functional test of PA63 , LF, and EF. In addition, results can be obtained in minutes rather than in days as is required by cell-based methods.
5.3
Potential for High-throughput Screening of Therapeutic Agents against Anthrax
Another promising prospect includes identifying and screening compounds and/or antibodies that
16
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
disrupt toxin function or interaction.50 To test this hypothesis, we used a previously characterized monoclonal antibody (mAb), 1G3-1-1, which prevents the binding of LF to PA63 through steric hindrance.51 The mAb 1G3-1-1-neutralized LF toxin both in vivo and in vitro. Figure 15(f) demonstrates that the antibody had virtually no effect on the I –V relationship of the PA63 channel. However, it completely inhibited LF-induced blockade. The results suggest that the (PA63 )7 channel can function as a biosensor for rapidly screening anthrax therapeutics. Agents that bind to the PA63 channel or to either LF or EF and that do not cause current blockades by themselves would inhibit LF- or EF-induced rectification of the (PA63 )7 channel I –V relationship.
5.4
Detection of Anthrax Lethal Toxin from Infected Animals
The strikingly distinct and sensitive electrophysiological signature produced by the binding of LF and/or EF to PA63 suggests its application as a possible clinical diagnostic assay. Recent work provided evidence for this.50 The first study demonstrated that the anthrax lethal toxin complex is present as a complex in the serum of infected animals.50 Both the in vitro purified lethal toxin complex and the complex from the serum exhibited enzymatic activity. As the next step to show the potential of the method as a diagnostic tool, the anthrax lethal toxin complex was isolated from the serum of infected animals using size-exclusion chromatography. This process was necessary to prevent possible interference from cellular and bacterial proteins. Addition of a small aliquot of sample (purified in vivo (PA63 )7 :LF complex) containing only ∼30 pM initial LF concentration to the cis chamber with an applied potential of −50 mV resulted in the reconstitution of strongly rectifying nanopores. This strong rectification is seen not only in these samples from infected animals, but also with PA63 channels after the addition of LF and a purified (PA63 )7 :LF complex formed in vitro. These results suggest not only a clinical diagnostic biosensor, but also a sensitive assay that lends credence to previous results that showed complexed (PA63 )7 :LF is present in infected animals’ blood.
6 EMERGING TECHNOLOGIES 6.1
Planar Lipid Bilayer Technology: Limitations and Future Directions
The examples described in this chapter provide evidence that protein nanopores offer significant potential as components of biosensors. However, ion channels currently only function in lipid bilayer membranes, which currently are not a robust and practical matrix for real-world sensor applications. There are two approaches that might resolve this issue. First, channels have been reconstituted into membranes affixed to a gold electrode on a solid support. For example, Cornell and colleagues demonstrated a robust and functional gramicidin channel–based sensor system tethered to a solid support.52 That impressive method has yet to demonstrate single-channel activity in such matrices. Until then, detailed kinetic information inherent in the reversible binding of the analyte to the nanopore will be lost to population averaging. Second, the possibility of reconstituting single channels into membranes that can be hardened after the channels have formed has been explored. For example, it was recently shown that αHL and PA63 channels can be reconstituted into membranes formed by photopolymerizable lipids.53 In addition, upon exposure to UV light, the physical properties of those membranes (e.g., monolayer surface pressure and bilayer membrane specific capacitance) change, as one would expect if the lipids polymerize with their neighbors. Moreover, the function of single αHL channels is unaffected by the polymerization. However, it is not yet clear how robust these membranes are or even what fraction of the lipids are polymerized. These questions need to be addressed before polymerized lipids can be used as a stable platform for nanopore-based sensors.
6.2
Solid-state Nanopores
There are other methods being developed to make robust nanopores. Because lipid membranes are fragile, several groups are trying to determine if nanopores formed in synthetic solid materials can provide the functionality of ion channels. Several methods have been developed to
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
produce solid-state nanopores. In one technique, micrometer-thick plastic is bombarded with a weak α-particle beam. The substrate is then chemically etched to form a single pore that is nanometerscale in diameter at one end.54,55 However, these pores are micrometer scale in length, which limits their utility in some applications. More recently, Golovchenko’s group and others made nanometerscale pores in solid supports (e.g., silicon nitride) by etching a pit in the material on one side and then bombarding the opposite side with a carefully controlled ion beam.56–58 The hole is then “sculpted” to ∼2-nm diameter with an electron beam. These solid-state portals have demonstrated capability of detecting DNA molecules and should find their way into practical applications if the cost of producing the nanopores can be reduced.
6.3
17
and Technology (NIST) Advanced Technology Program, the NIST “Single Molecule Manipulation and Measurement” program, the National Science Foundation (NIRT grant CTS-0304062), the Medical Biological Defense Research Program, the US Army Medical Research Institute of Infectious Diseases (USAMRIID Research Plan 02-42C-012), the National Cancer Institute, National Institutes of Health, under contract N01-CO-1240, in part by the Developmental Therapeutics Program in the Division of Cancer Treatment and Diagnosis of the National Cancer Institute and the Defense Advanced Research Projects Agency. The identification of commercial materials and their sources is made to adequately describe the experimental results. This identification neither implies recommendation by the NIST or USAMRIID nor does it imply that the material is the best available.
Theory and Modeling of Nanopores
Theoretical analyses of polymer partitioning into simple model geometries are now providing valuable insight into the physics of DNA confinement in structures with biologically relevant length scales.35,59–61,62–74 Theory and simulation of how nanopores function and how analytes might react with them will clearly enable the rational design of nanopore-based sensors.
7 CONCLUSIONS
Proof of concept for nanopore-based detection and quantitation of a wide variety of analytes, including ions, polynucleotides, and lethal toxins, has been demonstrated. However, there are several barriers that need to be overcome to make single nanopores practical and useful in sensor applications. First, they need to be made robust. Second, for DNA sequencing applications, single nanopores need to better discriminate between closely similar polynucleotides. Both goals are within reach and will hopefully be demonstrated soon. ACKNOWLEDGMENTS
The work performed in our laboratories was supported in part by the National Institute of Standards
REFERENCES 1. L. Stryer, Biochemistry, 3rd Edn, W.H. Freeman, San Francisco, 1988. 2. B. Hille, Ionic Channels of Excitable Membranes, 2nd Edn, Sinauer Associates, Sunderland, 1992. 3. A. L. Hodgkin and A. F. Huxley, Currents carried by sodium and potassium ions through the membrane of the giant axon of Loligo. Journal of Physiology (London), 1952, 116, 449–472. 4. M. Leippe, J. Andra, and H. J. Mullereberhard, Cytolytic and antibacterial activity of synthetic peptides derived from amoebapore, the pore-forming peptide of entamoebahistolytica. Proceedings of the National Academy of Sciences of the United States of America, 1994, 91, 2602–2606. 5. A. Harris, Emerging issues of connexin channels: biophysics fills the gap. Quarterly Reviews of Biophysics, 2001, 34, 325–472. 6. M. Welsh, Cystic fibrosis. Scientific American, 1995, 273(6), 52–59. 7. S. M. Simon and G. Blobel, A protein-conducting channel in the endoplasmic reticulum. Cell, 1991, 65, 371–380. 8. R. V. Miller, Bacterial gene swapping in nature. Scientific American, 1998, 278(1), 66–71. 9. L. Z. Song, M. R. Hobaugh, C. Shustak, S. Cheley, H. Bayley, and J. E. Gouaux, Structure of Staphylococcal alpha-hemolysin, a heptameric transmembrane pore. Science (USA), 1996, 274, 1859–1866. 10. T. L. Nguyen, Three-dimensional model of the pore form of anthrax protective antigen. Structure and biological implications. Journal of Biomolecular Structure and Dynamics, 2004, 22, 253–266. 11. S. Bhakdi, R. Fussle, and J. Tranum-Jensen, Alpha-toxin of Staphylococcus aureus. Microbiological Research, 1991, 55, 733–751.
18
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
12. G. Menestrina, Ionic channels formed by Staphylococcus aureus alpha-toxin: voltage dependent inhibition by divalent and trivalent cations. The Journal of Membrane Biology, 1986, 90, 177–190. 13. O. Beckstein, P. C. Biggin, P. Bond, J. N. Bright, C. Domene, A. Grottesi, J. Holyoake, and M. S. P Sansom, Ion channel gating: insights via molecular simulations. FEBS Letters, 2003, 555, 85–90. 14. J. J. Kasianowicz, Nanopores. Flossing with DNA. Nature Materials, 2004, 3, 355–356. 15. S. M. Bezrukov and J. J. Kasianowicz, Current noise reveals protonation kinetics and number of ionizable sites in an open protein ion channel. Physical Review Letters, 1993, 70, 2352–2355. 16. J. J. Kasianowicz and S. M. Bezrukov, Protonation dynamics of the α-toxin ion channel from spectral analysis of pH dependent current fluctuations. Biophysical Journal, 1995, 69, 94–105. 17. J. J. Kasianowicz, D. L. Burden, L. Han, S. Cheley, and H. Bayley, Genetically engineered metal ion binding sites on the outside of a channel’s transmembrane β-barrel. Biophysical Journal, 1999, 76, 837–845. 18. S. M. Bezrukov, I. Vodyanoy, R. A. Brutyan, and J. J. Kasianowicz, Dynamics and free energy of polymers partitioning into a nanoscale pore. Macromolecules, 1996, 29, 8517–8522. 19. J. J. Kasianowicz, E. Brandin, D. Branton, and D. W. Deamer, Characterization of individual polynucleotide molecules using a membrane channel. Proceedings of the National Academy of Sciences of the United States of America, 1996, 93, 13770–13773. 20. S. G. A. McLaughlin, Electrostatic potentials at membrane-solution interfaces. Current Topics in Membranes and Transport, 1977, 9, 71–144. 21. M. Misakian and J. J. Kasianowicz, Electrostatic influence on ionic current through the α-HL ion channel. The Journal of Membrane Biology, 2003, 195, 137–146. 22. D. E. Goldman, Potential, impedance, and rectification in membranes. The Journal of General Physiology, 1943, 27, 37–60. 23. A. L. Hodgkin and B. Katz, The effect of sodium ions on the electrical activity of the giant axon of the squid. The Journal of Physiology (London), 1949, 108, 37–77. 24. G. Feher and M. Weissman, Fluctuation spectroscopy: determination of chemical reaction rates from the frequency spectrum of fluctuations. Proceedings of the National Academy of Sciences of the United States of America, 1973, 70, 870–875. 25. L. J. deFelice, Membranes and Current Noise, Plenum Press, New York, 1989. 26. S. Machlup, Noise in semiconductors: spectrum of a two-parameter random signal. Journal of Applied Physics, 1954, 25, 341–343. 27. O. V. Krasilnikov, R. Z. Sabirov, V. I. Ternovsky, P. G. Merzliak, and J. N. Muratkodjaev, A simple method for the determination of the pore radius of ion channels in planar bilayer membranes. FEMS Microbiology Immunology, 1992, 105, 93–100. 28. O. V. Krasilnikov, Sizing Channels with Neutral Polymers, in NATO Advanced Research Workshop. Structure and
29.
30. 31.
32.
33.
34.
35.
36.
37.
38. 39.
40.
41. 42.
43.
44.
Dynamics of Confined Polymers, J. J. Kasianowicz, M. S. Z. Kellermayer, and D. W. Deamer (eds), Kluwer Press, Dordrecht, 2002, pp. 97–115. S. Kuga, Pore size distribution analysis of gel substances by size exclusion chromatography. Journal of Chromatography, 1981, 206, 449–461. A. Einstein, Investigations on the Theory of Brownian Movement, Dover Press, New York, 1956. S. E. Henrickson, M. Misakian, B. Robertson, and J. J. Kasianowicz, Driven asymmetric DNA transport in a nanometer-scale pore. Physical Review Letters, 2000, 85, 3057–3060. M. Akeson, D. Branton, J. J. Kasianowicz, E. Brandin, and D. W. Deamer, Microsecond time-scale discrimination between polycytidylic acid and polyadenylic acid segments within single RNA molecules. Biophysical Journal, 1999, 77, 3227–3233. J. J. Kasianowicz, S. E. Henrickson, M. Misakian, H. H. Weetall, B. Robertson, and V. Stanford, Physics of DNA Threading Through a Nanometer Pore and Applications to Simultaneous Multianalyte Sensing, in NATO Advanced Research Workshop. Structure and Dynamics of Confined Polymers, J. J. Kasianowicz, M. S. Z. Kellermayer, and D. W. Deamer (eds), Kluwer Press, Dordrecht, 2002, pp. 141–163. M. Prashant and R. K. Lal, The dnaSET: a novel device for single-molecule DNA sequencing. IEEE Transactions on Electron Devices, 2004, 51, 2004–2012. M. Muthukumar, Theory of sequence effects of DNA translocation through protein and nanotubes. Electrophoresis, 2002, 23, 1417–1420. J. Lagerqvist, M. Zwolak, and M. Di Ventra, Fast DNA sequencing via transverse electronic transport. condmat/0601394. Nano Letters, 2006 6, 779–782. W. Vercoutere, S. Winters-Hilt, H. Olsen, D. Deamer, D. Haussler, and M. Akeson, Rapid discrimination among individual DNA hairpin molecules at single-nucleotide resolution using an ion channel. Nature Biotechnology, 2001, 19, 248–252. J. Kling, Ultrafast DNA sequencing. Nature Biotechnology, 2003, 21, 1425–1427. S. Winters-Hilt, W. Vercoutere, V. S. DeGuzman, D. Deamer, M. Akeson, and D. Haussler, Highly accurate classification of Watson-Crick base pairs on termini of single DNA molecules. Biophysical Journal, 2003, 84, 967–976. V. M. Stanford and J. J. Kasianowicz, Transport of DNA Through a Single Nanometer-Scale Pore: Evolution of Signal Structure, IEEE Workshop on Genomic Signal Processing and Statistics, Baltimore, 2004. M. Zwolak and M. Di Ventra, Electronic signature of DNA nucleotides. Nano Letters, 2005, 5, 421–424. J. J. Kasianowicz, S. E. Henrickson, H. H. Weetall, and B. Robertson, Simultaneous multianalyte detection with a nanopore. Analytical Chemistry, 2001, 73, 2268–2272. A. J. Viterbi, Error bounds for convolutional codes and an asymmetrically optimum decoding algorithm. IEEE Transactions on Information Theory, 1967, IT-13, 260–267. V. Stanford and J. J. Kasianowicz, Using HMMs to quantify signals from DNA driven through a nanometer-scale pore, Workshop on Genomic Signal
DETECTION AND CHARACTERIZATION OF IONS, DNA, AND PROTEINS
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
Processing and Statistics (GENSIPS), Raleigh, NC, 2002, CP1-03. L. Baum, An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process. Inequalities, 1972, 3, 1–8. R. Redner and H. Walker, Mixture densities, maximum likelihood and the EM algorithm. SIAM Review, 1984, 26, 195–239. S. H. Chung, J. B. Moore, L. Xia, L. S. Premkumar, and P. W. Gage, Characterization of single channel currents using digital signal processing techniques based on Hidden Markov models. Philosophical Transactions of the Royal Society of London Series B: Biological Sciences, 1990, 329, 265–285. S.-H. Chung and P. W. Gage, Signal Processing Techniques for Channel Current Analysis Based on Hidden Markov Models. in Methods in Enzymology: Ion Channels, Part B, P. M. Conn (ed), Academic Press, New York, 1998. P. Ascenzi, P. Visca, G. Ippolito, A. Spallarossa, M. Bolognesi, and C. Montecucco, Anthrax toxin: a tripartite lethal combination. FEBS Letters, 2002, 531, 384–388. K. M. Halverson, R. G. Panchal, T. L. Nguyen, R. Gussio, S. F. Little, M. Misakian, S. Bavari, and J. J. Kasianowicz, Asymmetric blockade of anthrax protective antigen ion channel by lethal factor: anthrax therapeutic sensor. The Journal of Biological Chemistry, 2005, 280, 34056–34062. S. F. Little, J. M. Novak, J. R. Lowe, S. H. Leppla, Y. Singh, K. R. Klimpel, B. C. Lidgerding, and A. M. Friedlander, Characterization of lethal factor binding and cell receptor binding domains of protective antigen of Bacillus anthracis using monoclonal antibodies. Microbiology, 1996, 142, 707–715. B. A. Cornell, V. L. BraachMaksvyti, L. G. King, P. D. J. Osman, B. Raguse, L. Wieczorek, and R. J. Pace, A biosensor that uses ion-channel switches. Nature (London), 1997, 387, 580–583. D. K. Shenoy, W. Barger, A. Singh, R. G. Panchal, M. Misakian, V. M. Stanford, and J. J. Kasianowicz, Functional reconstitution of ion channels in polymerizable lipid membranes. Nano Letters, 2005, 5, 1181–1185. T. K. Rostovtseva, C. L. Bashford, G. M. Alder, G. N. Hill, C. McGiffert, P. Y. Apel, G. Lowe, and C. A. Pasternak, Diffusion through narrow pores: movement of ions, water and nonelectrolytes through track-etched PETP membranes. Journal of Membrane Biology, 1996, 151, 29–43. Z. Siwy and A. Fulinski, Fabrication of a synthetic nanopore ion pump. Physical Review Letters, 2002, 89, 198103. J. Li, D. Stein, C. McMullan, D. Branton, M. J. Aziz, and J. A. Golovchenko, Ion-beam sculpting at nanometre length scales. Nature (London), 2001, 412, 166–169. A. J. Storm, J. H. Chen, X. S. Ling, H. W. Zandbergen, and C. Dekker, Electron-beam-induced deformations of SiO2 nanostructures. Journal of Applied Physics, 2005, 98, 014307. J. B. Heng, C. Ho, T. Kim, R. Timp, A. Aksimentiev, Y. V. Grinkova, S. Sligar, K. Schulten, and G. Timp,
59.
60.
61.
62.
63.
64. 65.
66.
67.
68.
69. 70.
71.
72.
73. 74.
19
Sizing DNA using a nanometer-diameter pore. Biophysical Journal, 2004, 87, 2905–2911. A. Aksimentiev, J. B. Heng, G. Timp, and K. Schulten, Microscopic kinetics of DNA translocation through synthetic nanopores. Biophysical Journal, 2004, 87, 2086–2097. M. Muthukumar, Modeling of polynucleotide translocation through protein pores and nanotubes. Electrophoresis, 2002, 23, 2697–2703. E. Slonkina and A. B. Kolomeisky, Polymer translocation through a long nanopore. Journal of Chemical Physics, 2003, 118, 7112–7118. W. Sung and P. J. Park, Polymer translocation through a pore in a membrane. Physical Review Letters, 1996, 77, 783–786. D. K. Lubensky and D. R. Nelson, Driven polymer translocation through a narrow pore. Biophysical Journal, 1999, 77, 1824–1838. M. Muthukumar, Polymer translocation through a hole. Journal of Chemical Physics, 1999, 111, 10371–10374. P. deGennes, Passive entry of a DNA molecule into a small pore. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96, 7262–7264. K. K. Kumar and K. L. Sebastian, Adsorption-assisted translocation of a chain molecule through a pore. Physical Review E, 2000, 62, 7536–7539. K. L. Sebastian and A. K. R. Paul, Kramers problem for a polymer in a double well. Physical Review E, 2000, 62, 927–939. M. Muthukumar, Translocation of a confined polymer through a hole. Physical Review Letters, 2001, 86, 3188–3191. S. K. Lee and W. Sung, Barrier crossing of a semiflexible ring polymer. Physical Review E, 2001, 64, 041801. C. Y. Kong and M. Muthukumar, Modeling of polynucleotide translocation through protein pores and nanotubes. Electrophoresis, 2002, 23, 2697–2703. W. Sung and P. J. Park, The polymer barrier problem, In: NATO Advanced Research Workshop, Structure and Dynamics of Confined Polymers, Kluwer Press. Eds. J. J. Kasianowicz, M. S. Z. Kellermayer, and D. W. Deamer. pp. 261–280. Dordrecht, The Netherlands. 2002. A. Troisi, A. Nitzan, and M. A. Ratner, A rate constant expression for charge transfer through fluctuating bridges. Journal of Chemical Physics, 2003, 119, 5782–5788. M. Muthukumar, Polymer escape through a nanopore, Journal of Chemical Physics, 2003, 118, 5174–5184. C. Y. Kong and M. Muthukumar, Polymer translocation through a nanopore. II. Excluded volume effect. Journal of Chemical Physics, 2004, 120, 3460–3466.
FURTHER READING L. E. Baum and T. Petrie, Statistical inference for probabilistic functions of finite state Markov chains. Annals of Mathematical Statistics, 1966, 37, 1559–1563. R. Blaustein and A. Finkelstein, Voltage-dependent block of anthrax toxin channels in planar phospholipid bilayer membranes by symmetric tetraalkylammonium ions. The Journal of General Physiology, 1990, 96, 905–919.
20
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
B. Katz, Nerve, Muscle, and Synapse, McGraw-Hill, New York, 1966. X.-M. Wang, R. Wattiez, M. Mock, P. Falmagne, J.-M. Ruysschaert, and V. Cabiaux, Structure and interaction of PA63 and EF (edema toxin) of Bacillus anthracis with lipid membrane. Biochemistry, 1997, 36, 14906–14913.
L. Xu and M. Jordan, On convergence properties of the EM algorithm for Gaussian mixtures. Neural Computation, 1996, 8, 129–151. S. Zhang, E. Udho, Z. Wu, R. J. Collier, and A. Finkelstein, Protein translocation through anthrax toxin channels formed in planar lipid bilayers. Biophysical Journal, 2004, 87, 3842–3849.
51 Conducting Polymer Nanowire-Based Biosensors Adam K. Wanekaya,1 Wilfred Chen,2 Nosang V. Myung2 and Ashok Mulchandani2 1
Chemistry Department, Missouri State University, Springfield, MO, USA and 2 Department of Chemical and Environmental Engineering and Center for Nanoscale Science and Engineering, University of California, Riverside, CA, USA
1 INTRODUCTION
Conducting polymer nanowires (CP NWs) are part of one-dimensional (1D) nanostructured materials that include materials such as nanotubes, nanosprings, nanobelts, and other nanowires. These materials are the smallest-dimension structures that can be used for efficient transport of electrons and are thus critical to the function and integration of high-density nanoscale devices. Consequently, they are the focus of intensive research in sensing, optoelectronics, and other applications due to their unique properties. Because of their high surface-to-volume ratio and tunable electron transport properties due to quantum confinement effect, their electrical properties are strongly influenced by minor perturbations. This property provides an avenue for the much desired rapid, label-free, and direct electrical detection to the point that single-molecule detection is possible. The advantages of labelfree detection include a simple homogenous assay format without separation and washing and rapid near-real-time response. This has the potential to impact biological research as well as screening in medical, environmental, and homeland security applications.
Field effect transistor (FET)-type devices have many advantages such as small size and weight, fast response, high reliability, and on-chip integration with low-cost mass production. Basically, a FET consists of two electrodes, a source and a drain, connected by a semiconducting channel. The current can flow through the semiconductor only when appropriate voltage is applied to the gate electrode. The modulation of the applied gate potential has a tremendous effect on the conductivity of the semiconducting channel. This phenomenon can thus be used to amplify electrical signals resulting from the interaction of charged species with the semiconducting channel. The dependence of the conductance on gate voltage makes FETs natural candidates for electrically based sensing. Although the concept of sensing with FETs was introduced several decades ago, the limited sensitivity of planar devices precluded them from having a large impact. FETs based on 1D nanostructures are based on a similar framework but are more sensitive because, unlike planar FETs, they avoid the reduction in conductance changes caused by lateral current shunting. When used as the gate of a FET device, 1D nanostructures offer significant advantages over 2D thin-film planar gates. First, binding
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
to the surface of 1D nanostructures can lead to depletion or accumulation of carriers in the “bulk” of the nanometer-diameter structure versus only the surface region of a planar device, giving rise to large resistance/conductance changes, to the point that single-molecule detection is possible. Second, the direct conversion of chemical information into an electronic signal can take advantage of the existing microelectronic technology and lead to miniaturized sensor devices. Third, the sizes of biological molecules (BM), such as proteins and nucleic acids are comparable to nanoscale building blocks. Therefore, any interaction between such molecules should induce significant changes in the electrical properties of 1D nanostructures. Finally, the small size of the nanostructures makes development of high-density arrays of individually addressable nanostructures for simultaneous analysis of different substances possible. Also, 1D nanostructures, such as CP NWs are extremely attractive for nanoelectronics because they can function both as devices and as the wires that access them. Until recently the advancement of 1D nanostructures was slow because of the difficulties associated with the synthesis and fabrication of these nanostructures with well-controlled dimensions, morphology, phase purity, and chemical composition. Three classes of 1D nanostructured materials namely carbon nanotubes (CNTs), silicon nanowires (Si NWs), and lately CP NWs have shown profound performance in device fabrication in general and in label-free detection technology in particular. A major advantage of conducting polymers (CPs) is that they can be functionalized before polymerization, during polymerization, and after polymerization. This makes them very flexible materials because optimal conditions can be used for each step, to obtain optimum polymer conductivity and orientation of the functionalized moiety. Also, the conductivities of CPs can be modulated up to 15 orders of magnitude by changing the dopant and monomer/dopant ratios. It has been further demonstrated that their conductivity can be further modulated by controlling their oxidation state. In this chapter we discuss the fabrication, functionalization, and the sensing applications based on CP NWs. We highlight the successes and limitations of various methods from different laboratories and how we and other researchers have
attempted to address these limitations. We conclude by outlining some successes and challenges that are associated with the CP NWs.
2 FABRICATION OF CP NWS
CP NWs can be fabricated by a variety of methods including lithography, mechanical stretching, electrospinning, template-directed synthesis, and templateless alignment methods. Whatever the method, a good fabrication procedure should enable the simultaneous control of morphology, dimensions, and properties. The objective of this section is to highlight some of the methods that have been used in the fabrication of CP NWs.
2.1
Electrospinning
This method was originally developed for generating ultrathin polymer fibers.1 It uses electrical forces to produce polymer fibers with nanometerscale diameters. A microfabricated scanned tip is used as an electrospinning source. The tip is dipped in a polymer solution to gather a droplet. A voltage applied to the tip causes the formation of a Taylor cyclone, and at sufficiently high voltages, a polymer jet is extracted from the droplet. By moving the source relative to a surface that acts as a counter electrode, oriented nanofibers can be deposited and integrated with microfabricated surface structures. The morphology of the fibers depends on the solution concentration, applied electric strength, and the feeding rate of the precursor solution. Uniform nanofiber depositions have thus been fabricated by the electrospinning method.2–5
2.2
Lithography
CP NWs can also be fabricated by lithographic methods. The major advantage of this method is the fact that CPs can be precisely patterned based on different lithographic principles. For example, dip-pen nanolithography (DPN) is a scanning probe nanopatterning technique in which an atomic force microscope (AFM) tip is used to deliver
CONDUCTING POLYMER NANOWIRE-BASED BIOSENSORS
molecules to a surface via a solvent meniscus. The ionically charged CPs are used as the “ink” on oppositely charged substrates providing a significant driving force for the generation of stable patterns on substrates. Using this technique, polyaniline,6 polypyrrole (PPY),6 and poly(3,4ethylenedioxythiophene)7 nanowire lines down to 310-, 290-, and 30-nm widths, respectively, have been reported. Recently, Fuchs and coworkers demonstrated the lithographic fabrication of CP NW patterns by a copolymer strategy.8 In the first step of the procedure, a pattern is defined on a photoresist using e-beam lithography. Second, a copolymer film is deposited by the chemical oxidation of the appropriate monomers. Finally, the resist is lifted-off leaving patterns of CP NWs as shown in Figure 1.
2.3
Mechanical Stretching
CPs are electrochemically polymerized on a scanning tunneling microscope (STM) tip that is insulated except for a few square nanometers, thus localizing the growth of the polyaniline (PANI)
100 nm
Figure 1. A 100-nm-wide PPY NW bridging the ends of two PPY microelectrodes. [Reprinted with permission Dong et al.8 copyright 2005, Wiley VCH.]
3
NW at the tip end. After the formation of the CP NW, the diameter of the nanowire may be further reduced by stretching it with the STM tip. A highly conductive PANI NW with a diameter of about 20 nm has been fabricated using this method.9
2.4
Template-directed Methods
This method entails the synthesis of the desired material within the pores of a nanoporous template membrane. The membranes employed have cylindrical pores of uniform diameter. Porous anodic aluminum oxide (AAO), track-etched polymer membranes, and mica are the three types of membranes that are commonly used. The templatedirected method is an attractive procedure in the fabrication of CP NWs. The CP NWs may be synthesized within the pores by chemical or electrochemical deposition procedures.10,11 Electrochemical deposition is accomplished by coating one face of the template with an inert conducting material and using it as the anode. The template is then suspended in a solution containing the appropriate monomer and dopant. Application of electric current on the template induces anodic polymerization of the monomer within the template pores to form CP NWs. The length of the nanowires is determined by the current density and deposition time. The diameter of the nanowire is determined by the pore diameter of template. Chemical template synthesis can be similarly accomplished by simply immersing the template into a solution of the desired monomer and its oxidizing agent. Following the CP NW deposition, the inert conducting film is dissolved using appropriate acids or bases. Organic solvents may be used to dissolve polymer templates. DNA has also been used as a template in the assembly and polymerization of aniline to form PANI nanowires. For example, He and coworkers12 synthesized polyaniline nanowires by stretching, aligning, and immobilizing doublestranded λ-DNA on a thermally oxidized Si chip by the molecular combing method.13,14 Then the DNA templates were incubated in protonated aniline monomer solution to emulsify and organize the aniline monomers along the DNA chains. Finally, the aligned aniline monomers were polymerized enzymatically by adding horseradish peroxidase (HRP) and H2 O2 successively to form
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
polyaniline/DNA nanowires. Simmel and coworkers also synthesized polyaniline nanowires templated by DNA using three methods.15 They found that DNA templating worked best for polyaniline formed by oxidative polymerization of aniline with ammonium persulfate, both in solution and on templates immobilized on a chip. DNA was also a good template for polyaniline formed by enzymatically catalyzed polymerization utilizing HRP. However, immobilization of these structures between contact electrodes was compromised by extensive protein adsorption to the surface.
2.5
Templated Polymerization within Lithographically Defined Nanoscale Channels
Recently, template polymerization within lithographically defined nanoscale channels has proved to be very attractive in the fabrication of CP NWs16,17 and CP nanoribbons.18 The nanoscale channels have built-in electrical contacts that enable the application of electrical potentials for
Acc.V Spot 10.0 kV 3.0
Magn 30000x
Det SE
WD 21.2
polymerization of the monomers within the channels. The built-in electrical contacts thus remain and become interconnects to the array components. This procedure avoids the harsh and cumbersome template dissolution processes that are necessary in the conventional template-directed polymerization and are thus not suitable for biological applications. Further, any postsynthesis manipulation and electrical contacting processes that are required in the conventional template-directed polymerization are not necessary. Figure 2 shows a scanning electron microscope (SEM) image of a 100-nm-wide and 3-µm-long PANI NW grown within lithographically defined nanoscale channels. The nanowire was continuous, well defined, and dendrite-free and exhibited precise dimensionality. The ability to fabricate individually addressable nanowires with a high aspect ratio was demonstrated by synthesizing two 200-nm-wide by 2.5-µm-long PPY NWs (Figure 3). A complementary approach to the ones reported above is based on CP nanojunctions formed by bridging two electrodes separated with a gap of 1–100 nm.19 The gap between the electrodes is
2 µm
Figure 2. SEM image of a 100-nm-wide by 3-µm-long PANI nanowire. [Reprinted with permission from Ramanathan et al.16 2004 American Chemical Society.]
CONDUCTING POLYMER NANOWIRE-BASED BIOSENSORS
5
Polymer
Anode (−)
Cathode (+)
Gold pads 1 µm
Anode (−)
Cathode (+)
PPY nanowires gn 00x
Det SE
WD 16.5
10 µm
Figure 3. SEM image of two 200-nm-wide by 2.5-µm-long PPY nanowires separated by 10 µm, deposited one at a time. [Reprinted with permission from Ramanathan et al.16 2004 American Chemical Society.]
reduced down to ∼1 nm by first electrochemically depositing Au onto the electrodes thus causing an increase in the current flowing across the gap due to quantum tunneling effect. Au atoms may be etched away from the electrodes to optimize the gap by taking advantage of the reversibility of the electrochemical process. The gaps are then bridged with CPs by the cycling potential of the nanoelectrodes in solutions of the corresponding monomers (Figure 4). However, unlike the polymerization within lithographically defined nanoscale channels, the length-to-width ratio of the nanojunction is not well defined and controlled and the aspect ratio is small. On the other hand, since the conductance path is much smaller, the nanojunction approach is particularly suitable for poorly conducting polymers or polymers that loose much of their conductivity upon attachment of receptor groups.
2.6
Templateless Polymerization of Aligned CP NWs
To date, template-directed polymerization using porous membranes has been the most preferred method for the fabrication of oriented CP NWs.
Figure 4. SEM image of polyaniline-polyacrylic acid films deposited on gold pads with 20–60 nm gaps. [Reprinted with permission from Forzani et al.19 2004 American Chemical Society.]
However, there have been reports that oriented 1D nanostructure CP structures could only be obtained for wires or rods with a large diameter.20 Dissolution of the membrane supports for CP NWs with a diameter of less than 100 nm caused the nanowires to collapse without preferred orientation.20 As a means of solving this problem, some researchers have devised a method of direct templateless electropolymerization of large arrays of oriented CP NWs with a diameter much smaller than 100 nm. This technique involves a three-step electrochemical deposition procedure where a high current density is applied in the first step followed by the application of reduced current densities in the subsequent steps.21,22 The hypothesis is that at high current densities, CP nanoparticles are formed that are then used as nucleation sites to grow the extended CP NWs at reduced current densities in the second and third steps. A similar technique has been used for the fabrication of CP NW junction arrays.23
3 FUNCTIONALIZATION OF CP NWS
Functionalization of CP NWs is often necessary for their functionality and biocompatibility. Therefore, the interface between BM and CP NWs is critical because the unique electrical properties of these nanoscale materials when utilized in conjunction with the remarkable biomolecular recognition capabilities, could lead to miniature bioelectronic devices. The ultimate goal in functionalization is to retain, as much as possible, the properties of the biological molecule and the CP
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
NW. The biological molecule should be stable and should be able to retain its biorecognition properties. Most of the research in the functionalization of CPs has been based on thin films. However, the same techniques should also be applicable in the functionalization of CP NWs. The functionalization of CPs can be carried out in three ways: before, during, and after the polymerization process. The fourth procedure is an entrapment technique where the target material is immobilized during the polymerization processes. These processes are summarized in Scheme 1 with pyrrole as the model monomer. The first technique involves the covalent linkage of a specific biological molecule to the starting monomer prior to electropolymerization. This method is good only if the biological molecule is stable during polymerization. Good applications of this procedures include the fabrication of a peptide chip by the electro-copolymerization of pyrrole and pyrrole-peptide, 24 the electropolymerization of oligonucleotide (ODN)-functionalized pyrrole,25–27 and the electropolymerization of N-biotinylated pyrrole.28,29 The disadvantage of N-substituted pyrroles is the slower rate of polymerization and a marked drop in the conductivity of the polymer matrix due to nonplanarity of the PPY chain induced by the substituents. An alternative to the N-substitution is derivatization of the pyrrole ring in the 3 or 4 position, which normally requires lower anodic potentials and exhibits higher conductivities.30 The second route involves the specific incorporation of target molecules as dopants during the electropolymerization procedure. Therefore, functionalization is achieved by the irreversible capture of a negatively charged target molecule within the polymer matrix. A good example is the recent demonstration of the incorporation of PPY NWs with CNTs via a template-directed procedure.31 The negatively charged CNTs acted as dopants and served as charge-balancing counterions. It was further demonstrated that BM could be easily adsorbed on the CNTs prior to polymerization.32,33 Such simultaneous incorporation of CNTs and BM impart electrocatalytic and biocatalytic properties, respectively, thus improving the sensing performance. BM have also been similarly incorporated into PPY in the absence of supporting electrolyte.34 The third procedure is often termed as postpolymerization functionalization. In this case, the
functionalization with the biological molecule is performed after the polymerization. An appropriate functional group in the polymer is allowed to covalently bind to another functional group of the targeted biological molecule. This approach, therefore, requires the synthesis of CPs having reactive entities that are used as anchoring points to graft the appropriate functional groups on the biological molecule. The major advantage of this sequential procedure is the possibility of using optimal conditions for each step to obtain optimum polymer conductivity and precise localization and orientation of the biological molecule. A good example is the recent postpolymerization functionalization of PPY films with biotin entities.35 In this case, the β-ferrocene ethylamine used as redox probe was immobilized via a coupling reaction on the surface of a preformed PPY film bearing activated ester groups onto which biotin entities were immobilized. Other examples include ODN immobilization by postfunctionalization of PPY-bearing easy leaving groups36 and PPY-bearing carboxylic acid groups that enable easy covalent binding to biomolecules.37 The fourth procedure involves entrapment of target molecule within CPs. It involves the electropolymerization of the monomer in a solution containing the dopant and the target biomolecule. The major advantage of this procedure is that entrapment of the biomolecules occurs without any chemical reaction that could affect the activity of the biological molecule. Also, previous functionalization of the biological molecule by specific labels via chemical modification and genetic engineering is not necessary. Disadvantages associated with this procedure include the possibility of reduced accessibility, catalytic activity, and flexibility of the biological molecule as a result of random immobilization and steric hindrances within the CP matrix.38,39 We have successfully used this procedure to entrap avidin within the matrix of a 100-nm-wide PPY NW. In this process, avidin was entrapped during the electropolymerization of PPY NW in a solution containing an avidin-conjugated quantum dot, the pyrrole monomer dopant in a single step within lithographically defined nanoscale channels (Figure 5a).17 The immobilization of the avidin was confirmed by energy dispersive X-ray (EDX) spectrum analysis of the PPY which showed the presence of a Cd peak in the PPY entrapped with the avidin-conjugated quantum dot and no Cd peak in the control sample (Figure 5b
N H
Example: Ref. 36
ODN
H N O
∗ n
B M
ODN-NH2
∗
H N
O
O N
H N
N
(CH2)n
H N
O
O
∗ n
∗
n
H N
HOOC
R
H N
n
B M
R
H N
n
∗ (CH2)n BM NH CO
H N
Examples: Ref. 16,17,40
H N
Example: Ref. 37
EDC
n
Examples: Ref. 28,29
∗ BM-NH ∗ 2 (CH2)n
n
Copolymerization with 3-alkyl-4-carboxylated PY
BM entrapment in the presence of electrolyte
Copolymerization with PY containing easy leaving groups
Incorporation of BM as a dopant in the absence of electrolyte
n
BIOTIN
Polymerization
n
Scheme 1. Polymerization of conducting polymer with pyrrole as the model monomer. BM: biomolecule; EDC: 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide; ODN: oligonucleotide; PY: pyrrole
∗
H N
Examples: Refs 31−34
H N
Biotinylated BM
N
Avidin
(CH2)n
N
N
BIOTIN
(CH2)n
BIOTIN
(CH2)n
BIOTIN
AVIDIN
AVIDIN
Biotinylated Bm
CONDUCTING POLYMER NANOWIRE-BASED BIOSENSORS 7
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS Silicon Cd peak
Carbon Oxygen Gold
Sodium
Chlorine 0.4
1
1.6
2.2
2.8
Cadmium 3.4
4.1
Energy values (b) Silicon No Cd peak 200 nm
Gold
Carbon Oxygen Sodium
Chlorine 0.3 (a)
0.9
1.5
2.1
2.7
3.3
3.9
Energy values (c)
Figure 5. (a) SEM image of an Aqd-embedded polypyrrole nanowire (200-nm wide). The EDX analysis of polypyrrole nanowire with (b) and without (c) avidin-conjugated quantum dot. [Reprinted with permission from Ramanathan et al.17 2005 American Chemical Society.]
and 5c). AFM phase imaging analysis further confirmed the presence of avidin on the polymer surface (Figure 6). The higher contrast on the avidin-functionalized PPY surface compared with the control PPY reflected the difference in variation and hardness in the two polymers due to the presence of quantum dots that were conjugated to avidin. Similarly, Mallouk and coworkers recently reported the fabrication of gold-capped, avidin-entrapped PPY NWs using the conventional template-directed electrochemical deposition.40 Finally, the emerging technique of imprinting CP NW with BM is very promising.41,42 In this procedure, the imprint molecule may be immobilized on the pore walls of silica-treated nanoporous alumina membranes followed by the template-directed CP NW deposition.42 The alumina membranes are then dissolved leaving the CP NWs with biological molecule binding sites on the surface. This technique may be a good alternative to the immobilization of bioreceptors for affinity sensor development. However, the use
of electropolymerized molecularly imprinted polymers for sensor development is still very young.
4 ASSEMBLY/ALIGNMENT OF CP NWS
Alignment of CP NWs into practical, functional sensors is sometimes necessary depending on the method that was used for their fabrication. For example CP NWs fabricated via templatedirected synthesis and electrospinning methods require some kind of alignment/assembly procedures to form functional sensor devices. In principle, procedures that have been used in the alignment of other 1D nanostructures like CNTs and Si NWs can potentially be used in the alignment of CP NWs. For example, capping CP NWs with nickel ends and using applied magnetic field to orient and align between nickel electrodes as was recently demonstrated for other 1D nanostructures materials.43,44 Tao and coworkers demonstrated a magnetic-field-assisted method to assemble an
CONDUCTING POLYMER NANOWIRE-BASED BIOSENSORS
0
500 nm Data type Z range
0
500 nm
Phase 60.00°
(a)
9
Data type Z range
Phase 60.00°
(b)
Figure 6. AFM phase images for (a) PPY and (b) PPY with avidin-conjugated quantum dots. [Reprinted with permission from Ramanathan et al.17 2005 American Chemical Society.]
5 SENSING APPLICATIONS BASED ON CP NWS
Figure 7 presents the real-time responses of avidinfunctionalized PPY NW to different concentration of biotin conjugated to a 20-mer DNA oligonucleotide, elucidating the application of biologically
150
Concentration (nM) ∆R /R (%)
−3 13 50 54
0 1 100 1000
Injection 100 ∆R /R (%)
array of electrically wired CP junctions.45 An aqueous solution containing CP-coated Au/Ni/Au metallic bars was introduced onto an array of parallel microelectrodes. In the presence of a magnetic field, the polymer-coated magnetic bars are aligned perpendicular to the microelectrodes, thus enabling metal/polymer/metal junctions between the two microelectrodes. On the other hand, some CP NW fabrication methods totally avoid the alignment process altogether. Good examples are the template-directed synthesis within lithographically defined nanoscale channels,16,17 dip-pen lithography,6,7 other lithographic methods,8 and some forms of templateless polymerization.23
(c) 50 (b) (a)
0 0
50
100
150
Time (s)
Figure 7. Electrical responses of an unmodified nanowire (a) to 100 nM biotin-DNA (single stranded) and avidin-embedded polypyrrole (200 nm) nanowires to 1 nM (b) and 100 nM (c) biotin-DNA. The responses were recorded on two separate polypyrrole-avidin nanowires. Polypyrrole nanowires containing entrapped avidin were grown using 25 nM pyrrole in 10 mM NaCl and avidin. [Reprinted with permission from Ramanathan et al.17 2005 American Chemical Society.]
functionalized CP NWs for label-free sensing.17 The sensing was very rapid and concentrations
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS 1.1
8
PANI
0.7 0.6
558 nM 2.46 µM
0.5 200
400
6 5
58.8 nM
0
1.7 mM 1.7 mM 1.6 mM 1.5 mM
52 pM 650 pM 0.2 nM
600
800 1000 1200
4 3 2
1.8 mM
0.8
7 PANI-Gly-Gly-Hls
Isd (nA)
Normalized Isd
1 0.9
Time (s)
of biotin-DNA of up to 1 nM were detected in a few seconds. Similar response was observed with anti-avidin IgG. A sensitivity of potentially singlemolecule detection is possible by adjusting the nanowire’s conductivity to a value closer to the lower end of a semiconductor. Another demonstration of label-free sensing using biologically functionalized CPs was given by Tao, where a polyaniline nanojunction functionalized with gly–gly–his, hexa-his, and glucose oxidase (GOx) was used for the detection of Cu2+ , Ni2+ (Figure 8),46 and glucose (Figure 9),19 respectively. While the former involved a label-free detection due to the interaction of the metal ions with the peptidefunctionalized polyaniline nanojunction, the detection of glucose involved its catalytic oxidation by the enzyme followed by the reoxidation of the GOx by O2 in solution, which produces H2 O2 . The H2 O2 then oxidized polyaniline, thus triggering an increase in the polyaniline conductivity. The increase in polyaniline conductivity constituted the analytical signal. Owing to the small size of the nanojunction sensor, the GOx was regenerated naturally without the need of redox mediators. Therefore, responses were very fast (<200 ms) and a minimal amount of oxygen was consumed. 6 SUMMARY AND OUTLOOK
Compared to other 1D nanostructured materials like Si NWs and CNTs, CP NWs are relatively new in the chemical and biosensing arena. However,
1.9 mM
1 Figure 8. Simultaneous monitoring of the time course of normalized drain current (Isd ) on peptide-functionalized PANI (poly(GGH-ANI)) and regular PANI nanojunctions at drain potential (Vsd ) of 0.4 V upon the injection of Cu(NO3 )2 solutions. Numbers indicate Cu2+ final concentrations. [Reused with permission from Alvaro D´iaz Aguilar et al.46 2005.]
0 0
300
600
900
1200
1500
1800
Time (s) Figure 9. Time course of drain current (Isd ) at a gate voltage of 35 mV versus SCE (drain voltage = −20 mV) for PANi/GOx nanojunction in McIlvaine’s buffer upon successive additions of 40 mM of glucose. [Reprinted with permission from Forzani et al.19 2004 American Chemical Society.]
they offer distinct and very attractive advantages compared to other 1D nanostructured materials. For example, CP NWs can easily be synthesized using benign reagents at ambient conditions through well-known chemical and electrochemical procedures. Their conductivities can be modulated by up to 15 orders of magnitude by changing the dopant and monomer/dopant ratios. They can be functionalized before, during, and after synthesis. Also functional BM can be incorporated into the CP NWs in a one-step procedure within built-in electrical contacts thus avoiding the cumbersome alignment and positioning manipulations. These are major advantages of CP NWs over other 1D nanostructured materials like Si NWs and CNTs. One of the disadvantages of CP NWs is that they are mechanically weak and are more likely to break easily. Also, unlike the fabrication of CP NWs within defined nanoscale channels, the template-directed synthesis of CP NWs still requires postsynthetic alignment and positioning. This is one area that needs improvement. While several novel sensing concepts based on CP NWs have been demonstrated, incorporating these materials into routine functional integrated devices remains a challenge. Therefore, advances in the capabilities of assembling larger and more complex CP NW arrays and integrating them with
CONDUCTING POLYMER NANOWIRE-BASED BIOSENSORS
nanoscale electronics may lead to wider applications in health, environmental, and homeland security sectors.
REFERENCES 1. D. H. Reneker and I. Chun, Nanometre diameter fibres of polymer, produced by electrospinning. Nanotechnology, 1996, 7, 216–223. 2. J. Kameoka and H. G. Craighead, Fabrication of oriented polymeric nanofibers on planar surfaces by electrospinning. Applied Physics Letters, 2003, 83, 371–373. 3. J. Kameoka, R. Orth, Y. N. Yang, D. Czaplewski, R. Mathers, G. W. Coates, and H. G. Craighead, A scanning tip electrospinning source for deposition of oriented nanofibres. Nanotechnology, 2003, 14, 1124–1129. 4. J. Kameoka, R. Orth, B. Ilic, D. Czaplewski, T. Wachs, and H. G. Craighead, An electrospray ionization source for integration with microfluidics. Analytical Chemistry, 2002, 74, 5897–5901. 5. H. Q. Liu, J. Kameoka, D. A. Czaplewski, and H. G. Craighead, Polymeric nanowire chemical sensor. Nano Letters, 2004, 4, 671–675. 6. J. H. Lim and C. A. Mirkin, Electrostatically driven dippen nanolithography of conducting polymers. Advanced Materials, 2002, 14, 1474–1477. 7. B. W. Maynor, S. F. Filocamo, M. W. Grinstaff, and J. Liu, Direct-writing of polymer nanostructures: poly(thiophene) nanowires on semiconducting and insulating surfaces. Journal of the American Chemical Society, 2002, 124, 522–523. 8. B. Dong, D. Y. Zhong, L. F. Chi, and H. Fuchs, Patterning of conducting polymers based on a random copolymer strategy: toward the facile fabrication of nanosensors exclusively based on polymers. Advanced Materials, 2005, 17, 2736–2741. 9. H. X. He, C. Z. Li, and N. J. Tao, Conductance of polymer nanowires fabricated by a combined electrodeposition and mechanical break junction method. Applied Physics Letters, 2001, 78, 811–813. 10. C. R. Martin, Nanomaterials—a membrane-based synthetic approach. Science, 1994, 266, 1961–1966. 11. C. R. Martin, Template synthesis of electronically conductive polymer nanostructures. Accounts of Chemical Research, 1995, 28, 61–68. 12. Y. F. Ma, J. M. Zhang, G. J. Zhang, and H. X. He, Polyaniline nanowires on Si surfaces fabricated with DNA templates. Journal of the American Chemical Society, 2004, 126, 7097–7101. 13. A. Bensimon, A. Simon, A. Chiffaudel, V. Croquette, F. Heslot, and D. Bensimon, Alignment and sensitive detection of DNA by a moving interface. Science, 1994, 265, 2096–2098. 14. H. Nakao, H. Hayashi, T. Yoshino, S. Sugiyama, K. Otobe, and T. Ohtani, Development of novel polymer-coated substrates for straightening and fixing DNA. Nano Letters, 2002, 2, 475–479.
11
15. P. Nickels, W. U. Dittmer, S. Beyer, J. P. Kotthaus, and F. C. Simmel, Polyaniline nanowire synthesis templated by DNA. Nanotechnology, 2004, 15, 1524–1529. 16. K. Ramanathan, M. A. Bangar, M. H. Yun, W. F. Chen, A. Mulchandani, and N. V. Myung, Individually addressable conducting polymer nanowires array. Nano Letters, 2004, 4, 1237–1239. 17. K. Ramanathan, M. A. Bangar, M. Yun, W. Chen, N. V. Myung, and A. Mulchandani, Bioaffinity sensing using biologically functionalized conducting-polymer nanowire. Journal of the American Chemical Society, 2005, 127, 496–497. 18. C. Y. Peng, A. K. Kalkan, S. J. Fonash, B. Gu, and A. Sen, A “grow-in-place” architecture and methodology for electrochemical synthesis of conducting polymer nanoribbon device arrays. Nano Letters, 2005, 5, 439–444. 19. E. S. Forzani, H. Q. Zhang, L. A. Nagahara, I. Amlani, R. Tsui, and N. J. Tao, A conducting polymer nanojunction sensor for glucose detection. Nano Letters, 2004, 4, 1785–1788. 20. J. Duchet, R. Legras, and S. Demoustier-Champagne, Chemical synthesis of polypyrrole: structure-properties relationship. Synthetic Metals, 1998, 98, 113–122. 21. L. Liang, J. Liu, C. F. Windisch, G. J. Exarhos, and Y. H. Lin, Direct assembly of large arrays of oriented conducting polymer nanowires. Angewandte Chemie International Edition, 2002, 41, 3665–3668. 22. J. Liu, Y. H. Lin, L. Liang, J. A. Voigt, D. L. Huber, Z. R. Tian, E. Coker, B. Mckenzie, and M. J. Mcdermott, Templateless assembly of molecularly aligned conductive polymer nanowires: a new approach for oriented nanostructures. Chemistry- A European Journal, 2003, 9, 605–611. 23. M. M. Alam, J. Wang, Y. Y. Guo, S. P. Lee, and H. R. Tseng, Electrolyte-gated transistors based on conducting polymer nanowire junction arrays. Journal of Physical Chemistry B, 2005, 109, 12777–12784. 24. T. Livache, H. Bazin, P. Caillat, and A. Roget, Electroconducting polymers for the construction of DNA or peptide arrays on silicon chips. Biosensors and Bioelectronics, 1998, 13, 629–634. 25. N. Lassalle, A. Roget, T. Livache, P. Mailley, and E. Vieil, Electropolymerisable pyrrole-oligonucleotide: synthesis and analysis of ODN hybridisation by fluorescence and QCM. Talanta, 2001, 55, 993–1004. 26. N. Lassalle, P. Mailley, E. Vieil, T. Livache, A. Roget, J. P. Correia, and L. M. Abrantes, Electronically conductive polymer grafted with oligonucleotides as electrosensors of DNA—preliminary study of real time monitoring by in situ techniques. Journal of Electroanalytical Chemistry, 2001, 509, 48–57. 27. P. Guedon, T. Livache, F. Martin, F. Lesbre, A. Roget, G. Bidan, and Y. Levy, Characterization and optimization of a real-time, parallel, label-free, polypyrrole-based DNA sensor by surface plasmon resonance imaging. Analytical Chemistry, 2000, 72, 6003–6009. 28. S. Cosnier and A. Lepellec, Poly(pyrrole-biotin): a new polymer for biomolecule grafting on electrode surfaces. Electrochimica Acta, 1999, 44, 1833–1836. 29. L. M. Torres-Rodriguez, A. Roget, M. Billon, and G. Bidan, Synthesis of a biotin functionalized pyrrole and its
12
30.
31.
32.
33.
34.
35.
36.
37.
38.
MINIATURIZED, MICRO AND PARTICLE SYSTEMS electropolymerization: toward a versatile avidin biosensor, Chemical Communications, 1998, 1993–1994. D. Delabouglise, J. Roncali, M. Lemaire, and F. Garnier, Control of the lipophilicity of polypyrrole by 3-Alkyl substitution. Journal of the Chemical Society, Chemical Communications, 1989, 475–477. J. Wang, J. H. Dai, and T. Yarlagadda, Carbon nanotubeconducting-polymer composite nanowires. Langmuir, 2005, 21, 9–12. J. Wang and M. Musameh, Carbon-nanotubes doped polypyrrole glucose biosensor. Analytica Chimica Acta, 2005, 539, 209–213. H. Cai, Y. Xu, P. G. He, and Y. Z. Fang, Indicator free DNA hybridization detection by impedance measurement based on the DNA-doped conducting polymer film formed on the carbon nanotube modified electrode. Electroanalysis, 2003, 15, 1864–1870. J. Wang and M. Jiang, Toward genolelectronics: nucleic acid doped conducting polymers. Langmuir, 2000, 16, 2269–2274. M. L. Calvo-Munoz, B. E. A. Bile, M. Billon, and G. Bidan, Electrochemical study by a redox probe of the chemical post-functionalization of N-substituted polypyrrole films: application of a new approach to immobilization of biotinylated molecules. Journal of Electroanalytical Chemistry, 2005, 578, 301–313. H. KorriYoussoufi, F. Garnier, P. Srivastava, P. Godillot, and A. Yassar, Toward bioelectronics: specific DNA recognition based on an oligonucleotide-functionalized polypyrrole. Journal of the American Chemical Society, 1997, 119, 7388–7389. A. I. Minett, J. N. Barisci, and G. G. Wallace, Immobilisation of anti-Listeria in a polypyrrole film. Reactive and Functional Polymers, 2002, 53, 217–227. L. Cocheguerente, A. Deronzier, P. Mailley, and J. C. Moutet, Electrochemical immobilization of
39.
40.
41.
42.
43.
44.
45.
46.
glucose-oxidase in poly(amphiphilic pyrrole) films and its application to the preparation of an amperometric glucose sensor. Analytica Chimica Acta, 1994, 289, 143–153. S. Cosnier and C. Innocent, A novel biosensor elaboration by electropolymerization of an adsorbed amphiphilic pyrrole tyrosinase enzyme layer. Journal of Electroanalytical Chemistry, 1992, 328, 361–366. R. M. Hernandez, L. Richter, S. Semancik, S. Stranick, and T. E. Mallouk, Template fabrication of protein-functionalized gold-polypyrrole-gold segmented nanowires. Chemistry of Materials, 2004, 16, 3431–3438. Y. Li, H. H. Yang, Q. H. You, Z. X. Zhuang, and X. R. Wang, Protein recognition via surface molecularly imprinted polymer nanowires. Analytical Chemistry, 2006, 78, 317–320. H. H. Yang, S. Q. Zhang, F. Tan, Z. X. Zhuang, and X. R. Wang, Surface molecularly imprinted nanowires for biorecognition. Journal of the American Chemical Society, 2005, 127, 1378–1379. S. Niyogi, C. Hangarter, R. M. Thamankar, Y. F. Chiang, R. Kawakami, N. V. Myung, and R. C. Haddon, Magnetically assembled multiwalled carbon nanotubes on ferromagnetic contacts. Journal of Physical Chemistry B, 2004, 108, 19818–19824. A. K. Bentley, J. S. Trethewey, A. B. Ellis, and W. C. Crone, Magnetic manipulation of copper-tin nanowires capped with nickel ends. Nano Letters, 2004, 4, 487–490. H. Q. Zhang, S. Boussaad, N. Ly, and N. J. J. Tao, Magnetic-field-assisted assembly of metal/polymer/metal junction sensors. Applied Physics Letters, 2004, 84, 133–135. A. D. Aguilar, E. S. Forzani, X. L. Li, N. J. Tao, L. A. Nagahara, I. Amlani, and R. Tsui, Chemical sensors using peptide-functionalized conducting polymer nanojunction arrays. Applied Physics Letters, 2005, 87, 193108–193111.
52 Biosensors Based on Single-Walled Carbon Nanotube Near-Infrared Fluorescence Paul W. Barone,1 Esther S. Jeng,1 Daniel A. Heller2 and Michael S. Strano1 1
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA and 2 Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
The optical characteristics of individual singlewalled carbon nanotubes (SWNTs) make them excellent candidates for optical sensors, as has been shown previously.1–3 SWNTs can be visualized as sheets of graphene rolled into seamless structures. Depending on the angle of rolling (chirality) and the diameter of the nanotube, semiconducting, or metallic tubes are formed.4 Individual semiconducting nanotubes photoluminesce with discrete bands between 900 and 1600 nm. This range in the near-infrared (nIR) region is in the “tissue-transparent window” where the scattering, autofluorescence,5 and absorption of optically dense biologically relevant molecules such as blood, water, and tissue6–8 are low, allowing for transmission through this otherwise highly scattering media6,7 (Figure 1a). In particular, Rayleigh scattering, which constitutes the majority of the scattering intensity, is inversely proportional to the wavelength raised to the fourth power, resulting in dramatically reduced scattering in the nIR.9 Therefore, SWNTs have the potential to be used in biological applications and environments, including live cells and tissues. Also SWNTs are sensitive to molecular events at their surface1,4 and
are uniquely photostable.10 Figure 1(b) compares the rate of photobleaching of an organic fluorophore, quantum dots, and carbon nanotubes, showing that nanotubes excited at high laser fluence for 10 h show no diminution in emission.10 This section presents the use of individually dispersed HiPCO SWNT (Rice Research Reactor run 107, length 400–1000 nm) as fluorescent biosensors. Fluorescent and Raman scattering measurements are done simultaneously using a Kaiser Optical Holospec f/1.8 imaging spectrograph with excitation at 785 nm. 1 SINGLE-WALLED CARBON NANOTUBE GLUCOSE SENSORS
Implantable biosensors are a major focus of ongoing biomedical research,11–17 because of their many advantages over the current analyte detection techniques.17 Such sensors would have an immediate impact on diseases such as diabetes, where continuous monitoring along with intensive therapy is often necessary to prevent longterm complications.18 SWNTs present one avenue
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS 1 SWNT fluorescence
8
0.6
4
0.4 0.2
2 Blood absorbance 400
650
(a)
Water absorbance 900
1150
IR Dye 78-CA
I
Normalized intensity
0
1400
Wavelength (nm) 10 nIR QDs DNA-carbon nanotubes
1.5 1 0.5 0 0 2 4 6 8 10 Time (h)
1
0.1 0.00001 (b)
0.8
6
0
Normalized fluorescence
Absorbance (cm−1)
10
0.001 0.1 10 Exposure time (h)
1000
Figure 1. (a) “Tissue-transparent window” composed of the absorption spectra of blood (red) and water (black). Fluorescence spectrum of SWNT (blue). (b) Photobleaching curve of a near-IR organic dye, near-infrared quantum dots (QDs), and carbon nanotubes. The nanotubes show no photobleaching over 10 h of excitation. [Reprinted with permission Heller et al.10 copyright 2005, Wiley VCH.]
toward the creation of implantable biosensors.1–3 The combination of the nanotube’s sensitivity β-D-glucose HO
O
to surface adsorption events4,19,20 and their nIR fluorescence7 makes them promising candidates for fluorescence-based devices. One method to create a SWNT sensor that is both sensitive and selective, is to link the actions of enzymes or proteins to the nanotube and its fluorescence. The idea being that, when the enzymatic reaction or binding event occurs, a measurable change in nanotube fluorescence would be observed. In the case of enzymes, a reaction intermediary is necessary to mediate the nanotube fluorescence in response to the enzymatic reaction.1 Figure 2 shows a schematic of a glucose sensor using glucose oxidase (GOx) as the enzyme and potassium ferricyanide (K3 Fe(CN)6 ) as the intermediary. The enzyme is adsorbed to the side of the nanotube where it catalyzes the oxidation of β-D-glucose, producing gluconolactone and hydrogen peroxide. Ferricyanide ions adsorb to the side of the nanotube, which quench SWNT emission, then react with the hydrogen peroxide resulting in a recovery of SWNT fluorescence. To assemble the sensor, GOx is first adsorbed to the surface of the SWNT. Nanotubes are initially solubilized using sodium cholate.1,3,7 The GOx is self assembled on the surface of the nanotube by removing the cholate coating the SWNT through dialysis. Such a process allows the GOx to retain its functionality. Figure 3 shows SWNT fluorescence spectra before and after GOx assembly via a 20 h dialysis. The adsorption of GOx to the surface of the nanotube causes the fluorescence emission to decrease in energy, as compared to cholate suspended nanotubes. Such a shift is indicative of a more porous coating on Glucose oxidase
OH
HO
OH OH HO
Excitation + O2 O
HO
+
H2O
O OH
+
H2O2
OH
SWNT Emission
Adsorbed FeCN63− Adsorbed H2O2 Figure 2. Schematic of glucose sensing using enzyme–nanotube complex and a reaction mediator (Fe(CN)6 3− ). Glucose oxidase adsorbed to the nanotube catalyzes the oxidation of glucose, producing hydrogen peroxide. The hydrogen peroxide then reacts with the adsorbed ferricyanide causing a fluorescence restoration. [Reprinted with permission Barone et al.1 copyright 2005, Nature Publishing Group.]
SINGLE-WALLED CARBON NANOTUBE BIOSENSORS
Intensity (arb units)
10
t = 20 h
8
t=0h
6 4 2 0 870
920
Normalized fluorescence
(a)
1020
Fe(CN)6−3 added to 2% cholate
1.2 1 0.8
Fe(CN)6−4/GOx
0.6 0.4
Fe(CN)6−3/GOx
0.2 0 0
(b)
970
Wavelength (nm)
50
100
150
200
250
Analyte concentration (mM)
Figure 3. (a) Single-walled carbon nanotube fluorescence before (orange) and after (green) adsorption of GOx from a 20 h dialysis. (b) GOx suspended nanotube fluorescence decreases up to 83% when titrated with ferricyanide (red). Titration with the redox partner ferrocyanide (black) results in a lesser degree of fluorescence attenuation. The addition of ferricynide to sodium cholate suspended nanotubes does not alter the fluorescence intensity (blue). [Reprinted with permission Barone et al.1 copyright 2005, Nature Publishing Group.]
the surface of the nanotube.21 The porous enzyme coating makes permeation by the ferricyanide
3
possible. Addition of ferricyanide to the GOx suspended SWNT solution results in ferricyanide adsorption to the nanotube and a measurable fluorescence decrease (Figure 3b). The attenuation in SWNT fluorescence is concentration dependent with nanotube fluorescence decreasing by a maximum of 83% at 225 mM ferricyanide. If potassium ferricyanide’s redox partner, potassium ferrocyanide (K4 Fe(CN)6 ) is instead titrated into the GOx suspended SWNT solution, the attenuation of SWNT fluorescence is less. Interestingly, the adsorption of ferricyanide is partially irreversible. Figure 4 shows fluorescence from GOx suspended nanotubes contained in a dialysis cassette immersed in standard Tris buffer at pH 7 and 37 ◦ C. Additions of 10 and 120 mM ferricyanide to the buffer cause SWNT fluorescence to attenuate. Cycling to reagent free buffer causes only a partial restoration of nanotube fluorescence indicating irreversible adsorption. Addition of β-D-glucose to the GOx–ferricyanide–SWNT sensing complex results in nanotube fluorescence restoration. Figure 5(a) shows the response of nanotube fluorescence as 62.5 mM ferricyanide is added to GOx suspended SWNT followed by subsequent additions of 1.4, 2.8, and 4.1 mM total glucose. The fluorescence recovery after glucose additions is rapid, on the order of tens of seconds. The total fluorescence recovery can then be mapped to glucose added to the sample (Figure 5b). The resulting response function follows a Type 1 Langmuir adsorption isotherm with a Km = 0.91 mM−1 and a calculated sensitivity of 37.4 µM. Conceivably, this type of sensing system
1 120
∆I irrev
100
0.6
80
0.4
60 40
∆I rev
0.2
Fe(CN)6−3 (mM)
Relative intensity
140 0.8
20
0
0 0
0.5
1 1.5 Time (h)
2
2.5
Figure 4. GOx suspended SWNT fluorescence (blue) decreases upon addition of 10 and 120 mM ferricyanide (red). Removal of free ferricyanide results in only a partial fluorescence recovery, indicating irreversible adsorption to the nanotube. [Reprinted with permission Barone et al.1 copyright 2005, Nature Publishing Group.]
4
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
2 SINGLE-WALLED CARBON NANOTUBES AS DNA HYBRIDIZATION SENSORS
1.10
Relative intensity
(i) 4.2 mM
0.80 2.4 mM
0.50 1.4 mM 0.20 0
(a)
20
10 Time (min)
Normalized fluorescence
0.80
0.60
0.40
0.20
0 0 (b)
5
10
Glucose concentration (mM)
Figure 5. (a) GOx suspended SWNT fluorescence decreases upon addition of 62.5 mM ferricyanide and recovers upon subsequent additions of glucose. (b) The response function follows a Type 1 Langmuir adsorption isotherm. [Reprinted with permission Barone et al.1 copyright 2005, Nature Publishing Group.]
could be implanted inside the body through the use of a small dialysis capillary.1,22 Such a capillary would allow glucose to diffuse in, but would retain the sensing medium since the GOx–SWNT complex would be too large to diffuse through and the ferricyanide is irreversibly adsorbed to the surface of the nanotube. This sensing device is analogous to the flux-based electrochemical sensors currently being devised for implantation. This work demonstrates the viability of carbon nanotubes as components in implantable biomedical sensors. Passive, optically responsive implantable sensors have clear advantages over electrochemical23 and photo-electrochemical24,25 devices. Additionally, the sensing mechanism outlined above is not relegated to just GOx, but could also be used with other redox enzymes that create hydrogen peroxide as a by-product, such as lactate oxidase or glutamate oxidase.
Detection of specific DNA sequences has many applications in the medical, life, and environmental sciences.26–34 The use of fluorescence detection is advantageous because of the sensitivity and selectivity of the technique,35 as well as ease of use. SWNT can be individually suspended by adsorbing molecules to its surface in solution, allowing for fluorescent label-free and dye-free1,21,36,37 systems. Earlier work has shown that some DNA sequences adsorb strongly to the surface of nanotubes resulting in a stable suspension.37,38 The use of SWNT led to the first photobleaching resistant, nanoparticle system that could detect DNA hybridization through the modulation of an nIR fluorescence signal from the DNA–SWNT complex.3 This system allowed for optical detection of selective hybridization of DNA with its complementary strand directly on the surface of SWNT, and therefore opens possibilities for new types of nanotube-based biosensors. The DNA–SWNT used for the hybridization sensors is assembled through a two-step dialysis technique (Figure 6a). In the first step a sodium cholate–SWNT solution1,3 is dialyzed against standard Tris buffer pH 7.6 in the presence of the oligonucleotide strands through a membrane with a 12–14 kDa molecular weight cutoff (MWCO). A random sequence DNA1 (5 -TAG CTA TGG AAT TCC TCG TAG GCA-3 ) was used to illustrate the concept of the sensor.3 The sodium cholate dialyzes out through the membrane while the larger oligonucleotide strands assemble on the SWNT surface. The remaining free DNA strands are removed through a second dialysis (100 kDa MWCO). Combined photoluminescence and Raman spectra of the initial cholateSWNT and final DNA1–SWNT solutions shows a bathochromic shift (Figure 6b). The shifting of SWNT fluorescence energy has been attributed to a change in the coverage of the SWNT surface in water.21 The small cholate molecules are able to pack the SWNT surface more densely than the oligonucleotide strands. An atomic force microscopy (AFM) image (Figure 6c) shows that the DNA strands are adsorbed randomly to the surface of the SWNT and uneven heights suggest that each strand is folded on itself.
SINGLE-WALLED CARBON NANOTUBE BIOSENSORS A
(a)
Normalized intensity
1.2
B
C
DNA1
12 14 kDa dialysis membrane
Cholate
100 kDa dialysis membrane
DNA1 SWNT
1
5
−17.6 meV
Cholate SWNT
0.8 0.6 0.4 0.2
230 nm
0 900 (b)
950
1000 Wavelength (nm)
1050
1100 (c)
Figure 6. Assembly of DNA1 on SWNT (a) (A) Cholate–SWNT is dialyzed (12–14 kDa membrane) in the presence of DNA1, resulting in cholate removal and DNA1 adsorption to SWNT. (B) Free DNA1 is removed through a second dialysis step (100 kDa membrane). (C) Final DNA1–SWNT sample. (b) Comparison of initial cholate–SWNT and final DNA1–SWNT photoluminescence spectra reveals a bathochromic shift of 17.6 meV in the (7,5) nanotube with DNA assembly. (c) AFM image of DNA suspended SWNT with thicker sections denoting nonuniform adsorption of DNA on the SWNT with varying heights.
Hybridization of DNA1–SWNT with the complementary deoxyribonucleic acid strand (cDNA 5 -GCC TAC GAG GAA TTC CAT AGC T-3 ) is transduced through a hypsochromic shift in the (6,5) nanotube fluorescence. An illustration of the detection scheme and the hypsochromic shift are shown in Figure 7(a) and (b). The (6,5) SWNT was excited with a 785-nm laser while the fluorescence (λmax = 994 nm) was monitored. The DNA1–SWNT was incubated with cDNA and noncomplementary deoxyribonucleic acid (nDNA 5 -TCG ATA CCT TAA GGA GCA TCC G-3 ) for 48 h to ensure that steady state was reached. The addition of cDNA caused a fluorescence energy increase of up to 2.02 ± 0.07 meV while additions of nDNA at the same concentrations resulted in negligible energy changes (Figure 7c). The energy increased with the concentration of cDNA added until (cDNA) reached 400 nM, where
the shift remained 2.02 meV. This energy shift can be attributed to the change in the dielectric environment of the SWNT, which changes the exciton binding energy. The dielectric constant, ε, at the SWNT surface is determined to be ε = αεDNA + (1 − α)εH2 O (1) using a local dielectric medium approximation where α is the fraction of SWNT surface area covered by DNA, and εDNA = 2.1, εH2 O = 88 represent the dielectric constants of DNA and water, respectively. The exciton binding energy is a function of the dielectric constant according to the following equation: E = Aµn−1 rtn−2 ε−n
(2)
where A and n are constants (24.1 and 1.4 eV) found by fitting nanotubes with diameters of
6
MINIATURIZED, MICRO AND PARTICLE SYSTEMS hn1
Normalized intensity
hn1
hn2
hn3
cDNA 2 meV 879 nM
1.02 1 0.98 0.96 0.94 0.92 988
(a)
0 nM
992
996
1000
Wavelength (nm)
(b) 2.5
∆E (meV)
2 cDNA (complementary DNA)
1.5 1 0.5
nDNA (noncomplementary DNA)
0 −0.5 0 (c)
500
1000
1500
cDNA or nDNA (nM)
Figure 7. Detection of DNA hybridization on the SWNT surface (a) Illustration of detection mechanism. Incident laser light (energy hν1 ) causes SWNT to fluoresce at a given energy (hν2 ). After hybridization the same incident light energy causes the SWNT to fluoresce at a different energy (hν3 ). (b) The 2 meV hypsochromic shift of (6,5) SWNT fluorescence energy after addition of complementary DNA (cDNA) is shown. (c) The steady-state energy increase of the SWNT fluorescence is shown (blue circles) as a function of cDNA added to the system. In contrast, the nDNA causes a negligible change in energy (red triangles). The solid line represents the calculated exciton binding energy change that is theorized to occur as the dielectric environment around the SWNT is changed. [Reprinted with permission Jeng et al.3 copyright 2006, American Chemical Society.]
1–2.5 nm, µ = 0.068 is the reduced effective mass of the (6,5) nanotube,6 and β = 0.0529 nm is the Bohr radius constant. Approximating that hybridization doubles the surface area coverage of SWNT and using the energy increase of 2.02 meV, the surface area coverage is predicted to be 3.5–7%. In this model, Perebeinos et al. solved the Bethe–Salpeter equation to find an exciton binding energy scaling relationship.39 The model is shown as the solid line in Figure 7(c). Hybridization on the SWNT surface was confirmed using Forster resonance energy transfer (FRET) of fluorophore labeled DNA (5 -TAG CTA TGG AAT TCC TCG TAG GCA-3 -6-FAM and TAMRA NHS Ester–5 - GCC TAC GAG GAA TTC CAT AGC T-3 ).3 The hybridization kinetics on SWNT were studied through transient measurements of the fluorescence energy shift. Unlike the hybridization of free DNA, the DNA1–SWNT system
cannot be adequately described with a secondorder reaction.40 Instead the hybridization can be modeled using a two-step Langmuir isotherm followed by a first-order reaction (Figure 8a), similar to previous modeling.41 The equilibrium number of occupied sites on the SWNT surface, Aθ , is fixed by the adsorption step as shown below: A+θ Aθ cDNA + Free sites Occupied sites
(3)
The number of occupied sites is determined by combining a total site (θT ) balance and the equilibrium constant, K. θT = Aθ + θ [Aθ ] K= [A](θT − [Aθ ])
(4) (5)
SINGLE-WALLED CARBON NANOTUBE BIOSENSORS
DNA1
cDNA
(a) Type 1 Langmuir isotherm
First-order kinetic reaction 2.4
2
2 ∆E (meV)
1.6 ∆E (meV)
7
1.2 0.8 cDNA = 100 nM
0.4
1.6 1.2 0.8
cDNA = 1400 nM
0.4
0
0 0
5
(b)
10
15
20
0
5
10
15
20
Time (h)
Time (h)
Figure 8. A two-step model of adsorption followed by reaction is fitted to the measured energy shifts caused by addition and hybridization of complementary cDNA (22 bases) with DNA1 (24 bases) on SWNT. (a) An illustration of the two-step model. (b) The change in SWNT energy with time at various concentrations (100–1400 nM) of complementary DNA are fitted using the same kinetic constant k = 5.57 × 10−5 s−1 , total binding sites on SWNT θT = 120 nM, and equilibrium constant K = 5 × 107 M−1 . The measured and fitted energy shifts of the lowest and highest concentrations of cDNA are shown. [Reproduced from Jeng, E. S., Barone, P. W., Nelson, J. D., and Strano, M. S. Small (2007) submitted.]
The total concentration of hybridization sites in solution is θT (M), Aθ is the concentration of occupied sites (M), K is the equilibrium constant (M−1 ), and A is the concentration of cDNA strands (M). An occupied site concentration is determined from coupling of these two equations. [Aθ0 ] =
K[A0 ][θT ] 1 + K[A0 ]
(6)
A slower and irreversible hybridization reaction of two complementary strands follows the adsorption step. k
1 H Aθ −−−−→ Hybridized complex Occupied site
(7)
H is the concentration of the hybridized complex (M) and k1 is the kinetic constant in s−1 M−1 . The reaction is modeled as a simple first-order reaction d[Aθ ] d[H ] = −k1 [Aθ ] = − dt dt
(8)
with a hybridized complex formation of
H = (1 − e−k1 t )
K[A0 ][θT ] 1 + K[A0 ]
(9)
The hybridization reaction that is transduced through the energy shift of the (6,5) SWNT, is fitted using the method of least squares as shown in Figure 8(b). At 25 ◦ C the kinetic constant, k1 , is 5.57 × 10−5 s−1 , and the equilibrium constant, K, is 5 × 107 M−1 . The total number of binding sites is 120 nM, which is the amount of DNA adsorbed to the SWNT surface. The process of hybridization on SWNT takes about 3.4 h to reach half of the steady-state energy shift observed for detection. Hybridization DNA–SWNT sensors hold promise for the detection of specific DNA sequences in many applications. Although this new technology can still be improved through a decrease in detection time and an enhancement in the transduction signal, this label-free detection mechanism has the potential to be used for nonphotobleaching detection in scattering biological media and even inside cells.
8
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
3 SINGLE-WALLED CARBON NANOTUBE ION SENSORS
left-handed Z form upon exposure to divalent metal cations.42–44 This change in DNA secondary structure is caused preferentially by ions that bind to the DNA bases. The structural transformation was exploited for sensing by adsorbing 30-mer oligonucleotides onto the nanotube sidewall in a tight, helically-wrapped configuration. The method of encapsulation, developed by Zheng et al.38,45 forms a colloidally stable complex (Figure 9a).2 Complexes of d(GT)15 oligonucleotides and HiPCO carbon nanotubes (GT–SWNT) were prepared via ultrasonication. Single-stranded DNA
SWNTs functionalized with DNA respond to divalent metal ions of the type that induce the structural conformational transition of DNA from the native B form to the Z form.42 Nanotube fluorescence shows a reversible concentration-dependent red shift of up to 16 meV upon introduction of metal cations. Oligonucleotides containing certain sequences will transit from the right-handed B form to the
50 nm
(a) 3
1.252 Co2+
1.249 1.246 1.243 1.24
1 0.9 0.8 0.7 0.6 1.23
1.237 0.001
Hg2+
1.24
Peak energy (eV)
Ca2+
1.25
1000
1 000 000
1.5 0
1.251
3.1
1.249
1.6 0.1
1.246
−1.4
Hg2+ 1.243
−2.9
1.241
−4.4
25 µM 0 µM
4.5 µM 2.6 µM
−1.5 0.48 µM
−3
240 µM 215
(c)
Concentration (µM)
1.238 0.001
44 µM
−4.5
1
(b)
(d)
Θ−5 (deg-cm2 dmol−1)
Mg2+
240
430 µM 2300 µM
265 290 Wavelength (nm)
315
Θ−5 (deg-cm2 dmol−1)
Peak energy (eV)
1.255
−5.9 0.1
10
1000
Concentration (µM)
100 000 (e)
Figure 9. (a) AFM image of GT-DNA-encapsulated carbon nanotube complexes synthesized by ultrasonication. [Reproduced from Zheng, M. et al. Science, 302(2003):1545–1548.] (b) Metal ion-induced spectral changes of the GT-SWNT complex show a monotonic energy decrease. One nanotube species is used for all measurements. Inset: Nanotube spectra at starting and ending concentrations of Hg2+ . (c) Circular dichroism spectra of the free d(GT)15 oligonucleotide with increasing concentrations of Hg2+ . (d) Nanotube emission energy (red) and 285 nm ellipticity from CD spectra (black) versus Hg2+ concentration. (e) Representation of B–Z transition on carbon nanotube. [Reprinted with permission Heller et al.2 copyright 2006, AAAS.]
SINGLE-WALLED CARBON NANOTUBE BIOSENSORS
with the GT sequence is postulated to form a double-stranded structure on the nanotube via weak pairing of G to T. The complexes were probed via nIR spectrofluorometry in a pH 7.4 buffer. The nanotube emission displayed a distinct, monotonic red shift with concentration of divalent metal cations (Figure 9b). The relative sensitivity to the ions added was dictated by the relative tendency for the ions to bind to DNA.46 Removal of the metal ions restored the emission energy, indicating a reversible thermodynamic transition. Circular dichroism (CD) spectroscopy, performed under identical conditions, confirmed that the unbound oligonucleotide of the same sequence undergoes a conformational change from the B to the Z form seen in the inversion of the 285 nm peak, which indicates a reversal of helicity (Figure 9c). We compare the ellipticity of the 285-nm CD peak versus Hg2+ concentration with the fluorescent emission energy from the nanotube, under identical conditions (Figure 9d). The overlapping points of inflection indicate that the difference in the free energy ( G) changes for the DNA on and off the nanotube is quite small ( ( G) ∼ 0.05 kB T per phosphate, where kB T is the thermal energy). Thus, the transitions for DNA in solution or adsorbed on the SWNT can be considered thermodynamically identical. It is interesting to note that the slopes at the inflection show a distinct difference. Pohl42 describes the B–Z transition, which requires a double-stranded helix to separate, change helicity and re-form, as a process of nucleation and propagation in series. The dsDNA strand initially separates with a ratio of rate constants βB /βZ while propagation proceeds as a series of equilibrium steps proportional to the number of base-pairs, N , as the dislocation proceeds down the chain. The expression for the fractional transition K,42,47 contains a scaling factor C0 which is the ion concentration (C) where K is independent of oligonucleotide length (N ). K=
C C0
aN
βB + βZ
C C0
aN −1 (10)
Pohl used this equation to describe his observed changes in slope with oligonucleotide length or the propagation length, aN. Regression of the data in Figure 9(d) suggests that, given a length of 30
9
nucleotides on the free DNA, the nanotube-bound DNA exhibits an effective length of 5 nucleotides. In other words, the transition proceeds through only one-sixth the number of transitions as in the case of the free strand. As expected, βB /βZ , which is associated with the initiation of the event, is similar for the cases on and off the nanotube (1.21 and 1.04, respectively). The model suggests that the transition propagates in small steps and requires about 2π/3 rads of the strand to unravel for propagation down the nanotube (Figure 9e). Detection of divalent ions is also possible inside live cells. DNA-nanotube complexes (GT–SWNT) entered mammalian cells via endocytosis and reside in a perinuclear orientation within the cells over long time intervals.10 Nanotubes were detected after 3 months in cell culture. Fluorescence area maps composed of multiple rasterscanned spectra show nanotube emission accumulated near the nucleus in the cytoplasm surrounded by membrane bound vesicles (Figure 10a).10 The GT–SWNT complexes function as singlecell sensors for ion concentration upon addition of Hg2+ into the cell media. Murine 3T3 fibroblasts containing GT–SWNT complexes were perfused with various concentrations of HgCl2 in the extracellular buffer space and were monitored via photoluminescence. The SWNT emission, although shifted by 3 meV already upon uptake within the cell, red shifts additively with increasing Hg2+ concentration. After correcting for the initial shift caused by the new environment, the response of cell-bound DNA–SWNT fits the model curve created by the same complexes in pure buffer (Figure 10b). Detection is also possible in media, such as muscle tissue and blood, which possess strong visible absorption. A GT–SWNT-filled dialysis capillary was inserted into whole blood and mammalian tissue and probed via photoluminescence. Also, nanotube complexes were added to a black dye solution (optical density >4). Detection of mercuric chloride was possible through these highly absorptive materials (Figure 10c). The nIR fluorescence of GT–SWNT in the dye solution exhibited the same response as GT–DNA in pure buffer. In whole blood and tissue, the presence of interfering absorbers of Hg2+ (free DNA, proteins, etc.) shift the observed sensitivity to larger values (C0 = 3500 µM in blood and 8000 µM in tissue), however the complexes still provided a measure
10
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
1.05 10 000 µM 1000 µM 0 µM
I
Peak energy (eV)
1.252
1.247
0.95
0.85 1.228
1.238 1.248 Energy (meV)
1.242
1.237 0
2500
5000
7500 10 000
Concentration (µM)
(b) Peak energy (eV)
(a)
1.252 1.247 1.242 1.237 0
(c)
10 1000 Concentration (µM)
10 0000
Figure 10. (a) Area map of nanotube emission. (b) Emission energy of GT–SWNT fluorescence upon addition of Hg2+ . Blue curve obtained from original GT–SWNT shift taken outside of cells. Inset: Individual spectra obtained at each Hg2+ concentration. (c) Emission energy of GT–SWNT in a solution of black ink (black squares), chicken muscle tissue (green circles), and whole rooster blood (red triangles) shown on blue curve obtained from the pristine GT–SWNT shift. [Reprinted with permission Heller et al.2 copyright 2006, AAAS.]
of the residual ions that are locally bound to the complex in these heterogeneous media. This work reveals the use of SWNT as biosensors for ions in live cells, opening an avenue for single-cell detection in a host of applications.
such as an enzymatic sensor for glutamate or the detection of single-nucleotide polymorphisms in DNA, but will also focus on the discovery and explanation of new detection modalities.
REFERENCES 4 FUTURE DIRECTION OF SINGLE-WALLED CARBON NANOTUBE BIOSENSORS
The work outlined in this chapter shows the promising beginnings of a new type of sensor based on SWNT nIR photoluminescence. While we have demonstrated the ability to detect a wide range of analytes, from nucleic acids to small molecules, there is still much work left to do. A fundamental understanding of signal transduction to the nanotube is necessary for the rational design of any SWNT-based device. Future research in this area will not only focus on the application of current detection mechanisms for other analytes,
1. P. W. Barone, S. Baik, D. A. Heller, and M. S. Strano, Near-infrared optical sensors based on singlewalled carbon nanotubes. Nature Materials, 2005, 4(1), 86–92. 2. D. A. Heller, E. S. Jeng, T. K. Yeeung, B. M. Martinez, A. E. Moll, J. B. Gastala, and M. S. Strano, Optical detection of DNA conformational polymorphism on single-walled carbon nanotubes. Science, 2006, 311(5760), 508–511. 3. E. S. Jeng, A. E. Moll, AA. C. Roy, J. B. Gastala, and M. S. Strano, Detection of DNA hybridization using the near-infrared band-gap fluorescence of single-walled carbon nanotubes. Nano Letters, 2006, 6(3), 371–375. 4. R. Saito, G. Dresselhaus, and M. S. Dresselhaus, Physical Properties of Carbon Nanotubes, Imperial College Press, London, 1998.
SINGLE-WALLED CARBON NANOTUBE BIOSENSORS 5. R. Weissleder and V. Ntziachristos, Shedding light onto live molecular targets. Nature Medicine, 2003, 9(1), 123–128. 6. S. M. Bachilo, M. S. Strano, C. Kittrell, R. H. Hauge, R. E. Smalley, and R. B. Weisman, Structure-assigned optical spectra of single-walled carbon nanotubes. Science, 2002, 298(5602), 2361–2366. 7. M. J. O’Connell, S. M. Bachilo, C. B. Huffman, V. C. Moore, M. S. Strano, E. H. Haroz, K. L. Rialon, P. J. Boul, W. H. Noon, C. Kittrell, J. P. Ma, R. H. Hauge, R. B. Weisman, and R. E. Smalley, Band gap fluorescence from individual single-walled carbon nanotubes. Science, 2002, 297(5581), 593–596. 8. S. Wray, M. Cope, D. T. Delpy, J. S. Wyatt, and E. O. R. Reynolds, Characterization of the near-infrared absorptionspectra of cytochrome-Aa3 and hemoglobin for the noninvasive monitoring of cerebral oxygenation. Biochimica et Biophysica Acta, 1988, 933(1), 184–192. 9. C. F. Bohren and D. R. Huffman, Absorption and Scattering of Light by Small Particles, Wiley, New York, 1983, p. 530. 10. D. Heller, S. Baikk, T. E. Eurell, and M. S. Strano, Singlewalled carbon nanotube spectroscopy in live cells: towards long-term labels and optical sensors. Advanced Materials, 2005, 17(23), 2793–2799. 11. L. L. E. Salins, R. A. Ware, C. M. Ensor, and S. Daunert, A novel reagentless sensing system for measuring glucose based on the galactose/glucose-binding protein. Analytical Biochemistry, 2001, 294(1), 19–26. 12. H. Fang, G. Kaur, and B. H. Wang, Progress in boronic acid-based fluorescent glucose sensors. Journal of Fluorescence, 2004, 14(5), 481–489. 13. M. Shichiri, N. Asakawa, Y. Yamasaki, R. Kawamori, and H. Abe, Telemetry glucose monitoring device with needletype glucose sensor - a useful tool for blood-glucose monitoring in diabetic individuals. Diabetes Care, 1986, 9(3), 298–301. 14. K. W. Johnson, J. J. Mastrototaro, D. C. Howey, R. L. Brunelle, P. L. Burdenbrady, N. A. Bryan, C. C. Andrew, H. M. Rowe, D. J. Allen, B. W. Noffke, W. C. McMahan, R. J. Morff, D. Lipson, and R. S. Nevin, Invivo evaluation of an electroenzymatic glucose sensor implanted in subcutaneous tissue. Biosensors and Bioelectronics, 1992, 7(10), 709–714. 15. B. J. Gilligan, M. C. Shults, R. K. Rhodes, and S. J. Updike, Evaluation of a subcutaneous glucose sensor out to 3 months in a dog-model. Diabetes Care, 1994, 17(8), 882–887. 16. W. K. Ward, E. S. Wilgus, and J. E. Troupe, Rapid detection of hyperglycemia by a subcutaneously-implanted glucose sensor in the rat. Biosensors and Bioelectronics, 1994, 9(6), 423–428. 17. D. A. Gough, J. C. Armour, and D. A. Baker, Advances and prospects in glucose assay technology. Diabetologia, 1997, 40, S102–S107. 18. H. Shamoon, H. Duffy, N. Fleischer, et al., The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulindependent diabetes-mellitus. New England Journal of Medicine, 1993, 329(14), 977–986.
11
19. T. Durkop, S. A. Getty, E. Cobas, and M. S. Fuhrer, Extraordinary mobility in semiconducting carbon nanotubes. Nano Letters, 2004, 4(1), 35–39. 20. R. J. Chen, S. Bangsaruntip, K. A. Drouvalakis, N. W. S. Kam, M. Shim, Y. M. Li, W. Kim, P. J. Utz, and H. J. Dai, Noncovalent functionalization of carbon nanotubes for highly specific electronic biosensors. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100(9), 4984–4989. 21. M. S. Strano, V. C. Moore, M. K. Miller, M. J. Allen, E. H. Haroz, C. Kittrell, R. H. Hauge, and R. E. Smalley, The role of surfactant adsorption during ultrasonication in the dispersion of single-walled carbon nanotubes. Journal of Nanoscience and Nanotechnology, 2003, 3(1–2), 81–86. 22. R. Ballerstadt and J. S. Schultz, A fluorescence affinity hollow fiber sensor for continuous transdermal glucose monitoring. Analytical Chemistry, 2000, 72(17), 4185–4192. 23. A. Guiseppi-Elie, C. H. Lei, and R. H. Baughman, Direct electron transfer of glucose oxidase on carbon nanotubes. Nanotechnology, 2002, 13(5), 559–564. 24. R. Tantra, R. S. Hutton, and D. E. Williams, A biosensor based on transient photoeffects at a silicon electrode. Journal of Electroanalytical Chemistry, 2002, 538, 205–208. 25. L. M. Peter, Dynamic aspects of semiconductor photoelectrochemistry. Chemical Reviews, 1990, 90(5), 753–769. 26. F. S. Nolte, B. Metchock, J. E. McGowan, A. Edwards, O. Okwumabua, C. Thurmond, P. S. Mitchell, B. Plikaytis, and T. Shinnick, Direct-detection of mycobacteriumtuberculosis in sputum by polymerase chain-reaction and DNA hybridization. Journal of Clinical Microbiology, 1993, 31(7), 1777–1782. 27. S. J. Hamiltondutoit, G. Pallesen, M. B. Franzmann, J. Karkov, F. Black, P. Skinhoj, and C. Pedersen, Aidsrelated lymphoma - histopathology, immunophenotype, and association with epstein-barr-virus as demonstrated by insitu nucleic-acid hybridization. American Journal of Pathology, 1991, 138(1), 149–163. 28. K. Senda, Y. Arakawa, K. Nakashima, H. Ito, S. Ichiyama, K. Shimokata, N. Kato, and M. Ohta, Multifocal outbreaks of metallo-beta-lactamase-producing pseudomonas aeruginosa resistant to broad-spectrum betalactams, including carbapenems. Antimicrobial Agents and Chemotherapy, 1996, 40(2), 349–353. 29. F. J. Louws, D. W. Fulbright, C. T. Stephens, and F. J. Debruijn, Specific genomic fingerprints of phytopathogenic xanthomonas and pseudomonas pathovars and strains generated with repetitive sequences and PCR. Applied and Environmental Microbiology, 1994, 60(7), 2286–2295. 30. S. Juretschko, G. Timmermann, M. Schmid, K. H. Schleifer, A. Pommerening-Roser, H. P. Koops, and M. Wagner, Combined molecular and conventional analyses of nitrifying bacterium diversity in activated sludge: nitrosococcus mobilis and nitrospira-like bacteria as dominant populations. Applied and Environmental Microbiology, 1998, 64(8), 3042–3051.
12
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
31. Y. Wei, J. M. Lee, C. Richmond, F. R. Blattner, J. A. Rafalski, and R. A. LaRossa, High-density microarraymediated gene expression profiling of escherichia coli. Journal of Bacteriology, 2001, 183(2), 545–556. 32. L. D. Kuykendall, B. Saxena, T. E. Devine, and S. E. Udell, Genetic diversity in Bradyrhizobium-japonicum Jordan 1982 and a proposal for Bradyrhizobium-elkanii Sp-Nov. Canadian Journal of Microbiology, 1992, 38(6), 501–505. 33. M. J. Heller, DNA microarray technology: devices, systems, and applications. Annual Review of Biomedical Engineering, 2002, 4, 129–153. 34. A. C. Pease, D. Solas, E. J. Sullivan, M. T. Cronin, C. P. Holmes, and S. P. A. Fodor, Light-generated oligonucleotide arrays for rapid DNA-sequence analysis. Proceedings of the National Academy of Sciences of the United States of America, 1994, 91(11), 5022–5026. 35. M. U. Kumke, G. Li, L. B. McGown, G. T. Walker, and C. P. Linn, Hybridization of fluorescein-labeled DNA oligomers detected by fluorescence anisotropy with protein-binding enhancement. Analytical Chemistry, 1995, 67(21), 3945–3951. 36. V. C. Moore, M. S. Strano, E. H. Haroz, R. H. Hauge, R. E. Smalley, J. Schmidt, and Y. Talmon, Individually suspended single-walled carbon nanotubes in various surfactants. Nano Letters, 2003, 3(10), 1379–1382. 37. M. Zheng, A. Jagota, M. S. Strano, A. P. Santos, P. Barone, S. G. Chou, B. A. Diner, M. S. Dresselhaus, R. S. McLean, G. B. Onoa, G. G. Samsonidze, E. D. Semke, M. Usrey, D. J. Walls, Structure-based carbon nanotube sorting by sequence-dependent DNA assembly. Science, 2003, 302(5650), 1545–1548. 38. M. S. Strano, M. Zheng, A. Jagota, G. B. Onoa, D. A. Heller, P. W. Barone, and M. L. Usrey, Understanding the nature of the DNA-assisted separation of singlewalled carbon nanotubes using fluorescence and Raman spectroscopy. Nano Letters, 2004, 4(4), 543–550. 39. V. Perebeinos, J. Tersoff, and P. Avouris, Scaling of excitons in carbon nanotubes. Physical Review Letters, 2004, 92(25), 257402.
40. J. G. Wetmur and N. Davidson, Kinetics of renaturation of DNA. Journal of Molecular Biology, 1968, 31(3), 325–633. 41. D. Erickson, D. Q. Li, and U. J. Krull, Modeling of DNA hybridization kinetics for spatially resolved biochips. Analytical Biochemistry, 2003, 317(2), 186–200. 42. F. M. Pohl, Salt-induced transition between 2 doublehelical forms of oligo(Dc-Dg). Cold Spring Harbor Symposia on Quantitative Biology, 1982, 47, 113–117. 43. T. M. Jovin, D. M. Soumpasis, and L. P. Mcintosh, The transition between B-DNA and Z-DNA. Annual Review of Physical Chemistry, 1987, 38, 521–560. 44. A. Rich, The biology of left-handed Z-DNA. Journal of Biological Chemistry, 1996, 271(20), 11595–11598. 45. M. Zheng, A. Jagota, E. D. Semke, B. A. Diner, R. S. Mclean, S. R. Lustig, R. E. Richardson, and N. G. Tassi, DNA-assisted dispersion and separation of carbon nanotubes. Nature Materials, 2003, 2(5), 338–342. 46. J. Duguid, V. A. Bloomfield, J. Benevides, and G. J. Thomas, Raman spectral studies of nucleicacids. 44. Raman-spectroscopy of DNA-metal complexes. 1. Interactions and conformational effects of the divalent-cations - Mg, Ca, Sr, Ba, Mn, Co, Ni, Cu, Pd, and Cd. Biophysical Journal, 1993, 65(5), 1916–1928. 47. F. M. Pohl and T. M. Jovin, Salt-induced co-operative conformational change of a synthetic DNA: equilibrium and kinetic studies with poly(dG-dC). Journal of Molecular Biology, 1972, 67, 375–396.
FURTHER READING E. S. Jeng, P. W. Barone, J. D. Nelson, M. S. Strano, Hybridization kinetics and thermodynamics of DNA adsorbed to individually dispersed single walled carbon nanotubes. Small, 2007 (submitted).
53 Nucleic Acid Arrays Hirotaka Miyachi School of Bionics, Tokyo University of Technology, Tokyo, Japan
1 INTRODUCTION
2 TECHNICAL FOUNDATIONS OF DNA ARRAY
Over the past years, the completion of the genome project over a variety of organisms such as human,1–3 mouse,4,5 birds, fishes,6 yeast, plants, fruit fly,7 bacteria,8 marsupial species,9 and in the other species, has generated a large amount of genomic information. The sequencing data from such diverse organisms has led to a comprehensive functional analysis. These advantages facilitated the demands to understand biological mechanisms in a comprehensive genome complexity. Without a research tool known as nucleic acid array (also referred to as DNA array, DNA microarray, or DNA chip) a survey of a large number of genes may not have been possible.10 DNA array offers tremendous advantages over traditional methods compared to the conventional single gene analysis methods such as northern hybridization11,12 and reverse transcriptasepolymerase chain reaction (RT-PCR). These days, DNA array technology has become one of the principal technologies for the high-throughput analysis in biological studies, and is capable of determining gene expression patterns and DNA sequence information of thousands of genes in a single experiment. This review is aimed to summarize the general aspects and to discuss the latest developments in the different application areas of nucleic acid array–based technology.
The utilization of sequence complementarity of DNA duplex is the principal method in DNA array. Traditionally, labeled nucleic acid molecules were used to determine the location of a particular sequence of DNA within a complex mixture. The detection relies on a hybridization procedure called Southern blotting.13 In the Southern blot procedure, DNA fragments digested by DNA restriction endonucleases are separated by electrophoresis, and denatured by soaking the gel in an alkaline solution. The fragments of singlestranded DNAs were then blotted onto a nylon membrane, reproducing the distribution of DNA fragments in the gel. This membrane is immersed in a solution containing a radioactively labeled DNA probe. By exposing X-ray film to the membrane, the results displayed on autoradiography, reveal the fragment to which the probe hybridizes. With the advent of recombinant technology, this technique is used for gene cloning and mapping, DNA fingerprinting, and restriction fragment length polymorphisms (RFLPs). The technique relies on membrane-based analysis introducing particular sequence correspondence between clones and hybridization signals. In every newly sequenced genome, it was almost impossible to describe relationships to known genes. The researchers established approaches to hybridize mRNA to cDNA libraries spotted on nylon filters for the expression analysis. This
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
analytical method seems to be more relevant to the form of the DNA array technology today, but modification of the immobilization method of probes is yet to be improved. The technical foundation for the development of DNA array revealed after the use of the solid support as an immobilization matrix. The improvement has also been made to the probe immobilization procedure by the use of robotic equipment called spotter14 or photolithographic techniques15 adapted from the semiconductor technology. The main distinction between DNA arrays and dot blots is the use of an impermeable solid substrate, such as glass or silicon. These types of substances have a number of advantages compared to the porous membrane used in dot blots, where the effect of the diffusion is negligible; because liquid solution cannot pass through the support, it results in direct access to the target DNA with probes. The flatness of the support is also advantageous in visualizing fluorescent microscopic images, improving reproducibility without the effect of interference of the support.16 As a result of the genome project, there has been an explosion in the amount of information available on the DNA sequence and a huge number of novel genes have been identified. Consequently, this feature greatly facilitated the study to organize and catalog the huge amount of DNA sequence information into the assignment of cellular functions to newly identified genes.
3 THE APPLICATION OF DNA ARRAY
Although the most common use of DNA arrays is gene expression profiling,17 this analytical tool has been used for multiple applications including genotyping, large-scale sequencing, copy number analysis, novel gene identification, diagnostics,18 and DNA–protein interactions. In expression profiling, DNA array is used to estimate the amount of mRNA transcribed across different tissues at the different cell stages,19,20 response to drugs, and comparative expression research between normal and diseased states.21 These studies are likely to help us to understand and explore the molecular physiological changes. The effect of the transcription and signal transduction by the various compounds are useful to define target molecules for
drug discovery.22 Alternatively, it could help us to clarify the specificity of the effects of inhibitors in cells, organs, and tissues. DNA array can also be used to read the particular sequence of a genome. SNP (single-nucleotide polymorphisms) DNA array is one of the examples used to identify genetic variation in individuals.23 The genetic variations are thought to be responsible for the susceptibility to genetically caused diseases in individuals; therefore the rapid detection and discovery of genetic predisposition to disease using DNA arrays are of importance to health care and medical treatment for selecting drugs and effective treatments. The microarrays for the determination of SNPs are being used to profile somatic mutations in cancer. Alternatively, DNA arrays to resequence portions of the genome in individuals have also been developed.24–27
4 DNA ARRAY FABRICATION
In general, oligonucleotides can be deposited on nylon membranes,28 controlled pore glass beads,29 activated dextran,30 avidin-coated polystyrene beads,31 nitrocellulose,32 polystyrene matrix,33 acrylamide gel,34 silicon, and glass.35 DNA arrays are usually made using an impermeable, rigid substrate, such as glass microscope slide and silicon. Therefore, target nucleic acids can be accessed by the probe without the effect of diffusion into pores. The oligonucleotides can be printed, spotted, or synthesized directly onto the support. DNA arrays can be classified into two groups depending on their fabrication method: (i) solid-phase synthesis, and (ii) by spotting presynthesized materials onto the solid substrates.
4.1
Solid-phase Synthesis
The first solid-phase synthesis utilizing photolithographic technology was applied to synthesize polypeptides. Photolithography, a method derived from semiconductor technology, possesses the ability of producing oligonucleotides with independent positions on the solid substrate.36–39 Phosphoramidite chemistry, which can be activated by light irradiation at appropriate positions and respond to characteristic patterns of lithographic
NUCLEIC ACID ARRAYS
3
Light Mask O O
O O O
O
O OH OH O
C
O O
C C
O
Chemical coupling
Substrate
Light
G T C C A C A A G T G C T C G A G G T A T T C C T
T
T
C
C
T
T
OH OH C
C
OH
Chemical coupling
Repeat Figure 1. Photolithographic DNA synthesis.
masks used to either transmit or block light onto the surface, is used (Figure 1). Mechanical and optical instrumentation are adopted and only distinct areas are illuminated. The coupling occurs only where that has been deprotected. The repetition of the removal of the photoprotecting groups and the phosphoramidite coupling steps synthesize probe DNAs on appropriate locations on the substrate by immersing in a solution containing adenine, thymine, cytosine, or guanine (GeneChip array technology by Affymetrix). New array fabrication formats are being developed. The use of a mechanical system similar to computer overhead projection systems and a Digital Micromirror Device (DMD) similar to Texas Instruments’ Digital Light Processor (DLP), have been reported for the replacement of the physical chromium masks used in Affymetrix array fabrication methods.40,41 The Maskless Array Synthesizer (MAS) technology (NimbleGen) has flexibility in creating a custom array.
4.2
Immobilization of Presynthesized Oligonucleotides
An alternative method is to place DNA directly on a solid surface. DNA fragments from the known genes, polymerase chain reaction (PCR) products, and oligonucleotides can be placed by
using robotic devices, known as spotters, that accurately deposit the DNA solution onto the support (Figure 2). Many thousands of spots are deposited in nanoliter quantities on a small surface area. The data generated from a single array experiment can mount up easily, where some DNA array experiments can contain up to tens of thousands of probe immobilized spots.
4.3
DNA Array Fabricated by Semiconductor Technologies
CombiMatrix has developed circuits containing arrays of individually addressable microelectrodes on the semiconductor device. Each microelectrode has the ability to selectively direct chemical reaction, facilitate the in situ synthesis of oligonucleotides onto each spot on the surface. The technique for the oligonucleotide synthesis reaction is called virtual flask technology where the reaction occurs only within the layer above each electrode.42,43 Using semiconductor technology, Nanogen has developed NanoChip Electronic Microarray for the rapid movement and concentration of a negatively charged DNA and/or RNA molecule by applying a positive electric current to designated electrodes on the device. The technology is applicable not only to electronically addressing nucleic
4
ARRAY TECHNOLOGIES Pressure
(a)
(b)
(c)
(d)
Pressure
Pressure
Figure 2. Examples of the spotter. (a) Pin, (b) ink-jet, (c) capillary, and (d) pin and ring type.
acid solutions and hybridization but can also apply stringency to remove nonspecifically bounded target DNAs after the hybridization process.44–46 The characteristic feature to concentrate and remove molecules on the device may offer advantages in efficiency and obtaining accurate results.
4.4
Other DNA Array Fabrication Technologies
Mitsubishi Rayon has created fibrous DNA array called Genopal , developed with the slicing method (http://www.mrc.co.jp/genome/e/index. html). Oligonucleotides are immobilized in the hollow fiber and put together in a “block”, and the blocks of DNA arrays are sliced. In this method, many DNA arrays can be created with unified specification, and are suited for the experiments for large quantities that are interested in the same sequences. Each oligonucleotide is immobilized in a 3D structured spot, said to be suitable for the effective hybridization and has high reproducibility, because equal quantities of the same sequences are thought to be immobilized in duplicate to each DNA array.
5 TARGET HYBRIDIZATION AND IMAGE ANALYSIS
A DNA array can be prepared from any known DNA sequences from any source, and positioned
on a solid substrate. DNA array can be hybridized with other fluorescently labeled target nucleic acids. In general, mRNA (messenger RNA) samples are collected from cells at two different cell stages, types of cells, or tissue samples. Two target DNAs are made from the cDNA, labeled with nucleotides that fluorescence in the different colors for each sample.47 After the addition of labeled cDNAs to a DNA array, cDNA hybridize to complementary probe sequences at appropriate temperatures and target DNA are washed to remove unhybridized target DNA. After the hybridization step, DNA array will be placed in a confocal laser scanning microscope. The target hybridized spots are excited by the laser, while spots that do not hybridize to a target are not. The fluorescence intensities are detected with each fluorescent by analyzing the digital image of the DNA array. Background data for each spot are calculated to create the ratios of the fluorescence intensities for every spot. Each spot on a DNA array is associated with a particular gene. Therefore, by comparing the fluorescence intensities for each spots, we may conclude which cells express genes of interest more than the other. The location and intensity of a fluorescent will also provide information of whether the mutation is present in the genome used as a target DNA. The computer program creates a table of the ratios labeled in the different colors.48 For example, when two fluorescent intensities were at nearly equal intensities, the computer may conclude that both cells express gene at the same level.
NUCLEIC ACID ARRAYS
The analysis of DNA arrays poses a large number of statistical problems, including standardization of the data for every spot on the array and this cause difficulties in evaluating all the data on every single gene.
6 POLYMORPHISM ANALYSIS
DNA arrays are used to detect polymorphisms in a gene sequence. In the analysis, probe sequences immobilized on support differs from that of the other spots in the same DNA array, sometimes by only one or a few sequences. This type of the analysis is called single-nucleotide polymorphisms, or SNPs (pronounced “snips”); small genetic differences of approximately 1 bp (base pair) in every 1000 bp that can occur between human population. The SNPs DNA array technology is used to survey a risk of developing particular diseases. The genomic DNA taken from an individual is hybridized to DNA array loaded with various labeled SNP sequences. The spots derived from the fluorescence scanning on the DNA array will show greater intensity when the target DNA hybridizes to a specific probe. SNP analysis can be used to test whether the individual may have or is at risk for developing a particular disease.
7 DNA ARRAY FABRICATED BY PLASMA-POLYMERIZATION TECHNOLOGY
Sequence-specific discrimination is the most important issue in DNA–DNA hybridization based gene analysis. Recent developments of DNA array technology have brought us a platform of already working daily routine systems and are widely applied to characterize and monitor the genome sequencing, expression analysis, disease diagnosis, and biological response to genotoxic contaminants. Although there are many promising new fields and techniques, some problems in selectivity still remain. To improve the specificity, one important aspect of the study will be the modification of the immobilization technique of the probe DNA on the solid support. Several technical issues
5
must be considered in investigating an immobilization technique including the chemical stability, the amenability to chemical modification, the surface area and loading capacity, and the degree of nonspecific binding. A method to decrease nonspecific binding of a target DNA has been described by the use of hydrophobic properties of thin films deposited using plasma-polymerization (PP) technique.49 Plasma processing is a standard industrial method for the deposition of thin polymeric films and modification of material surfaces (Figure 3). The films can be formed free of pinholes, will adhere strongly to a wide range of materials, and are highly resistant to chemical and physical treatments.50,51 PP technique is attractive because it is easy to control film thickness, the procedure can be performed in a dry condition, and the surface properties of the film can be controlled easily by changing monomer gas. A plasma-polymerized film (PPF) of hexamethyldisiloxane (HMDS: (CH3 )3 SiOSi(CH3 )3 ) was used52,53 to immobilize streptavidin on a glass substrate. Another layer of HMDS was additionally plasma-polymerized to the absorbed streptavidin on the substrate. As a result, the streptavidin was “embedded” between the two PPFs of HMDS, enabling them to capture biotinylated molecules such as end-primed biotinylated oligonucleotides (Figure 4). The second PPF-layer ˚ of PPF was sufficient of approximately 30–45 A to capture biotinylated molecules, while thick˚ significantly hindered the nesses of more than 90 A
Matching box
External electrode
Monomer
Sample stage
RF generator Rotary pump
Pressure gauge
Figure 3. An overview of the plasma-polymerization apparatus used to deposit thin film.
6
ARRAY TECHNOLOGIES
Oligonucleotide
either of the HMDS-PP layers, which is used for immobilizing streptavidin molecules, resulted in a decrease in biotin binding.49 This immobilization technique was used to bind biotinylated oligonucleotides in sequence-specific DNA–DNA hybridization. The hydrophobic properties of the HMDS-PPF (Figure 6) decreased nonspecific DNA binding to the substrate compared with a conventional poly-L-lysine-coated array.49 The method described here shows remarkable adaptability for the DNA hybridization analysis. Antibodies, too, can be immobilized on the solid support using PP technology. Antibodies are spotted and the second PPF-layer of approximately ˚ was sufficient to define presence or absence 60 A of proteins in a sample. Antibody array has been applied for the elucidation of interaction partners (Figure 7).
Probe DNA
Biotin Streptavidin
Second PP film First PP film
Substrate (glass or silicon)
Figure 4. The illustration of the expected dimension of the immobilized protein.
streptavidin–biotin interactions (Figure 5). Fluorescence analysis revealed that the absence of
0
30
90
60
120
240
First PP layer (Å)
50
0
15 30 45 60 90 120 240
Second PP layer (Å)
15 30 45 60 90 120
Fluorescence intensity (au)
0 40
30
20
10
240 0
0 15 30 45 60 90 120 240 Thickness of the second PP layer (Å)
Figure 5. The result of the fluorescent intensities on the different thicknesses of the PPF. In order to examine whether immobilized streptavidin retained its binding properties with biotin, the streptavidin-immobilized support was immersed in fluorescein-labeled ˚ for biotin solution and screened for fluorescence. The result showed that the highest fluorescence intensity is observed at 30 A ˚ The the second plasma-polymerization layer. The fluorescence intensity dropped dramatically upon application of more than 30 A. result indicates that the PP layer of greater thickness have an adverse effect on streptavidin–biotin interactions. We assume that the ˚ streptavidin binding site was buried after deposition of second film greater than 30 A.
NUCLEIC ACID ARRAYS
hydrophobic and/or hydrophilic surface PPF based on the PP–DNA array fabrication method. The sequences of two polymorphic loci were used as a probe on the array and the effect on singlenucleotide mismatch detection has been studied with the unique structure of the target DNA.56 To investigate whether or how hybridization is affected by the surface properties, 5 -biotinylated oligonucleotides were immobilized by streptavidin–biotin binding on the surface-modified support. The probe sequences were derived from positions within the human SNPs site, ApoE gene.57–61 Among three common ApoE isoforms; ApoE2 has Cys at amino acids 112 and 158; ApoE3, Cys at amino acid 112 and an Arg at 158; ApoE4, Arg at both positions. The ApoE genotypes were tested at the two different allele positions (at 112 and 158). Eight types of biotinylated oligonucleotides were immobilized, and hybridized with the labeled target complementary oligonucleotide.55 The highest signal was obtained with the fully complementary oligonucleotides compared with those with the single-base mismatch or having unrelated sequences. The results also showed that the fluorescence signals obtained using the HMDS-PP (surface hydrophobic) array was higher than that from the acetonitrile–PP (surface hydrophilic) array (Figure 8). A comparison of time dependency of hybridization between two surface properties was also examined. The results of the hybridization analysis show that the fluorescence signal increased rapidly when HMDS-PP (hydrophilic support surface) was
(b)
Figure 6. The hydrophobic properties of HMDS-PPF. A side view of 2 µl of water delivered (a) glass, (b) 6-nm of HMDS plasma-polymerized film.
8 THE EFFECT OF THE SURFACE PROPERTIES
fe ns
fe
tra
ns
ti-
ra
An
Transferrin
i-t
FITC FITC FITC
An t
FITC
rri
n
In our previous work, PPF of HMDS was applied to devise an immobilization method as a decent DNA-immobilization matrix.49 Compared to the conventional poly-lysine matrix, nonspecific binding of target DNAs onto the surface was reduced.54 This may be attributed to the hydrophobicity of the HMDS-PP layer. Though probe-surrounding properties may influence DNA interactions, there have been only a few systematic studies of the factors affecting hybridization behavior. To improve the overall efficiency of hybridization on the DNA array, we studied the hybridization behavior by changing the surface hydrophobicity and determined whether probe-surrounding properties are essential factors for the specific DNA hybridization on the DNA array.55 This study was done by immobilizing probe DNAs on a
rri n An tiAn tran ti- sfe An tran rrin ti- sfe tra rr ns in fe rri n
(a)
7
FITC
Fluorescence intensity
Second PP layer High
FITC
Antibody (antitransferrin)
Fluorescence intensity
First PP layer
Low
Nonspecific antibodies Figure 7. Antibody array fabricated by PP technology.
ARRAY TECHNOLOGIES Biotinylated molecule Hydrophobic film
Hydrophilic film
Streptavidin HMDS-PP layer (60 Å)
Hydrophobic Fluorescence intensity (au)
8
500 400 300 Hydrophilic 200 100 0
Glass substrate
AGCT
AGCT
Probe DNA Figure 8. Hybridization experiment on hydrophilic and hydrophobic DNA array surfaces.
used as an immobilization matrix. It is also an important factor to carefully control the surface charge of the DNA array. The differences of the hybridization behavior may be because the probe DNAs were detached from the PP matrix and that contributed to an improvement in the signal-tonoise ratio. These results suggest that the surface properties of DNA array are one of the crucial factors to obtain reliable results and significantly influence the environment in which the DNA hybridization takes place.
9 OUTLOOK OF DNA ARRAY TECHNOLOGY
Over the years, DNA array technology has become one of the principal platform technologies for the high-throughput analysis in biological research. New array formats are being developed to study biological functions. Cell-based array is one of the platforms of the DNA array–based technique to elucidate the biological function of each gene function.62,63 In cell-based array technology, plasmids or RNAs are spotted on the substrate and used to transfect cultured cells. Cells were cultured, and transfected with the localized probes. This technique allows the rapid generation of a desired phenotype, screening of specific proteins, and assays on transient phenotypes of living cells in real time
with limited adherent cells for easily transfectable cells. A new platform has been proposed for the genomewide location analysis. ChIP-chip (also known as ChIP-on-chip) is a technique that joins DNA array (DNA chip) with chromatin immunoprecipitation (ChIP) technology. ChIP-chip is used to investigate interactions of the specific DNAbinding proteins (DBPs) within a particular region on the genomic DNA. In ChIP-chip assay, intact cells are fixed and stabilized with formaldehyde in vivo to preserve protein–DNA interactions. The cross-linked chromatin-associated proteins to DNA are then conjugated with specific antibodies associated with the protein of interest. Chromatin immunoprecipitation is performed by immunoprecipitating antibody–protein–DNA complexes. The DNA is eluted by the reversal of cross-links and the removal of proteins. DNA fragments are then performed blunting and ligation steps followed by PCR; because the immunoprecipitated DNA is typically present in very small quantities, it is necessary to perform an amplification step prior to subsequent labeling and DNA array analysis. The results of ChIP-chip assay indicate the functions of transcriptional regulators including promoters, repressors, enhancers, and DNA replication, and so on,64–66 in the development and/or disease progression. Any DBP can be analyzed with this technique, without the knowledge of the potential binding sites and therefore the applications of ChIP-chip assay gives genomewide distribution of the binding sites of many DBPs, promoter
NUCLEIC ACID ARRAYS
regions, transcription factors, chromatin-associated proteins, DNA replication, recombination, histone modifications, and chromatin structure. Fukumori et al. reported a rapid and efficient detection of DBPs using a single-stranded stemloop structured DNA as a probe.67 To demonstrate the validity of detecting DBPs on the solid support, Cro protein68 derived from λ phage was used as a model DBP associated with two commonly used modification enzymes; exonuclease III and Taq DNA polymerase. By combining these two enzymes and by the use of fluorescently labeled deoxynucleotide as one of the substrates in the extension step, DBPs were to be detected by a counterpart of fluorescence incorporated signal visualized as a “spot” on DNA array. The assay depends on inhibition of Exo III reaction, the same principle known as Exo III stop assay69–71 and strand elongation by a thermostable Taq DNA polymerase, commonly used in PCR. The unique feature of this method is that it uses a stem-loop structured probe, because fluorescently labeled dUTP is incorporated covalently to the digested probe DNA allowing extreme washing without any effect on the resulting fluorescence signals. Therefore, the errors caused by the nonspecific adsorption can be avoided. This reaction can also be applied to detect DBPs present in the nucleus. NF-κB72 in the Jurkat cell extract has been detected in the same way. In this method, any DBPs can be detected within 30 min using a stem and loop ds-DNA array without labeling proteins or the use of the antibodies. Obtaining an insight into entire genomes for the acquisition of complete and reliable information on cells, tissues, or the entire organisms, that previously would have taken years, has been shortened to a matter of weeks by the use of DNA array technology. A new method of applying other technologies with a DNA array is still in its infancy but growing rapidly due to the interest in gaining a wider understanding of the biological processes. These new developments may become a new platform for the high-throughput screening technology in the future. REFERENCES 1. International Human Genome Sequencing Consortium, Finishing the euchromatic sequence of the human genome. Nature, 2004, 431(7011), 931–945.
9
2. J. C. Venter, J. C. Venter, M. D. Adams, E. W. Myers, P. W. Li, R. J. Mural, G. G. Sutton, H. O. Smith, M. Yandell, C. A. Evans, R. A. Holt, J. D. Gocayne, P. Amanatides, R. M. Ballew, D. H. Huson, J. R. Wortman, Q. Zhang, C. D. Kodira, X. H. Zheng, L. Chen, M. Skupski, G. Subramanian, P. D. Thomas, J. Zhang, G. L. Gabor Miklos, C. Nelson, S. Broder, A. G. Clark, J. Nadeau, V. A. McKusick, N. Zinder, A. J. Levine, R. J. Roberts, M. Simon, C. Slayman, M. Hunkapiller, R. Bolanos, A. Delcher, I. Dew, D. Fasulo, M. Flanigan, L. Florea, A. Halpern, S. Hannenhalli, S. Kravitz, S. Levy, C. Mobarry, K. Reinert, K. Remington, J. Abu-Threideh, E. Beasley, K. Biddick, V. Bonazzi, R. Brandon, M. Cargill, I. Chandramouliswaran, R. Charlab, K. Chaturvedi, Z. Deng, V. Di Francesco, P. Dunn, K. Eilbeck, C. Evangelista, A. E. Gabrielian, W. Gan, W. Ge, F. Gong, Z. Gu, P. Guan, T. J. Heiman, M. E. Higgins, R. R. Ji, Z. Ke, K. A. Ketchum, Z. Lai, Y. Lei, Z. Li, J. Li, Y. Liang, X. Lin, F. Lu, G. V. Merkulov, N. Milshina, H. M. Moore, A. K. Naik, V. A. Narayan, B. Neelam, D. Nusskern, D. B. Rusch, S. Salzberg, W. Shao, B. Shue, J. Sun, Z. Wang, A. Wang, X. Wang, J. Wang, M. Wei, R. Wides, C. Xiao, C. Yan, A. Yao, J. Ye, M. Zhan, W. Zhang, H. Zhang, Q. Zhao, L. Zheng, F. Zhong, W. Zhong, S. Zhu, S. Zhao, D. Gilbert, S. Baumhueter, G. Spier, C. Carter, A. Cravchik, T. Woodage, F. Ali, H. An, A. Awe, D. Baldwin, H. Baden, M. Barnstead, I. Barrow, K. Beeson, D. Busam, A. Carver, A. Center, M. L. Cheng, L. Curry, S. Danaher, L. Davenport, R. Desilets, S. Dietz, K. Dodson, L. Doup, S. Ferriera, N. Garg, A. Gluecksmann, B. Hart, J. Haynes, C. Haynes, C. Heiner, S. Hladun, D. Hostin, J. Houck, T. Howland, C. Ibegwam, J. Johnson, F. Kalush, L. Kline, S. Koduru, A. Love, F. Mann, D. May, S. McCawley, T. McIntosh, I. McMullen, M. Moy, L. Moy, B. Murphy, K. Nelson, C. Pfannkoch, E. Pratts, V. Puri, H. Qureshi, M. Reardon, R. Rodriguez, Y. H. Rogers, D. Romblad, B. Ruhfel, R. Scott, C. Sitter, M. Smallwood, E. Stewart, R. Strong, E. Suh, R. Thomas, N. N. Tint, S. Tse, C. Vech, G. Wang, J. Wetter, S. Williams, M. Williams, S. Windsor, E. Winn-Deen, K. Wolfe, J. Zaveri, K. Zaveri, J. F. Abril, R. Guig´o, M. J. Campbell, K. V. Sjolander, B. Karlak, A. Kejariwal, H. Mi, B. Lazareva, T. Hatton, A. Narechania, K. Diemer, A. Muruganujan, N. Guo, S. Sato, V. Bafna, S. Istrail, R. Lippert, R. Schwartz, B. Walenz, S. Yooseph, D. Allen, A. Basu, J. Baxendale, L. Blick, M. Caminha, J. Carnes-Stine, P. Caulk, Y. H. Chiang, M. Coyne, C. Dahlke, A. Mays, M. Dombroski, M. Donnelly, D. Ely, S. Esparham, C. Fosler, H. Gire, S. Glanowski, K. Glasser, A. Glodek, M. Gorokhov, K. Graham, B. Gropman, M. Harris, J. Heil, S. Henderson, J. Hoover, D. Jennings, C. Jordan, J. Jordan, J. Kasha, L. Kagan, C. Kraft, A. Levitsky, M. Lewis, X. Liu, J. Lopez, D. Ma, W. Majoros, J. McDaniel, S. Murphy, M. Newman, T. Nguyen, N. Nguyen, M. Nodell, S. Pan, J. Peck, M. Peterson, W. Rowe, R. Sanders, J. Scott, M. Simpson, T. Smith, A. Sprague, T. Stockwell, R. Turner, E. Venter, M. Wang, M. Wen, D. Wu, M. Wu, A. Xia, A. Zandieh, and X. Zhu, The sequence of the human genome. Science, 2001, 291(5507), 1304–1351.
10
ARRAY TECHNOLOGIES
3. E. S. Lander, L. M. Linton, B. Birren, C. Nusbaum, M. C. Zody, J. Baldwin, K. Devon, K. Dewar, M. Doyle, W. FitzHugh, R. Funke, D. Gage, K. Harris, A. Heaford, J. Howland, L. Kann, J. Lehoczky, R. LeVine, P. McEwan, K. McKernan, J. Meldrim, J. P. Mesirov, C. Miranda, W. Morris, J. Naylor, C. Raymond, M. Rosetti, R. Santos, A. Sheridan, C. Sougnez, N. StangeThomann, N. Stojanovic, A. Subramanian, D. Wyman, J. Rogers, J. Sulston, R. Ainscough, S. Beck, D. Bentley, J. Burton, C. Clee, N. Carter, A. Coulson, R. Deadman, P. Deloukas, A. Dunham, I. Dunham, R. Durbin, L. French, D. Grafham, S. Gregory, T. Hubbard, S. Humphray, A. Hunt, M. Jones, C. Lloyd, A. McMurray, L. Matthews, S. Mercer, S. Milne, J. C. Mullikin, A. Mungall, R. Plumb, M. Ross, R. Shownkeen, S. Sims, R. H. Waterston, R. K. Wilson, L. W. Hillier, J. D. McPherson, M. A. Marra, E. R. Mardis, L. A. Fulton, A. T. Chinwalla, K. H. Pepin, W. R. Gish, S. L. Chissoe, M. C. Wendl, K. D. Delehaunty, T. L. Miner, A. Delehaunty, J. B. Kramer, L. L. Cook, R. S. Fulton, D. L. Johnson, P. J. Minx, S. W. Clifton, T. Hawkins, E. Branscomb, P. Predki, P. Richardson, S. Wenning, T. Slezak, N. Doggett, J. F. Cheng, A. Olsen, S. Lucas, C. Elkin, E. Uberbacher, M. Frazier, R. A. Gibbs, D. M. Muzny, S. E. Scherer, J. B. Bouck, E. J. Sodergren, K. C. Worley, C. M. Rives, J. H. Gorrell, M. L. Metzker, S. L. Naylor, R. S. Kucherlapati, D. L. Nelson, G. M. Weinstock, Y. Sakaki, A. Fujiyama, M. Hattori, T. Yada, A. Toyoda, T. Itoh, C. Kawagoe, H. Watanabe, Y. Totoki, T. Taylor, J. Weissenbach, R. Heilig, W. Saurin, F. Artiguenave, P. Brottier, T. Bruls, E. Pelletier, C. Robert, P. Wincker, D. R. Smith, L. Doucette-Stamm, M. Rubenfield, K. Weinstock, H. M. Lee, J. Dubois, A. Rosenthal, M. Platzer, G. Nyakatura, S. Taudien, A. Rump, H. Yang, J. Yu, J. Wang, G. Huang, J. Gu, L. Hood, L. Rowen, A. Madan, S. Qin, R. W. Davis, N. A. Federspiel, A. P. Abola, M. J. Proctor, R. M. Myers, J. Schmutz, M. Dickson, J. Grimwood, D. R. Cox, M. V. Olson, R. Kaul, C. Raymond, N. Shimizu, K. Kawasaki, S. Minoshima, G. A. Evans, M. Athanasiou, R. Schultz, B. A. Roe, F. Chen, H. Pan, J. Ramser, H. Lehrach, R. Reinhardt, W. R. McCombie, M. de la Bastide, N. Dedhia, H. Bl¨ocker, K. Hornischer, G. Nordsiek, R. Agarwala, L. Aravind, J. A. Bailey, A. Bateman, S. Batzoglou, E. Birney, P. Bork, D. G. Brown, C. B. Burge, L. Cerutti, H. C. Chen, D. Church, M. Clamp, R. R. Copley, T. Doerks, S. R. Eddy, E. E. Eichler, T. S. Furey, J. Galagan, J. G. Gilbert, C. Harmon, Y. Hayashizaki, D. Haussler, H. Hermjakob, K. Hokamp, W. Jang, L. S. Johnson, T. A. Jones, S. Kasif, A. Kasprzyk, S. Kennedy, W. J. Kent, P. Kitts, E. V. Koonin, I. Korf, D. Kulp, D. Lancet, T. M. Lowe, A. McLysaght, T. Mikkelsen, J. V. Moran, N. Mulder, V. J. Pollara, C. P. Ponting, G. Schuler, J. Schultz, G. Slater, A. F. Smit, E. Stupka, J. Szustakowski, D. Thierry-Mieg, J. ThierryMieg, L. Wagner, J. Wallis, R. Wheeler, A. Williams, Y. I. Wolf, K. H. Wolfe, S. P. Yang, R. F. Yeh, F. Collins, M. S. Guyer, J. Peterson, A. Felsenfeld, K. A. Wetterstrand, A. Patrinos, M. J. Morgan, P. de Jong, J. J. Catanese, K. Osoegawa, H. Shizuya, S. Choi, Y. J. Chen, and J. Szustakowski, Initial sequencing and analysis of the human genome. Nature, 2001, 409(6822), 860–921.
4. C. M. Wade, E. J. Kulbokas III, A. W. Kirby, M. C. Zody, J. C. Mullikin, E. S. Lander, K. Lindblad-Toh, and M. J. Daly, The mosaic structure of variation in the laboratory mouse genome. Nature, 2002, 420(6915), 574–578. 5. R. H. Waterston, K. Lindblad-Toh, E. Birney, J. Rogers, J. F. Abril, P. Agarwal, R. Agarwala, R. Ainscough, M. Alexandersson, P. An, S. E. Antonarakis, J. Attwood, R. Baertsch, J. Bailey, K. Barlow, S. Beck, E. Berry, B. Birren, T. Bloom, P. Bork, M. Botcherby, N. Bray, M. R. Brent, D. G. Brown, S. D. Brown, C. Bult, J. Burton, J. Butler, R. D. Campbell, P. Carninci, S. Cawley, F. Chiaromonte, A. T. Chinwalla, D. M. Church, M. Clamp, C. Clee, F. S. Collins, L. L. Cook, R. R. Copley, A. Coulson, O. Couronne, J. Cuff, V. Curwen, T. Cutts, M. Daly, R. David, J. Davies, K. D. Delehaunty, J. Deri, E. T. Dermitzakis, C. Dewey, N. J. Dickens, M. Diekhans, S. Dodge, I. Dubchak, D. M. Dunn, S. R. Eddy, L. Elnitski, R. D. Emes, P. Eswara, E. Eyras, A. Felsenfeld, G. A. Fewell, P. Flicek, K. Foley, W. N. Frankel, L. A. Fulton, R. S. Fulton, T. S. Furey, D. Gage, R. A. Gibbs, G. Glusman, S. Gnerre, N. Goldman, L. Goodstadt, D. Grafham, T. A. Graves, E. D. Green, S. Gregory, R. Guig´o, M. Guyer, R. C. Hardison, D. Haussler, Y. Hayashizaki, L. W. Hillier, A. Hinrichs, W. Hlavina, T. Holzer, F. Hsu, A. Hua, T. Hubbard, A. Hunt, I. Jackson, D. B. Jaffe, L. S. Johnson, M. Jones, T. A. Jones, A. Joy, M. Kamal, E. K. Karlsson, D. Karolchik, A. Kasprzyk, J. Kawai, E. Keibler, C. Kells, W. J. Kent, A. Kirby, D. L. Kolbe, I. Korf, R. S. Kucherlapati, E. J. Kulbokas, D. Kulp, T. Landers, J. P. Leger, S. Leonard, I. Letunic, R. Levine, J. Li, M. Li, C. Lloyd, S. Lucas, B. Ma, D. R. Maglott, E. R. Mardis, L. Matthews, E. Mauceli, J. H. Mayer, M. McCarthy, W. R. McCombie, S. McLaren, K. McLay, J. D. McPherson, J. Meldrim, B. Meredith, J. P. Mesirov, W. Miller, T. L. Miner, E. Mongin, K. T. Montgomery, M. Morgan, R. Mott, J. C. Mullikin, D. M. Muzny, W. E. Nash, J. O. Nelson, M. N. Nhan, R. Nicol, Z. Ning, C. Nusbaum, M. J. O’Connor, Y. Okazaki, K. Oliver, E. Overton-Larty, L. Pachter, G. Parra, K. H. Pepin, J. Peterson, P. Pevzner, R. Plumb, C. S. Pohl, A. Poliakov, T. C. Ponce, C. P. Ponting, S. Potter, M. Quail, A. Reymond, B. A. Roe, K. M. Roskin, E. M. Rubin, A. G. Rust, R. Santos, V. Sapojnikov, B. Schultz, J. Schultz, M. S. Schwartz, S. Schwartz, C. Scott, S. Seaman, S. Searle, T. Sharpe, A. Sheridan, R. Shownkeen, S. Sims, J. B. Singer, G. Slater, A. Smit, D. R. Smith, B. Spencer, A. Stabenau, N. StangeThomann, C. Sugnet, M. Suyama, G. Tesler, J. Thompson, D. Torrents, E. Trevaskis, J. Tromp, C. Ucla, A. UretaVidal, J. P. Vinson, A. C. Von Niederhausern, C. M. Wade, M. Wall, R. J. Weber, R. B. Weiss, M. C. Wendl, A. P. West, K. Wetterstrand, R. Wheeler, S. Whelan, J. Wierzbowski, D. Willey, S. Williams, R. K. Wilson, E. Winter, K. C. Worley, D. Wyman, S. Yang, S. P. Yang, E. M. Zdobnov, M. C. Zody, and E. S. Lander, Initial sequencing and comparative analysis of the mouse genome. Nature, 2002, 420(6915), 520–562. 6. S. Aparicio, J. Chapman, E. Stupka, N. Putnam, J.-M. Chia, P. Dehal, A. Christoffels, S. Rash, S. Hoon, A. Smit, M. D. S. Gelpke, J. Roach, T. Oh, I. Y. Ho, M. Wong, C. Detter, F. Verhoef, P. Predki, A. Tay, S. Lucas,
NUCLEIC ACID ARRAYS P. Richardson, S. F. Smith, M. S. Clark, Y. J. K. Edwards, N. Doggett, A. Zharkikh, S. V. Tavtigian, D. Pruss, M. Barnstead, C. Evans, H. Baden, J. Powell, G. Glusman, L. Rowen, L. Hood, Y. H. Tan, G. Elgar, T. Hawkins, B. Venkatesh, D. Rokhsar, and S. Brenner, Whole-genome shotgun assembly and analysis of the genome of Fugu rubripes. Science, 2002, 297(5585), 1301–1310. 7. M. D. Adams, S. E. Celniker, R. A. Holt, C. A. Evans, J. D. Gocayne, P. G. Amanatides, S. E. Scherer, P. W. Li, R. A. Hoskins, R. F. Galle, R. A. George, S. E. Lewis, S. Richards, M. Ashburner, S. N. Henderson, G. G. Sutton, J. R. Wortman, M. D. Yandell, Q. Zhang, L. X. Chen, R. C. Brandon, Y. H. Rogers, R. G. Blazej, M. Champe, B. D. Pfeiffer, K. H. Wan, C. Doyle, E. G. Baxter, G. Helt, C. R. Nelson, G. L. Gabor, J. F. Abril, A. Agbayani, H. J. An, C. Andrews-Pfannkoch, D. Baldwin, R. M. Ballew, A. Basu, J. Baxendale, L. Bayraktaroglu, E. M. Beasley, K. Y. Beeson, P. V. Benos, B. P. Berman, D. Bhandari, S. Bolshakov, D. Borkova, M. R. Botchan, J. Bouck, P. Brokstein, P. Brottier, K. C. Burtis, D. A. Busam, H. Butler, E. Cadieu, A. Center, I. Chandra, J. M. Cherry, S. Cawley, C. Dahlke, L. B. Davenport, P. Davies, B. de Pablos, A. Delcher, Z. Deng, A. D. Mays, I. Dew, S. M. Dietz, K. Dodson, L. E. Doup, M. Downes, S. Dugan-Rocha, B. C. Dunkov, P. Dunn, K. J. Durbin, C. C. Evangelista, C. Ferraz, S. Ferriera, W. Fleischmann, C. Fosler, A. E. Gabrielian, N. S. Garg, W. M. Gelbart, K. Glasser, A. Glodek, F. Gong, J. H. Gorrell, Z. Gu, P. Guan, M. Harris, N. L. Harris, D. Harvey, T. J. Heiman, J. R. Hernandez, J. Houck, D. Hostin, K. A. Houston, T. J. Howland, M. H. Wei, C. Ibegwam, M. Jalali, F. Kalush, G. H. Karpen, Z. Ke, J. A. Kennison, K. A. Ketchum, B. E. Kimmel, C. D. Kodira, C. Kraft, S. Kravitz, D. Kulp, Z. Lai, P. Lasko, Y. Lei, A. A. Levitsky, J. Li, Z. Li, Y. Liang, X. Lin, X. Liu, B. Mattei, T. C. McIntosh, M. P. McLeod, D. McPherson, G. Merkulov, N. V. Milshina, C. Mobarry, J. Morris, A. Moshrefi, S. M. Mount, M. Moy, B. Murphy, L. Murphy, D. M. Muzny, D. L. Nelson, D. R. Nelson, K. A. Nelson, K. Nixon, D. R. Nusskern, J. M. Pacleb, M. Palazzolo, G. S. Pittman, S. Pan, J. Pollard, V. Puri, M. G. Reese, K. Reinert, K. Remington, R. D. Saunders, F. Scheeler, H. Shen, B. C. Shue, I. Sid´en-Kiamos, M. Simpson, M. P. Skupski, T. Smith, E. Spier, A. C. Spradling, M. Stapleton, R. Strong, E. Sun, R. Svirskas, C. Tector, R. Turner, E. Venter, A. H. Wang, X. Wang, Z. Y. Wang, D. A. Wassarman, G. M. Weinstock, J. Weissenbach, S. M. Williams, T. Woodage, K. C. Worley, D. Wu, S. Yang, Q. A. Yao, J. Ye, R. F. Yeh, J. S. Zaveri, M. Zhan, G. Zhang, Q. Zhao, L. Zheng, X. H. Zheng, F. N. Zhong, W. Zhong, X. Zhou, S. Zhu, X. Zhu, H. O. Smith, R. A. Gibbs, E. W. Myers, G. M. Rubin, and J. C. Venter, The genome sequence of Drosophila melanogaster. Science, 2000, 287(5461), 2185–2195. 8. F. R. Blattner, G. Plunkett, C. A. Bloch, N. T. Perna, V. Burland, M. Riley, J. Collado-Vides, J. D. Glasner, C. K. Rode, G. F. Mayhew, J. Gregor, N. W. Davis, H. A. Kirkpatrick, M. A. Goeden, D. J. Rose, B. Mau, and Y. Shao, The complete genome sequence of Escherichia coli K-12. Science, 1997, 277(5331), 1453–1474. 9. T. S. Mikkelsen, M. J. Wakefield, B. Aken, C. T. Amemiya, J. L. Chang, S. Duke, M. Garber, A. J. Gentles, L. Goodstadt, A. Heger, J. Jurka, M. Kamal, E. Mauceli,
11
S. M. Searle, T. Sharpe, M. L. Baker, M. A. Batzer, P. V. Benos, K. Belov, M. Clamp, A. Cook, J. Cuff, R. Das, L. Davidow, J. E. Deakin, M. J. Fazzari, J. L. Glass, M. Grabherr, J. M. Greally, W. Gu, T. A. Hore, G. A. Huttley, M. Kleber, R. L. Jirtle, E. Koina, J. T. Lee, S. Mahony, M. A. Marra, R. D. Miller, R. D. Nicholls, M. Oda, A. T. Papenfuss, Z. E. Parra, D. D. Pollock, D. A. Ray, J. E. Schein, T. P. Speed, K. Thompson, J. L. VandeBerg, C. M. Wade, J. A. Walker, P. D. Waters, C. Webber, J. R. Weidman, X. Xie, M. C. Zody, Broad Institute Genome Sequencing Platform; Broad Institute Whole Genome Team Assembly, J. Baldwin, A. Abdouelleil, J. Abdulkadir, A. Abebe, B. Abera, J. Abreu, S. C. Acer, L. Aftuck, A. Alexander, P. An, E. Anderson, S. Anderson, H. Arachi, M. Azer, P. Bachantsang, A. Barry, T. Bayul, A. Berlin, D. Bessette, T. Bloom, T. Bloom, L. Boguslavskiy, C. Bonnet, B. Boukhgalter, I. Bourzgui, A. Brown, P. Cahill, S. Channer, Y. Cheshatsang, L. Chuda, M. Citroen, A. Collymore, P. Cooke, M. Costello, K. D’Aco, R. Daza, G. De Haan, S. DeGray, C. DeMaso, N. Dhargay, K. Dooley, E. Dooley, M. Doricent, P. Dorje, K. Dorjee, A. Dupes, R. Elong, J. Falk, A. Farina, S. Faro, D. Ferguson, S. Fisher, C. D. Foley, A. Franke, D. Friedrich, L. Gadbois, G. Gearin, C. R. Gearin, G. Giannoukos, T. Goode, J. Graham, E. Grandbois, S. Grewal, K. Gyaltsen, N. Hafez, B. Hagos, J. Hall, C. Henson, A. Hollinger, T. Honan, M. D. Huard, L. Hughes, B. Hurhula, M. E. Husby, A. Kamat, B. Kanga, S. Kashin, D. Khazanovich, P. Kisner, K. Lance, M. Lara, W. Lee, N. Lennon, F. Letendre, R. LeVine, A. Lipovsky, X. Liu, J. Liu, S. Liu, T. Lokyitsang, Y. Lokyitsang, R. Lubonja, A. Lui, P. MacDonald, V. Magnisalis, K. Maru, C. Matthews, W. McCusker, S. McDonough, T. Mehta, J. Meldrim, L. Meneus, O. Mihai, A. Mihalev, T. Mihova, R. Mittelman, V. Mlenga, A. Montmayeur, L. Mulrain, A. Navidi, J. Naylor, T. Negash, T. Nguyen, N. Nguyen, R. Nicol, C. Norbu, N. Norbu, N. Novod, B. O’Neill, S. Osman, E. Markiewicz, O. L. Oyono, C. Patti, P. Phunkhang, F. Pierre, M. Priest, S. Raghuraman, F. Rege, R. Reyes, C. Rise, P. Rogov, K. Ross, E. Ryan, S. Settipalli, T. Shea, N. Sherpa, L. Shi, D. Shih, T. Sparrow, J. Spaulding, J. Stalker, N. Stange-Thomann, S. Stavropoulos, C. Stone, C. Strader, S. Tesfaye, T. Thomson, Y. Thoulutsang, D. Thoulutsang, K. Topham, I. Topping, T. Tsamla, H. Vassiliev, A. Vo, T. Wangchuk, T. Wangdi, M. Weiand, J. Wilkinson, A. Wilson, S. Yadav, G. Young, Q. Yu, L. Zembek, D. Zhong, A. Zimmer, Z. Zwirko, Broad Institute Whole Genome Team Assembly, D. B. Jaffe, P. Alvarez, W. Brockman, J. Butler, C. Chin, S. Gnerre, I. MacCallum, J. A. Graves, C. P. Ponting, M. Breen, P. B. Samollow, E. S. Lander, and K. LindbladToh, Genome of the marsupial Monodelphis domestica reveals innovation in non-coding sequences. Nature, 2007, 447(7141), 167–177. 10. A. Marshall and J. Hodgson, DNA chips: an array of possibilities. Nature Biotechnology, 1998, 16(1), 27–31. 11. J. C. Alwine, D. J. Kemp, and G. R. Stark, Method for detection of specific RNAs in agarose gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes. Proceedings of the National Academy of Sciences of the United States of America, 1977, 74(12), 5350–5354.
12
ARRAY TECHNOLOGIES
12. J. C. Alwine, D. J. Kemp, B. A. Parker, J. Reiser, J. Renart, G. R. Stark, and G. M. Wahl, Detection of specific RNAs or specific fragments of DNA by fractionation in gels and transfer to diazobenzyloxymethyl paper. Methods in Enzymology, 1979, 68, 220–242. 13. E. M. Southern, Detection of specific sequences among DNA fragments separated by gel electrophoresis. Journal of Molecular Biology, 1975, 98(3), 503–517. 14. V. G. Cheung, M. Morley, F. Aguilar, A. Massimi, R. Kucherlapati, and G. Childs, Making and reading microarrays. Nature Genetics, 1999, 21(Suppl. 1), 15–19. 15. R. J. Lipshutz, S. P. A. Fodor, T. R. Gingeras, and D. J. Lockhart, High density synthetic oligonucleotide arrays. Nature Genetics, 1999, 21(Suppl. 1), 20–24. 16. E. Southern, K. Mir, and M. Shchepinov, Molecular interactions on microarrays. Nature Genetics, 1999, 21(Suppl. 1), 5–9. 17. M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270(5235), 467–470. 18. J. G. Hacia, Resequencing and mutational analysis using oligonucleotide microarrays. Nature Genetics, 1999, 21(Suppl. 1), 42–47. 19. V. R. Iyer, M. B. Eisen, D. T. Ross, G. Schuler, T. Moore, J. C. Lee, J. M. Trent, L. M. Staudt, J. Hudson, M. S. Boguski, D. Lashkari, D. Shalon, D. Botstein, and P. O. Brown, The transcriptional program in the response of human fibroblasts to serum. Science, 1999, 283(5398), 83–87. 20. P. T. Spellman, G. Sherlock, M. Q. Zhang, V. R. Iyer, K. Anders, M. B. Eisen, P. O. Brown, D. Botstein, and B. Futcher, Comprehensive identification of cell cycleregulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell, 1998, 9(12), 3273–3297. 21. J. Marx, Medicine. DNA arrays reveal cancer in its many forms. Science, 2000, 289(5485), 1670–1672. 22. C. Debouck and P. N. Goodfellow, DNA microarrays in drug discovery and development. Nature Genetics, 1999, 21(Suppl. 1), 48–50. 23. A. Chakravarti, Population genetics–making sense out of sequence. Nature Genetics, 1999, 21(Suppl. 1), 56–60. 24. Z. Strezoska, T. Paunesku, D. Radosavljevi´c, I. Labat, R. Drmanac, and R. Crkvenjakov, DNA sequencing by hybridization: 100 bases read by a non-gelbased method. Proceedings of the National Academy of Sciences of the United States of America, 1991, 88(22), 10089–10093. 25. N. E. Broude, T. Sano, C. L. Smith, and C. R. Cantor, Enhanced DNA sequencing by hybridization. Proceedings of the National Academy of Sciences of the United States of America, 1994, 91(8), 3072–3076. 26. R. Drmanac, S. Drmanac, I. Labat, R. Crkvenjakov, A. Vicentic, and A. Gemmell, Sequencing by hybridization: towards an automated sequencing of one million M13 clones arrayed on membranes. Electrophoresis, 1992, 13(8), 566–573.
27. R. Drmanac, I. Labat, I. Brukner, and R. Crkvenjakov, Sequencing of megabase plus DNA by hybridization: theory of the method. Genomics, 1989, 4(2), 114–128. 28. J. Meinkoth and G. Wahl, Hybridization of nucleic acids immobilized on solid supports. Analytical Biochemistry, 1984, 138(2), 267–284. 29. S. S. Ghosh and G. F. Musso, Covalent attachment of oligonucleotides to solid supports. Nucleic Acids Research, 1987, 15, 13 5353–5372. 30. T. R. Gingeras, D. Y. Kwoh, and G. R. Davis, Hybridization properties of immobilized nucleic acids. Nucleic Acids Research, 1987, 15(13), 5373–5390. 31. V. Lund, R. Schmid, D. Rickwood, and E. Hornes, Assessment of methods for covalent binding of nucleic acids to magnetic beads, Dynabeads, and the characteristics of the bound nucleic acids in hybridization reactions. Nucleic Acids Research, 1988, 16(22), 10861–10880. 32. R. K. Saiki, P. S. Walsh, C. H. Levenson, and H. A. Erlich, Genetic analysis of amplified DNA with immobilized sequence-specific oligonucleotide probes. Proceedings of the National Academy of Sciences of the United States of America, 1989, 86(16), 6230–6234. 33. S. R. Rasmussen, M. R. Larsen, and S. E. Rasmussen, Covalent immobilization of DNA onto polystyrene microwells: the molecules are only bound at the 5 end. Analytical Biochemistry, 1991, 198(1), 138–142. 34. E. Fahy, G. R. Davis, L. J. DiMichele, and S. S. Ghosh, Design and synthesis of polyacrylamide-based oligonucleotide supports for use in nucleic acid diagnostics. Nucleic Acids Research, 1993, 21(8), 1819–1826. 35. U. Maskos and E. M. Southern, Oligonucleotide hybridizations on glass supports: a novel linker for oligonucleotide synthesis and hybridization properties of oligonucleotides synthesised in situ. Nucleic Acids Research, 1992, 20(7), 1679–1684. 36. S. P. Fodor, J. L. Read, M. C. Pirrung, L. Stryer, A. T. Lu, and D. Solas, Light-directed, spatially addressable parallel chemical synthesis. Science, 1991, 251(4995), 767–773. 37. G. McGall, J. Labadie, P. Brock, G. Wallraff, T. Nguyen, and W. Hinsberg, Light-directed synthesis of highdensity oligonucleotide arrays using semiconductor photoresists. Proceedings of the National Academy of Sciences of the United States of America, 1996, 93(24), 13555–13560. 38. M. H. Caruthers, Gene synthesis machines: DNA chemistry and its uses. Science, 1985, 230(4723), 281–285. 39. A. C. Pease, D. Solas, E. J. Sullivan, M. T. Cronin, C. P. Homes, and S. P. Fodor, Light-generated oligonucleotide arrays for rapid DNA sequence analysis. Proceedings of the National Academy of Sciences of the United States of America, 1994, 91(11), 5022–5026. 40. E. F. Nuwaysir, W. Huang, T. J. Albert, J. Singh, K. Nuwaysir, A. Pitas, T. Richmond, T. Gorski, J. P. Berg, J. Ballin, M. Mccormick, J. Norton, T. Pollock, T. Sumwalt, L. Butcher, D. Porter, M. Molla, C. Hall, F. Blattner, M. R. Sussman, R. L. Wallace, F. Cerrina, and R. D. Green, Gene expression analysis using oligonucleotide arrays produced
NUCLEIC ACID ARRAYS
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
by maskless photolithography. Genome Research, 2002, 12(11), 1749–1755. S. Singh-Gasson, R. D. Green, Y. J. Yue, C. Nelson, F. Blattner, M. R. Sussman, and F. Cerrina, Maskless fabrication of light-directed oligonucleotide microarrays using a digital micromirror array. Nature Biotechnology, 1999, 17(10), 974–978. A. L. Ghindilis, M. W. Smith, K. R. Schwarzkopf, K. M. Roth, K. Peyvan, S. B. Munro, M. J. Lodes, A. G. Stover, K. Bernards, K. Dill, and A. McShea, CombiMatrix oligonucleotide arrays: genotyping and gene expression assays employing electrochemical detection. Biosensors and Bioelectronics, 2007, 22(9–10), 1853–1860. R. H. Liu, T. Nugyen, K. Schwarzkopf, H. S. Fuji, A. Petrova, T. Siuda, K. Peyvan, M. Bizak, D. Danley, and A. McShea, Fully integrated miniature device for automated gene expression DNA microarray processing. Analytical Chemistry, 2006, 78(6), 1980–1986. C. F. Edman, D. E. Raymond, D. J. Wu, E. Tu, R. G. Sosnowski, W. F. Butler, M. Nerenberg, and M. J. Heller, Electric field directed nucleic acid hybridization on microchips. Nucleic Acids Research, 1997, 25(24), 4907–4914. P. N. Gilles, D. J. Wu, C. B. Foster, P. J. Dillon, and S. J. Chanock, Single nucleotide polymorphic discrimination by an electronic dot blot assay on semiconductor microchips. Nature Biotechnology, 1999, 17(4), 365–370. M. J. Heller, A. H. Forster, and E. Tu, Active microelectronic chip devices which utilize controlled electrophoretic fields for multiplex DNA hybridization and other genomic applications. Electrophoresis, 2000, 21(1), 157–164. P. O. Brown and D. Botstein, Exploring the new world of the genome with DNA microarrays. Nature Genetics, 1999, 21(Suppl. 1), 33–37. D. E. Bassett Jr, M. B. Eisen, and M. S. Boguski, Gene expression informatics–it’s all in your mine. Nature Genetics, 1999, 21(Suppl. 1), 51–55. H. Miyachi, A. Hiratsuka, K. Ikebukuro, K. Yano, H. Muguruma, and I. Karube, Application of polymerembedded proteins to fabrication of DNA array. Biotechnology and Bioengineering, 2000, 69(3), 323–329. F. F. Shi, Recent advances in polymer thin films prepared by plasma polymerization Synthesis, structural characterization, properties and applications. Surface and Coatings Technology, 1996, 82, 1–15. S. Kurosawa, N. Kamo, D. Matsui, and Y. Kobatake, Gas sorption to plasma-polymerized copper phthalocyanine film formed on a piezoelectric crystal. Analytical Chemistry, 1990, 62, 353–359. G. Akovali, D. G. Mamedov, and Z. M. O. Rzaev, Plasma surface modification of polyethylene with organosilicon and organotin monomers. European Polymer Journal, 1996, 32, 375–383. D. J. Li, F. Z. Cui, H. Q. Gu, and J. Zhao, Ion-beaminduced biomedical behavior of hexamethyldisiloxane films on deposited polyetherurethanes. Applied Surface Science, 1998, 126, 1–10. H. Miyachi, G.-T. Nomizo, A. Hiratsuka, K. Ikebukuro, H. Muguruma, and I. Karube Fabrication of DNA Sensing Array Using Plasma Polymerization, The Sixth World
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
13
Congress on Biosensors. San Diego, USA, 24–26 May 2000, ELSEVIER. H. Miyachi, K. Ikebukuro, K. Yano, H. Aburatani, and I. Karube, Single nucleotide polymorphism typing on DNA array with hydrophobic surface fabricated by plasma-polymerization technique. Biosensors and Bioelectronics, 2004, 20(2), 184–189. H. Miyachi, K. Yano, K. Ikebukuro, M. Kono, S. Hoshina, and I. Karube, Application of chimeric RNA-DNA oligonucleotides to the detection of pathogenic microorganisms using surface plasmon resonance. Analytica Chimica Acta, 2000, 407(1–2), 1–10. R. W. Mahley, Apolipoprotein E: cholesterol transport protein with expanding role in cell biology. Science, 1988, 240(4852), 622–630. E. H. Corder, A. M. Saunders, W. J. Strittmatter, D. E. Schmechel, P. C. Gaskell, G. W. Small, A. D. Roses, J. L. Haines, and M. A. Pericak-Vance, Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science, 1993, 261(5123), 921–923. Y. K. Paik, D. J. Chang, C. A. Reardon, G. E. Davies, R. W. Mahley, and J. M. Taylor, Nucleotide sequence and structure of the human apolipoprotein E gene. Proceedings of the National Academy of Sciences of the United States of America, 1985, 82(10), 3445–3449. A. D. Roses, Alzheimer diseases: a model of gene mutations and susceptibility polymorphisms for complex psychiatric diseases. American Journal of Medical Genetics, 1998, 81(1), 49–57. A. M. Saunders, W. J. Strittmatter, D. Schmechel, P. H. St George-Hyslop, M. A. Pericak-Vance, and S. H. Joo, Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer’s disease. Neurology, 1993, 43(8), 1467–1472. J. Ziauddin and D. M. Sabatini, Microarrays of cells expressing defined cDNAs. Nature, 2001, 411(6833), 107–110. D. Vanhecke and M. Janitz, High-throughput gene silencing using cell arrays. Oncogene, 2004, 23(51), 8353–8358. J. D. Lieb, X. Liu, D. Botstein, and P. O. Brown, Promoterspecific binding of Rap1 revealed by genome-wide maps of protein-DNA association. Nature Genetics, 2001, 28(4), 327–334. B. Ren, F. Robert, J. J. Wyrick, O. Aparicio, E. G. Jennings, I. Simon, J. Zeitlinger, J. Schreiber, N. Hannett, E. Kanin, T. L. Volkert, C. J. Wilson, S. P. Bell, and R. A. Young, Genome-wide location and function of DNA binding proteins. Science, 2000, 290(5500), 2306–2309. V. R. Iyer, C. E. Horak, C. S. Scafe, D. Botstein, M. Snyder, and P. O. Brown, Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF. Nature, 2001, 409(6819), 533–538. T. Fukumori, H. Miyachi, and K. Yokoyama, Exo-Taqbased detection of DNA-binding protein for homogeneous and microarray format. Journal of Biochemistry (Tokyo), 2005, 138(4), 473–478. W. F. Anderson, D. H. Ohlendorf, Y. Takeda, and B. W. Matthews, Structure of the cro repressor from
14
ARRAY TECHNOLOGIES
bacteriophage lambda and its interaction with DNA. Nature, 1981, 290(5809), 754–758. 69. C. Wu, An exonuclease protection assay reveals heatshock element and TATA box DNA-binding proteins in crude nuclear extracts. Nature, 1985, 317(6032), 84–87. 70. B. Han, H. Hamana, and T. Shinozawa, Sensitive detection of the binding of E2F to its promoter by exonuclease IIIand BssHII-protection PCR assays. Journal of Biochemical and Biophysical Methods, 1999, 39(1–2), 85–92.
71. J. K. Wang, T. X. Li, Y. F. Bai, and Z. H. Lu, Evaluating the binding affinities of NF-kappaB p50 homodimer to the wild-type and single-nucleotide mutant Ig-kappaB sites by the unimolecular dsDNA microarray. Analytical Biochemistry, 2003, 316(2), 192–201. 72. F. Chen, V. Castranova, X. Shi, and L. M. Demers, New insights into the role of nuclear factor-kappaB, a ubiquitous transcription factor in the initiation of diseases. Clinical Chemistry, 1999, 45(1), 7–17.
54 Protein Chips and Detection Tools Kenji Yokoyama, Atsunori Hiratsuka, Hideki Kinoshita, Keisuke Usui and Yoshio Suzuki Research Center of Advanced Bionics, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
1 INTRODUCTION
Proteome research comprehensively analyzing proteins occupies a special place in the methods of analyzing vital phenomena incapable of being elucidated by genome and transcriptome analyses. It has been a long time since the word proteome began to prevail. At the same time, substantial progress in protein analysis hardly seems real. One of the factors impeding the progress of proteome analysis is delay in the development of analytical instruments and techniques. Two-dimensional (2D) electrophoresis1,2 and mass spectrometry (MS) as conventional proteome analysis methods come readily to mind—proteins are separated by 2D electrophoresis and identified with a mass spectrometer. The process of conventional 2D electrophoretic analysis, however, is yet to be automated. So far, only fully trained personnel have been able to obtain reproducible results. Even with a small gel, the electrophoresis process takes 20 h or longer; for a large gel, it takes about 3 days, thereby lowering the throughput extremely. Another method of proteome analysis is liquid chromatography (LC)/MS shotgun protein analysis,3 with the combined use of LC and MS. In this method, protein samples are analyzed according to the following steps: (i) the samples are digested with trypsin and (ii) the resultant peptides are separated by LC and then subjected to MS to determine each of the peptides. The advantages
of this method are that the analysis of huge proteins, including membrane proteins, is convenient because of digestion performed before separation, and the analytical process can be easily automated; however, a number of peptide fragments produced from a protein are repeatedly analyzed, thereby producing low efficiency. This method is not suitable for quantitative analysis of posttranslational modification. Furthermore, isoelectric point and molecular weight, which have been conventionally used by researchers, are not available as well as the enormous database for 2D electrophoresis. Thus, 2D electrophoresis is a useful method and has many advantages in proteome analysis. Our research group is currently developing a system allowing fully automated 2D electrophoresis as well as the completion of analysis and detection within 1 h. In this chapter, we introduce the protein microarray typical of a chip for proteome analysis and the high-throughput fully automated 2D electrophoresis system. A novel fluorescent dye for staining proteins in a 2D electrophoresis gel is also described.
2 PROTEIN MICROARRAY
A DNA microarray, on which a lot of DNAs used as probes are arrayed on a solid substrate, is used for identifying DNA or RNA. A protein
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
microarray is used for arraying proteins in the place of DNAs. Proteins are typically analyzed, in some cases, nucleic acids, sugars, and lowmolecular-weight compounds are also used. Like the DNA microarray, the protein microarray has been attracting attention because a high throughput of comprehensive biochemical analyses has become necessary. The typical preparation process and the use of a protein microarray are as follows: (i) a target protein is spotted on a glass slide or silicon substrate for immobilization to prepare a protein microarray; (ii) then, a sample protein solution labeled with a fluorescent dye is contacted on the substrate surface, reacting within a given time to bind a sample protein matching the capturing protein (in the case of proteins to be measured). Quantitative determination of the protein or its affinity with a capturing protein can be studied by visualizing the binding behavior with a fluorometer with a positional resolution, that is fluorescence microscope or fluorescence image scanner, or by measuring the fluorescence intensities. If it is difficult to label a sample protein with a fluorescent dye, fluorescent detection can be achieved by combining the binding sample protein with the corresponding labeled antibody. Recently, substrates coated with a threedimensional gel are often used in place of a simple glass substrate: the surface of the glass substrate is coated with cross-linked hydrophilic polymers having functional groups forming covalent linkages with amino acids including N -hydroxysuccinimide esters. This substrate on which the capturing protein is immobilized has the advantage of ensuring the stability of the analysis. As the capturing protein is immobilized in gel, the reaction is similar in conditions to an aqueous solution system. In addition, capturing proteins are immobilized three dimensionally; a number of proteins can be immobilized, thereby enabling highly sensitive detection of the target substances. Glass substrates coated with three-dimensional gel are commercially available. Unlike DNA microarrays offering stable immobilization of probes, the protein microarrays in general have a problem with stability because of the proteins immobilized on the substrate. Thus, the protein microarray is partially marketed, although its market scale is smaller than that of the
DNA microarray. To solve the problem on stability, in vitro probe protein synthesis on each spot was proposed.4
3 AUTOMATED 2D ELECTROPHORESIS SYSTEM 3.1
On-chip 2D Electrophoresis System
The protein microarray is of advantage exclusively in identifying known proteins; the conventional 2D electrophoresis method is suitable for identifying unknown proteins or evaluating protein processing or post-translational modification. As mentioned above, however, the 2D electrophoretic analysis of proteins requires considerable time as well as a high level of skill. Therefore, we are aiming at developing a system that allows shorter running time for the 2D electrophoretic analysis, with simple operation. Initially, our research group designed a system for performing first-dimensional isoelectric focusing (IEF) and second-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDSPAGE) on a common substrate: a 2D electrophoresis chip integrated with IEF and SDS-PAGE has been developed.5 A schematic illustration of the chip is shown in Figure 1. Specific features of the structures were fabricated into the chip. Details of the chip layout are as follows. The chip was constructed of three different parts, a polymer plate, a glass cover, and a solution inlet. An immobilized pH gradient (IPG) gel strip and a polyacrylamide gel were fabricated as the first and second separation regions, respectively. The two regions were arranged perpendicular to each other and spatially separated by a junction structure. Grooves on both sides of the chip were fabricated as solution reservoirs for second-dimension electrophoresis. A pair of electrodes was connected via the reservoirs. The solution inlet was fabricated and equipped with an IPG gel strip. The details of the structures are illustrated in Figure 2. The solution inlet comprised a cover plate, a slit plate, an IPG gel strip, and a pair of electrodes. The slit plate covered the junction structure. A capillary structure was formed by the cover plate, slit plate, and IPG gel strip. The solutions were loaded into the IPG gel by capillary action. The cathode and anode were
PROTEIN CHIPS AND DETECTION TOOLS 7
3 1
4
2
5 5
8 60 mm
4
6 (a)
(a)
3
70 mm
3
4
2
1 7
5
6
9
2
8 0.5 mm
3 mm
1
3
2 mm
37 mm 20 mm
7 mm
(b)
70 mm 7
3
(b)
5
8
3
4
6
6
1
6
1
5
1.5 mm
(c) 4
2
7
5
4 (c)
Figure 1. Chip layout. (a) Perspective view, (b) cross section, and (c) photograph. 1: IPG gel strip; 2: polyacrylamide gel; 3: solution inlet; 4, 5, 6, 7: electrodes; 8: glass cover; 9: junction structure.
3.2
3.1 (d) 6
0.5 mm 3 mm
1 0.5 mm
fabricated on the slit plate and contacted to both sides of the IPG gel. The entrance of the agarose solution formed on top of the junction structure. The electrophoresis procedure for the solution inlet and the junction structure is illustrated in Figure 3. Initially, a sample solution was loaded into the dry IPG gel strip from the opening of the capillary. The capillary structure on the IPG gel prevented leakages of the solution. The IPG gel was rehydrated and expanded downward. The backing plate was fitted on a gutter, which was fabricated on the chip substrate. The IEF was then performed. After performing the IEF, the agarose solution was introduced from the entrance into the junction structure. Thus, the IPG and polyacrylamide gels were connected. Subsequently, the samples were transferred from the IPG gel to the polyacrylamide gel for the second separation.
3.1 (e)
2
70 mm
0.8 mm
2
7 3.2
Figure 2. Structure of solution inlet. (a) Photograph of decomposed structure, (b) schematic drawing of the structure, (c) overhead view, (d) cross-section front view, (e) crosssection side view. Arrow: sample solution inlet; 1: cover plate; 2: slit plate; 3: IPG gel strip (3.1: IPG gel, 3.2: backing plate); 4: anode; 5: cathode; 6: capillary structure; 7: agarose inlet.
The results of 2D electrophoresis are shown in Figure 4. Before performing the SDS-PAGE, the protein samples were observed in the IPG gel region (Figure 4a). When the SDS-PAGE was performed, the protein bands moved from the IPG gel region to the junction region within 3 min (Figure 4b). After 6 min, the band was getting narrow in the junction region (Figure 4c). These results showed that the agarose gel region played a role on a stacking gel concentrating proteins. After
4
ARRAY TECHNOLOGIES
separated as a diagonal line across the seconddimensional gel; as the pI increased, the molecular weight decreased (Figure 4e). This separation result was identical to the result using the conventional 2D gel separation method. The precedent smear band in the basic area was Cy5 bound with lysine (Figure 4c,d). This material was produced during the process of preparing the Cy5-labeled proteins. These results showed that the junction structure efficiently transferred the focused samples to the second-dimension gel without fractionation, and the samples were separated depending on their molecular weights by SDS-PAGE. These techniques including the function of the solution inlet, junction structure, miniaturized gel, and the simultaneous detection system achieved a 2D gel electrophoresis in a chip system. In addition, all the procedures were employed within 1 h. Figure 5 shows the results of the 2D separation of the extracted proteins. These results were achieved using the chip and commercially available minigel system, respectively. The proteins were separated and the protein spots were visualized over the entire gel region. Figure 5(a,b)
1 4
9 0.5 mm (a)
5 2
8
6
7 3
(b)
(c)
Figure 3. Cross section of solution inlet and junction structure. (a) Sample introduction, (b) rehydration and IEF, (c) agarose introduction and gel connection. The entire chip structure is shown at the bottom. The thick line is around the solution inlet and the junction structure. Solid arrow: entrance for solution introduction; broken arrow: direction of gel inflation; 1: IPG gel; 2: backing plate; 3: polyacrylamide gel; 4: agarose inlet; 5: glass cover; 6: junction structure; 7: agarose; 8: gutter; 9: sample solution.
the protein bands reached the SDS-polyacrylamide gel, the second separation was started along the direction of the potential (Figure 4d). When the lowest-molecular-weight protein reached the terminus of the gel, four kinds of proteins were Acidic
pH
Basic
Acidic
pH
Basic
Acidic
pH
Basic
(a)
0 min pH
(b) Basic
3 min Acidic
SDS-PAGE
SDS-PAGE
Acidic
SDS-PAGE
2
SDS-PAGE
SDS-PAGE
1
pH
(c)
6 min
Basic
A B C D
(d)
10 min
(e)
24 min
Figure 4. Continuous images of the second separation results of 2D protein markers. 2D protein markers (2 µg) labeled with Cy5 were applied to the chip. The images were continuously taken by a CCD camera while performing the SDS-PAGE. Images were taken according to the time course. The times when taking the images are shown below the images. (A) Aspergillus niger amyloglucosidase; (B) ovalbumin; (C) human erythrocytes carbonic anhydrase; (D) horse heart myoglobin. 1: IPG gel; 2: junction structure.
PROTEIN CHIPS AND DETECTION TOOLS pH
Basic
SDS-PAGE
Acidic
5
(a) Basic
Acidic SDS-PAGE
pH
SDS-PAGE
Acidic
(b)
(c)
pH
Basic
Figure 5. 2D separation result of extracted proteins from mouse brain. The extract proteins were labeled with Cy5. 2D results were achieved using the chip and a commercially available minigel system (ZOOM IPGRunner system, Invitrogen Corporation; IPG gel strip: ZOOM Strip pH 3–10 NL, Cat. No. ZM0011; PAG: Nupage 4–12% Bis-Tris ZOOM Gel, Cat. No. NP0330BOX). The chip system (a,b) 5 µg protein applied, minigel system and (c) 40 µg protein applied.
shows the results from 5 µg of the protein sample applied for comparing numbers of the spot Migration length and gel thickness for SDS-PAGE of the minigel are 80.0 and 1.0 mm, respectively. Meanwhile, the dimension of the chip is almost half (37 mm long and 0.5 mm thick). This miniaturization of the chip may cause the short-time migration and the low protein diffusions. Hence, there were lesser fluorescence reductions and a large amount of the proteins were visualized on the chip. Figure 5(c) shows the result obtained by applying 40 µg of the sample using the minigel system. A number of protein spots were visualized by increasing the amount of the sample. Although the chip visualized lesser spots than the minigel using 40 µg of the sample, more than 100 spots were clearly visualized using the chip. Accordingly, the chip system still showed the utility and the resolving power to separate complex biological samples. In the normal 2D electrophoresis, the entire process takes 10 h or longer and manual transfer
of gel is required. On the contrary, use of the chip reduced the time required for obtaining 2D electrophoresis images to 60 min including 5 min elapsing from the loading of the protein sample to the loading of the agarose, accomplishing our goal time of less than 1 h. However, there are problems preventing commercialization, including the loading of agarose between the first-dimensional and second-dimensional electrophoretic analysis. We have made the transition to a separate model of the fully automated 2D electrophoresis system.
3.2
High-throughput Fully Automated 2D Electrophoresis System
Development personnel are eager to develop the 2D electrophoretic system in which the IEF system is integrated with the SDS-PAGE system, which does not necessarily appeal to users. The current, better choice is the electrophoretic system only requiring smaller sample quantities and a
6
ARRAY TECHNOLOGIES
chose in its place an automated transfer system that can carry samples. Figure 6 shows the system diagram and photograph of the fully automated 2D electrophoresis system. This system is designed to sequentially convey the IEF chip containing the IEF gel strip fixed on the support. Figure 7 shows photographs of the IEF, the reaction solution, and the
providing high-throughput, automated output of analytical results, irrespective of whether the components composing the system are built into a single piece. The separate model has fewer factors crucial to development than an integrated model, seemingly facilitating the development. The authors separated IEF, staining, washing, and SDS-PAGE units from the integrated model, and
Detection system Highly sensitive CCD camera Excitation lamp IEF chip holder moving in X and Z direction
X
Z
Isoelectric focusing (IEF) chip composed of immobilized pH gradient gel with supporting plate
IEF chamber
Solution chip (70 × 70 mm)
Reaction chamber Sample soak, (staining, rinsing, gel rehydration equilibrating) chamber
SDS-PAGE gel Electrophoresis buffer reservoirs SDS-PAGE chip Cooling stage (70 × 70 mm)
(a)
Stepping motor in box Electrode holder
IEF chip holder IEF chip
Controlling and monitoring computer temperature voltage current stepping motor
Z X SDS-PAGE chip
Solution chip
(b)
Electrodes for IEF
Electrodes for SDS-PAGE
Figure 6. Fully automated 2D electrophoresis system.
High-voltage power supplies in box
PROTEIN CHIPS AND DETECTION TOOLS
7
SDS-PAGE chip (Ultrasonic-bonded plastic chip) Width: 70 mm Length: 70 mm Thickness: 10 mm
IEF chip Width: 14 mm Length: 52 mm Thickness: 1.2 mm
Assembled SDS-PAGE chip with glass plate and plastic package
IEF gel (immobilized pH gradient gel) pH range: 3–10 Width: 1.2 mm (after rehydration) Length: 52 mm Thickness: 0.5 mm
Solution chip Made of plastic for soaking sample, gel rehydration, IEF, staining, rinsing, and SDS-equilibration Width: 70 mm Length: 70 mm Thickness: 10 mm
SDS-PAGE gel Stacking gel: 3% Separation gel: 12.5% Width: 60 mm Length: 48 mm Thickness: 1 mm
Figure 7. Chips of fully automated 2D electrophoresis system.
SDS-PAGE chips. The operation procedure is as follows: First, the IEF chip holder catches the dried IEF chip and immerses it in a protein sample solution, and then transfers it to the IEF gel swelling solution chamber. Then, the IEF chip is transferred to the IEF chamber, in which a certain voltage is applied to the IEF gel. On completion of the IEF process, the IEF chip is transferred sequentially to the washing chamber followed by the staining chamber, modifying proteins with a fluorescent dye including Cy5. Next, the excessive dye is washed away from the chip, equilibrating with SDS. Subsequently, the IEF chip is transferred to the starting point of the second-dimensional SDS-PAGE gel to contact with the IEF gel, initiating the SDS-PAGE process. Equipped with a charge coupled device (CCD) camera, this system can visualize, in real time, the separation process during the SDS-PAGE process, thereby achieving a reduction of the conventional operating time of 20 h to 60–90 min: the loading of protein samples and gel swelling, 10 min; IEF, 20–30 min; staining/washing/equilibration, 10–20 min; and SDS-PAGE/detection, 20–30 min. Whereas the conventional method requires the manual transfer of gel at every process step, this system can do
everything fully automatically from the loading of a protein sample to detection. Also, the system is reduced in size to one-fourth or less, compared with the conventional 2D electrophoresis system, saving installation space. The performance of the system was evaluated using solubilized liver proteins as a protein sample. As for intermediate staining with the SDS-PAGE chip assembled with a glass slide, the results from intermediate staining (Cy5) and post-SDS-PAGE staining (SYPRO Ruby) were satisfied. On the contrary, with a chip welded with a plastic substrate by supersonic bonding, noise was caused in a low-molecular-weight region possibly by the adhesion of Cy5 to the plastic surface; coating of the plastic substrate is under review. Reproducibility of this system was compared with a commercialized manual small gel system, and the results showed a high reproducibility in both systems. Failure in the evaluation of reproducibility may be attributed to the unparalleled skills of our research personnel conducting the comparative test. Therefore, results from many other research personnel with different skills should be evaluated for ensuring an accurate comparison. Then, IEF and SDS-PAGE were evaluated for their resolution;
8
ARRAY TECHNOLOGIES
and the resolution was comparable to the small gel, although it did not reach that of the large gel, about 200 mm2 . As mentioned above, this system, including reproducibility and resolution, performs as well as or better than commercialized systems equal in size. In addition, the automated acquisition of the 2D electrophoretic data in a shorter time seemingly proves that the method using this system is apparently superior compared with conventional methods.
4 FLUORESCENT DYE FOR STAINING PROTEINS
We have reported a novel fluorescent dye (Dye 1) based on the intramolecular charge transfer for the highly sensitive detection of a protein whose structure is shown in Figure 8.6 Dye 1 has the following characteristics: (i) Dye 1 itself indicates a weak fluorescence, whereas a strong red emission is observed upon binding to a protein molecule, (ii) a high molar extinction coefficient and high fluorescent quantum yield upon binding to protein, (iii) low protein-to-protein variation, (iv) low interference from nonprotein substances (inorganic salts, detergents, reductants, organic solvents, etc.), (v) high chemical and photophysical stabilities, and (vi) low-cost starting materials and easy synthetic method (one-step synthesis). Moreover, the successful demonstration of protein staining in minigels after SDS-PAGE was performed using Dye 1. In this chapter, we described a study to develop the high-performance staining of proteins in the gel OH
O
CN NC Figure 8. Chemical structure of Dye 1.
using Dye 1 as a further application to carry out the high-throughput protein analysis. The normal protein staining protocol for Coomassie brilliant blue (CBB) staining or SYPRO Ruby staining, which is “SDS-PAGE, fixation, staining, washing, and detection”, was simplified while maintaining sensitivity for proteins and the sharp band resolution of proteins in the gel. The experimental results finally showed that protein staining using Dye 1 can simultaneously be carried out together with SDS-PAGE separation by dissolving Dye 1 into the electrophoresis buffer solution. Moreover, it was successful in shortening the handling time of protein staining after SDS-PAGE (general SYPRO Ruby method takes about 18 h, whereas the procedure presented here takes 45 min) to obtain the experimental results without the loss of the sensitivity for proteins in the gel, and it was found that Dye 1 had significantly better characteristics than commercially available dyes for protein staining. To demonstrate the staining of proteins in the gel using Dye 1, proteins after the separation using the 1D SDS-PAGE minigels were fixed in the gel by incubation in the fixing solution for 30 min and then immersed in the staining solution containing Dye 1 for 30 min. After washing of the gels by the fixation solution for 30 min, the bands of the proteins on the gel were scanned using the image analysis systems. Figure 9 shows the typical gel images of the bovine serum albumin (BSA) after Dye 1 staining. The association of Dye 1 with BSA and the visual examination of the staining response were successful. The Dye 1 staining indicated a good linear relationship between the integrated volume of the densitometry units for scanned bands of BSA in the gel and BSA concentration as shown in Figure 9(b). The detection limit was 7.0 ng/band of BSA, which is as sensitive as the short-protocol silver staining methods.7 To examine the reproducibility of the calibration graph, reproducibility tests (n = 3) were carried out. The relative standard deviation of the response was found to be within 2.0%. Other proteins at the various concentrations (chymotrypsinogen A, transferrin, immunoglobulin G (IgG)) were stained by Dye 1 after SDS-PAGE, and their calibration graphs were constructed as shown in Figure 9(b). From this result, this protein staining using Dye 1 indicated only slight protein-to-protein variation, which makes it possible to accurately compare the protein expression levels and to monitor the correct
PROTEIN CHIPS AND DETECTION TOOLS 0.1
0.4
1.1
3.3
2000
10 (µg) Integrated volume in densitometry units
0.02
1500 1000
(a)
0
0.2
(b) 0.4
1.1
3.3
10 (µg)
0.6
0.8
1
1.2
2000 Integrated volume in densitometry units
0.1
0.4
(Protein) (µg/well)
1500 1000 Chymotrypsinogen A BSA Transferrin IgG
500 0
(c)
Chymotrypsinogen A BSA Transferrin IgG
500 0
0.02
9
(d)
0
0.2
0.4
0.6
0.8
1
1.2
(Protein) (µg/well)
Figure 9. Fluorescent staining and densitometry of proteins with Dye 1. (a) Typical gel image of BSA stained by Dye 1 using conventional staining protocol. (b) The relationship between the integrated volume in densitometry units for scanned bands and various protein concentrations (BSA, chymotrypsinogen A, transferrin, IgG) in gels using conventional staining protocol. (c) Gel image of BSA stained by Dye 1 using rapid staining protocol. (d) The relationship between the integrated volume in densitometry units for scanned bands and various protein concentrations (BSA, chymotrypsinogen A, transferrin, IgG) in gels by 1D SDS-PAGE using rapid staining protocol. The numerical values in (a) and (c) are the amounts of BSA applied to each gel well.
protein concentration using only one calibration graph such as commercially available fluorescent dyes (SYPRO Ruby and SYPRO Orange). For the SDS-PAGE measurement, it takes a long time to obtain the results after separation of the proteins, because of the multiple steps and intensive labor for protein staining in the gel using the conventional staining method, such as SYPRO Ruby staining or CBB staining. The staining protocol of SYPRO Ruby after SDS-PAGE and each treatment time is as follows: fixation (30 min), staining (overnight), washing (30 min), and detection (it takes a total time of about 18 h). Dye 1 was useful for protein staining in the gel, and the proteins were completely stained by Dye 1 within 30 min, a time that is much shorter than that for the SYPRO Ruby staining and CBB staining. Therefore, it was thought that Dye 1 might reduce the protein staining time, and each treatment in
the general protocol for the protein staining was simplified. In our previous report, the fixation procedure was omitted in order to investigate whether proteins were able to be stained by Dye 1 in the presence of an excess amount of sodium dodecyl sulfate (SDS).6 The association of Dye 1 with BSA and IgG and a visual examination of the staining response were successful in the presence of an excess amount of SDS. After washing of the gel for 30 min, clear protein bands were obtained owing to reduction of the background. Under the same experimental conditions, SYPRO Ruby and CBB could not stain the proteins, because the excess amount of SDS interfered with the binding of these dyes to the proteins. On the other hand, it was recognized that the binding between Dye 1 and the proteins was not affected by the excess amount of SDS in the solution in the previous
ARRAY TECHNOLOGIES High MW Electrophoresis
report, which contributed to the success of the protein staining by Dye 1 independent of the SDS removal. As the next step to reduce the staining protocol time, the SDS-PAGE experiment was carried out together with the protein staining. An electrophoresis buffer solution containing Dye 1 was prepared under the optimum experimental conditions, and Dye 1 was bound to the protein during the SDS-PAGE experiment. Figure 9(c) shows the gel images of the various concentrations of the BSA using Dye 1 staining during a 1D SDS-PAGE experiment after washing the gels. The association of Dye 1 with proteins during the SDS-PAGE experiment was successful and the staining response was clearly observed by visual examination. For this staining method, it was successful in greatly reducing the staining time and intensive handling from several hours for the general method to 15 min. The integrated volume in densitometry units for the scanned protein bands in the gel had a linear relationship with the concentration of the proteins (r 2 > 0.995), and little protein-to-protein variation was observed as shown in Figure 9(d). The detection limit of the proteins using this staining method was 7.0 ng/band of BSA (signal-to-noise ratio was 3.0) when washing the gel, which is as sensitive as the general staining methods using Dye 1, and it was noted that the sensitivity for proteins was maintained regardless of reducing the staining procedures and time. Other proteins at various concentrations (chymotrypsinogen A, transferrin, IgG) were stained by Dye 1 under the same experimental conditions, and their calibration graphs were constructed as shown in Figure 9(d). As a result, this protein staining using Dye 1 indicated only a slight protein-to-protein variation similar to the result of the general staining method. Under the same experimental conditions, 2D SDS-PAGE was carried out for the separation of 40 µg of mouse brain lysates, and well-resolved gel images were observed. These gel images are shown in Figure 10. The fluorescent image of proteins with some nonspecific spots and small background was observed despite the SDS removal and excess dyes in the gel as shown in Figure 10(a). By washing the gel, the background and nonspecific spots in the gel disappeared, and a clearer gel image was observed as shown in Figure 10(b). As a result, the binding of Dye 1 to proteins during the
Low MW (a)
pH 3
pH gradient
pH 3
pH gradient
pH 9
High MW
Electrophoresis
10
Low MW (b)
pH 9
Figure 10. Rapid staining with Dye 1 for 2D PAGE of mouse brain lysate (40 µg) before (a) and after (b) washing gel.
SDS-PAGE experiment was successful regardless of the 1D or 2D SDS-PAGE gel separation. SYPRO Orange is a commercially available fluorescent protein staining dye which makes it possible to stain proteins in the presence of SDS and is a simple and rapid method.8,9 Although this stain works well with the 1D SDS-PAGE gel, its performance with 2D gels was inconsistent and failed to achieve the sensitivity levels obtained by the 1D SDS-PAGE.10 Moreover, no proteins were stained by SYPRO Orange under the same experimental conditions, because the movement of SYPRO Orange into the gel was prevented by the 1D strip gel. Both Dye 1 and SYPRO Orange could bind to proteins using a simple and rapid method, whereas Dye 1 succeeded in the staining of proteins not only in 1D SDS-PAGE gels, but also in 2D gels with a high sensitivity. From this viewpoint, it was demonstrated that Dye 1 had significantly improved characteristics than the commercially available staining dyes. Our procedures significantly reduced protein staining times for the SDS-PAGE compared to the general method for the SYPRO Ruby staining of 18 h and for CBB at 105 min. For this study, it took 15 min (or 45 min in the case of washing of the gel after SDS-PAGE together with staining). Moreover, the gel image analysis to detect the protein bands in this experiment could be
PROTEIN CHIPS AND DETECTION TOOLS
directly performed after the SDS-PAGE experiment without the labor-intensive treatments such as fixation, washing, and lengthy staining of the general staining protocol using SYPRO Ruby and CBB. Although the detection limit of the protein for Dye 1 (7 ng/band) was slightly lower than that for SYPRO Ruby (1–2 ng/band), the detection limit of the proteins in this study was as sensitive as the short-protocol silver staining methods (7 ng/band), and was much higher than that of CBB (64 ng/band). The SDS-PAGE experiment using Dye 1 made it possible to carry out the highthroughput protein analysis and highly sensitive detection of proteins, which satisfies the requirements in the rapidly growing field of proteomics. The present study demonstrated the highperformance staining for 1D and 2D SDS-PAGE using the novel protein-binding fluorophore, Dye 1. The proteins in the gel could be stained by Dye 1 during the SDS-PAGE experiment by preparation of the electrophoresis buffer solution containing Dye 1 under optimum conditions and by the binding to proteins in the gel during the SDS-PAGE experiment. This method for SDS-PAGE significantly simplified the staining protocols without any loss of the protein-to-protein variation and sensitivity. Recently, proteomic analysis has become an important field and it is increasingly important to refine the techniques generating proteomic data. This highly sensitive, rapid, and easy handling staining method using Dye 1 should be widely applicable and convenient for multiple scientific disciplines including biochemistry, medicine, and pharmacology.
5 PROSPECTS FOR THE FUTURE
The fully automated 2D electrophoresis system developed by the authors is believed to be an epoch-making system that allows anyone to conduct a simple, rapid 2D electrophoretic analysis conventionally limited to a few highly trained researchers. This makes protein analysis more familiar to us; it may be used for laboratory tests in the near future. The global market scale of products related to the fully automated 2D electrophoresis, including instruments and consumable items, reached US$3.13 million in 2003.11 If a chip is developed that allows post-translational
11
modifications including glycosylation and phosphorylation, the market scale will greatly expand in the future. ACKNOWLEDGMENTS
The development of the automated 2D electrophoresis system was financially supported as the High-throughput Biomolecule Analysis System Project by the New Energy and Industrial Technology Development Organization (NEDO), Japan. Authors thank cooperative researchers: Y. Unuma, Y. Maruo, T. Matsushima, K. Takahashi, M. Mieda, M. Nakamura from Sharp corporation, K. Sakairi, C. Hayashida, M. Kano, K. Ueyama from Toppan Printing, I. Namatame, K. Yodoya, Y. Ishii, T. Shibata, H. Inamochi, Y. Nakada, Y. Ogawa, H. Marusawa, T. Komatsu, Y. Saito from Astellas Pharma, K. Yano, S. Akutsu, and I. Karube from Tokyo University of Technology. REFERENCES 1. G. A. Scheele, Two-dimensional gel analysis of soluble proteins. Charaterization of guinea pig exocrine pancreatic proteins. Journal of Biological Chemistry, 1975, 250, 5375. 2. P. H. O’Farrell, High resolution two-dimensional electrophoresis of proteins. Journal of Biological Chemistry, 1975, 250, 4007. 3. D. A. Wolters, M. P. Washburn, and J. R. Yates III, An Automated Multidimensional Protein Identification Technology for Shotgun Proteomics. Analytical Chemistry, 2001, 73, 5683. 4. N. Ramachandran, E. Hainsworth, B. Bhullar, S. Eisenstein, B. Rosen, A. Y. Lau, J. C. Walter, and J. LaBaer, Self-Assembling Protein Microarrays. Science, 2004, 305, 86. 5. K. Usui, A. Hiratsuka, K. Shiseki, Y. Maruo, T. Matsushima, K. Takahashi, Y. Unuma, K. Sakairi, I. Namatame, Y. Ogawa, and K. Yokoyama, A selfcontained polymeric 2-DE chip system for rapid and easy analysis. Electrophoresis, 2006, 27, 3635. 6. Y. Suzuki and K. Yokoyama, Design and Synthesis of Intramolecular Charge Transfer-Based Fluorescent Reagents for the Highly-Sensitive Detection of Proteins. Journal of the American Chemical Society, 2005, 127, 17799. 7. F. Gharahdaghi, C. R. Weinberg, D. A. Meagher, B. S. Imai, and S. M. Mische, Mass spectrometric identification of proteins from silver-stained polyacrylamide gel: a method for the removal of silver ions to enhance sensitivity. Electrophoresis, 1999, 20, 601. 8. T. Steinberg, L. Jones, R. P. Haugland, and V. Singer, SYPRO orange and SYPRO red protein gel stains:
12
ARRAY TECHNOLOGIES
one-step fluorescent staining of denaturing gels for detection of nanogram levels of protein. Analytical Biochemistry, 1996, 239, 223. 9. L. Steinberg, R. P. Haugland, and V. Singer, Applications of SYPRO orange and SYPRO red protein gel stains. Analytical Biochemistry, 1996, 239, 238.
10. J. P. Malone, M. R. Radabaugh, R. M. Leimgruber, and G. S. Gerstenecker, Practical aspects of fluorescent staining for proteomic applications. Electrophoresis, 2001, 22, 919. 11. World 2 D Gel Electrophoresis Market, Frost & Sullivan, Palo Alto, 2004.
55 Surface-Enhanced Laser Desorption/ Ionization (SELDI) Technology Lee O. Lomas1 and Scot R. Weinberger2 1
Ciphergen Biosystems Inc., Fremont, CA, USA and 2 GenNext Technologies Inc., Montara, CA, USA
1 OVERVIEW OF SELDI BIOCHIP TECHNOLOGY
Surface enhanced laser desorption/ionization mass spectrometry (SELDI-MS) was first conceptualized in the early 1990s when Hutchens and Yip demonstrated that chromatographic affinity probes used to specifically enrich fragments of lactoferrin could then be directly presented to a laser desorption/ionization source for mass spectrometric detection.1 The capability of the probe to actively participate in the extraction of the analyte and subsequent removal of sample components that interfere with or suppress ionization was a logical improvement over the classical matrix-assisted laser desorption/ionization (MALDI) applications where the sample probe surface plays a passive role in the analytical scheme and merely presents the sample to the mass spectrometer for analysis; in order to produce usable MALDI-MS signal, crude samples must first be fractionated and purified of any ionization suppressants such as salts, chaotropic agents, detergents, and so on. SELDI, as originally defined by Hutchens and Yip, consists of two subsets of technology: surface enhanced affinity capture (SEAC) and surface enhanced neat desorption (SEND).1 By far the SELDI array technology showing the most utility to date is SEAC and as such is generally
referred to as SELDI in the published domain. In this format, the probe surface plays an active role in the extraction, concentration, and presentation of the analyte and elimination of ionization suppressants. Figure 1 depicts the elements of a SELDI biochip and associated variety of chemical and biochemical SELDI array surfaces used in differential protein expression applications. Chemical surface arrays are derivatized with classic chromatographic separation ligands such as reverse phase, ion exchange, immobilized metal affinity capture (IMAC), and normal phase media. Such surfaces, with broad binding properties, are typically used for general protein profiling and de novo biomarker discovery, where large populations of proteins are compared (e.g., from diseased vs normal samples) with the goal of elucidating differentially expressed elements. Biomolecules bind to these surfaces through hydrophobic, electrostatic, coordinate covalent bond or Lewis acid–base interaction, the strengths of which can be directly modulated by modifying the binding and/or washing buffer compositions. Biochemical arrays are created by immobilizing bait molecules upon the surface of preactivated SELDI surfaces via covalent attachment using either primary amines or hydroxyl groups. In this way, specific protein-interaction arrays of virtually any content may be created, including antibodies,
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
Functionalized hydrogel
Hydrophobic barrier
Chemical surface Reverse phase Quaternary a mine (anionic) Carboxymethyl (cationic) Nitrilotriacetic acid (IMAC) Silica (normal phase) Biochemical surfaces Carboimidazol reactive Epoxy reactive
SELDI biochip Figure 1. Elements of a SELDI biochip. The array consists of a glass-coated aluminum strip that displays discrete affinity locations or spots. Each spot incorporates a hydrogel that is functionalized with classical chromatographic ligands, such as C9–C12 aliphatic chains (reverse phase), quaternary amines (strong anionic), carboxymethyl (weak cationic), nitrilotriacetic acid (IMAC) and silicon oxide (normal phase). The biochips also incorporate a hydrophobic barrier that surrounds the spot locations and prevents sample movement between spots. Dimensions and spot locations are such that 12 strips side-by side provide the standard 96-well microtiter footprint and sample processing can be achieved using standard robotics.
receptors, enzymes, DNA, small molecules, ligands, and lectins. In contrast with standard chromatographic media, these biochemical surfaces provide a greater degree of enrichment of captured analytes, because of the high specificity of biomolecular interactions. Because specific biochemical interaction motifs demonstrate high affinity and low equilibrium disassociation constants, biochemical surfaces facilitate a vast array of microscale experiments that facilitate the analysis of very low sample volumes. Such experiments include SELDI immuno assays, targeted protein identification and/or purification, ligand binding domain analysis, epitope-mapping experiments, post–translational modification detection, as well as reliable quantitative studies, even when fishing for target proteins within a complex biological sample. When compared to MALDI, SELDI-based arrays have demonstrated not only a simplified workflow, but also improved analytical sensitivity and associated mass detection limit. The latter is attributed to a marked reduction in sample loss
inherent in combining and miniaturizing sample processing workflow. 2 USE OF SELDI IN PROTEOMICS 2.1
Differential Protein Display and Biomarker Discovery
Over the course of the last decade, SELDI technology has mostly been applied to challenges of proteomics research. Among today’s most popular proteomic research activities is differential protein display or expression monitoring. Differential protein display is a comparative technique that contrasts protein profiles between different organisms, individuals, pathogenic and/or metabolic conditions, and phenotypic response to environmental or chemical challenges. Unlike differential studies of transcription, differential protein display studies are not easily enabled by amplification strategies such as reverse polymerase chain reaction (PCR). In this manner, differential protein
SELDI TECHNOLOGY
studies require approaches that isolate and enrich both major as well as minor protein constituents from a complex biological mixture, with specific attention to preanalytical and analytical biases that may compromise conclusional integrity. The proteomic community performs differential protein display for biomarker discovery in two formats; the so-called top down and bottom up approaches. SELDI has been used most extensively in the top down approach whereby protein mass signatures within a biological sample are detected and compared without any further reduction to peptide fragments by post sample collection methods such as global tryptic digestion. The implication of this is that proteins and protein modifications due to the biology of the system are preserved through to detection as they may be indicative of the biological question to be answered. For such experiments, the workflow is performed in two phases; a scouting phase whereby a large number of chromatographic separations are performed using multiple array chemistries and binding/washing conditions, and a validation phase whereby select differentially expressed protein candidates are validated using only the chromatographic surface and binding/washing condition that gave the initial differential profile. As an example, the process of SELDI-based sample preparation using four different chemical surfaces is demonstrated in Figure 2. A series of orthogonal SELDI surfaces including reverse phase, anionic, cationic, and IMAC loaded with a transitional metal such as Cu2+ , Ni2+ , or Zn2+ are arranged in plate format. A complex biological sample is deposited upon every chemically active “spot” of each array. After binding, the spots on each array are washed with appropriate buffers in gradient manner. Within a given array, subsequent spots experience a greater degree of stringency, removing analytes with comparatively weaker surface interaction potential and enriching for those of strong surface affinity. In some cases, particularly when using specific biomolecular interactions, purification to almost-complete homogeneity is possible, without substantial loss of analyte. Benefits of this workflow also reveal insight into the physical–chemical properties of the analyte retained on the surfaces such as hydropathicity, charge, pI, and post–translational modifications such as phosphorylation and/or glycosylation. Such de facto knowledge can be further exploited
3
particularly in analyte purification whereby such knowledge can be used to design efficient scaleup purification strategies by matching the array chemistry and binding/washing conditions used for discovery with that of a more conventional chromatographic bead chemistry in a column format. This is particularly useful when additional purified material is needed for the purpose of protein identification and further characterization. In contrast to research-based proteomics, clinical proteomic studies endeavor to follow the progress of disease within an individual or a small population with the ultimate goal of finding biomarkers potentially useful as diagnostic agents or new drug targets; this topic is now known best as “translational medicine”. Under such circumstances, sample or tissue availability is limited and the dependence upon highly efficient, small-scale techniques is becoming more and more essential. Typically protein populations between groups are compared using univariate and/or multivariate statistical analysis schemes with the ultimate goal of elucidating a protein or groups of proteins whose expression levels correlate with a given clinical condition.2 Automation requirements here are primarily focused upon running many samples in a massively parallel manner and only proteins of interest are further characterized to provide insight into identification and post–translational modifications, or to provide insight into the disease mechanism or host response to disease. Because of its reproducibility, throughput, and starting material requirements, SELDI-MS has gained acceptance as a tool of choice for clinical proteomic studies.
3 SELDI CLINICAL PROTEOMIC STUDIES
Clinical proteomics aims to scan the realm of expressed proteins to identify biomarkers that can answer specific clinical questions. The most obvious are markers that can be used for diagnosis or prognosis. Another important issue that clinical proteomics promises to help resolve, is the ability to predict a patient’s response to a specific drug. For example, diagnostic markers can themselves be candidates for drug targets and pharmaceutical companies pursue clinical proteomics to identify markers that predict toxicity of candidate drugs. The overriding determinant of the success of a clinical proteomics program is the choice
4
ARRAY TECHNOLOGIES ∆ Salt
Cu2+ Ni2+ Ga2+
∆ Imidazole
∆ pH
Q
CM
Chaotroph
∆ Organic
RP
IMAC
IMAC-Cu2+ 20 Condition 1
10
Peak intensity
0 20 Condition 2 10 0 60 40
Condition 3
20 0 2000
4000
6000
8000
10 000
Molecular mass (M/z)
Figure 2. Typical workflow for a discovery phase using SELDI biochips. A series of arrays of different chromatographic characteristics are screened, such as anionic (Q), cationic (CM), IMAC, and reverse phase. Samples are incubated on chemistries under a number of different binding/washing conditions to modulate the specific population of proteins retained by the surface. After final wash to remove any buffer components that may interfere with MS detection, MS spectra are generated that represent a protein fingerprint of that sample under the specific chemistry and binding conditions; which can then be compared across samples such as control versus disease to identify differentially expressed proteins.
of clinical question followed by careful study design and implementation.3 The underlying clinical question will drive the decision on the choice of proteomics technique, the success criteria, how many samples to examine, how to analyze the data, and ultimately, whether the clinical proteomics
program is a success. Therefore, the initial task is to balance the advantages of simplifying the clinical study with the practical utility of the outcome. Obviously the more limited the population on which an outcome is based, the more limited the population the outcome can be applied to,
SELDI TECHNOLOGY
unless additional work is performed to demonstrate the validity of the biomarkers for a more general population. The importance of proper study design cannot be more exemplified than by a study published by Petricoin et al.4 that described the grail of clinical proteomics, the capability of a panel of biomarkers to distinguish early-stage ovarian cancer with 100% sensitivity, 95% specificity and a positive predictive value of 94%. Although this study energized the research community, subsequent scrutiny indicated a number of study design flaws that ultimately provided a conclusory bias that is now generally acknowledged.5 Although this study polarized the proteomic community with respect to the utility of biomarkers, it did solidify for all the importance of all aspects of study design including sampling methods, sample collection, preparation and data generation, candidate biomarker selection based on appropriate statistical analysis, biomarker validation, identification, and finally quantitative assay generation. Today, clinical proteomics is becoming a concerted effort that involves biostatisticians, clinicians, and the bio-analytical core facilities. During the course of the last two years, researchers have used SELDI array technology to perform biomarker discovery research in a variety of diseases including infectious disease,6–8 Alzheimer’s disease,9–13 and cancer.14–17 Further information regarding SELDI array technology and clinical proteomics research is found in the following recent reviews.18–23 As with research proteomics, once the samples are defined and appropriately collected, a typical SELDI clinical proteomic study begins with a discovery phase, in which assay conditions are tested on a relatively small number of samples. Usually, profiling proceeds with at least 30 samples in each classification group (e.g., disease vs healthy or treated vs untreated). This number of samples is usually enough to yield greater than 90% statistical confidence in single markers with p values <0.01 and to allow the use of some forms of multivariate analysis. The samples themselves are another critical parameter. Because the initial sample set size is relatively small, inherent biological variability always threatens the ability to conclude that the differences seen are consequences specific to the disturbance under study. Therefore, it is imperative that the study includes well-chosen samples (e.g., patients of the same age group or
5
all of a single sex) and, equally important, appropriately chosen controls. Naturally, in vitro studies show less variability than do animal studies, which in turn show less variability than human studies. Finding single proteins responsible for differentiating disease versus normal or treated versus untreated is a natural first step in analyzing expression data.24 SELDI analysis generally employs nonparametric statistical methods since one cannot assume that peak intensity data conforms to a normal distribution and SELDI studies often have a small sample size. These methods include the Mann-Whitney, the nonparametric equivalent of the student’s t-test, and the Kruskal-Wallis, the nonparametric equivalent of analysis of variance (ANOVA) thus eliminating any assumption on the distribution of the peak intensity data.25 Essentially, these nonparametric tests sort the peak intensities and their corresponding ranks are used in the p-value calculation. The p-value results of these tests help identify potential markers in conjunction with data visualization tools. These statistical tests simply give an indication of group mean differences, which may not always be helpful if there is a very large spread in the distribution of data. Simply increasing the sample size can improve p values while discrimination between groups may remain poor.26 This is especially important when attempting to use the biomarker in a diagnostic assay as a biomarker’s p value may have no correlation to its clinical value. Furthermore, one may not find single biomarkers with acceptable p values. At this point, it is prudent to turn to other analytical methods that are both multivariate in nature and lend themselves toward developing a clinical assay. There are a number of different analysis tools that identify and use multivariate patterns in the expression profile data for the purposes of identifying groupings and/or classifying groupings. These methods can generally be lumped into one of the two categories—unsupervised learning in the form of cluster analysis, or supervised learning in the form of classification methods. A number of these (only a fraction of existing literature is cited here) have been applied to gene expression data including clustering and visualization,27,28 self-organizing maps,29 and support vector machines.30 Most SELDI clinical proteomic studies have relied upon regression tree-based methods,31,32 and
6
ARRAY TECHNOLOGIES
for the most part, use the algorithms embodied in Ciphergen’s Biomarker PatternsS oftware. Similar to the way a clinician makes his/her diagnosis by correlating and integrating various findings from a patient’s physical examination with laboratory test results, the classification tree creates similar rules based on peak intensity such as, “peak intensity at 13 979 Da <5.169, and at 3272 Da >12.283—therefore this sample belongs to the disease group”. In addition, for each peak cluster that is determined to be a good classifier, Biomarker Patterns Software determines the intensity value that serves as a threshold above or below which a given classification is assigned. A number of characteristics of classification trees make it an attractive tool for protein expression studies. The model is easy to interpret compared to “black-box” classifiers such as neural networks and nearest neighbor classifiers. The protein peaks used in the model are easily attainable by examination of the rules, and these rules are easily validated by examination of the spectra. This openness of the tree-based model is an attractive feature for researchers wanting both a diagnostic assay as well as potential therapeutic targets. In addition, classification trees can sift through all the input variables and select the subset to use in the tree. As such, it alleviates some of the burden of performing feature selection up front. Regardless of study design, once a protein of interest has been detected, protein characterization efforts often ensue. Proteins are characterized by identifying post-translational modifications, providing primary sequence information, and, ultimately, by elucidating protein identity.
4 ASSAY DEVELOPMENT AND VALIDATION
Once a candidate biomarker or panel of markers has been identified, a phase of assay design and validation ensues. This involves optimizing the methods for the routine detection and quantitation of these markers in a massively parallel process. In situations where the analyte to be quantified is a single member of a single family, methods such as immunoassay become an obvious choice for this purpose. However, in instances where the analyte is a specific isoform or protein fragment from a larger protein family, the use of MS
offers an excellent opportunity to provide highly specific analyte detection. As discussed in the preceding text, the incorporation of activated surfaces onto the SELDI-MS probes have overcome many of the difficulties associated with extracting analytes from small sample volumes. Additionally, SELDI biochips are specifically formatted in individual strips of eight spots per array. When 12 such arrays are combined together, the resultant footprint resembles the industry standard 96-well microtiter plate format and allows many options for automation using conventional fluidic robots. Utilization of such robotics not only yields a marked improvement in analytical throughput, but also demonstrates superior qualitative and quantitative reproducibility when compared to manual processing of arrays. For serum profiling experiments, typical protein quantitative profiles demonstrate %coefficient of variation (CVs) of less than 20%. Reducing %CV below this value, however, continues to be challenging due to the laser desorption/ionization process that is inherent in MALDI and SELDI-MS. For example, the laser desorption process is a complex and poorly understood event that depends on the interaction of a laser ionization source and co-crystals of sample and matrix. Variability in the total protein composition between samples can influence the matrix co-crystallization and influence relative ion abundance formations with respect to different analytes to be detected and during the laser desorption/ionization event, ionization of one analyte cannot occur independent of any other analyte exposed at the same time to the ionization source. The best opportunity to define a reliable method of normalization is to make all parameters as similar as possible, however, by definition, calibrants differ in analyte concentration in a predictable manner while samples may differ unpredictably. When such differences are dramatic, even common methods to normalize using total ion current normalization are not sufficient. Most recently, we have developed new methods that have generally resolved much of the normalization difficulties associated with analyte: matrix co-crystallization and laser desorption/ionization. This method relies on many of the principles of displacement chromatography33 and is particularly well suited for use with SELDI biochips. The method involves spiking the sample with a foreign matrix of proteins that contain members of high affinity to the chosen array
SELDI TECHNOLOGY E.coli normalization peaks
(a)
uA
uA
uA
uA
uA
Transthyretin (13.8 kDa)
uA
uA
uA
uA
uA
uA
uA
Serial dilution of serum to generate calibration curve 60 40 20 0 60 40 20 0 60 40 20 0 60 40 20 0 60 40 20 0 60 40 20 0 5000
10 000 15 000 Molecular mass (M/z)
7
20 000 (b)
150 100 50 0 150 100 50 0 150 100 50 0 150 100 50 0 150 100 50 0 150 100 50 0 5000
E.coli normalization peaks
51 mg dl–1
34 mg dl–1
26 mg dl–1
13 mg dl–1
6 mg dl–1
0 mg dl–1 10 000
15 000
20 000
Molecular mass (M/z)
Figure 3. Normalization by addition of a complex protein matrix. MS spectra of a decreasing calibration series of cysteinylated transthyretin (from top to bottom) generated from serial dilution of serum into buffer only (a) or into buffer containing a constant amount of E. coli extract (b). Dilution of serum into buffer only cannot be adequately normalized by total ion current methods to compensate for assay variability because of the lack of sufficient unchanging background. Dilution of serum into buffer containing a constant amount of E. coli protein provides both sufficient unchanging background for normalization and also acts as an internal standard that can also compensate for variability throughout the assay. Using such a method, %CV across assays (day-to-day, operator-to-operator) are 5–10%.
surface. As an example, Ciphergen is currently developing a seven-protein marker assay panel that may aid in the stratification of women with a pelvic mass.34 One such protein marker, a cysteinylated form of transthyretin, is particularly difficult to quantitate in serum because it is an abundant protein and standard curves are generally prepared by serial dilution of control serum into an appropriate assay buffer. Thus, the overall protein background and subsequent mass spectra generated from the highest concentration calibrant is significantly different from the mass spectra generated from the lowest concentration calibrant (Figure 3) and normalization methods using total ion currents are not valid. Supplementing such samples with a foreign material, in this case an Escherichia coli extract, provides an overall consistency in mass spectra between calibrants and
samples. Additionally, the individual mass signatures associated with E. coli specific proteins allows for an internal normalization process that also accounts for variability across the entire sample handling process and has resulted in absolute quantitation with high reproducibility (CV < 10%).
5 FURTHER SEPARATION OF COMPLEX MIXTURES
The ability to detect low abundant species remains a critical challenge in deciphering an entire proteome and correlating proteome changes with metabolic events for diagnostic purposes. Anderson and Anderson35 have thoroughly described
8
ARRAY TECHNOLOGIES
the topic of protein concentration dynamic range in serum and the obstacles in detecting lowabundance proteins. Depletion methodologies are frequently used to remove the most abundant species, however, this removal not only fails significantly to enrich trace proteins, but it may also nonspecifically and nonreproducibly deplete them due to their interactions with the removed highabundance proteins. Albuminomics, for example, specifically looks at only biomolecules that are codepleted during albumin removal because of their specific interaction with albumin.36 Although this is an interesting approach for the detection of specific and potentially low-abundance molecules, its clinical utility has yet to be established. Recently, we reported a new methodology that reduces the protein concentration range of a complex mixture, like whole serum, through the simultaneous dilution of high-abundance proteins and the concentration of low-abundance proteins. The principle of this novel strategy is based on the selective adsorption of proteins on a solid-phase combinatorial ligand library under capacity-overloading binding conditions. The spatial arrangement of amino acids within a protein defines its physicochemical properties, for example, isoelectric point, charge density and hydrophobicity index, and conformation. The latter determines the ability of a protein to interact in vivo with other molecules having complementary structures and forms the basis of protein separation by affinity chromatography where the interacting molecule (ligand) is chemically attached to a solid carrier.37 The complementary proteins to the immobilized ligands are captured from complex mixtures up to the saturation of the available ligand. With sufficient diversity of ligands, it is theoretically possible to have a ligand to every protein in a complex mixture, ensuring that each is adsorbed. When a biological extract like serum is exposed to such a ligand library under specific capacity-constrained conditions, an abundant protein will quickly saturate all of its available high affinity ligands and the vast majority of the same protein will remain unbound. In marked contrast, a trace protein will not saturate all its high affinity ligands and the majority of the same protein will be bound. Thus, based on the saturation-overloading principle, a combinatorial solid-phase library will enrich for trace proteins relative to their abundant counterparts. Following
washing to remove unbound or weakly bound proteins, elution of the adsorbed proteins from the beads will result in a solution with a narrower dynamic range of protein concentrations while still representing all proteins present in the original material. To be effective, the library must meet three criteria: (i) a sufficient reproducible diversity of ligands must be present to reliably bind each protein in the mixture; (ii) dissociation constants of the ligands and proteins must be compatible with the protein concentration; and (iii) the ligand and its support must be compatible with the unfractionated test sample and have a binding capacity high enough to capture sufficient protein to be detected by current methods. The technology is founded upon libraries of peptide ligands on which proteins can be adsorbed. On the basis of the work of Merrifield38 on solid-phase synthesis using the “split, couple and recombine” method, libraries of peptide ligands are synthesized on resin beads.39–41 Each bead has millions of copies of a single, unique ligand, and each bead potentially has a different ligand. Using only the 20 natural amino acids, a library of linear hexapeptides contains 206 , or 64 million different ligands. The addition of unnatural amino acids and D-enantiomers into branched, linear, or circular ligands generates a potential library diversity that is, for all practical purposes, unlimited and may contain a ligand to every protein present in a biological sample. In the current format, a given volume of affinity beads, typically 100 µl to 1 ml, is incubated with at least a 10-fold excess of biological sample for about 1–3 h. Once ligands bind their corresponding proteins, the beads are washed to eliminate unbound or weakly bound proteins. Adsorbed proteins are subsequently released by means of classical elution methods used in chromatography. The eluted protein mixture can then be analyzed by standard methods such as 1-dimensional electrophoresis (DE) and 2-DE and/or SELDI-MS. As reviewed by Righetti et al.42 such enrichment was evidenced in a variety of very different biological samples, including human sera, low concentration cell culture supernatant, and chicken egg white. Thus, the method largely addresses the problem of the dynamic range in clinical proteomic analyses.
SELDI TECHNOLOGY
6 CONCLUDING REMARKS
During the course of the last decade, SELDI protein array technology has demonstrated utility in the analysis of protein complexes, the discovery of relevant biomarkers, and the creation of assays for clinical, drug discovery, or basic biological research. With the more recent global proteomic focus on biomarkers and their utility in human health, the amount of time and resources directed to this topic will likely increase at a pace not seen earlier. Irrespective of the detection method, a fundamental problem of enriching for the disproportionately large number of lowabundance proteins in a background of a few dozen high-abundance proteins is the current challenge. Currently, the clear direction is for the depletion of the abundance proteins followed by the concentration of the rare species. Whether this is accomplished serially by abundance protein depletion followed by subsequent remaining analyte concentration and/or liquid chromatographic steps, or simultaneously via combinatorial approaches such as that used in Ciphergen’s equalizer bead technology, the ultimate decision will be driven by the reproducibility of the methods and how this translates to the biological question. Greatest efforts will also be directed to adequately work with samples at ever-decreasing volumes. Considerable efforts are already directed toward micro and nanofluidics separation techniques that can be interfaced with conventional detection methods such as fluorescence or MS. In this area, such capabilities of chromatographic separation or equalizer bead enrichment followed by secondary cleanup on SELDI arrays is a logical approach to this problem. In terms of SELDI surface chemistry, continued efforts in developing novel affinity surfaces to further extract unique populations of proteins from a biological sample will provide an additional level of specificity and will ultimately lead toward the design of specific surfaces for the routine quantitative analyses of analytes demonstrated to be statistically correlated with a biological question. Improvements in chip reader technology is also expected as work toward the creation of MS devices with simultaneous high detection sensitivity for proteins and mass resolving power for peptides and proteins is enabled by implementing new laser optic, ion optic, and mass analyzer approaches. Additionally, it is expected
9
that the next generation of chip readers will not only demonstrate improved analytical performance when compared with their predecessors, but also provide a more robust, easier-to-use, and quantitative platform for the purpose of facilitating translational proteomic studies as well as the performance of in vitro diagnostic tests.
REFERENCES 1. T. W. Hutchens and T. T. Yip, New desorption strategies for the mass spectrometric analysis of macromolecules. Rapid Communications in Mass Spectrometry, 1993, 7, 576–580. 2. S. R. Weinberger, E. A. Dalmasso, and E. T. Fung, Current achievements using ProteinChip array technology. Current Opinion in Chemical Biology, 2002, 6, 86–91. 3. E. T. Fung, Strategies in clinical proteomics: from discovery to assay. Preclinica, 2004, 2, 253–258. 4. E. F. Petricoin, A. M. Ardekani, B. A. Hitt, P. J. Levine, V. A. Fusaro, S. M. Steinberg, G. B. Mills, C. Simone, D. A. Fishman, E. C. Kohn, and L. A. Liotta, Use of proteomic patterns in serum to identify ovarian cancer. Lancet, 2002, 359, 572–577. 5. D. F. Ransohoff, Lessons from controversy: ovarian cancer screening and serum proteomics. Journal of the National Cancer Institute, 2005, 97, 315–319. 6. J. L. Hess, L. Blazer, T. Romer, L. Faber, R. M. Buller, and M. D. P. Boyle, Immunoproteomics. Journal of Chromatography B, 2005, 815, 65–75. 7. D. Barzaghi, I. D. Jenefir, L. P. Kimberly, and T. L. Born, Use of surface-enhanced laser desorption/ionization -time of flight to explore bacterial proteomes. Proteomics, 2004, 4, 2624–2628. 8. X. D. Zhu, W. H. Zhang, C. L. Li, Y. Xu, W. J. Liang, and P. Tien, New serum biomarkers for detection of HBV-induced liver cirrhosis using SELDI protein chip technology. World Journal of Gastroenterology, 2004, 10, 2327–2329. 9. E. Head, K. Moffat, P. Das, F. Sarsoza, W. W. Poon, G. Landsberg, et al., Beta-amyloid deposition and tau phosphorylation in clinically characterized aged cats. Neurobiology of Aging, 2005, 26, 749–763. 10. O. Yalkinoglu, G. Koenig, D. F. Hochstrasser, J. C. Sanchez, O. Carrette, SELDI-TOF MS Detection and Identification of Protein Biomarkers for Diagnosing Alzheimer’s Disease, Vol. Application: WO, Bayer Healthcare A.-G, Germany, 2004, pp. 38. 11. A. S. Maddalena, A. Papassotiropoulos, C. GonzalezAgosti, A. Signorell, T. Hegi, T. Pasch, et al., Cerebrospinal fluid profile of amyloid β peptides in patients with alzheimer’s disease determined by protein biochip technology. Neurodegenerative Diseases, 2004, 1, 231–235. 12. H. D. Lewis, D. Beher, D. Smith, L. Hewson, N. Cookson, D. S. Reynolds, et al., Novel aspects of accumulation dynamics and Ab composition in transgenic models of AD. Neurobiology of Aging, 2004, 25, 1175–1185.
10
ARRAY TECHNOLOGIES
13. P. Lewczuk, H. Esselmann, W. T. Groemer, M. Bibl, J. M. Maler, P. Steinacker, et al., Amyloid beta peptides in cerebrospinal fluid as profiled with surface enhanced laser desorption/ionization time-of-flight mass spectrometry: evidence of novel biomarkers in Alzheimer’s disease. Biological Psychiatry, 2004, 55, 524–530. 14. L. Le, K. Chi, S. Tyldesley, S. Flibotte, D. L. Diamond, M. A. Kuzyk, and M. D. Sadar, Identification of serum amyloid a as a biomarker to distinguish prostate cancer patients with bone lesions. Clinical Chemistry, 2005, 51, 695–707. 15. K. Junker, J. Gneist, C. Melle, D. Driesch, J. Schubert, U. Claussen, and F. Von Eggeling, Identification of protein pattern in kidney cancer using ProteinChip arrays and bioinformatics. International Journal of Molecular Medicine, 2005, 15, 285–290. 16. Y. F. Wong, T. H. Cheung, K. W. K. Lo, V. W. Wang, C. S. Chan, T. B. Ng, et al., Protein profiling of cervical cancer by protein-biochips: proteomic scoring to discriminate cervical cancer from normal cervix. Cancer Letters (Amsterdam, Netherlands), 2004, 211, 227–234. 17. C. Melle, R. Kaufmann, M. Hommann, A. Bleul, D. Driesch, G. Ernst, and F. Von Eggeling, Proteomic profiling in microdissected hepatocellular carcinoma tissue using protein chip technology. International Journal of Oncology, 2004, 24, 885–891. 18. K. R. Coombes, Analysis of mass spectrometry profiles of the serum proteome. Clinical Chemistry, 2005, 51, 1–2. 19. S. J. Walker and A. Xu, Biomarker discovery using molecular profiling approaches. International Review of Neurobiology, 2004, 61, 3–30. 20. T. D. Veenstra, L. R. Yu, M. Zhou, and T. P. Conrads, Diagnostic proteomics: serum proteomic patterns for the detection of early stage cancers. Disease Markers, 2003, 19, 209–218. 21. N. Tang, P. Tornatore, and S. R. Weinberger, Current developments in SELDI Affinity technology. Mass Spectrometry Reviews, 2003, 23, 34–44. 22. E. F. Petricoin and L. A. Liotta, Clinical applications of proteomics. Journal of Nutrition, 2003, 133, 2476S–2484S. 23. H. J. Issaq, T. P. Conrads, D. A. Prieto, R. Tirumalai, and T. D. Veenstra, SELDI-TOF MS for diagnostic proteomics. Analytical Chemistry, 2003, 75, 148A–155A. 24. A. D. Long, H. J. Mangalam, B. Y. Chan, L. Tolleri, G. W. Hatfield, and P. Baldi, Improved statistical inference from DNA microarray data using analysis of variance and a Bayesian statistical framework: analysis of global gene expression in Escherichia coli K12. Journal of Biological Chemistry, 2001, 276, 19937–19944. 25. R. Sprinthall, Basic Statistical Analysis, Prentice-Hall, New Jersey, 1997. 26. T. F. Pajak, G. M. Clark, D. J. Sargent, L. M. McShane, and M. E. Hammond, Statistical issues in tumor marker
27.
28.
29.
30.
31.
32.
33. 34.
35.
36.
37. 38. 39.
40.
41.
42.
studies. Archives of Pathology and Laboratory Medicine, 2000, 124, 1011–1015. A. Ben-Dor, R. Shamir, and Z. Yakhini, Clustering gene expression patterns. Journal of Computational Biology, 1999, 6, 281–297. M. B. Eisen, P. T. Spellman, P. O. Brown, and D. Botstein, Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95, 14863–14868. T. R. Golub, D. K. Slonim, P. Tamayo, C. Hurard, M. Gaasenbeek, J. P. Mesirov, et al., Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science, 1999, 286, 531–537. E. J. Moler, M. L. Chow, and L. S. Mian, Analysis of molecular profile data using generative and discriminative methods. Physiological Genomics, 2000, 4, 109–126. L. Breiman, J. Friedman, R. Olshen, C. Stone, Classification and Regression Trees, Wadsworth, Pacific Grove, California, 1984. H. Zhang, C. Y. Yu, B. Singer, and M. Xiong, Recursive partitioning for tumor classification with gene expression microarray data. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98, 6730–6735. H. Kalasz, Editorial: displacement chromatography. Journal of Chromatographic Science, 2003, 41, 281–283. Z. Zhang, et al., Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Research, 2004, 64, 5882–5890. N. L. Anderson and N. G. Anderson, The human plasma proteome: history, character, and diagnostic prospects. Molecular and Cellular Proteomics, 2002, 1, 845–867. M. S. Lowenthal, et al., Analysis of albumin-associated peptides and proteins from ovarian cancer patients. Clinical Chemistry, 2005, 51, 1933–1945. M. Wilchek, T. Miron, and J. Kohn, Affinity chromatography. Methods in Enzymology, 1981, 104, 3–55. R. B. Merrifield, Automated synthesis of peptides. Science, 1965, 150, 178–185. K. S. Lam, et al., A new type of synthetic peptide library for identifying ligand-binding activity. Nature, 1991, 354, 82–84. A. Furka and F. Sebetyen, General methods for rapid synthesis of multi-component peptide mixtures. International Journal of Peptide and Protein Research, 1991, 37, 487–493. A. D. Watts, N. H. Hunt, B. D. Hanbly, and G. Chaudhri, Separation of tumor necrosis factor alpha isoforms by two-dimensional polyacrylamide gel electrophoresis. Electrophoresis, 1997, 18, 1086–1091. P. G. Righetti, E. Boschetti, L. Lomas, A citterio, protein equalizer technology: the quest for a ‘democratic proteome’. Proteomics, 2006, 6, 3980–3992.
56 Fiber-Optic Array Biosensors Rahela Gaˇsparac and David R. Walt Department of Chemistry, Tufts University, Medford, MA, USA
1 INTRODUCTION
Biosensors are chemical sensors that consist of three basic elements: a receptor (biological recognition element), transducer (physical component), and a separator (membrane or coating).1–3 Optical biosensors are a class of biosensors that use light to detect the presence of a chemical or biochemical. An optical fiber biosensor is a biosensor that employs either a single optical fiber or an optical fiber array as the biosensing platform. A typical single optical fiber is made of glass or plastic. Each fiber consists of an inner glass called the core and an outer glass called the cladding. Both core and cladding are encased in a buffer coating that protects the fiber from moisture and damage.4 Optical fibers operate via a process called total internal reflection, which occurs when the core refractive index is higher than the clad refractive index (Figure 1a). Several optical fibers can be fused and drawn into a coherent bundle, creating an optical fiber array (Figure 1b).5 Optical fiber arrays containing between 3000 and 100 000 individual optical fibers fused into a total diameter of 0.2–2 mm have been reported.6 Fiber-optic arrays possess both advantages and disadvantages for biosensing.7–11 Some important advantages include increased sensitivity, amenability to miniaturization, relatively low cost, electromagnetic immunity, and geometric flexibility.9 Different sensing chemistries may be attached to the end of the optical fiber array, allowing spatial and spectral resolution. Thus, optical fiber arrays
have become extremely important in medical research,12,13 clinical diagnostics,14,15 food quality control,14,16,17 and pharmacology and pharmaceuticals development.18 Biomolecules commonly immobilized on optical fiber arrays include oligonucleotides, polymerase chain reaction (PCR) products, enzymes, and antibodies. Living cells have also been loaded in microwell optical fiber arrays, allowing live whole-cell biosensing. Fiberoptic array biosensors are classified on the basis of the nature of the biological recognition element used for sensing. In this review, we discuss nucleic acid, enzyme, whole-cell, and immunoassay (antibody/antigen) fiber array–based biosensors. 1. Nucleic acid biosensing relies on immobilization of a single-stranded deoxyribonucleic acid (ssDNA) on one end of the fiber-optic array surface. Detection is based on hybridization between ssDNA and a fluorescently labeled complementary ssDNA sequence. 2. Enzymes are one of the most commonly used biological recognition elements for fiberoptic biosensors. The enzyme acts as a catalyst, facilitating a highly specific and sensitive reaction. The products of the enzymatically catalyzed reaction are usually detected either directly or indirectly upon interaction with an indicator. 3. Whole-cell fiber-optic array biosensors commonly employ genetically engineered whole cells as the biological recognition elements. A wide variety of live mammalian cell types such
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES Core
Cladding
hn (out)
a
hn (in) a
(a)
×10 000 2 µm #42 Illumina
1.00 kv Polished
3 mm
Current Opinion in Chemical Biology
(b)
Figure 1. (a) Schematic of an optical fiber. Light propagates in the fiber along the entire length because of the refractive index differences of the core and clad materials. (b) Scanning electron micrograph (SEM) of a region of an optical imaging fiber array. The circles are the fiber cores that carry light signals. The darker gray regions are the cladding that confines the light within the cores. [Reprinted with permission Walt5 copyright 2002, Elsevier.]
as neurons, cardiomyocytes, hepatocytes, and immune cells, as well as viruses, yeasts, and bacteria, have been used to fabricate wholecell-based biosensors. 4. Immunoassay fiber-optic array biosensors report on the specific binding between an antibody as the biological recognition element and an antigen. Immunoassays are usually performed in one of three modes: direct, competitive, and sandwich. The specific binding of an antibody to an antigen allows for the detection of sample analytes by a variety of immunoassay modes.
2 FIBER-OPTIC ARRAYS AS NUCLEIC ACID BIOSENSORS
Over the past decade, there has been a significant increase in the development and use of nucleic acid–based fiber-optic arrays. This increase is, in part, due to the completion of the Human Genome Project and availability of genetic information from additional sequencing efforts.19,20 Nucleic acid optical fiber arrays have been applied to pathogen detection,21,22 medical diagnostics,12,13 new drug discovery,18 genetic analysis for detecting single-nucleotide polymorphisms (SNPs),23–25 and gene expression analysis26–28 with the potential for whole-genome screening.29,30 Nucleic acid biosensing relies on the immobilization of an ssDNA called the probe on one end of the fiberoptic array surface. The detection method is based on hybridization between the probe and a fluorescently labeled complementary sequence of ssDNA called the target. The target of interest may first need to be amplified using PCR. The optimization of the nucleic acid immobilization strategy, the choice of fluorophore, and the hybridization temperature may improve selectivity, signal intensity, and signal-to-noise ratio.13,22,31–33 The following section is a review of the recent advances in nucleic acid–based biosensing on optical fiber array platforms. A versatile optical fiber array platform has been fabricated by chemically etching the distal end of a polished optical fiber bundle (typically containing between 6000 and 50 000 individual fibers). Chemical etching agents such as hydrofluoric acid or diluted hydrochloric acid are typically employed. Chemical etching allows selective etching of the fiber’s core relative to the cladding.10,34–36 Since the etching rate is faster for the core material, an array of identical microwells is created with diameters corresponding to the individual fiber cores (Figure 2a). Microwells of different depths can be tailored depending on the etching-agent concentration and the exposure time.34,35 Figure 2(a) shows an atomic force micrograph (AFM) image of an etched optical fiber bundle containing ∼3.6µm-diameter microwells that are ∼3-µm deep.37 Complementary-sized latex or silica microspheres with different sensing chemistries can be loaded into the microwells either by applying a small aliquot of microsphere suspension directly to the
6.000 µm
FIBER-OPTIC ARRAY BIOSENSORS
µm 10 5
6.000 µm
(a)
µm 10 (b)
5
Figure 2. (a) Atomic force micrograph (AFM) image of ∼3.6-µm-diameter microwells created by chemically etching a polished, 1000-µm-diameter imaging fiber. The distal end of the imaging fiber was submerged into a buffered hydrofluoric acid solution for 80 s. The microwells produced are ∼3-µm deep. (b) AFM image of ∼3.6-µm-diameter microwells containing a single 3.1-µm-diameter microsphere in each microwell. [Reprinted with permission Michael et al.37 copyright 1998, American Chemical Society.]
optical fiber end or by dipping the etched optical fiber into a microsphere-containing solution (Figure 2b). Figure 2(b) shows an AFM image of ∼3.6-µm-diameter microwells containing a single 3.1-µm microsphere in each microwell. It is important to note that the microspheres match the size of the etched microwell and remain firmly in the microwells via electrostatic interactions. Since each microwell is connected to its own optical fiber, each microwell can be interrogated as an individual sensor. Nucleic acid optical fiber arrays can be prepared by attaching oligonucleotide probes to the microspheres. Oligonucleotide probes are usually attached to microspheres via an amine-linker, but
3
other attachment strategies have been reported.38 Each microsphere carries a specific DNA probe sequence. Microspheres of different DNA probe sequences are mixed together into a library and randomly distributed onto the etched optical fiber array surface (Figure 3a).10,27,35,36,39,40 The position of the individual microspheres on the fiberoptic array cannot be predetermined. Thus, it is necessary to have a method for resolving the location of the microspheres in the array. Two methods for microsphere registration are employed. In the first method, a unique combination of fluorescent dyes is used to encode different types of microspheres either before or after DNA probe attachment. Fluorescent dyes used for encoding must have different excitation and emission wavelengths that allow a unique signature, that is, an “optical bar code” for each microsphere type to be determined. The encoding step is important because it enables the positional registration of every microsphere in the fiber array.11,39,41 Each microsphere with its unique optical bar code can then be easily decoded by simply collecting a series of fluorescence images with a chargecoupled device (CCD) camera at different excitation and emission wavelengths, and analyzing the resultant intensities of each microsphere with imaging software (Figure 3b). Once the positional registration of each encoded microsphere with its specific DNA probe in the array is determined, the platform is then exposed to a fluorescently labeled target DNA solution, producing signals only on those microspheres bearing the DNA probes complementary to the target DNA in solution. It is important to note, that fluorescent dyes used for microsphere encoding must have different excitation and emission wavelengths than fluorescent dyes used for target DNA labeling to prevent spectral overlap. The second approach to array decoding uses a combinatorial decoding scheme that allows each microsphere type in the optical fiber array to be identified.39,42 In this approach, each DNA probefunctionalized microsphere is identified using an algorithm that involves sequential hybridization of fluorescently labeled target DNA or decoders complementary to probe DNA sequences (Figure 4). Gunderson et al. were able to decode thousands of different DNA sequences with only a few fluorescent labels (called states) and several sequential hybridizations (called stages).42
4
ARRAY TECHNOLOGIES Probe A Probe B Probe C Different DNA probes are attached to dye-encoded microspheres
Probes are combined into a library Microwells on etched optical fiber
CCD chip Distal face of imaging optical fiber Probe microsphere library is distributed randomly into microwells on fiber array surface
(a)
Computer monitor
Xenon arc lamp
Filters CCD camera
Dichroic housing and, microscope nosepiece (b)
Fiber holder micropositioner
Figure 3. (a) Decoding scheme using a dye-encoded-microspheres approach. Three different DNA probes are attached to fluorescently encoded microspheres, combined into a probe microsphere library, and randomly distributed on the distal end of the optical fiber end. Each microsphere with its unique optical bar code is decoded by collecting a series of fluorescence images with a charge-coupled device (CCD) camera at different excitation and emission wavelengths. (b) The general setup of the custom-built imaging system consisting of computer-controlled modified epifluorescence microscope, a xenon arc lamp, excitation and emission filters, microscope objectives, and a CCD camera. Fluorescence images are processed using imaging software.
Figure 4 illustrates an example of decoding eight different microsphere types using sequential hybridization of fluorescently labeled target DNA in a two-state, three-stage system. Target DNA sequences complementary to DNA probes attached to the microspheres were synthesized and mixed
in different combinations, creating unique decoder pools. The decoder pools were then used in sequential hybridizations with the microsphere array, generating a unique combinatorial code for each microsphere type. This combinatorial code identifies each microsphere type. With more
FIBER-OPTIC ARRAY BIOSENSORS Stage 1
Dehybridized
Stage 2
5 Stage 3
Dehybridized
3′ #2′
#2
#2′
#2
#2′
#2
#2
#2
(a)
(b)
Sequences
Stage 1
Stage 2
Stage 3
Signature
Code
Parity code
0
GGG
000
0000
1
GGR
001
0011
2
GRG
010
0101
3
GRR
011
0110
4
RGG
100
1001
5
RGR
101
1010
6
RRG
110
1100
7
RRR
111
1111
(c) Figure 4. Combinatorial decoding process. (a) The sequential hybridization process is illustrated for a single microsphere, of microsphere type 2. In stage 1, a complementary decoder hybridizes to the oligonucleotide probe that is attached to the microsphere. The decoder is labeled with a fluorophore (green in stage 1, red in stage 2, and green in stage 3). The fluorescent signal is read by imaging the entire array. The array is then dehybridized, and the process is repeated for two more stages. (b) A scanning electron micrograph of an array of microspheres, false colored to represent three sequential hybridization stages. The images, taken collectively, reveal a combinatorial code for each microsphere. Note that the microsphere circled in yellow has the color signature GRG or code 010. (c) Colors or states are assigned to individual decoder sequences in each stage to produce a unique combination across stages. This signature, or code, identifies each microsphere type. As indicated in the parity code column, an extra decoding stage can be performed to provide an error checking parity bit. After three stages of decoding, all the microspheres are uniquely identified by their color. [Reprinted with permission Gunderson et al.42 copyright 2004, Cold Spring Harbour Laboratory Press.]
dyes and more stages, the combinatorial decoding scheme enables the identification of up to 1792 different microsphere types42 and was used in applications such as SNP genotyping24,43,44 and gene expression profiling.27,28
Epstein et al. reported zeptomole detection limits (DLs) (∼600 molecules) of three different target DNA sequences using this microsphere fiber array platform.45 The DNA probe sequences used for this study belonged to interleukin 2 (IL2),
6
ARRAY TECHNOLOGIES
IL6, and the F508C mutation in the cystic fibrosis gene. The mixture of probe DNA–functionalized microspheres was randomly distributed on the 3.1-µm-diameter fiber array etched distal face. Hybridization with fluorescently labeled target DNA was allowed to proceed for up to 12 h. Satisfactory hybridization signals were achieved by averaging 10 microspheres of each probe type, enabling an acceptable signal with 7% coefficient of variation. In addition, target DNA concentrations of 1 fM gave 100% reproducible results, while 100 aM concentrations had a reproducibility of 80%. Ferguson et al. reported a 10 fM DL of fluorescently labeled DNA targets using an optical encoding scheme.46 Yeakley et al. used the microwell optical fiber array platform for profiling messenger ribonucleic acid (mRNA) isoforms.47 The mRNA transcripts were analyzed without prior RNA purification or complementary deoxyribonucleic acid (cDNA) synthesis. The detection of mRNA isoforms was achieved from 10 to 100 pg of total cellular RNA. The reported sensitivity may be suitable for monitoring gene expression in tissues and the fiber-optic array matrix format permits parallel analysis of different samples. Steemers et al. were able to screen unlabeled genomic cystic fibrosis–related DNA targets using molecular beacons (MBs) immobilized on microspheres.48 Thrombin detection was achieved by Lee et al.49 using immobilized aptamers on microspheres. Bowden et al. developed a fiber-optic array integrated with a microfluidic platform for the detection of the biological warfare agent (BWA) simulant Bacillus thuringiensis Kurstaki (BTK ) capable of attomolar target DNA detection.50 BWA detection draws lots of attention these days in order to minimize human casualties caused by a biological attack, improve public health, and enhance homeland security.51 The detection of BWAs is very challenging because it needs to be specific, rapid, and extremely low concentrations of harmful substances need to be identified. In these studies 50-mer probe oligonucleotides were designed. The microfluidic fiber-optic array platform is depicted in Figure 5. The target DNA was passed across the fiber array surface via pressuredriven flow in a microfluidic channel, ensuring laminar flow. Using this system, the hybridization of 10 aM target DNA occurred in less then 15 min at a flow rate of 1 µ l min−1 . Comparison studies
of static (no flow) and microfluidic measurements showed two significant advantages of the microfluidic setup: faster hybridization and lower DLs (1000-fold lower over static setup). It has been also shown that dehybridization in the microfluidic setup were both very rapid and very reproducible, enabling regeneration of the fiber-optic array. In continuing research on BWA detection, Song et al. reported the use of the fiber-optic array platform for multiplexed BWA detection.52,53 Eighteen different 50-mer oligonucleotide sequences were designed for Bacillus anthracis, Yersinia pestis, Francisella tularensis, Brucella melitensis, Clostridium botulinum, Vaccinia virus, and one BWA simulant—BTK. A cyanuric chloride coupling procedure was used to enhance DNA probe coupling efficiency to the encoded microspheres.46 A DL of 10 fM was reported for B. anthracis, Y. pestis, Vaccinia virus, and BTK. The crossreactivity assays of the multiplexed DNA array were established by exposing single-microsphere types to their complementary DNA targets and to the 17 noncomplementary ones. Some crossreactions occurred but usually were limited to other probes from the same organism. Multiplexed arrays with mixed samples were also prepared by combining B. anthracis with BTK, and Y. pestis with F. tularensis in different ratios. The results obtained in these studies clearly indicated high specificity of the amplification and hybridization assay for detecting target BWAs. While the identification and detection of BWAs are clearly needed, the classification of emerging pathogenic strains54 such as SARS (severe acute respiratory syndrome),55 West Nile virus,56 and a virulent strain of Vibrio cholerae O13957 are of great importance as well. In the effort to develop a fiber-optic array for bacterial detection, Shepard et al. used multilocus sequence typing (MLST) methodology58–60 on a fiber-optic array platform to characterize 12 Escherichia coli strains at five loci: ycgW, yaiN, osmB, galS, and serW.54 This group specifically selected a set of probe sequences for each locus allowing them to simplify the response to a binary signal/no signal response upon hybridization to each of the probes. Using this approach, 6 different oligonucleotide probes were enough to rapidly classify 12 different E. coli strains. A patterned response method was able to classify an “unknown” strain as wild-type nonpathogenic E. coli strain ECOR-44.
FIBER-OPTIC ARRAY BIOSENSORS
7
Optical fiber
PMMA microfluidic chip
Rubber tubing Optical fiber
Pump
Sample vial Teflon nut and PEEK flangeless ferrules
(a)
Microfluidic channel C O R E Microsphere with DNA probe
C L A D D I N G
Fluorescently labeled complementary target
(b)
Direction of 1 µl min−1 flow
Figure 5. (a) A cross-sectional schematic diagram showing the microfluidic T-junction layout. The poly(methyl methacrylate) (PMMA) microfluidic chip was fabricated in a Tefzel tee consisting of a 1.25-mm inner diameter channel and a dead volume of <20 µl. The fiber bundle is positioned perpendicular to the flowing stream. The optical fiber array was jacketed by Teflon tubing and attached to the flow chamber by a PEEK nut and ferrule. (b) Schematic diagram of the optical imaging fiber bundle showing DNA hybridization in the microfluidic manifold. DNA probe microspheres that are complementary to the fluorescently labeled DNA targets fluoresce upon illumination through the imaging fiber proximal end. [Reprinted with permission Bowden et al.50 copyright 2005, American Chemical Society.]
One of the challenges in the development of nucleic acid biosensors is SNP detection.61 This process is often cumbersome—it requires amplification, followed by time-consuming enzymatic digestion or extension, and separation of the resulting products. Several authors reported the use of a commercially available microsphere-based optical fiber array platform for high-throughput SNP genotyping.24,43,44 This platform not only combines multiplexed analysis but is also highly accurate, robust, and cost-effective, giving the
opportunity to associate genes with phenotypes of interest. Shen and coworkers showed that high-throughput SNP genotyping can be performed on a universal microsphere fiber-optic array platform using the Illumina GoldenGate genotyping assay.43 This assay detects up to 1536 SNPs in a single DNA sample (minimum 250 ng at 50 ng µl−1 ). Gunderson et al. developed a whole-genome genotyping (WGG) assay on the microsphere-based optical fiber array platform that was used for genotyping hundreds of previously
8
ARRAY TECHNOLOGIES
characterized SNPs.44 A high signal-to-noise ratio was achieved by combining hybridization of relatively high concentrations (∼2–3 pM) of WGA genomic deoxyribonucleic acid (gDNA) to arrayed 50-mer oligonucleotide probes with allele-specific primer extension (ASPE) and signal amplification. A high specificity was achieved in the presence of the entire genome. In the continuing research of the WGG assay technology, Steemers et al. described an improved version of the WGG assay.29 This version of the WGG assay includes single-base extension (SBE) rather than the ASPE step. The details of the ASPE and SBE steps in the WGG assay can be found elsewhere.30 The genotyping performance was demonstrated by resequencing homozygous loci from the 100 k Human-1 Genotyping BeadChip, showing accurate and reproducible SNP genotyping assay data. Finally, Brogan et al. gave a detailed overview of the use of the microsphere-functionalized fiber-optic array platform for SNP, genotyping, and quantitative gene expression profiling.21 In addition, several recent publications by the Krull research group described nucleic acid–based optical fibers that did not require traditional labels.31,62–64 The intercalating fluorescent dye thiazole orange (TO) was covalently linked to a 5 -oligonucleotide probe (nonpathogen Erwinia herbicola gene fragment)-modified fused silica optical fiber.63 Hybridization with the complementary oligonucleotide sequence occurred in a sample solution and was monitored by detection of fluorescence intensity changes. It was shown that TO exhibits enhanced fluorescence intensity upon hybridization to a complementary DNA sequence in solution.62 A sixfold fluorescence intensity enhancement has been reported upon hybridization with the complementary DNA sequence. Hence, the fluorescence intensity was decreased upon hybridization with the SNP target sequence, suggesting the potential application of DNA TO-based sensing in SNP analysis.
3 FIBER-OPTIC ARRAYS AS ENZYME BIOSENSORS
Enzymes are the most abundantly used biological recognition elements for fiber-optic biosensors.
In these systems, the enzyme acts as a catalyst facilitating a highly specific and sensitive reaction. The products of the enzymatically catalyzed reaction can be detected in direct fashion or indirectly upon interaction with an indicator (reagent).8,65 Direct detection mode is possible when the substrates, products, or intermediates are spectroscopically active (e.g., they exhibit absorbance, fluorescence, or chemiluminescence (CL)). In this case, the optical transducer directly detects the optical changes. Indirect detection via an indicator is necessary when the substrates, products, or intermediates of the enzymatic reaction possess no intrinsic optical properties (e.g., O2 , CO2 , NH3 , pH, NADH, H2 O2 ). In this case, the reduction or production of one of these species is detected by its reaction with the indicator.7,9,66,67 In the last decade, a plethora of papers have been published about enzyme optical fiber biosensors based on different types of transduction mechanisms.7–9,68 Enzymes are employed in either pure form or contained on or within a biological matrix such as a cell or vesicle. This review focuses mainly on the fiber-optic array platform when substrates, products, or intermediates of the enzymatic reaction exhibit optical properties (fluorescence, CL, or electrogenerated chemiluminescence or electrochemiluminescence (ECL)).
3.1
Fluorescence Methods
Durrieu et al. developed an enzymatic whole-cell fiber-optic biosensor for the detection of freshwater pollutants such as Pb2+ and Cd2+ .69,70 Chlorella vulgaris cells, which display alkaline phosphatase (AP) on the external surface of their cell membranes, were immobilized on a glass microfiber filter. This filter was placed in front of an optical fiber bundle inside a flow cell. The AP-catalyzed reaction produces two reaction products, phosphate and fluorescent methylumbelliferone (MUF) from methylumbelliferoyl phosphate (MUP). It has been shown that the AP catalytic activity is strongly inhibited in the presence of heavy metals, resulting in a decrease of MUF fluorescence intensity. Comparisons between a fiber-optic biosensor and a microplate reader were similar. Approximately 35% AP inhibition was achieved for 0.01 mg l−1 concentrations of Cd2+ and Pb2+ .
FIBER-OPTIC ARRAY BIOSENSORS
Doong and Tsai developed a fluorescence solgelbased fiber-optic biosensor for the determination of acetylcholine.71 This approach employed the fluorescent dye fluorescein isothiocyanate (FITC)dextran encapsulated with acetylcholinesterase (AChE) in a solgel network. The solgel matrix was immobilized on the distal end of an optical fiber bundle. The enzymatic reaction of AChE and acetylcholine forms acetic acid, resulting in a fluorescence intensity change of the pH-sensitive fluorescent FITC-dextran dye. This reversible and reproducible fiber-optic biosensor showed linearity between 0.5 and 20 mM of acetylcholine. These authors also reported the use of this fiberoptic biosensor for detecting organophosphorous pesticides such as paraoxon. A 30% AChE inhibition was obtained when 152 ppb paraoxon was added into the system, resulting in increased fluorescence intensity (Figure 6). A fluorescence optical fiber biosensor based on E. coli cytoplasmic membranes as the source of enzyme was described by Ignatov et al.72 E. coli cells were cultured in the presence of sodium lactate to initiate formation of the enzyme L-lactate oxidase. The L-lactate oxidase enzyme catalyzes the conversion of L-lactate to pyruvate. During this process, molecular oxygen is consumed and peroxide is liberated. An oxygen-sensitive dye, ruthenium tris(diphenylphenoanthroline) (Ru(ph)2 phen)3 2+ , was encapsulated in a thin polysiloxane film on
9.5
Intensity (V)
9 8.5 ACh
8
ACh
ACh
7.5
9
the surface of an optical fiber bundle. When the enzyme is active, oxygen is consumed in the catalytic reaction, causing a fluorescence increase of the Ru-based dye. Interferences with other substances (glucose, fructose, and glutamic acid in 50-mM concentrations) were not observed, demonstrating good selectivity of the sensor. Issberner et al. reported an enzyme-based fiberoptic array biosensor for L-glutamate release and reuptake from the foregut plexus of the tobacco hornworm Manduca sexta.73 A gel composed of the enzyme L-glutamate oxidase (GLOD), a pH-sensitive fluorescent dye SNAFL (5- and 6carboxy seminaphthofluorescein), and poly(acrylamide-co-N -acryloxysuccinimide) (PAN) was attached to the distal face of an optical fiber array by spin-coating. When L-glutamate reacts with GLOD, NH3 is released. The increased ammonia concentration reduces the fluorescence intensity of SNAFL. The DL of L-glutamate was 10–100 µM. Interferences with other amino acids both in vitro and in vivo were not observed, demonstrating good specificity of the L-glutamate sensor. This paper also demonstrated the ability to visualize L-glutamate release in vivo from the nerves of the foregut plexus with a relatively high temporal resolution. This platform is distinguished from other enzyme-based array approaches because L-glutamate release can be localized using the spatial resolution of the array to provide both chemical and visual images of the sample. A dual-enzyme fiber-optic array biosensor for pyruvate has been developed by Zhang et al.74 An optical fiber bundle consisting of 14 individual fibers was used for these studies. Lactate oxidase (LOX) and lactate dehydrogenase (LDH) were immobilized at the optical fiber distal end. Pyruvate detection was accomplished by monitoring the consumption of the fluorophore NADH during the enzymatic reactions:
7 Paraoxon
6.5 0
20
40
60
Lactate + NAD+
80 100 120 140 160 180 200 Time (min)
Pyruvate + NADH + H+ (1)
Lactate + O2 Figure 6. Time–response curve of an acetylcholinesterasebased fiber-optic biosensor before and after exposure to 0.54 mM (152 ppb) paraoxon. Paraoxon was added at the time indicated by the arrow. [Reprinted with permission Doong and Tsai.71 Copyright 2001, Elsevier.]
LDH ←−→
LOX −−−−→
Pyruvate + H2 O2
(2)
By adjusting the pH of the sample solution the equilibrium of the first reaction can be controlled. NADH and pyruvate diffuse from the bulk solution
10
ARRAY TECHNOLOGIES
toward the dual-enzyme (LDH and LOX) layer immobilized at the optical fiber end. At low pH, LDH catalyzes the formation of lactate and NAD+ . As the reaction proceeds, pyruvate is reduced and NADH is consumed at the fiber end. LOX then regenerates pyruvate as shown in the second reaction, allowing more NADH to react thereby making the measurement more sensitive. A steadystate NADH concentration is established when the rate of NADH consumption is counterbalanced with the NADH diffusion from bulk solution. The sensor was tested in response to the change of several key parameters: pH dependence, the pyruvate concentration, the NADH concentration, and amount of LOX applied to the optical fiber end. This dual-enzyme biosensor for pyruvate showed eightfold and fivefold improved sensitivity and DL, respectively, compared to single-enzyme fiber-optic biosensors. In addition, the biosensor works well when large amounts of NADH are added to the sample solution. Thus, it cannot be used in vivo where the levels of NADH and oxygen cannot be controlled. Single-molecule enzymology is the ultimate in ultrasensitive biosensing.75 In an effort to achieve this type of sensitivity, Rissin et al. developed a fiber-optic array–based biosensor capable of single-enzyme molecule detection.76 The activity of single β-galactosidase molecules were monitored in femtoliter sized microwells that were fabricated by etching one end of a fiberoptic array (Figure 2a).34 Each individual optical fiber monitored a reaction in which fluorescent products were built up from single-enzyme
molecule catalysis. The fluorescence intensity of the enzymatic product resorufin was monitored across the array by β-galactosidase catalysis of the substrate resorufin-β-D-galactosidase. The collective monitoring of many single molecules over a large area, combined with Poisson statistics, allowed the enzyme concentration in the bulk solution to be calculated. The number of single β-galactosidase molecules predicted from the Poisson distribution correlated well with the observed number of molecules in the array measurements (Table 1). This sensor was capable of detecting β-galactosidase concentrations of 72 fM. 3.2
Chemiluminescence and Electrogenerated Chemiluminescence Methods
CL is the generation of visible light by the release of energy from a chemical reaction. ECL is a form of CL generated by an electrochemically initiated reaction.77 Both methods offer numerous advantages over traditional optical techniques (fluorescence, absorbance, etc.). The background in CL and ECL is significantly reduced due to the lack of an optical excitation source. As an analytical technique, ECL offers greater control over a reaction because the initiation trigger can be easily modulated. Additionally, ECL typically offers better selectivity and sensitivity over CL. A few recently published CL and ECL fiber-optic array biosensors based on an enzymatic reaction are described here. Navas Diaz et al. developed an enzyme-based fiber-optic biosensor for the detection of hydrogen
Table 1. Digital readout from the arrays(a)
Digital readout of enzyme concentrations Enzyme-to-well ratio 1:5 1 : 10 1 : 20 1 : 40 1 : 80 1 : 100 1 : 200 1 : 500
Concentration −12
7.20 × 10 3.60 × 10−12 1.80 × 10−12 9.00 × 10−13 4.50 × 10−13 3.60 × 10−13 1.80 × 10−13 7.20 × 10−14
Experiments
Actual % active
Poisson % active
t1
t2
t3
Average
Stand dev
18.2 9.5 4.9 2.5 1.2 1.0 0.5 0.2
14.87 11.46 5.57 3.47 1.46 1.10 0.25 0.10
15.44 14.96 4.78 2.80 1.26 1.11 0.42 0.15
14.56 6.92 5.73 1.92 1.31 1.70 0.74 0.09
14.96 11.11 5.36 2.73 1.34 1.30 0.47 0.11
0.45 4.03 0.70 0.78 0.11 0.34 0.25 0.03
[Reprinted with permission Rissin and Walt76 copyright 2006, American Chemical Society.] a The actual percentages of chambers exhibiting activity, in comparison to the expected percentage calculated from the Poisson distribution, are listed for the various concentrations analyzed.
FIBER-OPTIC ARRAY BIOSENSORS
peroxide (H2 O2 ) as well as the phenol derivatives p-iodophenol, p-coumaric acid, and 2-naphthol.78 The enzyme horseradish peroxidase (HRP) was encapsulated in a solgel matrix and immobilized on the distal end of an optical fiber bundle. The reaction of luminol and H2 O2 forms luminol radicals that initiate CL light emission. When the CL enhancers p-iodophenol, p-coumaric acid, and 2-naphthol were added to the luminol–H2 O2 –HRP system enhanced CL occurred.79,80 The DLs for p-iodophenol, p-coumaric acid, and 2-naphthol were reported to be 0.83 µM, 15 nM, and 48 nM,
11
respectively, showing that p-coumaric acid is the best CL enhancer of the luminol–H2 O2 –HRP system. The CL enhancement of the phenol derivatives on H2 O2 detection was established as well. The best CL enhancement was achieved with p-coumaric acid when a DL of 1.6 µM H2 O2 was obtained. Chovin et al. demonstrated the used of a nanoaperture fiber-optic array platform4,81–87 for ECL detection of NADH in the presence of tris(2,2 -bipyridine) ruthenium (II) chloride (Ru(bpy)3 Cl2 ).88 Figure 7 is a schematic
Nanoaperture
Paint Nanoaperture
Paint
Gold ring Gold
(b) Electrical contact (a)
10 µm
1 µm (c)
(d)
Figure 7. Schematic illustration of the nanoaperture array, (a) side view and (b) top view. (c) Scanning electron micrograph of the distal face of the nanoaperture array. (d) High magnification of a single nanoaperture in the array. [Reproduced by permission of Elsevier from Chovin et al.88 ]
12
ARRAY TECHNOLOGIES
illustration showing the nanoaperture fiber-optic array which comprised ∼6000 individual optical fibers. The nanoaperture fiber array was sputtercoated with gold, creating a gold ring that acted as an electrode. Additionally, each nanoaperture confines light within each optical fiber core. The Ru(bpy)3 2+ complex mediates the NADH oxidation, generating ECL light at the distal end of the nanoaperture array by each gold ring (radius ∼200 nm). A fraction of the collected ECL light is then transmitted through the optical fiber nanoaperture array and imaged with a CCD camera. Thus, this optical fiber array platform combines imaging and electrochemical properties. The nanoaperture array was characterized by cyclic voltammetry, showing good electrochemical performance. Stable and reproducible ECL intensities showed linear behavior in the NADH concentration range of 0.5–15 mM.
4 FIBER-OPTIC ARRAYS AS WHOLE-CELL BIOSENSORS
Another trend in fiber-optic array biosensing is employing living cells as biorecognition elements. Whole-cell-based sensing is unique, because live cells generate a specific physiological or genetic signal in response to a wide variety of biologically active compounds or environmental conditions. These biosensors are often considered functional biosensors because they only respond when the analyte of interest can access and bind to its receptor(s) and cause downstream effects. Cell biosensors provide information about bioavailability and biological relevance in the context of a living cell. In contrast, conventional sensors and biosensors only report on binding. Whole-live-cell biosensing has recently found applications for water quality testing,89 clinical diagnostics,90 and metal monitoring.91 A wide variety of mammalian cell types such as neurons, cardiomyocytes, hepatocytes, immune cells, as well as viruses, yeasts, and bacteria have been used to fabricate whole-cell-based biosensors.92–94 Methods for analyzing cell responses include cytometry,95–97 electrochemistry,98,99 capillary electrophoresis,100–102 and various separation techniques.103 These methods are usually invasive, disturbing the cell contents, require complex experimental setups, and are limited to short-term
measurements. To overcome these limitations, new techniques offering small-volume sampling, noninvasiveness, and repetitive measurements of whole cells are needed. Taylor et al. demonstrated that fluorescent dye– encoded NIH 3T3 mouse fibroblast cells can be loaded onto fiber-optic microwell arrays and optically interrogated.104 An optical fiber array containing ∼6750 individual fibers (diameter = 7 µm) was etched, creating a 3-µm-deep microwell. Each microwell can host a single cell that preferentially attaches to the well bottom, eliminating the need for an entrapment matrix. Three distinct lipophilic dyes (PKH26, PKH67, and DiIC18 ) were used to encode the cells to enable them to be distinguished from one another. The locations of the cells within the array were detected by a CCD camera by collecting the fluorescence from the encoding dye upon excitation (Figure 3b). The encoding fluorescent dyes were rapidly incorporated into the cell and exhibited no toxic effects on the cell. In fact, cells retained their viability over 20 h without disturbing the cell contents, making them suitable for practical screening applications. The whole-cell sensor arrays have become an attractive approach for high-throughput screening (HTS) applications.92,105,106 Walt and coworkers used the microwell fiber-optic array platform for simultaneous monitoring of large numbers of individual cells from different strains or cell lines.107–109 The use of the fiber-optic array platform was demonstrated using the yeast (Saccharomyces cerevisiae) two hybrid (Y2H) system107 and genetically modified bacterial (E. coli ) strains108,109 for monitoring single-cell expression. Fluorescence detection was employed to monitor gene expression using lacZ, EGFP, ECFP, and DsRed reporter genes. A Y2H system was constructed by transforming yeast cells with two plasmids in order to detect protein–protein interactions in vivo. If two proteins of interest interact, the reporter gene transcription is enabled, allowing these reporter genes to be detected.110,111 Figure 8 shows a scanning electron micrograph (SEM) image of a single yeast cell and an array of yeast cells in a fiber-optic array.108 Yeast cells were encoded with fluorescent dyes, enabling them to be identified. Fluorescence signals obtained from individual cells of 3 yeast strains showed that 33% of cells in a positive strain, 5% in a negative strain, and none in a wild-type strain
FIBER-OPTIC ARRAY BIOSENSORS
(a)
(b) Figure 8. Loading cells into wells. Scanning electron micrograph (SEM) of (a) an array of yeast cells in microwells and (b) a single yeast cell in a microwell. Each microwell has a diameter of 6 µm. [Reprinted with permission Biran and Walt107 copyright 2002, American Chemical Society.]
exhibited a fluorescence increase over 100 units from the background after 4 h.107 In another study, bacteria were genetically engineered to express reporter genes coding for optically detectable proteins. Three plasmids were used, each encoding for red, green, or cyan fluorescent protein. This genetic encoding scheme creates a unique optical signature for individual cells, allowing positional registration of each cell in the array. Many different sensing cell lines have been constructed for the detection of toxic metals,112–115 aromatic compounds,116 genotoxins,117,118 and drug discovery.119 Biran et al. incorporated an E. coli mercury-sensing strain on the microwell fiber-optic array platform.108 The bacterial strain E. coli RBE27-13 containing lacZ fused to zntA was used. Single-cell lacZ expression was monitored as a function of mercury concentration
13
(0–5 µM). As low as 100 nM Hg2+ was detected within 1 h, demonstrating the possibility of using the system for mercury ion detection. Ikariyama et al. used E. coli pTSN316 strain carrying a xylR-xylS::lux fusion for benzene-related aromatics detection.120 These authors immobilized a genetically modified E. coli strain on a fiberoptic bundle composed of 75 individual fibers (diameter = 0.3 mm). A DL of 5 µM l−1 for mxylene was achieved, showing promise for using this platform for detecting environmental contamination by benzene derivatives. Kuang et al. used a high-density optical fiber array platform for genotoxin detection including the compounds mitomycin C (MMC), N -methylN -nitro-N -nitrosoguanidine, hydrogen peroxide, nalidixic acid, and formaldehyde.109 E. coli cells (strain MG1655) carrying a toxin-sensitive recA promoter fused to a fluorescent gfp reporter gene (recA::gfp) were placed on the etched end of an optical fiber bundle and used as sensing components. This whole-cell biosensor exhibited highly sensitive genotoxic detection during short incubation times (1 ng ml−1 MMC after 90 min). With longer incubation times, it should be possible to detect even lower MMC concentrations. A shelf lifetime of two weeks and active sensing lifetime of more than 6 h were reported. Whole-cell–based fiber-optic microwell arrays have also been used for fundamental cell biology studies such as monitoring gene expression rates and the dynamics of genetic noise.121 A single living cell is a complex system in which many biochemical processes occur simultaneously, exhibiting inherent stochasticity or noise in the process of gene expression. Genetic noise provides information about the structure of gene regulatory circuits122,123 and helps in predicting and designing gene network functions.124–126 Monitoring gene expression allows investigation of genetic noise among individual cells in a cell population.127 Two populations of cells (E. coli strains carrying pSC101 plasmids with lacZ::gfp or recA::gfp fusions) were used to simultaneously monitor genetic activity in single cells over 80 min (Figure 9). Hundreds of individual E. coli cells were employed to study lacZ and recA gene expression kinetics and dynamic changes in cell population noise. Fluorescence signal intensities were plotted for individual recA::gfp cells
ARRAY TECHNOLOGIES 2.4
1.5
2.1
1.4
1.8
1.3
It/I0
It/I0
14
1.5 1.2
1.1
0.9
1.2
0.6
0.9 0
10
20
30
40
50
60
70
80
0
10
20
(b)
Time (min)
1.5
2.1
1.4
1.8
1.3
1.5
30
40
50
60
70
80
60
70
80
Time (min)
2.4
It/I0
It/I0
(a)
1.2
1.2
1.1
0.9
1.2 0.9
0.6 0 (c)
1.2
10
20
30
40
50
60
70
0
80
Time (min)
(d)
10
20
30
40
50
Time (min)
Figure 9. Monitoring lacZ and recA promoter activity in multiple individual cells. Fluorescence signals are expressed as the fluorescence intensity increase (It /I0 ). (a) Individual recA::gfp cells from an array exposed to 10 µg ml−1 MMC. (b) recA::gfp cells in the control array incubated only with medium. (c) Individual lacZ::gfp cells in an array exposed to 5 mM IPTG. (d) lacZ::gfp cells in the control array incubated only with medium. Approximately 200 cells from each array are shown. Fluorescence images from a small portion of the imaging fiber-based cell array corresponding to each experiment are shown in the insets. In each inset, the left panel shows the fluorescence image at time 0 and the right panel shows the image after 80 min. [Reprinted with permission Kuang et al.121 copyright 2004, American Chemical Society.]
in the control array incubated only with M9 medium, for individual recA::gfp cells in the array exposed to M9 medium supplemented with 10 µg ml−1 MMC, and for individual lacZ::gfp cells that were induced with 5 mM isopropyl β-D1-thiogalactopyranoside (IPTG) (Figure 9). Gene expression was measured by acquiring fluorescence images from the array (Figure 9 insets) every 5 min. In addition, gene noise values for both recA and lacZ showed that expression levels and noise of noninduced recA cells were higher than those of lacZ cells (recA noise 40.33 ± 16.4, lacZ noise 8.5 ± 5.8). The fully induced lacZ gene was noisier than the fully induced recA gene, in spite of the more complex gene regulation mechanism of lacZ.
Recently, a nonetched fiber-optic array platform was used to monitor whole-cell and subcellular migration.128 Cell migration analysis is of great importance in cancer proliferation. In many cases, malignant cancer cells migrate from the original tumor site and create metastases in other parts of the body.128 The authors deposited fluorescently encoded fibroblasts onto a polished nonetched optical fiber array.128 Cell migration was monitored with and without exposure of the whole array to different concentrations of the antimigratory drug nocodazole. Fluorescence intensity spikes were recorded over time when cells migrated over an individual fiber. This group showed that when nocodazole was applied, the whole-cell and subcellular migration velocity decreases, causing each
FIBER-OPTIC ARRAY BIOSENSORS
cell to spend more time over an individual fiber. In the whole-cell studies, the cell velocity decreased ∼6 times upon 300 nM nocodazole exposure, and in subcellular studies the cell velocity decreased ∼3 times for the same nocodazole exposure concentration. This array platform can be easily used to detect changes in other cell types by altering the drugs and fluorescent encoding dyes.
5 FIBER-OPTIC ARRAYS AS IMMUNOASSAY BIOSENSORS
Immunoassay biosensors are a class of biosensors that report on the specific binding between an antibody as the biological recognition element and an antigen (analyte). Antibodies possess high specificity and affinity for antigens of interest. An antigen can be a naturally fluorescent compound or can be fluorescently labeled. A primary antibody is typically immobilized on the surface of a transducer.129 Immunoassays are usually performed in one of four modes: direct, competitive, binding inhibition, and sandwich (Figure 10).9,130–132 Figure 10 shows assay formats commonly employed in immunosensing. In a direct assay (Figure 10a), the fluorescence signal is generated when a naturally fluorescent antigen and immobilized antibody form a complex. In this format, the signal is directly proportional to the amount of antigen. The sensitivity of this assay depends on the number of immobilized antibody molecules available for complex formation with the antigen. In a competitive assay format, the unlabeled analyte in the sample and fluorescently labeled antigen compete for immobilized antibody binding sites (Figure 10b). In this assay, the fluorescence intensity of the labeled antigen is measured. The
(a) Direct assay
15
unlabeled analyte blocks binding by the labeled antigen. Thus, the measured signal intensity is inversely related to the concentration of the unlabeled analyte: the higher the fluorescence signal, the lower the analyte concentration. Finally, the sandwich assay is based on the formation of a complex, the “sandwich”, between two highly specific antibodies—a primary antibody that is immobilized on the transducer and a second fluorescently labeled antibody that binds to a second antigenic site (Figure 10c). The signal in sandwich immunoassays is generated only if the analyte binds to both the primary antibody and the fluorescently labeled antibody. This assay is highly specific with the ability to detect specific analytes at low concentrations, enabling the reduction of false positives.133,134 Immunosensing signal transduction can be achieved by a variety of different techniques such as electrochemical, piezoelectric, optical, or calorimetric ones.132,135–138 In recent years considerable research effort has been devoted to the development of fiber-optic immunoassay biosensors for the detection of specific analytes,16,116,131,139–142 harmful food-borne pathogens,17,139,143 clinically relevant drugs,144 proteins,18,133,145–148 and viruses.135,149 Several studies have focused on the optical fiber probe immunoassay biosensors,150–152 and some of them have focused on the development of the optical fiber array immunoassay biosensors.153–156 The following section is a review of the recent advances in immunoassaybased biosensing on optical fiber array platforms. Szurdoki et al. used an etched optical fiber bundle (Figure 2a) to simultaneously detect the clinically important drugs digoxin and theophylline.144 Two sets of amine-functionalized microspheres (3.15 µm in diameter) were subjected to different encoding dyes and attachment strategies.
(b) Competitive assay
Antigen (analyte)
Labeled antibody
Antibody
Signal transducer
(c) Sandwich assay Labeled antigen (analyte)
Figure 10. Assay formats commonly employed in immunosensors: (a) direct assay, (b) competitive assay, and (c) sandwich assay.
ARRAY TECHNOLOGIES 100
lgA sensors Lactoferrin sensors
80 Net signal
The amine-functionalized microspheres for the theophylline assay were encoded with BODIPY 493/503 dye. These encoded microspheres were activated with glutaraldehyde and derivatized with polyethyleneimine to increase the number of antigen binding sites on the microspheres. The functionalized microspheres were then coated with a theophylline–casein conjugate, and treated with casein to minimize nonspecific binding. Microspheres for the digoxin assay were encoded with amine reactive Cy 5.5 monofunctional dye. Digoxin was attached to microspheres by the periodate/borohydrate method and treated with casein to minimize nonspecific binding. The competitive immunoassay was performed with HRP-labeled polyclonal rabbit antitheophylline or antidigoxin in the presence of the desired analyte. The generated fluorescence signal was amplified by a catalyzed reporter deposition method.157–159 This fiber-optic array platform allowed a semiquantitative analysis and provided a proof of principle. Microspheres analyzed on microscope slides showed high sensitivity for both assays. The IC50 was ∼8 ppb for theophylline, and ∼0.5 ppb for digoxin. Recently, Rissin et al. used a high-density optical fiber array–based duplexed sandwich immunoassay to detect two salivary immune system proteins: immunoglobulin A (IgA) and lactoferrin.160 Methylstyrene/divinylbenzene microspheres with unique optical bar codes were functionalized with monoclonal primary antibodies to IgA and lactoferrin. After loading the microspheres onto an optical fiber array, incubation with 10 µg ml−1 lactoferrin and 100 µg ml−1 IgA fluorescently labeled secondary monoclonal antibodies was performed, followed by rinsing the unbound antibodies with blocking buffer. The custom-built epifluorescence imaging system shown in Figure 3(b) was used to acquire all fluorescence images. The working concentration range of IgA was between 700 pM and 100 nM, while the working concentration range for lactoferrin was between 385 pM and 10 nM (Figure 11). Lactoferrin exhibited a smaller concentration range compared to IgA, probably due to the higher specificity of lactoferrin antibodies for their target. This fiberoptic array showed enough specificity for possible useful measurements on diluted human saliva samples.
60 40 20 0 −20
0
100
50
150
200
250
Concentration (nM)
(a) 100 80 Net signal
16
60 lgA sensors Lactoferrin sensors
40 20 0 −20
(b)
0
5
10
15
20
25
30
Concentration (nM)
Figure 11. Dose–response curve for (a) IgA detection and (b) lactoferrin detection showing probe specificity and working concentration range. [Reprinted with permission Rissin and Walt160 copyright 2006, Elsevier.]
6 CONCLUSIONS
Optical fiber array technology has advanced substantially in the last decade. The marriage of this detection technology with multiplexed specific and sensitive assays results in a powerful, costeffective detection system for genotyping, gene expression studies, pharmaceutical research, cellbased biosensing, enzyme, and immunoassay highcontent analysis. An optical fiber microsphere array platform generates thousands of signals simultaneously, allowing for the identification of a specific oligonucleotide sequence on every microsphere in the array, offering multiplexed genotyping, and gene expression analysis with the potential for whole-genome screening. The ability to reuse DNA arrays is a major advantage of this platform. Its small dimensions enable small sample volumes to be used, making it amenable for integration with a portable instrument.
FIBER-OPTIC ARRAY BIOSENSORS
Enzyme-based fiber-optic array biosensors are the most extensively used among the biosensors described in this chapter. These biosensors typically employ enzymes in either pure form or contained on or within a biological matrix such as a cell or vesicle. Enzyme-based fiber-optic arrays have been described for the detection of freshwater pollutants, organophosphorous pesticides, and neurotransmitters. Microsphere-based fiber-optic arrays demonstrated the ability to image the localized chemical releases. Single-molecule enzymology studies on optical fiber bundles are becoming another attractive area toward ultrasensitive biosensing, revealing molecular behaviors at the single-molecule level. The development of versatile whole-cell fiberoptic arrays provides a means to perform screening of large populations of cells, allowing environmental, toxicological, gene expression kinetics, single-cell genetic noise monitoring, genotoxin monitoring, and drug discovery. This technology demonstrates significant potential for subcellular imaging, and multiorganelle interactions. The specificity of antibodies covalently attached to the fiber-optic array platform makes them suitable for reliable drug detection, food quality control, and disease diagnostics. Antibodies can be used for the recognition of an antigen from complex samples such as blood, urine, or saliva. Despite improvements in immunoassay development, improvements in antibody production and in understanding immunoreaction mechanisms and kinetics are required.
ACKNOWLEDGMENTS
The DOE, NIH, NSF, NCI, and DARPA supported the work discussed in this chapter.
REFERENCES 1. D. R. Thevenot, K. Toth, R. A. Durst, and G. S. Wilson, Electrochemical biosensors: recommended definitions and classification. Biosensors and Bioelectronics, 2001, 16, 121–131. 2. M. Mehrvar and M. Abdi, Recent developments, characteristics, and potential applications of electrochemical biosensors. Analytical Sciences, 2004, 20, 1113–1126.
17
3. M. Mehrvar, C. Bis, J. M. Scharer, M. Moo-Young, and J. H. Luong, Fiber-optic biosensors–trends and advances. Analytical Sciences, 2000, 16, 677–692. 4. J. M. Tam, S. Szunerits, and D. R. Watt, Optical fibers for nanodevices. Encyclopedia of Nanoscience and Nanotechnology, 2004, 8, 167–177. 5. D. R. Walt, Imaging optical sensor arrays. Current Opinion in Chemical Biology, 2002, 6, 689–695. 6. D. R. Walt, Fiber optic imaging sensors. Accounts of Chemical Research, 1998, 31, 267–278. 7. D. J. Monk and D. R. Walt, Optical fiber-based biosensors. Analytical and Bioanalytical Chemistry, 2004, 379, 931–945. 8. B. Kuswandi, R. Andres, and R. Narayanaswamy, Optical fibre biosensors based on immobilised enzymes. The Analyst, 2001, 126, 1469–1491. 9. M. D. Marazuela and M. C. Moreno-Bondi, Fiber-optic biosensors–an overview. Analytical and Bioanalytical Chemistry, 2002, 372, 664–682. 10. J. R. Epstein and D. R. Walt, Fluorescence-based fiber optic arrays: a universal platform for sensing. Chemical Society Reviews, 2003, 32, 203–214. 11. J. R. Epstein, A. P. K. Leung, K.-H. Lee, and D. R. Walt, High-density, microsphere-based fiber optic DNA microarrays. Biosensors and Bioelectronics, 2003, 18, 541–546. 12. D. R. Walt, Chemistry: miniature analytical methods for medical diagnostics. Science, 2005, 308, 217–219. 13. P. A. E. Piunno and U. J. Krull, Trends in the development of nucleic acid biosensors for medical diagnostics. Analytical and Bioanalytical Chemistry, 2005, 381, 1004–1011. 14. X. J. Liu and W. H. Tan, Development of an optical fiber lactate sensor. Mikrochimica Acta, 1999, 131, 129–135. 15. M. Bibikova, Z. Lin, L. Zhou, E. Chudin, E. W. Garcia, B. Wu, D. Doucet, N. J. Thomas, Y. Wang, E. Vollmer, T. Goldmann, C. Seifart, W. Jiang, D. L. Barker, M. S. Chee, J. Floros, and J. B. Fan, High-throughput DNA methylation profiling using universal bead arrays. Genome Research, 2006, 16, 383–393. 16. S. Ko and S. A. Grant, A novel fret-based optical fiber biosensor for rapid detection of Salmonella typhimurium. Biosensors and Bioelectronics, 2006, 21, 1283–1290. 17. D. R. DeMarco, E. W. Saaski, D. A. McCrae, and D. V. Lim, Rapid detection of Escherichia Coli O157:H7 in ground beef using a fiber-optic biosensor. Journal of Food Protection, 1999, 62, 711–716. 18. D. Yu, B. Blankert, J. C. Vire, and J.-M. Kauffmann, Biosensors in drug discovery and drug analysis. Analytical Letters, 2005, 38, 1687–1701. 19. P. Janssen, B. Audit, I. Cases, N. Darzentas, L. Goldovsky, V. Kunin, N. Lopez-Bigas, J. M. PeregrinAlvarez, J. B. Pereira-Leal, S. Tsoka, and C. A. Ouzounis, Beyond 100 genomes. Genome Biology, 2003, 4, 402–404. 20. P. Janssen, L. Goldovsky, V. Kunin, N. Darzentas, and C. A. Ouzounis, Genome coverage, literally speaking. EMBO Reports, 2005, 6, 397–399. 21. K. L. Brogan and D. R. Walt, Optical fiber-based sensors: application to chemical biology. Current Opinion in Chemical Biology, 2005, 9, 494–500.
18
ARRAY TECHNOLOGIES
22. A. Almadidy, J. Watterson, P. A. E. Piunno, S. Raha, I. V. Foulds, P. A. Horgen, A. Castle, and U. Krull, Direct selective detection of genomic DNA from coliform using a fiber optic biosensor. Analytica Chimica Acta, 2002, 461, 37–47. 23. J. H. Watterson, S. Raha, C. C. Kotoris, C. C. Wust, F. Gharabaghi, S. C. Jantzi, N. K. Haynes, N. H. Gendron, U. J. Krull, A. E. Mackenzie, and P. A. E. Piunno, Rapid detection of single nucleotide polymorphisms associated with spinal muscular atrophy by use of a reusable fiber-optic biosensor. Nucleic Acids Research, 2004, 32, e18-1–e18-9. 24. J. B. Fan, A. Oliphant, R. Shen, B. G. Kermani, F. Garcla, K. L. Gunderson, M. Hansen, F. Steemers, S. L. Butler, P. Deloukas, L. Galver, S. Hunt, C. McBride, M. Bibikova, T. Rubano, J. Chen, E. Wickham, D. Doucet, W. Chang, D. Campbell, B. Zhang, S. Kruglyak, D. Bentley, J. Haas, P. Rigault, L. Zhou, J. Stuelpnagel, and M. S. Chee, Highly parallel SNP genotyping. Cold Spring Harbor Symposia on Quantitative Biology, 2003, 68, 69–78. 25. B. G. Healey, R. S. Matson, and D. R. Walt, Fiberoptic DNA sensor array capable of detecting point mutations. Analytical Biochemistry, 1997, 251, 270–279. 26. M. Bibikova, D. Talantov, E. Chudin, J. M. Yeakley, J. Chen, D. Doucet, E. Wickham, D. Atkins, D. Barker, M. Chee, Y. Wang, and J.-B. Fan, Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays. American Journal of Pathology, 2004, 165, 1799–1807. 27. J.-B. Fan, J. M. Yeakley, M. Bibikova, E. Chudin, E. Wickham, J. Chen, D. Doucet, P. Rigault, B. Zhang, R. Shen, C. McBride, H.-R. Li, X.-D. Fu, A. Oliphant, D. L. Barker, and M. S. Chee, A versatile assay for highthroughput gene expression profiling on universal array matrices. Genome Research, 2004, 14, 878–885. 28. K. Kuhn, S. C. Baker, E. Chudin, M.-H. Lieu, S. Oeser, H. Bennett, P. Rigault, D. Barker, T. K. McDaniel, and M. S. Chee, A novel, high-performance random array platform for quantitative gene expression profiling. Genome Research, 2004, 14, 2347–2356. 29. F. J. Steemers, W. H. Chang, G. Lee, D. L. Barker, R. Shen, and K. L. Gunderson, Whole-genome genotyping with the single-base extension assay. Nature Methods, 2006, 3, 31–33. 30. Illumina Homepage. (2006). Information on the SNP genotyping and whole-genome genotyping; http://www. illumina.com/products/snp/whole genome genotyping. ilmn. 31. A. Almadidy, J. Watterson, P. A. E. Piunno, I. V. Foulds, P. A. Horgen, and U. Krull, A fiber-optic biosensor for detection of microbial contamination. Canadian Journal of Chemistry, 2003, 81, 339–349. 32. J. H. Watterson, P. A. E. Piunno, C. C. Wust, S. Raha, and U. J. Krull, Influences of non-selective interactions of nucleic acids on response rates of nucleic acid fiber optic biosensors. Fresenius Journal of Analytical Chemistry, 2001, 369, 601–608. 33. J. Zeng, A. Almadidy, J. Watterson, and U. J. Krull, Interfacial hybridization kinetics of oligonucleotides immobilized onto fused silica surfaces. Sensors and Actuators, B: Chemical, 2003, B90, 68–75.
34. P. Pantano and D. R. Walt, Ordered nanowell arrays. Chemistry of Materials, 1996, 8, 2832–2835. 35. D. D. Bernhard, S. Mall, and P. Pantano, Fabrication and characterization of microwell array chemical sensors. Analytical Chemistry, 2001, 73, 2484–2490. 36. D. R. Walt, Techview: molecular biology: bead-based fiber-optic arrays. Science, 2000, 287, 451–452. 37. K. L. Michael, L. C. Taylor, S. L. Schultz, and D. R. Walt, Randomly ordered addressable high-density optical sensor arrays. Analytical Chemistry, 1998, 70, 1242–1248. 38. G. Steinberg, K. Stromsborg, L. Thomas, D. Baker, and C. Zhao, Strategies for covalent attachment of DNA to beads. Biopolymers, 2004, 73, 597–605. 39. J. R. Epstein, J. A. Ferguson, K.-H. Lee, and D. R. Walt, Combinatorial decoding: an approach for universal DNA array fabrication. Journal of the American Chemical Society, 2003, 125, 13753–13759. 40. J. M. Tam, L. Song, and D. R. Walt, Fabrication and optical characterization of imaging fiber-based nanoarrays. Talanta, 2005, 67, 498–502. 41. J. R. Epstein, I. Biran, and D. R. Walt, Fluorescencebased nucleic acid detection and microarrays. Analytica Chimica Acta, 2002, 469, 3–36. 42. K. L. Gunderson, S. Kruglyak, M. S. Graige, F. Garcia, B. G. Kermani, C. Zhao, D. Che, T. Dickinson, E. Wickham, J. Bierle, D. Doucet, M. Milewski, R. Yang, C. Siegmund, J. Haas, L. Zhou, A. Oliphant, J.-B. Fan, S. Barnard, and M. S. Chee, Decoding randomly ordered DNA arrays. Genome Research, 2004, 14, 870–877. 43. R. Shen, J.-B. Fan, D. Campbell, W. Chang, J. Chen, D. Doucet, J. Yeakley, M. Bibikova, E. Wickham Garcia, and C. McBride, High-throughput Snp genotyping on universal bead arrays. Mutation Research-Fundamental and Molecular Mechanisms of Mutagenesis, 2005, 573, 70–82. 44. K. L. Gunderson, F. J. Steemers, G. Lee, L. G. Mendoza, and M. S. Chee, A genome-wide scalable SNP genotyping assay using microarray technology. Nature Genetics, 2005, 37, 549–554. 45. J. R. Epstein, M. Lee, and D. R. Walt, High-density fiber-optic genosensor microsphere array capable of zeptomole detection limits. Analytical Chemistry, 2002, 74, 1836–1840. 46. J. A. Ferguson, F. J. Steemers, and D. R. Walt, Highdensity fiber-optic DNA random microsphere array. Analytical Chemistry, 2000, 72, 5618–5624. 47. J. M. Yeakley, J.-B. Fan, D. Doucet, L. Luo, E. Wickham, Z. Ye, M. S. Chee, and X.-D. Fu, Profiling alternative splicing on fiber-optic arrays. Nature Biotechnology, 2002, 20, 353–358. 48. F. J. Steemers, J. A. Ferguson, and D. R. Walt, Screening unlabeled DNA targets with randomly ordered fiber-optic gene arrays. Nature Biotechnology, 2000, 18, 91–94. 49. M. Lee and D. R. Walt, A fiber-optic microarray biosensor using aptamers as receptors. Analytical Biochemistry, 2000, 282, 142–146. 50. M. Bowden, L. Song, and D. R. Walt, Development of a microfluidic platform with an optical imaging microarray capable of attomolar target DNA detection. Analytical Chemistry, 2005, 77, 5583–5588.
FIBER-OPTIC ARRAY BIOSENSORS 51. D. R. Walt and D. R. Franz, Biological warfare detection. Analytical Chemistry, 2000, 72, 738A–746A. 52. L. Song, S. Ahn, and D. R. Walt, Detecting biological warfare agents. Emerging Infectious Diseases, 2005, 11, 1629–1632. 53. L. Song, S. Ahn, and D. R. Walt, Fiber-optic microsphere-based arrays for multiplexed biological warfare agent detection. Analytical Chemistry, 2006, 78, 1023–1033. 54. J. R. E. Shepard, Y. Danin-Poleg, Y. Kashi, and D. R. Walt, Array-based binary analysis for bacterial typing. Analytical Chemistry, 2005, 77, 319–326. 55. K. V. Holmes and L. Enjuanes, Virology: the sars coronavirus: a postgenomic era. Science, 2003, 300, 1377–1378. 56. M. Enserink, Infectious disease: west Nile’s surprisingly swift continental sweep. Science, 2002, 297, 1988–1989. 57. R. R. Colwell, Global climate and infectious disease: the cholera paradigm. Science, 1996, 274, 2025–2031. 58. C. C. Stuart, Nucleotide sequence-based typing of bacteria and the impact of automation. BioEssays, 2002, 24, 858–862. 59. M. C. J. Maiden, J. A. Bygraves, E. Feil, G. Morelli, J. E. Russell, R. Urwin, Q. Zhang, J. Zhou, K. Zurth, D. A. Caugant, I. M. Feavers, M. Achtman, and B. G. Spratt, Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95, 3140–3145. 60. E. R. Packard, R. Parton, J. G. Coote, and N. K. Fry, Sequence variation and conservation in virulencerelated genes of bordetella pertussis isolates from the UK. Journal of Medical Microbiology, 2004, 53, 355–365. 61. V. N. Kristensen, D. Kelefiotis, T. Kristensen, and A.-L. Borresen-Dale, High-throughput methods for detection of genetic variation. BioTechniques, 2001, 30, 318–332. 62. X. Wang and U. J. Krull, Tethered thiazole orange intercalating dye for development of fiber-optic nucleic acid biosensors. Analytica Chimica Acta, 2002, 470, 57–70. 63. X. Wang and U. J. Krull, A self-contained fluorescent fiber optic DNA biosensor. Journal of Materials Chemistry, 2005, 15, 2801–2809. 64. X. Wang and U. J. Krull, Synthesis and fluorescence studies of thiazole orange tethered onto oligonucleotide: development of a self-contained DNA biosensor on a fiber optic surface. Bioorganic and Medicinal Chemistry Letters, 2005, 15, 1725–1729. 65. O. S. Wolfbeis, Fiber-optic chemical sensors and biosensors. Analytical Chemistry, 2002, 74, 2663–2677. 66. I. del Villar, I. R. Matias, F. J. Arregui, and R. O. Claus, Fiber-optic hydrogen peroxide nanosensor. IEEE Sensors Journal, 2005, 5, 365–371. 67. I. Del Villar, I. R. Matias, F. J. Arregui, J. Echeverria, and R. O. Claus, Strategies for fabrication of hydrogen peroxide sensors based on electrostatic self-assembly (ESA) method. Sensors and Actuators, B: Chemical, 2005, B108, 751–757. 68. A. Kishen, M. S. John, C. S. Lim, and A. Asundi, A fiber optic biosensor (FOBS) to monitor mutans streptococci
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
19
in human saliva. Biosensors and Bioelectronics, 2003, 18, 1371–1378. C. Durrieu, C. Chouteau, L. Barthet, J.-M. Chovelon, and C. Tran-Minh, A Bi-enzymatic whole-cell algal biosensor for monitoring waste water pollutants. Analytical Letters, 2004, 37, 1589–1599. C. Durrieu and C. Tran-Minh, Optical algal biosensor using alkaline phosphatase for determination of heavy metals. Ecotoxicology and Environmental Safety, 2002, 51, 206–209. R. A. Doong and H. C. Tsai, Immobilization and characterization of sol-gel-encapsulated acetylcholinesterase fiber-optic biosensor. Analytica Chimica Acta, 2001, 434, 239–246. S. G. Ignatov, J. A. Ferguson, and D. R. Walt, A fiber-optic lactate sensor based on bacterial cytoplasmic membranes. Biosensors and Bioelectronics, 2001, 16, 109–113. J. P. Issberner, C. L. Schauer, B. A. Trimmer, and D. R. Walt, Combined imaging and chemical sensing of l-glutamate release from the foregut plexus of the lepidopteran, manduca sexta. Journal of Neuroscience Methods, 2002, 120, 1–10. W. Zhang, H. Chang, and G. A. Rechnitz, Dual-enzyme fiber optic biosensor for pyruvate. Analytica Chimica Acta, 1997, 350, 59–65. Y. Rondelez, G. Tresset, K. V. Tabata, H. Arata, H. Fujita, S. Takeuchi, and H. Noji, Microfabricated arrays of femtoliter chambers allow single molecule enzymology. Nature Biotechnology, 2005, 23, 361–365. D. M. Rissin and D. R. Walt, Digital concentration readout of single enzyme molecules using femtoliter arrays and poisson statistics. Nano Letters, 2006, 6, 520–523. K. A. Fahnrich, M. Pravda, and G. G. Guilbault, Recent applications of electrogenerated chemiluminescence in chemical analysis. Talanta, 2001, 54, 531–559. M. C. Ramos, M. C. Torijas, and A. N. Diaz, Enhanced chemiluminescence biosensor for the determination of phenolic compounds and hydrogen peroxide. Sensors and Actuators, B: Chemical, 2001, B73, 71–75. A. Navas Diaz, F. Garcia Sanchez, and J. A. Gonzalez Garcia, Phenol derivatives as enhancers and inhibitors of luminol-H2o2-horseradish peroxidase chemiluminescence. Journal of Bioluminescence and Chemiluminescence, 1998, 13, 75–84. A. Navas Diaz, M. C. Ramos Peinado, and M. C. Torijas Minguez, Sol-gel horseradish peroxidase biosensor for hydrogen peroxide detection by chemiluminescence. Analytica Chimica Acta, 1998, 363, 221–227. S. Szunerits, J. M. Tam, L. Thouin, C. Amatore, and D. R. Walt, Spatially resolved electrochemiluminescence on an array of electrode tips. Analytical Chemistry, 2003, 75, 4382–4388. S. Szunerits and D. R. Walt, The use of optical fiber bundles combined with electrochemistry for chemical imaging. Chemphyschem, 2003, 4, 186–192. Y. H. Liu, T. H. Dam, and P. Pantano, A Ph-sensitive nanotip array imaging sensor. Analytica Chimica Acta, 2000, 419, 215–225. A. Chovin, P. Garrigue, G. Pecastaings, H. Saadaoui, I. Manek-Hoenninger, and N. Sojic, Microarrays of
20
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
99.
100.
ARRAY TECHNOLOGIES near-field optical probes with adjustable dimensions. Ultramicroscopy, 2006, 106, 57–65. A. Chovin, P. Garrigue, L. Servant, and N. Sojic, Electrochemical modulation of remote fluorescence imaging at an ordered opto-electrochemical nanoaperture array. Chemphyschem, 2004, 5, 1125–1132. A. Chovin, P. Garrigue, and N. Sojic, Electrochemiluminescent detection of hydrogen peroxide with an imaging sensor array. Electrochimica Acta, 2004, 49, 3751–3757. A. Chovin, P. Garrigue, P. Vinatier, and N. Sojic, Development of an ordered array of optoelectrochemical individually readable sensors with submicrometer dimensions: application to remote electrochemiluminescence imaging. Analytical Chemistry, 2004, 76, 357–364. A. Chovin, P. Garrigue, and N. Sojic, Remote NADH imaging through an ordered array of electrochemiluminescent nanoapertures. Bioelectrochemistry, 2006, 69, 25–33. K. D. Hughes, D. L. Bittner, and G. A. Olsen, New fluorescence tools for investigating enzyme activity. Analytica Chimica Acta, 1995, 307, 393–402. N. Zurgil, S. Gerbat, P. Langevitzh, M. Tishler, M. Ehrenfeld, and Y. Shoenfeld, Intracellular fluorescence polarization measurements by the cellscan system: detection of cellular activity in autoimmune disorders. Israel Journal of Medical Sciences, 1997, 33, 273–279. S. Ramanathan, W. Shi, B. P. Rosen, and S. Daunert, Sensing antimonite and arsenite at the subattomole level with genetically engineered bioluminescent bacteria. Analytical Chemistry, 1997, 69, 3380–3384. S. Belkin, Microbial whole-cell sensing systems of environmental pollutants. Current Opinion in Microbiology, 2003, 6, 206–212. A. Baeumner, Biosensors for environmental pollutants and food contaminants. Analytical and Bioanalytical Chemistry, 2003, 377, 434–445. A. M. Karlsson, K. Bjuhr, M. Testorf, P. A. Oberg, E. Lerner, I. Lundstrom, and S. P. S. Svensson, Biosensing of opioids using frog melanophores. Biosensors and Bioelectronics, 2002, 17, 331–335. L. J. Dietz, R. S. Dubrow, B. S. Manian, and N. L. Sizto, Volumetric capillary cytometry: a new method for absolute cell enumeration. Cytometry, 1996, 23, 177–186. H. N. Zhou, A. Xu, J. A. Gillispie, C. A. Waldren, and T. K. Hei, Quantification of Cd59(-) mutants in humanhamster hybrid (a(L)) cells by flow cytometry. Mutation Research-Fundamental and Molecular Mechanisms of Mutagenesis, 2006, 594, 113–119. M. Burmolle, L. H. Hansen, and S. J. Sorensen, Use of a whole-cell biosensor and flow cytometry to detect AHL production by an indigenous soil community during decomposition of litter. Microbial Ecology, 2005, 50, 221–229. L. Huang and R. T. Kennedy, Exploring single-cell dynamcis using chemically-modified microelectrodes. Trends in Analytical Chemistry, 1995, 14, 158–163. K. A. Marx, Quartz crystal microbalance: a useful tool for studying thin polymer films and complex biomolecular systems at the solution-surface interface. Biomacromolecules, 2003, 4, 1099–1120. M. Moini and H. L. Huang, Application of capillary electrophoresis/electrospray ionization-mass spectrometry to
101.
102.
103.
104.
105.
106.
107.
108.
109.
110.
111.
112.
113.
114.
115.
116.
subcellular proteomics of escherichia coli leribosomal proteins. Electrophoresis, 2004, 25, 1981–1987. F. E. Regnier, D. H. Patterson, and B. J. Harmon, Electrophoretically-mediated microanalysis (EMMA). Trends in Analytical Chemistry, 1995, 14, 177–181. W. Wang, S. B. Han, and W. R. Jin, Determination of lactate dehydrogenase isoenzymes in single rat glioma cells by capillary electrophoresis with electrochemical detection. Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences, 2006, 831, 57–62. J. B. Shear, H. A. Fishman, D. Garigan, R. N. Zare, N. L. Allbritton, and R. H. Scheller, Single cells as biosensors for chemical separations. Science, 1995, 267, 74–77. L. C. Taylor and D. R. Walt, Application of high-density optical microwell arrays in a live-cell biosensing system. Analytical Biochemistry, 2000, 278, 132–142. F. Becker, N. Costa-Rold´an, C. Kaufmann, U. Hanke, C. Degenhart, S. Baumann, W. Wallner, A. Huber, S. Dedier, S. Dill, S. Meier-Ewert, N. Kley, K. Murthi, C. Smith, J. Come, D. Kinsman, M. Hediger, N. Bockovich, and A. F. Kluge, A three-hybrid approach to scanning the proteome for targets of small molecule kinase inhibitors. Chemistry and Biology, 2004, 11, 211–223. D. Vanhecke and M. Janitz, High-throughput gene silencing using cell arrays. Oncogene, 2004, 23, 8353–8358. I. Biran and D. R. Walt, Optical imaging fiber-based single live cell arrays: a high-density cell assay platform. Analytical Chemistry, 2002, 74, 3046–3054. I. Biran, D. M. Rissin, E. Z. Ron, and D. R. Walt, Optical imaging fiber-based live bacterial cell array biosensor. Analytical Biochemistry, 2003, 315, 106–113. Y. Kuang, I. Biran, and D. R. Walt, Living bacterial cell array for genotoxin monitoring. Analytical Chemistry, 2004, 76, 2902–2909. S. Fields and O. K. Song, A novel genetic system to detect protein protein interactions. Nature, 1989, 340, 245–246. P.-O. Vidalain, M. Boxem, H. Ge, S. Li, and M. Vidal, Increasing specificity in high-throughput yeast twohybrid experiments. Methods, 2004, 32, 363–370. K. Hakkila, P. Leskinen, T. Green, R. Marks, A. Ivask, and M. Virta, Detection of bioavailable heavy metals in eilatox-oregon samples using whole-cell luminescent bacterial sensors in suspension or immobilized onto fibreoptic tips. Journal of Applied Toxicology, 2004, 24, 333–342. S. Leth, S. Maltoni, R. Simkus, B. Mattiasson, P. Corbisier, I. Klimant, O. S. Wolfbeis, and E. Cs¨oregi, Engineered bacteria based biosensors for monitoring bioavailable heavy metals. Electroanalysis, 2002, 14, 35–42. K. B. Riether, M. A. Dollard, and P. Billard, Assessment of heavy metal bioavailability using Escherichia Coli Zntap::lux and copap::lux-based biosensors. Applied Microbiology and Biotechnology, 2001, 57, 712–716. I. Biran, R. Babai, K. Levcov, J. Rishpon, and E. Z. Ron, Online and in situ monitoring of environmental pollutants: electrochemical biosensing of cadmium. Environmental Microbiology, 2000, 2, 285–290. A. A. Wise and C. R. Kuske, Generation of novel bacterial regulatory proteins that detect priority pollutant
FIBER-OPTIC ARRAY BIOSENSORS
117.
118.
119.
120.
121.
122.
123.
124.
125. 126.
127.
128.
129.
130.
131.
132.
phenols. Applied and Environmental Microbiology, 2000, 66, 163–169. Y. Davidov, R. Rozen, S. Belkin, D. R. Smulski, T. K. Van Dyk, A. C. Vollmer, D. A. Elsemore, and R. A. LaRossa, Improved bacterial SOS promoter::lux fusions for genotoxicity detection. Mutation Research-Genetic Toxicology and Environmental Mutagenesis, 2000, 466, 97–107. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Bioluminescent whole cell optical fiber sensor to genotoxicants: system optimization. Sensors and Actuators, B: Chemical, 2001, 74, 18–26. Y. Kuang and D. R. Walt, Monitoring “promiscuous” drug effects on single cells of multiple cell types. Analytical Biochemistry, 2005, 345, 320–325. Y. Ikariyama, S. Nishiguchi, T. Koyama, E. Kobatake, M. Aizawa, M. Tsuda, and T. Nakazawa, Fiber-optic-based biomonitoring of benzene derivatives by recombinant E. Coli bearing luciferase gene-fused TOL-plasmid immobilized on the fiber-optic end. Analytical Chemistry, 1997, 69, 2600–2605. Y. Kuang, I. Biran, and D. R. Walt, Simultaneously monitoring gene expression kinetics and genetic noise in single cells by optical well arrays. Analytical Chemistry, 2004, 76, 6282–6286. M. D. Levin, Noise in gene expression as the source of non-genetic individuality in the chemotactic response of Escherichia Coli. FEBS Letters, 2003, 550, 135–138. J. M. G. Vilar, H. Y. Kueh, N. Barkai, and S. Leibler, Mechanisms of noise-resistance in genetic oscillators. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99, 5988–5992. F. J. Isaacs, J. Hasty, C. R. Cantor, and J. J. Collins, Prediction and measurement of an autoregulatory genetic module. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100, 7714–7719. J. Paulsson, Summing up the noise in gene networks. Nature, 2004, 427, 415–418. M. L. Simpson, C. D. Cox, and G. S. Sayler, Frequency domain analysis of noise in autoregulated gene circuits. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100, 4551–4556. P. Cluzel, M. Surette, and S. Leibler, An ultrasensitive bacterial motor revealed by monitoring signaling proteins in single cells. Science, 2000, 287, 1652–1655. C. DiCesare, I. Biran, and D. R. Walt, Individual cell migration analysis using fiber-optic bundles. Analytical and Bioanalytical Chemistry, 2005, 382, 37–43. W. Schramm, S. H. Paek, and G. Voss, Strategies for the immobilization of antibodies. ImmunoMethods, 1993, 3, 93–103. M. C. Moreno-Bondi, J. Mobley, J. P. Alarie, and T. VoDinh, Antibody-based biosensor for breast cancer with ultrasonic regeneration. Journal of Biomedical Optics, 2000, 5, 350–354. T. Vo Dinh, M. J. Sepaniak, G. D. Griffin, and J. P. Alarie, Immunosensors: principles and applications. ImmunoMethods, 1993, 3, 85–92. J. Cruz Helder, C. Rosa Carla, and G. Oliva Abel, Immunosensors for diagnostic applications. Parasitology Research, 2002, 88, S4–S7.
21
133. D. M. Rissin and D. R. Walt, Duplexed sandwich immunoassays on a fiber-optic microarray. Analytica Chimica Acta, In press. 134. G. MacBeath, Protein microarrays and proteomics. Nature Genetics, 2002, 32, 526–532. 135. S. Herrmann, B. Leshem, S. Landes, B. Rager-Zisman, and R. S. Marks, Chemiluminescent optical fiber immunosensor for the detection of anti-west nile virus igg. Talanta, 2005, 66, 6–14. 136. M. Liu, Q. X. Li, and G. A. Rechnitz, Gold electrode modification with thiolated hapten for the design of amperometric and piezoelectric immunosensors. Electroanalysis, 2000, 12, 21–26. 137. G. Sakai, T. Saiki, T. Uda, N. Miura, and N. Yamazoe, Evaluation of binding of human serum albumin (HSA) to monoclonal and polyclonal antibody by means of piezoelectric immunosensing technique. Sensors and Actuators, B: Chemical, 1997, B42, 89–94. 138. E. Zacco, M. I. Pividori, X. Llopis, M. del Valle, and S. Alegret, Renewable protein a modified graphiteepoxy composite for electrochemical immunosensing. Journal of Immunological Methods, 2004, 286, 35–46. 139. S. A. Grant, M. E. Pierce, D. J. Lichlyter, and D. A. Grant, Effects of immobilization on a fret immunosensor for the detection of myocardial infarction. Analytical and Bioanalytical Chemistry, 2005, 381, 1012–1018. 140. L. L. E. Salins, S. K. Deo, and S. Daunert, Phosphate binding protein as the biorecognition element in a biosensor for phosphate. Sensors and Actuators, B: Chemical, 2004, B97, 81–89. 141. R. S. Marks, A. Novoa, D. Thomassey, and S. Cosnier, An innovative strategy for immobilization of receptor proteins on to an optical fiber by use of poly(pyrrolebiotin). Analytical and Bioanalytical Chemistry, 2002, 374, 1056–1063. 142. T. Konry, A. Novoa, S. Cosnier, and R. S. Marks, Development of an “electroptode” immunosensor: indium tin oxide-coated optical fiber tips conjugated with an electropolymerized thin film with conjugated cholera toxin B subunit. Analytical Chemistry, 2003, 75, 2633–2639. 143. T. Geng, M. T. Morgan, and A. K. Bhunia, Detection of low levels of listeria monocytogenes cells by using a fiber-optic immunosensor. Applied and Environmental Microbiology, 2004, 70, 6138–6146. 144. F. Szurdoki, K. L. Michael, and D. R. Walt, A duplexed microsphere-based fluorescent immunoassay. Analytical Biochemistry, 2001, 291, 219–228. 145. I. Balcer Heath, J. Kwon Hyun, and A. Kang Kyung, Assay procedure optimization of a rapid, reusable protein C immunosensor for physiological samples. Annals of Biomedical Engineering, 2002, 30, 141–147. 146. J. Gl¨okler and P. Angenendt, Protein and antibody microarray technology. Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences, 2003, 797, 229–240. 147. U. B. Nielsen and B. H. Geierstanger, Multiplexed sandwich assays in microarray format. Journal of Immunological Methods, 2004, 290, 107–120. 148. S. Aoyagi and M. Kudo, Development of fluorescence change-based, reagent-less optic immunosensor. Biosensors and Bioelectronics, 2005, 20, 1680–1684.
22
ARRAY TECHNOLOGIES
149. T. Konry, A. Novoa, Y. Shemer-Avni, N. Hanuka, S. Cosnier, A. Lepellec, and R. S. Marks, Optical fiber immunosensor based on a poly(pyrrole-benzophenone) film for the detection of antibodies to viral antigen. Analytical Chemistry, 2005, 77, 1771–1779. 150. R. Kapoor, N. Kaur, E. T. Nishanth, S. W. Halvorsen, E. J. Bergey, and P. N. Prasad, Detection of trophic factor activated signaling molecules in cells by a compact fiber-optic sensor. Biosensors and Bioelectronics, 2004, 20, 345–349. 151. J. H. Watterson, P. A. E. Piunno, C. C. Wust, and U. J. Krull, Controlling the density of nucleic acid oligomers on fiber optic sensors for enhancement of selectivity and sensitivity. Sensors and Actuators, B: Chemical, 2001, B74, 27–36. 152. D. R. Fry and D. R. Bobbitt, Hapten immobilization for antibody sensing using a dynamic modification protocol. Talanta, 2001, 55, 1195–1203. 153. M. C. Moreno-Bondi, J. P. Alarie, and T. Vo-Dinh, Multi-analyte analysis system using an antibody-based biochip. Analytical and Bioanalytical Chemistry, 2003, 375, 120–124. 154. K. Blank, A. Lankenau, T. Mai, S. Schiffmann, I. Gilbert, S. Hirler, C. Albrecht, H. Clausen-Schaumann, M. Benoit, and H. E. Gaub, Double-chip protein arrays: force-based multiplex sandwich immunoassays
155.
156.
157.
158.
159.
160.
with increased specificity. Analytical and Bioanalytical Chemistry, 2004, 379, 974–981. G. MacBeath and S. L. Schreiber, Printing proteins as microarrays for high-throughput function determination. Science, 2000, 289, 1760–1763. M. Pawlak, E. Schick, M. A. Bopp, M. J. Schneider, P. Oroszlan, and M. Ehrat, Zeptosens’ protein microarrays: a novel high performance microarray platform for low abundance protein analysis. Proteomics, 2002, 2, 383–393. M. N. Bobrow, G. J. Litt, K. J. Shaughnessy, P. C. Mayer, and J. Conlon, The use of catalyzed reporter deposition as a means of signal amplification in a variety of formats. Journal of Immunological Methods, 1992, 150, 145–149. M. N. Bobrow, K. J. Shaughnessy, and G. J. Litt, Catalyzed reporter deposition, a novel method of signal amplification. 2. Application to membrane immunoassays. Journal of Immunological Methods, 1991, 137, 103–112. M. N. Bobrow, T. D. Harris, K. J. Shaughnessy, and G. J. Litt, Catalyzed reporter deposition, a novel method of signal amplification–application to immunoassays. Journal of Immunological Methods, 1989, 125, 279–285. D. M. Rissin and D. R. Walt, Duplexed sandwich immunoassays on a fiber-optic microarray. Analytica Chimica Acta, 2006, 564, 34–39.
57 Surface Plasmon Resonance Array Devices Masayasu Suzuki,1 Yasunori Iribe1 and Tatsuya Tobita2 1
Departmemt of Electric and Electronic Engineering, University of Toyama, Toyama, Japan and 2 NTT Advanced Technology Corp., Atsugi, Japan
1 SURFACE PLASMON RESONANCE (SPR) AND SPR IMMUNOSENSORS
Many types of immunosensors have been developed, but only surface plasmon resonance (SPR) immunosensors, e.g., the BIAcore system, have achieved commercial success. Surface plasmon oscillation is a localized wave that propagates along the interface between the metal and the ambient medium, and this wave is very sensitive to changes in the refractive index near the metal surface. Figure 1 shows the principle of SPR measurement based on Kretschmann prism arrangement.1 This is based on total internal reflection in a glass prism onto which a thin metal film is deposited. Under the condition that total internal reflection occurs, a part of the light, which is called the evanescent field, penetrates outside the prism. When the metal film is sufficiently thin (e.g., ca. 50 nm) the evanescent field can penetrate the metal film and set up a surface plasmon at the metal–ambient interface. This surface plasmon wave propagates along the interface between the metal and the ambient medium. When the propagation vector of the evanescent wave, ke (=kp sin θ, kp is propagation vector of incident light), equals that of the surface plasmon wave, ksp (= (ω/c)[εn2 /(ε + n)]−(1/2) ), the resonance occurs, and most of the incident light
is transferred into the surface plasmon wave and a sharp minimum in the reflected light intensity is observed. This condition is expressed as follows: kp sin θ = (ω/c)[εn2 /(ε + n)]−(1/2)
(1)
This incident angle, θ , is called the SPR angle. If the light source (angular frequency ω, velocity c), metal (dielectric constant ε), and prism are not changed, the SPR angle depends only on the refractive index of the ambient medium near the metal, n. Although the SPR phenomenon was initially used for the characterization of thin metal films, the group from Linkoping University have applied SPR to gas and biochemical sensing.2 These studies were linked to the development of the BIAcore system,3 which enabled label-free, realtime affinity monitoring of biochemical species such as antibodies, DNA, receptors, and so on. Although SPR-based immunosensors also have many advantages, e.g., multichannel integration with enzyme sensors, conventional SPR immunosensor systems require large instruments. For this reason the miniaturization of the SPR sensor system was investigated, and Texas Instruments developed and commercialized a fully integrated, miniaturized, manufacturable SPR sensor, the Spreeta .4 This sensor chip costs only
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES Measurement medium (refractive index: n)
Surface plasmon
Metal film (dielectric constant: e) Prism
Evanescent wave q
Incident light Reflected light
Figure 1. Principle of surface plasmon resonance sensor.
approximately US$50, and includes all the necessary components for SPR measurements, namely, light source, polarizer, prism, sensing area, and SPR angle detector. Suzuki et al.5 have developed a miniature SPR immunosensor using this sensor chip.
2 TWO-DIMENSIONAL SPR IMAGERS AND THEIR APPLICATIONS
In order to monitor immunoreactions occurring in a large number of spots on microarrayed protein chips or cell chips, conventional SPR sensors could not be applied. The two-dimensional SPR imaging technique is suitable for this purpose. Theoretically, two-dimensional SPR imaging could be realized by adding another dimension to a conventional SPR sensor. Actually such instruments were constructed by several groups, but the instruments became very large and expensive. The first practical two-dimensional SPR imager was reported by Corn et al.6 They achieved two-dimensional SPR imaging with the conventional Kretschmann configuration instrument by using a collimated beam as incident light. This SPR imager has already been commercialized by GWC technologies (USA).7 Traditional SPR sensors determine the shift in “SPR angle” (angle of minimum reflectivity) when the material adsorbs to the surface. But angle scanning requires a long time to determine the SPR angle. Therefore, commercial “one-dimensional” SPR sensors, such as BIAcore , employ a charge coupled device (CCD) line sensor as a detector. In two-dimensional SPR sensors, angle scanning is unavoidable in determining the SPR angle. GWC’s SPR imager takes SPR measurement at a fixed angle of incidence,
and collects the reflected light with a CCD camera. This enables real-time monitoring of SPR images on the surface of DNA or protein arrays. Since SPR sensor is an affinity sensor, it can be applied to immunoreactions, DNA–DNA or DNA–RNA interaction, receptor assay, and so on. Many applications using this SPR imager have been reported. Lee et al.8 applied this SPR imager as a detector of DNA microarrays. They created one- or twodimensional DNA microarrays from microfluidic channels on a thin gold film (SPR sensor membrane). This two-dimensional DNA array was used to detect a 20 fmol sample of in vitro transcribed RNA from the uidA gene of a transgenic Arabidopsis thaliana plant. Wegner et al.9 applied the SPR imager to peptide array. They studied the kinetics of protein adsorption/desorption onto peptide microarrays by using a SPR imager. Real-time measurement with SPR sensor is a powerful tool for kinetics studies. They also applied it to the study of the surface enzymatic activities of the protease factor Xa. Further application could be found in GWC’s website.7 The same type of SPR imagers have been commercialized by Toyobo Co. Ltd. (Japan). They also supply a spotting machine for preparing DNA or protein arrays suitable for observation with the SPR imager. Kyo et al.10 applied this SPR imager to label-free detection of proteins with antibody arrays. They measured the expression of eight proteins in the mouse brain. The detection limit of the antibody array was approximately 30 ng ml−1 in crude cell lysate. Inamori et al.11 applied this system to detect and quantify onchip phosphorylated peptides using a phosphate to capture molecules. The peptide probes, which were phosphorylated on the surface by protein kinase A, could be detected and quantified by this SPR imager. The advantage of such prism-coupled SPR is its high sensitivity compared with gratingcoupled SPR described in the next paragraph. The SPR imager based on grating-coupled SPR was also reported.12 The advantages of gratingbased SPR sensing include the fact that a prism is not necessary to excite surface plasmons and optical quality of the substrate is not crucial. Furthermore, inexpensive and disposable plastic gratings can be used as substrates. This type of SPR imagers were originally commercialized by Applied Biosystems and are now marketed as BIAcore Flexchip.
SURFACE PLASMON RESONANCE ARRAY DEVICES
Localized SPR based on a nanoparticle layer is another principle for realizing SPR imaging. The advantage of this SPR imager is that it is free of SPR image deformation, which is unavoidable in the SPR imager based on Kretschmann configuration. But the sensor performance is strongly affected by the formation of nanoparticles. Improvement of reproducibility might be necessary for this type of SPR imagers.
In this section, we describe the importance of microarrayed well chips and microarrayed immunosensors. Recently, much attention has been focused on cell chips. Typical cell chips are toxicity test chips using hepatic cells and microarray chips, whose well size is over hundreds of micrometers. On the other hand, studies on single-cell analysis are also increasing. After the completion of human genome sequencing, it is now necessary to develop means to observe the functions of biomolecules in single cells as minimal units of living cells. Therefore the First International Workshop on Approaches to Single-Cell Analysis was held at Uppsala University, Sweden, in 2006.13 In Japan, the “Lifesurveyor” project (supported by MEXT, Japan) was started in 2005.14 This project aims at the development of tools and methods for analyzing single cells based on an accurate quantitative and digital analysis of molecules. We have developed a single-cell-based microarray chip system for rapid screening of antigenspecific B lymphocytes. Detection and collection of antigen-specific B lymphocytes for the target antigen is quite important for the development of antibody medicines which are expected as “future medicines”. We are, in Toyama Medical-Bio Cluster Projects, developing the antigen-specific B lymphocytes screening system based on the microarrayed lymphocyte chip on which a quarter million of 10-µm microwells, which are approximately the same size as human lymphocytes, are arranged.15 Figure 2 shows the procedure of the microarray-based, antigen-specific B lymphocytes screening. This screening process consists of the process of seeding the cell onto the microarrayed cell chips, the stimulation process with target antigens, the
[Ca2+] Change metabolic activity proliferation, etc.
Lymphocytes 1cell/well
Setting
Stimulation (antigen, chemicals, etc.) Antigen-specific lymphocyte
Detector
Detection
3 SINGLE-CELL-BASED MICROARRAY CHIP SYSTEM
3
Sampling
Diagnosis and medical treatment
Figure 2. Microarray-based antigen-specific B lymphocytes screening.
Figure 3. Single-cell-based automatic cell screening system.
detection process for target cells, and the collection process of the target cells. We have developed the automatic single-cell screening system based on the microarrayed cell chips. The system consists of a cell seeding unit for microwell array chips, a high-resolution detection unit, and an automatic single-cell collection unit. Figure 3 shows the photograph of the developed cell screening system. We engaged in the development of the novel sensor systems for microwell array chips. In the single-cell-based microarrayed cell chips, the applicable sensing technologies are very limited
4
ARRAY TECHNOLOGIES Receptor molecules (protein A) Analytes
Metal film (Au)
PDMS microwell-array sheet
Glass substrate
Reflected light
Prism
Incident light
q Incident angle Lens unit (1,2,4,7X)
CCD camera
Figure 4. Structure of the two-dimensional SPR imaging sensor.
because of their small size and large number of spots. High-resolution imaging techniques are required. We developed the microarrayed optical pH and oxygen sensor systems using the high-resolution laser confocal scanner for cell activity monitoring,16 and the high-resolution, two-dimensional SPR imaging affinity sensor system for protein detection.17 4 CONSTRUCTION OF THE MICROSCOPIC SPR IMAGER
Among the various types of SPR imagers, the SPR imager based on Kretschmann configuration might be the best choice for realizing highresolution imaging. Therefore we employed the SPR imager based on Kretschmann configuration (2DSPR-04A, NTT advanced technologies). Figure 4 shows the structure of our SPR imager. A collimated beam, generated by an LED source (λ = 660, 740, and 840 nm) illuminates the metal sensor surface, which is in contact with the sample solution, through a coupling prism. The incident beam is transverse magnetically (TM) polarized and the reflected light is imaged onto the cooled CCD camera via a microscopic long working distance (WD) lens (1X, 2X, 4X, and 7X). Figure 5 shows the photograph of our SPR imager. The disadvantage of the SPR imager based on Kretschmann configuration is deformation of the
Figure 5. Two-dimensional SPR imaging sensor.
SPR image because the image is given a sidelong glance. This problem might be serious when the image is small as in the present study. In order to decrease this deformation, a high-refractive optical system was employed. The conventional SPR sensor employs BK7 for prism because its refractive index is similar to glass. In our SPR imager, SF6, a high-refractive material, was used as the prism and as a substrate for the sensor chip. Furthermore, a cooled CCD camera was employed in order to suppress the entropy noise. In the conventional Kretschmann type SPR imager, the SPR sensor chip was set vertically because of its optical system structure. This is not suitable for microarrayed well chips. In our SPR imager, the SPR sensor chip can be set horizontally by employing an optical fiber cable.
16
30
12
25
8 4 0 −4 −8 −0.9
5
Conventional
∆Relative intensity (-)
∆Light intensity (au)
SURFACE PLASMON RESONANCE ARRAY DEVICES
−0.7 −0.5 −0.3 −0.1 0.1 0.3 Measurement angle – SPR angle (deg)
Optimized 1 Optimized 2
20
Optimized 3
15 10 5
0.5
0
0
5
10
15
20
Glucose (g l−1)
5 OPTIMIZATION OF SPR SENSING
In order to improve the sensitivity of the SPR sensor, measurement conditions of the sensor were optimized. Sensitivity could be greatly improved by optimization of the measurement angle, exposure time, light source intensity, and so on. For example, the maximum response was obtained when the measurement angle was set at SPR angle: −0.5◦ , as shown in Figure 6. By optimization of the measurement angle and exposure time of CCD camera, SPR sensitivity was improved by over 20 times, as shown in Figure 7 (at 20 mg ml−1 glucose). Under this condition, immunoglobulin G (IgG) was measured in 10- and 30-µm microwells. In 30-µm microwells, sensor response to 0.1 mg ml−1 mouse IgG was improved by five times. Under the same condition, 0.01 mg ml−1 IgG also could be detected. In 10-µm microwells, 0.1 mg ml−1 IgG could be successfully detected with this microarrayed 2D-SPR sensor (Figure 8). These results show the possibility of real-time monitoring for antibody production by a single B lymphocyte in a microwell.
6 RESOLUTION OF SPR IMAGE AND METALS OF SPR SENSOR CHIPS
Improvement of the resolution of SPR images (sharpness of images) is very important for twodimensional SPR sensing. SPR phenomena are affected by the dielectric constant (ε) of thin metal film on the prism. Dielectric constants of metals
Figure 7. Effect of exposure time and measurement angle on SPR sensitivity. Exposure time and measurement angle were 2 s and SPR angle (conventional), 20 s and SPR angle (optimized 1), 2 s and (SPR angle: −0.5◦ ) (optimized 2), and 20 s and (SPR angle: −0.5◦ ) (optimized 3), respectively.
4 ∆Light intensity (-)
Figure 6. Effect of measurement angle on SPR sensitivity, measured with gold film and 770-nm light source.
3 2 1 0 −1
0
500
1000
1500
2000
Time (s)
Figure 8. IgG detection in 10-µm wells 0.1 g l−1 mouse IgG was measured under the optimized condition 3. Gold film and 770-nm light source were used.
are expressed as a complex number. For example, dielectric constant of gold is −21.7 + 1.36i, and that of silver is −28.7 + 0.34i when the wavelength of light source is 770 nm and temperature is 20 ◦ C. The real part of the dielectric constant (εr ) denotes reflection, and the imaginary part (εi ) reflects absorption. Therefore, a larger |εi /εr | means higher energy absorption. SPR curves may become broader and SPR sensitivity might be decreased in the case of higher |εi /εr |. For example, |εi /εr | of gold, silver, and aluminum are 0.063, 0.012, and 0.573, respectively. This means silver film might be a suitable material for highly sensitive SPR measurement. Therefore the relationship between the brightness gradient at the boundary of well images and the kind of metal film was investigated, and the resolution of 2D-SPR imaging was improved.
6
ARRAY TECHNOLOGIES 88.0
86
87.5 87.0
84
f (deg)
f (deg)
85
83
86.5 86.0 85.5
82 Gold
Silver
Aluminum
85.0 84.5
Figure 9. Comparison of resolution with various metal films. Metal film was prepared with vacuum vapor deposition (open column) or ion-sputtering (closed column). Distilled water in 10-µm wells was measured by using 770-nm light source.
By using a 10-µm microarray, the effect of the metal layer on the resolution of SPR images was investigated. As shown in Figure 9, the clearest image was obtained with silver film. Approximately similar results were obtained with gold and aluminum films. The effects of the preparation methods of metal layers on the resolution were also investigated. Silver and gold layers were prepared by the ionsputtering method and vacuum vapor deposition method. Clearer and higher-resolution SPR images were obtained with metal layers prepared by the ion-sputtering method as shown in Figure 9. The results show that the highest resolution was obtained by the silver layer prepared by the ionsputtering method. The problem with using a silver layer as an SPR sensor membrane is its instability in buffer solution. Actually, the prepared silver layer was destroyed when dipped in 0.05 M Hepes-HCl buffer (pH 7.5) containing 4.46 g l−1 NaCl for 2 h. In order to improve the stability of the silver film, Zhu et al.18 reported the effects of protection layers, such as Al2 O3 , Cr2 O3 , and Nb2 O5 , on the stability of silver layer for SPR biosensors. We employed a thin layer of alumina as a protection layer for the silver film. The effect of alumina layer as a protection layer was investigated. One nanometer of aluminum layer was prepared by vacuum vapor deposition on the silver layer of the SPR sensor chip. Then the sensor chip was baked at 100 ◦ C for 30 min. The stability of the silver layer coated with the thin film of alumina was investigated by dipping it in 0.05 M Hepes-HCl buffer (pH 7.5)
Au
Ag
Ag /Alumina
Figure 10. Effect of alumina coating on resolution. Distilled water in 10-µm wells was measured by using 670-nm light source.
containing 4.46 g l−1 NaCl for 2 h. Even after 2 h, no destruction of silver film was observed. In the same way, the resolution of the SPR image was compared by using a 10-µm microarray on alumina-coated silver, bared silver, and gold. As shown in Figure 10, a sharp image was obtained with alumina-coated silver film as in bared silver film. Although silver film is unstable in buffer solution, alumina-coated silver film is stable in buffer solution, and shows approximately similar characteristics as SPR sensor membrane. 7 SENSITIVITY DECREASE OF SPR SENSING IN 10-µM-ORDER AREA
Figure 11 shows the relationship between SPR sensitivity and well size. SPR sensitivity was evaluated by glucose responses. With 30-µm wells, SPR sensitivity was the same as in the case without wells (bared gold film). But the SPR sensitivity was drastically decreased with 10- and 8.5-µm microwells. This sensitivity decrease was also observed with the SPR immunosensing for mouse IgG. Since SPR is a phenomenon of surface waves, it may depend on the wavelength of incident light if the area is extremely small as in 10-µm microwells. Therefore a shorter wavelength would be suitable for SPR measurement in 10-µm microwells. But the wavelength of incident light affects the dielectric constant of metal film. Figure 12 shows the relationship between wavelength and the ratio of the real (εr ) and imaginary parts (εi ) of the dielectric constant, |εi /εr |, of gold
25
70
20
60
15
50
∆Intensity (-)
∆Intensity (-)
SURFACE PLASMON RESONANCE ARRAY DEVICES
10 5 0
40 30 20
0
20 40 60 80 Glucose concentration (g l−1)
100
10 0
A
Figure 11. SPR sensitivity and well size. : without wells, : 30 µm wells, : 10 µm wells, •: 8.5 µm wells. Measured with gold film and 670-nm light source.
|ei/er| (-)
0.4
Gold
0.3
D
0.2
4
0.1
(a) 0.1 0.08 0.06 0.04 0.02 0 500
700 900 Wavelength (nm)
1100
3
Silver
Response (-)
0 500
|ei /er| (-)
B C Metal sensor film
Figure 13. Comparison of SPR sensitivity with various metal films. Metal sensor film: (A) Ag (55 nm), (B) Ag (55 nm)/alumina (1 nm), (C) Ag (55 nm)/alumina (1 nm)/Au (2 nm), and (D) Au (65 nm); 100 g l−1 glucose was measured with 670-nm light source.
0.5
(b)
7
2
1 700 900 Wavelength (nm)
1100
Figure 12. Wavelength of light source and dielectric constant.
(Figure 12a) and silver (Figure 12b). In the case of gold sensor film, |εi /εr | was drastically increased when the wavelength of light source was under 700 nm. Therefore SPR curves became broad and the sensitivity of SPR sensor became lower. But in the case of the silver film, |εi /εr | was stable over 500 nm. Therefore with the use of a silver sensor film and shorter-wavelength light source, more sensitive SPR measurement could be possible even in a small area in the order of under 10 µm. Figure 13 shows the comparison of SPR sensitivity with various metal films. The sensitivity was evaluated with the response to 100 g l−1 glucose. For sensor film C, called multilayered metal film,
0 10-µm well
8.5-µm well
Figure 14. Detection of immunoglobulin G with various metal films. Metal sensor film D (Au (65 nm)) (open column) or metal sensor film C (Ag (55 nm)/alumina (1 nm)/Au (2 nm)) (closed column) was used to measure 0.1 g l−1 mouse IgG. A 670-nm light source was used for SPR measurement.
gold film (2 nm) was prepared on alumina-coated silver film to immobilize affinity ligands, by using bifunctional molecules with thiols. High SPR sensitivity was also obtained with three kinds of silver-based sensor films. Finally, mouse IgG was detected by using the multilayered metal film as sensor film. As shown in Figure 14, greater response to 0.1 g l−1 mouse IgG could be obtained with the multilayered metal film, especially with the 8.5-µm microwells, where the response was approximately 16 times higher than the gold sensor film.
8
ARRAY TECHNOLOGIES
8 CONCLUSION
In this chapter, two-dimensional SPR imaging techniques and their application to microarray technologies have been described. After the general survey of two-dimensional SPR imaging techniques, including commercially available instruments, our recent studies on the highresolution SPR imager which may be applicable to the single-cell-based microwell array were described. The SPR sensor has wide application fields. Not only the affinity measurement described in this chapter, but direct measurement of cell dynamics may also be possible. Giebel et al.19 have reported the imaging of cell/substrate contacts of living cells with the SPR imager. The problems of the SPR imager at the present stage may be because of low sensitivity. In order to achieve high sensitivity as in BIAcore , effective control measures which eliminate the effects of environmental fluctuations may be necessary.
5.
6. 7. 8.
9.
10.
11.
ACKNOWLEDGMENTS
Most of the work described in this chapter was done as a project study organized by Toyama Medical-Bio Cluster Projects supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan, and Toyama prefecture. The work was partially supported by the Grantin-Aid for Scientific Research on Priority Areas “Lifesurveyor” and “Bio-Manipulation” from the Ministry of Education, Culture, Sports, Science and Technology of Japan.
12.
13.
14. 15.
16.
REFERENCES 17. 1. E. Kretschmann and H. Raether, Radiative decay of nonradiative surface plasmons excited by light. Zeitschrift fur Naturforschung, 1968, 23, 2135. 2. B. Liedberg, C. Nylander, and I. Lundstroem, Surface. Plasmon resonance for gas detection and biosensing. Sensors and Actuators, 1983, 4, 299–304. 3. R. L. Earp and R. E. Dessy, Surface Plasmon Resonance, in Commercial Biosensors, G. Ramsay (ed), John Wiley & Sons, 1998, pp. 99–164. 4. J. Melendez, R. Carr, D. U. Bartholomew, K. Kukanskis, L. Elkind, S. Yee, C. Furlong, and R. Woodbury, A
18.
19.
commercial solution for surface plasmon sensing. Sensors and Actuators, 1996, B35 – B36, 212–216. M. Suzuki, F. Ozawa, W. Sugimoto, and S. Aso, Miniature surface-plasmon resonance immunosensors–rapid and repetitive procedure. Analytical and Bioanalytical Chemistry, 2002, 372, 301–304. A. G. Frutos and R. M. Corn, SPR of ultrathin organic films. Analytical Chemistry, 1998, 70, 449A–455A. SPR imager II array instrument, GWC Technologies, www.gwctechnologies.com/gwcSPRimager.htm, 2007. H. J. Lee, T. T. Goodrich, and R. M. Corn, SPR imaging measurements of 1D and 2D DNA microarrays in PDMS microfluidic channels on gold thin films. Analytical Chemistry, 2001, 73, 5525–5531. G. J. Wegner, A. W. Wark, H. J. Lee, E. Codner, T. Saeki, S. Fang, and R. M. Corn, Real time SPR imaging measurements for the multiplexed determination of protein adsorption/desorption kinetics and surface enzymatic reactions on peptide microarrays. Analytical Chemistry, 2004, 76, 5677–5684. M. Kyo, K. Usui-Aoki, and H. Koga, Label-free detection of proteins in a crude cell lysate with antibody arrays by surface plasmon resonance imaging technique. Analytical Chemistry, 2005, 77, 7115–7121. K. Inamori, M. Kyo, Y. Nishiya, Y. Inoue, T. Sonoda, E. Kinoshita, T. Koike, and Y. Katayama, Detection and quantification of on-chip phosphorylated peptides by surface plasmon resonance imaging techniques using a phosphate capture molecule. Analytical Chemistry, 2005, 77, 3979–3985. B. K. Singh and A. C. Hiller, Surface plasmon resonance imaging of biomolecular interactions on a grating-based sensor array. Analytical Chemistry, 2006, 78, 2009–2018. The First International Workshop on Approaches to Single-Cell Analysis, Uppsala, Sweden, June, 2006, www.conference.slu.se/single cell, 2006. Lifesurveyor Project, www.tuat.ac.jp/∼surveyor/Eng/Engindex.htm, 2007. S. Yamamura, S. R. Rao, M. Omori, Y. Tokimitsu, S. Kondo, H. Kishi, A. Muraguchi, Y. Takamura, and E. Tamiya, High-throughput screening and analysis for antigen specific single-cell using microarray. Micro Total Analysis Systems, 2004, 1, 178–180. M. Suzuki, H. Nakabayashi, Y. Jing, and M. Honda, Optical pH and oxygen sensing for micro-arrayed cell chips. Micro Total Analysis Systems, 2005, 2, 1482–1484. M. Suzuki, S. Hane, T. Ohshima, Y. Iribe, and T. Tobita, Detection of antibodies in 10 µm wells on micro-arrayed cell chips by 2D-SPR affinity imaging. Micro Total Analysis Systems, 2006, 1, 756–758. X.-M. Zhu, P.-H. Lin, P. Ao, and L. B. Sorensen, Surface treatment for surface plasmon resonance biosensors. Sensors and Actuators, 2002, B84, 106–112. K.-F. Giebel, C. Bechinger, S. Herminghaus, M. Riedel, P. Leiderer, U. Weiland, and M. Bastmeyer, Imaging of cell/substrate contacts of living cells with surface plasmon resonance microscopy. Biophysical Journal, 1999, 76, 509–516.
58 Label-Free Gene and Protein Sensors Based on Electrochemical and Local Plasmon Resonance Devices Kagan Kerman,1 Tatsuro Endo2 and Eiichi Tamiya3 1
School of Materials Science, Japan Advanced Institute of Science and Technology (JAIST), Ishikawa, Japan, 2 Department of Mechano-Micro Engineering, Tokyo Institute of Technology, Yokohama, Japan and 3 Department of Applied Physics, Osaka University, Osaka, Japan
1 INTRODUCTION
Since its discovery in early 1950s by Watson and Crick,1 DNA has never ceased to fascinate the researchers in many diverse fields. Double helix is formed with the coupling of two strands with complementary base sequences. The codes behind the order of the four nucleotides have made DNA the most attractive biomaterial in scientific research. The detection of specific DNA base sequences has a significant impact in various fields of life sciences. For this task, DNA biosensors using several detection principles; such as electrochemical,2–5 piezoelectric,6,7 and optical8,9 transducers have been developed. Recently, micro- or nanometerscale DNA biosensors and biochips have become a major interest with the significant advances in fabrication technologies. 2 LABEL-FREE ELECTROCHEMICAL GENE SENSORS BASED ON THE OXIDATION OF DNA BASES
The majority of the label-free electrochemical DNA biosensors are based on the determination
of purine oxidation current signals, mainly the guanine oxidation signal. This is due to the fact that guanine has the lowest oxidation potential of all DNA bases.10–12 The main oxidation product, 8-oxo-7,8-dihydroguanine13 is considered the biomarker of DNA damage by oxidative stress14 and can be quantified using its oxidation peak current intensity.15,16 The detailed studies on the electrochemical behavior of purine and pyrimidine bases were reported. The majority of these reports were about the electrochemical reduction of purine and pyrimidine derivatives on mercury electrodes. The reduction peak current signal of guanine, adenine, and cytosine could be observed; however, no polarographic wave was reported for thymine on the mercury electrodes.10 Carbon electrodes were extensively used for the detection of oxidation peak current signals derived from the purine bases.17,18 The electroactivity of pyrimidine-derivative compounds at solid electrodes was reported.19 Brett and coworkers reported that guanine and adenine were more easily detected than thymine and cytosine.20 The well-defined oxidation signal of guanine has been utilized for the detection of DNA
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
ARRAY TECHNOLOGIES
(w/w) ratio. The carbon paste was then tightly packed into a Teflon tube (3 mm i.d.). SWNTpaste electrode was prepared by mixing SWNT powder and mineral oil in a 60 : 40 (w/w) in a similar fashion as reported by Palleschi and coworkers.41 About eightfold amplification in the oxidation signal of polyA was observed at the SWNT-paste electrode (Figure 1a). The oxidation peak of polyA shifted 0.15 V toward lower potential values, which was attributed to the good electron transfer characteristics of SWNTs. PolyG oxidation signal was also amplified threefold, and its oxidation peak shifted about 0.25 V toward lower potential values at SWNT-paste CPE (Figure 1b). We anticipate that the development of DNA sensors based on the intrinsic electrochemical signals will continue to evolve and bring new and exciting findings and a closer look into the structure and interaction mechanisms of DNA with small ligands. 10- ppm polyA with CNT
10 - ppm polyA without CNT
0 (a)
0.25
0.5
0.75 1 Potential (V)
10 - ppm polyG with CNT
0
0.2
1.25
1.5
Peak shift 0.25 V
500 nA
(b)
Peak shift 0.15 V
500 nA
Current
hybridization.21–25 Guanine oxidation signal was also monitored to detect the interaction mechanisms between several types of drugs and DNA.26–28 Toxic molecules that interact with DNA could also be detected by monitoring the changes in guanine oxidation signal in connection with electrochemical DNA biosensors.29–31 The use of inosine-substituted probes and the appearance of a guanine signal upon hybridization with the native target DNA molecule provided new challenges in electrochemical gene sensors.32,33 Ariksoysal et al.33 described a label-free electrochemical DNA biosensor protocol that the detection of hybrid formation was performed by using the guanine oxidation signal of the target DNA. A pencil-based renewable biosensor for labelfree electrochemical detection of hybridization was also reported by Kara et al.21 Magnetocomposite electrodes have recently been developed for the label-free electrochemical detection of DNA hybridization using magnetic beads.34 Carbon nanotubes (CNTs) possess unique properties that are amenable to biosensor applications. CNTs are one-dimensional structures that are extremely sensitive to electronic perturbations, readily functionalized with biorecognition layers, and compatible with many semiconducting manufacturing processes.35,36 To date, there have been several reports on the electrochemical detection of DNA hybridization using CNTmodified electrodes.37,38 Whereas electrochemical methods rely on electrochemical behavior of the labels, measurement of direct electron transfer between CNTs and DNA molecules paves the way for label-free DNA detection. Singlestranded deoxyribonucleic acid (ssDNA) has been recently demonstrated to interact noncovalently with single-walled carbon nanotubes (SWNTs).39 The ssDNA forms a stable complex with individual SWNTs by wrapping around them by means of the aromatic interactions between nucleotide bases and SWNT sidewalls. Double-stranded DNA molecules have also been proposed to interact with SWNTs as major groove binders.40 Figure 1 shows the differential pulse voltammograms for the detection of polynucleotides. The voltammetric oxidation peaks of 10-ppm poly-adenine (polyA) and poly-guanine (polyG) were obtained at a carbon paste electrode (CPE). CPE was prepared by mixing graphite powder (Fisher) and mineral oil (Acheson 38) in a 70 : 30
Current
2
0.4
0.6 0.8 Potential (V)
10- ppm polyG without CNT
1
1.2
Figure 1. Differential pulse voltammograms for the label-free electrochemical detection of polynucleotides; (a) 10-ppm poly-adenine (polyA) at a bare carbon paste electrode (CPE), 10-ppm polyA at SWNT-paste electrode, (b) 10-ppm polyguanine (polyG) at a bare CPE, 10-ppm polyG at SWNT-paste electrode in 0.50 M acetate buffer solution (pH 4.5).
LABEL-FREE GENE AND PROTEIN SENSORS
3 LABEL-FREE GENE AND PROTEIN SENSORS BASED ON FIELD-EFFECT TRANSISTORS
A field-effect transistor (FET) device uses an electric field to control the shape, and hence the conductivity of a “channel” in a semiconductor material. FETs are sometimes employed as voltage-controlled resistors. FET is simpler in concept than the bipolar transistor. The channel region of any FET is either doped to produce n-type semiconductor, producing an “N channel”, or with p-type to produce a “P channel”. The doping determines the polarity of the gate operation. FET devices can be constructed from a wide range of materials. FETs made of semiconductor nanowires (NWs) and SWNTs show promising potential for biosensor applications. The depletion or accumulation of charge carriers, which are caused by the binding of charged biological macromolecules on the surface of NWs or SWNTs, greatly affects the entire cross-sectional conduction pathway of these nanostructures. Electrical detection of biomolecular interactions with metal–insulator–semiconductor diodes has recently been reported by Estrela et al.42 They have also reported the detection of biomolecular interactions using FET devices; such as metal-oxide-semiconductor field-effect transistor (MOSFET) capacitor structures and polycrystalline silicon thin-film transistors (Poly-Si TFTs).43 FET-based biosensors in connection with semiconducting Si NWs are promising candidates, since the doping type and concentration can be controlled, which allows tuning of the sensitivity without the need for an external gate. Since the report of Lieber and coworkers44 about the ultrasensitive detection of biological and chemical species by exploring nanoscale Si NW-based FETs, there has been an intensive amount of research on FET-based biosensors with Si NWs. NW arrays were modified with antibodies for influenza A, and discrete conductance changes were observed due to the binding and unbinding events in the presence of influenza A but not paramyxovirus or adenovirus.45 Lieber and coworkers also reported the electrical detection of small-molecule inhibitors of ATP binding to Abl, a protein tyrosine kinase, by using Si NW-FET devices.46 NW arrays also allowed highly selective and sensitive multiplexed detection
3
of prostate-specific antigen (PSA), PSA-α1 antichymotrypsin, carcinoembryonic antigen, and mucin-1 with a detection limit of 0.9 pg ml−1 in undiluted serum samples.47 Recently, Lieber and coworkers48 demonstrated that Ge/Si core/shell NWs had long carrier mean free paths at room temperature. They concluded that the performance of Ge/Si NW-FETs was comparable to similarlength CNT-FETs and substantially exceeded the length-dependent scaling of planar silicon MOSFETs. CNT-based FETs also have excellent operating characteristics,49,50 and they have already been explored for highly sensitive electronic detection of gases.51–53 We developed back-gate CNT-FET nanosensor arrays, where the biomolecules could easily be immobilized onto the gold-coated back gate (Figure 2a and b). We have employed these back-gate devices based on CNT-FETs for the
(a) Drain
Side gate
(b) Source
Figure 2. (a) Microelectrode array based on carbon nanotube field-effect transistor (CNT-FET) devices and (b) close-up image of a single CNT-FET device.
4
ARRAY TECHNOLOGIES
ultrasensitive detection of hybridization between peptide nucleic acid (PNA) probes and DNA target strands. PNA is a synthetic DNA analog, in which both the phosphate and the deoxyribose of the DNA backbone are replaced by a polypeptide.54 Even so, PNA retains the ability to hybridize with complementary DNA or RNA sequences. An additional advantage of using PNA instead of DNA in sensing systems is its neutral polypeptide backbone, which leads to an improved PNA–DNA base-pairing free of ionic strength influence, and resistance to degradation by proteases and nucleases.55 A self-assembled monolayer (SAM) of PNA probes related to the tumor necrosis factor alpha gene (TNF-α) was prepared on the gold electrode at the reverse side of the CNT-FET device as illustrated in Figure 3(a). A time-dependent conductance increase was monitored upon flowing negatively charged DNA target molecules through the microfluidic channel of a poly(dimethylsiloxane) (PDMS) chip as shown in Figure 3(b). The high selectivity of PNA probes only toward
PNA probe modified (a) CNT-FET device
PNA–DNA hybridization on CNT-FET device 180 min
ISD (µA)
1
VG = 0 V
1 min
0 −1 −1
(b)
0 VSD (V)
1
Figure 3. (a) Schematic illustration of a back-gate carbon nanotube field-effect transistor (CNT-FET) device. Peptide nucleic acid (PNA) probes were attached onto the gold surface using covalent modification. (b) As the hybridization with the negatively charged target DNA molecules took place, the source–drain current response versus source–drain potential increased.
the full-complementary DNA samples enabled the rapid and simple discrimination against singlenucleotide polymorphism (SNP) or noncomplementary (NC) DNA.56 Concentration-dependent measurements indicated a limit of detection of 6.8 fM target DNA.56
4 CONDUCTING POLYMERS FOR LABEL-FREE ELECTROCHEMICAL GENE SENSORS
Conducting polymers (CP) are attractive substrates for gene sensors, because they can act as an electronic transducer for the charged species binding to the surface. No redox indicator is necessary, because the CP itself can directly report the hybridization event. An additional advantage of CP is that a bioelement that serves as a probe can be covalently grafted to the polymer backbone, and a variety of organic synthetic methods are available for this purpose.57 Several methods for the immobilization of DNA probes onto CP have been reported.58,59 Initial approaches to the construction of CP-based gene sensors included the direct adsorption of the oligonucleotides onto oxidized polypyrrole (PPy) films by electrostatic attractions60 or incorporation of the oligonucleotides into the polymer film as a macrocounterion.61 However, these methods suffered from effects arising from constraints on the orientation of the oligonucleotides resulting in high steric and kinetic barriers to hybridization, and the possibility of oxidative damage to the oligonucleotide probes. To overcome such steric constraints, several groups have electrocopolymerized, N-position-substituted pyrroles.62 Mugweru and Rusling63 adsorbed poly(4-vinylpyridine) (PVP) with attached Ru(bpy)2+ onto pyrolytic 2 graphite electrodes for the development of reusable DNA sensors. Recently, Komarova et al.64 developed a label-free DNA sensor using ultrathin films of PPy doped with an oligonucleotide probe related to a biowarfare virus, Variola major. Piro et al.65 reported the characterization of a new bifunctional electroactive polymer, poly(5-hydroxy-1,4-naphthoquinone (juglone)-co5-hydroxy-3-thioacetic acid-1,4-naphthoquinone), which was used for the label-free electrochemical detection of DNA hybridization.
LABEL-FREE GENE AND PROTEIN SENSORS
Peng et al.66 reported synthesis of a new precursor monomer, (4-(3-pyrrolyl) butanoic acid), which was used to form a copolymer of poly(pyrrole-co-4-(3-pyrrolyl) butanoic acid) by electropolymerization. The relatively long butanoic acid side chains positioned the oligonucleotide probe away from the copolymer backbone and facilitated efficient hybridization. The hybridization with target DNA was detected in connection with cyclic voltammetry and the AC impedance spectroscopy. Label-free DNA detection has recently been performed using modified conducting PPy films at microelectrodes.67 The use of PPy in conjunction with bioaffinity reagents is a powerful method that has expanded the range of applications of electrochemical detection and its future development is expected to continue. The use of a wide range of counterions will provide significant improvements in affinity at the PPy ion-exchange sites. The application of CNTs will also be beneficial to the development of PPy-based biosensors at the nanoscale.
5 IMPEDANCE SPECTROSCOPY FOR THE LABEL-FREE GENE AND PROTEIN SENSORS
Electrochemical impedance spectroscopy (EIS) (sometimes also called AC impedance) is an electrochemical technique, in which a low-amplitude alternating potential (or current) wave is imposed on top of a direct current potential (often the corrosion potential and zero imposed current). EIS has been explored in detail as the dominant method in label-free biosensors owing to its high sensitivity in the detection of small proteins; such as interferon γ .68 Impedimetric immunosensors have been reviewed in depth by Katz and Willner.69 Moreover, conjugated biomolecules with gold nanoparticles have recently been used for the amplification of impedance and capacitance signals.70 The comparison of label-free and impedance-amplifying label-based systems was performed by Ma et al.71 The sensing of DNA binding drugs using gold substrates modified with gold nanoparticles was reported by Li et al.72 DNA hybridization was detected using EIS investigation of conducting properties of a functionalized polythiophene matrix.73 Yang et al.74 reported
5
a new antibody immobilization strategy based on electrodeposition of nanometer-sized hydroxyapatite for label-free capacitive immunosensors. Oligonucleotide-functionalized PPy was also applied to the impedimetric detection of DNA hybridization.75 Interdigitated ultramicroelectrodes using electrochemical redox probes were developed for impedimetric detection of DNA.76 An impedance array biosensor was fabricated by Yu et al.77 for the detection of multiple antibody–antigen interactions. M¨oller et al.78 have recently utilized the resistance in the gap between the microfabricated electrodes for monitoring DNA hybridization. Capture DNA was immobilized in the gap. Then, the biotin-modified target DNA hybridized with its complementary capture DNA. Afterward, the chip was incubated with either streptavidin-modified gold nanoparticles or a streptavidin–peroxidase polymer, which was bound to the biotin modification. Silver enhancement produced a conductive layer to bridge the gap between the electrodes, so that a significant drop in the electrical resistance could be detected. Aptamers, derived from the Latin word, “aptus” meaning “to fit”, are artificial nucleic acid ligands that can be generated against amino acids, drugs, proteins, and many other molecules.79 They are isolated from combinatorial libraries of synthetic nucleic acids by a process called SELEX (systematic evolution of ligands by exponential enrichment) involving adsorption, recovery, and re-amplification.80 Aptamers, first reported in the early 1990s, are still attractive in the areas of therapeutics and diagnostics and offer themselves as ideal candidates for use as biocomponents in biosensors (aptasensors), possessing many advantages over the other affinity sensors.81 Recently, aptamers have been applied as the recognition layer in impedimetric biosensors. Aptamer-based array electrodes were developed by Xu et al.82 for immunoglobulin detection. An aptamer-based impedance measurement assay was also developed for thrombin with a detection limit of 0.1 nM.83 Radi et al.84 developed reusable impedimetric aptasensors. Wang and coworkers reported the recognition-induced switching of the surface charge for aptasensors.85 Surely, the potential of EIS as a biosensor is immense, and this exciting research area is on the brink of exponential growth.
ARRAY TECHNOLOGIES
6 LABEL-FREE ELECTROCHEMISTRY OF PROTEINS
Although many advanced transducers have been developed in the past decades, the electronic transduction of protein interactions has been a major challenge in electrochemistry, because the proteins have been considered to be “electroinactive”. Thus, a major interest has been focused on “metalloproteins”, which are chemical combinations of protein atoms with ions of metals such as iron, calcium, copper, and zinc. The first reports on the direct electron transfer between the metal ion center of the metalloprotein and an electrode surface were published in 1977, when Eddowes et al.86 and Yeh et al.87 independently showed that cytochrome c on bipyridyl-modified gold and tin-doped indium oxide electrodes, respectively, went through “bioelectrocatalysis” with reversible cyclic voltammograms. The electrocatalytic voltammetry of metalloproteins continues to be the subject of intense investigation88,89 to the present day. The catalytic evolution of hydrogen on dropping mercury electrodes in weakly alkaline solutions was a milestone discovery of Heyrovsky, which had caused a series of publications to investigate the possibility of protein electrochemistry.90 Especially, the Bridcka reaction, which represents the catalytic lowering of hydrogen overvoltage in the presence of cobalt ions has been the main means of protein polarography.90 The first introduction of the direct oxidation of tyrosine (Tyr), tryptophan (Trp), and cysteine (Cys) residues on carbon electrodes, about two decades ago, created a new notion in electroanalysis: that not only metalloproteins, but also all proteins that contained either Tyr, Trp, and/or Cys could be detected directly on carbon electrodes.91,92 Oxidation of Tyr and Trp at a wax-impregnated spectroscopic graphite electrode was reported to be a twoelectron transfer process.93 The alanine-substituted indole ring of Trp is susceptible to electrochemical oxidation from its heteroatom.91–93 Several groups reported the electrochemical detection of clinically important proteins and amino acids.94–96 Recently, the electrochemical oxidation signal of amyloid-β peptides related to Alzheimer’s disease was employed as the indicator of fibril formation.97
The electrical responses of some representative proteins and amino acids are shown in Figure 4. Bovine serum albumin (BSA) showed a wide electrochemical peak of ∼208 nA at 500 pg ml−1 (Figure 4C), but the signal was not as high as one would have expected from a protein with 21 Tyr and 3 Trp residues. The structure of BSA with about 607 amino acids might have masked the exposure, and eventually the contact of these electroactive amino acids with the carbon electrode surface. As expected, the electroactive amino acids, Tyr (Figure 4A) and Trp (Figure 4B) alone gave the highest electrical responses. The proteins with small molecular weights, such as human chorionic gonadotropin (hCG) (Figure 4D), and PSA (Figure 4E), gave high responses. This trend in their signals was attributed to the steric proximity of the electroactive residues of these proteins to the electrode surface and their less complex structure owing to their small molecular weight. The detection of electroactive amino acids was assessed on the bare Pt and SWNT-modified Pt electrodes in connection with differential pulse voltammetry (DPV). SWNT-Pt electrodes were prepared by dispersing acid-treated SWNTs in chitosan solution. A 2% (w/v) chitosan solution was prepared in 1% (v/v) acetic acid. SWNTs were treated in concentrated nitric acid for 5 h, filtered and A
200 nA B E
Current
6
C D
0
0.25
0.5
0.75
1
Potential (V) Figure 4. Differential pulse voltammograms of proteins and amino acids on a carbon paste electrode (CPE), (A) 250 µg ml−1 tyrosine (Tyr), (B) 250 µg ml−1 tryptophan (Trp), (C) 500 µg ml−1 bovine serum albumin (BSA), (D) 300 µg ml−1 human chorionic gonadotropin hormone (hCG), (E) 0.250 µg ml−1 prostate-specific antigen (PSA) in 50-mM phosphate buffer solution (pH 7.4).
LABEL-FREE GENE AND PROTEIN SENSORS
washed with ultrapure water until the filtrate was neutral, and finally dried under vacuum. Then, a desired amount of CNTs (1 mg ml−1 ) was dissolved in chitosan solution under 1-h sonication. Chitosan–CNT solution (20 µl) was spread uniformly on the Pt electrode surface. After the solution was dried in air, the SWNT-modified electrode was immersed in 0.1 M NaOH for 30 min to make the film more stable. Then, the electrode was rinsed with ultrapure water and air-dried. The scanning electron microscopy (SEM) images of the SWNT–chitosan matrices are shown in Figure 5(a) and (b). The differential pulse voltammograms for the detection of Tyr, Trp, and Cys are shown in Figure 6(a–c), respectively. The electrochemical oxidation signals were clearly observed from the SWNT-modified electrodes (red line). On the other hand, low signals were obtained from the devices with bare Pt-arrayed electrodes (blue line). Moreover, the peak current intensities for the amino acids obtained from SWNT-modified electrodes were about 20-fold higher than those obtained from bare Pt, which was attributed to the remarkable enhancement in total surface area of the working electrode with the efficient electron transfer characteristics of SWNTs. Further research about the intrinsic electroactivity of proteins will surely provide extensive data regarding their structure, and protein–protein, protein–nucleic acid, or protein–drug interaction mechanisms. Label-free electrochemistry provides a powerful method for the challenge of developing effective biosensors for identifying, quantifying, and characterizing proteins.
10.0 µm
(a)
S4800 1.0 kV 1.6 mm × 100 k SE(M,LA0) 2005/12/19
500 nm
(b)
Figure 5. (a) Scanning electron microscopy (SEM) image of a single-walled carbon nanotube (SWNT)-dispersed chitosan matrix with the close-up of the same SEM image (b).
50 nA
100 nA
Current
100 nA
S4800 1.0 kV 1.6 mm × 3.50 k SE(M,LA0) 2005/12/19
7
(a)
0.5 0.6 0.7 0.8 Potential (V)
0.4 0.5 0.6 0.7 0.8 (b) Potential (V)
0.4 (c)
0.5 0.6 Potential (V)
Figure 6. Differential pulse voltammograms of amino acids at SWNT-Pt (red line) and bare Pt electrodes (blue line), (a) 10 µg ml−1 Tyr, (b) 5 µg ml−1 Tyr, (c) 5µg ml−1 Cys, in 50 mM phosphate buffer solution (pH 7.4).
8
ARRAY TECHNOLOGIES
7 LOCALIZED SURFACE PLASMON RESONANCE
Colloidal gold and silver have been attractive materials for architects, scientists, and artists for centuries because of their unique optical properties. Such properties are strongly dependent on the size, shape, and local environment of their nanostructures, as described by Mie theory.98 Briefly, as the size of a metal structure decreases from the bulk scale (meters to micrometers) to the nanoscale (<100 nm), the movement of electrons through the internal metal framework becomes restricted. As a result, metal nanoparticles display extinction bands in their UV–visual spectra, when the incident light resonates with the conduction band electrons at their surfaces. These charge-density oscillations are simply defined as local surface plasmon resonance (LSPR). The excitation of LSPR by light at an incident wavelength, where resonance would occur, results in the appearance of surface plasmon (SP) absorption bands. The intensity and position of the SP absorption bands are characteristic of the type of the nanomaterial, its diameter, and its distribution. LSPR is also highly sensitive to the changes of its surrounding environment.99,100 Thus, LSPR enables the detection of an immediate increase in thickness of a biomolecular layer on the surface of a substrate caused by a reaction between the solution component under study and the receptor layer immobilized on the surface. The high sensitivity of LSPR has been utilized to design biosensors for the label-free detection of biomolecular interactions between various ligands.101–104 However, almost all of the LSPR-based optical biosensors were designed in connection with gold and silver nanoparticles. The synthesis of the nanoparticles and the control of their diameters have been the most challenging problems. Since LSPR has extreme sensitivity toward size, a uniform layer of nanoparticles with the exact same size had to be built for reproducible results. Moreover, monitoring small shifts in the peak wavelength obtained from these nanoparticles was a difficult task for the complicated applications to real samples. Therefore, we focused our attention on the fabrication of gold-capped nanoparticle layer substrates.105 The gold-capped nanoparticle substrate brings several advantages along with its cost-effective and easy fabrication procedure. In addition, the optical characteristics
of the gold-capped nanoparticle layer substrate depend on the dielectric nanoparticle diameter and the thickness of the gold layer, which is deposited on the glass substrate surface. These characteristics may be attributed to a similar phenomenon described for the plasmon resonance spectra of the nanoshell-structured nanoparticles. As reported by Petit et al.106 the variations in the intensity of the plasmon resonances depended on the cluster size. The electronic relaxation after the electromagnetic excitation is accelerated due to the decrease in damping with increasing particle size.107 8 LSPR-BASED GENE AND PROTEIN SENSORS
Advanced chemical and biological nanosensors for the detection of single molecules are under development.108 Chau et al.109 have recently reported a novel reflection-based LSPR fiber-optic probe for chemical and biochemical sensing. The sensor is based on intensity measurement of the internal reflected light at a fixed wavelength from an optical fiber where the extinction cross-section of self-assembled gold nanoparticles on the unclad portion of the optical fiber changes with the different refractive index of the environment near the gold surface. They have achieved the detection of “spectroscopically silent” Ni2+ ions and the detection of streptavidin and staphylococcal enterotoxin B at the pM level. Silver particles generated by the evaporation–condensation method were deposited on the solgel-derived silica film or the silica glass substrate to form LSPR sensors.110 We constructed the LSPR-based nanochip with a unique core-shell-structured nanoparticle layer (Figure 7a), the surface-modified silica nanoparticle (particle diameter: 100 nm) was used as the core, and the shell was applied with the top (30 nm) and the bottom (40 nm) gold layers that were deposited using thermal deposition. When the top gold layer was deposited on the nanoparticle layer–modified substrates using thermal evaporator, we could observe the LSPR band at 520 nm with a simple optical probe. The multiarray (20 × 60 mm2 ) of core-shell-structured nanoparticle layer substrate was used for biosensor applications (Figure 7b).
LABEL-FREE GENE AND PROTEIN SENSORS
9
Optical probe
Light source
Incident light
Detector
Reflected light Au top layer
Au bottom layer Ti layer
(a)
Surface-modified silica nanoparticle
Slide glass
1 cm
Absorbance
(b)
Optical probe
Addition of samples
Wavelength Antibody
(c)
Antibody immobilization
Antigen
Antigen–antibody reaction
Incident light
Reflected light
LSPR measurement
Figure 7. (a) Construction of the multiarray LSPR-based nanochip. The surface-modified silica nanoparticles were aligned onto the gold-deposited glass substrate surface. Consecutively, the top gold layer was evaporated onto the silica nanoparticle layer, (b) photograph of the nanoparticle layer substrate, (c) illustration for the experimental flow of the LSPR-based immunosensor application.
We used PNAs as the biorecognition layer on our core-shell nanoparticle layer substrate and detected PNA–PNA and PNA–DNA hybridization reactions.111 Moreover, the nanoparticle layer substrate was applied as an immunosensor. The antifibrinogen antibody was immobilized
onto the nanoparticle layer substrate surface (Figure 7c). Different concentrations of fibrinogen were introduced to the antifibrinogen antibodyimmobilized nanoparticle layer substrate surface, and the change in the absorption spectrum, caused by the antigen–antibody reaction, was observed.
10
ARRAY TECHNOLOGIES
By using this antifibrinogen antibody-immobilized nanoparticle layer substrate, the detection limit for fibrinogen was 10 ng ml−1 . 9 CONCLUSIONS
Here, we would like to quote Label-free Methods Are Not Problem Free from Emma Hitt.112 On the other hand, there have been many significant and promising advances to solve the problems of labelfree methods and improve them since the publication of her article.112 Especially for the commonly sample-limited applications of DNA and protein analysis, electrochemical and LSPR methods have become particularly well suited, as they can be miniaturized and multiplexed relatively easily in connection with nanomaterials; such as gold nanoparticles and CNTs. However, the superiority of label-free electrochemistry would be due to its ability to provide new and complementary information about the oxidation/reduction process. LSPR biosensors have a promising potential in a wide variety of applications. The inherently small size of the nanosensors and nondestructive nature of the optical measurement are significant advantages over macroscale biosensors or electrochemical schemes that usually do not permit the recovery of the target analyte. Eventually, we anticipate the development of credit card–sized sensor arrays in connection with electrochemical or LSPR-based methods in the near future. REFERENCES 1. J. Watson and F. Crick, A structure for deoxyribose nucleic acid. Nature, 1953, 171, 737–738. 2. E. Palecek, Past, present and future of nucleic acids electrochemistry. Talanta, 2002, 56, 809–819. 3. T. G. Drummond, M. G. Hill, and J. K. Barton, Electrochemical DNA sensors. Nature Biotechnology, 2003, 21, 1192–1199. 4. K. Kerman, M. Kobayashi, and E. Tamiya, Recent trends in electrochemical DNA biosensor technology. Measurement Science and Technology, 2004, 15, R1–R11. 5. L. Murphy, Biosensors and bioelectrochemistry. Current Opinion in Chemical Biology, 2006, 10, 177–184. 6. C. K. O’Sullivan and G. G. Guilbault, Commercial quartz crystal microbalances–theory and applications. Biosensors and Bioelectronics, 1999, 14, 663–670. 7. K. A. Marx, Quartz crystal microbalance: a useful tool for studying thin polymer films and complex biomolecular systems at the solution-surface interface. Biomacromolecules, 2003, 4, 1099–1120.
8. R. Karlsson, SPR for molecular interaction analysis: a review of emerging application areas. Journal of Molecular Recognition, 2004, 17, 151–161. 9. P. Pattnaik, Surface plasmon resonance: applications in understanding receptor-ligand interaction. Applied Biochemistry and Biotechnology, 2005, 126, 79–92. 10. E. Palecek, M. Fojta, F. Jelen, and V. Vetterl, Electrochemical Analysis of Nucleic Acids, in Encyclopedia of Electrochemistry, Bioelectrochemistry, A. J. Bard, M. Stratmann, and G. S. Wilson (eds), John Wiley & Sons, Weinheim, Germany, 2002, Vol. 9, pp. 365–429. 11. S. Steenken, Purine bases, nucleosides, and nucleotides: aqueous solution redox chemistry and transformation reactions of their radical cations and e- and OH adducts. Chemical Reviews, 1989, 89, 503–520. 12. A. M. Oliveira Brett, S. H. P. Serrano, J. A. P. Piedade, Electrochemistry of DNA, in Comprehensive Chemical Kinetics, Applications of Kinetic Modelling 37, R. G. Compton and G. Hancock (eds), Elsevier, Oxford, 1999, pp. 91–119. 13. W. Saenger and C. R. Cantor, Principles of Nucleic Acid Structure, Springer, New York, 1984. 14. B. Halliwell and J. M. C. Gutteridge, Free Radicals in Biology and Medicine, 3rd Edn, Oxford University Press, New York, 1999. 15. A. M. Oliveira-Brett, J. A. P. Piedade, and S. H. P. Serrano, Electrochemical oxidation of 8-oxoguanine. Electroanalysis, 2000, 12, 969–973. 16. I. A. Rebelo, J. A. P. Piedade, and A. M. Oliveira-Brett, Development of an HPLC method with electrochemical detection of femtomoles of 8-oxo-7,8-dihydroguanine and 8-oxo-7,8-dihydro−2 deoxyguanosine in the presence of uric acid. Talanta, 2004, 63, 323–331. 17. C. M. A. Brett, A. M. Oliveira Brett, and S. H. P. Serrano, On the adsorption and electrochemical oxidation of DNA at glassy carbon electrodes. Journal of Electroanalytical Chemistry, 1994, 366, 225–231. 18. A. M. Oliveira Brett, L. A. Silva, and C. M. A. Brett, Adsorption of guanine, guanosine, and adenine at electrodes studied by differential pulse voltammetry and electrochemical impedance. Langmuir, 2002, 18, 2326–2330. 19. A. M. Oliveira Brett and F.-M. Matysik, Voltammetric and sonovoltammetric studies on the oxidation of thymine and cytosine at a glassy carbon electrode. Journal of Electroanalytical Chemistry, 1997, 429, 95–99. 20. A. M. Oliveira-Brett, V. Diculescu, and J. A. P. Piedade, Electrochemical oxidation mechanism of guanine and adenine using a glassy carbon microelectrode. Bioelectrochemistry, 2002, 55, 61–62. 21. P. Kara, D. Ozkan, A. Erdem, K. Kerman, S. Pehlivan, F. Ozkinay, D. Unuvar, G. Itirli, and M. Ozsoz, Detection of achondroplasia G380R mutation from PCR amplicons by using inosine modified carbon electrodes based on electrochemical DNA chip technology. Clinica Chimica Acta, 2003, 336, 57–64. 22. K. Kerman, Y. Morita, Y. Takamura, and E. Tamiya, Label-free electrochemical detection of DNA hybridization on gold electrode. Electrochemistry Communications, 2003, 5, 887–891.
LABEL-FREE GENE AND PROTEIN SENSORS 23. B. Meric, K. Kerman, D. Ozkan, P. Kara, and M. Ozsoz, Indicator-free electrochemical DNA biosensor based on adenine and guanine signals. Electroanalysis, 2002, 14, 1245–1250. 24. K. Kerman, D. Ozkan, P. Kara, A. Erdem, B. Meric, P. E. Nielsen, and M. Ozsoz, Label-free bioelectronic detection of point mutation by using peptide nucleic acid probes. Electroanalysis, 2003, 15, 667–670. 25. K. Kerman, Y. Morita, Y. Takamura, M. Ozsoz, and E. Tamiya, DNA-directed attachment of carbon nanotubes for enhanced label-free electrochemical detection of DNA hybridization. Electroanalysis, 2004, 16, 1667–1672. 26. A. Erdem and M. Ozsoz, Electrochemical DNA biosensors based on DNA–drug interactions. Electroanalysis, 2002, 14, 965–974. 27. J. A. P. Piedade, I. R. Fernandes, and A. M. OliveiraBrett, Electrochemical sensing of DNA–adriamycin interactions. Bioelectrochemistry, 2002, 56, 81–83. 28. B. Meric, K. Kerman, D. Ozkan, P. Kara, A. Erdem, O. Kucukoglu, E. Erciyas, and M. Ozsoz, Electrochemical biosensor for the interaction of DNA with the alkylating agent 4,4 -dihydroxy chalcone based on guanine and adenine signals. Journal of Pharmaceutical and Biomedical Analysis, 2002, 30, 1339–1346. 29. K. Kerman, B. Meric, D. Ozkan, P. Kara, A. Erdem, and M. Ozsoz, Electrochemical DNA biosensor for the determination of benzo[α]pyrene–DNA adducts. Analytica Chimica Acta, 2001, 450, 45–52. 30. F. Lucarelli, A. Kicela, I. Palchetti, G. Marrazza, and M. Mascini, Electrochemical DNA biosensor for analysis of wastewater samples. Bioelectrochemistry, 2002, 38, 113–118. 31. M. Ozsoz, A. Erdem, P. Kara, K. Kerman, and D. Ozkan, Electrochemical biosensor for the detection of interaction between arsenic trioxide and DNA based on guanine signal. Electroanalysis, 2003, 15, 613–619. 32. J. Wang and A. N. Kawde, Amplified label-free electrical detection of DNA hybridization. Analyst, 2002, 127, 383–386. 33. D. O. Ariksoysal, H. Karadeniz, A. Erdem, A. Sengonul, A. A. Sayiner, and M. Ozsoz, Label-free electrochemical hybridization genosensor for the detection of hepatitis B virus genotype on the development of lamivudine resistance. Analytical Chemistry, 2005, 77, 4908–4917. 34. A. Erdem, M. I. Pividori, A. Lermo, A. Bonani, M. del Valle, and S. Alegret, Genomagnetic assay based on label-free electrochemical detection using magnetocomposite electrodes. Sensors and Actuators B, 2006, 114, 591–598. 35. J. Wang, Carbon-nanotube based electrochemical biosensors: a review. Electroanalysis, 2004, 17, 7–14. 36. E. Katz and I. Willner, Biomolecule-functionalized carbon-nanotubes: applications in nanobioelectronics. ChemPhysChem, 2004, 5, 1084–1104. 37. J. Li, H. T. Ng, A. Cassell, W. Fan, H. Chen, Q. Ye, J. Koehne, J. Han, and M. Meyyappan, Carbon nanotube nanoelectrode array for ultrasensitive DNA detection. Nano Letters, 2003, 3, 597–602. 38. K. Kerman, Y. Morita, Y. Takamura, and E. Tamiya, Escherichia coli single-strand binding protein-DNA interactions on carbon-nanotube-modified electrodes
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50. 51.
52.
53.
11
from a label-free electrochemical hybridization sensor. Analytical and Bioanalytical Chemistry, 2005, 381, 1114–1121. M. Zheng, A. Jagota, E. D. Semke, B. A. Diner, R. S. Mclean, S. R. Lustig, R. E. Richardson, and N. G. Tassi, DNA-assisted dispersion and separation of carbon nanotubes. Nature Materials, 2003, 2, 338–342. M. Zheng, A. Jagota, M. S. Strano, A. P. Santos, P. Barone, S. G. Chou, B. A. Diner, M. S. Dresselhaus, R. S. Mclean, G. B. Onoa, G. G. Samsonidze, E. D. Semke, M. Usrey, and D. J. Walls, Structure-based carbon nanotube sorting by sequence-dependent DNA assembly. Science, 2003, 302, 1545–1548. F. Valentini, A. Amine, S. Orlanducci, M. L. Terranova, and G. Palleschi, Carbon nanotube purification: preparation and characterization of carbon nanotube paste electrodes. Analytical Chemistry, 2003, 75, 5413–5421. P. Estrela, P. Migliorato, H. Takiguchi, H. Fukushima, and S. Nebashi, Electrical detection of biomolecular interactions with metal-insulator-semiconductor diodes. Biosensors and Bioelectronics, 2005, 20, 1580–1586. P. Estrela, A. G. Stewart, F. Yan, and P. Migliorato, Field effect detection of biomolecular interactions. Electrochimica Acta, 2005, 50, 4995–5000. Y. Cui, Q. Wei, H. Park, and C. M. Lieber, Nanowire nanosensors for highly sensitive and selective detection of biological and chemical species. Science, 2001, 293, 1289–1292. F. Patolsky, G. Zheng, O. Hayden, M. Lakadamyali, X. Zhuang, and C. M. Lieber, Electrical detection of single viruses. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101, 14017–14022. W. U. Wang, C. Chen, K. H. Lin, Y. Fang, and C. M. Lieber, Label-free detection of small-molecule-protein interactions by using nanowire nanosensors. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102, 3208–3212. G. Zheng, F. Patolsky, Y. Cui, W. U. Wang, and C. M. Lieber, Multiplexed electrical detection of cancer markers with nanowire sensor arrays. Nature Biotechnology, 2005, 23, 1294–1301. J. Xiang, W. Lu, Y. Hu, Y. Wu, H. Yan, and C. M. Lieber, Ge/Si nanowire heterostructures as highperformance field-effect transistors. Nature, 2006, 441, 489–493. S. J. Tans, A. R. M. Verschueren, and C. Dekker, Roomtemperature transistor based on a single carbon nanotube. Nature, 1998, 393, 49–52. P. Avouris, Molecular electronics with carbon nanotubes. Accounts of Chemical Research, 2002, 35, 1026–1034. J. Kong, N. R. Franklin, C. Zhou, M. G. Chapline, S. Peng, K. Cho, and H. Dai, Nanotube molecular wires as chemical sensors. Science, 2000, 287, 622–625. P. G. Collins, K. Bradley, M. Ishigami, and A. Zettl, Extreme oxygen sensitivity of electronic properties of carbon nanotubes. Science, 2000, 287, 1801–1804. R. J. Chen, S. Bangsaruntip, K. A. Drouvalakis, N. Wong Shi Kam, M. Shim, Y. Li, W. Kim, P. J. Utz, and H. Dai, Noncovalent functionalization of carbon nanotubes for highly specific electronic biosensors. Proceedings of the
12
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
ARRAY TECHNOLOGIES National Academy of Sciences of the United States of America, 2003, 100, 4984–4989. P. E. Nielsen, M. Egholm, R. H. Berg, and O. Buchardt, Sequence-selective recognition of DNA by strand displacement with a thymine-substituted polyamide. Science, 1991, 254, 1497–1500. P. Wittung, P. E. Nielsen, O. Buchardt, M. Egholm, and B. Norden, DNA-like double helix formed by peptide nucleic acid. Nature, 1994, 368, 561–563. K. Kerman, Y. Morita, Y. Takamura, E. Tamiya, K. Maehashi, and K. Matsumoto, Peptide-nucleic acidmodified carbon nanotube field-effect transistor for ultrasensitive real-time detection of DNA hybridization. Nanobiotechnology, 2005, 1, 65–70. J. Janata and M. Josowicz, Conducting polymers in electronic chemical sensors. Nature Materials, 2003, 2, 19–24. N. Lassalle, P. Mailley, E. Vieil, T. Livache, A. Roget, J. P. Correia, and L. M. Abrantes, Electronically conductive polymer grafted with oligonucleotides as electrosensors of DNA preliminary study of real time monitoring by in situ techniques. Journal of Electroanalytical Chemistry, 2001, 509, 48–57. H. Korri-Youssoufi, F. Garnier, P. Srivastava, P. Godillot, and A. Yassar, Toward bioelectronics: specific DNA recognition based on an oligonucleotide-functionalized polypyrrole. Journal of the American Chemical Society, 1997, 119, 7388–7389. D. S. Minehan, K. A. Marx, and S. K. Tripathy, Kinetics of DNA binding to electrically conducting polypyrrole films. Macromolecules, 1994, 27, 777–783. J. Wang, M. Jiang, A. Fortes, and B. Mukherjee, New label-free DNA recognition based on doping nucleicacid probes within conducting polymer films. Analytica Chimica Acta, 1999, 402, 7–12. J. Wang and M. Jiang, Toward genolelectronics: nucleic acid doped conducting polymers. Langmuir, 2000, 16, 2269–2274. A. Mugweru and J. F. Rusling, Catalytic squarewave voltammetric detection of DNA with reversible metallopolymer-coated electrodes. Electrochemistry Communications, 2001, 3, 406–409. E. Komarova, M. Aldissi, and A. Bogomolova, Direct electrochemical sensor for fast reagent-free DNA detection. Biosensors and Bioelectronics, 2005, 21, 182–189. B. Piro, J. Haccoun, M. C. Pham, L. D. Tran, A. Rubin, H. Perrot, and C. Gabrielli, Study of the DNA hybridization transduction behavior of a quinonecontaining electroactive polymer by cyclic voltammetry and electrochemical impedance spectroscopy. Journal of Electroanalytical Chemistry, 2005, 577, 155–165. H. Peng, C. Soeller, N. Vigar, P. A. Kilmartin, M. B. Cannell, G. A. Bowmaker, R. P. Cooney, and J. TravasSejdic, Label-free electrochemical DNA sensor based on functionalized conducting polymer. Biosensors and Bioelectronics, 2005, 20, 1821–1828. C. dos Santos Riccardi, H. Yamanaka, M. Josowicz, J. Kowalik, B. Mizaikoff, and C. Kranz, Label-free DNA detection based on modified conducting polypyrrole films at microelectrodes. Analytical Chemistry, 2006, 78, 1139–1145.
68. M. Bart, E. C. A. Stigter, H. R. Stapert, G. J. de Jomg, and W. P. van Bennekom, On the response of a labelfree interferon-γ immunosensor utilizing electrochemical impedance spectroscopy. Biosensors and Bioelectronics, 2005, 21, 49–59. 69. E. Katz and I. Willner, Probing biomolecular interactions at conductive and semiconductive surfaces by impedance spectroscopy: routes to impedimetric immunosensors, DNA-sensors, and enzyme biosensors. Electroanalysis, 2003, 15, 913–947. 70. J. Wang, J. A. Profitt, M. J. Pugia, and I. Suni, Au nanoparticle conjugation for impedance and capacitance signal amplification in biosensors. Analytical Chemistry, 2006, 78, 1769–1773. 71. K.-S. Ma, H. Zhou, J. Zoval, and M. Madou, DNA hybridization detection by label-free versus impedance amplifying label with impedance spectroscopy. Sensors and Actuators B, 2006, 114, 58–64. 72. C.-Z. Li, Y. Liu, and J. H. T. Luong, Impedance sensing of DNA binding drugs using gold substrates modified with gold nanoparticles. Analytical Chemistry, 2005, 77, 478–485. 73. C. Gautier, C. Cougnon, J.-F. Pilard, and N. Casse, Label-free detection of DNA hybridization based on EIS investigation of conducting properties of functionalized polythiophene matrix. Journal of Electroanalytical Chemistry, 2006, 587, 276–283. 74. L. Yang, W. Wei, X. Gao, J. Xia, and H. Tao, A new antibody immobilization strategy based on electrodeposition of nanometer-sized hydroxyapatite for label-free capacitive immunosensor. Talanta, 2005, 68, 40–46. 75. C. Tlili, H. Korri-Youssoufi, L. Ponsonnet, C. Martelet, and N. J. Jaffrezic-Renault, Electrochemical impedance probing of DNA hybridization on oligonucleotidefunctionalized polypyrrole. Talanta, 2005, 68, 131–137. 76. V. Dharuman, T. Grunwald, E. Nebling, J. Albers, L. Blohm, and R. Hintsche, Label-free impedance detection of oligonucleotide hybridisation on interdigitated ultramicroelectrodes using electrochemical redox probes. Biosensors and Bioelectronics, 2005, 21, 645–654. 77. X. Yu, R. Lv, Z. Ma, Z. Liu, Y. Hao, Q. Li, and D. Xu, An impedance array biosensor for detection of multiple antibody-antigen interactions. Analyst, 2006, 131, 745–750. 78. R. M¨oller, R. D. Powell, J. H. Hainfeld, and W. Fritzsche, Enzymatic control of metal deposition as key step for a low-background electrical detection for DNA chips. Nano Letters, 2005, 5, 1475–1482. 79. C. Tuerk and L. Gold, Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science, 1990, 249, 505–510. 80. A. D. Ellington and J. W. Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature, 1990, 346, 818–822. 81. A. E. Radi, J. L. Acero Sanchez, E. Baldrich, and C. K. O’Sullivan, Reagentless, reusable, ultrasensitive electrochemical molecular beacon aptasensor. Journal of the American Chemical Society, 2006, 128, 117–124. 82. D. Xu, D. Xu, X. Yu, Z. Liu, W. He, and Z. Ma, Labelfree electrochemical detection of aptamer-based array electrodes. Analytical Chemistry, 2005, 77, 5107–5113.
LABEL-FREE GENE AND PROTEIN SENSORS 83. H. Cai, T. M.-H. Lee, and I.-M. Hsing, Label-free protein recognition using an aptamer-based impedance measurement assay. Sensors and Actuators B, 2006, 114, 433–437. 84. A. E. Radi, J. L. Acero Sanchez, E. Baldrich, and C. K. O’Sullivan, Reusable impedimetric aptasensor. Analytical Chemistry, 2005, 77, 6320–6323. 85. M. C. Rodriguez, A.-N. Kawde, and J. Wang, Aptamer biosensor for label-free impedance spectroscopy detection of proteins based on recognition-induced switching of the surface charge. Chemical Communications, 2005, 34, 4267–4269. 86. M. J. Eddowes and A. O. H. Hill, Novel method for the investigation of the electrochemistry of metalloproteins: cytochrome c. Journal of the Chemical Society, Chemical Communications, 1977, 21, 771–772. 87. P. Yeh and T. Kuwana, Reversible electrode reaction of cytochrome c. Chemistry Letters, 1977, 10, 1145–1148. 88. A. Christenson, E. Dock, L. Gorton, and T. Ruzgas, Direct heterogeneous electron transfer of theophylline oxidase. Biosensors and Bioelectronics, 2004, 20, 176–183. 89. Z. Dai, X. Xu, and H. Ju, Direct electrochemistry and electrocatalysis of myoglobin immobilized on a hexagonal mesoporous silica matrix. Analytical Biochemistry, 2004, 332, 23–31. 90. M. Heyrovsky, Early polarographic studies on proteins. Electroanalysis, 2004, 16, 1067–1073. 91. J. A. Reynaud, B. Malfoy, and A. Bere, The electrochemical oxidation of three proteins: RNAase A, bovine serum albumin and concanavalin A at solid electrodes. Journal of Electroanalytical Chemistry, 1980, 116, 595–606. 92. V. Brabec and I. Schindlerova, Electrochemical behavior of proteins at graphite electrodes. Part III. The effect of protein adsorption. Bioelectrochemistry and Bioenergetics, 1981, 8, 451–458. 93. V. Brabec and V. Mornstein, Electrochemical behavior of proteins at graphite electrodes. II. Electrooxidation of amino acids. Biophysical Chemistry, 1980, 12, 159–165. 94. E. Palecek, F. Jelen, C. Teijeiro, V. Fucik, and T. M. Jovin, Biopolymer-modified electrodes in the voltammetric determination of nucleic acids and proteins at the submicrogram level. Analytica Chimica Acta, 1993, 273, 175–186. 95. L. Moreno, A. Merko¸ci, S. Alegret, S. Hern´andezCassou, and J. Saurina, Analysis of amino acids in complex samples by using voltammetry and multivariate calibration methods. Analytica Chimica Acta, 2004, 504, 251–257. 96. E. Palecek, M. Masarik, R. Kizek, K. Kuhlmeier, J. Hassmann, and J. Sch¨ulein, Sensitive electrochemical determination of unlabeled MutS protein and detection of point mutations in DNA. Analytical Chemistry, 2004, 76, 5930–5936. 97. M. Vestergaard, K. Kerman, M. Saito, N. Nagatani, Y. Takamura, and E. Tamiya, A rapid labelfree electrochemical detection and kinetic study of Alzheimer’s amyloid beta aggregation. Journal of the American Chemical Society, 2005, 127, 11892–11893.
13
98. G. Mie, Grundlagen einer theorie der materie. Annalen Der Physik, 1908, 25, 377–445. 99. R. Jin, Y. Cao, C. A. Mirkin, K. L. Kelly, G. C. Schatz, and J. G. Zheng, Photoinduced conversion of silver nanospheres to nanoprisms. Science, 2001, 294, 1901–1903. 100. N. P. Prasad, Nanophotonics, John Wiley & Sons, New York, 2004. 101. A. J. Haes and R. P. Van Duyne, A unified view of propagating and localized surface plasmon resonance biosensors. Analytical and Bioanalytical Chemistry, 2004, 379, 920–930. 102. N. Nath and A. Chilkoti, Label-free biosensing by surface plasmon resonance of nanoparticles on glass: optimization of nanoparticle size. Analytical Chemistry, 2004, 76, 5370–5378. 103. A. J. Haes, L. Chang, W. L. Klein, and R. P. Van Duyne, Detection of a biomarker for Alzheimer’s disease from synthetic and clinical samples using a nanoscale optical biosensor. Journal of the American Chemical Society, 2005, 127, 2264–2271. 104. D. A. Stuart, A. J. Haes, C. R. Yonzon, E. M. Hicks, and R. P. Van Duyne, Biological applications of localised surface plasmonic phenomenae. IEEE Proceedings: Nanobiotechnology, 2005, 152, 13–32. 105. T. Endo, S. Yamamura, N. Nagatani, Y. Morita, Y. Takamura, and E. Tamiya, Localized surface plasmon resonance based optical biosensor using surface modified nanoparticle layer for label-free monitoring of antigen–antibody reaction. Science and Technology of Advanced Materials, 2005, 6, 491–500. 106. C. Petit, P. Lixon, and M. P. Pileni, Synthesis of cadmium sulfide in situ in reverse micelles. 2. Influence of the interface on the growth of the particles. Journal of Physical Chemistry, 1990, 94, 1598–1603. 107. T. S. Ahmadi, S. L. Logunov, M. A. El-Sayed, in Nanostructured Materials: Clusters, composites, and thin films, V. M. Shalaev and M. Moskovits (eds), American Chemical Society, Washington, 1997, pp. 125–140. 108. C. R. Yonzon, D. A. Stuart, X. Zhang, A. D. McFarland, C. L. Haynes, and R. P. Van Duyne, Towards advanced chemical and biological nanosensorsan overview. Talanta, 2005, 67, 438–448. 109. L.-K. Chau, Y.-F. Lin, S.-F. Cheng, and T.-J. Lin, Fiberoptic chemical and biochemical probes based on localized surface plasmon resonance. Sensors and Actuators B, 2006, 113, 100–105. 110. N. Hashimoto, T. Hashimoto, T. Teranishi, H. Nasu, and K. Kamiya, Cycle performance of sol-gel optical sensor based on localized surface plasmon resonance of silver particles. Sensors and Actuators B, 2006, 113, 382–388. 111. T. Endo, K. Kerman, N. Nagatani, Y. Takamura, and E. Tamiya, Label-free detection of peptide nucleic acidDNA hybridization using localized surface plasmon resonance based optical biosensor. Analytical Chemistry, 2005, 77, 6976–6984. 112. E. Hitt, Label-free methods are not problem free. Drug Discovery and Development, 2004, 9, 1–6.
59 An Electrochemical Biochip Sensor for the Detection of Pollutants Rachela Popovtzer,1 Yosi Shacham-Diamand1 and Judith Rishpon2 1
Department of Physical Electronics, Tel Aviv University, Ramat-Aviv, Israel and 2 Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Ramat-Aviv, Israel
1 INTRODUCTION
In the present era, the increasing concern regarding the effect of environmental pollution on the public human health and well-being have led to the necessity of developing sensors to monitor air, wastewaters, and drinking water. The threat of chemical warfare terrorism and the pollution of ground water due to rapid industrialization stimulated numerous studies and investigations of methods to detect the toxicity in water. Both acute and chronic toxicity are important, although they pose different problems. In this chapter we focus mainly on acute toxicity detection, as it requires shorter measurement time and simpler decision-making process than chronic toxicity detection. Acute toxicity detection also poses severe immediate damage and has significant implications to society. The use of living organisms as active components in electronic devices is an innovative and challenging area combining recent progress in molecular biology and micro technology. Bacterial-based biosensor chips can be defined as measurement electronic devices that use living cells as sensing elements. They can detect the signal and also record, process, and analyze the obtained information. The significance of these “whole-cell” biosensors lies in their capability to provide functional physiological information
regarding the effect of chemicals on living systems. The conventional sensors such as molecular, enzymes, or DNA sensors are based on specific interactions and structural recognition within the biological materials; thus, they can only identify and quantify anticipated chemicals. Whole-cellbased biosensor chips can be applied in many fields including health care and medical applications, pharmaceutical screening, and environmental monitoring. The detection mechanism combines a biologically sensitive element with a physical or chemical transducer to detect the presence of specific or nonspecific compounds in a given external environment. There are many detection methods used in biosensors, sensors and biochips, while the most common are mechanical, optical, and electrochemical. The sensors are expected to provide highly sensitive, accurate, and rapid results. In addition, monitoring environmental pollution in the field requires robust, miniaturized, and portable sensors. In this study we utilized the electrochemical detection method, which proved to be simple, sensitive, provides fast response time and can be performed using compact and mobile equipment.1 The portability of such a system is essential for on-site environmental monitoring, and for various medical applications. Miniaturization of electrochemical devices is highly important
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
because of portability, convenient handling, and reduced requirement of reagents.
2 ELECTROCHEMICAL NANOBIOCHIP FOR TOXICITY DETECTION IN WATER
An electrochemical nanobiochip for water toxicity detection is presented. In this chapter we describe chip design, fabrication, and performance. Bacteria, which have been genetically engineered to respond to environmental stress, act as a sensor element and trigger a sequence of processes, which leads to generation of electrical current. The specific design and process of the electrochemical “lab on a chip”, which integrates the recombinant bacteria provides highly accurate, sensitive, and rapid detection of acute toxicity in water. In the first part of this chapter, we will describe the design and fabrication of the silicon chip. Then the general concept of the bacterial genetic engineering and the cascade of mechanisms by which the bacteria generate a current signal will be explained. The second part of the chapter contains experimental results of toxicity detection in water; followed by extensive discussion of the efficiency of the present method in comparison to other available methods. Finally the possible use of the electrochemical “lab on a chip”-based whole-cell sensors for different applications is described.
(a)
3 DEVICE FABRICATION
The silicon-based biochip has been designed and fabricated using standard microsystem-technology (MST) methods. Its architecture includes an array of miniaturized electrochemical cells. The nanovolume chambers (i.e., the electrochemical cells) contain the bacteria, which are brought into contact with the water to be examined. The cylindrical chambers hold 100 nl volume each. All arrays include positive and negative control chambers. The device is manufactured in two parts: (i) a disposable chip—with the nanochambers containing the bacteria, and (ii) a reusable chip—with an interface to electronic circuitry that includes a multiplexer, potentiostat, temperature control, and a pocket PC for sensing and data analysis. This setting allows continuous reusing for multiple measurements. The chip was produced from silicon, and contains an array of eight miniaturized electrochemical cells. Each electrochemical cell consists of three circular-shaped electrodes, surrounded by an insulating silicon nitride layer: (i) gold working electrode, (ii) gold counter electrode and (iii) Ag/AgCl reference electrode. The electrodes are made by gold sputtering, microlithography, and by selectively depositing Ag and anodizing it in a chloride-containing solution for the reference electrode. The chambers walls were constructed from photo-polymerized polyimide (SU-8) as shown in Figure 1. The silicon chip was wire bonded to
(b)
Figure 1. Image of the electrochemical chip. (a) Silicon chip contains an array of eight miniaturized electrochemical cells with external pads. (b) The electrodes without the top layer (SU-8). Each electrochemical cell consists of three circular-shaped electrodes: gold working and counter electrodes and Ag/AgCl reference electrode.
ELECTROCHEMICAL BIOCHIP SENSOR FOR DETECTION OF POLLUTANTS
a plastic chip that was interfacing the electronic circuit. The signal sensing is performed by the handheld palm-potentiostat with an interface to electronic circuitry for electrode signal regulation and detection (Palm Instruments BV-2004). The electronics consists of eight independent duplicate circuits of electrochemical cells, which are temperature controlled. A potential is applied between a working and a reference electrode in each electrochemical cell, and the output current is measured. 4 BACTERIAL-BASED BIOCHIPS
The most important reason for utilizing living cells as biosensors lies in their capability to provide functional information, that is, information about the effect of a stimulus on living organisms. The aim of the present biochip is to offer the unique “functionality” sensing capability. It answers the question “Is the water toxic?” and it does not intend to perform chemical analysis or to identify the nature of the toxicant. These whole-cell sensing systems can be visualized as an environmental switch, which is turned on in the presence of toxins or stressful conditions. In many cases, functional rather than analytical information is ultimately desired. In other applications, it complements and adds a special feature to a system by emulating the behavior of living entities. 5 GENETICALLY ENGINEERED BACTERIA
Whole-cell-based biosensors are intact, living unicellular organisms that have been genetically engineered to produce a measurable signal in response to a specific chemical or physical perturbation in their environment. They contain two essential genetic elements: a promoter gene and a reporter gene. The promoter gene is turned on (transcribed) when the toxic chemical, or target agent, is present in the cell’s environment. In a normal cell, the promoter gene is coupled to number of genes that are transcribed and then translated into proteins that help the cell in either combating or adapting to the toxicant. In the case of a recombinant wholecell biosensor, this promoter gene is coupled to his normal reporter genes, and additionally, to a specific reporter gene that was chosen because of
3
his ability to be easily assayed and to produce a detectable signal. Therefore, when the promoter gene senses a toxicant, he activates the reporter genes. Activation of the reporter gene leads to production of reporter proteins that ultimately generate some type of detectable signal. Therefore, the presence of a signal indicates that the biosensor has sensed chemical interference in its environment. This work was carried out using Escherichia coli (MC1061), which is the most convenient tool for genetic engineering, and a suitable host cell for carrying a variety of promoter–reporter fusions. 6 PROMOTERS FOR CELL-BASED BIOSENSORS
Three different recombinant strains of E. coli that contain the fabA (responsive to membrane damage-related stress), dnaK and grpE (both responsive to protein damage-related stress) promoters, were fused to the bacterial lacZ gene. Using different types of promoters that respond to a variety of stresses, mechanisms can react in response to a broad spectrum of chemicals. 7 REPORTERS FOR CELL-BASED BIOSENSORS
Reporter genes are nucleic acid sequences that can be easily assayed. In recombinant cell-based biosensors, the reporter gene is fused to a promoter of a gene whose expression is preferred to be monitored. There are several commonly used reporter proteins such as green fluorescent protein (GFP), bacterial luciferase (Lux), and β-galactosidase. In this work, the different promoters were fused to the lacZ reporter gene, which was monitored using an electrochemical assay of β-galactosidase activity. The activity of β-galactosidase is determined by using the substrate p-aminophenyl-β-Dgalactopyranoside (PAPG). 8 BIOELECTROCHEMISTRY: BACTERIAL CURRENT GENERATION
Several detection methods for β-galactosidase are available including colorimetric histochemical, fluorescent, luminescent, and electrochemical. These detection strategies are dependent
4
ARRAY TECHNOLOGIES
on the substrates used. The most common substrates employed for β-Gal are o-nitrophenyl-β-Dgalactopyranoside (ONPG) for colorimetric detection, 5-bromo-4-chloro-3-indolyl-β-D-galactoside (X-gal) for histochemical detection, 4-methylumbelliferyl-β-D-galactopyranoside (MUG) for fluorometry, 1,2-dioxetane substrates for luminescence, and PAPG for electrochemical analysis. In our work we utilize the electrochemistry detection method that requires the addition of an external substrate (PAPG), but it does not require lysis or permeabilization of the cells and thus is ideal for on-line continuous measurement of enzymatic activity.2 Moreover, this detection strategy can be performed in turbid solutions and under anaerobic conditions. Recombinant bacteria, which were genetically engineered to respond to environmental stress, act as a sensing element and trigger a cascade mechanism: (i) In the presence of a toxin, this promoter is activated, and induces the production of the reporter enzyme β-galactosidase. (ii) As the enzyme is produced, the activity of βgalactosidase is determined by using the substrate PAPG. (iii) The product of the enzymatic reaction, p-aminophenol (PAP), is oxidized on the working electrode. This oxidation current is monitored and visualized on the PC screen.
electronic unit for sensing and data analysis. A fixed potential was applied between the working and the reference electrode in each electrochemical cell in the array on the chip by the potentiostat, and the output current signal was measured. In these experiments we used recombinant E. coli bacteria bearing plasmid with one of the following promoters: dnaK, grpE, or fabA. These promoters were fused to the reporter enzyme β-galactosidase. The toxic chemical, in each experiment, was introduced to the bacterial samples in the presence of the substrate PAPG. Immediately after (∼1 s), the suspensions were placed in the electrochemical cells. The response of the bacteria to the different toxic chemicals was measured on line by applying a potential of 220 mV. The substrate, PAPG, was added to a final concentration of 0.8 mg ml−1 (100 nl total volume). The product of the enzymatic reaction (PAP) was monitored by its oxidation current using the amperometric technique. Additional measurements in the absence of the bacteria were performed to exclude the possibility of electroactive species in the LB medium, in the substrate, or in the substrate and the LB medium mixture, which can contribute to the current response.
10.1 9 BACTERIAL CULTURES
E. coli strains were grown to early log phase at 30 ◦ C in 100 ml of Luria broth (LB) medium with aeration by shaking. Ampicillin, at a final concentration of 100 µg ml−1 , was added to ensure plasmid maintenance. Cultures at 3 × 107 cells per ml were used for all experiments.
10 WATER TOXICANTS MEASUREMENTS
The analytical performance of the biochip was determined with various chemicals, in order to exemplify its ability to detect acute toxicity in water. Toxic chemicals were introduced to the recombinant E. coli cultures. The measurement setup includes two units: the silicon chip attached to the printed circuit board (PCB) that was replaced in every experiment, and the reusable
Ethanol Detection
Ethanol, an efficient inducer of the heat shock proteins, was introduced to E. coli cultures harboring the promoters grpE and dnaK. The samples of the E. coli cultures (3 × 107 cells per ml) with the PAPG substrate were brought into contact with samples containing increasing concentrations of ethanol, and were immediately (∼after 1 min) placed into the electrochemical chambers. The induced β-galactosidase activity was monitored electrochemically and the results are shown in Figure 2. These results show the bacterial ability to generate a cascade of mechanisms that leads to current signal in the biochip system. For example for the grpE promoter, after 600 s, a current signal of 120 nA is produced in response to 2% ethanol, and a current of 20 nA is produced in response to 0.5% ethanol. These current signals are well above the background signal, which is defined as the measured current of the bacteria, bacterial medium, and the substrate without ethanol. For
ELECTROCHEMICAL BIOCHIP SENSOR FOR DETECTION OF POLLUTANTS 70
140 No ethanol 0.5 % 1% 1.5 % 2%
120 100 80 60 40
LB grpE dnaK fabA
60 50 Current (nA)
Current (nA)
5
20
40 30 20
0 10 0
100 200 300 400 500 600 700
0
Time (s) Figure 2. Amperometric response curves for on-line monitoring of ethanol using the electrochemical silicon chip. The recombinant E. coli containing a promoterless lacZ gene fused to promoter grpE exposed to 0.5–2% concentration of ethanol. The bacteria cultures with the substrate PAPG and the ethanol were placed into the 100 nl volume electrochemical cells on the chip immediately after the ethanol addition (∼1 min) and were measured using the amperometric technique at 220 mV.
the dnaK promoter, after 600 s, a current signal of 70 nA is produced in response to 2.5% ethanol, and a current of 10 nA is produced in response to 1% ethanol. The results indicate that there is a direct correlation between the currents signals and the toxicants concentrations. In order to prevent false alarms, all arrays can include positive and negative control chambers. In the positive control chamber, pure water is to be added besides adding the tested sample with the unknown chemicals to the bacterial solution. In case a current signal was generated, it is a false alarm. A negative control chamber may include w.t. (MG1655) E. coli bacteria that constitutively expresses β-galactosidase, thus, current should be generated in all cases. When no current is generated, measurement is incorrect, because of bacterial death caused by adding highly toxic chemicals. However, chemicals can produce only constant DC current signal, while the enzymatic reaction acts as an intrinsic amplifier, and generates increasing current signal. Real-time detection of the response of recombinant E. coli bacteria, with one of the promoters dnaK, grpE, or fabA, to ethanol is shown in Figure 3.
0
100
200
300 400 Time (s)
500
600
Figure 3. Amperometric response curves for on-line monitoring of different E. coli reporters in response to the addition of 1% ethanol, using the electrochemical silicon chip. The different E. coli reporters are fabA, dnaK, and grpE. Measurement performed immediately after the ethanol addition (∼1 min) at 220 mV working potential versus Ag/AgCl reference electrode. The LB curve represents the bacterial response to the LB medium with the substrate PAPG without ethanol.
The results show that for all different promoters, concentration of 1% ethanol could be detected within 10 min.
10.2
Phenol Detection
Phenol was introduced to the E. coli bacteria culture harboring the promoter grpE under the same conditions as the ethanol. The samples of the E. coli cultures with the PAPG substrate were brought into contact with samples containing increasing concentrations of phenol, and were immediately (approx. after 1 min) placed into the electrochemical chambers. The induced β-galactosidase activity was monitored electrochemically and the results are shown in Figure 4. As in the previous experiment, the results demonstrate the direct correlation between the currents signals and the toxicants concentrations, and the fast response time. Real-time detection of the responses of E. coli bacteria, with one of the promoters dnaK, grpE, or fabA, to phenol are shown in Figure 5. The results show that concentrations as low as 1.6 ppm of phenol could be detected within 6 min.
6
ARRAY TECHNOLOGIES
In all measurements, an induction period appears before the current emerges since there is a response time at the genetic level.
250 No phenol 1.6 ppm 8.3 ppm 16 ppm
Current (nA)
200
150
11 DISCUSSION
100
50
0 0
100 200 300 400 500 600 700 800 900 Time (s)
Figure 4. Amperometric response curves for on-line monitoring of phenol using the electrochemical silicon chip. The recombinant E. coli containing a promoterless lacZ gene fused to promoter grpE exposed to 1.6–16 ppm concentration of phenol. The bacteria cultures with the substrate PAPG and the phenol were placed into the 100 nl volume electrochemical cells on the chip immediately after the phenol addition (∼1 min) and were measured at 220 mV.
70 LB fabA grpE dnaK
60
Current (nA)
50 40 30 20 10 0 0
100
200
300 400 Time (s)
500
600
Figure 5. Amperometric response curves for on-line monitoring of different E. coli reporters in response to the addition of 1.6 ppm phenol, using the electrochemical silicon chip. The different E. coli reporters are fabA, dnaK, and grpE. Measurement performed immediately after the ethanol addition (∼1 min) at 220 mV working potential versus Ag/AgCl reference electrode. The LB curve represents the bacterial response to the LB medium with the substrate PAPG without phenol.
The results that were obtained from all measurements indicate that this bacterial-based sensor system is highly sensitive and provides rapid results. Concentrations as low as 0.5% of ethanol and 1.6 ppm of phenol could be detected in less than 10 min of exposure to the toxic chemical (Figures 2 and 4). In comparison to other bacterial-based studies, which utilize optical detection methods for water toxicity detection, these results proved to be more sensitive and produce faster response time. Recent study,3 which utilized bioluminescent E. coli sensor cells, detected 0.4 M (2.35%) ethanol after 220 min. An additional study1 based on fluorescent reporter system (GFP), enabled detection of 6% ethanol and 295 ppm phenol after more than 1 h. Cha et al.4 used optical detection methods of fluorescent GFP proteins, detected 1 g of phenol per liter (1000 ppm) and 2% ethanol, after 6 h. Other studies,5 could not be directly compared due to different material used, however their time scale for chemicals identification is hours. Different intensity response of the various bacterial sensors, dnaK, grpE, and fabA, to ethanol (Figure 3) and phenol (Figure 5) is due to the specific activation of each promoter to the type of the toxicant. The promoters dnaK and grpE are sensitive to protein damage (SOS system), thus, they were induced in response to ethanol which is known as protein damage agent.6 grpE showed high induction activity in response to ethanol, dnaK showed reduced enzyme activity, and fabA was only slightly induced above the background level. fabA promoter is sensitive to membrane damage, and thus, reacts to phenol exposure, which is known membrane damage chemical. As expected, grpE and dnaK promoters were less activated by phenol (Figure 5). The results that were obtained from measuring the bacterial harboring the grpE and dnaK promoters response to ethanol (Figures 2 and 6), are in agreement with the results of previous studies,4,7 which illustrate that the response current signals
ELECTROCHEMICAL BIOCHIP SENSOR FOR DETECTION OF POLLUTANTS 80 No ethanol 1% 1.5 % 2% 2.5 %
Current (nA)
60
40
20
0 0
100
200
300
400
500
600
700
Time (s) Figure 6. Amperometric response curves for on-line monitoring of ethanol using the nanobiochip. The recombinant E. coli containing a promoterless lacZ gene fused to promoter dnaK exposed to 0.5–2% concentration of ethanol. The bacteria cultures with the substrate PAPG and the ethanol were placed into the 100 nl volume electrochemical cells on the chip immediately after the ethanol addition (∼1 min) and were measured using the amperometric technique at 220 mV.
140 120
grpE dnaK
Current (nA)
100 80 60 40 20 0 0
0.5
1
1.5
2
2.5
3
% Ethanol Figure 7. Comparison between the grpE and dnaK promoters response to ethanol detection. The two experiments were performed under the same conditions. Current points were sampled after 600 s.
generated by the dnaK promoter were typically lower than that of the grpE promoter (Figure 7). Different intensity response of the bacterial sensors fabA, grpE, and dnaK to phenol (Figure 5) is due to the specific activation response of the promoter to the type of the toxicant. fabA promoter is sensitive to membrane damage, while
7
the promoters dnaK and grpE are more sensitive to protein damage.6 Therefore, E. coli bacteria harboring the fabA promoter showed high induction activity in response to phenol exposure, which is a known membrane damage chemical. As expected, grpE and dnaK promoters were less activated by phenol. There is a fundamental difference between nonenzymatic microbial sensing systems (e.g., GFP), in which the concentration of the reporter protein is determined, and enzymatic systems, which are based on measuring enzyme activity (e.g., β-galactosidase and alkaline phosphatase). Biochemical process that intends to produce a measurable signal has a great benefit while utilizing enzymatic activity. Since enzymes form continuously, and each enzyme reacts with many substrate molecules successively, this enzymatic mechanism serves as an intrinsic amplifier; consequently, the signal produces faster responses, is more sensitive, and increasing with time.8 For example, for the fabA promoter, after 300 s, a current signal of 10 nA is produced in response to 1.6 ppm phenol, and a current of 14 nA is produced in response to 3.3 ppm phenol (Figure 8). The current signal increases significantly with time, since the current results from an enzymatic reaction.9 The enzymes are continuously generated due to a sustained exposure of the bacteria to the toxicant. Therefore, after 600 s, a current signal of 60 nA is produced in response to 1.6 ppm phenol, and 80 nA in response to 3.3 ppm phenol. Figure 8 shows that current intensity is linearly proportional to the toxicant concentration, while the toxicant concentration is above the detection limit. The dashed line represents a linear interpolation between the minimal detection concentration (1.6 ppm) and 0 phenol concentration. When the phenol concentration was lower than 1.6 ppm, no significant reaction was measured; the current was approximately 0 during the measurement time. Electrochemical detection methods are also highly sensitive, since the measured current signal, that is, the number of transferred electrons that result from an enzymatic reaction can be accurately quantified. Furthermore, electrochemical monitoring can be carried out in turbid solutions or even under anaerobic conditions, as it does not require oxygen, in contrast to the light-emitting biosensors.10 Combining enzymatic system with
8
ARRAY TECHNOLOGIES Phenol detection after 600 s
Phenol detection after 300 s 200
50 45
fabA grpE dnaK
40
30 25 20
grpE dnaK
120 100 80
15
60
10
40
5
20 0
0 0 (a)
fabA
160 140 Current (nA)
Current (nA)
35
180
2
4
6 8 10 12 14 Concentration (ppm)
16
0
18 (b)
2
4
6
8
10
12
14
16
18
Concentration (ppm)
Figure 8. Recombinant bacterial current response to increasing concentrations of phenol, (a) after 300 s and (b) after 600 s. The E. coli reporters are fabA, grpE, and dnaK. Amperometric measurements were performed immediately after phenol addition (∼1 min) at 220 mV working potential versus Ag/AgCl reference electrode. The dashed line represents a linear interpolation between the minimal detection concentration (1.6 ppm) and 0 phenol concentration.
electrochemical detection methods enables measurements in turbid solutions and under anaerobic conditions.11 This new design of nanochambers array on chips allows a broad band of measurements. We can simultaneously test eight different toxicant types with the general stress responsive promoter by introducing to each chamber a different toxicant, or, in order to specify unknown aqueous sample, we can test the sample with eight different stress responsive promoters, thus we obtain an indication of the toxicant type. In addition, the array configuration enables the addition of positive and negative control chambers for each experiment.
12 CONCLUSIONS
A novel integration between microelectronic device and living organisms for electrochemical detection of toxicity in water has been successfully developed and tested. This electrochemical “lab on a chip” that integrates bacteria as sensors cells, provides rapid and sensitive real-time electrochemical detection of acute toxicity in water. A clear signal is produced within less than 10 min of exposure to various concentrations of toxicants, or to stress conditions, with a direct correlation between
the toxicant concentration and the induced current. The small volume (100 nl) of the electrochemical cells allows minimum interaction with the water flow, resulting in increased speed and sensitivity due to the small diffusion length of the analytes to the electrode surface. The construction of an array of nanochambers on one chip leads to high throughput in addition to the capability of performing multi experiments simultaneously and independently. During the measurement period the bacteria remained active and were capable of performing cellular gene expression and enzymatic activity, which demonstrates the chip biocompatibility. These results emphasize the advantages of merging electrochemical detection methods with adjusted design and process of nanovolume electrochemical cells array on silicon chip, which results in small sampling requirement and fast response time. The electrochemical detection method has been shown to be sensitive, simple, and can be performed even in turbid solutions and under anaerobic conditions. By using compact and portable device, we are capable of measuring water toxicity in the field. It is expected that this technology can be most beneficial to the health care and medical industry, for environmental monitoring and for control of chemical or pharmaceutical industry processing.
ELECTROCHEMICAL BIOCHIP SENSOR FOR DETECTION OF POLLUTANTS
REFERENCES 1. S. Belkin, Microbial whole-cell sensing systems of environmental pollutants. Current Opinion in Microbiology, 2003, 6, 206–212. 2. I. Biran, L. Klimentiy, R. Hengge-Aronis, E. Z. Ron, and J. Rishpon, On-line monitoring of gene expression. Microbiology, 1999, 145, 2129–2133. 3. J. R. Premkumar, O. Lev, R. S. Marks, B. Polyak, R. Rosen, and S. Belkin, Antibody-based immobilization of bioluminescent bacterial sensor cells. Talanta, 2001, 55, 1029–1038. 4. H. J. Cha, R. Srivastava, V. M. Vakharia, G. Rao, and W. E. Bentley, Green fluorescent protein as a noninvasive stress probe in resting Escherichia coli cells. Applied and Environmental Microbiology, 1999, 65, 409–414. 5. D. E. Nivens, T. E. McKnight, S. A. Moser, S. J. Osbourn, M. L. Simpson, and G. S. Sayler, Bioluminescent bioreporter integrated circuits: potentially small, rugged and inexpensive whole-cell biosensors for remote environmental monitoring. Journal of Applied Microbiology, 2004, 96, 33–46. 6. S. Daunert, G. Barrett, J. S. Feliciano, R. S. Shetty, S. Shrestha, and W. Smith-Spencer, Genetically
7.
8.
9.
10.
11.
9
engineered whale-cell sensing systems: coupling biological recognition with reporter genes. Chemical Reviews, 2000, 100, 2705–2738. S. Rupani, K. Konstatninov, P. Dhurjati, T. Vandyk, W. Majarian, and R. Larossa, Online monitoring of recombinant Escherichia-coli in batch and continuous cultures using a grpe promoter bioluminescence reporter gene system. Abstracts of Papers of the American Chemical Society, 1994, 207, 127–BIOT. E. Sagi, N. Hever, R. Rosen, A. J. Bartolome, J. R. Premkumar, R. Ulber, O. Lev, T. Scheper, and S. Belkin, Fluorescence and bioluminescence reporter functions in genetically modified bacterial sensor strains. Sensors and Actuators. B, Chemical, 2003, 90, 2–8. R. Popovtzer, T. Neufeld, N. Biran, E. Z. Ron, J. Rishpon, and Y. Shacham-Diamand, Novel integrated electrochemical nano-biochip for toxicity detection in water. Nano Letters, 2005, 5, 1023–1027. I. Biran, R. Babai, K. Levcov, J. Rishpon, and E. Z. Ron, Online and in situ monitoring of environmental pollutants: electrochemical biosensing of cadmium. Environmental Microbiology, 2000, 2, 285–290. Y. Paitan, D. Biran, I. Biran, N. Shechter, R. Babai, J. Rishpon, and E. Z. Ron, On-line and in situ biosensors for monitoring environmental pollution. Biotechnology Advances, 2003, 22, 27–33.
60 Microcantilever Array Devices Daniel Haefliger and Anja Boisen Department of Micro- and Nanotechnology, Technical University of Denmark, Kongens Lyngby, Denmark
1 BACKGROUND
Micrometer-sized diving boards, also called cantilevers, started to be used for sensing purposes shortly after the invention of the atomic force microscope (AFM) in 1986.1 Basically, the AFM functions as a miniaturized phonograph where images are obtained by scanning the surface with an AFM probe. The probe consists of a sharp tip mounted on a cantilever, which deflects due to the forces between tip and sample. Usually, the deflection of the AFM probe is detected by optical leverage where a laser is reflected off the backside of the cantilever onto a position-sensitive diode. However, for operations in nontransparent liquids and for the realization of compact AFMs, other readout techniques are needed. Since 1989, research groups have been reporting on self-sensing AFM probes where the cantilever deflection is sensed at the cantilever by using different integrated transducer principles. Among the promising principles that have been developed are piezoresistive,2 piezoelectric,3 and capacitive readout.4 The AFM probe needs to have micrometer dimensions in order to achieve a relatively high resonant frequency (in the kHz regime) and a low spring constant (in the N/m regime). Typically the cantilevers are 100-µm long, 50-µm wide, and 0.5-µm thick. The high resonant frequency makes the probe less sensitive to external vibrations and the low spring constant improves the force
sensitivity of the probe. Because of the small dimensions microfabrication is necessary. The first micromachined cantilevers with integrated tips were realized in 1990 by Tom Albrecht and coworkers in the group at Stanford University, CA, USA,5 and by the group of O.Wolter at IBM Sindelfingen, Germany.6 These microfabricated AFM probes soon became commercially available through the companies Park Scientific Inc. and NanoWorld AG. Today, several companies offer AFM probes in a large span of spring constants and resonant frequencies. These values are tuned by the choice of cantilever material(s) and geometry. Possibly inspired by some of the often encountered annoyances in AFM work, Thomas Thundat and coworkers at Oakridge National Laboratory, TN, USA, in 1994, started to explore the cantilever’s possible potential as a physical and chemical sensor.7 Their initial work demonstrated that an AFM probe which is coated on one side with a metal layer for improved reflection of the laser beam will be prone to bimorph effects. This can cause severe drift problems in the AFM setup. However, the effect can also be used as a simple principle for a very sensitive thermometer, where a static cantilever deflection can be related to a given temperature change. Moreover, it was demonstrated that a metal-coated cantilever kept at constant temperature responds reproducibly with a constant bending to humidity changes and to exposure of other vapors such as mercury. Also, it was shown that the amount of adsorbates could be
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
estimated by monitoring the shift in the resonant frequency of the cantilever. The change in the static deflection of the cantilever is related to the difference in surface stress of the two faces of the cantilever, as will be discussed later. A related technique to study surface-stress changes is called the bending plate technique and was first observed and applied on wafers of III–V compounds in the 1960s.8 By introducing the cantilever technique this measurement principle was significantly improved. Using the bending plate technique, surface-stress changes of 1 N m−1 were normally reported, whereas the first measurements of surface-stress changes with the micrometer-sized cantilevers were of the order of 10−3 N m−1 . The change in the resonant frequency of the cantilevers is caused by a change in mass and/or stiffness of the cantilever. For the micrometer-sized AFM probes people initially reported mass changes in the picogram regime. The mass sensitivity has continuously been improved as discussed in the subsequent text and has been pushed, by researchers like Michael Roukes at the California Institute of Technology, Pasadena, CA, USA, to the point where single molecule detection is possible. Soon after the cantilever-based sensing principle was initiated, researchers started to apply surfacestress change measurements in liquid environment. For example, the unspecific binding of proteins to a hydrophobic surface was reported in 1996,9 and studies of electrochemical processes were also initiated in 1996.10 The cantilever sensors were further used for online monitoring of the self-assembly of alkanethiol monolayers on goldcoated cantilevers.11 The surface stress, in this work, was seen to be related to the length of the alkane chain. Most of the early cantilever-based sensing work was performed in standard AFM setups using normal AFM probes. In a normal AFM setup, it is not possible to measure on more than one cantilever at a time. This makes it impossible to simultaneously perform control measurements on a reference cantilever (RC). The AFM probes used in these experiments typically had tips although for sensor applications this was not necessary. One of the first specifically designed large scale sensor systems was developed by Christoph Gerber and coworkers at the IBM Research Laboratory in Zurich, Switzerland. An array of polymer-coated Si cantilevers was used to simultaneously detect
the adsorption-induced change in the surface stress of the cantilevers. The system could readout from eight cantilevers simultaneously using an optical leverage technique and different alcohols could be detected due to their different adsorption rates in the polymers.12 In these measurements uncoated cantilevers were employed for reference. The potential of the cantilever-based sensing in the field of diagnostics was highlighted in 2000, when it was demonstrated that a pair of cantilevers coated with two short strands of DNA oligos that only differ by a single base can be used for single nucleotide polymorphism (SNP) detection.13 From the bioapplication point of view, these data were the onset of many studies related to the specific recognition of DNA, proteins, and macromolecules. On the technology side cantilevers with integrated readout started to appear in the late 1990s. As for the AFM, the integrated readout facilitates the realization of compact devices that can operate in even nontransparent environments. For example, in 2000, piezoresistive cantilevers for surface-stress sensing were presented demonstrating the possibility of realizing a dense array of sensors with a compact readout system.14 Even highly advanced systems with integrated electronics were soon demonstrated.15 The field of selfsensing cantilevers has developed rapidly. Today several groups around the world are investigating different readout techniques for the cantilever, and the technological solutions typically address either the surface-stress detection or the mass detection. Today (2006) cantilever-based sensors are developed and commercialized by several companies including, NanoNord A/S in Aalborg, Denmark, Protiveris Inc. in Rockville, MD, USA, Concentris GmbH in Basel, Switzerland, and SIS GmbH in Herzogenrath, Germany. NanoNord A/S develops cantilevers with piezoresistive readout whereas the three other companies use different types of optical detection. The company SIS GmbH provides a solution where the deformation of the complete cantilever is monitored simultaneously.
2 MEASUREMENT PRINCIPLES
In general, three different operation modes are employed in cantilever arrays as illustrated in Figure 1: static mode, dynamic mode, and heat
MICROCANTILEVER ARRAY DEVICES Static mode (Surface stress)
Dynamic mode (Microbalance)
Adsorption
Heat mode (Bimorph)
Adsorption
Recognition
(a)
∆s1 ∆zmax
Calorimetry A
B
∆s2
t
Recognition
(b)
3
R
(c)
Figure 1. Operation modes.
mode. Common to all modes is the fact that the cantilever’s surface is usually functionalized in such a way that one surface is rendered chemically active while the other surface is passivated by a chemically inactive substance. Chemical and physical reactions on the active cantilever surface can then be observed by the temporal evolvement of the cantilever’s response. The reaction partner immobilized on the cantilever surface is usually a liquid or solid such as a polymer film or a self-assembled monolayer (SAM) of biomolecules. The other partner, which is to be detected via the reaction with the immobilized substance, can be a gas, vapor, biomolecule, or microorganism. In the static mode, the chemical or physical reaction occurring on the cantilever surface is transduced into a nanomechanical bending of the cantilever. The reaction provokes a change in surface stress on the chemically active surface. The passivated surface remains inactive yielding no change in surface stress. Hence, due to the asymmetric surface property of the cantilever, an asymmetric surface stress is produced upon chemical or physical reaction. This asymmetric loading causes the cantilever to bend. The detection of the reaction is finally achieved by measuring the nanomechanical bending by means of optical or electrical sensors. The bending of commonly used cantilevers of a few 100-µm lengths is typically between a few nanometers and a few hundred nanometers. This minute deflection imposes particularly high demands on the detection systems. The most widely used techniques are described in Section 3.
Figure 2. Lateral view of a thin cantilever of thickness t loaded by surface-stress changes σ1 and σ2 . The cantilever bends around a neutral plane with a constant radius R.
From a mechanical point of view, the deflection of the cantilever upon a change in surface stress is usually described by the simple classical relationships that Stoney derived and applied to electroplated metal films at the beginning of the twentieth century.16 Stoney’s equation provides a first order approximation for the radius of curvature, R, and the deflection of the cantilever tip, zmax , in relation to the differential surface-stress change (σ1 − σ2 ) = σ1 − σ2 (Figure 2): 1 6(1 − ν) = (σ1 − σ2 ) R Et 2
(1)
3(1 − ν)L2 (σ1 − σ2 ) zmax ∼ = Et 2
(2)
where σ1 and σ2 are the surface-stress changes on the active and the passivated surfaces, respectively. t and L denote the thickness and the length of the cantilever, respectively, E is the Young’s modulus, and ν the Poisson’s ratio of the material. Stoney’s formula assumes that the thickness of the functionalizing coatings on the active and passivated cantilever surfaces is much thinner than the thickness of the cantilever. It thus provides good estimations for cantilevers coated with very thin films. Measured surface-stress changes typically range between 0.001 and 1 N m−1 . The physical origin of the surface stress is discussed in the following, separately for unspecific and specific reactions. In the case of unspecific reactions, one cantilever surface is commonly activated by a thin polymer coating which can adsorb
4
ARRAY TECHNOLOGIES
vapor from, for example, water or alcohols.12,14 The polymer film swells upon diffusion of the vapor molecules into the polymer and bends the cantilever away from the coated surface. The bending is caused by compressive stress induced onto the cantilever due to a volumetric change of the active film (Figure 1). The interpretation of the origin of surface stress is, however, more complex to interpret in the case of specific reactions such as DNA hybridization and antibody–antigen binding. In this case, one cantilever surface is commonly activated by covalent binding of a receptor via thiol–gold chemistry. The cantilever is coated with a 20–100-nm-thick gold film on which a SAM of thiolated receptors is immobilized. The other surface of the cantilever is usually passivated by adsorption of bovine serum albumine (BSA) to avoid unspecific binding of the analyte. Several different interactions occur when the analyte reacts with the receptor. The reaction changes the size of the molecules forming the SAM on cantilever and it may alter conformation and charge distribution of the species. These modifications affect the interaction between the molecules via electrostatic, dispersion, steric, osmotic, and solvation forces, which induce a net change in surface stress.13,17 To which extent each force is contributing to the surface stress depends heavily on the involved species and the specific reaction. Recently, theoretical calculations revealed that interactions between the molecules and the gold film used for immobilization can also significantly contribute to a surfacestress change.18 In this case, the stress originates from surface charge redistribution in the gold film in response to the charges in the molecules. Microcantilevers operating in dynamic mode are essentially mechanical oscillators that are driven at resonance. The resonance frequency f0 for a rectangular cantilever can be expressed as k f0 = 0.323 (3) m∗ where k is the spring constant and m∗ the effective mass of the cantilever. The resonance frequency of microcantilevers typically ranges in the kilohertz to megahertz regime. These vibrating cantilevers are used as microbalances capable of measuring minute mass changes of a few atograms (10−18 g). By adsorption of a mass m on the surface of the cantilever its effective mass will be increased. As
shown by Equation (3), a change in the effective mass translates into a shift of the resonant frequency. In the case of mass adsorption the resonance will decrease. Using appropriate electronics to track the resonance shift, f , the adsorbed mass can be determined by 1 1 m = 0.104k (4) − 2 (f0 − f )2 f0 This interpretation of the frequency shift assumes that changes in the cantilever’s spring constant k during mass adsorption are negligible. This is the case for adsorption of single particles such as microorganisms19 (Figure 1b) and molecules at low concentrations. However, from Equation (3), it is clear that changes in resonance frequency can result from both a change of the effective mass m∗ and variations in the spring constant k. The spring constant relates directly to the stiffness of the cantilever, which is determined by the cantilever material and any applied surface stress. As seen in static mode measurements, adsorption of molecules by diffusion or biological recognition can provoke considerable surface-stress changes. At high concentration, these stress changes affect the stiffness of the cantilever and have to be taken into consideration when interpreting the measured frequency shift. The resonance shift can then be approximated by20 k m∗ 1 (5) − f = f0 2 k m∗ where k denotes the surface-stress change and m∗ the change in specific mass. Equation (5) is valid as long as k and m∗ are much smaller than the stiffness and mass of the cantilever, respectively. In most experiments, changes in k and m∗ are small and these requirements are fulfilled. To decouple the influence of mass loading and spring constant variations, a simultaneous measurement of bending and resonant frequency shifts is required.21 The heat mode employs the bimorph effect to measure the heat adsorbed or released by an endothermic or exothermic reaction on the cantilever surface. The cantilever is coated asymmetrically on one surface with a layer of different thermal expansion properties than those of the cantilever material (Figure 1c). Some of the most
MICROCANTILEVER ARRAY DEVICES
popular coatings are metals such as gold, platinum, or aluminum. If such a cantilever is subjected to temperature changes, it will bend to the mismatch in thermal expansion coefficients of the cantilever material and the coating. Detecting the bending via optical or electronic means allows for the measurement of temperature changes in the microkelvin range.
3 INSTRUMENTATION
The measurement of cantilever deflections or mass change in the nanometer or atogram range imposes high demands on the detection systems, and various intriguing setups have been developed. We concentrate here on an overview of the most widely used techniques in the field of static and dynamic mode biosensors. The readout of the cantilever deflection in static mode operation is predominantly achieved by the optical lever method originally developed for atomic force microscopy.22 As illustrated in Figure 3(a), a laser beam of typically few milliwatts power is focused onto the free end of the cantilever. The cantilever surface acts as a mirror reflecting the beam onto a position-detection diode. Depending on the degree of cantilever bending, the reflected laser beam is tilted away from its initial position resulting in a shift of the laser spot impinging onto the diode. The travel distance of the laser spot is proportional to the cantilever tip deflection and can be extracted electronically from the position-detection diode. A microcantilever array commonly exists of at least two cantilevers. One cantilever is functionalized with the receptor and acts as the active measurement cantilever (MC) while the other exhibits an inert surface and is used for reference. Numerous measurements have shown that a RC is vital to ensure reliable signal interpretation. Cantilever sensors are prone to various artefacts induced by variations in ambient temperature, pressure, humidity, and composition of biological solutions (pH, ionic strength, etc.).7 By implementing a reference, such crosstalk can be cancelled out to a large extent. Increasing the number of cantilevers in an array opens up the possibility of exposing several MCs and RCs in a single experiment under identical conditions in terms of temperature, flow rate, and pressure. The MCs can thereby be functionalized
5
with different receptors enabling fast screening for multiple analytes, including negative controls (Figure 3a). Figure 3(b) shows a cantilever array made in silicon used together with optical readout. The deflection readout of each individual cantilever is achieved in one of the following ways: (i) in parallel fashion by an array of laser diodes and position sensors aligned to the cantilever array,12 (ii) sequentially by one laser diode scanned over the cantilever array,23 or (iii) in parallel by flood illumination of the complete array and digital image analysis to track the spot of light reflected off each individual cantilever.24 Cantilever arrays are commonly fabricated in silicon or silicon nitride using conventional processes known from the semiconductor industry. Recently, arrays have also been fabricated in polymers as shown in Figure 3(c).25,26 Polymers are much softer than silicon since they can exhibit up to 100 times lower Young’s modulus, E. As is clear from Equation (2), a low E
L MC
RC PSD (a)
100 µm
100 µm (b)
(c)
Figure 3. Microcantilever array with optical lever readout. (a) Principle with laser (L) and position-sensitive diode (PSD). The array shows two pair of sensors with a measurement cantilever (MC) and a reference cantilever (RC). Note the beam shift on the PSD of the deflected MC. (b) Scanning electron microscopy image of a silicon cantilever array fabricated at the IBM Zurich Research Laboratory. The cantilevers are 1-µm thick, 500-µm long, and 100-µm wide. (c) Polymeric cantilever array fabricated in epoxy resist (Epon SU-8). The cantilevers are 4.5-µm thick, 200-µm long and 20-µm wide.
6
ARRAY TECHNOLOGIES
WB
v
v
MC
V0 RC
(a)
PR
2 mm (b) Figure 4. Cantilever array with piezoresistive readout. (a) Principle with Wheatstone bridge (WB), piezoresistor (PR), measurement cantilever (MC), and reference cantilever (RF). (b) Optical microscopy image of an integrated piezoresistive cantilever sensor chip.
translates into a larger deflection zmax for a given surface-stress change and thus increases the sensor’s sensitivity. Optical readouts, however, suffer from several disadvantages: tedious alignment of the optical components to the cantilever array is required, susceptibility to optical artefacts arising from changes in the optical properties of the medium surrounding the array (e.g., variation in refractive index upon exchange of the medium) is observed, and operation in nontransparent solutions is impossible. These problems are generally circumvented by using cantilever arrays with piezoresistive deflection readouts (Figure 4a). In this configuration a thin, stress-sensitive film is directly integrated into the cantilever material. This film consists of a piezoresistive material such as doped silicon that changes electrical conductivity when it is strained by the cantilever bending. The change in conductivity can be measured via a simple Wheatstone bridge. Unlike the optical lever system, the integrated piezoresistive readout is very compact allowing for complete on-chip integration
of the electronic circuitry and a microfluidic handling system useful for biochemical diagnostics. Figure 4(b) shows a silicon chip with an array of ten cantilevers equipped with encapsulated metal wires suitable for operation in a liquid environment.27 Such chips bear high potential in portable, point-of-care diagnostic devices. The main disadvantage of piezoresistive cantilevers is, however, to date, imposed by the high intrinsic noise level, which affects the resolution and sensitivity. For dynamic mode sensors, the readout inherently demands for an external actuation to drive the cantilevers in resonance. Actuation of microstructures is widely used in the field of microelectromechanical systems (MEMS) and a large variety of mechanisms have been developed. Most actuation schemes use piezoelectrically, electrostatically, magnetically, or thermally induced forces for excitation. The detection of the cantilever oscillation can be performed by employing the same type of forces for passive sensors. Moreover, detection of the vibration by the optical lever technique or piezoresistors (PRs) as discussed in the preceding text is often used. In the simplest readout scheme, the cantilever is mounted on a millimeter-sized driving piezo and the cantilever oscillation is detected by an optical lever. Due to the large size of the piezoelectric element, the excitation, however, stimulates not only the cantilever but also the complete measurement setup. The noise jeopardizes the detection of the cantilever resonance when working in liquids. To confine the stimulation to the cantilever, beams with integrated piezoelectric elements have been fabricated.28 The piezos can be used simultaneously for detection of the cantilever resonance. Such integrated readout schemes enable very compact sensors design. Dynamic microcantilevers can be hooked up to integrated circuitry and microprocessors on a single substrate using MEMS and complementary metal oxide semiconductor (CMOS) technology. Figure 5 shows a microcantilever sensor monolithically integrated into a CMOS chip designed to detect volatile organic compounds.15 The cantilever is excited by a thermally actuated bimorph element; the response is acquired by integrated PRs. The chip combines the cantilever sensor with a capacitive and calorimetric sensor to improve the wealth of information about the analyte.
MICROCANTILEVER ARRAY DEVICES
7 f0 = 315 kHZ
(d) (a)
(a)
(b) (e)
f1 = 180 MHz (c) (f)
(b) 1 µm (g)
Figure 5. Optical microscopy image of a gas microsensor chip (size: 7 × 7 mm). The different components include: (a) flip-chip frame, (b) reference capacitor, (c) sensing capacitor, (d) calorimetric sensor, (e) temperature sensor, (f) dynamic cantilever sensor, and (g) digital interface. [Reprinted with permission Hagleitner et al.15 copyright 2001, Nature Publishing Group.]
The need of dynamic mode devices as pure microbalances drives the development of ultrahigh sensitive mass sensors for trace analysis. One route to achieve high mass sensitivity is offered by downscaling the cantilever structure. The smaller the cantilever, the smaller its mass becomes. Intuitively, a given minute mass added to a small cantilever exerts higher influence on the resonance behavior than if it is adsorbed on a bigger and heavier structure. Mathematically, the resolution m/f of a resonating rectangular cantilever can be derived from Equation (4):
m ∼ m k = 0.208 3 (kg/Hz) = 6.172m f k f0
(6)
which provides further evidence of increased mass sensitivity on reducing the size and therefore mass of a cantilever. Figure 6 shows a resonating nanocantilever microfabricated in polysilicon.29 The actuation and detection for readout is performed by electrostatic electrodes. The mass of such a nanocantilever is about 10 000 times smaller than for conventional silicon cantilevers as shown in Figure 3(b). It provides an ultrahigh mass resolution of a few atogram per Hertz. The readout signal for such minute mass changes is very low and requires direct integration of the nanosensor
Figure 6. Scanning electron microscopy image of an electrostatically actuated nanocantilever made of polysilicon. (a) Fundamental mode, f0 and (b) first mode, f1 . The cantilever is 800-nm wide, 2-µm thick, and 40-µm long.
into CMOS circuitry to reduce the noise level and improve measurement reliability. The functionalization of all kinds of cantilevered sensors with receptors can be achieved by selfassembly of thiolated molecules on a gold coating. For this, the gold is sputter- or evaporationdeposited on the cantilever structure in vacuum equipment. A top-down approach for functionalization is offered by depositing the receptor via ink-jet printing or by dipping the cantilever array into a conformal microcapillary array filled with the receptor solution.
4 APPLICATIONS
The microcantilever array devices are generally employed for label-free detection of biomolecules using both static and dynamic mode operations. Moreover, the fundamentals behind the signal generation can be used to track the evolvement of local surface-stress changes for fundamental studies. Such measurements are difficult to achieve by any other technology. Also, the cantilever is inherently a very sensitive thermometer, and owing to its small size, can be used for local temperature measurements or for calorimetry on very small sample volumes. In terms of mass detection, the ultimate limit is the detection of a single molecule and the use of cantilevers in mass spectroscopy is being pursued. The specific recognition of biomolecules has mainly been performed using static mode. Such
8
ARRAY TECHNOLOGIES
measurements are generally performed in liquid environment, which imposes high experimental challenges for dynamic mode operation. The liquid damps the oscillation of the cantilever rendering the precision of the resonant frequency measurements very low. Lately, it has been demonstrated that the mass resolution can be improved by operating the device at higher order modes (as shown in Figure 6b), where the damping loss is lower.30 Specific recognition has been demonstrated for mainly DNA,31 proteins,32 bacteria,19 and antigens.33 For specific recognition, the cantilever surface needs to be coated with a “detector” layer that binds only to one type of molecules. For DNA detection, the common technology is to immobilize short strands of thiolated DNA on a gold surface. The discussion in cantilever sensing today is: “what is the optimal surface for generation of a large surface-stress signal?” Here the data obtained from standard characterization techniques such as fluorescents and radio labelling cannot be directly transferred to the cantilever surface. A high density of target DNA on a surface does not automatically give a large change in surface stress. Instead, it seems that the molecules should be placed as close to the surface as possible and the sensor signal will be strongly affected by the pH and the salt concentration of the solution.17 For bacteria detection, recent results indicate that the largest results are obtained by using Fab fragments on the surface, hereby bringing the molecules close to the cantilever surface.34 Ongoing work by the group of Martin Hegner at the University of Basel, Switzerland has demonstrated that it is possible to detect DNA oligos in concentrations of pM, which indicates that the specific recognition can be performed without polymerase chain reaction (PCR) amplification. It has even been possible to detect specific DNA oligos in a background mixture of many DNA fragments. Moreover, the kinetics of DNA immobilization and hybridization can be investigated. In these experiments, the quality of the surface plays an essential role. For example, the cleanliness of the gold has been demonstrated to have a huge impact on the size of the surface-stress signal and the adsorption rate of the thiols.35 By immobilizing 25-mer DNA oligos at different concentrations on a gold-coated cantilever, the surface free energy of the thiol-modified DNA-oligo adsorption on gold is found to be 32.4 kJ mol−1 . The adsorption
experiments also indicate that first a single layer of DNA oligos is assembled on the gold surface after which a significant unspecific adsorption takes place on top of the first DNA-oligo layer.36 Pathogens such as Escherichia coli (E. coli ) have been detected employing dynamic mode. The cantilever is coated with anti-E. coli antibodies and then dipped into a solution containing the bacteria.19 After surface adsorption of E. coli, the cantilever is dried and the resonant frequency is compared to the resonant frequency prior to the exposure to the bacteria. The resonant frequency revealed to drop as expected due to the added mass of the adsorbed E. coli. The system enabled the detection of a single E. coli cell. A calculation according to Equation (4) revealed that the cell weighed 665 fg, which is consistent with other reports. By adding a nutritious agarose film onto the cantilever, the biosensor has been employed to detect the growth of the pathogen. Sensitivity in the pg/Hz regime has been achieved, which is seen to be three orders of magnitude higher than for common quartz crystal microbalances (QCM). The high sensitivity enabled rapid cellgrowth detection within less than an hour, about 10 times faster than with QCM.37 Cantilevers coated with proteins for specific fungus recognition can be used as small Petri dishes for investigation of fungus growth.38 Initially, the cantilevers are placed in a solution of fungus and afterwards kept in a humid environment. The presence of fungus and mycelium growth are monitored as a change in the mass of the cantilever using dynamic mode operation and the mass of a single fungal spore can be detected. Vital spores can be detected in situ within 4 h, which is approximately 10 times faster than the procedures applied today in fungal detection. The biosensor could detect the target fungi in a range of 103 –106 colony-forming units per milliliter. Potentially, such measurements can be used in, for example, water and food quality control. The ability to measure very small changes in surface stress is a unique feature of the cantilever device operated in the static mode. For example, conformational changes in proteins can be monitored. Protein folding is hard to measure by other simple techniques and could potentially be used, for example, in drug screening. As a test system, conformational changes of bacteriorhodopsin have quantitatively been monitored.39 The results
MICROCANTILEVER ARRAY DEVICES
indicate that it is possible to measure ligand unbinding from membrane proteins based on the intrinsic nanomechanical changes of the receptor. The most impressive mass sensing achieved to date has been presented by Michael Roukes group at California Institute of Technology, in Pasadena, CA, USA. Their current generation of devices is sensitive to added mass at the level of a few zeptograms.40 In their experiments, this represents about thirty xenon atoms which is the typical mass of an individual protein molecule. The high mass resolution is primarily achieved by reducing the cantilever dimensions to the nanometer regime. The sensor system is operated at temperatures below 50 K. Metal-coated cantilevers can be used as calorimeters. One of the first applications was the investigation of surface catalytic reactions. A cantilever was coated with a thin Pt layer, which is used to catalyze the exothermic conversion of H2 and O2 to form water vapor.41 Lately, the exothermic reaction caused by the deflagration of a small amount of trinitrotoluene (TNT) has been monitored using heated cantilevers.42 Such micrometer-sized devices might hold great potential for handheld explosive sniffers.
5 OUTLOOK
The field of microcantilever array devices is expanding on the technology as well as the application side. More players are joining the game and more advanced devices with integrated fluidics, readout, and actuation are being developed. Moreover, large arrays are now being built and there seems to be no real practical limit to the number of cantilevers that can be operated in parallel. Just think of the millipede project from IBM Research Laboratory in Zurich, Switzerland,43 where more than 1000 cantilevers are operated simultaneously for reading and writing on a polymer surface for data storage. Polymer cantilevers are emerging and these devices will probably become widely used because they are more sensitive than Sibased devices and cheaper to fabricate. They offer high prospects for the field of single-use, disposable devices. Recently, the principle of chemically induced change in surface stress has been explored for direct actuation of micromechanical structures
9
such as valves. The valves are self actuated upon a chemical trigger, enabling new possibilities in the development of autonomous devices for use in, for example, drug delivery.44 Also, the surface chemistry developed and the applications that are being reported become more advanced in terms of detection limit and complexity of the receptor-ligand schemes. However, there are still several fundamental questions to be addressed. For example, the origin of surfacestress changes is still not fully understood and several models have been proposed for, for example, the generation of signals from DNA hybridization. Nowadays researchers start to perform thorough and detailed studies on rather simple systems such as alkanethiols. They verify these results against computational simulations, taking advantage of recent developments in the field of modeling of intra- and intermolecular interactions. It seems that no real commercial breakthrough has yet occurred for cantilever sensors, but it can be expected soon. The technology is in a maturing phase where some of the unanswered questions are now being addressed. One important experimental factor is the use of RCs as controls and to filter unspecific signals stemming from variations in temperature and buffer solutions. Moreover, the chemical blocking of the backside of the cantilever is crucial for static mode measurements in order to guarantee an unambiguous signal interpretation. It is thus crucial to conduct the measurements under very well-controlled conditions. For proof-of-concept of a novel sensor application, it is important to perform control measurements by other supplementing techniques such as X-ray photoelectron spectroscopy (XPS), surface plasmons resonance, fluorescence detection, and Fourier transform infra red spectroscopy (FTIR). Such hybrid setups are starting to emerge. The cantilever sensors have picked up speed and the research society now seems to address the fundamental questions such as signal generation and optimal sensing principles. At the same time, more sensitive devices and highly advanced applications such as detection of conformational changes in proteins and the detection of the mass of a single protein are appearing at a high pace. In conclusion, the cantilever sensors have demonstrated unencumbered mass sensitivity and surface-stress sensitivity and it seems very likely that those features will be utilized for future products in,
10
ARRAY TECHNOLOGIES
for example, diagnostics and drug discovery. The cantilever field is exciting and dynamic. The limit for detection is constantly challenged and just the imagination sets the limit to new applications. REFERENCES 1. C. F. Quate, G. Binnig, and C. Gerber, Atomic force microscope. Physical Review Letters, 1986, 5, 930–932. 2. M. Tortonese, H. Yamada, R. C. Barrett, and C. F. Quate, Atomic Force Microscopy using Piezoresistive Cantilever, In Proceedings of Transducers ‘91 Conference, San Francisco, CA, USA, 1991, 448–451. 3. T. Itoh and T. Suga, Development of a force sensor for atomic fore microscopy using piezoelectric thin films. Nanotechnology, 1993, 4, 218–224. 4. J. Brugger, R. A. Buser, and N. F. de Rooij, Micromachined atomic force microprobe with integrated capacitive read-out. Journal of Micromechanics and Microengineering, 1992, 2, 218–220. 5. T. R. Albrecht, S. Akamine, T. E. Carver, and C. F. Quate, Microfabrication of cantilever styli for the atomic force microscope. Journal of Vacuum Science and Technology A, 1990, 8, 3386–3396. 6. O. Wolter, T. Bayer, and J. Greschner, Micromachined silicon sensors for scanning force microscopy. Journal of Vacuum Science and Technology B, 1991, 9, 1353–1357. 7. T. Thundat, R. J. Warmack, G. Y. Chen, and D. P. Allison, Thermal and ambient-induced deflections of scanning force microscope cantilevers. Applied Physics Letters, 1994, 64, 2894–2896. 8. H.-J. Butt and R. Raiteri, Measurements of the Surface Tension and Surface Stress of Solids, in Surface Characterization Methods, Marcel Dekker, 1999. 9. H.-J. Butt, A sensitive method to measure changes in the surface stress of solids. Journal of Colloid and Interface Science, 1996, 180, 251–260. 10. S. J. O’Shea, M. E. Welland, T. A. Brunt, A. R. Ramadan, and T. Rayment, Atomic force microscopy stress sensors for studies in liquids. Journal of Vacuum Science and Technology B, 1996, 14, 1383–1385. 11. R. Berger, E. Delamarche, H. P. Lang, C. Gerber, J. K. Gimzewski, E. Meyer, and H.-J. G¨untherodt, Surface stress in the self-assembly of alkanethiols on gold. Science, 1997, 276, 2021–2024. 12. H. P. Lang, R. Berger, F. Battiston, J. P. Ramseyer, E. Meyer, C. Andreoli, J. Brugger, P. Vettiger, M. Despont, T. Mezzacasa, L. Scandella, H. J. G¨untherodt, C. Gerber, and J. K. Gimzewski, A chemical sensor based on a micromechanical cantilever array for the identification of gases and vapors. Applied Physics A, 1998, 66, 561–564. 13. J. Fritz, M. K. Baller, H. P. Lang, H. Rothuizen, P. Vettiger, E. Meyer, H. J. G¨untherodt, C. Gerber, and J. K. Gimzewski, Translating biomolecular recognition into nanomechanics. Science, 2000, 288, 316–318. 14. A. Boisen, J. Thaysen, H. Jensenius, and O. Hansen, Environmental sensors based on micromachined cantilevers with integrated read-out. Ultramicroscopy, 2000, 82, 11–16.
15. C. Hagleitner, A. Hierlemann, D. Lange, A. Kummer, N. Kerness, O. Brand, and H. Baltes, Smart singlechip gas sensor microsystem. Nature, 2001, 414, 293–296. 16. G. G. Stoney, The tension of metallic films deposited by electrolysis. Proceedings of the Royal Society of London Series A, 1909, 82, 172–177. 17. G. Wu, H. Ji, K. Hansen, T. Thundat, R. Datar, R. Cote, M. F. Hagan, A. K. Chakraborty, and A. Majumdar, Origin of nanomechanical cantilever motion generated from biomolecular interactions. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98, 1560–1564. 18. P. Grutter, M. Godin, V. Tabbard-Cosa, H. Bourque, T. Monga, Y. Nagai, and R. B. Lennox, CantileverBased Sensing: Origins of Surface Stress, In Proceedings of International Workshop on Nanomechanical Sensors, Copenhagen, Denmark, May 7-10, 2006, 36–37. 19. B. Ilic, D. Czaplewski, M. Zalalutdinov, H. G. Craighead, P. Neuzil, C. Campagnolo, and C. Batt, Single cell detection with micromechanical oscillators. Journal of Vacuum Science and Technology B, 2001, 19, 2825–2828. 20. G. Y. Chen, T. Thundat, E. A. Wachter, and R. J. Warmack, Adsorption-induced surface stress and its effects on resonance frequency of microcantilevers. Journal of Applied Physics, 1995, 77, 3618–3622. 21. F. M. Battiston, J. P. Ramseyer, H. P. Lang, M. K. Baller, C. Gerber, J. K. Gimzewski, E. Meyer, and H. J. G¨untherodt, A chemical sensor based on a microfabricated cantilever array with simultaneous resonance-frequency and bending readout. Sensors and Actuators, B, 2001, 77, 122–131. 22. G. Meyer and N. M. Amer, Novel optical approach to atomic force microscopy. Applied Physics Letters, 1988, 53, 1045–1047. 23. M. Alvarez and J. Tamayo, Optical sequential readout of microcantilever arrays for biological detection. Sensors and Actuators, B, 2005, 106, 687–690. 24. M. Yue, H. Lin, D. E. Dedrick, S. Satyanarayana, A. Majumdar, A. S. Bedekar, J. W. Jenkins, and S. Sundaram, A 2-D microcantilever array for multiplexed biomolecular analysis. Journal of Microelectronic Systems, 2004, 13, 290–299. 25. M. Calleja, J. Tamayo, M. Nordstr¨om, and A. Boisen, Low-noise polymeric nanomechanical biosensors. Applied Physics Letters, 2006, 88, 113901. 26. D. Haefliger and A. Boisen, Three-dimensional microfabrication in negative resist using printed masks. Journal of Micromechanics and Microengineering, 2006, 16, 951–957. 27. J. Thaysen, R. Marie, and A. Boisen, Cantilever-Based Bio-Chemical Sensor Integrated in a Microfluidic Handling System, In Proceedings of IEEE MEMS Conference, Interlaken, Switzerland, 2001, 401–404. 28. J. H. Lee, K. S. Hwang, J. Park, K. H. Yoon, D. S. Yoon, and T. S. Kim, Immunoassay of Prostate-Specific Antigen (PSA) using resonant frequency shift of piezoelectric nanomechanical microcantilever. Biosensors and Bioelectronics, 2005, 20, 2157–2162. 29. Z. J. Davis, G. Abadal, B. Helbo, O. Hansen, F. Campabadal, F. P´erez-Murano, J. Esteve, E. Figueras, J. Verd, N. Barniol, and A. Boisen, Monolithic integration of mass
MICROCANTILEVER ARRAY DEVICES
30.
31.
32.
33.
34.
35.
36.
sensing nano-cantilevers with CMOS circuitry. Sensors and Actuators, A, 2003, 105, 311–319. M. K. Ghatkesar, V. Barwich, T. Braun, A. H. Bredekamp, U. Drechsler, M. Despont, H. P. Lang, M. Hegner, and C. Gerber, Real Time Mass Sensing by Nanomechanical Resonators in Fluid, Proceedings of IEEE Sensors, Vienna, Austria, 2004, 1060–1063. R. McKendry, J. Zhang, Y. Arntz, T. Strunz, M. Hegner, H. P. Lang, M. K. Baller, U. Certa, E. Meyer, H. J. Guntherodt, and C. Gerber, Multiple label-free biodetection and quantitative DNAbinding assays on a nanomechanical cantilever array. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99, 9783–9788. Y. Arntz, J. E. Seelig, J. Zhang, H. P. Lang, P. Hunziker, J. P. Ramseyer, E. Meyer, M. Hegner, and C. Gerber, A label-free protein assay based on a nanomechanical cantilever array. Nanotechnology, 2003, 14, 86–90. G. Wu, R. H. Datar, K. M. Hansen, T. Thundat, R. J. Cote, and A. Majumdar, Bioassay of prostatespecific antigen (PSA) using microcantilevers. Nature Biotechnology, 2001, 19, 856–860. N. Backmann, C. Zahnd, F. Huber, A. Bietsch, A. Pl¨uckthun, H. P. Lang, H. J. G¨untherodt, M. Hegner, and C. Gerber, A label-free immunosensor array using single-chain antibody fragments. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102, 14587–14592. A. G. Hansen, M. W. Mortensen, J. E. T. Andersen, J. Ulstrup, A. K¨uhle, J. Garnæs, and A. Boisen, Stress formation during self-assembly of alkanethiols. Probe Microscopy, 2001, 2, 139–150. R. Marie, A. Boisen, J. Thaysen, H. Jensenius, and C. B. Christensen, Adsorption kinetics and mechanical properties of thiol-modified DNA -oligos on gold investigated by microcantilever sensors. Ultramicroscopy, 2002, 91, 29–36.
11
37. A. J. Detzel, G. A. Campbell, and R. Mutharasan, Rapid assessment of Escherichia coli by growth rate on piezoelectric-excited millimeter-sized cantilever (PEMC) sensors. Sensors and Actuators, B, 2006, in press. 38. N. Nugaeva, K. Y. Gfeller, N. Backmann, H. P. Lang, M. D¨uggelin, and M. Hegner, Nanomechanical cantilever array sensors for selective fungal immobilization and real-time growth detection. Biosensors and Bioelectronics, 2005, 21, 849–856. 39. T. Braun, N. Backmann, M. V¨ogtli, A. Bietsch, A. Engel, H. P. Lang, C. Gerber, and M. Hegner, Conformational change of bacteriorhodopsin quantitatively monitored by microcantilever sensors. Biophysical Journal, 2006, 90, 2970–2977. 40. Y. T. Yang, C. Callegari, X. L. Feng, K. L. Ekinci, and M. L. Roukes, Zeptogram-scale nanomechanical mass sensing. Nano Letters, 2006, 6, 4583–4586. 41. J. K. Gimzewski, C. Gerber, E. Meyer, and R. R. Schlitter, Observation of a chemical reaction using a micromechanical sensor. Chemical Physics Letters, 1994, 217, 589–594. 42. L. A. Pinnaduwage, A. Wig, D. L. Hedden, A. Gehl, D. Yi, T. Thundat, and R. T. Lareau, Detection of trinitrotoluene via deflagration on a microcantilever. Journal of Applied Physics, 2004, 95, 5871–5875. 43. A. Knol, P. B¨achtold, J. Bonan, G. Cherubini, M. Despont, U. Drechsler, U. D¨urig, B. Gotsmann, W. H¨aberle, C. Hagleitner, D. Jubin, M. A. Lantz, A. Pantazi, H. Pozidis, H. Rothuizen, A. Sebastian, R. Stutz, P. Vettiger, D. Wiesmann, and E. S. Eleftheriou, Integrating nanotechnology into a working storage device. Microelectronic Engineering, 2006, 83, 1692–1697. 44. D. Haefliger, R. Marie, and A. Boisen, Self-Actuated Polymeric Valve for Autonomous Sensing and Mixing, Digest of Technical Papers Transducers ’05 Conference, Seoul, Korea, 2005, 1569–1572.
61 Biosniffers (Gas-Phase Biosensors) as Artificial Olfaction Kohji Mitsubayashi Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, Tokyo, Japan
1 A BIOCHEMICAL SNIFFER FOR A GAS-PHASE BIOASSAY
The detection and quantification of gaseous substances with high sensitivity and selectivity are required in many different areas such as environmental assessment, food process control, fire detection, anti-terrorism measures, etc. In addition, some substances in the gas phase can be related to human health and behavior. For example, chemical malodors can affect human mental and physical conditions.1 In several reports, analysis of the volatile components in the expiratory gas of patients can help in the diagnosis of diseases such as oral ailments,2 hepatocirrhosis, and cancer of the lung,3,4 head, and neck regions. Expiratory gas analysis would provide a noninvasive, convenient, and safe method of diagnosing and monitoring disease states. A way for measuring gaseous substances with high sensitivity and selectivity is therefore required. Many types of gas sensors have been investigated and developed. Considerable effort has gone into improving the ethanol selectivity and sensitivity of semiconductor-type gas sensors.5–7 Semiconductor sensors are still inadequate for sensing multianalyte samples such as expiratory gas, because the sensor response is based only on changes in the electrical conductivity of the device, following adsorption
of gaseous substances.1,5–8 Although an improvement in semiconductor sensors and quartz crystal microbalance (QCM) devices (including electronic nose) has been reported, it is still far from the selectivity achievable using biological recognition systems such as enzymes. For the measurement of chemical substances in the liquid phase, biosensors have been extensively researched. Biosensors use biologically derived materials such as enzymes, microorganisms, antigen and antibody, and organelles, which possess high specificity for their substrates.9 It is difficult to use biosensors for detection of gaseous chemicals, however, because of deactivation of the biological component in the gas phase. Some kinds of biochemical gas sensors (biosniffers) as gas-phase bioassay have been developed in many fields such as environmental assessment, clinical and dental measurement, and so on. The biosniffers for continuous monitoring have been constructed using a reaction unit with gas and liquid cells. Stick-type biosniffers as disposable devices for a batch gas measurement have been also fabricated by microelectromechanical systems (MEMS) or screen-printing process. A drug metabolizing system and an enzyme inhabitation mechanism are also used as biological recognition materials. In this chapter, the diaphragm-type and the stick-type biosniffers are introduced with their
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
sensor performances. Applications of the biosniffers (i.e., physiological analysis, dental diagnosis, environmental analysis) are also explained. 2 BIOSNIFFERS WITH A DIAPHRAGM REACTION UNIT 2.1
Alcohol Biosniffer
Expiratory gas analysis would provide a noninvasive, convenient, and safe method of diagnosing and monitoring disease states. One of the major applications of breath analysis is in the quantification and detection of ethanol in expiratory gas after alcohol consumption. Blood ethanol concentration can be determined from its concentration in breath, a blood-breath alcohol partition ratio of 2000 having been widely adopted.10 The breath alcohol level can be related to the degree of intoxication (i.e., haziness: 0.5–1 g l−1 in blood (130–260 ppm in breath); slight drunkenness: 1–1.5 g l−1 (260–390 ppm); drunkenness: 1.5–2.5 g l−1 (390–650 ppm))11 and used as a measure of drunken driving. In certain industrial fields, such as fermentation and distillation, the ethanol vapor concentration can reach toxic levels, causing inflammation of the nasal mucous membrane and conjunctiva, irritation of the skin, and, at high levels, even alcohol poisoning. The maximum permitted concentration of ethanol vapor in the workplace as defined by American Conference of Governmental Industrial Hygienists (ACGIH) is 1000 ppm. Since gaseous ethanol is a malodorous substance for humans (the ethanol selection and detection limits for the human sense of smell have been reported to be 6.1 and 0.36 ppm,12 respectively), The continuous monitoring of ethanol concentration in the gas phase is significant for assessing the human health and behavior related to ethanol vapor from a physiological point of view. An alcohol biosensor for the liquid phase has also been investigated and applied widely for the measurement of ethanol concentration in fermentation processes. Alcohol oxidase (AOD, EC 1.1.3.13) is commonly used in the construction of alcohol biosensors, catalyzing the oxidation of lower primary alcohols according to the reaction: R–CH2 OH + O2
AOD −−−−→
R–CHO + H2 O2
A biosniffer was constructed using the AOD catalytic reaction for the measurement of gaseous substances. 2.1.1 Construction of the Alcohol Biosniffer
Figure 1 illustrates the structure of the biosniffer for measurement of ethanol vapor.13 The sensor consisted of an enzyme electrode, a reaction cell with two compartments for liquid and gas phases, and a porous diaphragm membrane between these compartments. The enzyme electrode was constructed using a commercially available Clark-type dissolved oxygen electrode with an enzyme membrane. AOD (EC 1.1.3.13) was used for constructing the enzyme electrode. For enzyme immobilization, AOD was mixed with acrylamide gel monomer solution in a volume ratio of 1 : 4, then sandwiched between 2 glass plates, and irradiated with a UV lamp (254 nm) for 5 min in order to photocrosslink the monomer solution and immobilize the enzyme. The enzyme electrode was constructed by cutting the enzyme membrane to the required dimensions using a scalpel and placing it onto the sensing area of the dissolved oxygen electrode. Two hollow polytetrafluoroethylene (PTFE) tubes (OD: 40 mm, ID: 20 mm) were cut to a length of 20 mm and the surfaces of the tubes were polished. Four PTFE tube connectors (OD: 6 mm, ID: 2 mm) were screwed into the outside of all of the tapped holes. A porous PTFE membrane was sandwiched between the two tube blocks, which were then held together firmly using a mechanical clamp. In this way, the membrane acted as a separating diaphragm between the two hollow compartments of the tubes. A cylindrical rubber stopcock (OD: 20.5 mm) was inserted into the large hole of one of the tubes, thus forming the gas compartment of the reaction cell. The tip of the enzyme electrode was immersed in the liquid compartment filled with phosphate buffer (0.067 M, pH 7) and adjusted so as to directly touch the surface of the diaphragm membrane. Gas and phosphate buffer solution could be flowed individually through each inlet tube connector to the gas and liquid compartments of the reaction cell, respectively. Gaseous substances in the gas compartment could diffuse through into the liquid compartment of the reaction cell through the PTFE diaphragm membrane.
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION
3
AOD immobilized biosensor
Ringed rubber
Liquid compartment
PTFE pipe Silicon sheet Buffer solution MM vapor PTFE diaphragm membrane Gas compartment MAO-A immobilized biosensor
Ringed rubber
Silicone sheet PTFE pipes
Reaction unit
PTFE diaphragm membrane
Stopcock
Figure 1. Structure of an alcohol biosniffer with a diaphragm reaction unit. [T. Minamide, et al., Sensors and Actuators, B, 2005, 108, 639–645.]
2.1.2 Characteristics of the Alcohol Sniffer
Figure 2 shows the current response of the biosniffer to ethanol in the gas phase at a concentration of 41.5 ppm for 5 min with and without buffer flow (1.9 l h−1 ) through the liquid compartment. As the figure indicates, experiments both with and without buffer flow gave rectangular curves, in which the current decreased rapidly following application of ethanol, followed by a steady state current which gradually increased to the initial output following standard air application. The decrease in output current relates to the concentration of ethanol in the gas phase, since ethanol that
diffuses through the enzyme membrane is oxidized by AOD using oxygen as electron acceptor, causing a decrease in the concentration of dissolved oxygen (see the following equations). AOD
Enzyme reaction : R–CH2 OH+O2 −−−−→ R–CHO + H2 O 2 Working electrode : O2 + 2H2 O + 4e− −−−→ 4OH− Counter electrode : 4Ag + 4Cl− −−−→ 4AgCl + 4e−
102
Standard air
−1.5
Output current (µA)
Buffer flow rate: 1.9 l h−1
−1
10−1 101
100 80 60 40 20 00
10−2 10−3 2 4 6 8 10 Time (min)
10−4 100 101 102 103 104 Concentration of ethanol in gas phase (ppm)
100 −0.5
Nonbuffer flow 0
100
Sensor output (%)
Ethanol vapor (41.5 ppm)
Standard air
0
5
10
15
Time (min) Figure 2. Typical responses for ethanol measurement in the gas phase using the biosniffer with buffer flow and without buffer flow. [Reprinted with permission Mitsubayashi et al.13 copyright 1994.]
Comparison of the curves showed that the sensor current without buffer flow had lower noise and slightly higher sensitivity than with buffer flow. With buffer flow, however, there was a more rapid recovery of the initial current following application of standard air. The steady state current value and the maximum slope calibration curves for ethanol in the gas phase are shown in Figure 3. The inset figure shows the typical response of the biosniffer to gaseous ethanol at various concentrations. In these figures, the steady state output signal is represented as a percentage of the current value for standard air. As Figure 3 indicates, the steady output and the slope of the response were related to the concentration of ethanol in the gas phase over the range of 1.57–41.5 ppm and 15.7–1242 ppm, respectively, deduced from exponential regression analysis of the log–log plot by a method of least squares according to the following equations: Output(%) = 3 × [gaseous ethanol (ppm)]0.943 (1) Slope(s−1 ) = 0.00091 × [gaseous ethanol (ppm)]0.685 (2)
Maximum slope of output (s−1)
ARRAY TECHNOLOGIES
Steady state output (%)
4
Figure 3. Calibration curves of biosniffer using steady state output (filled circles) and maximum response slope (open triangles). Inset: typical response to varying concentrations of ethanol in the gas phase (1.57, 4.49, 7.86, 15.7, 41.5, 98.2, and 680 ppm). [Reprinted with permission Mitsubayashi et al.13 copyright 1994.]
This calibration range using the maximum slope covers the maximum permissible concentration of ethanol vapor in the workplace (1000 ppm) and the alcohol levels encountered in breath (over 130 ppm)11 and can be utilized to determine the level of intoxication as described in the preceding text. The biosniffer was calibrated using the steady state output, to give a detection limit of 1.57 ppm for the sensor (diaphragm membrane pore size: 1–2 µm, thickness: 0.25 mm), which is lower than the ethanol selective detection limit (6.1 ppm), but higher than ethanol detection limit (0.36 ppm) for the human sense of smell.12 2.1.3 Gas Selectivity of the Alcohol Biosniffer
The selectivity of both the biosniffer and the commercially available semiconductor gas sensor for several gases and blends of gases is shown in Figure 4. The semiconductor gas sensor responded to all of the applied gases, confirming the extremely poor selectivity of such devices as generally known.8 The biosniffer using an immobilized AOD electrode, however, gave negligible responses to all the chemicals other than ethanol. The gas-phase sensor output using a mixture of ethanol and n-pentane was the same as the response to ethanol alone with a confidence level of 97.5%. The biosniffer thus possessed much greater selectivity and accuracy than the semiconductor gas sensor.
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION
5
Applied gas substances (concentration: ppm) 96.25
3.26
Ethanol (268.6) Ethanol + n-pentane (268.6 + 301.0)
95.26
100
80
60
40
4.07
2.06
n-pentane (301.0)
3.61
0.63
Benzene (457.4)
3.54
0.50
Methylethyketone (322.5)
0.04
Hexane (569.0)
0.71
Acetone (735.2)
20
0
Gas-phase biosensor output (%)
2.85
3.53
3.96 0
1
2
3
4
5
Semiconductor gas sensor output (V)
Figure 4. Gas selectivity of the biosniffer and semiconductor gas sensor for various substances in the gas phase. [Reprinted with permission Mitsubayashi et al.13 copyright 1994.]
2.2
Acetaldehyde Biosniffer
Gaseous acetaldehyde is also one of the chemical malodorous substances. The maximum permitted concentrations of gaseous acetaldehyde as defined by ACGIH and by the Environment Agency in Japan are 100 and 50 ppm, respectively.14,15 The convenient measurement of acetaldehyde concentration in the gas phase is required in the fields of alcohol fermentation process (brewery, winery) and physiological research of alcohol metabolism as is well known. The bioelectronic sniffer for acetaldehyde vapor was also constructed using the diaphragm reaction unit with the porous diaphragm membrane.16 2.2.1 Acetaldehyde Biosniffer with the Diaphragm Reaction Unit
As mentioned in the previous section, the aldehyde dehydrogenase (ALDH) immobilized biosensor was incorporated into the reaction cell with
both gas and liquid phase compartments separated by the PTFE diaphragm membrane,13 thus obtaining the bioelectronic sniffer for acetaldehyde vapor. Acetaldehyde is dehydrogenated by ALDH using oxidized β-Nicotinamide-adenine dinucleotide (NAD+ , oxidized form) as electron acceptor. Then NADH (reduced form) is dehydrogenated by diaphorase using potassium ferricyanide (1 mmol l−1 ) as an electrochemical mediator, thus obtaining the oxidizing current of its reduction form at the Pt-electrode17 as shown in Figure 5. A fixed voltage of 81 mV (vs a Pt-wire counterelectrode) was applied to the Pt working electrode coated with the hydrophilic polytetrafluoroethylene (H-PTFE) membrane.18 The sensor output was related to the concentration of acetaldehyde in the gas phase over the range 0.525–20 ppm using the 1–2 µm pore size and 0.105–5.25 ppm using the 20–30 µm pore size, respectively, deduced from exponential regression analysis of the log–log plot by a method of least squares according to the following
6
ARRAY TECHNOLOGIES
NAD+
CH3—CHO
2[Fe(CN)6]4− Electrode
ALDH
CH3—CO2−
Diaphorase
2[Fe(CN)6]3−
NADH
2e−
Figure 5. Enzymatic and electrochemical reactions for measuring acetaldehyde. [Reprinted with permission Mitsubayashi et al.16 copyright 2003.]
equation: Pore size : 1–2 µm Output current (nA) = 97.8[acetaldehyde (mmol l−1 )]0.935 (3) Pore size : 20–30 µm Output current(nA) = 226[acetaldehyde (mmol l−1 )]0.979
(4)
By use of the more porous type of diaphragm membrane, it is possible to improve the detection limit from 0.525 to 0.105 ppm of gaseous acetaldehyde. The detection limit of the sniffer is equal to the sensitive level 3 (0.15 ppm) for sense of smell in humans.12 The calibration range of the biosniffer covered the maximum permitted concentrations of acetaldehyde vapor in the United States (100 ppm) and Japan (50 ppm) as described in the preceding text.
3 ODOR ANALYSIS WITH DRUG METABOLIZING SYSTEM FOR ODOR CHEMICALS 3.1
Trimethylamine (Fish-odor) Sniffer with Flavin-containing Monooxygenase
Trimethylamine (TMA, fish-odor substance), is one of the volatile organic compounds (VOCs) and the specified malodorous substances as defined by ACGIH and the Environment Agency, Government of Japan. In certain industrial areas,
such as a chemical plant and a canning factory for marine products, the concentration of TMA fume can reach toxic levels, causing inflammation of the nasal mucous membrane, conjunctiva irritation of the skin, and, at high levels, even a spontaneous combustion (autoignition temperature: 190 ◦ C) and a gas explosion (explosive limit: 2–11.6 vol%).19 The maximum permissible concentration of TMA vapors in the workplace is 5 ppm (12 mg m−3 , time-weighted average (TWA) concentration) and 15 ppm (36 mg m−3 , short-term exposure limit (STEL) concentration) as defined by ACGIH.19 In humans, TMA is metabolized exclusively to trimethylamine N -oxide (TMAO) with up to 60 mg day−1 excreted in the urine of healthy people and less than 5% excreted as the parent compound.20,21 The reaction is widely considered to be catalyzed by flavin-containing monooxygenase (FMO, EC 1.14.13.8) as one of the xenobiotic metabolizing enzymes,22 which can decompose and detoxicate most chemicals in vivo, even the inhaled VOC. Trimethylaminuria or “fishodor syndrome” is a human disorder characterized by an impaired ability to convert the malodorous TMA to its odorless N -oxide.23 A mutation in the FMO gene, which decreases TMA metabolism, has been described recently.24 FMO3 (type 3 of the polymorphic FMO family enzymes) has been recognized to be the major hepatic form in adults and catalyzes the majority of TMAO formation from TMA25 in vivo with the following reaction: TMA + NADPH + H+ + O2
FMO3 −−−−→
TMAO + H2 O + NADP+
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION 0 Trimethylamine
200 Drug metabolizing enzyme
37 ppm
0
111 ppm
37 ppm
0
Sensor output (nA)
Biosniffer
Odorless oxidation form
Figure 6. Drug metabolizing system for trimethylamine in human liver. [K. Mitsubayashi, Annales de Chimie-Science des Materiaux, 2004, 29(6), 103–114.]
Chemical reaction DAsA
111 ppm
7
TMA
Enzymatic reaction O2
Detecting by oxygen electrode
100
0 0
20
40 Time (min)
60
Figure 8. Typical response of the biosniffer to varying concentrations of trimethylamine in the gas phase. [Reprinted with permission Mitsubayashi and Hashimoto26 copyright 2002, IEEE.]
FMO3 AsA
TMAO
H2O
Figure 7. Principle of cyclic reaction for signal-amplified biosensor for trimethylamine (TMA) using FMO3 enzyme and ascorbic acid (AsA) as reducing reagents. TMAO: trimethylamine N -oxide; DAsA: dehydroascorbic acid. [Reprinted with permission Mitsubayashi and Hashimoto26 copyright 2002, IEEE.]
The TMA biosensor was constructed by cutting the FMO3 immobilized membrane to the required dimensions using a cutter and placing it onto the sensing area of the dissolved oxygen electrode (Figure 6).26 In order to amplify the output signal of the biodevices, the substrate regeneration cycle was applied for measuring TMA in the liquid and gas phases by coupling with the reducing reagent system of ascorbic acid (AsA)27 and FMO3 enzyme, respectively (Figure 7).
3.1.1 FMO Immobilized Biosniffer
Figure 8 illustrates the output response of the FMO3 biosniffer with 10 mmol l−1 AsA in phosphate buffer to TMA vapor varying the concentration. The sensor output is represented by the
absolute value of the difference between the initial and the present current value for standard purified air. As the figure indicates, the output increased rapidly following application of TMA vapor, followed by a steady state output that decreased as a result of lowering the concentration of TMA and then approached the initial output following standard air application (TMA free); and this was successfully repeated for the TMA measurement. On the basis of these results, it was possible to use the biosniffer, with good response, for continuous monitoring of the change in the concentration of TMA vapor. The increase in the sensor output relates to the concentration of gaseous TMA, since TMA that diffuses through the enzyme membrane is oxidized by FMO3 using oxygen as an electron acceptor, causing a decrease in the concentration of dissolved oxygen. The sensor output was related to the concentration of TMA vapor over the range of 0.52–105 ppm, deduced from exponential regression analysis of the log–log plot by the leastsquares method according to the following equation: Sensor output(nA) = 2.13[gaseous TMA(ppm)]0.89
(5)
8
ARRAY TECHNOLOGIES
This calibration range of the sniffer with FMO3 covers the maximum permissible concentration of TMA vapor in the workplace (TWA: 5 ppm, STEL: 15 ppm by ACGIH), thus allowing the determination of the level of intoxication. As described in the preceding text, the TMA sensing level 5 (3 ppm) for the human sense of smell was also encountered to the sniffer calibration range.
It has also been reported that breath acetaldehyde is related to its blood concentration as an intoxicant substance, especially for aldehyde dehydrogenase type 2 (ALDH2) deficiency type. Nearly half of the Japanese people are negative for ALDH2. In this section, stick-type biosniffers for the convenient measurement of gaseous ethanol and acetaldehyde in breath air are described.
4 HUMAN ODOR ANALYSIS BY THE BIOSNIFFERS
4.1.1 Construction of Stick-type Biosniffers for Ethanol and Acetaldehyde
4.1
Both biosniffers, for ethanol and acetaldehyde, were constructed in sandwich configurations with a stick shape as shown in Figure 9 (a: ethanol, b: acetaldehyde).29 For the ethanol sniffer, carbon and Ag/AgCl electrodes were formed by printing the respective pastes onto each sides of a filter membrane, respectively. By applying AOD, the oxidation current of hydrogen peroxide being produced by AOD enzyme reaction could be measured by amperometric analysis between carbon and Ag/AgCl electrodes. The electrode-coated membrane was cut using a scalpel into the shape of a stick. In order
Stick-type Biosniffers for Ethanol and Acetaldehyde in Breath Air after Drinking
Expiratory gas analysis would provide a convenient and safe noninvasive method of diagnosing and monitoring disease states. One of the major applications of breath analysis is in the quantification and detection of ethanol and acetaldehyde (as metabolic products of ethanol) in expiratory gas after alcohol consumption. Blood ethanol concentration can be determined from its concentration in breath, a blood-breath alcohol partition ratio of 2000 having been widely adopted.5,11,28
Carbon electrode Filter paper Ag/AgCl electrode
70 mm
Electrical terminal area (10 mm) Cyanoacrylate adhesive
0.36 mm 2 mm
Sensitive area (5 mm)
(a)
Pt electrode (thickness: 3000 Å) 5
65 H-PTFE (ALDH immobilization)
H-PTFE membrane (thickness: 80 µm) Pt electrode
5 Electrical terminal area Styrol resin adhesive 3 (b)
Sensitive area
Figure 9. Structure of bioelectronic sniffers for gaseous ethanol (a) and acetaldehyde (b). [Reprinted with permission Mitsubayashi et al.29 copyright 2005, Elsevier.]
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION
to isolate the sensitive area, a cyanoacrylate adhesive was applied to the middle part of the electrode membrane. The stick membrane was thus separated into three discrete areas: sensitive area, lead area, and electrical terminal area as illustrated in Figure 9(a). AOD was immobilized in the sensitive area of the stick membrane. Figure 9(b) illustrates the structure of the biosniffer for acetaldehyde. The acetaldehyde sniffer was constructed according to a similar method. The platinum electrodes were formed by sputter deposition on both sides of a H-PTFE membrane. The oxidation current of NADH (reduced form) produced by ALDH from the enzyme reaction with NAD+ (oxidized form) could be measured by amperometric analysis between the two Pt electrodes.30 ALDH (EC 1.2.1.5) was immobilized on the additional H-PTFE membrane with PVA-SbQ. 4.1.2 Performances of Stick-type Biosniffers in the Gas Phase
The enzyme electrodes were used as sniffer devices for assessing gaseous substances. A gassampling bag (880 ml) was filled with various concentrations of gaseous substances supplied from the gas generator. The sensitive area of the stick-type sniffers, wetted with 10 µl of phosphate buffer (pH 8, 100 mM, with or without 2 mmol l−1 NAD+ ), was quickly inserted into the opening mouth of the sampling bag containing the gaseous substance. The AOD sniffer responded to standard ethanol vapor and gave a steady state output, which was related to the applied ethanol concentration. The response time to reach 90% of the steady current after applying ethanol vapor was approximately 40 s, which is slower than that in the liquid phase. The steady output was related to the concentration of ethanol in the gas phase over the range 1–500 ppm, deduced from logarithmic regression analysis of the semilog plot by a method of least squares according to the following equation: Output current(µA) = 0.141 × 1.09 log[gaseous ethanol(ppm)] (6) This calibration range covered the alcohol levels encountered in breath (over 130 ppm) after drinking. The detection limit of 1 ppm is lower than
9
the ethanol selective detection limit for the human sense of smell (6.1 ppm).11 The ALDH sniffer was also used to measure acetaldehyde from 0.11 to 10 ppm, deduced from exponential regression analysis of the log–log plot by a method of least squares according to the following equation: Output current(nA) = 108[gaseous acetaldehyde(ppm)]0.430 (7) Upon testing with various gas substances at 2 ppm, the ALDH biosniffer did not respond to any of the chemicals apart from acetaldehyde, thus indicating high gas selectivity attributable to the substrate specificity of ALDH, and similar to that of the AOD sniffer. 4.1.3 Breath Analysis with Biosniffers after Drinking
For physiological applications, the concentrations of ethanol and acetaldehyde in expired gas after drinking were measured for healthy male subjects aged 21–35. Figure 10 illustrates the measurement processes of the breath analysis (ethanol and acetaldehyde) by the biosniffers and gas detector tubes, respectively. The expired gas was collected in the sampling bag at 15 or 20 min intervals after the subjects took 350 ml of beer (5.5% alcohol), and was then used for gas measurement with the same method as described in the preceding text. The sniffer devices were used repeatedly after cleaning the sensitive area with phosphate buffer solution. Both the sniffers for ethanol and acetaldehyde were applied in the analysis of breath air collected from the ALDH2 [+] and [−] subjects after drinking. Figure 11 illustrates the comparisons of the ethanol (a) and acetaldehyde (b) concentration changes with time in breath ethanol between the ALDH2 [+] (open square) and ALDH2 [−] (filled circle) subjects, which had been classified by the ethanol patch test. The concentration values of ethanol in the figure are represented as average of the measured concentrations from the subjects by the biosniffer. As Figure 11(a) indicates, both the concentrations of breath ethanol from the ALDH2 [+] and [−] subjects increased following alcohol drinking,
10
ARRAY TECHNOLOGIES Biosniffer measurement
Alcohol drinking Beer (5.5% alcohol, 350 ml)
Potentiostat
A/D converter
Biosniffer
Breath sampling
Sampling bag (880 ml)
Computer
Detector tube
Figure 10. Measurement processes of breath analysis by the biosniffers and gas detector tubes for ethanol and acetaldehyde after drinking (350 ml of beer: 5.5% alcohol). [Reprinted with permission Mitsubayashi et al.29 copyright 2005, Elsevier.]
with the peak value at 30 min after drinking, and then decreased gradually over a period of hours. These peak values for the ALDH2 [+]5 and [−] subjects were evaluated as alcohol haziness or slight drunkenness levels after drinking (even 350 ml of beer: 5.5% alcohol), and reached the human sense of smell level 3 (100 ppm) for ethanol vapor as noted in the preceding text. It was possible to use the biosniffer repeatedly by rinsing the sensor tip, in contrast with the disposable detector tube. The sniffer device is convenient to use for the noninvasive analysis of ethanol metabolism condition using expired air. As Figure 11(a) also indicates, the breath ethanol concentration in the ALDH2 [−] subjects was higher (approx. twofold) than that in the ALDH2 [+] subjects, from beginning to end of the examination. As a previous paper has reported,31 the lower activity of ALDH2 induced an adverse effect on ethanol metabolism, with the result that ethanol and acetaldehyde remain in the human body for a long time. Breath acetaldehyde as an intoxicant substance was also analyzed by the ALDH sniffer for the ALDH2 [+] and [−] subjects, similar to the breath ethanol measurement. The comparison of the concentration changes in breath acetaldehyde with time between the ALDH2 [+] and ALDH2 [−] subjects is illustrated in Figure 11(b). Like the results of breath ethanol, both the concentrations of breath acetaldehyde from the ALDH2 [+] and
[−] subjects increased following alcohol drinking, with a peak value at 30 min after drinking, and then decreased gradually over a period of hours. The peak concentrations in breath air of the ALDH2 [+] and [−] reached the human sense of smell level 3.5 (0.46 ppm) and 4 (1.4 ppm), respectively, for gaseous acetaldehyde. For example, breath acetaldehyde is a sharper odorous chemical for the human olfactory nerve system than ethanol in breath after drinking. In addition, the acetaldehyde concentration in the ALDH2 [−] subject breath air was much higher (approx. 10-fold) than that of the ALDH2 [+] subjects. The significant difference of breath acetaldehyde concentrations between ALDH2 [+] and [−] subjects is clarified by a T-test. As the results indicated, the lower activity of ALDH2 induced an adverse effect on the ethanol metabolism, thus acetaldehyde remained in the human body, even in human expired air. The biosniffer with high gas selectivity would be an effective and convenient noninvasive approach to evaluate the condition and rate of ethanol metabolism using expired air, even with halitosis. 4.2
Optical Biosniffer for Methyl Mercaptan in Halitosis
An optical biosniffer for methyl mercaptan (MM), one of the major odorous chemicals in halitosis
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION
Ethanol concentration (ppm)
250
11
Tip of sensor Optical-fiber
: ALDH2 [−] [n = 5]
200
Stainless pipe
o-ring
150
Buffer
100
Flow cell
Nylon net Enzyme immobilized membrane
50 : ALDH2 [+] [n = 5] 0
0
1
2
3
Time (h) Acetaldehyde concentration (ppm)
(a) 6
ALDH2 [−] [n = 3]
5
Flow cell 4
Enzyme immobilized membrane Fiber-optic oxygen sensor
3
o-ring
2
Nylon net
ALDH2 [+] [n = 3]
1 0
(b)
Buffer
0
1
2
3
Time (h)
Figure 11. Comparisons of the ethanol and acetaldehyde concentration changes with time in the expired air between ALDH2 [−] (filled circle) and ALDH2 [+] (open square) subjects after drinking. [Reprinted with permission Mitsubayashi et al.29 copyright 2005, Elsevier.]
(bad breath) was also constructed by immobilizing monoamine oxidase type A (MAO-A) onto a tip of a fiber-optic oxygen sensor (OD: 1.59 mm) with an oxygen-sensitive ruthenium organic complex (excitation: 470 nm, fluorescent: 600 nm). After evaluating the sensor characteristics using a gas flow measurement system with a gas generator, the optical biosniffer was applied to expired gases from healthy male volunteers for halitosis analysis as a physiological application. 4.2.1 Construction of an Optical Biosniffer for MM
Figure 12 illustrates the structure of the optical biosniffer for MM vapor.32 The sniffer device
Figure 12. Structure and photograph of an optical biosniffer with a sensor tip cleaning system in the gas phase and the device components. [Reprinted with permission Mitsubayashi et al.33 copyright 2006, Elsevier.]
consisted of an enzyme membrane, a reaction unit, and an oxygen-sensitive optical fiber with an AOD membrane. The optical fiber was coated by solgel process with ruthenium organic complex, which generates optical quenching to the existence of oxygen molecule in both the liquid and gas phases. MAO-A (EC 1.4.3.4.) was used as the MM recognition material for the halitosis biosniffer.33 The performance of the biosniffer for MM vapor was assessed with the batch flow measurement system. The output increased rapidly following application of MM vapor and reached a steady state output within 3 min because of the reduction of optical quenching of the ruthenium organic complex emission induced by the consumption of oxygen (as electron acceptor) which is the result of the MAO-A catalytic reaction with MM. The calibration curve of the optical biosniffer for MM in the gas phase is illustrated in Figure 13.34 An arrow sign in this figure indicates a threshold (200 ppb MM) of pathologic halitosis. As the
12
ARRAY TECHNOLOGIES 34
Sensor output (counts)
32 30 28 26 24 22
Threshold (200 ppb) of pathologic halitosis
20 18
101
102
103 MM (ppb)
104
figure illustrates, the changes in output of the biosniffer were found to be related to the MM concentrations in the gas phase because gaseous MM that diffuses through the enzyme membrane was oxidized by MAO-A using oxygen, causing a decrease in the concentration of dissolved oxygen. The calibration range of the biosniffer for MM vapor was from 8.7 to 11 500 ppb including an MM threshold (200 ppb) of pathologic halitosis and the human sense of smell level 3.5 (10 ppb). The sensor output deduced from logarithmic regression analysis of the semilog plot by a method of a least squares was according to the following equation:
Figure 13. Calibration curve of the optical biosniffer for methyl mercaptan in the gas phase (arrow: 200 ppb MM as threshold of pathologic halitosis). [Reprinted with permission Mitsubayashi et al.33 copyright 2006, Elsevier.]
A/D converter
Sniffer output(counts) = 14.54 + 4.61 log[MM(ppb)] (with10 mmol l
Spectrometer
−1
(8)
AsA)
Light source
Computer MM biosniffer Activated carbon filter Standard air
Gas generator
Mass flow controller Breath sample
Peristaltic pump
Mass flow controller 3-port valve
Stirrer Exhaust gas vent Sampling bag (880 ml)
Breath sampling every 1 h
Healthy male volunteer age : 23.3 ± 0.58 years
Figure 14. Breath analysis procedure and system by the optical biosniffer with MAO-A for methyl mercaptan in the gas phase. [Reprinted with permission Mitsubayashi et al.33 copyright 2006, Elsevier.]
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION
13
4.2.2 Halitosis Monitoring with the Optical Sniffer
For a physiological application, breath samples from healthy male volunteer subjects were applied to the gas measurement system (Figure 14) with the optical biosniffer for monitoring halitosis (expired air). No subjects (23.3 ± 0.58 years) had oral or dental disease. As shown in Figure 14, the expired gas was collected in the sampling bag (800 ml) every 1 h from 7 am to 4 pm in a day, and then used for gas measurement with the same method as described in the preceding text. As the physiological application, the breath samples from healthy male volunteer subjects were provided to the gas measurement system with the optical biosniffer for monitoring halitosis. Figure 15 shows the change of the average and the standard deviation in the biosniffer output corresponding to breath samples from the subjects during the daytime. As the figure indicates, the high output of biosniffer on awakening decreased significantly after breakfast and increased gradually by noon. The elevated sensor signal declined quickly after lunch and increased toward evening again. The sniffer signal would be found to take a regular fluctuation with low deviations dependent on food intakes. As reported in the Lunch
Breakfast
Sensor output (counts)
25 20
Figure 16. A halitosis local analysis with the fiber-optic sniffer to detect an odor source site. [K. Mitsubayashi, et al., Analytica Chimica Acta, 2006, 20, 573–574, 75–80.]
previous papers, human halitosis changes throughout the day, decreasing after food consumption and increasing over the course of time relative to saliva flow,35,36 thus resulting in bad breath on awakening because of reduced saliva secretion during sleep. In this study, the sensor signal to breathe air from young male volunteers had not reached the threshold value (approx. 25.2 counts) calculated from the calibration equation using the MM threshold (200 ppb) of pathologic halitosis. The potential applications of the thin biosniffer include not only the batch analysis of expired air for diagnosing and monitoring disease states in the respiratory and digestive systems, but also a local (spot) analysis to search an odorous source in the mouth cavity (Figure 16), and so on. 5 POTENTIAL APPLICATIONS OF THE BIOSNIFFERS AS ARTIFICIAL OLFACTION
15 10 5 0
8
9
10
11 12 13 Time (h)
14
15
16
Figure 15. Change in the sniffer output to breath sample from healthy male volunteers during daytime. [Reprinted with permission Mitsubayashi et al.33 copyright 2006, Elsevier.]
The detection and quantification of gaseous substances, such as odors, toxic and combustible gases, with high sensitivity and selectivity are required in many different areas. The biosniffers have good gas selectivity because of the biological recognition materials such as enzyme catalytic reaction, drug metabolizing system, and enzyme inhabitation mechanism. The biochemical sniffers measure harmful chemicals (such as VOCs, nerve gases, illegal drugs), not only for environmental assessment but also for antiterrorism measures in place of sniffer dogs. In addition, some substances
14
ARRAY TECHNOLOGIES
Intelligent nose
Detector
A/D convertor
Computer
Computer
Gas substance 1
Standard air Mass flow controller
Gas substance 2 Gas substance 3 Gas substance 4 Gas generator
Intelligent nose system
Mixture box Nose pad
Gas regeneration system
Figure 17. Schematic diagram of a smell communication system with an artificial olfaction.
in the gas phase can be related to human health and behavior. The expiratory gas and human odor analysis by the biosniffer would provide a noninvasive, convenient, and safe method of diagnosing and monitoring disease states, and also a detection of disaster victims. An artificial olfaction was developed with the integrated array system of the fiber-optic biosniffers with biological materials for analyzing and monitoring various kinds of chemicals in the gas phase. A novel chemical code system with nonodorous vapors and a chemical biometrics using human odor pattern have also constructed the selective sniffers because they can recognize and identify gaseous chemicals as digital information in the computer. The intelligent olfaction device would be used for the development of a smell communication system (Figure 17) by integrating with a gas generator, thus improving the quality of chemical information in the gas phase (smell informatics). REFERENCES 1. M. Tonoike, Current status and future view of development for odorant sensors. Bulletin of the Electrotechnical Laboratory, 1988, 52(5), 63–79.
2. J. G. Kostelc, G. Preti, P. R. Zelson, L. Brauner, and P. Baehmi, Oral odors in early experimental gingivitis. Journal of Periodontal Research, 1984, 19, 303–312. 3. M. Watanabe, Unten-tekisei (Driver’s Attitude for Safety Driving. J. Japan Association of Traffic Medicine & Engineering, 1992, 39–46. 4. L. Thomas (ed), Alcohol and Nutrition: The Energy Value of Alcohol in the Diets of Alcoholics, Pamphlet of Monell Chemical Senses Center, 1986. 5. Y. Hiranaka, T. Abe, and H. Murata, Gas-dependent response in the temperature transient of SnO2 gas sensors. Sensors and Actuators, B, 1992, 9, 177–182. 6. T. Maekawa, N. Miura, and N. Yamazoe, Development of SnO2 -based ethanol gas sensor. Sensors and Actuators, B, 1992, 9, 63–69. 7. Z. Chen and K. Colbow, MgO-doped Cr2 O3 : solubility limit and the effect of doping on the resistivity and ethanol sensitivity. Sensors and Actuators, B, 1992, 9, 49–53. 8. X. Wang, S. Yee, and P. Carey, An integrated array of multiple thin-film metal oxide sensors for quantification of individual components in organic vapor mixtures. Sensors and Actuators, B, 1993, 13 – 14, 458–461. 9. I. Karube, H. Matsuoka, S. Suzuki, E. Watanabe, and K. Toyama, Determination of fish freshness with an enzyme sensor system. Journal of Agricultural and Food Chemistry, 1984, 32, 315. 10. A. W. Jones, Variability of the blood: breath ratio in vivo. Journal of Studies on Alcohol, 1978, 39, 1931–1939. 11. S. Sato, K. Kitagawa, in The Portable Alcohol Testerin, Traffic Safety Series, Japan Association of Traffic Medicine & Engineering, MIZUHO printing, Nagoya (Japan), 1993, pp. 26–30.
BIOSNIFFERS (GAS-PHASE BIOSENSORS) AS ARTIFICIAL OLFACTION 12. Japan Environmental & Sanitary Center, A Report of Chemical Malodor Analysis, (A Study for The Japan Environmental Agency), 1980, pp. 248–250. 13. K. Mitsubayashi, K. Yokoyama, T. Takeuchi, and I. Karube, Gas-phase biosensor for ethanol. Analytical Chemistry, 1994, 66, 3297–3302. 14. T. Yoshida, Revision and Trend Measures of Preventive a Bad Smell Code, N.T.S Co., Ltd, Tokyo, 1996, p. 16. 15. Special Pollution Section, Conservation of the Atmosphere Bureau, Environmental Agency, Preventive a bad Smell Code, Gyosei Co., Ltd, 1993, p. 18. 16. K. Mitsubayashi, H. Amagai, H. Watanabe, and Y. Nakayama, Bioelectronic sniffer with a diaphragm flow-cell for acetaldehyde vapor. Sensors and Actuators, B, 2003, 95, 303–308. 17. T. Noguer and J. L. Marty, High sensitive bienzymic sensor for the detection of dithiocarbamate fungicides. Analytica Chimica Acta, 1997, 347, 63–70. 18. T. Noguer and J. L. Marty, An amperometric bienzyme electrode for acetaldehyde detection. Enzyme and Microbial Technology, 1995, 17, 453–459. 19. International Chemical Safety Cards (ICSCs), The International Program on Chemical Safety & the Commission of the European Communities, 1998, pp. ICSC # 0206. Prepared in the context of cooperation between the International Programme on Chemical Safety & the Commission of the European Communities IPCS CEC 1993. http://www.ilo.org/public/english/protection/safework/cis /products/icsc/dtasht/ icsc02/icsc0206.htm. 20. A. Q. Zhang, S. C. Mitchell, R. Ayesh, and R. L. Smith, Determination of trimethylamine and relate aliphatic amines in human urine by head-space gas chromatography. Journal of Chromatography, 1992, 584, 141–145. 21. M. Al-Waiz, S. C. Mitchell, J. R. Idle, and R. L. Smith, The metabolism of 14C-labelled trimethylamine and its N-oxide in man. Xenobiotica, 1987, 17, 551–558. 22. D. M. Ziegler, Recent studies on the structure and function of. multisubstrate flavin-containing monooxygenases. Annual Review of Pharmacology and Toxicology, 1993, 33, 179–199. 23. S. C. Mitchell, The fish-odor syndrome. Perspectives in Biology and Medicine, 1996, 39, 514–526. 24. D. H. Lang, C. K. Yeung, R. M. Peter, C. Ibarra, R. Gasser, K. Itagaki, R. M. Philpot, and A. E. Rettie, Isoform specificity of trimethylamine N-oxygenation by human flavin containing monooxygenase (FMO) and P450
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35. 36.
15
enzymes - Selective catalysis by FMO3. Biochemical Pharmacology, 1998, 56, 1005–1012. C. T. Dolphin, A. Janmohamed, R. L. Smith, E. A. Shepard, and I. R. Philips, Missense mutation in flavincontaining mono-oxygenase 3 gene, FMO3, underlies fishodour syndrome. Nature Genetics, 1997, 17, 491–494. K. Mitsubayashi and Y. Hashimoto, Bioelectronic sniffer device for trimethylamine vapor using flavin containing monooxygenase, IEEE Sensors Journal, 2002, 2(3), 133–139. Y. Hasebe, K. Oshima, O. Takise, and S. Uchiyama, Chemically amplified kojic acid responses of tyrosinasebased biosensor, based on inhibitory effect to substrate recycling driven by tyrosinase and L-ascorbic acid. Talanta, 1995, 42, 2079–2085. T. Maekawa, J. Tamaki, N. Miura, and N. Yamazoe, Development of SnO2 -based ethanol gas sensor. Sensors and Actuators, B, 1992, 9, 63–69. K. Mitsubayashi, H. Matsunaga, G. Nishio, S. Toda, and Y. Nakanishi, Bioelectronic sniffers for ethanol and acetaldehyde in breath air after drinking. Biosensors and Bioelectronics, 2005, 20, 1573–1579. J. K. Park, H. J. Yee, K. S. Lee, W. Y. Lee, M. C. Shin, T. H. Kim, and S. R. Kim, Determination of breath alcohol using a differential-type amperometric biosensor based on alcohol dehydrogenase. Analytica Chimica Acta, 1999, 390, 83–91. N. Enomoto, S. Takase, N. Takada, A. Takada, A. Alcoholic liver disease in heterozygotes of mutant and normal aldehyde dehydrogenase-2 genes. Hepatology, 1991, 13(6), 1071–1075. K. Mitsubayashi, T. Kon, and Y. Hashimoto, Optical bio-sniffer for ethanol vapor using an oxygen-sensitive optical fiber. Biosensors and Bioelectronics, 2003, 19, 193–198. K. Mitsubayashi, T. Minamide, K. Otsuka, H. Kudo, and H. Saito, Optical bio-sniffer for methyl mercaptan in halitosis. Analytica Chimica Acta, 2006, 573 – 574, 75–80. T. Minamide, K. Mitsubayashi, N. Jaffrezic-Renault, K. Hibi, H. Endo, and H. Saito, Bioelectronic detector with monoamine oxidase for halitosis monitoring. The Analyst, 2005, 130, 1490–1494. E. L. Attia and K. G. Marshall, Halitosis. Canadian Medical Association Journal, 1982, 126, 1281–1285. M. Rosenberg, Clinical assessment of bad breath: Current concepts. The Journal of the American Dental Association, 1996, 127, 475–481.
62 Design of Data Algorithms for Blood Glucose Biosensors John J. Rippeth and Wah O. Ho Research and Development, Hypoguard Ltd., Woodbridge, UK
1 INTRODUCTION
Blood glucose biosensor test kits (blood glucose meters, BGMs), are primarily used by diabetics at home or in the workplace. Users are usually people without formal training in clinical diagnostic testing with diverse educational backgrounds and an age range from the young to the elderly. This dictates to the manufacturers that glucose testing meters and strips must be as simple and intuitive as possible with safeguards to minimize the risk of erroneous results. Diabetes is a disease in which the body does not produce or properly use insulin. Insulin is a hormone produced by the pancreas in response to an increase in circulating glucose concentration, for example, after a meal or a sugary drink, that signals cells to absorb glucose and convert this to energy. Diabetics can be classified into two types. Broadly, around 10% of diabetics are Type 1, who are insulin dependent and rely on injections of insulin to control their blood glucose concentrations to within acceptable limits. It is generally recommended that they test at least four times a day. The remaining 90% of diabetics are Type 2, who are noninsulin-dependent and are usually able to manage their blood glucose concentrations through diet, drugs, and exercise. These people usually test less frequently. Three good sources of information with regard to diabetes and diabetes care can be found on the websites from
the American Diabetes Association, Diabetes UK, and the World Health Organization.1–3 Accuracy and precision in glucose measurement is critical in blood glucose biosensor development, as an inaccurate measurement can lead to contradictory treatment to that actually required. The biosensor and meter system must be designed so that the user is unable to affect the result, for example, by placing an insufficient amount of blood onto the sensor strip, or by attempting to test outside the specified operating temperature range. If the BGM is misused, the meter should detect this error state and notify the user with a warning or error.
2 MARKET AND REGULATORY REQUIREMENTS
Various regulatory organizations and market requirements dictate the performance safety limits within which BGMs are expected to perform. These naturally form part of any BGM design input. Documents such as ISO 15197:2003 detail the minimum requirements of BGMs in terms of precision and accuracy.4 Repeatability or precision is evaluated by making 100 replicate measurements at 5 glucose concentrations over specified intervals within the range of 30–400 mg dl−1 (1.7–22.2 mmol l−1 ) (Table 1). Generally, the precision is evaluated by calculating
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
DATA ANALYSIS, CONDITIONING AND PRESENTATION Table 1. Glucose concentration intervals for precision (or repeatability) evaluation
Clarke error grid 600
Glucose concentration
1 2 3 4 5
1.7–2.8 2.9–6.1 6.2–8.3 8.4–13.9 14.0–22.2
500
(mg dl−1 )
Test result (mg dl−1)
(mmol l−1 )
Interval
30–50 51–110 111–150 151–250 251–400
[Reproduced by permission of the European Committee for Standardization.]
C
400
E
B B
200 D
0
Glucose concentration
Interval
Percentage of samples (%)
(mmol l−1 )
(mg dl−1 )
1 2 3 4 5 6 7
5 15 20 30 15 10 5
<2.8 2.8–4.3 4.4–6.7 6.7–11.1 11.2–16.6 16.7–22.2 >22.2
<50 50–80 80–120 120–200 201–300 301–400 >400
[Reproduced by permission of the European Committee for Standardization.]
D C
0
Table 2. Glucose concentrations of samples for system accuracy evaluation and the ideal distribution of the total number of samples at each glucose interval
A
300
100
the average, standard deviation (sd), and the coefficient of variation (CV) (by dividing the sd by the average and multiplying by 100) for each glucose concentration. For concentrations greater than 75 mg dl−1 , a CV value is used which should be less than 5%, and for concentrations less than 75 mg dl−1 , an SD value is used which should be less than 9 mg dl−1 . Accuracy is evaluated by obtaining results from at least 100 donors over a stratified glucose range from <50 to >400 mg dl−1 (<2.8 to >22.2 mmol l−1 ) (Table 2). Acceptable accuracy is defined as having 95% of results falling within 0.83 mmol l−1 (15 mg dl−1 ) of the reference glucose value for glucose concentrations <4.2 mmol l−1 (<75 mg dl−1 ) and within ±20% of the reference glucose value for glucose concentrations ≥ 4.2 mmol l−1 (>75 mg dl−1 ). Reference glucose concentration values are typically obtained from benchtop analyzers such as the YSI 2300 STAT Plus from Yellow Springs Instruments (YSI) Inc.5
A
E
100 200 300 400 500 Reference glucose (mg dl−1)
600
Figure 1. Clarke error grid. (A) <20% bias, clinically accurate result, correct action or inaction; (B) >20% bias but would lead to benign or no treatment; (C) leads to unnecessary corrective treatment; (D) potentially dangerous failure to detect and treat hyper- or hypoglycemia; (E) erroneous treatment zone, corresponding treatments would be opposite to that required to correct hypo- or hyperglycemia.
One commonly used method to assess the accuracy of a system or to compare different systems is to use a Clarke error grid plot, which compares the glucose concentration result obtained from a reference analyzer to the result obtained from a meter and strip test system from the same sample.6 The grid clearly illustrates the consequence of an inaccurate reading and how it can lead to inappropriate treatment (Figure 1). Results falling within zone A are considered clinically accurate, that is, it would lead the user either to a course of action to correct a hypo- or hyperglycemic state or to one of inaction if the glucose result is within the normal range. One of the key areas on the Clarke error grid is at low glucose levels (<70 mg dl−1 ), where a positive bias in meter result can lead to a result in zone D, or worse, in E, which implies a hyperglycemic treatment (e.g., an insulin injection) for a hypoglycemic subject resulting in gross hypoglycemia leading to coma and potentially death.
3 DRIVING FORCES FOR BGM DEVELOPMENT
The three driving forces for the development of a BGM system are as follows: (i) An ability to
DESIGN OF DATA ALGORITHMS FOR BLOOD GLUCOSE BIOSENSORS
fit the lifestyle of the user. These systems will not be used under laboratory conditions of controlled temperature and humidity; neither will the actual blood testing be conducted in a controlled laboratory fashion with any sample preparation or use a specialized sample delivery. The test will usually be performed by placing a drop of blood acquired from a simple fingerprick onto the strip. (ii) Any new system must be competitive in performance and specifications and offer advantages over existing systems in the market or anticipated for market. (iii) Cost, which is continually falling due to competition with more products entering the market from low-cost geographical regions, and increased simplicity of meter and strip design. The above requirements have led to challenges in system development as the market demands continuous performance improvements and additional features, such as glucose trend analysis, smaller blood volumes, shorter time to display result, all at continual lower costs. Advanced strip design and inexpensive bulk manufacturing techniques, such as screenprinting, have reduced costs and improved the quality of BGMs. Improved algorithm design has enabled these biosensors to be interrogated in a manner to meet new marketing specifications. The following is a list of the minimum expected requirements for a new BGM: 1. sample volume <1 µl, preferably <500 nl; 2. read time of <10 s, preferably <5 s; 3. 20–600 mg dl−1 (0.5–33.3 mmol l−1 ) glucose range (hypoglycemia is recognized <40 mg dl−1 ); 4. 30–55% hematocrit, preferably 20–70% hematocrit range, to have <10% deviation in final result; 5. operating temperature 15–35 ◦ C, preferably 10–40 ◦ C; 6. precision: CV <5% in the glucose range 75–600 mg dl−1 (4.2–33.3 mmol l−1 ); 7. accuracy: 95% of results within 20% of a reference glucose value; 8. adequate blood fill detection (insufficient volume of a sample would give a low estimate of the glucose level); 9. blood misdose detection (e.g., blood placed on wrong part of strip, adding a second drop during measurement of the first drop);
3
10. download capability (PC software to analyze glucose trends to assess how well glucose concentration has been controlled); 11. simple to use (single button, calibration free); 12. large display (diabetics may have poor vision); 13. robust (withstand transport in a pocket or bag); 14. discrete (small, easy to carry). 4 BLOOD GLUCOSE METER – SOFTWARE REQUIREMENTS
The algorithms used in biosensor meters can be considered to be split into two functions, the first is the actual control of the meter and how it arrives at the final result and the second is the user interface software. The former should ensure that the electrochemical measurement taken arrives at an accurate final blood glucose value rapidly, using the meter calibration algorithms and any error detection; the latter should be easy and intuitive for a user to make a measurement. The algorithms performed by a particular BGM are very much dependent on the intrinsic performance of the biosensor itself and would be optimized as such. The simplest and most widespread measurement for an amperometric BGM is a single endpoint current measurement, which is converted to a glucose value through an algorithm. Arriving at a correct final glucose value requires BGM algorithms to have the necessary fail-safe mechanisms for simple and reliable use. The flowchart (Figure 2) outlines how such algorithms may operate.
5 INITIAL METER AND STRIP CHECKS
The first part of the meter algorithm is a check of the meter hardware to ensure that all the components are working correctly or are the correct components (i.e., the calibration chip). Meters and calibration chips are often assigned an original equipment manufacturer (OEM) number, which needs to match and is usually done for commercial reasons to separate different geographical markets (which may have different pricing structures) or if a meter system is sold by more than one branded distributor. It can also be used as method of controlling the introduction of an upgraded meter or biosensor strip.
4
DATA ANALYSIS, CONDITIONING AND PRESENTATION Insert the calibration chip into the meter Insert a new biosensor strip Meter switches on and runs selfdiagnostic
Consult your heathcare professional for a new meter or strips with a new calibration chip
Check internal meter OEM number matches keycode OEM number
OEM numbers match?
No
Meter displays error message
Yes
Remove dirty or faulty strip
Meter displays an error message
Yes
Run strip diagnostic − check if strip has a short circuit indicating either a used or dirty strip, or a manufacturing defect
Meter measures temperature
Is temperature within operating limits?
No
Meter displays error message
Move meter and test in a place within the operating temperature limits
Yes
Figure 2. Flowchart illustrating the operational steps taken by users and meter algorithms in obtaining a glucose reading from a typical blood glucose monitor.
DESIGN OF DATA ALGORITHMS FOR BLOOD GLUCOSE BIOSENSORS
5
Select mode to test blood or control solution
Is the sample blood?
No
Use control solution algorithm to calculate glucose result
Yes Polarize strip
Run sample detection algorithm No
Has sample been applied within a preset time limit?
Yes User applies a drop of blood or control solution to the strip
Algorithm detects the sample
Has the current threshold been exceeded to indicate a valid volume of sample?
Yes
Figure 2. (continued).
No
Meter either prompts user for blood or will autoshut down after a preset time limit to conserve battery power
End
6
DATA ANALYSIS, CONDITIONING AND PRESENTATION Monitor the current profile over the measurement time
Run current profile error detection algorithms
Meter displays an error message
Yes
Errors in current detected?
No Record the end-point value (current or charge passed etc), and the temperature and pass these values to the calibration algorithm
Is the raw current (or charge) within an acceptable valid range?
No
Meter displays an error message indicating a faulty strip, meter or sample
End
Yes
Figure 2. (continued).
The second part of the algorithm is a check on the biosensor and other conditions prior to the test being performed. As BGM biosensors are for single use, the meter must be able to determine if a strip has been used or not. Often this is done by simply checking if there is a leakage current between the working and reference electrodes and if this exceeds a set value, an error is indicated; this method can also detect manufacturing defects, for example, short circuiting between electrodes. The next stage is the biosensor measurement. Initially the strip is polarized at the required potential and the current is continuously sampled.
When a sample such as blood enters the strip, the meter detects the current change, and if this exceeds a predetermined threshold, the meter starts to monitor the current being produced over the time of measurement. The initial sampling rate is fast which ensures that the reading is started at an accurate time point but can then be lowered to allow the data to be processed by inexpensive electronic components. During the time between the introduction of a sample and the final displayed meter result, a whole host of processing techniques can be employed. The simplest technique is a single
DESIGN OF DATA ALGORITHMS FOR BLOOD GLUCOSE BIOSENSORS
7
The calibration algorithm consults the calibration table in the codechip to calculate a glucose result
Is glucose result within range?
No
Display a ‘HI’ or ‘LO’ warning message
Yes Display the glucose result
Write the result to memory
Has the user removed the used strip within a preset time limit?
No
Meter auto-shuts off after a preset time limit to conserve battery power
End
Yes Meter auto-shuts off to conserve battery power
End
Figure 2. (continued).
record of the current at the end of the measurement time. This single current value is compared to calibration information and converted by the algorithm to a glucose value. More sophisticated processes can switch the meter to an inactive potential during a preincubation step which allows reagents to dissolve and react with glucose in the sample to produce a buildup of electroactive species such as hydrogen peroxide or a reduced form of a mediator.7 At the end of the incubation period, the meter changes the polarizing potential to an active value
which causes oxidation of the electroactive species and produces a current proportional to the glucose concentration. An advantage with this technique is that given enough reagent, all or most of the glucose can be converted to an electroactive product during the incubation period. The final analytical process is much simplified because there is no need to consider the combined reaction kinetics of both the biochemical reaction between glucose and reagents (i.e., enzymes, mediators) and the electrochemical reaction of either hydrogen peroxide or the reduced mediator at the electrode. The final
8
DATA ANALYSIS, CONDITIONING AND PRESENTATION
current is thus read under a constant concentration of electroactive analyte, which leads to a more precise determination of the current and thus a more precise final glucose result.
Current curve with error detection 400 350
6 ERROR DETECTION
Current
300 250 200 150
Once the current profile of a biosensor has been characterized, then detection of errors in the current measurement profile can be identified and addressed by procedures in the algorithm. Amperometric biosensors are in general expected to follow Cottrell-type current decay behavior, and one strategy for error detection can be to determine deviation from this and thus detect abnormalities.8 This requires the meter to monitor current throughout the measurement period and test for such deviations, which could occur in real time or at the end of measurement. Processing the passing current in real time would mean the meter could flag an error immediately when it is detected, otherwise the meter continues until the end before flagging an error. The choice would be determined by memory capacity and commercial decisions. The first method requires no great memory storage and thus has the potential to be cheaper to implement and probably slightly quicker to display a result, good or otherwise. This current profile analysis must be sensitive enough to detect abnormalities but must not be so sensitive to be triggered by any acceptable background noise or by signal deviations that do not significantly affect the final result. There would be an extremely limited amount of tolerance in the market for a BGM that continuously gave error messages and quickly used up expensive pots of strips. Any error detection must cover current response profiles over the entire glucose response range as well as consider the range of operating temperatures. Therefore, any threshold settings must be validated for the algorithm to operate correctly within these limits. Figure 3 is an example of a typical current response from a BGM with the current measured at various points that could be used as the basis of detecting abnormal current responses. If the current (i0 ) differs positively or negatively from its immediate predecessor (i−1 ) by more than a
100 50
i−2 i−1
i0 icalc
0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Time
Figure 3. A typical current profile from an amperometric biosensor strip with error detection. The measured current (i0 ) is compared to a calculated current (icalc ) which is the extrapolated value from the previous two current values (i−1 and i−2 ). If the difference between i0 and icalc is within some preset limit (e.g., 5%), then no error is generated. This method is useful in detecting sudden current spikes where the current curve departs sharply beyond the preset limit from the expected continued current path (shown as the dashed line continuing from the solid line). The dashed line represents a prediction of current values over time based on a Cottrell current decay. Significant departures from the model could indicate an error in the glucose measurement.
preset value or percentage, then an error is flagged, otherwise the algorithm continues to compare the next measured current to the previous current until the end of the measurement time. This is useful for situations where the current profile grossly deviates over a relatively long period from its expected rate of change of current profile, which could lead to a gross under- or overestimation of the glucose concentration. Another strategy, which could run in parallel with the first error detection above, would be for a second algorithm to compare the measured current (i0 ) to a value of icalc that has been calculated from a linear extrapolation between i−1 and i−2 . If the values of i0 and icalc differ by more than a predetermined limit, then the measurement can be stopped and an error flagged. This is useful for situations where there is a current spike that could cause the current profile to read an unexpectedly high current, leading to a false high-glucose result. A more sophisticated treatment of the current profile error analysis could use the first few
DESIGN OF DATA ALGORITHMS FOR BLOOD GLUCOSE BIOSENSORS
seconds of the current to predict the remainder of the current profile based on the Cottrell model (Figure 3, dashed line). Significant deviations from the model could indicate an error.
7 BLOOD GLUCOSE DETERMINATION
The majority of BGM biosensors are sold in pots or packets of 25–50 strips, which are packaged with an electronic calibration chip or strip that contains calibration information for that specific batch. This is in contrast to older systems where a meter would have a store of predetermined calibration datasets and the user has to enter into the meter a code read off the strips pot. Failure to do so could lead to erroneous results and thus to inappropriate treatment or inaction. This reliance on the user to enter the correct batch specific code was removed when calibration chips were introduced. It was expected that user compliance to change calibration information with a new pot of strips would increase due to the simpler operation of removing an old calibration chip and inserting the new one. This calibration chip is inserted into the BGM and the information is either copied into the meter memory when the meter is turned on or read directly off the chip during meter operation.9 The business model of BGM systems is to create a return on the investment made on strip and meter development and costs of promotion. Fierce competition keeps prices low, and manufacturers and distributors commonly resort to providing users and institutions (e.g., diabetic clinics, hospitals, long-term care homes) with the initial meter and strip package at below manufacturing cost or for free. The return in investment is made by the sale of further strips although competition keeps profit margins low; therefore several packs of strips need to be sold in order to recoup the cost of each meter placed. This means that a meter life cycle is usually at least 3 years during which time controlled changes to the associated test strip may be made. This may be the use of different materials for cost reduction or performance improvement. The advantage of using a swappable chip to provide the calibration information to the meter means that any changes to the performance of the strip, either through product enhancement or
9
variations within manufacturing tolerances, can immediately be accounted for to enable the same meter to deliver a consistently precise and accurate result. This flexibility can be further extended to using strips for analytes other than glucose in the same meter as long as the correct calibration chip is inserted into the meter, for example, the Abbott Medisense Optium Xceed system which also measures blood ketones (ß-hydroxybutyric acid). Some established biosensor products now have such stable manufacturing processes that the same calibration chip can be used for each new batch of strips. The obvious commercial benefit of this is that such meters and strips are advertised as “calibration free” systems, for example, the Abbott Medisense ExacTech RSG system. Users insert a strip into the meter and immediately test; there are no requirements for plugging in separate calibration chips or entering a calibration code, and thus such a system is very simple to use. This is an older biosensor system that has been relaunched as a new meter system that has the calibration built into the meter; such systems are usually sold in low-cost, third-world markets as they often do not offer the performance benefits that the Western market demands. 8 CALCULATION OF THE FINAL GLUCOSE VALUE
This subject is one of the most complex and critical parts of the algorithm where a raw signal such as current with another key factor such as temperature is passed through a calculation process to arrive at an accurate and precise estimate of the concentration of glucose in a blood or control solution sample as judged by the Clarke error grid (Figure 1). Essentially the relationship between glucose concentration, temperature, and current is a three-dimensional surface in which the dependent variable is current. Potentially, the equation used to describe this can be quite complex and can have at least four parameters. The process of developing the algorithm to calculate the glucose concentration may be quite long and complex. However much of the complexity and effort of deriving the descriptive equation for this three-dimensional relationship can be reduced and simplified to a two-dimensional calibration table of glucose concentration, temperature, and current.
10
DATA ANALYSIS, CONDITIONING AND PRESENTATION
Usually, the data in the calibration table is created by a running series of calibration curves for blood or control solution over a wide range of glucose concentrations and temperatures, which is discussed in detail below (control solution is a glucose solution(s) that is used to check if the meter and strip system is working correctly as a quality control check). A calibration table is then independent of any complex calibration calculation, and allows a large amount of flexibility in the dimensions of calibration as this can all be done prior to writing a table as well, ensuring a large degree of future proofing against any changes that may occur.
9 BIOSENSOR CALIBRATION
Glucose determination is done on the basis of biosensor calibration, and it should dictate correctly to the user either a course of action (i.e., inject insulin or ingest glucose) or inaction (glucose concentration acceptable, no adjustment necessary). An incorrect glucose value could lead the user to inappropriate action as exemplified by the Clarke error grid (Figure 1). Biosensor strip manufacture is primarily a batch process. The material of the strip will most likely be supplied on a roll or precut sheets and made in batches, inks are made in batches, and reagents such as enzymes and stabilizers are supplied from batches. Traditionally, the most common, cheapest, and fastest method of manufacturing singleuse disposable test strips is the screenprinting of one or more inks onto a polymer substrate. This process has a start and an end as inks are loaded, printed, dried, and repeated until the strip has been built up, and the number of sheets to be printed has been achieved. This may be followed by the application of the biochemical reagents, typically glucose oxidase or glucose dehydrogenase, with a mediator such as potassium ferricyanide ferrocene or hexaammineruthenium (III) chloride. Common application methods include dropcoating, dipcoating, screenprinting, and ink-jetting, depending on the viscosity of the reagent and quantity. Through this process, batch-to-batch variations of strips arise, since the conditions, or batches of material, printing temperature and humidity, print thickness, and print quality may vary. This could
give rise to slightly different responses in current to the same glucose concentration, hence the need to characterize each batch through a calibration process. This process would also serve to identify where the process has failed, that is, a quality control process in which the product would show an unacceptable calibration (e.g., currents too low, not linear enough, etc.). Calibration usually involves running a series of venous blood samples over a range of glucose concentrations slightly beyond the glucose measurement range claimed by the product, typically 10–900 mg dl−1 . The type of hardware used to operate the strip and record the data is worthy of mention. Commercial or bespoken electrochemical workstations may be used for the initial development of any strip, as these have the advantage of being flexible enough to carry out a wide variety of electroanalytical procedures such as amperometry, coulometry, potentiometry, and impedimetry. The final choice of method is made on the basis of which gives the most precise and accurate result in a reasonably short amount of time for many different batches of strips, and also ideally does not infringe upon the intellectual property (i.e., patents) of other companies. Once a method has been decided, the hardware and software from these electrochemical workstations must be reduced and simplified to the point of a handheld, battery operated, blood glucose monitor operated by a diabetic at home. Blood glucose monitors for home testing comprise a biosensor test strip and an accompanying meter that work together as “the test system”. It is unlikely that a strip from one manufacturer would work correctly, if at all, in another manufacturer’s meter. At worst, a glucose result would be displayed that could be wildly inaccurate and certainly should not be used to indicate any action or inaction. In order to have a high degree of confidence in the results of calibration, the current data should ideally be collected with the same meter used by the user of the strip, so that the data accounts for any hardware characteristics of the meter that may influence the final calculation of the glucose concentration. Using the meter for calibration purposes also saves the need for any time-consuming and expensive validation and verification exercises to qualify the use of such a parallel system.
DESIGN OF DATA ALGORITHMS FOR BLOOD GLUCOSE BIOSENSORS
anticoagulant, hemolysis, differing oxygen tension, and the age of the blood need to be considered. Once a dataset of currents has been collected through many measurements of different glucose concentrations at a variety of temperatures, the mathematical process of fitting a calibration line through the data can begin. Initially, a typical dataset would show a family of current response against glucose concentration curves at each temperature as illustrated in Figure 4. This calibration at its simplest and most preferable would be a linear relationship. This can be fitted with a simple linear equation. Deviations from linearity add a complication, although it may be possible to fit a second-order polynomial or other types of equations such as logarithmic plots and power or exponential fits. Depending on the equation or model chosen, the complexity of using the calibration model to convert any current value to a glucose value will become evident. The complexity further increases when factors other than glucose can affect the current measured. One obvious factor is temperature. The temperature at which the current is measured should also be recorded in order to provide an accurate estimate of glucose over a range of permitted temperatures. Following the determination of the calibration, it is often converted into a simple calibration table containing the three critical factors current (or an equivalent measure, e.g., total charge passed, Cottrell-type measurements), temperature, and glucose. It is this table that is stored in the calibration chip and read by the calibration algorithm in the BGM to convert its raw measurement 500
15 °C 20 °C 25 °C 30 °C 35 °C 40 °C
400 Current (nA)
In practice, these meters may be enhanced by having more memory to collect all of the current response, storing this in memory for later download and analysis, although the essential hardware elements responsible for polarizing the strip and measuring the current would be the same. Using meters has the advantage that many meters can be used in parallel under a variety of temperatures to collect replicate measurements for statistical treatment of the data to estimate the accuracy and precision of the batch of strips. The current is recorded for each glucose concentration at the claimed read time of the product (e.g., 5 or 10 s). The nature of the test samples for deriving the calibration for a batch of strips is worthy of discussion. The usual intended sample for BGMs is fresh capillary blood obtained by a finger prick with a typical volume of 1–10 µl. However, much greater volumes (milliliters) of blood are required in order to fulfill all of the various testing required to derive the calibration data for the batch, and to carry out other quality control checks such as effects of drugs and endogenous substances found in blood that have the potential to influence the glucose result. The use of capillary blood also necessitates the need to run calibration trials at diabetic clinics in order to gain the required information over the entire glucose range which would be costly and time consuming; using healthy volunteers even through a glucose tolerance test would only satisfy a narrow range of what is needed. A glucose tolerance test is where a volunteer imbibes a meal high in sugar to increase their blood glucose; for a healthy individual, this has the transient effect of temporarily increasing the blood glucose, but for a diabetic, the blood glucose will not recover quickly to a normal baseline concentration. To satisfy this requirement for greater volumes of test blood, venous blood is used. Venous blood may be collected into any suitable preservative or anticoagulant such as heparin or potassium ethylenediaminetetraacetic acid (K-EDTA). This blood may then be spiked with glucose from a concentrated aqueous stock solution to the various glucose concentrations required for calibration. The calibrations obtained from venous blood must either match that of fresh capillary blood or be shown to match after a correction factor has been applied. Where venous blood samples may give different responses to capillary samples, issues such as the presence of the
11
300 200 100 0 0
100
200
300
400
500
600
Glucose concentration (mg dl−1)
Figure 4. Glucose calibration curves obtained over a range of temperatures used to derive the calibration table shown in Table 3.
12
DATA ANALYSIS, CONDITIONING AND PRESENTATION Table 3. Calibration table representing the calibration curves shown in Figure 4. Interpolation by the calibration algorithm between the current values in the table at a measured temperature enables the value of the glucose concentration in a blood sample to be estimated. For example, a strip returning a current of 207 nA measured at a temperature of 23 ◦ C would give a glucose value of 250 mg dl−1 . Values beyond the highest glucose value in the table can be linearly extrapolated from the last pair of currents in the table, that is, from the currents, at 500 and 600 mg dl−1 , at each temperature
Glucose (mg dl−1 )
Temperature ( ◦ C)
0 100 200 300 400 500 600
15
20
25
30
35
40
30 91 152 212 258 288 303
38 102 165 229 277 311 329
47 114 180 247 298 335 356
58 127 197 267 321 361 385
70 142 215 288 345 388 415
83 159 235 311 371 417 447
data (i.e., current, charge, voltage) into a glucose value. The amperometric method used to measure the current response from a glucose strip is used along with the calibration table to arrive at a glucose value, this measurement may simply be the value of the current at a defined endpoint, for example, the current after 10 s, to be used by the calibration algorithm to calculate the glucose concentration. The ambient temperature is also measured to allow any temperature correction as the kinetics of the biosensor will be influenced by temperature. The simplest forms of the calibration table contain values which are points or nodes selected from calibration curves of the biosensor glucose–current response at each temperature. The cells in the calibration table (Table 3, Figure 4) contain the value of the current at each pair of glucose concentration and temperature. When a meter has been used with a sample, the final current (or coulometric value, etc.) is recorded together with the temperature. The calibration algorithm compares the recorded current value to the values in the calibration table. If there are no exact matches, then the algorithm can interpolate between neighboring cells to derive the glucose concentration value that will be displayed to the user. Values of current beyond the table limits may, for simplicity, be linearly extrapolated from the edge of the table and the glucose value displayed. An added safety check by the algorithm would be that if the current exceeds the currents in the table beyond a preset limit, then this may indicate
an error state either with the meter or strip and an error message could be indicated to the user; this is an important safety issue as a fault that would give a current that equates to a very high or low glucose value may lead the user to instigate the incorrect treatment on a false diagnosis, whereas an error message would merely lead to a retest. Owing to the nature of utilizing a relatively small number of nodes to represent the full calibration curve, very low or very high glucose concentrations may become increasingly inaccurate, especially if the calibrations curves are not linear over a wide range (ideally 10–900 mg dl−1 ); therefore the choice of node positions and the number of nodes needs to address this issue to achieve an acceptable degree of accuracy at the limits of the calibration curve. The use of a calibration table allows a great deal of flexibility in the glucose calibration, so, complicated mathematical models can be used to characterize the blood glucose response and can then be described by a relatively simple table, without the need to build such models into the meter algorithms, resulting in a saving in the cost of expensive processors.
10 BLOOD GLUCOSE METER USER INTERFACE
This is the part of any meter algorithm that the user will see and control; it must be designed so that the user cannot influence the final blood glucose
DESIGN OF DATA ALGORITHMS FOR BLOOD GLUCOSE BIOSENSORS
result however the meter is used. Meter hardware and software design is often done by consulting groups of meter users, so-called focus groups, to gauge the needs of real diabetic users, to ensure that what is designed and developed fits those needs. After the meter, and its software, has been developed, it undergoes a series of consumer and manufacturer testing to ensure its operation does not lead to undesirable consequences through use; this is essentially a series of challenge tests, that is, making sure all of the documented features of the meter actually work as intended, such as results being stored correctly, alarms working, screens displaying all of the digits and icons correctly, drop tests, vibration tests, and so on, to locate any potential hardware and software errors or oversights. BGMs are designed to be small and portable but not too small as many diabetics have dexterity problems and poor eyesight, so the meter ergonomics needs to be designed for easy handling as well as having a large and clear display for the user to read the result. However, the needs of different customers do differ with medical facilities wanting larger, durable units that can withstand heavy use, while self-testers usually prefer something more discrete so that they can carry the device in a pocket or a small bag. The display must be designed such that any errors or user flags are easily observed by the user, often as extra icons, which in turn must have an obvious symbol; such flag icons can include a thermometer to indicate a high or low temperature, a battery to indicate a low battery, or a word like “Ketone” to indicate the danger of increased ketone concentration associated with a high glucose reading, and hypo- or hyperglycemic flags; these types of flags can also use an audible signal to alert the user. The display is also controlled so that a user knows it is in action during a measurement such as displaying a countdown or a series of diminishing flashing bars. The meter will be designed with a minimum number of buttons, both to remove complexity of use and also to reduce cost. Many meters only have a single button for control; however, extended features in a meter would obviously require extra buttons. The display must be designed in such a way that only the displayed result and not the time or date be recognized as a result leading to a misreading. Similarly the units of measure
13
(either mmol l−1 or mg dl−1 ) must be clearly displayed so that an incorrect diagnosis cannot be made. The units of measure are often changeable on a meter, so depending upon which market a particular meter is destined for, this is often set prior to dispatch so that the user does not have to make any change. The units of measure are usually distinguished by having a decimal point with mmol l−1 and never having a decimal point with mg dl−1 results (e.g., 3.3 mmol l−1 or 60 mg dl−1 ). Most meters feature a memory function that can access previous results for the user to manage their condition; this memory function must distinguish between blood glucose results and any control solution results. Control solutions are supplied with BGM kits so that the user can run a check on the meter and strip prior to use to ensure both are functioning within acceptable limits. Any averaging of blood glucose results should therefore not include control solution results. The averaging is often time based with a number of different averages given such as the average over the last 24 h, 7 days, and 14 days. Some meters even provide a graphing function, so trends can be easily observed (e.g., Lifescan One Touch Ultrasmart ). The results in the meter are often accessible by a personal computer, so a user or clinician can easily download the patient’s data to keep a record and monitor a patient’s condition. While each manufacturer will have their own systems for measuring glucose or any other analyte, the basic principle of converting the raw data (i.e., current (amperometry), charge (coulometry), voltage (potentiometry), resistance, impedance, optical reflectance, or absorbance) obtained from measuring the response from a blood sample in a test strip with a meter, must still pass through a calibration process that correlates the raw data or signal to glucose concentration. Algorithms similar to those described earlier are then able to use this calibration data to present the user with a glucose concentration value. Thus this chapter illustrates that algorithms controlling data and meter responses within blood glucose monitors are the essential interface between the measurement technology and the user, helping to guide millions of diabetics toward good control of their glucose concentration and thus their long-term health.
14
DATA ANALYSIS, CONDITIONING AND PRESENTATION
REFERENCES 1. American Diabetes Association Homepage, http://www. diabetes.org/, 2006. 2. Diabetes UK Homepage, http://www.diabetes.org.uk/, 2006. 3. World Health Organization, Diabetes Program, http://www. who.int/diabetes/, 2006. 4. International Standard, EN ISO 15197, 2003, In vitro Diagnostic Test Systems–Requirements for Blood-Glucose Monitoring Systems for Self-Testing in Managing Diabetes Mellitus. 5. Yellow Springs Instrument Incorporated Homepage, http:// www.ysi.com/, 2006.
6. W. L. Clarke, D. Cox, L. A. Gonder-Frederick, W. Carter, and S. L. Pohl, Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care, 1987, 10, 622–628. 7. N. J. Szuminsky, J. Jordan, P. A. Pottgen, and J. L. Talbott, Method and Apparatus for Amperometric Diagnostic Analysis, US Patent RE36268. 8. F. G. Cottrell, Der Reststrom bei galvanischer Polarisation, betrachtet als ein Diffusionsproblem. Zeitschrift fur Physikalische Chemie, 1902, 42, 385. 9. B. E. White, R. A. Parks, P. G. Ritchie, and T. A. Beaty, Biosensing Meter with Pluggable Memory Key, US Patent 5,366,609.
63 Microarray Analysis Software and its Applications Conrad Bessant Cranfield Health, Cranfield University, Silsoe, UK
1 INTRODUCTION
As discussed in detail elsewhere in this book, array technology permits multiple biological entities to be monitored in a single experiment. Today the term arrays is most associated with gene expression microarrays, but there are many other types of bioarrays. For example, a collection of enzymemediated amperometric biosensors for different metabolites might be used for the determination of fruit ripeness or a chip spotted with antibodies may be used for the detection of a range of proteins. Whatever the array, the way in which the data acquired from it is processed and interpreted requires some thought. It is possible to treat array data simply as a collection of individual assays, but this looses valuable relationships between the individual components of the data, and anyway becomes intractable when dealing with arrays with more than a handful of elements. A more advanced, multivariate, approach to the interpretation of the acquired data is therefore required. The aim of this chapter is to introduce the techniques used to analyze data acquired from bioarrays, focusing primarily on spotted cDNA microarrays as a case study. This focus has been chosen because the data analysis approaches for such arrays are well established, and spotted arrays are the typical format used by researchers generating novel array platforms due to the relative ease of fabrication. The chapter focuses on generic
principles, rather than on specific software packages, hardware platforms, or applications as the details of these change rapidly over time. However, lists of software available at the time of writing are provided as a starting point for those wishing to implement the techniques discussed. Processing of microrray data is best considered in two specific stages. Firstly, it is necessary to determine the quantity of material bound to each spot by processing the image scanned from the array. For gene expression microarrays, this ultimately results in a list of the expression levels of each gene represented on the array. The second stage of analysis is to extract biologically relevant information from this table of expression levels. The exact way in which this latter stage is done depends on the particular biological question being asked, but typically involves some kind of the comparison between the data from different samples. The remainder of this chapter describes these two main analysis stages. 2 IMAGE PROCESSING 2.1
Nature of Data
Before considering how the image data is processed, it is important to appreciate the nature of the data involved. This can vary considerably according to the specific array platform. In the case
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
DATA ANALYSIS, CONDITIONING AND PRESENTATION
of a spotted cDNA array, the starting point is two high-resolution scanned images of the array—one for each of the fluorescent compounds (typically Cy3 and Cy5) used to label the cDNA from the samples being analyzed. The level of fluorescence intensity of a pixel in the image is proportional to the amount of material bound at that particular location. Often the two images are combined (following normalization as described in Section 2.2.2) in such a way that the red component of each pixel represents the intensity at that point of the label associated with the sample of interest, and the green component indicates the intensity of the control label. Therefore, spots associated with genes that are upregulated compared to the control appear red and those that are downregulated appear green. Microarray images are necessarily of high resolution and therefore large (typically at least 1500 × 3500 pixels). These images cannot be compressed using methods of high compression ratio such as JPEG, as these introduce artifacts into the image that degrade the quality of the results.
2.2
Aim of Image Processing
The ultimate aim of the image processing is to produce a list of the relative expression levels for each individual gene. This requires several steps: • Identify spots and separate them from the background (often referred to as feature extraction). • Relate each spot to its associated gene. • Check that each spot is of the required quality, and detect spotting anomalies. • Normalize the data to account for interimage variability, background fluorescence, and nonspecific hybridization. • Determine the relative amount of material bound to each spot. Relating spots to genes is not scientifically challenging, as the designer of the array will have known which fragment of cDNA they were spotting in each position, and therefore what gene each spot corresponds to. However, there is an information management issue in that for any analysis there needs to be a record of the array design, listing the genes represented on the array and the
positions at which they were spotted. Microarray analysis software requires that this information be provided in a suitably formatted file that can be loaded prior to analysis. For commercially available arrays, such files are provided by the array vendor, but for purpose-built arrays these obviously need to be generated by the array designer.
2.2.1 Alignment of Spots to Grid, Determination of Spot Quality, and Errors
Spots on an array tend to be deposited in a simple grid formation, but inherent errors in spotting precision mean that spots are not always on a perfect linear alignment. Furthermore, scanning can introduce a slight angle or displacement to the grid layout. A step is therefore required to rotate and shift the image so that it aligns with the grid design expected for the specific microarray. A grid is then superimposed on the image, in which each spot should fall into a particular cell within that grid. Each cell can then be linked to the relevant gene using the microarray design information mentioned earlier. All of this is fairly straightforward in computational terms and is built into currently available software packages (see Section 2.4) as an automatic process. Sometimes, a spot will not fall fully within a square on the grid. This is an indication of a problem with the array, either regarding the spotting process or contamination. A spot may be out of position or merged with another, or a piece of dust may have fallen on the array, creating a feature in the image that spans multiple grid squares. In these cases the cell in question is usually flagged as being unreliable and therefore excluded from subsequent analysis. If the array is large enough and well designed, there should be repetitions of the spot elsewhere on the array to mitigate this type of problem. Once a spot has been assigned to a grid square, it is defined as a shape to separate it from the background. The purpose of this is both to define which pixels are to be used to calculate the expression level of the gene associated with that spot, and to determine the background level of fluorescence across the array. Assigning a boundary between spot and background can also be used as a quality measure—ideally each spot should be circular, so
MICROARRAY ANALYSIS SOFTWARE AND ITS APPLICATIONS
calculating how well a circle fits to the spot outline is one way of approximating spotting quality. This is a fairly trivial computational process and so can be carried out rapidly in software, even on a microarray with thousands of spots. Distribution of fluorescence across a spot is also an indicator of spotting quality—generally we are seeking uniform distribution across the spot. However, spots sometimes form a concave shape, giving them a donut appearance in the scanned image, or they have a diminishing level of material across the width of the spot.
2.2.2 Normalization
Aside from method development studies, it is unlikely that an array image will be considered in isolation. Real experiments will more typically involve the analysis of multiple samples and/or multiple time points, resulting in multiple array images for a given experiment. To make this type of analysis possible, it is essential to equalize the fluorescence intensity across the group of images so that they can be sensibly considered in the same analysis. This process is referred to as normalization, and essentially involves scaling the intensity of the microarray images such that they are directly comparable across an experiment. Indeed, it is even necessary to normalize the intensities of the two different labels from a single array, as they may be subject to a systematic error, which prevents the intensity of the two labels being directly compared. Such a disparity between labels can be caused by factors such as the scanner, the topology of the array, or the labeling or binding processes. Because of the many potential sources of systematic error, the exact normalization method depends on the type of array and scanning platform being used, and sources of errors can be tackled collectively or in turn. For example, a simple way of addressing inconsistencies in scanning intensity across a set of individual arrays would be to scale the intensities of every pixel in the image such that the background intensity is consistent across the arrays. More often the array will have been designed with a selection of control spots, typically housekeeping genes whose expression level is expected to be consistent across the experiments. The intensity values from each array can then be scaled so that the values for these control spots are
3
consistent across the experiment. There are many more advanced normalization techniques, built on solid statistical foundations, which space does not allow us to include here. Suffice to say, normalization is an essential part of microarray data analysis and it has a significant impact on all the analysis that follows.
2.2.3 Calculation of Expression Levels
Once the above steps have been carried out, determination of the expression levels is straightforward, essentially taking the average intensity of pixels within the defined spot area. These intensities are then stored alongside the spot information in a results file. In cases where intensity is not uniform across the spot, as mentioned in Section 2.2.1, something more advanced than a simple average will be needed to determine a representative spot intensity. Normally, the raw intensities are transformed by taking logs to base 2, as this results in a more convenient distribution of data for most microarray data sets.
2.3
MGED Reporting Standards
To enable sharing of unambiguous data between different researchers, the Microarray Gene Expression Data (MGED) Society produced the MIAME1 (Minimum Information About a Microarray Experiment) standard for reporting microarray results. MIAME captures normalized gene expression data, as well as the raw data from which it was derived, and other pertinent information such as experimental procedures, experimental design, and the design of the microarray. The microarray and gene expression markup language (MAGE-ML) is the primary embodiment of the MIAME standard, providing an extensible markup language (XML)based data format for convenient exchange of data. Most of the microarray image processing software packages are capable of producing MAGE-ML output, and it is often used as a starting point for the data interpretation described in the next part of this chapter. Many scholarly journals now require that researchers submitting papers involving microarray analysis deposit MIAME compliant data supporting their work into a public repository
4
DATA ANALYSIS, CONDITIONING AND PRESENTATION Table 1. Examples of software for microarray image processing
Software BlueFuse GenePix Pro ScanAlyze TIGR Spotfinder (part of TM4)
Provider
License
BlueGnome Molecular Devices Michael Eisen, University of California at Berkeley The Institute for Genomic Research
Commercial Commercial Free for academic use Open source
Web site 4 5 6 7
such as Gene Expression Omnibus (GEO)2 or ArrayExpress.3
the most common multivariate data interpretation techniques are described below.
2.4
3.2
Microarray Image Processing Software
Various software packages are available for microarray image processing. A selection of some of the most cited software available at the time of writing is listed in Table 1. As software specifications can change rapidly, it is recommended that the reader consults the providers’ web sites for the latest information regarding functionality.
3 DATA INTERPRETATION 3.1
Aims
Quantifying the level of expression of each gene on each array is only the first stage in microarray data processing. In most experiments, the researcher will analyze multiple samples, and will want to compare the results from these different samples. Typical aims of the data interpretation step will be identification of differentially expressed genes, clustering of molecular entities according to behavior, clustering of samples according to their profile, or identification of genes whose behavior changes over time. The exact nature of the data analysis will vary according to the biological study being conducted, but analysis of the raw data by eye alone is obviously out of the question when the expression of thousands of genes has been monitored across tens or hundreds of samples. Even for small arrays, the application of multivariate data interpretation techniques can allow more information to be extracted from the available data as it considers the data as a whole, rather than piece by piece. Several of
Nature of Data
Before discussing how data can be analyzed, it is important to consider exactly what data we are starting with and how this is most conveniently organized. In essence, all data collected from a series of array experiments can be represented by some kind of data matrix. In what follows, we will concentrate on gene expression microarrays for simplicity, but the techniques described are equally appropriate to data from other types of array. In a microarray experiment, the gene expression levels for each sample can be represented by a vector of expression measurements, denoted as xi , where i is the sample number. Within this vector, each element xij represents the expression level of gene j on the microarray. The expression level of each gene can be considered to be a variable, of which there are many, hence array data is clearly highly multivariate and multivariate data analysis techniques are required to interpret it. The vectors representing the gene expression levels from individual samples can be amalgamated into an I × J data matrix, X, where I is the total number of samples considered and J is the number of genes per array. Each row of the X matrix therefore represents an individual array, while each column indicates the expression level of each specific gene over all samples. A single data matrix is therefore sufficient to describe all the samples analyzed in a given series of experiments. Figure 1 shows how such a data matrix is constructed. An important issue with microarray data is that missing values are possible due to spots failing the quality tests described earlier, in Section 2.2.1. Most multivariate data analysis algorithms are
MICROARRAY ANALYSIS SOFTWARE AND ITS APPLICATIONS Expression profile
X
xi
Sample number Single intensity measurement Gene ID
xij
Figure 1. Organization of gene expression data into a data matrix. For data from a gene expression microarray, the row vector xi would be the gene expression profile over the samples analyzed. Each column of the matrix represents the expression profile of an individual gene over all sample.
unable to deal directly with missing values, so these need to be replaced or removed. The most elegant solution is to estimate the missing value on the basis of data from the rest of the matrix, although it is important to remember that the new value is only an estimate and there is obviously a limit to the number of values that can be substituted in this way. An alternative approach is to simply remove all the data associated with a particular gene (an entire column) or sample (entire row). Once a data matrix has been constructed, there are essentially two main data interpretation activities that can be of interest: data exploration and sample classification. Approaches for tackling these tasks are described below, along with examples of where these approaches have been used.
5
3.3.1 Scatter Plots
One of the simplest, yet most effective, forms of exploratory analysis is the construction of scatter plots. By plotting, for each gene, a point on a graph at coordinates (aj , bj ), where aj is the expression level of gene j in sample A and bj is the expression level in sample B, genes which show substantially different expression levels between the two samples can be clearly seen. Typically, the expression values are plotted on log scales to provide more clarity to the figure. Genes with similar expression levels fall along a diagonal line across the plot. Genes that fall more than a specified distance from this line can be considered to exhibit a significant difference in expression between the two samples. The definition of a significant difference varies depending on the application and according to the general level of noise in the data, but typically a twofold change in expression would be considered significant. Lines marked on the scatter plot representing a twofold change can be superimposed so that the genes of interest can be clearly seen. The scatter plot shown in Figure 2 is an example of this. Most gene expression analysis software permits the creation of these plots, and allow the user to click on the points of interest to see what genes they relate to. Also, through a simple comparative test, the software is able to automatically generate a list
101
3.3
Exploratory Data Analysis
The aim of data exploration techniques is to provide a way of visualizing variation within large multivariate data sets. This is sometimes an end in itself, but it is also a useful way of evaluating whether the data is of sufficient quality or sufficient information content to warrant further analysis. Clearly, there is no point in expending effort attempting to classify samples into different groups according their gene expression profiles if initial exploration of the data shows that there is no sign of correlation between the data acquired and the sample types analyzed.
Sample
100 10−1 10−2 10−3 10−4 −4 10
10−3
10−2
10−1
100
101
Control
Figure 2. Comparison of data from two microarrays for samples taken from two different positions in mouse brain. The solid line indicates identical expression between the two samples. The dotted lines denote a twofold expression change either way. [Reprinted with permission Brown et al.8 copyright 2002, Coldspring Harbour Press.]
6
DATA ANALYSIS, CONDITIONING AND PRESENTATION
of such genes, which the researcher would then investigate further. Sample number
3.3.2 Principal Components Analysis
A significant limitation of the scatter plot approach is that it is limited to pairwise comparisons, with just two samples in any one plot. If we want to compare data from more than two samples or compare the actual expression profiles of multiple genes, then more advanced techniques are required. One such technique is principal components analysis (PCA). PCA is a way of reducing a large multivariate data matrix into a matrix with a much smaller number of variables, without loosing important information within the data. The principle behind PCA is that the multivariate data can be decomposed by linear projections onto a new coordinate system. The new axes, known as principal components (PCs), are orientated such that the first PC captures the largest amount of common variance. The next PC is orthogonal (meaning totally uncorrelated) to the first and captures common variance in its direction. The maximum number of PCs is limited to the number of variables in the original multivariate data set but, due to the reorientation of the coordinate system to maximize common variance, most data variance can be captured by a much smaller number of PCs due to correlation and redundancy in the original data. In mathematical terms, PCA is the reduction of the data matrix, X, into two smaller matrices, the scores, T, and loadings, P. The product of the two, plus a residual matrix, E, gives the original data matrix (equation 1). X =T ·P +E
T
(1)
There are a number of algorithms for calculating T and P, the most common being nonlinear iterative partial least squares (NIPALS) and singular value decomposition (SVD). In both cases, T is a matrix of column eigenvectors, with the columns in order of largest variance first, hence PCs are delivered in order of their information content. The scores matrix T is determined by multiplying X by the matrix of loadings, P, as shown in Figure 3. In simple terms, this means that the scores for a particular sample are weighted sums of the original
X
P
=
PCs PCs
Gene ID
n×d
n×m
m×d
Figure 3. Relationship between the data matrix (X), scores matrix (T), and loadings matrix (P) in PCA. In this simple example, the number of samples, n, is 10, the number of measured variables (e.g., genes), m, is 7, and the number, d, of PCs considered is 3. The highlighted row in X and column in P show what is required to generate first PC score for sample 3.
variables. For example, the first PC score for the third sample in the data matrix shown in Figure 3 would be calculated as follows: t3,1 = x3,1 p1,1 + x3,2 p2,1 + x3,3 p3,1 + x3,4 p4,1 + x3,5 p5,1 + x3,6 p6,1 + x3,7 p7,1
(2)
In many cases just the first two or three components are sufficient to capture the bulk of the variance in a given data set. Each sample can then be plotted on a simple two- or three-dimensional graph at the position dictated by its first two or three PCA scores. The relative position of the samples in this plot indicates the relative similarities between samples, with similar samples appearing at similar positions within the graph. As PCA uses linear projection, random noise does not fit the model so is relegated to the latter PCs. For this reason PCA lends itself to compression of linear data with simultaneous filtering of random noise. PCA can be used to compress nonlinear data; however, more PCs have to be kept, which would normally be rejected as being noise, as the nonlinear element of the data will be contained within these PCs. An example of a PCA scores plot generated from microarray data is shown in Figure 4. In this study, cells were exposed to the carcinogen benzo(a)pyrene (BaP) and its noncarginogenic isomer benzo(e)pyrene (BeP). Using this plot of the scores of the first two PCs it can clearly be seen that the cells respond differently to the different
Principal component 2
MICROARRAY ANALYSIS SOFTWARE AND ITS APPLICATIONS
7
1.10 1 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0 –0.10 –0.20 –0.30 –0.40 –0.50 –0.60 –0.70 –0.10
0
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1
Principal component 1 Figure 4. A PCA scores plot generated from a data matrix comprising 165 selected genes, monitored over 21 samples. Samples exposed to BaP (black dots) exhibit clearly different behavior to those exposed to BeP (grey dots). [Adapted from Hockley et al., 2006.9 ]
compounds, which provides strong evidence for more detailed investigation.
3.3.3 Hierarchical Cluster Analysis
Hierarchical cluster analysis (HCA) is another exploratory data analysis technique which, like PCA, is designed to reveal relationships between samples or between the molecular entities (e.g., genes) being studied. The result of HCA is a tree diagram, or dendrogram, in which each sample is represented by a branch, and the distance between branch tips indicates the level of similarity between samples. The dendrograms are created by a recursive process in which the pairwise similarity between every sample and every other sample is calculated. The samples representing the two most similar samples are then joined using branches whose length is related to the level of similarity between the samples. The process is then repeated, with the two samples already accounted for being agglomerated in such a way that they can be considered as a single sample. This process is repeated until
all samples have been joined together. An example of the result of this process for a fairly small data set is shown in Figure 5. This method is clearly capable of displaying the relation between entities in a data set, and unlike PCA it is easily extended to very large data sets without cluttering the plot or loosing information. It is therefore very popular in microarray analysis, and many examples of its use can be found in the literature. All hierarchical clustering follows the general approach set out above, but there are a lot of variations in how the similarity between samples is calculated, and how samples are joined together. The primary method of determining the level of similarity between two samples is by calculating the distance between them in the multidimensional space of the measured variables (e.g., the gene expression values). The process is easy to visualize for two measured variables, as shown in Figure 6, but is equally applicable to any number of variables. Taking the two-dimensional case in the figure as an example, the most intuitive distance measure is the euclidean distance—the shortest distance between the two points. This
8
DATA ANALYSIS, CONDITIONING AND PRESENTATION
2
3
4
P– 080 P–138 P–101 P– 078 P– 084 P–166 P–126 P–146 P– 096 P– 093 P– 063 P–142 P–129 P– 039 P– 085 P–136 P– 083 P–151 P– 087 P–172 P–130 P–125 P– 041 P–008 P–133 P–032 P–068 P–092 P–152 P–120 P–148 P–042 P–024 P–074 P–005 P–067 P–018 P–054 P–115 P–072 P–058 P–028 P–053 P–014 P–025 P–073 P–055 P– 097
1
MSN TBX3 LSM3 CKS2 MRPL11 MRPS23
(a) Node positive tumors
P – 008 P – 014 P – 042 P – 055 P – 063 P – 068 P – 085 P – 092 P – 093 P – 096 P – 120 P – 125 P – 126 P – 129 P – 136 P – 138 P – 146 P – 148 P – 172 P – 005 P – 018 P – 024 P – 025 P – 028 P – 032 P – 039 P – 041 P – 053 P – 054 P – 058 P – 067 P – 072 P – 073 P – 074 P – 078 P – 080 P – 083 P – 084 P – 087 P – 097 P – 101 P – 115 P – 130 P – 133 P – 142 P – 151 P – 152 P – 166
Node negative tumors
MSN TBX3 LSM3 CKS2 MRPL11 MRPS23
(b) Figure 5. Example output when performing HCA on gene expression data. In both cases, a data matrix comprising the expression levels of 6 genes measured in 48 samples has been used. These have then been clustered according to (a) the expression profile of each sample and (b) the behavior of each gene. The blocky heat map represents the gene expression data matrix (equivalent to Figure 1), in which the rows and columns have been rearranged in light of the HCA results. [Adapted from Lyng et al., 2006.22 ]
distance, d, is trivially calculated using Pythagoras’ theorem dA,B = (A1 − B1 )2 + (A2 − B2 )2 (3)
be as follows:
dA,B
N = (An − Bn )2
(4)
n=1
Extending this to further variables simply involves adding the squared differences for the other variables within the square root. For the case of N variables, the calculation for each sample would Variable 2 A2
A
C
B
B2
Variable 1 A1
B1
Figure 6. Illustration of distance between samples in variable space. In this case, we consider two samples, A and B, with two measured variables. There are many ways in which the distance between the samples can be calculated.
However, the euclidean distance is not the only measure. If we want to particularly emphasize samples that are markedly different from others, we can amplify the distance by squaring it. For the two-dimensional example, the squared euclidean distance is simply equation (3) with the square root removed. If we want to emphasize the difference between samples according the value of the largest difference between values of a single variable, regardless of what that variable is, we can use the Chebychev distance: dA,B = max |An − Bn |
(5)
Just as there is a choice of method for calculating the distance, or similarity, between two samples, so there is a range of linkage algorithms
MICROARRAY ANALYSIS SOFTWARE AND ITS APPLICATIONS
for joining clusters together as the clustering process progresses. Essentially a linkage algorithm defines which point in a cluster is used to represent that cluster when the distances are calculated. The most obvious approach is the weighted average, where each cluster is represented by the average position in the variable space of the samples that make up the cluster—this essentially represents the “center of gravity” of the cluster. Other popular methods include complete and single linkage. Using complete linkage the distance between two clusters is calculated using the largest distance between individual points in those clusters—this promotes tight clusters over those with more variance. Single linkage is the opposite, where the distance is measured according to the closest two points in the two clusters—this allows clusters to be joined on the basis of just two similar samples, regardless of the spread across the variable space that each cluster exhibits. A more advanced linkage algorithm, called Ward’s method, moves away from simple geometric solutions and joins clusters not just on simple distance measures but according to which of the agglomerated clusters will have the least variance. This approach has the benefit of promoting tight clusters, but does not suffer the sensitivity to outliers found in complete linkage. For this reason, it is often used as the linkage algorithm of choice in microarray work. Sometimes, if noise, correlation, and redundancy are expected to be significant, PCA is applied prior to cluster analysis, with the distance between samples being calculated according to the positions of the samples in PC scores space instead of in the original variable space. Clearly there is a wide range of possible combinations of parameters for performing HCA, and experience shows that these can result in markedly different dendrograms, leading to potentially different interpretations of the data set. It is therefore very important to ensure that the particular distance measures and linkage algorithms used are appropriate, either by considering in detail how each approach works and how this relates to the particular data set being analyzed, or by following the best practice described in the literature for similar data sets. It is also important to consider the robustness of the results obtained—if a particular clustering behavior is observed only in the dendrogram created by a very specific set of HCA
9
parameters then it may not be wise to assume that the clusters genuinely represent the relationships between the samples.
3.4
Classification
In many applications, we are particularly interested in being able to classify samples according to their analytical response. For example, many papers have been published showing how gene expression profiles can be used to classify biological samples into “healthy” and “diseased” states for particular diseases. This is important because it raises the possibility of detecting diseases according to the behavior of multiple biomarkers, rather than a single biomarker as has traditionally been the case. This has the potential to improve diagnosis accuracy, simply because it takes into account more biological factors. Such classification could be done by looking at the output of an exploratory technique such as HCA or PCA, but we really want an automated computational method if we are to ensure objectivity and high data throughput. Multivariate classification is the name given to the data analysis approach used to achieve this. It involves building a classification model from a data matrix acquired from samples of known class. The model is effectively a mathematical transformation relating the measured variable to a number indicating the class of sample (e.g., 0 for healthy, 1 for diseased). Crucially, a separate matrix of data from samples of known class is collected and used to test the resulting classification model. The performance of the calibration model can therefore be quoted using easily understood quantitative measures such as the proportion of test samples that are correctly identified by the model. Alternatively, the performance can be specified in terms of the specificity and sensitivity of the model, which are derived individually from the proportion of correctly identified positive samples and correctly identified negative samples. There exists a plethora of methods for constructing a classification model—far more than can be dealt with in detail here, but the details can be found in chemometrics textbooks.10,11 Provided samples from similar classes cluster well in a PC scores plot, one of the easiest solutions is to divide the scores plot into sections using
10
DATA ANALYSIS, CONDITIONING AND PRESENTATION Table 2. Software for microarray data interpretation
Software ArrayMiner Bioconductor GeneSpring GX Partek Genomics Suite Rosetta Resolver TM4 Vector Xpression
Provider
License
Optimal Design Fred Hutchinson Research Center Agilent Technologies Partek Rosetta Biosoftware The Institute for Genomic Research Invitrogen
a collection of linear boundaries. New samples are then identified according to which side of the boundaries they fall on. In the example in Figure 4 the two response types could easily be defined by inserting a vertical boundary at the point where the PC1 score equals 0.35. This approach is referred to as linear discriminant analysis (LDA). LDA is capable of automatically generating the boundaries using fairly simple mathematics, and the technique can be extended to multiple dimensions—in three dimensions the boundary becomes a twodimensional plane, and in higher dimensions it is a hyper plane. This means that LDA can be used on the original data matrix as well as on PCA scores, regardless of the number of variables measured. In more complex data sets, where there are many classes of sample, or classes of sample which cluster in an unusual shape or with a lot of variance, it is not always possible to separate classes using simple linear features defined by LDA. One solution to this problem is soft independent modeling of class analogies (SIMCA), which works by creating individual PC models for each class, using different numbers of PCs for each class if necessary. Classification of an unknown sample can then be performed by projecting it into each PCA model to look for the best fitting class. If the classes still cannot be defined, it is necessary to look to machine learning approaches such as artificial neural networks (ANNs).12 ANNs are an extremely powerful tool, based on a rough approximate simulation of the neural systems that make up the brain. Given sufficient data, it is theoretically possible to train an ANN to model any relationship that exists between the measured data and sample class, regardless of its complexity. In reality, however, correctly training an ANN is a time consuming and difficult task, and careful validation of the models produced is essential if the network
Commercial Open source Commercial Commercial Commercial Open source Commercial
Web site 13 14 15 16 17 18 19
is not to become over fitted to the test set and therefore unable to classify new samples that are presented to it.
3.5
Software
The are many general-purpose data analysis packages available that have implementations of the algorithms above and can therefore be used to interpret microarray data. Such packages include Matlab, R, and Statistica. As such general packages always carry an overhead in terms of adapting them to a specific task, several packages have been produced specifically for microarray analysis. A selection of some of the most widely used software at the time of writing is listed in Table 2. As with the image analysis software, updates are provided frequently so the reader is encouraged to consult the providers’ web sites. Most of these web sites provide downloadable trial versions of the software, allowing its fitness for purpose to be determined prior to purchase.
4 CONCLUSIONS
This chapter intended to provide an awareness of current approaches for the analysis of data from sensor arrays. Clearly, it has not been possible in the space available to cover all the possible techniques, but those described represent the core of common practice. There is now an everincreasing selection of textbooks available, which explain the approaches covered here in much more detail.20,21 Hopefully, it is clear from this chapter that powerful techniques for the analysis of data from bioarrays are well established. Now that these techniques have been implemented in user-friendly
MICROARRAY ANALYSIS SOFTWARE AND ITS APPLICATIONS
software packages they are within easy reach of the laboratory researcher, but it is important to realize that the processes underlying these analyses are reasonably complex, and that an appreciation of what is happening is essential if we are to have confidence in the information extracted. Looking ahead, bioinformatics is very much an ongoing research discipline, and new algorithms and software are being generated all the time. This will undoubtedly lead to further advances in the information, which can be extracted from gene expression data, and the confidence that we can associate with that data. To give just one example, much work is currently under way to reliably extract gene regulatory networks from gene expression data. The interested reader is encouraged to monitor journals such as Bioinformatics, BMC Bioinformatics, and PLoS Computational Biology to see the directions in which research is progressing.
REFERENCES 1. 2. 3. 4. 5. 6.
http://www.mged.org/Workgroups/MIAME/miame.html. http://www.ncbi.nlm.nih.gov/geo/. http://www.ebi.ac.uk/arrayexpress/. http://www.cambridgebluegnome.com, 2007. http://www.moleculardevices.com, 2007. http://rana.lbl.gov/EisenSoftware.htm, 2007.
11
7. http://www.tm4.org/spotfinder.html, 2007. 8. V. M. Brown, A. Ossadtchi, A. H. Khan, S. Yee, G. Lacan, W. P. Melega, S. R. Cherry, R. M. Leahy, and D. J. Smith, Multiplex three dimensional brain gene expression mapping in a mouse model of Parkinson’s disease. Genome Research, 2002, 12(6), 868–884. 9. S. L. Hockley, V. M. Arlt, D. Brewer, I. Giddings, and D. H. Phillips, Time- and concentration-dependent changes in gene expression induced by benzo(a)pyrene in two human cell lines, MCF-7 and HepG2. BMC Genomics, 2006, 7, 260. 10. M. Otto, Chemometrics: Statistics and Computer Application in Analytical Chemistry, John Wiley & Sons, 1998. 11. R. Brereton, Chemometrics: Data Analysis for the Laboratory and Chemical Plant, John Wiley & Sons, 2003. 12. H. B. Demuth, M. H. Beale, and M. T. Hagan, Neural Network Design, PWS Publishing, 1996. 13. http://www.optimaldesign.com, 2007. 14. http://www.bioconductor.org, 2007. 15. http://www.genespring.com, 2007. 16. http://www.partek.com/, 2007. 17. http://www.rosettabio.com, 2007. 18. http://www.tm4.org/, 2007. 19. http://www.invitrogen.com, 2007. 20. D. Stekel, Microarray Bioinformatics, Cambridge University Press, 2003. 21. G. J. McLachlan, K. A. Do, and C. Ambroise, Analyzing Microarray Gene Expression Data, John Wiley & Sons, 2004. 22. H. Lyng, R. S. Brøvig, D. H. Svendsrud, R. Holm, O. Kaalhus, K. Knutstad, H. Oksefjell, K. Sundfør, G. B. Kristensen, and T. Stokke, Gene expressions and copy numbers associated with metastatic phenotypes of uterine cervical cancer. BMC Genomics, 2006, 7, 268.
64 Data Validation and Interpretation Ursula E. Spichiger-Keller Centre for Chemical Sensors and Chemical Information Technology, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
1 INTRODUCTION
1.1
Communication, Validation, and Information Yield
The development of analytical tools for diagnostic purposes is having an increasing impact in analytical and clinical chemical research. The results of a chemical test contribute to deciding how to treat an individual or a source and are, therefore, economically and socially relevant. Two parameters, the quality of the chemical analysis and the biological uncertainty, together contribute to the information that can be drawn from the specimen that was investigated by chemical analysis. The value of a test result is established using a validation procedure where information from both processes, the chemical analysis and the biological processes, are involved in the final allocation of a result to the population of “affected” or “unaffected” sources. For the qualitative assessment of a diagnostic test, the biological uncertainty1 (intraindividual variation, cvintra , relative to the interindividual variation, cvinter ,) has to be related to the analytical variation (cva relative to cvintra ). In a very useful diagram, Keller2–4 related these criteria to the allowable limits of uncertainty given by CAP5 for a number of diagnostic parameters. The analytical value of a test result is established using an analytical validation process (see Section 3), and the diagnostic value of a test result is established by investigating the biological processes and their uncertainties.
A general drawback of automation with highthroughput screening and array technologies is the production of large amounts of data, which are never transformed into information.4 Screening tests are run to collect information on decisive characteristics of a representative sample of a natural source (individuals, animals, air, rivers, etc.) or a product. Source and receiver (investigator, customer) are connected by a communication process described by Shannon and Weaver.6 They distinguish three planes of communication, which contribute to the uncertainty of an information process: the technical plane (which affects the reliability of the communication process), the plane of semantics (which has to do with the real content of the information contained in the message), and the plane of effectiveness (which concerns the effect of a message on the receiver). By validating the method that is used to yield information, the sources of uncertainty are supposed to be reduced or at least elucidated. If both the analytical and biological validation processes are omitted, however, information is as good as lost! As Gabrieli7 says: “Data per se are lifeless.” Data validation is absolutely necessary to interpret data and to yield information on the status of a source. In this respect, information technology is essential in stringently regulated fields of analytical chemistry such as
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
DATA ANALYSIS, CONDITIONING AND PRESENTATION
environmental chemistry, food chemistry, forensic analytical chemistry, and clinical chemistry.8 The standard procedure is for an analytical method to be validated by the provider and the user, who normally follow different protocols (see Section 3). In addition to the purely technical and statistical validation of results, the plane of effectiveness of the information yielded should be investigated in a second phase as well as how to interpret data (see Section 2). In this second phase, the biological uncertainty of a test result is investigated as well as the impact of a particular information on the receiver. It is important to carry out this phase not only for medical diagnosis but in other fields of analytical chemistry as well, since a misinterpreted analytical result may have serious consequences in both domains.
Table 1. Terminology used to describe the diagnostic performance of a test:4 (i) characteristics of the source(a) and (ii) interpretation of the analytical test result (tr) referred to a fixed discriminator position(b)
1.2
Efficiency
Data Allocation and the Discriminating Power of a Test
Handling a request addressed to an analytical laboratory induces formulation of a diagnostic question comparable to a medical decision. Such questions could be: “What is the phosphate level of the water of a river or lake?”, “Is the hormone level too high or not?”, or “What is the reason for the ‘fish acute toxicity syndrome (FATS)’ in a fish pool?”.9,10 FATS is a respiratory and cardiovascular disease of fish caused by toxic agents in water. The cutoff values which are, as an example, accepted for environmental pollution (the allowable concentration limits), in food technology, and forensic analytical chemistry are regularly based on scientist’s recommendations, which then become fixed in law. However, those working in the field already had extensive validation processes running long before such recommendations were published. The intention of each chemical analysis is to clearly allocate a specimen to the “healthy, unpolluted, unaffected” population or, alternatively, to the “affected, polluted, diseased” one. The discriminating power of a test is defined by its efficiency 11 and efficacy 4 (see Table 1). In the course of this allocation procedure, a set of numerical data is reduced to a binary scale, and the final decision is independent of the distance of a result from the center of gravity (median, mean) of its population. Remarkably, it is usually easier to make a single analysis highly efficient and effective than it
Diagnostic sensitivity
Diagnostic specificity
Positive predictive value, pV+, pVpos
Negative predictive value, pV−, pVneg
Efficacy
Prevalence
TP/DIS
Fraction of correctly allocated DIS, TP results among all DIS TN/REF Fraction of correctly allocated REF, TN results among all REF TP/ALL POS Fraction of true positive test results among all positive test results TN/ALL NEG Fraction of true negative test results among all negative test results (TP + TN)/ALL Fraction of correctly allocated specimens among all classified TP/ALL Fraction of correctly allocated positive tr among all classified tr DIS/ALL Number of affected sources in the population investigated.
[Reprinted from Spichiger-Keller,4 with permission from Wiley-VCH.] (a) DIS: diseased, affected; REF: nondiseased, nonaffected population; ALL: REF + DIS; n: number of subjects, sources, or specimens under study. (b) POS: positive test result; TP: true positive test result (POS and DIS); FP: false positive test result (α-error) (POS and REF); NEG: negative test result; TN: true negative test result (NEG and REF); FN: false negative test result (β-error) (NEG and DIS); tr: analytical test result; Xi , class of values of the ith test.
is to achieve this for an analytical array test since each additional test field in an array statistically decreases the odds of receiving a clearly discriminating result.12,13 If the fields in a test array are responding to independent qualities of a sample, these odds decrease exponentially with the product of the number of test fields. In summary, the probability of receiving a “normal” result decreases with the number of simultaneously evaluated test parameters and depends on the biological interrelationship between test results.12 Example: Between 1979 and 1983, the IFCC published a series of recommendations on the
DATA VALIDATION AND INTERPRETATION
3
represented the reference range after elimination of partially correlating extreme values.
theory of reference values.14 By convention the reference interval of an analyte was defined as the central 0.95 fraction of all values from samples collected from a reference population. If these samples were analyzed by 23 different laboratory tests and if all test results were independent of each other, the probability of finding all test results within the reference range would be 0.9515 which is equal to 0.3 or 30%. Contrarily, if all tests were totally redundant, this probability would be 1.0 and 100%; it would have been sufficient to investigate a sample by only one test. The truth lies mostly in between. A typical example is shown in Figure 1 where, the data of 196 men and 96 women out of 601 male and 528 female blood donors
2 THE DISCRIMINATING POWER OF A TEST AND INTERPRETATION OF ANALYTICAL RESULTS 2.1
The Quality of Screening Tests and Decision Making (The Discriminators)
When screening technology became available in 1970s with high-throughput analysis of biochemical profiles, multiple testing became popular among physicians and hospitals, even though it was not necessarily more cost-effective or did not Univariate
Variable = V14
ALT/UV
Kin.
USZ: 3 –60
U/L, 37 °C
Moments N Mean Std Dev Skewness USS CV T : Mean = 0 Sgn rank Num ^ = 0 D : Normal
601 22.9867 13.3504 2.49169 424501 58.0788 42.2104 90450.5 601 0.151945
Quantiles
Sum wgts Sum Variance Kurtosis Css Std mean Prob > |T| Prob > |S|
601 13815 178.233 11.4641 106940 0.544574 0.0001 0.0001
Prob > D
100% 75% 50% 25% 0%
Max Q3 Med Q1 Min
133 27 20 15 2
Range Q3–Q1 Mode
131 12 19
< 0.01
Histogram
#
135 +*
Boxplot
1
*
1
*
1 4 4 18 23 60 170 267 52
* *
• • • •
*
* * * *** **** ********* **************************** ******************************************* 5 +******** • • • • • • • •
+
+
+
+
+
+
+
+
*
0 0 0 | +
+
*
+
|
+
* May represent up to six counts Figure 1. Frequency distribution of the results of a diagnostic screening test, the alanine aminotransferase (ALT) in the heparinated blood plasma of 601 male blood donors (compare Table 2). To get the reference values for “healthy subjects”, the extreme values were eliminated by an iterative process over 38 laboratory tests. The samples of four hundred and five male blood donors were eliminated by matching the central 0.98 fraction of the results of all laboratory tests. The final reference values for ALT were set to <50 U l−1 for men and women (University Hospital Zurich, older values <60 U l−1 ). These values change with the analytical method applied (optimized kinetic UV test at 37 ◦ C), the population studied, and the sex and age of the subjects investigated. The cutoff value between the undiseased and diseased population is relevant to distinguish the two groups. Data of univariate statistics as presented by the SAS statistics software (SAS Statistics Institute, CA).12,13 [Reprinted from Spichiger and Vonderschmitt13 with permission from the American Association for Clinical Chemistry.]
4
DATA ANALYSIS, CONDITIONING AND PRESENTATION
treatment. A screening test is normally used as the initial step of a sequential process to analyze a risk. Screening in medicine is an attempt to detect disease in asymptomatic persons where the prevalence (see Table 1) is normally small. In preventive medicine, a screening test is typically used to detect a risk (e.g., pollution) before widespread damage occurs. In medical care, a screening test is applied to answer diagnostic questions highly relevant to society and public health such as the early detection of myocardial infarction,18 liver disease,19 diabetes,20 and genetic predispositions,21 but also in preventive veterinary medicine.22,23 For an example, see Table 2.15
always produce more reliable diagnostic results than single analyses. In the 1980s and 1990s, guidelines were published by the American College of Pathologists and the US Preventive Services Task Force, which increased the awareness regarding the prevalence and incidence of specific diseases and the effectiveness of screening tests and preventive examinations.16,17 2.2
The Screening Test as Used in Medical Applications
A diagnostic process in modern medicine is a structured process that starts with the history (anamnesis) of a “case” and ends with the
Table 2. The relationship between the diagnostic parameters and the prevalence of an event. Two hundred and seventeen patients subjected to chronic hemodialysis were investigated with a test for alanine aminotranferase (ALT), an enzyme immunoassay to detect hepatitis C virus (HCV) antibodies and a nested PCR procedure to genotype the HCV/RNA. The objective was to adjust the cutoff value of the ALT test in order to identify patients with HCV infection. The diagram shows an example for the calculations of the diagnostic specificity and sensitivity related to the prevalence of the HCV infection in the selected population. Seventeen infected patients were identified by HCV/RNA positive results. This population was assumed to be truly diseased (DIS). By reducing the cutoff level of the ALT screening test, one more subject was detected as truly positive (TP), which results in an increased sensitivity of the test. Simultaneously, six subjects showed positive ALT values. These subjects have to be additionally investigated by the immunoassay and, in a second step, the HCV/RNA test. Test 1, test 2, allocation of subjects by the ALT test before and after reducing the cutoff value to 50%.15
Previous prevalence, united kingdom Total population: Number average age (years) 217
51.2 y
6.9% = 0.069
(15 / 217) Test 1
Test
Results
Status
NEG
POS
Affected
5
10
0.67
Sensitivity
67%
Unaffected
168
34
0.83
Specificity
83%
173
44
All pV neg
: 0.971
Test parameters
0.227 : pV pos After
test 2
Test
results
NEG
POS
Affected
4
11
0.73
Sensitivity
73%
Unaffected
162
40
0.80
Specificity
80%
Status
All pV neg
166 : 0.976
Test parameters
51 0.216 : pV pos
[Reprinted from Smith and Slenning,23 with permission from Elsevier.]
DATA VALIDATION AND INTERPRETATION
The success of a screening procedure manifests itself in the ratio of individuals who are correctly allocated to the group of “affected” and “unaffected” individuals relative to those who are incorrectly allocated (see Table 1). The parameters that describe this ratio for both groups are the efficiency and, the more economically relevant parameter, the efficacy of a test. These two parameters summarize the quality of a screening procedure, however, they rely on a number of more basic parameters.2,4,11,12,24,25 These basic parameters involve the biological uncertainty described by factors such as the intra- and interindividual variation of test results for healthy and diseased individuals;1,4,12 the typical frequency distribution of the test results for the two populations “unaffected” and “affected”, which include the biological variations; the overlap of the test results for two populations; and the detection limit, which is characteristic for the analytical method. In addition, the analytical uncertainties contribute to the overall uncertainty of the individual allocation (see Section 3). In summary, several factors are related to the efficiency and efficacy of a test: • The prevalence of affected sources, which is the basis of the Bayes Theorem and the Bayes equations (a priori and a posteriori probability of answer A and B) (see Section 7.2. in this volume and Refs 4 and 9) • The position of a cutoff limit (truncation limit) and the distance of an individual value from the cutoff limit, which divides the diagnostic results of two overlapping populations into two entities • The analytical quality of a diagnostic tool, which should allow to distinguish two populations (analytical uncertainty of a result) • The position of the detection and determination limits in a laboratory test referred to the frequency distribution of the “unaffected” (reference values) and the “affected” population • As the sum of all these performance standards, the diagnostic specificity, and sensitivity of a diagnostic tool • The positive and negative predictive value of tests and the likelihood ratio2,11 These factors provide a basis for interpreting the diagnostic result. They allow conclusions
5
to be drawn about the accuracy of the information yielded and the results to be quantified (probability of an event).26 In the following part, these performance criteria are explored in more detail.
2.3
The Frequency Distribution and the Cutoff Value
The diagnostic sensitivity and specificity of a test depend on the position of the cutoff value that separates the two populations, “unaffected” and “affected” (see Table 1). The sensitivity is the response to the question “What percentage of all diseased or affected species are identified by the test result?” (i.e., the fraction of true positive test results). The specificity refers to the percentage of all nonaffected species that show a negative test result (the fraction of true negative results). Both discriminators are linked to a reference population of samples drawn from unaffected sources12,27 or to a cutoff limit that allows the results to be referred to a borderline value (which is typically the case in legal metrology). Unlike analytical sensitivity and specificity, diagnostic sensitivity and specificity refer to the power of the test to separate two populations from each other. The investigator normally is interested in the positive event since this “case” will be investigated further with a set of more specific tests and then normally treated. The positive predictive value of a diagnostic test defines the percentage of species with positive test results that are indeed affected (see Table 1). The negative predictive value describes the opposite situation and answers the question: “What percentage of species with negative test results are really not affected?”. The positive and negative predictive values are influenced by the prevalence of a specific event or “case” in a population (see Table 2). The rarer a case, the higher the uncertainty that a specific test will be able to identify this case. The positive predictive value becomes low. This is the situation with tests to identify many genetic disorders and was the case in tests for identifying HIV in the mid 1980s. For DNA tests, the uncertainty, in the best case, can be compensated for by increasing the number of redundant and dependent results in the nucleic acid profile. Generally redundant tests are not recommended.
6
DATA ANALYSIS, CONDITIONING AND PRESENTATION
They raise costs without providing any additional benefit.15,22,23
2.4
The Likelihood Ratio
In medical diagnostics, the terms considered in the Section 2.3 specify the power of a test to identify a “case” in an epidemiological situation. The diagnostic sensitivity and specificity of a test are regularly specified for new tests and provide valuable information if novel assays are compared to older ones. Gambino,28 however, warned in a critical comment that laboratories often fail to recognize that sensitivity and specificity vary with the strength of the signal observed. A signal and result far higher than the cutoff value is more likely to indicate “disease” than a value just beyond the cutoff is. However, both values are reported as positive. This problem is linked to the final step in chemical analysis of data reduction where data are reduced from a continuous numerical scale to a binary decision. In view of this problem, the likelihood ratio is specified.2,11 In order to evaluate the likelihood ratio, a relevant range, where the values of the affected and not affected population are overlapping, is divided into classes with different “weights”. In each class, the ratio between negative results for those unaffected and positive results for affected sources is calculated. This procedure allows the distance (weight) of a class of results from the cutoff position along a scale of numerical data (x axis) to be taken into account. 2.5
The Influence of the Detection and Determination Limit on Decision Making
The performances of screening tests and point-ofcare tests (POCT)29 that are economically attractive are often of limited analytical quality. It is not primarily the uncertainty of the test that is critical but the detection limit. In order to distinguish between “polluted” sources and natural ones and to sort out “affected” people from a population, a decisive cutoff value has to be set. This cutoff value is a reference limit that allows two different conditions to be distinguished, that is, healthy and diseased or natural and polluted.
Example: For populations suffering from metabolic disorders where a low level of the target analyte as well as a high level are critical (for blood glucose or hormones, for instance), two cutoff values have to be set. These discriminate between three populations namely a “normal” status, a status linked to “low” results and a status linked to “high” results. Such two-sided statistical distributions of test results involving two cutoff values are relatively rare. A similar situation, however, arises in the quality assessment of production lines where vitamins, catalysts, enzymes, dyes, and so on, are added to a product and the quantity of the added compound can be “just appropriate”, “low” or “high” or “out of range” depending on the distance from the center of gravity on both sides of the frequency distribution. Skewed distributions (see Figure 1) are the rule for tests where the detection limit of the test is close to the cutoff value and for environmental specimens where two populations are not clearly separated. The degree of pollution results in a long right-hand tailing of the frequency distribution of the analytical results. In the first case, the distribution of test results is distorted artificially owing to the detection and determination limit of the tests.30 For the design and quality of a screening test, the detection limit of the analytical procedure is most relevant. An inappropriate detection limit will not enable the results to be allocated correctly. The performance of a test may, nevertheless, be sufficient to sort out extreme cases and to identify highly polluted sources. A similar situation arises if the analytical selectivity of a test is insufficient. In contrast, the uncertainty contributes primarily to the rigor with which two events are separated from each other. As a consequence, the diagnostic quality of the test is impaired.
2.6
Point-of-care Testing (POCT)
Emergency tests and a relatively small number of screening tests are preferentially executed on site and near the patient—the so-called “POCT”.29 It is then possible to obtain an answer immediately and to tightly coordinate diagnostics and treatment (remediation). POC tests should therefore be simple, have a reasonable price, and demonstrate the appropriate discriminating power.
DATA VALIDATION AND INTERPRETATION
3 THE VALIDATION OF AN ANALYTICAL PROCESS 3.1
Introduction
The analytical chemist is supposed to answer a specific question about the composition of a specimen by measuring one or several target analytes (or measurands). In many cases in chemical analysis, the measurand will be the concentration of an analyte. However, chemical analysis is used to measure other quantities additionally, for example, color, pH or temperature and therefore the term measurand is more generally used in quality assessment guides. In order to receive the required information, the specialist selects, develops, and uses chemical or physicochemical methods which suit the purpose and provide the necessary quality, which may not necessarily be the best one, but adequate for investigating the specimen. According to Kellner et al.,31 the validation of an analytical method means having “to identify all possible sources of errors which might affect its performance”. The validation of an analytical method is the process that shows whether the results produced by this method are reliable and reproducible, and whether the method is suitable for the intended application. A more substantial and more stringent definition is given by the international organizations such as IUPAC, which refer the definition to reference materials and to quantities defined by the SI (Syst`eme International d’Unit´es) (see subsequent text). However, independent of the definition, the results of every analytical method must meet the goals of discriminating between at least two different conditions of a specimen and two different populations of results. In the preanalytical phase, this discrimination task has to be decided on and the expected efficiency and efficacy of the analytical method must be identified. A result subjected to a high uncertainty is of no value. In parallel, the term model validation describes the “assessment of the extent to which a diagnosis/an assumption/a model is well founded, is tractable, and fulfills the purpose for which it is formulated” (Ref. 11, p. 109). As a basis for the development of multiple tests and diagnostic arrays, a model of the chemical/biochemical
7
background of a diagnostic question must be formulated. This model must be validated on the basis of analytical investigations before it is used daily to solve diagnostic challenges. Depending on how the model performs, it will either be confirmed or rejected. In the first part of this section, the focus was on the diagnostic impact of an analytical method and its uncertainties. In the second part, the technical sources of the analytical uncertainty are considered. The analytical uncertainty is referred to: the choice of the analytical method, the sampling and pretreatment of a specimen, sample storage and transport, the determination process (manual, automatic, highly complex, etc.), calibration and quality of reference specimens, calculations, choice of quantities, presentation of results, validation, and comments.
3.2
Quality Assessment is the Pathway to Validated Results
The basics of classical quality assessment guidelines are described in Ref. 31 The guidelines of international organizations are specified for different applications and purposes and documented in various documents published by IFCC, ISO, and NIST,30,32–35 and in volumes such as the WHO Guidelines for Drinking-Water Quality.36 Moreover, the quality assessment protocols in the EU and the standardization bodies of every country have their own documents on their homepages for downloading. Here, more specific questions concerning the applications of biosensors and sensor arrays and the quality of information are addressed. The procedure for providing a valid diagnosis and a “best practice” treatment is similar worldwide, wherever the standard of medical care is comparable. Therefore, diagnostic tools and treatments can be commercialized globally. The circle can be considered closed, if the analytical methods and results are of comparable quality around the globe. This last goal can be met by implementing the recommendations for the quality assessment of analytical methods and tools of international organizations such as the Cooperation on International Traceability in Analytical Chemistry (CITAC),37
8
DATA ANALYSIS, CONDITIONING AND PRESENTATION
the World Health Organization (WHO),36 the International Federation of Clinical Chemistry (IFCC),30 the International Union of Pure and Applied Chemistry (IUPAC),38 and others. Each of these organizations has a number of committees and subcommittees with specialists who are involved in global surveys and drawing up recommendations. One such organization is the ISO organization in Geneva,32 which publishes international recommendations and standards, known as ISO guides and ISO standards, devoted to a range of specific topics (see Refs 32–35).
3.3
Method Validation and Quantifying Uncertainty
Generally validation of a method means to trace back the results of an analytical investigation to internationally accepted quantities and to the values found in a reference material by a method that achieves the best possible performance linked to the lowest possible uncertainty for a biological sample. The relevant ISO guidelines 15194:2002(E) are entitled “In vitro diagnostic medical devices— Measurement of quantities in samples of biological origin—Description of reference materials”. Section 5.9 of this ISO guide is devoted to the validation process for an analytical method, where the steps involved are: 5.9.1 Planning of the experimental design 5.9.2 Assessment of homogeneity 5.9.3 Statistical evaluation of results 5.9.4 Assessing the stability 5.9.5 Value assignment 5.9.6 Value and uncertainty of measurements assigned by one measurement procedure in one laboratory 5.9.7 Regional recognition (of the reference material).
These subtitles give us an idea of the content and complexity of the “validation process”, which has to be performed not only for traditional wet-chemical screening tests but in as much for analytical procedures by chemical and biochemical sensors such as ion-selective electrodes, immunoassays etc. (see Refs 12, 13, 15, 39, 40).
3.4
The Terminology Used in Chemical Analysis and Diagnostics
The International Vocabulary of Basic and General Terms in Metrology (VIM, International vocabulary of basic and general terms in metrology. ISO, Geneva (1993)) defines a number of statistical terms such as uncertainty, standard deviation, and traceability.
3.4.1 Uncertainty and Standard Deviation
The definition of the term uncertainty (of measurement) used in this protocol is taken from the version adopted in the current International Vocabulary of Basic and General Terms in Metrology: “A parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand.” This parameter may be assigned, for example, a standard deviation (or a given multiple of it) or the width of a confidence interval. The uncertainty of measurement comprises, in general, many components. Some of these components may be evaluated from the statistical distribution of the results of a series of measurements and can be characterized by standard deviations. The other components, which can also be characterized by standard deviations, are evaluated from model probability distributions (model distributions, reference values) based on experience or other information. The ISO Guide refers to these different cases as Type A and Type B estimations, respectively. Every experimentally evaluated, measured value is subjected to uncertainties inherent in the physicochemical procedure and in the handling of a sample. This uncertainty of the value reduces the discriminating power of the result and the performance of the method. The validation process investigates and characterizes the performance of an analytical method and the discriminating power of its results. Simultaneously, the process provides information about the efficiency of the method for the purpose for which the method was selected. One EU document, the EURACHEM/CITAC guide,41 (2nd edition), is devoted to “Quantifying Uncertainty in Analytical Measurement”.
DATA VALIDATION AND INTERPRETATION
3.4.2 Traceability and Comparability
The VIM-guide, ISO, Geneva (1993) defines traceability as the “property of the result of a measurement or the value of a standard whereby it can be related to stated references, usually national, or international standards, through an unbroken chain of comparisons all having stated uncertainties”. This definition implies a need for effort at the national and international level to provide widely accepted reference standards, and at the individual laboratory level to demonstrate the necessary links to these standards. At the national and international level, the comparability between national measurement systems is being continually improved by intercomparison of measurement standards at the National Metrology Institute (NMI) level. A multilateral mutual recognition agreement was signed in 1999 by the member nations of the Meter Convention in response to the need for an open, transparent, and comprehensive scheme to give users reliable quantitative information on the comparability of national metrology systems.
3.5
Standard Reference Materials (SRMs)
These are to a large extent provided by (European) Institute for Reference Materials and Measurements (IRMM) 42 and the (US) National Institute for Standardization (NIST) 43 : http://ts.nist.gov/ts/ htdocs/230/232/232.htm) The National Institutes for Standardization such as NIST support accurate and compatible measurements by certifying and providing Standard Reference Materials (SRMs) with well-characterized composition or properties, or both. The mission of the IRMM is to promote a common and reliable European measurement system in support of EU policies. The prime objective of the IRMM is to build up confidence in the comparability of measurements by producing and disseminating internationally accepted quality assurance tools. These tools include validated methods, reference materials, reference measurements, interlaboratory comparisons, and training. NIST provides more than 1100 products. These are used to perform instrument calibrations in units as part of the overall quality assurance programs, to verify the accuracy of specific measurements,
9
and to support the development of new measurement methods. Industry, academia, and government use reference materials such as NIST SRMs “to facilitate commerce and trade and to advance research and development. NIST SRMs are also one mechanism for supporting measurement traceability in the United States”.43 NIST SRMs are currently available for use in areas such as microanalysis, health, and industrial hygiene (e.g., DNA profiling), forensics (e.g., drug abuse, DNA profiling), ion activity (pH, pNa, pK, pCl, pF), and food and agriculture (e.g., vitamins, fat, proteins). Reference materials (RM) can be ordered on-line (https://srmors.nist.gov/). The products are labeled as “Certified Reference Material (CRM), Reference Material (RM), NIST Standard Reference Material (SRM), NIST Reference Material, NIST Traceable Reference Material (NTRM )”. The homepage43 provides a link where definitions of these materials can be found. Similar to the label of the materials, the values of the amount or concentration of a target analyte is defined by the terms Certified Value and Reference Value. The certificates for the content and specification of the products are shipped together with the product. The certificates define and confirm the quality of the product.
3.6
‘‘Abuse and Misuse of Quantities’’31
The first edition of the “Manual of Symbols and Terminology for Physicochemical Quantities and Units” was prepared for publication on behalf of the Physical Chemistry Division of IUPAC by M.L. Glashan in 1969. He described the objective of his contribution in the preface to that first edition as being “to secure clarity and precision, and wider agreement in the use of symbols, by chemists in different countries, among physicists, chemists, and engineers, and by editors of scientific journals”. (Ref. 38). By convention physical quantities are organized in a multidimensional system built upon seven base quantities (length, mass, time, electric current, thermodynamic temperature, amount of substance, and luminous intensity). All other physical quantities are called derived quantities. The dimensions of these quantities are algebraically derived from the seven base quantities by multiplication and division. Units, which do not
10
DATA ANALYSIS, CONDITIONING AND PRESENTATION The process of chemical analysis: analytical and diagnostic validation of data
The customer’s request: Is a specific source polluted? Is an animal/person diseased? Specimen
• • • •
Yes? No?
•
Preconditioning, pretreatment of the specimen, stability assessment of the analyte, chemical analysis
Output: raw data, readout
•
Analytical data validation: Calibration: scaling, produces a quantitative result. Quality control, statistics: reliable quantitative result. Validation by a reference material (SRM): Result of general acceptability. Fix specific analytical parameters: detection limit, selectivity, sensitivity (slope of the calibration function), uncertainty of the method, lifetime of the tools, dynamic range. Method comparison: comparability of results and reference range investigated by other methods.
No
Analytical performance acceptable? Yes
Diagnostic data validation: efficiency of a procedure Investigate the reference range for the negative and positive event by investigating a statistical number of sources with known history. Evaluate the scattering range of data within sources and between sources. Fix the cut off value to discriminate events and sources; investigate the diagnostic specificity and sensitivity of the test in account of the cutoff value (seeTable 1). Investigate the likelihood ratio: (positive results/all affected) relative to (negative result/all unaffected). Increase the prevalence of an event by using screening tests and set the cutoff value at high sensitivity and low specificity not to exclude polluted sources (high pV negative). Adjust the cutoff value of the screening test. 1. Use different non redundant screening tests in a strategic sequence to increase the prevalence of the positive event. 2. Fix the reference range for the negative and positive event. Investigate unknown sources. Data reduction to a binary scale: Allocate the result to the class of affected or unaffected sources.
No No interaction necessary
Yes?
Output to the customer’s request: Is a specific source polluted? Is an animal/person diseased?
No? Yes
Interaction necessary
Figure 2. The process of chemical analysis: analytical and diagnostic validation of data.
DATA VALIDATION AND INTERPRETATION
conform to these fundamental guidelines, are not recommended. Given the SI dimensions (Syst`eme International), quantities such as ppm, ppb, mmHg, and g/100 ml are not recommended and should not be used anymore. It is absolutely essential to state which quantity is measured by the analytical method. A typical example is that of measuring the active molality of substrates and electrolytes by biosensors and ion-selective electrodes, which is reported in molar units (mol−1 instead of osmol or active molality per mass of solvent (in mol per kg water)). The active molality is a quantity defined on a purely thermodynamic basis and, at the same time, it is the quantity measured by sensors and biosensors in a specimen directly. This quantity is independent of the amount of proteins, lipids, and water in a specimen. Unfortunately, most reference materials also do not yet routinely report these quantities.
4 CONCLUSIONS
The technical validation of methods and procedures which are applied to investigate the substance concentration of decisive chemical compounds (analytes, measurands) is absolutely necessary in order to be able to interpret the results of laboratory tests. The technical validation has to be executed globally on the basis of generally valid international recommendations and rules for the results to be globally comparable. The goal of the technical validation of analytical procedures is to minimize the technical uncertainty of laboratory results. In addition to the technical uncertainties, biological variations, and shifts of the value of a measurand contribute to the overall uncertainty of a test result. In order to investigate these natural uncertainties, the technical uncertainties must be known. Figure 2 provides an overview on the subsequent validation processes involved. The procedure and rules are the basis to validate the analytical data, to reduce data to a binary decision, and to draw conclusions in environmental control, health monitoring, quality assessment of food, and others. The whole process is the fundament of actions to be initiated.
11
REFERENCES 1. C. G. Fraser, Interpretation of Clinical Chemistry Laboratory Data, Blackwell Scientific, Oxford, 1986. 2. H. Keller, Clinical and laboratory investigation. Scandinavian Journal of Clinical and Laboratory Investigation, 1986, 46, Suppl. 181, 1–74. 3. H. Keller, Klinisch-Chemische Labordiagnostik f¨ur die Praxis, Georg Thieme Verlag, Stuttgart, New York, 1986. 4. U. E. Spichiger-Keller, Chemical Sensors and Biosensors for Medical and Biological Applications, Wiley-VCH, Weinheim, 1998. 5. College of American Pathologists (CAP), Analytical, Goals in Clinical Chemistry, in Proceedings of the 1976 Aspen Conference on Analytical Goals in Clinical Chemistry, F. R. Elevitch (ed), British Library, Boston, Special Issue 6842–48635, 1978. 6. C. E. Shannon and W. Weaver, The Mathematical Theory of Communication, University of Illinois Press, Chicago, 1949. 7. E. R. Gabrieli, Clinically Oriented Documentation of Laboratory Data, Academic Press, London, 1972, pp. 9–36. 8. K. Eckschlager and K. Danzer, Information Theory in Analytical Chemistry, in Chemical Analysis, J. D. Wineforder (ed), John Wiley & Sons, New York, 1994, Vol. 128. 9. http://www.epa.gov/Region5/defs/html/tsca.htm EPA Region 5, Toxic Substances Control Act of 1976. 10. S. P. Bradbury, T. R. Henry and R. W. Carlson, in Practical Applications of Quantitative Structure-Activity Relationship (QSAR) in Environmental Chemistry and Toxicology, Chemical and Environmental Science Series W. Karcher, and J. Devillers (eds), Kluwer Academic Publisher, Dodrecht, 1990, Vol. 1, pp. 295–315. 11. H. Keller and Ch. Trendelenburg, Data Presentation, Interpretation, in Clinical Biochemistry, H. Ch. Curtius and M. Roth (eds), Walter de Gruyter, Berlin, New York, 1989, Vol. 2. 12. U. Spichiger-Keller, A Selfconsistent Set of Reference Values, Ph.D. Thesis Nr. 8830, Swiss Federal Institute of Technology, 1989. 13. U. E. Spichiger and D. Vonderschmitt, A self-consistent set of reference values for 23 clinical chemical analytes. Clinical Chemistry, 1989, 35, 448–452. 14. H. E. Solberg, IFCC, 1985/5, The theory of reference values, Part 5. Statistical treatment of collected reference values. Determination of reference limits. Journal of Clinical Chemistry and Clinical Biochemistry, 1983, 21, 749–760; IFCC, International Federation of Clinical Chemistry. http://www.ifcc.org. 15. E. P. A. Lopes, E. C. Gouveia, A. C. C. Albuquerque, L. H. B. C Sette, L. A. Mello, R. C. Moreira and M. R. C. D. Coelho, Determination of the cut-off value of serum alanine aminotransferase in patients undergoing hemodialysis, to identify biochemical activity in patients with hepatitis C viremia, Journal of Clinical Virology, 2006, 35, 298–302. 16. G. H. Tabas and M. S. Vanek, Is ‘routine’ Laboratory Testing a Thing of the Past?, 2006, www.postgradmed.com/ issues/1999/03 99/tabas.htm.
12
DATA ANALYSIS, CONDITIONING AND PRESENTATION
17. M. I. Evans, R. S. Galen, and D. W. Britt, Principles of Screening, Seminars in Perinatology, Elsevier, 2005, 364–366,
[email protected]. 18. A. H. B. Wu, Analytical and clinical evaluation of new diagnostic tests for myocardial damage. Clinica Chimica Acta, 1998, 272, 11–21. 19. D. Thabut, S. Naveau, F. Charlotte, J. Massard, V. Ratziul, F. Imbert-Bismut, D. Cazals-Hatem, A. Abella, D. Messous, F. Beuzen, M. Munteanu, J. Taieb, R. Moreau, D. Lebrec and T. Poynard, The diagnostic value of biomarkers (AshTest) for the prediction of alcoholic steato-hepatitis in patients with chronic alcoholic liver disease. Journal of Hepatology, 2006, 44, 1175–1185. 20. F. Guerrero-Romero and M. Rodr´ıguez-Mor´an, Lowered criterion for normal fasting plasma glucose: impact on the detection of impaired glucose tolerance and metabolic syndrome. Archives of Medical Research, 2006, 37, 140–144. 21. M. K. Schwartz, Genetic testing and the clinical laboratory improvement amendments of 1988: present and future. Clinical Chemistry, 1999, 45, 739–745. 22. D. Jordan and S. A. McEwen, Herd-level test performance based on uncertain estimates of individual test performance, individual true prevalence and herd true prevalence. Preventive Veterinary Medicine, 1998, 36, 187–209. 23. R. D. Smith and B. D. Slenning, Decision analysis: dealing with uncertainty in diagnostic testing. Preventive Veterinary Medicine, 2000, 45, 139–162. 24. R. Galen and S. Gambino, Beyond Normality: The Predictive Value and Efficiency of Medical Diagnoses, John Wiley & Sons, New York, 1975. 25. R. S. Galen and S. R. Gambino, Norm und Normabweichung klinischer Daten, Gustav Fischer Verlag, Stuttgart, 1979. 26. C. Heusghem, A. Albert, and E. S. Benson, Advanced Interpretation of Clinical Laboratory Data, in Clinical and Biochemical Analysis, M. K. Schwartz (ed), Marcel Dekker, New York and Basel, 1982, Vol. 2. 27. H. F. Martin, B. J. Gudzinowicz, and H. Fanger, Normal Values in Clinical Chemistry, A Guide to Statistical Analysis of Laboratory Data, in Clinical and Biochemical Analysis, M. K. Schwartz (ed), Marcel Dekker, New York and Basel, 1975, Vol. 2. 28. R. Gambino, The misuse of predictive value—or why you must consider the odds. Annalidell Istituto Superiore Di Sanita, 1991, 27(3), 395–399 PMID: 1809058 [PubMed—indexed for MEDLINE]. 29. Ch. P. Price and J. M. Hicks, Point-of-Care Testing, The American Association for Clinical Chemistry, AACC-Press, Washington, 1999 (
[email protected];
[email protected]). 30. IFCC/NCCLS, EP17-A, Protocols for Determination of Limits of Detection and Limits of Quantitation, Approved Guidelines, NCCLS, Wayne, 2005, 24/34; IFCC, International Federation of Clinical Chemistry, homepage: http://www.ifcc.org/ifcc.asp. 31. R. Kellner, J.-M. Mermet, M. Otto, and H. M. Widmer, Analytical Chemistry, Wiley-VCH, Weinheim, 1998.
32. ISO, Capability of Detection—Part 1 to 4, ISO 11843–1 to 11843–4, ISO, Geneva, 1997 and 2000, International Organization for Standardization, Geneva, Homepage and ISO documents to order, http://www.iso.org/iso/en/ISO Online.frontpage; http://www.iso.org/iso/en/isostore. 33. ISO, Accuracy (Trueness and Precision) of Measurements and Results—Part 1. General Principles and Definitions, ISO 5725–1, Geneva, 1994. 34. ISO 3822-1; 1999, Measurement uncertainty, and ISO/TS 21749:2005, http://store.iso.org/isostore/public. 35. ISO/TS 21748, Geneva, 2004, Guide to the Expression of Uncertainty in Measurement, ISO, Geneva, 1993. International Organization for Standardization, Geneva, Homepage and ISO documents to order, http://www.iso. org/iso/en/ISOOnline.frontpage; http://www.iso.org/iso/en /isostore. 36. World Health Organization (WHO), Guidelines for Drinking-Water Quality, 2nd Edn, WHO, Geneva, 1993, Vol. 1, (ISBN 92 4 154460); 1996, Vol. 2, (ISBN 92 4 154480 5); 1997 Vol. 3, (ISBN 92 4 154503 8), homepage: www.who.int/water sanitation health/dwq/gdwq2v1/en/ print.html. 37. CITAC, Co-Operation on International Traceability in Analytical Chemistry, 2006, http://www.citac.ws. 38. IUPAC, International Union of Pure and Applied Chemistry, 2006, http://www.iupac.org/index to.html. 39. U. E. Spichiger, Basic Principles in Magnesium Assessment. The Relationship Between the Diagnostic Value of a Laboratory Determination and the Quality of the Analytical Procedure, in Magnesium, A Relevant Ion, B. Lasserre and J. Durlach (eds), John Libbey & Company Limited, London, 1991, pp. 217–226. 40. H. W. Bucher, U. E. Spichiger, and E. Jenny, Total Magnesium Concentrations in Serum and Erythrocytes Before and After Treatment with Magnesium l-Aspartate Hydrochloride: Reference to Clinical Symptoms, in Magnesium 1993, S. Golfe, D. Dralle and L. Vecchiet (eds), John Libbey & Company Limited, London, 1993, pp. 155–161. 41. CITAC, Quantifying Uncertainty in Analytical Measurement (QUAM), 2nd Edn, 2000 P1, homepage: http://www.citac.ws, and http://www.measurementuncer tainty.org. The guide has been produced primarily by a joint EURACHEM/CITAC Working Group in collaboration with representatives from AOAC International and EA. Production of the guide was in part supported under the contract with the UK Department of Trade and Industry as part of the National Measurement System Valid Analytical Measurement (VAM) Programme. 42. IRMM, Institute for Reference Materials and Measurements, Homepage, http://www.irmm.jrc.be; Contact: European Commission; Directorate-General Joint Research Centre, Institute for Reference Materials and Measurements; B-2440 Geel, Belgium. For reference materials sales, contact the sales department, 2006, E-mail:
[email protected]. 43. NIST, (US) National Institute for Standardization, homepage: http://ts.nist.gov/ts/htdocs/230/232/232.htm); program questions: Public Inquiries Unit: (301) 975-NIST (6478), TTY (301) 975–8295, NIST, 100 Bureau Drive, Stop 1070, Gaithersburg, MD 20899–1070, 2006.
65 Introduction to Bayesian Methods for Biosensor Design Edmund S. Jackson and William J. Fitzgerald Department of Engineering, University of Cambridge, Cambridge, UK
1 INTRODUCTION
Biosensors are an exciting technology, rapidly growing in sophistication and expanding in their application. One factor is common to all biosensors: an a priori knowledge of the entity to be measured by the sensor. It is in discovering this entity, be it a molecule, molecular concentration or relationship between such concentrations, or any other indicator of state, that the chapters shall be concerned with. A typical workflow resulting in a biosensor is the collection of both control and condition samples, high sensitivity screening of those samples to discover the properties that discriminate between control and condition, verification of these findings and finally the design of a biosensor. The philosophy is that the initial high sensitivity screening, based on sensitive, high dynamic range technologies such as NMR or mass spectrometry, is able to measure a wide variety of substances and hence provide the greatest probability of finding interesting substances. However, due to their expense and complicated operation these technologies are not widely available. Hence, it is desired to identify a small subset of these interesting substances against which a specific and inexpensive biosensor may be designed, for wide deployment. Hence the work of the Bayesian analyst is in the mining of high throughput data to identify this subset of interesting targets. However this
classification must be very reductionist in nature. It is clearly of no value to construct a classifier, regardless of performance, that requires a great many inputs over a wide dynamic range, for then the original instrument is required to perform the classification, whereas the goal is to classify using a smaller, inexpensive device. Hence, the designed classifier must have “acceptable” performance, but the primary design goal is the minimizing of the number of inputs. This is often thought of as “finding biomarkers”, for with a few such markers a specific, and hence inexpensive, device may be designed against each in order to perform the classification. Unfortunately, the Bayesian paradigm in inclined toward the opposite, with complex classifiers, such as model averaging methods, as the norm. Nevertheless, it is entirely possible to proceed fruitfully and in this chapter we shall explore such avenues. Bearing in mind the nonspecialist nature of our audience we shall provide an introduction to each idea, presented simply with references to more thorough treatments for the adventurous. This chapter is organized linearly, presenting all the required concepts and components and arriving finally at the desired classifier. In the Section on 2 we introduce Bayesian inference and its two component tasks, parameter estimation and model selection. In order to achieve these tasks on real data we require techniques of numerical integration which we describe in the Section on 3.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
DATA ANALYSIS, CONDITIONING AND PRESENTATION
Finally, in the Section on 4 we present a Bayesian classification algorithm tuned specifically to the problem of biosensor design.
2 BAYESIAN INFERENCE
We begin our exploration with an introduction to Bayesian inference and its two constituents parameter estimation and model selection. It will be seen that prediction and classification, are particular cases of the ideas given here.
2.1
Parameter Estimation
At the first level it is assumed that one of the models within a chosen set, is the correct (or appropriate) model with which to interpret the data and the problem of inference at this level consists of extracting values for the free parameters of the model, given the observed data.1 Bayes’ theorem may be used to express the posterior probability of the parameters as: P (θk |D, Mk ) =
P (D|θk , Mk ) P (θk | Mk ) (1) P (D | Mk )
where Mk represents the kth model, D is a vector of observed data, θk is a vector of model parameters. P (θk |D, Mk ) is the posterior probability and P (D|θk , Mk ) is the likelihood. P (θk | Mk ) is the prior probability of the parameters θk before the data were observed and P (D | Mk ) is a quantity called the evidence which at this level is a constant. The evidence plays an essential role in model selection. All of the probabilities and probability density functions have to be conditioned on Mk , which represents the particular model structure being considered. For example, if we were considering spectral estimation and we were interested in the number of sinusoids present in the observed data, the model structures, Mk , would be M1 , M2 , M3 , and so on, corresponding to one, two or three sinusoids being consistent with the data.2 In many problems it may not be required to estimate all the elements of the model parameter vector θk and parameters which are of no interest are known as nuisance parameters. A powerful feature of the Bayesian framework is that the nuisance
parameters may be removed from consideration by integration, a process called marginalization. The parameter vector may be partitioned into two sets of parameters: θk,1 , which are the parameters of interest and θk,2 , which are the nuisance parameters. The posterior probability can now be rewritten as: P (θk |D, Mk ) ≡ P (θk,1 , θk,2 |D, Mk )
(2)
And the posterior marginal density of the parameters of interest, θk,1 , may be obtained from P (θk,1 )|D, Mk ) = P (θk,1 , θk,2 |D, Mk ) dθk,2 Rk
(3) In an estimation problem one assumes that the model is true for some unknown values of the model parameters, and one explores the constraints imposed on the parameters by the data, using Bayes’ theorem. The hypothesis space for an estimation problem is therefore the set of possible values of the parameter vector θk , for a fixed, assumed model structure, Mk , and it is this vector that will form the hypothesis that will be used in Bayes’ theorem. The data form the sample space, and both the hypothesis space and the sample space may be either discrete or continuous. Any data which may be described in terms of a linear combination of basic functions with an additive Gaussian noise component satisfies the general linear model. Suppose the observed data may be described by a model of the form: d(n) =
Q
bq gq (n) + e(n)
for
1≤n≤N
q=1
(4) where gq (n) is the value of a time dependent model function gq (t) evaluated at time tn , represented by integers, n, for uniform sampling. This can be written in the form of a matrix equation: D=G b+e (5) where: D is an N × 1 vector of data points, e is an N × 1 vector of noise samples, G is an N × Q matrix whose columns are the basic functions evaluated at each point in the time series and b is a Q × 1 linear coefficient vector.
INTRODUCTION TO BAYESIAN METHODS FOR BIOSENSOR DESIGN
Many of the standard signal processing model structures can be represented with the general linear model: the sinusoidal model, the autoregressive (AR) model, the autoregressive with external input (ARX) model, the nonlinear autoregressive (NAR) model, the Volterra model, the radial basis function model and so on.1 Under certain simplifying assumptions, for example, uniform and Jeffreys’ priors for certain parameters,1 and assuming Gaussian noise statistics, the linear parameters in the general linear model and the noise variance can be integrated out of the posterior distribution giving the marginal posterior for the remaining parameters, θQ , of interest:1 P (θQ | D, MQ ) −(N2−Q) −1 DT D − DT G GT G GT D ×∝ det GT G
(6)
Note that this is a function of θQ only. This means that there is no need to know about the standard deviation nor the values of the linear parameters in order to infer the values of θQ . Here the integrals have been done analytically so the dimensionality of the parameter space was reduced for each parameter integrated out. This reduction of the dimensionality is a property of Bayesian marginal estimates and can be a major advantage in many applications.
2.2
Model Selection
There are numerous statistical inference problems that require model selection with respect to a set of competing models, {Mk }, k = 1, . . . , K. This is the basis of the second level of inference. The Bayesian solution to the model-selection problem is to choose one that fits the prior knowledge and data the best, that is, one that has the highest posterior probability. This is however, only optimal in the sense of maximizing the expected utility function if one uses a zero-one utility function and the choice of a model is the main objective rather than as the basis of a decision problem.2,3 This is of course rather nice, but the question starts to become a problem if you take it too far.
3
One must always keep in mind what it is that one is requiring from a model selection criteria—the “true” model might not be within the set chosen, one might just be interested in how well the model predicts future data and the concept of a “true” model might not be appropriate—or a “true” model might not even exist. In many cases, the optimal model choice is taken as the one that maximizes arg maxk P (Mk | D). Since P (Mk | D) ∝ P (D | Mk )P (Mk )
(7)
one can readily see that the central element of the Bayesian model selection procedure is the evaluation of the quantity P (D | Mk ), referred to as the marginal likelihood, integrated likelihood or model evidence. Denoting θk to be a vector of parameters under model Mk , P (D | Mk ) can be written as P (D | Mk ) = P (D | θk , Mk )P (θk | Mk ) dθk (8) It can also be expressed through a straightforward application of Bayes’ theorem as P (D | Mk ) =
P (D | θk , Mk )P (θk | Mk ) P (θk | D, Mk )
(9)
which gives a new interpretation to model evidence as the normalizing constant that makes the product of the prior and the likelihood the density of the posterior distribution. Note that equation (9) holds for all θk . It follows that provided there exists one point θk∗ in the entire parameter space for which normalized values of the prior density, likelihood and posterior density are available, the evidence can be computed using this identity. One might thus be inclined to think that this is a far easier way of evaluating the evidence than the integral approach. Nevertheless, though it is often trivial to compute the prior density and the likelihood function, to obtain the normalized posterior density is generally as difficult a task as computing a complex multidimensional integral. Equation (9) does suggest however that in addition to numerical integration methods, one can also employ multivariate density estimation techniques to compute the model evidence.4
4
DATA ANALYSIS, CONDITIONING AND PRESENTATION
The Bayes’ factor BFa,b (D) for model Ma against model Mb , which is used extensively in Bayesian hypothesis testing and model selection, is defined to be the ratio of the respective evidences of the two models, namely, BFa,b (D)=
P (D | Ma ) P (D | Mb )
(10)
The Bayes’ factor can be interpreted as providing a measure of how much the data D have increased or decreased the odds on Ma relative to Mb , and is given by, BFa,b (D) =
P (Ma | D) P (Ma ) P (Mb | D) P (Mb )
(11)
BFa,b (D) > 1 signifies that in relative terms model Ma is more plausible in the light of D. The posterior odds ratio P (Ma | D)/P (Mb | D) provides a summary of the evidence for Ma against Mb . From the preceding text, it is clear that the model evidence depends on the corresponding prior density P (θk | Mk ) as well as the likelihood function. In a general inference setting involving model uncertainty, two levels of prior knowledge are required, P (Mk ) and P (θk | Mk ). While the impact of the former on the end result is clear, the latter affects the result in a way that is rather subtle, but certainly not insignificant.
• Evidence evaluation Evidence is a real number whose value is used as a merit index for comparing the performance of different models at describing the data. We can either calculate absolute evidence, P (D | Mk ) = P (D | θk , Mk )P (θk | Mk ) dθk (12) which is the normalizing factor for the product of likelihood and prior, or calculate relative evidence, which is the ratio of the evidence of one model compared to another. • Marginalization A marginal density is a function of one or more parameters that is used to compare the plausibility of different parameter values, and is as such used for parameter estimation. The shape of the marginal density is more important than its size, and in fact, we almost always dispense with the computation of the normalization factor. Because the marginal density is a curve we must compute enough sample points for it to be possible to make an accurate plot of the density. Typically, about thirty sample points are required for a good representation of a one dimensional marginal density. This means evaluating no less than thirty integrals! P (θk,1 )|D, Mk ) P (θk,1 , θk,2 |D, Mk ) dθk,2 =
(13)
Rk
3 INTRODUCTION TO MONTE CARLO SIMULATION
In the last sections it has been shown how to conduct inference in situations where the integrals required to perform marginalization have been analytically tractable. However, in more realistic situations the integrations have to be performed numerically and this requirement has lead to a fullscale investigation of such integration methods. It is now clear that methods based on Monte Carlo techniques hold the greatest scope and in this paper the ideas concerning Markov Chain Monte Carlo methods will be introduced. References 1, 5–7 deal with other schemes. Three areas of Bayesian analysis that require evaluation of integrals are as follows:
• Moments and expectation values Computing moments and expectations of functions is not significantly different to computing marginal densities or evidence, depending on whether the result is in the form of a curve or a single real number. However, unlike marginalization, it is important not to discard normalization constants. Ɛπ (f ) = f (θ )π(θ ) dθ (14) For most statistical applications, the numerical aspect of the problem can be cast in the form of computing the expected value of some function of interest f (θ ), with respect to a target probability density π(θ ), where θ is a vector of parameters of interest. In Bayesian inference, π is typically
INTRODUCTION TO BAYESIAN METHODS FOR BIOSENSOR DESIGN
taken as a posterior distribution. For scalar θ , the usual way to evaluate an analytically intractable integral will be via deterministic numerical integration. As the dimensionality increases, however, there are problems associated with applying deterministic techniques. In contrast, Monte Carlo integration is as easy in 10 dimensions as in 1 dimension. Suppose θ 1 , . . . , θ n are an iid sample set from π and that we evaluate 1 f (θ i ) fˆ = n i=1 n
(15)
Then fˆ is said to be a Monte Carlo estimator of Ɛπ (f ). Since Ɛfˆ =
1 Ɛf (θ i ) = Ɛπ (f ) n i=1 n
(16)
fˆ is clearly an unbiased estimator. and the variance is given by var(fˆ) =
1 n
[f (θ ) − Ɛπ (f )]2 π(θ ) dθ
(17)
implying that the error (i.e., the standard deviation) of a Monte Carlo estimator is O(n−1/2 ), which can be contrasted with some deterministic methods which may be of O(n−4 ) or even exp(−n). The basic problem that Monte Carlo addresses is how to generate random samples from a given probability distribution π on some state space. The theoretical underpinning of Monte Carlo is the duality between samples and the distributions from which they are generated: given a distribution, there exist, in principle, ways to generate samples from it; and given samples, one can, at least approximately, recreate the distribution. There are broadly two classes of Monte Carlo methods: static and dynamic. Static methods generate a sequence of iid random numbers from the desired distribution π, an example being rejection sampling in the onedimensional case. In theory, a static simulation method always exists, because of the following
5
identity for a k-component parameter vector, π(θ ) = π(θ1 , . . . , θk ) =
k
π(θj | θj −1 , . . . , θ1 )
j =1
(18) However, the univariate distributions on the righthand side are rarely all available in a form that is suitable for simulation purposes. Therefore static simulation methods are typically not applicable to complex problems. Dynamic Monte Carlo simulates a stochastic process that has π as its unique equilibrium distribution (by which it is meant that π is the distribution to which a process converges irrespective of the starting point). Once equilibrium has been reached, under ergodicity one can substitute sample path (temporal) averages for ensemble averages. The crucial part of a dynamic Monte Carlo method is how to invent the best ergodic stochastic time evolution for the underlying system that converges to the desired distribution. In practice, one invariably uses a firstorder Markov process to accomplish this, hence the term Markov Chain Monte Carlo (MCMC). In physical terms, different MCMC algorithms simply correspond to different invented dynamics. High-order Markov processes or non-Markovian processes are significantly more difficult to analyze in terms of their theoretical convergence properties.
3.1
The Theory of Markov Chains
A Markov chain with state space E is a sequence of E-valued random variables {θi } such that the probability of one state given previous states is P (θi | θi−1 , . . . , θ0 ) = P (θi | θi−1 ). The elements of E are thought of as the possible states of a system, θi representing the state at time i. To predict the future state of a Markovian system, one only needs knowledge of the present. Knowledge of the past is not required—it has already been fully accounted for by the present state.5 A Markov chain is defined by two components: the initial distribution P (θ0 ) and the transition kernel, T (θ , A) = P (θi+1 ∈ A | θi = θ ),a where E denotes a σ -algebra on E, ∀θ ∈ E and ∀A ∈ E. T (θ , ·) is a probability measure on (E, E): E × E → [0, 1].
6
DATA ANALYSIS, CONDITIONING AND PRESENTATION
3.2
Definitions of Key Concepts
• Equilibrium distribution Let T n (θ0 , A) represent the conditional distribution P (θn ∈ A | θ0 ). π is an equilibrium distribution for the chain if for π-almostb all θ0 , lim T n (θ0 , A) = π(A), ∀A
n→∞
(19)
• Invariant distribution π is an invariant or stationary distribution for a Markov chain if
the transition kernel T is such that π(A) = π(dθ )T (θ , A), ∀A. It is possible for a Markov chain to have more than one invariant distribution. • Irreduciblity A Markov chain is π-irreducible on (E, E) if for a σ -finite measure π, ∀θ ∈ E, ∀A with π(A) > 0, ∃n, such that T n (θ , A) > 0. • Aperiodicity A Markov chain is periodic if, informally, there are portions of the state space it can only visit at certain regularly spaced times; otherwise, it is aperiodic. • Reversibility and detailed balance A Markov chain with transition kernel T is reversible with respect to distribution π if and only if ∀B, C ∈ E, the detailed balance condition
π(dθ )T (θ , C) =
B
π(dθ )T (θ , B)
(20)
C
is satisfied. Equivalently, detailed balance holds if and only if π(dx)T (x, dy) = π(dy)T (y, dx),
∀x, y ∈ E (21) The two sides of this identity are measures on E ⊗ E and detailed balance means these two measures are identical. If T is reversible with respect to π, π is invariant for T . A reversible Markov chain has the property that for any function f ,
f (y)π(dx)T (x, dy) =
f (y)π(dy)T (y, dx)
=
f (y)π(dy)
(22)
It follows that detailed balance is a sufficient condition for having an invariant distribution, the former being more amenable to analysis.
• Transience, persistence, and recurrence For a discrete state space, a state x is persistent if a system starting at x is certain to return to it sometime in the future. Transience of state x is equivalent to P (θn = x io | θ0 = x) = 0, where io means infinitely often, and to n n T (x, x) < ∞; and persistence of state x is equivalent to P (θn = x io | θ0 = x) = 1 and to n T (x, x) = ∞. In the discrete case, if the n Markov chain is irreducible, the states are either all transient or all persistent. The chain itself can accordingly be called either transient or persistent, respectively. A crucial concept in convergence theory is recurrence. The definition given in Ref. 8 for a discrete state space is that a π-irreducible chain with invariant distribution π is recurrent if, ∀B with π(B) > 0, P (θn ∈ B io | θ0 = x) > 0, ∀x, and P (θn ∈ B io | θ0 = x) = 1, for π-almost all x. It is Harris recurrent if P (θn ∈ B io | θ0 = x) = 1, ∀x. • Convergence It is shown in Ref. 8 that if a chain is π-irreducible and has π as an invariant distribution, then it must be positive recurrent, where the term positive refers to the total mass of the measure being finite,c and π is its unique invariant distribution. If the chain is also aperiodic, ∀θ π-almost, ||T n (θ , ·) − π(·)|| → 0
(23)
where || · || denotes the total variation distance.d If the chain is Harris recurrent, the convergence occurs ∀θ . The main point about convergence is whether or not the effect of the initial state wears off. Having an invariant distribution does not guarantee convergence to it. A much stronger condition for convergence is positive recurrence, which is a corollary of irreducibility and having a proper invariant distribution. With positive recurrence, convergence holds for almost every starting point. Harris recurrence ensures convergence from every starting point. If {θ 1 , . . . , θ n , . . .} is a realization of a Markov n i chain, for the sample path average n1 i=1 f (θ ) to converge to Ɛπ (f ), one needs positive recurrence with invariant distribution π. The condition for ergodicity is positive Harris recurrence and aperiodicity. Limiting properties of sample path averages however do not depend on aperiodicity.
INTRODUCTION TO BAYESIAN METHODS FOR BIOSENSOR DESIGN
An ergodic Markov chain with invariant distribution π is said to be geometrically ergodic if
there exists a function h such that |h(θ )|π(dθ ) < ∞ and a positive constant r < 1 such that ||T n (θ , ·)|| ≤ h(θ )r n
(24)
There are other forms of ergodicity and the convergence rate can also be characterized by studying how quickly the sample path average of an arbitrary square π-integrable function approaches its expectation under the invariant distribution.
3.3
The Metropolis – Hastings Algorithm
The Metropolis–Hastings algorithm9 is a method of constructing a reversible Markov transition kernel with a specified invariant distribution. A Metropolis–Hastings kernel on (E, E) can be expressed as,1 T (x, dy) = Q(x, dy)A(x, y) + I (x ∈ dy) × [1 − A(x, θ )]Q(x, dθ ) (25) where I is the indicator function; A(x, y) is a function: E × E → [0, 1]; Q(x, dy) is a transition kernel that generates a candidate y for the next state conditional on the current state x. The candidate is accepted with probability A(x, y). The Metropolis–Hastings kernel satisfies detailed balance if and only if π(dx)Q(x, dy)A(x, y) = π(dy)Q(y, dx)A(y, x) (26) If with transition kernel Q and invariant distribution π, r(x, y) represents the rate of transitions from x to y relative to those from y to x, it is shown in Ref. 10 that in order to satisfy the detailed balance condition, A must satisfy A(y, x) = r(x, y) A(x, y)
π(x)q(x, y) π(y)q(y, x)
The standard Metropolis–Hastings acceptance probability can be written as π(y)q(y, x) AMH (x, y) = min 1, (29) π(x)q(x, y) It is worthy of note that there exist several alternative forms of the acceptance probability function, but the Hastings version is optimal for a quite extensive range of choices chiefly because it rejects proposals less frequently than the others. For distributions of high dimensions, it is often preferable to update only a subset of the target vector at a time so as to avoid low acceptance rates. A general version of the Metropolis–Hastings algorithm is given below: 1. Partition θ into m blocks such that θ = (θ1 , . . . , θm ); let θ−j be a subvector containing all the components of θ not included in θj . 2. At iteration t + 1, select a subvector θj for updating by a deterministic or random mechanism that ensures each component of θ should (t) be visited with nonzero probability. Let θ−j be the most recent update of θ−j . Update the j th block by generating a candidate θj from a proposal density qj (θj , θj | θ−j ). 3. Accept it with probability (t) (t) π(θj , θ−j )qj (θj(t) , θj | θ−j ) min 1, (t) (t) π(θj(t) , θ−j )qj (θj , θj(t) | θ−j ) or else θj(t+1) = θj(t) . 4. Increment t and go to step 2. Step 1 can be modified to allow for random partitioning of θ subject to the condition that each component may be visited with positive probability while maintaining irreducibility of the Markov chain.
(27) 3.4
If there exists a common dominating measure with respect to which π(dx) has density π(x) and Q(x, dy) has density q(x, y), r(x, y) =
7
(28)
Reversible Jump MCMC
An MCMC algorithm that jumps between parameter spaces of variable dimensions can be used and is referred to as the reversible jump MCMC sampler.11 In this approach, the state space is defined to be the union of the parameter spaces
8
DATA ANALYSIS, CONDITIONING AND PRESENTATION
of all the entertained models. The Metropolis–Hastings algorithm is generalized to allow for moves between subspaces with different dimensions by using proposals that match the differing degrees of freedom. The reversible jump MCMC framework enables an algorithm to be constructed which samples from p(k, θ (k) |D), where k indexes the models of differing dimensionality, θ (k) are the parameters of the kth model and D is the data. We need to construct the transition kernel T (x, dx ) to maintain detailed balance when moving between the different subspaces. This is in general a difficult problem, drawing on measure theory, however, we only require the simplest case in our application. When the current state is x, choose to make a move of type m which will take the current state to dx with probability qm (x, dx ) (this includes the probability of choosing this move type). The acceptance probability can be derived as π(dx )qm (x , dx) Am (x, x ) = min 1, π(dx)qm (x, dx )
(30)
The main condition when using this in practice is that the proposal density must be constructed such that π(dx)qm (x, dx ) has finite density with respect to a symmetric measure. This can be done by constructing the proposals such that π(dx )qm (x , dx) and π(dx)qm (x, dx ) are of the same dimensionality (even though x and x are of differing dimensionality), by making the qm ’s functions of a number of new random variables, which are introduced to match the dimensions. The argument is complex in general, however it may be greatly simplified in our case. Following Ref. 12, we impose that the variable in the space of unknown dimension are discrete, and only allow transdimensional moves that add or remove a single dimension without altering the value of the variables in the other dimensions. These are termed birth and death steps respectively. In addition, a within-dimension step called a move is allowed, which alters the values of the parameters in one dimension, leaving the rest unmodified. These moves occur with independent probability bk , dk , and 1 − bk − dk respectively, when the current dimension is k.
In this case a Metropolis–Hastings algorithm, using independence sampling, will have an acceptance probability similar to equation (28) of Ref. 12 π(y)q(x, y) Am (x, y) = min 1, · R (31) π(k)q(y, x) = min 1, BF (x, y) · R (32) Here R accounts for the change of dimension, and is dk+1 bk , Birth R = bdk−1 , Death (33) k 1, Move By setting bk = dk = 1 in all cases except at the dimensionality borders (k = 0 or k = kmax ), R = 1. For further details see Refs. 3, 11–14. 4 BAYESIAN CLASSIFICATION
Having begun in general by defining Bayesian inference as the process of model selection and parameter estimation in Section 2, and then having shown in Section 3 how to use Monte Carlo methods to perform the analytically intractable integrals that result, it remains only to provide the specifics of models to be used for our problem. Our goal is classification: based on a feature set of measurements, X ∈ n×p , to correctly predict a class Y ∈ Cn , C ∈ [1, q] ∈ , where n is the number of samples, p is the number of features extracted from each and q is the number of classes (typically two). In addition, given our goal of biosensor production, we wish to minimize p. 4.1
Bayesian Regression
We shall present a framework, drawing heavily on Ref. 12 (which gives an extremely good treatment), that affects classification based on regression. Consider the basic linear regression model Y = βX + ε
(34)
p
yj =
i=1
βi xi,j + ,
∀j ∈ [1, n]
(35)
INTRODUCTION TO BAYESIAN METHODS FOR BIOSENSOR DESIGN
where i ∼ N(0, σ 2 ), and hence Y ∼ N(βX, ε). Thus the likelihood may be written12 −n/2 p X|β, σ 2 = 2πσ 2 (Y − Xβ) (Y − Xβ) × exp − 2σ 2 (36) Our inference is thus over β and σ 2 , and hence we must place priors over these quantities. The standard approach is to use a normal-inverse distribution for the joint distribution as it is the conjugate prior12 p(β, σ 2 ) 2
= N(m, σ 2 , V)IG(a, b) ba (σ )−2(a+(k/2)+1) = (2π)k/2 |V|1/2 (a) −(β − m) V−1 (β − m) + 2b × exp (2σ 2 ) (37) Utilizing equations (36) and (37) the parameter posterior is then12 p(β, σ 2 |X) =
p(β, σ 2 )p(X|β, σ 2 ) p(X) ∗
∗
(b∗ )a (σ )−2(a +(k/2)+1) = (2π)k/2 |V|1/2 (a) − β − m∗ ) V∗−1 (β − m∗ ) + 2b∗ × exp (2σ 2 (38) where
p(X|Mi ) = =
p(X|βi , σ 2 )p(βi , σ 2 ) p(βi , σ 2 |X) |V∗i |1/2 ba (ai∗ ) ∗ −a ∗ (b ) i |Vi |1/2 π n/2 (a) i
(39)
BF (Mi , Mj ) =
4.2
|Vj |1/2 |V∗i |1/2 (bj∗ )a
∗
|Vi |1/2 |Vj∗ |1/2 (bi∗ )a ∗
(40)
Bayesian Classification
Having examined Bayesian regression, we now turn to classification, which we cast as a regression problem. The regression framework described in the preceding text relies on Y ∼ N(·, ·), whereas in (two-class) regression Y ∼ BR. In order to proceed we propose, following Ref. 12 closely once again, introducing a latent variable, Z, associated with Y , which is normally distributed and against which we may thus perform regression. Consider equation (34) once again, but substituting a latent variable, z for y. Z = βX + ε
(41)
p
zj =
βi xi,j + ,
∀j ∈ [1, n]
(42)
i=1
−1 −1 m∗ = V−1 + X X V m + X Y −1 V∗ = V−1 + X X a ∗ = a + n/2 b∗ = b +
the Bayes’ factor between two models. In this case the models will simply be linear regressions where the parameter matrix, β, is of different dimensions, corresponding to the number of features included in the regression. Using the preceding equations it can be shown that the evidence for a model with i features included in the regression12 is
and hence the Bayes’ factor in favor of a model of dimension i over another of dimension j is12
= p(β|σ )p(σ ) 2
9
1 −1 m V m + Y Y − m∗ V∗−1 m∗ 2
These equations are sufficient for parameter estimation, however for model selection we require
where in this case i ∼ N(0, 1). If regression is performed on z, similar results to the general regression described above result, but for the knowledge of that σ 2 = 1. Thus p X|β, σ 2 = (2π)−n/2 (Z − Xβ) (Z − Xβ) × exp − 2 (43)
10
DATA ANALYSIS, CONDITIONING AND PRESENTATION
p(σ 2 ) = δ(1)
(44)
p(β|X) = N(m∗ , V∗ ) =
(45)
1 (2π)k/2 |V|1/2 − β −m∗ ) V∗−1 (β −m∗ × exp 2 (46)
p(X|Z) ∝ where
∗ 1/2
∗
|V | exp(−b ) |V|1/2 (2π)n/2
(47)
−1 −1 m∗ = V−1 + X X V m + X Z −1 V∗ = V−1 + X X b∗ =
T 1 p(y = 1|x, β (t) ) N t=0 p (t) T β xi,j i=1 i 1 1 = √ N t=0 −∞ 2π 2 −a da (52) × exp 2
p(y = 1|x, X) ≈
1 −1 m V m + Z Z − m∗ V∗−1 m∗ 2
Finally, the Bayes’ factor is BF (Mi , Mj ) =
|Vj∗ |1/2 |V∗1 |1/2 |V1 |1/2 |V∗2 |1/2
exp(bj∗ − bi∗ )
(48) It remains to associate Z with Y , which is done by assuming (see Ref. 12 for justification) for each feature j that 1, if zj > 0 p(yj = 1|zj , β) = (49) 0, else in which case, (Section 2.1)
by
p
marginalization
of
zj ,
2 1 −a p(yj = 1|β) = √ exp da 2 2π −∞ (50) which is simply the normal distribution function (CDF), which is simple to sample from and hence perform a numerical integration over. A measure of the predictive performance of a set of parameters β is thus the Euclidean distance of the predicted labels, from the true labels. i=1
βi xi,j
Thus we require a numerical method in order to estimate the distribution (46) and another numerical integration to marginalize the equation (49). Fortunately the two may be elegantly combined such that we sample z for its marginalization, and for each such sample perform a single step of a RJMCMC (Section 3.4) integration, using the linear regression model. This is described in Algorithm 1 in the subsequent text. The fully Bayesian solution is to perform model averaging for prediction, that is, in order to label an unseen datum x to use each of the β (t) imputed in the preceding text12
This is unacceptable for our purposes as biosensors are not equipped with either the memory or the computational wherewithal to perform such a calculation. Instead we must compromise. The usual solution in such cases is the maximum a posteriori solution, however it is not directly available to us as the parameter posterior argmaxβ p(X|β) is a function of the latent variable, z, requiring its integration for use. This is the purpose of γ (t) in 1, we can approximate the MAP parameter by βˆ = β (t) : t = argmaxt γ (t)
(53)
which is the β that performs the most accurate prediction on our training set. Another improper notion from the Bayesian perspective that is required by pragmatism, is the stipulation of a kmax , the maximum number of predictors to allow in the model. Specification of this quantity is arbitrary and hence a design time
p (t) 2 2 n β xi,j i=1 i 1 −a da γ = Yj − √ exp 2 2π −∞ j =1
(51)
INTRODUCTION TO BAYESIAN METHODS FOR BIOSENSOR DESIGN
11
Algorithm 1 Bayesian RJMCMC Classifier for t = 0 to Num Iterations do p Zj ← N( i=1 βi(t) xi,j ), ∀j p Zj ← N ( i=1 βi(t) xi,j ), ∀j (t) β ← N(m∗ , V∗ ) β (t) ← N (m∗ , V∗ ) %Propose move: %Sample Move Type if k == 1 then u1 ← U (0, bk ) else if k == kmax then u1 ← U (bk , 1) else u1 ← U (0, 1) %Propose Parameter if u1 ≤ bk then βb ← p(β) β = [β, βb ] else if u1 ≤ bk + dk then r ← U [1, k] β = β (t) \βr else r ← U [1, k] β = β (t) \βr βb ← p(β) β = [β , βb ] end if %Accept or Reject Proposed Move u2 ← U [0, 1]
if u2 < min 1, BF (β , β (t) ) · R then (t+1) =β β else β (t+1) = β (t) end if γ (t) = γ end for
decision, motivated either through the eventual limitations of the biosensor technology, or tuned iteratively by observing the predictive performance over a range of kmax and choosing the best compromise of performance and simplicity. A final critical step is the estimation of predictive performance on unseen data. We advocate the process of cross-validation. The data is split into two nonoverlapping groups, termed the training and testing data. The algorithm is run on the training set and the performance on the testing set is noted. This is then repeated with different training and testing sets and the average performance is taken as an estimate of prediction accuracy. This is a robust estimate of the classifier performance on unseen data.
%Sample %Sample %Sample %Sample
Latent Variables Latent Variables Regression Parameters Regression Parameters
%Force Birth Move %Death or Move Move %Any Move
%Birth Move: Sample Variable %Add to Set %Death Move: Sample Index %Remove Variable %Death Move %Birth Move
%Sample Acceptance Probability %Accept Proposed Move %Reject Proposed Move %Record Performance
5 CONCLUSION
In this chapter we have attempted to indicate the main role that Bayesian statistics plays in the realm of biosensors. Given the nature of the problem, we have argued that main contribution of the Bayesian methods is in classification, specifically the identification of features to design the biosensors. We have argued that as a large majority of biosensors are noncomputing and operate by sensing the presence, absence, or large concentration differences, of molecules (or other features), the Bayesian method must produce a classifier amenable to such implementation. Specifically, this requires a small feature set and a noncomputing discriminant. We have endeavored
12
DATA ANALYSIS, CONDITIONING AND PRESENTATION
to produce a complete discussion of just such a system, with an introduction to all the necessary components. We have presented an introduction to Bayesian classification specifically for biosensor design with the minimum necessary accompaniment of detail. Initially we introduced Bayesian inference and indicated the two main divisions of labor: parameter estimation and model selection. These problems highlighted the need for numerical integration techniques which we introduced briefly, giving specific attention to the Metropolis–Hastings algorithm and its transdimensional generalization, the reversible jump algorithm. With this framework in hand, we then introduced a popular Bayesian classification algorithm, and made specialization for the application area of biosensor design. We have only touched briefly on each area, and recommend further reading on the area. Specifically in Bayesian statistics we recommend Ref. 15 and for a more philosophical outlook Ref. 16. As regards numerical techniques Ref. 7 is outstanding and as our numerous citations indicate, Ref. 12 is a prime source for Bayesian techniques for classification. The Bayesian approach is not the only one for classification and Ref. 17 provides an excellent overview of the plethora of alternatives.
END NOTES a.
Sometimes in the definition of the Markov chain, the transition kernel is allowed to depend on i. b. A property that holds for θ outside a set of measure 0 under π is said to hold π-almost everywhere, or for π-almost all θ . The symbols ∀ and ∃ mean “for all” and “there exists” respectively. c. There is a possibility that the invariant measure is null. d. For a measure φ on (E, E), the total variation distance ||φ||= supA∈E φ(A) − infA∈E φ(A). There
are several other distance measures that can be used to measure closeness to the target distribution.
REFERENCES 1. J. J. K. O’Ruanaidh and W. J. Fitzgerald, Numerical Bayesian Methods Applied to Signal Processing, Springer Verlag, New York, 1996. 2. J. M. Bernardo and A. F. M. Smith, Bayesian Theory, John Wiley & Sons, New York, 1994. 3. C. Andrieu, P. M. Djuric, and A. Doucet, Model Selection by MCMC Computation. Signal Processing, unpublished. 4. J. Besag, A candidate’s formula: a curious result in Bayesian prediction. Biometrika, 1989, 76(1), 183. 5. W. R. Gilks, S. Richardson, and D. J. Spieglehalter, Markov Chain Monte Carlo in Practice, Chapman Hall, New York, 1996. 6. A. E. Gelfand and A. F. M. Smith, Sampling based approaches to calculating marginal densities. Journal of the American Statistical Association, 1990, 410(85), 398–409. 7. C. P. Robert and G. Casella, Monte Carlo Statistical Methods, Springer Verlag, 1999. 8. L. Tierney, Markov chains for exploring posterior distributions (with discussion). Annals of Statistics, 1994, 22(4), 1701–1762. 9. W. K. Hastings, Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 1970, 57, 97–109. 10. L. Tierney, A note on metropolis-hastings kernels for general state spaces, School of Statistics, University of Minnesota, no. 606, June, 1995. 11. P. J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika, 1995, 82, 711–732. 12. D. G. Denison, C. C. Holmes, B. K. Mallick, and A. F. Smith, Bayesian Methods for Nonlinear Classification and Regression, John Wiley & Sons, 2002. 13. R. Morris and W. J. Fitzgerald, A Sampling Based Approach to Line Scratch Removal From Motion Picture Frames, In: Proc. IEEE International Conference on Image Processing, Lausanne, Switzerland, 1996, September. 14. C. P. Robert and G. Casella, Monte Carlo Statistical Methods, 2nd Edn, Springer, 2004. 15. J. M. Bernardo and A. F. M. Smith, Bayesian Theory, Wiley, 2004. 16. E. Jaynes, Probability Theory: The Logic of Science, Cambridge University Press, 2003. 17. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, Springer, 2001.
66 Genetic and Other DNA-Based Biosensor Applications Wim Laureyn,1 Tim Stakenborg1,2 and Paul Jacobs3 1
NEXT-Nano-Enabled Systems, Leuven, Belgium, 2 Veterinary Research Institute, Brussels, Belgium and 3 Innogenetics NV, Zwijnaarde, Belgium
1 INTRODUCTION
The interest and research effort into the development of DNA diagnostic tools has increased dramatically. Without any doubt, the development of the polymerase chain reaction (PCR) heralded a new era in molecular analysis: the specific analysis of extremely small quantities of DNA suddenly became feasible. As a consequence, applications in which the sensitivity extends far beyond the sensitivity for protein analysis, down to below 100 targets per ml, could be addressed. Not only did this open the way to sensitive detection of organisms such as bacteria or viruses but it also produced sufficient material that enabled further study of other structural elements of the detected nucleic acids and to expand insights into structure–function relationships. The discovery of numerous genetic loci related to monogenic diseases and complex polygenic diseases, the rapid spread of (newly emerging) infectious agents, the problems associated with drug resistance, the increasing quality standards for food production and consumption, and the necessity of detecting genetically modified organisms (GMO) are just a few examples of what has led to completely new challenges in molecular diagnostics. Now, not only the speed of detection but also the specific detection of single nucleotide
polymorphisms (SNPs) or combinations of alleles in a particular sample has become essential. The advent of microarray technology provided an analytical tool that allows genome-wide expression profiling,1,2 which has proved to be an increasingly important methodology. An example can be found in the field of cancer research where arrays may be used for early disease detection, prediction of therapy, and follow-up of treatment outcome.3,4 Biosensors, in combination with instruments that can detect, analyze, and quantify these new targets, are expected to revolutionize healthcare, particularly in the field of molecular diagnostics. Systems are awaited that are especially userfriendly (i.e., no hands-on manipulations, fast and easy interpretation of results) and that can be used preferably as portable instruments for point-ofcare (POC) applications.5,6 However, according to the strict definition, a biosensor can be defined merely as a device containing a biological sensing element coupled to a transducer that generates a detectable signal.7 In this perspective, a DNA-based biosensor is a device incorporating oligonucleotides either intimately connected to or integrated within a transducer. This exact translation of the biosensor definition to DNA-based biosensors is particularly important to delineate the scope of this chapter. Recent developments
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
in miniaturization have resulted in a plethora of technologies and assay formats that are referred to as biosensors although they do not fulfill the strict requirement of integration or intimate contact with a transducer. As a consequence, microarrays or DNA chips as such are not considered as biosensors and therefore not discussed in this chapter, nor are the many examples of miniaturized capillary separation-based systems that are often associated with biochips or lab-on-a-chip devices. In this chapter, a number of application fields for DNA-based biosensors are described, together with some examples to illustrate the existing state of the art, without pursuing complete coverage of all current research. Nonetheless, the given examples highlight the specific nature of DNA-based diagnostics, its impact on biosensor requirements, and how specific challenges in this field can be addressed. An overview, illustrated with some of our original work, provides aspects of a potential route toward affordable DNA-sensor arrays with a particular focus on multiplexing and compatibility with polymer integration technology. 2 OVERVIEW OF APPLICATIONS 2.1
Infectious Diseases
Worldwide, one death in three is the result from a communicable or infectious disease.8 Millions of people suffer from acute and chronic disorders caused by infectious agents (e.g., influenza, hepatitis C, hepatitis B, human papilloma and human immunodeficiency viruses, Mycobacterium tuberculosis, Plasmodium species, etc.), some of which are implicated in cancer development.9 As a consequence, research has been expressly directed toward developing newer methods to detect pathogenic agents and treat the diseases they cause. Shorter detection times may lead to faster treatment, examining the molecular epidemiology may yield information for prevention or vaccination, and improvements in food and water quality may result in better sanitary practices. Unsurprisingly, most research in the area of biosensors is directly or indirectly linked to the diagnosis of infectious diseases. Numerous examples of biosensors optimized for the detection of infectious agents are available.10 The simultaneous detection of these agents for
some applications (e.g., food-borne diseases) is particularly demanding as sample preprocessing steps are far from universal and certainly not all available in a standardized format.11,12 Also, the choice of target genes may be debatable. Often, species-specific genes, or more generic type sequences such as rRNA sequences, are used as targets.13–15 The latter sequences have the advantage that they are relatively stable and are present in high amounts in bacterial cells. On the other hand, they are largely conserved, even among different taxonomic units, and the specificity must be well assessed before using them as a marker. In that respect, the spacer region between the genes coding for rRNA may form a good alternative. It can likewise be amplified with universal primers, but in addition shows sufficient variability to allow adequate differentiation and specificity.16 Besides bacteria, DNA-sensor technologies have also been reported for some of the most important human viruses such as human papillomaviruses,17 hepatitis viruses,18 and human immunodeficiency viruses.19,20 In the case of bacteria, a surface plasmon resonance (SPR) fluorescence sensor used PCR-generated fragments from Neisseria gonorrhoeae and Chlamydia trachomatis as target sequences. Under experimental conditions, the technique could detect as low as 106 DNA copies and was also shown to be useful for the detection of SNPs.21 Moreover, in parasitology, DNA-based biosensors for the detection of, or the sensitivity to, eukaryotic parasites are currently being developed.22 A DNA chip has already been used to monitor the sensitivity of children toward Plasmodium spp., the causative agents of malaria.23 DNA sensors have not been developed only for diseases that are important for humans. A sensor based on a quartz crystal microbalance (QCM) was described that could specifically detect 1-ng RNA originating from two different orchid viruses. A 10-fold lower detection limit was observed with crude orchid samples.24 2.2
Human Genetic Testing
2.2.1 Genetic Disorders
Since the completion of the Human Genome Project, an increasing understanding of the human genetic code has led to the discovery of many
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS
new hereditary genetic disease loci. Base mutations, deletions, insertions, chromosomal aneuploidy, or triplet and repeat expansions may all relate to genetic disorders. To better detect and understand such monogenetic or complex diseases (e.g., Alzheimer’s disease, sickle cell anemia, schizophrenia, depression, attention-deficit/ hyperactivity disorder (ADHD), etc.), the mapping of different genotypes has received worldwide attention (www.hapmap.org). Cystic fibrosis is a monogenic disease for which already close to 1000 mutations have been identified in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Persons with mutations in this gene may suffer from the accumulation of mucus, especially in the lungs. Although cystic fibrosis is widespread, the distribution of these mutations in the gene and their relative frequency varies markedly between geographic and ethnic populations. However, early diagnosis of the disease allows the timely initiation of selected treatments in order to retard irreversible damage and improve the quality of life and life expectancy of the patient.25 The numerous multiethnic variants and the move toward neonatal or even prenatal detection of these genetic disorders require sensitive biosensor systems able to detect multiple factors simultaneously on samples of minimal size. In early work on electrochemical DNA biosensors, the selective detection of the common F508 deletion mutation of the CFTR gene was used as a demonstrator.26 More recently, F508 has also been used as a demonstrator for the ultrasensitive (<10 fM) and reproducible electrical detection of sequence variations using nanowire-based sensors.27 Advances in large-scale assembly of nanowires should allow high-throughput multiplex DNA detection.28 Cystic fibrosis could be the first diagnostic field to really benefit from DNA biosensor systems. The eSensor (Clinical Micro Sensors, Inc., a former business unit of Motorola, acquired by Osmetech Inc., Roswell, GA, USA) is a commercially available system detecting a panel of 24 mutations recommended by the American College of Medical Genetics and American College of Obstetricians and Gynecologists (ACMG/ACOG). The assay is based on sandwich hybridization of the singlestranded target to a capturing probe immobilized on a gold electrode. Added reporter probes labeled with ferrocene are detected upon hybridization by
3
charge transfer through the molecular wires. Free, nonhybridized redox material does not interfere because of the blocking insulator molecules.29 The construction of the electrode array is based on established printed-circuit board technology. The moderate ambitions with respect to probe site density will most probably result in an affordable product. DNA-based biosensors are currently also under investigation for other genetic diseases. Using impedance spectroscopy, an oligonucleotide mutation related to the lethal Tay–Sachs disease was examined.30 Microgravimetric detection of specific hybridization using QCMs has been reported for Tay–Sachs disease31 as well as for the rapid detection of ß-thalassemia disease.32 In addition, an optical detection technique was used to quantify SNPs associated with spinal muscular atrophy.33 DNA probes, specific for the SMN1 and SMN2 gene fragments, were immobilized on the surface of fused silica optical fiber segments. Labeled DNA targets were subsequently measured by means of an epifluorescence scanning instrument in a total internal reflection fluorescence format. It is worthwhile to mention that interfacial thermal denaturation profiles were collected by applying a temperature ramp (25–85 ◦ C, using a rate of 0.3 ◦ C min−1 ), yielding extra information about the hybridization event. 2.2.2 Oncology
The number of persons diagnosed annually with cancer, and the established finding that earlier detection almost invariably leads to better clinical outcome, highlights the importance in developing new treatment and diagnostic tools in this area. Although risk factors of various origins have been documented, the mapping of genetic mutations and, increasingly, expression profiling, provide direct links to cancer. Mutations may activate oncogenes or repress tumor-suppressor antigens and may eventually lead to the development of cancers. One such example is the P 53 tumorsuppression gene that encodes a nuclear protein with an essential role in the regulation of the cell cycle. Mutation of this gene, leading to deficiency or absence of the P53 protein, is believed to contribute to the majority of cancers and already a number of SPR and QCM analyses were performed to detect such P 53 mutations.34,35 BRCA1
4
BIOSENSOR APPLICATIONS
and BRCA2 are two other tumor-suppressor genes, several genotypes of which are linked to an increased risk for breast cancer. Certain mutations of the BRCA1 gene were successfully determined using a biochip.36 Such research may well allow for predictive testing in the field of cancer diagnosis.6,37 Although genomic analysis is primarily a research tool to study vast amounts of data, many of the complex patterns can be represented by subsets of more manageable numbers of markers, thus paving the way for practical multiparametric assays to allow simultaneous disease detection and prognosis, or to provide information on preferred treatment options.38 There is important evidence that free circulating DNA in plasma may be useful as a marker for disease prognosis as well as for therapy monitoring. Indeed, circulating cell-free DNA appears to be the result of cell death, either caused by apoptosis/necrosis or associated with disease and malignant cells. The mere increase of circulating DNA plasma levels has been studied as a prognostic marker for long-term survival of hepatocellular carcinoma patients.39 A more specific approach used the hTERT gene as a marker in plasma to study its significance in lung cancer.40 Even detection of DNA in urine has been mentioned as a possible cancer diagnostic, but in this case certain precautions need to be taken into account.41 It is surprising that little or no work on DNA-based biosensors for these targets in plasma and urine is in progress, since it appears to offer a unique condition in which the complexity of DNA extraction is expected to be significantly lower than that required for cells or virus particles. Furthermore, the levels of detection (1–10 ng ml−1 ) do not seem to be particularly demanding. 2.2.3 Tissue Typing for Transplantation
Successful organ or tissue transplantation relies upon sufficient control of the host immune response to induce tolerance toward the foreign material that is introduced. In this respect, the human leukocyte antigen (HLA) system plays a pivotal role. The HLA system enables the body to distinguish “self” from “nonself” material and to react accordingly by mounting an adequate immune response. To this end, HLA molecules are presented at the cell surface, forming a discrete recognition pattern, unique for every person (with the exception of monozygotic
twins). As a consequence, the identification of donor material that matches the recipient HLA type as closely as possible is of major importance to minimize the risk of rejection. Taking into account the variety of alleles that have been discovered (and still continue to be discovered), a typing methodology based on sequence-specific oligonucleotide hybridization must be able to address hundreds of specific sites simultaneously. Although microarray platforms offer sufficient multiplexing, classical solid-phase arrays require tremendous development and optimization efforts for such a complex set of oligonucleotide probes. The bead-based LabMap system (Luminex Corp., Austin, TX, USA) offers a suspension array platform that is being used for this purpose, but is still limited to below 100 probes per reaction. The PamChip technology (PamGene, ‘s-Hertoghenbosch, The Netherlands), on the other hand, offers significant advantages for the development of complex typing assays such as the one presented by HLA typing.42 This unique microarray system makes use of nanoporous alumina membranes and allows efficient mixing and dynamic monitoring of melting curves without the need for complex microfluidics.43 However, of the currently available systems, neither LabMap nor the PamGene technology can be regarded strictly as biosensors. Apart from fundamental binding studies on the Biacore biosensor system, little work on biosensors specifically for tissue typing can be found. This may be explained by the complexity of the topic and the demanding requirements with respect to multiplexing. 2.2.4 Forensics
Genomic profiling of individuals is increasingly linked to forensic science or the search for evidence in crime scenes. Residual traces of DNA can be used for genetic fingerprinting or profiling and may help to convict suspects or to exonerate prisoners. Currently, a PCR of 13 common heterologous short tandem repeat (STR) sequences or base pair differences in mitochondrial DNA is used for individual profiling.44 These data are subsequently stored in national databases (e.g., combined DNA index system (CODIS) and national DNA database (NDNAD)). Although the different STR fragments are now analyzed after electrophoresis, DNA arrays or biosensors may be useful to
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS
simultaneously hybridize various fragments. However, as current techniques are sufficiently robust and only specialized accredited laboratories are allowed to carry out these investigations, little effort is being made to develop portable sensing systems for these kinds of applications. It might even be questioned whether less stringent systems are desirable in view of the impact of mistyping. 2.3
Agriculture
As DNA sensors are still under full investigation, much less research has been reported for applications not related to human diseases. Nevertheless, many potential applications can be found in the area of agriculture. Molecular marker-assisted selection (MAS) may greatly improve plant selection45 and animal breeding.46 Already, many alleles linked to biotechnological benefits (e.g., higher yield, better resistance to disease and/or stress factors, modified nutritional properties, etc.) have been discovered, but the use of MAS is rather limited. In particular, for inbreeding and/or minor crops, the price involved for the selection of different traits is still too high and cheaper alternatives are needed.47 Genetic engineering has also gained attention in food production. The use of GMO may result in higher yields and better food safety.48 On the other hand, the effects of large-scale implementation on environmental safety, public opinion, intellectual property rights, and internal quality parameters may not be overlooked. For these reasons, performance monitoring of GMO needs to be assured. At present, few research groups are developing DNA sensors for either the screening of GMO or MAS. Nevertheless, some data have been published. Selection markers of genetically modified plants were used to investigate the usefulness of a piezoelectric sensor for label-free detection,49,50 while an optical sensor was described that monitors hybridization events with fluorescent-labeled target sequences in real time.51 In another study, an electrochemical detector was optimized using a specific ssDNA target of transgenetic corn.52 2.4
Bioterrorism
Bioterrorism has existed for decades,53 but has received much attention since packages containing anthrax were posted in 2001. It has driven
5
the need for a fast, sensitive, and accurate testing of unknown, potentially biohazardous samples. Detectors for biological warfare agents should be decentralized and networked.54 In addition, their obligatory use in or near the area of attack requires portable systems that allow rapid, yet sensitive diagnosis. Because of sensitivity needs, many systems for biological warfare agents are based on real-time PCR.55,56 In order to ensure specificity and statistical confidence in the result of an assay for very low copy numbers (e.g., 100 copies ml−1 ), a minimum volume of a few hundred microliters must be processed. Integration and interfacing with sample pretreatment, therefore, requires advanced microfluidic technologies to bridge the gap between relatively large sample volumes and microstructures used for rapid analysis.57 A biosensor, based on an isothermal amplification step in combination with an optical detection, was validated for the detection of viable Bacillus anthracis spores.58 For further examples, readers are referred to a comprehensive review on this issue.59 It must be emphasized that the challenge remains to detect any of the possible pathogenic microorganisms that could be used in an attack, taking into account the huge background of similar nonpathogenic microorganisms constantly present in the environment and the desired speed of detection of such organisms. Arrays of sensitive sensors with rapid readout are therefore desirable in order to realize an adequate identification and decision system.
2.5
Personalized Medicine
Personalized medicine is increasingly mentioned in connection with multiparameter and biosensor applications. Indeed, several monogenic genotypic variants (alleles) have been correlated with phenotypic variations, for example, adverse drug reactions or even serious adverse events. In 2004, rofecoxib, a drug used widely at that time to treat patients with arthritis, was voluntarily withdrawn from the market, after some patients displayed signs of an increased risk for cardiovascular disease. It must, however, be noted that, the side effects and the therapeutic efficacy of drugs usually vary from person to person, making individually adapted treatments preferable. A first step toward
6
BIOSENSOR APPLICATIONS
such personalized drug delivery was enabled by Food and Drug Administration (FDA) approval of the AmpliChip CYP450 (Roche Diagnostics, Basel, Switzerland) test. In this test, the genotype of two genes of the cytochrome P450 can be determined, which gives an indication of the patient’s ability to metabolize and clear certain medical compounds. A second example is the UGT1A1 Invader assay (Third Wave Technologies, Madison, WI, USA) for detection of irinotecan-associated toxicity in the treatment of metastatic colorectal cancer. 3 REQUIREMENTS IMPOSED ON DNA-BASED BIOSENSORS
Despite impressive progress in the development of various promising types of biosensors (Figure 1), some challenges are still very difficult to overcome. Consequently, very few sensors have been validated with real samples and little more than a proof of concept has been reported. The examples
given in the preceding text show that developers of DNA biosensors face two important challenges: the necessity for a combination of extreme sensitivity and selectivity required for detection, plus the ever-increasing complexity of the clinical question to be addressed, which calls for the combination of multiple polymorphisms. The success of the glucose sensor has led to POC diagnostics often being put forward as the ideal biosensor application. From a medical point of view, detection of glucose offers an ideal scenario: the assay is monoparametric, it can be measured using an enzyme with a high catalytic turnover, the time-frame for decision-making is favorable, and the outcome leads to a clear action with immediate benefit for the patient. However, bringing DNA molecular tests to the POC imposes a number of challenging requirements that are not met by current DNA-based biosensors. The target DNA is most often embedded in a complex matrix, which, depending on its origin, can be very heterogeneous. As a consequence, extraction and further purification of the DNA is mandatory before its
Transducer
Capturing probe
Signal
Signal amplification
Working electrode
Passive sequence-specific probe
Charge
Redox cycling
Electrode pair
Capturing probe
Electroactive bases
Silver enhancement
FET
Specific hairpin probe
Electroactive mediator
Branched DNA
Redox label (e.g., ferrocene)
Liposomes
Nanowire
Specific probe with modified bases
Optical fibre
Peptide– nucleotide probe
FRET pair
Quartz crystal microbalance
Aptamers
Fluorescent dye
SPR surface
Quantum dot
Cantilever
Rayleigh scattering
SAW device
Up-converting phosphor
Giant magnetic resistor
Fluorescent intercallator Enzyme-induced precipitation Gold nanoparticle Gold particle and silver enhancement Magnetic particle
Figure 1. A schematic overview of the variety of reported DNA-based sensing schemes based on the basic transduction principle, the type of capturing molecules used, the signal-generating component, and possible signal-amplification strategies.
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS
actual detection. A POC system should therefore couple a DNA-based biosensor with highly sensitive, multiplex-specific detection to some device that preprocesses the sample. In many cases, the yield of target DNA is low, down to a few copies per milliliter of biological fluid. Biosensors with sufficient sensitivity to reach these targets have not yet been developed. Even when cultivating cells or bacteria under optimal conditions, below picomolar detection limits must be reached.60 The strategy that has been explored in many different variants is that of signal amplification. It is, however, questionable whether it is reasonable to assume that the required specificity can be guaranteed in vitro on the basis of the hybridization specificity and kinetics alone.61 A certain level of nonspecific reaction will not influence the clinical outcome when there is an abundance of specific material or where the hybridization kinetics are sufficiently discriminative. However, in view of the increased complexity of many applications, it is desirable to safeguard options in order to enhance their robustness. One way to achieve this is by using additional information of the intrinsic melting behavior of the formed duplexes, a feature that is jeopardized if precipitation reactions are used as a signal-amplification strategy. Enzymatic target-amplification reactions such as PCR allow the selective enrichment of the particular genetic loci to be analyzed up to an abundant level far above that of the background. Without any doubt PCR-based tests are currently indispensable in the field of molecular diagnostics. Since PCR requires sequential thermal cycling, miniaturization offers the benefit of increased speed.62 In combination with real-time fluorescence methods to monitor the progress of the PCR cycle by cycle, a major step toward integration has been taken. This has already lead to the development of POC systems such as the GeneXpert (Cepheid, Sunnyvale, CA, USA) and Liat Analyzer (IQUUM Inc., Marlborough, MA, USA). A major drawback of this approach is the limitation on the number of mutations or polymorphisms that can be analyzed simultaneously. DNA-based biosensors could offer such multiplexing capabilities. An alternative approach could be envisaged using miniaturized transponders.63 A transponder is, in principle, a device that combines a transmitter and a responder circuit. The PharmaSeq microtransponders (PharmaSeq Inc., New York, NY,
7
USA) are highly miniaturized and are activated by light. The chips, measuring only 0.25 × 0.25 × 0.1 mm, contain a photocell that, upon illumination with a laser-beam, powers a radio transmitter circuit. The activated chip then transmits its hardcoded 64-bit identification code. This code can be linked to the type of probe that has been immobilized on the microtransponder. Interrogation with a second laser system is used to determine the presence of fluorescent-labeled target molecules in a flow-cytometric setup. It might be feasible to further refine this type of chip to hold an electronic detection element connected to the logic of the identification transmitter, activating the chip only if hybridization has occurred. This would simplify the setup significantly, and, instead of integrating the wet-chemical process steps into fluidic cartridges, the electronic detection elements would be fully immersed in any homogeneous reaction system, reporting the binding events only upon activation with light. Despite the already extreme miniaturization, the combination of a high number of such chips in a small sample volume poses some challenges in keeping the chips suspended and consequently individually addressable. Another revolutionary development, specifically focused on the challenge of multiparameter testing, could emerge from single-molecule sequencing. One promising approach uses 50-nm-wide waveguides to restrict the effective observation volume to the vicinity of a single immobilized DNA polymerase molecule. When this polymerase incorporates a fluorescent-tagged nucleotide, the tag is excited and the emission is detected. Using four dyes with distinct spectral characteristics, each sequentially incorporated nucleotide can theoretically be identified.64 Besides the attractive detection features, many sensing devices may offer additional functionality. Although not exploited as a biosensor system, electrophoretic attraction and repulsion has been used in the NanoChip system (Nanogen Inc., San Diego, CA, USA) for rapid hybridization and increased stringency.65 Electronically addressed in situ synthesis is used by Combimatrix Corp. (Mukilteo, WA, USA) for making custom arrays66 for which an electrochemical readout system was developed and is marketed as ElectraSense . Magnetic bead-based systems offer the advantage that manipulation can easily be implemented and combined with sensitive
8
BIOSENSOR APPLICATIONS
detection and even evaluation of the binding force.67 In summary, the DNA-based biosensor in the strict sense will only be a part of a fully integrated system or a so-called lab-on-a-chip device.68 Ideally, such a device would integrate multiple bioanalytical functions into an easy-to-use, small, and portable instrument with further potential benefits including low reagent consumption, low timeto-result, and minimal waste.6 In most cases, an array of sensing elements will be required to address multiple parameters (SNPs, mutations, etc.) simultaneously. 4 A POLYMER ARRAY OF INTERDIGITATED ELECTRODE DNA SENSORS 4.1
Introduction
Electrochemical biosensors offer great potential for miniaturization and integration. This aspect is of particular interest for DNA-based biosensors due to the necessity of analyzing multiple genetic loci simultaneously. As mentioned earlier, some sensor arrays are currently finding their way to commercialization, such as the GeneLyzer (Toshiba Corporation, Tokyo, Japan) or the eSensor system. With 20 and 36 sensing sites respectively, the multiplexing capability, although better than that of real-time fluorescence systems, still falls short in accommodating an ever-increasing number of applications. In this regard, some researchers investigated the capability of combining integrated circuit sensor arrays such as photodiode arrays69 or a charge-coupled device (CCD)-element70 with oligonucleotide-capturing probe arrays. The polyanionic nature of DNA has been exploited in a number of sensing schemes that assess the charge density in the case of hybridization to a solid-phase immobilized probe (Table 1). A simple way of assessing charge is by evaluating
2 1.5 ksol 1
50% kDNA-associated ions
0.5 0 −2
−1.5
−1
−0.5
0
0.5
1
1.5
2
Figure 2. Contour plot indicating the reach of the field lines if an electric field is applied between two planar electrodes of width 1 arb unit and with an equal interelectrode spacing of 1 arb unit. Assuming that a typical probe–target duplex of about 30 bp measures about 10 nm, and a typical target DNA sequence would comprise 300 or more bases, submicron electrode width and spacing is required in order to bring the assessed portion of the field lines within the area where the binding event is monitored. As the associated ion distribution is highly influenced by the ionic strength, the associated diffuse charge layer will expand further away from the solid phase as low-ionic-strength buffers are used (light-blue shaded area). In that case, the change in local conductivity (κDNA−associated ions ) versus the background electrolytic conductivity of the measurement solution (κsol ) can be optimized.
the local electrolytic impedance. Most impedancebased work addresses the electrochemical interfacial impedance, since probes are easily immobilized on electrode surfaces in a self-assembled monolayer. An alternative approach is to treat the microenvironment between two electrodes as a conductivity cell, in which the concentration of mobile ions determines the local electrolytic conductivity. However, to obtain a sufficient signal-to-noise ratio in such a setup, the electrical field lines need to be confined as close as possible to the molecules to be assessed (Figure 2). As a consequence, micron-sized or even submicron-sized electrode structures are needed. Since cost is always a major driver, this section describes attempts made to develop a scalable process that results in such micron-sized thin-film
Table 1. Different detection methods using nucleic acid–associated charge
Transducer Silicon oxide
Si nanowires Gold electrode Electrode pair
Effect Interfacial impedance Field effect Interfacial impedance Field effect Capacitance Interdigitated electrode impedance
Method Electrical impedance spectroscopy Surface potential Optoelectrochemical impedance spectroscopy
Reduction in associated mobile counterions
References 71 72 73 27 74 75
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS
carrier material is expensive, but it offers the best substrate to realize highly accurate micron-sized structures by micromachining. If combined with state-of-the-art micromolding techniques, these micron-sized structures can be replicated in polymers resulting in very inexpensive microstructures. It is known that, under certain conditions, metal deposition by evaporation suffers from a shadowing effect and will only deposit metal on the surfaces that are “seen” from the standpoint of the evaporation source. This effect has been exploited for the realization of arrays of nanowires.76 Elaborating further on this principle, an appropriate design of a three-dimensional microstructure in a substrate could result in a self-contained shadowing effect that enables the creation of electrically disconnected interdigitated electrodes (IDEs). Such a three-dimensional design is shown in Figure 3. The combination of channels and hills results in the proper shadow regions where no metal is deposited, while the exposed parts form the electrodes of the interdigitated pairs. An attractive feature of IDE structures is that they show a very reproducible and wellcontrolled impedance characteristic. Furthermore,
microelectrode structures, for which an innovative manufacturing approach has been evaluated in combination with the assessment of labelfree hybridization detection. This route has been researched by a European consortium within the 5th Framework, coordinated by Innogenetics NV (Ghent, Belgium) to assess its potential use in future markets in the in vitro diagnostics field. It is based on building awareness that multiparameter diagnostics will gain in importance in routine analysis, and the assumption that dedicated technologies for detection should be compatible with low-cost manufacturing (http://cordis.europa.eu/nanotechnology/src/ pressroom-pub.htm).
4.2
9
Directional Metal Deposition on 3D Structures for Microelectrode Production
Until recently, micron-sized electrode structures could only be obtained with sophisticated and expensive lithographic techniques. Furthermore, this type of manufacturing is mainly used in silicon foundries. The use of silicon as a passive Channels
(a)
tion
osi
Hills ion
ect
Dir
ep of d
(b) Shadow region Channel Open, not metallized
Hill
Electrode A
Electrode B (c)
(d)
Figure 3. An appropriate combination of parallel channels and hills forms the basis for making interdigitated electrode structures by a single directional metal deposition: (a) before metal deposition and (b) after metal deposition. Scanning electron microscope images of realized three-dimensional structures as they were designed to show the desired shadowing effect: (c) detail of a silicon master structure and (d) the result after metal deposition.
10
BIOSENSOR APPLICATIONS
this characteristic can be described very accurately using a fairly simple electrical equivalent model.77 A mathematical fit of this model with the experimental data allows easy interpretation (Figure 4). A plot of the impedance characteristics after metal deposition on the silicon master structures, which can be used as the basis for polymer replication, is given in Figure 5. The impedance characteristics on the resulting three-dimensional interdigitated structures show a similar profile as the silicon-based planar interdigitated structures that were used as a reference. In the lowfrequency range (1–10 kHz), the characteristic is almost purely capacitive. Between 10 kHz and a few hundred kHz, a clear resistive plateau reflecting the bulk electrolyte resistance is observed.
At the higher end of the tested frequency range (1 MHz), the parasitic capacitances dominate the impedance. Using state-of-the-art micromolding techniques, the silicon microstructures can be replicated in polymers. The combination with directional metal deposition leads to an elegant, two-step production process: In a first step, replicas of the appropriate three-dimensional structures are produced by injection molding. In the second step, metal is deposited by directional deposition, which can be processed in the same fashion, leading to affordable IDEs. The mold inserts to be used in the molding tools can be derived from the silicon microstructures by galvanoplating (Figure 6). Multicavity molding ZCPE = (j wC int ) −n Rsol
108
|Z |
ZPAR = (j wC PAR) −1 106
104 101
102
103
104
105
106
105
106
Frequency (Hz)
Phase (°)
0 −20 −40 −60 −80 101
102
103
104 Frequency (Hz)
Figure 4. Typical impedance plots (modulus and phase) of low-signal impedance when using interdigitated electrodes in an electrolytic solution. Inset illustrates a simple equivalent model that fits this characteristic. ZCPE is a so-called constant phase element that approximates the interface impedance. As the interdigitated electrodes are driven in the linear region (low driving signal typically 5–10 mVrms ), the value of n is between 0.9 and 1, being close to purely capacitive. ZPAR is the parasitic capacitance. The parameter of interest is the electrolytic conductivity in the close proximity of the electrodes, which is reflected in the Rsol .
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS
Impedance (Ω)
1 000 000
100 000
IDE on Si 10−3 M KCl IDE on Si 10−2 M KCl
Master 10−2 M KCl Master 10−3 M KCl
IDE on Si 10−1 M KCl
Master 10−1 M KCl
11
10 000
1000
100 1000
10 000
100 000
1 000 000
10 000 000
Frequency (Hz) Figure 5. Illustration of the similarity of the electronic impedance measured with state-of-the-art silicon-based 1-µm planar interdigitated electrode structures (IDE, lines) and structures obtained by directional metal deposition on the proposed three-dimensional structures as they were realized in silicon. A clear resistive region at decreasing levels as electrolyte concentration increases is present in both cases. In the low-frequency region, a flattening of the slope for the three-dimensional structures can be observed. This is due to a secondary resistive effect between the contact pads and the electrolyte solution. Careful encapsulation removes this effect as is proved in the case of the standard planar electrodes.
(a)
(b)
Hill Channel
(c)
(d)
Figure 6. Several master structures for arrays of interdigitated electrode structures have been tested. Using these silicon master structures, mold inserts were fabricated by galvanoforming. (a) A prototype for a 128-sensel array. (b) SEM image showing the detailed negative. The mold inserts were used in standard injection molding equipment to make polymer replicas. (c) The molding chamber in which two cavities containing the mold inserts are addressed simultaneously. Each molding shot therefore results in two replicas still fixed to each other by the runner polymer. The resulting pair of devices can be seen in the foreground. (d) SEM image of a detail of the resulting molded replica showing the accurate reproduction of the channels and hills that form the basis of the required three-dimensional structures.
12
BIOSENSOR APPLICATIONS
tools are often used to further reduce the cost. For reasons of minimizing additional process steps to realize interconnections to each of the electrodes, a physical shadow mask can be used during the metal deposition step to form a common interconnect line to one electrode of each of the interdigitated pairs in a column. To avoid the need for a multilayer process, access to the counterelectrode of each individual pair can be provided by contact pins through the housing of the fluidic chip after assembly (Figure 7).
4.3
Assessing the DNA-associated Electrolytic Conductivity
The goal of this work was to make an array of detection elements for the specific detection of hybridization of amplified DNA targets to
immobilized probe oligonucleotides based on the assessment of electric charge accumulation. The phosphate backbone of DNA provides a negative charge to the molecule at neutral pH. These negative charges are neutralized by cationic counterions. The counterions are associated to the phosphate backbone in a condensed layer and/or a diffuse layer, depending on the ionic strength of the solution. Figure 8 shows the impedance characteristics of a 1-µm silicon-based planar IDE structure before and after probe immobilization and after hybridization. There is a clear effect of probe immobilization in the capacitive region as well as in the resistive plateau. After hybridization with an 87-nucleotide HLA-DQB synthetic target, a further distinct decrease in the equivalent resistance was observed, while the capacitive component remained unchanged. The corresponding
Physical shadow mask
Counterelectrode contact pad
(a)
(b)
Shadowed region
Sensel region
Interconnect line
(d)
(c) Figure 7. During the directional metal deposition step, an additional physical shadow mask was aligned on top of the structures to define the column addressing interconnection lines while electrically separating the different columns (a). At this stage, an array of 96 interdigitated sensing elements or sensels was formed in an 8-column by 12-row format. One electrode of each sensing element in one column is already interconnected and the interconnect lines reach the edge of the arrays (b). A polymer cover defines the fluidic path over the different sensing elements and contains perforations that allow contact between the counterelectrodes and contact pins. A number of prototype fluidic lids have been made (c). A diagram of the 96-element assembly is shown (d).
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS
13
|Z | (Ω)
106
104 103
102
104 Frequency (Hz)
105
106
105
106
0
Phase (°)
−20 −40
Start measured data After probe coupling measured data After hybridization measured data At start: calculated by fitting After probe coupling: calculating by fitting After hybridization: calculated by fitting
−60 −80 102
103
104 Frequency (Hz)
Figure 8. Measured impedance characteristic for a 1-µm interdigitated sensel at different stages. The discrete dots are the measured raw data points. The lines are the result of the calculated data based on the best fit of the equivalent model to the measured data. The resulting extracted parameters are summarized in Table 2.
equivalent model parameters calculated by curve fitting, are given in Table 2. In a first investigation of the effect of decreasing the electrode dimensions on the impedance shift upon accumulation of DNA, planar IDE structures with varying electrode width and spacing were tested. The 15 sensels (defined as sensing el ement in analogy to the definition of “pixel”) of one single chip were activated for oligonucleotide coupling by application of a mercaptosilane film. A great deal of attention was paid to the optimization of this activation step since it is critical to obtain stable impedances throughout the whole process. The impedance characteristics of each individual sensel were measured in the frequency range of 1 kHz–1 MHz. A 10-µM oligonucleotide solution was manually spotted on 12 of the 15 sensels. Three types of thiol (SH)-modified Table 2. Calculated equivalent model parameters after fitting
Start Modification Hybridization
Cint
n
Rsol ()
CPAR (pF)
465 × 10−12 363 × 10−12 398 × 10−12
0.94 0.94 0.93
37 323 20 825 13 534
9.9 11.0 14.0
oligonucleotides were used in this instance: (i) a 16-nucleotide HLA-DQB probe with a single hexaethylene glycol (HEG) spacer molecule between the probe and the SH-group; (ii) a variant of this same probe, with a five-unit HEG spacer; and (iii) a 25-nucleotide Mycobacterium probe with a single HEG-unit spacer but preceded by 41 adenines before the actual specific probe (66 nucleotides in total). After probe coupling and washing, the impedance characteristics were recorded again in the same measurement buffer. The results showed that a low-conductivity buffer is preferable for this purpose. A 1-mM Tris or a 50-mM glycine buffer was the buffer of choice since they both conserved the duplexes formed after the hybridization reaction. For interpretation, the change in resistance before and after the probe coupling was determined as: Relative R =
(Rsol
before
Rsol
− Rsol
after )
(1)
before
The graph in Figure 9 summarizes the results. Each bar represents the average of the change of impedance of four sensels. It can be seen that the change in resistance increases with decreasing electrode dimensions. In addition, the decrease
14
BIOSENSOR APPLICATIONS 0
Relative ∆Rsol (%)
−10 −20 −30
0.5 µm
−40
1 µm
−50
5 µm
−60 −70 −80
HEG-DQB
HEG5-DQB
HEG-A41-Myc
Figure 9. Change in Rsol extracted from the measured data by curve fitting for the three types of interdigitated structures that have been investigated (0.5, 1, and 5 µm), comparing the value after silanization, preparing the sensels for immobilization, and after probe coupling. The experiment summarizes the data of 12 sensels of a 15-sensel array. Each type of probe was deposited on a group of four sensels Error bars indicate full range (minimum and maximum out of the four observations).
is systematically higher for longer oligonucleotide probes (25 vs 66 nucleotide probes). The effect of the longer ethylene glycol spacer on the resistance change might be due to the increased hydrophilicity near the surface.
4.4
Detection of Sequence-specific Hybridization
In a subsequent step, the response to hybridization with synthetic complementary oligonucleotides was studied in more detail. Using planar prototype electrode structures, a further analysis of the effect of the reduction of dimensions on hybridization detection was performed. Although a somewhat increased response was evident in some cases for the electrode structures with the smallest dimensions, the reproducibility was lower, mainly due to the instability of the submicron-sized gold electrodes even when produced using the standard liftoff process (data not shown). Therefore, only 1-µm IDE structures were used in further experiments. To challenge the specificity of detection, three variants of HLA-DQB probes were used on a single chip: in addition to the DQB probe used earlier, a probe with three nucleotides difference in the center of the probe-sequence (DQB3MM) and one with only a single nucleotide difference (DQB1MM) were immobilized on a 15-sensel
array. Firstly, a synthetic 80-base oligonucleotide with a perfectly matching complementary region for the DQB probe was incubated over the 15-sensel array at a concentration of 10 nM. Subsequently, the hybrids formed were denatured on chip and incubated again with 10-nM synthetic target, but in this case with a perfectly complementary region for the DQB3MM probe. The respective results are shown in Figure 10. When probes with the same spacer are used, a signal-tonoise ratio (perfect match signal versus mismatch signal) of at least 4 is obtained. In a further set of experiments, the DQB probe and the DQB1MM probe were used on a single chip and hybridized with a 261-nucleotide PCR fragment of DQB (∼1 nM). As one of the primers in the PCR reaction contained a 5 -phosphate group, single-stranded material could be obtained before incubation by digestion with λ exonuclease. It can be seen that using such a long target the effect of the spacer length for the specific probe becomes more significant. Again comparing the probes with the same spacer, a signal-to-noise ratio of higher than 3 was achieved. These results show that specific post-PCR detection of multiple targets using this approach is feasible without any additional signal-amplification strategy. Additional functionality, such as on-chip localized heating, has also been demonstrated (data not shown), opening the way to multiplex melting analysis. The integration of the sensels in a microfluidic system that would allow dynamic
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS Probe
Sequence
HEG3-DQB
3′HS-(CH2)6-(HEG)3 -CAGGTGGCTGCGGGCC-5′
HEG5-DQB
3′HS-(CH2)6-(HEG)5 -CAGGTGGCTGCGGGCC-5′
15
HEG3-DQB1MM 3′HS-(CH2)6-(HEG)3 -CAGGTGGGTGCGGGCC-5′ HEG3-DQB3MM 3′HS-(CH2)6-(HEG)3 -CAGGTGTGCGCGGGCC-5′ Target
Sequence
80 nt
5′CTGTCCACCGACGCCCGGGCCCCCTCCAGGACTTCCTTCT GGCTGTTCCAGTACTCGGCGCTAGGCCGCCCCTGCGGCGT 3′
87 nt
5′GCACACCCTGTCCACACGCGCCCGGGCCCCCTCCAGGACTTCC TTCTGGCTGTTCCAGTACTCGGCGCTAGGCCGCCCCTGCGGCGT 3′
Relative decrease in resistance after hybridization (%)
10 0 −10 −20 −30 −40 −50
HEG3-DQB
HEG5-DQB
HEG3DQB1MM
HEG3DQB3MM
Probe Hybr DQB80
Hybr DQB87 3MM
Hybr 1nM ssPCR DQB
Figure 10. Change in Rsol extracted from the measured data by curve fitting for 1-µm interdigitated structures, comparing the value before and after hybridization. The graph summarizes the data for three experiments: the first target was an 80-nucleotide synthetic complement for the DQB probe, the next was a synthetic complement of 87 nucleotides matching the DQB3MM, and, finally, a 261-nucleotide ssPCR product of DQB was hybridized at a concentration of approximately 1 nM.
incubation and improve mass transfer is a straightforward next step.
5 CONCLUSIONS AND FUTURE PERSPECTIVES
An enormous potential may be expected from future developments in DNA-based biosensors in view of the ever-increasing number of applications that require the decoding of specific nucleic acid targets in a single sample. Arrays of biosensors offer the potential of efficient and simultaneous detection of multiple hybridization events without the need for sophisticated instrumentation. As
discussed, it will be quite a challenge to attain the required sensitivity and specificity if the combination with a target-amplification step is not realized. In addition, for most real-life applications, the DNA target molecules are embedded in a heterogeneous complex matrix. Integration with at least the extraction and purification steps is required, preferably even in closed-tube systems, if the full benefit of biosensor-based systems is to be appreciated in easy-to-use, handheld instruments. Integration of biochemical processes such as cell lysis, DNA extraction and purification, and enzymatic target amplification, preferably with arrays of sensors, brings enormous challenges with respect to microfluidics, electronic interconnection, and
16
BIOSENSOR APPLICATIONS
interfacing. A unique approach that could circumvent a number of these challenges makes use of extremely miniaturized transponders. The development of these extremely small chips, known as “smart dust”, may offer a completely new perspective to sensing and associated instrumentation.
ACKNOWLEDGMENTS
The work on the Polymer Array of Interdigitated Electrode DNA Sensors was carried out in the framework of two projects funded by the Flemish Government (IWT 960096, IWT 030059) and one EC-funded project (BRPR-CT98-0770). The contributions of our colleagues at Innogenetics (Georges Van Reybroeck, Walter Hofer, Wim Tachelet), IMEC Vzw (Peter Vangerwen, Andrew Campitelli, Jan Suls), IMM GmbH (Peter Detemple, Marion B¨ar), Cranfield University (Jeff Newman, David Cullen) and Biodot Ltd. (Chris Flack, Anthony Peloe) are greatly appreciated. Finally we would like to thank Andr´e Van de Voorde for the many constructive discussions and valuable input and Anne Farmer for the critical review of the manuscript.
REFERENCES 1. J. D. Hoheisel, Microarray technology: beyond transcript profiling and genotype analysis. Nature Reviews Genetics, 2006, 7(3), 200–210. 2. J. Khan, L. H. Saal, M. L. Bittner, Y. D. Chen, J. M. Trent, and P. S. Meltzer, Expression profiling in cancer using cDNA microarrays. Electrophoresis, 1999, 20(2), 223–229. 3. Y. Pawitan, J. Bjohle, L. Amler, A. L. Borg, S. Egyhazi, P. Hall, X. Han, L. Holmberg, F. Huang, S. Klaar, E. T. Liu, L. Miller, H. Nordgren, A. Ploner, K. Sandelin, P. M. Shaw, J. Smeds, L. Skoog, S. Wedren, and J. Bergh, Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Research, 2005, 7(6), R953–R964. 4. B. K. Zehentner, D. C. Dillon, Y. Q. Jiang, J. C. Xu, A. Bennington, D. A. Molesh, X. Q. Zhang, S. G. Reed, D. H. Persing, and R. L. Houghton, Application of a multigene reverse transcription-PCR assay for detection of mammaglobin and complementary transcribed genes in breast cancer lymph nodes. Clinical Chemistry, 2002, 48(8), 1225–1231. 5. T. M. H. Lee and I. M. Hsing, DNA-based bioanalytical microsystems for handheld device applications. Analytica Chimica Acta, 2006, 556(1), 26–37.
6. S. A. Soper, K. Brown, A. Ellington, B. Frazier, G. GarciaManero, V. Gau, S. I. Gutman, D. F. Hayes, B. Korte, J. L. Landers, D. Larson, F. Ligler, A. Majumdar, M. Mascini, D. Nolte, Z. Rosenzweig, J. Wang, and D. Wilson, Point-of-care biosensor systems for cancer diagnostics/prognostics. Biosensors and Bioelectronics, 2006, 21(10), 1932–1942. 7. A. Brecht and G. Gauglitz, Optical probes and transducers. Biosensors and Bioelectronics, 1995, 10(9–10), 923–936. 8. World Health Organization, Scaling up the Response to Infectious Diseases. A Way Out of Poverty, Report on infectious diseases, 2002 WHO/CDS/2002.7 (Geneva: WHO, 2002). link: www.who.int/infectious-disease-report/ index.html. 9. S. A. Hoption, J. P. van Netten, and C. van Netten, Acute infections as a means of cancer prevention: opposing effects to chronic infections. Cancer Detection and Prevention, 2006, 30(1), 83–93. 10. B. Pejcic, R. D. Marco, and G. Parkinson, The role of biosensors in the detection of emerging infectious diseases. Analyst, 2006, 131(10), 1079–1090. 11. P. D. Patel, Overview of affinity biosensors in food analysis. Journal of AOAC International, 2006, 89(3), 805–818. 12. A. Rasooly and K. E. Herold, Biosensors for the analysis of food- and waterborne pathogens and their toxins. Journal of AOAC International, 2006, 89(3), 873–883. 13. A. K. Deisingh and M. Thompson, Sequences of E. coli O157:H7 detected by a PCR-acoustic wave sensor combination. Analyst, 2001, 126(12), 2153–2158. 14. J. C. Liao, M. Mastali, V. Gau, M. A. Suchard, A. K. Moller, D. A. Bruckner, J. T. Babbitt, Y. Li, J. Gornbein, E. M. Landaw, E. R. McCabe, B. M. Churchill, and D. A. Haake, Use of electrochemical DNA biosensors for rapid molecular identification of uropathogens in clinical urine specimens. Journal of Clinical Microbiology, 2006, 44(2), 561–570. 15. B. P. Nelson, M. R. Liles, K. B. Frederick, R. M. Corn, and R. M. Goodman, Label-free detection of 16S ribosomal RNA hybridization on reusable DNA arrays using surface plasmon resonance imaging. Environmental Microbiology, 2002, 4(11), 735–743. 16. G. Jannes and V. D. De, A review of current and future molecular diagnostic tests for use in the microbiology laboratory. Methods in Molecular and Cellular Biology, 2006, 345, 1–21. 17. J. H. Wang, W. L. Fu, M. H. Liu, Y. Y. Wang, Q. Xue, J. F. Huang, and Q. Y. Zhu, Multichannel piezoelectric genesensor for the detection of human papilloma virus. Chinese Medical Journal, 2002, 115(3), 439–442. 18. M. Chen, M. H. Liu, L. L. Yu, G. R. Cai, Q. H. Chen, R. Wu, F. Wang, B. Zhang, T. L. Jiang, and W. L. Fu, Construction of a novel peptide nucleic acid piezoelectric gene sensor microarray detection system. Journal of Nanoscience and Nanotechnology, 2005, 5(8), 1266–1272. 19. K. Kukanskis, J. Elkind, J. Melendez, T. Murphy, G. Miller, and H. Garner, Detection of DNA hybridization using the TISPR-1 surface plasmon resonance biosensor. Analytical Biochemistry, 1999, 274(1), 7–17.
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS 20. J. Wang, X. H. Cai, G. Rivas, H. Shiraishi, P. A. M. Farias, and N. Dontha, DNA electrochemical biosensor for the detection of short DNA sequences related to the human immunodeficiency virus. Analytical Chemistry, 1996, 68(15), 2629–2634. 21. B. Campbell, J. Lei, D. Kiaei, D. Sustarsic, and S. El Shami, Nucleic acid testing using surface plasmon resonance fluorescence detection. Clinical Chemistry, 2004, 50(10), 1942–1943. 22. A. Logrieco, D. W. Arrigan, K. Brengel-Pesce, P. Siciliano, and I. Tothill, DNA arrays, electronic noses and tongues, biosensors and receptors for rapid detection of toxigenic fungi and mycotoxins: a review. Food Additives and Contaminants, 2005, 22(4), 335–344. 23. X. B. Zhong, L. Leng, A. Beitin, R. Chen, C. McDonald, B. Hsiao, R. D. Jenison, I. Kang, S. H. Park, A. Lee, P. Gregersen, P. Thuma, P. Bray-Ward, D. C. Ward, and R. Bucala, Simultaneous detection of microsatellite repeats and SNPs in the macrophage migration inhibitory factor (MIF) gene by thin-film biosensor chips and application to rural field studies. Nucleic Acids Research, 2005, 33(13), e121. 24. A. J. C. Eun, L. Q. Huang, F. T. Chew, S. F. Y. Li, and S. M. Wong, Detection of two orchid viruses using quartz crystal microbalance-based DNA biosensors. Phytopathology, 2002, 92(6), 654–658. 25. J. Zielenski and L. C. Tsui, Cystic fibrosis: genotypic and phenotypic variations. Annual Review of Genetics, 1995, 29, 777–807. 26. K. M. Millan and S. R. Mikkelsen, Sequenceselective biosensor for DNA-based on electroactive hybridization indicators. Analytical Chemistry, 1993, 65(17), 2317–2323. 27. J. Hahm and C. M. Lieber, Direct ultrasensitive electrical detection of DNA and DNA sequence variations using nanowire nanosensors. Nano Letters, 2004, 4(1), 51–54. 28. D. Whang, S. Jin, Y. Wu, and C. M. Lieber, Large-scale hierarchical organization of nanowire arrays for integrated nanosystems. Nano Letters, 2003, 3(9), 1255–1259. 29. R. M. Umek, S. W. Lin, J. Vielmetter, R. H. Terbrueggen, B. Irvine, C. J. Yu, J. F. Kayyem, H. Yowanto, G. F. Blackburn, D. H. Farkas, and Y. P. Chen, Electronic detection of nucleic acids: a versatile platform for molecular diagnostics. Journal of Molecular Diagnostics, 2001, 3(2), 74–84. 30. A. Bardea, F. Patolsky, A. Dagan, and I. Willner, Sensing and amplification of oligonucleotide-DNA interactions by means of impedance spectroscopy: a route to a Tay-Sachs sensor. Chemical Communications, 1999, 1, 21–22. 31. A. Bardea, A. Dagan, I. Ben-Dov, B. Amit, and I. Willner, Amplified microgravimetric quartz crystal-microbalance analyses of oligonucleotide complexes: a route to a TaySachs biosensor device. Chemical Communications, 1998, 7, 839–840. 32. X. C. Zhou, L. Q. Huang, and S. F. Y. Li, Microgravimetric DNA sensor based on quartz crystal microbalance: comparison of oligonucleotide immobilization methods and the application in genetic diagnosis. Biosensors and Bioelectronics, 2001, 16(1–2), 85–95. 33. J. H. Watterson, S. Raha, C. C. Kotoris, C. C. Wust, F. Gharabaghi, S. C. Jantzi, N. K. Haynes, N. H. Gendron,
34.
35.
36. 37.
38.
39.
40.
41.
42.
43.
44. 45.
46.
17
U. J. Krull, A. E. Mackenzie, and P. A. E. Piunno, Rapid detection of single nucleotide polymorphisms associated with spinal muscular atrophy by use of a reusable fibreoptic biosensor. Nucleic Acids Research, 2004, 32(2), e18. T. Jiang, M. Minunni, P. Wilson, J. Zhang, A. P. Turner, and M. Mascini, Detection of TP53 mutation using a portable surface plasmon resonance DNA-based biosensor. Biosensors and Bioelectronics, 2005, 20(10), 1939–1945. J. Wang, P. E. Nielsen, M. Jiang, X. H. Cai, J. R. Fernandes, D. H. Grant, M. Ozsoz, A. Beglieter, and M. Mowat, Mismatch sensitive hybridization detection by peptide nucleic acids immobilized on a quartz crystal microbalance. Analytical Chemistry, 1997, 69(24), 5200–5202. D. Stipp, Gene chip breakthrough. Fortune, 1997, 135(6), 56. D. P. Malinowski, Molecular diagnostic assays for cervical neoplasia: emerging markers for the detection of high-grade cervical disease. Biotechniques, 2005, 38(4), S17–S23. A. Rasooly and J. Jacobson, Development of biosensors for cancer clinical testing. Biosensors and Bioelectronics, 2006, 21(10), 1851–1858. N. Ren, Q. H. Ye, L. X. Qin, B. H. Zhang, Y. K. Liu, and Z. Y. Tang, Circulating DNA level is negatively associated with the long-term survival of hepatocellular carcinoma patients. World Journal of Gastroenterology, 2006, 12(24), 3911–3914. G. Sozzi, D. Conte, M. E. Leon, R. Cirincione, L. Roz, C. Ratcliffe, E. Roz, N. Cirenei, M. Bellomi, G. Pelosi, M. A. Pierotti, and U. Pastorino, Quantification of free circulating DNA as a diagnostic marker in lung cancer. Journal of Clinical Oncology, 2003, 21(21), 3902–3908. Y. H. Su, M. J. Wang, D. E. Brenner, A. Ng, H. Melkonyan, S. Umansky, S. Syngal, and T. M. Block, Human urine contains small, 150 to 250 nucleotide-sized, soluble DNA derived from the circulation and may be useful in the detection of colorectal cancer. Journal of Molecular Diagnostics, 2004, 6(2), 101–107. I. De Canck, G. Mersch, I. Dossche, P. Adams, R. Bray, H. Gebel, and G. Parish, Testing a new technology platform for typing HLA alleles (4-MAT (TM)). Tissue Antigens, 2006, 67(6), 557. R. van Beuningen, H. van Damme, P. Boender, N. Bastiaensen, A. Chan, and T. Kievits, Fast and specific hybridization using flow-through microarrays on porous metal oxide. Clinical Chemistry, 2001, 47(10), 1931–1933. M. Schanfield, Forensic science. Croatian Medical Journal, 2001, 42(3), 217–352. R. K. Varshney, D. A. Hoisington, and A. K. Tyagi, Advances in cereal genomics and applications in crop breeding. Trends in Biotechnology, 2006, 24(11), 490–499. P. K. Basrur and W. A. King, Genetics then and now: breeding the best and biotechnology. Revue Scientifique Et Technique De L Office International Des Epizooties, 2005, 24(1), 31–49.
18
BIOSENSOR APPLICATIONS
47. R. K. Varshney, A. Graner, and M. E. Sorrells, Genomicsassisted breeding for crop improvement. Trends in Plant Science, 2005, 10(12), 621–630. 48. V. Garcia-Canas, A. Cifuentes, and R. Gonzalez, Detection of genetically modified organisms in foods by DNA amplification techniques. Critical Reviews in Food Science and Nutrition, 2004, 44(6), 425–436. 49. I. Mannelli, M. Minunni, S. Tombelli, and M. Mascini, Quartz crystal microbalance (QCM) affinity biosensor for genetically modified organisms (GMOs) detection. Biosensors and Bioelectronics, 2003, 18(2–3), 129–140. 50. M. Minunni, S. Tombelli, J. Fonti, M. M. Spiriti, M. Mascini, P. Bogani, and M. Buiatti, Detection of fragmented genomic DNA by PCR-free piezoelectric sensing using a denaturation approach. Journal of the American Chemical Society, 2005, 127(22), 7966–7967. 51. C. Peter, M. Meusel, F. Grawe, A. Katerkamp, K. Cammann, and T. Borchers, Optical DNA-sensor chip for real-time detection of hybridization events. Fresenius Journal of Analytical Chemistry, 2001, 371(2), 120–127. 52. Y. Ren, K. Jiao, G. Y. Xu, W. Sun, and H. W. Gao, An electrochemical DNA sensor based on electrodepositing aluminum ion films on stearic acid-modified carbon paste electrode and its application for the detection of specific sequences related to bar gene and CP4 Epsps gene. Electroanalysis, 2005, 17(23), 2182–2189. 53. M. D. Phillips, Bioterrorism: a brief history. Northeast Florida Medicine Journal, 2005, 56(1), 32–35. 54. D. Ivnitski, D. J. O’Neil, A. Gattuso, R. Schlicht, M. Calidonna, and R. Fisher, Nucleic acid approaches for detection and identification of biological warfare and infectious disease agents. Biotechniques, 2003, 35(4), 862–869. 55. C. A. Bell, J. R. Uhl, T. L. Hadfield, J. C. David, R. F. Meyer, T. F. Smith, and F. R. Cockerill, Detection of Bacillus anthracis DNA by lightcycler PCR. Journal of Clinical Microbiology, 2002, 40(8), 2897–2902. 56. A. R. Hoffmaster, R. F. Meyer, M. P. Bowen, C. K. Marston, R. S. Weyant, K. Thurman, S. L. Messenger, E. E. Minor, J. M. Winchell, M. V. Rassmussen, B. R. Newton, J. T. Parker, W. E. Morrill, N. McKinney, G. A. Barnett, J. J. Sejvar, J. A. Jernigan, B. A. Perkins, and T. Popovic, Evaluation and validation of a real-time polymerase chain reaction assay for rapid identification of Bacillus anthracis. Emerging Infectious Diseases, 2003, 9(4), 511. 57. P. Belgrader, M. Okuzumi, F. Pourahmadi, D. A. Borkholder, and M. A. Northrup, A microfluidic cartridge to prepare spores for PCR analysis. Biosensors and Bioelectronics, 2000, 14(10–11), 849–852. 58. A. J. Baeumner, B. Leonard, J. McElwee, and R. A. Montagna, A rapid biosensor for viable B. Anthracis spores. Analytical and Bioanalytical Chemistry, 2004, 380(1), 15–23. 59. S. S. Iqbal, M. W. Mayo, J. G. Bruno, B. V. Bronk, C. A. Batt, and J. P. Chambers, A review of molecular recognition technologies for detection of biological threat agents. Biosensors and Bioelectronics, 2000, 15, 549–578.
60. T. T. Goodrich, H. J. Lee, and R. M. Corn, Direct detection of genomic DNA by enzymatically amplified SPR imaging measurements of RNA microarrays. Journal of the American Chemical Society, 2004, 126(13), 4086–4087. 61. A. C. Syvanen and H. Soderlund, DNA sandwiches with silver and gold. Nature Biotechnology, 2002, 20(4), 349–350. 62. N. A. Northrup, C. Gonzalez, D. Hadley, R. F. Hills, P. Landre, S. Lehew, R. Saw, and R. Watson, A MEMS-Based Miniature DNA Analysis System. In: Proceedings of the IEEE International Conference on SolidState Sensors and Actuators, Stockholm, Sweden, 1995, 764–767. 63. W. Mandecki, Three-Dimensional Arrays of Microtransponders Derivatized with Oligonucleotides, D&MD Library Series Publication, Southborough, 1999, pp. 179–187. 64. J. Korlach, M. Levene, S. W. Turner, H. G. Craighead, and W. W. Webb, Single molecule analysis of DNA polymerase activity using zero-mode waveguides. Biophysical Journal, 2002, 82(1), 507A. 65. R. Sosnowski, M. J. Heller, E. To, A. H. Forster, and R. Radtkey, Active microelectronic array system for DNA hybridization, genotyping and pharmacogenomic applications. Psychiatric Genetics, 2002, 12(4), 181–192. 66. R. H. Liu, T. Nguyen, K. Schwarzkopf, H. S. Fuji, A. Petrova, T. Siuda, K. Peyvan, M. Bizak, D. Danley, and A. McShea, Fully integrated miniature device for automated gene expression DNA microarray processing. Analytical Chemistry, 2006, 78(6), 1980–1986. 67. G. U. Lee, L. A. Chrisey, and R. J. Colton, Direct measurement of the forces between complementary strands of DNA. Science, 1994, 266(5186), 771–773. 68. J. Wang, From DNA biosensors to gene chips. Nucleic Acids Research, 2000, 28(16), 3011–3016. 69. T. Vo-Dinh, J. P. Alarie, N. Isola, D. Landis, A. L. Wintenberg, and M. N. Ericson, DNA biochip using a phototransistor integrated circuit. Analytical Chemistry, 1999, 71(2), 358–363. 70. J. B. Lamture, K. L. Beattie, B. E. Burke, M. D. Eggers, D. J. Ehrlich, R. Fowler, M. A. Hollis, B. B. Kosicki, R. K. Reich, S. R. Smith, R. S. Varma, and M. E. Hogan, Direct-detection of nucleic-acid hybridization on the surface of a charge-coupled-device. Nucleic Acids Research, 1994, 22(11), 2121–2125. 71. W. Cai, J. R. Peck, D. W. van der Weide, and R. J. Hamers, Direct electrical detection of hybridization at DNAmodified silicon surfaces. Biosensors and Bioelectronics, 2004, 19(9), 1013–1019. 72. J. Fritz, E. B. Cooper, S. Gaudet, P. K. Sorger, and S. R. Manalis, Electronic detection of DNA by its intrinsic molecular charge. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(22), 14142–14146. 73. E. Souteyrand, C. Chen, J. P. Cloarec, X. Nesme, P. Simonet, I. Navarro, and J. R. Martin, Comparison between electrochemical and optoelectrochemical impedance measurements for detection of DNA hybridization. Applied Biochemistry and Biotechnology, 2000, 89(2–3), 195–207.
GENETIC AND OTHER DNA-BASED BIOSENSOR APPLICATIONS 74. C. Guiducci, C. Stagni, G. Zuccheri, A. Bogliolo, L. Benini, B. Samori, and B. Ricco, DNA detection by integrable electronics. Biosensors and Bioelectronics, 2004, 19(8), 781–787. 75. M. Gheorghe and A. Guiseppi-Elie, Electrical frequency dependent characterization of DNA hybridization. Biosensors and Bioelectronics, 2003, 19(2), 95–102. 76. J. Jorritsma, M. A. M. Gijs, J. M. Kerkhof, and J. G. H. Stienen, General technique for fabricating large arrays of nanowires. Nanotechnology, 1996, 7(3), 263–265. 77. P. Van Gerwen, W. Laureyn, W. Laureys, G. Huyberechts, M. O. De Beeck, K. Baert, J. Suls, W. Sansen, P. Jacobs,
19
L. Hermans, and R. Mertens, Nanoscaled interdigitated electrode arrays for biochemical sensors. Sensors and Actuators B-Chemical, 1998, 49(1–2), 73–80.
FURTHER READING A. Rangel-Lopez, R. Maldonado-Rodriguez, M. SalcedoVargas, J. M. Espinosa-Lara, A. Mendez-Tenorio, and K. L. Beattie, Low density DNA microarray for detection of most frequent TP53 missense point mutations. BMC Biotechnology, 2005, 5.
67 Examples of Biosensors for the Measurement of Trace Medical Analytes Maria Minunni, Sara Tombelli, Sonia Centi and Marco Mascini Department of Chemistry, University of Florence, Florence, Italy
1 INTRODUCTION
Analyses in the clinical laboratory concern metabolites in human blood and urine in the millimolar concentration range. However, a better understanding of several diseases requires the measurements of different analytes, such as those reported in Table 1, in the micro- and submicromolar range. Steroids, drugs and their metabolites, hormones, and protein factors represent the molecular targets of many clinical analyses for elucidating several diseases. The concentration of these molecules is in the range 10−11 –10−6 mol l−1 . Conventional approaches are based mainly on immunochemical assays, coupled to enzymatic or fluorescent labels. These methods assure very high sensitivity and specificity and short analysis time (few hours). However, there is a need for label-free approaches, which should be more rapid (from many hours to minutes). An interesting approach for the detection of trace clinical analytes is based on affinity biosensors. The biological element in an affinity biosensor can be an antibody, a receptor (natural or synthetic), a nucleic acid or an aptamer. In all of these interactions, the binding between the target analyte and the immobilized biomolecule on the transduction element is governed by an affinity interaction like the antigen–antibody (Ag–Ab), the
DNA–DNA or the protein–nucleic acid binding. The specificity of the biosensor system is given by the immobilized molecule. Many examples related to the analysis of clinical relevant analytes by immunosensing have been reported in the last 20 years when this approach first started.1–4 The most relevant applications are related to the detection of hormones, drugs, and protein factors such as immunoglobulin and their subclass identification.5–9 More recently, in the last decade, DNA-based sensing has appeared for real applications to clinical diagnostics to detect the presence of pathogenic species responsible of infections, to identify genetic polymorphisms10,11 and to detect point mutations.12–14 In DNA-based sensors the affinity interaction is the hybridization reaction between the DNA probe immobilized on the transducer surface and the complementary sequence in solution. This reaction is fast and specific. The specificity relies on the probe sequence, which is chosen on the basis of the target sequence (analyte) when the DNAbased sensor is developed. When the hybridization reaction occurs, a complex consisting of double stranded DNA (dsDNA) is formed at the sensor surface. This complex can be revealed using different transduction principles. Some of them require labeling of reagents some others are label free. So far most of the reported samples consist in amplified DNA, mainly by polymerase chain
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Table 1. Concentrations of clinically relevant analytes
Concentration (mol l−1 ) 10−6 10−7 10−8 10−9 10−10 10−11
Drugs
Digoxin
Steroids, aminoacids
Proteins, polypeptides
Cortisol, estradiol
Placental lactogen
Corticosterone Progesterone
Antibodies Specific IgG Rubella
Prolactin, insulin, hCG hGH, luteinizing hormone TSH, oxytocin
Total IgE
hCG: human chorionic gonadotropin; hGH: human growth hormone; TSH: thyroid stimulating hormone.
reaction (PCR), although some attempts in detecting target sequences directly into genomic DNA are reported.15–19 Very recently a new category of relevant receptors, nucleic acid sequences selected in vitro named aptamers, has found an interesting application in the so-called aptasensors, which represent a most interesting and innovative emerging field in biosensor research. So far different aptamers have been selected20–33 and a list of analytes of clinical interest is reported in Table 2. All the mentioned affinity sensors have been coupled to a variety of transduction principles. In this chapter we report some examples of the work carried out over the last 10 years by our group, starting from the development of immunosensors for progesterone detection by electrochemical sensing. Then DNA-based sensing for point mutation detection in the β-globin gene, occurring in β-thalassemia, will be reported and Table 2. Selected protein-binding aptamers
Target Thrombin IgE NF-kB Lysozyme HIV-1 tat protein VEGF CD4 antigen HIV-1 gag protein L-selectin IRP HIV-1 rev protein PDGF TTF1 Acetylcholine receptor
Type of aptamer
References
DNA DNA RNA DNA RNA RNA RNA RNA DNA RNA RNA DNA DNA RNA
20 21 22 23 24 25 26 26 28 29 30 31 32 33
VEGF: vesicular endothelial growth factor; IRP: iron regulatory protein; PDGF: platelet-derived growth factor; TTF1: thyroid transcription factor.
finally aptasensing for thrombin detection will be discussed. The last two examples deal with piezoelectric and electrochemical sensing. Some considerations are important at this regard: when developing a biosensor for clinical diagnostics, a relevant aspect is the simplification of operation, and test strips are at present still superior.34 Their mass production allowed the development of very cheap devices, which are user friendly; the well-known glucose electrode is a typical example. Nowadays it is also possible to print many different working electrodes by screen printing technology allowing multianalyte detection in one measurement shot. However, the dilemma of a disposable or multiuse sensing is still open: savings provided by reusable sensors should not be exceeded by the expenses of necessary maintenance.34 The choice of the device to be used depends on the final user: test strips are mainly employed in home monitoring, in the doctors consulting room, and in small clinical laboratories, while reusable devices are better employed in clinical laboratories (as bench instruments) or in bed side instrumentation in hospitals. Here we choose to give examples of both approaches: disposable sensing using screenprinted electrodes (SPEs) while reusable sensors are based on piezoelectric sensing.
2 IMMUNOSENSORS FOR HORMONE DETECTION
The first reported application refers to the detection of progesterone by a disposable immunosensor, based on the use of screen-printed electrodes SPEs coupled to modern electrochemical techniques.
BIOSENSORS FOR MEASUREMENT OF TRACE MEDICAL ANALYTES
The measurement of this hormone is important in women life. Progesterone, a C21 steroid secreted by the corpus luteum, promotes the development of the endometrial lining. Serum levels of progesterone rise during the luteal phase of the menstrual cycle. If conception occurs, during pregnancy, levels increase from the end of the first trimester to term. Because progesterone is required for the continuation of pregnancy, low levels are associated with luteal phase defect, ectopic gestation, and miscarriage. The main role of such a hormone is to make the uterine mucosa able to accept the fertilized egg and during the pregnancy it is necessary for the placenta maintenance. In Table 3 the reference concentration range of progesterone in plasma is reported. Immunoassays are commonly used for the determination of progesterone in serum, urine, or Table 3. Progesterone levels
Progesterone (ng ml−1 )
Sex
Phase
Women
Follicular Luteal
0.1–1.5 3.8–28.0 <0.6
Men
Carbon screen–printed electrode IgG antisheep
Progesterone
saliva. Most of these were radioimmunoassays (RIAs), which involved the handling of radioactive materials.35 Given the inherent problems, different nonradioactive methods have been developed for measuring progesterone.36–39 Among the large number of possible immunoassay techniques, the enzyme-linked immunosorbent assays (ELISA) combined with a colorimetric measurement are the most widely used for measuring hormone concentrations.40–42 Another interesting approach is the use of immunosensors. Both electrochemical and optical biosensors have been reported, using screen printing technology coupled to cyclic voltammetry43,44 and chronoamperometry.45 For optical sensing surface plasmon resonance (SPR) has been used.46 SPEs have been used in immunosensor development for progesterone detection as a solid phase for the competitive immunoassay as described in Figure 1. An enzymatic label is used to estimate the extent of the affinity reaction and in this case alkaline phosphatase was used as label and 1-naphthyl phosphate as enzymatic substrate. The addition of the enzymatic substrate gives rise to the formation of an electroactive product (1-naphthol), which can be detected by an electrochemical
Sheep IgG anti–progesterone E Progesterone–enzyme conjugate
E E E
E
Substrate
E
Prod
3
Electrochemical measurement
Figure 1. Electrochemical immunosensor based on a competitive immunoassay scheme for progesterone detection.
BIOSENSOR APPLICATIONS
measurement using differential pulse voltammetry (DPV). In our approach IgG specific for sheep (10 µg ml−1 ) were bound to the carbon surface through passive adsorption, in order to favor the oriented immobilization of antibodies against progesterone from sheep. Using optimized parameters, a dose–response curve for progesterone was performed. The experiments were carried out incubating for 30 min the sensor surface modified by adsorption of antisheep IgG and then by immobilization of antiprogesterone IgG with competition solutions containing progesterone-AP and different concentrations of progesterone (in the range 0.01–100 ng ml−1 ). After a washing step, the enzymatic substrate was added to the sensor surface and after 5 min of incubation time the electrochemical measurement was performed. The calibration curve was obtained reporting the height of the peaks against the progesterone concentration and it is shown in Figure 2. A signal decrease was observed with the lowest current measured for 100 ng ml−1 concentration. The EC50 value (the analyte concentration necessary to displace 50% of the enzyme label) was calculated as 2 ng ml−1 , whereas the limit of detection (LOD), calculated by evaluation of the mean of the blank solution response (containing the tracer only) minus two times the standard deviation, was estimated as 32 pg ml−1 . The reproducibility of the assay, evaluated as average coefficient of variation (CV) on three measurements, was 10%. Nonspecific adsorption was evaluated comparing the signals measured in presence and in 10
10
Current (µA)
4
8 6 4 2
0
0.01
0.1
1
10
100
1000
Progesterone concentration (ng ml−1)
Figure 3. Comparison between the signals measured in presence () and in absence (•) of IgG antiprogesterone.
absence of antibody against progesterone. For this purpose, the experiments were carried out incubating the sensor surface modified by immobilization of antisheep rIgG with the competition solution containing progesterone-AP and different concentrations of progesterone (in the range 0.01–100 ng ml−1 ). Figure 3 indicates a residual signal due to nonspecific adsorption estimated as 40% lower than the specific binding. This system represents an interesting approach for the detection of this analyte in human specimens as well as in cow milk for application to food analysis and to detect metabolite levels in veterinary testing and animal husbandry.47 Nowadays different commercially available devices for electrochemical immunoassays are available with automated liquid handling, sample dispensing, and so on, which make these approaches competitive respect to traditional immunoassays.48,49
Current (µA)
8
3 DNA-BASED BIOSENSORS FOR GENETIC DISEASES INVESTIGATION
6
4
2 0
0.01
0.1
1
10
Progesterone concentration (ng ml−1)
Figure 2. Calibration curve for progesterone.
100
Nucleic acid–based biosensors represent a promising tool for gene sequence analysis and for mutation detection.50 In this case the immobilization of single-stranded oligonucleotides (probe) on the surface of the transducing element is necessary and the variations of the transducer signal caused by the hybridization between the probe and the complementary strand in solution (target) are recorded. In particular, these devices can be applied to the
BIOSENSORS FOR MEASUREMENT OF TRACE MEDICAL ANALYTES
3.1
Application to Point Mutations Detection: the Case of β-Thalassemia
A DNA piezoelectric biosensor has been developed for the determination of a mutation which is frequent in β-thalassemia syndromes in the Mediterranean area.65 The biosensor was used to detect the extent of the hybridization between the immobilized probe and PCR-amplified DNA samples extracted from human blood of healthy, β-thalassemia healthy carriers, and thalassemic patients. β-thalassemia is an autosomal recessive disease characterized by reduced or absent β-globin gene expression resulting from gene deletions or mutations that affect the transcription or stability of mRNA products.66 β-thalassemias are caused by mutations in and around the structural gene of the adult hemoglobin (HbA) β-chain. More than a hundred mutations have been characterized around the world. In the Mediterranean population, this disease is caused mainly by the nonsense C → T substitution at codon 39 (west Mediterranean area).67 The determination of codon 39 mutation by the use of a DNA piezoelectric biosensor, which is able to detect the hybridization reaction both using synthetic 25-mer oligonucleotides or real PCR-amplified DNA samples and to distinguish between sequences differing in only one base in both cases, has been proposed as an alternative method.
A probe internal to the codon 39 has been identified, carrying the base involved in the mutation in the center of the sequence (5 -biotin-CAA AGA ACC TCT GGG TCC AAG GGT A-3 ). Piezoelectric quartz crystals of 10 MHz with gold electrodes were modified with the probe using the strong affinity between biotin and streptavidin. The probe was biotinylated and streptavidin was previously immobilized following an optimized protocol.11 Experiments with complementary, noncomplementary and mismatched oligonucleotides (25-mer) were performed by using appropriate oligonucleotide solutions (100 µl). In Figure 4 the responses of fully complementary (100%), mismatch (100%), and a mixture of the two (50 + 50%) are compared. In the presence of the mismatch a decreased signal is always obtained (conc. >1 ppm), comparing the responses at the same concentration. The decrease in the sensor response in the case of mismatch is 30% when the oligonucleotides are tested at the same concentration. Also the solution of the two oligonucleotides together, mimicking the healthy carrier (50% complementary and 50% mismatch), could be distinguished by evaluating the frequency shift, which is about 15% lower than that obtained with the complementary strand. The reproducibility of the system is good (CV%av = 9%, calculated over three repeated measurements for each concentration on the same
−140 −120 Shift (Hz)
detection of point mutations: when the matching with the complementary target is complete the biosensor reports the maximum response, whereas a decrease in the signal is observed when a mismatch occurs. Several types of nucleic acid–based biosensors have been developed over recent years. In particular, piezoelectric biosensors offer the possibility of monitoring the hybridization reaction in real time and without the use of any label51–54 and they have been presented as alternatives to gel electrophoresis and to traditional methods of specific DNA sequences detection, where labeled probes are required. DNA piezoelectric biosensors have been already realized55–62 and applied with success to clinical analysis.11,53,63,64
5
−100 −80 −60 −40 −20 0 0
1
2
3
4
5
6
7
Concentration (ppm) Figure 4. Calibration curves obtained with probe 2 immobilized on the crystal. Concentration range: 1–6 ppm. Solutions prepared in hybridization buffer. Frequency recorded after 10 min of interaction with the probe. ( ) complementary; (- - - - ) 50% complementary +50% mismatch; ( . . . . ) mismatch.
6
BIOSENSOR APPLICATIONS
crystal). The reproducibility among different crystals (n = 10) is also evaluated resulting in an average CV% < 10%. It is important to note that the measurements obtained with a negative control (noncomplementary strand) did not result in a frequency shift, showing the high specificity of the system. For the analysis of real samples, DNA was extracted from peripheral blood of healthy, β-thalassemia healthy carrier and thalassemic patients. All the samples are tested with a standard method, which included DNA amplification by PCR using four 5 -biotinylated primers, amplifying two fragments of different length (771 and 577 bp). After PCR and purification, the 771 bases amplicons were denatured by heating at 95 ◦ C for 5 min followed by cooling in ice for 1 min and 100 µl of the solution was then added to the cell well. The hybridization reaction proceeds for 20 min, and then the crystal is washed with the hybridization buffer. In this application, all the samples were diluted to 0.15 µM in order to compare the results and to have a significant frequency shift. To evaluate the specificity of the system, not only the PCR blanks (PCR reagents without DNA template) are used, but two other samples
(negative controls) were also tested: PCR-amplified DNA extracted from plants (negative control) and PCR-amplified DNA extracted from β-thalassemia healthy carrier having a mutation in another region of DNA, not in codon 39 were chosen. In these samples the sequence of codon 39 corresponds to the one of healthy patients DNA. As reported in Figure 5, the biosensor is able to distinguish between samples from healthy (100% CAG), healthy carrier (50% CAG + 50% TAG) and thalassemic patients (100% TAG). Moreover, the system results are very specific as the negative control (PCR-amplified DNA from plants) resulted in a negligible signal and samples from β-thalassemia healthy carriers carrying a mutation in different region, shows the same behavior of samples from healthy patients. When real samples are employed it is possible to perform up to 10 measurements on the same crystal, regenerating between cycles with an acid treatment. The results demonstrated that piezoelectric biosensor could be successfully applied to the analysis of real clinical samples of DNA amplified by PCR for β-thalassemia detection. Rapid assignment of the samples to different genotype groups could be possible based on such a quick method.
−30
−25
Shift (Hz)
−20
−15
−10
−5
0 A
A
B
B
C
D
E
F
Figure 5. Results with purified real samples. All the samples are diluted to 80 ppm. Blanks consisted of PCR mixture without DNA template. The negative control corresponds to PCR-amplified DNA from plants. The mean value estimated over three replicate measurements. (A) Healthy patients; (B) healthy carrier patients; (C) β-thalassemic patients; (D) healthy carrier patients with mutation not in codon 39; (E) PCR blank; (F) negative control.
BIOSENSORS FOR MEASUREMENT OF TRACE MEDICAL ANALYTES
The detection principle has a wide range of applicability, since the specificity of the system relies on the particular choice of the probe. It could be applied to the detection of many diseases based on gene mutations and also to characterize different genotypes (i.e., polymorphism investigation). Biosensors were demonstrated to be a powerful tool for fast screening of clinical samples, providing fast and cheap responses. For these reasons they represent an interesting approach for a preliminary screening of samples, eventually further characterized by more expensive and time consuming, well established nonbiosensor approaches (e.g., real-time PCR).
4 APTAMER-BASED BIOSENSORS FOR PROTEINS DETECTION
Aptamers are nucleic acid ligands that have been designed through an in vitro selection process called SELEX (Systematic Evolution of Ligands by Exponential Enrichment).68,69 These DNA/RNA ligands have been selected to bind non-nucleic acid targets to which they bind through their particular structures and not via a hybridization reaction. The high affinity of aptamers for their targets is given by their capability of folding upon binding their target molecule: they can incorporate small molecules into their nucleic acid structure or integrate into the structure of larger molecules such as proteins. Because of the high diversity of molecular shapes of all possible nucleotide sequences, aptamers have been selected for a wide array of targets, including proteins, carbohydrates, lipids, or small molecules. Aptamers offer several advantages over antibodies as they can be completely engineered in vitro, produced and labeled by chemical synthesis, and possess good storage properties.70,71 In addition, aptamers receptors, due to their production by chemical synthesis, have a number of advantages that make them very promising in analytical applications. Aptamers have been recently used in analytical chemistry as immobilized ligands or in homogeneous assays.71 A very attractive application is the exploitation of aptamers as biorecognition elements in biosensors. The application of aptamers as biocomponents in biosensors offers classical affinity sensing
7
methods mainly based on antibodies, a multitude of advantages, such as the possibility of easy regeneration of the function of immobilized aptamers, their homogeneous preparation, and the possibility of using different detection methods due to easy labeling.70,71 Quartz crystals biosensors have been developed with aptamers immobilized on the sensing surface.72,73 Liss et al.72 compared the behavior of aptamers as receptor molecules with that of conventional antibodies. Regarding the application to trace level analytes the detection of IgE (Table 1) could represent an interesting example. Using an IgE-specific aptamer and an antiIgE antibody as model system, with a piezoelectric transduction, the aptasensor resulted in an increased stability with respect to the relative immunosensor (several weeks) and presented a more complete and reversible surface regeneration. The sensitivity of the two systems was comparable (minimum detectable IgE concentration, 100 µg l−1 ) but the one having the aptamer as recognition element presented an extended linear measurement range (up to 10 mg l−1 ). A similar comparison between an aptamer- and an antibodybased quartz crystal biosensor has been presented using HIV-1 Tat protein as target molecule.73 The developed piezoelectric aptasensor, proved to be specific, reproducible, and reusable in the detection of Tat protein. Both receptors, aptamer and antibody, detected Tat at a minimum concentration of 0.01 µM with a comparable reproducibility in terms of coefficient of variation (CV% = 6%). Aptamers have been used as biorecognition element in optical sensors, both labeled (fluorescencebased methods) or in systems not requiring labels (SPR). A fluorescence aptamer-based biosensor array has been developed using aptamers specific for several proteins with relevance to cancer, inosine monophosphate dehydrogenase (IMPDH), VEGF and basic fibroblast growth factor (bFGF).74 The array was proposed for multiplex analysis of proteins of clinical interest present at trace levels (ppt). The possible use of unlabeled aptamers in optical biosensors has been evidenced mainly in methods based on SPR. The SPR-based device Biacore (Biacore, Uppsala, Sweden) has been widely used to study the affinity of the selected
8
BIOSENSOR APPLICATIONS
aptamers for their target molecules, such as HIV-1 Rev protein,75 CD4 antigen26 and TTF1.32 A label free electrochemical method has been presented by Kawde et al.76 The detection of lysozyme at submicromolar levels has been achieved by combining the protein specific aptamer immobilized onto magnetic particles and the electrochemical measurement of the captured protein (oxidation of tyrosine and tryptophan residues). This reagent-less label-free detection cannot be accomplished with traditional immunoassays due to the presence of the electroactive residues both in the target protein and in the antibody. Also this method has been presented as an alternative technique for the development of protein biochips to be applied in clinical analysis.
4.1
also important to the overall process.78 Thrombin represents an interesting clinical target in trace level. The thrombin-binding aptamer (15-mer, 5 -GGTTGGTGTGGTTGG-3 ) has been the first DNA aptamer selected in vitro, specific for a protein without nucleic acid’s binding properties20 and it has been studied as an anticlotting therapeutic tool. This aptamer has been used as a model system, coupled to different transduction principles to demonstrate the wide applicability of aptamers as bioreceptors in biosensors.79–82 The thrombinbinding aptamer has been extensively investigated: its G-quartet structure has been established83,84 and the binding site has been studied and determined.85 We report here an example of an aptamer-based assay for the detection of thrombin directly into human plasma.86 The assay is based on electrochemical transduction coupled to magnetic particles, modified with the aptamer. With the addition of a second aptamer after the interaction of the analyte with the modified beads, similar to immunoassays, this approach can be thought as a sandwich method (Figure 6). The work aims to couple a simple target capturing step, by employing magnetic beads, to the high sensitivity requested for thrombin analysis, assured by the electrochemical detection with DPV on SPEs. A sandwich assay format is chosen following an approach similar to the one reported by Ikebukuro et al.81 who employed
Application to Thrombin Detection
Thrombin (factor IIa) is the last enzyme protease involved in the coagulation cascade and it converts fibrinogen to insoluble fibrin that forms the fibrin gel either in physiological conditions or in a pathological thrombus.77 The concentration of thrombin in blood can vary considerably: thrombin, not present in blood under normal conditions, can reach low micromolar concentrations during the coagulation process but low levels (low nanomolar) of thrombin generated early in hemostasis are
E
Streptavidin-coated magnetic bead
5´ Biotinylated aptamer
Thrombin
5´ Biotinylated secondary aptamer
Streptavidin–alkaline phosphatase conjugate E
S P
E
E
E Working electrode Magnetic bar
Figure 6. Scheme of the electrochemical sandwich assay coupled to magnetic beads.
BIOSENSORS FOR MEASUREMENT OF TRACE MEDICAL ANALYTES
12
Current (µA)
10 8 6 4 2 0
0.1 1 10 Log thrombin concentration (nM)
100
Figure 7. Electrochemical assay for thrombin coupled to magnetic beads: dose–response curve for thrombin.
12
9 Current (µA)
an electrochemical detection using a conventional gold electrode and limited to standard solutions of the analyte down to a concentration of 10 nM. In both approaches, two selected aptamers binding thrombin in two different, non-overlapping, sites are used. The protein captured by the first aptamer is detected after the addition of the second biotinylated aptamer and of streptavidin labeled with an enzyme (alkaline phosphatase). Detection of the product generated by the enzymatic reaction was achieved by DPV onto SPEs. This approach based on the use of two different aptamers overcomes some of the drawbacks related to the use of antibodies. Using this novel design, an electrochemical biosensor recognizing thrombin with high affinity, sensitivity, and specificity was obtained, opening the possibility of a real application to diagnostics or medical investigation. The optimized conditions resulted in an immobilized biotinylated aptamer, named primary aptamer, with a polyT tail to ensure a certain flexibility in the binding (1 µM 15-mer: 5 -biotinTT TTT TTT TTT TTT TTT TTT GGT TGG TGT GGT TGG-3 ) and a biotinylated 29-mer as secondary aptamer to be used in the sandwich (5 biotin-AGTCCGTGGTAGGGCAGGTTGG-GGT GACT-3 ) (0.1 µM, incubation time 15 ). A dose-response curve for thrombin is reported in Figure 7. The height of the peaks obtained by DPV measurements for different concentrations of thrombin increases with the increase of thrombin concentration showing a typical behavior of a sandwich assay. In the figure, the signals are reported as peak current against log of thrombin concentration. A signal increase was observed for thrombin concentrations greater than 0.1 nM and the highest current was measured at a protein concentration of 100 nM. The reproducibility, expressed as the average CV is 8% (n = 5 in the range 0–100 nM). The detection limit (DL) is 0.45 nM. Human serum albumin (HSA) at physiological concentration in human plasma (HSA 72 µM (5000 ppm)) was used to test the specificity of the aptamer, which was found to be very high since a negligible signal in presence of HSA or of the blank solution was observed. The applicability of the assay to plasma samples was evaluated by investigating the presence of any matrix effect. Plasma, after fibrinogen precipitation, diluted 10 times was tested alone or
9
6
3
0 0
10
50
100
Thrombin concentration (nm) Figure 8. Results obtained with serum samples spiked with thrombin (black histograms) and comparison with the same concentrations tested in buffer (white histograms) and in plasma after fibrinogen precipitation (gray histograms).
spiked with thrombin (in the concentration range 0–100 nM), and the results were compared with thrombin standard buffer solutions. Figure 8 shows that comparable responses were found for buffer, and plasma: addition of thrombin to the sample resulted in protein concentration-dependent signal. The samples were incubated with the beads (coated with primary aptamer) and then the assay was carried out by adding the secondary aptamer and the conjugate. For plasma a weak matrix effect was found considering the lower currents (average decrease ∼80%) measured with respect to buffer. Probably this decrease is due to a reduced concentration of thrombin available for
10
BIOSENSOR APPLICATIONS
the binding caused, by the interaction with some matrix components. These results demonstrate the applicability of aptamer-based assays to the detection of molecules of clinical interest present in trace level, directly into plasma samples. 5 CONCLUSIONS
The detection of clinical important molecules at micromolar or submicromolar concentration, employing different strategies in affinity sensing has been reported. The examples span from an electrochemical immunosensor for progesterone using disposable devices, to nucleic acid–based sensors, for the detection of point mutations, which are based on the hybridization reaction, revealed in real time by label free piezoelectric sensing. Finally, a new emerging category of receptors called aptamers have been introduced and discussed in the application to thrombin detection. Both single use and multiuse sensing have been shown to be suitable for trace analysis in clinical chemistry. Both approaches possess sensitivity, reproducibility, and analysis times compatible with the final application. However, while strips are widely commercialized and applied to the analysis of clinical analytes by nonskilled personnel, for piezoelectric sensing much less commercial investments and diffusion are seen at the moment. REFERENCES 1. P. B. Luppa, L. J. Sokoll, and D. W. Chan, Immunosensorprinciples and applications to clinical chemistry. Clinica Chimica Acta, 2001, 314, 1–26. 2. W. M. Mullett, E. P. C. Lai, and J. M. Yeung, Surface plasmon resonance-based immunoassays. Methods, 2000, 22, 77–91. 3. J. Lin and H. Ju, Electrochemical and chemiluminescent immunosensors for tumor markers. Biosensors and Bioelectronics, 2005, 20, 1461–1470. 4. D. Purvis, O. Leonardova, D. Farmakovsky, and V. Cherkasov, An ultrasensitive and stable potentiometric immunosensor. Biosensors and Bioelectronics, 2003, 18, 1385–1390. 5. B. Zhang, Q. Mao, X. Zhang, T. Jiang, M. Chen, F. Yu, and W. Fu, A novel piezoelectric quartz microarray immunosensor based on self-assembled monolayer for determination of human chorionic gonadotropin. Biosensors and Bioelectronics, 2004, 19, 711–720. 6. G. Lillie, P. Payne, and P. Vadgama, Electrochemical impedance spectroscopy as a platform for reagentless
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
bioaffinity sensing. Sensors and Actuators B: Chemical, 2001, 78, 249–256. B. S. Attili and A. A. Suleiman, A piezoelectric immunosensor for the detection of cocaine. Microchemical Journal, 1996, 54, 174–179. A. de la Escosura-Mu˜nz, M. B. Gonz´alez-Garc´ıa, and A. Costa-Garc´ıa, Aurothiomalate as an electroactive label for the determination of immunoglobulin M using glassy carbon electrodes as immunoassay transducers. Sensors and Actuators B: Chemical, 2006, 114, 473–481. X. Su, F. T. Chew, and S. F. Y. Li, Self-assembled monolayer-based piezoelectric crystal immunosensor for the quantification of total human IgE. Analytical Biochemistry, 1999, 273, 66–72. G. Marrazza, G. Chiti, M. Mascini, and M. Anichini, Detection of human apolipoprotein E genotypes by DNA electrochemical biosensor coupled with PCR. Clinical Chemistry, 2000, 46, 31–37. S. Tombelli, M. Mascini, L. Braccini, M. Anichini, and A. P. F. Turner, Coupling of a DNA piezoelectric biosensor and polymerase chain reaction to detect apolipoprotein E polymorphisms. Biosensors and Bioelectronics, 2000, 15, 363–370. D. Dell’Atti, S. Tombelli, M. Minunni, and M. Mascini, Detection of clinically relevant point mutations by a novel piezoelectric biosensor. Biosensors and Bioelectronics, 2006, 21, 1876–1879. T. Jiang, M. Minunni, P. Wilson, J. Zhang, A. P. F. Turner, and M. Mascini, Detection of TP53 mutation using a portable surface plasmon resonance DNA-based biosensor. Biosensors and Bioelectronics, 2005, 20, 1939–1945. F. Patolsky, A. Lichtenstein, and I. Willner, Electronic transduction of DNA sensing processes on surfaces: amplification of DNA detection and analysis of single-base mismatches by tagged liposomes. Journal of the American Chemical Society, 2001, 123, 5194–5205. M. Minunni, S. Tombelli, J. Fonti, M. M. Spiriti, and M. Mascini, Detection of genomic DNA by PCRfree piezoelectric sensing. Journal of American Chemical Society, 2005, 127, 7966–7967. A. Almadidy, J. Watterson, P. A. E. Piunno, S. Raha, I. V. Foulds, P. A. Horgen, A. Castle, and U. Krull, Direct selective detection of genomic DNA from coliform using a fibre optic biosensor. Analytica Chimica Acta, 2002, 461, 37–41. T. T. Goodrich, H. J. Lee, and R. Corn, Direct detection of genomic DNA by enzymatically amplified SPR imaging measurements of RNA microarrays. Journal of the American Chemical Society, 2004, 126, 4086–4087. F. Patolsky, A. Lichtenstein, M. Kotler, and I. Willner, Electronic transduction of polymerase or reverse transcriptase induced replication processes on surfaces: highly sensitive and specific detection of viral genomes. Angewandte Chemie International Edition, 2001, 40, 2261–2265. R. B. Towery, N. C. Fawcett, P. Zhang, and J. A. Evans, Genomic DNA hybridizes with the same rate constant on the QCM biosensor as in homogeneous solution. Biosensors and Bioelectronics, 2001, 16, 1–8. L. C. Bock, L. C. Griffin, J. A. Latham, E. H. Vermaas, and J. J. Toole, Selection of single-stranded DNA molecules that bind and inhibit human thrombin. Nature, 1992, 355, 564–566.
BIOSENSORS FOR MEASUREMENT OF TRACE MEDICAL ANALYTES 21. T. W. Wiegand, P. B. Williams, S. C. Dreskin, M. H. Jouvin, J. P. Kinet, and D. Tasset, High-affinity oligonucleotide ligands to human IgE inhibit binding to Fc epsilon receptor I. Journal of Immunology, 1996, 157, 221–230. 22. L. L. Lebruska and L. L. Mather, Selection and characterization of an RNA decoy for transcription factor NFkappa B. Biochemistry, 1999, 38, 3168–3174. 23. J. C. Cox and A. D. Ellington, Automated selection of antiprotein aptamers. Bioorganic and Medicinal Chemistry, 2001, 9, 2525–2531. 24. R. Yamamoto, M. Katahira, S. Nishikawa, T. Baba, K. Taira, and P. K. R. Kumar, A novel RNA motif that binds efficiently and specifically to the Tat protein of HIV and inhibits the trans-activation by Tat of transcription in vitro and in vivo. Genes to Cells, 2000, 5, 371–388. 25. D. W. Drolet, L. Moon-Mcdermott, and T. S. Romig, An enzyme-linked oligonucleotide assay. Nature Biotechnology, 1996, 14, 1021–1025. 26. E. Kraus, W. James, and A. N. Barclay, Novel RNA ligands able to bind CD4 antigen and inhibit CD4+ T lymphocyte function. Journal of Immunology, 1998, 160, 5209–5212. 27. M. A. Lochrie, S. Waugh, D. G. Pratt, J. Clever, T. G. Parslow, and B. Polisky, In vitro selection of RNAs that bind to the human immunodeficiency virus type-1 gag polyprotein. Nucleic Acids Research, 1997, 25, 2902–2910. 28. B. J. Hicke, S. R. Watson, A. Koenig, C. K. Lynott, R. F. Bargatze, and Y. F. Chang, DNA aptamers block L-selectin function in vivo. The Journal of Clinical Investigation, 1996, 98, 2688–2692. 29. F. Lisdat, D. Utepbergenov, R. F. Haseloff, I. E. Blasig, W. Stocklein, F. W. Scheller, and R. Brigelius-Flohe, An optical method for the detection of oxidative stress using protein-RNA interaction. Analytical Chemistry, 2001, 73, 957–962. 30. W. Xu and A. D. Ellington, Anti-peptide aptamers recognize amino acid sequence and bind a protein epitope. Proceedings of the National Academy of Sciences of the United States of America, 1997, 94, 7475–7480. 31. X. Fang, Z. Cao, T. Beck, and W. Tan, Molecular aptamer for real-time oncoprotein PDGF monitoring by fluorescence anisotropy. Analytical Chemistry, 2001, 73, 5752–5757. 32. M. B. Murphy, S. T. Fuller, P. M. Richardson, and S. A. Doyle, An improved method for the in vitro evolution of aptamers and applications in protein detection and purification. Nucleic Acids Research, 2003, 31, e110–e118. 33. H. Ulrich, J. E. Ippolito, O. R. Pagan, V. A. Eterovic, R. M. Hann, H. Shi, J. T. Lis, M. E. Eldefrawi, and G. P. Hess, In vitro selection of RNA molecules that displace cocaine from the membrane-bound nicotinic receptor. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95, 14051–14056. 34. F. Sheller and F. Schubert, Biosensors, Technique and Instrumentation in Analytical Chemistry Series, Elsevier, 1992, pp. 291–322. 35. J. Reinsberg, E. Jost, and H. Van Der Ven, Performance of the fully automated progesterone assays on the Abbott. Clinical Biochemistry, 1997, 30, 469–471.
11
36. S. A. Miller, M. S. Morton, and A. Turkes, Chemiluminescence immunoassay for progesterone in plasma incorporating acridinium ester labelled antigen. Annals of Clinical Biochemistry, 1988, 25, 27–34. 37. S. E. Kakabakos and M. J. Khosravi, Direct timeresolved fluorescence immunoassay of progesterone in serum involving the biotin-streptavidin system and the immobilized-antibody approach. Clinical Chemistry, 1992, 38, 725–730. 38. M. J. Choi, J. Choi, D. Y. Yoon, J. Park, and S. A. Eremin, Fluorescence polarization immunoassay of progesterone. Biological and Pharmaceutical Bulletin, 1997, 20, 309–314. 39. J. Y. Hong and M. J. Choi, Development of one-step fluorescence polarization immunoassay for progesterone. Biological and Pharmaceutical Bulletin, 2002, 25, 1258–1262. 40. A. Basu, T. G. Shrivastav, and S. K. Maitra, A direct antigen heterologous enzyme immunoassay for measuring progesterone in serum without using displacer. Steroids, 2006, 71, 222–230. 41. L. A. Singer, M. S. A. Kumar, W. Gavin, and S. L. Ayres, Determining the onset of parturition in the goat using CITE progesterone tests. Small Ruminant Research, 2004, 52, 203–209. 42. R. W. Claycomb, M. J. Delwiche, C. J. Munro, and R. H. BonDurant, Rapid enzyme immunoassay for measurement of bovine progesterone. Biosensors and Bioelectronics, 1998, 13, 1165–1171. 43. Y. F. Xu, M. Velasco-Garcia, and T. T. Mottram, Quantitative analysis of the response of an electrochemical biosensor for progesterone in milk. Biosensors and Bioelectronics, 2005, 20, 2061–2070. 44. R. M. Pemberton, J. P. Hart, P. Stoddard, and J. A. Foulkes, A comparison of 1-naphthyl phosphate and 4 aminophenyl phosphate as enzyme substrates for use with a screen-printed amperometric immunosensor for progesterone in cows’ milk. Biosensors and Bioelectronics, 1999, 14, 495–503. 45. J. P. Hart, R. M. Pemberton, R. Luxton, and R. Wedge, Studies towards a disposable screen-printed amperometric biosensor for progesterone. Biosensors and Bioelectronics, 1997, 12, 1113–1121. 46. E. H. Gillis, J. P. Gosling, J. M. Sreenan, and M. Kane, Development and validation of a biosensorbased immunoassay for progesterone in bovine milk. Journal of Immunological Methods, 2002, 267, 131–138. 47. M. N. Velasco-Garcia and T. Mottram, Biosensors in the livestock industry: an automated ovulation prediction system for dairy cows. Trends in Biotechnology, 2001, 19, 433–434. 48. Web Page: http://www.alderonbiosciences.com/. 49. Web Page: http://www.diagnoswiss.com., 2006. 50. C. N. Jayarajah and M. Thompson, Signaling of transcriptional chemistry in the on-line detection format. Biosensors and Bioelectronics, 2002, 17, 159–171. 51. S. Tombelli, M. Mascini, C. Sacco, and A. P. F. Turner, A DNA piezoelectric biosensor assay coupled with a polymerase chain reaction for bacterial toxicity determination in environmental samples. Analytica Chimica Acta, 2000, 418, 1–9.
12
BIOSENSOR APPLICATIONS
52. L. M. Furtado and M. Thompson, Hybridization of complementary strand and single-base mutated oligonucleotides detected with an on-line acoustic wave sensor. Analyst, 1998, 123, 1937–1945. 53. X. C. Zhou, L. Q. Huang, and S. F. Y. Li, Microgravimetric DNA sensor based on quartz crystal microbalance: comparison of oligonucleotide immobilization methods and the application in genetic diagnosis. Biosensors and Bioelectronics, 2001, 16, 85–95. 54. A. K. Deisingh and M. Thompson, Sequences of E. coli 0157:H7 detected by a PCR-acoustic wave sensor combination. Analyst, 2001, 126, 2153–2158. 55. S. Yamaguchi, T. Shimomura, T. Tatsuma, and N. Oyama, Adsorption, immobilization, and hybridization of DNA studied by the use of quartz crystal oscillators. Analytical Chemistry, 1993, 65, 1925–1927. 56. H. Su and M. Thompson, Rheological and interfacial properties of nucleic acid films studied by thickness—shear mode sensor and network analysis. Canadian Journal of Chemistry, 1996, 74, 344–358. 57. F. Caruso, E. Rodda, D. Furlong, K. Niikura, and Y. Okahata, Quartz crystal microbalance study of DNA immobilization and hybridization for nucleic acid sensor development. Analytical Chemistry, 1997, 69, 2043–2049. 58. I. Mannelli, M. Minunni, S. Tombelli, and M. Mascini, Quartz crystal microbalance (QCM) affinity biosensor for genetically modified organisms (GMOs) detection. Biosensors and Bioelectronics, 2003, 18, 129–140. 59. Y. Okahata, M. Kawase, K. Nukura, F. Ohtake, H. Furusawa, and Y. Ebara, Kinetic measurements of DNA hybridisation on an oligonucleotide-immobilised 27-MHz quartz crystal microbalance. Analytical Chemistry, 1998, 70, 1288–1296. 60. H. Sun, Y. Zhang, and Y. Fung, Flow analysis coupled with PQC/DNA biosensor for assay of E. coli based on detecting DNA products from PCR amplification. Biosensors and Bioelectronics, 2006, 22, 506–512. 61. F. He and S. Liu, Detection of P. aeruginosa using nano-structured electrode-separated piezoelectric DNA biosensor. Talanta, 2004, 62, 271–277. 62. M. Minunni, I. Mannelli, M. M. Spiriti, S. Tombelli, and M. Mascini, Detection of highly repeated sequences in non-amplified genomic DNA by bulk acoustic wave (BAW) affinity biosensor. Analytica Chimica Acta, 2004, 526, 19–25. 63. X. Zhou, L. Liu, M. Hu, L. Wang, and J. Hu, Detection of hepatitis B virus by piezoelectric biosensor. Journal of Pharmaceutical and Biomedical Analysis, 2002, 27, 341–345. 64. C. K. O’Sullivan and G. G. Guilbault, Commercial quartz crystal microbalances—theory and applications. Biosensors and Bioelectronics, 1999, 14, 663–670. 65. M. Minunni, S. Tombelli, R. Scielzi, I. Mannelli, M. Mascini, and C. Gaudiano, Detection of β-thalassemia by a DNA piezoelectric biosensor coupled with polymerase chain reaction. Analytica Chimica Acta, 2003, 48, 55–64. 66. S. R. Chern and C. P. Chen, Molecular prenatal diagnosis of thalassemia in Taiwan. International Journal of Gynecology and Obstetrics, 2000, 69, 103–106. 67. L. Rigoli, A. Meo, M. R. Miceli, K. Alessio, R. A. Caruso, M. A. La Rosa, D. C. Salpietro, M. Ricca, and I. Barberi,
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
Molecular analysis of β-thalassaemia patients in a high incidence area of southern Italy. Clinical and Laboratory Haematology, 2001, 23, 373–378. A. D. Ellington and J. W. Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature, 1990, 346, 818–822. C. Tuerk and L. Gold, Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science, 1990, 249, 505–510. C. K. O’Sullivan, Aptasensors-the future of biosensing. Analytical and Bioanalytical Chemistry, 2002, 372, 44–48. S. Tombelli, M. Minunni, and M. Mascini, Analytical applications of aptamers. Biosensors and Bioelectronics, 2005, 20, 2424–2434. M. Liss, B. Petersen, H. Wolf, and E. Prohaska, An aptamer-based quartz crystal protein biosensor. Analytical Chemistry, 2002, 74, 4488–4495. M. Minunni, S. Tombelli, A. Gullotto, E. Luzi, and M. Mascini, Development of biosensors with aptamers as bio-recognition element: the case of HIV-1 Tat protein. Biosensors and Bioelectronics, 2004, 20, 1149–1156. T. G. McCauley, N. Hamaguchi, and M. Stanton, Aptamerbased biosensor arrays detection and quantification of biological macromolecules. Analytical Biochemistry, 2003, 319, 244–250. D. I. Van Ryk and S. Venkatesan, Real-time kinetics of HIV-1 rev-rev response element interactions. Journal of Biological Chemistry, 1999, 274, 17452–17463. A. Kawde, M. C. Rodriguez, T. M. H. Lee, and J. Wang, Label-free bioelectronic detection of aptamerprotein interactions. Electrochemistry Communications, 2005, 7, 537–540. C. A. Holland, A. T. Henry, H. C. Whinna, and F. C. Church, Effect of oligodeoxynucleotide thrombin aptamer on thrombin inhibition by heparin cofactor II and antithrombin. FEBS Letters, 2000, 484, 87–91. M. A. Shuman and P. W. Majerus, The measurement of thrombin in clotting blood by radioimmunoassay. The Journal of Clinical Investigation, 1976, 58, 1249–1258. E. Baldrich, A. Restrepo, and C. K. O’Sullivan, Aptasensor development: elucidation of critical parameters for optimal aptamer performance. Analytical Chemistry, 2004, 76, 7053–7063. T. Hianik, V. Ostatn´a, Z. Zajacov´a, E. Stoikova, and G. Evtugyn, Detection of aptamer-protein interactions using QCM and electrochemical indicator methods. Bioorganic and Medicinal Chemistry Letters, 2005, 15, 291–295. K. Ikebukuro, C. Kiyohara, and K. Sode, Electrochemical sensing of protein using two aptamers in sandwich manner. Biosensors and Bioelectronics, 2005, 20, 2168–2172. T. M. A. Gronewold, S. Glass, E. Quandt, and M. Famulok, Monitoring complex formation in the blood-coagulation cascade using aptamer-coated SAW sensors. Biosensors and Bioelectronics, 2005, 20, 2044–2052. R. F. Macaya, P. Schultze, F. W. Smith, J. A. Roe, and J. Feigon, Thrombin-binding DNA aptamer
BIOSENSORS FOR MEASUREMENT OF TRACE MEDICAL ANALYTES forms a unimolecular quadruplex structure in solution. Proceedings of the National Academy of Sciences, 1993, 90, 3745–3749. 84. I. Smirnov and R. H. Shafer, Effect of loop sequence and size on DNA aptamer stability. Biochemistry, 2000, 39, 1462–1468.
13
85. L. R. Paborsky, S. N. McCurdy, L. C. Griffin, J. J. Toole, and L. L. Leung, The single-stranded DNA aptamerbinding site of human thrombin. Journal of Biological Chemistry, 1993, 268, 20808–20811. 86. S. Centi, S. Tombelli, M. Minunni, and M. Mascini, Analytical Chemistry, 2007, 79, 1466–1473.
68 Biosensors for Monitoring Metabolites in Clinical Medicine John C. Pickup Metabolic Unit, King’s College London School of Medicine, London, UK
1 INTRODUCTION
Metabolites are relatively small molecular weight intermediates or products of metabolic reactions. They are measured in clinical medicine for several reasons including their use as biomarkers of disease presence and severity (e.g., glucose in diabetes), as an index of organ or tissue functioning (e.g., urea and creatinine in renal function tests), or as risk factors for the future development of disease (e.g., cholesterol and atherosclerosis). Until the last few decades, measurements in clinical chemistry have been centered on large central laboratories in hospitals and the discrete analysis of samples, usually blood or urine. However, the emergence of biosensor technology in recent years, particularly in the form of miniature probe-type devices, has provided the clinician and patient with three new and valuable capabilities: near-patient testing at the bedside, in the doctor’s office, or in the home and workplace; the possibility of also monitoring analyte concentrations in the body itself (in vivo) rather than in samples of fluid extracted from the body; and the ability to sense analyte fluctuations continuously or nearcontinuously throughout the day.1 The most important metabolite for sensing, both clinically and commercially, is undoubtedly glucose in the context of diabetes, which is reviewed
elsewhere in this volume. Here, I discuss a number of other clinically important analytes where biosensing technologies are increasingly playing a role.
2 MONITORING RENAL FUNCTION: UREA AND CREATININE
Since the ammonia produced by oxidative deamination is toxic to the body, ammonia is formed into urea in the liver and excreted by the kidney; creatinine is the breakdown product of creatine phosphate in muscle. Serum concentrations of urea and creatinine are routinely used as measures of glomerular function in the kidney. If the glomerular filtration rate (GFR) falls because of kidney disease or restriction of the blood supply to the kidney, waste products of metabolism like urea and creatinine are retained in the blood. A further clinical use is the on-line or intermittent assessment of the adequacy of renal dialysis by measuring urea or creatinine in the dialysate fluid.2–4 The reference range for urea is about 2.5–8.0 mM but levels can reach 50 mM in serious renal disease. Creatinine levels are normally about 40–130 µM but begin to increase when the GFR has fallen to half its normal value, reaching several hundred micromolar in serious kidney disease. Generally, creatinine is preferred over urea
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
as a measure of renal function because it is less affected by short-term dietary changes. Urea biosensors are based on immobilized urease, which catalyzes the hydrolysis of urea to ammonia and carbon dioxide: Urease
Urea + H2 O −−−−→ 2NH3 + CO2 Numerous urea sensors have been described where the products of this reaction are detected electrochemically or optically.1 Ammonia is hydrolyzed to NH4 + , which can be sensed potentiometrically by a change in pH at an H+ ion–selective electrode or by detecting NH4 + at an ammonium ion–selective electrode incorporating an ionophore such as nonactin.5 Miniaturized sensors can be manufactured using ion-selective field-effect transistors (ISFETs) with the enzyme immobilized at the gate.6 However, a significant problem with NH4 -sensitive electrodes is interference by Na+ and K+ ions due to the limited selectivity of the ionophore. For example, in a disposable biosensor for urea there was excellent agreement between sensor-determined urea and a reference method in blood from healthy subjects, but with samples from the renal laboratory with expected electrolyte disturbances there was significant error.5 Alternatively, the sensor can be based on measuring the charged products at a conductivity electrode. Here, an alternating potential is applied between two electrodes and the increase in ionic strength in the solution mediates an increase in current between the electrodes. This technology has been used for continuous monitoring of urea in the dialysate fluid when patients are undergoing hemodialysis. The dialysate is allowed to flow through an enzyme column of immobilized urease on porous glass2 or acrylic beads3 and then to a conductivity electrode. A recently described optical urea sensor uses pH-sensitive transducer reflection holograms manufactured by embedding interference fringe patterns comprising layers of ultrafine silver grains within thin polymer hydrogel films.7 When acidic or basic monomers are incorporated within the polymer, pH changes induce ionization and cause the grating to swell, increasing fringe separation and thus changing the diffraction wavelength, and therefore the color. Urease was immobilized within the polymer film and the initial rate of
change in diffraction wavelength increased nonlinearly, with saturation above 50 mM. The first biosensor for creatinine, a potentiometric enzyme electrode, was described by Meyerhoff and Rechnitz in 1976.8 Of the many creatinine sensors subsequently reported,9 the most common technology has been an amperometric threeenzyme system consisting of immobilized creatinine amidohydrolase, creatine amidohydrolase, and sarcosine oxidase, which sequentially converts creatinine to creatine, sarcosine, and thence to hydrogen peroxide, glycine, and formaldehyde: Creatinine amidohydrolase
Creatinine + H2 O −−−−−−−−−−−−−−−−−−−→ Creatine Creatine amidohydrolase
Creatine + H2 O −−−−−−−−−−−−−−−−−−→ Sarcosine + Urea Sarcosine + H2 O + O2
Sarcosine oxidase −−−−−−−−−−−−−→
Glycine
+ Formaldehyde + H2 O2 The final reaction has usually been monitored by electrochemical detection of H2 O2 , though measurement of O2 consumption is also possible. Endogenous creatine is a potential interferent. Potentiometric creatinine biosensors are generally based on the immobilization of creatinine iminohydrolase (deiminase) at the surface of an NH4 + -sensitive ion-selective electrode:9,10 Creatinine iminohydrolase
Creatinine + H2 O −−−−−−−−−−−−−−−−−−−→ N -Methylhydantoin + NH+ 4 + OH− Although such systems are simpler than the three-enzyme amperometric creatinine sensors and avoid interference from creatine, there can be interference from NH4 + in blood and urine. A recently described optical system known as intelligent polymerized crystalline colloidal array (IPCCA) technology, somewhat reminiscent of the hologram sensor for urea described in the preceding text, has been adapted for creatinine sensing.11 Here, an array of colloidal polystyrene latex particles that diffract light was embedded in a pH-responsive polyacrylamide hydrogel, forming
BIOSENSORS FOR MONITORING METABOLITES IN CLINICAL MEDICINE
a “photonic crystal”, and also containing creatinine deiminase. Metabolism of creatinine and release of OH− swells the gel and red shifts the diffraction according to the creatinine concentration.
3 MONITORING TISSUE OXYGENATION: LACTIC ACID
Lactate monitoring is important in critical care12 and sports medicine.13 Lactic acidosis is usually seen in medicine in seriously ill patients as a result of systemic hypoperfusion and/or tissue hypoxia, for example, cardiogenic, septic, or hypovolemic shock, severe anemia, and severe asthma. Lactic acidosis is less commonly associated with a number of illnesses where there is no obvious evidence of tissue hypoxia, such as liver disease, malignancy, and drug and toxin exposure. The clinical importance of this analyte can be seen, for example, from the fact that the initial arterial lactate concentration in patients in intensive care units correlates negatively with the probability of survival.12 Blood lactate accumulation is also a predictor of exercise performance13 and lower lactate accumulation per unit of work reflects a higher training status.14 Numerous discrete lactate biosensors have been described, and several commercial analyzers are available. A widely used example is the amperometric enzyme electrode incorporated in the Yellow Springs Instruments (YSI) device, which is based on lactate oxidase and a technology identical to the YSI glucose analyzer (save for the use of glucose oxidase in the latter), that is, oxidation of lactate producing pyruvate and hydrogen peroxide, which can be detected electrochemically by the positively charged base electrode: Lactate + O2
Lactate oxidase −−−−−−−−−−−→
Pyruvate + H2 O2
H2 O2 −−−→ 2H+ + O2 + 2e− In this instrument, lactate oxidase is immobilized between an outer polycarbonate membrane controlling lactate diffusion and an inner cellulose acetate membrane, which restricts interfering electroactive substances, though a dilution step is also used. Modifications to the lactate oxidase technology that have been used to minimize interfering species in unprocessed blood samples that might
3
be oxidized at the high potential required to detect H2 O2 and/or render the device less dependent on oxygen levels include lowering the required electrode overpotential by its modification with Prussian blue15 and “wiring” the enzyme to the electrode via an osmium-based redox polymer, so that electrons flow directly from the enzyme’s prosthetic group, FADH2 , to the electrode, rather than to oxygen.16 The alternative enzyme, lactate dehydrogenase, has been less used in lactate sensors because of the need to co-immobilize the cofactor NAD: L-lactate
+ NAD+
Lactate dehydrogenase −−−−−−−−−−−−−−−−→
Pyruvate + NADH + H+ One example is an optical lactate sensor where lactate dehydrogenase and its cofactor were encapsulated in a silica solgel and generated NADH, measured by its fluorescence at 460 nm or its absorbance.17 Nevertheless, there was some leaching of the enzyme and cofactor from the matrix. Lactate dehydrogenase has also been employed in a sensor described by D’Auria et al.,18 but here the dye 8-anilino-1-naphthalene was noncovalently bound to the enzyme as a reporter, displaying a 40% decrease in fluorescence emission on binding to lactate. Moving away from enzymes and naturally occurring protein receptors, Looger et al.19 have recently used a computer-based method to change the binding specificities of bacterial periplasmic proteins, leading to “virtually designed” receptors, including one for lactate. After mutating the wildtype gene as specified in the program, protein designs were expressed, modified with fluorescent dyes conjugated to cysteine residues introduced by mutation, and shown by change in fluorescence with binding of lactate. Continuous (as opposed to discrete) lactate sensing is receiving increasing attention, and it is probably second only to glucose as an analyte that favors such a monitoring strategy. Technologies include continuous blood sampling via a heparinized double-lumen cannula and flow through a chamber containing an amperometric lactate oxidase–based electrode.20 Several microdialysisbased continuous lactate sensors have been described; in a recent example,21 the GlucoDay (Menarini) continuous in vivo glucose analyzer
4
BIOSENSOR APPLICATIONS
was modified with a sensor employing immobilized lactate oxidase and microdialysis probes implanted subcutaneously in rabbits and a human volunteer. A twisted-wire dual glucose and lactate sensor has also been evaluated for continuous sensing of these analytes, implanted in the subcutaneous tissue of in rats, and has promise for human in vivo monitoring.22
4 MONITORING NUCLEIC ACID METABOLISM: URIC ACID
Uric acid is primarily the end product of purine metabolism, that is, the nucleic acids adenine and guanine. Because urate is relatively insoluble, elevated levels can cause precipitation, for example in the urinary tract as stones and in the joints as gout. Causes of hyperuricemia include reduced excretion by the kidney and increased nucleic acid turnover, for example, in malignancy. Enzyme electrodes for urate are based on uricase: Urate + 2H2 O + O2
Uricase −−−−→
Allantoin
+ H2 O2 + CO2 Although early urate sensors detected O2 consumption in the preceding reaction, more typically the H2 O2 produced is monitored, an example being a device with uricase cross-linked to albumin, with an organosilane-treated polycarbonate outer membrane to extend the linear range and diminish biofouling, and an inner cellulose acetate membrane to exclude electroactive interferents.23 Fluorescence-based urate detection has some advantages in that it is extremely sensitive and can be done in highly dilute samples, thus reducing the risk of interference. A system has been described24 incorporating uricase and peroxidase coencapsulated in solgel, with (initially nonfluorescent) amplex red detection of produced H2 O2 :
Hydrogen peroxide production by oxidase enzymes such as uricase can also be monitored by an electrochemiluminescent method, where luminol is oxidized at an electrode surface such as glassy carbon which catalyzes its chemiluminescence when reacting with H2 O2 .25 This methodology is extremely sensitive and may offer some advantages for operating in complex solutions such as blood without interference. 5 MONITORING LIPID METABOLISM: CHOLESTEROL, TRIGLYCERIDE, AND KETONES
Lipid and lipoprotein disorders are some of the commonest metabolic diseases. Cholesterol, particularly the low-density lipoprotein (LDL) cholesterol subfraction, is the best established risk factor for the development of atherosclerosis. Cholesterol levels can be elevated because of primary genetic disorders (e.g., familial hypercholesterolemia), or secondary to some other condition such as kidney disease, or most commonly because of a combination of many genes producing a tendency to elevated cholesterol in the presence of environmental influences such as diet. Lowered concentrations of high-density lipoprotein (HDL) cholesterol are also related to arterial disease. Triglyceride and its carrier lipoprotein, very low density lipoprotein (VLDL), are typically elevated in type 2 diabetes in association with low HDL, a combination known as dyslipidemia and associated with increased cardiovascular risk. Hypertriglyceridemia also occurs in some primary genetic defects such as lipoprotein lipase deficiency; triglyceride excess is associated with pancreatitis. Cholesterol biosensors frequently make use of the enzyme cholesterol oxidase, measuring oxygen consumption at an oxygen electrode or amperometric H2 O2 production:26,27 Cholesterol + O2
Cholesterol oxidase −−−−−−−−−−−−−−→
δ4-Cholestenone-3 + H2 O2 Uric acid +
Uricase O2 −−−−→
H2 O2 + Amplex red
Allantoin + H2 O2
Horseradish peroxidase −−−−−−−−−−−−−−−−−→
Resorofin (highly fluorescent)
This reaction has been adapted to fiber-optic technology for free cholesterol sensing by monitoring oxygen consumption via the fluorescence of a dye such as decacyclene that is quenched
BIOSENSORS FOR MONITORING METABOLITES IN CLINICAL MEDICINE
by molecular oxygen.28 Since about 70% of the serum cholesterol is esterified with fatty acids, it is necessary to co-immobilize cholesterol oxidase with cholesterol esterase for blood total cholesterol detection:29 Cholesterol ester + H2 O −−−→ Cholesterol + Fatty acid An alternative optical approach to H2 O2 production is the color development of an added dye in the presence of peroxidase29 (therefore, not strictly a biosensor). Cholesterol is one of the analytes that have been successfully detected by biosensors employing the relatively new electrode material of carbon nanotubes, which promote electron transfer and sensitivity and decrease the overvoltage for H2 O2 detection, for example, a screen-printed device where carbon paste is modified with nanotubules.30 An alternative enzyme for cholesterol biosensors is the mono-oxygenase cytochrome P450scc which catalyzes cholesterol side chain cleavage: Cholesterol + O2
Cytochrome P450scc −−−−−−−−−−−−−−−→
Pregnenolone
+ Isocaproic acid aldehyde Riboflavin can be used as an electrochemical mediator to transfer electrons from an electrode to the enzyme, reducing the cytochrome heme iron.31 Triglyceride sensing has received comparatively little attention, perhaps because its clinical value is less certain than that of cholesterol. One example uses the enzyme lipase immobilized on oxidized porous silicon, the spongelike matrix of which has a large surface area and great absorptive properties:32 Lipase
Triglyceride −−−−→ Glycerol + Fatty acids The resultant change in pH is the basis of a potentiometric measurement of triglyceride. Ketones form in the body as the result of the breakdown of fats under conditions of insulin deficiency, such as in undiagnosed or uncontrolled type 1 diabetes. The three ketone bodies are acetone, which is volatile; 3-hydroxybutyric acid; and acetoacetic acid. The standard clinical test for ketones is based on a color reaction with
5
nitroprusside, but this is relatively insensitive, not reacting with the quantitatively most important of the ketones, 3-hydroxybutyrate. There is thus a clinical need for an improved and more sensitive ketone monitoring technology. A recently developed commercial device for sensing 3-hydroxybutyrate in blood33,34 is an adaptation of the successful MediSense glucose sensor technology, where a ferrocene mediator transfers electrons from the flavoprotein glucose oxidase to the base electrode.35 The electrode of the ketone sensor incorporates 3-hydroxybutyrate dehydrogenase (HBDH), with the mediated detection of the NADH which is generated by the oxidation of the ketone: 3-Hydroxybutyrate + NAD+
HBDH −−−−→
Acetoacetic
acid + NADH Ferrocene is not suitable as an NADH mediator, and amongst various quinoid NADH mediators that have been studied, 1,10-phenylanthroline quinone does not inhibit the enzyme and has good performance in the commercial biosensor MediSense Optium. However, a bienzyme system for ketone detection is claimed to have improved operation;36 a recent report employs immobilized HBDH and salicylate hydroxylase on a Clark-type oxygen electrode (to monitor consumed O2 ), with the NADH produced enabling the decarboxylation and hydroxylation of the salicylate: Salicylate + NADH + O2
Salicylate hydoxylase −−−−−−−−−−−−−−−−→
Catechol + NAD+ + CO2 Note that the operating buffer requires added NAD and salicylate, so the device is again not a biosensor by conventional definition.
6 MONITORING JAUNDICE: BILIRUBIN
Jaundice is the typical yellow discoloration of the skin due to excessive blood levels of bilirubin; it is apparent when serum levels are greater than about 22 µM. Bilirubin is the breakdown product of the heme group found in hemoglobin and cytochromes and is normally eliminated by conjugation with
6
BIOSENSOR APPLICATIONS
glucuronic acid in the liver and excretion in the bile. The main causes of raised bilirubin levels and jaundice are hemolysis (the increased breakdown of blood cells and hemoglobin), liver disease causing failure of the conjugating mechanism, and obstruction of the biliary system (e.g., gall stones). Bilirubin itself is potentially toxic, particularly in newborns, and is an important analyte in neonatal monitoring,37 but is also used as a general indicator of the liver and blood disorders in all patients. Bilirubin biosensors have received rather little attention, however. Bilirubin oxidase potentially can be incorporated in enzyme electrodes: Bilirubin + O2
Bilirubin oxidase −−−−−−−−−−−−→
Biliverdin + H2 O2
However, two significant problems are that the enzyme is comparatively unstable and easily undergoes denaturation, and bilirubin itself is electrochemically active and is oxidized in association with the formation of a dark-colored, eventually insulating polymer at the base electrode.38 One approach to a sensor with improved functioning is a multilayer of enzyme covalently attached to a (gold) base electrode (which has increased stability and excludes bilirubin), with electron transfer mediated by a ferrocene derivative.39 Another approach is to make use of the pseudoperoxidase activity of hemoglobin, whereby hemoglobin catalyzes the conversion of bilirubin to biliverdin in the presence of H2 O2 . The H2 O2 can be generated in situ by co-immobilizing hemoglobin with glucose oxidase in a polyvinyl alcohol membrane, with detection of biliverdin spectrophotometrically at 450 nm:39 Glucose oxidase
Glucose + O2 −−−−−−−−−−−−→ Gluconic acid + H2 O2 Hemoglobin, H2 O2
Bilirubin −−−−−−−−−−−−−−→ Biliverdin
7 CONCLUSIONS
The development and description of new biosensor technologies for clinically important analytes in recent years is impressive but has far exceeded their take up into clinical practice. The impact of metabolite sensors is still modest in most diseases, excepting the measurement of glucose in diabetes. This is partly because many altered analyte levels
in disease and risk states, apart from glucose, are relatively constant throughout the day and do not need to be monitored frequently and rapidly. The true impact of biosensors in clinical chemistry may come from the potential to construct cheap and robust multianalyte sensors on a single miniature device—the so-called “lab on a chip”. Armed in the future with this type of technology at the bedside, in the home and workplace, and in developing countries where access to conventional hospital laboratories is limited, we will likely see a major biosensor-led improvement in clinical care.
REFERENCES 1. P. D’Orazio, Biosensors in clinical chemistry. Clinica Chimica Acta, 2003, 334, 41–69. 2. P. Thavarungkul, H. H˚akanson, O. Holst, and B. Mattiasson, Continuous monitoring of urea in blood during dialysis. Biosensors and Bioelectronics, 1991, 6, 101–107. 3. L. D. Ciana and G. Caputo, Robust, reliable biosensor for continuous monitoring of urea during dialysis. Clinical Chemistry, 1996, 42, 1079–1085. 4. B. Tombach, J. Schneider, F. Matzkies, R. M. Schaefer, and G. C. Chemnitius, Amperometric creatinine biosensor for hemodialysis patients. Clinica Chimica Acta, 2001, 312, 129–134. 5. C. Eggenstein, M. Borchardt, C. Diekman, B. Gr¨undig, C. Dumschat, K. Cammann, M. Knoll, and F. Spener, A disposable biosensor for urea determination in blood based on an ammonia-sensitive transducer. Biosensors and Bioelectronics, 1999, 14, 33–41. 6. A. P. Soldatkin, J. Montorial, W. Sant, C. Martlet, and N. Jaffrezic-Renault, A novel urea sensitive biosensor with extended dynamic range based on recombinant urease and ISFETs. Biosensors and Bioelectronics, 2003, 19, 131–135. 7. A. J. Marshall, D. S. Young, J. Blyth, S. Kabilan, and C. R. Lowe, Metabolite-sensitive holographic biosensors. Analytical Chemistry, 2004, 76, 1518–1523. 8. M. Meyerhoff and G. A. Rechnitz, An activated enzyme electrode for creatinine. Analytica Chimica Acta, 1976, 85, 277–285. 9. A. J. Killard and M. R. Smith, Creatinine biosensors: principles and designs. Trends in Biotechnology, 2000, 18, 433–437. 10. G. G. Guilbault and P. R. Coulet, Creatinine-selective enzyme electrodes. Analytica Chimica Acta, 1983, 152, 223–228. 11. A. C. Sharma, T. Jana, R. Kesavamoorthy, L. Shi, M. A. Virji, D. N. Finegold, and S. A. Asher, A general photonic crystal sensing motif: creatinine in bodily fluids. Journal of the American Chemical Society, 2004, 126, 2971–2977. 12. B. A. Mizock and J. L. Falk, Lactic acidosis in critical illness. Critical Care Medicine, 1992, 20, 80–93. 13. I. Jacobs, Blood lactate. Implications for training and sports performance. Sports Medicine, 1986, 3, 10–25.
BIOSENSORS FOR MONITORING METABOLITES IN CLINICAL MEDICINE 14. K. E. Friedl, The promise of lactic acid monitoring in ambulatory individuals. Diabetes Technology and Therapeutics, 2004, 3, 402–404. 15. R. Garjonyte, Y. Yigzaw, R. Meskys, A. Malinauskas, and L. Gorton, Prussian Blue-and lactate oxidase-based amperometric biosensor for lactic acid. Sensors and Actuators, B, 2001, 79, 33–38. 16. I. Katakis and A. Heller, L-α-glycerophosphate and L-lactate electrodes based on the electrochemical ‘wiring’ of oxidases. Analytical Chemistry, 1992, 64, 1008–1013. 17. C.-I. Li, Y.-H. Lin, C.-L. Shih, J.-P. Tsaur, and L.-K. Chau, Sol-gel encapsulation of lactate dehydrogenase for optical sensing of L-lactate. Biosensors and Bioelectronics, 2002, 17, 323–330. 18. S. D’Auria, Z. Gryczynski, I. Gryczynski, M. Rossi, and J. R. Lazowicz, A protein biosensor for lactate. Anal Biochem, 2000, 283, 83–88. 19. L. L. Looger, M. A. Dwyer, J. J. Smith, and H. W. Hellinga, Computational design of receptor and sensor proteins with novel functions. Nature, 2003, 423, 185–190. 20. C. Meyerhoff, F. Bischof, F. J. Mennel, F. Sternberg, J. Bican, and E. F. Pfeiffer, On line continuous monitoring of blood lactate in men by a wearable device based upon an enzymatic amperometric lactate sensor. Biosensors and Bioelectronics, 1993, 8, 409–414. 21. A. Poscia, D. Messeri, D. Moscone, F. Ricci, and F. Valgimigli, A novel continuous lactate monitoring system. Biosensors and Bioelectronics, 2005, 20, 2244–2250. 22. W. K. Ward, J. L. House, J. Birck, E. M. Anderson, and L. B. Jansen, A wire-based dual-analyte sensor for glucose and lactate: in vitro and in vivo evaluation. Diabetes Technology and Therapeutics, 2004, 3, 389–401. 23. F. H. Keedy and P. Vadgama, Determination of urate in undiluted whole blood by enzyme electrode. Biosensors and Bioelectronics, 1991, 6, 491–499. 24. D. Martinez-P´erez, M. Ferrer, and C. R. Mateo, A reagent less fluorescent sol-gel biosensor for uric acid detection in biological fluids. Analytical Biochemistry, 2003, 322, 238–242. 25. C. A. Marquette, A. Degiuli, and L. J. Blum, Electrochemiluminescent biosensors array for the concomitant detection of choline, glucose, glutamate, lactate, lysine and urate. Biosensors and Bioelectronics, 2003, 19, 433–439. 26. I. Satoh, I. Karube, and S. Sazuki, Enzyme electrode for free cholesterol. Biotechnology and Bioengineering, 1977, 19, 1095–1099. 27. M. Mascini and G. G. Guilbault, Clinical uses of enzyme electrode probes. Biosensors, 1986, 2, 147–172.
7
28. W. Trettnack and O. S. Wolfbeiss, A fiberoptic cholesterol biosensor with an oxygen optrode as the transducer. Analytical Biochemistry, 1990, 184, 124–127. 29. A. Krug, A. A. Sulerman, and G. G. Guilbault, Enzymebased fiber-optic device for the determination of total and free cholesterol. Analytica Chimica Acta, 1992, 256, 263–268. 30. G. Li, J. M. Liao, G. Q. Hu, N. Z. Ma, and P. J. Wu, Study of carbon nanotube modified biosensor for monitoring total cholesterol in blood. Biosensors and Bioelectronics, 2005, 20, 2140–2144. 31. V. Shumyantseva, G. Deluca, T. Bulko, S. Carrara, C. Nicolini, S. A. Usanov, and A. Archakov, Cholesterol amperometric biosensor based on cytochrome P450. Biosensors and Bioelectronics, 2004, 19, 971–976. 32. R. R. K. Reddy, A. Chadha, and E. Bhattacharya, Porous silicon based potentiometric triglyceride biosensor. Biosensors and Bioelectronics, 2001, 16, 313–317. 33. N. J. Forrow, G. S. Sanghera, S. J. Walters, and J. L. Watkin, Development of a commercial amperometric biosensor electrode for the ketone D-3hydroxybutyrate. Biosensors and Bioelectronics, 2005, 20, 1617–1625. 34. R. W. K. Chiu, C. S. Ho, S. F. Tong, K. F. Ng, and C. W. Lam, Evaluation of a new handheld biosensor for pointof-care testing of whole blood beta-hydroxybutyrate concentration. Hong Kong Medical Journal, 2002, 8, 172–176. 35. A. E. G. Cass, G. Davis, G. D. Francis, H. A. O. Hill, W. J. Aston, I. J. Higgins, E. V. Plotkin, L. D. L. Scott, and A. P. F. Turner, Ferrocene-mediated enzyme electrode for the amperometric determination of glucose. Analytical Chemistry, 1984, 56, 667–671. 36. R. C. H. Kwan, P. Y. T. Hon, W. C. Mak, L. Y. Law, J. Hu, and R. Renneberg, Biosensor for rapid determination of 3-hydroxybutyrate using bienzyme system. Biosensors and Bioelectronics, 2006, 21, 1101–1106. 37. I. Murkovic, M. D. Steinberg, and B. Murkovic, Sensors in neonatal monitoring: current practice and future trends. Technology and Health Care, 2003, 11, 399–412. 38. B. Shoham, Y. Migron, I. Willner, and B. Tartakovsky, A bilirubin biosensor based on a multilayer network enzyme electrode. Biosensors and Bioelectronics, 1995, 10, 341–352. 39. M. M. Vidal, I. Delgadillo, M. H. Gil, and J. AlonsoChamarro, Study of an enzyme coupled system for the development of fibre optical bilirubin sensors. Biosensors and Bioelectronics, 1996, 11, 347–354.
69 Need for Biosensors in Infectious Disease Epidemiology Laurence Baril Unit of Infectious Disease Epidemiology, Institut Pasteur, Dakar, S´en´egal
1 WHAT IS INFECTIOUS DISEASE EPIDEMIOLOGY?
Infectious disease epidemiology deals with three main issues: causes, distribution, and control of infectious diseases occurring in the human population. This is based on the observation that most infectious diseases do not occur randomly, but are related to environmental, economic, societal, and personal characteristics. In the past decades, increased development, deforestation, and other environmental changes have brought people into contact with animals (recent epidemic of SARS, and Ebola and Marburg hemorrhagic fevers) or insects (vectorborne diseases such as human infections with the dengue, West Nile, or Chikungunya viruses) that harbor diseases only rarely encountered before in humans.1–4 In addition, the recent threefold increase in international travel as well as the greater importation of fresh foods across national borders are other examples of potential exposures with growing numbers of people who have no or weakened immunity to these new pathogens (see Annex 1). The etymology of epidemiology comes from the Greek epi = among, demos = people, and logos = science, whereas the definition of infectious disease is related to a communicable disease. Communicable disease was initially defined as a disease that can be transmitted from person to person through a microbial agent. However, of
the around 1400 recognized species of human pathogens (prions, viruses, bacteria, fungi, protozoa, and helminths) almost 60% are zoonotic, that is, able to infect other host species.5 These recognized zoonotic pathogens have been, at least once, successfully introduced from a nonhuman source. In infectious disease epidemiology, the identification of the pathogen (the diseasecausing organism) is a pivotal step in understanding infectious disease etiology.6,7 Then, it is necessary to study the factors that influence the occurrence of this disease and its distribution in the human population. Therefore, infectious disease epidemiology examines epidemic (excess or new) and endemic (always present) infectious diseases. It is a cornerstone methodology of public health research for identifying risk factors for infectious diseases and determining optimum treatment or preventive measures. Infectious diseases are still the leading cause of death worldwide. It is estimated that around 180 human pathogens are regarded as emerging or reemerging among which two-thirds are known to be zoonotic.5 However, most zoonotic pathogens are not highly transmissible within human populations and do not cause major epidemics but only outbreaks. In infectious diseases, the etiologic agent and the biological interaction between host and pathogen are the major components leading to disease. Small
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
changes in the nature of the host–pathogen interaction can lead to the emergence or reemergence of an epidemic. There is a joint action between the biological events including genetic factors and the societal determinants in transmission of infectious diseases in the human population. The AIDS pandemic and the reemergence of vectorborne diseases could illustrate this causal coaction of biological and societal or environmental factors. The transmission of AIDS was dramatic in the intravenous drug user and homosexual communities, both stigmatized by society in highly developed countries, and in the heterosexual population living in developing countries, abandoned by the global economical system. For vectorborne diseases such as malaria, the reemergence of dengue, or the recent Chikungunya epidemic, the slowdown of the vector-control measures, the impact of warmed-up climate, the growing suburban population are certainly among the causative factors that promote the high burden of those diseases in tropical areas. Historically, the epidemiologic approach has helped to explain the transmission of communicable diseases such as cholera and measles; this was done by discovering what exposures or host factors were shared by individuals who became sick. The founding event in infectious disease epidemiology was when John Snow, in 1854, removed a public water pump in London and ended an outbreak of cholera. Nowadays, the identification of the pathogens using newly developed biological tools has changed the epidemiological approach to infectious diseases. In this way, pathogens were quite rapidly identified in the recent epidemics of West Nile virus, SARS coronavirus, and Ebola and Marburg hemorrhagic fevers (see Annex 1). However, in terms of public health measures in response to epidemics, a rapid recognition of emerging infections requires the core capacity to assure almost an “on-the-field” detection. This detection implies the use of newly developed diagnostic tools, ideally a lab on a chip or, at least, some portable (easy to use) tools such as optical fiber biosensors.8–10 In addition, onthe-field, noninvasive remote diagnosis tools are necessary for safety reasons. Such diagnostic tools to identify existing and possibly new pathogens could be essential for determining control and prevention efforts during the investigation of a new outbreak.
2 METHODS IN INFECTIOUS DISEASE EPIDEMIOLOGY
The epidemiologists attempt to answer the following questions: • • • •
Who is prone to a particular infectious disease? What exposure do the patients have in common? Where is the risk highest? When is the disease most likely to occur and what is its trend over time? • By how much does the risk increase given a specific exposure? • How many cases of the disease could be avoided by eliminating the exposure? However, many diseases (diarrheal or respiratory diseases, meningitis, etc.) can be caused by more than one species of pathogen. This explains that most of the time the first epidemiological approach is a syndromic approach and emphasizes how much the rapid identification of the pathogen helps the epidemiologist to carry out the first control and prevention measures. During the second half of the twentieth century, different methods have been developed to understand factors that influence the risk of onset and severity of infectious diseases: • outbreak investigation to identify the component causes of a specific infectious disease, its incubation period, and its mode of transmission; • surveillance system with notifiable infectious diseases at national or international levels of reporting;11,12 • cohort studies to understand incidence, determinants, and occurrence patterns of a particular disease (mainly applicable to chronic infectious diseases such as HIV infection or viral hepatitis);13 • clinical research to improve prevention measures or therapy; • modeling method to contribute to the formulation of public health policies and support public health decision-makers.14 The different outcome measures used by the epidemiologists are summarized in Annex 2.
NEED FOR BIOSENSORS IN INFECTIOUS DISEASE EPIDEMIOLOGY
3
3 A MULTIDISCIPLINARY APPROACH IS ESSENTIAL
4 COMMUNICATIONS AND REGULATIONS AT AN INTERNATIONAL LEVEL
Epidemiological studies in humans offer the advantage of producing results relevant to people, but have the disadvantage of not always allowing perfect control of study conditions. Unlike experimental science, budget and societal concerns impose some limitations on epidemiological research. One major difficulty in epidemiological research is the expensive effort needed to gather the necessary information. In addition, epidemiology research is sometimes viewed as a collection of data analyzed using some statistical tools! However, the epidemiologists use gathered data on a broad range of biomedical domains in an interactive way to generate or expand theory, to test hypotheses, and to make assertions about which relationships are causal and about how they are causal. Thus, one essential concept in epidemiology is to keep in mind that people are classified according to causal indicators or etiologic agents. Some causal components could remain hidden despite efforts to understand a complex causal mechanism. Moreover, the organization and the logistics required to obtain biological samples for etiologic diagnostics and to transport these samples to the laboratory of reference are difficult. This is why it is essential that diagnostic tools be developed on the basis of biosensor, lab-on-a-chip, or biochip technologies that would enable the epidemiologists to carry out on-the-field tests. Therefore, a multidisciplinary approach is essential to investigate emerging or reemerging infectious diseases. Not only infectious disease epidemiologists or public health authorities but also researchers from other fields should be rapidly recruited, such as virologists and immunologists for the study of microbial pathogenesis and host responses, researchers in biotechnologies to develop novel diagnostics tools and even new therapeutic or vaccine approaches, and researchers in the field of vector or animal control. This multidisciplinary approach at an early phase of the investigation will also allow collaborators to obtain well-characterized samples that are essential to study disease severity biomarkers and test newly developed diagnostics tools that require proper statistical analysis for validation (see Annex 3).
One other challenge for the epidemiologists is to translate surveillance or epidemics information into disease prevention and control activities and also to optimize the exploitation of the results. Several means of information sharing are now available through the web at national or international levels (available from the websites of the World Health Organization (WHO), the US Centers for Disease Control and Prevention (CDC), the ProMED society, etc.). Emphasis has been placed on the critical importance of communicating alerts about clusters of illness, data on disease trends, and guidelines for disease prevention. In this regard, the recent SARS epidemic was quite a success in terms of the collaborative international effort to contain the epidemic. In addition, WHO has set up a legal instrument to notify the outbreak of diseases of international importance: the International Health Regulations (IHR, available from http://www.who.int/csr/ihr). The most recent IHR version emphasizes the immediate notification of all disease outbreaks of urgent international importance. This should facilitate alert and appropriate international response while awaiting laboratory verification.
5 PREPAREDNESS FOR EPIDEMICS
Preparedness for epidemics (including deliberate epidemics) is becoming a major issue for national and international public health organizations. For instance, it has been estimated that only 0.4% of all extant bacterial species have been identified despite the development of different molecular methods such as DNA microarray technology.2 We have highlighted how important laboratory assessment is for identifying the cause of an infectious disease, but what would epidemiologists ideally need on the field from an efficient collaboration with the partners from other disciplines? • coordination of the respective activities and sharing of the information: this includes the elaboration of a written protocol and standard operational procedures;
4
BIOSENSOR APPLICATIONS
• previous laboratory management skills (including biosafety issues as defined by WHO15,16 ) in the field conditions; • rapid, reproducible, high-sensitivity, and specific bioassays (see Annex 3) to detect antigens for early diagnostic, and to detect antibodies (IgM and IgG) for confirmation of the diagnostic during the early convalescent phase; • the laboratory assessment should allow for syndromic approach (i.e., taking into account differential diagnosis) and for the detection of subclinical cases to monitor the spread of the disease; • the bioassays should be able to perform the analysis using small amounts of different biological samples (blood, urine; stools, cerebrospinal fluid, tissue biopsy, etc.); • a compatible electronic data system to be able to perform comprehensive data analysis and easily diffuse information. Adequate funding and institutional and community support are also critical to perform an effective investigation and to implement control measures.
6 CONCLUSION
Like novel biotechnologies, infectious disease epidemiology is still an emerging discipline. This domain requires a strong interdisciplinary approach; the epidemiologists face the problem of obtaining cooperation from numerous people to perform epidemiological investigation or research essential in efforts to understand, prevent, control, and respond to new or reemerging infectious diseases. Innovations in biotechnology have an increasingly important role in identifying pathogens. Novel laboratory testing tools such as optical biosensors will improve the quality of the epidemiological information. In developing countries with resource constrains where most of the recent new viral epidemics have occurred in the past decades (see Annex 1), such innovative diagnosis tools are necessary to improve the feasibility of epidemiological research. This is not a paradox when we look at what happened in the telecom and informatics domains where cell phones and microcomputers have been easily implemented and taken up by the population all over the world.
7 ANNEX 1: EXAMPLES OF INFECTIOUS DISEASE SURVEILLANCE SYSTEMS AND RECENTLY DIAGNOSED VIRAL DISEASES
1. Examples of disease-specific surveillance: (a) tuberculosis (b) HIV/AIDS (c) sexually transmitted infections (d) foodborne/waterborne diseases (Campylobacter, Clostridium, Escherichia coli O157:H7, Listeria, nontyphoid Salmonell a, or Staphylococcus aureus, etc.) (e) respiratory diseases (f) vectorborne/zoonotic diseases (malaria, dengue, Japanese encephalitis, yellow fever, etc., in some tropical areas or as imported diseases) (g) drug resistance (malaria, tuberculosis, bacterial community-acquired pneumonia, etc.) (h) vaccine-preventable diseases (including rabies) (i) diseases transmitted by blood transfusions or blood products (hepatitis C, for instance) (j) other emerging infectious diseases (agents of viral hemorrhagic fevers, Lyme disease, borreliae, bartonellae, babesiae, rickettsiae, etc.) (k) parasitic diseases (trypanosomiasis, etc.). The disease-specific surveillance systems to improve the prevention and control of emerging or reemerging infectious diseases differ from country to country.11,12 In addition, public health risks may change over time; therefore, priorities are reviewed periodically by the public health authorities. 2. Examples of recently diagnosed viral diseases and causes of death in human population are shown in Figure 1. 8 ANNEX 2: LEXICON OF THE CURRENT DEFINITIONS USED IN EPIDEMIOLOGY
Definitions adapted from Refs. 13 and 14. Descriptive measures: these are used for identifying populations and subgroups at high or low risk of infectious diseases and for monitoring time trends for specific infectious diseases. Analytic measures: these are used for identifying specific factors that increase or decrease the
NEED FOR BIOSENSORS IN INFECTIOUS DISEASE EPIDEMIOLOGY 7
Other causes Tobacco
AIDS, 1981
HIV
Log10 global death rate
Hepatitis, 1989
West Nile encephalitis, 1999
Caused by viruses
5
6
HBV + HCV
5
Measles RSV, Rota Flu Dengue
4
HPV
Malaria Road accidents Non-HIV TB
Hospital infection Suicide
West Nile 3
SARS, 2003 Ebola, 1976 2
Hantavirus, 1992
SARS Ebola Polio Hanta vCJD
1
Adapted from Ref. 1
Figure 1. Recently diagnosed viral diseases and causes of death in human population.
risk of infectious disease and for quantifying the associated risk. Hypothesis in statistical testing: Assumptions to be tested in a statistical procedure, the null hypothesis (noted H0 ) is often in the form “no relationship exists between x and y”. When the statistical test cannot disprove the null hypothesis, it is termed failure to reject the null hypothesis rather than acceptance. In statistical testing, a hypothesis is accepted if a sample contains sufficient evidence to reject the null hypothesis. In most cases, the alternative hypothesis (H1 ) is the expected conclusion (why the test was completed in the first place).
that it will not make a Type II error (probability β). As power increases, the chances of a Type II error decrease, and vice versa. Therefore, power is equal to 1—β. Case fatality rate: number of deaths over a period per 1000 persons at risk. Incidence density: number of new cases over a period per 100 000 persons at risk. Cumulative incidence: number of new cases divided by the studied persons over a period. Prevalence: number of existing cases at a given time per 100 persons at risk.
P value: It is the probability of obtaining a finding at least as impressive as that obtained by assuming the null hypothesis is true, so that the finding was the result of chance alone. The fact that P values are based on this assumption is crucial to their correct interpretation. Therefore, in practical terms, the higher the P value, the higher the probability that the observations you are studying are just chance. If the null hypothesis (H0 ) is true, the significance level (α) is the probability that it will be rejected in error (a decision known as a Type 1 error). P values used to decide the statistical significance represents the level of belief in the null hypothesis (choice of level often set at α = 0.05).
Odds ratio (OR): The ratio of the odds of an event occurring in one group to the odds of it occurring in another group. These groups might be an experimental group and a control group, or any other dichotomous classification. If the probabilities of the event in each of the groups are p (first group) and q (second group), then the odds ratio is OR = p (1—q)/q (1—p). An OR of 1 indicates that the condition or event under study is equally likely in both groups. An OR greater than 1 indicates that the condition or event is more likely in the first group and an OR less than 1 indicates that the condition or event is less likely in the first group.
Power of a statistical test: It is the probability that the test will reject a false H0 , or in other words,
Relative risk (RR): It is the risk of an event (or of developing a disease) relative to exposure; it is
6
BIOSENSOR APPLICATIONS
used frequently in the statistical analysis of binary outcomes where the outcome of interest has relatively low probability: RR = pexposed /pcontrol . RR is different from OR, although it asymptotically approaches it for small probabilities. An RR of 1 means there is no difference in risk between the two groups. An RR less than 1 means the event is less likely to occur in the experimental group than in the control group. An RR greater than 1 means the event is more likely to occur in the experimental group than in the control group. Hazard ratio: the effect of an explanatory variable on the hazard or risk of an event (used in survival analysis). Confidence interval (CI ): It is an interval between two numbers with an associated probability p, which is generated from a random sample of an underlying population, such that if the sampling was repeated numerous times and the confidence interval recalculated from each sample according to the same method, a proportion p of the confidence intervals would contain the population parameter. Confidence intervals are the most prevalent form of interval estimation. Infectivity (R0 ): The possible magnitude of an infectious disease outbreak is related to the basic reproduction number R0 . For pathogens that are minimally transmissible within human populations (R0 close to 0), outbreak size is determined largely by the number of introductions from the reservoir. For pathogens that are highly transmissible within human populations (R0 > 1), outbreak size is determined largely by the size of the susceptible population. For pathogens that are moderately transmissible within human populations (corresponding to R0 ∼ 1), notable outbreaks are possible (for instance, if multiple introductions occur), but the scale of these outbreaks is very sensitive to small changes in R0 .
9 ANNEX 3: LEXICON OF THE PERFORMANCE OF NEWLY DEVELOPED DIAGNOSTIC TOOLS
Some indicators should help to estimate the performances of laboratory methods and to support their comparisons (see Table 1). For instance, to determine whether a patient has a certain infectious disease or not, a newly developed diagnostic tool should be compared to a reference method through the following indicators: Sensitivity (Se): number of true positives/ (number of true positives + number of false negatives). Specificity (Sp): number of true negatives/(number of true negatives + number of false positives). Positive predictive value: number of true positives/(number of true positives + number of false positives). It is the proportion of patients who present the disease, among the patients diagnosed by the method. Negative predictive value: number of true negatives/(number of true negatives + number of false negatives). It is the proportion of patients who do not present the disease, among the patients not diagnosed by the method. Positive predictive value is called precision, and sensitivity is known as recall. F measure can be used as a single measure of the performance of the test, it is calculated as follows: F = 2 × precision × recall/(precision + recall). The receiver operating characteristic (ROC) is a graphical plot of the sensitivity versus 1-specificity for a binary testing system as its discrimination threshold is varied. The ROC curve can also be represented equivalently by plotting the fraction of true positives versus the fraction of false positives. Reproducibility refers to the ability of a laboratory method to be accurately reproduced, or replicated.
Table 1. Link between statistical tests and performance of laboratory tests
Statistical significance No statistical significance
H1
H0
1−β
α
β
1−α
Disease
No disease
Positive test
Se
1 − Sp (False positive)
Negative test
1 − Se (False negative)
Sp
NEED FOR BIOSENSORS IN INFECTIOUS DISEASE EPIDEMIOLOGY
The calibration curve is a plot of how the instrumental response changes with changing concentration (for instance) of substance to be measured (adapted from Ref. 8). The operator will create a series of standards across a range of concentrations near the expected unknown concentration. Analyzing each of the standards using the chosen technique will produce a series of readings. The results could follow different types of equations (linear, logarithmic, sigmoid, etc.) and the curve also indicates the precision of the results. Moreover, if there is evidence of a relationship, the technique of correlation (r = correlation coefficient) allows one to test the statistical significance of the association. However, a significant correlation only shows that two factors vary in a related way but does not necessarily demonstrate a causal relationship. The lower detection limit is important to report; it describes the lower analyte dilution that can be efficiently distinguished by the detecting system. For a definite dilution, the difference of the signal level between the experimental points with positive or control biological samples is modulated by the standard deviation of the control (adapted from Ref. 17). Some recommendations before publications of laboratory testing methods are available from http:// www.consort-statement.org/ stardstatement. htm.17,18
REFERENCES 1. R. A. Weiss and A. J. McMichael, Social and environmental risk factors in the emergence of infectious diseases. Nature Medicine, 2004, 12, 70–76. 2. A. S. Fauci, New and re-emerging diseases: the importance of biomedical research. Emerging Infectious Diseases, 1998, 4, 374–378. 3. N. D. Wolfe, A. A. Escalante, W. B. Karesh, A. Kilbourn, A. Spielman, and A. A. Lal, Wild primate in emerging infectious disease research: the missing link? Emerging Infectious Diseases, 1998, 4, 149–158. 4. J. Lederberg, Emerging infections: an evolutionary perspectives. Emerging Infectious Diseases, 1998, 4, 366–370.
7
5. M. E. Woolhouse and S. Gowtage-Sequeria, Host range and emerging and re-emerging pathogens. Emerging Infectious Diseases, 2005, 11, 1842–1847, see Appendix available on http://www.cdc.gov/ncidod/eid/vol11no12/ 05-0997 app.htm). 6. P. Houpikian and D. Raoult, Traditional and molecular techniques for the study of emerging bacterial diseases: one laboratory’s perspective. Emerging Infectious Diseases, 2002, 8, 122–131. 7. C. A. Cummings and D. A. Relman, Using DNA microarrays to study host-microbe interactions. Emerging Infectious Diseases, 2000, 6, 513–525. 8. S. Herrmann, B. Leshem, S. Landes, B. Rager-Zisman, and R. S. Marks, Chemiluminescent optical fiber immunosensor for the detection of anti-West Nile virus IgG. Talanta, 2005, 66, 6–14. 9. T. Konry, A. Novoa, Y. Shemer-Avni, N. Hanuka, S. Cosnier, A. Lepellec, and R. S. Marks, Optical fiber immunosensor based on a poly(pyrrole-benzophenone) film for the detection of antibodies to viral antigen. Analytical Chemistry, 2005, 77, 1771–1779. 10. S. Cosnier, R. E. Ionescu, S. Herrmann, L. Bouffier, M. Demeunynck, and R. S. Marks, Electroenzymatic polypyrrole-intercalator sensor for the determination of West Nile virus cDNA. Analytical Chemistry, 2006, 78, 7054–7057. 11. World Health Organization. Settings Priorities in Communicable Surveillance, 2006, (available from www.who.int/ csr/labepidemiology). 12. World Health Organization. Developing Laboratory Partnerships to Detect Infections and Prevent Epidemics, 2005, (available from www.who.int/csr/labepidemiology). 13. K. J. Rothman and S. Greenland, Modern Epidemiology, 2nd Edn, Lippincott—Raven Publishers, Philadelphia, 1998. 14. R. M. Anderson and R. M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, Oxford, 2002. 15. World Health Organization. Laboratory Biosafety Manual, 3rd Edn, 2004, (available from http://www.who.int/csr/ resources:publications/biosafety). 16. World Health Organization. Guidance on Regulations for the Transport of Infectious Substances, 2005, (available from http://www.who.int/csr/resources/publications/ transport). 17. N. Smidt, A. W. Rutjes, D. A. van der Windt, R. W. Ostelo, P. M. Bossuyt, J. B. Reitsma, L. M. Bouter, and H. C. de Vet, Reproducibility of the STARD checklist: an instrument to assess the quality of reporting of diagnostic accuracy studies. BMC Medical Research Methodology, 2006, 6, 12. 18. P. M. Bossuyt, L. Irwig, J. Craig, and P. Glasziou, Comparative accuracy: assessing new tests against existing diagnostic pathways. British Medical Journal, 2006, 332, 1089–1092.
70 Biosensors for Neurological Disease Kathryn M. Bell and Steven E. Kornguth Center for Strategic and Innovative Technologies, University of Texas at Austin, Austin, TX, USA
1 INTRODUCTION
Biosensors are capable of rapid, sensitive, and accurate identification of metabolic, proteomic, and genomic biomarkers of neurological disease (ND). Many neurological disorders can be identified by testing the activity of a single enzyme (e.g., mental retardation in phenylketonuria is associated with reduced levels of phenylalanine hydroxylase) or genomic element (e.g., a large number of deoxynucleotide triplet repeats in Huntington’s disease, HD). For other diseases the analysis of a single biomarker may provide a tentative diagnosis that is burdened by a high number of false positives or negatives. The ability to generate a multitarget profile of disease probability or “signature” of disease is therefore of major interest. As an example, autoantibody signatures for prostate cancer were developed from markers present in prostate cancer tissues, a technique that can be adapted to nervous system cancers.1 Using iterative biopanning of a phage display library derived from the cancer tissues, a 22phage peptide panel had 88.2% specificity and 81.6% sensitivity in discriminating the prostate cancer group from the control group. In an analogous manner, a robust sensor array that could detect multiple genomic and proteomic ND markers from saliva, urine, serum, or cerebrospinal fluid (CSF) could increase the probability of accurate diagnosis.
For most neurological disorders there is no one test that can provide a definitive diagnosis. In addition to the collection of full medical history and multiple neurological examinations, tests such as magnetic resonance imaging, electromyography, and electroencephalography are performed. Where established, tests for a single, or in some cases a limited set, of biochemical or genetic biomarker(s) are performed. Conventional biochemical tests include immunoassay (e.g., enzyme-linked immunosorbent assay, ELISA, for amyloid-β peptides in Alzheimer’s disease, AD) and enzymatic assay (e.g., hexosaminidase A assay for Tay–Sachs). Using conventional genetic tests, gene mutation is determined using PCR (e.g., allele-specific PCR for Tay–Sachs) or RT-PCR (e.g., retroviral detection). The disadvantages of conventional immunoassay include poor precision, time required, and difficulty automating the techniques. Though highly sensitive, one disadvantage of PCR-based methods is the reliance upon polymerase enzyme function, which can be costly and reduce reliability of the system.2 Immunosensors, microarrays, and nonenzymatic amplification techniques are expected to markedly reduce these disadvantages in diagnosing disease, including ND. Not only do biosensors currently serve as diagnostics, they also enable tissue-derived and genome-based biomarker discovery that can identify the components of complex disease signatures.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
For the health care provider, the process of ND determination is complex. Measurements of analytes in biological fluids are routinely performed at locations outside of the physician’s office or hospital. Conventional laboratory testing would be complemented by rapid sensor-based methods. For the patient, availability of biosensors could greatly facilitate disease management. In many cases, biomarkers exist in the blood and urine that can indicate state of progression, recovery, or response to medication.3 Unlike glucose, pregnancy, and HIV home test kits, there are currently no products on the market that allow a patient to track the state of neurological health. Likewise, there is no health care industry standard for clinical biomarker profiling of ND.
2 DISCUSSION 2.1
Biosensors for Neurological Disease
Biosensors are analytical devices composed of a high-affinity recognition probe of biological origin and a transducer, which converts chemical signals to electrical or optical outputs. In general, all sensors are designed to achieve one or more of the following goals: lowering the limits of detection, parallel detection of multiple analytes or signals (multiplexing), and signal amplification by several orders of magnitude. Current disease biosensors, including several platforms that have been used for ND analyte sensing, are capable of binding genetic targets or biochemical analytes in saliva, urine, blood, CSF, or tissue of interest. The concept of creating disease biomarker signatures involves testing for multiple targets, some of which may hold high correlation to a specific disease and some of which may indicate general nervous system involvement but do not identify a specific illness. Negative controls must be included on the signature platform to rule out false positives. Table 1 is a selected list of potential targets for disease signatures. Some of the targets are already used in ND testing, while others have been identified but are not yet incorporated into clinical testing. There is a current requirement for separate platforms for genomic and proteomic or biochemical biosensing. The specificity and sensitivity of genomic sensing is dependent upon the
thermal dissociation of the hydrogen bonding between the bases of nucleic acid. The specificity and sensitivity of biochemical sensing in the case of immunological-based sensing is dependent upon the dissociation constant, or Kd , of the probe–analyte complex. This complex is dependent not only upon hydrogen bonding but also upon electrostatic forces, π-bonding, and van der Waals forces. Patient sensitivity to and tolerance of treatment are crucial to selecting the proper course of care for individuals with NDs associated with significant pain and inflammation. Understanding the mechanisms behind cancer and ND symptoms and correlating biomarkers to pain, stress, and inflammation can advance current treatment modalities. Many biomarkers for pain susceptibility and chronic inflammation have been identified including interleukins (ILs), interferon-α, and tumor necrosis factor (TNF).14,56,57 Activation of these pathways is involved in the pathogenesis of many complex diseases including NDs, cancer, and cardiovascular disease. Until recently, the genes associated with cytokine production were not well understood. In addition to the long list of cytokines that were known to be involved in pain and inflammation, a recent study has identified a gene associated with cytokine production. The selenoprotein S (SEPS1) gene (also called SELS, SELENOS, or VIMP) was identified as a mediator of inflammation.58 SEPS1 polymorphisms were identified and strongly associated (multivariate p = 0.0000002) with elevated levels of the cytokines IL-6, IL-1-β, and TNF-α in plasma. This knowledge will allow for sensors to determine gene polymorphisms associated with pain and inflammation, elucidating the risk of stress susceptibility. Table 1 includes a brief list of known stress susceptibility markers. Pain susceptibility when combined with ND biomarker data can provide a powerful tool for creating individual patient susceptibility profiles. Personalized medicine can be realized on diverse, multiplexed platforms with technology that is commercially available.
2.2
Biomarker Overlap
Supporting the concept of disease signatures is the common event in which any one biomarker exists
Autoimmune
Degenerative
General category of disorder, incidence
Lupus (CNS, PNS), 122/100 000(a), 10
ANAb11 Cardiolipin11 IgG12 TRAIL13
8-hydroxydeoxyguanosine7 α-synuclein contained in Lewy bodies5 Altered DAT5 DARP8
Parkinson’s Disease (CNS), 100/100 000 over 65 years of age4
Fragile X syndrome (CNS) 6/100 000 males4 HD (CNS) 0.5–5/100 0004
Tau protein, phospho-tau ApoE5 Aggregated β-amyloid peptide5,6
5
Biochemical biomarker
AD (CNS), 120/100 000, over 60 years of age4
Primary cause of neurological disorder, incidence
Table 1. Biomarker targets for neurological disease, and stress (pain/inflammation) susceptibility
Serum
CAG repeats5
(continued overleaf )
Serum Serum CSF in mice Serum
Serum Serum Serum Serum
Brain histology CSF Serum
Urine Brain histology
CSF Serum Serum, CSF Serum Serum
Sample source
α-synuclein mutations5 Parkin gene mutations5 UCH-L1 mutations5 NR4A2 mutations5 FMR1 CGG repeats9
APP mutations5 Presenilin-1 and -2 mutations5
Genetic biomarker
BIOSENSORS FOR NEUROLOGICAL DISEASE 3
Seizure disorders, 44/100 000 Primary brain tumors, 15/100 00031
Cardiovascular accident, 100–300/100 000
General category of disorder, incidence
Table 1. (continued)
CK26 cTn127 CRP28 IL-1Ra29 Pipecolic acid30 VEGF33
Stroke/impeded vascular flow (CNS)
Myocardial infarction Pyridoxine-dependent seizures (CNS)
Astrocytoma (CNS), 6-12/100 00031,32
PND (CNS)
Anti-GQ1b ganglioside antibody in Miller–Fisher syndrome22 Autoantibodies to AchRs19 Autoantibodies to MuSK19 ANA-Ma223 (for SCLC19 ), ANA-1 (anti-Hu), ANA-2 (anti-Ri), ANA-323 PCA-1, PCA-2, PCA-Tr, CRMP5-IgG, amphiphysin IgG23 Anti-Rc antibody, for SCLC24 Progelatinase B/proMMP-9 correlating with CRP25
Oligoclonal IgG17 Glycoprotein17 Autoantibodies to the 20S proteasome18 Anti-hnRNP-B1 antibody19,20
Myelin basic protein
15,16
Biochemical biomarker
Guillain–Barr´e syndrome (PNS), 1.5/100 0004 Myasthenia gravis (PNS) 0.3/100 0004
MS (CNS), 10–80/100 000, dependent on geography, ethnicity, and environmental factors4
Primary cause of neurological disorder, incidence
ASCL1 (Drosophila; HASH 1)34
HLA-DR mutations21
Genetic biomarker
Serum, histology
CSF
Serum Serum Serum Serum Serum, CSF
Serum, histology Pleural fluids
Serum, CSF
Serum, CSF Serum, CSF Serum, CSF, histology
Serum, CSF CSF, CNS, and thymic tissue Serum
CSF, urine, cervical lymph nodes CSF CSF Serum, CSF
Sample source
4 BIOSENSOR APPLICATIONS
IL-2, −6, −8, −1053 TNF-α 39 IFN-γ 54 CRP55
(Chloride channel myopathy) CK MM isoforms50 (MD)
Chloride channel myopathy MD (PNS)
Manifested as inflammation, pain
(Hyperkalemic)
NSE, tau protein, amyloid-β, 14-3-3 protein6
Polysialylated NCAM44 (PML) PrP45
Tay–Sachs (CNS), 170/100 000 in Ashkenazi jews Hyperkalemic periodic paralyses (PNS)
Glycogen storage diseases (CNS)
Meningioma (CNS), 3/100 00031 PML (CNS), 5000/100 000 in AIDS Creutzfeldt-Jakob disease (CNS), 0.2/100 000
Cathepsin D35 IGF-136 ANX7 for survivorship37 MAPK, PKC, PLC-γ 38 Polysialic acid NCAM39,40 Antirecoverin33 Survivin41
SEPS1 gene (also called SELS, SELENOS )53
Serum
CACNA1s, SCN4A genes51 CLCN1 gene52
Serum Serum Serum Serum Serum
Serum Serum
Serum Serum Serum
Histology CSF, histology Histology; CSF, urine45 CSF
Histology
PRKAG2 gene48 LAMP2 gene48 HEXA gene variants49
JC virus46,47
BMI-1 oncogene pathway42,43
Serum Serum Histology Histology CSF, histology Serum, CSF CSF, histology
ApoE: apolipoprotein E; APP: amyloid precursor protein; DAT: dopamine transporter; DARP: dopamine releasing protein; UCH-L1: ubiquitin carboxy-terminal hydrolase L1; NR4A2: nuclear receptor family; FMR1: fragile X mental retardation gene 1; ANAb: antineuronal nuclear antibody b; TRAIL: tumor necrosis factor–related apoptosis inducing ligand; HLA-DR: histocompatibility leukocyte antigen; AchRs: acetylcholine receptors; MuSK: muscle-specific receptor tyrosine kinase; PND: paraneoplastic neurological disorder; PCA-1: Purkinje cell cytoplasmic Ab type 1, anti-Yo; CRMP5: collapsin-response mediator protein; Anti-Rc: antirecoverin; CRP: C-reactive protein; CK: creatine kinase; cTn1: cardiac troponin 1; IL-1Ra: interleukin 1 receptor agonist; VEGF: vascular endothelial growth factor; ASCL1: Achaete-scute complex-like 1; IGF-1: insulin-like growth factor 1; ANX7: annexin VII; MAPK: mitogen-activated protein kinase; NCAM: neural cell adhesion molecule; PML: progressive multifocal leukoencephalopathy; PrP: prion protein; NSE: neuron-specific enolase; PRKAG2: associated membrane protein–adenosine monophosphate γ 2; LAMP2: lysosome-associated membrane protein 2; MD: muscular dystrophy; IFN: interferon. (a) Excluding drug-induced lupus.
Stress susceptibility
Channelopathies, 1/100 00031
Inborn errors of metabolism
Infectious
Medulloblastoma (CNS), 0.3/100 000 in adult31
Glioblastoma multiforme (CNS), 7.5/100 00031
BIOSENSORS FOR NEUROLOGICAL DISEASE 5
6
BIOSENSOR APPLICATIONS
in multiple diseases or syndromes. For example, a tumor marker might be found across several different cancer etiologies. Interleukins are general markers for inflammation but are also indicators of pain susceptibility. Myelin basic protein is released during traumatic neural injury, but is also a strong indicator for multiple sclerosis (MS). These are examples where a single marker is not pathognomonic for a specific disease. The use of a multiplexed platform in conjunction with a robust statistical database can generate a profile of susceptibility to specific diseases.1,59 Multiplexed sensors can be used to address the issue of biomarker overlap. Table 2 demonstrates selected examples where a particular biomarker appears changed in concentration across multiple diseases, including ND.
2.3
Currently Available Biosensor Technology
The function of biosensors for ND is twofold; they can be used for biomarker discovery and as diagnostic tools. The sensors discussed here include a broad range of technologies including commercially available kits and experimental proofs of principle. These sensors exhibit levels of detection comparable to or better than the conventional assay. Many procedures currently used for the diagnosis of ND in clinical laboratories involve multistep immunoassays. Because the immunoassay relies upon antibody (Ab)–antigen (Ag) binding, such tests are readily being converted to operate in biosensor systems such as Biacore SPR (surface plasmon resonance), Roche Diagnostics’ handheld therapeutic drug monitor, and other advanced Ab-based diagnostic tools. Extensive biomarker discovery is ongoing with the use of microarrays from companies such as Affymetrix and Agilent (gene based) and Ciphergen (protein based). A brief list of biosensor companies and their platforms is included in Table 3. Many of the platforms listed in the table are discussed in more detail here. 2.3.1 Immunosensors
Immunosensors detect the binding event between Ab and Ag. Immobilized Abs or immunoglobulins are used to detect the presence of specific Ags,
Table 2. Biomarker overlap with corresponding diseases
Biomarkers
Corresponding diseases
α-synuclein contained in Lewy bodies Antirecoverin
Parkinson’s disease, DLB, multiple system atrophy5
Cathepsin D CRP
IGF-1
IgG and albumin in CSF
MAPK family: PKC, PLC Myelin basic protein
Polysialic acid NCAMS
Survivin
VEGF
Paraneoplastic neurological disorder (cancer-associated retinopathy,60 SCLC24 ), glioma33 Glioblastoma,35 colorectal cancer61 General marker of inflammation,55 stroke,28 multiple tumor etiologies25 Reduced levels in AD;62 elevated levels in colorectal,61 breast,63 prostate,64 lung65 cancer Breached blood–brain barrier due to CNS damage during systemic lupus erythematosus-like disease,12 traumatic neural injury, MS66 Pancreatic cancer,67 non-SCLC68 MS, HIV, PML, HTLV-1 associated myelopathy,69 traumatic neural injury Diseased muscles,70 multiple tumors including medulloblastoma,40 meningioma,44 retinal cell carcinoma,71 and choroid plexus tumors72 Elevated in medulloblastoma41 and pancreatic cancer73 —negative prognostic marker of survival Elevated in many cancers including glioma,33 colorectal, and lung adenocarcinoma74
HTLV-1: Human T-cell Lymphotropic Virus; DLB: dementia with Lewy bodies.
or conversely immobilized immunogenic peptides are used to detect the presence of specific Abs in biological fluids. These sensors minimize, and in some cases eliminate, time-consuming separation and washing steps and utilize the convenience of various physical transducers. Many immunosensors can be regenerated after immersion in acid (e.g., HCl, H2 SO4 ), base (e.g., tetraethylamine), denaturant (e.g., urea), or high salt. The regenerated probes can be reused cost-efficiently. A large class of immunosensors utilizes SPR for detection and quantitation of neurological biomarkers. For AD detection, a nanoscale optical biosensor based on SPR has been used for quantitative assay of the interaction between
BIOSENSORS FOR NEUROLOGICAL DISEASE
7
Table 3. Biosensor platforms and technology
Company
Platform probe/technology
Affymetrix Agilent Applied Biosystems Biobarcode
Target analyte type
GeneChip : DNA-based microarray DNA-based microarray, uses 60-mer probes DNA-based microarray and protein biomarker discovery Nonenzymatic amplification
Cepheid Ciphergen Luminex
DNA-based microarray ProteinChip: protein, peptide, and Ab microarrays xMAP technology: cDNA or peptide/protein/Ab-coated beads Plexigen GeneCube , geneCard : genetic-, proteomic-, and immunogenic-based Roche Diagnostics TDM technology: Ab-based handheld device Third Wave Technologies Invader technology: nucleic acid quantitation
the amyloid-β-derived diffusible ligands (ADDLs) and specific anti-ADDL Abs.75 Biacore SPR systems have been used to characterize normal and expanded polyglutamine tracts to determine pathologic threshold for HD.76 The HD trait marker is readily identifiable, but additional markers are needed for a better understanding of age of onset and course of the disease. SPR is also widely used for detection of cancer biomarkers. Many examples exist for the detection of the prostate cancer marker, prostate-specific antigen (PSA), at nano- to femtomolar levels.77,78 There are additional examples for microcantilever and amperometric detection of PSA.79–81 Another cancer diagnostic model is the piezoelectric immunosensor array for clinical immunophenotyping of acute leukemia.82 Regeneration of the probe was performed through denaturation of target in high-molar urea. In another example, picomolar levels of IL-8 were detected in human saliva in oropharyngeal cancer patients with less than 3% coefficient of variation using SPR.83 IL-8 is an indicator of inflammation and is a general marker for cancer and stress susceptibility. Ultrasonic radiation was tested for inexpensive regeneration of an Ab-based immunosensor for breast cancer Ag.84 Capable of dissociating the Ab–Ag pair for reuse of the probe, ultrasonic radiation does not require use of strong acids or bases. The same research group has done work on Ab-based multianalyte systems, which performed simultaneous detection of multiple targets.85 Often termed biochips, many versions of this technology exist. One example is a fluorescence-based nineanalyte array sensor that detected both pathogenic
Genetic Genetic Genetic, proteomic Genetic, proteomic, immunogenic, small molecules, complex targets Genetic Proteomic, immunogenic Genetic, proteomic, immunogenic Genetic, proteomic, immunogenic Drug analytes, potentially any Ag–Ab pair Genetic
bacteria and bacteria-derived Ags on one platform “without significant cross-reactivity”.86 SPR has been used to detect complex targets as well. Efficient and selective capture of peptide-labeled metastatic epithelial cancer cells from flowing blood was recently demonstrated using SPR.87 When immobilized on appropriate surfaces, these peptides could be used in both in vivo and ex vivo cell separation devices. Selective peptides that bind viruses, bacteria, or cells involved in the ND process could be incorporated into the SPR system. Conceivably, highly selective cost-effective aptamers could replace peptides in this application. Roche Diagnostics currently offers an FDAapproved, patented electrochemical immunosensor technology for therapeutic drug monitoring (TDM) in point-of-care testing (POCT) (http://www. fuentek.com/technologies/TDM2.htm).88 Designed as a plug-in for a handheld device, immobilized Abs are used to detect drug concentrations in biological samples (e.g., saliva, urine, serum). Because the detection is Ab-based, the Roche TDM technology is readily adaptable to Ab detection of ND biomarkers. 2.3.2 Microarrays
Protein- or peptide-based chips have been used for biomarker discovery. Ciphergen Biosystems, Inc. offers the ProteinChip platform for biomarker discovery and analysis. Extensive biomarker panels have been identified for determination of AD using this platform.89,90 Ciphergen protein
8
BIOSENSOR APPLICATIONS
arrays have identified a novel panel of early-stage AD biomarkers from CSF samples using surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry. Twenty-seven total markers were characterized using five different solid phase chemistries.90 A multimarker prototype assay of four markers was able to distinguish mild AD from control individuals with high sensitivity and specificity in a blinded test set. Luminex bead-based array systems allow for multiplexed detection and quantification of analytes using both nucleic acid (e.g., cDNA) and protein (e.g., Ab) complexed probes. Research using Luminex systems characterized 756 sera from cervical cancer patients. There are more than 100 different human papillomaviruses (HPVs), many of which cause proliferative diseases such as cervical cancer. In this study, simultaneous detection of Abs against 27 in situ affinity-purified recombinant HPV proteins was accomplished.91 The Luminex xMAP technology specifications indicate that the assay has the capacity for testing up to 100 different Ags in parallel per well of reaction. In May of 2005, Luminex Corporation announced that it has teamed with Zeus Scientific to offer multiplex autoimmune disease test kits. SuperArray Bioscience Corporation provides high-throughput gene expression profiling featuring Plexigen’s geneCube technology, which utilizes stacked detection arrays. The arrays can be functionalized with nucleic acids, proteins, or Abs and can be used to screen for a wide variety of targets in biological fluids. The technology can analyze hundreds of thousands of samples in days. For example, 30 geneCubes can measure the expression of “200 genes in 10 000 samples in less than 2 months” (http://www.plexigen.com/technology. htm).92 Affymetrix microarrays are the dominant nucleic acid–based array used for multigene expression profiling. A compelling example of how current array capabilities can provide genetic profiling for cancer was demonstrated by Glinsky et al.59 The research group identified an 11-gene probability-of-cancer signature based on the BMI-1 oncogene pathway. An Affymetrix microarray was used to test for the expression of these cancer-related genes. When combined with mathematical analysis of patient therapy outcome data, the authors were able to correlate the 11-gene signature to probability of survival. Furthermore,
they were able to do so across 11 different types of cancer. This same strategy is being applied to AD and other NDs to identify disease signatures. The Affymetrix GeneChip was used to identify gene expression changes following traumatic spinal cord injury in rats.93 With the help of The MathWorks, Inc. (MATLAB) algorithms to analyze the extensive data sets, a large panel of genes including caspase, multiple cathepsins, and IL-6 was identified. 2.3.3 Amplification and Quantification Technologies
One problem challenging conventional detection of early disease states is the low concentration of biomarkers in biological fluids. Many of the techniques discussed here are highly sensitive and selective, yielding impressive levels of detection (nano- to femtomolar). Directly addressing the issue of detection levels is the biobarcode system. Essentially a nonenzymatic amplification method, the biobarcode assay developed by Chad Mirkin et al. at Northwestern, has shown promise as a fast, sensitive, inexpensive, enzyme-free method for detecting tiny amounts of nucleic acid, protein, small molecules, and metal ions.94 While previous less-invasive detection of pathogenic AD markers in CSF has not been possible due to low biomarker concentrations (<1 picomolar), the barcode assay was able to detect the amyloid-β-derived AD marker in CSF at 100 fM–100 aM. Notably, the biobarcode assay when combined with a PCR step to amplify signal can detect PSA at 6 orders of magnitude higher sensitivity than conventional ELISA (3 aM vs 3 pM, respectively).95 The barcode assay has also been used for detection of the AD biomarker tau protein. Biochemical markers previously analyzed through invasive tumor biopsy or postmortem brain histology (e.g., ADDLs, prion protein PrP) might now be detectable in urine, blood, or CSF as a result of more sensitive detection like the biobarcode assay and genomics (e.g., SEPS1 gene for cytokine expression).58,75,94 Quantitation of RNAs can determine viral titer, disease progression, and therapeutic efficacy.96 The Third Wave Technologies Invader assay has been developed for detection of nucleic acids. The RNA Invader uses fluorescence resonance energy transfer (FRET)-based signal amplification for detecting RNA.97 The assay can detect
BIOSENSORS FOR NEUROLOGICAL DISEASE
fewer than 100 copies of RNA per reaction and discriminate among 95% homologous sequences (1 in ≥20 000). In biplex reaction format, the RNA Invader can analyze simultaneous expression of two genes in the same sample. The DNA Invader can be used for genotyping and gene expression monitoring without the target amplification steps required in conventional sequencing and other methods. The Invader assay has been used to monitor gene expression of detoxification enzymes including several cytochrome P450 variants and multidrug resistant enzyme (MDR1). Expression of these drug metabolizers and transporters can cause drug–drug interactions or determine efficacy of a drug treatment.98 Rapid methods for determining drug potential have been explored with the Invader assay by examining neuronal differentiation biomarkers of treated pheochromocytoma cells.99 The assay has also been used to examine expression levels of inflammatory biomarkers including IL-10 and TNF-α 100 and degenerative disease biomarkers including the AD-associated apolipoprotein E.101 The Invader technology is offered as “accurate, simple to use, scalable, and cost-effective”.102 One of the concerns with sensor technology is the time lapse between acquisition of sample and data output. All of the platforms described here can provide data output within 1 h from the application of sample onto the sensor device. Generally, the most time-consuming step is sample preparation for the device, amplification of genomic sequences, or releasing the ligand to be detected from the sample. This process may require several hours. Additional time is needed for interpretation of the data output from the device and statistical analysis. This interpretation is based upon comparing the signature elements with a database correlating a signature with a differential diagnosis. In addition, the data has to be correlated with the clinical presentation of the patient and with prior medical history. We believe that a diagnosis cannot be determined based on a single laboratory test, but must involve correlations with the clinical presentation. 2.4
Market Demand
Biosensors in general and disposable sensors in particular offer utility over traditional clinical laboratory testing methods by permitting (i) rapid
9
indication of clinical state, (ii) determination of the progression of illness, (iii) determination of a patient’s vulnerability/resilience to disease and corresponding treatment, and (iv) private selfassessment by a patient. All of these factors affect the market demand for medical sensors. Sensors that meet market potential include glucose, pregnancy, and HIV tests. The costs of the devices range from $2 (pregnancy test strip) to around $100 (glucose monitor). An individual glucose test costs only about 10¢. Not only are the sensor products available over the counter but they also provide rapid information of clinical state to the patient and health care professional. Similar to glucose monitors, ND sensors could complement disease management by monitoring effects of diet, exercise, and medication. Ideally, the tests would require only microliters of blood or small urine sample, limiting discomfort and allowing for easy assessment in POCT. Even in cases where a CSF sample is required for detection of ND analytes, the process can be faster and more sensitive than conventional testing. Using the diabetes/glucose monitor as a comparison template, an estimated 6–12 million persons in the United States have type II diabetes.103 An estimated 360 000 people have AD and over 300 000 people have Parkinson’s in the United States alone (Table 1). Many of these degenerative NDs have late onsets (over 50 years of age) and the baby boom generation now fills this age-group. This represents a significant economic driver for investment in biosensors for NDs. The market funding for pharmaceutical research and development in the central nervous system (CNS) disorder area approximates the funding for cancer and endocrine disorders and is estimated to become $15 billion by 2007.104 These areas receive about double the funding of cardiovascular disorders and infectious diseases. Factors affecting investment include the large number of persons affected by ND; the cost of testing; the cost of technology which involves the availability of reusable or disposable devices; the need for disease detection, diagnosis, and management (POCT); the need for personalized medicine (e.g., sensors for distinguishing proper morphine dosage due to the great variance in individual sensitivity); and continued discovery of biomarkers and development of disease signatures.
10
BIOSENSOR APPLICATIONS
3 CONCLUSION
Several neurological disorders, whether autoimmune or degenerative, have a variable course during progression of the disease. MS can follow a course of exacerbations and remissions, each with differing lengths of time; it can also follow a steadily progressive course. Signature elements can distinguish these patterns. HD exhibits a variable age of onset depending, in part, upon the number of triplet repeats in the genome. The progression of AD and Parkinson’s is highly variable. Parkinsonism exhibits the most variability in symptoms, rate of progression, and etiology. Sensor systems based on biomarkers highly correlated to disease states would assist in prognosis of and clinical care for these illnesses. The decoding of the human genome now permits an analysis of the relationship between phenotypic expressions of ND and the genomic correlates of that disease. Similarly correlates between individual responses to drugs and effectiveness of the drugs in treating specific diseases are now possible. For example, genes that encode detoxifying enzymes (e.g., cytochrome P450, glutathione S-transferase) and multidrug resistant pumps have been shown to affect patient response to specific therapeutic drugs and stress. Biosensor systems allow for the definition of genomic and proteomic signatures necessary for improved determination of disease susceptibility, prognosis, and treatment. Proper application of available technologies can allow for management of ND and aid in the selection of therapeutics based upon the individual genome. The age distribution of the US population in the coming two decades will significantly increase the need for ND management and treatment, and therefore the need for sensor platforms.
REFERENCES 1. X. Wang, J. Yu, A. Sreekumar, S. Varambally, R. Shen, D. Giacherio, R. Mehra, J. E. Montie, K. J. Pienta, M. G. Sanda, P. W. Kantoff, M. A. Rubin, J. T. Wei, D. Ghosh, and A. M. Chinnaiyan, Autoantibody signatures in prostate cancer. New England Journal of Medicine, 2005, 353(12), 1224–1235. Comment in: New England Journal of Medicine, 2005, 353(12), 1288–1290. 2. J. Lin and H. Ju, Electrochemical and chemiluminescent immunosensors for tumor markers. Biosensors and Bioelectronics, 2005, 20(8), 1461–1470.
3. A. Szilvas, A. Blazovics, G. Szekely, E. Dinya, J. Feher, and G. Mozsik, Comparative study between the free radicals and tumor markers in patients with gastrointestinal tumors. Journal of Physiology-Paris, 2001, 95, 247–252. 4. M. Victor and A. H. Ropper, Principles of Neurology, 7th Edn, Mcgraw-Hill, 2001. 5. V. Rachakonda, T. H. Pan, and W. D. Le, Biomarkers of neurodegenerative disorders: how good are they? Review. Cell Research, 2004, 14(5), 347–358. 6. B. Van Everbroeck, J. Boons, and P. Cras, Cerebrospinal fluid biomarkers in Creutzfeldt-Jakob disease. Review. Clinical Neurology and Neurosurgery, 2005, 107(5), 355–360, Epub 2005 Jan 12. 7. S. Sato, Y. Mizuno, and N. Hattori, Urinary 8-hydroxydeoxyguanosine levels as a biomarker for progression of Parkinson disease. Neurology, 2005, 64(6), 1081–1083. 8. L. Verdugo-Diaz, C. Morgado-Valle, G. Solis-Maldonado, and R. Drucker-Colin, Determination of dopaminereleasing protein (DARP) in cerebrospinal fluid of patients with neurological disorders. Archives of Medical Research, 1997, 28(4), 577–581. 9. Y. Curlis, C. Zhang, J. J. Holden, P. K. Loesch, and R. J. Mitchell, Haplotype study of intermediate-length alleles at the fragile X (FMR1) gene: ATL1, FMRb, and microsatellite haplotypes differ from those found in common-size FMR1 alleles. Human Biology, 2005, 77(1), 137–151. 10. K. M. Uramoto, C. J. Michet Jr, J. Thumboo, J. Sunku, W. M. O’Fallon, S. E. Gabriel, Trends in the incidence and mortality of systemic lupus erythematosus, 1950–1992. Arthritis and Rheumatism, 1999, 42(1), 46–50. 11. R. A. Sinico, B. Bollini, E. Sabadini, L. Di Toma, A. Radice, The use of laboratory tests in diagnosis and monitoring of systemic lupus erythematosus. Review. Journal of Nephrology, 2002, 15(Suppl. 6), S20–S27. 12. M. M. Sidor, B. Sakic, P. M. Malinowski, D. A. Ballok, C. J. Oleschuk, and J. Macri, Elevated immunoglobulin levels in the cerebrospinal fluid from lupus-prone mice. Journal of Neuroimmunology, 2005, 165(1–2), 104–113. 13. V. Rus, V. Zernetkina, R. Puliaev, C. Cudrici, S. Mathai, and C. S. Via, Increased expression and release of functional tumor necrosis factor-related apoptosisinducing ligand (TRAIL) by T cells from lupus patients with active disease. Clinical Immunology, 2005, 117(1), 48–56. 14. C. L. Raison, M. Demetrashvili, L. Capuron, and A. H. Miller, Neuropsychiatric adverse effects of interferonalpha: recognition and management. CNS Drugs, 2005, 19(2), 105–123. 15. J. Palace, Clinical and laboratory characteristics of secondary progressive MS. Review. Journal of the Neurological Sciences, 2003, 206(2), 131–134. 16. B. O. Fabriek, J. N. Zwemmer, C. E. Teunissen, C. D. Dijkstra, C. H. Polman, J. D. Laman, and J. A. Castelijns, In vivo detection of myelin proteins in cervical lymph nodes of MS patients using ultrasound-guided fine-needle aspiration cytology. Journal of Neuroimmunology, 2005, 161(1–2), 190–194.
BIOSENSORS FOR NEUROLOGICAL DISEASE 17. S. A. McMillan, G. V. McDonnell, J. P. Douglas, and S. A. Hawkins, Evaluation of the clinical utility of cerebrospinal fluid (CSF) indices of inflammatory markers in multiple sclerosis. Acta Neurologica Scandinavica, 2000, 101(4), 239–243. 18. A. Storstein, A. Knudsen, and C. A. Vedeler, Proteasome antibodies in paraneoplastic cerebellar degeneration. Journal of Neuroimmunology, 2005, 165(1–2), 172–178. 19. K. Endo, Advances in neuroimmunological laboratory studies on neuromuscular diseases. Review Japanese. Rinsho Byori, 2004, 52(9), 759–766. 20. E. Sueoka, M. Yukitake, K. Iwanaga, N. Sueoka, T. Aihara, and Y. Kuroda, Autoantibodies against heterogeneous nuclear ribonucleoprotein B1 in CSF of MS patients. Annals of Neurology, 2004, 56(6), 778–786. 21. E. Prat, U. Tomaru, L. Sabater, D. M. Park, R. Granger, N. Kruse, J. M. Ohayon, M. P. Bettinotti, and R. Martin, HLA-DRB5*0101 and -DRB1*1501 expression in the multiple sclerosis-associated HLA-DR15 haplotype. Journal of Neuroimmunology, 2005, 167(1–2), 108–119. 22. K. Paparounas, Anti-GQ1b ganglioside antibody in peripheral nervous system disorders: pathophysiologic role and clinical relevance. Archives of Neurology, 2004, 61(7), 1013–1016. 23. S. J. Pittock, T. J. Kryzer, and V. A. Lennon, Paraneoplastic antibodies coexist and predict cancer, not neurological syndrome. Annals of Neurology, 2004, 56(5), 715–719. 24. A. V. Bazhin, M. S. Savchenko, O. N. Shifrina, S. A. Demoura, S. Y. Chikina, G. Jaques, E. A. Kogan, A. G. Chuchalin, and P. P. Philippov, Recoverin as a paraneoplastic antigen in lung cancer: the occurrence of anti-recoverin autoantibodies in sera and recoverin in tumors. Lung Cancer, 2004, 44(2), 193–198. 25. J. Kotyza, M. Pesek, V. Bednarova, M. Terl, and B. Werle, Pleural fluids associated with metastatic lung tumors are rich in progelatinase B/proMMP-9. Neoplasma, 2005, 52(5), 388–392. 26. T. Q. Kong, C. J. Davidson, S. N. Meyers, J. T. Tauke, M. A. Parker, and R. O. Bonow, Prognostic implication of creatine kinase elevation following elective coronary artery interventions. JAMA, 1997, 277(6), 461–466. 27. E. Di Angelantonio, M. Fiorelli, D. Toni, M. L. Sacchetti, S. Lorenzano, A. Falcou, M. V. Ciarla, M. Suppa, L. Bonanni, G. Bertazzoni, F. Aguglia, and C. Argentino, Prognostic significance of admission levels of troponin I in patients with acute ischaemic stroke. Journal of Neurology Neurosurgery and Psychiatry, 2005, 76(1), 76–81. 28. L. Masotti, E. Ceccarelli, S. Forconi, and R. Cappelli, Prognostic role of C-reactive protein in very old patients with acute ischaemic stroke. Journal of Internal Medicine, 2005, 258(2), 145–152. 29. G. Patti, S. Mega, V. Pasceri, A. Nusca, G. Giorgi, E. M. Zardi, A. D’Ambrosio, A. Dobrina, and G. Di Sciascio, Interleukin-1 receptor antagonist levels correlate with extent of myocardial loss in patients with acute myocardial infarction. Clinical Cardiology, 2005, 28(4), 193–196. 30. B. Plecko, C. Hikel, G. C. Korenke, B. Schmitt, M. Baumgartner, F. Baumeister, C. Jakobs, E. Struys, W. Erwa, and S. Stockler-Ipsiroglu, Pipecolic acid as
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
11
a diagnostic marker of pyridoxine-dependent epilepsy. Neuropediatrics, 2005, 36(3), 200–205. C. G. Goetz and E. J. Pappert, Textbook of Clinical Neurology, ISBN 0-7216-6423-7, Philadelphia, WB Saunders, 1999. S. H. Landis, T. Murray, S. Bolden, and P. A. Wingo, Cancer statistics, 1999. CA: A Cancer Journal for Clinicians, 1999, 49(1), 8–31, 1. P. Sampath, C. E. Weaver, A. Sungarian, S. Cortez, L. Alderson, and E. G. Stopa, Cerebrospinal fluid (vascular endothelial growth factor) and serologic (recoverin) tumor markers for malignant glioma. Cancer Control, 2004, 11(3), 174–180. K. Somasundaram, S. P. Reddy, K. Vinnakota, R. Britto, M. Subbarayan, S. Nambiar, A. Hebbar, C. Samuel, M. Shetty, H. K. Sreepathi, V. Santosh, A. S. Hegde, S. Hegde, P. Kondaiah, and M. R. Rao, Upregulation of ASCL1 and inhibition of Notch signaling pathway characterize progressive astrocytoma. Oncogene, 2005, 24(47), 7073–7083. M. E. Fukuda, Y. Iwadate, T. Machida, T. Hiwasa, Y. Nimura, Y. Nagai, M. Takiguchi, H. Tanzawa, A. Yamaura, and N. Seki, Cathepsin D is a potential serum marker for poor prognosis in glioma patients. Cancer Research, 2005, 65(12), 5190–5194. L. A. Trojan, P. Kopinski, M. X. Wei, A. Ly, A. Glogowska, J. Czarny, A. Shevelev, R. Przewlocki, D. Henin, and J. Trojan, IGF-I: from diagnostic to triple-helix gene therapy of solid tumors. Review. Acta Biochimica Polonica, 2002, 49(4), 979–990. K. S. Hung and S. L. Howng, Prognostic significance of annexin VII expression in glioblastomas multiforme in humans. Journal of Neurosurgery, 2003, 99(5), 886–892. C. Mawrin, S. Diete, T. Treuheit, S. Kropf, C. K. Vorwerk, C. Boltze, E. Kirches, R. Firsching, and K. Dietzmann, Prognostic relevance of MAPK expression in glioblastoma multiforme. International Journal of Oncology, 2003, 23(3), 641–648. C. Dubois, D. Figarella-Branger, G. Rougon, and C. Rampini, Polysialylated NCAM in CSF, a marker for invasive medulloblastoma. French. Comptes Rendus des Seances de la Societe de Biologie et de ses Filiales, 1998, 192(2), 289–296. C. Dubois, A. Okandze, D. Figarella-Branger, C. Rampini, and G. Rougon, A monoclonal antibody against meningococcus group B polysaccharides used to immunocapture and quantify polysialylated NCAM in tissues and biological fluids. Journal of Immunological Methods, 1995, 181(1), 125–135. J. Pizem, A. Cort, L. Zadravec-Zaletel, and M. Popovic, Survivin is a negative prognostic marker in medulloblastoma. Neuropathology and applied Neurobiology, 2005, 31(4), 422–428. C. Leung, M. Lingbeek, O. Shakhova, J. Liu, E. Tanger, P. Saremaslani, M. Van Lohuizen, and S. Marino, Bmi1 is essential for cerebellar development and is overexpressed in human medulloblastomas. Nature, 2004, 428(6980), 337–341. G. V. Glinsky, O. Berezovska, and A. B. Glinskii, Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple
12
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
BIOSENSOR APPLICATIONS types of cancer. Journal of Clinical Investigation, 2005, 115(6), 1503–1521. D. Figarella-Branger, P. H. Roche, L. Daniel, H. Dufour, N. Bianco, and J. F. Pellissier, Cell-adhesion molecules in human meningiomas: correlation with clinical and morphological data. Neuropathol Appl Neurobiol., 1997, 23(2), 113–122. H. Seeger, M. Heikenwalder, N. Zeller, J. Kranich, P. Schwarz, A. Gaspert, B. Seifert, G. Miele, and A. Aguzzi, Coincident scrapie infection and nephritis lead to urinary prion excretion. Science, 2005, 310(5746), 324–326. J. R. Berger andI. J. Koralnik, Progressive multifocal leukoencephalopathy and natalizumab-unforeseen consequences. New England Journal of Medicine, 2005, 353(4), 414–416, Epub 2005 Jun 9. E. O. Major, K. Amemiya, C. S. Tornatore, S. A. Houff, and J. R. Berger, Pathogenesis and molecular biology of progressive multifocal leukoencephalopathy, the JC virus-induced demyelinating disease of the human brain. Review. Clinical Microbiology Reviews, 1992, 5(1), 49–73. J. C. Roos and T. M. Cox, Glycogen storage diseases and cardiomyopathy. New England Journal of Medicine, 2005, 352(24), 2553 author reply 2553. No abstract available. M. Karpati, E. Gazit, B. Goldman, A. Frisch, R. Colombo, and L. Peleg, Specific mutations in the HEXA gene among Iraqi Jewish Tay-Sachs disease carriers: dating of founder ancestor. Neurogenetics, 2004, 5(1), 35–40, Epub 2003 Nov 27. X. Zhao, C. Bi, and Z. Yang, Studies on the creatine kinase MM isoforms of normal and Duchenne muscular dystrophic patients. Chinese Medical Journal, 1998, 111(1), 75–77. W. Y. Ng, K. F. Lui, A. C. Thai, and J. S. Cheah, Absence of ion channels CACN1AS and SCN4A mutations in thyrotoxic hypokalemic periodic paralysis. Thyroid, 2004, 14(3), 187–190. B. J. Simpson, T. A. Height, G. Y. Rychkov, K. J. Nowak, N. G. Laing, B. P. Hughes, and A. H. Bretag, Characterization of three myotonia-associated mutations of the CLCN1 chloride channel gene via heterologous expression. Human Mutation, 2004, 24(2), 185. J. E. Curran, J. B. Jowett, K. S. Elliott, Y. Gao, K. Gluschenko, J. Wang, D. M. Azim, G. Cai, M. C. Mahaney, A. G. Comuzzie, T. D. Dyer, K. R. Walder, P. Zimmet, J. W. Maccluer, G. R. Collier, A. H. Kissebah, and J. Blangero, Genetic variation in selenoprotein S influences inflammatory response. Nature Genetics, 2005, 37(11), 1234–1241, Epub 2005 Oct 9. T. Ek, M. Jarfelt, L. Mellander, and J. Abrahamsson, Proinflammatory cytokines mediate the systemic inflammatory response associated with high-dose cytarabine treatment in children. Medical and Pediatric Oncology, 2001, 37(5), 459–464. A. Y. Wang, Prognostic value of C-reactive protein for heart disease in dialysis patients. Current Opinion in Investigational Drugs, 2005, 6(9), 879–886. X. Chevalier, B. Giraudeau, T. Conrozier, J. Marliere, P. Kiefer, and P. Goupille, Safety study of intraarticular injection of interleukin 1 receptor antagonist in patients
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
with painful knee osteoarthritis: a multicenter study. Journal of Rheumatology, 2005, 32(7), 1317–1323. S. Kopp, P. Alstergren, S. Ernestam, S. Nordahl, P. Morin, and J. Bratt, Reduction of temporomandibular joint pain after treatment with a combination of methotrexate and infliximab is associated with changes in synovial fluid and plasma cytokines in rheumatoid arthritis. Cells Tissues Organs, 2005, 180(1), 22–30. J. E. Curran, J. B. M. Jowett, K. S. Elliott, Y. Gao, K. Gluschenko, J. Wang, D. M. A. Azim, G. Cai, M. C. Mahaney, A. G. Comuzzie, T. D. Dyer, K. R. Walder, P. Zimmet, J. W. MacCluer, G. R. Collier, A. H. Kissebah, and J. Blangero, Genetic variation in selenoprotein S influences inflammatory response. Nature Genetics, 2005, 37(11), 1234–1241. G. V. Glinsky, O. Berezovska, and A. B. Glinskii, Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer. Journal of Clinical Investigation, 2005, 115(6), 1503–1521. C. E. Thirkill, A. M. Roth, and J. L. Keltner, Cancerassociated retinopathy. Archives of Ophthalmology, 1987, 105(3), 372–375. E. Skrzydlewska, M. Sulkowska, A. Wincewicz, M. Koda, and S. Sulkowski, Evaluation of serum cathepsin B and D in relation to clinicopathological staging of colorectal cancer. World Journal of Gastroenterology, 2005, 11(27), 4225–4229. T. Watanabe, A. Miyazaki, T. Katagiri, H. Yamamoto, T. Idei, and T. Iguchi, Relationship between serum insulin-like growth factor-1 levels and Alzheimer’s disease and vascular dementia. Journal of the American Geriatrics Society, 2005, 53(10), 1748–1753. J. V. Vadgama, Y. Wu, G. Datta, H. Khan, and R. Chillar, Plasma insulin-like growth factor-I and serum IGFbinding protein 3 can be associated with the progression of breast cancer, and predict the risk of recurrence and the probability of survival in African-American and hispanic women. Oncology, 1999, 57(4), 330–340. A. Wolk, S. O. Andersson, C. S. Mantzoros, D. Trichopoulos, and H. O. Adami, Can measurements of IGF-1 and IGFBP-3 improve the sensitivity of prostatecancer screening? Lancet, 2000, 356(9245), 1902–1903. D. Olchovsky, I. Shimon, I. Goldberg, T. Shulimzon, A. Lubetsky, A. Yellin, C. Pariente, A. Karasik, and H. Kanety, Elevated insulin-like growth factor-1 and insulin-like growth factor binding protein-2 in malignant pleural effusion. Acta Oncologica, 2002, 41(2), 182–187. K. P. Johnson, Cerebrospinal fluid and blood assays of diagnostic usefulness in multiple sclerosis. Review. Neurology, 1980, 30(7 Pt 2), 106–109. J. M. Summy, J. G. Trevino, C. H. Baker, and G. E. Gallick, c-Src regulates constitutive and EGF-mediated VEGF expression in pancreatic tumor cells through activation of phosphatidyl inositol-3 kinase and p38 MAPK. Pancreas, 2005, 31(3), 263–274. K. T. Chang, C. M. Tsai, Y. C. Chiou, C. H. Chiu, K. S. Jeng, and C. Y. Huang, IL-6 induces neuroendocrine dedifferentiation and cell proliferation in non-small cell lung cancer cells. The American Journal of Physiology—Lung Cellular Molecular Physiology, 2005, 289(3), L446–L453, Epub 2005 May 13.
BIOSENSORS FOR NEUROLOGICAL DISEASE 69. M. Ohta, K. Ohta, M. Nishimura, and T. Saida, Detection of myelin basic protein in cerebrospinal fluid and serum from patients with HTLV-1-associated myelopathy/tropical spastic paraparesis. Annals of Clinical Biochemistry, 2002, 39(Pt 6), 603–605. 70. D. Figarella-Branger, J. Nedelec, J. F. Pellissier, J. Boucraut, N. Bianco, and G. Rougon, Expression of various isoforms of neural cell adhesive molecules and their highly polysialylated counterparts in diseased human muscles. Journal of the Neurological Sciences, 1990, 98(1), 21–36. 71. L. Daniel, C. Bouvier, B. Chetaille, J. Gouvernet, A. Luccioni, D. Rossi, E. Lechevallier, X. Muracciole, C. Coulange, and D. Figarella-Branger, Neural cell adhesion molecule expression in renal cell carcinomas: relation to metastatic behavior. Human Pathology, 2003, 34(6), 528–532. 72. D. Figarella-Branger, H. Lepidi, C. Poncet, D. Gambarelli, N. Bianco, G. Rougon, and J. F. Pellissier, Differential expression of cell adhesion molecules (CAM), neural CAM and epithelial cadherin in ependymomas and choroid plexus tumors. Acta Neuropathologica, 1995, 89(3), 248–257. 73. M. A. Lee, G. S. Park, H. J. Lee, J. H. Jung, J. H. Kang, Y. S. Hong, K. S. Lee, D. G. Kim, and S. N. Kim, Survivin expression and its clinical significance in pancreatic cancer. BMC Cancer, 2005, 5, 127. 74. R. Cressey, O. Wattananupong, N. Lertprasertsuke, and U. Vinitketkumnuen, Alteration of protein expression pattern of vascular endothelial growth factor (VEGF) from soluble to cell-associated isoform during tumourigenesis. BMC Cancer, 2005, 5, 128. 75. A. J. Haes, L. Chang, W. L. Klein, and R. P. Van Duyne, Detection of a biomarker for Alzheimer’s disease from synthetic and clinical samples using a nanoscale optical biosensor. Journal of the American Chemical Society, 2005, 127(7), 2264–2271. 76. M. J. Bennett, K. E. Huey-Tubman, A. B. Herr, A. P. West Jr, S. A. Ross, and P. J. Bjorkman, Inaugural article: a linear lattice model for polyglutamine in CAGexpansion diseases. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(18), 11634–11639. 77. L. Huang, G. Reekmans, D. Saerens, J. M. Friedt, F. Frederix, L. Francis, S. Muyldermans, A. Campitelli, and C. V. Hoof, Prostate-specific antigen immunosensing based on mixed self-assembled monolayers, camel antibodies and colloidal gold enhanced sandwich assays. Biosensors and Bioelectronics, 2005, 21(3), 483–490. 78. F. Yu, B. Persson, S. Lofas, and W. Knoll, Surface plasmon fluorescence immunoassay of free prostatespecific antigen in human plasma at the femptomolar level. Analytical Chemistry, 2004, 76(22), 6765–6770. 79. J. H. Lee, K. S. Hwang, J. Park, K. H. Yoon, D. S. Yoon, and T. S. Kim, Immunoassay of prostate-specific antigen (PSA) using resonant frequency shift of piezoelectric nanomechanical microcantilever. Biosensors and Bioelectronics, 2005, 20(10), 2157–2162. 80. K. W. Wee, G. Y. Kang, J. Park, J. Y. Kang, D. S. Yoon, J. H. Park, and T. S. Kim, Novel electrical detection of label-free disease marker proteins using
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92. 93.
94.
13
piezoresistive self-sensing micro cantilevers. Biosensors and Bioelectronics, 2005, 20(10), 1932–1938. P. Sarkar, P. S. Pal, D. Ghosh, S. J. Setford, and I. E. Tothill, Amperometric biosensors for detection of the prostate cancer marker (PSA). International Journal of Pharmaceutics, 2002, 238(1–2), 1–9. H. Wang, H. Zeng, Z. Liu, Y. Yang, T. Deng, G. Shen, and R. Yu, Immunophenotyping of acute leukemia using an integrated piezoelectric immunosensor array. Analytical Chemistry, 2004, 76(8), 2203–2209. C. Y. Yang, E. Brooks, Y. Li, P. Denny, C. M. Ho, F. Qi, W. Shi, L. Wolinsky, B. Wu, D. T. Wong, and C. D. Montemagno, Detection of picomolar levels of interleukin-8 in human saliva by SPR. Lab on a Chip, 2005, 5(10), 1017–1023. M. C. Moreno-Bondi, J. Mobley, J. P. Alarie, and T. VoDinh, Antibody-based biosensor for breast cancer with ultrasonic regeneration. Journal of Biomedical Optics, 2000, 5(3), 350–354. M. C. Moreno-Bondi, J. P. Alarie, and T. Vo-Dinh, Multianalyte analysis system using an antibody-based biochip. Analytical and Bioanalytical Chemistry, 2003, 375(1), 120–124. C. R. Taitt, G. P. Anderson, B. M. Lingerfelt, M. J. Feldstein, and F. S. Ligler, Nine-analyte detection using an array-based biosensor. Analytical Chemistry, 2002, 74(23), 6114–6120. S. Aggarwal, S. Janssen, R. M. Wadkins, J. L. Harden, and S. R. Denmeade, A combinatorial approach to the selective capture of circulating malignant epithelial cells by peptide ligands. Journal of Biomaterials, 2005, 26(30), 6077–6086. Roche Diagnostics biosensor for therapeutic drug monitoring (TDM) in point-of-care testing (POCT); http://www.fuentek.com/technologies/TDM2.htm# techdet, 2006. L. H. Choe, M. J. Dutt, N. Relkin, and K. H. Lee, Studies of potential cerebrospinal fluid molecular markers for Alzheimer’s disease. Electrophoresis, 2002, 23(14), 2247–2251. O. Carrette, I. Demalte, A. Scherl, O. Yalkinoglu, G. Corthals, P. Burkhard, D. F. Hochstrasser, and J. C. Sanchez, A panel of cerebrospinal fluid potential biomarkers for the diagnosis of Alzheimer’s disease. Proteomics, 2003, 3(8), 1486–1494. T. Waterboer, P. Sehr, K. M. Michael, S. Franceschi, J. D. Nieland, T. O. Joos, M. F. Templin, and M. Pawlita, Multiplex human papillomavirus serology based on in situ-purified glutathione s-transferase fusion proteins. Clinical Chemistry, 2005, 51(10), 1845–1853. Plexigen geneCube Technology, North Carolina, US; http://www.plexigen.com/technology.htm, 2006. J. B. Aimone, J. L. Leasure, V. M. Perreau, M. Thallmair, and The Christopher Reeve Paralysis Foundation Research Consortium, Spatial and temporal gene expression profiling of the contused rat spinal cord. Experimental Neurology, 2004, 189(2), 204–221. D. G. Georganopoulou, L. Chang, J. M. Nam, C. S. Thaxton, E. J. Mufson, W. L. Klein, and C. A. Mirkin, Nanoparticle-based detection in cerebral spinal fluid of a soluble pathogenic biomarker for Alzheimer’s disease.
14
95.
96.
97.
98.
99.
BIOSENSOR APPLICATIONS Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(7), 2273–2276. J. M. Nam, S. I. Stoeva, and C. A. Mirkin, Bio-barcode-based DNA detection with PCR-like sensitivity. Journal of the American Chemical Society, 2004, 126(19), 5932–5933. K. Ariyoshi, S. Jaffar, A. S. Alabi, N. Berry, M. Schim van der Loeff, S. Sabally, P. T. N’Gom, T. Corrah, R. Tedder, and H. Whittle, Plasma RNA viral load predicts the rate of CD4 T cell decline and death in HIV2-infected patients in West Africa. AIDS, 2000, 14(4), 339–344. P. S. Eis, M. C. Olson, T. Takova, M. L. Curtis, S. M. Olson, T. I. Vener, H. S. Ip, K. L. Vedvik, C. T. Bartholomay, H. T. Allawi, W. P. Ma, J. G. Hall, M. D. Morin, T. H. Rushmore, V. I. Lyamichev, and R. W. Kwiatkowski, An invasive cleavage assay for direct quantitation of specific RNAs. Nature Biotechnology, 2001, 19(7), 673–676. Erratum in: Nature Biotechnology, 2002, 20(3), 307. J. B. Mills, K. A. Rose, N. Sadagopan, J. Sahi, and S. M. de Morais, Induction of drug metabolism enzymes and MDR1 using a novel human hepatocyte cell line. Journal of Pharmacology and Experimental Therapeutics, 2004, 309(1), 303–309. P. Roux, I. Menguy, S. Soubigou, J. Chinn, S. Ricard, S. Williams, J. D. Guitton, T. Tian, S. Singh, and C. Grepin, Direct measurement of multiple mRNAs in nerve growth factor-induced PC12 cells using electrophoretic tags to monitor biomarkers of neuronal differentiation in 96-well format. Assay and Drug Development Technologies, 2004, 2(6), 637–646.
100. P. Agarwal, M. C. Oldenburg, J. E. Czarneski, R. M. Morse, M. R. Hameed, S. Cohen, and H. Fernandes, Comparison study for identifying promoter allelic polymorphism in interleukin 10 and tumor necrosis factor alpha genes. Diagnostic Molecular Pathology, 2000, 9(3), 158–164. 101. R. W. Kwiatkowski, V. Lyamichev, M. de Arruda, and B. Neri, Clinical, genetic, and pharmacogenetic applications of the invader assay. Molecular Diagnosis, 1999, 4(4), 353–364. 102. M. de Arruda, V. I. Lyamichev, P. S. Eis, W. Iszczyszyn, R. W. Kwiatkowski, S. M. Law, M. C. Olson, and E. B. Rasmussen, Invader technology for DNA and RNA analysis: principles and applications. Expert Review of Molecular Diagnostics, 2002, 2(5), 487–496. 103. CDC, Surveillance for Diabetes Mellitus—United States, 1980–1989. Morbidity and Mortality Weekly Report, 1993, 42(SS-2), 1–20. 104. R. Steinbrook, Wall street and clinical trials. New England Journal of Medicine, 2005, 353(11), 1091–1093.
FURTHER READING K. Blennow, CSF biomarkers for Alzheimer’s disease: use in early diagnosis and evaluation of drug treatment. Expert Review of Molecular Diagnostics, 2005, 5(5), 661–672. http://www.emedicine.com/emerg/topic334.htm. http://www.emedicine.com/med/topic2692.htm. http://www.emedicine.com/neuro/topic624.htm.
71 Utility of Biosensors in the Pharmaceutical Industry Trevor Chapman,1 Coulton Legge2 and Ash Patel3 1 2
Drug Discovery (Neurodegeneration Research), GlaxoSmithKline, Harlow, UK Pharmaceutical Development, GlaxoSmithKline, Ware, UK and 3 Drug Discovery (Biopharmaceuticals), GlaxoSmithKline, Beckenham, UK
1 INTRODUCTION
The pharmaceutical industry has undergone a rapid transformation over the last decade, as a result of many factors and influences. Much of this change has resulted from a change in the R&D process for discovering new drug molecules that is now more akin to scientific investigation than serendipitous good fortune; all of the low-hanging fruit drug molecules have been picked. While one discouraging consequence of this is that the average cost to bring a new drug to the market has now escalated to be greater than $1 billion and takes on the order of 10 years to reach the market, our understanding of the way in which diseases function is growing at an unprecedented rate. The process of discovering drugs, while complicated, can be broken down into several key development areas (Figure 1), each of which requires access to specific knowledge and tools. The range of scientific disciplines required through this process is extensive, requiring both multi- and interdisciplinary skills. So, while biological knowledge space is very much the new science of the pharmaceutical industry, it requires access to all other disciplines. This was evident, for example, in the speed with which the coding sequence of human DNA was unraveled. It relied not just on genetic understanding, but also on
analytical instrumentation development to speed up the decoding of DNA segments. Also, highthroughput screening (HTS) developed through the introduction of high-density microtiter plates and breakthroughs in the ability to dispense low volumes of sample into them and then detect the assay results through recent developments in imaging and spectroscopy. Much of these advances can be directly attributed to the instrumentation, which enabled increased productivity and gave scientists tools that would no longer be the bottleneck in the process of drug discovery. Biosensors are one of the main tools that are assisting our knowledge of disease and how molecules can interact with targets to solicit a positive pharmacological response in a label-free environment. They can play a part in many aspects of drug discovery (Figure 1), but they are of most immediate importance in the areas of secondary screening and in the monitoring of biopharmaceutical product development (red chevrons in Figure 1), both of which will be discussed in detail in this chapter. It should be noted that although much of the current focus of the use of biosensors in an industrial setting is in the later parts of drug discovery, this should not indicate that they are of little use in early research. The fact is that the most value can be obtained in their current setting, but
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Target ID
Target validation
Screen development
Primary screening
Secondary screening
Deorphaning receptors, ligand fishing
Lead optimization
Clinical Preclinical development development Phase I-III
Production
ADME / Tox
Biomarker diagnostics, serum screening
Binding assays (protein, nucleic acids) and cell-based assays
High-information-content screening (affinities, mechanisms, kinetics)
Quality control industrial scale applications
High-throughput screening of immobilized targets and ligands Process analytical technology Biopharmaceutical product characterization, and comparability
Figure 1. Overview of the drug discovery process within the pharmaceutical industry and where biosensors can be applied. The chevrons colored red represent the part of the drug discovery process that is discussed in this chapter. It should be noted that this does not indicate any scale in terms of time, as some processes can last several times longer than others.
with time, development, and success in their current application fields, they should become more utilized across the whole process. For example, biosensors could be developed for molecular interaction analysis in supporting pathway genomics, deorphaning receptors, and for characterizing the functionality of reagents within primary screens. These applications will only gain more support and uptake once biosensor technology becomes more mature in its current applications. Primary (high-throughput) screening is performed to throw huge libraries of potential druglike molecules against targets for disease. This results in a number of compounds generating a signal that can be considered an indication of action. In most cases this signal is derived from a fluorescent label, which while having a major impact on the productivity of screening, does add steps to the process. While this approach is very much qualitative in nature, it allows the number of molecules for subsequent analysis to be reduced from hundreds of thousands (even millions) to several thousands. This reduced set can then be investigated further to increase our quantitative data and knowledge in
what is referred to as secondary screening. By nature, secondary screening involves more focused work on the action between target and molecule and thus requires access to more detailed analytical tools, biosensors forming an essential part of them. An important feature in this step is to utilize label-free systems to ensure that the measured response is truly indicative of the biological system. Another important growth area in the pharmaceutical industry has been the development of biological drug molecules, which are distinguished by being large and complex molecules rather than the more traditional small molecular weight drugs. The manufacture of biopharmaceuticals has been a major development within the pharmaceutical industry over the last decade, requiring large-scale processing equipment to generate comparatively small quantities of end product. The impact of on-line and at-line analysis of these processes, which can vary dramatically under certain changes, has resulted in the application of biosensors to process analytical technology (PAT) to ensure quality production.
UTILITY OF BIOSENSORS IN THE PHARMACEUTICAL INDUSTRY
The following sections will detail the current requirements of secondary screening and biopharmaceutical manufacture and highlight areas of current biosensor application within them. Conclusions will be drawn at the end of this chapter on the current shortcomings of biosensors, to give the reader an indication of where future developments will need to be met to expand their application field throughout the drug discovery process.
2 BIOSENSORS IN DRUG DISCOVERY SECONDARY SCREENING
The mainstay for biosensor use in pharmaceutical discovery research has traditionally been in the field of antibody characterization and interaction analysis for larger biomolecules rather than small molecular weight druglike compounds. The expansion in biopharmaceutical research in recent years has secured the value of biosensors. As an example, the Biacore A100 has been used to screen for potential therapeutic antibodies with high affinity and potency (http://www.biacore.com). This relatively new array base instrument can monitor four unpurified monoclonal antibody supernatants individually over four antigen surfaces and a control surface at the same time, so reasonable numbers of samples can be screened fairly quickly. Maximum binding responses and off-rates are used for ranking potentially useful monoclonals, since the purity and concentration of the antibodies is unknown at an early stage in screening for monoclonal supernatants. After purification of selected clones an instrument like the Biacore S100 can be used to obtain full and comparative kinetic and affinity information. Furthermore, one can check that affinity is preserved after any modifications to the antibody, such as humanization of a mouse sequence to modify the Fc region to reduce immunogenicity and toxicity. Finally epitope mapping and mutational analysis can be performed on biosensors to back up patent claims or aim to further enhance a selected antibody’s properties. In recent years the sensitivity of certain optical biosensors has improved to the extent that small molecular weight druglike molecules, typically at around 400–500 Da, can now be detected when binding to immobilized therapeutic targets without the need for labels. Prior to this, drug binding
3
was only monitored on label-free optical biosensors in less direct competition assays, where their interference on interactions between larger binding partners could be monitored, similar to the antagonist screen recently used by Vassilev et al.1 Instruments such as the Biacore S51, and the earlier Biacore 3000, have been marketed toward drug screening applications.2,3 However, it is not only sensitivity that is important in drug screening. Assay throughput is also crucial when testing large libraries of compounds. The above-mentioned systems utilize a flow delivery system across 2–4 channels, and therefore compounds are serially tested with a throughput of up to 384 tests per day. This figure is dependent on each compound test cycle time and may be reduced, for example, if time-consuming surface regeneration steps are required. Clearly this throughput is insufficient for current random compound HTS campaigns that may run over 1 million compounds. With an example hit rate of 1%, even full secondary screening would be unfeasible for 10 000 compounds. However, the information-rich data provided by screening compounds with biosensors such as the Biacore S51 (affinities, kinetics, stoichiometries of binding) can provide added value in the selection of the best candidates for further study from a more manageable number of random primary hits. Alternatively, and more usually the case, biosensors are applied to screening project compounds generated by chemists exploring structure–activity relationships around a particular chemical template. A number of other biosensor manufacturers are beginning to achieve the sensitivity obtained by Biacore and required for compound binding detection. For example, the SRU BIND (http://www.srubiosystems.com) and the Corning Epic (http://www.corning.com) are two optical biosensors that are plate based and have the potential of testing up to 384 compounds in parallel. Certainly, early work on the SRU BIND system has shown promise in providing compound binding affinities from equilibrium data.4 Akubio (http://www.akubio.com) have also been developing a multichannel biosensor that can detect compound binding and relies on an acoustic rather than optical technology for detection. It can be expected that other label-free biosensor technologies will emerge in the near future, aimed at the lucrative yet competitive drug screening market.
4
BIOSENSOR APPLICATIONS
All these systems, however, will need good automated data handling packages for correct and fast interpretation of results. If biosensors are to replace more conventional technologies used in drug discovery and compound secondary screening, then they must possess a number of advantages that will drive their increased use. One advantage that biosensor assays often have stems from their simplicity. They are often label-free assays with few components. Without the need to design and test relevant detection labels they can often be relatively quick to set up and modify if necessary. Another advantage they hold is in the elimination of false positive compound “hits” from primary HTS screens. These can originate from compound color quenching in fluorescent assays, for example. Biophysical detection systems used in many biosensors are often less susceptible to these false positives. False positives can also originate from nonspecific binding or even chemical interference with HTS assay labels and secondary reagents. Biosensor binding data can often eliminate these false positives and be used to select specific binders to target proteins rather than to other components of the primary assay. It is often possible to mimic a primary screen assay on a biosensor surface with the minimum of components, and at the same time, by exploiting the multichannel nature of many biosensors, include off-target components to which binding may be undesirable. Off-target components may for example, be nucleic acid used in a nucleic acid–associated protein target primary screen. Another off-target activity that could be excluded in parallel biosensor screening is drug binding to similar protein family members, which may lead to a toxicity liability. Indeed the same similar protein can provide an indication of a nonspecific binding mode of action and be used to eliminate detergents and “promiscuous” inhibitors. Biosensors directly measuring mass of binding components can often distinguish between “clean” interactions with a binding stoichiometry of 1 : 1 and “dirty” interactions from multisite or adsorbing nonspecific binders, detergents, DNA intercalators, and even insoluble compound aggregates coming out of solution. The later interactions can be identified by unexpectedly high maximum binding responses and complex kinetic data.
A flow system biosensor, such as the Biacore S51, can provide affinity and kinetic information on drug binding and this can be applied to build up a quantitative structural and functional relationship (QSAR) within a single compound template series under test, as used by Markgren et al.5 for HIV protease inhibitors. However, affinity data is usually the driver in selecting the most potent compounds for further development, and occasionally, kinetic information may become increasingly important. For example, if the pharmacokinetic data suggests a short half-life for a compound series, then a long off-rate may be key to success. In reality, the evidence to support such use of kinetic data alone is not usually available at such an early stage in drug discovery. Recently thermodynamic data was also used by Shuman et al.6 to characterize HIV protease inhibitors, but in a similar way the necessary structural information is rarely available for newly identified drug targets. Published examples of the use of biosensors for drug screening are increasing and have recently been reviewed by Myszka,7 Rich,8 and Comley.9 Although these examples are often on more stable targets and soluble compound series, the information provides an insight into the diversity of drug target assays that can be developed. Inhibitors to enzymes such as carbonic anhydrase II, HIV protease, and thrombin have been studied.4,10,11 The success of kinase assays is increasing with careful immobilization strategies.12,13 Screens involving proteins or drugs directly binding to nucleic acids are also possible.14–16 Receptor protein assays have been possible with some purified proteins1,17 and a few brave attempts have been made to measure direct compound binding to receptors expressed in their natural membrane environment.18 Lastly, a number of papers have focused on measuring drugs binding to the serum proteins albumin and α(1)-acid glycoprotein19 and on drugs penetrating lipid membranes,20 although biosensors are yet to routinely replace existing methods, except when additional, structural, or kinetic information is needed. As yet biosensors do not play a dominant role in the secondary drug screening environment and this is because of a number of limitations with present technology. For the most developed systems such as the Biacore S51 that have achieved the sensitivity required for small molecule work,
UTILITY OF BIOSENSORS IN THE PHARMACEUTICAL INDUSTRY
automation for compound screening and the comparative cost in protein and compound use per assay is not a hurdle. Limited throughput is a problem and this has been referred to earlier. Serial testing of compounds over the same target protein surface can create a second problem. With random compound sets under test, it is often inevitable that one nonspecific binder will irreversibly damage the test surface and spoil the remainder of a screen run. Array or plate-based approaches to screening compounds in parallel is more preferable and it is hoped that systems like the SRU BIND or Corning Epic continue to be developed. For such systems, a 384- and 1536-well-plate-based compound delivery system would be beneficial and in-well referencing for solvent effects and nonspecific binding would be a great advantage. Kinetic ranking of compounds may not be possible in a plate-based format unless a flow or mixing system were introduced. Fort´eBio have developed one such mixing system in the Octet instrument (http://www.fortebio.com). The correct immobilization of target proteins to a biosensor surface is critical in maintaining structure and activity for drug recognition and binding. Certain targets are difficult to assemble on biosensors, for example, membrane spanning proteins such as 7TM receptors, multicomponent enzymes and certain unstable proteases. Sufficient immobilized protein is also needed in order to detect direct binding of small molecular weight compounds in present biosensors with their current sensitivity. Poor developments in immobilization strategies can adversely affect the likely success of biosensors in drug discovery applications. This has been compounded by a high level of intellectual property in this area, which restricts competitors from marketing similar and successful immobilization strategies. A typical drug may need to pass through cell membranes or the blood–brain barrier before binding to a hydrophobic pocket on its target protein. For this reason, many compounds in drug screening libraries are hydrophobic by nature and require solvents such as dimethyl-sulphoxide (DMSO) to aid solubility. In fact, as a matter of routine, compounds submitted for screening in large pharma organizations often arrive as DMSO stock solutions and should be filtered after addition to running buffers or have their solubilities checked prior to test on biosensors. Biosensors employed in drug
5
discovery need to be robust to test solutions containing at least 1% DMSO. For optical biosensors affected by refractive index, it is vital that controls and calibrations are run to take into account solvent effects between samples. Biosensor technologies less affected by solvent effects, such as acoustic devices, may hold advantages in this area. There is much debate between advocates of drug-binding assays as opposed to target activity–modulation assays. Biosensor assays that measure binding only may fall into the trap of detecting too many compounds that bind but do not modulate activity. It is a possibility that too many of these false positives can make the selection of candidate drugs a very difficult task. Finally, biosensors often require expert users to be skilled in experimental design and data interpretation: biosensors are not currently a technology platform that could be considered for general use and are a long way from being considered as a “black-box”. Consequently, researchers involved in screening require detailed training, which may also be a factor in preventing biosensors playing a dominant role in drug screening. In conclusion of this section, biosensors are being used as platforms for information-rich but low throughput secondary drug screens, to confirm the activities of “hits” and prioritize leads for further development. Parallel rather than serial screening technologies are required to increase throughput and robustness if biosensors are ever to be used for high-throughput random compound screening.
3 BIOSENSORS AS A TOOL FOR BIOPHARMACEUTICAL MANUFACTURE
Biopharmaceuticals are therapeutic agents produced by recombinant DNA technology in living systems and include recombinant monoclonal antibodies, recombinant proteins, therapeutic vaccines, and gene therapy products. The development of biopharmaceuticals, compared to that of small drug molecules, is an extremely complex entity that poses its own unique challenges. Some major challenges in the industry include speed-to-market, scale up, product differentiation, and more emphasis toward outsourcing due to limited manufacturing capacity. Ultimately, the
6
BIOSENSOR APPLICATIONS
focus is toward providing patients with innovative medicines but requires creating a positive regulatory environment to facilitate timely approval of products by meeting high quality, efficacy and safety standards. Researchers must identify candidate molecules for disease targets with sufficiently high binding affinity that they can be translated into lower doses of the drug to meet safe and acceptable dosing regime for patients. Cell line development, maximizing fermentation/purification for production efficiency, scale up from laboratory to pilot/manufacturing scale, addressing capacity issues, formulation for stability, release testing to strict quality standards for safety and efficacy together with testing safety in preclinical studies are just some of the significant issues faced prior to starting a program of clinical studies. The industry is therefore reliant on new and emerging technologies to address such challenges and biosensors can fulfil some of these requirements. A selection of biosensors are either currently available or under development, and those most commonly used are based on optical surface plasmon resonance (SPR) principles. Biosensors provide an exquisite binding specificity for biomolecules with specific ligand partners. Such interactions cause changes in physical parameters (e.g., mass, enthalpy, conformation change, etc.), measured by transducers to produce a digital signal, which is directly proportional to the interaction. Following identification and selection of a candidate biopharmaceutical molecule for manufacture, recombinant DNA is transfected into a suitable cell line for expression of the relevant protein. Regulatory guidance21 requires the selection of cell clones prior to the manufacture of a cell bank, which is both labor intensive and time consuming. Thousands of potential clones require screening for high but stable expression of the therapeutic product, requiring aseptic removal of 50–100 µl supernatants from 96 well plates. However, the protein concentrations in many of the samples are too low (low µg ml−1 range) to be detected using current methods. Screening therefore tends to be biased toward high productivity samples, but rarely takes into account the quality of the product. This may be achieved through the use of biosensors. For example, Hellwig et al.22
have monitored clones after scale up into shakeflasks to produce sufficient fusion proteins to enable detection on a Biacore 2000 using ligandcoated sensor surfaces. A careful understanding of cellular function during cell line development can thus prove to be useful in monitoring cell line stability. Bionas (http://www.bionas.de) recently launched an in vitro silicon sensor chip used as an analogue for a cell culture plate to profile metabolic activity of living cells using a label-free and noninvasive method by simultaneous measurement of oxygen consumption, acidification, and even adhesion of living cells, without compromising sterility. Similarly, ACEA Bioscience Inc. (http://www.aceabio.com) introduced a revolutionary microelectronic cell sensor system, based on microelectronic cell sensor arrays integrated into the bottom of microtiter plates. The system provides quantitative measurements of the biological status of the cells (e.g., cell growth, apoptosis, and changes in cell morphology) by using electrical impedance in real-time cell electronic sensing (RT-CES). Such technologies afford a continuous monitoring of metabolic activities of cloned cells in culture plates, but as a potential application for PAT, they lack an ability to measure the quantity of expressed proteins, essential for the selection of optimal clones for manufacture of biopharmaceuticals. A key driver for the pharmaceutical (including biopharmaceutics) industry has now been introduced by the Food and Drug Administration (FDA) in the shape of a draft guidance document on “PAT – A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance”,23 to enable manufacturers to develop and implement new efficient tools for use during pharmaceutical development, manufacturing, and quality assurance, while maintaining or improving the current level of product quality assurance. PAT is considered a paradigm shift in the manufacture and control of pharmaceuticals by demonstrating process consistency. It involves timely measurements of raw materials, intermediates, and process parameters and control of key critical process and quality parameters (“risk management”) with an aim to ensure product quality. It offers a number of advantages for example, optimization of product development, improvement in product quality, and product knowledge. By adopting biosensors
UTILITY OF BIOSENSORS IN THE PHARMACEUTICAL INDUSTRY
for monitoring bioprocesses, the industry will benefit from reducing the number of batch failures, through a rationalization of in-process controls and either a reduction or elimination of batch testing of the finished product. Adapting cell lines for culturing in suspension, so that they can be grown in batch and fed-batch bioreactors with consistent media formulation and the ability to scale up is considered the most variable step in the manufacture of biopharmaceuticals and the industry can benefit from early implementation of PAT. Small but subtle changes to the culture conditions can dramatically alter post–translational modification and alter the impurity profile of the product. Although productivity of mammalian cells in bioreactors has reached the gram per liter range, opportunities still exist for improving mammalian cell systems through further advancements in production systems as well as through vector and host cell engineering and appropriate post–translational modifications such as glycosylation. More recently, a number of manufacturers have started to use spectroscopic probes (e.g., UV, IR, and fluorescence), together with biosensors and applying multivariate data analysis to better understand fermentation processes for a robust and more reliable monitoring and control strategy. However, estimation of on-line or at-line monitoring of product titers is still an issue that requires binding of specific ligands to sensor surfaces. The Spreeta chip (Sensata Technologies, http://www.sensata.com), based on SPR, coupled to a Flow Injection Analyser (FIA system) offers an opportunity to utilize biosensors for at-line monitoring of product concentration in production vessels. Bracewell et al.24 have shown that an SPR sensor with automated sample handling only requires 30 s to perform an analysis compared with an enzyme-linked immunosorbent assay (ELISA) which requires approximately 3–24 h to determine product concentration. Utility of SPR sensors for at-line monitoring is not only limited to quantitation of proteins but also offers an opportunity to determine binding kinetics of the product to its ligand. For recombinant monoclonal antibodies, immobilization of the molecule via the Fc domain (using either anti-Fc antibodies or Protein A), followed by the antigen offers a unique ability for at-line monitoring of quality through measurements of the immunoreactive fraction for a typical fermentation batch
7
analysis. Additionally, immobilization of suitable lectins with binding specificity for specific glycoforms offers a unique opportunity for continuous monitoring of post–translational modifications in cell culture systems. For off-line monitoring, recombinant proteins have traditionally relied on labor-intensive and time-consuming methodologies such as immunoassays, rapid chromatography, and nephelometry. The use of optical biosensors has been directly compared against traditional methods and offers some significant advantages in terms of speed, automation, and assay variability by Baker et al.25 In bioreactors, glucose sensors are very important, especially for fed-batch processes, to monitor the carbon source as a feeding strategy to meet metabolic demands of cells in culture. Other components such as amino acids, especially lysine and glutamine, are important markers of cell growth and protein secretion in mammalian cell cultures. Therefore, continuous monitoring of these components in media to prevent depletion of these vital components is important. Ammonia, a byproduct of mammalian culture is toxic and can inhibit cell growth. Designing of suitable biosensors to monitor such components during a typical fermentation process is essential. In this respect, De Lorimier et al.26 reported the use of bacterial periplasmic binding proteins (bPBPs), with specificity for a wide variety of small molecules. These binding proteins undergo a large, ligandmediated conformational change, which is linked to reporter functions to monitor ligand concentrations. This provides an opportunity to engineer sensitive molecules for reagentless optical biosensors for a diverse range of specific ligands (e.g., sugars, amino acids, anions, cations, and dipeptides). On-line biosensors consisting of a combination of a continuous flow microcalorimeter with a dielectric spectroscope (to monitor viable cell mass) have also been developed by Guan et al.27 Specific heat flow rate and enthalpy changes are stoichiometrically related to the net specific rates of substrates, products, and indeed to specific growth rate, and therefore a direct reflection of metabolic rate. For a batch culture of Chinese hamster ovary cells, producing recombinant human interferon-γ (IFN-γ ), total metabolic rate decreased with increasing time in batch culture, coincident with the decline in the two major
8
BIOSENSOR APPLICATIONS
substrates, glucose and glutamine, and the accumulation of the by-products, ammonia and lactate. Ultrasonic measurements have also been used for on-line monitoring of biomass by Zips.28 Formulation is pivotal for a successful biopharmaceutical product. Careful control of excipients, salt concentration, and pH is required for longterm storage of the product while maintaining safety and efficacy of the molecule. Changes in salt concentrations may either have little or a dramatic impact on the binding affinity for monoclonal antibodies. Reduced sensitivity to salt concentrations suggests that electrostatic interactions may be relatively less important in the overall binding affinity. Similarly, changes in pH can significantly influence binding characteristics (association and dissociation rates) and affinity binding by 8–20fold within a pH range 5.5–8.5.29 Biosensors offer an opportunity to rapidly analyze numerous buffer conditions in parallel with antibody characterization and aid in the selection of optimal formulation conditions. They also offer an ability to screen stability when binding of the product to its ligand may be the only relevant bioassay, which closely mimics mode of action. Recently, Biacore C was specifically designed for rapid concentration measurements and meets high standards of method validation and good manufacturing principals (GMP) demands by regulatory agencies. A significant challenge for the biopharmaceutical industry occurs during scale up, which is currently being addressed through the “Design for Manufacture” initiative throughout the pharmaceutical industry. Changes in scale must be carefully monitored to ensure that the product purity, protein structure, concentration, and potency remain comparable. Products may contain new impurities with an altered quality, safety, stability, and efficacy profile. This frequently requires a detailed physicochemical, conformational, and biological characterization of the product before and after scale up. Characterization of proteins is considered far more challenging than that of small molecules. Large molecules tend to be complex with varied structures and are frequently sensitive to temperature, pH, and isotonicity, changes in which can result in loss of higher order structure or formation of aggregated structures under suboptimal conditions. Glycosylation also contributes toward the heterogeneity of the molecule. Good and robust
analytical data is required to demonstrate pharmaceutical equivalence between products from different batches. Such supporting data is essential to underwrite changes to the process during development and to provide a high degree of confidence to the regulatory authorities. This requires sophisticated analytical methods to demonstrate comparability and a detailed characterization strategy, which requires new tools, technologies, and more complex assays. Measurements of immunoreactive fraction, affinity, association and dissociation rates, and enthalpy changes are powerful characterization techniques offered by optical biosensors. Additionally, determination of potency is a key measure of the final active structure, which cannot always be determined using physicochemical characterization methods. Effective potency assays often require cell-based assays to monitor functional biological activity. During a comparability study, it is essential to determine changes in the native structure of the protein, which can have a direct effect on the biological activity of the molecule. The technology commercialized by Biacore offers a potential to identify changes in the native structure of the molecule through epitope mapping and aid in comparability studies. While utility of biosensors for potency determination is less extensive, ACEA’s RT-CES technology (mentioned earlier) may be useful and is noninvasive and harmless for cells. Cells cultured in individual microtiter plates for bioassays can be monitored continuously and provide a quantitative measurement of functional activity (e.g., cell proliferation, cytotoxicity profiling, cell adhesion, functional analysis of growth factor/death receptor, etc.). In some situations, the key mode of action may simply be a binding event (i.e., monoclonal antibody binding to specific proteins in serum). Under this circumstance, determination of immunoreactive fraction analysis alone may be considered as a true functional activity assay. Routine immunogenicity testing is also used as a quality control test to demonstrate batch-to-batch consistency for traditional vaccines (tetanus and diphtheria toxoids). Although regulatory authorities expect animal testing to demonstrate potency, the biosensor offers an attractive opportunity for in vitro testing of immunogenicity. Protein therapeutics inevitably induce an immune response and while such a response is undesirable, it can reduce efficacy and in extreme
UTILITY OF BIOSENSORS IN THE PHARMACEUTICAL INDUSTRY
cases lead to a development of a life threatening immune reaction. Emphasis is therefore placed on testing of immunogenicity at early stages of product development. This involves early detection of antibodies (either binding and or neutralization) against the therapeutic protein in preclinical and clinical studies. Measurement of the antibody response and biomarker is now a regulatory requirement during the development of the therapeutics and post–marketing surveillance of immunogenicity of protein therapeutic is an FDA requirement. Swanson et al.30 reported a comparison between radioimmune precipitation, ELISA, biosensor immunoassay, and biological assay for the detection, quantitation, and characterization of antibodies against recombinant human Erythropoietin in patient samples. A combination of biosensor-based immunoassay (for detection of low-affinity antibodies) together with the bioassay (to monitor neutralizing activity) was recommended. More recently, introduction of the Biacore T100/A100 systems to detect an immune response by characterizing serum antibodies has made this strategy more practical. In conclusion, while the utility of biosensors to aid biopharmaceutical product development has been extensive, there are still some areas (e.g., detectors for continuous purification process with feedback controls) that need to be explored and further developed.
4 CONCLUSIONS
The pharmaceutical industry is currently undergoing a great deal of transformation across many areas of research and development. The drivers for this are multitude, but are generally related to the costs associated with discovery and development of new drug candidates and how these are passed on to the end customer, who could be the patient, the doctor prescribing the medication, or the healthcare practice and/or insurance company who pays the bill. The R&D process is undergoing an industrialization in order to establish improved productivity through the use of new technologies. However, all this has to be done while still maintaining equivalent safety concerns for the final patient—the regulatory bodies police the industry and will continue to push pharmaceutical firms to engage any new methods that will
9
ensure patient safety and drug efficacy. With this in mind, biosensors, which have been explored for a number of years, offer the potential to bring quantitative assessment to what has traditionally been an experience-based qualitative process. This leads to improved understanding and increased knowledge of molecular interactions in biological systems. However, current biosensor platforms have suffered a number of drawbacks that have limited their increased uptake. Two intimately linked variables, that are yet to be fully explored in the development of biosensors, relate to speed of analysis and throughput. While many biosensor systems operate much more rapidly, in comparison to most incumbent techniques, they have always suffered when they are expanded to high throughputs. Higher throughputs are required because even if speeds of analysis are reduced, one still has to overcome the practical situation of preparing samples and being ready for the eventuality that a sensor is poisoned or requires regeneration. Thus, the need to combine these two factors is very strong and once accomplished will undoubtedly open up greater scope for biosensor implementation. It is also important to note that in doing this, one must maintain the unique advantage that biosensors have of being quantitative. Should this be lost then they may simply become a new screening platform, in competition with others. The unique property of generating knowledge should not be lost, but through the development of speed and throughput, biosensors should make the transition from secondary to primary screening. It also follows from this that current biosensor platforms come in a wide variety of different platforms and do not operate on any standard, in comparison to HTS where the microtiter plate is evident. This reduces the flexibility of biosensors when considering the aspects of multiplexing between competing technologies. Standardization can be even more of a problem in the PAT arena where the concept of plug-andplay is very much the requirement for analytical systems. The same issue used to be true in conventional screening where one had to invest in different instruments for different analysis techniques, for example, fluorescence and absorbance, but now this is not the case—a single instrument can be bought which not only incorporates multiple optical sensing schemes but can
10
BIOSENSOR APPLICATIONS
also include integrated liquid dispensing to aid in kinetic studies. The biosensor community needs to be aware of this and consider the possibility of developing standard platforms for implementation. In addition to this, instrumentation and control will have to be further developed that will enable a reduction in the skills required to operate—the concept of the black-box instrument is an essential requirement for future uptake across increased applications and use by multiple users, rather than individual experts in support groups. On a final note, it is essential to remember that virtually all biosensor platforms require a degree of materials processing. These processes are an essential component of the system, often requiring the most development for successful implementation. Material linkage to whichever transduction technique is used can often be the difference between success and failure, and as such has attracted a great deal of intellectual property protection through patents. Thus, further developments in novel materials will be required that enable close coupling and analysis of biological responses. These will have to take into account the real life application scenarios for biosensors; samples will poison the sensors, requiring regeneration and solvents, and impurities will be present that were previously needed to be eliminated. Overcoming these issues would normally require an additional process in the already timeconsuming sample preparation step, but biosensor platforms that are developed and can overcome these limitations will have increased scope in their application. The previous sections have given an insight into how biosensors are currently being targeted in the two areas of drug discovery that can establish the most value from their current use. And, with further advancements in their current limitations, identified and discussed in the preceding text, their scope will widen and biosensors will become more mainstream within the industry. Biosensors hold a great deal of potential, and given their intimate link to the understanding of disease and ability to monitor biological processes, they should continue to expand across the industry and become common tools of use, rather than expert-driven instrumentation systems.
REFERENCES 1. L. T. Vassilev, B. T. Vu, B. Graves, D. Carvajal, F. Podlaski, Z. Filipovic, N. Kong, U. Kammlott, C. Lukacs, C. Klein, N. Fotouhi, and E. A. Liu, In vitro activation of the p53 pathway by smallmolecule antagonists of MDM2. Science, 2004, 303, 844–848. 2. D. G. Myszka, Analysis of small-molecule interactions using Biacore S51 technology. Analytical Biochemistry, 2004, 329, 316–323. 3. D. G. Myszka and R. L. Rich, Implementing surface plasmon resonance biosensors in drug discovery. Pharmaceutical Science and Technology Today, 2000, 3(9), 310–317. 4. B. T. Cunningham, P. Li, S. Schulz, B. Lin, C. Vaird, J. Gerstenmaier, C. Genick, F. Wang, E. Fine, and L. Laing, Label-free assays on the BIND system. Journal of Biomolecular Screening, 2004, 9, 481–490. 5. P. O. Markgren, M. T. Lindgren, K. Gertow, R. Karlsson, M. Hamalainen, and U. H. Danielson, Determination of interaction kinetic constants for HIV-1 protease inhibitors using optical biosensor technology. Analytical Biochemistry, 2001, 291, 207–218. 6. C. F. Shuman, M. D. Hamalainen, and U. H. Danielson, Kinetic and thermodynamic characterization of HIV-1 protease inhibitors. Journal of Molecular Recognition, 2004, 17, 106–119. 7. D. G. Myszka and R. L. Rich, SPR’s high impact on drug discovery. Drug Discovery World, 2003, Spring, 49–55. SPR impact in drug discovery. 8. R. L. Rich and D. G. Myszka, Why you should be using more SPR biosensor technology. Drug Discovery Today. Technologies, 2004, 1, 301–308. 9. J. Comley, Label free detection: new biosensors facilitate broader range of drug discovery applications. Drug Discovery World, 2005, 6, 63–74. 10. Y. S. Day, C. L. Baird, R. L. Rich, and D. G. Myszka, Direct comparison of binding equilibrium, thermodynamics, and rate constants determined by surface- and solution-based biophysical methods. Protein Science, 2002, 11, 1017–1025. 11. R. Karlsson, M. Kullman-Magnusson, M. D. Hamalainen, A. Remaeus, K. Andersson, P. Borg, E. Gyzander, and J. Deinum, Biosensor analysis of drug-target interactions: direct and competitive binding assays for investigation of interactions between thrombin and thrombin inhibitors. Analytical Biochemistry, 2000, 265, 340–350. 12. D. Casper, M. Bukhtiyarova, and E. B. Springman, A Biacore biosensor method for detailed kinetic binding analysis of small molecule inhibitors of p38 ∝ mitogenactivated protein kinase. Analytical Biochemistry, 2004, 325, 126–136. 13. H. Nordin, M. Jungnelius, R. Karlsson, and O. P. Karlsson, Kinetic studies of small molecule interactions with protein kinases using biosensor technology. Analytical Biochemistry, 2005, 340, 359–368. 14. R. L. Chapman, T. B. Stanley, R. Hazen, and E. P. Garvey, Small molecule modulators of HIV Rev/Rev response element interaction identified by random screening. Antiviral Research, 2002, 54, 149–162.
UTILITY OF BIOSENSORS IN THE PHARMACEUTICAL INDUSTRY 15. S. H. Verhelst, P. J. Michiels, G. A. van der Marel, C. A. van Boeckel, and J. H. van Boom, SPR evaluation of various aminoglycoside-RNA hairpin interactions reveal low degree of selectivity. Chembiochem, 2004, 5, 937–942. 16. R. Gambari, G. Feriotto, C. Rutigliano, N. Bianchi, and C. Mischiati, Biospecific interaction analysis of low-molecular weight DNA-binding drugs. Journal of Pharmacology and Experimental Therapeutics, 2000, 294, 370–377. 17. P. Debnam, P. Huxley, I. R. Matthews, D. Thrige, and J. Abery, Screening lead CD80 inhibitors. Current Drug Discovery, 2004, 25–29 January issue www.liebertonline.com/doi/pdf/10.1089/adt.2004.2.407. 18. M. A. Cooper, Advances in membrane receptor screening and analysis. Journal of Molecular Recognition, 2004, 17, 286–315. 19. S. Cimitan, M. T. Lindgren, C. Bertucci, and U. H. Danielson, Early absorption and distribution analysis of antitumor and anti-AIDS drugs: lipid membrane and plasma protein interactions. Journal of Medicinal Chemistry, 2005, 48, 3536–3546. 20. Y. N. Abdiche and D. G. Myszka, Probing the mechanism of drug/lipid membrane interactions using Biacore. Analytical Biochemistry, 2004, 328, 233–243. 21. International Conference on Harmonisation: Quality Guideline ICH-Q5b – Quality Of Biotechnological Products: Analysis Of The Expression Construct In Cells Used For Production Of R-DNA Derived Protein Products, which can be accessed through the ICH website at http://www.ich.org. 22. S. Hellwig, F. Robin, J. Drossard, N. P. G. Raven, C. Vaquero-Martin J. E. Shively, and R. Fischer, Production of carcinoembryonic antigen (CEA) N-A3 domain in Pichia pastoris by fermentation. Biotechnology and Applied Biochemistry, 1999, 30, 267–275.
11
23. This guidance document can be accessed through the FDA Center for Drug Evaluation and Research website at http://www.fda.gov/CDER/GUIDANCE/6419fnl.htm. 24. D. G. Bracewell, R. A. Brown, A. Gill, and M. Hoare, Monitoring and control of bioproducts from conception to production in real-time using an optical biosensor. Chemical Engineering and Technology, 2001, 24(7), 25–31. 25. K. N. Baker, M. H. Rendall, A. Patel, P. Boyd, M. Hoare, R. B. Freedman, and D. C. James, Rapid monitoring of recombinant protein products: a comparison of current technologies. Trends in Biotechnology, 2002, 20(4), 149–156. 26. R. M. De Lorimier, J. J. Smith, M. A. Dwyer, L. L. Looger, K. M. Sali, C. D. Paavola, S. S. Rizk, S. Sadigov, D. W. Conrad, L. Loew, and H. W. Hellinga, Construction of a fluorescent biosensor family. Protein Science, 2002, 11(11), 2655–2675. 27. Y. Guan, P. M. Evans, and R. B. Kemp, Specific heat flow rate: An on-line monitor and potential control variable of specific metabolic rate in animal cell culture that combines microcalorimetry with dielectric spectroscopy. Biotechnology and Bioengineering, 1998, 58(5), 464–477. 28. A. Zips and U. Faust, Determination of biomass by ultrasonic measurements. Applied and Environmental Microbiology, 1989, 55, 1801–1807. 29. Early kinetic screening of hybridomas for confident antibody selection using Biacore A100: An application note (number 84) provided through the Biacore website at http://www.biacore.com/lifesciences/technology/ application notes/index.html. 30. S. J. Swanson, J. Ferbas, P. Mayeux, and N. Casadevall, Evaluation of methods to detect and characterize antibodies against recombinant human erythropoietin, Nephron Clinical Practice, 2004, 96, c88–c95.
72 Glucose Measurement Within Diabetes via ‘‘Traditional’’ Electrochemical Biosensors Elizabeth A. H. Hall Institute of Biotechnology, University of Cambridge, Cambridge, UK
1 INTRODUCTION1 – 8
Elevated blood glucose levels caused either by an inability to produce sufficient insulin or by failure to use insulin in regulation of glucose affect an increasing proportion of the population in the developed and developing world. The condition, known as diabetes mellitus, is diagnosed in >17 million people in the United States. Type 2 diabetes has reached epidemic levels in Asia, where younger people are being affected, and 194 million people worldwide have diabetes. Causes attributed to this increase include poor nutrition and fast food culture, obesity, and sedentary lifestyle. By 2025, the International Diabetes Foundation estimates 333 million people will have diabetes, equivalent to the rate currently seen in the United States repeated worldwide (Table 1), making diabetes one of the most important international health issues. The inability to control blood glucose leads to hypoglycemia (low blood glucose) or hyperglycemia (excessive blood sugar levels). The former causing mental confusion, convulsions, or even coma and death whereas the latter results in a wide range of long-term microvascular and neuropathic complications due to abnormally high levels of protein glycosylation.
The discovery of insulin, in 1922, and the development of a self-monitoring glucose test kit in 1978 mark events that enabled significant advances in the management of diabetes mellitus in the twentieth century. Self-monitoring of blood glucose levels, allowed diabetics to adjust treatment regimens and achieve more normal blood glucose levels and as a result of data from different trails in the early 1990s (e.g., the Diabetes Control and Complications Trial, released in 19939 ) in which intensive insulin therapy and self-monitoring of blood glucose were shown to give better glycemic control, self-monitoring of blood glucose levels has become the standard of care. The original measurement technology available for home use was a urine glucose test strip, limited to diagnosing hyperglycemia on the basis of the chromogenic reduction of a copper solution by glucose and other reducing sugars. This was superseded by a glucose biosensor that has traditionally used the enzyme glucose oxidase (GOx ). The key feature of GOx, enabling it to be used in an electrochemical biosensor is that it is a redox enzyme. Redox enzymes are so named because they contain a cofactor or prosthetic group that contains a redox system. A common group of redox proteins are the flavoproteins and there are about 80 different enzymes containing: flavin adenine dinucleotide
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Table 1. Incidence of diabetes assuming the current rate of incidence in the United States is projected worldwide
Region North America Central America Caribbean South America Northern Europe Western Europe Central Europe Eastern Europe SW Europe Southern Europe SE Europe Northern Asia Central Asia Eastern Asia Southwestern Asia Southern Asia Southeastern Asia Middle East Northern Africa Western Africa Central Africa Eastern Africa Southern Africa Oceania TOTAL
Incidence
monitor blood glucose levels in diabetics due to its catalytic specificity for the oxidation of glucose:
Population
25 360 167 431 122 873 1 171 369 19 913 300 229 291 3 897 960 17 705 226 300 988 901 1 171 072 19 908 270 9 102 581 154 743 914 9 142 561 155 202 055 12 310 147 209 272 527 3 727 481 63 367 202 4 041 470 68 705 006 3 011 101 51 188 794 161 841 2 751 314 2 856 803 48 565 676 89 833 064 1 527 162 188 4 052 583 68 893 918 83 306 574 1 416 211 830 29 834 507 507 186 716 10 630 621 180 720 662 7 111 597 120 897 168 4 293 681 67 817 637 4 696 275 79 836 729 10 299 076 175 084 338 4 290 175 81 933 044 1 725 130 29 327 241 340 064 393 5 784 699 263
(FAD) and flavin mononucleotide (FMN). The flavin unit is very strongly associated with the protein: covalently bound to the amino acids of the protein or held by H-bonding and weaker forces. The electrochemistry of the redox group from these enzymes can be shown by examining the voltammetric i–V (current–voltage) curves for their respective prosthetic groups. For example, for FMN (Figure 1) the process occurs via a semiquinoid free radical intermediate. Depending on pH and measurement conditions, the i–V curve can reveal the charge transfer (CT) as one twoelectron step or two one-electron steps. Embedded within the flavin enzymes, the redox potential for the FMN or FAD may vary by more than 500 mV from one enzyme to another, according to the effect of the association forces with the protein. The class of enzymes known as oxidoreductases, which include GOx, are electron transfer agents that participate in CT pathways culminating in molecular oxygen. GOx (glucose 1-oxidase or β-D-glucose:oxygen-1-oxidoreductase, EC 1.1.3.4), a globular protein 2.5 × longer than its diameter is a flavin enzyme with molecular mass of 150–180 kDa, and has been extensively used to
O
O O
O + O2
O O
O
O
β-D-glucose
O
Glucose oxidase O
O
+ H2O2
O D-glucono-1,5-lactone
(1) GOx was discovered in 1928, the year before penicillin was isolated and is probably the most investigated and used enzyme for biosensor applications. In principle GOx is ideally suited for measurement of glucose, since the number of electrons used in the reduction of FAD during the glucose oxidation process is directly related to the amount of glucose consumed or the concentration of glucose present (Figure 2). However, the FAD group of GOx is deeply embedded within a protective protein matrix (Figure 3), so that the matrix or glycoprotein shell surrounding the redox site creates an effective kinetic barrier for electron transfer. Direct electron transfer between protein and an electrode is controlled mainly by three factors10 : • reorganization energies, • potential differences and orientations of the redox-active sites involved in each oxidation state, and • distances between redox-active sites and CT agent/mediator. Thus, glucose oxidase cannot get close enough to the electrode for direct electron transfer to occur. The protein is in the way. This dilemma was solved first by Leyland Clark.
2 CLARK OXYGEN AND GLUCOSE ELECTRODES11 – 13
An important early glucose biosensor was based on the Clark oxygen electrode developed in 1950s primarily for blood-gas measurements. This exploits the reduction of oxygen at a cathode: O2 + 4H+ + 4e → 2H2 O
(2)
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
3
I (µA) 0.3
A
B
C 0.2
0.1
−0.6
−0.4
0 0
−0.2
0.2 0.4 V versus SCE
−0.1 −0.2 −0.3
(a) R N
R N
O
R H N
N
O
e−, H +
H N
O
e−, H +
NH
NH N
N
(b)
N
NH N H
O
O
O
Figure 1. (a) FMN electrochemistry (A) pH13.4; (B) pH 8.0; (C) pH 1.0; (b) FMN redox pathways.
O
H N
CH3
N
CH3
HN O
FADH2 N H
Electrons for reoxidation to FAD
Gluconolactone
R + O2
O
Two electrons per glucose molecule consumed
GOxred
OH O H N
CH3
N
CH3
HN O
4a-Hydroperoxy FAD N
R − H2O2 O N HN O
CH3
Glucose
FAD N
N R
CH3
GOxox
Figure 2. Redox pathway in GOx associated with glucose oxidation. The electrochemical glucose biosensor needs to be able to monitor the number of electrons used in the FAD/FADH2 redox process.
4
BIOSENSOR APPLICATIONS
(a)
(b) Figure 3. The glucose oxidase (GOx) E.C.1.1.3.4 (a) homo dimer from data in the protein data bank (PDB); 3D image of structure of PDB code 1gpe (b) one GOx protein monomer showing the deeply embedded FAD site surrounded by the protein shell. From data in the PDB 3D image of structure of PDB code 1gal.
As can be seen in Figure 4 the four-electron reduction (n = 4) can be measured on the diffusion-controlled plateau of a Pt electrode at a potential of approximately ∼ −650 mV relative to Ag/AgCl. The Clark electrode is immersed in a simple electrolyte solution (e.g., KCl) and separated from the sample by a semipermeable membrane that allows diffusion of oxygen. Since blood contains many other electroactive species that could interfere with the measurement, this semipermeable membrane also acts to separate the sample from the internal electrolyte solution. A
steady-state current, i, for the electrode is obtained, which depends on the partial pressure of oxygen (PO2 ) given by: i = nF
Pm PO2 b
(3)
where F is Faraday’s constant, Pm is the permeability of O2 in the membrane, and b is the membrane thickness. From this oxygen electrode, Clark and Lyons went on to describe the first biosensor—the
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS I–V curves
5
Calibration
Relative current output (I )
% Oxygen = 21 17 12
7
1.5 0 (a)
0.2 0.4 0.6 0.8 Negative bias potential (V)
0 (b)
5
10 15 % Oxygen
20
Figure 4. Oxygen reduction waves measured by linear sweep (i–V ) voltammetry (a) and the resultant calibration plot (b). Potentials measured versus Ag/AgCl.
glucose enzyme electrode. This contained an embedded oxygen electrode within a concentrated solution of the enzyme glucose oxidase and was used to measure glucose as part of a study into continuous patient monitoring in the operating room during surgery. The principle involved is already demonstrated by examination of equation (1): the enzyme-catalyzed oxidation of glucose consumes oxygen. By placing GOx, in the electrolyte solution between the membrane and the oxygen electrode, Clark found that the concentration of glucose could be monitored by measuring the decrease in oxygen tension resulting from the enzyme reaction (equation 1). In the early designs, GOx was held between two semipermeable membranes, wrapped around the end of a cylinder, which contained an internal solution with the oxygen sensing and reference electrodes. Alternatively, equation (1) also reveals that glucose concentration could be correlated with production of hydrogen peroxide, which conveniently can be oxidized at a potential of approximately +0.6 V versus Ag/AgCl. This enables a current measurement for hydrogen peroxide to be calibrated for glucose concentration. After refinement, this latter approach became the basis for the first commercial instrument developed by Yellow Springs Instruments (YSI) in the early 1970s. YSI instruments have retained this modus operandi and their glucose measurement still follows this principle. The membranes contain three layers: for
example, the outer porous polycarbonate, limiting the diffusion of glucose from the sample into the middle enzyme layer, preventing the reaction from becoming enzyme limited. The third internal layer, for example cellulose acetate, permits hydrogen peroxide diffusion to the electrode, but blocks many electrochemically active compounds that could interfere with the measurement (Figure 5). This remains a successful laboratorybased instrument with autocalibration, reuse of the enzyme membrane, and capability for highthroughput batch measurement. It has not been designed for the diabetic wishing to monitor glucose levels several times a day in their own home or discretely at work or in a more public place. It is certainly not portable. Furthermore, interference effects—like other electroactive species arriving at the working electrode contributing to the observed current, giving an erroneous result—demand the careful choice of membrane, electrode material, and applied potential. The YSI multilayer membrane is thus not a viable solution for a disposable, noncalibrating instrument designed for the self-testing market. The required self-test system needs to be small, cheap, and portable, but the fundamental and essential requirement of any self-test assay method is accuracy. System calibration by the user is eliminated, but the sensor signal must still indicate the blood glucose concentration within a specified error. The reported concentration must be reliable
6
BIOSENSOR APPLICATIONS Cellulose acetate H2O2
Polycarbonate H2O2
H2O2
O2
H2O2
H2O2
Glucose
H2O2
O2
O2
Glucose
Glucose O2
Glucose O2
Glucose
Pt electrode
O2
O2
Glulose oxidase
O2 Glucose
Glucose O2
Figure 5. Construction of the YSI glucose amperometric biosensor.
H2O2
GOxox
Glucose
Ascorbic acid O2
Gluconolactone
GOxred
Peroxide
0.08 0.07 Current (mA)
Electrode
H2O2 is oxidized at an electrode, giving a current proportional to glucose
Acetaminophen Oxidation of interfering substances Uric acid producing errors in the current signal
0.06 0.05
At this potential measure ascorbate Ascorbate
0.04 0.03
At this potential measure ascorbate + peroxide
0.02 0.01 0 0.2
(a)
0.4
0.6 0.8 Potential (V )
(b)
1
Ascorbate + glucose
30
mA
25 50 mV s−1
20 15 10
Glucose
5 −0.1 (c)
0 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
E (V ) versus Ag/AgCl
Figure 6. (a) Interference at the measuring potential for hydrogen peroxide by common electroactive species present in blood samples. i–V cyclic voltammograms for (b) ascorbate and hydrogen peroxide showing how ascorbate can be separated from peroxide, but peroxide cannot be separated from ascorbate. (c) Measurement of glucose using a membrane GOx electrode in the presence and absence of ascorbate.
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
for the user and the user must not be required to make further judgments about its accuracy before acting on the result. Figure 6 demonstrates the problem of electrochemical interference by some common electroactive species. The issue is clear: hydrogen peroxide is oxidized at a higher potential than many interferents and thus at the potential required to perform the peroxide assay, the current measured (Figure 6b and c) potentially leads to falsely high readings. Accordingly, a key consideration is to lower the measuring potential below that for the interferents. Clearly, this creates a problem if hydrogen peroxide is the measurand, but the redox potential for FMN (Figure 1) suggests that it should be possible to reoxidize the enzyme at a lower potential, if the problem of achieving direct electron transfer to the protein can be overcome. There are several ways of achieving this.
3 ALTERNATIVE OXIDIZING SUBSTRATES/MEDIATORS14 – 24
The action of GOx is sometimes called a pingpong mechanism that involves two molecules of FAD per GOx. This describes the mechanism by
which an oxidase enzyme moves from the fully oxidized state to the fully reduced form and back to an oxidized state in a catalytic cycle (Figure 6a), and for GOx has been described according to Michaelis–Menten kinetics: d[S]t k2 [E][S]t = dt [S]t + Km
(4)
where [S] is the substrate (glucose), [E] enzyme concentration, and Km the Michaelis–Menten constant. The reduced GOx normally forms a complex with an electron acceptor (such as O2 , Figure 8a), regenerating the active, oxidized form of the enzyme. However, there is precedent for other oxidizing substrates in addition to oxygen (Figure 7), such as quinones (pH 5.6) and indophenols (acidic pH), diamines, ferrocenes, ferricyanide, methylene blue, meldola blue, phenoxazines, tetrathiafulvalene, tetracyanoquinodimethane and benzyl viologen (pH 7.5), tris(2,2 -bipyridine) cobalt(III) perchlorate, and so on, so the possibility of using an alternative electron acceptor or so-called mediator offers a clear advantage in a glucose test strip, if the measuring potential can be lowered. An enzyme mediator is thus a redox couple that gives efficient and rapid electron transfer to or from the enzyme. However, it has to be remembered
Medred
GOxFAD
Medox
GOxFADH2
Glucose
Gluconolactone
(a)
1 µA Fe
e−
7
FC+
Glucose GOX
Electrode surface
+0.3 V
(b)
Reagents layer
FC
GOX
Mediator = Ferrocene (Fc)
Fc/Fc+ + GOx + Glucose
2e− Fc/Fc+ + GOx
GOX Gluconolactone Sample
0 (c)
0.1 0.2 0.3 0.4 0.5 Potential versus SCE
Figure 7. (a) The glucose oxidase redox system coupled with a mediator to shuttle electrons between enzyme and electrode. (b) Compound electrode components with layer on the electrode containing both enzyme and mediator. (c) Cyclic voltammogram of ferrocene/ferrocenium redox couple, recorded in the presence of GOx and in the absence and presence of glucose.
8
BIOSENSOR APPLICATIONS Electrode
k1 Eox + S
EoxS
k−1 Ered + Medox
k3 k4
Ered + O2
k2
Ered + P
Enzyme
Solution
1/2O2 O2
2e−
Eox + Medred
KP P
Ered
H2O2
Eox + H2O2
P
DM
KM Med
Medox
DO O2
Medred
Eox
(a)
P
(b)
S
DS
KO
KS S
Med O2 S
d
12
4
2.5 2.2 1.9 1.6 1.3 1 0.7 0.4 0.1
100 80 60 40 20 0
Current (%
In air
6
2
In oxygen
0 0
2
4 6 Glucose (mM)
8
10
(c)
)
In nitrogen
8
k 3/k 4
Current (µA)
10
0
4
(d)
20 24 28 32 36 8 12 16 Glucose (mM)
Figure 8. (a) Enzyme reaction pathways; (b) scheme of an enzyme layer biosensor with diffusion into the layer of thickness d; (c) calibration curve for glucose using a mediator with rate constant 105 l mol−1 s−1 reaction with glucose oxidase; and (d) effect on the calibration curve for glucose depending on k3 /k4 .
that oxygen may still be present in the sample, so that the mediator must compete efficiently with the oxygen to reoxidize the enzyme, else the current measured at the mediator’s oxidation potential will not represent the total glucose concentration (Figure 8c).
DO
= DM
3.1
d2 [Medox ] dy 2
k 2 k1 [Eox ][S] k−1 + k2
(5)
= k3 [Ered ][Medox ] =
Oxygen – mediator Competition
We can understand this by examining the kinetics of the reactions described in Figure 8(a). In the sensor, the reaction becomes a function of time and space with diffusion into the enzyme layer of thickness y = d. Taking the simplest case of one-dimensional diffusion obeying Fick’s laws:
d2 [O2 ] = k4 [Ered ][O2 ] dy 2
k 2 k1 [Eox ][S] k−1 + k2
(6)
and DS
d2 [S] = k1 [Eox ][S] − k−1 [ES] dy 2 k−1 k1 [Eox ][S] = k1 − k−1 + k2
(7)
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
where DO , DM , and DS are the diffusion coefficients of oxygen, mediator, and the glucose within the enzyme layer. The electrode current is directly proportional to the first differential of the concentration of electroactive species present at the electrode surface. The model can be solved numerically to predict the calibration curve and Figure 8(c,d) reveals the mediator/oxygen competition for the enzyme (k3 /k4 ), particularly at lower glucose concentration. The importance of maximizing k3 /k4 is evident. The PO2 of an average venous blood sample is approximately 40 mm Hg (equivalent to ∼0.06 mmol l−1 dissolved O2 ). In contrast, for an arterial sample, PO2 of approximately 110 mm Hg is typical, or 0.15 mmol l−1 dissolved oxygen, with capillary samples a little lower. Therefore, measurements of glucose taken at different sites may be expected to produce different results, resulting in difficulty for the user in interpretation.
3.2
Mediator Candidates
The Fe(III)/(II) redox couple is a well known and efficient, fast electron transfer reversible system. Among the substrates listed above, ferrocenes show efficient electron acceptance properties at an optimum pH (Table 2). This system was the basis for the blood glucose sensor first developed by MediSense (1987) and represented a major breakthrough in self-test technology. Test strips were manufactured by screen-printing a series of layers on to a poly(vinyl chloride) strip. It used a three-electrode cell with a silver/silver chloride electrode (SCE) employed as the combined reference/counterelectrode. There were two working electrodes, the first containing enzyme and mediator and the second containing mediator. The latter electrode’s function was to provide a “blank”, quantifying the level of interfering substances that may be present in the sample. Thus, the glucose concentration was measured by subtracting the current obtained at the second electrode from that obtained at the first electrode. Adopting the same principle, other redox couples can also be used, and have become varyingly successful. For example, one particular favorite is Prussian blue: 2Fe(CN)6 3− + 2e− ↔ 2Fe(CN)6 4−
(8)
3.3
9
Improving CT Between Enzyme and Mediator
However, one aspect of all these mediators is that k3 /k4 < 1. Another approach is to return to the problem described by Marcus’ theory of CT and to consider how to improve the CT success rate. Remembering that only a certain number of collisions between the freely diffusing mediator and the protein macromolecule will be anywhere near the redox site and have the right orientation to allow CT, any method that improves this collision success rate is likely to have some impact on the CT kinetics. An obvious way to improve this is by chemical modification of amino acid groups on the protein, so that they become derivatized by redox groups. Keeping in mind that the chemistry must be amenable to mass production, the main candidates for derivatization are lysine and cysteine groups, since their derivatization is most facile. There are two ways of approaching this: in the first case, what might be called the brute force method of opportunist modification of all convenient surface groups (Figure 9a); this produces a highly derivatized enzyme (e.g., GOx has 24 accessible lysine residues per monomer, 3 lying in the funnel between the monomers making up the dimer) whereas the second method gives a so-called intelligent site-directed modification, close to the redox site of the CT pathway through the protein. The latter is only realistically achieved by introducing convenient amino acid groups (most likely cysteine) at the appropriate position by site-directed mutagenesis. Unlike the wild-type enzyme available off the shelf for the brute force method, the mutant enzyme has to be cloned, expressed, and produced in quantities suitable for mass production of biosensors. Although very high CT rates can be achieved, the cost effectiveness of this has to be proved for GOx, although the method is demonstrated for other enzymes in research use. In contrast, the more general surface modification method has been adopted in self-test glucose sensors. Foulds and Lowe were among the first to demonstrate the potential of enzyme modification in the 1980s, using a ferrocene–pyrrole conjugate modified GOx that was subsequently linked into a conducting polypyrrole polymer “wiring matrix” (Figure 9b), providing CT pathway control all the way from the redox site in the enzyme to the electrode. Their early work identified two core
10
BIOSENSOR APPLICATIONS
Table 2. Redox mediators, giving their redox potentials in aqueous solution, and second-order rate constants (k) for their reduction by reduced GOx from Aspergillus niger (pH 5.5 or 7)
Mediator redox potential (mV) versus SCE
ks (M−1 s−1 )
Structure
0.26 × 10−5
Ferrocene 210 Fe
0.77 × 10−5
Fc(Me)2 109 Fe
5.5 × 10−5
Fc-CH2 -N-(CH3 )2 370 NMe2
Fe
Fc(COOH) 290
COOH
2.0 × 10−5
COOH
0.26 × 10−5
Fe
Fc(COOH)2 403 Fe
COOH
p-Ferrocenylaniline 245
Not reported
NH2 Fe
Benzoquinone 275 1,4-Bis(N,N -dimethylamino) benzene 450 4,4-Dihydroxybiphenyl 320
1.97 × 10−5
o
o
1.2 × 10−5
N
N
3.0 × 10−5
OH
HO
Methylene blue 30
1.86 × 10−5
N N
Tetrathiafulvalene 150
N+
S
S
S
S
S
1.28 × 10−5 1.2 × 10−5
[Os(Me2 bpy)2 Cl2 ]5 150 Me2bpy=
N
N
1.8 × 10−5
[Ru(bpy)2 Cl2 ] 300 bpy=
[Ru(2-phenylimidazole) (1,10-phenanthroline)]PF6 280
0.75 × 107 R N L
Ru L
[Os(phenylpyridine)(1,10phenanthroline)2 ] PF6 55
PF6
L=
L
N
N
L
1.1 × 107 R N L
Os L
PF6 L
L
L=
N
N
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
H
Fe
N
Redox center
O
Fe
11
N H
H N
H N
zy
m
H
e
N H
Enzyme
Fe
N
H N
O
N H
O
Fe
Electrode
NH H N
Fe O
O
H N Fe
H N O
O
Electron transporting pathway
O
Fe
Fe
N H
Fe
Fe
Fe
O
N H
N H
Enzyme
Fe
O
O
Enzyme
H N
H N Fe
Fe
O
O
Fe
O
En
Fe
O
Fe
N H
O
NH
Fe
NH
O
Fe
O
(a)
N
HN n1
NH
n
N HN
HN
N
HN
N
O
O
CI N
Fe
N + + Os 2 /3 N
N
NH
Fe (b)
O (c)
Figure 9. (a) Covalently modified with ferrocene electron-relay groups. Covalent attachment of electron mediators units at the protein periphery yields short electron transfer distances and provides an electron transporting pathway. Electrical contacting of immobilized enzymes through (b) a redox modified conducting polymer, for example shown for ferrocene and polypyrrole and (c) incorporation of mediators as complexes with polycationic redox polymers containing Os(bpy)2 Cl groups attached to a poly(vinylpyridine) backbone. The Os site can be switched from Os(II) to Os(III) upon application of a potential and can also exchange electrons with the flavin site on the enzyme.
12
BIOSENSOR APPLICATIONS
parameters that have been optimized in subsequent developments: • The CT between the group attached and the enzyme must be fast. For example, CT for pyrrole is slow and so this cannot be used alone. A fast redox couple must be employed to modify the enzyme to ensure fast kinetics. • A CT “wire” between the modified enzyme and electrode must be created (it is not sufficient to modify the surface of the enzyme without also making the link to the electrode). A weakness of this early “wiring” attempt was the kinetics of the mixed redox system–conducting polymer hybrid. However, this was resolved during the subsequent decade by others, who adopted redox polymers rather than conducting polymers to move charge to the electrode. Heller led one of the research efforts synthesizing GOx “wiring” electron conducting hydrogels. These were cross-linked, water-soluble polymers containing, osmium poly pyridine–based fast redox centers (Figure 9c). By cross-linking nonprecipitating electrostatic adducts of polyanionic GOx with an excess of the polycationic osmium complex–derived, polyvinyl pyridine–based, polymer, the GOx became “wired” to the electrode, and the gel was highly permeable to sample (glucose) uptake. This system therefore also has many attractive features for GOx sensor fabrication, including the achievement of FADH2 oxidation via the osmium redox couple at a potential of approximately—0.1 V versus Ag/AgCl.
3.4
Alternative Enzyme Choice
Even with fast wiring, the opportunity for shortcircuiting the CT pathway with oxygen remains a possibility, since it is the natural cosubstrate for GOx. Alternative enzymes have therefore also been explored. Quinoproteins utilize quinone species as cofactors and prosthetic groups. In most bacterial quinoproteins pyrroloqinoline quinone (PQQ, Figure 10c) is tightly but noncovalently bound. Most of the quinoproteins are dehydrogenases, and often do not require any further soluble cofactors, the natural electron acceptor being a copper protein or membrane-bound ubiquinone.
These enzymes can be used in the same way as described for oxidases and have an easily accessible redox potential, that is lower than most of the common interferents. The soluble PQQ–glucose dehydrogenase (GDH EC 1.1.5.2, Figure 10a) is a basic dimeric enzyme. The glucose binding site is a wide solvent accessible cavity, located directly above the PQQH2 . Routine assays employ artificial electron acceptors without danger of susceptibility to oxygen interference. 4 ACCURACY, PRECISION, AND REPRODUCIBILITY25 – 31
In practice, in producing the self-test strips, the electrode is coated with the mediator and enzyme giving disposable, single-use minielectrodes that simply “plug and play” into the handheld instrument. Each of the test strips now available performs reasonably well as a home use test for glucose, but it has been a challenge to equal the YSI test in terms of accuracy and precision. Figure 11(a and b) shows an early (1999) comparison between some test strips from different manufacturers and highlights the potential for variation between and within strips. The clear improvement that has emerged over a 5-year period is also evident (Figure 11c). There are several factors needing consideration that can influence the measurement and must be accommodated in the calibration: For example, in whole blood glucose is distributed between plasma and the red cells. By using a dilution step, such as that employed in the original YSI, a 25 times dilution into isotonic buffer ensures that virtually all of the glucose in the red cells is transferred to the solution phase. However, for a rapid single-step self-test kit, dilution is not an option. The tests can suffer from a significant hematocrit (HCT) bias. Normal levels of hematocrit are ca 45% and thus it would be rational to calibrate the test for this level, but if 21% change per percent HCT bias is observed, the glucose estimate will be 10% low when the hematocrit is 55%, and 10% high when the hematocrit is 35%. Models of enzyme electrodes have allowed variations in the device parameters to be investigated. Parameters such as dissolution and sample wicking
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
Epa2
Current
Epa1
13
Epc –0.4
(a)
–0.2 0 0.2 Potential versus SCE
0.4
(b) O
O
O
O 1
C
OH
HN
2
C
C
OH
OH
C
3
9 8
O
+2e− , +2H+
4
C 7 N
O
−2e− , −2H+
O
5
6
C
O
OH
N
OH OH
OH
O
O 2′ C
O −
O
C 9′
H
N
1
9
O
7
C 7′ O
N6
Ca2+ PQQ
O
−
O C
3
5
O
O
−
2
8 −
OH
HN
C O−
H
N
+2H+ , +2e−
O
4
O
C O−
N
Ca2+
OH OH
PQQH2
(c)
Figure 10. (a) PQQ–glucose dehydrogenase structure, from data in the protein data bank (PDB); 3D image of structure of PDB code 1c9u. (b) Cyclic voltammogram of the PQQ redox group (C electrode, 0.2 mM in phosphate buffer pH 7.2). (c) Electron and proton transfer equilibria, with stabilization of the carboxylate group through cation binding.
or integrated control and measurement techniques (steady state, dynamic, end point, etc.) can all be investigated producing very valuable models to aid in the design process.32,33 Even from a simplified analysis of the amperometric steady-state Leyland Clark geometry, an understanding of the early GOx electrodes can be obtained. The reaction scheme for an oxidase enzyme linked assay, monitoring hydrogen peroxide or mediator, results in
nonlinear second-order differential equations, from which the electrode current can be predicted, since it is related to the flux of electroactive material to the electrode surface, and hence the first differential of the concentration at x = 0 (Figure 12a). Applying boundary conditions, equations (5–7) can be nondimensionalized, giving the respective Thiele moduli which can be evaluated and are indicative of the reaction/diffusion balance
BIOSENSOR APPLICATIONS 20
Test strip I Test strip II
15
Test strip III
10 5 0 1
2
3
(a)
4 5 6 Patient sample
7
Millimoles of glucose determined
Glucose concentration as determined (mM)
14
8
8.5 8 7.5 7 6.5 6
Repetitive measurements from a single blood sample (1999)
5.5 Test strip I Test strip II Test strip III
YSI
(b)
Comparison with reference method (YSI) for a selection of test strips (n = 2500). Difference, Mean ± SD% Newer (2004 data) −0.6 ± 6.3 1.6 ± 1.1 0.9 ± 0.8 2.1 ± 1.2
Test strip A Test strip B Test strip C Test strip D Early (1999 data)
−17.6 ± 19.6 10.8 ± 10.0 5.8 ± 4.7 −13.5 ± 10.6
Test strip I Test strip II Test strip III Test strip IV (c)
Figure 11. Comparative data collected from test strips (data compiled from multiple studies). (a) Three different test strips used to compare samples from eight patients. (b) The same sample repeatedly measured using three different test strips and compared with the YSI glucose measurement. (c) Data from different test strips in 1999 and 2004 compared with YSI reference measurement.
characteristic of the enzyme matrix of the designed biosensor: 2O = 2M
=
2S
=
d 2 k2 [ET ] DO [O2 ]b d 2 k2 [ET ] DM [S]b d 2 k2 [ET ] DS [S]b
(9) (10) (11)
The thickness, d and enzyme loading [ET ], are the two parameters within 2 which are controlled in the fabrication of the biosensor. Matching 2 for electrodes is important in obtaining matched output. The membrane thickness is especially sensitive, since its effect appears as a squared term.
In the field of electronics, deposition and definition is performed to precise limits of accuracy. In this field, thick- and thin-film technologies have become versatile and cheap tools in the fabrication of miniaturized electronic circuits. Biosensor fabrication has been compared with chip manufacturing, but biosensor devices differ from integrated circuit (IC) manufacture because they require a greater diversity of materials (mainly organic with potentially shorter shelf-lives) and initially lower volumes per product. This creates an obvious need for a nonsilicon approach to inexpensive disposable chemical and biological sensors and sensing systems. However, by merging conventional manufacturing technologies with IC-type fabrication methodologies, a variety of manufacturing options more suited to this type of biomedical application has been developed. Combined with the use of more cost-effective materials,
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS 1.1
(i)
30 1.0 µM 20 0.5 µM 10
0
(b)
2.2 µm
2.0 µm
1.0
1.8 µm
0.9
0
(a) Current is proportional to concentration gradient in reagent layer
(ii)
2.0 µM Relative response
40 Current density (µA cm−2)
Concentration
Electrode
Analyte
Thick diffusion Thin diffusion layer, steeper layer, concentration gradient
Concentration
Reagent Sample layer layer
15
10
20
30
(Substrate) (mM)
40
0
10
20
30
40
(Substrate) (mM)
Figure 12. (a) Schematic of “thick” and “thin” enzyme layer sensors. (b) (i) Comparison of calibration curves at different enzyme layer thicknesses and (ii) effect on relative current response for 2 ± 0.2 µm enzyme layer.
like polymers and plastics, this finally achieves a viable reality for the economical application of biosensor devices. In particular, deposition technologies based on a solution, ink, or paste have been successfully adapted for biosensor fabrication, but in the 1980–1990s these options were still limited in their resolution and replay accuracy, thereby also impacting the performance data (Figure 11c) and revealing one factor in understanding the early variability in test strips. To further understand the challenges of accuracy and reproducibility, it is necessary to consider the impact of these fabrication processes and the deposition of the layers on the electrodes and their subsequent dissolution in the sample or, in the case of a nonsoluble immobilized layer, the diffusion of the sample through the layers. Thick-film screen-printing 100 µm lateral resolution; thickness control of approximately 500 µm. Ink-jet printing 1–500 000 drops per second; 0.5–1.5 nl per drop; 1–5-µm resolution. Photolithography Conventional resolution of approximately 250 nm with a 350–450-nm light source; with proteins typically 400–1800 µm; thickness control 125 ± 10 µm. Figure 12(b)(ii) shows the effect of a change of just ±0.2 µm on the deposited thickness for a
2D layered geometry as depicted in Figure 12(a). It is most striking that the variation in the relative response is also dependent on the substrate (analyte) concentration and can become a complex algorithm for the calibration process. Thus, the rewards for overcoming these issues through improved fabrication precision or changes in geometry or measurement technique are substantial. In the decade since these first test strips were manufactured, different deposition technologies which are widely used tools for the fabrication of electronic circuits have been further adapted in their own right for biosensors. Screen-printing has become available with a number of special pastes with lower firing temperatures, leading to more options for biological sensor fabrication. Using this thick-film technology for the whole device (all components: electrodes to enzyme) is cheaper and it becomes possible to produce disposable sensors at a rather low price for a low- to medium-scale production. A so-called soft lithography printing process, called microcontact printing, is also showing potential for printing biomolecules. The process prints directly from a patterned elastomeric stamp. The elastomer can compensate for some degree of local surface-roughness up to approximately 1 µm, depending on the material properties, whereas macroscopic warp (>100 µm) is compensated by the flexibility of the backplane. In the past, printing and soft lithography have been used only for single component transfer but new contact printing allows precise alignment on the final substrate. Proteins (e.g., enzymes such as GOx) adsorb
16
BIOSENSOR APPLICATIONS
spontaneously to the hydrophobic surface of a stamp (e.g., polydimethylsiloxane (PDMS) with a high Young’s modulus) by incubation with an aqueous solution and the main advantage is the capability of processing large surfaces in one step with arbitrary patterns. There are two ways to print different components onto a single substrate using soft-lithographic techniques: (i) successive, iterative inking and printing (Figure 13) and (ii) parallel inking of a stamp followed by a single printing step. However, perhaps the biggest impact in deposition technologies for GOx sensors so far, has
come in ink-jet printing technology. Over the past 20 years, this technology has been a dominant player in the low-cost color printer market but it has also become accepted as a precision microdispensing technology. There are some key characteristics that have made it a highly useful fluid microdispensing tool for industrial, medical, and other applications. It requires no masks or screens, it is noncontact and it is data-driven (processing information can be written directly in the CAD package and stored digitally). Manufacturing of devices for biomedical diagnostics using ink-jet technology dates to the 1980s,
Enzyme/reagent solution
Stamp
“Inked” stamp
Printing on substrate
Circa 500 nm
(a)
Patterned surface
(b)
Drop size optimized for the solution and substrate characteristics; dispensed drop retains its ‘‘shape’’
Drop size not optimized; dispensed drop too large and spreads on substrate
Figure 13. (a) Contact printing process applied for enzyme printing. (b) Impact of metered volume on the dispensed drop, depending on the substrate properties (e.g., hydrophobicity).
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
with the fabrication of glucose sensors being one of the first examples, but the billion-dollar pregnancy test kit market predominantly driving the early technology. Precision microdispensing based on ink-jet technology has been used in medical diagnostics since the early 1990s. It can reproducibly dispense spheres of fluid with diameters of 15–100 µm (2 pl–5 nl). Perhaps a key driver toward better resolution and repeatability came in the effort to miniaturize biological assays and to conduct many assays in parallel for gene chip technology. This required high-density resolution of DNA probes, say better than 75 µm spots on <200 µm centers. To be able to use ink-jet methods, the working fluid must be low viscosity, nearly Newtonian, and free of particles of the size of the orifice diameter. Controlled sample dispensing is then the criticalstep and precise metering and application of the dispensed component (droplet) is essential for all quantitative measurements. The dispensing process is optimized according to the characteristics of the solution (ink) and the substrate materials used for the wetted surfaces (Figure 13b) setting different limitations for proteins to those established in DNA printing. Proteins adhere to most surfaces but can loose their functionality (denature), so that controlling the solution and wetted surface area is critical. The general trend toward miniaturization (irrespective of the deposition technology employed) offers several advantages. In small volumes, the ratio of surface area to enclosed volume is considerably greater. This results in the surface effects and capillary and adsorption phenomena dominating instead of the volume effects at higher dimensions. Electrochemical double layers have considerable influence, since their thickness, 10–100 nm, becomes a significant proportion of the total enzyme thickness and mass transport by diffusion becomes fast, so that mixing and chemical reactions can be accelerated accordingly. This means that the impact on 2 of variation in deposition is lessened and, of course, the measurement result is obtained faster. Furthermore, the components are used more efficiently, and lower volumes of samples or reagents are required. As the sample size is reduced to a minimum, the total amount of glucose within the sample can become consumed within the
17
measurement period. If the blood volume used can be accurately sampled, a coulometric assay then offers a viable alternative to steady-state current measurement. In conclusion, for the successful self-test glucose biosensor, the test must be simple to run and convenient for use by a layperson as part of the normal daily routine. Future refinements will no doubt further increase the reliability and precision of each of the tests, so that the evolution of glucose assay methods will continue to be central to the development of therapies for diabetes mellitus. This chapter has given a flavor of a few of the issues that have been considered in the history of the glucose test strip. However, blood glucose assay with this methodology, still requires frequent blood sampling with the associated degree of inconvenience. Traditionally for practical reasons, blood is collected from the fingertips, a sensitive part of the body, so the sampling should be as painless as possible, invade a minimum sampling site (frequent testing leads to heavily calloused hands) and require a small volume (<2–3 µl). Studies suggest that some people with diabetes may choose not to monitor their glucose levels and strive for close blood glucose control because of the obtrusiveness of blood sampling. The frequency of blood sampling that is acceptable to most patients is still less than the frequency of blood glucose fluctuations and does not detect spontaneous hypoglycemia or other rapid blood glucose imbalances. As useful as the present glucose assay technologies have become, an important feature that is not part of a disposable self-test strip is continuous monitoring.34–39 This would permit routine therapeutic intervention. Continuous glucose sensing provides a basis for insulin administration at more appropriate dosages and timing, or for automatic insulin delivery from a pump and could also be employed beneficially in parallel with other existing or potential forms of insulin replacement, such as transplantation or hybrid islet devices. Nevertheless, even though the clinical benefit of continuous measurement is easy to defend, continuous sensing technologies still have to be unobtrusive and more convenient than discrete sensing approaches to achieve widespread application and replacement of the disposable self-test kit.
18
BIOSENSOR APPLICATIONS
REFERENCES 1. A. E. G. Cass, Biosensors, A Practical Approach, IRL Press at Oxford University Press, 1990. 2. E. A. H. Hall, Biosensors, Open University Press/Wiley, 1990. 3. E. Magner, Trends in electrochemical biosensors. Analyst, 1998, 123, 1967–1970. 4. L. S. Kuhn, Biosensors: blockbuster or bomb? electrochemical biosensors for diabetes monitoring. The Electrochemical Society Interface, 1998, 7(4), 26–31. 5. N. R. Stradiotto, H. Yamanaka, and M. V. B. Zanoni, Electrochemical sensors: a powerful tool in analytical chemistry. Journal of the Brazilian Chemical Society, 2003, 14(2), 159–173. 6. D. C. Klonoff, Continuous glucose monitoring roadmap for 21st century diabetes therapy. Diabetes Care, 2005, 28, 1231–1238. 7. J. D. Newman and A. P. F. Turner, Home blood glucose biosensors: a commercial perspective. Biosensors and Bioelectronics, 2005, 20(12,), 2435–2453. 8. S. P. Mohanty and E. Kougianos, Biosensors: a tutorial review. IEEE Potentials, 2006, 25(2), 35–40. 9. The Diabetes Control and Complications Trial Research Group, The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. New England Journal of Medicine, 1993, 329(14), 977–986. 10. R. A. Marcus and N. Sutin, Electron Transfer Reactions in Chemistry: Theory and Experiment, Nobel Lecture Dec, 1985, http://nobelprize.org/nobel prizes/chemistry/ laureates/. 11. K. H. Mancy, D. A. Okun, and C. N. Reilley, A galvanic cell oxygen analyzer. Journal of Electroanalytical Chemistry, 1962, 4, 65–92. 12. L. C. Clark and C. Lyons, Electrode systems for continuous monitoring in. cardiovascular surgery. Annals of the New York Academy Sciences, 1962, 102, 29–45. 13. S. J. Updike and G. P. Hicks, The enzyme electrode. Nature, 1967, 214, 986–988. 14. A. E. Cass, G. Davis, G. D. Francis, H. A. Hill, W. J. Aston, I. J. Higgins, E. V. Plotkin, L. D. Scott, and A. P. Turner, Ferrocene-mediated enzyme electrode for amperometric determination of glucose. Analytical Chemistry, 1984, 56, 667–671. 15. C. Bourdillon, C. Demaille, J. Moiroux, and J. M. Saveant, New insights into the enzymic catalysis of the oxidation of glucose by native and recombinant glucose oxidase mediated by electrochemically generated one-electron redox cosubstrates. Journal of the American Chemical Society, 1993, 115, 2–10. 16. J. Kulys, T. Buch-Rasmussen, K. Bechgaard, V. Razumas, J. Kazlauskaite, J. Marcinkeviciene, J. B. Christensen, and H. E. Hansen, Study of the new electron transfer mediators in glucose oxidase catalysis. Journal of Molecular Catalysis, 1994, 91, 407–420. 17. V. N. Goral and A. D. Ryabov, Reactivity of the horseradish peroxidase compounds I and II toward organometallic substrates. A stopped-flow kinetic study of oxidation of ferrocenes. Biochemistry and Molecular Biology International, 1998, 45, 61–71.
18. A. D. Ryabov, V. S. Kurova, V. N. Goral, M. D. Reshetova, J. Razumiene, R. Simkus, and V. Laurinavicius, p-Ferrocenylaniline and p-ferrocenylphenol: promising materials for analytical biochemistry and bioelectrochemistry. Chemistry of Materials, 1999, 11, 600–604. 19. A. D. Ryabov, Y. N. Firsova, A. Y. Ershov, and I. A. Dementiev, Spectrophotometric kinetic study and analytical implications of the glucose oxidasecatalyzed reduction of [MIII(LL)2 Cl2 ] + complexes by D-glucose (M = Os and Ru, LL = 2, 2 -bipyridine and 1,10-phenanthroline type ligands). Journal of Biological Inorganic Chemistry, 1999, 4, 175–182. 20. A. D. Ryabov, Y. N. Firsova, V. N. Goral, V. S. Sukharev, A. Y. Ershov, C. Lejbolle, M. J. Bjerrum, and A. V. Eliseev, Horseradish peroxidase-catalyzed oxidation of cis-[RuII(LL)2XY] complexes by hydrogen peroxide (LL = 2, 2-bipyridine and 1,10-phenanthroline): equilibria, kinetics, mechanism, and active site reassembly. Inorganic Reaction Mechanisms, 2000, 2, 343–360. 21. N. Anicet, A. Anne, C. Bourdillon, C. Demaille, J. Moiroux, and J.-M. Saveant, Electrochemical approach to the dynamics of molecular recognition of redox enzyme sites by artificial cosubstrates in solution and in integrated systems. Faraday Discussions, 2000, 116, 269–279. 22. A. D. Ryabov, V. S. Sukharev, L. Alexandrova, R. Le Lagadec, and M. Pfeffer, New synthesis and new bioapplication of cyclometalated ruthenium(II) complexes for fast mediated electron transfer with peroxidase and glucose oxidase. Inorganic Chemistry, 2001, 40, 6529–6532. 23. C. Loechel, A. Basran, J. Basran, N. J. Scrutton, and E. A. H. Hall, Using triethylamine dehydrogenase in an enzyme linked amperometric electrode. Rational design engineering of a ‘wired’ mutant. Analyst, 2003, 128, 889–898. 24. A. W. Bott, Investigation of enzyme-mediated electron transfer using DigiSim . Current Separations, 2004, 20, 4–8. 25. J. C. N. Chan, R. Y. M. Wong, C.-K. Cheung, P. Lam, C.C. Chow, V. T. F. Yeung, E. C. Y. Kan, K.-M. Loo, M. Y. L. Mong, and C. S. Cockram, Accuracy, precision and user-acceptability of self blood glucose monitoring machines. Diabetes Research and Clinical Practice, 1997, 36, 91–104. 26. L.-J. Cartier, P. Leclerc, M. Pouliot, L. Nadeau, G. Turcotte, and B. Fruteau-de-Laclos, Toxic levels of acetaminophen produce a major positive interference on glucometer elite and accu-chek advantage glucose meters. Clinical Chemistry, 1998, 44, 893–894. 27. R. Weitgasser, B. Gappmayer, and M. Pichler, Newer portable glucose meters—analytical improvement compared with previous generation devices? Clinical Chemistry, 1999, 45, 1821–1825. 28. Z. Tang, J. H. Lee, R. F. Louie, and G. J. Kost, Effects of different hematocrit levels on glucose measurements with handheld meters for point-of-care testing. Archives of Pathology and Laboratory Medicine, 2000, 124, 257–266. 29. J. C. Boydand and D. E. Bruns, Quality specifications for glucose meters: assessment by simulation modeling of errors in insulin dose. Clinical Chemistry, 2001, 47(2), 209–214. 30. P. B. B¨ohme, M. Floriot, M.-A. Sirveaux, D. Durain, R. O. Ziegler, P. Drouin, and B. Guerci, Evolution of analytical
GLUCOSE MEASUREMENT VIA ‘‘TRADITIONAL’’ ELECTROCHEMICAL BIOSENSORS
31.
32.
33.
34.
performance in portable glucose meters in the last decade. Diabetes Care, 2003, 26, 1170–1175. W. L. Clarke, S. Anderson, L. Farhy, M. Breton, L. Gonder-Frederick, D. Cox, and B. Kovatchev, Evaluating the clinical accuracy of two continuous glucose sensors using continuous glucose—error grid analysis. Diabetes Care, 2005, 28(10), 2412–2417. N. Martens and E. A. H. Hall, Model for an immobilized oxidase enzyme electrode in the presence of two oxidants. Analytical Chemistry, 1994, 66, 2763–2770. M. E. G. Lyons, Modelling the transport and kinetics of electroenzymes at the electrode/solution interface. Sensors, 2006, 6, 1765–1790. D. Moatti-Sirat, G. Velho, and G. Reach, Evaluating in vitro and in vivo the interference of ascorbate and acetaminophen on glucose detection by a needle-type glucose sensor. Biosensors and Bioelectronics, 1992, 7, 345–352.
19
35. W. Kerner, M. Kiwit, B. Linke, F. S. Keck, H. Zier, and E. F. Pfeiffer, The function of a hydrogen peroxidedetecting electroenzymatic glucose electrode is markedly impaired in human subcutaneous tissue and plasma. Biosensors and Bioelectronics, 1993, 8, 473–482. 36. D. Gough and J. C. Armour, Development of the implantable glucose sensor: what are the prospects and why is it taking so long? Diabetes, 1995, 44, 1005–1009. 37. J. Pickup, Technology advances in glucose monitoring. Pediatric Diabetes, 2002, B, 125–126. 38. V. Bozzetti, M. Viscardi, R. Bonfanti, A. Azzinari, F. Meschi, E. Bognetti, and G. Chiumello, Results of continuous glucose monitoring by GlucoWatch biographer in a cohort of diabetic children and adolescents under real-life conditions. Pediatric Diabetes, 2003, 4, 57–58. 39. I. M. Wentholt, J. B. Hoekstra, and J. H. Devries, A critical appraisal of the continuous glucose–error grid analysis. Diabetes Care, 2006, 29(8), 1805–1811.
73 Field-Operable Biosensors for Tropical Dispatch Rodica E. Ionescu,1 Victoria Yavelsky,2 Tamar Amir,2 Natalie Gavrielov2 and Leslie Lobel2 1
Centre de Genie Electrique de Lyon, Ecole Centrale de Lyon, Lyon, France and 2 Department of Virology, Ben-Gurion University of the Negev, Beer-Sheva, Israel
1 INTRODUCTION – INFECTIOUS DISEASES
Emerging infectious diseases generally arise from infectious agents that circulate in their respective reservoir before making a jump to humans. Although many of these emerging infectious agents can and have caused significant morbidity and mortality, only recently has there been a concerted effort for rapid pathogen identification. The National Institutes of Health of the United States has prioritized pathogens in large part owing to the recent awareness of the potential use of these dangerous infectious diseases as agents of bioterror or biowarfare (Table 1).1 Nonetheless, for successful prevention and treatment of infectious agents that emerge from either the environment or result from nefarious plots, multiple detection technologies need to be developed to serve different fields, such as bioscience research, medical diagnostics, analytical screening for food processing, and environmental testing. In tropical areas, especially equatorial regions of the world, pathogens such as bacteria and viruses are responsible for grave respiratory diseases (such as measles, respiratory syncytial virus, tuberculosis, TB) and sexually transmitted diseases (such as gonorrhea and human immunodeficiency virus, HIV). In addition, many diseases can be spread
through contaminated water and food resources, since clean water and sanitary conditions are often a luxury. One prime example is Typhoid fever (or enteric fever) caused by Salmonella Typhi that leads to about 16.6 million cases and 600 000 deaths annually with the vast majority of cases occurring in southeast Asia, Africa, and South America.2 Insects are major vectors of emerging diseases worldwide as they transmit deadly tropical diseases by picking up the pathogen from an infected person or animal and transmitting it to uninfected organisms during the feeding process. This is the case for the single-stranded RNA viruses of the Flaviviridae family, which replicate in the cytoplasm of infected cells. The members of this family consist of very small (50 nm) spherical enveloped virions and are transmitted to humans by mosquitoes predominantly in Africa, the Americas, and Australia. Representative viruses of the Flaviviridae family are West Nile virus (WNV), dengue virus (DEN), yellow fever (YF) virus, and Japanese encephalitis virus.3 The importance of studying such viruses can not be overstated since it has been reported, for example, that a rapid spread of WNV may pose a significant public health problem in the coming
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS Table 1. Biological pathogens
National institute of allergy and infectious diseases (NIAID) category A, B, and C priority pathogens Category A Bacillus anthracis (anthrax) Clostridium botulinum (botulinum neurotoxin) Yersinia pestis (plague) Variola major (smallpox) and other pox viruses Viral hemorrhagic fevers Arenaviruses LCM, Junin virus, Machupo virus Guanarito virus, Lassa fever Bunyaviruses Hantaviruses Rift Valley fever Flaviviruses Dengue Filoviruses Ebola Marburg Category C Tickborne hemorrhagic fever viruses Crimean–Congo Hemorrhagic fever virus Tickborne encephalitis viruses Yellow fever Multidrug-resistant TB Influenza Other rickettsias Rabies
Category B Burkholderia pseudomallei Coxiella burnetii (Q fever) Brucella species (brucellosis) Burkholderia mallei (glanders) Ricin toxin (from Ricinus communis) Epsilon toxin of Clostridium perfringens Staphylococcus enterotoxin B Typhus fever (Rickettsia prowaxekii ) Food and waterborne pathogens Bacteria Diarrheagenic E. coli Pathogenic Vibrios Shigella species Salmonella Listeria monocytogenes Campylobacter jejuni Yersinia enterocolitica Viruses (Caliciviruses) Protozoa Cryptosporidium parvum Cyclospora cayatanensis Giardia lamblia Entamoeba histolytica Toxoplasma Microsporidia Additional viral encephalitides West Nile virus LaCrosse California encephalitis VEE EEE WEE Japanese encephalitis virus Kyasanur Forest virus
http://www.niaid.nih.gov/biodefense/bandc priority.htm.
years.4 Thus far, no licensed human WNV vaccine is available to protect at-risk populations from WNV-induced illness. On the other hand, YF virus causes a viral hemorrhagic fever in humans with a fatality rate that exceeds 50%,5 affecting predominantly the human population in sub-Saharan Africa and tropical South America despite the availability of a safe and effective vaccine. Dengue is the most common mosquito-borne viral disease in humans; however, viral pathogenesis has been difficult to examine because there are no laboratory or animal models of the disease. Nonetheless, indirect evidence suggests that dengue viruses differ in virulence, including their
pathogenesis in humans.6 It was experimentally demonstrated that dengue serotype 2 viruses causing fatal dengue hemorrhagic fever7 epidemics (southeast Asian genotype) could outcompete viruses that cause dengue fever only (American genotype). This implies that the southeast Asian genotype will continue to displace other strains.8 The origin in nature of another deadly virus, Ebola, remains a mystery and humans are easily infected by close contact with patients. Since Ebola infections have mortality rates of 72% on average,9 rapid laboratory diagnosis of Ebola hemorrhagic fever is very important for preventing the spread of infection in a population. Indeed, much
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
research has focused on the rapid diagnosis of this and other deadly viruses, as the potential decimation of a large civilian or military population is apparent in the absence of a rapid response and quarantine based on accurate information. In this same vein, one of the most dramatic diseases that has created a global pandemic, AIDS, has been characterized by the rapid emergence and devastating spread of human immunodeficiency virus type 1 (HIV-1) accounting for more than 56% of all global infection.10 Major outbreaks are occurring in every country of southern Africa, with some regions reporting adult prevalence rates as high as 40%.11 The rapid spread of HIV has occurred largely in the absence of appropriate diagnostic and monitoring systems. Countries that have deployed diagnostic and monitoring for HIV along with treatment, such as the United States and interestingly Uganda, have made significant progress in the battle against AIDS. To fight viral and bacterial diseases, numerous techniques of direct or indirect viral or bacterial detection are being or have been developed. These include both immunological and nucleic acid–based analytics. Most immunological detection methods used for bacterial pathogen identification are also applicable for the detection of viruses with nearly identical sample preparation formats.12 However, sample preparation for nucleic acid–based detection of viruses, such as separation and isolation of viral DNA or RNA, is much simpler and faster than that for bacterial detection. Nonetheless, immunological detection of viruses is more difficult than that of bacteria. Viral antigens are often changed or altered allowing the virus to escape detection by immunological methods. Since most detection methods target either viral antigens displayed on the surface of the host cells or host antibodies produced as a result of immune response to these antigens, such methods are not very useful for detecting viral infection at its onset. However, sensitive immunological methods have been developed to detect a variety of viruses for example, herpes simplex viruses (HSV)13 and hepatitis A virus.14 Generally speaking, traditional detection methods such as plating, culturing, staining, and biochemical tests are often time-consuming, requiring extensive training in microbiology and lengthy time for obtaining results. The situation is somewhat improved with automated systems, which
3
use similar routine procedures but have minimal human input. Automated systems incorporating polymerase chain reaction (PCR),15 DNA and RNA probe techniques,16 flow cytometry,17 immunomagnetic separation,18 as well as quartz crystal microbalance (QCM),19 surface plasmon resonance (SPR),20 and microelectromechanical devices21 can identify microorganisms in few hours, although they require expensive equipment and specialized reagents. Furthermore, they are either too costly for wide applicability or have difficulty discriminating false-positive and falsenegative results. For direct pathogen detection, various molecular methods have been introduced over the years, like classical PCR, real-time PCR, multiplex PCR, improved in situ hybridization assays, and in situ PCR.22 Techniques that are still under development include PCR robotics, PCR for protein detection (DNA tags), novel nucleic acid hybridization methods, amplification without thermocycling, and macro- and microarrays. With respect to indirect detection, recombinant proteins and novel monoclonal antibodies are being employed for immunochromatographic lateral flow assays, enzyme-linked immunosorbent assays (ELISA), time-resolved fluorescence (TRF), immunomagnetic separation–electrochemiluminescence (ECL) and biosensors.23 As previously mentioned, conventional methods for pathogen detection require time-consuming steps, although they yield reproducible and reliable data. As such, methods including ELISA and PCRs are still actively employed for pathogen detection. In addition, labor-intensive techniques such as electron microscopy are also a useful tool and have two advantages over ELISA and nucleic acid–based tests. After a simple and fast negative stain preparation, “open view” of electron microscopy allows morphologic sample identification (10 min) and differential diagnosis of the various agents contained in the specimen.24 Electron microscopy can be applied to many types of samples (e.g., DEN, Rift valley virus,25 ) and can also hasten routine cell-culture diagnosis. However, to fully exploit and control the potential of pathogen diagnostics using electron microscopy, this technique must be run in parallel with other standard laboratory assays.26 Furthermore, it is too expensive and complicated for routine use.
4
BIOSENSOR APPLICATIONS
For speed and sensitivity in direct and indirect pathogen detection, portable, rapid, and miniaturized medical and environmental diagnostic kits must be developed. To this end, biosensors have become pivotal as efficient detectors of local bacteria or viral infectious agents and require few “particles” to stimulate signal generation. For practical applications, biosensors can detect much fewer than 1000 microorganisms per ml of suspension. In terms of experimental timing, whereas ELISA and PCR tests are performed over 10–28 and 4–6 h, respectively, biosensors can make accurate determinations within 2 h under working conditions and with enhanced sensitivity.27,28
2 BIOSENSOR CAPABILITIES FOR FIELD OPERATIONS
Owing to their unique features, biosensors have been pursued by the military as field-operable, real-time instruments to detect and identify pathogenic microorganisms in contaminated areas. The origin of biosensors is in the union of molecular biology with electronic information technology. In essence, they make use of specific technologies to qualify or quantify parameters of biomolecule–analyte reactions. As such, they can be classified according to their bioreceptor or transducer type. Examples of various systems in operation and development are listed in Table 2. Bioreceptors are key for the specificity of biosensor technology and are responsible for binding the analyte of interest to the sensor for measurement. They can take many forms, and the different bioreceptors that have been used are as numerous as the different analytes that have been monitored using biosensors. However, bioreceptors can generally be classified into five major categories: (i) antibody/antigen, (ii) enzymes, (iii) nucleic acids, (iv) cellular structures/cells, and (v) biomimetic. Depending on the method of signal transduction, a number of detection technologies are being investigated and validated for microorganism detection such as electrochemical-, piezoelectric-, optical-, acoustic-, and thermal-based systems.29 In addition, biosensors can be classified into sensors for direct or indirect (labeled) analyte detection. Direct biosensors measure physical
changes induced by immunocomplex formation, whereas the indirect ones are generally based on detection of products resulting from a biochemical reaction. Another biosensor classification distinguishes between biocatalytic and bioaffinity sensors. The biocatalytic biosensor uses primarily enzymes as the biological material, catalyzing a biochemical reaction that emits a signal. The bioaffinity biosensors use specific binding proteins (antibodies), nucleic acids, or whole cells and are designed to monitor the binding phenomena. If antibodies or antibody fragments are the biological elements the device is called an immunosensor. With respect to bacteria, biosensors can also be grouped into sensors operating in batch (intermittent) and continuous (monitoring) mode. Overall, biosensors are efficient diagnostic tools, predominantly in point-of-care testing, based on molecular recognition technologies that include antibodies, peptides, aptamers, and nucleic acids that are specific for target pathogens. Additional strategies are still under development, which will finally transform biosensor technologies into field-operable instruments to provide rapid, realtime pathogen detection, reducing substantially the labor, time, and cost as compared to classical laboratory testing.
2.1
Immunosensors
Currently, there are three popular types of immunosensors including electrochemical (potentiometric, amperometric, or conductometric/capacitive), optical, and microgravimetric. Electrochemical devices have some advantages over optical sensors in that they can operate in turbid media, offer comparable instrumental sensitivity, and are more amenable to miniaturization. Modern electroanalytical techniques have very low detection limits (down to 10−9 M), which can even be achieved using small volumes (1–20 µl) of samples.30 The immunosensors can either be developed as direct (nonlabeled) or indirect (labeled) devices. Whereas the direct sensors detect the physical changes during formation of an immunocomplex, the indirect ones use signal-generating labels when incorporated into the complex. Labels that are used include a spectrum of compounds ranging from enzymes such as peroxidase, glucose oxidase, catalase, or alkaline phosphatase to electroactive
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
5
Table 2. Examples of devices useful for developing biodefense programs
Type Bacillus microchip BIDS
CRP IBAD
IOTA
JBPDS
LRBSDS
LIBRA
MAGIChip
PAB
Portal Shield
Features Detects Bacillus anthracis, and identifies it from among other generic members such as Bacillus thuringiensis, Bacillus subtilis, and Bacillus cereus Biological integrated detection system detects through a laser-based sensor large areas under biological attack. Also functions as a warning system. BIDS is also capable of speeding-up treatment of biowarfare casualties by narrowing down the range of identities of specific biological agents used as bioweapons. Variations of the system allow for the detection of between to four and eight biological warfare agents in lees than an hour. The system is transportable for use by vehicle and laboratory-designed aircraft Critical reagent program designed to provide a ready available resources of antibodies, antigens, and gene probes for use in field detection and neutralization of biological warfare agents Interim biological detector designed as a manual handheld assay for use on ships with links to aural and visual alarms, IBAD provides advance warning of the presence of biological warfare agents through immunochromatographic analysis Voltametric instrument comprising miniaturized electrodes for optional use with antibodies, enzymes, organic dyes, and molecules for detection of heavy metals in body fluids, microorganisms, pesticide contaminants in foods and potable water, and so on, accompanied by graphic computation Joint biological point detection system is designed for use in protecting ports, naval ships, airfields, and as a portable warning system in conjunction with meteorological data. Automatic detection and identification of up to 10 biological warfare agents in less than 30 h is feasible. Enhanced versions of the systems focus on providing rapid facilities for the identification of 25 biological warfare agents thus speeding-up choice of treatment of casualties Long-range biological standoff detection system possesses a detection range of 50 km and through a laser eye distinguishes between artificial and natural aerosol clouds. The system has also been designed for complementary use with BIDS Comprises quartz crystal resonators coated with optional layers of antibodies, enzymes, and so on, for use in identification of microorganisms, pesticides, and other dangerous organic molecules and chemical gases with computer prints Microarray of gel-immobilized compounds that identify simultaneously numerous biological agents through reliance on microbe-specific gene sequences and microbe-specific sequences of ribosomal ribonucleic acids (rRNAs) Biosensor system with potentiometric alternating biosensing silicon chip, which interacts with a biological element such as cells, enzymes, and so on, with measured pH rates or redox potential variation. Used in determining metabolic variations in bacterial cells in response to presence of pollutants, drugs, hormones, pesticides, and so on, with graphic computation Used in the southeast Asian region for the protection of harbor and airfields, this biodefense system facilitates biological detection and identification, decontamination of biosensor equipment, and reduction of casualties
species such as ferrocene and fluorescent material (fluorescein, ruthenium complexes, etc.).
2.1.1 Electrochemical Pathogen Detection
Potentiometric Immunosensors All potentiometric sensors such as ion-selective electrodes, transmembrane potential sensors, and field-effect transistors measure alterations in surface potential at near-zero current flow. The main advantages of these sensors are their simplicity and small electrode dimensions, which facilitates miniaturization. However, potentiometric methods in general suffer from the lack of high sensitivity and occasional nonspecificity. One application
that uses a light-addressable potentiometric sensor is the detection of Venezuelan equine encephalitis virus where the pathogen low level of detection (LOD) limit is 30 ng ml−1 .31 Moreover, a similar approach was used for rapid detection of Newcastle disease virus with LOD varying from 400 ng ml−1 to 1.3 ng ml−1 with an antibody incubation step ranging from 1 to 60 min. The assay format is suitable for both virus and protein antigens. Furthermore, new assays can be developed and optimized readily, often within 1 day.32 Amperometric Immunosensors Amperometric immunosensors are based on measurement of a current flow generated by an electrochemical reaction at constant voltage. For direct sensing there are only a few applications available
6
BIOSENSOR APPLICATIONS
since most analytes (proteins) are not able to act as redox partners for the electrochemical reaction. Therefore, electrochemical species such as oxygen or hydrogen peroxide used either as substrates or as reaction products are introduced for sensing the electrochemical reaction of the analyte. This indirect testing approach has excellent sensitivity. In one application that combines flow-through immunofiltration with amperometry, bacteria Escherichia coli O157:H7 detection is reported.33 The authors obtained LOD of 100 cells per ml in an approximately 30-min experimental run. By using an electrogenerated biotinylated polypyrrole film copolymerized with pyrrole-lactobionamide monomer it was possible to amperometrically detect cholera antitoxin in the presence of the horse radish peroxidase (HRP) marker with a LOD down to 50 ng ml−1 .34 With two other enzymatic markers based on biotinylated polyphenol oxidase (PPO-B) and biotinylated glucose oxidase (GOX-B) the LOD was 100 and 1 µg ml−1 , respectively.35 The same research team designed amperometric immunosensors for the detection of photochemical grafted T7 bacteriophage displaying a specific WNV epitope with the low LOD for the antibody titer being 1:106 . For bacteriophage anchorage, a novel copolymeric film was used based on pyrrole-benzophenone and tris(bipyridine pyrrole) ruthenium (II) units.36 An amperometric sensor for detection of antibodies to Salmonella Typhi in the serum of patients was also developed.37 This involved use of screen-printed electrodes and a recombinant flagellin fusion protein. An indirect ELISA was used for detection of antibodies to Salmonella Typhi in the patient serum. The time taken for the detection by this electrochemical method is 1 h and 15 min, as compared to the time taken by other analytic means being 18 h. Conductometric and Capacitive Immunosensors These immunosensors measure conductivity changes at fixed voltage as a result of biochemical reactions, when biological entities are immobilized onto noble metals (such as Au or Pt) electrodes. Since biological media has high ionic strength, making it difficult to sense small conductivity changes, an ion-channel conductance immunosensor was developed.38 As an application an E. coli O157:H7 –monitoring conductometric biosensor was designed.39 The LOD was
approximately 7.9 × 10 colony-forming units per ml within a 10-min process. By changing the specificity of the antibodies, this biosensor can become a platform technology for sensitive detection of other types of pathogens too.
2.1.2 Optical Immunosensors
For bioanalytics the most frequently used transducers are optical immunosensors due to their durability despite frequent manipulations, rapid signal generation, and ease of data interpretation. In addition, the potential use of fiber-optic bundles with this technology can considerably speed-up multiple-pathogen identification in a clinical laboratory setting.40,41 The optical technology can provide information regarding the status of several phenomena such as luminescence, refractive index, fluorescence, and optical surface modification. They have been employed in multiple applications over the years; in optical detection of either the direct label-free immunological reaction of labeled immunoentites or of the indirect product(s) of enzymatic reactions. Fluorescent labels have been the most popular but the bio- and chemiluminescence labels are used frequently too and are rapidly becoming just as popular. A rapid assay for cholera toxin (CT) detection using a fluorescence-based biosensor has been developed42 using an optical detection sensor. This sensor was capable of analyzing six samples simultaneously for CT in 20 min with few manipulations required by the operator. The biochemical assays utilized a ganglioside “capture” for capture of analyte, immobilized on discrete locations of the surface of an optical waveguide. Limits of detection for CT were 200 ng ml−1 in direct assays and 40 ng ml−1 and 1 µg ml−1 in sandwich-type assays performed using rabbit and goat tracer antibodies, respectively. This assay claimed to be the first description of a non-antibody-based recognition system in a multispecific planar array sensor. The CT B subunit molecules were also detected using indium tin oxide–coated fiber-optics modified with electroploymerized biotinylated polypyrrole films and used for tethering molecular recognition probes through avidin–biotin interactions. The obtained LOD of the optical immunosensor was 100 ng ml−1 .43
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
An ELISA-based optical fiber methodology was also developed for the detection of anti-WNV IgG antibodies using a silanization technique for anchoring biological moieties. The lower antibody titer obtained was 1:106 .44 More recently, the same research team developed an optical immunosensor for Ebola virus detection by using an electrogenerated poly(pyrrole-benzophenone) film deposited upon an indium tin oxide–modified fiber-optic for tethering Ebola virus antigen.45 The lowest detectable titers measured with this optical sensor for anti-Ebola IgG for subtypes Zaire and Sudan were 1:960 000 and 1:1 000 000, respectively. Over all, fiber-optic immunosensors are highly sensitive and specific when compared with conventional immunoassays such as colorimetric ELISA systems.
2.1.3 Microgravimetric Sensors
Microgravimetric sensors are divided into QCM devices that apply a thickness-shear mode and devices applying a surface acoustic wave as the detection principle. The development of acoustic technology for the field of biology was recently reviewed.46 Thus far, comparison of results suggests that47 piezoimmunosensors may be powerful alternatives to optical sensors. QCM technology was used for the development of an immunosensor for detection of HIV.48 The sensor was based on the immobilization of recombinant viral peptides on the surface of the transducer and direct detection of anti-HIV antibodies in human sera. Recently, detection of Ebola glycoprotein using a QCM immunosensor was presented.49 The immunosensors for the sensitive and selective detection of Ebola glycoprotein from the Zaire and Sudan/Gulu strains were assembled using four different antibody samples. Monoclonal IgG1, IgG2a, IgM, and polyclonal IgG were immobilized on QCM gold electrodes using a variety of antibody capture proteins. These sensor assemblies allowed for the determination of specificity of one antibody sample for a given Ebola strain and for a determination of the detection limits. Initial detection limits were in the range of 10–50 nM of Ebola glycoprotein. Antibody-based biosensors that are sensitive and selective for a given Ebola strain, as well as inexpensive and portable,
7
have tremendous potential for early environmental Ebola detection. Impedimetric Immunosensors A group of sensitive pathogen detection strategies using electrical characterization, which scans the detection volume with an electrical frequency sweep over a range of frequencies is electrical impedance spectroscopy (EIS). The technique inspects impedances typically from tens of hertz to the megahertz range. EIS systems are simpler to construct than optical systems and more compatible with microtechnology, as well as more reliable. Applications have been reported on microfabricated EIS prototypes intended for use in miniaturized systems with microfluidics for direct biological species detection, which are based on changes in solution conductivity.50 The total fluidic path volume in the device is on the order of 30 nl. Flow fields in the closed chip were mapped by particle image velocimetry. Electrical impedance measurements of suspensions of the live microorganism Listeria innocua injected into the chip demonstrate an easy method for detecting the viability of a few bacterial cells. By-products of bacterial metabolism modify the ionic strength of a low-conductivity suspension medium, significantly altering its electrical characteristics. 2.2
Immunosensor Applications
Immunosensors for the detection of bacterial pathogens are rapidly evolving with improved sensitivity and specificity. Many companies such as Roche, Morningstar, and Diagnology have developed simple dipstick/dot blot tests for rapid detection of enteric pathogens, while others are developing sensitive, immunosensors that selectively detect antigenic targets for example, Molecular Devices’ Threshold System, ILA based on sandwich ELISA immunological detection of antigen. Although, immunosensors have greatly decreased the time of sample analysis, they are not as sensitive as nucleic acid–based ones (detection limit about 102 cfu).12 2.3
DNA Sensors for Microorganism Detection
Clinical applications of nucleic acid (gene) probes represent an intensive area of research.51 The
8
BIOSENSOR APPLICATIONS
nucleic acid probe describes a segment of nucleic acid that specifically recognizes and binds to a nucleic acid target. The recognition is dependent upon the formation of a stable duplex between the two nucleic acid strands. This is different from the antigen–antibody complex formation where hydrophobic, ionic, and hydrogen bonds are involved. Moreover, the nucleic acid coupling takes place at regular (nucleotide) intervals along the chain of the nucleic acid duplex, whereas antigen–antibody linkage occurs only at a few specific sites (epitopes). Although nucleic acid recognition is very stable, the main advantage of DNA-based sensors is that they can be easily regenerated through melting of the duplex by controlling buffer concentration and other variables.52 The detection of specific nucleic acid sequences provides the basis for detecting a wide variety of bacterial and viral pathogens. Conventional detection methods of a specific DNA use either radiolabeled probes53 or gene amplification (the PCR).54 Since both techniques suffer from the short shelf life of labeled probes, high cost, hazards, disposal problems of the radioactive residues, and from relatively long time for analysis, new DNA-biosensor technology was introduced, which can operate under special conditions.51,55 With respect to the nature of the physical transducer used, the DNA sensors can be classified as electrochemical, optical, or gravimetric.
2.3.1 Electrochemical DNA Biosensors
Recently, detection of DNA sequences to the waterborne pathogen Cryptosporidium have been developed.56 The sensor relies on the immobilization of a specific oligonucleotide to Cryptosporidium onto the carbon-paste transducer and employs a highly sensitive chronopotentiometric transduction mode for monitoring the hybridization event. After a 20–30-min hybridization time very sensitive detection of Cryptosporidium was achieved. Similar hybridization-chronopotentiometric schemes were developed for detection of pathogens such as Giardia, E. coli, and Mycobacterium tuberculosis (MTB).56,57 In particular, a biosensor for the determination of short sequences from MTB has been described. The sensor relies on modification of the carbon-paste transducer with
27- or 36-mer oligonucleotide probes and their hybridization to complementary strands from the MTB DNA direct repeat region. Chronopotentiometry is employed to transduce the hybridization event. Short (5–15 min) hybridization periods permit quantitation of nanogram per milliliter levels of MTB target DNA to transduce the hybridization event.56 2.3.2 Optical DNA Biosensors
A fiber-optic DNA sensor array is capable of simultaneously monitoring multiple hybridization events. Typically, DNA probes are immobilized in an acrylamide-based polymer matrix on the surface of an optical fiber. Sample DNA is amplified by PCR and real-time hybridization of 5 -fluorescein isothiocyanate–labeled target oligonucleotides to the array is monitored by following fluorescence emission at 530 nm. Detection of labeled target oligonucleotides in the range of 0.2–196 nmol l−1 is possible with these systems and identification of a point mutation in the H-ras oncogene PCR product is a good proof of concept.58 SPR and evanescent wave sensing using optical waveguides can be used to enhance the fluorescence emission of labeled oligonucleotides bound to surface-attached probes. SPR is efficient for the study of association and dissociation kinetics as well as affinity constants for binding of complimentary target strands in solution. The lowest detectable concentration of target oligonucleotides (9.2 nmol l−1 ) compares favorably with other biosensor methods that require labels. Regeneration of the surface-immobilized probe is also possible, allowing reuse of the sensor without significant loss of hybridization activity.59,60
2.3.3 Gravimetric Biosensors
Gravimetric biosensor technology is based on thinfilm bulk acoustic wave resonators on silicon and the feasibility of detecting DNA and protein molecules has been demonstrated. The detection principle of these sensors is label-free and relies on a resonance frequency shift caused by mass loading of an acoustic resonator, a principle very well known from QCM. Integrated zinc oxide
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
bulk acoustic wave resonators with resonance frequencies around 2 GHz have been fabricated, employing an acoustic mirror for isolation from the silicon substrate. DNA oligos have been thiolcoupled to the gold electrode by on-wafer dispensing. In a further step, samples have either been hybridized or alternatively a protein has been coupled to a receptor. Measurements have demonstrated that the new biosensor is capable of both protein detection as well as DNA hybridization without using a label. Owing to the substantially higher oscillation frequency, these sensors have demonstrated much higher sensitivity and resolution compared to QCM.61 3 NANOTECHNOLOGY AND BIOSENSORS
New technologies such as “nanotechnology” hold considerable promise for advances in the development of immunosensors for pharmaceutical and medical diagnostic applications (particularly in proteomics and cellomics).62 Nanotechnology involves the scaling down to microfluidic and nanofluidic biochips and the design and construction of platforms from the bottom up. The result of ongoing nanodiagnostic research will be improvements in the sensitivity and extent of the present limits of molecular diagnostics. Miniaturization is key for this technology, focusing on the integration of all steps of an analytical process into a singledevice (known as “lab on chip”), which will be partly disposable.63 Some of the earliest applications of nanotechnology reported for molecular diagnostics involve the use of nanoparticles; however, there is some concern about their potential effects on the human body and the environment. Nonetheless, nanotechnology has great potential for the production of in-dwelling controlled-release devices with autonomous operation that is responsive to individual needs. This has led to much research focused on the development of implantable, inexpensive immunosensors64 for clinical applications. 3.1
Nanotechnological Methods for the Detection of Pathogenic Microorganisms and Viruses
The detection of microorganisms and viruses using a “portable” atomic force microscope (AFM)65
9
have been reported. The method is based on the creation of an immunochip with highly specific antibodies and a miniaturized scanning probe microscope performs the detection of the captured material. The AFM has the ability to sense tiny bumps on the surface at the nanometer scale. Such a technique is very sensitive and does not destroy the biological entities, so they can be further analyzed. The typical immunochip surface is produced with the Langmuir–Blodgett (LB) method66 using amphiphilic polyelectrolytes and includes (i) production of an affinity surface (antibodies, receptors, and DNA (RNA) probes can be employed); (ii) performance of specific adsorption of the substance bearing the analyte; (iii) scanning of the surface; and (iv) image analysis and identification of the biological agent using pattern-recognition techniques. This method was demonstrated for analysis of Coxiella burnetii, vaccinia virus, and Yersinia pestis with a high sensitivity of down to a few bound entities.67 At this stage there are no practical devices for field use due to size constraints and cost.
3.2
Nanobiosensor Applications
Another application that utilizes the capabilities of the AFM technology for virus detection is based on the ViriChip device,68 a small silicon chip about 6 mm across that accommodates tiny droplets of antibodies on the surface. The chip can be printed with hundreds of different antibodies that can then be used for analysis in record time of different viral infectious agents simultaneously, using just a single drop of blood from the patient. These antibodies serve as receptor capture surfaces for viruses, which attach themselves selectively to them. Once the viruses have landed on a particular droplet, they can be detected using the AFM technology. Researchers have demonstrated a proof of principle for this technique by detecting six different strains of Coxsackie B virus, a virus that causes symptoms ranging from mild cold to death and is one of the key factors leading to the failure of heart transplants. The ability to detect it in a rapid and sensitive way will save thousands of lives by allowing physicians to determine in real time if a donor heart is infected.
10
BIOSENSOR APPLICATIONS
A unique example of nanotechnology implemented for viral detection (e.g., influenza A) in real time and for impure samples is a detector based on nanowire transistors. Such a detector uses antibodies attached to aldehyde-coated nanowires to capture the individual virus particles causing conductance changes of the nanowire, which signals the presence of virus. The researchers found that the duration of the bind-and-release cycle depends on the density of the antibody proteins on the nanowires. The cycle averaged just over 1 s at a low concentration of antibody proteins, about 20 s at a moderate density, and 5–10 min at a high density. This chip detector can be useful for studying how viruses bind to receptors by determining which viruses bind to which receptors, how long virus particles bind to receptors, and what substances block or disrupt binding. The device can also eventually be used to detect individual biomolecules, including viral DNA and proteins.
4 LAB-ON-CHIP TECHNOLOGIES
Microfluidic devices integrating sample handling, reagent mixing, separation, and detection processes are of considerable interest. Since the early 1990s, when the modern concept of the micro total analysis system (µTAS, or lab on a chip) was proposed by Manz et al.69 considerable effort was made toward the development of highly miniaturized analytical systems. Miniaturization revealed many potential benefits including low consumption of costly reagents (nanoscale volumes) and power, minimized handling of dangerous materials, short reaction times, portability, and versatility in design, and capability for parallel operations. Such “miniaturized sensors” can be ideal tools for monitoring personal exposure to individual compounds and pathogens.28,70 In order to prove the principle, many examples of bioassays and biological procedures have been miniaturized into a chip format including PCR,71 DNA analysis and sequencing,72 electrophoresis,73 immunoassays,74 and intra- and intercellular analysis.75 The main challenges in micro- and nanofluidics, however, are the integration of multiple assays and functional components into a single chip to perform a total analysis of the sample.
5 PORTABLE DEVICES FOR DETECTION OF ‘‘TROPICAL’’ PATHOGENIC VIRUSES AND BACTERIA – EXAMPLES 5.1
Devices Already Operable in the Field
5.1.1 Tuberculosis
TB is a disease of increasing importance. Mortality is highest in the tropics, where over three-quarters of cases occur. Annually over three million people die from TB and one-third of the world population is infected with MTB. Patients spread the disease by producing aerosols containing the MTB bacteria. Persons that have close contact with these patients inhale these microdroplets and thus become infected. The mycobacteria multiply in the lung and can cause disease in 10% of infected people. It is estimated that the incidence of TB worldwide and the number of cases attributable to coexisting HIV infection will continue to increase substantially during the next decade. Most of this burden occurs among the low-income countries of the world, particularly those in southeast Asia and sub-Saharan Africa. Few systems for the detection of the pathogenic bacteria MTB are disposable. One qualitative diagnostic kit for detection of MTB DNA in clinical samples such as sputum, urine, and pleural aspiration contains TB lysis solution for DNA extraction and reagents for PCR. Part of the sputum samples that are prepared for culture may be used for PCR. Total processing time for 10 clinical samples is 5 h. Ready-to-use PCR mix, positive control, and other qualified reagents along with an easy to follow protocol are included. In this assay specific primers amplify conserved regions in the MTB genome. Using this kit, as few as 20 bacteria per ml can be detected (CinnaGen Inc.). Another extensively used kit is provided by Gen-Probe (San Diego, CA) and is highly sensitive and specific for bacterial detection. The detection takes place in contaminated broth cultures in about 4 days, which is about 12 days shorter than when a non-amplified DNA probe alone76 is employed. Other systems available for TB detection include the COBAS AMPLICOR (Roche, Switzerland) and the BD ProbeTec ET (Franklin Lakes, NJ). COBAS is a commercial amplification system less
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
sensitive than mycobacteria growth indicator tubes (MGIT) but better than solid media (Ogawa).77
5.1.2 E. coli O157:H7
Portable detection kits available in the market have been developed for E. coli O157:H7. The Immunocard STAT system from Meridian Diagnostics (Cincinnati, OH) tests for the presence of E. coli O157:H7 in just 10 min. The test can be performed either directly on stool or on overnight broth cultures. Stool material is diluted and added to the sample port of the device. The analyte is immobilized on gold particles coated with a monoclonal antibody specific for the E. coli O157 lipopolysaccharide. This detection system apparently has a specificity of 95%. A portable colorimetric immunoassay using antibody-directed liposomes encapsulating dye has also been developed. Antibodies (anti-E. coli O157:H7 ) thiolated by 2-iminothiolane were coupled to maleide-tagged liposomes encapsulating sulforhodamine (the marker dye). A sandwich format was used to allow for capillary migration of wicking agent. The color density of the measurements was directly proportional to the amount of the E. coli in the sample. The immunoassay does not need washing and incubation steps and can be performed in 8 min with a low detection limit of 104 cfu (colony-forming units) ml−1 .78
5.1.3 Gonorrhoeae
GonoGen is a monoclonal antibody-based coagglutination test intended for the confirmatory identification of Neisseria gonorrhoeae. The test does not require isolated, viable, or fresh cultures. After heating the specimen, a positive reaction will be indicated by the clumping with the detection reagent. GonoGen II is another monoclonal antibody–based colorimetric test intended for the confirmatory identification of N. gonorrhoeae. The test requires less than 7 min to run with no heating or pretreatment. The test does not require isolated, viable, or fresh cultures. GonoGen II eliminates agglutination, guesswork, by developing a red dot for a positive reaction (New Horizons Diagnostics, Columbia, MD). Finally, Roche developed a
11
multiplex AMPLICOR PCR test for female urine samples and wet and dry endocervical swabs (ES) for N. gonorrhoeae detection.79 The system makes use of an internal amplification control, being highly sensitive and specific in particular with ES.
5.1.4 Salmonella Typhi
Since typhoid fever annually afflicts about 17 million people (particular those from southeast Asia, Africa, and Latin America), scientists’ efforts have been focused on early diagnostic techniques. Researchers have developed a dipstick assay for the detection of Salmonella Typhi–reactive immunoglobulin M (IgM) antibodies. The dipstick assay is a simplified version of the ELISA, providing either a positive or a negative result, and using stabilized components that can be stored for more than 2 years outside the refrigerator. ELISA for typhoid fever has been found superior to the Widal test.80 The complete genetic code of Salmonella Typhi (responsible for typhoid fever)81 has recently been deciphered, which raises hope for eventual complete eradication of the disease.
5.1.5 Visceral Leishmaniasis
Visceral leishmaniasis (VL) is the most severe form of leishmaniasis. The disease is fatal if left untreated. The diagnosis of human VL is difficult. The principal signs of VL are an enlarged spleen and a prolonged irregular fever. Other signs and symptoms include loss of weight, pallor, enlarged liver, enlarged lymph nodes, anemia, cough, and diarrhea. These signs and symptoms may mimic those of malaria, typhoid, TB, schistosomiasis, and a number of other diseases. Clinical suspicion may be confirmed directly by the detection of parasites in patient material or by culture. However, sample collection is invasive for the patient and parasite isolation by culture is time-consuming, expensive, and difficult. Owing to the limitations of the aforementioned direct diagnostic methods, a number of indirect immunological methods, such as indirect immunofluorescent-antibody tests, ELISAs, and a direct agglutination test (DAT), have been developed. DAT remains the first-line diagnostic tool in many developing countries such as Ethiopia and
12
BIOSENSOR APPLICATIONS
Sudan. It is a simple and economical test with a high sensitivity and specificity. A problem with DAT is that the often-used aqueous antigen is not heat-stable, thus requiring refrigeration. To obviate this limitation a freeze-dried antigen has been developed by KIT Biomedical Research that remains stable at ambient temperature for years. The sensitivity and specificity of this freeze-dried antigen is high. A drawback of the DAT is the relatively long incubation time (18 h; results available only the next day) and the fact that serial dilutions of blood or serum must be made, which makes the test less suitable for screening large numbers of samples. In order to circumvent this problem, a kit based on a fast agglutination screening test (FAST) for detection of anti-Leishmania antibodies in less that 4 h, in serum samples from human patients with VL, was developed.82
5.1.6 Leptospirosis
Leptospirosis is a zoonotic disease with a worldwide distribution. The disease, also known as Weil’s syndrome, is easily confused with other febrile illnesses including viral hemorrhagic fevers. Laboratory confirmation is essential for a proper diagnosis. Culture, the microscopic agglutination test (MAT) and ELISA for the detection of specific immunoglobulin M (IgM) antibodies are important standard laboratory tests for the confirmation of leptospirosis. KIT Biomedical Research has developed a number of rapid and robust tests including a dipstick assay, a lateral flow test, and a latex agglutination test that can be used outside the established laboratory as an alternative to the complicated standard tests. The dipstick assay is based on the binding of specific IgM antibodies to a broadly reactive antigen prepared from a nonpathogenic strain. The use of the broadly reactive antigen ensures the detection of a wide range of commonly occurring serotypes. The assay utilizes a stabilized detection reagent that can be stored without the need for refrigeration for at least 2 years without losing reactivity. The result of the dipstick assay is obtained after 3 h and no special equipment is required to perform the assay.82 Like the dipstick assay, the lateral flow test is aimed at the detection of Leptospira-specific
IgM antibodies in human serum or whole blood samples. The assay is similarly based on the binding of specific IgM antibodies to a broadly reactive antigen prepared from a nonpathogenic strain ensuring detection of a wide range of serotypes. The assay similarly utilizes stabilized components and the result of the lateral flow assay is obtained within 10 min. No special equipment is required to perform the assay.82 The LeptoTek Dri Dot assay consists of colored latex particles activated with a broadly reactive Leptospira antigen that is dried onto an agglutination card. The assay is based on the binding of Leptospira-specific antibodies, present in the serum sample, to the Leptospira antigen causing a fine granular agglutination that tends to settle at the edge of the droplet (the positive result). The assay is performed by suspending the dried detection reagent in 10 µl of serum using a plastic stick. The liquid is then mixed further by gently swirling the card. Agglutination occurs within 30 s.82
5.1.7 Mycobacterium Leprae
KIT Biomedical Research has also developed a simple dipstick assay for the detection of antibodies to a specific component of Mycobacterium leprae (ML). The dipstick assay is aimed at the rapid detection of ML-specific IgM antibodies in human serum or whole blood samples. The dipstick assay is based on the binding of specific IgM antibodies to a semisynthetic antigen consisting of the terminal sugar groups of the phenolic glycolipid-I (PGL-I) antigen of ML attached to bovine serum albumin. The use of this antigen ensures that the ML dipstick has a sensitivity and specificity that is comparable to ELISA. The assay utilizes a stabilized detection reagent that can be stored without the need for refrigeration for at least 2 years without losing its reactivity. The result of the dipstick assay is obtained after 3 h and no special equipment is required to perform or read the assay.82
5.1.8 Brucellosis
Brucellosis is an important but often neglected cause of morbidity in many regions of the
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
world especially in developing areas of the Mediterranean region, the Middle East, western Asia, and parts of Africa and Latin America. The disease is most common in rural areas and among those involved in animal husbandry. Brucellosis also occurs in urban settings when animals are kept in compounds around houses, among meat packers, dairy workers, and veterinarians. Brucella abortus, Brucella suis, and Brucella melitensis are the causative agents. The treatment of chronic brucellosis is complicated and requires prolonged medication compared to acute brucellosis. The disease should be diagnosed early and the patient treated promptly. Typical severe acute brucellosis in its early stages cannot be diagnosed on clinical grounds alone. KIT Biomedical Research has developed simple dipstick and flow assays for the detection of Brucella-specific IgM and IgG antibodies in human serum samples. The dipstick assay is aimed at the rapid detection of Brucella-specific IgM antibodies in human serum or whole blood samples from patients in the early stage of the disease. The dipstick assay is based on the binding of specific IgM antibodies to a lipolysaccharide fraction prepared from B. abortus. The assay utilizes stabilized nonenzymatic detection reagents that can be stored without the need for refrigeration for at least 2 years without losing reactivity. The result of the dipstick assay is obtained after 3 h and no special equipment is required to perform the assay.82 KIT Biomedical Research has also developed a new assay system for the serodiagnosis of human brucellosis. The assay consists of two tests: one for the detection of Brucella-specific IgM antibodies in the serodiagnosis of patients with an acute infection and one for the detection Brucellaspecific IgG antibodies in the serodiagnosis of patients with persistent or recurrent infection. These Brucella IgM and IgG flow assays are very simple to apply, provide a quick result, and are most ideal for developing countries and rural settings.82
13
qualitative NASBA has recently been further developed into a quantitative NASBA that allows for the quantification of Plasmodium falciparum over a wide range of levels of parasitemia, 50–108 parasites per ml of blood. Since only 50 µl of blood is subjected to nucleic acid isolation, 50 parasites per ml was considered to be the lower threshold of detection, which is approximately 50× more sensitive than conventional microscopy.82 Given the distribution of P. falciparum in many third world countries and the relative paucity of well-equipped laboratories, the development of a rapid on-the-spot diagnostic for P. falciparum infection is very timely. Presently, two diagnostic test kits namely ParaSight -F, a dipstick antigencapture assay (Becton Dickinson, Sparks, MD), and immunochromatographic test (ICT Malaria Pf , ICT Diagnostics, Brookvale, NSW, Australia) are available for rapid diagnosis of P. falciparum infection. Both these tests are based on detection of circulating antigen from P. falciparum histidinerich protein-2 (Pf HRP-2) in whole blood. It is a water-soluble protein synthesized by the parasite and released from the P. falciparum–infected erythrocytes. Both these test kits are qualitative test methods based on the presence or absence of P. falciparum–specific antigen in the blood, and results may not always correlate well with the other methods that detect presence of parasite in the peripheral blood. However, these kits are simple to use for on-the-spot diagnosis of P. falciparum infection and do not require special equipment and can be performed with minimum skill. It takes less than 8 min to get a definite diagnosis so that treatment can begin without any delay; the latter being the prime cause of mortality due to malaria.83 5.2
Field-operable Devices Under Development
5.2.1 PCR Units 5.1.9 Malaria
KIT Biomedical Research has developed a qualitative nucleic acid sequence–based amplification (NASBA) procedure for the detection and semiquantification of Plasmodium parasites. The
In late 1996, Lawrence Livermore laboratory delivered to the US Army the first fully portable, battery-powered, real-time DNA analysis system. To detect DNA in a sample, a synthesized DNA probe or primer tagged with a fluorescent dye is introduced into the sample before it is inserted
14
BIOSENSOR APPLICATIONS
into the heater chamber. Each probe or primer is designed for a specific organism that is the causative agent of diseases such as anthrax, plague, and so on. If that organism is present in the sample, the probe attaches to its DNA. By measuring the sample’s fluorescence, the instrument reports the presence (or absence) of the targeted organism. In Livermore’s portable unit, the thermal cycling process takes place in a micromachined, silicon chamber that has integrated heaters, cooling surfaces, and windows through which detection takes place. The PCR reaction and DNA analysis take place in a disposable polypropylene reaction tube inserted into the chamber. Because of the low thermal mass and integrated nature of Livermore’s silicon chambers, they require very low power and can be heated and cooled much faster than conventional units. So the unit is not only portable but also much faster and more energy-efficient than benchtop models. A multiple-chamber unit that enables the analysis of many samples at the same time has been field-tested. Multiplex PCR packages are still under development for the simultaneous detection of eight important viruses of swine: classical swine fever virus, African swine fever virus, porcine reproductive and respiratory syndrome virus, Aujeszky’s disease virus, porcine parvovirus, swine vesicular disease virus, foot and mouth disease virus, and vesicular stomatitis virus. To simplify and accelerate the work, robotic nucleic acid extraction and pipetting are incorporated. This demonstrates that PCR diagnostic procedures can be rapid, robust, and automated.84 In addition, the sensitivity of each nested PCR within these systems is very high; 1–10 genomic copies of the target viruses can be detected. As a result, the simultaneous nested PCR assays of the multiplex packages provide very high specificity.
transport, have the advantage of a rapid time to result, and can easily be repeated.
5.2.3 Mini-flow Cytometer
Recently, Lawrence Livermore’s laboratories reported a prototype for a miniature flow cytometer (miniFlow ) that is portable and sensitive. Over the past two decades, flow cytometers have been used in laboratories to analyze cells and their characteristics, perform blood typing, test for diseases and viruses, and identify and separate out particular cells. These capabilities are enabled in the Livermore device through a technique that eases alignment and increases the accuracy of the standard flow-cytometric techniques. In a traditional flow cytometer, the cells flow in single file in solution while the experimenter directs one or more beams of laser light at them and observes the scattered light, which is caused by variations in the cells or DNA. Instead of using a microscope lens or an externally positioned optical fiber as a detector, the Livermore method uses the flow stream itself as a waveguide for the laser light, capturing the light and transmitting it to an optical detector. This approach not only eliminates the alignment problems that plague traditional flow cytometers but also collects 10 times more light than a microscope lens does. In the future, simplification of the alignment and more light collection will facilitate better and faster analysis. Bacteria are large enough for individual detection in the miniFlow, but viruses and proteins are not. So beads large enough to be detected are coated with an antibody and added to the sample. The virus or protein attaches itself to the bead and can then be detected. When different beads are coated with different antibodies, simultaneous detection of several biological agents is possible.
5.2.2 Pen-side Test for Antibody Detection
Genesis Diagnostics designed a pen-side test for the reaction between antibody and antigen and based on a chromatographic technology that maybe replaced in the future by biosensors. Several other companies85 are also working on this test. One prototype is based on a pan-serotype monoclonal antibody for capture of antigens. Penside tests do not require any specialized sample
5.2.4 Virus Batteries
Belcher and her team are developing a way to actually “grow” rechargeable batteries with the help of viruses.86 The team is forcing the viruses to interact with materials that they normally do not interact with. They use bacteriophage (M13) mixed together with a metal or other materials
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
on which millions of them can align and stack themselves into orderly layers, creating a new material. The team also uses M13 viruses to synthesize and assemble nanowires of cobalt oxide at room temperature. By incorporating gold-binding peptides into the filament coat, hybrid gold–cobalt oxide wires were formed that improved battery capacity. Combining virus-templated synthesis at the peptide level with methods for controlling twodimensional assembly of viruses on polyelectrolyte multilayers provides a systematic platform for integrating the nanomaterials to form thin, flexible lithium ion batteries. 5.2.5 Biochips
For rapid and accurate field identification of biological and chemical agents, biochips in concert with portable readers are being developed. One example is a system designed at Argonne National Laboratory for pathogen detection in less than 2 h. Argonne’s biochips contain hundreds to thousands of test positions, each chip being a matrix of threedimensional gel pads about 100 × 100 × 20 µm in size. These pads are in defined locations such that reaction of a sample at a given position immediately identifies the sample. A segment of a DNA strand, protein, peptide, or antibody is inserted into each pad, tailoring it to recognize a specific biological agent or biochemical signature.87,88 The biochip also makes use of PCR, enabling lowabundance bacteria and threat agents to be detected with relative ease, within hours instead of days.89 With Argonne’s miniaturized portable system one can simultaneously detect a multitude of bacteria and other agents from a single sample.90
5.2.6 BioPen
The BioPen is a penlike instrument that runs an automatic bioassay protocol at the end of a fiberoptic tip being developed in the group of Prof. R. Marks at Ben-Gurion University. The outcome of this assay, light radiation, is produced if the patient carries the pathogenic markers or if the target pathogen is detected. The light is translated ultimately into a number or a positive/negative answer on an LCD screen at the far end of the “cap” of the BioPen. The BioPen
15
represents the first test that presents the full capabilities of bioassays in an easy-to-handle penshaped device. Bioassays on this device are based on specific modification of an optical fiber with a test-adapted biorecognition entity. The novelty lies in the development of original genetically engineered bioreceptors and the chemistry used to bind them covalently to the fiber surface. Necessary fluids are brought in through a unique shape-adapted microfluidic system (HydroLogic assembly) to the fiber-optic tip. A positive signal is reported by light emission transduced through the fiber to an innovative ultracompact photosensitive platform able to perform single-photon counting. The innovative technologies incorporated in the BioPen constitute major breakthroughs in several fields such as surface chemistry, microoptoelectronics, microfluidics, and biology. In general, BioPen demonstrates several improvements over existing systems. First, the entire test device is expected to weigh no more than 300 g with a penlike size. It can be therefore used as a personal bioassay or serve for in-the-field testing without requiring any additional systems or laboratory installation. In addition, the disposable cone that contains the whole bioassay is completely closed and provides the user with a high level of biocontainment with no risk of contamination and can easily replace any desired bioassay. The bioassay itself will be performed in 20 min and demonstrates a better level of sensitivity than commonly used fluorescent tests due to the combined luminescence/fiber/photocounting assembly that results in a very low background. The multiplicity of bioreporters that can be coupled to the fiber (DNA/RNA, protein, whole cells, etc.) also makes the BioPen a remarkable tool for detecting not only biological entities but also a wide range of chemicals and toxins91,92 that cannot be detected with standard antibody-based sensors.
5.2.7 Prototype of a Sensor to Smell Bacteria
KIT Biomedical Research, together with Cranfield University in the United Kingdom, have joined their expertise for the development and optimization of a portable prototype gas/volatile sensor array and associated computational analysis, for the rapid detection, identification, and analysis of MTB in culture, sputum, and ultimately breath
16
BIOSENSOR APPLICATIONS
samples. The aim is to develop a simple breath analysis device capable of distinguishing TB from other lung diseases.82
5.2.8 Lab-on-a-chip Portables
The development of a portable lab on a chip that could let doctors identify the strain of flu viruses in less than 2 h was reported in June, 2005.93 The device, called the Genotyper, integrates fluidic and thermal components such as heaters, temperature sensors, and addressable valves to perform two independent serial biochemical reactions, followed by an electrophoretic separation. Integration of multiple steps of biological assays on a single device provides significant advantages in terms of sample/reagent consumption, process automation, analysis speed and efficiency, and contamination reduction. The key components (phase-change valves, thermally isolated reaction chambers, gel electrophoresis, and pulsed drop motion) of this device are electronically addressable and simple to operate—properties that could eventually lead to autonomous operation. The device’s compact design and mass-production technology make it an attractive platform for a variety of genetic analyses. Ultimately, the Genotyper will be fully portable (about the size of a TV remote control), with wireless connectivity, and thus able to track the spread of existing or emerging flu strains around the world. The Genotyper identifies flu type through a process resembling the genetic fingerprinting used in DNA identification. The process uses standard biochemical assays, only miniaturized. First, the influenza virus RNA is converted to DNA using reverse transcriptase. Then, a segment of the DNA is amplified manyfold through standard PCR. Finally, enzymes are released that “digest” or cut the amplified DNA in a sequence-specific manner. The DNA is then stained and pushed through a polymer gel matrix by an electric field. The DNA pieces move at rates controlled by their size. One type of flu, for example, would have DNA that is not cut by the enzyme, while another is cut. So, DNA bands are formed, whose locations within the gel determine if the DNA is cut or not. This provides a “fingerprint” that is diagnostic for the strain of flu. Different types of DNAs can be tested and identified using the Genotyper device
by simply using different reagents. To demonstrate this versatility, DNA from a human and a mouse were “typed” with this device along with strains of influenza. Currently, there are different versions of the Genotyper chip measuring between 1 and 2 in. in length and width. The chip does not yet include a purification unit, and there is still a need for external “readers” to see the DNA bands. Some versions require external air pressure while others generate pressure within the chip itself. The Genotyper is still in the development phase until its reliability can be established. Recently, another research team from a Singapore-based medical firm Veredus Laboratories has designed a disposable laboratory on a chip that can detect various strains of avian influenza (H5N1) and other influenza viruses (influenza A or B), in a single test, rather than conducting a series of tests, as is now required. The chip is a plastic slide, about 75 by 25 mm, containing a microscopic laboratory with its own plumbing, pumps, and temperature controls. To use such a “lab”, a droplet of a sample is placed on the slide and traces of RNA in the droplet are amplified using the reverse transcription PCR. The amplified DNA copies are pumped to other areas of the chip for comparison with particular DNA profiles, such as those of the flu virus strains. A match causes the appropriate part of the chip to fluoresce. Processing the sample takes about an hour, after which the results can be obtained in seconds with a portable optical reader. This lab-on-chip approach should also reduce the risk of cross-contamination inherent in conventional analytic methods.
6 CONCLUSIONS AND FUTURE TRENDS
The detection of some tropical pathogens and other dangerous microbial contaminants using conventional and improved identification technologies has been summarized in the present chapter. Also, the advantages and limitations of particular detection techniques for specific pathogens are briefly pointed out. With currently available technologies, medical staff faces a choice between faster, bedside tests that indicate the presence of a virus but do not specifically identify the lethal strain, or more precise testing that typically requires sending
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
samples to a laboratory. To be safe, it is still better to perform routine laboratory methods in parallel with use of advanced technologies, even though classical technologies are often time consuming, to obtain a better track record of positive correlation. Although new and improved methods for detection will continually be developed, it must always be remembered that preventative measures are key for reducing the rate of disease appearance. In the same vein, scientists are making huge efforts to create vaccines to protect humans from developing harmful diseases. Thus, a new TB vaccine is set to undergo human trials, the first in 80 years. If successful, it will likely be used in tandem with the current bacillus Calmette–Guerin (BCG) vaccine.94 Nowadays, most of the existing immunological methods are coupled with electronic sensing modules.95 An automated system based on solid-phase ELISA coupled with a multichannel optical flow cell with a sensor composed of a light emitting diode and a photodetector has been elaborated for the simultaneous detection of staphylococcal enterotoxin B, bacteriophage M13, and E. coli.96 Another system that uses a light-addressable potentiometric sensor and a flowthrough immunofiltration enzyme assay, which can simultaneously detect eight analytes in 15 min, has also been reported.97 All these systems present multiple advantages such as automation, rapidity, and throughput. In the near future, advances in immunoassays coupled with biosensor technologies will provide simpler designs and higher sensitivity along with results being recorded in real time. Most importantly, however, it should be clear that the most crucial and pivotal component for any type of biosensor under development is the molecular recognition entity such as antibody, aptamer, enzyme, nucleic acid, receptor, and so on. Sensitive and specific identification of pathogens such as bacteria and viruses has been dramatically increased with the introduction of immunoassays and nucleic acid technologies. These technologies have contributed in a major way to the advances made possible through the miniaturized devices such as microarrays or labon-chip systems. Already, several academic and nonacademic institutions such as Nanogen, Caliper Technologies, and Lawrence Livermore laboratories are deeply involved in the design of smart, miniaturized, and portable devices that will require
17
only microliter quantities of reagents for specific microbial detection. Finally, continuous improvements in the affinity, specificity, and molecular recognition of bioreceptor capture moities will synergize with development of more accessible pathogen detection technologies that will easily be integrated in routine diagnostics.
REFERENCES 1. Y. Compton, Military Chemical and Biological Agents, Telford Press, Caldwell, NJ, 1987. 2. Y. H. Shangkuan and H. C. Lin, Application of random amplified polymorphic DNA analysis to differentiate strains of Salmonella typhi and other Salmonella species. Journal of Applied Microbiology, 1998, 85, 693–702. 3. S. T. Nichol, J. Arikawa, and Y. Kawaoka, Emerging viral diseases. Proceedings of the National Academy of Sciences of the United States of America, 2000, 97, 12411–12412. 4. L. H. Gould and E. Fikrig, West Nile virus: a growing concern. Journal of Clinical Investigation, 2004, 113, 1102–1107. 5. O. Tomori, Impact of yellow fever on the developing world. Advances in Virus Research, 1999, 53, 5–34. 6. S. B. Halstead, Observations related to pathogenesis of dengue hemorrhagic fever. VI. Hypotheses and discussion. Yale Journal of Biology and Medicine, 1970, 42, 350–362. 7. WHO, Dengue/Dengue Hemorrhagic Fever [Online], 2004. 8. R. Cologna, P. M. Armstrong, and R. Rico-Hesse, Selection for virulent dengue viruses occurs in humans and mosquitoes. Journal of Virology, 2005, 79, 853–859. 9. E. S. Lloyd, S. R., Zaki, P. E. Rollin, K. Tshioko, M. A. Bwaka, T. G. Ksiazek, P. Calain, W. J. Shieh, M. K. Konde, E. Verchueren, H. N. Perry, L. Manguindula, J. Kabwau, R. Ndambi, and C. J. Peters, Long-term disease surveillance in Bandundu region, Democratic Republic of the Congo: a model for early detection and prevention of Ebola hemorrhagic fever. Journal of Infectious Diseases, 1999, 179, Suppl 1, S274–S280. 10. P. M. Sharp, D. L. Robertson, F. Gao, and B. H. Hahn, Origins and diversity of human immunodeficiency viruses. Aids, 1994, 8, 27–42. 11. N. C. Rollins, M. Dedicoat, S. Danaviah, T. Page, K. Bishop, I. Kleinschmidt, H. M. Coovadia, and S. A. Cassol, Prevalence, incidence, and mother-to-child transmission of HIV-1 in rural South Africa. Lancet, 2002, 360, 389. 12. S. S. Iqbal, M. W. Mayo, J. G. Bruno, B. V. Bronk, C. A. Batt, and J. P. Chambers, A review of molecular recognition technologies for detection of biological threat agents. Biosensors and Bioelectronics, 2000, 15, 549–578. 13. P. Cattani, G. M. Rossolini, S. Cresti, R. Santangelo, D. R. Burton, R. A. Williamson, P. P. Sanna, and G. Fadda, Detection and typing of herpes simplex viruses by using recombinant immunoglobulin fragments produced in bacteria. Journal of Clinical Microbiology, 1997, 35, 1504–1509.
18
BIOSENSOR APPLICATIONS
14. C. Jehl-Pietri, B. Hugues, M. Andre, J. M. Diez, and A. Bosch, Comparison of immunological and molecular hybridization detection methods for the detection of hepatitis a virus in sewage. Letters in Applied Microbiology, 1993, 17, 162–166. 15. N. Ahmed, A. K. Mohanty, U. Mukhopadhyay, V. K. Batish, and S. Grover, PCR-based rapid detection of Mycobacterium tuberculosis in blood from immunocompetent patients with pulmonary tuberculosis. Journal of Clinical Microbiology, 1998, 36, 3094–3095. 16. X. Mao, L. Yang, X. L. Su, and Y. Li, A nanoparticle amplification based quartz crystal microbalance DNA sensor for detection of escherichia coli O157:H7. Biosensors and Bioelectronics, 2006, 21, 1178–1185. 17. H. Yu and J. G. Bruno, Immunomagnetic-electrochemiluminescent detection of Escherichia coli O157 and Salmonella typhimurium in foods and environmental water samples. Applied and Environment Microbiology, 1996, 62, 587–592. 18. Z. Bukhari, R. M. McCuin, C. R. Fricker, and J. L. Clancy, Immunomagnetic separation of Cryptosporidium parvum from source water samples of various turbidities. Applied and Environment Microbiology, 1998, 64, 4495–4499. 19. Y. Y. Wong, S. P. Ng, M. H. Ng, S. H. Si, S. Z. Yao, and Y. S. Fung, Immunosensor for the differentiation and detection of Salmonella species based on a quartz crystal microbalance. Biosensors and Bioelectronics, 2002, 17, 676–684. 20. S. Jindou, A. Soda, S. Karita, T. Kajino, P. Beguin, J. H. Wu, M. Inagaki, T. Kimura, K. Sakka, and K. Ohmiya, Cohesin-dockerin interactions within and between Clostridium josui and Clostridium thermocellum: binding selectivity between cognate dockerin and cohesin domains and species specificity. Journal of Biological Chemistry, 2004, 279, 9867–9874. 21. A. Hiratsuka, H. Muguruma, K. H. Lee, and I. Karube, Organic plasma process for simple and substrateindependent surface modification of polymeric Biomems devices. Biosensors and Bioelectronics, 2004, 19, 1667–1672. 22. C. A. Bell, J. R. Uhl, T. L. Hadfield, J. C., David, R. F. Meyer, T. F. Smith, and F. R. Cockerill III, Detection of bacillus anthracis DNA by lightcycler PCR. Journal of Clinical Microbiology, 2002, 40, 2897–2902. 23. A. H. Peruski and L. F. Peruski Jr, Immunological methods for detection and identification of infectious disease and biological warfare agents. Clinical and Diagnostic Laboratory Immunology, 2003, 10, 506–513. 24. H. R. Gelderblom and P. R. Hazelton, Specimen collection for electron microscopy. Emerging Infectious Diseases, 2000, 6, 433–434. 25. W. Zhang, P. R. Chipman, J. Corver, P. R. Johnson, Y. Zhang, S. Mukhopadhyay, T. S. Baker, J. H. Strauss, M. G. Rossmann, and R. J. Kuhn, Visualization of membrane protein domains by cryo-electron microscopy of dengue virus. Nature Structural Biology, 2003, 10, 907–912. 26. P. R. Hazelton and H. R. Gelderblom, Electron microscopy for rapid diagnosis of infectious agents in emergent situations. Emerging Infectious Diseases, 2003, 9, 294–303.
27. A. D. Livingston, C. J. Campbell, E. K. Wagner, and P. Ghazal, Biochip sensors for the rapid and sensitive detection of viral disease. Genome Biology, 2005, 6, 112. 28. N. V. Zaytseva, V. N. Goral, R. A. Montagna, and A. J. Baeumner, Development of a microfluidic biosensor module for pathogen detection. Lab on a Chip, 2005, 5, 805–811. 29. W. Gopel and P. Heiduschka, Interface analysis in biosensor design. Biosensors and Bioelectronics, 1995, 10, 853–883. 30. S. H. Jenkins, W. R. Heineman, and H. B. Halsall, Extending the detection limit of solid-phase electrochemical enzyme immunoassay to the attomole level. Analytical Biochemistry, 1988, 168, 292–299. 31. W. G. Hu, H. G. Thompson, A. Z. Alvi, L. P. Nagata, M. R. Suresh, and R. E. Fulton, Development of immunofiltration assay by light addressable potentiometric sensor with genetically biotinylated recombinant antibody for rapid identification of Venezuelan equine encephalitis virus. Journal of Immunological Methods, 2004, 289, 27–35. 32. W. E. Lee, H. G. Thompson, J. G. Hall, R. E. Fulton, and J. P. Wong, Rapid immunofiltration assay of Newcastle disease virus using a silicon sensor. Journal of Immunological Methods, 1993, 166, 123–131. 33. I. Abdel-Hamid, D. Ivnitski, P. Atanasov, and E. Wilkins, Flow-through immunofiltration assay system for rapid detection of E. coli O157:H7. Biosensors and Bioelectronics, 1999, 14, 309–316. 34. R. E. Ionescu, C. Gondran, L. A. Gheber, S. Cosnier, and R. S. Marks, Construction of amperometric immunosensors based on the electrogeneration of a permeable biotinylated polypyrrole film. Analytical Chemistry, 2004, 76, 6808–6813. 35. R. E. Ionescu, G. Gondran, S. Cosnier, L. A. Gheber, and R. S. Marks, Comparison between the performances of amperometric immunosensors for cholera antitoxin based on three enzyme markers. Talanta, 2005, 66, 15–20. 36. R. E. Ionescu, S. Cosnier, G. Herzog, K. Gorky, B. Leshem, S. Herrmann, and R.S. Marks, Amperometric immunosensor for the detection of anti-West Nile Virus IgG using a photoactive copolymer. Enzyme and Microbial technology, 2006, 40, 403–408. 37. V. Kameswara Rao, G. P. Rai, G. S. Agarwal, and S. Suresh, Amperometric immunosensor for detection of antibodies of Salmonella typhi in patient serum. Analytica Chimica Acta, 2005, 531, 173–177. 38. H. C. Berney, J. Alderman, W. A. Lane, and J. K. Collins, Development of a capacitive immunosensor: a comparison of monoclonal and polyclonal capture antibodies as the primary layer. Journal of Molecular Recognition, 1998, 11, 175–177. 39. Z. Muhammad-Tahir and E. C. Alocilja, A conductometric biosensor for biosecurity. Biosensors and Bioelectronics, 2003, 18, 813–819. 40. Y. M. Bae, B. K. Oh, W. Lee, W. H. Lee, and J. W. Choi, Immunosensor for detection of Yersinia enterocolitica based on imaging ellipsometry. Analytical Chemistry, 2004, 76, 1799–1803. 41. Y. H. Chang, T. C. Chang, E. F. Kao, and C. Chou, Detection of protein a produced by Staphylococcus
FIELD-OPERABLE BIOSENSORS FOR TROPICAL DISPATCH
42.
43.
44.
45.
46.
47.
48.
49.
50.
51. 52.
53.
54. 55.
56.
aureus with a fiber-optic-based biosensor. Bioscience Biotechnology and Biochemistry, 1996, 60, 1571–1574. C. A. Rowe-Taitt, J. J. Cras, C. H. Patterson, J. P. Golden, and F. S. Ligler, A ganglioside-based assay for cholera toxin using an array biosensor. Analytical Biochemistry, 2000, 281, 123–133. T. Konry, A. Novoa, S. Cosnier, and R. S. Marks, Development of an “electroptode” immunosensor: indium tin oxide-coated optical fiber tips conjugated with an electropolymerized thin film with conjugated cholera toxin B subunit. Analytical Chemistry, 2003, 75, 2633–2639. S. Herrmann, B. Leshem, S. Landes, B. Rager-Zisman, and R. S. Marks, Chemiluminescent optical fiber immunosensor for the detection of anti-West Nile virus IgG. Talanta, 2005, 66, 6–14. A. Petrosova, T. Konry, S. Cosnier, I. Trakht, J. Lutwama, E. Rwaguma, A. Chepurnov, E. Muhlberger, L. Lobel, and R. S. Marks, Development of a highly sensitive, field operable biosensor for serological studies of Ebola virus in central Africa. Sensors and Actuators B: Chemical, 2007, 122(2), 578–586. B. A. Cavic, G. L. Hayward, and M. Thompson, Acoustic waves and the study of biochemical macromolecules and cells at the sensor-liquid interface. Analyst, 1999, 124, 1405–1420. A. Janshoff, H. J. Galla, and C. Steinem, Piezoelectric mass-sensing devices as biosensors-an alternative to optical biosensors. Angewandte Chemie International Edition in English, 2000, 39, 4004–4032. F. Aberl, H. Wolf, C. Kosslinger, S. Drost, P. Woias, and S. Koch, HIV serology using piezoelectric immunosensors. Sensors and Actuators B, 1994, 18, 271–275. J. S. Yu, H. X. Liao, A. E. Gerdon, B. Huffman, R. M. Scearce, M. McAdams, S. M. Alam, P. M. Popernack, N. J. Sullivan, D. Wright, D. E. Cliffel, G. J. Nabel, and B. F. Haynes, Detection of Ebola virus envelope using monoclonal and polyclonal antibodies in ELISA, surface plasmon resonance and a quartz crystal microbalance immunosensor. Journal of Virological Methods, 2006, 137, 219–228. R. Gomez, R. Bashir, A. Sarikay, M. R. Ladisch, J. Sturgis, J. P. Robinson, T. Geng, A. K. Bhunia, H. L. Apple, and S. Wereley, Microfluidic biochip for impedance spectroscopy of biological species. Biomedical Microdevices, 2001, 3, 201–209. J. Zhai, H. Cui, and R. Yang, DNA based biosensors. Biotechnology Advances, 1997, 15, 43–58. C. R. Graham, D. Leslie, and D. J. Squirrell, Gene probe assays on a fibre-optic evanescent wave biosensor. Biosensors and Bioelectronics, 1992, 7, 487–493. P. Feng, Commercial assays systems for detection foodborne Salmonella. Journal of Food Protection, 1992, 55, 927–934. K. B. Mullis, The unusual origin of the polymerase chain reaction. Scientific American, 1990, 262, 56–61, 64–55. B. Zhu and G. O. Wang, Current status and prospects for the nucleic-acid biosensors. Progress in Biochemistry and Biophysics, 1997, 24, 510–513. J. Wang, G. Rivas, X. Cai, N. Donatha, H. Shiraishi, D. Luo, and F. S. Valera, Sequence-specific
57.
58.
59.
60.
61.
62.
63.
64. 65.
66.
67.
68.
69.
70.
71.
19
electrochemical biosensing of M. tuberculosis DNA. Analytica Chimica Acta, 1997, 337, 41–48. J. Wang, J. R. Fernandes, and L. T. Kubota, Polishable and renewable DNA hybridization biosensors. Analytical Chemistry, 1998, 70, 3699–3702. B. G. Healey, R. S. Matson, and D. R. Walt, Fiberoptic DNA sensor array capable of detecting point mutations. Analytical Biochemistry, 1997, 251, 270–279. D. Kambhampati, P. E. Nielsen, and W. Knoll, Investigating the kinetics of DNA-DNA and PNA-DNA interactions using surface plasmon resonance-enhanced fluorescence spectroscopy. Biosensors and Bioelectronics, 2001, 16, 1109–1118. H. J. Watts, D. Yeung, and H. Parkes, Real-time detection and quantification of DNA hybridization by an optical biosensor. Analytical Chemistry, 1995, 67, 4283–4289. R. Gabl, H. D. Feucht, H. Zeiniger, G. Eckstein, M. Schreiter, R. Primig, D. Pitzer, and W. Wersing, First results on label-free detection of DNA and protein molecules using a novel integrated sensor technology based on gravimetric detection principles. Biosensors and Bioelectronics, 2004, 19, 615–620. B. M. Cullum and T. Vo-Dinh, The development of optical nanosensors for biological measurements. Trends in Biotechnology, 2000, 18, 388–393. R. A. Felder and G. J. Kost, Automation. Part 1. Modular stepwise automation and the future of diagnostic testing. Medical Laboratory Observer, 1998, 30, 22–24, 26–27. A. P. Turner, Immunosensors: the next generation. Nature Biotechnology, 1997, 15, 421. O. P. Lymans’kyi and O. Lymans’ka, Study of microorganism genome DNA by atomic force microscopy. Tsitologiya I Genetika, 2002, 36, 30–36. A. L. Weisenhorn, H. E. Gaub, H. G. Hansma, R. L. Sinsheimer, G. L. Kelderman, and P. K. Hansma, Imaging single-stranded DNA, antigen-antibody reaction and polymerized Langmuir-Blodgett films with an atomic force microscope. Scanning Microscopy, 1990, 4, 511–516. I. A. Budashov, I. N. Kurochkin, A. K. Denisov, V. V. Skripniuk, and T. A. Shabanov, The use of atomic-force microscopy for the analysis of microbiological objects. Zhurnal Mikrobiologii Epidemiologii I Immunobiologii, 1997, 6, 11–15. K. M. Radke, S. R. Nettikadan, J. C. Johnson, S. G. Vengasandra, and E. Henderson, ViriChip enhances reverse transcriptase polymerase chain reaction in biological fluids and environmental samples. Analytical Biochemistry, 2004, 330, 350–352. A. Manz, N. Graber, and H. M. Wildmer, Miniaturized total chemical analysis systems: a novel concept for chemical sensing. Sensors and Actuators B, 1990, 1, 244–248. L. Hood, J. R. Heath, M. E. Phelps, and B. Lin, Systems biology and new technologies enable predictive and preventative medicine. Science, 2004, 306 640–643. M. Hashimoto, P. C. Chen, M. W. Mitchell, D. E. Nikitopoulos, S. A. Soper, and M. C. Murphy, Rapid PCR in a continuous flow device. Lab on a Chip, 2004, 4, 638–645.
20
BIOSENSOR APPLICATIONS
72. N. Goedecke, B. McKenna, S. El-Difrawy, L. Carey, P. Matsudaira, and D. Ehrlich, A high-performance multilane microdevice system designed for the DNA forensics laboratory. Electrophoresis, 2004, 25, 1678–1686. 73. D. C. Duffy, J. C. McDonald, O. J. A. Schueller, and G. M. Whitesides, Rapid prototyping of microfluidic systems in poly-(dimethylsiloxane). Analytical Chemistry, 1998, 70, 4974–4984. 74. N. Chiem and D. J. Harrison, Microchip-based capillary electrophoresis for immunoassays: analysis of monoclonal antibodies and theophylline. Analytical Chemistry, 1997, 69, 373–378. 75. M. A. McClain, C. T. Culbertson, S. C. Jacobson, N. L. Allbritton, C. E. Sims, and J. M. Ramsey, Microfluidic devices for the high-throughput chemical analysis of cells. Analytical Chemistry, 2003, 75, 5646–5655. 76. X. Zheng, M. Pang, H. D. Engler, S. Tanaka, and T. Reppun, Rapid detection of Mycobacterium tuberculosis in contaminated BACTEC 12B broth cultures by testing with amplified Mycobacterium tuberculosis direct test. Journal of Clinical Microbiology, 2001, 39, 3718–3720. 77. E. J. Oh, Y. J. Park, C. L. Chang, B. K. Kim, and S. M. Kim, Improved detection and differentiation of mycobacteria with combination of Mycobacterium growth indicator tube and Roche COBAS amplicor system in conjunction with duplex PCR. Journal of Microbiological Methods, 2001, 46, 29–36. 78. S. Park and R. A. Durst, Immunoliposome sandwich assay for the detection of Escherichia coli O157:H7. Analytical Biochemistry, 2000, 280, 151–158. 79. L. Mukenge-Tshibaka, M. Alary, F. Bernier, E. van Dyck, C. M. Lowndes, A. Guedou, S. Anagonou, and J. R. Joly, Diagnostic performance of the roche amplicor PCR in detecting Neisseria gonorrhoeae in genitourinary specimens from female sex workers in Cotonou, Benin. Journal of Clinical Microbiology, 2000, 38, 4076–4079. 80. M. Hatta and H. L. Smits, Detection of Salmonella typhi by nested polymerase chain reaction in blood, urine, and stool samples. American Journal of Tropical Medicine and Hygiene, 2007, 76, 139–143. 81. J. Parkhill, G. Dougan, K. D. James, N. R. Thomson, D. Pickard, J. Wain, C. Churcher, K. L. Mungall, S. D. Bentley, M. T. Holden, M. Sebaihia, S. Baker, D. Basham, K. Brooks, T. Chillingworth, P. Connerton, A. Cronin, P. Davis, R. M. Davies, L. Dowd, N. White, J. Farrar, T. Feltwell, N. Hamlin, A. Haque, T. T. Hien, S. Holroyd, K. Jagels, A. Krogh, T. S. Larsen, S. Leather, S. Moule, P. O’Gaora, C. Parry, M. Quail, K. Rutherford, M. Simmonds, J. Skelton, K. Stevens, S. Whitehead, and B. G. Barrell, Complete genome sequence of a multiple drug resistant Salmonella enterica serovar typhi CT18. Nature, 2001, 413, 848–852. 82. Royal Tropical Institute (KIT), Mauritskade 63, 1092 AD, Amsterdam, The Netherlands. 83. V. Dev, Relative utility of dipsticks for diagnosis of malaria in mesoendemic area for Plasmodium falciparum and P. vivax in northeastern India. Vector Borne and Zoonotic Diseases, 2004, 4, 123–130.
84. S. Bel´ak, P. Thor´en, and M. Hakhverdyan, Advances in Diagnostic Techniques. In: 4th International Symposium on Emerging and Re-emerging Pig Diseases Rome, 2003. 85. S. M. Reid, N. P. Ferris, A. Bruning, G. H. Hutchings, Z. Kowalska, and L. Akerblom, Development of a rapid chromatographic strip test for the pen-side detection of foot-and-mouth disease virus antigen. Journal of Virological Methods, 2001, 96, 189–202. 86. K. T. Nam, D. W. Kim, P. J. Yoo, C. Y. Chiang, N. Meethong, P. T. Hammond, Y. M. Chiang, and A. M. Belcher, Virus-enabled synthesis and assembly of nanowires for lithium ion battery electrodes. Science, 2006, 312, 885–888. 87. D. P. Chandler and A. E. Jarrell, Automated purification and suspension array detection of 16S rRNA from soil and sediment extracts by using tunable surface microparticles. Applied and Environment Microbiology, 2004, 70, 2621–2631. 88. J. Zlatanova and A. Mirzabekov, Gel-immobilized microarrays of nucleic acids and proteins. Production and application for macromolecular research. Methods in Molecular Biology, 2001, 170, 17–38. 89. S. V. Tillib, B. N. Strizhkov, and A. D. Mirzabekov, Integration of multiple PCR amplifications and DNA mutation analyses by using oligonucleotide microchip. Analytical Biochemistry, 2001, 292, 155–160. 90. S. G. Bavykin, J. P. Akowski, V. M. Zakhariev, V. E. Barsky, A. N. Perov, and A. D. Mirzabekov, Portable system for microbial sample preparation and oligonucleotide microarray analysis. Applied and Environment Microbiology, 2001, 67, 922–928. 91. B. Polyak, S. Geresh, and R. S. Marks, Synthesis and characterization of a biotin-alginate conjugate and its application in a biosensor construction. Biomacromolecules, 2004, 5, 389–396. 92. B. Polyak, E. Bassis, A. Novodvorets, S. Belkin, and R. S. Marks, Bioluminescent whole cell optical fiber sensor to genotoxicants: system optimization. Sensors and Actuators B-Chemical, 2001, 74, 18–26. 93. C. Allix, P. Supply, and M. Fauville-Dufaux, Utility of fast mycobacterial interspersed repetitive unitvariable number tandem repeat genotyping in clinical mycobacteriological analysis. Clinical Infectious Diseases, 2004, 39, 783–789. 94. M. Tishler and Y. Shoenfeld, BCG immunotherapy–from pathophysiology to clinical practice. Expert Opinion on Drug Safety, 2006, 5, 225–229. 95. A. Bossi, S. A. Piletsky, P. G. Righetti, and A. P. Turner, Capillary electrophoresis coupled to biosensor detection. Journal of Chromatography A, 2000, 892, 143–153. 96. J. Kohn, An immunochromatographic technique. Immunology, 1968, 15, 863–865. 97. K. A. Uithoven, J. C. Schmidt, and M. E. Ballman, Rapid identification of biological warfare agents using an instrument employing a light addressable potentiometric sensor and a flow-through immunofiltrationenzyme assay system. Biosensors and Bioelectronics, 2000, 14, 761–770.
74 Lateral-Flow Immunochromatographic Assays R. J. Davies, S. S. Eapen and S. J. Carlisle Unipath Ltd., Bedford, UK
1 HISTORICAL PERSPECTIVE
In 1988 Unipath launched the first one-step rapid lateral-flow immunochromatographic assay (LFiA), a urine based pregnancy test simple enough for use by the untrained consumer. Prior to this, consumers were offered either miniimmunochemistry, or mini-laboratory kits. The immumochemistry kit involved the transfer of an antibody-coated peg through several solutions in the following sequence, urine sample, antibodyenzyme conjugate, wash buffer, and finally a substrate containing solution that left a colored precipitate on the peg if the urine donor was pregnant. The lab kit included sheep blood cells, pipette, purified water, a mirror, and test tube, and a two hour wait for a result (the first version of the e.p.t. by Warner–Chilcott). The e.p.t. test was affected by vibration and gave a high incidence of false nonpregnant results and could not detect pregnancy before the third day after a missed period.1 Slower, and presumably less accurate tests involving rabbits and frogs were never used in the consumers hands. However, the earliest consumer pregnancy test was described in an ancient Egyptian papyrus of ca 1350–1200 BC.2 Here a woman urinated on a mixture of wheat and barley seeds several times, if the wheat grew it indicated a female child, if the barley grew it indicated a male child, no growth indicated that she was not
pregnant. In 1963 this test was replicated3 and revealed that the urine of nonpregnant women did not promote growth, while that of pregnant women did in 70% of the tests, no indication of the sex of the infant could be discerned from this modern replication. The use of a nonenzymatic, color generating label greatly simplified pregnancy testing, and later other tests. The desire for home testing was the impetus for the first immunochromatographic assays. In its latest guise, Clearblue Digital (released 2003), utilizes an inexpensive optical reader to overcome any difficulties users may have in interpreting the test line. To date many different LFiAs have been developed for use with different sample fluids, viz : sputum,4 blood,5 plasma and/or serum,6 fecal,7 food,8 for the measurement of viruses,9 drugs,10 micro-organisms,11 spores,12 polymerized nucleic acid sequences.13 Some of these tests are so easy to use that they have been CLIA waived United States.14 However, the apparent simplicity of many of these tests belies the great pains the manufacturers have taken in their construction.
2 LFiAs: BASIC OPERATING PRINCIPLES
LFiAs utilize porous membranes, antibodies and usually a visible signal generating system to produce sensitive, disposable, and easy to use tests.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Fluid flow is sustained by means of capillary forces and resisted by viscous drag generated by the materials used to construct the test strip. All components in the test strip must be water wettable and hydraulically connected—usually by means of small overlaps of the test strip components. These are either formed when the strip is laminated together on an adhesive tape, or by holding them together with pinch points designed into the plastic strip housing. In general the intrinsic capillary pull of the different functional zones of the strip increase with distance from the sample application zone, so as to produce a sustained capillary pull during the test; the overall hydraulic resistance to flow also increases as the sample migrates up the strip. For low volume LFiAs evaporative loss of liquid can stall flow, but this can be reduced by covering some of the components with a clear adhesive film. The plastic casework has other functions apart from that mentioned above, it must direct the sample to the first capillary element (unless that is a protruding wick), usually via a sample well, and prevent the sample escaping to wet the interior of the housing. It can also act as a handle, and a means of carrying visual information for the user. In some devices the casework also holds desiccant. This maintains the sugar matrix and nitrocellulose (NC) glaze (see later sections in this chapter) in a glassy state in which molecular mobility and hence chemical reactivity, have almost ceased, extending product shelf life. Such is the sensitivity of LFiAs to water that they are packed in plastic heat-sealable films having a continuous metal layer, this is a far superior water barrier than a nonmettalized film. The casework may also hold the analytical membrane so that the test line(s) are precisely positioned, enabling a reader to make measurements of line intensity. Often with optically read strips, the casework will also contain a high level of filler, usually titania, to block light. Finally, the casework has to protect the test strip from mechanical damage. There are two main LFiA formats; the sandwich assay used for the measurement of molecules large enough for two antibodies to bind simultaneously, and the competitive assay for small (hapten) molecules, which can only bind to one antibody at any particular time.
2.1
Sandwich Assays
Typical architecture is depicted in Figure 1. With Clearblue the user urinates onto the wick, which will transport the urine by capillary forces to the conjugate pad. The wick contains solutes to condition the urine. The conjugate pad contains the signal generating system, in this case 400nm diameter spheres of a blue-dyed polystyrene latex. Adsorbed on the latex surface is a monoclonal antibody (mAb), which binds to the αsubunit of the human chorionic gonadotrophin (hCG) molecule.15 The latex is embedded in an amorphous sugar/protein matrix designed to prevent it adhering to the high surface area conjugate pad. This prevents latex aggregation upon drying and stabilizes the antibody over the ca. three year life of the product. Also, it facilitates rapid dispersion of the latex when wetted by urine. After liberation from the matrix, latex will bind a proportion of the hCG and the mixture (latex, sugar, free hCG, etc.) moves onto the analytical membrane. In Clearblue this is a custom manufactured, white porous NC membrane bonded to a clear Mylar backing during manufacture. This membrane allows passage of up to 700-nm diameter protein-coated latex. A second mAb, which binds specifically to the β-subunit of hCG, is adsorbed as a test line across the width of the membrane and a third is plotted downstream of the second to capture latex that has flowed through the test line. The NC is blocked with a proprietary treatment to prevent the nonspecific capture of the protein-coated latex. The mixture of latex with bound and free hCG travels through the test line whereupon the latex is bound, creating a blue line against a white background. The strength of the line color depends upon the number of latex particles captured and, to a lesser extent on the specific area of NC on which it is captured. The fraction of captured latex will, up to a point, increase with the number of hCG molecules on the latex. The assay is set up so that a visible test line develops above 25 mIU ml−1 hCG (∼100 pg ml−1 based on 70 µg = 650 IU).16 The control line develops regardless of hCG level, indicating that the test has run properly. As the hCG level increases a smaller fraction of latex passes onto the control line, and this would be increasingly feint unless corrected. To maintain a consistently strong control line the conjugate pad contains two lattices, one of which
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
3
Schwanger Nicht schwanger
Cap
W
CP
L
NC
Schwanger Nicht schwanger
TW
CW
Handle
(a)
Nitrocellulose
Label
Pressure bars
Desiccant Antibodies
Casing
Mylar backing
Wick Adhesive tape
Conjugate pad
Test and control windows
Locating peg
(b) Figure 1. Photograph of the Clearblue pregnancy test. The center image shows the functional components, namely, W = wick, CP = conjugate pad, L = latex, NC = nitrocellulose. The two lines on the NC indicate the position of the test and control antibody lines plotted on the NC, these lie in the center of the test (TW) and control (CW) windows respectively. The lower image shows a developed test after running 100 mIU ml−1 hCG in urine. The positive symbol indicates pregnancy and is made up of a latex line (vertical) and an ink line printed on the NC surface which only becomes visible when the NC becomes more transparent upon wetting by urine. (b) Schematic shows the main components of a Clearblue test strip.
does not have the anti-hCG antibody adsorbed and only captured by the control line. By careful design and choice of materials the test delivers a result in one minute and is over 99% accurate when used from the day menses are due. Clearblue was originally designed as a visual read product, but it is possible to optically measure the signal and produce a semi-quantitative assay.
Figure 2 shows results from an hCG sandwich assay using the same monoclonal pairs used in Clearblue measured using a Persona optical reader. This reader measures the amount of light from a red light emitting diode (LED) (633 nm) transmitted through the wet NC, both at the test line and at regions either side of the line, which are used to set the baseline value. The
4
BIOSENSOR APPLICATIONS
Average signal +/− SD (n = 5)
50 40 30 20 10 0
0
1
10
100
1000 10 000 100 000
[hCG] mIU ml−1
Figure 2. The form of the optical signal in a hCG test strip measured with a Persona optical reading system.
optical geometry is arranged so that when the latex at the test line blocks all light transmission the reading is 50%. In addition to showing the typical sigmoidal response of these assays to increasing analyte concentration, the curve also shows a high dose hook. This is because the concentration of hCG is so great that the latex immobilized mAb fails to bind enough of the free analyte to prevent substantial occupancies of the binding sites on the NC located mAbs. With such occupancy of binding sites on the latex and test line the probability of forming the immunological sandwich is reduced, at 100% occupancy of test line and latex no binding will occur. Some theoretical aspects of sandwich17 and competitive18 LFiAs have appeared recently, these begin to give a mathematical understanding to the importance of the various factors that can influence signal development at the test line.
2.2
Competitive LFiAs
These are used for the detection and semiquantification of small molecules, typically drugs of abuse and their catabolites19 or natural metabolites, such as estrone-3-glucuronide (E3G), an estorogen metabolite and one of the species measured in the LFiA contraceptive device, Persona . In Persona , E3G is conjugated to a carrier protein and plotted at the test line. Urine is sampled from a flowing stream by a wick, which transfers it to a conjugate pad containing two blue-dyed lattices. The first has adsorbed anti-leutenizing hormone for a sandwich leutenizing hormone (LH) assay conducted on the same strip, the second has an
anti–E3G monoclonal with a very high affinity for E3G (KD ≤ 0.1 nM), which is understandable given the deep binding cleft in this antibody.20 Figure 3 shows a schematic for this assay, of similar format to many other competitive assays, and data showing how the curve can be adjusted. The assay curve can be controlled by the amount of E3G linked to the carrier, by altering the amount of conjugate plotted at the test line, or as shown above by altering the concentration of label in the urine sample. A standard assay is similar to that of the curve with a relative concentration of 7.5. However, the assay sensitivity can be improved so that it responds to about 2 ng ml−1 (∼5 nm) E3G. If we consider the sample volume, this test detects just 125 atto moles of E3G. In the presence of E3G concentrations above 20 ng ml−1 the line coloration is very weak. With visual read competitive LFiAs the lack of signal at high hapten concentrations presents some user difficulty as the result is counterintuitive. A control line or indicator must be present to reassure the user that the test has run properly.
3 MATERIALS USED IN LFiA SYSTEMS 3.1
Labels
The label generates a signal that can be seen by eye or an electronic reader. It can be a color due to absorption/reflection of visible light, fluorescence or even magnetic field set up by an assembly of magnetic particles. Labels must stably hold upon their surface one of the antibody pairs used to ensure its capture at the line of immobilized capture species on the analytical membrane, and must be small enough to flow through the pores of the membrane. Consequently they tend to be colloidal particles and as such are susceptible to aggregation when the mechanisms promoting dispersion are overcome. Bare colloidal labels used in LFiAs have charged surfaces—due to adsorbed anions (e.g., citrate in the case of gold sol), or ionisable groups (e.g., sulphate and carboxylate based initiators used in the emulsion polymerization of lattices). This gives rise to sufficient electrostatic repulsion to prevent irreversible aggregation. Care has to be taken when coating labels with antibodies to keep the ionic
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
High [E3G] in sample
5
No E3G in sample
Test lines LH E3G
Sample +/−E3G
E3G – protein conjugate
Latex with anti-E3G antibody
Anti-E3G antibody
Average persona signal (n = 5)
80
60
15 7.5
10
40 5 3 20 1 0 0
10
20 [E3G] ng ml−1
30
40
Figure 3. Schematic of a competitive assay for E3G and data showing displacement of the assay curve with increasing amounts of label. The numbers on the curves indicate the relative concentrations of blue latex-anti-E3G label incubated with urine spiked with E3G, a 25 µL volume of urine/label mix was passed up the 6-mm wide NC strip.
strength low and control pH to ensure electrostatic stability is not impaired. Once coated the particles usually tolerate environments of higher ionic strength found in standard samples, that is, ca. 0.15 mM in saline, saliva, plasma, sera, and urine. This is due to electrostatic and steric stabilization interactions from adsorbed antibody layer. An understanding of the interplay between the typically repulsive electrostatic and attractive van der Waals forces (DLVO theory) operating in aqueous suspensions of colloidal labels suggests useful guidelines to the process of antibody coating.21 To produce a well controlled test the label should have
a low variation in size (low polydispersity), surface chemistry, and “signal content”—dye, fluor, or magnetic moment for a latex. It is also important to ensure that the label is uniformly coated with the antibody. For example, poor mixing of antibody and latex has been shown by flow cytometry to yield a mixture of particles, some fully coated with antibody and others with a sparse coverage (Inger Jonruup, personal communication). Good conjugation can be achieved with use of in in-line mixer.22 A pertinent question asked by those developing LFiAs is “what is the best label?”. A trite answer is
6
BIOSENSOR APPLICATIONS
“the one that gives the most signal”. Signal derives from a combination of the particle’s signal generating properties, antibody binding activity when immobilized upon the surface, and its tendency toward nonspecific binding (NSB). With a machine read strip the result also depends upon the components used in the reader, which is governed by permitted expenditure. Further consideration must also be given as to how easy it is to load the label with antibodies (i.e., can it be washed between each coating stage in a centrifuge without aggregating, how susceptible is it to aggregation during the coating process, and how reproducibly can the base particle be made). Consequently there is no answer to this question. LFiAs have evolved around the traditional particles (latex, gold, selenium, and carbon sols), with new labels constantly being discovered and evaluated.
3.1.1 Traditional Labels
These yield visible lines and do not require an electronic reading system, although they are also used in conjunction with a reading system for semi-quantitative measurements. Gold Sol A preferred label in many tests is gold sol. Methods for preparing near monodisperse gold sol have been known from Zsigmondy’s 1906 work onward,23 but only recently has well-controlled material become commercially available. Gold sol has the advantage of not requiring dye, its color originates a strong, broad optical absorption band not present the bulk metal. The adsorbed photons set up collective oscillation of the conduction electrons (a plasmon), which extends to the surface as a surface plasmon wave, the frequency of this resonance (surface plasmon resonance (SPR)), is diameter dependant. Sols used in LFiAs have diameters from 20 to 60 nm and absorb green light (520–540 nm) making them appear red in white light.24 Typically a 40-nm diameter sol, with a standard deviation on diameter of better than 5% is used, this produces a red test line under appropriate conditions. Another advantage of sol is that when coating with antibody or during the test, aggregation is easily observed. This is apparent when gold surface to surface separation is less
than the particle diameter, and is shown by a color change from red to blue/purple.25 Gold sol are typically 1/10th the diameter of the lattices used in LFiAs and have a high curvature, making it more likely that adsorbed antibody (of length ca 15 nm) protrudes from the surface of the sol. This increases mAb accessibility to binding analyte, particularly if it was inflexible and did not undergo structural rearrangement on the surface by the short range van der Waals dispersion forces. Measurements of the small decrease in the SPR wavelength when hCG binds to an antibody-coated 40-nm gold sol indicate that at least 25 hCG molecules bind per sol.26 Measurements in our laboratory of the uptake of hCG by an anti-αhCG coated 40 nm sol indicate ca. 100 molecules bound, with an expected 60 molecules of antibody adsorbed to the sol based on a coverage of 5 mg m−2 . This suggests that the binding activity of antibody on sol is very high. We found that about 400 hCG molecules bound to a 400-nm latex coated with the same antibody. Polystyrene Latex The quality of polystyrene and other polymer lattices has improved over the past 20 years. It is now possible to obtain from commercial sources almost monodisperse latex with controlled surface chemistries and reproducible dye or fluor levels that are surfactant free. (Surfactant free lattices are available from: Interfacial Dynamics Corp., Molecular Probes Inc., 29851 Willow Creek Rd., Eugene, OR 97402, USA. www.idclatex.com. Duke Scientific Inc, 2463 Faber Place, Palo Alto, USA. www.dukescientific.com. Polysciences Inc., 400 Valley Rd., Warrington, Pennsylvania, USA. www.polysciences.com.) The surfactant-free lattices remain stable in suspension because they have a greater surface charge density capable providing electrostatic stabilization. This simplifies protein adsorption as the protein no longer has to compete with surfactant for the surface, and the coating procedure does not require diafiltration, or the like, to gradually remove the surfactant while the protein adsorbs to maintain stability. Dyed lattices are good for visually read assays. Many dyed lattices are available with the dye permeating the bulk of the latex. The dye may be incorporated by solvent swelling of the latex in the presence of the dissolved dye, then washing with a nonsolvent to collapse the latex and remove the unincorporated dye.
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
Selenium Sol Selenium is a metal, which in colloidal form like gold sol has a visible color (orange/red). Antibodies and other proteins will adsorb to it enabling it to be used in LFiAs. The sol is not commercially available and was used in Abbott Laboratories’ Test Pak range of tests. It appears to have no advantages over gold sol. Carbon Sol Carbon sol, essentially soot from the controlled burning of oil, is typically used a filler in car tyres. It is the least expensive label and offers perfect contrast against the white NC membrane. Its major disadvantage is that it is usually quite hydrophobic and of an irregular size and shape. So while it will bind antibodies strongly, the preparation usually ends up highly aggregated even when detergents are used to disperse the starting material. It has been claimed that it is possible to select a carbon sol based upon measurement of its surface oxidation, highly oxidized sols are water dispersible and can be coated with antibody;27 one commercial LFiA uses a carbon sol label. (The Contrast II hCG urine/serum LFiA, Genzyme Corp. 500 Kendall St., Cambridge, MA 02141, USA, www.Genzyme.com.)
3.1.2 Emerging Labels
Fluorescent Latices Fluorescent lattices may improve assay sensitivity but need a light source and well defined (expensive) optical filters to discriminate the emission, which may only be 10–20 nm higher in wavelength (stokes shift), from the scattered incident light. Latices loaded with organic fluorophores have been available for many years, but have not been used in commercial LFiAs. Recently lanthanide chelates have been incorporated into lattices,28 this circumvents one complication of the well known DELFIA (dissociation-enhanced lanthanide fluoroimmunoassay) microtitre plate based assay system. In this a lanthanide ion chelated to a secondary antibody is dissociated from the protein by an acid/detergent solution, which contains chelator and antenna molecules. The liberated ions become chelated in a micelle and thereby shielded from the massive quenching effect of water, allowing
7
them to emit light. The antenna molecules absorb UV (e.g., 340 nm) and pass this energy on to the chelated lanthanide: a europium chelate emits a sharp band at 615 nm (bandwidth ca. 10 nm) with a lifetime of about 1 µs. The long lifetime and large stokes shift allow the emission to be separated from the UV induced autofluorescence of the sample and materials used in the construction of the assay. This is achieved using crude optical filters and/or time-gating of the detection signal, and provides far better discrimination against background than is possible with more conventional organic fluors. Quantum dots are monodisperse semiconductor materials, for example, CdSe, ranging in size from about 1 to 10 nm. They have very high extinction coefficients for two photon absorption, orders of magnitude higher than organic fluorophores,29 absorb light over a wide range of wavelengths below their sharp emission peaks, and have high quantum efficiencies of typically 20–50%. Emission results from electron–hole recombination within a geometric space (the quantum dot core) smaller than the natural dimension of the hole-pair (exciton). Small changes in the size and shape of the core have profound effects on the emission wavelength. Sharp photoemission bands (in the 0.4–2 µm wavelength range) increase with Qdot diameter. Excitation of many different types (emission colors) of quantum dots (Qdots) is possible with one UV light source, making multiplexed assays possible. Although, the spatial separation of test zones or patches in LFiA makes this feature redundant. One problem with Qdots is that they are hydrophobic and colloidal stability is difficult to attain. They are often coated with a thin layer of ZnSe. In the case of CdSe this greatly increases the emission intensity of the core and allows for the attachment of other layers and biological materials.30 Qdots have recently been used in bioassays31 and their potential for use in LFiAs is underway.32 Qdots can also be incorporated into latex particles (Qbeads) making them more tractable to those attempting antibody conjugation.33 Magnetic Latex Superparamagnetic particles, which only become magnetic in a magnetic field have been produced using magnetite-loaded latex (Indicia Diagnostics, 33, Avenue de la Californie, 69600, Oullins,
8
BIOSENSOR APPLICATIONS
France) and magnetite-silica aggregates coated with dextran.34 Para- and ferro-magnetic particles are not suitable as they would aggregate due to their mutual magnetic attraction. The base magnetite is too small (ca. 10–20 nm) to maintain a permanent magnetic moment, and these particles can constitute up to 80% of the weight of a latex. The characteristics of these particles are not as well controlled as emulsion polymerized latex, they are available as stable dispersions in detergents, their mean magnetic moment and its variation requires tight control if they are to be used in assays. Although the particles are colored (brown to black, depending upon the loading and composition of the oxide), they are intended to be used with a reader that measures the magnetic properties of the captured material at the test line. Magnetic reading technology has been commercialized by Quantum Design—MAR reader. (Quantum Design, 6325 Lusk Boulevard, San Diesgo, CA 92121. www.qdusa.com.) This moves the developed test strip line immediately beneath a thin sapphire window on whose distal surface is a series of flat, spiral conducting coils, and above a fixed magnet, which magnetizes the superparamangnetic latex. Movement of the magnetic latex line induces a voltage in the coils, the magnitude of which depends upon the magnetite content of the test line. This system appears to detect 30 pg ml−1 staphylococcal enterotoxin B. Phosphorescent Particles Inorganic phosphors, such as those coated on the interior of television screens are prepared by grinding a ceramic formed at high temperature. They are irregular in shape and too large (ca. 10 µm) to be of use in LFiAs. A phosphorescent particle has been claimed to be useful in NC based LFiA. The material has a particle size of between 5–200 nm, comprises a ceramic of aluminium oxide doped with europium, lanthanum, and neodymium oxides, and Sr2 C03 : the latter compound appears to store energy from the UV incident light and also determines the color of the emitted light; strontium causes emission at 540 nm and calcium at 450 nm, the peak width at half maximum intensity as ca. 60 nm. The emission persists for several hundred seconds. These particles are coated with a silane coupling reagent, 3-aminopropyl-trimethoxysilane, and linked to
antibody using carbodiimide. In LFiA format they are visible in subdued lighting and are claimed to be far more sensitive then gold sol.35 Up-converting phosphors are crystals of lanthanide elements, which absorb low energy infrared and emit at higher energy (higher frequency) visible wavelengths.36 This is achieved by a multiphoton adsorption process and different colors are available, depending upon the lanthanide dopants. For example, ytterbium ions will adsorb two 980 nm photons and excite erbium ions to emit at 550 nm (green) close to the wavelength of highest visual acuity. Red and blue phosphors are also available. However, despite emitting visible radiation the intensity is too low to be detectable by eye, and an optoelectronic reader has to be employed. One benefit of these materials is that IR causes negligible fluorescence in biological samples and so the background signal is low. Wavelength-gated and time-gated detection and even phase-sensitive detection can be used to eliminate background, enabling extremely sensitive signal detection. These labels are eminently suited to highly colored and fluorescent samples. One technical issue is that the light output of the particle is exceptionally dependent on particle size; halving the particle diameter gives approximately a sixfold reduction in signal. It was not until the manufacture of spherical, low polydispersity particles37 that they could be commercially exploited. To stabilize the crystals and make them water dispersible they are coated with a thin layer of silica. This can be chemically modified to permit covalent coupling of protein.38 One company pioneering the use of these labels is OraSure Technologies, Inc, their products include saliva based drug tests and utilize a reader containing an LED and photodiode detector. Liposomes The aqueous lumen of bilayer lipid vesicles can be loaded with a variety of dyes/fluors and by means of the appropriate lipid and coupling chemistry it is possible to create a antibody-coated label. One problem is that large osmotic forces arising when the liposome is dried in the conjugate pad transiently break open the vesicle to release some of the entrapped signal molecules. However, by appropriate choice of the drying sugar most (>70%) of the liposomes and their contents can be recovered and mobilized up the NC upon rehydration.39
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
3.2
Analytic Membranes
NC is the most widely used polymer membrane for LFiAs. Initially the membrane was adhered to a carrier plastic using pressure sensitive adhesives. However, ingress of adhesive into the pores of the membrane gave rise to poor consistency and now leading manufacturers (Schleicher & Schuell, Millipore, Whatman, Sartorius, and MDI of India) cast the polymer directly onto a Mylar film to provide handling strength. Unbacked membranes find applications in flow-through immunoassays. As NC is a hydrophobic polymer manufacturers incorporate surfactants to enable wetting of the dry membrane. Properties such as the pore size and membrane thickness are carefully controlled during manufacture by manipulation of the evaporation rate and the film thickness of the polymer slurry on the Mylar. Figure 4 is an electron micrograph of the interior of a good NC membrane. Substitute membranes for NC have been developed based on nylon (Cuno Corporation’s Novylon ), and poly ethersulphone (Pall Corporation’s Predator ), but these do not have all the attributes of a good NC membrane. 3.2.1 Characterization of NC
Manufacturers continually adjust their processes to maintain and improve consistency within and
9
between batches, and have devised standard tests to qualify their membranes. Membrane Flow Rate This common test is the time taken for water to wick 40 mm vertically up the membrane under defined conditions (RH, temp, etc.). It provides a measure of the pore size and aqueous wettability of the NC, which will depend on the type and amount of surfactant incorporated. Note that as the pore size decreases, the lateral wicking rate of the membrane also decreases, but the protein binding capacity of the membrane increases in line with its surface area. A slower wicking rate increases the effective sensitivity as it permits reagents to spend a longer time in the capture zone, allowing the label to make more collisions with the antibody on the test line. Membrane thickness This parameter is easy to measure and variations in membrane thickness will have a direct influence on flow rate and protein binding capacity, affecting signal. Membrane thickness is typically 50–200 µm. Absorption Time and Capacity for Liquids This test evaluates the time required for a membrane to take up a certain volume of test liquid under defined conditions, and the area of the resulting wet spot, which depends indirectly on void volume and thickness. These parameters are usually called absorption time and absorption capacity, and are respectively reported in seconds per µl and cm2 µl−1 . 3.2.2 Deposition of Proteins onto NC
10 µm
Figure 4. A scanning electron micrograph showing a cross-section through a NC membrane in the region of the anti-hCG test line. This test line was developed with 500-nm diameter polystyrene lattices in the absence of hCG and so has a sparse coverage of particles (some indicated by arrows). Note the typical nodular structure of the NC fiber and the variable “pore” dimension. A typical NC membrane is ∼100 µm thick and about 80% air by volume.
There are many systems with excellent volumetric precision available for dispensing reagents onto membranes. Generally they are of two types: contact and non-contact dispensers. Although contact dispensers are the most widely used, these can compress and damage the soft NC membrane leaving an indent at the application zone if they are not well set up. Non-contact dispensers, typically inkjet systems, are less likely to suffer from this problem and offer the added advantage of printing more complex patterns designed to give the user information on test performance (e.g., the tick mark that acts as a positive control in IMI’s Test
10
BIOSENSOR APPLICATIONS
Pak pregnancy test). Once proteins are deposited on the membrane they are often fixed by drying and then blocked using manufacturer’s favored reagents.
3.3
Ancillary Membranes
At each end of the NC, either nearest the sample (proximal), or furthest from its point of application (distal), membranes of different functional requirement may be attached.
3.3.1 Conjugate Pad (Proximal End of NC)
This material is used to hold the dried label, typically ∼109 particles, in an amorphous/crystalline sugar phase, containing other additives such as detergents and protein to reduce NSB, as well as buffer salts to control pH and other excipients. Ideally the label is uniformly held about the fibers of the pad so that dispersion is uniform and gradual into the flowing sample. Too slow release of label from the pad results in a high background of label on the NC. Very sharp release results in label only interrogating analyte from a very small fraction of the sample. Release characteristics are determined by the physical properties of the pad, formulation of the dried matrix holding the label, and sample viscosity.
amongst others. One of the most effective, in terms of plasma yield and rate of plasma delivery, is a mixed glass fiber matrix; it is also off patent and freely available for use. Red cell movement through this matrix is retarded leading to the development of a plasma front, which can be sucked up by the NC. This material may be used in a lateral or vertical flow mode if the material is thick and placed on top of the conjugate pad or analytic membrane. The label may be loaded into the blood separator in ways similar to those used to load the conjugate pad.
3.3.3 Sinks (Distal End of NC)
A sink is a piece of absorbent material placed in hydraulic contact with the membrane on the distal end of the device. Its main function is to ensure residual label is drawn away from the test and control lines, enabling a good contrast between these and the regions of the analytical membrane either side of them. In cases where a large volume of sample must pass through the conjugate pad and NC the sink must have enough capacity to imbibe this volume while maintaining a reasonable flow. As NC only has a small capacity for fluid this is used to increase the volume of sample interrogated to reduce the lower limit of detection of the test. 4 ATTACHMENT OF ANTIBODIES TO LABELS AND NC
3.3.2 Blood Separator (Proximal End of NC)
4.1
Red cells, flexible, biconcave discs of ca. 8 × 2 µm, are typically larger than the “pores” of an analytic membrane. This would greatly reduce fluid flow, and may even cause haemolysis if they get into the membrane. With some labels, particularly gold and selenium sols, their contrast against the membrane would be reduced in the presence of released haemoglobin. Use of a cell separating membrane overcomes these issues and also provides a more accurate measurement of the analyte concentration in blood plasma, overcoming the need for haematocrit correction. Patents have been issued on several materials suitable for use as a plasma generator in a LFiAs, viz: glass fibers,40 polymer fibers,41 and asymmetric pore polymers42
Proteins irreversibly adsorb to nearly all surfaces by virtue of the many interactions shown in Figure 5.43 Once the summed interactions exceed ∼10 kT the protein is essentially irreversibly adsorbed. Strong adsorption is expected via hydrophobic interactions with latex and carbon sol due to strong van der Waals interactions, and for gold sol owing to its high Hamaker constant.44 When coating a label by absorption the label must remain colloidally stable (dispersed as singletons), to achieve this it is important to keep the electrolytes concentration to a minimum while maintaining a pH at which the electrostatic charge on the label is sufficient to maintain stability. Fortunately antibody/protein adsorption is so
Adsorption
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
11
H2O exclusion
Protein
+
COO− Ca COO−
Adsorption mechanism
General rules
+
NH3
2+
Na
+
Io
Sa
n
lt b
rid
ge
NH3
NH2
COO−
OH OH
Va
n
ex
ch
an
Electrostatic
de
ge
rW
Hy
aa
ls
H
dr
op
ho
bic
bo
nd
ing
• Larger the protein the stronger the adsorption (generally) • Adsorption maximum is near the pI of protein • Denatured protein adsorbs stronger than native
Figure 5. Protein adsorption mechanisms. Attractive interactions causing protein to adsorb to a surface will depend upon the properties of the surface (hydrophobicity, ionic nature, availability of H-bonding sites, roughness on a nanometer to sub-nanometer scale and the protein). Although the strength of the individual interactions may be less than kT, when added they can be sufficient to hold a protein at a surface irreversibly. The literature on protein adsorption is extensive, but three general rules appear to apply.
strong to most labels that only a low concentration of antibody is needed, typically 10–100 µg ml−1 ,6 this reduces the effect of the antibody’s counterions on the bulk ionic strength. Gaps between the antibody adsorbed on the label are partially filled in a process called blocking with another smaller protein, such as bovine serum albumen to reduce the NSB of the particle to the test line. This is particularly important in sample matrices containing low levels of protein, such as urine. Complete blocking (i.e., preventing access to the latex surface by protein on the test line), is probably not achievable with one protein, but for most instances this suffices. As the adsorbed antibody is not orientated on the particle with its binding sites (paratopes) directed away from the surface, the analyte binding capacity of the label is reduced. While it is possible to measure the binding capacity of a label for analyte, what is really important is the fraction of these that project from the surface enabling sandwich binding to occur at the test line. This has not been measured, but if it could be it might offer a means
of evaluating different methods of attaching antibodies to labels. Immuno-reactivity changes with the combination of surface, protein characteristics, and adsorption conditions. With NC there is an increase in label binding capacity with antibody coverage (mg m−2 ), but this tails off as the surface becomes crowded with antibody (authors unpublished observations), the same occurs for the binding of hCG to antibody adsorbed on planar surfaces.45 The explanation is that adsorption of one antibody may obscure the paratope of another that has adsorbed earlier, and that this later adsorbing antibody does not provide a functional binding site. Simplicity and wide applicability makes adsorption the most common route of attachment of antibodies to labels. It is also used to anchor antibodies to the NC membrane, where similar interactions to those depicted in Figure 5 occur. One specific interaction believed to predominate in the adsorption of protein to NC is the dipole–dipole interaction between the nitro group and the carbonyl of the peptide bond.46 While it is clearly
12
BIOSENSOR APPLICATIONS
easier to apply protein to NC compared with colloids, as there are no concerns over stability, there are other factors to consider. The antibody needs to have a uniform binding activity throughout the volume of the test line, and the test line should be well defined spatially, particularly for an instrument read strip. Small levels (<10% v/v) of low alcohols (methanol, ethanol or propanol), may be added to facilitate wetting of the NC and to reduce the solubility of antibody so that it is strongly adsorbed. High levels of electrolyte may block pores in the dried strip and interfere with sample/label flow through the membrane; it may also reduce adsorption of the protein.
4.2
Covalent Immobilization
Covalent coupling of antibodies can be applied to analytical membranes, but is more commonly used with labels. While it is easy to give reasons for employing this more complex immobilization strategy, many of these are unreasonable given the paucity of publications that give experimental support to them, viz: to increase the loading of antibody to the surface; to prevent desorption of antibody by other materials (proteins) in the sample; to orientate the antibody and thereby increase the binding capacity of the surface. There are many publications where authors have gone through some chemical ritual designed to couple protein to latex, but they rarely demonstrate what fraction of the antibody has been covalently linked and the benefit over the control (adsorbed) system. Some authors appear to believe that an antibody having a reactive group at one end impacts upon the substrate to which it is to be coupled in such a way that a covalent bond is formed and the antibody has simply lost the ability to adsorb! Chemical coupling may appear useful, but its implementation in a manufacturing environment, which must produce a high yield of devices that function to certain analytical tolerances present added difficulties. Any coupling chemistries must be proven to have benefit and the reagents need a relevant, device independent quality control process. Covalent coupling may, however, be of benefit in coupling antibody fragments and antibodies to protein adhesive surfaces and to systems exposed
to harsh environments, for example, samples containing nondenaturing surfactants. To construct such a surface the label is first coated with a layer, a hydrogel, typically of a hydrophilic polymer such as dextran, polyethylene glycol, or ethoxylated celluloses either by adsorption or via chemical linkers, for example, thiols and silanes, which will bond to gold and silica based surfaces respectively. The bio-resistive polymer hides the label surface, and if suitably derivatized will couple protein without it encountering the denaturing effect of the underlying (hidden) surface. It also prevents nonspecific binding because it consists of a flexible, water soluble polymer holding a high level of water at the surface.47 Binding of a protein to the coating, or binding of the coated latex to a surface, would require the entropically unfavourable restriction of mobility of the polymer.48 When constructing a bio-resistive surface it is important not to make the hydrogel so thick that it contains antibodies within its thickness as these will simply deplete the sample of analyte and reduce the sensitivity of the assay. Covalent immobilization of antibody to the analytical membrane does not appear to be of benefit judging by the absence of commercial tests using membranes that are available for such coupling, for example, Pall Corporation’s Immunodyne ABC membrane.
5 SAMPLE MATRIX AND ISSUES
For a LFiA to meet its analytical performance interfering materials in the sample may have to be ameliorated to a tolerable level. The FDA has recommended that assay kits employing mouse mAbs include a warning that samples from donors who had received diagnostic or therapeutic antibodies may show a falsely elevated or depressed value when tested.49 It is not possible to give a useful figure for the proportion of samples within a population that would give rise to false results, as this depends upon the materials used in the test. Recognizing the above caveat one can expect from 2–40% of samples to cause problems.50 A powerful example of an interference problem is that of the blood hCG test, which indicated pregnancy in women who were not pregnant. As hCG
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
13
Latex bead
HABSA
BSA
R.F
HAMA
Mouse monoclonal antibody NSB
Nitrocellulose C1 “Sticky factors” (fibrinogen, fibronectin) Figure 6. Illustration of the types of protein—protein interactions that can cause problems in particle based LFiAs—note not all the possible interactions are shown. Particles may be aggregated by human anti-BSA (HABSA), human anti-mouse antibody (HAMA), Rheumatoid factor (RF) or the complement protein C1q. Small aggregates of particles may be linked to antibodies on the NC by similar interactions. Large proteins like fibrinogen and fibronectin may also link protein free surfaces together owing to their large size and tendency toward adsorption.53 [Reprinted with permission Prime and Whitesides53 copyright 1993, American Chemical Society.]
is also a marker for choriocarcinoma these unfortunate women were subjected to unnecessary surgery because of the clinicians belief in the infallibility of the test.51 The erroneous measurements (“false positives”) were due to heterophile antibodies, a cause of concern in all blood assays. This type of interference can also cause “false negatives”, if for example, the interfering protein binds and masks paratopes in a sandwich assay. Heterophilic antibodies are human antibodies, which can be of several classes (IgG, IgM, IgA), which will bind to the antibodies used in the LFiA.50 Heterophiles usually arise as a normal immune response to the passage of dietary antigens through a compromised gut wall, as in celiac disease. Also through blood transfusions, vaccinations, antibody based drug targeting, and radio-imaging techniques.49,52 Figure 6 shows most of the types of interference possible in blood and how they can act in an LFiA. Other samples have their own problems, for example, mucus in sputum can aggregate latex. In some bacterial tests the antigen (e.g., Streptococcal protein A) has to be extracted from the cell wall, a procedure involving chemical extraction and its neutralization prior to applying to the test device as in the Clearview Strep A
test. (ClearviewTM StrepA details may be viewed at www.clearview.com/strepa.cfm.) In some urine based drug tests the sample can be easily adulterated in the privacy of the collection booth by the donor. Manufacturers strive to overcome these problems in order to meet the demands of the regulatory authorities, to better meet consumer needs and, of course, to secure the commercial advantage of a superior test.
6 CONCLUSION
LFiA offer an assay platform that can be as simple as unwrap, wet and measure, with a quick time to a visual result. With a reading system this can offer semi-quantitative measurements of large and small analytes in a variety of samples. New materials, reading systems and a better understanding of how to normalize samples will lead to quantitative assays and an even wider range of applicability than they currently enjoy. It is often overlooked that LFiAs are a massively parallel microfluidic assay platform, which has yet to be superseded as a mass market product, by the single, or multichannel, microfluidic systems that
14
BIOSENSOR APPLICATIONS
have been extensively researched over at least the past decade.
REFERENCES 1. T. A. Gossel and M. P. Mahalik, Ovulation and pregnancy testing products. US Pharmacis, 1993, 18(7), 36–45. 2. http://history.nih.gov/exhibits/thinblueline, 2003. 3. P. Ghalioungui, Magic and Medical Science in Ancient Egypt, Hodder and Stoughton, London, 1963. 4. S. Jehanli, L. Brannan, L. Moore, and V. R. Spiehler. Blind trials of an onsite saliva drug test for marijuana and opiates. Journal of Forensic Sciences, 2001, 46, 1214–1220. 5. Double CheckGold HIV 1&2. Orgenics, Yavne 70650, Israel. www.organic.com. 6. A. S. Valari, R. K. Hickman, J. R. Hackett, C. A. Brennan, V. A. Varitek, and S. G. Devare, Rapid assay for simultaneous detection and differentiation of immunoglobulin G antibodies to human immunodeficiency virys type 1 (HIV-1) group M, HIV-1 group O, and HIV-2. Journal of Clinical Microbiology, 1998, 36(12), 3657–3661. 7. Y. Al-Yousif, J. Anderson, C. Chard-Bergstrom, and S. Kapil, Development, evaluation and application of lateral flow immunoassay(immunochromatography) for the detection of rotavirus in bovine fecal samples. Clinical and Diagnostic Laboratory Immunology, 2002, 9, 925–926. 8. S. K. Sharma, B. S. Eblen, R. L. Bull, D. H. Burr, and R. C. Whiting, Evaluation of lateral—flow clostridium botulinum neurotoxin detection kits for food analysis. Applied and Environmental Microbiology, 2005, 71(7), 3935–3941. 9. C. Quach, D. Newby, G. Daoust, E. Rubin, and J. McDonald, QuickVue influenza test for rapid detection of influenza A and B viruses in a pediatric population. Clinical and Diagnostic Laboratory Immunology, 2002, 9, 723–724. 10. Med Plus Drug Screen Test, Applied Biotech, Incorporated, San Diego. 11. H. L. Smits, C. K. Eapen, S. Sugathan, M. Kuriakose, M. H. Gasem, C. Yersin, D. Sasaki, B. Pujianto, M. Vestering, T. H. Abdoel, and G. C. Gussenhoven, Lateral flow assay for rapid sero-diagnosis of human leptospirosis. Clinical and Diagnostic Laboratory Immunology, 2001, 8, 166–169. 12. D. King, V. Luna, A. Cannons, J. Cattani, and P. Amuso, Performance assessment of three commercial assays for direct detection of bacillus anthracis spores. Journal of Clinical Microbiology, 2003, 41, 3454–3455. 13. Y. Oku, K. Kamiya, H. Kamiya, Y. Shibahara, T. Li, and Y. Uesaka, Development of oligonucleotide lateralflow immunoassay for multi-parameter detection. Journal of Immunological Methods, 2001, 258, 73–84. 14. E. Lee-Lewandrowski and K. Lewandrowski, Regulatory compliance for point-of-care testing. A perspective from the United States (circa 2000). Clinics in Laboratory Medicine, 2001, 21(2), 241–253.
15. M. Tegoni, S. Spinelli, M. Verhoeyen, P. Davis, and C. Cambillau, Crystal structure of a ternary complex between human chorionic gonadotrophin (hCG) and two Fv fragments specific for the a and b subunits. Journal of Molecular Biology, 1999, 289(5), 1375–1385. 16. C. M. Sturgeon and E. J. McAllister, Analysis of hCG: clinical applications and assay requirements. Annals of Clinical Biochemistry, 1998, 35(4), 460–491. 17. S. Qian and H. H. Bau, A mathematical model of lateral flow bioreactors applied to sandwich assays. Analytical Biochemistry, 2003, 322, 89–98. 18. S. Qian and H. H. Bau, Analysis of lateral flow biodetectors: competitive format. Analytical Biochemistry, 2004, 326, 211–224. 19. C. Barrett, C. Good, and C. Moore, Comparison of point of collection screening of drugs of abuse in oral fluid with a laboratory-based urine screen. Forensic Science International, 2001, 122, 163–166. 20. C. H. Trinh, S. D. Hemmington, M. E. Verhoeyen, and S. E. Phillips, Antibody fragment Fv4155 bound to two closely related steroid hormones: the structural basis of fine specificity. Structure, 1997, 5(7), 937–948. 21. J. Israelachvili. Intermolecular and Surface Forces, 2nd Edn, Academic Press, New York, 1991, pp. 246–254. 22. D. H. Ostrow, L. M. Cohen, K. S. Eble, P. J. Maney, E. W. Steckle, B. L. Rubin, C. A. Whittman, and P. A. Johnson. Procedure for Attaching Substances to Particles, International Patent Application. WO 98/08095, 1988. 23. D. J. Shaw. Introduction to Colloid and Surface Chemistry, 4th Edn, Butterworth-Heinemann, Oxford, 2003, p. 13. 24. W. R. Glomm, Functionalised gold nanoparticles for applications in bionanotechnology. Journal of Dispersion Science and Technology, 2005, 26, 389–414. 25. R. Elghanian, J. J. Storhoff, R. C. Mucic, R. L. Letsinger, and C. A. Mirkin, Selective colorimetric detection of polynucleotides based on the distance-dependent optical properties of gold nanoparticles. Science, 1997, 277, 1078–1081. 26. P. Englebienne, Use of colloidal gold surface plasmon resonance peak shift to infer affinity constants from the interactions between protein antigens and antibodies specific for single or multiple epitopes. Analyst, 1998, 123, 1599–1603. 27. A. W. J. van Doorn, J. H. Wichers, W. Martinns, and J. van Gelden, Stable Aqueous Carbon Sol Composition for Determining Analyte, US patent 5,641,689, 1997. 28. J. R. Schaeffer, T. J. Chen, and M. A. Schen, Latex Particles Incorporating Stabilised Fluorescent Rare Earth Labels, US patent 4,784,912, 1988. 29. P. Alivisatos, The use of nanocrystals in biological detection. Nature Biotechnology, 2004, 22(1), 47–52. 30. M. Danek, K. F. Jensen, C. B. Murray, and M. G. Bawendi, Synthesis of luminescent thin-film CdSe/ZnSe quantum dot composites using CdSe quantum dots passivated with an overlayer of ZnSe. Chemistry of Materials, 1996, 8, 173–180. 31. W. C. W. Chan and S. Nie, Quantum dot bioconjugates for ultrasensitive nonisotopic detection. Science, 1998, 281, 2016–2018. 32. A. M. Fisher, S. J. Sirk, J. L. Lambert, and M. P. Bruchez. Development of a Qdot Lateral Flow Assay. A Simple
LATERAL-FLOW IMMUNOCHROMATOGRAPHIC ASSAYS
33.
34.
35.
36.
37. 38.
39.
40.
41. 42.
43.
Multiplexing Strip Test, 2003, Quantum Dot Vision, 8–9, October. Y. Li, E. C. Y. Liu, N. Pickett, P. J. Skabara, S. S. Cummins, S. Ryley, A. J. Sutherland, and P. O’Brien, Synthesis and characterisation of CdS quantum dots in polystyrene microbeads. Journal of Materials Chemistry, 2005, 15, 1238–1243. NASA Technical Reports Server, Nanomag Range of Particles from Micromod Partikeltechnologie GmbH, Document ID 20060043413, Friedrich-Barnewitz Strasse, Rostock, Germany. G. Li, H. Wu, and C. Liu, Europium Containing Fluorescent Nanoparticles and Methods of Manufacture Thereof, US patent 6,783,699. 2004. D. A. Zarling, M. J. Rossi, N. A. Peppers, J. Kane, G. W. Faris, M. J. Dyer, S. Y. Ng, and L. V. Schneider. UpConverting Reporters for Biological and Other Assays Using Laser Excitation Techniques, US patent 5,674,698 1997. J. Kane, Method for Preparing Small Particle Size Fluoride Up-Converting Phosphors, US patent 5,891,361, 1999. P. Corstjens, M. Zuiderwijk, A. Brink, S. Li, H. Feindt, R. S. Niedbala, and H. Tanke, Use of up-converting phosphor reporters in lateral—flow assays to detect specific nucleic acid sequences: a rapid, sensitive DNA test to identify human papillomavirus type 16 infection. Clinical Chemistry, 2001, 47(10), 1885–1893. D. Martorell, S. T. Siebert, and R. A. Durst, Liposome dehydration on nitrocellulose and its application in a biotin assay. Analytical Biochemistry, 1999, 271(2), 177–185. P. Vogel, H.-P. Braun, D. Berger, and W. Werner. Process and Composition for Separating Plasma or Serum from Whole Blood, US patent 5,055,195, 1984. D. B. Pall and R. L. Manteuffel, Fibrous Web for Processing a Fluid, US patent 5,846,438, 1998. D. M. Koenhen and J. J. Scharstuhl, Process and Device for the Separation of a Body Fluid from Particulate Materials, US patent 5,240,862, 1993. W. Norde, Driving Forces for Protein Adsorption at Solid Surfaces, in Biopolymers at Interfaces, Surfactant Science
44.
45.
46.
47.
48.
49.
50. 51.
52.
53.
15
Series, M. Malmsten, (ed), Marcel Dekker, New York, 1998, 75: pp. 27–54. J. Visser, On Hamaker constants: a comparison between Hammaker constants and Lifshitz-van der Waals constants. Advances in Colloid and Interface Science, 1972, 3, 331–363. H. Xu, J. R. Lu, and D. E. Williams, Effect of surface packing density of interfacially adsorbed monoclonal antibody on the binding of hormonal hCG. Journal of Physical Chemistry B, 2006, 110, 1907–1914. Rapid Lateral Flow Test Strips. Considerations for Product Development. Millipore Corp. Lit. No. TB500EN00, Revn. 06/02, 2002, 5. R. G. Chapman, E. Ostuni, S. Takayama, R. E. Holmlin, L. Yang, and G. M. Whitesides. Surveying for surfaces that resist the adsorption of proteins. Journal of the American Chemical Society, 2000, 122, 8303–8304. E. P. K. Currie, J. Van der Gucht, O. V. Borisov, and M. A. Cohen-Stuart, Stuffed brushes: theory and experiment. Pure and Applied Chemistry. Chimie Pure Et Appliquee, 1999, 71, 1227. L. J. Kricka, Human anti-animal antibody interferences in immunological assays. Clinical Chemistry, 1999, 45, 942–956. C. Selby, Interference in immunoassay. Annals of Clinical Biochemistry, 1999, 36, 704–721. S. Rotmensch and L. A. Cole, False diagnosis and needless therapy of presumed malignant disease in women with false-positive human chorionic gonadotrophin concentrations. Lancet, 2000, 355, 712–715. T. H. Webber, K. I. Kapyaho, and P. Tanner. Endogenous interference in immunoassays in clinical chemistry. Scandinavian Journal of Clinical and Laboratory Investigation, 1990, 50(Suppl. 201), 77–82. K. L. Prime and G. M. Whitesides, Adsorption of proteins onto surfaces containing end-attached oligo (ethylene oxide): a model system using self assembled monolayers. Journal of the American Chemical Society, 1993, 115, 10714–10721.
75 Chip-Based Biosensors for Environmental Monitoring Kim R. Rogers National Research Exposure Laboratory, Environmental Protection Agency, Las Vegas, NV, USA
1 INTRODUCTION
Monitoring the environment (air, water, and soil) for contaminants is a critical component for understanding and managing risks related to human health. Given the large and increasing number of environmental analyses as well as the future potential for monitoring biomarkers of human exposure to environmental pollutants, there exists a need for rapid, portable, and cost-effective analytical methods to support these measurements. Biosensors and bioanalytical methods appear to be well suited to complement standard analytical techniques for a number of environmental monitoring applications. In this regard, several recent reviews have addressed biosensor technology from perspectives that include agricultural monitoring,1 groundwater screening,2 ocean monitoring,3 global environmental monitoring,4 and recent advances.5 The intention for this chapter is to discuss the topic of chip-based biosensors for potential environmental monitoring applications. One of the areas of technological advancement that sensor and biosensor scientists have used to their advantage is miniaturization and adaptation of biochemical assays onto small planar surfaces (i.e., microchips) to form “biochip” arrays. A wide range of chip-based biosensors or biochips has been described in the literature.
Although there does not seem to be a specific definition for a biosensor chip, the consensus opinion would suggest a biological recognition element (i.e., enzyme, antibody, receptor, or microorganism) immobilized on a planar surface (e.g., glass, plastic, gold, silicon, etc.) that together respond in a concentration-dependent manner to a chemical species. One of the earliest immunoassays that could be considered to be chip-based was the microspot immunoassay introduced by Ekins, which used plastic substrates and confocal fluorescence microscopy.6 Although the most common substrate for immobilization of biorecognition elements is a glass microscope slide, a range of other formats has been reported. Other substrates include gold coated onto quartz or glass using a chromium adhesion layer that has been used for ellipsometry,7 quartz crystal microbalance or surface plasmon resonance (SPR) techniques, carbon ink or nanoparticles adhered onto ceramic substrates that have been reported for electrochemical biosensors,8 imaging fibers that have been etched to produce microwell arrays,9 and microelectrode pipettes that have been used to electropolymerize polypyrrole microspots onto silicon chips.10 One question, however, remains open to discussion concerning chip-based biosensors for environmental monitoring—Is smaller better? The basic premise for adapting environmental biosensors into chip designs involves a range of
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. Published in 2007 by John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4. This chapter is in the public domain in the United States but is copyright John Wiley & Sons Ltd. in the rest of the world.
2
BIOSENSOR APPLICATIONS
potential technical, operational, and commercial advantages. Many of the potential advantages overlap in several of the following areas. The reduced use of construction materials (e.g., gold, platinum, etc.) can be advantageous in terms of fabrication cost and disposal of toxic materials (e.g., mercury, lead, etc.) both in fabrication and in use. The reduced volume required for each environmental sample can also be an advantage, especially for highly contaminated samples that must meet environmental disposal regulations or biomarkers in blood that must meet biohazard disposal requirements. The most compelling advantages for chip-based biosensor formats over larger biosensors, microwell plate assays, or standard test-tube methods are the potential for high sample throughput, rapid assay times, and the ability to determine multiple analytes in a single sample. Primarily because of considerations of scale, assay kinetics, and reagent delivery, the sample detection limits can also be significantly improved as compared to test-tube or, in some cases, microwell-type bioassays. Reduced instrument size and power requirement can result in mobile- and field-measurement capabilities. Manufacturing advantages for chip biosensors are numerous and include greater production throughput, lower cost per sales unit, greater versatility, and expanded application and market opportunities. Multiplexing a number of assays for different pollutants that can be detected using the same analysis platform could also provide a distinct advantage for chip-based biosensors. There are, however, some limitations with respect to potential environmental applications. Although chip biosensors are typically formatted on a small planar surface, there are differences among the biochips that should be considered in any discussion of potential environmental applications for these devices. Environmental monitoring has significantly different requirements than that for clinical, diagnostic, or food industry applications. One way to discuss environmental applications for these devices would be to consider the requirements for several possible environmental monitoring scenarios. For the purpose of comparison to a well-established immunoassay format, one potential benchmark might be the 96-well ELISA. In the first example, the proposed task requires the assay of 96 samples for a single pesticide for which well-characterized antibodies are available.
This type of assay would require the chip to have a separate microfluidics flow channel to handle each sample. For example, a biochip with 4 parallel flow channels would require 24 separate runs (a single flow channel would require 96 sequential runs) not including calibration, performance references, and duplicate analyses. If the biochip cannot be regenerated, then a separate chip would be required for each run. An ELISA for this monitoring scenario could be performed on a single plate (excluding calibration, etc.). In another scenario, consider analysis of multiple compounds (say 24) in each of the 96 samples. In this case, an array of 24 capture antibodies placed in separate locations on the chip could report 24 compounds in a single run with a single flow channel. For this format, the chip-based assay would show some advantages over a plate assay format that detects a single analyte in each well. Because the chip could be designed and fabricated to detect multiple compounds, it could also be subjected to the same sequence of assay solutions for all of the analytes of interest. Although reported biochip platforms are fairly versatile, they are still somewhat limited in their configurations, in that the chips must be specifically constructed for a particular group of compounds. By contrast to clinical applications, potential environmental application scenarios can be extremely variable ranging from analysis of hazardous waste, persistent organics, or biomarkers in matrices ranging from biological fluids to sewage sludge. For certain environmental monitoring scenarios, sample preparation, and cleanup could limit the time, cost, and simplicity advantages gained by chip-based assay formats. For example, if each experimental sample requires a complex and timeconsuming cleanup and preparation protocol, a simple and rapid assay format loses much of its advantage. Consequently, the answer to the question “is smaller better” depends to a large extent on the proposed environmental application. Unfortunately, a significant number of reports of novel chip-based biosensors for potential environmental applications have shown limited discussion concerning this topic. I am not suggesting that these reports have any less value; however, without solving these application challenges, it is unlikely that these techniques will be adopted for routine environmental monitoring.
CHIP-BASED BIOSENSORS FOR ENVIRONMENTAL MONITORING
2 BIOLOGICAL RECOGNITION ELEMENTS
The advantages and limitations for enzyme-, antibody-, receptor-, or microorganism-based chip biosensors for potential environmental applications are, to some extent, similar to those for biosensors in general. Advantages for the use of enzymes include a stable source of material primarily through biorenewable sources (e.g., bacteria, plants, or animal by-products), the ability to modify the catalytic properties or substrate specificity through genetic engineering, and the catalytic amplification of the biosensor response by modulation of the target analyte. Limitations of the enzyme biosensors with respect to environmental applications involve the relatively few environmental pollutants that interact specifically with enzymes either as substrates or inhibitors. Nevertheless, recent progress has been reported in areas such as genetic modification of enzymes to increase sensitivity, specificity, stability, and shelf life. Because assays for different enzymes used for environmental applications require different substrates, monitoring formats, and so on, it is unlikely that an array of enzymes on a single chip would be feasible. An inexpensive, disposable single-assay format that could be read with a small portable instrument, however, may be useful in a number of environmental monitoring scenarios. Although antibodies are inherently more versatile than enzymes as biological recognition elements in biosensors for environmental applications, they show several inherent limitations. These limitations include the complexity of assay formats and the number of specialized reagents (e.g., antibodies, antigens, tracers, etc.) that must be developed and characterized for each analyte. Because antibodies can be selective for the detection of specific compounds, they are amenable to incorporation into sensor chip arrays to form multianalyte detection systems. In this case, the antibodies are different at each location in the array and a single sample, or in some cases multiple samples, would be exposed to each of these “sensor” sites. Small arrays have been demonstrated for the simultaneous detection of multiple analytes. For example, the detection of six hazardous bacteria and protein toxins has been demonstrated using a planar waveguide array biosensor.11 This biosensor array was able to simultaneously measure six analytes for each run. In another microchip
3
format, the six toxins ricin, viscumin, staphylococcal enterotoxin B, tetanus toxin, diphtheria toxin, and anthrax toxin were detected at nanogram per milliliter levels on a glass chip using a fluorescence microscope equipped to measure four wavelengths with a CD camera.12 Although there are distinct advantages for chip-based biosensors that can analyze multiple analytes in single or multiple samples, this format requires each sample or small group of samples to use a separate chip. Because this process is sequential for each assay sample, such a scenario would limit many of the cost or throughput advantages that might potentially be gained over standard GC/MS or LC/MS techniques. An exception to this limitation would be in cases where a multichannel biosensor chip could be regenerated such that samples could be repeatedly analyzed using the same chip as in the case of the Automated Water Analyzer ComputerSupported System.13 This chip-based biosensor system was demonstrated to simultaneously detect several compounds in a repeatable sequence. Another possible array format might involve numerous environmental samples using the same antibody, with each sample analyzed at separate locations on the chip. Again, one of the challenges for this scenario would be the requirement for separate flow channels to each of the sensor locations. Although this biochip configuration is feasible and could be adapted to several of the previously cited systems,11–13 it has not yet been reported for the simultaneous detection of large (i.e., >100) numbers of samples. Although formatting issues for potential environmental applications continue to present challenges, advances in biosensor detection technology also continue to make chip-based biosensors an active research area and a promising solution for certain environmental applications. One area that forms the basis of advances in detection capabilities for biosensors involves the use of nanomaterials. For example, the use of metal nanoparticles in electrochemical detection has been shown to increase the surface area and enhance or modulate the conductivity properties of polymeric electrodes.14 The use of gold nanoparticles has also been shown to increase the signal resolution for SPR-based biosensors.15 This improvement could potentially allow the direct detection of small molecules—a problem that currently requires the
4
BIOSENSOR APPLICATIONS
use of more complicated assays that use indirect competitive formats. In addition to electrochemical detection improvements, advances in optical detection capabilities have also been reported using multicolor luminescent semiconductor nanocrystals (quantum dots). Because of their well defined emission spectra, these labels have been used to simultaneously quantitate the binding of four separate immunolabels in a single assay.16 A wide range of cell-based biosensors has also been reported for potential environmental applications. The cell types used in these bioanalytical assays include bacteria, yeast, algae, and tissue culture cells. The most commonly reported microorganisms are genetically modified bacteria that respond to nonspecific stressors such as DNA damage, γ -radiation, heat shock, and oxidative stress; toxic metals such as lead, mercury, nickel, and zinc; organic environmental pollutants such as chlorinated aromatics, benzene derivatives, organic peroxides, trichloroethylene, and PCBs; and compounds of biological importance such as nitrate, ammonia, and antibiotics.17 Genetically modified microbial and cell-based biosensors show several advantages and limitations with respect to environmental biosensors, in general, and, more specifically, for chip-based biosensors. Bioreporter microorganisms show the potential to be interfaced to a wide range of transducers including those that operate using optical, electrochemical, and SPR techniques. Their limitations primarily involve the maintenance of a required cellular environment (e.g., nutrients, O2 , pH, ionic strength, etc.), and the time required for a response (e.g., hours for systems that require protein expression). One of the potential advantages for this type of biological recognition element involves the wide range of promoter genes that have been linked to reporter gene systems. Unique chiplike platforms have also been reported for a number of cell-based biosensors for potential environmental applications. For example, a bioreporter strain of Escherichia coli that produces green fluorescent protein (GFP) in response to arsinite and antimonite was used to demonstrate a micofluidics platform.18 Comparison of this system to a standard fluorescence cuvette platform showed that mixing and analysis using this centrifugal microflow system decreased the assay time and increased the assay reproducibility. Another
unique assay platform that has been demonstrated for an E. coli strain that is responsive to Hg (II), involved immobilization of individual bacteria into microwells on the face of an imaging fiber.9 Recent advances in bacterial luminescence assays also include an automated and continuous toxicity monitoring system using a genetically engineered freshwater bacterium that is sensitive to heavy metals as well as a number of toxic organic compounds.19 For this system, cell cultures were lyophilized in a series of 384-well plates, which were automatically reconstituted with wastewater, and the bacterial response was recorded allowing the determination of toxicity spikes in the sample stream. This type of system could potentially be adapted to a microchip system by immobilizing the microorganisms onto a planar array and sequentially directing water stream samples to microflow cavities above each microcell. The potential benefit of adapting these types of systems to chipbased assays would be the development of less expensive fluidics transfer systems. Another potential advantage for the incorporation of bioreporter microorganisms into biochips would be to form multiorganism–multianalyte arrays. Bioreporter microorganisms that each respond to a different environmental pollutant and use the same biochemical reporter (e.g., luminescence, production of GFP, etc.) could be brought together in a single biochip array. In addition to reporting a range of compounds in a single assay, matrix interferences and cross-reactivity issues could be normalized through the integrated response of multiple organisms to the same environmental sample.
3 IMMOBILIZATION
A critical aspect of biosensor chip development involves immobilization of the biological recognition element onto the chip surface. These structures must be physically rugged as well as resistant to a range of chemical and thermal environments. Spatial resolution and sensor indexing are also important features in sensor design. Biological materials are typically imaged, micropipetted, or self-assembled onto meticulously cleaned planar surfaces. These materials can be chemically tethered or incorporated into solgel, hydrogel,12 or polymer matrices.20
CHIP-BASED BIOSENSORS FOR ENVIRONMENTAL MONITORING
Another approach for spatial positioning of immunochemicals involves the use of an electrical field that attracts biotin-labeled capture antibodies to specific streptavidin-coated microelectrodes.21 This electronic addressing technique was applied to the detection of fluorescently labeled staphylococcal enterotoxin B using a microelectrode array.21 Each labeled toxin was concentrated from a mixture onto its specific antibody-coated electrode. In addition to the spatial positioning afforded by this technique, the time required for the antibody–antigen binding was shortened because of the imposed potential at the electrode surface. Another approach to the spatial positioning of antibodies onto a sensor array involves the use of complementary oligonucleotides or peptide nucleic acids (PNAs) as a tether to attach analyte derivatives or capture antibodies.22 There are two advantages to this immobilization scheme. First, specific sequences of DNA can direct immunochemicals to specific locations with attached complementary oligonucleotide sequences. Next, after the assay is complete, chemical disruption can be used to strip away the immunochemical, and another oligonucleotide-labeled conjugate can be bound to a specific location on the sensor surface. Antibodies and enzymes can be covalently or noncovalently bound to chemically modified planar surfaces using a wide range of chemistries that have been well characterized over several decades. Although immobilization of enzymes typically reduces their initial activity, it also stabilizes their function over extended periods. Antibodies can also be immobilized with most of their binding function intact. Although most microorganismbased biosensors use microscale reaction chambers or flow cells, these bioreporters have also been tethered to planar surfaces using chemical linkers such as cysteine-terminated synthetic oligonucleotides.23
4 SIGNAL TRANSDUCERS AND COMMERCIAL PERSPECTIVES
The detection of biorecognition responses for chipbased biosensors is primarily based on optical, plasmon resonance, or electrochemical transducers. There are several inherent advantages and limitations for each technique. One advantage for
5
optical transducers is that an entire array can be read using absorbance, fluorescence, or luminescence with a range of well-developed and relatively inexpensive optical imaging instruments. In addition, signal-processing software is widely available for a range of applications. Although multi-laser examination of individual locations in the array can reduce background signal noise and increase assay sensitivity, it also adds a degree of complexity and expense. SPR has been well described as a detection strategy in a chip-based format. This technique is quite versatile in that it does not require the use of a probe to detect surface binding; however, small, environmentally important compounds typically require the use of indirect competition assays rather than measurement of direct surface binding. In addition, the chips mounted in flow cells are typically limited to sequentially reading one analyte at a time. When discussing potential chip-based biosensors, there are a number of issues that should be addressed in the larger context of related bioanalytical assays. It is likely that biochips with the greatest potential for future development will become central components in commercial bioanalysis systems. Consequently, it is important to mention other bioanalytical systems and the general basis for their operation. Some of these systems include the following: The Luminex system is based on internally color-coded microspheres with surface linking chemistry to accommodate antibodies, receptors, or oligonucleotides. Beads containing from 1 of 100 specific dye sets can be differentiated using a flow-cytometry system. Binding of the surface label is indicative of analyte binding and can also be determined using a second, shorter-wavelength dye and a dual laser detector.24 The use of this system has also been described for multiplexed sandwich immunoassays for an array of cytokines.25 The SearchLight system uses multiplexed sandwich ELISAs with up to 16 different capture antibodies prespotted onto 96-well plates or 4 capture antibodies spotted onto 384-well plates. Assays are run using standard ELISA methods with a secondary antibody tag of peroxidase activating a chemiluminescent substrate that is detected using a cooled CCD instrument. The SearchLight system has been recently compared to the Luminex and the FAST Quant for the detection of cytokines.26
6
BIOSENSOR APPLICATIONS
The authors describe the advantages and limitations for each system. The Meso Scale Diagnostics microplate system integrates microelectrodes into the bottom of each well of a 96-microwell plate. Various assays can be configured using electrogenerated chemiluminescent labels.27 These labels, consisting primarily of Ru(bpy)3 2+ analogs, luminesce only when they are in close proximity to the electrode surface so that bound and unbound tags can be differentiated without a plate washing step. The Multi-Spot plates use a patterned micoarray within each of the wells.28 Electrochemical transduction can be performed on a chip using electrodes that are patterned to form a disposable sensor or grouped together and incorporated into a microwell array similar to an ELISA microwell plate. An advantage of this type of system is that each of the electrodes in the array can be used for a separate assay and even subjected to different electrochemical conditions. One disadvantage of this configuration is that the microwell electrode plate limits many of the advantages of biochips (e.g., the assay becomes like an ELISA with electrochemical detection).29
5 SUMMARY
With the exception of the electrochemically based blood glucose monitor, few stand-alone biosensors have become commercially viable. Nevertheless, a wide range of biosensor concepts and technologies form the basis of or provide key components in clinical, diagnostic, and research instrumentation. In addition, with respect to environmental monitoring applications, several biosensor-based systems are becoming more widely used for a limited number of pollutant-screening applications. Advances in microfabrication, biomolecule immobilization, and detection techniques have led to the conception and realization of chip-based biosensors. As a consequence of these advances, a wide range of chip-based biosensors, primarily using antibodies and some bacterial cells, has been reported. In addition, the use of nanomaterials to improve the operational characteristics of biosensors is becoming increasingly common. Potential environmental applications present a range of challenges for chip-based biosensors.
These challenges include the broad and shifting group of compounds of environmental interest as well as the wide range of contaminated matrices that might be involved. Chip-based biosensors, owing to their unique size and format characteristics, show the potential to provide rapid and cost-effective solutions to environmental monitoring problems.
NOTE
The US Environmental Protection Agency through its Office of Research and Development has funded and managed the research described here. It has been subjected to the Agency’s administrative review and approved for publication as an EPA document. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
REFERENCES 1. S. Rodriguez-Mozaz, M. J. Lopez de Alda, M.-P. Marco, and D. Barcelo, Biosensors for environmental monitoring: a global perspective. Talanta, 2005, 65, 291–297. 2. U. Bilitewski, A. P. F. Turner, Biosensors for Environmental Monitoring, Harwood Academic Publishers, New York, 2000. 3. M. N. Velasco-Garcia and T. Mottram, Biosensor technology addressing agricultural problems. Biosystems Engineering, 2003, 84, 1–12. 4. S. Rodriguez-Mozaz, M. Farre, and D. Barcelo, Screening water for pollutants. Trends in Analytical Chemistry, 2005, 24, 165–169. 5. K. R. Rogers, Recent advances in biosensor techniques for environmental monitoring. Analytica Chimica Acta, 2006, 568, 222–231. 6. R. Ekins, F. Chu, and E. Biggart, Fluorescence spectroscopy and its application to a new generation of highly sensitive multi-microspot, multianalyte, immunoassay. Clinica Chimica Acta, 1990, 194, 91–114. 7. Y. M. Bae, B.-K. Oh, W. Lee, W. H. Lee, and J.-W. Choi, Immunosensor for detection of Yersinia enterocoitica based on imaging ellipsometry. Analytical Chemistry, 2004, 76, 1799–1803. 8. Y. Paitan, I. Biran, N. Shechter, D. Biran, J. Rishpon, and E. Ron, Monitoring aromatic hydrocarbons by whole cell electrochemical biosensors. Analytical Biochemistry, 2004, 335, 175–183. 9. I. Biran, D. M. Rissin, E. Z. Ron, and D. R. Walt, Optical imaging fiber-based live bacterial cell array biosensor. Analytical Biochemistry, 2003, 315, 106–113. 10. S. Szunerits, L. Bouffier, R. Calemczuk, B. Corso, M. Demeunynck, E. Descamps, Y. Defontaine, J.-B.
CHIP-BASED BIOSENSORS FOR ENVIRONMENTAL MONITORING
11.
12.
13.
14.
15.
16.
17.
18.
Fiche, E. Fortin, T. Livache, P. Mailley, A. Roget, and E. Vieil, Comparison of different strategies on DNA chip fabrication and DNA-sensing: optical and electrochemical approaches. Electroanalysis, 2005, 17, 2001–2017. C. A. Rowe-Taitt, J. W. Hazard, K. E. Hoffman, J. J. Cras, J. P. Golden, and F. S. Ligler, Simultaneous detection of six biohazardous agents using a planar waveguide array biosensor. Biosensors and Bioelectronics, 2000, 10, 579–589. A. Y. Rubina, V. I. Dyukova, E. I. Dementieva, A. A. Stomakhin, V. A. Nesmeyanov, E. V. Grishin, and A. S. Zasedatelev, Quantitative immunoassay of biotoxins on hydrogel-based protein microchips. Analytical Biochemistry, 2005, 340, 317–329. J. Tschmelak, G. Proll, J. Riedt, J. Kaiser, P. Kraemmer, L. Barzaga, J. S. Wilkinson, P. Hua, J. P. Hole, R. Nudd, M. Jackson, R. Abuknesha, D. Barcelo, S. RodriguezMozaz, M. J. Lopez de Alda, F. Sacher, J. Stien, J. Slobodnik, P. Oswald, H. Kozmenko, E. Korenkova, L. Tothova, Z. Krascsenits, and G. Gauglitz, Automated water analyser computer supported system (AWACSS) part I: project objectives, basic technology, immunoassay development, software design and networking. Biosensors and Bioelectronics, 2005, 20, 1509. E. Katz, I. Willner, and J. Wang, Electroanalytical and bioelectroanalytical systems based on metal and semiconductor nanoparticles. Electroanalysis, 2004, 16, 19–44. W. P. Hu, S.-J. Chen, K.-T. Huang, J. H. Hsu, W. Y. Chen, G. L. Chang, and K.-A. Lai, A novel ultrahighresolution surface plasmon resonance biosensor with an Au nanocluster-embedded dielectric film. Biosensors and Bioelectronics, 2004, 19, 1465–1471. E. R. Goldman, A. R. Clapp, G. P. Anderson, H. T. Uyeda, J. M. Mauro, I. L. Medintz, and H. Mattoussi, Multiplexed toxin analysis using four colors of quantum dot fluororeagents. Analytical Chemistry, 2004, 76, 684–688. D. E. Nivens, T. E. McKnight, S. A. Moser, S. J. Osbourn, M. L. Simpson, and G. S. Sayler, Bioluminescent bioreporter integrated circuits: potentially small, rugged and inexpensive whole-cell biosensors for remote environmental monitoring. Journal of Applied Microbiology, 2004, 96, 33–46. A. Rothert, S. K. Deo, L. Millner, L. G. Puckett, M. J. Madou, and S. Daunert, Whole-cell-reporter-genebased biosensing systems on a compact disk microfluidics platform. Analytical Biochemistry, 2005, 342, 11–19.
7
19. J.-C. Cho, K.-J. Park, H.-S. Ihm, J.-E. Park, S.-Y. Kim, I. Kang, K.-H. Lee, D. Jahng, D.-H. Lee, and S.-J. Kim, A novel continuous toxicity test system using a luminously modified fresh water bacterium. Biosensors and Bioelectronics, 2004, 20, 338–344. 20. I. Roy and M. N. Gupta, Smart polymeric materials: emerging biomedical applications. Chemistry and Biology, 2003, 10, 1161–1171. 21. K. L. Ewalt, R. W. Haigis, R. Rooney, D. Ackley, and M. Krihak, Detection of biological toxins on an active electronic microchip. Analytical Biochemistry, 2001, 289, 162–172. 22. M. G. Weller, A. J. Schuetz, M. Winklmair, and R. Niessner, Highly parallel affinity sensor for the detection of environmental contaminants in water. Analytica Chimica Acta, 1999, 393, 29–41. 23. J.-W. Choi, K.-W. Park, D.-B. Lee, W. Lee, and W. H. Lee, Cell immobilization using self assembled synthetic oligopeptides and its application to biological toxicity detection using surface plasmon resonance. Biosensors and Bioelectronics, 2005, 20, 2300–2305. 24. J. Dasso, J. Lee, H. Bach, and R. G. Mage, A comparison of ELISA and flow microsphere-based assays for quantification of immunoglobulins. Journal of Immunological Methods, 2002, 263, 23–33. 25. D. A. A. Vignali, Multiplexed particle-based from cytrometric assays. Journal of Immunology Methods, 2000, 243, 243–255. 26. G. E. Lash, P. J. Scaife, B. A. Innes, H. A. Qtun, S. C. Robson, R. F. Searle, and J. N. Bulmer, Comparison of three multiplex cytokine analysis systems: Luminex, SearchLight , and FAST Quant . Journal of Immunology Methods, 2006, 309, 205–208. 27. J. D. Debad, E. N. Glezer, J. N. Wohlstadter, and G. B. Sigal, Clinical and Biological Applications of ECL, in Electrogenerated Chemiluminescence, A. J. Bard (ed), Marcel Dekker, New York, 2003, pp. 43–78. 28. A. J. Bard, J. D. Debad, J. k. Leland, G. B. Sigal, J. L. Wilbur, and J. N. Wohlstadter, Chemiluminescence, Electrogenerated. In Encyclopedia of Analytical Chemistry, R. A. Meyers (ed), John Wiley & Sons, Chichester, 2000, pp. 9842–9849. 29. R. M. Pemberton, R. Pittson, N. Biddle, G. A. Drago, and J. P. Hart, Studies toward the development of a screen printed carbon electrochemical immunosensor array for mycotoxins: A sensor for aflatoxin B1 . Analytical Letters, 2006, 39, 1573–1586.
76 Environmental Biochemical Oxygen Demand and Related Measurement Yoko Nomura,1 Mifumi Shimomura-Shimizu2 and Isao Karube2 1
Department of Biomedical Engineering, University of California, Davis, CA, USA and 2 School of Bionics, Tokyo University of Technology, Tokyo, Japan
1 HISTORY OF BOD MEASUREMENT USING BIOSENSORS
Biochemical oxygen demand (BOD) is one of the important pollutant indices of aquatic environments such as river or wastewater because it can measure organic pollutants. Excess contamination of organic substances in aquatic environment causes serious ecosystem damage. BOD is conventionally measured by the BOD 5-day method, which is very commonly used around the world.1,2 Although it is frequently used, the procedures include sample dilutions and 5-day incubation and require special skills and laboratory facilities. The BOD 5-day method also includes a titration procedure that requires a number of chemicals. The data obtained by this conventional method might be accurate, but it is not suitable for urgent and daily measurements such as monitoring of wastewater from factories. To overcome these disadvantages, a biosensor for BOD estimations was first developed in 1977.3,4 The biosensor was also the first whole-cell biosensor. Biosensors using whole cells of microorganisms are called microbial sensors, which exploit the metabolic functions of living cells. Since whole-cell biosensors or microbial sensors have advantages such as long life, low cost, and low environmental impact, they
have frequently been applied to environmental monitoring.5
2 PRINCIPLE OF BOD SENSOR
Figure 1 shows the BOD sensor fabricated by Karube et al.6 The operating principle of this biosensor is to measure the change in respiration activity of immobilized microorganisms. The biosensor consists of an oxygen electrode (Clark-type oxygen electrode) and an acetylcellulose membrane–immobilized omnivorous yeast Trichosporon cutaneum. The BOD 5-day method uses a consortium of microorganisms, but one of the microorganism species was used in this sensor to obtain high reproducibility of BOD estimation values. Immobilized T . cutaneum can oxidatively degrade most organic compounds (pollutants) in wastewater samples with high respiration activity. T . cutaneum consumes dissolved oxygen in samples when it oxidatively degrades organic compounds, and the oxygen electrode measures the reduction of the dissolved oxygen as current decrease (sensor response). The BOD sensor using T. cutaneum was able to estimate BOD in 20 min without special skills.6 The correlation of the sensor response and the BOD values was linear between 0 and 60 mg l−1 when
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Examples of BOD sensors were also summarized in current reviews,8 and Liu et al. compared performance characteristics of BOD sensors in their review.12 Several BOD sensors are described in the subsequent text.
1 2
4
3.1 5 3
9
8
6
7
Figure 1. The operating principle of the first BOD sensor.6 (1) Aluminum anode, (2) electrolyte, (3) platinum cathode, (4) insulator, (5) bored cap, (6) O-ring, (7) Teflon membrane, (8) immobilized microorganisms, and (9) acetylcellulose membrane. [Reprinted with permission Hikuma et al.6 copyright 1979, Springer.]
glucose-glutamine (GGA) standard solution was measured. The BOD sensor was able to measure several kinds of untreated wastewater from fermentation plants.6 The sensor was commercialized in 1983, and offered an environmentally friendly alternative to BOD measurement, only requiring phosphate buffer and GGA standard solution for the daily measurements. 3 EXAMPLES OF BOD SENSORS
To date, various improvements have been made on BOD biosensors, for example shorter response time (30 s), longer lifetime (16 months) and higher sensitivity (BOD 0.2 mg O l−1 ).7,8 To compensate for the limitation of biosensor measurements caused by short response time or immobilization of only one or a few kinds of microorganisms, enzymes such as cellulase were also used for pretreatment when the BOD sensor was applied to some specific wastewater from pulp factories, and so on8 . Several recent studies describe BOD sensors aimed for practical use and so flow injection analysis (FIA) BOD sensors were developed.8–10 Other transducers such as optical fibers have been used for BOD sensors.11
Disposable BOD Sensor Using Micromachining Techniques
Conventional BOD sensors were bench top instruments because the transducers were not disposable. Yang et al. fabricated a BOD sensor using a disposable oxygen electrode as the transducer.13 This oxygen electrode was a miniature electrode (15 × 2 × 0.4 mm, MOE05, Fujitsu, Japan) fabricated on silicon wafers using micromachining techniques. This BOD sensor measured 0.5 mg l−1 of BOD using GGA solution, which is a standard solution for the BOD 5-day method.
3.2
BOD Sensor for River Water Monitoring
BOD monitoring of river water (below BOD 3 mg l−1 ) was required in Japan but the conventional BOD sensor was not suitable for river water monitoring because of its insensitivity. The sensitivity of a BOD sensor depends on the biodegradation properties of immobilized microorganisms when enough dissolved oxygen is contained in a sample. Immobilized T. cutaneum on the oxygen electrodes cannot degrade the less-biodegradable organic substances, which are the main BOD pollutants in river water discharged from municipal secondary effluents after wastewater treatment. Chee et al. fabricated a BOD sensor that combined an oxygen electrode and isolated bacteria strain of Pseudomonas putida from activated sludge used for municipal wastewater treatments.14 This sensor estimated low BOD values of river water with the use of different dilutions of artificial wastewater for calibration. The correlation coefficient of the values by the sensor and the BOD 5-day method (r 2 ) was 96% when it measured river water, and the correlation improved by incorporating preozonation or photocatalytic oxidation (TiO2 ) as a pretreatment.15,16 This research was supported by the Japanese Ministry of Construction (Ministry of Land Infrastructure and Transport).
BIOCHEMICAL OXYGEN DEMAND AND RELATED MEASUREMENT
3.3
Mediator-type BOD Sensor
The sensitivity of a BOD sensor using an oxygen electrode also depends on the level of dissolved oxygen in the sample, but BOD sensors of mediator type are different. The mediator type of BOD sensors is composed of microorganisms and redox-active substance (e.g., potassium ferricyanide or 2,6dichlorophenolindophenol, DCIP). Yoshida et al. fabricated a mediator-type biosensor as a new approach to BOD estimation. This amperometric biosensor integrated Pseudomonas fluorescens biovar V as an immobilized bacteria and potassium hexacyanoferrate(III) (HCF(III)) of potassium ferricyanide as a mediator. The operating principle is shown in Figure 2.17 The sensor does not directly measure oxygen uptake, but it measures the change in the current response due to the reduction of HCF(III) to HCF(II) during the metabolic oxidation of organic substances by immobilized P. fluorescens biovar V. HCF(III) was the mediator of the oxidized form, and HCF(II) was the mediator of the reduced form. When HCF(III) was present in the reaction medium, it acted as an electron acceptor and was preferentially reduced to HCF(II) during the metabolic oxidation of organic substances. The reduced HCF(III) was then reoxidized at a working electrode (+600 mV vs Ag/AgCl) which was held at a sufficiently high electric potential. As a result, a current was generated and detected using the electrode system. P. fluorescens biovar V was immobilized on a disposable sensor tip (working electrode) by photopolymerizing polymer poly(vinyl alcohol)-quaternized stilbazol (PVA-SbQ). The sensor was tested to measure
3
BOD of the anaerobic synthetic wastewater in which the oxygen electrode could not detect dissolved oxygen. The estimated BOD values up to 150 mg l−1 were almost the same as those when oxygen was supplied.17 After optimization, the dynamic range of the sensor was 15–260 mg l−1 and the reproducibility was also good (Relative Standard Devation was 12.7%). This sensor was able to measure real wastewater samples.17,18 Several mediator-type BOD sensors such as MICREDOX are also currently produced.19 The mediator-type BOD sensors are summarized in the review by Moris et al.20 Moreover, Kim et al. succeeded in the fabrication of a BOD sensor using a micro fuel cell without mediators.21 BOD sensors based on bacterial luminescence were also developed.22,23 3.4
Commercial BOD Sensor
Several BOD sensors have been commercialized to date (Central Kagaku Co., Tokyo; Autoteam GmbH, Berlin, etc.) since the first commercial BOD sensor was produced by Nisshin Electric Co. Ltd in 1983.24 Several companies in Japan and other countries tried to commercialize the BOD sensor. These sensors are based on the first BOD sensor, which detects the change in the respiration activity of the immobilized microorganisms by an oxygen electrode. These commercialized BOD sensors have been described in several reviews.5,7,12,24 The market for BOD sensors was 400 million yen (approximately $3.6 million) in 2003,25 and the interest in biosensors for environmental analysis is still high. The BOD sensor method was established as Japanese Industrial Standard (JIS) in 1990 (JIS Mediator (Re) HCF (II)
Organics + O2 Microorganism
e−
Electrode
Respiratory chain Metabolites CO2, H2O
Dehydrogenase Cytochromes Ubiquinone
Mediator (Ox) HCF (III)
Figure 2. The principle of mediator-type BOD sensor.17 [Reprinted with permission Yoshida et al.17 copyright 2000, Royal Society of Chemistry.]
4
BIOSENSOR APPLICATIONS
4 APPLICATIONS OF BOD SENSOR RESEARCH TO OTHER ENVIRONMENTAL MEASUREMENTS
Figure 3. Commercial BOD sensor “BOD 3300” (http: //www.aqua-ckc.jp/bod 2 Frame.html).
K3602).26 Central Kagaku Co. offers several types of commercial BOD sensors according to JIS K3602 in cooperation with Nisshin Electric Co. Ltd, which manufactures the BOD sensors. Figure 3 shows a photograph of one of the commercial BOD sensors. This sensor “BOD 3300” is used for in situ, continuous monitoring of samples such as wastewater. The sensor can measure up to BOD 500 mg l−1 in 30–60 min. Their latest BOD sensor is a bench top instrument “QuickBOD α-1”, whose detection limit is BOD 2 mg l−1 (http://www.aquackc.jp/bod Frame.html). The sandwich method using two porous membranes was used for immobilization of T . cutaneum to obtain high reproducibility and stability.
Numerous microbial sensors have been fabricated since the development of the BOD sensor as the first microbial sensor. In environmental analysis, microbial sensors can detect and measure nitrogen compounds, sulfur compounds, cyanide, heavy metals (e.g., Hg or Cu, etc.), detergent, and toxic organic compounds such as phenols and polycyclic aromatic hydrocarbons (PAHs), and so on.5,8 Some techniques developed for BOD sensors were useful for developing other microbial sensors. For example, genetically modified microorganisms have been used in whole-cell sensors to detect heavy metals.8,27 Cyanide compounds are highly toxic to fishes and animals, as well as humans. Since aquatic environments such as river water can be accidentally contaminated, rapid and continuous monitoring of cyanide is required. Cyanide has been detected by microbial sensors based on two different operating principles. Some of these sensors used a cyanide biodegrading strain and an oxygen electrode and measured the consumption of dissolved oxygen, similar to the first BOD sensor.28 Other cyanide sensors detected the inhibition of the respiration activity of immobilized microorganisms by cyanide,29 in contrast to the BOD sensors that measure increased respiration activity of the microorganisms. A microbial sensor that measures linear alkylbenzene sulfonates (LAS), an anionic surfactant contained in detergents, was developed.30 Detergent contained in domestic wastewater is not acutely toxic as is cyanide but excess detergent contamination in domestic wastewater can negatively affect the microorganism ecosystem in the activated sludge used at municipal sewage plants. The detergent biosensor developed was a bioreactor type sensor which consisted of LAS-degrading bacteria and a flow-cell-type oxygen electrode.30 The oxygen electrode measured the consumption of dissolved oxygen caused by the biodegradation of LAS by the immobilized strain in the columns. This biosensor also responded to organic compounds in river water, but the selectivity of this sensor was improved by the use of another microbial sensor, immobilized T. cutaneum. The optimized LAS sensor could measure 0.2 mg l−1 of LAS in 15 min and the sensor was tested for continuous river water monitoring in situ.31
BIOCHEMICAL OXYGEN DEMAND AND RELATED MEASUREMENT
5
Figure 4. Soil quality sensor “Biosensor for soil diagnosis” (http://www.aist.go.jp/aist e/latest research/2004/20040402 1/ 20040402 1.html).
Currently, techniques developed for BOD sensors are being applied to soil quality measurement (http://www.aist.go.jp/aist e/latest research/2004/ 20040402 1/20040402 1.html). Our group and Sakata Seed Company fabricated a soil-diagnosis sensor that can rapidly detect soil diseases. Figure 4 shows the photograph of the “Biosensor for soil diagnosis”, which is the first prototype instrument based on the measurement of respiration change in immobilized soil microorganisms by oxygen electrodes. The principle of the mediator-type microbial sensor is also applicable to such soil diagnosis. Numerous microbial sensors were derived from the first BOD sensor, and some of these might be commercialized in the near future. Microbial sensors offer quick and convenient detection of environmental pollutants and toxicants.
REFERENCES 1. Japanese Industrial Standard Committee, Testing Methods for Industrial Wastewater (JIS K0102) 1993 Japanese Standards Association, Tokyo.
2. American Public Health Association, Standard Methods for Examination of Water and Wastewater 1986 American Public Health Association, Washington. 3. I. Karube, T. Matsunaga, S. Mitsuda, and S. Suzuki, Microbial electrode BOD sensors. Biotechnology and Bioengineering, 1997, 19, 1535–1547. 4. I. Karube, T. Matsunaga, and S. Suzuki, A new microbial electrode for BOD estimation. Journal of Solid-Phase Biochemistry, 1977, 2, 97–104. 5. I. Karube, Y. Nomura, and Y. Arikawa, Biosensors for environmental control. Trends in Analytical Chemistry, 1995, 14, 295–299. 6. M. Hikuma, H. Suzuki, T. Yasuda, I. Karube, and S. Suzuki, Amperometric estimation of BOD by using living immobilized yeasts. European Journal of Applied Microbiology and Biotechnology, 1979, 8, 289–297. 7. Y. Nomura, G. J. Chee, and I. Karube, Biosensor technology for determination of BOD. Field Analytical Chemistry and Technology, 1998, 2, 333–340. 8. K. Riedel, G. Kunze, and A. Konig, Microbial sensors on a respiratory basis for wastewater monitoring. Advances in biochemical engineering/biotechnology, 2002, 75, 81–118. 9. J. Liu, G. Olsson, and B. Mattiasson, Short-term BOD (BODst ) as a parameter for on-line monitoring of biological treatment process Part I. A novel design of BOD biosensor for easy renewal of bio-receptor. Biosensors and Bioelectronics, 2004, 20, 562–570. 10. J. Liu, G. Olsson, and B. Mattiasson, Short-term BOD (BODst ) as a parameter for on-line monitoring
6
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
BIOSENSOR APPLICATIONS of biological treatment process Part II: instrumentation of integrated flow injection analysis (FIA) system for BODst estimation. Biosensors and Bioelectronics, 2004, 20, 571–578. G. J. Chee, Y. Nomura, K. Ikebukuro, and I. Karube, Optical fiber biosensor for the determination of low biochemical oxygen demand. Biosensors and Bioelectronics, 2000, 15, 371–376. J. Liu and B. Mattiasson, Microbial BOD sensors for wastewater analysis. Water Research, 2002, 36, 3786–3802. Z. Yang, H. Suzuki, S. Sasaki, S. McNiven, and I. Karube, Comparison of the dynamic transient- and steady-state measuring methods in a batch type BOD sensing system. Sensors and Actuators B, 1997, 45, 217–222. G. J. Chee, Y. Nomura, and I. Karube, Biosensor for the estimation of low biochemical oxygen demand. Analytica Chimica Acta, 1999, 379, 185–191. G. J. Chee, Y. Nomura, K. Ikebukuro, and I. Karube, Development of photocatalytic biosensor for the evaluation of biochemical oxygen demand. Biosensors and Bioelectronics, 2005, 21, 67–73. G. J. Chee, Y. Nomura, K. Ikebukuro, and I. Karube, Development of highly sensitive BOD sensor and its evaluation using preozonation. Analytica Chimica Acta, 1999, 394, 65–71. N. Yoshida, K. Yano, T. Morita, S. J. McNiven, H. Nakamura, and I. Karube, A mediator-type biosensor as a new approach to biochemical oxygen demand estimation. The Analyst, 2000, 125, 2280–2284. N. Yoshida, J. Hoashi, T. Morita, S. J. McNiven, H. Nakamura, and I. Karube, Improvement of a mediator-type biochemical oxygen demand sensor for onsite measurement. Journal of Biotechnology, 2001, 88, 269–275. N. Pasco, K. Baronian, C. Jeffries, J. Webber, and J. Hay, MICREDOX -development of a ferricyanide-mediated rapid biochemical oxygen demand method using an immobilised Proteus vulgaris biocomponent. Biosensors and Bioelectronics, 2004, 20, 524–532. K. Morris, H. Zhao, and R. John, Ferricyanide-mediated microbial reactions for environmental monitoring. Australian Journal of Chemistry, 2005, 58, 237–245.
21. I. S. Chang, J. K. Jang, G. C. Gil, M. Kim, H. J. Kim, B. W. Cho, and B. H. Kim, Continuous determination of biochemical oxygen demand using microbial fuel cell type biosensor. Biosensors and Bioelectronics, 2004, 19, 607–613. 22. C. K. Hyun, E. Tamiya, T. Takeuchi, and I. Karube, A novel BOD sensor based on bacterial luminescence. Biotechnology and Bioengineering, 1993, 41, 1107–1111. 23. T. Sakaguchi, K. Kitagawa, T. Ando, Y. Murakami, Y. Morita, A. Yamamura, K. Yokoyama, and E. Tamiya, A rapid BOD sensing system using luminescent recombinants of Escherichia coli . Biosensors and Bioelectronics, 2003, 19, 115–121. 24. K. Riedel, Application of Biosensors to Environmental Samples, in Commercial Biosensors: Applications to Clinical, Bioprocess, and Environmental Samples, G. Ramsay (ed) 1998 John Wiley & Sons, New York, pp. 267–294. 25. Nikkei Business Publications Inc., Nikkei Bio Nenkan 2004 (Annual Report of Bio Market) 2004 Nikkei Business Publications, Tokyo. 26. Japanese Industrial Standard Committee, Apparatus for the Estimation of Biochemical Oxygen Demand (BODs) with Microbial Sensor (JIS K3602) 1990 Japanese Standards Association, Tokyo. 27. A. Ivask, K. Hakkila, and M. Virta, Detection of organomercurials with sensor bacteria. Analytical Chemistry, 2001, 73, 5168–5171. 28. J. I. Lee andI. Karube, A novel microbial sensor for the determination of cyanide. Analytica Chimica Acta, 1995, 313, 69–74. 29. K. Ikebukuro, A. Miyata, S. J. Cho, Y. Nomura, S. M. Chang, Y. Yamauchi, Y. Hasebe, S. Uchiyama, and I. Karube, Microbial cyanide sensor for monitoring river water. Journal of Biotechnology, 1996, 48, 73–80. 30. Y. Nomura, K. Ikebukuro, K. Yokoyama, T. Takeuchi, Y. Arikawa, S. Ohno, and I. Karube, A novel microbial sensor for anionic surfactant determination. Analytical Letters, 1994, 27, 3095–3108. 31. Y. Nomura, K. Ikebukuro, K. Yokoyama, T. Takeuchi, Y. Arikawa, S. Ohno, and I. Karube, Application of a linear alkylbenzene sulfonate biosensor to river water monitoring. Biosensors and Bioelectronics, 1998, 13, 1047–1053.
77 Optical Biosensor for the Determination of Trace Pollutants in the Environment Guenter Gauglitz,1 Guenther Proll1 and Jens Tschmelak2 ¨ ¨ 1
Institute of Physical and Theoretical Chemistry, Eberhard Karls University of Tuebingen, Tuebingen, Germany and 2 Bierlachweg, Erlangen, Germany
1 INTRODUCTION
Clean water, its secure delivery to consumers, and protection of resources are among the most important problems for humans in the future. Thus, pollution of water sources, aquifers, and wetland systems caused by industry, agriculture, municipally created waste water, and recreational activities is identified as a Europe-wide problem, especially in the newly admitted European Union member states. Today, pollution of ground, surface, and riverwater by agriculture, industry and mining, traffic, boating, sports, and tourism presents a growing danger for drinking water. Therefore, the European Community has funded projects, beginning with the Framework IV programme, in order to implement strategies to measure and control pollution from various sources and to establish their practical use. These are demonstrated by the European Community Water Directives.1,2 In parallel, projects were funded to establish fast, sensitive, cost-effective, and easy-to-use analytical systems capable of measuring a variety of small organic pollutants in aqueous systems, especially in the areas of herbicides, fungicides, insecticides, antibiotics, blue algae, toxins, endocrine disrupting compounds, and suspected carcinogens. At present, technologies for water analyses are available, such as liquid chromatography (LC),
high-performance liquid chromatography (HPLC), and gas chromatography (GC) in combination with detection principles such as mass spectrometry (MS) or diode array detection (DAD) and especially fluorescence detection (FLD). These methods have been reviewed in preceding years.3–5 However, although these methods are well established and can look back on decades of developments and successful application, all of them require enrichment of water samples by several orders of magnitude prior to analysis to enable suitable trace analysis performance. Accordingly, a time-consuming solid phase extraction (SPE) is typically used as an enrichment procedure. This pretreatment step makes it difficult and rather expensive to develop suitable online monitoring systems and might be the reason why only a few such systems exist so far.6,7
2 IMMUNOASSAY-BASED SYSTEMS
Within the preceding context, immunoassays were introduced into water analysis since they offer very low detection limits. Thus, they are considered not to need any enrichment steps and require neither cleanup steps nor preconcentration. The common immunoassay formats of enzymelinked immunosorbent assay (ELISA) are based
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
on immunochemistry and are supposed to offer a high potential for new application in the future.8 However, all these new approaches lack the possibility of automation, are time consuming, and require personnel. A combination of these immunoassays and FLD techniques at least lowers the limit of detection and the limit of quantification. In combination with a suitable test format, for example, sandwich assay or noncompetitive, they can easily be carried out by flow-injection analysis (FIA).9 The new approaches in array technology, miniaturization and transduction in sensor signals, provide a new generation of immunosensor systems. Accordingly, the group of Ligler developed one of the first portable and fully automated total internal reflection fluorescence (TIRF)-based biosystems, suitable for multianalyte detection.10,11 These newly developed strategies of biosensing can take advantage of arraying or layout array systems of recognition elements to allow simultaneous detection and quantification of multiple analytes.12 In contrast to the above-mentioned well-established ELISA methods, biosensors13 allow easy automation of immunoassays and therefore provide perfect features to meet current requirements in water analyzing systems. Some of the research groups currently using TIRF-based biosensors for a variety of applications are cited in Ref. 14.
3 AUTOMATIC MEASURING DEVICES
In our group, this approach of a fully automated system gaining low limits of detection and quantification by using the TIRF method and being based on either integrated optics or bulk-optic chips has been followed for many years. The first successful instrumentation was the river analyzer (RIANA) system (ENV4-CT95-0066).15–17 Following the requirements of the EU water legislation and the needs of wastewater and drinking water facilities as well as according to the risk assessment/risk management approach,18 target compounds are selected mainly from the groups of modern pesticides, endocrine disrupting compounds, pharmaceuticals, and toxins. In addition, a potential water-monitoring device needs to be robust, cost-effective, automated, and able to measure several tens of organic pollutants at
low nanogram per liter levels in a very short time, preferably without any time-consuming sample concentrations and prior sample pretreatments. Another feature is considered to become more and more interesting for the future, namely the possibility of instruments with remote control, automated data processing, and the generation of alarm signals when the pollutant’s concentration exceeds a preset threshold value. The RIANA system mentioned above allows measurement of water samples without preconcentration and even in various matrices. In the case of many target samples, lower limits of detection than those defined by the European Commission at micrometer per liter levels could be achieved.19,20 Data can be referenced by classical analytical methods.21 On the basis of this successful implementation of the RIANA system, a joint European project, Automated Water Analyzer Computer Supported System (AWACSS),22 was launched 5 years ago, where 9 different groups from all over Europe started to set up a device meeting the abovementioned prerequisites. Within the setup, flow injection was combined with a microfluidic cell, covering an integrated optical device in which laser radiation in the visible range is coupled in via optical fiber. The pigtailed IO chip provides waveguide arms with radiation totally internally reflected and supplying an evanescent field at the surface. At the surface, analytes are immobilized covalently using a biolayer interface, which supplies high loading of recognition elements and drastic reduction of nonspecific binding and fast biomolecular interaction processes. Modern spotting techniques using a Top Spot23 offer the possibility of a spatially resolved surface chemistry to immobilize 32 recognition spots either for replica measurements or for multiple analyte analysis. Pollutant-specific antibodies are added to the sample, the mixture is transferred by a flowinjection system, passing this optical transduction element. The added antibodies are all labeled with the same fluorophore, in this case Cy5.5. If the specific pollutant is present, the antibody is blocked in the sample solution, and the other nonblocked antibody can diffuse to the surface, which is monitored laterally resolved by an array of 32 fibers. This binding inhibition test format (see Figure 1) allows shifting the system via the antibody concentration to low limits of detection.
OPTICAL BIOSENSING OF TRACE POLLUTANTS IN THE ENVIRONMENT Antibodies
* ** *** * * * * Analytes
Flow cell
Incubation phase
*
*
3
Dye
*
* *** * * * *
** * * ** **
Laser pigtail
Volume
Surface
IO chip
Figure 1. The AWACSS biosensor employs fluorescence-based detection of the binding of fluorophore-tagged biomolecules to the surface of an IO chip. The recognition is based on a binding inhibition assay.
Figure 2. Picture of the setup with control unit, measuring system, and autosampler.
The setup is shown in Figure 2, including an autosampler for sample delivery, washing steps, and regeneration. The system includes a computer as a control unit for the measuring device and as a link to a web server, which contains a database as well as a threshold-based warning system. A typical calibration curve is given in Figure 3. For accurate measurements with this heterogeneous noncompetitive assay format it is necessary to minimize effects that have an influence on the detected fluorescent light intensity. Beside a stabilized excitation light source, for example, a semiconductor laser with a monitoring diode, it is of great importance to reduce nonspecific binding of antibodies to the matrix or to the sensor surface. During assay design for the above-mentioned
systems we obtained best results by adding an excess of ovalbumin as a background protein to the antibody stock solution. Nonspecific binding to the sensor surface was suppressed by layers of bio-polymers like polyethylene glycol and/or aminodextrane. In the following some details of a typical evaluation are discussed. Results are limit of detection, limit of quantification, and working range.
4 EVALUATION STRATEGIES
The standard experimental design for a calibration routine consists of nine independent blank (e.g., Milli-Q water) measurements and eight
4
BIOSENSOR APPLICATIONS Working range from 0.025 to over 10 µg l−1
110 Estrone
100
Logistic fit 90
Horwitz curve
10−90% of the dynamic signal range
Relative signal (%)
80 70 60 50 40 30
Precision profile
20
cAb = 120 ng ml−1
10 0 0
0.01
0.1 1 Estrone concentration (µg l−1)
10
100
Figure 3. Calibration curve for estrone including logistic function, Horwitz curve, working range, and precision profile.
concentration steps (each measured as three replicas) of the analyte (e.g., spiked Milli-Q water). For all concentration steps and the blank measurements (nine replicas), the mean value and the standard deviation value (SDV) for the replica were calculated. The measured signal for the mean value of the blanks was set to 100%, and all spiked samples could be obtained as a relative signal below this blank value. To fit the data set a logistic fit function (parameters of a logistic function: A1 , A2 , x0 , and p)24 was used: y=
A1 − A2 p + A2 1 + xx0
(1)
A1 is the upper asymptote and A2 the lower one. The range between A1 and A2 is the dynamic signal range. The inflection point is given by the variable x0 and represents the analyte concentration, which corresponds to a decrease of 50% of the dynamic signal range—the inhibitory concentration 50% (IC50 ). The slope of the tangent in this point is given by the parameter p. Out of the logistic fit data, the 10–90% range of the dynamic signal can be calculated, which gives a
first impression of the possible utilization range of the received calibration curve. In compliance with the International Union of Pure and Applied Chemistry (IUPAC) rules “The Orange Book”,25 the limit of detection (LOD) is calculated as 3 times the standard deviation of the blanks (SDVb ) and the limit of quantification (LOQ) is calculated as 10 times the SDVb . The use of LOQ for logistic calibration curves is a contentious issue, because with its nonlinear behavior the results for immunoassays are often worse than they need to be. A real alternative is the use of the 95% confidence belt and the associated minimum detectable concentration (MDC) and reliable detection limit (RDL), which can easily be calculated for the sigmoidal calibration curves.26 These authors reported on calibration and assay development using the four-parameter logistic model and assay quality control procedures. To determine the working range, the precision profile (xcv,i ) and its intersections with the Horwitz curve27,28 has to be calculated. On the basis of scores of Association of Analytical Communities (AOAC) intercomparison programs, Horwitz developed an empiric correlation between the comparative standard deviation (SD) and the
OPTICAL BIOSENSING OF TRACE POLLUTANTS IN THE ENVIRONMENT
concentration. For laboratory intercomparison programs Horwitz proposed an equation for the reproducibility σR = f · c0.8495 with a factor f = 0.02. The corresponding error is the relative standard deviation RSD = 100 (σR c) that can be calculated with the reproducibility σR and the analyte concentration c. For intralaboratory reproducibility, Horwitz found a higher precision and consequently lower RSD values. In this case, the factor f can be reduced to two-thirds up to half of its former value. RSD values can be calculated for each concentration and they represent the Horwitz curve. An applicable concentration determination is possible only if the precision profile is below the Horwitz curve. The SD values of the inverse function (SDVxi ) can be calculated using the SD values of the measured data (SDVyi ) and the associated values of the first derivative (y ) of the logistic fit (y) for each concentration. Then the variation coefficients (xcv,i ) can be calculated and plotted together with the values of the Horwitz curve and the calibration data including the logistic fit in the semilogarithmic graph. Finally, the range between the intersection
points of the Horwitz curve and the precision profile represents the working range. 5 RECENT IMPROVEMENTS
Improvement of the optical transduction system and the quality of the evanescent field by the University of Southampton, the improvement of the electronic devices by Siemens, and the microfluidics by CRL resulted in a drastic improvement of the limits of detection obtained with this instrument in comparison with the first RIANA setup. At the final presentation, the consortium could demonstrate a fully automated system requiring water samples and sending the analytical results via the Internet to a host computer system in which the values and the database-based EU threshold values were compared. Accordingly, warning was sent via SMS to a mobile of a representative. In the meantime, a large variety of analytes has been examined. Table 1 provides an overview of the samples, the limits of detection, and the limits of quantification.29–35 All details are given in these publications. Since the apparatus is working
Table 1. Summarized results of trace measurements of pollutants in water
LOD (µg l−1 )
LOQ (µg l−1 )
SDV (%)
Atrazine Isoproturon Propanil
0.0099 0.0008 0.0006
0.0710 0.0089 0.0045
2.70 1.22 1.29
Bisphenol A Caffein
0.0080 0.0008
0.0710 0.0090
0.90 0.90
Sulphadimethoxine Sulphatiazole Sulphadiazine Sulphadimidine Sulphamethoxazole Sulphamethizole Sulphamethoxypyridazine
0.0038 0.0027 0.0038 0.0032 0.0066 0.0042 0.0042
0.0447 0.0284 0.1167 0.0452 0.1781 0.0748 0.0523
1.56 1.24 1.26 1.42 1.06 1.43 0.68
Tetrahydrocanabiol
0.0029
0.0424
1.52
Estrone Progesterone Testosterone
0.0002 0.0002 0.0002
0.0014 0.0020 0.0052
0.67 2.70 3.40
Before optimization Atrazine Simazine Isoproturon Alachlor 2,4-D Paraquat PCP
0.03 0.03 0.11 0.07 0.07 0.01 4.23
Analyte
5
0.30 0.30 1.10 0.70 0.70 0.09 45
3.33 1.70 2.08 3.98 2.15 10 4.59
6
BIOSENSOR APPLICATIONS
highly reproducibly, the SDVs are small, and most recovery rates are in the ranges given by the AOAC International. Some of these values have been referenced to classical and standardized analytical methods in laboratories of the partners.36
6 RESULTS OF A FIELD TEST
Within the first field test of the instrument a small river in the southern part of Germany was selected, where the complete measurement station was installed together with a sampling setup in a watershed for raw tap water. The IO chip was modified and calibrated to measure atrazine, isoproturon, estrone, and bisphenol A. The simultaneous calibration was performed from 0 to 90 µg l−1 in nine steps and resulted in four calibration curves (see Figure 4). For all compounds, the calculated LOD was below 7 ng l−1 . The small river was successfully monitored over a period of approximately 24 h by using the AWACSS instrument in unattended and quasicontinuous mode. The fully automated system measured several times triplicates of riverwater
samples and Milli-Q blanks as a reference. On the basis of the calibration parameters, the individual concentrations of the four compounds were automatically calculated by the instrument’s software package. The river has been sampled also manually for intensive comparison measurements with common analytical methods at an accredited laboratory. For estrone, all biosensor measurements as well as the HPLC control measurements have been below the LOQ for both systems. Bisphenol A was not possible to measure because of an enormous leaching of this chemical substance out of the tubing of the sampling system. For the continuous monitoring of the two pesticides very good results that are confirmed by HPLC measurements could be obtained with the biosensor system. This field test demonstrated the ability of the AWACSS providing a tool for the continuous monitoring of organic pollutants in riverwater. Once a measurement station is installed only a little maintenance of the system is necessary. Nonexperts can carry out the exchange of buffer solutions and the replacement of the sensor-chip unit after 500 measurements.37
100
Estrone Bisphenol A Isoproturon Atrazine
90 80
Relative signal (%)
70 60 50 40 30 20 10 0 0
0.01
0.1
1
10
100
Analyte concentration (µg l−1) Figure 4. Simultaneous calibration for atrazine, bisphenol A, estrone, and isoproturon. For all compounds the calculated LOD is below 0.007 µg l−1 .
OPTICAL BIOSENSING OF TRACE POLLUTANTS IN THE ENVIRONMENT
7 CONCLUSION
For the first time in water analysis an automated device facilitated the monitoring of a multianalyte system based on a fully automated immunoassay with limits of detection in the range of 1 ng l−1 for many analytes. The verification of the reproducibility, precision, and robustness of the optical sensor was also demonstrated by successful real sample measurements. Most recovery rates were between 70 and 100% for spiked tap water and different riverwaters. To avoid false-negative finds at very low analyte concentrations, a new strategy for matrix measurements was developed.38 Very good recovery rates were achieved for ultra-sensitive measurements of various endocrine disrupting compounds,39 algae toxins, and even measurements in nonaqueous matrices such as milk or sera.40 All in all, time for one measurement includes incubation and a regeneration step below 15 min, where the real measurement takes just 2 min. The sophisticated surface chemistry allows regenerating the optical transduction devices more than 500 times without loss of quality.
7
James Wilkinson, Optoelectronics Research Centre, Southampton University, Southampton, UK; microfluidics were included in the system together with some electronics by the Central Research Laboratories Ltd., Hayes, UK; system integration and web-based process control was supplied by Mr. Kaiser, Siemens AG, Erlangen, Germany; reference measurements were carried out by Professor Barcel´o, Ministerio de Ciencia y Tecnolog´ıa, Department of Environmental Chemistry, Barcelona, Spain; real water samples and reference methods were carried out by Frank Sacher, PhD, DVGW-Technologiezentrum Wasser, Karlsruhe, Germany, E. Korenkov´a, Environmental Institute, Kos, Slovak Republic, and Jaroslav Slobodnik, PhD, Water Research Institute, Bratislava, Slovak Republic. Jens Tschmelak held a fellowship, and G¨unther Proll participated in the research training group “Quantitative Analysis and Characterization of Pharmaceuticals and Biochemically relevant Substances” funded by the DFG (Deutsche Forschungsgesellschaft) at the Eberhard Karls University of Tuebingen.
REFERENCES ACKNOWLEDGMENTS
The work was done with some European-funded projects such as the River Analyzer project (RIANA ENV4-CT95-0066) by the European Commission under the Environment and Climate Programme (4th Framework Programme), the Automated Water Analyzer Computer Supported System project (AWACSS EVK1-CT-200000045), supported by the European Commission under the 5th Framework programme and contributing to the implementation of the key action “Sustainable Management and Quality of Water” within the Energy, Environment, and Sustainability Development Programme. Part of this work was also funded by the Bundesministerium f¨ur Bildung und Forschung (BMBF) within the PIWAS project (Parallisiertes Immunreaktionsbasiertes Wasseranalysatorsystem; 02WU0243). The antibodies were supplied by Ram Abuknesha, PhD, King’s College London, London, UK. The integrated optics were optimized by
1. Council directive (98/83/EC) of 3 November 1998 relating to the quality of water intended for human consumption. Official Journal of the European Community, 1998, L330, 32–54. 2. Directive 2000/60/EC of the European parliament and of the council of 23 October 2000 establishing a framework for community action in the field of water policy. Official Journal of the European Community, 2000, L327, 1–72. 3. D. Barcel´o and M. C. Hennion, Trace Determination of Pesticides and their Degradation Products in Water, Elsevier, Oxford, 1997. 4. D. Barcel´o and M. C. Hennion, Sampling of polar pesticides from water matrices. Analytica Chimica Acta, 1997, 338, 3–18. 5. D. Barcel´o (ed), Environmental Analysis: Sample Handling and Trace Analysis of Pollutants—Techniques, Applications and Quality Assurance, Elsevier, Oxford, 2000. 6. B. Allner, G. Wegener, T. Knacker, and P. StahlschmidtAllner, Electrophoretic determination of estrogen-induced protein in fish exposed to synthetic and naturally occurring chemicals. Science of the Total Environment, 1999, 233, 21–31. 7. P. Lopez-Roldan, M. J. Lopez de Alda, and D. Barcel´o, Simultaneous determination of selected endocrine disrupters (pesticides, phenols and phthalates) in water by in-field solid-phase extraction (SPE) using the prototype PROFEXS followed by on-line SPE (PROSPEKT)
8
8. 9.
10.
11.
12.
13.
14. 15. 16.
17.
18.
19.
20.
21.
22. 23.
24.
BIOSENSOR APPLICATIONS and analysis by liquid chromatography-atmospheric pressure chemical ionisation-mass spectrometry. Analytical and Bioanalytical Chemistry, 2004, 378, 599–609. R. J. Schneider, Environmental immunoassays. Analytical and Bioanalytical Chemistry, 2003, 375, 44–46. P. M. Kraemer, A. Franke, and C. Standfuss-Gabisch, Flow injection immunoaffinity analysis (FIIAA)—a screening technology for atrazine and diuron in water samples. Analytica Chimica Acta, 1999, 399, 89–97. F. S. Ligler, J. P. Golden, C. A. Rowe-Taitt, and J. P. Dodson, Array biosensor for simultaneous detection of multiple analytes. Proceedings of SPIE, 2001, 4252, 32–36. K. E. Sapsford, Y. S. Shubin, J. B. Delehanty, J. P. Golden, C. R. Taitt, L. C. Shriver-Lake, and F. S. Ligler, Fluorescence-based array biosensors for detection of biohazards. Journal of Applied Microbiology, 2004, 96, 47–58. F. S. Ligler, K. E. Sapsford, Y. S. Shubin, J. Lemmond, C. A. Rowe-Taitt, J. B. Delehanty, and J. P. Golden, Array biosensor for environmental monitoring. Proceedings of SPIE, 2002, 4576, 63–67. H. H. Weetall, Chemical sensors and biosensors, update, what, where, when and how. Biosensors and Bioelectronics, 1999, 14(2), 237–242. O. S. Wolfbeis and R. Narayanaswamy (eds), Optical Sensors, Springer, 2004 (ISBN 3-540-40886-X). RIANA ENV4-CT95-0066. U. Schobel, C. Barzen, and G. Gauglitz, Immunoanalytical techniques for pesticide monitoring based on fluorescence detection. Fresenius Journal of Analytical Chemistry, 2000, 366, 646–658. A. Klotz, B. Brecht, C. Barzen, G. Gauglitz, R. D. Harris, G. R. Quigley, J. S. Wilkinson, and R. A. Abuknesha, Immunofluorescence sensor for water analysis. Sensors and Actuators B-Chemical, 1998, 51(1–3), 181–187. World Health Organization, Guidelines for Drinking Water Quality, 3rd Edn, World Health Organization, Geneva, 2003. C. Barzen, A. Brecht, and G. Gauglitz, Optical multipleanalyte immunosensor for water pollution control. Biosensors and Bioelectronics, 2002, 17, 289–295. S. Rodriguez-Mozaz, S. Reder, M. Lopez de Alda, G. Gauglitz, and D. Barcel´o, Simultaneous multi-analyte determination of estrone, isoproturon and atrazine in natural waters by the river analyser (RIANA), an optical immunosensor. Biosensors and Bioelectronics, 2004, 19, 633–640. E. Mallat, C. Barzen, A. Klotz, A. Brecht, G. Gauglitz, and D. Barcelo, River analyzer for chlorotriazines with a direct optical immunosensor. Environmental Science and Technology, 1999, 33, 965–971. AWACSS EVK1-CT-2000-00045. B. de Heij, M. Daub, O. Gutmann, R. Niekrawietz, H. Sandmaier, and R. Zengerle, Highly parallel dispensing of chemical and biological reagents. Analytical and Bioanalytical Chemistry, 2004, 378, 119–122. R. A. Dudley, P. Edwards, R. P. Ekins, D. J. Finney, I. G. M. McKenie, G. M. Raab, D. Rodbard, and R. P. C. Rodgers, Guidelines for immunoassay data processing. Clinical Chemistry, 1985, 31, 1264–1271.
25. J. Inczedy, T. Lengyel, and A. M. Ure, Compendium of Analytical Nomenclature. Definitive Rules 1997 , The Orange Book, 3rd Edn, Blackwell Science, Oxford, 1998. 26. M. A. O‘Connell, B. A. Belanger, and P. D. Haaland, Calibration and assay development using the fourparameter logistic model. Chemometrics and Intelligent Laborary Systems, 1993, 20, 97–114. 27. W. Horwitz, L. R. Kamps, and K. W. Boyer, Quality assurance in the analysis of foods and trace constituents. Journal of The Association of Official Agricultural Chemists, 1998, 63, 1344–1353. 28. V. R. Meyer, Are duplicate determinations necessary? Schweizerische Laboratoriums-Zeitschrift, 2003, 60, 63–65. 29. J. Tschmelak, G. Proll, and G. Gauglitz, Verification of performance with the automated direct optical TIRF immunosensor (River Analyser) in single and multianalyte assays with real water samples. Biosensors and Bioelectronics, 2004, 20, 743–752. 30. J. Tschmelak, G. Proll, and G. Gauglitz, Sub-nanogram per liter detection of the emerging contaminant progesterone with a fully automated immunosensor based on evanescent field technique. Analytica Chimica Acta, 2004, 519, 143–146. 31. J. Tschmelak, G. Proll, and G. Gauglitz, Ultra-sensitive fully automated immunoassay for the detection of propanil in aqueous samples—steps of progress toward a subnanogram per liter detection. Analytical and Bioanalytical Chemistry, 2004, 379, 1004–1012. 32. J. Tschmelak, G. Proll, J. Riedt, J. Kaiser, P. Kraemmer, L. B´arzaga, J. S. Wilkinson, P. Hua, J. P. Hole, R. Nudd, M. Jackson, R. Abuknesha, D. Barcel´o, S. Rodriguez-Mozaz, M. J. L´opez de Alda, F. Sacher, J. Stien, J. Slobodn´ık, P. Oswald, H. Kozmenko, E. Korenkov´a, L. T´othov´a, Z. Krascsenits, and G. Gauglitz, Automated water analyser computer supported system (AWACSS)—Part I: project objectives, basic technology, immunoassay development, software design and networking automated water analyser computer supported system (AWACSS)—Part II: Intelligent, remote–controlled, cost–effective, on–line, water-monitoring measurement system. Biosensors and Bioelectronics, 2005, 20, 1499–1508; 1509–1519. 33. G. Proll, J. Tschmelak, and G. Gauglitz, Fully automated biosensors for water analysis. Analytical and Bioanalytical Chemistry, 2005, 381, 61–63. 34. J. Tschmelak, G. Proll, J. Riedt, J. Kaiser, P. Kraemmer, L. B´arzaga, J. S. Wilkinson, P. Hua, J. P. Hole, R. Nudd, M. Jackson, R. Abuknesha, D. Barcel´o, S. RodriguezMozaz, M. J. L´opez de Alda, F. Sacher, J. Stien, J. Slobodn´ık, P. Oswald, H. Kozmenko, E. Korenkov´a, L. T´othov´a, Z. Krascsenits, and G. Gauglitz, Biosensors for unattended, cost-effective and continuous monitoring of environmental pollution: automated water analyser computer supported system—AWACSS and river analyser—RIANA. International Journal of Environmental Analytical Chemistry, 2005, 85, 837–852. 35. J. Tschmelak, G. Proll, and G. Gauglitz, Improved strategy for biosensor based monitoring of water bodies with diverse organic carbon levels. Biosensors and Bioelectronics, 2005, 21, 979–983.
OPTICAL BIOSENSING OF TRACE POLLUTANTS IN THE ENVIRONMENT 36. M. Petrovic, E. Eljarrat, M. J. Lopez de Alda, and D. Barcel´o, Recent advances in the mass spectrometric analysis related to endocrine disrupting compounds in aquiatic environmental samples. Journal of Chromatography A, 2002, 974(1–2), 23–51. 37. G. Proll and G. Gauglitz, Viable Methods of Soil and Water Pollution Monitoring, Protection and Remediation, NATO Science Series, Irena. Twardowska, Herbert. E. Allen, M. H. H¨aggblom (eds), ISBN-10 1-4020-4728-2 (e-book), Springer 2006. 38. J. Tschmelak, G. Proll, and G. Gauglitz, Optical biosensor for pharmaceuticals, antibiotics, hormones, endocrine disrupting chemicals and pesticides in water: assay
9
optimisation process for estrone as example. Talanta, 2005, 65, 313–323. 39. J. Tschmelak, M. Kumpf, N. K¨appel, G. Proll, and G. Gauglitz, Total internal reflectance fluorescence (TIRF) biosensor for environmental monitoring of testosterone with commercially available immunochemistry: antibody characterization, assay development and real sample measurements. Talanta, 2006, 69, 343–350. 40. J. Tschmelak, N. K¨appel, and G. Gauglitz, TIRF-based biosensor for sensitive detection of progesterone in milk based on ultra-sensitive progesterone detection in water. Analytical and Bioanalytical Chemistry, 2005, 382, 1895–1903.
78 Food and Beverage Applications of Biosensor Technologies Helge R. Schnerr Department of Food Safety and Food Quality, Leatherhead Food International Ltd., Leatherhead, UK
1 INTRODUCTION
Food products are analyzed for a variety of reasons, for example, compliance with legal and labeling requirements, confirmation of quality and safety, hygienic aspects, nutritional adequacy, and authenticity of food products. To categorically confirm the quality and safety of final products, raw materials and products must be closely monitored for contaminants, disease-causing agents, and the presence of harmful compounds, such as allergens, as well as for nutritional evaluation purposes. The quality control of nutritional content and confirmation of food safety are major tasks for food and drinks manufacturers to ensure high-quality standards and minimize risk for the consumer. Since food products and their raw materials are complex mixtures of chemical compounds, highly specific, cost-effective, and reliable methods are increasingly needed. For the past 25 years, we have witnessed remarkable progress in the development of affinity biosensors and their applications in areas such as medical diagnostics, drug screening, and food safety and security. Food analysis still involves extensive sample preparation, isolation, and concentration, and sometimes even derivatization of very complex matrices. Difficulties may be compounded by the fact that the components are present at very low concentrations.
Biosensors offer attractive alternatives to existing methods that can allow the creation of on line or on-site, sensitive, low-cost devices for routine use. The monitoring and control of manufacturing processes becomes possible owing to improvements in analysis speed and their application on line. Furthermore, portable biosensors can be used for monitoring products during manufacturing, distribution, and retail. The biomolecular interaction analysis (BIA) is not limited to proteins. Interactions between DNA–DNA, DNA–protein, lipid–protein, and hybrid systems of biomolecules and nonbiological surfaces can be investigated. It can be used to monitor whether two or more interactants bind to each other, how strong the interactions are or measure the actual association or dissociation rates. In addition, the binding of two interactants can be used to measure the concentration of one of the interactants using a calibration curve. MindBranch, Inc. has estimated that the market size for worldwide biosensors at year-end 2003 was about $7.3 billion. The market is projected to improve and grow to about $10.8 billion by 2007 with a growth rate of about 10.4%.1 This chapter presents a review of the potential application of biosensors in the food and drinks industry, the commercially available systems, and some upcoming technology for future developments in this sector.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
2 NEEDS OF THE FOOD AND DRINKS INDUSTRY
Biosensors are analytical devices, which use biological interactions to provide either qualitative or quantitative results. They are extensively employed in many fields such as clinical diagnostics, biomedicine, process control, fermentation control and analysis, pharmaceutical analysis as well food and drink analysis. It has been estimated that the food industry spends, on average, 1.5–2% of the value of its total sales on quality control and appraisal.2 According to a new market report of Strategic Consulting Inc. entitled Food Micro 2005, the worldwide food microbiology market in 2005 represented over 625 million tests with a market value in excess of $1.65 billion.3 Characterizations of food products include determination of food components and nutritional composition (e.g., proteins, carbohydrates, and vitamins), food additives (aspartame, benzoate, and colorants), chemical contaminants (e.g., mycotoxins, pesticides, or veterinary drug residues), and contaminants of microbiological origin. Food produce may be microbiologically contaminated at source or at any stage during processing, packaging, and distribution. Contamination of food and beverages with bacteria (e.g., Salmonella, Campylobacter), viruses (e.g., noroviruses, hepatitis A), fungi (e.g., Aspergillus spp.), and parasites (e.g., Giardia duodenalis, Cryptosporidium parvum) can cause foodborne diseases. Biosensors have a high potential for automation and allow the construction of simple and portable equipment for fast analysis. These properties will open up many new applications within quality and process control, including fermentation and quality and safety control of raw materials. Because most food is highly sensitive to critical process parameters and can easy undergo rapid and destructive changes, process control is a key point in a modern industrial environment. Rapid feedback of information could help the food or drinks manufacturer to both reduce wastage from poorly controlled processes and increase productivity. McMurdo and Whyard published a schematic diagram of feedback control in a theoretical process (Figure 1).4 The data generated through external analysis of raw materials, intermediates, and
Control
Internal control system
Inputs
Process
Outputs
Internal analysis
External analysis
Samples
Figure 1. Desired feedback control of a process. [Extended adaptation from McMurdo and Whyard.4 ]
final products can be used to plan the production more safely and more efficiently. Nowadays, many operations in the food industry are continuous processes with a high level of automation. There is thus an increasing demand for analytical technology suitable for automatic quality control through the process and at the end of the line so that the real-time state of the process can be controlled. Biosensors do not offer just rapid results, on-line biosensor technology offers food industry monitoring in real time and an option of internal process control to fulfill the demands of a high standard of quality control. However, biosensors have not been used extensively for on-line processing for several reasons. Firstly they are composed of biological material, which may be inactivated by sterilization or harsh processing conditions, like the extremes of pH and temperature, encountered in food processing. Furthermore, biosensors usually have a limited testing life owing to the stability of the biological recognition element. 3 GENERAL ASPECTS OF BIOSENSORS
A biosensor can be defined as a self-contained integrated device, which is capable of providing specific quantitative or semiquantitative analytical information incorporating a biological, biologically derived, or biomimetic sensing element either integrated within or intimately associated with an applicable transduction element.5,6 Accordingly, the basic principle of biosensor technology is to convert a biologically induced recognition event into either discrete or continuous
FOOD AND BEVERAGE APPLICATIONS OF BIOSENSOR TECHNOLOGIES
3
Analyte Enzymes, antibodies, antigens, cells, oligonucleotides, molecules
Recognition element Antibodies, antigens, receptors, oligonucleotides, microorganisms
Calorimetric biosensors
Electrochemical biosensors
Optical biosensors SPR TIR
Amperometric Potentiometric Ion-sensitive FETs
Piezoelectric biosensors
Signal processing Output using an electronic readout device
Figure 2. Key components of a biosensor showing examples of biocomponents, transducers, and signal display used in biosensor construction.
digital electronic signals that are proportional to a single analyte or a related group of analytes (Figure 2). Biosensors may be classified according to the mechanism of biological selectivity (Table 1) or, alternatively, the mode of physicochemical signal transduction (see Table 2). Biosensors offer several advantages such as small size, low cost, and selective and fast measurements even in complex environments, allowing direct applications in the field or in remote monitoring. While these advantages can be
significant, the potential disadvantages cannot be ignored. Owing to the instability of biomaterials biosensor reliability is reduced as measurements are repeated, thereby requiring frequent replacement of the sensing film. Additionally nonspecific binding to the recognition element can result in inactivation. 4 POTENTIAL APPLICATIONS
The food and drinks industry needs suitable methods for monitoring and control of key parameters
Table 1. Main biological recognition elements used for biosensors
Biological component
Advantages
Disadvantages
Biocatalytic
Enzymes Catalytic transformation Inhibition
Simple in design and operation
Sensitive to ambient conditions
Bioaffinity
Antibody–Antigen Direct assay Indirect assay
Specificity Rapid
Cross reactions Regeneration
Oligonucleotides Hybridization to species-specific sequence
High specificity Rapid
Preamplification
Whole cells Increase in or inhibition of cellular respiration
Inexpensive Measures bioavailable fraction
Long response times Short lifetime
Microorganism based
Promoter regulation resulting in a gene expression
Variance
4
BIOSENSOR APPLICATIONS
Table 2. Classification of biosensors according to the mode of the physicochemical transducers
Principle
Transducer
Detection
Example
Electrochemical
Amperometric
Detection of movement of electrons produced in a redox reaction
Potentiometric
Detection of changes in the distribution of charges causing an electrical potential to be produced Detection of change of conductivity of the medium when microorganisms metabolize uncharged substrates
Pesticides7 Phytase8 Choline9 Histamine10
Conductometric
Pesticides in water11
Thermal
Calorimetric
Detection of the heat output (or absorbed) by the reaction
Process monitoring; enzyme activity12 E. coli O157:H713
Optical
SPR
Detection of changes in the plasmon resonance as a change in the angle of the incident light or shift in the wavelength of light absorbed Detection of the change in the intensity of emitted light
β-casein in milk and cheese14 Protein in cell lysate15
Detection of effects due to the mass of the reactants or products
GMOs18 Toxic chemicals19
Chemi/bioluminescence
Acoustic
Piezoelectric
Nitrate in water16 Histamine in fish17
SPR: surface plasmon resonance; GMOs: genetically modified organisms.
not only for the characterization of the final product, but also for monitoring during the manufacturing process for process optimization and control. Additionally, the analytical monitoring should also deal with chemical and microbiological changes in food during storage and transport. Food analysis has to deal with both a wide range of analytes and within a variety of different matrices that consequently results in the use of a complex range of analytical methods. Since the pioneering work of the 1960s20,21 there has been a phenomenal growth in the field of biosensors. Table 3 shows a general survey of the great number of components to be determined. However, the difficulty of food analysis arises not only from the variety but also from the complexity of the food materials. Food products might be liquids, pastes, or solids, the last two forms being incompatible for direct analysis by most of the common existing analytical techniques. This requires the use of suitable extraction methods to bring the analyte of interest into a soluble form and secondly to remove some matrix effects which could mask the analyte or interfere with the detection method.
5 COMMERCIALLY AVAILABLE BIOSENSORS
Despite the great number of publications on biosensors applied in food analysis, only a few systems are commercially available. Key factors influencing the market are food safety requirements and legislation that may require due diligence testing. However it should be noted that quality assurance of raw materials is primarily supported by traceability systems owing to the sampling issues associated with large volume trading in bulk commodities. The application and commercialization of biosensor technology has lagged behind the output of research laboratories. Although many biosensorrelated patents are fielded each year, very few play a prominent role in the food and drinks industry. There have been many reasons for the slow technology transfer from the research laboratories to the marketplace: limited lifetime of the biological components, mass production, quality assurance, and instrumentation design. However, the important one is the lack of effective, systematic commercialization strategies.37 Studies of the market estimated that 96% of commercial biosensors are sold in the clinical
FOOD AND BEVERAGE APPLICATIONS OF BIOSENSOR TECHNOLOGIES
5
Table 3. Examples of biosensor applications in the food and beverage industry
Analyte
Function/property
Application area Process control22,23 General analysis Quality control24–26
Proteins
Indicator for quality Nutritional value Marker of nutritional damage during heat treatment Evidence of authenticity
Inorganic Sulfite
Preservatives
Quality control29
Contaminants/residues
Food safety30–32
Food spoilage
Food safety30
Organic Alcohols Carbohydrates Vitamins
Toxins Shellfish toxins Mycotoxins Pesticides Pathogens Salmonella Hepatitis A Toxic plankton
Authenticity27,28
Contamination with toxins
Pesticides Paraxon, carbaryl
Crop protection
Food safety33,34
Hormones Progesterone, clenbuterol
Growing promoters
Food safety35
Antibiotics Penicillin G, tetracyclines
Veterinary drugs
Food safety36
diagnostic sector, and only 4% are commercialized for use in the industrial biotechnology sector, in the food industrial sector, and in the environmental and wastewater sector.37 This high difference might be at least be partially explained by the type of matrix in which the tests are carried out: medical biosensors are applied mainly on serum samples with a low variation of the matrix composition. On the other hand, biosensors in the food and drinks industry must be adapted to a wide range of diverse matrices, each of them associated with particular difficulties in terms of matrix effects and concentration range of interest. After Clark and Lyon developed the glucose analyzer in 1962 on the basis of the amperometric detection of hydrogen peroxide, Yellow Springs Instruments Company put great efforts into biosensor commercialization, development, and production and entered successfully the market in 1979. This was the first of the many biosensorbased analyzers to be built by companies around the world. Since then, biosensors for determination of food components, pathogens, toxins, and
pesticides have become commercially available, even if only in limited numbers. Some examples of commercially available biosensors and a summary of their characteristics are presented in Table 4. Even though the commercially available biosensors for quantifying food components, pathogens, and toxins are in continuous development, the food and drinks industry is still not very receptive to biosensor technology. Most of the biosensors available on the market are enzyme-based, but antibody, receptor, or DNA-based sensors have also been commercialized. Bacteria can be detected by direct conductometry, which is achieved by monitoring changes in the growth medium or by indirect conductometry, which monitors changes due to evolution of CO2 produced by the metabolism of substrates in the culture medium. Direct conductometry has been used extensively to detect both pathogens and nonpathogens, like Salmonella, Campylobacter, yeasts, or fungi, in foods.50–54 Several instruments that monitor the change in electrical conductance
Biacore Q
Biacore AB
Distell
Research International Inc.
Distell Fish Fatmeter Distell Meat Fatmeter Distell Fish Freshness Meter
Analyte 2000
Spreeta
YSI 2700 SELECT
YSI Inc.
Texas Instruments Inc.
Instrument
Manufacturer
Hand-portable equipment Real time
Water Water Appropriate dielectric properties
Real time One sample per second
Hand-portable equipment Real time
Real-time, automatic analysis of batches up to 40 samples Optimized, ready-to-use Qflex kits
Real-time analysis of batches of up to 24 samples or on-line monitoring possible 1 min analysis time
Comments
E. coli O157:H7
Ingredients Contaminations
Biotin Vitamin B2 and B12 Pantothenic acid Veterinary drug residues Antibiotics Growth promoters
Folic acid
(Dextrose) Sucrose Lactose L-Lactate L-Glutamate Ethanol Starch
Glucose
Target compounds
Table 4. Examples of commercially available biosensors for use in the food and beverage industry
Fish
Fish Meat
Hamburger
Water Beverages
Milk powder Infant food Multivitamin Meat Honey Milk
Cereals
Potatoes Cereals
Molasses
Food sample
42
41
40
39
38
References
6 BIOSENSOR APPLICATIONS
ABD 3000
Universal Sensors Inc.
RABIT
OptiSense Optical biosensor
Don Whitley Scientific Ltd.
OptiSense BV
RABIT: rapid automated bacterial impedance technique.
Malthus Systems
Malthus Instruments Ltd.
BioFlash system
SIRE
Chemel AB
Innovative Biosensors Inc.
OLGA
Sensolytics GmbH
Antibiotics Mycotoxins
Food pathogens
E. coli O157:H7 Fungi Yeasts
E. coli O157:H7
Alcohols sugars Amino acids
Glucose Sucrose L-Lactate Methanol Ethanol H2 O2 Ascorbic acid
Glucose Lactate Sucrose Ethanol Glutamate Glutamine
Highly sensitive real-time test
Dairy industry
Vegetables
Shellfish Evaluation of antifungal activity
Conductometric assay using whole cells Conductometric assay using whole cells
Lettuce
Food Beverage
Soft drinks Beer Fermentation broths Yogurt
Beer
Extremely rapid detection of pathogens at previously unseen levels of sensitivity and specificity
Specific, fast, and inexpensive biosensor assay
Fast, easy, and accurate biochemical analyses
On-line automated sterile filtration process monitoring and control
49
48
47
46
45
44
43
FOOD AND BEVERAGE APPLICATIONS OF BIOSENSOR TECHNOLOGIES 7
8
BIOSENSOR APPLICATIONS
of the media caused by the growth of microorganisms have been exploited by Malthus Instruments Ltd. or in RABIT by Don Whitley Scientific Ltd. The SPR principle allows real-time detection of the specific interaction between an immobilized biorecognition element and a variety of analytes. Companies like Biacore AB or Texas Instruments Inc. have exploited SPR technology.55,56 Biosensors are available in several forms, such as autoanalyzers, manual laboratory instruments, and portable devices. 6 UPCOMING TECHNIQUES, FUTURE DEVELOPMENTS IN BIOSENSOR TECHNOLOGY AND MARKETPLACE
Some promising developments in the biosensor field are listed in Table 5. These recent developments have already entered the market or will be available soon. The most promising breakthroughs are to be expected in the area of sensor technology, that will allow the creation of on-line or on-site, sensitive, low-cost devices for routine use. Biosensors have a high potential for automation and allow the construction of simple and portable equipment for fast analysis. These properties will open up many new applications within quality and process control, including fermentation and quality and safety control of raw materials. The new application possibilities offered should be further explored and technologically evaluated. Biosensor advancement in the commercial world could be accelerated by the use of intelligent instrumentation, electronics, and multivariate signal-processing methods. A biosensor array strategy, adaptable to multiple analytes detection, will allow the spread of development costs
over several products. These future improvements will produce devices more competitive than the presently available instruments. 7 CONCLUSIONS
This chapter summarizes ongoing efforts, trends, and developments in the field of biosensors for food analysis. Food has an important role in promoting and invigorating health and quality of life. To meet consumer requirements and provide healthy and high-quality food, the production- and processingdistribution chain has to be carefully monitored. Moreover, tracing possible sources of contaminants throughout the food chain and quantifying risk factors is also critical. There is a great need for rapid and affordable methods to assure quality of products and process control in the food and beverage sector. The application of the biosensor techniques in the field of food processing and quality control offers advantages as alternatives to conventional methods due to speed, cost efficiency, high sensitivity, and specificity of measurements. Biosensors are a tool for determining and measuring a wide range of target analytes, occurring in a variety of food matrices, and within a diversity of process conditions. Biosensors will complement or replace existing conventional analytical methods. However, as with most technologies, there is still room for improvement. The stability of the recognition element can be improved by using new immobilization technologies and developing novel protein stabilization, engineering, and automated manufacturing technologies, as well as by using more robust biological or nonbiological materials, like molecular imprinted polymers (MIPs).63 But for a
Table 5. Examples for upcoming biosensors in the near future
Company
Development
Aim
AKUBIO Ltd.
RAPid 4
Axela Biosensors, Inc.
DOT sensor and DOT reader Phage Biosensor UTS technology
Resonant Acoustic Profiling (RAP ) technology for molecule interactions in complex matrices like serum or growth media Applications are potentially in agriculture, environmental, and food and beverage QC E. coli O157:H7, Campylobacter, Salmonella in water Aqueous-based samples
Biophage Pharma Inc. Universal Sensors, Ltd. Sensortec, Ltd. Stratophase, Ltd.
Refractive index sensor chips
Liquid samples
References 57 58 59 60 61 62
FOOD AND BEVERAGE APPLICATIONS OF BIOSENSOR TECHNOLOGIES
direct competition with established analytical procedures, biosensors must be designed to measure several different analytes in parallel using a single analyzer without having to change any component of the sensor system.2 Furthermore, the clearly defined and wellfinanced needs in medicine have driven some of the most successful biosensor developments to date, such as home blood glucose monitors. The food and beverage industry, however, has been characterized by low profit margins and a somewhat conservative approach to new technology. Public concern for food safety and increased demands for food labeling is likely to provide more impetus for innovative approaches to food analysis in the future.64 The promise shown by biosensor technology is real, but there are still technological problems to be solved. Additionally, the market penetration has to be improved for areas where biosensor technologies are ideal for upgrading food diagnostics. These potential opportunities include better quality control, on-line monitoring of processes and their control as well as seminal markets of authenticity and traceability of raw materials, intermediates, and food products. In conclusion, as concerns regarding safe food and water supply increase, the demand for rapid detecting biosensors will only increase. REFERENCES 1. U.S. & Worldwide Biosensor Market, R&D and Commercial Implication, Fuji-Keizai USA, Incorporated, Pub ID: FJ9744212004, 2004. 2. J. H. T. Luong, P. Bouvrette, and K. B. Male, Developments and applications of biosensors in food analysis. Trends in Biotechnology, 1997, 15, 369–377. 3. Food Micro-2005, Strategic Consulting Incorporated, 2005. 4. I. H. McMurdo and S. Whyard, Suitability of rapid microbiological methods for the hygienic management of spray drier plant. Journal of the Society of Dairy Technology, 1984, 37, 4–9. 5. D. R. Thevenot, K. Toth, R. A. Durst, and G. S. Wilson, Electrochemical biosensors: recommended definitions and classification. Biosensors and Bioelectronics, 2001, 16, 121–131. 6. S. White, Biosensors for Food Analysis, in Handbook of Food Analysis, L. M. L. Nollet (ed), Marcel Dekker, Inc., New York, 2004, pp. 2133–2148. 7. M. Waibel, H. Schulze, N. Huber, and T. T. Bachmann, Screen-printed bienzymatic sensor based on sol-gel immobilized Nippostrongylus brasiliensis
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
9
acetylcholinesterase and a cytochrome P450 BM-3 (CYP102-A1) mutant. Biosensors and Bioelectronics, 2006, 21, 1132–1140. W. C. Mak, Y. M. Ng, C. Chan, W. K. Kwong, and R. Renneberg, Novel biosensors for quantitative phytic acid and phytase measurement. Biosensors and Bioelectronics, 2004, 19, 1029–1035. S. Pati, M. Quinto, F. Palmisano, and P. G. Zambonin, Determination of choline in milk, milk powder, and soy lecithin hydrolysates by flow injection analysis and amperometric detection with a choline oxidase based biosensor. Journal of Agricultural and Food Chemistry, 2004, 52, 4638–4642. K. M. May, Y. Wang, L. G. Bachas, and K. W. Anderson, Development of a whole-cell-based biosensor for detecting histamine as a model toxin. Analytical Chemistry, 2004, 76, 4156–4161. S. Suwansa-Ard, P. Kanatharana, P. Asawatreratanakul, C. Limsakul, B. Wongkittisuksa, and P. Thavarungkul, Semi disposable reactor biosensors for detecting carbamate pesticides in water. Biosensors and Bioelectronics, 2005, 21, 445–454. K. Ramanathan and B. Danielsson, Principles and applications of thermal biosensors. Biosensors and Bioelectronics, 2001, 16, 417–423. S. M. Radke and E. C. Alocilja, A high density microelectrode array biosensor for detection of E. coli O157:H7. Biosensors and Bioelectronics, 2005, 20, 1662–1667. S. Muller-Renaud, D. Dupont, and P. Dulieu, Quantification of beta casein in milk and cheese using an optical immunosensor. Journal of Agricultural and Food Chemistry, 2004, 52, 659–664. M. Kyo, K. Usui-Aoki, and H. Koga, Label-free detection of proteins in crude cell lysate with antibody arrays by a surface plasmon resonance imaging technique. Analytical Chemistry, 2005, 77, 7115–7121. A. G. Prest, M. K. Winson, J. R. Hammond, and G. S. Stewart, The construction and application of a lux-based nitrate biosensor. Letters in Applied Microbiology, 1997, 24, 355–360. Y. Sekiguchi, A. Nishikawa, H. Makita, A. Yamamura, K. Matsumoto, and N. Kiba, Flow-through chemiluminescence sensor using immobilized histamine oxidase from Arthrobacter crystallopoietes KAIT-B-007 and peroxidase for selective determination of histamine. Analytical Sciences, 2001, 17, 1161–1164. I. Mannelli, M. Minunni, S. Tombelli, and M. Mascini, Quartz crystal microbalance (QCM) affinity biosensor for genetically modified organisms (GMOs) detection. Biosensors and Bioelectronics, 2003, 18, 129–140. J. H. Sung, H. J. Ko, and T. H. Park, Piezoelectric biosensor using olfactory receptor protein expressed in Escherichia coli. Biosensors and Bioelectronics, 2006, 21, 1981–1986. L. Clark and C. Lyons, Electrode systems for continuous monitoring in cardiovascular surgery. Annals of the New York Academy of Sciences, 1962, 102, 29–35. S. Updike and G. Hicks, Enzyme electrode. Nature, 1967, 214, 986.
10
BIOSENSOR APPLICATIONS
22. M. Boujita, M. Chapleau, and N. El Murr, Biosensors for analysis of ethanol in food: effect of the pasting liquid. Analytica Chimica Acta, 1996, 319, 91–96. 23. A. G.-V. De Prada, N. Pena, M. L. Mena, A. J. Reviejo, and J. M. Pingarron, Graphite-teflon composite bienzyme amperometric biosensors for monitoring of alcohols. Biosensors and Bioelectronics, 2003, 18, 1279–1288. 24. H. E. Indyk, E. A. Evans, M. C. Bostrom Caselunghe, B. S. Persson, P. M. Finglas, D. C. Woollard, and E. L. Filonzi, Determination of biotin and folate in infant formula and milk by optical biosensor-based immunoassay. Journal of AOAC International, 2000, 83, 1141–1148. 25. H. E. Indyk, B. S. Persson, M. C. Caselunghe, A. Moberg, E. L. Filonzi, and D. C. Woollard, Determination of vitamin B12 in milk products and selected foods by optical biosensor protein-binding assay: method comparison. Journal of AOAC International, 2002, 85, 72–81. 26. D. Dupont, O. Rolet-Repecaud, and S. Muller-Renaud, Determination of the heat treatment undergone by milk by following the denaturation of alpha-lactalbumin with a biosensor. Journal of Agricultural and Food Chemistry, 2004, 52, 677–681. 27. W. Haasnoot, K. Olieman, G. Cazemier, and R. Verheijen, Direct biosensor immunoassays for the detection of nonmilk proteins in milk powder. Journal of Agricultural and Food Chemistry, 2001, 49, 5201–5206. 28. W. Haasnoot, N. G. Smits, A. E. Kemmers-Voncken, and M. G. Bremer, Fast biosensor immunoassays for the detection of cows’ milk in the milk of ewes and goats. Journal of Dairy Research, 2004, 71, 322–329. 29. D. Corbo and M. Bertotti, Use of a copper electrode in alkaline medium as an amperometric sensor for sulphite in a flow-through configuration. Analytical and Bioanalytical Chemistry, 2002, 374, 416–420. 30. A. X. J. Tang, M. Pravda, G. G. Guilbault, S. Piletsky, and A. P. F. Turner, Immunosensor for okadaic acid using quartz crystal microbalance. Analytica Chimica Acta, 2002, 471, 33–40. 31. J. S. Yoo, B. S. Cheun, I. S. Park, Y. C. Song, Y. Seo, N. G. Kim, H. W. Shin, and J. H. Lee, Use of sodium transfer tissue biosensor (STTB) for monitoring of marine toxic organism. Journal of Environmental Biology, 2004, 25, 431–436. 32. L. Pogacnik and M. Franko, Detection of organophosphate and carbamate pesticides in vegetable samples by a photothermal biosensor. Biosensors and Bioelectronics, 2003, 18, 1–9. 33. H. Schulze, E. Scherbaum, M. Anastassiades, S. Vorlova, R. D. Schmid, and T. T. Bachmann, Development, validation, and application of an acetylcholine-esterasebiosensor test for the direct detection of insecticide residues in infant food. Biosensors and Bioelectronics, 2002, 17, 1095–1105. 34. Y. Zhang, S. B. Muench, H. Schulze, R. Perz, B. Yang, R. D. Schmid, and T. T. Bachmann, Disposable biosensor test for organophosphate and carbamate insecticides in milk. Journal of Agricultural and Food Chemistry, 2005, 53, 5110–5115. 35. M. A. Johansson and K. E. Hellenas, Sensor chip preparation and assay construction for immunobiosensor
36.
37.
38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50.
51.
52.
53.
54.
55.
56.
57. 58. 59. 60. 61. 62.
determination of beta-agonists and hormones. The Analyst, 2001, 126, 1721–1727. E. Gustavsson, J. Degelaen, P. Bjurling, and A. Sternesjo, Determination of beta-lactams in milk using a surface plasmon resonance-based biosensor. Journal of Agricultural and Food Chemistry, 2004, 52, 2791–2796. C.-T. Lin and S.-M. Wang, Biosensor commercialization strategy—a theoretical approach. Frontiers in Bioscience, 2005, 10, 99–106. http://www.ysi.com (2007). http://www.biacore.com (2007). http:// www.spreeta.com (2007). http://www.resrchintl.com (2007). http://www.distell.com (2007). http://www.sensolytics.com (2007). http://www.chemel.com (2007). http://chemweb.ucc.ie/ (2007). http://www.innovativebiosensors.com (2007). http://www.labm.com (2007). http://www.dwscientific.co.uk (2007). http://www.optisense.nl/ (2007). F. J. Bolton, Conductance and Impedance Methods for Detecting Pathogens, in International Congress on Rapid Methods and Automation in Microbiology and Immunology, A. Vaheri, R. C. Tilton, and A. Barlows (eds), 1991, Springer-Verlag, pp. 176–181. J. Dupont, F. Dumont, C. Menanteau, and M. Pommepuy, Calibration of the impedance method for rapid quantitative estimation of Escherichia coli in live marine bivalve molluscs. Journal of Applied Microbiology, 2004, 96, 894–902. J. Sawai and T. Yoshikawa, Quantitative evaluation of antifungal activity of metallic oxide powders (MgO, CaO and ZnO) by an indirect conductimetric assay. Journal of Applied Microbiology, 2004, 96, 803–809. J. Sawai and T. Yoshikawa, Measurement of fungi by an indirect conductimetric assay. Letters in Applied Microbiology, 2003, 37, 40–44. J. E. Line and K. G. Pearson, Development of a selective broth medium for the detection of injured Campylobacter jejuni by capacitance monitoring. Journal of Food Protection, 2003, 66, 1752–1755. A. N. Naimushin, S. D. Soelberg, D. K. Nguyen, L. Dunlap, D. Bartholomew, J. Elkind, J. Melendez, and C. E. Furlong, Detection of Staphylococcus aureus enterotoxin B at femtomolar levels with a miniature integrated twochannel surface plasmon resonance (SPR) sensor. Biosensors and Bioelectronics, 2002, 17, 573–584. S. D. Soelberg, T. Chinowsky, G. Geiss, C. B. Spinelli, R. Stevens, S. Near, P. Kauffman, S. Yee, and C. E. Furlong, A portable surface plasmon resonance sensor system for real-time monitoring of small to large analytes. Journal of Industrial Microbiology and Biotechnology, 2005, 32, 669–674. http://www.akubio.com/ (2007). http://www.axelabiosensors.com (2007). http://www.biophage.com (2007). http://www.universalsensors.co.uk (2007). http://www.sensortec.uk.com (2007). http://www.stratophase.com (2007).
FOOD AND BEVERAGE APPLICATIONS OF BIOSENSOR TECHNOLOGIES 63. S. A. Piletsky, S. Alcock, and A. P. Turner, Molecular imprinting: at the edge of the third millennium. Trends in Biotechnology, 2001, 19, 9–12.
11
64. L. A. Terry, G. Volpe, G. Palleschi, and A. P. F. Turner, Biosensors for the microbiological analysis of food. Food Science and Technology, 2004, 18, 22–24.
79 Agriculture, Horticulture, and Related Applications Leon A. Terry Plant Science Laboratory, Cranfield University, Silsoe, UK
1 INTRODUCTION
The application of biosensor technology is still fundamentally dominated by the blood glucose market. Transfer to the food sector has been slow and still represents a very small proportion of current sales. However, with the increasing trend from yield-driven to quality-driven provision of agricultural products, the concurrent demand for reliable and inexpensive methods for assessment of food quality, safety, traceability, and authenticity is set to expand; biosensors have the potential to fulfill this niche.1 Traditionally, agriculture and the food industry, in general, have taken a particularly conservative approach to the introduction of biosensors. Fundamentally, continued price deflation within the agricultural sector has discouraged investment despite rapid growth in food testing over recent years. Secondly, the problems posed by ensuring representative sampling and sample interference on sensor performance have often been overlooked during the development stage for sensors. This oversight or lack of recognition of the complexity of many foodstuffs has invariably inhibited the widespread introduction of biosensors within the agricultural sector. However, it is not necessarily the inherent specificity, selectivity, and adaptability of biosensors which make them ideal candidates for use throughout the food industry, but their relative
low cost and ease of use, as compared with more conventional testing methodologies (e.g., HPLC, GC/MS), that really make them an attractive alternative quality assurance tool.
2 RECENT ADVANCES IN BIOSENSOR DEVELOPMENT FOR FOODSTUFF QUALITY ASSURANCE
A number of biosensor-based devices have been developed for agriculture and horticulture to quantify the concentration/presence of particular target analytes that may be indicators of food quality/acceptability or assist in selection (Tables 1 and 2). These devices have principally either relied on immunosensors or electrochemical biosensors.
2.1
Monitoring Livestock Condition
Reproductive management is a major financial concern of the livestock industry. For instance, predicting estrus onset in cattle, where artificial techniques are employed, can lead to considerable cost saving in herd management.26 Despite visual observations still being used to detect estrus, it is recognized that considerable inaccuracies in predicting this time window are common since estrus does not always coincide with ovulation
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Table 1. Examples of the range of analytes monitored in food matrices other than fresh produce by amperometric biosensors
Analyte
Food matrix
Essential fatty acids
Fats and oils
Lysine Glucose and maltose
Range of foods Beer
Glucose and glutamate
Beverages
Rancidification indicators Lactate D- and L-amino acids
Olive oils Wine and yogurt —
Choline Organophosphorous pesticide Insecticide residues Laminarin
Dairy produce Range of foods Infant food Seaweed
Alcohol
Beer and wine
Enzyme Lipoxygenase, lipase, and esterase Lysine oxidase Glucose oxidase and amyloglucosidase Glucose oxidase and glutamate oxidase Tyrosinase Lactate oxidase Amino acid oxidase Choline oxidase Acetylcholinesterase Acetylcholinesterase β1,3-Glucanase and glucose oxidase Alcohol oxidase and horseradish peroxidase
Detection limit
References
0.04 mM in an FIA system
2
1 × 10−5 mol l−1 40 mM to glucose (only upper limit stated) 10 µM for glucose and 3 µM for glutamate 0.2–2.0 µM in different oils 1.4 × 10−6 mol l−1 0.1 or 0.2 mM for L- and D-amino acids 5 µmol l−1 0.2–1.8 ppm 5 µg Kg−1 50 µg ml−1
3 4
9 10 11 12
5.3 × 10−6 mol l−1
13
5 6 7 8
Adapted from Terry et al. 2005.
Table 2. Examples of the range of analytes monitored in fresh produce matrices by amperometric biosensors
Analyte
Food matrix
Fructose Amines L-ascorbic
Citrus fruits Apricots and cherries acid
Sucrose
Malic acid Polyphenols β-D-glucose; total D-glucose; sucrose; L-ascorbic acid
Cysteine sulfoxides Pyruvic acid
Fruit juices Fruit juices
Apples, Potatoes, and tomatoes Vegetables Tropical fruits (mango, pineapple, papaw)
Alliums (e.g., onion and garlic) Onion
Enzyme
Detection limit
References
10 µM 2 × 10−6 mol l−1
14 15
5.0 × 10−5 M 9.25 g l−1 in pineapple juice
16 17
0.028 mM
18
Horseradish peroxidase Glucose oxidase; glucose oxidase, mutarotase; invertase, mutarotase, and glucose oxidase; ascorbate oxidase Allinase
1 µmol l−1 7 mM
19 20,21
Pyruvate oxidase
2 µmol g−1
Fructose dehydrogenase Diamine oxidase and polyamine oxidase Ascorbate oxidase Sucrose phosphorylase, phosphoglutaminase, glucose-6-phosphate 1-dehydrogenase Malate dehydrogenase
5.9 × 10−6 M
22 23–25
Adapted from Terry et al. 2005.
and can even occur in pregnant animals. As an alternative, sensors have been developed to detect bovine progesterone during milking.27,28 Both approaches adopted a liquid handling system linked to a suitable immunoassay sensor. The approach adopted by Pemberton et al.28 which relied upon a reduction in the binding to the sensor surface of alkaline phosphate–labeled
progesterone in the presence of endogenous milk progesterone, was further improved by Mottram et al.29 who demonstrated that an automated ovulation system was capable of detecting concentrations of progesterone between 3 and 30 ng ml−1 in whole fresh milk. Similarly, flow injection analysis (FIA) coupled to an electrochemicalbased immunosensor system has been developed
AGRICULTURE, HORTICULTURE, AND RELATED APPLICATIONS
for the detection of gentamicin in milk.30 Again the aim was to develop a field-based system that could be operated at-site. The system was able to distinguish between 100 µg kg−1 gentamicin in milk in <10 min with no sample pretreatment required. In addition to the use of antibody-based immunosensors, receptor-based devices have also been described. Setford et al.31 employed an amperometric affinity sensor for the rapid quantification of β-lactam in milk. Biorecognition was achieved using an immobilized β-lactam antibiotic specific receptor binding protein to measure penicillin G levels in milk. This device was designed to be a one-shot disposable sensor, based on screenprinted sensors, making it an ideal field-based screening tool. Similarly, an enzyme immunoassay for β-lactam penicillins was reported by Delwiche et al.32 but rather than using an ELISA affinity assay couple to amperometric determination of bound enzyme label activity,31 the system used involved a photometric sensor as the transducer.
2.2
Improving Fresh Produce Quality Control
The fresh produce industry illustrates many of the problems encountered across the whole food industry in terms of still generally employing archaic quality control (QC) methodologies. For example, fresh produce quality in the intact or minimally processed/fresh-cut form is initially assessed by sight: other important quality attributes include taste, smell, and texture. Each of these four quality attributes can be assessed either subjectively or objectively. Typically, fruit processors reject approximately 10% of fruit intakes. Better selection through improved quantitative QC at low cost will inevitably result in improved overall quality for intact and minimally processed fruit products. Improved QC will probably, in the short-term, lead to increased rejections and reduce the number of “concessions” for fruit processors. A “concession” is where fruit material can be used but is expected to incur a cost penalty due to greater QC costs. Improved QC may result in approximately 25% saving on concessions for fruit processors. In reality, current standard product-orientated QC operations are inadequate, and consider only appearance (e.g., colour, size, and shape), presence/absence of disease, and the concentration
3
of total soluble solids (TSS). TSS is commonly expressed as degrees Brix (◦ Bx) and is typically still measured using a hand-held refractometer. There is often poor correlation between TSS and total sugar concentration.33 Fruit sugars are one of the main soluble components in fresh produce that are important for flavor. In addition to sugar composition, fruit acid concentration can affect flavor directly and can regulate cellular pH, influencing the appearance of fruit pigments within the tissue during processing. The total titratable acidity (TTA) of fruit is not routinely measured as part of the standard QC procedures that are implemented by growers, suppliers, fresh produce distribution centres, and fruit processors. Titratable acidity is a measure of the buffering capacity of the fruit and is generally expressed as a percent of the predominant organic acid. Current standard QC operations do not use TTA because of the cumbersome and time-consuming nature of titrations. Fruit sugar/acid ratios can be used as an important index of consumer acceptability and act as one determinant of overall fruit quality. However, sugar/acid ratios are not frequently assessed for all fruit types due to primitive QC instrumentation and the requirement for skilled analytical scientists. An initial step to improving routine QC assessment would constitute producing a simple and low-cost alternative to refractometry and titrations so that specific sugar and organic acid ratios can be standardized for fresh produce types. Biosensors may offer the opportunity to fulfill this niche and allow industry to adjudge fruit quality on the basis of taste (sugar/acid ratios) rather than just appearance alone. Introducing biosensor technology within the fresh produce industry (Table 2) may provide the ideal solution to providing improved QC, safety, and traceability methodologies.20,25 It follows that biosensor applications could be extended across the whole food industry, for example, meat, dairy foods, and beverages (Table 1).
3 ADVANTAGES OF BIOSENSORS FOR FOOD ANALYSIS
Unquestionably, biosensors have made their greatest impact in the field of medical diagnostics. The use of screen-printed electrochemical biosensors
4
BIOSENSOR APPLICATIONS
Table 3. Examples showing the use of biosensors to detect the presence of contaminating microorganisms in food
Target organism
Food matrix
Detection method
Detection limit
References −1
Acoustic Optical
3 × 10 − 6.2 × 10 ml 10–100 ng g−1
34 35
Salmonella typhimurium Staphylococcal enterotoxin B Salmonella group B, D and E E. coli
Dairy products Hot dogs, potato salad, milk, and mushrooms Chicken carcass wash fluid Milk Range of foods Range of foods
Optical Optical Optical QCM (acoustic)
36 37 38 39
E. coli O157:H7
Range of foods
Optical
1 × 105 − 1 × 107 ml−1 0.5 ng ml−1 1 × 107 CFU ml−1 1.7 × 105 − 8.7 × 107 CFU ml−1 1 × 103 CFU ml−1
Escherichia coli Staphylococcal enterotoxin A
5
7
40
by diabetics to regularly monitor their blood glucose levels has provided sufferers with a powerful method for controlling this pernicious condition. Using modern printing methods, these devices are manufactured on a scale of millions per month and sold globally. The accuracy, comparative low cost, and ease of use of biosensors have led to their widespread application. Adapting this technology for use not only for fresh produce (Table 2) but also in the wider food industry could lead to immense improvements in QC, food safety (cf. Table 3), and traceability. Abayomi et al.25 demonstrated that pungency in bulb cvs. Renate and SupaSweet (SS1) onions (as measured by pyruvate concentration in macerated tissue) could be determined 20-fold more rapidly using a mediated biosensor format in comparison with the standard colorimetric assay used by the industry41 (Figures 1 and 2) with no loss in resolution. Moreover, biosensors have been developed for determination of concentration of metabolites such as glucose, sucrose, lactate, alcohol, glutamate, and ascorbic acid, typically found in many food items (Figure 3)42 and for rapidly detecting the presence of contaminating agents such as microorganisms, pesticide residues,43 and antibiotics.44,45 Biosensor systems can be operated either as simple “one-shot” measurement tools or, when incorporated into a suitable fluid handling system, as multimeasurement devices. Both approaches can also be adapted to measure several different analytes, using the same sample solution. This versatility, coupled with a high degree of sensitivity and selectivity has prompted worldwide interest in both the fundamental research and commercial exploitation of biosensor technology. Biosensor systems can be designed such that they can be operated
Biosensor response (µC)
QCM: quartz crystal microbalance.
60 50 40 30 20 10 0
0
1
2 3 Pyruvate (µmol g–1 fresh weight)
4
Figure 1. Mediated biosensor response to onion juices from six individual low pungency bulbs of increasing pyruvate concentration verified against conventional colorimetric analysis.39 R 2 = 0.83; y = 14x − 9; P < 0.001. Standard error bars are from the mean of three experiments. +200 mV; phosphate buffer pH 5.7; cofactor mix B. [Reprinted with permission Abayomi et al.25 copyright 2006, Elsevier.]
at-site on a real-time basis, removing the reliance on expensive centralized laboratory-based testing. Moreover, the process of miniaturization can be adapted to biosensors. Hence, an array of sensors can be integrated into a small portable device for multiple parameter determination for use by nonspecialized persons with a minimum of manual manipulation. This is one of the major advantages of using biosensors, as measurements can be made either during raw material preparation, food processing (e.g., as QC devices) or for checking the reliability of storage conditions. Hence, these devices can act as cost-effective tools for QC, process control, and the determination of food safety.
AGRICULTURE, HORTICULTURE, AND RELATED APPLICATIONS
4 BIOSENSOR OPTIMIZATION FOR FOOD ANALYSIS
Biosensor response (µC)
160 140 120 100 80 60 40 20 0
0
2
4 6 8 10 12 Pyruvate (µmol g–1 fresh weight)
Figure 2. Mediated biosensor response to onion juices from two individual mild (cv. SS1) and three pungent (cv. Renate) bulbs of increasing pyruvate concentration verified against conventional colorimetric analysis.39 R 2 = 0.97; y = 15x − 27; P = 0.001. Standard error bars are from the mean of three experiments. +200 mV; phosphate buffer pH 5.7; cofactor mix B. [Reprinted with permission Abayomi et al.25 copyright 2006, Elsevier.]
0.3 Scaled principal component 1
5
Late mature Early ripe Ripe
0.2 0.1 0 –0.1 –0.2 –0.3 0.48
0.50
0.52
0.54
0.56
0.58
0.60
Scaled principal component 2
Figure 3. Chemometric (principle component analysis) output from biosensor array to score pineapple cv. Queen Victoria fruit ripeness. PCA scores plot for the scaled data matrix. PC1 and PC2 represent the first and second principal components respectively. [Reprinted with permission Jawaheer et al.20,21 copyright 2002, 2003, Elsevier.]
Most biosensor research for the food industry has been done using enzyme-based amperometric electrochemical biosensors. However, to obtain functional biosensor devices, which can be manufactured within the necessary performance and cost constraints, other components and technologies must also be considered.
Almost all biosensors rely on membranes for improved functionality. Membranes can play different roles in the sensor format and are typically used to retain the biological component, while allowing the analyte to pass; one of the key features of a biosensor is the proximity of the biological recognition element to the transducer. Usually this is achieved using an immobilization process. Another useful function of membranes is their ability to extend the linear range of a biosensor by acting as a mass transport barrier. A limiting factor for a linear response from an enzyme-based biosensor may be the Km of the catalyst. By imposing an analyte diffusion barrier (i.e., a membrane) over the enzyme a pseudo Km may be produced, extending the linear range of the sensor. Membranes can provide a protective barrier for the sensor system, preventing fouling of the sensor by components in the sample matrix and, conversely contamination of the sample solution by the sensor. Membranes can also act to provide stability for the sensor, both for long-term storage and the operational capability of the sensor. By the use of a suitable membrane a high degree of selectivity can be achieved, either by allowing only the target analyte to reach the sensor surface or by eliminating other interfering compounds that may affect the sensor signal. Numerous materials have been used as membrane materials for biosensors including, cellulose acetate (CA), PVC, and Nafion (a polyfluorosulfonated hydrocarbon). Jawaheer et al.20,21 demonstrated that interferences related to electrochemically active compounds present in tropical fruits could be significantly reduced by inclusion of a suitable CA membrane on a rhodinized carbon electrode. CA membranes improved the linear range of biosensors for β-D-glucose, total D-glucose, sucrose, and L-ascorbic acid by as much as 5-fold compared with sensors without an additional diffusion barrier. Immobilization of the recognition element on or close to the transducer is a major factor in biosensor design and fabrication. Adopting this approach allows an efficient transfer of signal from the biological element to the transducer and hence to the biosensor user. In addition, with an immobilized biological element, the opportunities for reusing of the biosensor are greatly enhanced. The
6
BIOSENSOR APPLICATIONS
main methods of immobilization, particularly for enzymes, include physical adsorption, entrapment in a matrix (using gels, polymers, or printing inks), covalent binding, or electrochemical polymerization and photopolymerization. Physical adsorption is generally based on interactions such as van der Waals forces between the biological element and the transducer (e.g., a carbon electrode surface). Jawaheer et al.21 demonstrated that pectin, a natural polysaccharide present in plant cell walls, could be used as a novel matrix to enhance enzyme entrapment on rhodinized carbon electrodes. Pectin also assisted in prolonging enzyme storage stability rather than improving operation performance and could be applied as a viscous paste of screen-printable consistency. It has long been realised that advanced fabrication techniques are key to the successful development of commercially viable biosensors. Fortunately, many technologies have been developed for other applications, such as the microelectronics industry, that can be adapted to biosensor fabrication. Screen-printing is a thick-film process, which has been used for many years in artistic applications and, more recently, for the production of miniature, robust, and cheap electronic circuits. This technique has been successfully exploited by electrochemical biosensor manufactures. The process has been one of the major reasons for the commercial success of many biosensors and is the process by which a number of medical diagnostic companies annually produce more than 1 billion (electrochemical) biosensor strips for home blood glucose monitoring. It follows, therefore, that the inexpensive nature of biosensor fabrication lends itself to an increasingly price-competitive industry, such as the fresh produce sector. Given this fact, it is perhaps surprising that biosensor fabrication techniques have not been transferred to the measurement of important target analytes in the food industry. The ability to handle small volumes of liquids with high precision will be one of the key areas of development for some of the next generation of biosensors. In particular, where high-value reagents, such as particular enzymes or antibodies, are needed, screen-printing may not (because of cost implications) be the most appropriate method of production. For example, fructose, which normally increases during physiological fruit ripening,
is a potentially desirable target for fresh produce biosensor development since it has been positively correlated to perceived sweetness.46 However, the commercial availability of the fructose enzyme, fructose dehydrogenase, is relatively expensive and unstable and, therefore, not economically viable at present unless significant research is forthcoming. In addition, the same economic barrier exists for malate, which is the principle organic acid found in pome fruit (e.g., apples and pears) and an important parameter characterizing wine quality (e.g., malolactic fermentation). Malic acid measurement can be cost prohibitive when using either the malic acid enzyme (L-malate: NADP+ oxidoreductase) associated with NADP+ and pyruvate oxidase47 or malate dehydrogenase and diaphorase immobilized on gold electrodes using glutaraldehyde.48 Other printing methods can be used to overcome high-price enzyme usage, including ink-jet printing and other automated dispensing deposition systems. The deposition of biological agents, such as enzymes, can be carried out accurately and reproducibly using these print methods, which are suitable for depositing droplets of <1 nl in volume. Furthermore, non-contact technology, such as ink-jet printing, allows fluid to be placed on almost any surface, irrespective of texture and shape. In addition to the variety of biosensor devices available, there are a number of methods that can be adapted to facilitate sampling. By their very nature, many food items are complex mixtures of many compounds; this can present a significant challenge to the efficient operation of a biosensor. Hence, whenever biosensor technologists design sensors for applications in the food industry, careful consideration must be given to sampling. For solid or semi-solid foods this, usually, involves an extraction process, possibly followed by a simple preparation step such as filtration. Broadly, the main sampling methods that are used with biosensors can be categorized in several ways. At-site sampling involves taking a sample from the matrix and carrying out an extraction process followed by measurement by the biosensor. This approach to sampling can be detrimental in terms of efficiency. Manually removing and pretreating a sample prior to measurement may require some limited degree of technical skill. However, careful design of the sensor system should reduce this complexity to a level at which
AGRICULTURE, HORTICULTURE, AND RELATED APPLICATIONS
the procedure can be carried out rapidly and easily. At-site sampling is, probably, more suited to liquids (e.g., beer, wine, and fruit juices) where (generally) the target analyte of interest is more readily available. Similarly, sampling from fresh produce is usually not as challenging as for other more heterogeneous foodstuffs as many of the potential target analytes are in solution when tissue is disrupted/decompartmentalized and, thus, available for measurement in extracted fruit juice.21,25 This said, significant variation in the spatial and temporal distribution of target analytes does exist in all fresh produce; a fact that reconfirms that sampling procedures must be optimized. In situ sensors are placed directly in the matrix containing the target analyte. The use of in situ sensors has long been established in the bioprocess industry, where “dip in” devices are used to monitor a number of parameters such as pH and dissolved gas concentrations. A number of advantages are gained by operating sensors in this fashion including, real-time monitoring and a continuous output signal from the sensors (any rapid change in the analyte concentration can be readily observed). In addition, labour requirements are significantly reduced. This approach would be most applicable in the food processing field, where the careful (automatic) sampling and measurement of processed food (e.g., processes that incorporate a fermentation or distillation step) would be very useful. However, given the complex nature of many foods, in situ sampling and monitoring can be very difficult. Components in the food matrix can adhere to and foul the sensor surface, leading to erroneous signals. Calibration of the sensor (in situ) may be difficult. In addition, the sensor operation may be affected by varying conditions, during the process cycle, such as temperature, pH, and salinity. Methods of on-line sampling involve the automatic removal and measurement of a sample, or sample stream, from the food matrix (e.g., FIA). FIA is a liquid handling technique that has proved flexible in adapting to most chemical and biochemical reaction procedures,49 representing an effective compromise between the desirability of in situ monitoring and the technical ease of offline measurements. The use of liquid handling systems can be used to present a sample in an appropriate format to the sensor. Flow operations are comparatively easy to automate, miniaturise,
7
and control as closed tubing avoids evaporation of fluids and provides exactly repeatable environment for highly reproducible mixing of compounds. Moreover, sensors can be protected from fouling during contact time and from interfering compounds that may be present in the food sample. This is especially relevant when considering target analytes within fresh produce matrices. For example, phenolic compounds (e.g., catechin and epicatechin) and ascorbic acid, which are commonplace in many fresh produce products, are electrochemically active and, thus, their influence must be greatly reduced or eliminated.21
5 FUTURE DEVELOPMENT IN BIOSENSOR TECHNOLOGY FOR FOOD
Overall, the use of biosensors for food analysis can provide a route to a specific, sensitive, rapid, and inexpensive method for monitoring a range of target analytes. This applies to monitoring carried out not only under laboratory conditions but also (e.g., with the use of screen-printed sensors) at on-site locations. These devices can be designed such that the non-specialist operator can use them effectively. However, as with most technologies, there is still room for improvement. Perhaps one of the main areas where biosensor technology can be improved is the actual recognition element itself. Developments in both enzyme (e.g., protein engineering) and antibody (e.g., antibody fragments) technology, and complementary DNA probes continue apace.50 Advances in computational techniques now allow the modeling of both electron transfer reactions and receptor binding interactions with increasing accuracy. This not only enhances understanding of the receptor/transducer interface, but also allows consideration of the design of new receptors based on biological molecules. In contrast to the development of purely biological recognition elements, the use of synthetic material (to perform the same task) has increased. Undoubtedly, these new techniques (e.g., molecularly imprinted polymers; MIPs) will impinge on the evolving biosensor field. Most importantly, biomimetics have the potential to overcome some of the shortfalls associated with biological components, primarily: poor stability
8
BIOSENSOR APPLICATIONS
and higher cost of production.50 The successful introduction of such materials would enable biosensors to be used in many difficult environments. Along with these improvements in the biological recognition elements, other developments in areas such as further miniaturisation and advanced fabrication procedures should lead to more robust and inexpensive sensors. Linked to advances in sampling and extraction, the use of biosensors for monitoring target analytes in a range of foods that are at present difficult to access will become a real possibility. The global food analysis market currently stands at ¤1.1 billion with rapid methods accounting for ¤115 million.51 Therefore, although biosensors are likely to see growth in this area, it is probable that standard food analysis for microorganisms will remain a difficult market to penetrate. There are, however, several areas where biosensors are ideal candidates for improving food diagnostics. These potential opportunities include improved QC and assurance of food-derived raw materials,25 testing for absence/presence of genetically modified constituents where feasible,52 food authenticity/traceability, and incorporation into smart packaging. Fundamentally, however, the trend from yield-driven to quality-driven provision of agricultural products in response to consumer demands for improved food quality, safety, and traceability is set to grow in the developed world. The demand for reliable and inexpensive methods for assessment of quality is set to expand: biosensors offer the opportunity to fulfill this niche.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
REFERENCES 1. L. A. Terry, S. F. White, and L. A. Tigwell, The application of biosensors to fresh produce and the wider food industry. Journal of Agricultural and Food Chemistry, 2005, 53, 1309–1319. 2. M. Schoemaker, R. Feldbrugge, B. Grundig, and F. Spencer, The lipoxygenase sensor, a new approach in essential fatty acid determination in foods. Biosensors and Bioelectronics, 1997, 12, 1089–1099. 3. A. Curulli, S. Kelly, C. A. O’Sullivan, G. G. Guilbault, and G. Palleschi, A new interference-free lysine biosensor using a non-conducting polymer film. Biosensors and Bioelectronics, 1998, 13, 1245–1250. 4. F. Ge, X.-E. Zhang, Z.-P. Zhang, and X.-M. Zhang, Simultaneous determination of maltose and glucose
15.
16.
17.
using a screen-printed electrode system. Biosensors and Bioelectronics, 1998, 13, 333–339. F. Mizutani, Y. Sato, Y. Hirata, and S. Yabuki, High throughput flow-injection analysis of glucose and glutamate in food and biological samples by using enzyme/polyion complex bilayer membrane based electrodes as the detectors. Biosensors and Bioelectronics, 1998, 13, 809–815. L. Campanella, G. Favero, M. Pastorino, and M. Tomassetti, Monitoring the rancidification process in olive oils using a biosensor operating in organic solvents. Biosensors and Bioelectronics, 1999, 14, 179–186. B. Serra, A. J. Reviejo, C. Parrado, and J. M. Pingarron, Graphite-Teflon composite bienzyme electrode for the determination of L-lactate: application to food samples. Biosensors and Bioelectronics, 1999, 14, 505–513. M. Varadi, N. Adanyi, E. E. Szabo, and N. Trummer, Determination of the ratio of D- and L- amino acids in brewing by an immobilised amino acid oxidase enzyme reactor coupled to amperometric detection. Biosensors and Bioelectronics, 1999, 14, 335–340. G. Panfili, P. Manzi, D. Compagnone, L. Scarciglia, and G. Palleschi, Rapid assay of choline in foods using microwave hydrolysis and a choline biosensor. Journal of Agricultural and Food Chemistry, 2000, 48, 3403–3407. K. C. Gulla, M. D. Gouda, M. S. Thakur, and N. G. Karanth, Reactivation of immobilised acetyl cholinesterase in an amperometric biosensor for organophosphorus pesticide. Biochemica Et Biophysica Acta, 2002, 1597, 133–139. H. Sculze, E. Scherbaum, M. Anastassiades, S. Vorlova, R. D. Schmid, and T. T. Bachmann, Development, validation and application of an acetylcholinesterase biosensor for the direct detection of insecticide residues in infant food. Biosensors and Bioelectronics, 2002, 17, 1095–1105. N. Miyanishi, Y. Inaba, H. Okuma, C. Imada, and E. Watanabe, Amperometric determination of laminarin using immobilised β-1,3-glucanase. Biosensors and Bioelectronics, 2004, 19, 557–662. A. G.-V. Prada, N. Pena, M. L. Mena, A. J. Reviejo, and J. M. Pingarron, Graphite-teflon composite bienzyme amperometric biosensors for monitoring of alcohols. Biosensors and Bioelectronics, 2003, 18, 1279–1288. K. T. Kinnear and H. G. Monobouquette, An amperometric fructose biosensor based on fructose dehydrogenase immobilized in a membrane mimetic layer on gold. Analytical Chemistry, 1997, 69, 1771–1775. M. Esti, G. Volpe, L. Massingham, D. Compagnone, E. La Notte, and G. Palleschi, Determination of amines in fresh and modified atmosphere packaged fruits using electrochemical biosensors. Journal of Agricultural and Food Chemistry, 1998, 46, 4233–4237. E. Akyilmaz and E. Dinckaya, A new enzyme electrode based on ascorbate oxidase immobilized in gelatin for specific determination of L-ascorbic acid. Talanta, 1999, 50, 87–93. E. Maestre, I. Katakis, and E. Dominguez, Amperometric flow-injection determination of sucrose with a mediated tri-enzyme electrode based on sucrose phosphorylase and electrocatalytic oxidation of NADH. Biosensors and Bioelectronics, 2001, 16, 61–68.
AGRICULTURE, HORTICULTURE, AND RELATED APPLICATIONS 18. M. Arif, S. J. Setford, K. S. Burton, and I. E. Tothill, L-Malic acid biosensor for field-based evaluation of apple, potato and tomato horticultural produce. The Analyst, 2002, 127, 104–108. 19. L. D. Mello, M. D. P. T. Sotomayor, and L. T. Kubota, HPR-based amperometric biosensor for the polyphenols determination in vegetables extract. Sensors and Actuators, 2003, B96, 636–645. 20. S. Jawaheer, S. F. White, C. Bessant, S. D. D. V. Rughooputh, and D. C. Cullen, Determination of Fruit Status Using a Disposable Multi-Analyte Biosensor Array and Principle Component Analysis, In: 7th World Congress on Biosensors, Kyoto, Japan, 2002 May 15–17. 21. S. Jawaheer, S. F. White, C. Bessant, S. D. D. V. Rughooputh, and D. C. Cullen, Development of a common biosensor format for an enzyme based biosensor array to monitor fruit quality. Biosensors and Bioelectronics, 2003, 18, 1429–1437. 22. M. Keusgen, M. Junger, I. Krest, and M. J. Schoning, Development of biosensor specific for cysteine sulphoxides. Biosensors and Bioelectronics, 2003, 18, 805–812. 23. L. A. Abayomi, L. A. Terry, S. F. White, and P. J. Warner, Development of a Biosensor to Determine Pungency in Onions, In: The 8th World Congress on Biosensors, Granada, Spain, 2004 May 24–26. 24. L. A. Abayomi, L. A. Terry, S. F. White, and P. J. Warner, Defining Onion Pungency Using Amperometric Biosensors, In: International Workshop on Biosensors for Food Safety and Environmental Monitoring, Agadir, Morocco, 2005 November 10–12. 25. L. A. Abayomi, L. A. Terry, S. F. White, and P. J. Warner, Development of a disposable pyruvate biosensor to determine pungency in onions (Allium cepa L.). Biosensors and Bioelectronics, 2006, 21, 2176–2179. 26. M. N. Velasco-Garcia and T. Mottram, Biosensor technology addressing agricultural problems. Bioprocess and Biosystems Engineering, 2003, 84, 1–12. 27. R. W. Claycomb and M. J. Delwiche, Biosensor for online measurement of bovine progesterone during milking. Biosensors and Bioelectronics, 1998, 13, 1173–1180. 28. R. M. Pemberton, J. P. Hart, and J. A. Foulkes, Development of a sensitive, selective, elctrochemcial immunoassay for progesterone in cow’s milk based on a disposable screen-printed amperiometric biosensor. Electrochimica Acta, 1998, 43, 3567–3574. 29. T. Mottram, J. Hart and R. Pemberton, A Sensor Based Automatic Ovulation Prediction System for Diary Cows, In: Proceedings of 5th AISEM Conference, 2000, Lecce, Italy. 30. R. M. Van Es and S. J. Setford, Detection of gentamicin in milk by immunoassay and flow-injection analysis with electrochemical measurement. Analytica Chimica Acta, 2001, 429, 37–47. 31. S. J. Setford, R. M. Van Es, and S. Kr¨oger, Receptor binding protein affinity sensor for rapid β-lactam quantification in milk. Analytica Chimica Acta, 1999, 398, 13–22. 32. M. Delwiche, E. Cox, B. Goddeeris, C. Van Dorpe, J. De Baerdemaeker, E. Decuypere, and W. Sansen, A biosensor to detect pencillin residues in food. Transactions of the ASAE, 2000, 43, 153–159.
9
33. G. A. Chope, L. A. Terry, and P. J. White, Onion bulb storage is related to a temporal decline in abscisic acid concentration. Postharvest Biology and Technology, 2006, 39, 233–242. 34. J. C. Pyun, H. Beutel, J.-U. Meyer, and H. H. Ruf, Development of a biosensor for E. coli based on a flexural plate wave (FPW) transducer. Biosensors and Bioelectronics, 1998, 13, 839–845. 35. L. Rasooly and A. Rasooly, Real time biosensor analysis of staphylococcal enterotoxin A in food. International Journal of Food Microbiology, 1999, 49, 119–127. 36. K. H. Seo, R. E. Brakett, N. F. Hartman, and D. P. Campbell, Development of a rapid response biosensor for detection of Salmonella typhimurium. Journal of Food Protection, 1999, 62, 431–437. 37. J. Homola, J. Dostalek, S. Chen, A. Rasooly, S. Jiang, and S. S. Yee, Spectral surface plasmon resonance biosensor for detection of staphylococcal enterotoxin B in milk. International Journal of Food Microbiology, 2002, 75, 61–69. 38. G. C. Bokken, R. J. Corbee, F. Van Knapen, and A. A. Bergwerff, Immunochemical detection of Salmonella group B, D and E using an optical surface plasmon biosensor. FEMS Microbiology Letters, 2003, 222, 75–82. 39. N. Kim and I.-S. Park, Application of a flow-type antibody sensor to the detection of Escherichia coli in various foods. Biosensors and Bioelectronics, 2003, 18, 1101–1107. 40. T. B. Tims and D. V. Lim, Confirmation of viable E. coli 0157:H7 by enrichment and PCR after rapid biosensor detection. Journal of Microbiological Methods, 2003, 55, 141–147. 41. S. Schwimmer and W. J. Weston, Enzymatic development of pyruvic acid in onion as a measure of pungency. Journal of Agricultural and Food Chemistry, 1961, 9, 301–305. 42. A. O. Scott, Biosensors for Food Analysis, The Royal Society of Chemistry, London, 1998. 43. L. Pogacnik and M. Franko, Detection of organophosphate and carbamate pesticides in vegetable samples by a photothermal biosensor. Biosensors and Bioelectronics, 2003, 18, 1–9. 44. R. H. Hall, Biosensor technologies for detecting microbial foodborne hazards. Microbes and Infection, 2002, 4, 425–432. 45. P. D. Patel, (Bio)sensors for measurement of analytes implicated in food safety: a review. Trends in Analytical Chemistry, 2002, 21, 96–115. 46. L. A. Terry, K. A. Law, K. J. Hipwood, and P. H. Bellamy, Non-structural Carbohydrate Profiles in Onion Bulbs Influence Taste Preference, In: Information and Technology for Sustainable Fruit and Vegetable Production. Frutic 05 , Montpellier, France, 2005 September 12–16. 47. N. Gajovic, A. Warsinkef, and W. Scheller, Comparison of two enzyme sequences for a novel L-malate biosensor. Journal of Chemical Technology and Biotechnology, 1997, 68, 31–36. 48. M. Stredansky, B. Cini, C. Benetello, and S. Stredanska, Biosensors for L-malate with Improved Sensitivity, In: 8th World Congress on Biosensors, Granada, Spain, 2004 May 24–26.
10
BIOSENSOR APPLICATIONS
49. M. Kim and M.-J. Kim, Isocitrate analysis using a potentiometric biosensor with immobilised enzyme in a FIA system. Food Research International, 2003, 36, 223–230. 50. J. D. Newman, L. J. Tigwell, A. P. F. Turner, and P. J. Warner, Biosensors: A Clearer View , In: 8th World Congress on Biosensors, Granada, Spain, 2004 May 24–26.
51. L. Kahr, M. Brannback, and G. Von BlankenfeldEnkvist, Trends and Needs in Food Diagnostics, In: CE Food Congress, Ljubljana, Slovenia, 2002 September 22–25. 52. I. Mannelli, M. Minunni, S. Tombelli, and M. Mascini, Quartz crystal microbalance (QCM) affinity biosensor for genetically modified organisms (GMOs) detection. Biosensors and Bioelectronics, 2003, 18, 129–140.
80 From Earth to Space: Biosensing at the International Space Station Christa Baumstark-Khan and Christine E. Hellweg Radiation Biology Department, Institute of Aerospace Medicine, K¨oln, Germany
1 HUMAN ACTIVITIES IN SPACE
The endeavor of men to escape the boundaries of Earth and to travel to the heavens is as old as the history of mankind itself. Religion, mythology, and literature reaching back thousands of years are sprinkled with references to magic carpets, flying horses, flaming aerial chariots, and winged gods. The ancient Greek legends tell the story of the first but unsuccessful space flight by Icarus and Jules Verne’s classical fiction of a Moon voyage is the most prominent story known to nearly everyone. Manned space flight started in the mid-twentieth century, when the development and refinement of aeronautics and the construction of rockets accomplished the necessary prelude to the exploration of near and outer space. The first milestone on the way to space was the launch of the Soviet Sputnik II, which carried its canine passenger “Laika” into orbit on November 3, 1957. Major achievements of the first era of space exploration were the launch of Yuri Gagarin on board a Russian Vostok rocket, thereby initiating the age of manned space flight, and the first spacewalk by the Soviet cosmonaut Alexei Leonov in 1965. Since that time, numerous manned missions to Earth orbit have been carried out routinely by the Americans and Russians and in 2003 by China, lasting from a few days in capsules to several hundred days in space stations.
A highlight in manned space flight was achieved in July 1969, when Neil Armstrong, commander of Apollo 11, set foot upon the Moon, declaring famously that it was “one small step for a man, one giant leap for mankind”. The next notable achievement in space was the launch of the first space station, Salyut 1, from the USSR. After the first 20 years of exploration, focus began shifting from one-off flights to renewable hardware, such as the Space Shuttle program, and from competition to cooperation as on the International Space Station (ISS). With the beginning of not only a new century but also a new millennium, mankind extends its view to other planets in order to search for life out there. Recently, private interests have begun promoting space tourism, while larger government programs have been advocating a return to the Moon and possibly missions to Mars in the near future.
1.1
First Flight Programs
The years 1958–1961 were busy ones in both the United States and the Soviet Union for the development of manned space vehicles. Developmental works on the Soviet carrier rocket and the spacecrafts have commenced a series of five unmanned test flights. These Vostok precursor flights, Korabl
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
Sputnik I through V, were designed to collect data on the effects of space environment (especially solar radiation) on biological specimens and to test the spacecraft systems. In late 1960 to early 1961 the Soviets were ready to begin manned space flight operations. The Vostok flights intended to collect data on weightlessness, a topic of considerable concern not only to Soviet flight physicians. For the second manned flight, the medical specialists insisted that the duration of the flight should not be longer than two or three orbits for judging the effects of zero gravity on physiology. But in accordance with political considerations the cosmonaut Titov and his advisors wanted to go for a day-long mission. During his flight Titov went through a phase of motion sickness,1 a fact which held up the progress of the Soviet flight program for nearly one year. The Project Mercury was the United States’ first man-in-space program.2 From 1958 till 1963 six manned space flights were accomplished as part of a 25-flight program showing that man can function as a pilot, an engineer and an experimenter without undesirable reactions or deteriorations of normal physiology for periods up to 34 h of weightless flight. Other facets of the Mercury experience were the development of manned space vehicles, accurate and detailed test procedures, and more responsive configuration control techniques. During the initial phase the Americans preferred ballistic shots resulting in only suborbital space flights. In February 1962, after a series of frustrating delays John Glenn became the first American to orbit the Earth with his space ship MA-6 Friendship 7. Mercury and Vostok demonstrated the feasibility of placing a human being in orbit, observing his reactions to the space environment, and returning him safely to Earth at a known point. The second stage in human space flight was the development of multi-place spacecrafts for the conduction of more complicated missions—the era of Gemini and Voskhod. The program Gemini, which involved 12 flights, including two unmanned flights, provided techniques, equipment, and experience that helped bridge the difficult translation from experimental, Earth-orbiting Mercury to ambitious, lunar-landing Apollo. The Gemini spacecrafts were equipped with a computer and radar to aid in solving the rendezvous problem. All of these systems went through troubled development and qualification
periods and, in most cases, required extensive redesign. The same was true for design work on astronaut equipment and space suits to achieve a range of capabilities from extravehicular activity to cabin operations. The 10 manned flights of the Gemini program spanned 603 days (a flight every 60 days), and 1940 man hours in space during 970 mission-hours gave 16 different astronauts the chance for gaining experience. The length of the Gemini missions, for example, 330 h on Gemini VII in December 1965, reassured major medical concerns over man’s ability to adapt to and function in space. It became more and more an accepted fact that man could withstand the space environmental conditions and would fly to the Moon, despite the rumors that run in some medical circles that the astronauts might die after being in long weightless flight. Gemini’s most lasting contribution will probably be seen by future historians in the changing views toward our Earth and Earth’s environmental problems, which was brought about by bringing back photographs from the blue planet from space. For some time, the development phase of Gemini and Apollo proceeded along parallel lines. Experience from the Gemini program was passed on to Apollo, as 15 of the 20 Gemini astronauts subsequently flew in the lunar program.3 The Apollo program was designed to land humans on the Moon and bring them safely back to Earth. It included a large number of unmanned test missions and crewed missions. The 11 crewed missions include two Earth-orbiting missions, two lunar orbiting missions, a lunar swing-by and six Moon landing missions. Lunar surface experiments included soil mechanics, meteoroids, seismic, heat flow, lunar ranging, magnetic fields, and solar wind experiments.
1.2
The Era of Space Stations
Designed for long-duration missions, space stations proved that humans could live and work in space for extended periods. Such missions expanded our knowledge of solar astronomy well beyond Earth-based observations. The Soviet Union launched the world’s first space station, Salyut 1, in 1971, a decade after launching the first human into space. The United States sent its first space station, the larger Skylab, into orbit
BIOSENSING AT THE INTERNATIONAL SPACE STATION
in 1973 and it hosted three crews before it was abandoned in 1974. Russia continued to focus on long-duration space missions and in 1986 launched the first modules of the Mir space station. In 1998, the first two modules of the ISS were launched and joined together in orbit. Other modules soon followed and the first crew arrived in 2000. 1.2.1 Salyut
The Soviet Salyut 1 was the first Salyut space station, and the first space station of any kind. It was launched on April 19, 1971. Its first crew was launched in Soyuz 10 but was unable to board it due to a failure in the docking mechanism; its second crew was launched in Soyuz 11 and remained on board for 362 orbits. During these productive 23 days different tasks were performed by the crew involving checking and testing the design and equipment of the orbital piloted station. Scientific topics were related to geological and geographical objects on Earth’s surface and to physical characteristics and phenomena in the atmosphere and outer space (e.g., the spectrum of electromagnetic radiation). Beneath that, cosmonauts conducted medico-biological studies to determine the possibilities of performing various jobs by them in the station and to study the influence of space flight factors on the human organism. On June 29 the cosmonauts Dobrovolski, Patsayev, and Volkov returned to Earth, but unfortunately they were killed during reentry into the atmosphere due to a cabin pressure leak. The Salyut space station reentered Earth’s atmosphere October 11, 1971 after 175 days in space. During the years 1971 to 1991 the Soviets have operated seven Salyut stations in space for military and scientific purposes thereby collecting data on human physiology on long-duration space flight.4 From 1977 until 1982 Salyut 6 was visited by five long-duration crews including cosmonauts from other Warsaw Pact countries. The longest flight onboard Salyut 6 lasted 185 days. Salyut 7 was inhabited for 4 years and 2 months, during which time it was visited by 10 crews constituting (including French and Indian cosmonauts). Salyut 7 de-orbited on February 7, 1991.
3
1.2.2 Skylab
The US space station Skylab was launched May 14, 1973, from the NASA’s Kennedy Space Center by a huge Saturn V launch vehicle and reached its near-circular orbit at the altitude of 435 km. Shortly after liftoff, the meteoroid shield was torn off from the space station inadvertently by atmospheric drag. All other major functions and pressurization of the space station occurred as planned. The misfortune during launch resulted in considerable problems that had to be conquered before the space station would be habitable for the three manned periods of its planned 8-month mission. The manned Skylab missions were thus dedicated to repair works on the station in addition to their science program. In the Skylab, both the man hours in space and the man hours spent in performance of extravehicular activities (EVA) under microgravity conditions exceeded the combined totals of all of the world’s previous space flights up to that time. The effectiveness of the Skylab crews exceeded any expectations, especially in their ability to perform complex repair tasks within the station and during EVA, although all crew members had some initial problems with motion sickness. The capability to conduct longer manned missions was conclusively demonstrated in Skylab, first by the crew returning from the 28 day mission and, more forcefully, by the good health and physical condition of the second and third Skylab crews who stayed in weightless space for 59 and 84 days respectively. Following the final manned phase of the Skylab mission, after return of crew 4 to Earth, Skylab was positioned into a stable altitude and systems were shut down. In the fall of 1977, it was determined that Skylab was no longer in a stable altitude and on July 11, 1979, Skylab impacted the Earth surface. The debris dispersion area stretched from the South-eastern Indian Ocean across a sparsely populated section of Western Australia.5
1.2.3 MIR
The Soviet Mir orbital station was the first consistently inhabited long-term research station in space.6 Based on the previously launched Salyut series of space stations Mir was assembled in orbit by successively connecting several
4
BIOSENSOR APPLICATIONS
modules, each launched separately from 1986 to 1996. The major part of the entire orbital station was the core module combining its modules into a single complex. It accommodated control equipment for the station crew life support systems and science hardware, as well as crew rest locations. The Kvant astrophysics module consisted of a laboratory compartment with a transfer chamber and unpressurized compartment for science instruments. The Kvant 2 module consisted of three pressurized compartments (instrument–cargo, instrument–science compartments and airlock compartment) supplying the station with science hardware and equipment. It supported crew spacewalks as well as the performance of various scientific research and biotechnological experiments. The Kristall module consisted of two pressurized compartments (instrument–cargo and transfer–docking compartment) for the conduction of biological and materials processing research and experiments. The Kristall module was equipped with an active docking compartment for support of dockings of the US space shuttle orbiters to the MIR Station without modifying its configuration. The Spektr module (two compartments; pressurized instrument cargo and nonpressurized compartment with solar arrays and science instruments) was aimed to investigate atmospheric and geophysical processes. The Priroda remote sensing module, consisting of one pressurized instrumentcargo compartment, was the laboratory for studying geophysical processes in near Earth orbit, especially space radiation. By mid-1996, the completely configured station had a total mass of 11.5 tons and spanned an area of 31 × 33 m. The station existed for 13 years until March 23, 2001, at which point it was deliberately de-orbited, and broke apart during atmospheric re-entry.6 It was the first international collaboration bringing together cosmonauts and astronauts of many different countries to perform different scientific missions, such as the German–Russian MIR 92 mission,7 various EUROMIR missions8 and different missions from the US-Russian Shuttle–Mir program.9 During that time, major experience was gained on international knowledge exchange, on space station operation and navigation, and on scientific experimentation in space. Prior to the Shuttle–Mir Program, NASA’s longest duration experiences had been the Skylab missions of 1973–1974. Shuttle–Mir enabled astronauts to spend hundreds
of days on Mir, more time in orbit than had been accumulated in orbit since the Shuttle Program began in 1981. Shuttle–Mir’s long-duration residences provided experience and data that will help in the ISS and in possible future missions to the Moon and Mars. Science conducted by astronauts aboard Mir included over 100 investigations in eight disciplines, including advanced technologies, earth sciences, fundamental biology, human life sciences, ISS risk mitigation, life support risk management, microgravity, and space sciences. The major lesson learned from the international cooperation on MIR was that space exploration is no longer a competition between nations. Working with Russia in the Shuttle–Mir Program provided the US with experience that is currently being applied to the ISS with its 16 participating nations. Implementation of long-duration missions on the orbital station and conducting of large amount of medical experiment have allowed to develop the national long-duration space flight support system. Achieved space flight duration (up to 438 days by the Russian cosmonaut Polyakov in 1995) has confirmed a principal opportunity for human interplanetary space flight. 1.2.4 The ISS
The most complex engineering and construction project in the world is currently taking place in space.10 Sixteen countries and over 100 000 people are contributing to this monumental achievement. The ISS is a unique platform for conducting research in a variety of disciplines; to better understand the role gravity or its absence plays in biological and physical processes. As a longduration laboratory, it enables research that was not possible on earlier platforms. In particular, ISS is ideally suited for studying the effects of long-duration space flight on humans, important for perfecting countermeasures to the deleterious effects to ensure crew safety and to enable exploration missions. Configuration of the ISS Construction of ISS began in late 1998, with the launch of the Russian module Zarya. Since that time, many flights of Russian and American vehicles have added the major elements to the station, enlarging the platform from its original 20,000 kg single module configuration to the
BIOSENSING AT THE INTERNATIONAL SPACE STATION
current 180,000 kg facility.11 Up to May 2007 Russian Soyuz spacecrafts and American Space Shuttles have brought 15 long-duration crews to live aboard the station for 4–6 months each, resulting in a continuous human presence in space since October 2000. Concurrent with the launch of the first research rack in March 2001, the payload operations and integration center (POIC) at the Marshall Space Flight Center (MSFC) in Huntsville became operational. Additional payload-specific support beginning with Expedition 2 was provided by Telescience Support Centers at other NASA Centers, including Johnson Space Center for human life sciences investigations. Remote sites at investigators’ institutes, domestic, and international, are also routinely tied in during times when those experiments are operating. The ISS depends on the Russian Soyuz rockets and the US Space shuttles to deliver crews and payloads to the station. Prior to the space shuttle Columbia disaster in early 2003, when seven astronauts were tragically lost,12 station planners were targeting 2004 for the completion of the US contribution to the project. But the accident delayed construction works considerably. During the two-half years, NASA spent recovering from the Columbia accident Russia’s Federal Space Agency supported the ISS with a lifeline of unmanned Progress cargo ships and steady launches of crew-carrying Soyuz spacecraft. Unmanned Russian Progress vehicles have brought the required logistics to maintain the station and its crews. Among the payload items delivered so far have been seven large research racks and logistics totaling more than 6500 kg. NASA’s three remaining orbiters (Atlantis, Discovery, and Endeavour) are vital to the space station’s construction since they are the only vehicles capable of delivering major components to the orbital research platform, including heavy modules and supply containers.13 Recently, NASA and its partner agencies have set a new plan to complete the ISS by 2010, delaying science utilization.14 Assembly of ISS will continue in the near future with completion of the trusses, addition of solar arrays for power generation, and radiator panels for cooling, and the International Partner research modules, leading to a configuration represented in Figure 1.15 The European Space Agency (ESA)’s Columbus module will increase the station’s research capability with additional 10 research rack locations, with the Japanese Kibo
5
module adding 11 more. The full set of research modules will also allow optimal location of life sciences research racks for maximal synergy. Laboratory Modules The US Laboratory Module DESTINY A significant milestone for ISS-based research was the addition of the US laboratory module Destiny,16 launched on the STS 98/5A mission in February 2001. Weighing 14 000 kg at launch, Destiny is a cylindrical module, 8.5 m long with an external diameter of 4.3 m. Internally, it is configured with 24 racks lining the four surfaces. The racks contain various systems equipments such as life support, controls for the station’s robotic arms, medical hardware, a crew sleep station, and up to 10 research facilities, of which 7 are already on orbit. The first research rack was the human research facility (HRF) Rack 1, installed in March 2001. The rack provides a core set of experiment hardware to support investigations, as well as power, data and commanding capability, and stowage. The second HRF rack, to complement the first with additional hardware and stowage capability, will be launched once Shuttle flights resume. Future years will see additional capability to conduct human research on ISS as International Partner modules and facility racks are added to ISS. Crew availability, both as a subject count and time, will remain a major challenge to maximizing the science return from the bioastronautics research program. The Japanese Laboratory Module KIBO The Japanese Experiment Module (JEM) or Kibo (which means hope) will be the first Japanese manned experimental facility.17 It is a combine module consisting of two different facilities composed of four components: the pressurized module (PM) and the exposed facility (EF). The core component PM is of cylindrical shape, 11.2 m long and 4.4 m in diameter. It contains 10 standard payload racks in which the astronauts perform scientific experiments on the effects of microgravity, space radiation, high vacuum, and abundant solar energy. The EF is a terrace located outside the port cone of the PM where experiments can be fully exposed to the space environment. The experiment logistic module (ELM) contains a pressurized section to serve the PM and a nonpressurized section to serve the EF. It is placed atop the port side of the PM and
6
BIOSENSOR APPLICATIONS
(a)
ISS Configuration As of April 2007 Docking compartment (DC) 1 P1 truss SO truss segment S1 truss Mobile segment segment servicing system
Zarya control module
Zvezda service module
PMA 1
SM MMOD shields Research module (RM)
ESP-3 Port photovoltaic arrays
S3/4 truss segment
P6 truss segment
Multipurpose laboratory module (MLM) and ERA MLM outfitting ELCs
P5 truss segment
S6 truss segment ELC S5 truss segment
Canadarm2 SPDM/"Dextre"
Starboard photovoltaic arrays Mobile remote servicer base system (MBS), Mobile transporter (MT) Z1 truss segment
P3/4 truss segment
JEM ELM-PS JEM RMS & exposed facility
Airlock ESP-2 Node 1 Node 3
PMA 3 Cupola
US Lab Columbus
Node 2
ESP-1 PMA-2
JEM PM
Elements currently on orbit Elements pending US shuttle launch
(b)
Elements pending russian launch
Figure 1. (a) Artistic view of the complete configuration of ISS; (b) configuration of ISS including the International Partners’ modules. [Adapted from Kitmacher et al.15 with permission, copyright 2005, International Academy of Astronautics.]
BIOSENSING AT THE INTERNATIONAL SPACE STATION
is intended as a storage and transportation module. The Remote Manipulator System (JEM–RMS) is a robotic arm, mounted at the port cone of the PM, where it will serve the EF and move equipment from and to ELM. Kibo is intended to be docked to the ISS in 2008. The European Module COLUMBUS The Columbus laboratory is ESA’s biggest single contribution to the ISS.18 The 4.5-m-diameter cylindrical module (see Figure 2) is equipped with flexible research facilities that offer extensive science capabilities. During its 10-year projected life span, Earth-based researchers will be able to conduct experiments in life sciences, materials science, fluid physics, and a whole host of other disciplines, all in the weightlessness of orbit. Their efforts will be channeled through the Columbus Control Centre in Germany, which will interface with the module itself and also ESA’s NASA partners in the United States. The Columbus laboratory has room for 10 international standard payload racks (ISPRs), 8 situated in the sidewalls, and 2 in the ceiling area.19 Each rack is the size of a telephone booth and able to host its own autonomous and independent laboratory, complete with power and cooling systems, and video and data links back to researchers on Earth. ESA has developed a range of payload racks,20 all tailored to squeeze the maximum amount of research from the minimum
7
of space and to offer European scientists across a wide range of disciplines full access to a weightless environment that cannot possibly be duplicated on Earth. The Biolab, for example, supports experiments on microorganisms, cells, and tissue cultures, and even small plants and small insects. Another rack contains the European physiology modules (EPM) facility, a set of experiments that will be used to investigate the effects of long-duration spaceflight on the human body. Experiment results will also contribute to an increased understanding of age-related bone loss, balance disorders, and other ailments back on Earth. The material science laboratory electromagnetic levitator (MSL-EML) is a facility for the melting and solidification of conductive metals, alloys, or semiconductors and a fluid science laboratory (FSL) will accommodate experiments on the strange behavior of weightless liquids. These too, could bring far-reaching benefits on Earth: better ways to clean up oil spills, for example, and even improved manufacture of optical lenses. Outside its comfortable, pressurized body, Columbus has four mounting points for external payloads. Exposed to the vacuum of space, and with an unhindered view of the Earth and outer space, science packages can investigate anything from the ability of bacteria to survive on an artificial meteorite to volcanic activity 400 km below on the Earth.
10027
1343
Overhead 3404
+ZColumbus Port +XColumbus
+ZColumbus
705
esa columbus Starboard
+YColumbus
Deck 1168 6871 7534
Dimensions in mm
Figure 2. The European contribution to the ISS: the laboratory module Columbus with integrated external payloads.
8
BIOSENSOR APPLICATIONS
The European laboratory module Columbus is scheduled to be delivered at the station in December 2007 with the carrier flight STS-122, the 24th mission to the ISS. The actual launch date of Columbus is not known at present, it is dependent on the success of the return to flight of the space shuttle.
1.3
Beyond the ISS
After the realization of the ISS, human exploratory missions beyond low Earth orbit (LEO) are widely considered as the next logical step in a worldwide peaceful cooperation in space. The NASA vision for space exploration calls for humans to return to the Moon by the end of the next decade, paving the way for eventual journeys to Mars and beyond. During the late 1960s and early 1970s, the Apollo program demonstrated US technical strength in a race against the Soviet Union to land humans on the Moon. Today, NASA’s plans for a return to the Moon are not driven by Cold War competition, but by the need to test new exploration technologies and skills on the path to Mars and beyond. NASA will begin its lunar test bed program with a series of robotic orbiter and landing missions. A human mission to the Moon will follow these robotic missions as early as 2015.21 The purpose of a human mission to the Moon is to establish a base, perform surveys, establish infrastructure for permanent human base, collect and return material samples, and serve as an analogue environment for subsequent Mars exploration. This capability will be established as quickly as possible following the return of humans to the Moon. To best accomplish science and explorative goals, the outpost is expected to be located at the lunar south pole. The lunar outpost consisting of a habitat, power supply, communication, and navigation infrastructure, and surface mobility, and robotic systems shall already be emplaced when the first crew arrives at the Moon. Accordingly, construction work on the architecture of the habitat has to be done by robotic missions, and the crew will perform only some final assembly and verification tasks to make the outpost operational. Starting in 2011, NASA will also launch the first in a new series of human precursor missions to Mars to demonstrate technologies and to obtain critical data for future human missions on
chemical hazards, resource locations, and research sites. The first human mission beyond the Moon will be determined on the basis of available resources, accumulated experience, and technology readiness.22 The timing of the first human research missions to Mars will depend on discoveries from robotic explorers, the development of techniques to mitigate Mars hazards, advances in capabilities for sustainable exploration, and available resources. The Mars exploration employs conjunction-class missions, often referred to as long-stay missions (1000 day mission), to minimize the exposure of the crew to the deep-space radiation and zero-gravity environment while, at the same time, maximizing the scientific return from the mission. This is accomplished by taking advantage of optimum alignment of Earth and Mars for both the outbound and return trajectories by varying the stay time on Mars, rather than forcing the mission through nonoptimal trajectories, as in the case of the short-stay missions (500 day mission). This approach allows the crew to transfer to and from Mars on relatively fast trajectories, on the order of 6 months, while allowing them to stay on the surface of Mars for a majority of the mission, on the order of 18 months. The habitat on Mars is implemented through a split mission concept in which cargo is transported in manageable units to the surface, or Mars orbit, and checked out in advance of committing the crews to their mission. The establishment of such permanently inhabitable bases on Moon and Mars will add a new dimension to human space flight, concerning the distance of travel, the habitability of the base, and the durability of the astronauts. Above all radiation response, gravity related effects as well as psychological issues will become a possible limiting factor to human adaptability to the mission scenario.
2 FACTORS OF THE SPACE ENVIRONMENT
The story of Daedalus and Icarus in Greek mythology about the misfortune of Icarus when he ignored the risk limits set by Daedalus for flying toward the sun (not too high and not too low) might be one of the first written theses about the potential dangers from solar radiation in space.
BIOSENSING AT THE INTERNATIONAL SPACE STATION
Today, after decades of relatively frequent shuttle trips and orbital missions, and the realization that interplanetary missions “toward a human presence in space” are technically feasible, although not safe, space environmental factors are considered as major hazards. Humans in space, on board of the ISS as well as in interplanetary missions, are confronted to a complex matrix of a multitude of environmental factors of various kinds and intensities, with microgravity and cosmic radiation as the most dominant stressors. In the endeavor to assess the risks for humans in space—especially for long-duration missions—the concerted action of all stimuli has to be known and warning signals about changes of the “health” status of the environment are required. 2.1
Planetary Atmospheres and Space Vacuum
Stars, planets, and moons keep their atmospheres by gravitational attraction; accordingly atmospheres have no clearly defined boundary. The density of atmospheric gas simply decreases with distance from the object. In LEO the atmospheric density is about 1 × 10−7 Pa, still sufficient to produce significant drag on satellites. Beyond planetary atmospheres, space has been compared to a vacuum of about 1 × 10−16 Pa. On Earth, humans are subjected to an atmospheric surface pressure of 1.014 × 105 Pa, the surface pressure on Moon and Mars are about 3 × 10−10 and 636 Pa, respectively. There are limited data available from human accidents, describing the effects of exposure to near vacuum. Humans cannot survive the condition of vacuum. Exposed humans will lose consciousness after a few seconds and will die within minutes from ebullism and oxygen loss, before the body swells to about double size. The hazardous effects of vacuum can be omitted by containment in a space suit,23 in which an artificial atmosphere of 2 × 103 Pa is maintained. 2.2
Gravity Levels
The most fascinating medical characteristic of space flight is undoubtedly weightlessness, an effect created by “zero g”, the balance of centrifugal and centripetal forces. (The gravitational field at the Earth’s surface, denoted g, is approximately 9.80665 m s−2 .) In the early days of space
9
flight, speculation on organ failure in microgravity circled among aviation physicians, as well as worries on disturbed signal perception and cognitive functions. They feared that pressure on the nerves and organs, muscle tone, posture, and the labyrinth of the inner ear would give conflicting signals in the weightless state. The basic difficulty regarding long-term studies of weightlessness is the impossibility of simulating the exact condition on the Earth for extended time. The only possibility to achieve weightlessness is putting an object in a state of free fall. Microgravity experiments on Earth by using drop towers (about 5 s free fall), and aircrafts flying parabolic trajectories (up to 90 s weightlessness) have been conducted with biological samples. The best but most expensive device for zero microgravity experimentation is the sounding rocket; however, such sounding rocket flights are composed of an initial high g, an intermediate micro-g and a final high g phase. From 1951 on ballistic experiments were performed on mice, dogs, and monkeys, which revealed the survivability of these species exposed to varying levels of acceleration and deceleration.24 Test pilots, who flew the first parabolic flights complained about spinning and described the feeling of “lost in space”,25 now known as disorientation. In 1955 the principal problems of weightless flight seemed solvable, as eating and drinking at zero microgravity were not troublesome when squeeze bottles and tubes were used, and urination presented no real difficulty. Some subjects suffered nausea, disorientation, loss of coordination, and other disturbances, but the majority reported that after they adjusted to the condition they found it “pleasant” and had a feeling of “well-being”. Another problem perplexing aeromedical experts at the beginning era of space flight was the effect on the human body of the heavy acceleration and deceleration forces, called g loads. Acceleration of a vehicle into space and the deceleration accompanying its return to Earth results in g loads several times the normal accelerative force of gravity, thereby imposing severe strain on astronauts’ body organs. Accordingly tests were required before sending men into space. The ability to withstand immediate impact forces was shown by test pilots who survived rides on rocket-driven impact sledges at an impact force of 35–40 g. Experiments performed later on human centrifuges had more immediate relevance to space
10
BIOSENSOR APPLICATIONS
medicine than impact sledge tests, because of the relatively gradual buildup of g forces encountered during the launch and re-entry phases of ballistic, orbital, or interplanetary flight. Results from such centrifuge tests recommended acceleration forces from 3 to 8 g for takeoff from the physiological standpoint. As a consequence, human test subjects were exposed to peaks of 10 g for something over two minutes; chest pain, shortness of breath, and occasional loss of consciousness were the symptoms in response to the higher g loads.26 Chimpanzees exposed to peak accelerations of 40 g for 1 min suffered internal injuries, including heart malfunctions. It appeared that prolonged subjection to high g forces might be severely injurious or perhaps even fatal to a man.27 Further experiments with different materials led to the development of anti-g devices in the kind of contour seats, which allow short duration g loads of up to 20 g. Under nominal launch and landing conditions impacts greater than 9 g are not to be expected. For the lunar roundtrip maximum g loads of 3 g during launch and ascend to the moon surface will not be exceeded; the gravity level during the aero capture manoeuvre at Earth arrival is calculated to lay in the range of about 6 g due to the atmospheric drag. Descending from LEO to Earth with a Space shuttle type spacecraft will result in 1–2 g. For the Mars mission, similar g loads are expected to occur during launch and landing; for aero capture and landing on Mars a maximum of 6 g will be
reached. The interplanetary cruise is carried out a zero-gravity level. The two crew members orbiting Mars instead of landing on the planet’s surface will cumulative zero-gravity periods of either 450 or 900 days (depending on the mission type), only interrupted by orbit insertion at Mars (6 g) and injection toward Earth (3 g). Especially the high gravity levels of 6 g at Mars arrival (aero capture) and landing on Earth (with a capsule) after the long period at microgravity seems critical for the health of the crew. 2.3
Radiation Environment
In addition to vacuum, weightlessness, and g loads, the problems of space flight included protecting the passenger from different kinds of electromagnetic radiation found above the atmosphere (Figure 3). The prime instrument for cosmic ray research from 1952 to 1958 was the oldest vehicle for human flight, the balloon. Most data on space radiation was obtained from satellites, probes and measurements performed during space flights, and on space stations. In the interplanetary space, the radiation field is composed mainly of two groups: the solar cosmic radiation (SCR) and the galactic cosmic radiation (GCR). In the vicinity of the Earth, a third radiation component is present: the radiation trapped by the Earth’s magnetosphere, the socalled van Allen belts.28
Jovian electrons Galactic and extragalactic cosmic radiation
Solar X-rays
Neutrons and g-rays from solar particle events Radiation belt particles Electrons, protons, and heavy ions from solar particle events
Figure 3. The radiation field in our solar system.
BIOSENSING AT THE INTERNATIONAL SPACE STATION
SCR consist of the low energy solar wind particles that flow constantly from the sun and the so-called solar particles events (SPEs) that originate from magnetically disturbed regions of the sun, which sporadically emit bursts of charged particles with high energies.29 These events are composed primarily of protons with a minor component (5–10%) being helium nuclei (α particles) and an even smaller part (1%) heavy ions and electrons. SPEs develop rapidly and generally last for no more than some hours, however, some proton events observed near Earth may continue over several days. The emitted particles can reach energies up to several GeV. In a worst case scenario; doses as high as 10 Gy could be received within a short time. Such strong events are very rare, typically about one event during the 11-year solar cycle. Concerning the less energetic, though still quite intensive events, for example, in cycle 22 (1986–1996) there were at least eight events for proton energies greater than 30 MeV. For LEO, the Earth’s magnetic field provides a latitude dependent shielding against SPE particles. Only in high inclination orbits and in interplanetary missions, SPEs create a hazard to humans in space, especially during EVA. GCRs originate outside the solar system in cataclysmic astronomical events, such as supernova explosions. Detected particles consist of 98% baryons and 2% electrons.30 The baryonic component is composed of 85% protons (hydrogen nuclei), with the remainder being α particles (helium nuclei) (14%) and heavier nuclei (about 1%). The latter component comprises the so-called HZE particles (particles of high charge Z and high Energy), which are defined as cosmic ray primaries of charges Z > 2 and of energies high enough to penetrate at least 1 mm of spacecraft or of spacesuit shielding. Though they only contribute to roughly 1% of the flux of GCR, they are considered as a potential major concern to living beings in space, especially for long-term missions at high altitudes or in high inclination orbits, or for missions beyond the Earth’s magnetosphere. Reasons for this concern are based, on the one hand on the inefficiency of adequate shielding and, on the other hand on the special nature of HZE particleproduced lesions. If the particle flux is weighted according to the energy deposition, iron nuclei will become the most important component, although their relative abundance is comparatively small.
11
The fluence of GCR is isotropic and energies up to 1020 eV can be present. When GCR enter our solar system, they must overcome the magnetic fields carried along with the outward-flowing solar wind, the intensity of which varies according to the about 11-year cycle of solar activity. With increasing solar activity the interplanetary magnetic field increases, resulting in a decrease of the intensity of GCR of low energies. This modulation is effective for particles below some GeV per nucleon. Hence, the GCR fluxes vary with the solar cycle and differ by a factor of approximately five between solar minimum and solar maximum with a peak level during minimum solar activity and the lowest level during maximal solar activity. At peak energies of about 200–700 MeV per unit during solar minimum, particle fluxes (flow rates) reach 2 × 103 protons per 100 µm2 (mean area of a human cell nucleus) per year and 0.6 Fe-ions per 100 µm2 per year (100 µm2 being the typical cross section of a mammalian cell nucleus). Although iron ions are 1/10th as abundant as carbon or oxygen, their contribution to the GCR dose is substantial, since dose is proportional to the square of the charge. The fluxes of GCR are further modified by the geomagnetic field. Only particles of very high energy have access to low inclination orbits. Towards higher inclination particles of lower energies are allowed. At the pole, particles of all energies can impinge in the direction of the magnetic field axes. Due to this inclination-dependent shielding, the number of particles increases from lower to higher inclination. The van Allen belts in the vicinity of the Earth are a result of the interaction of GCR and SCR with the Earth’s magnetic field and the atmosphere. Two belts of radiation are formed comprising electrons and protons, and some heavier particles trapped in closed orbits by the Earth’s magnetic field. The main production process for the inner belt particles is the decay of neutrons produced in cosmic particle interactions with the atmosphere. The outer belt consists mainly of trapped solar particles. In each zone, the charged particles spiral around the geomagnetic field lines and are reflected back between the magnetic poles, acting as mirrors. Electrons reach energies of up to 7 MeV and protons up to about 200 MeV. The energy of trapped heavy ions is less than 50 MeV, although their radiobiological impact is very small.
12
BIOSENSOR APPLICATIONS
The trapped radiation is modulated by the solar cycle: proton intensity decreases with high solar activity, while electron intensity increases, and vice versa. 2.4
Resources and Waste
When humans embark on long-duration missions such as the establishment of permanent bases on the lunar surface or travel to Mars for exploration, they will continue to need food, water and air, and to produce metabolic and other waste products. For these long-duration missions it may not be economical or practical to resupply basic life support needs from Earth. For long-duration missions it will therefore be essential to develop systems to produce food, purify and supply water, regenerate oxygen, and remove undesirable components of the air. A very important issue will be the waste treatment in general. It has to be considered that a variety of different waste products (liquid waste, gaseous waste, solid waste) from different sources (human, processes, power generation etc.) will be collected during long-term missions. Main aim should be to further process the waste products to get back all inherent consumables, so that a minimum of substances will really be lost. “Environmental control and life support systems” (ECLSS) are essential for all kinds of confined volumes or habitats within which people are supposed to live and to work over longer periods of time. The main, practically the only objective of any kind of life support system is to achieve and to control a physiologically acceptable environment within all kinds of confined habitats. In practice, ECLSS’s must process human and other outputs, and must provide required input resources for humans and other biological species as required. The measurement and monitoring of relevant parameters from such ECLSS is absolutely necessary in order to know about and to control the actual conditions of the environment within which people are living and working, far away from a safe haven.
3 BIOSENSORS IN SPACE 3.1
Animals as Whole-organism Sensors
The first biosensors in space were whole organisms as substitutes for human beings, because
testing of survivability of spaceflight conditions was considered to be a prerequisite before manned space missions were attempted. In mid 1946 the first animals sent into space were fruit flies to explore the effects of radiation exposure at high altitudes. Numerous monkeys of several species were flown by the United States in the 1950s and 1960s. They were implanted with sensors to measure vital signs, and many were under anesthesia during launch. Able, a rhesus monkey, and Baker, a squirrel monkey, the first living beings, which successfully returned to Earth after traveling in space aboard an American Jupiter AM-18 rocket in 1959 experienced accelerations of 38 × g and were weightless for about 9 min. Thirty-two monkeys flew in the American space program, each had only one mission. Numerous back-up monkeys also went through the programs but never flew. Monkeys from several species were used. In 1949 the rhesus monkey Albert II became the first monkey in space; however, he died during landing as a consequence of a parachute failure. The first animal orbiting the Earth was launched on November 3, 1957. The Soviet dog Laika, had been intended to die, as the Sputnik 2 satellite was not designed to be retrievable. The Russian scientists had planned to euthanize Laika with a poisoned serving of food after 10 days of space flight. Russian authorities had previously circulated reports that Laika survived in orbit for four days and then died due to oxygen starvation when the cabin overheated from a battery failure. The physiological variables that were monitored and telemetered back to Earth included electrocardiogram (chest lead), blood pressure, respiration rate, and motor activity.31 Prelaunch physiological parameters of Laika were normal, but pulse rate went up by a factor three at launch and at peak acceleration the respiration rate had increased three to four times above prelaunch values. At the start of weightlessness the pulse rate decreased to values near the prelaunch rate. However, it took three times longer than after a centrifuge ride on the ground to return to prelaunch values. Electrocardiogram traces also approached normal as the flight continued. However, telemetry showed that temperature and humidity in the dog cabin increased gradually. After 5–7 h into the flight no physiological parameters were transmitted and on the fourth orbit it was impossible to obtain any data on the condition of the dog. Postflight simulations
BIOSENSING AT THE INTERNATIONAL SPACE STATION
showed that Laika probably died on the third or fourth orbit, due to overheating, fear and stress. But that was enough to prove that a living organism could tolerate a long time in Apollo, and later in Skylab. Later animals were flown to investigate various biological processes and the effects microgravity and space flight might have on them. As of 2007, the national space programs of the United States, the Soviet Union, France, China and Japan have flown animals into space. Such missions, especially missions with “primate” astronauts, such as “Ham”, demonstrated the ability to perform tasks during spaceflight.
3.2
Humans as Whole-organism Sensors
The first humans in space, the Russian cosmonauts as well as the US astronauts, can be considered as test objects for analyzing space environmental factors. As the test animals before, space travelers were connected to measurement devices and data were transmitted to Earth.32 Nowadays, the conduction of these investigations has been facilitated by the HRF as part of the US laboratory Destiny.33 From the short-term space missions in the early era of space flight, acute effects were observed and future mission planning was derived from such information. Up to now, more than 400 humans of both sexes and different age traveled into space and were confronted with the two main risk factors, namely microgravity and radiation, for various periods of time. The longest single flight (438 days) was performed by cosmonaut Polyakov in 1995; Expedition-11 Commander Krikalev became the human with the most cumulative time in space with a total of 803 days, 9 h and 39 min in space, including eight EVA’s; and John Glenn became the oldest astronaut aged 77 years when flown the second time to space. Cosmonauts’ as well as astronauts’ physiological data were monitored during performance inside the spaceship and outside during EVA’s and analyzed nearly on-line after transmittance to Earth. Short-term effects induced by the state of weightlessness include “space sickness syndrome” which is very similar to seasickness or general travel sickness on Earth. The symptoms of normally disappear within a time span of a few hours up to five days. Changed hydrostatic pressure gradients
13
along the body axes cause a fluid shift within the body, and the input to the body’s many gravity receptors is altered significantly.34 A long-term effect and a severe medical problem is the loss of bone and muscle mass during longer stays under microgravity conditions, which is based on an adaptation of the body to the lack of gravity (Table 1). So far, investigations have shown, that humans loose about 10% bone mass during a one year stay on a space station under microgravity. As a result, the physical and mental performance of the person in orbit drops and the ability to fast readapt again to gravity decreases. Furthermore, the decrease of performance is accompanied by cardiac arrhythmia, especially during extra vehicular activities. It is not clear so far, which level of gravity is sufficient to prevent the described problems. The problem of potential hazard to astronauts from cosmic ray HZE particles became “visible”, when the astronauts of the Apollo 11 mission returning from the Moon, reported of light flashes, that is, faint spots and flashes of light at a frequency of 1 or 2 min−1 after some period of dark adaptation. These events were observed during trans–lunar coast, in lunar orbit, on the lunar surface, and during trans-earth coast. Evidently, these light flashes that were predicted by Tobias in 1952, result from HZE particles of cosmic radiation penetrating the spacecraft structure and the astronaut’s eyes and producing visual sensations through interaction with the retina. During the following six Apollo missions that carried the spacecraft outside the magnetic shielding of the Earth and on the Apollo–Soyuz Test Project (ASTP) in LEO as well as at ground-based accelerators, systematic observations demonstrated a variety of different types of flashes, such as thin short, or long streaks, double streaks, star like flashes or diffuse clouds, respectively, that were white in general. However, the pattern of types of flashes was different in LEO, in lunar missions, or at accelerators. In order to record the passage of HZE particles through the astronaut’s head and eyes and to correlate them with observed light flashes, a helmet-like device with nuclear emulsions was used by the crew of Apollo 16 and 17. This Apollo light flash moving emulsion detector (ALFMED) consisted of two sets of glass plates coated with nuclear emulsions, of which one set was fixed in position, whereas the second parallel located set was
14
BIOSENSOR APPLICATIONS
Table 1. A comparison of some space-related health concerns with medical issues on Earth
Research area
Space
Earth
Bone
Bone loss and increased fracture risk Increased kidney-stone formation Injury to soft connective tissue Postflight orthostatic intolerance Cardiac atrophy
Osteoporosis and other bone disorders
Cardiovascular
Performance/Sleep
Immunology/Infection
Muscle
Neurovestibular
Radiation effects
Orthostatic intolerance Heart disorders, such as sudden cardiac death due to heart rhythm disturbances
Heart rhythm disturbances Errors due to sleep loss and disruption of the biological clock Activation of dormant viruses in the body Increased infection risk Space flight-related anemia Interference with wound healing Muscle loss and atrophy
Space motion sickness and body orientation problems Re-entry vertigo Postflight dizziness, balance, posture and gaze stability Cancer
Sleep problems due to jet lag, shift work and extended work schedules Accidents due to sleepiness Immune system disorders Viral outbreaks due to stress conditions (shingles, cold sores) Anaemia and other blood disorders Muscle wasting diseases Muscle weakening due to prolonged bed rest, immobilization, nerve crush injury and ageing Vertigo and other balance disorders
Risks from exposure to naturally occurring and work-related radiation
Damage to central nervous system Cataracts and other diseases
moved at a constant rate of 10 µm s−1 for a total translation time of 60 min. Only in few cases the passage of an HZE particle through the astronaut’s eyes coincided with a light flash event. However, the number of HZE particles traversing the eyes of the astronaut during the translation period agreed with the total number of flashes observed during this period. Investigations on the frequency of visual light flashes in LEO and its dependence on orbital parameters were performed on Skylab 4, on ASTP and recently on MIR. The highest light flash rates were recorded when passing through the South Atlantic Anomaly (SAA). In this part of the orbit, the inner fringes of the inner radiation belts come down to the altitude of LEO which results in a 1000 times higher proton flux than in other parts of the orbit. These high light flash event rates during the SAA passages can be deduced either to the high proton fluxes or to the occurrence of some particles heavier than protons in the inner belts of trapped radiation. With the SILEY experiments on board of the space station MIR,35 two separate mechanisms for the induction of light flashes
were identified: a direct interaction of heavy ions with the retina causing excitation or ionization, and proton-induced nuclear interactions in the eye (with a lower interaction probability) producing knockout particles. Possible mechanisms for stimulating the retina could be electronic excitation resulting in UV radiation in the vicinity of the retina, ionization in a confined region associated with δ rays around the track, or shock wave phenomena when HZE particles pass through the tissue matrix.
3.3
Sensing Radiation for Human Protection in Space
Knowledge of the radiation situation inside of a space vehicle is mandatory for each mission under consideration and shall be based on inflight dosimetry data. Such measurements of radiation exposures (Figure 4) were performed during manned spaceflights at various altitudes, orbital inclinations, durations, periods during the solar cycle, and mass shielding, respectively.36
BIOSENSING AT THE INTERNATIONAL SPACE STATION
15
10
Effective dose (mSv/day)
<40° inclination 40− 60° inclination Deep space
1
0.1 1960
1970
1980
1990
2000
2010
Calendar year Figure 4. Effective doses, measured in low Earth orbit missions and missions to the Moon.
The deposition of energy by radiation strongly depends on the type of radiation under consideration, both macroscopically and microscopically. The contribution of the sparsely ionizing component of the radiation in space has been mostly determined by lithium fluoride thermoluminescence dosimeters (TLD), which “absorb” radiation dose by its valence electrons being excited to a higher energy state. The number of electrons at the higher energy state is directly proportional to the amount of ionizing radiation the crystal is exposed to. When the crystal is heated, these electrons fall back to their resting energy and emit photons, causing the crystal to glow. The emitted light intensity as a function of the temperature is called the glow curve. In a heating cycle the amount of emitted light, that is, the integral of the resulting glow curve, is proportional to the total dose received by the crystal since the last time it was heated (“annealed”). The sensitivity of TLDs is nearly constant in the energy range of interest. For densely ionizing radiation, the spatial pattern of energy deposition at the microscopical level is important. Their fluence has been mainly determined by use of plastic track detectors or nuclear emulsions. Plastic detectors are diallylglycol carbonate (CR39), cellulose
nitrate (CN) or polycarbonate (Lexan), covering different ranges of linear energy transfer (LET). The tracks of heavy ions are developed by etching; the track etching rate grows as a function of the LET. Plastic detectors allow determining the fluence, charge and LET spectrum of the heavy ions. These passive (in the sense that no power is needed during mission) dosimetry systems integrate over exposure time. Advantages are their independence of power supply, small size, high sensitivity, good stability, wide measuring range, and relatively low cost. However, long-duration space missions require time-resolved measurements, especially for protection purposes. This has been met by a small, portable, and spacequalified TLD reader suitable for repeated TLD readouts on board.37 In addition to passive dosimeters, active dosimeters have been developed to provide real-time dosimetry data. The measurement principle is based either on ionizations (e.g., ionization chamber, proportional counter, Geiger-M¨uller Counter, semiconductors, charged coupled devices (CCD)), or on scintillations (e.g., organic or inorganic crystals). A combination of two silicon detectors, the dosimetry telescope (DOSTEL), has been flown onboard of the Space Shuttle, the MIR station,
16
BIOSENSOR APPLICATIONS
and the ISS. Particle count rates, dose rates, and LET spectra were measured separately for GCR, the radiation belt particles in the SAA and SPEs.38 During human spaceflight a personnel dosimetry is required for each astronaut and separately for different activities, above all during EVA, when the astronauts are only shielded by the material of the space suit. A number of active devices such as small silicon detectors or small ionization chambers may be used but they need power and are difficult to design in sufficiently small dimensions. In most cases, passive integrating detector systems have been used, such as TLDs. However, these personal dosimetry systems provide only data on the “surface” or skin dose. In order to assess the depth dose distribution within the human body and especially at the most radiation sensitive organs, such as the brain, the blood forming organs, and the gonads, human phantoms are required equipped with different dosimetry systems at the sites of sensitive organs. The anthropomorphic phantom “MATROSHKA” was exposed for one year to the radiation in space outside of the ISS in order to determine the depth dose distribution of radiations within the human body during EVAs.39 Complementary to physical dosimetry, biological dosimetry systems have been developed and applied, which weigh the different components of environmental radiation according to their biological efficacy. They are especially important when interactions of radiation with other parameters of space flight, above all microgravity, may occur. Basically intrinsic biological dosimeters record the individual radiation exposure (humans, plants, animals) in measurable units; and extrinsic biological dosimeters/indicators that record the accumulated dose in biological model system. If applied in parallel with physical dosimetry, biological dosimetry systems can provide valuable complementary information because of reasons as follows: their ability to weigh the different components of environmental radiation according to their biological efficacy; their ability to give a record of the accumulated radiation exposure of individuals; their capacity to monitor the cumulative biological effects of all environmental stressors present; their high specificity; and their generally high sensitivity. Intrinsic biological dosimeters are for example, G0 lymphocytes, which respond to ionizing radiation with the expression of chromosome-type
aberrations such as polycentric and ring chromosomes. The frequencies of these aberrations are correlated with radiation dose and can therefore be used as a biological dosimeter. After long-term space flights, for example, on board of the MIR station,40 observed significantly elevated frequencies of chromosome-type aberrations with indications that the aberrations were radiation induced. The frequencies of dicentrics found in lymphocytes of MIR cosmonauts before and after their last space flight compared well with frequencies expected from doses of low and high-LET radiation to which they were exposed during flights. These data have also been used to predict the radiation risks of astronauts during interplanetary space missions. Another promising technique is premature chromosome condensation (PCC) that allows interphase chromosome painting and the detection of nonrejoining chromatin breaks without going though the first mitosis. This method is especially relevant for biological dosimetry for astronauts that are exposed to high doses of high-LET radiation in space, which may induce interphase death and cell cycle delay. In addition to chromosomal aberrations, other intrinsic biomarkers for genetic or metabolic changes may be applicable as biological dosimeters, such as germ line minisatellite mutation rates or radiation induced apoptosis, metabolic changes in serum, plasma, or urine (e.g., serum lipids, lipoproteins, ratio of HDL/LDL cholesterol, lipoprotein lipase activity, lipid peroxides, melatonin, or antibody titers), hair follicle changes and decrease in hair thickness, triacylglycerol concentration in bone marrow and glycogen concentration in liver. Whereas the first three systems mentioned are noninvasive or require only blood samples for analysis, the latter systems are invasive and therefore appropriate for radiation monitoring in animals only. Dose response relationships have been described for most of the intrinsic dosimetry systems, yet their modification by microgravity remains to be established. 3.4
The ISS as Test Bed for Development and Validation of Biomonitors for Human Space Flight Activities and Earth-bound Applications
In the initial phase of human space flight, engineers, and scientists did not work closely together.
BIOSENSING AT THE INTERNATIONAL SPACE STATION
Engineers had concentrated on construction and operations work and most scientists had preferred to have their experiments ride aboard NASA’s unmanned satellites. When it became clear in 1963, that the Gemini vehicle did not completely use its room capacity, a chance to set up an experiments program in orderly fashion was seized. Accordingly, more than 600 scientists were invited to send proposals for space experiments. With the establishment of the NASA Manned Space Flight Experiments Board in January 1964 science gained a permanent foothold in manned space flight operations. By the fourth Gemini flight—the second manned—experiments and principal investigators had been worked into mission operations with fair success; by the last flight, procedures had been sharpened sufficiently for the board to continue in Apollo, and later in Skylab. The ISS seems to be ideally suited as a technology test bed and an opportunity for verification and space qualification.41 In the past, technology development suffered under the lack of flight opportunities. Initial experiments will consist of exposing materials, components, mechanisms, new sensors, spacecraft subsystems, etc. to the environment of space. In the preparatory phase of the Columbus multi-user facility for all four major microgravity research disciplines, namely materials science, fluid physics, biology, and human physiology became integrated in the design and developmental process of the ISPRs and the relevant user communities were actively involved in all reviews of these facilities. 3.4.1 The BIOLAB Facility aboard COLUMBUS
The Biolab is a biological research facility that will be a major contributor to the scientific capabilities of the European Columbus laboratory (Figure 5). It is designed to support biological experiments on micro-organisms, cells, tissue cultures, small plants, and small invertebrates. The effect of gravity on biological samples has been one of the most important areas of research on numerous space missions. The major objective of performing Life Sciences experiments in space is to identify the role that microgravity plays at all levels of an organism, from the effects on a single cell up to a complex organism including humans. The
17
Biolab facility is integrated into an ISPR that will be launched inside Columbus on ISS flight 1E. Prepared standard experiment containers (ECs) and vials will be transported separately within the multi-purpose logistics module (MPLM), a cargo carrier that is located inside the Space Shuttle cargo bay, or other available transport means such as the European automated transfer vehicle (ATV), Russian Progress vehicles or the Shuttle’s middeck lockers.42 After manual loading by the crew, all activities are automatic in the core unit on the left side of the Biolab. This drastically reduces the demand on crew time. The manual section (right side) is mainly for sample storage and specific crew activities. The main element of the core unit is the large incubator, a thermally controlled volume where the experiments take place. The incubator’s thermal housing has been built by Ferrari, using masssaving composite materials derived from Formula 1 racing technology. Inside the incubator are two centrifuges that can each hold up to six ECs and be independently spun to generate artificial gravity in the range from 10−3 to 2 g. Both are very precisely balanced, to avoid disturbing the space station’s microgravity environment. On top of the incubator, a drawer supports the handling mechanism, the automatic stowage (ambient and temperature-controlled) units and the two analysis instruments (a microscope and a spectrophotometer).43 The handling mechanism is the key element of Biolab’s automation, providing automatic operations such as insertion into the analysis instruments for immediate, in situ analysis. This handling mechanism can also place samples in the automatic stowage units for preservation or further analysis later. Biolab’s manual section carries a laptop for crew control, two temperature-controlled units (TCUs) for sample storage and a BioGlovebox (BGB). The TCUs are cooler/freezers (+10◦ to −20 ◦ C) for storing larger items and ECs. To minimize mass, the TCU skeleton is made of carbon fiber reinforced plastics on which layers of aluminized kapton as an infrared radiation barrier are glued. Taking advantage of the lack of convection in microgravity, the air between the layers also acts as thermal insulation. The BGB is a safe cabinet for handling toxic materials (such as the fixatives used to terminate biology experiments) and delicate biological samples that must
18
BIOSENSOR APPLICATIONS
(b)
(c)
(a) g vector
(d) Figure 5. Biolab—one of the payloads racks that will fit inside Columbus. Biolab’s right side is devoted to manual elements (a), such as the protruding BioGlovebox (b), while the left side houses the automated units, such as the incubator containing the centrifuge (c). A Biolab Experiment Container (d) with three sample vials. The large cylinder at right is part of the performance verification hardware in this test version.
be protected against contamination by the space station environment. An ozone generator ensures sterilization of the BGB working volume. This generator was developed specially for Biolab but it could also become a useful spin-off on Earth, where, for example, it could be used for sterilizing dental equipment. The ECs are basically “empty boxes”, with standard interfaces to Biolab that carry the biological samples.44 Scientists need to concentrate only on the experiment hardware contained by the EC, with an available volume of 60 × 60 × 100 mm3 . The biological samples, together with their ancillary items are transported from the ground to Biolab, either within the ECs or in small vials. The latter case will apply if the samples require storage prior to use, in the minus eighty laboratory freezer for ISS (MELFI). In orbit, astronauts will manually insert the ECs into Biolab for processing. A frozen sample will
first be thawed out in the experiment preparation unit (EPU) and then installed inside the BGB.45 Once this manual loading is accomplished, the automatic processing of the experiment can be initiated by a crew member. The experiments are undertaken in parallel on a 0 and a 1 g centrifuge respectively. The latter provides the flight reference experiment, while the ground reference experiment is performed at the facility responsible centre. During processing of the experiment, the facility handling mechanism will transport the samples to the facility’s diagnostic instrumentation, where, through tele-operations, the scientist on the ground can actively participate in the preliminary in situ analyses. Typical experiment durations range from 1 day to 3 months. The facility responsible centre for the Biolab facility will have the overall responsibility of operating it according to the needs of individual EC providers.
BIOSENSING AT THE INTERNATIONAL SPACE STATION
The individual EC providers could monitor the processing of their experiments from their user home bases. The selection, definition, and development phases of a Life Sciences flight research experiment have been consistent throughout the past decade. The implementation process is driven primarily by the shift from highly integrated, dedicated research missions on platforms with welldefined processes to self-contained experiments with stand-alone operations on platforms, which are being concurrently designed. For experiments manifested on the ISS or on short duration missions, the more modular, streamlined, and independent the individual experiment is, the more likely it is to be successfully implemented before the ISS assembly is completed. During the assembly phase of the ISS, science operations are lower in priority than the construction of the station. After the station has been completed, it is expected that more resources will be available to perform research. The complexity of implementing investigations increases with the logistics needed to perform the experiment. Examples of logistics issues include: hardware unique to the experiment; large up and down mass and volume needs; access to crew and hardware during the ascent or descent phases; maintenance of hardware and supplies with a limited shelf life; baseline data collection schedules with lengthy sessions or sessions close to the launch or landing; onboard stowage availability, particularly cold storage; and extensive training where highly proficient skills must be maintained. As the ISS processes become better defined, experiment implementation will meet new challenges due to distributed management, on-orbit resource sharing, and adjustments to crew availability preand post increment.46
3.4.2 The ESA Topical Team on Biomonitors
Research in Space Life Sciences has evolved rapidly through several stages. The first objective of this research was oriented toward the survival and safety of the crew. When the progress of technology made access to space easier, spaceflight, and especially microgravity became a real tool for research. Nowadays, well-controlled experiments are paving the way for consolidated research in Space Life Sciences as well as in other sciences.
19
In order to optimize the research outcome of these experiments, ESA’s Life Sciences Working Group and the Microgravity Advisory Committee identified so-called focused science topics. These topics were chosen because they are the most promising research areas and in order to stimulate collaborative research initiatives. ESA is encouraging and actively supporting the teaming-up of European scientists from life sciences, biotechnology, and physical sciences, who all share a common interest in performing experiments under microgravity conditions using the ISS, other carriers, or ground facilities. Such topical teams (TT) comprise researchers from academia and industry who are already actively involved in space experiments, as well as scientists who are presently not yet involved in space research. Topical Team meetings are an excellent forum for discussing international cooperation in space research with scientists within and beyond the European borders. TT have been created in different fields of Life Sciences research using space environment. Their tasks are spread over the support of hardware concepts, their development, and adequate use, the promotion of coordination, collaboration, and cooperation, definition of control experiment, promotion of applications, ground research, and promotion of space research by education. TT will also define the objectives of the future research in space environment by identifying innovative high-priority research areas. The following TT in the fields of biotechnology are presently active: the Biomonitors TT, the Controlled Tissue Development TT, the Gas Liquid Transfer TT, the Microencapsulation TT, the Nutrition TT, the Tissue, and Cell Engineering TT, and the Preservation of Samples TT. In 1999 the Biomonitors TT came together at first, aiming to identify the potential of the innovative biotechnology research area within a space application program. It assesses environmental factors of potential risks that can be addressed by biomonitoring systems, especially by systems that respond to the gravity stress, to confinement, and/or to an increased level of radiation. Such external biomarkers should complement the spectrum of physical instruments and devices, since biological systems are capable of weighting the effects, which space environments of differing
20
BIOSENSOR APPLICATIONS
complexities exert on living beings. From the planetary protection point of view biomarkers and biosensors would have the potential to add considerable value to the analysis of the bioburden of spacecrafts and spacecraft assembly facilities. In such artificial environments micro-organisms, if they withstand the controlled environmental conditions in the clean rooms, are expected to be the source of biological contaminations for spaceships and as a consequence for other planets. Accordingly, environmental monitoring for life-related compounds and factors plays an important role in defining and managing the risks to artificial ecosystems on other planets from biological contaminations. Complementary to currently available physical and chemical monitoring techniques, the use of biomarkers as well as of biosensors has the potential of recognizing the composition of microbial communities in closed systems.
3.4.3 Biotechnology for the ISS
Since the days of Mercury flights, astronauts have been connected to myriad electronic sensors that monitor their vital signs. Some astronauts are wired with electrodes, while some sensors might even be swallowed. However, nanotechnology inspired biosensors may change that, making spacecraft like the space shuttle simpler, safer, and more efficient operations. The creation of nanodevices such as nanobots capable of performing diagnostic or therapeutic functions in vivo is a destination within the emerging field of nanomedicine. Significant technological advances across multiple scientific disciplines, including miniaturization of analytical tools, led to the development of 3-D nanobot spheres. After being injected into the blood stream of an astronaut, the inexpensive sensor would be phagozytosed by macrophages or taken up into lymphocytes by receptor-controlled transport where it would monitor vital or death signals, for example, the presence of a virus or the expression of apoptosis related proteins. Such selfdestructing cells express particular markers proteins, the CD-95 receptors, which can be tagged by specific antibodies delivered by the nanobots. By coupling with light-emitting reporter molecules, such tagged cells would be counted as they flow through capillaries beneath the eardrum by a tiny laser which is shaped like a hearing aide and is
inserted in the astronaut’s ear. A wireless link would relay the data to the spaceship’s main computer for further processing. This scenario is at least 15 years away; however, many of the necessary pieces are already taking shape in the laboratory.47 DNA sequence biosensors for the detection of life signs are currently being developed as alternatives to conventional DNA microarrays and can be used to verify presence or absence of life signs on spaceship surfaces or in habitats. In the endeavor to develop a method significantly more rapid and sensitive than microarrays, most biosensors are at the proof-of-principle stage and only few are now in use as laboratory tools. The biosensor for DNA sequence detection relays on the molecular recognition event of a known probe with its counterpart directly on the surface of an active signal transducer. The most sensitive and functional technologies use fiber optics or electrochemical sensors in combination with DNA hybridization. Biosensors with single-molecule resolution represent an evolution of these systems, and may be the next generation of DNA sequence biosensors.48 Monitoring the environment for compounds and factors of concern plays an important role in defining and managing the risks to humans and ecosystems resulting from physical, chemical and biological contamination of the environment. Biological monitoring represents a relatively new branch in biotechnology with a worldwide rapidly growing market. Trends in biomonitoring are distinguished by miniaturization, implementation of new functions and cost-effective production. However, at present, only few devices have reached the state of standard environmental monitoring equipment. Therefore, it is expected, that the development of biomonitoring systems for applications in space will be performed concomitantly with the development of biomonitoring systems for routine applications on Earth. The unique monitoring challenges presented by the ISS and the demand for high reliability of space technology will be a driver in the development of multifunctional biological monitoring systems for a wide range of applications in space and on Earth. Complementary to currently available physical and chemical monitoring techniques, bioanalytical methods and the use of biosensors as well as internal and external biomarkers have the potential of providing solutions to a number of environmental problems.
BIOSENSING AT THE INTERNATIONAL SPACE STATION
Matters of concern are of global as well as of local nature and include closed habitats, such as given by the ISS as well as future extraterrestrial habitats accommodating artificial ecosystems for bioregenerative life support purposes. Several of such biomonitoring systems suitable for applications in the ISS are based on gene expression, signal transduction, immune responses, and cell metabolisms. A step in this direction is the space experiment TRIPLE LUX (Gene, immune, and cellular responses to single and combined space flight conditions), which has been selected by ESA to be performed during the first increment of Biolab. The principal investigator and several co-investigators are members of the Biomonitors TT. The SOS-Lux-toxicity test, as part of the TRIPLE-LUX project will provide an estimation of the health risk resulting from exposure of astronauts to the radiation environment of space in microgravity. The bacterial biosensor, developed at the German Aerospace Center (DLR), consists of recombinant bacteria are transformed with the pBR322-derived plasmid pPLS-1 carrying the promoterless lux operon of Photobacterium leiognathi as the reporter element controlled by a DNA damage-dependent SOS promoter as sensor element. The SOS-Lux-test indirectly monitors the kinetics of DNA damage-processing in the SOS system by measuring the luminescence emitted by the genetically altered bacteria. This system enables performing the test from radiation to data acquisition in microgravity, and therefore the estimation of the effect of the combination of space radiation and microgravity on the living cell, and particularly on the DNA damage repair system. Absorption is measured to provide data for the correction of a growth-related luminescence increase and for the detection of cytotoxicity. Automation and on-line data registration as early as 2 h after the test start satisfy minimal crew time requirements and make this test applicable for use on the ISS. During genotoxicity measurement campaigns, in comparison with other genotoxicity tests, the test proved its reliability, and low genotoxicity detection limit, as well as its short response time, in double-blind tests.49 A similarly designed biosensors for toxicity measurements uses brewer’s yeast Saccharomyces cerevisiae modified with the jellyfish gene coding for green fluorescent protein (GFP) as a reporter
21
for the DNA damage-induced gene RAD54. A measure of the reduction in cell proliferation is used to characterize general toxicity. Biosensors like these have already found use in fields such as environmental monitoring, and even chemical weapons detection. This biosensor, codenamed FORRAY (fluorescence orbital radiation risk assessment using yeast), was send to space with expedition 9 in the spring of 2004 launching from the Russian Space Agency’s launch site with a Soyuz rocket. For the experimental period of six days, the astronauts pressed a plunger every day, thereby mixing millions of dormant yeast cells with nutrients, forcing them into two compartments: one exposed to the damaging space radiation, and one shielded by aluminum. After return to Earth, the cellular fluorescence in the exposed and unexposed yeast samples was measured allowing them to link radiation levels to DNA damage. The same yeast, trademarked as “GreenScreen”, is used by the University of Manchester Institute of Science and Technology (UMIST) spin out company Gentronix Ltd in products designed to detect potential DNA damaging agents in drug development and environmental samples.50 Because space research sheds light on the fundamental effects of gravity on tissue formation and development, continued cell culture research aboard the ISS will allow scientists to refine Earth-based biomedical techniques. By using space-based experimental platforms as a model, basic research will add valuable information to biomedicine and environmental sciences. A biomonitoring system, based on the use of mammalian cells is the space experiment “Cellular Responses to Radiation in Space” (CERASP).51 At the Radiation Biology Department of the German Aerospace Center (DLR), mammalian cell systems were developed as reporters for cellular signal transduction modulation by genotoxic environmental conditions. The space experiment CERASP to be performed at the ISS will make use of reporter cell lines thereby supplying basic information on the cellular response to radiation applied in microgravity. One of the biological endpoints will be survival reflected by radiationdependent reduction of constitutive expression of the Enhanced variant of Green Fluorescent Protein (EGFP). A second endpoint will be gene activation by space flight conditions in mammalian
22
BIOSENSOR APPLICATIONS
cells, based on fluorescent promoter reporter systems using the destabilized d2EGFP variant. The promoter element to be investigated reflects the activity of the nuclear factor kappa B (NF-κB) pathway. The NF-κB family of proteins plays a major role in the inflammatory and immune response, cell proliferation, and differentiation, apoptosis, and tumor genesis. Results obtained with X-rays and accelerated heavy ions produced at the French heavy ion accelerator GANIL (Grand Accelerateur National d’ Ions Lourds) imply that densely ionizing radiation has a stronger potential to activate NF-κB dependent gene expression than sparsely ionizing radiation. The correlation of NF-κB activation to negative regulation of apoptosis could favor survival of cells with damaged DNA. A third endpoint to be examined will be DNA damage induced by combined exposure to radiation and microgravity and its repair. The nematode Caenorhabditis elegans has been proposed as a whole organism experimental system for behavior and longevity studies in space due to its relative simplicity, short generation cycle, and life span. A miniaturized compact device for cultivating nematode worms in a microfluidic environment and monitoring them using shadow imaging was designed. It consists of a polycarbonate micro culture chamber with a volume of 4 µl, enabling gas exchange through a permeable membrane forming the top of the chamber. Images are acquired with a complementary metal-oxide semiconductor (CMOS) video camera chip attached to the bottom of the micro chamber. As an alternative to video acquisition, the filtered video output signal is used to determine worm activity, yielding a system that allows image acquisition in combination with a low-bandwidth activity measurement. Until now, five Space Shuttle missions have carried C. elegans experiments, but high cost and limited availability of space shuttles has led to the efforts to use satellites as a launch platform. Using the described system, the activity of C. elegans as a function of temperature was measured. Data obtained by manual counting of worm strokes and the video signal showed good correlation. The first demonstration of maintaining and monitoring C. elegans in a micro fluidic environment52 makes the system attractive for research at the ISS.
3.5
Future Perspectives
NASA embodies the human spirit’s desire to discover, to explore, and to understand. The Space Shuttle and ISS are not viewed as ends in themselves, but the means to achieving the broader goals of the nation’s space program. Transportation and orbital facilities support and enable our efforts in science, exploration, and enterprise. As NASA defines and expands its goals and objectives for long-duration exploration of space, interest in genetics, cell, and molecular biology have become key and critical topics. Increasingly, the capability to perform autonomous, in situ acquisition, preparation and analysis of biological samples and specimens to determine the presence and composition of biological components is required for both space biology and medical researchers. Technology developments and advances are needed to support applications across all of the relevant technology application areas, including bioastronautics, fundamental biology, and astrobiology. Biological and biomolecular as well as genomic research is enabling unprecedented insight into the structure and function of cells, organisms, and subcellular components and elements, and a window into the inner workings and machinations of living things. Triggered by advances in microelectronics and related areas, we are now able to fabricate and construct devices and components such as sensors, actuators, machines, motors, valves, switches, pumps, and other items on the same scale as the biological targets of interest, even in some cases on the order of tens of nanometers in size. This directly scaled relationship allows for new strategies and interactions between physical devices and living systems. These techniques and technologies have permitted the emergence of a new class of instruments and devices, generally described as mesoscale technologies. Many devices, techniques, and products are now available or emerging, which allow measurement, analysis, and interpretation of the biological composition at the molecular level, and which permit determination of DNA/RNA and other analytes of interest. Finally, advances in information systems and technologies, and bioinformatics, provide the capability to understand, simulate, and interpret the
BIOSENSING AT THE INTERNATIONAL SPACE STATION
large amounts of complex data being made available from these biological–physical hybrid systems. These synergistic relationships facilitate the development of revolutionary technologies in many areas, and bode well for the future of space biology research objectives. It is evident that, biomonitors and biomedical sensors will keep improving. They will get a great, in many cases even vital, contribution to astronaut health. The biosensors, as being an integral part of biomedical devices, will continue to be a prosperous market segment. This suggests an everevolving trend coupled along with innovation. The biomedical sensors are also suitable and applicable for a broad spectrum of monitoring purposes in risky environments in space as well as on Earth.
REFERENCES 1. G. S. Titov, Preparation and results of a 24-hour orbital flight. Life Science Space Research, 1963, 1, 128–140. 2. J. P. Loftus, Historical overview of NASA manned spacecraft and their crew stations. Journal of the British Interplanetary Society, 1985, 38, 354–370. 3. C. A. Berry, Medical legacy of Apollo. Aerospace Medicine, 1974, 45, 1046–1057. 4. N. L. Johnson, Military and civilian Salyut space programmes. Spaceflight, 1979, 21, 364–370. 5. J. H. Disher, Manned space stations—a perspective. Earth-Oriented Applications of Space Technology, 1982, 2, 167–177. 6. F. Sietzen, Mir: resting in peace. Aerospace America, 2001, 39, 36–43. 7. H. Binnenbruck, H. W. Gronert, and C. Nitzschke, Mir 92 project. Space Technology, 1993, 13, 205–208. 8. R. D. Andresen and R. Domesla, The euromir missions. European Space Agency Bulletin, 1996, 88, 6–12. 9. J. Oberg, Shuttle-Mir’s lessons for the international space station. IEEE Spectrum, 1998, 35, 28–37. 10. L. David, International space station: becoming a reality. Aerospace America, 1999, 37, 1–15. 11. J. D. F. Bartoe and L. Fortenberry, One year old and growing: a status report of the international space station and its partners. Acta Astronautica, 2000, 47, 589–597. 12. J. Grey, Columbia—aftermath of a tragedy. Aerospace America, 2003, 41, 26–29. 13. F. Culbertson, A tour of the ISS. Acta Astronautica, 2004, 54, 793–797. 14. S. R. Morrissey, Completing the station. Chemical and Engineering News, 2006, 84, 28. 15. G. H. Kitmacher, W. H. Gerstenmaier, J. D. F. Bartoe, and N. Mustachio, The international space station: a pathway to the future. Acta Astronautica, 2005, 57, 594–603.
23
16. N. R. Pellis and R. M. North, Recent NASA research accomplishments aboard the ISS. Acta Astronautica, 2004, 55, 589–598. 17. H. Kozawa, Japanese ISS program involvement. Acta Astronautica, 2004, 54, 787–788. 18. A. Thirkettle, B. Patti, P. Mitschdoerfer, R. Kledzik, E. Gargioli, and D. Brondolo, ISS: Columbus. European Space Agency Bulletin, 2002, 109, 27–33. 19. G. Reibaldi, R. Nasca, H. Mundorf, P. Manieri, G. Gianfiglio, S. Feltham, P. Galeone, and J. Dettmann, The ESA payloads for Columbus—a bridge between the ISS and exploration. European Space Agency Bulletin, 2005, 122, 60–70. 20. B. Patti, R. Chesson, and M. Zell, A thirkettle, columbus: ready for the international space station. European Space Agency Bulletin, 2005, 121, 46–51. 21. G. Horneck, R. Facius, M. Reichert, P. Rettberg, W. Seboldt, D. Manzey, B. Comet, A. Maillet, H. Preiss, L. Schauer, C. G. Dussap, L. Poughon, A. Belyavin, G. Reitz, C. Baumstark-Khan, and R. Gerzer, Humex, a study on the survivability and adaptation of humans to long-duration exploratory missions, Part I: Lunar missions. Advances Space Research, 2003, 31, 2389–2401. 22. G. Horneck, R. Facius, M. Reichert, P. Rettberg, W. Seboldt, D. Manzey, B. Comet, A. Maillet, H. Preiss, L. Schauer, C. G. Dussap, L. Poughon, A. Belyavin, G. Reitz, C. Baumstark-Khan, and R. Gerzer, Humex, a study on the survivability and adaptation of humans to longduration exploratory moissions, Part II: missions to mars. Advances Space Research, 2006, 38, 752–759. 23. P. Webb, The space activity suit: an elastic leotard for extravehicular activity. Aerospace Medicine, 1968, 39, 376–383. 24. A. G. Kousnetzov, Some results of biological experiments in rockets and Sputnik II. Journal of Aviation Medicine, 1958, 29, 781–784. 25. H. J. von Beckh, Human Reactions during flight to acceleration preceded by or followed by weightlessness. Aerospace Medicine, 1959, 30, 391. 26. A. C. Fisher, Aviation Medicine on the Threshold of Space, National Geographic, 1955, 108, 241–278. 27. D. G. Simons, Review of biological effects of subgravity and weightlessness. Jet Propulsion, 1955, 25, 209–211. 28. W. N. Spjeldvik, S. Bourdarie, and D. Boscher, Towards multi-dimensional space weather modeling for energetic oxygen ions in the earth’s inner magnetosphere: equilibrium configuration. Advances Space Research, 2002, 30, 2839–2842. 29. D. F. Smart and M. A. Shea, The local time dependence of the anisotropic solar cosmic ray flux. Advances Space Research, 2003, 32, 109–114. 30. G. D. Badhwar and P. M. O’Neill, Long-term modulation of galactic cosmic radiation and its model for space exploration. Advances Space Research, 1994, 14, 749–757. 31. J. B. West, Historical aspects of the early Soviet/Russian manned space program. Journal Applied Physiology, 2001, 91, 1501–1511. 32. H. S. Fuchs, Hypertension and orthostatic hypotension in applicants for spaceflight training and spacecrews: a review of medical standards. Advances in Space Research, 1983, 3, 199–204.
24
BIOSENSOR APPLICATIONS
33. J. J. Uri and C. P. Haven, Accomplishments in bioastronautics research aboard international space station. Acta Astronautica, 2005, 56, 883–889. 34. R. J. White and M. Averner, Humans in space. Nature, 2001, 409, 1115–1118. 35. M. Casolino, V. Bidoli, A. Morselli, L. Narici, M. P. De Pascale, P. Picozza, E. Reali, R. Sparvoli, G. Mazzenga, M. Ricci, P. Spillantini, M. Boezio, V. Bonvicini, A. Vacchi, N. Zampa, G. Castellini, W. G. Sannita, P. Carlson, A. Galper, M. Korotkov, A. Popov, N. Vavilov, S. Avdeev, and C. Fuglesang, Dual origins of light flashes seen in space. Nature, 2003, 422, 680. 36. G. Reitz, Space radiation dosimetry. Acta Astronautica, 1994, 32, 715–722. 37. I. Ap´athy, S. Deme, I. Feh´er, Y. A. Akatov, G. Reitz, and V. V. Arkhanguelski, Dose measurements in space by the Hungarian Pille TLD system. Radiation Measurements, 2002, l35, 381–391. 38. R. Beaujean, J. Kopp, S. Burmeister, F. Petersen, and G. Reitz, Dosimetry inside MIR station using a silicon detector telescope (DOSTEL). Radiation Measurements, 2002, 35, 433–438. 39. J. Dettmann, G. Reitz, and G. Gianfiglio, MATROSHKAThe first ESA external payload on the international space station. Acta Astronautica, 2007, 60, 17–23. 40. G. Obe, I. Johannes, C. Johannes, K. Hallmann, G. Reitz, and R. Facius, Chromosomal aberrations in blood lymphocytes of astronauts after long-term space flights. International Journal of Radiation Biology, 1997, 72, 726–734. 41. S. A. Voels and D. B. Eppler, The international space station as a platform for space science. Advances in Space Research, 2004, 34, 594–599. 42. A. Petrivelli, The ESA laboratory support equipment for the ISS. European Space Agency Bulletin, 2002, 109, 35–54. 43. E. Brinckmann, New facilities and instruments for developmental biology research in space. Advances in space biology and medicine, 2003, 9, 253–280.
44. E. Brinckmann, ESA hardware for plant research on the international space station. Advances in Space Research, 2005, 36, 1162–1166. 45. E. Brinckmann, BIOLAB, EPU and EMCS for cell culture experiments on the ISS. Journal of Gravitational Physiology, 2004, 11, 67–74. 46. L. J. Miller, C. P. Haven, S. G. McCollum, A. M. Lee, M. R. Kamman, D. K. Baumann, M. E. Anderson, and M. C. Buderer, The international space station human life sciences experiment implementation process. Acta Astronautica, 2001, 49, 3–10. 47. E. S. Kawasaki and A. Player, Nanotechnology, nanomedicine, and the development of new, effective therapies for cancer. Nanomedicine: Nanotechnology, Biology and Medicine, 2005, 1, 101–109. 48. W. Vercoutere and M. Akeson, Biosensors for DNA sequence detection. Current Opinion in Chemical Biology, 2002, 6, 816–822. 49. E. Rabbow, N. Stojicic, D. Walrafen, C. BaumstarkKhan, P. Rettberg, D. Schulze-Varnholt, M. Franz, and G. Reitz, The SOS-LUX-TOXICITY-test on the international space station. Research in Microbiology, 2006, 157, 30–36. 50. A. W. Knight, P. O. Keenan, N. J. Goddard, P. R. Fielden, and R. M. Walmsley, A yeast-based cytotoxicity and genotoxicity assay for environmental monitoring using novel portable instrumentation. Journal of Environmental Monitoring, 2004, 6, 71–79. 51. C. E. Hellweg, M. Thelen, A. Arenz, and C. BaumstarkKhan, The German ISS-experiment cellular responses to radiation in space (CERASP): the effects of single and combined Space Flight Conditions on Mammalian Cells. Advances in Space Research, 2007, in press, doi:10.1016/j.asr.2006.11.015. 52. D. Lange, C. W. Storment, C. A. Conley, and G. T. A. Kovacs, A microfluidic shadow imaging system for the study of the nematode Caenorhabditis elegans in space. Sensors and Actuators B, 2005, 107, 904–914.
81 Life Detection within Planetary Exploration: Context for Biosensor and Related Bioanalytical Technologies David C. Cullen1 and Mark R. Sims2 1
Cranfield Health, Cranfield University, Silsoe, UK and 2 Department of Physics and Astronomy, University of Leicester, Leicester, UK
1 INTRODUCTION
Are we the unique example of life in the universe? If given appropriate conditions, is the emergence of life commonplace throughout the universe? These are fundamental questions for humanity and ones whose answers would be at the pinnacle of discoveries within human history to date. Biosensors, biochips, and other bioanalytical technologies have an emerging role in attempting to answer these questions due to their proposed inclusion as instruments on rover missions to the planet Mars. Mars is a focus as it is one of the best candidates within the solar system as a possible abode of life either now or in the past. Here the sensors would be used as part of a suite of complementary analytical instruments to search for molecular evidence of ancient and current life in the Martian environment. Finding evidence of life on Mars could indicate that life here on Earth is not necessarily unique and therefore potentially widespread within the universe. This chapter’s authors are the lead investigators for a project to develop an antibody microarraybased instrument called SMILE (Specific Molecular I dentification of Life Experiment) and more generically termed the life marker chip (LMC) instrument. This instrument has been selected into
the baseline instrument payload for the European Space Agency’s (ESA) ExoMars rover mission1 ; a mission scheduled for launch in 2013. The development of the LMC is at an early stage and therefore this chapter will focus on describing (i) a brief scientific case for life on Mars, (ii) the analytical targets this implies, (iii) previous approaches to in situ life detection on Mars, (iv) the environmental, system-level, and regulatory constraints that all impact upon the design of biosensor and bioanalytical technology intended for such applications, and (v) an overview of the biosensor approaches being taken in the development of suitable instruments. The goal of the chapter is therefore to inform the biosensor and biochip community of the unique challenges that planetary exploration applications offer and encourage others within this community to consider these challenges. It is anticipated that addressing the challenges may produce solutions that will also benefit and advance biosensor technology for more routine Earth applications. 2 LIFE AND ORGANICS IN THE SOLAR SYSTEM
To place into context the requirement for in situ analytical techniques such as biosensors and
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
related bioanalytical technologies for life detection in planetary exploration, a brief overview of the science case for life elsewhere in the solar system is given. 2.1
Formation of the Solar System
The current view of the formation of the solar system is summarized as follows.2 The solar system initially formed approximately 4.6 Gyr ago over a period of approximately 100 Myr by the gravitational collapse of a dense molecular cloud. The gravitational collapse resulted in the formation of the early Sun, which heated the associated protoplanetary disk. The heating in the inner parts of the protoplanetary disk only allowed the condensation of refractory materials—metals and minerals—from the original materials of the molecular cloud. The rocky terrestrial planets, including Earth and Mars, eventually formed from the refractory-material-rich inner regions of the protoplanetary disk. Other gases were cleared from the inner early solar system by the Sun’s solar wind and UV radiation effects to the outer and cooler parts of the solar system. Here the gas giant planets formed and beyond which the icy bodies (comets, dwarf planets, etc.) of the Oort cloud and Kuiper belt came to reside. The refractorymaterial-rich asteroid belt was formed due to the gravitational influence of Jupiter. It is thought that the gravitational driven evolution of the solar system resulted in the migration of the orbits of the gas giants, which disturbed the asteroid belt and the Oort cloud about 4.1–3.8 Gyr ago.3 This resulted in bodies from these regions, asteroids, and comets, being placed into eccentric orbits that crossed the inner solar system resulting in a large increase in the rate of impact events on the terrestrial planets. This has been termed the Late Heavy Bombardment period and would have delivered significant levels of volatiles such as water and organics to early Earth, Mars, and Venus as well as possibly providing planetary wide sterilization events for any early surface or nearsurface emerging life. 2.2
Abiotic Organics in the Solar System
The initial input of organic material to the protosolar nebula comprised material synthesized in
the interstellar medium and the molecular cloud from which the solar system formed. Subsequent processing of the material depended upon its position within the nebula and ensuing protoplanetary disc and may have included thermal and aqueous processing—the latter heated in water-rich planetesimals and asteroids.4 The present evidence for such abiotically produced material is from meteorites. Some classes of meteorites—the carbonaceous chondrites—contain significant levels of solvent extractable organic material; up to 10% by weight and with polyaromatic hydrocarbons dominating this. The wide range of molecules detected in such classes of meteorites5 includes amino acids at the tens of parts per million level and purines and pyrimidines at around the parts per million level. For amino acids, over 70 types have been identified, all without any appreciable chiral excess and with a structural population distribution different from the biotic amino acids on Earth. As explained above, early Earth and other terrestrial planets would have most likely received a significant input of organics from extraterrestrial objects during the Late Heavy Bombardment period.6 Such abiotic organic material is still being delivered to all the planets via micrometeorites (derived from interplanetary dust particles) and for Mars at present an estimated 240 tonnes per annum is being delivered.7 The possible detection of such abiotic organic material needs to be considered in any Martian life detection experiment.
2.3
Venus, Earth, and Mars
During the early evolution of the three outer terrestrial planets it is known for Earth, highly likely for Mars, and possible for Venus, that each had epochs or episodic periods with significant bodies of liquid water present. Additionally, the early organic molecular inventory of the three planets are expected to have been broadly similar—a combination of outgassed material from the planetary interiors and delivery of exogenous materials by impactors. This inventory will have been further developed by geochemical, atmospheric, and thermal processing. It is therefore possible that environments conducive to the emergence of life—i.e., liquid water and a complex inventory of organics—were present on all three planets.
LIFE DETECTION WITHIN PLANETARY EXPLORATION
However the subsequent evolutions of the three planets from such early periods differ markedly. Earth has maintained a relatively stable environment suitable for the continuous presence of life since as early as 3.8 Gyr ago (see Section 2.4.1) and possibly much earlier. Active plate tectonics has resurfaced much of Earth so that it is extremely difficult to find unprocessed rocks from the early Earth that harbor evidence of very early life. Venus has evolved a runaway greenhouse effect such that the current surface temperature (> 400 ◦ C) is not compatible with life. Additionally, volcanism and tectonics appear to have episodically resurfaced the planet and therefore destroyed any evidence of life that may have been present in an early and possibly clement Venusian environment. Considering Mars, the current generation of Mars rovers and orbiters have recently allowed a rapid reappraisal of the history of Mars. A current view8 is that an early warm, wet, and nonacidic chemistry phase was characterized by the formation of phyllosilicate (“clay type”) minerals—the mostly likely epoch for the emergence of life (4.5–4.2 Gyr ago). A period of significant volcanic outgassing of volatiles including sulfur followed and resulted in an acidic wet phase with the formation of sulfate minerals (4.2–3.8 Gyr ago). This period may be correlated with the shutting down of the Mars geodynamo and gradual loss of a planetwide magnetic field with the resultant erosion and loss of a possibly dense atmosphere by the solar wind. The resulting final period, and extending to the present, is one of cold temperatures with a thin atmosphere and water-free mineral alteration with the formation of anhydrous ferric oxides (3.8–3.5 Gyr ago and continuing to the present). There is also considerable speculation and research concerning recent and ongoing water cycling on Mars. Water volume, presence, and mobility due to obliquity changes,9 seasonal variations, and even possible suggestions of liquid water or brines present near the Martian surface10 are all under investigation. An important point when comparing Mars to Earth and Venus is the lack of planetwide resurfacing on Mars since the earliest epochs such that mineral deposits from these periods remain accessible in the present. It is therefore expected that evidence of any early Martian life could be preserved in such deposits.
2.4
3
Life in the Solar System
There is evidence that life appeared rapidly on early Earth (see Section 2.4.1). It is therefore possible that life could have emerged independently—i.e., three or more independent geneses of life—on all three terrestrial planets under consideration given their likely similar environments. Alternatively, a single genesis of life could have evolved on any one of the three planets and seeded life on the other planets via the mechanism of lithopanspermia (see Section 2.4.3). Within this alternative scenario, life on all three planets would have a common single ancestor and hence a common fundamental biochemistry. This scenario has important implications for any life detection experiments as specific molecular indicators generic to Earth life are known. 2.4.1 Life on Earth
On Earth, evidence of life in the form of fossils of microorganisms can be found at 3.5 Gyr ago11 and from isotopic evidence, possibly earlier at around 3.8 Gyr ago12 although this interpretation is still hotly debated in the relevant communities. This latter date corresponds with the end of the Late Heavy Bombardment phase in the evolution of the solar system, which is likely to have resulted in major planetwide sterilizing impacts from asteroid and comets impactors. The implication is that life rapidly emerged on a geological timescale as soon as a stable environment was established. It is important to note that all present life on Earth appears to be the result of a single biochemistry, although other life chemistries may have existed in the distant past and may have been removed by evolution or impact events. This is the only example of life that we currently know.13
2.4.2 Life on Mars
At present, we can only speculate on the possibilities of life on Mars but it is important to consider the various possibilities as these not only have important scientific implications but are also crucial inputs into the design of analytical instruments to find evidence of life. Given the preceding discussion of a warm and wet early Mars, a number
4
BIOSENSOR APPLICATIONS Table 1. Various scenarios for the existence of life on Mars
Scenario
Consequence
1. 2.
Life never evolved on Mars Life independently evolved on Mars in an early wet and warm epoch. Martian conditions changed and Martian life became extinct
3.
Life independently evolved on Mars in an early wet and warm epoch. Martian conditions changed and Martian life evolved to allow survival to the present day in protected environments—such as in a water-rich deep subsurface
4.
5.
Life evolved on a single unknown location in the early system. Via lithopanspermia, life on Mars and Earth a common ancestry Then evolution as in 2 Life evolved on a single unknown location in the early system. Via lithopanspermia, life on Mars and Earth a common ancestry Then evolution as in 3
of scenarios can be envisaged and are summarized in Table 1. 2.4.3 Lithopanspermia
Within the context of finding life on Mars, it is crucial to understand that it is possible that life on Mars and life on Earth could both be the same example of life. This understanding derives from a modern interpretation of the concept of interplanetary panspermia, specifically lithopanspermia. The lithopanspermia14 hypothesis states that viable microorganisms, protected within rocks, can be transported between planets as impact ejecta. The protection offered by a few centimeters of a mineral phase has been shown to protect organisms from the thermal, vacuum, and radiation environments expected during ejection, interplanetary transfer, and entry and impact phases of this process.15 The observation that some meteorites on Earth have a Martian origin is further justification for the hypothesis. If this process occurred, then life could have emerged in principle on any suitable location in the solar system and seeded other bodies with suitable habitats. The consequence is that life on more than one body in the solar system could have had a common ancestor. For life detection, this means that generic biochemical
solar had
solar had
No evidence of life on Mars Preserved evidence of extinct life present
Biochemistry may be different to Earth life Preserved evidence of extinct life present
Evidence of extant life present Biochemistry may be different to Earth life Preserved evidence of extinct life present
Common biochemistry with Earth life Preserved evidence of extinct life present
Evidence of extant life present Common biochemistry with Earth life
indicators of life on Earth might be suitable for detecting life on Mars. 2.4.4 Other Locations
A number of other potential locations for life in the solar system are being considered. The possibility of extant Venusian life has been considered.16 At high altitudes in the Venusian atmosphere, temperature and pressure are similar to Earth and while water is present at low concentrations and the environment is highly acidic, these conditions are known to support life on Earth. Thus mission concepts are being developed that include the possibility of detecting life in the upper atmosphere of Venus (For example the possible inclusion of extant life detection instrumentation on a long-duration balloon-based aerobot within the European-led Venus Entry Probe concept; Cullen and Sims, personal communication). The other class of possible locations for life are those that harbor liquid water. Of these, Europa—one of the Jovian moons—is the subject of great speculation17 and possible future life detection missions (see Section 4.4.2). Europa is a world that comprises an ice crust covering a putative liquid-water ocean. The presence of a large and long-lived body of liquid water leads to the possibility of the emergence and support of life.
LIFE DETECTION WITHIN PLANETARY EXPLORATION
3 ANALYTICAL CONTEXT FOR LIFE DETECTION
The following section will limit discussion to the detection of life on Mars as this is the current community priority. Given the constraint that our understanding of life is limited to the single example of life on Earth, we assume that development of independent Martian life will, given similar environmental constraints, have followed broadly similar pathways to Earth, i.e., similar molecular evolution and solutions. Therefore assuming a water-based life with biomolecules providing membrane components and compartmentalization, energy production and storage mechanisms, storage of hereditary information, exploitation of chirality, and so on, does not appear to be an unreasonable assumption. Furthermore, as will be discussed later, the use of some approaches to biosensor detection of life requires a significant level of predetermination of the nature of the life to be detected. The term biomarker is used within the astrobiology community to refer to any type of evidence of life. The major categories of biomarkers are listed in Table 2. Only those directly relevant to biosensor and related techniques will be considered further, i.e. items 3–5 from Table 2. Furthermore, items 3 and 4 can be termed molecular biomarkers.
3.1
Table 2. Classes of biomarkers for the detection of life
1. Structural evidence such as fossilized organisms (e.g., accessible by microscopic observations) 2. Isotopic fractionation between reservoirs (e.g., accessible by mass spectrometry) 3. Organic molecules of obvious biotic origin, i.e., no known natural abiotic synthetic route (possible biosensor targets) 4. Significant chiral excess within appropriate organic molecules (possible biosensor targets) 5. Metabolic activity (possible biosensor targets)
categories relevant to performing and interpreting a life detection experiment are given in Table 3. Some molecular targets can of course have a variety of origins, i.e., biotic and abiotic, see Section 3.1.2. Hence, in reality a number of different targets must be measured and detected to enable a case for positive indication of life to be made. An international workshop on biomarkers for life detection on Mars was organized in May 2006 at the University of Leicester (UK) as part of the authors’ ongoing SMILE LMC development program. The output of the workshop, including a detailed list of possible biomarkers, has been submitted for publication.18 The following subsections describe the classes of molecular targets relevant to life detection and are partially based upon the publication resulting from the workshop.
3.1.1 Extant and Extinct Life Molecular Biomarkers
Molecular Targets
A summary of the classes or categories of molecular targets relevant to life detection and additional
Within the context of biosensor and bioanalytical instruments, molecular biomarkers often fall into
Table 3. Categories of molecular biomarkers and other relevant targets for biosensor-based life detection
Category
5
Context
Stable breakdown/preservation products of life—typically membrane derived Molecular biomarkers of extant/recent life Full range of molecules from metabolites to macromolecules Molecular biomarkers of microbial spacecraft Species-specific targets—antigens or nucleic contamination acid sequence Abiotic organics Meteoritic in fall
Typical properties
Molecular biomarkers of ancient extinct life
Low-molecular-weight apolar
Other targets
Low- to high-molecular-weight polar High-molecular-weight macromolecules Low-molecular-weight apolar and polar Various
Manmade synthetic molecules as positive controls Nonbiological contamination
Various—e.g., cleaning materials, rocket exhaust products
6
BIOSENSOR APPLICATIONS
one of two main categories, those that are stable breakdown and preservation products of ancient extinct life and those that represent extant or recent life (recent in terms of significant degradation of the core molecular components to recalcitrant molecules). The bases for this discrimination are (i) the obvious scientific context, (ii) the difference in the typical molecular nature of such classes, and (iii) the consequential impact on instrument design and especially molecular biomarker extraction protocols and suitability of targets for biosensor detection. Molecular biomarkers of ancient extinct life represent the result of degradation, alteration, and preservation and clearly will be influenced by environmental and geological factors including geochemistry, thermal processes, and radiation. On Earth we know the typical products of these processes for ancient Earth life. Nucleic acids and proteins are quickly degraded over geological timescales. Amino acids are modified with certain members of the biogenic amino acids degraded to simpler but longer-lived members. The key observation in Earth’s biomarker record from ancient life on Earth is the dominance of degradation, alteration, and preservation products of membrane molecules. The assumption of a similar molecular evolution of function for Martian life leads to targets such as saturated hydrocarbon structures from classes such as hopanes, steranes, isoprenoids, porphyrins, and straight-chain hydrocarbons as well as chirally resolved generic amino acid detection. Molecular biomarkers of extant and recent life again require some consideration of the nature of Martian life. Assuming similar molecular evolution of function, and even the possibility of a common ancestor with Earth life, leads to the identification of biomarkers generically associated with Earth life. Examples include adenosine triphosphate (ATP), generic pyrimidine and purine bases and their polymers—nucleic acids, amino acids, with chiral discrimination, and their polymers—polypeptides, carbohydrates such as trehalose, lipopolysaccharide, and possibly even conserved proteins such as the molecular chaperones (e.g., GroEL)—the latter examples are of course strongly associated with an expectation of a common ancestor between Earth and Mars life.
3.1.2 Other Molecular Targets
In addition to possible molecular biomarkers of Martian life, a number of other categories of organic molecular targets need to be considered when attempting an in situ Martian life detection experiment based upon molecular biomarkers. Firstly, it is expected there will be abiotic organic molecules in the Martian environment. As previously mentioned (Section 2.2), one source of abiotic organic molecules is the continual delivery of micrometeorites to the Martian surface. The detection of such molecules is important due to (i) scientific questions concerning abiotic organic molecules in the solar system and on Mars, including questions concerning their degradation and preservation within the Martian environment24 and (ii) contextual setting for the detection of molecular biomarkers as some abiotics, e.g., amino acids, could also have a biological origin. Examples of such abiotic molecular markers include polycyclic aromatic hydrocarbon (PAHs), isovaline, α-aminoisobutyric acid, and aromatic carboxylic acids. To validate any in situ life detection measurement, it is critically important to confirm that a false positive signal has not occurred. An obvious source for false positive signals are Earth life molecular biomarkers that could be present as a result of contamination within the life detection instrumentation or elsewhere within a rover including any sample collection and preparation components. As will be described in Sections 5.1 and 5.2, minimizing this possibility is a major design input to any life detection mission and instrument. The detection of specific markers of contamination via the presence of speciesspecific antigens from microorganisms known to colonize/be present within spacecraft clean-room assembly areas is one approach. Hence in situ detection of such a biomarker would cast doubt upon validity of the co-detection of any generic molecular biomarker as the default interpretation would be that the generic signals came from the contamination. Finally, to further validate in situ measurements, positive control molecular markers can be envisaged that would be dosed into an experiment. The choice of these is dictated by the criteria of avoiding molecules that have either natural abiotic or biological potential. Examples would
LIFE DETECTION WITHIN PLANETARY EXPLORATION
be synthetic organic molecules for which specific receptors are readily available. (The authors are using a manmade herbicide—specifically atrazine due to its low molecular weight and relatively polar nature and ready availability of high affinity and specificity antibodies—as a positive control marker in development work for the SMILE LMC experiment.)
3.2
Environmental Context
When considering the detection of biomarkers, the environmental context of the sample in which biomarker detection will occur is crucial. Owing to the intense interest in the results of a life detection experiment on Mars, the limited number of opportunities for measurements and the difficult in revisiting a location at a future date to clarify any ambiguities, the choice of sampling site is crucial. Three major criteria contribute to the choice of a location and comprise (i) expectation for life to have been, or currently be, present, (ii) expectation for the preservation of evidence of life, and (iii) ability to physically access the site. 3.2.1 Suitable Locations
As our understanding of Mars continues to grow due to the variety of currently active surface rovers and orbiters, the possible number of locations that could be considered relevant for life detection also continues to grow. Obvious sites are those that have evidence of the presence of water, either historically or at present. For extinct, ancient life, locations include weathered volcanic deposits exhibiting possible phyllosilicate signatures suggesting extended periods of water alteration8 and bedded sediments again suggesting the long-lived presence of water.19 For extant or recent life, hydrothermal deposits, recent impact sites, numerous locations of ice, and areas that exhibit terrain features in common with terrestrial permafrosts are all possible locations. A very recent report has suggested the possibility of current outbursts of near-surface water or brines.10 Additionally the deep subsurface is an intriguing possible location and mirrors the similar interest directed toward Earth’s deep subsurface.20 Within a life detection context, it is not apparent how
7
access to the Martian deep subsurface locations will be gained within the near future, without perhaps the presence of a manned expedition.
3.2.2 Preservation
For the detection of molecular evidence of life, not only must appropriate locations for life have existed in the past, but conditions suitable for the preservation of such evidence over intervening, potentially billions of, years must have been present. The apparent dominance of cold and dry conditions over a significant portion of Martian history is therefore favorable for preservation of such molecules. Radiation effects, a combination of solar UV radiation, solar energetic particles, galactic cosmic rays, and mineral radioactivity, will however have provided an energy source for the degradation of organic molecules. The depth profile of these effects is such that at depths below a few meters, only indigenous mineral radioactivity will have had a significant effect.21 Additionally oxidation chemistry is expected to dominate the near-surface chemistry of Mars.22 This results from the interaction of solar UV radiation with constituents of the atmosphere and the surface regolith producing putative superoxides and other oxidizing species. These are expected to oxidize organic material in the near-surface region. A conclusion therefore is that subsurface locations, of a few meters or more depth, offer the best situations for the long-term preservation of molecular biomarkers. 3.2.3 Accessibility of Locations
It must be remembered that in addition to sciencedriven choice of a sampling site, operation requirements restrict the choice of locations. This can occur at a global scale with landing site selection limited by factors such as (i) site altitude, (ii) latitude, e.g. due to reduced efficiency of photovoltaic power generation at high latitudes and restrictions imposed by the nature of launch and atmospheric insertion, i.e. from-orbit or by hyperbolic approach, and (iii) surface topography, i.e. topographical features that risk loss of the lander such as boulders and significant gradients. Additionally, local spatial restrictions apply due to
8
BIOSENSOR APPLICATIONS
limitations of rover mobility and access to areas of significant gradient, surface roughness, and unsuitable regolith consolidation.
4 MISSION HISTORY AND FUTURE OF LIFE DETECTION IN PLANETARY EXPLORATION
To date there have only been three attempts at direct, in situ life detection on another planetary body within the solar system. The first two attempts were the pair of NASA Viking landers that arrived on the Martian surface in July 1976 and September 1976. The third and most recent attempt was the UK’s Beagle 2 probe that flew as part of the ESA Mars Express mission and is assumed to have been lost by an off-nominal landing on the surface of Mars in December 2003, which resulted in loss of contact with the lander and therefore no scientific return. All other Martian missions have concentrated on the geochemistry or geology of Mars. Into the future, further attempts are being planned. The next life detection mission will be the ESA’s ExoMars rover mission that is currently due for launch in 2013.1 Additionally NASA has proposed an astrobiology-focused rover mission called the Astrobiology Field Laboratory (AFL)23 with a possible Mars arrival date in the latter part of the next decade. Early-stage discussions are currently taking place concerning possible future Europa orbiter and possibly lander missions (for examples see Gershman et al.24 and Atzei et al.25 ) as well as a long-duration upper atmosphere Venus probe with the potential for detecting life in the upper Venusian atmosphere.
4.1
Viking Missions
The NASA Viking missions were developed with detection of Martian life as the main objective. Moreover, there was premission expectation of extant life and this was reflected in the choice of life detection experiments flown. Developed in the late 1960s and early 1970s, four experiments are relevant to life detection26 ; three to detect metabolic activity within any regolith microorganisms and a GC/MS instrument for organic carbon detection.
4.1.1 GC/MS Experiment
A mass spectrometer together with a gas chromatograph and sample heaters was flown.27,28 For organic detection, regolith samples were collected from within the top 10 cm of the Martian regolith (via a scoop and robot arm). The samples were heated in miniovens at various temperatures up to 500 ◦ C and evolved volatiles and volatile pyrolysis products transported into a GC and eluted material analyzed with a mass spectrometer. The detection limits for specific organic species expected to be eluted from the GC column varied but were typically in the parts per billion levels.
4.1.2 Carbon Assimilation Experiment
The carbon assimilation experiment was designed to detect life in Martian samples by supplying 14 CO and 14 CO2 to a Martian sample incubated in a closed chamber under Martian-like environmental conditions. The incorporation of 14 C into organic material within the sample would be taken as an indication of metabolic activity and hence life within the sample.29 The detection of 14 C incorporation into organic material was achieved though the pyrolysis of the sample after incubation and selective trapping of the volatile pyrolysis products. The 14 C content of this fraction was determined with a simple radioactivity detector.
4.1.3 Labeled Release Experiment
The basis of the label release experiment was addition to Martian samples of 14 C-labeled organic substrates such as formate, lactate, glucose, and glycine in a closed chamber under varying environmental conditions. The release of 14 C into the gas phase would be been indicative of the presence of metabolically active life.30
4.1.4 Gas Exchange Experiment
The gas exchange experiment again incubated a number of Martian samples in the presence of experimentally added water, nutrients, and gases. A gas chromatograph periodically monitored the
LIFE DETECTION WITHIN PLANETARY EXPLORATION
head space gases within the incubation container to observe changes in the gas composition due to chemical and possible biological processes.31 4.1.5 Results of the Viking Life Detection Experiments
The GC/MS experiment did not detect any organic carbon signal above an upper limit of a few parts per billion. This was surprising given the expected continuing delivery of abiotic organic carbon to the Martian surface by meteorites. Initial positive results from the life detection experiments were soon interpreted as resulting from abiotic chemistry within the Martian regolith, e.g. in some cases activity was still present after “sterilization” of the regolith samples by heating. The current widely held view is that an oxidizing chemistry within the regolith samples is the most likely explanation of the results.32 Indeed, further consideration of this hypothesis could explain the lack of organic detection with the GC/MS as the metastable oxidation products of organic molecules, e.g. salts of carboxylic acids, while possibly present in the samples would not have been expected to generate volatile products amenable to GC/MS analysis.22 The vast majority of the planetary community agree that the results of the three Viking life detection experiments and the GC/MS experiment indicated no evidence of extant life in the samples tested. 4.2
Beagle 2
The UK Beagle 2 lander was designed primarily to search for evidence of past and present life within the Martian environment.33 The gas analysis package (GAP) was the primary scientific instrument on Beagle 2 and was central to the life detection aspect of the mission. Beagle 2 also included a percussive-driven “mole” sample acquisition system to enable regolith samples to be obtained from depths of up to 1.5 m34 and therefore potentially below the proposed surface oxidant layer. 4.2.1 The Gas Analysis Package (GAP)
The GAP35 was designed to include the ability to detect carbon, both organic and inorganic, within
9
the Martian environment. The GAP consisted of a number of sample ovens to receive samples and then to increasingly heat the samples in the presence of O2 to perform stepped combustion of Martian samples. The emission profile of the resultant CO2 combustion product (of any carbon) verses temperature would allow differentiation of the differing carbon reservoirs such as organic and carbonate reservoirs. The evolved CO2 was to be detected using a mass spectrometer that would also enable analysis of the 12 C and 13 C isotopic constitution of the evolved carbon. The 12 13 C/ C isotopic ratio is diagnostic of life as it is known from Earth that life favors the incorporation of 12 C compared to 13 C and thereby results in 12 C isotopic enrichment of biogenic carbon. The lower detection limit for carbon was stated as 0.02–0.01 ppm. 4.2.2 Mission Outcome
No surface experimentation on Mars occurred due to loss of contact with Beagle 2 after it was ejected from the Mars Express spacecraft within the vicinity of Mars as part of the Beagle 2 entry, descent, and landing phase of the mission.36 The cause of the loss of contact is still unclear at the present time (early 2007). 4.3
ExoMars Mission
The ESA ExoMars mission1 is design primarily as an astrobiology mission and therefore is expected to be the next Mars mission with the specific goal of detecting evidence of life. The mission is currently scheduled for launch in 2013 and with arrival at Mars approximately 2 years later.1 The mission contains a solar powered surface rover (see Figure 1) with a mobility range of a few kilometers. A key novel feature of the rover will be a drill capable of obtaining samples from a depth of down to 2 m below the surface. This is crucial for evidence of life detection as the previously mentioned preservation issues of organic molecular biomarkers reduce the likelihood of detecting organics in the top few centimeters of regolith or consolidated material. The rover will contain a range of possible instruments, which are currently divided into panoramic
10
BIOSENSOR APPLICATIONS
of a biosensor-based experiment, and the next Mars astrobiology mission, NASA is developing an astrobiology Mars mission called the AFL. This has a primary scientific goal of life detection and within the baseline mission specification is consideration of antibody microarray devices.38 A possible launch date is 2016.
4.4.2 Europa Lander
2-m depth
Figure 1. Computer generated image (CGI) representation of the ESA ExoMars rover demonstrating the deployment of the drill. [Image courtesy of ESA.]
(panoramic camera, infrared spectrometer, ground penetrating radar), contact (M¨ossbauer spectrometer, Raman-LIBS), analytical (X-ray diffractometer, LMC, GC/MS, Urey), support (drill, sample handling, and distribution system), and environmental suites. Of these instruments, the three proposed organic detection instruments within the analytical suite are of most interest for evidence of life detection. The Urey instrument comprises an integrated system that includes a microfabricated capillary electrophoresis system for the detection of amine-containing organics after in situ derivatization with fluorescamine.37 The LMC is an antibody microarray biosensor instrument (see Section 6.1.3). The third instrument is the GC/MS. 4.4
Other Future Missions
4.4.1 NASA Astrobiology Field Laboratory
While ESA’s ExoMars mission is the most developed mission, the first, to propose the inclusion
Apart from Mars, the other location in the solar system that is of significant interest to the astrobiology community is the Jovian moon Europa (see Section 2.4.4) due to the presence of a putative liquid-water ocean below an ice crust. The sampling of the ocean for evidence of life is a long-term objective. Two major issues need to be addressed for such a mission; they are (i) the intense radiation environment within the Jovian system due to the trapping of solar particle radiation by the Jovian magnetosphere and (ii) the penetration of the ice crust that may be many kilometers thick. For life detection instrumentation, and especially those that contain radiationsensitive components such as bioassay and other chemical reagents, the radiation exposure dictates either significant levels of shielding and therefore all the associated detrimental issues of mass or the selection of compounds that are radiation tolerant. For molecular recognition sensors, it may be possible to exploit more robust receptor materials such as molecular imprinted polymers, in future applications. The interpretation of various Europa surface features as sites of contemporary ocean upwellings and melt-through may offer a route to the sampling of recently exposed ocean contents without resort to penetration of the ice crust.
4.4.3 Earth Missions
As an analog to possible Europa missions, the exploration of subglacial lakes in Antarctica39 offers some similarity with liquid-water lakes of biological interest located beneath several kilometers of an ice overlayer. Thus Lake Vostok and more recently subglacial Lake Ellsworth40 are being considered for exploration using robotic probes equipped with life detection instrumentation.
LIFE DETECTION WITHIN PLANETARY EXPLORATION
5 TYPICAL MISSION CONSTRAINTS FOR LIFE DETECTION INSTRUMENTATION
The detection of evidence of life in Martian samples would be relatively easy if samples could be returned to state-of-the-art Earth laboratories. The techniques, instrumentation, and protocols then used would be those that are already developed to analyze similar samples for biomarker detection in ancient Earth rocks and the full arsenal of techniques within the modern biotechnology sector. This scenario in the form of a Mars sample return mission41 is being discussed but due to mission complexity is unlikely to happen until 2020 at the very earliest. Until such a mission occurs, samples need to be analyzed in situ on the Martian surface. This imposes a number of limitations and restrictions on analytical techniques due to engineering, environmental, and ethical considerations and requirements. It is therefore important that these limitations and restrictions are considered in any bioanalytical life detection instrumentation development and are described in the following subsections and summarized in Table 4.
5.1
Planetary Protection
A critical design constraint for any biosensor-type technology for use in life detection and planetary exploration concerns the topic and implications of planetary protection.42 There is a risk that Earth organisms contaminating a spacecraft
could be transferred to a planetary body—termed forward contamination. Such contamination of a planetary body raises ethical and scientific concerns. In essence, ethically one does not want to contaminate a pristine environment with Earth organisms with possible detrimental affect on any indigenous life and scientifically the contamination of an environment with Earth life makes scientific interpretation of that environment in terms of indigenous life more difficult. The level of concern is related to the nature of the planetary body and specific location being accessed and whether there is a possibility of there beginning or having been indigenous life and/or an environment conducive to maintenance and even colonization by contaminating Earth life. Planetary protection for missions is overseen internationally by COSPAR (Committee on Space Research). COSPAR categorizes missions into a number of classes43 depending on the objective of the mission, i.e., life detection or not, and the potential of the visited region to harbor life historically, at present or into the future. This categorization also includes setting upper limits for the degree of contamination or bioburden allowed. For example, Mars lander missions with extant life detection experiments will be either Category IVb or IVc. This requires the bioburden levels to be equivalent to, or less than, those of the NASA Viking landers after their sterilization step. The current default method for sterilizing spacecraft to reduce their bioburden was established during the Viking missions and comprises the dry thermal baking of a spacecraft and
Table 4. Extreme environments and other constraints typically encountered by instruments during development, build integration, and use within a planetary exploration mission
Sterilization Contamination control Radiation Thermal environment
Shock loadings Acoustic energy exposure Chemically aggressive sample matrices Extended storage times Reduced gravity
11
Default of dry heated treatment at > 100 ◦ C although alternatives are possible Need to reduce instrument contamination levels to below the detection limit of the analytical techniques deployed γ radiation, various particle radiations Both thermal cycling and extreme excursions during prelaunch and launch, cruise phase, and on-surface operations For example, during launch, pyrotechnic firings, entry, descent, and landing operations For example, during launch For example, oxidants in Martian regolith Including prelaunch, cruise phase, and on-surface operations On-surface gravity and microgravity conditions during cruise phase
12
BIOSENSOR APPLICATIONS
any instrument payload at elevated temperatures (>100 ◦ C) for many hours. This obviously is problematic for most biosensor technology as the biologically derived components, e.g., antibodies, are unlikely to survive such treatment. Therefore alternative sterilization, or more specifically bioburden reduction approaches, are required and must be validated. Alternative approaches could include UV treatment, hydrogen peroxide plasma, γ irradiation, chemical treatments, and for some molecular reagents ultrafiltration. In reality, combinations of these approaches together with appropriate aseptic handling and assembly procedures are required to meet the stringent limits of contamination set. The most recent experience of preparation for a Category IVa (less stringent than Category IVb or IVc) mission that did not use terminal heat sterilization was gained by the Beagle 2 team.44 It is important to note that providing the validation of the bioburden reduction approaches and verifying the obtained levels of bioburden for the flight components are also major challenges. The current approaches for validation and monitoring involve various sampling techniques coupled with detection of viable organism by culture techniques as well as more modern approaches such as the limulus amebocyte lysate (LAL) assay, polymerase chain reaction, and ATP measurements.
5.2
Contamination Control
The normal approach to ensuring a limit on the number of viable organisms that are present on a spacecraft is sterilization by dry heat treatment. This and many other sterilization procedures render microorganism contamination nonviable but do not necessarily remove the physical presence of inactivated microorganisms. If, as is the case under consideration, the analytical targets of an instrument are the molecular components of life, then the presence of inactivated microorganism would provide a significant reservoir of molecular biomarkers and hence potential for false positive detection signals. Therefore the physical removal or prevention of contamination and understanding the resultant upper limits of contamination levels is a critical task. In essence, the level of contamination should be below the lower limit of detection of the most
relevant and sensitive analytical instrument within an instrument suite. The approaches to achieve this rely upon a combination of (i) cleaning techniques, (ii) choice of, or modification of, surfaces to optimize cleaning and minimize levels of contamination, (iii) handling and assembly of instruments in clean conditions, and (iv) appropriate instrument designs that limit the surface area of relevance and routes for the transfer of contamination.
5.3
Radiation Environments
A Mars mission has two major phases during which a biosensor instrument would be exposed to a variety of radiation environments and those are in addition to any radiation used to ensure instrument sterilization during assembly. These are the interplanetary cruise phase and the Martian surface operations phase. For the following discussion it will be assumed that the radiation environment at the Martian surface approximates to that during the interplanetary cruise phase—a reasonable assumption given the lack of a protective thick atmosphere and a planetwide magnetic field. During the interplanetary cruise phase the spacecraft will be subject to radiation primarily from the Sun and galactic cosmic rays. A wide range of radiation types are produced from these sources and comprise energetic particles such as electrons, protons, neutrons, and heavier ions and electromagnetic radiation including UV, X rays, and γ rays. The relevant energies of these radiations vary from a few megaelectron volts to thousands of gigaelectron volts. Additional sources of radiation can include radioactive sources within a spacecraft and rover, for example, radioisotope thermoelectric generators and radioisotope heaters units, and secondary radiation produced by the interaction of primary radiation with the structure of the spacecraft and rover. For surface operations, this can include secondary radiation products from the Martian surface. The levels of radiation for a typical Mars mission can be calculated. Thus as an example for the ExoMars mission with a 2-year interplanetary cruise phase during solar maximum and 6 months surface operations, appropriate calculations produce a total radiation dose of 6.6 krad assuming a shielding level equivalent to 4 mm of aluminum from the spacecraft and rover
LIFE DETECTION WITHIN PLANETARY EXPLORATION
structure (Alex Hands and David Rodgers, private communication). For biosensor-type instruments, the components of concern, as far as radiation stability is considered, are biological materials and associated assay reagents. For the case of antibody microarray devices with fluorescent labels, there has been little study of the effect of the various radiations on these materials apart from limited studies of γ irradiation due to the interest in food sterilization45 and sterilization of antibodies for biotechnological applications.46 Therefore the current authors have initiated a test campaign to de-risk issues surrounding the stability of antibodies and fluorescent dyes to Mars mission radiation exposure levels. Preliminary data indicates that dried fluorescence dyes survive many times mission levels of proton and helium ion radiation47 as well as γ radiation. Dried antibodies retain significant levels of activity when exposed to mission level radiation of proton and helium ions. It is also apparent that the storage of antibodies46 or fluorescent dyes in a hydrated form is inappropriate as radiolysis products, such as free radicals, produced from water can inactivate both antibodies and fluorescent dyes. Thus for Mars missions there does not appear to be a fundamental issue concerning exposure to the expected radiation environment although for other missions, such as to Europa, the much higher levels of radiation exposure may provide a very significant challenge. It should be noted that γ radiation doses reported to demonstrate sterilization in antibody preparations were 1.5–4.5 Mrad.46 This illustrates that a γ radiation sterilization protocol may be applicable to address planetary protection requirements and if used would provide a significantly greater exposure to ionizing radiation than the mission itself.
5.4
Other Mission Constraints
In addition to the preceding three topics, a number of other constraints need to be considered when developing instrumentation for planetary exploration. While a number of these are typically considered during development of biosensor technologies for common Earth-based applications, they are often more severe for planetary exploration applications. For the sake of brevity, these will simply be listed in Table 4.
13
6 BIOSENSOR AND BIOANALYTICAL TECHNOLOGIES FOR LIFE DETECTION
The approach to the detection of evidence of life can take a number of directions, the specific details of which depend upon the exact questions beginning asked and also to a large extent of the mission opportunity. Historically, the Viking missions were searching for extant life and therefore looked for evidence of metabolism as this did not require a strong Earth-centric view of the nature of life. The current expectations of Mars are primarily focused on detecting preserved evidence of ancient extinct life while also maintaining as a secondary goal the detection of extant life. Therefore given that the most likely situation is that of detecting trace levels of recalcitrant preservation products of ancient life, antibody-based biosensor and bioanalytical systems are receiving the most attention. The drivers for this include (i) proven ability to detect a broad range of molecule types—from low-molecular-weight polar and apolar molecules through to macromolecules, (ii) proven ability to detect trace levels of molecules in environmental samples, (iii) a wide range of demonstrated instrument platforms such as lateral-flow immunodiagnostics devices, especially for simultaneous detection of multiple targets, antibody microarrays, and (iv) exploitation of antibody cross-reactivity to detect classes of related molecules. Two of these drivers warrant further discussion. The first listed driver is a powerful reason for the planetary exploration community’s emerging interest in biosensor and bioanalytical technologies. The ability to detect a wide range of molecule types with a single instrument, i.e., by simply including different antibodies, enables a large scientific return for a single instrument. In spacecraft design where the need to minimize instrument mass and volume cannot be over estimated, this is a very appealing feature. The last listed driver is crucial as the obvious concern in the use of antibodies for life detection is the need to predetermine the biomarker targets to which to raise appropriate antibodies prior to the flight of the instrument. If a highly specific antibody was employed for a given target and that had little cross-reactivity to other related biomarkers that may belong to the same target class, a negative life detection signal could result indicating that the specific biomarker is absent even if there was a high level of other
14
BIOSENSOR APPLICATIONS
members of the class which would indicate life. Therefore selection of antibodies with appropriate levels of cross-reactivity to biomarker classes will be important. The types of targets for which antibodies will need to be raised have already been discussed (see Section 3.1.1) and have also been considered elsewhere.48 Although antibody-based systems are the present focus for development of biosensor technology for life detection on Mars, other approaches are being considered. These are briefly discussed at the end of this section.
6.1
Antibody-based Systems
Sample input module Sample
Data
Sample homogenizing module Sample processing module
Sample distribution module Liquid Liquid handling management module
Power
Data reading module
Reaction module
Global control module
Power module
(a) Sonicator
Three groups are currently exploring antibody microarray-based systems and comprise (i) the Spanish Signs-of-Life Detector (SOLID) activity from the Centro de Astrobiologia in Madrid, (ii) the US-led Modular Assays for Solar System Exploration (MASSE) activity focused on Dr Andrew Steele’s work in the Geophysical Laboratory at the Carnegie Institution of Washington, and (iii) the UK-led SMILE activity based on the work of the current authors.
Laser
Processing Reaction Electronics module module
CCD (b)
75
A Spanish group from the Centro De Astrobiologia (Madrid, Spain) have been developing an automated antibody microarray system for biomarker detection for robotic and remote field analysis. An application focus has been the Rio Tinto in southern Spain that offers a possible analog of a wet and acidic early Mars.49 The initially reported SOLID prototype system50 is shown in Figure 2. The system contains 12 independent sample-extraction and microarray reaction modules. It comprises: 1. A funnel input to receive up to 0.5 g of a particulate sample and a sample-distribution system that places the sample in 1 of 12 sampleprocessing modules. 2. A movable ultrasonic unit that acts as a reusable closure for each sample-processing module and enables application of ultrasonic energy to aid sample extraction. It also allows compression
25
6.1.1 SOLID
Microarray
Sample-processing module Reaction chamber Filter
Valve
Waste recipient Washing pathway (c)
Figure 2. SOLID prototype. (a) SOLID module diagram, (b) SOLID picture showing the main components, and (c) details of sample-processing and reaction modules. [Reprinted with permission Parro et al.50 copyright 2005, Elsevier.]
of the sample and expulsion of extraction fluid from the sample-processing module to a reaction module.
LIFE DETECTION WITHIN PLANETARY EXPLORATION
3. Each sample-processing module contains an exit valve protected by a filter to withhold particulate samples after extraction and during expulsion of the extracted material and solvent. It also provides additional chambers and fluidic conduits to enable the dosing of required solvents for extraction and assay reagents. 4. Expulsion of the extracted material, assay reagents, and solvent results in flow into a reaction module containing an antibody microarray within a thin-layer flow cell. Sandwich immunoassays occur on the microarray before washing with further solvent flow. 5. A laser excitation and CCD imaging system enables readout of the fluorescently labeled sandwich immunoassays. 6. The system has supporting control electronics and fluid pumps and valving and reservoirs for solvents and waste fluids. The system has been demonstrated using real samples collected from Rio Tinto. After running the SOLID system with 0.25 g of sediment and an antibody microarray using a sandwich assay format and containing polyclonal antibodies against Leptospirillum ferrooxidans and Acidithiobacillus ferrooxidans, microarray spots with both these antibodies gave a positive signal. Both bacterial species were known to be present at the sampling location. The system was also demonstrated with a 0.25 g particulate sample that was flooded with 1 ml of an aqueous solution containing a number of protein antigens each at a concentration of 10 ng ml−1 . The relevant assay spots in the array gave a positive reading from the spiked particulate mineral sample. More recently the group has demonstrated the ability to perform competitive multiplexed immunoassays in a microarray format.51 This is an important demonstration as the vast majority of likely biomarker targets for an initial Mars mission will be low-molecular-weight molecules. Such molecules are normally detected using competitive immunoassay formats as their size and often lack of suitable reactive groups precludes the use of either sandwich assay formats or direct labeling of the targets as is commonplace in the mainstream proteomics applications of antibody microarrays. In the reported demonstration, various antigens were immobilized on the microarrays. An aqueous solvent with 10% methanol was used
15
to extract antigens from mineral samples spiked with antigens. The extracted antigen contained within the aqueous solvent (with 10% methanol) was incubated with soluble antibodies and then exposed to the microarrays. Presence of extracted antigen occupied the appropriate antibody binding sites thereby inhibiting antibody binding to the appropriate microarray spot. Binding of the antibodies was detected after washing by a further incubation step with fluorescently labeled Protein A and reading in a standard microarray scanner. Depending on the specific antibody–antigen pair, detection levels ranged from sub–parts per billion to hundreds of parts per billion. 6.1.2 MASSE
The group of Dr Andrew Steele at the Geophysical Laboratory of the Carnegie Institution of Washington (USA) has long advocated the use of biotechnological approaches to life detection for planetary exploration. They proposed the MASSE concept that includes the use of antibody microarrays for the in situ detection of biomarkers.52 Significant research and technology development is underway within this and associated groups, institutes, and companies funded by various NASA programs but full details of the outputs and current status are not currently available within the public domain due to governmental technology transfer policies. (The International Traffic in Arms Regulations (ITAR) is a set of US government regulations that limits sharing of information with non-US persons on defense-related information and technology. Space technology falls within its remit and inhibits the collaboration and interchange of information in international collaborators with NASA supported researchers.) Briefly, a handheld fieldbased fluorescent antibody microarray device has been demonstrated and field tested at the Arctic Mars Analog Svalbard Expedition (AMASE) site in 2006. Additionally a variant of this has been flown in 2007 on the space shuttle. A lipopolysaccharide bioassay system based upon LAL has also been field tested at the AMASE site. 6.1.3 SMILE
This chapter’s authors are the proposers and lead investigators of the SMILE instrument (The current team developing SMILE for the ExoMars
16
BIOSENSOR APPLICATIONS
rover is UK led (by the authors) and with additional partners from the United Kingdom, The Netherlands, Germany, and the United States). Again this is an antibody, or more specifically an immunoassay, microarray device using fluorescent labels and therefore optical readout. It has been proposed and accepted into the outline and baseline instrument payload for the ESA ExoMars mission known as the Pasteur package. The decision as to which instruments will be included in the eventual mission is pending ongoing design and engineering studies at the time of writing. Within the context of ExoMars, the term LMC is used to generically denote such instruments. The primary focus for the SMILE instrument development is directed toward an implementation that is appropriate as a flight instrument for the ExoMars mission rather than Earth-based applications. The SMILE instrument is in an early phase of development and therefore the following is a brief overview of the design and approaches being taken. To avoid regeneration of microarrays, to minimize cross-contamination between samples and avoid the complexities of emptying, cleaning, and reuse of solid-sample containers and particulate filters, multiple single use components and subsystems are to be used. For the baseline instrument, up to 40 independent “assay channels” are included, therefore allowing up to 40 samples to be analyzed. An assay channel consists of: 1. Sample extraction and preconcentration A sample container to receive approximately 1 g of Martian sample—either crushed regolith or crushed rock core—and that can be sealed and solvent added. Appropriate choice of solvent and application of heat and/or ultrasonic energy enables extraction of organic molecular biomarkers. A sample preconcentration step is included that offers the potential for (i) solvent volume reduction and hence preconcentration, (ii) exchange of solvent, and (iii) sample cleanup, e.g., removal of solvent soluble sample salts. 2. Immunoassay microarray with optical readout The extracted components in a solvent suitable for performing an immunoassay are passed into a microfluidic portion of the assay channel. The channel contains predosed and dried immunoassay
reagents that dissolve into the solvent. The solvent, extracted components, and immunoassay reagents are then passed over an immobilized microarray of immunoassay components that are within the microfluidic channel allowing appropriate binding of fluorescently labeled assay components. Further flow of solvent flushes unbound assay components and washes the microarray. The baseline design includes the use of thin-film optical waveguides as the support for the immobilized microarray thereby allowing evanescent wave excitation of the fluorescent labels when at the surface of the waveguide. This enables (i) improved efficiency of fluorescent label excitation and (ii) the possibility of kinetic measurements that will aid in the interpretation of the assay, i.e., a definitive endpoint measurement will only be considered further if an appropriate kinetic binding profile is also seen. Optical imaging and detection of the fluorescent output of the array occurs with a single optical imaging subsystem. 3. Support components Components include fluid pumps and valves to allow pressurization of the fluidic system and distribution of fluids through the sample channels, mechanisms to rotate a carousel configuration of up to 40 sample channels, heaters to raise the temperature to levels suitable for the immunoassays and handling of aqueous solvents, a box structure to contain the instrument, and support electronics and controllers. The immunoassay microarray baseline design contains 100 assay spots and allowing for various control and calibration spots and triplication of spots, up to 25 independent immunoassays can be accommodated and therefore detection of 25 targets will be housed per assay channel. As previously described, the range of assay targets is wide; from low-molecular-weight molecules to macromolecules. The SMILE design is compatible with a variety of assay formats and that includes (i) sandwich assays for multiple-epitopecontaining macromolecules, (ii) capture assays for target that are compatible with in situ fluorescent labeling, (iii) competition assays with prelabeled traces, and (iv) inhibition assays with immobilized antigens and soluble labeled antibodies.
LIFE DETECTION WITHIN PLANETARY EXPLORATION
An ongoing development program for the SMILE instrument includes (i) development of appropriate antibody libraries to populate the instrument, (ii) development of suitable sample-extraction and processing protocols, (iii) development of sterilization protocols for planetary protection, (iv) testing the radiation tolerance of assay reagents including antibodies, (v) breadboard de-risking studies of key components and subsystems, and (vi) production of detailed flight model designs.
6.2
Other Bioanalytical Systems and Components
6.2.1 Bioassays
Sensitive and generic life detection methods have already been developed for a number of terrestrial applications. ATP bioluminescence is commonplace in food hygiene and other applications. It has been considered for Martian use53 but the most likely applications are in support of planetary protection issues during spacecraft, rover, and instrument assembly (see Section 5.1) and for Earth analogs of other solar system locations such as Antarctic subglacial lakes.40 The LAL assay again is well established as a sensitive bioassay for lipopolysaccharide from gram-negative bacteria. Similar to the ATP bioluminescence assay, it’s current and near-future application is likely to be limited to study of Earth analogs of other solar system locations and support of planetary protection protocols.
6.2.2 Nucleic Acid Detection
At present, the lack of knowledge concerning life elsewhere in the solar system has resulted in little current consideration of nucleic acid amplification and detection techniques being employed as dedicated instruments for planetary exploration. The narrowness of the scientific return allied with the mass requirements for an instrument is an obvious driver for this situation. The application of life detection instrumentation to Earth analogs of planetary environments is a more likely application of these technologies and although development programs specific to these applications are not well
17
established, similar technologies are being rapidly developed for field-based applications within the security and defense sector.54 Migration of such hardware to application within Earth analogs of planetary environments is an obvious step.
6.2.3 Artificial Receptors
Given the extreme environments that biological reagents will have to endure in some planetary exploration mission, e.g., to Europa, and the simplification to implementing planetary protection requirements if receptors could withstand heat sterilization, robust artificial sensors would be desirable. Molecular imprinted polymers are one such possible technology that is starting to receive interest for future applications. Both the current authors55,56 and others are considering such technology.57
6.3
In situ Sample Acquisition, Processing, and Delivery
Although the preceding emphasis has been toward analytical techniques and the justification for their use, a major component of realizing in situ measurements is successful sample acquisition, processing into a suitable form, and delivery to an analytical instrument. The importance of this process cannot be over estimated. The difficulty in engineering such systems to operate within the constraints already described can consume equal, if not more, development and spacecraft/rover resources than the analytical instruments they serve. It will suffice here to list a number of approaches that have been used or are currently being considered or developed. For sample acquisition these include (i) scoops on arms, e.g., Viking and the upcoming Phoenix mission,58 (ii) the percussivedriven “mole”34 on Beagle 2, and (iii) the drill proposed for the ExoMars mission. For sample processing, examples include (i) rock crushing, (ii) sample sieving, (iii) addition of reagents such as liquids and solutes, (iv) heating of samples in ovens, (v) solvent extraction, (vi) sublimation, and (vii) subcritical water extraction.
18
BIOSENSOR APPLICATIONS
7 SUMMARY
We are at a unique and exhilarating point in time where two distinctive streams of endeavor are merging for the first time. Firstly humankind is actively planning and implementing missions to planetary bodies such as Mars to ask questions concerning the potential for, and existence of, life. Secondly biosensor technology has matured to a level where it can be seriously proposed as a tool to help answer such questions. This chapter has therefore given an overview of the context and issues surrounding the development and future use of biosensor, biochip, and other bioanalytical technologies for the detection of evidence of life in a planetary exploration context. Mars has been the focus of this chapter as it is the place thought most likely to harbor evidence of life and is the target of a number of upcoming missions although other planetary bodies such as Europa are of interest. For the biosensor community, the unique combination of challenges and drivers coming from the planetary exploration community results in a development environment that may stimulate novel design solutions which could also benefit more traditional Earth-based biosensor applications. We hope that this chapter will stimulate others within the biosensor community to look toward some of the challenges of detecting life elsewhere in the solar system using biosensor and related technology.
ACKNOWLEDGMENT
We would like to thank Daniel Thompson and Paul Wilson for their critical reading of the manuscript and suggestions.
REFERENCES 1. J. Vago, B. Gardini, G. Kminek, P. Baglioni, G. Gianfiglio, A. Santovincenzo, S. Bay´on, and M. van Winnendael, ExoMars Project Team, ExoMars—searching for life on the red planet. ESA Bulletin-European Space Agency, 2006, 126, 16–23, (ISSN 0376–4265) (Note the launch date information within this publication has been superseded and the launch date is currently 2013 with arrival at Mars in 2015—correct January 2007). 2. I. de Pater and J. J. Lissauer, Planetary Sciences, Cambridge University Press, 2001.
3. R. Gomes, H. F. Levison, K. Tsiganis, and A. Morbidelli, Origin of the cataclysmic late heavy bombardment period of the terrestrial planets. Nature, 2005, 435, 466–469. 4. J. F. Kerridge, Formation and processing of organics in the early solar system. Space Science Reviews, 1999, 90, 275–288. 5. O. Botta and J. L. Bada, Extraterrestrial organic compounds in meteorites. Surveys in Geophysics, 2002, 23, 411–467. 6. C. Chyba and C. Sagan, Endogenous production, exogenous delivery and impact-shock synthesis of organic molecules: an inventory for the origins of life. Nature, 1992, 355, 125–132. 7. G. J. Flynn, The delivery of organic matter from asteroids and comets to the early surface of Mars. Earth Moon and Planets, 1996, 72, 469–474. 8. J.-P. Bibring, Y. Langevin, J. F. Mustard, F. Poulet, R. Arvidson, A. Gendrin, B. Gondet, N. Mangold, P. Pinet, and F. Forget, Global mineralogical and aqueous mars history derived from omega/Mars express data. Science, 2006, 312, 400–404. 9. J. W. Head, J. F. Mustard, M. A. Kreslavsky, R. E. Millikien, and D. R. Marchant, Recent ice ages on Mars. Nature, 2003, 426, 797–802. 10. M. C. Malin, K. S. Edgett, L. V. Posiolova, S. M. McColley, and E. Z. N. Dobrea, Present-day impact cratering rate and contemporary gully activity on Mars. Science, 2006, 314, 1573–1577. 11. J. W. Schopf, Microfossils of the early Archean apex chert—new evidence of the antiquity of life. Science, 1993, 260, 640–646. 12. S. J. Mojzsis, G. Arrhenius, K. D. McKeegan, T. M. Harrison, A. P. Nutman, and C. R. L. Friend, Evidence for life on earth before 3,800 million years ago. Nature, 1996, 384, 55–59. 13. P. C. W. Davies and C. H. Lineweaver, Finding a second sample of life on earth. Astrobiology, 2005, 5, 154–163. 14. C. Mileikowsky, F. A. Cucinotta, J. W. Wilson, B. Gladman, G. Horneck, L. Lindegren, J. Melosh, H. Rickman, M. Valtonen, and J. Q. Zheng, Natural transfer of viable microbes in space–1. From Mars to earth and earth to Mars. Icarus, 2000, 145, 391–427. 15. G. Horneck, C. Mileikowsky, H. J. Melosh, J. W. Wilson, F. A. Cucinotta, and B. Gladman, Viable Transfer of Micro-Organisms in the Solar System and Beyond , in Astrobiology: the Quest for the Conditions of Life, G. Horneck and C. Baumstark-Khan (eds). Springer, Berlin, 2002, pp. 57–76. 16. D. Schulze-Makuch, J. M. Dohm, A. G. Fair´en, V. R. Baker, W. Fink, and R. G. Strom, Venus, Mars, and the ices on Mercury and the Moon: astrobiological implications and proposed mission designs. Astrobiology, 2005, 5, 778–795. 17. C. F. Chyba and C. B. Phillips, Possible ecosystems and the search for life on Europa. Proceedings of the National Academy of Sciences, 2001, 98, 801–804. 18. J. Parnell, D. C. Cullen, M. R. Sims, S. Bowden, C. Cockell, R. Court, P. Ehrenfreund, F. Gaubert, B. Grant, V. Parro, M. Rohmer, M. Sephton, H. Stan-Lotter, A. Steele, J. Toporski, and J. Vago, Searching for life on Mars: selection of molecular targets for ESA’s aurora ExoMars mission. Astrobiology, submitted.
LIFE DETECTION WITHIN PLANETARY EXPLORATION 19. A. H. Squyres and A. H. Knoll, Sedimentary rocks at Meridiani Planum: origins, diagenesis and implications for life on Mars. Earth and Planetary Science Letters, 2005, 240, 1–10. 20. K. Pedersen, Exploration of deep intraterrestrial microbial life: current perspectives. FEMS Microbiology Letters, 2000, 185, 9–16. 21. L. R. Dartnell, L. Desorgher, J. M. Ward, and A. J. Coates, Modelling the surface and subsurface martian radiation environment: implications for astrobiology. Geophysical Research Letters, 2007, 34, L02207. 22. S. A. Benner, K. G. Devine, L. N. Matveeva, and D. H. Powell, The missing organic molecules on Mars. Proceedings of the National Academy of Sciences, 2000, 97, 2425–2430. 23. MEPAG Astrobiology Field Laboratory Science Steering Group, The Astrobiology Field Laboratory, JPL Document Ref. # CL#06-3307 2006. 24. R. Gershman, E. Nilsen, and R. Oberto, Europa lander. Acta Astronautica, 2003, 52, 253–258. 25. A. C. Atzei, P. Falkner, M. L. van den Berg, and A. Peacock, The Jupiter minisat explorer, a technology reference study. Acta Astronautica, 2006, 59, 644–650. 26. H. P. Klein, J. Lederberg, and A. Rich, Biological experirments: the Viking Mars lander. Icarus, 1972, 16, 139–146. 27. D. M. Anderson, K. Biemann, L. E. Orgel, J. Or´o, T. Owen, G. P. Shulman, P. Toulmin, and H. C. Urey, Mass spectrometric analysis of organic compounds, water and volatile constituents in the atmosphere and surface of Mars: the Viking Mars lander. Icarus, 1972, 16, 111–138. 28. K. Biemann, J. Oro, P. Toulmin, L. E. Orgel, A. O. Nier, D. M. Anderson, P. G. Simmonds, D. Flory, A. V. Diaz, D. R. Rushneck, and J. A. Biller, Search for organic and volatile inorganic compounds in two surface samples from the chryse planitia region of Mars. Science, 1976, 194, 72–76. 29. N. H. Horowitz, J. S. Hubbard, and G. L. Hobby, The carbon-assimilation experiment: the Viking Mars lander. Icarus, 1972, 16, 147–152. 30. G. V. Levin, Detection of metabolically produced labeled gas: the Viking Mars lander. Icarus, 1972, 16, 153–166. 31. V. I. Oyama, The gas exchange experiment for life detection: the Viking Mars lander. Icarus, 1972, 16, 167–184. 32. H. P. Klein, The Viking biological experiments on Mars. Icarus, 1978, 34, 666–674. 33. I. P. Wright, M. R. Sims, and C. T. Pillinger, Scientific objectives of the beagle 2 lander. Acta Astronautica, 2003, 52, 219–225. 34. L. Richter, P. Coste, V. V. Gromov, H. Kochan, R. Nadalini, T. C. Ng, S. Pinna, H.-E. Richter, and K. L. Yung, Development and testing of subsurface sampling devices for the beagle 2 lander. Planetary and Space Science, 2002, 50, 903–913. 35. D. Pullan, M. R. Sims, I. P. Wright, C. T. Pillinger, and R. Trautner, Beagle 2: the Exobiological Lander of Mars Express, in ESA Special Publication, SP-1240, The European Space Agency, 2004, pp. 165–204. 36. M. R. Sims (ed), Beagle 2—Mission Report, University of Leicester, 2004.
19
37. A. M. Skelley, H. J. Cleaves, C. N. Jayarajah, J. L. Bada, and R. A. Mathies, Application of the Mars organic analyzer to nucleobase and amine biomarker detection. Astrobiology, 2006, 6, 824–837. 38. A. Steele, D. W. Beaty, J. Amend, R. Anderson, L. Beegle, L. Benning, J. Bhattacharya, D. Blake, W. Brinckerhoff, J. Biddle, S. Cady, P. Conrad, J. Lindsay, R. Mancinelli, G. Mungas, J. Mustard, K. Oxnevad, J. Toporski, and H. Waite, The Astrobiology Field Laboratory: Final report of the MEPAG Astrobiology Field Laboratory Science Steering Group (AFL-SSG), Jet Propulsion Laboratory document Ref. CL#06-3307 2006. 39. M. J. Siegert, S. Carter, I. Tabacco, S. Popov, and D. D. Blankenship, A revised inventory of Antarctic subglacial lakes. Antarctic Science, 2005, 17, 453–460. 40. M. J. Siegert, A. Behar, M. Bentley, D. Blake, S. Bowden P. Chritoffersen, C. Cockell, H. Corr, D. C. Cullen, H. Edwards, A. Ellery, C. Ellis-Evans, G. Griffiths, R. Hindmarsh, D. A. Hodgson, E. King, H. Lamb, L. Lane, K. Makinson, M. Mowlem, J. Parnell, D. A. Pearce, J. Priscu, A. Rivera, M. A. Sephton, M. R. Sims, A. R. Smith, M. Tranter, J. L. Wadham, G. Wilson, and J. Wodward, Lake Ellsworth Consortium, Exploration of Ellsworth subglacial lake: a concept paper on the development, organisation and execution of an experiment to explore, measure and sample the environment of a West Antarctic subglacial lake. Reviews in Environmental Science and Biotechnology, 2007, 6, 161–179. 41. B. Sherwood, Mars sample return: architeture and mission design. Acta Astronautica, 2003, 53, 353–364. 42. J. D. Rummel and L. Billings, Issues in planetary protection: policy, protocol and implementation. Space Policy, 2004, 20, 49–54. 43. J. D. Rummel, P. D. Stabekis, D. L. Devincenzi, and J. B. Barengoltz, Cospar’s planetary protection policy: A consolidated draft. Advances in Space Research, 2002, 30, 1567–1571; and updates for the introduction of category IVc missions to Mars at http://www.cosparhq. org/Scistr/Pppolicy.htm—published 25 March 2005. 44. J. M. Pillinger, C. T. Pillinger, S. Sancisi-Frey, and J. A. Spry, The microbiology of spacecraft hardware: lessons learned from the planetary protection activities on the beagle 2 spacecraft. Research in Microbiology, 2006, 157, 19–24. 45. S. Lee, S. Lee, and K. B. Song, Effect of gammairradiation on the physicochemical properties of porcine and bovine blood plasma proteins. Food Chemistry, 2003, 82, 521–526. 46. T. Grieb, R.-Y. Forng, R. Brown, T. Owolabi, E. Maddox, A. McBrain, W. N. Drohan, D. M. Mann, and W. H. Burgess, Effective use of gamma irradiation for pathogen inactivation of monoclonal antibody preparations. Biologicals, 2002, 30, 207–216. 47. D. P. Thompson, P. K. Wilson, M. R. Sims, D. C. Cullen, J. M. C. Holt, D. J. Parker, and M. D. Smith, Preliminary investigation of proton and helium ion radiation effects on fluorescent dyes for use in astrobiology applications. Analytical Chemistry, 2006, 78, 2738–2743. 48. B. L. Tang, A case for immunological approaches in detection and investigation of alien life. International Journal of Astrobiology, 2007, 6(1), 11–17.
20
BIOSENSOR APPLICATIONS
49. D. Fernandez-Remolar, J. Gomez-Elvira, F. Gomez, E. Sebastian, J. Martin, J. A. Manfredi, J. Torres, C.G. Kesler, and R. Amils, The Tinto river, an extreme acidic environment under control of iron, as an analog of the Terra Meridiani hematite site of Mars. Planetary and Space Science, 2004, 52, 239–248. 50. V. Parro, J. A. Rodriguez-Manfredi, C. Briones, C. Compostizo, P. L. Herrero, E. Vez, E. Sebasti´an, M. MorenoPaz, M. Garc´ıa-Villadangos, P. Fern´andez-Calvo, E. Gonzalez-Toril, J. Perez-Mercader, D. Fernandez-Remolar, and J. Gomez-Elvira, Instrument development to search for biomarkers on Mars: terrestrial acidophile, iron-powered chemolithoautotrophic communities as model systems. Planetary and Space Science, 2005, 53, 729–737. 51. P. Fernandez-Calvo, C. Nake, L. A. Rivas, M. Garc´ıaVilladangos, J. G´omez-Elvira, and V. Parro, A multi-array competitive immunoassay for the detection of broadrange molecular size organic compounds relevant for astrobiology. Planetary and Space Science, 2006, 54, 1612–1621. 52. J. G. Maule and A. Steele, A Prototype Life Detection Chip, In: 35th Lunar and Planetary Science Conference, League City, Texas, 2004 March 15–19, Abstract no. 2091. 53. R. K. Obousy, A. C. Tziollas, K. Kaltsas, M. R. Sims, and W. D. Grant, Searching for extant life on Mars:
54.
55.
56.
57.
58.
the ATP-firefly luciferin/luciferase technique. Journal of the British Interplanetary Society, 2000, 53, 121–130. D. V. Lim, J. M. Simpson, E. A. Kearns, and M. F. Kramer, Current and developing technologies for monitoring agents of bioterrorism and biowarfare. Clinical Microbiology Reviews, 2005, 18, 583–607. O. Y. F. Henry, S. Piletsky, W. D. Grant, M. R. Sims, and D. C. Cullen, Robust Molecular Imprinted Polymer Thin-Films for An Astrobiology Biomimetic Sensor Array, in Proceedings of the First European Workshop on ExoAstrobiology, Huguette Lacoste, Graz, Austria, ESA SP518, 2002 September 16–19, 513–514. M. R. Sims, D. C. Cullen, N. P. Bannister, W. D. Grant, O. Henry, R. Jones, D. McKnight, D. P. Thompson, and P. K. Wilson, The specific molecular identification of life experiment (SMILE). Planetary and Space Science, 2005, 53, 781–791. N. R. Izenberg and O. M. Uy, Molecularly Imprinted Polymer Geochemical Detectors for Outer Solar System Exploration, in Forum on Innovative Approaches to Outer Planetary Exploration 2001–2020, Lunar and Planetary Institute, Houston, TX, 2001, p. 42. R. Shotwell, Phoenix—the first Mars Scout mission. Acta Astronautica, 2005, 57, 121–134.
82 Biacore – Creating the Business of Label-Free Protein-Interaction Analysis Stefan L¨of˚as Biacore AB, Uppsala, Sweden
1 INTRODUCTION
The impact of biosensors on life science research has gone through a tremendous development since the early 1980s. Significant advances have been made: new detection principles for different types of applications, improved commercialization of biosensor instruments, and a much better general understanding of the potential and limitations of biosensors. Despite these major advances, there are not many good examples of successful business cases directly related to biosensor technologies. One clear exception, however, is the company Biacore AB in Sweden, and its development of commercial optical biosensor instruments based on surface plasmon resonance (SPR) detection. The company started research and technology development in the mid 1980s and, because of major breakthroughs in surface chemistry, detector development, and microfluidics-based sample handling successfully launched the first in a subsequent series of bioanalytical instrumentation in 1990. The label-free, real-time interaction analysis made possible by these technological developments has proven to be a versatile, general tool for studies of different types of protein and biomolecular interactions within academic life science research, drug discovery and development, manufacturing and quality control, and, more recently,
within a completely new market of food analysis. The instruments are used for a wide range of applications with typical data including specificity assays, binding affinities and kinetics, concentration measurements, as well as thermodynamics. Over the years, new systems have been launched to meet the needs within the widening range of user environments. This chapter describes the Biacore story from a business case perspective, with special emphasis on the reasons for the successful outcome, both from the technology and corporate perspectives. Recent developments in the technology, applications, and new instruments are also included.
2 BACKGROUND AND RATIONALE BEHIND BIACORE
Sweden has a long tradition in the development of instrumentation and other tools for the life science industry. This tradition began with Professor Theodor Svedberg at Uppsala University, who was instrumental in developing the ultracentrifuge in the 1930s, and Professor Arne Tiselius, inventor of the electrophoresis technique, both later rewarded with the Nobel prize. Commercialization of these technologies was successfully achieved via the Swedish companies Pharmacia Fine Chemicals AB and LKB Produkter AB (now both part
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BUSINESS AND REGULATORY ISSUES
of GE Healthcare), which subsequently have been very active in providing tools for biomolecule purification and analysis. Realizing the potential in new biosensor technologies, Pharmacia, in 1984, decided to establish the new company, Pharmacia Biosensor AB (later renamed to Biacore AB), to develop bioanalytical systems based on new basic research developments. Close contacts and collaborations with the academic community in Sweden had laid the foundations for this new company. In particular, the team formed by Professor Ingemar Lundstr¨om at Link¨oping University in the late 1970s was very important in this context. Lundstr¨om initiated the research around various physical detection technologies for use in new areas such as chemical, biochemical, and clinical analysis. At the same time, the National Defense Research Institute in Sweden had started a program in close collaboration with Professor Lundstr¨om, focused on research into new technologies for the detection of chemical and biological warfare agents. Pharmacia Biosensor was formed with the belief that the new technologies would result in a shift in the way analysis of biomolecules would be performed. Other ongoing biosensor-related activities within Pharmacia were also consolidated into this new entity, into which staff were initially recruited both from research groups and Pharmacia. During a three-year period from 1985 to 1988, basic technology development was carried out for a totally new instrument concept based on SPR detection. This was made possible by creating a truly cross-disciplinary team working in all areas, from mechanics, optics, electronics, and software development to chemistry and biochemistry. As described in more detail, novel technology solutions were achieved within surface chemistry, microfluidics, and in the configuration of the optics. The company included former Pharmacia staff with experience, and mind-set, from product development. Following these research activities, a seamless commercialization phase then resulted in the first product launch in 1990. This phase was based on the evaluation of various business concepts for the technology, which resulted in a primary focus on products for biomolecular interaction analysis studies aimed toward the life science research community in academia and the
pharmaceutical industry. Other potential applications, such as concentration analysis of analytes in the clinical diagnostics area were also evaluated, but it was realized that both the technical and commercial competition was significant within this area of use. The availability of SPR-based instruments for real-time, label-free biomolecular interaction analysis was well timed to meet the growing needs for better understanding of the relationships between structure and function of biomolecules, particular proteins, and nucleic acids. With the molecular biology revolution in the 1980s, entirely new collections of tools were created for efficient construction of antibodies, mutant variants of proteins with important biological functions, as well as oligonucleotide collections. Consequently, quantitative determination of function in relation to structural variations in biomolecules had become a real need and with the launch of Biacore’s first systems, the company had created a user-friendly, high-quality, and versatile tool that provided an entirely new type of approach for obtaining important data. In particular, reliable information could be obtained about relevant parameters like specificity, activity, affinity, and binding kinetics of the biomolecules. From a funding perspective, this timing was also important. Significant investments were made initially by Pharmacia and later by Swedish risk capital during years of positive, forward-looking attitudes. The situation was more difficult during the early 1990s, when the funding climate became much more restricted in conjunction with a more narrow focus on the genomics area. The areas of protein analysis and antibody-based therapeutics became less favored, a situation that did not change until the proteomics revolution came into being in the late 1990s.
3 THE TECHNOLOGY BEHIND BIACORE SYSTEMS
In Biacore systems, the phenomenon of SPR is used to measure mass concentration-dependent changes in refractive index close to a sensor surface. The potential of SPR-based optical detection for biomolecular interaction studies was first described in 1983 in a publication from Professor Lundstr¨om’s group.1 They used an
BIACORE – LABEL-FREE PROTEIN-INTERACTION ANALYSIS
experimental setup with reflectivity measurement at a fixed angle of incidence halfway down the reflectance minimum. There are also several other possible configurations of SPR detectors, which are described elsewhere in this book, and have been reviewed elsewhere, see, for example, Garland.2 However, the application focus for the commercialization of Biacore instruments required a new detector concept. Limitations in prior art solutions for parameters like detection rate, sensitivity, and dynamic range, as well as the dependence on specialists for the acquisition of data were strong driving forces for the creation of the system. This involved the integration of exchangeable sensor surface with stationary optics, miniaturized sample handling, and real-time data readout and interpretation.3 In particular the development of three cornerstones was instrumental for the successful launch of an easy-to-use and reliable new technology: (i) integrated optical detection, (ii) sensor surfaces with biospecific coatings, and (iii) the integrated microfluidic cartridge for controlled sample delivery (Figure 1).
3.1
3
Detection
The optical detectors in the original Biacore systems where constructed using a Kretschmann configuration, with back-illumination of the chip via a prism and a light emitting diode as light source. This creates a wedge-shaped light beam with a range of incident angles, which employs a photodetector array as an imaging system (Figure 2). This enables the monitoring of changes in the reflection angle over time without the need for any movable parts, with high dynamic range, and high linearity over the whole range.4 The configuration also allows simultaneous monitoring of multiple sensing spots. In the first commercialized Biacore systems, four spots were defined by docking the flow cells in the integrated microfluidics, toward the sensor chip. To enable a user-friendly handling of the sensor interface, innovative solutions were developed. A separate sensor surface consisting of a glass substrate with a thin gold coating for the resonance interaction is used for quick exchange after usage. Efficient optical contact between the prism
Intergrated SPR detection
Coated sensor surfaces
Integrated microfluidic cartridge
Figure 1. Picture of a Biacore instrument with the cornerstones outlined: optical detection system; integrated microfluidic system; sensor chips with dextran chemistry coating.
4
BUSINESS AND REGULATORY ISSUES
Light source Reflectance minimum
Sensor chip
Photodetector array
Figure 2. Schematics of the optical detection system in Kretschmann configuration with light source, sensor chip, flow cells, and array detector.
and the sensor surface is achieved by a novel thin interfacing unit (optointerface) consisting of a glass substrate coated with an elastomer layer with matching refractive index. This eliminated the inconvenient use of matching oil. A docking mechanism built into the instrument facilitated a defined and repeatable assembly of the detector unit, the optointerface, sensor chip, and microfluidics.
3.2
Sample Handling
The intended applications also placed special demands on the quality, precision, and amount of sample delivery to the sensor areas in the SPR detector. The possibility for multiplex detection in different sensor areas also has to be matched with flexible addressing of the samples, simultaneously or in sequence. These requirements led to the development of a totally new type of integrated fluidic handling cartridge (IFC), connected to pumps for liquid delivery over the sensor surface, and an autosampler module for sample transfer from microtiter plates or other types of vials to the IFC.5 The fluidics cartridge consists of microchannels and diaphragm valves that are pneumatically operated to facilitate precise switching between buffer flow and delivery of a well-defined sample plug (Figure 3). The valves are placed near the sensor areas, thereby reducing dispersion to a minimum.
The flow channels are formed by precision casting in a hard silicon polymer plate. The thin-layer flow cells in the sensor area are formed by pressing the sensor chip against a part of the IFC with multiple open rectangular grooves at the outlet side of the microchannels. Typical dimensions for the flow cell are 1.6-mm long, 500-µm wide, and 50-µm high, with a total cell volume of 40 nl. The thin-layer flow cell enables optimal mass transfer conditions with linear flow rates from 1 to 100 µl min−1 .
3.3
Surface Chemistry
In the first publications describing the use of SPR for biochemical detection, the surface-associated component (a potential interaction partner) was attached by simple adsorption to the metal surface. However, owing to the high tendency for the fragile proteins to denature on adsorption to solid surfaces resulting in a loss or alteration of binding properties, a more elaborate strategy was needed to meet the demands for a generalpurpose sensor surface with reliable immobilization methods for different kinds of biomolecules. Prior art techniques for immobilization of proteins to various types of surfaces were developed for label-based detection, but because of the relative limitation in sensitivity of label-free techniques, novel surface-attachment approaches that
BIACORE – LABEL-FREE PROTEIN-INTERACTION ANALYSIS
5
Valves
Sensor chip
Valve Figure 3. Schematics of the integrated microfluidic cartridge of original Biacore instrument with flow cell dimensions and membrane valves outlined.
preserved binding activity were required. Development of such techniques focused on (i) minimizing nonspecific binding and denaturation, (ii) maximizing immobilization capacity, and (iii) introducing functional groups for the covalent coupling of biomolecules. On the basis of the concept of self-assembled molecular monolayers (SAM) of thiol or disulfide molecules on metal surfaces, originally developed by Allara and Nuzzo as models for interface studies,6,7 hydroxyl-terminated long-chain thiol alkanes were designed for the formation of the SAM on gold.8 This layer forms the basis for a low adsorbing interface that can be further derivatized in a stepwise manner with carboxymethyl dextran (CM-dextran). This thin hydrogel-like polymer layer, based on dextran polymer, is composed of mainly unbranched glucose units, providing high flexibility, and water solubility. The introduction of carboxymethyl groups facilitates further activation for subsequent immobilization of different biomolecules (Figure 4). This type of surface modification successfully meets the multiple objectives outlined previously:
• The hydrogel-like layer provides a highly hydrophilic environment with an intrinsically low nonspecific protein adsorption. • The extended polymer structure increases the binding capacity severalfold compared to flat surfaces. • Dextran is also highly suited for well-defined covalent immobilization of proteins that rely on a wide variety of chemistries. • Finally, this thin-layer extension is well matched to the penetration depth of the SPR evanescent wave.9 The carboxylic acid residue in the CM-dextran coating acts as a functional group that can either be used for direct coupling or be switched to other functionalities. Figure 5 shows how the carboxylic groups can either be directly reacted with amine groups or be converted for use in coupling chemistries based on thiol reactions, aldehyde and carboxylic acid condensations, and biotin capture techniques. The amine coupling method in combination with the CM-dextran surface is by far the most widely used immobilization strategy in Biacore instruments.10
BUSINESS AND REGULATORY ISSUES
OH
OH
O
OH
Diglyme/ 0.4 M NaOH (1:1)
O
OH
OH
OH
OH
OH
OH
O
6
+
SAM
Cl
Glass/gold substrate
Dextran/ 0.1 M NaOH COOH COOH
OH
OH
O
OH
1 M NaOH
OH
BrCH2COOH
OH
OH
O
OH
OH
COOH
Figure 4. Chemistry modification sequence for the carboxymethylated dextran–coated sensor chip.
O Ligand NH2
PDEA EDC/ NHS COOH
O C N
S
H
O O C ON O
S
(1) Cystamine
O
(2) DTE (DTT)
C N H
Hydrazine
O
Ligand SH N
Ligand SH
SS
(1) Ligand C
C NHNH2
N
C NH Ligand Amine
O C N H
H
(2) NaBH3CN
Ligand thiol
SS Ligand
Surface thiol
O C N H
O
SS Ligand
O C NHNHCH2 Ligand Aldehyde O
Aminobiotin C
NH
Biotin
Figure 5. Alternative attachment chemistries starting from the carboxylic functions of the sensor chip, including direct amine coupling, surface thiol, ligand thiol, aldehyde, and biotin coupling.
Achieving high-capacity immobilization levels relies on a novel approach, with electrostatic attraction of the proteins to an N -hydroxysuccinimide (NHS) ester-activated, carboxylated surface, on which a fraction of the carboxylic groups remains unreacted.11 Much lower protein concentrations than those normally used in
coupling to solid phases can consequently be employed. The reaction times are also considerably shorter, in the range of 1–10 min. Coupling occurs under very mild conditions, where only a small fraction of the nucleophilic groups on the protein are reactive (e.g., the amino groups on the lysine residues are unprotonated), which results
BIACORE – LABEL-FREE PROTEIN-INTERACTION ANALYSIS
in very few immobilization points, little or no cross-linking, and a high likelihood of preserving activity.
4 ASSAYS AND METHODOLOGY
The data output from assays performed by Biacore systems required a new set of terminology.12 The real-time monitoring of the responses generated by association or dissociation of molecules to the sensor chip was termed sensorgram, by analogy with chromatograms, for example (Figure 6). Responses resulting from mass concentrationdependent changes in the plasmon resonance angle were given an arbitrary unit called resonance unit (RU ). Verification experiments have shown that 1 RU is approximately 1 pg mm−2 for a typical protein.13 Responses can also be recorded at specific times and are called report points. The inclusion of a step called regeneration, where the bound analyte is removed from the surface by the injection of a suitable solution, is enabled by the continuous monitoring of the absolute response
7
of the surface coverage, showing that the step is quantitative and that the surface is ready to be used in a new analysis cycle. The most-used assay format is a direct binding assay where the interaction between an immobilized interactant and an injected analyte is measured. Affinity and kinetics measurements are normally performed using this format. Subsequent injections of binding molecules can also easily be performed in a so-called sandwich assay, using an antibody for verification or enhancement of the first binding for example. Alternative assay formats include competition-based assays, where an analyte in solution competes for binding to the interacting partner with a derivative of the analyte attached to the surface. This assay format is most commonly used for concentration determinations, in food analysis applications for example.14
5 APPLICATIONS
There is no doubt that the main reason for the wide acceptance of Biacore’s technology has
Report point
Response (RU)
Curve shape reveals kinetics of interaction
Binding response
Baseline
Time
Baseline Association (buffer) (sample solution)
Dissociation (buffer)
Figure 6. The basics of a sensorgram: a real-time monitoring of the change in the reflectance minimum angle (response) as a function of time. The response is expressed in the arbitrary unit RU. Response levels at specific time intervals are called report points.
8
BUSINESS AND REGULATORY ISSUES
been driven by its use in quantitative kinetics and affinity analysis of biomolecular interactions within basic and applied research.12 This is evident from the steady stream of peer-reviewed papers published since 1990. Until 2005, more than 4500 papers based on data obtained with Biacore instruments can be tracked. Thorough reviews of the content of these articles have been published on a regular basis from Myszka and collaborators.10,15–18 The wide spread of journals where these papers appear underline the versatility of this technology and demonstrate that it now has emerged as a well-established, common biophysical tool, alongside the likes of analytical chromatography, mass spectrometry, and light spectroscopy. Among the plethora of different applications, those related to studies involving antibodies or fragments thereof are most abundant. Interactions studies involving antibodies were amongst the earliest important applications after the launch of the first Biacore systems as a result of the development of monoclonal antibody technology in the 1980s. Antibodies or similar binding molecules have become an indispensable tool for use in various types of diagnostic assays and more recently as reagents in biomarker research. But perhaps more importantly, antibody development has, over the last couple of years, finally reached a level where the therapeutic applications have reached maturity, largely owing to the introduction of humanized antibodies and variants thereof. Today some 20 antibodies are approved as therapeutic drugs and several hundred are in various stages of clinical trials. Biacore systems have become standard tools in the selection, characterization, and optimization stages of the antibodies, where data of both the affinity and the binding kinetics to the target molecule are central. The use of Biacore technologies in monitoring the adverse effects of unwanted immune responses has also developed as a natural consequence of the increasing success of biotherapeutic drugs, where immunogenicity is a common side effect of this drug class.14 Here the real-time monitoring of weak-affinity antibodies with rapid kinetics in human plasma, which have developed as a result of the administration of the therapeutic drug, can be performed with Biacore systems. These
antibodies can be clinically significant and crucially, such data are hard or impossible to achieve with more common techniques like enzyme-linked immunosorbent assay (ELISA). Within basic research, there are a large number of publications related to a wide variety of protein–protein interactions in the context of various disease areas such as cancer, neuroscience, and infection. Most prominently, Biacore systems are used within cancer research, aiming at a deeper understanding of the cellular signaling cascades involved, which present potential therapeutic targets for the development of better cancer drugs. Examples include studies performed to evaluate binding properties of substances that potentially intervene in growth factor interactions with cellsurface receptors in order to regulate the downstream signaling.12 The performance of Biacore systems has steadily improved, and studies of direct, small-molecule binding to immobilized proteins or oligonucleotide structures are now routinely performed. This has been made possible by improved detector sensitivity, efficient signal referencing, and improved data handling. Kinetic analysis of small-molecule binding can also be achieved, which has opened up entirely new applications within the drug discovery area. In particular, the detailed characterization of the kinetic binding properties of lead compounds to their target proteins has recently attracted great interest as a means for obtaining additional information in the selection and optimization process to the final drug candidate.19–21 Traditionally, the potency of a drug candidate is measured by the equilibrium binding affinity measurements. However, information about the on-rate and off-rate binding gives an additional dimension for understanding the drug interaction with the target, which can be directly relevant to their therapeutic efficacy. With the advent of fragment-library screening approaches as an alternative to traditional compound libraries, drug discovery requires a novel analytical solution. These small compounds have weak-affinity binding to the target proteins, but have the potential to be better in the optimization to the final candidate. Biacore systems provide an attractive alternative in this screening process, as weak, transient binding down in the millimolar range can be detected.
BIACORE – LABEL-FREE PROTEIN-INTERACTION ANALYSIS
6 BUSINESS ASPECTS
At the launch of the first commercial system in 1990, Biacore had already established its own sales and marketing organization in the United States and in Europe. This was achieved with key people partly recruited from the sister company, Pharmacia Biotechnology, who already had knowledge about a potential customer base and an understanding of the needs for a new technology for protein-related analysis. In Japan and other parts of Asia too, an early introduction was made possible by the use of the Pharmacia organization as a distributor. The market introduction was initially limited to few applications and mostly related to antibody-based studies, but close relationship with the early users successively built up examples for wider applications. One important vehicle here was the introduction of a user-group meeting forum called Biasymposium, the first in London in 1991 followed by annual events in the United States, Europe, and later in Japan. Here the users are given possibilities to present data, and participants can interact with other users, potential buyers, and experts in the use of Biacore systems. Biacore sales have steadily increased over the years to reach an annual revenue level around 500–600 million SEK ($50–70 million, depending on currency exchange rates). More than 2500 instruments have been sold and besides the instrument revenues, consumables like sensor chips and coupling reagents generate a significant recurrent business stream. The early establishment of a complete organization with all functions from R&D and manufacturing to sales and marketing has also been important in the development of a profitable company, which happened as early as 1995. The sales organization has grown accordingly, with multiple sales and support teams in each of the different regions; the latest addition being the establishment of an organization in China in May 2006. The wide range of applications in various fields, as witnessed by the reference list covering more then 4500 peer-reviewed publications (2006), has become of great importance for successful marketing. As already described, the technology has gradually expanded from initial use for protein–protein interactions in academia and pharmaceutical research into further downstream applications in the drug discovery and
9
development process. During recent years, interesting applications have also increased within the food analysis area.14 Concentration determinations of additives of vitamins in food and testing of drug residues have traditionally been made with standard techniques like ELISA and microbiological methods. By applying immunobased competitive methods on the Biacore platform, reliable, automated analysis using ready-to-go kits is now possible. To date, kits have been developed for a range of B-vitamins such as folic acid, vitamin B12, and biotin, as well as for drug residues such as the antibiotics sulfonamides, beta lactams, and hormones such as clenbuterol. 7 RECENT DEVELOPMENTS AND FUTURE OUTLOOK
It is evident that the technology underlying Biacore systems has improved greatly since the introduction in 1990. The original instrument was designed to measure interactions based on mass changes from proteins and peptides larger than 5000 Da. More recent instruments such as Biacore S51 (2001) and Biacore T100 (2005) now readily detect binding of small molecules with molecular weight down to 100 Da. Likewise, the measurable intervals for the association rate constant have improved from 105 to ∼108 M−1 s−1 and dissociation rate constants from 10−2 to ∼1 s−1 . Equilibrium affinity measurements can now be made within the millimolar to picomolar range. This has been accomplished by improvements in the detector hardware, reference subtraction, and numeric analysis of the sensorgrams. The user friendliness is another part that has developed tremendously and guided methods for the control and evaluation software (e.g., software wizards) speed up experiments and secure data quality. For example, in Biacore T100 a thermodynamics wizard is implemented that runs an experiment with automatic changes in temperatures and subsequent data evaluation for generation of the energy parameters. Another example of how Biacore technology has developed and adapted is related to fulfilling the requirements placed by regulatory authorities such as the Food and Drug Administration (FDA) in the United States on instruments providers. These have increased significantly during recent years. In particular, instruments for use
10
BUSINESS AND REGULATORY ISSUES
in drug development and quality control have to follow rules to meet the demands related to good practice (GxP) including traceability of electronic records. Therefore, all recently developed Biacore instruments that are intended for use within these environments are fully compliant with these regulations. The proteomics era has increased the demands for higher throughput in the generation of proteininteraction data. The increased use of Biacore systems in the pharmaceutical and biotech drug discovery has also generated a demand for increased throughput for applications in drug candidate screening. A first major step to meet these demands was made with the launch of Biacore A100 in 2005. On the basis of the same core technology as its predecessors, this system is configured with a fluidic system with four parallel flow cells, each including five detection spots (Figure 7). Individual addressing of each spot using hydrodynamic flow steering enables precise in situ immobilization of different interaction partners. Flexible assay configurations facilitate generation of several hundred up to thousands of data points per day with the same quality of data as the previous systems. Built-in software for quality control of the sensorgrams enables quick
4 flow cells—5 spots monitored in each
processing of and selection from the large volume of data generated. In keeping with its position as global leader in the protein-interaction-analysis market, Biacore has also begun to acquire externally developed technology that complements its business. Flexchip (acquired in 2005) has an SPR-based, interaction-array format that enables analysis of a single sample against up to 400 interactants simultaneously, thus facilitating rapid interaction profiling and selection in upstream research applications. We have come a long way from the first data on the original Biacore to today’s advanced instruments. The technology is now totally accepted as a central biophysical tool for characterizations of interactions with proteins and other biomolecules. It is likely that the future will see wide-ranging further improvements, such as in small-molecule studies, higher throughput, assay configurations, and data handling. The proteomics area will be central for life science research and drug discovery for several decades to come and the continuing development of high-performance systems from Biacore should contribute significantly to this next exciting phase in biomedical research and development.
Flow cell system enables flexible assay design Optimized for sample throughput 4×5 immobilized interactants 4 samples = 20 interactions/cycle
Optimized for information per sample 20 immobilized interactants 1 sample = 20 interactions/cycle Figure 7. Schematics of the flow cell system in Biacore A100, comprising four parallel flow cells, designed for hydrodynamic addressing. Five detection spots can be simultaneously monitored in each flow cell and up to 20 interactions can be characterized during each analysis cycle. Examples of different assay designs are outlined.
BIACORE – LABEL-FREE PROTEIN-INTERACTION ANALYSIS
REFERENCES 1. B. Liedberg, C. Nylander, and I. Lundstr¨om, Surface plasmon resonance for gas detection and biosensing. Sensors and Actuators, 1983, 4, 299–304. 2. P. Garland, Optical evanescent wave methods for the study of biomolecular interactions. Quarterly Reviews of Biophysics, 1996, 29, 91–117. 3. U. J¨onsson, L. F¨agerstam, B. Ivarsson, B. Johnsson, R. Karlsson, K. Lundh, S. L¨of˚as, B. Persson, H. Roos, I. R¨onnberg, S. Sj¨olander, E. Stenberg, R. St˚ahlberg, ¨ C. Urbaniczky, H. Ostlin, and M. Malmqvist, Real-time biospecific interaction analysis using surface plasmon resonance and a sensor chip technology. Biotechniques, 1991, 11, 620–627. 4. B. Ivarsson and M. Malmqvist, Surface Plasmon Resonance-Developments and Use of BIACORE Instruments for Biomolecular Interaction Analysis, in Biomolecular Sensors, E. Gizeli and C. R. Lowe (eds), Taylor & Francis, London, 2002, pp. 241–268. 5. S. Sj¨olander and C. Urbaniczky, Integrated fluid handling system for biomolecular interaction analysis. Analytical Chemistry, 1991, 63, 2338–2345. 6. R. G. Nuzzo and D. J. Allara, Adsorption of bifunctional organic disulfides on gold surfaces. Journal of the American Chemical Society, 105, 1983, 4481–4483. 7. A. Ulman (ed), Thin Films: Self-Assembled Monolayers of Thiols, Academic Press, San Diego, 1998. 8. S. L¨of˚as and B. Johnsson, A novel hydrogel matrix on gold surfaces in surface plasmon resonance for fast and efficient covalent immobilization of ligands. Journal of the Chemical Society, Chemical Communications, 1990, 21, 1526–1528. 9. S. L¨of˚as, M. Malmqvist, I. R¨onnberg, E. Stenberg, B. Liedberg, and I. Lundstr¨om, A novel hydrogel matrix on gold surfaces in surface plasmon resonance sensors for fast and efficient covalent immobilization of ligands. Sensors and Actuators B, 5, 1991, 79–84. 10. D. G. Myszka, Survey of the 1998 optical biosensor literature. Journal of Molecular Recognition, 1999, 12, 390–408. 11. B. Johnsson, S. L¨of˚as, and G. Lindquist, Immobilization of proteins to a carboxymethyldextran modified gold
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
11
surface for biospecific interaction analysis in surface plasmon resonance. Analytical Biochemistry, 1991, 198, 268–277. G. Franklin and A. McWhirter, Seeing Beneath the Surface of Biomolecular Interactions: Real-Time Characterization of Label-Free Binding Interactions Using Biacore’s Optical Biosensors, in Protein Microarray Technology, D. Kambhampati (ed), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, 2004, pp. 57–106. E. Stenberg, B. Persson, H. Roos, and C. Urbaniczky, Quantitative determination of surface concentration of protein with surface plasmon resonance by using radiolabeled proteins. Journal of Colloid and Interface Science, 1991, 143, 513–526. R. Karlsson, SPR for molecular interaction analysis: a review of emerging application areas. Journal of Molecular Recognition, 2004, 17, 151–161. R. L. Rich and D. G. Myszka, Survey of the 1999 optical biosensor literature. Journal of Molecular Recognition, 2000, 13, 388–407. R. L. Rich and D. G. Myszka, Survey of the year 2000 commercial optical biosensor literature. Journal of Molecular Recognition, 2001, 14, 273–294. R. L. Rich and D. G. Myszka, Survey of the year 2001 commercial optical biosensor literature. Journal of Molecular Recognition, 2002, 15, 352–376. R. L. Rich and D. G. Myszka, Survey of the year 2003 commercial optical biosensor literature. Journal of Molecular Recognition, 2005, 18, 1–39. R. L. Rich, L. R. Hoth, K. F. Geoghegan, T. A. Brown, P. K. LeMotte, S. P. Simons, P. Hensley, and D. G. Myszka, Kinetic analysis of estrogen receptor/ligand interactions. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99, 8562–8567. S. L¨of˚as, Optimizing the hit-to-lead process using SPR analysis. Assay and Drug Development Technologies, 2004, 2, 407–416. W. Huber, A new strategy for improved secondary screening and lead optimization using high-resolution SPR characterization of compound-target interactions. Journal of Molecular Recognition, 2005, 18, 273–281.
83 Commercialization of DNA Arrays – Affymetrix a Case Study Stanley Abramowitz Advanced Technology Group, Silver Spring, MD, USA
1 INTRODUCTION
Medicine will be practiced in the twenty-first century with the benefit of genotype phenotype relationships. The knowledge of genetics of the human and model organisms has increased exponentially during the last decades along with the knowledge of biological pathways. This knowledge base coupled with the constantly developing technologies of sequencing and resequencing has enabled this coming transformation in the practice of medicine. The Human Genome Program, a cooperative international effort to sequence the human genome and model organisms and to develop advanced methodologies to sequence and resequence genomes has fueled and continues to advance these changes. The advancement of technology continues and the goals of the Human Genome Project in the United States are to develop methodologies for sequencing the human genome for $1000.1,2 The Human Genome Program in the United States is a cooperative venture of the DOE (Department of Energy) and the NIH (National Institutes of Health). More information concerning these programs can be found on the NIH, NHGRI (National Human Genome Research Institute) website: www.genome.gov. These technologies hold the promise for everyone to have their own DNA sequence available in a credit card–sized document with them at all times. This
coupled with the ever-expanding knowledge of genotype phenotype relationships will lead to an era of personalized medicine. Medicine will treat diseases before they are clinically apparent. NCI (National Cancer Institute) and NHGRI have recently announced a $100 million cooperative effort to accelerate the understanding of the molecular basis of cancer through genome analysis technologies including large-scale genome sequencing.3 This three-year project will determine the feasibility of a full-scale effort to systematically study the genomic changes involved in all human cancers. Medicine will treat diseases before they are clinically apparent. Appropriate drugs for the treatment of disease will be chosen, taking into account the patient’s genetic makeup. The number of bad interactions of drugs with the patient or the use of drugs that do not have therapeutic value will be drastically reduced. Much of this development has been and will be realized through the use of DNA arrays. We are already seeing the benefits of this personalized medicine. Herceptin is being used to treat those persons whose breast cancer has the genotype that will be responsive to this medication. Similarly Gleevac is being prescribed for those having a particular type of leukemia that is identified by a DNA diagnostic. Studies have indicated that Iressa is useful for those 10% of lung cancer patients with a particular mutation but is hardly useful for others. The stratification of patients by genotype has the promise
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BUSINESS AND REGULATORY ISSUES
of affording more effective medicine while not using precious time to treat those who will not be responsive to the medication, or worse, damaging the patient. It also will be utilized in drug trials so that those people with genotypes that allow them to be potentially receptive to a particular drug will enter the trials. It will also allow the introduction of drugs for people with particular genotypes. Drugs that will only be useful for small percentages of the total population, which would not be easily approvable without specific knowledge of the patient’s or the cancer’s genotype, will be acceptable for use. This holds the promise of aiding the drug discovery process and possibly leading to fewer failures in phase III clinical studies.
2 DNA ARRAYS – DESCRIPTION
In the late 1980s and early 1990s three research groups working independently of each other were actively doing research that would result in the technology we now know as DNA microarrays. Edward Southern, developer of the Southern blot, developed a methodology to synthesize DNA probes, in situ, using ink-jet technology and in this manner build an array. This development ultimately led to the company Oxford Gene Technology. Other companies, as discussed later, have adopted this technology to construct DNA arrays. Stephen Fodor, working at Affymax, was working on using photolithographic masks to provide the template for the in situ synthesis of DNA probes one oligonucleotide at a time. This technology, which was later developed in Affymetrix, a spin-off of Affymax, afforded the advantage of making very dense DNA microarrays. At about the same time, Patrick Brown at Stanford University was developing a distinct technique for fabricating what he described as DNA microarrays. Brown’s group used previously constructed oligonucleotides and deposited these on glass substrates. Brown popularized this technology by actually publishing detailed methods and plans for the apparatus necessary for the synthesis of DNA microarrays on the web and in the open literature. The technologies he developed were adapted by many companies including Incyte and Agilent. All three of these generic technologies and other
variants that followed afford the researcher the possibility of doing a multitude of experiments in parallel with one of several DNA microarrays. One can use DNA arrays in a multitude of technology areas such as health and health care, clinical diagnostics, basic biology research to assess pathways for biological processes, genome diversity, toxicology, biomass diversity, infectious agent monitoring, agriculture including assessing and maintaining diversity, improving yield, monitoring and improving disease resistance, and assessment of nutritional value, biotechnology, environmental monitoring, measurements of pathogens in food and water, animal husbandry; personal identification, and forensics.4,5 Arrays are used for gene expression, genotype discovery and detection, resequencing, whole-genome analyses, forensics, personal identification, and disease detection and monitoring. In DNA arrays, target single-stranded DNA binds to immobilized DNA probes generating double-stranded DNA. Many different formats can be used in these array technologies, varying from the use of short probes (typically about 25–60 oligonucleotides), to the use of large sequences up to gene sizes, such as those used in FISH (fluorescent in situ hybridization) technologies. There are several methodologies utilized for the fabrication of DNA arrays depending on the length and the density of probes desired. If one is dealing with large lengths of DNA consisting of gene fragments or cDNAs one can use a spotting technique that can deliver DNA via piezoelectric techniques, similar to those used in ink-jet printers or quills. The matrix can be glass, silicon, or a polymer substrate. The ink-jet spotters are commercially available or can be fabricated with available instrumentation. Companies including Agilent,6 Motorola,7 Clinical Microsensors (now Motorola),8 and GE (General Electric)9 utilize these technologies for the fabrication of DNA arrays. DNA arrays based on small polynucleotides with lengths of about 25 oligonucleotides can be made by photolithographic techniques similar to those used in the semiconductor industry. Many probes can be made on a wafer by the use of suitable masks and light-directed synthesis chemistries to construct the desired oligonucleotides on the substrate. The power of this method is that four steps are required for each nucleotide of the probe. So that 100 steps or masks are required for
COMMERCIALIZATION OF DNA ARRAYS – AFFYMETRIX A CASE STUDY
a polynucleotide containing 25 oligonucleotides. Using this technology, more than 106 probes/cm2 can be fabricated. Many arrays can be fabricated on a single wafer and then diced up and packaged. Present technology is producing 10 million probes per DNA array. Each wafer can be diced into tens or hundreds of identical DNA arrays. A “foundry” has been built by Affymetrix, the principle purveyor of this technology, in order to manufacture arrays in bulk and to provide quality control. There has been considerable effort to replace the photolithographic masks with multimirror technologies to direct the light for synthesis. Several companies are using this technology including Nimblegen10 and Febit.11 These companies are not synthesizing the massively dense arrays described in the preceding text. Nimblegen fabricates arrays that are “Affymetrix like” and can be used with the Affymetrix instrumentation. They currently collaborate with Affymetrix, fabricating arrays for fast turnaround, in a program called NimbleExpress. With the maskless technology that is utilized, as many as 12 000 transcripts can be determined with 282 000 unique oligonucleotide probes. Febit is fabricating custom arrays for researchers and others and has introduced a “desktop” array synthesizer, which designs the array and fabricates it from the sequence given to the system. Using this system, a researcher can fabricate several DNA microarrays containing 7600 individual probes. Nanogen12 utilizes a unique system to make short polynucleotide arrays. They utilize the electronic charge inherent in DNA to perform directed synthesis onto an array having as many as 400 probes, each of which can be electronically addressed, thus, allowing the fabrication of the DNA array. Clinical Microsensors (now Motorola) makes use of the fact that doubly stranded DNA is a conductor and allows electron transfer, but is not a “molecular wire”. Therefore, one can determine whether hybridization has taken place by measuring the conductivity of each site in the array. Other technologies including those of Illumina,13 Luminex,14 and Pharmaseq15 utilize “nongeometric arrays”. Illumina uses randomly ordered, addressable high-density optical sensor arrays. DNA is immobilized in microspheres on an optical substrate containing thousands of micrometer-scale wells. The sensors occupy different locations from array to array. A two-color technique is used to separately identify the probe and
3
the hybridized DNA. Luminex and Pharmaseq utilize “homogeneous assays” in which DNA probes are attached to microspheres or transponders and the targeted DNA is hybridized on these probes. The analysis is then done via a flow cell cytometer. In most of the applications fluorescent dye readouts are being used for the assay. Lasers excite the fluorescent dyes, which are chemically attached to the DNA targets, and the emission is analyzed by confocal microscopy or CCD arrays. Other methodologies have also been used including 32 P radioactive labels including mass spectroscopy. Some exceptions to this are explained in the preceding text. There are also a large number or industrial, academic, and government laboratories that utilize other technologies for DNA sequence analysis including electrophoresis and mass spectroscopy.
3 AFFYMETRIX – INTRODUCTION
Affymetrix, a spin-off of Affymax, was founded in 1993 by Stephen Fodor with funding and inspiration from Alejandro Zaffaroni. Zaffaroni, a noted biochemist and experienced and famous venture capitalist, is the founder of many biotechnology companies including Alza (now Johnson & Johnson), Affymax, Dynax, Surromed, Maxygen, Symyx, and Alexza. Before this he did pioneering research at Syntex and served as the president of the company and its research institute. Affymax was founded before 1989. Affymetrix was founded to exploit the developments in the synthesis of DNA microarrays using photolithographic technologies and to provide these DNA microarrays to researchers and ultimately to the Clinical Diagnostic market. Affymetrix received its first patent in 1992 and its first round of funding in 1993. Their Initial Public Offering (IPO) was in 1996. In a similar manner to other biotechnology companies and those in the DNA analysis area they parlayed federal grants to demonstrate their technology. NIH awarded a RO1 grant in 1992 and they received a DOE, Small Business Innovation Research (SBIR) grant in 1993. This was followed by an Applied Technology Program (ATP)16 grant in 1994. This award, a joint award with Molecular Dynamics (now GE), the largest award given by the ATP, was designed to demonstrate the ability to analyze DNA completely
4
BUSINESS AND REGULATORY ISSUES
under computer control from sample preparation through to data analysis. Affymetrix utilized its DNA array technology, while Molecular Dynamics used electrophoresis microchannel plates to analyze the DNA. Both companies were successful in demonstrating their technologies. During this 5-year grant period, they developed other products including the DNA sequencers that were ultimately used together with those from Applied Biosystems to sequence the human genome and other model organisms and the development of DNA microarrays for human immunodeficiency virus (HIV), P53 gene (a gene that normally inhibits the growth of tumors, thereby, preventing or slowing the growth of cancers), and the first gene chip for assaying 1500 single nuclear polymorphisms (SNPs). Moreover the ATP grant provided both companies with exposure and a verification of their technologies, which made subsequent funding and scientific collaborations easier and also provided additional visibility to the scientific community. Affymetrix supplies a complete system for DNA analysis consisting of sample preparation modules with fluidics station, read-hybridization apparatus, data analysis software, and associated workstations. There are over 2000 installations of these systems. The software and workstations provide the researcher with the genes and/or sequences that are found in the target samples. One can also obtain the “raw” data and do the analysis with alternative software. They also built a foundry for the fabrication of chips in 1999 in order to ramp up production of DNA arrays and obtain a greater degree of quality control and reproducibility from batch to batch. By the end of 2004 there were over 3000 archival publications from government, academic, and industrial entities utilizing the Affymetrix technology. Most of these studies focused on humans, but these arrays have also been used to study biology, gene expression, and sequence variation of any organism with a sequenced genome. Affymetrix dominates the market for DNA microarrays controlling about 70% of the market. They have many DNA microarrays in their catalog and also fabricate custom arrays for those requiring small numbers of arrays for research purposes. Many government, academic, and industrial research laboratories, which had fabricated their own DNA microarrays using
technologies based on ink-jet printing or quill printing for their research needs, have switched to Affymetrix DNA microarrays. Presumably, they have switched because of the reproducibility and quality control available in Affymetrix DNA arrays. Some have also utilized DNA microarrays of other companies including Agilent, Motorola, Nanogen, and those nongeometric arrays such as those of Illumina presumably for the same reason. Throughout its corporate existence Affymetrix has been very aggressive in seeking patent protection for its technology in the Americas, Europe, and Asia. They zealously protect these assets and have brought suit with other companies when deemed necessary. They have engaged in many collaborations allowing the cross-licensing of technologies when it is in their interest. They have been successful in settling their most serious patent litigations namely those with Oxford Gene Technology, HySeq, and Incyte. The Incyte litigation also involved Stanford University. The successful settlement of these patent litigation cases has allowed Affymetrix and the others to cross-license their technologies and practice their art. Affymetrix and the other companies exploiting DNA array technologies have had to overcome several hurdles in order to successfully commercialize their technologies. The technology was a new one and a bit complicated for many of the potential users. It marked a distinct change in the way biology research is done. Automated systems coupled with the use of powerful computer technologies replaced the traditional “wet chemistry” that biological researchers were used to. This coupled with the many different arrays that are available from different suppliers and the “homemade” arrays based on Brown’s published technologies for fabricating apparatus for the synthesis of arrays and the analysis of the results made the choice of these expensive systems difficult. This was exacerbated by the lack of compatibility between the various technologies. The patent litigations also added to the problems that these technologies were involved in and did not make these choices easier. Happily for Affymetrix and the other companies involved in DNA array technologies, most of these problems have been resolved.
COMMERCIALIZATION OF DNA ARRAYS – AFFYMETRIX A CASE STUDY
4 AFFYMETRIX PRODUCTS
Affymetrix provides DNA arrays for a multitude of organisms including human, mouse, Drosophila, Caenorhabditis elegans, rat, zebra fish, agricultural species, Arabidopsis, barley, maize, sugarcane, tomato, grape, wheat, and bacteria including Escherichia coli, Plasmodium, and Bacillus subtilis. With these microarrays one can study gene expression, species differences, and so on. By comparing diseased and nondiseased tissue one can find which genes are upregulated and which are downregulated as a result of the disease state. These arrays can also be utilized for the discovery and determination of genotype via SNPs. This allows the researcher to correlate disease states with the existence of SNPs within the diseased genome. High-density DNA microarray technology affords the researcher the ability to analyze nucleotide sequence as well as to measure gene expression, gene diversity, and so on, for essentially the whole human and other genomes in a single experiment, often on a single array.17 Whole-genome analysis can be performed and hence elucidates the molecular basis of disease as well as genetic pathways that are not properly operating in a wide variety of disease states including cancers, infectious diseases, multiple sclerosis, sudden infant death syndrome, and so on. The high-density DNA arrays have been designed to differentiate between splice variants of a single gene each of which yields a different protein. They have also been designed to differentiate between polyadenylation variants. A more complete description of the technology, the available apparatus and microarrays, and the data acquisition systems can be found at the Affymetrix website: www.affymetrix.com.
5 AFFYMETRIX – ACQUISITIONS AND COLLABORATIONS
Early in their corporate life, Affymetrix developed liaisons with academic, industrial, and government laboratories. These collaborations afforded Affymetrix a window into current biological research and how these technologies could be used for the research developments that later could lead
5
to products. Affymetrix supplied these entities with DNA microarrays for their particular needs and the associated instrumentation.
5.1
Acquisitions
Affymetrix has also been quite active in purchasing other companies with core competencies that would be useful to their technology. They acquired Genomic Microsystems, a company that has developed a rapid technology for scanning arrays using confocal microscopy and have also developed methodologies for fabricating lowdensity microarrays. This methodology could be useful for rapid turnaround times for custom arrays that would not necessarily warrant the expense of making the large number of photolithographic masks necessary for the Affymetrix high-density fabrication technology discussed in the preceding text. Affymetrix acquired other companies for the computer algorithms they developed including Neomorphic, a computer genomics company, which has developed successful algorithms for the discovery of unique genes for the identification of potential drug targets. ParAllele a company that has developed unique genotyping reagents for use with the Affymetrix DNA SNP microarrays was acquired in 2004.
5.2
Collaborations
Affymetrix has been very active in fostering collaborations with other companies, academia, and government agencies both in the United States and in other countries. A shortlist of their industrial collaborators listed at their website for 2004–2005 includes Invitrogen,18 Caliper,19 Aventis,20 Curagen,21 GlaxoSmithKline,22 bioMerieux,23 Serono,24 Stratagene,25 and Veridex.26 Of particular interest is their collaboration with PreAnalytix,27 a coventure of Qiagen28 and Becton Dickinson,29 to make kits for blood RNA for use in Affymetrix DNA microarrays. These kits are very useful in improving gene expression assays using the Affymetrix technology. Their academic collaborators include Fred Hutchinson Cancer Center,30 Broad Institute31 (a coventure of Harvard and
6
BUSINESS AND REGULATORY ISSUES
Massachusetts Institute of Technology), Cambridge University,32 Institut Curie,33 Karolinska Institute,34 University of California,35 and Rockefeller University.36 They are collaborating or doing research and development for government laboratories including NHGRI,37 NHLBI38 (National Heart Lung Blood Institute), EPA38 (Environmental Protection Agency), NIAID,39 (National Institute of Allergy and Infectious Diseases), NIMH40 (National Institute of Mental Health), DOE41 and agencies in other countries including Wellcome Trust Case Control Consortium42 and Wellcome Trust Sanger Institute43 and Max Delbruck Center for Molecular Medicine.44 Of particular interest is their work for NIAID, for whom they are fabricating a DNA microarray for the detection of pathogens of interest to biodefense. They will produce DNA microarray(s) for 26 different bacterial and 10 viral species and many of their subspecies. A smallpox DNA microarray is being fabricated with a grant from CDC45 (Center for Disease Control). They are also collaborating with nonprofit entities including National Alliance for Autism Research46 and the Michael J. Fox Foundation.47
5.3
Clinical Diagnostics
Affymetrix has been very active in translating research results into clinical diagnostics. The development of standards for the introduction of DNA microarrays into the drug approval process and for clinical diagnostics has been a complicated issue for the FDA.48,49 They have, with the inputs of academia, industry, and government, issued several guidelines. Affymetrix has a longstanding relationship with Roche50 for the design and fabrication of DNA microarrays for clinical diagnostics. They signed an Easy Access agreement in 1997, in which they agreed to share information for use in the development of clinical diagnostics. In 2003, Roche licensed Affymetrix GeneChip technologies for the development of clinical diagnostics for a host of human ailments including cancer, osteoporosis, and cardiovascular, metabolic, infectious, and inflammatory diseases. This collaboration with Roche has resulted in the introduction of a complete system for clinical diagnostics (similar to those developed by Affymetrix for research uses, but tailor-made for the clinical diagnostic market) that has received FDA
and European approval. The first DNA microarray for use in this system has also recently received approval from FDA51 and European regulators.52 The DNA microarray measures a person’s genotype for the P450 enzyme, CYP4502D6, which is implicated in the metabolism of prescription drugs. It is estimated that the metabolism of 25% of prescribed drugs could be assayed with this DNA microarray. A patient’s genotype for these enzymes is determined with the DNA microarray, and the results are interpreted with Roche software, which indicates the patient’s ability to metabolize and the prescribed drugs and its toxicology based on the patient’s genotype. This DNA microarray is expected to find wide use in the choice of appropriate prescription drugs for a great variety of diseases. This is only the first of what one can expect to be a steady stream of DNA microarrays for a variety of clinical diagnostic uses. There are home brews developed on the basis of scientific papers for a host of applications that utilize Affymetrix DNA microarrays. These DNA microarrays mostly in the gene expression area have been developed and marketed for research use and have not received FDA approval for clinical diagnostic uses. Nevertheless there are laboratories that offer these analyses for a variety of diseases including breast and other cancers, inflammatory, cardiovascular, and so on. These laboratories run these assays and deliver the results to clinical physicians for interpretation. It is still an open question whether gene expression profiles as determined from DNA microarrays or other DNA analysis technologies will receive FDA approval for clinical diagnostic uses.
6 PERLEGEN
Perlegen,53 a spin-off of Affymetrix, was founded in 2000. Its mission is to develop the pharmacogenomics information necessary to predict drug response. Affymetrix retained a majority interest in Perlegen after a $1 000 000 private placement, in 2001. The two facets of drug response, efficacy and safety, are being addressed. This is accomplished by measuring genomic diversity at single-base resolution. They utilize Affymetrix Gene Chip technology for this. Currently, among
COMMERCIALIZATION OF DNA ARRAYS – AFFYMETRIX A CASE STUDY
other DNA microarrays, they are utilizing a twomicroarray set capable of assaying 500 000 SNPs. These microarrays have more than 10 million probes. They have sequenced 50 human genomes to assess human diversity. They have also identified SNPs in 71 individuals of European American, African-American, and Han Chinese American ancestry. Perlegen also does contract research for others and is involved in assaying diversity in other species including rice. They will be collaborating with the International Rice Research Institute to identify SNPs in 15 rice strains.
7 AFFYMETRIX – COMMERCIAL STRATEGY
Affymetrix regards itself as a foundry similar to the foundries that are used for electronic chip fabrication. They have the basic know-how in the design of DNA microarrays and the instrumentation to prepare samples, amplify DNA, hybridize the target DNA on arrays, detect the hybridized DNA using confocal microscopy, and analyze the results using computer algorithms using workstations. They supply all the instrumentation for these tasks as well as data handling systems. They have also developed instrumentation, as discussed earlier, for the analysis of DNA samples in the clinical diagnostic arena. Others including many of their collaborators in industry, government, and academic laboratories have the capability to develop the detailed genetic information necessary for the determination of the genetics and genetic pathways of particular diseases, toxicology, and the choice of drugs for particular disease states and ultimately the development of clinical diagnostics. Affymetrix also collaborates with groups interested in other genomes, including those interested in agricultural, bacterial, viral, and other model organisms. Their website indicates the breadth of their DNA microarray catalog offerings and their research and development interests. They also have a program for the fabrication of custom DNA arrays for research uses. The researcher provides the sequence information and Affymetrix will design and fabricate the DNA microarray for their use. Their industrial collaborators including Roche, bioMerieux, and PreAnalytix take the developed clinical diagnostic through FDA and European
7
approval and market them. Affymetrix receives up-front payment and royalties on the DNA microarrays sold. The companies receive DNA microarrays for their research and development of the eventual product, presumably, at a lower price. Affymetrix will also entertain proposals for collaboration with biotechnology companies including small ones who have genetic expertise, who can supply the necessary genomic information. They would then work collaboratively toward the development of clinical diagnostics. The developed clinical diagnostics could then be brought through the FDA and/or European approval processes and marketed by Affymetrix’s larger collaborators as discussed in the preceding text.
REFERENCES 1. NHGRI Seeks Next Generation of Sequencing Technologies, 2004, www.genome.gov/12513210. 2. NHGRI Expands Effort to Revolutionize Sequencing Technologies, 2005, www.genome.gov/1501528. 3. NIH Launches Comprehensive Effort to Explore Cancer Genomics, The Cancer Genome Atlas Begins with Three-Year, $100 Million Pilot, 2005, www. cancer.gov/newscenter/pressreleases/ CancerGenomeLaunchPressRelease. 4. S. Abramowitz, Towards inexpensive DNA diagnostics. Trends in Biotechnology, 1996, 14, 397–401. 5. S. Abramowitz, DNA analysis in microfabricated formats. Journal of Biomedical Microdevices, 1999, 1, 107–112. 6. www.chem.agilent.com. 7. www.motorola.com/lifesciences. 8. www.amershambiosciences.com. 9. A. C. Pease, D. Solas, E. J. Sullivan, M. T. Cronin, C. P. Holmes, and S. P. Fodor, Light generated oligonucleotide arrays for rapid DNA sequence analysis. Proceedings of the National Academy of Sciences of the United States of America, 1994, 91, 5022–5026. 10. www.nimblegen.com. 11. www.febit.de. 12. www.nanogen.com. 13. www.illumina.com. 14. www.luminex.com. 15. www.pharmaseq.com. 16. www.atp.nist.gov. 17. J. A. Warrington and T. B. Broudy, Microarrays: Human Disease Detection and Monitoring in Nucleic Acid, in Testing and Human Disease, Ch. 3, A. Lorincz (ed), CRC Press, 2006. 18. www.invitrogen.com. 19. www.caliperls.com. 20. www.aventis.com. 21. www.curagen.com. 22. www.gsk-us.com. 23. www.biomerieux.com.
8 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43.
BUSINESS AND REGULATORY ISSUES www.serono.com. www.stratagene.com. www.veridex.com. www.preanalytix.com. www.qiagen.com. www.bd.com. www.fhcrc.org. www.broad.mit.edu. www.cambridge.ac.uk. www.curie.fr. www.ki.se. www.ucdavis.edu. www.rockefeller.edu. www.genome.gov. www.epa.gov. www.idri.gov. www.nimh.nih.gov. www.energy.gov. www.ccc.sanger.ac.uk. www.sanger.ac.uk.
44. 45. 46. 47. 48.
49.
50. 51.
52. 53.
www.mdc-berlin.de. www.cdc.gov. www.naar.org. www.michaeljfox.org. Multiple Tests for Heritable DNA Markers, Mutations, and Expression Patterns; Draft Guidelines for Industry and FDA Reviewers, 2003, www.fda.gov/cdrh/guidance/1210. html. E. F. Pretricoin III, J. L. Hackett, L. J. Lesko, R. K. Puri, S. I. Guttman, K. Chumakov, J. Woodcock, D. W. Feigal Jr, K. C. Zoon, F. D. Sistare, Medical applications of microarray technologies: a regulatory perspective. Nature Genetics Supplement, 2002, 32, 474–479. www.roche-diagnostics.com. New Device Clearance: P450 Genotyping Test and Affymetrix Microarray Instrumentation System— K042259, 2004, wwww.fda.gov/cdrh/mda/KO42259. html. www.devicelink.com/ivdt/archive/04/11/007.html. www.perlegen.com.
84 RAPTOR: Development of a Fiber-Optic Biosensor George P. Anderson1 and David A. McCrae2 1
Center for Bio/Molecular Science and Engineering, US Naval Research Laboratory, Washington, DC, USA and 2 Research International, Monroe, WA, USA
1 INTRODUCTION
Since the discovery of the evanescent wave, scientists have taken advantage of its unique properties to develop biosensor systems.1,2 The maturation of fiber-optic technologies provided new optical platforms for the continued advancement of evanescent wave-based systems.3,4 One particular implementation, fluoroimmunoassays utilizing evanescent wave excitation, had many perceived advantages: high sensitivity, remote near-real-time detection, and surface-sensitive detection for analyses in complex matrices. Among those attracted to exploit this promising avenue were scientists at the US Naval Research Laboratory (NRL). Anticipating the growing threat of biowarfare and bioterrorism, they decided to pursue development of a fiber-optic immunoassay system and evaluate its potential to meet current and future biothreatdetection needs. Anticipation of future military needs is a central theme of NRL, which traces its beginnings back to 1915, when worry over the great European war prompted Thomas Edison to reflect that, “The Government should maintain a great research laboratory. . . . In this could be developed . . . all the technique of military and naval progression without any vast expense.” 5 While over time expenses have risen, the value
placed in protecting our sons and daughters from hostile elements is, if anything, more paramount.
2 NRL FIBER-OPTIC BIOSENSOR
The first NRL fiber-optic biosensor (Figure 1) was assembled on an optical table using off-the-shelf components and utilized step-index plastic-clad silica optical fiber (200-µm core) to form the sensing surface.6 While crude by today’s standards, it did allow testing and validation of the fundamental principles inherent in the development of an efficient evanescent wave sensor system. The keys to creating a highly sensitive immunosensor were efficient evanescent wave stimulation of surfacebound fluorophores with subsequent recovery of that fluorescence and the successful attachment of proteins, primarily antibodies, to the silica surface of the optical waveguides necessary to specifically capture the targeted molecules. The first breakthrough came when Thompson and Villarruel deduced the fiber geometry required to efficiently excite fluorophores at the sensing surface.7 Soon after, Golden and Anderson described in great detail, both theoretically and experimentally, the mismatch in the mode carrying capacity created when an optical fiber’s cladding is removed and its core is placed in a fluid having a lower
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BUSINESS AND REGULATORY ISSUES
detects the fluorescent complex. Assays for a variety of targets such as ricin, botulinum toxoid A, or Yersinia pestis F1 antigen were tested.
3 ANALYTE 2000
Figure 1. Photograph of the NRL fiber-optic biosensor.
index of refraction.8–10 This understanding permitted the design of optimally efficient tapered optical probes. This advance, when coupled with highly effective immobilization chemistry developed earlier at NRL, facilitated the creation of very sensitive sensing elements.11 Once a simple means of encasing the fiber-optical probe in a flow chamber was developed, numerous sensitive immunoassays were readily demonstrated, albeit with considerable difficulty owing to the fragile nature of the fiber-optic probe and the limitations of a single-channel instrument.8,12,13 Most assays developed were sandwich fluoroimmunoassays (Figure 2), where capture antibodies immobilized on the surface of the optical probe bind the antigen. Fluorescently labeled antibody then binds to the captured antigen, and the instrument
While the laboratory breadboard fiber-optic sensor assembled at NRL proved to be a highly effective instrument, it had little else to recommend it. Primarily because of the large size, immense weight (150 lb), and high power requirements, any potential for field use was quite limited. To meet the need for a small, portable, rugged, multichannel instrument capable of performing in the field, NRL requested proposals to construct such an instrument in 1994. Among the many responses was one from Research International (RI), who proposed the Analyte 2000, an instrument that easily met those requirements (Figure 3). Described in detail elsewhere, the instrument used four pairs of diode lasers and photodiodes, which provide the excitation and monitor fluorescence, respectively. Each pair was placed on one of four printed-circuit cards. The cards were mounted on a controller board enclosed in an 8 × 11 × 17-cm box.14 Each card was connected via a fiber bundle jumper to a separate 600-µm core diameter plastic-clad silica optical probe similar in design to the 200-µm core optical probes used on the NRL device. The fiber bundle consisted of a central quartz fiber that carried the excitation light to the probe and a circular array of plastic fibers surrounding the
Capture antibody Cy5-labeled fluorescent antibody Antigen
Figure 2. Schematic of a sandwich fluoroimmunoassay on an optical probe.
Figure 3. Photograph of the Analyte 2000 paired with the NRL automated fluidics unit developed in 1997. Note airplane icons represent number of flights on which this unit was tested, broken wing airplane icons represent crashes.
RAPTOR: DEVELOPMENT OF A FIBER-OPTIC BIOSENSOR
excitation fiber, which carried the returning fluorescence signal. The tapered probe surface readily converted the lower-order modes launched into the fiber into higher-order modes useful to excite fluorescence, and although the tapered probe functioned to convert the higher-order modes of the returning fluorescence into lower-order modes, the majority of the signal was still captured by the circular array of collection fibers. Thus, the arrangement of collection fibers surrounding the excitation fiber proved highly efficient. A laptop computer controlled the instrument through an RS-232 connection. Numerous immunoassays were developed using the Analyte 2000, and its utility for field testing was demonstrated on a number of occasions. The first field test occurred in Korea (1995) immediately following delivery of the first Analyte 2000s (see Figure 4). The Analyte 2000 saw extensive use with many immunoassays being demonstrated on this platform.15–18 In addition, it became the first automated biosensor to fly on an unmanned aerial vehicle (UAV) during testing at Dugway Proving Ground, UT in 1997 and again in 1998 (see Figure 5).19,20 For this test the Analyte 2000 was paired with an NRL custom-built fluidic unit that utilized a microcontroller to manage commercial peristaltic pumps and solenoid valves, and a ramair powered cyclone aerosol collector, built by RI. In a sense, this unit presaged the future development of the BioHawk biosensor described at the conclusion of this chapter. Although NRL moved beyond the Analyte at this point to the
Figure 4. Photograph of the Analyte 2000 being demonstrated at the Demilitarized Zone, Korea, 1995.
3
Figure 5. Photograph of the Analyte 2000 paired with the RI ram-air cyclone and NRL automated fluidics unit developed in 1998. [Reprinted with permission Ligler et al.19 copyright 1998, American Chemical Society.]
testing of follow-on systems, it remains a useful, well-built instrument; other researchers and organizations have continued to utilize this versatile assay platform, aided by the fact that it has been upgraded to allow the use of the same polystyrene fibers utilized by the RAPTOR.21–23
4 RAPTOR
While the Analyte 2000 was a huge improvement over the laboratory breadboard device, it still had operational limitations. Perhaps the most critical were the fragile optical probes, each of which had both fluidics and optical connections that had to be made individually. This limited its operational use to laboratory assay development and the occasional field demonstration. Thus, to meet the desire to have a truly man-portable biosensor, the Navy Technology Insertion Program provided funding in 1997 to develop just such an instrument. This prototype instrument, a precursor to the RAPTOR, was also developed by RI (Figure 6); called the MANTIS, it had many of the desirable features that are still found in the current RAPTOR design. It was a semiautomated self-contained sensor system, with integrated optics, fluidics, electronics, and computer control to perform four parallel immunoassays on a single sample. All the components were enclosed in a hardened 10 × 10 × 7-in. package weighing less than 13 lb, and included a battery to provide power sufficient to operate for over 8 h. The fragile quartz waveguides of the Analyte were redesigned to be manufactured
4
BUSINESS AND REGULATORY ISSUES
Figure 6. Photograph of the Mantis.
from injection-molded polystyrene and included a patented “concentrator” to maximize evanescent excitation and an integral lens to focus the return signal on the photodiode detector. This change not only permitted mass production of the optical probes, but simplified the antibody attachment process as well, thereby enhancing manufacturability. Simple adsorption of the antibody or adsorption of NeutrAvidin followed by a biotinylated antibody replaced the relatively more complex silane/chemical cross-linker chemistry utilized for the silica probes. Once the wave-guide were coated, they were mounted four at a time into assay cartridges. The assay cartridges could then be easily inserted into the instrument and, upon door closure, the optics were aligned and fluidic connections made. The MANTIS was used effectively in several tests, and immunoassays were successfully demonstrated.24 The MANTIS used a pneumatically powered fluidic system both to move fluids and to actuate valves for power conservation and noise control reasons. Unfortunately, because materials with requisite properties to construct reliable, long-endurance pneumatic valves could not be found, the device had an unacceptably high failure rate. To overcome these limitations, the instrument was redesigned to use peristaltic pumps for fluid movement, which had the added benefit of supplanting the need for additional fluidcontrol valves. Numerous design improvements were made over the course of the development
Figure 7. Photograph of the RAPTOR. [Reprinted with permission Jung et al.25 copyright 2003, IEEE.]
of the new instrument, and it was also renamed RAPTOR. The design of the RAPTOR has been described in detail, so only the highlights will be mentioned here (Figure 7).25 The RAPTOR has three reversible peristaltic pumps: one singlechannel pump and two four-channel pumps. The single-channel pump provides the wash buffer. One of the four-channel pumps moves the sample or wash buffer over the four optical probes, and the other four-channel pump moves the reagent from separate tracer reagent vials over each respective probe and then back again. The use of peristaltic pumps solved all reliability issues, exemplified by the fact that we have had a RAPTOR operating now for years without a failure. Additionally, the pumps allowed the use of separate tracer reagents (the MANTIS had a single reservoir in which all four tracers were mixed), thereby obviating the issue of reagent compatibility. Interestingly, separate tracer reagents allowed us to demonstrate the detection of eight different analytes using only four waveguides. To accomplish this, we coated the optical probes with multiple capture antibodies and used mixed tracer reagents to generate a pattern of responses, which was then used to identify which target was present. While the overall sensitivity decreased as expected, since total reagent concentration was held constant, it was a nice example of what the future held in store.26 The RAPTOR has been tested in numerous trials and found to be an ideal instrument for the automated detection of threat agents. It can be paired with and control the function of the Smart
RAPTOR: DEVELOPMENT OF A FIBER-OPTIC BIOSENSOR
Figure 8. Photograph of the SASS 2000.
Air Sampler System (SASS 2000) (Figure 8), a portable wetted-wall cyclone, which RI developed independently following the initial test with the ram-air-driven prototype used for collection of BW simulants using UAVs. Since an ideal application of the RAPTOR is as an unattended sentry for detection of aerosolized threat agents, the next generation RAPTOR, the BioHawk, has an integrated SASS, whose features are described in the subsequent text. The SASS series of portable wetted-wall cyclones has two key features: high energy efficiency, permitting 24 h operation on a single battery, and water inventory control. The water is maintained at a constant volume, replenishing that lost to evaporation, allowing very high concentration ratios or extended sampling periods. The cyclone has four main sections: (i) a cyclonic cup, (ii) a mixing column, (iii) a cistern, and (iv) a water feedback loop. A high-efficiency, battery-operated centrifugal blower pulls air into the cyclonic cup, which has a rapidly swirling film of water on exposed walls. This water film also passes across the inlet nozzle region, in essence forming a water curtain through which the incoming air passes. In parallel with this process, additional water continuously enters through a nozzle mounted in the cup base. This nozzle distributes
5
a fine spray of droplets into the cup and, along with the wetted walls and water curtain, provides effective air-to-water mixing. Next, air flows from the cup into the stripping tube that is connected to the cup’s upper surface. Air entering the smaller-diameter stripping tube increases in rotational velocity, enhancing particulate collection by the wet stripping tube ID. The airflow rate and tube diameter are selected so that adequate shear force is produced to create a concurrent flow of water on the tube wall: the stripping tube is operated beyond the so-called flooding limit, meaning that liquid introduced at the base of the tube cannot flow counter to the upwelling air. The upward-moving film of particulate-laden water is captured in a cistern at the top of the unit. From that point, a small-diameter tube allows the water to flow back into the cyclone cup via the spray nozzle previously mentioned. The circulating water provides a pumpless, three-tiered capture strategy through the action of the water curtain, cyclone cup, and stripping column.
5 BIOHAWK AND THE FUTURE
The latest incarnation of the RAPTOR technology is a completely redesigned system, designated the BioHawk, which incorporates both air sample collection and analysis into a single man-portable package (Figure 9). The BioHawk is built of two main modules; the instrument unit and a separate liquids package. The liquids package has containers for water for the air sampler, buffer for the analyzer, and waste. Within the instrument unit are several components: the air sampler (which is the cyclone from the SASS), the analyzer (which is a highly modified version of the RAPTOR fluoroimmunoassay optics), the fluidics, as well as the electronics for control and communication, and a battery. One key requirement for the redesigned system is the ability to conduct eight simultaneous assays rather than four. To meet this requirement and still maintain portability and relative simplicity of manufacture, the basic optical interrogation mode was changed. The optical waveguide is now of noncylindrical symmetry. Excitation light is still introduced to the waveguide via a “concentrator” on axis. However, emitted fluorescence is now
6
BUSINESS AND REGULATORY ISSUES
Figure 10. Drawing of the BioHawk’s assay cartridge.
Figure 9. Photograph of the BioHawk.
detected perpendicular to the waveguide axis with a linear photodiode array. This approach allows the waveguide to be partitioned spatially into two portions, with a different capture antibody spray coated on each portion, permitting two independent assays to be conducted on each waveguide. The decrease in surface area of the waveguide available for the immunoassay is counterbalanced by the decrease in noise afforded by perpendicular detection and the S/N ratios remain about the same for the two configurations. As with the RAPTOR, the waveguides are coated with capture antibody. Unlike the RAPTOR, the secondary antibodies are also stored on board the disposable cartridge (Figure 10). Two different labeled antibodies are lyophilized in each of the four reservoirs; mixing two reagents is a fair compromise to increase capability while adding minimally to the fluidics complexity. During instrument start-up, buffer is introduced to the reservoirs and agitated gently to redissolve the antibodies. This critical design change allows the user to switch assay panels simply by replacing the cartridge, whereas the RAPTOR had required that both the cartridge and the accompanying reagent vials be switched out. Combining both functions also avoids the inevitable human error such a process portends, avoiding potentially disastrous consequences.
The resulting biosensor unit can collect particulates and toxins from the air or can accept fluid samples manually, and then perform simultaneous immunoassays for up to eight target analytes. Like the RAPTOR, assays take about 10–20 min each and the device can perform 20 or more sequential assays on a single disposable cartridge. Results are displayed on an LCD touch screen or remotely via RS-232/RF link. It is a knapsack-size, manportable, MILSPEC product that offers integrated performance for both sampling and analysis of aerosolized BW threats.
ACKNOWLEDGMENTS
We would like to thank Dr Frances Ligler, for it was her vision and determined efforts that sustained this project over the years. We also thank Joel Golden, Lisa Shriver-Lake, Keeley King, Dave Cuttino, Dr James Whelan, Dr Richard Foch, and Dr Chris Taitt to name but a few of the scientists at NRL, for their indispensable efforts on this project; and acknowledge the key contributions of Elric Saaski, Chuck Jung, and our many colleagues at RI. We thank the Department of Defense, the Office of Naval Research, and the US Marine Corps for their support.
REFERENCES 1. M. N. Kronick and W. A. Little, A new immunoassay based on fluorescence excitation by internal reflection
RAPTOR: DEVELOPMENT OF A FIBER-OPTIC BIOSENSOR
2.
3.
4.
5.
6.
7. 8.
9.
10.
11.
12.
13.
14.
spectroscopy. Journal of Immunological Methods, 1975, 8, 235–240. C. R. Taitt and F. S. Ligler, Evanescent Wave Fiber Optic Biosensors, in Optical Biosensors: Present and Future, F. S. Ligler and C. A. Taitt (eds), Elsevier Science B.V., Amsterdam, 2002, pp. 57–94. T. B. Hirschfeld and M. J. Block, Fluorescent immunoassay employing optical fiber in capillary tube. 1984, US Patent 4,447,546. J. D. Andrade, R. A. Vanwagenen, D. E. Gregonis, K. Newby, and J. N. Lin, Remote fiber optic biosensors based on evanescent-excited fluoroimmunoassays: concept and progress. IEEE Transactions on Electron Devices, 1985, ED-32, 1175–1179. The Naval Research Laboratory’s web page. About NRL’s history and Edison’s role; 2002, http://www.nrl.navy.mil/ content.php?P=HISTVISION. J. P. Golden, L. C. Shriver-Lake, G. P. Anderson, R. B. Thompson, and F. S. Ligler, Fluorometer and tapered fiber optic probes for sensing in the evanescent wave. Optical Engineering, 1992, 31, 1458–1462. R. B. Thompson and C. Villarruel, Waveguide-binding sensor for use with assays, U.S. Patent 5061857, 1991. G. P. Anderson, J. P. Golden, and F. S. Ligler, Fiber optic biosensor: combination tapered optical fibers designed for improved signal acquisition. Biosensors and Bioelectronics, 1993, 8, 249–256. G. P. Anderson, J. P. Golden, and F. S. Ligler, An evanescent wave biosensor-Part I: fluorescent signal acquisition from step-etched fiber optic probes. IEEE Transactions on Biomedical Engineering, 1994, 41, 578–584. J. P. Golden, G. P. Anderson, S. Y. Rabbany, and F. S. Ligler, An evanescent wave biosensor-Part II: fluorescent signal acquisition using tapered fiber optic probes. IEEE Transactions on Biomedical Engineering, 1994, 41, 585–591. S. K. Bhatia, L. C. Shriver-Lake, K. J. Prior, J. H. Georger, J. M. Calvert, R. Bredehorst, and F. S. Ligler, Use of thiolterminal silanes and heterobifunctional crosslinkers for immobilization of antibodies on silica surfaces. Analytical Biochemistry, 1989, 178, 408–413. F. S. Ligler, J. P. Golden, L. C. Shriver-Lake, R. A. Ogert, D. Wijesuria, and G. P. Anderson, Fiber-optic biosensor for the detection of hazardous materials. Immunomethods, 1993, 3, 122–127. L. K. Cao, G. P. Anderson, F. S. Ligler, and J. Ezzell, Detection of Yersinia pestis F1 antigen by a fiber optic biosensor. Journal of Clinical Microbiology, 1995, 33, 336–341. J. P. Golden, E. W. Saaski, L. C. Shriver-Lake, G. P. Anderson, and F. S. Ligler, Portable multichannel fiber
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
7
optic biosensor for field detection. Optical Engineering, 1997, 36, 1008–1013. L. A. Tempelman, K. D. King, G. P. Anderson, and F. S. Ligler, Quantitating staphylococcal enterotoxin B in diverse media using a portable fiber-optic biosensor. Analytical Biochemistry, 1996, 233, 50–57. G. P. Anderson, K. D. King, L. K. Cao, M. Jacoby, F. S. Ligler, and J. Ezzell, Quantifying serum antiplague antibody using a fiber optic biosensor. Clinical and Diagnostic Laboratory Immunology, 1998, 5, 609–612. C. A. Rowe, J. S. Bolitho, A. Jane, P. G. Bundesen, D. B. Rylatt, P. R. Eisenberg, and F. S. Ligler, Rapid detection of D-dimer using a fiber optic biosensor. Thrombosis and Haemostasis, 1998, 79, 94–98. I. B. Bakaltcheva, F. S. Ligler, C. H. Patterson, and L. C. Shriver-Lake, Multi-analyte explosive detection using a fiber optic biosensor. Analytica Chimica Acta, 1999, 399, 13–20. F. S. Ligler, G. P. Anderson, P. T. Davidson, R. J. Foch, J. T. Ives, K. D. King, G. Page, D. A. Stenger, and J. P. Whelan, Remote sensing using an airborne biosensor. Environmental Science and Technology, 1998, 32, 2461–2466. G. P. Anderson, K. D. King, D. Cuttino, J. Whelan, F. Ligler, J. MacKrell, C. Bovais, D. Indyke, and R. Foch, Biological agent detection with the use of an airborne biosensor. Field Analytical Chemistry and Technology, 1999, 3, 307–314. D. R. DeMarco, E. W. Saaski, D. A. McCrae, and D. V. Lim, Rapid detection of Escherichia coli O157:H7 in ground beef using a fiber-optic biosensor. Journal of Food Protection, 1999, 62, 711–716. N. Nath, M. Eldefrawi, J. Wright, D. Darwin, and M. Huestis, A rapid reusable fiber optic biosensor for detecting cocaine metabolites in urine. Journal of Analytical Toxicology, 1999, 23, 460–467. H. J. Kwon, S. C. Peiper, and K. A. Kang, Fiber optic immunosensors for cardiovascular disease diagnosis: Quantification of protein C, factor V leiden, and cardiac troponin T in plasma. Advances in Experimental Medicine and Biology, 2003, 510, 115–119. K. D. King, G. P. Anderson, K. E. Bullock, M. J. Regina, E. W. Saaski, and F. S. Ligler, Detecting staphylococcal enterotoxin B using an automated fiber optic biosensor. Biosensors and Bioelectronics, 1999, 14, 163–170. C. Jung, E. W. Saaski, D. A. McCrae, B. M. Lingerfelt, and G. P. Anderson, RAPTOR: a fluoroimmunoassaysbased fiber optic sensor. IEEE Sensors Journal, 2003, 3, 352–360. G. P. Anderson, B. M. Lingerfelt, and C. R. Taitt, Eight analyte detection using a four-channel optical biosensor. Sensor Letters, 2004, 2, 18–24.
85 Regulatory and Validation Issues for Biosensors and Related Bioanalytical Technologies Nikolay V. Sergeev,1 Keith E. Herold2 and Avraham Rasooly1,3 1
Center for Devices and Radiological Health, FDA, Silver Spring, MD, USA, 2 Department of Bioengineering, University of Maryland, College Park, MD, USA and 3 Diagnostic Biomarkers and Technology Branch, NIH-National Cancer Institute, Rockville, MD, USA
1 FOREWORD
2 INTRODUCTION
The usage of the term biosensor in this chapter is consistent with the definition of biosensor by the International Union of Pure and Applied Chemistry (IUPAC) as a “device that uses specific biochemical reactions mediated by isolated enzymes, immunosystems, tissues, organelles, or whole cells to detect chemical compounds usually by electrical, thermal, or optical signals”. Thus, clinical assays that utilize ligands such as antibodies or nucleic acids as recognition elements in combination with a signal transducer meet this definition. The term biosensor is used along with assay, bioanalytical technique, device, and test interchangeably in the chapter to signify clinical tests carried out with biosensors. There are many types of diagnostic tests and each type has its own capabilities, limitations, standardizing procedures, and acceptance criteria. This chapter is a review of the most common measurements and metrics that characterize performance of biosensors intended for use as clinical tests. Statements in this chapter do not necessarily represent the official opinion of any of the organizations with which the authors are associated.
Biosensor-based clinical diagnostics is a dynamic and rapidly evolving area. Biosensors and bioanalytical technologies have the potential to decrease detection time, lower the detection limit, increase specificity and sensitivity, and allow high-throughput analysis of biologically important molecules. These biosensor characteristics position them as extremely powerful tools for in vitro diagnostics (IVDs). IVDs are considered to be medical devices and are defined as “reagents, instruments, and systems intended for use in the diagnosis of disease or in the determination of the state of health in order to cure, mitigate, treat, or prevent disease” 21 CFR § 809.3(a). According to the Food, Drug, and Cosmetic Act, 21 U.S.C. 321(h) enacted by the US Congress in 1976, IVD tests that are to be commercialized for the diagnosis and management of patients are subject to FDA (United States Food and Drug Administration) regulation. The main safety concerns associated with biosensors for IVD arise from the risk of misdiagnosis due to a false-positive or a false-negative result, leading to improper patient
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BUSINESS AND REGULATORY ISSUES
management and, in some cases, inappropriate public health response. To reduce risk to the public health associated with such devices, International Standardization Organization (ISO) and regulatory agencies have developed regulations, guidelines, and policies applicable to major aspects of biosensors manufacturing, validation, and use. From a medical device regulatory perspective, it is critical to define key quality system requirements and ensure that they are met or exceeded enabling the development of a safe and effective diagnostics device. In all cases the work performed before routine implementation of IVD tests is divided into two major components: analytical verification and clinical validation. This chapter is a review of the key regulatory and validation issues affecting overall (both analytical and clinical) performance of biosensors for IVD, such as intended use, accuracy, precision, analytical sensitivity, analytical specificity, crossreactivity, interference, sample matrix effects, clinical accuracy, and predictive positive/negative values with prevalence.
3 INTENDED USE
Clear definition of the intended use of an IVD test or device is one of the main steps in the development of IVD tests. Claimed performance characteristics of a clinical test are always evaluated by regulatory agencies (such as FDA) in the context of the intended use. The intended use specifications should include the analyte the device is intended to measure (biomarker and its type), proof of concept under intended conditions of use (showing that the biomarker has a diagnostic value), the clinical purpose of measuring the analyte (disease or infection), the populations for which the device is indicated, and the intended setting where the test or device will be used (e.g., home use or clinical/point-of-care settings) by the intended user (clinical personnel or an individual). The analytical and clinical data required greatly depends on both the detection principle and the claims made regarding intended use. For new IVD products, it is recommended that manufacturers consult with an appropriate regulatory agency for premarket device approval or clearance. This practice was introduced by FDA to help manufacturers
avoid wasting resources on studies that would not support FDA approval for their intended use. This is especially important for devices in emerging fields, such as microarray-based diagnostics, where technology, review policy, and regulatory science are continually evolving.
4 ANALYTICAL PERFORMANCE
The aim of analytical verification1 is to determine that the biosensor can measure its intended analyte reproducibly and accurately when the measurement is performed by the intended user. The analytical performance of a biosensor or a bioanalytical technique is most properly characterized by a number of interrelated parameters such as accuracy, precision, sensitivity, specificity, detection/quantitation limits, and linear/measuring range. Very often, different types of bioanalytical tests, for example, immunoassays or detection of nucleic acids, utilize different metrics and have specific performance evaluation criteria. Additionally, it should be mentioned that in different regulatory documents one or even several of the mentioned parameters may have different meanings, implying different evaluation procedures. On the other hand, analytical performance parameters with identical meaning may be defined differently in international, regional, and local regulatory documents. To avoid confusion, users and developers of IVD tests are encouraged to contact an appropriate regulatory agency for updated guidelines that regulate specific types of assays in particular areas. In general, the combination of performance parameters allows verification of the analytical performance of a biosensor, specifically whether or not it meets the requirements of the intended application. Any analytical or operational limitations of the bioanalytical test can be revealed and worked out before conducting diagnostic evaluations on clinical samples. Sources of analytical variability are inherent in any analytical procedure and can be divided into three main groups: preanalytical variables—including sampling procedure, sample preparation and handling, sample loading, storage, and transport; analytical variables—including precision and accuracy of the test method and factors which may interfere with an assay performance; and postanalytical variables—including result validation, interpretation
REGULATORY AND VALIDATION ISSUES
of the result, data entry, data transfer, and the method used to report the results. In this chapter only the major parameters related to analytical and clinical performance of bioanalytical tests are described. As a rule, more technologically complex devices involving multiple steps (e.g., sample handling and processing) present a more challenging analytical validation requirement. Also, different analytical performance parameters are usually evaluated for quantitative and qualitative tests as listed in Table 1. It is important to point out that since biosensors combine biological recognition elements with physical transducers, two very different elements, each of the components uniquely affects the device’s performance. In general, the variability of the biological ligands will be far greater than that of the electronic transducer, but from the regulatory viewpoint, the analytical performance of the device is a measure of combined performance of both elements, that is, the whole system. The validation of the individual biological and physical elements separately is highly recommended but may not be required.
4.1
Analytical Accuracy (Trueness and Precision)
The biosensor’s accuracy (analytical) is defined as “a closeness of agreement between a test value and the accepted reference (established) value”.2 This term sometimes is used interchangeably with trueness3 and is usually understood to be the total error of the measurement. Trueness in turn is defined by ISO as “the closeness of agreement between the average value obtained from a Table 1. Performance parameters used for the analytical verification of quantitative and qualitative tests
Parameter
Qualitative tests
Quantitative tests
Trueness Precision Specificity LoD LoQ Linearity Measuring range
− − + + − − −
+ + + + + + +
+ Signifies that this parameter is normally evaluated. − Signifies that this parameter is not normally evaluated. LoD: limit of detection; LoQ: limit of quantitation.
3
large series of test results and an accepted reference value”4 and along with the “precision”4 is the measure of analytical accuracy. Accuracy of a biosensor is usually verified using protocols specific to the type of instrument, detection principle, and the assay output. Typically, for biosensors that measure the concentration, amount, or activity of analyte present, the accuracy can be verified by analyzing a large number of samples and comparing the measured values with the true (known) or accepted reference values obtained with a “gold standard method”. The systematic signed deviation (systemic error) of the test results from the “true value”5 is called bias and is usually specified along with the trueness of the bioanalytical test. Bias can arise if the sample preparation step systemically fails to fully extract the analyte of interest or if other substances present in the sample interfere with the detection of intended analyte. The term precision is used as a measure of “closeness of agreement between independent test/measurement results obtained under stipulated conditions”.4,6 While trueness and bias are the measures of a systemic deviation of the tests results, the precision is an estimate of random errors inherent in every measurement procedure, that is, the factors that cannot be completely controlled. In other words the analytical precision accounts for unidentified variables coming from various sources such as reagent lots, instruments, and operators. The precision is calculated as a standard deviation (SD) or a coefficient of variation (CV%), which expresses the SD as a percentage of the mean value of the replicate measurements. The precision of a bioanalytical procedure is usually verified in a series of individual measurements of an analyte “when the analytical procedure is applied repeatedly to multiple aliquots of a single homogeneous volume of biological matrix”.3 Determination of the precision requires knowledge of the true levels of the analyte of interest in the samples being tested and is usually specified in terms of three separate parameters: repeatability, “intermediate precision”, and reproducibility.4,6 Repeatability is determined by measurements performed in one laboratory by the same operator using the same equipment on the same day (also called within-day or intraday precision) and represents the irreducible inherent precision of the method. Repeatability should be tested by a minimum of five determinations at
4
BUSINESS AND REGULATORY ISSUES
three different concentrations (low, medium, and high) in the range of expected concentrations.3 The intermediate precision shows the variations of dayto-day analysis, by different operators and different instruments. Reproducibility (also called the interlaboratory precision) is defined as the measured precision in multiple measurements obtained by different laboratories (different operators, equipment, and laboratories). However, in some regulatory documents7 interlaboratory reproducibility is referred to as a clinical performance parameter because such performance is recommended to be assessed with clinically relevant specimens in laboratory settings typical of where the device test system will likely be used. As a rule the reproducibility needs to be established by conducting repeatability experiments in different locations (e.g., multicenter trials) and isolating betweenlaboratory precision from the within-laboratory components. Variability between laboratories (i.e., reproducibility) is often the largest single component of precision while repeatability is often the smallest component of precision. Intermediate precision (between runs, between days, or between operators) is also usually small since it is controlled by an individual laboratory. The detailed calculations for multilaboratory or multiinstrument study designs can be found in references on the analysis of variance and are usually performed according to recognized protocols.4,6
4.2
Sensitivity/Specificity
The purpose of many IVD biosensors is to detect the presence of small amounts of analytes in various matrixes and often in the presence of interfering substances. This implies that the device must not only be capable of detection of low levels of the intended analyte (sensitivity) but also should be able to selectively differentiate between target and nontarget analytes (specificity). In general, sensitivity and specificity characterize the ability of the biosensor to selectively recognize the intended analyte and produce specific interpretable signal under the specified assay conditions. There are several alternative common uses of the term sensitivity. The IUPAC defines the analytical sensitivity as the “the slope of the calibration curve.” The calibration curve relates the mean of the measured signal to the actual (known) concentrations; the
steeper the slope of the calibration curve, the more sensitive the assay is to slight changes in amount of analyte. However, the term sensitivity is also used in several other contexts either alone or with modifiers. An example is functional sensitivity, which is used to describe the interassay precision at very low analyte concentrations, for certain diagnostic assays with high precision requirements at low concentrations. In many clinical laboratories and diagnostic applications, “sensitivity” or “analytical sensitivity” are used interchangeably with “limit of detection (LoD),” “lower LoD,” or “detection limit.”8 In these cases the sensitivity of a biosensor system generally corresponds to the LoD and is understood to be the minimal detectable analyte concentration typically given in units of particles or mass per unit volume (particles/liter or mass/liter). The preferred use of the term sensitivity in relation to qualitative IVD tests is the ability of the test system to detect the presence of the target analyte in samples where it is actually present at concentrations equal to or exceeding the LoD. Specificity refers to the ability of a biosensor to correctly identify (and) quantify an analyte in the presence of interfering variables. In qualitative testing, specificity is “the ability of a measurement procedure to determine only the component it is intended to measure,”9 that is, to produce negative results in concordance with negative results obtained by a reference method. In other words, the specificity is the ability of a biosensor to respond only to the specified analyte and not to other substances present in the sample, and very often is a function of experimental conditions. Often, the specificity of an assay can be expressed in a unique way accepted in the area of application (e.g., length of a PCR amplicon in a PCR-based test). The specificity is inversely related to the cross-reactivity of the test, that is, a lower cross-reactivity corresponds to a higher specificity. To determine the specificity of a bioanalytical method, a panel of similar analytes and nonrelated interfering substances inherent in the sample matrix, should be tested.10 Frequently, nonidentifiable interferents come from the sample matrix requiring that the specificity evaluation studies be performed in each specimen matrix indicated for use. Interference11 can also occur owing to competitive inhibition when other structurally related analytes are present in the sample or, for
REGULATORY AND VALIDATION ISSUES
example, for PCR-based assays when amplification kinetics between an internal control and the target are unbalanced. From the regulatory viewpoint, the specificity testing should quantify the interference and demonstrate that potentially interfering substances or conditions encountered in actual specimens do not confound assay results.
4.3
Limits of Detection/Quantitation
The LoD is an important performance criterion for qualitative tests when results are reported as “positive” or “negative”. When the sample is diluted below the minimal detectable concentration of the analyte, the test will not produce a positive output even though the target is present. Sometimes the term LoD is used interchangeably with sensitivity and “minimum detectable concentration” and generally corresponds to the lowest amount of analyte in a sample that can be detected with stated probability, although perhaps not quantified as an exact value.8 Other “limits” that are widely used in clinical diagnostics include, but are not limited to, “limit of blank” (LoB), LoQ, “lower end of the measuring range” (LMR), and “lower limit of linear range” (LLR). The use of these parameters is closely associated with the particular assay design and its intended use. For example, the LoD is usually reported both for qualitative and quantitative assays, while LoQ is relevant only to quantitative assays. Depending on the assay type, there is often an overlap in the definition of these parameters. In general, these quantities are related such that LoB < LoD ≤ LoQ. The placement of LMR and LLR in relation to these depends on the particular biosensors system. As a rule, the lowest “limit” is the LoB, which is the highest value of the test output signal obtained in a series of experiments on clinical samples that do not contain the intended analyte. In other words LoB is a measure of the background signal “noise” produced by the device in response to sample matrix only and is sometimes called the critical value.12 It is important to note that the LoB refers to an observed test result only, while all of the other mentioned limits refer to actual concentrations of the analyte. The LoD is the analyte concentration at which a biosensor’s response exceeds the LoB and may therefore be declared as “positive”. The LoD is
5
typically determined by a standard technique consisting of testing the biosensor against samples of the target analyte prepared as a serial dilution. While LoD is a necessary performance parameter mainly attributed to quantitative tests, the knowledge and regular confirmation of the LoD for a qualitative test is a valuable tool for monitoring the consistency of the test performance. It is common to see changes in LoD of bioanalytical tests due to, for example, minor variations in reagent lots. An unknown increase of LoD for a clinical test can increase the rate of false-negative results, because samples with theoretically detectable levels of an analyte may fall below the actual LoD, while samples at higher concentrations may still give correctly positive responses. Consequently, frequent experimental confirmation of the LoD is important for interpretation and for monitoring consistency of the performance of many qualitative tests. The LoQ is the lowest actual concentration at which the analyte is reliably detected and at which the analyte can be quantitatively determined with stated acceptable precision and trueness, under stated experimental conditions.8 The LoQ is also called “lower limit of determination”, “lower limit of quantitation” (LLoQ), and LMR and has meaning only when specified along with the coupled parameters (precision and trueness). Depending on the intended use and objectives of the test, the LoQ can be equal to or significantly higher than the LoD. The LLR is the lowest concentration at which the method response has a linear relationship with the true concentration of the intended analyte.13 The LLR is widely used in tests where accurate analyte quantitation is required and may be equal to or higher than the LoQ. Currently, many devices report LoD and LoQ that come from measurements of blank samples.3 In this approach, the mean value of LoB is taken as a basis which then is adjusted by a factor of 10 times the SD to estimate the LoQ and a factor of 2 or 3 to estimate the LoD. However, for clinical tests it is recommended that one follow the approach described by the ISO defining LoD in relation to stated levels of Type I and II errors14 (also called α and β errors in CLSI guidelines8 ). α error (Type I error) is a probability of falsely claiming that a substance is present when it is true that substance is absent. LoB is established
6
BUSINESS AND REGULATORY ISSUES
in such a way that the test is positive for the samples without analyte only α% of the time. β error (Type II error) is a probability of falsely claiming that a substance is absent when it is true that substance is present. LoD is then defined as an amount of analyte in a sample for which the probability of falsely claiming the absence is β, given a probability α of falsely claiming its presence. As a rule, LoD and LoQ values should be determined and specified along with a confidence interval (e.g., 95%).
4.4
Linearity and Range
The linearity of a bioanalytical test is defined as “the ability (within a given range) to provide results that are directly proportional to the concentration (amount) of the analyte in the test sample”.13 Linearity is typically measured by testing serially diluted samples containing levels (concentrations or activities) of the target analyte, which are known by formulation or known relative to each other (not necessarily known absolutely). When the overall system responses (measurement results) are plotted against known values of the analyte levels, the degree to which the plotted curve conforms to a straight line is a measure of system linearity. It should be mentioned that some bioanalytical tests (i.e., competitive immunoassays) are nonlinear by nature, so the test results may not be linear even after data transformation such as logarithmic conversion. The linear relationship between the observed system response values and the true levels of the analyte is valuable for interpretation of quantitative test results through simplified interpolation. Furthermore, for a quantitative bioanalytical method (i.e., real-time qPCR), it is impossible to accurately interpolate between points unless the functional form of the results is known and the simplest functional form is a linear relationship. The evaluation of the test linearity should include the following important concentrations: minimum analytical concentration or LLR, various medical decision limits, and maximum analytical concentration or the “upper limit of the linear range” (ULR). The test linearity can be verified with a calibration (standard) curve generated with six to eight nonzero standard samples prepared in the same matrix as the samples in the
intended study.3 A serial dilution often gives a better correlation coefficient (r), but could give a false regression coefficient if an error has occurred in the preparation of the initial sample. The linear range of an analytical method is defined as the span of analyte concentrations for which the system output results are directly proportional (with stated trueness and precision) to the input analyte levels. The measuring range (also referred to as the reportable range or working range 15 ) is similar to the linear range but without the requirement for the direct proportionality. In other words, within the measuring range the test system response may have acceptable accuracy and precision, but have a nonlinear relationship to the analyte levels. In some cases the linear range and the measuring range coincide but more typically the linear range is contained within the measurement range. The boundaries of the measuring range are LoQ and “upper limit of quantitation” (ULQ), while the linear range is characterized by LLR and ULR that are usually higher and lower than LoQ and ULQ, respectively.
5 CLINICAL PERFORMANCE (DIAGNOSTIC UTILITY)
While analytical validation presents its own challenges, the process of clinical validation1 of bioanalytical tests is an even larger issue, because in addition to all of the analytical variables discussed previously it accounts for biological variations between individuals in the target population. One of the major issues in validation of clinical performance of IVD tests is the validation of biomarkers the IVD test is intended to measure. This is a challenging stand-alone problem that is discussed in detail elsewhere.16 Clinical performance of bioanalytical tests has to be evaluated in clinical studies in order to establish safety and effectiveness. In cases such as microbial identification assays, the goal is to define “positives” and “negatives” with a high degree of certainty because mistaken diagnosis can lead to adverse health effects due to inappropriate treatment. In other cases, such as the measurement of a blood-borne marker that is elevated in certain disease states the diagnosis typically depends on the relative concentration of
REGULATORY AND VALIDATION ISSUES
the marker compared to a disease-free population. In both types of cases, the diagnosis depends on the accuracy of the data from the tests. From a clinical perspective there is no “linear range” for the disease quantitation, instead the quantitative determination of a biomarker in a clinical sample can be used for giving the categorical “answer” to the question about the patient status. In other words, during the clinical validation it is necessary to access the ability of the test to correctly classify individual persons into two subgroups, for example, a subgroup of persons affected by some disease (and therefore needing treatment) and a second subgroup of unaffected (healthy) persons. Because of this requirement for the highest possible predictive power of the assay, one may say that from the clinical validation point of view all IVD tests are considered to be purely qualitative, where the “disease status” of a patient is the intended “analyte”. We believe that this simple and not entirely correct perspective will be helpful in understanding the meaning of the process of clinical validation of IVD tests.
5.1
Diagnostic Accuracy
While many sources on the verification of analytical performance are available, the validation of clinical performance is much less extensively described in the literature. The cornerstone of the establishment of the clinical performance of a diagnostic device or IVD test is to prove that it provides information about a disease or a clinical condition that is useful and/or meaningful to the health care provider and the patient. This characteristic is called the diagnostic accuracy and may be expressed in a number of ways (clinical sensitivity and specificity, positive and negative predictive values with prevalence, test efficiency) depending upon its intended use.17 As a rule diagnostic accuracy refers to the comparison of the results between the test system under evaluation and the true diagnosis obtained with the best available technique (e.g., a combination of methods and procedures) and should be evaluated during extensive trials using clinical samples from the intended-use population. The exact types of clinical data that are needed depend greatly on the claims that are made in the intended use but, in any case, should include
7
examination of both normal and affected patient samples. In addition, the test population should be clearly defined (e.g., infants, pregnant women, or men over age 50). The number of samples used for clinical validation should allow calculation of confidence intervals (as a rule 95% confidence interval) for each of the clinical performance parameters. Several interrelated parameters are used to validate the diagnostic accuracy of bioanalytical tests and are described in the subsequent text.
5.2
Diagnostic Sensitivity/Specificity
The terms diagnostic or clinical sensitivity 9 are used to characterize or compare the performance of diagnostic tests in relation to prespecified clinical information (e.g., presence or absence of a target analyte related to a disease). Diagnostic sensitivity and specificity are related to the performance of the test in terms of the detection of the disease and may not directly relate to the analytical sensitivity and specificity of the biosensor itself. In other words, analytical performance of the test provides a basis (i.e., test “score”) for the interpretation of test results (e.g., “positive” or “negative”), which are then used to classify patients into two clinically relevant groups (e.g., “diseased” or “normal”). Comparison of the distribution of the test results within the groups with true values determined by a reference method is then used to calculate the clinical sensitivity and specificity of the test in relation to the particular disease. For a qualitative diagnosis, diagnostic sensitivity for a patient’s “diseased” status (or other relevant target condition) is the proportion of patients with a positive output value in the test device system determined to be infected by the reference method. Diagnostic specificity is usually calculated as the proportion of “normal” patients with a “negative” output value in the test results.
5.3
Predictive Values with Prevalence/Test Efficiency
Although diagnostic sensitivity and specificity are commonly used to describe the clinical accuracy of a test, in practice, predictive value of the test provides a different perspective that includes disease
8
BUSINESS AND REGULATORY ISSUES
prevalence. The risk to the patient of false-positive or false-negative results is often tied to the clinical decisions made on the basis of the result. It is therefore important to establish valid, accurate predictive values of the test allowing definition of a patient’s status with high confidence. Predictive values of the test are a function of the diagnostic sensitivity and specificity. The proportion of total positive test results that are truly positive is called the predictive value of a positive test result (PVP).9 In other words, the PVP is the measure of the probability that an individual with a positive test result actually has a particular disease or condition the test is designed to detect, so the PVP is a function of both sensitivity and prevalence. Alternatively, the proportion of total negative test results that are truly negative determines the negative predictive value of the test (PVN)9 and is a function of specificity. The “prevalence of disease” is not one of the biosensor performance parameters, but directly affects the predictive value of a test result and is usually considered during the test validation. Prevalence represents the total number of cases per unit of the targeted population (which differs from incidence representing the number of new cases per year per unit of population). Estimated efficiency of the test (EET) is the total agreement of the test results with the true diagnosis and is represented by the percent of all results that are true results, whether positive or negative. By the definition, the EET is a function of both clinical sensitivity and specificity and can reach its maximal value (100%) only if both sensitivity and specificity are 100%. All clinical performance parameters are affected by occurrence of cases of mistaken diagnosis based on the test results. They are described by the false-positive fraction (FPF), which is a fraction of “positive” test results declared “negative” by a reference method, and
the false negative fraction (FNF), which is a measure of “negative” test results obtained on truly “positive” samples. A useful way of organizing the clinical performance parameters of a test is a 2 × 2 contingency table2 as shown in Table 2. Using the values given in Table 2 we get the following: Diagnostics sensitivity = 100% × A/(A + C), Diagnostics specificity = 100% × D/(B + D), PVP = 100% × A/(A + B), PVN = 100% × D/(C + D), EET = 100% × (A + D)/N, FPF = 100% × B/(B + D), (can also be defined as 1-specificity) FNF = 100% × C/(A + C).
5.4
Interrelation between Clinical Performance Parameters
For any hypothetical clinical test results, the distribution of test responses to “diseased” and “normal” samples from the intended population can be plotted as two corresponding histograms, giving the “test-performance curve” as in Figure 1. The two histograms show distributions of “scores” of test results plotted from biosensor responses to samples identified as “normal” (left histogram) and “diseased” (right histogram). Both histograms have a range of values because of biological variations between individuals. In an ideal case, when the distribution of test results does not exhibit any overlap, as in Figure 1(a), the test can correctly identify all positive and negative samples by defining a cutoff score at the base of the trough
Table 2. Comparison of test results with the known true diagnosis
Known true diagnosis Test results Test positive (T+) Test negative (T−) Total number of samples with known diagnosis
Positive (D+)
Negative (D−)
Total number of test results in each category
A C A+C
B D B +D
A+B C+D N
Key: test/disease (T/D). A: T+/D+ (true positive); B: T+/D− (false positive); C: T−/D+ (false negative); D: T−/D− (true negative); N: total number of samples used in the study.
REGULATORY AND VALIDATION ISSUES “Normal” histogram “Diseased” histogram
Number of samples
C1
(a)
Test score
Number of samples
C100 C95 C90
(b)
Test score
Figure 1. Test-performance curves. Simulated data produced by tests with nonoverlapping (a) and overlapping (b) distributions of “negative” and “positive” test results.
between the two peaks. The cutoff score (decision level, decision threshold) is used as a criterion to classify the subjects as “positive” or “negative” on the basis of test results. At the selected cutoff (C1 in Figure 1a) all samples are correctly identified (both FPF and FNF are 0) giving “zero” B and D values in Table 2. In this case, the clinical sensitivity of the test is 100% (all true-positive samples are correctly identified as “positives” by the test), specificity is 100% (all true negative samples are identified), the EET is 100% (all samples both “positive” and “negative” are correctly identified). Furthermore, the ability of the test to correctly predict either “positive” or “negative” patient status is 100% (both PVP and PVN are 100%). For any test in which the distributions of results from the two categories of subjects overlap (Figure 1b), there are inevitable “trade-offs” between clinical performance parameters. The overlap between tests results can occur if some fractions of the test results were assigned to wrong categories (as determined by a true diagnosis), that
9
is, the test results contain false-positive and falsenegative fractions. The amount of the overlap may be strongly dependent on how closely the used biomarker is correlated with the disease state. The sensitivity and specificity (and other related parameters discussed in the preceding text) of this test will depend on the choice of the cutoff value. Outside the overlap region, either clinical sensitivity or clinical specificity is 100% and both are unvarying. Within the overlap region, neither specificity nor sensitivity is 100% and both are varying along with other clinical performance parameters as the cutoff varies. By plotting and analyzing “diseased” and “normal” histograms, it is easy to appreciate the interrelationship between clinical performance parameters and to determine cutoffs, above which lie biosensor responses with preferred (depending on the intended use) performance characteristics. As a rule, high cutoff value minimizes falsepositives while a low cutoff value minimizes false negatives. For example, for screening tests used to test entire populations for the presence of an analyte (biomarker or infectious agent), it is usually desired to have a high sensitivity to ensure that true-positive results are detected at the cost of producing more false-positive results, as long as the negative consequences of a false-positive diagnosis are not severe. The highest theoretical test sensitivity (100%) can be achieved only if 100% of the test responses to “diseased” samples lie above the test cutoff. At the cutoff value C100 (Figure 1a), truly “positive” samples in the tested population are correctly identified by the test with no “false-negatives”, giving the clinical sensitivity of the test and PVN of 100%. However, a fraction of negative test results (i.e., 10%) lies above the C100 thus giving a nonzero FPF value of 10%, reducing the clinical specificity (not all “negative” samples are identified) and PVP (not all “positive” results are actually “positive”). This lower specificity can be tolerated if a good confirmatory test exists and if the social/economic consequences of the false-positive results are not too severe. Confirmatory tests are designed to be specific (at the expense of sensitivity, if necessary) and have a high positive predictive value. These performance characteristics of the test can be achieved at the assay cutoff value labeled as C90 in Figure 1(b). With the cutoff set at C90, 90% of the biosensor responses to positive samples lie above
10
BUSINESS AND REGULATORY ISSUES
1.00
C100
0.95
C95
0.90
C90 0
5 False-positive fraction (%)
Cutoff values
Sensitivity (true-positive fraction) × (100%)
the cutoff, with no “false-positives” (F P F = 0). However, 10% of test responses to “positive” samples are mistakenly declared as “negative”, giving FNF of 10%. At the C90 cutoff value the clinical performance of the test is characterized by the following values: sensitivity is 90%, specificity is 100%, PVP is 100%, PVN is ≈91%, and EET is 95%, which may be acceptable for a confirmatory test. For diagnostic tests, which are used to diagnose a particular disease or condition on the basis of a clinical suspicion that it might be present, both high sensitivity and specificity are usually desired. By choosing a cutoff value between C90 and C100, different unique combinations of sensitivity and specificity can be obtained. In other words, within the overlap region there is a continuum of sensitivities and specificities in which each sensitivity value has a corresponding specificity value. The “trade-off” between sensitivity and specificity in the overlap region in Figure 1(b) is quantitatively captured by the receiver’s operating characteristics (ROC)18 in Figure 2. Typically, on the Y axis, sensitivity, or the true-positive fraction, is plotted. On the X axis, false-positive fraction (“1-specificity”) is plotted. In the ROC plot, the various combinations of sensitivity and specificity possible for the test in a given setting are readily apparent. As the decision level changes, sensitivity improves at the expense of specificity or vice versa. At the cutoff value C95 (Figure 1b)
10
Figure 2. Receiver operating characteristic (ROC) of the test in the overlap area illustrated in Figure 1(b).
both clinical sensitivity and specificity are 95%, which may be an acceptable clinical accuracy for diagnostics tests.
6 CONCLUSION
In the last 10 years the methodology of method validation has been extensively developed. Analytical verification and clinical validation of IVD tests are required to demonstrate the performance of the clinical test and the reliability of results obtained with the test. Numerous guidelines have been published by recognized authorities establishing performance parameters and acceptance criteria for different types of IVD biosensors. These guidelines provide a standardized and systematic approach for a bioanalytical method validation, helping manufacturers to establish a validation plan at an early stage of assay development. As the technologies becomes more complex, regulatory and validation policies are evolving to assure efficacy and safety of biosensors, but in many cases it is still left to the manufacturers to establish quality requirements of novel IVD tests. Appropriate validation policies for novel clinical tests can be very dependent on the nature of the sample, the type of analytical methodology, and the intended use of the assay. For newly developed devices analogous to ones already existing on the market (approved for IVD), the validation process usually consists of systematically comparing the performance of the new test with the accepted performance characteristics of the existing device. For novel clinical assays, the validation process requires rigorous demonstration of analytical performance and clinical validity through extensive laboratory and clinical testing. In recent years biosensor technologies have developed rapidly, combining advances in biological recognition elements and physical transducers. One clear trend is the development of multiple sensing integrated instruments enabling automated multianalyte analysis in one chip. The use of such integrated biosensor chips may allow a complete analysis of a complex sample, reporting the presence of a wide range of chemical and biological analytes. The recent development of nanotechnology offers promise in several new areas including transducers, recognition ligands, and labeling
REGULATORY AND VALIDATION ISSUES
technology. The new nanosensors may offer new capabilities such as miniaturization to nanoscale size, higher sensitivity down to detection of one or a few molecules, reduced cost of production, and high throughput. Novel advanced technologies implemented in biosensors are expected to bring new, not yet identified regulatory and validation issues, which are to be resolved through the combined efforts of analytical scientists, test developers, clinicians, and regulatory agencies.
7.
8.
9.
ACKNOWLEDGMENTS
10.
The authors thank Larry Bockstahler (NIST), Brandon Gallas (CDRH/OSEL/DIAM), and Marina Kondratovich (CDRH/OSB/DBS) for valuable suggestions and critical review of the manuscript.
11.
REFERENCES 1. ISO, Quality Management Systems–Fundamentals and Vocabulary. ISO 9000, International Organization for Standardization, Geneva, 2000. 2. ISO, Statistics–Vocabulary and symbols–Part 1: Probability and General Statistical Terms. ISO 3534-1, International Organization for Standardization, Geneva, 1993. 3. Food and Drug Administration, Center for Drug Evaluation and Research (CDER). Center for Veterinary Medicine (CVM), Guidance for Industry: Bioanalytical Method Validation, US Department of Health and Human Services, Rockville, 2001. 4. ISO, Accuracy (Trueness and Precision) of Measurement Methods and Results–Part 1: General Principles and Definitions. ISO 5725-1, International Organization for Standardization, Geneva, 1994. 5. Method Comparison and Bias Estimation Using Patient Samples, Approved Guideline- 2nd Edn, CLSI document EP9-A2, Clinical and Laboratory Standards Institute, Pennsylvania, 2002. 6. Evaluation of Precision Performance of Clinical Chemistry Device, Approved Guideline- 2nd Edn, CLSI document
12.
13.
14.
15.
16.
17.
18.
11
EP5-A2, Clinical and Laboratory Standards Institute, Pennsylvania, 2004. Food and Drug Administration, Center for Devices and Radiological Health, Office of In Vitro Diagnostics Device Evaluation and Safety, Division of Microbiology Devices, Draft Guidance for Industry and FDA Staff, Nucleic Acid Based In Vitro Diagnostic Devices for Detection of Microbial Pathogens, Rockville, 2005. Protocols for Determination of Limits of Detection and Limits of Quantitation, Approved Guideline. CLSI document EP17-A, Clinical and Laboratory Standards Institute, Pennsylvania 19087-1898 USA, 2004. Molecular Diagnostics Methods for Infectious Diseases, Proposed Guideline. CLSI document MM3-P2, Clinical and Laboratory Standards Institute, Pennsylvania, 2005. Evaluation of Matrix Effects, Approved Guideline- 2nd Edn, CLSI document EP14-A2, Clinical and Laboratory Standards Institute, Pennsylvania, 2005. Interference Testing in Clinical Chemistry, Approved Guideline- 2nd Edn, CLSI document EP7-A2, Clinical and Laboratory Standards Institute, Pennsylvania, 2005. ISO, Capability of Detection–Part 3: Methodology of Determination of the Critical Value for the Response Variable When no Calibration Data are Used, ISO/DIS 11843-3, International Organization for Standardization, Geneva, 2000. Evaluation of the Linearity of Quantitative Measurement Procedures: A Statistical Approach, Approved Guideline. CLSI document EP6-A, Clinical and Laboratory Standards Institute, Pennsylvania, 2003. ISO, Capability of Detection—Part 1. Terms and Definitions, ISO 11843-1, International Organization for Standardization, Geneva, 1997. Clinical Evaluation of Immunoassays, Approved Guideline. CLSI document I/LA21-A, Clinical and Laboratory Standards Institute, Pennsylvania, 2002. W. A. Colburn and J. W. Lee, Biomarkers, validation and pharmacokinetic-pharmacodynamic modelling. Clinical Pharmacokinetics, 2003, 42(12), 997–1022. P. M. Bossuyt, J. B. Reitsma, D. E. Bruns, C. A. Gatsonis, P. P. Glasziou, L. M. Irwig, D. Moher, D. Rennie, H. C. de Vet, and J. G. Lijmer, Standards for reporting of diagnostic accuracy. The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clinical Chemistry, 2003, 49(1), 7–18. Assessment of the Clinical Accuracy of Laboratory Tests Using Receiver Operating Characteristic (ROC) Plots, Approved Guideline. CLSI Document GP10-A, Clinical and Laboratory Standards Institute, Pennsylvania, 1995.
Introduction to Biosensor and Biochip Technologies Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
The concept of biosensors and biochip technologies is not new; in fact, it is as old as evolution itself and has been used by all living organisms for hundreds of millions of years. All living systems possess sensors and sensor array processing capabilities that they use to interrogate and respond to their proximal environment. Evolution offers many solutions for a plethora of sensory challenges; for example, mechanoreceptors and proprioreceptors on oligochaete worms sense mechanical stimuli and hydrostatic pressure respectively, whilst other natural receptors can sense temperature, light, odors, pheromones, and highly specific chemicals. All of these systems comprise arrays of individual sensing receptors and/or cells linked into a highly intelligent biochemical cascade that leads to an appropriate macroscopic response. Sadly, man’s attempts to emulate these natural sensing systems using state-of-the-art biological, chemical, and physical technologies falls far short of nature’s efforts in several crucial areas. Natural receptor systems display remarkable sensitivity, in some cases close to single molecule detection, and specificity, including class-, regio-, and stereospecificity, for the target molecules. They also exhibit relatively rapid response times, are biocompatible, biodegradable, and self -assembling. Not surprisingly, therefore, biology has been the inspiration for developing a raft of new technologies over the last three or more decades to mirror these mechanisms found in biological systems but
with enhanced ease of use and robustness. One branch consists of the concept of biosensors, while another includes the artificial noses and tongues. A biosensor comprises a biological recognition system, an enzyme, a sequence of enzymes, antibody, whole cell, or tissue slice, in intimate contact with an electrochemical, optical, acoustic, thermal, or magnetic transducer. The electronic tongues and noses take a signal pattern from a sensor array of different selectivities and process it with multivariate data analysis for recognition and learning. These are the biomimetic equivalents of natural sensing systems and are the subject matter for this section of the handbook. However, these considerations prompt several important questions, such as, why do we need such devices, are they of any value, are they being used and if not, why not? Biosensors and biochips are an important class of analytical devices that are designed to fill an important niche in the larger picture of analytical chemistry. Higson addresses the needs of modern analytical chemistry and points out that most people think of analytical chemistry as involving highly trained chemists using sophisticated instrumentation such as chromatographic or spectroscopic techniques to identify and quantify specific chemical substances (see Overview of Modern Analytical Needs). Acquiring chemical intelligence touches upon almost every aspect of our lives and is crucial for the analysis of samples for
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR AND BIOCHIP TECHNOLOGIES
the biomedical, agricultural, food, beverage, industrial, energy, aerospace, defense, forensic, and security sectors. While these analytical challenges are being met largely with increasingly sophisticated instrumentation coupled with chemometrics and expert systems, the effect of biology on analytical science should not be understated. Perhaps, surprisingly, in view of the paucity of knowledge about biology, the marriage of biology and analytical chemistry occurred about half way through the 19th century, when starch was determined using a malt extract and guaiac tincture. Since then, the impressive power of biocatalytic systems has been developed extensively and they are now within every analytical chemist’s armory. However, until recently, the traditional “wet” biological methodologies and the “dry” physical instrumentation and computer techniques have developed along separate tracks, with defined target analytes and enthusiastic proponents for each branch of analytical science. Biosensors reflect the recent push to couple closely these wet and dry methods into a simplified analytical system that may be performed, dare I say it, by non-chemists to effect new analyses required in a changing world. Biosensors directly transduce the biological reaction into an electrical signal and offer significant advantages of high specificity, facile use and the prospect of basing the analysis of molecules on function rather than structure. Such systems are particularly apposite when the analysis is required close in space and time to where the sample is taken, for example, in the ward, physician’s office, operating theatre, home, workplace, roadside, or battlefield. In these circumstances, analysis requires a rapid, direct, and fool-proof read-out from a sample that requires no pre-preparation on a hand-held or portable instrument with low logistics burden. These considerations lead the researcher in the natural direction of biosensors, in which the biology and transducer are in close harmony and enveloped by simple instrumentation. These technologies are also of great value in circumstances where human contact is undesirable, inadvisable, or impossible, such as when dealing with toxic materials or analyses in inhospitable environments such a down oil well, deep sea exploration, or extraterrestrial locations. The choice of biology and transducer depends on the nature, concentration, and distribution of
the analyte, the required sensitivity and selectivity, the logistics burden of the associated instrumentation, and the nature and treatment of the sample. The history of biosensors, as chronicled by Newman, shows that most early biosensor concepts were based on well-established techniques such as spectrophotometry or electrochemistry, which have been exploited in analytical chemistry for at least 100 years (see Historical Perspective of Biosensor and Biochip Development). This is well illustrated by the early work of Clark in 1956 where relatively conventional enzymology was coupled with well-established electrochemistry. The inspiration for this work lay, not in the individual technologies being assembled, but in the way they were combined to create an entirely new option for analytical chemistry. Nowadays, as pointed out by Lowe, increasingly sophisticated planar and fiber optic, acoustic, calorimetric, magnetic, and microengineered technologies are being used to create sensors which require no additional labels and “directly” read the biorecognition event (see Overview of Biosensor and Bioarray Technologies). This trend reflects a more generalized pattern where physical and engineering science is increasingly applied to resolve challenges in bioscience and where the specificity of biology is designed to circumvent the deficiencies in physics. For example, all physical transducers are “dim” in the discriminating chemical sense and cannot resolve the difference between specific and nonspecific adsorption onto the transducer surface. The use of biorecognition molecules such as antibodies significantly improves their “intelligence” by enhancing the signal-to-noise ratio and hence the selectivity. Disparity between the desired selectivity and sensitivity and that achievable in practice with the man-made sensor systems is one reason why arrays have been developed. They allow discrimination of specific reagents by monitoring the responses of a matrix of sensors each with slightly different specificity, in a fashion similar to the way our natural taste and smell senses function. The “fingerprint” response obtained from the combined array is characteristic for each compound, which is identified from look-up tables. In this mode, each individual sensor does not have to have the exquisite specificity required to identify an individual chemical compound in a complex sample matrix. Array
BIOSENSOR AND BIOCHIP TECHNOLOGIES
technologies using oligonucleotides and antibodies as receptors perform a similar function in that they can monitor complex expression profiles in a massively parallel fashion. The concept of performing biological studies in a parallel mode is relatively new and is derived from the original advantages perceived for combinatorial chemistry in drug discovery. Nowadays, the term array is applied to a variety of parallel transducer systems involving dots, beads, plates, fiber optics, and optical, acoustic, and magnetic principles. The only real difference between a biosensor and an array is the volume of data emanating from the system and how it is handled. Nevertheless, array
3
systems offer advantages of using miniaturized components, smaller diffusion distances and hence faster response times and lower sample volumes. Biosensors and biochip technologies are generally applied where chemical surveillance is required quickly, accurately, and close to where the sample is taken in circumstances where skilled laboratory assistance is not readily available. Nevertheless, with ever-increasing levels of complexity in computing and data transfer, it is possible to collect and analyse samples remote from their interpretation. Thus, the requirement for the future will be for accurate and reliable sensors that can be interpreted remotely.
Biological and Molecular Recognition Systems Robert S. Marks Department of Biotechnology Engineering and National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
There is a plethora of properties that make biosensors ideal diagnostic devices. One of them is specificity from which biosensors derive their strength. Specificity is a wholly molecular property connected to the physicochemical recognition properties between the molecular entities. Biosensors generally integrate them via their intimate conjugation to the transducer. Unlike most features found in biosensors that are mainly derived from human-made design, most present molecular recognition systems are provided to us by nature as they still work best. Examples are enzymes, antibodies, phages, or natural luminescent bacteria, all described in the forthcoming chapters Protein Recognition in Biology, Enzymology, Molecular Antibody Technologies for Biosensors and Bioanalytics, Luciferase Reporter Bacteriophages, and Natural Luminescent Whole-Cell Bioreporters. This is not to say that successful attempts at changing nature’s design did not provide us with useful recognition entities and this is nicely seen in such chapters as Phage-Displayed Epitopes as Bioreceptors for Biosensors, Aptameric Biosensors, Molecularly Imprinted Polymers as Recognition Elements in Sensors, or Yeast-Based Biosensors
and Their Incorporation of Mammalian Protein Receptors for High-Throughput Screening. In addition to molecular recognition, oftentimes it is useful or required to incorporate a labeling system in order to measure the recognition of the molecular interaction event. Examples here are found in Recombinant Aequorin-Based Systems for Biomarker Analysis, Recombinant Whole-Cell Bioreporter Systems Based on Beetle Luciferases, Luciferase Reporter Bacteriophages, or Recombinant Bacterial Reporter Systems. Sometimes one can even contemplate improving the natural recognition entity via molecular engineering, mutation, and other means, while also incorporating aforementioned reporter systems. Furthermore, once scientists master the chemical synthesis of artificial recognition systems, improved biomaterials will provide sensors with extra features such as robustness. This will however require many more years in protein engineering as well as polymer structural engineering. As the reader will see in the chapters of the handbook, biosensors today work well with nature’s gift of recognition molecules while definite progress in science has occurred in making useful biomimetic molecules.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
The Biology–Materials Interface: Interfacial Science and Receptor Integration David C. Cullen Cranfield Health, Cranfield University, Silsoe, UK
At the heart of most biosensor and biochip devices is the need to interface the biological world represented by the molecular recognition components of a sensor with the physical world of the transducer or other support material. While it is crucial to have an appropriate transducer and appropriate molecular recognition components within a biosensor design, if these components are not correctly integrated together the final device can be far less than the sum of its parts. This is obviously not a direction that any sensible person or group should knowingly take. Therefore how a link is made between these components, how this link can be characterized, how to predict through modeling studies the expected performance of the interface, and finally how the link can be scaled to the rigors and requirements of a mass production setting are all important areas for the biosensor and biochip community. A classic example of the importance of the materials interface and receptor integration is the hydrophilic polymer layers used in the commercial Biacore surface plasmon resonance instruments which is discussed elsewhere in this handbook. It can be argued that one of the two key innovations that enabled the success of the Biacore company was the carboxyl-methyl dextran coatings that are used to enable the immobilization of the biological receptors to the gold surface of the surface
plasmon resonance transducer chips. These gave a strong intellectual property position and offered a number of important properties at the molecular level including a biocompatible environment for immobilized receptors, ability to increase the amount of receptors immobilized per unit surface area and ease of end-user receptor integration. It is questionable if Biacore would have been such a commercial success without this key integration approach. Within this section, three examples will be used to raise issues relating to receptor immobilization—firstly, entrapment of biomolecules in electrochemically grown films (see Immobilization of Biomolecules by Electropolymerized Films by Serge Cosnier), secondly, in situ production of artificial molecular imprinted polymer receptors via electropolymerization (see Electrochemical Polymerization for Preparation of Electrochemical Sensors by Howard Weetall) and thirdly, the use of hydrogels as responsive matrices for biomolecule immobilization (see Smart Hydrogel Materials by Elizabeth Moschou, Leonidas Bachas and Sylvia Daunert). Both immobilization and characterization of sensor surfaces will be discussed with a further electrochemical example (see Scanning Electrochemical Microscopy for Biomolecular Immobilization and Imaging by Sabine Szunerits). Additionally, the general points
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE BIOLOGY – MATERIALS INTERFACE
of modeling of biosensor interfaces will be highlighted with a consideration of modeling applied to electrochemical systems (see Modeling of Biosensor Interfaces by Mike Lyons). Finally, the critical
issue of how integration approaches can be implemented in a mass-production environment will be described with an example of ion-channel sensors (see Ion Channel Biosensors by Bruce Cornell).
Transducer Technologies for Biosensors and Bioarray Technologies Howard H. Weetall Under Cooperative Agreement with the National Association for Hispanic Elderly Senior Environmental Program Assisting the US Environmental Protection Agency, Las Vegas, NV, USA
Over the last several years, a variety of transducer technologies have been utilized in conjunction with biomaterials to produce sensing devices for the detection and quantitation of a variety of compounds both large and small. These transducers are optical, acoustical, or electrochemical in nature. They have been combined with antigens, antibodies, enzymes, nucleic acids, and other molecules capable of interacting with the compounds of interest. Biosensors, in general consist of three major components: the transducer, the bio-element, and a means of separating the two elements, such that only the material of interest crosses the separation from the boundary between the bio-element to the transducer. The transducers that have been developed and utilized for sensing devices are generally rapid, accurate, reproducible, and easily fabricated and prepared. Sensors have generally been used in situations where single analytes, such as glucose and cholesterol, are monitored. Sensor arrays have permitted detection and quantitation of blood proteins and metabolites simultaneously. The cost of a typical sensor is far less than the cost of instrumentation, particularly for clinical applications. Today, sensors are fabricated using integrated circuit technology that permits ease of manufacture at decreased cost. In many cases they are biocompatible and therefore implantable in animals for real-time measurements of important blood components. With the miniaturization available
today, sensing technologies have advanced and been modified to include chemical sensing devices that do not require a biocomponent. These devices are generally more robust and capable of detecting a larger variety of small molecules than can biosensors. Miniaturization offers the user greater sensitivity and application to smaller samples. They can be utilized in harsh environments and in organic solvents that would denature the biological component of a typical biosensor. Chemical sensors can also be produced for the detection of unique compounds based on technologies first developed by Klaus Mosbach and called molecular imprinting. These technologies involve the polymerization of one or more monomers in the presence of an analyte of interest. When polymerization is completed, the analyte is removed, leaving behind an “imprint” of the wash away molecules. This imprint is capable of binding to the original molecule such that the polymer has obtained specificity for the molecule of interest. Molecular imprints have been used for purification, separation, detection, and identification of a large number of small molecules ranging from drugs to explosives. Molecular imprinting appears to be useful only for small molecules. Larger molecules used as templates create imprints that are obviously large, thereby permitting entrance and possible binding of molecules with many different shapes and sizes destroying any specificity.
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
The capability of miniaturization and the application of chemical sensing technologies have led to the development of sensing arrays containing thousands of sensing elements. These arrays have been utilized for the detection of DNA sequences, protein antigens, and individual metabolites in metabolic pathways. Arrays of sensors have also been developed for the detection of gases, essential oils, and tea flavors, coffee flavors and even whiskey flavors. These arrays have been designed to mimic taste and smell. Bioarrays, particularly for detection and identification of various proteins and gene sequences, are now available commercially and are also described in this volume. These arrays can be either electrochemical, as exemplified by a system developed and commercialized by Nanogen, or optical, as developed and commercialized by Affimetrix. Both of these systems have advanced the detection and quantitation of genes and gene sequences under a variety of conditions and in a variety of diseases and disease conditions. These techniques are also now capable of detecting numerous antigens in solution or biological fluids using immobilized antibodies and antibody fragments attached to the array system. These arrays have shown differences, for example, in cancers that were previously classified as the same. These arrays may soon be used to help the physician decide on a course of treatment specific for the individual. The following series of chapters cover areas of electrochemical and optical methods of sensing both large and small analytes. The first chapter describes amperometric and potentiometric biosensors (see Electrochemical Techniques in Biosensors). Amperometric biosensors, when in contact with the compound of interest, produce a change in current that is proportional to the concentration of the analyte of interest. The potentiometric technique is the more classical method of detection, and based on Nernstian behavior theoretically produces a 59.1 mV change in electrode potential for every 10-fold change in analyte concentration. The sensors described in the first chapter utilize a biologically active component in close proximity with a transducer. The action of the biological component, an enzyme, antigen, antibody, or DNA or DNA fragment perturbs the sensor environment and induces a signal that is proportional to the concentration of the analyte being examined.
The next chapter deals with conductometric sensors that are in fact potentiometric sensors; they rely on voltage changes at constant current (see Conductometric Enzyme Biosensors). Unlike amperometric sensors, these sensors use two electrodes and they show a Nernstian response to increasing concentrations of analyte (see Chemical and Biological Field-Effect Sensors for Liquids – A Status Report). Subsequent chapters deal with optical and acoustic technologies (see Overview of Optical Biosensing Techniques and Picoscopes, New Label-Free Biosensors). Fiber optics are described whereby the fiber is the optical transducer and the biocomponent is attached to the distal end of the fiber. When the analyte of interest binds to the biocomponent it causes a change in the frequency or intensity of the light gathered from the fiber. This change can be related to the concentration of the component of interest. More recently fiber bundles have been etched to produce a small well. Beads with different DNA segments, proteins or organic molecules can be allowed to settle within these wells. Illumination of the fiber bundle causes either fluorescence or some other form of light modification that can be related back to the binding of the analyte of interest. These bundles contain thousands of individual fibers, permitting the detection of thousands of dissimilar molecules. Thus, one has an array similar to other types of arrays described in later chapters. Modification of optical fibers or planar surfaces leads to transducers that produce evanescent waves. The evanescent wave will pass along the surface permitting light to escape along the surface for a short distance. Any molecules found within the evanescent wave will be illuminated such that, if an immobilized antibody were to bind to a fluorescent molecule, that molecule would fluoresce due to the evanescent wave. Therefore, there is the basis of an analytical technology. Other optical approaches are discussed in this section, including the widely studied surface plasmon resonance (SPR) techniques (see Localized Surface Plasmon Resonance (LSPR) Spectroscopy in Biosensing). This approach is an evanescent technology and is capable of real-time measurements, binding kinetics, and binding constants. This approach is utilized in the Biacore instrument, which has made the determination of binding kinetics and binding constants simple, reliable, and rapid. SPR can be considered one of the
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
key optical biosensor technologies and it is worth noting that SPR-related chapters occur in numerous other sections throughout this handbook. The next several chapters describe specifically the mechanisms and applications of optical technologies using chemiluminescence, bioluminescence, and electroluminescence for the detection and quantitation of a variety of analytes (see Chemiluminescent Optical Fiber Immunosensor, Bioluminescent Whole-Cell Optical Fiber Sensors, Phagocyte Luminescent Sensor and Applications of the Electrogenerated Luminescent Reactions in Biosensor and Biochip Developments). A novel concept in optical sensing is the use of hologram sensors with broad applications (see Holographic Sensors). The application of optical waveguide techniques, grating optical sensors (see GratingBased Optical Biosensors and Dual Polarization Interferometry: A Real-Time Optical Technique for Measuring (Bio)molecular Orientation, Structure and Function at the Solid/Liquid Interface) completes the applications of optical sensing methods described in this section. Together these chapters cover inclusively the electrochemical and optical methodologies that are presently available to the research and commercial communities. Most of these technologies operate in real-time and measure binding events or enzymatic events as they occur. This permits detection, quantitation and kinetic parameters of analytes of interest. Acoustic Technologies
Acoustic technologies like electrochemical technologies rely on a biological component that binds to the acoustic transducer and on binding perturbs one or more of the transducers’ characteristics (see Introduction to Acoustic Technologies and Love Wave Biosensors). Acoustic technologies are not so well developed as optical systems, they are more difficult to use because any binding to the transducer causes a change in characteristics. Usually, two devices are required, one as a control, used to subtract any background “noise”. As an example, the binding of an antigen to an antibody coated SAW device causes a change in the frequency of the device, permitting the detection of the analyte in real-time, this change in frequency is
3
due to the change in the weight or microviscosity of the complex versus the weight of the antibody alone that is bound to the transducer. Such a device is known as a quartz crystal microbalance. The chapter on these devices explains the mechanisms involved and the variations available utilizing devices of this type. There are other sensing devices that use modifications of those described. Magnetic resonators are particles that increase the sensitivity of a quartz crystal microbalance by increasing the mass of the binding particles. In addition, the application of magnetic particles decreases the non-specific background due to binding of proteins or other materials in the solution under investigation. The application of particle sensing techniques generally increase the sensitivity of any optical or acoustical approach as further discussed in this section. Thermal methods and thermistor-based technologies are capable of detecting small changes in temperature caused by the binding of two complementary molecules, i.e. antigen/antibody interactions or the reaction of an enzyme on its analyte (see Thermal Biosensor and Microbiosensor Techniques). These techniques have been commercialized for the detection of both enzymatic reactions and binding reactions and are detailed in this section. Differences as small as 0.001 ◦ C are discernible. Differential calorimetry is even more sensitive for the detection of molecular interaction. It has generally been used as a research tool. However, with advances in miniaturization available, this approach could become an important and extremely sensitive technique (see Microcalorimetry and Related Techniques). The last chapter of this section discusses data validation and interpretation. This area, known as bioinformatics, has become extremely important, particularly for understanding the data accumulated from arrays. Data mining has become a major area, requiring special technical expertise and the application of several commercially available computer programs or modified programs capable of handling thousands of bits of data from a single experiment. Biosensor technology is evolving from systems for the detection and quantitation of single analytes to systems that detect and quantitate thousands of different components simultaneously, requiring computer programs for the mining and interpretation of the acquired data. In addition, biosensor technology has evolved
4
TRANSDUCER TECHNOLOGIES FOR BIOSENSORS
from detection of microgram or even nanogram quantities of a single analyte to the detection of single molecules of these same analytes both individually and in array formats. Not only have the technologies advanced to the detection of single molecules, it has advanced to a point where it is now possible to detect single substitutions in a genetic sequence in a single molecule known as single nucleotide polymorphisms (SNP’s). There are several technologies available today that will detect specific SNPs that may relate to genetically derived disease states or potential disease states. These technologies range from array approaches that detect many sequence modifications simultaneously to approaches that detect specific single SNP’s related to a specific disease state or genetic malfunction. Many of the technologies described here have moved from research to commercialization. Others, although of interest, will never see the light of day because, although they may be accurate, precise, rapid, and even inexpensive, they are just another way of carrying out an analysis that is already accurate, precise, rapid, and inexpensive. Those that are commercial or will become commercial have qualities that include simplicity or ease of use, sensitivity, specificity, reproducibility, and low cost and perform an assay or group of assays not easily carried out by previously available technologies. They “push the envelope”. Technologies with high cost and technical expertise will be much more difficult to move to commercialization.
The greatest strides will come in the clinical applications. Sequencing of individual genomes, detecting sequences of DNA in individuals that indicate the need for specific therapies are not far off. These techniques have already shown that cancers classified as a particular type are actually different as shown by DNA analysis of the cancer cells. This type of information, as it becomes available to the physician, will lead to major changes in the treatment of cancer. Similar discoveries in other disease states using bio-sensing technologies will similarly lead to major changes in the way clinicians treat these diseased patients. Are their advantages of using one type of sensor over another? The answer is simply that the choice of sensor is dependent on the conditions under which it will be used. Arrays are most applicable for detection and quantitation of large numbers of analytes simultaneously. Single sensors are most useful for detection and quantitation of specific analytes of interest such as in environmental monitoring, or in physicians’ offices, for agents that are important to the condition of the individual. In the case of the physician’s office, glucose, BUN, or creatinine are a few examples. In the environment, individual sensors are most useful for detection of pesticides, herbicides, heavy metals, and organic pollutants. The sensor types commercially available are somewhat limited today, however they are increasing constantly and will eventually offer the user a large stable of sensor types and sensor specificities.
Miniaturized, Microengineered, and Particle Systems David C. Cullen Cranfield Health, Cranfield University, Silsoe, UK
One of the current themes within the biosensor sector is to reduce critical size scales and thus there is a resultant emphasis on miniaturization and production of microengineering based systems. In part, this theme is greatly benefiting from developments in many other sectors such as electronics, optics, and mass-manufacture of micro-scale devices and the science of miniaturization and micro-scale phenomena. These sectors provide both fabrication and manufacturing techniques at the micro- and smaller size scales as well as specific components such as miniaturized transducers. For the biosensor and biochip community, obvious advantages of these approaches include the need for reduced sample volumes, new approaches to the deployment of sensors, i.e. their small size enabling novel applications including implantable sensors, distributed sensor systems, instrumentation of real world processes, and integration of sensors into array-based systems. Additionally as size scales are reduced, new basic phenomena appear that can be exploited. Examples range from how the behavior of liquids changes through to new optical and electronic properties resulting from the spatial containment of electrons and photons. Therefore the following collection of chapters highlights a number of the key subthemes within the application of miniaturized and microengineered systems within a biosensor and biochip context.
Microfluidics is a major topic within modern biosensor and biochip activities. Underpinning this topic, consideration of the theoretical aspects of microfluidics is crucial to optimize the resources deployed to implement the use of microfluidic components and devices in the biosensor and biochip community (see Introduction to Microfluidic Techniques by Bernhard Weigl, Ron Bardell, and Catherine Cabrera and Practical Aspects of Microfluidic Devices: Moving Fluids and Building Devices by the same authors). This situation arises from the behavior of fluids changing drastically at small size scales with one unable to simply scale our everyday observations of fluid flow to the micro-scale. To allow the development, and real-world impact, of miniaturized and microengineered systems, fabrication and manufacturing approaches are required that are compatible with commercial realities. The historically used silicon photolithographic based fabrication approaches from the traditional microelectronics sector are unlikely to be appropriate for widespread application in the biosensor sector. Thus, low cost massproduced polymeric microfluidic devices are one approach that is gaining widespread acceptance (see Polymer-Based Microsystem Techniques by Matthias Schuenemann and Erol Harvey). Furthermore, as one moves to the sub-micrometer size scale, further issues arise that require additional developments for the fabrication of biosensor
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
MINIATURIZED, MICRO AND PARTICLE SYSTEMS
and biochip components (see Nanobiolithography of Biochips Levi Gheber), (see Nanosphere Lithography-Based Chemical Nanopatterns for Biosensor Design by Pascal Colpo, Andrea Valsesia, Patricia Lisboa and Fran¸cois Rossi). Further examples of the fabrication, integration and usage issues of miniaturized systems can be seen in the areas of electrochemical systems (see Microelectrochemical Systems by Stuart Evans and Lindy Murphy) and electro-mechanical systems (see Micro- and Nanoelectromechanical Sensors, Keith Aubin, Bojan Ilic, Harold Craighead). Bead- or particle-based technology is another growth area. Some particulate materials have benefits due to the emergence of new properties such as the optical properties of quantum dots and their exploitation as optical labels (see Quantum Dots: Their Use in Biomedical Research and Clinical Diagnostics by Stanley Abramowitz) whilst others enable new physical manipulations as well as new labeling possibilities (see Manipulation and Detection of Magnetic Nanoparticles for
Diagnostic Applications, by Benjamin Yellen and Randall Erb). The changing electronic properties of materials at the nanometer scale are also being utilized for biosensor development. The novel electronic properties of polymeric nanowires (see Conducting Polymer Nanowire-Based Biosensors by Adam Wanekaya, Wilfred Chen, Nosang Myung and Ashok Mulchandani) and carbon nanotubes (see Biosensors Based on Single-Walled Carbon Nanotube Near-Infrared Fluorescence by Paul Barone, Esther Jeng, Daniel Heller and Michael Strano) are two examples that highlight the exploitation of new nano-scale phenomena for biosensing. Additionally, more traditional biological nano-scale phenomena are being used (see The Detection and Characterization of Ions, DNA, and Proteins Using Nanometer-Scale Pores by John Kasianowicz, Sarah Henrickson, Jeffery Lerman, Martin Misakian, Rekha Panchal, Tam Nguyen, Rick Gussio, Kelly Halverson, Sina Bavari, Devanand Shenoy and Vincent Stanford).
Array Technologies Isao Karube School of Bionics, Tokyo University of Technology, Tokyo, Japan
Two score years have passed since my first paper on biosensors appeared in a scientific journal. Since then, the discoveries in the field of biochemistry and molecular biology have been breathtaking. As represented by the completion of the sequence of the human genome, the developments in biotechnology have provided a deeper understanding of our lives. As a result, we know not only what is occurring within whole cells but also when, where, and how the reaction occurs at the distinct location of the cells or tissues. These latest scientific findings brought us new developments in biotechnology and biosensor research that are now indispensable and versatile tools for various studies. Biosensors already provide many benefits to the public and are now vital for patients who have diabetes (e.g. glucose sensors), and medical testing (e.g. immune sensors). Today, biosensor research finds wide-ranging applications, and has become a part of the studies ranging from the detection of fundamental reaction to environment and high-tech health care. Due to natural phenomena and the complexity of the biological process, introducing a one-to-one correspondence of only a single molecule became insufficient to cover a wide-range, panoramic view. The request for a simultaneous readout of many different components contributed to the development of multiple-sensing tools. These demands were considered to be critical in the development of multifunctional biosensing devices. Recent developments in array technologies such as DNA arrays allowed remarkable
progress in genomics. The incremental advances in medical science acknowledged the importance of proteomics. Therefore, the research has now focused on taking advantage of using semiconductor technologies, as it turned out, to perform several tasks at the same time on extremely minute scales. The array technology now offers views in a systematic way to survey the variation of proteins and has now lead to further development. This section is designed to assimilate knowledge of existing biosensor array technologies of both academic and industrial interest that are accessible to scientists, engineers, students and newcomers to the subject. It begins with an introductory article on nucleic acid arrays (see Nucleic Acid Arrays). The technical foundations of array technology as well as recent research and development are discussed. With considerable effort and tightening of experimental conditions, the researchers developed an automated protein chip system along with the detection system. A fully-automated, twodimensional electrophoresis (2DE) system for proteomic analysis system is described (see Protein Chips and Detection Tools). This 2DE system has one huge advantage compared with conventional laboratory work; it can be controlled by machines without the influence of humans (researchers). A decrease in the reproducible error is expected by using this system. The specific, characterized proteins with different binding conditions on the solid surface allow simplification of the workflow and improve analytical sensitivity. The technology used in the array
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
ARRAY TECHNOLOGIES
of mass spectrometry (MS) detection is described. The use of MS in the characteristic manner of proteins has an advantage in comparing particular proteins across samples (see Surface-Enhanced Laser Desorption/Ionization (SELDI) Technology). The optical fiber array (see Fiber-Optic Array Biosensors) and surface plasmon resonance array technologies (see Surface Plasmon Resonance Array Devices) have contributed to the advance of biosensor research. The array detection technology, by multiplexing assays, generates thousands of signals simultaneously, with a small dimension. Electronic devices have been used for the electrochemical detection of toxicity in water (see An Electrochemical Biochip Sensor for the Detection of Pollutants), DNA and protein detection (see Label-Free Gene and Protein Sensors Based on Electrochemical and Local Plasmon Resonance Devices) in a label-free format. Many approaches have been reported in electrochemical analysis on biosensor research to monitor chemical and biological agents in nature. The chapters in this section focus on applying electrochemical analysis by integrating other technologies, such as micro-fabrication, carbon nanotubes, and optical probes, etc. The label-free detection of biomolecules has also been discussed by the use of the microcantilever array devices (see Microcantilever Array Devices). These devices are used to track the location where the surface stress changes. The advantage of this technique is its small size and use in identifying local information in small sample volumes.
New technical challenges for the artificial biochemical sniffers have been discussed for the environmental assessment and human odor analysis (see Biosniffers (Gas-Phase Biosensors) as Artificial Olfaction). This research development has a potential for integration with a portable instrument to be used in the biosensor sensor system, and expected to have potential for growth in new industry by the integration of array technology. This section introduces and discusses leadingedge research and development of array technologies. Although the technologies described here are quite new, systems for the detection of chemical agents and biological molecules are in demand in medical treatment, the food industry, environmental science, etc. Because certain technologies described in this section have become established in only a few laboratories, the tools remain prohibitively expensive, owing to complicated handling procedures and costs. However, these problems are likely to be solved by social need, economy of scale, market competition, and rapid implementation of analysis. The new generation of array technologies is still in its infancy, but will meet demand in the near future. To understand the complicated nature and biological processes, simultaneous and accurate detection by a sensor system is required. Therefore, instead of typical single-function biosensors, multiple-function sensor devices with small configuration and small sample volumes using array technology will form the next approach for biosensor research.
Data Analysis, Conditioning and Presentation David C. Cullen Cranfield Health, Cranfield University, Silsoe, UK
Within the range of disciplines and components that go together to make a biosensor device, the relative effort given to handling of the basic data output of a device is often small. This is especially true of the majority of reports in the research literature. Often, little more than a simple calibration graph with some error bars is given. This situation obviously overlooks the key role that data analysis, conditioning, and presentation play in real world applications of biosensor technology. For a commercial device, these topics are crucial for a successful device. This is true at all stages of the life of a product, from the R&D phase, through regulatory approval, quality assurance and control, and of course for a final analytical measurement. The following section covers three key areas concerning data handling, plus an emerging approach. Firstly, with glucose sensors dominating the commercial biosensor sector, this represents a mature field concerning data handling and offers a good example of the current state of the art. Given the apparent simplicity of the basic electrochemical glucose sensing approach, the details and amount of effort and resources devoted to the data handling aspects may come as a surprise to some readers (see Design of Data Algorithms for Blood Glucose Biosensors by John Rippeth and Wah Ho). Secondly, the biochip
and micro-array community has from its earliest embodiment had to deal with significant levels of raw data and to consider how this can be converted into easily interpretable and useful information. This is encompassed in the ballooning discipline of bioinformatics that focuses on data analysis, conditioning and presentation. Consideration of this area with a focus on micro-array techniques will hopefully offer insight into approaches that may be transferred to other array-based biosensor devices that are being considered for applications within point-of-care, environmental and other non-laboratory locations (see Microarray Analysis Software and its Applications by Conrad Bessant). Thirdly, and more generally, consideration of the quality of data arising from analytical analyses and the relationship of these to the diagnostic value of measurements, for example, taking into account the end application of the information, will be presented (see Data Validation and Interpretation, by Ursula Spichiger-Keller). Lastly, Bayesian theory is a topic that is being applied to an ever-increasing range of applications. Biosensor development and data processing is no different and it is therefore time to consider how this topic can benefit the biosensor community (see Introduction to Bayesian Methods for Biosensor Design by Edmund Jackson and William Fitzgerald).
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
Areas and Examples of Biosensor Applications Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
There is a greater demand for chemical and biological intelligence now than there has ever been in the history of analytical chemistry. Such demand stems from the desire to gain a better understanding of the major issues facing the planet in the future, the human genome, the impact of infectious diseases, bioterrorism, bioenergy, global warming and climate change, and the consequent requirement for making measurements of key analytes in a variety of samples and circumstances. Nowhere more important are these measurements than in clinical medicine and the pharmaceutical industry, where recent understanding of the genome, proteome, and metabolome is likely to lead to new drug targets, personalized medicine, and diagnostics based on novel biomarkers. In principle, biosensors could be applied to disease predisposition, pre-symptomatic diagnosis, prognosis, drug and patient stratification, compliance, and adverse drug reactions. Jacobs describes genetic and other DNA-based biosensor applications, which may find application as pre-disposition monitors for a variety of genetics-based disorders and, when combined with suitable dietary or lifestyle indicators, as prognostic indicators. More recently, two significant developments in biomedical diagnostics have been reported. First, the use of sophisticated hyphenated mass spectrometry techniques has allowed the identification of trace peptide and protein biomarkers in readily accessible fluids with diagnostic potential. In this section,
Mascini picks up this theme (see Examples of Biosensors for the Measurement of Trace Medical Analytes) and describes examples of biosensors for the measurement of trace medical analytes. The second major development concerns the migration of analytical procedures from the well-serviced central laboratory to the physician’s office, operating theatre, ward, or home. Lateral flow immunochromatographic assays are described by Davies (see Lateral-Flow Immunochromatographic Assays) and constitute a major contribution to user-friendly, zero-power devices for monitoring pregnancy hormones, heart disorders, drugs of abuse, and other analytes in the home, workplace, and roadside. The notion of field operable biosensors is elaborated on by Lobel (see FieldOperable Biosensors for Tropical Dispatch) and demonstrates how far this technology has come since the first introduction of biosensors, some three decades ago. In principle, making the technology accessible to lay users was one of the original goals of the then nascent biosensor community, but has proven difficult to implement without the introduction of inexpensive measurement and manufacturing processes. However, many of these developments are in the realm of future activity, and despite considerable speculation on the value of biosensor technologies, and a substantial worldwide research activity, the reality is that there are very few biosensors actually in the market. The exception, and an archetypal
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BIOSENSOR APPLICATIONS
example of a home-use sensor, highlighted by Hall, is glucose measurement via conventional electrochemical biosensors, which constitutes a $4 billion market of about 7 billion tests per annum for diabetes management (see Glucose Measurement Within Diabetes via “Traditional” Electrochemical Biosensors). However, as reviewed by Newman and Pickup, even this market is beginning to change with newer approaches aimed at real-time monitoring of glucose concentrations via a variety of minimally-invasive and non-invasive techniques being developed (see Biosensors for Monitoring Metabolites in Clinical Medicine). Other sensors for debilitating neurological and psychiatric disorders and infectious diseases facing modern and aging societies are described by Kornguth (see Biosensors for Neurological Disease) and Baril (see Need for Biosensors in Infectious Disease Epidemiology). Biosensor, bioarray, and biochip technologies are increasingly being exploited in non-medical diagnostics. For example, the pharmaceutical industry has desires to increase its throughput for drug discovery by coupling a variety of these approaches to miniaturized combinatorial chemistry to allow synthesis and bioassay to be linked in the same high throughput system. Legge engages this theme and describes the utility of biosensors in the pharmaceutical industry (see Utility of Biosensors in the Pharmaceutical Industry). Similarly,
other sectors have not been slow to appreciate the value of these platform technologies. For example, Rogers describes their application in environmental monitoring (see Chip-Based Biosensors for Environmental Monitoring), Karube for environmental biological oxygen demand (BOD) and other applications (see Environmental Biochemical Oxygen Demand and Related Measurement), Gauglitz for monitoring trace pollutants (see Optical Biosensor for the Determination of Trace Pollutants in the Environment), Terry for agriculture, horticulture, hydroponics and related applications (see Agriculture, Horticulture, and Related Applications) and Schnerr for the food and beverage industries (see Food and Beverage Applications of Biosensor Technologies). Finally, a significant advantage of this raft of the technologies is that they are lightweight and useable in remote environments with limited requirements for power. Such characteristics make them ideal for extraterrestrial applications on the International Space Station, as described by Baumstark-Khan (see From Earth to Space: Biosensing at the International Space Station), for planetary exploration for life forms, as noted by Cullen (see Life Detection within Planetary Exploration: Context for Biosensor and Related Bioanalytical Technologies), and potentially in the future for truly exo-galaxy investigation.
Commercialization, Business and Regulatory Issues Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
As noted earlier in this handbook, there is a substantial demand for chemical and biological intelligence in almost all aspects of human lifestyle and welfare. Such demand stems from a better appreciation of the major issues that our planet will face in the future, notably, the impact of understanding the human genome, proteome, and metabolome, the spread of infectious diseases via mass movement of people, bioterrorism, new forms of energy, global warming, and climate change, and the consequent requirement for making measurements of key analytes in a variety of samples and circumstances. In principle, technologies for these measurements have been in existence for many decades. Thus a key question to pose, is why have biosensor, bioarray, and biochip technologies not had a greater impact on these unmet needs? As a proportion of the total analytical market for instruments, services, and consumables, at present, the biosensor market is negligible and still dominated by a few key analytes. Why is this? First, the old adage is that to be successful in the marketplace, a new technology has to be tentimes better or ten-times cheaper than an existing product to be acceptable and to displace sunk investments in hardware, software, and humanware. Sadly, most biosensor technologies do not meet these criteria and merely offer the advantage of convenience of use. This is particularly true of the glucose monitoring market, where the
price of the sensor replacing the traditional colored paper test was not very different and the advantage was user friendliness and accuracy. Consequently, these glucose sensors have displaced the majority of other glucose tests and now account for the majority of biosensor sales worldwide. A second issue is whether current biosensors are fit for the purpose, i.e. are they capable of measuring analytes quantitatively with the accuracy and speed required at a price the customer is willing to pay? For example, in the heady days when biosensors were expected to replace all other enzymes and immunoassays, newer techniques such as surface plasmon resonance (SPR) were considered to address the deficiencies of the then current assays. In reality, SPR could not cope with the throughput, sensitivity, and harsher environment that most of these assays were conducted in. Unsurprisingly, therefore, the technique has found a natural niche in the well-controlled laboratory, being used by skilled operators for interaction analysis. The chapter on the Biacore by L¨of˚as describes the rocky path from biosensor concept to the creation of the business of label-free protein interaction analysis (see Biacore – Creating the Business of Label-Free Protein-Interaction Analysis). A similar story could be told for other sensors-turned interaction analysis equipment based on the resonant mirror and the quartz crystal microbalance. In a similar vein, Abramowitz describes a case study on the development of the Affymetrix DNA
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
BUSINESS AND REGULATORY ISSUES
chip (see Commercialization of DNA Arrays – Affymetrix a Case Study) and Anderson the development hurdles facing a fiber optic biosensor (see RAPTOR: Development of a Fiber-Optic Biosensor). The final issue relates to how the technologies are validated and regulated for analytes where these issues have important consequences, for
example, in the clinical, environmental, security, and health and safety sectors. The article by Sergeev describes a number of these regulatory and validation issues for putative biosensors; without these, no biosensor will be commercially acceptable (see Regulatory and Validation Issues for Biosensors and Related Bioanalytical Technologies).
The Future Christopher R. Lowe Institute of Biotechnology, University of Cambridge, Cambridge, UK
The current substantial demand for chemical and biological analysis in almost all aspects of human lifestyle and welfare is likely to increase as the major issues facing our planet become more pressing in the future and we are likely to require more convincing metrics to monitor and subsequently control seriously disruptive events. Major sociological disturbances involving climate change, energy usage, carbon footprints, environmental pollution, exposure to toxic substances, population demographics, and infectious diseases all require careful monitoring of key biomarkers. Thus, future developments in biosensors and biochips will have to address several key issues, including the ability to address point-of-sampling measurement, realtime monitoring, systems integration, and remote interrogation. Each of these scenarios will require the development of specific technologies and approaches suited to that environment. Perhaps the fastest growing sector of analytical science is that of point-of-sampling analysis, i.e. the ability to perform analyses of complex samples at the point at which the sample is collected and without returning the sample to a central laboratory. Such techniques are required in point-of-care analysis of clinical samples, where the analytical procedure is performed in the home, workplace, physician’s office, day-care centre, ward, or operating theatre and where time is of the essence. Similar methodologies are required for on-the-spot detection of alcohol, illicit drugs, or other behavior-altering compounds at the roadside, workplace, or transport hub, or in security,
military, or first responder situations where conventional explosives, chemical or biological agents are suspected of being deployed. The ability to analyse samples on-the-spot would permit early detection and identification and allow delineation of the extent and geographical area of the affected location. Forensic analysis of scenes of crime would benefit immeasurably from point-ofsampling analysis of body fluids to identify the nature, source, and potential characteristics of individuals suspected of committing crimes. However, all these applications, and those in food, water, and raw material quality monitoring, require analytical measurements to be made without the benefit of clean, well organized laboratories with skilled operators. Thus, the requirements to perform precise, and in most cases, quantitative measurements in an uncontrolled environment in an inexpensive, relatively small “handleable” sensor which is capable of sample pre-processing and has low logistics burden is a real challenge to the sensor community. Field samples will often be cluttered with pollen, dust, and other natural biological and chemical constituents that will require separation, extraction, or filtration to allow measurement of the target analytes. Biochip technology based on silicon or glass devices with on-chip microfluidics, valves, and separation systems are potentially capable of resolving some of these issues, although the conversion of micro devices into instruments with macroscopic human interfaces still poses a significant hurdle. Devices constructed of inexpensive materials, particularly plastics, present a less
Handbook of Biosensors and Biochips. Edited by Robert S. Marks, David C. Cullen, Isao Karube, Christopher R. Lowe and Howard H. Weetall. 2007 John Wiley & Sons, Ltd. ISBN 978-0-470-01905-4.
2
THE FUTURE
expensive alternative, although the techniques for fabricating plastic fluidics, valves, pumps, channels, filters, and separation systems are less well developed than those constructed in more conventional inorganic materials. Similarly, the fabrication of plastic electronic devices based on amorphous silicon and polymer-based optical waveguide, grating and organic light emitting diode systems is still very much in its infancy. Nevertheless, inexpensive polymer sensors offer substantial benefits of manufacturability, lightness, low power burden, and disposability. Not surprisingly, such polymer-based sensors have been employed in the home measurement of glucose for at least two decades since they offer inexpensiveness combined with adequate accuracy. Real-time measurements of key analytes using biosensor and biochip technologies poses several quite difficult issues to resolve, not least ensuring that the sensor response times are within the rise and fall times of the analyte levels itself. Sadly, for most analytes, particularly those that require sample preparation or are at a low concentration, the sensor response is often too slow for real-time monitoring and discrete sampling and analysis has to be performed at discrete intervals. In most cases, where the analyte concentration changes rapidly, physical or spectroscopic techniques involving UV-VIS, near-IR, or Raman spectroscopy are often the only option. However, for analytes at higher concentrations, such as glucose, lactate, and certain other key metabolites, enzyme and chemical recognition systems, allow reversible measurements with fast kinetics. For analytes at low concentrations, such as hormones, high affinity recognition systems based on antibodies or receptor proteins are required, and this, combined with avidity affects created by immobilisation on the transducer surface, creates effectively an irreversible sensor with exceptionally slow offconstants, which requires a regeneration process to present a new binding surface. Thus, real-time monitoring of low concentration analytes is a challenge that needs to be addressed, possibly by using recombinant engineered proteins where the affinity for the analyte is modulated by some characteristic, such as heat, light, sound, or magnetism, of the transducer, i.e. the transducer becomes a transceiver. A third key challenge is to develop integrated networks of sensors that could report events over
a substantial area. This is particularly apposite for military, civilian, and environmental analyses where spatial concentration profiles are required in real-time. Such systems would be ideal for plotting the occurrence, source strengths, distribution, and fate of toxic substances through food or beverage intake, inhalation or contact in order to protect human health and the environment. Thus, miniaturized postage stamp-sized biosensors containing biochips for monitoring battlefields, water courses or civilian events may be distributed widely at fixed locations, on vehicles, or worn on protective clothing or about the person as arm bands or wrist watches. In sufficient quantity, these inexpensive miniature sensors could provide hundreds or thousands of monitoring points for target molecules in the air, water, or on personnel. In vivo biosensors could monitor physical reactions to adverse stimuli injurious or detrimental to the health of exposed person. Again, like the point-of-sampling sensors, the requirement is for inexpensive, lightweight, low-power sensors with appropriate sensitivity and selectivity. In addition, the sensors should ideally be biodegradable, to pose no ongoing threat to persons or the environment, and remotely interrogateable. Remote sensors integrated into an extensive network will present additional challenges to the sensor developer; ideally, they should be fabricated from inexpensive glass or plastic materials and be interrogateable via optical, electromagnetic, or radio-frequency radiation. Such technologies exist in other sectors such as radio frequency identification (RFID) tags and there are signs that this know-how will be applied to sensors. Remote sensing is particularly important for monitoring toxic industrial chemicals, noxious and polluting gases and in circumstances, such as space exploration, where human contact is impossible. A further significant challenge is to integrate sensor technology into actuator systems that allow an in-built response to the measured analyte. Such systems will find application in vivo for delivering therapeutic or modulating drugs in response to changes in the concentration of clinically significant analytes, the so-called pharmacy- or pillon-a-chip. The best example of such a putative approach would be the release of human insulin in response to rising levels of blood glucose; however, key considerations include the size of the implanted device which would have to include
THE FUTURE
a reservoir of the insulin, the stability of the protein, its release kinetics, and the algorithm relating insulin dose to glucose concentration, power delivery and longevity, and the potential fouling and de-calibration of the sensor. Other systems involving the sensor-controlled release of analgesics and anti-hypertensives offer more tractable alternatives, particularly in the former case, if there is a manual override via a remote activation mechanism. Such systems could be fabricated in more durable substrates such as silicon or hybrid technologies since any implanted device would require in situ use for a minimum of six months. Another challenge would be to exploit sensors or sensor arrays into autonomous or robotic systems in order to collect real-time data on local concentrations of analytes and pollutants in aerial and aqueous environments. Such devices would require a radio feedback loop and report on the presence, source, and identity of suspicious components in the air or water supplies. Data handling, with or without sophisticated artificial intelligence
3
algorithms, and the fusion of data from several different autonomous devices would be an essential component for the interpretation of events monitored by these integrated systems. Many of these future sensor devices and systems will require highly selective, reversible and durable recognition systems to discriminate the target analyte from the morass of non-specific chaff. Consequently, future sensor technologies will require the development of novel recognition elements based on engineered biosystems, stabilized cell lines, antibody and receptor fragments, catalytic antibodies, and various biomimetic systems centred on molecularly imprinted polymers. For any in vivo applications, it will be important to ensure that such systems are durable and do not leach toxic components into body fluids. An important effect of creating biomimetic recognition elements is that such systems could be integrated into the fabric of the transducer to create a combined sensor/transducer in the same way that the holographic sensors described in this handbook are fabricated.
