Single Molecule Analysis: Methods and Protocols (Methods in Molecular Biology 783)

METHODS

IN

M O L E C U L A R B I O L O G Y TM

Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK

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Single Molecule Analysis Methods and Protocols

Edited by

Erwin J.G. Peterman and Gijs J.L. Wuite Department of Physics and Astronomy, VU University Amsterdam, Amsterdam, The Netherlands

Editors Erwin J.G. Peterman Department of Physics and Astronomy VU University Amsterdam Amsterdam, The Netherlands [email protected]

Gijs J.L. Wuite Department of Physics and Astronomy VU University Amsterdam Amsterdam, The Netherlands [email protected]

ISSN 1064-3745 e-ISSN 1940-6029 ISBN 978-1-61779-281-6 e-ISBN 978-1-61779-282-3 DOI 10.1007/978-1-61779-282-3 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011935030 ª Springer ScienceþBusiness Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o Springer ScienceþBusiness Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Humana press is a part of Springer Science+Business Media (www.springer.com)

Preface Life scientists have been brought up for ages with the idea that life is driven, directed, and shaped by biomolecules, working on their own or in concert. Only since a decade of two to three, it has been possible to study the properties of molecules in ultimate isolation: individual molecules. Technical breakthroughs in the field of sensitive fluorescence microscopy have made it possible to observe single fluorescent molecules and measure their properties. Other researchers have developed optical tweezers into a method to measure the mechanic properties of single molecules. Around the same time, atomic force microscopy has been developed, with a spatial resolution good enough to resolve single biomolecules. Together, these techniques (and several other ones) have been applied more and more to the study of biologically relevant molecules, such as DNA, DNA-binding proteins, and motor proteins. These single-molecule approaches have led both not only to new views into how biomolecules bring about biology, but also to novel insights in the way physical and statistical principles underlie the behavior and mechanism of biomolecules. By now, single-molecule tools are slowly becoming commonplace in molecular biophysics, biochemistry, and molecular and cell biology. Thanks not only to their success, but also to their accessibility: in the beginning, these tools were solely developed and custom-built by (bio)physicists; now, commercial tools are becoming available. We foresee that this trend will prevail, and single-molecule tools will play an even more prominent role in molecular biology. The aim of Single-Molecule Techniques: Methods and Protocols is to provide a broad overview of single-molecule approaches applied to biomolecules, on the basis of clear and concise protocols. In addition, we provide a solid introduction to the most widely used single-molecule techniques. The idea is that these introductions, together with the protocols provide enough basis for nonspecialists to make the step to single-molecule experiments. The protocols contain a “Notes” section, in which the authors provide tips and tricks, rooted in experience, that are often decisive between failure and success. Our selection of topics for Single-Molecule Techniques: Methods and Protocols cannot be all-inclusive, but we hope that we have covered the most important ones, which can serve as a starting point for further exploration of single-molecule methods. The volume opens with four chapters on optical tweezers. In Chapter 1, a general overview of the method is provided. In the next chapters, protocols of applications of optical tweezers to studies of DNA/RNA (Chapters 2 and 3) and motor proteins (Chapter 4) are presented. The second part of the volume (Chapters 5–10) deals with single-molecule fluorescence tools. First, a general overview of these techniques is provided (Chapter 5), followed by protocols for fluorescent labeling of proteins (Chapter 6). In the following chapters, applications to motor proteins (Chapter 7), structural proteins in living bacteria (Chapter 8) and DNA (Chapter 9) are explained. In the last chapter of this part, the method fluorescence correlation spectroscopy is presented in detail (Chapter 10). The next part of the volume deals with atomic force microscopy (Chapters 11–14). Also this part opens with a general overview of the approach (Chapter 11), followed by protocol chapters describing applications to DNA and DNA-binding proteins (Chapter 12), protein folding and unfolding (Chapter 13), and viruses (Chapter 14). In the remaining chapters of the book methods

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that fall outside these three categories are discussed, including magnetic tweezers (Chapter 15) and tethered particle motion (Chapter 16). We have taken great care to provide a broad and thorough overview of the exciting and still emerging field of single-molecule biology in this volume Single-Molecule Techniques: Methods and Protocols. It is unavoidable that there is some overlap between the chapters. Furthermore, it might well be that within a few years new techniques have emerged and become important that are not discussed here. Nevertheless, we hope that the presented protocols will be useful to many researchers, inspire them and help them to go single molecule! Amsterdam, The Netherlands

Erwin J.G. Peterman Gijs J.L. Wuite

Contents Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction to Optical Tweezers: Background, System Designs, and Commercial Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joost van Mameren, Gijs J.L. Wuite, and Iddo Heller 2 Optical Trapping and Unfolding of RNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Katherine H. White and Koen Visscher

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3

DNA Unzipping and Force Measurements with a Dual Optical Trap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ismaı¨l Cisse´, Pierre Mangeol, and Ulrich Bockelmann

Probing the Force Generation and Stepping Behavior of Cytoplasmic Dynein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arne Gennerich and Samara L. Reck-Peterson 5 A Brief Introduction to Single-Molecule Fluorescence Methods . . . . . . . . . . . . . . . . Siet M.J.L. van den Wildenberg, Bram Prevo, and Erwin J.G. Peterman

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4

6 7

8

63 81

Fluorescent Labeling of Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Mauro Modesti Fluorescence Imaging of Single Kinesin Motors on Immobilized Microtubules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Till Korten, Bert Nitzsche, Chris Gell, Felix Ruhnow, Ce´cile Leduc, and Stefan Diez Exploring Protein Superstructures and Dynamics in Live Bacterial Cells Using Single-Molecule and Superresolution Imaging. . . . . . . . . . . . . . . . . . . . . 139 Julie S. Biteen, Lucy Shapiro, and W.E. Moerner

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Fluorescence Microscopy of Nanochannel-Confined DNA . . . . . . . . . . . . . . . . . . . . . 159 Fredrik Persson, Fredrik Westerlund, and Jonas O. Tegenfeldt 10 Fluorescence Correlation Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Patrick Ferrand, Je´roˆme Wenger, and Herve´ Rigneault 11

Introduction to Atomic Force Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Pedro J. de Pablo

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Sample Preparation for SFM Imaging of DNA, Proteins, and DNA–Protein Complexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Dejan Ristic, Humberto Sanchez, and Claire Wyman Single-Molecule Protein Unfolding and Refolding Using Atomic Force Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Thomas Bornschlo¨gl and Matthias Rief

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How to Perform a Nanoindentation Experiment on a Virus. . . . . . . . . . . . . . . . . . . . 251 Wouter H. Roos

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Contents

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Magnetic Tweezers for Single-Molecule Manipulation . . . . . . . . . . . . . . . . . . . . . . . . 265 Yeonee Seol and Keir C. Neuman

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Probing DNA Topology Using Tethered Particle Motion. . . . . . . . . . . . . . . . . . . . . . 295 David Dunlap, Chiara Zurla, Carlo Manzo, and Laura Finzi

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315

Contributors JULIE S. BITEEN • Department of Chemistry, University of Michigan, Ann Arbor, MI, USA ULRICH BOCKELMANN • Laboratoire de Nanobiophysique, UMR Gulliver CNRS – ESPCI, Paris, France THOMAS BORNSCHLO¨GL • Department of Physics, TU Munich, Garching, Germany ISMAI¨L CISSE´ • Laboratoire de Nanobiophysique, UMR Gulliver CNRS – ESPCI, Paris, France STEFAN DIEZ • Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany DAVID DUNLAP • Department of Cell Biology, Emory University, Atlanta, GA, USA PATRICK FERRAND • Mosaic Group, Institut Fresnel, CNRS, Aix-Marseille Universite´, Ecole Central Marseille, Marseille, France LAURA FINZI • Department of Physics, Emory University, Atlanta, GA, USA CHRIS GELL • Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany ARNE GENNERICH • Department of Anatomy and Structural Biology, Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, NY, USA IDDO HELLER • Department of Physics and Astronomy, VU University, Amsterdam, The Netherlands TILL KORTEN • Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany CE´CILE LEDUC • Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany JOOST VAN MAMEREN • JPK Instruments AG, Berlin, Germany PIERRE MANGEOL • Laboratoire de Nanobiophysique, UMR Gulliver CNRS – ESPCI, Paris, France CARLO MANZO • Department of Physics, Emory University, Atlanta, GA, USA MAURO MODESTI • Laboratory of Genome Instability and Carcinogenesis, CNRS, Marseille, France W.E. MOERNER • Department of Chemistry, Stanford University, Stanford, CA, USA KEIR C. NEUMAN • Laboratory of Molecular Biophysics, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA BERT NITZSCHE • Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany PEDRO J. DE PABLO • Departamento de Fı´sica de la Materia Condensada Universidad Auto´noma de Madrid, Madrid, Spain FREDRIK PERSSON • Department of Physics, University of Gothenburg, Gothenburg, Sweden ERWIN J.G. PETERMAN • Department of Physics and Astronomy, VU University Amsterdam, Amsterdam, The Netherlands BRAM PREVO • Department of Physics and Astronomy, VU University Amsterdam, Amsterdam, The Netherlands ix

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SAMARA L. RECK-PETERSON • Department of Cell Biology, Harvard Medical School, Boston, MA, USA MATTHIAS RIEF • Department of Physics, Technical University Munich, Garching, Germany HERVE´ RIGNEAULT • Mosaic Group, Institut Fresnel, CNRS, Aix-Marseille Universite´, Ecole Central Marseille, Marseille, France DEJAN RISTIC • Department of Cell Biology and Genetics, Erasmus Medical Center, Rotterdam, The Netherlands WOUTER H. ROOS • Department of Physics and Astronomy, VU University Amsterdam, Amsterdam, The Netherlands FELIX RUHNOW • Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany HUMBERTO SANCHEZ • Department of Cell Biology and Genetics, Erasmus Medical Center, Rotterdam, The Netherlands YEONEE SEOL • Laboratory of Molecular Biophysics, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA LUCY SHAPIRO • Department of Developmental Biology, Stanford University, Stanford, CA, USA JONAS O. TEGENFELDT • Department of Physics, Lund University, Lund, Sweden Department of Physics, University of Gothenburg, Gothenburg, Sweden KOEN VISSCHER • Department of Physics, University of Arizona, Tucson, AZ, USA JE´ROˆME WENGER • Mosaic Group Institut Fresnel, CNRS, Aix-Marseille Universite´, Ecole Central Marseille, Marseille, France FREDRIK WESTERLUND • Department of Physics, University of Gothenburg, Gothenburg, Sweden KATHERINE H. WHITE • Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, USA SIET M.J.L. VAN DEN WILDENBERG • Department of Physics and Astronomy VU University Amsterdam, Amsterdam, The Netherlands GIJS J.L. WUITE • Department of Physics and Astronomy, VU University Amsterdam, Amsterdam, The Netherlands CLAIRE WYMAN • Department of Cell Biology and Genetics, Erasmus Medical Center, Rotterdam, The Netherlands Department Radiation Oncology, Erasmus Medical Center, Rotterdam, The Netherlands CHIARA ZURLA • Department of Physics, Emory University, Atlanta, GA, USA

Chapter 1 Introduction to Optical Tweezers: Background, System Designs, and Commercial Solutions Joost van Mameren, Gijs J.L. Wuite, and Iddo Heller Abstract Optical tweezers are a means to manipulate objects with light. With the technique, microscopically small objects can be held and steered while forces on the trapped objects can be accurately measured and exerted. Optical tweezers can typically obtain a nanometer spatial resolution, a piconewton force resolution, and a millisecond time resolution, which make them excellently suited to study biological processes from the single-cell down to the single-molecule level. In this chapter, we provide an introduction on the use of optical tweezers in single-molecule approaches. We introduce the basic principles and methodology involved in optical trapping, force calibration, and force measurements. Next, we describe the components of an optical tweezers setup and their experimental relevance in single-molecule approaches. Finally, we provide a concise overview of commercial optical tweezers systems. Commercial systems are becoming increasingly available and provide access to single-molecule optical tweezers experiments without the need for a thorough background in physics. Key words: Optical tweezers, Optical trap, Radiation pressure, Single molecule, Trap stiffness calibration, Force spectroscopy, Instrument design, Commercial optical tweezers, Molecular motors, DNA–protein interactions

1. Introduction 1.1. History of Optical Tweezers

At the heart of optical tweezers techniques is the interaction between light and matter. The minute forces that are generated in this interaction can be used to displace and trap microscopic objects. In 1970, Ashkin laid the foundations for present-day optical tweezers techniques. At Bell labs, Ashkin observed that micron-sized latex spheres (beads) were attracted toward the center of an argon laser beam of a few mW power (1). It is this attractive force that makes optical trapping possible. Ashkin also observed, however, that the laser light scattered and propelled the beads forward. By using two counterpropagating beams, he managed to avoid forward propulsion, and thus created the first stable

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_1, # Springer Science+Business Media, LLC 2011

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J. van Mameren et al. forward scattered light is deflected

external force on trapped particle

trapped particle

forcused laser

restoring force

forcused laser

Fig. 1. Schematic of optical trapping. Left: A tightly focused laser beam (cone ) attracts refractive objects (dark sphere ), such as glass beads, nanoparticles, or even whole cells to its focus. Right : External forces pushing or pulling on the particle slightly displace it from the center of the focus, leading to a slight deflection of the forward-scattered laser light. This deflection forms the basis for quantitatively detecting the forces and displacements experienced by the trapped object.

optical trap for beads suspended in water. It was not until 1986 that Ashkin together with Chu and others demonstrated the present form of optical tweezers that uses a single, tightly focused laser beam to stably trap particles – of diameters between 25 nm and 10 mm – in three dimensions (see Fig. 1, left) (2). Later on, Chu and others used techniques inspired by optical tweezers to trap and cool atoms, which brought him the 1997 Nobel Prize in physics (3, 4). 1.2. Optical Tweezers in Biology

Currently, optical tweezers have found widespread applications in biology (5–7). One of the important reasons for the success of optical tweezers in biology is that it provides biological scientists with “microscopic hands” to manipulate biological objects and feel or exert forces, yet with the same low level of invasiveness as light microscopy techniques. Furthermore, the length scales, time scales, and force scales accessible to optical tweezers are biologically relevant from the single-cell down to the single-molecule level. In 1987, Ashkin presented the first applications of optical tweezers in biology by manipulating individual viruses and living bacteria (8). By a correct choice of laser power and wavelength, photodamage to biological samples could be minimized, which allowed trapping and manipulation of single living cells (9). Since

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Fig. 2. Prototypical single-molecule optical tweezers assays. Top : A single kinesin motor protein bound with its two heads to an optically trapped bead moves along a surface-immobilized microtubule track. Its 8-nm steps, the forces exerted, and the mechanics of the stepping have been elucidated in such assays. Bottom: DNA suspended between two optically trapped beads.

the late 1980s, optical tweezers approaches have been extended down to the single-biomolecule level (10–20). In these singlemolecule studies, the biomolecules of interest are not themselves trapped directly, but are manipulated through optically trapped microbeads that act as handles and force transducers. A large fraction of this single-molecule work includes the study of the activity of individual motor proteins (10, 14, 20). With optical tweezers, the motion and forces generated by these motor proteins have been studied and controlled to reveal their dynamics and energetics (Fig. 2, top). Another important area of research includes the study of biopolymers, such as DNA (7, 13, 16, 21). In these experiments, the DNA molecule is attached to one or more optically trapped beads which allows stretching the molecule and studying its mechanical properties through force spectroscopy (Fig. 2, bottom). In addition, this layout has been used to studyDNA–protein interactions (12, 15, 19, 22). A wide range of DNA–protein interactions affect the structure of DNA, and thus

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the (force-dependent) length of the DNA molecules. In optical tweezers, these length changes can be observed by measuring the displacements of the microbeads. Examples include the study of DNA-binding proteins and the activity of DNA and RNA polymerases. With the advent of commercial optical tweezers systems in recent years, this powerful single-molecule technique is approaching maturation and is becoming more and more accessible to a wide range of biological scientists. As with the development of commercial fluorescence and AFM techniques, it is to be expected that commercial optical tweezers greatly contribute to our knowledge of biology on the single-molecule level. As a final motivation to read more about optical tweezers: in an interview with Physics Today, Nobel Prize winner Steven Chu said that he would not be surprised if in the coming decennium another Nobel Prize would be attributed to groundbreaking discoveries in molecular biology facilitated by optical tweezers or other single-molecule techniques (23).

2. Principles of Optical Tweezers Techniques

2.1. Forces in an Optical Trap

The basic physical principle underlying optical tweezers is the radiation pressure exerted by light when colliding with matter. For macroscopic objects, the radiation pressure exerted by common light sources is orders of magnitude too small to have any measurable effect: we do not feel the light power of the sun pushing us away. However, for objects of microscopic dimensions (<100 mm), the radiation pressure of high-intensity light sources is sufficient to facilitate optical trapping. When photons enter an object that has a different refractive index than its surrounding medium, part of the momentum of the photons can be transferred to this object. This transfer of momentum is the physical principle that underlies optical trapping (see Fig. 1, right). The forces exerted by photons on an optically trapped object can be divided into two components: the scattering force that pushes the object away from the light source and the gradient force that pulls the object toward the region of highest light intensity. The correct physical description of optical trapping depends on the size d of the trapped object in comparison to the wavelength l of the trapping light. In the regime d >> l, one speaks of the “ray-optics” regime while the regime where d << l is called the Rayleigh regime. In biological experiments where micrometer-sized objects are trapped, the correct description is often in between these two regimes such that neither description

1 Introduction to Optical Tweezers

a

b

lateral trapping force dp1

dp2

5

axial trapping force dp2

dp1 p1'

p2' p1'

p2'

p1 p1

p2

p2

–dp1

–dp1

–dp2

–dp2 dpz dpx

Fig. 3. Forces on an optically trapped particle in the ray-optics regime. (a) Lateral gradient force of a Gaussian laser beam profile. (b) Axial gradient force toward the focus of the trapping light. The white arrows indicate the net restoring force. Note that the scattering component due to reflection by the particle is not indicated.

is quantitatively accurate. To provide a qualitative understanding of optical trapping, we here describe the forces in the more intuitively interpretable ray-optics regime. In the ray-optics regime, the trapping force can be understood in terms of refraction of light rays between media with different indices of refraction (24). Figure 3 qualitatively depicts the origin of the trapping forces in this regime. The lateral gradient restoring force (Fig. 3a) can be understood as follows. If rays p1 and p2 have different intensity, the momentum changes of these rays (Dp1 and Dp2, respectively) differ in magnitude, causing a net reaction force on the refracting medium in the direction of highest intensity. The x-projection of this force, Dpx, tends to counteract a displacement from the laser beam axis, pulling the particle toward the center of the beam. The axial gradient force is similarly caused by momentum transfer upon refraction, resulting in a restoring force toward the focus, as in Fig. 3b. The scattering force (not depicted) would cause the object to be propelled out of the focus, along the positive zdirection. The object is stably trapped only if the scattering force along the positive z-direction is compensated by the gradient force along the negative z-direction. To achieve this, a significant fraction of the incident light should come in at large angles, calling for a tightly focused trapping light source typically obtained by using a microscope objective. 2.2. Trap Stiffness

An optical trap forms a three-dimensional potential well for the trapped particle. The particle experiences an attractive force

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toward the potential minimum, which is located at a stable position where the trapped particle experiences no net force. Close to the potential minimum, the trap can be approximated to be harmonic, e.g., the attractive force F is directly proportional to the displacement x of the particle according to Hooke’s law: F ¼ kx. Here, the spring constant k has units [N/m] like a mechanical spring and represents the stiffness of the optical trap. Knowledge of the trap stiffness allows accurate quantification of the external forces acting on a trapped particle from a measurement of the particle’s displacement. The trap stiffness, however, is a complex function of the intensity profile and wavelength of the laser, the shape and size of the particle, the indices of refraction, and other parameters and is difficult to calculate from first principles. Therefore, the trap stiffness is commonly determined by performing calibration experiments. Using a laser of 1 W, the typical trap stiffness that can be obtained in a single-beam optical trap is in the order of 100 pN/mm. 2.3. Principles of Trap Calibration

To allow quantitative measurement of the forces on optically trapped particles, several calibration methods to measure the trap stiffness have been developed. Drag force calibration: The simplest way to calibrate an optical trap is to apply an external force of known magnitude and measure the displacement of the trapped particle. The external force is typically generated by inducing a fluid flow. The drag force by a fluid (viscosity , flow velocity v) on a spherical bead of diameter d is given by Stokes’ law: F ¼ gv, where g is the drag coefficient g ¼ 3pd. The fluid drag displaces the bead from the center of the trap until the drag force is opposite and equal to the restoring force from the optical trap, which yields k ¼ gv=x. The trap stiffness can, thus, be obtained by measuring the displacement, x, of a bead of known size due to the fluid flow of a liquid with known viscosity and velocity. Brownian motion calibration: Another, more accurate calibration procedure is based on the Brownian motion of a bead in an optical trap, caused by the continuous and random collisions with solvent molecules. The stiffness of an optical trap can be calibrated by recording the power spectrum of the displacement fluctuations of a trapped bead of known size, as shown in Fig. 4. The power spectrum Sx(f) describes how the power of these displacement fluctuations is distributed in frequency f and is found to have a Lorentzian shape (25, 26): Sx ðf Þ ¼

kB T
; gp2 fc 2 þ f 2

where kBT is the available thermal energy. The power spectrum exhibits a characteristic corner frequency fc  k=2pg, which is

1 Introduction to Optical Tweezers

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10–3

fc (3W) fc (6W)

–4

power spectrum [V2 Hz–1]

10

10–5

10–6

10–7

2

10–8

10–9 10

100

1000

frequency [Hz] Fig. 4. Power spectra representative of the positional fluctuations of a particle trapped at different laser powers. A 1-mm diameter polystyrene bead is held in an optical trap while the displacement signal in volts is sampled at 195 kHz. The graph shows power spectra of the displacement signal at 3 W (dark gray ) and at 6 W (light gray ) laser power. Both the downward shift of the low-frequency plateau S0 and the upward shift of the corner frequency fc (see arrows at 250 and 650 Hz, obtained from Lorentzian fits) for the stiffer 6 W trap can clearly be observed.

proportional to the trap stiffness. Figure 4 shows that at low frequencies f << fc, the power spectrum is roughly constant, S x ðf Þ ¼ Sx;0 ¼ 4gkB T k2 . At high frequencies f >> fc, however, the power spectrum falls off like 1/f 2, which is characteristic of free diffusion. The inverse of the corner frequency represents the time response of the optical trap, which is typically in the order of 1–0.1 ms. For shorter timescales, the particle does not “feel” the confinement of the trap which means that behavior of biological systems at timescales more rapid than this response time cannot be detected by the optical tweezers. The two power spectra of Fig. 4, acquired at two different trap stiffnesses, illustrate that when higher trap stiffnesses are used (i.e., by increasing the laser power), the bead fluctuations at low frequencies are reduced and the time response of the optical trap increases. On the other hand, a higher trap stiffness implies smaller bead displacement at a given force which means that more accurate bead displacement detection is required to obtain the same force sensitivity. It is important to note that, in practice, the detector used to determine the bead position reads uncalibrated displacement fluctuations u(t) (i.e., as some voltage rather than as a displacement

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in nanometers). The response of the detector R, which has units m/V, relates the displacement to u(t) as x(t) ¼ Ru(t). To fully calibrate an optical trap, the power spectrum of the uncalibrated displacement fluctuations Su(f) is fitted with a Lorentzian: Su ðf Þ ¼

Su; 0 fc 2 : ðfc 2 þ f 2 Þ

Once the parameters Su;0 and fc are obtained, the trap stiffness can be calculated using k¼

2kB T pSu;0 fc

or k ¼ 2pgfc ;

and, providing the bead diameter and solvent viscosity are known, the detector response can be calculated using "

kB T R¼ 2 p gSu;0 fc 2

"

#1=2 25 C

¼

#1=2 5:0  1020 m3 =s : Su;0 fc 2 d

Finally, to convert uncalibrated displacement data to forces, the displacement signal should be multiplied by R and the trap stiffness such that F ¼ kx ¼ kRu.

3. Optical Tweezers Systems An optical tweezers setup consists of various dedicated components. In this section, we discuss the role of these components in optical tweezers function and performance. Below, we divide and discuss the components in five groups: the trap, the environment of the trap, trap steering, position and force detection, and the environment of the setup. In addition, we also discuss the ability to combine optical tweezers with other techniques and the different optical trapping assays that are typically used in biological experimentation. For illustration, Fig. 5 shows the schematic layout of an optical tweezers setup that combines two steerable optical traps with fluorescence microscopy. 3.1. The Optical Trap

At the heart of every single-beam optical tweezers instrument is the microscope objective, which creates a tight focus to form a stable optical trap. Tight focusing implies that a significant fraction of the incident light comes in at large angles such that the scattering force is overcome by the gradient force. The maximum incidence angle of the light Ymax is determined by the numerical aperture (NA) of the objective used to focus the laser beam. This is a measure for the solid angle over which the objective lens can

1 Introduction to Optical Tweezers

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InGaAs InGaAs

InGaAs QPD (x,y) signal attenuation

laser

TRAP 2

TRAP 1

isolator main shutter

shutters

moving

OPTICAL MICROSCOPE

TRAP STEERING

power control

LASER

Fig. 5. Optics layout of a typical optical tweezers instrument. The various parts of the system as described in the text are bounded by dashed boxes. The depicted layout was adopted from that of the “NanoTracker” commercial optical tweezers platform of JPK Instruments (see Subheading 5).

gather light and is defined as: NA ¼ n sin Ymax, where n is the refractive index of the immersion medium (i.e., the medium between the objective lens and the sample) and Ymax is one-half the angular aperture. The value of n varies between 1.0 for air and 1.5 for most immersion oils. For typical oil-immersion objectives, an NA of 1.4 corresponds to a total acceptance angle of the objective of about 130 . To obtain a stable three-dimensional optical trap, the laser beam entering the objective has to be wide enough to fill or overfill the back aperture of the objective. This way, one provides sufficient convergent, high-angle rays that contribute to counteracting the scattering force. The maximum forces that can be exerted by an optical trap can be enhanced by either increasing the laser power or optimizing the quality of the focal spot of the laser and the refraction of the laser by the trapped particle (i.e., choosing the proper optics and materials with proper optical densities; see below). The laser power can be increased only up to a certain limit, above which more laser light would lead to heating or photodamage of the examined system (often delicate biomaterials) or even of the optics in the instrument (27). Therefore, care must be taken to optimize the quality of the focal spot of the trapping laser. The difference in refractive index of the trapped object n2 compared to that of the

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surrounding medium n1 determines how strongly the incident rays are refracted and, consequently, how strong the trapping force is. The required balance between gradient and scattering forces yields an optimal refractive index of n2 ¼ 1.69 (5). One often uses silica (glass) particles (n2 ¼ 1.37–1.47) or polystyrene particles (n2 ¼ 1.57). The trapping forces that can be obtained for polystyrene particles are, thus, higher. When using an oilimmersion objective, the refractive index of the immersion oil matches both that of the objective lens and that of the glass of the sample. Therefore, the maximum NA can be achieved with oil-immersion objectives. However, due to the refractive index mismatch between the sample glass and the buffer, spherical aberrations deteriorate the quality of the laser focus when the distance of the focus to the sample surface increases (optical trapping in water with oil-immersion objectives is typically performed within several tens of micrometers of the glass surface) (28). To allow equally stable trapping at any distance to the surface, waterimmersion objectives are often used. Despite the fact that the NA is somewhat compromised (typically, NA ¼ 1.2 for waterimmersion objectives), the ability to move away from the sample surface without lowering the trap quality can be a good reason to use water-immersion objectives. For optical trapping, single-mode continuous wave lasers with a Gaussian beam profile (i.e., operated in the lowest, TEM00, mode) are commonly used. The laser power typically ranges from a few hundred milliwatts up to several watts. Important properties of the laser for stable trapping are low intensity fluctuations and high pointing stability (little angular and transverse wandering of the beam). Of particular interest for biological experiments is the wavelength. Since the light intensity at the focus is very high, heating and damage through light absorption by the often delicate biological material need to be considered. Near-infrared lasers (800–1,200 nm, most often the 1,064-nm line from diode-pumped solid-state lasers) are typically used because of the low absorption of biological material as well as water in this spectral range (5). Although in current biological applications optical traps are most commonly formed by tightly focusing a single laser beam (2), the first stable optical trap was accomplished in 1970 by using two counterpropagating focused laser beams (1). The counterpropagating layout does not require tight focusing such that low NA (<1) objectives or no objective at all may be used. Advantageously, this allows for a larger working distance and lower local light intensity at the trap, making it useful to handle living cells. The “optical stretcher,” designed to probe the deformability of individual cells, is a key example of this approach (29).

1 Introduction to Optical Tweezers

3.2. Environment of the Trap

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Microfluidics: To ascertain well-controlled experimental conditions in single-molecule experiments, it is often useful – if not required – to implement a way to bring the biochemical “ingredients” together under the microscope. The use of microfluidics allows for a fine control over this process by fluid flow of minute volumes of the solutions used. In addition, microfluidic control allows for drag force calibration of the trap, as well as flow stretching of biopolymers, such as DNA (30). An alternative way to induce viscous drag is by moving the fluid reservoir with respect to the trap using a motorized microscope stage. Particularly useful is the combination of either a motorized or a piezoelectric stage with a laminar flow cell. The laminar flow ensures that different buffer flows can be in contact with each other with minimal buffer mixing. By moving the stage to change the position of the trapped beads in the microfluidic device, the buffer conditions can be rapidly exchanged between the regions of different buffer flow. Recently, Brewer et al. extensively reviewed the use of microfluidics devices in single-molecule experiments (31). Temperature control: In biological experiments, temperature often plays an important role. As in conventional microscopy, temperature-controlled fluidics, stages, and objectives can be used to control the temperature at which biological processes take place. In optical tweezers experiments, temperature control of the objective is, in particular, considered. Objectives with short focal lengths, required to obtain a tight focus, are necessarily in close contact with the trapping region through the immersion medium and act as an effective heat sink. Moreover, apart from the relevance for the temperature of the biological system, temperature control of the objective can be beneficial for the performance of the optical tweezers as well. The high laser intensities in optical trapping may produce heating of the optical components, thus causing optical drift, increased stabilization time, and/or decreased spatial resolution. A millikelvin temperature-stabilized objective has been employed to obtain base pair resolution in optical tweezers experiments on DNA (32). Finally, judicious design and analysis of the experiment are required when large temperature fluctuations are anticipated. Among other issues, the reliability of (real time) calibration of optical tweezers using Brownian fluctuations is impacted by significant temperature fluctuations.

3.3. Position and Force Detection

The key to quantitative optical trapping is the accurate detection of the position of the particle in an optical trap. Within the volume of the laser focus, the displacement of the particle from its equilibrium position is directly proportional to the forces acting on this particle.

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Several techniques have been developed for sensitive position detection which are discussed below. Lateral position and force detection – The simplest position-detection scheme relies on video-based imaging of a bead in the optical trap. Using centroid-tracking or template-matching algorithms, the position of one or multiple beads can be obtained with subpixel resolution (down to several nanometers) either by off-line or online digital video analysis (33, 34). Although video-based position detection is simple and direct, it is limited in time resolution by the video acquisition rate (from typically 25 up to 100 Hz with faster cameras). More dedicated imaging techniques, where one bead is directly imaged on a position-sensitive detector (PSD) or quadrant photodiode (QPD), provide a higher time resolution, but require high magnifications and are thus limited in range and signal-to-noise ratio (35, 36). Besides allowing the calculation of the active forces in a biological system when the trap stiffness is known, imaging also provides spatial information on the studied system; observation of the absolute position of beads in the camera’s field of view can provide information on the length scale of a biological system, such as a stretched biopolymer between two beads or the motion of a molecular motor through the field of view, independent of the optical trapping (cf. Fig. 2). The highest time resolution (~ms) and spatial resolution (~pm) are currently obtained with laser-based interferometry techniques for position detection. Currently, the most common position-detection scheme is back-focal-plane (BFP) interferometry (37, 38). Here, the interference between unscattered and forward-scattered light of a laser beam focused on a bead is used to provide positional information in the two lateral dimensions. By imaging the intensity distribution in the BFP of a condenser lens on a QPD or PSD, the recorded signals are rendered insensitive to the location of the trap in the field of view. A major advantage of these interference techniques is that the trapping laser can be used to perform trapping and position detection simultaneously. In this situation, the detection and trap are intrinsically aligned and only relative displacements of the bead with respect to the trap are measured. Displacements of typically up to a few hundred nanometers away from the center of the optical trap are directly proportional to the measured shift on the photodiodes in this configuration. On top of this, simultaneous video analysis of optical images can still be used to measure absolute positions and distances in the studied system. Axial position detection – True three-dimensional position detection allows tracking the (suppressed) Brownian motion of the trapped particle and, thereby, fully quantifying the forces felt by the object in the optical trap. This can be accomplished by combining axial position detection with the abovementioned

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lateral position-detection techniques. The axial position of trapped particles has been detected by using fluorescence methods, performing template-based analysis of bead images (as is often done in magnetic tweezers experiments, see Chapter 15), measuring the forward-scattered light intensity, or using nonimaging interference methods (6). The nonimaging axial interference method, in which modulations in the total laser intensity are detected in the BFP of the condenser, is most practical since it is accurate as well as easily combined with lateral interferencebased detection. Contrary to lateral detection, the best axial sensitivity is obtained when only the low-NA fraction of the light is detected (39). 3.4. Trap Steering

If microscope stage movements do not provide enough flexibility to manipulate trapped objects, the trapping beam itself can be steered through the sample. This is particularly useful for steering multiple traps. Lateral trap movement can be achieved by changing the incoming angle of the trapping beam into the objective while axial movement is effected by changing the level of collimation of the beam. In practice, such three-dimensional trap steering can be accomplished by moving the lenses in a telescope in front of the objective. Alternatively, the use of tip-tilt or galvanometric mirrors, for which accurate and reproducible positioning can be obtained through closed-loop feedback systems, allows rapid lateral trap movement up to several kHz. Finally, more advanced techniques for trap steering include acousto-optical deflectors (AODs) and electro-optical deflectors (EODs). These provide higher scanning speeds up to the MHz range, but typically have more limited deflection ranges. Additional drawbacks are the lower throughput efficiency and inhomogeneous diffraction of AODs and the high costs of EODs. To avoid nonlinearities in the lateral trap steering, it is important to place the steering elements in the setup such that the angular deflection from the optical axis originates in planes conjugate to the BFP of the objective, such as the telescope configuration in Fig. 6. Otherwise, the transmitted laser power and, therefore, the trap stiffness will be dependent on the position in the sample. Finally, it is important to realize that trapped objects are limited in manipulation speed. Viscous drag causes the trapped particle to escape from the trap at high steering speeds. If scanned across multiple positions, galvanometric mirrors and the even faster AODs or EODs can be used to generate multiple traps from a single laser source (see Fig. 7). If the laser is scanned rapidly enough, a trapped particle may not sense the transient absence of the optical trap when at the other scanned positions. This way of generating multiple traps is called trap multiplexing or “time sharing.” An alternative approach to generate multiple

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so f1

TL1

si f2

BFP

TL2

objective

Fig. 6. Steering of an optical trap using a telescope configuration. The second telescope lens (TL2) images the plane of the first one (TL1) onto the back focal plane (BFP) of the objective: 1/si ¼ 1/f2  1/(f1 + f2). Lateral movement of the first telescope lens causes the incident collimated laser beam to enter the BFP under an angle. The laser focus in the sample, thereby, displaces laterally. No intensity changes occur when displacing the beam, hence keeping the trap stiffness position independent.

Fig. 7. Microscopy image of the time-shared optical trapping of 42 beads using AODs. This image demonstrates the smallest game of Tetris ever played. The corresponding video can be found online at http://www.nat.vu.nl/compl/dualdna/tetris.

traps from a single laser line is provided by diffractive optical elements, such as spatial light modulators (SLMs). Multiple trap generation and steering in this case rely on the holographic pattern that causes the incident laser to diffract into separate foci in the sample. The intricate computation of the holographic pattern practically limits the update rates with which the traps can be steered, although this technique is continuously improved. So far, holographic schemes based on SLMs have proven difficult to combine with position- and force-sensing schemes. 3.5. Environment of the Setup

To ensure stability and high spatial resolution, the environment of the optical tweezers setup needs to be well-controlled. Common

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precautions include the use of passively damping optical tables and temperature stabilization within 0.5–0.1 K. Convection of the air in the optical pathway can induce beam deviations through local density fluctuations. These effects can be minimized by enclosing the optical path, reducing the optical path length, or reducing the number of foci along the optical path, since the beam is more sensitive to local density fluctuations in these focal points. For the most demanding applications, optical tweezers instruments have been placed in acoustically isolated rooms with air conditioning equipment that filters out dust particles in the air or even in enclosures in which ambient air is replaced by helium, the even lower refractive index of which renders the instruments less susceptible to density fluctuations of the gas (40). 3.6. Combining Optical Tweezers with Other Techniques

Optical tweezers instruments are composed of common microscopy components and are often incorporated into commercial microscopes. This makes it attractive to combine optical tweezers, and their high level of control, with the capabilities of other optical techniques in order to study biological systems in greater detail. The design of an optical tweezers instrument, however, directly influences its capabilities and to what extent other microscopy or related techniques can be integrated with it. The counterpropagating beams layout, for instance, requires critical coaxial alignment, is difficult to implement in conventional microscopes, and puts strong restrictions on the optics and additional functionalities of the experimental setup. A single-beam optical trap, on the other hand, requires a tightly focused laser beam for stable trapping, which in turn requires a high-NA objective lens and a suitably expanded laser beam at the input aperture. Other than that, no strong requirements are imposed on the microscope, which renders the single-beam trap the more widely used configuration. A new development is the integration of sensitive fluorescence microscopy with optical tweezers, as recently reviewed (30). The direct visualization of single molecules in controlled optical tweezers manipulation experiments has proven a powerful method for the detailed investigation of biomolecular systems, in particular for unraveling DNA–protein interactions (30, 41, 42). In these experiments, DNA is manipulated with optical tweezers while the binding and activity of proteins that interact with the DNA are directly observed through fluorescence microscopy. Changes in DNA structure due to DNA–protein interactions or movement of proteins along DNA can, thus, be simultaneously studied with force spectroscopy and fluorescence microscopy, providing a high level of versatility and unambiguity in these experiments. Furthermore, other advanced optical microscopy techniques, such as polarization or Raman spectroscopy, have been fruitfully combined with optical tweezers (43–46).

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3.7. Optical Trapping Assays Employed in Biology

4. Commercial Optical Tweezers Systems

Several experimental layouts have been developed to employ optical tweezers in biology. The simplest layout consists of a single optical trap, in which particles can be manipulated and, optionally, forces between the trapped particle and its surroundings can be measured. A single optical trap has, for instance, been used to perform force spectroscopy on biomolecular systems that are tethered between the trap and a fixed substrate (see Fig. 2, top). Examples of experiments using this geometry include measurements of the mechanical and structural properties of biopolymers tethered between a trapped bead and a fixed substrate (i.e., a glass slide or a bead held by a micropipette (15)) and measurements of the forces involved in biomolecular activity (10, 20). This activity can be observed either directly, such as in the motion of motor proteins tethered to a trapped bead, or indirectly by measuring structural changes in biomolecules, such as DNA, due to enzymatic activity. The fixed substrate can also be replaced by a particle trapped in a second optical trap (see Fig. 2, bottom). In this dual-trap assay, a biomolecular system tethered between two trapped beads can, thus, be fully suspended in solution, which prevents unwanted surface interactions. In addition, this layout suppresses noise associated with fluctuations or drift in the relative positions of the optical trap and a fixed substrate. This geometry has been employed to obtain single base pair resolution of RNA polymerase activity (40). Finally, advanced optical trapping geometries include the use of multiple optical traps (see Fig. 7), which allow manipulating large biological structures and multiple colloidal particles (47–50). On the single-molecule level, multiple optical traps have been used to measure interactions of multiple DNA molecules and bound proteins (22, 51).

The design and construction of an optical tweezers instrument can be a tedious task, requiring practical and theoretical experience in fields ranging from laser physics, optics, thermodynamics, hydrodynamics, and analog and digital electronics to computer science in order to allow some level of computer control of the instrument as well as data acquisition. In addition, the maintenance of a home-built instrument can be time consuming as well. In view of that, it needs little explanation that many life science researchers hesitate to switch to this type of experimentation. During the past decade, several companies have started offering commercial solutions for optical trapping experiments (23).

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These solutions range from do-it-yourself kits, like that from Thorlabs or the miniTweezers from the Bustamante lab (see http://tweezerslab.unipr.it), to fully automated turnkey platforms. Recently, a product review appeared that describes and compares most commercial platforms (52). The review and the comparison chart therein make clear that optical tweezers technology has ripened over the past decades. Most manufacturers provide instruments that can be flexibly attached or integrated into a standard research-grade inverted optical microscope. Depending on the details of the instrument, this may leave open the possibility to configure the optical microscope in order to combine optical tweezers with other microscope techniques, as described above. However, when the optical trapping laser is coupled into the microscope through the fluorescence port, it is obviously difficult or impossible to combine optical tweezers and fluorescence microscopy. A number of commercial suppliers offer optical tweezers instrumentation primarily as a micromanipulation add-on, integrated with microdissection equipment for controllably cutting cells or tissues. Both the Zeiss PALM product series and those from Molecular Machines and Industries (MMI) originate from the microdissection field. Others are designed as automated, precise force-sensing optical tweezers microscopes, such as the NanoTracker from JPK Instruments (see Figs. 5 and 8), which include sample-handling modules for microfluidics or live-cell work. The BioRyx 200 from Arryx Inc. focuses on the simultaneous manipulation of large groups of particles through holographic trap arrays.

Fig. 8. Dr. Remus T. Dame (Leiden University, The Netherlands) using his NanoTracker from JPK Instruments.

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When considering the purchase of a commercial optical tweezers instrument, the aforementioned review may be a good starting point. Several aspects should be kept in mind. Obviously, the first thing to define is the main application for the instrument. Is the system going to be used only for manipulation, or is quantification of the forces exerted going to be useful? Is fluorescence imaging required, or are other microscope features important? Is the delivered software flexible enough to accommodate the required experiments? Important characteristics, like user friendliness or flexibility in system design, are best assessed in a live demonstration of the instrument.

5. Concluding Remarks Optical tweezers techniques form a valuable addition to the single-molecule toolkit. These minimally invasive techniques provide scientists with the ability to actively manipulate biomolecules with nanometer precision and to measure or apply forces with piconewton resolution. Examples of the application of these powerful tools in molecular biology include the study of active molecular motors, the mechanical properties of DNA, and the mechanochemistry of DNA–protein interactions. Commercial optical tweezers systems are becoming increasingly available, which makes this powerful and versatile technique accessible to a broad range of researchers from different backgrounds and undoubtedly drives new biological discoveries on the singlemolecule level. The following chapters describe detailed methods and protocols of several applications of optical tweezers in molecular biology. References 1. Ashkin, A. (1970) Acceleration and Trapping of Particles by Radiation Pressure Physical Review Letters 24, 156–9. 2. Ashkin, A., Dziedzic, J. M., Bjorkholm, J. E., and Chu, S. (1986) Observation of a single-beam gradient force optical trap for dielectric particles Optics Letters 11, 288–90. 3. Chu, S. (1991) Laser manipulation of atoms and particles Science 253, 861–6. 4. Chu, S. (1992) Laser trapping of neutral particles Scientific American 266, 70–6. 5. Svoboda, K., and Block, S. M. (1994) Biological Applications of Optical Forces Annual Review of Biophysics & Biomolecular Structure 23, 247–85.

6. Neuman, K. C., and Block, S. M. (2004) Optical trapping Review of Scientific Instruments 75, 2787–809. 7. Moffitt, J. R., Chemla, Y. R., Smith, S. B., and Bustamante, C. (2008) Recent Advances in Optical Tweezers Annual Review of Biochemistry 77, 205–28. 8. Ashkin, A., and Dziedzic, J. M. (1987) Optical trapping and manipulation of viruses and bacteria Science 235, 1517–20. 9. Ashkin, A., Dziedzic, J. M., and Yamane, T. (1987) Optical trapping and manipulation of single cells using infrared-laser beams Nature 330, 769–71. 10. Block, S. M., Goldstein, L. S. B., and Schnapp, B. J. (1990) Bead Movement by Single

1 Introduction to Optical Tweezers Kinesin Molecules Studied with Optical Tweezers Nature 348, 348–52. 11. Bustamante, C., Macosko, J. C., and Wuite, G. J. L. (2000) Grabbing the cat by the tail: Manipulating molecules one by one Nature Reviews Molecular Cell Biology 1, 130–6. 12. Davenport, R. J., Wuite, G. J. L., Landick, R., and Bustamante, C. (2000) Single-molecule study of transcriptional pausing and arrest by E. coli RNA polymerase Science 287, 2497–500. 13. Smith, S. B., Cui, Y., and Bustamante, C. (1996) Overstretching B-DNA: the elastic response of individual double-stranded and single-stranded DNA molecules Science 271, 795–9. 14. Svoboda, K., Schmidt, C. F., Schnapp, B. J., and Block, S. M. (1993) Direct Observation of Kinesin Stepping by Optical Trapping Interferometry Nature 365, 721–7. 15. Wuite, G. J. L., Smith, S. B., Young, M., Keller, D., and Bustamante, C. (2000) Singlemolecule studies of the effect of template tension on T7 DNA polymerase activity Nature 404, 103–6. 16. EssevazRoulet, B., Bockelmann, U., and Heslot, F. (1997) Mechanical separation of the complementary strands of DNA Proceedings of the National Academy of Sciences of the United States of America 94, 11935–40. 17. Kellermayer, M. S. Z., and Bustamante, C. (1997) Folding-unfolding transitions in single titin molecules characterized with laser tweezers (vol 276, pg 1112, 1997) Science 276, 1112–6. 18. Tskhovrebova, L., Trinick, J., Sleep, J. A., and Simmons, R. M. (1997) Elasticity and unfolding of single molecules of the giant muscle protein titin Nature 387, 308–12. 19. Wang, M. D., Schnitzer, M. J., Yin, H., Landick, R., Gelles, J., and Block, S. M. (1998) Force and velocity measured for single molecules of RNA polymerase Science 282, 902–7. 20. Yin, H., Wang, M. D., Svoboda, K., Landick, R., Block, S. M., and Gelles, J. (1995) Transcription against an applied force Science 270, 1653–7. 21. Bustamante, C., Bryant, Z., and Smith, S. B. (2003) Ten years of tension: single-molecule DNA mechanics Nature 421, 423–7. 22. Dame, R. T., Noom, M. C., and Wuite, G. J. L. (2006) Bacterial chromatin organization by H-NS protein unravelled using dual DNA manipulation Nature 444, 387–90. 23. Matthews, J. N. A. (2009) Commercial optical traps emerge from biophysics labs Physics Today 62, 26–8.

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24. Ashkin, A. (1992) Forces of a Single-Beam Gradient Laser Trap on a Dielectric Sphere in the Ray Optics Regime Biophysical Journal 61, 569–82. 25. Gittes, F., and Schmidt, C. F. (1998) Signals and noise in micromechanical measurements, in Methods in Cell Biology, pp 129–56, Academic Press, London. 26. Reif, F. (1965) Fundamentals of statistical and thermal physics, McGraw Hill, New York. 27. Peterman, E. J. G., Gittes, F., and Schmidt, C. F. (2003) Laser-induced heating in optical traps Biophysical Journal 84, 1308–16. 28. Vermeulen, K. C., Wuite, G. J. L., Stienen, G. J. M., and Schmidt, C. F. (2006) Optical trap stiffness in the presence and absence of spherical aberrations Applied Optics 45, 1812–9. 29. Guck, J., Ananthakrishnan, R., Mahmood, H., Moon, T. J., Cunningham, C. C., and Kas, J. (2001) The optical stretcher: A novel laser tool to micromanipulate cells Biophysical Journal 81, 767–84. 30. van Mameren, J., Peterman, E. J. G., and Wuite, G. J. L. (2008) See me, feel me: methods to concurrently visualize and manipulate single DNA molecules and associated proteins Nucleic Acids Research 36, 4381–9. 31. Brewer, L. R., and Bianco, P. R. (2008) Laminar flow cells for single-molecule studies of DNA-protein interactions Nature Methods 5, 517–25. 32. Mahamdeh, M., and Schaffer, E. (2009) Optical tweezers with millikelvin precision of temperature-controlled objectives and base-pair resolution Optics Express 17, 17190–9. 33. Cheezum, M. K., Walker, W. F., and Guilford, W. H. (2001) Quantitative comparison of algorithms for tracking single fluorescent particles Biophysical Journal 81, 2378–88. 34. Crocker, J. C., and Grier, D. G. (1996) Methods of digital video microscopy for colloidal studies Journal of Colloid and Interface Science 179, 298–310. 35. Finer, J. T., Simmons, R. M., and Spudich, J. A. (1994) Single myosin molecule mechanics piconewton forces and nanometer steps Nature 368, 113–9. 36. Visscher, K., Gross, S. P., and Block, S. M. (1996) Construction of multiple-beam optical traps with nanometer-resolution position sensing. IEEE Journal of Selected Topics in Quantum Electronics 2, 1066–76. 37. Denk, W., and Webb, W. W. (1990) Optical measurement of picometer displacements of transparent microscopic objects Applied Optics 29, 2382–91.

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38. Gittes, F., and Schmidt, C. F. (1998) Interference model for back-focal-plane displacement detection in optical tweezers Optics Letters 23, 7–9. 39. Dreyer, J. K., Berg-Sorensen, K., and Oddershede, L. (2004) Improved axial position detection in optical tweezers measurements Applied Optics 43, 1991–5. 40. Abbondanzieri, E. A., Greenleaf, W. J., Shaevitz, J. W., Landick, R., and Block, S. M. (2005) Direct observation of base-pair stepping by RNA polymerase Nature 438, 460–5. 41. van Mameren, J., Gross, P., Farge, G., Hooijman, P., Modesti, M., Falkenberg, M., Wuite, G. J. L., and Peterman, E. J. G. (2009) Unraveling the structure of DNA during overstretching by using multicolor, singlemolecule fluorescence imaging Proceedings of the National Academy of Sciences of the United States of America 106, 18231–6. 42. van Mameren, J., Modesti, M., Kanaar, R., Wyman, C., Peterman, E. J. G., and Wuite, G. J. L. (2009) Counting RAD51 proteins disassembling from nucleoprotein filaments under tension Nature 457, 745–8. 43. Bennink, M. L., Scharer, O. D., Kanaar, R., Sakata-Sogawa, K., Schins, J. M., Kanger, J. S., de Grooth, B. G., and Greve, J. (1999) Singlemolecule manipulation of double-stranded DNA using optical tweezers: interaction studies of DNA with RecA and YOYO-1 Cytometry 36, 200–8. 44. Murade, C. U., Subramaniam, V., Otto, C., and Bennink, M. L. (2010) Force spectroscopy and fluorescence microscopy of dsDNA-

YOYO-1 complexes: implications for the structure of dsDNA in the overstretching region Nucl. Acids Res. 45. Petrov, D. V. (2007) Raman spectroscopy of optically trapped particles Journal of Optics A: Pure and Applied Optics 9, S139-S56. 46. Rao, S., Ba´lint, t., Cossins, B., Guallar, V., and Petrov, D. (2009) Raman Study of Mechanically Induced Oxygenation State Transition of Red Blood Cells Using Optical Tweezers 96, 209–16. 47. Grier, D. G. (2003) A revolution in optical manipulation Nature 424, 810–6. 48. Liesener, J., Reicherter, M., Haist, T., and Tiziani, H. J. (2000) Multi-functional optical tweezers using computer-generated holograms Optics Communications 185, 77–82. 49. Mio, C., Gong, T., Terray, A., and Marr, D. W. M. (2000) Design of a scanning laser optical trap for multiparticle manipulation Review of Scientific Instruments 71, 2196–200. 50. Visscher, K., Brakenhoff, G. J., and Krol, J. J. (1993) Micromanipulation by multiple optical traps created by a single fast scanning trap integrated with the bilateral confocal scanning laser microscope Cytometry 14, 105–14. 51. Noom, M. C., van den Broek, B., van Mameren, J., and Wuite, G. J. L. (2007) Visualizing single DNA-bound proteins using DNA as a scanning probe Nature Methods 4, 1031–6. 52. Piggee, C. (2008) Optical tweezers: not just for physicists anymore Analytical Chemistry 81, 16–9.

Chapter 2 Optical Trapping and Unfolding of RNA Katherine H. White and Koen Visscher Abstract Optical tweezers have proven a useful tool for exploring the structure and function of individual molecules, such as proteins, DNA, and RNA. The ability to unfold and refold biological molecules has provided novel insights that complement and go beyond traditional biochemical and structural approaches. With sophisticated optical tweezers instrumentation coming to the market, single-molecule stretching studies now have become feasible and available to a wide range of users. Therefore, a step-bystep protocol for stretching individual biomolecules utilizing a simple experimental geometry is timely and presented here. While we have taken the unfolding of an RNA structure held between two RNA/DNA hybrid handles as an example, the technical protocol should be readily applicable to other biomolecules and may serve as a starting point for more sophisticated experiments. Key words: Single molecule, RNA unfolding, Optical tweezers, RNA pseudoknot

1. Introduction Biochemical techniques, such as X-ray crystallography, thermal denaturation, and mutational analysis, have provided detailed pictures of RNA secondary and tertiary structures. However, such methods often lack a dynamic picture of RNA behavior during biological processes, such as translation by ribosomes and ribozyme catalysis (1, 2). Single-molecule techniques utilizing fluorescence resonance energy transfer (FRET), atomic force microscopy (AFM), or magnetic and optical tweezers are capable of providing detailed structural and kinetic information complementing and going beyond ensemble-averaged approaches, see refs. 3–5 for reviews of single-molecule FRET, AFM, and optical tweezers, respectively. The latter three techniques allow one to investigate the effect of an external force upon structure and function (6). Here, we focus on the stretching and unfolding of single RNA molecules

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_2, # Springer Science+Business Media, LLC 2011

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using optical tweezers. It is becoming apparent that force may well control critical biological processes, such as translation of messenger RNA by ribosomes and associated processes such as minus one (
1) frameshifting (7–10) and SecM arrest (11). Optical tweezers are an ideal tool for such experiments because they allow a wide range of loading rates, probing the system of interest both close and far removed from thermal equilibrium (12). As the RNA is stretched, structural transitions become visible in the forceextension graph, enabling one to derive thermodynamic and kinetic parameters, such as unfolding force, increase in contour length, and rates and free energies of folding and unfolding (6). Since obtaining high-quality data from these experiments does not come without its challenges, here we provide guidance for preparing, performing, and analyzing an RNA-stretching experiment in its simplest experimental geometry using optical tweezers. We have divided the overall procedure into five subcategories: 3.1. Determination of Assay Geometry 3.2. Preparation of Samples 3.3. Calibration of the Optical Tweezers 3.4. Stretching RNA and Collecting Data 3.5. Analyzing Stretching Data

2. Materials 2.1. RNA/DNA Handle Hybridization

1. 1.5-mL Eppendorf Safe-Lock tube (Eppendorf, 226002-8). 2. Phosphate buffer: 25 mM Na2HPO4, 75 mM NaH2PO4, pH 6.4, 100 mM NaCl. 3. 1 pmol/mL single-stranded DNA handles (see Subheading 3.2), termed handles A and B. 4. 1 pmol/mL single-stranded RNA construct (see Subheading 3.2).

2.2. Coating Polystyrene Beads with Anti-digoxigenin

1. 80 mg/mL acetylated bovine serum albumin (BSA) in ddH2O. 2. 1 phosphate-buffered saline (PBS), pH 7.2 (Bio-Rad). 3. 0.770 mm diameter, 4.0% (w/v) surfactant-free, white aldehyde/ sulfate latex polystyrene beads stored at 4 C (Invitrogen). 4. 1 mg/mL anti-digoxigenin, Fab fragments (Roche). 5. 2% (w/v) sodium azide in ddH2O (Sigma). 6. 1.0 M glycine in 1 PBS (Sigma).

2 Optical Trapping and Unfolding of RNA

2.3. Attaching RNA/ DNA Hybrid to the Antidigoxigenin-Coated Bead

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1. 1.5-mL Eppendorf Safe-Lock tube (Eppendorf, 226002-8). 2. RNA stretching buffer (RSB, 5): 100 mM Tris–HCl, pH 7.0, 1,250 mM NaCl, 30 mM bME. Tris–HCl plus NaCl can be stored at room temperature. bME is added on the day of the experiment. 3. 1 M MgCl2 in ddH2O (Ambion). 4. 50 mg/mL acetylated BSA in ddH2O.

2.4. Flow Cell Assembly

1. 25  75 mm, 1.0-mm thick microscope glass slide (VWR). 2. Double-sided sticky tape, such as Scotch. 3. 22  40 mm, 0.17-mm thick (number 1½) streptavidincoated microscope cover slips (Xenopore) (see Note 1). 4. Epoxy glue, such as Devcon Fast-Drying Epoxy.

2.5. Specimen Preparation

1. Washing buffer: 1 RSB buffer, 20 mM MgCl2, 0.5% w/v acetylated BSA. Washing buffer should always be made fresh on the day of the experiment. 2. Clear nail polish, any brand.

3. Methods 3.1. Determination of Assay Geometry

Optical tweezers allow for a variety of experimental geometries to be used for stretching individual biomolecules. The tweezers may be used simply to manipulate and hold a molecule stretched by laminar fluid flow (13) or be utilized as the actual force transducers and force probes yielding the force-extension characteristics of the molecule (14). Here, we address experimental geometries that are in common use, each with distinct advantages and disadvantages. RNA stretching data presented here follows the first method, surface–bead tethering.

3.1.1. Surface–Bead Tethering

Perhaps the most commonly used geometry tethers the molecule between a microscope coverslip surface and a microscopic bead held in the optical tweezers (Fig. 1a). The molecule then is stretched by movement of the piezo-driven microscope stage. Following calibration of the tweezers’ spring constant (see Subheading “Spring Constant Calibration”), recording of the bead’s position with respect to the optical tweezers’ center and the stage position enables computation of force-extension data. Stage motion to stretch the molecule is generally in the lateral direction (perpendicular to the laser beam), but can also be axially along the laser beam axis (15). The main advantage of this geometry is that the specimen preparation is relatively simple. Incubation of molecule-coated

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Fig. 1. Experimental geometries for unfolding RNA structures. (a) Surface–bead tethering, (b) bead–bead tethering from the surface, and (c) bead–bead tethering with two optical tweezers.

beads in appropriately surface-treated sample cells readily enables identification of surface-tethered beads in the optical microscope, even when tether formation proves inefficient. However, the geometry has two main complications. First, instrumental drift, predominately of the microscope stage, may hamper slow stretching experiments performed near thermal equilibrium. Second, lateral motion of the piezo stage results in both lateral and axial displacement of the bead from the center of the optical tweezers because the force vector is not parallel to the coverslip surface due to finite size of the bead. The latter becomes particularly problematic for short molecules of <0.5 mm in contour length (LC) (relative to the size of the bead, ~1 mm), where the angle with the horizontal becomes large. However, both issues have been addressed in the past, with the effects of drift minimized or eliminated in a differential detection scheme (16) and the nonhorizontal force vector accounted for in detailed data analysis

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and/or simultaneous measurement of the axial position of the bead in the optical tweezers (14). 3.1.2. Bead–Bead Tethering

To avoid any axial bead displacement in the optical tweezers, the molecule can be tethered between two beads rather than between a bead and the microscope coverslip. In such geometries, one bead is held in the optical tweezers while the other bead may be attached to the microscope coverslip, held on the tip of a micropipette, or held in an additional optical tweezers as seen in Fig. 1b, c (5). Beads with different surface chemistries are available commercially and relatively inexpensive. In addition, the sizes of purchased beads can be selected to meet the needs of the experiment. When the second bead is immobilized on the microscope coverslip, it needs to be larger than the bead in the optical tweezers to avoid any undesired surface interactions. We further note that stage drift problems remain, except when the second bead is also held with optical tweezers as in Fig. 1c (17). Bead–bead tethering tends to be more laborious than surface tethering with the operator actively moving beads together to promote tether formation. The application of fluid flow to automate part of the process may alleviate some of these concerns. Bead–bead tethering may also become problematic when tethers are short and interbead distances become small as a consequence. Many optical tweezers apply back-focal-plane detection scheme to measure the position of a bead within the optical tweezers (18). When one considers the response curves of such detection schemes (19), it becomes apparent that the presence of a nearby bead may well affect the position signal of the bead held in the optical tweezers. Naively, one may think of this as if the nearby bead intercepts the light cone making up the detection probe as shown in Fig. 2a. Therefore, using a much smaller bead as some

Fig. 2. “Cross-talk” due to proximity of beads. In a bead–bead geometry using three beads, the “cross-talk” due to the close proximity of the beads is reduced when compared to a bead–bead geometry using two beads. (a) A bead may naively be thought to “intercept” the detector laser light when using microscope objectives with a large numerical aperture. (b) Detector cross-talk signals with two and three bead–bead geometries as a function of the interbead distance.

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sort of spacer may help to alleviate this “cross-talk” problem (20). To test this, we measured the detector response as a function of interbead distance for both two- and three-bead setups; results shown in Fig. 2b. When a small-bead spacer is applied, the “crosstalk” is significantly smaller. In both cases, the signals are highly reproducible and can be corrected for. Particle-imaging detectors, such as a CCD camera, should be much less affected by the bead proximity issues, but have their own problems (21). One should realize that at the same time as the detection signal is modified, the optical tweezers’ properties, such as spring constant and harmonic nature of the potential, may also be affected. Such effects upon the optical tweezers have to the best of our knowledge not been quantified (but presumably are small). Since the complications discussed above are due to the short length of the RNA/DNA handles used, one may wonder why longer handles are not used. Fluctuations potentially obscuring the unfolding transition in the force-extension graph depend upon the total stiffness. By the equipartition theorem, the higher the stiffness, the smaller the fluctuations are and the easier an unfolding transition is detected. The total stiffness or spring constant includes both that of the optical tweezers and the RNA/ DNA hybrid. Because the stiffness of the RNA/DNA hybrid scales as LC
1, the longer the handles, the larger the fluctuations. It is worth to carefully estimate which lengths of handles prove optimal for the expected increase in extension (and/or LC) upon unfolding of the RNA of interest at the typical spring constant of the optical tweezers used. In summary, surface–bead tethering readily produces tethers, but data analysis is complicated by axial bead motion. Bead–bead geometries offer the advantage of easier data analysis, but tethering can be more cumbersome and bead–bead detection cross-talk is possible. In the remainder of this paper, we provide a detailed description for performing a stretching experiment using the surface–bead geometry. 3.2. Preparation of Samples

We discuss steps to prepare a specimen for stretching an RNA structure, such as a hairpin or pseudoknot, using the surface–bead geometry, where the molecule is tethered between a bead in the optical tweezers and a surface. The RNA structure of interest is sandwiched in between hybrid RNA/DNA handles as developed by Liphardt (22).

3.2.1. RNA/DNA Handle Hybridization

An RNA structure, such as a pseudoknot, is part of a long, single-stranded RNA molecule (~1.2 kb) to be hybridized to two complementary, single-stranded DNA molecules at the flanks. The DNA molecules are end-labeled on one end with biotin and digoxigenin on the other, enabling attachment to

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streptavidin-coated cover slips and anti-digoxigenin-coated beads. Here, we assume that RNA molecules and DNA handles are already available. 1. Add 6 mL of ddH2O water to a 1.5-mL Eppendorf tube. 2. Add 1 mL of phosphate buffer. 3. Add 1 mL of DNA handle A. 4. Add 1 mL of DNA handle B. 5. Heat up the tube for 5 min using a heat block set to 100 C. 6. Add 1 mL of RNA construct (see Note 2). 7. Take the heat block out and allow to cool to room temperature. This should take about an hour. 8. Dilute the RNA/DNA hybrid by adding 90 mL of ddH2O to the 10 mL of sample. 9. Divide into 5-mL aliquots, quick freeze, and store at
20 or
80 C. 10. When ready to use, pull out one aliquot and allow thawing by warming with hand or leaving on lab bench. We found this procedure to produce a high fraction of appropriately hybridized molecules. Incomplete or incorrect hybridization may, however, occur. Such pathological molecules are readily recognized in a stretching study because they display many more and larger unfolding events than reasonably can expected and/or yield persistence and contour lengths too far removed from what may be expected for the two double-stranded handles. 3.2.2. Attaching the RNA/ DNA Hybrid to Antidigoxigenin Beads

Next, the RNA/DNA hybrids are attached to a polystyrene bead that can be optically trapped. For convenience sake, polystyrene beads may be purchased with a variety of functional groups already attached. Or, to reduce cost, one may coat aldehyde–sulfatemodified polystyrene beads with functional groups. The following protocol is used to coat polystyrene beads with anti-digoxigenin.

Coating Polystyrene Beads with Anti-digoxigenin

1. In two 1.5-mL Eppendorf tubes, mix 1.2 mL 2 mg/mL BSA in 1 PBS for 2 h with gentle mixing on a rotator at room temperature. 2. Empty and rinse tubes with water. 3. Add 0.6 mL of aldehyde/sulfate polystyrene beads and 0.6 mL 1 PBS buffer and mix by vortexing for 30 s. 4. Spin down beads for 2 min at 16,000  g. 5. Discard supernatant and resuspend beads in 1.2 mL 1 PBS buffer by vortexing. 6. Repeat step 5 and resuspend beads in 0.935 mL 1 PBS buffer; vortex for 30 s.

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7. Add 600 mL of 1 mg/mL anti-digoxigenin fragments to the above tube and mix gently by pipeting solution up and down. 8. Add 80 mL of 1 mg/mL acetylated BSA in ddH2O and mix by vortexing for 30 s. 9. Mix/incubate overnight in a rotator at 4 C. 10. Spin beads down for 2 min at 16,000  g. 11. Discard supernatant and resuspend in 1.2 mL 1.0 M glycine. 12. Incubate for 40 min at 4 C with gentle mixing. 13. Spin down and resuspend in 0.960 mL 1 PBS. Add 40 mL 80 mg/mL acetylated BSA and 5 mL of 2% (w/v) sodium azide in ddH2O. 14. Transfer bead suspension to the second BSA-treated tube from step 1 (see Note 3). The next step is to attach the RNA/DNA hybrid to the newly coated anti-digoxigenin beads. Attaching the RNA/DNA hybrids to the beads preferably needs an overnight incubation, so plan to set this up the day before an experiment. Attaching the RNA/DNA Hybrid to the Antidigoxigenin-Coated Bead

1. Add 28.5 mL of water to a 1.5-mL Eppendorf tube. 2. Add 10 mL of 5 RSB. 3. Add 0.5 mL of 1 M MgCl2. 4. Add 5 mL of anti-digoxigenin-coated beads (diluted 1:10 in ddH2O from stock solution). 5. Add 2 mL of 50 mg/mL acetylated BSA in ddH2O. 6. Mix well by vortexing. 7. Add 5 mL of RNA/DNA hybrid (see Subheading 3.2.1, step 10). 8. Incubate and tumble overnight at 4 C. RNA/DNA hybrids and beads are mixed at a theoretical 5:1 ratio (see Note 4). One may increase the concentration of RNA/ DNA hybrid to reduce incubation times. RSB can be made in a large stock solution ahead of time, but bME must be added on the day of the experiment. Anti-digoxigenin beads remain useable generally for up to 6 months when stored with sodium azide at 4 C. However, when molecules cannot be seen tethered to the surface, the anti-digoxigenin-coated beads are usually the culprit and a new batch should be made.

3.2.3. Flow Cell Assembly

Following the attachment of the digoxigenin end of the molecule to an anti-digoxigenin bead, the next step is to create a flow cell that can be mounted onto a microscope stage.

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Fig. 3. A typical flow cell. Double-sided tape is applied to a glass slide, and then coated lightly with epoxy glue (not shown). A streptavidin-coated coverslip is mounted, creating a chamber for the aqueous RNA solution. After all steps in Subheading 3.2 are performed, the flow cell is sealed on both ends with clear nail polish.

1. Collect a microscope slide, double-sided sticky tape, epoxy glue, and a streptavidin-coated coverslip. 2. Lay the glass slide horizontally and apply two thin strips of tape approximately ½ in. apart of center to create a chamber (Fig. 3). 3. Coat the tape with a light layer of epoxy glue (see Note 5). 4. Place the streptavidin-coated coverslip on top of the glue perpendicular to the glass slide. This creates a chamber of 20–50-mL volume. Place in a Petri dish for easy transportation to a lab bench or to the optical trap. 5. The sample cell is ready in about 5 min, but can be stored in Petri dish at 4 C up to about 1 week. 3.2.4. Specimen Preparation, Putting It All Together

With the various components prepared, the final step is to attach the biotinylated end of the RNA/DNA hybrid to a microscope coverslip and seal the flow cell for use in a stretching experiment. 1. Take a flow cell from the 4 C fridge and let sit for 15 min at room temperature. 2. Take the tube containing the tethered bead out of the fridge and let sit at room temperature. 3. Introduce washing buffer and flow through at least 4 volumes. 4. Fill the chamber with washing buffer and let sit for 1 h (see Note 6). 5. Add beads that have been incubated with RNA/DNA (result of Subheading “Attaching the RNA/DNA Hybrid to the Anti-digoxigenin-Coated Bead”) into the cell. 6. Let sit for 2 h at room temperature (see Note 6). 7. Wash out the unbound beads and nucleic acid by flowing through 200 mL or more of washing buffer.

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8. Seal both ends of the sample cell using nail polish and wait until it dries. 3.3. Calibration of the Optical Tweezers

Stretching of individual biomolecules using optical tweezers requires two main calibration procedures to enable both extension and force to be measured: calibrations of the position sensor and of the spring constant of the tweezers. These calibration procedures have been extensively discussed and we refer to review articles (5, 21) and also to Chapter 1 of this volume. The foundation of these calibrations lies with a length standard (preferably traceable to NIST standards), such as ruled stage micrometer or piezo-driven microscope stage with subnanometer position accuracy. These standards enable calibration of the CCD camera, laser beam deflectors to move the optical tweezers (acousto- or electrooptical deflectors, piezo-driven mirrors), and eventually the quadrant or position-sensitive diode used in the back-focal-plane detection scheme. The details of these procedures depend on the precise physical layout of the instrument used (21).

3.3.1. “One-Time” Calibrations

We calibrate our CCD-based imaging system by using a 10-mm ruled stage micrometer and counting the number of pixels between markings, thus yielding the CCD pixel size in units of nm/pixel. Uncertainties are usually <0.25% (depending on overall microscope magnification). Subsequently, the acousto-optic deflectors (AODs) controlling the position of the optical tweezers in the lateral directions are calibrated. To do this, the microscopic bead is trapped and moved by changing the acoustic frequency applied to the AODs. Subpixel resolution particle-tracking software (e.g., as a free plug-in to ImageJ) then provides the particle position as a function of acoustic frequency, yielding the AOD calibration in units of nm/MHz. Averaging of particle positions and/or trajectories is advisable when the optical tweezers are weak and the particle experiences large (e.g., visible) fluctuations. Furthermore, care should be taken in matching the rate of change of tweezers’ position and the CCD sampling rate in order to avoid undersampling and/or missed events.

3.3.2. “Online” Calibrations

The surface–bead geometry allows repeated detector and spring constant calibration interspersed with stretching experiments for the lifetime of the tether. This capability is particularly useful when stage drift is of concern. Furthermore, such online calibrations compensate for any variability in bead size from tether to tether.

Position Detector Calibration

Even with a short biomolecule (LC ~ 300 nm), the position detector can be calibrated by moving the optical tweezers and trapped bead with an amplitude of 200 nm from the position detector’s center, which is also the tether anchoring point. At a maximum bead excursion of 200 nm, the typical relative extension

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(which depends upon the height of the bead above the microscope coverslip) amounts to 35–60%. For a double-stranded DNA molecule, this results in hardly any force (0.1–0.25 pN) so that the bead remains practically at the optical tweezers’ center in a reasonably stiff trap (0.25 pN/nm) throughout the calibration (see Note 7). The proportion of single-stranded RNA over the entire RNA/DNA hybrid is less than 2%, so using double-stranded DNA properties to calibrate the instrument works well. Spring Constant Calibration

Also the tweezers’ spring constant can readily be determined in the presence of the RNA/DNA hybrid tether. The equipartition theorem of statistical mechanics states that: 1 1
 kB T ¼ k x 2 ; 2 2 with
2  kB the Boltzmann constant, T the absolute temperature, and x the variance in bead position. In the surface–bead geometry, k is the sum of the optical tweezers’ spring constant and that of the RNA/DNA hybrid. However, so long the tether remains relaxed (relative extension LxC < 12 ), the RNA/DNA hybrid spring constant is negligible and kequals the optical tweezers’ spring constant. Other popular calibration methods for the spring constant, such as the power spectrum method and any others that rely on the temporal response of the trapped bead, are difficult to use since these require knowledge about the viscous drag coefficient of the bead and the RNA/DNA hybrid. The latter, however, is not readily available.

Mechanical Drift

Online calibration methods are ideal when microscope stage drift is of any concern. For example, drift can be so large that the reported bead position exceeds the calibration limits. Restoring the stage position and recalibration allows for further stretching experiments once the drift has ceded (see Note 8). As mentioned above, drift may drive the bead into a position relative to the position detector, where the detector response is no longer the same as at the point of calibration. Optical tweezers instruments that use an extra laser for back-focal-plane detection in addition to the one used for the optical tweezers enable the user to minimize the effect of axial drift upon lateral position response. By moving the detection laser focus with respect to the tweezers’ center, a “sweet spot” can be found that gives a maximum lateral response while at the same time being less sensitive to axial drift. To find this optimal setting, a wide range of axial positions for the detector beam focus can be sampled to find a position of greatest lateral signal. Figure 4 shows the lateral (x) signal scope vs. axial (z) position of the detector beam. The units of the z position are arbitrary and specific to the instrument used. What is important to

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Fig. 4. Finding the detector “sweet spot.” The lateral detector response amplitude plotted as a function of the axial detector beam focus position. In our instrument, this position is found to be near z ¼ 5.5 (arbr. units), which reflects the micrometer readout of one of the lenses in a 1:1 telescope used to position the detector laser focus in the specimen in all three dimensions.

note is that the region where the x signal is maximized also shows the least change in response with changes in the axial position. In our instrument, the lateral detector response remains unaffected over ~80 nm range (z displacement in the specimen) around the “sweet spot.” This is an optimal regime to work at because axial drift has the least effect on detector response in the lateral direction. 3.4. Stretching RNA and Collecting Data

3.4.1. Preparations Using a Free, Untethered Bead

At the start of the day, well before any experiment is performed, it is often a good idea to turn on all required instrumentation (lasers, microscope light source, piezo stage, electronics, computers, etc.) to let the instrument and experiment room thermally equilibrate, thus minimizing drift. This includes running your favorite software programs (e.g., Labview) that control and initialize the piezo stage and AODs. 1. Mount sample on the microscope and survey the sample quality. This is a time when one may recognize problems that prohibit successful experiments. Such problems could range from (a) small particulates diffusing through the sample and becoming trapped in the optical tweezers (solution: wash the sample cell or discard specimen) and (b) excessive fluid flow due to a leak (solution: discard specimen) to (c) finding almost all beads stuck to the microscope coverslip due to nonspecific binding (one possible solution: when using BSA as blocking reagent,

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refresh BSA stock as its aging is known to cause sticking). An ideal sample cell has many tethered beads as well as a few freely floating beads per field of view. 2. Trap a freely diffusing bead with the optical tweezers. Silica beads are readily trapped with the tweezers without much effort. Due to the nature of the 3D trapping potential, capturing a polystyrene bead requires a little more effort. First, remain close to the coverslip surface (up to 10–20 mm away, depending upon alignment and/or spherical aberrations). Then, aim the tweezers at a bead which is located between the coverslip and the laser beam focus (a laser beam shutter may be helpful here, but not necessarily required). This procedure takes some practice, but generally leads to efficient trapping of polystyrene beads. When the tweezers is aimed at a polystyrene bead located beyond the focus, the bead is pushed upward into the sample. If trapping of polystyrene beads remains problematic, further expansion of the tweezers’ laser beam diameter before entering the microscope objective will help to alleviate this problem. Note that inexperienced users may sometimes mistake the pushing of polystyrene beads upward against the “ceiling” of the specimen (usually, the microscope slide) for actual 3D trapping near the coverslip. Therefore, it is useful to keep track of precisely where the microscope is focused. 3. Overlap detector laser focus with the optical tweezers. We find that the two laser beams get slightly out of alignment in a day’s time. To overlap the beams, we laterally move a trapped bead through the detector focus using the AODs while optimizing detector response and minimizing cross-talk by moving the 1:1 telescope lens in the optical path of detector laser beam. 4. Estimate and set the axial position of the trap with respect to the coverslip. Neuman and Block have extensively described methods to accurately determine the axial position (5). We do not further comment further on this method here. The position of the trap with respect to the coverslip surface may be estimated by moving the piezo stage and microscope coverslip up against the bead in the trap until the quadrant photodiode sum signal changes significantly. A more precise estimate may be obtained off-line by correlating this sum single change with (a one-time) Neuman–Block procedure (5). The stage is then moved relative to this user-defined reference plane to set the bead height above the surface. This procedure may also be utilized to perform a full calibration of the quadrant photodiode sum signal, which is proportional to the axial position of the bead with respect to the detector focus. 5. Calibrate the lateral, x and y, responses of the position sensor. After the bead’s axial position has been set, the detector

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calibration is performed as described in Subheading 3.3. By fitting the bead displacements vs. detector voltages data using polynomial functions, the range of the detector may be extended beyond the linear regime. If the data seems scattered or a polynomial cannot readily be fit, this is an indicator of problems, such as the following. (a) Sticking, slipping of the bead when too close to or on the glass coverslip surface. Or, if the bead was carrying a biomolecule, it may have bound to the surface and formed a tether. (b) The overlap between detector and the optical tweezers’ beam is off. 6. Determine the tweezers’ spring constant. At this point, we generally calibrate the spring constant of the optical tweezers using the equipartition method (which requires a calibrated position detector) and the power spectrum method. We check if both methods agree to within ~5–10%. Measuring the tweezers’ spring constant with a free bead provides a baseline to compare the tethered bead measurements as well as gives the user initial information on the trap stiffness. 7. Optional – Run a “stretching” experiment on a free bead. It is sometimes useful to evaluate experimental parameters, such as stretching direction (x or y, or x and y), amplitude, stretching or stage speed, data acquisition sampling rate, etc. A quick check can be done by running an experiment as you would for a tether, but only on a free bead. A “fake” free bead stretching experiment may also provide an indication of the presence of drift. Ideally, mean bead displacement should remain at zero (as there is no tether) during stage motion. Departure from the baseline may be an indication of and illustrate the seriousness of drift (usually, not stage drift as the bead is not physically attached to the coverslip). With these kinds of checks in mind, we have found it useful that the experimenter has access to as much data as possible in real time as it is acquired. This includes stage and bead position as a function of time, but also stage vs. bead position, which gives an uncorrected and crude impression of the force extension and unfolding behavior in the presence of a tether. 3.4.2. Stretching the RNA/ DNA Hybrid

1. Identify a tethered bead. Depending on the properties (contour length, persistence length) of the biomolecule, a tether is harder or easier to recognize. As a rule of thumb, any bead visibly fluctuating due to Brownian motion, but having a limited range of motion and stays more or less in focus, is a good candidate for further exploration. Keep in mind that due to the entropic nature of the biopolymer’s elasticity, the

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bead fluctuations may appear much smaller than you may expect when naively thinking of the biopolymer as a stiff rod. Nonspecifically surface-bound beads usually fluctuate less and usually appear stuck to the surface (but not always!). The existence of a tether, then, may be confirmed by a gentle tug on the bead with the optical tweezers. This may be achieved by either moving the microscope piezo stage or the optical tweezers (by hand or AOD) as one can readily stretch the polymer up to 80% of its contour length without much trouble. A scale bar on your video/computer screen displaying the CCD image of microscopes is useful in this regard. In this step, one may choose to make all displacement using the microscope (piezo) stage, so as not to change any position detector calibrations or spring constant calibrations, which may occur when moving the optical tweezers. On the other hand, as we have discussed in Subheading 3.3, these calibrations can also be repeated in the presence of a tethered bead. 2. Center the anchor point. Once a tether has been identified, one should “center the anchor point.” In other words, one should position the trapped bead and position detection laser focuses directly over the point, where the tether is anchored to the surface (see ref. 5). In a simplified scheme, one moves the piezo stage back and forth [e.g., over a range (
xpz, xpz)] while simultaneously observing the bead displacement vs. stage displacement graph in real time. This graph should appear antisymmetric with respect to the piezo stage null position, x0. One may then change x0 until the graph appears symmetric. It is sometimes useful to invert the bead displacements data in [
xpz, x0] and graph it on the [x0, xpz] axis instead. When the anchor point has been identified, both curves should then overlap. 3. Estimate and set the axial position of the trap with respect to the coverslip. See Subheading 3.4.1. 4. Calibrate the lateral, x and y responses of the position sensor. Calibrations can be done so long the tether remains relatively relaxed as in Subheading 3.4.1. After this point, one may choose to return and repeat steps 2–4 if any abnormal behavior arises or after drift affects the system. 5. Determine the tweezers’ spring constant. If the optical tweezers have been moved, it is advisable to recalibrate the trap’s spring constant. Calibration can be done so long the tether remains relatively relaxed, see Subheadings 3.3 and 3.4. Usually, however, one finds negligible differences. 6. Stretch/unfold the RNA/DNA hybrid. It is useful to record and display stage displacement vs. time and bead displacement vs. time in real time. The bead displacement measurement

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enables determination of the applied force, whereas the difference in bead and stage displacement determines the extension of the molecule. In recording stretching data, one may choose to stretch the molecule repeatedly while making instantaneous measurements of bead displacement, followed by averaging of the acquired stretching curves. This procedure works well when stretching/unfolding is at thermal equilibrium and curves are identical from one stretch to the next as in the case of, e.g., poly(U), poly(A), and poly(C) (23, 24). Alternatively, one may step the stage and reside at the new location for a finite amount of time in order to be able to determine an averaged position of the bead. This procedure is appropriate when stretching curves that are not identical from one run to the next. The choice of the residence time depends upon the spring constant and viscous drag in the system (tether and tweezers), which sets the timescale required to make stochastically uncorrelated measurements of bead position. However, too long residence times and too much averaging may obscure rapid unfolding transitions, so care should be taken. Clearly, one has to experiment with the parameters, such as stage amplitude, stage speed, data acquisition sampling rate, and bead position averaging, to come to settings compatible with the kinetics of the molecular structure being unfolded. For example, one may choose to stretch at high speed, far removed from thermal equilibrium, in order to be able to use nonequilibrium methods for determining the equilibrium free energy changes (25, 26). During lateral stretching, the bead should ideally remain in focus, indicating that axial motion is within the focal depth of the microscope. If this is not the case, the stretching procedure may have been started with the bead too far above the surface. On the other hand, starting too close to the surface may result in the bead running into the surface, which is not always detectable but sometimes yields unexpected stick and slip of the bead, or result in a sudden change of the quadrant photodetector’s sum signal (depending upon optical alignment). In fact, axial motion of the bead may be determined by measuring this sum signal after appropriate calibration (for details, see refs. 5, 14, 19). We omit such detection method-specific procedures here and remain more general, allowing easy adaption of the protocols to other detection methods, such as image particle tracking. It is advised that stretching is interrupted and centering and calibrations repeated in the presence of drift. Upon considering the multiple steps involved in a stretching experiment, control software should allow for easy access (e.g., buttons) to all functions, as well as seamless passing of parameter values (e.g., calibration parameters) between these functions.

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Too much off-line processing impedes direct online evaluation of acquired data. 3.5. Analyzing Stretching Data

3.5.1. Data Treatment/ Corrections

As discussed in Subheading 3.1, stretching RNA in a surface–bead geometry offers the advantage that the experiment is relatively simple, making it ideally suited for testing and exploration before utilizing more elaborate methods. The trade-off is that the data analysis is generally more involved as outlined in the following steps. The procedure has been adapted from Wang et al. (14), who have derived a set of geometric corrections for stretching DNA that yields force and extension in the direction of stretching. Here, we review the calculations in the context of stretching RNA molecules, including specific instructions for analyzing short molecules as well as troubleshooting issues that may arise during computations. For an extensive and detailed discussion, we refer to Wang et al. (14). 1. Collect available data and survey its quality. If calibration parameters are automatically passed on to stretching software routines, the data as saved will contain stage displacement or position (nm), bead displacement (nm), and force (pN). Alternatively (or in addition), one may choose to store position detector voltages, bead position power spectra, and calibration parameters for off-line computation of displacements and forces in units of nm and pN, respectively. Fig. 5 shows an example of stretching and relaxation data of an RNA

Fig. 5. Data as extracted from a stretching experiment: bead position vs. stage position. Each molecule is stretched in both the negative and positive lateral (x) directions, yielding four data sets: two stretching and two relaxation curves.

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pseudoknot, plotting bead displacement vs. stage position. Stretching was back and forth, i.e., performed in both x directions. At this stage, one may make a crude evaluation of the data and decide if it is fit for further analysis. For example, incomplete hybridization and/or surface sticking may result in a multitude of sharp transitions in the curve, physically incompatible with the RNA structure studied. One may further get a first estimate of unfolding force by simply multiplying the bead displacement and the tweezers’ spring constant. Also, a first impression of the extension may be obtained by considering the bead and stage displacement. Too large a stage displacement, exceeding the contour length of the RNA structure studied by a factor of ~2 or so (depending upon bead size, etc.), may point to pathological hybridized handles. Further analysis of such data using the procedure described below may, however, be required to make a firm statement and is advised in case of doubt. 2. Correct data for asymmetry around the anchor point. Centering the trapped bead over the anchoring point as described in Subheading 3.4 is an imperfect process. It is possible to improve centering during data analysis by locating a center of symmetry for the data and reassigning a point of origin. Similar to the procedure developed by Wang (14), the data is fit with an empirically chosen seventh-order polynomial iP ¼7 yðxÞ ¼ ai x i because a parity point can be assigned to an i¼0

odd function. Using the coefficients from the polynomial of best fit, the parity point can be defined as (x0, y0), where: x0 ¼


a6 7a7

and y0 ¼ yðx0 Þ:

The data can then be reassigned using (x0, y0) as a revised origin. 3. Compute extension by using geometric corrections. Our “raw” data as illustrated in Fig. 5 contains two sets of stretching and relaxation obtained by moving the piezo stage symmetrical around the anchoring point (with or without a specific waiting time at the anchoring point). As these data are displayed real time during the experiment, any excessive asymmetry in the bead displacement data serves as an online indicator for drift. For further analysis of these data, individual stretching and relaxation curves are isolated while keeping close track of their time-stamp in the entirety of the stretching experiment for a particular molecule. To compute the force and extension of the RNA/DNA hybrid tether, one needs to take into account the experimental

2 Optical Trapping and Unfolding of RNA

39

Fig. 6. Experimental geometry corrections. (a) The bead is at the trap center with negligible extension (or force acting on) of the biomolecule. (b) The stage has been moved a distance, xstage, and the biomolecule extended. The bead is displaced in both the x and z directions. It is necessary to keep track of lateral and axial bead displacement to make an accurate calculation of the extension of and the tension in the molecule (see Subheading 3.5).

geometry and force in both axial and lateral directions. With a surface–bead geometry, the direction of force on a bead varies with the angle between the tether and the surface as seen in Fig. 6. The final force and extension parameters can be calculated using three steps. (a) Since lateral stage motion results in both lateral and axial motion of the bead in the optical tweezers, the axial motion, zbead, is computed according to: zbead ¼

ztrap   ; ðkz =kx Þ xstage
xbead =xbead þ 1

where kx and kz are the tweezers’ spring constants in the lateral (x or y) and axial (z) directions. kz can either be measured during the calibration (5, 19) or estimated based upon knowledge of kx (kx ~ 6 kz (5, 14)). xbead and xstage are the bead and stage displacements of the bead from the center of trap and are reported in the raw data. ztrap is set at the beginning of the experiment as

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Fig. 7. Force-extension data for the stretching of an RNA pseudoknot before and after geometrical corrections.

described in Subheading 3.4. (b) Calculate the extension of the molecule, Lmol, by: Lmol ¼

z
zbead   trap  
r;
1 sin tan ztrap
zbead xstage
xbead

where r is the bead radius. (c) Compute the force in the direction of stretching, F: F ¼

kx xbead     :
1 cos tan ztrap
zbead xstage
xbead

The effect of the geometric corrections on the force and extension measurements is illustrated by the stretching data shown in Fig. 7. As one can see, the displacement of the bead in the axial direction from the trap may change the extension measurement by 15% or more. A final force-extension curve of the stretching of the Beet Western Yellow Virus pseudoknot is shown in Fig. 8. There is a great deal of additional data analysis that can be performed using these types of data. Recent studies have used the unfolding of RNA structures to elucidate the free energy values of unfolding (12). In addition, much can be learned about the equilibrium behaviors of the process. At low loading rates (such as 2 pN/s), the RNA structure often hops between folded and unfolded states. When stretching is off-equilibrium as indicated by hysteresis (unfolding and refolding occur at significantly different forces), Jarzynski’s Equation and

2 Optical Trapping and Unfolding of RNA

41

Fig. 8. A force-extension curve for the stretching of the Beet Western Yellow Virus pseudoknot, exhibiting transitions where the pseudoknot unfolds near 15 pN.

Crook’s Fluctuation Theorem should be utilized to extract equilibrium parameters (25, 26). This subsequent analysis is specific for the force extension obtained and is beyond the scope of this stretching protocol, which is designed to introduce novices to stretching of individual molecules with a simple, single optical tweezers.

4. Notes 1. Alternatively, one may prepare streptavidin- or neutravidincoated coverslips in-house by incubation of cleaned coverslips with biotinylated BSA followed by incubation with streptavidin or neutravidin. We use purchased slides for consistency and convenience. 2. The small volume will most likely have condensed on the lid of the Eppendorf tube. Tap the Eppendorf tube firmly on a lab bench a few times before opening to add the RNA construct. 3. We find that the second prepared tube provides an environment that is free of unbound anti-dig fragments. Also, the BSA coating the sides from nonspecific sticking has not been compromised by the centrifugation process. 4. The 5:1 ratio yields a sufficient, but not large, number of surface tethers that generally do not form multiple tethers to the surface. Multiply tethered beads may be recognized in a stretching experiment as they tend to display too many

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unfolding events, require more force to stretch, and have too small of an apparent persistence length. 5. Getting the right amount of glue on this region of the flow cell requires some practice. Too little glue creates crevices for the aqueous buffer to leak from. Too much glue migrates into the center of the flow cell when the coverslip is added, perhaps meeting in the center of the chamber and sealing up the chamber completely rendering it useless. 6. The relatively long incubation times used under dry conditions may lead to evaporation, which is prevented by placing the sample in a “humidity chamber” (a closed Petri dish with a wet piece of filter paper or KimWipe inside). 7. Molecules with a much smaller persistence length than doublestranded DNA, e.g., single-stranded RNA (Lp ~ 1 nm), take more force to stretch to the same relative extension. For this reason, the allowable calibration range may be smaller than 200 nm. One has to compute the force expected – e.g., using a worm-like chain model – to assure that the bead does not move away from the optical tweezers’ center during the calibration. The same type of argument also applies to the spring constant calibration. 8. Excessive drift, however, may be due to the use of either too little or too much oil when using oil-immersion microscope objectives and condensers. Gentle clamping down of the specimen also may help to minimize drift. References 1. Wen, J., Lancaster, L., Hodges, C., Zeri, A., Yoshimura, S.H., Noller, H.R., Bustamante, C., and Tinoco, I. (2008) Following translation by single ribosomes one codon at a time Nature 452, 598–603. 2. Zhuang, X., Kim, H., Pereira, M.J.B., Babcock, H.P., Walter, N.G., and Chu, S. (2002) Correlating structural dynamics and function in single ribozyme molecules Science 24, 1473–1476. 3. Moerner, W.E., and Fromm, D.P. (2003) Methods of single-molecule fluorescence spectroscopy and microscopy Rev. Sci. Instrum. 74, 3597–3619. 4. Zlatanova, J., Lindsay, S.M., and Leuba, S.H. (2000) Single molecule force spectroscopy in biology using the atomic force microscope Prog. in Biophy. and Mol. Bio. 74, 37–61. 5. Neuman, K.C. and Block, S.M. (2004) Optical trapping Review of Scientific Instruments 75, 2787–2809.

6. Tinoco, Jr., I., Li, P.T.X., and Bustamante, C. (2006) Determination of thermodynamics and kinetics of RNA reactions by force Quart. Rev. Biophys. 39, 325–360. 7. Hansen, T.M., Reihani, S.N.S., Oddershede, L.B., and Sorensen, M.A. (2007) Correlation between mechanical strength of messenger RNA pseudoknots and ribosomal frameshifting Natl. Acad. Sci. U.S.A. 104, 5830–5835. 8. Giedroc, D.P. and Cornish, P.V. (2009) Frameshifting RNA pseudoknots: Structure and mechanism Vir. Res. 139, 193–208. 9. Cao, S. and Chen, S-J. (2008) Predicting ribosomal frameshifting efficiency Phys. Biol. 5, 68136–68139. 10. Plant, E.P., Jakobs, K.L., Harger, J.W., Meskauskas, A., Jacobs, J.L., Baxter, J.L., Pet˚ rov, A.N., and Dinman, J.D. (2003) The 9 A solution: how mRNA pseudoknots promote efficient programmed
1 frameshifting RNA 9, 168–174.

2 Optical Trapping and Unfolding of RNA 11. Butkus, M.E., Prundeanu, L.B., and Oliver, D.B. (2003) Translocon “pulling” of nascent SecM controls the duration of its translational pause and secretion-responsive secA regulation J. Bact. 185, 6719–6722. 12. Liphardt, J., Dumont, S., Smith, S.B., Tinoco, Jr., I., and Bustamante, C. (2002) Nonequilibrium measurements in an experimental test of Jarzynski’s Equality Science 202, 1832–1835. 13. Perkins, T.T., Smith, D.E., Larson, R.G., and Chu, S. (1995) Stretching of a single tethered polymer in a uniform flow Science 268, 83–87. 14. Wang, M.D., Yin, H., Landick, R., Gelles, J., and Block, S.M. (1997) Stretching DNA with optical tweezers Biophysical Journal 72, 1335–1346. 15. Deufel, C., and Wang, M.D. (2006) Detection of forces and displacements along the axial direction in an optical trap Biophysical Journal 90, 657–67. 16. Nugent-Glandorf, L., and Perkins, T.T. (2004) Measuring 0.1-nm motion in 1 ms in an optical microscope with differential backfocal-plane detection Opt Lett 29, 2611–3. 17. Moffitt, J.R., Chemla, Y.R., Izhaky, D., and Bustamante, C. (2006) Differential detection of dual traps improves the spatial resolution of optical tweezers PNAS 103, 9006–9011. 18. Gittes, F., and Schmidt, C.F. (1998) Interference model for back-focal-plan displacement detection in optical tweezers Opt Lett 23, 7–9.

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19. Rohrback, A., Kress, H., and Stelzer, E.H.K. (2003) Three-dimensional tracking of small spheres in focused laser beams: influence of the detection angular aperture Opt Lett 28, 411–413. 20. Sun, Y., Luo, Z., and An, K. (2001) Stretching short biopolymers using optical tweezers Biochem and Biophys Res Comm 286, 826–830. 21. Visscher, K., Gross, S.P., and Block, S.M. (1996) Construction of multiple-beam optical traps with nanometer-resolution position sensing IEEE JOURNAL 2, 1066–1076. 22. Liphardt, J., Onoa, B., Smith, S.B., Tinoco, I. Jr., and Bustamante, C. (2001) Reversible unfolding of single RNA molecules by mechanical force Science 292, 733–737. 23. Seol, Y., Skinner, G.M., and Visscher, K. (2004) Elastic properties of single-stranded charged homopolymeric ribonucleotide Phys Rev Lett 93, 118102–118105. 24. Seol, Y., Skinner, G.M., and Visscher, K. (2007) Stretching of homopolymeric RNA reveals single-stranded helices and basestacking Phys Rev Lett 98, 158103–158106. 25. Crooks, G.E. (1999) Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences Phys Rev E 60, 2721–2726. 26. Jarzynski, C. (1997) Nonequilibrium equality for free energy differences Phys. Rev. Letters 78, 2690–2693.

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Chapter 3 DNA Unzipping and Force Measurements with a Dual Optical Trap Ismaı¨l Cisse´, Pierre Mangeol, and Ulrich Bockelmann Abstract In order to open the DNA double helix mechanically, a molecular construction is prepared which allows specific attachment of the two complementary strands of an individual molecule to two different mm-sized beads. The beads are separately captured by a dual optical trap, thus holding the DNA construction in solution. The opening of a molecule is obtained by increasing the distance between the traps, one trap being slowly moved while the other is held fixed. Force is measured to sub-piconewton precision by back focal plane interferometry of the bead in the fixed trap. The experiment allows us to measure base sequence-dependent force signal. In this chapter, important technical aspects of this type of singlemolecule force measurements are considered. Key words: DNA, Single molecule, Optical trap, Force, Unzipping, Base pair, Sequence, Molecular construction

1. Introduction The field of single-molecule force measurements on nucleic acids started more than 15 years ago. It has thrived ever since and has been covered by a number of reviews (1–4). The most noteworthy feature common to all single-molecule techniques is the absence of ensemble averaging. This aspect is particularly highlighted in DNA unzipping measurements, where base sequence-dependent force signals are observed (5–9). The double optical tweezers configuration, which can achieve very accurate and low drift measurements, enables the reproducible observation of sequence features on a single molecule. Let us briefly consider possible applications of unzipping experiments. First, unzipping experiments could be used to obtain sequence information of unknown single DNA molecules. Recently, theoreticians started to work on approaches to predict the most probable base sequence from force versus extension Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_3, # Springer Science+Business Media, LLC 2011

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curves (10, 11). Second, unzipping experiments can be used to investigate DNA/protein interactions (12–14). Third, the technique can also be applied to unzip RNA molecules. In this case, the force curves provide information about sequence and structure, and in particular about dynamical aspects that are difficult to obtain by other approaches (15–18). Fourth, a very promising prospect is single-molecule studies of RNA/protein interactions, including the action of RNA helicases or polymerases (19–21). Successful unzipping experiments require many different elements to be tuned carefully for optimal results. These preparations are the very essential condition to record high-quality force signals. There are many possible reasons for failure; some of them are listed in the Notes section. The chapter provides protocols and notes on the setup of a dual optical trap, the preparation of the molecular constructions, and an example of a single-molecule DNA unzipping measurement. Other important technical points, not addressed in detail here, include the preparation and surface functionalization of the beads, the force calibration of the setup, and the details of data acquisition and analysis.

2. Materials 2.1. Dual Optical Trap

1. Trapping laser: CW, linearly polarized, diode-pumped, Nd: YVO4 laser, emitting at 1,064 mm with a maximum power of 10 W (Millenia IR, Spectra-Physics, Mountain View, CA, USA). 2. Trapping objective: 100
, N.A. ¼ 1.4, oil immersion, Plan Apo IR (Nikon, Tokyo, Japan). 3. Condenser objective: 60
, N.A. ¼ 1.2, water immersion, UPlanSApo (Olympus, Tokyo, Japan). 4. Beam steering: piezoelectric mirror mount with an integrated position sensor operating in a feedback loop (Mad City Labs Inc., Madison, WI, USA). 5. Acousto-optic frequency shifter (AA Optoelectronic, Orsay, France). 6. Position-sensitive detector (Pacific Silicon Sensor, Westlake Village, CA, USA).

2.2. Molecular Construction

1. Lambda DNA digested by Hind III (Promega). 2. Oligonucleotides (Eurogentec): Right Primer [Phos]50 CAGTGGACGCCAGAAAATTAAG30 Left Primer [Dig]50 GGGTTTTGCTATCACGTTGTG30 Oligo 1 [Phos]50 CAAGGCGTTCCC30 Oligo 2 [Biot] 50 CTAACGATTAAAAAAAGATGCTGTAAC30

3 DNA Unzipping and Force Measurements with a Dual Optical Trap

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Oligo 3 [Phos]50 TCGGGTTACAGCATCAGGGAACGC30 Hairpin [Phos]50 GCACAGGCGACTTCGAAAACGAAGTCGCCT30 3. GoTaq polymerase and GoTaq Flexi Buffer 5
(Promega). 4. MgCl2 25 mM solution (supplemented with GoTaq polymerase) (Promega). 5. dNTP mix 10 mM (each NTP) (Promega). 6. Restriction enzymes: Sty I, Ava I, and Ban I (New England Biolabs). 7. Restriction enzyme buffers: NEB buffer 4 (for Ava I and Ban I) and NEB buffer 3 (for Sty I) (New England Biolabs). 8. BSA 100
(supplemented with Sty I) (New England Biolabs). 9. T4 DNA ligase and T4 DNA ligase 10
buffer (New England Biolabs). 10. rATP 100 mM (Promega). 11. Purification kits: Promega Wizard SV Gel and PCR Clean-up system (Promega) and Chroma Spin TE 1000 (Clontech). 12. Agarose and Bionic buffer (Sigma). 13. Digestion buffer: 50 mM Tris–HCl, 100 mM NaCl, 10 mM MgCl2, 1 mM dithiothreitol, and 100 mg/mL BSA. 14. Ligation buffer: 50 mM Tris–HCl 10 mM MgCl2, 1 mM ATP, and 10 mM dithiothreitol. 15. Double digestion buffer: 20 mM Tris acetate , 50 mM potassium acetate, 10 mM magnesium acetate, and 1 mM dithiothreitol.

3. Methods 3.1. The Dual Optical Trap Setup

Our setup is presented schematically in Fig. 1. It is based on a custom-designed inverted microscope. The optical components are mounted on an optical table for vibration isolation. For trapping and force detection, we use a diode-pumped near-infrared laser. To create two independent traps, a polarizing cube C1 splits the laser beam by polarization. A half-wave plate allows us to adjust the distribution of the laser intensity on the two polarizations. The direction of one of the two beams is varied by a piezoelectric mirror mount. As explained in Note 1, its frequency is shifted with an acousto-optic modulator (“frequency shifter”) to eliminate the interference taking place between the two beams on the detection plane (22) (see Note 1). After recombination with a second polarizing cube C2, the two beams exhibit perpendicular polarization, and their directions of propagation are slightly

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Fig. 1. Schematic layout of the dual optical trap setup. The trapping beams are indicated in dark gray and the illumination light in light gray. The optical components are described in the text.

different, in order to create two laterally separated traps in the sample. To this end, lenses L3 and L4 image the center of the mirror mounted on the piezoelectric stage on the back focal plane of the trapping objective. The beams are focused by the trapping objective, pass through the sample, and are then collimated by the condensor objective (see Note 3). One of the two beams is removed with a Glan-laser polarizer. Finally, lens L5 images the back focal plane of the condensor objective on a position-sensitive detector. Part of the optical path is also used to image the beads on a CCD camera.

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Fig. 2. Generic molecular construct suitable for DNA unzipping experiments.

To avoid fluctuations from air currents, the optical path is fully enclosed. Most mechanical parts are custom designed to reduce drifts and vibrations. 3.2. Preparation of the Molecular Construction

A typical molecular construction for unzipping measurements is shown schematically in Fig. 2. It usually contains the following parts:

3.2.1. Main Elements

l

Two linker arms. Together the two spacers should be long enough to make handling during measurements easier. On the contrary, shorter spacers are preferred in order to achieve higher stiffness and in turn higher sensitivity of the force signal to the base sequence. In the following experiments, one linker arm carries a biotin, the other one a digoxigenin modification. At least one of them is a long double-stranded DNA fragment; typically obtained by PCR and at least 1,000 base pairs in length. The other linker is either a long double strand or a short single strand.

l

The double-stranded molecule to be opened.

l

A set of “opening” oligonucleotides. These oligos are used to join specifically the linker arms and the double-stranded molecule to be opened.

l

A “hairpin” oligonucleotide. This oligo is ligated to the end of the molecule to be opened, in order to allow unzipping of the entire construction without separation of the strands.

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3.2.2. Preparation of the Linker Arms

Oligonucleotide sequences can be found in Subheading 2.2 (see Note 4). 1. PCR setup: PCR amplification of a 3,186-base pair fragment (about 1 mm) was performed by adding 5 ng of Lambda Hind III digest to 25 mL PCR mix containing 5 mL GoTaq Flexi buffer 5
, 2.5 mM MgCl2, 2 pmol of right primer and left primer, 200 mM dNTP (each), and 1.9 U of GoTaq polymerase. The reaction was placed in a thermal cycler at 95 C for 2 min, and then cycled 30 times between 95 C for 30 s, 54.3 C for 30 s, and 72 C for 2 min and finally held for 5 min at 72 C. A 0.8% agarose gel in Bionic buffer was run to check the PCR product (see Note 5). The product was purified using Wizard SV Gel and PCR Clean-up system. 2. Sty I digestion: Restriction of the PCR fragment was performed by adding 3 mg of purified PCR fragment to 30 mL of digestion buffer and 30 U of Sty I enzyme. The reaction was incubated at 37 C for 3 h. A 0.8% agarose gel in Bionic buffer was run to check that no anomalous cutting occurred (see Note 5). 3. Purification: The restriction product is purified using Wizard SV Gel and PCR Clean-up system (see Note 6). 4. Ligation of the opening oligonucleotides: A 50 mL mixture containing ligation buffer and 15 pmol of both oligo 1 and oligo 3, and 0.5 pmol of restriction product is incubated for hybridization (65 C for 5 min, 45 C for 15 min, 40 C for 15 min, 35 C for 40 min, 30 C for 40 min, 25 C for 30 min, 20 C for 30 min, and 16 C for 5 min). Once at 16 C, 1,600 units of T4 DNA ligase and 0.5 mL of rATP at 100 mM are added to the reaction. The reaction is incubated at 16 C for a minimum of 2 h. Finally, the reaction is incubated at 65 C for 20 min to heat inactivate the enzyme. 5. Purification: The ligation product is purified using Wizard SV Gel and PCR Clean-up system (see Fig. 3). After the purification, there are still unreacted products that cannot be eliminated because of their size being too similar to that of the linker arm. Since these unreacted products are digoxigenin labeled, they can fix on the anti-digoxigenin-coated beads that are used for measurements (see Note 6).

3.2.3. Preparation of the Molecule to be Opened

1. Double digestion: We use a purified DNA fragment exhibiting a length of about 500 base pairs and containing the two restriction sites AvaI and BanI. The 50 mL double digestion mixture contains 0.7 pmol of the fragment DNA, double digestion buffer, 30 U Ava I, and 60 U Ban I enzymes. The mixture is incubated at 37 C for 3 h. Then the reaction mixture is purified using Wizard SV Gel and PCR Clean-up system.

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Fig. 3. Preparation of the linker arm.

A 1.5% agarose gel in Bionic buffer is run to check that the restriction is effective (see Note 5). 2. Ligation of the hairpin: A 50 mL mixture containing 50 mM Tris–HCl, 10 mM MgCl2, 1 mM ATP, 10 mM dithiothreitol, 10 pmol of hairpin, and 0.3 pmol of double restriction product is incubated for hybridization (65 C for 5 min, 45 C for 15 min, 40 C for 15 min, 35 C for 40 min, 30 C for 40 min, 25 C for 30 min, 20 C for 30 min, and 16 C for 5 min). Once at 16 C, 1,600 units of T4 DNA ligase and 0.5 mL of rATP at 100 mM are added to the reaction. The reaction is incubated at 16 C for a minimum of 2 h. Finally, the reaction is incubated at 65 C for 20 min to heat inactivate the enzyme. 3. Purification: The ligation product is purified using Wizard SV Gel and PCR Clean-up system. After the purification, there are still unreacted products that cannot be eliminated because of their size being too close to that of the molecule to be opened. However, they will be eliminated during the final

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Fig. 4. Preparation of the molecule to be unzipped.

purification occurring in Subheading 2.4 (see Note 6). The resulting molecule is depicted in Fig. 4. 3.2.4. Final Ligation and Purification

1. Final ligation: The 50 mL reaction mix containing 0.3 pmol of molecule to be opened, 0.2 pmol of linker arm, 20 pmol of oligo 2, and ligation buffer is incubated for hybridization (65 C for 5 min, 45 C for 15 min, 40 C for 15 min, 35 C for 40 min, 30 C for 40 min, 25 C for 30 min, 20 C for 30 min, and 16 C for 5 min). Once at 16 C, 1,600 units of T4 DNA ligase and 0.5 mL of rATP at 100 mM are added to the reaction. The reaction is incubated at 16 C for a minimum of 4 h. Finally, the reaction is incubated at 65 C for 20 min to heat inactivate the enzyme. 2. Purification: The reaction mix is purified using Chroma Spin TE 1000. In the end, there are still unwanted products such as the one pictured in Fig. 5 (see Note 6).

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Fig. 5. Final ligation and purification.

3.3. Example of an Unzipping Force Measurement 3.3.1. Preparing an Unzipping Experiment

1. First and foremost, prepare the DNA–bead complex. We use 1.87-mm streptavidin-coated polystyrene beads, 0.97-mm anti-digoxigenin-coated silica beads, and a 10–100 times dilution of the molecular construction. A mixture containing 1 ml of each type of beads is added to 1 ml of the molecular construction dilution, and then incubated at 25 C for 3 h. 2. Then add 18 mL of buffer to the mixture. We usually use phosphate buffer or phosphate buffer saline 1
. 3. Prepare the sample cell, which is basically made of a 24
60 mm microscope coverslip on top of which a 22
22 mm coverslip is glued with Parafilm (see Fig. 6). 4. Gently inject the DNA-bead solution through the channel by capillarity (if the injection is too rough, the DNA–beads complex might break). 5. Seal the cell with wax to avoid any evaporation. 6. Switch on the laser and acousto-optic modulator 1 h before the measurements to reach thermal equilibrium (see Note 3). The laser should go through the objectives during this period. 7. Place the sample in the microscope.

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Fig. 6. Preparation of a sample cell. (a) Two coverslips are glued together using Parafilm. (b) The solution containing the DNA–bead complex is gently injected into the cell by capillarity. (c) The cell is sealed to avoid evaporation of the solution.

8. Check that the beam is proper for detection use, i.e., the image of the beam on the position-sensitive detector should not be clipped or spattered. 3.3.2. Sequence of a Typical Unzipping Experiment

1. Search for the appropriate bead duplexes, i.e., in our experiments, a big bead in the vicinity of a small bead. The typical distance between the two beads is 1 mm. Such duplexes are likely to be linked by a DNA molecule and so to be opened. 2. Initially, separate the two traps (about 1.5 mm for the 1.87- and 0.97-mm beads) so that you can trap each bead in a different trap. 3. Trap one bead in each trap. 4. Move the objective to focus the laser in the sample at about 5 mm above the glass–water interface. 5. Using the piezoelectric stage, pull apart the two traps at a displacement velocity between 5 and 500 nm/s. 6. Monitor the force extension curves in real time and assure that during the cycle no free beads enter one of the traps; otherwise, the force measurement will be erroneous.

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Fig. 7. Typical DNA unzipping measurement curve.

7. Finally, stretch the molecule until it breaks and calibrate the force measurement. For instance, a power spectrum can be recorded and analyzed in order to determine the trap stiffness and the conversion factor between the force and the output voltage of the position-sensitive detector electronics. 3.3.3. Example of a Force Versus Extension Curve

A typical force extension curve is shown in Fig. 7. First, the curve exhibits an initial flat region at low force, corresponding to a relaxed DNA molecule. Then the force increases due to the stretching of the linker arm. It corresponds to the elastic response of a double-stranded DNA. Next, one can see a quasi-plateau with rapid variations in force between 14 and 18 pN. This region corresponds to the opening of the molecule, i.e., the mechanical denaturation of the doublestranded DNA. Afterward, one can see a sudden drop in force which is due to the complete unzipping of the construction, in the present case induced by a full opening of a DNA construction without incorporated hairpin. Finally, we again measure a flat region at zero force; the two beads are apart with no molecule in between.

4. Notes 1. Interference and cross talk. The two beams used in the dual optical trap are of perpendicular polarization before entering the trapping objective. The purpose of the perpendicular polarization is to avoid interference of the two beams to allow detection and force measurement on only one trap (typically, the fixed one).

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29 28 27 26 25 24 23 0

50

100

150

200

Time (min) Fig. 8. Force measurements with two 0.97-mm silica beads without DNA trapped with the frequency shifter on (bottom: kf ¼ 213 pN/mm and P ¼ 910 mW) and off (top: kf ¼ 192 pN/mm and P ¼ 800 mW). The displacement velocity between the two beads is 1 mm/s, and sampling is done at 800 Hz with an anti-aliasing filter of 352 Hz. The signal measured without the frequency shifter on is shifted vertically for better visualization.

Unfortunately, as known from polarization microscopy, the polarization of light is not fully conserved when going through conventional microscope objectives (23, 24). The separation of the two beams before detection is, therefore, never complete and an important problem appears: the beams interfere and create a parasitic signal when measuring force, especially at high laser power and small distance between the traps (Fig. 8). However, a solution for this problem is accessible. One can shift the frequency of one of the two beams with an acousto-optic modulator at a few tens of MHz (22). The beams still interfere, but the interference pattern moves so fast that the electronics does not detect it, due to low-pass filtering. The effect of interference can thus be totally eliminated (Fig. 8). A fraction of light coming from the nondesired beam is still present, but it is usually small enough to be neglected (about 2% of the total force signal in our case). 2. Regulation of the relative height of the two beads. The use of an acousto-optic modulator on the path of one of the beams or trapping two different types of beads in the two traps may lead to an undesirable consequence: the two beads may not be trapped in the same plane. A good estimation of the distance between the two beads along the axis of beam propagation (z) can be achieved if the

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57

5

Force (pN)

4

3

2

1

0 2

4

6

8

10

Fig. 9. Force measurement on two different trapped beads on the z direction while oscillating the coverslip height. When a bead touches the coverslip, the force increases quickly. Top curve, measurement for a 1.87-mm polystyrene bead, bottom curve, measurement for a 0.97-mm silica bead.

setup has a piezoelectric translator in this direction and two photodiodes to measure the force acting on the beads in the z direction (as the total light received on the detector using the back focal plane method is proportional to this force). By oscillating the position of the translator, one can reach positions where the beads touch the coverslip and determine these positions by measuring the force acting on the bead in the z direction, as when a bead touches the coverslip, the force in z direction increases quickly. An example of this measurement is shown in Fig. 9. If the distance between the two beads is not the desired one, a telescope can be added in the path of one of the beam to adjust its diameter and change the relative height of the bead trapped by this beam. One should remind that these measurements are done close to the surface. If the experiment is carried out far away from the surface, specific calibrations have to be done. In our case, this adjustment is still correct up to 5 mm. 3. Thermal drift. The trapping laser is usually chosen so that it does not significantly damage and warm up too much samples and biological molecules; near-infrared lasers can solve this issue properly. However, the light power is usually high enough to induce an unavoidable rise in temperature. Local heating close to a trapped particle has been reported previously and modeled with success (25).

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Fig. 10. Temperature measurement on the trapping objective tip (gray crosses) and exponential fits for temperature increasing and decreasing (dashed curves). The trapping laser is switched on at time t ¼ 0 min and switched off at t ¼ 125 min.

We focus here on heating of the trapping objective. Even if this heating is the most obvious one, it has not been reported in the literature. It is important to know to which extent an objective is heated: first, because it will expand and produce mechanical drift and second, because since the immersion objective is in thermal contact to the sample, it can heat the latter. Knowing the real temperature of a sample is crucial for trap calibration and for temperature-dependent biological processes that are studied with optical tweezers. We measured the temperature of the tip of the trapping objective with a thermocouple (Fig. 10). Initially, the objective was at room temperature and we started the measurement when the laser started to go through the objective. After 125 min, we switched off the laser and let the objective cool down. We found that both heating and cooling can be properly fitted by simple exponential laws (DT et/t) with a typical time t of about 20 min and a change in temperature DT of about 6.5 C. The important consequences of this measurement are the following: l

Temperature variations induce mechanical drifts that can expand objectives and translate the position of the focal point by about 10 mm.

3 DNA Unzipping and Force Measurements with a Dual Optical Trap

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l

Before starting an experiment, the laser has to go through the trapping objective for an hour at least. It should be avoided to switch off the laser for more than 5 min.

l

In steady state, the sample temperature can be several degrees above the ambient temperature.

4. Controlling oligonucleotide sequences. One should carefully check the oligonucleotide sequences ordered since the slightest mistake might harm the whole process. For instance, a single nucleotide mistake on a restriction site will prevent the restriction enzyme from cutting the DNA fragment. One should also check if the ordered sequence and the one written on the supplier’s datasheet are the same, since typing errors happen. Ordering polyacrylamide gel electrophoresis (PAGE)-purified oligonucleotides can be useful to avoid length issues; indeed, polyacrylamide gels are very sensitive to length (up to one base difference can be detected). Roughly checking the length of the oligonucelotides by a simple agarose gel can also be useful. Finally, synthesis errors may occur, but in that case only sequencing will help detecting if what is written on the datasheet and what you have in your tube are the same. It is advised to check the functionalization of the oligonucleotides by a gel shifting method. For force measurements, we use biotin-and digoxigenin-labeled DNA; a good test is to run a gel with, on one hand, the native oligonucleotides and on the other hand, with oligonucleotides incubated with streptavidin and antidigoxigenin, respectively. As shown in Fig. 11a, there is a clear difference in migration between the native oligonucleotides and the oligonucleotides incubated with streptavidin and anti-digoxigenin. Oligonucleotides that are to be used for ligation should either be modified to have a 50 -phosphate or treated with kinase, otherwise ligation will not be performed. 5. Implement intermediate tests. While designing the construct, one should foresee intermediate tests to check that each enzymatic reaction occurred the right way. For example, while digesting a DNA fragment, one should be able to run a control agarose gel to be sure that the fragments have the right size after the reaction and that the digestion is complete. For instance, in Fig. 11b, one can see that the restriction was successfully performed since there is a clear shift between the original fragment and the one digested. 6. Purification. It is mandatory to think carefully about the purification processes occurring throughout the different steps and check for the availability of DNA purification procedures with the appropriate cutoff. The right procedure should give a solution containing only the molecular construct to be unzipped;

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Fig. 11. (a) Example of a gel shift test on a 1.5% agarose gel in Bionic buffer. From left to right: a digoxigenin-functionalized 21 mer, the same 21 mer incubated with antidigoxigenin, a biotinylated 34 mer, the same 34 mer incubated with streptavidin. (b) 1.5% agarose gel in Bionic buffer. Double digestion of a DNA fragment with Ava I and Ban I. From left to the right: DNA fragment, DNA fragment digested with Ava I and Ban I, and 100-bp DNA ladder (NEB).

however, in the end, we still have long DNA fragments that we cannot get rid of. Purifying the final construction by excising the corresponding band from an electrophoresis gel might be thought of; however, such a process can cause some loss of material and some deterioration of the DNA (during such a purification, the gel is usually illuminated with UV light, which is known to induce nicks). References 1. Bustamante C., Bryant Z., Smith S. (2003) Ten years of tension: single molecule DNA mechanics. Nature 421, 423–427. 2. Allemand J. F., Bensimon D., Croquette V. (2003) Stretching DNA and RNA to probe

their interactions with proteins. Curr Opin Struct Biol 13, 266–274. 3. Bockelmann U. (2004) Single-molecule manipulation of nucleic acids. Curr Opin Struct Biol 14, 368–373.

3 DNA Unzipping and Force Measurements with a Dual Optical Trap 4. Neuman K. C. and Block S. M. (2004) Optical trapping. Rev. Sci. Instrum. 75, 2787–2809. 5. Essevaz-Roulet B., Bockelmann U. and Heslot F. (1997) Mechanical separation of the complementary strands of DNA. Proc Natl Acad Sci USA 94, 11935–11940. 6. Bockelmann U., Essevaz-Roulet B. and Heslot F. (1997) Molecular stick-slip motion revealed by opening DNA with piconewton forces. Phys Rev Lett 79, 4489–4492. 7. Rief M., Clausen-Schaumann H. and Gaub H. E. (1999) Sequence dependent mechanics of single DNA molecules. Nat Struct Biol 6, 346–349. 8. Bockelmann U., Thomen P., Essevaz-Roulet B., Viasnoff V. and Heslot F. (2002) Unzipping DNA with optical tweezers: high sequence sensitivity and force flips. Biophys J 82, 1537–1553. 9. Danilowicz C., Coljee V. W., Bouzigues C., Lubensky D. K., Nelson D.R. and Prentiss M. (2003) DNA unzipped under a constant force exhibits multiple metastable intermediates. Proc Natl Acad Sci USA 100, 1694–1699. 10. Baldazzi V., Cocco S., Marinari E. and Monasson R. (2006) On the inference of DNA sequences from mechanical unzipping experiments. Phys. Rev. Lett. 96, 128102. 11. Baldazzi V., Bradde S., Cocco S., Marinari E. and Monasson R. (2007) Inferring DNA sequences from mechanical unzipping data: the large-bandwidth case. Phys. Rev. E 75, 011904. 12. Koch S. J., Shundrovsky A., Jantzen B. C., Wang MD (2002) Probing protein-DNA interactions by unzipping a single DNA double helix. Biophys J 83, 1098–1105. 13. Koch S. J., Wang M. D. (2003) Dynamic force spectroscopy of protein-DNA interactions by unzipping DNA. Phys Rev Lett 91, 28103. 14. Bockelmann U., Thomen P. and Heslot F. (2004) Dynamics of the DNA duplex formation studied by single molecule force measurements. Biophys J 87, 3388. 15. Liphardt J., Onoa B., Smith S.B., Tinoco I. Jr. and Bustamante C. (2001) Reversible unfolding of single RNA molecules by mechanical force. Science 292, 733–737.

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16. Onoa B., Dumont S., Liphardt J., Smith SB, Tinoco I. Jr. and Bustamante C. (2003) Identifying the kinetic barriers to mechanical unfolding of the T. thermophila ribozyme Science 299, 1892–1895. 17. Mangeol P., Coˆte D., Bizebard T., Legrand O. and Bockelmann U. (2006) Probing DNA and RNA single molecules with a double optical tweezer. Eur. Phys. J. 19, 311. 18. William J, Greenleaf WJ, Frieda KL, Foster DAN, Woodside MT, Block SM. (2008) Direct observation of hierarchical folding in single riboswitch aptamers. Science 319, 630–633. 19. Dumont S., Cheng W., Serebrov V., Beran R. K., Tinoco I. Jr., Pyle A. M. and Bustamante C. (2006) RNA translocation and unwinding mechanism of HCV NS3 helicase and its coordination by ATP. Nature 439, 105–108. 20. Cheng W., Dumont S., Tinoco I. Jr. and Bustamante C. (2007) NS3 helicase actively separates RNA strands and senses sequence barriers ahead of the opening fork. Proc. Nat. Acad. Sci. 104, 13954–13959. 21. William J. Greenleaf W. J., Frieda K. L., Foster D. A. N., Woodside M. T., Block S. M. (2006) Single-molecule, motion-based DNA sequencing using RNA polymerase. Science 313, 801. 22. Mangeol P. and Bockelmann U. (2008) Interference and crosstalk in double optical tweezers using a single laser source. Rev. Sci. Inst. 79, 083103. 23. Inoue´ S. (1952) Studies on depolarization of light at microscope lens surfaces I. The origin of stray light by rotation at the lens surfaces. Exp. Cell Res. 3, 199–208. 24. Inoue´ S. and Hyde W. L. (1957) Studies on depolarization of light at microscope lens surfaces II. The simultaneous realization of high resolution and high sensitivity with the polarizing microscope. J. Biophys. Biochem. Cytol. 3, 831–838. 25. Peterman E. J. G., Gittes F. and Schmidt, C. F. (2003) Laser-induced heating in optical traps. Biophys. J. 84, 1308–1316.

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Chapter 4 Probing the Force Generation and Stepping Behavior of Cytoplasmic Dynein Arne Gennerich and Samara L. Reck-Peterson Abstract Cytoplasmic dynein, which is the largest and arguably the most complex cytoskeletal motor protein, plays fundamental roles during cell division, nuclear positioning, and organelle and mRNA transport, by generating force and movement toward the minus ends of microtubules. Consequently, dynein is central to many physiological processes, and its dysfunction is implicated in human diseases. However, the molecular mechanism by which dynein produces force and movement remains poorly understood. Here, we describe the use of optical tweezers to probe the nanometer-scale motion and force generation of individual dynein molecules, and provide a hands-on protocol for how to purify cytoplasmic dynein from budding yeast in amounts sufficient for single-molecule studies. Key words: Optical tweezers, Optical trapping, Single-molecule assays, Molecular motors, Cytoplasmic dynein, Saccharomyces cerevisiae, Budding yeast, Microtubules

1. Introduction Despite the increasingly well-characterized in vivo functions of cytoplasmic dynein (1–3), our knowledge of dynein’s molecular mechanism is just emerging. A structural and mechanistic model for cytoplasmic dynein is still missing, owing largely to the lack of atomic-resolution structures and the unavailability (until recently) of recombinant dynein capable of processive movement (the ability to take multiple steps) along microtubules (MTs). However, recent single-molecule experiments with purified brain dynein and the generation and characterization of the first recombinant processive dynein have begun to shed light on dynein’s molecular mechanism (4–9). In addition, the X-ray structure of dynein’s MT-binding domain was recently solved, providing the first structural insights into how dynein binds to its track (10). Since its application to study individual kinesin (11) and myosin (12) motor proteins, optical trapping microscopy has become an Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_4, # Springer Science+Business Media, LLC 2011

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established and valuable technique in the cytoskeletal motor field for probing the mechanochemistry of force-generating single motors. Optical tweezers can be used to trap and hold a motorcoated polystyrene bead using a near-infrared laser beam that is tightly focused into a diffraction-limited focal volume by an objective lens of high numerical aperture. The bead position can then be tracked with nanometer precision using a quadrant photodiode (QPD) detector or position-sensitive detector (PSD). Once the trapped bead is displaced from the trap center by a molecular motor, a restoring force acts to pull the bead back toward the center of the trap (analogous to the restoring force of a Hookean spring). Modern designs allow the trap to be operated in either a “nonfeedback” mode with a fixed trap position, or in a “force-feedback” mode in which the force exerted on the bead is kept constant by maintaining a fixed bead-trap separation using a computercontrolled trap or stage positioning. The nonfeedback mode is commonly used to measure piconewton forces that single cytoskeletal motors generate, by observing motor stepping under increasing opposing loads until movement slows and eventually ceases. The force-feedback mode allows precise measurement of nanometer-scale motor stepping along MTs as a function of constant opposing or assisting forces (8, 13, 14). Below, we describe the use of an optical tweezers setup to study the force production and force-dependent stepping behavior of individual dynein molecules. We also provide detailed protocols for the use of Saccharomyces cerevisiae as a model system to generate recombinant dynein molecules, enabling hypothesis-driven structure–function studies.

2. Materials 2.1. Yeast Growth

1. YPD plates: 10 g Bacto yeast extract, 20 g Bacto peptone, 20 g dextrose, and 20 g agar per 1 L double distilled (dd) H2O. Autoclave in a 2-L flask for 30 min. Pour plates (100
15 mm) when the flask is just cool enough to handle with your bare hands. 2. Liquid YP + sugars: 10 g Bacto yeast extract and 10 g Bacto peptone per 900 ml ddH2O. Autoclave 30 min. Autoclave 20 g of the sugars (dextrose, raffinose or galactose) separately in 100 ml ddH2O. Pour the sugar into the YP using sterile technique.

2.2. Dynein Preparation

1. Lysis buffer: For the initial lysis, 4
lysis buffer is used while later steps require 1
lysis buffer. Here, we list the composition of 1
lysis buffer: 30 mM HEPES (pH 7.2), 50 mM K acetate, 2 mM Mg acetate, 1 mM EGTA, 10% glycerol, 1 mM

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DTT, 0.1 mM ATP, and 0.5 mM Pefabloc SC (Roche). Note: In all solution preparations, DTT, ATP, and Pefabloc should be freshly added prior to use. 2. 1
wash buffer: 1
lysis buffer supplemented with 250 mM KCl and 0.1% Triton X-100. 3. IgG beads (IgG Sepharose 6 Fast Flow, Amersham). Store at 4 C. 4. BioRad poly-prep column (BioRad Poly-Prep Chromatography Column, BioRad). 5. 1
TEV buffer: 10 mM Tris–HCl (pH 8.0), 150 mM KCl, 10% glycerol, 1 mM DTT, 0.1 mM ATP, and 0.5 mM Pefabloc (Pefabloc does not inhibit TEV protease). 6. Millipore spin column (Millipore). 2.3. Microtubule Binding and Release

1. Tubulin (Cytoskeleton Inc.). Resuspend the lyophilized pellet as described by the manufacturer, aliquot and freeze immediately in liquid nitrogen. Use one aliquot per experiment. Store at 80 C. 2. 1 mM DTT (dithiothreitol) stock solution. Store at 20 C. 3. 10 mM taxol (paclitaxel, Sigma) stock solution dissolved in DMSO. Store at 20 C in small aliquots. 4. 2
tubulin polymerization buffer: 2
BRB80 (see below), 2 mM DTT, 2 mM MgGTP, and 20% DMSO. Store at 80 C in small aliquots. 5. BRB80: 80 mM PIPES (pH 6.8), 2 mM MgCl2, and 1 mM EGTA. Store at room temperature. 6. Apyrase stock solution: 660 U/ml apyrase (Sigma) made in 30 mM HEPES (pH 7.2). Store in aliquots at 20 C. 7. MT-binding buffer: 30 mM HEPES (pH 7.2), 2 mM Mg acetate, 1 mM EGTA, 10% glycerol, 1 mM DTT, 20 mM taxol, and 6.6 U/ml apyrase. Add DTT, taxol and apyrase immediately before use. 8. Sucrose cushion buffer: 30 mM HEPES (pH 7.2), 2 mM Mg acetate, 1 mM EGTA, 10% glycerol, 1 mM DTT, 10 mM taxol, and 40% sucrose. 9. ATP-release buffer: 30 mM HEPES (pH 7.2), 150 mM KCl, 7 mM Mg acetate, 1 mM EGTA, 10% glycerol, 1 mM DTT, 10 mM taxol, and 5 mM ATP (see Note 1).

2.4. Protein Concentration Determination

1. Sypro Red Gel Stain (Sigma). 2. Purified actin protein (Cytoskeleton Inc.). Resuspend the lyophilized pellet as described by the manufacturer, aliquot and freeze immediately in liquid nitrogen. Use one aliquot per experiment.

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2.5. Preparation of Biotinylated and TMR-Labeled Microtubules

1. Tubulin (Cytoskeleton Inc.). Resuspend the lyophilized pellet as described by the manufacturer, aliquot and freeze immediately in liquid nitrogen. Use one aliquot per experiment. 2. Biotin-tubulin (Cytoskeleton Inc.). Resuspend the lyophilized pellet as described by the manufacturer, aliquot and freeze immediately in liquid nitrogen. Use one aliquot per experiment. 3. TMR-tubulin (Rhodamine-tubulin, Cytoskeleton Inc.). Resuspend the lyophilized pellet as described by the manufacturer, aliquot and freeze immediately in liquid nitrogen. Use one aliquot per experiment. 4. 2
tubulin polymerization buffer (see above). 5. BRB80 (see above). 6. 10 mM taxol stock solution (see above). 7. 1 M DTT stock solution (see above).

2.6. Coating Polystyrene Beads with GFP Antibodies

1. Trapping beads: 100 mg/ml carboxyl-functionalized microspheres (0.92 mm diameter, Bangs Laboratories). Store at 4 C. 2. Activation buffer: 100 mM NaCl and 10 mM MES (pH 6.0). Store at room temperature. 3. Cross-linking reagents: 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide, hydrochloride (EDAC, Invitrogen) and N-hydroxysulfosuccinimide (NHSS, Invitrogen). Make sure both reagents are fresh and frozen at 20 C. 4. Quenching reagent: 14.3 M b-mercaptoethanol. Store at room temperature. 5. Coupling buffer: 100 mM sodium phosphate buffer (pH 7.4) prepared by combining 77.4 ml 1 M Na2HPO4 and 22.6 ml 1 M NaH2PO4. Store at room temperature. 6. Protein solution: 100 mg/ml BSA. Store at 4 C. 7. Antibody solution: 1–4 mg/ml GFP antibody stock solution. Store at 20 C. 8. PBS rinse solution: 137 mM NaCl, 2.7 mM KCl, 4.3 mM Na2HPO4, and 1.47 mM KH2PO4. 9. Quenching solution: 30 mM hydroxylamine hydrochloride (NH2OHHCl) in PBS (pH 8.0), prepared by dissolving 0.42 g NH2OHHCl in 200 ml PBS and adjusting pH to 8.0. 10. Antibacterial reagent: 10% w/v sodium azide (NaN3) solution.

2.7. Optical Trapping Assay

1. Slide chamber: acid-washed coverslips (15) from Corning (18
18
0.16 mm), glass microscope slides from Fisher (76.2
25.4
1 mm), and double-sided sticky tape.

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2. Assay buffer: 30 mM HEPES (pH 7.2), 2 mM MgAcetate, and 1 mM EGTA. Filter and store at room temperature. 3. Stock solutions: 100 mM ATP (store at 80 C), 25 mg/ml casein (store at 80 C), 1 M DTT (store at 20 C), 450 mg/ml glucose (2.25 M, store at 80 C), 200 mM phosphoenylpyruvate (store at 20 C), and 10 mg/ml pyruvate kinase (store at 4 C). 4. Oxygen-scavenging system: 25 mg/ml glucose oxidase and 3 mg/ml catalase made in assay buffer. Centrifuge the solution at maximum speed in a microfuge for 5 min at 4 C, filter (Millipore), and store at 4 C (do not freeze). Use within a few days.

3. Methods Cytoplasmic dynein generates forces and motion in eukaryotic cells. To dissect the structural basis of dynein’s force-generation and processive motion, we have recently developed methods to engineer and purify cytoplasmic dynein from S. cerevisiae (7). In this chapter, we describe in detail the use of S. cerevisiae to express and purify a fully functional “minimal” dynein motor (GST-Dyn1331 kDa (7)). This tail-truncated, artificially dimerized dynein motor retains near normal force- and motion-generating capabilities and can be produced in quantities sufficient for biochemistry and single-molecule studies (7, 8) (Fig. 1a). By performing homologous recombination-based genetic manipulations, this S. cerevisiae minimal dynein motor can be used for mutagenesis and structure–function studies, as well as for generating dynein motors with site-specific protein tags for fluorescence labeling. Ultimately, probing the force-dependent motility of single dynein molecules requires a single-molecule interrogation instrument that can simultaneously measure nanoscale displacements and piconewton forces. This can be achieved with a force-feedback enhanced optical trapping microscope. Here, we first provide a detailed protocol for expressing and purifying recombinant cytoplasmic dynein. We then describe hands-on protocols for utilizing a custom-built force-feedback optical trapping microscope to determine the stall force, force–velocity relationship and the nanoscale stepping behavior of single dynein molecules. 3.1. Growth and Harvesting of Minimal Dynein-Expressing S. cerevisiae Strains

This protocol is for expression of minimal processive dyneincontaining strains. The minimal processive dynein motor is a homodimer of two 331 kDa dynein monomers (amino acids 1219–4093 of the S. cerevisiae Dyn1 protein) that have been artificially dimerized with glutathione S-transferase (GST)

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b

microtubule

c IgG

dynein

tail linker motor stalk

TEV Protease

5 4

Bind MTs (-ATP)

actin

6 3 1 2 GST GFP ZZ-TEV

Release MTs (+ATP)

“minimal motor” “full-length”

Fig. 1. Purification of GST-Dyn1331 kDa from S. cerevisiae. (a) Full-length cytoplasmic dynein is a dimer of two 470-kDa heavy chains. To make the minimal dimer (GST-Dyn1331 kDa), the tail of full-length dynein was truncated and then artificially dimerized with GST [7]. This construct also contains an amino terminal purification tag (ZZ-TEV) and GFP for bead attachment for optical trapping experiments. (b) An overview of the purification protocol for cytoplasmic dynein. After cell lysis and an ultracentrifugation step, dynein is bound to IgG beads via the ZZ tag. After washing the beads, dynein is cleaved from the IgG beads with TEV protease. As a second affinity purification step, dynein is bound to MTs in the absence of MgATP and then released from MTs in the presence of MgATP. (c) SDS-PAGE gel stained with Sypro-Red (Sigma) of purified minimal dynein. Serial dilutions of dynein (top) and the actin standard (bottom) are shown.

(Fig. 1a) (7). High expression levels are achieved by using a galactose-inducible promoter to drive dynein expression. A list of published strains that express variants of the minimal dimer can be found in Table 1. It is also possible to purify full-length native yeast dynein (7, 16). However, yields for the full-length protein are 50–100 times lower compared to the minimal dimer and the protein is more difficult to purify. Thus, for the purpose of this book chapter, we have chosen to focus on the purification protocol used for the minimal processive dynein. 1. From a frozen glycerol stock, streak yeast cells onto a YPD plate and incubate the plate at 30 C for 2–3 days. 2. Inoculate 10 ml of liquid YPD medium with a single yeast colony and grow in a 25-ml test tube overnight, shaking (250 rpm) at 30 C. 3. The following morning, add the entire 10 ml YPD culture to 50 ml YP + 2% raffinose in a 250-ml Erlenmeyer flask. Grow by shaking (250 rpm) at 30 C for the rest of the day. 4. At the end of the day, transfer the 50 ml YP + raffinose yeast culture to 2 L YP + 2% galactose in a 6-L Erlenmeyer flask. Grow by shaking (200 rpm) at 30 C overnight until the OD600 reaches 1.5–2.0 (approximately 16–22 h).

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Table 1 Yeast strains expressing minimal processive dynein motors Dynein description

Strain name

Minimal dimer

Genotype

Reference

VY149

pGAL-ZZ-TEV-GFP-3XHA-GST331DYN1

(7)

Minimal dimer with a C-terminal HaloTag

VY208

pGAL-ZZ-TEV-GFP-3XHA-GST331DYN1-gs-DHA1-KanR

(7)

Minimal dimer with a N-terminal HaloTag

VY268

PAC11-13MYC::TRP; ZZ-TEV-gs-DHA- (7) GST-331D

Minimal dimer with a point mutation in AAA domain 1 (E1849Q)

RPY546 pGAL-ZZ-TEV-GFP-3XHA-GST-D6DYN1-E1849Q-gs-DHA-KanR

(9)

Minimal dimer with a point mutation in AAA domain 3 (E2488Q)

RPY542 pGAL-ZZ-TEV-GFP-3XHA-GST-D6DYN1-AAA3E2488Q-gs-DHA-KanR

(9)

Minimal dimer with a point mutation in AAA domain 4 (E2819Q)

RPY548 pGAL-ZZ-TEV-GFP-3XHA-GST-D6DYN1-E2819Q-gs-DHA-KanR

(9)

These yeast strains all express minimal dynein (the C-terminal 331 kDa of the protein) that is dimerized with GST. All strains are made in a parent strain with the following genotype: MATa; his3-1,15; ura3-1; leu2-3,112; ade2-1; trp1-1; can1-100; pep4D::HIS5; prb1D. “DHA” refers to the HaloTag (Promega) and “gs” refers to glycine and serine amino acids used as spacers. The N-terminal tag includes the galactose promoter (pGAL), two copies of the IgG-binding motif (ZZ), a TEV protease cleavage site (TEV), green-fluorescent protein (GFP), three copies of the HA-epitope tag (HA), and GST for dimerization (GST)

5. To harvest the cells, centrifuge the culture in 1-L Beckman bottles (Beckman) at 6,000 rpm (6,900
g) at 4 C in a Beckman JLA 8.1 rotor in an Avanti J-26 XP Beckman centrifuge or equivalent. 6. Decant the supernatant and resuspend the cell pellets completely in 1 L ddH2O. Centrifuge again as in step 5. 7. Decant the water and resuspend the cell pellet in any residual ddH2O that remains in the bottle using a 10-ml pipette (it may be necessary to add 1–2 ml of ddH2O). 8. Using a 10-ml pipette, drop-freeze the cell slurry into liquid nitrogen. The frozen yeast bears some resemblance to popcorn at this stage. From this point on the yeast pellets should not be allowed to thaw. Store the frozen yeast pellets at 80 C until ready to proceed.

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3.2. Purification of S. cerevisiae Cytoplasmic Dynein

All minimal dynein dimer constructs that we have made contain an amino-terminal (dynein tail) purification tag consisting of two copies of an IgG-binding domain (ZZ) and a TEV protease cleavage site (Fig. 1a, b). 1. Lyse the frozen yeast pellets by grinding in a coffee grinder (we use KitchenAid BCG100 Blade Coffee Grinders). It is important to keep the yeast pellets frozen at all times. The coffee grinder must be pre-chilled with liquid nitrogen and it may be necessary to add liquid nitrogen a second time during the grinding. The yeast pellets should be ground until they resemble powdered sugar or a very fine espresso grind (approximately 1 min of total grinding time). Note: to prevent loss of yeast pellets do not operate the coffee grinder until all liquid nitrogen has evaporated. Wear heavy gloves while operating the coffee grinder. Alternatively, the frozen yeast pellets can by lysed by grinding manually using a mortar and pestle in the presence of liquid nitrogen. 2. Remove the yeast powder from the coffee grinder with a small spatula to a 50-ml conical tube. Immediately add 4
lysis buffer to the yeast powder so that the final concentration of lysis buffer after the yeast powder thaws is 1
(approximately 1 ml 4
lysis buffer per 10 ml yeast powder). 3. Place the conical tube into a 37 C water bath to quickly thaw the yeast powder. As soon as the powder has thawed, the lysate should be placed on ice. All future steps should be performed on ice or in a cold room unless otherwise specified. 4. Estimate the final lysis volume and adjust the lysis buffer concentration to 1
(using 4
lysis buffer) if necessary. 5. To remove cell debris and unlysed cells, centrifuge the lysate in a Beckman TLA110 rotor at 90,000 rpm (338,000
g) for 20 min at 4 C in a Beckman tabletop ultracentrifuge. Use thick walled polycarbonate tubes (Beckman). Tubes must be balanced to 0.01 g prior to centrifugation. 6. During the spin, prepare IgG beads for the affinity purification step. Use 10 ml of 50% bead slurry per 1 ml of lysate (volume estimated in step 4). Wash the beads twice with at least 10
the bead volume in a BioRad Poly-Prep Column. 7. Remove the supernatant from the spin in step 5. Avoid the lipid layer that is floating on top of the supernatant. Pipette the supernatant into a 15- or 50-ml conical tube. Remove and freeze (in liquid nitrogen) 20 ml for a gel sample. 8. Add the washed beads to the extract (use the extract to pipette the beads out of the BioRad column). Incubate the beads and extract in the cold room for 1–2 h on a rocking platform at a slow speed to avoid air bubble production (which can denature proteins).

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9. Wash the beads twice (20
bead volume per wash) with 1
wash buffer. 10. Wash the beads once (20
bead volume) with 1
TEV buffer. 11. Optional: Most of the minimal dynein constructs we have made include a HaloTag (Promega) on either the N or C terminus. To label the HaloTag with a fluorophore or biotin, add 100 ml 1
TEV buffer per 100 ml bead bed volume. The labeling step can be done directly on the BioRad column (be sure to cap the bottom of the column). Add HaloTag ligand to a final concentration of 10 mM and incubate at room temperature for 10 min (covered with foil if using a fluorophore ligand). 12. Optional: If labeling the HaloTag, wash the beads an additional two times (20
bead volume per wash) with 1
TEV buffer to remove any unbound dye or biotin. 13. Cleave dynein off the beads with TEV protease. Transfer the beads from the BioRad column to a microfuge tube with 100 ml 1
TEV buffer per 100 ml bead bed volume (depending on the pipette tips used, it may be necessary to cut the tip of the pipette with a razor blade to ensure the beads can be removed). Note: the volume added at this step will be equal to the final elution volume. Add TEV protease (see Note 2). We use 4 mg TEV protease per 100 ml TEV buffer added in the previous step. Incubate at 16 C for 1–2 h (or 4 C overnight) rocking slowly (avoid air bubble formation). 14. Transfer the entire reaction (beads and buffer containing cleaved dynein) from the microfuge tube to a 2-ml Millipore spin column. Centrifuge the spin column in a microfuge at maximum speed at 4 C for 30 s. Save the beads for a gel sample. 15. Prepare 50 ml aliquots of the supernatant and freeze immediately in liquid nitrogen. Store the protein at 80 C. Alternatively, you can proceed directly to the MT-binding and -release step without freezing the protein in between. 3.3. Microtubule Binding and Release

As a second affinity purification step that also removes any nonfunctional motors, dynein is mixed with MTs in the absence of ATP (tight MT-binding state) and then released from MTs in the presence of ATP (weak MT-binding state). The first steps of this protocol describe how to polymerize tubulin, while the later steps include the MT binding and release of dynein. 1. Thaw one aliquot of tubulin and one aliquot of DTT and place both on ice. Thaw one aliquot of taxol and keep at room temperature (see Note 3). 2. Polymerize 15 ml 100 mM tubulin by mixing with 15 ml of 2
polymerization buffer. Incubate at 37 C for 20 min. This will yield 30 ml of 50 mM MTs. From this point on, the MTs

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should never be placed on ice and taxol should be included in all subsequent steps to prevent MT depolymerization. 3. Stabilize MTs with taxol by combining the MTs (30 ml of 50 mM MTs) from the previous step with 30 ml BRB80 supplemented with 1 mM DTT and 100 mM taxol. Incubate at 37 C for 10 min. The final yield will be ~60 ml of 25 mM MTs. 4. MT-binding step: thaw a 50 ml aliquot of dynein solution (~0.6 mM) and place on ice. Mix together 50 ml dynein solution, 25 ml MTs (~25 mM), and 25 ml MT-binding buffer. Incubate at room temperature for 10 min. Gently pipette the 100 ml reaction mixture over 100 ml sucrose cushion buffer and centrifuge in a Beckman TLA100 rotor (the rotor should be at room temperature) for 15 min at 50,000 rpm (109,000
g) at 22 C. 5. After the spin, remove the top 50 ml of the supernatant for a gel sample. Discard the remainder of the supernatant and wash the MT pellet carefully with 100 ml MT-binding buffer, being careful not to disrupt the dynein-MT pellet. 6. Resuspend the MT pellet in 100 ml ATP-release buffer and incubate at room temperature for 10 min. 7. Centrifuge the resuspended pellet in a Beckman TLA100 rotor (the rotor should be at room temperature) for 15 min at 50,000 rpm (109,000
g) at 22 C. 8. Remove the supernatant (dynein-containing solution), aliquot (3–5 ml samples, see Note 4) and freeze immediately in liquid nitrogen. Store the protein at 80 C. 3.4. Protein Quantification

We quantify dynein protein concentration by running a SDSPAGE gel with a dilution series of dynein and a dilution series of a protein of known concentration (e.g., actin, Fig. 1c). The gel is then stained with Sypro Red Gel Stain. Sypro Red’s fluorescence intensity is linear with protein quantity over several orders of magnitude. After staining, densitometry analysis is used to quantify the intensity of the known actin concentrations and a standard curve is generated. The intensity of the dynein bands is also quantified and the actin standard curve is used to assign protein concentration to the dynein sample. The typical concentration of minimal dimeric dynein motor from a 2 L preparation (eluted in 300 ml) before the MT-binding and -release step is 500 mg/ml or ~0.6 mM.

3.5. Preparation of Biotinylated and TMR-Labeled Microtubules

In this step, unlabelled tubulin is polymerized in the presence of biotinylated and fluorescently labeled tubulin subunits. The biotin is used for attachment to coverslips and the fluorescent label for visualization. We purify tubulin from bovine or porcine brains using

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the protocol from the Mitchison lab website: http://mitchison. med.harvard.edu/protocols/tubprep.html. Alternatively, tubulin can be obtained from Cytoskeleton Inc. 1. Spin unlabeled tubulin in a Beckman TLA100 rotor at 90,000 rpm (352,000
g) for 10 min at 4 C in thick-walled polycarbonate tubes (Beckman) to remove any tubulin aggregates. Keep the tubulin on ice at this point. 2. Mix together 18 ml 50 mM unlabelled tubulin, 1 ml 100 mM biotin-tubulin and 1 ml 100 mM TMR-tubulin. Mix gently and incubate on ice (covered with foil) for 10 min. 3. Add 20 ml 2
polymerization mix to the tubulin prepared in step 2. Mix gently and incubate in the dark at 37 C for 30 min. The tubulin will polymerize during this step. From this point on the MTs should never be placed on ice, as this will depolymerize the MTs. 4. Add 40 ml BRB80 supplemented with 1 mM DTT and 20 mM taxol and incubate at 37 C for 10 min. 5. Store the taxol-stabilized MTs in the dark at room temperature. Polymerized MTs are stable for several days. 3.6. Coating Polystyrene Beads with GFP Antibodies

1. Wash carboxyl-modified microspheres in activation buffer. Pipette 100 ml bead solution into a 1.5-ml microfuge tube and add 0.9 ml activation buffer. Centrifuge 15 min at 2,000
g (all bead centrifugation steps should be performed at 2,000
g) and discard the supernatant. Resuspend in 1 ml activation buffer (vortex and sonicate solution for a few seconds). Repeat this procedure 2–3 times. 2. Following the final resuspension step, add 10 mg of both EDAC and NHSS. Sonicate the solution for 10 s in a water bath sonicator and incubate on a rocking platform at low speed at room temperature for 30 min. 3. Add 1.4 ml 14.3 M b-mercaptoethanol to quench the EDAC reaction. 4. Wash the beads four times in coupling buffer (centrifuge the solution, discard the supernatant and resuspend the beads in coupling buffer). Ensure that the beads are well suspended before the final centrifugation step (vortex and sonicate for a few seconds). 5. Mix the antibody solution of your choice with BSA to bring the final total protein concentration to 5–10 mg/ml (500–1,000 ml volume) (see Note 5). We use approximately 0.3 mg of GFP antibody. React 10 mg of beads with the antibody-BSA solution for 2–4 h at room temperature (or overnight at 4 C) with constant mixing (sonicate briefly if necessary in a water bath sonicator).

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6. Wash the beads once in PBS rinse solution and resuspend in quenching solution. Incubate on a rocking platform at room temperature for 30 min (or overnight at 4 C). 7. Rinse beads four times in PBS. Resuspend beads in 100 ml PBS (original volume of bead solution) containing 0.1% NaN3 and 0.5 mg/ml BSA. Store the bead stock solution at 4 C (do not freeze the beads). 3.7. Optical Trapping Assay

1. Make a flow cell by placing two strips of double-sided sticky tape between a standard microscope slide and a 160-mm thick 18 mm
18 mm coverslip to form a channel (Fig. 2a). If the two pieces of tape are about 3 mm apart, the approximate volume of the flow cell will be 10 ml. 2. Dilute 2 ml bead stock solution (resuspend beads before use by pipetting, but do not sonicate) with 18 ml assay buffer. This solution should be stored at 4 C and can be kept for a few days. Sonicate the diluted solution in a water bath sonicator for 10 s before use. 3. Thaw one aliquot of each: ATP (100 mM), casein (25 mg/ml), DTT (1 M), and glucose (2.25 M), and store on ice.

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4. Quickly thaw a 3 ml aliquot of frozen dynein (from Subheading 3.3, step 8) and place on ice immediately. Dilute the motor with assay buffer containing 1 mg/ml casein. Start with an initial dilution of 1,000
by serially diluting the motor in tenfold dilution steps. 5. Combine 4 ml diluted bead solution (from step 2) and 4 ml motor solution (from step 4) and incubate on ice for 10 min. 6. During the incubation time, coat the flow cell with biotinylated BSA for 2 min, incubate with streptavidin for 2 min, and then incubate with biotinylated and TMR-labeled MTs for 5 min. Finally, wash the flow cell with 20 ml assay buffer + 1 mg/ml casein. 7. Prepare motility buffer: 1 ml 100 mM ATP, 4 ml 25 mg/ml casein, 1 ml 1 M DTT, 1 ml 2.25 M glucose, and 2 ml assay buffer, and place on ice. Add 1 ml oxygen-scavenging solution just prior to adding the motility buffer to the bead-dynein solution in the next step. 8. Combine motility buffer with the bead-dynein solution: mix 4 ml prepared motility buffer (step 7), 28 ml assay buffer, and 8 ml bead-dynein solution (step 5). The final solution (40 ml) contains 1 mM MgATP, 1 mg/ml casein, 10 mM DTT, 22.5 mM glucose, 0.25 mg/ml glucose oxidase, and 0.03 mg/ml catalase in assay buffer (30 mM HEPES (pH 7.2), 2 mM Mg acetate, and 1 mM EGTA). 9. Finally, pipette and flow the solution into the slide chamber and seal the flow cell with clear nail polish. 3.8. Measuring Dynein’s Stall Force

1. Mount the slide chamber to the microscope stage and adjust the microscope condenser using a sufficient amount of immersion oil. 2. Turn on all required components for the fluorescenceimaging system (see Note 6) and adjust the z-position of the stage to bring the surface-attached MTs into the object plane. 3. Select a horizontally aligned MT (look for straight MTs) and position it (using the x-/y-stage positioning system) near the center of the object field. Shutter the fluorescence excitation light to prevent further photo bleaching. 4. Trap a diffusing bead (see Note 6) and measure the response of the photo detector by scanning the trapped bead along the x-axis of the object field (from 200 to +200 nm). Use a MatLab script (or equivalent) to convert the QPD-voltage signals into nm-displacements. 5. Calibrate the trap stiffness by measuring the amplitude of thermal diffusion (equipartition analysis) and/or by analyzing the power spectrum of thermal diffusion (see Note 7).

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6. Open the shutter that blocks the fluorescence excitation light and position the axial center of the preselected MT (see step 3) in the center of the object field, which coincides with the center of the QPD detection system. 7. Move the MT near the trapped bead by adjusting the zposition of the stage. The thermal noise of the bead will decrease once the MT makes contact with the trapped bead. Keep the MT surface as close to the trapped bead as possible, but avoid direct contact (Fig. 2b). 8. Observe the bead position for 1 min. The positional fluctuations of the trapped bead will decrease once a dynein motor binds to the MT. Upon MT binding, the motor will advance along the MT and pull the bead away from the fixed trap center (in the nonfeedback mode) (Fig. 2c). If MT binding and subsequent bead movement is not observed, reposition the bead on the MT and monitor for an additional minute. 9. To ensure that the behavior of single molecules is being measured, adjust the motor dilution such that the number of beads binding to or moving along MTs is 0.3. At this dynein-to-bead ratio, the probability that two or more motors generate the bead movement is <0.01 (8) (see Note 8). 10. Determine the dynein stall force using the established dyneinto-bead ratio. The force load (F ) that the motor experiences increases with increasing bead-trap separation x (F ¼ kx). The motor movement will gradually slow down and eventually cease once the stall force is reached (Fig. 2c). A stalling event can be identified as a horizontal plateau in the displacement trace. It is important to note that premature dissociation of dynein from the MT can also terminate a run before the stall force is achieved (Fig. 2c, right). To avoid including premature dissociation events in the stall force measurements, include only stalls in the analysis that last for more than 10 s (see Note 9). To calculate the stall force, multiply the trap stiffness by the mean maximum distance reached. We typically accumulate ~100 stall-force values to create a stall-force histogram (8). 3.9. Measuring Dynein’s Force–Velocity Relationship

1. Prepare a sealed flow chamber with dynein-coated beads and 1 mM ATP (saturating concentration) as described in Subheading 3.7. 2. Record dynein displacement traces under varying average constant force loads using the force-feedback mode of the optical trap (Fig. 2d). To minimize force errors associated with Brownian movements of the bead, adjust the trap stiffness so that the bead-trap separation is ~100 nm at the desired load (17). For example, set the trap stiffness to 0.04 pN/nm

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when acquiring displacement traces under 4 pN constant backward load (Fig. 2d). At the smallest force load of 0.5 pN, set the trap stiffness to 0.01 pN/nm, which corresponds to a bead-trap separation of 50 nm. 3. Calculate motor velocity by fitting the displacement traces of the beads moving under constant load with a line and determine its slope. 3.10. Measuring Dynein’s Nanoscale Motion as a Function of Load and ATP

1. Perform force-feedback measurements at various constant force loads as described above using saturating (1 mM) and subsaturating ATP concentrations. In the case of yeast dynein, motor stepping is slow enough to be resolved even at saturating ATP concentrations (Fig. 2d, inset) (7). The Km (the ATP concentration at which motor velocity reaches half maximal velocity) of S. cerevisiae cytoplasmic dynein is approximately 10 mM (8). When working with ATP concentrations in the micromolar range, use an ATP regeneration system by adding 1 ml 200 mM phosphoenylpyruvate and 1 ml 10 mg/ml pyruvate kinase in place of the 2 ml assay buffer when preparing the motility buffer (see Subheading 3.7, step 7). 2. Motor steps (approximate center-of-mass movement of dynein) can be determined from the bead displacement records using the step-finding algorithm developed by Kerssemakers et al. (18) (Fig. 2d, inset) (see Note 10).

4. Notes 1. In all solutions containing ATP, Mg++ should be present at an equal or greater concentration than the ATP concentration. This is because Mg++ ions are important for coordinating the binding of ATP to dynein’s ATP-binding sites. 2. We express and purify TEV protease using the method of Kapust et al. (19). TEV protease can also be purchased from Invitrogen. 3. Because the taxol stock solution is made in 100% DMSO, it will freeze immediately on ice. The taxol stock can be kept at room temperature during the MT-binding and -release step. 4. After the MT-binding and -release step, we aliquot and freeze the dynein solution into small (3–5 ml) aliquots and do not freeze/thaw the protein again. Each aliquot is intended for a single experiment (one slide chamber). Because dynein motors become nonfunctional more rapidly at 4 C than when frozen at 80 C, this ensures that each experiment is performed at the same concentration of functional protein.

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5. The surface-functionalized beads will aggregate when the local protein concentration is not high enough to comprise a monolayer on the bead surface. Resuspending the beads in a premixed BSA-antibody solution ensures a complete surface coating of the beads. 6. Measurements are performed at room temperature (25  0.5 C) with a custom-built, force-feedback optical trapping microscope. A near-infrared laser beam (Nd:YVO4, 1,064 nm; Spectra Physics) is coupled to an inverted microscope equipped with a 63
/1.4 NA oil-immersion objective (Plan-Apochromat, Carl Zeiss, Thornwood, NY). To generate two independently controllable traps, the laser beam is split into horizontally (trap 1) and vertically (trap 2) polarized light. Trap 1 is steered by a computer-controlled mirror system and is used to capture a bead anywhere in the object field. Trap 1 then transfers the captured bead to trap 2 in the object center. The position of trap 2 is restricted to a 1.5
1.5 mm area located in the center of the object field and is integrated into a position feedback loop that is controlled by a DSPboard (M67, Innovative Integration, Simi Valley, CA) via a two-axis acousto-optic deflection system (DTD-274HA6, IntraAction, Bellwood, IL). All optical trapping experiments are performed with trap 2. Force-feedback is operational in an area of 200 nm along both the x- and y-axis of the object field. The microscope is further equipped with a Xenon lamp (Oriel, Stamford, CT) for bright field and epifluorescence imaging, as well as a computer-controlled x-/y-stage. The brightfield image is captured by both a charge-coupled camera (CCD) and a QPD detector, whereas the fluorescence image is captured by a silicon intensified (SIT) camera, allowing visualization of the TMR-labeled MTs. The position of the trapped bead detected by the QPD is recorded at 2 kHz and filtered at 1 kHz. 7. According to the equipartition theorem, the energy associated with the fluctuations (with respect to the x-axis) of the trapped bead 0.5k<x2> is equal to 0.5kBT of thermal energy, where <x2> is the positional variance, k is the trap stiffness, kB is the Boltzmann constant, and T is the absolute temperature, respectively. This yields an equation for the trap stiffness k: k ¼ kBT/<x2> (for a detailed discussion on bead calibration methods, see ref. 20). 8. To determine if a motor is processive, it is customary and recommended (especially in the case of an uncharacterized motor) to determine the fraction of motor-coated beads binding to and moving along filaments as a function of the relative motor concentration. In these experiments, the bead concentration is kept constant for all measurements while the motor concentration is

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varied. If the resulting data fits well with the Poisson probability 1  exp(lC) that a given bead carries one or more motor molecules (where C is the relative motor concentration and l is a fit parameter; (21)), the data provide evidence that a single motor is sufficient to drive continuous bead movement (as is the case for cytoplasmic dynein). However, if the data can be better fit by the probability 1  exp(lC)  (lC)exp(lC), this suggests that bead movement requires two or more motors, and is indicative of a nonprocessive motor. 9. S. cerevisiae cytoplasmic dynein typically stalls for several minutes before it detaches from its track (8), whereas mammalian cytoplasmic dynein tends to detach prematurely or within a few seconds after motor stalling (4, 5). 10. This algorithm assumes that steps are hidden in normaldistributed noise but makes no assumptions about step size or duration. The only parameter that is user-supplied is an estimate of the number of hidden steps. This parameter is chosen so that the algorithm appears to slightly “overfit” the data (18). The resulting data are then manually examined and only those steps that can be visually separated from noise are included in step size histograms. Using this method and depending on the applied load, one can typically assign step sizes to 40–90% of a given dynein run.

Acknowledgments The authors would like to thank Julie Huang and Matthew Nicholas for critical comments on the manuscript. References 1. Vallee, R. B., Williams, J.C., Varma, D., and Barnhart, L. E. (2004) Dynein: An ancient motor protein involved in multiple modes of transport. J. Neurobiol. 58, 189–200. 2. Vallee, R. B., Tai, C., and Faulkner, N. E. (2001) LIS1: cellular function of a diseasecausing gene. Trends Cell Biol. 11, 155–160. 3. Puls, I., Jonnakuty, C., LaMonte, B. H., Holzbaur, E. L. F., Tokito, M., Mann, E., Floeter, M. K., Bidus, K., Drayna, D., Oh, S. J., Brown Jr., R.H., Ludlow, C.L., and Fischbeck, K.H. (2003) Mutant dynactin in motor neuron disease. Nat. Gen. 33, 455–456. 4. Mallik, R., Carter, B. C., Lex, S. A., King, S. J., and Gross, S. P. (2004) Cytoplasmic dynein

functions as a gear in response to load. Nature 427, 649–652. 5. Toba, S., Watanabe, T. M., YamaguchiOkimoto, L., Toyoshima, Y. Y., and Higuchi, H. (2006). Overlapping hand-over-hand mechanism of single molecular motility of cytoplasmic dynein. Proc. Natl. Acad. Sci. USA 103, 5741–5745. 6. Ross, J. L., Wallace, K., Shuman, H., Goldman, Y. E., and Holzbaur, E. L. (2006). Processive bidirectional motion of dynein-dynactin complexes in vitro. Nat. Cell. Biol. 8, 562–570. 7. Reck-Peterson, S. L., Yildiz, A., Carter, A. P., Gennerich, A., Zhang, N., Vale, R. D. (2006) Single-molecule analysis of dynein

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processivity and stepping behavior. Cell 126, 335–438. 8. Gennerich, A., Carter, A. P., Reck-Peterson, S. L., Vale, R. D. (2007) Force-induced bidirectional stepping of cytoplasmic dynein. Cell 131, 952–965. 9. Cho, C., Reck-Peterson, S. L., and Vale, R. D. (2008) Cytoplasmic dynein’s regulatory ATPase sites affect processivity and force generation. J. Biol. Chem. 283, 25839–25845. 10. Carter, A. P., Garbarino, J. E., Wilson-Kubalek, E. M., Shipley, W. E., Cho, C., Milligan, R. A., Vale, R. D., and Gibbons, I. R. (2008) Structure and functional role of dynein’s microtubule-binding domain. Science 322, 1691–1695. 11. Block, S. M., Goldstein, L. S., and Schnapp, B. J. (1990) Bead movement by single kinesin molecules studied with optical tweezers. Nature 348, 348–352. 12. Finer, J. T., Simmons, R. M., and Spudich, J. A. (1994) Single myosin molecule mechanics: piconewton forces and nanometre steps. Nature 368, 113–119. 13. Asbury, C. L., Fehr, A. N., and Block, S. M. (2003) Kinesin moves by an asymmetric handover-hand mechanism. Science 302, 2130–2134. 14. Altman, D., Sweeney, H. L., and Spudich, J. A. (2004) The mechanism of myosin VI translocation and its load-induced anchoring. Cell 116, 737–749.

15. Pierce, D. W., Hom-Booher, N., Otsuka, A. J., and Vale, R. D. (1999) Single-molecule behavior of monomeric and heteromeric kinesins. Biochemistry 38, 5412–5421. 16. Kardon, J., Reck-Peterson, S. L., and Vale, R. D. (2009) Regulation of the processivity and intracellular localization of Saccharomyces cerevisiae dynein by dynactin. Proc. Natl. Acad. Sci. USA 106, 5669–5674. 17. Block, S. M., Asbury, C. L., Shaevitz, J. W., and Lang, M. J. (2003) Probing the kinesin reaction cycle with a 2D optical force clamp. Proc. Natl. Acad. Sci. USA 100, 2351–2356. 18. Kerssemakers, J. W. J., Munteanu, E. L., Laan, L., Noetzel, T. L., Janson, M. E., and Dogterom, M. (2006) Assembly dynamics of microtubules at molecular resolution. Nature 442, 709–712. 19. Kapust, R. B., To¨zse´r, J., Fox, J. D., Anderson, D. E., Cherry, S., Copeland, T. D., and Waugh, D. S. (2001) Tobacco etch virus protease: mechanism of autolysis and rational design of stable mutants with wild-type catalytic proficiency. Protein Eng. 14, 993–1000. 20. Neuman, K. C. and Block, S. M. (2004) Optical Trapping. Rev. Sci. Instrum. 75, 2787–2809. 21. Svoboda, K. and Block, S. M. (1994) Force and velocity measured for single kinesin molecules. Cell 77, 773–784.

Chapter 5 A Brief Introduction to Single-Molecule Fluorescence Methods Siet M.J.L. van den Wildenberg, Bram Prevo, and Erwin J.G. Peterman Abstract One of the more popular single-molecule approaches in biological science is single-molecule fluorescence microscopy, which is the subject of the following section of this volume. Fluorescence methods provide the sensitivity required to study biology on the single-molecule level, but they also allow access to useful measurable parameters on time and length scales relevant for the biomolecular world. Before several detailed experimental approaches are addressed, we first give a general overview of single-molecule fluorescence microscopy. We start with discussing the phenomenon of fluorescence in general and the history of single-molecule fluorescence microscopy. Next, we review fluorescent probes in more detail and the equipment required to visualize them on the single-molecule level. We end with a description of parameters measurable with such approaches, ranging from protein counting and tracking, to distance measurements with Fo¨rster Resonance Energy Transfer and orientation measurements with fluorescence polarization. Key words: Microscopy, Confocal fluorescence, TIRF, Wide-field epifluorescence, Fluorophore

1. Introduction 1.1. A Brief Introduction to Fluorescence Spectroscopy

The name fluorescence was first used by Sir George Gabriel Stokes in his seminal 1852 paper “On the Change of Refrangibility of Light” (1), where he describes this phenomenon in many different materials, following in the steps of Herschel’s studies on quinine solutions (2, 3) and Brewster’s on fluorspar (fluorite) (4). In a note Stokes states: “I am almost inclined to coin a word, and call the appearance fluorescence, from fluorspar, as the analogous term opalescence is derived from the name of a mineral.” By now, fluorescence spectroscopy has become an indispensible technique, in particular in biomolecular research (5). Fluorescence is defined as light emitted by a molecule after absorption of light by the same molecule and involves a spin-allowed, singlet–singlet electronic transition. As an example, in Fig. 1a an imaginary absorption and

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_5, # Springer Science+Business Media, LLC 2011

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Fig. 1. (a) Absorption (Abs) and fluorescence emission (Em) spectrum of an imaginary molecule. The maximum of the emission spectrum is shifted toward the red (longer wavelength) with respect to the maximum of the absorption spectrum, a property called the Stokes’ shift. (b) Jabłon´ski diagram. The electronic states (S0, S1, S2) and their vibronic states are depicted by horizontal lines. The straight arrows indicate radiative transitions, the wavy ones nonradiative transitions.

fluorescence emission spectrum is shown. The energy levels involved in absorption and fluorescence are usually depicted in a Jabłon´ski diagram (Fig. 1b). The electronic ground state and first and second excited singlet states are designated S0, S1, and S2, respectively. The thin horizontal lines represent vibronic levels, involving in addition to electronic, vibrational excitation. Transitions between the levels are depicted as vertical arrows, straight ones involving radiative transitions, wavy ones radiationless ones. From the ground state S0 a molecule can absorb a photon, leading to an excited state, in Fig. 1b to S2. Usually, excitation from a higher vibronic state is followed by fast (typical time scale: ~10
12 s) radiationless relaxation to the lowest vibrational level of S1, a process called internal conversion, leading to the generation of heat. From S1, the excited molecule can usually relax to the ground state in one of three ways. (1) The molecule can return to the ground state while emitting a photon, fluorescence (~10
8 s). (2) The molecule can get rid of the excitation energy via internal conversion, without emitting a photon (IC, ~10
8 s). Finally, (3) the electrons in the molecule can undergo a spin conversion to a triplet state, a process called intersystem crossing (ISC, ~10
8 s). The resulting triplet state (T1) can decay to the ground state in a radiationless way via internal conversion or while emitting a photon, phosphorescence, which usually takes place on a much longer time scale than fluorescence, since it involves a spin-forbidden transition. The time scales mentioned are typical values and vary substantially among different molecules and can also depend on the (solvent) environment. An important property of fluorescence of molecules in condensed phases is the so-called Stokes’ shift: the energy of the emitted photons is generally lower than that of

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the absorbed photons (Fig. 1a). The most important reason, as depicted in Fig. 1b, is fast relaxation of the excited state to the lowest vibrational level of S1, from which transitions can occur to vibrationally excited states of S0. In addition, in the liquid state, solvent effects can contribute to the energy shift (5). 1.2. A History of Single-Molecule Fluorescence Microscopy

A key cause for the popularity of fluorescence to study biomolecules is its sensitivity. The sensitivity is such that, using the appropriate instrumentation, the fluorescence emitted by a single fluorophore can readily be detected. An important reason for the sensitivity is the Stokes’ shift, which allows, after proper filtering, detection of the fluorescence signal against a black background. Over the last decades, researchers have pushed the detection limit further and further. In the 1970s, Hirschfeld observed single antibodies, labeled with ~100 fluorescein molecules (6). Later in the 1980s, single phycoerythrin proteins, also containing multiple fluorophores, were detected (7, 8). In 1989, Moerner and coworkers succeeded in detecting, at liquid helium temperatures, the absorption of single dye molecules embedded in organic crystals (9). At these low temperatures and in crystalline environment, the absorption line of a single molecule is extremely narrow but very strong, making the detection of a single molecule possible. Orrit and coworkers detected, for the first time, using the same molecular system, the fluorescence of a single fluorophore (at low temperature) (10). For most biological applications, more ambient conditions are required: room temperature and solutions in water. Such conditions lead to different spectral properties (absorption and emission bands are often tens of nanometers wide) and quite different instrumentation is required. In 1990, Keller and coworkers were able to detect single Rhodamine-6G (R6G) molecules flowing through a small detection volume (11). This discovery paved the way for the new advancements in methodology described in this part of the book that have made single-molecule fluorescence microscopy to a successful tool to study the ways and means of biomolecules (5, 12, 13).

2. Materials 2.1. Important Properties of Fluorescent Molecules Used for SingleMolecule Methods

Single-molecule fluorescence microscopy at ambient conditions relies on the accurate detection of photons emitted by one or more fluorophores attached to a single biomolecule while, at the same time, limiting the background signal using advanced microscopy techniques. The higher the signal-to-background ratio, the more detailed and clear the information is that can be obtained. Optimization of the signal-to-background ratio is therefore an essential element in single-molecule fluorescence microscopy

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(14). Generally speaking, two approaches can be distinguished. (1) Increasing the signal, by creating the optimal conditions for the fluorophore to emit photons and by increasing the sensitivity and efficiency of photon collection and detection. (2) Decreasing the background, using advanced microscopy techniques that probe only small volumes around the molecule of interest. Under optimized conditions, the signal from a single fluorophore, such as R6G can be detected (11). To provide an idea about the expected fluorescence intensity due to a single R6G, we will make a rough estimation of the number of photons that can be detected when a laser (l ¼ 532 nm), with an intensity of 100 W/cm2, illuminates a single R6G molecule suspended in water. We first have to calculate how many photons are absorbed by the molecule, using its absorption cross section, s, which can be determined from the molecular extinction coefficient, e, of R6G (~100,000 L/mol/cm at 532 nm) using: s¼

2:303e ; NA

(1)

where NA is Avogadro’s constant. Use of this equation yields a cross section of 3.8  10
16 cm2 for R6G (5). Next, we calculate the energy of a single photon: E¼

hc ; l

(2)

with h Planck’s constant, c the velocity of light, and l the excitation wavelength resulting in 3.7  10
19 J/photon. This means that with an illumination intensity of 100 W/cm2 the sample is bombarded by 2.7  1020 photons/s/cm2. Multiplying the photon flux per cm2 (qp) with the absorption cross section of R6G: qa ¼ qp sR6G ;

(3)

we find that every second 1.0  105 photons are absorbed (qa) by a single R6G molecule. From S1, the molecule can relax to the ground state in one of three ways and thus not every photon that is absorbed by R6G leads to fluorescence. The fluorescence quantum yield Фf is the ratio between photons absorbed and photons emitted. For R6G, the fluorescence quantum yield is about 0.45 in water, resulting in an emission rate of 4.5  104 photons/s for a single R6G under the conditions defined above (15). Even with fully optimized instrumentation only about 12% of the emitted photons can be counted by the detector (16). Thus, one can expect a fluorescence photon flux of ~5  103 photons/s from a single R6G fluorophore illuminated with an intensity of 100 W/cm2. R6G is a water-soluble, synthetic fluorophore with properties comparable to other fluorophores widely used in single-molecule microscopy. Below we discuss the

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key properties of a fluorophore relevant for making a proper choice which fluorophore to use for what experiment. 2.2. Important Characteristics of Fluorescent Labels

Nowadays, a large array of different fluorophores exists that can be detected simultaneously to study different single molecules at the same time. Four different classes of fluorescent labels can be distinguished (1) synthetic dyes, such as Cy3, Cy5, R6G, and fluorescein isothiocyanate (FITC), (2) semiconductor nanocrystals, such as quantum dots (QDs), (3) genetically encoded fluorescent labels like eGFP and yellow fluorescent protein (YFP), and (4) natural occurring fluorophores, such as flavin and chlorophyll. Every fluorophore has its own advantages and disadvantages. To determine which fluorophore to use for a certain experiment one has to look at the different fluorophore characteristics. Besides the fluorescence quantum yield and the molecular extinction coefficient, which were already described above, several other characteristics should be considered. Fluorophore excitation and emission wavelengths are the most important and determine the choice of the excitation source and filters. Not all colors are equally apt for single-molecule measurements. Wavelengths below ~450 nm are generally speaking problematic since detectors can be relatively insensitive, microscope optics are often not optimized in this range of the spectrum, and these colors often result in high background signals due to impurities in glass or sample. Another key fluorophore characteristic is the rate of photobleaching. In general, a fluorophore does not survive infinite absorption/ emission cycles. In many cases, there is a certain probability that an absorption/emission cycle leads to an irreversible modification of the fluorophore, resulting in an abrupt loss of its ability to fluoresce called photobleaching. The propensity of a fluorophore to photobleach is expressed in the average number of photons a fluorophore can emit. Photostable synthetic dyes, such as Cy3 and Cy5, can emit 105–106 photons before photobleaching (17), QDs are orders of magnitude more photostable. Fluorescent proteins, such as eGFP, are usually slightly less stable than their optimized, synthetic equivalents (18). Photobleaching is a probability process; in general, the rate of bleaching decreases linearly with decreasing excitation intensity. An important cause of photobleaching is molecular oxygen, which can react with the fluorophore’s triplet to form singlet oxygen. Singlet oxygen in turn is very reactive and can readily react with the fluorophore or surrounding molecules (13). Adding an oxygen scavenger system (a mixture of glucose, glucose oxydase and catalase is often used) to the sample decreases the concentration of molecular oxygen and can help to increase the lifetime of the fluorophores. Addition of antioxidants like Trolox® or ascorbic acid can have additional effect. Other problems with fluorophore photostability include triplet blinking, which can be a problem when the triplet

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lifetime is rather long (>ms). Certain fluorophores show different on–off blinking behavior, for example, fluorescent proteins are known to undergo cis–trans isomerization and intramolecular proton transfer, both resulting in long-lived dark states (18). Another example is the photoblinking of QDs, which is caused by ejection of electrons from the semiconductor core (19). Considering all the fluorophore characteristics mentioned above the ideal single-molecule fluorophore (1) has high fluorescence quantum yield and molecular extinction coefficient, (2) has welldefined excitation and emission wavelengths, (3) shows steady emission intensity (20), (4) can be followed for a long time using high illumination intensity, (5) does not affect the natural behavior of the single molecule, (6) shows no blinking behavior, (7) can be easily attached to the molecule of interest, (8) is soluble in buffers used (21), and (9) its characteristics are well described. 2.3. Fluorophores Used for Single-Molecule Research

Next, we take a closer look at the different classes of fluorescent labels and compare and discuss some of their characteristics important for single-molecule research (Fig. 2). (1) Synthetic

Fig. 2. Structure, size, and spectra of different fluorescent probes used in single-molecule fluorescence microscopy. (a) Chemical structure and absorption/emission spectrum of the synthetic dye rhodamine 6G (R6G). (b) Structure (Protein Databank entry 1S6Z (58)) and absorption/emission spectrum of enhanced Green Fluorescent Protein (eGFP). (c) Schematic representation of a functionalized QD consisting of a core and different shells and corresponding absorption/emission spectrum.

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dyes have been around for decades, are commercially available and constructed to suit the means of use. They are constructed in a way that they contain different reactive groups, such as maleimides or succynimidyl esters, which can be used for attachment of the label to a protein or biomolecule of interest. Succynimidyl esters react with free amino groups, which are available in large quantities on the surface of most proteins. Maleimides or other sulfhydryl reactive probes can be used for more specific labeling of cystein residues, which are generally less abundant. Because synthetic dyes have been around for a long time, their characteristics have been optimized and labeling protocols are widely available. Their small size (~0.5 nm) minimizes the chance of causing steric hindrance to the labeled molecule. Cyanine and rhodamine dyes (Fig. 2a) are most often used for in vitro single-molecule research, in particular Cy3, Cy5, Alexa555 of the cyanine family and R6G and Texas Red of the rhodamine family (20). (2) QDs are very bright fluorophores with a very wide range of absorption wavelengths, narrow (about 10 nm) and symmetric emission bands and quantum yields close to 90% (Fig. 2c) (22, 23). QDs in general consist of a CdSe, CdTe, InP, or InAs core and a ZnS shell. Their size, shape, and structure can be controlled precisely, in order to tune the emission from visible to infrared wavelengths (24, 25). For biological applications, QDs are normally coated to make them hydrophylic or prepare them for specific attachment to the biomolecule of interest (26). Compared to organic dyes, QDs are brighter (molecular extinction coefficients between 105 and 106 L/mol/cm). They are also more photostable and therefore can be followed longer and their position can be determined with higher accuracy (21). However, their size varies between 6 and 60 nm (with coating), which is relatively large in comparison to organic dyes (~0.5 nm). In addition, as mentioned above, they can suffer from on/off blinking on a wide range of time scales (19). (3) Green fluorescent protein (GFP, Fig. 2b) is an autofluorescent protein from the jellyfish Aequorea Victoria, which is very well suited for (but not restricted to) in vivo applications. A key advantage of GFP is that the protein is genetically encoded, does not require a cofactor and that every protein copy can be labeled by fusing its gene with that of GFP (27). Another advantage is that it is less sensitive to its surroundings than many synthetic dyes (28). Disadvantages of GFP are that it is rather large (27 kDa, ~4 nm in diameter), its emission shows blinking behavior and its photostability is substantially less than good synthetic dyes (18). By now, many different variants with different colors, optimized for different organisms have been developed on the basis of the A. Victoria protein and related proteins in other organisms (29). A very exciting recent development is the generation of photoactivatable and photoswitchable fluorescent proteins that are very well suited for superresolution methods like PALM (30). (4) Biological

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materials also contain naturally occurring fluorescent molecules. Many of these (such as tryptophan and NADH), which are widely used in bulk fluorescence measurements, are not photostable enough and absorb and emit too far in the ultraviolet to allow single-molecule detection. Protein cofactors, such as chlorophyll and flavin, can be very fluorescent and have been used for in vitro applications (31, 32). Their occurrence is however limited to a small subset of proteins, which hinders general application.

3. Methods 3.1. Microscopic Detection of Single Fluorophores

Single, fluorescently labeled particles can be detected using a fluorescence microscope. The main components of such a microscope are an illumination source for excitation of the fluorophores, filters to extract light of wanted colors and suppress unwanted light, an objective to direct the excitation light and efficiently collect the emission light, and a detector. Since much of the emitted light is lost in the detection pathway and the total number of photons that a fluorophore can emit is restricted due to photobleaching, it is imperative in single-molecule fluorescence studies to use optimal components in each part of the instrument. In the next section, we discuss the different parts of a fluorescence microscope in more detail.

3.1.1. Light Sources

To maximize the signal obtained from a single fluorophore, it is essential to excite it with a wavelength close to its absorption maximum. In bulk fluorescence microscopy often broad-band sources, such as metal halide or mercury arc lamps, are used (33). A key advantage of these sources is that they are broad-band and contain several intense spectral lines. This allows them to be used to excite spectrally distinct fluorophores, with the proper excitation filters to suppress unwanted lamp light. Relatively new on the market are LED sources, which are more monochromatic than lamps (spectra with a width of several tens of nanometers). LEDs are much more energy efficient and thus produce less heat. In single-molecule applications, in most cases, lasers are used for fluorescence excitation since they emit monochromatic and collimated light, allowing better separation of excitation from fluorescence light and a more straightforward construction of complex optical paths using mirrors, lenses, filters, polarizers, etc. In addition, collimated laser beams can be focused to diffraction limited spots (see below), which is indispensable for confocal fluorescence microscopy. Apart from cost, there are two key disadvantages of lasers. (1) Laser beams are Gaussian and this can result in uneven excitation intensity profiles. (2) Lasers are in many cases monochromatic meaning that for

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each spectrally distinct fluorophore an additional laser needs to be purchased and installed. 3.1.2. Filters and Dichroic Mirrors

Optical filters are used to separate fluorescence light from scattered excitation light and other background signals. On the basis of their transmission spectra two classes of filters can be discerned: edge filters and band-pass filters. Edge filters transmit light above (long-pass) or below (short-pass) a specific wavelength, and block the other light. Band-pass filters transmit only a narrow range of wavelengths and block wavelengths on either side of this range. The performance of the filters depends on three aspects: the percentage of transmission of the desired light, the optical density in the blocked region of the spectrum, and the steepness of the edges between the transmitted and blocked regions (14). In the past, filters were based on stained glass, which often suffered from considerable autofluorescence. Later, thin film interference filters, consisting of repetitive, thin layers evaporated on a surface were developed with substantially better performance and flexibility. Recently, new technologies to make precise thin layers based on ion-beam sputtering have further improved filter performance. Nowadays, filters that are designed for simultaneous excitation and/or detection of several, spectrally distinct fluorophores are available. A typical fluorescence microscope consists of three optical filters. (1) The excitation filter that selects one line or band from excitation source to illuminate the sample. In many cases, the use of an excitation filter is not required when using lasers. (2) A dichroic beam-splitting mirror that reflects excitation light in the direction of the objective, but transmits fluorescence light collected by the objective. (3) The emission filter that is used to select for an emission band and block any residual excitation light. In principle, for each light source and dye combination a separate combination of these filters needs to be used.

3.1.3. Detectors in SingleMolecule Fluorescence Microscopy

In single-molecule fluorescence methods, the number of photons emitted is very limited, putting forward strong demands on the quantum efficiency and noise characteristics of detectors used. Broadly speaking, two distinct classes of detectors can be used, depending on the imaging modality (see below) (14, 34). (1) Point detectors, such as avalanche photodiodes (APD) and photomultipliers, which do not provide position information but are capable of counting single photons with high time resolution. APDs have high quantum efficiency, but a small active area, which makes alignment tedious. Photomultipliers usually have a lower quantum efficiency and worse dark noise characteristics, but a larger active area. For single-molecule applications, photomultipliers are usually only used in the blue part of the spectrum, where APDs perform poorly. In general, point detectors are used in

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confocal instruments or when time resolution is important. Key applications are in burst analysis of diffusing molecules, for example, in fluorescence correlation spectroscopy (FCS) (35, 36) or in FCS-like experiments (37). (2) Array detectors, such as charged coupled devices (CCDs) are the most widely used detectors in wide-field fluorescence microscopy. CCD detectors are twodimensional array detectors that can be read out in one of three ways, full-frame, frame-transfer, or interline-transfer. The latter two are fast and allow for continuous detection. Limitations of CCD detectors are read-out noise due to analog-to-digital conversion (a problem solved in modern electron multiplying CCDs) and the relatively slow speed: an entire frame is integrated and read out. For single-molecule detection, frame rates up to ~100 per second can be reached. Key advantages are the almost unity quantum efficiency (in the visible) and the very low dark currents. These detectors are, therefore, optimally suited in conditions when acquisition times of down to ~10 ms are sufficient (38). 3.1.4. Microscope Objectives

The key optical element in a fluorescence microscope is the objective. The objective concentrates the excitation light in the sample and collects the emitted light. In principle, an objective is nothing more than a strong lens, but in order to fulfill its tasks it needs to be highly corrected for optical aberrations, which can only be achieved by complex designs involving multiple optical elements. Important properties with respect to single-molecule experiments are the magnification, which determines the size of the field of view and the number of pixels over which a single fluorescent particle is imaged and the numerical aperture (NA), which is a measure of the angle over which photons can be detected, defined as (33): NA ¼ n sin ymax :

(4)

With n is the refractive index of the medium between the sample and the objective, and ymax is the maximum half-angle of the collection cone of the objective. A fluorophore emits light in all directions and to maximize the collected light the NA of the objective should be as high as possible. This may be achieved by using an objective designed to be immersed in a high-n medium (14, 39). Furthermore, the NA is not only important for collection efficiency, but it also determines the resolution of the optical system, as is discussed in the next section. 3.1.5. The Resolution of a Fluorescence Microscope

A fluorescent molecule is much smaller than the wavelength of visible light and after excitation the molecule emits photons in random direction. Using a single microscope objective, it is impossible to collect light emitted in all directions and consequently only a fraction of the emitted photons can be collected. The circular apertures of the microscope optics (in particular the

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objective) result in diffraction of the transmitted light, which causes the fluorescent particle not being imaged as an infinitely small point, but as an Airy disk, with a finite width and side lobes. A three-dimensional representation of this diffraction pattern is referred to as the point spread function (PSF). The diameter (d) of the PSF only depends on the NA of the objective and the wavelength of the light (l) (33): d¼

1:22l : 2NA

(5)

The width of the PSF is also a measure of the resolution of the optical system: when the distance between two closely spaced point sources is less than d, the images of the sources overlap and their peaks cannot be resolved. This definition of the resolution is called the Rayleigh criterion (33). For a typical fluorescence microscope (NA ¼ 1.4, l ¼ 505 nm), the resolution is ~220 nm. 3.2. Key Imaging Modalities in Fluorescence Microscopy 3.2.1. Confocal Fluorescence Microscopy

In confocal fluorescence microscopy, the sample is illuminated with a diffraction limited spot and an image is acquired by moving this spot over the sample (Fig. 3a). To this end, a collimated laser beam is coupled in the microscope objective, resulting in a tightly focused spot with a diameter of typically 200–300 nm, ruled by the same effects of diffraction as discussed above. The fluorescence resulting in the focus is collected by the objective, separated from the excitation beam by a dichroic mirror and further spectrally filtered by an emission filter. In addition, the fluorescence light is

Fig. 3. Schematic representation of the three most common microscope designs used in single-molecule fluorescence microscopy. (a) Confocal setup. (b) Epi-wide field setup. (c) TIRF-wide field setup. A zoom of the excitation path, the laser is coupled off-axis into the objective. The laser is reflected on the glass-water interface and creates an exponentially decaying evanescent wave in the sample. Ex is Excitation source, L lens, O objective, E emission filter, D Dichroic mirror, and A confocal aperture.

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spatially filtered with a pinhole before being detected with a point detector (APD or photomultiplier). The pinhole increases spatial resolution, but its key purpose is to suppress out-of-focus background signal, allowing optical sectioning. To create an image, scanning of the beam (using galvanic mirrors) or the sample (using a piezo stage) is required. In single-molecule experiments, excitation intensities need to be reduced to avoid saturation or limit photobleaching, resulting in rather long image acquisition times. Consequently, the most important single-molecule application of confocal microscopy is to study molecules freely diffusing in and out the confocal spot and FCS. 3.2.2. Wide-Field Epifluorescence Microscopy

In wide-field epifluorescence microscopy, the excitation beam is not tightly focused to a diffraction-limited spot in the sample plane, but illuminates a substantially larger area (Fig. 3b). The fluorescence arising from this illuminated area can be detected with an array detector, such as a CCD camera. Uniform illumination throughout the sample can be obtained by focusing the excitation beam in the back-focal plane of the objective. In case of a laser, this results in a collimated, Gaussian-shaped beam illuminating the sample. Filters and dichroic mirrors are applied in exactly the same way as confocal fluorescence microscopy. Single-molecule wide-field fluorescence microscopy is particularly useful when molecules are moving in the sample or when a time resolution of ~100 Hz is sufficient. As discussed above, modern CCD cameras are superior with respect to dark noise and quantum efficiency, compared to point detectors used in confocal microscopy. In addition, wide-field fluorescence microscopes are optically simpler and often require less frequent and precise alignment (14).

3.2.3. Total Internal Reflection Fluorescence Microscopy

As discussed above, wide-field approaches have, in certain cases, advantages over confocal approaches, at the cost of time resolution and worse suppression of out-of-focus background fluorescence than in confocal microscopy. This latter problem is addressed in total internal reflection fluorescence microscopy (TIRF), in which the evanescent wave resulting from a totally internally reflected laser beam is used for fluorescent excitation. The evanescent wave, generated by reflection on a glass water interface, penetrates into the medium with lower refractive index (the water) and its intensity I drops exponentially with distance (z) into the low-index medium (40):
z I ðzÞ ¼ I0 exp ð Þ: d

(6)

With I0 the intensity at the surface and d the decay constant. The decay constant of the intensity of the evanescent wave is on the order of 100 nm, depending on the angle of incidence and the

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refractive indices of glass and medium. To obtain total reflection and generate an evanescent wave, the angle of incidence of the laser beam impinging on the glass/water interface needs to be larger than the critical angle (yc): yc ¼ arcsinðn1 =n2 Þ;

(7)

where n1 and n2 are the refractive indexes of water and glass, respectively. At the glass-water interface, the internal reflection is achieved at an yc of 61 . These high angles of incidence are usually obtained in one of two ways: (1) by using a prism, coupled to the coverslip on the side of the sample opposite to the objective. (2) By using an objective with NA higher than 1.45 and coupling in the laser beam off axis, on the edge of the entrance pupil (41) (Fig. 3c). The key advantage of TIRF microscopy is that only fluorophores close to the interface will be excited and fluorophores deeper in the sample will not, resulting in a reduced background. Disadvantages of TIRF microscopy are that the excitation intensity strongly depends on the depth in the sample, making comparison of fluorescence intensities difficult and that the polarization of the evanescent wave is complex.

4. Measurables 4.1. Counting the Number of Fluorescent Molecules Within a Diffraction-Limited Spot

So when an instrument is built and a sample prepared, how does one know one is looking at a single molecule? Observation of a single diffraction-limited spot is not enough: the Rayleigh criterion tells us that when particles are too close, they cannot be resolved and are imaged as a single spot. The most straightforward signature of fluorescence arising from a single fluorophore is stepwise photobleaching: the intensity is for a while rather constant, until photobleaching occurs and the signal abruptly drops to the background level. Another signature is the intensity, which should be constant from molecule to molecule; however, orientation or polarization effects can substantially modulate fluorescence intensity (see below). If the intensity of a fluorescent spot is due to more than one fluorophore, the number of fluorophores can be determined in two ways. (1) By comparing the fluorescence intensity of the spot to the average value of single fluorophores (Fig. 4a). To correct for possible bleaching within the first frame, the intensity at t ¼ 0 can be extrapolated by fitting an exponential decay to the fluorescence intensity profile over time (42). (2) One can also determine the number of fluorophores by counting the number of bleaching steps. This approach has, for example, been used to determine the number of Ase1p dimers incorporated in multimers bound to microtubules (43). On the other hand, at conditions when photobleaching is negligible the

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Fig. 4. Measurable parameters in single-molecule fluorescence microscopy. (a) The number of fluorophores within a fluorescent spot, even though they are not resolvable, can be deduced from the intensity of that spot. (b) Localization of single fluorophores. The fluorophores are imaged as Airy disks, which can be approximated with a 2D Gaussian. The limit in which two neighboring fluorophores can still be resolved is described by Rayleigh criterion. (c) Colocalization is achieved by using labels with different colors. By imaging both color channels simultaneously on a CCD camera, the precise localization of both fluorophores can be determined. (d) FRET reports on the distance between two spectrally distinct dyes, and can be used to study for example intramolecular conformational changes. When the distance between the dyes is in the order of tens of A˚ (20 A˚ < r < 90 A˚), the energy can get transferred from the donor (D) to the acceptor (A) causing an increase in acceptor signal. When the distance between the dyes is large (r > 90 A˚), no energy transfer occurs and the acceptor signal will be low. (e) Fluorescence polarization reports on orientation or orientational dynamics. Circular polarized light can be used to excite dyes in all orientations. Subsequently, the emitted light is filtered for a specific polarization.

changes in numbers of molecules due to association or dissociation can be measured. This approach has been used to determine the number of Rad51 monomers disassembling from DNA in a single burst (44). 4.2. Localization of Single Molecule

We have seen above that the resolution of a fluorescence microscope is limited by diffraction, to about half the wavelength of the emitted light. The resolution is a measure for how close two point sources can be to be still resolvable (Fig. 4b), it does not restrict the accuracy with which the location of a single point source can

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be determined. By fitting the resulting image with the PSF (often an approximation with a Gaussian is sufficient), the location of the maximum of the image can be determined with far greater accuracy than the width of the PSF. This method is frequently used in single particle tracking (SPT) (38, 45). Given the noise encountered in most single-molecule experiments a PSF of the microscope with a full width at half maximum of ~1.5–2 pixel yields best results for the accuracy (46). The uncertainty in the localization of a point source (Dx) depends on the size of the pixels (a), the number of photons (N), the background noise (b), the standard deviation of the PSF (s) (46, 47): D E s 2 ða 2 =12Þ 8ps 4 b 2 ðDx Þ2 ¼ þ þ 2 2 : (8) N N a N The first term represents the photon counting noise (s2/N), the second term represents pixilation noise arising from the uncertainty of where in the pixel the photon arrived ((a2/12)/N). The final term is due to background noise. Under typical single-molecule fluorescence conditions, position accuracies down to about 2 nm can be achieved (47). 4.3. Detection of Motion of Single Molecules

Given this high localization accuracy, the positions of an emitting fluorophore can be determined in each image from a time stack of images and subsequently a trajectory can be reconstructed by connecting the positions. Using this approach, the motion of single-molecules can be accurately determined. Care has to be taken that the motion of the molecules are not too large within the acquisition time of an image, since this can smear out the Gaussian intensity profile, complicating fitting. This problem can be avoided by using short acquisition times and increasing the excitation intensity, at the cost of enhanced photobleaching. It is important in single-molecule tracking to find the proper balance between movement of a particle within the acquisition time, and the total number of time points (frames) over which the particle is observed (48). Motion of biomolecules can be directional (for example driven by motor proteins) or diffusive (like membrane proteins). To analyze the precise nature of mobility, often the mean square displacement (MSD) is calculated as a function of time. Motion with constant speed (and direction) leads to an MSD that increases with the square of time while diffusive motion results in a linear increase of the MSD with time. The localization uncertainty leads to a constant offset in the MSD, due to its timeindependence (38, 49). The MSD analysis was, for example, used to show that, depending on the exact conditions, the motor protein kinesin-5 can switch between different mode of motility, diffusion, and directed motion (50).

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4.4. Colocalization of Fluorescent Molecules

One of the key interests in (cell) biology is to resolve which proteins interact and how. To this end, proteins of interest can be labeled with differently colored fluorophores (51–53). Subsequently, the different dyes can be excited by the appropriate lasers and the fluorescence signal can be separated in two or more wavelength channels and detected independently using different cameras or side-by-side on one. In this way, different biomolecules can be tracked simultaneously and their motion can be correlated to resolve whether they move independently or interact (part of the time) (Fig. 4c). High-resolution colocalization was applied to show myosin V’s alternating heads while it walked hand-over-hand along an actin filament (53).

4.5. Fo¨rster Resonance Energy Transfer

Positions and distances of single fluorophores can be determined with an accuracy that is substantially smaller than the diffraction limit using PSF fitting (see above). This approach is very powerful, but has its limitations, in particular in its poor time resolution and its inability to resolve multiple molecules that are closer than the optical resolution, without photobleaching them. An excellent method to measure relative distances and changes on a length scale of ~2–9 nm is Fo¨rster resonance energy transfer (FRET) (Fig. 4d). In FRET, two spectrally distinct fluorophores are used. One, with the highest energy excited state, is excited and serves as donor, the other as acceptor. When the two fluorophores are close and their dipoles oriented favorably, dipole–dipole coupling can occur and excitations can be transferred from donor to acceptor. The distance dependency of the FRET efficiency (E ) is: E¼

1 1 þ ðR=R0 Þ6

(9)

with R the distance between donor and acceptor and R0 the Fo¨rster distance. The Fo¨rster distance is defined as the distance at which half the fluorescence of the donor is transferred to the acceptor. The Fo¨rster distance depends on the overlap of the emission spectrum of the donor with the absorption spectrum of the acceptor, the relative orientation of donor and acceptor dipole moments and the fluorescence quantum yield of the donor. It has a typical value of about 5 nm (5). FRET has proven to be a valuable tool to study conformational dynamics in nucleic acids and proteins. Examples are the folding of ribozymes (54) and the observation of conformational dynamics in kinesin-1 (55). 4.6. Fluorescence Polarization

Another way to measure conformational dynamics of single biomolecules is to use the polarization of the fluorescence signal. Absorption and emission are governed by the interaction of the absorption and emission transition dipole moments of the chromophore, which are vectors, with the electric component of the electromagnetic light field, also a vector. Using polarized light for excitation and/or a polarizer in the emission path allows

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obtaining the orientation and dynamics of the transition dipole moment. Care needs to be taken that the fluorophore is not free to rotate with respect to the biomolecule of interest, but that its orientation is tightly linked to that of the biomolecule. This can be achieved by using bisfunctional fluorophores that are connected with two chemical links to the protein or nucleic acid of interest (56). One way of determining dipole orientations on the single-molecule level is to excite with circular polarized light and to split the resulting fluorescence in two perpendicular linear polarized signals, detected with two APDs or side-by-side on a CCD chip (Fig. 4e). Another way is to detect without polarizers, but to use alternating (linear) polarization of the excitation light. If one combines polarized excitation with polarized detection, a separation can be obtained of the depolarization due to rapid fluorophore orientation (on the nanosecond scale) and much slower conformational changes. Polarization methods have, for example, been applied to study the conformational changes occurring during stepping of the kinesin-1 motor protein (57).

5. Concluding Remarks Here, we have provided a short and broad overview of the wealth of single-molecule fluorescence approaches and their backgrounds. These tools have become indispensible in the study of diverse processes, such as the active and diffusive motion of biomolecules, their conformational changes, and their assembly and disassembly. In the following Chapters 6 to 10, several approaches are discussed in more depth, including detailed protocols. References 1. Stokes, G. G. (1852) On the Change of Refrangibility of Light, Philosophical Transactions of the Royal Society of London 142, 463–562. 2. Herschel, J. F. W. (1845) No. I. On a Case of Superficial Colour Presented by a Homogeneous Liquid Internally Colourless, Philosophical Transactions of the Royal Society of London 135, 143–145. 3. Herschel, J. F. W. (1845) No. II. On the Epipolic Dispersion of Light, Being a Supplement to a Paper Entitled, “On a Case of Superficial Colour Presented by a Homogeneous Liquid Internally Colourless”, Philosophical Transactions of the Royal Society of London 135, 147–153. 4. Brewster, D. (1846) On the decomposition and dispersion of light within solid and fluid

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Quantum dots versus organic dyes as fluorescent labels, Nature Methods 5, 763–775. 22. Alivisatos, A. P. (1996) Semiconductor clusters, nanocrystals, and quantum dots, Science 271, 933–937. 23. Kaji, N., Tokeshi, M., and Baba, Y. (2007) Single-molecule measurements with a single quantum dot, Chemical Record 7, 295–304. 24. Alivisatos, P. (2004) The use of nanocrystals in biological detection, Nature Biotechnology 22, 47–52. 25. Gao, X. H., Yang, L. L., Petros, J. A., Marshal, F. F., Simons, J. W., and Nie, S. M. (2005) In vivo molecular and cellular imaging with quantum dots, Current Opinion in Biotechnology 16, 63–72. 26. Michalet, X., Pinaud, F. F., Bentolila, L. A., Tsay, J. M., Doose, S., Li, J. J., Sundaresan, G., Wu, A. M., Gambhir, S. S., and Weiss, S. (2005) Quantum dots for live cells, in vivo imaging, and diagnostics, Science 307, 538–544. 27. Chalfie, M., Tu, Y., Euskirchen, G., Ward, W. W., and Prasher, D. C. (1994) Green Fluorescent Protein as a Marker for GeneExpression, Science 263, 802–805. 28. Giepmans, B. N. G., Adams, S. R., Ellisman, M. H., and Tsien, R. Y. (2006) Review - The fluorescent toolbox for assessing protein location and function, Science 312, 217–224. 29. Shaner, N. C., Steinbach, P. A., and Tsien, R. Y. (2005) A guide to choosing fluorescent proteins, Nature Methods 2, 905–909. 30. Patterson, G. H., and Lippincott-Schwartz, J. (2002) A photoactivatable GFP for selective photolabeling of proteins and cells, Science 297, 1873–1877. 31. Lu, H. P., Xun, L. Y., and Xie, X. S. (1998) Single-molecule enzymatic dynamics, Science 282, 1877–1882. 32. Rutkauskas, D., Novoderezhkin, V., Cogdell, R. J., and van Grondelle, R. (2005) Fluorescence spectroscopy of conformational changes of single LH2 complexes, Biophysical Journal 88, 422–435. 33. Murphy, D. B. (2001) Fundamentals of light microscopy and electronic imaging, Wiley-Liss, Inc. 34. Michalet, X., Siegmund, O. H. W., Vallerga, J. V., Jelinsky, P., Millaud, J. E., and Weiss, S. (2007) Detectors for single-molecule fluorescence imaging and spectroscopy, Journal of Modern Optics 54, 239–281. 35. Magde, D., Elson, E. L., and Webb, W. W. (1974) Fluorescence Correlation Spectroscopy .2. Experimental Realization, Biopolymers 13, 29–61. 36. Eigen, M., and Rigler, R. (1994) Sorting Single Molecules - Application to Diagnostics

5 A Brief Introduction to Single-Molecule Fluorescence Methods and Evolutionary Biotechnology, Proceedings of the National Academy of Sciences of the United States of America 91, 5740–5747. 37. Verbrugge, S., Kapitein, L. C., and Peterman, E. J. G. (2007) Kinesin moving through the spotlight: Single-motor fluorescence microscopy with submillisecond time resolution, Biophysical Journal 92, 2536–2545. 38. Anderson, C. M., Georgiou, G. N., Morrison, I. E. G., Stevenson, G. V. W., and Cherry, R. J. (1992) Tracking of Cell-Surface Receptors by Fluorescence Digital Imaging Microscopy Using a Charge-Coupled Device Camera Low-Density-Lipoprotein and InfluenzaVirus Receptor Mobility at 4-Degrees-C, Journal of Cell Science 101, 415–425. 39. Hecht, E. (1998) Optics, third edition. 40. Dickson, R. M., Norris, D. J., Tzeng, Y. L., and Moerner, W. E. (1996) Three-dimensional imaging of single molecules solvated in pores of poly(acrylamide) gels, Science 274, 966–969. 41. Axelrod, D. (2001) Total internal reflection fluorescence microscopy in cell biology, Traffic 2, 764–774. 42. Leake, M. C., Greene, N. P., Godun, R. M., Granjon, T., Buchanan, G., Chen, S., Berry, R. M., Palmer, T., and Berks, B. C. (2008) Variable stoichiometry of the TatA component of the twin-arginine protein transport system observed by in vivo single-molecule imaging, Proceedings of the National Academy of Sciences of the United States of America 105, 15376–15381. 43. Kapitein, L. C., Janson, M. E., van den Wildenberg, S., Hoogenraad, C. C., Schmidt, C. F., and Peterman, E. J. G. (2008) Microtubule-Driven Multimerization Recruits ase1p onto Overlapping Microtubules, Current Biology 18, 1713–1717. 44. van Mameren, J., Modesti, M., Kanaar, R., Wyman, C., Peterman, E. J. G., and Wuite, G. J. L. (2009) Counting RAD51 proteins disassembling from nucleoprotein filaments under tension, Nature 457, 745–748. 45. Schmidt, T., Schutz, G. J., Baumgartner, W., Gruber, H. J., and Schindler, H. (1996) Imaging of single molecule diffusion, Proceedings of the National Academy of Sciences of the United States of America 93, 2926–2929. 46. Thompson, R. E., Larson, D. R., and Webb, W. W. (2002) Precise nanometer localization analysis for individual fluorescent probes, Biophysical Journal 82, 2775–2783. 47. Yildiz, A., and Selvin, P. R. (2005) Fluorescence imaging with one manometer accuracy:

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Application to molecular motors, Accounts of Chemical Research 38, 574–582. 48. Saxton, M. J. (1997) Single-particle tracking: The distribution of diffusion coefficients, Biophysical Journal 72, 1744–1753. 49. Gross, D., and Webb, W. W. (1986) Molecular Counting of Low-Density-Lipoprotein Particles as Individuals and Small Clusters on CellSurfaces, Biophysical Journal 49, 901–911. 50. Kwok, B. H., Kapitein, L. C., Kim, J. H., Peterman, E. J. G., Schmidt, C. F., and Kapoor, T. M. (2006) Allosteric inhibition of kinesin-5 modulates its processive directional motility, Nature Chemical Biology 2, 480–485. 51. Lacoste, T. D., Michalet, X., Pinaud, F., Chemla, D. S., Alivisatos, A. P., and Weiss, S. (2000) Ultrahigh-resolution multicolor colocalization of single fluorescent probes, Proceedings of the National Academy of Sciences of the United States of America 97, 9461–9466. 52. Agrawal, A., Deo, R., Wang, G. D., Wang, M. D., and Nie, S. M. (2008) Nanometer-scale mapping and single-molecule detection with color-coded nanoparticle probes, Proceedings of the National Academy of Sciences of the United States of America 105, 3298–3303. 53. Churchman, L. S., Okten, Z., Rock, R. S., Dawson, J. F., and Spudich, J. A. (2005) Single molecule high-resolution colocalization of Cy3 and Cy5 attached to macromolecules measures intramolecular distances through time, Proceedings of the National Academy of Sciences of the United States of America 102, 1419–1423. 54. Zhuang, X. W., Bartley, L. E., Babcock, H. P., Russell, R., Ha, T. J., Herschlag, D., and Chu, S. (2000) A single-molecule study of RNA catalysis and folding, Science 288, 2048–2051. 55. Mori, T., Vale, R. D., and Tomishige, M. (2007) How kinesin waits between steps, Nature 450, 750–715. 56. Corrie, J. E. T., Craik, J. S., and Munasinghe, V. R. N. (1998) A homobifunctional rhodamine for labeling proteins with defined orientations of a fluorophore, Bioconjugate Chemistry 9, 160–167. 57. Asenjo, A. B., and Sosa, H. (2009) A mobile kinesin-head intermediate during the ATPwaiting state, Proceedings of the National Academy of Sciences of the United States of America 106, 5657–5662. 58. Rosenow, M. A., Huffman, H. A., Phail, M. E., and Wachter, R. M. (2004) The crystal structure of the Y66L variant of green fluorescent protein supports a cyclization-oxidationdehydration mechanism for chromophore maturation, Biochemistry 43, 4464–4472.

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Chapter 6 Fluorescent Labeling of Proteins Mauro Modesti Abstract Many single-molecule experimental techniques exploit fluorescence as a tool to investigate conformational dynamics and molecular interactions or track the movement of proteins in order to gain insight into their biological functions. A prerequisite to these experimental approaches is to graft one or more fluorophores on the protein of interest with the desired photophysical properties. Here, we present detailed procedures for the current most efficient methods used to covalently attach fluorophores to proteins. Alternative direct and indirect labeling strategies are also described. Key words: Fluorescence, Fluorophore, Maleimide, Cys light, NHS ester, Lys light, RAD51, RPA, HOP2/MND1, RecA, hSSB

1. Introduction The design of fluorescence-based single-molecule experiments requires choosing an optimal fluorophore as marker to monitor a particular protein activity. Tryptophan intrinsic fluorescence emission can be very useful to study the folding, conformational dynamics, and interactions of a protein. However, since quartz optics are required, complicated photophysical properties and many proteins lack tryptophan residues; the choice of tryptophan as a fluorophore is often unpractical for single-molecule experimental techniques. Thus, attaching an “extrinsic” fluorophore moiety to the protein of interest is the most frequent route used to make the protein glow. One approach commonly used for in vivo experiments is to generate a chimer of the protein of interest by fusion to an intrinsically fluorescent protein that fluoresces in the visible/near infrared range of the electromagnetic spectrum. Collections of intrinsically fluorescent proteins exist, such as the jellyfish green fluorescent protein (GFP) and its variants that can be attached by genetic engineering to either the Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_6, # Springer Science+Business Media, LLC 2011

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amino or the carboxyl terminus of a protein or even inserted in frame internally to the protein (1). These protein-based fluorophores are very useful for in vitro experiments as well, but they are relatively bulky and can perturb the original protein function. In addition, their photophysical properties are complex and influenced by pH, ionic strength, or any factors affecting protein folding. Instead of fusing such an intrinsic fluorescent protein, small synthetic fluorescent organic compounds can covalently be attached to the protein of interest. A large number of small fluorophores, including ATTO dyes, CF dyes, cyanine dyes, HiLyte Fluors, Alexa Fluors, or DyLight Fluors, have been developed and are commercially available. These small, photostable, and bright fluorophores are generally much less sensitive to buffer conditions as compared to intrinsically fluorescent proteins. Moreover, the chemical and photophysical properties of these small fluorophores are usually well-defined, which allows selection of the dye with the most optimal properties for a given single-molecule application. In a fluorescence correlation spectroscopy experiment, for example, a dye with high quantum yield, weak nonspecific binding to the protein of interest, and resistant to irreversible photobleaching and to triplet state excitation can be optimally selected. Or, if the application requires detection and visualization of a single fluorophore, one would want to select a dye with reduced blinking behavior. Most of these chemical dyes can be purchased in a “functionalized” form with a reactive group for specific covalent attachment to proteins on, for instance, the –SH group of cysteine residues or the –NH2 group of lysine residues. In this chapter, we describe procedures for labeling proteins with such functionalized fluorophores, as well as alternative procedures. The presentation of these protocols is intended to guide researchers in biophysics that do not have much experience with protein handling. Each method is illustrated with an example from our laboratory not only to show to the reader how results should look like, but also to highlight commonly encountered problems and drawbacks when using these procedures.

2. Materials 2.1. Buffers and Solutions

1. 0.5 M MES–NaOH, pH 6.2. 2. 0.5 M MOPS–NaOH, pH 7.0. 3. 1 M Tris–HCl, pH 7.5; 1 M Tris–HCl, pH 8.0. 4. 1 M HEPES–NaOH, pH 8.2. 5. 2 M imidazole–HCl, pH 7.5, stored at dark at +4
C.

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6. 0.5 M EDTA–NaOH, pH 8.0. 7. IPTG dissolved in water at 1 M and stored at 20
C. 8. 1 M DTT freshly prepared as a solution in water. 9. 5 M NaCl. 10. 3 M KCl. 11. Anhydrous DMSO stored at +4
C in a desiccator. 12. Glycerol. 13. SDS 20% (w/v). 14. ß-mercaptoethanol. 15. Coomassie Brilliant Blue R-250. 16. Ampicillin sodium salt, solution at 100 mg/ml in water, store at 20
C. 17. Chloramphenicol, solution made at 34 mg/ml in ethanol, store at 20
C. 18. Storage buffer A: 0.3 M KCl, 20 mM Tris–HCl, pH 8, 1 mM DTT, 0.5 mM EDTA, and 10% glycerol. 19. Labeling buffer A: 0.5 M NaCl, 50 mM MOPS–NaOH, pH 7, 0.5 mM EDTA, and 10% glycerol. 20. Storage buffer B: 0.5 M KCl, 20 mM Tris–HCl, pH 8, 1 mM DTT, 0.5 mM EDTA, and 10% glycerol. 21. Labeling buffer B: 0.5 M NaCl, 50 mM HEPES–NaOH, pH 8.2, 0.5 mM EDTA, and 10% glycerol. 22. Labeling buffer C: 1 M NaCl, 50 mM MOPS–NaOH, pH 7, 0.5 mM EDTA, and 10% glycerol. 23. PBS: 137 mM NaCl, 2.7 mM KCl, 4.3 mM Na2HPO4, and 1.47 mM KH2PO4. Adjust to pH 7.4 with NaOH. 24. 2 lysis buffer: 1 M NaCl, 40 mM Tris–HCl, pH 7.5, 4 mM bmercaptoethanol, 10 mM imidazole, pH 8, and 20% glycerol. 25. Buffer R: 50 mM KCl, 20 mM Tris–HCl, pH 7.5, 1 mM DTT, 0.5 mM EDTA, and 10% glycerol. 26. Protein sample buffer: 2% w/v SDS, 62.5 mM Tris–HCl, pH 6.8, 25% glycerol, 0.01% w/v bromophenol blue, and 0.72 M ß-mercaptoethanol. 27. Staining solution: 10% ethanol, 7% acetic acid, and 1 g/L Coomassie Brilliant Blue R-250. 28. Destaining solution: 10% ethanol and 7% acetic acid. 2.2. Dyes

Alexa Fluor dyes (Invitrogen) and ATTO dyes (Sigma-Aldrich) are dissolved in anhydrous DMSO and used immediately.

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2.3. SDS-PAGE

1. Precast NuPAGE Bis-Tris Gels with MOPS running buffer (Invitrogen). 2. Prestained Precision Plus Protein Standards (BIO-RAD).

2.4. Columns

1. Econo-Pac 10DG columns (BIO-RAD). 2. PD SpinTrap G-25, HisTrap FF, HiTrap Q HP, and HiTrap Heparin HP columns (GE Healthcare).

2.5. Media and Bacterial Expression

Rosetta/pLysS cells (Novagen) were used as host for inducible expression of hRPA-eGFP. Cells were grown in LB broth (bactotryptone 10 g/L, yeast extract 5 g/L, NaCl 10 g/L) supplemented with antibiotics as indicated.

3. Methods The “Cys light” and “Lys light” methods for covalent attachment of small organic fluorophores to proteins are described. Alternative labeling procedures are presented that can be used in case the latter two methods fail to yield suitable reagents. Each method is illustrated with an example from our laboratory, highlighting commonly encountered problems when using these methods. We describe means to analyze the extent and the specificity of the labeling reaction. Importantly, whatever the labeling method used, it is essential to verify that the original activity of the protein has not been altered by the labeling procedure. 3.1. The Cys Light Method: Labeling of the hHOP2–MND1 Protein Complex

The maleimide chemical group reacts with the –SH group (thiol) of cysteine residues of proteins to form a covalent thioether bond (see Note 1). Because of the high specificity and efficiency of this reaction, the functionalization of organic fluorescent compounds with a maleimide group has developed as the method of choice over other –SH reactive groups, such as iodoacetamide. A large selection of organic fluorophores functionalized with a maleimide group is available commercially. Below, we present a modification of the labeling method recommended by Molecular Probes but adapted to the labeling of the hHOP2–hMND1 protein complex on cysteine residues. The hHOP2 and hMND1 proteins form a heterodimeric complex (2). Each protein contains three cysteine residues. The lack of three-dimensional structural information does not allow prediction of the surface-exposed cysteine residues of the complex. Since the focus of this chapter is on protein labeling procedures and not purification methods, we assume that the researcher has access to a source of purified protein. For all procedures, work on ice or in the cold as much as possible and avoid exposure to light when handling fluorophores.

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1. To ensure that surface-exposed cysteines are in a reduced form and reactive toward the maleimide group, freshly prepared DTT (see Note 2) is added to a final concentration of 20 mM to 3 ml of the protein solution at a concentration of 2 mg/ml in storage buffer A and incubated on ice for 30 min. 2. After reduction, the protein sample is buffer exchanged (see Note 3) into deoxygenated labeling buffer A (see Notes 4 and 5) and finally recovered into 4 ml. 3. Alexa Fluor 488 C5 maleimide (or Alexa Fluor 546 C5 maleimide) is dissolved in anhydrous DMSO (see Note 6) and immediately added to the protein solution at fivefold molar excess of dye over the protein (see Note 7). From this step on, protect the sample from exposure to light as much as possible using aluminum foil. The dye solution should be added rapidly drop by drop while stirring the solution with a small magnetic bar to avoid local concentration effects. The reaction mixture is left to incubate at +4
C for 2 h with stirring. 4. At the end of the reaction, DTT is added to 10 mM final concentration and further incubated for 30 min to quench the excess reactive dye. 5. The volume is brought up to 6 ml with labeling buffer A and centrifuged at 20,000  g in a Sorval SS34 rotor for 30 min to remove aggregates (see Note 8). The sample is divided into two aliquots of 3 ml, and each aliquot is buffer exchanged into the desired buffer using Econo-Pac 10DG columns to remove excess dye (see Note 3). In this case, we buffer exchange into storage buffer A. The two aliquots are pooled giving 8 ml of labeled protein solution that should be at around 0.7 mg/ml, if no loss by aggregation has occurred. At this stage, the sample can be concentrated if desired (see Note 9), aliquoted, and stored at 80
C after flash freezing in liquid nitrogen. Even after passage on the Econo-Pac 10DG column, presence of free dye is often observed. To remove the residual free dye, we dialyze the protein samples (8 ml) prior to concentration for 4 h against 2 L of storage buffer A (see Note 10). 6. The extent of the labeling reaction was assessed by denaturing and reducing SDS-PAGE analysis using 20 ml of the preparation (see Note 11). As shown in Fig. 1, the labeling is apparently complete since the mobility of both proteins after labeling is retarded compared to the unlabeled control (see Note 12). The dye has been covalently attached to both hHOP2 and hMND1 subunits. The degree of labeling (DOL or dye-to-monomer ratio) is estimated spectrophotometrically (see Note 13), giving in this case DOL of 4.5 and 4.3 for the Alexa Fluor 488 C5 maleimide and the Alexa Fluor 546 C5 maleimide-labeling reaction, respectively. This suggests that four of the possible

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before Coomassie staining 473 nm Excitation LP 510 nm

before Coomassie staining 532 nm Excitation LP 575 nm

Fig. 1. Fluorescent labeling of the hHOP2–hMND1 complex by the Cys light method. The hHOP2–hMND1 complex was labeled with Alexa Fluor 488 maleimide (A-488) or Alexa 546 Fluor maleimide (A-546) and compared to the unlabeled preparation (U) by denaturing and reducing SDS-PAGE analysis. M ¼ protein size standards. After electrophoresis, the gel was first scanned with a Fluor Imager FLA-5100 (Fujifilm) to detect emission of Alexa Fluor 488 (middle panel ) or Alexa Fluor 546 (bottom panel ). Next, the gel was stained with Coomassie Brilliant Blue R-250 to reveal all proteins and visualized by bright-field illumination (top panel ).

six Cys residues in the heterodimeric complex are exposed to solvent. It can also be noticed that the fluorescent signal after labeling is more intense for hMND1 than for hHOP2 (see Fig. 1; bottom panel obtained by fluor imager scanning of the gel before Coomassie staining). This difference in intensity suggests that hMND1 has more cysteine residues exposed to solvent than hHOP2, but further analysis by mass spectrometry is required to prove this point. 7. This protocol is relatively large scale, but the reactions can be scaled down to 100 ml when optimizing reaction conditions keeping the protein concentration at around 1–2 mg/ml. First, treat the protein sample with DTT as described in step 1. Then, buffer exchange the protein into labeling buffer A

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using a PD SpinTrap G-25 column (see Note 14). Perform reaction series to optimize labeling conditions (label-toprotein ratio, time of incubation, temperature of incubation, pH, buffer conditions, and ionic strength and we typically use NaCl or KCl). The reaction is quenched by addition of DTT as in step 4. Ten microliters of each reaction mixture can directly be analyzed by SDS-PAGE analysis to verify covalent attachment of the dye. Excess free dye is visible in the running front of the gel. The reaction that is most optimal can further be buffer exchanged into a desired storage buffer using a PD SpinTrap G-25 column as described above. In general, this small-scale preparation gives enough reagent to perform pilot experiments in single-molecule setups keeping in mind that free dye might still be present in the preparation. 8. When using recombinant protein that contains a polyhistidine tag, the labeling reaction can be done on a 1 ml HisTrap FF. Load 1–5 mg of protein on the column in a labeling buffer free of DTT and EDTA and pH not lower than 7. As a general practice, keep all fractions for analysis by SDS-PAGE analysis if required. Dilute the DMSO dye solution in 2 ml of labeling buffer at the desired dye-to-protein ratio. Gently flush the dye solution in the column and let incubate at the desired temperature for the desired time. After the reaction, flush 10 ml of labeling buffer to remove free dye. Elute the labeled protein with labeling buffer A containing 250 mM imidazole, pH 8.0 (adding 1 mM EDTA to the elution buffer is fine but may strip the nickel). First, flush 1 ml of elution buffer on the column and let sit for 15 min. Recover the protein by injecting 2 ml of elution buffer. Discard the column, as it is best to avoid reusing it to prevent contamination with different dyes. Dialyze into the desired storage buffer containing 10% glycerol. Aliquot, flash freeze in liquid nitrogen, and store at 80
C. 3.2. Site-Specific Labeling by the Cys Light Method: Labeling of hRAD51

For many fluorescent single-molecule applications, it is advantageous to obtain a preparation of a fluorescent variant of the protein of interest in which every monomer is specifically labeled at a selected surface position. The development of such a reagent is of course more time consuming, but in the end, it greatly helps interpretation and analysis of results. As an example, we describe here how the Cys light method was used to specifically label a protein at a specific surface position (3). The human RAD51 recombinase monomer contains five cysteine residues of which Cys31 and Cys319 are exposed to solvent according to structural predictions. To obtain a homogeneous population of monomers having a single and discrete label, each on the same position, namely, residue Cys31, we mutated Cys319 to Ser by site-directed mutagenesis of the plasmid expression construct, thereby removing the –SH group

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at position 319. Labeling of the C319S hRAD51 variant with Alexa Fluor 488 C5 maleimide or Alexa Fluor 555 C2 maleimide was performed as described in Subheading 3.1 (steps 1–6). DOL of 0.8 and 1.1 was measured, respectively, and has shown in Fig. 2a; both labeling reactions went to completion as judged by the retarded mobility of the labeled samples in the gels. Mass spectrometry of the full-length labeled protein samples (see Note 15) shows that the Alexa Fluor 488 C5 maleimide-labeled sample is homogeneous, containing mostly monomers with one single dye covalently attached (Fig. 2b, left panel). In contrast, analysis of the Alexa Fluor 555 C2 maleimide-labeled sample shows that a substantial fraction of monomers have incorporated two dye molecules (Fig. 2b, right panel). Thus, different dyes with different carbon arm linkers may have different specificities. The identification of the residue(s) giving nonspecific labeling requires further detailed mass spectrometry analysis after protease digestion. 3.3. The Lys Light Method: Labeling of hSSB1 and hSSB2

The other popular chemistry used to covalently attach a fluorophore to a protein is succinimidyl ester or N-hydroxysuccinimide (NHS) ester conjugates, which are reactive toward amine groups, such as e-amino groups of lysines or the amine terminus of proteins, forming a chemically stable amide bond (see Note 1). Below, we describe the labeling of hSSB1 and hSSB2 proteins with modifications of the procedure recommended by ATTO-TEC (see Note 16) (4). Lysine residues are typically abundant in proteins and the procedure can give very high DOL. 1. The protein sample (3 ml) is supplied in storage buffer B at a concentration of 2 mg/ml and buffer exchanged in labeling buffer B using an Econo-Pac 10DG column and recovered in 4 ml. Maintaining the pH just above 8 ensures that the exposed e-amino groups are sufficiently deprotonated and, thus, reactive toward the NHS ester and that the competing reaction with hydroxyl ions is minimized. 2. Atto 488-NHS ester is dissolved in anhydrous DMSO and added at twofold molar excess of dye over the protein (see Notes 6 and 7). The dye solution should be added rapidly drop by drop while stirring the solution with a small magnetic bar to avoid local concentration effects. The reaction mixture is left to incubate at +4
C for 1 h or at room temperature for 30 min with stirring. We find that the reaction is quite fast and that with some samples a 5-min incubation at room temperature is sufficient to label the protein to completion. 3. The reaction is quenched by addition of Tris–HCl, pH 7.5, to 0.1 M and further incubated for 5 min.

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b 8000 37,210

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Fig. 2. Site-specific fluorescent labeling of hRAD51 by the Cys light method. (a) Preparations of the hRAD51 variant C319S were labeled with Alexa Fluor 488 maleimide (A-488) or Alexa Fluor 555 maleimide (A-555) and compared to the unlabeled preparation (U) by denaturing and reducing SDS-PAGE analysis. M ¼ protein size standards. After electrophoresis, dye attachment was directly visualized by bright-field illumination of the gels (before panels) or after Coomassie Brilliant Blue R-250 staining (after panels). (b) The degree and homogeneity of labeling were analyzed by MALDI-TOF of the full-length protein preparations (lower panels ).

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4. The volume is brought up to 6 ml with labeling buffer and centrifuged at 20,000  g in a Sorval SS34 rotor to remove aggregates. The sample is divided into two aliquots of 3 ml, and each aliquot is buffer exchanged into the desired buffer using Econo-Pac 10DG columns to remove excess dye (see Note 3). In this case, we buffer exchange into storage buffer B. The two aliquots are pooled giving 8 ml of labeled protein solution that should be at around 0.7 mg/ml if no loss by aggregation has occurred. At this stage, the sample can be concentrated if desired (see Note 9), aliquoted, and stored at 80
C after flash freezing in liquid nitrogen. Even after passage on the Econo-Pac 10DG column, some low level of free dye is often observed. To remove the residual free dye, we dialyze the protein samples (8 ml) for 4 h against 2 L of storage buffer B (see Note 10). 5. Figure 3 shows an assessment of the extent of the labeling procedure by SDS-PAGE analysis. DOL of six and five dyes per monomer was measured for hSSB1 and hSSB2, respectively (13 and 11 possible lysine residues for hSSB1 and hSSB2, respectively). However, although we obtained very high DOL with this method, the labeled proteins were not able to bind DNA as efficiently as the unlabeled proteins. Further optimization (lower dye-to-protein ratio, shorter time, and lower

Fig. 3. Fluorescent labeling of hSSB1 and hSSB2 by the Lys light method. Preparations of hSSB1 or hSSB2 were labeled with ATTO 488 NHS (A-488) and compared to the unlabeled preparations (U) by denaturing and reducing SDS-PAGE analysis. M ¼ protein size standards. After electrophoresis, dye attachment was visualized by UV light transillumination of the gel (bottom panels) or after Coomassie Brilliant Blue R-250 staining (top panels).

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temperature of incubation) is required to find labeling conditions that preserve the original activity of the proteins. Alternatively, the Cys light method could be tried. 3.4. N-Terminus Labeling by the Lys Light Method: RecA Labeling

Because the N-terminal amine group of proteins has a pKa value that is lower than 9, performing a labeling with an NHS ester dye conjugate at pH 7 or lower can in principle target the attachment of the dye to the N-terminal amine group of proteins. At this pH, e-amino groups of solvent-exposed lysines are expected to be fully protonated and nonreactive toward NHS esters. Thus, applying the Lys light method at low pH could in principle be a convenient method to generate a preparation of a fluorescent variant of the protein of interest in which every monomer is specifically labeled at a specific surface position. We tried to apply this principle to the labeling of the RecA protein. First, we produced a variant of RecA with a cleavable N-terminal polyhistidine tag that can be cut by incubation with the TEV protease (see Fig. 4a). After TEV protease cleavage, we can therefore assess whether the incorporated label has been specifically attached to the N-terminus of the protein. 1. The protein sample (3 ml) is supplied in storage buffer A at a concentration of 2 mg/ml and buffer exchanged in labeling buffer C using Econo-Pac 10DG column and recovered in 4 ml. 2. ATTO 488-NHS ester or ATTO 633-NHS ester is dissolved in anhydrous DMSO and added rapidly drop by drop while stirring at twofold molar excess of dye over the protein (see Notes 6 and 7). The reaction mixture is incubated at room temperature for 30 min with stirring. 3. The reaction is quenched by addition of Tris–HCl (pH 7.5) to 0.1 M and further incubated for 5 min. 4. The reaction is processed as in Subheading 3.3, step 4, using storage buffer A as recovery buffer. 5. Figure 4b shows the analysis of the extent of labeling and the label incorporation after TEV cleavage. Clearly, it can be seen that the label has been attached to the N-terminal fragment but also internally. DOL of 2.2 and 2.3 for the ATTO 488 and ATTO 633 labeling was measured spectrophotometrically. Thus, under these conditions of pH 7, specificity of the reaction toward the N-terminus was not observed. Mass spectrometry analysis of the labeled full-length proteins shows that we obtained a very complex and heterogeneous mixture with species that have acquired even four dyes per monomer (see Fig. 4c). Perhaps, the e-amino groups of solvent-exposed lysine residues of RecA have a pKa value lower than expected due to their local environment. It can be noticed that the

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Fig. 4. Fluorescent labeling of RecA by the Lys light method at low pH. (a) The RecA protein was produced with an N-terminal His tag cleavable by the TEV protease. (b) The His-RecA preparation was labeled with either ATTO 488 NHS (A-488) or ATTO 633 NHS (A-633) and compared to the unlabeled preparations (U) before and after TEV protease cleavage (+TEV) by denaturing and reducing SDS-PAGE analysis. M ¼ protein size standards. After electrophoresis, the gel was first scanned with a Fluor Imager FLA-5100 (Fujifilm) to detect emission of ATTO 488 (middle panel ) or ATTO 633 (bottom panel ). Next, the gel was stained with Coomassie Brilliant Blue R-250 to reveal all proteins and visualized by bright-field illumination (top panel ). (c) The degree and homogeneity of labeling were analyzed by MALDI-TOF of the full-length protein preparations.

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DOL determined spectrophotometrically only give average and approximate values. 6. To further optimize the labeling reaction, we performed additional labeling reactions with ATTO 633 NHS as described in steps 1–5 using labeling buffer C in which the MOPS–NaOH, pH 7.0, is replaced with MES–NaOH, pH 6.2, or HEPES–NaOH, pH 8.2. Unfortunately, as judged by fluorescence quantification after TEV cleavage, the labeling in the three different pH conditions behaved similarly giving both N-terminal and internal attachment of the dye (data not shown). We conclude that at least one internal Lys residue is reactive toward the NHS ester group even when the pH is buffered at 6.2. Perhaps, the local environment is influencing the pKa of this putative surface-exposed lysine residue. However, another group has been successful in specifically labeling RecA at the N-terminus using a 5(6)-carboxyfluorescein, succinimidyl ester (5). Thus, the chemical properties of the dye might also influence the specificity of the reaction. Alternatively, we have to optimize the ratio of dye to protein and/ or the reaction kinetics when working with ATTO NHS ester conjugates. 3.5. Fusion to an Intrinsically Fluorescent Protein: Production and Purification of hRPAeGFP

Sometimes, fluorescent labeling by chemical modification is not efficient or destroys the original activity of the protein. An alternative to make the protein glow is to generate a fusion of the protein to an intrinsically fluorescent protein, such as eGFP. Below, we describe this approach for the labeling of hRPA, a single-stranded DNA-binding heterotrimeric protein complex (6). We generated a bacterial polycistronic expression construct phRPA-eGFP (or phRPA-mRFP1 expressing a red fluorescent construct) that produces the large subunit of hRPA tagged at its C-terminus with a polyhistidine-tagged variant of eGFP to facilitate purification (details of plasmid constructs are available upon request). Below, we describe the expression and purification procedures as well as the DNA-binding activity analysis. 1. The expression plasmid is transformed in Rosetta/pLysS cells (Novagen), and cells containing the plasmid are selected on LB plates supplemented with ampicillin (100 mg/ml) and chloramphenicol (34 mg/ml). A single colony is used to inoculate 50 ml of LB+ amp + cm and incubated overnight at 37
C with agitation. The next morning, 3 L of medium in a 6-L flask are inoculated with 30 ml of overnight preculture and incubated at 37
C with vigorous shaking until the OD at 600 nm reaches 0.5. At that stage, IPTG is added to a final concentration of 1 mM and the temperature of the incubator is turned down to +15
C. Incubation at +15
C is continued for at least 16 h. Cells are collected by centrifugation at

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3,500  g and resuspended in 10 ml of PBS. The cell paste is flash frozen in liquid nitrogen and stored at 80
C. 2. To extract the protein, the frozen cell paste is quickly thawed in lukewarm water and immediately chilled on ice. Keep working in the cold from now on. The suspension should become very viscous due to cell lysis and release of genomic DNA. Add 1 volume of 2 lysis buffer and resuspend by mixing with a pipette (see Note 17). The viscosity of the sample is reduced by sonication (see Note 18). The mixture is clarified by centrifugation at 20,000  g for 1 h at +4
C (Sorval SS42 rotor). The supernatant containing RPA-eGFP is flushed through a filter device with 0.45-mm pores (Millipore). Cleaner preparations are usually obtained when using a chromatography system, such as an ¨ KTAFPLC (GE Healthcare). However, since most biophysics A laboratories are not equipped with such equipment, we present a procedure that can be performed manually with a syringe and gives very pure preparations as shown in Fig. 5a. The supernatant is loaded (slowly, drop by drop) on a 1-ml HisTrap FF column preequilibrated with 1 lysis buffer. The column is washed with 10 volumes of 1 lysis buffer. The column is further washed in 5 ml steps by increasing the imidazole concentration starting from 5 to 10, 20, 50, and finally 250 mM imidazole in 1 lysis buffer. The bulk of hRPA-eGFP should elute in the last 250 mM imidazole step. The protein sample is dialyzed against 2 L of buffer R for at least 2 h at +4
C, but overnight is also fine (see Note 10). Slowly load the protein sample on a 1-ml HiTrap Heparin HP column equilibrated with buffer R and wash with at least 10 ml of buffer R. Step wash the column (5 ml) by increasing the concentration of KCl in buffer R by 50 mM increments starting from 50 to 500 mM. The bulk of hRPA-eGFP elutes around 200–250 mM. Aliquot the fraction, flash freeze in liquid nitrogen, and store at 80
C. Presence of nucleases should be tested. If desired, the protein can be further purified by chromatography through a 1-ml Hitrap Q HP column by performing exacting the same protocol as for the HiTrap Heparin HP. Elution of hRPA-eGFP occurs around 250–300 mM KCl. We advise to keep every fraction for analysis by SDS-PAGE. 3. Figure 5a shows the denaturing SDS-PAGE analysis of a hRPA-eGFP preparation obtained by the Histrap/Hitrap heparin protocol described above. Figure 5b presents the analysis of the single-stranded DNA-binding activity by electrophoretic mobility shift assay. Reassuringly, the presence of the eGFP tag fused at the C-terminus of the large hRPA subunit does not affect its DNA-binding activity in this assay.

a KDa 150

M RPA70-eGFP

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RPA32 25 20 15 10

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Protein ssDNA

U.V. light excitation

mRFP1 emission

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Ethidium bromide and mRFP1 emission

Fig. 5. Purification and single-stranded DNA binding of hRPA-eGFP. (a) SDS-PAGE/ Coomassie staining of an aliquot of the hRPA-eGFP preparation (2 mg) purified on HisTrap and Heparin columns. M ¼ molecular weight standard. (b) Electophoretic mobility shift assay showing that the fusion of eGFP or mRFP1 to C-terminus of the large subunit of hRPA does not interfere with its single-stranded DNA-binding activity. For each preparation, the protein (1 mM for the highest final concentration, and diluted in twofold increments) was incubated with or without 200 ng of PhiX174 single-stranded DNA in a 10 ml reaction volume containing 50 mM KCl, 20 mM Tris–HCl, pH 7.5, 5% glycerol, 1 mM EDTA, 1 mM DTT, and 100 mg/ml BSA. After a 20-min incubation, the binding reactions were directly analyzed by electrophoresis in a 0.6% agarose/ Tris–Borate–EDTA. Before staining, the gel was scanned with a Fluor Imager for detection of mRFP1 or eGFP emission (middle two panels ). Afterward, the gel was stained with ethidium bromide to detect DNA and visualized on a UV light transilluminator (top panel ) or by scanning the gel with a Fluor Imager (bottom panel , notice that with these settings both mRPF1 and ethidium bromide emissions contribute to the signal).

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3.6. Indirect Strategies for Protein Fluorescent Labeling

It is also possible to label a protein by adding an affinity tag by genetic engineering, allowing indirectly labeling with secondary fluorescent reagents specific for the tag. Here, we enumerate and briefly describe a few of the possible tags that can be used and cite companies from which reagents can be obtained (see Note 19). 1. The AviTag (Avidity) consists in a 15 amino acid peptide tag (GLNDIFEAQKIEWHE) that can specifically be biotinylated in vivo or in vitro on the lysine residue using the biotin ligase (BirA) from E. coli. Commercially available fluorescent avidin or streptavidin can subsequently be attached “nearly covalently” to the AviTagged protein. 2. The strep tag (IBA-biotagnology) is a very small peptide that can be fused to a protein of interest by genetic engineering. The strep tag mimics biotin and can bind streptavidin or avidin with high affinity. Addition of fluorescently labeled streptavidin or avidin, thus, indirectly labels the biotinylated protein. 3. The FlAsH/ReAsH system (Invitrogen): The small 6-amino acid 1 kDa tetracysteine tag (CCPGCC) that can be fused to a protein of interest by genetic engineering coordinates the FlAsH-EDT2 or ReAsH-EDT2 compounds with high affinity. These biarsenical compounds fluoresce upon coordination to the tetracysteine tag. 4. Fluorescently labeled antibodies specific to the protein of interest could also be used for indirect labeling as long as they do not interfere with its activities. Instead, a number of fluorescently labeled monoclonal antibodies specific for various epitopes that can be fused to the protein of interest by genetic engineering are commercially available. The FLAG, HA, and myc epitopes are among the most popular ones. Finally, since many recombinant proteins are produced as fusions to the glutathione S-transferase or the maltose-binding protein, these moieties can also be used as anchor point for a fluorescent antibody. 5. Fluorescent nanocrystals (quantum dots, Evident Technologies, Invitrogen) functionalized with NHS ester or maleimide groups, or coupled to streptavidin or antibodies, might be used for direct or indirect protein labeling (7, 8).

4. Notes 1. See Molecular Probes Handbook at http://www.invitrogen. com/site/us/en/home/References/Molecular-Probes-TheHandbook.html for a description of the chemistry.

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2. The 1 M DTT stock solution should be prepared freshly. 3. The Econo-Pac 10DG column is first equilibrated by gravity flow with 20 ml of labeling buffer (or recovery buffer). The 3 ml sample is next loaded on the column and after it has fully entered the gel, add 4 ml of labeling buffer to elute the protein. When performing a buffer exchange after labeling, most of the dye should stay in the column bed. 4. Buffers are deoxygenated by gently bubbling argon gas for 30 min. 5. Most protocols do not recommend high-salt concentrations during labeling. However, we find that many proteins that we work with require at least 250 mM salt (NaCl or KCl) to be maintained in solution. The high-salt concentration does not affect the reactivity of the maleimide toward the –SH groups. Performing the labeling in the presence of 0.5 M NaCl (and sometimes, even up to 1 M NaCl) helps in obtaining more homogeneous labeling by avoiding protein aggregate formation. It is important to keep the pH below 7.5; otherwise, the maleimide group can also react with unprotonated primary amines. 6. We purchase dyes in small quantities, typically 1 mg, and use them promptly. Routinely, we dissolved the dye in anhydrous DMSO (stock kept in a desiccator) because many dyes have a poor solubility in water. Once dissolved in DMSO by vortexing, spin the solution in a microfuge to remove insoluble matters. It is best to immediately use the dye solution in a labeling reaction. However, we find that the dye solution in anhydrous DMSO can be kept for several weeks when stored at 20
C in an O-ring screw cap tube. Reactivity drops with time due to maleimide (or NHS ester) hydrolysis. It is, thus, important to avoid contact with humid environment and test the labeling efficiency of the dye after prolonged storage in anhydrous DMSO. 7. To obtain complete labeling, the choice of the molar ratio of dye to protein during labeling can be critical as well as the incubation time and temperature. We typically use fivefold and one- to twofold molar excess of dye for maleimide and NHS ester reaction, respectively. However, it is wise to first perform small-scale pilot reactions to optimize conditions (see Subheading 3.1, step 7). 8. It is common to find that some or all of the protein forms aggregates after labeling. This is not a surprise since the surface properties of the protein can be changed after labeling. Another dye can be tried or alternatively use a variant of the dye with a different charge, for example. 9. Protein concentration can conveniently be achieved using Amicon Ultra centrifugal filter devices from Millipore. They

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come in different sizes and with different MWCOs. Follow the supplier recommendation for the choice of centrifugal speed. We first spin an aliquot of buffer through the filter before adding the protein sample. Be careful not to concentrate too much as the protein might aggregate at high concentration. Proceed first in 5-min time intervals and gentle resuspension with a Pasteur pipette without damaging the filter. 10. We use SnakeSkin Pleated Dialysis Tubing from Pierce (10,000 MWCO). Protein aggregation may occur after dialysis. 11. Before loading the protein sample on the gel, 1 volume of protein sample buffer is added to the protein aliquot and the mixture is heated at 95
C for 5 min. After electrophoresis, the gel is placed in destaining solution and can directly be scanned with a Fluor Imager to visualize and quantify fluorescent signals. Free dye runs with the electrophoresis front and diffuses away after prolonged incubation. Note that this fluorescence imaging procedure is very useful to determine if the dye exhibits nonspecific binding to the protein of interest. For Coomassie staining, the gel is placed in staining solution and incubated for 1 h to overnight on a rotating table. The gel is next destained by several incubations in destaining solution (note that Coomassie quenches the fluorescence). 12. The mobility shift after labeling is often, but not always, detectable. The mobility shift depends on the mass-to-charge ratio, which can be affected by attachment of the dye to the protein and the resolving power of the gel chosen. 13. Measurement and calculation of DOL by spectrophotometry are described in detail at (http://www.atto-tec.com/index. php?id¼62&L¼1). 14. First, equilibrate the PD SpinTrap G-25 spin column by five consecutive 400 ml washes in labeling buffer and then proceed as recommended by the supplier. Do not exceed 100 ml for the sample. 15. Mass spectrometry procedures are not described here since most universities and research centers have nowadays access to a mass spectrometry service. For full-length protein mass measurements by MALDI-TOF, it is important to work at protein concentrations of at least 5 mM and to avoid salt, detergents, and glycerol. Reversed-Phase ZipTips from Millipore can be very convenient. Sinapinic acid often works well as matrix for ionization of full-length proteins. Finer mass spectrometry analysis to identify modified residues after labeling can also easily be performed by in-gel trypsin digestion (or using other proteases). 16. http://www.atto-tec.com/index.php?id¼62&L¼1.

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17. Protease inhibitor cocktails can be added during resuspension. We typically use 1 mM PMSF in this protocol. Avoid EDTA in your sample because it chelates the Ni2+. Do not go higher than 20 mM ß-mercaptoethanol or add DTT to avoid reducing Ni2+. 18. Sonicate with a microtip in short intervals of max 1 min with interruption on ice to avoid heating of the sample. Alternatively, benzonase nuclease (Novagen) can be added to the sample, but Mg2+ should then be added. 19. There is an important danger in using antibody, quantum dots, or fluorescent streptavidin to label proteins because these reagents may have multiple binding sites and can thus, under the wrong conditions, multimerize the protein of interest.

Acknowledgments Work in our laboratory is supported by Laserlab-Europe, the Association for International Cancer Research (AICR), the Agence pour la Recherche contre le Cancer (ARC), The city of Marseille, The Region of Provence-Alpes-Coˆtes d’Azur, and the Mediterranean Institute of Microbiology (IMM/IFR88). We would like to thank Sabrina Lignon from the mass spectrometry platform, Marielle Bauzan from the fermentation unit, and Yann Denis from the transcriptome platform of the IMM/IFR88 for advice and help with instrumentation and services. We thank Marc Wold (University of Iowa) for the gift of the p11d-tRPA polycistronic expression construct. References 1. Nathan C. Shaner, Paul A. Steinbach, & Roger Y. Tsien. (2005). A guide to choosing fluorescent proteins. Nature Methods. 2, 905–909. 2. Petukhova GV, Pezza RJ, Vanevski F, Ploquin M, Masson JY, Camerini-Otero RD. (2005). The Hop2 and Mnd1 proteins act in concert with Rad51 and Dmc1 in meiotic recombination. Nat. Struct. Mol. Biol. 12, 449–453. 3. Modesti M, Ristic D, van der Heijden T, Dekker C, van Mameren J, Peterman EJ, Wuite GJ, Kanaar R, Wyman C. (2007). Fluorescent human RAD51 reveals multiple nucleation sites and filament segments tightly associated along a single DNA molecule. Structure. 15, 599–609. 4. Richard DJ, Bolderson E, Cubeddu L, Wadsworth RI, Savage K, Sharma GG, Nicolette ML, Tsvetanov S, McIlwraith MJ, Pandita RK,

Takeda S, Hay RT, Gautier J, West SC, Paull TT, Pandita TK, White MF, Khanna KK. (2008). Single-stranded DNA-binding protein hSSB1 is critical for genomic stability. Nature. 453, 677–681. 5. Galletto R., Amitani I., Baskin R.J., Kowalczykowski S.C. (2006). Direct observation of individual RecA filaments assembling on single DNA molecules. Nature. 443, 875–878. 6. Henricksen LA, Umbricht CB, Wold MS. (1994) Recombinant replication protein A: expression, complex formation, and functional characterization. J. Biol. Chem. 269, 11121–11132. 7. Visnapuu M.-L., Duzdevich, D. and Greene, E. C. (2007). Using Total Internal Reflection Fluorescence Microscopy, DNA Curtains, and Quantum Dots to Investigate Protein-DNA

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Interactions at the Single-molecule Level. Modern Research and Educational Topics in Microscopy. Me´ndez-Vilas, A. and Diaz, J. (Eds). Microscopy series N
3 Vol. 1, pp 297–308.

8. Visnapuu ML, Greene EC. (2009). Singlemolecule imaging of DNA curtains reveals intrinsic energy landscapes for nucleosome deposition. Nat. Struct. Mol. Biol. 16, 1056–1062.

Chapter 7 Fluorescence Imaging of Single Kinesin Motors on Immobilized Microtubules Till Korten, Bert Nitzsche, Chris Gell, Felix Ruhnow, Ce´cile Leduc, and Stefan Diez Abstract Recent developments in optical microscopy and nanometer tracking have greatly improved our understanding of cytoskeletal motor proteins. Using fluorescence microscopy, dynamic interactions are now routinely observed in vitro on the level of single molecules mainly using a geometry, where fluorescently labeled motors move on surface-immobilized filaments. In this chapter, we review recent methods related to single-molecule kinesin motility assays. In particular, we aim to provide practical advice on: how to set up the assays, how to acquire high-precision data from fluorescently labeled kinesin motors and attached quantum dots, and how to analyze data by nanometer tracking. Key words: Kinesin, Single molecule, Imaging, TIRF microscopy, Motor protein, Microtubule

1. Introduction In vitro motility assays, where the movement of molecular motors along surface-bound cytoskeletal filaments is imaged by optical methods, have greatly improved our understanding of the mechanochemical properties of motor proteins. First, such assays were performed by binding the motors to large, micron-sized beads, which could be followed by video microscopy (1–3) or held in an optical trap (4–6). Later on, Funatsu et al. pushed the sensitivity of the fluorescence microscope to the limit of being able to visualize individual motor molecules labeled with cyanine-based fluorophores (7). Using total internal reflection fluorescence (TIRF) microscopy, the processive movement of individual kinesin-1 molecules along microtubules was visualized by labeling the motors with Cy3 (8) or with green fluorescent protein (GFP) (9). Since then, the number of single-molecule fluorescence measurements of kinesin and dynein motors interacting with Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_7, # Springer Science+Business Media, LLC 2011

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microtubules has vastly expanded. Nowadays, not only the stepping of motors is observed in these assays, but also diffusion, (de)polymerizing activities of motors (and other microtubuleassociated proteins), as well as interactions between motors and other proteins on the microtubule lattice (10–19). In this chapter, we describe protocols for the imaging of single kinesin-1 molecules stepping along surface-immobilized microtubules using TIRF microscopy. These procedures should be understood as examples that need to be adapted in order to work for other motors or filaments (see also Notes 17 and 24). As the name indicates, TIRF microscopy excites fluorophores using light that is totally internally reflected at the interface of two materials with different refractive indices (e.g., glass and buffer). This reflected light produces an electromagnetic near field (termed “evanescent field”) that decays exponentially with a decay length of 50–200 nm into the material with lower refractive index (see Fig. 1, left panel; for reviews, see refs. 20–23). A low penetration depth ensures that only fluorophores are excited which are very close to the surface. This “optical sectioning” reduces the background noise caused by molecules diffusing freely in solution, thus allowing the imaging of single fluorescent molecules. Due to the sensitivity of this fluorescence technique, it is essential to use clean glass surfaces that can be passivated efficiently (Subheading 3.2). Microtubules that self-assemble in vitro (Subheading 3.1) can be attached to these surfaces via antibodies

Fig. 1. Imaging single GFP-labeled kinesin-1 molecules moving along microtubules. Left : Schematic drawing of the assay. Microtubules are bound to a passivated glass surface with anti-tubulin antibodies. Single GFP-labeled kinesin-1 motors are imaged using the evanescent field generated by a totally internally reflected laser beam. Middle : Three frames of an image sequence showing a single kinesin-1 molecule (indicated with arrows) moving along a microtubule. Right : Kymograph of the same image sequence (microtubule not shown). Time progresses downward while the horizontal axis represents the distance along the microtubule. To record this data, we used an inverted fluorescence microscope (Zeiss Axiovert 200 M, Zeiss, Jena, Germany) with a commercially available TIRF-slider and an alpha PlanApochromat 100
oil 1.46 NA DIC objective (both Zeiss). Fluorescence signals were recorded using an EMCCD camera (Ixon DV 897, Andor, Belfast, N. Ireland). Excitation was achieved using either a mixed gas argon-krypton laser (Innova 70C Spectra; Coherent, Santa Clara, CA) or a liquid-waveguide coupled Lumen 200 metal arc lamp (Prior Scientific Instruments Ltd., Rockland, MA). Image acquisition and basic data processing were done using MetaMorph (Universal Imaging, Downingtown, PA).

Fluorescence Imaging of Single Kinesin Motors on Immobilized Microtubules

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Fig. 2. Resolving 8 nm steps of a single kinesin-1 molecule using TIRF microscopy. Top-left: Schematic drawing of the assay. In addition to the assay explained in Fig. 1, a streptavidin-coated Qdot is attached to the kinesin-1 molecule via a biotinylated anti-GFP antibody. Top-right: Tracked x–y data of the Qdot positions. The dashed line indicates the average path of the Qdot. Bottom-left: Walked distance of the Qdot projected onto its average path plotted against time. Steps identified by a step-finding algorithm (47) are overlaid. Bottom-right: Histogram of step sizes identified by the step-finding algorithm (data from 12 molecules). The imaging setup used to acquire this data was the same as that was used for Fig. 1.

(Subheading 3.3). Single GFP- or quantum dot (Qdot)-labeled, truncated kinesin-1 molecules can then be observed moving along these microtubules. Using Gaussian model-based tracking algorithms, the position of these molecules can be localized with higher precision than the resolution of an optical microscope (24–28). With bright fluorescent labels, it is possible to resolve 8 nm steps of kinesin-1 (Fig. 2) and even smaller steps produced by two motors working collectively (29).

2. Materials 2.1. In Vitro Polymerization of Microtubules

1. BRB80: 80 mM Piperazine-N,N0 -bis(2-ethanesulfonic acid) (PIPES), pH 6.9, with KOH, 1 mM ethylene glycol tetraacetic acid (EGTA), 1 mM MgCl2. 2. Microtubule polymerization mix: BRB80 supplemented with 24% ml DMSO, 20 mM MgCl2, and 5 mM GTP.

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3. Tubulin, bovine (Cytoskeleton Inc, Denver, CO; unlabeled #5.11.2146; rhodamine labeled #5.11.2148). Store at 80 C. Stable for ~6 months. 4. Taxol (Paclitaxel; Sigma-Aldrich, Steinheim, Germany, #T7191): Dissolve to a final concentration of 100 mM in DMSO. Store 10-ml aliquots at 20 C. Stable for at least 1 year. 5. BRB80T: Dilute Taxol to a final concentration of 10 ml in BRB80. 2.2. Preparation of the Sample Chambers

1. Coverglasses 18
18 mm and 22
22 mm (Menzel, Braunschweig, Germany, #BB018024A1 and #BB022022A1, ask for thickness 1.5!). 2. Soap bath: 2% Mucasol in water. 3. Acetone. 4. Ethanol. 5. Nanopure water (>18 MO/m). 6. Piranha solution: Carefully mix 30% H2O2 with 97% H2SO4 at a ratio of 1:2 in a suitable container. 7. 0.1 M KOH in nanopure water. 8. Trichloroethylene (TCE)/dichlorodimethylsilane (DDS) solution: 0.05% DDS in TCE. Add TCE first, and stir while adding DDS to TCE (see Note 9). Prepare freshly in the clean container used for cover glass treatment (see Subheading 3.2.4). 9. Methanol. 10. Nescofilm (Roth, Karlsruhe, Germany, #2569.1).

2.3. Surface Passivation and Microtubule Binding

1. Tetraspeck fluorescent microspheres (0.2 mm, Invitrogen, Carlsbad, CA, #T7280): 1:100 dilution in BRB80 (see Subheading 2.1). 2. Anti-beta-tubulin antibody, SAP4G5 (Sigma-Aldrich, Steinheim, Germany, #T7816): Typically, a 1:200 to 1:1,000 dilution in BRB80 is used (see Note 16). The undiluted stock is stored at 4 C for several weeks. 3. F127 solution: 1% Pluronic F127 (Sigma-Aldrich, Steinheim, Germany, #P2443) is dissolved in BRB80 overnight, filtered (0.22-mm syringe filter), and stored at 4 C. Stable for ~6 months. 4. BRB20: 20 mM PIPES, pH 6.9, with KOH, 1 mM EGTA, 1 mM MgCl2. 5. BRB20T: 10 mM Taxol (see Subheading 2.1) in BRB20.

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1. Casein (Sigma-Aldrich, Steinheim, Germany, #C7078): Add 35 ml BRB80 (see Subheading 2.1) to 1 g casein in a 50-ml Falcon tube. Place the Falcon tube in a rotating wheel at 4 C and allow the casein to dissolve overnight. Let the large precipitates sediment in the Falcon tube placed upright. Centrifuge the supernatant at 10,000
g at 4 C for 5 min. Filter the supernatant using a 0.22-mm syringe filter. Determine the concentration by measuring the absorbance at 280 nm. Dilute to the desired concentration (e.g., 10 mg/ml), snap freeze 40-ml aliquots in liquid nitrogen, and store at 20 C. Stable for at least 1 year. 2. GFP kinesin-1: We use truncated, GFP-labeled kinesin-1 constructs (rkin430GFP), which consist of the first 430 amino acids of kinesin-1 fused to a GFP and a his-tag at the tail domain. Cloning and purification have been described (30). 3. Antifade solution (see Notes 20–24): Supplement BRB20T (see Subheading 2.3) with final concentrations of 10 mM Taxol (see Subheading 2.1) and antifade reagents: 40 mM D-glucose, 160 mg/ml glucose oxidase (SERVA Electrophoresis GmbH, Heidelberg, Germany, #22778), 20 mg/ml catalase (Sigma-Aldrich, Steinheim, Germany, #C40), and 10 mM 1,4-dithio-DL-threitol (DTT). 4. Motor solution: Add final concentrations of 100 mg/ml casein, 1 mM ATP, and 50–500 pM GFP kinesin-1 to the antifade solution (see Notes 24 and 25).

2.5. Imaging Quantum Dot-Labeled Kinesin Motors

1. Biotinylated anti-GFP antibodies (produced by our antibody facility in-house): Biotinylated using EZ-Link NHS-PEO Solid Phase Biotinylation Kit (Pierce, Rockford, IL, #21450). 2. Qdots 655, streptavidin-coated quantum dots, emission peak at 655 nm (Invitrogen, Carlsbad, CA, #Q10121MP). Store at 4 C. Stable for ~1 year.

3. Methods 3.1. In Vitro Polymerization of Microtubules

Microtubules are commonly reconstituted from purified tubulin. Their physical structure, including the number of protofilaments and the stiffness, strongly depends on the assembly conditions (31–33). Below, we describe the production of stabilized (i.e., nondynamic) microtubules using GTP and the microtubulestabilizing drug Taxol (see Note 1). 1. Add 1.25 ml of microtubule polymerization mix to 5 ml of 4 mg/ml tubulin in BRB80 (containing 3–25% rhodaminelabeled tubulin, see Note 2).

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2. Incubate at 37 C for 30 min to allow microtubule assembly. 3. Dilute assembled microtubules by adding 493.75 ml of BRB80 supplemented by 10 mM Taxol and store them for up to 1 week at room temperature (see Notes 1 and 3). 4. Immediately before using the microtubules, centrifuge 50 ml of the microtubule solution at 100,000
g for 5 min and resuspend (see Note 4) in 200 ml of BRB80T (final tubulin concentration ~100 nM). 3.2. Preparation of the Sample Chambers

3.2.1. Cover Glass Precleaning

Clean, low-fluorescence glass surfaces are essential for singlemolecule TIRF microscopy of kinesin motors. Formed into simple flow cells, these glass surfaces allow convenient perfusion of solutions for immobilization of microtubules and introduction of kinesin. Unwanted nonspecific adsorption of fluorescent motors can be effectively prevented by surface passivation. 1. Place an equal number of 18
18-mm and 22
22-mm cover glasses into Teflon racks, ensuring that adjacent cover glasses cannot contact. 2. Sonicate for 15 min in a soap bath; rinse in deionized water for 1 min. 3. Bathe, sequentially, in acetone for 10 min, ethanol for 10 min, and nanopure water for 1 min.

3.2.2. “Piranha Solution” Cleaning

1. Transfer the cover glasses directly from the water bath to Piranha solution. Bathe for 1 h, heating the solution to 60 C. Extreme caution should be used, as Piranha solution is highly corrosive and potentially explosive (see Note 5). 2. Transfer racks directly from the Piranha solution sequentially to three nanopure water baths, bathing for 1 min each (see Notes 6 and 7).

3.2.3. Activating OH Groups on the Glass Surface for Silanization Using KOH

1. Transfer racks from the third nanopure water bath to a 0.1 M KOH bath for 15 min. 2. Transfer racks sequentially through two nanopure water baths, bathing in each for 1 min. 3. Remove from water bath and dry cover glasses completely with clean nitrogen gas (see Note 8).

3.2.4. Glass Silanization

1. Gently place the cover glasses into a container filled with TCE/DDS solution so that the glasses are completely immersed; bathe for 1 h. 2. Transfer the silanized glass, sequentially, through three methanol baths, placed in an ultrasonic bath for times of 5, 15, and 30 min.

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3. Remove from the final methanol bath and dry cover glasses completely with clean nitrogen gas. Store in clean, sealed glass containers (see Notes 10 and 11). 3.2.5. Sample Chamber Assembly and Use

1. Cut out several small (30
2 mm) Nescofilm strips using a (razor) blade (see Notes 12 and 13). 2. Arrange the Nescofilm strips on one side of a silanized 22
22-mm cover glass, forming a series of parallel channels (up to 4), and cut off (using a razor blade) those parts of the strips that protrude over the edges of the cover glass. 3. Place an 18
18-mm silanized cover glass on top, sandwiching the Nescoflm strips. 4. Transfer the assembly (22
22-mm cover glass facing down) to a hot plate at a temperature of 150 C. 5. The two cover glasses are firmly joined by the melted Nescofilm. This process can be monitored by a change in the optical properties of the Nescofilm. Gently applying pressure to the top cover glass ensures a tight seal. 6. Without delay, place the flow chamber onto the surface of a metal (e.g., aluminum) block, at room temperature, for fast cooling. 7. Mount the assembly in an appropriate holder. The process results in channels with a volume of 5 ml, and solutions can then be repeatedly perfused into the channels independently.

3.3. Surface Passivation and Microtubule Binding

We found that a hydrophobic surface can be very efficiently blocked using F127, a tri-block copolymer consisting of a hydrophobic poly(propylene oxide) (PPO) block in between two hydrophilic poly(ethylene glycol) (PEG) blocks. The PPO block strongly adsorbs onto the hydrophobic-rendered glass surface. The outer PEG parts form a polymer brush that is very effective in blocking protein adsorption. Stabilized microtubules are bound to the surface via anti-tubulin antibodies (see Fig. 1). 1. Perfuse Tetraspeck fluorescent microspheres into the hydrophobic-rendered glass flow cell with the assistance of a vacuum (see Notes 14, 15, and 29). 2. After a 5-min incubation, flush out excess microspheres with BRB80 (see Note 15). 3. Perfuse anti-beta-tubulin antibodies into the flow cell (see Notes 16 and 17). 4. After a 5-min incubation, flush out excess antibodies with BRB80.

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5. Using F127 solution, passivate the remaining exposed surface in order to block any further nonspecific surface binding of proteins. 6. After a 10–30 min incubation, remove excess F127 with 10 channel volumes of BRB80 (see Note 18). 7. Perfuse the solution containing microtubules (see Subheading 3.1). The incubation time depends on the desired microtubule density in the channel. Typical times range from 5 to 15 min. 8. Wash out unbound microtubules with BRB20T (see Note 19). 3.4. Imaging GFPLabeled Kinesin-1 Motors

Due to the nature of TIRF microscopy, only fluorophores that are close to the surface are excited. Therefore, it is possible to have free GFP-labeled motors in solution and still observe single kinesin-1 molecules moving along surface-immobilized microtubules. Using this technique, it is possible to measure biophysical parameters of the motors, such as: speed, run length, and dwell time. However, the limited resolution of an optical microscope in conjunction with fast bleaching (see Notes 20–23) and low fluorescence intensity of GFP does not allow the observation of individual steps of the motor protein. This limitation can be overcome using highly efficient fluorescence probes, like Qdots, together with advanced image analysis (see Subheadings 3.5 and 3.6). 1. Perfuse 2 channel volumes of motor solution into a channel containing surface-bound microtubules. Place the sample onto the microscope stage (see Notes 26–29). 2. Using arc lamp illumination and a rhodamine filter set, focus on the microtubules (see Note 30). Switch to laser illumination (488 nm wavelength) and a GFP filter set. In order to find the optimal TIRF angle, adjust the angle of the laser until the image becomes dark, and then turn back just until single molecules become visible in the whole field of view (see Notes 31 and 32). 3. Switch back to arc lamp illumination and rhodamine filters, move to a different field of view, and record a snapshot of the microtubule positions. Switching to laser illumination and the GFP filter set, acquire a continuous sequence of images, each with 100 ms exposure time (see Notes 33–35). An example microscope setup used to observe a kinesin-1 molecule moving along microtubules is given in the caption of Fig. 1.

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1. Mix 10 nM streptavidin-coated Qdots with 1 nM biotinylated anti-GFP antibodies. Incubate for 5 min. 2. Add 0.1–1 nM GFP-kinesin-1 to the above solution and incubate for 5 min (see Note 36). 3. Prepare the motor solution by supplementing the antifade solution from Subheading 2.4 with 4% (v/v) Qdot–kinesin solution, 100 nM ATP (if individual steps are to be resolved at 10 frames/s), and 100 mg/ml casein. 4. Continue with step 1 from Subheading 3.4 (see Notes 37 and 38).

3.6. Image Analysis: Tracking of Motors

GFP molecules with a diameter of 2 nm or Qdots with a diameter of ~20 nm appear as point sources of light; therefore, their intensity profile can be regarded identical to the point spread function (PSF) of the imaging system. The PSF is well-approximated by a 2D Gaussian (34, 35). Therefore, fluorescent particles can be localized by fitting their camera-captured intensity profiles to a 2D Gaussian. One possibility of implementing this approach is fitting by a radially symmetric 2D Gaussian with a fixed width corresponding to the dimension of the PSF. However, we found it important to also allow radially symmetric 2D Gaussians with nonfixed widths (Eq. 1) as well as elliptical 2D Gaussians (Eq. 2). These additional degrees of freedom accommodate slightly defocused images as well as particles of larger sizes (such as fluorescent Tetraspeck beads in the 200-nm range). " # h ðx  x^Þ2 þ ðy  ^y Þ2 I ðx; yÞ ¼
exp  (1) 2ps2 2s2 I ðx;yÞ ¼

h pffiffiffiffiffiffiffiffiffiffiffiffiffi 2psx sy 1  r2 " !# 1 ðx  x^Þ2 ðx  x^Þ ðy ^y Þ ðy ^y Þ2
exp  r þ ð1  r2 Þ sx sy 2s2x 2s2y (2)

Here, I(x, y) denotes the intensity value at pixel position x, y; h denotes the height of the Gaussian; x^, ^y denote the position of the center of the fitting function; s, sx, sy denote the widths; and r denotes the correlation coefficient determining the orientation of the Gaussian. 3.6.1. Implementation of the Tracking Routines

A tracking algorithm was developed in MATLAB (The MathWorks, Natick, MA). First, every frame is processed individually to determine the positions of all objects: (1) Rough scanning. Gray-scale images are converted to binary images using

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predefined threshold values. Objects with intensity values above this threshold are classified as particles. (2) Fine scanning. The regions around the particles are fitted by Eq. 1 or 2 using estimated starting parameters. The algorithm employs a nonlinear least squares fitting routine (36, 37) and estimates the error for each parameter. Second, the fitted particle positions from individual frames are connected into tracks using an adapted feature point-tracking algorithm (38). Thereby, a cost function for four subsequent frames is calculated and includes parameters, like position, velocity, direction, or intensity. Occlusions are handled with a post-processing step, where corresponding tracks are merged automatically. The final tracking results can be displayed in an overlay with the original images offering manual verification of the fitting. The described tracking approach was implemented in a MATLAB software package named Fluorescence Image Evaluation Software for Tracking and Analysis (FIESTA) which is freely available (39). Using FIESTA and microtubule-attached Qdots, we were able to resolve the 8 nm steps that kinesin-1 takes on the microtubule (see Fig. 2) and even smaller steps produced by two motors working collectively (29).

4. Notes 4.1. In Vitro Polymerization of Microtubules

1. As an alternative to the taxol stabilization of microtubules described in Subheading 3.1, stabilized microtubules can also be obtained by tubulin assembly in the presence of guanosine 50 -[a,b-methylene] triphosphate (GMP-CPP). For this, supplement 100 ml BRB80 with 2 mM tubulin, 4 mM MgCl2, and 1 mM GMP-CPP. Allow the microtubules to assemble for 2 h at 37 C. Immediately before use, centrifuge the microtubule solution at 100,000
g for 5 min and resuspend in BRB80 (final tubulin concentrations 0.4–4 mM). If particularly stable microtubules (lasting for several weeks at room temperature) are desired, assembled microtubules should be centrifuged immediately after polymerization and resuspended in BRB80 containing 10 mM Taxol. 2. When using chemically labeled tubulin, keep the labeling ratio as low as possible. Controls should be performed to check that labeling does not generate artifacts, such as decreased or increased run length of motor proteins on the microtubules. 3. Low temperatures cause microtubule depolymerization. Therefore, do not keep microtubules on ice or in the refrigerator.

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4. Resuspending and pipetting microtubules may break them by shearing. This effect can be reduced by slow, controlled pipetting and by cutting off the pipette tip to enlarge the opening. 4.2. Preparation of the Sample Chambers

5. Piranha solution is extremely corrosive. Work with proper protective equipment and under a fume hood. Dispose of Piranha properly. Used solutions must not be stored in closed containers since gas formation continues and closed containers bare the risk of explosions (40, 41). 6. Clean glass surfaces are wetted by water. A test for cleanliness is to check whether a droplet of water spreads immediately over the complete cover glass. If a drop with a contact angle not close to 0 forms, the cover glasses are dirty! 7. Clean glass surfaces are an attractant for dirt. Therefore, it is best to use clean surfaces right away. 8. Use a clean nitrogen source for drying; use a filter on the nitrogen gas line, and clean the nitrogen gun in acetone to remove oil. 9. DDS forms insoluble crystals during storage; store upright in a sealed container at 4 C; avoid agitating the DDS in its bottle. Use a long needle and syringe to pierce the Teflon seal on the DDS bottle and draw off the required amount from the top. Using the syringe, add DDS below the TCE surface to avoid air contact. DDS vigorously reacts with water, resulting in cross-linking and crystal formation. Crystals, if present on cover glass surfaces, greatly reduce the surfaces’ ability to be passivated. Store DDS under nitrogen or in a desiccator. 10. The quality of the silanization can be checked by putting a water droplet onto the glass surface and measuring its contact angle. The water contact angle should ideally be larger than 100 . Over time, the quality of silanization deteriorates. Use DDS-coated glasses within 1 week after preparation. 11. It is essential to prepare the cover glasses at all stages in as clean an environment as is possible; dry glasses in an environment free from any sources of dust; store the glass in doublesealed holders and bags; open the containers only briefly to remove glasses. 12. In place of Nescofilm, double-sided sticky tape can be used to form channels. 13. Using multiple layers of Nescofilm or tape can increase the channel volume; this decreases the surface area-to-volume ratio of the channel, mitigating the effects of any undesirable surface binding.

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4.3. Surface Passivation and Microtubule Binding

14. The cover glasses used here are hydrophobic. Therefore, a vacuum line is needed to help draw the first solution into the channels. After that, filter paper can be used. Caution is needed not to introduce air bubbles into the channel because air immediately denatures any proteins on the surface. 15. The flow profile in the channel is parabolic; thus, there is slower movement of the solution near the channel walls. In order to exchange solutions in the channels thoroughly, it is necessary to flow several channel volumes of solution. Unless noted otherwise, use 5 channel volumes. 16. Antibody concentrations should be as low as possible to not compromise surface blocking; places where antibodies are attached to the surface are not blocked by F127 in the subsequent surface passivation step. 17. As an alternative to anti-tubulin antibodies, in some cases it can be advantageous to use anti-fluorophore antibodies (42) or neutravidin (18) binding to tubulin labeled fluorescently or with biotin, respectively. 18. The channels can dry out. This damages proteins in the channel (see above). To avoid this, keep the sample chamber in a moist environment by covering it (e.g., with the lid of a pipette tip box) and adding a moist tissue. Alternatively, a drop of buffer can be added to each end of the channel, but in this case evaporation increases the salt concentration. If no additional solutions are to be perfused, channels can be sealed for long-term experiments using immersion oil or vacuum grease. 19. After the microtubules are immobilized on the surface, the low-salt buffer BRB20 is used because it increases the run length of kinesin-1.

4.4. Imaging GFP-Labeled Kinesin-1 Motors

20. In order to reduce photobleaching of fluorescent labels and to provide a reducing environment for the proteins, we add an oxygen-sequestering antifade cocktail to all our motor solutions. The antifade cocktail consists of D-glucose, glucose oxidase, catalase, and DTT. When adding these components, add the glucose oxidase last and just before actually using the motor solution, for this starts the antifade reaction. Once the antifade is complete, do not use the respective solution longer than 15–30 min. Otherwise the pH might drop significantly due to acid produced by the glucose oxidase. 21. High concentrations of glucose oxidase and catalase protein can interfere with the assay. At the same time, it is important to have high enzymatic activities in order to keep the oxygen concentration low. Therefore, it is important to always use

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glucose oxidase and catalase of the highest available relative activities (i.e., units per mg). 22. For convenience and reproducibility, store all antifade components separately at 20 C in aliquots of 10 ml at a 100
concentration. Catalase and glucose oxidase are dissolved in BRB80 and snap frozen in liquid nitrogen. The frozen aliquots are stable for 6 months; when thawed and stored on ice, aliquots maintain activity for several hours. DTT is dissolved in nanopure water, stored at 20 C, and stable for ~3 months. 23. DTT can be substituted with 2-mercaptoethanol (BME). Using 10 mM BME can prolong the time until bleaching of GFP by ~50%. However, BME is less stable than DTT. Therefore, antifade solution containing BME should not be used longer than 30 min. Also, ensure that the BME stock is fresh and not oxidized by air. 24. When using motor proteins other than kinesin-1, in most cases the buffer conditions of the motor solution have to be adjusted. While BRB buffers are well-suited for microtubules and kinesin-1, our experience is that other motor proteins tend to aggregate under these conditions. In those cases, it can help to use other buffering reagents, vary the salt concentration, and add low amounts of detergents, like 0.1% Tween 20. Never add calcium and always add at least 1 mM EGTA because free calcium ions depolymerize microtubules. Also, phosphate buffers are not very suitable because phosphate is a product of the motor hydrolysis cycle. 25. The concentration of motor protein needed for singlemolecule imaging greatly depends on the quality of surface blocking and the salt concentration. The flow channels have a high surface-to-volume ratio. Therefore, motor protein adsorption to the surface greatly influences the amount of free motor in solution. With increasing salt concentration, the affinity of the motor protein for the microtubule is reduced. Thus, a higher salt concentration requires more freely diffusing motor in solution. 26. To reduce thermal drift during imaging, allow the flow chamber to thermally equilibrate for about 2 min before image acquisition (sample already in contact with the immersion fluid, if non-air microscope objectives are used). 27. Another source of stage drift is airflow (e.g., in airconditioned rooms). Shielding the microscope by a closed box (e.g., made of transparent plastic) provides a simple and effective solution. 28. The epi-fluorescence arc lamps on many microscopes generate considerable heat. To avoid unwanted sample drift, and also heating the sample itself, we do not mount our arc lamp on

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the microscope and couple the light to the microscope through a multimode optical fiber. 29. To compensate for stage drift, fluorescent Tetraspeck beads can be used as drift control in the sample. 30. In order to minimize photobleaching of GFP-labeled kinesin-1, it is best to always focus on the rhodamine-labeled microtubules and then switch to the GFP filter set (start the recording immediately without refocusing). For this to work, it may be necessary to compensate for chromatic aberrations by measuring the focus offset between the GFP and the rhodamine channels and compensate for this difference before switching channels. Alternatively, a highly corrected objective, such as a Zeiss alpha Plan-Apochromat 100
oil 1.46 NA DIC (Zeiss, Jena, Germany), can be used. 31. Due to the nature of TIRF imaging, the laser comes out of the objective as a collimated beam (as opposed to a confocal microscope). Therefore, extreme precautions must be taken when the laser is on. (1) Make sure that no reflective material is above the microscope. (2) Never add or remove the sample while the laser is on. (3) Place a sheet of paper over the sample while adjusting the TIRF angle. This diffuses the laser beam while helping to see whether the laser still comes out of the objective. (4) Adjust the TIRF angle such that the laser points away from you. 32. Accurate focusing on the back focal plane can be achieved by observing the transmitted laser beam emerging from the objective some meters away on the ceiling, and adjustment of the position of the focusing lens in the TIRF condenser can then be performed. 33. For single-molecule imaging, we typically use a laser beam power of 1–3 mW, measured as it exits the microscope objective. A higher laser power reduces the time until photo bleaching of the motors while a lower power decreases tracking accuracy. 34. A good compromise between collecting enough photons per pixel while maintaining sufficient temporal resolution is critical. We found that for many applications exposure times of 30–100 ms per frame are optimal. 35. Keep your microscope clean, and use good antireflectioncoated filters and lenses. This reduces undesirable interference with reflections of the laser light from the optical components and diffraction from dust on the surfaces of optical components, which otherwise may cause a spatially nonuniform illumination due to interference fringes.

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36. When binding Qdot–streptavidin conjugates to the biotinylated antibody, make sure that there is no other source of biotin that might compete for free streptavidin-binding sites. 37. For imaging of Qdot-labeled kinesin motors, the same considerations as above apply, except that a higher laser power can be used in order to increase spatial and/or temporal resolution. We typically use a laser beam power of 5–10 mW, measured as it exits the microscope objective. 38. Qdots are bright and photostable fluorescent emitters. Therefore they are ideally suited for high-precision nanometer tracking. One drawback of Qdots is that they blink on various timescales (ranging from submilliseconds to many seconds). Although there is no way to eliminate blinking completely, it has been reported that the use of the reducing agents BME and DTT reduces blinking dramatically (43). There are also recent reports about the synthesis of nonblinking Qdots (44–46). The localization uncertainty for GFP molecules is a magnitude higher (10–40 nm) than for Qdots (1–4 nm).

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model for processivity, Proc. Natl. Acad. Sci. U. S. A. 97, 9482–9486. 6. Schnitzer, M. J., Visscher, K., and Block, S. M. (2000) Force production by single kinesin motors, Nat. Cell. Biol. 2, 718–723. 7. Funatsu, T., Harada, Y., Tokunaga, M., Saito, K., and Yanagida, T. (1995) Imaging of Single Fluorescent Molecules and Individual ATP Turnovers by Single Myosin Molecules in Aqueous-Solution, Nature 374, 555–559. 8. Vale, R. D., Funatsu, T., Pierce, D. W., Romberg, L., Harada, Y., and Yanagida, T. (1996) Direct observation of single kinesin molecules moving along microtubules, Nature 380, 451–453. 9. Pierce, D. W., HomBooher, N., and Vale, R. D. (1997) Imaging individual green fluorescent proteins, Nature 388, 338–338.

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Chapter 8 Exploring Protein Superstructures and Dynamics in Live Bacterial Cells Using Single-Molecule and Superresolution Imaging Julie S. Biteen, Lucy Shapiro, and W.E. Moerner Abstract Single-molecule imaging enables biophysical measurements devoid of ensemble averaging, gives enhanced spatial resolution beyond the optical diffraction limit, and enables superresolution reconstruction of structures beyond the diffraction limit. This work summarizes how single-molecule and superresolution imaging can be applied to the study of protein dynamics and superstructures in live Caulobacter crescentus cells to illustrate the power of these methods in bacterial imaging. Based on these techniques, the diffusion coefficient and dynamics of the histidine protein kinase PleC, the localization behavior of the polar protein PopZ, and the treadmilling behavior and protein superstructure of the structural protein MreB are investigated with sub-40-nm spatial resolution, all in live cells. Key words: Single-molecule imaging, Live-cell imaging, Live-cell PALM, Superresolution imaging, Superlocalization, Caulobacter crescentus

1. Introduction Since its advent 20 years ago, single-molecule fluorescence imaging has given rise to a host of exciting experiments (1). Beyond enabling fundamental investigations of the physics of emissive molecules, one main advantage of this technique is its utility in biologically relevant, live-cell experiments. The optical fluorescence microscope is an important instrument for cell biology, as light can be used to noninvasively probe a sample with relatively small perturbation of the specimen, enabling dynamical observation of the motions of internal structures in living cells. Single-molecule epifluorescence microscopy extends these capabilities by achieving nanometer-scale resolution, taking advantage of the fact that one can precisely characterize the

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_8, # Springer Science+Business Media, LLC 2011

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point spread function (PSF) of a microscope, allowing the center of a distribution, and thus the exact position of an emitter, to be localized with accuracy much better than the diffraction limit itself. This localization accuracy improves beyond the diffraction limit roughly as one over the square root of the number of detected photons (2). Single-molecule imaging has shown utility in the investigation of live-cell images from a number of different cellular systems (3–9). More recently, single-molecule epifluorescence microscopy has been used to probe the inner workings of live bacteria. The small size of bacterial cells makes the optical diffraction limit particularly restrictive, which has stimulated the push toward superlocalization and superresolution to overcome this obstacle. As a result, the nascent field of bacterial structural biology has benefited greatly from single-molecule investigations of proteins in live cells. The overall shapes of such cells can be seen in a standard light microscope, but those interested in probing subcellular details, such as protein structure and localization, have typically had to resort to in vitro characterization combined with extrapolation to the cellular environment, as well as to indirect biochemical assays. While cryo-electron microscopy (EM) can provide extremely high spatial resolution, fixation or plunge freezing is essential, and in contrast to labeling by fluorescent protein (FP) fusions, methods for identifying specific proteins by cryo-EM are still lacking. As a consequence, bacterial cell biology is an area of study ripe for investigation with direct, noninvasive optical methods of probing position, coupling, and structure, with resolution below the standard diffraction limit. Several groups have extended single-molecule imaging techniques to live bacterial samples (10–15). In this chapter, we focus on the application of single-molecule imaging and single-molecule-based superresolution studies of live cells to investigate the localization, movement, and structure of three proteins, PleC, PopZ, and MreB, that play important functions in Caulobacter crescentus cell cycle progression (10, 11, 14, 15). The C. crescentus cell cycle is characterized by dynamic changes in polar morphology and asymmetric cell division, and thus is a key model organism for study of bacterial developmental processes. Each round of dimorphic C. crescentus cell division gives rise to two distinct daughter cells: a motile, nonreplicating swarmer cell with a polar flagellum and a replicating stalked cell with an adhesive stalk (Fig. 1). This process of asymmetric division is partly driven by patterns of protein localization, which explains why study of specific proteins in this system is of great interest.

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Fig. 1. Schematic of the dynamic localization of the proteins PleC (stars ), PopZ (circles ), and MreB (lines ) over the course of the Caulobacter crescentus cell cycle. PleC is localized to the flagellar pole of the nonreplicating swarmer cell. As the swarmer cell differentiates into a stalked cell, PleC becomes delocalized. As the stalked cell progresses into a predivisional cell, a new flagellum is formed opposite the stalk and PleC is localized to the new flagellar pole. PopZ is also positioned at the flagellar end of swarmer cells. Upon differentiation into a stalked cell, a second concentration of PopZ begins to accumulate at the opposite pole (distal from the stalk) with an intensity that increases as the cell cycle progresses. Prior to the onset of the division process, MreB is arranged in a helix along the longitudinal axis of the cell. As the cell begins cytokinesis, MreB is assembled into a ring at the division plane. The helical structure is then reassembled in the two daughter cells.

2. Materials 2.1. Growth Media

1. PYE: 2 g bactopeptone, 1 g yeast extract, 0.3 g MgSO4, and 0.0735 g CaCl2 per L PYE. The mixture is autoclaved for 20 min and vented for 10 min to sterilize. 2. PYE solid media: Add 1.5% Bacto Agar (15 g/L); no CaCl2 needed. 3. M2G minimal media: 930 mL water, 50 mL 20
M2 salts (17.4 g Na2HPO4, 10.6 g KH2PO4, and 5.0 g NH4Cl per L), 1 mL 0.5 M MgSO4, 10 mL 20% glucose, 1 mL 10 mM FeSO4 (Sigma #F-0518), and 5 mL 0.1 M CaCl2.

3. Methods 3.1. Sample Preparation

Single-molecule fluorescence imaging of proteins in living cells can be accomplished via a genetically encoded fusion of the protein of interest to a photostable fluorescent protein emitting at long enough wavelengths to avoid cellular autofluorescence. However, single-molecule imaging requires a low copy number of fluorophores in the cell at any one time so that the ~250-nm

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diameter image spots from single molecules do not overlap. This low concentration can be achieved in several ways: 1. The gene encoding the protein–FP fusion is integrated into the chromosome in lieu of the gene encoding the native protein. In such strains, the initial FP concentration is generally too high for single-molecule imaging, so the emitting FP population must be reduced via photobleaching before measurements are made (10). 2. The gene encoding the protein–FP fusion is integrated into the chromosome under the control of an inducible promoter while maintaining the gene encoding the untagged wild-type protein at its native chromosomal locus. This has the advantage of allowing the experimenter to control the level of tagged protein while maintaining a significant background of the native protein in order to minimize any physiological effects of the tagging (11, 14). 3. A large number of protein–FP fusions are expressed in the cell, and the number of emitting FPs in any imaging frame can be subject to optical control, for instance by using a photoactivatable FP or by bleaching all of the FPs and then photoreactivating a sparse subpopulation (15). In order to resolve the emission from single FPs above background, cell and sample autofluorescence must be minimized. In C. crescentus, this is accomplished by the following: 1. After initial growth in rich PYE medium, cells are grown in minimal M2G medium for >24 h. 2. Blue and green FP mutants are avoided in favor of yellow and red FPs. At these longer wavelengths, cell autofluorescence is greatly diminished. The experiments discussed below all use the enhanced yellow fluorescent protein EYFP (S65G, V68L, S72A, T203Y) which can be excited at 514 nm. The high resolution provided by single-molecule imaging also requires the cells to lie still on a substrate. This is accomplished by preparing an agarose pad onto which the cells are deposited for imaging. 1. Agarose is added to M2G to a final concentration of 1.5–2% by mass. 2. The agarose/M2G mixture is heated in the microwave for 1–2 min until boiling, shaking every 30 s. 3. 1 mL warm agarose solution is pipetted onto a clean slide and then covered by a clean coverslip to ensure a flat surface.

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4. Just prior to imaging, the coverslip is removed, 5 mL cells are deposited on the agarose pad, and the cells are then covered by a clean coverslip. 5. The sample is sealed with wax (melted on a hot plate) to prevent drying (see Note 1). The sample of cells on agarose must also contain fiduciary markers that can quantify stage drift over the imaging time. Fiducials can be any bright, nonbleaching emitters, for example quantum dots (11) or fluorescent beads (15); these are added to the cells in nM concentration (see Note 2). 3.2. Imaging

Single-molecule imaging of bacterial cells is accomplished in a standard wide-field epifluorescence microscopy configuration, and the general imaging considerations have been described in detail (16). Confocal or total internal reflection methods are often not necessary because the entire cell itself is mostly within the depth of focus of a high numerical aperture (NA) microscope (~500–1,000 nm). Because the photon emission rate from a single molecule is typically ten orders of magnitude smaller than the number of scattered photons per second irradiating one pixel of the detector, appropriate filtering is necessary to reject scattered laser light. To optimize the number of detected photons, the single-molecule fluorescence microscope should incorporate a high-NA oil-immersion objective, sharp and carefully chosen filters, and a sensitive detector capable of detecting single photons. In modern experiments, this detector is generally an electronmultiplying charge-coupled detector (EMCCD) (11, 14, 15), though single-molecule imaging has also been accomplished in live cells with an intensified CCD (10). For imaging of EYFP–protein fusions (see Note 3), 1. The sample is excited with a 514-nm Ar+ ion or solid-state laser with similar wavelength. 2. The excitation beam is converted from linear to circular polarization with a l/4 wave plate in order to avoid the preferential detection of certain chromophore orientations (which often cannot be directly correlated with the orientation of the protein under investigation due to the FP fusion). 3. In the detection pathway, a 525-nm longpass dichroic filter and a 530-nm longpass filter are used to reject scattered laser light with an optical density of OD 8–10. Bandpass filters may also be used when necessary to reject other sources of background. 4. In experiments where photoswitching is useful, photoreactivation of EYFP to control the emitting fluorophore density is performed with a 407-nm laser. This light is also

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circularly polarized and is coupled into the excitation pathway with a dichroic mirror. Superresolution imaging based on single-molecule fluorescence and photoreactivation is accomplished by capturing different sparse subsets of emitters in each imaging frame. Upon photobleaching of a sparse subset, a new subset is generated by photoreactivation and the imaging cycle continues. The final image is generated based on the sum of localizations from many single-molecule imaging frames (15, 17–20). EMCCD cameras can operate at rates as fast as ~50 frames/s for a fairly large field and even faster for subimages. The integration time is chosen based on the experimental system. 1. A longer integration time (100 ms) increases the signal-tonoise ratio when detecting quasi-stationary or slow-moving FPs. These long integration times are applied to the slowly diffusing mobile protein PleC (10) and to MreB monomers incorporated into filaments (11, 15). The long-integrationtime imaging cannot easily observe fast-moving emitters. 2. On the other hand, a shorter integration time is employed to resolve freely or quickly diffusing FPs. Typical fast integration times used in C. crescentus are 15.4–32.2 ms for the quickly diffusing unpolymerized proteins, PopZ and MreB (11, 14). 3.3. Data Processing

Single molecules of the protein–FP fusion are identified by several criteria, including: 1. Digital (one-frame) photobleaching 2. Appropriate number of detected photons 3. A diffraction-limited emission PSF The position of a nanometer-sized isolated emitter is at the center of the PSF; this center can be identified by eye as the brightest pixel in the emission spot (10, 14) or the molecule can be more accurately localized by fitting the PSF to a 2D, symmetric Gaussian function (11, 15). High-density superresolution images based on multiple cycles of single-molecule imaging frames require the fitting software to be automated (15), and it is essential to carefully analyze the data in terms of numbers of photons detected and localization precision in order to represent the position determinations in an unbiased manner (20). Absolute protein positions and direction of movement are determined relative to fiducials and to bright- or dark-field images of the C. crescentus cells. The midpoint and endpoints of each cell are observable, the stalked end is recognized by its stalk, and the cell cycle stage can be identified from the cell morphology and the presence or absence of a stalk. It would also be possible to use DIC images, but the changes in microscope optics compared to those

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for single-molecule fluorescence imaging would have to be carefully calibrated. The techniques described in this chapter measure images in only two dimensions, but 2D measurements of diffusion on the surface of the bacterial cell membrane can be corrected appropriately by simulating 3D diffusional movement along an appropriately curved membrane (10, 11). 3.4. Dynamic Localization of the PleC Histidine Protein Kinase

A short region of the PleC histidine kinase, near its N-terminus, is inserted in the inner (cytoplasmic) membrane while the major portion of the protein resides in the cytoplasm. In C. crescentus, the dynamic localization of PleC regulates polar organelle biogenesis, motility, and asymmetric cell division by localizing to the flagellar pole at specific points of the cell cycle (Fig. 1). The swarmer cell must differentiate into a stalked cell, shedding its flagellum and building a stalk, in order to replicate and divide, and during this differentiation process, PleC becomes delocalized. As the stalked cell progresses into a predivisional cell, a new flagellum is formed opposite the stalk and PleC is localized to the new flagellar pole (21). Three different mechanisms have been postulated for the crucial process of PleC localization: free diffusion of PleC through the inner membrane followed by capture and immobilization at a binding site (22, 23), directed insertion of PleC into the inner membrane at the flagellar pole at the time of translation (24, 25), and active transport of PleC to the pole by a motor protein. Deich et al. used single-molecule microscopy to distinguish among these putative mechanisms by measuring the diffusion coefficients and movement directionality of PleC molecules in C. crescentus cells as a function of cell type and position within the cell (10). 1. Strain EJ148 of C. crescentus was created with PleC–EYFP fusions replacing the wild-type PleC on the chromosome and expressed under control of the PleC promoter. 2. The EYFP tags are exposed to 514-nm illumination until all but a sparse subset remained in the emissive state. 3. These isolated single-molecule emitters are imaged and their positions recorded as a function of time in order to measure the movement of PleC molecules in the cells. Figure 2 shows representative fluorescence images of this system. The first image in each of the series in Fig. 2a–c is a dark-field image illustrating the position, size, and orientation of the cell under investigation. The other images in each series represent successive 100-ms imaging frames of the same cells in which each punctate spot is the fluorescence image of a single PleC-EYFP molecule. Figure 2a shows images acquired uninterruptedly (every 100 ms). Due to the relatively slow dynamics of the membrane-bound PleC, such continuous imaging bleached

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Fig. 2. Dynamics of single PleC histidine kinase molecules. (a–c) Leftmost image: Dark-field image of the cell under investigation. Columns 2–7: Consecutive fluorescence images of single PleC-EYFP molecules spaced by different time intervals: (a) images acquired every 100 ms, (b–c) images acquired every 1 s. (d) Measured mean square displacement (triangles ) and geometry-corrected mean square displacement (circles ) vs. time lag. The corrected data slope of 0.049 mm2/s corresponds to a diffusion coefficient, D ¼ 12  2 mm2/s. (e) Direction of motion in stalked cells without localized PleC (black bars ) and swarmer and predivisional cells with localized PleC (gray bars ), where s indicates motion toward the flagellar pole. Each bin represents one-tenth of the cell length, with the polar bins excluded. Reprinted with permission from ref. 10.

the molecules before significant motion could be observed. Indeed, the lower molecule in Fig. 2a is bleached during the last frame, after only 600 ms of imaging. Time-lapse (TL) imaging was, therefore, utilized to increase the information attained before photobleaching. Figure 2b, c shows two different cells in which a 100-ms imaging frame is acquired every 1 s. In this way, more movement is observed before photobleaching. The single-molecule investigation of PleC in C. crescentus demonstrated several key aspects of PleC dynamics. Bulk microscopy indicates the presence of a bright, fixed PleC locus at the flagellar pole of swarmer and predivisional cells, but by resolving PleC-EYFP on a single-molecule level, a population of mobile PleC molecules could be identified in these cells. Mobile PleC molecules were also seen in the stalked cells, which show no evidence of localization in bulk microscopy. The trajectories of

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400 such mobile molecules were further investigated by tracking the PleC-EYFP molecules, and the measured mean square displacement (MSD) of the molecules at different time lags is shown in the triangles in Fig. 2d. Because the observed motion is a 2D projection of 3D motion along a membrane surface, the actual distance moved by the molecule is larger than the observed movement. By simulating diffusion on a cell surface, modeled as a cylinder with spherical ends, the measured MSD is converted to a geometry-corrected MSD (circles in Fig. 2d). The geometrycorrected MSD is linear with the time lag, Dt, consistent with Brownian diffusion with a diffusion coefficient, D ¼ MSD/(4Dt), of 12  2 mm2/s. A normalized coordinate system was created in which the variable s (0  s  1) indicates the position of a molecule along the long axis of a C. crescentus cell. The position s ¼ 0 represents the flagellar pole, and s ¼ 1 the stalked pole. The geometrycorrected coefficients D for the mobile PleC-EYFP molecules were classified based on the cell type in which the molecules were imaged (stalked, swarmer, or predivisional) and their position in the cell along the s axis. No measurable difference in D was observed for the different cell types. The geometry-corrected coefficient D was also not found to vary significantly as a function of s, except for a small reduction in D at the cell flagellar pole of swarmer and predivisional cells, perhaps attributable to immobilization at the binding site during the course of observation. Finally, Fig. 2e shows the direction of PleC-EYFP motion along the s axis, where s indicates motion toward the flagellar pole, as a function of position and cell type. Here, stalked cells, which do not have localized PleC, are in black, and swarmer and predivisional cells, which have localized PleC in addition to the mobile PleC under consideration, are in gray, and each cell is divided into ten equal bins, so length bin 2 includes data for molecules starting with 0.1 < s < 0.2. All molecules were equally likely to move in the +s or s direction, regardless of cell type or PleC position. The motion of PleC in the membrane appears to be governed by Brownian diffusion and is the same at all times in the cell cycle and all positions in the cell. In addition, the absence of directed motion argues against the existence of an active transport mechanism. Overall, the results of single-molecule investigations of PleC in C. crescentus were consistent with the diffusion and capture model of PleC localization at the flagellar pole. 3.5. Diffusion Dynamics of the Polar Protein PopZ

The ability of single-molecule microscopy to track individual intracellular proteins was subsequently applied to the prolinerich protein PopZ in live C. crescentus cells. PopZ is required to anchor the C. crescentus chromosome origins to the cell poles via the DNA-binding protein ParB, an anchoring that is critical for the control of its temporal and spatial localization in the cell cycle.

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PopZ is positioned at the flagellar end of nonreplicating swarmer cells (Fig. 1). Upon differentiation into a stalked cell, a second concentration of PopZ begins to accumulate at the opposite pole (distal from the stalk) with an intensity that increases as the cell cycle progresses. This second polar accumulation of PopZ is, thus, in place to tether the newly replicated chromosomal origin when it completes its transit across the cell. The mechanism of PopZ localization was investigated on a single-molecule level (14). 1. The merodiploid strain GB175 of C. crescentus was created with an unperturbed popZ locus and popZ-eyfp under control of the vanillate promoter at the vanA chromosomal locus. 2. Leakage of the vanillate promoter ensures the expression of 1–10 copies of PopZ-EYFP per cell in a background of untagged PopZ molecules. 3. These isolated single-molecule emitters are imaged and their positions recorded as a function of time. Two subpopulations of PopZ were, thereby, identified: polelocalized molecules that remained fixed within the measurement localization accuracy (60 nm) and mobile molecules that were resolved with fast (32.2 ms) imaging frames. Figure 3a, d shows the motion of two molecules tracked in one cell under investigation. In Fig. 3a, the tracks are overlaid on a transmitted white-light image of the cell with the cell outline shown (dotted line) while in Fig. 3d, the longitudinal positions of the same two molecules are recorded as a function of imaging time. In Fig. 3a, d, the gray traces (indicated by the white arrow in Fig. 3a) show the position of a polar-localized molecule, and the black traces show the trajectory of a mobile molecule that explores a large portion of the cell interior. Figure 3b–f shows the trajectories of 12 fixed (gray) and mobile (black) PopZ-EYFP molecules in five cells. The mobile PopZ-EYFP molecules exhibited random, diffusive movement in the cytoplasm during most of the time they were tracked, though on some occasions, they remained fixed at a pole (e.g., Fig. 3d at 3–4 s). This movement is consistent with a diffusion and capture mechanism for PopZ localization at the cell pole. The spatial dynamics of single PopZ molecules would not have been observable without single-molecule imaging. 3.6. Movement of the Structural Protein MreB

The structural protein MreB mediates polarity, chromosome segregation, and cell shape in C. crescentus (26–28). Bulk-level imaging and biochemical studies of the cytoplasmic MreB protein are consistent with the formation of a dynamic superstructure made up of actin-like filaments. This structure provides the machinery for key cellular processes, and the dynamics of MreB molecules were investigated on a single-molecule level (11).

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Fig. 3. Visualization of single PopZ-YFP molecules in live cells. (a) Positions of two PopZEYFP molecules within a cell, with heavy lines tracking the distance moved between 32.2-ms frames. One molecule (black ; indicated by arrow at top right ) remains localized to the pole, and the other (dark gray ) has increased mobility. The tracks are overlaid on a white-light image of the cell, which is outlined in black. (b–f) Timedependent behavior of 12 single molecules in five cells. Stationary and mobile molecule positions are both tracked with heavy lines. The heavy lines are dotted during dark (blinking-off) periods. Thin horizontal dotted lines in (b) and (d) mark the positions of the poles opposite to the pole at which stationary molecules are localized. The trajectories in (d) correspond to the longitudinal position of the molecules tracked in (a) as a function of time. Reprinted with permission from ref. 14.

1. The merodiploid strain LS3813 of C. crescentus was generated by integrating a single Pxyl::eyfp-mreB construct into the xylX locus in a C. crescentus chromosome already containing a wild-type, unlabeled copy of MreB under its endogenous promoter (26). 2. Cells with only a small number of isolated EYFP-MreB molecules are prepared by incubating the cells in the M2G minimal medium with 0.0006–0.003% xylose for 4 h. 3. The cells are imaged with 15.4-ms imaging frames in order to resolve the tagged MreB molecules. Figure 4a1 shows one such frame, in which three single molecules were captured. The image is smoothed by applying

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Fig. 4. Analysis of motion of EYFP-MreB. (a) 15.4-ms integration time fluorescence images of single EYFP-MreB molecules in a C. crescentus cell. White line shows the cell outline. (a1) 15.4-ms epifluorescence image showing three single EYFP-MreB molecules. The top and bottom molecules (arrowheads ) are stationary on this timescale, and the middle molecule (arrow ) is mobile. (a2) Smoothed image of (a1) obtained by applying a low-pass filter. (a3) Recorded trajectory of the mobile (middle ) molecule in (a1). (a4) Summed image of 450 sequential imaging frames. The fluorescence from the two stationary molecules is still evident, whereas the middle molecule does not appear on this 6.93-s integration timescale (scale bar, 1 mm). (b) Measured (open circles ) and geometry-corrected (filled circles ) MSD of fast-moving MreB molecules. The solid line is a linear fit of the corrected data. (c) Velocity autocorrelation of fastmoving molecules; this quantity drops to zero at the very first time lag. (d) Inverted-contrast, 100-ms integration time fluorescence images of single slow-moving EYFP-MreB molecules in a C. crescentus cell at 30-s intervals. The arrows illustrate the directional movement of the molecules and the black line shows the cell outline. The superlocalized track of a single molecule leads to a superresolution image of the filament through which the molecule is treadmilling. (e) Measured MSD versus time lag for slow-moving MreB molecules. The solid line is a quadratic fit to the data, indicative of directional motion. (f) Velocity autocorrelation of slow-moving MreB; this quantity remains positive over at least 80 s. Reprinted with permission from ref. 11.

a low-pass filter (3
3 kernel of 0.0625, 0.125, 0.0625, 0.125, 0.25, 0.125, 0.0625, 0.125, and 0.0625) in Fig. 4a2 for enhanced visibility. In this cell, two subpopulations of MreB were distinguished from one another: slow-moving molecules and fast-moving molecules (arrowheads and arrow, respectively, in Fig. 4a1). The trajectory of the fast-moving molecule in Fig. 4a1, obtained by fitting the fluorescence image in every frame to a 2D Gaussian function, is plotted in Fig. 4a3. This molecule diffused rapidly and explored a large portion of the cell. Four hundred and fifty successive frames were summed to form the fluorescence image in Fig. 4a4. After this 7-s integration

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time, the fluorescence from the two slow-moving molecules was still evident, but emission from the fast-moving molecule was smeared out over many pixels and did not appear. The white line in Fig. 4a shows the outline of the C. crescentus cell. Because the dynamics of the moving molecules were unchanged in the presence of the MreB-depolymerizing drug A22, the fast-moving EYFP-MreB molecules were ascribed to a free, unpolymerized population. The behavior of the unpolymerized single molecules was further characterized based on 111 trajectories. The observed MSD of the fast-moving molecules is plotted as a function of time lag (Dt) in the open circles of Fig. 4b. Based on the first four points, a diffusion coefficient of D ¼ MSD/(4Dt) of 1.11  0.18 mm2/s was extracted. This value of D is smaller than expected for a free cytoplasmic protein, but is consistent with the motion of a membrane-associated protein. Since the observed motion represents a 2D projection, simulations were again performed to correct for the three-dimensionality of the cell, and the geometry-corrected MSD of the molecules is plotted in the filled circles of Fig. 4b. The geometry-corrected MSD is linear with the time lag, Dt, consistent with diffusion along the cell membrane with D ¼ MSD/(4Dt) of 1.75  0.17 mm2/s. The velocity autocorrelation function, CV(t), was also calculated for these molecules. As shown in Fig. 4c, for the fastmoving molecules, CV(t) dropped to zero at the very first time step, indicating a nondirected random walk. Further experiments addressed the behavior of the slowmoving MreB. Because slow-moving EYFP-MreB molecules were not observed in the presence of the MreB-depolymerizing drug A22, the slow-moving molecules represent polymerized MreB. The dynamics of 120 single members of this subpopulation were carefully examined. Since the molecules were stationary within the 30-nm resolution of the measurement over the course of the 7-s integration time shown in Fig. 4a4, time-lapse imaging was used. Specifically, 100-ms imaging frames are separated by 9.9 s. In this way, the slow movement of polymerized MreB molecules could be followed over a longer time period before photobleaching. Figure 4d shows eight such fluorescence images in reverse contrast, where a single molecule is tracked for 220 s. The molecule moves from left to right, and then turns and moves right to left at a downward angle, shown by the arrow. The observed MSD of the slow-moving MreB molecules is plotted as a function of Dt in Fig. 4e. Here, the MSD was characterized by a quadratic dependence on time lag, as is typical of directed motion. Also consistent with directed motion is the computed velocity autocorrelation function, CV(t), shown in Fig. 4f, in which CV(t) remains positive until t ¼ 80 s. The slow, directed motion of polymerized MreB was further explored by analyzing the trajectories of each individual molecule

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in the context of two putative models for the motion of an MreB molecule in an MreB filament: (1) the filaments into which the monomers are incorporated were moving or (2) the monomers themselves were treadmilling through largely stationary filaments, analogous to the motion of actin. If the motion of polymerized MreB is due to whole filament movement, then the observation time for the slow-moving single molecules should be limited by the photobleaching time of the EYFP, independent of experiment timescale. The total emission time of EYFP-MreB before photobleaching under continuous emission was measured, with an average on-time of 4.6 s. However, the true irradiation time before photobleaching of the molecules imaged with 9.9-s time lapses was found to be only 0.8 s. Most of the fluorescence from the polymerized MreB molecules, therefore, disappeared before photobleaching occurred likely as a result of dissociation from the end of a filament and the onset of fast diffusive motion not resolvable with the 100-ms imaging frames. This result indicates that MreB molecules treadmill through filaments with fixed ends. Given that the polymerized MreB molecules exhibited directed motion, a speed value was extracted from each singlemolecule trajectory. The average speed was 6.0  0.2 nm/s. From its crystal structure, the length of an MreB monomer is 5.4 nm (29); the average speed, therefore, corresponded to 1.2 monomer additions per second in steady-state fixed MreB filaments. The average length traveled by a polymerized MreB molecule before dissociation, which corresponds to the filament length, was also measured by considering only MreB molecules that became polymerized after the start of imaging and that dissociated before the end of imaging. The average length of 128 MreB filaments was 392  23 nm – quite small relative to the average cell length of 3.5 mm. Most of the trajectories moved perpendicular to the long axis of the cell. A smaller number of trajectories were oblique. These nonperpendicular trajectories were characterized as moving toward the swarmer pole or toward the stalked pole, but no preferred orientation was observed. 3.7. Cell CycleDependent Superresolution Structure of MreB

By fitting the PSF of isolated nanoscale emitters with 30-nm localization accuracy and following these superlocalized molecules over time, the previous experiment attained superresolution via single-molecule tracking, as displayed in Fig. 4d. That is, as a single labeled MreB treadmills through a filament, the track shows the shape of the filament. This approach was, however, limited by the isolated fluorophore requirement to ~1–3 tagged MreB molecules, and therefore ~1–3 trajectories per cell. To address this upper bound and more fully observe the full superstructure in one cell, photoactivated localization microscopy (PALM) was used to extend the investigation of EYFP-MreB to cells expressing high concentrations of these molecules, and thus to visualize the

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superstructure formed by a collection of MreB filaments in these cells (15). In particular, bulk visualization of MreB in C. crescentus indicates that MreB forms a cell cycle-dependent structure (26, 28, 30). Prior to the onset of the division process, MreB is arranged in a helix-like shape along the longitudinal axis of the cell. As the cell begins cytokinesis, MreB is assembled into a ring at the division plane. The helical structure is then reassembled in the two daughter cells (Fig. 1). Single-molecule-based superresolution imaging was applied to measure these structures. 1. C. crescentus cells expressing 100–1,000 copies of EYFP-MreB are created by incubating the strain LS3813, described above, in the M2G minimal medium with 0.006–0.075% xylose for 4 h. 2. The cells are imaged with 100-ms imaging frames in order to resolve only the slow-moving, polymerized MreB molecules. The initial density of fluorescent tags in these cells was initially too great for isolated, single-molecule imaging, but this could be addressed based on the fact that apparently bleached EYFP molecules can be reactivated with violet light (31). 3. After the bleaching of all emissive EYFP-MreB molecules, a sparse subset is reactivated with 407-nm irradiation, where the reactivation intensity of 103–104 W/cm2 is chosen such that at most one EYFP molecule is reactivated in each diffraction-limited region. 4. The positions of these isolated molecules are determined by PSF fitting. 5. The reactivation and imaging process was repeated 20 times until a superresolution image could be reconstructed from the sum of the localizations. To illustrate the photoreactivation process, Fig. 5a–f shows the fluorescence emission from EYFP-MreB molecules in a single cell over time. Each punctate white spot is the emission from a single molecule, and the fluorescence images (acquired with 100-ms integration times) are superimposed on a reversedcontrast white-light image of the cell. After the initial bleaching step, two single EYFP-MreB molecules were observed in the cell (Fig. 5a). Additional imaging with 514-nm light bleached all the fluorophores (Fig. 5b). A 2-s dose of 407-nm laser illumination returned some EYFP-MreB to an emissive state (Fig. 5c, e), though all fluorophores are apparently bleached prior to the 407-nm pulse (Fig. 5d, f). 1. The positions of these molecules are calculated from a fit of the fluorescence images to a 2D Gaussian function and are recorded for every such frame.

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Fig. 5. Superresolution imaging of MreB superstructure. (a–f) Reactivation of single EYFP-MreB fusions in the same live C. crescentus cell using 407-nm light. Fluorescence images of single EYFP-MreB molecules from 514-nm excitation are overlaid on a reversed-contrast, white-light image of the cell. (a) Initial image showing two isolated emissive EYFP-MreB molecules. (b, d, f) After photobleaching by 514-nm irradiation, the cell contains no emissive EYFP-MreB. (c, e) Reactivated EYFP-MreB molecules are observed following a short 407-nm reactivation pulse (scale bar, 1 mm). (g–j) TL-PALM images of EYFP-MreB in C. crescentus cells created by fitting molecule positions in imaging frames, such as those in (a), (c), and (e). (g, h) Quasi-helical structure in a stalked cell. (i, j) Midplane ring in a predivisional cell. Fluorescence PALM images are shown in (g) and (i). The PALM images in (h) and ( j ) are from the same cells as in (g) and (i), respectively, overlaid on a reversed-contrast, white-light image of the cell (scale bars, 300 nm). Reprinted with permission from ref. 15.

2. At the end of a 4-min acquisition period, these localization events are summed. 3. To form a final superresolution image, each localized molecule is depicted in the reconstruction as a unit area Gaussian with fixed width equal to the average statistical localization accuracy of 30–40 nm. This technique, termed “Live-Cell PALM,” enabled the imaging of the EYFP-MreB superstructure in C. crescentus. In particular, it resolved several MreB bands spanning the length of stalked cells and a tightly focused midplane ring in predivisional cells. Importantly, understanding superresolution features derived from many image acquisitions requires careful consideration of the emitter photophysics and the dynamics, if any, of the underlying structure. Since, as described above, polymerized MreB molecules treadmill slowly along MreB filaments, time-lapse imaging, as described above, was incorporated into live-cell PALM to increase the number of localization events given the fact that the maximum labeling concentration in live-cell experiments is limited due to changes in the cell morphology at high concentrations of fusion

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protein. Specifically, a 900-ms delay was introduced between each 100-ms imaging frame, and the sample was only illuminated with 514-nm light during the short acquisition time. 407-nm reactivation pulses were again applied after photobleaching to generate novel sparse subsets of emissive EYFP-MreB. Figure 5g–j presents the results from TL-PALM imaging of EYFP-MreB in C. crescentus. Two distinct MreB superstructures were identified in the cells: a quasi-helical arrangement in a stalked cell (Fig. 5g, h) and a midplane ring in the predivisional cell (Fig. 5i, j). In Fig. 5h, j, the TL-PALM reconstruction is superimposed on a reversed-contrast, white-light image of the cell in which the EYFP-MreB was visualized. The images obtained by TL-PALM were more continuous than those acquired without the introduction of dark periods. Furthermore, the use of TL increased the number of localization events (487 in Fig. 5g and 330 in Fig. 5j) to the point, where the Nyquist criterion for 40-nm resolution was satisfied (32), giving rise to a true superresolution reconstruction of the MreB superstructure in C. crescentus.

4. Summary and Outlook Single-molecule imaging permits high-resolution measurements of fluorescent emitters in time and space. This noninvasive, nonperturbative technique is quite useful for the study of single protein molecules in live cells. By applying the techniques of single-molecule microscopy to EYFP-tagged proteins in live C. crescentus cells, the diffusion dynamics, localization patterns, and structure of three key proteins, PleC, PopZ, and MreB, could be explored. By providing a noninvasive tool for high-resolution imaging that is beginning to approach the spatial resolution of cryo-electron microscopy, single-molecule, superresolution imaging can enable investigations of many more intracellular processes and has become an important biophysical tool. Because the single-molecule-based imaging techniques described here are based on wide-field microscopy, they can further provide the basis for more sophisticated experiments. Specific challenges that are being addressed include improving the axial resolution of single-molecule microscopes (33–35), incorporating multiple excitation and emission wavelengths (36, 37), and imaging thick samples (38).

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5. Notes Axial drift of the sample, as caused, for instance, by microscope objective settling or by sample drying, is particularly detrimental to superresolution experiments. These notes outline several strategies used by the experimenters to address this concern. 1. Sealing the cells-on-agarose-pad with wax prevents excessive drying of the agarose pad over time. This is important in order to maintain constant cell sample thickness. 2. Despite sealing in wax, samples settle over the course of the experiment. It is, therefore, important to ensure that the coverslip is in close contact with the microscope stage and not hanging through an opening in the microscope stage. 3. The microscope objective settles over time, changing the instrument focus and blurring the acquisition. We have, therefore, found it necessary to let the microscope settle after initial focusing, and then use a PIFOC P721 piezo scanner/objective positioner for any needed further focus adjustments.

Acknowledgments The authors warmly thank members of the Shapiro laboratory, specifically Ellen Judd, Harley McAdams, Grant Bowman, and Zemer Gitai, as well as members of the Moerner laboratory, specifically, Jason Deich, Marcelle Koenig, So Yeon Kim, Anika Kinkhabwala, Michael Thompson, and Nicole Tselentis, for their contributions to this work. This research was supported in part by DARPA Grant MDA-972-00-1-0032, NSF Grant MCB0212503, Department of Energy Grants DE-FG02-04ER63777 and DE_FG02-05ER64136 9 (to LS), and NIH Grants P20-HG003638, R01-GM086196, R01-GM085437, R01GM51426 (to LS), and R01-GM32506 (to LS). References 1. Ambrose W. P., Moerner W. E. (1991) Fluorescence spectroscopy and spectral diffusion of single impurity molecules in a crystal Nature 349, 225–7. 2. Thompson R. E., Larson D. R., Webb W. W. (2002) Precise nanometer localization analysis for individual fluorescent probes Biophys J 82, 2775–83. 3. Sch€ utz G. J., Kada G., Pastushenko V. P., Schindler H. (2000) Properties of lipid micro-

domains in a muscle cell membrane visualized by single molecule microscopy EMBO J 19, 892–901. 4. Sako Y., Minoghchi S., Yanagida T. (2000) Single-molecule imaging of EGFR signalling on the surface of living cells Nat Cell Biol 2, 168–72. 5. Moerner W. E. (2003) Optical measurements of single molecules in cells Trends Anal Chem 22, 544–8.

8 Exploring Protein Superstructures and Dynamics in Live Bacterial Cells. . . 6. Vrljic M., Nishimura S. Y., Moerner W. E., McConnell H. M. (2005) Cholesterol Depletion Suppresses the Translational Diffusion of Class II Major Histocompatibility Complex Proteins in the Plasma Membrane Biophys J 88, 334–47. 7. Vrljic M., Nishimura S. Y., Brasselet S., Moerner W. E., McConnell H. M. (2002) Translational Diffusion of Individual Class II MHC Membrane Proteins in Cells Biophys J 83, 2681–92. 8. Lee H. D., Dubikovskaya E. A., Hwang H., Semyonov A. N., Wang H., Jones L. R., Twieg R. J., Moerner W. E., Wender P. A. (2008) Single-Molecule Motions of Oligoarginine Transporter Conjugates on the Plasma Membrane of Chinese Hamster Ovary Cells J Am Chem Soc 130, 9364–70. 9. Harms G. S., Cognet L., Lommerse P. H. M., Blab G. A., Schmidt T. (2001) Autofluorescent Proteins in Single-Molecule Research: Applications to Live Cell Imaging Microscopy Biophys J 80, 2396–408. 10. Deich J., Judd E. M., McAdams H. H., Moerner W. E. (2004) Visualization of the movement of single histidine kinase molecules in live Caulobacter cells Proc Nat Acad Sci USA 101, 15921–6. 11. Kim S. Y., Gitai Z., Kinkhabwala A., Shapiro L., Moerner W. E. (2006) Single molecules of the bacterial actin MreB undergo directed treadmilling motion in Caulobacter crescentus Proc Nat Acad Sci USA 103, 10929–34. 12. Xie X. S., Choi P. J., Li G. W., Lee N. K., Lia G. (2008) Single-Molecule Approach to Molecular Biology in Living Bacterial Cells Annu Rev Biophys 37, 417–44. 13. Conley N. R., Biteen J. S., Moerner W. E. (2008) Cy3-Cy5 Covalent Heterodimers for Single-Molecule Photoswitching J Phys Chem B 112, 11878–80. 14. Bowman G. R., Comolli L. R., Zhu J., Eckart M., Koenig M., Downing K. H., Moerner W. E., Earnest T., Shapiro L. (2008) A Polymeric Protein Anchors the Chromosomal Origin/ParB Complex at a Bacterial Cell Pole Cell 134, 945–55. 15. Biteen J. S., Thompson M. A., Tselentis N. K., Bowman G. R., Shapiro L., Moerner W. E. (2008) Super-resolution imaging in live Caulobacter crescentus cells using photoswitchable EYFP Nat Methods 5, 947–9. 16. Moerner W. E., Fromm D. P. (2003) Methods of Single-Molecule Fluorescence Spectroscopy and Microscopy Rev Sci Instrum 74, 3597–619.

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17. Betzig E., Patterson G. H., Sougrat R., Lindwasser O. W., Olenych S., Bonifacino J. S., Davidson M. W., Lippincott-Schwartz J., Hess H. F. (2006) Imaging intracellular fluorescent proteins at nanometer resolution Science 313, 1642–5. 18. Rust M. J., Bates M., Zhuang X. (2006) Subdiffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) Nat Methods 3, 793–5. 19. Hess S. T., Girirajan T. P. K., Mason M. D. (2006) Ultra-high resolution imaging by fluorescence photoactivation localization microscopy Biophys J 91, 4258–72. 20. Thompson M. A., Biteen J. S., Lord S. J., Conley N. R., Moerner W. E. (2010) Molecules and Methods for Super-resolution Imaging Methods Enzymol 475, 27–59. 21. Wheeler R. T., Shapiro L. (1999) Differential localization of two histidine kinases controlling bacterial cell differentiation Mol Cell 4, 683–94. 22. Shapiro L., McAdams H., Losick R. (2002) Generating and exploiting polarity in bacteria Science 298, 1942–6. 23. Rudner D. Z., Pan Q., Losick R. M. (2002) Evidence that subcellular localization of a bacterial membrane protein is achieved by diffusion and capture Proc Nat Acad Sci USA 99, 8701–6. 24. Steinhauer J., Agha R., Pham T., Varga A. W., Goldberg M. B. (1999) The unipolar Shigella surface protein IcsA is targeted directly to the bacterial old pole: IcsP cleavage of IcsA occurs over the entire bacterial surface Mol Microbiol 32, 367–77. 25. Robbins J. R., Monack D., McCallum S. J., Vegas A., Pham E., Goldberg M. B., Theriot J. A. (2001) The making of a gradient: IcsA (VirG) polarity in Shigella flexneri Mol Microbiol 41, 861–72. 26. Gitai Z., Dye N., Shapiro L. (2004) An actin-like gene can determine cell polarity in bacteria Proc Nat Acad Sci USA 101, 8643–8. 27. Gitai Z., Dye N. A., Reisenauer A., Wachi M., Shapiro L. (2005) MreB actin-mediated segregation of a specific region of a bacterial chromosome Cell 120, 329–41. 28. Dye N. A., Pincus Z., Theriot J. A., Shapiro L., Gitai Z. (2005) Two independent spiral structures control cell shape in Caulobacter Proc Nat Acad Sci USA 102, 18608–13. 29. Van Den Ent E., Amos L. A., Lowe J. (2001) Prokaryotic origin of the actin cytoskelecton Nature 413, 39–44.

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30. Figge R. M., Divakaruni A. V., Gober J. W. (2004) MreB, the cell shape-determining bacterial actin homologue, co-ordinates cell wall morphogenesis in Caulobacter crescentus Mol Microbiol 51, 1321–32. 31. Dickson R. M., Cubitt A. B., Tsien R. Y., Moerner W. E. (1997) On/Off Blinking and Switching Behavior of Single Green Fluorescent Protein Molecules Nature 388, 355–8. 32. Shroff H., Galbraith C. G., Galbraith J. A., Betzig E. (2008) Live-cell photoactivated localization microscopy of nanoscale adhesion dynamics Nat Methods 5, 417–23. 33. Juette M. F., Gould T. J., Lessard M. D., Mlodzianoski M. J., Nagpure B. S., Bennett B. T., Hess S. T., Bewersdorf J. (2008) Threedimensional sub-100 nm resolution fluorescence microscopy of thick samples. Nat Meth 5, 527–9. 34. Huang B., Wang W., Bates M., Zhuang X. (2008) Three-Dimensional Super-Resolution Imaging by Stochastic Optical Reconstruction Microscopy Science 319, 810–3.

35. Pavani S. R. P., Thompson M. A., Biteen J. S., Lord S. J., Liu N., Twieg R. J., Piestun R., Moerner W. E. (2009) Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread function Proc Nat Acad Sci USA 106, 2995–9. 36. Shroff H., Galbraith C. G., Galbraith J. A., White H., Gillette J., Olenych S., Davidson M. W., Betzig E. (2007) Dual-color superresolution imaging of genetically expressed probes within individual adhesion complexes Proc Nat Acad Sci USA 104, 20308–13. 37. Bates M., Huang B., Dempsey G. T., Zhuang X. (2007) Multicolor super-resolution imaging with photo-switchable fluorescent probes Science 317, 1749–53. 38. Vaziri A., Tang J., Shroff H., Shank C. V. (2008) Multilayer three-dimensional super resolution imaging of thick biological samples Proc Nat Acad Sci USA 105, 20221–6.

Chapter 9 Fluorescence Microscopy of Nanochannel-Confined DNA Fredrik Persson, Fredrik Westerlund, and Jonas O. Tegenfeldt Abstract Stretching of DNA in nanoscale confinement allows for direct visualization of the genetic contents of the DNA on the single DNA molecule level. DNA stretched in nanoscale confinement also allows for studies of DNA–protein interactions and DNA polymer physics in confined environments. This chapter describes the basic steps to fabricate the nanostructures, to perform the experiments, and to analyze the data. Key words: DNA, Nanochannels, Single molecule, Fluorescence

1. Introduction Stretching of single DNA molecules in nanochannels occurs spontaneously due to the confinement and does thus not require any active application of force, for example through chemically attached anchor groups. Visualization of stretched DNA using fluorescence microscopy provides a diffraction-limited resolution corresponding to approximately 1 kbp. Furthermore, the length of the DNA in the channels scales linearly with the total length of the DNA (1). Confining DNA in nanochannels has previously shown applicability to both single-molecule studies of DNA–protein interactions (2, 3), and studies of DNA conformation and dynamics (1, 4–6). Possible future applications may include fingerprinting and investigations of finer structural rearrangements in the genome, such as copy number variations (CNV), microdeletions and insertions, as well as translocations (7). There are a few important parameters to consider when dealing with confined DNA: 1. Contour length – total length of the DNA backbone, here denoted L.

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_9, # Springer Science+Business Media, LLC 2011

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2. Persistence length – length-scale over which the DNA can be considered a rigid rod, here denoted P. 3. Effective width – a measure of the width of the DNA, composed of the physical width of the DNA (~2 nm) and an electrostatic contribution (8). The effective width is here denoted weff. When a long DNA molecule is free in solution it forms a coil, often characterized by its radius of gyration (RG). When confined in a tube-like confinement with a diameter Dav smaller than RG, the DNA stretches out in the tube. As long as the diameter of the tube is larger than P, the DNA can backfold and adopt an elongated coiled up conformation. In this regime, commonly denoted the deGennes regime, the DNA is modeled as a series of noninteracting blobs, where the DNA inside each blob behaves as it would in free solution. This leads to an extension, r, of the DNA along the channel of (9):
 r weff P 1=3 / ; 2 L Dav 2 , the parameter relating to the tube dimensions, can be replaced Dav by the geometric average of the height, D1, and the width, D2, of a 2 rectangular channel, Dav ¼ D1 D2 (10). What is convenient from an experimental point of view is that r scales linearly with L. This means that a position along the stretched DNA can be directly related to a position along the contour of the DNA, i.e., the sequence, with a resolution primarily determined by the degree of stretching and the optics of the microscope. The authors recommend refs. 1, 4, 6, 11–13 for further insight into the polymer physics of confined DNA. There is also a vast literature on general polymer theory, notably the books by deGennes (14), Doi and Edwards (15), and Rubinstein and Colby (16).

2. Materials 2.1. Fabrication of Chips

There are a multitude of ways to fabricate nanostructured chips depending on the facilities and equipment available (see Note 1) (17). We here present a fabrication scheme based on fused silica wafers, for which the following are needed: 1. Fused silica wafers (Available from Hoya). 2. 110-mm thick fused silica coverslips for sealing of the chips. The thickness is optimized for compatibility with oilimmersion objectives. (Available from Valley Design). 3. Access to clean-room equipment for photo (UV) and electron-beam (e-beam) lithography and reactive ion etching

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(RIE), as well as standard resists (e.g., AZ (photo lithography) and ZEP (e-beam lithography) resists) and chemicals from any large supplier. 2.2. Chemicals

Two important additives are b-mercaptoethanol (BME) (see Note 2) for suppression of photobleaching and polyvinylpyrrolidone (PVP) (see Note 3) for suppression of electroosmosis when using electrophoresis. Note that genomic length DNA should be handled with wide-orifice pipettes to avoid shear-induced breakage. (Available from e.g., Molecular Bioproducts)

2.2.1. Buffer for DNA Experiments

Tris–Borate–EDTA (TBE) is a standard buffer for DNA studies, especially for electrophoresis due to its low conductivity that ensures a low degree of Joule heating. TBE buffer consists of the following: 1. Tris (tris(hydroxymethyl)aminomethane): Buffering agent for slightly basic conditions (pH range 7– 9). 2. Boric acid: Weak acid that improves the buffering capabilities of Tris. 3. EDTA (Ethylenediaminetetraacetic acid): Chelating agent that scavenges multivalent metal ions, in particular magnesium (Mg2+). Since multivalent metal ions are common cofactors for many enzymes, such as nucleases that digest DNA, the removal of these ions will prevent enzymatic degradation of DNA.

2.2.2. Protocol for Preparing 1 L 5 TBE Buffer

1. Prepare 0.5 L of 0.5 M EDTA solution by weighing out 93.06 g of disodium EDTA (372.24 g/mol) and adding it to 350 mL of water (see Note 4). EDTA will not go into solution until pH is adjusted to 8.0. Add NaOH pellets to the solution, one by one, while stirring vigorously on a magnetic stir plate. Monitor solution pH using a digital pH meter so as not to overshoot. Bring the final solution volume to 0.5 L with water. 2. Prepare a 5 TBE solution by adding 20 mL of 0.5 M EDTA solution from item 1, 54 g of Tris (121.1 g/mol) and 27.5 g of boric acid (61.8 g/mol) to 800 mL of water. Then adjust pH to 8.0–8.5 by adding HCl while monitoring pH. Bring final solution volume to 1 L with water. 3. Autoclave the buffer. This stock buffer can be diluted to any arbitrary ionic strength. For the following steps, 0.5 TBE buffer is used as an example. 4. Dilute the 5  TBE buffer ten times. Then use a syringe with a 0.2-mm filter to aliquot approximately 1.2 mL of buffer into a large number of 1.5 mL microcentrifuge tubes. Store these

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tubes in the refrigerator for future use. Degas the buffer prior to use. The final 0.5 TBE solution contains 44.6 mM Tris, 44.5 mM boric acid, and 1 mM EDTA and has an ionic strength of approximately 15 mM at pH 8.5. 2.2.3. Protocol for Staining 1 mL of 10 mg/mL DNA at a Dye Ratio of 10:1 in 0.5 TBE Buffer

Always use wide-orifice pipette tips to handle DNA solutions. 1. Create 250 mL of 50 mg/mL solution of DNA in 0.5 TBE (see Note 5). 2. Pipette 769 mL of 0.5 TBE buffer into a separate 1.5-mL microcentrifuge tube. 3. Pipette 47.5 mL of 0.5 TBE buffer into a 0.65-mL tube. Add 2.5 mL of YOYO-1 from the stock solution (1 mM). This creates a 50 mM dye solution. Work in low light from now on to avoid bleaching of the dye. 4. Pipette 31 mL of the 50 mM dye solution from item 3 into the buffer-filled tube from item 2. This creates a solution with a dye concentration of 1.55 mM. Vortex and centrifuge the solution to evenly distribute the dye. 5. Pipette 200 mL of DNA from item 1 into the buffer filled tube from item 4. Do not ever vortex or centrifuge solutions containing DNA – that will fragmentize the DNA. In order to mix the DNA, use a wide-orifice tip and gently pipette a part of the solution a minimum of three times while evenly distributing the ejected solution throughout the tube. 6. To evenly distribute the dye throughout the population of molecules, wrap the tube in aluminum foil and heat the solution to 50 C for 3 h and then store at 4 C.

2.2.4. Protocol for Preparing 500 mL Loading Buffer and 100 mL DNA in Loading Buffer

1. Mix 485 mL of degassed buffer with 15 mL of BME (see Note 6) in a 0.65-mL microcentrifuge tube. BME will collect at the bottom of the tube, so mixing by pipetting and/or vortexing is essential at this stage. Note that vortexing should not be performed after the DNA has been added. Below, we refer to this as the loading buffer. 2. Pipette 95 mL of the loading buffer into a 0.65-mL microcentrifuge tube. 3. Add 5 mL of the 10-mg/mL solution of stained DNA using wide-orifice pipettes. Mix the solution very gently with the pipette. Work in low light to protect the DNA, and wrap the tube in aluminum foil once the DNA-solution is made. Below, we refer to this as the DNA loading sample.

2.3. DNA Samples

In order to characterize the experimental techniques, it is necessary to use monodisperse DNA. There are a few different purified and monodisperse DNA solutions commercially available, and using

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Table 1 Selection of commercially available DNA molecules Name

Length (kbp)

Supplier

l-DNA

48.5

New England Biolabs

l-DNA concatamers (in gel)

48.5  n (n 1–50)

New England Biolabs

Yeast DNA (in gel plug)

3500 – 5700

Bio-Rad Laboratories

T4GT7-DNA

166

Nippon Gene

Charomid 9 (circular)

19.7–42.2

Nippon Gene

T7

39.9

Yorkshire Bioscience

restriction enzymes different size distributions can be obtained. Table 1 above lists a few common examples of commercially available, purified and monodisperse DNA. 2.4. Fluorescence Microscopy

For a thorough introduction to microscopy, the authors recommend the MicroscopyU Web site from Nikon (http://www. microscopyu.com), especially the tutorial section on fluorescence microscopy (http://www.microscopyu.com/articles/fluorescence/ index.html), as well as ref. 18. Owing to the low light levels and the risk of photodamaging the DNA, the optical system must be designed to maximize photon detection probability and signal-to-noise ratio. Key considerations are as follows: 1. High-quality filters with high transmission (~90%) in the wavelength region relevant for the dye used and low transmission in the rest of the spectrum, corresponding to a high optical density (OD > 5). 2. Objectives (40–100) with high numerical apertures (NA). Oil-immersion objectives readily achieve NA of 1.4 but have a working distance (WD) of only 100–200 mm. To combine a good NA and a large WD, a 60 water immersion objective with an NA of 1.0 and a WD of 2 mm, originally designed for electrophysiology by Nikon, can be used. This provides sufficient clearance to accommodate thick and easy-to-use cover glasses in the chip-fabrication process. 3. A detector with high quantum yield (QY) and low noise. Electron-multiplying CCDs (EMCCD) have an integrated, virtually noiseless, amplification on the CCD chip. As opposed to intensification technologies based on multichannel plates, the EMCCD is not easily damaged by excessive light levels.

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The EMCCD can be back-thinned to allow for a QY approaching 90–95% over the visible spectrum. Less expensive EMCCDs are not back-thinned and thus suffer from QYs that are roughly a factor of two lower. To minimize thermal noise, the CCD is normally cooled from 50 to 100 C in modern cameras. EMCCDs are available from, for example, Andor, Photometrics, and Hamamatsu. See Note 7 for examples of additional optical tools and technologies. 2.5. Addressing the Chip

The two most common ways of manipulating DNA in fluidic systems are by electrophoresis or pressure-driven fluid flow. In order to have both these capabilities, a chip holder with both electrical and air pressure connections to internal reservoirs can be used (Fig. 1) (19). The holder can be fabricated in Lucite® (PMMA), allowing the sample to be illuminated from the top and making it easy to detect bubbles trapped in the reservoirs in the chip holder. However, Lucite® has poor resistance to solvents, as it swells and dissolves easily. For experiments involving more aggressive solvents, a holder made in PEEK (Polyetheretherketone) is more suitable, but then the holder is opaque. The holder in Fig. 1 has eight independently accessible reservoirs that are connected to the fabricated chips by pressing the chip against o-rings mounted in the bottom of the reservoirs using a stainless steel frame that is screwed into the chip holder. The other end of the reservoirs is sealed with o-rings and screws with integrated electrodes, supplying the electrical connection to the buffer for electrokinetic transport. Pumps are needed for controlling DNA using pressure-driven flow. Standard diaphragm pumps capable of producing pressures of up to 5 Bar are sufficient in most cases (available from VWR).

Fig. 1. Example of chuck for mounting samples. Eight reservoirs linked by o-rings to the fluidic access holes on the chip. Each reservoir is individually addressable by pressure and electrical connections. Reproduced with permission from ref. 19.

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When using pressure-driven flow the pressure is routed through a network of valves giving the possibility of applying pressures to selected reservoirs while others are kept at ambient pressure. To control the pressure, a needle valve can be used as a leak valve, which enables the pressure to be controlled with an accuracy of down to 2 mBar. Accessories such as manifolds, needle valves, and tubing to direct and control the pressure are available from Cole Parmer. When using electrophoresis to control the DNA, a power supply and electrodes are needed. Platinum wires dipped into the DNA solution in the reservoir are often sufficient as electrodes. The electrophoretic mobility of DNA is on the order of 1 mm/s per V/cm. 2.6. Data Analysis

Commonly used software packages for data analysis are as follows: 1. ImageJ – A Java™ based freeware image processing and analysis software developed at the National Institutes of Health, USA (http://rsbweb.nih.gov/ij/). The software benefits from the extensive use of open-source plug-ins developed by users. The MBF plug-in set from the Biophotonics Facility at McMaster University is recommended (http://www. macbiophotonics.ca/imagej/). 2. MatLab – A common high-level technical computing language from The Mathworks™. 3. FreeMat – Open-source freeware available at http://freemat. sourceforge.net/. 4. GNU Octave – Freeware available at http://www.gnu.org/ software/octave/.

3. Methods 3.1. Design and Fabrication of Chips 3.1.1. Design

A careful design of the DNA-visualization device is crucial for its user-friendliness. Typically, two or four U-shaped inlet channels (50 mm  1 mm, each connected to two reservoirs) for efficient fluid transport are combined with nanoscale channels for stretching of the DNA. In this way, the sample can be transported quickly through the large channels to the entrance of the nanochannels by applying a driving force across the microchannel, enabling rapid exchange of buffer. Using nanochannels of dimensions 100 nm  100 nm ensures both a relatively high degree of DNA stretching (~60%) without encountering many of the problems that appear when the channel size approaches the persistence length of DNA (~50 nm). The degree of stretching can be tuned by altering the buffer conditions (20), such as the ionic strength.

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See Notes 8–10 for examples on how to include extra functionalities on the chip. An important concern is the introduction of the DNA into the nanochannels. There is a significant entropic barrier between the large micron-scale channels and the nanochannels (21). To facilitate the entry of the DNA, a gradual change in entropy can be used. This can be implemented by a gradually evolving degree of confinement combined with obstacles, such as pillar arrays, for prestretching the DNA (1). 3.1.2. Fabrication

When fabricating nanofluidic channels for optical observation of stretched DNA, there are some requirements to consider: 1. The channels should be sealed. 2. At least one side (substrate or lid) must be optically transparent. 3. The surface of the channels should be negatively charged with a minimal roughness to prevent sticking and entanglement of the DNA. 4. The material used should be hydrophilic to allow for easy wetting of the channels. In the following section, a commonly used fabrication process based on fused silica is outlined. A full-scale clean room, with spinners for resist deposition, mask aligners for exposure of micron scale patterns and an electron-beam writer for definition of nanoscale structures, is required (see Note 11). Reactive-ion etchers are used for etching channels with straight walls. In order to align the nanostructures and the microchannels, it is useful to first define alignment marks in the wafer periphery. This can be done by either etching or depositing metals on the wafer (see Note 12), the latter described below. It is assumed that the clean room used has its own standard processes for the following steps.

3.1.3. Definition of Alignment Marks

1. Treat the fused silica wafers with HMDS (hexamethyldisilazane) to increase resist adhesion. 2. Spin-coat and bake a combination of resists used for liftoff, e.g., a LOR/AZ or other similar sandwich constructs, to enable a pattern with an undercut. 3. Expose and develop the resist to create the undercut structure. 4. Run a low-power oxygen descum plasma to remove remaining resist residues. 5. Evaporate a 5-nm Cr (or Ti) adhesion layer and subsequently a 50–80-nm thick Au layer.

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6. Strip the resist using a chemical stripper, e.g., Microposit Remover 1165 or acetone (see Note 13). 3.1.4. Definition of Nanochannels

1. Treat the fused silica wafers with HMDS to increase resist adhesion. 2. Spin-coat and bake a 150–250 nm thick layer of ZEP520A e-beam resist. ZEP is chosen because of its good dry-etch resistance. Other resists can be used, but they often require deposition of an extra metallic etch mask. 3. Thermally evaporate 15 nm Al on top as a discharge layer. (This is only needed when working with isolating substrates such as fused silica.) 4. Expose the resist (exposure dose approximately 280 mC/cm2 at 100 kV). 5. Remove the Al layer using, for example, MF322 developer. 6. Develop the resist using, for example, ZED N50 developer. 7. Run a low-power oxygen descum plasma to remove remaining resist residues. 8. Etch the nanochannels into the fused silica using RIE with CHF3/CF4 chemistry. 9. Strip the resist using a chemical stripper, e.g., Microposit Remover 1165.

3.1.5. Definition of Microchannels

1. Treat the fused silica wafers with HMDS to increase resist adhesion. 2. Spin-coat and bake a 2–5 mm thick layer of photoresist, e.g., an AZ resist, that has relatively high etch resistance. 3. Expose and develop the resist. 4. Run a low-power oxygen descum plasma to remove remaining resist residues. 5. Etch the microchannels (approximately 1 mm deep) using RIE with CHF3/CF4 chemistry. 6. Strip the resist using a chemical stripper, e.g., Microposit Remover 1165 or acetone.

3.1.6. Drilling of Access Holes

There is a multitude of ways of producing access holes through a wafer (see Note 14). Here, we describe a setup based on powder blasting. 1. Spin-coat at least 5 mm photoresist on both sides of the wafer. 2. Cover the backside (i.e., the nonstructured side) with an adhesive plastic film, e.g., 70 mm thick Nitto SWT 20 film (see Note 15). 3. Make holes through the film over the reservoir structures using a scalpel or for example laser ablation.

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4. Powder-blast using 50–110 mm sized Al2O3 particles from the backside of the wafer (i.e., the nonstructured side). A small powder-blasting tool and the powder can be obtained from Danville Materials. 5. Remove the film, strip the resist in a chemical stripper and/or acetone, and carefully clean the wafers in an ultrasonic bath. 3.1.7. Sealing of the Chips

The last step in the production of the chips is sealing. This can be done in several different ways depending on the material of the chips (see Note 16). Fused silica can be bonded covalently via condensation of hydroxyl groups when two surfaces are brought together. Table 2 summarizes two standard ways of creating a high density of the necessary hydroxyl groups, involving thorough cleaning to remove organic residues and subsequent surface activation (see Note 17). For the RCA-based method, the hydrogen peroxide should be added after the mixture has reached the correct temperature to avoid disintegration of the hydrogen peroxide.

3.2. Chemicals

When using techniques for studying single DNA molecules, it is very important that the molecules are kept in a controlled environment and not subjected to reactive contaminants such as radicals or enzymes that damage or digest DNA. Some of these enzymes, such as endonucleases, are present on our skin to break down foreign DNA that we come in contact with. It is, therefore, crucial that gloves are worn at all times when handling DNA and that all tools and pipette tips that come in contact with either the

Table 2 Two fusion-bonding protocols for fused silica (see Note 17) RCA-based

Piranha-based

Chemical

Time

Chemical

RCA2 at 80 C (1:1:5 HCl–H2O2–H2O)

10 min Piranha (1:3 H2O2–H2SO4)

Time 20 min

Rinse carefully with DI water for 5 min RCA1 at 80 C (1:1:5 NH4OH–H2O2–H2O) 10 min Ammonium hydroxide (NH4OH) 40 min Rinse carefully with DI water for 5 min Blow dry in N2 Press together by hand to form a prebond Anneal at 1,050 C for at least 3 h (ramp temperature at approximately 300 C/h for both heating and cooling)

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buffer or the DNA samples have been autoclaved or sterilized in another way, e.g., by wiping them with ethanol. 3.2.1. Fluorescent Labeling of DNA

Dimeric cyanine dyes such as YOYO®-1 (YOYO) (Invitrogen, Carlsbad, CA, USA) are extensively used for imaging single DNA molecules (4, 22) due to their high binding affinity (KA ¼ 1010–1012 M1) and a fluorescence enhancement upon binding to DNA of over 1,000, which ensures a low fluorescence background from unbound dye molecules (23). Figure 2 shows the absorption and emission spectra as well as the chemical structure of YOYO (24). At moderate binding densities, YOYO binds to DNA by bis-intercalation and increases the contour length of DNA by approximately 0.68 nm per YOYO molecule (one base pair (0.34 nm) per intercalation event) (25, 26). Note that the highly charged YOYO affects the physical properties of DNA (11, 27). When staining the DNA, it is important to know the resulting dye ratio ([base pair]–[dye molecule]). The easiest way of calculating this is to use the molar concentration of the dye and DNA, respectively. If the concentration of DNA is known in mg/mL, it is easily converted using the molar mass of one DNA base pair (bp), Mbp ¼ 618 g/mol. The DNA concentration can also be determined by absorbance measurements, using the molar absorption coefficient for DNA at l ¼ 260 nm, e260 ¼ 13,200 cm1 M1 (base pair) or 50 mg/mL for OD 1 (1 cm optical path length).

Fig. 2. (Left ) Excitation (solid )/emission (dashed ) spectra of YOYO®-1. Adapted from data from Invitrogen. Inset: TOTO®-1 intercalating in DNA, visualized using the open-source viewer JMol. The structure (PDB ID: 108D) was determined by nuclear magnetic resonance (24). (RIGHT ) Chemical structure of YOYO®-1.

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Knowing the molar concentrations of the DNA and the dye, the dye ratio is readily obtained. In the case of dimeric cyanine dyes, such as YOYO, the DNA should not be stained at dye ratios higher than 10:1 to avoid crowding of dye on the DNA. 3.3. Running Experiments (Loading of DNA)

Prior to mixing the loading buffer, the TBE buffer should be degassed in a vacuum chamber for 2 h to reduce the amount of dissolved air in the system and to avoid bubble formation in the channels. The degassing process can be shortened to about 10–20 min by ultrasonic agitation. Fresh loading buffer should be prepared in conjunction with every experiment, since the BME degrades with time (see Note 18). Use the loading buffer to wet the chip. Placing droplets over the fluidic access holes is normally sufficient to wet the chip by capillary forces (see Note 19). Remaining air bubbles can be removed by applying a pressure across the channels or by submerging the chip in buffer and placing it in a vacuum desiccator overnight for degassing. Using degassed buffer solution during experiments ensures that bubbles formed during the capillary wetting (28) are absorbed into the liquid and also prevents the DNA from degrading. When the chip is properly wetted, it is mounted in the chip holder. Thereafter, the DNA loading sample is added to the desired reservoirs and loading buffer to the remaining reservoirs. The DNA can be moved through the chip by electrokinetic transport or pressure-driven flow. A pressure difference of approximately 100 mBar results in reasonable sample velocities when transporting the DNA in the micron-sized channels, from the inlet reservoirs to the nanostructures. Once the DNA molecules are in close proximity to the inlets of the nanochannels, the driving force is shifted so that it is applied across the nanochannel array instead. The most convenient way to introduce DNA into the nanochannels is to pulse the pressure, switching rapidly between a low pressure and 1–3 Bar. When the DNA molecule of interest is in the nanochannel and in the field of view of the CCD, stacks of images of at least 200 frames are recorded (see Note 20). During the measurements, the coordinates of at least two alignment marks on the chip as well as the stage coordinates for all the recorded stacks should be recorded. This allows for both rotational correction as well as accurate localization of the molecule within the fluidic network in the case of a more intricate design of the chip. There are a few things to be aware of during image/data acquisition: 1. If one of the ends of the DNA molecule appears much brighter, it might have been folded while entering the nanochannel. Given time (usually minutes), the end will unfold;

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else, the molecule can be pushed out into the microchannels and reinjected into the nanochannels. 2. A small pressure offset when using pressure-driven flow can cause the molecule to not be in its equilibrium state while imaging. 3. Photonicking may cause the DNA to be cut into smaller pieces while imaging. However, the ordering of the fragments will not change, since two pieces cannot diffuse past each other while confined in a nanochannel. 4. During long imaging periods, the molecules will most likely fade significantly in fluorescence intensity due to photobleaching, especially in the absence of BME. 5. The DNA present close to the nanochannels can suffer from some degree of photobleaching and photonicking during imaging of the DNA in nanochannels. Therefore, an important consideration is to make sure that the illuminated area does not extend beyond the region of interest, if necessary using the field aperture. 3.4. Data Analysis

To extract essential parameters from the movies (or rather stacks of images) of DNA molecules confined in a nanofluidic structure, a simple pattern recognition and fitting script can be used (1). The key steps of the analysis are listed and explained below. 1. The position of the DNA molecule is detected. A region of interest (ROI) is created around the molecule and the rest of the image is discarded to reduce the amount of data to store (Fig. 3a) (19). 2. The pixels are summed over the width of the extended DNA yielding a one-dimensional intensity profile of the molecule. 3. Step 2 is repeated for each frame in the movie, except that the molecule is identified based on its position in the previous frame. Stacking these intensity profiles next to each other yields a timetrace (also known as a kymograph) (Fig. 3b). In this way, a whole movie can be reduced to one single composite image. 4. The intensity profiles are fitted to a model profile, described below, by a least-square algorithm (Fig. 3c). This fitting provides the center position, intensity (with subtracted background) and length of the DNA for each frame in the original movie. The model intensity profile, I(x), consists of a convolution of a modified box function (height I0, length Lx) with a Gaussian point-spread function (PSF), with a full width at half maximum l (FWHM) of 2:35 s0 ¼ 0:61 NA (l is the wavelength of the light

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Fig. 3. (a) The first fluorescence image in an image stack. A box is drawn enclosing the extended DNA molecule. The scale bar corresponds to 20 mm. (b) Time trace obtained by averaging over the molecule shown in (a) in the direction transverse to the DNA extension for every frame. Each column of pixels corresponds to the averaged intensity profile of one frame. The scale bars correspond to 20 mm and 10 s, respectively. (c) The intensity profile I (x ) and the corresponding fit for one column of the time trace. (d) A histogram over all the fitted lengths from one movie containing 400 frames. The data is well described by a Gaussian distribution (solid line). Reproduced with permission from ref. 19.

and NA is the numerical aperture of the objective) (see Note 21) (1). The model is represented by the following equation: I0 I ðxÞ ¼ Ibg þ 2 

 x  x0 x  ðx0 þ L0 Þ pffiffiffi  ð1 þ BÞ Erf pffiffiffi  ð1  BÞ Erf ; s0 2 s0 2 where Ibg is the background intensity value, B is a numerical factor introduced to allow for a nonconstant background, Erf is the error function, and x0 is the center position of the box function (see Note 22). It is important to realize that the biologically relevant gauge of resolution in these experiments is base pairs and not nanometers

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or pixels. Standard fluorescence microscopy has a resolution limited by diffraction to roughly half the wavelength of the detected light. The resolution in base pairs is determined by the degree of DNA stretching, the DNA fluctuations and the total photon budget. Thus, maximum resolution is obtained in channels with the smallest possible cross section yielding fully stretched DNA with a minimum of thermal fluctuations. In practice, there is an optimum resolution for each experiment and it is important to design the experiments accordingly. A relatively low resolution is appropriate when targeting the overall structure of chromosomes and can be done in a fast way without extensive efforts. On the contrary, studies of a selected region of interest along the genome may require the highest possible resolving power, requiring extensive efforts in terms of data acquisition, storage, and handling. In some applications, the resolving power per se is not relevant; instead, the positioning of one or more specific labels contains the important information. In this case, the measurement uncerpffiffiffiffiffi tainty scales roughly as 1= N where N is the number of detected photons, giving accuracies approaching a single nanometer (29).

4. Notes 1. One common fabrication method uses nanoimprint lithography (NIL). This has the benefit that it is possible to order finished master stamps commercially (available from NIL Technology, Denmark), thus eliminating the need for an electronbeam lithography system. A common mass production technique, capable of defining nanostructures, is injection molding. With suitable choice of low-fluorescence polymer matrix, it may prove useful for large series of devices. Although focused ion beam (FIB) milling is a slow linear technique, it may find use for creating complicated three-dimensional structures with resolution comparable to that of electron-beam lithography. Direct laser writing systems (available from Nanoscribe GmbH, Germany) are now also capable of creating complex three-dimensional structures with feature sizes below 100 nm. A multitude of more exotic alternative fabrication techniques are described in the literature. 2. 0.1 M dithiothreitol (DTT) can replace BME as reducing agent. 3. Performance Optimized Polymer 6 (POP6) from Applied Biosystems can be used as an alternative to PVP. 4. Whenever water is mentioned in the context of buffer composition, we refer to ultrapure water with resistivity 18.2 MO cm

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(at 25 C) (referred to as Milli-Q water when using water purification equipment from the Millipore Corporation). 5. DNA in stock solutions at concentrations of 100–500 mg/mL is very viscous and hard to pipette accurately. Tip the tube sideways and suck in the solution very slowly to ensure that the correct amount of DNA is withdrawn. (For l-DNA from New England Biolabs the stock solution is 500 mg/mL, so 25 mL of the solution is added to 225 mL of 0.5 TBE in a 1.5-mL microcentrifuge tube.) When working with lambda phage DNA, it may be advisable to heat it to 50 C for 10 min in a microcentrifuge tube heater and quench in icy water to avoid concatamers due to the hybridization of the single-strand overhangs. 6. BME, a highly toxic chemical that serves as a biological antioxidant by scavenging oxygen and hydroxyl radicals in the buffer, thereby preventing photobleaching and photoinduced damage (photonicking) of the DNA. An enzymatic oxygen scavenger system may constitute a useful alternative when reducing agents cannot be used. It consists of 0.2 mg/mL glucose oxidase, 0.04 mg/mL catalase and 4 mg/mL b-D-glucose (available from Sigma-Aldrich). The oxygen scavenger system can be combined with BME but typically does not provide any additional benefit for the experiments listed. 7. One useful option in a fluorescence microscope is a unit that sends a selected field of view through two different optical paths and projects the resulting images on two separate areas of the CCD. This allows the user to acquire two (or more) colors or two polarization directions simultaneously. Existing systems include DV2™ from Photometrics and OptoSplit™ from Cairn Research. To improve imaging resolution, a wide range of novel techniques have been developed, each one capable of reaching a resolution of below 100 nm (30). They essentially fall into three categories: local quenching of the fluorescence emission (STED), repeated photoactivation and subsequent imaging of a subset of the fluorophores in the sample (STORM, FPALM), and structured illumination (SIM). Most imaging is carried out with B/W cameras giving information on the intensity in each pixel. For additional contrast information, multicolor (spectroscopic) or fluorescence life-time imaging (FLIM) may be utilized. 8. In order to expose the DNA to a gradual change in confinement in one single chip, it is possible to use funnel-like channels (6). This is an analogue to force spectroscopy techniques using optical tweezers that allows for probing of low DNA

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Fig. 4. (Left ) Chip design with nanochannels spanning between two U-shaped microchannels. This design enables fast buffer exchanges since all of the liquid does not have to pass through the nanochannels. The size of each chip as seen in the lower image is 1  1 in. In order to visualize the nanochannel region, the central region is exaggerated. (Right ) Schematics of a similar design as the left one with an added nanoslit oriented perpendicular to the nanochannel array. In the nanoslit, the nanochannels become nanogrooves in the bottom, working as entropic traps for the DNA. This design also allows for enrichment of DNA in the nanogrooves by applying positive pressures at both ends of the nanochannels. In order to visualize the nanochannel region, the central region is exaggerated. The nanoslit and nanochannels are 50 mm and 100 nm wide respectively. Reproduced with permission of The Royal Society of Chemistry from ref. 36.

extensions, corresponding to forces in the femtonewton regime, without anchoring the molecules. Another feature that can be added to the chip is demonstrated in Fig. 4 (right). In this chip design, a nanoslit is etched orthogonal to the nanochannels. This allows for enrichment of DNA in the nanogrooves by applying moderate positive pressures at both ends of the nanochannels. If the slit is sufficiently shallow, entropy keeps the DNA in the grooves while buffer flows through the slit. This design also allows for changing the chemical environment of the DNA, by flushing the desired solution in the slit, while monitoring the DNA in real time. 9. When analyzing long, genomic DNA extra care has to be taken due to the relatively large size of the molecules. Considering human DNA, it can be noted that the largest single DNA molecule has a fully extended length of over 8 cm (chromosome 1). If the DNA molecule is too long for the whole molecule to be easily extended in a single nanochannel, one possibility is to stretch it by shear flow (31) in a device made by conventional photolithography. With this approach, there is no need for nanofabrication. However, it is a dynamic

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system in which the DNA conformation will not be at equilibrium as compared to DNA confined in nanochannels. 10. The layout of a DNA analysis chip may also contain features for sample preparation such as cell-sorting, cell lysis, DNA extraction and purification, and DNA staining in addition to the actual analysis of the DNA molecules. This kind of integration would enable the analysis of DNA from a single cell, which would be especially useful in the study of e.g., rare circulating tumor cells. A potentially very useful development with this regard is the use of deterministic lateral displacement to continuously guide cells and chromosomes through different chemical environments for cell lysis and DNA staining (32). 11. Even without an e-beam writer, slit-like channels (depth in the nanometer range and widths larger than 0.5 mm) can readily be defined with UV lithography and carefully tuned RIE etching. 12. Alignment marks can alternatively be formed by anisotropic RIE etching, and in the case of silicon also through anisotropic wet etching using, for example, KOH. If etching is used to define the alignment marks, it is important that they provide a sufficient contrast for the alignment in the mask aligner. An etch depth of at least 200 nm is recommended. For metal alignment marks it is also possible to first deposit a layer of metal and subsequently spin on and pattern a photoresist and in a last step etch away the exposed metal. Al is commonly etched using either a wet etch using phosphoric acid or a dry etch containing chlorine chemistry. Au is commonly etched by using wet etches of either potassium iodine or aqua regia (1:3 HNO3–HCl). 13. Instead of using chemicals, the resist can be stripped by an oxygen plasma treatment. However, this is not recommended since it can burn the resist, making it very hard to remove, and also induces roughness on the sample surface. 14. Examples include micromilling, deep reactive ion etching (DRIE) or ultrasonic drilling. However, these techniques often demand some specialized equipment, which is very expensive compared to that needed for powder blasting. 15. Instead of using a soft film to mask the wafers/chips during powder blasting, a metal mask defined in a thick brass plate can be used. The chip is then attached to the metal mask using reversible thermal glue. It should be noted that since the metal mask is hard, it will also be degraded by the powder blasting, which attacks hard surfaces. 16. Polymer-based devices are generally sealed using polymer fusion bonding. The device is bonded to a lid with a polymer film by heating until the polymer layers on the chip and lid intermix. The combination of polymer compositions and

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temperatures must be carefully chosen to create a sufficiently strong bond while maintaining the structural integrity of the micro- and nanochannels. Anodic bonding is the standard technique to bond borosilicate glass to silicon, also for silicon with a hydrophilic oxide layer, but it might cause wide nanochannels (nanoslits) to collapse. 17. The Piranha-based protocol can be used to bond silicon with a thin layer of oxide (<150 nm) and borosilicate glass. However, the final annealing should in this case be done at moderate temperatures of 400–450 C to avoid excessive strain due to the difference in thermal expansion coefficient between silicon and glass (33). 18. BME degrades in the presence of oxygen, and therefore, a small amount should be transferred to a microcentrifuge tube and used for the experiments to avoid opening the main bottle too many times. The main bottle should be filled with nitrogen after each time it is opened. A sealed bottle is expected to be stable for at least 3 years. The BME in a mixed loading buffer will last approximately 1 day. 19. For chips that are difficult to wet, e.g., in the case of hydrophobic materials or dead-end channels, critical point wetting (34) can be used. However, critical point wetting requires that the material used is capable of withstanding at least the temperature at the critical point of water, T ¼ 374 C. 20. The frame rate should be selected based on the timescales of interest. Long exposure times might blur the image due to drift and diffusion of the DNA. Signal-to-noise might become insufficient for very short exposure times. For typical imaging applications, 10 fps is a suitable choice. Very short exposure times enable detailed studies of dynamics and fluctuations, typically occurring at higher rates than 10 Hz. Long exposure times can, on the contrary, be used to discern bound molecules from freely diffusing molecules. It has also been shown that altering the exposure times makes it possible to obtain binding kinetics for transcription factors on DNA (35). 21. More intricate pattern recognition algorithms can be used to detect the position and relative intensity of distinct fluorescent probes along the DNA, variation in fluorescence labeling or intensity fluctuations associated with the sequence or physical properties of DNA. 22. It should be noted that to be mathematically rigorous an Airy function should be used for an ideal optical system rather than the more convenient-to-use Gaussian approximation. Furthermore, to fully optimize the analysis, it has been shown that a careful choice of fitting function that closely mimics the real PSF will give a slight but significant improvement.

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Acknowledgments We thank Camilla Freitag for valuable discussions and comments on the manuscript. This work was supported by the European Community’s Seventh Framework Program [FP7/2007–2013] under grant agreement number [HEALTH-F4–2008–201418] entitled READNA, the Swedish Research Council under grants number 2007-584 and 2007-4454 and the Knut and Alice Wallenberg Foundation. References 1. Tegenfeldt, J. O., Prinz, C., Cao, H., Chou, S., Reisner, W. W., Riehn, R., Wang, Y. M., Cox, E. C., Sturm, J. C., Silberzan, P., and Austin, R. H. (2004) The dynamics of genomic-length DNA molecules in 100-nm channels, Proceedings of the National Academy of Sciences of the United States of America 101, 10979–10983. 2. Wang, Y. M., Tegenfeldt, J. O., Reisner, W., Riehn, R., Guan, X. J., Guo, L., Golding, I., Cox, E. C., Sturm, J., and Austin, R. H. (2005) Single-molecule studies of repressorDNA interactions show long-range interactions, Proceedings of the National Academy of Sciences of the United States of America 102, 9796–9801. 3. Riehn, R., Lu, M. C., Wang, Y. M., Lim, S. F., Cox, E. C., and Austin, R. H. (2005) Restriction mapping in nanofluidic devices, Proceedings of the National Academy of Sciences of the United States of America 102, 10012–10016. 4. Reisner, W., Morton, K. J., Riehn, R., Wang, Y. M., Yu, Z. N., Rosen, M., Sturm, J. C., Chou, S. Y., Frey, E., and Austin, R. H. (2005) Statics and dynamics of single DNA molecules confined in nanochannels, Physical Review Letters 94, 196101. 5. Persson, F., Westerlund, F., Tegenfeldt, J. O., and Kristensen, A. (2009) Local Conformation of Confined DNA Studied Using Emission Polarization Anisotropy, Small 5, 190–193. 6. Persson, F., Utko, P., Reisner, W., Larsen, N. B., and Kristensen, A. (2009) Confinement Spectroscopy: Probing Single DNA Molecules with Tapered Nanochannels, Nano Letters 9, 1382–1385. 7. Stankiewicz, P., and Lupski, J. R. (2002) Genome architecture, rearrangements and genomic disorders, Trends in Genetics 18, 74–82.

8. Vologodskii, A., and Cozzarelli, N. (1995) Modeling of long-range electrostatic interactions in DNA, Biopolymers 35, 289–296. 9. Daoud, M., and de Gennes, P. G. (1977) Statistics of macromolecular solutions trapped in small pores, Le Journal de Physique 38, 85–93. 10. Turban, L. (1984) Conformation of Confined Macromolecular Chains - Crossover Between Slit and Capillary, Journal De Physique 45, 347–353. 11. Zhang, C., Zhang, F., van Kan, J. A., and van der Maarel, J. R. C. (2008) Effects of electrostatic screening on the conformation of single DNA molecules confined in a nanochannel, Journal of Chemical Physics 128. 12. Hsieh, C. C., and Doyle, P. S. (2008) Studying confined polymers using single-molecule DNA experiments, Korea-Australia Rheology Journal 20, 127–142. 13. Persson, F., and Tegenfeldt, J. O. (2010) DNA in nanochannels - directly visualizing genomic information, Chemical Society Reviews 39, 985–999. 14. de Gennes, P. G. (1979) Scaling Concepts in Polymer Physics, Cornell University Press, Ithaca, NY. 15. Doi, M., and Edwards, S. F. (1986) The Theory of Polymer Dynamics, Vol. 73, Oxford University Press, Inc., New York. 16. Rubinstein, M., and Colby, R. H. (2003) Polymer Physics, Oxford University Press, New York. 17. Madou, M. J. (2002) Fundamentals of Microfabrication: the science of miniaturization, 2 ed., CRC Press LLC. 18. Mertz, J. (2010) Introduction to optical microscopy, Roberts and Company Publishers, Greenwood Village. 19. Persson, F. (2009) Nanofluidics for Single Molecule in DTU Nanotech - Department of

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Micro- and Nanotechnology, Technical University of Denmark, Kongens Lyngby. 20. Reisner, W., Beech, J. P., Larsen, N. B., Flyvbjerg, H., Kristensen, A., and Tegenfeldt, J. O. (2007) Nanoconfinement-enhanced conformational response of single DNA molecules to changes in ionic environment, Physical Review Letters 99, 058302. 21. Han, J., Turner, S. W., and Craighead, H. G. (1999) Entropic trapping and escape of long DNA molecules at submicron size constriction, Physical Review Letters 83, 1688–1691. 22. Quake, S. R., Babcock, H., and Chu, S. (1997) The dynamics of partially extended single molecules of DNA, Nature 388, 151–154. 23. Glazer, A. N., and Rye, H. S. (1992) Stable dye-DNA intercalation complexes as reagents for high-sensitivity fluorescence detection, Nature 359, 859–861. 24. Spielmann, H. P., Wemmer, D. E., and Jacobsen, J. P. (1995) Solution Structure of a DNA Complex with the Fluorescent Bis-Intercalator TOTO Determined by NMR-Spectroscopy, Biochemistry 34, 8542–8553. 25. Lerman, L. S. (1961) Structural Considerations in Interaction of DNA and Acridines, J. Mol. Biol. 3, 18–30. 26. Reinert, K. E. (1973) DNA stiffening and elongation caused by binding of ethidium bromide, Biochimica Et Biophysica Acta 319, 135–139. 27. Murade, C. U., Subramaniam, V., Otto, C., and Bennink, M. L. (2009) Interaction of Oxazole Yellow Dyes with DNA Studied with Hybrid Optical Tweezers and Fluorescence Microscopy, Biophysical Journal 97, 835–843.

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28. Thamdrup, L. H., Persson, F., Bruus, H., Kristensen, A., and Flyvbjerg, H. (2007) Experimental investigation of bubble formation during capillary filling of SiO2 nanoslits, Applied Physics Letters 91, 163505. 29. Thompson, R. E., Larson, D. R., and Webb, W. W. (2002) Precise nanometer localization analysis for individual fluorescent probes, Biophysical Journal 82, 2775–2783. 30. Huang, B., Bates, M., and Zhuang, X. (2009) Super-Resolution Fluorescence Microscopy, Annual Review of Biochemistry 78, 993–1016. 31. Perkins, T. T., Smith, D. E., and Chu, S. (1997) Single polymer dynamics in an elongational flow, Science 276, 2016–2021. 32. Morton, K. J., Loutherback, K., Inglis, D. W., Tsui, O. K., Sturm, J. C., Chou, S. Y., and Austin, R. H. (2008) Crossing microfluidic streamlines to lyse, label and wash cells, Lab on a Chip 8, 1448–1453. 33. Persson, F., Thamdrup, L. H., Mikkelsen, M. B. L., Jaarlgard, S. E., Skafte-Pedersen, P., Bruus, H., and Kristensen, A. (2007) Double thermal oxidation scheme for the fabrication of SiO2 nanochannels, Nanotechnology 18, 245301. 34. Riehn, R., and Austin, R. H. (2006) Wetting micro- and nanofluidic devices using supercritical water, Analytical Chemistry 78, 5933–5934. 35. Elf, J., Li, G. W., and Xie, X. S. (2007) Probing transcription factor dynamics at the singlemolecule level in a living cell, Science 316, 1191–1194. 36. Persson, F. and Tegenfeldt, J. O. (2010) DNA in nanochannels - directly visualizing genomic information, Chem Soc Reviews, 39, 985–999.

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Chapter 10 Fluorescence Correlation Spectroscopy Patrick Ferrand, Je´roˆme Wenger, and Herve´ Rigneault Abstract Fluorescence correlation spectroscopy (FCS), implemented in microscopy, relies on performing an autocorrelation of the time fluctuating intensity arising from individual molecules diffusing through a confocal volume. It allows us to investigate a large variety of dynamic processes and to quantify photophysical, photochemical, interaction, diffusion, and transport properties of molecules. This tutorial chapter is intended to give an “hands on” view of FCS. After a brief introduction on the principle of FCS, the major theoretical assumptions are emphasized, and the main analytical expression are given. Then the key parameters that have to be considered when building a FCS system are discussed. The complete method of operation is described, including calibration, measurement, and data treatment. The major difficulties that are encountered when performing for the first time FCS are illustrated by examples of measurements, and possible solutions are proposed. Key words: Fluorescence correlation spectroscopy, Autocorrelation, Fluctuations, Single molecule spectroscopy, Confocal microscopy, Diffusion

1. Introduction “Intensity is not enough,” that could be the motto for fluorescence correlation spectroscopy (FCS), a quite mature technique nowadays that was born in the 1970s (1) from the work done at that time on dynamic light scattering (DLS) (2). FCS (as DLS) relies on performing a time correlation on a fluctuating light signal with the assumption that this fluctuating signal is coming from a limited and fluctuating number of particles, the size of the particles being small compared to the characteristic length of the observation volume. In principle, time correlation can be performed on any kind of signal, we shall further be interested in fluorescence as the contrast mechanism used in FCS, whereas DLS relies on light scattering. To make things clear, let us consider a volume of observation that defines a restricted area in a much larger open volume, where Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_10, # Springer Science+Business Media, LLC 2011

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1.014 1.012 1.010 1.008 1.006 1.004 1.002 1.000 10–6 10–5 10–4 10–3 10–2 10–1 100 tau (s)

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Fig. 1. Schematic view of a typical FCS measurement. (a) Diffusion of fluorescent molecules through the observation volume of a confocal microscope (represented by the dotted circle). (b) The resulting fluctuating fluorescence intensity. (c) The autocorrelation function calculated from the intensity, according to Eq. 1.

particles are freely moving, as illustrated in Fig. 1a. For simplicity, we consider here a 2D diffusion process, this can be, for instance, what happens when a fluorescent molecule is freely moving in a biomembrane. Now looking at the fluorescence intensity recorded as a function of time in the observation volume, it is clear that molecule entering and living the volume will make this intensity fluctuate, as depicted in Fig. 1b. Now in FCS, we are not only interested in the amplitude of these fluctuations, but also in their average time duration. In principle, one could imagine retrieving this information by measuring how much time was elapsed between an increase and a decrease of fluorescence intensity. However, this view is very simplistic and in practice, such information is very difficult to extract, because there is no way to ensure that the obtained increase and decrease are due to the same molecule. On the other hand, although the signal looks chaotic, it is obvious that any molecule entering the volume will leave after a certain time, on average. Indeed, the key of the mathematical treatment of FCS relies on this on average notion, more generally on the concept of correlation. Starting from intensity I(t), the so-called autocorrelation function (ACF) G(t) is defined as GðtÞ ¼

hI ðtÞ I ðt þ tÞi hI ðtÞi2

;

(1)

where the brackets hi indicate a time average. The ACF has to be understood as a way to quantify how much a signal is still similar to itself after a given delay t. In our example of 2D diffusion, it is clear that the signal does not have the time to change too much within a delay t if t is much smaller than the typical residence time of the molecules in the observation volume. Mathematically, this would give hI(t) I(t + t)i ’ hI2(t)i > hI(t)ihI(t)i and therefore

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G(t) > 1. On the contrary, if t is much larger than the typical residence time, then signals I(t) and I(t + t) have no similarity and hI(t) I(t + t)i can be written as hI(t)ihI(t + t)i, thus G(t) ¼ 1. It is intuitive at this stage that the intermediate values of the ACF will carry the information on the duration of the fluctuation, here the residence time of the molecule in the observation volume. A typical ACF is plotted in Fig. 1c. Although sensitive to single molecule fluctuation, FCS is intrinsically a statistic method, thanks to the huge number of individual events that are analyzed. Although the above explanation is hand waving and limited to the simple case of 2D diffusion, for tutorial purposes, FCS is supported by a rigorous theory as described below. It permits to quantify a wide range of phenomena such as photophysical, photochemical, interaction, diffusion, and transport properties of molecules (3). The scope of this chapter is very practical, “what shall I do to build and run my own FCS setup” has been our guideline when writing this chapter. 1.1. Theoretical Assumptions

The most important assumption behind FCS measurements deals with the concept of stationarity. The system under study is assumed to be stationary, i.e., from a mathematical point of view, both quantities hI(t)i and hI(t) I(t + t)i of Eq. 1 need to be independent of time t. In other words, the total measurement duration Ttot has to be much larger than the fluctuation duration (4). A practical figure of merit of the stationarity is the value of G(t), which should be unity for the largest values of t. As we will see later, a signal that is not stationary is not be suitable for a FCS analysis. The second assumption deals with the shape of the observation volume, which is described by the point spread function (PSF) of the confocal microscope. In the case of a high numerical aperture microscope objective, the PSF is in principle a complicated distribution that depends both on the excitation and collection optics. However, for FCS studies, it is generally assumed that it can be reasonably described by a 3D gaussian distribution (5) " !# x 2 þ y 2 z2 (2) PSFðx; y; zÞ ¼ I 0 exp 2 þ 2 ; o2xy oz where wxy and wz denote the transverse and axial waist, respectively. With this assumption, an effective observation volume is usually defined as V eff ¼ p3=2 w 2xy w z : Although this Gaussian assumption does not constitute a sine qua non condition for performing FCS, it allows us to derive relatively simple analytical expressions for the ACF G(t), as described in Subheading 1.5.

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1.2. Amplitude of the ACF

By writing the fluctuating intensity as I ðtÞ ¼ hI i þ dI ðtÞ, Eq. 1 becomes GðtÞ ¼ 1 þ

hdI ðtÞdI ðt þ tÞi hI i2

:

In case of diffusing molecules, the fluctuations of intensity recorded by an ideal setup are only due to the fluctuation number of molecule in the observation volume. We shall name dN as fluctuation number. For a given count rate per molecule (CRM), hI i ¼ hN i CRM and dI(t) can be simply written as dI(t) ¼ dN(t) CRM, and then, for short delays, the amplitude of the ACF is Gðt ! 0Þ ¼ 1 þ

hdN 2 i 2

hN i

¼1þ

1 ; hN i

(3)

where we have used the property that the quantity N is governed by a Poisson statistics, and as such, hdN2i ¼ hN i. The important result of Eq. 3 emphasizes that FCS is intrinsically designed to analyze small number of molecules. 1.3. Relevant Time Scales

Although FCS can address a large range of time scales, a priori knowledge of the fluctuation time, that we denote tf, is necessary to set the optimum conditions for measurement, that we summarize here as Dt  tf  T tot ;

(4)

where Dt is the correlator sampling time with which the intensity I(t) is recorded. Indeed, in order to be sensitive to the fluctuations, Dt needs to be much smaller than tf. Note that Dt will be the first channel of the computed ACF, usually named the correlogram. In addition, as discussed in Subheading 1.1, the condition of stationarity requires that the total measurement duration Ttot is much larger than correlogram. 1.4. Signal-to-Noise Ratio in FCS

Noise and statistical accuracy in FCS deserve specific consideration. First, understanding the origin of the signal-to-noise ratio (SNR) enables optimization of the experimental apparatus. Second, proper weighting procedures based on statistical estimates for the noise enable more accurate analysis. Beyond technical noise, two physical phenomena bring fundamental contributions to the noise in FCS: the quantum nature of light that induces shot noise and the stochastic nature of the fluorescence fluctuation process itself. In the most common experimental conditions for FCS: Gaussian molecular detection efficiency, 3D Brownian diffusion, negligible background, and small sample time (Dt ! 0), but without any assumption on the average number of molecules hN i,

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it can be demonstrated that the SNR of the ACF is simply given by (6) pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi CRM T tot Dt SNR t!0 ’ ; (5) ð1 þ 1=hN iÞ1=2 where CRM denotes as previously the CRM. This shows that the SNR in FCS does not depend on the total detected fluorescence, but on the fluorescence CRM, on the square root of the experiment duration Ttot, and on the correlator channel minimum width Dt. This further emphasizes the single molecule nature of FCS and provides guidelines to improve the statistical accuracy in FCS. For a fixed experimental apparatus, one can either increase the excitation power to raise the CRM or wait for longer integration times Ttot. However, both of these strategies have significant practical limitations. First, saturation and photobleaching limit the CRM increase to a certain extent. Second, due to the square root dependence of the SNR on the acquisition time, increasing Ttot to a few hundred seconds has only a minor influence on the SNR. 1.5. Analytical Expression of the ACF

With the assumptions described in Subheading 1.1, analytical expressions of the ACF can be derived for a large variety of physical processes. For the sake of generality, we shall write the ACF as GðtÞ ¼ 1 þ

1 X ðtÞ G D ðtÞ BðtÞ; hN i

(6)

where X(t), GD(t), and B(t) denote the intra- or intermolecular reactions, diffusion, and background contributions, respectively, to the ACF. Note that this separation of different dynamical contribution is only possible when molecular reactions takes place at much shorter time scale than diffusion, which is usually a reasonable assumption. 1.5.1. Inter- and Intramolecular Dynamics

The first factor in Eq. 6 accounts for changes in fluorescence yield as molecules undergo inter- or intramolecular dynamics, such as triplet blinking. The general expression for X(t) is   T t ; (7) exp  X ðtÞ ¼ 1 þ 1T tT where T is the fraction of molecule in a dark state and tT is the corresponding duration of the triplet fluorescence fluctuation (7).

1.5.2. Translational Diffusion

The factor GD(t) is derived from the diffusion equation that governs the evolution of the concentration C (r, t) of the fluorescent molecule, given by @Cðr; tÞ ¼ DDCðr; tÞ; @t

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where D is the diffusion coefficient of the molecule. For a 3D translational diffusion, G 3D D ðtÞ ¼

1 1 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 þ ðt=tD Þ 1 þ s 2 ðt=tD Þ

(8)

with tD ¼ w 2xy =4D is the average residence time in the observation volume and s ¼ wxy =w z is a purely geometrical factor. In case of 2D diffusion, the limit s ! 0 gives G 2D D ðtÞ ¼

1.5.3. Background Signal

1 1 þ ðt=tD Þ

(9)

Last but not least, the factor B(t) accounts for the contribution of background signal in the ACF. It has been demonstrated that (6)   hBi 2 ; (10) BðtÞ ¼ 1  hI i where hB i is practically the intensity measured by replacing the fluorescent sample by a nonfluorescent one.

2. Materials 2.1. FCS System

Several companies offer turn-key FCS systems. Most of them are based on confocal laser scanning microscope (CLSM) systems (see Note 1), while some others rely on a more simple optical systems, require no optical alignment but suit therefore to more diluted systems. These systems include excitation laser, appropriate filter sets, photon counting systems, and a dedicated data analysis software. Alternatively, most commercial CLSMs can be customized in order to perform FCS measurements, according to the optical scheme presented in Fig. 2. It requires, however, a solid background in photonics instrumentation, electronics, data acquisition, and programming. The following points need to be considered 1. It is important to ensure that the scanning system can be turned off in one way or an other, in order to perform static measurements. Sometimes, this can be done by setting the scanning range to 0. 2. A system with various available pinhole sizes will be useful in the case of signal concerns (the larger the pinhole, the stronger the signal). 3. A high numerical aperture objective (typically NA ¼ 1.2) is preferable, because it ensures the largest collection efficiency

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Fig. 2. A basic FCS setup as well as a typical correlogram as computed by the correlator. The inset shows a schematic view of the 3D PSF of the system. APD stands for avalanche photodiode.

and therefore the largest CRM, in addition to the highest spatial resolution. 4. Laser excitation power will need to be measured in order to provide controlled and producible operating conditions. Photodiode power meters are usually the best choice for low power measurement, i.e., below a few milliwatts. 5. Because CLSM detection usually relies on photomultiplier tubes in analog mode, the detector must be replaced by one (or two, see Note 2) photon counting module(s) such as avalanche photodiodes (APDs) (e.g., SPCM-AQR series by PerkinElmer Optoelectronics, PDM series by Micro-PhotonDevices, or id100 series by id Quantique). The key parameter to be considered here is quantum efficiency, because this directly affects the CRM. 6. The correlation function can be built up either by using a digital hardware correlator (by correlator.com or ALVGmbH) or by software correlation. Although it means an additional cost, the first approach is the most easy way to implement and also the most secure concerning numerical error and/or artifacts. In this case, the signal form the detectors is correlated on-line, and the ACF can be monitored in real time. Such correlator can work either in linear mode

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or in multitau mode, the later offering a wider range of accessible fluctuation times, thanks to channels of increasing width in a quasi-logarithmic progression. Alternatively, correlation can be performed afterwards on the intensity series, usually in multitau or equivalent computation scheme. The major drawback of this approach is the huge volume of data that need to be stored and the often prohibitive calculation time. For this reason, it is only relevant for slow processes (fluctuation time larger than 1 ms). Even if the correlation is built up on-line, we recommend to always record (with a very low time sampling, typically 100 ms), the time series, for further analysis of stationarity. 7. Last but no least, FCS data analysis strongly relies on advanced fitting procedures. The work flow will be much more effective by using data analysis software offering powerful fitting algorithms, such as Levenberg-Marquardt, as well as a complete macroprogramming language, such as Origin, Igor Pro, Matlab, etc. 2.2. Labeling

When choosing the fluorescent label to be used on the biological system you want to investigate, remember that the golden rule is “to maximize the CRM.” Therefore, 1. Select robust dyes, labels, fluorescent proteins with the highest quantum efficiency. 2. Check carefully the filter set in order to match the spectral features of the label. 3. Always prefer labels that have been extensively documented in the literature. Even if they are not the subject of your investigations, photophysical properties, such as conformal changes, triplet blinking, may be visible on the ACF, and an a priori knowledge will by a real plus when fitting the data. Diffusion coefficient of the molecule in solution is required if the label is used to calibrate the measurement volume of your FCS system.

2.3. Calibration Solution

The calibration solution will be used in order to determine the measurement volume of the system. 1. Choose a solution of a robust dye those fluorescence can be measured with the same laser/filter configuration as the one that labels your biological system. 2. Choose a dye those diffusion coefficient Dcal is documented (8). 3. Feel free to use the same label as for your biological system, if you think it is stable and bright enough.

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4. First prepare a 1-mL aliquot of high concentration in ultrapure water, typically 1 mM. This will constitute the stock solution for future dilutions. Keep it stored at  18 ∘ C. 5. Prepare from the stock solution four successive dilutions in 1-mL aliquots with typical concentrations 10 mM, 1 mM, 100 nM, 10 nM. Store at + 4 ∘ C in the dark.

3. Methods 3.1. Coarse Optical Alignment

Note that although CLSM can produce relative clear images even in case of a moderate misalignment, FCS is optically much more demanding and requires l

A perfect centering of the excitation laser on the back aperture of the microscope objective.

l

A perfect conjugation of the pinhole with the excitation spot.

In case of a commercial FCS system or of a FCS-upgraded CLSM, some of the alignment settings may not be accessible to the user, and therefore require maintenance by the company. Note that this procedure needs to be followed only if the system has not been used for several weeks or if an important modification has been made on the optical system (laser replacement, filter change, etc.). 1. Switch the system on, with the correct excitation sources, microscope objective and filter set. 2. Select the largest pinhole diameter. 3. Stop the beam with an appropriate beam stopper. Set laser power to a moderate level. This should be a few hundreds mW for a one-photon fluorescence process and a few tens of milliwatts for a two-photon fluorescence process. 4. Put a droplet of the appropriate immersion liquid on the objective. 5. Place a standard coverslip on the sample stage. 6. Put about 50 mL of the most concentrated calibration solution (10 mM). 7. Release the laser beam stopper. 8. Move the focus until the laser spot is located inside the solution. You should see the fluorescence spot when looking at the sample, your eyes been protected from laser radiation by goggles. Alternatively, remove the sample holder, and place the coverslip directly on the objective, the capillary effect of the immersion should maintain it horizontally. This ensures that the observation volume is into the solution.

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9. Switch on the detector. Run a static intensity measurement. Reduce laser excitation power if the detector is saturating. 10. Optimize the signal by adjusting the pinhole alignment. Reduce laser excitation power if the detector is saturating. 11. Repeat optimization with the next dilution (1 mM). 12. Repeat optimization with a smaller pinhole diameter. 3.2. Calibration of the Measurement Volume

This procedure has to be followed before any series of measurements, in order to prevent any slight misalignment. In addition, it allows to determine the values of wxy and wz for the system. steps 12–13 allow us to set the best measurement conditions for a given solution on the system. It does not need to be repeated daily. 1. Switch the system on, with the appropriate excitation sources, microscope objective and filter set. 2. Select the largest pinhole diameter. 3. Set laser power to a moderate level. Stop the beam with an appropriate beam stopper. 4. Put a droplet of the appropriate immersion liquid on the objective. 5. Place a standard coverslip on the sample stage. 6. Put about 50 mL of the 100-nM calibration solution. 7. Release the laser beam stopper. 8. Move the focus until the laser spot is located inside the solution. 9. Record a ACF for Ttot ¼ 30 s, and measure simultaneously the average value of the fluorescence intensity hI i. If ACF is too noisy, use a larger measurement duration. 10. Fit the obtained ACF with analytical expression of Eq. 6, in order to obtain values hN i, tD, as well as T and tT, if necessary. Usually, s can be fixed to s ¼ 0. 2 for the first fitting iterations. 11. From hI i and hN i, calculate the count rate per molecule CRM ¼ hIi=hNi. 12. Repeat steps 9–11 for various sizes of pinhole (see Notes 3 and 4) and various excitation powers Pexc. 13. Plot variations of CRM and tD versus Pexc. The range of excitation power for which CRM has a linear dependence upon Pexc and tD does not depends on Pexc is the one which suits to this calibration solution on your system. In practice, use a power 20% below the maximum suitable excitation power.

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Fig. 3. Example of ACF recorded in a calibration solution of Rhodamine 6G. Measurement duration was 10 s. Circle are experimental points, while solid line is the fit according to Eqs. 6–8. Inset is the intensity series, top graph is the residuals. Fitting values: hN i ¼ 1.93, T ¼ 0. 133, tT ¼ 4.1 ms, tD ¼ 29 ms, and s ¼ 0.2.

14. The lateral width of the measurement volume is given by pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi wxy ¼ 4D ref tD , where tD is measured in the correct range of excitation power. An example of FCS performed in a 30 nM solution of Rhodamine 6G in water (9) under a typical excitation power of 200 mW is plotted in Fig. 3, as well as the corresponding fit, according to Eqs. 6–8. Note that the background signal was negligible and therefore B(t) was assumed to be unity. Given a value Dref ¼ 280 mm2/s, measurement volume here is characterized by wxy ¼ 179 nm and wxy ¼ 895 nm. 3.3. FCS Measurements

1. Place your sample on the microscope. 2. Set the excitation power to a moderate level. 3. In the case of a cell or other specific sample, use the LSCM capabilities of the system in order to set the correct focus and set the FCS measurement area (by moving the sample or by moving the measurement spot, depending on the system in use). 4. Set the excitation power to a low level, compatible with static recording of intensity (see Note 5).

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5. Record a set of short correlogram as well as the corresponding intensity series. 6. Repeat the measurement on equivalent locations, on another part of the sample. 3.4. FCS Data Analysis

1. Browse all correlograms together with the corresponding intensity series that have been recorded at one location. 2. Discard all correlograms whose intensity series are not stationary (see Note 6). This often happens in complex samples such as cells because of membrane fluctuations, dye aggregation, etc. 3. Average the remaining correlograms. 4. Fit the obtained correlogram with the most appropriate model. If the obtained physical parameters do not make physical sense, reject the fit. 5. Repeat this procedure for all sets of correlograms.

4. Notes 1. FCS is not limited to one-photon absorption fluorescence, but has been successfully extended to nonlinear optical contrasts, such as two-photon absorption fluorescence, etc. From an instrumental point of view, because nonlinear microscopy systems are free of pinhole, detection relies usually on large area photomultiplier tubes. It is therefore subject to parasitic light, in addition to a lower quantum efficiency. In practice, two-photon FCS is subject to strong photobleaching and requires significantly higher incident power (tens of milliwatts) than one-photon FCS (hundreds of microwatts). Nevertheless it has several advantages like being able to excite several fluorophores with the same wavelength; it does not require pinhole, it has a potential deeper penetration depth in scattering samples. 2. Detectors can be subject to measurement artifacts (dead time, after pulse, etc.) that compromise the ACF for short delays (typically for t < 1 ms). In case values at short delays are necessary for the process under study (photophysics, for instance), this random noise can be efficiently rejecting by splitting the signal on two detectors and by cross-correlating the signals obtained by the two detectors. The system illustrated in Fig. 2 is set up in this configuration. 3. Pinhole diameter is directly related to the axial extent of the PSF. Although this feature is crucial for CLSM imaging, because it determines the axial sectioning capability of the

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system, it can often be reasonably sacrificed while doing FCS measurement, a larger pinhole diameter providing a significantly larger CRM, and therefore a larger SNR. Indeed, enlarging the pinhole diameter produces only limited modifications of the diffusion time tD. This is because wxy (transverse width of observation volume) is defined by the excitation beam rather than the collection optics (that defined wz). 4. When repeating measurements with new samples, you may experience a sudden degradation of CRM and/or diffusion time, these two figures being of course much more clearly visible when measuring solutions. This is often due to a defect of the coverslip that is sometimes outside the nominal range indicated by the manufacturer. In this case, it is usually more effective to discard the coverslip and to start a new measurement than to try to adjust the correction collar of the microscope objective. Another common problem is the drying of water between the coverslip and a water-objective lens. 5. Although FCS can address fluctuation processes at all timescales (within the limitations mentioned in Subheading 1.3, of course), slow diffusion cannot be measured in practice, because slow species are usually bleached before leaving the measurement volume. This produces a typical drop of the recorded intensity, as illustrated in Fig. 4d. In this case, scanning FCS approaches such as image correlation spectroscopy and its variants may be more relevant (see Note 7). 6. Figure 4 illustrates some examples of odd-looking correlograms that constitute the usual first taste of FCS for new users and that may be quite discouraging. Possible explanations and suggestions are given for each case. Measurements like cases C and D must be definitely discarded, because they do not satisfy to the condition of stationarity required by the FCS analysis. Although these correlograms may in some cases be successfully fitted, they would produce erroneous values. More generally, these examples emphasize that FCS analysis must be operated by experienced users only, especially for measurements carried out in complex systems such as cells, where the diffusion is mostly non-Brownian and the signal subjected to other spurious fluctuations. 7. Latest development of FCS focus both on hardware and software. From the hardware side the current trends are (a) dual-spot measurement to measure FCS simultaneously at various locations (9) and/or to access to absolute diffusion coefficient (8) and (b) multispot FCS using EMCCD cameras as detector (). From the data analysis side, recent development focus on the improvement of spatio-temporal information by means of scanning FCS (11) and image correlation

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a Problem - No visible correlation

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To do - Use a lower excitation power - If you are only interested in the fast moving fraction, also consider the possibility to i) bleach out all the slow fraction, ii) run your FCS measurement on the remaining fast fraction. 101

Fig. 4. A nonexhaustive panel of unsuitable correlograms, with the corresponding intensity series plotted in the inset. For each case, the problem is detailed, diagnosis and possible solutions are given.

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spectroscopy techniques (12) that give access to both temporal and spatial correlations. Another powerful variant of FCS is fluorescence cross- correlation spectroscopy (FCCS), which extends the capabilities of standard FCS by introducing two different fluorescent probes with distinct excitation and/or emission properties, which can be detected in the same confocal volume. It allows to probe interactions between different molecular species (13).

References 1. Magde, D., Elson, E. L., and Webb, W. W. (1972) Thermodynamic fluctuations in a reacting system – measurement by fluorescence correlation spectroscopy. Phys. Rev. Lett.29, 705 2. Berne, B. J., and Pecora, R. Dynamic light scattering: with applications to chemistry, biology, and physics; Dover, 2000 3. Webb, W. W. (2001) Fluorescence correlation spectroscopy: inception, biophysical experimentations, and prospectus. Appl. Opt.40, 3969 4. Tcherniak, A., Reznik, C., Link, S., and Landes, C. F. (2008) Fluorescence correlation spectroscopy: criteria for analysis in complex systems. Anal. Chem.81, 746 5. Rigler, R., Mets, U., Widengren, J., and Kask, P. (1993) Fluorescence correlation spectroscopy with high count rate and low-background – analysis of translational diffusion. Eur. Biophys. J.22, 169 6. Wenger, J., Ge´rard, D., Aouani, H., Rigneault, H., Lowder, B., Blair, S., Devaux, E., and Ebbessen, T. W. (2009) Nanoaperture-enhanced signal-to-noise ratio in fluorescence correlation spectroscopy. Anal. Chem.81, 834–9 7. Widengren, J., Mets, U., and Rigler, R. (1995) Fluorescence correlation spectroscopy of triplet-states in solution – a Theoretical and experimental-study. J. Phys. Chem.99, 13368

8. M€ uller, C. B., Loman, A., Pacheco, V., Koberling, F., Willbold, D., Richtering, W., and Enderlein, J. (2008) Precise measurement of diffusion by multi-color dual-focus fluorescence correlation spectroscopy. Europhys. Lett.83, 46001 9. Ferrand, P., Pianta, M., Kress, A., Aillaud, A., Rigneault, H., and Marguet, D. (2009) A versatile dual spot laser scanning confocal microscopy system for advanced fluorescence correlation spectroscopy analysis in living cell. Rev. Sci. Instrum.80, 083702 10. Burkhardt, M., and Schwille, P. (2006) Electron multiplying CCD based detection for spatially resolved fluorescence correlation spectroscopy. Opt. Express14, 5013 11. Petra´sˇek, Z., Hoege, C., Mashaghi, A., Ohrt, T., Hyman, A., and Schwille, P. (2008) Characterization of protein dynamics in asymmetric cell division by scanning fluorescence correlation spectroscopy. Biophys. J.95, 5476 12. Kolin, D. L., and Wiseman, P. W. (2007) Advances in image correlation spectroscopy: Measuring number densities, aggregation states, and dynamics of fluorescently labeled macromolecules in cells. Cell Biochem. Biophys.49, 141 13. Bacia, K., Kim, S. A., and Schwille, P. (2006) Fluorescence cross-correlation spectroscopy in living cells. Nature Meth.3, 83

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Chapter 11 Introduction to Atomic Force Microscopy Pedro J. de Pablo Abstract Atomic force microscopy (AFM) is an invaluable tool not only to obtain high-resolution topographical images, but also to determine certain physical properties of specimens, such as their mechanical properties and composition. In addition to the wide range of applications, from materials science to biology, this technique can be operated in a number of environments as long as the specimen is attached to a surface, including ambient air, ultra high vacuum (UHV), and most importantly for biology, in liquids. The versatility of this technique is also reflected by the wide range of sizes of the sample that can dealt with, such as atoms, molecules, molecular aggregates, and cells. Indeed, this technique enables biological problems to be tackled from the single-molecule point of view and it allows not only to see but also to touch the material under study (i.e., mechanical manipulation at the nanoscale), a fundamental source of information for its characterization. In particular, the study of the mechanical properties at the nanoscale of biomolecular aggregates constitute an important source of data to elaborate mechano-chemical structure/function models of single-particle biomachines, expanding and complementing the information obtained from bulk experiments. Key words: Scanning, Surface, Cantilever, Liquids, Force curve

1. Introduction The first thing that comes to mind on hearing the word “microscopy” is an optical device that manipulates light to obtain a magnified image of a sample. As a consequence, the first question that is usually posed when seeing an atomic force microscopy (AFM) for the first time is: where do I have to look to see the specimen? A microscope is generally considered a machine in which a source emits particles such as photons or electrons that are used as probes thrown onto the specimen to provoke an interaction. This probe–specimen interaction can be registered by a detector and this result is communicated of to an analyzer, which processes the information received to make it comprehensible. There are two kinds of microscopes that fit readily into this Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_11, # Springer Science+Business Media, LLC 2011

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source–specimen–detector–analyzer scheme. The first is the optical microscope, where the photons coming from the incandescent lamp are conveniently manipulated by a system of lenses and mirrors both before and after the interaction with the specimen arriving to the eyepiece where the detector (i.e., the eyes) collects the information. A typical optical microscope can reach a resolution of l/2 ~200 nm (l being the wavelength of the light). Anton van Leeuwenhoek (1632–1723) is credited with bringing the optical microscope to the attention of biologists, even though simple magnifying lenses were already being produced in the 1500s. The electron microscope (EM) is a little more complicated. In this case, the particles that act as probes are not photons but electrons produced by an incandescent wire. Here, electromagnetic lenses are used to manipulate and focus the electron beam in order to provoke the right interaction with the specimen. The electrons are then collected by a screen, which is conveniently monitored. The first prototype electron microscope was built in 1931 by the German engineers Ernst Ruska and Max Knoll and 2 years later, Ruska constructed an electron microscope that exceeded the resolution possible with an optical microscope, reaching about 1 nm. In scanning probe microscopy, a sharp tip of a few nanometers in diameter, which can be considered as a probe, approaches the surface of the sample. The first member of this family of microscopes was the scanning tunneling microscope (STM) invented by Binning and Rhorer (1), who received the Nobel Prize for Physics along with Ruska in 1986. This system is based upon a quantum effect (tunneling) that occurs when a sharp metallic tip is brought to a distance (z) of less than 1 nm from a conductive surface. This effect involves the flow of an electronic current (I) between pffiffiffiffi the surface and the tip according to the formula I / expð ’zÞ, where f is the work-function of the metallic surface (2). The strong dependence on the tip–surface distance can be used to obtain topographic and electronic maps of the sample by moving (i.e., scanning the tip on the surface) while keeping the tip–sample distance constant through a feedback algorithm. Although this tool provides true atomic resolution in UHV conditions, a prerequisite is that both the tip and sample should be conductive. Therefore, it follows that STM is not suitable for biological samples since these are mainly insulators, which need to be covered with a metallic layer (3). In 1986, Binnig et al. (4) invented the AFM combining the principles of both the STM and the so-called stylus profilometer (5). In an AFM, a sharp stylus (approximately tenths of a nanometer) attached to the end of a cantilever is approached to the surface. As a consequence, a force appears between the tip and surface that can be attractive or repulsive (see below) causing

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the cantilever to bend. When this bending is controlled with a feedback algorithm, it is possible to obtain a topographic map by scanning the surface in a plane perpendicular to the tip. In the original paper (4), the topographic profiles of a ceramic sample, an insulator, were shown. This is one of the main advantages of AFM: the fact that both tip and sample may be insulators, opening the door to a whole range of possibilities such as the study of biological samples (biomolecules like proteins, membranes, whole cells, etc.).

2. AFM Implementation: Technical Issues

Although there are a variety of ways to control the deflection of the cantilever in AFM we will focus on the beam deflection method (6) since it is commonly employed when working with biological samples. The beam deflection system involves focusing a laser beam on the end of the cantilever and collecting the reflected light with a photodiode. As a consequence, any bending of the cantilever will affect the position of the reflected laser spot on the photodiode. A normal bending will originate a so-called normal force signal Fn on the photodiode sectors, whereas a lateral torsion will result in the so-called lateral force F l. The core of an AFM is the head (Fig. 1a), where the beam

Fig. 1. Principle of an AFM. The software running on the computer (a) controls the electronics, which give and receive information to and from the AFM head (inside the oval ). Panels (b) and (c) show the AFM sensor: the cantilever. Panel (b) shows a rectangular cantilever attached to a chip and panel (c) presents a typical tip at the end of the evident pyramid.

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deflection system is integrated along with the piezoelectric-tube that moves the sample in all three directions (x, y, and z). In Fig. 1a, an AFM head configuration is shown where the tip is fixed and the sample is moved by the piezotube. Another configuration known as “stand alone” fixes the sample and makes the scanning movement with the tip. The electronic components receive the signals coming from the photodiode, mainly Fn and Fl, and provide high voltages (~240 V) to move the piezotube to which the sample is attached. The computer is in charge for managing the data and calculating all the parameters required to move the piezotube in a convenient way. Integrated tip and cantilever assemblies can be fabricated from silicon or silicon nitride using photolithographic techniques. More than 1,000 tip and cantilever assemblies can be produced on a single silicon wafer. The cantilevers can be rectangular (see Fig. 1b) or V-shaped and they typically range from 60 to 200 mm in length, 10 to 40 mm in width, and 0.3 to 2 mm in thickness. The typical tip radius is about 30 nm, although sometimes lower diameters can be obtained (Fig. 1c). The cantilever spring constant k ranges between 0.03 and 40 N/m, and it strongly depends on the cantilever’s dimensions. For example, for a rectangular cantilever k ¼ ðEW =4ÞðT =LÞ3, where E is the Young Modulus of the cantilever, and W, T, and L are the cantilever width, thickness, and length, respectively (Fig. 1b). While W and L can be fairly precisely known, T is always difficult to measure. As a consequence, the manufacturers normally provide the cantilever spring constant with an error of 10–30% and therefore the user should calibrate each cantilever (7). The spring constant k is used to calculate the Hookean force applied on the cantilever as a function of bending Dz, i.e. F ¼ k  Dz. The vertical resolution of the cantilever (Dz) strongly depends on the noise of the photodiode, since it defines the minimum significant displacement of the laser beam on the detector (see Fig. 1a). A typical cantilever of 100 mm length has about 0.1 A˚ resolution assuming a signal-to-noise ratio of around 1 (6). Another important parameter that can have influence on the vertical resolution is the thermal noise (8): the cantileverp oscillates ffiffiffiffiffiffiffiffiffiffiffiffiffiffi at the resonance frequency with an amplitude Dz ¼ kB T =k, where kB is the Boltzmann constant, T is the absolute temperature, and k the cantilever spring constant. For example, at room ˚ for a cantilever of spring temperature, there is a noise of about 5 A constant 0.02 N/m. 2.1. Interaction Between the AFM-Tip and the Surface

In order to understand the interaction between the tip and sample, we shall refer to potentials rather than forces. Physicists prefer this as potentials are scalar and therefore easier to deal with

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Fig. 2. Force curves, feedback, and lateral resolution. Panel (a) shows the force of the tip–sample interaction (represented in the inset ). The numbers inside the circles indicate the cantilever instabilities (see text). Panel (b) shows force versus z-piezo displacement curve in air and (c) in liquid. Panel (d) presents the contact mode showing the variation of Fn (gray ), as a function of a step (dark ). In panel (e), the geometric features of the tip–surface contact are depicted (see text).

than vectors such as forces. For this purpose, let us consider a Lennard-Jones potential. U ðrÞ ¼ 

A B þ 12 ; 6 r r

where r is the tip–sample distance, A ¼ 1077 Jm6 and B ¼ 10134 Jm12. This describes the interaction of all the atoms in a particular solid (9). A rough approximation to the AFM tip–sample interaction is to consider the approach of two such atoms where, as depicted in the inset of Fig. 2a, the lower part is a solid surface and the above it is the apex of a sharp tip that moves down. We can find an interaction force such that F ðrÞ ¼ ðdU =drÞ and this force is attractive (F < 0) when r > r0 or repulsive (F > 0)

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when r < r0, (Fig. 2a). These regions define the attractive and the repulsive regimes of operation, respectively. Now let us consider the role of these regimes in a force versus distance (F–z) AFM experiment that involves the tip approaching to the surface (Fig. 2b). The experiment starts with the tip situated far from the surface in the attractive regime. As the tip is approaching and as soon as the gradient (i.e., the slope) of the force equals the cantilever spring constant, the tip jumps to the surface from dark point 1 to the dark point 2 (both connected by the slope). This is seen in the F–z of Fig. 2b at point A like a sudden jump of the cantilever deflection (vertical scale). Thus, the tip establishes mechanical contact with the surface and it rapidly enters the repulsive regime (FN > 0). The z-piezo (horizontal scale) is elongated until a given FN or deflection value is reached and then stops (point B of Fig. 2b). The external loading force Fext can be calculated as the difference between the zero deflection position (i.e., before the jump to contact in A) and the deflection at point B. Since the vertical scale is about 10 nm per division and the cantilever spring constant k ¼ 0.1 N/m, we have Fext ~ 0.5 div  10 nm/div  0.1 nN/nm ¼ 0.5 nN. Subsequently, the z-piezo retrace cycle starts, and the tip is released from the surface at C (i.e., once more where the derivative of the tip– surface force equals the cantilever spring constant) jumping from the gray point 1 to 2 following the gray arrow. The cantilever deflection jumps-off to zero with a dampened oscillation. This jump-off is known as the adhesion force Fadh (in this case Fadh ~ 2div  10 nm/div  0.1 nN/nm ¼ 2 nN). The total force at point B is the sum of Fext and Fadh (i.e., 2.5 nN). It is interesting to note that no matter how small Fext is the total force applied to the surface will always be at least Fadh. 2.2. Contact Mode

The contact mode is the simplest operational method used for AFM and it was the first to be developed, in the mid-1980s (4). Here, the tip is brought into contact with the surface until a given deflection in the cantilever (Fn) is reached and the tip then scans a square area of the surface to obtain a topographic map. By elongating or retracting the z-piezo, the feedback algorithm tries to maintain the cantilever deflection constant by comparing the Fn signal with a set point reference value established by the user. The topographic data are obtained by recording the z-piezo voltage that the feedback algorithm is applied to correct the cantilever deflection at each position on the surface. Since the z-piezo is calibrated, the voltages are transformed into heights and a topography map is obtained. Let us consider a simple example where the tip is scanning a step (dark line in Fig. 2d) with Fn ¼ k  Dz. When the cantilever moves to the upper part of the step, it undergoes a deflection greater than Dz. Therefore, the feedback algorithm retracts the z-piezo in order to achieve the same deflection

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Dz as when the tip was in the lower part of the step and as a consequence, a topographic profile of the step is obtained. On the other hand, Fn varies at the step and is corrected by the feedback, which can be observed as a peak in the deflection signal (gray line in Fig. 2d). The latter is known as the “constant deflection” mode, otherwise named as the constant height mode, since the z-piezo is not modified and a map of the changes in Fn is obtained. The reader is encouraged to reproduce Fig. 2d when the tip goes down the step. Let us consider now the lateral resolution that can be achieved in contact mode. We can make an estimate of this parameter by applying the Hertz theory (10), which accounts for the deformation of solids in contact. Once the tip is in contact with the sample, the radius r of the tip–surface contact area is given by (Fig. 2e):   3FR 1=3 r¼ ; 4E  where F is the applied force, i.e., Fn, E* is the effective Young modulus expressed by 1 1  vt2 1  vs2 ¼ þ ; E Et Es with Et, nt and Es, ns being the Young Modulus and Poisson ratio for the tip and sample, respectively. R is the effective radius expressed as a combination of the tip Rt and sample radius Rs. 1 1 1 ¼ þ R Rtip Rsample In the case of metals, E ¼ 100 GPa, n ~ 0.5, and the mechanical thermal noise of the cantilever is10 pN, with Rt ~ 20 nm, the radius of contact r is about 0.15 nm, which implies atomic resolution. However, the adhesion force in air (see below) is about 5 nN, increasing r to about 1 nm. Atomic resolution can be achieved by either working in liquids (11) or in UHV conditions (12), where even individual atoms can be chemically identified (13). 2.3. Geometrical Dilation

When the surface asperities are comparable to the tip radius (which is very common in AFM experiments), the size of the tip plays an important role. The tip distorts the image due to the dilation of certain features of the image by the finite tip size (14). Such dilation effects occur in all AFM operational modes. An example is shown in Fig. 3a, b, in which we image singlewalled carbon nanotubes that are essentially rolled-up graphene in the form of a cylinder of a few nanometers in diameter. In Fig. 3c, two profiles of similar carbon nanotubes are compared showing that the nanotubes of Fig. 3b (dark line of Fig. 3c)

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Fig. 3. Geometrical dilation and sample preparation. Panels (a) and (b) are AFM images of the same sample of carbon nanotubes adsorbed on silicon oxide. The topographic profiles obtained along the lines in (a) show different widths due to dilation in (c) (see text). Panel (d) shows the geometric parameters in the dilation process. The line depicts the dilated section of the carbon nanotube section (circle).

are wider than those in Fig. 3a (gray line of Fig. 3c) due to the larger tip used for imaging Fig. 3b. The geometric dilation effect is seen in Fig. 3c whereby the scanning of the carbon nanotube by the tip results in the Black profile since the tip cannot get closer to the tube than the tip radius rt. Therefore, by geometrical

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considerations of Fig. 3d, the tip radius rt can be calculated as rt ¼ b 2 =2h . The topographies of Fig. 3a, b have been obtained using tips with a radius of 15 nm and 70 nm, respectively. We can conclude that the sharper is the tip the better it is for imaging. It is quite instructive to exanimate the dilation effects in biological specimens, such as single viral particles. A very popular and impressive experiment used to teach AFM is to image graphite (in particular, highly oriented pyrolitic graphite or HOPG) in air conditions (15), where the elastic deformation of the tip–sample contact plus the dilation effects result in atomic corrugation, although atomic defects are not visualized. 2.4. Dynamic Modes

Dynamic modes (DMs) (16) are those in which thepcantilever is ffiffiffiffi oscillated near to or at its resonance frequency (o0 / E T =L 2 for a rectangular cantilever). As the tip approaches the sample, the oscillating amplitude decreases until it establishes contact with the sample, following a similar cycle to that in Fig. 2b but now with oscillation. Therefore, the feedback loop involves the amplitude rather than the Fn and by keeping the oscillation amplitude constant, a topographical map can be obtained. The amplitude is reduced because the resonance frequency (Do) changes with the tip–sample distance z and with the tip–sample interaction force Fts according to Do=o0 / ð1=2kÞðdFts =drÞ, thereby decreasing with attractive forces. The new resonance frequency o is positioned to the left of o0 and since the cantilever is still oscillating at o0, the cantilever amplitude decreases. The very high lateral forces that are applied to the surface (17), which can damage the sample, present an important problem in the contact mode. This is especially important for single biomolecules adsorbed onto a surface, these being delicate samples from which to obtain images. However, when operated in noncontact mode (18), DM does not apply huge dragging forces and as such it is commonly used to image weakly attached molecules on surfaces in air. Maps other than topographical maps can also be obtained in DM, such as the phase (the time difference between the excitation and the response of the cantilever) map, which in air carries information on the composition of the sample (see specific details in ref. 18). When DM is used in liquid, the landscape completely changes as the viscosity of water reduces the resonance frequency about fourfold and the quality factor (a measure of the cantilever damping) of the oscillation is reduced from ~100 to 10. When oscillating the cantilever in liquid, mechanical contact between tip and sample is established, thereby applying lateral and normal forces that may damage the specimen (19).

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2.5. Jumping or Pulse Force Mode

3. Biological Applications of Imaging AFM

Jumping or pulse force mode (JM) (20, 21) is a contact mode where lateral tip displacement occurs when the tip and sample are not in mechanical contact, thereby avoiding shear forces and the corresponding damage to the tip–sample system. A F–z curve (Fig. 2b) is obtained at every point of the image, moving the tip to the next point at the end of each cycle when the tip and sample lose their contact. Feedback is engaged at point B of Fig. 2b, moving the z-piezo in a convenient way to maintain a constant deflection or loading force Fext. Adhesion force maps can be routinely obtained by using JM in air, which provides compositional or geometrical information of the surface (22). The adhesion force between the tip and the surface can be described as Fadh ¼ 4pRgL cos y þ 1:5pDgR, where gL is the water surface tension and y is the angle of the water meniscus present between the tip and surface; R is the effective radius (described above), and Dg is the tip–surface energy difference. Although the effective radius R is present in both terms, the first one mainly informs about the hydrophobicity of the sample and as such a rough estimate in air at room temperature results in ~7 nN for a Rt of about 20 nm. In air, the first term is the main contribution to Fadh while the second one depends mainly on the tip–surface geometry. The importance of the first term can be appreciated by comparing the F–z curves taken from glass in both air (Fig. 2b) and liquid (Fig. 2c): in liquid the adhesion force is almost absent, since there is no water meniscus between the tip and sample, although some hysteresis appears in the F–z curve due to the dragging of the water on the cantilever.

Let us look first at the applications of AFM for imaging in biology when operated in air. For example, DM is readily used for imaging DNA on mica. As DNA and mica are both negatively charged, MgCl2 is added to the DNA solution so that the Mg2+ ions are sandwiched between DNA and mica, resulting in the adsorption of DNA molecules on the surface. Subsequently, the sample is dried out and DM is used to image the DNA molecules on the surface. Although DNA itself has been the focus of much research using AFM (23), the obvious application of AFM is to investigate the binding of proteins to DNA, for there is now an important body of literature (24–26). In this kind of single-molecule experiments, the researcher is not interested in the average result of the bulk reaction but rather in the action of single proteins on DNA. Hence, once the protein is pipetted into the DNA solution, the reaction starts and the DNA–protein complex is adsorbed onto the mica at the appropriate time and air dried. Therefore, on the

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surface, there is a snapshot of the process taking place between proteins and DNA, and the topography provides single-molecule information of the protein–DNA complex. To pick up just one example of many, this technique has been used to study how the H-NS enzyme stops the activity of DNA-polymerase (27). While the DNA–protein complexes can be seen before copying commences, the DNA-polymerase (the big round blob on the DNA filament) becomes trapped between two pieces of DNA that are bridged by the H-NS enzyme, stopping the copying process. However, in biology, we are particularly interested in AFM imaging in a liquid milieu. This is an important issue since biomolecules are normally fully functional in aqueous solutions. First, good attachment of the biomolecule to the supporting surface is required to achieve good resolution during the imaging process. Although biomolecules can be covalently linked to a chemically modified surface (28), covalent modifications could potentially damage the biomolecules, and therefore this tends to be avoided. Fortunately, physisorption is usually sufficient and thus, the specimens can be directly adsorbed in a physiological buffer. The relevant forces that drive the physisorption process are the van der Waals force, the electrostatic double-layer force (EDL force), and the hydrophobic effect (29). Unlike the van der Waals interaction, the EDL force depends strongly on the concentration and valence of charged solutes, as well as the surface charge density of both surface and specimen. The EDL force between two equally charged surfaces is repulsive and hence opposite to the van der Waals attraction (30). To this end, one of the most extended AFM applications is to image two-dimensional protein crystals in liquid, such as membranes, by using contact mode. Biological macromolecules become attached to the surface (mica, silicon, gold, glass, etc.) when there is a net attractive force between them and the surface pulling their surfaces into contact. This force can be estimated to the light of the DLVO theory (9) like the sum of the electrostatic force between surface and molecule Fel, and the van der Waals interaction FvdW. FDLVO ¼ Fel ðzÞ þ FvdW ðzÞ ¼

2ssurf ssample z=lD Ha e  ee e0 6pz 3

where z is the distance between the surface and specimen; ssurf and ssample are the charge densities of surface and specimen, respectively; ee and e0 are the dielectric constants of the electrolyte and the vacuum, respectively; lD is the Debye length that depends on the electrolyte valence (29); and Ha the Hamaker constant. The adsorption of a sample onto freshly cleaved mica (atomically flat) can be manipulated by adjusting both the ion content and the pH of the buffer solution. An estimate of the FDLVO

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Fig. 4. Imaging the purple membrane and single viruses. Establishing the buffer conditions for imaging: in (a) the interaction force between the purple membrane and the mica surface is depicted as a function of the distance and the electrolyte concentrations. Panel (b) shows a typical AFM image of a purple membrane in liquids with bacteriorhodopsin, a light absorbing membrane protein (adapted from refs. 29 and 31). Images (c)–(e) are three MVM particles showing three-, two-, and fivefold symmetries, respectively (after ref. 38).

between a purple membrane (a 2D crystal lattice formed by bacteriorhodopsin) and mica is shown in Fig. 4a, highlighting the strong influence of the electrolyte concentration (after ref. 29). Figure 4b shows a region of purple membrane adsorbed on mica (after ref. 31). Interestingly, in this kind of set-up, the cantilever can be used to apply forces that trigger conformational changes in single proteins such us GroEL (32). AFM can also be used to visualize single proteins at work and generally AFM is used in dynamic mode and in liquid for this purpose since it is faster (33). Maximum peak forces of a few nN are applied (19), in relation to the stiffness of the sample (34) and, although these forces could in principle be damaging to the sample, they are applied for very short periods of time such as 10% of an oscillating period (i.e., for cantilever with a resonance frequency of 10 kHz in liquid, the forces are applied during 10 ms for every 0.1 ms). Using this method, it has been possible to visualize, for example, the activity of RNA polymerase on DNA,

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for instance (35), or the conformational changes in a DNA–repair complex upon binding DNA (36). Imaging viruses by AFM is a good way to illustrate this methodology. Structural and chemico-physical characterization has been critical to understand the biology of viruses. X-ray crystallography and EM (cryo-EM/IR) techniques have traditionally been used and they provide direct three-dimensional structural information as well as allowing both the interior and the surface of the virus to be visualized. However, a limitation of these techniques is that they are both averaging (“bulk”) techniques and thus they present an average time and space model of the entire population of particles found in the crystal or on the EM grid. As such, these techniques provide rather limited information (although some) on the characteristics of the individual elements in the population that distinguishes them from the average. For this reason, the beautifully symmetrical and apparently perfect models of larger viruses derived from these techniques may be somewhat deceptive as they may not be entirely representative of the individual viruses. Therefore, the imaging and interpretation of individual virus particles should always be a part of the initial virus characterization (37). Since viruses are individual particles that adsorb weakly to typical surfaces, they are prone to destruction by lateral forces in contact mode, as they are not held by a surrounding neighborhood (alike a protein in a two-dimensional crystal). In this case, the jumping mode is used (instead of the contact mode) since the loading forces can be accurately controlled thereby avoiding the application of lateral forces. Single viral particles of the minute virus of mice (MVM) adsorbed in three-, two-, and fivefold symmetries, respectively, are shown in Fig. 4c–e. By making nanoindentations with F–z curves on single viruses, it has been shown that single-stranded DNA within this virus does contribute to the overall mechanical stiffness of the virus particles (38), something that could be important for viral stability during the extracellular cycle. Moreover, it is possible to selectively disrupt these DNA–protein interactions and thereby engineer a virus with altered mechanical properties (39).

4. Perspectives and Future Directions

Some of the current developments in imaging with AFM are aimed at increasing the speed (a typical AFM image takes minutes to be acquired) in order to directly visualize the dynamics of biological processes in real time. For example, conformational changes of single myosin V proteins on mica have been shown with high video rates (80 ms/frame) using very soft cantilevers

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Fig. 5. Dynamic mode and stiffness. Panel (a) presents the topography of a mature f29 virion and (b) the simultaneously acquired phase lag related with the stiffness of the sample. They are both compared at a longitudinal profile in panel (c). Panel (d) shows the three-dimensional EM reconstruction of the virion (dark gray ) with a superposed image of the expected AFM topography including the geometric tip dilation (adapted from ref. 42).

with a high frequency of resonance in liquids (40). This was achieved by decreasing the cantilever thickness and reducing the cantilever width and length proportionally. Beyond the indentation experiments (41), dynamic mode operating in liquids can also extract information about mechanical properties (e.g., stiffness), by mapping the phase lag (Fig. 5) (42). Finally, the invention of noninvasive imaging techniques where sample destruction is minimized is also important. For example, frequency modulation AFM (43) is a dynamic technique where forces of about tens of pN can be applied to the surface. This promising technique is based on the use of three simultaneous feedbacks. A phase lock loop ensures that the cantilever is always in resonance while a second feedback (working over the phase lock loop) changes the tip–sample gap to keep a set point frequency, such that its output gives the topography. Finally, a

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third feedback is used to maintain the oscillation amplitude constant by changing the amplitude of the cantilever driving signal, which results in more stable operation. References 1. Binnig G & Rohrer H (1982) Scanning Tunneling Microscopy. Helvetica Physica Acta 55, 726–735. 2. Chen CJ (1993) Introduction to Scanning Tunneling Microscopy (Oxford University Press, Oxford). 3. Baro AM, Miranda R, Alaman J, Garcia N, Binnig G, Rohrer H, Gerber C, & Carrascosa JL (1985) Determination of Surface-Topography of Biological Specimens at High-Resolution by Scanning Tunnelling Microscopy. Nature 315, 253–254. 4. Binnig G, Quate CF, & Gerber C (1986) Atomic Force Microscope. Phys Rev Lett 56, 930–933. 5. Schmalz G (1929) Uber Glatte und Ebenheit als physikalisches und physiologishes Problem. Verein Deutscher Ingenieure. 6. Meyer G & Amer NM (1988) Novel Optical Approach to Atomic Force Microscopy. Applied Physics Letters 53, 1045–1047. 7. Sader JE, Chon JWM, & Mulvaney P (1999) Calibration of rectangular atomic force microscope cantilevers. Review of Scientific Instruments 70, 3967–3969. 8. Butt HJ & Jaschke M (1995) Calculation of Thermal Noise in Atomic-Force Microscopy. Nanotechnology 6, 1–7. 9. Israelachvili J (2002) Intermolecular and surface forces (Academic Press, London). 10. Johnson KL (1985) Contact mechanics (Cambridge University Press, Cambridge). 11. Ohnesorge F & Binnig G (1993) True Atomic-Resolution by Atomic Force Microscopy through Repulsive and Attractive Forces. Science 260, 1451–1456. 12. Giessibl FJ (1995) Atomic-Resolution of the Silicon (111)-(77) Surface by Atomic-Force Microscopy. Science 267, 68–71. 13. Sugimoto Y, Pou P, Abe M, Jelinek P, Perez R, Morita S, & Custance O (2007) Chemical identification of individual surface atoms by atomic force microscopy. Nature 446, 64–67. 14. Villarrubia JS (1997) Algorithms for scanned probe microscope image simulation, surface reconstruction, and tip estimation. J Res Natl Inst Stan 102, 425–454. 15. Marti O, Drake B, Gould S, & Hansma PK (1988) Atomic Resolution Atomic Force

Microscopy of Graphite and the Native Oxide on Silicon. Journal of Vacuum Science & Technology a-Vacuum Surfaces and Films 6, 287–290. 16. Martin Y, Williams CC, & Wickramasinghe HK (1987) Atomic Force Microscope Force Mapping and Profiling on a Sub 100-a Scale. Journal of Applied Physics 61, 4723–4729. 17. Carpick RW, Ogletree DF, & Salmeron M (1997) Lateral stiffness: A new nanomechanical measurement for the determination of shear strengths with friction force microscopy. Applied Physics Letters 70, 1548–1550. 18. Garcia R & Perez R (2002) Dynamic atomic force microscopy methods. Surface Science Reports 47, 197–301. 19. Legleiter J, Park M, Cusick B, & Kowalewski T (2006) Scanning probe acceleration microscopy (SPAM) in fluids: Mapping mechanical properties of surfaces at the nanoscale. P Natl Acad Sci USA 103, 4813–4818. 20. Miyatani T, Horii M, Rosa A, Fujihira M, & Marti O (1997) Mapping of electrical doublelayer force between tip and sample surfaces in water with pulsed-force-mode atomic force microscopy. Applied Physics Letters 71, 2632–2634. 21. de Pablo PJ, Colchero J, Gomez-Herrero J, & Baro AM (1998) Jumping mode scanning force microscopy. Applied Physics Letters 73, 3300–3302. 22. De Pablo PJ, Colchero J, Gomez-Herrero J, Baro AM, Schaefer DM, Howell S, Walsh B, & Reifenberger R (1999) Adhesion maps using scanning force microscopy techniques. Journal of Adhesion 71, 339–356. 23. Hansma HG, Sinsheimer RL, Li MQ, & Hansma PK (1992) Atomic Force Microscopy of Single-Stranded and Double-Stranded DNA. Nucleic Acids Research 20, 3585–3590. 24. Lyubchenko YL, Jacobs BL, Lindsay SM, & Stasiak A (1995) Atomic-Force Microscopy of Nucleoprotein Complexes. Scanning Microscopy 9, 705–727. 25. Dame RT, Wyman C, & Goosen N (2003) Insights into the regulation of transcription by scanning force microscopy. Journal of Microscopy-Oxford 212, 244–253. 26. Janicijevic A, Ristic D, & Wyman C (2003) The molecular machines of DNA repair:

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scanning force microscopy analysis of their architecture. Journal of Microscopy-Oxford 212, 264–272. 27. Dame RT, Wyman C, Wurm R, Wagner R, & Goosen N (2002) Structural basis for HNS-mediated trapping of RNA polymerase in the open initiation complex at the rrnB P1. Journal of Biological Chemistry 277, 2146–2150. 28. Wagner P, Hegner M, Guntherodt HJ, & Semenza G (1995) Formation and in-Situ Modification of Monolayers Chemisorbed on Ultraflat Template-Stripped Gold Surfaces. Langmuir 11, 3867–3875. 29. Muller DJ, Amrein M, & Engel A (1997) Adsorption of biological molecules to a solid support for scanning probe microscopy. Journal of Structural Biology 119, 172–188. 30. Muller DJ, Janovjak H, Lehto T, Kuerschner L, & Anderson K (2002) Observing structure, function and assembly of single proteins by AFM. Progress in Biophysics & Molecular Biology 79, 1–43. 31. Muller DJ, Schabert FA, Buldt G, & Engel A (1995) Imaging Purple Membranes in Aqueous-Solutions at Subnanometer Resolution by Atomic-Force Microscopy. Biophysical Journal 68, 1681–1686. 32. Viani MB, Pietrasanta LI, Thompson JB, Chand A, Gebeshuber IC, Kindt JH, Richter M, Hansma HG, & Hansma PK (2000) Probing protein-protein interactions in real time. Nature Structural Biology 7, 644–647. 33. Moreno-Herrero F, Colchero J, GomezHerrero J, & Baro AM (2004) Atomic force microscopy contact, tapping, and jumping modes for imaging biological samples in liquids. Physical Review E 69. 34. Xu X, Carrasco C, de Pablo PJ, GomezHerrero J, & Raman A (2008) Unmasking imaging forces on soft biological samples in liquids when using dynamic atomic force microscopy: A case study on viral capsids. Biophysical Journal 95, 2520–2528. 35. Kasas S, Thomson NH, Smith BL, Hansma HG, Zhu XS, Guthold M, Bustamante C,

Kool ET, Kashlev M, & Hansma PK (1997) Escherichia coli RNA polymerase activity observed using atomic force microscopy. Biochemistry 36, 461–468. 36. Moreno-Herrero F, de Jager M, Dekker NH, Kanaar R, Wyman C, & Dekker C (2005) Mesoscale conformational changes in the DNA-repair complex Rad50/Mre11/Nbs1 upon binding DNA. Nature 437, 440–443. 37. Plomp M, Rice MK, Wagner EK, McPherson A, & Malkin AJ (2002) Rapid visualization at high resolution of pathogens by atomic force microscopy – Structural studies of herpes simplex virus-1. American Journal of Pathology 160, 1959–1966. 38. Carrasco C, Carreira A, Schaap IAT, Serena PA, Gomez-Herrero J, Mateu MG, & Pablo PJ (2006) DNA-mediated anisotropic mechanical reinforcement of a virus. P Natl Acad Sci USA 103, 13706–13711. 39. Carrasco C, Castellanos M, de Pablo PJ, & Mateu MG (2008) Manipulation of the mechanical properties of a virus by protein engineering. P Natl Acad Sci USA 105, 4150–4155. 40. Ando T, Kodera N, Takai E, Maruyama D, Saito K, & Toda A (2001) A high-speed atomic force microscope for studying biological macromolecules. P Natl Acad Sci USA 98, 12468–12472. 41. Ivanovska IL, de Pablo PJ, Ibarra B, Sgalari G, MacKintosh FC, Carrascosa JL, Schmidt CF, & Wuite GJL (2004) Bacteriophage capsids: Tough nanoshells with complex elastic properties. Proc. Natl. Acad. Sci. U. S. A. 101, 7600–7605. 42. Melcher J, Carrasco C, Xu X, Carrascosa JL, Gomez-Herrero J, de Pablo PJ, Raman A (2009) Origins of phase constrat in the atomic forces microscopy in liquids. P Natl Acad Sci USA 106, 13655–13660. 43. Hoogenboom BW, Hug HJ, Pellmont Y, Martin S, Frederix PLTM, Fotiadis D, & Engel A (2006) Quantitative dynamic-mode scanning force microscopy in liquid. Applied Physics Letters 88, 193109.

Chapter 12 Sample Preparation for SFM Imaging of DNA, Proteins, and DNA–Protein Complexes Dejan Ristic, Humberto Sanchez, and Claire Wyman Abstract Direct imaging is invaluable for understanding the mechanism of complex genome transactions where proteins work together to organize, transcribe, replicate, and repair DNA. Scanning (or atomic) force microscopy is an ideal tool for this, providing 3D information on molecular structure at nanometer resolution from defined components. This is a convenient and practical addition to in vitro studies as readily obtainable amounts of purified proteins and DNA are required. The images reveal structural details on the size and location of DNA-bound proteins as well as protein-induced arrangement of the DNA, which are directly correlated in the same complexes. In addition, even from static images, the different forms observed and their relative distributions can be used to deduce the variety and stability of different complexes that are necessarily involved in dynamic processes. Recently available instruments that combine fluorescence with topographic imaging allow the identification of specific molecular components in complex assemblies, which broadens the applications and increases the information obtained from direct imaging of molecular complexes. We describe here basic methods for preparing samples of proteins, DNA, and complexes of the two for topographic imaging and quantitative analysis. We also describe special considerations for combined fluorescence and topographic imaging of molecular complexes. Key words: Scanning force microscopy, Atomic force microscopy, DNA–protein complexes, Single-molecule imaging, Combining fluorescence and topography

1. Introduction Proper expression and maintenance of genomic DNA are executed with precision and control by the coordinated action of proteins arranged in specific assemblies on DNA. Understanding how these proteins work together, to package, transcribe, replicate, and repair DNA, requires knowing how they are arranged into functional assemblies. Direct images of protein–DNA complexes are an essential tool to achieve this understanding. They reveal a wealth of inherently correlated information on structures, their variation, and distributions. Scanning force microscopy (SFM), also commonly known as atomic force microscopy (AFM), Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_12, # Springer Science+Business Media, LLC 2011

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is an excellent and practical method for direct imaging of proteins, DNA, and complexes of the two at the single molecule/complex level. Molecules and complexes are individually analyzed, providing information on the variety of arrangements possible and their frequency in a mixture. Importantly, this type of single-molecule structural analysis allows coherent description of features that would otherwise be lost in the averaging of bulk analysis. In addition, direct observation allows correlation of multiple structural features of individual molecular complexes. Sample preparation is relatively simple and requires component biomolecules in easily obtainable amounts and purity. SFM imaging has literally provided a new view of the molecular machinery responsible for DNA processing and by this new insight into molecular mechanisms of vital processes such as DNA packaging, repair, replication, and transcription (1, 2). Mechanistic information is obtained by quantitative analysis of image data. Typically, it is necessary to devise an appropriate scheme to divide complexes or structures observed into relevant categories and determine the distribution of these categories in different conditions. For instance, the percentage of DNA bound by a protein at a specific binding site versus at nonspecific sites would be determined as a function of conditions such as the addition of a nucleotide cofactor or another protein. SFM images are also ideal for revealing mechanistically important proteininduced distortions in DNA such as changes in DNA bending, contour length, and flexibility. Protein-induced distortions of DNA can be determined at specific binding sites and at nonspecific sites for comparison, usually from the same sample (3). DNA substrates are constructed with specific sequence or structural features at defined locations, such as a recognition sequence, a single modified or damaged base, nicks, gaps, various lengths of single- and double-stranded DNA, and complex DNA junctions such as those recognized by replication or recombination proteins. In all cases, the DNA strands not including the specific feature are by definition nonspecific binding sites and serve as unavoidable internal control DNA. Proteins and their functional assemblies often involve multiple DNA sites and strands. These functional assemblies, for example, DNA looped between protein bound at two sites or proteins associating to join or connect multiple DNA molecules, are sometimes hard to define by indirect means but obvious by simply looking at images. Biomolecules are typically deposited onto an atomically flat mica surface and imaged in air. The samples are dried of bulk water but not desiccated and likely retain their native structure (4). The volume of the particles observed can be used to estimate size and multimeric state. DNA can be deposited on mica by equilibration on the surface so that it is not kinetically trapped. In this way, the arrangement of the DNA on the surface accurately reflects its

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properties in solution, such as contour length, flexibility, and presence of bent segments. Protein–DNA complexes prepared in appropriate biochemical conditions are deposited onto mica in a similar fashion. Changes in the DNA induced by bound proteins can be accurately measured. Some proteins have features that are distinct in SFM images, such a long coiled-coil regions or multiple globular lobes, but most proteins appear as similar globular objects. Here, we describe basic methods for obtaining topographic images of DNA, proteins, and their complexes that can be used for a variety of quantitative structural analyses. Many functionally important protein–DNA complexes include multiple component proteins. The identity of components in multi-protein complexes can be estimated based on their volume and known molecular weights. However, it is not always possible to determine molecular composition and stoichiometry unambiguously by volume alone. It is, therefore, necessary to label or tag specific proteins to identify different, possibly similarly sized, components in complex assemblies. Combining fluorescence and topographic imaging allows specific identification of fluorescently labeled proteins and greatly expands the application of SFM to analysis of increasingly complex molecular assemblies. Several instruments that combine SFM topographic imaging with fluorescent imaging are currently commercially available. There are specific challenges for using these instruments for the analysis of protein–DNA complexes that we address here. It is necessary to deposit the molecules of interest onto an atomically flat surface such as mica for topography, but this substrate must also be sufficiently optically transparent to allow fluorescence. In addition, appropriate marker objects are essential to achieve nanometer accuracy in aligning optical and topographic images when the objects of interest are smaller than optical resolution. We briefly describe methods for sample preparation and image alignment that allow properly correlated SFM and fluorescence imaging.

2. Materials 2.1. Instrumentation

1. Scanning probe microscope: These instructions are guided toward eventual imaging by intermittent contact mode in air. We have a Digital Instruments MultiMode scanning probe microscopes. The methods for sample preparation and guidelines for data acquisition are applicable to any similar instrument and imaging mode (see Note 1). 2. Computers (PC, Mac) that meet the requirements of image analysis software. Software such as ImageJ (http://rsbweb. nih.gov/ij/), Image SXM (extended version of NIH image

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by Steve Barrett, Surface Science Research Centre, Univ. of Liverpool, Liverpool, U.K.), WSxM (Nanotec Electronica S.L.), or a similar image analysis software is required for quantifications of various features of visualized molecules. 2.2. General Supplies

1. Glass pasture pipettes. 2. Standard facial tissues. 3. Lens cleaning tissues (Whatman 105). 4. Forceps (DZM, Italy). 5. A source of filtrated air or N2. 6. For preparation of all solutions, Mili-Q filtered deionized water (resistivity
16 MO cm, TOC 1–5 ppb). 7. Standard protein deposition buffer: 20 mM HEPES-KOH, pH 7–8, 50–100 mM KCl (or NaCl), and 1 mM DTT (chemical supplied by SigmaAldrich). 8. Standard DNA deposition buffer: 5–10 mM HEPES-KOH pH 7.5, 5–10 mM MgCl2 (chemical supplied by Sigma–Aldrich).

2.3. Sample Substrates

1. Metal disks such as those usually supplied with a scanning probe microscope. 2. Mica sheets (Muscovite Mica V-5 quality, thickness ¼ 0.15–0.21 mm, Electron Microscopy Sciences). 3. Punch & die set (Precision brand) for cutting mica into disks. The diameter of mica disks is 1–2 mm smaller than the diameter of metal disks. 4. Superglue to attach mica disks to metal disks. 5. Invisible tape (19 mm width, Magic from 3M) to cleave mica.

2.4. DNA Preparation

General molecular biology reagents and instruments for preparation of DNA (purification from bacteria or PCR amplification) are needed. General knowledge on methods for DNA preparation, such as those found in various editions of Molecular Cloning: A Laboratory Manual from CSHL Press, is assumed.

2.5. Combining Fluorescence and SFM

For identifying specific molecules and nano-objects in SFM topography images, we use a combined SF-fluorescent microscope setup which consists of the following: An inverted fluorescence microscope equipped with high numerical aperture (1.45) objectives with a minimum magnification of 60 (Nikon TE2000); signal detections with a Cascade II:512B EMCCD camera (Princeton Instruments); running MetaMorph software (Molecular Devices) or custom made Labview (National Instruments) software for microscope operation and image acquisition;

2.5.1. Instrumentation

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and a coupled NanoWizard®II scanner (JPK instruments). Similar instruments and equivalent components would perform as well. 2.5.2. Sample Substrates for Combined Fluorescence and SFM

1. Mica sheets (Muscovite V-1 quality, from Electron Microscopy Science). 2. Glass coverslips, round, 24-mm diameter, thickness 00 (from Menzel-Glazer). 3. Optical adhesive NOA88 (Norland products). 4. Handheld UV lamp. 5. Sodium tetrahydridoborate 0.25% w/v solution in water (see Note 2). 6. Invisible tape (19 mm width, Magic from 3M).

2.5.3. Fluorescent Markers and Labels

1. FluoSpheres® carboxylate-modified microspheres (0.04 mm diameter, yellow–green fluorescent (505/515), orange fluorescent (540/560), and red fluorescent (580/605) from Invitrogen).

3. Methods 3.1. Considerations for Preparing Proteins Used in SFM Imaging

Purified proteins should be stored and used without addition of stabilizing proteins such as BSA. The protein purity requirements differ with application and the nature of possible contaminants. For example, if the protein of interest binds to DNA, contaminating proteins not bound to DNA can be ignored. Also, DNAbinding proteins should be without any trace of DNA. In general, 80% protein purity, estimated by Coomassie blue staining of the purified protein displayed by gel electrophoresis, is sufficient for SFM analysis.

3.2. Considerations for Preparing DNA Used in SFM Imaging

The length of DNA to be used depends on the eventual data desired and the specific experimental question. In general, DNA should be at least 500 bp or longer so that it is obviously DNA by appearance based on relative width, height, and length. We commonly use DNA in the range of 500–3,000 bp. Linear DNA is generally more useful. Circular DNA tends to fold over itself on the surface, making it harder to analyze. In addition, linear DNA allows determining the location of a specific sequence or feature of interest by its relative position from an end. DNA should be clean and free of proteins or other material that will deposit onto mica and complicate the imaging. Kits/columns for DNA purification (Quiagen, GE Healthcare, Sigma–Aldrich) usually produce DNA of sufficient purity for SFM, though some problems with residual column material or buffer components occasionally occur.

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The cleanest DNA is obtained by the following methods depending on the source: from solutions such as PCRs or by enzyme digestion purify DNA by phenol:chloroform extraction followed by chloroform extraction; from gel slices, purify DNA by electroelution; purify DNA from plasmid or phage preparations by cesium gradient purification. These DNA purification and isolation methods often reduce final yield. Therefore, the tradeoff between purity and yield has to be considered when choosing purification methods for individual applications. Ethanol precipitation tends to result in contaminating material when imaging, often assumed to be excess salt. For this reason, ethanol precipitation is avoided or preformed with care to wash excess salt from pellets before resuspension. 3.3. Preparation of Mica Substrates

1. Attach mica to metal by applying a very small drop of supergule onto the metal disks, placing the mica disk over the glue and gently pressing. Avoid glue spreading beyond the mica as this will interfere with cleaving the mica. 2. Freshly cleaved mica is prepared by applying scotch tape (Magic, 3M) to the mica glued to metal and peeling off the top mica layers. The peeled off layer stuck to the tape is inspected to see if it is a complete circle. If a complete layer is not cleaved off, the procedure is repeated until a complete layer, smooth unbroken circle, is removed. The mica is usually cleaved for only a few minutes to a half-hour before use to assure a clean surface.

3.4. Immobilizing Molecules on Mica: General Considerations

In order to visualize molecules in SFM, they have to be immobilized on a surface. However, molecules have to be free from the surface to enable their dynamic interactions and to prevent steric hindrance that might affect molecular interactions. Thus, the immobilization of molecules on the surface has to be carefully controlled to enable imaging while minimizing disturbing the relevant molecular interactions. Molecules can be deposited on a surface through specific or nonspecific interaction. We most often take advantage of relatively nonspecific electrostatic adsorption, which depends on the charge of the surface and molecules, and is sufficient to provide controlled attachment of DNA, proteins, and their complexes. Specific interactions such as streptavidin and biotin or digoxigenin and anti-digoxigenin provide much stronger attachment of molecules to the surface with defined molecule orientation. However, surface modification also increases roughness and interferes with imaging. The most commonly used surface for deposition of biomolecules is Muscovite mica. Mica can be cleaved at crystal planes that produce large atomically flat surfaces. This uniform flat surface allows detection of biomolecules that are only a few

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nanometers high. The mica surface is negatively charged and the heterogeneous charged domains on most proteins result in sufficient deposition without additional treatment of either surface or protein. HEPES buffers, in biologically relevant pH range (pH 7–8), are preferred for protein deposition. Tris–HCl buffers tend to deposit on mica and interfere with SFM imaging. Other common protein storage or reaction buffer components, such as KCl, MgCl2, DTT, ATP, low concentration of detergents such as NP40, and glycerol, do not interfere with protein deposition or eventual imaging in our experience. The composition of buffers used for deposition of proteins is less strict than that used for deposition of DNA because proteins deposit effectively onto mica in a wider range of salt and pH conditions. Thus, it is a good first step to deposit proteins in buffers that are optimal for maintaining protein structure and/or activity. If the protein of interest is already biochemically characterized, the optimal buffer for deposition for SFM would be the same (or very similar) as the optimal buffer for protein activity. In case of an uncharacterized protein, SFM deposition can be done in a standard deposition buffer consisting of 20 mM HEPES, pH 7–8, 50–100 mM KCl (or NaCl), and 1 mM DTT. If the protein appears aggregated upon deposition, increasing salt concentration and/or including some NP40 (0.05%) often helps to prevent undesired protein–protein interaction. Adsorption of negatively charged DNA on negatively charged mica surface requires the presence of divalent cations. Those interested in the effects of different divalent cations on DNA deposition on mica are referred to published studies on this topic (5–8). The mica surface can be modified for more efficient adsorption of DNA. This has advantages and disadvantages. The treatment of mica with either 3-aminopropyltriethoxysilane (APTES) or poly-L-lysine results in a positively charged surface. DNA binding to such surfaces does not require the addition of divalent cations. The resulting DNA is strongly attached to the modified surface and can be imaged by SFM both in air and in buffer. However, DNA does not equilibrate on these modified surfaces but become kinetically trapped (9). Deposition by kinetic trapping results in DNA conformations on mica that are strongly influenced by interaction with the surface. This complicates and in some cases precludes determining experimentally important changes in DNA conformation, such as measuring DNA bends or distortions induced by protein binding, or changes in DNA conformation induced by binding small molecules prior to deposition. In order to measure and analyze protein-induced changes in DNA, we do not use treated mica (9). In addition, any mica treatment results in a rougher surface that can complicate imaging.

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The persistence length of DNA can be determined from SFM images and is used as a test of deposition by equilibration on the surface. Persistence length reflects intrinsic flexibility of a polymer and is a well-characterized feature of DNA. Persistence length is obtained by measurements of the contour length and the end-toend distance of deposited DNA as described in (9). A persistence length of ~50 nm is characteristic of DNA and thus indicates deposition by equilibration. We have described that proteins adhere to mica in a wider variety of buffer conditions than DNA. Because of this, protein-bound DNA can also adhere to mica due to the behavior of the proteins. Thus, a protein-bound DNA will often adhere to mica in deposition conditions that are effective for the protein alone, without the need to add Mg2+ or reduce monovalent cation concentration. It should be noted, however, that free DNA, not bound by proteins, will behave differently and may not adhere to mica in conditions effective for adherence of protein–DNA complexes. Thus, deposition conditions should be chosen carefully depending on the goal of the experiment. For instance, if it is necessary to quantify the amount of protein bound and protein-free DNA, controls that show equal deposition of these need to be included. The best conditions for protein–DNA complex formation should be determined by standard quantitative biochemical assays prior to initiating SFM imaging experiments. This will form the starting point for determining conditions to be used in SFM imaging. Binding reactions for SFM typically require more concentrated DNA than many biochemical assays and there are limitations to the excess of protein that can be used. As a general rule, the solution deposited onto mica should have DNA at 1–10 ng/ml and proteins should not be more than 50-fold molar excess to their binding sites. The upper limit to excess protein is due to problems in observing DNA if the surface becomes covered by protein, or even more dramatically, if protein saturates the surface and prevents DNA binding. Thus, protein to DNA ratios and protein concentrations optimal for biochemical assays may not be optimal for SFM imaging. 3.5. Deposition of Protein for SFM Imaging

1. Prepare a solution of protein to be deposited, concentration of about 0.5 mM in an appropriate buffer is a good starting point. Optimal protein concentration for deposition will differ for each protein depending, for instance, on purity, size, and oligomeric state. Usually, protein concentrations of less than 0.5 mM (final in deposition buffer) provide reasonable coverage of the mica surface for further analysis. 2. Place a drop, 5–30 ml depending on the size of the mica surface, of protein solution onto the freshly cleaved mica surface and allow it to deposit for ~30 s.

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Fig. 1. Washing mica surfaces with water. The sample substrate is held by forceps on the edge of the metal disk, not over the mica. Water or buffer is washed over the surface using a pasture pipette.

3. Rinse the mica surface with Mili-Q filtered deionized water, about one pasture pipette full, as shown in Fig. 1. 4. Blot excess water by touching a piece of facial tissue to the edge of the mica. 5. Dry the mica surface in a stream of filtrated air (or N2). 6. Observe the sample with the SFM; typically scanning fields of 1  1 mm with a Z scale of 5 nm or less will give a good impression of the protein coverage. 7. Assess the protein coverage and modify deposition if needed. If deposition is too crowded (Fig. 2a), additional dilution of five- to tenfold usually results in surface coverage where proteins are nicely separated on the surface and can be analyzed (Fig. 2b). 3.6. Deposition of DNA for SFM Imaging

1. Prepare a solution of DNA to deposit; DNA 0.5–10 ng/ml in deposition buffer of 5–10 mM HEPES, pH 7.5,and 5–10 mM MgCl2. Since the presence of monovalent cations dramatically reduces Mg2+ promoted adsorption of DNA to mica, the concentration of monovalent salt in the solution being deposited should be less than or equal to the concentration of Mg2+. 2. Place a drop, 5–30 ml depending on the size of the mica surface, of the solution containing DNA onto the freshly cleaved mica surface and let it sit to deposit for 30 s to 1 min.

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Fig. 2. Examples of excess or appropriate protein coverage. The 37-kD human RAD51 protein was deposited as described from a buffer containing 25 mM HEPES-KOH, pH 8.0, and 100 mM KCl and imaged in tapping mode in air with a Digital Instruments multimode NanoScope. (a) Too much protein covering the mica surface prevents identification and analysis of individual molecules. Here, a 2 mM solution was used for deposition onto mica. (b) Adequate protein deposition showing many single molecules well separated and few overlapping unresolved molecule pairs. Here, a 0.2 mM solution was used for deposition onto mica. The image dimensions are shown; height is indicated by color according the scale shown on the right.

3. Wash the mica surface with Mili-Q filtered deionized water, about one pasture pipette full, as shown in Fig. 1. 4. Blot excess water by touching a piece of facial tissue to the edge of the mica. 5. Dry the mica surface in a stream of filtrated air (or N2). 6. Observe the sample with the SFM; typically scanning fields of 2  2 mm with a Z scale of 2 nm will give a good impression of the DNA coverage. 7. Assess the DNA coverage and modify deposition if needed. Excess DNA coverage is shown in Fig. 3a and appropriate coverage of DNA on mica is shown in Fig. 3b. If the DNA on the surface is too crowded, then try two- to tenfold dilution of the solution for deposition. If there is not enough DNA on the surface (only one, a few, or no molecules in a 2  2 mm scan), one of the several variations in the deposition will usually help: increase the time for the DNA solution sitting on mica to 1–2 min, increase the DNA concentration, increase the Mg2+ concentration, or decrease the monovalent cation concentration. 3.7. Deposition of Protein–DNA Complexes for SFM Imaging

1. Prepare a protein–DNA binding reaction for deposition. This typically should include DNA at 1–10 ng/ml (see Note 3).

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Fig. 3. Examples of excess and appropriate DNA coverage. DNA was deposited onto mica as described and imaged in tapping mode in air with a Digital Instruments multimode NanoScope. (a) Too much DNA covering mica prevents identification of individual molecules and precludes any meaningful analysis. Here, a solution of 800-bp linear doublestranded DNA at 10 ng/ml in 10 mM HEPES and 10 mM MgCl was used for deposition onto mica. (b) Appropriate DNA density with clearly separated and nonoverlapping DNA molecules. Depending on the length of the DNA, there should be 5–20 molecules in a field. Here, a solution of 0.5 ng/ml DNA in 10 mM MgCl was used for deposition onto mica. This resulted in about 15 isolated, identifiable, and analyzable linear DNA molecules. This linear DNA consists of a 500-bp double-stranded and 300-nt single-stranded segment. The single-stranded DNA appears as a small knob at one end of the linear molecule. The image dimensions are shown; height is indicated by color according the scale shown on the right.

2. Place a drop of the protein–DNA complex sample onto mica, as described above for protein or DNA alone, and allow it to sit for 30 s to 1 min. 3. Wash off unbound material with a small volume of binding buffer, as shown in Fig. 1. 4. Remove excess buffer by touching a tissue to the edge of the mica surface, but the surface is not dried. 5. Cover the surface with 30–40 ml of buffer containing 10 mM HEPES-KOH (pH 7.5) and 10 mM MgCl2 in order for DNA to attach to mica. 6. Almost immediately or after about 5 s, wash the mica with water, about 1 pasture pipette full, as shown in Fig. 1. 7. Blot excess liquid by touching a tissue to the edge of the mica and dry the surface in a stream of filtered air, as described above. 3.8. Deposition of Protein–DNA Complexes and Free DNA in Binding Reactions for SFM Imaging

1. Prepare a binding reaction and dilute with deposition buffer (10 mM HEPES and 10 mM MgCl2) so that the concentration of DNA is 1–10 ng/ml and the concentration of monovalent cations is equal to or less than 10 mM (see Note 4). This will allow free DNA and protein-bound DNA to adhere to mica. The initial binding reaction may need to be adjusted

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so that after dilution the solution that will be deposited still contains DNA at 1–10 ng/ml (see Note 5). 2. Place a drop of the protein–DNA complex sample onto mica, as described above for protein or DNA alone, and allow it to sit for 30 s to 1 min. 3. Wash off the unbound material with water, about 1 pasture pipette full, as shown in Fig. 1. 4. Blot excess water by touching a piece of facial tissue to the edge of the mica. 5. Dry the mica surface in a stream of filtrated air (or N2). 6. Observe the sample with the SFM; typically scanning fields of 2  2 mm or 4  4 mm with a Z scale of 2–5 nm will give a good impression of the sample. Density of DNA on the surface, either with or without bound protein, similar to that shown in Fig. 3b is sufficient for most analysis (see Note 6). 3.9. Guidelines for Collecting Image Sets for Analysis

Once the stoichiometry of DNA and protein is optimized for imaging and good coverage of mica is achieved, for proteins alone, DNA alone, or protein–DNA complexes, a collection of images needs to be obtained for eventual analysis. 1. Issues of actual microscope operation and image acquisition are not discussed or described here (refer to specific instrument operating manual). The operation of a scanning force microscope and data acquisition differ depending on the instrument and are beyond the scope of this article. The samples we have described are usually imaged in our laboratory using intermittent contact or “tapping” mode in air. We use standard silicon tapping tips for a variety of suppliers with equivalent success. It is important that the tips have a confirmed end radius of curvature of about 10 nm or less (see Note 7). 2. For most applications, scan sizes ranging from 1  1 mm up to 4  4 mm are most useful. For instance, when analyzing proteins, scans of 1  1 mm usually provide sufficient resolution and sufficient data per image. For DNA–protein complexes that individually cover more surface, scans of 2  2 mm or 4  4 mm are better (see Note 8). In any case, all images to be used in the same analysis need to be of the same size and resolution. 3. Images should be collected from nonoverlapping fields without selection for areas of interest. If scanning is stable and interference free, images can be collected without changing the scanning parameters; the autoscan function of the microscope software can be used to collect an unbiased series.

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4. Most analyses require a significant number of molecules or complexes to measure. For example, if 100 or more DNA–protein complexes have to be analyzed and the reaction results in 1/5 of the DNA molecules being bound by protein and deposition results 10 DNA molecules of about 1 kpb long in a 2  2 mm field, then a minimum of 50 such images need to be collected. It will take considerable time to collect these 50 images. In the optimistic case that everything works well, this is a half-day of collecting images. Taking into account that images are needed for control samples, planning is very important to perform efficient imaging experiments. 3.10. Guidelines for Standard Image Analysis

A number of features of protein, DNA, and protein–DNA complexes can be measured from SFM images (1). The size of proteins alone or bound to DNA can be accurately determined from SFM images. Also, protein-induced changes in DNA, such as wrapping, elongating, and bending, can be quantitatively described. DNA length can be measured from SFM images imported into specialized software such as IMAGE SXM. This is a customized version of NIH Image modified to run on a number of operating systems and to import image data automatically from a variety of commercial scanning probe microscopes. 1. We determine DNA contours by manually tracing in an appropriate image analysis program. In the case of DNA–protein complexes, contour length is traced as the shortest possible DNA path through the bound protein. Custom software that can automate DNA length measurements has been developed in several laboratories but is not currently commercially available. The length of DNA  protein will indicate whether bound protein alters DNA by wrapping or stretching (see, for example, ref. 10). 2. The volume of proteins (not bound to DNA) can be determined using a semi-automated method developed by Glenn C. Ratcliff and Dorothy A. Erie (11). Using this approach, large protein populations can be analyzed in a rapid and accurate manner. 3. The volume of DNA-bound protein complexes has to be determined by manual tracing. Area and average height of a complex are measured, and a background volume of the same traced area at an adjacent position including DNA is subtracted (12, 13). 4. DNA bending is a feature of many DNA-binding proteins (see, for example, refs. 3, 14). Using SFM, DNA bending can be directly evaluated. A comparison of different methods to determine DNA bend angles is presented in (15).

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3.11. Preparation of Mica Substrates for Combined SFMFluorescence

1. Cut the mica disk slightly smaller than the size of the coverslips. 2. Cleave the mica disk with tape until almost transparent. The color at this stage should still be slightly brownish. Be sure that one side of the mica surface is clearly flat (by eye) with no irregularities (as described in Subheading 3.3). The flat side of the mica is to be glued to the coverslip. 3. Place the coverslip to be used onto a lens cleaning tissue (Whatman 105). 4. Put a small drop of the optical glue in the end of a yellow-tip pipette. Spread slightly on the center of a round coverslip (the amount of glue could be enough for 10 coverslips). 5. Place the mica disk over the glue with the flat side facing the glue. 6. Tape the mica and the coverslip and attach to the lens cleaning tissue as shown in Fig. 4. Press down on the middle of the mica with your thumb for a homogeneous distribution of the glue under the surface. 7. Cure the UV glue by placing the UV light around 4 cm over the coverslips and switch on the 350-nm light for 3 min (see Note 9). It is most convenient to keep the glass-glued mica taped to the lens tissue (Fig. 4). A piece of lens tissue including the taped down coverslip is cut to about the size of a microscope slide. Accidentally breaking the coverslip is

Fig. 4. Illustration of preparing mica glued to glass coverslips. The mica is glued to a glass coverslip as described and then attached with tape to a lens cleaning tissue as shown. The tissue is used to pick up the fragile glass coverslip and the sample surfaces are also stored in this way.

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avoided by handling the tissue. The mica–coverslips can be stored for future use for as long as necessary. 8. Before using the mica–coverslip, the mica surface should be made as thin as possible, by cleaving as many layers as possible using the scotch tape. The transparency of the mica now should be close to 100%, otherwise the focusing step with the short-distance working objectives would be simply impossible (see Note 10). 9. Once the thickness of the mica–coverslip has been assessed (see Note 10), this layer can be stripped off and a new one treated by placing a 200 ml drop of 0.25% w/v sodium tetrahydridoborate on the mica for 20 min to reduce auto-fluorescence. Wash with water as shown in Fig. 1. The surface is now ready for depositing the solution containing the DNA and protein complex to be analyzed. 3.12. Fluorescent DNA and Proteins for Combined SFMFluorescence: General Considerations

3.13. Sample Preparation for Combined SFM-Fluorescence

General considerations for DNA and proteins: Fluorescence labels can be attached to DNA and/or protein. DNA is typically labeled (1) by PCR using fluorescence nucleotide analogs for uniform labeling if the fluorophore does not interfere with protein interactions; (2) with PCR primers including a 50 fluorophore; and (3) by conjugating biotin to DNA, also introduced by PCR with 50 biotin-modified primers, bound to any of a variety of streptavidincoupled fluorophores. Protein can be labeled with fluorophores by a variety of methods such as those described in this issue in the chapter by Modesti. 1. Prepare a DNA, Protein, or DNA–protein complex binding reaction in appropriate functional conditions. 2. Dilute the binding reaction into 20 ml of deposition buffer (10 mM HEPES and 10 mM MgCl2, including 3 pM FluoSpheres® markers) according to the guidelines given above in Subheadings 3.4–3.8. 3. Place a 20–40 ml drop of the diluted sample onto the freshly cleaved mica surface and let it sit for 1 min. 4. Wash off the unbound material with water, about 1 pasture pipette full, as shown in Fig. 1. 5. Blot off excess liquid by touching a tissue to the edge of the mica. 6. Dry the sample in a stream of filtered air.

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3.14. General Considerations for Imaging with Combined SFM-Fluorescence

3.15. Using FluoSpheres® to Align Topographic and Optical Images (Fig. 5)

Familiarity with the available fluorescence microscope setup is assumed. Specific operating instructions will vary depending on the setup and are in any case beyond the scope of this article. With respect to excitation light source, we note that a mercury lamp is often sufficient for visualization of quantum dots and FluoSpheres®, and to a limited extent for single fluorophores such as Alexa 633. Laser excitation specific to the dyes used is preferable for most single fluorophore visualization applications. In our setup, the optical microscope is coupled to a NanoWizard®II scanner (JPK instruments). In this instrument, correlation of fluorescence and topographic images is accomplished first by DirectOverlay™ software. Optical images are obtained at the highest magnification possible, usually as 60-mm fields. Topographic images are obtained as fields of 2–10 mm depending on the size of the objects deposited and the eventual analysis needed. 1. Obtain an optical image with at least 3 FluoSpheres®. The FluoSpheres® attach to mica together with the biomolecules during standard deposition and fall at random on the surface (see Note 11).

Fig. 5. Aligning optical and topographic images using FluoSpheres®. A mixture of polystyrene spheres with three different colors, were deposited for combined SFM and fluorescence imaging, as described. The samples were imaged in tapping mode in air with a JPK NanoWizard scanner mounted on a Nikon TE2000 microscope. The density of FluoSpheres® shown is appropriate for both optical and topographic imaging. (a) Optical image, 60  60 mm, of a mixture of polystyrene spheres with three different colors: green and red channels were overlaid. Polystyrene beads are recognized by the co-localization of both signals. The indicated area (5  5 mM, square) was chosen for scanning force microscopy. (b) Overlay of the fluorescence signal with the height image. (c) Topography image of the selected area, Z scale 0–30 nm. The overlay in b shows that the optical and topographic images can be aligned by centering the height image of the FluoSpheres® in the optical signals from the same objects. Panels (b) and (c) present the area scanned rotated about 135 clockwise relative to its position in panel (a).

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2. Obtain a topographic scan of the same area at a resolution that will allow clear identification of the 20–40-nm diameter FluoSpheres®. 3. Use the microscope software to overlay the two images so that the topographic image of the spheres (always smaller than the diffraction-limited fluorescent spot) is aligned with the center of the optical spots. This overlay now defines the register of the fluorescent and topographic images to nanometer accuracy and can be used to identify fluorescent signals as belonging to specific topographic features (such as specific proteins or fluorescently labeled sites on DNA).

4. Notes 1. Here, we describe the use of SFM imaging of air-dried samples with the following standard settings: scanned in intermittent contact mode (air), using Silicon Tapping/Non-Contact Mode tips 125 mm in length with a spring constant of 25–75 N/m from Applied Nanostructures, drive frequency of the cantilevers on average 300 kHz, and a line rate of 2 Hz to acquire images. 2. Tetrahydridoborate is a flammable solid and should be handled according to the precautions indicated by the supplier. The solution should be made in a fume hood. 3. Because deposition is not always perfect but easy to repeat, it is a good idea to make several depositions of the same sample. When working with protein–DNA binding reactions, depositions should be done at the same time to keep the binding conditions, such as incubation time, constant. It is also a good idea to deposit different dilutions, differing by a factor of 2–5, at once to assure that one will be appropriate for analysis without requiring repetitive binding reactions and additional material. 4. After dilution, the sample should be transferred to mica as fast as possible to avoid changes in binding behavior due to changed salt conditions. Typically, adding a small volume of binding reaction to a premeasured volume of deposition buffer for dilution and immediately pipetting onto mica take less than 20 s. 5. The optimal buffer conditions, stoichiometry of DNA and protein, and the expected number of complexes are best extracted from previous biochemical characterizations. As mentioned above, these will indicate starting conditions as the amounts and concentration of DNA and proteins that

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are optimal for SFM imaging may be different. Based on the initial SFM results, it may be necessary to vary the stoichiometry of DNA and protein to obtain sufficient protein–DNA complexes for analysis or to minimize background of unbound proteins. This is best done in small steps, such as twofold changes in concentration of proteins or DNA, in order to improve the image data that can be obtained. 6. If enough material is not deposited on mica, small variations in the dilution step that may effect cation concentrations by twofold or less can also make a big difference. 7. The sharpness of the tips determines the resolution and detail of the images obtained. Although specialized tips with end radius of curvature considerably less than the usual 10 nm (some as small as 2 nm) are available, they are still rather expensive. In our experience, for most applications, the added resolution and detail are minimal and do not justify the extra cost. We use uncoated tips. Even though coatings that increase reflectivity of the back of the cantilevers should not influence the size of the end of the tips, in our experience coated tips produced poorer resolution. 8. Many commercial SFMs produce images with maximally 512  512 pixels, independent of the scan size. Thus, larger scan sizes produce data with lower resolution. Clearly, higher resolution is achieved with smaller scan size (scan of 1  1 mm, 1 pixel ~2 nm vs. scan of 4  4 mm, 1 pixel ~8 nm). Due to the size of the scanning tips, we typically use standard silicon noncontact tips with a radius of curvature of about 10 nm, resolution does not improve much by decreasing scan size below 1  1 mm. 9. When using a UV light, wear UV safety glasses and avoid skin exposure. 10. It is wise, before going further in the sample preparation, to check if the mica glued to glass thickness is appropriate. Deposit the fluorescent test object such as the FluoSpheres® (3 pM solution in deposition buffer) and check if it is possible to focus on the surface in the fluorescent microscope. If it is not possible, more mica layers need to be cleaved off. 11. We have also tested quantum dots as markers for aligning fluorescence and topographic images. However, due to the relatively large percentage of dark quantum dots in the preparations we have used, it is not easy to align the patterns from the topographic and fluorescence image unambiguously. Thus, in our experience, quantum dots are not a robust marker for alignment.

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References 1. Janicijevic, A., Ristic, D. and Wyman, C. (2003) The molecular machines of DNA repair: scanning force microscopy analysis of their architecture. J Microsc. 212, 264–72. 2. Dame, R.T., Wyman, C. and Goosen, N. (2003) Insights into the regulation of transcription by scanning force microscopy. J Microsc. 212, 244–53. 3. Erie, D.A., Yang, G., Schultz, H. C. and Bustamante, C. (1994) DNA bending by Cro protein in specific and nonspecific complexes: implications for protein site recognition and specificity. Science 266, 1562–6. 4. Ristic, D., Modesti, M., van der Heijden, T., van Noort, J., Dekker, C., Kanaar, R. and Wyman, C. (2005) Human Rad51 filaments on doubleand single-stranded DNA: correlating regular and irregular forms with recombination function. Nucleic Acids Res. 33, 3292–302. 5. Bustamante, C., Vesenka, J., Tang, C. L., Rees, W., Guthold, M. and Keller, R. (1992) Circular DNA molecules imaged in air by scanning force microscopy. Biochemistry 31, 22–6. 6. Vesenka, J., Guthold, M., Tang, C. L., Keller, D., Delaine, E. and Bustamante, C. (1992) Substrate preparation for reliable imaging of DNA molecules with the scanning force microscope. Ultramicroscopy 42–44, 1243–9. 7. Hansma, H.G. and Laney, D.E. (1996) DNA binding to mica correlates with cationic radius: assay by atomic force microscopy. Biophys J. 70, 1933–9. 8. Han, W., Lindsay, S. M., Dlakic, M. and Harrington, R. E. (1997) Kinked DNA. Nature 386, 563.

9. Rivetti, C., Guthold, M. and Bustamante, C. (1996) Scanning force microscopy of DNA deposited onto mica: equilibration versus kinetic trapping studied by statistical polymer chain analysis. J Mol Biol. 264, 919–32. 10. Beerens, N., Hoeijmakers, J. H., Kanaar, R., Vermeulen, W. and Wyman, C. (2005) The CSB protein actively wraps DNA. J Biol Chem. 280, 4722–9. 11. Ratcliff, G.C. and Erie, D.A. (2001) A novel single-molecule study to determine protein– protein association constants. J Am Chem Soc. 123, 5632–5. 12. Wyman, C., Rombel, I., North, A. K., Bustamante, C. and Kustu, S. (1997) Unusual oligomerization required for activity of NtrC, a bacterial enhancer-binding protein. Science 275, 1658–61. 13. van der Linden, E., Sanchez, H., Kinoshita, E., Kanaar, R. and Wyman, C. (2009) RAD50 and NBS1 form a stable complex functional in DNA binding and tethering. Nucleic Acids Res. 37, 1580–8. 14. Janicijevic, A., Sugasawa, K., Shimizu, Y., Hanaoka, F., Wijgers, N., Djurica, M., Hoeijmakers, J. H. and Wyman, C. (2003) DNA bending by the human damage recognition complex XPC-HR23B. DNA Repair (Amst). 2, 325–36. 15. Dame, R.T., van Mameren, J., Luijsterburg, M. S., Mysiak, M. E., Janicijevic, A., Pazdzior, G., van der Vliet, P. C., Wyman, C. and Wuite, G. J. (2005) Analysis of scanning force microscopy images of protein-induced DNA bending using simulations. Nucleic Acids Res. 33, e68.

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Chapter 13 Single-Molecule Protein Unfolding and Refolding Using Atomic Force Microscopy Thomas Bornschlo¨gl and Matthias Rief Abstract Over the past few years, atomic force microscopy (AFM) became a prominent tool to study the mechanical properties of proteins and protein interactions on a single-molecule level. AFM together with other mechanical, single-molecule manipulating techniques (Bustamante et al., Nat Rev Mol Cell Biol 1:130–136, 2000) made it possible to probe biological molecules in a way that is complementary to single-molecule methods using chemicals or temperature as a denaturant (Borgia et al., Annu Rev Biochem 77:101–125, 2008). For example, AFM offered new insights into the process of protein folding and unfolding by probing single proteins with mechanical forces. Since many proteins fulfill mechanical function or are exerted to mechanical forces in their natural environment, AFM allows to target physiologically relevant questions. Although the number of proteins unfolded with AFM continually increases (Linke and Grutzner, Pflugers Arch 456:101–115, 2008; Zhuang and Rief, Curr Opin Struct Biol 13:88–97, 2003; Clausen-Schaumann et al., Curr Opin Chem Biol 4:524–530, 2000; Rounsevell et al., Methods 34:100–111, 2004), the total number of proteins studied so far is still relatively small (Oberhauser and Carrion-Vazquez, J Biol Chem 283:6617–6621, 2008). This chapter aims at giving protocol-like instructions for people who are actually getting started using AFM to study mechanical protein unfolding or refolding. The instruction includes different approaches to produce polyproteins or modular protein chains which are commonly used to screen for true singlemolecule AFM data traces. Also, the basic principles for data collection with AFM and the basic data analysis methods are explained. For people who want to study proteins that unfold at small forces or for people who want to study protein folding which also occurs typically at small forces (<30 pN), an averaging technique is explained, allowing to increase the force resolution in this regime. For topics that would go beyond the scope of this chapter – as, for example, the details about different cantilever calibration methods – references are provided. Key words: Atomic force microscopy, Single-molecule technique, Mechanical protein unfolding and refolding, Polyprotein design, Cystein engineering, Coiled-coil engineering

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_13, # Springer Science+Business Media, LLC 2011

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1. Introduction In recent years single-molecule force spectroscopy offered many new insights into the mechanics of single molecules that are complementary to other single-molecule methods (25, 29). One of these powerful force-spectroscopy techniques is AFM that allows to mechanically stretch and unfold a single protein which is attached between cantilever tip and surface (19, 30–33). In order to anchor proteins between an AFM cantilever tip and a substrate, one can take advantage of an inherent property that proteins have, which is that they stick to various surfaces by nonspecific adsorption. The downside of this property is that the exact anchoring points are not known and that by chance, more than one single protein might bind between the cantilever tip and surface. An elegant way to circumvent this disadvantage is to use a modular protein chain consisting of many similar or identical protein subunits. If such a modular protein chain binds to the tip and surface, the exact anchoring points become irrelevant because the force onto a protein inside the chain is transduced via its neighbors and their connection can be exactly determined. Also, the unfolding of such a highly repetitive structure leads to a repetitive force vs. extension signal when probed with AFM. By taking advantage of this repetitive fingerprint, it is possible to select traces where only one single molecule is bound between a cantilever tip and a surface. In order to study proteins that do not occur naturally as modular protein chains, different protein engineering approaches evolved. For example, you can insert your protein of interest into a naturally occurring modular protein or you can directly construct polyprotein chains using coiled-coils or “cysteine engineering.” These methods will be described in the first part of the Methods section. Using these modular protein chains, the basic principles of AFM measurement and how to select and analyze the data are explained in the second part of the Methods chapter. An averaging technique that allows to increase the force resolution in the low-force regime is explained in the third part of the Methods section.

2. Materials 2.1. Protein Design

1. T7 promoter-based E. coli cytosolic expression vector (e.g., pET28 family (Novagen) or pRSET family (Invitrogene)). 2. BL21 CodonPlus(DE3)-RIL E. coli competent cells (Stratagene). 3. XL10 Gold Ultracompetent E. coli cells (Stratagene).

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4. QiaPrep spin miniprep columns (Qiagen). 5. QiaQuick gel extraction kit (Qiagen). 6. HisTrap HP or FF affinity chromatography columns (GE Healthcare). 7. Mutagenesis primers (Metabion). 8. Phusion Site-directed Mutagenesis kit (New England BioLabs). 9. Quickchange Multi Site-directed mutagenesis kit (Stratagene). 10. T4 DNA ligase (NewEngland BioLabs). 11. Restriction enzymes for the restriction sites of your choice (NewEngland BioLabs). 12. Lysis buffer: 50 mM NaH2PO4 and 300 mM NaCl, adjust pH to 8.0 using NaOH. 13. Size-exclusion analytical chromatography columns such as Superose 10/300 GL columns (GE Healthcare). 14. French press or sonicator. 15. Centricon centrifugal filter units (Millipore). 2.2. Atomic Force Microscopy

1. Atomic force microscope (e.g., Asylum research). 2. Phosphate-buffered saline (PBS): 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, and 1.8 mM KH2PO4 (adjust to pH 7.4 with HCl). 3. Clean glass coverslips or freshly gold-evaporated glass coverslips. 4. Soft AFM cantilever (e.g., Bio Lever Type A or B, Olympus).

3. Methods 3.1. Protein Design and Purification

To study mechanical protein unfolding, typically researchers stretch modular proteins that have been adsorbed unspecifically between AFM cantilever tip and surface. Because such a protein consists of similar subunits, one gets a highly repetitive force-extension pattern from one molecule which can be used to choose true single-molecule unfolding events for data analysis. To study any protein of interest, different methods based on molecular biology can be used. One of these protein engineering methods is to insert the protein of interest into an already known, naturally occurring modular protein background such as the giant muscle protein titin or the Dictyostelium discoideum filamin (ddFLN) (Fig. 1a–c). Using this approach, the protein of interest should differ in size (amount of amino acids forming the protein) or in average unfolding force from the used modular protein background. Only then can the unfolding event associated with the inserted protein be easily identified.

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Fig. 1. Different protein engineering approaches to construct modular protein chains for mechanical protein unfolding experiments using AFM. (a–c) Insertion of the sequence coding for the protein of interest into a naturally occurring modular protein background (such as ddFLN1-5) leads after translation to the modular protein schematically shown in (b). AFM measurements reveal the unfolding events of the background protein (gray ) as well as the unfolding event of the inserted protein (black in c). The example curve was measured on GFP inserted between domains 3 and 4 of ddFLN1-5. Data were kindly provided by H. Dietz. (d–f) Flanking the sequence coding for your protein of interest by coiled-coil sequences leads after translation to the protein construct shown on top in (e). Due to coiled-coil dimerization, the single proteins will self-assemble into elongated modular protein chains. (f) AFM measurements lead to repetitive sawtooth-like traces, where every sawteeth corresponds to an unfolding event of the protein of interest (black ). In the low force regime (here before 200 nm), the unfolding of the connecting coiled-coils can be observed using Subheading 3.3.2. A force plateau at ~10 pN becomes visible, which is associated with the unzipping of several coiled-coils in series, while the force plateau at ~25 pN is connected to the overstretching of the coiled-coils. (Inset). (g–i) Mutation of two surface exposed amino acid residues in your protein of interest to cysteines leads to the structure schematically shown on top in (h). At high concentrations, the cysteines will build covalent disulfide bridges, which lead to elongated modular protein chains. (i) AFM measurement on such chains reveals sawtooth-like force pattern where the sawteeth are associated with the unfolding event of your protein of interest. The trace was measured on GFP connected via the amino acid positions 3 and 212 where also intermediate states can be observed. Data provided by H. Dietz. The traces (in c and i) are measured with the Type A Biolever, while (f) was measured with the Type B cantilever (Olympus).

(See, for example, black unfolding event in Fig. 1c for GFP inserted in a ddFLN background shown in gray). Other protein engineering approaches take advantage of artificially designed polyproteins consisting of identical protein subunits. By stretching such a construct with AFM, one gets directly from one single-molecule measurement many unfolding events associated with the protein of interest, which facilitates the generation of datasets with statistical relevance. The design and production of such polyproteins can be done in different ways.

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One approach is to repeat the protein-decoding DNA sequence multiple times within the plasmid by using molecular biology methods (1). This leads after translation to a polyprotein chain where the individual proteins are connected via their N- and C-termini. This approach is very robust but the molecular weight of the protein construct and, therefore, the total number of protein subunits on the chain are limited. A second approach is to add coiled-coils onto the N- and Ctermini of the protein of interest. In solution, the coiled-coil dimerizes, thereby leading to a repetitive structure where the protein subunits of interest are connected via coiled-coils (Fig. 1d–f). This approach leads to long polyproteins containing a high number of subunits, but their connection is still limited to the N- and C-terminal ends of the protein (2). A third way to produce polyproteins is to introduce two solvent-accessible cysteines into the protein structure of interest. In solution, the protein then polymerizes via the formation of covalent disulfide bridges. This approach leads to long polyproteins where the force onto a single molecule can be applied in a desired arbitrary three-dimensional direction (3). In the following, we give protocols involving standard molecular biology methods to produce modular proteins that can be used for AFM studies. The advantages and drawbacks are summarized in Note 1. 3.1.1. Insert Your Protein of Interest into a Naturally Occurring Modular Protein Chain (Such as ddFLN1-5)

1. Use a T7 promoter-based E. coli cytosolic expression vector (e.g., pET28a+ or pRSET family). 2. Insert the DNA coding for the domains 1–5 of the Dyctiostelium discoideum actin-binding protein (ddFLN1-5 or abp120; PubMed location: P13466) into the multiple cloning site of the expression vector (4). Use codons with high expression yield for E. coli (GeneArt). For cutting, use restriction enzymes (New England BioLabs) of your choice. Take care that the restriction site occurs only once in your vector. For re-ligation, use T4 DNA ligase. Alternatively, you can use different modular proteins as background protein (see Note 2). 3. If not already present in the expression vector, add a DNA sequence coding for 6 histidine residues (His6 tag) to the sequence coding for ddFLN1-5 domains using, for example, the Phusion site-directed mutagenesis kit (New England BioLabs). This allows protein purification using the HisTrap columns afterward. 4. Insert two restriction sites of your choice between domains 2 and 3 (amino acid (AA) position 449 (4)) or between domains 3 and 4 (AA position 549) using the Quickchange Multi site-directed mutagenesis kit or the Phusion sitedirected mutagenesis kit.

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5. Insert the sequence coding for your protein of interest (black sequence in Fig. 1a) between these restriction sites. 6. Confirm your final vector by sequencing (GATC). 7. For protein expression, transform the plasmid into an E. coli expression strain such as the BL21-CodonPlus(DE3)-RIL and follow the manufacturer’s protocol. 8. Centrifuge the gained cell culture and resuspend the pelleted cells in lysis buffer (e.g., resuspend cells out of 500 ml cell culture in 30 ml lysis buffer). 9. Lyse the cells using a French press or a sonicator. Keep the cell suspension at 4
C. 10. Pellet the cell fragments by centrifuging for 40 min at 30,000  g and keep the supernatant cell extract at 4
C. 11. Apply the supernatant cell extract onto Ni-NTA affinity chromatography columns (using, e.g., HisTrap FF columns). Wash the columns using the lysis buffer with increasing concentrations of imidazole (use, e.g., 50, 100, 200, and 500 mM imidazole suspensions). 12. Use SDS-Page gel electrophoresis to determine the elution fraction that contains your protein and the degree of purity. 13. If needed, you can increase the degree of purification by using size-exclusion analytical chromatography. 14. Determine protein concentration using, e.g., the Bradford assay (ca. 1 mg/ml is convenient). 15. Continue with the AFM measurement. 3.1.2. Construct Polyproteins Using Coiled-Coils

1. Use a T7 promoter-based E. coli cytosolic expression vector (e.g., pET28 family or pRSET family) containing a His6 tag sequence (See Subheading 3.1.1, step 3). 2. Insert two times in a row the DNA sequence coding for a homo-dimeric coiled-coil as, for example, the LZ10 coiledcoil (RMKQLEQKVEELLQKNYHLEQEVARLKQLVGECEG (5, 6)) using codons with high expression yield for E. coli (GeneArt). 3. If you prefer to use other homo-dimeric coiled-coil sequences, determine the a and d positions of the heptad repeat (underlined in the above LZ10 sequence) using free programs such as coils (http://www.ch.embnet.org/software/COILS_ form.html) (7) or paircoils (http://groups.csail.mit.edu/cb/paircoil/cgibin/paircoil.cgi) (8), and change the last a or d position of your coiled-coil to a cysteine (black circles in Fig. 1d). 4. Insert two restriction sites of your choice between both coiled-coil coding sequences using the Phusion site-directed mutagenesis kit.

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5. Insert your protein of interest between these restriction sites (black in Fig. 1d). 6. Check your vector by sequencing (GATC). 7. Continue with protein expression and purification (steps 7–14 of Subheading 3.1.1) and the AFM measurement. When you use the LZ10 coiled-coil as polymerization motif, the protein polymerization will take place already for protein concentrations >25 mM. Thus, polymerization will already occur during the steps for expression and purification so that no further incubation is needed. If you observe sedimentation in your protein solution due to aggregation, spin down aggregates at 10,000  g for >10 min and use the supernatant for the AFM experiments. 3.1.3. Construct Polyproteins Using “Cysteine Engineering”

1. Use your T7 promoter-based E. coli expression vector containing a His6 tag sequence. 2. Insert your protein of interest into the multiple cloning site of the vector (See Fig. 1g). 3. Choose two residues within the amino acid sequence of your protein of interest and change them into cysteines using the Phusion site-directed mutagenesis kit. These cysteines will later on define the linkage geometry. Therefore, it is critical that they are solvent accessible. Use the protein structure if it is available to determine these linkage points; if not available, try the N- and C-termini as linkage points because they are often solvent accessible. Choosing residues that are located at opposite sites of the protein structure might decrease the hindrance for polymerization due to sterical restrictions. Also, check if your protein already contains solvent-accessible cysteines, and either exchange them with, e.g., alanine or serine or use them as linkage points. For troubleshooting and further details, see the protocol (3). 4. Continue with protein expression and purification (steps 7–14 of Subheading 3.1.1). 5. Concentrate the purified protein in the lysis buffer solution to more than 0.2 mM using, e.g., Centricon centrifugal filter units. 6. For polymerization, incubate the protein solution for ca. 80 h at 37
C if this temperature does not affect your protein. Else, incubate at lower temperatures for longer times. Check the progress of the polymerization using, e.g., SDS-Page with nonreducing SDS buffer. When the wanted degree of polymerization is reached (average of octamers is convenient for AFM measurements), dilute the protein solution to decrease further polymerization (e.g., dilute to 0.02 mM).

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7. Continue with the AFM experiments. If you observe sedimentation in your protein solution due to aggregation, spin down aggregates at 10,000  g for >10 min and use the supernatant for the AFM experiments. 3.2. Principal Data Collection and Analysis Using AFM

3.2.1. Experimental Setup and Data Collection

The development and availability of relatively easy-to-use commercial atomic force microscopes allow the application of this technique by researchers who are interested in single-molecule protein folding and unfolding, and who do not necessarily have to be AFM specialists. Most of the commercially available instruments also include automated procedures, e.g., in order to calibrate the force constants of the used cantilevers. For details on how to use your specific AFM, the relevant manual will provide much more useful information than this chapter is able to. Therefore, we will only shortly explain the basic principles of AFM measurements and provide relevant references for further reading. Due to the unspecific binding of proteins between cantilever tip and surface, the collected data will consist of a huge fraction of non-interpretable traces as, for example, traces where many molecules have bound in parallel. The second part of this chapter, therefore, provides a protocol on how to select relevant and interpretable single-molecule data when the modular polyprotein chains from Subheading 3.1 are used for the measurements. This section also explains the principal steps to determine the length increase due to protein unfolding. 1. Apply ca. 10 ml of the protein suspension to a clean glass coverslip or a freshly gold-evaporated glass surface and incubate for 20 min. To avoid air bubbles when you apply a drop (ca. 30 ml) of PBS onto the cantilever (Bio Lever Type A or B, Olympus), use degassed PBS. Join both drops and align the AFM (as shown in Fig. 2a), where a beam of light that is focused on the tip of the cantilever’s back side is reflected onto the middle of a 2-segment photodiode. To determine the bending of the cantilever, read out the deflection D(t) by reading the intensities I measured on the two photodiodes A and B. (D(t) ¼ (IA  IB)/(IA + IB)). 2. If not already available, install a piezo control (Physik Instrumente) that allows, e.g., to move the surface back and forth over distances of several micrometer at constant velocity. Applicable velocities for protein unfolding experiments range between 1 nm/s and 10,000 nm/s (some of the limiting factors are instrument drift for slower pulling speeds and hydrodynamic effects for the upper border). 3. Gently approach the cantilver tip toward the surface. You can do so by observing the hysteresis in the deflection signal that originates from the hydrodynamic drag due to a repetitive,

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Fig. 2. Experimental setup. (a) Schematic drawing of the AFM setup. (b) By applying a triangular voltage signal to the piezo-actuator, the surface should move toward the cantilever and then away from the cantilever at constant velocity. (c) Deflection signal when no protein has been attached between cantilever tip and surface after contact.

forward, and backward movement at constant velocities (~5 mm/s) of the surface. This hysteresis will increase with decreasing cantilever–surface distance. When close to the surface, apply a triangular voltage signal to the piezo-actuator, leading to surface movement as shown in Fig. 2b. If you are close enough to the surface, you should gain a deflection trace as the one shown in Fig. 2c, which defines the position of the surface (slightly tilted vertical line that also defines the proportionality constant p) and the zero line for the force acting on the cantilever (horizontal line). 4. Check your instrument drift. The deflection should stay constant when the surface is not moved. Particles swimming through the optical path of the light beam might lead to slow variations in the signal, while cantilever drift caused, e.g., by the bimetal effect might lead to a constantly creeping drift. Check also if the absolute distance of cantilever to surface stays constant over time. Without drift the curve shown in Fig. 2c should be exactly reproducible after some time, and forward and backward traces at slow velocities <500 nm/s should not significantly differ. 5. Start the measurement by repeatedly pressing the cantilever against the surface and by retracting it afterward at constant velocity. To increase protein adsorption between cantilever tip and surface, you can increase the time of cantilever–surface contact.

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6. After your measurement, calibrate the spring constant of the used cantilever far away from the surface. Commonly, the method of thermal equilibration is used and already implemented in most commercially available AFMs. For further details, see (9–12). 7. Calculate from the deflection signal D(t) and from the absolute surface position signal x0 the force and the tip to surface distance z(t) (extension) using F ðtÞ ¼ kC =p DðtÞ and

zðtÞ ¼ x0 ðtÞ  1=p DðtÞ;

where p can be calculated as shown in Fig. 2c. 3.2.2. Data Selection

1. Select the force traces where only one single molecule has been attached between cantilever tip and surface while pulling. Use the following selection criteria: –

Only select sawtooth-like pattern with more than 2 sawteeth. The sawteeth should appear equidistantly as in Fig. 1f for the polyproteins made with steps in Subheadings 3.1.2 and 3.1.3. (See Subheading 3.2.3 for how to measure contour length increases). When ddFLN is used as protein background, the sawteeth should look like the gray ones in Fig. 1c.

–

Preferentially, select curves where the last sawtooth rises to higher force than the forgoing ones. This corresponds to a clear detachment or rupture event of the molecule. After this detachment, you should not see any other rising force in the relaxation event of the cantilever.

–

Preferentially, select force traces where the effect of other bound molecules in the beginning of the force curve is negligible. (See black event below 100 nm in Fig. 1f as an example of an unwanted, additionally bound molecule.)

As a more objective method to select typical force traces associated with the measured protein, you can use a pattern recognition algorithm (13). 2. Compare the force traces from at least 4 different experiments, e.g., by overlaying them. The contour length gains due to unfolding should be exactly reproducible for different measurements. A total amount of 50–100 different unfolding events is convenient. When you use a natural protein as background (Subheading 3.1.1), the force traces should contain an additional unfolding event with reproducible length associated with the inserted protein of interest. 3. If you use steps in Subheading 3.1.1 and observe unfolding events of the matrix protein without a new effect for your protein of interest, check if your protein unfolds at low forces

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using Subheading 3.3.2. Also, it might be that your protein unfolds at forces that are much higher than the unfolding forces of the matrix protein. Check this by using Subheading 3.1.2 or 3.1.3. 3.2.3. Determining Contour Length Gain, Number of Unfolded Amino Acids, and Unfolding Forces

1. The end-to-end distance of a polymer in solution increases in a nonlinear fashion with increasing force. As a quick way (e.g., for the first data selection) to compare the length increases of the unfolding proteins, you can take the distances between two consecutive sawteeth. Compare only the distances that you measured at the same force. 2. Determine the contour length of the polymer by fitting the interpolation formula based on the worm-like chain (WLC) model to your data (14): ! kB T 1 1 z F ðzÞ ¼  þ ; p 4ð1  z=LÞ2 4 L where kB is the Boltzmann constant, T is Temperature in Kelvin, L is the contour length (in this formula, the total length of the polymer when an infinite force is applied), and p is the persistence length describing the flexibility of the polymer. In the force regime between 50 and 150 pN, the formula reproduces experimentally measured data very well using a persistence length of 0.5 nm (15). (See Note 3 for other force regimes.) 3. Determine the contour length increase due to protein unfolding by measuring the difference in contour length between consecutive force peaks using step 2. The contour length increase can be used to calculate the amount of unfolding amino acids if the folded structure of the protein is known. The contour length increase DL is given by DL ¼ ndAA  dfolded ; where n is the number of unfolding amino acids, dAA is the contour length of a single amino acid, and dfolded is the initial distance of the amino acids onto which force is applied in the native structure. Using ddFLN and titin as “gauge proteins,” we find a value of dAA ¼ 0.365  0.002 nm. Since this value might slightly differ for your AFM, you should determine your dAA, e.g., by using Subheading 3.1.1 and by measuring the contour length increases due to ddFLN unfolding (for ddFLN, n ¼ 100 and dfolded ¼ 4.0  0.1 nm). 4. Calculate the amount of unfolding amino acids for your protein of interest using step 3. If you find a value which is deviating from the expected one, check if your protein does not show any pre-unfolded parts. When using Subheading 3.1.1 or

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3.1.2, you can check this by deleting the presumably unstable N- or C-terminal parts of your protein and by redoing the AFM measurements. When using Subheading 3.1.3, insert the cysteines further away from the termini. To check if parts of your protein unfold already at lower forces, use the steps explained in Subheading 3.3. Be aware that stable intermediate states might also be observed, leading to one or more (16) force peaks occurring during protein unfolding; see, e.g., the intermediate state of ddFLN4 in Fig. 1c at ~50 nm (17) or the intermediate states occurring in Fig. 1i. 5. Determine the distribution of unfolding forces (the height of the individual sawteeth peaks relative to the 0 force line) for datasets collected at different pulling velocities, respectively. From these data, you can, for example, interpolate to the rate of unfolding at 0 force and reconstruct parts of the underlying energy landscape. There are different approaches including Monte Carlo simulations which have been applied to reconstruct the underlying energy landscape. For more details, see (18, 19). 3.3. Protein Folding and Unfolding Close to Thermodynamic Equilibrium

Atomic force microscopy can not only be used to observe the mechanical unfolding of proteins, but it also allows to study their refolding. Commonly, the unfolding of globular proteins occurs at relatively high forces (>50 pN), while they refold at forces in the lower pN regime where the resolution of commercially available cantilevers can become the limiting factor. It is demanding but possible to observe the refolding of such proteins directly (20, 21). Another approach that has been already used to deduce the folding properties of a protein is to retract the cantilever toward the surface after the protein has been successfully unfolded. After a certain time during which the protein is allowed to refold, one can check if folding had occurred by stretching the whole protein again (22) (17). However, AFM is perfectly suited to study protein unfolding and refolding even at very small forces if this process occurs close to thermodynamic equilibrium. In this case, either many folding/unfolding transitions can be observed during one stretching cycle of one molecule (23) or many stretching and relaxing cycles with highly reproducible force extension pattern can be obtained on the same molecule (5, 24). This allows to separate the signal easily from unspecific background such as drift. It should be noted that the use of an optical trap comprising of a higher force resolution is an alternative for the study of proteins in this force regime, especially if constant force experiments are wanted (25). But the AFM with its higher force constants can provide insights into this low force regime that might be complementary to those measured with optical trapping. The following subchapter provides a protocol for how the force

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resolution of an AFM in the low force regime can be enhanced by recording many folding/unfolding cycles and by averaging them. 3.3.1. Protein Design and First Steps

1. Use a naturally occurring modular protein or an artificially designed modular protein as matrix protein and insert only once your protein of interest (see Subheading 3.1.1). The used matrix protein should have been already probed with AFM and should be known to be stable enough to not interfere with the unfolding of your protein of interest. Subheading 3.1.1 facilitates the screening for true single-molecule events compared to a polyprotein approach (Subheadings 3.1.2 and 3.1.3) because you expect that the unfolding forces of your protein of interest are small. Moreover, the unfolding/folding behavior of one single protein might be already rather complex so that using the polyprotein approach might complicate the data analysis. 2. Start with the standard measurement and data analysis (Subheadings 3.2.1 and 3.2.2) at slow velocities (~100 nm/s). This will prove successful protein design and purification, and it may give you a first idea of the unfolding behavior of your protein. Since your protein will unfold in the beginning of the force curve where often unspecific interactions occur (e.g., gray effect in Fig. 3a before ~75 nm), data collection using Subheading 3.2.2 might be demanding.

Fig. 3. High resolution experiments for proteins that unfold and refold close to thermodynamic equilibrium. (a) Example curve to study coiled-coil unzipping (black at forces <20 pN) within a ddFLN background protein (unfolding shown in gray at forces of ~60 pN) gained with an approach similar to Subheading 3.1.1. (b) The surface is consecutively approached and retracted from the cantilever tip, which leads to multiple unfolding/refolding cycles. (c) Three single unfolding traces stacked by 20 pN steps for better comparison. (d) Outcome of averaging the unfolding (black ) and refolding (gray ) traces, respectively.

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3.3.2. High Resolution Measurements

1. Apply a consecutively increasing and decreasing voltage signal to the piezo control after the cantilever has touched the surface. The anticipated extension signal (Fig. 3b) leads to consecutive unfolding/refolding cycles in the beginning of the force curve and thus in the low force regime, and is followed by a total retraction from the surface after the last cycle. The calculation of the turning points (a and b in Fig. 3b) is crucial: –

First, approach the cantilever to the surface with constant velocity (leading to a force trace as shown in Fig. 2c).

–

Use this signal to determine the point of contact of the cantilver tip with the surface (piezoposition 0 in Fig. 2c).

–

The turning point a should not be too close to the surface to avoid unspecific attachment of additional proteins during the cycles. On the contrary, it should not be too far from the surface to allow for protein refolding at low forces. A value of ~20 nm might be convenient to start with.

–

The turning point b depends on the contour length increase which you expect from your protein. As a rough guess, take the sum of the expected contour length increase of your protein of interest and the contour length of the folded matrix proteins, and add 75% of this sum to the position of the turning point a. If you find very often an already unfolded matrix protein in the beginning of the measurement, add 75% of its contour length too. Note that your resolution diminishes with the amount of unfolded polypeptide because the stiffness of the system comprising cantilever stiffness, stiffness of unfolded polypeptides, and stiffness of folded proteins decreases. Therefore, it is desirable to avoid pre-unfolded matrix proteins and to measure as close as possible to the surface.

2. To start, collect only a few (~3) unfolding/refolding cycles per molecule at slow velocities (~100 nm/s). The average time after which the protein detaches from cantilever tip or surface is the limiting factor. Try to increase the number of cycles. You can do more cycles if the cycle length is small or if you are measuring at higher velocities. Very often you have to discard the first cycles because they are overlaid by some additionally bound proteins which detach during the first cycles. 3. Check if you see the same unfolding/refolding event in the cycles using box smoothing at low velocities (~100 nm/s). Note that this becomes more and more difficult with increasing pulling velocity. Already at velocities of ~800 nm/s, the unfolding effect might be hard to identify (see Fig. 3c). Check if you find the expected contour length

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increase (see Subheading 3.2.3). If you do not observe a refolding event and no unfolding events in the following cycles, decrease the turning point position a to facilitate protein folding. 4. Check your instrument drift. You can do this by measuring the contour lengths of the polypeptide after your protein of interest has unfolded (L0 in Fig. 3a). This length should not change during the cycles. For illustration, different forward cycles are plotted in Fig. 3c. After protein unfolding, the forward cycles follow the gray WLC traces (gray shaded area) that are stacked in 20 pN steps for better comparison. 5. Average the forward and backward traces, respectively. Average the deflection vs. x0 signal rather than the force vs. extension signal to avoid averaging effects on the turning point positions. Alternatively, you can tilt the force vs. extension traces so that the noise gets vertical again for averaging. This should lead to traces as shown in Fig. 3d, which was measured on one single molecule. In Fig. 3d, the averaged forward trace is shown in black and the backward trace in gray. 6. Determine the area between unfolding and refolding traces, which tells you how far the system is away from thermodynamic equilibrium. If you are close to equilibrium (if the hysteresis is <10kBT), the equilibrium averaging method is rectified and you can use a model based on thermodynamic equilibrium (26) to describe your data. If the hysteresis is higher, try to decrease it by decreasing the pulling velocity. 7. Do the experiment with different pulling velocities (between 100 and 2,000 nm/s). 8. To further increase resolution, you can average different preaveraged traces gained from step 5 if they are comparable. Comparable means that they must have been measured under the same buffer conditions at the same pulling velocities and they must show the same unfolded polypeptide spacer (same absolute value for L0). 9. You can still use the averaging method for systems that are further away from equilibrium. However, it might be easier to determine, e.g., the unfolding force histograms directly from slowly pulled data than reconstructing it from the averaged traces (27). 10. To measure at very slow velocities (~1 nm/s), you might use NiNTA-coated surfaces in order to increase the time before detachment of protein from the surface occurs (23). Also in this regime, measurement drift gets the limiting factor; therefore, try to keep drift effects low, e.g., by using short light pathways of the detection system through the sample solution.

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4. Notes 1. The different approaches to construct polyproteins have different assets and drawbacks, which are summarized in the following table. Since some of them might not immediately work for your protein of interest, you should try different approaches in parallel. Approach

Using naturally occurring, already probed modular proteins as background (Subheading 3.1.1)

Advantages

Produces long chains of Produces long chains of Straight forward method polyproteins, allowing polyproteins allowing because the matrix protein for a quick collection of for a quick collection of is already known to be statistically relevant data statistically relevant data measurable with AFM The coiled-coil fingerprint Force can be applied in any The matrix protein can be wanted threecan be used to used as “gauge protein” dimensional direction determine the 0 force to determine parameters Can be used to determine very accurately such as daa (see structural information by Subheading 3.2.3) mechanical triangulation Allows to identify complex [15] unfolding pattern easily, e.g., for proteins showing many unfolding intermediate states [16]

Disadvantages Force application only in N-C-terminal direction The collection of statistical relevant data may be demanding because you get only one unfolding event per measured molecule

Constructing polyproteins Constructing polyproteins using coiled-coils using cysteine (Subheading 3.1.2) engineering (Subheading 3.1.3)

Force application only in Determination of linkage points may be N-C-terminal direction demanding when the Does not necessarily work protein structure is not for all proteins of known interest because of Does not necessarily work possible sterical for all proteins because hindrances [2] the reactivity of cysteines to form a disulfide bond may be low for some proteins

2. Alternative to the modular background protein ddFLN used in Subheading 3.1.1, you can take other naturally occurring modular proteins. For example, you can insert your protein of interest in the middle of the domains Ig27–Ig34 from the giant muscle protein titin. The domain boarders are given in (28) and the corresponding AFM experiments in (22). Because all proteins in the chain are in series and, therefore, simultaneously exerted to the mechanical force, the order in which the proteins unfold depends on their stability. If your protein is the weakest in the chain, it will likely unfold at the beginning of the force curve and this event might then often

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be masked by additional proteins that have bound in parallel. Therefore, it might be convenient to insert your protein of interest in a mechanically stable protein background (e.g., titin) as well as in a less stable background (e.g., ddFLN). You might also construct your own matrix protein with, e.g., the following order: 2 titin – 2 ddFLN – your protein of interest – 2 ddFLN – 2-titin. 3. When the persistence length p is held constant, the interpolation formula given in Subheading 3.2.3 only reproduces experimental data within a certain force regime very well. As mentioned above, a persistence length of 0.5 nm reproduces experimental data in the force regime between 50 and 150 pN. To fit data collected in the force regime between 150 and 300 pN, a persistence length of 0.35 nm can be used. For data measured in the low force regime (e.g., with Subheading 3.3.2) between 0 and 30 pN, a persistence length of 0.7 nm leads to good agreement. If you want to compare with very high precision (e.g., to get structural information) different contour length increases measured in different force regimes, you have to correct for this effect (15).

Acknowledgments We thank Hendrik Dietz for providing the data traces in Fig. 1c and i and for his major contribution to the protein engineering approaches in Subheadings 3.1.2 and 3.1.3. We also thank Morten Bertz, Michael Schlierf, Felix Berkemeier, Jan Philipp Junker, Roland Heym, Frauke Ko¨nig, and Ingo Schwaiger for their important help in developing the protein engineering approaches and the data analyzation methods. References 1. Carrion-Vazquez, M., Oberhauser, A.F., Fisher, T.E., Marszalek, P.E., Li, H., and Fernandez, J.M., (2000) Mechanical design of proteins studied by single-molecule force spectroscopy and protein engineering. Prog Biophys Mol Biol 74, 63–91. 2. Dietz, H., Bornschlo¨gl, T., Heym, R., Ko¨nig, F., and Rief, M., (2007) Programming protein self assembly with coiled coils. New J. Phys 9, 424. 3. Dietz, H., Bertz, M., Schlierf, M., Berkemeier, F., Bornschlo¨gl, T., Junker, J.P., and Rief, M., (2006) Cysteine engineering of polyproteins

for single-molecule force spectroscopy. Nat Protoc 1, 80–84. 4. Fucini, P., Koppel, B., Schleicher, M., Lustig, A., Holak, T.A., Muller, R., Stewart, M., and Noegel, A.A., (1999) Molecular architecture of the rod domain of the Dictyostelium gelation factor (ABP120). J Mol Biol 291, 1017–1023. 5. Bornschlogl, T., and Rief, M., (2006) Single molecule unzipping of coiled coils: sequence resolved stability profiles. Phys Rev Lett 96, 118102. 6. Zitzewitz, J.A., Ibarra-Molero, B., Fishel, D. R., Terry, K.L., and Matthews, C.R., (2000)

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Preformed secondary structure drives the association reaction of GCN4-p1, a model coiled-coil system. J Mol Biol 296, 1105–1116. 7. Lupas, A., Van Dyke, M., and Stock, J., (1991) Predicting coiled coils from protein sequences. Science 252, 1162–1164. 8. Berger, B., Wilson, D.B., Wolf, E., Tonchev, T., Milla, M., and Kim, P.S., (1995) Predicting coiled coils by use of pairwise residue correlations. Proc Natl Acad Sci U S A 92, 8259–8263. 9. Hutter, J.L., and Bechhoefer, J., (1993) Calibration of atomic-force microscope tips. Rev. Sci. Instrum. 64, 1868. 10. Butt, H.J., and Jaschke, M., (1995) Calculation of thermal noise in atomic force microscopy. Nanotechnology 6, 1. 11. Burnham, N.A., Chen, X., Hodges, C.S., Matei, G.A., Thoreson, E.J., Roberts, C.J., Davies, M.C., and Tendler, S.J.B., (2003) Comparison of calibration methods for atomic-force microscopy cantilevers. Nanotechnology 14, 1. 12. Walters, D.A., Cleveland, J.P., Thomson, N. H., Hansma, P.K., Wendman, M.A., Gurley, G., and Elings. V., (1996) Short cantilevers for atomic force microscopy. Rev. Sci. Instrum. 67, 3583. 13. Dietz, H., and Rief, M., (2007) Detecting molecular fingerprints in single molecule force spectroscopy using pattern recognition. Jap J Appl Phys 46-8B, 5540. 14. Bustamante, C., Marko, J.F., Siggia, E.D., and Smith, S., (1994) Entropic elasticity of lambda-phage DNA. Science 265, 1599–1600. 15. Dietz, H., and Rief, M., (2006) Protein structure by mechanical triangulation. Proc Natl Acad Sci U S A 103, 1244–1247. 16. Bertz, M., and Rief, M., (2008) Mechanical unfoldons as building blocks of maltose-binding protein. J Mol Biol 378, 447–458. 17. Schwaiger, I., Schleicher, M., Noegel, A.A., and Rief, M., (2005) The folding pathway of a fast-folding immunoglobulin domain revealed by single-molecule mechanical experiments. EMBO Rep 6, 46–51. 18. Izrailev, S., Stepaniants, S., Balsera, M., Oono, Y., and Schulten, K., (1997) Molecular dynamics study of unbinding of the avidinbiotin complex. Biophys J 72, 1568–1581. 19. Rounsevell, R., Forman, J.R., and Clarke, J., (2004) Atomic force microscopy: mechanical unfolding of proteins. Methods 34, 100–111.

20. Fernandez, J.M., and Li, H., (2004) Forceclamp spectroscopy monitors the folding trajectory of a single protein. Science 303, 1674–1678. 21. Schlierf, M., Berkemeier, F., and Rief, M., (2007) Direct observation of active protein folding using lock-in force spectroscopy. Biophys J 93, 3989–3998. 22. Rief, M., Gautel, M., Oesterhelt, F., Fernandez, J.M., and Gaub, H.E., (1997) Reversible unfolding of individual titin immunoglobulin domains by AFM. Science 276, 1109–1112. 23. Junker, J.P., Ziegler, F., and Rief, M., (2009) Ligand-dependent equilibrium fluctuations of single calmodulin molecules. Science 323, 633–637. 24. Lee, G., Abdi, K., Jiang, Y., Michaely, P., Bennett, V., and Marszalek, P.E., (2006) Nanospring behaviour of ankyrin repeats. Nature 440, 246–249. 25. Bustamante, C., Macosko, J.C., and Wuite, G. J., (2000) Grabbing the cat by the tail: manipulating molecules one by one. Nat Rev Mol Cell Biol 1, 130–136. 26. Tinoco, I., Jr., and Bustamante, C., (2002) The effect of force on thermodynamics and kinetics of single molecule reactions. Biophys Chem 101–102, 513–533. 27. Bornschlogl, T., and Rief, M., (2008) Singlemolecule dynamics of mechanical coiled-coil unzipping. Langmuir 24, 1338–1342. 28. Politou, A.S., Gautel, M., Improta, S., Vangelista, L., and Pastore, A., (1996) The elastic I-band region of titin is assembled in a “modular” fashion by weakly interacting Ig-like domains. J Mol Biol 255, 604–616. 29. Borgia, A., Williams, P.M., and Clarke, J., (2008) Single-molecule studies of protein folding. Annu Rev Biochem 77, 101–125. 30. Linke, W.A., and Grutzner, A., (2008) Pulling single molecules of titin by AFM–recent advances and physiological implications. Pflugers Arch 456, 101–115. 31. Zhuang, X., and Rief, M., (2003) Single-molecule folding. Curr Opin Struct Biol 13, 88–97. 32. Clausen-Schaumann, H., Seitz, M., Krautbauer, R., and Gaub, H.E., (2000) Force spectroscopy with single bio-molecules. Curr Opin Chem Biol 4, 524–530. 33. Oberhauser, A.F., and Carrion-Vazquez, M., (2008) Mechanical biochemistry of proteins one molecule at a time. J Biol Chem 283, 6617–6621.

Chapter 14 How to Perform a Nanoindentation Experiment on a Virus Wouter H. Roos Abstract To broaden our knowledge on virus structure and function, a profound insight into their mechanical properties is required. Nanoindentation measurements with an atomic force microscope (AFM) are increasingly being performed to probe such material properties. This single-particle approach allows for determining the viral spring constant, their Young’s modulus, as well as the force and deformation at which failure occurs. The experimental procedures for viral nanoindentation experiments are described here in detail, focusing on surface preparation, AFM imaging and nanoindentation, and the subsequent data analysis of the force–distance curves. Whereas AFM can be operated in air and in liquid, the described methods are for probing single viruses in liquid to enable working in a physiologically relevant environment. Key words: Virus, Viral structure, Bacteriophage, Capsid, Atomic force microscopy, Nanoindentation, Force spectroscopy, Mechanical properties, Materials science, Biophysics

1. Introduction Knowledge of the mechanical properties of viruses is an essential part in obtaining a complete overview of viral life cycles. This is, for instance, apparent from experiments showing that (1) virus stiffness of certain retroviruses is correlated with infectivity (1), (2) capsid strength is governing the maximum packaged genome length of bacteriophages (2), and (3) stabilisation of herpes simplex virus capsids is triggered by scaffold expulsion and DNA packaging (3). Since the landmark paper by Ivanovska et al. (4) in 2004 describing nanoindentation measurements on bacteriophage F29, the mechanical properties of a range of viral particles have been probed by atomic force microscopy nanoindentation. Viral nanoindentation is a single-particle technique based on atomic force microscope (AFM) imaging and force spectroscopy, which are techniques often used in single-molecule approaches.

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_14, # Springer Science+Business Media, LLC 2011

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Fig. 1. Nanoindentation experiment on a viral particle. (a–c) Schematic of an AFM nanoindentation experiment and (d–f) the corresponding force indentation curves. During imaging, the piezo scanner moves in the x, y, and z direction, but during the nanoindentation experiment only in z. Initially, there is no contact between virus and cantilever while moving the sample up, thus the force on the cantilever is zero (a and d). Moving it further up, the cantilever touches the virus and starts to deflect, thereby changing the signal on the quadrant photodiode (b and e). This is the linear, reversible indentation regime. Moving it even further increases the deflection of the cantilever (as well as the indentation of the virus) and the depicted virus breaks (c and f). This is the irreversible indentation regime. The laser beam path and the cantilever in the undeflected state (a) are shown respectively as a dashed line and a light grey tone in b and c. The liquid, in which the virus and cantilever are immersed, is omitted in the schematic for reasons of simplicity.

When using AFM to probe viral material properties, the viruses need first to be immobilised on a surface. As a next step, a single virus is imaged to determine its centre and finally the particle is indented. While indenting, a force–distance (FZ) curve is recorded from which the mechanical properties of the particle are determined. Figure 1 shows a schematic diagram of a nanoindentation experiment. The material properties of viruses are recently reviewed in refs. 5, 6. Here, I will discuss in detail the experimental procedures for performing viral nanoindentation experiments. To ensure a physiologically relevant environment, the described methods are for AFM nanoindentation experiments in liquid.

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2. Materials 2.1. Surface Preparation

1. Glass coverslips. 2. KOH solution (1.5 M final concentration) in 1 part of deionised water and 9 parts of ethanol; make fresh as required. 3. Hexamethyldisilazane (HMDS). 4. Glass container with lid. 5. Parafilm.

2.2. Nanoindentation

1. Hydrophobic glass coverslips. 2. Atomic force microscope. 3. Cantilevers. 4. Chloroform to clean dirty cantilever tips. 5. Stock solution with viral particles. 6. Buffer solution to dilute the viral particles (depends on the used virus).

2.3. Analysis of Nanoindentation Results

1. AFM software for visualisation and height determination. 2. Graphing and curve fitting software.

3. Methods As mentioned above, the described procedures are for probing the material properties of viruses in liquid, whereby the viral particles are continuously immersed in liquid/buffer solution to ensure a physiologically relevant environment. The three major steps in viral nanoindentation are discussed here in detail: (1) Glass coverslips are coated with an alkyl silane to make them hydrophobic. (2) These surfaces are used to adhere viral particles in liquid and to perform the nanoindentation measurements (see Fig. 1). (3) Finally, the data are analysed whereby linear as well as nonlinear deformation is discussed. 3.1. Surface Preparation ( See Note 1)

It is advised to work under the fume hood of a chemistry lab (see Note 2) and to wear proper protection (lab coat, goggles, gloves etc.). KOH solutions and HMDS are dangerous because of their corrosive nature. HMDS is furthermore very volatile and both solutions should only be used under the fume hood.

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1. Take glass coverslips with the proper size for the AFM measurements. 2. Immerse the coverslips in the KOH solution and leave for 15 h. This procedure etches the surface of the glass coverslip, making them hydrophilic (see Notes 3 and 4). 3. Lift the coverslips out of the KOH bath and remove the KOH solution from the coverslips by rinsing them one by one with deionised water. 4. Blow dry the coverslips with a gentle stream of nitrogen (see Note 5). 5. Place the coverslips in a clean and dry container. 6. Add ~1 ml of HMDS into the container, close the container, and seal with parafilm. Leave it for 15 h. Take care that the HMDS is not touching the coverslips (by putting the coverslips on an elevation, for instance) (see Note 6). 7. Remove the lid of the container (still under the fume hood) and leave the container open to let the HMDS completely evaporate. 8. The hydrophobic glass coverslips are now ready to use (see Notes 7 and 8). 3.2. Nanoindentation

1. Select the AFM imaging mode. It is important to minimise the force applied to your sample to reduce the chances of damaging the (generally) fragile viruses while imaging. The two most widely used modes for virus imaging, in combination with nanoindentation measurements, are tapping mode (7, 8) and jumping mode AFM (9) (see Note 9). These modes are much less invasive than contact mode imaging. 2. Select a cantilever. The cantilever spring constant should be comparable to that of the studied viral particles. Preferably, the cantilever has a bit smaller, rather than larger, spring constant to reduce damage to the viruses. Rectangular cantilevers with a spring constant of ~0.05 N/m and a nominal tip radius of ~20 nm have been used for nanoindentation experiments on a variety of prokaryotic and eukaryotic viruses (2–4, 10–14). 3. Determine the spring constant of your cantilever. Even though manufacturers normally supply the approximate spring constant of their cantilevers, it is always advisable to calibrate them yourselves. It is beyond the scope of this chapter to discuss all calibration methods. A calibration method used for several virus nanoindentation studies is described in ref. 15 (see also Note 10).

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4. Incubate the viral particles (see Note 11) for ~20 min on the hydrophobic glass coverslips (see Note 12 on the particle concentration). When a minimum volume of 200 ml is used, one can generally measure for a few hours without too much evaporation of the buffer solution (see Note 13). 5. Approach the cantilever to start the measurement (see Notes 14 and 15). 6. To check whether the cantilever responds linearly to deformation and to calibrate the system, a force–distance (FZ) curve on the glass needs to be performed. To do this, just look for a clean place in between the viral particles. You need to have a linear response on the glass, otherwise clean or replace your cantilever. 7. Before starting the nanoindentation measurements, the particles need to be imaged first to ensure that they have the proper shape and height (otherwise, it is likely that they are broken or have dirt attached to them) (see Fig. 2a and Note 16). This is generally just a rough check; a more accurate analysis will be performed during data analysis (Subheading 3.3, step 1). Set the imaging parameters to ensure a proper balance between high resolution imaging on one hand and gentle imaging on the other. The former allows for imaging surface substructures such as viral capsomeres (Fig. 2). The latter is essential as well, otherwise you might have already broken the particles before you started your nanoindentation measurement (see also Subheading 3.2, step 1). 8. After imaging, the tip is directed to the middle of the viral particle and a FZ curve is recorded (Figs. 1 and 3). Loading (or forward) and unloading (or backward) curves can be recorded and by pushing several times in a row, one can observe whether there is a change in response after one or multiple indentations.

Fig. 2. Viral imaging and nanoindentation. Capsid before (a) and after (b) indentation. The corresponding cross-sections in (c) show the profile of the capsomeres before indentation and the hole after indentation. The white arrows in (a, b) depict the line along which the cross-sections are taken. The shape of the hole reflects the shape of the AFM tip. Reproduced with permission from ref. 3.

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Fig. 3. Two ways of representing the same FZ curve data. (a) In this “classical” form, the piezo height is depicted on the x-axis and the FZ glass curve is shifted laterally to have the contact point coincide with the contact point of the FZ virus curve. The indentation of the virus is the difference between the FZ glass and the FZ virus curve. The point where the particle breaks (failure) is marked. The first, second, and third time pushing (FZ 1 Loading, FZ 2 Loading, and FZ 3 Loading) as well as the unloading curve after the first time indenting (FZ 1 Unloading) are shown. The conclusion that the particle is broken can be inferred from (1) the drop in the force around 2 nN, (2) the large hysteresis between loading and unloading curves, and (3) the fact that the subsequent indentation curves (FZ 2 & 3) do not fall onto FZ 1, but start to go up at a much higher Z displacement. (b) The force is here directly plotted as a function of the indentation. The x-axis depicts the difference between the FZ glass and FZ virus curves (denoted as indentation in (a)). The subtle nonlinearities in the beginning of the FZ 1 curve in (a) are now much better visualised. Furthermore, one can notice that all FZ curves show an incompressible behaviour at the end of indentation. This indicates that one is pushing on the glass. Likely there is still some protein between the tip and the glass (probably one or two shell thicknesses), because FZ 2 & 3 do not rise sharply around 55 nm. It seems that for these indentations a bit of protein is first indented, before an incompressible behaviour is recorded.

9. Image your particle again after the nanoindentation, to see whether the shape and/or height has changed. Figure 2 clearly shows how a particle can be permanently deformed after nanoindentation. 10. Perform again a FZ curve on the glass to assure that your cantilever still shows a linear deformation behaviour with the same slope as before the imaging and nanoindentation of your viral particle (see Note 17). 3.3. Analysis of Nanoindentation Results

1. One starts with determining the diameter of the imaged particles. As already mentioned in Note 16, the convolution of the tip with the substrate leads to an overestimation of the lateral widths. However, the height above the surface is a reliable parameter. Therefore, one measures the maximum height of the particle, to determine the particle diameter (Fig. 2c). When this height is far from what you expect, it is likely that the particle is either broken or has dirt on it, or is not one but rather a cluster of multiple particles or is not a viral particle at all (see also Subheading 3.3, step 8, and Note 18).

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2. When you are confident that the imaged particle is indeed one complete viral particle, you start to analyse the FZ curves. The FZ glass curve is needed to calibrate the signal on the quadrant photodiode. Generally, the units in which the FZ glass curve is recorded are (nano)metres on the x-axis and Volt on the y-axis. Determine the slope of the FZ glass curve SlopeFZglass and divide the cantilever spring constant kcantilever by this slope: kcantilever ½N =m ¼ ConvFact[N =V  SlopeFZglass ½V =m

(1)

This gives you the conversion factor ConvFact to transform the quadrant photodiode signal in Volt to a signal in Newton. 3. Multiply the values on the y-axis of the FZ glass and FZ virus curves with ConvFact to depict the forces in Newton instead of Volt. 4. Now the FZ curves on the virus are analysed. There are two different ways of plotting your data. One can plot it together with the FZ glass curve with the piezo vertical displacement on the x-axis (Fig. 3a). Alternatively, one can plot it without the FZ glass curve with the actual indentation of the particle on the x-axis (Fig. 3b). The latter method has the advantage that subtle nonlinearities are more easily discerned from the FZ curves and that the FZ glass is removed, a parameter in which we are generally not really interested (of course, it is needed for calibration purposes, but does not necessarily need to be plotted). One can opt for the former method when one wants to represent the data in a more raw data format, close to how it is recorded (see Note 19). 5. In case the initial indentation behaviour is linear (Fig. 1e and f), one can deduce the spring constant of the virus kvirus from the slope of the initial linear part. If the initial indentation behaviour is nonlinear, as in Fig. 3, one cannot accurately determine a viral spring constant from the graphs. In this case, it is an option to resort to nonlinear (finite element) simulations – performed on realistic capsid models – to determine the viral material properties (16, 17). However, in a first-order approximation, one can deduce a spring constant of nonlinearly deformed viruses by taking the averaged slope between the contact point and the point of failure. When one represents the data as in Figs. 1e, f and 3b, one can directly read out the (approximate) spring constant from the curve. However, while representing the data as in Fig. 3a, one cannot directly read out the spring constant from the graph. The initial part of the FZ 1 loading curve in Fig. 3a represents, namely, the combined spring constant ktotal of the cantilever–virus system.

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Therefore, one needs to use Hooke’s law for two springs in series to determine kvirus: kvirus ¼

ktotal  kcantilever kcantilever  ktotal

(2)

6. After determining kvirus, one can express the material properties of the studied viral particle in terms of Young’s modulus of their shell. This allows for comparing viruses with different dimensions to each other. As above, one can compare the indentation curves with finite element simulations of nanoindentation experiments, in order to obtain Young’s modulus (see Note 20). However, for sphere-like particles of which the dimensions are known, one can also obtain an estimate of Young’s modulus by using a thin shell model (18). For various viral particles, Young’s modulus E has been estimated using the following simple equation (3, 4, 10, 12). kvirus ¼

aEh 2 R

(3)

with the shell thickness h and the particle radius R. For the proportionality factor a, a value of 1 turns out to be a reasonable approximation for various capsids (4, 10, 16). 7. Next to the spring constant and Young’s modulus, the breaking force (force at which failure occurs) and the indentation at breaking can be extracted from the FZ curves. This will give us in total four, partially related parameters with which we can describe the mechanical properties of viral particles. It allows for comparison between the material properties of various viruses to discern similarities and differences (see, e.g. refs. 6, 19). 8. The measured height Heightmeasured, as described in Subheading 3.3, step 1, is generally an underestimation of the actual particle height. The reason for this is that during imaging, one taps gently on the surface leading to a small indentation of soft surfaces like viruses. Whereas for tapping mode imaging, it is not always clear how much force exactly one exerts on the surface; for jumping mode imaging, this force is easily controllable and can be extracted from the imaging parameters. The viral spring constant (determined in Subheading 3.3, step 5) together with the imaging force Fimaging can now be used to determine the actual particle height Heightreal

Heightreal ¼ Heightmeasured þ

Fimaging kvirus

(4)

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9. Average the data of all your measurements to get estimates, also accounting the error (see Note 21), of the material properties of the viral particle you are studying.

4. Notes 1. The described surface preparation method follows essentially the steps described in ref. 4, but with much more detail. 2. In general, it is not necessary to perform the surface preparation in a clean room. A normal, clean chemistry laboratory with not too many people working at the same time will usually be OK. However, if it turns out that you have too much dirt on your samples, consider moving to a clean room for the surface preparation. 3. Even though the glass coverslips are cleaned by the KOH solution, it is advisable to perform a “pre-cleaning” step of the coverslips. For instance, (1) clean the coverslips for 30 min in a plasma etcher, or (2) remove the dirt (left from the glass production process) by wiping the coverslips one by one with a lint-free, clean tissue, or (3) immerse the coverslips in isopropanol and put them into a sonication bath for 10 min and repeat this treatment 3 times with a clean isopropanol solution. 4. To hold the glass coverslips in place, one can use a teflon holder (fabricated by yourselves, or a mechanical workshop) in which one can put the coverslips, lined up vertically next to each other. This will allow you to do batch processing relatively easily. 5. Instead of blow drying, one can also leave the coverslips at a place with little dust but a good ventilation (in the clean fume hood of a clean laboratory, for instance), to dry by themselves. This will save you laboratory time; however, you have to wait longer and there is more chance of dust particles adhering to your surfaces. Vacuum drying is possible as well. Drying in an oven should be considered carefully, as dirt particles from inside the oven could attach to the coverslips. 6. The volume of the added HMDS should be such that after 15 h, there is still a bit of liquid HMDS left, ensuring that the coverslips were in a saturated vapour pressure of HMDS all the time. 7. To check the cleanliness of your prepared glass surfaces, you can image several of them in deionised water. Glass coverslips generally have a roughness of a few nanometre and you should

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not see more than 1 dust or dirt particle per approximately 55 mm. 8. Next to hydrophobic glass coverslips (used in refs. 1–4, 10–14, 20, 21), other surfaces have also been used to immobilise viral particles for nanoindentation studies. Herpes simplex virus capsids were, besides immobilisation on hydrophobic glass coverslips (3), also immobilised on poly-lysine-coated mica (22): Incubate a 0.01% poly-L-lysine solution on freshly cleaved mica for 15 min. The surface is ready for use after a brief rinse with deionised water and air drying. Freshly cleaved mica was used to deposit tobacco mosaic virus (23); however, murine leukaemia virus particles were deformed when deposited on freshly cleaved mica that was pretreated with 20 mM MnCl2 (20). In an approach where human rhinoviruses were imaged to study genome release, these viruses were absorbed on freshly cleaved mica in the presence of 5 mM NiCl2 (24). The reported height of these particles was close to the stated literature values. These two examples of immobilising viruses on mica in the presence of divalent cations show that sometimes particles are significantly deformed, and sometimes they are not. So always carefully check whether the particles retain their original shape, after adhering to the surface. 9. For jumping mode imaging of viruses (implemented on Nanotec AFMs, Madrid, Spain; see, for instance, ref. 2–4, 10–14), the maximum force applied to the viruses while imaging can be easily set. Depending on the size and stiffness of the particle, the maximum force applied while imaging is generally between 50 and 300 pN. For tapping mode imaging (implemented on a wide variety of commercial AFMs; see, for instance, refs. 1, 20, 22), this maximum force is not easily defined. Xu et al. (25) examined the peak forces exerted to viruses while imaging in tapping mode and they showed how it is possible to control the damage to the capsids by properly choosing the cantilever and setting the AFM imaging parameters. 10. Please consult, for instance, ref. 26 for further reading on cantilever calibration methods, if needed. 11. It is very important to have a high purity of your viral particles with as little broken capsids and other, non-viral material as possible in there. This for various reasons: (1) The AFM cantilever is prone to collect dirt as it touches the surfaces repeatedly while scanning. You do not want to have to change your tip continuously because it became dirty. (2) Whereas with electron microscopy imaging, you can quickly move from a “bad” place on the sample to a “good” place; this is not the case with AFM. For AFM imaging, it takes a lot of

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time to scan different areas on your surface, so the first place where you start imaging should have a nice collection of intact viral particles without dirt lying around. This implies, as you never know where exactly you will start imaging, that the whole sample should consist of “perfect particles” without dirt. 12. An ideal particle concentration is a few attached particles per 11 mm of surface area. In this way, you do not have to search very long to find a particle and the chance of having several particles lying next to each other (which will make it difficult to ascertain that the particle is not broken and does not have dirt attached to it) is not too high. Some guidelines from the literature: (1) A stock solution of bacteriophage F29 proheads at a 6 mg/ml concentration was diluted 100-fold before starting nanoindentation measurements (4). (2) Experiments on phage l were performed by diluting from stock that had a concentration of 1012 virions per ml (2). (3) Capsids of hepatitis B virus (HBV) were applied to the surface at a 4.2 mM concentration of capsid protein (12). (The T ¼ 3 and T ¼ 4 HBV capsids are made up from respectively 180 and 240 copies of capsid protein). 13. To reduce the amount of protein needed, one can incubate a smaller volume of viruses (20–50 ml) and add buffer after the 20-min incubation time to fill it up to 200 ml. 14. Before starting the measurements, it is an option to rinse the surface, onto which the viral particles are attached, with buffer. This will wash away unbound and poorly bound particles. Take care to not let the surface dry out while rinsing, as this will denature your proteins. 15. You can pre-wet the (mounted) cantilever with 20 ml of buffer solution before placing the cantilever holder + cantilever above your sample (11). This can give a reduced chance of trapping air bubbles between the cantilever and the cantilever holder while approaching and immersing into the sample solution. 16. Due to the convolution of the AFM tip and the substrate (i.e. virus), you will overestimate the width of the particle when you measure this from your recorded image. Unless you have calibrated the tip shape, you cannot get accurate particle sizes from the lateral dimensions in your image. Therefore, one should look at the height of the particle (see also Subheading 3.3, step 1, and Fig. 2c). 17. When the FZ glass curve is not linear anymore, you probably picked up some dirt. As it is generally not possible to say whether you picked up the dirt before the virus nanoindentation or during the virus nanoindentation (the particles often break and some protein can then attach to the tip), you have

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to discard these data points and clean/replace your tip to continue measuring. When the slope of your FZ glass curve has changed, there could be some drift in the laser alignment. In this case, you also have to discard your data (as you do not know with which of the FZ glass curves you have to compare your FZ virus curve). 18. For many regularly studied viruses, their (approximate) diameter is known from (cryo)-electron microscopy or x-ray crystallography. Especially high resolution reconstructions give an accurate size of the viral particles and one can compare the measured size from AFM (corrected for the indentation during imaging, see Subheading 3.3, step 8) to the literature values. 19. Note that throughout the text both the force–displacement curves (Fig. 3a) and the force–indentation curves (Fig. 3b) are denoted by FZ curve, where Z, respectively stands for the distance the piezo has moved and the distance the tip has moved while deforming the virus. 20. To get a profound insight into the material properties of viruses, the experimental nanoindentation results can be compared to simulations and theoretical models. For more information on general modelling approaches of viral particles and on specific modelling approaches of viral nanoindentation, please see refs. 27 and 19 respectively. 21. Data from biophysical single-molecule and single-particle experiments commonly show a big spread, as is also the case for viral nanoindentation experiments. This is inherent to the studied system and originates from the biological variation in the material. Furthermore, while studying icosahedral particles, the spread in data can be enhanced due to the different symmetry axes along which the particle can be indented (11). Care should be taken to gather enough data to have reliable statistics. As usual with statistics, it is not clearly defined what “enough” is; published data show a varying number of measurements N from ~20 to 100, depending on the studied system. Because of the inherent biological variation, the standard deviation (SD), as a measure for the error in your data, will stabilise after reaching a critical number of measurements and will not go down anymore for a further increase in N. However, one does get a better estimate of the average when one performs more measurements. To account for the number of recorded measurements, the standard error of the mean (SEM ¼ SD/√N) can be used as a measure for the error in the data.

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Acknowledgments I would like to thank G.J.L. Wuite and I. Ivanovska for introducing me to the experimental nanoindentation technique and analysis tools. M. Baclayon is thanked for critical reading of the manuscript. References 1. Kol, N., Shi, Y., Tsvitov, M., Barlam, D., Shneck, R. Z., Kay, M. S., and Rousso, I. (2007) A stiffness switch in human immunodeficiency virus, Biophys J 92, 1777–83. 2. Ivanovska, I., Wuite, G., Jonsson, B., and Evilevitch, A. (2007) Internal DNA pressure modifies stability of WT phage, Proc Natl Acad Sci USA 104, 9603–8. 3. Roos, W. H., Radtke, K., Kniesmeijer, E., Geertsema, H., Sodeik, B., and Wuite, G. J. (2009) Scaffold expulsion and genome packaging trigger stabilization of herpes simplex virus capsids, Proc Natl Acad Sci USA 106, 9673–8. 4. Ivanovska, I. L., de Pablo, P. J., Ibarra, B., Sgalari, G., MacKintosh, F. C., Carrascosa, J. L., Schmidt, C. F., and Wuite, G. J. L. (2004) Bacteriophage capsids: Tough nanoshells with complex elastic properties, Proc Natl Acad Sci USA 101, 7600–5. 5. Roos, W. H., Ivanovska, I. L., Evilevitch, A., and Wuite, G. J. L. (2007) Viral capsids: Mechanical characteristics, genome packaging and delivery mechanisms, Cell Mol Life Sci 64, 1484–97. 6. Roos, W. H., and Wuite, G. J. L. (2009) Nanoindentation studies reveal material properties of viruses, Adv Mater 21, 1187–92. 7. Hansma, P. K., Cleveland, J. P., Radmacher, M., Walters, D. A., Hillner, P. E., Bezanilla, M., Fritz, M., Vie, D., Hansma, H. G., Prater, C. B., Massie, J., Fukunaga, L., Gurley, J., and Elings, V. (1994) Tapping Mode AtomicForce Microscopy in Liquids, Appl Phys Lett 64, 1738–40. 8. Putman, C. A. J., Vanderwerf, K. O., Degrooth, B. G., Vanhulst, N. F., and Greve, J. (1994) Tapping Mode AtomicForce Microscopy In Liquid, Appl Phys Lett 64, 2454–6. 9. de Pablo, P. J., Colchero, J., Gomez-Herrero, J., and Baro, A. M. (1998) Jumping mode scanning force microscopy, Appl Phys Lett 73, 3300–2.

10. Michel, J. P., Ivanovska, I. L., Gibbons, M. M., Klug, W. S., Knobler, C. M., Wuite, G. J. L., and Schmidt, C. F. (2006) Nanoindentation studies of full and empty viral capsids and the effects of capsid protein mutations on elasticity and strength, Proc Natl Acad Sci USA 103, 6184–9. 11. Carrasco, C., Carreira, A., Schaap, I. A. T., Serena, P. A., Gomez-Herrero, J., Mateu, M. G., and Pablo, P. J. (2006) DNA-mediated anisotropic mechanical reinforcement of a virus, Proc Natl Acad Sci USA 103, 13706–11. 12. Uetrecht, C., Versluis, C., Watts, N. R., Roos, W. H., Wuite, G. J., Wingfield, P. T., Steven, A. C., and Heck, A. J. (2008) High-resolution mass spectrometry of viral assemblies: Molecular composition and stability of dimorphic hepatitis B virus capsids, Proc Natl Acad Sci USA 105, 9216–20. 13. Carrasco, C., Castellanos, M., de Pablo, P. J., and Mateu, M. G. (2008) Manipulation of the mechanical properties of a virus by protein engineering, Proc Natl Acad Sci USA 105, 4150–5. 14. Arkhipov, A., Roos, W. H., Wuite, G. J., and Schulten, K. (2009) Elucidating the mechanism behind irreversible deformation of viral capsids, Biophys J 97, 2061–9. 15. Sader, J. E., Chon, J. W. M., and Mulvaney, P. (1999) Calibration of rectangular atomic force microscope cantilevers, Rev Sci Instrum 70, 3967–9. 16. Gibbons, M. M., and Klug, W. S. (2007) Nonlinear finite-element analysis of nanoindentation of viral capsids, Phys Rev E 75, 031901. 17. Gibbons, M. M., and Klug, W. S. (2008) Influence of nonuniform geometry on nanoindentation of viral capsids, Biophys J 95, 3640–9. 18. Landau, L. D., and Lifshitz, E. M. (1986) Theory of Elasticity, 3rd ed., Elsevier, Oxford. 19. Baclayon, M., Wuite, G. J. L., and Roos, W. H. (2010) Imaging and manipulation of single

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viruses by atomic force microscopy, Soft Matter 6, 5273–85. 20. Kol, N., Gladnikoff, M., Barlam, D., Shneck, R. Z., Rein, A., and Rousso, I. (2006) Mechanical properties of murine leukemia virus particles: Effect of maturation, Biophys J 91, 767–74. 21. Klug, W. S., Bruinsma, R. F., Michel, J. P., Knobler, C. M., Ivanovska, I. L., Schmidt, C. F., and Wuite, G. J. L. (2006) Failure of viral shells, Phys Rev Lett 97, 228101. 22. Liashkovich, I., Hafezi, W., Kuhn, J. E., Oberleithner, H., Kramer, A., and Shahin, V. (2008) Exceptional mechanical and structural stability of HSV-1 unveiled with fluid atomic force microscopy, J Cell Sci 121, 2287–92. 23. Zhao, Y., Ge, Z. B., and Fang, J. Y. (2008) Elastic modulus of viral nanotubes, Phys Rev E 78, 031914.

24. Kienberger, F., Zhu, R., Moser, R., Blaas, D., and Hinterdorfer, P. (2004) Monitoring RNA release from human rhinovirus by dynamic force microscopy, J Virol 78, 3203–9. 25. Xu, X., Carrasco, C., de Pablo, P. J., GomezHerrero, J., and Raman, A. (2008) Unmasking imaging forces on soft biological samples in liquids when using dynamic atomic force microscopy: A case study on viral capsids, Biophys J 95, 2520–8. 26. Butt, H. J., Cappella, B., and Kappl, M. (2005) Force measurements with the atomic force microscope: Technique, interpretation and applications, Surface Science Reports 59, 1–152. 27. Gibbons, M. M., and Klug, W. S. (2007) Mechanical modeling of viral capsids, J Mater Sci 42, 8995–9004.

Chapter 15 Magnetic Tweezers for Single-Molecule Manipulation Yeonee Seol and Keir C. Neuman Abstract Magnetic tweezers provide a versatile tool enabling the application of force and torque on individual biomolecules. Magnetic tweezers are uniquely suited to the study of DNA topology and protein–DNA interactions that modify DNA topology. Perhaps due to its presumed simplicity, magnetic tweezers instrumentation has been described in less detail than comparable techniques. Here, we provide a comprehensive description and guide for the design and implementation of a magnetic tweezers instrument for single-molecule measurements of DNA topology and mechanics. We elucidate magnetic trap design, as well as microscope and illumination setup, and provide a simple LabVIEW-based real-time position tracking algorithm. In addition, we provide procedures for production of supercoilable DNA tethers, flow-cell design, and construction tips. Key words: Magnetic tweezers, Image tracking, DNA, Topology, Single molecule

1. Introduction Single-molecule force spectroscopy has emerged as a powerful tool to investigate the mechanical properties of biomolecules (1). Among the common force spectroscopy techniques, including optical tweezers and atomic force microscopy, magnetic tweezers are versatile and technically the simplest to implement. Furthermore, magnetic tweezers naturally afford passive force clamping and provide a simple means to precisely control the rotation of individual particles, features that are cumbersome to achieve with other techniques. A typical magnetic tweezers instrument is capable of applying forces ranging from a few femtonewtons (10
15 N) to hundreds of piconewtons (10
12 N) and can measure the three-dimensional position of a magnetic particle with an accuracy of a few nm (10
9 m) at a sample rate

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_15, # Springer Science+Business Media, LLC 2011

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of ~100 Hz. Magnetic tweezers can be implemented with either permanent magnets (2, 3) or electromagnets (4). In the simplest configuration, a pair of permanent magnets is placed above a flow-cell on the stage of an inverted microscope, and particle tracking software is used to obtain the three-dimensional position of the magnetic particle from images acquired with a CCD camera. The magnets are separated by a small distance with their opposite poles facing each other. In this configuration, the magnetic field decreases exponentially with distance from the magnets and generates a field gradient along the axial direction. A magnetic particle in the flow-cell experiences an axial force along the direction of the field gradient, and its magnetic moment aligns with the external field. Force is controlled by changing the height of the magnets relative to the flow-cell. Torque can be applied on rotationally constrained biomolecules attached at multiple points to both the surface of the flow-cell and the magnetic particle. For example, a DNA molecule anchored at one end to a surface and the other end attached to a superparamagnetic bead can be supercoiled by rotating the magnets. Magnetic tweezers have been used to study the mechanical properties of nucleic acids and nucleic acid–protein interactions (3, 5–7). Moreover, the technique is well suited for the study of topoisomerases (5–9), since the topology of rotationally constrained DNA molecules can be precisely manipulated and measured. This chapter provides instructions for implementing magnetic tweezers and methods for constructing rotationally constrained (“coilable”) DNA molecules and flow-cells for single-molecule experiments. We highly recommend two recent book chapters (2, 10) that are excellent general references and cover theoretical aspects of magnetic tweezers.

2. Materials 2.1. Coilable DNA Substrate Preparation 2.1.1. PCR Reaction

1. PCR templates. pET28a plasmid (EMD4Biosciences) pBluescript II KS plasmid (Stratagene) 2. PCR primers (Operon). pET28a forward: GGACCTGCTTTCCAACAGTCAGAGG TGGCGAAACCC pET28a reverse: GGGTCTCGACCA-TACACTCCGCTAT CGCTACG

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pBluescript II KS forward: GGACCTGCTTTCGTTGTGG CGTAATCATGGTCATAG pBluescript II KS reverse: GGGTCTCGTGGTTTATAGTC CTGTCGGGTTTC 3. Phusion DNA polymerase (F-530S, Finnzymes) and Taq DNA polymerase (M2073, New England Biolabs). 4. 5 Phusion buffer (F-519, Finnzymes) and 10 Taq standard buffer (New England Biolabs). 5. dNTPs (10 mM, Roche). 6. Biotin-16-dUTP (11093070910, Roche). 7. Digoxigenin-11-dUTP (11093088910, Roche). 8. Thermocycler (Eppendorf). 9. PCR cleanup kit (QIAquick PCR purification kit, Qiagen). 2.1.2. Restriction Enzyme Digestion

1. BsaI (New England Biolabs). 2. BfuAI (New England Biolabs). 3. 10 Buffer 3 (New England Biolabs). 4. pET28a and pBluescript II KS PCR products.

2.1.3. DNA Ligation

1. T4 DNA ligase (New England Biolabs). 2. 10 T4 DNA ligase buffer (New England Biolabs). 3. Products from restriction enzyme digestions.

2.1.4. DNA Tethering

1. Anti-digoxigenin, polyclonal (11333089001, Roche). 2. 10 PBS (P7059, Sigma). 3. DNA ligation products. 4. Bovine serum albumin (BSA) (A3059, Sigma). 5. Tween-20 (P9416, Sigma). 6. Magnetic beads (Dynabeads MyOne Streptavidin T1; 35601, Invitrogen).

2.2. Sample Cell/ Surface Treatment

1. #1½ cover glass (24 mm  60 mm, Corning). 2. #1 cover glass (22 mm  40 mm, VWR). 3. 80-mm thickness adhesive transfer tape (300LSE, 3M). 4. Flow-cell assembly (custom-made, eMachine Shop). 5. PrecisionGlide needle, 18 G1 (305195, Becton Dickinson). 6. Tygon tubing (I.D. 0.0400 , O.D. 0.08500 ).

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7. 5 min epoxy (Devcon). 8. KOH pellets (ACS grade, Mallinckrodt). 9. 95% ethanol (ACS grade, Sigma-Aldrich). 10. Glass beaker, 1 L (Corning). 11. Cover glass holder (custom-made). 12. Sonicator (VWR). 13. Cover glass container. 14. Polystyrene beads (1 mm; A37294, Invitrogen). 15. Stuck bead buffer (SB) (13 mg/ml NaHCO3 in water). 16. Stuck bead wash buffer (SBW) [10 mM Tris–HCl (pH 7.5), 100 mM MgCl2]. 17. Sample cell wash buffer (WB) (1 PBS, 1% w/v BSA, 0.04% Tween-20). 18. Bead wash buffer (BWB) [10 mM Tris–HCl (pH 7.5), 1 M NaCl].

2.3. Equipment for Magnetic Tweezers (Listed in Table 1)

3. Methods 3.1. Instrumentation 3.1.1. Overview of Magnetic Tweezers Construction

We have found that it is more efficient to build magnetic tweezers instrumentation from components, rather than modifying a commercial microscope. The design and construction of a microscope with the modest imaging capability required for magnetic tweezers are relatively straightforward. We provide a brief overview of the microscope assembly and details on specific topics essential for magnetic tweezers (11, 12). First, design considerations for the magnet geometry are discussed, followed by the design and implementation of illumination, imaging, and tracking. Our magnetic tweezers apparatus (Fig. 1) is assembled on a vibration isolation workstation (VH-FR3036, Newport). A 95mm structural rail (XT95-750, Thorlabs) supports the magnet assembly and the illumination source. A 1000  1200 aluminum breadboard on four 1.500 solid stainless steel posts (P10, Thorlabs) supports a fine and a course scale piezoelectric stage to which the flow-cell sample holder is affixed. The illumination system (LED and two lenses) is attached by an angle bracket to a manual stage on the structural rail. The linear motorized stage to control the axial position of the magnets is mounted on a rail

Remark

Linear Translation Stage and Track PIFOC adaptor Flow cell holder Rail carrier adapter Magnet rotation system Cage cube base

Rail carrier

Cage cube system

Mounting Posts Side Angle bracket

Microscope body Structural rail Rail plate and base Sample cell platform

Phillips Thorlabs Gardasoft Vision Ltd Newport Thorlabs Prosilica

Vendor

Custom machined

Linear and rotary stages mount to the rail carrier via adapters Illumination height control

Edmunds Optics

Newport

Mount illumination and linear/rotary motors Thorlabs Mounting plate and base Aluminum breadboard, 10" x 12" x 1/2", ¼-20 Threaded 1.5” Solid aluminum mounting post, Length=10" Clamp both sides of the PIFOC mount to the platform Build 3-D optical path

Illumination/Visualization LED Royal Blue LED, Luxeon1 III LED illuminator Illumination light (l =505nm) LED driver LED controller Lens Converging lens: f=150 mm Collecting lens: f=300mm Camera GigE CCD camera

Microscope

Name

Table 1 List of parts for magnetic tweezers instrument

NA

NT59-337

LC60W, LB1C, LB2C, LB3C, LB5C, ER3 and ER6 CXL95-120

P10 AP90

XT95-75 XT95P1/ XT95P3 MB1012

LXHL-LR3C LEDC10 PP610F KPX193AR.14 AC508-300-A1 GE680

Catalogue number

(continued)

219

157.08

–

59.7(x4) 74.2(x2)

102.0 39.6/28.1 164.6

7.5 331.5 1,181 65.99 97.85 2090

Price (USD)

15 Magnetic Tweezers for Single-Molecule Manipulation 269

Remark

Electronic devices and control software Computer Computer for hardware control and data analysis Monitor 19-inch flat panel LCD Motion control devices PILine1 Piezo Motor XY open frame stage system PIFOC1 High-Speed Nanofocusing drive PIFOC controller Precision translation stage, DC motor DC-Motor, drive unit, PWM-amplifier DC-Motor controller PC board, 4 axes, PCI Digital piezo controller, 3 channels, sub-D connector PIMars™ XYZ piezo nanopositioning/scanning Stage Interface control NI PCIe-8231, GigE Vision board with vision acquisition DAQ (16 AI, 24 DIO, 2 AO) GPIB control - NI-488.2 For Windows Shielded cable, 68 D-Type to 68 VHDCI offset Software NI developer suite Magnets 30 rectangular magnets (N=52; NdFeBr; Ni-plated; 583 mm)

Name

Table 1 (continued)

National Instruments Pacific PAC Technologies

National Instruments

Physik Instumente

Dell

Vendor

499.0 966.91 549.0 209 4699 250

NI PCIe-6251 GPIB-USB-HS SHC68-68-EPM NA NA

15,342

P-561.3CD NI PCIe-8231

2,878.4 244 19,250 5,693 6800 2,684 1391 4383 15,956

Price (USD)

Dell workstation T7400 UltraSharp 1908FP19-inch M-686.XYPM C-866 P-725.2CD E-750.CP M-126.PD1 C-150.PD C-843.41 E-710.3CD

Catalogue number

270 Y. Seol and K.C. Neuman

16.7(2), 95, 80.4

MB1012 CP06, CM1-4E, CRM1

3625

1658 49.4 25.8 (4) 164.6

SR640

Stanford Research Systems

3000

800

310 74 74 600 82.2

690 550 550

7083

562-XYZ MB4 P2

NA

NIH electronic shop

Laser detection mechanical parts 3 axis stage Position adjustment for laser and beam expander Newport Riser for 3 axis stage Aluminum Breadboard, 4"  6"  1/2", ¼-20 Thorlabs Threaded, 1.5” post and post mounts Optics platform Aluminum Breadboard, 10"  12"  1/2", ¼-20 Threaded 1 Optics mounts Lens mounts, PBS mounts, wave plate mount

DL100-7PCBA3

PBS-830-100 01 LAO 519 01 LAO 789 780dcspxr FB830-10

CWBX-7.0-4X-670-1064 QWPO-825-10-4 QWPO-825-10-2

iFLEX2000 P-#-830-0.7-35-N

Pacific silicon sensor

Chroma technologies Thorlabs

Melles Griot

CVI

4 beam expander Quarter wave plate Half wave plate

Polarization beam splitting cube Lens1: f=90 mm Lens2: f =125 mm Dichroic mirror (Ø=2”) Laser line band pass filter

Point source

Fiber coupled laser diode

Laser detection electronics Position sensitive Position sensor detector Detection signal Normalized X, Y, and Sum with variable gain amplifier and offset Anti-aliasing filter 2 channels

Mirror 830 nm filter

Beam splitter Lenses

Laser detection optics 35 mW laser diode, Ø=0.7mm Beam expander l/4 plate l/2 plate

Laser Detection

15 Magnetic Tweezers for Single-Molecule Manipulation 271

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carrier. The rotary motor and the spindle assembly are attached to the linear motor. The spindle assembly consists of a hollow shaft with a rotation bearing fixed near its center. The rotation bearing is held in an x–y translation stage, allowing the spindle assembly to be centered on the optical axis. A pulley, attached below the rotation bearing, is coupled to the rotary motor by a tension belt, and the magnet assembly is attached to the bottom of the spindle (Fig. 2a). A pair of permanent magnets is secured by two set screws in the magnet holder. A soft iron yoke encircles the outer faces of the magnets, blocking the leakage field from interfering with the fringing field. A 60 oil immersion objective, which defines the optical axis, is attached to a piezoelectricfocusing element (PIFOC), which enables fine focus control. The PIFOC is mounted on an adaptor plate secured to the underside of the breadboard via two angle brackets. Three stacked cage cubes below the objective are centered on the optical axis. The top cube holds a dichroic, which reflects the infrared detection laser and transmits the visible illumination. The bottom cube holds a turning mirror to steer illumination light from the objective to an imaging lens, which projects a magnified image onto the CCD camera. The translation and rotation motors and piezoelectric-stages are computer controlled via LabVIEW. Image data from the camera are transferred to the computer via the GigE Vision standard. 3.1.2. Magnet Geometry Design Using RADIA

The dipole configuration, in which opposite poles of two permanent magnets are separated by a small gap, generates a magnetic fringe field parallel to the gap that decays exponentially in the axial direction and is the most common configuration for magnetic tweezers (2, 10). The amplitude and gradient of the magnetic force depend on magnet geometry, i.e., the dimensions of the magnets and distance between them. It is instructive and useful to optimize the magnet geometry by calculating the gradient and force (8). To compute the magnetic field distribution of different magnetic geometries, we used Mathematica to run RADIA, which is a suite of three-dimensional magnetostatic calculation routines developed by the European Synchrotron Radiation Facility (ESRF) to aid in the design of magnetic insertion devices. Magnetic fields are calculated through an iterative process based on boundary integral methods, which are much less computationally intensive than the commonly used finite element methods. RADIA is free; however, it requires Mathematica. 1. Magnets, magnet dimensions, and magnetic beads. The maximum magnetic field strength is determined by the material properties of the permanent magnet. To date, neodymium–iron–boron (NdFeB) permanent magnets offer the

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highest magnetic energy density ranging from N 26–52 in mega-gauss-oersteds (MGOe) (1 MGOe ¼ 7.958 kJ/m3). Typically, an N 50 rated NdFeB magnet produces a magnetic field strength of approximately 1.4 T. This value can be obtained from the vendor and directly verified with a Hall probe. The force (F) applied on a magnetic particle is given by the following equation: F ¼

1~ rð~ mð~ BÞ  ~ BÞ; 2

(1)

It is dependent on the induced magnetization (m) of the magnetic particle, magnetic field strength (B), and field gradient. m is a characteristic of the magnetic particle: ~ ðBÞ ¼ m ~ sat ðcoth ðB=B0 Þ
B0 =B Þ m

(2)

where msat is the saturation magnetization, and B0 is a material dependent scaling parameter. The maximum force generated primarily depends on the gap size as long as the magnet dimensions are larger than the gap (8) (Fig. 2b). The maximum force increases as the gap decreases; however, the force gradient also increases, so a balance must be struck between applying a large force and applying a constant force. Moreover, the gap creates an aperture through which the illumination must pass (Fig. 2b). In practice, the balance of these considerations results in gap widths ranging from 0.5 to 1.5 mm for ~10-mm magnets (8). 2. Calculation of magnetic fields. The magnetic fields generated by a given set of magnet parameters, including magnet field strength, dimensions, and gap size, are calculated with RADIA functions running in Mathematica (see Note 1). The process involves defining the dimensions and magnetic properties of both the magnet and the iron yoke that surrounds them. The elements are then subdivided for the purpose of calculating the external fields. The optimum number of subdivisions is operationally determined as the number for which the calculated fields become independent of the subdivisions. 3.1.3. Illumination, Imaging, and Image Tracking

1. Illumination. The illumination should be relatively monochromatic, planar, and spatially coherent to achieve good diffraction patterns from the magnetic particles (13). High-power LEDs are well suited to these requirements, though some care is required in choosing among the emitter patterns and wavelengths that are commercially available. The important criteria in choosing an LED is intensity rather than power as the light

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Fig. 1. Magnetic tweezers instrument. (a) Photograph and (b) diagram of magnetic tweezers. The magnet assembly and the illumination LED are mounted on a structural rail. The flow-cell holder sits on the piezoelectric stages, which are mounted on the platform. The objective is mounted on a piezoelectric focusing element attached to the underside of the platform. The illumination (heavy dashed line ) is collected by the objective and directed to the CCD camera via a mirror. The detection laser light (light dashed lines ) is introduced into the objective via a dichroic mirror that sits in a cage-cube below the objective. The front view illustrates how the PIFOC adaptor is mounted on the platform with two right angle brackets. (c) Backscattered laser detection setup. The expanded laser beam is reflected by the turning mirror and passes through a half wave plate, polarizing beam splitter (PBS), a pair of lenses, and a quarter wave plate before being focused by the objective. Light backscattered by the bead is collected by the objective and follows the reverse path, until the PBS, where it is reflected onto a position sensitive detector.

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Fig. 2. Magnet assembly and calculation of magnetic field and force. (a) Detailed drawing of the magnet assembly. The rotary motor drives a pulley that is coupled via a tension belt to a pulley on the magnet holder spindle assembly. The spindle runs through a rotary bearing held in the two axis stage, which allows the spindle to be centered on the optical axis. The magnet holder is affixed to the end of the spindle with set screws. The magnet holder has a slot machined across the bottom face to accommodate the magnets, which are held in place with set screws. A soft iron yoke can be slipped over the magnets and held in place by the magnets. (b) Magnetic field and force for a pair of NdFeBr magnets (N ¼ 52) with different geometries in a dipole configuration (solid line w  h  l ¼ 3  5  8 mm, gap ¼ 0.5 mm; long dashed line 3  5  8 mm, gap ¼ 0.8 mm; short dashed line 3  5  8 mm, gap ¼ 1 mm; medium dashed line 5  5  5 mm, gap ¼ 1 mm). The magnetic field at the center of the gap as a function of the distance from the magnet edge is shown in the top panel. The corresponding force on a 1-mm superparamagnetic bead is shown in the lower panel.

must pass through the small (<1 mm) gap between the magnets. Some high-power LEDs have multiple emitters, which do not lead to higher intensity. We replaced the LED in an illuminator from Thorlabs with a Luxeon® III LED, which has four emitters and an operating current of 1.4 A. The radiation angle of an LED is generally large, >150 . Thus, either a high numerical aperture (NA) condenser lens or an aspheric lens with a large clear aperture is required to collimate the light for imaging. We use a 200 aspheric lens (f ¼ 37 mm) to decrease the NA of the light from the LED followed by a 200 spherical lens (f ¼ 150 mm) to collimate (actually weakly converge) the light. We enclose the illumination light path in a 200 long lens tube and add an iris at the end to block scattered light and improve spatial coherence (see Note 2). To improve the temporal resolution of the position tracking (see below), we employ stroboscopic imaging by synchronizing brief (2 ms) high intensity LED pulses with the camera exposure. The maximum drive current and output light intensity of an LED are limited by heating. Above a critical temperature, the performance and longevity of the LED deteriorate. Manufacturer suggested maximum currents are intended to maximize

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the lifetime and performance of the LED, but can often be exceeded several-fold to obtain higher intensity output at the expense of decreased lifetime (14). LEDs can also be overdriven if used in a pulsed mode. As a rule of thumb, the time-averaged current should not significantly exceed the maximum current rating. Taking advantage of pulsed LED operation requires a CCD camera with programmable exposure and external trigger capabilities. The Prosilica CCD camera that we employ for imaging has user programmable exposure time, frame rate, gain, and region of interest settings, which can be controlled on the fly. We use a function generator to control the duration and period of the LED pulse and as an external trigger for the CCD. Stroboscopic imaging also minimizes camera blur that complicates analysis of motion occurring on a timescale faster than the exposure time (4, 15). The detailed steps for synchronizing the LED and camera are as follows: (a) Generate a 0–5 V square wave with a period corresponding to the desired CCD camera frame rate and a pulse width and delay time (relative to the synchronization output (Sync)) to match the exposure time of the CCD camera. (b) Connect the output of the function generator to the CCD trigger input port and the Sync to the LED driver trigger input. (c) Set the desired current output of the LED driver by adjusting input voltage (this step may be different for different LED drivers). (d) Set the camera frame rate and exposure time using either manufacturer provided software or other interface control software such as National Instruments Measurement and Automation. (e) Measure the image light intensity to verify the synchronization between the camera and the LED pulse. Synchronization, exposure, and delay times can be optimized by recording the intensity on the CCD camera during the exposure. 2. Imaging and image acquisition. The imaging system is composed of a 60 oil immersion objective, a 200 He–Ne laser mirror, a 200 collection/imaging lens (f ¼ 300 mm), a 100 silver mirror, and a CCD camera. The final resolution of the imaging system is 81 nm/pixel. Scattered and incident light are collected by the objective lens and reflected off the mirror (Fig. 1a). Approximately 300 mm away from the back focal plane of the objective, we place the 200 imaging lens that diffracts incoming light onto the CCD surface via the 100 silver mirror. Image data are transferred to a computer through a GigE Vision camera bus. GigE Vision is an interface standard for cameras that transfer images over

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gigabit Ethernet. It provides a relatively fast transmission rate with lower-cost cabling (Cat 5 Ethernet cable). It requires a driver to parse the image data wave-packets, which may cause excessive CPU loading. It is more efficient to implement a driver written for a dedicated network interface card (NIC) allowing data parsing by the NIC rather than the CPU. We use a National Instruments GigE network PCI card and Vision software to optimize image acquisition and processing. 3. Real-time particle image tracking in three dimensions. One of the most critical functions of a magnetic tweezers instrument is accurate, real-time, three-dimensional position measurement of the magnetic particle. Video-based position tracking remains the method most commonly used for magnetic tweezers experiments (4). The basic concept of 3D particle tracking is straightforward (2, 4, 13). Under the slightly converging LED illumination, the image of a magnetic bead consists of a series of concentric diffraction rings that change as a function of the axial position of the bead relative to the objective focal plane (Fig. 3a). Axial position tracking relies on correlating the diffraction pattern with axial displacement. This process is simplified by the fact that the phase of the ring pattern is proportional to the axial displacement (4). The axial calibration method based on this phase shift is well explained in ref. 1 (see Note 3). Alternatively, we have found that after taking an FFT (fast Fourier transform) of the ring pattern, the amplitudes of the four lowest frequency peaks change monotonically as a function of axial position, which are well fit by thirdorder polynomials (Fig. 3b). In the following section, we explain 3D image tracking using LabVIEW. 4. Lateral calibration. In typical magnetic tweezers experiments, the axial direction (optical axis) is parallel to the applied force and is the primary measurement axis. However, accurate axial position measurements require the lateral center position of the bead. Moreover, lateral position information is necessary for force calibration (see below) (4). Lateral calibrations employ the built-in LabVIEW IMAQ sub vi file (“IMAQ Detect Shapes”), which identifies and returns the center position of a shape in a region of interest. With a relatively simple routine, we can track a 1-mm magnetic bead with a resolution of a few nm at 100 Hz. Resolution is further refined by fitting the center region of the bead image to a two-dimensional Gaussian. x and y positions are measured in pixels and must be normalized to obtain real-space dimensions. We obtain the conversion factors by using the piezoelectric-stage to move a stuck particle with a triangle wave of 1-mm amplitude in 10 nm steps while measuring the x and y displacement in

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Fig. 3. Image tracking method. (a) The image of a bead at two different axial positions is shown in the left panel. The top image is at the objective focal plane and the other is 7 mm below the focal plane. The corresponding radial profiles are shown in the center panel and the fast Fourier transform (FFT) of the profiles is shown in the right hand panel. The four lowest frequency peaks in the FFT profiles, the amplitudes of which are used for the axial calibration, are indicated by arrows. (b) Amplitudes of the four lowest frequency peaks as a function of axial displacement.

pixels. In our system, the conversion factors are 80.6 nm/ pixel for x and 80.8 nm/pixel for y. 5. Axial calibration. Once the center is determined, intensity line profiles through the center in the x and y directions are averaged together to obtain the radial profile I(r), which is employed for axial position calibration. The detailed steps are as follows: (a) Either a stuck bead or a DNA tethered bead can be calibrated. For a tethered bead, Brownian motion is reduced by either applying a high force or by supercoiling the DNA. The stage is moved so that the bead is positioned slightly below the image plane, where a few diffraction rings appear. Selecting a region of interest around the bead (~160  160 pixels for a 1-mm bead) expedites the calibration procedure. (b) The radial profile, I(r), is obtained by averaging the radial intensity over the width of the arms of a cross centered on the image of the bead (Fig. 3a). The arms of the cross are

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typically 150 pixels long (along the radius) and 8 pixels wide (over which the averaging is done). The radial profiles from 20 successive video frames are normalized by the background intensity, averaged, and spatially smoothed with a 20 point, sixth-order Savitzky–Golay filter, after which a Parzen window function is applied. We compute the FFT of this processed I(r) to find the amplitudes of the four lowest frequency peaks (Fig. 3). (c) We lower the piezoelectric stage over 7 mm in the axial dimension and obtain the amplitudes of the first four FFT peaks every 10 nm. (d) At the end of the program, we fit the axial displacement as a function of each of the four FFT amplitudes with thirdorder polynomials to obtain a set of four axial fit coefficients (Fig. 3b). The fit coefficients are saved as global variables allowing them to be called by the real-time tracking routine. (e) It is important to note that the z stage motion should be scaled by the relative refractive index (nw/ng ¼ 0.869 for the refractive indices of water nw ¼ 1.3 and glass ng ¼ 1.53) to correct for the focal shift due to the refractive index mismatch at the glass–water interface (16). In practice, axial motions of the stage or objective are multiplied by the ratio of refractive indices (nw/ng) to obtain the actual motion of the objective focus with the sample chamber. 6. Force calibration. Force calibration relies on the fact that the bead–DNA system can be treated as an inverted pendulum, for which the lateral stiffness (kx) is given by the ratio of the vertical force (F) to the length of the DNA (zDNA): kx ¼ F/zDNA. The applied force can be determined by the equipartition theorem. According to the equipartition theorem, kx ¼ kB T =hdx 2 i ¼ F =zDNA , where kB is the Boltzmann constant, T is the ambient temperature in Kelvin, and hdx 2 i is the lateral variance of the bead. By simultaneously measuring the transverse fluctuations and the extension of the DNA molecule, the force can be determined: F ¼ kB TzDNA =hdx 2 i (4, 5). Lateral position is measured by tracking the center of a DNA-tethered magnetic bead as explained above. Due to camera integration, the variance measurement for the equipartition theorem method should be corrected for the ratio of the camera integration time to the roll-off frequency of the system (4, 15). We find that the correction factor is less than 5% at 2 ms integration in our setup due to the low rolloff frequency of the tethered magnetic bead (<100 Hz).

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The z position is simultaneously measured by tracking the axial position of the bead relative to the zero length reference position, at which the bead is on the surface. (a) Rotate the magnet to twist the DNA tether at low force (F ¼ 0.4 pN) to form enough plectonemes to pull the bead down to the surface. For rotationally unconstrained DNA, the reference point is set to the extension of the DNA stretched at the maximum applied force. However, this method may result in 5–10% uncertainty in the contour length as the DNA may not reach its contour length at the maximum force. (b) Measure x, y, and z reference points, xref, yref, and zref. (c) Rotate the magnet back to zero turns, making sure that the magnets are aligned with the x or y measurement axis. The magnetic bead can rotate in the plane perpendicular to the field of the external magnets, but is rigidly held in the plane of the external field. This leads to a slight asymmetry in the variance of the tethered bead. For motion parallel to the field, the tether length is equal to the DNA extension, whereas for motion perpendicular to the field, the effective tether length includes the radius of the magnetic bead. As a result the variance is higher in the direction perpendicular to the field than in the parallel direction. The force calibration should be based on the motion parallel to the field, as the tether length for this motion corresponds to the measured z extension. Move the magnet to apply the maximum force, as close as possible to the top surface of the flow-cell. (d) Measure x, y, and z for a time duration based on the theoretical correlation time [we typically measure for 20 correlation times ðtc ¼ 6przDNA =F Þ; where r is the bead radius and  is the viscosity of water]. (e) At the end of each cycle, obtain x and y variances, and the extension of the DNA molecule to calculate the force using the relation F ¼ kB TzDNA =hdx 2 i. (f)

We repeat this step for 20 different magnet positions that range from 0.01 to 8 pN by moving the magnets away from the surface. The force versus magnet position is fit with an exponential function with a characteristic length on the order of the gap size.

7. Surface drift compensation using backscattered laser detection. In many single-molecule experiments, sample cell drift limits measurement precision. Drift can result from thermal expansion, vibration, and buffer exchange in the flow-cell. The effects of drift can be minimized by measuring the position of a fixed fiducial reference on the surface (1-mm polystyrene particle

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melted on the surface) and moving the sample in three dimensions to compensate the drift. This can be accomplished with image tracking (17) or with laser based backscattered detection (18, 19). Laser based detection provides better spatial and temporal resolution and decreases image processing time. The detection setup consists of a linearly polarized 826 nm laser, a 4 beam expander, a beam steering mirror, a half wave plate, a polarization beam splitting cube (PBS), two lenses (f ¼ 90 and 125 mm) and a quarter wave plate (Fig. 1b). The key idea of the backscattered laser detection scheme is to use polarization selection to collect only light reflected from the sample cell. Linearly polarized light passes through the PBS and then through a quarter wave plate just prior to entering the objective. Backscattered light undergoes a 180 phase shift and on returning through the quarter wave plate will be linearly polarized in a plane orthogonal to the input light. The backscattered light is then picked off by the PBS and directed onto a position sensing photodiode. (a) A linearly polarized laser is required for polarizationbased backscattered position detection. (b) In general, power fluctuations and pointing instability lead to positional noise. Thus, the laser should be carefully chosen to meet requirements of the intended application. The noise will depend on the details of the optical system. In our system a 1% peak-to-peak intensity noise results in 1 nm of axial noise and the pointing instability leads to lateral position noise of ~4 nm per microradian angular fluctuation. (c) A polarization beam splitting cube with high extinction ratio (>500:1) is recommended. The PBS will clean up polarization of the laser and select out the reflected light that is orthogonally polarized with respect to the input light. A half-wave plate inserted before the PBS provides control over the laser intensity at the sample. We typically set the laser intensity to 2–3 mW. (d) The backscattered intensity reaching the detector can be optimized by rotating the quarter-wave plate. Sensitivity of position detection is proportional to the input beam size. Thus a 4 beam expander (expansion from 0.7 to 2.8 mm) is employed to enhance detection sensitivity. A simple telescope formed by an f ¼ 90 mm lens and an f ¼ 125 mm lens separated by the sum of their focal lengths provides another ~1.4 beam expansion. A beam steering mirror 90 mm away from the first lens, which places the mirror in a conjugate plane of the objective back focal plane, is used to control the position of the laser focus in the specimen plane. In this configuration,

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adjusting the mirror moves the position of the laser focus in the specimen plane without changing the position of the laser at the back focal plane of the objective lens. The axial position of the focus can be adjusted relative to the objective by moving one of the lenses in the telescope along the optical axis. For lateral and axial calibration, we use the piezoelectric-stage to scan a bead across the laser focus in x, y, and z and obtain the corresponding voltage signals from the position sensitive detector. For each axis we fit the position versus output voltage with a seventh-order polynomial, which provides resolution on the order of 1 nm. 3.2. Preparation of Multiple Digoxigeninand Biotin-Labeled DNA

Rotationally constrained DNA tethers require multiple attachments between the DNA and the bead at one end and between the DNA and the surface at the other. The most commonly used linkers are biotin–streptavidin and digoxigenin– anti-digoxigenin. To construct DNA with multiple biotin moieties on one extremity and multiple digoxigenin moieties on the other, we produce three PCR products that we cut and ligate together. Standard PCR is used to make the unlabeled DNA, whereas the two “handles” containing multiple biotin- or digoxigenin-labeled nucleotides are made by adding a small percentage of appropriately labeled dUTP to the PCR reaction of a ~500 bp template. The primers for the three PCR reactions are designed with unique nonpalindromic restriction sites such that after restriction digest and clean up the two labeled DNA handles will ligate onto the unlabeled DNA in a unique orientation with no side products (see Note 4). This scheme improves the yield and specificity of the DNA assembly process (see Note 5).

3.2.1. Protocol for Creating Coilable DNA Molecules

1. PCR to make digoxigenin/biotin-labeled DNA handles (500 bp). Individual PCR reactions should be run for biotin and digoxigenin-labeled handles: (a) Mix the PCR reagents Taq DNA polymerase

0.5 ml

10 standard Taq buffer

5 ml

pBluescript II KS forward (100 mM)

0.25 ml

pBluescript II KS reverse (100 mM)

0.25 ml

pBluescript

1 ng

dNTP (10 mM)

1 ml

Bio/Dig-labeled dUTP (1 mM)

1 ml

ddH2o up to

50 ml

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(b) PCR reaction conditions Standard PCR conditions with the following specific steps: Denaturation: 95 C for 30 s Annealing: 62 C (Tm + 3 C) for 30 s Elongation: 68 C for 30 s Cycles: 30 (c) Purify DNA product using Qiagen PCR cleanup kit. (d) Quantify DNA (typical yield is 50 ml of ~200 ng/ml) 2. PCR of main DNA segment (5 kb): (a) Mix the following: Phusion polymerase

0.5 ml

5 Phusion HF buffer

10 ml

pET28a forward (100 mM)

0.25 ml

pET28a reverse (100 mM)

0.25 ml

pET28a

1 ng

dNTP (10 mM)

1 ml

ddH2o up to

50 ml

(b) PCR reaction conditions. Standard PCR conditions with the following specific steps: Denaturation: 98 C for 15 s Annealing: 62 C for 30 s Elongation: 72 C for 5 min (based on 1 min/kb) Cycles: 30 (c)

Purify DNA product using Qiagen PCR cleanup kit.

(d) Quantify DNA (typical yield is 50 ml of 50–100 ng/ml). 3. Digestion of biotin-labeled (digoxigenin-labeled) DNA handles. Two separate reactions should be run: one with BsaI and the biotin-labeled DNA handles and one with BfuAI and the digoxigenin-labeled DNA handles: (a) Mix the following: 10 NEB Buffer 3

5 ml

Biotin (digoxigenin)-labeled DNA handles from step 1

2 mg

Bsa I (BfuAI)

3 (4) ml

ddH2O up to

50 ml

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(b) Incubate overnight at 50 C. (c) Purify DNA for ligation using PCR cleanup kit. 4. Digestion of the main DNA segment: (a) Mix the following: 10 NEB Buffer 3

5 ml

PCR product of main DNA segment from step 2

2 mg

Bsa I

3 ml

BfuAI

4 ml

ddH2O up to

50 ml

(b) Incubate overnight at 50 C. (c) Purify DNA for ligation using PCR cleanup kit. 5. Ligate biotin- and digoxigenin-DNA handles to main DNA segment: (a) Mix the following: DNA ligase

0.5 ml

10 T4 DNA ligase buffer

6 ml

DNA center segment

2 nM

Biotin DNA handle

4 nM

Digoxigenin DNA handle

4 nM

ddH2O up to

60 ml

(b) Incubate the sample tube at 16 C for 48 h. (c) Clean up DNA with a PCR cleanup kit (d) Gel-purify (Qiagen) ligated product (~6 kb) on 1% agarose gel. (e) Quantify DNA (typical yield is 50 ml of ~2 ng/ml of final product). 3.3. DNA Manipulation Using Magnetic Tweezers 3.3.1. Flow-Cell Preparation

1. Cover glass cleaning: (a) Place cover glass (#1½, 24 mm  60 mm) in a Teflon cover glass holder that holds the cover glass vertically. (b) Prepare enough KOH–ethanol solution (15% w/v) in a 1-L glass beaker to submerge cover glass holder. (c) Sonicate the cover glass in the KOH solution for 20 min. (d) Remove the holder and place it in a 1-L glass beaker containing deionized water.

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(e) Sonicate for 20 min. (f) Repeat steps (d) and (e). (g) Take out the holder and rinse each cover glass 2–3 times with DI water to remove remaining KOH. (h) Squirt 95% ethanol over each cover glass. (i) Dry the cover glass either by microwaving for a few minutes or baking for 15 min at 150 C. (j) Store the cover glasses in an air-tight container. 2. Flow-cell assembly: (a) Attach double-sided tape (80 mm) with a ~3  50 mm hole in the center to a cleaned coverslip (Fig. 4). (b) Put top cover glass (22 mm  40 mm) over the bottom cover glass to form a ~10 ml volume sample chamber. (c) Put epoxy around the edge of the sample chamber to increase rigidity (optional). 3. Stuck bead protocol: (a) Make a 0.1% (w/v) polystyrene bead suspension in freshly prepared SB buffer. (b) Pipette 20 ml of this bead suspension into the flow-cell and incubate at room temperature for an hour. (c) Flow 200 ml of SBW buffer through the flow-cell. (d) Incubate for 30 min. (e) Flow ~100 ml ethanol through the flow-cell and remove it completely. (f) Bake sample cells for 7 min on hot plate at ~175 C. (g)

Add water and wait for 10 min, then wash with 2 ml of water.

(h)

Incubate for 2 h.

(i)

Wash with 2 ml of water.

(j)

Suck water out completely and air-dry.

4. Generation of coilable DNA tethers on the surface with superparamagnetic beads: (a) Mix 6 ml of anti-digoxigenin solution (0.2 mg/ml in 1 PBS), 4 ml of 0.4 nM coilable DNA (from step 5 above), 10 ml of 5 PBS-0.5 mM EDTA, and water up to 50 ml. (b)

Incubate for 15–20 min at room temperature.

(c)

Pipette 15 ml into the flow-cell assembly.

(d)

Incubate the flow-cell overnight at 4 C or 1 h at RT.

(e)

Wash the flow-cell twice with 200 ml of WB buffer and incubate for 10 min.

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Fig. 4. Schematic of flow-cell assembly. The flow-cell assembly consists of a flow-cell, two Teflon flow-cell adapters, and two clamps. The flow-cell adapters are used to enclose the flow-cell and facilitate buffer exchange. As shown in the figure, buffer flows in from the left through a needle into the adapter and is removed by vacuum.

(f)

While waiting, pipette 10 ml of a 1% w/v 1 mm streptavidin magnetic particle suspension and put it in a microcentrifuge tube.

(g)

Pull beads to the bottom of the tube by placing it on top of a permanent magnet.

(h)

Gently pipette out the supernatant.

(i)

Add 200 ml of BWB buffer and vortex the tube quickly to mix.

(j)

Repeat steps 7–9 three times.

(k)

After the final wash, instead of adding BWB, add 100 ml of WB.

(l)

Introduce the bead solution into the flow-cell and incubate overnight to passivate the surface with BSA.

(m) Before use, remove free beads by washing 1 ml of WB through the flow-cell.

3.3.2. Measurements

(n)

Put the flow chamber on the sample holder platform.

(o)

Assemble the two flow-cell adapters onto the sample holder (Fig. 4).

1. Stretching DNA. Once the magnetic tweezers system is up and running, measuring the elasticity of bare DNA is a good way to ensure that everything is working properly and is a precursor to subsequent studies of protein–DNA interactions (Fig. 5a). Force-extension measurements using magnetic tweezers have been discussed in detail (1, 2, 10). DNA elasticity is well described by the worm-like chain model (WLC) (20).

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Fig. 5. Force vs. extension and extension vs. number of magnet turns. (a) Experimental force vs. extension curve for a DNA molecule (solid circles) fit with a WLC model (solid line). The persistence length and contour length are 53  3 and 1,971  3 nm, respectively. (b) DNA extension as a function of the number of magnet turns at F ¼ 0.2 pN (solid circle). The extension vs. rotation curves is symmetric at low forces (<0.4 pN). As turns are imposed, there is a slight decrease in extension corresponding to an increase in the twist of the DNA, followed by an abrupt decrease in extension at the buckling transition (~5 turns). Past the buckling transition, the extension decreases linearly with the number of turns.

With this model, force vs. extension data can be fit with two parameters: persistence length and contour length. Contour length L is the length of DNA molecule defined by rise per base of 0.338 nm. The persistence length P is a characteristic of the DNA bending rigidity and is ~50 nm (21). 2. Twisting DNA. With DNA templates prepared and tethered as described above, we find that more than 50% of the DNA tethers are rotationally constrained. To rapidly identify rotationally constrained DNA molecules, we impose enough clockwise, i.e., negative supercoiling, turns beyond the buckling transition, NB, so that at low forces (<0.4 pN), the bead will be pulled to the surface of the flow-cell. At high forces (>0.5 pN), on the contrary, the DNA will locally denature and the bead will be pulled upward (5). By rapidly switching the force between high and low values, the change in the diffraction pattern as the bead moves up and down can be visually identified. NB can be estimated for a given contour length of DNA and force based on a simple model in which the torsional energy is balanced by the work done against the magnetic force and

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pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi the bending energy of the DNA ðNB ¼ L 2PkB TF =2pCÞ; where C  90kBT is the torsional modulus, and P ¼ 50 nm (5). The number of additional turns beyond NB required to pull the bead to the surface can be estimated from the observation that each additional turn reduces the extension by ~50 nm. If DNA is coilable, we explore the behavior of double-stranded DNA under torsion by measuring DNA extension as a function of rotation and force. Extension-rotation curves provide a powerful method to study dynamic changes in DNA topology and the activity of topoisomerases (Fig. 5b).

4. Notes 1. An example of the calculation program for the following magnet geometry is as follows: width ¼ 5 mm; length ¼ 8 mm; thickness ¼ 3 mm; gap ¼ 1 mm. Figure 2b displays the results of the calculations for this and other magnet geometries. (a) Download RADIA from the following Web link. (http://www.esrf.eu/Accelerators/Groups/InsertionDevices/Software/Radia). (b) Start Mathematica and initialize Radia by typing “<
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radObjDrwAtr[gb,{0,1,0.5}]; (*Applies drawing attributes*) g1¼radObjCnt[{ga,gb}]; (*Creates a container combining objects capable of producing a magnetic field *) radObjDivMag[g1,{5,5,5}]; (*Sub-division of magnets – divided into 5 segments in each dimension*) ironcolor¼{0,0.5,1}; (*Create an iron yoke*) ironmat¼radMatSatIso[{20000,2},{0.1,2},{0.1,2}]; (*Defines magnetic properties of iron yoke.*) (*Define shape of iron yoke so that the ends of the magnets are flush with the yoke*) nseg¼8; (*Number of faces in the polygon. The results are relatively insensitive to this parameter*) rint1¼wy+gap/2; (*Create a polygon with inside radius equal to the sum of the length of the magnet and half of the gap size*) (*Create three radial layers of the polygon shell with a total thickness of 3 mm*) rext1¼rint1+1.0; rint2¼rext1; rext2¼rext1+1.0; rint3¼rext2; rext3¼rext2+1.0; Lz¼wz; (* Sets the height of the iron yoke polygon equal to the magnet thickness*) (*Define an initial and a final angle for the polygon. The initial angle sets the relative rotation of the polygon. For a closed polygon, the final angle should be 360 larger than the initial angle*) phi1¼(360/nseg)*0.5/180*Pi; (*Initial angle of the polygon, which must be set so that polygon orientation is flush with magnets*) phi2¼phi1+2 Pi; (*Final angle*) (*Makes polygon layers*) nz¼1; nr¼{1,1}; pt¼{0,0,
1.5}; br¼0; (*Set initial flux through iron yoke polygon due to magnets previously defined*) a¼N[radFld[g1,"by",{0,wy+gap/2,0}]];

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mag¼{0,a,0,0}; (*Create three layers of polygon yoke*) cyl1¼RadCylinder[pt,rint1,rext1,phi1,phi2,Lz,nr, nseg,nz,mag]; cyl2¼RadCylinder[pt,rint2,rext2,phi1,phi2,Lz,nr, nseg,nz,mag]; cyl3¼RadCylinder[pt,rint3,rext3,phi1,phi2,Lz,nr, nseg,nz,mag]; cyl¼radObjCnt[{cyl1,cyl2,cyl3}]; layers into one object*)

(*Combine

three

radMatApl[cyl,ironmat]; (*Defines the material of the assembled polygon*) radObjDrwAtr[cyl,ironcolor]; (*Sets the display color of the polygon*) radObjDivMag[cyl,{1,1,5}]; (*Defines the subdivision of the individual components of the polygon for the purpose of calculating the magnetic fields*) g2¼radObjCnt[{g1,cyl}]; (*Combine magnets and yoke*) N[radFld[g2,"by",{0,0,zend}]] (*Flux calculation in Z*) RadPlot3DOptions[];(*Three-dimensional plot of the defined objects using RADIA*) Show[Graphics3D[radObjDrw[g2],Axes-->True]] (*Calculate the y component of the magnetic field at the center of the gap as a function of z*) ob¼g2;x¼0;y¼0;zmax¼5;Nn¼200;dz¼2.5/80; RadPlotOptions[]; (*Take default plot option*) by¼radFldLst[ob,"By",{x,y,0},{x,y,zmax}, Nn,"arg",0]; ListPlot[by,Joined-->True,FrameLabel-->{"Z [mm]","By[T]","X ¼ 0 mm, Y ¼ 0 mm",""}] n¼Table[by] (*Tabulate data*) Export["G:\\MT paper v1\\Radia\\Data\\filename.xls", n] (*Exports data to an Excel file*) (c) Force is calculated from the computed field using Eqs. 1 and 2 with vendor specified Msat ¼ 43.3 kA/m, B0 ¼ 12 mT for MyOne superparamagnetic beads (Fig. 2b). 2. We do not recommend laser as an illumination source due to its relatively long temporal coherence length compared to an

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LED. This creates interfering diffraction patterns of any objects along the path of light in the flow-cell. 3. Alternative axial calibration method based on relative phase shift (2, 4): (a) Measure calibration radial profiles, IC(r) over 10 mm every 0.33 mm. (b) For coarse estimation of z position, find the calibration profile that is closest to the measured I(r) based on a least-squared algorithm. (c) For more accurate determination of z position, the phase of I(r) is calculated and interpolated between the two nearest IC(r)s since the phase depends linearly on the axial displacement. To obtain the phase, j, of the radial profile, perform the Hilbert transform, H, on I(r) then compute the inverse tangent of the ratio of I(r) to H[I(r)]. More generally: ’ðzÞ ¼ tan
1 ðI ðr; zÞ= H½I ðr; zÞÞ: Note that I(r,z) should be offset so that the end point of I(r,z) is 0. 4. Primer design. Factors to be considered are as follows: (a) Primers have an additional 50 overhang containing a nonpalindromic restriction enzyme recognition sequence. (b) The nonpalindromic restriction endonucleases were specifically chosen to cut arbitrary sequences distal from their recognition sequences. The sequences at which the enzymes cut are designed to lack adenines since we assume that digoxigenin/biotin-uracil in the cutting sequence decreases the cutting efficiency. (c) Once the 50 extensions have been determined, the remainder of the primers can be designed following procedures for standard PCR. We find that it is helpful to go through the cutting and ligation process with DNA manipulation software (such as Clone Manager) to ensure that the products give the desired results. Example: Primer design with BfuAI and BsaI nonpalindromic restriction enzymes. pET28a forward -BfuAI: GGACCTGCTTTCCAACAGTCA GAGGTGGCGAAACCC

pET28a reverse: GGGTCTCGACCATACACTCCGCTATCGC TACG

pBluescript II KS forward -BfuAI: GGACCTGCTTTCGTTG TGGCGTAATCATGGTCATAG

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pBluescript II KS reverse -BsaI: GGGTCTCGTGGTTTAT AGTCCTGTCGGGTTTC

These primers give a ~5 kb fragment of pET28a DNA and a ~500-bp fragment of pBluescript. BfuAI:

ACCTGCNNNN TGGACGNNNNNNNN

BsaI:

GGTCTCN CCAGAGNNNNN

Primers and their associated restriction enzymes (50 extensions are in bold and the overhangs after digest are underlined): 5. The efficiency and specificity of the PCR reaction can be improved by linearizing the plasmid template.

Acknowledgments We thank Vincent Croquette, David Bensimon, Jean-Francois Allemand, Timothee Lionnet, Terence Strick, Yashuharu Takagi, and Marie-Paule Strub for help and advice. We thank Joseph Mears for machining. We are grateful to Grace Liou, Richard Neuman, Jonathan Silver, and Ashley Hardin for critical reading of the manuscript. This research was supported by the Intramural Research Program of the National Heart Lung and Blood Institute, National Institutes of Health. References 1. Neuman, K. C., and Nagy, A. (2008) Singlemolecule force spectroscopy: optical tweezers, magnetic tweezers and atomic force microscopy, Nat Meth 5, 491–505. 2. Lionnet, T., Allemand, J.-F., Revyakin, A., Strick, T. R., Saleh, O. A., Bensimon, D., and Croquette, V. (2008) Single-Molecule Studies Using Magnetic Traps in Single-Molecule Techniques: A Laboratory Manual. (Selvin, P. R., and Ha, T., Eds.), Cold Spring Harbor Laboratory Press. 3. Neuman, K. C., Lionnet, T., and Allemand, J. F. (2007) Single-molecule micromanipulation techniques, Annu. Rev. Mater. Res. 37, 33–67. 4. Gosse, C., and Croquette, V. (2002) Magnetic tweezers: micromanipulation and force

measurement at the molecular level, Biophys. J. 82, 3314. 5. Charvin, G., Allemand, J. F., Strick, T. R., Bensimon, D., and Croquette, V. (2004) Twisting DNA: single molecule studies, Contemp. Phys. 45, 383. 6. Charvin, G., Bensimon, D., and Croquette, V. (2003) Single-molecule study of DNA unlinking by eukaryotic and prokaryotic type-II topoisomerases, Proc. Natl. Acad. Sci. USA 100, 9820–9825. 7. Neuman, K. C., Charvin, G., Bensimon, D., and Croquette, V. (2009) Mechanisms of chiral discrimination by topoisomerase IV, Proc Natl Acad Sci U S A 106, 6986–6991.

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8. Lipfert, J., Hao, X., and Dekker, H. N. (2009) Quantitative modeling and optimization of magnetic tweezers, Biophys. J. 96, 5040–5049. 9. Charvin, G., Strick, T. R., Bensimon, D., and Croquette, V. (2005) Tracking topoisomerase activity at the single-molecule level, Annu. Rev. Biophys. Biomol. Struct. 34, 201–219. 10. Vilfan, I. D., Lipfert, J., Koster, D. A., Lemay, S. G., and Dekker, N. H. (2009) Magnetic Tweezers for Single-Molecule Experiments. in Handbook of Single-Molecule Biophysics p371, Springer. 11. Davidson, M. W., and Abramowitz, M. (2002) Optical Microscopy, in Encyclopedia of Imaging Science and Technology (Hornak, J., Ed.). 12. Inoue´, S., and Spring, K. R. (1997) Video Microscopy : The Fundamentals 2nd ed., Springer. 13. Ovryn, B., and Izen, S. H. (2000) Imaging of transparent spheres through a planar interface using a high-numerical-aperture optical microscope, J. Opt. Soc. Am. A 17, 1202–1213. 14. Bormuth, V., Howard, J., and Schaffer, E. (2007) LED illumination for video-enhanced DIC imaging of single microtubules, Journal of Microscopy 226, 1–5. 15. Wong, W. P., and Halvorsen, K. (2006) The effect of integration time on fluctuation

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measurements: calibrating an optical trap in the presence of motion blur, Opt. Express 14, 12517–12531. Neuman, K. C., Abbondanzieri, E. A., and Block, S. M. (2005) Measurement of the effective focal shift in an optical trap, Opt. Lett. 30, 1318–1320. Kim, K., and Saleh, O. A. (2008) Stabilizing method for reflection interference contrast microscopy, Appl. Opt. 47, 2070–2075. Carter, A. R., King, G. M., and Perkins, T. T. (2007) Back-scattered detection provides atomic-scale localization precision, stability, and registration in 3D, Opt. Express 15, 13434–13445. Nugent-Glandorf, L., and Perkins, T. T. (2004) Measuring 0.1-nm motion in 1 ms in an optical microscope with differential backfocal-plane detection, Optics Lett. 29, 2611. Bouchiat, C., Wang, M. D., Allemand, J. F., Strick, T., Block, S. M., and Croquette, V. (1999) Estimating the Persistence Length of a Worm-Like Chain Molecule from ForceExtension Measurements, 76, 409–413. Baumann, C. G., Smith, S. B., Bloomfield, V. A., and Bustamante, C. (1997) Ionic effects on the elasticity of single DNA molecules, Proceedings of the National Academy of Sciences of the United States of America 94, 6185–6190.

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Chapter 16 Probing DNA Topology Using Tethered Particle Motion David Dunlap, Chiara Zurla, Carlo Manzo, and Laura Finzi Abstract Transcription factors mediate the formation of nucleoprotein complexes that are critical for efficient regulation of epigenetic switches. In these complexes, DNA is frequently bent or looped by the protein; other times, strong interactions lead the DNA to fully wrap the regulatory protein(s). The equilibrium between the bending, looping, full and partial wrapping of DNA governs the level of transcriptional regulation and is tuned by biophysical parameters. Characterization of the structure, kinetics, and thermodynamics of formation of such nucleoprotein complexes is fundamental to the understanding of the molecular mechanisms that underlie the operation of the genetic switches controlled by them. Here, we describe in detail how to perform tethered particle motion experiments aimed at understanding how protein–DNA interactions influence the formation and breakdown of these regulatory complexes. Key words: Tethered particle, DNA looping, Lambda repressor, Brownian motion

1. Introduction 1.1. Tethered Particle Motion

In the context of this chapter, tethered particle motion (TPM) refers to the Brownian motion of microscopic particles tethered by single polymer molecules (usually and hereafter DNA) to a surface. The tether limits the random motion of the particle, and realtime analysis of the magnitude of excursions of the particle from the anchor point reveals changes in the effective tether length. These changes can reflect modifications in the flexibility of the DNA or in the physical length of the DNA, as in the case of topological modifications induced by interacting proteins. Using TPM to explore protein-induced conformational changes in DNA avoids ensemble averaging and can reveal configurational heterogeneities which would be undetected in bulk measurements.

1.2. The Niche for TPM Among SingleMolecule Techniques

The niche for TPM experimentation is defined by the resolution of the analysis to determine the tether length, the acceptable time resolution, and the sensitivity of the topological changes to

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3_16, # Springer Science+Business Media, LLC 2011

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tension in the polymer. Double-stranded DNA is a weak entropic spring that is readily extended by the inertia of a submicroscopic particle undergoing Brownian motion. Relatively simple microscopy and recent theoretical advances are powerful tools with which to analyze the range of Brownian motion to interpret changes in the DNA topology (1). Compared to experiments that require manipulation of the particle, TPM experiments are simple and require only a stable, high-magnification microscope equipped for differential interference contrast and digital video analysis. The TPM technique is limited to observation of the particle’s motion, which requires a few seconds to establish in aqueous, low viscosity solutions. Minimal tension is exerted by the particle on the DNA tether, which remains rotationally unconstrained. Tension can be critical for investigation of certain molecular mechanisms in which even forces in the range of tens of femtonewtons can interfere with the formation of DNA loops (2). At the other extreme, tether length changes on the order of tens of nanometers can be measured for DNA tethers several hundred base pairs in length (1, 3–5). TPM originated in the laboratory of Michael Sheetz to study RNA polymerase (6). However, given that RNA polymerase translocates DNA with considerable force, single-molecule manipulation has proven more advantageous for studies of polymerases (7). Instead, TPM has been used to study more mechanically fragile phenomena such as DNA bending (8, 9) and looping (10–15). 1.3. TPM and the Regulation of Transcription

Protein-mediated DNA bending, wrapping, and looping occur ubiquitously in all organisms for purposes of packaging and transcriptional regulation. Some examples of DNA bends are those induced by the integration host factor (IHF) protein in prokaryotic DNA (16) and by the high mobility group 1 (HMG1) protein in eukaryotic DNA (17). In eukaryotes, histone octamers are well known for binding and wrapping about 147 base pairs of DNA in almost two turns around each octamer (18). Note, however, that it has been hypothesized that most, if not all, DNA binding proteins may have evolved the capability to wrap and thereby organize regions of DNA flanking the consensus binding site (19). Examples of DNA looping are also well known: in eukaryotes in which loops appear to constitute insulator domains (20); in prokaryotes, such as those mediated by the lac (11, 13) and gal (21) repressors; and in bacteriophages, such as the lambda repressor (15, 22). These examples all pertain to transcriptional regulation, but similar conformational changes occur in the regulation of most DNA transactions, such as replication, recombination, etc. Therefore, characterization of the kinetics and thermodynamics of the formation of these nucleoprotein complexes, as well as their structure and stoichiometry, is paramount to understanding their regulatory function.

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2. Materials 2.1. Stock Solutions

All reagents were purchased from Thermo Fisher Scientific (Waltham MA) and can be stored at 4
C unless stated otherwise. 1. 0.015 mg/ml a-casein (Sigma-Aldrich, St. Louis, MO). a-casein is not highly soluble in PBS but a 1–2% solution can be prepared. Store it at 4
C. 2. 1 M DTT. Store it at 20
C. 3. 0.5 M EDTA. 4. 10 Phosphate-buffered saline (PBS). 5. 3 M Potassium chloride. 6. 1 M Tris–HCl pH 8.0. 7. DMSO. 8. Molecular biology grade water. 9. Ethanol 99%.

2.2. Producing DNA Tethers Using PCR

1. 1 mg/ml pDL1051 plasmid DNA (available upon request). 2. 10 mM 50 -biotin-(C6)-forward primer (50 -cgcaattaatgtgagttagctcactcattaggcaccccaggc-30 (see Note 1); Integrated DNA Technologies, Coralville, Iowa) in 10 mM Tris–HCl pH 8.0. 3. 10 mM 50 Digoxigenin NHS Ester of reverse primer (50 -gcattg cttatcaatttgttgcaacgaacaggtcactatcagtc-30 (see Note 1); Integrated DNA Technologies) in 10 mM Tris–HCl pH 8.0. 4. Taq polymerase and 10 Standard Taq buffer (New England Biolabs, Ipswich, MA). 5. 6 mM dNTP mix. 6. MinElute PCR Purification Kit (Qiagen, Hilden, Germany). 7. Tubes for thermocycling. 8. Thermocycler.

2.3. Preparing Tethered Beads

1. 40 mg/ml Biotinylated-BSA (Sigma) in PBS. 2. 50 mg/ml Streptavidin (Sigma) in PBS (Store it at 20
C). 3. Antidigoxigenin-coated polystyrene microspheres (480 nm; Indicia Diagnostics, Oullins, France; see Note 2).

2.4. Flow Chamber Assembly

1. Kimwipe tissues. 2. Vacuum grease. 3. Syringe with cut micropipette tip for application of grease to glass. 4. 24  40 (or 24) mm No. 1 coverslips.

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5. Microscope slides. 6. Ethanol to clean microscope slides and coverslips. 7. Double-sided tape with backing on one side. 8. Scissors to cut tape. 9. Ceramic coverslip rack (Thomas Scientific, Swedesboro, NJ, part no. 8542E40). 10. Shandon Vertical or Horizontal Staining Jar. 11. Measurement buffer: 10 mM Tris–HCl pH 8.0, 0.1 mM EDTA, 200 mM KCl, 5% DMSO, 0.2 mM DTT, and 0.01 mg/ml a-casein. 12. Wash buffer: 10 mM Tris–HCl pH 8.0, 0.1 mM EDTA, 200 mM KCl, and 0.01 mg/ml a-casein. 13. A pipette tip box with wet tissue in the bottom to be used as a humid incubation box for the flow chamber. 2.5. Microscope Operation

1. Upright DM LB2 microscope (Fig. 1; Leica Microsystems GmbH, Wetzlar, Germany). 2. 100 1.2–1.4 numerical aperture, oil-immersion objective (Leica). 3. Differential interference contrast optics (Leica). 4. 1.4 NA oil-immersion condenser (Leica). 5. CV-A60 video camera (JAI, Copenhagen, Denmark).

Fig. 1. An upright Leica microscope used for tethered particle motion experiments. The small CCD camera is mounted on a 1 coupler attached to the trinocular.

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1. Pentium III or faster computer. 2. LabView (National Instruments, Austin, TX). 3. IMAQ Vision (National Instruments). 4. PCI-1407 frame grabber (National Instruments). 5. MatLab, version R2006b (MathWorks, Natick, MA) for tether length analysis. 6. Custom routines for tether length analysis (Finzi laboratory Web page, http://www.physics.emory.edu/faculty/finzi/).

3. Methods 3.1. Producing DNA Tethers Using PCR

1. Mix the following in a thin-walled thermocycler tube: Reagent

Concentration

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2. Set the thermocycler to execute the following sequence: Step

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C)

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3. Purify PCR product with Qiagen PCR cleanup kit according to manufacturer instructions. Elute in 50 ml of 10 mM Tris–HCl pH 8.0. Gel electrophoresis in 1% agarose in TAE should show a band at 2210 base pairs (Fig. 2).

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Fig. 2. Gel electrophoresis of the PCR product using the indicated primers and plasmid template. Marker DNA bands shown on the left show that the PCR product migrates with a molecular weight between 2,000 and 2,500 base pairs as expected.

3.2. Flow Chamber Assembly

1. Wash the microscope slide and the coverslip thoroughly with ethanol and dry (see Note 6). 2. Cut two, 1 in. pieces of double-sided tape and place along the long edges of the slide. Using the syringe filled with vacuum grease deposit lines of grease to make a channel just inside the tape. The channel does not need to be wide, because there will be plenty of beads for observation along the length of it (see Fig. 3). 3. Peel the backing tape from the double-sided tape. Center the coverslip on the slide and press it down, flattening (and spreading) the grease until the coverslip adheres to the tape. The channel narrows significantly as the grease encroaches. 4. Deposit lines of grease across the ends of the channels and across the short edges of the coverslip to create hydrophobic dams to contain solutions.

3.3. Preparing Tethered Beads

1. To deposit biotin sparsely on a coverglass, prepare 50 ml of a 40 mg/ml solution of Bio-BSA in PBS. Draw the solution into the microchamber and incubate for at least 2 h in the refrigerator in the humid box to avoid evaporation. 2. Meanwhile, link DNA to antidigoxigenin-coated beads. First, dilute the DNA after the PCR cleanup 1:1,000 in TE and mix 1 ml of diluted DNA with 39 ml of antidigoxigenin-coated

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Fig. 3. A microchamber formed with tape spacers (dark ) and filled with dye (shaded ) was assembled for illustration. At the upper left end there are grease dams on the slide and across the coverslip to contain the solution. At the lower right end lines of grease form a channel that narrows considerably under the coverslip pressed into the grease.

beads diluted 1:50 in wash buffer without DMSO or DTT. The ratio may require adjustment depending on the yield of DNA from the PCR. Incubate the DNA–bead mixture on ice for an hour. 3. Wash the chamber. Twist to roll up each corner of a Kimwipe. Place the twisted end in contact with the solution at the exit of the chamber to draw 400 ml of wash buffer through the chamber (see Note 7). 4. Then, link streptavidin to the BSA-biotin on the coverslip. Prepare 50 ml of a 50 mg/ml solution of streptavidin in PBS. Draw the solution into the microchamber and incubate for 15 min at room temperature in the humid box. 5. Wash the chamber (see above). 6. To tether the DNA–bead assembly in the chamber, draw 40 ml of bead-labeled DNA into the chamber and incubate at room temperature for 15 min to 1 h. 7. Gently wash the chamber with 4–5 volumes of measurement buffer before observation. 3.4. Microscope Operation

1. At least 1 h before observing tethered beads, switch on the microscope lamp with oil on the objective if necessary. This allows the microscope to equilibrate thermally before beginning observations and will significantly reduce drift (see Note 8). 2. When the tethered beads are ready, switch on the video camera and activate the software (next section).

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Fig. 4. A representative field of view shows 480 nm diameter microspheres tethered to a coverslip by DNA molecules.

3. Place the sample on the stage, bring the objective to focus on the beads, and then focus and align the condenser. 4. Select a field in which there are at least six vigorously moving beads (Fig. 4). Appropriate beads for data collection should all be randomly moving about an anchor point, but even immobile beads can and should be used to correct the drift if less than six mobile beads are visible. 3.5. Particle Tracking

1. Activate the program “Measurement and Automation” to set the image acquisition parameters. Select “Devices and Interfaces,” select NI-IMAQ devices, select the relevant camera channel. Check that the field/frame windows mode is set to “frame” and that “first field” is odd. Click save and exit the program. 2. Activate the program JAI A-S to set the video camera. 3. Click the first icon to open a window and confirm that the scan mode is set to “interlaced full frame, accumulation frame” and that the shutter speed is 1/1,000 (1 ms). 4. Click on the second icon to open another window and select “synchronize” to initialize the camera. 5. Activate the Particle-Tracking virtual instrument (VI) to select the beads and record data. 6. The Particle tracking VI opens a live display from the camera (Fig. 4) and a control window from which one can activate a region of interest (ROI) in which to track beads and select a directory in which to save text files containing the sequences of coordinates. 7. Choose a directory/filename for the collected data.

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8. Activate a region of interest in the control window. A small, square icon will appear in the live display which can be resized and moved to position it around a bead. Click “done” to confirm the positioning/sizing and a sequence of coordinates should begin to display in the control window associated with that ROI. 9. When all ROIs have been activated and positioned, switch on “Save data” in the control panel and record the motion of the control beads for 10 min (see Note 9). 10. At the end of the 10 min, switch off “Save data,” select “Stop” to interrupt tracking, and set a new filename for the experimental data to follow. 11. Change solutions to create the experimental conditions and reactivate the live display. Reposition the tracking ROIs around the beads which may have shifted slightly during solution exchange. 12. When all ROIs have been positioned, switch on “Save data” in the control panel and record the motion of the experimental beads for about 30 min. 13. Switch off “Save data,” select “Stop” to interrupt tracking, and set a new filename for the next experiment. 3.6. Tether Length Analysis

1. MatLab routines are used to analyze the text files with list of coordinates produced by the Particle Tracking VI. Locate the MatLab routine for analysis of control data, “controls_ filtrect4_50hz.m.” Execute this routine and begin by selecting a text file of coordinates for analysis in the “File selector” window. The coordinate are read and displayed in a panel as shown in Fig. 5.

3.6.1. Selection of Beads for the Drift Calculation

1. The analysis routine then produces xy plots of the positions determined for individual beads throughout the entire recording (Fig. 6). At this point the user should select beads that appear to have dense, perhaps slightly elongated, clouds of xy coordinates that will be used to calculate the drift. Irregular clouds of coordinates may indicate multiple tethers or intermittent adhesion to the slide and should be excluded from the calculation of the drift. However, the drift correction will be applied to the coordinates for all beads, and later, portions of sequences for asymmetric clouds of coordinates may be salvaged for analysis by excluding time intervals with obvious problems. 2. The positions of the individual beads oscillate rapidly about their respective anchor points. Usually, due to mechanical instability of the microscope, these anchor points also appear to slowly drift. To correct this artifact, the average position of

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3

3 1 y position (nm)

2.5

2 4 1.5

1

0.5

5 0.5

1

1.5

2 2.5 x position (nm)

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4 x 104

Fig. 5. An overlay plot of the xy positions determined for all tracked beads in a field of view before correction for drift. Tracking produces a tight group of recorded positions for each bead (see also Fig. 16.6).

the entire group of beads filtered with a time window (40 s; Fig. 7) is subtracted from the time trace of each bead. 3.6.2. Symmetry Test

1. After subtraction of the drift determined for the entire group from the motion of each individual bead, the corrected distributions of the x and y positions about their average values are presented for each bead so that the user can judge the symmetry of the scatter and accept or discard each bead. Acceptable tethers exhibit very symmetric, broad distributions, and any beads with asymmetric distributions should be discarded. 2. Portions of the data corresponding to discarded beads may be salvaged in a later step, in which the user may eliminate any intervals distorted by transient adhesion or momentary tracking failures due to material drifting through the field of view (Fig. 8). This truncation is sufficient to restore the data to a broad, symmetric distribution about the centroid as shown in Fig. 9.

3.6.3. Average Tether Length

Finally a 4-s moving average of the xy displacements of each bead from the anchor point is calculated and displayed for each bead above a histogram of the values (Fig. 10). This data should oscillate about a mean value that can be accurately predicted theoretically (1, 2, 23) (see Note 10). Figures depicting the data for each bead are automatically saved in the active folder while the

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Fig. 6. An overlay plot of xy positions determined for two individual beads in a field of view before correction for drift. (a) One bead had quite symmetric clouds of coordinates, but another bead (b) had a slightly asymmetric distribution of x positions and was discarded from the drift calculation.

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a 2.72

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2.67

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b 2.38

x 104

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y position (nm)

2.36 2.35 2.34 2.33 2.32 2.31 2.3

0

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Fig. 7. x (a) and y (b ) of the average position determined for the entire group of tracked beads vs. time (points ). The drift curves (lines ) are obtained by time filtering the data with a 40 s window.

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x position (nm)

x 104 3.55 3.5 3.45 3.4 0

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Fig. 8. After drift correction, x (upper ) and y (lower ) position versus time data show the Brownian motion along the x and y axis observed for the bead in the lower panel of Fig. 16.6. Near 410 s, the x positions suddenly shift toward one side. In addition, during a brief interval near 560 s the bead adhered to the coverslip.

probability

0.03 0.02 0.01 0 −1000

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−600

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−200 0 200 y position (nm)

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probability

0.03 0.02 0.01 0 −1000

Fig. 9. The probability distribution for the x (upper ) and y (lower ) positions for the bead in the lower panel of Fig. 16.6 after exclusion of the data between 410 and 600 s. These broad distributions extend symmetrically from the centroid.

corresponding data is recorded in a separate MatLab matrix file. An Excel format file is created containing the average and standard deviation xy excursions corresponding to the unlooped states for each bead.

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<ρ> (nm)

400 300 200

μ = 337.3

σ = 31.4

100 0

50

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200 time (s)

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counts

0.06 0.04 0.02 0 260

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Fig. 10. A 4-s moving average (gray ) of the xy excursions of the bead away from the anchor point for the bead in the lower panel of Fig. 16.5 after exclusion of the interval with shifted x coordinates. The mean value for the entire trace is 337.3 nm (dotted line ) with a standard deviation of 31.4 nm (dashed line ).

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Fig. 11. Upper : The time average xy excursion of the bead about the tether point switches between two states when 100 nM CI protein is present. The moving average (dark points ) intermittently switches between excursion values corresponding to looped (dark gray ) and unlooped (light gray ) states. The dotted lines represent average excursions bounded by standard deviations indicated by dashed lines. Transitions between these states are identified using a threshold crossing algorithm (broad light gray) and refined by retaining only states that endure longer than the dead time of the filter (thin black line, overlaid on all but one of the broad gray steps ). Lower: A histogram of xy excursion amplitudes observed for the tethered bead during the entire recoding of almost 1,600 s clearly reveals two predominant excursion amplitudes which were fit using two Gaussians (curve).

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1. The analysis of the xy excursions of tethered beads in the presence of proteins such as the lambda CI repressor, which induces the formation of loops in the DNA, proceeds in a similar fashion. 2. However, this routine, “experiment_filtrect4_50Hz.m,” can also furnish estimates of average excursion amplitudes in the data (Fig. 11). If a bimodal distribution is observed, the operator can choose to perform a double-Gaussian fit. From the fit-determined mean values of the distribution, the routine automatically calculates a half amplitude threshold and performs an analysis of the dwell times spent in each configuration. Dwell times shorter than the filter dead-time (half of the time-window duration) are successively discarded (24, 25) (see Note 11). As for the control beads, figures with data for the experimental beads are automatically saved, and the values of the means, standard deviations, and dwell times are appended to the Excel file created during analysis of the control beads.

4. Notes 1. Primers should have strong hybridization (GC-rich) at the 30 -end from which extension must proceed. Many researchers select primers with G and/or C as the final two bases. Primers should also be selected to minimize intramolecular hairpins and intermolecular pairing that would interfere with hybridization to the template strands. There are programs for predicting hybridization that might interfere and they are useful for discarding undesirable base pairing. In practice, these predictions are not always accurate and several primer pairs for a given template sequence may need to be screened to optimize the yield. 2. The size of microspheres can affect the experiment in two ways. First, larger microspheres will experience significant hydrodynamic drag and move slowly. Thus, they will require more time to adequately explore the available hemisphere of motion determined by the tether length and the time resolution will decrease slightly (26). Second, bulky labels attached to the end of a DNA molecule will limit the motion of the end and effectively stretch the DNA through an entropically generated force (2). 3. During the annealing step the short, usually 18–24 base pair, primers quickly locate complementary sites on the template strands. However, the longer, slower template DNA can ultimately form a more stable hybrid and might displace the

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primers if the annealing interval is too long. 15–30 s is usually sufficient for annealing. 4. The annealing temperature should be low enough to promote hybridization of the forward and reverse primers to the template. The annealing temperature depends on the primer sequence. A productive temperature is usually 5–10
C below the lowest melting temperature (Tm) of the two primers. A rough guess can be made using Tm ¼ 2  NAT þ 4  NGC ; where NAT and NGC are the numbers of A-T and G-C base pairs, respectively, in the duplex formed by the primer and the template. 5. The elongation interval should be long enough to allow polymerases to complete complementary strand synthesis. As a rule of thumb, thermostable polymerases will require 1 min to polymerize 1,000 base pairs. 6. To more thoroughly clean glass surfaces, one can use one of the following methods: Plasma cleaning (11) Acid washing: In a fume hood, heat several coverslips in a loosely covered glass beaker of 1 M HCl at 50–60
C for 4–16 h. Allow them to cool to room temperature and wash coverslips extensively in distilled H2O, then rinse in doubledistilled H2O. Rinse coverslips in ethanol and separate them between sheets of Whatman paper to dry. Store the clean coverslips for as long as a year in a clean, dry tissue culture dish. Washing organic solvents: Place slides and coverslips in ceramic or metal racks (slotted Copeland jars work well for slides) and place the rack in a glass vessel. Fill the vessel to submerge the slides and coverslips in xylene and agitate gently for 30 min. Drain the xylene and replace with acetone and agitate for 30 min. Drain the acetone and replace with ethanol and agitate for 30 min. Store the slides and coverslips in ethanol. Dry with a stream of dry gas or by burning off the residual ethanol. 7. A Kimwipe wicks solution rapidly just after contact and then slows down as the tissue becomes saturated. To produce gentle flow rates, use a thin, highly twisted Kimwipe that is already wet with the buffer. 8. Research-grade microscopes have been designed to minimize vibration, but for tethered particle tracking, the microscope should be further isolated from vibration. A heavy table top (stone or steel) resting on elastic rubber pads is sufficient isolation, but tables with active vibration damping can also be used. When linearly responsive elastic elements are

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compressed to about one half of the operational range, the resonant frequencies transmitted to the microscope will be minimized. 9. Experiments require control and experimental traces for the same beads. If a bead breaks free or eludes the tracking program, for example when a freely diffusing bead drifts through the scene, it may be best to continue tracking the remaining beads. However, if the measurement has just started, interrupt the tracking and start again. 10. Since an interlaced camera updates odd and even rows of the CCD alternately at the stated frame rate, images of fast moving beads may be slightly blurred if even and odd frames are combined for processing. Blurring tends to reduce the apparent amplitude of excursions about the anchor point. Instead, sequences of even (and odd) frames may be analyzed separately with no blurring provided the pixel density oversamples the image of the bead. 11. To analyze traces showing changes in amplitude with time resolution higher than the one provided by the time filtering/ thresholding method, an alternative approach has been devised (27) based on a previously published method for temporal sequences exhibiting discrete jumps in intensity (28). First, a generalized likelihood ratio test is used to establish time points at which the amplitude of the excursions changes significantly. Recursive application of the test to an entire sequence of excursion data identifies all probable transitions between different excursion amplitudes. Then expectation-maximization clustering and the Bayesian information criterion are used to estimate the number of states accessible to the system and refine the selection of time points at which the amplitude changes. This procedure allows objective and quantitative determination of transitions between different tethered states in a model-independent way and without the artificial time-resolution limitations that arise from filtering and thresholding.

Acknowledgments We acknowledge Doriano Brogioli who adapted the Particle Tracking VI from code available from National Instruments libraries. We are grateful to Phil Nelson and John Beausang for strategies with which to filter instrumental drift from the data, as well as to Qing Shao for an image of the PCR product.

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INDEX A Actin-binding protein ..................................................237 Alexa .......................... 87, 102, 103, 105, 106, 109, 228 Atomic force microscopy (AFM) ..............................4, 21, 197–211, 213, 233–249, 251–255, 260–262, 265 ATTO, 102, 103, 108, 110–113 Autocorrelation .......................................... 150, 151, 182 Avalanche photodiode (APD) .................89, 92, 97, 187

B Bacteria ........................................................... 2, 140, 216 Bacteriophage ............................................. 251, 261, 296 Bead ................. 1, 22, 46, 64, 121, 143, 228, 266, 297 Biotin .......................... 26, 49, 59, 66, 71–73, 116, 132, 218, 227, 267, 282–284, 291, 300, 301 Brownian motion ....6, 12, 34, 278, 295, 296, 307, 309 Budding yeast .................................................................64

C Calibration.................................. 6–8, 11, 22, 23, 30–37, 39, 42, 46, 57, 58, 78, 188–191, 254, 257, 260, 277–280, 282, 291 Cantilever.......................................... 198–203, 205, 206, 208–210, 229, 230, 234–236, 240–242, 244–246, 252–257, 260, 261 Capsid ...............................251, 255, 257, 258, 260, 261 Caulobacter crescentus .........................................140, 141 Charge coupled device (CCD)...................... 26, 30, 35, 48, 78, 90, 92, 94, 97, 143, 163, 164, 170, 174, 266, 269, 272, 274, 276, 298, 311 Cleaning of glass ........................................ 126, 284–285 Coiled-coil-engineering ...............................................234 Confocal fluorescence .......................................88, 91–92 Contact mode.......201–203, 205–207, 209, 215, 229, 254 Corner frequency .........................................................6, 7 Correlator ................................................... 184, 185, 187 Cover slip................................................................. 23, 27 Cysteine-engineering ........................ 234, 239–240, 248 Cystein light ............................................... 104–109, 111 Cysteine-reactive ..........................................................105

D Data analysis ............. 24, 26, 37, 38, 40, 165, 171–173, 186, 188, 192, 193, 235, 245, 255, 270

Deposition of DNA................................. 219, 221–222 Deposition of proteins ........................................ 219–224 Dichroic mirror ...................... 89, 91, 92, 144, 271, 274 Dictyostelium discoideum filamin (ddFLN).......235–238, 242–245, 248, 249 Diffraction limit ........................................ 64, 88, 91–94, 96, 140, 144, 153, 159, 229 Diffusion...................................7, 75, 95, 122, 145–148, 151, 155, 177, 182–186, 188, 193 Digoxigenin........................... 22, 23, 26–29, 49, 50, 53, 59, 60, 218, 267, 282–285, 291, 297 DNA looping ...............................................................296 DNA-protein interactions ..........3, 15, 18, 46, 159, 209 DNA unzipping....................................................... 45–60 Drag force.................................................................. 6, 11 Drift .......................... 11, 16, 24, 25, 30–32, 34–36, 38, 42, 45, 49, 57, 58, 133, 134, 143, 156, 177, 240, 241, 244, 247, 262, 280, 281, 301–307, 311 Dye......................................... 71, 83, 85–87, 89, 94, 96, 102, 103, 105, 107–111, 113, 117, 118, 162, 163, 169, 170, 188, 192, 228, 301 Dynamic light scattering (DLS) ..................................181 Dynamic modes (DMs) .................... 205, 206, 208, 210 Dynein .............................................................63–79, 121

E Electron-multiplying charge-coupled detector (EMCCD)................... 122, 143, 144, 163, 164, 193, 216 Excited state ......................................................82, 83, 96 Expression .................. 67, 68, 104, 107, 113, 119, 148, 183, 185–186, 190, 213, 234, 237–239 Extinction coefficient .............................................. 84–87

F Fast Fourier transform (FFT)............................. 277–279 Feedback ................................ 13, 46, 64, 67, 74, 76–78, 198, 199, 201–203, 205, 206, 210, 211 Filamin ..........................................................................235 Flow cell................................. 11, 23, 28–29, 42, 74, 75, 126, 127, 266–269, 274, 280, 284–287, 291 Fluorescence correlation spectroscopy (FCS) .............90, 92, 102, 181–195 Fluorescence quantum yield .............................84–86, 96

Erwin J.G. Peterman and Gijs J.L. Wuite (eds.), Single Molecule Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 783, DOI 10.1007/978-1-61779-282-3, # Springer Science+Business Media, LLC 2011

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INGLE MOLECULE ANALYSIS 316 || SIndex

Fluorophore ............................... 71, 83–91, 93–97, 101, 102, 104, 108, 121, 122, 128, 132, 141, 143, 152, 153, 174, 192, 227, 228 Force detection ............................................ 8, 11–13, 47 Force spectroscopy...........3, 15, 16, 174, 234, 251, 265 Fo¨rster resonance energy transfer (FRET).................. 96

G Green fluorescent protein (GFP).................. 66, 68, 69, 73–74, 85–87, 101, 104, 113–115, 121–123, 125, 128–130, 132–135, 236 Ground state............................................................ 82, 84

H Hairpin.........................................26, 47, 49, 51, 55, 309 Helicase...........................................................................46 Histidine tag .................................................................237 HOP2/MND1............................................... 104–107 hSSB.............................................................. 108–111

I Image analysis............................128–130, 215, 216, 225 Internal conversion ........................................................82 Intersystem crossing.......................................................82

J Jabłon´ski diagram...........................................................82 Jumping mode .................................. 209, 254, 258, 260

K Kinesin ......................................... 3, 63, 95–97, 121–135

L Labeling ................67, 71, 87, 101–119, 121, 130, 140, 154, 169–170, 177, 188, 227 LabView.......................................32, 216, 272, 277, 299 Lambda repressor .........................................................296 Laser.................... 1, 2, 5–17, 23, 25, 30–33, 35, 46–48, 53, 54, 56–59, 64, 78, 84, 88, 89, 91–93, 96, 122, 128, 134, 135, 143, 153, 167, 173, 186–190, 199, 200, 228, 252, 262, 271, 272, 274, 276, 280–282, 290 Light emitting diode (LED) ...................... 88, 268, 269, 273–277, 291 Linker............................................... 49–52, 55, 108, 282 Live-cell imaging ..........................................................140 Lysin light................................................... 104, 108–113 LZ10.............................................................. 238, 239

M Magnetic tweezers........................................ 13, 265–292

Maleimides................. 87, 104–106, 108, 109, 116, 117 Mass spectrometry ................... 106, 108, 111, 118, 119 Matlab............... 75, 129, 130, 165, 188, 299, 303, 307 Mica ..........................206–209, 214–224, 226–230, 260 Microfluidics............................................................ 11, 17 Microparticle ......................................................... 10, 259 Microscope objective ....................... 5, 8, 25, 33, 42, 56, 90, 91, 133–135, 156, 183, 189, 190, 193 Microscopy ....................................... 2, 8, 11, 14, 15, 17, 21, 56, 63, 83, 84, 86, 88–94, 121–123, 126, 128, 139, 140, 143, 145–147, 152, 155, 159–178, 192, 197–211, 213, 216, 217, 228, 233–249, 251, 260, 262, 265, 296 Microtubules (MTs).................................... 3, 63–66, 68, 71–73, 75–78, 93, 121–135 Molecular motors.....................................12, 18, 64, 121 Motility assay ................................................................121 Motor protein ..............................3, 16, 63, 95, 97, 121, 128, 130, 133, 145 MreB...................................... 140, 141, 144, 148–155

N Nanochannels ...................................................... 159–178 Nanoindentation ........................................ 209, 251–263 Numerical aperture (NA) ........................... 8–10, 13, 15, 25, 64, 78, 90, 91, 93, 134, 143, 163, 172, 183, 186, 216, 269–271, 275, 298

O Optical filter....................................................................89 Optical trap.............................1, 2, 4–17, 21–42, 45–60, 63, 66–68, 74–76, 78, 121, 244 Optical tweezers ....................... 1–18, 21–26, 30–35, 39, 41, 42, 45, 58, 64, 174, 265

P Particle tracking .............................30, 36, 95, 266, 277, 299, 302–303, 310, 311 Phosphorescence ............................................................82 Photoactivated localization microscopy (PALM) .......17, 87, 152, 154, 155 Photobleaching .........................................85, 88, 92, 93, 95, 96, 102, 132, 134, 142, 144, 146, 151, 152, 154, 155, 161, 171, 174, 185, 192 Photodamage ...............................................................2, 9 Piezo .................................................. 23, 24, 30, 32, 33, 35, 38, 92, 156, 201–203, 206, 240, 241, 246, 252, 256, 257, 262, 270 PleC, 140, 141, 144–147, 155 Point spread function (PSF) ...................91, 95, 96, 129, 140, 144, 152, 153, 171, 177, 183, 187, 192 Polarization of fluorescence...........................................96

SINGLE MOLECULE ANALYSIS | 317

Index |

Polymerase...................................4, 16, 46, 47, 50, 207, 208, 267, 282, 283, 296, 297, 299, 310 Poly-protein......................234, 236–240, 242, 245, 248 PopZ .................................140, 141, 144, 147–149, 155 Position detection .................................... 12–13, 35, 281 Protein quantification ....................................................72 Protein refolding ..........................................................246 Protein unfolding................................................ 233–249

Q Quantum dot (QDs) ...........................85–87, 116, 119, 123, 125, 129, 135, 143, 228, 230

R RAD51..................................................... 94, 107, 222 Radiation pressure............................................................ 4 RecA.............................................................. 111–113 Regulation of transcription..........................................296 Resolution ............................ 11, 12, 14, 16, 18, 30, 63, 89–92, 94, 96, 123, 128, 134, 135, 139–156, 159, 160, 172–174, 187, 198, 200, 201, 203, 207, 215, 224, 229, 230, 234, 244–247, 255, 262, 275–277, 281, 282, 295, 309, 311 Rhodamine–6G (R6G)........................................ 83–87 RNA/DNA handle ...........................................22, 26–27 RNA/DNA hybrid ....................... 23, 26–29, 31, 34–38 RNA/protein interactions .............................................46 RNA pseudoknot .................................................... 37, 40 RNA unfolding........................................................ 35–36 RPA........................................................ 104, 113–115

S Saccharomyces cerevisiae................................................... 64 Scanning force microscopy (SFM)................... 213–230 Signal to noise ratio (SNR) ................12, 163, 184–185, 193, 200 Silanization ................................................. 126–127, 131

Silica wafer .................................................. 160, 166, 167 Spring constant ........................6, 23, 26, 30, 31, 34–36, 38, 39, 42, 200, 202, 229, 242, 254, 257, 258 Stall force ...........................................................67, 75–76 Streptavidin.............23, 27, 29, 41, 53, 59, 60, 75, 116, 119, 123, 125, 129, 135, 218, 227, 267, 282, 286, 297, 301 Succynimidyl esters ........................................................87 Superlocalization ..........................................................140 Superresolution ............................................ 87, 139–156 Surface passivation ............................ 124, 126–128, 132

T Temperature control ......................................................11 Tether............................... 16, 23–26, 28–36, 38, 39, 41, 148, 267, 278–280, 282, 285, 287, 295–311 Tethered particle motion .................................... 295–311 Titin ................................................... 235, 243, 248, 249 Topology ........................................... 266, 288, 295–311 Total internal reflection fluorescence microscopy (TIRF)........ 81, 91–93, 121–123, 126, 128, 134 Tracking ...........................12, 30, 36, 95, 123, 129–130, 134, 135, 147, 149, 152, 266, 268, 273–282, 299, 302–304, 310, 311 Trap stiffness..........................5–8, 12–14, 34, 55, 74–78 Triplet state............................................................ 82, 102 Twist ..........................................280, 287–288, 301, 310

V Virus..................................2, 40, 41, 208, 209, 251–263

W Wide-field epifluorescence .................................... 92, 143

Y YOYO ......................................................... 162, 169, 170