Protein Biosynthesis

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PROTEIN BIOSYNTHESIS No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

PROTEIN BIOSYNTHESIS

TOMA E. ESTERHOUSE AND

LADO B. PETRINOS EDITORS

Nova Biomedical Books New York

Copyright © 2009 by Nova Science Publishers, Inc.

All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Available Upon Request

ISBN: 978-1-61470-704-2 (eBook)

Published by Nova Science Publishers, Inc. New York

CONTENTS

Preface

vii

Chapter I

Protein Synthesis and Ageing Kostoula Troulinaki and Nektarios Tavernarakis

Chapter II

Neuropeptide Biosynthesis in the Nematode Caenorhabditis elegans: From Precursor to Bioactive Peptides Steven J. Husson and Liliane Schoofs

13

Stereochemical Mechanism of Translation Based on Intersubunit Complementarities Kozo Nagano

23

Chapter III

1

Chapter IV

Trans-Translation of tmRNA and a Protein Mimicking tRNA and mRNA Hyouta Himeno, Daisuke Kurita, and Akira Muto

Chapter V

Modification of mRNA Translation Initiation to Stimulate Protein Synthesis in Sepsis Thomas C. Vary

Chapter VI

Protein Synthesis in Hepatocytes of Mice as Revealed by Electron Microscopic Radioautography Tetsuji Nagata

Chapter VII

Recent Advances in Label-free BiosensorsApplications in Protein Biosynthesis and HTS Screening Shawn O’Malley

163

Translating Memories: The Role of Protein Biosynthesis in Synpatic Plasticity Cara J. Westmark and James S. Malter

195

Chapter VIII

vi Chapter IX

Contents Secreted Protein and Peptide Biosynthesis: Precursor Structures and Processing Mechanisms Sergey A. Kozlov, Alexander A. Vassilevski and Eugene V. Grishin

Chapter X

The effects of temperature on ectotherm protein metabolism Nia M. Whiteley and Keiron P. P. Fraser

Chapter XI

Protein Biosynthesis:A new Method for Functional Expression of Sodium-Dependent Glucose Transporter (SGLT) to Study Inhibition of Transport Activity and Drug Discovery Francisco Castaneda

Chapter XII

Chapter XIII

Index

Effect of Hypoxic Conditions on Translational Control of Gene Expression Ota Fuchs The Role of Eukaryotic Translation Intiation Factor 4E and its Binding Factors 4E-BP1 and 4E-BP2 in Body Weight Regulation, Ageing and Tumorigenesis Ota Fuchs

225 249

267

285

307 331

PREFACE Protein biosynthesis (synthesis) is the process in which cells build proteins. The term is sometimes used to refer only to protein translation but more often it refers to a multi-step process, beginning with amino acid synthesis and transcription which are then used for translation. Protein biosynthesis, although very similar, differs between prokaryotes and eukaryotes. This new book presents important research in the field from around the globe. Chapter I - Protein synthesis is an essential cellular process affecting growth, reproduction and survival in response to both intrinsic and extrinsic cues such as nutrient availability and energy levels. Studies in many organisms, including humans, have revealed that during ageing, the rate of global protein synthesis declines, indicating a link between the regulation of protein synthesis and the ageing process. Recent studies in C. elegans demonstrate that depletion of specific translation initiation factors, such as eIF4G, eIF2B and eIF4E increases lifespan. Similarly, depletion of specific ribosomal proteins increases lifespan both in yeast and worms. In all cases, these manipulations reduce the rate of general protein synthesis. Why does attenuation of protein synthesis promote longevity? The process of mRNA translation is one of the most energy consuming cellular processes, requiring, depending on growth conditions, up to 50% of the total energy generated by the cell. A reduction of protein synthesis would moderate this energy load, generating an energy surplus, which can be channeled to mechanisms of damage repair and cellular maintenance, thus, extending lifespan. In addition, lowering protein synthesis may be beneficial during ageing by reducing the accumulation of altered, misfolded, aggregated or damaged proteins, as it occurs in many age-related pathologies, such as Alzheimer’s and Parkinson’s disease. The recent experimental findings reveal a key role for protein synthesis in ageing and suggest that perturbation of mRNA translation provides an effective approach for interventions aiming to modulate ageing and senescent decline. Chapter II - Endogenous neuropeptides are small signaling molecules that occur in all metazoan species. They function as neurotransmitters or hormones and orchestrate a wide variety of physiological processes by binding G protein-coupled receptors upon initiation of diverse signaling pathways. Over 115 neuropeptide-encoding genes appear to be present in the soil nematode Caenorhabditis elegans. The biosynthesis of these endogenous biologically active peptides involves a series of enzymatic processing steps, starting from a preproprotein. First, the signal peptide is removed and the remaining part of the precursor will be cleft by

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proprotein convertases at defined motifs displaying basic amino acids. Next, carboxyterminal basic amino acids are removed by the action of a carboxypeptidase. Finally, the carboxyterminal glycine (if present) will be transformed into an amide. A peptidomics platform, which uses state-of-the-art liquid chromatography combined with mass spectrometry, allows us to biochemically identify endogenous peptides present in any tissue or organism. This technology was used to compare the peptide profiles of C. elegans strains having mutations in the presumed peptide precursor processing enzymes. Doing so, we were able to characterize the major processing enzymes KPC-2/EGL-3, CPE/EGL-21 and the chaperone protein 7B2/SBT-1. Chapter III - A universal rule is found in nucleotide sequence complementarities between the regions 2653-2666 in the GTPase binding site of 23S rRNA and 1064-1077 of 16S rRNA as well as between the region 1103-1107 of 16S rRNA and GUUCG (or GUUCA) of tRNAs. This means that there are two extreme cases of conformational states between the above regions. One is responsible for GTP hydrolysis, and the other plays an important role in the structural transitions, particularly for activation of three tRNAs bound to A, P, and E sites in the proofreading step of codon recognition, and in the process of translocation. In order to understand the mechanism of the conformational change, the present author assumed that four kinds of GTPases, viz. aminoacyl-tRNA•EF-Tu•GTP ternary complex, EF-G•GDP complex, peptide chain release factor 3 (RF-3), and initiation factor 2 (IF-2), first binds to the cavity region on the 30S ribosomal subunits, where it is known that an antibiotic spectinomycin binds. Amino acid sequence comparison of effector region for the above four GTPases has shown why the first three GTPases unfolds the region around helix 35 of 16S rRNA and goes to the GTPase- associated region on the 50S subunit, while IF-2 promotes binding of initiator tRNA to the 30S subunit. On the other hand, the crystal structure of the whole ribosome binding three deacylated tRNAs (PDB accession number 1GIX) has shown that the three elbow regions of the tRNAs are distantly separated from each other, resulting in difficulty in explaining the negative cooperativity between A- and E-site tRNAs. Moreover, the existence of a barrier region at the nucleotides G1338 and A1339 of 16S rRNA presents a difficulty in understanding how codon recognition and translocation could occur. The present author explains on the basis of the universal rule of intersubunit complementarities, 1) how the barrier melts before movements of tRNAs, 2) how the cooperative phenomenon in the proofreading is brought about, and 3) how translocation occurs and results in expelling E-site tRNA from the decoding centre. Such a mechanism was reasonably explained by a series of three-dimensional models of rRNAs and proteins that have already been deposited in the PDB. Chapter IV - Usually, a single polypeptide or even multiple polypeptides is produced from a single mRNA. Trans-translation is an irregular translation system in eubacteria, in which a single polypeptide is synthesized from two separate molecules of coding RNAs, mRNA and tmRNA. It rescues a stalled translation on the ribosome and provides a peptide tag for degradation to the C-terminus of the nascent polypeptide to enable recycling of ribosomes, promote degradation of truncated mRNA and prevent accumulation of abortively synthesized polypeptides in the cell. Trans-translation is involved not only in a quality control system in the cell but also in various kinds of cellular functions. During transtranslation, tmRNA plays a dual function both as a tRNA and as an mRNA. Alanyl-tmRNA

Preface

ix

somehow enters the vacant A-site of the stalled ribosome like aminoacyl-tRNA but without a codon-anticodon interaction, and thereafter the coding region of tmRNA is substituted for mRNA. As a consequence, alanine encoded nowhere but aminoacylated to tmRNA serves as the connector between the truncated peptide encoded by mRNA and the C-terminal tagpeptide encoded by tmRNA. Such an acrobatic feat is accomplished by elaborate interplay between the tRNA and mRNA functions of tmRNA with the help of a protein factor SmpB. Our recent study has suggested that both tmRNA and SmpB mimic the structures and functions of tRNA and mRNA during trans-translation, addressing how tmRNA preferentially recognizes the stalled ribosome, and what substitutes for a codon-anticodon interaction. Chapter V - Sepsis, the systemic manifestation to bacterial infection, induces profound alterations in whole-body protein metabolism. Nitrogen losses up to 17% of total body protein may be observed in septic patients despite aggressive nutritional support. Organ system dysfunction and, eventually, organ failure can result from the persistent loss protein in sepsis. Sustained muscle protein catabolism continues to complicate recovery in septic patients. This review will illuminate potential molecular mechanisms responsible for increasing mRNA translation initiation in striated muscle. Emphasis will be placed on the role of growth hormones and nutrients in promoting rates of protein synthesis during sepsis. In this regard, elevating amino acids and IGF-I both interact to maximally enhance rates of protein synthesis acutely during sepsis through an acceleration of the mRNA translation initiation. IGF-I appears unique in accelerating protein synthesis during sepsis as growth hormone appears to enhance mortality while muscle shows a general resistance to the anabolic actions of insulin. Like IGF-I, amino acids and leucine in particular stimulate mRNA translation initiation by targeting specific signal transduction pathways. The hastening of mRNA translation initiation most likely results from a stimulation of mammalian target of rapamycin (mTOR) acting through its downstream effector proteins to enhance assembly of eIF4G with eIF4E via 4E-BP1 and eIF4G phosphorylation and to increase S6K1 phosphorylation. The physiologic importance lies in the potential ability of IGF-I and amino acids as specific nutrients designed to counteract the accelerated host protein wasting in septic patients and improve nutrition to maintain muscle mass. Chapter VI - For the purpose of studying the aging changes of protein synthesis in mouse hepatocytes, 20 groups of aging mice during development and senescence, each consisting of 3 individuals of both sexes, total 60, from fetal day 19 to postnatal day 1, 3, 9 and 14, month 1, 2 and 6, and year 1 and 2, were injected with RI-labeled amino acids, such as 3H-leucine, 3H-glycine, 3H-proline or 3H-hydroxyproline, which are the protein precursors, sacrificed 1 hr later and the liver tissues were fixed, sectioned and processed for electron microscopic radioautography. On electron microscopic radioautograms obtained from each animal, the localization of silver grains due to 3H-amino acids incorporations showing protein biosynthesis in respective cell organelles, the nucleus, Golgi apparatus, endoplasmic reticulum, mitochondrion and cytoplasmic matrix was qualitatively observed. On the other hand, the numbers of silver grains localizing over respective cell organelles were counted and analyzed quantitatively. The numbers of silver grains localized over the nuclei, Golgi apparatus, endoplasmic reticulum and cytoplasmic matrices increased from perinatal stages to the young adult stage at postnatal month 1, reaching the maximum, then decreased to year 2

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due to aging and senescence. However, the number of silver grains localizing over the mitochondria, i. e. the number of labeled mitochondria per cell and the mitochondrial labeling index in each hepatocyte revealed that the numbers of mitochondria increased gradually from perinatal stages to the postnatal year 2, while the numbers of labeled mitochondria and the labeling indices of intramitochondrial protein syntheses in hepatocytes of mice at various ages increased from embryonic day 19 to postnatal month 6, reaching the maxima, then decreased to year 2 due to aging of animals. Chapter VII- The enzymatic maintenance of biopolymeric structures within a cell is widely known to play a critical role in the regulation of numerous bio-processes from activation, cell signaling and metabolic pathways. This chapter examines the recent advances in label-free biosensing and describes how these technologies have been used to examine protein biosynthesis and protein degradation. Label free biosensing has matured through the years into a powerful technique for examining these processes with quantitative metrology. The emergence of imaging tools with microarray technology in these label free platforms will greatly expand the throughput of these assays thus enabling the user to study globally biosynthetic reactions. Label-free functional enzymatic biosensor assays have recently been applied toward the development of a new generation of protein biosynthesis assays. Labelfree biosensors enable the study of real time biosynthetic and biodegradation reactions while maintaining an open format for exploring modulation factors. When these surface based synthetic and degradation assays are applied in high throughput platforms they provide yet a new screening tool for drug discovery. Chapter VIII - The 1990s, “The Decade of the Brain”, resulted in major scientific advances involving brain imaging, gene therapy, brain/robotic interfacing and the neurobiology and molecular biology of learning and memory. However, despite these critical insights, we still do not know exactly how thoughts or memories are formed or stored in the brain, which leaves much exciting research for the twenty-first and probably centuries to come. This review will elaborate on recent advances in the field of protein biosynthesis as related to synaptic plasticity. We will discuss the molecular players (RNA binding proteins and neuronal mRNAs), the signal transduction pathways that have been implicated in learning and memory and how localized translation of selected mRNAs is involved in synaptic plasticity. We will also discuss the pathology of human diseases including Alzheimer’s disease, Fragile X syndrome, autism and Down syndrome, which show altered or diminished protein synthesis dependent synaptic plasticity. Learning and memory are manifested in their highest form in humans and allow for the retrieval of and action on past events. Understanding the pathology of these neurological disorders will elucidate the normal mechanisms of memory formation and storage. Chapter IX - Protein biosynthesis is rarely restricted to mRNA translation into an amino acid sequence. To yield the mature form, most proteins undergo various posttranslational modifications due to the action of different enzymes. Certain combinations of amino acid residues (primary structure motifs) have been defined to guide the sequence of modifications during the process of precursor protein maturation into the final product. In this chapter, we specifically focus on the secreted polypeptide maturation. For a number of precursor sequences retrieved from UniProt databank, complete sets of enzymes have been identified that execute processing of secreted polypeptides. This finds reflection in the amino acid

Preface

xi

sequences of the corresponding protein precursors that carry information about the queue of posttranslational events in the form of specific motifs arrangement. Extensive data analysis allowed us to propose a simple set of principals that facilitate effective sequence information handling. Utilization of the proposed principals significantly improves mature protein sequence prediction from available gene structures. We also address the problem of known motif identification and novel motif prediction from large sets of data. A number of proteins are considered in greater detail as examples of the proposed principals utilization conveniences. Chapter X - Protein metabolism in ectotherms is strongly influenced by body temperature and thermal history. In many species, rates of protein synthesis increase with temperature up to a species-specific, thermal optimum. Temperature effects protein synthesis by directly influencing the rates of specific biochemical processes involved in the synthesis of proteins, and also by effecting food consumption. In turn, an increase in food consumption will elevate rates of protein synthesis. Animals have evolved the ability to at least partially compensate rates of protein synthesis as ambient temperatures change, by increasing or decreasing tissue RNA concentrations (RNA to protein) and RNA activity (kRNA). However, at polar temperatures, full compensation of protein synthesis does not appear to occur, and ectotherms are only capable of very low rates of protein synthesis. Temperature also has a direct effect on the proportion of synthesised protein that is degraded, with approximately twice as much protein degraded in polar ectotherms as tropical ectotherms. The result of this is that protein growth at temperatures near the lower limits of life is considerably less efficient than at warmer temperatures. The aim of this review is to examine the effects of temperature on protein metabolism in ectotherms from stable thermal environments and those from more variable thermal regimes. Examples mainly from aquatic environments, will be considered at different levels of biological organisation. In this way, the review will cover both temporal and spatial changes in protein metabolism in ectotherms, with particular interest in those organisms living at thermal extremes. Chapter XI - The sodium-dependent D-glucose transporter (SGLT) family is involved in glucose uptake via intestinal absorption (SGLT1) or renal reabsorption (SGLT1 and SGLT2). SGLT plays an important role in the regulation of glucose blood levels. As a result, increasing attention is being focused on SGLT as a drug target for the therapy of diabetes. Therefore, a selective and specific technique for the study of different potential SGLT inhibitors is mandatory. The expression of functional SGLT is regulated by a complex mechanism involving changes in transcription, mRNA stability, and amount of transporter within the plasma membrane. In addition, SGLT expression depends on the state of cellular differentiation of epithelial cells, which can be observed by confluent cell monolayer growth. Therefore, the use of differentiated epithelial cells represents a unique factor required to obtain functional recombinant SGLT protein that can not be reproduced in other cell systems, such as the brush border membrane, oocytes or liposomes. We found that differentiated Chinese hamster ovary (CHO) cells, either stable or transient transfected with a eukaryotic expression vector containing human SGLT1 or SGLT2 gene, expressed functional SGLT in the cell membrane. The extent of hSGLT1 and hSGLT2 expression was evaluated by relative real-time reverse transcription-polymerase chain reaction (RT-PCR) quantification, Western blotting, and immunocytochemical analysis. Moreover, functional activity of hSGLT1 and

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hSGLT2 activity was determined by measuring the sodium-dependent uptake of α-methyl [14C]-D-glycoside. The advantage of the 96-well method we developed is the low amount of radioactive compounds and inhibitory substances required, and its reproducibility. This method represents an initial approach in the development of transport-based high-throughput screening in the search for inhibitors of glucose transport and the development of new antidiabetic drugs. Chapter XII - Hypoxic conditions, found in limb ischemia, aortic aneurysms, myocardial ischemia and in tumors as well as during normal embryogenesis activate a transcriptional response that promotes vascular development and the formation of red blood cells. The master transcriptional regulator of oxygen-controlled gene expression is the hypoxiainducible factor HIF. Many of the proangiogenic and antiangiogenic factors are directly or indirectly regulated by transcription factor HIF. Hypoxia suppresses protein synthesis at the level of mRNA translation initiation in many nontransformed cells whereas highly transformed cells are largely resistant. Two different pathways are involved in response of mRNA translation initiation in cells to hypoxia and it results in biphasic inhibition of translation. The first pathway is associated with endoplasmic reticulum (ER) stress and through it with activation of unfolded protein response. Transient phosphorylation of eukaryotic initiation factor (eIF) 2 alpha in the first phase by double-stranded RNA-activated protein kinase-like endoplasmic reticulum kinase PERK inhibits mRNA translation initiation. The second phase occurs more slowly and is independent on eIF2alpha and is connected with eIF4F (containing the cap- binding protein eIF4E, the scaffold protein eIF4G and the RNA helicase eIF4A) disruption and with inactivation of the ternary complex (eIF2/MettRNA/GTP). The availability of the cap-binding protein eIF4E is rate-limiting under normal conditions. During tumorigenesis eIF4E is often over expressed because eIF4E-binding proteins sequester eIF4E in hypophosphorylated form. Hyperphosphorylation of the eIF4Ebinding proteins lowers their affinity for eIF4E, resulting in an increased interaction between eIF4E and eIF4G and stimulation of translation. Phosphorylation of eIF4E-binding proteins is largely controlled by the mammalian target of rapamycin (mTOR) kinase. Hypoxia inhibits the activation of kinase mTOR and results in hypophosphorylated eIF4E-binding proteins and in increased their affinity for eIF4E and in decreased association between eIF4E and eIF4G necessary for eIF4F disruption. Inhibition of the kinase mTOR suppresses mRNA translation also through a novel mechanism mitigated in transformed cells. This mechanism is based on disruption of proteasome-targeted degradation of eukaryotic elongation factor 2 (eEF2) kinase. However, regulation of translation also results in a specific increase of the synthesis of a subset of hypoxia-induced proteins as activating transcription factor 4 (ATF4), CCAAT/enhancer binding protein homologous protein (CHOP, also named GADD153), growth arrest and DNA damage inducible protein (GADD34), hypoxia inducible factor (HIF1alpha), vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and immunoglobulin heavy chain binding protein (BiP). Translation in these cases is often cap independent due to the presence of an internal ribosome entry site (IRES) in the 5´ noncoding region of some these mRNAs. Hypoxic tumor cells that are target of tumor therapy are exposed to additional endoplasmic reticulum stress by using proteasome inhibitors, such as PS-341 (Velcade), which is Food and Drug Administration approved for

Preface

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treating human malignancies. This therapy may be selectively cytotoxic to hypoxic tumor cells. Chapter XIII - Translation in eukaryotes is usually regulated at the level of initiation. Translation initiation on the majority of eukaryotic cellular mRNAs is mediated by a cap deperndent mechanism. Eukaryotic translation initiation factor 4E (eIF4E) binds to the mRNA cap structure and interacts with the RNA helicase eIF4A and a large scaffold protein eIF4G to create the eIF4F complex. Binding of eIF4E to eIF4G can be blocked by eIF4Ebinding proteins (4E-BP1 and 4E-BP2) acting as competitive inhibitors of eIF4E-eIF4G interaction. Scaffold protein eIF4G brings the mRNA to the 40 S small ribosomal subunit in a complex with eIF2, GTP and the initiator methionine-transfer RNA by its interaction with eIF3 and forms the 48 S preinitiation complex on the mRNA. Scanning of the mRNA with the aid of eIF4A and recognition of initiation AUG start codon in an optimal context is required and other factors as well as the 60S ribosomal subunit are then recruited and polypeptide chain elongation begins. 4E-BP1 and 4E-BP2 double knockout (DKO) mice were used to determine the physiologic functions of these factors. 4E-BP1 and 4E-BP2 DKO mice had a significant increase in both body weight and fat content. The obese phenotype was caused by reduced energy expenditure and reduced lipolysis. Both embryonic fibroblasts and preadipocytes from these 4E-BP1 and 4E-BP2 DKO mice had an increased expression of CCAAT/enhancer-binding proteins and of peroxisome proliferator-activated receptor (PPAR) gamma, essential regulators of adipogenesis. Specific knockdown of the main eIF4E isoform in Caenorhabditis elegans resulted in an increased lifespan of the organism. Because eIF4E is the least abundant among translation initiation factors, changes in the levels of this translation initiation factor affect translation rates, preferentially of a subset of mRNAs with strong secondary structure in the 5´ untranslated region encoding proteins such as Myc, fibroblast growth factor, ornithine decarboxylase, cyclin D1, survivin, Bcl-2, matrix metalloprotease 9 and vascular endothelial growth factor. These mRNAs play important roles in the control of cell growth, proliferation, angiogenesis, survival and malignancy. In experimental models, eIF4E overexpression induces cellular transformation, tumorigenesis, invasion, and metastasis, notably cancers as lymphomas, lung and prostatic adenocarcinomas, bladder cancers, cervical cancers, hepatomas, breast tumorigenesis, head and neck cancers, colorectal cancers and angiosarcomas. A better understanding of the role of eIF4E and its binding proteins (eIF4E-BP) in regulating the translation of the diverse gene products involved in tumorigenesis will improve the capacity to exploit eIF4E and eIF4E-BP as therapeutic targets and as markers for human cancer progression. Modulators of the eIF4E activity by peptides containing an eIF4E-binding site, RNA aptamers which bind eIF4E, eIF4E-specific antisense oligonucleotides and small molecule inhibitors of the eIF4E-eIF4G interaction are tested and may be in future used in therapy for the treatment of cancer.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter I

PROTEIN SYNTHESIS AND AGEING Kostoula Troulinaki and Nektarios Tavernarakis∗ Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion 71110, Crete, Greece.

ABSTRACT Protein synthesis is an essential cellular process affecting growth, reproduction and survival in response to both intrinsic and extrinsic cues such as nutrient availability and energy levels. Studies in many organisms, including humans, have revealed that during ageing, the rate of global protein synthesis declines, indicating a link between the regulation of protein synthesis and the ageing process. Recent studies in C. elegans demonstrate that depletion of specific translation initiation factors, such as eIF4G, eIF2B and eIF4E increases lifespan. Similarly, depletion of specific ribosomal proteins increases lifespan both in yeast and worms. In all cases, these manipulations reduce the rate of general protein synthesis. Why does attenuation of protein synthesis promote longevity? The process of mRNA translation is one of the most energy consuming cellular processes, requiring, depending on growth conditions, up to 50% of the total energy generated by the cell. A reduction of protein synthesis would moderate this energy load, generating an energy surplus, which can be channeled to mechanisms of damage repair and cellular maintenance, thus, extending lifespan. In addition, lowering protein synthesis may be beneficial during ageing by reducing the accumulation of altered, misfolded, aggregated or damaged proteins, as it occurs in many age-related pathologies, such as Alzheimer’s and Parkinson’s disease. The recent experimental findings reveal a key role for protein synthesis in ageing and suggest that perturbation of mRNA translation provides an effective approach for interventions aiming to modulate ageing and senescent decline.

∗

Correspondence concerning this article should be addressed to: Nektarios Tavernarakis, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Vassilika Vouton, P.O.Box 1527, Heraklion 71110, Crete, GREECE. tel: +30 2810 391066; fax: +30 2810 391067; email: [email protected].

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Kostoula Troulinaki and Nektarios Tavernarakis∗

Keywords: Ageing, Caenorhabditis elegans, Lifespan, mRNA translation regulation, Protein modification

INTRODUCTION To maintain their homeostasis and function, cells must continuously synthesize and degrade proteins in a highly regulated manner. The mechanisms of transcription and mRNA translation regulate the synthesis of new proteins. Damaged or aggregated proteins are removed by specialized and selective protein degradation mechanisms (Ding et al., 2007). Studies in various organisms, ranging from yeast to humans, revealed that both protein synthesis and protein degradation rates change during ageing (Makrides, 1983; Partridge and Gems, 2002; Rattan, 1996). The activity of key translation factors appears to decline with age, resulting in reduction of protein synthesis rates (Kimball et al., 1992; Moldave et al., 1979; Takahashi et al., 1985; Vargas and Castaneda, 1981, 1983; Webster and Webster, 1983). However, it was unclear whether these changes were simply a consequence of the general deterioration of the cellular functions that characterize ageing or they had a causative role in the process. Recent studies in the nematode C. elegans revealed that impeding mRNA translation significantly affects longevity, indicating that the levels of protein synthesis may affect ageing (Hansen et al., 2007; Kaeberlein and Kennedy, 2007; Pan et al., 2007; Syntichaki et al., 2007).

DOWN-REGULATION OF PROTEIN SYNTHESIS EXTENDS LIFESPAN Protein synthesis or the translation of mRNA is a conserved process involving three main steps: initiation, elongation and termination. Initiation of translation requires the concerted action of a large number of proteins known as translation initiation factors (eIFs). These factors recognize the cap structure at the 5’ end of mRNA and allow the binding of the 40S ribosome subunit that scans downstream for the initiation codon. The next step is the elongation, during which the fully assembled ribosome reads the transcript and uses amino acid-charged tRNAs to synthesize the peptide chain, with the participation of elongation factors. Finally, the process is terminated when a release factor binds to the final (STOP) codon and releases the complete polypeptide from the ribosome that breaks apart into its two subunits (Gebauer and Hentze, 2004; Proud, 2007). All steps of protein synthesis are tightly regulated and are carried out with superb precision, ensuring the fidelity of the proteins. Many studies have demonstrated that mRNA translation fidelity does not change during ageing (Filion and Laughrea, 1985). However, it has been shown that the rate of protein synthesis declines with age in a variety of organisms (Makrides, 1983; Partridge and Gems, 2002; Rattan, 1996). Initiation, the first step of mRNA translation, is a rate-limiting process and the most common target of protein synthesis control. The initiation factor eIF4E plays a key role in the

Protein Synthesis and Ageing

3

process, by recognizing the 5’-end cap structure of most eukaryotic mRNAs and facilitating their recruitment to the ribosomes (Gingras et al., 1999). In the nematode C. elegans, five eIF4E isoforms, termed IFE-1 - IFE-5, are encoded in the genome (Keiper et al., 2000). IFE1, IFE-3 and IFE-5 are expressed in the germline, whereas IFE-2 and IF-4 are expressed specifically in somatic cells (Keiper et al., 2000). Depletion of the isoforms that are expressed in the germline, or of the somatic isoform IFE-4, does not affect lifespan (Syntichaki et al., 2007). However, loss of IFE-2, which is the most abundant in the soma causes significant extension of lifespan (Syntichaki et al., 2007). This result indicates that down-regulation of protein synthesis specifically in the soma extends lifespan. Interestingly, the observed lifespan extension does not require a functional germline, since lack of germline does not suppress the effect of IFE-2 deficiency (Syntichaki et al., 2007). Notably, depletion of the IFE-1 during adulthood leads to moderate adult lifespan extension, indicating that IFE-1 also modulates longevity (Pan et al., 2007). Other studies in the nematode have further revealed that elimination of other translation initiation factors or their regulators, after completion of the development of the organism, results in similar effects on adult lifespan. For example, knocking down of eIF4G (ifg-1) by RNAi or the eIF2 beta subunit (iftb-1) during adulthood results in 30% increase of lifespan (Chen et al., 2007; Hansen et al., 2007; Pan et al., 2007). In addition, RNAi with several ribosomal proteins or the ribosomal-protein S6 kinase (S6K) –after completion of development- leads to increased lifespan. In all cases, the rate of protein synthesis in “longlived” animals is reduced, compared to wild type control animals (Hansen et al., 2007; Pan et al., 2007). Furthermore, an RNAi screen for essential genes that extend lifespan when inactivated post-developmentally has revealed many genes encoding for several components of the eIF complex and the ribosome. These include C. elegans homologs of eIF2G, eIF3F and eIF4A (Chen et al., 2007; Curran and Ruvkun, 2007).

SIGNALING PATHWAYS THAT REGULATE PROTEIN SYNTHESIS AND AGEING Translation of mRNA is a highly regulated process that enables the cell to fine-tune gene expression by stimulating or repressing translation of specific mRNAs, usually through the reversible phosphorylation of mRNA translation factors. Various signaling pathways, activated by hormones, growth factors and nutrients regulate protein synthesis (Figure 1). For example, the insulin-like pathway, the TOR pathway and the MAPK pathway are key signal transduction pathways implicated in ageing that also modulate protein synthesis (Gingras et al., 2004; Proud, 2007). The insulin-IGF-1 pathway plays a vital role in the regulation of somatic growth and cellular proliferation and in parallel is a key modulator of ageing in various organisms (Guarente and Kenyon, 2000). The pathway is engaged by the insulin receptor that binds the insulin ligand and phosphorylates the phosphatidylinositol 3 kinase (PI3K) that generates phosphatidylinositol-3,4,5-trisphosphate (PtdIns(3,4,5)P3) or phosphatidylinositol-3,4biphosphate (PtdIns(3,4)P2), which in turn activate the 3-phosphoinositide-dependent protein kinase 1 (PDK1). Subsequently, PDK1 activates the serine-threonine protein kinase

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Kostoula Troulinaki and Nektarios Tavernarakis∗

AKT/protein kinase B (PKB). These kinases target the FOXO transcription factor DAF-16 and block its transcriptional activity. Mutations that down-regulate this signaling cascade- for example in the insulin/IGF-like receptor DAF-2 or the phosphatidylonisol-3-OH kinase (PI3K) AGE-1 have been found to extend nematode life span. The extension is dependent on the activity of DAF-16, a forkhead (FOXO) transcription factor that controls the expression of a variety of genes involved in stress resistance (superoxide dismutase, catalase, glutathione, heat-shock protein 16 and others), metabolism (apolipoproteins, glyoxylate cycle and cytochrome P450s) fat accumulation and fertility (Gems and Partridge, 2001; Kenyon, 2005). Similarly, mutations in the insulin-IGF-1 pathway in Drosophila (in the insulin-like receptor), also increase the lifespan of flies (Clancy et al., 2001; Tatar et al., 2001). For example, a mild reduction of the insulin-like receptor (Inr) increases mean female lifespan by up to 85% (Partridge and Gems, 2002). In mammals, different receptors for insulin and IGF-1 participate in divergent pathways in different tissues (Yang et al., 2005). Mutations that down-regulate either the insulin pathway or the IGF pathway, result in prolonged lifespan (Bluher et al., 2003; Flurkey et al., 2001; Holzenberger et al., 2003). In addition, such long lived mice have decreased rate of protein synthesis compared with the control animals (Hsieh and Papaconstantinou, 2004). TOR (target of rapamycin) signaling is stimulated by serum, insulin and growth factors, and promotes protein synthesis through multiple outputs (Gingras et al., 2004; Proud, 2007). The most characterized effector is the ribosomal S6 kinase (S6K), which induces mRNA translation through phosphorylation of ribosomal protein S6 and through regulation of translation initiation factors, such as eukaryotic initiation factor 4B (eIF4B) (Proud, 2004). In addition, TOR signaling promotes translation by regulating the activity of the initiation factor eIF4E. More specifically, TOR phosphorylates the eIF4E–binding protein (4E-BP) and liberates the eIF4E, enabling it to interact with eIF4G and to form a complex competent to mediate cap-dependent translation. Moreover, it has been found that the TOR pathway promotes transcription of genes encoding for ribosomal proteins. In many cell types, the TOR pathway is impaired under amino acid starvation. In this case many of the above proteins undergo dephosphorylation. Studies in C. elegans revealed that TOR deficiency, which dampens the rate of translation, extends lifespan (Vellai et al., 2003). MAPK signaling pathway is also clearly linked with the control of the protein synthesis, by affecting a number of mRNA translational machinery components to promote the assembly of initiation factor complexes and the activation of the elongation machinery (Hsieh and Papaconstantinou, 2004; Proud, 2007). It contains several modules of which the best understood are the classical MAPK (ERK), p38 MAPK α/β and JNK (c-Jun N-terminal kinase) pathways. Each involves kinases that phosphorylate components of the translational machinery and/or other proteins that regulate mRNA translation. ERK activates the protein kinases RSKs (or p90RSKs) that phosphorylate other kinases leading to activation of the TOR pathway. Moreover, RSKs phosphorylate at least two other proteins involved in translational control: the eEF2 kinase and eIF4B, promoting its association with eIF3. p38 MAPK α/β activates MK-2, which regulates the stability of mRNAs, probably through the phosphorylation of ARE-binding proteins. In addition, the MAPK signaling pathway leads to the phosphorylation and activation of the kinases Mnk1 and 2. Mnks bind to eIF4G and mediate eIF4E phosphorylation (Waskiewicz et al., 1999). The physiological significance of

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Figure 1. Signaling pathways that modulate protein synthesis by regulating the activity of specific translation factors. Insulin-insulin growth factor 1 (INS-IGF-1) signaling is activated by the binding of insulin or IGF-1 to the insulin receptor and results in the activation of the phosphatidylinositol 3 kinase (PI3K). PI3K converts phosphatidylinositol (4,5) –bisphosphate (PIP2) to phosphatidylinositol (1,4,5)trisphosphate (PIP3). PIP3 in turn activates the serine threonine protein kinase Akt (also known as protein kinase B; Akt/PKB) which phosphorylates and activates the S6 kinase (S6K), while it suppresses the serine threonine protein kinase GSK3 (glycogen synthase 3). The GSK3 kinase regulates the activity of the eukaryotic translation initiation factor 2B (eIF2B). S6K phosphorylates the small ribosomal subunit S6 and the eukaryotic initiation factor 4B (eIF4B). S6K can also be activated by the target of rapamycin (TOR) signaling pathway. In addition to S6K, the TOR pathway leads to the phosphorylation of the eukaryotic initiation factor 4E-binding protein (4E-BP), which inhibits protein synthesis by blocking the eukaryotic translation initiation factor 4E (eIF4E). In addition, TOR signaling can be activated by the mitogen activated protein kinase (MAPK) signaling cascade. The MAPK pathway stimulates the RSKs or p90RSKs kinases that phosphorylate the eukaryotic translation initiation factor 4B (eIF4B) and the kinase of the eukaryotic elongation factor 2 (eEF2K). Moreover, MAPK signaling activates the mitogen-activated protein kinase-interacting kinases (Mnks) that in turn phosphorylate the eukaryotic translation initiation factor 4E (eIF4E) and the eukaryotic translation initiation factor 4G (eIF4G). Arrows indicate positive regulation events whereas the bar lines indicative negative regulation events.

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this phosphorylation is still unclear. However, it is notable that such phosphorylation is generally mediated by mitogen- or stress- and cytokine-activated signaling. In addition to eIF4E, Mnks also phosphorylate eIF4G.

PROTEIN DAMAGE DURING AGEING One of the most common symptoms of ageing at the molecular level is the accumulation of altered proteins both within the cells and extracellularly (Hipkiss, 2006; Rothstein, 1975, 1979, 1989). Protein damage may result in the loss of protein function or it can also lead to protein aggregation. In the latter case, the interaction of damaged proteins with normal cellular proteins may cause sequestration and inhibition of key molecules, like transcription factors, cytoskeletal proteins, molecular chaperones and hydrolytic enzymes (Hipkiss, 2006). Although protein modifications are continuously generated, through a variety of processes, cellular homeostatic mechanisms either suppress the formation of altered proteins, or enhance their destruction, thereby preventing their accumulation. Such protective mechanisms are the lysosomal and proteasomal pathways. Many studies, involving both biochemical and micro array expression assays, have shown that proteolytic activity decreases with age in many cell types (Gems and McElwee, 2003; Makrides, 1983; Martinez-Vicente et al., 2005; Sarkis et al., 1988; Szweda et al., 2002). Certain pathways of lysosomal protein degradation, such as macroautophagy and chaperone-mediated autophagy, exhibit age-dependent decline in function (Arslan et al., 2006). In addition, alterations in the activity of certain lysosomal enzymes, including cathepsins, have been reported to occur during ageing (Sarkis et al., 1988). Moreover, decline in the function of the proteasome during ageing has been observed in cultured cells and in tissues from various organisms, resulting in an increased half-life of oxidized proteins (Sitte et al., 2000a; Sitte et al., 2000b). This can be attributed to down regulation of genes that encode proteasome subunits and the accumulation of proteasome inhibitory proteins as a function of ageing. Interestingly, many age-related pathologies such as Alzheimer’s disease, Parkinson’s disease and atherosclerosis are characterized by increased levels of altered proteins, which are thought to be the cause of aged-related pathology (Hipkiss, 2006).

WHY IS LIFESPAN EXTENDED WHEN PROTEIN SYNTHESIS IS REDUCED? It is well known that mRNA translation is one of the most energy-consuming cellular processes (Proud, 2002). The addition of a single amino acid in the polypeptide chain during mRNA translation requires the energy released by the hydrolysis of four ATP molecules. The amount of total cellular energy that is devoted to translation varies between different cell types and growth states. For example, dividing cells spend more energy on mRNA translation than post-mitotic cells, given their higher requirement for protein synthesis. In all cases, a high proportion of cellular metabolic energy is used in translation and almost all is consumed

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during the elongation phase. Therefore, reduction of protein synthesis would lead to significant conservation of cellular energy. Extra energy could be channeled towards mechanisms of maintenance and repair, contributing to cell survival under stress conditions, such as oxidative stress (Figure 2). Interestingly, the basic concept of the “disposable soma” theory of ageing is that soma is mortal and frail because fails to divert energy towards repairing stochastic damage that accumulates during life (Kirkwood, 1977; Kirkwood and Austad, 2000). By contrast, the germ line may achieve immortality by investing most of the energy to mechanisms of repair.

Figure 2. A working model linking down regulation of protein synthesis to prolonged lifespan. A) Normal lifespan: Cellular energy is distributed between both protein synthesis and repair. However, since protein synthesis is a highly energy-consuming process, the energy remaining for mechanisms of repair and maintenance is limited, resulting in progressive structural and functional deterioration and ageing. B) Increased lifespan: Down-regulation of protein synthesis may lead to prolonged lifespan by allowing for more cellular energy to be channeled towards repair mechanisms, enabling the cell to better withstand stress.

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In support of this hypothesis, it has been found that ife-2 C. elegans mutants, which are defective for a somatic isoform of the translation initiation factor eIF4E and have reduced rate of protein synthesis, are more resistant than wild type animals to oxidative stress induced by the herbicide paraquat and/or sodium azide, an inhibitor of the respiratory chain cytochrome c oxidase, (Syntichaki et al., 2007). Moreover, IFE-2 deficiency increases oxidative stress resistance and extends lifespan of mev-1 mutants that are continuously under oxidative stress due to their lack of the cytochrome b large subunit in complex II of the mitochondrial electron transport chain (Ishii et al., 1998; Syntichaki et al., 2007). Resistance to oxidative stress corresponds to increased capability for detoxification and repair, indicating a higher capacity for damage repair in these mutants. Thus, down regulation of protein synthesis in the soma, due to elimination of a specific initiation factor of translation (eIF4E) leads to increased oxidative stress resistance and increased lifespan.

CONCLUDING REMARKS AND FUTURE PROSPECTS Protein synthesis and protein degradation are the two essential processes that determine the rate of cellular protein turnover. The recent finding that down-regulation of mRNA translation leads to increase of lifespan establishes a direct link between protein synthesis and ageing (Hansen et al., 2007; Pan et al., 2007; Syntichaki et al., 2007). However, the exact mechanism through which protein biosynthesis affects ageing still remains unknown. Given that mRNA translation is one of the most energy consuming processes; its reduction would result in notable energy savings. This energy could be diverted to cellular repair and maintenance processes, thus contributing to longevity. Moreover, reduction of mRNA translation may prevent the synthesis of unwanted proteins that could interfere with the cellular stress response. Interestingly, under stress, global mRNA translation is attenuated, while there is a switch to selective translation of proteins that are required for cell survival under stress (Clemens, 2001; Holcik and Sonenberg, 2005). The mechanisms that regulate this switch are poorly understood. Mild stress is known to stimulate maintenance and repair mechanisms, a phenomenon known as “hormesis” (Mattson, 2008). Hormesis is associated with reduced accumulation of damaged proteins, stimulation of proteasomal activity and increased cellular resistance to toxic agents (Cypser and Johnson, 2002; Rattan, 2004). Hormesis has also been found to prolong lifespan. It is possible that hormesis depends on lowering protein synthesis to levels that increase energy availability but enable production of essential and vital proteins. In this context, it remains to be seen whether reducing protein synthesis is part of hormetic effects on ageing.

ACKNOWLEDGEMENTS Work in the authors’ laboratory is funded by grants from the European Union 6th Framework Programme, the European Molecular Biology Organization (EMBO) and the Institute of Molecular Biology and Biotechnology.

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REFERENCES Arslan, M.A., Csermely, P., and Soti, C. (2006). Protein homeostasis and molecular chaperones in aging. Biogerontology 7, 383-389. Bluher, M., Kahn, B.B., and Kahn, C.R. (2003). Extended longevity in mice lacking the insulin receptor in adipose tissue. Science 299, 572-574. Chen, D., Pan, K.Z., Palter, J.E., and Kapahi, P. (2007). Longevity determined by developmental arrest genes in Caenorhabditis elegans. Aging Cell 6, 525-533. Clancy, D.J., Gems, D., Harshman, L.G., Oldham, S., Stocker, H., Hafen, E., Leevers, S.J., and Partridge, L. (2001). Extension of life-span by loss of CHICO, a Drosophila insulin receptor substrate protein. Science 292, 104-106. Clemens, M.J. (2001). Translational regulation in cell stress and apoptosis. Roles of the eIF4E binding proteins. J Cell Mol Med 5, 221-239. Curran, S.P., and Ruvkun, G. (2007). Lifespan regulation by evolutionarily conserved genes essential for viability. PLoS Genet 3, e56. Cypser, J.R., and Johnson, T.E. (2002). Multiple stressors in Caenorhabditis elegans induce stress hormesis and extended longevity. J Gerontol A Biol Sci Med Sci 57, B109-114. Ding, Q., Cecarini, V., and Keller, J.N. (2007). Interplay between protein synthesis and degradation in the CNS: physiological and pathological implications. Trends Neurosci 30, 31-36. Filion, A.M., and Laughrea, M. (1985). Translation fidelity in the aging mammal: studies with an accurate in vitro system on aged rats. Mech Ageing Dev 29, 125-142. Flurkey, K., Papaconstantinou, J., Miller, R.A., and Harrison, D.E. (2001). Lifespan extension and delayed immune and collagen aging in mutant mice with defects in growth hormone production. Proc Natl Acad Sci U S A 98, 6736-6741. Gebauer, F., and Hentze, M.W. (2004). Molecular mechanisms of translational control. Nat Rev Mol Cell Biol 5, 827-835. Gems, D., and McElwee, J.J. (2003). Ageing: Microarraying mortality. Nature 424, 259-261. Gems, D., and Partridge, L. (2001). Insulin/IGF signalling and ageing: seeing the bigger picture. Curr Opin Genet Dev 11, 287-292. Gingras, A.C., Raught, B., and Sonenberg, N. (1999). eIF4 initiation factors: effectors of mRNA recruitment to ribosomes and regulators of translation. Annu Rev Biochem 68, 913-963. Gingras, A.C., Raught, B., and Sonenberg, N. (2004). mTOR signaling to translation. Curr Top Microbiol Immunol 279, 169-197. Guarente, L., and Kenyon, C. (2000). Genetic pathways that regulate ageing in model organisms. Nature 408, 255-262. Hansen, M., Taubert, S., Crawford, D., Libina, N., Lee, S.J., and Kenyon, C. (2007). Lifespan extension by conditions that inhibit translation in Caenorhabditis elegans. Aging Cell 6, 95-110. Hipkiss, A.R. (2006). Accumulation of altered proteins and ageing: causes and effects. Exp Gerontol 41, 464-473. Holcik, M., and Sonenberg, N. (2005). Translational control in stress and apoptosis. Nat Rev Mol Cell Biol 6, 318-327.

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Holzenberger, M., Dupont, J., Ducos, B., Leneuve, P., Geloen, A., Even, P.C., Cervera, P., and Le Bouc, Y. (2003). IGF-1 receptor regulates lifespan and resistance to oxidative stress in mice. Nature 421, 182-187. Hsieh, C.C., and Papaconstantinou, J. (2004). Akt/PKB and p38 MAPK signaling, translational initiation and longevity in Snell dwarf mouse livers. Mech Ageing Dev 125, 785-798. Ishii, N., Fujii, M., Hartman, P.S., Tsuda, M., Yasuda, K., Senoo-Matsuda, N., Yanase, S., Ayusawa, D., and Suzuki, K. (1998). A mutation in succinate dehydrogenase cytochrome b causes oxidative stress and ageing in nematodes. Nature 394, 694-697. Kaeberlein, M., and Kennedy, B.K. (2007). Protein translation, 2007. Aging Cell 6, 731-734. Keiper, B.D., Lamphear, B.J., Deshpande, A.M., Jankowska-Anyszka, M., Aamodt, E.J., Blumenthal, T., and Rhoads, R.E. (2000). Functional characterization of five eIF4E isoforms in Caenorhabditis elegans. J Biol Chem 275, 10590-10596. Kenyon, C. (2005). The plasticity of aging: insights from long-lived mutants. Cell 120, 449460. Kimball, S.R., Vary, T.C., and Jefferson, L.S. (1992). Age-dependent decrease in the amount of eukaryotic initiation factor 2 in various rat tissues. Biochem J 286 ( Pt 1), 263-268. Kirkwood, T.B. (1977). Evolution of ageing. Nature 270, 301-304. Kirkwood, T.B., and Austad, S.N. (2000). Why do we age? Nature 408, 233-238. Makrides, S.C. (1983). Protein synthesis and degradation during aging and senescence. Biol Rev Camb Philos Soc 58, 343-422. Martinez-Vicente, M., Sovak, G., and Cuervo, A.M. (2005). Protein degradation and aging. Exp Gerontol 40, 622-633. Mattson, M.P. (2008). Hormesis defined. Ageing Res Rev 7, 1-7. Moldave, K., Harris, J., Sabo, W., and Sadnik, I. (1979). Protein synthesis and aging: studies with cell-free mammalian systems. Fed Proc 38, 1979-1983. Pan, K.Z., Palter, J.E., Rogers, A.N., Olsen, A., Chen, D., Lithgow, G.J., and Kapahi, P. (2007). Inhibition of mRNA translation extends lifespan in Caenorhabditis elegans. Aging Cell 6, 111-119. Partridge, L., and Gems, D. (2002). Mechanisms of ageing: public or private? Nat Rev Genet 3, 165-175. Proud, C.G. (2002). Regulation of mammalian translation factors by nutrients. Eur J Biochem 269, 5338-5349. Proud, C.G. (2004). Role of mTOR signalling in the control of translation initiation and elongation by nutrients. Curr Top Microbiol Immunol 279, 215-244. Proud, C.G. (2007). Signalling to translation: how signal transduction pathways control the protein synthetic machinery. Biochem J 403, 217-234. Rattan, S.I. (1996). Synthesis, modifications, and turnover of proteins during aging. Exp Gerontol 31, 33-47. Rattan, S.I. (2004). Aging, anti-aging, and hormesis. Mech Ageing Dev 125, 285-289. Rothstein, M. (1975). Aging and the alteration of enzymes: a review. Mech Ageing Dev 4, 325-338. Rothstein, M. (1979). The formation of altered enzymes in aging animals. Mech Ageing Dev 9, 197-202.

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Rothstein, M. (1989). An overview of age-related changes in proteins. Prog Clin Biol Res 287, 259-267. Sarkis, G.J., Ashcom, J.D., Hawdon, J.M., and Jacobson, L.A. (1988). Decline in protease activities with age in the nematode Caenorhabditis elegans. Mech Ageing Dev 45, 191201. Sitte, N., Huber, M., Grune, T., Ladhoff, A., Doecke, W.D., Von Zglinicki, T., and Davies, K.J. (2000a). Proteasome inhibition by lipofuscin/ceroid during postmitotic aging of fibroblasts. Faseb J 14, 1490-1498. Sitte, N., Merker, K., von Zglinicki, T., and Grune, T. (2000b). Protein oxidation and degradation during proliferative senescence of human MRC-5 fibroblasts. Free Radic Biol Med 28, 701-708. Syntichaki, P., Troulinaki, K., and Tavernarakis, N. (2007). eIF4E function in somatic cells modulates ageing in Caenorhabditis elegans. Nature 445, 922-926. Szweda, P.A., Friguet, B., and Szweda, L.I. (2002). Proteolysis, free radicals, and aging. Free Radic Biol Med 33, 29-36. Takahashi, R., Mori, N., and Goto, S. (1985). Accumulation of heat-labile elongation factor 2 in the liver of mice and rats. Exp Gerontol 20, 325-331. Tatar, M., Kopelman, A., Epstein, D., Tu, M.P., Yin, C.M., and Garofalo, R.S. (2001). A mutant Drosophila insulin receptor homolog that extends life-span and impairs neuroendocrine function. Science 292, 107-110. Vargas, R., and Castaneda, M. (1981). Role of elongation factor 1 in the translational control of rodent brain protein synthesis. J Neurochem 37, 687-694. Vargas, R., and Castaneda, M. (1983). Age-dependent decrease in the activity of proteinsynthesis initiation factors in rat brain. Mech Ageing Dev 21, 183-191. Vellai, T., Takacs-Vellai, K., Zhang, Y., Kovacs, A.L., Orosz, L., and Muller, F. (2003). Genetics: influence of TOR kinase on lifespan in C. elegans. Nature 426, 620. Waskiewicz, A.J., Johnson, J.C., Penn, B., Mahalingam, M., Kimball, S.R., and Cooper, J.A. (1999). Phosphorylation of the cap-binding protein eukaryotic translation initiation factor 4E by protein kinase Mnk1 in vivo. Mol Cell Biol 19, 1871-1880. Webster, G.C., and Webster, S.L. (1983). Decline in synthesis of elongation factor one (EF1) precedes the decreased synthesis of total protein in aging Drosophila melanogaster. Mech Ageing Dev 22, 121-128. Yang, J., Anzo, M., and Cohen, P. (2005). Control of aging and longevity by IGF-I signaling. Exp Gerontol 40, 867-872.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter II

NEUROPEPTIDE BIOSYNTHESIS IN THE NEMATODE CAENORHABDITIS ELEGANS: FROM PRECURSOR TO BIOACTIVE PEPTIDES Steven J. Husson∗ and Liliane Schoofs Functional Genomics and Proteomics, Department of Biology, K.U.Leuven, Naamsestraat 59, B-3000 Leuven, Belgium.

ABSTRACT Endogenous neuropeptides are small signaling molecules that occur in all metazoan species. They function as neurotransmitters or hormones and orchestrate a wide variety of physiological processes by binding G protein-coupled receptors upon initiation of diverse signaling pathways. Over 115 neuropeptide-encoding genes appear to be present in the soil nematode Caenorhabditis elegans. The biosynthesis of these endogenous biologically active peptides involves a series of enzymatic processing steps, starting from a preproprotein. First, the signal peptide is removed and the remaining part of the precursor will be cleft by proprotein convertases at defined motifs displaying basic amino acids. Next, carboxyterminal basic amino acids are removed by the action of a carboxypeptidase. Finally, the carboxyterminal glycine (if present) will be transformed into an amide. A peptidomics platform, which uses state-of-the-art liquid chromatography combined with mass spectrometry, allows us to biochemically identify endogenous peptides present in any tissue or organism. This technology was used to compare the peptide profiles of C. elegans strains having mutations in the presumed peptide precursor processing enzymes. Doing so, we were able to characterize the major processing enzymes KPC-2/EGL-3, CPE/EGL-21 and the chaperone protein 7B2/SBT-1.

∗

Correspondence concerning this article should be addressed to: Steven J. Husson, Tel.: 0032 16324260, Fax: 0032 16323902; [email protected].

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Keywords: Neuropeptide, peptidomics, mass spectrometry, MALDI-TOF MS, proprotein convertase, carboxypeptidase, egl-3, egl-21.

ABBREVIATIONS: CPE, flp, KPC, m/z, MALDI-TOF, MS, MS/MS, nlp, PC, Q-TOF,

carboxypeptidase E; FMRFamide-like peptide; kex2/subtilisin-like proprotein convertase; mass to charge ratio; matrix-assisted laser desorption ionization time-of-flight; mass spectrometry; tandem mass spectrometry; neuropeptide-like protein; proprotein convertase; quadrupole time-of-flight

INTRODUCTION Neuropeptides are important signaling molecules which are contained in inactive preproproteins or peptide precursors that need to be processed in order to yield the bioactive entities (Figure 1). After removal of the signal peptide, the peptide precursor is processed by proprotein convertases (PCs) at defined cleavage places that display basic amino acids like lysines and arginines. In mammals, seven PCs (furin, PC1/3, PC2, PC4, PC5/6, PC7/8/LPC and PACE4) have been described [1-3]. They all show similarity with the prototype member of the family, kex2 from yeast [4]. PC1 (also named PC3) and PC2 specifically recognize substrates that contain pairs of basic residues, reflecting their role in the processing of neuropeptide precursors. Searching the genomic sequence of C. elegans revealed the presence of four genes that encode for kex2/subtilisin-like proprotein convertases (KPC) [510]. As kpc-2 (also named egl-3) is exclusively expressed in the nervous system and appears to modulate mechanosensory responses in C. elegans, it is considered as the major PC needed for the processing of neuropeptides in this nematode [7]. Proprotein convertases are expressed as inactive proproteins that need to be activated. As extensively studied in mice, the neuroendocrine chaperone 7B2 appears to be responsible for the proteolytical activation of proPC2 [11]. Interestingly, the carboxyterminal part of 7B2 regulates the enzymatic activity of mature PC2 [12]. The orthologous 7B2 gene (sbt-1) from C. elegans has already been cloned in 1998 [13], but no biochemical data about the effects of 7B2 on neuropeptide processing in C. elegans was available in pre-peptidomics times. In the next step of biological peptide synthesis, a carboxypeptidase that is encoded by egl-21 in C. elegans will remove the basic residues from the carboxyterminal end of the intermediate peptides. It has been shown that this carboxypeptidase facilitates acetylcholine release at neuromuscular junctions in C. elegans [14]. Finally, a carboxyterminal amidation reaction can occur. This common post-translational modification involves an oxydation of the carboxyterminally

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located glycine residue, followed by a lyase reaction in which the amidated peptide is formed in additon to a glyoxylate molecule.

Figure 1. The neuropeptide processing pathway in C. elegans. All bioactive neuropeptides are derived from inactive preproproteins or peptide precursors that require several highly regulated posttranslational processing reactions to yield the endogenous neuropeptides. A typical peptide precursor contains an aminoterminal signal peptide that is cleaved off upon entry into the secretory pathway by a signal peptidase. Next, a proprotein convertase (EGL-3) cleaves the remaining part of the precursor at specific motifs containing basic amino acids (K, R, KR, RR, RK and KK). The neuroendocrine chaperone protein 7B2 (SBT-1) is needed for the proteolytical activation of pro-proprotein convertases, while the carboxyterminal part of 7B2 is involved in the regulation of the enzymatic activity of the mature proprotein convertase. The resulting intermediate peptides that are formed after cleavage of the neuropeptide precursor all contain carboxyterminal basic amino acids that are removed by a specific carboxypeptidase. Finally, the carboxyterminal glycine residue, if present, is transformed into an amide.

As neuropeptidergic signaling underlies many behaviors in C. elegans, knowledge about the biologically active peptides and their processing enzymes is inevitable for further functional research. Using genomic and biochemical techniques in addition to bioinformatics, a total of 33 flp (FMRFamide-like peptide) genes, 45 nlp (neuropeptide-like protein) genes and 40 insulin-like peptide (INS) genes could be found in C. elegans [15-21]. In the past, biochemical analyses of neuropeptides and their processing enzymes have been hampered by difficulties in purification and characterization of the peptides. As a consequence, only 12 FLP neuropeptides could be biochemically characterized in the pre-peptidomics era [22-27]. Elucidation of peptide sequences required laborious efforts for tissue collection and multiple chromatographic separations in order to isolate and characterize one active signaling molecule. The characterization of their processing enzymes relied on the generation of specific antibodies for a wide variety of neuropeptides and subsequent radioimmuno assays to determine potential substrates. In contrast, the peptidomics technology aims to biochemically visualize and identify endogenous peptides present in a cell, tissue or organism using high-throughput liquid chromatographic techniques and mass spectrometry [28-30]. Using a differential peptidomics approach, in which HPLC fractions are monitored with a matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) instrument, we compared the peptide profiles of various mutant animals, among which mutants of the presumed neuropeptide precursor

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processing enzymes. This way, we were able to characterize the major processing enzymes kpc-2/egl-3 [31], egl-21 [32] and the neuroendocrine chaperone protein 7B2 [33] of the nematode C. elegans. Here, we briefly report on the overall workflow used and discuss the obtained results.

Figure 2. Differential Peptidomics Workflow. Peptide extracts form different C. elegans strains that were made in exactly the same way are separated by reversed phase high performance liquid chromatography (RP-HPLC) generating a chromatogram as indicated. Each fraction from each mutant strain is analyzed by a matrix-assisted laser desorption ionization time-of-flight mass spectrometer (MALDI-TOF MS) of which a schematic representation is shown. All samples are deposited on a steel target plate (TP), together with a UV-absorbing matrix. By firing a focussed laser beam onto the target plate, an ion plume is generated. Individual ions are accelerated by an electric field that is applied on the acceleration plates (Acc) before entering the field-free flight tube of the time-of flight (TOF) analyzer. The main principle of the TOF analyzer is to measure the time an ion needs to reach the detector (DL) at the end of the field-free flight tube. Since the acquired velocity is a function of its mass (m) and charge (z), m/z ratios can easily be determined by measuring the time needed to cross the flight tube. To increase the resolution and mass accuracy of the instrument, a reflectron at the end of the flight tube acts as an electrostatic mirror to reflect the ions that are now detected by a second detector (DR).

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DIFFERENTIAL PEPTIDOMICS: WORKFLOW All C. elegans strains were kindly provided by the Caenorhabditis Genetics Centre (CGC) and were cultured on conventional nematode growth media (NGM) plates containing E. coli OP50 bacterial lawns, at 20°C. Peptide extracts of the wild type C. elegans strain N2 and kpc-2/egl-3, egl-21 and sbt-1 (7B2) mutants were made in exactly the same way, as previously described [15]. Briefly, mixed stage nematodes from twelve to fifteen fully grown Petri dishes, having a diameter 90 mm, were placed in 10 to 20 mL of an ice cold extraction solvent containing methanol/water/acetic acid (90/9/1). Worms were homogenized and the resulting solution was sonicated prior to centrifugation. The pellet was discarded and the methanol was evaporated. The remaining aqueous residue was delipidated by re-extraction with an equal volume of ethyl acetate or n-hexane. Finally, the peptide sample was desalted by solid phase extraction using a C18 cartridge and stored at 4°C. Each peptide extract was subjected to HPLC analyses on a Symmetry C18 column (5 µm, 4.6 x 250 mm, Waters). After injection of the sample, a wash step for ten minutes using 2% CH3CN in 0.1% aqueous TFA was initiated, followed by a linear three-step gradient of 60 minutes at a flow-rate of 1 mL per minute. The gradient was as follows: from 2% CH3CN to 22% CH3CN in 0.1% aqueous TFA in 20 minutes, from 22% CH3CN to 37% CH3CN in 0.1% aqueous TFA in 30 minutes and from 37% CH3CN to 50% CH3CN in 0.1% aqueous TFA in 10 minutes. Obviously, other HPLC columns and gradients can be used. Sixty fractions were automatically collected from the beginning of the three-step gradient. All the generated HPLC fractions were monitored by MALDI-TOF MS in positive ion, reflectron mode. Ion peaks were compared with the theoretical masses of predicted and previously identified neuropeptides from C. elegans to generate peptide profiles of the different strains. This overall differential peptidomics workflow is indicated in figure 2.

RESULTS In our first peptidomics experiments using two dimensional nanoscale liquid chromatography and quadrupole time-of-flight tandem mass spectrometry (2D-nanoLC QTOF MS/MS), we were able to sequence 60 naturally occurring FLP and NLP neuropeptides from C. elegans [15]. Here we report on the use of an off-line approach combining HPLC separation with mass spectrometric detection of peptides using a MALDI-TOF mass spectrometer. This approach allows a robust comparison of neuropeptide profiles from mutant strains. Doing so, analysis of the wild type N2 strain yielded the identification of 91 neuropeptides while only 41 peptides could be monitored in the 7B2 mutant [33]. As an example, mass read-outs of fraction 30 are shown in figure 3 (other fractions not shown). The potential role of the four kpc genes in the processing of endogenous neuropeptides was also assessed by this differential peptidomics approach. Animals mutant in kpc-2/egl-3 were found to be severely depleted in both FLP and NLP neuropeptides [31]. Only a few peptides (or even no peptides) could be monitored in the C. elegans strains carrying different alleles of the kpc-2/egl-3 gene. Our results provide biochemical evidence that KPC-2/EGL-3 is indeed the essential proprotein convertase in C. elegans [31]. In contrast, peptide profiles from kpc-1

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and kpc-4/bli-4 mutants resembled that of wild type animals, while the kpc-3/aex-5 mutant shows slightly decreased peptide content [31]. Finally, 115 carboxyterminally extended intermediate peptides could be found in the egl-21 mutans, in combination with 2D-nanoLC Q-TOF MS/MS [32]. Interestingly, about 20 fully processed neuropeptides could also be measured. These ion peaks, however, all showed a strongly reduced intensity in contrast to the wild type peptides. As an example, fraction 30 (Figure 3C) shows two fully processed peptides, (NGAPQPFVRFamide from the FLP-11 precursor and ASYDYIRFamide from FLP-25) in addition to five peptides that all contain KR residues at their carboxyterminus. These incompletely processed peptides are completely absent in wild type N2 (Figure 3A).

Figure 3. Comparison of MALDI-TOF MS spectra. Mass read-outs from wild type (A), egl-3 (B), egl21 (C) and sbt-1 (D) mutants are shown. Peptide extracts form wild type C. elegans and peptide processing mutants were subjected to a HPLC separation generating 60 fractions which were analyzed by MALDI-TOF MS. As an example, zoom regions from m/z 1000 to m/z 2000 of fraction 30 are shown.

CONCLUSION A peptidomics approach aims to biochemically visualize and identify all endogenous peptides present in a cell, tissue or organism, with a greater resolution and specificity than by traditional techniques like e.g. SDS-PAGE, Western blots and immunocytochemistry [34]. Using liquid chromatography and mass spectrometry, bioactive peptides can now be isolated

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and identified from small tissue extracts [28]. This allows us to construct and compare the neuropeptide profiles of various mutant C. elegans strains. While 41 out of 91 observed peptides from wild type N2 were unequivocally present in the 7B2 mutant, a clear absence of some defined ion peaks could be monitored in the latter strain [33]. Interestingly, highly abundant ion peaks that were present in the wild type strain were totally absent in the 7B2 mutant. This specific and determined absence or presence of a subset of neuropeptides was clearly not observed in strains mutant for kpc-2/egl-3 that only revealed the presence of a few peptides [31]. Our results indicate that KPC-2/EGL-3 is the major proprotein convertase in C. elegans, while the 7B2 chaperone protein is also (indirectly) involved in this processing pathway. Identification of 115 carboxyterminally extended intermediate peptides in the egl21 mutant animals establishes EGL-21 as the major carboxypeptidase for the processing of neuropeptides in C. elegans [32]. As the name implies, both egl-3 and egl-21 were initially identified in a genetic screen for egg laying defective mutants [35]. They also show a mild coiling phenotype and display altered defecation [14,35]. Recently, we found that both of these mutants show a widening of the intestinal lumen, particularly towards the anterior end [32]. Moreover, the egl-3 strain showed reduced intestinal fat accumulation [32]. In conclusion, our differential peptidomics approach provides a biochemical characterization of the major neuropeptide processing enzymes in the nematode C. elegans. Moreover, the altered neuropeptide processing in egl-3, egl-21 and sbt-1 mutant animals is reflected in diverse physiological processes including egg-laying, defecation rhythms, fat storage and locomotion. Our studies therefore establish the basis for identifying specific bioactive peptides that modulate these biological processes.

ACKNOWLEDGEMENTS Financial support from the Research Foundation Flanders (FWO) is greatly acknowledged (FWO-Vlaanderen grants G.0434.07 and 1.5.137.06). The authors want to thank the Interfacultary Centre for Proteomics and Metabolomics “ProMeta”, K.U.Leuven and appreciate the kind gifts of the Caenorhabditis Genetics Centre (CGC). S.J. Husson is a postdoctoral fellow of the Research Foundation Flanders.

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[4] Julius,D., Brake,A., Blair,L., Kunisawa,R., & Thorner,J. (1984) Isolation of the putative structural gene for the lysine-arginine-cleaving endopeptidase required for processing of yeast prepro-alpha-factor. Cell 37, 1075-1089. [5] Gomez-Saladin,E., Wilson,D.L., & Dickerson,I.M. (1994) Isolation and in situ localization of a cDNA encoding a Kex2-like prohormone convertase in the nematode Caenorhabditis elegans. Cell Mol. Neurobiol. 14, 9-25. [6] Gomez-Saladin,E., Luebke,A.E., Wilson,D.L., & Dickerson,I.M. (1997) Isolation of a cDNA encoding a Kex2-like endoprotease with homology to furin from the nematode Caenorhabditis elegans. DNA Cell Biol. 16, 663-669. [7] Kass,J., Jacob,T.C., Kim,P., & Kaplan,J.M. (2001) The EGL-3 proprotein convertase regulates mechanosensory responses of Caenorhabditis elegans. J. Neurosci. 21, 92659272. [8] Thacker,C., Peters,K., Srayko,M., & Rose,A.M. (1995) The bli-4 locus of Caenorhabditis elegans encodes structurally distinct kex2/subtilisin-like endoproteases essential for early development and adult morphology. Genes Dev. 9, 956-971. [9] Thacker,C. & Rose,A.M. (2000) A look at the Caenorhabditis elegans Kex2/Subtilisinlike proprotein convertase family. Bioessays 22, 545-553. [10] The C.elegans Sequencing Consortium (1998) Genome sequence of the nematode C. elegans: a platform for investigating biology. Science 282, 2012-2018. [11] Muller,L., Zhu,X., & Lindberg,I. (1997) Mechanism of the facilitation of PC2 maturation by 7B2: involvement in ProPC2 transport and activation but not folding. J. Cell Biol. 139, 625-638. [12] Van Horssen,A.M., van den Hurk,W.H., Bailyes,E.M., Hutton,J.C., Martens,G.J., & Lindberg,I. (1995) Identification of the region within the neuroendocrine polypeptide 7B2 responsible for the inhibition of prohormone convertase PC2. J. Biol. Chem. 270, 14292-14296. [13] Lindberg,I., Tu,B., Muller,L., & Dickerson,I.M. (1998) Cloning and functional analysis of C. elegans 7B2. DNA Cell Biol. 17, 727-734. [14] Jacob,T.C. & Kaplan,J.M. (2003) The EGL-21 carboxypeptidase E facilitates acetylcholine release at Caenorhabditis elegans neuromuscular junctions. J. Neurosci. 23, 2122-2130. [15] Husson,S.J., Clynen,E., Baggerman,G., De Loof,A., & Schoofs,L. (2005) Discovering neuropeptides in Caenorhabditis elegans by two dimensional liquid chromatography and mass spectrometry. Biochem. Biophys. Res. Commun. 335, 76-86. [16] Husson,S.J., Mertens,I., Janssen,T., Lindemans,M., & Schoofs,L. (2007) Neuropeptidergic signaling in the nematode Caenorhabditis elegans. Prog. Neurobiol. 82, 33-55. [17] Kim,K. & Li,C. (2004) Expression and regulation of an FMRFamide-related neuropeptide gene family in Caenorhabditis elegans. J. Comp. Biol. 475, 540-550. [18] Li,C., Kim,K., & Nelson,L.S. (1999) FMRFamide-related neuropeptide gene family in Caenorhabditis elegans. Brain Res. 848, 26-34. [19] Li,C. (2005) The ever-expanding neuropeptide gene families in the nematode Caenorhabditis elegans. Parasitology 131 Suppl, S109-S127.

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[20] Nathoo,A.N., Moeller,R.A., Westlund,B.A., & Hart,A.C. (2001) Identification of neuropeptide-like protein gene families in Caenorhabditis elegans and other species. Proc. Natl. Acad. Sci. U. S. A 98, 14000-14005. [21] Pierce,S.B., Costa,M., Wisotzkey,R., Devadhar,S., Homburger,S.A., Buchman,A.R., Ferguson,K.C., Heller,J., Platt,D.M., Pasquinelli,A.A., Liu,L.X., Doberstein,S.K., & Ruvkun,G. (2001) Regulation of DAF-2 receptor signaling by human insulin and ins-1, a member of the unusually large and diverse C. elegans insulin gene family. Genes Dev. 15, 672-686. [22] Marks,N.J., Shaw,C., Maule,A.G., Davis,J.P., Halton,D.W., Verhaert,P., Geary,T.G., & Thompson,D.P. (1995) Isolation of AF2 (KHEYLRFamide) from Caenorhabditis elegans: evidence for the presence of more than one FMRFamide-related peptideencoding gene. Biochem. Biophys. Res. Commun. 217, 845-851. [23] Marks,N.J., Maule,A.G., Geary,T.G., Thompson,D.P., Davis,J.P., Halton,D.W., Verhaert,P., & Shaw,C. (1997) APEASPFIRFamide, a novel FMRFamide-related decapeptide from Caenorhabditis elegans: structure and myoactivity. Biochem. Biophys. Res. Commun. 231, 591-595. [24] Marks,N.J., Maule,A.G., Geary,T.G., Thompson,D.P., Li,C., Halton,D.W., & Shaw,C. (1998) KSAYMRFamide (PF3/AF8) is present in the free-living nematode, Caenorhabditis elegans. Biochem. Biophys. Res. Commun. 248, 422-425. [25] Marks,N.J., Maule,A.G., Li,C., Nelson,L.S., Thompson,D.P., Alexander-Bowman,S., Geary,T.G., Halton,D.W., Verhaert,P., & Shaw,C. (1999) Isolation, pharmacology and gene organization of KPSFVRFamide: a neuropeptide from Caenorhabditis elegans. Biochem. Biophys. Res. Commun. 254, 222-230. [26] Marks,N.J., Shaw,C., Halton,D.W., Thompson,D.P., Geary,T.G., Li,C., & Maule,A.G. (2001) Isolation and preliminary biological assessment of AADGAPLIRFamide and SVPGVLRFamide from Caenorhabditis elegans. Biochem. Biophys. Res. Commun. 286, 1170-1176. [27] Rosoff,M.L., Doble,K.E., Price,D.A., & Li,C. (1993) The flp-1 propeptide is processed into multiple, highly similar FMRFamide-like peptides in Caenorhabditis elegans. Peptides 14, 331-338. [28] Baggerman,G., Verleyen,P., Clynen,E., Huybrechts,J., De Loof,A., & Schoofs,L. (2004) Peptidomics. J. Chromatogr. B 803, 3-16. [29] Clynen,E., De Loof,A., & Schoofs,L. (2003) The use of peptidomics in endocrine research. Gen. Comp Endocrinol. 132, 1-9. [30] Husson,S.J., Baggerman,G., Clynen,E., Boonen,K., & Schoofs,L. Peptidomics: the search for endogenous neuropeptides by mass spectrometry is coming of age. In: Farley E.P. Progress in Neuropeptide Research. New York: Nova Science Publishers Inc. 2007, 95-123. [31] Husson,S.J., Clynen,E., Baggerman,G., Janssen,T., & Schoofs,L. (2006) Defective processing of neuropeptide precursors in Caenorhabditis elegans lacking proprotein convertase 2 (KPC-2/EGL-3): mutant analysis by mass spectrometry. J. Neurochem. 98, 1999-2012. [32] Husson,S.J., Janssen,T., Baggerman,G., Bogert,B., Kahn-Kirby,A.H., Ashrafi,K., & Schoofs,L. (2007) Impaired processing of FLP and NLP peptides in carboxypeptidase E

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(EGL-21)-deficient Caenorhabditis elegans as analysed by mass spectrometry. J. Neurochem. 102, 246-260. [33] Husson,S.J. & Schoofs,L. (2007) Altered neuropeptide profile of Caenorhabditis elegans lacking the chaperone protein 7B2 as analyzed by mass spectrometry. FEBS Lett. 581, 4288-4292. [34] Clynen,E., Baggerman,G., Veelaert,D., Cerstiaens,A., Van Der Horst,D., Harthoorn,L., Derua,R., Waelkens,E., De Loof,A., & Schoofs,L. (2001) Peptidomics of the pars intercerebralis-corpus cardiacum complex of the migratory locust, Locusta migratoria. Eur. J. Biochem. 268, 1929-1939. [35] Trent,C., Tsuing,N., & Horvitz,H.R. (1983) Egg-laying defective mutants of the nematode Caenorhabditis elegans. Genetics 104, 619-647.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter III

STEREOCHEMICAL MECHANISM OF TRANSLATION BASED ON INTERSUBUNIT COMPLEMENTARITIES Kozo Nagano Nagano Research Institute of Molecular Biology, 4-8-24 Higiriyama, Kohnan-ku, Yokohama 233-0015 Japan

ABSTRACT A universal rule is found in nucleotide sequence complementarities between the regions 2653-2666 in the GTPase binding site of 23S rRNA and 1064-1077 of 16S rRNA as well as between the region 1103-1107 of 16S rRNA and GUUCG (or GUUCA) of tRNAs. This means that there are two extreme cases of conformational states between the above regions. One is responsible for GTP hydrolysis, and the other plays an important role in the structural transitions, particularly for activation of three tRNAs bound to A, P, and E sites in the proofreading step of codon recognition, and in the process of translocation. In order to understand the mechanism of the conformational change, the present author assumed that four kinds of GTPases, viz. aminoacyltRNA•EF-Tu•GTP ternary complex, EF-G•GDP complex, peptide chain release factor 3 (RF-3), and initiation factor 2 (IF-2), first binds to the cavity region on the 30S ribosomal subunits, where it is known that an antibiotic spectinomycin binds. Amino acid sequence comparison of effector region for the above four GTPases has shown why the first three GTPases unfolds the region around helix 35 of 16S rRNA and goes to the GTPaseassociated region on the 50S subunit, while IF-2 promotes binding of initiator tRNA to the 30S subunit. On the other hand, the crystal structure of the whole ribosome binding three deacylated tRNAs (PDB accession number 1GIX) has shown that the three elbow regions of the tRNAs are distantly separated from each other, resulting in difficulty in explaining the negative cooperativity between A- and E-site tRNAs. Moreover, the existence of a barrier region at the nucleotides G1338 and A1339 of 16S rRNA presents a difficulty in understanding how codon recognition and translocation could occur. The present author explains on the basis of the universal rule of intersubunit

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Kozo Nagano complementarities, 1) how the barrier melts before movements of tRNAs, 2) how the cooperative phenomenon in the proofreading is brought about, and 3) how translocation occurs and results in expelling E-site tRNA from the decoding centre. Such a mechanism was reasonably explained by a series of three-dimensional models of rRNAs and proteins that have already been deposited in the PDB.

INTRODUCTION Biological translation is performed by the following four processes: (1) initiation, (2) elongation, (3) polypeptide chain termination, and (4) recycling. From a viewpoint of evolution of life, the second process could have been developed first, while the others could have been spontaneous at first, and then developed later on by modifications of the first essential process. The second one consists of codon recognition and translocation, the former which requires aminoacyl-tRNA (aa-tRNA) and peptidyl-tRNA (pep-tRNA), and the latter preceeded by transpeptidation. Bacterial ribosomes require two protein factors for the elongation cycle: elongation factor Tu (EF-Tu) for accommodating a cognate aa-tRNA with the A site, and elongation factor G (EF-G) for translocation. The site near A2660 in 23S rRNA is called α–sarcin/ricin stem-loop (SRL), which is essential for binding the two GTPases, and for GTP hydrolysis. The present author has found the nucleotide sequence complementarities as a universal rule for all living kingdoms between the SRL and 5’-side of helix 35 of 16S rRNA (abbreviated as h35 hereafter) and between the other side of h35 and the GTΨC-sequence of almost all tRNAs (Nagano and Nagano, 2007). This finding has led to an explanation of how the driving force of translocation and codon recognition can be produced. Although the 3D structure of ribosome containing three deacylated tRNAs at A, P, and E sites (Yusupov et al., 2001) showed the distance of 100A°≈120A° between the above two regions of rRNAs, inspection of the structure around the region of 16S rRNA binding proteins, S2, S3 and S5, suggested a course of transformation that allows the ribosome to perform translocation and binding of an aa-tRNA•EF-Tu•GTP ternary complex according to the universal rule of the intersubunit rRNA complementarities. The purpose of the present paper is to show a series of reasonable predicted structures of the ribosome and tRNAs around the decoding site and the tRNA binding sites, and to explain how translocation occurs, how stop signals can be recognized, and also how discrimination of cognate aa-tRNA from noncognate and near-cognate ones as a proofreading mechanism can be made from the viewpoint of 3D structures.

RESULTS AND DISCUSSIONS 1. Nucleotide Sequence Complementarities and Possibility of Such Interactions in the 3D Structure The secondary structures of E. coli 16S rRNA, and 5’-half and 3’-half of 23S rRNA are shown in Figures 1a, b and c by following the layout style of Gutell (1993). A large part of

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these secondary structures are the same as the ones presented before (Brimacombe, 1995). E. coli sequence is a representative of eubacteria and its helix numbering is used as a standard for all kinds of living species. The regions of particular concern in the present paper are near h35 and h37, α-sarcin/ricin binding loop (SRL) in helix 95 of 23S rRNA (denoted as H95 hereafter), and L11 binding region in H43 and H44. The T-loop of tRNA is also added in Figure 1a so that it may implicate a possible interaction with one side of h35. Figure 2 shows that the region of nucleotides, 1064-1077 of 16S rRNA, is complementary with the region of SRL in the GTPase-binding site on 23S rRNA. The 3’ side of h35, CGAGC, is also complementary to the GTΨCG sequence on the T-loop of all tRNAs. This is a universal rule that holds for all living organisms (Nagano and Nagano, 2007). This rule implies that there are two extreme cases of conformational states for the nucleotides drawn in red and blue in Figure 2. The left-most structure seems to play an important role in GTP hydrolysis. Another structure is a long helix, which is shown on the right-hand side in Figure 2. This seems to be a transition-state structure, that could be observed neither by X-ray crystallography nor by cryo-electron microscopy. In order to understand the functional role of the structural change, it was assumed that both aa-tRNA•EF-Tu•GTP ternary complex and EF-G•GDP complex first interact with an exposed location on the small subunit. The nucleotide exchange from GDP to GTP could occur on EF-G shortly before GTP hydrolysis (Zavialov et al., 2005). The locations of both complexes to be touched with the small subunit are protruded portions such as T-loop-D-loop contact region of aa-tRNA of the ternary complex and domain IV-V bridge region of EF-G•GDP complex. The anticodon of aa-tRNA can find its A-site codon very easily. Near the binding site of the 3’ end adenine of aa-tRNA on EF-Tu, there exists a sequence of aminoacid residues that is called the effector region. Figure 3 shows a comparison of aminoacid sequences of the effector region of 7GTPases, EF-Tu, eukaryotic EF-1 (eEF-1), EF-G, eEF-2, peptide chain release factor 3 (RF-3), initiation factor 2 (IF-2), and archeal initiation factor 2 (aIF-2). The right-most residue of EF-Tu, Asn64, is known as the binding site of the 3’ end adenine of aa-tRNA. Thr62 is known to bind to two oxygen atoms of Pγ phosphate of GTP (Berchtold et al., 1993). Either tyrosine or phenylalanine at the 47th position of EF-Tu is known to bind to guanine base of GTP. Although KAR59 is a part of short α helix in the crystal structure of EF-Tu with a uncleavable GTP derivative (Berchtold et al., 1993), it is easy for us to imagine a binding mode to some phosphate groups of rRNA, probably a part of double-stranded RNA helix. It is also important to note that the acidic residues drawn in red in Figure 3, such as Asp51 and Glu56 of EF-Tu, are highly conserved in 5 GTPases, EF-Tu, eEF-1, EF-G, eEF-2, and RF-3, but not conserved in IF-2 and aIF-2. It is known that IF-2 promotes binding of fMet-tRNA to the 30S ribosomal subunit. Accordingly, the pair of acidic aminoacid residues could probably play a role in unfolding a specific part of double-stranded rRNA helix. When h35 and h37 are unfolded, the CGAGC nucleotides on the 3’ side of h35 would be taken by the T-loop of aa-tRNA, and its D-loop moves toward the T-loop of P-site tRNA, which is confirmed by the finding that the fluorescence signal of proflavin at D16 or D17 in the D-loop has shown a small initial increase even in the case of noncognate tRNA recognition (Rodnina et al., 1994). On the other hand, the 5’ side of h35 can go to the location of the SRL of 23S rRNA, resulting in formation of the long helix, as shown in Figure 2.

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a

Figure 1a.

Kozo Nagano

Stereochemical Mechanism of Translation...

b

Figure 1b.

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28 C

Figure 1. Secondary structure of E. coli rRNAs following the layout style of Gutell. (a) 16S rRNA along with TΨC-stem-loop of yeast Phe-tRNAPhe. 5’, C, 3’M, and 3’m represent 5’-domain for the region of 1-556, central domain for the region of 557-918, 3’-major domain for the region of 919-1396, and 3’-minor domain for the region of 1397-1542, respectively. Small numerals denote the residue numbers of the nucleotides indicated by the respective lines. The helices are numbered by large numerals as Brimacombe (1995). It is predicted that the T-loop of tRNA interacts with the 3’ side of h35. (b) 5’ half of 23S rRNA. I, II, and III represent domain numbers for the regions of 1-561, 5621269, and 1270-1646, respectively. A-site finger is the nucleotide range from 879 to 898. (c) 3’ half of 23S rRNA. IV, V, and VI represent domain numbers for the regions of 1647-2014, 2015-2627, and 2628-2904, respectively. The α–sarcin/ricin stem-loop region (SRL), P-loop, and A-loop are the nucleotide ranges from 2653 to 2667, from 2251 to 2253, and from 2552 to 2556, respectively. Numerals are as in (a).

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Figure 2. Schematic diagram showing a possibility of interactions between the α-sarcin/ricin loop (SRL) of 23S rRNA and one side of another highly conserved region (mostly helix 35) of 16S rRNA, using E. coli sequence as a representative example, as well as between the other side of h35 and GTΨC-region (T-loop) of tRNA. This figure is obtained from Figure 1 of Nagano and Nagano (2007). The sequence of SRL is shown mostly in red. UAGUACGAG (in red), AG (in gray) and GAC (in red). 5’ and 3’ represent that the adjacent nucleotides are 5’- and 3’-ends, respectively, of the nucleotide fragment. H95 designates the helix number in E. coli 23S rRNA secondary structure. The letters, h35, h36, and h37, represent the helix numbers of the nearby helices in E. coli 16S rRNA secondary structure. SpcF denotes spectinomycin footprint site. The nucleotides 1064-1077, displayed in light blue and gray is hypothesized to make base pairs with the red and gray region 2653-2666 of 23S rRNA, while the nucleotides in green are proposed to interact with the sequence GUUCG or GUUCA (in purple) in tRNA. The sequence UUA in brown is also highly conserved. The nucleotide positions of tRNA sequence are shown in a standard form using two-letter codes. The numbers 1, 18, 33, 37, 56, 61, and 76 are the nucleotide residue numbers in yeast tRNAPhe for the residues indicated by the connecting lines. N at position 33 represents that the residue is pyrimidine (viz. U or C), while R at position 37 is purine (viz. A or G or their modified bases). The nucleotide at position o5 or 61 is in most cases C and highly conserved. In exceptional cases, when the nucleotide at position n5 is A, the nucleotide at o5 could be U. When d4-e4 base pair is neither Watson-Crick nor wobble type, G·A pair occurs most frequently as a favorable noncanonical base pair and A··A and U·U pairs appear less frequently.

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Figure 3. Comparison of amino acid sequences from the GTP binding region to the effector region of the GTPases, EF-Tu, eEF-1α, EF-G, eEF-2, RF-3, IF-2, and aIF-2. Red letters, blue letters, and green letters denote the highly conserved acidic amino acid residues such as aspartic acid and glutamic acid, the highly conserved basic residues such as arginine and lysine, and the other highly conserved residues particularly around the GTP binding and effector regions of EF-Tu, respectively, while the other amino acid residues are represented in black. The abbreviated species name, the species name, the accession file name, and their residue number range of the aminoacid sequence are obtained from Swiss Protein Sequence Data Bank (PIR): (1) eubacterial elongation factor EF-Tu; Ecoli, Escherichia coli EFECT 1765. Taqua, Thermus aquaticus S00229 17-66. Hinfl, Haemophilus influenzae E64078 17-65. Pfalc, Plasmodium falciparum plastid S72277 17-65. clEgrat, Euglena gracilis chloroplast EFEGT 17-66. clPpurp, Porphyra purpurea chloroplast S73208 17-65. mtCeleg, Caenorhabditis elegans mitochondria T37273 50-98. mtScere, Saccharomyces cerevisiae mitochondria EFBYT 53-101. (2) eukaryotic elongation factor eEF-1α; Scere, S. cerevisiae EFBY1A 12-75. Tbruc, Trypanosoma brucei A54760 1275. Pfalc, P. falciparum S21909 12-75. Zmays, Zea mays S66339 12-75. Tpyri, Tetrahymena pyriformis A49171 13-76. Hsapi, Homo sapiens EFHU1 12-75. (3) eubacterial elongation factor EF-G; Ecoli, E. coli EFECG 15-65. S6803, Synechocystis sp. PCC 6803 S75863 15-65. Taqua, T. aquaticus

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EFTWG 17-67. Dradi, Deinococcus radiodurans E75536 18-68. clGmax, Glycine max chloroplast S35701 105-155. mtScere, S. cerevisiae mitochondria S43748 46-96. mtRnorv, Rattus norvegicus mitochondria S40780 52-105. (4) eukaryotic elongation factor eEF-2; Scere, S. cerevisiae A41778 2472. Bvulg, Beta vulgaris T14579 24-72. Athal, Arabidopsis thaliana A96602 27-75. Celeg, C. elegans A40411 24-72. Dmela, Drosophila melanogaster S05988 24-72. Hsapi, H. sapiens EFHU2 24-72. (5) eubacterial peptide chain release factor RF-3; Ecoli, E. coli E91295 18-72. Sente, Salmonella enterica AD1072 18-72. Paeru, Pseudomonas aeruginosa B83159 16-70. B.APS, Buchnera sp. APS C84993 1872. Linno, Listeria innocua AB1556 17-71. Llact, Lactococcus lactis E86668 15-69. Spneu, Streptococcus pneumoniae D97921 15-69. N7120, Nostoc sp. PCC 7120 AC2353 21-75. Saure, Staphylococcus aureus D89870 15-69. Atume, Agrobacterium tumefaciens AC2615 17-71. Bmeli, Brucella melitensis AB3539 15-69. Ccres, Caulobacter crescentus B87382 17-71. (6) eubacterial initiation factor IF-2; Ecoli, E. coli FIEC2 396-463. Bsubt, Bacillus subtilis A35269 224-291. Saure, S. aureus H89900 214-281. clPpurp, P. purpurea chloroplast S73178 268-335. mtScere, S. cerevisiae mitochondria S66706 150-219. mtSpombe, Schizosaccharomyces pombe mitochondria T39351 176245. (7) archeal initiation factor aIF-2; Mther, Methanobacterium thermoautotropicum E69132 10-95. Afulg, Archaeoglobus fulgidus H69345 18-100. Hsali, Halobacterium salinarum T43849 20-103.

2. Transition-state Conformation of three tRNA Molecules in Codon Recognition A crystal structure of the whole ribosome has been presented at 5.5 Å resolution for Thermus thermophilus 70S ribosome binding three deacylated tRNAs at A-, P- and E-sites and mRNA of A- and P-site codons (Yusupov et al., 2001), the atomic coordinates of which can be obtained by two PDB data files, 1GIX and 1GIY. If we assume that the locations of Patoms of the middle nucleotide of P-site codon and A422 of 23S rRNA at the foot of H22 are fixed, the distance between the two P-atoms is calculated as 138.95 Å, as shown in Figure 4. Figure 4 also shows those from the three 3’ end adenines of A-, P-, and E-tRNAs to the middle P-nucleotide, 74.47, 76.30, and 91.56 Å, respectively. In contrast to these values, those from the A-site 3’ end and P-site 3’ end to the middle P-nucleotide for A-P tRNA docking pair (Nagano and Nagano, 1997) in the PDB data file 1IP8 are 74.07 and 85.83 Å, respectively (not shown). In the next predicted model of Nagano and Nagano (1997) for entrance of T-site tRNA (in the recognition mode of A-site) to the two tRNAs in the posttranslocational state, PDB data file 1IPM, those from the T-site 3’ end, P-site 3’ end, and E-site 3’ end to the same position on mRNA are 72.29, 81.94, and 77.26 Å, respectively (not shown). If we concentrate our attention on a transition-state conformation of the three tRNA molecules in codon recognition, such a model can be presented as PDB data file 1IPU, and the corresponding values, 48.08, 79.31, and 75.60 Å, respectively, as shown in Figure 4. This should be an energetically elevated or activated substate between the two states of postribosome and preribosome. Since it is energetically elevated than the other two states, an important question has to be asked beforehand as to what is the source of energy for such an elevation of potential chemical energy. One of the basic hypotheses in the present paper is that this is also the result of the long helix formation, as shown in Figure 2. It has been shown by X-ray crystallography that the relative orientation of small and large ribosomal subunits is open in postribosome and closed in preribosome (Ogle and Ramakrishnan, 2005). We have already explained how it occurs in translation (Nagano and Nagano, 2007). The long helix formation brings about a counterclockwise rotation to the small subunit with respect to the

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large subunit viewing from the mRNA. On the other hand, the conformational change of large-subunit rRNA (LSU-rRNA) binding the 3’ end adenines of A- and P-site tRNAs would occur through a clockwise rotation of H95, that is accompanied by rotational movements about the locations of H94, H96, and H97. Since the P-P distance between C2394 at the foot of H88 and A422 at the foot of H22 of 23S rRNA in 1GIY is 62.02 Å, summation of 62.02 and 75.60, 137.62 Å, becomes almost equal to the P-P distance between the middle of P-site codon and A422 in 1GIY, 138.95 Å, as shown in Figure 4. This means that the C2394 bound to the 3’ end adenine of E-tRNA could move toward the P-site codon by rotation of about 32˚around the pivotal position at A422. Considering that the peptidyl end of P-tRNA is approximately fixed in postribosome, the 3’ end nucleotide of the E-tRNA would have moved by the effect of binding the aa-tRNA•EF-Tu•GTP ternary complex to the 30S ribosomal subunit, similarly to the amount of the movement of C2394 (and G2421) in translocation prior to the movement of 30S subunit by the effect of EF-G•GDP attachment to the small subunit for formation of the hybrid P/E state (Nagano and Nagano, 2007). This could be an important preparatory step for the movements of various associated regions for codon recognition. The putative first interaction site of the elongation factors could be assigned as the location where h34, h35, and h36 are folded back toward the neck of 30S subunit along the cleft side of its head, that is exactly the spectinomycin binding site, as shown in Figure 4c of Carter et al. (2000). It is known that spectinomycin inhibits EF-G dependent translocation (Bollen et al., 1968; Sigmund et al., 1984). Figure 4b of Carter et al. (2000) also showed how G1064, C1066 and G1068 are associated with the binding of spectinomycin. The shape of the cleft of 30S subunit fits very well for that of either T-loop-D-loop contact region of aa-tRNA of the EF-Tu•GTP ternary complex or the domain IV-V bridge region of EF-G•GDP. In the X-ray structures for various forms of ribosomes (Yusupov et al., 2001; Schuwirth et al., 2005; Korostelev et al., 2006; Selmer et al., 2006), a barrier between P- and E-tRNAs is observed as a ridge containing G1338 and A1339 and the 790 loop of 16S rRNA. It would also be important to note that G942 and U1341 form always a G-U wobble pair, indicationg a possibility of a functionally meaningful conformational change. The interatomic P-P distance between G1064 and U1341 is found to be 22.5 Å, which is an ideal distance for formation of a G-U wobble pair. Inspection of the P-P atomic distances in the neighbourhood of A1339 has shown that the important part of the barrier could be removed as a result of formation of a transient short double-stranded helix, GUCA1067/GAAU1341. This step will be referred to as barrier melting mechanism hereafter. Two anticodon stems of both P- and E-tRNAs are rotated, twisted and induce two kinds of conformational changes at T-loop-D-loop (elbow) regions and anticodon loops. Then, the 5’ end of the 5’ side of h35, G1068, remains at the location of U1341, while its 3’ end nucleotides, UGUUG1077, go closer to the SRL of 23S rRNA, resulting in the first contact between G2655 of 23S rRNA and U1075 of 16S rRNA, that was suggested by the result of mutant ribosome experiment with modification of G2655 of 23S rRNA (Leonov et al., 2003; Nagano and Nagano, 2007).

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Figure 4. Schematic representation of P-P atomic distances for two kinds of tRNA binding models on the 70S ribosome. The three tRNAs on the left-hand side are those of the X-ray structure of the whole ribosome binding three deacylated tRNAs (Yusupov et al., 2001; PDB file 1GIX and 1GIY) and their elbow regions are separated from each other, in which the P-P distances from C56 of E-tRNA to G18 of P-tRNA and from C56 of P-tRNA to G18 of A-tRNA are 47.43 Å and 34.04 Å, respectively, while those on the right-hand side are predicted as a transition-state conformation of three tRNAs in the proofreading mechanism and deposited in PDB with an accession number 1IPU, in which the P-P distances from C56 of E-tRNA to G18 of P-tRNA and from C56 of P-tRNA to G18 of A-tRNA are 21.11 Å and 20.57 Å, respectively. The P-P distances between the middle nucleotide of the P-site codon and the other nucleotide positions are as follows: 1) for 1GIX, A422 of 23S rRNA (1GIY), 138.95 Å; A76 of E-tRNA, 91.56 Å; A76 of P-tRNA, 76.30 Å; A76 of A-tRNA, 74.47 Å; 2) for 1IPU, A76 of EtRNA, 75.60 Å; A76 of P-tRNA, 79.31 Å; A76 of A-tRNA, 48.08 Å. The P-P distance between A422 of 23S rRNA and C2394 of 23S rRNA is 62.02 Å for 1GIY. If we assume that the nucleotide A422 and H14 of 23S rRNA in domain I (see Figure 1b) are fixed, the location of A76 of E-tRNA in 1IPU can be obtained by rotating the helical rod (H88, H22 and a pseudoknot helix CCA415/UGG2410) clockwise by about 32◦ around an axis passing through the P atom of A422. A part of barrier region, G1338 and A1339, exists between two anticodon stems of E- and P-tRNAs. GTP hydrolysis occurs near the A76 of A-tRNA (or T-tRNA) in the transition-state structure, 1IPU, in the proofreading mechanism.

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b

c

d

Figure 5. Stereo pictures showing the transition-state conformation of three tRNAs in the proofreading mechanism. The models are viewed from the small subunit to the large subunit, but rotated 30◦ around X-axis to see the nascent polypeptide chain, cysteinyl residue of aa-tRNA, and GTP. The models of

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tRNAs on the right-hand side, the middle one, and the one on the left-hand side are T-tRNA in red, PtRNA in green, and E-tRNA in violet, respectively. (a) Wire model representations of P atoms (which is called P-atom model hereafter) of three whole tRNA molecules without large variable loops are shown along with Cα atoms of the nascent polypeptide chain as α-helical conformation in greenish yellow, Cα atoms of EF-Tu with green small dots, Cα atom of cystenyl residue of aa-tRNA with large red ball, and P atoms of GTP with large golden balls. mRNA is drawn in dark blue. 16S rRNA from G1064 to G1077 are drawn in grey, and 23S rRNA from U2653 to C2666 are in black. (b) P-atom models from D17 to C60 of E-tRNA, from D17 to C60 of P-tRNA, and from D17 to the end nucleotide of the large variable loop (V16) of A-tRNA. mRNA is as in (a). The possibility of base-pairing from G18 of PtRNA to C56 of E-tRNA as well as from G18 of A-tRNA to C56 of P-tRNA is shown. E-site codon (m3, m-2, m-1), P-site codon (m 1, m 2, m 3), and A-site codon (m 4, m 5, m 6) are shown. The locations of three U33 positions of the anticodon loops are also shown. (c) P-atom models of h44 and part of h28 of 16S rRNA in grey and a helical rod through H88 and H22 connected with each other by CCA415/UGG2410 of 23S rRNA along with some of their adjacent nucleotides in black, both atomic coordinates are taken from those of 1GIX and 1GIY, are fitted to the cavity of the three codonanticodon base pairs, shown in (a) and (b). The location of C2394 of 23S rRNA is fitted to that of the 3’ end (A76) of E-tRNA. See text for the spatial relationship of h44 and H88 with mRNA and the three tRNA models. The conformations of the three tRNAs and mRNA are as in (a) and (b). (d) P-atom model of the joint region of h44 and part of h28 of the model in (c). In order to obtain an ideal basepairing capability with A1503-U33(E), A1398-U33(P), and A1396-U33(T), a G1504-C1399 base pair (see Figure 1a) should be broken. See text for further explanation. The locations of G920 as starting nucleotide of h28, A1492 and A1493, that interact with A-site codon-anticodon base pairs as A-minor motifs (Nissen et al., 2001), as well as A1396, A1398 and A1503 are shown by numerals.

It can be pointed out that the two elbow regions of the two tRNAs come close together to make a G-C base pair between G18 of P-tRNA and C56 of E-tRNA, that allows an exposed C56 of P-tRNA towards an incoming aa-tRNA. In the X-ray structure of the whole ribosome binding three deacylated tRNAs, the 3 tRNA molecules are all isolated and compactly folded with the elbow regions. Accordingly, the P-P distances between C56(E) and G18(P) and between C56(P) and G18(A) are 47.4 Å and 34.0 Å, respectively. In the present predicted model of transition-state conformation of three tRNA molecules in codon recognition (PDB data file 1IPU), those between C56(E) and G18(P) and between C56(P) and G18(A) are 21.1 Å and 20.6 Å, respectively. Both are capable of forming a stable single G-C base pair. Figure 5a shows such a model of three tRNAs as well as some of their associated regions displayed by a computer program RasMol V2.7.3 (Sayle and Milner-White, 1995; Bernstein, 2000). Here mRNA, E-tRNA and P-tRNA are drawn in dark blue, violet, and green, respectively. The T-tRNA is also drawn in red. We can see α–helical form of nascent polypeptide chain in brownish yellow, and SRL region of 23S rRNA in black. The grey strands at the lower part on the right-hand side of Figure 5a are the 14 nucleotides from C1064 to G1077 around the 5’ side of h35 and the 5 nucleotides of CGAGC1107 of 16S rRNA. The space between h35 of 16S rRNA and the SRL as well as A-tRNA is occupied by a molecule of EF-Tu, Cα atoms of which are shown by small dots in light green. We can see the triphosphate group of GTP (three P atoms) and the cysteinyl residue (Cα atom) at the 3’ end of aa-tRNA at the T site. In this model, the codon-anticodon base pairings are all made of cognate tRNAs. This state just corresponds to that when GTP hydrolysis is about to occur. GTP hydrolysis does not occur before reaching this state because of a slight distortion of GTP binding region on the long helix. It should also be important to note that the three tRNA molecules drawn in Figure 5b contain the largest variable loop of tRNA3Ser from E. coli (Yamada and Ishikura, 1973) as a

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hybrid molecule with tRNAPhe from yeast (Nagano and Nagano, 1997), but that it is omitted for the three tRNAs in Figure 5a for simplicity of the model. In Figure 5b the base-pairing possibilities of G18(A)-C56(P) and G18(P)-C56(E) can be seen.

3. Discrimination of Cognate, Noncognate and Near-cognate tRNAs and Proofreading Another conformational change accompanied by the barrier melting mentioned above occurs at the anticodon loops of A-, P-, and E-tRNAs. Such a conformation is shown in Figure 5b, in which mRNA and only three anticodon stem-loop of A-tRNA, P-tRNA, and EtRNA are drawn in dark blue, red, green, and violet, respectively. Here, we can see that three anticodon loops are all sharply pointed at U33. The codon-anticodons are nearly vertical and closely resemble an ideal A-form RNA helix structure. Accordingly, the base pairings of codon-anticodons are more stable than those observed by X-ray crystallography, but the shape of anticodon loops around U33 looks rather unstable unless it is supported by some conserved bases, such as adenines of 16S rRNA. It is well known that the nucleotides at the positions 32 and 33 are usually pyrimidines, and that U33 is highly conserved except for C33 of fMet-tRNA (Sprinzl et al., 1998). This implies a possibility of conformational change in the 7-nucleotide anticodon loop by exposing U33. It loses one hydrogen bond formed between N3 atom of the base and O5’ atom of A36 of the loop, and gains two hydrogen bonds if the uracil base could find an unpaired and conserved adenyl base in its neighbourhood. Such an adenine can be found as a highly conserved one at A1396. Accordingly, if a strong right-handed twist movement is given between the first and second anticodons by a cognate codon-anticodon base pairs, such a flip-flop motion of the loop could easily occur. This is exactly an induced fit that is expected to enhance the accuracy in translation. Since it is known that C1400 can be crosslinked to the first anticodon base (mG34 in ASLPhe) (Prince et al., 1982), it is possible for another highly conserved nucleotide, A1398, to base-pair with U33 of P-site tRNA. Both C1399 and C1397 are also highly conserved but are most weakly base-paired to the U33s of tRNAs at the A and P sites. In order to play a similar role for a deacylated tRNA at the E site in the poststate, A1503 of 16S rRNA could be the likeliest candidate. Although the P-P distance of U33(E)-A1503(16S) is 34.19 Å in the PDB data file 1GIX (Yusupov et al., 2001) (U33(A)-A1396(16S); 26.49Å, and U33(P)-A1398(16S); 23.48Å), the conformational twist of the transition-state three tRNA molecules, discussed in the preceding section, would make it much closer under a condition that both U33 nucleotides of P- and E-tRNAs are fully exposed. In this connection, it would be informative for us to know that the P-P distances of A1398(16S)-A1503(16S), A1396(16S)-A1503(16S), and A1398(16S)-A1396(16S) in 1GIX are only 16.69 Å, 15.71 Å, and 8.13 Å, respectively. Figure 5c shows that the cavity of three codon-anticodon helices surrounded by three exposed U33 nucleotides of the anticodon loops of T-, P-, and E-tRNAs is fitted to the joint region of h28 and h44 of 16S rRNA, viz. the region of nucleotides, 1393-1410 and 14901506, and that the 3’ end A76 of E-tRNA is taken by C2394 of 23S rRNA, as observed crystallographically by Schmeing et al. (2003) and Yusupov et al. (2001). The atomic

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coordinates of h28 and h44 of 16S rRNA and H88 and H22 of 23S rRNA are obtained from the PDB files 1GIX and 1GIY (Yusupov et al., 2001), but fitted to the coordinate system of 1IPU, in which the three tRNA molecules are viewed down along its Z-axis, as shown by Figures 6, 8, 11, and 12. However, the orientations of both helices of 16S and 23S rRNAs are modified by keeping only the distance between A1503 of 16S rRNA and C2394 of 23S rRNA. The surface of the nucleotides, 1393-1410 and 1490-1506, are fitted to the mRNA, and then, H88 and H22 along with their neighbouring nucleotides are rotated around the Zaxis, Y-axis, and X-axis, by -110.0◦, -11.0◦, and -4.1◦, respectively, with the A1503 fixed at the origin. Since this operation of the relative orientational change of the two helices h44 and H88 makes C2422 instead of C2394 closer to the 3’ end of E-tRNA, the rotation of 150.0◦ around the Y-axis, -38.8◦ around the X-axis, and -58.8◦ around the Z-axis with the C2394 fixed as the origin of the coordinate system. This implies that a considerable degree of rotational freedom could exist for both large helices of the small and large ribosomal subunits. Figure 5c also shows that a rotation of the helical rod of H88, H22, and a pseudo knot CCA415/UGG2410 around an axis passing through A422 and A423 would allow the C2394 to approach the 3’ end of P-tRNA very easily. After the E-tRNA leaves the large subunit E site near C2394, it would move in such a direction particularly when P-tRNA is deacylated in the ribosomal prestate, even if the conformation of the mRNA and the ASLs of A- and P-tRNAs still remain at the previous positions. This state could be exactly what we call the P/E and A/P hybrid sites, if both P-loop could also shift simultaneously toward the CCA end of A-tRNA by expelling A-loop. It can be achieved by binding of EF-G•GTP complex at the GTPase associated centre. Explanations for such a movement of LSU-rRNA will be given for Figure 8c in section 4. Specific interactions of A2433 and A2434 at the base of H74 with 2’-hydroxyl groups of the residues 71 and 76 of deacylated P-tRNA (Feinberg and Joseph, 2001) could play a decisive role in shifting the P-loop toward the old A-tRNA for formation of the hybrid sites, although the effect of C1892 of H68, as observed by Feinberg and Joseph (2001), cannot be explained by this model. On the other hand, this model explains very well the negative cooperativity between the T and E sites (Nierhaus, 1990), because EtRNA resists the entrance of T-tRNA into the A site by its steric hindrance, and because the T-tRNA, once it gets into the A site, expels the E-tRNA with exchange of two G-C pairs, as described by tRNA docking pair model of Nagano and Nagano (1997). In order to stabilize the transition-state three tRNA binding structure, three A-U pairs with the exposed U33 of E, P-, and T-tRNAs would be required under the auspices of the region of the nucleotides, 1393-1410 and 1490-1506. Figure 5d shows more detailed locations of A1503, A1398, and A1396 of 16S rRNA, assuming that the conformation of the region are the same as that of Yusupov et al. (2001) and just fitted to the cavity of mRNA and three ASLs shown in Figure 5b. It is clear that G1504-C1399 pair should be broken in order to obtain ideal base-pairings with A1503-U33(E-t), A1398-U33(P-t), and A1396-U33(T-t). This seems to be a kind of cooperative phenomenon that produce 6 hydrogen bonds of 3 A-U pairs at the expence of 3 hydrogen bonds of G1504-C1399 and 3 hydrogen bonds between N3 atom of U33 and O5’ atom of A36 of the three anticodon loops. This site is very close to h29, where the trgger of the barrier melting occurs as a result of h35 unfolding. A-minor motif interactions (Nissen et al., 2001) of A1492 and A1493 to the A-site codon-anticodon helix could be much more facilitated without help of paromomycin (Ogle et al., 2001).

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4. Predicted Models of two tRNAs and their Surrounding Regions in the Preribosome (1IP8) and Postribosomes (1IPM) Four types of experimental results have shown that conformational differences around the elbow region of tRNAs bound to A and P sites as well as to P and E sites; 1) G18 and G19 in the D-loop of the tRNA specifically bound to the A site are protected from kethoxal modification in contrast with those in the free state as well as those in the tRNA bound to the P site (Bertram et al., 1983). 2) Footprinting studies revealed striking differences in the Tand D-loops of tRNAs bound to the P and A sites (Jørgensen et al., 1985). They observed a more open structure for the tRNA in the A site. 3) G18 of A-site tRNA and C56 of P-site tRNA was found to crosslink to protein L27 (Abdurashidova et al., 1990). 4) Cleavage patterns of thioated tRNAs by iodine (I2) in the P site of preribosome and in the E site of postribosome showed that their T-loop (G53-C61) are strongly protected in contrast with the unprotected nucleotides in the D-loop (G15-A21) (Nierhaus et al., 1995). Furthermore, the patterns of A- and P-site tRNAs in the preribosome are very similar to those of P- and E-site tRNAs in the postribosome, respectively (Nierhaus et al., 2000). They proposed an α–ε domain carrying the two tRNAs from the A and P sites to the P and E sites (Spahn and Nierhaus, 1998). On the basis of the above findings, the present author partly followed the idea of Nierhaus and his coworkers, because their conveyor domain in the large subunit could not be assigned confidently, but presented different models of two tRNAs, A-P docking pair and P-E docking pair, in which the angle between the ASLs of A- and P-site tRNAs (or Pand E-site tRNAs) is 50° (Nagano and Nagano, 1997) under a requirement that the conformation of P-site ASL is common for both pre- and postribosome. Crystal structures of L11•rRNA complexes have been presented with and without thiostrepton binding N-terminal region of the protein, respectively (Conn et al., 1999; Wimberly et al., 1999). The above regions from G1051 to U1108 of 23S rRNA is called GTPase associated centre, while the SRL region is called GTPase binding site. The crystallographic analysis of 50S subunit of bacterial ribosome at 5 Å resolution (Ban et al., 1999) identified the locations of the L11•rRNA complex and the SRL on their electron density map. SRL was almost fully exposed on the surface of the 50S subunit, and its conformation was almost the same as that obtained by NMR study (Szewczak et al., 1993). The tentative model of EF-G was presented so that its location should be consistent with the EF-G binding site of SRL but should not contradict the assigned locations of H96 and H97 (Ban et al., 1999), resulting in dissatisfaction of crosslinking distance between EFG•GDPCH2P complex and the region of nucleotides 1055-1081 of 23S rRNA (Sköld, 1983). It was shown by crosslinking experiments that the regions of nucleotides 877-913 of H38 (Asite finger) of 23S rRNA are found near the A-site tRNA (Rinke-Appel et al., 1995). The nucleotide 885 at the top of H38 of the A-site finger is close to the position 20:1 of A-site tRNA, while 2475 to the position 47 of A-site tRNA (Rinke-Appel et al., 1995). (The position 20:1 of lupin tRNAmMet (Rinke-Appel et al., 1995) is an extra nucleotide residue between G20 and A21.) Such a model is obtained in the present work, as shown in Figure 6a, in which the structure of GTP is fitted to the G domain of EF-G, and also makes a close contact with A2660 that can be depurinated by ricin to inactivate the ribosome (Marchant and Hartley, 1995). (The atomic coordinates for Figure 6a are presented in the PDB file 1IP8.)

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This orientation of EF-G was determined so that its domain III would make a contact with the region of nucleotides 1055-1081 of 23S rRNA, as observed by crosslinking study (Sköld, 1983), and that the tip of domain IV would be directed toward the region around C1920 in H69, as suggested by directed hydroxyl radical probing (Wilson and Noller, 1998), although it was observed to occupy the location of A-site codon-anticodon helix after completion of translocation in the cryo-EM study of yeast 80S•eEF2•sordarin complex (Spahn et al., 2004). Figure 6a also shows the conformations of two tRNAs, mRNA, and helices h34, h35, h36, h37, h38 and h39 in the prestate. This substate is obtained after the putative first interaction of EF-G•GDP complex at the cavity of 16S rRNA, that is the binding site of spectinomycin which inhibits EF-G-dependent translocation, as already discussed in the section.2. Before reaching this substate, the barrier region of G1338 and A1339 as well as AU1341 interacted with the region of GUCA1067, rotated around the axis of the four base-paired helix, and unfolded again. This is also shortly before the long helix formation, that could induce a large conformational change in the central loop region of the 50S subunit, resulting in the reversible transition from the ‘relaxed state’ of preribosome, in which the 3’ end of A-site tRNA is peptidylated, the 3’ end of P-site tRNA is deacylated and does not lock the translocation to the A/P and P/E hybrid state (Valle et al., 2003; Zavialov et al., 2005), as described by Nagano and Nagano (2007). The structure of EF-G in Figure 6a is the same as the crystal structure of apo-EF-G (or nucleotide-free EF-G) (Ævarsson et al, 1994), that was found to be very similar to that of EF-G•GDP complex (Czworkowski et al., 1994). GTP model was fitted to the EF-G following the corresponding structure of EF-Tu•GDPNP (Berchtold et al., 1993). It was found that a pep-tRNA in the P site regulates the GTPase activity of EF-G and RF-3 in a similar manner by decreasing the binding affinity of the respective factors in the GTP form to the ribosome complex for both translocation and peptide release (Zavialov and Ehrenberg, 2003). A guanine nucleotide exchange was observed for both termination (Zavialov et al., 2001) and translocation (Zavialov et al., 2005). As described in the section.2, the region around h35 could unfold when the GTPases first interact with the cavity region, where it is known as the spectinomycin binding site. In such an instant, a certain region on the structures of EF-G and RF-3 could also be influenced so that they would lose the GDP molecule. Figure 3 suggests that Trp50 and Met51 in EF-G and Trp58 and Met59 in RF-3 on the amino acid sequences of the effector region of both GTPases are typical and could be responsible for instability of GDP binding. Then, it would be quite natural to think that the binding of GTP into the vacant G domain of both GTPases could occur when they collide with either SRL or L11 binding region of the GTPase associated centre of 23S rRNA. Figure 3b of Berchtold et al. (1993) suggests that hydroxo group of Tyr47 of EF-Tu is bound to an oxygen atom of Pα phosphate of GTP. Since the residues at the position of EF-Tu is either Tyr or Phe, as shown in Figure 3, the stacking effect of the aromatic ring could be the cause of the stability of GDP in EF-Tu. Along with the effect of either Thr60 in EF-G or Ser68 in RF-3 for binding to two oxygen atoms of Pγ phosphate of GTP, the conformational change at the instant of the collision to the SRL and GTPase associated centre would facilitate the GTP molecule to get into the G domain. It is, however, important to note that the recovery of GTP does not immediately result in its hydrolysis. Some kind of distortion must be effected to inactivate the G domain for a while. It

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could be due to the formation of the long helix around A2660 of SRL near the GTP binding site of the GTPases.

a

b

Figure 6. Stereo pictures showing the predicted 3D structures of A-tRNA and the regions around the GTPase associated centre. The main chains (P-O5’-C5’-C4’-C3’-O3’-) of RNAs and (N-C-C-O-) of proteins are drawn in colours by WebLabViewer Pro 3.0, and the labels and numerals are added by Adobe Illustrator 7.0J. (a) A- and P-tRNAs in the A-P tRNA docking pair model (Nagano and Nagano, 1997) are shown in magenta and green, respectively. The mark 76A represents the location of the position 76 of A-tRNA. The other numbers ending with A correspond to the residue numbers in yeast tRNAPhe at the A site, while those ending with P denote them at the P site. mRNA from the first nucleotide of P-site codon, which is denoted by m 1, to 6th nucleotide count from m 1, which is the third nucleotide of A-site codon and denoted by m 6, is shown in greenish yellow. The regions of nucleotides of 16S rRNA, 1069-1075 and 1103-1107, capable of base-pairing with SRL and GTΨCG sequence of almost all tRNAs, respectively, are drawn in light blue and grey, respectively, while the

Stereochemical Mechanism of Translation...

41

region 1090-1092 capable of binding stop signal is in pink. The other nucleotides from 1055 to 1202 are shown in blue. It can be seen that the interaction between SRL and the nucleotides 1069-1075 is possible. A purple letter U indicates the location of nucleotide U1075 of 16S rRNA, while a purple letter G shows that of nucleotide G2655 in the SRL region of 23S rRNA. This figure represents a substate of two tRNAs and their surrounding regions along with EF-G•GTP complex shortly after the first interaction between the complex and h35, and also after the melting of the barrier, G1338 and A1339. The distance between the two letter positions, G and U, is 58.7A°, but could be much closer, considering that the secondary structure around h35 is totally unfolded. See text for explanation about the interaction between U1075 and G2655. Large characters of A and P indicate the locations of the anticodon stem-loop of tRNAs at the A and P sites, respectively. (b). The main chains of the regions of nucleotides surrounding the 3’-end of P-tRNA in (a). P-tRNA in green, and the domains IV and V of EF-G in bluish olive green, and the domain III of EF-G in pink are the same as in (a), while H89 is in light blue. The nucleotides from 2246 to 2258 of H80 are drawn in red, while those from 2547 to 2561 of H92 are in magenta. The nucleotides from 2057 to 2085, from 2234 to 2240, from 2434 to 2454, and from 2607 to 2611 of 23S rRNA are drawn in brown, those from 2497 to 2546, and from 2562 to 2585 (including H90 and H91) are in blue, and those from 2586 to 2606 (H93) are in dark blue, and those from 1350 to 1378 (h43) are in grey. The nucleotides from 2299 to 2317 (H84) are in olive green. The nucleotides from 1860 to 1882 (H68) are in dark brown. The nascent polypeptide in α-helical form is shown in violet and denoted by a small letter p at its N-terminus. Helix numbers and the other symbols are as in (a).

The location of two highly conserved G18 and G19, near the position 20:1 in A-tRNA is facing toward the T-loop of P-tRNA. This is because the position 20:1 is accessible to h23 of 16S rRNA (Rinke-Appel et al., 1995). Their variable loops are replaced by the largest ones observed so far and situated remote from the two codons on the mRNA (Nagano and Nagano, 1997). The location of A1196 in h34 is closest to m8 and m9 positions of mRNA to represent a crosslinking distance between the two nucleotides (Sergiev et al., 1997). The closeness between h37 and h40 meets the requirement from a crosslink between the nucleotides 10901094 and 1161-1164 (Mueller and Brimacombe, 1997), while the location of U1126 in h39 is to satisfy a crosslink between the nucleotides 1125-1127 and 1280-1281 in h41 (not shown here but contained in 1IP8) (Mueller and Brimacombe, 1997). One of the purposes of Figure 6a is to show a possibility of SRL in red interacting with its complementary nucleotides 1069-1075 in light blue before the formation of the long helix, when domain G of EF-G enters into the interface of the two subunits and collides with the SRL. The nucleotide U1075 of 16S rRNA is shown by a purple letter U in Figure 6a, in which G2655 of 23S rRNA is also shown by another purple letter G. It was found that a G2655C mutation in the SRL region in E. coli sequence showed a lethal effect on cell growth (Macbeth and Wool, 1999). A more detailed analysis about the mutation of G2655 on EF-G-dependent translocation has shown the following effects: G2655A showed a little difference from the wild type, G2655C was the most defective, and G2655U was intermediate (Leonov et al., 2003). These results as well as no effect on EF-G-independent spontaneous translocation were reasonably explained by the base-pairing capabilities, as described above. Figure 6a can explain that the G2655 is the most probable target for triggering the EF-G-dependent translocation by an attack of U1075 of 16S rRNA under a condition that the h36 and a part of h35 could be considerably fragile. The distance between G2655 of 23S rRNA and U1075 of 16S rRNA in the X-ray structure of ribosome is 126.4A° and too far to allow the hypothetical base-pairing mechanism, while it is 58.7 A° in the present model. The shortest distance between the two regions is 47.6 A° for A2657 of 23S rRNA and U1073 of 16S rRNA, that would be close enough to make a

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Kozo Nagano

distance of about 20 A° for a base pair in the A-form helix upon conformational fluctuation. The distance could be much smaller when the region around h35 is totally unfolded shortly after the barrier melting, as discussed before. In the case of EF-G-independent spontaneous translocation, such a specific mutational effect was not detected (Leonov et al., 2003). It would probably mean that the collision between h35 and SRL is more randomly fluctuated without EF-G•GTP complex. A2309 at the loophead of H84 of 23S rRNA crosslinks strongly to the position 20:1 of A-site tRNA in the prestate and also to the same position of P-site tRNA (Rinke-Appel, 1995) probably in the pre- and poststates, as shown in Figure 6b. (The atomic coordinates for Figure 6b are the same as those for Figure 6a, viz. the PDB file 1IP8.) Since the same nucleotide can crosslink to the position 47 and the nucleotide C2306 to the position 8 of P-site tRNA (Rinke-Appel, 1995), this must be situated on the left-hand side to the position 20:1 of AtRNA, but closer to the nucleotide G693 of 16S rRNA. The location of the loophead of H84 in the crystal structure of 70S ribosome (see Figure 6E of Yusupov et al., 2001) does not seem to satisfy such a crosslinking condition. U2586 at the feet of both H90 and H93 also crosslinks to the same position of A-site tRNA, while U2584 to the aminoacyl residue (Rinke-Appel, 1995). On the other hand, A2602 is a footprint site of both A- and P-site tRNAs (Moazed and Noller, 1989). One more strong crosslinking nucleotide C885 at the loophead of H38 to the same position of A-site tRNA must be situated nearer to G693 of 16S rRNA. This location of H38 is not shown in Figures 6a and b, but in Figure 8a. H74 and H75 are positioned behind P-tRNA, because both helices seem indispensable for all living species but H76, H77, H78, and H79 are missing in animalia and trypanosome mitochondrial LSUrRNA (see Figures 10B and C of Raué et al., 1988). Such an arrangement of the abovementioned nucleotides are shown in Figure 6b. A stereochemically sound connection between H74 and H80 through the foot of H75 is made in order to achieve a G-C pair between G2252 in the P-loop of 23S rRNA and C74 of P-site tRNA (Samaha et al., 1995). Another direct base pair to C75 of A-site tRNA from G2553 of 23S rRNA (which is called Aloop) was found (Kim and Green, 1999) and was confirmed by use of a puromycin derivative in the difference fourier analysis of the 50S ribosome (Nissen et al., 2000). The puromycin crosslinked to G2553 could still form a peptide bond (Green et al., 1998). Figure 6b shows such a placement of helices, H74 and H80 as well as H90, H91 and H92. Under this condition the most reasonable arrangements of H73, H93 and H94 were explored. In order to connect the H73 with the SRL in H95, H73 must occupy a considerably large space below both tRNAs at the A and P sites, reserving rather small space for connecting with H90 and H93. The nascent polypeptide chain in α–helical form is also shown in Figure 6b, although it might not be α–helical. The locations of H89 and the domains IV and V of EF-G are quite the same as those in Figure 6a. Besides, the location of h43 of 16S rRNA in the prestate is also shown, at the foot of which the nucleotide C1378 crosslinks to position 32 of A-site tRNA (Rinke-Appel et al., 1995). The nucleotides U1376 and C1378 are observed to crosslink to the same position of E-site tRNA instead of P-site tRNA in the poststate (Rinke-Appel et al., 1995). (The distances discussed above are listed in Table 1.) This means that a considerably drastic conformational change would be involved in the 3D structure of 16S rRNA during translocation. A694 at the loophead of h23 is a strong crosslinking nucleotide for the 20:1 position of both A- and P-site tRNA (Mueller et al., 1997). When we restrict the crosslinking

Stereochemical Mechanism of Translation...

43

condition to the prestate, the A694 can approach to the position 20:1 of A-tRNA from the left-hand side. It can also crosslink to the same position of the P-tRNA after translocation. The adjacent nucleotide G693 is also a strong crosslinking candidate for the position 32 of both P- and E-tRNAs. This is the main reason why h23 must be situated on the left-hand side in both pre- and poststates, as shown in Figures 7a and b. (The atomic coordinates of the models in Figures 7a and b are given by 1IP8 for prestate and 1IPM for poststate, respectively). The location of A694 in Figure 7b explains well the crosslinking to the mC32 of E-tRNA but does not seem to be good for that to the A20:1 position of P-tRNA (Mueller et al., 1997). If it is situated at the same position as in Figure 7a, such a crosslinking condition would be satisfied. The location of the loophead of h23 in the crystal structure of the 70S ribosome binding three deacylated tRNAs is found near E-tRNA (see Figure 8A of Yusupov et al. (2001)), which seems to be the structure in the poststate.

a

b

Figure 7. Stereo pictures showing the locations of the nucleotides A694, U1376, and C1378 of 16S rRNA and some of the other nucleotides. The models are viewed as in Figure 5. (a) P-atom model of Aand P-tRNAs in the preribosome. A694 is situated near A20:1 which is adjacent to G19 of A-tRNA. (b) P-atom of P- and E-tRNAs in the postribosome. This model shows that G693 occupis a favourable location for explaining the crosslinking possibility of mC32 of E-tRNA to G693, but is not suitable for explaing a crosslinking of A694 to A20:1 in poststate. If the location of h23 is almost the same as in (a), A694 could be crosslinked to A20:1 of P-tRNA.

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Table 1. Comparison of the distances of interest among two different ribosome structures, X-ray structure of three tRNA binding 70S ribosome (1GIX, 1GIY), and the predicted models in the present work (1IP8, 1IPM, 1IPU) distance 1GIX-1GIY G2655(23S)-U1075(16S) U2656(23S)-G1074(16S) A2657(23S)-U1073(16S) C2658(23S)-G1072(16S) G2659(23S)-C1071(16S) A2660(23S)-U1070(16S) G2661(23S)-C1069(16S) A2662(23S)-U1068(16S) A1196(16S)-m61 A1196(16S)-m8 A1196(16S)-m9 U or A1197(16S)-m6 U1052(16S)-m6 G1053(16S)-m6 C1054(16S)-m6 C1054(16S)-Ala163(S3) A1055(16S)-m6 U1090(16S)-G1164(16S) U1091(16S)-G1164(16S) U1126(16S)-U1281(16S) G1127(16S)-A1280(16S) Pro 92(L11)-A 896(23S) Pro 92(L11)-C2474(23S) Thr 19(L11)-A2660(23S) C 885(23S)-G20(A-t) C 885(23S)-A21(A-t) C2475(23S)-U47(A-t) U1065(23S)-Gly502(EF-G) U1065(23S)-Gly503(EF-G) G1074(16S)-Asp393(EF-G) G1920(23S)-Gly520(EF-G) G1920(23S)-Gly520(EF-G) D16(A-t)-U47(P-t) A694(16S)-G20(A-t) A694(16S)-A21(A-t) A694(16S)-G20(P-t) A694(16S)-A21(P-t) G693(16S)-omC32(P-t) G693(16S)-omC32(E-t)

(Å) 126.40 125.46 123.71 117.40 109.45 102.20 105.56 106.66 18.91

20.72 27.88 24.05 21.88 29.98 23.64 19.62 19.54 8.97 16.64 26.69 22.95 33.64 20.90 22.70 29.98

11.90 69.52 69.07 50.96 48.82 35.07 26.43

distance 1IP8

distance 1IPM

distance 1IPU

(Å) 58.68 49.53 47.64 49.28 55.51 60.51 62.58 65.31 20.59 11.90 17.82 17.65 32.17 34.02 33.68

(Å) 18.53 20.05 19.49 18.96 18.46 18.29 20.66 23.54 37.24 30.81 29.02 39.95 27.32 30.73 35.78

(Å) 91.49 86.28 90.99 86.46 80.33 75.69 76.15 77.33 30.45 22.15 24.93 27.45

29.26 9.62 13.15 23.67 13.98 59.62 31.54 39.06 22.57 20.23 39.88

32.98 66.19 71.03 74.81 71.56

38.85 9.62 13.15

68.32 9.45 9.72 72.67 51.92 51.51

77.64

16.71 29.14 29.36 35.52 17.60 12.40 55.50 54.15 52.80

34.00

65.92 64.73 53.66 22.23

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45

Table 1. (Continued) distance 1GIX-1GIY C1378(16S)-omC32(A-t) C1378(16S)-omC32(E-t) U1376(16S)-omC32(E-t) A2309(23S)-G20(A-t) A2309(23S)-A21(A-t) A2309(23S)-G20(P-t) A2309(23S)-A21(P-t) A2309(23S)-G47(P-t) C2306(23S)-U 8(P-t) U2586(23S)-G20(A-t) U2586(23S)-A21(A-t) U2584(23S)-aa(A-t)2 A2602(23S)-A73(A-t) A2602(23S)-A76(A-t) A2602(23S)-U47(P-t) A2602(23S)-A76(P-t) A2451(23S)-aa(A-t) A2062(23S)-aa(A-t) G2252(23S)-C74(P-t) G2553(23S)-C75(A-t) C421(23S)-A76(A-t) C421(23S)-A76(P-t) C421(23S)-A76(E-t) C421(23S)-C2394(23S) C421(23S)-m2 G2394(23S)-A76(A-t) G2394(23S)-A76(P-t) G2394(23S)-A76(E-t) G2394(23S)-m2 1

(Å) 54.72 19.63 18.82 34.67 38.84 19.92 20.49 26.01 44.14 71.71 73.06 10.95 15.14 14.57 48.34 7.81 8.88 20.37 15.46 17.48 102.14 91.20 57.39 62.02 126.40 59.25 53.06 16.32 91.72

distance 1IP8 (Å) 13.52

distance 1IPM

distance 1IPU

(Å)

(Å)

6.83 11.36 15.19 12.96 43.19 42.38 46.81 51.50 9.03 13.96 31.68 32.48 33.36 12.57 35.77 29.47 13.08 17.55 16.39 74.42 60.17 35.72 118.12 58.18 48.04 112.58

10.87 15.55 38.42 23.23

67.64

66.45 46.62 48.70 32.70 18.50

89.93 64.14 36.39 132.64 61.29 63.39 118.72

42.06 38.77 17.35 12.55 51.13 36.49 54.53 55.32 81.03 38.67 51.18 54.33 17.53 107.62 51.18 18.50 79.95 128.57 91.11 64.14 55.86 138.38 120.57 63.28 46.56 110.00

m1 m9 represent P-atom positions of respective nucleotides on mRNA upstream count from m1 as the first P-site codon base-pairing with the 36th nucleotide of P-tRNA. m6 denote the third A-site codon base-pairing with the 34th nucleotide of A-tRNA. 2 aa denotes the aminoacyl-residue of the ternary complex of EF-Tu.GTP. The atomic coordinate of aminoacyl-residue of the ternary complex of EF-Tu.GTP is represented by that of O3* atom of A-tRNA in the crystal structure 1GIX. For the predicted models, 1IP8, 1IPM, and 1IPU, aa is represented by the P-atom coordinates of A76(A-t), A76(P-t), and A76(E-t), respectively. (A-t) denotes A-tRNA in the crystal structure, 1GIX, and A-tRNA in the predicted models, 1IP8 and 1IPU. (A-tRNA in 1IPU is the same as T-tRNA.) (E-t) denotes E-tRNA in the predicted models, 1IPM and 1IPU, while (P-t) represents three different P-tRNA models in 1IP8, 1IPM, and 1IPU.

Kozo Nagano

46

a

b

c

Figure 8. Stereo pictures showing the connectivity between H89 and H95. (a) The main chains of 23S rRNA in the preribosome corresponding to Figures 6a and b. H95 in red and H89 in light blue are the same as those in Figure 6. The region of nucleotides 862 to 915 of H38, the tip of which 881-895 is Asite finger, is drawn in orange. H92 and H93 as in Figure 6b. The nucleotides from 2246 to 2258 (H80) are in pink. The region from 2043 to 2057 and from 2611 to 2625 (H73) is in green, the region from 2626 to 2645 and from 2770 to 2788 (H94) in violet, the region from 2675 to 2731 (H96) in olive green, and the region from 2732 to 2769 (H97) in blue. The other regions are from 2023 to 2042 (H72), from 2058 to 2079 (H74 and H75), from 2241 to 2245 (H75), from 2434 to 2454 (H75), from 2497 to 2585, from 2607 to 2610 are in grey. The locations of four crosslinking nucleotides C885, A2309, and U2586 to the position 20:1 of A-tRNA and A2451 to aminoacyl residue, as well as two guanines G2252 base-pairing to C74 of P-tRNA and G2553 to C75 of A-tRNA are denoted by numerals. (b) The main chains of 23S rRNA in the postribosome. The regions drawn in this figure are almost the same as in (a) except the A-site finger region of H38. This structure represents the changes in the positions of the regions after the long helix formation, in which recognition of either stop signal or sense codon is about to occur. The colours and other symbols are as in (a). The location of U2586 is shown by a numeral, although it is not favourable for crosslinking to any particular nucleotides. (c) The main chains of the regions as in (b) in the midway substate during translocation. This structure represents the substate in which the tRNA docking pair (not shown) is rotated by 25° from the prestate around the symmetry axis of the ASLs of A-tRNA in the prestate and E-tRNA in the poststate (angle difference between A- and P-tRNAs and between P- and E-tRNAs is 50°). The colours and other symbols are as in (a). It is noticeable that H83 and H84 are behind the decoding region so that they do not obstruct the tRNA movement.

Before GTP hydrolysis of the EF-G•GTP complex, the domains IV and V of EF-G in the orientation, as shown in Figure 6a, would not only push A-tRNA toward P site, but also touch somewhere of 16S rRNA that could influence the h43 for inducing the necessary conformational change as a device for triggering in translocation. This might be associated with the movement of a part of the barrier, G1338 and A1339, as discussed in the section.2. Another device for triggering seems to be the orientation of H89 of 23S rRNA, which is locked by H38 in the prestate, as shown in Figure 8a. (The atomic coordinates for Figure 8a are the same as those for Figure 6a, viz. the PDB file 1IP8.) In Figure 8a, H89 is located on

Stereochemical Mechanism of Translation...

47

the right-hand side of H38. The reason for this is that C2475 at the tip of H89 is found to crosslink to the position 47 of A-site tRNA, while C885 at the tip of H38 (A-site finger) to the position 20:1 of A-site tRNA (Rinke-Appel et al., 1995). It was also shown by the method of directed hydroxyl radical probing that the 92nd residue of L11 is close to U896 at the stem of H38 (A-site finger) and U2474 at the tip of H89, while that its 19th residue is near to A2660 at the loophead of SRL (Holmberg and Noller, 1999). As to the placement of H89, G2455 must be situated near the 3’-end of A-tRNA, because both A2451 and A2062 at the foot of H74 crosslink to the aminoacyl residue attached to the 3’-end of A-site tRNA (RinkeAppel, 1995). Moreover, it was found that A2451 plays an important role in forming the peptide bond being synthesized (Nissen et al., 2000). (The distances between the residues discussed above are listed in Table 1.) After the binding of EFG•GTP complex the H89 is pushed down by the domains IV and V of EF-G, giving rise to opening the block of H93 against spontaneous translocation. H89 moves below the new P-tRNA (which was at the A site in Figure 6a), as shown in Figure 8b, although the P-tRNA is not shown. (The atomic coordinates for Figure 8b are given in 1IPM.) When translocation starts, H93 would move along with the old P-tRNA in the direction of E site, and work as a stopper of the new P-tRNA. Therefore, the orientation of EF-G in Figure 6a seems to be consistent with the well-known functions of the ribosome in translation. In Figure 8b, it is assumed that SRL is interacting with the region 1069-1107 of 16S rRNA in preparing for the interaction with the GTΨCG sequence of a new aa-tRNA by the region 1103-1107 of 16S rRNA. H38 would not appear because A-tRNA does not exist in the poststate. The location of H38 would be the same as that observed in the crystal structure of 70S ribosome (Yusupov et al., 2001). On the other hand, an intermediate substate model between the pre- and the poststates was explored as shown in Figure 8c, in which the location of a docking pair tRNA model (Nagano and Nagano, 1997) was rotated by 25˚ around the symmetry axis between the two tRNA pairs in the two stable elongation states. (The atomic coordinates for Figure 8c are given in the PDB file 1IPL.) The locations of H83 and H84 are quite different from the corresponding locations in Figures 8a and b, because base pairs of the pseudo knots, CCA415/UGG2410, AUG2330/CAU2387, and G2282/C2427 (Gutell, 1993) are kept, although their locations are also changed drastically. The SRL interacting with the region 1064-1107 of 16S rRNA gives a rotational twist about the relative locations of H94, H96 and H97 resulting in passing H73 and H94 across the base pair between the A-loop and the position 75 of A-tRNA and putting off the brake (H38) against the spontaneous translocation of the tRNA docking pair, while the interaction of the region 1103-1107 of 16S rRNA with the GTΨCG of A-tRNA produces a rotational twist around the symmetry axis of the two elongation states. This movement makes H93 collide with H80, disrupts the base pair between the P-loop and the position 74 of P-tRNA, and makes it possible to form new base pairs between the two consecutive guanines 2251 and 2252 and the two consecutive cytidines 74 and 75 of the old A-site tRNA at the P site. This seems to be the essential point of the mechanism of translocation.

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Kozo Nagano

5. Estimation of a Degree of Correctness in the Predicted Models Presented Above Moazed and Noller (1989) first presented by chemical probing the evidence of the nucleotide C2394 of 23S rRNA being in contact with E-site tRNA. Direct contact of this nucleotide with the A76 of the E-site tRNA was confirmed by X-ray analysis (Schmeing et al., 2003). It was also observed in the X-ray results of the whole ribosome (Yusupov et al., 2001). It was a little before the paper of Yusupov et al. (2001) appeared when the present author had deposited the models of 1IP8, 1IPU, and so on, to the Protein Data Bank without seriously considering the importance of the direct contact of C2394 with A76 of E-site tRNA. Figure 6a presents a model of two tRNA molecules bound to the A and P sites, in which the nascent polypeptide is just bridging between the two 3’-oxy groups of the A76 nucleotides in transpeptidation. After finishing the transpeptidation, the deacylated 3’-end nucleotide of PtRNA is open for accepting C2394 at the foot of H88 in preparing for the hybrid P/E site on the side of large subunit. Figures 9a and b shows the locations of the C2394 in the models of 1IP8 and 1IPU, just behind and below the A76 at the P and E sites, respectively. These models were built following the knowledge of secondary structure of 23S rRNA (Gutell, 1993; Brimacombe, 1995), the reasonability of experimental facts and the stereochemical consistency. As a result, the distances between the locations of A76 at the P site in Figure 9a (1IP8) as well as at the E site in Figure 9b (1IPU) and C2394 are quite reasonable considering the flexibility of the regions around the nucleotides 2388-2393 and 2422-2426 of 23S rRNA and the rather arbitrary positioning of the 3’-end of H22. The distance between the location of A421 of 23S rRNA in Figure 5c and that in Figures 9a and b is 26.0 A°. The 3’-end CCA conformation of the deacylated P-tRNA in Figure 9a and E-tRNA in Figure 9b can be directed toward the position of C2394. Figure 9a also shows that the spatial relationship between H88 and H22 could be rather flexible, unless the position of C2394 is fixed. This seems to show that a degree of correctness in the present prediction is rather satisfactory. When the long helix is made immediately after the binding of EF-G•GTP, the binding of C2394 to the A76 at the P site would affect the orientations of helices H74 and H80, and the changes of the locations of large subunit helices, described concerning to Figure 8b, would precede the rotation of the decoding site on the small subunit. Although the present author did not think about such a time lag at that time, the formation of the intermediate ‘twisted‘ hybrid state of P/E and A/P sites, that is still reversible (Moazed and Noller, 1989; Zavialov et al. 2005) before completion of translocation, can be explained from this model building work rather without difficulty. Kajiro (1978) first insisted that the binding of EF-G•GTP to ribosomes triggers for translocation, because EF-G complexed with an uncleavable GTP derivative promoted one cycle of translocation. The results of cryo-EM study of Spahn et al. (2004) on yeast 80S eEF2•sordarin complex supported the above view. In their structure, the tip of domain IV of eEF2 occupied the location of ASL of the A-site tRNA after completion of translocation despite no GTP hydrolysis. The main body of the domain IV was found near h34 and h33, while its G domain made a contact with the SRL. Experimental technique such as cryo-EM was not able to detect the structure of the whole ribosome shortly before translocation started, as suggested by the predicted model of the preribosome in Figure 6a. At that time the present

Stereochemical Mechanism of Translation...

49

author thought that the conformational change of EF-G between the GTP and GDP forms could be enough for pushing the A-site ASL toward the P site. In contrast, the nucleotides 1103-1107 could interact with the T-loop of A-site tRNA for pushing it toward P site in the case of EF-G independent spontaneous translocation. The potential energy of the preribosome binding eEF2•GTP (or EF-G•GTP for prokaryote) complex would be considerably high compared to that of the postribosome with the factor•GDP complex. Spahn et al. (2004), however, did not mention the conformational change between the two forms of the eEF2. GTP hydrolysis would be required for releasing the eEF2•GDP (EF-G•GDP) and restoring the open form of the small subunit (Ogle and Ramakrishnan, 2005). a

b

Figure 9. Stereo pictures showing a degree of correctness of the present predicted models. The models are viewed as in Figure 5. It is worthy to note that the C2394 in both pre- and poststates is at the reachable range from the 3’ end nucleotide A76 of both E- and P-tRNAs, even though the models were built without knowing the tight binding as a large subunit E site (Yusupov et al., 2001; Schmeing et al., 2003). (a) P-atom model of A- and P-tRNAs in the prestate and the H88 and H22 bound together by a pseudoknot helix CCA415/UGG2410. (b) P-atom model of T-, P-, and E-tRNAs in the transition-state in the proofreading mechanism and the H88 and H22 bound together.

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50

Before closing the foregoing sections on the problems of translocation, it must be clarified that the E site of the P-E tRNA docking pair model is consistent with the E site of Nierhaus et al. (2000) and the E’ site of Paulsen and Wintermyer (1986) in the sense that three nucleotides of the anticodon of the deacylated tRNA bound to this site are base-paired with the E-site codon on the mRNA, while the anticodons of the E2 site of the former and the E site of the latter are separated from the E-site codon. Nierhaus and his coworkers insist that such a situation of the three base pairings of E-site codon with the anticodon of the tRNA bound to only one defined E site can be achieved in poststate under the conditions of polyamine buffer and in native polyribosomes (Nierhaus et al., 2000).

a

b

Figure 10. Stereo pictures showing the all-atom representation of the conformation of the decoding site when a stop-signal recognizing tripeptide, Pro-Ala-Thr, is bound to the stop codon, UAA. This model is viewed as in Figure 5. The tripeptide is drawn in red, mRNA in light blue, and the anticodon region from A31 to A36 of P-tRNA in green. Some of the residue numbers are shown by numerals. (a) Part of the long helix is formed between the SRL nucleotides, G2655-A2662, of 23S rRNA in magenta and those of G1068-U1075 of 16S rRNA in grey. The other related regions of 16S rRNA are also shown in grey. UUA indicates the P-atom position of U1090 of 16S rRNA. (b) A more detailed model of the tripeptide and the UAA/UUA helix at the loophead of h37 of 16S rRNA, which is drawn in dark blue.

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6. Recognition of Stop Signal after Translocation Shortly after the step of translocation, described above, the next codon for a coming new aa-tRNA is checked whether it is one of the three stop signals, UAA, UAG, and UGA or not. Three kinds of class-1 release factors are known to recognize stop signals as follows: RF1 has the conserved tripeptide motif Pro-Ala-Thr for recognition of UAG and UAA, RF2 in prokaryotes has the motif Ser-Pro-Phe for UGA and UAA, and a single eukaryotic one eRF1 has the tetrapeptide motif Asn-Ile-Lys-Ser for UAG, UGA, and UAA (Kisselev and Buckingham, 2000). It was insisted that a tripeptide Pro-Ala-Thr in prokaryotic RF1 can recognize the stop signals specifically (Ito et al., 2000). Furthermore, the above three motifs of class-1 RFs have been believed to recognize stop signals directly as if they are anticodons, and are recently confirmed for RF2 by cryo-EM experiments (Rawat et al., 2003; Klaholz et al., 2003), and for eRF1 by analogy from its tRNA-like shape of the crystal structure (Song et al., 2000). However, a big question still remains unsolved as to how the first base of stop signals, U, is recognized (Kisselev and Buckingham, 2000). Here, it is explained by use of base pairing with the UUA sequence at the loop of h37, as a transient precursor before replacement with the stop-signal recognizing tripeptides. Such a model of tripeptide Pro-AlaThr binding to UAA/UUA helix is found stereochemically reasonable and shown in Figure 10a. (Its atomic coordinates for Figure 10a are given in the PDB file 1IPN.) A more detailed picture around the tripeptide Pro-Ala-Thr of the model is presented in Figure 10b. (Its coordinates are the same as those for Figure 10a.) If the codon is UGG, the UGG/UUA base pairs would not be stable enough because of two consecutive wobble pairs. If the stop signal is UAA, any one of RF1, RF2, and eukaryotic eRF1 will work for termination. If the stop signal is either UGA or UAG, the stability of the stop-codon/UUA helix would be a little weaker. Based on the effects of mutations of a conserved C1054 in h34 of small-subunit rRNA (SSU-rRNA) (C1054A, C1054U, and C1054G caused a suppression of UGA, UGA and UAG, and UAA and UAG, respectively), and the other two conserved nucleotides at the GTPase associated centre in H43 and H44 of LSU-rRNA (A1067 deletion, A1067C, and A1067U as well as G1093A caused a UGA-specific suppression), interactions of the rRNAs either with mRNA or with a stop-codon-RF complex have been proposed (Arkov and Murgola, 1999). On the other hand, a direct interaction between stop signals and RF2 has been proposed on the basis of crosslinking data suggesting that the fourth base of the stop signal interacts RF2 as well as the decoding site of SSU-rRNA, the nucleotides 1385-1420 in h28 and h44 (Brown and Tate, 1994). The two results of the above different approaches can be confirmed by the recent result of cryo-EM structures (Rawat et al., 2003; Klaholz et al., 2003). Particularly important is the result of mutations suggesting that the regions of both SSU- and LSU-rRNAs considerably far from the stop signal itself (Arkov and Murgola, 1999) actually affects the stability of the stop-codon-RF2 complex and that UGA makes it most unstable in contrast to the most stable complex of UAA. The other result of mutations on stop codon UGA and UAG readthrough in E. coli (O’Connor and Dahlberg, 1995) suggests that the change in the nucleotides only in contact with the body of RFs (not directly with the stop codon) could affect the stability of the stop-codon-RF complex. Ivanov et al. (2001) insisted that the hairpin loops of H69 and H89 of LSU-rRNA provide anticodons of UAG and UGA, respectively, as if both helices play a role of a stop signal recognizing tRNA.

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Although both loopheads were found in the proximity of the tripeptide motif Ser-Pro-Phe in the cryo-EM structures of the termination ribosome complex (Rawat et al., 2003; Klaholz et al., 2003), their locations were not close enough to make a complete helix in the presence of solid and voluminous structures of mRNA and tRNAs bound to P and E sites. The loophead of H89, in particular, seems to be located fairly far from the stop signal. Besides, what would happen to them when the A-site codon is either UAA or UGG. The codon for tryptophanyltRNA, UGG, would make more stable codon-hairpin helices with the hairpin loops of H69 and H89, CUA and UCA, respectively, than those of UAA/CUA and UAA/UCA. If one of the hairpin loops binds to the stop signal as if they were a kind of tRNA, there would be no more enough space for release factors. It is known that the neighborhood of mRNA in the A site is almost occupied by h18, h34, and h44 of SSU-rRNA. Accordingly, it would be more favourable for the UUA at the loophead of h37 of SSU-rRNA to make a first contact with the stop signal, to allow one of the tri- or tetrapeptide motifs to come close enough, and to withdraw immediately either after the recognition of a RF (or eRF1) for the purpose of receiving an aa-tRNA•EF-Tu(or eEF1)•GTP ternary complex. It seems to be a common mechanism to all living kingdoms except for mitochondria of some protista (T. brucei and P. falciparum) and animalia. An evolutionary trend can be observed that the number of nucleotides involved in the region of h34 – h37 has been larger and larger from mitochondria to eubacteria and eukarya. It is known that stop signals for vertebrate mitochondria are UAA, UAG, and instead of UGA, AGA and AGG (see Tables 10 and 12 of Osawa et al., 1992). Since mitochondrial tRNAs of animalia and some of the above protista are so simple, the first release factors might have evolved with a help of some regions of LSU-rRNA. This problem, however, remains still vague and uncertain. The codon for tryptophan is UGA for animalia and fungi mitochondria (see Table 12 of Osawa et al., 1992), UGG for plantae mitochondria as well as for archeae, chloroplast and eukarya, and either UGA or UGG for protista mitochondria and eubacteria (Sprinzl et al., 1998). The evolution of Trp-tRNA seems to have been developing in relation with that of stop signals (and protein factors, RF1, RF2, eRF1, and so on) as well as suppressor-tRNAs (Hirsh and Gold, 1971) and selenocysteine-tRNA (Hatfield and Diamond, 1993). Here the present author does not go into the problem of peptRNA hydrolysis. Rather interesting as to the present topic is the mechanism of removing class-1 release factors from the ribosome that requires GTP hydrolysis (Kisselev and Buckingham, 2000). If it is a process independent of translocation, the stability of the stopcodon/peptide-motif would not be strong enough compared to that of stop-codon/UUA helix. It is known that the X-ray structure of prokaryotic release factor does not resemble the shape of tRNA (Vestergaard et al., 2001). It is still enigmatic in what shape the RFs enter the decoding centre when a stop signal is detected, and retire from the location when GTP is hydrolyzed. When RF1 comes deep in touch with a stop signal UGA and finds itself unsatisfactory, how does RF2 take over the position by expelling the former occupant RF1 without GTP hydrolysis? The UUA in the loop of h37 could stay at the stop signal until a correct RF (either RF2 or eRF1 in this case) finds its binding site. When the UUA once leaves the position without finding any suitable RF, the stop signal could be open for either some suppressor-tRNAs or selenocysteine-tRNA, as described in the next section. If the stop signal is suppressed without having any frameshift, some role of the UUA could be important.

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7. Recognition of Sense Codon after Translocation When the A-site codon does not turn out to be a stop signal, the structures around the Asite tRNA as well as both the SRL region of 23S rRNA and the 5’-side of h35 of 16S rRNA return to those of poststate. When a newcomer of aa-tRNA•EF-Tu•GTP ternary complex comes at first to the strands 1103-1107 of 16S rRNA, its anticodon must be checked in the second place. It would be, however, almost without a break between translocation and codon recognition in the sense that the latter process could start before the elongation factor•GDP complex of the former process leaves the ribosome. More than 20 types of aa-tRNA complexed with EF-Tu•GTP could visit the A-site codon without need of making contact of its G domain with the GTPase associated centre. It would be a more efficient way of searching a cognate aa-tRNA if the GTPase associated centre around the SRL is still occupied by EF-G•GDP, although such an orientation of the ternary complex could not be confirmed by cryo-EM reconstruction of kirromycin-stalled ternary complex in the A site of the 70S ribosome at a resolution of ~ 20Å (Stark et al., 1997; Valle et al., 2002). It is known that peptidyl transferase reaction does not occur if aa-tRNA is bound to ribosome with EF-Tu and a nonhydrolyzable analogue of GTP (Skogerson and Moldave, 1968). Only when the GTPase associated centre is needed by a cognate (or near-cognate) ternary complex, the space would be open for the EF-Tu•GTP. On the other hand, EF-Tu•GDP must leave the place as quickly as possible after GTP hydrolysis, because EF-G•GTP comes to take over for accomplishing translocation. This could be the reason why EF-Tu•GDP (Kjeldgaard and Nyborg, 1992) makes a drastic conformational change with respect to the conformation of EF-Tu•GTP (Berchtold et al., 1993; Kjeldgaard et al., 1993). It seems possible for the newcomer ternary complex to approach the T site before EF-G•GDP leaves the GTPase associated centre of the ribosome completely. Figure 11a shows the model of the ternary complex of Cys-tRNA•EF-Tu•GDPNP (Nissen et al., 1995) at the instant of entering by the right-handed twist of the long helix into the GTPase binding site, the most of which is still occupied by EF-G•GDP complex. (The atomic coordinates for Figure 11a are given in the PDB file 1IPO.) It can be seen that the G base of position 53 of T-tRNA (designated as 53R) is closest to the C base of the nucleotide 1107 of 16S rRNA and that the anticodon of the TtRNA (from 34R to 36R) is already base-paired with the A-site codon (from m4 to m6). Most of the T-tRNA would be rejected from the ribosome without having GTP hydrolysis. Some of the noncognate newcomer bound to the T site might have good base pairs with a certain frame shift, yet the base pairing of its GTΨCG strand with the region 1103-1107 of 16S rRNA would not be satisfactory. Accordingly, only cognate and near-cognate newcomer would be successful in forming the base pairs. When the newcomer is either cognate or nearcognate, both anticodon and T-loop of the aa-tRNA would have close contacts with mRNA and the region 1103-1107 of 16S rRNA, respectively, so that its D-loop could also make a contact close enough to make two G-C pairs between G18 and G19 of the T-tRNA and C56 and C61 of P-tRNA. Sprinzl et al. (1976) found that various tRNA fragments containing Dloop inhibited the aa-tRNA binding at the A site. This is one of the main reasons why we adopt a tRNA docking pair model (Nagano and Nagano, 1997) for explaining the mechanism of translocation and codon recognition. Such a stereo picture is shown in Figure 11b. (The atomic coordinates for Figure 11b are given in 1IPQ.) In this model, its GTΨCG strand forms

Kozo Nagano

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a

b

Figure 11. Stereo pictures showing the behavior of aa-tRNA in the mechanism of sense codon recognition. (a) A ternary complex of Cys-tRNA•EF-Tu•GTP (Nissen et al., 1995) enters the decoding site to make the codon-anticodon base pairs in the most favourable orientation for its GTΨCG sequence (53R-57R) in light blue closest to the nucleotides 1103-1107 of 16S rRNA in light blue. This site is a recognition mode of A site, which is refered to as T site, and abbreviated as R in these figures. The TtRNA in the ternary complex is drawn in magenta, while its G domain of EF-Tu in violet (and designated as EF-Tu-G), its GTP in brown, and domain II of EF-Tu (EF-Tu-II) in pink. P-tRNA, mRNA, 16S rRNA and SRL are a little different from those in Figure 6a. SRL as in Figure 8b. P-V denotes the largest variable loop chimerically introduced onto the 3D structure of yeast tRNAPhe. This type of interaction between the A-site codon and 20 kinds of aa-tRNAs seems possible shortly after GTP hydrolysis of EF-G•GTP and translocation, even if EF-G•GDP still occupies a large space near the GTPase associated centre. The numerals ending with R are residue numbers of T-tRNA. (b) The region surrounding an aa-tRNA brought by a ternary complex with EF-Tu•GTP. T-tRNA is drawn in magenta. This picture represents base pairs between GTΨCG sequence of aa-tRNA and nucleotides 1103-1107 of 16S rRNA in light blue and also between the region 2655-2661 of 23S rRNA (SRL) in red and the region 1069-1075 of 16S rRNA in light blue. This arrangement of tRNA facilitates fitting of its anticodon with A-site codon and also its D-loop with the T-loop of P-tRNA. The large R denotes the location of the anticodon loop of T-tRNA. P-T is the T-loop of P-tRNA, while R-V is the chimerically introduced largest variable loop of T-tRNA. The other labels are as in Figures 6a and 8a.

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an A-form helix with the strand 1103-1107 of 16S rRNA in light blue. The SRL is still basepairing with the region 1069-1075 of 16S rRNA. EF-Tu•GTP is far from the viewer without disturbing both P-tRNA and 16S rRNA. This is a putative transition-substate model of mRNA•tRNA•16S rRNA complex in the mechanism of codon recognition. The conformation of the anticodon loop of the T-tRNA is the same as that of yeast tRNAPhe (Holbrook et al., 1978), in which a hydrogen-bond between N3 atom of the base of U33 and O5’ atom of A36 of T-tRNA is formed (see Figure 5c of Holbrook et al., 1978). When the long helix is unfolded in the next step, the competition for survival between the T- and E-tRNAs is going to be held through the trasition-state three tRNA binding conformation, as already described in the section 2 and shown in detail by Figures 5a, b, c, and d. In the case of noncognate tRNA recognition, the base-pairing between the A site codon and the anticodon of the T-tRNA does not fit very well. This discrepancy at the anticodon loop of the T-tRNA is amplified at the R-P contact region under the condition of the basepairing between the GTΨCG of T-tRNA and the strand 1103-1107 of 16S rRNA and leads to a failure in forming two G-C pairs between the P- and T-tRNAs. As its result, the ternary complex of such a noncognate tRNA could be quickly discarded, as visualized in Figure 12a. (The atomic coordinates for Figure 12a are given in the PDB file 1IPR.) This structure minus leaving noncognate aa-tRNA•EF-Tu•GTP and EF-G•GDP complexes is the structure closest to that of poststate ribosome, although the region around the spectinomycin binding site is still interacting with the SRL. When the T-tRNA is either cognate or near-cognate, the conformational change at the anticodon loop can be expected. More precisely speaking, the codon-anticodon base pairs have a tendency to become more stabilized to form an ideal Aform with a right-handed twist between the first and second Watson-Crick base pairs. This would break a hydrogen-bond between N3 atom of U33 and O5’ atom of A36 of T-tRNA and force the U33 base to stick out. This conformational change of the anticodon loop at the A site seems to affect the increase in the proflavin fluorescence from wybutine at position 37, which monitors the environment of the anticodons with cognate and near-cognate tRNAs, but is not observed with noncognate tRNA (Rodnina et al., 1995), while that of proflavin at the D-loop showed a small initial increase on binding with all tRNAs including noncognate aatRNA (Rodnina et al., 1994). The present author assumes that the U33 is base-paired with an invariant adenine base of 16S rRNA for much better stability, as already described in the section 3. As a result, rotation at the middle part of the T-tRNA occurs and gives rise to a collision of D-loop of T-tRNA with T-loop of P-tRNA, resulting in formation of two G-C pairs between the consecutive invariant G18 and G19 of T-tRNA and the other invariant C56 and C61 of P-tRNA at the expense of one G-C pair between G53 and C61 of P-tRNA (viz. a gain of three hydrogen bonds). If the T-loop of P-tRNA is blocked by the D-loop in the various tRNA fragments (Sprinzl et al., 1976), such a recognition would end in failure. Valle et al. (2002) showed by cryo-EM that the T-loop side of cognate aa-tRNA•EF-Tu•GDP ternary complex bound to kirromycin-stalled ribosome interacts with the L11 binding region of the GTPase associated centre. When the T-tRNA is either cognate or near-cognate, the conformational change at the anticodon loop leads to formation of two G-C pairs between the consecutive invariant G18 and G19 of T-tRNA and the other invariant C56 and C61 of PtRNA. In this case, the U33 base at the anticodon loophead of the T-tRNA is half exposed, but the conformation of 16S rRNA concerned is pushed out by a pressure exerted from the

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triangular RNA helices to restore the conformation as shown in Figure 6a. Thus, the SRL of 23S rRNA restores the GTPase-active conformation. Such a model is shown in Figure 12b. (The atomic coordinates for Figure 12b are given in the PDB file 1IPU.) The G domain of EF-Tu intervenes between the 16S rRNA and the SRL at the GTPase associated centre, although the location and the orientation of the SRL is a little different from the model that is shown in Figure 6a. The spatial relationship between the T-tRNA and EF-Tu•GTP in Figure 12b seems to be exactly what we see in Figure 1b of Stark et al. (1997). This might be a reasonable explanation for why thiostrepton does not inhibit binding of the ternary complex of aa-tRNA•EF-Tu•GTP on the ribosome. We can understand also why the 3’-end of the tRNA does not reach the site of puromycin when GTP is replaced by a noncleavable derivative such as GDPNP (Skogerson and Moldave, 1968). In order to achieve a new AtRNA with its 3’-end at the peptidyl transferase centre, the highest barrier to be overcome is to bring the G-C pairs between the D-loop of T-tRNA (R-D in Figure 12b) and the T-loop of P-tRNA (P-T in Figure 12b) much closer to the axis of rotational movement of tRNA docking pair in translocation to break the G-C pairs between the D-loop of P-tRNA (P-D) and the Tloop of E-tRNA (not shown in Figure 12b) as well as the codon-anticodon base pairs at the E site. Since the near-cognate tRNA is characterized by an excess of GTP cleavages, most of near-cognate ternary complex would be discarded after GTP hydrolysis. Only very few nearcognate and most of cognate ones go to the structure shown in Figures 6a and b (except for EF-G•GDP structure). In the case of a near-cognate aa-tRNA, particularly when it is discarded, the conformation of 16S rRNA should come back to that of Figure 12a (without EF-G•GDP), and further return to the structure of poststate ribosome. The functional role of H96 and H97 would be important in switching the location and orientation of the SRL back and forth. H97 could make a direct contact with the tip of H84 in this sub-state, as shown in Figure 12c. (The atomic coordinates for Figure 12c are the same as those for Figure 12b, viz. the PDB file 1IPU.) The locations of H84 and H97 are just below the E- and P-tRNAs and help the two G-C pairs of P-E tRNA docking pair resist against the invasion of the newly formed two G-C pairs between the T- and P-tRNAs. H93 is directed toward the SRL and located at the intermediate position between the pre- and poststates. This situation is just like two poises on a balance, and the shock transmitted from the conformational change of EFTu•GDP breaks the weaker side of the two codon-anticodon base pairs between the E and T sites. If the codon-anticodon interaction at the E site is either weaker or as strong as that of the T site, the H84 would move upward and breaks the P-E G-C pairs and expel the E-tRNA from the ribosome. T-tRNA occupies the A site, and H93 goes to the location of the prestate. On the contrary, if the T-site base pairs are weaker than those of the E site, H84, H93 and H97 return to their respective locations in the poststate, as shown in Figure 8b. This is exactly what we call proofreading mechanism. It would be important to realize that the above discussion does not hold at all for the most primitive ribosome structure of Trypanosoma brucei mitochondria, because H84, H96, and H97 are all missing. Accordingly, the functional role of the helices, H84, H96, and H97, could be that of enhancing the efficiency in the negative cooperativity between the T and E sites (Nierhaus, 1990), that is immediately related with enhancing the accuracy in codon recognition.

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a

b

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c

Figure 12. Stereo pictures showing the behavior of aa-tRNA in the mechanism of sense codon recognition as well as the regions surrounding the decoding site in the transition substate in with aatRNA•EF-Tu•GTP ternary complex. (a) When the T-tRNA in magenta is noncognate, it is discarded in the opposite direction from the GTPase associated centre near SRL in red. The ternary complex would shift in this direction under a pressure of the 16S rRNA involved in the model in Figure 8b when it’s Aform helix between the GTΨCG sequence of T-tRNA and the nucleotides 1103-1107 of 16S rRNA is unfolded. EF-G•GDP still occupies the same space as in Figure 6a and Figure 11a. Another ternary complex can approach the A-site codon by thrusting with its anticodon loop into the space between the discarded ternary complex and the EF-G•GDP complex and by restoring the 3D structure shown in Figure 6a. The symbols and colours are as in Figures 6a and b. (b) When the T-tRNA in magenta is either cognate or near-cognate, the 16S rRNA involved in the model in Figure 6a pushes the body of EF-Tu•GTP complex toward the SRL at the GTPase associated centre so that it could start GTP hydrolysis. Both base-pairings of codon-anticodon and between D-loop of T-tRNA and T-loop of PtRNA are kept. The A-form helices between the GTΨCG sequence of T-tRNA and the nucleotides 1103-1107 of 16S rRNA as well as between 1069-1075 of 16S rRNA and SRL are unfolded. G domain of EF-Tu shifts downward, and SRL also shifts below the G domain with its active A2660 facing to the GTP, which is not visible in this figure. In order for the aminoacyl group to reach the peptidyl transferase centre, EF-Tu•GDP must be released after GTP hydrolysis. A pressure due to the EFTu•GDP release would push the T-tRNA toward the axis of rotational movement in translocation, resulting in expelling E-tRNA, which is bound to the D-loop of P-tRNA at the location designated as PD in the case of cognate T-tRNA. On the contrary, a near-cognate codon-anticodon base pairs at the T site would be broken instead of breaking the codon-anticodon base pairs at the E site. R-D and R-T are the D- and T-loops of T-tRNA, respectively. It is clear from this picture that EF-G•GDP can no more occupy the space as in Figsures 6a and 11a. The other symbols and colours as in (a). (c) The regions surrounding the decoding regions in the transition substate of GTP hydrolysis in the aa-tRNA•EFTu•GTP ternary complex. It is important to note that the tip of H84 makes direct contact with H97 under the two G-C pairs of P-E tRNA docking pair (not shown in this figure), resulting in formation of a strong support against a pressure exerted from the new G-C pairs of R-P tRNA pair in the case of near-cognate T-tRNA but breaks the two G-C pairs of P-E tRNA pair in the case of cognate T-tRNA. See text for further explanation about the proofreading mechanism. The other labels and colours are as in Figures 6a and b as well as in Figures 8a, b and c.

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When the anticodon of T-tRNA is near-cognate, in contrast to the cognate codonanticodon base pairings at the P and E sites, the base pair, U33(A)-A1396(16S), would be finally broken, even if it could be once formed, because of an impulse caused by a conformational change of EF-Tu due to GTP hydrolysis and break the A-site codonanticodon base pairings as well as the G-C base pair between T- and P-tRNAs. In the case of cognate T-tRNA, on the other hand, those base pairs between P- and E-tRNAs would be broken faster by the reverse mechanism of barrier melting after the long helix formation is over. The codon-anticodon base pairings as well as the base pairs, U33(A)-A1396(16S) and G18(A)-C56(P), would be kept and induce another G-C pair, G19(A)-C61(P), that is exclusive against G18(P)-C56(E), resulting in formation of crystallographically observed Tloop-D-loop contact region. Such an elbow region of E-tRNA would be caught at the plane of its G19-C56 by a pseudoknot helix GUAGGAUA2119/ GACCUUGA2169, as observed by Korostelev et al. (2006), and brought away by a movement of L1 stalk as a result of 30S subunit closure (Ogle et al., 2002). The total of the above described conformational changes of the tRNAs and the surrounding decoding site on the small and large ribosomal subunits before and after GTP hydrolysis is usually referred to as proofreading mechanism. The 3’ end of aa-tRNA at the T site goes to the peptidyl transferase centre at the A site and becomes AtRNA, giving rise to transpeptidation with the 3’ end of P-tRNA. The final structure is ready for the next step of the elongation cycle in cooperation with EF-G•GTP complex at the GTPase associated centre of the large subunit ribosome.

8. Comparison of the Present Proofreading Mechanism with the other Proposed Ones In protein biosynthesis, mostly cognate and very few near-cognate aa-tRNAs can be allowed to enter the A site under the structural control of both EF-Tu•GTP and ribosome with an error rate of about 1 per 103 ~ 104 amino acid residues incorporated (Fersht, 1985). Such a high specificity of codon recognition is far beyond the thermodynamically expectable limit if the codon recognition occurs only in a single step. Even if a kind of induced-fit mechanism is introduced, only a simple conformational change would not be enough to explain such a low error rate of recognition (Hershlag, 1988). Accordingly, the two-step tRNA selection mechanism has been proposed. The first step before GTP hydrolysis is called initial selection, while the second after GTP hydrolysis is proofreading (Rodnina and Wintermeyer, 2001). Various steps more than two were detected using single-molecule fluorescence resonance energy transfer (smFRET) (Blanchard et al., 2004b), the schematic representation of which was shown as seven steps in total (Blanchard et al., 2004a). The measurements were made for the time-dependent distances between donor and acceptor fluorophores attached to the elbow region of tRNA molecules on the ribosome. The transition of FRET = 0.74 to 0.45 implies that the distance between tRNA elbows increases by about 10 Å (from 44.3 Å in the crystal structure of Yusupov et al. (2001) to 56.5 Å in our two tRNA docking model (Nagano and Nagano, 1997), as an example, although Blanchard et al. (2004b) insisted the presence of a hybrid state structure). In the seven-step mechanism of Blanchard et al. (2004a), step 0 binds only one tRNA at the P site, step 1 with 0.0 FRET has one aa-tRNA•EF-Tu•GTP ternary

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complex, step 2 with 0.35 FRET has the above complex making contact with the A-site codon, step 3 with 0.5 FRET has the above complex at the A site, step 4 with 0.5 FRET, in which GTP is hydrolyzed, step 5 with 0.5 FRET, in which some of the tRNA at the A site is rejected, step 6 with 0.75 FRET has the aa-tRNA•EF-Tu•GDP complex at the A site, and step 7 with 0.75 FRET, in which peptidyl transfer is completed but EF-Tu•GDP still remains at the A site. In these steps, steps 2 and 3 are considered to be the initial selection, while steps 5 and 6 are thought to be proofreading (Blanchard et al., 2004a). The step 1 of their mechanism could be the same as what we call the putative first interaction of the ternary complex with the cavity region of the small subunit in the present mechanism, as described in section 2, while the steps 3, 4, and 5 could correspond to unfolding of 16S rRNA, formation of the long helix between 16S and 23S rRNAs, and unfolding of the long helix, respectively, in the present mechanism. In order to achieve the high overall selectivity, the initial selection step must be about as precise as proofreading (Gromadski and Rodnina, 2004). During proofreading alone, about 1 amino acid out of 100 near-cognate aa-tRNAs is incorporated into peptide (Pape et al., 1999). On the other hand, early estimations for the efficiency of initial selection suggested the value of not more than 1 out of 10 ~ 100 near-cognate ternary complexes (Bilgin and Ehrenberg, 1994). There are two ways for enhancing efficiency of initial selection as follows: (1) by selective stabilization of cognate, but not near-cognate, codon-anticodon helices on the ribosome, and (2) by modulating the rates of forward reactions depending on the structure of the codon-anticodon helix by means of an induced fit (Pape et al., 1999) or ‘domain closure’ mechanism (Ogle et al., 2002). The structure of the 30S subunit with A-site codon and cognate tRNA ASL showed conformational changes in the 30S subunit, in which A1492, A1493, and G530 interact with the minor groove of the first two codon-anticodon base pairs (Ogle et al., 2001). In order to find the structural differences caused by binding one cognate and two near-cognate anticodons to the above, Ogle et al. (2002) used the sequences of the following three ASLs: (1) cognate ASLPhe GGGGAUUGAAAAUCCCC; (2) near-cognateASLLeu2 CUACCUUGAGGΨGGUAG; (3) near-cognate ASLSer CACGCCUGGAAAGΨGUG. Here, as (4), a hairpin loop of Thermus thermophilus helix 6 (so-called spur region) in a neighbouring 30S molecule having a following sequence was used as a mimic of P-site ASL: …GGCCGCGGGGUUUUACUCCGUGGUC… In the above four sequences, single underlines, double underlines, and broken underlines indicate anticodons, conserved U33s, and base-paired nucleotides, respectively. (It is important to note that the sequence (4) is not like the ASL of a real tRNA, in the sence that the base of U33 in (4) would not stick out because of a strong base pair G32-C38, which seems fatal in our proofreading mechanism.) As mRNAs, either …UUUAAA or …UUCAAA is used. The ‘domain closure’ is observed in the presence of cognate ASLPhe and involves rotations of the head toward the shoulder and the subunit interface and of the shoulder (S4, G530 loop with surrounding regions of 16S rRNA and S12) toward the intersubunit space and the h44/h27/platform region (Ogle et al., 2002). This ‘domain closure’ is enhanced in the additional presence of paromomycin and induces the decoding error. The NMR structural study of paromomycin bound to a fragment of A-site 16S rRNA suggested a conformational stabilization of the decoding site that specifically recognizes the codon-

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anticodon helix (Fourmy et al., 1996). With near-cognate ASLs, the closed 30S domain is not observed except for the cases in the presence of paromomycin. This is a kind of paradox, suggesting that stabilization does not necessarily contribute to enhancing the accuracy in translation. The ‘domain closure’ should still have a possibility of dynamic behavior that is called an induced fit. The structural role of A1492 and A1493 is hydrogen bonding to the minor groove of codon-anticodon helix at the A site, in which A1493 and A1492 interact with the first and second bases, respectively, as typical cases of A-minor motif (Nissen et al., 2001). However, the mode of interaction is rather vague (Ogle et al., 2001). It does not explain why both adenines are highly conserved, because substitution for either adenine by guanine could work about the same. In the case of cognate ASLPhe with paromomycin, the mode of interaction can be seen more clearly (Ogle et al., 2002). Even in the case of nearcognate ASLLeu2 with paromomycin, the N3 atom of A1493 is found to hydrogen-bond to N2 amino group of guanine base in the G-U mismatch at the first codon position as is the case for a Watson-Crick pair of either G-C or C-G. The hydrogen bond cannot be seen very well between the N3 of A1492 and the N2 amino group of guanine at the second codon position even in the presence of paromomycin, although it does not look like a wobble base pair (Ogle et al., 2002). Considering that both first and second codon positions take various base pairs, even though they are all Watson-Crick type, the hydrogen bonding mode of both A1492 and A1493 should be variable. Fixing their position in the presence of paromomycin does not seem to contribute to enhancing the accuracy in translation. The mechanism of translation described in the preceding sections has started from a consideration that, at the beginning of long evolutionary events of life, a process of noncognate aa-tRNA discarding without GTP hydrolysis could have been more important than the process of discriminating cognate one from near-cognate ones by means of GTP hydrolysis. Although it is well known that an aa-tRNA•EF-Tu•GTP ternary complex comes to the L7/L12 stalk shortly before GTP hydrolysis, it does not necessarily mean that the stalk is the first interaction site for the ternary complex, because most of them, such as noncognate ones, are discarded without GTP hydrolysis. Thiostrepton, which inhibits binding of EFG•GTP at the stalk, does not inhibit binding of an aa-tRNA•EF-Tu•GTP ternary complex. Another related basic question is how the next codon can be found without having a frame shift, if the stalk is the first interaction site for the elongation factors to the ribosome. The interaction between a GTΨC-loop of tRNA and the 3’-side of h35 seemed important for that purpose. The present hypothetical mechanism of the long helix formation between small and large ribosomal subunits was introduced in this way. Based on the smFRET method, described above, Blanchard et al. (2004a) proposed a kinetic proofreading mechanism, in which ribosomal recognition of correct codon-anticodon helix drives rotational movement of the incoming complex of aa-tRNA•EF-Tu•GTP toward pep-tRNA during selection on the ribosome, although their experiment completely ignores the significance of E-site tRNA. They found that the formation of the stable 0.5 FRET state occurs after initial selection is completed. The step of the ternary complex weakly bound to the ribosome before GTP hydrolysis could be considered to be the stage in our mechanism, at which a long base-pairing helix between the 5’-side of h35 of 16S rRNA and the SRL region of 23S rRNA is being unfolded, and the final match of the codon-anticodon helices between A and E sites is coming to a climax, as shown by the 3D structures in Figures 5 and 12.

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CONCLUSION The mechanism of translation has been studied for more than 40 years. First approaches were mostly based on chemical analyses such as sequencing of proteins (Giri et al., 1984) and rRNAs (Brosius et al., 1978; 1980), footprinting (Moazed and Noller, 1989), crosslinking (Brimacombe, 1995), and so on. At that time, the ribosome looked like an elephant elegantly moving its nose, while a mass of researchers were analogous to people watching and analyzing its functional movements. Electron microscopy (Stöffler and Wittmann, 1977) was like photography that allowed us to have an idea that the elephant has also large ears and feet. X-ray analysis of the whole ribosome (Yusupov et al., 2001) gave us a first picture of the roentgenograms of the elephant that had thick bones and internal organs. People first thought that the elephant was quite static, but finally realized that it was quite dynamic, when it was alive. This is the present situation regarding the image of the whole ribosome after the appearance of four more X-ray structures (Bashan et al., 2003; Schuwirth et al., 2005; Korostelev et al., 2006; Selmer et al., 2006). When the present author first submitted a paper on the mechanism based on the intersubunit long helix formation nearly ten years ago, it was rejected by saying that the mechanism would be soon denied by a forthcoming result of X-ray analysis. After the appearance of Yusupov et al. (2001), the distance between SRL and h35 larger than 100Å was the main reason for the critical objections. Despite the dynamic character of the X-ray results, however, the existence of the barrier between P- and E-tRNAs bothers crystallographers in explaining the first step of translocation. What the present author insists in this chapter is that such a phenomenon could not be explained based on the frozen results of X-ray structures, but by a chain reaction of conformational changes, which could allow the functional interactions of the regions widely separated by more than 100Å on the X-ray structure. Almost all enigmatic steps of the mechanism of translation could be clarified by this type of approach.

METHODS Programs and Coordinates The programs for manipulating the 3D models in the present work are the same as those used in the modelling of tRNA docking pair (Nagano and Nagano, 1997). The 3D structures of the region of the nucleotides 2646-2674 of 23S rRNA domain were built with reference to the NMR structure (Szewczak et al., 1993). The atomic coordinates of EF-G (Ævarsson et al, 1994) and the ternary complex of Cys-tRNA•EF-Tu•GDPNP (Nissen et al., 1995) are obtained from the Protein Data Bank. GTP model was fitted to EF-G following the corresponding structure of EF-Tu•GDPNP (Berchtold et al., 1993). In order to draw coloured stereo pictures and to edit them as we like, a program called RasMol (Sayle, 1992-1999; Bernstein, 1995-2000) and a program from Molecular Simulations Inc., San Diego, U.S.A., called WebLabViewer Pro 3.0, were used. The latter models were edited by adding labels and numerals by use of a software Adobe Illustrator 10.0J from Adobe Systems Inc., San Jose, U.S.A.

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Sprinzl, M., Horn, C., Brown, M., Ioudovitch, A. & Steinberg, S. (1998). Compilation of tRNA sequences and sequences of tRNA genes. Nucl. Acids Res., 26, 148-153. The database is available at www.uni-bayreuth.de/departments/biochemie/sprinzl/trna/ Sprinzl, M., Wagner, T., Lorenz, S. & Erdmann, V. A. (1976). Regions of tRNA important for binding to the ribosomal A and P sites. Biochemistry, 15, 3031-3039. Stark, H., Rodnina, M. V., Rinke-Appel, J., Brimacombe, R., Wintermeyer, W. & van Heel, M. (1997). Visualization of elongation factor Tu on the Escherichia coli ribosome. Nature, 389, 403-406. Stöffler, G. & Wittmann, H. G. (1977). Primary structure and three-dimensional arrangement of proteins within the Escherichia coli ribosome. In: Molecular mechanism of protein biosynthesis. Academic Press, Inc., New York, San Francisco, London. pp. 117-202. Szewczak, A. A., Moore, P. B., Chan, Y. L. & Wool, I. G. (1993). The conformation of the sarcin/ricin loop from 28S ribosomal RNA. Proc. Natl. Acad. Sci. USA, 90, 9581-9585. Valle, M., Sengupta, J., Swami, N. K., Grassucci, R. A., Burkhardt, N., Nierhaus, K.H., Agrawal, R. K. & Frank, J. (2002). Cryo-EM reveals an active role for aminoacyl-tRNA in the accommodation process. EMBO J., 21, 3557-3567. Vestergaard, B., Van, L. B., Andersen, G. R., Nyborg, J., Buckingham, R. H. & Kjeldgaard, M. (2001). Bacterial polypeptide release factor RF2 is structurally distinct from eukaryotic eRF1. Mol. Cell, 8, 1375-1382. Wilson, K. S. & Noller, H. F. (1998). Mapping the position of translational elongation factor EF-G in the ribosome by direct hydroxyl radical probing. Cell, 92, 131-139. Wimberly, B. T., Guymon, R., McCutcheon, J. P., White, S. W. & Ramakrishnan, V. (1999). A detailed view of a ribosomal active site: The structure of the L11-RNA complex. Cell, 97, 491-502. Yamada, Y. & Ishikura, H. (1973). Nucleotide sequence of tRNASer3 from Escherichia coli. FEBS Lett., 29, 231-234. Yusupov, M. M., Yusupova, G. Zh., Baucom, A., Lieberman, K., Earnest, T. N., Cate, J. H. D. & Noller, H. F. (2001). Crystal structure of the ribosome at 5.5 Å resolution. Science, 292, 883-896. Zavialov, A. V., Buckingham, R. H. & Ehrenberg, M. (2001). A posttermination ribosomal complex is the guanine nucleotide exchange factor for peptide release factor RF3. Cell, 107, 115-124. Zavialov, A. V. & Ehrenberg, M. (2003). Peptidyl-tRNA regulates the GTPase activity of translocation factors. Cell, 114, 113-122. Zavialov, A. V., Haurylink, V. V. & Ehrenberg, M. (2005). Guanine-nucleotide exchange on ribosome-bound elongation factor G initiates the translocation of tRNAs. J. Biol., 4(9), 119.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter IV

TRANS-TRANSLATION BY TMRNA AND A PROTEIN MIMICKING TRNA AND MRNA Hyouta Himeno, Daisuke Kurita, Akira Muto Department of Biochemistry and Molecular Biology, Faculty of Agriculture and Life Science, Hirosaki University, Hirosaki 036-8561, The United Graduate School of Agricultural Sciences, Iwate University, Morioka 020-8551 and RNA Research Center, Hirosaki University, Hirosaki 036-8561, Japan

ABSTRACT Usually, a single polypeptide or even multiple polypeptides is produced from a single mRNA. Trans-translation is an irregular translation system in eubacteria, in which a single polypeptide is synthesized from two separate molecules of coding RNAs, mRNA and tmRNA. It rescues a stalled translation on the ribosome and provides a peptide tag for degradation to the C-terminus of the nascent polypeptide to enable recycling of ribosomes, promote degradation of truncated mRNA and prevent accumulation of abortively synthesized polypeptides in the cell. Trans-translation is involved not only in a quality control system in the cell but also in various kinds of cellular functions. During trans-translation, tmRNA plays a dual function both as a tRNA and as an mRNA. Alanyl-tmRNA somehow enters the vacant A-site of the stalled ribosome like aminoacyltRNA but without a codon-anticodon interaction, and thereafter the coding region of tmRNA is substituted for mRNA. As a consequence, alanine encoded nowhere but aminoacylated to tmRNA serves as the connector between the truncated peptide encoded by mRNA and the C-terminal tag-peptide encoded by tmRNA. Such an acrobatic feat is accomplished by elaborate interplay between the tRNA and mRNA functions of tmRNA with the help of a protein factor SmpB. Our recent study has suggested that both tmRNA and SmpB mimic the structures and functions of tRNA and mRNA during transtranslation, addressing how tmRNA preferentially recognizes the stalled ribosome, and what substitutes for a codon-anticodon interaction.

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INTRODUCTION Recent progress in molecular biology has brought a new concept that a vast number of noncoding RNAs play diverse roles in the eukaryotic and prokaryotic cells (Zamore & Haley, 2005, Wasserman, 2002). In 1980th, however, most of the textbooks of molecular biology referred to only tRNA, mRNA and rRNA. TmRNA was initially found from Escherichia coli at 1979 (Ray & Apirion, 1979). Until the middle of the 1990th, it has been regarded merely as a small stable and presumably noncoding RNA of an unknown function. Later findings of the tRNA-like structure, a tRNA-like function and an mRNA function, have opened a door towards a novel molecular mechanism and a novel cellular system. TmRNA shares two different kinds of properties, a carrier of genetic information and a device for decoding genetic information, which are usually carried in separated RNA molecules. TmRNA facilitates an irregular translation named trans-translation, in which a single polypeptide is produced from two coding RNA molecules (Figure 1). Trans-translation rescues the ribosome stalled at the 3’ end of truncated mRNA lacking a termination codon and provides the incomplete nascent polypeptide from a truncated mRNA with a tag for degradation. This promotes recycling of the stalled ribosomes in the cell. As these marvellous functions were revealed, new questions arose in the light of the recent progress in our understanding about the processes of translation on the ribosome at the atomic level (Ramakrishnan, 2002) and the unexpectedly diverse functions of small noncoding RNAs in the control of gene expression (Zamore & Haley, 2005, Wasserman, 2002). What is the higher order structure of tmRNA? How does tmRNA elaborately coordinate the tRNA and mRNA functions in the limited space of the ribosome to accomplish trans-translation? How does tmRNA find a stalled translation? Are there any other factors involved in trans-translation? What is the fate of the aberrant polypeptide from tuncated mRNA? Does trans-translation serve merely as a surveillance system in the cell? Here, we review the history, the molecular mechanism and the cellular functions of trans-translation including our recent model.

TmRNA About thirty years ago, Ray & Apirion (1979) found a stable RNA in the fraction of sedimentation coefficient 10S from E. coli cell extracts and it was named 10S RNA. Later, 10S RNA has been found as a mixture of two RNA species that have been renamed 10Sa RNA and 10Sb RNA (Jain et al., 1982), the latter being a component of RNase P. After ten years from the finding, the primary structure of 10Sa RNA was determined (Chauhan & Apirion, 1989). As its novel functions have been revealed, its name has gradually been replaced from 10Sa RNA to tmRNA (transfer-messenger RNA), although some groups still call it SsrA from the name of its gene, ssrA (small stable RNA A).

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Figure 1. Schematic representation of trans-translation. Alanine aminoacylated to tmRNA (shown in white with a red background) serves as the connector between the truncated peptide encoded by truncated mRNA (shown in grey) and the C-terminal residues encoded by tmRNA (shown in red).

TmRNA is widely or perhaps almost exclusively distributed among the eubacterial kingdom. Their primary structures are available from two databases of tmRNA, the tmRDB (http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html) (Zwieb et al., 2003; Andersen et al., 2006) and the tmRNA Website (http://www.indiana.edu/~tmrna/) (Williams, 2000). TmRNA is also present in chloroplasts or mitochondria of some lineages of lower eukaryotes. However, tmRNA or its gene has never been found in the eukaryotic cytoplasms or archaebacteria.

STRUCURE OF TMRNA A tRNA-like secondary structure has been found by our and Inokuchi’s groups (Ushida et al., 1994; Komine et al., 1994). It can be formed by the 5’- and 3’-terminal sequences of tmRNA from Bacillus subtilis, Mycoplasma capricolum and E. coli. A 5-base-pair stem with a 7-base loop, a stem of 7 base pairs, a discriminator base and the CCA-3’ sequence are arranged just like the TΨC-arm, the amino acid acceptor stem, a discriminator base and the CCA-3’ sequence in the upper right half of the canonical secondary structure of tRNA (Figure 2). Consensus sequences in tRNA, such as UUCPuAPyU sequence in the TΨC-loop and the CCA-3’ sequence, are present in tmRNA. In addition, two major modified bases in typical tRNA, 5’-methyl cytosine (T or thymine) and pseudouridine (Ψ), have been identified in the TΨC-loop in E. coli tmRNA (Felden et al., 1998) (Figure 2). TmRNA has a noncanonical D-arm apparently lacking a stem structure, which is often found in some animal mitochondrial tRNA (Himeno et al., 1987), while it contains a GG sequence that is a consensus sequence in the D-loop of tRNA (Figure 2). The tertiary interaction between the D-arm and the TΨC-loop has been suggested by a cross-linking study (Zwieb et al., 2001). It has also been suggested that the GG sequence in the D-arm has a functional interaction with

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Figure 2. The secondary structure of E. coli tmRNA. The tag-encoded sequence is highlighted in white with a black background. The region required for recognition by alanyl-tRNA synthetase is designated with a blue background. Several base substitutions affect the efficiency and fidelity of trans-translation in vitro (Lee et al., 2001), designated by closed and open arrowheads in red, respectively.

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the TΨC-loop, like in the canonical tRNA structure (Barends et al., 2002). The finding of the tRNA-like secondary structure in tmRNA has brought the first breakthrough in its function, described below. In contrast to high conservation of both terminal regions comprising a tRNA-like secondary structure, the primary structure of the remaining 90% of total approximately 350 nucleotides are much less conserved, making difficult to predict the entire secondary structure of tmRNA. Sequence comparisons (Williams & Bartel, 1996; Felden et al., 1997) and chemical and enzymatic structural probings (Felden et al., 1996, 1997; Hickerson et al., 1998) have enabled to build a secondary structure model of this molecule (Figure 2). The central two third of this molecule forms a large loop comprised of four pseudoknot structures (PK1 to PK4) and a few stem and loops, being connected to the terminal tRNA-like domain by a long stem with a few bulges or loops. This secondary structure model has been validated by mutational analyses (Nameki et al., 1999a, 1999b) and by later accumulation of the tmRNA sequences. The secondary structure of tmRNA is widely conserved, although with some variation in the pseudoknot-rich region. For example, the fifth pseudoknot is found in tmRNA from some cyanobacteria (Williams, 2002). As an extreme example, a tmRNA molecule from some lineages of alphaproteobacteria, betaproteobacteria, cyanobacteria or mitochondria of lower eukaryotes is comprized of two separated chains, a 5’-coding piece and a 3’-amino acid acceptor piece (Keiler et al., 2000; Williams, 2002; Jacob et al., 2004; Sharkady &Williams, 2004). 2-piece tmRNA shares similar structural features such as the tRNA-like structure with one-piece tmRNA, although possessing fewer pseudoknots (Keiler et al., 2000; Gaudin et al., 2002; Sharkady & Williams, 2004). Indeed, the functional redundancy of pseudoknot structures except PK1 in E. coli tmRNA has been exemplified in vitro (Nameki et al., 2000), although they participate in the proper folding and processing of 1-piece tmRNA (Wower er al., 2004). The tertiary structure of tmRNA has been presumed to be difficult to be determined, since it is large and flexible as compared to tRNA (Felden et al., 1997). Models of PK2 and PK4 structures have been proposed from a comparative study (Zwieb et al., 1999). A model of the tRNA-like structure has been built based on the angle between two helices obtained by transient electric birefringence measurement (Stagg et al., 2001). NMR studies have revealed the structure of PK1 from Aquifex aeolicus (Nonin-Lecomte et al., 2006). A crystal structure of a fragment of the tRNA-like domain in complex with a binding protein, SmpB, from A. aeolicus (Gutmann et al., 2003) or Thermus thermophilus (Bessho et al., 2007) has been shown. According to the latter crystal structure, the long stem with a few bulges or loops leading to PK1 is thought to generate from the tRNA-like domain in a direction similar to that of the long variable arm in class II tRNA (Bessho et al., 2007). The entire 3D structure models of tmRNA from several eubacterial species have been built in consideration of the functional distance between the tRNA-like domain and the coding region (Burks et al., 2005). The entire structure of T. thermophilus tmRNA in complex with the ribosome and a few binding proteins has been visualized by cryo-electron microscopy, although with low resolution (Valle et al., 2003a; Kaur et al., 2006).

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PROCESSING OF TMRNA E. coli genome has a single gene for tmRNA (ssrA) under a putative sigma 70 promoter sequence (Oh et al., 1990; Komine et al., 1994). The 457-nucleotide primary transcript is processed into 363-nucleotide mature tmRNA (Komine et al., 1994). The tRNA-like structure allows removal of 7 nucleotides from the 5’-end of the 457-nucleotide precursor by RNase P that usually functions in the 5’ processing of tRNA (Inokuchi et al., 1994). The 3’ processing involves endoribonucleases, RNase III, RNase E (Srivastava et al., 1990, 1992; Lin-Chao et al., 1999), and exoribonucleases, RNase T, RNase PH and RNase R (Li et al., 1998; Cairrão et al., 2003). Like tRNA, tmRNA terminates with a CCA-3' sequence. The CCA-3' sequence of tmRNA in some eubacteria such as B. subtilis is not encoded on the gene and is added enzymatically (Ushida et al., 1994). The gene for 2-piece tmRNA in Caulobacter crescentus or cyanobacteria is circularly permuted (Keiler et al., 2000; Williams, 2002). The gene for the 3’-amino acid acceptor piece, an intervening segment and the gene for the 5’-amino acid acceptor piece are aligned in the genome in the 5’ to 3’ direction. The permuted precursor might be processed into a mature 2-piece tmRNA with the help of RNase P and exonucleases. A similar strategy has recently been found in the processing of tRNA in Cyanidioschyzon merolae (Soma et al., 2007). The pseudoknot structures are involved in the maturation of tmRNA, although they are apart from the tRNA-like structure in the secondary structure (Wower et al., 2004). It has also been shown that SmpB, a tmRNA binding protein, enhances the maturation of tmRNA (Wower et al., 2004).

FUNCTION AS A TRNA Unlike most other aminoacyl-tRNA synthetases, alanyl-tRNA synthetase does not require the anticodon sequence upon recongnition of tRNA, and instead it recognizes the upper half structure of the L-shaped tRNAAla molecule, especially G-U base pair at the third position of the amino acid acceptor stem (McClain & Foss, 1988; Hou & Schimmel, 1988) and A at the fourth position from the 3' end (discriminator base) (Tamura et al., 1991). Thus a model RNA fragment consisting of only an acceptor stem and a TΨC -arm of tRNAAla can be aminoacylated with alanine (Francklyn & Schimmel, 1989). A G-U base pair and an adenine residue are found at the corresponding positions in tmRNA (Figure 2). As expected, tmRNA from E. coli or B. subtilis is aminoacylated with alanine by alanyl-tRNA synthetase in vitro (Komine et al., 1994; Ushida et al., 1994). The tRNAAla-like features are exclusively conserved among tmRNA from various sources, suggesting the significance of aminoacylation with alanine for the function of tmRNA. TmRNA associates with 70S ribosomes but not with the dissociated ribosomal subunits in vivo (Ushida et al., 1994; Tadaki et al., 1996; Komine et al., 1996) and in vitro (Himeno et al., 1997). A mutant tmRNA having an A-U base pair instead of the G-U base pair at the third position of the amino acid acceptor stem, which fails to accept alanine, does not bind to the

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70S ribosomes (Tadaki et al., 1996; Himeno et al., 1997), indicating that aminoacylation with alanine is responsible for binding of tmRNA to the ribosome. Since the secondary structure of tmRNA fulfills the minimum requirements for the formation of a ternary complex of aminoacyl-tRNA, EF-Tu and GTP, it is conceivable that alanyl-tmRNA enters the A-site of the ribosome as a ternary complex. However, the absence of tmRNA in the polysome fraction has questioned the involvement in the canonical protein synthesis (Tadaki et al., 1996).

Function as an mRNA Tu et al. (1995) have found a strange fraction upon purification of overexpressed mouse interleukin-6 (IL-6) from the extracts of E. coli cells. It contains a mixture of polypeptides in that an AANDENYALAA sequence is connected to the IL-6 sequences that are C-terminally truncated from random positions. The last 10 of this 11-amino acid sequence called tagpeptide is identical to the last 10 amino-acid sequence of a putative peptide encoded in the middle of the tmRNA gene. Since the tag-peptide addition depends on the presence of the tmRNA gene on the genome, the last 10 amino acids are likely to be encoded by the gene for tmRNA, although the first alanine is of an unassigned origin. An identical 11 amino-acid tag sequence appears at the C-terminus of λ cI repressor or cytochrome b-562 that is translated in vivo from mRNA desinged to lack a termination codon (Keiler et al., 1996). The possibility that tmRNA itself acts as an mRNA for the tag-peptide has been raised (Figure 1). Direct evidence for the function as an mRNA for the tag-peptide was obtained from in vitro translation experiments (Muto et al., 1996; Himeno et al., 1997). E. coli tmRNA faciltates an incorporation of tag-specific amino acids into the growing polypeptide in a stoichiometrical fashion, only when poly (U)-directed poly-phenylalanine synthesis occurs. The tag-specific amino acid incorporation is not facilitated by a single-point mutant tmRNA that fails to accept alanine. These results have revealed the dual function of tmRNA both as an mRNA and as a tRNA and that the mRNA function requires the tRNA function in addition to an additional protein synthesis.

Trans-translation Based on the dual function of tmRNA, the novel suquence of tag-peptide and accumulation of truncated proteins with a tag-peptide from truncated mRNA, a transtranslation model has been proposed (Figure 1) (Keiler et al., 1996; Atkins & Gesteland, 1996; Muto et al., 1996, 1998). In this model, when a ribosome is stalled on a truncated 3' terminal of mRNA, alanyl-tmRNA, instead of aminoacyl-tRNA, is recruited to the vacant Asite of the ribosome, followed by a peptidyl transfer from peptidyl-tRNA in the P-site to alanyl-tmRNA in the A-site. Then translocation replaces truncated mRNA by the tagencoding region of tmRNA on the decoding region of the small subunit to allow translation of tmRNA-encoded tag-peptide. As a consequence, a chimeric protein of the truncated peptide and the tag-peptide connected by alanine is released from the ribosome using the inframe stop codon, allowing the ribosome to recycle. During these processes, tmRNA plays a

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dual function both as a tRNA and as an mRNA, and therefore tmRNA can be categorized as a new type of RNA, termed tmRNA. It should be noted that the connector alanine is encoded nowhere but was once aminoacylated to tmRNA. Alanine aminoacylated to tmRNA is actually incorporated into the growing polypeptide in the poly (U)-dependent tag-peptide synthesis system in vitro (Nameki et al., 1999c), strongly supporting the trans-translation model. The model of trans-translation addresses the question as to why tmRNA is not detected in the polysome fraction (Tadaki et al., 1996). All the ribosomes but the last one on a truncated mRNA are released from tmRNA upon translocation, and thereafter the translation of the last 10 amino acid residues of the tagpeptide encoded by tmRNA occurs on a single ribosome.

EVOLUTIONAL IMPLICATION FOR THE UNIQUE RECOGNITION MANNER OF ALANYL-TRNA SYNTHETASE It is generally believed that tmRNA universally adopts alanine as an amino acid charged, because of the exclusive conservation of G-U at the third base-pair position in the acceptor stem and A at the discriminator base position (Williams, 2000; Zwieb et al., 1999). Interestingly, trans-translation still occurs in vitro even when mutations are introduced so that tmRNA is aminoacylated with histidine instead of alanine (Nameki et al., 1999c), indicating that aminoacylation of tmRNA rather than alanylation is required for trans-translation. At the birth of tmRNA, some aminoacyl-tRNA synthetase should have been selected as the enzyme that catalyzes aminoacylation of tmRNA. TmRNA has no apparent anticodon, whereas up to 17 of 20 aminoacyl-tRNA synthetases except for alanyl-, seryl- and leucyltRNA synthetases require the anticodon sequence for recognition of the cognate tRNA. Since seryl- and leucyl-tRNA synthetases may be less appropriate for recognition of tmRNA, since they require the characteristic tertiary structures of their corresponding tRNA (Himeno et al., 1990; Asahara et al., 1993,1994; Soma & Himeno, 1998). Because alanyl-tRNA synthetase is unique in that the recognition area is unusually biased to the upper half of the tRNA molecule (Figure 2) (McClain & Foss, 1988; Hou & Schimmel, 1988; Tamura et al., 1991), it should have been the best one to recognize tmRNA. Eubacterial alanyl-tRNA synthetase has undergone co-evolution with two different kinds of molecules, tRNAAla and tmRNA. This has obliged the recognition area of alanyl-tRNA synthetase to be concentrated in their common structure including the acceptor stem and the TΨC-arm, which are also involved in recognitions by RNase P and EF-Tu. This might be the reason why alanyl-tRNA synthetase adopts the unique recognition manner unusually biased to the acceptor stem of tRNA.

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Figure 3. Trans-translation mediated by tmRNA and its binding proteins. By virture of transtranslation, the ribosome is recycled and the truncated mRNA and the resulting tagged proteins are degraded. The requirement of S1 is still controversial.

TmRNA Binding Factors Several protein factors, such as EF-Tu, S1 and SmpB, interact with tmRNA in vivo and in vitro (Figure 3). EF-Tu•GTP binds to the tRNA-like structure of alanyl-tmRNA (Rudinger-Thirion et al., 1999; Barends et al., 2000). It is thus conceivable that an alanyl-tmRNA, just like an aminoacyl-tRNA, enters the A-site as a ternary complex with EF-Tu and GTP. However, some reports have shown that EF-Tu is not essential for trans-translation in vitro (Hallier et al., 2004; Shimizu & Ueda, 2006). Additional EF-Tu binding sites outside the tRNA-domain have also been suggested (Zvereva et al., 2001; Stepanov & Nyborg, 2003). S1 protein is a component of the small subunit of the ribosome, although some population of S1 seems to be apart from ribosomes in the cell (Subramanian, 1983). S1 is thought to help the association of mRNA having a weak SD-sequence with the ribosome (Tzareva et al., 1994; Tedin et al., 1997). E. coli S1 binds tmRNA with high affinity (Wower et al., 2000; Hanawa-Suetsugu et al., 2001). It has also been suggested that more than one S1 can bind to one molecule of tmRNA in vitro (Bordeau & Felden, 2002). E. coli S1 has six repeating homologous oligonucleotide/oligosaccharide binding folds (OB-folds), of which the second OB-fold is essential for binding to tmRNA (Okada et al., 2004). S1 cross-links to PK2, PK3 and the upstream region of the tag-encoding sequence of tmRNA (Wower et al., 2000) to induce a conformational change of tmRNA (Bordeau & Felden, 2002; Valle et al., 2003a; Gillet et al., 2006). Thus, it is presumed that S1 guides tmRNA to the ribosome,

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anchors the upstream region of the resume codon on the ribosome and destabilizes the surrounding structured region to precisely set the resume codon at the A site. However, the role of S1 in trans-translation is still controversial. S1 is absent in the low-G+C group of Gram-positive bacteria, and indeed tmRNA from B. subtilis that lacks S1 can facilitate transtranslation in E. coli that has S1 (Ito et al., 2002). Note that B. subtilis has an S1 homologue, although it has no interaction with E. coli tmRNA probably due to the lack of the second OBfold (Okada et al., 2004). Overproduction of the N-terminal fragment of E. coli S1 inhibits general translation but not trans-translation, also suggesting the lack of significance for trans-translation (McGinness & Sauer, 2004). It has been shown that S1 is not essential for trans-translation in vitro, at least for the early stage (Takada et al., 2007; Qi et al., 2007; Saguy et al., 2007). This is consistent with a cryo-electron microscopic map of the ribosomal small subunit in complex with S1, in which S1 binds to the mRNA exit tunnel formed by the junction of the head, platform and main body of the small subunit of the ribosome (Sengupta et al., 2001), rather than to the shoulder side where tmRNA initially binds for transtranslation (Valle et al., 2003a; Kaur et al., 2006). A report has shown that S1 is involved in a later stage of trans-translation (Saguy et al., 2007), while another report has shown that it is not involved throughout the trans-translation processes (Qi et al., 2007). SmpB (small protein B) has been identified in E. coli as a tmRNA binding protein (Karzai et al., 1999). SmpB is widely conserved among eubacteria and chloroplasts, but not in mitochondria (Andersen et al., 2006). The gene for SmpB from many but not all eubacteria is located immediately upstream of the tmRNA gene on the genome, although the E. coli SmpB gene has an independent promoter sequence. NMR studies have revealed that SmpB is comprised of an antiparallel ß barrel core with three alpha helices and C-terminal basic residues that are disordered in solution (Dong et al., 2002; Someya et al., 2003). The primary binding site of SmpB of biological significance is in the TΨC-arm and the D-loop equivalents in the tRNA-like domain (Hanawa-Suetsugu et al., 2002; Gutmann et al., 2003; Nameki et al., 2005; Bessho et al., 2007). It has also been reported that total three molecules of SmpB can bind around the tRNA-like domain (Wower et al., 2002). Another report has also shown three SmpB binding sites in tmRNA, one of which is located in the lower half of tmRNA including the coding region and its surrounding pseudoknots (Metzinger et al., 2005). As described later, SmpB has crucial roles in trans-translation both inside and outside the ribosome. The level of SmpB in the cell changes in concert with that of tmRNA, probably because the complex formation between them protects not only tmRNA from nucleases but also SmpB from proteases (Hallier et al., 2004; Hong et al., 2005; Sundermeier & Karzai, 2007). Several proteins, phosphoribosyl pyrophosphate synthetase, RNase R and YfbG as well as S1 were copurified with tmRNA and SmpB from the E. coli cells in that both tmRNA and SmpB were overexpressed (Karzai & Sauer, 2001). A genetic interaction between phosphoribosyl pyrophosphate synthetase and tmRNA has been suggested by an observation that the slow growth of a temperature-sensitive mutant of phosphoribosyl pyrophosphate synthetase is suppressed by tmRNA (Ando et al., 1996). RNase R, a 3’ to 5’ exoribonuclease, is involved in tmRNA-mediated degradation of non-stop mRNA (Oussenko et al., 2005; Richards et al., 2006; Mehta et al., 2006), maturation of tmRNA in E. coli (Cairrão et al., 2003) and in cell cycle-regulated degradation of tmRNA in Caulobacter crescentus (Hong et

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al., 2005). YfbG is a protein of an unidentified function with sequence similarities to methionine tRNA formyl transferase and to sugar dehydratases and epimerases. A recent proteomic study has identified several tmRNA-binding proteins from Streptomyces aureofaciens, which includes DNA dependent RNA polymerase, polyribonucleotide nucleotidyltransferase (PNPase), SmpB, EF-Tu and a few ribosomal proteins (Mikulík et al., 2008). E. coli tmRNA has affinity to tRNAAla (Gillet & Felden, 2001a). Since the first codon for the tag-peptide on tmRNA is GCA designating alanine, the possibility of the involvement of this interaction in the trans-translation mechanism has been raised (Gillet & Felden, 2001b).

Cell-free trans-translation Systems As described above, a cell-free trans-translation system coupled with poly (U)-dependent polyphenylalanine syntheisis has initially been established using E. coli crude cell extracts (Himeno et al., 1997). This has contributed not only to providing the trans-translation model with evidence (Himeno et al., 1997; Nameki et al., 1999a) but also to identifying the nucleotides on tmRNA required for efficient and precise trans-translation (Figure 2) (Nameki et al., 1999a; Lee et al., 2001). Later, several trans-translation systems using purified factors from E. coli (Shimizu & Ueda, 2002; Ivanova et al., 2004; Asano et al., 2005; Konno et al., 2007) or from T. thermophilus (Takada et al., 2007) have been developed. These cell-free trans-translation systems using purified factors have revealed the minimum requirement for the first few steps of trans-translation including the binding of tmRNA to the ribosome, peptidyl-transfer from peptidyl-tRNA to alanyl-tRNA and decoding of the first codon on tmRNA for the tag-peptide. In addition to an mRNA lacking a termination codon and general translation factors, EF-Tu, EF-G, ribosome and aminoacyltRNAs, only two trans-translation-specific factors, alanyl-tmRNA and SmpB, are sufficient (Figure 3). The efficiency of trans-translation can be evaluated either by monitoring the incorporation of radio active amino acid attached to tmRNA or tRNA into the growing peptide or by monitoring the chimera polypeptide using antibody raised against the tagpeptide. For example, two steps of trans-translation, binding of Ala-tmRNA to the ribosome to undergo a peptide transfer reaction (1st step) and setting of the resume alanine codon to the A-site to be translated (2nd step), can independently be evaluated by monitoring the synthesis of peptidyl-Ala-tmRNA from peptidyl-tRNA and Ala-tmRNA and the synthesis of peptidylAla-Ala-tRNAAla from peptidyl-Ala-tmRNA and Ala-tRNAAla, respectively (Takada et al., 2007; Konno et al., 2007). Using a cell-free T. thermophilus trans-translation system containing S1-free ribosomes, S1 has been shown to be required for neither of these two steps (Takada et al., 2007). Essentially the same conclusion has been obtained using the cell-free E. coli trans-translation systems containing S1-free ribosomes (Qi et al., 2007; Saguy et al., 2007). These in vitro trans-translation systems have greatly contributed to clarifying the molecular mechanism of trans-translation, described below.

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MULTIPLE FUNCTIONS OF SMPB OUSIDE THE RIBOSOME SmpB has been suggested to play multiple roles outside the ribosome by binding to the tRNA domain of tmRNA. SmpB enhances the maturation of tmRNA (Wower et al., 2004), enhances the aminoacylation of tmRNA (Barends et al., 2001; Hanawa-Suetsugu et al., 2002; Shimizu & Ueda, 2002), protects tmRNA from degradation in the cell (Hanawa-Suetsugu et al., 2002; Hong et al., 2005) and recruits tmRNA in complex with EF-Tu and GTP to the stalled ribosome (Karzai et al., 1999; Hanawa-Suetsugu et al., 2002). Thus a single-point mutation in the tRNA domain of tmRNA, which seriously affects the interaction with SmpB, affects the latter three functions of SmpB (Hanawa-Suetsugu et al., 2001, 2002). Likewise, a single-point mutation in SmpB, which affects the interaction with tmRNA, also affects the recruitment of tmRNA to the stalled ribosome (Dulebohn et al., 2006). SmpB is essential for trans-translation in vitro and in vivo but not for canonical translation (Karzai et al., 1999; Hanawa-Suetsugu et al., 2002). Although SmpB has diverse roles in trans-translation outside the ribosome, its roles inside the ribosome are more crucial.

The Role of SmpB upon Entrance of tmRNA to the Ribosome Since Ala-tmRNA forms a complex with SmpB, EF-Tu and GTP in vitro (Barends et al., 2001; Hanawa-Suetsugu et al., 2001), this quarternary complex is likely to enter the empty Asite of the stalled ribosome for trans-translation. It has been demonstrated in vitro that E. coli SmpB can bind to the ribosome in the absence of tmRNA and that a stalled ribosome to that SmpB is pre-bound can trigger trans-translation in vitro, leading to the proposal of an alternative pathway in that SmpB pre-binds the ribosome to recruit a ternary complex of AlatmRNA, EF-Tu and GTP (Hallier et al., 2004). However, the alternative pathway does not seem to be consistent with another observation that SmpB is fewer than the ribosomes in the cell (Moore & Sauer, 2006). SmpB would not be enough for all the ribosomes, consequently for the stalled ribosomes of emergency, in the cell. A recent report has shown that SmpB binds the stalled ribosome in the presence of tmRNA more tightly than it does in the absence of tmRNA and that SmpB is enriched in the stalled ribosome only in the presence of tmRNA, making the alternative pathway unlikely to occur in the cell (Sundermeier & Karzai, 2007). Total two SmpB molecules can bind to a 70S ribosome, one to the small subunit and the other to the large subunit (Ivanova et al., 2005; Hallier et al., 2006). SmpB footprints nucleotides in the vicinity of the P-site facing the E-site in the small subunit and below the L7/L12 stalk in the large subunit (Ivanova et al., 2005). This is in agreement with a cryoelectron microscopic map of the putative pre-accommodated state complex of T. thermophilus ribosome•Ala-tmRNA•SmpB•EF-Tu•GDP in the presence of kirromycin that prevents EF-Tu from leaving the ribosome after hydrolysis of GTP, in which two molecules of SmpB bind both of the 70S ribosome and the tRNA-like domain of tmRNA (Kaur et al., 2006). One SmpB binding to the TΨC-arm equivalent of tmRNA contacts with the A-site on the small subunit and the other binding to the D-loop equivalent of tmRNA contacts with the vicinity of the GTP associated center on the large subunit. The latter SmpB is not visible in a complex of ribosome•Ala-tmRNA•SmpB representing the accommodated state of tmRNA.

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Thus the following model has been proposed: two molecules of SmpB are required upon binding of Ala-tmRNA to the ribosome and one of them is released from the ribosome concomitant with the release of EF-Tu after hydrolysis of GTP, so that the 3’-terminal of tmRNA is oriented toward the peptidyl-transferase center. This is also supported by a lead (II) probing of tmRNA in a putative pre-accommodated state (Ivanova et al., 2007). However, the 1:1 stoichiometry of tmRNA to SmpB in the cell (Sundermeier & Karzai, 2007) as well as only one molecule of SmpB binding to the tRNA-like domain with high affinity (Gutmann et al., 2003; Nameki et al., 2005; Bessho et al., 2007) does not appear to be consistent with the involvement of the sencond SmpB in trans-translation. Further studies are required to assess the validity of the above hypothesis.

STRUCTURAL AND FUNCTIONAL MIMICRY OF THE LOWER HALF OF TRNA In a crystal structure of a fragment of the tRNA-like domain (TLD) in complex with SmpB, SmpB binds the TΨC-arm and D-loop equivalents inside the opened L-form structure of TLD (Figure 4A,B) (Gutmann et al., 2003; Bessho et al., 2007). If TLD is fixed on the amino acid acceptor stem and the TΨC-arm, SmpB can be superimposed on the anticodon stem and loop of tRNA, indicating that SmpB structurally mimics the anticodon arm. This raises the possibility that SmpB acts as the functional mimicry of the anticodon arm during the trans-translation processes (Haebel et al., 2004). The functional mimicry is suggested by some studies showing the occupation of SmpB in the tRNA binding sites. In a cryo-electron microscopic map, T. thermophilus SmpB occupies the A-site in the pre-accommodated or accommodated state (Kaur et al., 2006). A study of site-directed hydroxyl radical probing using Fe(II)-BABE shows that two molecules of E. coli SmpB occupy the A-site and the Psite and that each SmpB can be superimposed on the lower half of tRNA behaving in translation (Kurita et al., 2007).

The C-terminal Tail of SmpB According to NMR studies, the C-terminal 1/5 of SmpB (comprised of about 30 amino acid residues in E. coli) is disordered in solution (Dong et al., 2002; Someya et al., 2003). Although the functional significance of the C-terminal tail has been exemplified in vivo and in vitro by its truncation or mutation (Sundermeier et al., 2005; Jacob et al., 2005; Konno et al., 2007; Kurita et al., 2007), cryo-electron microscopic studies fail to identify its location in the ribosome due to the lack of resolution (Kaur et al., 2006; Gillet et al., 2006). Instead, a site-directed hydroxyl radical probing study has succeeded in identifying the locations of two molecules of SmpB including its C-terminal tail in the ribosome from E. coli (Kurita et al., 2007). They can be superimposed on the lower halves of tRNA molecules behaving in translation at the A-site and the P-site. The C-terminal residues of A-site SmpB are aligned along the mRNA path towards the downstream tunnel, while those of P-site SmpB are located almost exclusively around the region of the codon-anticodon interaction in the P-site.

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Figure 4. Proteins structurally mimicking tRNA. (A) Saccharomyces cerevisiae tRNAPhe (PDB: 1EHZ), (B) T. thermophilus SmpB•TLD (PDB: 2CZJ), (C) Thermus aquaticus tRNAPhe•EF-Tu•GTP (PDB: 2EFG), (D) T. thermophilus EF-G•GDP (PDB: 2EFG), (E) Thermotoga maritima RRF (PDB: 1DD5) and (F) T. thermophilus EF-P (PDB: 1UEB) are shown. RNA and protein are designated in blue.

Figure 5. A model of the early stage of trans-translation based on a directed hydroxyl radical probing study. Upon or before entrance of tmRNA to the stalled ribosome, the C-terminal tail of SmpB may recognize the vacant A-site free of mRNA to lie along the mRNA path towards the downstream tunnel. After peptidyl-transfer to tmRNA, translocation of peptidyl-tmRNA/SmpB from the A-site to the P-site, possibly with the help of EF-G, occurs to drive out mRNA from the ribosome. During this event, the extended C-terminal tail somehow folds to substitute for the codon-anticodon interaction in the P-site. Then the resume codon of tmRNA is accommodated in the decoding region. SmpB and the tagencoding region are shown by red and blue, respectively.

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The probing signals appear at interval of 3 residues of the latter half of the C-terminal tail of A-site SmpB, suggesting the alpha helix structure, which has been predicted from the periodical occurrence of positively charged residues (Jacob et al., 2005).

A NEW MODEL OF TRANS-TRANSLATION SmpB molecules bound to the A-site and P-site shown by site-directed hydroxyl radical probing appears to reflect the pre- and post-translocation steps of trans-translation, respectively. Consequently, we have proposed the following model (Figure 5) (Kurita et al., 2007). The C-terminal tail of SmpB mimics mRNA and/or the codon-anticodon interaction and the main body of SmpB mimics the lower half of tRNA both before translocation in the A-site and after translocation in the P-site, while the upper half of tRNA is mimicked by TLD. Upon entrance of tmRNA to the stalled ribosome, the C-terminal tail of SmpB may recognize the vacant A-site free of mRNA to trigger trans-translation. After peptidyl-transfer to Ala-tmRNA, translocation of peptidyl-Ala-tmRNA·SmpB from the A-site to the P-site may occur. During this event, the extended C-terminal tail folds around the region of the codonanticodon interaction in the P-site, which drives out mRNA from the P-site, and consequently from the ribosome. Just after the movement of SmpB to the P-site, the A-site becomes free so that the resume codon of tmRNA can be accommodated. In this model, the truncated mRNA is pushed from the P-site to the E-site by the C-terminal tail of SmpB rather than by tmRNA, leading to the spontaneous dissociation from the E-site. This model can provide several insights into the yet-unidentified mechanism of transtranslation; how the stalled ribosome free of tRNA and mRNA is preferentially recognized, and what substitutes for a codon-anticodon interaction during trans-translation. It is quite reasonable that tmRNA preferentially recognizes the stalled ribosome free of tRNA and mRNA in the A-site. TLD and SmpB mimic the upper and lower halves of a tRNA molecule, respectively. TLD together with SmpB mimics an entire tRNA molecule. The C-terminal tail of SmpB mimics mRNA and/or the codon-anticodon interaction both before and after translocation, during which it undergoes a drastic conformational change. Consequently, SmpB•TLD behaves as mRNA+tRNA so that SmpB•tmRNA might decode the first alanine encoded by the C-terminal tail of SmpB. It has been shown that trans-translation can occur in the middle of a synthetic mRNA in vitro (Ivanova et al., 2004; Asano et al., 2005). The efficiency of trans-translation is inversely correlated with the length of the 3’-extension from the decoding region. This might be a result of competition in the mRNA path between the 3’-extension of mRNA and the Cterminal of A-site SmpB. Messenger RNA of a short 3’-extension occupies the mRNA path in the downstream of the decoding center with lower affinity than that of a long 3’-extension, and thereby tmRNA•SmpB prefers the stalled ribosome with a shorter 3’-extension.

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A NEW TYPE OF MOLECULAR MIMICRY The concept of “molecular mimicry” emerged, when the structure of EF-Tu in complex with Phe-tRNAPhe was found to be very much similar to that of EF-G (Figure 4C,D) (Nissen et al., 1995). The structural mimicry of the tRNA portion by a part of EF-G might reflect the common structure required for the entrance to the A-site. A ternary complex of aa-tRNA•EFTu•GTP initially binds the vacant A-site in the A/T hybrid state, and subsequent GTP hydrolysis at the GTPase-associated center in the large subunit promotes the dissociation of EF-Tu•GDP to allow aa-tRNA to be accommodated in the A/A state. EF-G•GTP binds to the A-site occupied by a peptidyl-tRNA to move it from the A/P state to the P/P state, and subsequent GTP hydrolysis at the same GTPase-associated center promotes the dissociation of EF-G•GDP from the ribosome. The concept of “molecular mimicry” has been extended to other translation factors. Since the structure of ribosome recycling factor (RRF) is very much similar to the L-shape of tRNA (Figure 4E) (Selmer et al., 1999), it has been predicted to enter the vacant A-site of the posttermination complex by mimicking tRNA to move deacylated tRNA from the P-site to the Esite. However, the structure of RRF in complex with the ribosome, which has been revealed by hydroxyl radical probing, cryo-electron microscopic and X-ray crystallographic studies (Lancaster et al., 2002; Agrawal et al., 2004; Wilson et al., 2005), does not support the functional aspect of “molecular mimicry”. In this complex structure, RRF binds the ribosome in an orientation dissimilar from that of tRNA relative to the ribosome: the longer arm of RRF is oriented to the P-site when the shorter arm is around the decoding region. EF-G moves RRF from the initial binding site to the P-site to dissociate the small subunit from the post-termination complex, although the mode of interaction of RRF with the P-site is different from that of tRNA in the P/P or P/E states (Barat et al., 2007). Release factor, RF1 or RF2, has been predicted to enter the vacant A-site by mimicking aminoacyl-tRNA (Nakamura et al., 1996), whereas the crystal structures of release factors are far from similar to the L-shape of tRNA (Vestergaard et al., 2001). Cryo-electron microscopic studies have suggested that RF1 or RF2 undergoes an extensive conformational change upon entrance to the ribosome, allowing the distance between two functional domains of a release factor, the GGQ domain that functions as the catalytic site for hydrolysis of peptide-tRNA in the P-site and the SPF domain that acts as an anticodon for the termination codon, quite similar to that between two functional domains of tRNA, the CCA-3’ end and the anticodon (Rawat et al., 2003; Vestergaard et al., 2005). This could be categorized into a kind of the functional mimicry rather than the typical structural mimicry. As far as we know, EF-P is the protein of that the structure is the most similar to the L-shape structure of tRNA (Figure 4F) (HanawaSuetsugu et al., 2004), although its function remains equivocal (Ganoza et al., 2002). TmRNA itself functionally and structurally mimics both tRNA and mRNA. These two different kinds of molecular mimicries are in collaboration with each other for transtranslation. In this case, a functional RNA (tRNA or mRNA) is mimicked by an RNA molecule rather than by a protein. The IRES（internal ribosomal entry site）5’-upstream of the coding sequence of Dicistroviridae virus RNA has a base pair with the immediately preceding the initiation codon at the P-site of the ribosome (Costantino et al., 2008). This

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structure apparently mimics a set of tRNA and mRNA with the codon-anticodon interaction for the 5’-cap-independent initiation of translation. This RNA is similar to tmRNA in that an RNA molecule acts both as tRNA and mRNA and that two functions are in collaboration with each other. The above trans-translation model provides a new concept of molecular mimicry. A protein molecule mimics both tRNA and mRNA. A wide variety of functional meanings of the tRNA and mRNA mimicry by SmpB•TLD are considered: (1) a function as the structural unit for the entrance to the A-site of the ribosome, (2) a function as the structural unit from the A-site to the P-site during translocation, (3) a function as the mRNA for the first alanine residue of the tag-peptide, (4) a function to find the target ribosome lacking mRNA downstream of the decoding region, (5) a function as the codon-anticodon interaction and etc. It has been reported that SmpB with a TLD fragment facilitates polyalanine synthesis in vitro without temperate mRNA (Shimizu & Ueda, 2006), functionally supporting the molecular mimicry of a set of tRNA and mRNA by SmpB•TLD. Unlike other proteins mimicking tRNA listed above, SmpB mimics not only the shape of tRNA but also the tRNA-like movement from the A-site to the P-site and presumably to the E-site in the ribosome.

TRANS-TRANSLATION PROCESSES IN THE RIBOSOME The functional mimicry by SmpB•TLD assumes the same behavior of SmpB•TLD as that of canonical tRNA+mRNA in the ribosome through several hybrid states, A/T, A/A, A/P, P/P and P/E. Although it is still controversial as already stated, the pre-accommodated state of SmpB•TLD in trans-translation could be in a somewhat different situation from the canonical A/T hybrid state; the second SmpB is required (Hallier et al., 2006; Kaur et al., 2006) and EF-Tu is not essential (Hallier et al., 2004; Shimizu & Ueda, 2006). In the canonical translation, EF-Tu contributes to proofreading to eliminate incorrect tRNA by recognizing a near-cognate codon-anticodon interaction (Valle et al., 2003b). This process might not be involved in the initial step of trans-translation in that no codon-anticodon interaction is assumed. A cryo-electron microscopic map has shown the location of the complex of tmRNA with the main body of SmpB in the A/A state (Kaur et al., 2006), and a directed hydroxy radical probing has revealed the positions of SmpB probably in the A/A and P/P states (Kurita et al., 2007). How the movement of the tRNA-like domain of tmRNA from the A/A state to the A/P state modulates the conformation and positioning of SmpB remains unknown. The existence of stable SmpB binding sites in the A-site and the P-site suggests the requirement of translocation, like in the canonical translation. It might possibly involve EFG•GTP, although the thermodynamic stability of the A/P state is yet unknown. Perhaps concomitantly with translocation, mRNA should be released from the ribosome. In fact, the release of mRNA as well as of deacylated tRNA is stimulated by EF-G•GTP (Ivanova et al., 2005). The next translocation is thought to move SmpB•TLD to the E-site, followed by the release from the ribosome. These ribosomal processes should involve extensive changes in the conformation of tmRNA (Wower et al., 2005) as well as in the modes of interactions of tmRNA with SmpB and the ribosome (Shpanchenko et al., 2005; Ivanova et al., 2007). According to a chemical probing study, SmpB remains bound to tmRNA at least in the initial

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few steps of trans-translation (Ivanova et al., 2007), although the SmpB binding site has not yet been found around the E-site. Another study has suggested the 1:1 stoichiometry of tmRNA to SmpB from the initiation to the termination of translation of the tag-peptide (Bugaeva et al., 2008).

Determination of the Resume Codon The coding region for the tag-peptide starts from the position about ten nucleotides downstream of PK1. In E. coli, it starts with G at position 90, 12 nucleotides downstream of PK1. The absence of an SD-like squence in the upstream region as well as of an apparent codon-anticodon interaction before the first translocation event of trans-translation makes the mechanism by which tmRNA resumes translation from the first codon mysterious. It should require an elaborate coordination between the two functional domains apparently distant from each other on the secondary structure (Hanawa-Suetsugu et al., 2001). It seems reasonable to assume that some structural unit on tmRNA fits elsewhere on the ribosome to set the first codon on the decoding center after the first translocation event. Indeed, PK1 is important for efficiency of trans-translation (Nameki et al., 1999a), whereas changing the span between PK1 and the coding region does not affect the start point of tag-translation, indicating the lack of contribution of PK1 to the determination of the initiation point of the tag-encoding sequence (Lee et al., 2001). A genetic selection of molecules active in trans-translation from a pool of E. coli tmRNAs having randomized sequences around the tag-initiation point has revealed strong base preference in the single-stranded region between PK1 and the tag-encoding region, especially at positions -4 and +1 (position 90) (Williams et al., 1999). The importance of this region for trans-translation has also been shown by an in vitro study (Lee et al., 2001). Some point mutations in the upstream sequence encompassing –6 to -1 decrease the efficiency of tag-translation, while some of them shift the tag-initiation point by –1 or +1 to a considerable extent (Figure 2) (Lee et al., 2001; Konno et al., 2007), indicating that the upstream sequence contains not only the enhancer of trans-translation but also the determinant for the taginitiation point. Thus the importance of an interaction of the upstream sequence with the ribosome either directly or via a trans-acting factor in determination of the tag-initiation point should be focused. The involvements of RF-1 and S1 as the trans-acting factor have been proposed based on the phylogenetically high conservation of –4 to –2 as UAA or UAG (Williams et al., 1999) and the cross-linking of uridine residue at position –5 to S1 (Wower et al., 2000), respectively. However, neither RF-1 nor S1 is essential for trans-translation in vitro (Takada et al., 2007; Qi et al., 2007; Saguy et al., 2007). A potential interaction between the upstream sequence and the putative anti-downstream box sequence on the decoding helix (44th helix) of the small subunit of the ribosome has been proposed based on the sequence complementarity (Muto et al., 1998), whereas it is not supported by a mutational study of the small subunit (O’Connor et al., 2000). Another proposal that the recognition of the triplet immediately preceding the resume codon by the decoding center is important for the entrance of tmRNA to the stalled ribosome (Lim & Garber, 2005) is not consistent with recent

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findings showing the occupation of A-site SmpB in the decoding center (Kaur et al., 2006; Kurita et al., 2007). Evidence for the interaction between the upstream region and SmpB has been obtained from a study of chemical modification (Konno et al., 2007). E. coli SmpB protects U at position –5 (85) from chemical modification. The main body of SmpB rather than the Cterminal tail is involved in this interaction. The protection at -5 was suppressed by a point mutation in the tRNA-like domain critical to SmpB binding, suggesting that SmpB serves to bridge two separate domains of tmRNA to determine the initial codon for tag-translation. Mutations that induce –1 and +1 shifts of the start point of tag-translation also shift the site of protection at -5 from chemical modification by –1 and +1, respectively (Konno et al., 2007), indicating the significance of the fixed span between the site of interaction on tmRNA with SmpB and the resume point of translation: translation of the tag-peptide starts from the position 5-nucleotides downstream of the site of interaction with SmpB (Figure 6). Thus the interaction between tmRNA and P-site SmpB as well as between the ribosome and P-site SmpB rather than that between tmRNA and the ribosome might be responsible for the determination of the resume codon on tmRNA. The interaction between the position at –5 from the intiation point of tag-translation and P-site SmpB would possibly be a substitute for the codon-anticodon interaction between intiator methionine tRNA and the initiation codon in the P-site. The initiation shift of tag-translation can also be induced by the addition of 4,5- or 4,6disubstituted class of aminoglycosides (Takahashi et al., 2003; Konno et al., 2004) that usually cause miscoding of translation by binding to the decoding center to induce a conformational change in its surroundings (Carter et al., 2000). This suggests the importance of the interaction of the decoding center with any portion of SmpB or tmRNA for precise tagtranslation.

Figure 6. The mechanism of the determination of the resume point of translation. The translation of the tag-peptide starts from the position 5-nucleotides downstream of the site of interaction with SmpB. Mutations that induce –1 and +1 shifts of the start point of tag-translation also shift the site of by –1 and +1, respectively. The tag-encoding sequence is designated in blue. The resuming point of translation is shown by red arrowhead. The interaction of SmpB and tmRNA is highlighted by red square.

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Degradation of Truncated mRNA Several kinds of endoribonucleases and exoribonucleases participate in the mRNA decay in the eubacterial cell (Condon et al., 2007). The ribosome translating on a truncated mRNA produced by an endonucleolytic cleavage would stall at and thus mask its 3’-end. It has been shown that trans-translation promotes decay of truncated mRNA in E. coli cell (Yamamoto et al., 2003; Sunohara et al., 2004a,b). Trans-translation would remove the stalled ribosome from truncated mRNA to allow the access of 3’ to 5’ exonucleases to its 3’-end. This had shed light on the significance of trans-translation as the quality control system of mRNA. It is a crucial role of trans-translation to prevent accumulation of aberrant mRNAs in the cell. Mutation introduced to the stem-loop structure of E. coli tmRNA including the last 1/3 of the tag-encoding sequence with the termination codon affects tmRNA-mediated decay of truncated mRNA without affecting the trans-translation activity (Mehta et al., 2006). This indicates that trans-translation is not enough for tmRNA-mediated decay of truncated mRNA, even though it unveils the 3’-end of truncated mRNA. Some kind of exoribonuclease associated with this stem-loop structure of tmRNA might somehow access the 3’-end of truncated mRNA on the ribosome before the dissociation of mRNA from the ribosome. RNase R, a 3’ to 5’ exoribonuclease, has been shown to be involved in tmRNA-mediated decay of truncated mRNA in B. subtilis and E. coli (Oussenko et al., 2005; Richards et al., 2006). Indeed, RNase R has been copurified with a complex of tmRNA and SmpB from E. coli cell (Karzai & Sauer, 2001).

Targets of Trans-translation Trans-translation occurs on stalled ribosomes at the 3’-end of mRNA, when mRNA has no stop codon (Keiler et al., 1996) or when the normal termination codon is read through by a nonsense suppressor tRNA (Ueda et al., 2002) or a miscoding drug (Abo et al., 2002). This system also operates upon translational pausings generated by rare codons (Roche & Sauer, 1999), inefficient termination codons (Roche & Sauer, 2001; Hayes & Sauer, 2002; Sunohara et al., 2002), programmed stalling sequences (Nakatogawa & Ito, 2002) and limited tRNA or release factors (Ivanova et al., 2004; Asano et al., 2005; Li et al., 2007). Efficiency of transtranslation is enhanced, when a proline codon or a minor arginine codon is present just preceding the termination codon (Hayes et al., 2002a,b). Eubacterial mRNAs rapidly turnover in the cells. Since mRNA degradation occurs by endonucleolytic cleavage followed by exonucleolytic degradation, most mRNAs might once be turned into a truncated mRNA lacking a stop codon, which can be a target of transtranslation. On the other hand, analyses of trans-translation products using a tmRNA variant with an undegradable tag-peptide sequence, terminating with a DD sequence instead of the AA sequence (tmRNA-DD), revealed that trans-translation preferentially occurs at specific sites of specific mRNAs. Six E. coli mRNAs (LacI, RbsK, GalE, YbeL, PhoP and RpsG) (Roche & Sauer, 2001; Collier et al, 2002) and eight B.subtilis mRNAs (TreP, PerR, EF-Tu, FolA, GsiG, YqaP, YtoQ and YloN) (Fujihara et al., 2002) have so far been identified as tmRNA substrates. These are no common substrates between the two species. Another recent

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proteomic study has identified at least 73 trans-translation products in C. crescentus (Hong et al., 2007). Only EF-Tu was common in two of three species. Thus most target proteins seem to be different in different species. The target proteins within a cell are also variable depending on the culture conditions (Fujihara et al., 2002). In C. crescentus, proteins involved in DNA replication, recombination and repair are overpresented among the target proteins identified.

Does Trans-translation Occur when Translation Stalled in the Middle of mRNA? Classically, tmRNA has been assumed to target a ribosome stalled at the 3’-end of mRNA. Later, it has been shown that trans-translation also occurs in the middle of mRNA, for example that at a tandem rare arginine (AGA) codons (Roche & Sauer, 1999) or at an inefficient termination codon (Roche & Sauer, 2001; Hayes & Sauer, 2002; Sunohara et al., 2002). This raises the question as to whether tmRNA actually targets the ribosome stalled in the middle of mRNA prior to cleavage. The apparent absence of accumulation of truncated mRNA in the cell suggests that trans-translation can occur in the middle of mRNA without cleavage of mRNA (Roche & Sauer, 1999). However, accumulation of truncated mRNA has been successfully detected in a tmRNA-deleted cell, arguing against this possibility (Li et al., 2006). Indeed, trans-translation by tmRNA promotes the degradation of truncated mRNA, making the detection of truncated mRNA in the normal cell difficult (Yamamoto et al., 2003; Sunohara et al., 2004a,b). Trans-translation can occur in the middle of mRNA in vitro, although less efficiently than it does in the 3’-end of mRNA (Ivanova et al., 2004; Asano et al., 2005). The efficiency is dramatically decreased with increase of the length of the 3’-extension from the decoding region. It has been found that bacterial toxins such as RelE (Pedersen et al., 2003) or ChpAK/MazF (Christensen et al., 2003) cleave an mRNA specifically at the A-site in the stalled ribosome, providing a new concept that mRNA of stalled translation is targeted initially by such A-site-specific endoribonucleases and subsequently by tmRNA for transtranslation. Perhaps, tmRNA would be recruited to a ribosome stalled in the middle of mRNA, but preferentially or exclusively after the cleavage around the rare codon. Several recent studies have suggested that the ribosome pausing induces endonucleotytic cleavage of mRNA around the A-site (Li et al., 2007; Garza-Sánchez et al., 2008). Cleavage of mRNA at the A-site has been detected even in cells lacking several bacterial toxins and some cellular ribonucleases (Hayes & Sauer, 2003; Sunohara et al., 2004a,b), raising the possibility that the ribosome itself is directly involved in the cleavage of mRNA at the A-site. However, trans-translation occurs without cleavage of mRNA in vitro (Asano et al., 2005).

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Competition between Trans-translation and Translation Several in vivo and in vitro studies have indicated that competition occurs at a nonsense codon between trans-translation and the termination of translation (Collier et al., 2002; Ivanova et al., 2004; Asano et al., 2005; Li et al., 2007) or at a sense codon between transtranslation and the elongation of translation (Asano et al., 2005). It has been shown in vitro that trans-translation can occur at either the nonsense codon (Ivanova et al., 2004; Asano et al., 2005) or the sense codon (Asano et al., 2005) without cleavage of mRNA at the A-site, although a shorter 3’-extention of mRNA from the A-site is preferable. The preference of a shorter 3’-extention of mRNA suggests the competition between the 3’-extention of mRNA and alanyl-tmRNA•SmpB. Perhaps, the mRNA path encompassing the decoding region to the downstream tunnel required for interaction with alanyl-tmRNA SmpB might be sequestered extensively by mRNA with a long 3’-extension but only weakly by mRNA with a short 3’extension. This is consistent with a directed hydroxyl radical probing study showing that the C-terminal tail of SmpB occupies the mRNA path downstream of the decoding region probably upon entrance of tmRNA to the stalled ribosome (Kurita et al., 2007), described in a previous session. Collectively, aminoacyl-tRNAs, release factors, alanyl-tmRNA and A-site-specific ribonucleases would always compete with one another for the A-site in the ribosome stalled on the intact mRNA. Alanyl-tmRNA might not substantially win the competition before the cleavage of mRNA by an A-site-specific ribonuclease (Ivanova et al., 2004). The competition should significantly be influenced by the activities or levels of these molecules in the cell, which fluctuate with change in the physiological conditions. For example, bacterial toxins are activated by degradation of antitoxins upon starvation of amino acids (Pedersen et al., 2003; Christensen et al., 2003), tmRNA is induced under some stressful conditions in B. subtilis (Muto et al., 2000) and tmRNA is cell cycle-dependently induced and degarded in C. crescentus (Keiler & Shapiro, 2003a; Hong et al., 2005).

ALTERNATIVE PATHWAYS TO RESCUE A RIBOSOME PAUSING The eubacterial cell has an alternative mechanism to rescue the stalled ribosome; a peptidyl-tRNA is dropped-off from the stalled ribosome, and then it is hydrolyzed by peptidyl-tRNA hydrolase (Pth) (Das & Varshney, 2006). Unlike tmRNA or SmpB, Pth is essential and it is distributed not only among eubacteria but also among eukaryotes and archaebacteria. It has been shown that the slow growth phenotype of a temperature-sensitive mutant of Pth is suppressed by overexpression of tmRNA (Singh & Varshney, 2004), suggesting that a single stalled ribosome can be rescued both by trans-translation and by drop-off. In fact, both trans-translation product with a tag-sequence and drop-off product without a tag-sequence probably produced from the same truncated mRNA have been identified in a cell (Williams et al., 1999; Ito et al., 2002). Perhaps, the drop-off mechanism would allow the trans-translation mechanism to be nonessential in some eubacteria including E. coli. Drop-off is enhanced by RRF alone or RRF together with RF3 (Heurgue-Hamard et

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al., 1998; Herr et al., 2001; Gong et al., 2007). By contranst, high concentration of RRF inhibits the trans-translation by tmRNA in vitro (Asano et al., 2005). There might be a wide variety of ribosome stallings, which are caused by a rare codon, a downstream pseudokonot or stem-loop structure or a too strong interaction between the nascent peptide and the peptide tunnel. They might be rescued by trans-translation, drop-off or sometimes LepA-dependent back-translocation (Qin et al., 2006). Some kinds of ribosome stallings may be programed for regulation of gene expression, e.g., frameshifting or translational bypassing, which may be a result from a temporary drop-off and immediate resumption of translation at another site prior to hydrolysis by Pth (Herr et al., 2000). As in the case of drop-off, translational bypassing is also enhanced by RRF (Herr et al., 2001). E. coli tryptophanase (tna) operon is induced by tryptophan via the translation arrest of the leader peptide (TnaC) due to the inhibition of the hydrolysis of peptidyl-tRNA (TnaCtRNATrp) by RF2 (Yanofsky, 2007). This stalled ribosome is rescued slowly by RRF and RF3 leading to drop-off, whereas it is not rescued by tmRNA-mediated trans-translation in the presence of tryptophan (Gong et al., 2007). The ribosome is also stalled at an internal proline codon of E. coli secM mRNA, which up-regulates the translation of the downstream secA mRNA presumably by disrupting the secondary structure that sequesters the ribosome binding site for translation of secA mRNA (Muto et al., 2006). This translational arrest is caused by the inefficient peptidyl-transfer of Prolyl-tRNAPro in the A-site, which inhibits the entrance of Ala-tmRNA to the A-site and the A-site specific cleavage of mRNA (GarzaSánchez et al., 2006).

mRNA Surveillance Systems in Eukaryotes Because of the absence of tmRNA and SmpB, trans-translation is not believed to occur in eukaryotes with the exception of some chloroplasts or mitochondria. Thus the question arises as to how the stalled translation is rescued in eukaryotes. Recently, two novel systems termed non-stop mRNA decay (NSD) and no-go mRNA decay (NGD) have been revealed. When translation stops at the 3’-end of a truncated mRNA having no termination codon, Ski7p, a GTPase having sequence similarity to EF1A or eRF3, enters the empty A-site to promote dissociation of the stalled complex, thereafter allowing 3’-to-5’ degradation of truncated mRNA by exosome (NSD) (Frischmeyer et al., 2002; van Hoof et al., 2002). When translation stops in the middle of mRNA, Dom34p and Hps1p, eRF1 and eRF3 homologues, respectively, enters the empty A-site to trigger cleavage of mRNA at the A-site by an A-site specific endonuclease that has not been identified (NGD) (Doma & Parker, 2006; Clement & Lykke-Andersen, 2006). The resulting 5’-half of mRNA is degraded by exosome in the 3’ to 5’ direction, while the 3’-half is degraded by Xrn1p in the reversed direction. The stalled ribosome due to the presence of a stem-loop structure is a preferential target of NGD, and that due to the presence of a pseudoknot, rare codon or even a premature stop codon is also a target. Neither tmRNA nor SmpB homologue is involved in these eukaryotic mRNA surveillance systems. The stalled translation is rescued only by protein factors, but not by any RNA molecule. On the other hand, it has never been found that any release factor homologue

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is involved in the rescue of the stalled translation in eubacteria. Therefore, the eukaryotic and eubacterial systems appear to have no evolutionary relationship with each other. Many components of exosome, a multi-protein complex including ribonucleases and helicases, are conserved among eukaryotes and archaebacteria (Büttner et al., 2006), and some of them have weak sequence similarity to those included in degradosome in eubacteria (Symmons et al., 2002).

DEGRADATION OF TAGGED PROTEINS Several proteases including ClpXP, ClpAP, FtsH, Tsp and Lon are involved in degradation of tmRNA-tagged proteins in E. coli. ClpXP and ClpAP are typical cytoplasmic ATP-dependent proteases, consisting of ClpP peptidase and hexamers of ClpX and ClpA, respectively. ClpX or ClpA recognizes the C-terminal ALAA sequence of the tagged proteins to unfold them for degradation by ClpP (Gottesman et al., 1998). SspB, a ribosomeassociated protein, specifically binds to the N-terminal AAND sequence of the tag-peptide to increase the affinity of ClpX to the tagged proteins, and consequently ClpXP serves as the major degradation machinery of tagged proteins in the cytoplasm (Flynn et al., 2001; Lessner et al., 2007). Lon, another cytoplasmic ATP-dependent protease, is also involved in the degradation of tagged proteins under stressful conditions (Choy et al., 2007). FtsH, an ATPdependent hexameric protease, anchored to the cytoplasmic side of the inner membrane, degrades the tagged proteins in the inner membrane (Herman et al., 1998). Tsp is involved in the degradation of the tagged proteins in the periplasm (Keiler et al., 1996). Although the Cterminal AA sequence of the tag-peptide is highly conserved, it terminates with FA in Mycoplasma, which lacks ClpXP, ClpAP and Tsp (Karzai et al., 2000).

Biological Function The trans-translation system seems to be present in all eubacteria, suggesting that it emerged at a very early stage of the eubacterial evolution. The high sequence conservation of tmRNA, together with that of SmpB, suggests crucial roles of this system in the cell growth. In some eubacteria, such as Neisseria gonorrhoeae (Huang et al., 2000), Haemophilis influenzae (Akerley et al., 2002) and Mycoplasma genitalium (Hutchison et al., 1999), tmRNA is essential for growth. In Salmonella enterica and Yersinia pseudotuberculosiss, tmRNA-deficiency leads to the loss of pathogenesity, probably due to an inability of the cells to survive in macrophages (Bäumler et al., 1994; Julio et al., 2000; Okan et al., 2006). The growths of immP22, a and P22 hybrid phage, in E. coli and of P22 in S. enterica cells also require tmRNA (Withey & Friedman, 1999; Julio et al., 2000). Mu prophage is induced in E. coli in a tmRNA-dependent manner (Ranquet et al., 2001). Although with such instances, in most eubacteria including E. coli and B. subtilis, the growths under normal nutrient culture conditions are not seriously affected by the deletion of tmRNA. However, the requirement of tmRNA is increased under several stressful conditions. A high temperature decreases the growth rate of tmRNA-deleted mutant of E. coli (Oh &

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Apirion, 1991) or B. subtilis (Muto et al., 2000). The heat shock response is constitutively induced in a tmRNA-deleted mutant cell (Munavar et al., 2005), and the recovery from carbon starvation is slower in E. coli (Oh & Apirion, 1991) and in Yersinia pseudotuberclosis (Okan et al., 2006). The expression level of a stress-response sigma factor RpoS, which controls the expression of many genes for the survival of the cell under stressful conditions, is positively controled by tmRNA (Ranque & Gottesman, 2007). In B. subtilis, several stresses, such as ethanol, cadmium and low temperature (Muto et al., 2000; Shin & Price, 2007), also seriously affect the growth of the cells lacking tmRNA, and the requirement of tmRNA increases as the strength of stresses increases (Muto et al., 2000). The spore formation of B. subtilis caused by nutrient starvation is significantly impaired by tmRNAdeficiency (Abe et al., submitted). Moreover, the amount of tmRNA in B. subtilis cells increases with the increase of stresses (Muto et al., 2000). Concomitantly, total transtranslation products increase under stresses. Stresses might increase aberrant translation events in the cells, which can be rescued by trans-translation. This may explain why tmRNA genes are conserved among eubacterial species, as bacteria must have been exposed to various environmental stresses during evolution. Many other phenotypes of tmRNA-deletion cells are summarized in the review article of Keiler (2007). The stall of translation should decrease the amount of free ribosomes for a new round of translation to impair the overall translation, leading to a decrease of the amount of the normal translation products in the cell. In particular, the amount and/or function of the protein translated from a very low level of mRNA would be seriously affected. This would be the case especially under insufficient growth conditions, such as under stressful conditions. Most of the defective phenotypes by the depletion of tmRNA can be complemented by an introduction of tmRNA-DD or tmRNA-His6, which is active in trans-translation reaction but defective in proteolytic degradation of tagged proteins, into the cells. N. gonorrhoeae and H. influenzae can grow with tmRNA-DD instead of wild-type tmRNA. The defective growth of immP22 and other phages in the cell lacking tmRNA is also complemented by tmRNADD. Thus it is generally accepted that the primary function of tmRNA-mediated transtranslation is rescuing stalled ribosomes rather than degrading the trans-translation products (for reviews, Withey & Friedman, 2003; Moore & Sauer, 2007; Keiler, 2007). The degradation of the trans-translation products is not important for the growth of many eubacteria in normal nutrient medium. Perhaps, the accumulation of nonfunctional proteins would not be serious for the cell. However, upon starvation of amino acids, the supply of amino acids from tagged proteins should be critical for a new protein synthesis in the cell (Pedersen et al., 2003; Li et al., 2008). Toxins such as RelE would accelerate the supply of amino acids from the nascent polypeptides on the stalled ribosomes via trans-translation. Trans-translation is sometimes involved in the regulation of the gene expression such as in the stress-responsive events described above. Trans-translation occurs at specific sites of specific mRNAs and it occurs on different mRNAs with the difference of culture conditions (Fujihara et al., 2002), supporting this concept. Several other examples have also been exemplified. The tagging of E. coli LacI, a repressor protein of the lac operon, occurs near the C-terminal, and the cells lacking tmRNA exhibit slower induction of -galactosidase (Abo et al., 2000). Degradation of LacI mRNA via tmRNA-mediated trans-translation might accelerate the derepression of the lac operon. In C. crescentus, the cell cycle (Keiler &

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Shapiro, 2003a) and the initiation of DNA replication (Keiler & Shapiro, 2003b) are controled by trans-translation. Indeed, the proteins involved in DNA replication have been overpresented in a proteomic study (Hong et al., 2007). Among eight target proteins identified in B. subtilis, the genes for three proteins, TreP, YtoQ and FolA, contain cre sequences (catabolite responsive element) within the protein-encoding regions around the presumed tagging sites (Fujihara et al., 2002). The genes involved in the carbon catabolite repression in B. subtilis are negatively regulated by binding of a repressor protein CcpA to the cre sequence (Fujita et al., 1995), which leads to a transcriptional roadblock upstream of the authentic stop codon (Miwa et al., 2000). Indeed, trans-translation occurs on TreP mRNA truncated at about 8-9 bp upstream of the cre sequence (Ujiie et al., unpublished). In consideration of the limitation of the detection of regulatory protreins of a low expression level, trans-translation would be much more deeply involved in the regulation of the gene expression than we have expected.

CONCLUSION Translating ribosomes often stall during the canonical mRNA turnover, upon stressdependent degradation of mRNA or under some special contexts of the sequence or structure of mRNA. Sometimes, translation is programmed to stall at a specific site on mRNA. Although with alternative pathways, trans-translation is a main pathway in the eubacterial cell to rescue the stalled translation for recycling of the ribosomes and dagradation of the truncated mRNA. Based on a directed hydroxyl radical probing study, we have proposed a novel molecular mechanism of trans-translation. In this model, a collaboration of a hybrid RNA molecule of tRNA and mRNA (tmRNA) and a protein mimicking a set of tRNA and mRNA (SmpB) facilitates trans-translaion. Upon entrance to the stalled ribosome, alanylTLD of tmRNA mimicking the upper-half of aminoacyl-tRNA and the main body of SmpB recognizes the A-site free of tRNA, and the C-terminal of SmpB mimicking mRNA interacts with the decoding region and the downstream mRNA path free of mRNA to recognize the stalled ribosome. While several proteins including SmpB mimic tRNA or its portion, SmpB is the first protein that mimics mRNA. When the tRNA domain of tmRNA•the main body of SmpB moves from the A-site to the P-site and then to the E-site like tRNA, a truncated mRNA, the C-terminal tail of SmpB encoding the first alanine residue of the tag-peptide and tmRNA encoding the last 10 amino acid residues of the tag-peptide pass through the decoding region in order. Our model depicts the outline of the trans-translaion processes in the ribosome. However, not only many enigmas remain unsolved but also the model poses new questions. Does SmpB•TLD move from the P-site to the E-site, and then release from the ribosome like deacylated tRNA, although no such protein has been found? How do the intermolecular interactions between tmRNA and ribosome, between tmRNA and SmpB and between ribosome and SmpB as well as the intramolecular interactions within tmRNA and within SmpB change during the course of the trans-translaion processes? Whether is EF-G required for translocation of SmpB•TLD from the A-site to the P-site? If so, how does it promote

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translocation? How deeply is trans-translaion involved in the regulations of gene expressions in the cell? How had tmRNA, SmpB and the trans-translaion system appeared and evolved?

ACKNOWLEDGEMENTS Authors are grateful to all those who have been involved in this work. This work was supported by Grants-in-Aid for scientific research from the Ministry of Education, Science, Sports and Culture, Japan to H.H. and A.M., Grants-in-Aid for scientific research from the Japan Society for the Promotion of Science to H.H. and A.M. and the 21th COE program of Iwate University for D.K.

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Valle, M., Zavialov, A., Li, W., Stagg, S.M., Sengupta, J., Nielsen, R.C., Nissen, P., Harvey, S.C., Ehrenberg, M., & Frank, J. (2003b). Incorporation of aminoacyl-tRNA into the ribosome as seen by cryo-electron microscopy. Nat. Struct. Biol., 10, 899-906. van Hoof, A., Frischmeyer, P.A., Dietz, H.C., & Parker, R. (2002). Exosome-mediated recognition and degradation of mRNAs lacking a termination codon Science, 295, 22622264. Vestergaard, B., Van, L.B., Andersen, G.R., Nyborg, J., Buckingham, R.H., & Kjeldgaard, M. (2001). Bacterial polypeptide release factor is structurally distinct from eukaryotic eRF1. Mol Cell, 8, 1375-1382. Vestergaard, B., Sanyal, S., Roessle, M., Mora, L., Buckingham, R.H., Kastrup, J.S., Gajhede, M., Svergun, D.I., & Ehrenberg, M. (2005). The SAXS solution structure of RF1 differs from its crystal structure and is similar to its ribosome bound cryo-EM structure. Mol. Cell, 20, 929-938. Wasserman, K.M. (2002). Small RNAs in bacteria: Diverse regulators of gene expression in response to environmental changes. Cell, 109, 141-144. Williams, K.P. (2000). The tmRNA website. Nucleic Acids Res, 28, 168. Williams, K.P. (2002). Descent of a split RNA. Nucleic Acids Res, 30, 2025-2030. Williams, K.P., & Bartel, D.P. (1996). Phylogenetic analysis of tmRNA secondary structures. RNA, 2, 1306-1310. Williams, K.P., Martindale, K.A., & Bartel, D.P. (1999). Resuming translation on tmRNA: a unique mode of determining a reading frame. EMBO J., 18, 5423-5433. Wilson, D.N., Schluenzen, F., Harms, J.M., Yoshida, T., Ohkubo, T., Albrecht, R., Buerger, J., Kobayashi, Y., & Fucini, P. (2005). X-ray crystallography study on ribosome recycling: the mechanism of binding and action of RRF on the 50S ribosomal subunit. EMBO J., 24, 251-260. Withey, J.H., & Friedman, D.I. (1999). Analysis of the role of trans-translation in the requirement of tmRNA for immP22 growth in Eschericia coli. J. Bacteriol., 187, 21482157. Withey, J.H., & Friedman, D.I. (2003). A salvage pathway for protein structures: tmRNA and trans-translation. Annu. Rev. Microbiol., 57, 101-123. Wower, I.K., Zwieb, C.W., Guven, S.A., & Wower, J. (2000). Binding and cross-linking of tmRNA to ribosomal protein S1, on and off the Escherichia coli ribosome. EMBO J., 19, 6612-6621. Wower, J., Zwieb, C.W., Hoffman, D.W., & Wower, I.K. (2002). SmpB: a protein that binds to double-stranded segments in tmRNA and tRNA. Biochemistry, 41, 8826-8836. Wower, I.K., Zwieb, C., & Wower, J. (2004). Contributions of pseudoknots and protein SmpB to the structure and function of tmRNA in trans-translation. J. Biol. Chem. 279, 54202-54209. Wower, I.K., Zwieb, C., & Wower, J. (2005). Transfer-messenger RNA unfolds as it transits the ribosome. RNA, 11, 668-673. Yamamoto, Y., Sunohara, T., Jojima, K., Inada, T., & Aiba, H. (2003). SsrA-mediated transtranslation plays a role in mRNA quality control by facilitating degradation of truncated mRNAs. RNA, 9, 408-418.

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In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter V

MODIFICATION OF MRNA TRANSLATION INITIATION TO STIMULATE PROTEIN SYNTHESIS IN SEPSIS Thomas C. Vary* Department of Cellular and Molecular Physiology, The Pennsylvania State University College of Medicine, Hershey, PA 17033, USA

ABSTRACT Sepsis, the systemic manifestation to bacterial infection, induces profound alterations in whole-body protein metabolism. Nitrogen losses up to 17% of total body protein may be observed in septic patients despite aggressive nutritional support. Organ system dysfunction and, eventually, organ failure can result from the persistent loss protein in sepsis. Sustained muscle protein catabolism continues to complicate recovery in septic patients. This review will illuminate potential molecular mechanisms responsible for increasing mRNA translation initiation in striated muscle. Emphasis will be placed on the role of growth hormones and nutrients in promoting rates of protein synthesis during sepsis. In this regard, elevating amino acids and IGF-I both interact to maximally enhance rates of protein synthesis acutely during sepsis through an acceleration of the mRNA translation initiation. IGF-I appears unique in accelerating protein synthesis during sepsis as growth hormone appears to enhance mortality while muscle shows a general resistance to the anabolic actions of insulin. Like IGF-I, amino acids and leucine in particular stimulate mRNA translation initiation by targeting specific signal transduction pathways. The hastening of mRNA translation initiation most likely results from a stimulation of mammalian target of rapamycin (mTOR) acting through its downstream effector proteins to enhance assembly of eIF4G with eIF4E via 4E-BP1 and eIF4G phosphorylation and to increase S6K1 phosphorylation. The physiologic *

Corresponding Author: Dr. Thomas C. Vary. Department of Cellular and Molecular Physiology, Rm C4718, Penn State University College of Medicine, H166, 500 University Drive, Hershey, PA 17033, Telephone: 717-5315014. Fax: 717-531-7667; Email: [email protected]

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INTRODUCTION Sepsis represents the host’s response to systemic infection. Despite the availability of a new generation of antibiotics and intensive supportive care, the overall hospital mortality rate ranges from 25-40% in septic patients making sepsis the leading cause of death in noncoronary intensive care units [23, 59] and the 12th leading cause of death [60, 72] accounting for nearly 10% (215,000 deaths) of all deaths in The United States (1). Mortality, morbidity, and cost remain high, despite many advances in the care for critically ill patients with severe injury or sepsis. The duration and extent of the metabolic changes seen in response to critical surgical illness and intensive care treatments have become better characterized. Although some of the changes in body water and fat are modifiable, loss of large amounts of (functional) protein has been resistant to various strategies so far studied. A major complication contributing to the morbidity and mortality in septic patients is the development of diffuse tissue injury referred to as multiple organ system dysfunction (MODS). MODS can lead to the failure of major organ systems of the body to maintain homeostasis. The septic process spares no organ system of the body. The hallmark of host’s response to systemic infection is the dyshomeostasis in protein metabolism that manifests itself in a severe loss of urea nitrogen. The net effect of these alterations is an overall catabolic condition, which seriously compromises recovery. These alterations lead to a functional redistribution of nitrogen (amino acids and proteins) and substrate metabolism among wounded tissues and major body organs. The redistribution of amino acids and proteins results in a quantitative reordering of the usual pathways of carbon and nitrogen flow within and among tissues of the body with resultant depletion of structural and functional proteins responsible for maintaining cellular homeostasis in important organs. Nitrogen losses up to 17% of total body protein may be observed in septic patients despite aggressive nutritional support (see for example [73]). Because skeletal muscle comprises approximately 45% of body weight, whole-body nitrogen balance reflects changes in protein turnover in muscle during sepsis. As such, approximately 70% of the septic-induced whole-body protein loss comes from erosion of skeletal muscle [73]. The persistent loss of large amounts of protein in sepsis leads to organ system dysfunction and, eventually, organ failure [46]. The clinical implications of continued loss of skeletal muscle protein in septic patients include poor wound healing [13], loss of muscle strength, diminished muscle activity [9, 11, 115], and, if severe enough, death [46]. Muscle weakness in septic patients contributes to a continued dependence on mechanical respirators, an increased risk of pneumonia, and the complications associated with extended periods of bed rest. These complications prolong hospitalization and convalescence, thereby increasing health-care costs [114]. Much effort has focused to modulate the overall amount of nutrients given to septic patients in a hope to improve efficiencies in utilization and nitrogen economies, rather than support of specific end-organ targets. Indeed, early enteral pharmaconutrition formula results in significantly

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faster recovery of organ function in medical patients with sepsis [7]. This review examines current understanding of the processes affected by sepsis and testable therapies (leucine and/or IGF-1) to circumvent the sepsis-induced defects in protein synthesis in skeletal muscle. In a healthy individual, nutrition involves an alternating system of feeding and fasting, with periods of fasting longer than 72 hr inducing a state of starvation. The hormonal response to nutrition is substrate controlled with glucose and amino acids, during the fed state, stimulating insulin secretion and decreasing glucagon secretion. Glycogen reserves and protein synthesis increase and the excess carbohydrate, amino acids and fats are stored as lipid. During the fasted state, plasma levels of glucose and amino acids fall, reducing insulin secretion and increasing glucagon secretion, stimulating gluconeogenesis and glycogenolysis. During injury and sepsis the nutritional hormones are no longer substrate controlled. In the septic state, in addition to the hormonal stress response, polypeptide mediators of tumor necrosis factor (TNF-alpha) and interleukin-1 are liberated, accelerating net skeletal muscle protein catabolism determined by the balance between protein synthesis and degradation. Emphasis will be placed on the role of selective nutrients in promoting rates of protein synthesis during the septic episode to limit net catbolism. In this regard, elevating amino acids or IGF-1 maximally enhance rates of protein synthesis acutely during sepsis through an acceleration of the mRNA translation initiation. IGF-I appears unique among peptide hormones in accelerating protein synthesis during sepsis as skeletal muscle shows a general resistance to the anabolic actions of insulin or growth hormone. Like IGF-I, amino acids stimulate mRNA translation initiation by targeting specific signal transduction pathways. For example, branched-chain amino acids (BCAA: leucine, isoleucine and valine) are not just structural constituents of proteins, but have ''pharmacologic'' properties that enhance protein synthesis through enhancing mRNA translation initiation. The hastening of mRNA translation initiation most likely results from a stimulation of mammalian target of rapamycin (mTOR) acting through its downstream effector proteins to enhance at the molecular level the assembly of eIF4G with eIF4E via 4E-BP1 and eIF4G phosphorylation and to increase S6K1 phosphorylation. The physiologic importance lies in the potential ability of IGF-I and amino acids as specific stimulators of mRNA translation designed to counteract the accelerated host protein wasting in septic patients and maintain muscle mass.

Skeletal Muscle Protein Metabolism Dyshomeostasis during Inflammation and Sepsis The protein wasting observed in skeletal muscle during sepsis results from an imbalance between rates of protein synthesis and protein degradation. In sepsis, an inhibition of protein synthesis and/or an acceleration of protein degradation leads to the loss of muscle protein during sepsis. The severity of the septic insult determines the relative contribution of slowing in protein synthesis and acceleration of proteolysis to the overall net catabolic state in muscle. Protein degradation varies, increasing as the septic episode worsens [10] and appears independent of the fiber composition of the muscle. In contrast, rates of protein synthesis are reduced to a similar extent regardless of the severity of the septic insult. Furthermore,

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inhibition of protein synthesis occurs preferentially in muscles composed of fast-twitch fibers [14, 51, 100]. Sepsis affects the overall process of protein synthesis. The synthesis of both myofibrillar and sarcoplasmic proteins is diminished to the same extent, indicating that some global mechanism controls protein synthesis during sepsis [106]. Indeed skeletal muscle mRNA content of myosin and actin are unaffected by the septic process. As the septic process wanes, muscle protein mass and protein synthesis return toward control values [43]. Non-septic trauma can also sometimes results in a decrease in protein synthesis and increase in proteolysis in skeletal muscle. In contrast to severe infection, changes in proteolysis and protein synthesis are short-lived in non-septic, trauma patients. With adequate nutritional support, restoration of positive nitrogen balance and lean body mass occurs within days of the injury. In agreement with studies in well-nourished non-septic trauma patients, skeletal muscle protein synthesis is not decreased by a wide-range of non-septic inflammatory insults [5, 39, 47, 50, 100, 108].

REGULATION OF PROTEIN SYNTHESIS Protein synthesis is a multistep, highly regulated process that includes cellular transport of amino acids, activation of protein factors, transcription, and translation. The process involves the association of the 40S and 60S ribosomal subunits, messenger RNA (mRNA), initiator methionyl-tRNA (met-tRNAimet), other amino acyl-tRNAs, cofactors (i.e. GTP; ATP), and protein factors, collectively known as eukaryotic initiation factors (eIF), elongation factors (eEF), and releasing factors (RF), through a series of discrete reactions that lead to translation of mRNA into proteins. Translation of mRNA is comprised of three phases: (a) initiation, whereby met-tRNAimet and mRNA bind to 40S ribosomal subunits, and subsequent binding of the 40S ribosomal subunit to the 60S subunit to form a ribosome complex capable of translation; (b) elongation, by which tRNA-bound amino acids are incorporated into growing polypeptide chains according to the mRNA template; and (c) termination, where the completed protein is released from the ribosome. Sepsis primarily affects the mRNA translation initiation step of protein synthesis. Impediments in mRNA translation initiation occur predominately through reductions in the abundance of ribosomes and/or translational efficiency. Sepsis does not diminish the relative abundance of ribosomes [14, 43, 100], but rather reduces the translational efficiency 50% in the skeletal muscle [14, 43, 82, 100]. The efficiency of translation, calculated by dividing the protein synthetic rates by the total RNA (or mRNA) content, provides an index of how rapidly the existing ribosomes synthesize protein. The decline in translational efficiency does not result from a decreased abundance of mRNA in muscles from septic rats [106]. Inhibition of the translational efficiency occurs by retarding either peptide-chain initiation whereas the rate of peptide-chain elongation is unaffected in skeletal muscle [100]. Therefore, inhibitory effects of sepsis on protein synthesis are related to derangements in mRNA translation initiation.

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Steps in Translation Initiation Inhibited during Sepsis In the first step, the 80S ribosome dissociates into 40S and 60S ribosomal subunits. In the second step, binding of met-tRNAimet to the 40S subunit forms the 43S preinitiation complex. The binding of met-tRNAimet to the 40S ribosomal subunit to form the 43S preinitiation complex is mediated by eukaryotic initiation factor 2 (eIF2) and is regulated by the activity of another eukaryotic initiation factor, eIF2B. In the third step, mRNA binds to the 43S preinitiation complex and from 48S preinitiation complex. The binding of mRNA to the 43S preinitiation complex is mediated by eIF4F. In the fourth step, the 60S ribosomal subunit associates with the 48S preinitiation complex leading to the formation of an 80S ribosome capable of carrying out the elongation phase of protein synthesis. The second and third steps in the process of mRNA translation initiation control the overall rate of protein synthesis (Figure 1). Sepsis inhibits both these regulatory steps involved in mRNA translation initiation [14, 43, 82, 98, 100, 109, 110].

REDUCED EIF2B ACTIVITY IN SKELETAL MUSCLE DURING SEPSIS Two mechanisms regulate the assembly of a 43S preinitiation complex catalyzed by eIF2. First, the amount of eIF2 in the cell may be altered. However, the cellular content of eIF2 is not significantly decreased in skeletal muscle from septic rats [97, 109]. Second, restraining recycling of GTP for GDP on eIF2 by lowered eIF2B activity restricts eIF2.GTP availability to form the ternary complex, thereby curbing translation initiation. Sepsis diminishes the activity of eIF2B in skeletal muscle where protein synthesis is inhibited [97, 98]. The best-characterized mechanism controlling eIF2B is through phosphorylation of eIF2 on its α subunit [eIF2(αP)] [54]. Phosphorylation of eIF2  converts the protein from a substrate into a competitive inhibitor of eIF2B [24, 54, 77], thereby limiting the ability of eIF2B to exchange GDP [24, 54, 77]. While this mechanism is important in regulating protein synthesis in other conditions, skeletal muscle from septic rats does not show elevations in eIF2α phosphorylation [97]. eIF2B is undergoes allosteric regulation by NAD+ and NADP+ [24, 45, 66, 79]. However, the NADPH/NADP+ concentration ratio is not significantly altered in gastrocnemius of septic rats [98]. Thus, diminished eIF2B activity does not relate to changes in the redox state during sepsis. Instead, the cellular content of eIF2B is reduced in chronic sepsis [109, 110]. However, eIF2B protein content is not increased in studies where protein synthesis in gastrocnemius from septic rats is acutely augmented [42, 44]. Thus, reduced eIF2B protein content can be overridden and, thus, other mechanisms may be involved.

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INCREASED PHOSPHORYLATION OF EIF2B DURING SEPSIS In addition to the above mechanisms for regulating eIF2B activity, the catalytic, εsubunit of eIF2B (eIF2Bε) undergoes reversible phosphorylation. An increase in the state of eIF2Bε phosphorylation (catalyzed by glycogen synthase kinase-3 (GSK-3)) inactivates the guanine nucleotide exchange activity [40, 111-113] Phosphorylation of eIF2Bε was significantly augmented over 2-fold and 2.5-fold after 3 and 5 days and returned to control after 10 days of sepsis when the septic process wanes. Sepsis augmented eIF2Bε phosphorylation by enhancing eIF2B kinase activity rather than reducing phosphatase activity [93]. Phosphorylation of glycogen synthase kinase-3 (GSK-3), a potential upstream kinase responsible for the elevated phosphorylation of eIF2Bε, was significantly reduced over 36 and 41% after 3 and 5 days and returned to control values after 10 days of sepsis. PKB has emerged as the most likely candidate to phosphorylate and inactivate GSK-3 [17]. PKB undergoes reversible phosphorylation with high levels of PKB activity associated with an increased GSK-3 phosphorylation. A disconnect between the phosphorylation of PKB and GSK-3 exists over the course of the septic episode. Initially, the extent of PKB phosphorylation becomes depressed during abscess formation stage, but beyond day 3 postinfection, the phosphorylation of PKB returns to basal values. Hence, reductions in PKB phosphorylation may explain the decrease in GSK-3 phosphorylation on day 3 postinfection. However, PKB phosphorylation is not altered in septic rats on day 5 postinfection, a time when GSK-3 phosphorylation remains diminished compared with sterile inflammatory rats. Treatment of septic rats with TNF-binding protein prevented the sepsis-induced changes in eIF2Bε and GSK-3 phosphorylation, implicating TNF in mediating the effects of sepsis. However infusion of TNF was without effects on eF2B phosphorylation [49]. The reasons for this dichotomy remain obscure. Thus increased phosphorylation of eIF2Bε via activation of GSK-3 is an important mechanism to account for the inhibition of skeletal muscle protein synthesis during sepsis. The dynamics of this signal transduction pathway over the course of the septic process requires additional explanation.

MRNA

RECRUITMENT TO RIBOSOME BY EIF4E IS IMPAIRED IN SKELETAL MUSCLE DURING SEPSIS

Another rate-controlling step in the process of peptide-chain initiation involves the recognition, unwinding and binding of mRNA to the 40S ribosomal subunit. The multisubunit complex of eukaryotic factors eIF4F catalyzes this step [81, 104]. eIF4F is composed of 1) eIF4A (a RNA helicase that functions with eIF4B to unwind secondary structure in 5’untranslated region of mRNA), 2) eIF4E (a protein that binds directly to the m7GTP cap structure present at the 5’-end of most eukaryotic mRNAs), and 3) eIF4G (a protein that functions as a scaffold for eIF4E, eIF4A and the mRNA and the ribosome). eIF4G appears to be the nucleus around which the initiation complex forms, because it has binding sites not only for eIF4E but also for eIF4A and eIF3 [48]. eIF4E is the least abundant initiation factor in most cells. eIF4E activity plays a critical role in determining global rates of mRNA

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translation, because essentially all mammalian mRNAs contain the m7GTP cap structure at their 5'-ends. eIF4E is regulated by alterations in either its availability or phosphorylation. Decreasing eIF4E content through transfection with anti-sense RNA causes an inhibition of protein synthesis at the level of translation initiation. However, the cellular content of eIF4E is not decreased in gastrocnemius of septic rats [99]. eIF4E is also regulated by reversible phosphorylation following activation of the MNK1 kinase. Phosphorylation of eIF4E enhances the affinity of the factor for m7GTP cap on mRNA and for eIF4G and eIF4A and correlates with enhanced rates of protein synthesis in cells in culture stimulated with mitogens, growth factors or serum, or transformed with ras or src oncogenes [61-63]. Conversely, reduced phosphorylation of eIF4E correlates with an inhibition of protein synthesis with serum depletion [26]. Sepsis does not modify the extent of eIF4E phosphorylation in skeletal muscle. Translation initiation may also be regulated through the formation of the eIF4E·eIF4G complex. A positive linear relationship between rates of protein synthesis and amount of eIF4G associated with eIF4E in muscle is observed in vivo [96]. Although this correlation does not prove cause and effect, the relationship between protein synthesis and amount of eIF4G associated with eIF4E is consistent with the proposed role of eIF4G·eIF4E complex in the overall regulation of protein synthesis. The assembly of the eIF4E·eIF4G complex is significantly diminished in skeletal muscle from septic rats [92, 94, 96, 99]. The diminished assembly of eIF4E·eIF4G complex is not the result of a reduced amount of eIF4G in the muscles from septic rats. Reduced amounts of eIF4E associated with eIF4G following chronic sepsis would be expected diminish the association of mRNA with the ribosome, and hence limit protein synthesis. The recruitment of the translational machinery to the 5’end of mRNA can be modulated by alterations in the phosphorylation of eIF4G. In support of this suggestion, Increased phosphorylation of eIF4G correlates with accelerated rates of protein synthesis in cell extracts [63]. Sepsis, but not sterile inflammation, diminishes phosphorylation of eIF4G(Ser1108), and are consistent with a role for reduced phosphorylation of eIF4G in mediating the diminution in formation of eIF4E·eIF4G complex during sepsis [94]. Phosphorylation of eIF4G is dependent upon the cytokine response. Infusion of tumor necrosis factor (TNF)- for 24 h in non-septic rats resulted in a 70% decrease in the phosphorylation of eIF4G. The biologic activity of TNF is modulated in vivo by the proteolytic shedding of the extracellular domain of the p55 and p75 TNF receptors. An increase in soluble TNF receptors in the bloodstream neutralizes circulating TNF , thereby lowering the biologically active concentration of TNF in the plasma. Treatment of septic animals with a specific TNF binding protein (TNFbp) completely attenuated the septicinduced decrease in eIF4G phosphorylation. Howevr, it is not possible to ascribe the metabolic effects of TNFbp on phosphorylation of eIF4G in gastrocnemius during hypermetabolic sepsis to a primary effect of TNF , or a secondary effect mediated through another cytokine or inflammatory mediator whose expression is dependent upon TNF . TNF is known to stimulate the secretion of other cytokines, including IL-1 and IL-6, as well as other inflammatory mediators. Furthermore, TNF often acts in synergy with other cytokines. TNFbp lowers plasma IL-1 following an E. coli or endotoxin challenge [75, 80, 88]. Consistent with a potential role of IL-1 in regulation protein metabolism, inhibition of

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IL-1 bioactivity with a specific IL-1 receptor antagonist (IL-1ra) abates the reduction in muscle loss and protein synthesis during sepsis through preventing the inhibition in peptidechain inhibition [16, 109]. Like TNFbp, IL-1ra reversed the sepsis-induced decrease in the phosphorylation of eIF4G. These results suggest a role of IL-1 in mediating the effects of sepsis on eIF4G phosphorylation. Thus, cytokines modulate skeletal muscle signal transduction pathways leading to phosphorylation of eIF4G. The anabolic and/or anticatabolic properties of branched-chain amino acids (leucine, valine, isoleucine)(BCAA) or their ketoacid derivatives have been known since the 1970's. This led to several clinical studies in the late 1970s and early 1980s aimed at evaluating the potential benefits of BCAA supplementation in nutritional support of the critically ill. The data on the efficacy of BCAAs in burn, trauma, and septic patients were far from definitive. In some studies the plasma concentration of leucine may not have raised to a sufficiently high enough concentration to evoke stimulate of protein synthesis [58]. Indeed, Cerra observed that the ability of BCAAs to lower nitrogen loss was proportional to the BCAA load [12]. In addition, many of these studies used very small numbers and there were problems with study design such as studying patients with an expected high mortality [89]. For example, while leucine is effective in stimulating protein synthesis whereas isoleucine and valine are much less efficacious [3, 56, 57]. In many studies, BCAA-supplemented nutrition very frequently consisted of virtually equivalent amounts of all three BCAAs. Moreover, several studies were performed without adequate basal nutritional support, which most probably hampered the correct metabolic utilization of these amino acids. More recently, acute oral leucine administration stimulates protein synthesis in an experimental model of sepsis [91]. BCAA supplementation in septic patients also demonstrated an improvement in patients' nutritional status and outcome [33, 34, 41, 64]. The binding of eIF4E with eIF4G occurs at a site that also binds the translation repressor protein 4E-BP1. Hence, the association of eIF4E with 4E-BP1 in an inactive eIF4E·4E-BP1 complex is thought to prevent binding to eIF4G and, hence limit translation initiation. The association of eIF4E with 4E-BP1 is regulated in part by the phosphorylation of 4E-BP1. Phosphorylation of 4E-BP1 lowers the affinity of 4E-BP1 for eIF4E and allows for the release of eIF4E from eIF4E·4E-BP1 complex and eIF4E reciprocal binding to eIF4G. This simplistic inverse relationship between formation of active eIF4E·eIF4G complex and release of eIF4E from inactive eIF4E·4EBP1 complex through phosphorylation of 4EBP1 represents an attractive hypothesis to account to changes observed. However, a disconnect exists in the proposed relationship between the formation of active eIF4E·eIF4G complex and inactive eIF4E·4EBP1 complex in response to infection or treatment with IGF-1/IGFBP-3 binary complex [82]. Despite the lack of effect on the abundance of inactive eIF4E·4EBP1 complex, the formation of active eIF4E·eIF4G was modulated. Likewise, infusion of TNF reduces the assembly of eIF4G·eIF4E complex by approximately 80% [49]. One mechanism to account for this change would be a decreased availability of eIF4E via sequestration in an inactive 4EBP1·eIF4E complex. However, the amount of 4EBP1 associated with eIF4E only rose by 60% indicating other factors may play a role in the assembly of eIF4G·eIF4E complex following infusion with TNF [94]. The availability of eIF4E for binding to eIF4G is regulated, in part, through the association of eIF4E with a family of translational repressor proteins (4E-BPs) and through

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phosphorylation of eIF4G. In skeletal muscle, 4E-BP1 is the predominant form of he 4E-BPs. When eIF4E is bound to 4E-BP1, eIF4E cannot bind to eIF4G. Consequently, the mRNA cannot bind to the ribosome [35], thereby inhibiting cap-dependent translation of mRNA by physically sequestering eIF4E into an inactive 4E-BP1·eIF4E complex. In muscles from control rats, phosphorylation of 4EBP-1 releases eIF4E from 4E-BP1·eIF4E complex and allows the eIF4E·mRNA complex to bind to eIF4G and, then to the 40S ribosome [55]. Unlike muscles from controls, increased phosphorylation of 4E-BP1 and decreased eIF4E·4E-BP1 complex formation is not associated with an enhanced formation of eIF4E·eIF4G complex in muscles from septic rats [96]. This observation indicates that sepsis alters the formation of eIF4E·eIF4G complex through mechanisms other than eIF4E availability.

MEAL FEEDING Feeding promotes protein accretion in skeletal muscle through a stimulation of the mRNA translation initiation phase of protein synthesis either secondary to nutrient-induced rises in insulin or owing to direct effects of the nutrients (amino acids including leucine) themselves. The initial rise in insulin causes stimulation of PI3-kinase-PKB signal pathway leading to enhanced mTOR phosphorylation and subsequent stimulation of phosphorylation of S6K1 and 4E-BP1 [102, 103]. However, stimulation of PKB is not maintained throughout the feeding period. Whereas PKB phosphorylation returns to baseline values, mTOR activation continues presumably because of the elevation of plasma amino acid concentrations. The branched chain amino acids are the most robust of the plasma amino acids in their ability to cause increased phosphorylation of mTOR [56, 57]. Meal feedinginduced activation of mTOR phosphorylation is maintained as long as the food is present. With removal of food, the assembly of eIF4G·eIF4E returns to levels observed prior to feeding. The reversal of the effects of meal feeding correlate with a fall in both plasma insulin and amino acid concentrations. Thus, acute leucine-induced stimulation of protein synthesis and the phosphorylation states of 4E-BP1 and S6K1 are facilitated by the transient increases in serum insulin concentrations [2, 4]. Hence, meal feeding stimulates assembly active eIF4F complex of through both insulin-dependent and -independent mechanisms involving phosphorylation of 4E-BP1, eIF4G and S6K1.

LEUCINE STIMULATES SKELETAL MUSCLE PROTEIN SYNTHESIS Amino acids and leucine in particular, serve not only as substrates for protein synthesis but regulators of protein synthesis as well. In healthy men is postabsorptive condition, infusing a solution containing mixed amino acids reverses whole-body protein balance from negative to positive and a major component of this is the increase in muscle protein synthesis [8]. Extracellular amino acid concentrations determine amino acid balance across peripheral

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tissues independently of non-protein calories, insulin and IGF-I [83]. The balance of globular proteins improved due to the stimulation of synthesis and attenuation of degradation across arm and leg tissues, despite insignificant uptake of tyrosine, tryptophan, and cysteine. Provision of amino acids did not attenuate the degradation of myofibrillar proteins. Neither insulin nor circulating IGF-I explained improved protein balance in skeletal muscles after elevation of plasma amino acids [84]. The effect of leucine to stimulate protein synthesis does not depend upon its metabolism [78]. Supraphysiological doses of amino acids stimulate protein synthesis through accelerating translation initiation in skeletal muscle [42, 95]. This is achieved by enhancing mRNA translation initiation independent of the activity of eIF2B, in the amount of eIF4E associated with the eIF4E-binding protein (4E-BP1), or in the phosphorylation of 4E-BP1. The order of potency of amino acids to stimulate this process was leucine > norleucine > threo-L-beta-hydroxyleucine approximately = Ile > Met approximately = Val. Other structural analogues of leucine, such as H-alpha-methyl-D/Lleucine, S-(-)-2-amino-4-pentenoic acid, and 3-amino-4-methylpentanoic acid, possessed only weak agonist activity [57]. The stimulatory effect of leucine on protein synthesis in skeletal muscle is unaffected by a specific inhibitor of PI3-kinase (LY 294002). Moreover, signaling through mTOR, as monitored by the phosphorylation status of 4E-BP1 or S6K1, was not further enhanced raising the leucine concentration [95]. However, binding of eIF4E to eIF4G and eIF4G(Ser1108) phosphorylation is enhanced when leucine concentration is elevated. Collectively, these observations illustrate an experimental model whereby leucine in the absence of other regulatory agents stimulates eIF4E·eIF4G assembly and protein synthesis directly in skeletal muscle, possibly by augmenting phosphorylation of eIF4G through a signaling pathway independent of mTOR. Hence formation of the active eIF4E·eIF4G complex controls protein synthesis in skeletal muscle when the amino acid concentration is raised above the physiological range. In using leucine or amino acids a nutritional supplement, the effects of chronic administration have not been well defined. Leucine or norleucine supplementation of drinking water for 12 days is accompanied by increased rates of protein synthesis in adipose tissue, liver, and skeletal muscle, but not in heart or kidney. Supplementation is not associated with increases in the anabolic hormones insulin or insulin-like growth factor I. Chronic supplementation did not cause apparent adaptation in either components of the mTOR cell-signaling pathway that respond to leucine (mTOR, ribosomal protein S6 kinase, and 4E-BP1) or the first two steps in leucine metabolism (the mitochondrial isoform of branched-chain amino acid transaminase, branched-chain keto acid dehydrogenase, and branched-chain keto acid dehydrogenase kinase), which may be involved in terminating the signal from leucine. These results suggest that provision of leucine or norleucine supplementation via the drinking water results in stimulation of postprandial protein synthesis in adipose tissue, skeletal muscle, and liver without notable adaptive changes in signaling proteins or metabolic enzymes. However, sepsis decreases plasma concentrations of valine, leucine, isoleucine, alanine, serine, glutamic acid, histidine, proline and glycine; while the concentrations of threonine, cysteine, the ratio of phenylalanine and tyrosine (Phe/Tyr) were elevated [29, 107]. Indeed, lowering the plasma leucine concentrations decreases the rate of protein synthesis in muscle. The inhibition of protein synthesis was associated with a 40% decrease in eIF2B activity and

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an 80% fall in the abundance of eIF4E·eIF4G complex. The fall in eIF4G binding to eIF4E was associated with increased 4E-BP1 bound to eIF4E and a reduced phosphorylation of 4EBP1. In contrast, the extent of phosphorylation of eIF4E was unaffected [95]. Hence, removal of leucine reduces protein synthesis through changes in both eIF2B and eIF4E. Based on the aforementioned studies, restoring and further elevating plasma amino acids represent one approach to augment protein synthesis in sepsis. Indeed, infusion of IL-1ra in septic patients elevates the plasma concentration of eleven amino acids and total amino acid concentration was increased by 50% within 70 hrs [15] and is associated with a lower nitrogen excretion. Concentrations of several amino acids including leucine were increased up to two-fold by infusion of IL-1ra. Hence IL-1ra may be a useful adjunct to promote muscle accretion during sepsis. Amino acids and leucine in particular stimulate mRNA translation initiation. Gavage with leucine stimulated protein synthesis and enhanced the assembly of the active eIF4G·eIF4E complex [91]. Increased assembly of the active eIF4GeIF4E complex was associated with a robust rise in phosphorylation of eIF4G(Ser1108) and a decreased assembly of inactive 4E-BP1-eIF4E complex in both sterile inflammatory and septic rats. The reduced assembly of 4E-BP1-eIF4E complexes was associated with an increase in phosphorylation of 4E-BP1 in the gamma-form following oral leucine gavage. Phosphorylation of 70-kDa ribosomal protein S6 kinase on Thr389 was also increased following oral leucine gavage, as well as the phosphorylation of mammalian target of rapamycin on Ser2448 or Ser2481. In contrast, phosphorylation of protein kinase B (PKB) on Thr308 or Ser473 was not augmented following oral leucine gavage in septic rats. Hence, leucine stimulates a PKB-independent signal pathway elevating the eIF4G-eIF4E complex assembly through increased phosphorylation of eIF4G and decreased association of 4E-BP1 with eIF4E in skeletal muscle during sepsis [91]. Likewise, amino acids stimulate skeletal muscle protein synthesis during acute endotoxemia via mTOR-dependent ribosomal assembly despite reduced basal protein synthesis rates in neonatal pigs [67]. There appears to be a threshold effect with regard to effects of branched chain amino acid effects on protein synthesis [18]. Phosphorylation of S6K1 is maximal at an oral dose of leucine that increases plasma leucine concentrations approximately threefold [58]. This may account for the failure of branched chain amino acids to augment protein synthesis in muscle during sepsis [38]. In contrast, changes in phosphorylation state of the branched chain -keto acid dehydrogenase (the enzyme responsible for oxidative decarboxylation of branched chain keto acids) require higher plasma leucine concentrations than that observed for activation of S6k1. The results seem more consistent with a role for BCKD and BCKD kinase in the activation of leucine metabolism/oxidation and removal of leucine signal than in the activation of the leucine signal to mTOR. Enteral leucine administration increases the formation of active eIF4G·eIF4E complex and activation of S6K1 pathway both of which are associated with accelerated rates of protein synthesis to values observed in rats with a sterile, non-septic abscess. Enteral leucine treatment modality appears to overcome the inhibition of protein synthetic process through acutely augmenting eIF4G·eIF4E complex formation during chronic sepsis. In summary, raising the plasma leucine concentration via oral administration of leucine to septic rats stimulated phosphorylation of both 4E-BP1 and eIF4G, maximizing the assembly of active eIF4G·eIF4E complex. The increase in formation of active eIF4G·eIF4E

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complex and activation of S6K1 pathway is associated with accelerated rates of protein synthesis. The enteral leucine treatment modality appears overcome the sepsis-induced inhibition of protein synthetic process through acutely augmenting eIF4G·eIF4E during chronic sepsis. Hence leucine appears to belong to a class of pharmaconutrients that act through modulating cell signaling, exert anabolic/anticatabolic functions when provided in sufficient amounts, with these effects occurring independently of the nutritional value of the supplement. This means that leucine supplementation should be given in addition to, and not as a replacement for, sufficient and balanced nutritional support [19]. How human muscle cells sense an increase in leucine and/or essential amino acids to activate mammalian target of rapamycin signaling is currently unknown.

INCREASING IGF-1 BIOAVILABILITY STIMULATES OF PROTEIN SYNTHESIS IN STRIATED MUSCLE DURING SEPSIS Protein synthesis in muscles from septic rats was unresponsive to stimulation by insulin [42, 96]. Insulin induced hyperphosphorylation of 4E-BP1 and of S6K1, two targets of insulin action on mRNA translation in gastrocnemius of septic rats. Hyperphosphorylation of 4E-BP1 in response to insulin resulted in its dissociation from the inactive eIF4E. 4E-BP1 complexes. However, assembly of the active eIF4F complex as assessed by the association of eIF4E with eIF4G did not follow the pattern predicted by the increased availability of eIF4E secondary to enhanced phosphorylation of 4E-BP1. Indeed, sepsis caused a dramatic reduction in the amount of eIF4G associated with eIF4E in the presence or absence of insulin [96]. Thus the inability of insulin to stimulate protein synthesis during sepsis may be related to a defect in signaling to a step in translation initiation involved in assembly of an active eIF4F complex. In contrast to adults, plasma levels of insulin are increased, and glucose and amino acids decreased, suggesting the absence of insulin resistance in neonatal pigs [70, 71]. Furthermore, high rates of neonatal muscle protein synthesis remain largely maintained as long as adequate substrate supply is present during sustained endotoxemia (20h) [68]. Maintenance of an anabolic response to the feeding-induced rise in insulin likely exerts a protective effect for the neonate to the catabolic processes induced by endotoxin [69]. Hence there may be fundamental differences in the response of skeletal muscle from neonates compared with adults. Aside from insulin, growth hormone promotes nitrogen retention and improves nitrogen balance in a variety of catabolic conditions. Septic patients have inappropriately high growth hormone concentrations indicative of a severe growth hormone resistance. Growth hormone has a reduced effectiveness to limit protein catabolism in septic patients [20, 74]. More problematic is the association of growth hormone administration with an increased morbidity and mortality in critically ill patients [85]. Therefore, growth hormone administration may have limited usefulness in the treatment of septic patients. IGF-I is believed to mediate the anabolic action of growth hormone in muscle. Consequently IGF-I may be of more importance than growth hormone in improving nitrogen balance in skeletal muscle during sepsis. IGF-I is a circulating hormone synthesized

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predominantly by the liver. It shares structural and functional similarities with insulin, and like insulin, IGF-I plays a distinct role in the regulation of whole body protein metabolism. More importantly IGH-1 preferentially stimulates protein synthesis in skeletal muscle [6]. Likewise, intravenous infusion of IGF-I directly increases protein synthesis in skeletal muscle provided plasma amino acid concentrations are maintained in humans [32, 76]. The importance of IGF-1 in muscle protein metabolism is shown by the positive linear relationship between IGF-I and protein synthesis in skeletal muscle [51]. IGF-1 accelerates protein synthesis by stimulating PI3 kinase and enhancing S6k1 phosphorylation [22]. In addition, IGF-I promotes assembly of the translationally active eukaryotic initiation factor (eIF)4G·eIF4E complex. The increased assembly of eIF4G·eIF4E is associated with an enhanced eIF4G phosphorylation and increased availability of eIF4E. Enhanced availability of eIF4E occurs as a consequence of diminished abundance of the inactive 4E-BP1·eIF4E complex following IGF-I administration. The assembly of the 4EBP1·eIF4E complexes diminishes through an IGF-I-induced phosphorylation of 4E-BP1. Activation of the potential upstream regulators of 4E-BP1 and S6K1 phosphorylation via PKB and mTOR is also observed. In contrast, IGF-I has no effect on phosphorylation of elongation factor 2. Thus, the major impact of IGF-I in striated muscle takes place via stimulation of translation initiation rather than elongation [101]. Furthermore, the assembly of active eIF4G·eIF4E complex and activation of S6K1 mediates the stimulation of mRNA translation initiation by IGF-I partially through a PKB/mTOR signaling pathway. However, the IGF-I effect was only partially inhibited by rapamycin, indicating a non-mTOR mediated pathway exists for IGF-I [22]. The mTOR-independent pathway remains obscure. Systemically administered IGF-I results in weight gain in normal rats, reduces weight loss in during starvation [65] or diabetes [87], and attenuates protein loss during glucocorticoid-induced cachetic states [21, 86], pediatric burn patients [36], chronic sepsis [44, 90], acute peritonitis [37], and endotoxin administration [25]. In contrast to insulin [105], the plasma concentration of IGF-I is depressed during endotoxemia [28], cytokine infusion [27] or following infusion of growth hormone in septic patients [20]. Based on the responsiveness of skeletal muscle to IGF-I in vitro and the decreased plasma concentrations of IGF-I during severe trauma [116] and sepsis, alterations in the bioavailability of IGF-I would be expected to have profound effects on rates of protein synthesis in skeletal muscles. Whereas, neutralization of muscle IGF-I by the addition of IGF-I antibody to the incubation medium reduced protein synthesis an average of 22%, rates of protein degradation were not affected [30]. The neutralizing effects of anti-IGF-1 on protein synthesis can be overcome by elevating amino acids [30]. The IGF-I system is composed of the hormone as well as at least six different IGF binding proteins (IGFBP). IGFBPs carry the IGF-I in the blood and modulate its bioavailability, thereby either inhibiting or potentiating the interaction of IGF-I with its receptor. In this regard a common feature of catabolic conditions including sepsis is an elevation in the plasma IGFBP-1 and IGFBP-2 concentration [27, 28, 51]. Indeed, IGF-BP-1 concentrations are elevated more than fivefold 2 h after LPS injection, and thereafter levels gradually returned toward baseline. IGFBP-2 concentration also increased after LPS injection, but the maximal increase (approximately 50% above basal) is observed during the final 2 h of the protocol. In contrast, IGFBP-3 levels do not vary over the period examined in

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response to LPS [52]. An increase in the plasma IGFBP-1 concentration would be expected to sequester IGF-I lowering the effective IGF-I concentration in plasma of septic rats. Acute in vivo elevation in IGFBP-1, of the magnitude observed in various catabolic conditions, is capable of inhibiting protein synthesis in fast-twitch skeletal muscle and up-regulating the hepatic and renal syntheses of IGFBP-1 per se [53]. Similarly, IGFBP-1 inhibits IGF-Imediated protein synthesis by binding to IGF-I in human skeletal muscle cells in culture [31]. IGFBP-1, acting independently of IGF-I, inhibits protein degradation. The IGF-independent response occurs via beta1 integrin binding and stimulation of a rapamycin-sensitive signal transduction pathway. Hence, elevations in circulating and tissue levels of IGFBP-1 may be an important mediator for the muscle catabolism observed in various stress conditions. Unlike IGFBP-1, IGFBP-3 is reduced in critically ill humans, but similar reductions in plasma IGFBP-3 are not observed in rodent models of sepsis. Infusion of IL-1ra completely prevented the rise in IGFBP-1, but was without effect on plasma IGFBP-2 or IGFBP-3 concentrations [51]. Inclusion of IGF-I (1 or 10 nM) in the isolated perfused hindlimb or incubated muscles stimulated protein synthesis in gastrocnemius of septic rats 2.5-fold, and restored rates of protein synthesis to those observed in control rats [44]. The stimulation of protein synthesis did not result from an increase in the RNA content, but was correlated with an increase in the translational efficiency. The enhanced translational efficiency was accompanied by a 33% and 55% decrease in the abundance of free 40S and 60S ribosomal subunits, respectively, indicating IGF-I accelerated peptide-chain initiation relative to elongation/termination. These studies provide evidence that IGF-I can accelerate protein synthesis in gastrocnemius during chronic sepsis by reversing the sepsis-induced inhibition of peptide-chain initiation. A limitation to infusing free IGF-1 is its rapid elimination from the circulation. rhIGFI/rhIGFBP-3 (SomatoKine™) stimulates muscle protein synthesis in chronically semi-starved animals whereas IGF-I alone failed to increase protein synthesis during the same experimental conditions. This stimulation was because of increased translation initiation of translation, likely induced by more physiologic concentrations/kinetics of plasma IGF-I and amino acids following rhIGF-I/rhIGFBP-3 treatment, compared to IGF-I in its free form [82]. Enhancing the bioavailability of IGF-I through administration of IGF-I/GFBP-3 complex stimulates the rate of protein synthesis in gastrocnemius by enhancing the translational efficiency in vivo [82]. The delivery of rhIGF-I/rhIGFBP-3 does not inhibit endogenously produced IGF-1 restores plasma IGF-1 concentrations in face of continuing septic challenge.

SUMMARY Sepsis rudely unhinges nitrogen metabolism homeostasis and profoundly disturbs the integration of inter-organ cooperatively in overall nitrogen and energy economy of the host. The result of such dyshomeostasis is a nitrogen catabolic state, which seriously compromises recovery and renders the septic patient semi-refractory to current therapeutic modalities. These alterations lead to a functional redistribution of nitrogen (amino acids and proteins) and substrate metabolism among major body organs. The metabolic response to sepsis is a highly integrated, complex series of reactions that manifest itself as excessive urea nitrogen

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excretion. To understand the regulation of the host's response to sepsis, a comprehensive, integrated analysis of the fundamental physiological relationships of key metabolic pathways and mechanisms is essential. Skeletal muscles possess the body's largest pool of nitrogen. The catabolism of skeletal muscles during sepsis, which is manifested by acceleration in protein degradation and inhibition in protein synthesis, persists despite state-of-the-art nutritional care. Much effort has focused on the overall amount of nutrients given to septic patients in a hope to improve efficiencies in utilization and nitrogen economies, rather than support of specific end-organ targets. Elevating leucine concentrations or enhancing IGF-1 bioavailability show promise as potential therapeutic modalities to improve skeletal muscle nitrogen balance during sepsis. The rationale for these two compounds appears to have the ability to reverse the septic-induced reduction in formation of active eIF4G·eIF4E. Unlike other therapeutic modalities, these approaches have been shown to improve protein metabolism after initiation of the septic insult rather than treating prophylactically.

ACKNOWLEDGEMENTS This work was supported in part by a National Institute of Health General Medical Sciences Award GM39277.

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Thomas C. Vary Vary TC. IGF-I stimulates protein synthesis in skeletal muscle through multiple signaling pathways during sepsis. Am J Physiol Regul Integr Comp Physiol 290: R313-R321, 2006. Vary TC, Deiter G, and Kimball SR. Phosphorylation of eukaryotic initiation factor eIF2Be in skeletal muscle during sepsis. Am J Physiol Endocrinol Metabol 283: E1032-E1039, 2002. Vary TC, Deiter G, and Lang CH. Cytokine-triggered decreases in levels of phosphorylated eukaryotic initiation factor 4G in skeletal muscle during sepsis. Shock 26: 631-636, 2006. Vary TC, Jefferson LS, and Kimball SR. Amino acid-induced stimulation of translation initiation in rat skeletal muscle. Am J Physiol Endocrinol Metabol 277: E1077-E1086, 1999. Vary TC, Jefferson LS, and Kimball SR. Insulin fails to stimulate muscle protein synthesis in sepsis despite unimpaired signaling to 4E-BP1 and S6K1. Am J Physiol Endocrinol Metab 281: E1045-E1053, 2001. Vary TC, Jurasinski CV, Karinch AM, and Kimball SR. Regulation of eukaryotic initiation factor 2 expression during sepsis. Am J Physiol Endocrinol Metab) 266: E193-E201, 1994. Vary TC, Jurasinski CV, and Kimball SR. Reduced 40S initiation complex formation in skeletal muscle during sepsis. Mol Cell Biochem 178: 81-86, 1998. Vary TC and Kimball SR. Effect of sepsis on eIF4E availability in skeletal muscle. Am J Physiol Endocrinol Metabol 279: E1178-E1184, 2000. Vary TC and Kimball SR. Sepsis-induced changes in protein synthesis: differential effects on fast- and slow-twitch muscles.. Am J Physiol Cell Physiol 262: C1513C1519, 1992. Vary TC and Lang CH. IGF-I activates the eIF4F system in cardiac muscle in vivo. Mol Cell Biochem 272: 209-220, 2005. Vary TC and Lynch CJ. Meal feeding enhances formation of eIF4F in skeletal muscle: role of increased eIF4E availability and eIF4G phosphorylation. Am J Physiol Endocrinol Metabol 290: E631-642, 2006. Vary TC and Lynch CJ. Meal feeding stimulates phosphorylation of multiple effector proteins regulating protein synthetic processes in rat hearts. J Nutr 136: 2284-2290, 2006. Vary TC and Lynch CJ. Nutrient signaling components controlling protein synthesis in striated muscle. J Nutr 137: 1835-1843, 2007. Vary TC and Murphy JM. Role of extrasplanchnic organs in the metabolic response to sepsis: Effect of insulin. Circ Shock 29:: 41-57, 1989. Vary TC, Owens E, Beers JK, Verner K, and Cooney R. Sepsis inhibits synthesis of myofibrillar and sarcoplasmic proteins: Modulation by interleukin-1 receptor antagonist. Shock 6: 13-18, 1996. Vary TC and Siegel JH. Sepsis, abnormal metabolic control and the multiple organ failure syndrome. In: In Trauma: Emergency Surgery and Critical Care. edited by (ed) JH Siegel. New York, NY: Churchill Livingstone, 1987, p. 411-502.

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[108] Vary TC, Siegel JH, Tall DH, Morris JG, and Smith JA. Inhibition of skeletal muscle protein synthesis in septic intraabominal abscess. J Trauma 28: 981-988, 1988. [109] Vary TC, Voisin L, and Cooney RN. Regulation of peptide-chain initiation during sepsis by interleukin-1 receptor antagonist. Am J Physiol Endocrinol Metabol 271: E309-E316, 1996. [110] Voisin L, Gray K, Flowers KM, Kimball SR, Jefferson LS, and Vary TC. Altered expression of eukaryotic initiation factor 2B in skeletal muscle during sepsis. Am J Physiol Endocrinol Metabol 270: E43-E50, 1996. [111] Welsh GI, Miller CM, Loughlin AJ, Price NT, and Proud CG. Regulation of eukaryotic initiation factor eIF2B: glycogen synthase kinase-3 phosphorylates a conserved serine which undergoes dephosphorylation in response to insulin. FEBS Lett 421: 125-130, 1998. [112] Welsh GI and Proud CG. Glycogen synthase kinase-3 is rapidly inactivated in response to insulin and phosphorylates eukaryotic initiation factor eIF-2B. Biochem J 294: 625-629, 1993. [113] Welsh GI, Wilson C, and Proud CG. GSK3: a shaggy frog story. Trends in Cell Biology 6: 274-279, 1996. [114] Wilmore DW. Metabolic response to severe surgical illness: Overview. World J Surg 24: 705-711, 2000. [115] Windsor JA and Hill GL. Grip strength: a measure of the proportion of protein loss in surgical patients. Br J Surg 75: 880-882, 1988. [116] Wojnar MM, Fan J, Frost RA, Gelato MC, and Lang CH. Alterations in the insulinlike growth factor system in trauma patients. Am J Physiol Regul Comp Physiol 268: R970-R977, 1995.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter VI

PROTEIN SYNTHESIS IN HEPATOCYTES OF MICE AS REVEALED BY ELECTRON MICROSCOPIC RADIOAUTOGRAPHY Tetsuji Nagata Department of Anatomy and Cell Biology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan, and Department of Anatomy, Shinshu Institute of Alternative Medicine and Welfare, Nagano 380-0816, Japan

ABSTRACT For the purpose of studying the aging changes of protein synthesis in mouse hepatocytes, 20 groups of aging mice during development and senescence, each consisting of 3 individuals of both sexes, total 60, from fetal day 19 to postnatal day 1, 3, 9 and 14, month 1, 2 and 6, and year 1 and 2, were injected with RI-labeled amino acids, such as 3H-leucine, 3H-glycine, 3H-proline or 3H-hydroxyproline, which are the protein precursors, sacrificed 1 hr later and the liver tissues were fixed, sectioned and processed for electron microscopic radioautography. On electron microscopic radioautograms obtained from each animal, the localization of silver grains due to 3H-amino acids incorporations showing protein biosynthesis in respective cell organelles, the nucleus, Golgi apparatus, endoplasmic reticulum, mitochondrion and cytoplasmic matrix was qualitatively observed. On the other hand, the numbers of silver grains localizing over respective cell organelles were counted and analyzed quantitatively. The numbers of silver grains localized over the nuclei, Golgi apparatus, endoplasmic reticulum and cytoplasmic matrices increased from perinatal stages to the young adult stage at postnatal month 1, reaching the maximum, then decreased to year 2 due to aging and senescence. However, the number of silver grains localizing over the mitochondria, i. e. the number of labeled mitochondria per cell and the mitochondrial labeling index in each hepatocyte revealed that the numbers of mitochondria increased gradually from perinatal stages to the postnatal year 2, while the numbers of labeled mitochondria and the labeling indices of intramitochondrial protein syntheses in hepatocytes of mice at various ages increased

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Keywords: mitochondria, EM radioautography, protein syntheses, mouse hepatocytes, aging

1. INTRODUCTION Macromolecular synthesis such as nucleic acids (DNA and RNA), proteins, glucides or lipids in nuclei and cell bodies of various kinds of cells in various organs of experimental animals has been extensively studied since many years by both biochemical and morphological approaches [1-18]. Among of these studies, we first demonstrated the intranuclear and cytoplasmic nucleic acid syntheses, both DNA and RNA, in mammalian and avian cells morphologically by means of electron microscopic radioautography with accurate localization in cell organelles such as mitochondria, endoplasmic reticulum and Golgi apparatus in primary cultured cells of the livers and kidneys of mice and chickens in vitro [1, 2] as well as some other established cell lines such as HeLa cells [3-15] or mitochondrial fractions prepared from in vivo cells [5]. These phenomena were later commonly found in various cells and tissues not only in vitro cells obtained from various organs in vivo [16-24], but also in vivo cells of such various organs taken out from experimental animals as the salivary gland [25], the liver [26-43], the pancreas [44-45], the trachea [46], the kidney [47], the testis [48,49], the uterus [50-53], the spleen [54,55], the adrenal gland [56,57], the brain [58] and of mice and the eyes of chickens [59-63] and mice [64,65] in our laboratory. The relationship between the intramitochondrial DNA and RNA syntheses and cell cycle was formerly studied and it was clarified that the intramitochondrial DNA and RNA syntheses were performed without any nuclear involvement [5]. This paper reviews the relationship between the protein synthesis in hepatocyte nuclei and cytoplasm including cell organelles especially mitochondria and aging of mice in vivo at various ages by means of electron microscopic radioautography which was developed and carried out in our laboratory [1-65]. These studies supply additional data to the serial studies on special cytochemistry [66] and radioautographology [67].

2. RADIOAUTOGRAPHIC PROCEDURES Four groups of normal adult ddY strain mice, aged at postnatal month 1, each consisting of 3 litter mates, total 12, were housed under conventional conditions and bred with normal diet (mouse chow Clea EC2, Clea Co., Tokyo, Japan) with access to water ad libitum in our laboratory. The animals of 4 groups were injected with one of the protein precursors, 3Hglycine (Amersham, England, specific activity 1002 GBq/mM), 3H-leucine (Amersham, England, specific activity 1002 GBq/mM), 3H-tryptophane (Amersham, England, specific activity 877 GBq/mM), 3H-proline (Amersham, England, specific activity 877 GBq/mM) and 3 H-hydroxyproline (Amersham, England, specific activity 877 GBq/mM), at 9:00 a.m. simultaneously at a dosage of 370 KBq/gm body in saline. They were perfused at 10 a.m.,

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one hr. after the injections, via the left ventricles of the hearts with 0.1 M cacodylate-buffered 2.5% glutaraldehyde under Nembutal (Abbott Laboratories, Chicago, Ill., USA) anesthesia, then the liver tissues were taken out, cut into small tissue blocks, prefixed in 0.1 M cacodylate-buffered 2.5% glutaraldehyde, postfixed in buffered 1.0% osmium tetroxide, dehydrated, embedded in epoxy resin, sectioned and processed for electron microscopic radioautography according to the conventional wet-mounting procedure to demonstrate insoluble macromolecular compounds [67]. On the contrary, in order to demonstrate soluble small molecular compounds, some liver tissues were taken out, trimmed into small tissue blocks (1.0 x 0.5 x 0.5 mm) with two pieces of razor blades on a cold plate cooled to 0˚C immediately after the tissues were taken out and the tissue pieces were attached to small pieces of aluminum foils, 5 x 5 mm in size. The tissue pieces were quickly plunged into cooling agents (isopentane and propane mixture) at -161˚C cooled in quenching fluid (liquid nitrogen at -196˚C) for rapid freezing, then either freeze-dried at -80˚C, embedded in epoxy resin and dry-sectioned or cryo-sectioned with an LKB ultrotome 4800 equipped with an LKB cyrokit 14800 or LKB-NOVA (LKB, Bromma, Sweden) at -100˚C [68]. After the cryotechniques, all the frozen sections were processed for dry-mounting radioautography in order to demonstrate the soluble radiolabeled compounds [68]. Other normal ddY strain mice of 8 aging groups, each consisting of 6 litter mates of male animals, aged from fetal day 19 to postnatal day 1, 3, 9, and 14, month 1, 2 and 12, each group consisting of 3 litter mates respectively, total 48, were housed under conventional conditions and bred with normal diet (mouse chow Clea EC2, Clea Co., Tokyo, Japan) with access to water ad libitum in our laboratory. They were divided into 2 sub-groups, each 8 aging groups and administered with one of the 2 RI-labeled macromolecular precursors, 3H4,5-leucine (Amersham, England, specific activity 1002 GBq/mM) and 3H-proline (Amersham, England, specific activity 877 GBq/mM), at 9:00 a.m. simultaneously at a dosage of 370 KBq/gm body in saline. The animals were perfused at 10 a.m., one hr. after the injections, via the left ventricles of the hearts with 0.1 M cacodylate-buffered 2.5% glutaraldehyde under Nembutal (Abbott Laboratories, Chicago, Ill., USA) anesthesia, then the liver tissues were taken out, postfixed in buffered 1.0% osmium tetroxide, dehydrated, embedded in epoxy resin, sectioned and processed for electron microscopic radioautography. All the procedures used in this study concerning the animal experiments were in accordance with the guidelines of the animal research committee of Shinshu University School of Medicine as well as the principles of laboratory animal care in NIH publication No. 86-23 (revised 1985). For light microscopy, thick sections at 1 µm thickness from respective specimens were cut in sequence and processed for radioautography with Konica NR-M2 radioautographic emulsion (Konica, Tokyo, Japan) by a dipping method [19,21,42,64,65]. For electron microscopy, semithin sections at 0.2µm thickness were cut in sequence, collected on collodion coated copper grid meshes and coated with Konica NR-H2 radioautographic emulsion (Konica, Tokyo, Japan) by a wire-loop method [19, 20, 21, 42, 64,65]. The electron microscopic radioautograms were examined in either a Hitachi H-700 electron microscope (Hitachi, Tokyo, Japan) at an accelerating voltage of 200 kV or a JEOL JEM-4000EX electron microscope (JEOL, Tokyo, Japan) at accelerating voltages of 300-400 kV for observing thick specimens [42,64,65].

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For quantitative analysis of electron micrographs, twenty EM radioautograms showing cross sections of mononucleate hepatocytes from each group, based on the electron microscopic photographs taken after observation on at least 100 hepatocytes from respective animals, were analyzed to calculate the total number of mitochondria in each hepatocyte and the number of labeled mitochondria covered with silver grains by visual grain counting. On the other hand, the number of silver grains in 10 circles with the same area size as a mitochondrion outside cells was also calculated in respective specimens as background fog. The average number of silver grains per mitochondrial area was 0.01-0.03/area in the respective groups, which resulted in less than 1 silver grain per area. Therefore, the grain count in each specimen was not corrected with background fog. Thus, the mitochondrion that was labeled with more than one silver grain was defined as labeled. The data were stochastically analyzed using variance and Student's t-test. The differences were considered to be significant at P value <0.01 (n=20).

Figures 1. Electron microscopic radioautograms of hepatocytes of an adult mouse injected with 3Hleucine, fixed in buffered 2.5% glutaraldehyde and 1.0% osmium tetroxide, dehydrated, embedded in Epon, wet-sectioned and processed for wet-mounting radioautogtraphy, showing intracellular amino acid localization in the nuclei and cytoplasm. Several silver grains can be seen in the nucleus as well as in mitochondria and endoplaslmic reticulum showing protein synthesis. Figure 1E. Electron microscopic radioautograms of a hepatocyte of an adult mouse at postnatal month 1, injected with 3Hleucine. Many silver grains can be seen over the nucleus as well as in cell organelles such as mitochondria, endoplasmic reticulum and cytoplasmic matrix. x3.000. Figure 1F. Electron microscopic radioautogram of a sinusoidal endothelial cell of the same mouse as in Figure 1E. Several silver grains can be seen over the nucleus and the cell organelles. x 3,000. (Copyright permission from Urban& Fischer, Elsevier, Jena, Nagata T.: In, Progress in Histochemistry and Cytochemistry, Vol. 37, No.2, p. 57-228, 2002)

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3. INCORPORATIONS OF RI-LABELED AMINO ACIDS INTO MOUSE HEPATOCYTES We studied the incorporations of RI-labeled amino acids, 3H-glycine and 3H-leucine, into hepatocytes of mice by means of both cryo-sectioned freeze-dried and dry-mounting radioautography [68] or freeze-dried, dry-embedded, dry-sectioned and dry-mounting radioautography [69] and compared with the conventional chemically fixed, wet-embedded, wet-sectioned and wet-mounting radioautography [70]. The results demonstrated that the silver grains due to the soluble amino acids, both 3H-glycine and 3H-leucine, were detected diffusely in all the nuclei, nucleoli, endoplasmic reticulum, Golgi apparatus, mitochondria and cytoplasmic matrix in contrast that the silver grains due to the insoluble amino acids incorporated into macromolecules were less in numbers and localized in only some of the nuclei, nucleoli, endoplasmic reticulum, Golgi apparatus and mitochondria and not in the cytoplasmic matrix (Figure 1). Therefore, it was supposed that small molecular compounds such as 3H-glycine and 3H-leucine were localized diffusely in nuclei, cell organelles and cytoplasmic matrix before they were incorporated into macromolecules such as proteins in the nuclei or cell organelles [67, 68, 69, 70].

Figure 2. Electron microscopic radioautograms of hepatocytes of an adult mouse injected with 3Hproline, fixed in buffered 2.5% glutaraldehyde and 1.0% osmium tetroxide, dehydrated, embedded in Epon, wet-sectioned and processed for wet-mounting radioautogtraphy, showing intracellular amino acid localization in the nuclei and cytoplasm. Several silver grains can be seen in the nucleus as well as in mitochondria and endoplaslmic reticulum showing protein synthesis. x 3,000. Figure 2G. Electron microscopic radioautogram of a hepatocyte of an adult mouse at postnatal month 2. Several silver grains can be seen over the nucleus as well as in mitochondria and endoplasmic reticulum. x3,000. Figure 2H. Electron microscopic radioautogram of a sinusoidal endothelial cell of the same mouse as in Figure 1E. Several silver grains can be seen over the nucleus and the cell organelles. x 3,000. (Copyright permission from Urban& Fischer, Elsevier, Jena, Nagata T.: In, Progress in Histochemistry and Cytochemistry, Vol. 37, No.2, p. 57-228, 2002)

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Figure 3. Electron microscopic radioautograms of mononucleate hepatocytes of prenatal and postnatal newborn, juvenile and young mice, labeled with 3H-leucine showing protein synthesis. Figure 3A. Electron microscopic radioautogram of a mononucleate hepatocyte of a prenatal mouse aged at embryonic day 19, labeled with 3H-leucine showing protein synthesis. Several silver grains due to 3Hleucine can be seen in the nucleus especially over the euchromatin as well as over some mitochondria and endoplasmic reticulum in the cytoplasm. x10,000. Figure 3B. Electron microscopic radioautogram of a mononucleate hepatocyte of a newborn mouse aged at postnatal day 1, labeled with 3H-leucine. x5,000. Figure 3C. Electron microscopic radioautogram of a mononucleate hepatocyte of a suckling mouse aged at postnatal day 3, labeled with 3H-leucine. x6,000. Figure 3D. Electron microscopic radioautogram of a mononucleate hepatocyte of a weanling mouse aged at postnatal day 9, labeled with 3 H-leucine. x3,000. Figure 3E. Electron microscopic radioautogram of a mononucleate hepatocyte of a juvenile mouse aged at postnatal day 14, labeled with 3H-leucine. Note that two silver grains are observable over the mitochondrial membranes of the two mitochondria at right as well as a silver grain over the crista of the mitochondrion at upper left. x10,000. Figure 3F. Electron microscopic radioautogram of a mononucleate hepatocyte of a juvenile mouse aged at postnatal day 14, labeled with 3 H-leucine. An endothelial cell can be seen at left. x3,000. Figure 3G. Electron microscopic radioautogram of a mononucleate hepatocyte of an adult mouse aged at postnatal month 1, labeled with 3 H-leucine. x6,000. Figure 3H. High power magnification electron microscopic radioautogram of a mononucleate hepatocyte of a juvenile mouse aged at postnatal day 14, labeled with 3H-leucine. A few silver grains in a few mitochondria and endoplasmic reticulum are observable. Note that a silver grain in the mitochondrion at left is localized over the mitochondrial matrix. x15,000. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 6: p.1583-1595, 2006)

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4. PROTEIN SYNTHESIS IN MOUSE HEPATOCYTE NUCLEUS By observing light microscopic radioautograms, which were processed through the conventional chemical fixation, wet-embedding, wet-sectioning and wet-mounting radioautography after injections of 3H-glycine, 3H-leucine (Figure 1), 3H-tryptophane, 3Hproline (Figure 2), 3H-hydroxyproline and 3H-taurine the silver grains were found over both the karyoplasm and cytoplasm of almost all the cells, hepatocytes (Figures 1E, 2G), sinusoidal endothelial cells (Figure 1F), ductal epithelial cells, stellate cells of Kupffer (Figure 2H), Ito’s fat-storing cells in the hepatic lobules and fibroblasts in Glisson’s sheath as well as hematopoietic cells not only at the perinatal stages from embryo day 19 to postnatal day 1, 3, 9, 14, but also at the adult and senescent stages from postnatal month 1 to 2, 6, 12 and 24 except hematopoietic cells at senescent stage. Among of the respective cell types which constituted the liver tissues, the silver grains were mostly found in the hepatocytes at each stage. By observing electron microscopic radioautograms, which were processed for conventional wet-mounting radioautography, the silver grains were observed in most hepatocytes which contained one nucleus in one cell body at respective aging groups, which were designated as mononucleate hepatocytes (Figures 3, 4). In the mononucleate hepatocytes, silver grains localized not only over euchromatin and nucleoli in the nuclei but also over many cell organelles such as endoplasmic reticulum, ribosomes, Golgi apparatus and mitochondria as well as cytoplasmic matrices in respective aging groups from perinatal stage at embryonic day 19 (Figure 3A), postnatal newborn stage at day 1 (Figure 3B), suckling stage at day 3 (Figure 3C), weanling stage at day 9 (Figure 3D), juvenile stage at day 14 (Figure 3E, 3F, 3H), to young adult stages at postnatal month 1 (Figure 3G, 4A) and month 2 (Figure 4B, 4C), senile stage at month 6 (Figure 4D, 4E), to senescent stage at month 12 (Figure 4F) and month 24 (Figure 4G) as was formerly reported [52]. Anyway, these silver grains observed over the nuclei were mainly localized over euchromatin and less grains were observed over heterochromatin (Figures 3, 4). Some silver grains were also observed over the nucleoli (Figure 3A). They were disseminatedly localized over both the fibrillar zone (nucleolonema) and the granular zone (pars amorpha). These silver grains demonstrate protein synthesis incorporated into the nuclear proteins, both DNAbound proteins in the chromatin and RNA-bound proteins over the nucleoli. For quantitative analysis, we first studied the incorporations of 3H-leucine and 3Htryptophane in mouse hepatocytes in connection to the binuclearity before and after feeding [36]. The results showed that the incorporations of both amino acids were greater in binucleate hepatocytes than mononucleate. When 3H-leucine was injected into several groups of mice at various ages, silver grains were observed over the nuclei and cytoplasm of mononucleate and binucleate hepatocytes [36]. We counted the number of silver grains observed over the nuclei (karyoplasm) and the cell body (cytoplasm) including various cell organelles of 10 mononucleate hepatocytes taken from each animal at random after 3Hleucine labeling at several aging stages from embryo day 19 to postnatal day 1, 3, 14, month 1, 2, 6, 12 and 24 (year 2). The numbers of silver grains over cytoplasm were divided into 4 cell compartments, endoplasmic reticulum, Golgi apparatus, mitochondria and cytoplasmic matrix [33, 35]. From the results, it is clarified that numbers of silver grains (grain counts)

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were more in the cytoplasm than in the karyoplasm at respective aging stages and the grain counts increased from embryo day 19 to postnatal day 1, 3, 14 up to month 1, reaching the maxima, then decreased to month 2, 6, 12 and 24 [42, 43]. On the other hand, the grain counts were more in the cell body (cytoplasm) than in the nuclei (karyoplasm) at respective aging stages in case of 3H-proline and 3H-hydroxyproline labeling and the grain counts in the cell bodies increased from embryo day 19 to postnatal day 1, 3, 14 up to month 1, 2, 6, reaching the maxima, then decreased to month 12 and 24 in contrast that the grain counts in the nuclei increased from embryo day 19 to postnatal day 1, 3, 14 up to month 1, 2, reaching the maxima, then decreased to month 6, 12 and 24 [35, 42, 43].

5. PROTEIN SYNTHESIS IN MOUSE HEPATOCYTE CYTOPLASM The hepatocytes, either mononucleate or binucleate, showed silver grains localizing not only over euchromatin and nucleoli in the nuclei but also over many cell organelles such as endoplasmic reticulum, ribosomes, Golgi apparatus, mitochondria, peroxisomes and lysosomes demonstrating protein synthesis in cytoplasm. Among of these silver grains showing protein synthesis, it is generally accepted that such RI-labeled protein precursors as 3 H-labeled amino acids are incorporated into the endoplasmic reticulum where they are synthesized into macromolecular proteins, then transported to Golgi apparatus where some other compounds such as sugars are added changing to glycoproteins and transferred to other cell organelles as well as into cytoplasmic matrix. To the contrary, mitochondria contain their own mitochondrial DNA and RNA which synthesize mitochondrial proteins independently from the nuclei and other cell organelles [1, 2, 34, 36, 37, 38, 40, 41]. Therefore, the protein synthesis in hepatocyte cytoplasm should be described in 2 sections, cytoplasm containing most cell organelles and mitochondria, separately.

5.1. Protein Synthesis in Cell Organelles of Mouse Hepatocytes The hepatocytes of respective aging stages showed silver grains localizing not only over the nuclei in both chromatin and nucleoli but also over many cell organelles. From the results obtained after short term incubation with 3H-labeled amino acids for a few minutes to several and 10, 15, 30 minutes in vitro, it is generally accepted that such RI-labeled protein precursors as 3H-labeled amino acids are first incorporated into the endoplasmic reticulum within a few minutes where they are synthesized into macromolecular proteins, then transported to Golgi apparatus within 10 or 20 minutes where some other compounds such as sugars are added changing to glycoproteins and transferred to other cell organelles as well as into cytoplasmic matrix within 30 minutes [66, 67]. To the contrary, mitochondria contain their own mitochondrial DNA and RNA which can synthesize mitochondrial proteins independently from the nuclei and other cell organelles [66, 67, 71-86].

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Figure 4. Electron microscopic radioautograms of mononucleate hepatocytes of adult mice aged at postnatal month 1 to 24, labeled with 3H-leucine showing protein synthesis. Figure 4A. Electron microscopic radioautogram of a mononucleate hepatocyte of an adult mouse aged at postnatal month 1, labeled with 3H-leucine showing protein synthesis. Several silver grains due to 3H-leucine can be seen in the nucleus especially over the euchromatin as well as over some mitochondria and endoplasmic reticulum in the cytoplasm. x10,000. Figure 4B. Electron microscopic radioautogram of a mononucleate hepatocyte of an adult mouse aged at postnatal month 2, labeled with 3H-leucine. x5,000. Figure 4C. High power magnification electron microscopic radioautogram of a mononucleate hepatocyte of an adult mouse aged at postnatal month 2, labeled with 3H-leucine. Silver grains can be seen localizing over mitochondrial membranes of the 2 mitochondria at top as well as another mitochondrion at bottom left. x20,000. Figure 4D. Electron microscopic radioautogram of a mononucleate hepatocyte of an senile mouse aged at postnatal month 6, labeled with 3H-leucine. x3,000. Figure 4E. Electron microscopic radioautogram of a mononucleate hepatocyte of an senile mouse aged at postnatal month 6, labeled with 3H-leucine. x5,000. Figure 4F. Electron microscopic radioautogram of a mononucleate hepatocyte of a senescent mouse aged at postnatal month 12 (1 year), labeled with 3H-leucine. Less silver grains can be seen as compared with the younger animals. x3,000. Figure 4G. Electron microscopic radioautogram of a mononucleate hepatocyte of a senescent mouse aged at postnatal month 24 (2 years), labeled with 3H-leucine. Less silver grains can be seen as compared with the younger animals. x3,000. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 6: p.1583-1595, 2006)

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Quantitative analysis by grain counting in 10 mononucleate hepatocytes taken from each animal at random after 3H-leucine labeling in our previous studies [33, 34] revealed that the grain counts in respective cell compartments, were different each others at the same aging stage, respectively. The grain counts of endoplasmic reticulum were the most, those of mitochondria were the next, followed by Golgi apparatus, and cytoplasmic matrix the least [33]. On the other hand, in case of 3H-proline and 3H-hydroxyproline labeling, the silver grain counts were localized not only over such cell organelles as endoplasmic reticulum, Golgi apparatus, mitochondria, peroxisomes and lysosomes similarly to 3H-leucine labeling but also over extracellular matrices including collagen fibers suggesting the collagen synthesis incorporating 3H-proline and 3H-hydroxyproline [35]. Quantitative analysis revealed that the grain counts in endoplasmic reticulum increased from embryo day 19 to postnatal day 1, 3, 14 up to month 1, 2, 6, reaching the maxima, then decreased to month 12 and 24 in contrast that the grain counts in the mitochondria increased from embryo day 19 to postnatal day 1, 3, 14 up to month 1, reaching the maxima, then decreased to month 2, 6, 12 and 24 [33, 34, 35].

5.2. Protein Synthesis in Mitochondria of Mouse Hepatocytes As described above, when hepatocytes of mice at various ages were labeled with RIlabeled amino acids and observed by electron microscopic radioautography, it was found that almost all the hepatocytes were labeled with silver grains incorporating RI-labeled amino acids showing protein synthesis in their nuclei, cytoplasm and cell organelles. Among of the cell organelles, we analyzed mitochondria separately from other cell organelles because of the specificity of this cell organelle which synthesizes mitochondrial proteins by themselves independently from the nuclei [5, 66, 67]. Preliminary quantitative analysis on the number of mitochondria in 10 mononucleate hepatocytes whose nuclei were intensely labeled with many silver grains (more than 10 per nucleus) and other 10 mononucleate hepatocytes whose nuclei were not so intensely labeled (number of silver grains less than 9) in each aging group revealed that there was no significant difference between the number of mitochondria, number of labeled mitochondria and the labeling indices in both types of hepatocytes [43]. Thus, the numbers of mitochondria, the numbers of labeled mitochondria and the labeling indices were calculated in 10 mononucleate and 10 binucleate hepatocytes selected at random in each animal in respective aging stages, regardless whether their nuclei were very intensely labeled or not, except the prenatal stage at embryonic day 19, when no binucleate cell was found at this stage. The results obtained from the numbers of mitochondria in binucleate hepatocytes showed an increase from the postnatal days 1 (66.2/cell), to 3 (66.4/cell), 14 (81.8/cell), to postnatal months 1 (89.9/cell), 2 (95.1/cell), and 6 (102.1), reaching the maximum at month 12 (128.0/cell), then decreased to years 2 (93.9/cell) as shown in Figure 5. The increase and decrease were stochastically significant (P<0.01).

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Figure 5. Transitional curve demonstrating aging change of the total number of mitochondria per cell profile area in mononucleate hepatocytes labeled with 3H-leucine at respective aging groups from embryonic day 19 to postnatal month 24 (year 2), as expressed by mean ± standard deviation. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 6: p.1583-1595, 2006)

Figure 6. Transitional curve demonstrating aging change of the total number of mitochondria labeled with 3H-leucine showing protein synthesis per cell profile area in mononucleate hepatocytes at respective aging groups from embryonic day 19 to postnatal month 24 (year 2) as expressed by mean ± standard deviation. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 6: p.1583-1595, 2006)

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On the other hand, the results obtained from visual counting on the numbers of mitochondria labeled with silver grains from 10 mononucleate hepatocytes of each animal labeled with 3H-leucine demonstrating protein synthesis in 10 aging groups at postnatal day 1, 3, and 14, month 1, 6 and year 1 and 2, are plotted in Figure 6. The labeling indices in respective aging stages were calculated from the numbers of labeled mitochondria and the numbers of total mitochondria per cell which were plotted in Figure 7. The results showed that the numbers of labeled mitochondria with 3H-leucine showing protein synthesis increased from postnatal day 1 (7.3/cell) to day 3 (6.8/cell), 14 (10.2/cell), and month 1 (15.0/cell), 2 (15.9/cell), reaching the maximum at month 6 (19.6/cell), then decreased to year 1 (8.3/cell) and 2 (5.1/cell). On the other hand, the labeling indices increased from postnatal day 1 (11.8%) to 3 (10.2%), 14 (12.5%), month 1 (18.3%) and 2 (18.7%), reaching the maximum at month 6 (19.2/cell), then decreased to year 1 (6.4%) and 2 (5.5%). Stochastical analysis revealed that the increases and decreases of the numbers of labeled mitochondria as well as the labeling indices from the newborn stage to the adult and senescent stages were significant (P<0.01). Recently it was also clarified that there were no sexual difference between the numbers of mitochondria per cell, the number of labeled mitochondria with 3Hleucine and the labeling index of both male and female animals in respective aging stages as was formerly reported [88].

Figure 7. Transitional curve demonstrating aging change of the labeling index of mitochondria in mononucleate hepatocytes labeled with 3H-leucine showing protein synthesis (number of labeled mitochondria / number of total mitochondria) at respective aging groups from embryonic day 19 to postnatal month 24 (year 2) as expressed by mean ± standard deviation. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 6: p.15831595, 2006)

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5.3. Macromolecular Synthesis in Mitochondria of Binucleate Hepatocytes It is well known that some hepatocytes contained two nuclei in one cell body which were designated as binucleate hepatocytes [36-39, 87]. The binucleate hepatocytes were rarely found in the embryos at prenatal embryonic day 19, while they appeared at postnatal stages from postnatal newborn stage at day 1 (Figure 8A), suckling stage at day 3 (Figure 8B), weanling stage at day 9 (Figure 8C, 8D), juvenile stage at day 14 (Figure 8E), young adult stage at month 1 (Figure 8F) and month 2 (Figure 9A), 6 (Figure 8), 12 (Figures 9, 10), and 24 (Figures 11, 12). The numbers of binucleate hepatocytes increased from newborn stages to juvenile, adult and senescent stages as was previously reported [53]. Some of them contained two nuclei of equal size showing that their two nuclei were sectioned at their centers (Figures 1B, 1C, 1E, 1F, 2C). Other hepatocytes contained two nuclei of unequal size in one cell body, a large and a small, showing that their nuclei were not sectioned at their centers, due to the axes of cutting sections (Figures 1A, 1D, 2A, 2B, 2D, 2E, 2F). Some of them contained two nuclei separately (Figures 1A, 1D, 2A, 2B, 2C, 2D, 2E, 2F), while some of them contained two nuclei in contact with each others (Figures 1A, 1B, 1C, 1E, 1F). In adult and senescent stages, it is well known that considerable numbers of binucleate hepatocytes appear [36-39, 87]. They were supposed to be due to amitotic nuclear divisions without any cytoplasmic divisions [38, 39]. We formerly observed that the quantity of DNA and RNA synthesis as expressed by grain counting in karyoplasm and cytoplasm of both mononucleate and binucleate cells in mouse hepatocytes showed increases and decreases reaching the maxima at postnatal month 2 in case of mononucleate cell and at month 6 in case of binucleate karyoplasm and cytoplasm [36-39, 87]. It was noted that the differences of grain counts between the mononucleate and binucleate cells in the same aging groups were stochastically significant. These results indicated that the amount of DNA and RNA synthesized and distributed in karyoplasm and cytoplasm of each binucleate cell was much more than each mononucleate cell in respective aging groups [36-39, 87]. With regards to the protein synthesis, we also analyzed the number of mitochondria per cell, the number of labeled mitochondria with 3H-leucine per cell and the labeling index demonstrating protein synthesis in binucleate hepatocytes at respective aging stages from postnatal day 1 to month 24 (year 2). The results showed that the number of mitochondria per cell increased from postnatal day 1 to year 1, reaching the maximum, and decreased to year 2 (Figure 10), while the number of labeled mitochondria per cell increased from postnatal day 1 to month 6, reaching the maximum, and decreased to year 1 and 2 (Figure 11), and the labeling index also increased from postnatal day 1 to month 6, reaching the maximum, and decreased to year 1 and 2 (Figure 12).

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Figure 8. Electron microscopic radioautograms of binucleate hepatocytes of postnatal newborn, juvenile and young mice, labeled with 3H-leucine showing protein synthesis. Figure 8A. Electron microscopic radioautogram of a binucleate hepatocyte of a newborn mouse aged at postnatal day 1, labeled with 3Hleucine. Note that several silver grains are observable over the mitochondrial membranes and crista of several mitochondria at right. x5,000. Figure 8B. Electron microscopic radioautogram of a binucleate hepatocyte of a suckling mouse aged at postnatal day 3, labeled with 3H-leucine. Note that a few silver grains are observable over the mitochondrial membranes and crista of a few mitochondria at right bottom. x5,000. Figure 8C. Electron microscopic radioautogram of a binucleate hepatocyte of a weanling mouse aged at postnatal day 9, labeled with 3H-leucine. Note that the paired nuclei are contacting each other and a few silver grains are observable over a few mitochondria at top left. x5,000. Figure 8D. Electron microscopic radioautogram of a binucleate hepatocyte of a weanling mouse aged at postnatal day 9, labeled with 3H-leucine. Note that the paired nuclei are separated. x3,000. Figure 8E. Electron microscopic radioautogram of a binucleate hepatocyte of a juvenile mouse aged at postnatal day 14, labeled with 3H-leucine. Note that the paired nuclei are contacting each other. x5,000. Figure 8F. Electron microscopic radioautogram of a binucleate hepatocyte of a young mouse aged at postnatal day 30, labeled with 3H-leucine. An endothelial cell can be seen at right. x5,000. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 7: p.1008-1023, 2007)

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Figure 9. Electron microscopic radioautograms of binucleate hepatocytes of adult mice aged at postnatal month 2 to 24, labeled with 3H-leucine showing protein synthesis. Figure 9A. Electron microscopic radioautogram of a binucleate hepatocyte of an adult mouse aged at postnatal month 2, labeled with 3H-leucine showing protein synthesis. Many silver grains due to 3H-leucine can be seen in the 2 nuclei especially over the euchromatin as well as over many mitochondria throughout the cytoplasm. x5,000. Figure 9B. Electron microscopic radioautogram of a binucleate hepatocyte of an old adult mouse aged at postnatal month 6, labeled with 3H-leucine. Note that the paired nuclei are separated each other and several silver grains are observable over several mitochondria x5,000. Figure 9C. Electron microscopic radioautogram of a binucleate hepatocyte of a senile mouse aged at postnatal month 12 (1 year), labeled with 3H-leucine. Only a few silver grains can be seen localizing over mitochondrial membranes of the 3 mitochondria at top right and left. x5,000. Figure 9D. Electron microscopic radioautogram of a binucleate hepatocyte of a senile mouse aged at postnatal month 12 (1 year), labeled with 3H-leucine. Note that several silver grains can be seen over several mitochondria at bottom right and left. x5,000. Figure 9E. Electron microscopic radioautogram of a binucleate hepatocyte of an senile mouse aged at postnatal month 24 (2 years), labeled with 3H-leucine. Note that no silver grain can be observed over any mitochondria x5,000. Figure 9F. Electron microscopic radioautogram of a binucleate hepatocyte of a senescent mouse aged at postnatal month 24 (2 years), labeled with 3H-leucine. Note that only a few silver grains are observable over a few mitohchondria at bottom right. Less silver grains can be seen as compared with the younger animals. x5,000. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 7: p.1008-1023, 2007)

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Figure 10. Histogram demonstrating aging change of the total number of mitochondria per cell profile area in binucleate hepatocytes labeled with 3H-leucine at respective aging groups from postnatal day 1 to postnatal month 24 (year 2) as expressed by mean ± standard deviation. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 7: p.10081023, 2007)

Figure 11. Histogram demonstrating aging change of the total number of mitochondria labeled with 3Hleucine showing protein synthesis per cell profile area in binucleate hepatocytes at respective aging groups from postnatal day 1 to postnatal month 24 (year 2) as expressed by mean ± standard deviation. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 7: p.1008-1023, 2007)

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Figure 12. Histogram demonstrating aging change of the labeling index of mitochondria in binucleate hepatocytes labeled with 3H-leucine showing protein synthesis (number of labeled mitochondria / number of total mitochondria) at respective aging groups from postnatal day 1 to postnatal month 24 (year 2) as expressed by mean ± standard deviation. (Copyright permission from The Scientific World Ltd, Newbury, U.K., Nagata T.: In, The Scientific World Journal Vol. 7: p.1008-1023, 2007)

Comparing these results from binucleate hepatocytes with the results from mononucleate hepatocytes, it is obvious that the numbers of mitochondria and the numbers of labeled mitochondria per cell were more in binucleate hepatocytes than mononucleate hepatocytes at respective aging stages in contrast that the labeling indices were higher in mononucleate hepatocytes than binucleate hepatocytes at respective aging stages. These results indicate that binucleate hepatocytes contain more mitochondria than mononucleate hepatocytes and more mitochondria synthesize protein in each binucleate hepatocytes than mononucleate at various aging stages. However, the percentages of mitochondria synthesizing proteins at respective aging stages were lower in binucleate hepatocytes than mononucleate. Considering these results, it is supposed that some differences may exist between the mitochondrial protein synthesis of mononucleate and binucleate hepatocytes as was observed in DNA and RNA syntheses. There is a possibility that even though the number of mitochondria in each binucleate hepatocyte is more than each mononucleate hepatocytes but the activity of protein synthesis of respective mitochondria in binucleate hepatocytes is less than those of mononucleate hepatocytes. Anyway, the results obtained from the liver at present should form a part of special radioautographology [66], i.e., application of radioautography to the liver, as well as a part of special cytochemistry [67], as was recently reviewed by the present author. We expect that such special radioautographology and special cytochemistry should be further developed in all the organs in all the organ systems of experimental animals in the future. From the results obtained at present, it was concluded that almost all the hepatocytes of mice at various ages, from prenatal embryos to postnatal newborn, juvenile, young adult and

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senescent animals, were labeled with silver grains showing protein synthesis with 3H-leucine as well as other amino acids in their mitochondria. Quantitative analysis on the numbers of mitochondria in mononucleate hepatocytes resulted in an increase from the prenatal day to postnatal month 1, 2, 6, reaching the maximum at postnatal month 6, then decreased to year 2. The numbers of labeled mitochondria with 3H-leucine showing protein synthesis increased from prenatal days to postnatal days, reaching the maximum at postnatal month 1, then decreased to year 2, while the labeling indices increased from prenatal stage to postnatal stages, reaching the maximum at postnatal day 14, then decreased to year 2, to the contrary that the numbers of mitochondria in binucleate hepatocytes increased from the perinatal days to postnatal month 1, 2, 6 and 12, reaching the maximum at postnatal month 12 (year 1), then decreased to year 2. while the numbers of labeled mitochondria with 3H-leucine in binucleate hepatocytes increased from perinatal days to postnatal month 1, 2, reaching the maxima at postnatal month 6, then decreased to postnatal year 2, and the labeling indices increased from perinatal days to postnatal month 1, 2, reaching the maxima at postnatal month 6, then decreased to postnatal year 2.

6. MACROMOLECULAR SYNTHESIS IN VARIOUS CELLS Concerning to the macromolecular synthesis in various cells in various organs of experimental animals observed by light and electron microscopic radioautography, it is well known that the silver grains due to the radiolabeled precursor such as 3H-thymidine, 3Huridine and 3H-leucine, demonstrate DNA, RNA and protein syntheses, respectively [5, 6, 22, 23, 24, 36, 37, 38, 66, 67]. The present results obtained from the livers of aging mice revealed that the incorporation of 3H-leucine indicating protein synthesis resulted in silver grain localization over the nuclei and cell bodies of almost all mononucleate hepatocytes from perinatal animals at embryonic day 19, postnatal day 1, 2, 9, 14 to adult and senescent stages at postnatal month 1, 2, 6, 12 and 24, which showed the localization of newly synthesized proteins in the nuclei and the cytoplasmic cell organelles including mitochondria. From the results obtained at present, the numbers of mitochondria in respective hepatocytes showed increases and decreases reaching the maxima at postnatal month 6, while the numbers of labeled mitochondria with silver grains due to 3H-leucine incorporation demonstrating intramitochondrial protein synthesis also showed increases and decreases reaching the maximum at postnatal month 1, and the labeling indices of mitochondria labeled with 3H-leucine showed increases and decreases reaching the maximum at postnatal day 14. These results revealed that the nucleic acid syntheses, both DNA and RNA precede the protein synthesis in mitochondria of various cells.

6.1. Protein Synthesis in Mitochondria of Various Cells With regards to protein synthesis in mitochondria in animal cells or plastids in plant cells, many studies have recently been reported in various cells of some plants [71-73, 76-79]

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or several kinds of animals such as chick [74, 75], hamster [79], catfish [80] and rat [81], or human patients [77-79] by various approaches. Most of these authors observed mitochondrial protein synthesis in various cells by means of biochemical procedures. They supposed that the proteins detected in the mitochondria of these cells were synthesized in cytoplasmic cell organelles such as endoplasmic reticulum and moved into mitochondria, especially mitochondrial matrices. However, no evidence showing protein synthesis in mitochondria or plastids of any kind of cells, either plants or animals, has been demonstrated in situ by morphological methods except only several papers published from our laboratory [5, 33-37, 54, 55, 65-67]. Among of these studies, we first demonstrated that the numbers of mitochondria and the numbers of labeled mitochondria incorporating 3H-leucine in mouse hepatocytes increased from prenatal stage to postnatal adult stage at month 1, but the labeling indices did not show any significant increase [33-37, 66, 67]. In the our recent studies, it was clearly demonstrated that the numbers of mitochondria, the numbers of labeled mitochondria with 3H-leucine and the labeling indices of mouse hepatocytes showed significant increases and decreases from perinatal stage to adult and senescent stages. These studies showing the silver grain localization in the mitochondria of mouse hepatocytes incorporating 3H-leucine as observed by electron microscopic radioautography should be the first report demonstrating the protein synthesis in the mitochondria of animal cells in situ in connection to the animal aging from perinatal stages to postnatal adult and senescent stages as studied systematically. It should be worthy of notice that the silver grains localized over the mitochondrial membranes, cristae and matrices of all hepatocytes at various ages. The results indicated that the protein synthesis as shown by 3H-leucine incorporations demonstrated the synthesis of structural proteins in the mitochondrial membranes, cristae and matrices.

6.2. Nucleic Acid Synthesis in Mitochondria of Various Cells As for the macromolecular synthesis in various cells in various organs of experimental animals observed by electron microscopic radioautography, it is well known that the silver grains due to radiolabeled 3H-thymidine demonstrate DNA synthesis [1-9, 19-32, 34, 36-38, 40, 46-50, 52, 56, 58-60, 62-64, 66, 67], while 3H-uridine demonstrates RNA synthesis [116, 19-24, 27-29, 34, 36-38, 41, 66, 67] and 3H-leucine protein synthesis [14, 16, 19, 20-24, 33-37, 39, 45, 48, 49, 51, 52-55, 65-67]. The previous studies obtained from the livers of aging mice revealed that silver grains incorporating either 3H-thymidine or 3H-uridine were observed not only over the nuclei of some hepatocytes but also over the mitochondria showing intramitochondrial DNA and RNA synthesis [30-32, 34, 36-38, 40, 41, 44, 66, 67]. With regards to the incorporations of 3H-thymidine or 3H-uridine into mitochondria demonstrating DNA or RNA syntheses, many authors previously reported that DNA synthesis was observed by means of electron microscopic radioautography in lower organism such as slime mold [71, 72], tetrahymena [73, 94] or chicken fibroblasts in tissue culture under abnormal conditions [74, 75] or liver and kidney cells of chicken and mouse under normal conditions [5] as was formerly reviewed [80, 81]. Likewise, RNA synthesis in Agaricus [78], Ochromonas [79], chicken liver [80, 81], mouse liver [82], rat adrenal cortex [83] and human cells [5-16] were also demonstrated. Most of these authors, however, used

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old-fashioned developers consisting of methol and hydroquinone (MQ-developer) which produced coarse spiral silver grains resulting in inaccurate localization over cell organelles, especially mitochondria, when observed by electron microscopy. Thus, most of these authors, except Nagata et al. [7-13], showed photographs of electron radioautograms with large spiralformed silver grains (2-3 m in diameter) localizing not only over the mitochondria but also outside the mitochondria. In order to obtain smaller silver grains, we first used elon-ascorbic acid developer after gold latensification [7-13], which produced comma-shaped smaller silver grains (0.3-0.8 m in diameter) much better for localization over mitochondria than spiral silver grains (2-3 m in diameter), then later we used phenidon developer after gold latensification, producing dot-like smaller silver grains (0.2-0.3 m in diameter) localizing only inside the mitochondria showing ultrahigh resolution of radioautograms [1-8, 19-32, 34, 36-38, 40, 41, 66, 67, 93] as shown in Figures 1, 2, 3, 4, 8 and 9 in this article. Thus, those papers from our laboratory were the first which demonstrated intramitochondrial DNA, RNA and protein syntheses incorporating 3H-thymidine, 3H-uridine and 3H-leucine, respectively, with accurate intramitochondrial localization in avian and mammalian cells in 1960s-1970s [1-14]. Concerning to the resolution of electron microscopic radioautography, on the other hand, several authors discussed the sizes of silver grains under various experimental conditions and calculated various values of resolutions [16, 88-91]. Those authors who used the M-Q developers maintained the resolution to be 100-160 nm [98-91], while those authors who used the elon-ascorbic acid developer [8-10,92] calculated it to be 25-50 nm. When we used phenidon developer at 16˚C for 1 min after gold latensification, we could produce very fine dot-shaped silver grains and obtained the resolution around 25 nm [16, 22-24, 66, 67]. For the purpose of analyzing electron radioautographs, Salpeter et al. [90] suggested to use the half-distance and proposed to use very complicated calculations through which respective coarse spiral-shaped silver grains were judged to be attributable to the radioactive source in a certain territory within a resolution boundary circle. However, since we used phenidon developer after gold latensification to produce very fine dot-shaped silver grains, we judged only the silver grains which were located in the mitochondria which were dot-shaped very fine ones to be attributable to the mitochondria without any problem with the resolution around 25 nm as was formerly discussed [5-8]. As for the section thickness, we used thicker semithin sections at 0.2 m thickness which did not effect the HD value of this experiment since we used tritium as RI which emitted beta rays with very low energy having very short range as 0.2 m in the emulsions. Thus, the numbers of labeled mitochondria as well as the labeling indices which were calculated from the results obtained from the numbers of mitochondria over which the silver grains really existed without adding any hypothetical silver grains which should be less than 10% (only several %) if added under the experimental conditions that we carried out in this experiment. On the other hand, the incorporations of 3H-thymidine into mitochondria demonstrating DNA synthesis were formerly observed by means of electron microscopic radioautography not only in lower organisms such as slime mold [80, 81], tetrahymena [73] but also in higher animals such as chicken fibroblasts in tissue culture under abnormal conditions [82, 83] or liver and kidney cells of chicken and mouse under normal conditions [5, 6, 95]. We also demonstrated intramitochondrial DNA synthesis incorporating 3H-thymidine or RNA synthesis incorporating 3H-uridine in some other established cell lines originated from human

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being such as HeLa cells [5-10] or mitochondrial fractions prepared from in vivo mammalian cells such as rat and mouse [5]. It was later commonly found in various cells and tissues in vitro obtained from various organs such as the cultured human uterus cancer cells HeLa [6,11, 13], cultured rat sarcoma cells [19], mouse liver and pancreas cells in vitro [9,12], but also in vivo cells obtained from various organs such as the salivary gland [25], the liver [2643], the pancreas [44, 45], the trachea [46], the kidney [47], the testis [48, 49], the uterus [5053], the spleen [54, 55] the adrenal gland [56, 57], the brain [58] and the eyes [59-64] of chickens and mice. Thus, it is clear that all the cells in various organs of various animals synthesize DNA and RNA not only in their nuclei but also in their mitochondria. The relationship between the cell cycle and the intramitochondrial DNA as well as RNA syntheses was formerly studied in synchronized cells and it was clarified that both the intramitochondrial DNA and RNA syntheses were performed without any nuclear involvement [5]. However, the relationship between the aging of individual animals and the DNA and RNA syntheses has not yet been clarified except a few papers recently published by Korr and associates on mouse brain [96-98]. They reported both nuclear DNA repair, measured as nuclear unscheduled DNA synthesis, and cytoplasmic DNA synthesis labeled with 3H-thymidine in several types of cells in brains such as pyramidal cells, Purkinje cells, granular cells, glial cells, endothelial cells, ependymal cells, epithelial cells as observed by only light microscopic radioautography using paraffin sections. They observed silver grains over cytoplasm of these cells by light microscopy and maintained that it was reasonable to interpret these labeling as 3H-DNA outside the nuclei, which theoretically belonged to mitochondrial DNA without observing the mitochondria by electron microscopy. From the results, they concluded that distinct types of neuronal cells showed a decline of both unscheduled DNA and mitochondrial DNA syntheses with age in contrast that other cell types, glial and endothelial cells, did not show such age-related changes without counting the number of mitochondria in respective cells neither counting the number of labeled mitochondria nor calculating the labeling indices of mitochondria at respective aging stages. Thus, their results from the statistics obtained from the cytoplasmic grain counting seems to be not accurate without observing mitochondria directly by electron microscopy. To the contrary, we first showed the relationship between the DNA synthesis and aging in hepatocytes of mice in vivo at various ages by means of electron microscopic radioautography observing the small dot-like silver grains, due to incorporations of 3Hthymidine, which were developed with phenidon developer after gold latensification exactly localized inside the mitochondria [1, 2, 5, 7-9, 32, 34]. We demonstrated that increases and decreases were observed in the mitochondrial numbers and the numbers of labeled mitochondria as well as labeling indices of DNA synthesis with 3H-thymidine incorporations by direct observation on mitochondria at electron microscopic level. Likewise, we also demonstrated that increases and decreases were observed by direct observation on mitochondria at electron microscopic level and obtaining accurate mitochondrial number and labeling indices labeled with 3H-uridine [1, 3, 5-11, 36, 37]. Thus, our previous papers [3337, 66, 67] should be the first to show the relationship between the protein synthesis and aging in hepatocytes of mice in vivo at various ages from prenatal to postnatal juvenile, young adult and senescent stages by means of electron microscopic radioautography observing the small dot-like silver grains, due to incorporations of 3H-leucine, which exactly

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localized inside the mitochondria. It was recently reported that the macromolecular syntheses in hepatocytes of both male and female mice in aging, were not significanlty different between the both sexes [88, 99, 100].

8. CONCLUDING REMARKS From the results obtained in the hepatocytes of aging mice, it is concluded that almost all the hepatocytes of male and female mice at various ages, from newborn at postnatal day 1 to juvenile day 14, young adult at month 1, 2, 6 and senescent at year 1 and 2, were labeled with silver grains showing protein synthesis incorporating 3H-glycine, 3H-leucine and 3H-proline in their nuclei and cytoplasm especially in mitochondria. Quantitative analysis on the numbers of mitochondria in mononucleate hepatocytes resulted in an increase from the perinatal days to postnatal month 1, 2, 6, reaching the maximum at postnatal month 6, then decreased to year 1 and 2, while in binucleate hepatocytes the numbers of mitochondria increased from the perinatal days to postnatal month 1, 2, 6 and 12, reaching the maximum at postnatal month 12 (year 1), then decreased to year 2. On the other hand, the numbers of labeled mitochondria with 3H-leucine in mononucleate hepatocytes increased from perinatal days to postnatal days, reaching the maxima at postnatal month 1, then decreased to postnatal year 2, while the labeling indices increased from perinatal days to postnatal day 14, reaching the maxima then decreased to postnatal year 2. To the contrary, the numbers of labeled mitochondria with 3H-leucine in binucleate hepatocytes increased from perinatal days to postnatal month 1, 2, reaching the maxima at postnatal month 6, then decreased to postnatal year 2, while the labeling indices increased from perinatal days to postnatal month 1, 2, reaching the maxima at postnatal month 6, then decreased to postnatal year 2. These results indicate that mitochondria in hepatocytes synthesize proteins independently from the nuclei and cytoplasm of hepatocytes, but their synthetic activities are affected from the aging of the animals. Thus, the results obtained from the livers of mice in aging should form a part of special radioautographology [65], i.e., application of radioautography to the liver, as well as a part of special cytochemistry [64], as was recently reviewed by the present author. We expect that such special radioautographology and special cytochemistry should be further developed in all the organs in the future.

ACKNOWLEDGMENTS This study was supported in part by Grants-in-Aids for Scientific Research from the Japan Society for Promotion of Sciences (No. 18924034, No. 19924024 and No. 20929003). The author is also grateful to Dr. Kiyokazu Kametani, Research Center for Instrumental Analysis, Shinshu University, Matsumoto, for his technical assistance during the course of this study.

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[64] Kong Y, Nagata T. (1994). Electron microscopic radioautographic study on nucleic acid synthesis of perinatal mouse retina. Med Electron Microsc 27: 366-368. [65] Cui H, Gao F, Nagata T. (2000). Light microscopic radioautographic study on protein synthesis in perinatal mice corneas. Acta Histochem Cytochem 33: 31-37. [66] Nagata T. (2001). Special Cytochemistry in Cell Biology. Internat. Rev. Cytol., Jeon KW, ed., Academic Press, New York, Vol 211: pp. 33-151. [67] Nagata T. (2002). Radioautographology General and Special, Prog Histochem Cytochem. Graumann W ed. Urban & Fischer, Jena, Vol 37 No 2 : pp. 57-226. [68] Nagata T, Murata F. (1977). Electron microscopic dry-mounting radioautography for diffusible compounds by means of ultracryomicrotomy. Histochemistry 54: 75-82. [69] Nagata T, Ohno S, Murata F. (1977). Electron microscopic dry-mounting radioautography for soluble compounds. Acta Pharmacol. Toxicol. 41: 63-64. [70] Nagata T. (1994). Electron microscopic radioautographology with cryo-fixation and dry-mounting procedure. Acta Histochem Cytochem. 27: 471-489. [71] Guttes E, Guttes S. (1964). Thymidine incorporation by mitochondria in Physarum polycephalum. Science 145:1057-1058. [72] Schuster FL. (1965). A deoxyribose nucleic acid component in mitochondria of Didymium nigirpes, a slime mold. Exp Cell Res 39: 329-345. [73] Stone GE, Miller OL Jr. (1965). A stable mitochondrial DNA in Tetrahymena pyriformis. Exp Zool 159: 33-37. [74] Chévremont M. (1963). Cytoplasmic deoxyribonucleic acids: Their mitochondrial localization and synthesis in somatic cells under experimental conditions and during the normal cell cycle in relation to the preparation for mitosis. Cell Growth and Cell Division. Symposia of the Internat Soc for Cell Biol. Harris RJC ed. Academic Press, New York, Vol. 2: pp. 323-333. [75] Meyer RR. (1966). Cytochemical and electron microscopic studies of mitochondrial DNA in cultured chick fibroblasts grown at subnormal temperature. J Cell Biol 31: 151-152. [76] Schatz G. (1970). Biogenesis of mitochondria. Membranes of Mitochondria and Chloroplasts. Racker E, ed. Van Nostrand-Reinhold, New York, pp. 251-314. [77] Tandler B, Hoppel CL. (1972). Mitochondria, Ultrastructure of Cells and Organisms, Locke M ed. Academic Press, New York and London, pp. 1-59. [78] Vogel FS, Kemper L. (1967). Intrinsic ribonucleic acid synthesis in mitochondria of Agaricus campestris underscoring the probability of an extra-nuclear genetic system. Exp Cell Res 47: 209-201. [79] Gibbs SP. (1968). Autoradiographic evidence for the in situ synthesis of chloroplast and mitochondrial RNA. J Cell Sci 81: 227-228. [80] André J. (1968). Donneés récentes sur la physiologie des mitochondries. C R Soc Biol 162: 7-12. [81] André J, Marinozzi V. (1965). Présence dans les mitochondries de particules ressemblant aux ribosomes. J Microsc Paris 4: 615-626. [82] Curgy J J. (1968). Synthese d’ARN in vivo par les mitochondries du foie de poussin et du souriceau. Etude autoradiographique au microscope électronique. J Microscop 7: 849-864.

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In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter VII

RECENT ADVANCES IN LABEL-FREE BIOSENSORS APPLICATIONS IN PROTEIN BIOSYNTHESIS AND HTS SCREENING Shawn O’Malley Corning Incorporated, Biochemical Technologies, Corning, NY 14831, USA

ABSTRACT The enzymatic maintenance of biopolymeric structures within a cell is widely known to play a critical role in the regulation of numerous bio-processes from activation, cell signaling and metabolic pathways. This chapter examines the recent advances in labelfree biosensing and describes how these technologies have been used to examine protein biosynthesis and protein degradation. Label free biosensing has matured through the years into a powerful technique for examining these processes with quantitative metrology. The emergence of imaging tools with microarray technology in these label free platforms will greatly expand the throughput of these assays thus enabling the user to study globally bio-synthetic reactions. Label-free functional enzymatic biosensor assays have recently been applied toward the development of a new generation of protein biosynthesis assays. Label-free biosensors enable the study of real time biosynthetic and biodegradation reactions while maintaining an open format for exploring modulation factors. When these surface based synthetic and degradation assays are applied in high throughput platforms they provide yet a new screening tool for drug discovery.

INTRODUCTION Biosensors can be broadly defined as any detection system containing a biological or chemical signal relaying component coupled to a signal transducer. In some cases, the biological or chemical sensing agent is tethered to or located on the surface of the signal transducer. Many good reference books on the field have been written on the history and

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broadest diversity of the field of biosensors (see Biosensor: Theory and application Donald G. Buerk [1], Fiber optic chemical sensors and biosensors. Otto Wolfbeis [2]). The term label-free biosensing refers to that special case of biosensing wherein the detection of the chemical agent or biological (interaction/agent) by the transducer does not rely on dyes, enzymes or radiolabels. The label free detection field as a whole has been undergoing four major technical trends in recent years. First, label free detection methods have expanded into high throughput screening platforms. The second major trend has been in the development of newer optical and non-optically based label free signal transducer detection schemes. Many of these newer signal transducer schemes were enabled through advances in nanofabrication techniques. The third major trend has been the integration of the label free biosensors with other detection formats yielding the area of multi-modal detection. The forth major trend has been the expansion in the variety of applications for label free detection. Many of the traditional biosensing applications are now expanding beyond affinity based and molecular kinetic analysis (on/off rates) to include cell based assays and functional enzyme assays. Collectively, these newer trends in label free detection have raised awareness for how these tools may be used for high through put drug discovery screens. A major area targeted for drug development has been protein biosynthesis. The two major areas of protein biosynthesis research for drug screening are translation and degradation. In this chapter a broad over view of the advances in label free detection as well as their impact on the development of assays for protein biosynthesis are given with special focus on screening capability. Concluding remarks about the future prospective applications for protein biosynthesis will also be discussed.

Non-optical Label Free Detection The current landscape of label free detection can be divided between optical and nonoptical based signal transducer schemes (Gauglitz and Proll, 2008 [3] and Cooper, 2006 [4]). The signal transducer is the device which converts energy from the biological or chemical interaction into another detectable energy form. Here the term non-optical describes those transducers that do not rely on the alteration of light (angle, spectral selection or interference) to measure the physical change in the biological event. Many of these physical techniques have been used as traditional tools in the biophysical science for decades but are now being adopted into higher throughput screening formats. The non-optically based signal transducer techniques have included: field electron transistors which include metal oxide silicon (MOSFET, Park et. al., 2005 [5]), single electron transistors (SET, Brousseau , 2006 [6]), silicon nanowire field electron transistors (Si NW FET), single walled carbon nanotubes field electron transistors (SWNT FET), resonant acoustic profiling (RAP), mass spectrometry (ms including deuterium-hydrogen exchange), microcalorimetry, capillary electrophoresis, NMR, differential scanning calorimetry, surface enhanced Raman scattering microscopy (µSERS, Grow et al., 2003 [7]), MEMS based nanocantilvers (Burg et al. 2007 [8]), quartz crystal microbalances (QCM, Huang et. al., 2006 [9]), electrical impedance and dielectrophoresis. Of the non-optical formats previously mentioned many are considered novel and have not yet transitioned into commercial platforms.

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Table 1. Commercially avialable non-optical label-free biosensors Manufacturer Acea Biosciences

Technology Cell based impedance

Instrument RT-CES™

Akubio

Resonant Acousic Profiling Cell based impedance

RAP?id™

Applied Biophysics Bioforce Nanosciences

Micro-cantilever

Biopraxis Biotrove

µSERS Mass spectrometry Differential calorimetry, Isothermal calorimetry Capillary electrophoresis Hydrogendeuterium exchange ms Thermal denaturation with fluorescent dye Cellular Dielectric spectroscopy (CDS) Differential calorimetry, Isothermal calorimetry

Calorimetry Sciences

CETEK Exsar Corp.

Johnson & Johnson MDS Sciex

MicroCal

NanoNord A/S

Nano cantilever

Q-Sense

Quartz Crystal Microbalance Single electron transistors Isoelectric focusing/IR Thermal IR Isothermal titration calorimetry Differential calorimetry

Quantum logic devices Inc. Solus Biosystems TechElan TA instruments Vivactis

ECIS™ ViriChip™ Nano eNabler™ system NA RapidFire™ MS-HTS N-ITC III, NDSC III, MCDSC, IMC, INC CE Assay™

Throughput 96 well plate

Website www.aceabio.com

4 sensors with 384 well plate auto-sampler 96 well plate

www.akubio.com

www.biophysics.com

microarray

www.bioforcenano.com

NA 384 well plate

www.biopraxis.com www.biotrove.com

1 sample per cylce

www.calscorp.com

NA

www.cetek.com www.exsar.com

ExRx™

Automated HPLC-MS

ThermoFluor ® CellKey™

384 Well plate

www.jnjpharmarnd.com

www.mdssciex.com 384 Well plate VP-ITC, VPDSC, VPCapillary DSC, autoITC CantiLabPro E4, D300 NA Solus100™ NA TAM 48

MiDiCal™

www.microcalorimetry.com 96 Well plate

8 sensors per chip Single sensor modules Microarray interface NA 1536 well plate Up to 48 samples per cycle 96 well plate

www.cantion.com www.q-sense.com www.quantumlogicdevices. com www.solusbiosystems.com www.techelan.com www.thermometric.com

www.vivactis.com

A list of several commercially available non-optical biosensors used in drug screening technology is given in table I. Many of the platforms in table I are medium to low throughput and do not qualify for either high throughput screening or high density microarray platforms. Several of the formats in table I can be used for both cell based assays and molecular interaction analysis while other formats have been limited almost exclusively to either molecular interactions or cell based assays. A comprehensive review of all of these

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technologies is beyond the scope of this chapter. The purpose of this section is to discuss the uses of these technologies in the context of high through put screens and protein biosynthesis.

Mass Spectrometry Mass spectrometry is one of the most powerful bio-analytical tools in recent history and qualifies as a label-free detection method. The application space for mass spectroscopy has extended broadly across all fields of bio-science including: protein identification, biomarker discovery, single nucleotide polymorphism profiling, structural characterization, identification of post translational modification of proteins, carbohydrate structure studies, metabolomics, de novo protein sequencing, cellular phenotype, gene expression (GE-HTS), comparative protein expression, metabolic pathway analysis, proteolytic degradation and numerous other applications. The quantitative analysis of proteins and peptide fragments has continued to improve through use of various labeling techniques such as; ICAT, iTRAQ, SILAC and enzymatic labeling through O16/O18 exchange. Protein array technologies with surface enhanced laser desorption/ionization (SELDI) are commercially available from BioRad Labs (www.bio-rad.com) as a tool for screening complex protein mixtures for biomarker discovery (Simpkins et al., 2005 [10], Tang et al, 2004 [11], Shiau et al, 2008 [12]). Other notable advances have come in the form of instrumentation and software analysis. For example, Olsen et al., 2007 [13] recently reported the development of a hybrid mass spectrometer which uses high energy C-trap dissociation (HCD) linear ion trap coupled to an orbitrap analyzer (LTQ Orbitrap, ThermoFisher Inc.). The Orbitrap™ technology was first introduced in 2005, since that time the technology has been expanded to include the combined capability of electron capture dissociation (ECD) with collision-induced dissociation (CID) and HCD spectra. The ECD method has been used routinely to pinpoint the exact location of labile post translational modifications on peptides/proteins. This implementation has been a critical advance in that it provides a fragmentation process which preserves the post translational modification by generating radical cations from multiply protonated ions that capture low-energy electrons (Bakhtair and Guan, 2005 [14]). These new technological advances have greatly expanded the range of applications for mass spectrometry especially with regard to identification of post translational modifications and de novo sequencing. Recently, mass spectrometry has been demonstrated and validated as a viable tool for performing large-scale label-free automated functional enzyme assays (Roddy et al, 2007 [15]). In this report, a small molecule library (175,000 samples) was successfully screened in two primary campaigns. These campaigns screened for enzymatic product inhibition for acetylcholinesterase and anthrax lethal factor. While these functional screens via mass spectrometry had been reported previously by other groups (Özbal et al., 2004 [16] and Min et al., 2004 [17]), they nonetheless were not validated for large scale HTS campaigns. The anthrax lethal factor screen uses a self assembled monolayer technique (SAMDI). In this assay the substrate of interest (peptide from the natural substrate) is immobilized on the microplate surface and is exposed to the enzyme of interest (anthrax lethal factor). When the reaction is complete the plate is washed and the enzyme induced mass changes of the

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immobilized substrates are measured by mass spectrometry. In the case of anthrax lethal factor the immobilized peptide is cleaved unless inhibited by one of the compounds from the screen. The Roddy study examined three different instrument component interfaces along with a proprietary MS-HTS microfluidics system with online chromatographic purification (Biotrove Inc). The average Z' values reported in this study ranged between Z' = 0.72 and 0.75, thus clearly validating the use of mass spectrometry for HTS screens of enzymatic reactions. The key significance of this study is that it demonstrates that unattended drug screening is possible though multiple automation techniques using LC/MS/MS mass spectrometry. Affinity-selection mass spectrometry (AF-MS) and hydrogen-deuterium exchange (Exsar Inc. H/D-MS) also represent two newer screening techniques for mass spectrometry based drug screens. It is important to point out that in some of the AF-MS techniques special labels are used in conjunction with mass spectroscopy and therefore are not true label free detection. Makara and Athanasopoulos (2005) [18] have given a more detailed review of several affinity based technologies directed toward improving the success rates for lead compound generation. The general form of AS-MS uses a three step process: (1) affinity selection stage where the biomolecular target is equilibrated with a putative ligand allowing a complex to form (2) the complex is separated from unbound ligand solution and (3) the complex is digested and bound ligand is detected by MS or MS/MS. The affinity selection mass spectrometry technique can be either direct or indirect. Direct AS-MS means the complex is separated within the mass spectrometer while indirect uses a chromatographic separation of the complex before MS analysis (Annis et al, 2007 [19]). Sunesis Inc. ( www.sunesis.com ) uses a covalent linkage technique wherein the protein target is modified to enable covalent bonding with binders from a custom small molecule fragment library (Cancilla and Erlanson, 2007 [20]). The conventional modification of the target involves thiol bond placement with the target to allow for covalent disulfide bond formation between the target and the prospective ligand. This modified target technique has successfully captured ligands in the small fragment range (<150 Dalton). Telik Inc (www.telik.com ) employs a technique called "Target-Related Affinity Profiling" or TRAP ™. In this technique putative ligands are screened against a panel of multiple protein targets to yield an over all specificity ranking. A proprietary database allows them the ability to better access a drug leads potential viability. Novartis Pharmaceuticals (www.novartis.com ) has developed SpeedScreen technology. The SpeedScreen assay exposes a protein target to a mixed pool of putative small molecule ligands and after a given incubation period (complex formation) the mixture of ligand-ligate complex and free ligands are separated by fast size exclusion chromatography (SEC). The small molecule binders dissociated from the complex and are identified by mass spectrometry. The deuterium hydrogen exchange screening (HDX-MS) technique by Exsar Corporation ( www.exsar.com ) uses peptide mass spectrometry to provide a structural foot print of ligand-ligate interaction. In this technique, the interaction between a target protein and its ligand are tracked structurally by mapping changes in the rate of exchange of hydrogen atoms typically in the amide bonds of the protein backbone with deuterium ions. The process typically involves changing the buffer state with a deuterated buffer for either the native protein state or under denaturing conditions using control variables such as exchange time,

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pH ionic strength and temperature (Kaltashov and Eyles, 2005 [21]). The association of the ligand within the protein target in the presence of deuterated solvent results in subtle mass changes in the protein structure due to differences in the isotopic mass (deuterium) within the amide bonds. The complex is degraded by trypsin into peptides which are measured by peptide HPLC-MS. Specific ligand docking maps within a protein structure are obtained. This technique is somewhat comparable to the ligand ligate complex screening done by twodimensional 1H -15N heteronuclear single-quantum correlation (HSQC)-NMR spectroscopy. Medium throughput NMR screens for ligand binding signals of 15N-labeled protein have been reported (Moore et al., 2004 [22] and Fejzo et al., 1999 [23]) using a proprietary SHAPES library (Bemis and Murko, 1996 [24]). The SHAPES library is a collection of low molecular weight water-soluble compounds whose shapes or frameworks represent those structural regions most frequently found in known drug molecules (Liu et al., 2004 [25]). Other than drug screens, affinity based analytical methods have also been used in combination with mass spectrometry to provide unique proteomic profiles. A key aspect of protein biosynthesis is the formation of isoforms and post translational modification. ActivX Biosciences Inc. (www.activx.com ) uses an affinity based capture technique to profile classes of proteins from biological samples by employing a common substrate binding activity termed activity-based chemical probes (ABPs) (Okerberg et al., 2005 [26], Burbaum and Tobal, 2002 [27]). The enzyme substrate is chemically modified to generate a covalent adduct to the corresponding enzyme(s) that complex with it. Once this class of enzymes is linked to the substrate, it can be subsequently purified from non-bound components in the mixture and identified by a number of characterization techniques such as 2 D gel electrophoresis and mass spectrometry. In this case the ligand becomes the affinity agent and upon exposure to a cellular lysate yields a plurality of family related protein targets. While not purely label free these techniques can be use to profile entire classes of enzymes in a cell lysate such as proteases, phosphatases and kinase. Intrinsic Bioprobes Inc. ( www.intrinsicbio.com ) has developed a suit of analytical tools for proteomic profiling by mass spectrometry (MASSAY™, MSIA™, BRP™ and BIA/MS™). Researchers from Intrinsic Bioprobes using the antibody capture of five plasma proteins were able to track the population diversity of 27 protein variants for a 1000 human plasma samples taken from four geographic regions in the United States (Nedelkov et al., 2007 [28]). This work effectively highlights the analytical power of combining affinity specific selection with mass spectrometric profiling for obtaining novel population based proteomic profiles.

Calorimetric Based Label-free Detection In table I, five companies are listed which utilize calorimetric analysis. Microcalorimetry is one of the oldest label free means of detecting molecular interactions using thermodynamics (Sturtevant, 1977 [29]). Microcalorimetry has been used extensively to characterize small molecule binding to protein targets (Doyle, 1997 [30]). It is insensitive to molecular weight restrictions (ion binding interactions have been routinely observed) and does not require immobilization through surface chemistry. Isothermal titration calorimetry (ITC) measures the successive heat loss or gain as molecules are combined through multiple

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injections (titration). For small molecule interactions, ITC measures the binding constant (KB), stoichiometry of binding (n), and thermodynamics of binding (DH, DG). Todd and Gomez (2001) [31] have used ITC for enzyme kinetics to obtain Kcat and Km values. The newest instrument (auto-ITC200) from MicroCal LLC can measure samples in 96 well plates and requires sample volumes of 200 µl using 5-10 µg of protein per experiment. The MiDiCal™ chips from Vivactis provide 96 and 384 well plate differential calorimetric sample detection using well volumes of 25 µl through a nanocalorimetric platform. Some examples of the use of microcalorimetry to biosynthetic reactions are: protease inhibitor assays (Schön et al, 1998 [32]), measurement of ribosomal subunit stability (Bonincontro et al., 1998 [33]) and more recently RNA-protein interactions for translation factors (Stolarski, 2003 [34]).

Impedance and Dielectric Spectroscopy High content screening (HCS) (also known as high content assays (HCA)) was first introduced in the mid-1990’s to rapidly analyze fixed/stained cells in microplates (Haney et al., 2006 [35]). Conventional HCS has been defined as the multiplexed functional screening through imaging multiple targets in whole cells on a cell by cell basis determined using automated fluorescence microscopy (Giuliano et. al., 1997 [36]). Since its introduction HCS technology for characterizing drug induced cell based phenotypic changes has expanded to include fluorescence activated cell sorting (FACS, Gough and Johnston, 2007 [37]) and high throughput gene expression (GE-HTS, Stegmaier et al., 2004 [38]) as well as several other label-free technologies. Cell based high content screens have rapidly gained acceptance as a core technology for secondary compound screening (Rausch, 2007 [39], Cooper, 2006 [40], Valet, 2006 [41]). A key motivation behind acceptance of HCA has been the high failure rates of drug candidates due to toxicity in later stages of drug development. HCA offers the potential that compounds from HCA screens will have greater “physiological relevance” when hits are transferred to animal and human studies (Korn & Krausz, 2007 [42]). One of the complications of HCA has been the need for well defined phenotypic signatures (Gough and Johnston, 2007 [43]). Often to improve the informational content of HCA screens a multiplex approach has been taken wherein multiple fluorescent markers are used to provide a more detailed phenotypic profile. In addition to improved signature, Shelat and Guy, 2007 [44] have advocated the use of chemical libraries that are tailored around well-defined molecular descriptors as a means of improving the success of phenotypic screens. Several non-optical label-free technologies in table I have been applied to cell-based assays in drug discovery. The impedance (Acea Biosciences, RT-CES™, Applied Biophysics, ECIS™) and dielectric spectroscopy (MDS Sciex, Cellkey™) formats have exclusively been directed toward cell based assays. In general, the impedance assays measure changes in the flow of electrical current between two or more electrodes. The behavior of cells attached to the electrode sensors can be monitored by alterations in the electrical current flow. Some cell properties which can cause current shifts include; cell shape, density and motility. These impedance assays have been used to assay a range of cell behavior including; cell proliferation, cell adhesion, barrier function, cytotoxicity, differentiation, migration and

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invasion. A comparison and contrast of the two impedance systems has been made elsewhere (Solly et. al., 2004 [45]). The CellKey™ dielectric spectroscopy system from MDS Sciex uses a constant voltage (current) such that at low frequencies current flows around and between cells (extracellular current, Ziec) and at high frequencies through cells (transcellular current, Zitc). Changes in cell morphology, volume and adherence result in a change in these current patterns. The CellKey™ System uses a cell-based rapid kinetic screening (<15 minutes) protocol allowing up to 24,600 wells to be read in an eight-hour period. The applications for the Cellkey™ system include; screening for endogenous receptors in their native environment, hit identification, pharmacological profiling, signal transduction and deconvolution of signaling pathways. The integration of these high content screening tools with RNAi has allowed the users the ability to validate the specificity of the individual profiles. Also the assays can be used in conjunction with more traditional label based microscopy or FACS screens to provide additional information for phenotypic tracking.

Optically Based Label Free Detection Optical biosensing technologies continue to dominate the field of commercially available label-free detection. Table II provides a list of commercially available optically based biosensors. The physical principles behind most of the biosensors listed in Table II have been well described elsewhere (Hoa et al., 2007 [46], Ramsden, 1997 [47], Homola et al., 1999 [48], Gauglitz and Poll, 2008 [49]). As can be seen from Table II surface plasmon resonance (SPR) is by far the most widely deployed form of optical biosensing. The bulk of label-free optical biosensing studies on protein biosynthesis have been carried out using SPR biosensing. The two other formats involve optical waveguides and biolayer interferometry. A more detailed review of each of the various optical biosensors has been written elsewhere (Cooper, 2006 [50], Rich and Myska, 2007 [51], Yuk and Ha, 2005 [52], Fang, 2006 [53]). In SPR, metals and other conductors which carry charge density are used to generate quantized plasmon waves called plasmons. Surface plasmons are generated at the interface of two materials with opposite dielectric charge. The surface plasmons represent the collective fluctuation in the electron charge density between the two materials. These electromagnetic waves propagate parallel to interface of the two dielectric materials. In the case of SPR biosensors, surface plasmons are generated because the metal has a negative dielectric charge while aqueous phase buffers have a positive dielectric charge. Surface plasmons can be excited by both electrons and photons. In order to excite the surface plasmons optically, light is directed at the metal surface. Prism coupled SPR (Ketchman’s configuration) is the most commonly used means of coupling light to the metal surface. Another common method uses gratings. The evanescent field from the surface plasmon interacts with the incident light and can cause a shift in the intensity of the reflected light when a change in refractive index occurs at the surface.

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Table 2. Commercially avialable optics based biosensors Manufacturer

Technology

Instrument

Throughput

Website

Axela

Diffractive optics

DOT™

www.axelabiosensors.com

Biacore (GE)

SPR

A100,T100,S51, FLEXchip™

8 sensors per microfluidics chip 20 interactions per cycle to 400 interactions per FLEXchip™ 96 well autosampler

www.analytik-jena.de

ProteOn XPR36®

36 target array

www.biorad.com

Epic®

384 well plate

www.corning.com

SPR

AutoLab Espirit

2 channels per sensor

www.ecochemie.nl

SPR Biolayer Interferometry (BLI)

IAsys™ Octet Red, Octet Q and Octet QK SPRi-Plex™

2 well module

www.neosensors.com

96 Well plate

www.fortebio.com

1000 spots per sensor Microarray

www.genoptics-spr.com

Bioanalytic Jena

SPR

Bio-Rad

SPR Optical Waveguide Grating

Corning Incorporated EcoChemie FarField Group ForteBio

GenOptics Graffinity GWC Technologies IBIS Intrinsic Bioprobes Lumera

SPR imaging SPR imaging

SPR imaging

BIAffinity™

www.biacore.com

Plasmon Imager® SPRimager®II, FT-SPRi 200 IBIS-I,IBIS2,IBIS-iSPR

>25 microspots/chip >24 spot array/sensor

BIA/ms™ NA

384 well plate 1000 spot array

www.intrinsicbio.com www.lumera.com

BIND™

384 well plate

www.srubiosystems.com

SRU Biosystems

SPR imaging SPR-coupled ms SPR imaging Optical Waveguide Grating

Reichert

SPR

SR7000

Toyobo

SPR imaging

MultiSPRinter

www.graffinity.com

2 channel chips with auto injection Microarray

www.gwctechnologies.com www.ibis-spr.nl

www.reichertai.com/spr www.toyobo.co.jp/bio

The first commercialized optical SPR biosensor was manufactured by Pharmacia biosensor in 1990 which has later become Biacore AB (www.biacore.com). The integration of microfluidics with the sensor enabled researchers with a means of obtaining kinetic associative and dissociative biomolecular interactions without the use of labels. Through the years Biacore has continuously improved its microfluidics, surface chemistry, automation, scale and sensing technology and now currently sell 6 models of SPR based biosensors instrumentation (Biacore 2000, 3000, T100, flexchip, S51 and the A100). The newer A100 and T100 systems have demonstrated sensitivity high enough to detect low molecular weight

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binders (~150 Da). The Biacore A100 offers parallel processing with multiplexed assays allowing up to 3800 interactions to be screened in a 24 hr period. Other notable SPR instruments are the array based SPR imaging (SPRi) systems. These SPRi systems like conventional microarrays provide the capability to study interactions across multiple surface targets ranging from 25 up to 1000 targets. If the sensitivity of the SPRi instruments is as good as the current SPR systems then one expects that many future global proteomic based drug screens could be possible with these systems. Graffinity Pharmaceuticals has developed the Plasmon Imager which uses a spectral wavelength sensitive SPR to detect array based binding. In addition to array based SPR imaging, Graffinity Pharmaceuticals has also developed a custom fragment based tethering chemistry to allow small molecules of <300 Da to be immobilized onto their sensor creating what is termed a protein binding fingerprint (Neumann et al., 2007 [54]). In order to integrate optical biosensing with conventional high throughput microplate drug screening Corning Inc. (www.corning.com) has recently developed a label-free optical microplate biosensor for the high throughput market. The Epic® System shown in Figure 1 consists of an SBS-standard 384-well microplate with optical sensors and HTS-compatible microplate reader capable of reading up to 40,000 wells per 8 hours and a set of label-free, direct-bind and functional assay protocols. The optical biosensor used in these plates is based on the use a of a resonant waveguide (RWG) system. The RWG like SPR uses an evanescent field located on the sensor that is derived from the use of an optical waveguide. Briefly, a white light source is exposed to a nano-featured high index grating film. Light wavelengths that are in optical resonance with the structure of the waveguide and refractive index of the grating guide are selectively coupled into the guide. As these resonant wavelengths are reflected out of the waveguide they are measured externally. Changes in refractive index at the surface of the RWG sensor result in either angular or spectral shifts in the reflected resonant light. Its sensitivity of 5pg/mm2 enables the detection of the binding of a 300 Da compounds to a 70 kDa immobilized target with CVs of 10% or less. The open format of the system allows researchers the ability to screen conventional ligand-ligate binding interactions, functional enzymatic assays such as proteolysis and kinase assays as well as cell based HCA assays. The sensor microplates can be equipped with internal self- referencing for increased sensitivity (Yuen et. al., 2005 [55]).

Emerging Formats A number of emerging formats in biosensing have developed in recent years both through advances in nanofabrication as well as integration of one biosensing format with other detection schemes. Integration of other metrologies with optical biosensors has been attempted for some time. An early example is the use of surface force microscopy with SPR to characterize changes in the immobilized biomolecules (Chen et al. 1996 [56]). Recently, Nedelkov (2007) [57] have reported on the integration of an SPR imaging platform with mass spectrometry. In this study, antibodies directed against five human plasma proteins were arrayed in a 10 x 10 array. The capture and binding affinity of the proteins to their corresponding antibodies was monitored via SPR imaging and the identity of bound proteins

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on the chip was subsequently analyzed by MALDI-MS. The SPR-MS dual detection greatly expands conventional protein microarrays by providing a comprehensive identification of the interacting partners. Many other multimodal formats are being developed including; SPRfluorescence, SPR with scanning electrochemical microscopy (SPR-SECM, Szuneritis et. al., 2004 [58]), confined surface plasmon resonant imaging (Ly et. al., 2007 [59]), differential SPRi (Boecker et al, 2007 [60]) and surface plasmon coupled quantum dots (Brolo et al., 2006 [61])

Figure 1. Example of a high throughput label-free microplate based biosensor. The photo on the left shows the Epic® system biosensor plate reader with automated microplate fluid handler from Corning Incorporated. The photo on the right demonstrates the bottom of the 384 well Epic® system sensor plate.

Schematic examples of label free biosensors that are not currently available commercially are given in Figure 2. Figure 2 (a) is a representation of a zero- mode waveguide (ZWG) wherein small holes (<60 nm) in a metal film over a fused silica substrate are used to provide a cladding (Levene et al., 2003 [62]). The zero- mode waveguide gets its name from the fact that the metal cladding prevents the propagation of light inside the nanohole waveguide. The wavelength cutoff is dependent on the shape and size of the holes in the guide. The ZMG has been used to monitor enzymatic synthesis of fluorescently tagged molecules as well as binding interactions. Figure 2B depicts a nanoscale optofluidic sensor array (NOSA). The NOSA design consists of a silicon waveguide (the long continuous bar) that is evanescently coupled to a 1-D photonic crystal micro-cavity side resonator (the bar containing several holes). The NOSA design has a much lower bulk refractive index sensitivity compared to conventional SPR but can also confine the size of the volume interrogated thereby improving the low mass limits (Mandal and Erickson, 2007 [63]). Figure 2 c depicts a Fabry-Perot interferometer made using porous silicon (Cunin et al., 2002 [64]). In this case, nanometer scale pores (2 nm) are etched into a silicon wafer using an electrochemical process wherein liquid hydrofluoric acid is controllably etched into the silicon by electric currents underneath the silicon. The silicon is then exposed to a thermal oxygen treatment to convert the silicon into porous SiO2. While this detection scheme may be

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equivalent or slightly weaker than current SPR detection it is nonetheless an attractive biosensing prospect due to ease of manufacturability. Free standing micrometer scale forms of the porous silicon sensors have been made termed “smart dust” (Link and Sailor, 2003 [65]). Figure 2 D, depicts an extraordinary optical transmission (EOT) biosensor wherein a gold surface is designed by focused ion beam milling (FIB) to contain an array of nanoholes (150 nm in diameter). Arrays of nanoholes (each array is 3.3 µm with 10 x 10 nanoholes) are used to detect mass shifts at the nanoholes. The sensitivity of this format has been reported to be slightly better than conventional SPR detection (Ramachandran et al, 2005 [66]). Figure 2 E depicts a two dimensional array using nanoslits (Lee et al, 2007 [67], Lee and Park, 2005 [68]). Surface plasmon polaritons (SPP) are generated within the slits by transmitted light in metallic nanoslit structures. The coupling strength is found to be the product of the geometric opening ratio, the aperture momentum, and the Fabry-Perot factor. As with SPR the surface plasmons within the slit are sensitive to local changes in refractive index. Figure 2 F is a schematic representation of an ultra high-Q microtoroidal resonator sensor. The diameter of the toroid can typically range between 0.5-60 µm and is usually comprised of silica (HosseinZadeh and Vahala, 2007 [69]). The toroids act as optical cavities which allow light to be circulated within the dielectric volume of the structure (www.vahala.caltech.edu). The sensitivity of ultra high Q factor toroids (Q>107) is very high and has reported differences between deuterated water and water. These structures are currently being engineered as free standing to integrate with other optical waveguide devices ( www.vahala.caltech.edu ).

Figure 2. Schematic representations of non-commercial label free biosensor formats. A. Side view of a zero-mode waveguide B. Side view of a nanoscale optofluidic sensor array (NOSA). C. Etched porous Fabry-Perot interferometer surface with nanochannels etched into silicon (D) Nanohole array sensor fabricated from a gold surface (E) nanoslit array (F) Ultra-high Q toroidal microcavity resonator.

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Protein Biosynthesis and Label-free Biosensing Protein biosynthesis is the creation of proteins from DNA, RNA and proteins. The transcription process in both Eukaryotes and Prokaryotes begins with the preparation of an RNA template from DNA. The translation process occurs at the ribosome (ribonucleoprotein assembly) and converts the RNA or mRNA template from transcription process into protein. Translation is separated into four steps: initiation, elongation, termination and recycling. The reactions of these four steps are catalyzed by translation factors. The number of participating proteins in translation varies between organisms for example prokaryotes have 10 translation factors while eukaryotes a much larger number of participants. In addition to the translation factors there are also other participants known as chaperones and trigger factors that are believed to assist in folding and to protect nascent chains from digestion (Yonath, 2006 [70]). Chemicals such as chemical cross linking agents and interaction blocking agents have been used to probe the various stages of protein biosynthesis for many years (Cencic et al., 2007 [71]). On the ribosome, there are several prospective sites for drug interaction such as; the decoding center, the exit tunnel, the peptidyltransferase center (PTC) and the anchors of the A-site to P-site rotatory motion (Auerbach et al., 2004 [72]). The interactions between the translation factors themselves also offer an opportunity for therapeutics (Cencic et al., 2007 [71]). Small molecules that cause read-through nonsense mutations or ribosomal frame shifting through chemical suppression are being examined. Some of the most potent antibiotics have been directed toward control of protein biosynthesis (Wilson et al., 2005 [73]). The class of macrolide antibiotics is broad and several forms have been shown to bind to the tunnel of the large ribosomal subunit (Hansen et al, 2003 [74]). Elaborate proximity assays have been developed to screen for interaction inhibitors for two translation factors using time resolved fluorescence energy transfer assays (TR-FRET) with specially designed constructs for label introduction (Cencic et al., 2007 [71]). The question remains as to what role label-free biosensing has played or can play in the study of protein biosynthesis. Table III provides a chronological series of papers specifically directed at studying selective processes within protein biosynthesis through label-free optical biosensors. The table identifies both the immobilized target as well as any prospective binders (ligands). The immobilization chemistry is also identified to help the reader understand how the target is located on the sensor during its interaction. Typically, amine coupled targets are randomly displayed on the surface while biotinylated and hexa-histidine (His-tagged) protein involve a construct directed oriented immobilization. As an aside it is also important to note that many of the constructs used in these papers were before the time of inteins (Muralidharan and Muir 2006 [75]) and selective biotinylation technology using AviTag™( www.avidity.com ). The range of interactions put forth in the biosensor papers in Table III have included; the recognition of RNA by the ribosome and its subunits, the binding affinity between the ribosomal recycling factor and the ribosome, the interaction between eIF4E and eIF4G in the mRNA cap-binding complex, the interaction between Ricin toxin A-chain and the ribosome, the interaction between signal recognition particle (SRP) and the signal receptor (SR), and interactions between various translation factors eIF1, eIF4G, eIF3, eIF2 and so on. In short, each partnering component within any process of protein synthesis can be studied using label-free binding. Often to validate a pin pointed interaction selective point mutations or

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truncation mutations have been implemented to confirm a site-site interaction. In other cases, the kinetic analysis has enabled a view of the timing involved for partner participation during a complex assembly interaction. However, recently the examination of just ligand-ligate associations has been expanded to include a much more complex functional protein biosynthesis event. Table 3. Protein synthesis studies using label-free technology

Target(s)

Immobilization Chemistry

Ligand(s) E72A

His-eIF4G-BD4E region, his-P20

eIF4E, eIF4E , V71G W75R , eIF4E eIF4E

Synthetic mRNA

30S, 50S subunits, IF3, Met deacylated tRNA , fMetMet tRNA P1(±phosphorylation), P2(±phosphorylation), P2 S105D(±phosphorylation)

eEF2

Ribosome recycling factor (RRF), R132H R132G RRF ,RRF , EF-G eIF4A

70S ribosome and subunits 50S, 30S eIF4G1(wt) and eIF4G1

Biotin-mRNA cap (19mers) 5S rRNA

PheRS

Ni

2+/

NTA

Aldehyde

Amine coupling

Amine coupling

542-

883

Amine coupling

eIF4E, eIF4G-BD4E

capture of biotinylated targets by Streptavidin Biotin DNA capture of RNA

BstL5, BstL5

K33A

, BstL5

eIF1A-GDP-tRNA GDP

F122A

phe

, eIF1A-

Amine coupling

Ricin toxin A-chain (RTA)

80S 70S ribosomes (± depurination)

Thiol and amine coupling

eIF4G, eIF1

eIF4E and variants, eIF3

Amine coupling and 2+/ Ni NTA

RRF, RRF-DI

70S ribosome and subunits 50S, 30S

SRP receptor

Rabies virus matrix protein (M protein)

GST-eIF4G

2+/

393-490

Ni NTA

Amine coupling

SRP, ribosome and Ribosomal subunits

Biotinylated targets captured by Streptavidin

eIF3

Amine coupling

Apo-eIF4E Cap-eIF4E

His6-EGFP, AD transaminase

Amine coupling and anti-GST capture

Ni2+/ NTA

Interaction Kinetics/Affinity of P20 and eIF4G for eIF4E Initiation of ribosomal complexes to mRNA Kinetics/Affinity of P1 and P2 protein for eEF2 Kinetics/Affinity y between RRF and ribosomal subunits Structural dependence of eIF4A complex with eIF4G Kinetics/Affinity of yeast variants of eIF4E for mRNA Kinetics/Affinity of L5 protein for rRNA Interaction between eEF1A and PheRS Kinetics/Affinity of ricin toxin to Eukaryote / Prokaryote ribosome Cap-binding complex interactions Mode of RRF binding to 70S ribosome Affinity of SRP and ribosome for SRP receptor Effect of viral protein on translation Interaction of Capped eIF4E and eIF4G

Real-time cell free synthesis

Reference

Ptushkina et. al., 1998

Karlsson et. al., 1999 Bargis-Surgey et. al., 1999

Ishino et. al., 2000

Dominguez et. al., 2001

Ptushkina et. al., 2001 Iwasaki et. al., 2002

Petrushenko et. al., 2002

Honjo et. al., 2002

Von der Haar et. al., 2002 Nakano et. al., 2003

Mandon et. al., 2003 Komarova et. al., 2006

Von der Haar et. al., 2006

Lee et. al., 2007

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Figure 3. A. Real-time sensorgram of a protein being immobilized on a sensor while it is being synthesized using cell-free extract. The protein is his-tagged EGFP from plasmid pIVEX2.3d-EGFP (dotted line is the control reaction without DNA plasmid). Solid line indicates the protein incorporation onto a Nickel ion –NTA surface. The inset in Figure 3 A confirms that the EGFP protein was immobilized on the sensor using SPR imaging. B. Seven other proteins were also immobilized on the sensor and imaged by SPRi. C. Western Blot of the seven proteins imaged in B. The gel shows a comparison of pellet and supernatant (soluble) protein indicating that some proteins formed inclusion bodies. Reprinted here by Permission from Elsevier.

Lee et al., 2007 [76] published the use of an optical biosensor to monitor cell-free protein biosynthesis in real-time (Figure 3). While it is true that cell free synthesis has been used previously to procure proteins for biosensor (Tabuchi et al, 2002 [77] and Kawasaki et al., 2003 [78]), the real-time synthesis and solid phase incorporation has not been reported until recently. Figure 3 (A) shows the SPR sensogram (angle shift) for a 100 μl cell free expression reaction using a plasmid construct pIVEX2.3d-EGFP. The surface contains a standard nickelnitrilotriacetic acid (NTA) surface for binding to the nascently synthesized his tagged protein. The dotted line shows the control reaction which was unchanging during the time course. The inset figure of 3A shows a SPR image analysis which validated that the EGFP proteins were in fact located onto the sensor after synthesis. Figure 3 B shows other 2-D SPR images of seven other proteins that were also immobilized onto the SPR biosensor. The researchers then analyzed the cell free translated proteins for solubility using Western blots (Figure 3C). This work clearly opens up the possibility that label free kinetic and completeness investigations of the entire protein biosynthesis process by label-free screening. This technique need not be limited to proteins only. Robelek et al., 2007 [79] reported the use of a peptide construct (CSRARKQAASIKVAVSADR, p19) to retain unilamellar vesicles for cell free incorporation of a GPCR construct on a biosensor. This demonstrates that even membrane bound proteins

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are prospective targets for real-time kinetic studies with label-free biosensors. Yet there are other non-protein factors recently shown to play a role in protein biosynthesis that can also be studied by label free detection. MicroRNAs (miRNAs) are small single-stranded noncoding RNAs (~22 nucleotides) that have key roles in gene silencing. They are generated from endogenous hairpin-shaped transcripts encoded in the genomes of Eukaryotes and viruses. MicroRNAs function as part of large gene regulatory networks and have been cited as prospective targets for drug discovery (Mack, 2007). Several labs in 2007 reported on findings which help to identify the mechanisms of miRNA action in cells (Meister, 2007 [81], Thermann et al, 2007 [82]). One of these regulatory mechanisms relates directly to the inhibition of translation initiation. A model has developed wherein the Ago proteins compete with eIF4E for cap binding. Once an Ago protein is bound, the cap is no longer accessible for eIF4E and translational initiation is repressed. When miRNAs bind to the 3′ untranslated regions (UTRs) of the mRNA, Ago proteins compete with eIF4E for cap binding. The area of miRNA research is also active with label-free detection. In 2006, the group from Dr. R.M Corn’s lab demonstrated attomole SPR imaging microarray detection of miRNAs using in situ surface mediated enzymatic amplification of captured miRNAs (Fang et al., 2006 [83] and Wark et al, 2008 [84]). In this amplification method a poly A tail is enzymatically extended off of the 3’ of miRNAs captured by tethered locked nucleic acid capture probes on the SPR sensor surface. The in situ grown poly A tail is then decorated by poly T tagged gold nanoparticles. This gives an example of how label free SPRi array based detection can be very sensitive toward the detection of a small but very informative set of biological targets. It is interesting to note that Corn’s group had previously demonstrated signal amplification of nucleic acids detection on label free SPR biosensors using a digestion technique rather than in situ nucleic acid polymerization (Lee et al., 2005 [85] .

Protein Degradation The lytic breakdown of proteins within a cell is widely known to play a pivotal role in regulation, signaling circuits, biological pathways, metastasis and general maintenance of all biostructures within a cell (Lόpez-Otín et al, 2002 [86], Overall, C.M, 2004 [87], Hershko, A.V 1988 [88], Cal, S, 2003 [89], Folgueras et al., 2004 [90], Overall, C.M et al, 2004 [91]). Two basic forms of protein degradation occur in cells. Lysosomal disgestion occurs inside acidic organelles while cytosolic digestion occurs within proteasomes which are multienzyme complexes in the cytoplasm. Proteasomal digestion can involve the covalent attachment of ubiquitin to proteins for transportation to the proteasome. Degradomics like other “–omic” studies represents another way to track the complex molecular phenotype of cells. More than 30 companies are developing protease inhibitor therapies (Bogdanovic, S. and Langlands, 2005 [92]). Well known examples of protease and proteasomal inhibitors are AZT and Velcade for use as antiviral and anti-cancer agents. Conventional protease inhibitor screens have involved labeling of a substrate with fluorescent or radioactive probes. However, label based protease assays can cause steric artifacts as well as requiring the purification and validation of the labeled substrates. Recently, the use of functional

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proteolytic assays via label free detection in HTS format has been reported (O’Malley et al., 2007 [93]). SPR biosensors have been routinely used to characterize conventional kinetic associative and dissociative biomolecular interactions without the use of labels (Ramsden, 2005 [47] and Ramachandran et al, 2005 [66]). Evanescent biosensors have been used to measure ligand binding events smaller than 300 Daltons (Frostell-Karlsson et al., 2000 [94], and Rich et al., 2002 [95]). Protease inhibitor secondary screens have been reported using label independent direct binding screens wherein the protease is immobilized onto the biosensor and putative drugs are bound (Hämäläinen et al., 2000 [96]). Direct binding assays, however, do not guarantee enzymatic inhibitor activity and are limited to those molecular weights that are sufficiently able to provide a detectable change in refractive index. One tenable area of bioassay research that has been sparsely explored by label free biosensors is assays which utilize surface based enzymatic digestion of biomolecules on a biosensor. Chen et al. (1996) [56] have described the combined use of surface plasmon resonance (SPR) with surface force microscopy (SFM) to measure biodegradation of an immobilized polymer coating on an optical sensor. The degradation of polymeric, biopolymeric thin films and dye labeled peptides on SPR based biosensors has been reported (Sumner et al., 2001 [97] and Lin et al., 2002 [98]). Adsorption and Michaelis-Menten kinetic studies for surface based protease and DNAse reactions have also been reported (Kim, et al, 2001, [99] Lee, et al., 2005 [100]). SPR biosensors have also been used to characterize ubiquitin pathways (Hartmann-Petersen and Gordon, 2005) [101] and small ubiquitin-like modifiers (SUMO) (Oh et al, 2007 [102]). Despite these characterizations the demonstration of functional lytic inhibitor screens with native state biopolymeric substrates using high throughput biosensors has not been reported to date. Biosensors in HTS microplate format provide the possibility of establishing a new form of functional lytic assays and screens wherein the native substrate and enzyme may be studied without labels. O’Malley et al., 2007 [93] examined the properties of a surface based digestion on a biosensor as it relates to various hydrolytic enzymes, various substrates and various hydrolytic enzyme inhibitors. In this study it was found that each protein specific digestion profile was relatable to expected digestion specific properties. More specifically the digestion behavior on any biosensor was found to be affected by numerous factors such as cleavage site availability, number of cleavage, size of cleaved fragments as well as the enzyme reactivity on a surface. The albumins and their modified forms were examined as a means of assessing the structural correlation of digestion signals on a biosensor. The absolute percent conversion to product (ratio of digested mass to immobilized mass) was found to be a fairly useful tool for comparing digestion profiles between proteins. Figure 4 panel A depicts the proteolytic digestion of proteins off an optical waveguide biosensor as reported in O’Malley et al., 2007 [93]. As the protein is digested off the biosensor a corresponding mass loss results and a negative signal is observed. The optical waveguide operation is demonstrated in figure 4 B wherein the reflected power of the resonance light is observed as a function of the selected wavelengths. As mass changes at the sensor occur a corresponding shift in the spectral peak are observed. Figure 4 C shows the digestion patterns for several albumin family proteins and carbonic anhydrase by trypsin proteolysis (0.10 units/μL) on the RWG biosensor over a 35 minute time course. The

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hierarchy of digestion rate for the digestion signal was as follows: acetylated BSA >BSA>H.S.A.> carbonic anhydrase > methylated BSA. The percent conversion to digested product when averaged for 2 digestion trials was as followed: 21.2 ± 9.3 % acetylated BSA > 17.2 ± 5.3 % BSA> 11.8 ± 2.3 % H.S.A.> 9.2 ± 2.3 % carbonic anhydrase > 4.1± 0.4 % methylated BSA. Surprisingly, the acetylated BSA and normal fraction V BSA appear closely matched. Acetylation of BSA should eliminate lysine cleavage sites leaving only 26 arginine cleavage sites. The human serum albumin gave a slightly lower extent of digestion relative to normal BSA perhaps due to reflecting subtle differences in conformation. The digestion rate and extent of digestion for methylated bovine serum albumin was dramatically reduced relative to normal BSA fraction V. These profiles observed were very reproducible and clearly suggested that the digestion signal from the RWG biosensor does convey substrate specific digestion properties. Figure 4D depicts the digestion profile for three proteases using a fixed concentration of carbonic anhydrase II. All three proteases differ in their cleavage sites as well as in their mechanism. The typical proteolytic signature for three proteases (at 0.5 units/µL) for the immobilized substrate carbonic anhydrase II was measured. The observed hierarchy of proteolytic digestion rate of carbonic anhydrase II was as follows; Thermolysin> Chymotrypsin> trypsin. The thermolysin digestion resulted in a significantly higher degree of proteolysis which is likely due to the fact that thermolysin has more than two times the number of cleavage sites over either trypsin or chymotrypsin.

Figure 4. Real-time functional proteolytic assay on an HTS resonant waveguide (RWG) Epic® system biosensor microplate. A. Schematic illustration of how a protease removes immobilized proteins off of a sensor. B. Spectral profile of light selectively reflected off of the resonant waveguide. C. Trypsin digestion profiles for five different proteins immobilized on the RWG sensor. Trace 1) acetylated BSA, Trace 2) BSA fraction V, Trace 3) carbonic anhydrase II, Trace 4) human serum albumin (HAS), Trace 5) methylated BSA and trace6) PEG-amine control well. D. Effect of proteolytic enzyme digestion on carbonic anhydrase II. Trace 1) thermolysin, trace 2) chymotrypsin and 3) trypsin. All enzymes were at 0.5 units/μl. Reprinted here by permission from SAGE publishers.

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Figure 5. Protease inhibitor drug screens on an HTS label-free biosensor. A. Effect of titrating increasing amounts of leupeptin inhibitor on carbonic anhydrase II digestion from trypsin. B. Digestion response versus Log -molar concentration of Phosphoramidon . C. Direct protease inhibitor specificity profiling of 3 different classes of proteases obtained on an HTS biosensor. Reprinted here by permission from SAGE publishers.

The digestion technique was extended further into a drug screening approach. The ability of known inhibitors to be assayed using proteases and a dextranase over a 20 minutes time regime which is in keeping with standard high through put screening. Proteases from three different protease classes (Serine protease; trypsin, cysteine protease; papain and metalloproteinase; thermolysin) were examined. Carbonic anhydrase II was used as the common substrate for all protease variable screens. The effect of various concentrations of leupeptin on the trypsin-carbonic anhydrase II digestion time course is shown in Figure 5 A. As can be seen from figure 5A most of the inhibition has occurred prior to 6.5 µM leupeptin. In addition the digestion signal taken at the 20 minute time point appears to provide a reliable measure of inhibitor effect. These digestion profiles were found to be representative of the other protease inhibitor screens. The experimentally measured EC 50 values compared very closely with those reported EC 50 values (O’Malley et al., 2007 [93]). This agreement provided sufficient confidence that the surface based digestion profiles were capable of reliably detecting inhibitor effects. A representative response versus Log [Dose] curve for thermolysin-phosphoramidon is shown in figure 5 B. The EC 50 determinations were obtained from fitted curves for the enzyme-inhibitor pairs using a 2 log concentration range. The sigmoidal fitted data was obtained using Prism GraphPad. The work in O’Malley et al., 2007 [93] also demonstrated that the lytic enzymes were shown to be differentially

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susceptible to various inhibitors. Figure 5 C depicts the protease inhibitor specificity using three classes of proteases for various protease class inhibitors. The percent normal lytic activity was obtained by normalization to the digestion signals in 1x PBS. The inhibitor selectivity undoubtedly reflected the difference between the various hydrolytic mechanisms between the three enzymes. As a screening tool biosensors clearly appear to be highly effective tools at distinguishing between a non-inhibitor and an inhibitor A future prospect is that these surface-based hydrolytic assays could be used in highly parallel microarray formats. Microarray biosensors have provided the ability to look at global protein interactions (Yuk and Ha, 2005 [103]). Conceivable, the lytic assays from O’Malley et. al., 2007 [93] could also be applied toward global degradomic studies. In some applications one may wish to look at the off target specificity of a various hydrolytic enzyme inhibitors. In other cases, one may wish to examine the viability of peptide based therapeutics under in vivo like conditions. Whole proteomic digestion profiles may also be possible with this technology and will likely provide useful insights into a poorly understood cellular phenotype.

Atypical Proteolytic Assays In the previous section we focused on using label free detection as a tool for examining the inhibition of proteolytic enzymes. Here, we turn our attentions to the effects that ligands can have on substrates tethered to a biosensor with regard to their conformational state. The conformational state of the protein targets in the previous section was accepted as is. It was a given that the conformational state was intrinsic and specific to each of the protein targets examined. Yet, just as each protease has its own specific amino acid preference for cleavage it is also true that each protein target has its own amino acid sequence displayed in its own conformational state. However, molecular interactions such as small molecule ligand-ligate binding or macromolecular complex formation (e.g. protein-protein, nucleic acid-protein association) have been known to result in dramatic conformational changes. One anticipates that for some molecular interactions a conformational change might result which could either enhance or reduce proteolysis by changing the availability or degree of exposure of the cleavage sites. Many traditional biophysical methods have been used to study localized conformational changes such as fluorescence anisotropy, Stern-Volmer fluorescence quenching, FRET, circular dichroism, UV-Vi difference spectroscopy, Raman, NMR and so on. In each of these methods a specific structural signature is utilized to track changes in conformational state. For fluorescence assays either intrinsic fluorescent amino acids (e.g. tryptophan) or extrinsic fluorescent tags are used. The ability to use proteolytic signatures as a means to track conformational transitions for RNA-protein complex formation using mass spectrometry and gel electrophoresis profiling has been shown previously (O’Malley et al, 1995 [104]). However, a direct label free high through put technique for measuring changes in conformational state has been lacking. In recent years several publications using label free optical biosensing have been directed toward detection of conformational changes. One of the earliest efforts to use optical biosensing to detect conformational changes was reported by Sota et al, 1998 [105]. In this

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paper, a pH specific signal was measured for immobilized dihydrofolate reductase (DHFRASC) relative to blank sensors. The use of this comparative difference between bulk and surface pH to explain hydrodynamic modulation of protein structure was nonetheless not widely adopted. Similarly, Gestwicki et al., 2001 [106] later reported the use of negative refractive index changes via hydrodynamic -fluidic shifts to infer conformational changes between a small molecular weight binder (maltose) and its receptor maltose binding protein. Of course the absence or presence of affinity between two binder pairs by itself can be taken as evidence for a conformational state (Honjo et al., 2002 [107] and Robelek et al, 2007 [108]). Conformational diversity in some SPR studies has been inferred through the failure of an association and dissociation model to be adequately fitted to an observed kinetic reaction rate via global fitting routines (Von Der Haar et. al., 2006 [109]). However, despite these efforts the field of optical biosensing is still in need of specific assay tools which can be employed toward assaying conformational changes robustly. In this next section, it is shown that small molecular weight binding agents can result in a modulation (reduction) of a proteolytic signature. Also in this section we demonstrate the use of catalytic agents which can facilitate proteolysis degradation. One model system which conveniently demonstrates a dramatic conformational transition upon small ligand binding is heme insertion. Heme proteins are evolutionarily designed to stereo-specifically retain the heme moiety. Hemin or heme is a planar 20 carbon iron containing macro-cyclic compound (651.96 Dalton). The insertion of heme into the heme pocket of most heme-proteins is known to be extremely stable and requires special extraction methods. Removal of heme from human hemoglobin has been measured to cause a 50% loss in alpha helical content (Waks et. al., 1973 [110]). Perhaps the most compelling reason for this dramatic transition lies in the fact that both the alpha and beta protein subunits of the hemoglobin tetramer contain 18 to 20 atomic contacts (respectively) with the heme molecule (Fermi and Perutz, 1984 [111]). The results of the experiment shown in Figure 6 were done in order to demonstrate the effect ligand induced conformational changes on proteolytic cleavage. Horse apomyoglobin used in this experiment was prepared using the acid-acetone method of Rossi-Fanelli et al., 1958 [112] with modifications described in Ascoli et. al., 1981 [113]. The extent of heme removal was confirmed spectrophotometrically to be greater than 90%. Figure 6 A illustrates how heme insertion can result in a “protection” of cleavage sites on the surface of immobilized apomyoglobin. The red triangle on the protein surface in figure 6 A represents a trypsin cleavage site. Prior to heme insertion the structure is fairly lose and the cleavage site is fully available. Upon heme insertion the structure changes and now lacks complete solvent accessibility to trypsin. Figure 6 B depicts the sensogram recorded on the Corning Epic® system for the effect of heme insertion into apomyoglobin. Each trace represents an average of six kinetic time traces for trypsin digestion of myoglobin (3), apomyoglobin (1) and hemin inserted apomyoglobin (2). Traces 4 &5 are control wells for trypsin digests of blank wells coated with PEG only. Not surprisingly, the apomyoglobin exhibited the largest degree of digestion due to collapsed secondary structure while myoglobin (3) and hemin reconstituted myoglobin (2) both demonstrated a significant protection by maintenance of the occupied heme pocket structure. This experiment illustrates

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how proteolytic digestion can be used to provide a profile of ligand induced conformational changes. It is contemplated that these two ligand dependent effects on proteolysis can be extended further in two specific ways. First, for some specific ligand- ligate systems the interaction may be sufficiently robust to allow label free HTS drug screens. In such as case, one would first screen various enzymes and under various buffer conditions using a known ligand ligate binding pairs. Those conditions which give a ligand specific digestion signature are then used to screen for other putative ligands which yield a similar or matching substrate/target digestion signature. Controls would then be required to verify that the effect was restricted to the immobilized ligand and not a protease modulating drug. The second prospective expansion of these atypical label-free digestion assays is to use as a tool for comparing native state via an expected digestion signature to a mis-folded state. If the mis-folded state is validated to cause a detectable change in the digestion profile then these assays should provide a HTS-screens capability.

Figure 6. Effect of ligand induced protease protection. A. Schematic of heme insertion into apomyoglobin B. Kinetic time course for a trypsin digest of three forms of myoglobin on an RWG biosensor. Trace 1) Apomyoglobin, trace 2) Heme reconstituted myoglobin (Heme inserted), trace 3) native myoglobin and traces 4/5 are PEG-amine control wells. Note the reconstituted apomyoglobin trace 2 is almost as protected as the native myoglobin.

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Figure 7. Catalytic proteolysis probed by label-free biosensing. A. Schematic of how dimeric porphyrins invades an immobilized protein making its buried residues exposed to proteolytic cleavage. B. Kinetic time course for trypsin digest of cyctochrome C in the presence and absence of compound 2b (proteolytic catalyst). Note the dramatic increase in digestion when the catalyst is present.

Catalytic Digestion Assays Catalytic digestion involves the use of a chemical agent to alter the digestion activity of a digesting entity. The alteration to digestion can be an increase or a decrease. The catalytic description applies to this system wherein the chemical agent used to modulate the digestion process is not consumed in the reaction. The chemical agent can be organic, inorganic, polymeric and biopolymeric, organometalic, biologically derived phage peptide, a synthetic peptide, and aptamer, and DNA or any combination thereof. Groves et al., 2004, [114] describe a class of copper porphyrin dimmers which are examples of catalytic digestion agents. These agents when added to a digestion system can result in an enhancement or actual enablement of the digestion process. Below is a description of the Groves et. al. 2004 [113] based catalytic digestion system. Figure 7 A illustrative depiction of how a dimeric porphyrin physically invades a protein structure causing an unfolding event which then exposes amino acid residues within the biopolymer to be cleaved by a proteolytic. The authors demonstrate both circular dichroism and SDS PAGE gel electrophoresis of the protein. This paper limits itself to just protein targets yet in theory it should be extendable to any macromolecular structure such as a carbohydrate, protein, peptide, RNA, DNA, membrane protein and the like. The catalytic

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digestion should also not be limited to just copper II containing porphyrins. Chemical agents may be used to modulate label-free digestion signals on a biosensor. As in the previous section, these catalytic agents could be used to study biopolymer stability, detection of intermolecular interactions such a ligand-ligate systems, or to enable or aid in the formulation of a digestion assay when the immobilized agent is difficult to digest. The experiment in Groves et. al., 2004 [114] was reconstituted and is shown in Figure 7B. The catalytic agent described in Groves et.al. 2004 [114] that was used in this study was copper (II) tetra-(4-carboxyphenyl) phorine AKA “compound 2b”. The procedure for making compound 2b was as follows; (1) A 10-fold excess (w/w) of copper II acetate was added to a solution of the free base tetra-(4-carboxyphenyl_porphine in methanol. After 16 hours at room temperature, the insoluble copper porphine was then filtered off and washed with 1mM HCl, distilled water, ethanol and then dried by nitrogen and heat in a speed vac. The copper porphine extracts from the water phase wash were sufficient to use in the digestion assay. Equine cytochrome C was chemically immobilized onto the amine reactive surface of an Epic® System sensor microplate. The comparative trypsin digestion on the Epic® system was measured. The catalyst arrow points to the digestion trace (red/yellow) for the copper II porphine and demonstrate a significant enhancement of digestion. In these assays 15 units of trypsin/100 μl were used in each well. As can be seen from figure 7B the addition of catalyst does in deed enhance the rate and extent of catalysis.

CONCLUSION In this chapter recent advances in label free technology were reviewed with special focus on high throughput screens and protein biosynthesis. The biosensor field has matured to the point where label free detection can be applied in either high through put screens or in multiplexed microarray formats. The application space depending on the method of label free detection can be applied to high content cell based screens, conventional direct bind assays and functional cell free protein synthesis and protein degradation assays. As the application space for label-free detection continues to grow inevitably so will the user base. We have also seen that these biosensors can be used in conjunction with other formats to provide even more unique data. As seen in the union of mass spectrometry with SPR. As sensor designs improve, shrink and become free standing it is possible that we may see future applications wherein transfectable biosensors are deployed directly into cells for real time assay of in vivo biological events. The interaction partner pairs for protein biosynthesis (Table III) may now become components for high throughput drug screens using optical biosensors are microplate formats are now available. The last section on protein degradation offers the possibility that HTS lytic inhibitors can be rapidly and reliably screened. The dependence of the functional lytic screen on substrate structure may also avail itself toward the study of mis-folded proteins

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[73] Wilson DN, Harms JM, Nierhaus KH, Schlünzen F, Fucini P. Species-specific antibiotic-ribosome interactions: implications for drug development. Biol. Chem. 2005 386(12):1239-1252. [74] Hansen JL, Moore PB, Steitz TA. Structures of five antibiotics bound at the peptidyl transferase center of the large ribosomal subunit. J Mol Biol. 2003. 330(5):1061-75. [75] Muralidharan V, Muir TW. Protein ligation: an enabling technology for the biophysical analysis of proteins. Nat Methods. 2006. 3(6):429-38. [76] Lee KH, Joung HA, Ahn JH, Kim KO, Oh IS, Shin YB, Kim MG, Kim DM. Real-time monitoring of cell-free protein synthesis on a surface plasmon resonance chip. Anal Biochem. 2007. 366(2):170-4. [77] Tabuchi M, Hino M, Shinohara Y, Baba Y. Cell-free protein synthesis on a microchip Proteomics. 2002. 2(4):430-5. [78] Kawasaki T, Gouda MD, Sawasaki T, Takai K, Endo Y. Efficient synthesis of a disulfide-containing protein through a batch cell-free system from wheat germ. Eur J Biochem. 2003. 270(23):4780-4786. [79] Robelek R, Lemker ES, Wiltschi B, Kirste V, Naumann R, Oesterhelt D, Sinner EK. Incorporation of in vitro synthesized GPCR into a tethered artificial lipid membrane system. Angew Chem Int Ed Engl. 2007. 46(4):605-8. [80] Mack, G. MicroRNA gets down to business. Nature Biotech. 2007. 25 (6): 631-638. [81] Meister G. miRNAs get an early start on translational silencing. Cell. 2007. 131(1):2528. [82] Thermann R, Hentze MW. Drosophila miR2 induces pseudo-polysomes and inhibits translation initiation. Nature. 2007. 447(7146):875-878. [83] Fang S, Lee HJ, Wark AW, Corn RM. Attomole microarray detection of microRNAs by nanoparticle-amplified SPR imaging measurements of surface polyadenylation reactions. J Am Chem. Soc. 2006. 128(43):14044-14046 [84] Wark AW, Lee HJ, Corn RM. Multiplexed detection methods for profiling microRNA expression in biological samples. Angew. Chem Int. Ed. 2008. 47(4):644-52. [85] Lee HJ, Li Y, Wark AW, Corn RM. Enzymatically amplified surface plasmon resonance imaging detection of DNA by exonuclease III digestion of DNA microarrays. Anal Chem. 2005. 77(16):5096-100. [86] Lόpez-Otín, C. and Overall, C.M. Protease Degradomics: A New Challenge For Proteomics. Nature Reviews. 2002. (3):509-519. [87] Overall, C.M. Dilating the degradome: matrix metalloproteinase 2 (MMP-2) cuts to the heart of the matter. Biochem. J. 2004. 1: 383: e5-7. Review [88] Hershko, A.V. Ubiquitin Mediated Protein degradation. Minireview. J. Biol. Chem. 1988. 263. 30: 15237-15240. [89] Cal, S., Quesada, V., Garabaya, C. and Lόpez-Otín, C. Polyserase-I, a human polyprotease with the ability to generate independent serine protease domains from a single translation product. PNAS. 2003. 100 (16): 9185-9190. [90] Folgueras, A.R., Pendas, A.M., Sanchez, L.M. and Lόpez-Otín, C.. Amtrix Metalloproteinases in cancer: from new functions to improved inhibition strategies. Int. J. Dev. Biol. 2004. 48: 411-424.

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In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter VIII

TRANSLATING MEMORIES: THE ROLE OF PROTEIN BIOSYNTHESIS IN SYNPATIC PLASTICITY Cara J. Westmark and James S. Malter Department of Pathology & Laboratory Medicine and Waisman Center for Developmental Disabilities, University of Wisconsin, Madison, WI 53705, USA

ABSTRACT The 1990s, “The Decade of the Brain”, resulted in major scientific advances involving brain imaging, gene therapy, brain/robotic interfacing and the neurobiology and molecular biology of learning and memory. However, despite these critical insights, we still do not know exactly how thoughts or memories are formed or stored in the brain, which leaves much exciting research for the twenty-first and probably centuries to come. This review will elaborate on recent advances in the field of protein biosynthesis as related to synaptic plasticity. We will discuss the molecular players (RNA binding proteins and neuronal mRNAs), the signal transduction pathways that have been implicated in learning and memory and how localized translation of selected mRNAs is involved in synaptic plasticity. We will also discuss the pathology of human diseases including Alzheimer’s disease, Fragile X syndrome, autism and Down syndrome, which show altered or diminished protein synthesis dependent synaptic plasticity. Learning and memory are manifested in their highest form in humans and allow for the retrieval of and action on past events. Understanding the pathology of these neurological disorders will elucidate the normal mechanisms of memory formation and storage.

INTRODUCTION Synapses are the junctions between the axon of one neuron and the dendritic spine of another neuron. Electrical signals traveling down axons are converted to chemical

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information and released as neurotransmitters into the synaptic cleft to activate adjacent dendrites. Synaptic plasticity refers to changes in transmission frequency or strength in response to neurotransmitter stimuli. Donald Hebb proposed in 1949 that, “When an axon of cell A is near enough to excite cell B or repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased [1].” If true, changes in synaptic plasticity would be the biochemical basis for learning and memory. Exactly how are experiences, knowledge and skills formed, stored and recalled in the brain? Recent neuroscience research has established an essential role for biochemical changes in the structure of neurons and their synaptic connections. Santiago Ramon y Cajal described dendritic spines in the late 1800s as thorn-like structures that could provide the basis for learning and memory [2]. Dendritic spines project from the dendritic shaft and vary in shape and size. Mature, stable spines have a squat, short mushroom shape and reflect strong synaptic connections whereas immature spines are long and thin and form weaker synaptic connections. Thus, dendritic spines are “dynamic” or “plastic” in nature as their shape, size and number change in response to synaptic activity. A single neuron in the mammalian nervous system may contain ten thousand synapses. Dendritic spines regulate the movement of calcium into the dendritic shaft and organize the complex protein mesh adjacent to the synaptic cleft. This meshwork contains cytoskeleton and hundreds of proteins, and due to its electron dense appearance under electron microscopy, is called the post-synaptic density (PSD). Chemical and electrical stimuli can be transformed into biomolecules by de novo protein biosynthesis at dendritic spines. Activitydependent translation can then alter synapse morphology and synaptic strength. The morphology (shape and size) and density of dendritic spines thus reflects synaptic plasticity and depends on the organization of proteins at the PSD. The PSD is composed of approximately 100 different proteins including neurotransmitter receptors, scaffolding proteins and signal transduction molecules [3,4]. Scaffolding proteins, such as Homer, PSD95 and Shank, connect membrane receptors to downstream signaling molecules and regulate their number, distribution and subcellular location. Glutamate is the primary neurotransmitter at excitatory synapses, which through N-methyl-D-aspartic acid (NMDARs), alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPARs) and metabotropic glutamate (mGluRs) receptors contributes to dendritic protein synthesis [5]. The major downstream signaling pathways that bridge glutamate receptor activation with translation initiation include protein kinase A (PKA), extracellular-regulated kinase of the mitogen-activated protein kinase family (MAPKERK) and mammalian target of rapamycin (mTOR) [6,7]. Thus, interactions between membrane receptors, scaffolding proteins and signal transduction molecules in dendritic spines and spine heads underlie activity-dependent protein synthesis and ultimately the composition of the dendritic spines, generally, and the PSD in particular. Synapse remodeling occurs in response to learning [8] and the addition of new synapses is required for long-term information storage in the brain [9]. The role of protein biosynthesis in learning and memory has been studied in both invertebrate and vertebrate systems [10,11]. The marine mollusk Aplysia californica is a model system to study synaptic function. Aplysia has an intact central nervous system and local protein synthesis in presynaptic sensory

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neurons, but not postsynaptic cells, is required to induce long-term branch facilitation [12]. In mammals, long-term potentiation (LTP) and long-term depression (LTD) are electrophysiological correlates reflecting the cellular basis for learning and memory. LTP is the persistent increase in synaptic strength following high-frequency stimulation of a chemical synapse. LTP is composed of two forms, so-called “early” and “late-phase”. Earlyphase LTP models short-term memory, which lasts minutes to hours and is protein synthesis independent, whereas late-phase LTP (L-LTP) models long term memory (LTM), which lasts from days to a lifetime and requires de novo protein synthesis, gene transcription and the growth of new synaptic connections. Several processes may contribute to LTM, including (1) the sequestration of specific proteins at activated synapses, ie. synaptic tagging [13], (2) local protein synthesis at dendrites, and (3) protein trafficking. LTD is the weakening of a neuronal synapse resulting from strong synaptic stimulation or persistent weak synaptic stimulation. LTD can be elicited through the activation of NMDAR or mGluR. Translation, but not transcription, is required for the maintenance of LTD in the CA1 region of the hippocampus [14]. Thus, de novo protein synthesis is essential for L-LTP as well as LTD, suggesting that increases or decreases in synaptic strength reflect alterations in dendritic protein composition, amount or both. The transport and localization of mRNAs to synaptic sites have been recently reviewed [15-17]. Hence in this review, we will highlight the mechanisms that control the translation of dendritically localized mRNAs. A large number of dendritic mRNAs and mRNA binding proteins (RBPs) have been identified that contribute to these regulatory events. Finally, we will extrapolate to the pathology of neurological disease and in particular to the abnormal synaptic plasticity that occurs in Fragile X syndrome (FXS). We will discuss the role(s) of cis-elements and trans-factors in the translation of amyloid precursor protein (APP) mRNA, which is likely involved in the pathogenesis of Alzheimer’s disease (AD), Down syndrome (DS), FXS, autism and seizures.

TRANSLATIONAL MACHINERY AT DENDRITIC SPINES Dendrites have specific sites specialized for rapid translation [18]. These translational “hot spots” contain all of the required molecules, such as mRNAs, ribosomes, tRNAs, and translation initiation, elongation and release factors (eIF2α, eIF4E, eIF4G, eIF5, eIF6, eEF1α, eEF2, and ERF1), required for protein biosynthesis [19,20]. Neuronal stimulation increases the percentage of spines containing polyribosomes, which precedes enlargement of the PSD [21]. Similarly during LTP, polyribosomes move from dendritic shafts into dendritic spines [21] where they are preferentially located under the base of the spines [22]. Translational machinery and mRNAs localized near synapses allow for modulation of synaptic strength through local protein synthesis. The rate and efficiency of translation is regulated by phosphorylation. The initiation step of translation is the rate-limiting step and is controlled by the initiation factor eIF4E, which is a component of the cap binding complex, eIF4F. eIF4F is a binding partner of 4E-BP1/2 [23]. Stimulation with neurotrophic agonists, for example, brain-derived neurotrophic factor (BDNF), facilitates the translocation of eIF4E into dendritic spines [24]. The cap structure

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(eIF4F) facilitates the attachment of the 40S ribosomal subunit to mRNA. 4E-BPs inhibit translation by hindering eIF4F complex assembly through repressive interactions with eIF4E [25]. The translational repressor 4E-BP2 is necessary for synpatic plasticity and memory in the hippocampus [26]. The phosphorylation of eIF2α regulates the switch from short- to long-term synaptic plasticity and memory [27]. In addition to the translational machinery, dendritic spines contain the organelles necessary for protein processing and membrane insertion. The translation and processing of integral membrane proteins requires organelles of the secretory pathway to provide for proper synthesis, glycosylation, membrane targeting and insertion. Dendritic shafts and spines contain rough endoplasmic reticulum (RER), Golgi apparatus (GA) and associated vesicular transport machinery [28-30]. Hence, all of the mRNA and protein components as well as secretory organelles required for protein biosynthesis, modification and membrane insertion are locally available at dendritic spines. The key questions then are, “what mRNAs and proteins constitute the biological basis of memory,” and “how do their respective cis- and trans-elements interact to mediate mRNA transport and localization to and translation at dendrites?”

DENDRITICALLY LOCALIZED RNAS AND THEIR CIS-ELEMENTS Hippocampal dendrites contain approximately 400 distinct mRNAs coding for membrane receptors and channels, signaling molecules, cytoskeletal and adhesion molecules and proteins involved in membrane trafficking, translation, post-translational protein modification and protein degradation [31-34]. The immediate early gene Arc/Arg3.1, which is an activityregulated cytoskeleton-associated protein, selectively localizes to postsynaptic sites on activated dendrites [35,36]. Several neuronal mRNAs, such as the α-subunit of calcium/calmodulin-dependent kinase II (CaM-KIIα), MAP2 and β-actin, contain dendritic targeting signals in their 3’-untranslated regions (UTRs) [37-39]. While these and other mRNAs localize to dendritic spines, that does not necessarily mean that they are translated in response to synaptic signals [15,32]. Likewise, a wide range of proteins with varied functions are found at dendrites and include MAP2, dendrin, CaM-KIIα, Arc/Arg3.1, G-protein gamma subunit, calmodulin, NMDAR1, glycine receptor alpha subunit, vasopressin, neurofilament protein 68, inositol 3 phosphate (InsP3) receptor, ribosomal protein L7 and PEP1. Protein accumulation could reflect dendritic transport [16,17], dendritic translation [40-43] or both [15,44-47]. The “mRNA targeting hypothesis” suggests that plasticity-related mRNAs are localized/targeted to activated synapses, which allows for local protein synthesis as seen with Arc/Arg3.1 mRNA and protein [35,36]. To discriminate between transport to versus de novo protein synthesis at dendritic sites, the translation of specific dendritic mRNAs has been assessed in synaptoneurosome (SN) preparations. SN are sealed pre- and post-synaptic membranes formed after homogenization of brain tissue in sucrose solution. It is worth noting, however, that SN are not entirely pure dendritic preparations. CaM-KIIα is a dendritically localized mRNA, and if disrupted by 3’-UTR mutation, knock-in mice show

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reduced L-LTP and impairments in long-term spatial memory, associative fear conditioning and object recognition memory [48]. The fraction of CaM-KIIα mRNA associated with polyribosomes in WT SN as well as protein in the PSD is increased after neurotransmitter activation [49]. Therefore, the majority of CaM-KIIα in the PSD originates from local protein synthesis, and not transport from the cell body. The stability, transport and translation of mRNAs are often regulated through protein/mRNA interactions. Cis-elements often found in the 3’-UTR are bound by RBPs, which mediate variable stability, degradation, localization, docking and/or translation. Examples include AU-rich elements (AREs) [50], zip code elements [51], internal ribosome entry sites (IRES) [52] and cytoplasmic polyadenylation elements (CPEs) [53]. Almost 10% of mammalian coding mRNAs contain 3’-UTR AREs, which are composed of reiterated pentamers of AUUUA or simpler U-rich domains. These are commonly found in rapidly degraded mRNAs coding for cytokine, transcription factor, proto-oncogene and receptor mRNAs. HuR/ELAV family members, AUF1, TTP and KSRP (KH-type splicing regulatory protein) among others bind to AREs [54-57]. The HuR/ELAV proteins protect messages from degradation [58-60] whereas AUF1, TTP and KSRP can destabilize mRNAs [56,57,61]. ARE binding proteins (AUBPs) can also regulate translation. For example, competitive binding between AUF1 and TIAR determine translational efficiency of Myc mRNA [62]. RNA zip code elements route mRNAs to specific subcellular sites. These elements are bound by zip code binding proteins, such as ZBP2 whose mutation dysregulates mRNA localization and hence synthesis [63]. Internal ribosome entry sites (IRES) are found in several dendritically localized mRNAs including Arc/Arg3.1, CaM-KIIα, dendrin, MAP2, neurogranin and Fmr-1 [64,65]. The 5’-UTR IRES of Arc/Arg3.1, CaM-KIIα and MAP2 mRNAs enhanced translational efficiency [64]. Multiple cis-elements may co-exist in a single mRNA. For example, the 3’-UTR of PSD95 mRNA has 3 potential translational control elements including a differentially controlled element (DICE), a putative CPE involved in mRNA localization and translation and a G-quartet [66,67]. While a definitive understanding of how information from multiple and varied cis-elements are integrated is not known, the number, location and type of these elements clearly determines the stability, localization and translation of the messages. The function of some of these RBPs, such as AUF1, have not been specifically studied in dendritic locations, but others including the KSRP orthologue MARTA1 and CPEB are active in dendrites [68,69]. RBPs bind to the newly synthesized mRNAs in the nucleus and commence nuclear export to the cytoplasm via ribonucleoprotein complexes (RNPs). Exported RNPs may be translated in the perikaryal somatic region or travel to distant extrasomatic destinations for local on-site translation. Proteins and mRNAs travel along a network of microtubules/microfilaments composed predominantly of polymerized tubulin in cells and actin in dendrites [70-72]. Dendritic spines contain a network of dense, highly branched short actin filaments. RNA binding proteins bind to cis-acting elements in the mRNAs as well as to the cytoskeletal network to mediate transport. A well-studied example is the formation of an RNP including β-actin mRNA, ZBP1 and staufen2, which localizes to dendrites [73-76]. Subcellular mRNA localization and protein targeting and anchoring mechanisms play an important role in the functional organization of the dendrite and are dependent on ciselements, trans-factors and signaling pathways. However, communication between the cell

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body and synapses through RNP trafficking on the microtubule network is not required for protein synthesis dependent L-LTP [77]. Along with mRNA stability and localization, the timing and degree of polyadenylation is an important translational control mechanism. The translation of maternal mRNAs in maturing oocytes can be modulated by CPE-mediated polyadenylation [78]. Not all CPEcontaining mRNAs are polyadenylated at the same time, however. Polyadenylation may occur early in prophase or later at metaphase I. Early cytoplasmic polyadenylation requires CPE and Hex elements, which do not overlap, and late polyadenylation requires at least 2 CPEs with one of them overlapping the Hex element(s) [79]. Twenty-four different configurations of the basic CPE, Hex and PBE cis-elements define different modes of translational behavior with the number and relative position of the elements determining the timing and efficiency of translation [79]. Other RBPs, such as Xenopus Pumilio (Pum), interact with CPEB and are also involved in translational activation and repression. Neuroguidin binds to eIF4E and to CPEB and represses translation in a CPE-dependent manner [80]. Many mRNAs undergo activity-dependent polyadenylation in neurons, which coincides with enhanced translation in synaptodendritic compartments [81]. In addition to mRNA, microRNAs (miRNAs), are found at dendrites. miRNAs are small, non-coding RNAs that copurify with polyribosomes. After binding to complementary sequences, translation is suppressed by DICER-induced cleavage of the target mRNA [82,83]. Eighty-six miRNAs have been identified in mammalian neurons [84]. One example is miRNA-134, which is localized to synaptic sites in hippocampal neurons, and through translational repression of Limk1 mRNA, negatively regulates the size of dendritic spines. BDNF overrides miRNA-134-mediated inhibition of Limk1 synthesis and thus promotes synaptic plasticity [85]. RBPs, such as FMRP interact with miRNAs and components of the miRNA pathway, DICER and argonaute [86]. Thus, miRNAs and the mRNA sequences that they target play an important role in message degradation and translation.

RNA BINDING PROTEINS AND |MRNP COMPLEXES AT DENDRITES mRNA transport and translational repression are tightly coupled. Transport ribonucleoprotein particles (RNPs), RNA granules and processing bodies (P bodies) all contain mRNAs and RBPs that can repress translation [16,45,87]. RNPs function to transport mRNAs from the soma to dendrites in the absence of ribosomes. RNA granules are large assemblies of mRNAs, protein components of the translational machinery and RBPs involved in localization, stabilization and/or translational repression. In RNA granules, translation is repressed but ribosomes are present [47]. RNA granules are found in dendrites and neuronal somata, but formation likely begins in the nucleus because hnRNPs are present [47,88,89]. The best-characterized components include ZBP, FMRP, the double-stranded RNA binding protein staufen, the ELAV-like protein HuR and the DEAD-box RNA helicase RCK/Me31B/Dhh1p [16,90]. The RNA granule protein 105 (RGN105) represses translation, which can be reversed by BDNF [91]. P bodies are ribosome-free, cytoplasmic sites for mRNA decapping and turnover and transient storage of translationally repressed mRNAs

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[45,92]. Drosophila neuronal mRNPs are structurally and functionally related to P bodies and both types of granules contain staufen, FMRP, the non-sense mediated decay protein Upf1p, the RNA-degradative enzymes Dcp1p and Xrn1p/Pacman, the miRNA protein argonaute and the translation repression protein Dhh1p/Me31B [93]. Staufen1 regulates protein synthesisdependent LTP. Decreased levels of staufen1 impaired L-LTP and modified dendritic spine shape from regular to elongated spines, but did not change spine density [94]. Both Me31B/RCK and FMRP are core P-body components [95]. We would like to discuss in more detail the function of two well-studied RBPs, cytoplasmic polyadenylation element binding protein (CPEB) and FMRP. CPEB plays an important role in synaptic plasticity, learning and memory [96]. It contains an RNArecognition motif (RRM) and a zinc finger domain and recognizes cytoplasmic polyadenylation elements (CPEs) in the 3’-UTRs of mRNAs, such as maskin, and thereby modulates translation [96]. CPEB interacts with other RNA binding proteins, including p54 and Pum [97,98]. The Drosophila homologs of CPEB and FMRP interact [99]. CPEB has a prion-like form that has the greatest capacity to stimulate translation of mRNA suggesting that long-term synaptic changes are maintained by this physiological conversion [100]. Thus, CPEB may serve as a tag to mark active synapses. Over-expressed CPEB1 phosphorylation site mutants, Thr171 and Ser177, bind to CPE-containing mRNAs but do not stimulate translation and hence attenuate protein synthesis-dependent L-LTD [101]. This is accompanied by increased spine number and spine length in cerebellar neurons and suggests that CPEB1 is required for activity-driven protein synthesis and synaptic maturation [101]. FMRP is an mRNA binding protein that is absent in individuals with FXS. FMRP is ubiquitously expressed throughout the body, but with highest levels in the brain, gonads and young animals [102,103]. The protein has two heterogeneous nuclear ribonucleoprotein (hnRNP) K homology domains and one RGG box as well as nuclear localization and export signals [104,105]. FMRP is found in polyribosomes, transport particles, RNA granules, stress granules, P bodies and RISC complexes [106-108] where it functions as a repressor of translation [107,109-113]. The hypothesis that the mistranslation of one or multiple target mRNAs causes FXS has driven identification of the protein and mRNA binding partners of FMRP. To date, these include FXR1P, FXR2P, nucleolin, YB1/p50, Purα, staufen, NUFIP1, CYFIP1 and CYFIP2 as well as over 500 mRNAs with the potential to influence synaptic plasticity [109,114-116]. However, as some or even many of these mRNAs have not yet been defined by CLIIP [117], the true number may be lower. FMRP is locally translated at synapses in response to group 1 metabotropic glutamate receptor (mGluR) stimulation [118] or primary cortical neurons [67]. RNA targets of FMRP, such as postsynaptic density 95 (PSD95) and APP, are also rapidly translated in response to the group 1 mGluR agonist, DHPG [67,119]. PSD-95 is a scaffolding protein and its expression increases the number, size and maturation of dendritic spines [120]. APP is an integral membrane protein and the precursor of beta-amyloid (Aβ). FMRP is found in dendrites, dendritic branch points, the origins of spine necks, in spine heads, as well as in all known locations of neuronal polyribosomes where it associates with actively translating polyribosomes [121]. A missense mutation at I304N in the second KH domain of FMRP prevents polyribosome association [122]. FMRP represses the translation of microtubule associated protein 1B (Map1B) [123]. The lack of FMRP in Fmr-1 KO brain results in elevated Map1B levels and abnormally

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increased microtubule stability. Thus, FMRP plays a critical role in cytoskeleton organization. FMRP can function in the translational repression of mRNAs through protein/mRNA interactions [124]. Thus, FMRP plays important roles in mRNP complex formation, translation, dendritic spine structure and synaptic plasticity [125,126].

SIGNAL TRANSDUCTION PATHWAYS THAT MEDIATE MRNA/RBP INTERACTIONS AND PROTEIN BIOSYNTHESIS AT DENDRITES Cell signaling induces a variety of post-translational modifications to RBPs, which could provide a mechanism of epigenetic tagging of the mRNA pool. Epigenetic tagging of the genome is implicated in the formation of long-term memories [127], and it is likely that tagging of neuronal mRNAs and proteins contributes to synaptic plasticity. The pattern of DNA methylation and acetylation in conjunction with alterations in chromatin structure constitutes epigenetic modification [127]. Thus, the DNA/protein interactions involved in chromatin formation, which are regulated post-translationally, constitute an “epigenetic memory”. There are many structural and functional similarities between the nucleic acid/protein interactions important for transcription and translation. For example, the formation of transcription complexes on the promoters of genes targeted for active transcription allows for the recruitment of RNA polymerases and requires non-compacted DNA. Similarly, RBPs bind to and protect mRNAs from degradation as well as prevent translation as part of large mRNPs. Post-translational modifications of those RBPs in response to cell signaling alters the stability or constituents of those mRNPs such that rapid translational activation ensues. As some RBPs compact and translationally repress RNA while other RBPs form active complexes that recruit the translational machinery and polyribosomes to specific mRNAs, RBPs may provide similar functionality as DNA BPs. The stimulation of ion channels on the post-synaptic membrane by neurotransmitters and neurotrophic factors and the downstream involvement and activation of multiple scaffolding proteins and protein kinase pathways constitutes cell signaling and leads to alterations in cellular functions such as de novo protein synthesis [10]. Noradrenaline is an example of a neurotransmitter that is involved in memory [128]. Noradrenaline enhances the expression of monocarboxylate transporter MCT2 through translational activation via PI3K/Akt and mTOR/S6K [129]. The neurotrophic factor NT-3 regulates short-term plasticity through a de novo protein synthesis-dependent pathway at lateral perforant path-dentate granule cell synapses [130]. Glutamate stimulation rapidly increases translation of tissue plasminogen activator (tPA) [131]. Intracellular signaling molecules, such as cAMP, also contribute to synaptic plasticity and de novo protein synthesis. cAMP mediates LTP and LTD at CA3-CA1 synapses [132]. Brain-derived neurotrophic factor (BDNF) is the most well studied neurotrophic factor involved in neuronal cell signaling and LTP. BDNF produces long-lasting enhancement of synaptic transmission in the hippocampus [133]. Dendritic protein synthesis is stimulated by BDNF and completely blocked by anisomycin [134]. BDNF up-regulates 230 proteins in SN

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derived from cultured cortical neurons including those involved in translation [135]. De novo protein synthesis of FMRP, CaM-KIIα and Arc/Arg3.1 are induced in SNs by BDNF or glutamate receptor agonists [118,136,137]. BDNF initiates neuronal cell signaling that results in increased de novo protein synthesis through multiple pathways. BDNF modulates LTP through activation of TrkB receptor tyrosine kinases [138,139]. LTP induced by BDNF causes a rapid, transient phosphorylation of eIF4E and eEF2 and increased expression of eIF4E, which can be blocked by inhibition of MAPKERK [140]. Homer2 is localized to dendrites and locally translated at synapses in response to BDNF [141]. The activation of distinct voltage-gated ion channels by neurotransmitters, neurotrophins and ions are essential for the induction of various forms of LTP and LTD. NMDAR and AMPAR are upstream of LTP while mGluRs play a comparable role in LTD [142-144]. Stimulation of these membrane receptors results in conformational changes, which impact associated scaffolding proteins or kinases. Stimulation of NMDARs activates Src kinase signaling [145]. The Src family tyrosine kinases (Src, Fyn, Lyn, Lyk and Yes) are expressed in the central nervous system and bind to scaffolding proteins of the NMDA receptor complex. Src couples G-protein coupled receptors with downstream signaling molecules via the intermediary cell-adhesion kinase β (CAKβ), which activates Src thereby upregulating NMDAR in CA1 hippocampal neurons [146]. LTP induction can be blocked by inhibiting CAKβ [146]. NMDA receptor activation mediates phosphorylation and activation of CPEB [147]. The group 1 mGluRs (mGluR1 and mGluR5) are localized on the postsynaptic membrane and are excitatory, while group 2 and 3 mGluRs are primarily presynaptic and tend to suppress neurotransmission [148,149]. The group 1 mGluRs that mediate LTD signal through phosphoinositide 3-kinase, mTOR, MAPKERK and PKC [150-153]. Other receptors besides NMDAR, AMPAR and mGluRs are involved in neurotransmission. Stimulation of the μ-opioid receptor induces phosphorylation and activation of Akt and p70S6k and phosphorylation and inactivation of 4E-BP1 and 4E-BP2 [154]. The Akt signaling pathway is associated with neuronal survival while p70S6k, 4E-BP1 and 4E-BP2 are associated with translational control. M1 muscarinic acetylcholine receptor (mAChR) are involved in LTD in the CA1 region of the hippocampus, which is dependent on rapid protein synthesis as well as MAPKERK and mTOR [155]. Stimulation of the retinoic acid receptor (RAR) with all-trans-retinoic acid increases dendritic growth by approximately 2-fold within 30 min of stimulation through MAPK and mTOR pathways and increased dendritic translation [156]. Membrane receptors interact with scaffolding proteins on the inner side of the plasma membrane. RACK1 is an inhibitory scaffolding protein for the phosphorylation and function of NMDAR [157]. PSD-95 is a major scaffolding protein of the post-synaptic density at excitatory synapses, which is enriched in synaptically active neurons and reduced in inhibited neurons, in contrast to other PSD proteins, such as SAP102, Shank and GKAP [158]. PSD-95 can mediate the interaction of NMDAR with downstream signaling molecules. Homer interactions with mGluR are necessary for mGluR-induced LTD and translational activation [159]. The signaling pathways that regulate translation of mRNAs at dendrites has been an area of intense study. Signal transduction pathways that regulate LTP also regulate the translational machinery [160]. The mammalian target of rapamycin (mTOR) kinase

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contributes to long-term fear memory formation in the amygdala [161] and regulates the translation of many key proteins involved in synaptic plasticity. mTOR is a serine/threonine kinase that activates translation by phosphorylating 4E-BP1, which is eIF4E-binding protein [162-164]. Hyperphosphorylation causes dissociation of eIF4E and subsequent initiation of translation [165,166]. mTOR-mediated translation is dependent on PI3K and MAPKERK [167]. Several components of the ribosome recruitment machinery are targets of mTOR, including eIF4B, eIF4G, eIF4E, 4E-BPs, S6K, ribosomal protein S6 and eEF2. Components of the mToR pathway are present in dendrites [168]. Disruption of mTOR signaling by rapamycin reduces hippocampal late-phase LTP induced by high-frequency stimulation or BDNF, both of which require protein synthesis [168]. BDNF regulates the translation of Homer2 in the synaptodendritic compartment through activation of translation initiation via the mTOR-PI3K pathway [141]. PKA, PKC, CaM-KIIα and MAPKERK are intracellular kinases involved in LTP [169,170]. The early and late phases of LTP require activation of cAMP-dependent PKA, but only the late phase requires protein synthesis [171]. Serotonin regulates transcriptionindependent translation in Aplysia through protein kinase C, cAMP-dependent protein kinase (PKA), and a tyrosine kinase [172]. PKMζ is a form of PKC that is necessary and sufficient for maintaining LTP in the hippocampus [173,174]. The expression of pCaM-KII, BDNF, PSD-95 and zif268/egr-1 are significantly increased in the hippocampus of FVB/N mice after behavioral training, which supports the importance of these proteins for neuronal information storage [175]. zif268/egr-1 is necessary for protein synthesis-dependent late-phase LTP [176]. Rapid ocular dominance plasticity requires cortical protein synthesis [177]. Visual experience induces the translation of CaM-KIIα in the visual cortex, which is dependent on NMDAR [178]. CaM-KIIα contains CPEs, which are involved in glutamate-induced translation in cultured hippocampal cells [178]. CaM-KII regulates the synthesis and the phosphorylation of CPEB [179]. Co-activation of both MAPKERK and PI3K-Akt-mTOR after β1-adrenergic stimulation are required for the translation of striatal-enriched protein tyrosine phosphatase (STEP) [180]. Activation of β-adrenergic receptors facilitates the maintenance of LTP through MAPKERK and mTOR at the level of translation initiation [181]. MAPKERK inhibition blocks neuronal activity-induced translation and phosphorylation of eIF4E, 4EBP1 and ribosomal protein S6 [182]. Inhibition of MAPKERK blocks NMDA-induced protein synthesis in dendrites [183]. Group 1 mGluR activation causes phosphorylation of MAPKERK in WT SN and dephosphorylation in Fmr-1 KO SN [184]. Other kinases have also been implicated in synaptic plasticity. For example, p21activated kinase 3 (PAK3) knockout mice exhibit learning and memory deficiencies and impaired late-phase LTP. These mice have a large reduction in the active, phosphorylated form of cAMP-responsive element-binding protein (CREB) [185]. The expression of constitutively active CREB facilitates the late-phase of LTP [186]. Another example is the protein kinase GCN2, which regulates the initiation of translation. GCN2 regulates synaptic plasticity through modulation of the ATF4/CREB pathway [187]. Activated GCN2 induces translation of ATF4, which is an antagonist of CREB. Under basal conditions, GCN2 and eIF2α are phosphorylated, ATF4 levels are high and CREB-dependent transcription is repressed. Phosphorylation of eIF2α selectively enhances translation of ATF4 while inhibiting overall translation [188]. Changes in the phosphorylation status at a single site

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(serine 51) on eIF2α modulates synaptic plasticity and memory storage [27]. Decreased eIF2α phosphorylation facilitates while increased phosphorylation impairs the induction of L-LTP and LTM [27]. Adenyl cyclase activation is involved in LTP and translational regulation at the elongation step [189]. Thus, many proteins are involved in translational regulation and synaptic plasticity with CaM-KII, PKMζ, MAPKERK, Fos, C/EBP and CREB implicated as memory master control molecules [190].

PATHOLOGY OF SYNAPTIC PLASTICITY The morphology and density of dendritic spines is pivotal to synaptic plasticity. In FXS the loss of a single protein, FMRP, results in altered dendritic spine morphology, density and plasticity [191,192]. FXS is the most prevalent form of inherited mental retardation, affecting 1 in 4,000 males and 1 in 8,000 females. This X-chromosome-linked disorder is characterized by moderate to severe mental retardation (overall IQ<70), autistic-like behavior, seizures, facial abnormalities (large, prominent ears and long, narrow face) and macroorchidism [193]. At the neuroanatomical level, humans with FXS and transgenic Fmr-1 KO mice have an overabundance of long, thin, tortuous postsynaptic spines with prominent heads and irregular dilations resembling the spines observed during normal, early neocortical development [194201]. The increased length, density and immature morphology of dendritic spines in FXS suggest an impairment of synaptic pruning and maturation. The study of this disorder and the biological functions of FMRP has generated important information regarding normal dendritic spine development, protein biosynthesis at dendrites and synaptic plasticity. The study of LTD in Fmr-1 KO mice supports the contention that local protein synthesis affects the shape and activity of dendritic spines. DHPG induces a rapid, translation-dependent elongation of dendritic spines [202] and mGluR5 is required for the induction of LTD [203]. mGluR activation induces the internalization of AMPA and NMDA receptors [204,205]. mGluR-triggered LTD is augmented in the hippocampus of Fmr-1 KO mice and does not require new protein synthesis in contrast to WT mice [206]. This data suggests that elevated levels of synaptic proteins in KO increase the persistence of LTD without de novo protein synthesis [207]. Neurons from Fmr-1 KO mice have elevated steady-state levels of Map1B [123] and APP [119]. mGluR-LTD induces a transient, translation-dependent increase in FMRP, which is then rapidly degraded by the ubiquitin-proteasome pathway [208]. Proteasome inhibitors abolish mGluR-LTD in WT mice, and LTD is absent in mice that overexpress FMRP [208]. Neither translation nor proteasome inhibitors blocked the augmentation of mGluR-LTD in Fmr-1 KO mice suggesting that FMRP is rapidly synthesized and degraded and plays a critical role in mGluR-LTD. mGluR-LTD, but not NMDAR-LTD, is substantially enhanced in the hippocampus of Fmr-1 KO mice [206] while LTP is unaffected [209,210]. An example of a specific mRNA that is translationally regulated at dendrites in response to mGluR5 activation is APP mRNA. In 1906, Alois Alzheimer first described the pathology (Aβ plaques and neurofibrillary tangles) and clinical symptoms characteristic of the presenile dementia that now bears his name. Aβ is a proteolytic product of APP, a transmembrane protein that is highly expressed in neurons, localizes to postsynaptic densities, axons,

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dendrites and neuromuscular junctions, and may promote synapse formation and maturation in the developing brain [211-214]. APP is developmentally regulated with maximal expression during synaptogenesis and subsequent decline when mature connections are completed [215,216]. Over-expression of APP and Aβ have been implicated in impaired synaptic function and the synapse loss seen early in the development of AD [217,218]. Disordered synaptic transmission is also a hallmark of other neuronal disorders, such as FXS, autism and DS. APP and/or APP proteolytic products are elevated in all of these disorders providing a possible link between APP, de novo protein biosynthesis, and altered synapse formation and plasticity. Children with severe autism and aggression express >2-fold more secreted APPα than children without autism [219]. Individuals with trisomy 21/DS overexpress APP mRNA by four- to five-fold, deposit extracellular amyloid at a greatly accelerated rate [220], and develop senile plaques twenty to thirty years earlier than normal individuals [221]. Increased translation of APP provides more targets for cleavage by β- and γ-secretases and hence increased Aβ accumulation. A century after the discovery of Aβ, what do we know about the RNA/protein interactions that regulate APP mRNA stability, decay and translation and hence contribute to APP and Aβ production? APP mRNA decay and translation are post-transcriptionally regulated through ciselements in the 5’-UTR, coding region and 3’-UTR of the mRNA and mediated by RBPs that bind to these elements in response to cell signaling. APP mRNAs (70% of APP695 and 50% of APP 751/770) are associated with polyribosomes in rat brain [222], suggesting that translational regulation could play an important role in APP production. There is an average of 8 ribosomes per polyribosome with 1-2 polyribosomes per spine synapse in the hippocampus and gentate gyrus [21] with polyribosomes predominantly located at the bases of spines [21,22]. The length of APP mRNA can be estimated at 1.07 μm (mouse APP695 mRNA) suggesting that only 1 mRNA at a synapse is translated at a time and that there is competition between mRNAs for the translational machinery [223]. Translational regulation of APP mRNA occurs through at least two identified cis-elements. The first identified was a 90-nucleotide cis-element in the 5’-UTR mapping from +55 to +144 from the 5’-cap site. This translational control element is homologous to the iron-response elements (IRES) found in the light and heavy ferritin genes. APP translation is also responsive to IL-1α and IL-1β, but does not alter steady state levels of APP mRNA [224]. Translational control of APP mRNA also occurs through FMRP [119]. FMRP expression increases in the barrel cortex of the rat after unilateral whisker stimulation, a model of experience dependent plasticity [225]. FMRP is phosphorylated N-terminal to the RGG box and phosphorylation/dephosphorylation status of the protein correlates with binding to stalled versus active polyribosomes [226]. The RGG box of FMRP binds to intramolecular G-quartet sequences while the KH2 domain has been proposed to bind to kissing complex RNAs based on in vitro selection assays [116,227]. APP mRNA contains a putative G-quartet cis-element in its coding region (position 825-846 of the mouse sequence) embedded within a guanine-rich domain (nucleotides 694-846). FMRP binds directly to the 5’ end of this guanine-rich region prior to the putative G-quartet sequence [119]. FMRP also protects a 29 base instability element in the 3’-UTR of APP mRNA from ribonuclease digestion [119]. FMRP binds to uridine-rich mRNAs [228,229], and the 29 base element is uridine rich, but FMRP likely protects this region through protein/protein interactions with nucleolin and not by direct binding to the mRNA. No

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kissing complex-like elements have been identified in APP mRNA. Stimulation of WT SN with the mGluR agonist DHPG rapidly releases FMRP from APP mRNA and de-represses translation, an effect not seen in Fmr-1 KO neurons [119]. In KO SN or neurons, APP is constitutively elevated. This data suggests that FMRP represses the translation of APP through mGluR-dependent interactions with APP mRNA. Consistent with constitutively elevated APP levels, there are increased Aβ1-40 and Aβ1-42 in Fmr-1 KO mouse brain. Increased APP and/or APP proteolytic products could provide a common denominator at the molecular level for the impaired synaptic plasticity observed in AD, FXS, autism, DS and epilepsy. FMRP mRNA and protein expression are down regulated as a function of aging in the mouse brain [230], suggesting that repressed transcripts, such as APP, would be upregulated, a well-known phenomenon in animals and humans. APP over-production favors the β-secretase pathway. and alterations in APP processing have a detrimental effect on synaptic plasticity. Expression of the 104-amino acid carboxy-terminal fragment of APP, which contains the Aβ region, impairs spatial learning and maintenance of LTP in mice [231].A recent report indicates that soluble APPα is elevated in the sera of severely autistic children with the highest levels in two children who were also FXS [219]. In addition, all of these neurological disorders are associated with an increased prevalence of seizures. The underlying molecular mechanism(s) that cause seizures are not well understood. Epilepsy in the aging population is a significant, but often overlooked, clinical problem [232], and recent studies indicate that “silent seizures” are a characteristic of AD [233]. Seizures are 6-10X higher AD than in an age-matched population [234,235] with incidence increased in mild-tomoderate AD [236] and in early-onset AD with familial presenilin mutations [237]. 10-22% of AD patients have at least 1 unprovoked seizure [237]. The cumulative lifetime risk of unprovoked seizures is 4.1% in the general population with a higher incidence in the elderly [238]. FXS mice have a high propensity for audiogenic seizures [239], and two mouse models for AD have an increased susceptibility to both chemically induced and audiogenic seizures (AGS) [240,241]. Thus, APP or a proteolytic product of APP could contribute to seizure induction and severity.

CONCLUSION Localized protein synthesis in dendrites is essential for learning and memory. Understanding the mechanisms of protein/mRNA interactions in and localization to dendrites and their roles in selective protein biosynthesis are challenges for the 21st century. Refining our understanding of the mechanism of these pivotal interactions will define the molecular basis of learning and memory. This knowledge will also form the basis for the rational design of therapeutics to treat neurological disorders that result from aberrant protein expression and/or activity at synapses. Synaptic plasticity is required for normal learning and memory and is impaired in disorders such as FXS. Defining the role(s) and regulation of key dendritic proteins, such as FMRP, will be necessary to designing therapies for FXS and related disorders. Localized protein synthesis within individual dendrites regulates synaptic function and neurite outgrowth and guidance. FMRP is synthesized locally in response to synaptic activity and is likely a major player in the selective translation of dendritic mRNAs. In FXS,

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mRNAs that are normally repressed by FMRP, for example APP and Map1B, lose pulsatile expression and are constitutively elevated, resulting in loss of synaptic plasticity. Unraveling the mystery of the “RNA epigenetic memory” as regards FMRP/APP mRNA interactions will likely provide therapeutic targets for the treatment of AD, FXS, DS, autism and seizures as well as a better understanding of the normal processes that contribute to protein biosynthesis in learning and memory.

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[222] Denman R, Potempska A, Wolfe G, Ramakrishna N, Miller DL. (1991) Distribution and activity of alternatively spliced alzheimer amyloid peptide precursor and scrapie PrP mRNAs on rat brain polysomes. Arch Biochem Biophys 288(1): 29-38. [223] Schuman EM, Dynes JL, Steward O. (2006) Synaptic regulation of translation of dendritic mRNAs. J Neurosci 26(27): 7143-7146. [224] Rogers JT, Leiter LM, McPhee J, Cahill CM, Zhan SS, et al. (1999) Translation of the alzheimer amyloid precursor protein mRNA is up-regulated by interleukin-1 through 5'untranslated region sequences. J Biol Chem 274(10): 6421-6431. [225] Todd PK, Malter JS, Mack KJ. (2003) Whisker stimulation-dependent translation of FMRP in the barrel cortex requires activation of type I metabotropic glutamate receptors. Brain Res Mol Brain Res 110(2): 267-278. [226] Ceman S, O'Donnell WT, Reed M, Patton S, Pohl J, et al. (2003) Phosphorylation influences the translation state of FMRP-associated polyribosomes. Hum Mol Genet 12(24): 3295-3305. [227] Darnell JC, Fraser CE, Mostovetsky O, Stefani G, Jones TA, et al. (2005) Kissing complex RNAs mediate interaction between the fragile-X mental retardation protein KH2 domain and brain polyribosomes. Genes Dev 19(8): 903-918. [228] Chen L, Yun SW, Seto J, Liu W, Toth M. (2003) The fragile X mental retardation protein binds and regulates a novel class of mRNAs containing U rich target sequences. Neuroscience 120(4): 1005-1017. [229] Dolzhanskaya N, Sung YJ, Conti J, Currie JR, Denman RB. (2003) The fragile X mental retardation protein interacts with U-rich RNAs in a yeast three-hybrid system. Biochem Biophys Res Commun 305(2): 434-441. [230] Singh K, Gaur P, Prasad S. (2006) Fragile x mental retardation (fmr-1) gene expression is down regulated in brain of mice during aging. Mol Biol Rep [231] Nalbantoglu J, Tirado-Santiago G, Lahsaini A, Poirier J, Goncalves O, et al. (1997) Impaired learning and LTP in mice expressing the carboxy terminus of the alzheimer amyloid precursor protein. Nature 387(6632): 500-505. [232] Murphree LJ, Rundhaugen LM, Kelly KM. (2007) Animal models of geriatric epilepsy. Int Rev Neurobiol 81: 29-40. [233] Palop JJ, Chin J, Roberson ED, Wang J, Thwin MT, et al. (2007) Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of alzheimer's disease. Neuron 55(5): 697-711. [234] Hauser WA, Morris ML, Heston LL, Anderson VE. (1986) Seizures and myoclonus in patients with alzheimer's disease. Neurology 36(9): 1226-1230. [235] Hesdorffer DC, Hauser WA, Annegers JF, Kokmen E, Rocca WA. (1996) Dementia and adult-onset unprovoked seizures. Neurology 46(3): 727-730. [236] Amatniek JC, Hauser WA, DelCastillo-Castaneda C, Jacobs DM, Marder K, et al. (2006) Incidence and predictors of seizures in patients with alzheimer's disease. Epilepsia 47(5): 867-872. [237] Mendez M, Lim G. (2003) Seizures in elderly patients with dementia: Epidemiology and management. Drugs Aging 20(11): 791-803. [238] Hauser WA, Annegers JF, Kurland LT. (1993) Incidence of epilepsy and unprovoked seizures in rochester, minnesota: 1935-1984. Epilepsia 34(3): 453-468.

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In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter IX

SECRETED PROTEIN AND PEPTIDE BIOSYNTHESIS: PRECURSOR STRUCTURES AND PROCESSING MECHANISMS Sergey A. Kozlov∗, Alexander A. Vassilevski and Eugene V. Grishin Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia.

ABSTRACT Protein biosynthesis is rarely restricted to mRNA translation into an amino acid sequence. To yield the mature form, most proteins undergo various posttranslational modifications due to the action of different enzymes. Certain combinations of amino acid residues (primary structure motifs) have been defined to guide the sequence of modifications during the process of precursor protein maturation into the final product. In this chapter, we specifically focus on the secreted polypeptide maturation. For a number of precursor sequences retrieved from UniProt databank, complete sets of enzymes have been identified that execute processing of secreted polypeptides. This finds reflection in the amino acid sequences of the corresponding protein precursors that carry information about the queue of posttranslational events in the form of specific motifs arrangement. Extensive data analysis allowed us to propose a simple set of principals that facilitate effective sequence information handling. Utilization of the proposed principals significantly improves mature protein sequence prediction from available gene structures. We also address the problem of known motif identification and novel motif prediction from large sets of data. A number of proteins are considered in greater detail as examples of the proposed principals utilization conveniences.

∗

Correspondence concerning this article should be addressed to: S.A. Kozlov, [email protected]; tel.: +74953366540; fax: +74953307301.

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I. MAIN STAGES OF POLYPEPTIDE MATURATION PROCESS A wealth of different secreted proteins apart from signal peptide removal upon entry into the endoplasmic reticulum (ER) are subjected to further modifications along the secretory pathway. These modifications may imply a single or multiple steps of the polypeptide chain fragmentation, glycosylation, phosphorylation, acylation as well as other more or less common posttranslational events. In most cases, however, the so-called limited proteolysis due to the action of specific endopeptidases constitutes the crucial step of active polypeptide formation [1-5]. Polypeptides carry important functions in metabolism, immunity, development, signaling, etc., therefore, strict control over their genes’ expression level and maturation process is critical. This “quality control” function is in part performed by proteolytic enzymes [6-11]. Cell surface receptors, serum proteins, enzymes, neuropeptides, hormones, growth factors, and cytokines are among the natural “substrates” of limited proteolysis [12-16]. Accuracy of the enzymes involved in polypeptide maturation is strictly necessary for the organism survival, and flaws in their activity may lead to different pathologies including cancer [9,10,17,18]. Protein precursor amino acid sequence analysis in many cases permits identification of a doublet of positively charged residues exactly preceding the site of polypeptide chain degradation. In 1984, the first enzyme was shown to cleave this kind of site in yeast when αpheromone processing was addressed [1]. The new enzyme was named kexin and was found able to cleave large precursor molecules not only from yeast but also from mammals in vitro. Furin belonging to the same family of subtilisin-like serine endoproteinases became the first discovered mammalian processing enzyme [19]. A large number of related proteins were later found in mammals and named subtilisin-like proprotein convertases (SPC). Several types of SPC that differ both in size and subcellular localization have been described [20]. SPC are irregularly distributed in tissues; the most widespread and best studied remains furin or SPC1 that is found inside cells in the Golgi network, secretory vesicles, endosomes as well as on the cell surface. Throughout, the nomenclature of Schechter and Berger [21] will be followed in designating the cleavage sites of substrates as …P4-P3-P2-P1 ↓ P1’-P2’-P3’-P4’…, etc., with the scissile bond between P1 and P1’ and the C terminus of the substrate on the prime site. In case of SPC, the P2 position is usually represented by positively charged residues Arg or Lys, although Pro was revealed effective by phage display screening of substrates for SPC1 [22]. The P1 position is the most conserved and is most often occupied by Arg, although Lys is also possible [23]. The necessary conditions of proteolysis also include occurrence of another positively charged residue in position P6 or P4 [24,25]. Besides subtilisin-like proprotein convertases specifically recognizing doublets of positively charged residues, a number of other enzyme types are known to participate in limited proteolysis of precursor proteins. In these cases, Arg does not form the scissile bond. Pyrolysin-type subtilisin/kexin isozyme 1 (SKI-1) also known as site 1 protease (S1P) predominantly cleaves proproteins at Leu residues (P1) with Arg in position P4 [26,27]. Neural apoptosis-regulated convertase 1 (NARC-1) also known as SPC9 has not been

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assigned defined substrate specificity, yet a polar residue in position P1 is preferable and a hydrophobic stretch in the P5-P2 region is thought essential [28,29]. Specific enzymes of plant origin that perform limited proteolysis have also been described. These enzymes have been shown to play important roles in processes of plant development and storage protein hydrolysis. Vacuolar processing enzymes (VPE) are cysteine proteinases that have been found to selectively cleave vacuolar proteins such as legumin-type globulins (12S globulins) and napin-type albumins (2S albumins) at Asn residues (P1) in different plants [30,31]. A number of processing subtilases (subtilisin-like serine proteases) have been described: LeSBT1 from tomato [32], C1 from soybean [33] and two highly related saspases from oat [34]. Saspases just like VPE cleave scissile bonds formed by Asn residues and have been implicated in the proteolytic cascade of programmed cell death [34]. Subtilases are utilized by plants on the primary stages of storage protein digestion. C1 protease cleaves Glu-Glu and Glu-Gln scissile bonds [33], whereas LeSBT1 cleaves at Gln residues (P1), although its specificity has not been studied in detail and the recognized motif is thought to include other regulatory residues [32]. Table 1 lists motifs recognized by some extensively studied enzymes that selectively cleave precursor proteins. Table 1. Motifs recognized by processing enzymes Substrate position Origin

Enzyme P6

fungi

P5

K/R

X

SPC2, SPC3, SPC4, SPC6

P2

P1

↓

K/R

R

↓

R

X

K/R/P

R

↓

X

X

K/R

R

↓

R

X

K/R

R

↓

K

X

X

R

↓

SPC5 K

X

K

X

X

R

↓

R

X

X

X

K/R

R

↓

R

X

L/I/V

L/T/K

↓

L

V

F

A

Q

↓

Y/I

V

V

V/L

L/M

↓

VPE

N

↓

saspases

N

↓

subtilase C1

E

↓

subtilase LeSBT1

Q

↓

SPC7 SKI-1 (S1P) NARC1 (SPC9)

plants

P3

kexin furin (SPC1)

animals

P4

P1’

E/N

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Precursor protein polypeptide chain cleavage by convertases usually does not represent the final stage of active molecule maturation. The newly formed fragments in most cases carry excess positive charge at their C-termini that may interfere with the mature molecule function and, moreover, inhibits the process of limited proteolysis by SPC itself. This negative effect is removed due to C-terminal trimming of the fragments by carboxypeptidases (CP) specific to positively charged residues, carboxypeptidase D (CPD) or E (CPE) in most cases [35-37]; the productivity of convertases increases accordingly as was shown in vitro for SPC2 + CPE [38] and in vivo in CPE-defective knockout mice [39]. Besides C-terminal trimming, gradual stepwise fragmentation of the N-terminal sequence often occurs during polypeptide maturation. One of the most widespread enzymes that catalyzes this process is dipeptidyl-peptidase IV (DPP IV/CD26) that plays a role in regulation (inactivation) of biologically active peptides as well as in polypeptide maturation [40]. The enzyme cleaves off a pair of N-terminal residues Xaa-Pro or Xaa-Ala and the corresponding maturation motifs are usually represented by several tandem dipeptide repeats. Another important process in active molecule maturation is cleavage of the C-terminal Gly residue with simultaneous amidation of the preceding residue. This often leads to formation of a more stable and/or active form of the target molecule. The process is catalyzed by peptidylglycine α-amidating monooxygenase (PAM), a complex of two enzymes that act successively: peptidylglycine α-hydroxylating monooxygenase (PHM) that converts Gly residue into an α-hydroxylated intermediary product, and peptidyl-α-hydroxyglycine αamidating lyase (PAL) that catalyzes glyoxylate cleavage and amide formation [41-44]. As stated above, positively charged polypeptides are inclinable to inhibit proprotein convertases. Many highly basic peptides, for example olygoarginine (5-9 residues), represent a special class of SPC inhibitors [45,46]. Histidine-rich antibacterial peptides from human saliva histatin 3 (32 residues, 22% His) and histatin 5 (24 residues, 33% His) are able to inhibit convertases like furin and SPC7 whereas serve substrates for SPC3 [47]. Nevertheless, a great number of biologically active polypeptides are known to carry large positive charge with positively charged residues being indispensable for their function. These polypeptides are mainly represented by antimicrobial peptides and toxins. Due to their high activity and possible toxicity for the producing cells these molecules are usually produced in the form of inactive precursors with auxiliary stabilizing and protective fragments. Specialized convertases are needed to correctly cleave such Arg/Lys-rich polypeptide chains without unwanted fragmentation of the mature active molecules. In certain cases subtilisin-like convertases are utilized for the cause. For example, some bacterial and viral protein toxins such as anthrax toxin protective antigen, diphtheria toxin, clostridial α-toxin and hemagglutinin of a virulent avian influenza virus are known to get activated by SPC after their interaction with the target cell and/or endocytosis [6,48-50].

II. PRECURSOR AMINO ACID SEQUENCE ENCODES THE MATURATION PATHWAY The advent of powerful tools of bioinformatics and public databases of nucleotide and protein sequences forms the modern basis of protein maturation pathways investigation.

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Comparison between mature polypeptide sequences obtained experimentally and the corresponding genes enables identification of all stages of posttranslational modification. Conversely, given that all possible maturation events are known and the corresponding motifs of amino acid sequence established, prediction of active molecule structures from gene becomes reliable. This approach is illustrated by two examples – pro-opiomelanocortin (POMC, P01189), precursor of a number of hormones in humans [51], and prepromelittin (P01501), precursor of melittin, the principal component of the honeybee venom [52] (Figure 1). The primary cleavage of a secreted polypeptide precursor takes place cotranslationally. The leader peptide is cleaved off by the signal peptidase associated with the ER translocon. The widely used SignalP 3.0 program (available at www.cbs.dtu.dk/services/SignalP/) offers a robust method of signal peptide prediction. The next step of limited proteolysis is performed by different convertases that are characterized by a common recognition motif (K/R)-Xn-(K/R), where X – any residue except Cys; n = 0-4. A strong preference for Arg in the last position and n = 0 give the more common doublet motif (K/R)-R. In the given example, POMC has 9 such motifs (the identified cleavage sites are marked with red vertical arrows in Figure 1). Due to differential convertase specificity, however, formation of longer fragments corticotropin and β-lipotropin as well as shorter fragments (α-melanotropin, corticotropin-like intermediary peptide, γ-lipotropin, β-melanotropin, β-endorphin) is achieved. The newly formed molecules that still carry the convertase recognition motifs are subsequently trimmed C-terminally due to the action of CP (basic residues are cleaved off, blue left arrows in Figure 1). The peptides are also trimmed N-terminally by DPP (shown for melittin precursor, blue right arrows in Figure 1). Finally, PAM converts exposed C-terminal Gly residues into amide groups (red left arrows in Figure 1).

Figure 1. Precursor primary structure defines the maturation process. Amino acid sequences of proopiomelanocortin (P01189) and prepromelittin (P01501) are shown. Mature active molecules are marked with rectangles; convertase recognition motifs are shown in bold and the corresponding cleavage sites are marked with red vertical arrows. Residues cleaved off by dipeptidyl-peptidase are marked with blue right arrows; by carboxypeptidases, blue left arrows; by peptidylglycine α-amidating monooxygenase, red left arrows.

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To sum up, the primary structure of precursors not only specifies the set of processing enzymes but also defines their order of action.

III. NOVEL MOTIFS OF LIMITED PROTEOLYSIS In a large number of deduced amino acid sequences of precursor proteins the classical convertase-recognition motifs cannot be identified, although the N-terminal residue of mature molecules is known from experiment. For example, this is true for many toxins and antimicrobial peptides. It is obvious that processing is carried out by some specific endoproteolytic enzymes that have not been identified yet. The large information content, however, indicates a wide distribution of novel processing motifs and therefore suggests existence of the predicted enzymes in different organisms. In most precursors of spider toxins, the P1 residue is Arg, and one or more Glu residues are found in the P4-P2 region. This motif was named Processing Quadruplet Motif (PQM) [53]. It was later discovered that the same motif is found in other unrelated polypeptide precursors and should be extended to further include positions up to P6. A second similar motif was identified that also specifies polypeptide cleavage at Arg (P1) but has one or more Glu residues in the P1’-P5’ region. By analogy, this motif was named inversed Processing Quadruplet Motif (iPQM) [54]. Examples of precursors processed at PQM and iPQM are shown in Figure 2.

Figure 2. Novel motifs PQM and iPQM in polypeptide precursors. Amino acid sequences of precursors of ω-agatoxin IA (P15969) and acrorhagin II (Q3C256), and maximins-S type A precursor (Q5GC94) are shown. Mature active molecules are marked with rectangles; PQM and iPQM are marked with large rose right arrows and large blue left arrows, respectively, the corresponding cleavage sites are marked with red vertical arrows. Residues cleaved off by carboxypeptidases are marked with blue left arrows; by peptidylglycine α-amidating monooxygenase, red left arrows.

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Protein precursor cleavage at PQM/iPQM can result either in mere pro-sequence separation, or in extended polypeptide fragmentation. The latter case includes formation of a number of mature chains that can either be held together by disulfide bridges (ω-agatoxin IA in Figure 2) or represent independent functional molecules (maximins in Figure 2). In a number of cases, the PQM/iPQM contains a basic residue in position P2 that corresponds to the kexin recognition site. However, the lack of additional basic residues in the P4/P6 positions (Table 1) and the episodic character of such dibasic motif occurrence render processing of the corresponding precursors by SPC of a known type highly improbable. The common feature of the new motifs and the conventional convertase recognition sites is the high selectivity for Arg in the P1 position. It could be proposed that the predicted new types of processing enzymes are structurally related to subtilisin-type convertases. The name protoxin convertases (PTC) is suggested to describe the new type enzymes since the new motifs most often occur in precursors of molecules that exhibit toxic functions (neurotoxins, cytolytic peptides, etc.). Although a slim possibility exists that the same enzyme recognizes both PQM and iPQM, joint operation of a pair of enzymes – PTC “direct” and PTC “inversed” – seems more reasonable. The subcellular localization of PTC might differ from that of SPC. It is probable that toxin processing takes place in specific vesicles, or even extracellularly. In the latter case, both PTC and toxin precursors could be secreted into the gland duct. As discussed above, excess positive charge of the polypeptide chain has a negative effect on SPC activity. However, many active molecules rely on this feature and their highly basic nature is indispensable for their function. Therefore, the predicted PTC bridge the gap and are suggested to play a leading role in processing of precursors of basic molecules.

Figure 3. Complex precursor processing. The chart shows processing of two types of precursors: those containing the conventional R(K)toR motifs by SPC and those with the symmetrical EtoR/EafterR motifs by predicted PTC.

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IV. REGULAR AND SYMMETRICAL MOTIFS OF LIMITED PROTEOLYSIS Most processing motifs identified to date have an Arg in the P1 position. In case of SPC, another basic residue, Arg or Lys, is located upstream up to position P6. In order to simplify primary structure analysis, the term “arginine cleavage by basic control” or R(K)toR in abbreviated form was introduced to describe this set of motifs [54]. Following this principle, processing of precursors of a number of signaling molecules, neuropeptides and hormones, such as insulin, gastrin, endorphins, enkephalins, corticotropins, etc. occurs [55-58]. In case of the predicted PTC, the correct Arg-Xaa scissile bond is defined by a Glu residue located upstream up to position P6 for PQM and downstream up to position P5’ for iPQM. By analogy, these motifs were termed “arginine cleavage by glutamic acid control” [54]. Since these motifs are actually symmetrical with respect to the P1 residue, they have the short names EtoR and EafterR. The symmetrical nature of the EtoR/EafterR motifs has interesting consequences that are most evident in the structure of the so called complex precursor proteins [59] that get processed into a number of active molecules (Figure 3). The resultant mature polypeptides are usually relatively small and may be functionally similar as well as have distinct functional properties. For example, the precursor of the neurotensin-like octapeptide xenopsin is also processed into the linear antimicrobial peptide XPF (xenopsin precursor fragment) [60]; another example is the maximins-S type A precursor shown in Figure 2. By convention, the amino acid sequence of polypeptide precursors can be split into two parts, the target mature functional part and the “ballast” auxiliary part. In many cases the biological role of the auxiliary part is equally important and can be regulatory, inhibitory, structural, etc. One of the most important functions of the auxiliary part is to ensure correct folding, trafficking and processing of the functional part. Limited proteolysis motifs are usually located in the “ballast” part of the precursor polypeptide chain. In case of the R(K)toR motif recognition, the corresponding amino acid residues are removed from the N-terminus of the newly formed mature chain, but can be (sometimes partially) retained at the C-terminus. The symmetrical EtoR/EafterR motifs are typically present in pairs: the EtoR motif is always found in the N-terminal part of the precursor with respect to the mature sequence, whereas the EafterR motif always resides in the C-terminal part. This characteristic motif arrangement secures removal of the auxiliary amino acid residues within the “ballast” fragments. Following the final stage of maturation, the active molecules contain no additional “unwanted” residues (Figure 3).

V. PROCESSING ENZYME TYPE CAN BE PREDICTED FROM THE PRECURSOR PRIMARY STRUCTURE Precursor amino acid sequence analysis to locate the motifs of limited proteolysis and divide the functional and auxiliary parts does not always unambiguously determine the type of the processing enzyme. For example, the P6-P5’ region can simultaneously contain both

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the R(K)toR and EtoR/EafterR motifs (Figure 4). In other words, both Arg/Lys and Glu residues can be found in close proximity to the Arg residue in the P1 position. If it is a complex precursor with several processing sites then it is logical to assume that the same type of enzyme is utilized to cleave all scissile bonds. If all of the processing motifs are ambiguous, the amino acid sequence of the mature product should be addressed. Whereas the “ballast” auxiliary part can contain any number of processing sites and get cleaved into any number of fragments, the target mature functional part should be virtually devoid of such motifs in order to escape possible undesirable proteolysis and retain structural integrity.

Figure 4. Primary structure analysis of polypeptide precursors. Pro-opiomelanocortin (P01189) and precursors of PBAN (P09971), insulin (P01308), gomesin (P82358), apamin (P01500), huwentoxin III (P61103), imperatoxin I (P59888), latarcin 4a (Q1ELU5), magainin (P11006) and toxin Am 1 (P69929) are considered. In each case, partial amino acid sequences that contain the indicated processing sites and the motifs of limited proteolysis are shown. The split sites located in the analyzed sequences are shown inside the corresponding mature chains. Compact fold stands for mature polypeptide sequence containing a number of Cys residues and able to form a closely packed structure. Ballast peptides represent the auxiliary part of the precursors removed during maturation.

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Mature polypeptide sequence analysis reveals the presence of “unwanted” convertase recognition motifs that could be cleaved during biosynthesis; these motifs were named “split sites” [54]. The final choice of the processing enzyme type should be made on the basis of absence of the corresponding split sites in the mature chain(s). Quite often, however, when the mature product represents a closely packed structure, stabilized by disulfide bridges for instance, the possible processing motifs – split sites – are buried and protected from cleavage. One of the most evident examples is the structure of polypeptide neurotoxins. The closely packed structure named “compact fold” is most probably stable to limited proteolysis even if it contains a split site. Moreover, incorporation of split sites into the mature sequence might have a certain “quality control” function: incorrectly folded mature products will have such sites exposed and accessible to proteolysis. A totally different situation is seen in case of short linear (no Cys residues) peptides or molecules having extended loops: the split sites are always exposed and the type of the processing enzyme can be deduced directly. Assigning the correct type of limited proteolysis as a result of the known precursor sequences analysis has practical value and can be utilized to predict mature sequences. A closer attention should be paid to the possibility of occurrence of multiple mature chains in a single precursor. The evolutionary rationale often leads to complex precursor design where all mature sequences are difficult to infer. In this case the regular R(K)toR and symmetrical EtoR/EafterR motifs location allows a detailed analysis to predict mature polypeptide sequences. An interesting family of single-chain linear insectotoxins was discovered, each member consisting of a pair of typical short linear cytolytic peptides linked together by a mutated EtoR motif [61]. The lack of the key Arg residue in the P1 position abolishes the polypeptide chain fragmentation and the toxins are suggested to represent an example of complex precursor evolution towards a more simple structure with novel functions.

VI. POLYPEPTIDE PRECURSOR PRIMARY STRUCTURE ANALYSIS Polypeptide amino acid sequences were retrieved from the fully annotated entries in the Swiss-Prot section of the UniProt Knowledgebase. In total, 39,903 sequences of polypeptide precursors from different organisms were found in UniProtKB/Swiss-Prot (as of January 2008). Among these, 6,571 sequences from multicellular organisms were preproproteins (or prepropeptides) with one or more pro-sequences and were further inspected to locate the motifs of limited proteolysis recognized by furin-type convertases SPC and predicted PTC, as well as DPP, CP and PAM. 5,168 sequences were identified as simple precursors with just one mature chain and at least one pro-sequence (“ballast” peptide). The auxiliary “ballast” part may be located both N- and C-terminally. 770 and 109 precursors were found to contain the R(K)toR and EtoR motifs, respectively, and 407 sequences contained both motifs. These 407 sequences were inspected in greater detail. The split site and compact fold analysis assigned 102 sequences to the R(K)toR motif, and 65 sequences to the EtoR motif. In summary, primary structure

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analysis of simple precursors identified 872 R(K)toR motif-containing, 174 EtoR motifcontaining sequences; 240 sequences could not be assigned a preferable motif. 908 sequences were found to contain two mature polypeptide chains (heavy + light chains of a single molecule, active component + peptide of unknown function, or two active components) and were named “binary” precursors. In each sequence, four possible cleavage sites were examined: N-terminal with respect to the first mature chain, both N- and Cterminal in the fragment between the mature chains, and C-terminal with respect to the second mature chain. The EtoR/EafterR symmetrical motifs were additionally checked to reside inside the “ballast” part; as described above, this was not needed in case of the regular R(K)toR motifs. The processing type was reliably assigned to the sequences with all four sites suiting the described conditions. In total, 446 “binary” precursors were identified as R(K)toR motif-containing, 19 as EtoR/EafterR symmetrical motif-containing and 69 sequences could not be assigned a preferable processing type. 495 sequences were complex precursors processed into three or more mature polypeptide molecules. Among these, the ice-structuring glycoprotein precursor (P24856) contains 46 annotated mature chains, whereas the most composite precursor processed by convertases – LWamide neuropeptides precursor from a sea anemone (Q16992) – contains 36 annotated mature peptides. The sequence analysis was carried out as described above for the “binary” precursors, the total number of the analyzed sites equaled the number of mature chains multiplied by 2 (to inspect both N- and C-terminal processing events). A fairly common feature of such extended precursors was that although a great majority of mature chains were flanked by specific processing motifs, one or several mature sequences were not. One explanation is that some of the annotated mature molecules were only predicted from similarity and not isolated experimentally. Another possibility is that additional processing events under the action of unknown enzymes are operating in these cases. As a result, 203 complex precursors were found to get processed at R(K)toR motifs, 9 sequences at EtoR/EafterR motifs, and 39 sequences were ambiguous. The primary structure analysis revealed that for the majority of known active mature polypeptides the corresponding precursors are processed by SPC at the R(K)toR motifs (further referred to as type 1 maturation). Another group is formed by precursors that are processed by predicted PTC at the EtoR/EafterR motifs (type 2 maturation). A number of members from the second group are listed in Table 2. Uncommon maturation motifs have been noticed earlier for some precursor polypeptide sequences. Thorough investigation of the type 2 maturation was performed for the first time in the present work. It was not noticed before that the specific EtoR/EafterR motifs were present not only in toxin precursors. The analysis revealed that apart from neurotoxin precursors (51 spider toxin precursors and 10 conotoxin precursors annotated in UniProt), diverse precursors of antimicrobial peptides (37 precursors from spiders, insects, fish, amphibians and mammals), different types of enzymes (41 proenzymes mainly from spiders, insects and mammals), neuropeptides and hormones (48 proproteins mainly from mammals) and some pore-forming toxins from marine organisms (4 from sea anemones and 1 from cone snails) all carry the EtoR/EafterR maturation motifs.

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Table 2. Some polypeptide precursors containing EtoR/EafterR motifs Source organism taxonomy

Mature polypeptide

Reference

Activity

Name

Amphibia

antimicrobial peptides

brevinin, dermaseptins, magainins, ranatuerin

[62-65]

Anthozoa

phospholipase A2

AcPLA2

[68]

Anthozoa

pore-forming agents

Cytolysins, equinatoxins

[66,67]

Arachnida

antimicrobial peptides

cyto-insectotoxins, latarcins

[59,61]

Arachnida

neurotoxins

omega-agatoxin, BmCa-1, huwentoxins, neurotoxins Ph3X, plectoxins

[98,102105]

Arachnida

phosphodiesterases

dermonecrotic proteins

[106]

Arachnida

phospholipase A2

phaiodactylipin

[97]

Aves

regulatory protein

inhibin beta A

[73]

Aves

structural protein

fibrinogen

[72]

Crustacea

neurohormone

mandibular organ-inhibiting hormone

[74]

Echinoidea

neuropeptides

exogastrula-inducing peptides

[99]

Gastropoda

neurotoxin

T-1-conotoxin

[94]

Gastropoda

pore-forming agents

echotoxins

[95]

Insecta

antimicrobial peptide

lebocin

[100]

Insecta

neuropeptides

AeaHP, leucokinin

[79,80]

Insecta

non-toxic compound

secapin

[71]

Insecta

phenoloxidase

PO 2

[101]

Insecta

phospholipase A2

Api m I

[70]

Insecta

protease

trypsin iota

[78]

Mammalia

antimicrobial peptide

defensin-related cryptdin-6/12

[93]

Mammalia

GDNF family receptor

GFR-alpha-4

[92]

Mammalia

hormone

insulin-like growth factor II

[86]

Mammalia

interleukin

IL-1 alpha

[87]

Mammalia

neuropeptides

galanin-like peptide, neuropeptide S

[90,91]

Mammalia

proteases

acrosins, elastase, granzyme A

[82-85]

Mammalia

regulatory proteins

ghrelin, osteocrin, obestatin

[88,89]

Mollusca

pheromones component

enticin

[69]

Pisces

antimicrobial peptides

moronecidins

[75]

Pisces

hormone

C-type natriuretic peptide 1

[76]

Pisces

kininogenases

natterins

[77]

Polychaeta

antimicrobial peptides

arenicins

[81]

Trematoda

peptidase

hemoglobinase

[96]

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Figure 5. Maturation motifs in precursors grouped according to mature molecule functions. The numbers of precursors with the R(K)toR maturation motifs (green bars), the EtoR/EafterR maturation motifs (blue bars) and ambiguous (cyan bars) are indicated above the corresponding bars. AMP – antimicrobial peptides.

As was noted above, type 1 fragmentation and the corresponding R(K)toR motifs vividly prevail. The analyzed sequences were grouped according to the mature product function. Figure 5 shows the occurrence of the type 1 vs. type 2 maturation motifs inside six groups of precursors of molecules with certain functions. Type 1 R(K)toR motif is predominant in each group. The type 2 EtoR/EafterR motif-containing sequences constitute a large part of precursors for antimicrobial peptides and cytolytic toxins only; notably, together with the unassigned sequences they outnumber the conventional R(K)toR-containing precursors. It was also found that no more than one third of known toxins and even a smaller fraction of enzymes and regulators (neuropeptides and hormones) follow type 2 maturation. For four groups of precursors with a certain mature product function diagrams showing maturation motifs distribution among taxonomic groups of organisms were constructed (Figure 6). In precursors of antimicrobial peptides and cytolytic toxins, type 2 fragmentation prevails in most animals with the exception of insects and mammals with the classical type 1 maturation. To date, most antimicrobial peptide precursors have been described from amphibians, numerous active mature molecules are found in skin secretions [107,108]. Both simple and complex precursors have been annotated, and it seems more likely that processing is carried out at type 2 EtoR/EafterR motifs. The same stands for precursors from sea anemones, fish and gastropods, although current available information for these animals is scarce. Certain differentiation occurs in arachnids with most known precursors from spiders

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carrying type 2 motifs, whereas precursors of scorpion antimicrobial peptides and varisin A1 from acarian hemolymph are processed at conventional type 1 motifs [109-111].

Figure 6. Maturation motifs in animals of different taxonomy. Precursors of (A) antimicrobial peptides and cytotoxins, (B) neurotoxins, (C) enzymes, and (D) regulatory polypeptides were considered. The numbers of precursors with the R(K)toR maturation motifs (green bars), the EtoR/EafterR maturation motifs (blue bars) and ambiguous (cyan bars) are indicated on the Y-axis. Anem. – anemones, Arachn. – arachnids, Amphib. – amphibians, Mamm. – mammals, Gastrop. – gastropods.

In neurotoxin precursors, type 2 maturation is a characteristic feature of polypeptides from spiders, although some protoxins such as magi-4 precursor lack the EtoR/EafterR motifs [112]. Precursors of neurotoxins from scorpions, insects, sea anemones and snakes are all processed at the R(K)toR motif. The most numerous neurotoxins described to date originate from cone snails and according to the performed analysis many precursors follow type 1 maturation. A lot of conotoxin precursors are known to be processed under the action of a different type of enzymes. As an example, Tex31 recognizing a motif of four residues has been isolated and characterized [113]. Precursors of hormones, neuropeptides and other regulatory polypeptides are processed by SPC. Most secreted enzymes also feature type 1 maturation with the exception of those from arachnids. Just as neurotoxin precursors, arachnid proenzymes most often carry the EtoR/EafterR motifs. Two major results were obtained from motif distribution analysis. First, the EtoR/EafterR motifs are characteristic of polypeptide precursors from spiders, and not only of protoxins as suggested earlier [53]. Spiders seem to have deviated from other animals in terms of protein

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processing machinery due to some evolutionary reasons. Second, the type 2 maturation motifs are present in most antimicrobial and cytolytic peptide precursors. Selection for this type of motifs is due to the highly basic nature of the mature products: utilization of the EtoR/EafterR motifs as opposed to the R(K)toR motif allows any combinations of Arg/Lys residues inside the mature chain.

VII. MATURE CHAIN PREDICTION ALGORITHM The set of amino acid sequences analyzed to date is tiny compared to the expected number of polypeptides awaiting discovery and/or investigation and biased towards molecules with certain activity (the more intensively studied and with a higher medical impact) and source organisms of certain taxonomy (those more intensively studied and those with a full genome sequenced). For these reasons novel maturation motifs might be identified in the near future, and many more sequences with the motifs already described will appear. A detailed scheme for analysis of polypeptide precursor primary structure was developed to help identify mature product sequences (Figure 7). This procedure is thought to be effective in terms of mature polypeptide structure prediction from in silico translated nucleotide sequences. The presented scheme summarizes all the described approaches to precursor primary structure analysis. Four consecutive steps of precursor limited proteolysis (both in vivo and in silico) can be distinguished. On the first step, the signal peptide is identified. Next, on the second step, the R(K)toR and EtoR/EafterR motifs are located. If the sequence contains both type 1 and type 2 maturation motifs, a closer inspection of the sequence with identification of cysteine-rich regions (presumably forming a compact fold) and possible split sites is needed. The final decision between SPC or PTC type of fragmentation is then made and the probable processing sites are located (it is worth remembering that complex precursors with type 2 maturation carry symmetrical EtoR/EafterR motifs). As a result, on the second step the mature active and auxiliary “ballast” parts are separated. On the third step, N- and C-terminal trimming of the target mature sequences occurs due to the action of DPP and CP. As a rule, basic residues are removed from the C-terminus and repetitive dipeptides Xaa-Pro and XaaAla are cleaved off from the N-terminus. On the last stage, a C-terminal Gly residue (if present) is converted to an amide group by PAM. In the end of such an analysis according to the proposed scheme, the mature polypeptide sequences designed by nature are retrieved. Nevertheless, experimental “wet” verification of the acquired in silico data is always invaluable.

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Figure 7. Secreted protein and peptide maturation in silico. A detailed chart showing four major steps of secreted polypeptide maturation due to precursor proteolytic cleavage and trimming. Step 1, signal peptide removal. Step 2, adequate convertase processing. Step 3, N- and/or C-terminal trimming. Step 4, C-terminal amidation. For each step, sequence motifs that guide the corresponding processing events are indicated.

ACKNOWLEGMENTS This work was supported in part by the Russian Foundation for Basic Research (grant no. 08-04-00454), and the Program of Cell and Molecular Biology of Russian Academy of Sciences.

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[101] Kawabata, T; Yasuhara, Y; Ochiai, M; Matsuura, S; Ashida, M. Molecular cloning of insect pro-phenol oxidase: a copper-containing protein homologous to arthropod hemocyanin. Proc. Natl. Acad. Sci. U.S.A., 1995, 92, 7774-7778. [102] Cardoso, FC; Pacifico, LG; Carvalho, DC; Victoria, JM; Neves, AL; Chavez-Olortegui, C; Gomez, MV; Kalapothakis, E. Molecular cloning and characterization of Phoneutria nigriventer toxins active on calcium channels. Toxicon, 2003, 41, 755-763. [103] Quistad, GB; Skinner, WS. Isolation and sequencing of insecticidal peptides from the primitive hunting spider, Plectreurys tristis (Simon). J. Biol. Chem., 1994, 269, 1109811101. [104] Heck, SD; Siok, CJ; Krapcho, KJ; Kelbaugh, PR; Thadeio, PF; Welch, MJ; Williams, RD; Ganong, AH; Kelly, ME; Lanzetti, AJ; et al. Functional consequences of posttranslational isomerization of Ser46 in a calcium channel toxin. Science, 1994, 266, 1065-1068. [105] Diao, J; Lin, Y; Tang, J; Liang, S. cDNA sequence analysis of seven peptide toxins from the spider Selenocosmia huwena. Toxicon, 2003, 42, 715-723. [106] Tambourgi, DV; de F Fernandes Pedrosa, M; van den Berg, CW; Goncalves-deAndrade, RM; Ferracini, M; Paixao-Cavalcante, D; Morgan, BP; Rushmere, NK. Molecular cloning, expression, function and immunoreactivities of members of a gene family of sphingomyelinases from Loxosceles venom glands. Mol. Immunol., 2004, 41, 831-840. [107] Nicolas, P; Vanhoye, D; Amiche, M. Molecular strategies in biological evolution of antimicrobial peptides. Peptides, 2003, 24, 1669-1680. [108] Simmaco, M; Mignogna, G; Barra, D. Antimicrobial peptides from amphibian skin: what do they tell us? Biopolymers, 1998, 47, 435-450. [109] Johns, R; Sonenshine, DE; Hynes, WL. Identification of a defensin from the hemolymph of the American dog tick, Dermacentor variabilis. Insect Biochem. Mol. Biol., 2001, 31, 857-865. [110] Zeng, XC; Wang, SX; Zhu, Y; Zhu, SY; Li, WX. Identification and functional characterization of novel scorpion venom peptides with no disulfide bridge from Buthus martensii Karsch. Peptides, 2004, 25, 143-150. [111] Dai, L; Corzo, G; Naoki, H; Andriantsiferana, M; Nakajima, T. Purification, structurefunction analysis, and molecular characterization of novel linear peptides from scorpion Opisthacanthus madagascariensis. Biochem. Biophys. Res. Commun., 2002, 293, 15141522. [112] Corzo, G; Gilles, N; Satake, H; Villegas, E; Dai, L; Nakajima, T; Haupt, J. Distinct primary structures of the major peptide toxins from the venom of the spider Macrothele gigas that bind to sites 3 and 4 in the sodium channel. FEBS Lett., 2003, 547, 43-50. [113] Milne, TJ; Abbenante, G; Tyndall, JD; Halliday, J; Lewis, RJ. Isolation and characterization of a cone snail protease with homology to CRISP proteins of the pathogenesis-related protein superfamily. J Biol Chem., 2003, 278, 31105-31110.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter X

THE EFFECTS OF TEMPERATURE ON ECTOTHERM PROTEIN METABOLISM Nia M. Whiteley1,* and Keiron P. P. Fraser2 1

Bangor University, School of Biological Sciences, Bangor, Gwynedd, LL57 2UW, USA 2 British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley road, Cambridge, CB3 OET, USA

ABSTRACT Protein metabolism in ectotherms is strongly influenced by body temperature and thermal history. In many species, rates of protein synthesis increase with temperature up to a species-specific, thermal optimum. Temperature effects protein synthesis by directly influencing the rates of specific biochemical processes involved in the synthesis of proteins, and also by effecting food consumption. In turn, an increase in food consumption will elevate rates of protein synthesis. Animals have evolved the ability to at least partially compensate rates of protein synthesis as ambient temperatures change, by increasing or decreasing tissue RNA concentrations (RNA to protein) and RNA activity (kRNA). However, at polar temperatures, full compensation of protein synthesis does not appear to occur, and ectotherms are only capable of very low rates of protein synthesis. Temperature also has a direct effect on the proportion of synthesised protein that is degraded, with approximately twice as much protein degraded in polar ectotherms as tropical ectotherms. The result of this is that protein growth at temperatures near the lower limits of life is considerably less efficient than at warmer temperatures. The aim of this review is to examine the effects of temperature on protein metabolism in ectotherms from stable thermal environments and those from more variable thermal regimes. Examples mainly from aquatic environments, will be considered at different levels of biological organisation. In this way, the review will cover both temporal and spatial

*

Mailing Address: N. M. Whiteley. School of Biological Sciences. Bangor University, Bangor, Gwynedd, LL57 2UW, UK. Tel.:+44 1248 388080; Fax: +44 1248 370371. Email: [email protected]

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Nia M. Whiteley and Keiron P. P. Fraser changes in protein metabolism in ectotherms, with particular interest in those organisms living at thermal extremes.

INTRODUCTION Temperature is an important environmental variable that has a marked effect on ectothermic animals (invertebrates and lower vertebrates) at all levels of biological organisation. As biological rate processes are influenced by temperature, thermal fluctuations are a particular problem for ectotherms because their body temperatures generally vary with environmental temperature. All metazoan life is restricted to a relatively narrow band of thermal conditions imposed by the freezing point of seawater and the thermal sensitivity of proteins (-1.86 to 40ºC). Within these physical limits, ectotherms experience a tremendous variety of temperature ranges, dictated by the physical properties of their thermal surroundings and their thermal habitats. Differences in sensitivity to temperature are described as variations in thermal tolerances or thermal windows (Pörtner, 2002). The upper and lower critical limits of which are determined by genotype but are subject to phenotypic plasticity. Consequently, ectotherms are adapted by genetic selection to function optimally in their particular thermal niche (Hochachka & Somero, 2002). This means that ectotherms experiencing relatively stable temperatures in their natural environments (stenotherms) are less likely to tolerate temperature fluctuations, for example polar and tropical aquatic ectotherms. Those that are more tolerant of temperature change tend to be temperate aquatic ectotherms or terrestrial ectotherms that naturally encounter variations in temperature (eurytherms), either on a seasonal or diurnal scale. In order to maintain adequate function and activity during temperature changes many ectotherms can compensate biological functions within limits, and acclimate to a range of temperatures in the laboratory, or acclimatize in the wild under the influence of many different factors. The degree of thermal compensation, however, varies tremendously and can differ between species and also between tissues of the same species, also one biochemical pathway may show compensation while others do not (Hochachka & Somero, 2002). The variations in body temperatures experienced by ectotherms and the variability in thermal experiences and responses, provides thermal biologists, attempting to understand the relationship between temperature and biological rate processes, with an almost infinitely variable and highly complex biological system. Protein metabolism is the continuous synthesis and degradation of an animal’s total protein pool, and as such encompasses two important biological rate processes. Soft tissue growth is the result of protein that is retained when synthesis rates exceed degradation rates. As protein degradation is so difficult to measure (cf. Fraser and Rogers, 2007), the majority of ectothermic studies depend on protein synthesis estimates. The main methodology used is the flooding-dose technique which introduces a single flooding dose of labelled and unlabelled amino acids into the intracellular free-pools (Garlick et al., 1980; Martinez, 1987). Changes in protein synthesis rates are estimated from the specific activities of radio-labelled amino acids in both the protein-bound and intracellular free-pools. Temperature is one of the most important factors controlling protein synthesis rates, but much of the protein synthesis work has been carried out on aquatic ectotherms at temperatures raging from 0 to 27ºC

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(McCarthy & Houlihan, 1997; Fraser & Rogers, 2007; Lewis & Driedzic, 2007). Only limited data has been collected from tropical species, and very little is available from terrestrial ectotherms. Consequently most of the information available comes from polar and temperate species where body temperatures are 10 to 37ºC lower than the body temperatures of mammals. Rates of protein metabolism in ectotherms are temperature dependent at a variety of levels of biological organisation, from single cells to tissues and whole organisms, and from single celled organisms to metazoans. The relationship, however, is complex, and it is important to note that there are distinct differences in examining the effect of a range of temperatures on a physiological process in a single species and in making the same measurements across a range of species adapted to differing temperatures (Fraser & Rogers, 2007). For example, the slopes describing metabolic rates of a single species exposed to a range of temperatures are likely to be significantly steeper than a slope fitted to the metabolic rates of a range of species adapted to differing temperatures (Clark & Fraser, 2004). A similar response occurs for whole-organism protein synthesis rates. In the ectotherms studied to date, there is some compensation for low temperatures in the medium to long-term but the relationship varies within and between species, and tissue responses do not always follow that of the whole-organism. Thermal histories (natural thermal environment) and thermal experiences (acclimation versus acclimatization) also make a difference, as does the timecourse of the temperature change (Loughna & Goldspink, 1985). The increase in food consumption with temperature is an added complication because the associated increase in amino acid uptake increases protein synthesis rates at constant temperature (McCarthy et al., 1993; 1994). Consequently it is difficult to determine the effects of temperature in isolation, especially during seasonal acclimatization where temperature doesn’t act alone but interacts with a large number of abiotic and biotic factors. Individual variation can also occur due to variations in size, stage of development and age. This chapter aims to summarise all of this information, to present our current understanding of the effects of temperature on protein metabolism in ectotherms at different levels of biological organisation. We will include examples from ectotherms exposed to a variety of thermal experiences, both in the laboratory and in the field, and the emphasis throughout will be on overall rates of synthesis rather than the synthesis of specific proteins. As ectothermic animals make up the majority of life on earth in terms of biomass and number of species, and as ectotherms are important sources of food for many higher vertebrates, it is important that we understand the fundamental process affecting the ability of organisms to cope with temperature fluctuations. Changes in protein metabolism influence growth rates and ultimately both individual and population performance. Understanding the effects of temperature on protein metabolism is of great interest, in particular with regard to understanding how ectotherms will continue to survive further changes in global temperatures.

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FUNDAMENTAL EFFECTS OF TEMPERATURE ON PROTEIN METABOLISM Rates of protein synthesis in ectotherms generally increase with temperature up to a species-specific thermal maxima, after which they will rapidly decrease (Haschemeyer et al., 1979; Haschemeyer & Mathews, 1983; McCarthy et al., 1999). The rate at which an animal synthesises protein can be regulated in a variety of ways, including; transcriptional control and the concentration and activity of the RNA (Fraser et al., 2007; Hofmann et al., 2005; Mathers et al., 1993; Storch et al., 2005; McCarthy & Houlihan, 1997). As we are focussing on the effect of temperature on overall protein synthesis rates, rather than specific proteins in this chapter, our discussion will concentrate on the regulation of global protein synthesis rates via RNA concentration and activity. RNA concentrations are sometimes expressed relative to fresh weight of tissue (μg RNA.mg-1 fresh weight) or more commonly as RNA to proteins ratios (μg RNA.mg-1 protein), while RNA activity (kRNA) is expressed as mg protein synthesised per mg RNA per day. Measurements of the total RNA concentrations in an organism will include not only ribosomal RNA, but also messenger (mRNA) and transfer RNA (tRNA). With regard to the overall control of protein synthesis rates we are really interested in the concentration and activity of ribosomes, however, mRNA and tRNA only account for ~ 13% of the total RNA measured, therefore total RNA concentrations provide a reasonable proxy estimate of ribosomal concentrations (Sugden & Fuller, 1991). If RNA to protein ratios are compared in ectotherms living at a range of water temperatures the ratio decreases with increasing water temperature (Figure 1; Fraser et al., 2002; Fraser & Rogers, 2007). Likewise if either whole animal, tissue or cellular RNA to protein ratios are compared in individuals of the same species living at differing water temperatures the ratios will tend to be elevated at lower temperatures (Foster et al., 1992; McCarthy et al., 1999; Wagner et al., 2001). It should be noted, however, that food consumption rates in ectotherms, which will also effect RNA concentrations, are also elevated at higher temperatures (McMillan & Houlihan, 1988; Houlihan et al., 1990). It is therefore impossible to fully separate the effects of food consumption and temperature per se on RNA concentrations in ectotherms. Body mass also has a significant effect on RNA to protein ratios, therefore to allow valid comparisons of RNA to protein ratios between species it is important that data are mass standardised as in Figure 1 (Fraser & Rogers, 2007). In bacteria the relationship between ambient temperature and RNA to protein ratios appears less clear. In E. coli there was no significant change in RNA to protein ratios between 25 and 37oC (Farewell & Neidhardt, 1998). RNA activity is temperature dependent and increases with temperature (McCarthy & Houlihan, 1997; Fraser et al., 2002; Fraser & Rogers, 2007). To compensate for the decrease in RNA activity at low temperatures, higher tissue RNA concentrations are maintained. This mechanism appears to be widespread across ectotherms studied to date, although in the Antarctic zoarcid, Pachycara brachycephalum thermal compensation of protein synthesis maybe achieved primarily via an increase in the RNA activity rather than elevated levels of RNA (Storch et al., 2005). However, it appears that full compensation of protein synthesis

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Table 1. Sources of RNA to protein data used to plot Figure 1 Data point label 1 2 3 4 5 6 7 8 9 10 11 12 13

Species

Group

Reference

Limanda limanda Clupea harengus Oncorhynchus mykiss Ctenopharyngodon idella Gadus morhua Dicentrarchus labrax Anarhichas lupus Nacella concinna Saduria entomon Glyptonotus antarcticus Idotea resecata Homarus gammarus Rattus norvegicus

Teleost Teleost Teleost Teleost Teleost Teleost Teleost Gastropod Isopod Isopod Isopod Decapod Mammal

Houlihan et al., 1994 Mathers et al., 1994 McCarthy et al., 1994 Carter et al., 1993 Lyndon et al., 1992 Langar and Guillaume, 1994 McCarthy et al., 1999 Fraser et al., 2002 Robertson et al., 2001a Robertson et al. 2001b Whiteley et al., 1996 Mente et al., 2001 Goldspink and Kelly, 1984

RNA to protein ratio (μg.mg-1)

16 14

8

12

1 5

10

10

7

8

11

6

3 9

4

12 13

2

6

4

2

0

3.2

3.3

3.4

3.5

3.6

3.7

Temperature (1000/K) Figure 1. Mass standardised whole-body RNA to protein ratios plotted against the reciprocal of temperature. All values are standardised to a mass of 160g, the mean body mass of the animals used in the analysis, using a scaling coefficient of -0.26. The scaling coefficient was calculated by fitting a least-squares regression model to the natural log-transformed body mass and RNA to protein ratio data for all species. The plotted regression line was fitted using least-squares regression analysis ( y = -81.5 + 25.0x, r2 = 49%, p<0.05). For sources of data see Table 1.

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Loge mass standardised fractional protein synthesis rate (%.d-1)

rates by elevation of tissue RNA concentrations is not possible at temperatures lower than ~45oC, at which point protein synthesis rates decrease precipitously (Figure 2). At ambient temperatures ranging between 7 and 27oC whole-organism protein synthesis rates do not appear to vary greatly between species. Animals living at low ambient temperatures therefore appear incapable of compensating protein synthesis rates to a level where they can produce proteins at rates comparable to temperate and tropical species.

2

1 6

1

2

5

9 10

4 3

711

0

12 -1

813 -2 -3 0

10

20

30

Temperature (oC) Figure 2. Mass standardised whole-animal fractional protein synthesis rates for a range of marine ectotherms. Each data point represents a single species. The literature source used to produce each data point is listed in Table 2. The fitted regression line (third-power, cubic) is represented by y = 7947 – 6986x + 2047x2 – 200x3, F = 15.71, r2 = 84%, p<0.001.

Not all the protein that an animal synthesises is retained as protein growth, a large proportion of protein is degraded via a range of degradation pathways (Herschko & Ciechanover, 1982; 1998). Proteins are degraded for a number of reasons including; missfolding after synthesis, damage and loss of function, or that they are no longer required. Ambient temperature also appears to have a direct effect on the proportion of synthesised proteins that are degraded (Figure 3). The protein synthesis retention efficiency is the proportion of synthesised proteins that are retained as net protein growth. Animals living at 0oC appear to only retain half as much of the protein that they synthesise as animals living at tropical water temperatures. Similarly, in studies exposing single species to a range of experimental temperatures protein synthesis retention efficiencies decrease at temperatures towards the lower and upper thermal limits of the species (McCarthy et al., 1999; Katersky & Carter, 2007). These findings have important implications for ectotherms living at low ambient temperatures, in particular in polar environments, as not only is their growth constrained by reduced rates of protein synthesis, but in addition, a greater proportion of the protein they synthesise is degraded (Fraser et al., 2007). In turn, inefficient protein growth, as a result of both low rates of protein synthesis and increased rates of protein degradation, will

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Table 2. Sources of whole animal protein synthesis data used to plot Figure 2 Data point label 1 2 3 4 5 6 7 8 9 10 11 12 13

Species

Group

Author

Gadus morhua

Teleost

Salmo salar Anarhichas lupus Hippoglossus hippoglossus Rhombosolea tapirina Pleuronectes flesus Dicentrarchus labrax

Teleost Teleost Teleost

Houlihan et al., 1988a; Houlihan et al., 1989 Carter et al., 1993a McCarthy et al., 1999 Fraser et al., 1998

Nacella concinna Octopus vulgaris Litopenaeus vannamei Homarus gammarus Saduria entomon Glyptonotus antarcticus

Gastropod Cephalopod Decapod Decapod Isopod Isopod

80

14 10

Teleost Teleost Teleost

Carter and Bransden, 2001 Carter et al., 1998 Langar et al., 1993 Langar and Guillaume, 1994 Fraser unpublished data Houlihan et al., 1990a Mente et al., 2002 Mente et al., 2001 Robertson et al., 2001a Whiteley et al., 1996

11

70 4

8

PSRE (%)

60

9

6 1 2

50 40

12

5 7

30 20

3

15 13

10 3.30 3.35 3.40 3.45 3.50 3.55 3.60 3.65 3.70

Temperature (1000/K) Figure 3. The relationship between mass standardised protein synthesis retention efficiencies (PSRE) and the reciprocal of temperature in a range of ectotherm species. The protein synthesis retention efficiency is the percentage of synthesised proteins that are retained as protein growth. The regression line was fitted using least squares regression analysis (y = 449.9-114.9x, r2 = 28.8%, P<0.05). For data sources see Table 3.

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256

limit polar species to slow inefficient growth; a feature of most polar ectotherms (Clarke et al., 2004; Peck et al., 1997). Table 3. Sources of data used in Figure 3, relating protein synthesis retention efficiency and temperature Data point label 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Species

Group

Author

Limanda limanda Gadus morhua Salmo salar Hippoglossus hippoglossus Oncorhynchus mykiss Anarhichas lupus Pleuronectes flesus Ctenopharyngodon idella Dicentrarchus labrax Oreochromis mossambicus Chondrostoma nasus Carassius auratus Homarus gammarus Octopus vulgaris Nacella concinna

Teleost Teleost Teleost Teleost Teleost Teleost Teleost

Houlihan et al., 1994 Houlihan et al., 1988, 1989 Carter et al., 1993 Fraser et al., 1998 McCarthy et al., 1994 McCarthy et al., 1999 Carter et al., 1998 Carter et al., 1993 Langar et al., 1993 Houlihan et al., 1993 Houlihan et al., 1992 Heba, 1992 Mente et al., 2001 Houlihan et al., 1990 This study

Teleost Teleost Teleost Teleost Decapod Cephalopod Gastropod

TEMPERATURE ACCLIMATION AND PROTEIN METABOLISM Acclimation to various temperatures in the laboratory can be used to directly address the effects of temperature on protein metabolism in ectotherms. As stated previously, the relationship between acclimation temperature and rates of protein synthesis is complicated by the increase in food consumption at higher temperatures. McCarthy & Houlihan (1997) termed the combination of various temperatures and changes in food intake as ‘acclimatization’, as the two factors vary simultaneously. Under these conditions, wholeanimal and tissue rates of protein synthesis are lower in cold-acclimatized versus warmacclimatized individuals, when measured at their respective acclimation temperatures (Whiteley et al., 1996; McCarthy & Houlihan, 1997; Robertson et al., 2001a,b). Elevated protein synthesis rates in the warm are linked to elevated RNA activities and the unlimited supply of amino acids (Fauconneau & Arnal, 1985; McCarthy & Houlihan, 1997). When measured at a common temperature, however, protein synthesis rates are higher in coldacclimatized animals due to a compensatory increase in RNA concentrations in the cold (Watt et al., 1988). A similar response occurs in cell-free preparations (Haschemeyer, 1978). Regardless of cold- or warm-acclimatization, protein synthesis rates in whole-organisms, tissues and isolated cells increase exponentially on further exposure to short term changes in temperature (<7 days), rising 2-3 fold every 10˚C increase in temperature due to an

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associated increase in RNA activity (Simon, 1987; Watt et al., 1988; Pannevis & Houlihan, 1992). After this time, further compensatory adjustments take place as shown in the white muscle of carp where protein synthesis rates are less sensitive to temperature change after 4 weeks acclimatization (Loughna & Goldspink, 1985). An exponential relationship between temperature and protein synthesis is also observed in certain tissues when comparisons are made between ectothermic and endothermic species (McCarthy & Houlihan, 1997). This common relationship is dependent on the ectotherms having access to food and being held for many weeks at one specific temperature. RNA activities were the same in both liver and muscle and increased with temperature, but protein synthesis rates were greater in the liver due to higher concentrations of RNA. McCarthy and Houlihan (1997) concluded that a single relationship between ectotherms and endotherms indicates that RNA performance is being directly affected by temperature. Interestingly, similar comparisons between whole animal rates of synthesis show much greater increases in protein synthesis rates between ectotherms and endotherms. For example, the mean whole animal protein synthesis rate for the non-polar ectotherms is estimated by Fraser and Rogers (2007) to be approximately 2.7% day-1 at a mean body mass of 90g and a mean water temperature of 15ºC. In 50g rats (Rattus norvegicus), rates of protein synthesis are estimated to be 31% day-1 at a body temperature of 38ºC (Goldspink & Kelly, 1984). When values are standardised for body mass and the ectothermic value extrapolated to 38ºC, assuming a doubling of the rate for every 10ºC rise in temperature, ectothermic rates of synthesis are still 2.5 times lower than the mammalian value. Lower rates of protein synthesis in ectotherms coincides with lowered rates of metabolism (4 to 5 times lower per g of tissue), lowered mitochondrial concentrations, changes in mitochondrial function, and decreased rates of ion and amino acid fluxes across the cell membranes (Akhmerov, 1986; Brand et al., 1991; Hochachka & Somero, 2002). Consequently whole-animal protein synthesis rates in ectotherms are likely to be restricted by rates of ATP turnover and the transport of substrates into the cells for catabolism and anabolism. It is also possible that comparisons on this scale involve too many uncontrolled variables such as differences in nutritional status, stage of development and life cycle, body size, holding conditions and methodology, plus the fact that protein synthesis rate are tissue-specific and the proportion of tissues with high turnover rates will be greater in endotherms. The high rates of protein synthesis and degradation in the kidney, for example, accounts for a significant proportion of whole-body protein turnover in humans (Garibotto et al., 1997), but not in fish where white muscle with a relatively low rate of synthesis accounts for 58% of body mass (Houlihan et al., 1995). When food supply is restricted to a set ration, or removed completely, two different responses have been observed. In juvenile cod (Gadus morhua) fed a single meal of 3% of body weight, tissue rates of protein synthesis were the same after 6-7 weeks acclimation to 5 and 15˚C indicating complete compensation for the effects of temperature (Foster et al., 1992). In all tissues, cold-acclimated fish had significantly higher total RNA concentrations to compensate for the slower rates of translation. Similar responses were observed in the livers of several fish species, although the data needs to be treated with caution because the feeding status of the fish is unknown (Houlihan et al., 1995). In contrast, whole animal protein synthesis rates in fasting cold-water isopods are directly related to temperature as standardized values increased 3-fold from 0 to 13˚C (Whiteley et al., 2001). It is difficult to

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draw any meaningful conclusions from these two disparate studies and further work is needed to separate the effects of temperature from that of feeding. It is also well known that patterns of protein synthesis in individual tissues do not always follow that of the whole animal, and it might be more important to maintain relatively constant protein synthesis rates in certain tissues to maintain function in the face of temperature change.

SEASONAL CHANGES IN PROTEIN METABOLISM Many terrestrial and aquatic environments experience large seasonal variations in physical and biological factors that in turn may affect ectotherm protein metabolism. Physical factors such as temperature, day length, water availability, salinity and biological factors such as food availability can vary greatly with season, particularly at polar and temperate latitudes (Clarke, 1988). Very few studies have examined the effects of seasonality on ectotherm protein metabolism and it is impossible to separate the effects of seasonally changing temperatures from other factors such as food consumption (Fraser & Rogers, 2007). Typically, in species so far examined, tissue RNA concentrations decrease during autumn, reach a minimum in winter before increasing in spring towards maximal summer values (Båmstedt, 1983; Robbins et al., 1990; Fraser et al., 2002; Fraser et al., 2004; Fraser et al., 2007). Carp RNA synthesis rates and tRNA concentrations have also been shown to be higher in summer than winter, while aminoacyl-tRNAs levels are lower suggesting protein synthesis rates are elevated in summer (Zuvic et al., 1980; Saez et al., 1982). However, seasonal variations in RNA concentrations may not be generic in all ectotherms, Whiteley et al. (2005) demonstrated no seasonal changes in Ligia oceanica whole animal RNA to protein ratios. As winter ambient temperatures are generally lower than summer, it would perhaps be expected to see an increase in tissue RNA concentrations (see above). However, many species reduce their food consumption in winter, which is in turn is likely to counteract any increase in tissue RNA concentrations. When Gadus morhua, were exposed to simulated autumn and winter conditions but fed ad libitum, they had elevated white muscle RNA concentrations, providing evidence that winter field decreases in tissue RNA concentrations are a result of reduced winter feeding (Foster et al., 1993). Protein synthesis rates also show a seasonal pattern with winter protein synthesis rates typically lower than summer rates. In two Antarctic invertebrates, the limpet, Nacella concinna and the sea cucumber, Heterocucumis steineni, winter protein synthesis rates were 52% and 35% lower respectively, than summer values (Fraser et al., 2002, 2004). While protein synthesis rates in the mussel, Mytilus edulis were 3.5 fold higher in summer than winter (Hawkins, 1985; Kreeger, 1995). Seasonal variations in protein synthesis may not, however, occur in all species, Whitley et al. (2005) reported no seasonal changes in Ligia oceanica protein synthesis. Only two studies have reported seasonal protein turnover data for marine ectotherms. In N. concinna rates of protein degradation decreased significantly in winter, in parallel with decreases in protein synthesis rates. The result of this was similar protein synthesis retention efficiencies in summer and winter (Fraser et al., 2007). In contrast, in M. edulis, during spring, protein degradation rates exceeded synthesis rates and the animals lost protein (Hawkins, 1985). During the summer, protein degradation rates were

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very low and protein synthesis was elevated, resulting in very high protein synthesis retention efficiencies. Ectotherms living in cold-temperate and freshwater environments can experience broader ranges of annual water temperatures than their marine counterparts. Some ectotherms survive at the extremes of the temperature range by utilizing metabolic depression to reduce ATP demand. A good example of this is the cunner, Tautogolabrus adspersus, a northern temperate teleost species which remains motionless and without food during the winter when temperatures fall to 0˚C. A decrease in the ambient water temperature from 8 to 0˚C results in the active depression of protein synthesis rates in the liver, white muscle, heart, brain and gills which precedes winter dormancy (Lewis & Driedzic, 2007). A similar response is observed in the muscle tissue of freshwater crayfish, where a reduction in water temperature from 12 to 1˚C results in an exaggerated decline in protein synthesis rates (N. M. Whiteley, unpublished observations). In both cases, the reduction in protein synthesis rates was accompanied by a reduction in RNA content, but in the cunner, recovery from winter dormancy involved an increase in translational efficiency associated with increased activity and feeding (Lewis & Driedzic, 2007). Other freshwater teleosts, such as the salmonids, over winter under various ice formations in lakes and rivers where they prefer sheltered, slow velocity microhabitats and where they refrain from interacting with other individuals or species (Huusko et al., 2007). Although little is known about their associated levels of protein metabolism, juvenile Atlantic salmon migrating seaward early in the season maximized growth by minimizing protein turnover i.e. lowered rates of protein degradation (Morgan et al., 2000). At the other extreme, freshwater fish can also undergo metabolic depression to avoid the direct effects of elevated summer temperatures. The coldstenothermal freshwater gadid, Lota lota, can experience water temperatures above its preferred thermal range in the lowland rivers of central Europe. When temperatures are high, this species decreases its metabolic rate and down regulates aerobic enzymes (Hardewig et al., 2004). Unfortunately, the consequent effects on protein metabolism are unknown but a depression of protein synthesis is likely as feeding rates decline in the summer. Seasonal differences in protein metabolism also occur in juvenile rainbow trout subjected to a simulated global warming scenario in which natural variations in water temperature are increased by an additional and constant +2˚C in controlled, laboratory conditions (Morgan et al., 2001). In the summer, the additional of +2ºC to the natural thermal regime in fish feed to satiation had little effect on protein metabolism until the late summer when protein accretion in the liver and white muscle was reduced (Reid et al., 1995). Protein suppression was caused by an increase in protein degradation rates at constant protein synthesis rates, and coincided with a loss in appetite. In the winter, general rates of protein metabolism in juvenile trout feed to satiation were lower than those recorded in the summer, but the 2˚C increase in water temperature had a remarkable effect on rates of protein turnover in the liver (Morgan et al., 1998). As expected, limitation of the food ration to only 1% wet body weight every 4 days suppressed both metabolism and growth (D’Cruz et al., 1998).

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TEMPERATURE EFFECTS ON THE METABOLIC COSTS OF PROTEIN METABOLISM Protein synthesis is an energetically expensive process typically thought to account for 11-42% of total oxygen consumption in endotherms and ectotherms (Houlihan et al., 1995). However, at present there are relatively few direct measurements of the energetic costs of synthesising proteins and the values that have been reported vary over two orders of magnitude (Bowgen et al., 2007). Only three studies have attempted experimentally to investigate whether the costs of synthesising proteins are temperature dependent (Bowgen et al., 2007; Storch et al., 2003; Whiteley et al., 1996). Storch et al. (2003) found no significant difference in the costs of synthesising proteins in temperate or polar scallops and that the costs measured were similar to minimum theoretical costs of protein synthesis. A further study has demonstrated no significant difference in the cost of synthesising protein in the Antarctic limpet, Nacella concinna, at 0 or 3oC (Bowgen et al., 2007). In addition, comparison of the cost of protein synthesis in a meta-analysis of published cost of protein synthesis data has demonstrated no significant effect of temperature on the energetic cost of protein synthesis in a range of species living at temperatures between –2 and 41oC (Bowgen et al., 2007). Two further studies came to contrasting conclusions on the energetic costs of protein synthesis in Antarctic marine ectotherms. Correlation of respiration and protein synthesis rates in sea urchin embryos (Sterechinus neumayeri) indicated that energetic costs were much lower than the values reported for other ectotherms (Marsh et al., 2001). Direct measurements on the giant Antarctic isopod, Glyptonotus antarcticus, however, indicated much higher energetic costs than temperate species (Whiteley et al., 1996). While differences in methodology and stage of development may account for some of these differences, it is known that experimental estimations are dependent on the type and concentration of the protein synthesis inhibitor used (Bowgen et al., 2007). Further determinations using complimentary inhibitors and experimental regimes are needed to resolve these discrepancies. For example, the marked differences in the costs of proteins synthesis observed between polar and temperate crustaceans by Whiteley et al (1996) is currently being re-examined in marine amphipods distributed along a latitudinal cline. At present it is not known whether the costs of degrading proteins, which occurs via a range of pathways, is temperature dependent (Hershko & Ciechanover, 1982).

CONCLUSION Ectotherms provide an ideal opportunity to study the detailed effects of temperature on protein metabolism. Unlike mammals and birds, body temperatures in ectotherms are at the mercy of their thermal surroundings. Collectively ectotherms show a wide variety of thermal ranges and tolerances, although most of our current understanding on the thermal sensitivity of protein metabolism primarily relies on protein synthesis measurements from cold-water species. Studies to date, however, indicate that protein synthesis rates increase with temperature between individuals of the same species in the majority of ectotherms, but not

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between species at temperatures of 7-27ºC. Compensation for low temperatures occurs during seasonal acclimatization and in response to temperature acclimation at constant food intake in the laboratory. Costs of protein synthesis are estimated to be the same in polar and temperate ectotherms, although two studies suggest otherwise. Much less is known about the thermal effects and costs of protein degradation in ectotherms. Clearly many more studies are needed at all levels of biological organisation to fully identify the effects of temperature on ectotherms.

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Houlihan, D.F., Carter, C.G. and McCarthy, I.D. (1995). Protein turnover in animals. In: Nitrogen excretion and metabolism. (eds. Walsh PJ and Wright PA). CRC Press, Boca Raton, 1995, pp. 1-32. Huusko, A., Grennberg, L., Stickler, M., Linnansaari, T., Nykanen, M., Vehanen, T., Koljonen, S., Louhi, P, & Alfredsen, K. (2007). Life in the ice lane: The winter ecology of stream salmonids. River Research and Applications, 23, 469-491. Katersky, R. S. & Carter, C. G. (2007). High growth efficiency occurs over a wide temperature range for juvenile barramundi Lates calcarifer fed a balanced diet. Aquaculture, 272, 444-450. Kreeger, D.A., Hawkins, A.J.S., Bayne, B.L. & Lowe, D.M. (1995). Seasonal variation in the relative utilization of dietary protein for energy and biosynthesis by the mussel Mytilus edulis. Marine Ecology Progress Series, 126, 177-184. Lewis, J. M. & Driedzic, W. R. (2007). Tissue-specific changes in protein synthesis with seasonal metabolic depression and recovery in the north temperate labrid, Tautogolabrus adspersus. American Journal of Physiology, 293, R474-R481. Loughna, P.T. & Goldspink, G. (1985). Muscle protein synthesis rates during temperature acclimation in a eurythermal (Cyprinus carpio) and a stenothermal (Salmo gairdneri) species of teleost. Journal of Experimental Biology 118, 267-276. Marsh, A. G., Maxson, R. E. & Manahan, D. T. (2001). High macromolecular synthesis with low metabolic cost in Antarctic sea urchin embryos. Science, 291, 1950-1952. Martinez, J. A. (1987). Validation of a fast, simple and reliable method to assess protein synthesis in individual tissues by intraperitoneal injection of a flooding dose of [3H]phenylalanine. Journal of Biochemical and Biophysical Methods, 14, 349-354. Mathers, E.M., Houlihan, D.F., McCarthy, I.D. & Burren, L.J. (1993). Rates of growth and protein synthesis correlated with nucleic acid content in fry of rainbow trout, Oncorhynchus mykiss: effects of age and temperature. Journal of Fish Biology, 43, 245263. McCarthy, I. D., Houlihan, D. F., Carter, C. G. & Montou, K (1993). Variation in individual consumption rates of fish and its implications for the study of fish nutrition and physiology. Proceedings of the Nutrition Society, 52, 427-437. McCarthy, I. D., Houlihan, D. F. & Carter, C. G. (1994). Individual variation in protein turnover and growth efficiency in rainbow trout Oncorhynchus mykiss (Walbaum). Proceedings of the Royal Society of London Series B, 257, 141-147. McCarthy, I.D., & Houlihan, D.F. (1997). The effect of temperature on protein metabolism in fish: the possible consequences for wild Atlantic salmon (Salmo salar L.) stocks in Europe as a result of global warming. In C.M. Wood & D.G. McDonald (Eds.), Global Warming: Implications for Freshwater and Marine Fish (pp. 51-77). Cambridge: Cambridge University Press. McCarthy, I.D., Moksness, E., Pavlov, D.A., & Houlihan, D.F. (1999). Effects of water temperature on protein synthesis and protein growth in juvenile Atlantic wolfish (Anarhichas lupus). Canadian Journal of Fisheries and Aquatic Science, 56, 231-241 McMillan, D.N. & Houlihan, D.F. (1988). The effect of refeeding on tissue protein synthesis in rainbow trout. Physiological Zoology, 61, 429-441.

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Morgan, I. J., McDonald, D. G. & Wood, C. M. (2001). The cost of living for freshwater fish in a warmer, more polluted world. Global Change Biology, 7, 345-355. Morgan, I. J., D’Cruz, L. M., Dockray, J. J. Linton, T. K., McDonald, D. G. & Wood, C. M. (1998). The effects of elevated winter temperature and sub-lethal pollutants (low pH, elevated ammonia) on protein turnover in the gill and liver of rainbow trout (Oncorhynchus mykiss). Fish Physiology and Biochemistry, 19, 377-389. Pannevis, M. C. & Houlihan, D. F. (1992). The energetic cost of protein synthesis in isolated hepatocytes of rainbow trout (Oncorhynchus mykiss). Journal of Comparative Physiology, 162, 393-400. Peck, L.S., Brockington, S. & Brey, T. (1997). Growth and metabolism in the Antarctic brachiopod Liothyrella uva. Philosophical Transactions of the Royal Society of London B, 352, 851-858. Pörtner, H. O. (2002). Climate change and temperature dependent biogeography: systemic to molecular hierarchies of thermal tolerance in animals. Comparative Biochemistry and Physiology, 32A, 739-761. Reid, S. D., Dockray, J. J., Linton, T. K., McDonald, D. G., & Wood, C. M. (1995). Effect of a summer temperature regime representative of a global warming scenario on growth and protein synthesis in juvenile rainbow trout (Onchorynchus mykiss). Journal of Thermal Biology, 20, 231-244. Robbins, I., Lubet. P & Besnard, J.-Y. (1990). Seasonal variations in the nucleic acid content and RNA:DNA ratio of the gonad of the scallop Pecten maximus. Marine Biology, 105, 191-195. Robertson, R. F., El-Haj, A. J, Clarke, A. & Taylor, E. W. (2001). Effects of temperature on specific dynamic action and protein synthesis rates in the Baltic isopod crustacean, Saduria entomon. Journal of Experimental Marine Biology and Ecology 262, 113-129. Robertson, R. F., El-Haj, A. J, Clarke, A., Peck, L. S. & Taylor, E. W. (2001). The effects of temperature on metabolic rate and protein synthesis following a meal in the isopod Glyptonotus antarcticus Eights (1852). Polar Biology, 24, 677-686. Saez, L., Goicoechea, O. & Amthauer, R. (1982). Behaviour of RNA and protein synthesis during the acclimatization of the carp. Studies with isolated hepatocytes. Comparative Biochemistry and Physiology 72B, 31-38. Simon, E. (1987). Effect of acclimation temperature on the elongation step of protein synthesis in different organs of rainbow trout. Journal of Comparative Physiology B, 157, 210-207. Storch, D., Heilmayer, O., Hardewig, I. & Pörtner, H. O. (2003). In vitro protein synthesis capacities in a cold stenothermal and a temperate eurythermal pectinid. Journal of Comparative Physiology B, 173, 611-620. Storch, D., Lannig, G. & Pörtner, H.O. (2005). Temperature-dependent protein synthesis capacities in Antarctic and temperate (North Sea) fish (Zoarcidae). The Journal of Experimental Biology, 208, 2409-2420. Sugden, P. H. & Fuller, S. J. (1991). Regulation of protein turnover in skeletal and cardiac muscle. Biochemical Journal, 273, 21-37.

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Wagner, M.M., Campbell, R.G., Boudreau, C.A. & Durbin, E.G. (2001). Nucleic acids and growth of Calanus finmarchicus in the laboratory under different food and temperature conditions. Marine Ecology Progress Series, 221, 185-197. Watt, P.W., Marshall, P.A., Heap, S.P., Loughna, P.T., & Goldspink, G. (1988). Protein synthesis in tissues of fed and starved carp, acclimated to different temperatures. Fish Physiology and Biochemistry 4, 165-173. Whiteley, N.M. & Faulkner, L.S. (2005). Temperature influences whole-animal rates of metabolism but not protein synthesis in a temperate intertidal isopod. Physiological and Biochemical Zoology, 78, 227-238. Whiteley, N. M., Robertson, R. F., Meagor, J., El Haj, A. J. & Taylor, E. W. (2001). Protein synthesis and specific dynamic action in crustaceans: effects of temperature. Comparative Biochemistry and Physiology A, 128, 595-606. Whiteley, N. M., Taylor E. W. & El Haj, A. J. (1996). A comparison of the metabolic cost of protein synthesis in stenothermal and eurythermal isopod crustaceans. American Journal of Physiology, 271(5), R1295-R1303. Zuvic, T., Brito, M., Villanueva, J. & Krauskopf, M. (1980). In vivo levels of aminoacyltRNA species during acclimatization of the carp, Cyprinus carpio. Comparative Biochemistry and Physiology, 67B, 167-170.

In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter XI

PROTEIN BIOSYNTHESIS: A NEW METHOD FOR FUNCTIONAL EXPRESSION OF SODIUM-DEPENDENT GLUCOSE TRANSPORTER (SGLT) TO STUDY INHIBITION OF TRANSPORT ACTIVITY AND DRUG DISCOVERY Francisco Castaneda Max Planck Institute of Molecular Physiology, Molecular Pathobiochemistry and Clinical Research Laboratory, Dortmund, Germany

ABSTRACT The sodium-dependent D-glucose transporter (SGLT) family is involved in glucose uptake via intestinal absorption (SGLT1) or renal reabsorption (SGLT1 and SGLT2). SGLT plays an important role in the regulation of glucose blood levels. As a result, increasing attention is being focused on SGLT as a drug target for the therapy of diabetes. Therefore, a selective and specific technique for the study of different potential SGLT inhibitors is mandatory. The expression of functional SGLT is regulated by a complex mechanism involving changes in transcription, mRNA stability, and amount of transporter within the plasma membrane. In addition, SGLT expression depends on the state of cellular differentiation of epithelial cells, which can be observed by confluent cell monolayer growth. Therefore, the use of differentiated epithelial cells represents a unique factor required to obtain functional recombinant SGLT protein that can not be reproduced in other cell systems, such as the brush border membrane, oocytes or liposomes. We found that differentiated Chinese hamster ovary (CHO) cells, either stable or transient transfected with a eukaryotic expression vector containing human SGLT1 or SGLT2 gene, expressed functional SGLT in the cell membrane. The extent of hSGLT1 and hSGLT2 expression was evaluated by relative real-time reverse transcription-

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Francisco Castaneda polymerase chain reaction (RT-PCR) quantification, Western blotting, and immunocytochemical analysis. Moreover, functional activity of hSGLT1 and hSGLT2 activity was determined by measuring the sodium-dependent uptake of α-methyl [14C]-Dglycoside. The advantage of the 96-well method we developed is the low amount of radioactive compounds and inhibitory substances required, and its reproducibility. This method represents an initial approach in the development of transport-based highthroughput screening in the search for inhibitors of glucose transport and the development of new antidiabetic drugs.

INTRODUCTION Transport of glucose through the cell membrane depends either on glucose-facilitated transporters (GLUT), or on sodium-dependent glucose transporters (SGLT) [1,2]. GLUT transports glucose down its concentration gradient, while SGLT is driven by a sodiumgradient generated by the Na+/K+-ATPase. SGLT belongs to the sodium/glucose cotransporter family SLCA5 [3]. Two different SGLT isoforms, SGLT1 and SGLT2, have been identified as important regulators of the blood glucose levels [4]. SGLT1 transports glucose as well as galactose, and is expressed both in the kidney and in the intestine, while SGLT2 is found exclusively in the S1 and S2 segments of the renal proximal tubule [5]. As a consequence, glucose filtered in the glomerulus is reabsorbed into the renal proximal tubular epithelial cells by SGLT2, a low-affinity/high-capacity system. Much smaller amounts of glucose are recovered by SGLT1, a high-affinity/low-capacity system found in the distal segment of the renal tubules. In addition to glucose, SGLT also recognizes glucose analogues as a substrate. The role of glucose analogues in inhibiting glucose transport has been well demonstrated in vitro [6,7] and in vivo animal models [8-10]. Inhibition of SGLT activity leads to increased urinary glucose excretion and consequently reduces blood glucose concentration [11,12]. Therefore, inhibition of glucose reabsorption in the kidney, mediated by SGLT, represents a promising therapeutic target for the control of hyperglycemia. For that purpose, expression of functional SGLT proteins is mandatory to analyze different potential inhibitors of the glucose transport through SGLT with the objective to investigate potential targets for the treatment of hyperglycemia and diabetes.

EXPRESSION OF FUNCTIONAL RECOMBINANT SGLT Functional recombinant protein expression requires a complex system in which several important characteristics must be present. These include, cell growth optimization, rapid high cell density growth, sequence of the desired protein, high yield protein expression, and posttranslational modifications among others. There are two main systems for the expression of recombinant proteins, the prokaryotic (bacterial) and the eukaryotic (usually yeast, oocytes or mammalian cell) systems. The selection of one of them depends on the expression vector that will be used to clone the specific cDNA of the desired protein.

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Prokaryotic expression system has been used to analyze the structure of membrane proteins, due to the large quantities of recombinant protein that can be expressed [13]. The prokaryotic recombinant protein expression system has several advantages, including ease of culture and rapid cell growth allowing a fast cloning of cDNA and high levels of expression. Expression of functional membrane proteins; however, is difficult to obtain in the prokaryotic expression system. There are only a few examples in which membrane proteins are functional when expressed in prokaryotic cells [14-18]. The main reason for this problem is that in prokaryotic cells different kinds of posttranslational modifications take place compared to those found in eukaryotic cells. For example, a protein that ordinarily binds to sugars in a eukaryotic cell will be expressed as a bare protein when cloned in bacteria. This alters the activity and the stability of the protein. In addition, proper folding of the protein in the interior of a bacterial does not take place in the same way as in the interior of eukaryotic cells. To avoid this problem, the eukaryotic expression system has been used [19,20]. Different eukaryotic expression systems have been used to express SGLT such as Xenopus laevis oocytes [21-23], COS-7 cells [24], Sf9 cells [25], and Chinese Hamster Ovary (CHO) cells [26].

FUNCTIONAL CHARACTERIZATION OF RECOMBINANT SGLT With the methods and techniques currently used, expression of the cDNA of interest is not difficult. However, to be able to express cDNA as a functional recombinant protein an appropriate system must be used. In addition, functional studies should be performed to confirm the expression of the desired protein. A complete functional characterization of a protein, in this case SGLT, can be obtained using different methods including protein-protein interaction experiments, kinetic analysis, functional studies of the protein (glucose transport activity), and structural studies (including protein crystallization, protein structure and NMR). The activity of SGLT has been studied in native intestinal and kidney tissue [27,28], brush-border membrane vesicles [29,30], proteoliposomes [31,32] and different prokaryotic and eukaryotic systems using rabbit intestinal SGLT [21] transporter, which has been well characterized [33,34]. The combination of different expression systems (i.e, oocytes for electrophysiological characterization, yeast for the selection of mutant proteins with altered functions, and cell cultures for the production of protein for crystallization) has also been used to characterize the function of SGLT. Functional characterization of expressed SGLT protein can be performed by kinetic analysis using electrophysiological methods. Rabbit SGLT1 cRNA expressed in oocytes is one of the most commonly used methods to study the electrophysiological properties of this transporter [30,35], based on the successfully expression of cloned genes in oocytes [36]. Electrophysiological analysis of SGLT expressed in oocytes allow the characterization of steady-state as well as pre-steady-state events associated with SGLT1 function [37,38]. The kinetics of recombinant SGLT in intact cells or membrane vesicles, and reconstituted into proteoliposomes demonstrated similar activity to those determined for

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SGLT in native tissue and oocytes [39,40]. More importantly, proteoliposomes and membrane vesicles of Escherichia coli have been used to determine the functional asymmetry of SGLT1 [41,42]. The forward transport (from outside to inside) depends on a right-side-out orientation of the recombinant SGLT1 in proteoliposomes. In this system, however; a randomly oriented SGLT cannot be excluded. The functional characteristics of the forward and reverse transport modes of the human SGLT1 have been analyzed using plasma membrane vesicles of E. coli expressing recombinant human SGLT1 [43]. Correctly and inverse-oriented vesicles demonstrate the functional asymmetry of hSGLT1. Moreover, the effect of the competitive inhibitor of SGLT phlorizin has been shown to be different in the forward transport than in the reverse mode. The latter demonstrated a low inhibitory effect of phlorizin on glucose transport [43]. Another important factor required for the functional characterization of SGLT is localization of the protein in the plasma membrane. For this purpose, different tags have been included into the expression vectors, such as his, myc and other tags. Localization of taggedproteins can be demonstrated by Western blot or immunohistochemistry [44,45]. TaggedSGLT1 functionally expressed protein in Xenopus oocytes or mammalian cells has been reported [26,46,47]. These tags; however, can interfere with the function of the recombinant SGLT. Studies performed in Caco-2 cells demonstrate that insertion of the vesicular stomatitis virus G protein (VSV-G protein) at the C-terminal domain of SGLT1 interferes with the kinetic properties of the transporter [48]. In contrast, insertion of the myc sequence in the N-terminal domain in COS cells [46,49] and oocytes [47,50] did not alter the function and kinetics of SGLT1. Moreover, a chimera constructed from the last 13 transmembrane domains of human SGLT1 and the N-terminal first transmembrane segment of SMIT, and expressed in oocytes, conserves similar activity to that of SGLT1. This confirms that modifications of the N-terminal domain of SGLT are not associated with functional changes of this protein [51], and hence that the N-terminus is not directly involved in the activity of hSGLT1 [46].

REGULATORY MECHANISMS INVOLVED IN THE EXPRESSION OF FUNCTIONAL RECOMBINANT SGLT Protein biosynthesis is a multi-step process in which transcription and translation are involved. Furthermore, other regulator mechanisms (such as post-transcriptional and posttranslational modifications of the synthesized protein) are required for the production of a functional protein. The expression of SGLT is regulated by several mechanisms including changes in transcription [52,53]), mRNA stability [54], effect of transcriptional factors, such as the hepatocyte nuclear factor 1α (HNF1α) [55], intracellular trafficking [56], and transporter activity [50]. In addition, SGLT expression depends on the state of differentiation of the epithelial cells in which SGLT is expressed. The regulatory mechanisms involved in the expression of a functional SGLT are shown in Figure 1. The most important regulatory factors associated with the expression of a functional expression of SGLT include post-translational modifications, trafficking, appropriate localization at the cell membrane, and cell differentiation.

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Figure 1. Regulatory mechanisms involved in the expression of a functional recombinant SGLT.

Post-translational Modifications Post-translational modifications, such as glycosylation and protein folding are required for the expression of a functional recombinant protein. As mentioned before, posttranslational modifications are not carried out in the same manner in prokaryotic cells as in mammalian cells. Glycosylation is required for an appropriate processing, membrane targeting, protein stability and/or function of the expressed recombinant protein. Glycosylation plays an important role on functional expression of SGLT1 as demonstrated in studies performed in COS-7 cells expressing rabbit SGLT1 in which inhibition of glycosylation results in a significant decrease in glucose transport [24]. In addition, glycosylation is also involved in the regulation of the amount of SGLT found in the plasma membrane. On the other hand, protein folding is required for the formation of the secondary and tertiary structure of the protein. This includes the formation of disulfide bridges or attachment of any of a number of biochemical functional groups, such as acetate, phosphate, various lipids and carbohydrates.

Intracellular Trafficking and Localization of SGLT at the Cell Membrane Intracellular SGLT is found inside vesicles. As a result, trafficking of SGLT from the intracellular pools to the plasma membrane represents an important regulatory mechanism for the appropriate function of a recombinant SGLT. Trafficking of SGLT1-containing vesicles from the intracellular pools, found in the endoplasmic reticulum from the Golgi complex, to the plasma membrane has been associated with the intracellular protein RS1 (human gene

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RSC1A1). The role of RS1 protein on inhibition of trafficking of SGLT1 has been demonstrated in studies performed in oocytes [57-60]. Mutations of human SGLT have been associated with mistargeting of this protein. The oocyte expression system has been used to analyze the activity of human SGLT1 mutants (such as D28N, A166C, A304V, R427A and R499H) found in patients with glucosegalactose malabsorption syndrome [46,61,62]. These mutations interfere with trafficking of SGLT1 to the plasma membrane leading to retention of SGLT1 in the intracellular compartment. Although genetic disorders of membrane proteins are frequently caused by altered trafficking of membrane proteins to the cell membrane, in vitro studies using human SGLT1 mutants demonstrated a functional protein [62,63]. Kinetic analysis of human SGLT1 mutants expressed in eukaryotic cells show that these retain their catalytic activity [42].

Cell Differentiation The role of cell differentiation on SGLT expression has been demonstrated in LLC-PK1 cells that constitutively express SGLT [64,65]. The LLC-PK1 cell line obtained from porcine kidney posses a nucleotide sequence of SGLT that is homologous to the SGLT1 of intestinal cells [21,64]. Studies performed with these cells demonstrate that the degree of expression of SGLT1 depends on specific differentiation characteristics including cell confluence, presence of tight junctions, microvilli and brush border enzymes [66]. Under subconfluent conditions, as well as in actively dividing cells, the expression or SGLT is significantly reduced. Another important factor observed in confluent monolayers of LLC-PK1 cells is the presence of two different regions, a basolateral and an apical region [67]. The apical region shows a significant glucose uptake activity as compared to the basolateral region [68,69]. Similar data has been reported in confluent monolayers of the Caco-2 (human colon carcinoma) cell line [70,71]. Cell differentiation is associated with intracellular regulatory mechanisms such as protein kinases. Protein kinase A (PKA) and protein kinase C (PKC) exert opposing effects on SGLT1 mRNA levels in confluent cultures [72]. PKA stabilizes SGLT1 mRNA [73,74]. On the other hand, activation of PKC in confluent LLC-PK1 cells leads to destabilization of SGLT1 mRNA followed by downregulation of SGLT1 protein [75]. The instability of SGLT1 mRNA induced by PKC is blocked by a PKC inhibitor [75]. Interestingly, a similar effect has been observed by high levels of glucose in the medium of LLC-PK1 cells [64]. The role of protein kinases in the regulation of the activity of SGLT1 has also been demonstrated in oocytes expressing SGLT1. PKA regulates glucose transport through SGLT1 [76]. Similar increases in maximum transport have been obtained with activation of PKA in oocytes expressing rabbit, human, and rat SGLT1 isoforms, but with activation of PKC the response was found to be isoform-dependent. PKC activation decreased the maximum rate of transport by rabbit and rat SGLT1, but increased transport by human SGLT1. In addition, protein kinases regulate the activity of SGLT1 by mediation of the distribution of transporters between intracellular compartments and the plasma membrane, which occurs by exo- and endocytosis [77].

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Interestingly, the COS-7 cell line obtained from the simian kidney cell line CV-1 transformed with an origin defective mutant of simian virus 40 (SV40) [78], has also been used to identify receptors and cell membrane proteins [79]. Although, the COS-7 cell line did not possess endogenous SGLT [24], it lacks the apical localization of this protein on the cell membrane. However, rabbit SGLT1 expressed in COS-7 cells demonstrates the same sugar selectivity [80], as well as similar kinetic characteristics, than those of SGLT1 expressed in intestinal brush borders [43] and oocytes [81].

EXPRESSION OF FUNCTIONAL HUMAN RECOMBINANT SGLT IN CHO CELLS The Chinese Hamster Ovary cell line (CHO) was one of the first mammalian cell lines successfully used in the production of therapeutically valuable proteins. CHO cells as an expression system has several advantages over other eukaryotic cells for the expression of a functional SGLT protein. First, the high transfection efficiency observed in CHO cells makes this system suitable for expression of human genes. Second, proteins expressed in CHO undergo post-translational modifications (such as glycosylation and protein folding), that prokaryotic cells like E. coli do not possess. Third, SGLT produced intracellularly undertake trafficking to the cell membrane. Fourth, CHO cells has been used to develop a geneticallyengineered cell line to express functionally recombinant rabbit SGLT1 [26]. For these reasons, the coding region of the rabbit SGLT1 inserted into the eukaryotic expression vector GFP-N1 was used and stable transfected. The resulted cell line, G6D3; posses a markedly high expression of rabbit SGLT1[26]. We used the expression vector pcDNA5 to express functional SGLT in CHO cells [82]. This expression vector contains the SV40 origin of replication that has been used for expression of receptors and cell surface proteins in mammalian cell lines [79]. Moreover, it contains three important components, namely, a replicator, a selectable marker, and a cloning site. The replicator or "ori" refers to the origin of replication with regard to location in bacteria where replication begins. The marker refers to a gene that usually contains resistance to antibiotics (i.e., ampicilin and hygromycin). In this case hygromycin was used as the selection media for stable transfected CHO clones. In addition, pcDNA5 also contains the Flp recombinase target (FRT) promoter, which allows to produce higher amounts of the desired protein. FRT allows targeted integration of the plasmid into CHO Flp-In cells leading to efficient generation of isogenic expression cells [83,84]. Finally, the cloning site is a sequence of nucleotides representing one or more positions where cleavage by restriction endonucleases occurs. In this case, the expression vector pcDNA5 was linearised with XhoI restriction enzymes to allow the insertion of the specific oligonucleotide sequence that code for human intestinal SGLT1 or human kidney SGLT2. Human SGLT1 and SGLT2 were cloned using the following primers: SGLT1 forward, 5’-CCG CCG AAG CTT CCG CCA TGG ACA GTA GCA CCT GGA GC-3’; SGLT1 reverse, 5’-CCG CCG CTC GAG TCA GGC AAA ATA TGC ATG GC-3’; SGLT2 forward, 5’-CCG CCG AAG CTT CCG CCA TGG AGG AGC ACA CAG AGG C-3’; and SGLT2 reverse, 5’-CCG CCG CTC GAG TTA GGC ATA GAA GCC CCA CAG G-3’. The obtained cDNA was used for transformation in electrocompetent E. coli DH10B cells. The plasmid

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construct obtained (pcDNA5-SLGT1 or pcDNA5-SGLT2) was then used for stable or transient transfection of CHO cells [82]. Prior to be used for transport studies, the expression of human SGLT1 and SGLT2 in the transfected CHO cells was confirmed by relative RT-PCR quantification. Specific primers for human SGLT1 forward (5’-CAC CAC CAT AAA CAG GCT G-3’) and SGLT1 reverse (5’AGC CTG ATA GAG CAT TCT TT-3’); and for SGLT2 forward (5’-CAC CAC CAT AAA CAG GCT G-3’) and SGLT2 reverse (5’-AGC CTG ATA GAG CAT TCT TT-3’) were used. The analysis of relative RT-PCR quantification was calculated using the threshold cycle (CT) method [85]. For normalization, primers for human β-actin forward (5’-GCG CAT GGG TCA GAA GGA CT-3’) and β-actin reverse (5’-TCG TCC CAG TTG GTG ACG AT-3’) were used. A calibrator cDNA from non-transfected cells was also used [82]. As shown in Figure 2, SGLT1 gene expression in clones 2D1, 3B6 and 6B8 was higher than in clones 4G9 and 2E10. SGLT2 gene expression in clones 6D9, 3G1 and 6A12 was higher than in clones 4C4 and 3F7. In order to evaluate further the expression of SGLT1 and SGLT2 at the protein level, Western blot and immunocytochemical analysis were performed (Figure 3). Specific antibodies against human SGLT1 (S1010-86K) or against human SGLT2 (S1010-87E) were used for Western blot analysis. Cell homogenates obtained from Caco-2 cells, a human colon adenoma cell line that constitutively express SGLT, and non-transfected CHO cells, were used as controls. Immunocytochemical analysis confirmed the expression of human SGLT1 and human SGLT2 in the stable transfected CHO cells [82].

Figure 2. Relative RT-PCR quantification results obtained by plotting the relative quantitation values versus the stably transfected CHO clones.

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Uptake studies represent the most exact technique to determine the activity of SGLT. For that purpose, [14C]-methyl-α-D-glucopyranoside (AMG), a non-metabolized substrate for SGLT, has been used in intestinal brush-border membrane [29,86], in isolated proximal tubules, in renal cortical brush-border membrane vesicles [87], and in transfected cells analysis of SGLT. We developed a 96-well method for the study of SGLT activity [82]. This method was establish and validated after several AMG-uptake measurements using transfected CHO cells (either stable or transient transfected), as well as non-transfected CHO cells under confluent monolayer culture condition. For that purpose, Krebs-Ringer-Henseleit (KRH) solution containing 120 mM NaCl, 4.7 mM KCl, 1.2 mM MgCl2, 2.2 mM CaCl2, 10 mM Hepes (pH 7.4 with Tris) was used to assess sodium-dependent D-glucose transport. For sodium free conditions, KRH solution containing 120 mM n-methyl-glucamine (NMG) instead of NaCl (Na+) was used to assess sodium-independent D-glucose transport. Sodium-dependent AMGD-glucose uptake was calculated by subtracting uptake under sodium-free conditions from the uptake obtained in the presence of sodium.

Figure 3. (A) Western blotting analysis of human SGLT1 and SGLT2 in CHO transfected cells compared to non-transfected cells. CaCo2 cells, a cell line that constitutively express SGLT, were used as a positive control. (B) Immunocytochemistry analysis of stable transfected CHO cells that express human SGLT1 and SGLT2.

The results of transport studies using the 96-well method are shown in Figure 4. Sodiumdependent D-glucose transport assessed by AMG-uptake was significantly higher in the stable transfected CHO cells expressing human SGLT1 or SGLT2 than in non-transfected cells. The sodium-independent D-glucose uptake in the stable transfected cells was as low as

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the basal values in non-transfected cells, indicating no activity from this type of transport in the CHO cells [82]. In addition, kinetic analysis including maximal rate of transport (Vmax), Michaelis constant (Km) and inhibition constat (Ki) can be calculated using the 96-well method. The estimation of the inhibition constant (Ki) was performed using Dixon plot analysis [88]. As shown in Figure 5, Ki was determined by the point of intersection of two different substrate concentrations (AMG) and five concentrations of the analyzed inhibitor substance (phlorizin). This analysis confirms the strong inhibitory effect of phlorizin on SGLT, which depends on a competitive inhibitory mechanism.

Figure 4. AMG-uptake determination in stably transfected CHO cells compared to non-transfected CHO cells.

DRUG DISCOVERY AND DEVELOPMENT Hyperglycemia represents the main pathogenic factor for the development of diabetic complications including coronary heart disease, retinopathy, nephropathy, and neuropathy [89,90]. In addition, chronic hyperglycemia leads to progressive impairment of insulin secretion and to insulin resistance in peripheral tissues (referred to as glucose toxicity) [91,92]. Due to the high prevalence of diabetes [93,94] associated with high morbidity and mortality, the development of new strategies for the control of hyperglycemia are required. Current methods for the screening of inhibitors of SGLT transporters are complex, expensive and labor intensive, and have not been applied to human SGLT transporters. This is due to the reported substrate selectivity and the kinetics of SGLT on different species [95]. The 96-well method [82] represents an important instrument that can be used in the development of transport-based high-throughput screening in the search for inhibitors of glucose transport, and the development of new antidiabetic drugs. One example of this

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application is the discovery of glucose analogues such as thioglycoside I (phenyl-1'-thio-β-Dglucopyranoside) and thioglycoside VII (2-hydroxymethyl-phenyl-1'-thio-β-D-galactopyranoside) [96]. As shown in Figure 6, the concentration of thioglycoside VII and thioglycoside I required for 50% inhibition of AMG-uptake rate (IC50) were lower than those obtained with phlorizin for human SGLT1 and SGLT2, respectively. Specifically, thioglycoside I inhibited human SGLT2 more strongly than it did human SGLT1 and to a larger extent than that seen with phlorizin. Therefore, these thioglycosides represent promising therapeutic agents for the control of hyperglycemia in patients with diabetes.

Figure 5. Kinetic analysis of human SGLT1 and human SGLT2 expressed in stably transfected CHO cells.

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Figure 6. Kinetic analysis of thioglycosides.

CONCLUSION Functional expression of recombinant human SGLT1 and human SGLT2 in CHO cells represents an important instrument for the study of inhibition of SGLT activity based on the presence of post-translational modifications of this eukaryotic system. Furthermore, the application of differentiated epithelial cells constitutes a main factor for the expression of a functional recombinant SGLT protein. This factor is the basis of the novel 96-well method we developed in CHO cells, which cannot be reproduced in other systems such as the brush border membranes, oocytes, or liposomes. In addition, this method represents an initial approach in the development of transport-based high-throughput screening in the search for inhibitors of glucose transport as potential therapeutic agents for the control of hyperglycemia and ultimately diabetes complications.

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In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter XII

EFFECT OF HYPOXIC CONDITIONS ON TRANSLATIONAL CONTROL OF GENE EXPRESSION Ota Fuchs1,2,∗ 1

2

Institute of Hematology and Blood Transfusion, 128 20 Prague 2, Czech Republic; Center of Experimental Hematology with Institute of Pathophysiology, First Medical Faculty, Charles University, Prague, Czech Republic.

ABSTRACT Hypoxic conditions, found in limb ischemia, aortic aneurysms, myocardial ischemia and in tumors as well as during normal embryogenesis activate a transcriptional response that promotes vascular development and the formation of red blood cells. The master transcriptional regulator of oxygen-controlled gene expression is the hypoxia-inducible factor HIF. Many of the proangiogenic and antiangiogenic factors are directly or indirectly regulated by transcription factor HIF. Hypoxia suppresses protein synthesis at the level of mRNA translation initiation in many nontransformed cells whereas highly transformed cells are largely resistant. Two different pathways are involved in response of mRNA translation initiation in cells to hypoxia and it results in biphasic inhibition of translation. The first pathway is associated with endoplasmic reticulum (ER) stress and through it with activation of unfolded protein response. Transient phosphorylation of eukaryotic initiation factor (eIF) 2 alpha in the first phase by double-stranded RNAactivated protein kinase-like endoplasmic reticulum kinase PERK inhibits mRNA translation initiation. The second phase occurs more slowly and is independent on eIF2alpha and is connected with eIF4F (containing the cap- binding protein eIF4E, the scaffold protein eIF4G and the RNA helicase eIF4A) disruption and with inactivation of the ternary complex (eIF2/Met-tRNA/GTP). The availability of the cap-binding protein eIF4E is rate-limiting under normal conditions. During tumorigenesis eIF4E is often over ∗

Correspondence concerning this article should be addressed to: Ota Fuchs, PhD. Tel: +420 221977313; Fax: +420 221977370; E-mail: [email protected].

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Ota Fuchs expressed because eIF4E-binding proteins sequester eIF4E in hypophosphorylated form. Hyperphosphorylation of the eIF4E-binding proteins lowers their affinity for eIF4E, resulting in an increased interaction between eIF4E and eIF4G and stimulation of translation. Phosphorylation of eIF4E-binding proteins is largely controlled by the mammalian target of rapamycin (mTOR) kinase. Hypoxia inhibits the activation of kinase mTOR and results in hypophosphorylated eIF4E-binding proteins and in increased their affinity for eIF4E and in decreased association between eIF4E and eIF4G necessary for eIF4F disruption. Inhibition of the kinase mTOR suppresses mRNA translation also through a novel mechanism mitigated in transformed cells. This mechanism is based on disruption of proteasome-targeted degradation of eukaryotic elongation factor 2 (eEF2) kinase. However, regulation of translation also results in a specific increase of the synthesis of a subset of hypoxia-induced proteins as activating transcription factor 4 (ATF4), CCAAT/enhancer binding protein homologous protein (CHOP, also named GADD153), growth arrest and DNA damage inducible protein (GADD34), hypoxia inducible factor (HIF-1alpha), vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and immunoglobulin heavy chain binding protein (BiP). Translation in these cases is often cap independent due to the presence of an internal ribosome entry site (IRES) in the 5´ -noncoding region of some these mRNAs. Hypoxic tumor cells that are target of tumor therapy are exposed to additional endoplasmic reticulum stress by using proteasome inhibitors, such as PS-341 (Velcade), which is Food and Drug Administration approved for treating human malignancies. This therapy may be selectively cytotoxic to hypoxic tumor cells.

Keywords: eIF2alpha, eIF4E, mRNA translation, hypoxia, HIF-1 alpha, IRES, endoplasmic reticulum stress, PERK, mTOR kinase.

INTRODUCTION Oxygen (O2) is essential for the viability and function of most organisms and its abundance in normal tissues is 3-9%. O2 deprivation, or hypoxia, is a drop in the oxygen partial pressure and has important effects on cell metabolism and growth. In addition to mild hypoxia (0.01-2% O2), some tumors contain regions of severe hypoxia called anoxia (<0.01% O2). The best described response to hypoxia is mediated by the hypoxia inducible factor (HIF) family of transcription factors, through the stabilization of the α subunit of this heterodimeric factor through hydroxylation by prolyl hydroxylase domain (PHD) proteins [13]. Therefore, HIF is activated via post-transcriptional mechanism during hypoxia and regulates the expression of a wide range of genes, either positively or negatively [4-6]. However, SUMOylation of HIF-1α decreases its transcriptional activity but does not change its half-life. The genes that are targeted by hypoxia in the survival response are involved in a wide variety of cell functions including angiogenesis, glycolysis, vasodilation and respiration, erythropoiesis and molecular-oxygen sensing. Thus, HIF1 promotes tumor growth and hypoxic regions in tumors in general correlate with poor prognosis, radiotherapy and chemotherapy resistance, and increased metastatic potential. On the other hand, HIF1 stimulates the expression of angiogenic cytokines such as vascular endothelial growth factor (VEGF) and others and is useful for neovascularization in patients with ischemic diseases. Decreased synthesis of homologous recombination proteins by hypoxia (for example RAD51

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and BRCA1) is HIF-1α-independent and can be mediated by altered E2F transcriptional activation and repression [7-9]. Hypoxia has also been shown to suppress an additional level of genetic control, protein synthesis, through the regulation of the initiation step of mRNA translation by two distinct pathways [10-15]. The first occurs rapidly, is transient and is conected with phosphorylation of eIF2α. Hypoxia activates the endoplasmic reticulum kinase PERK, leading to phosphorylation of eIF2α and inhibition of mRNA translation initiation. Continued hypoxic exposure induces a second, eIF2α –independent pathway that maintains repression of translation. This second pathway is based on disruption of the cap-binding protein complex eIF4F, which consists of eIF4A, eIF4E and eIF4G [16-21]. eIF4E participates in a protein bridge between the mRNA and ribosome. eIF4E simultaneously interacts with the mRNA 5´ cap structure and with the scaffolding protein eIF4G. eIF4G then interacts with eIF3 that is bound to the small 40S ribosomal subunit. A set of binding proteins (4E-BPs) binds reversibly to eIF4E in their hypophosphorylated form and inhibits the interaction between eIF4E and eIF4G. Phosphorylation of the 4E-BPs is controlled by the mTOR protein kinase (mammalian target of rapamycin) which receives signals from multiple upstream signaling pathways [22-25]. Rapamycin is a specific inhibitor of the target of rapamycin (TOR). Rapamycin is an immunosuppressant which antagonizes cellular proliferation by inhibiting the function of mTOR. The mTOR:FKBP12: rapamycin complex blocks G1/S transition by inhibiting downstream targets essential for cell cycle progression. One such target is p70S6k1 (S6K1), a serine/threonine kinase which is inactivated by the mTOR : FKBP12 : rapamycin complex, and which has been linked to translational control by virtue of its ability to phosphorylate the ribosomal protein S6. A novel S6K1 homolog, p54 S6 kinase 2 (p54S6k2/S6K2) similar to S6K1 was also described. S6K2 is activated by mitogens and by constitutively active PI3K, and is inhibited by rapamycin as well as wortmannin. Differences between activation of S6K1 and S6K2 by PDK1 (phosphoinositide-dependent kinase-1) were observed, suggesting potential differences in the regulation of these homologs. The protein kinase TOR genes (TOR1 and TOR2) were identified in a screen for rapamycin-resistant yeast mutants [26]. mTOR enhances translation initiation not only by phosphorylation of 4E-BPs, but also by phosphorylation of the S6 ribosomal protein kinases (S6K1 and S6K2) that cooperate to regulate translation initiation rates. S6 ribosomal protein is a component of the 40S ribosome subunit. Moderate hypoxia inhibits the activation of mTOR and subsequent phosphorylation of its substrates 4E-BP1 and S6K. Hypophosphorylation of 4E-BP1 was found only after prolonged hypoxia (16 h), whereas decreased association between eIF4E and eIF4G that means eIF4F disruption was observed after 4 h of hypoxia. Inhibition of protein synthesis during hypoxia strongly depends on cell transformation [27]. Hypoxia causes a 4E-BP1 dependent decrease in protein synthesis in untransformed cells, but no decrease of protein synthesis in cancer cells. Although hypoxia causes a global inhibition in translation, some mRNAs bypass this general inhibition in protein synthesis by mechanism dependent on 5´ and 3´ untranslated regions (UTR) of these mRNAs. Internal ribosome entry sites (IRES) facilitate direct ribosome binding independent of formation of eIF4F at the cap. IRES dependent translation contributes to selective gene expression during hypoxia when eIF4F integrity is disrupted.

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The list of mammalian mRNAs with IRES is growing, and includes a number of hypoxia regulated genes (HIF-1α, VEGF, the immunoglobulin heavy-chain binding protein BiP and others) [28-33]. Under hypoxia where eIF2α is phosphorylated, ternary complex (eIF2-GTPmethionine-loaded initiator tRNA /Met-tRNA/) availability is low, the translation can initiate at the second upstream open reading frame (for example in mRNA for ATF4, CHOP or GADD34) [12,34].

PHOSPHORYLATION OF EIF2α DURING HYPOXIA Translation initiation of eukaryotic mRNA begins with assembly of eIF4F at the m7GpppN (where “N” is any nucleotide and “m” is a methyl group) cap structure at the 5´terminus of the mRNA [16,17,21,35]. eIF4F consists of three subunits (the cap binding protein eIF4E, a scafolding protein eIF4G and an ATP-dependent helicase eIF4A). eIF4E binds to the mRNA cap structure and interacts with eIF4G, which is a large scaffold protein for assembly of eIF4A and eIF4E to form the eIF4F complex. Binding of eIF4F to mRNA facilitates the recruitment of the 43S preinitiation complex, which is necessary to initiate translation. This complex contains the small 40S ribosomal subunit, eIF3 and the ternary complex (eIF2-GTP-Met-tRNA). The 43S preinitiation complex scans through the 5´ untranslated region of the mRNA until it recognizes the AUG initiation codon. At this place it recruits the 60S large ribosomal subunit to assemble the 80S ribosome and starts the elongation phase of translation. The exchange of eIF2-GDP for GTP is carried out by the guanine nucleotide exchange factor, eIF2B and is necessary for formation of the ternary complex. Phosphorylated eIF2α (eIF2α/P/) can not undergo GDP/GTP exchange and forms a nondissociable complex with eIF2B. Intracellular levels of eIF2B are approximately 10-20% that of eIF2 in the cytoplasm. Thus, phosphorylation of as little as 10% of eIF2 can be sufficient to sequester virtually all available eIF2B, to block the eIF2B exchange activity and to inhibit protein synthesis completely. Hypoxia induces the phosphorylation of eIF2α subunit at serine 51. This eIF2α phosphorylation suppresses the exchange eIF2-GDP for GTP and inhibits translation initiation (Figure 1). Specific phosphatase complexes can counteract phosphorylation of eIF2α on serine 51. The first such complex to be identified consists of a viral regulatory subunit encoded by the herpes simplex virus gamma1 (34.5) gene and a cellular catalytic subunit of serine/threonine protein phosphatase-1 (PP1). By dephosphorylating eIF2α, γ1(34.5) enables the virus to escape the inhibitory effect of protein kinase R (PKR) activation. Catalytic subunit of PP1 can be also bound by the growth arrest and DNA damage-inducible protein, GADD34 or the constitutive repressor of eIFα phosphorylation, CReP and both these PP1 complexes can dephosphorylate eIF2α (Figure 1). Cells respond to environmental stress stimuli by regulating initiation of mRNA translation through the phosphorylation of eIF2α subunit. Several serine/threonine eIF2α subunit kinases that respond to different stress signals (PKR, an IFN-induced, double-stranded RNA-activated kinase that is activated during virus infection and helps protect the cell from viral infection, heme-regulated inhibitor kinase /HRI/, general control non-derepressible-2 /GCN2/ kinase, and PKR-like endoplasmic reticulum /ER/ kinase /PERK/) have been identified (Figure 1).

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Phosphorylation of eIF2α during hypoxia requires activation of the endoplasmic reticulum resident kinase PERK. PERK is activated during the unfolded protein response (UPR), a cellular response to the accumulation of misfolded proteins in the ER [36]. Hypoxia causes a rapid, eIF2α dependent loss in polysomal RNA [12]. The remained polysomes have lower molecular weight reflecting a significant drop in ribosome density [13]. This is consistent with a drop in ternary complex availability and a slowing in the recruitment of ribosome complex to the mRNA. Phosphorylation of eIF2α at serine 51 in the response to hypoxia is reversible upon reoxygenation and importantly, correlates with a reduction in the levels of overall protein synthesis [37].

Figure 1. Model of the interaction of activated PERK with its substrate (the nonphosphorylated form of eIF2). In its unstressed, nonphosphorylated inactive form, PERK has a low affinity for its substrate. Upon activation during hypoxia, PERK undergoes phosphorylation-dependent changes, oligomerization that markedly increase its affinity for the substrate. Phosphorylation of the substrate results in a marked decline in its affinity for the kinase and likely promotes substrate dissociation. The phosphorylated eIF2 product is free to migrate away from the kinase and to interact with and inhibit the guanine nucleotide exchange factor eIF2B, thereby attenuating protein synthesis. Several serine/threonine eIF2α subunit kinases that respond to different stress signals (PKR, an IFN-induced, double-stranded RNA-activated kinase that is activated during virus infection and helps protect the cell from viral infection, hemeregulated inhibitor kinase /HRI/, general control non-derepressible-2 /GCN2/ kinase, and PKR-like endoplasmic reticulum /ER/ kinase /PERK/) have been identified. Catalytic subunit of serine/threonine protein phosphatase-1 (PP1) can be bound by the growth arrest and DNA damage-inducible protein, GADD34 or the constitutive repressor of eIFα phosphorylation, CReP and both these PP1 complexes can dephosphorylate eIF2α.

Cells derived from knock-in mice containing a nonphosphorylated allele of eIF2α (S51A) that has an alanine substituted at serine 51 and thereby can act in in a dominant-negative fashion, were unable to effectively inhibit overall translation in response to acute hypoxia

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during short hypoxic exposures, providing a causal relationship between eIF2α phosphorylation and hypoxia-induced translation repression. However, these cells displayed similar levels of translation supression as the wild type cells after 16 h of hypoxia. Thus, severe hypoxia induces a biphasic inhibition of translation. The second phase occurs more slowly and is independent on eIF2α. Interestingly tumor cells expressing the eIF2α (S51A) construct still showed only a modest reduction in translation after 10 h of hypoxia, suggesting additional mechanisms of translational regulation. Long exposures to hypoxia also disrupt the cap binding eIF4F complex by dephosphorylation 4E-BP1 and the eIF4E translocator (4E-T) mediated –sequestration of eIF4F [13]. Recently, it has been shown by Thomas et al. [38] that translational repression during chronic hypoxia is dependent on glucose levels and is PERK independent. . Phosphorylation of eIF2α is reversed by glucose addition. Since the physiological conditions that lead to tumor hypoxia would also likely lead to reduced glucose levels, understanding the interplay of glucose and hypoxia in regulating tumor metabolism will improve our knowledge about the growth and development of solid tumors.

PHOSPHORYLATION OF EIF2α STIMULATES TRANSLATIONAL UPREGULATION OF THE TRANSCRIPTION FACTOR ATF4 PERK is a type-I ER transmembrane protein ubiquitously expressed [38,39]. PERK has a lumenal domain bound by the ER chaperone BiP/GRP78 in unstressed conditions and a cytoplasmic domain containing kinase activity. Cytoplasmic domain is highly homologous to a yeast stress-responsive kinase GCN2 [39,40]. Upon ER stress, BiP releases the lumenal domain of PERK. PERK dimerizes and autophosporylates and dramaticaly increases affinity towards eIF2α [41-43]. This activation of PERK leads to eIF2α phosphorylation at serine 51 and to translation inhibition [44,45]. Recently, it has been demonstrated that PERK also possesses tyrosine kinase activity [46]. PERK is capable of autophosphorylating on tyrosine residues in vitro and in vivo. Tyrosine 615 in a highly conserved region of the kinase domain of PERK, is essential for autocatalytic activity. Thus, PERK is a dual specificity kinase whose regulation by tyrosine phosphorylation contributes to its optimal activation in response to ER stress [46]. Hypoxia induces energy stress which results in a rapid and reversible inhibition of global protein synthesis to help alleviate energy demands when oxygen and ATP levels are low. However, the exact mechanisms controlling translational regulation are not fully understood. While early responses to hypoxia involve the activation of PERK and transient phosphorylation of the alpha subunit of translation initiation factor 2 [36,37,47], translational inhibition appears to occur in distinct phases and to involve multiple pathways [12-15,48-50]. Translational inhibition paradoxically leads to the selective translation of several mRNAs necessary for the survival and adaption of cells to cellular stress (Figure 2), including the transcription factor ATF4 [12,34,51-53]. ATF4 (also named CREB2, TAXREB67 and TAXCREB67) is a member of the activating transcription factor (ATF) /cAMP responsive element binding protein (CREB) family. ATF4 is basic region-leucine zipper (bZip) transcription factor. ATF4 protein consists of 351 amino acids. The protein is structured into

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several domains that are important for ATF4 homo/heterodimerization, DNA binding, and the regulation of ATF4 protein stability in response to stress. ATF/CREB family of proteins bind to DNA via their basic region and dimerize via their bZip domain to form a large variety of homodimers and/or heterodimers that allow the cell to coordinate signals from different pathways. A transcription activation domain is located at the N-terminus of ATF4. Genes with ATF4 binding sites are involved in the unfolded protein response (UPR), supporting the possibility of an integrated stress response (ISR) between the UPR and hypoxia through the translational regulation of ATF4. This signaling pathway initiated by phosphorylation of eIF2α protects cells against ISR. ATF4 induction does not involve HIF1 or electron transport [54]. ATF4 binds to cAMP responde sites in its target genes and can activate the ISR. ATF4 transcript has two short upstream open reading frames (uORFs) in the 5´-untranslated region. During unstressed conditions ribosomes scan along the mRNA translating upstream ORF1 and then rebind eIF2/GTP/Met-tRNA ternary complex in time to translate inhibitory upstream ORF2. The second upstream ORF overlapping with the ATF4 open reading frame has repressive function and prevents downstream translation of ATF4. However, during hypoxia, the level of eIF2α phosphorylation is increased, limiting levels of eIF2 ternary complex and scaning ribosomes can not reinitiate at ORF2 but instead scan to the ATF4 initiation codon. Thus, translation of ATF4 is enhanced during hypoxia.

Figure 2. Mechanisms and consequences of cellular responses to hypoxia. Signaling via PERK to eIF2α and ATF4 and promotion of energy homeostasis, cell survival and tumor growth. ATF4 is a transcription factor which plays a role in the transcriptional activation of CHOP (CCAAT/enhancer binding protein homologous protein, also named GADD153), transcription factor X-box binding protein 1 (XBP1), growth arrest and DNA damage inducible protein (GADD34) and of other proteins.

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The importance of ATF4 induction and its downstream genes during hypoxia is still not well known. ATF4 – / - mouse embryonic fibroblasts are significantly more sensitive to severe and moderate hypoxia [34]. ATF4 has an important role in protecting cells against oxidative stress [55]. Increased oxidative stress in the cytoplasm of hypoxic cells is most likely caused by release of reactive oxygen species from the mitochondria following disruption of the mitochondrial electron transport chain [56]. In addition, reoxygenation following exposure to hypoxia is known to produce oxidative stress [57]. Thus, ATF4 could induce transcriptional up-regulation of antioxidant-related genes (Figure 2), such as heme oxygenase-1 [58]. CHOP, one of the targets of ATF4 (Figure 2), is also transcription factor with proapoptotic properties [59-61]. Some evidence suggests that phosphorylation of eIF2α in addition to regulation of ribosomal scanning also activates translation from some internal ribosomal entry sites (IRES) and the use of alternative AUG start codons [62]. Although general cap-dependent translation is downregulated during hypoxia, mRNAs important for adaption to hypoxia, such as hypoxia-inducible factors (HIF) (Figure 3), vascular endothelial growth factor (VEGF), and platelet-derived growth factor (PDGF), continue to be translated. In the case of VEGF mRNA and HIF mRNA (Figure 3) is translation cap independent due to the presence of an internal ribosome entry site (IRES) [63,64] and in the case PDGF mRNA, 5'-UTR sequence contains two promoters (termed P1 and P2) but no IRES [65].

Figure 3. Schema of HIF-1α mRNA translation. Under normal oxygen conditions HIF-1α mRNA translation can be stimulated through mTOR dependent growth factor signaling. This mRNA contains 5´-terminal oligopyrimidine tract (TOP) sequences. mTOR signaling results in phosphorylation of its two well known substrates S6K and 4E-BP1. S6K phosphorylation promotes translation of a subset of mRNAs that contain 5´TOP in their 5´-untranslated region. During hypoxia mTOR signaling and therefore cap-dependent translation is inhibited. Hypoxia promotes IRES-dependent translation of HIF1 independent on eIF4F function.

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POSTTRANSLATIONAL MECHANISM OF ATF4 REGULATION Hypoxia regulates ATF4 also by reduced proteolysis on the protein level [66]. ATF4 interacts with F-box protein βTrCP in yeast two-hybrid assays and this interaction was confirmed by coimmunoprecipitation in vivo. Only the phosphorylated form (specific phosphorylation of Ser219) of ATF4 can associate with βTrCP. Interaction of ATF4 with βTrCP depends on motif DSGXXXS similar to that found in the other substrates of βTrCP (IκBα, β-catenin, HIV-1 and others). F-box of βTrCP is necessary for its association to Skp1, which is required for its recruitment to the SCF-E3 ubiquitin ligase complex, and the targeting to the proteasome. βTrCP colocalizes with ATF4 in the nucleus of cells. Köditz et al. [67] showed interaction of ATF4 with prolyl-4-hydroxylase domain PHD3 oxygen sensor in yeast two-hybrid system. The hypoxic induction of PHD3 correlates with increased hydroxylation activity, which compensates for decreased oxygen levels [68,69]. ATF4 protein becomes unstable following reoxygenation and is rapidly degraded with a half-life of 9 minutes [67]. Adding of the PHD inhibitor dimethyloxalylglycine (DMOG) at the time of hypoxia resulted in a prolonged ATF4 protein half-life of 21 minutes [67]. ATF4 stability is also modulated by the histone acetyltransferase p300, which induces ATF4 stabilization by inhibiting its ubiquitination [70]. Despite p300 acetylates ATF4, we found that p300-mediated ATF4 stabilization is independent of p300 catalytic activity, using either the inactive form of p300 or the acetylation mutant ATF4-K311R [70]. In consequence of ATF4 stabilization, both p300 and the catalytically inactive enzyme increase ATF4 transcriptional activity.

HYPOXIC INHIBITION OF PROTEIN SYNTHESIS THROUGH 4E-BPI AND ELONGATION FACTOR 2 KINASE PATHWAY CONTROLLED BY MAMMALIAN TERGET OF RAPAMYCIN KINASE Although the phosphorylation of eIF2α by hypoxia is transient, translation of majority of mRNAs remains low during prolonged hypoxic exposure, which lasts more than 8 hours. In this case, translation is inhibited by disruption of the cap-binding protein complex eIF4F, which consists of the eIF4E cap binding protein, the eIF4G scaffolding protein and the ATP dependent eIF4A RNA helicase. Transient phosphorylation of eIF2α and subsequent dissociation of eIF4F are two mechanisms operating independently and both play role in gene expression during hypoxia. Three related eIF4E-binding proteins (4E-BP1, 4E-BP-2 and 4EBP3) inducibly regulate the formation of the cap-initiation complex and control capdependent mRNA translation. The major member of this family, 4E-BP1, binds eIF4E and prevents its association with eIF4G. This event prevents formation of the cap-initiation complex and inhibits cap-dependent mRNA translation. Hyperphosphorylation of 4E-BP1 by mammalian target of rapamycin (mTOR) kinase inhibits binding of 4E-BP1 to eIF4E and promotes protein synthesis [27,71-75]. Hypoxia inhibits mTOR kinase (also known as FRAP

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/FKBP12-rapamycin associated protein/, RAPT /rapamycin-target/ and RAFT /rapamycin and FKBP12-target/) and induces increased binding of eIF4E to 4E-BP1 [76,77].

Figure 4. Schematic diagram of the mTOR signaling pathway involved in translational control during hypoxia. The mTOR regulation involves the AMPK/TSC2/Rheb pathway and is activated by hypoxiainduced decreases in cellular bioenergetics. HIF-inducible REDD1 (regulated in development and DNA damage response) has been implicated in the regulation of mTOR upstream of TSC2 (tuberous sclerosis complex 2). Mutations of TSC2 in tumor cells greatly impede hypoxia-induced mTOR inhibition and G1 arrest. Phosphorylation of eukaryotic elongation factor 2 (eEF2) at position Thr-56 inhibits the elongation step of protein synthesis.

Hypoxia prevents insulin stimulation of mTOR kinase [76]. mTOR may be partly inhibited via REDD1 (regulated in development and DNA damage response) and TSC1/2 (tuberous sclerosis complex 1/2). Induction of REDD1 (also known as RTP801) during hypoxia activates the mTOR inhibitory complex TSC1/2 (Figure 4) [77]. TSC that consists of TSC1 and TSC2 dimers represses mTOR by activation of the small GTPase Rheb (Figure 4) [78]. LST8, a Saccharomyces cerevisiae gene encoding a 34-kD WD-repeat protein, negatively regulates amino acid biosynthesis as a component of the TOR pathway. Raptor is a regulatory associated scaffold protein of mTOR (Figure 4). Raptor, mTOR binding partner that also binds p70S6k and 4E-BP1, is essential for mTOR signaling in vivo. Akt1 activates the mammalian target of rapamycin by regulating cellular ATP level and AMP-activated kinase (AMPK) activity [79]. TSC phosphorylation by Akt1 and ERK suppresses Rheb

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[80,81]. Akt1 is the serine/threonine-specific protein kinase, which was originally identified as the oncogene in the transforming retrovirus AKT8. Akt1 is involved in cellular survival pathways by inhibiting apoptotic processes. The MAPK (mitogen-activated protein kinases)/ERK (extracellular signal-regulated kinases) is a signal transduction pathwaythat couples intracellular responses to the binding of growth factors to cell surface receptors. AMPK enhances activity of Rheb [82,83]. This mechanism of inhibition of protein synthesis during hypoxia through hypophosphorylation of 4E-BP1 remains unclear because prevention of 4E-BP1 dephosphorylation by mTOR kinase overexpression during anoxia did not remove protein synthesis inhibition [71]. In addition, REDD1 is an HIF-dependent gene and both mTOR inhibition and and translation inhibition during hypoxia occur in HIF1α-knockout cells [37,76]. REDD1 functions downstream of Akt1 [84]. However, 4E-BP1 knockdown models have provided some support for a role of 4E-BP1 in regulating translation during moderate hypoxia [27]. Recently, Magagnin et al. [85] generated HeLa cells stably expressing a short hairpin interfering RNA (shRNA) against 4E-BP1 and using a proteomics approach identified seven proteins that were exclusively expressed in these 4E-BP1 knockdown cells during both normoxic and hypoxic conditions. Quantitative RT-PCR showed that the loss of 4E-BP1 causes a significant increase in the synthesis of S100 calcium-binding protein A4 and transgelin-2. 4E-BP1 directly regulates their translation efficiency. These proteins have previously been associated with tumor cell motility, invasion and metastasis.Tumors have poorly oxygenated (hypoxic) areas and hypoxic tumors are associated with a more malignant phenotype. The rate of synthesis of eIF4G decreases with prolonged hypoxia but stability of this protein does not change [12]. A possible cause of the cap-binding protein complex eIF4F disruption is the translocation of eIF4E to the nucleus or to cytoplasmic bodies of mRNA processing (P/bodies) [86,87]. Transporting protein for eIF4E is protein 4E-T [88,89]. A redistribution of both eIF4E and 4E-T during prolonged hypoxia correlates with the gradual dephosphorylation of 4E-T [12]. Phosphorylation of eukaryotic elongation factor 2 (eEF2) at position Thr-56 inhibits the elongation step of protein synthesis. eEF2 kinase (eEF2K) phosphorylates eEF2. eEF2K can be inhibited or activated by phosphorylation at a number of sites [90]. Both mTOR and the p70 ribosomal S6 kinase (p70S6k) inhibit eEF2K by phosphorylation and stimulate eEF2 activity and protein synthesis [91,92]. AMPK and p70S6k regulate also partly mTOR activity. AMPK decreases the activity of p70S6k, which inhibits eEF2K activity. Thus, AMPK inhibits protein synthesis [93-95]. AMPK can also activate the TSC2 protein, which with TSC1 inhibits mTOR [82,83,96]. Inhibition of mTOR by hypoxia can be also AMPK-independent and involves transcriptional upregulation of the hypoxia gene REDD1 and the TSC1/2 complex [77,97]. REDD1 inhibits mTOR function to control cell growth in response to energy stress. Endogenous REDD1 is induced following energy stress, and REDD1-/- cells are highly defective in dephosphorylation of the key mTOR substrates S6K and 4E-BP1 following either ATP depletion or direct activation of the AMPK. REDD1 likely acts on the TSC1/2 complex, as regulation of mTOR substrate phosphorylation by REDD1 requires TSC2 and is blocked by overexpression of the TSC1/2 downstream target Rheb but is not blocked by

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inhibition of AMPK. Tetracycline-inducible expression of REDD1 triggers rapid dephosphorylation of S6K and 4E-BP1 and significantly decreases cellular size. Conversely, inhibition of endogenous REDD1 by short interfering RNA increases cell size in a rapamycin-sensitive manner, and REDD1-/- cells are defective in cell growth regulation following ATP depletion. These results define REDD1 as a critical transducer of the cellular response to energy depletion and hypoxia through the TSC-mTOR pathway [77,97].

PROTEASOME INHIBITORS AS THERAPY SELECTIVLY CYTOTOXIC TO HYPOXIC TUMOR CELLS The ubiquitin-proteasomal pathway (UPP) of degradation of proteins is activated or repressed in response to a number of environmental stresses and thereby plays an essential role in cell function and survival. Hypoxic stress, resulting from a decrease in the concentration of oxygen in tissues, is encountered in both physiological and pathological situations, in particular in cancer. The transcriptional complex hypoxia-inducible factor (HIF) is the key player in the signalling pathway that controls the hypoxic response of mammalian cells. Under hypoxic conditions it transactivates an impressive number of genes involved in a multitude of cellular functions. Tight regulation of this response in part involves the ubiquitin-proteasomal system where oxygen-dependent prolyl-4-hydroxylation of the alpha subunit of HIF triggers a cascade of events that leads to its degradation by the 26S proteasome. Inhibition of the proteasome in conjunction with topoisomerase inhibition has shown some promise in the treatment of experimental cancer. Such treatment may impact on the hypoxic adaptation of tumour cells [98]. The UPP is involved in regulation of multiple cellular processes. Hypoxia-inducible factor 1 alpha (HIF-1α) is a prototypic target of the UPP and, as such, is stabilized under conditions of proteasomal inhibition. Using carbonic anhydrase IX (CAIX) and vascular endothelial growth factor (VEGF) expression as paradigmatic markers of HIF-1 activity, we found that proteasomal inhibitors (PI) abrogated hypoxia-induced CAIX expression in all cell lines tested and VEGF expression in two out of three. Mapping of the inhibitory effect identified the C-terminal activation domain (CAD) of HIF-1α as the primary target of PI. PI specifically inhibited the HIF-1 alpha CAD despite activating the HIF-1α coactivator p300 and another p300 cysteine/histidine-rich domain 1dependent transcription factor, STAT-2. Coimmunoprecipitation and glutathione Stransferase pull downs indicated that PI does not disrupt interactions between HIF-1α and p300. Mutational analysis failed to confirm involvement of sites of known or putative posttranslational modifications in regulation of HIF-1α CAD function by PI. Our data provide evidence for the counterintuitive hypothesis that inhibition of HIF-1 function could be responsible for at least some of the antitumor effects of proteasomal inhibition. Further studies of the mechanism of the PI-induced attenuation of HIF-1α will provide important, potentially novel insight into regulation of HIF-1 activity and possibly identify new targets for HIF-directed therapy. Experimental data suggest therapeutic advantage from selective disruption of the hypoxia response. We recently found that the PI bortezomib decreases tumor carbonic anhydrase IX (CAIX) expression in colon cancer patients and herein report a companion laboratory study to test if this effect was the result of HIF inhibition. Human

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cervical (SiHa and Me180) and colon (RKO) carcinoma cell lines were treated with bortezomib or the structurally unrelated PI MG132 in normoxic and hypoxic conditions in vitro. Two different in vivo experiments investigated bortezomib effects after single dose (2 mg/kg, 24 h) or longer exposure in severe combined immunodeficient mice bearing SiHa xenografts. Treatment with either drug produced accumulation of HIF-1alpha in vitro but strongly inhibited the production of CAIX and vascular endothelial growth factor (VEGF) under hypoxia. This correlated with more than 10-fold reduction in HIF-1 transcriptional activity under hypoxic conditions. A similar effect of bortezomib was seen in vivo, using the nitroimidazole probe EF5 to define regions of tumor hypoxia and a triple immunofluorescence technique to measure the spatial distributions of HIF-1alpha and CAIX. Plasma VEGF levels decreased by approximately 90% during treatment with bortezomib, indicating that this agent can potently inhibit the hypoxia response in tumors [100]. Tumor cells under hypoxia already have an active PERK- eIF2α-ATF4 pathway, surviving close to a treshold limit of ER stress. Subjecting of these hypoxic tumor cells to additional ER stress by proteasome inhibitors would force them past their tolerance levels and onto cell death. Bortezomib (also known as PS-341) stimulated the phosphorylation of PERK and the unfolded protein response, resulting in the induction of the transcription factor ATF-4 [101]. Importantly, the Bcl-2 homology domain 3-only (BH3-only) proapoptotic protein Noxa was found to be strongly induced by bortezomib [101]. Brief treatment (4 hours) by proteasome inhibitors (MG132 or bortezomib) does not inhibit protein synthesis by apoptosis as is known to occur after long periods. Proteasome inhibitors activate hemeregulated inhibitor kinase (HRI) and increase significantly phosphorylation of eIF2 and inhibition of global protein synthesis [102].

CONCLUSION AND PERSPECTIVES Specific translational control is known now for many genes during hypoxic stress. The question, what predominant mechanism is used for this control, is not successfully answered. Upstream ORF, IRES, and 5´-terminal oligopyrimidine tracts sequences have been found in some of these transcripts. Translational up-regulation of the EGFR (epidermal growth factor receptor) by tumor hypoxia induced HIF2α activation provides a nonmutational explanation for its overexpression in glioma cells [103]. Amplification of EGFR expression and signaling is a common feature in a variety of human cancers including renal, breast, glioma, ovarian , non-small-cell lung, prostate, pancreatic, and head and neck cancers. Control of mRNA translation during hypoxia in cancer has not been adequately addressed. Tumour hypoxia is a major constraint for radiotherapy and many types of chemotherapy. A variety of different pathogenetic mechanisms contribute to the development of hypoxia in solid tumours. Hypoxia is associated with unfavourable prognosis, regardless of the treatment modality applied. Two different effects have been considered to explain the deleterious effects of hypoxia on the outcome of tumour patients. The first aspect encompasses the direct interference of hypoxia with antineoplastic treatment modalities. The efficacy of ionizing radiation, but also of a variety of cytotoxic drugs and cytokines rely directly on adequate oxygen tensions. The second aspect concerns the effects of hypoxia on the biology of tumour

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and stromal cells. Hypoxia is related to malignant progression, increased invasion, angiogenesis and an increased risk of metastasis formation. Possibly, hypoxia is furthermore a stressor which selects cells with increased resistance to apoptosis and thereby indirectly contributes to treatment resistance. All this considerable experimental and clinical evidence support the notion that hypoxia fundamentally alters the physiology of the tumor towards a more aggressive phenotype [104,105]. Therefore, delineating the mechanisms by which hypoxia affects tumor physiology at the cellular and molecular levels will be crucial for a better understanding of tumor development and metastasis and for designing better antitumor modalities. Disruption of eIF4F varies considerably among different tumors. eIF4F is an important target of phosphatidylinositol 3-kinase signaling during tumor development. PTEN (Phosphatase and Tensin homolog) gene is a human gene that acts as a tumor suppressor gene. PTEN functions as lipid phosphatase to dephosphorylate the D-3 position of phosphoinositide phosphates. This phosphoinositide phosphatase is able to inactivate antiapoptotic Akt kinase activity which is induced following PI3K activation in various growth factor receptor-mediated signaling cascades. PTEN on chromosome 10 is frequently affected by germline and somatic mutations or PTEN is deleted in human cancer. PTEN counteracts the pro-oncogenic effects of elevated PI3K activity by decreasing the intracellular levels of Akt-activating phospholipids [106]. PTEN-/- cells are hypersensitive to growth inhibition by rapamycin and CCI-779 [107]. Rapamycin and its derivatives (ester analogs CCI-779 and RAD 001) showed long-lasting objective tumour responses in clinical trials, with CCI-779 being a first-in-class mTOR inhibitor that improved the survival of patients with advanced renal cell carcinoma [108]. Rapamycin in combination with the protein tyrosine kinase inhibitor Imatinib (Gleevec, STI571) synergises to inhibit bcr/abl transformed cells [109] and rapamycin is effective also in Imatinib-resistant cases [110]. Inhibition of the mammalian target of rapamycin (mTOR) signaling pathway is a potentially useful therapeutic strategy in the treatment of advanced prostate cancer. However mTOR antagonists used as single agents are not likely to result in dramatic clinical responses, so that combination with Imatinib enhanced the anti-proliferative effects of rapamycin [111]. The constitutive activation of the S6 ribosomal protein via mTOR and ERK signaling in the peripheral blasts of acute leukemia patients likely reflets alterations in growth factor signaling and could potentially have prognostic significance. Inhibition of PI3K by a selective inhibitor LY294002 (2-(4morpholinyl)-8-phenyl-4H-1-benzopyran-4-one) and inhibition of MAPK pathway by specific inhibitor UO126 (1,4-Diamino-2,3-dicyano-1,4 bis(2-aminophenylthio)-butadiene) suppressed phosphorylation of S6 ribosomal protein in majority of cases indicating that both, PI3K and ERK pathways contribute to constitutive phosphorylation of the S6 ribosomal protein [112]. Targeting the eIF4E and 4E-BP1 for cancer therapy is described in the further chapter named “The role of eukaryotic translation initiation factor 4E and its binding factors 4E-BP1 and 4E-BP2 in body weight regulation, ageing and tumorigenesis“.

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ACKNOWLEDGEMENTS This work was supported by the grant VZ 00023736 from the Ministry of Health of the Czech Republic, and grant LC 06044 from Ministry of Education, Youth and Sport of the Czech Republic.

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In: Protein Biosynthesis Editors: Toma E. Esterhouse and Lado B. Petrinos

ISBN 978-1-60692-156-2 © 2009 Nova Science Publishers, Inc.

Chapter XIII

THE ROLE OF EUKARYOTIC TRANSLATION INTIATION FACTOR 4E AND ITS BINDING FACTORS 4E-BP1 AND 4E-BP2 IN BODY WEIGHT REGULATION, AGEING AND TUMORIGENESIS Ota Fuchs1,2,∗ 1

2

Institute of Hematology and Blood Transfusion, 128 20 Prague 2, Czech Republic; Center of Experimental Hematology with Institute of Pathophysiology, First Medical Faculty, Charles University, Prague, Czech Republic.

ABSTRACT Translation in eukaryotes is usually regulated at the level of initiation. Translation initiation on the majority of eukaryotic cellular mRNAs is mediated by a cap deperndent mechanism. Eukaryotic translation initiation factor 4E (eIF4E) binds to the mRNA cap structure and interacts with the RNA helicase eIF4A and a large scaffold protein eIF4G to create the eIF4F complex. Binding of eIF4E to eIF4G can be blocked by eIF4Ebinding proteins (4E-BP1 and 4E-BP2) acting as competitive inhibitors of eIF4E-eIF4G interaction. Scaffold protein eIF4G brings the mRNA to the 40 S small ribosomal subunit in a complex with eIF2, GTP and the initiator methionine-transfer RNA by its interaction with eIF3 and forms the 48 S preinitiation complex on the mRNA. Scanning of the mRNA with the aid of eIF4A and recognition of initiation AUG start codon in an optimal context is required and other factors as well as the 60S ribosomal subunit are then recruited and polypeptide chain elongation begins. 4E-BP1 and 4E-BP2 double knockout (DKO) mice were used to determine the physiologic functions of these factors. 4E-BP1 and 4E-BP2 DKO mice had a significant increase in both body weight and fat content. ∗

Correspondence concerning this article should be addressed to: Ota Fuchs, PhD. Tel: +420 221977313; Fax: +420 221977370; E-mail: [email protected].

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Ota Fuchs The obese phenotype was caused by reduced energy expenditure and reduced lipolysis. Both embryonic fibroblasts and preadipocytes from these 4E-BP1 and 4E-BP2 DKO mice had an increased expression of CCAAT/enhancer-binding proteins and of peroxisome proliferator-activated receptor (PPAR) gamma, essential regulators of adipogenesis. Specific knockdown of the main eIF4E isoform in Caenorhabditis elegans resulted in an increased lifespan of the organism. Because eIF4E is the least abundant among translation initiation factors, changes in the levels of this translation initiation factor affect translation rates, preferentially of a subset of mRNAs with strong secondary structure in the 5´ untranslated region encoding proteins such as Myc, fibroblast growth factor, ornithine decarboxylase, cyclin D1, survivin, Bcl-2, matrix metalloprotease 9 and vascular endothelial growth factor. These mRNAs play important roles in the control of cell growth, proliferation, angiogenesis, survival and malignancy. In experimental models, eIF4E overexpression induces cellular transformation, tumorigenesis, invasion, and metastasis, notably cancers as lymphomas, lung and prostatic adenocarcinomas, bladder cancers, cervical cancers, hepatomas, breast tumorigenesis, head and neck cancers, colorectal cancers and angiosarcomas. A better understanding of the role of eIF4E and its binding proteins (eIF4E-BP) in regulating the translation of the diverse gene products involved in tumorigenesis will improve the capacity to exploit eIF4E and eIF4E-BP as therapeutic targets and as markers for human cancer progression. Modulators of the eIF4E activity by peptides containing an eIF4E-binding site, RNA aptamers which bind eIF4E, eIF4E-specific antisense oligonucleotides and small molecule inhibitors of the eIF4E-eIF4G interaction are tested and may be in future used in therapy for the treatment of cancer.

Keywords: eIF4E, eIF4E-BP, mRNA translation, mRNA transport, mTOR kinase, eIF4E phosphorylation, Mnk1, Mnk2, antisense oligonucleotides, aptamers

INTRODUCTION Control of mRNA translation is very important for regulation of gene expression in mammalian cells. Initiation of translation is the rate-limiting step. This step involves the formation of eIF4F complex which contains three subunits: eIF4E, eIF4A, and eIF4G. This complex is required to recruit ribosomal subunits to the mRNA during cap-dependent initiation [1-10]. Cap (7-methyl-GpppN structure at the 5´end of the mRNA, where N is any nucleotide) -dependent translation initiation requires a large number of protein factors that act in a stepwise assembly process. Cap-dependent translation is not, however, the only possibility by which mRNA translation can be initiated. In members of the Picornaviridae family, such as poliovirus or encephalomyocarditis virus (EMCV) mRNA, the 5´ untranslated region (5´-UTR) contains approximately 450 nucleotides long domain necessary for capindependent translation. The term internal ribosomal entry sites (IRESs) was used for this domain [11-14]. Eukaryotic translation initiation factor 4E (eIF4E) availability plays a critical role in the switch from cap-dependent to IRES-mediated viral mRNA translation. Thus, viral mRNAs are preferentialy translated during EMCV and other picornavirus infections. eIF4E plays also a role in the nucleus, where it interacts with a number of homeodomain proteins and regulates cap binding and inhibit mRNA export from the nucleus

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to cytoplasm [15-20]. Promyelocytic leukemia protein (PML) and the proline-rich homeodomain protein (PRH) bind eIF4E and this binding inhibits the cap-eIF4E interaction. The eIF4E activity is controlled by mammalian target of rapamycin (mTOR) through phosphorylation of the eIF4E-binding proteins (4E-BP) [21,22]. mTOR-mediated phosphorylation of 4E-BP liberates eIF-4E enabling assembly of the eIF4F complex. Enhanced eIF4F complex formation increases the translation of all cap-dependent mRNAs and increases protein synthesis rate. eIF4E preferentially enhances translation of a subset of mRNAs, which have lengthy, G and C rich and complex, highly structured 5´ UTRs. These mRNAs are products of expression of transformation-related and survival genes (e.g., c-myc, platet derived growth factor /PDGF/, vascular endothelial growth factor /VEGF/, insulin-like growth factor 2 /IGF-2/, fibroblast growth factor-2 /FGF-2/, cyclin D1, ornithine decarboxylase /ODC/, survivin and others mRNAs) and their translation is highly sensitive to eIF4E availability [21,22]. They are poorly translated under normal conditions when eIF4E level is limiting for the eIF4F complex formation. However, most cellular mRNAs have short and unstructured 5´UTR (e.g., housekeeping genes products GAPDH /glyceraldehyde-3phosphate dehydrogenase/, β-actin and others mRNA) that enable efficient scanning of the 40S ribosomal subunit, initiation codon recognition, second ribosomal subunit loading and translation even when eIF4F complex is limiting.

Figure 1. Primary sequence of eIF4E and three-dimensional structure of eIF4E in a complex with m(7)GDP and peptide from eIF4G. Great sequence conservation was detected in human (Protein Bank Accession No. P06730), mouse (Protein Bank Accession No. P63073) and Sacharomyces cerevisiae (Protein Bank Accession No. P07260) eIF4E. Residues important for cap binding (W56 and W102) and ligand binding (W73) are marked.

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SEQUENCE AND STRUCTURE OF EIF4E Primary structure of 25 kDa eIF4E showed the high degree of sequence conservation from Saccharomyces cerevisiae to human eIF4E (Figure 1) [23-27]. Three long α-helices span the exterior convex surface while two shorter α-helices extend at the perimeter and fold into the interior concave surface of the protein. Eight anti-parallel β-strands form a semi continuous β-sheet within the convex interior of the protein. The shape of eIF4E resembles a baseball glove in which the long helices form the the exterior surface of the glove while the beta sheet form the interior surface of the glove. Within the pocket you will find the m7G residue linked to the 5' end. This cap functions to protect the mRNA from degradation and is essential for efficient protein synthesis. Within the m7G cap binding pocket were found two residues that are absolutly critical for the recognition of the cap structure. These residues are Trp-58 and Trp-104 for yeast eIF4E, TRp-56 and Trp-102 for human eIF4E. Further examination showed additional residues that were important for the stability of the m(7)G cap within the pocket. They include Thr-48, Leu-62, His-94, Val-153, and Trp-166 for yeast eIF4E and corresponding amino acid residues in human eIF4E. Trp-75 for yeast and Trp-73 for human eIF4E are necessary for ligand (eIF4G) binding.

UBIQUITINATION AND PROTEASOME-DEPENDENT DEGRADATION OF EIF4E Despite the importance of eIF4E, little is known about the regulation of eIF4E protein expression levels. Transcription of gene for eIF4E is induced in response to serum, growth factors or immunological activation in T cells [28,29]. State of cellular differentiation also affects levels of the eIF4E [30,31]. The promoter of the gene for eIF4E contains two c-Myc binding sites [32] and a heterogeneous nuclear ribonucleoprotein K-binding site [33], both of which are critical for regulation of eIF4E on the transcriptional level. Othumpangat et al. [34,35] showed that exposure of human cell lines to cadmium or to sodium arsenite (NaAsO2) resulted in enhanced ubiquitination of eIF4E protein while inhibitors of proteasome activity reversed the cadmium or sodium arsenite-induced decrease of eIF4E protein. Ubiquitination and proteasome degradation of eIF4E was confirmed in the human embryonic kidney 293T cells [35]. eIF4E is ubiquitinated primarily at Lys-159 and incubation of cells with a proteasome inhibitor MG132 leads to increased eIF4E levels. Because heat shock or the expression of the carboxyl terminus of heat shock cognate protein 70-interacting protein (Chip) dramatically increased eIF4E ubiquitination, Chip may be at least one ubiquitin E3 ligase responsible for eIF4E ubiquitination. The ubiquitination of eIF4E may be affected by its phosphorylation, cap binding, and eIF4G binding. Residues responsible for these events (Ser-209, the residue phosphorylated by mitogen-activated protein kinases /MAPK/; Trp-56, a residue located within the eIF4E hydrophobic pocket, required for cap binding and Trp-73, a residue essential for the interaction of eIF4E with eIF4G/4E-BP) were mutated and the effect of these mutations on ubiquitination was studied [36]. Although the ubiquitination of either S209A or W56A eIF4E was comparable with that

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seen with wild type eIF4E, the ubiquitination of the W73A mutant was dramatically increased, suggesting a role of eIF4G/4E-BP association in regulating eIF4E ubiquitination.

PHOSPHORYLATION OF EIF4E Mnk1 and Mnk2 are protein kinases that are directly phosphorylated and activated by extracellular signal-regulated kinase (ERK) or p38 mitogen-activated protein (MAP) kinases and implicated in the regulation of protein synthesis through their phosphorylation of eIF4E at Ser-209 [37-40] (Figure 2). To investigate their physiological functions, mice lacking the Mnk1 or Mnk2 gene or both were generated. The resulting KO mice were viable, fertile, and developed normally. In embryonic fibroblasts prepared from Mnk1-Mnk2 DKO mice, eIF4E was not detectably phosphorylated at Ser-209, even when the ERK and/or p38 MAP kinases were activated. Analysis of embryonic fibroblasts from single KO mice revealed that Mnk1 is responsible for the inducible phosphorylation of eIF4E in response to MAP kinase activation, whereas Mnk2 mainly contributes to eIF4E's basal, constitutive phosphorylation. Lipopolysaccharide (LPS)- or insulin-induced upregulation of eIF4E phosphorylation in the spleen, liver, or skeletal muscle was abolished in Mnk1(-/-) mice, whereas the basal eIF4E phosphorylation levels were decreased in Mnk2(-/-) mice. In Mnk1-Mnk2 DKO mice, no phosphorylated eIF4E was detected in any tissue studied, even after LPS or insulin injection. However, neither general protein synthesis nor cap-dependent translation, as assayed by a bicistronic reporter assay system, was affected in Mnk-deficient embryonic fibroblasts, despite the absence of phosphorylated eIF4E. Thus, Mnk1 and Mnk2 are exclusive eIF4E kinases both in cultured fibroblasts and adult tissues, and they regulate inducible and constitutive eIF4E phosphorylation, respectively. These results strongly suggest that eIF4E phosphorylation at Ser-209 is not essential for cell growth during development. However, it has been shown that phosphorylation of eIF4E stimulates export eIF4E mRNA and its transformation activity [18,19]. Decrease in eIF4E phosphorylation was observed during viral infections due to the viral protein binding to eIF4G and displacing the Mnks [41,42]. Adenovirus prevents cellular translation by displacing Mnk1 from eIF4F, thereby blocking phosphorylation of eIF4E. Over expression of an eIF4E mutant that cannot be phosphorylated by Mnk1 impairs translation of cellular but not viral late mRNAs. Adenovirus 100k protein is shown to bind the C-terminus of eIF4G in vivo and in vitro, the same region bound by Mnk1. In vivo, viral 100k protein displaces Mnk1 from eIF4G during adenovirus infection, or in transfected cells. Purified 100k protein also evicts Mnk1 from isolated eIF4F complexes in vitro. A mutant adenovirus with a temperature-sensitive 100k protein that cannot inhibit cellular protein synthesis at restrictive temperature no longer blocks Mnk1 binding to eIF4G, or phosphorylation of eIF4E. We describe a mechanism whereby adenovirus selectively inhibits the translation of cellular but not viral mRNAs by displacement of Mnk1 from eIF4G and inhibition of eIF4E phosphorylation.

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COMPLEX FORMATION AND CAP-DEPENDENT TRANSLATION

Initiation of cap-dependent translation starts in the nucleus where eIF4E associates with a capped transcript facilitating nuclear export of selected mRNAs. In the cytoplasm, eIF4EmRNA complexes associate with eIF4G, which serves a docking function. NH2 –terminal one-third of the eIF4G binds eIF4E and COOH-terminal two thirds of the eIF4G associate in the same time with the helicase eIF4A [1-10]. eIF4G has also recognition sites for the poly(A)-binding protein (PABP), for the multimeric factor eIF3 and for the protein kinases Mnk1 and Mnk2. eIF3 directs the initiation complex to the 40S ribosomal subunit. The role of proteinkinases Mnk1 and Mnk2 in phosphorylation of the eIF4E was described above. The eIF3 complex can also associate with the mammalian target of rapamycin (mTOR) [43]. eIF4G bound to eIF4E and mRNA brings the 5´ end of mRNA in proximity to the 3´ poly(A) tail, the small ribosome subunit and protein kinases Mnk1 and Mnk2. Complex scans along the 5´ UTR of the transcript toward the initiation codon. eIF4A unwinds secondary structure in the 5´ UTR and facilitates scanning. eIF4E is the least abundant component in comparison with others, which are needed for initiation of translation under physiological conditions. Thus, eIF4E is rate-limiting component in translation initiation process.

NUCLEAR CAP-BINDING COMPLEX AND PIONEER ROUND OF TRANSLATION In eukaryotes the majority of mRNAs have an m(7)G cap that is added cotranscriptionally and that plays an important role in many aspects of mRNA metabolism. The nuclear cap-binding complex (CBC; consisting of CBP20 and CBP80) mediates the stimulatory functions of the cap in pre-mRNA splicing, 3' end formation, and U snRNA export. Proteins that interact with CBC in HeLa cell nuclear extracts were characterized as potential mediators of its function. Using cross-linking and coimmunoprecipitation, McKendrick et al. [44] showed that eIF4G, in addition to its function in the cytoplasm, is a nuclear CBC-interacting protein. eIF4G interacts with CBC in vitro and that, in addition to its cytoplasmic localization, there is a significant nuclear pool of eIF4G in mammalian cells in vivo. Immunoprecipitation experiments suggest that, in contrast to the cytoplasmic pool, much of the nuclear eIF4G is not associated with eIF4E (translation cap binding protein of eIF4F) but is associated with CBC. While eIF4G stably associates with spliceosomes in vitro and shows close association with spliceosomal snRNPs and splicing factors in vivo, depletion studies show that it does not participate directly in the splicing reaction. Taken together the data indicate that nuclear eIF4G may be recruited to pre-mRNAs via its interaction with CBC and accompanies the mRNA to the cytoplasm, facilitating the switching of CBC for eIF4F. This may provide a mechanism to couple nuclear and cytoplasmic functions of the mRNA cap structure [44]. Nonsense-mediated decay (NMD) eliminates mRNAs that prematurely terminate translation [45]. Antibody to the nuclear cap binding protein CBP80 or its cytoplasmic

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counterpart eIF4E was used to immunopurify RNP containing nonsense-free or nonsensecontaining transcripts. Data indicate that NMD takes place in association with CBP80. Other components of NMD-susceptible mRNP as CBP20, PABP2, eIF4G, and the NMD factors Upf2 and Upf3 were defined. Consistent with the dependence of NMD on translation, the NMD of CBP80-bound mRNA is blocked by cycloheximide or suppressor tRNA. These findings provide evidence that translation can take place in association with CBP80. They also indicate that CBP80-bound mRNA undergoes a "pioneer" round of translation, before CBP80-CBP20 are replaced by eIF4E, and Upf2 and Upf3 proteins dissociate from upstream of exon-exon junctions [45]. Pioneer round of translation, which can be assessed by measuring NMD, is not inhibited by 4E-BP1, which is known to inhibit steady-state translation by competing with eIF4G for binding to eIF4E. Therefore, at least in this way, the pioneer round of translation is distinct from steady-state translation [46]. On the other hand, both ways of translation involve several same transcription factors (eIF4G, eIF3, eIF4A and eIF2), despite both modes of translation use distinct mRNP substrates [46].

Figure 2. Schema of eIF4E and its binding partners (eIF4G, 4E-BP1, 4E-T, Mnks) and their function. Binding of 4E-BP1 to eIF4E prevents the formation of eIF4F complexes by competing with eIF4G. The phosphorylation of 4E-BP1 prevents its binding to eIF4E. The Mnks are activated by phosphorylation and phosphorylate eIF4E. 4E-T is phosphoprotein involved in eIF4E transportation. The kinase which phosphorylates 4E-T is unknown and the effect of this phosphorylation is also unclear.

EFFECT OF ENVIRONMENTAL SIGNALS ON NUCLEAR AND CYTOPLASMIC INTERACTIONS OF EIF4E eIF4E was found in both, nucleus (about 60-70% of eIF4E) and cytoplasm of cells. eIF4E enters the nucleus by binding to its transporter (4E-T) (Figure 2). Overexpression of 4E-T preferentially inhibits cap-dependent steady-state translation, but not the pioneer round

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of translation. Overexpression of 4E-T triggers the movement of eIF4E into the processing bodies (cytoplasmic P bodies where mRNAs are destructed) (Figure 2). The majority of nuclear eIF4E colocalises with promyelocytic leukemia protein (PML) nuclear bodies. Nuclear eIF4E regulates gene expression by facilitating the nuclear-cytoplasmic export of a subset of mRNAs encoding growth promoters but does not alter the transport of mRNAs for housekeeping proteins. Overexpression of eIF4E dramatically increases the nuclearcytoplasmic transport of the cyclin D1 transcript and causes malignant transformation of cells, while nuclear export of mRNAs for GADPH or β-actin is unaltered [47-51]. Nuclear eIF4E promotes the transport of cyclin D1 mRNA from the nucleus to the cytoplasm and promyelocytic leukemia protein (PML) is a key negative regulator of this function [52,53]. Therefore, PML has the transformation suppression activity. eIF4E-dependent transport is modulated in response to environmental conditions [54]. Cadmium treatment, which disperses PML nuclear bodies, leaves eIF4E bodies intact, leading to increased transport of cyclin D1 mRNA and increased cyclin D1 protein levels. Removal of cadmium allows PML to reassociate with eIF4E nuclear bodies, leading to decreased cyclin D1 transport and reduced cyclin D1 protein levels. In contrast, treating cells with interferon increased the levels of PML protein at the PML-eIF4E nuclear body, leading to nuclear retention of cyclin D1 transcripts and reduced cyclin D1 protein levels. Neither interferon nor cadmium treatment altered cyclin D1 levels in PML(-/-) cells. Consistently, overexpression of a series of PML and eIF4E mutant proteins established that PML eIF4E interaction is required for the observed effects of cadmium and interferon treatment. Physiological factors modulate the mRNA transport functions of eIF4E and that this regulation is PML dependent [54]. Elevated eIF4E impedes granulocytic and monocytic differentiation and contributes to leukemogenesis, specifically in a subset of acute and chronic myelogenous leukemia patients [55]. Mutagenesis studies indicate that this block is a result of dysregulated eIF4E-dependent mRNA transport. The cytoplasmic interaction of eIF4E and eIF4G is also regulated by extracellular signals and metabolic needs. In nontransformed mammalian cells, an increase in translation rates are necessary for entry into and transit through G1 phase of the cell cycle [56]. Abundance of the eIF4E is low in cultured quiescent fibroblasts. Levels of eIF4E rise sharply in response to mitogenic stimulation, peaking at the late G1 phase of the cell cycle before entry into S phase. Regulation of transcriptional level of eIF4E expression was described above [28-33]. The association of free eIF4E with the mRNA cap is much less stable than the interaction of capped mRNAs with eIF4E-eIF4G complex [15]. IF4G uses a conserved Tyr-X-X-X-X-Leuphi segment (where X is variable and phi is hydrophobic residue) to recognize eIF4E during cap-dependent translation initiation in eukaryotes. High-resolution X-ray crystallography and complementary biophysical methods have revealed that this eIF4E recognition motif undergoes a disorder-to-order transition, adopting an L-shaped, extended chain/alpha-helical conformation when it interacts with a phylogenetically invariant portion of the convex surface of eIF4E. Inhibitors of translation initiation known as eIF4E-binding proteins (4EBPs) contain similar eIF4E recognition motifs. These molecules are molecular mimics of eIF4G, which act by occupying the same binding site on the eIF4E (Tyr-X-X-X-X-Leu-phi motif). They block assembly of the translation machinery and function as translational repressors [57].

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PROTEINS AND THEIR PHOSPHORYLATION AND UBIQUITINATION

Cap-dependent translation is dependent on assembly of the eIF4F complex, which is inhibited by the family of eIF4E-binding proteins (4E-BPs; also known as PHAS /phosphorylated heat- and acid-stable/). This family contains three small (10-12 kD) acidic proteins designated 4E-BP1, -BP2 and BP3 [25,58-62]. 4E-BP3 is homologous to 4E-BP1 and 4E-BP2, exhibiting 57 and 59% identity, respectively. The homology is most striking in the middle region of the protein, which contains the eIF4E binding motif and residues that are phosphorylated in 4E-BP1. 4E-BP3 is a heat stable protein that binds to eIF4E in vitro as well as in vivo in both cell compartments, the cytoplasm and the nucleus [63,64]. Binding of the 4E-BPs to eIF4E is reversible and is dependent on the phosphorylation status of 4E-BP. Hypophosphorylated 4E-BP1 interacts strongly with eIF4E. Binding of 4E-BP to eI4F4E decreases with increased phosphorylation of 4E-BP1 at multiple sites (Figure 2). The phosphorylation of 4E-BP1 is increased by a wide range of extracellular stimuli, such as hormones, mitogens, growth factors, cytokines, and G-protein-coupled receptor agonists). All these extracellular stimuli increase translation rate. Conversely, nutrient or growth factor deprivation results in 4E-BP1 dephosphorylation and decrease cap-dependent translation [6568]. Phosphorylation of 4E-BP1 on Thr-37 and Thr-46 is relatively insensitive to serum deprivation and rapamycin treatmen. Phosphorylation of these residues is required for the subsequent phosphorylation of a set of unidentified serum-responsive sites. Using mass spectrometry, the serum-responsive, rapamycin-sensitive sites Ser-65 and Thr-70 were detected [69]. Utilizing a novel combination of two-dimensional isoelectric focusing/SDSPAGE and Western blotting with phosphospecific antibodies, the order of 4E-BP1 phosphorylation in vivo was established (Figure 3). Phosphorylation of Thr-37/Thr-46 is followed by Thr-70 phosphorylation. Ser-65 is phosphorylated last. Phosphorylation of Ser65 and Thr-70 alone is insufficient to block binding to eIF4E, indicating that a combination of phosphorylation events is necessary to dissociate 4E-BP1 from eIF4E [69]. Phosphoinositide 3-kinase (PI3K) and its downstream effector, the serine-threonine kinase Akt (also known as protein kinase B) are involved in the pathway leading to 4E-BP1 phosphorylation [66,68,70]. Treatment of cells with two potent PI3K inhibitors, LY294002 and wortmannin, prevents 4E-BP1 hyperphosphorylation following hormone or growth factor stimulation. On the other hand, expression of an activated form of the PI3K increases 4E-BP1 phosphorylation. Conversely, overexpression of Akt without kinase activity prevents insulininduced 4E-BP1 phosphorylation [70]. Expression of the activated Akt mutant confers wortmanin but not rapamycin resistance to 4E-BP1 phosphorylation [70]. Thus, rapamycinsensitive component of signaling pathway in the 4E-BP1 phosphorylation cascade lies downstream of Akt. Rapamycin is a macrolide antibiotic originally isolated from Streptomyces hygroscopicus [71]. Rapamycin is the immunosuppressive drug with similar biochemical structure to cyclosporin A and FK506. Rapamycin acts as an inhibitor of G1 cell cycle progression and blocks the activation of p70S6k. The rapamycin-sensitive component of signaling pathway in the 4E-BP1 phosphorylation is FRAP/mTOR (FKBP12-rapamycin associated protein/ mammalian target of rapamycin), also known as RAFT1 (rapamycin and 12 kD FK506 binding protein target 1)(Figure 4). Rapamycin in a complex with the

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immunophilin FKBP-12 binds to FRAP/mTOR to inhibit its function (Figure 4). Amino acid deprivation decreases the phosphorylation of 4E-BP1 through modulation of FRAP/mTOR activity [72-74]. Thus, mTOR is a well-conserved serine/threonine protein kinase that functions as an intracellular nutrient sensor to control protein synthesis, cell growth, and metabolism.

Figure 3. mTOR-regulated phosphorylation of 4E-BP1. This phosphorylation occurs at least on four sites and results in the release of eIF4E from 4E-BP1. The N-terminal sites depends on the N-terminal RAIP motif, whereas phosphorylation of Ser-65 and Thr-70 depends on both motifs, RAIP and TOS. The order of 4E-BP1 phosphorylation in vivo was established. Phosphorylation of Thr-37/Thr-46 is followed by Thr-70 phosphorylation. Ser-65 is phosphorylated last. Phosphorylation of Ser-65 and Thr70 alone is insufficient to block binding to eIF4E, indicating that a combination of phosphorylation events is necessary to dissociate 4E-BP1 from eIF4E.

It remains unclear whether mTOR directly phosphorylates all the regulated sites in 4EBP1 [75]. Some may be targets for other kinases that are associated with and/or controlled by mTOR. Importance of 4E-BP for the regulation of overall protein synthesis remains still unclear. Knockouts of 4E-BP1 and 4E-BP2 do not have general phenotypes. Reported effects were detected in specific tissues such as fat and brain, respectively, in which these proteins are expressed at very high levels [76-80]. Many tissues express both proteins, 4E-BP1 and 4E-BP2, leading to redundancy in function. 4E-BP1 is a substrate for polyubiquitination and some forms of 4E-BP1 are simultaneously polyubiquitinated and phosphorylated [81] (Figure 5). Calyculin A, a potent inhibitor of protein phosphatases, decreases stability of 4E-BP1 protein. The phosphorylation of 4E-BP1 plays a dual role in the regulation of protein synthesis. It reduces the affinity of 4E-BP1 for eIF4E and promotes polyubiquitination of 4E-BP1. Induction or activation of the tumour suppressor protein p53 rapidly leads to 4E-BP1 dephosphorylation, resulting in sequestration of eIF4E, decreased formation of the eIF4F complex and inhibition of protein synthesis [82]. Activation of p53 also results in modification of 4E-BP1 to a truncated form [83]. Unlike full-length 4E-BP1, which is reversibly phosphorylated at multiple sites, the truncated protein is almost completely unphosphorylated. Moreover the latter interacts with eIF4E in preference to full-length 4E-BP1. Inhibitor studies indicate that the p53-induced cleavage of 4E-BP1 is mediated by the proteasome. Measurements of the turnover of 4E-BP1 indicate that the truncated form is much more stable than the full-length protein. The data

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suggest a model in which proteasome activity gives rise to a stable, hypophosphorylated and truncated form of 4E-BP1 which may exert a long-term inhibitory effect on the availability of eIF4E, thus contributing to the inhibition of protein synthesis and the growth inhibitory and pro-apoptotic effects of p53 [83].

Figure 4. A schematic depiction of mTOR and MAPK signaling in the regulation of translation. mTOR is regulated by multiple inputs, such as for example growth factors, to control translation. Arrows indicate activation and bars indicate inhibition. Activation of PI3K and Ras leads to a cascade of phosphorylation events that results in phosphorylation of the 4E-BP1, its dissociation from eIF4E and an increase in translation. The translational activity of eIF4E can be also modulated by phosphorylation via Mnk1 (MAP kinase-interacting protein kinase-1) which is activated through the Ras-regulated MAPK cascade.

4E-BP1 AND 4E-BP2 DOUBLE KNOCKOUT MICE-A LINK BETWEEN PROTEIN TRANSLATION, INSULIN RESISTANCE AND OBESITY To determine the physiologic functions of 4E-BP1 an 4E-BP2, Le Bacquer et al. [79] simultaneously deleted the both these genes in mice. They obtained double knockout (DKO) mice which had a significant increase in body weight and fat content. The obese phenotype was the result of reduced energy expenditure and of reduced lipolysis. Insulin resistance was

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induced simultaneously. Embryonic fibroblasts and preadipocytes from DKO mice had an increased ability to differentiate into adipocytes. Expression of key regulators of this differentiation (CCAAT/enhancer-binding proteins and PPARγ /peroxisome proliferatoractivated receptor gamma/) is induced prior to the transcriptional activation of most adipocyte-specific genes. Furthermore, PPARγ is required to promote fat cell differentiation. On the contrary, single deletion of 4E-BP1 in mouse led to decreased adipocyte differentiation, 10% reduction in body weight and to increased energy expenditure [77]. The discrepancy between DKO mice and 4E-BP1-deficient mice is obviously the result of two different genetic backgrounds in which knockouts were realised.

Figure 5. 4E-BP1 as a substrate for polyubiquitination and phosphorylation. Calyculin A, a potent inhibitor of protein phosphatases, inhibits dephosphorylation of 4E-BP1 and decreases stability of 4EBP1 protein. The phosphorylation of 4E-BP1 plays a dual role in the regulation of protein synthesis. It reduces the affinity of 4E-BP1 for eIF4E and promotes polyubiquitination of 4E-BP1 and its degradation by proteasomes. Proteasome inhibitor MG132 causes dephosphorylation of 4E-BP1 and stabilizes this protein.

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MODULATOR OF AGEING IN CAENORHABDITIS ELEGANS

Regulation of protein synthesis is critical for cell growth and maintenance. Ageing in many organisms, including humans, is accompanied by marked alterations in both general and specific protein synthesis. Whether these alterations are simply a consequence of the ageing process or have a causative role in senescent decline remains unclear. An array of protein factors facilitates the tight control of messenger RNA translation initiation. The eukaryotic initiation factor 4E (eIF4E), which binds the 7-monomethyl guanosine cap at the 5' end of all nuclear mRNAs, is a principal regulator of protein synthesis. The loss of a specific eIF4E isoform (IFE-2) that functions in somatic tissues reduces global protein synthesis, protects from oxidative stress and extends lifespan in Caenorhabditis elegans [84]. Lifespan extension is independent of the forkhead transcription factor DAF-16, which mediates the effects of the insulin-like signalling pathway on ageing. Furthermore, IFE-2 deficiency further extends the lifespan of long-lived age and daf nematode mutants. Similarly, lack of IFE-2 enhances the long-lived phenotype of clk and dietary-restricted eat mutant animals. Knockdown of target of rapamycin (TOR), a phosphatidylinositol kinaserelated kinase that controls protein synthesis in response to nutrient cues, further increases the longevity of ife-2 mutants. Thus, signalling via eIF4E in the soma is a newly discovered pathway influencing ageing in C. elegans [84].

EIF4E IN

CANCER

As was described above, elevated eIF4E function in cancer selectively increases translation of so called “weak” mRNAs encoding potent growth, and survival factors involved in malignancy such as c-myc, ODC, VEGF, IGF2, FGF2, cyclin D1, Bcl-2, survivin, etc. [47-50, 85-90] (Figure 6). Selectively increased expression of these genes can induce cellular transformation and tumorigenesis. Ectopic eIF4E expression in transgenic mice increases the incidence of multiple cancers, including lymphomas, lung adenocarcinomas, hepatomas, and angiosarcomas and accelerates lymphomagenesis [91]. eIF4E is overexpressed in several tumors and has been linked to patient prognosis [85-90,9294]. Reducing or inhibiting eIF4E function suppresses malignancy by decreasing expression of potent growth and angiogenesis factors [95-99]. eIF4E affects cancer-related processes such as apoptosis [100,101] and senescence [93]. Phosphorylated eIF4E promotes tumorigenesis primarily by suppressing apoptosis. The anti-apoptotic protein Mcl-1 is one target of both phospho-eIF4E and MNK1 that contributes to tumor formation [101]. Many chemotherapeutic agents induce apoptosis, and so disruption of apoptosis during tumour evolution can promote drug resistance. For example, Akt is an apoptotic regulator that is activated in many cancers and may promote drug resistance in vitro. Nevertheless, how Akt disables apoptosis and its contribution to clinical drug resistance are unclear. Using a murine lymphoma model, Wendel et al. [102] showed that Akt promotes tumorigenesis and drug resistance by disrupting apoptosis, and that disruption of Akt signalling using the mTOR

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inhibitor rapamycin reverses chemoresistance in lymphomas expressing Akt, but not in those with other apoptotic defects. eIF4E, a translational regulator that acts downstream of Akt and mTOR, recapitulates Akt's action in tumorigenesis and drug resistance, but is unable to confer sensitivity to rapamycin and chemotherapy. eIF4E acts as an oncogene alone or in combination with c-myc [93,101,102].

Figure 6. Inhibition of eIF4E function as a strategy for the treatment of many different cancers. Reducing eIF4E expression in tumors inhibits cell proliferation, suppresses tumor-related angiogenesis, represses metastasis, and increases apoptosis by selectively repressing the expression of potent growth and survival factors such as c-myc, ODC, VEGF, IGF2, FGF2, cyclin D1, Bcl-2, survivin, etc. These products of “weak” mRNAs become selectively increased with higher free eIF4E, which results in increased active eIF4F complex. Increased translation of these weak mRNAs increases with malignant progression in relation to increased free eIF4E.

ANTICANCER THERAPY BASED ON THE TARGETING EIF4E AND EIF4F COMPLEXES AND ON MODULATION OF EIF4E ACTIVITY Aptamers are oligonucleic acid or peptide molecules that bind a specific target molecule. Aptamers are usually created by selecting them from a large random sequence pool, but natural aptamers also exist in riboswitches. Nakamura and his coworkers [103,104]

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developed RNA aptamers to mammalian initiation factors 4E and 4G. These aptamers inhibited cap-dependent translation by blocking the formation of initiation factor complexes. eIF4E-specific antisense oligonucleotides (ASOs) designed to have the necessary tissue stability and nuclease resistance required for systemic anticancer therapy were developed in Graff´s laboratory [105,106]. In mammalian cultured cells, these ASOs specifically targeted the IF4E mRNA for destruction, repressing expression of eIF4E-regulated proteins (e.g., VEGF, cyclin D1, survivin, c-myc, Bcl-2), inducing apoptosis, and preventing endothelial cells from forming vessel-like tube structures. Thus, eIF4E plays a role in the response of endothelial cells to angiogenic stimuli. Most importantly, intravenous ASO administration selectively and significantly reduced eIF4E expression in human tumor xenografts, significantly suppressing tumor growth. Because these ASOs also target murine eIF4E, we assessed the impact of eIF4E reduction in normal tissues. Despite reducing eIF4E levels by 80% in mouse liver, eIF4E-specific ASO administration did not affect body weight, organ weight, or liver transaminase levels, thereby providing the first in vivo evidence that cancers may be more susceptible to eIF4E inhibition than normal tissues. These data show that targeting eIF4E elicit an antitumor effect and selectively diminish the expression of multiple proteins important to malignancy. These results have prompted eIF4E-specific ASO clinical trials for the treatment of human cancers [91]. The eIF4E/eIF4G complex is regulated by the 4E-BPs, which compete with eIF4G for binding to eIF4E and which have tumor-suppressor activity. To pharmacologically mimic 4EBP function Wagner´s laboratory [107] developed a high-throughput screening assay for identifying small-molecule inhibitors of the eIF4E/eIF4G interaction. The most potent compound identified, 4EGI-1, binds eIF4E, disrupts eIF4E/eIF4G association, and inhibits cap-dependent translation but not initiation factor-independent translation. While 4EGI-1 displaces eIF4G from eIF4E, it effectively enhances 4E-BP1 association both in vitro and in cells. 4EGI-1 inhibits cellular expression of oncogenic proteins encoded by weak mRNAs, exhibits activity against multiple cancer cell lines, and appears to have a preferential effect on transformed versus nontransformed cells. The identification of this compound provides a new tool for studying translational control and establishes a possible new strategy for cancer therapy [107].

ACKNOWLEDGEMENTS This work was supported by the grant VZ 00023736 from the Ministry of Health of the Czech Republic, and grant LC 06044 from Ministry of Education, Youth and Sport of the Czech Republic.

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INDEX A abdominal, 124 aberrant, 70, 88, 93, 207 abiotic, 251 abnormalities, 205, 220 absorption, 262, 267 abundance, 314 acceptor, 58, 71, 73, 74, 76, 81, 96, 97, 101, 102 access, 88, 134, 135, 167, 257 accessibility, 183 acclimatization, 251, 256, 261, 264, 265 accommodation, 67 accounting, 110 accuracy, 16, 36, 56, 60 acetate, 186, 271 acetic acid, 17 acetone, 183 acetylation, 202, 293 acetylcholine, 14, 20, 203 acetylcholinesterase, 166, 187 acid, 23, 30, 59, 74, 75, 97, 102, 117, 118, 119, 129, 130, 134, 152, 156, 158, 161, 177, 178, 182, 183, 196, 203, 216, 218, 225, 229, 230, 232, 233, 261, 315, 316, 320, 323, 326 acidic, 25, 30, 178, 315 acoustic, 164 actin, 112, 198, 199, 210, 211, 212, 274, 309, 314 activation, 4, 5, 14, 15, 20, 23, 112, 114, 115, 117, 119, 120, 121, 128, 129, 158, 163, 196, 197, 199, 200, 202, 203, 204, 205, 208, 210, 215, 216, 217, 218, 219, 220, 222, 242, 243, 244, 272, 281, 282, 283, 284, 285, 287, 288,

289, 290, 291, 294, 295, 296, 297, 301, 302, 304, 305, 310, 311, 315, 316, 317, 318, 323 active site, 67, 242 acute, 116, 117, 119, 121, 123, 128, 289, 298, 299, 306, 314 acute leukemia, 298, 306 acylation, 226 adaptation, 118, 296, 302 adenine, 25, 32, 36, 55, 60, 74, 280 adenocarcinomas, 308, 319 adenoma, 274 adenovirus, 311 adhesion, 198, 203 adipocyte, 318 adipocytes, 127, 318, 326 adipose, 9, 118 adipose tissue, 9, 118 administration, 116, 118, 119, 120, 121, 122, 124, 125, 129, 156, 279, 321 adrenal cortex, 151 adrenal gland, 134, 153, 158 adsorption, 192 adult, 3, 20, 133, 134, 136, 137, 138, 139, 141, 144, 145, 147, 149, 150, 151, 153, 154, 222, 311 adult tissues, 311 adulthood, 3 adults, 120, 129 Aedes, 246 aerobic, 259 age, 1, 2, 6, 10, 11, 21, 64, 153, 207, 251, 263, 319

332 ageing, 1, 2, 3, 6, 7, 8, 9, 10, 11, 298, 319, 327 agent, 163, 168, 185, 186, 297 agents, 8, 118, 135, 175, 178, 183, 185, 186, 193, 236, 279, 298, 306 aggression, 206, 221 aging, 9, 10, 11, 125, 133, 134, 135, 139, 140, 142, 143, 144, 145, 148, 149, 150, 151, 153, 154, 156, 157, 158, 160, 161, 207, 222 aging population, 207 agonist, 118, 201, 207, 283 aid, 186, 307 alanine, 69, 74, 75, 76, 79, 83, 85, 94, 99, 102, 118, 289 albumin, 179, 192 algorithm, 239, 244 allele, 289 alleles, 17 allosteric, 64, 113 alpha, 20, 78, 83, 101, 118, 183, 193, 196, 198, 210, 216, 217, 236, 243, 245, 247, 280, 284, 285, 286, 290, 296, 301, 302, 314, 323 alternative, 80, 90, 94, 292, 303 alters, 117, 126, 202, 269, 298 aluminum, 135 Alzheimer, 1, 6, 195, 197, 205 amide, viii, 13, 15, 167, 228, 229, 239 amine, 175, 180, 184, 186 amino, 2, 4, 6, 13, 14, 15, 30, 39, 58, 60, 71, 73, 74, 75, 76, 79, 81, 90, 93, 94, 101, 109, 110, 111, 112, 116, 117, 118, 119, 120, 121, 122, 124, 125, 126, 127, 129, 133, 136, 137, 139, 140, 142, 150, 182, 185, 196, 207, 225, 226, 228, 229, 230, 232, 233, 234, 239, 241, 245, 250, 251, 256, 257, 280, 283, 290, 294, 302, 310, 326 aminoglycosides, 87, 100 ammonia, 264 amphibia, 245, 248 amphibians, 235, 237, 238 Amsterdam, 282 amygdala, 204, 218, 221 amyloid, 197, 201, 206, 215, 221, 222, 223 amyloid beta, 221 amyloid precursor protein, 197, 215, 221, 222, 223 anabolic, 109, 111, 116, 118, 120, 129 anabolism, 126, 257 analog, 65 analytical tools, 166, 168

Index angiogenesis, 286, 298, 299, 302, 303, 308, 319, 320 angiogenic, 286, 299, 321 anhydrase, 179, 180, 181, 296 animal care, 135 animal models, 268 animals, 3, 4, 8, 10, 15, 18, 19, 115, 122, 134, 135, 136, 141, 144, 147, 149, 150, 151, 152, 153, 154, 201, 207, 227, 237, 238, 250, 251, 253, 254, 256, 258, 261, 262, 263, 264, 319 anisotropy, 182 anoxia, 286, 295, 302 antagonist, 116, 124, 127, 130, 131, 204, 306 antagonists, 298 Antarctic, 249, 252, 258, 260, 261, 262, 263, 264 anthrax, 166, 187, 228, 241 antiangiogenic, 285 antiapoptotic, 328 anti-apoptotic, 298, 319 antibacterial, 228, 247 antibiotic, 23, 62, 63, 191, 315, 326 antibiotics, 63, 96, 102, 110, 175, 190, 191, 245, 273 antibody, 79, 121, 125, 168 anticancer, 300, 303, 306, 321 anti-cancer, 178 anticodon, 25, 32, 33, 35, 36, 39, 41, 50, 53, 54, 55, 57, 58, 59, 60, 63, 69, 74, 76, 81, 82, 83, 84, 85, 86, 87, 104 antidiabetic, 268, 276, 279 antigen, 228, 241, 244 antimicrobial, 228, 230, 232, 235, 236, 237, 238, 239, 244, 245, 246, 248 antineoplastic, 297 antioxidant, 292 antisense, 308, 321, 328 anti-sense, 115 antisense oligonucleotides, 308, 321 antisense RNA, 328 antiserum, 246 antitoxin, 96 antitumor, 296, 298, 321 antiviral, 64, 178 anxiolytic, 247 aortic aneurysm, 285 apoptosis, 9, 226, 242, 297, 298, 300, 301, 305, 319, 320, 321, 326, 328 apoptotic, 295, 317, 319 apoptotic effect, 317 appetite, 259

Index application, 149, 154, 156, 164, 166, 186, 187, 277, 278, 281 aquatic, 249, 250, 258 Arabidopsis thaliana, 31, 280 arachnids, 237, 238 arginine, 20, 30, 88, 89, 98, 180, 232, 241, 243 aromatic, 39 arousal, 247 arrest, 9, 91, 286, 288, 289, 291, 294, 300 arsenite, 310, 324 artificial, 191, 193 ascorbic, 152 ascorbic acid, 152 assessment, 21 associations, 176 asymmetry, 270, 281 atherosclerosis, 6 Atlantic, 259, 263 atomic distances, 32, 33 atoms, 25, 31, 35, 39 ATPase, 268, 281 attachment, 32, 178, 198, 271 attention, 31, 234, 267 atypical, 184 auditory stimuli, 223 Australia, 155 autism, 195, 197, 206, 207, 208 automation, 167, 171 autophagy, 6 autoradiography, 155, 160 availability, 1, 8, 110, 113, 115, 116, 120, 121, 130, 179, 182, 258, 285, 288, 289, 300, 308, 309, 317, 326 avian influenza, 228, 244 avoidance, 218 awareness, 164 axon, 195 axons, 195, 205

B B. subtilis, 74, 78, 88, 90, 92, 93, 94 Bacillus subtilis, 31, 71, 97, 99, 101, 102, 103, 104, 105 Back to Basic, 187 bacteremia, 129 bacteria, 78, 93, 97, 106, 107, 252, 269, 273 bacterial, 17, 38, 66, 89, 90, 100, 102, 103, 109, 228, 268, 269, 280, 281 bacterial infection, 109

333 bacteriophage, 103, 192 bacterium, 194 ballast, 232, 233, 234, 235, 239 barrier, 23, 32, 33, 36, 37, 39, 41, 42, 46, 56, 58, 61, 169 base pair, 29, 35, 36, 42, 47, 50, 51, 53, 54, 55, 57, 58, 59, 66, 71, 74, 84 Bcl-2, 297, 308, 319, 320, 321 behavior, 54, 57, 60, 85, 169, 179, 200, 205, 208, 221 Belgium, 13 benefits, 116 beta, 3, 118, 152, 183, 193, 201, 210, 211, 212, 218, 219, 221, 236, 245, 283, 310 bioactive, 13, 14, 15, 18, 19, 241 bioassay, 179 bioavailability, 121, 122, 123 biochemical, 6, 14, 15, 17, 19, 134, 151, 196, 214, 249, 250, 271, 315 biodegradation, 163, 179 bioenergetics, 294 biogeography, 264 bioinformatics, 15, 228 biologic, 115, 305 biological, 14, 19, 21, 78, 158, 163, 164, 168, 178, 186, 191, 198, 205, 232, 248, 249, 250, 251, 258, 261 biological processes, 19 biologically, 13, 15, 115, 185, 228 biology, 20, 70, 126, 190, 297, 305 biomarker, 166, 187 biomass, 251 biomolecular, 167, 171, 179, 190, 244 biomolecules, 172, 179, 187, 188, 196 biophysical, 164, 182, 191, 314 biophysics, 188 biopolymer, 185, 192 Biopolymers, 248 Biosensor, 164, 187, 192 biosensors, 163, 164, 165, 170, 171, 172, 173, 175, 178, 179, 182, 186, 187, 189, 192 biosynthesis, 8, 13, 19, 58, 67, 97, 133, 163, 164, 166, 168, 170, 175, 177, 186, 195, 196, 197, 198, 205, 206, 207, 225, 234, 243, 244, 263, 270, 294 biotic, 251 biotic factor, 251 birds, 260 birefringence, 73 birefringence measurement, 73

Index

334 birth, 76 black, 30, 35, 72 bladder, 308 blastocyst, 158 blocks, 135, 204, 243, 287, 311, 315 blood, 121, 267, 268 blood glucose, 268 bloodstream, 115 blot, 270, 274 blots, 18, 177 body size, 257 body temperature, 249, 250, 251, 257, 260 body weight, 110, 257, 259, 298, 307, 317, 321 bonding, 60 bonds, 37, 167, 227, 233 bone, 247 Bortezomib, 297 Bose, 98 bottlenecks, 189 bovine, 180, 244 brain, 11, 134, 153, 160, 195, 196, 197, 198, 201, 206, 207, 212, 213, 214, 215, 216, 218, 221, 222, 259, 316 brain development, 221 BRCA1, 287, 299 breakdown, 126, 178, 262 breast, 297, 300, 302, 308 breast cancer, 300, 302 buffer, 50, 167, 184 burn, 116, 121, 126 business, 191 butadiene, 298 bypass, 287

C C60, 35 Ca2+, 216 cadmium, 93, 310, 314, 324, 325 Caenorhabditis elegans, 2, 9, 10, 11, 13, 20, 21, 22, 30, 308, 319, 327 calcium, 196, 198, 219, 241, 247, 248, 295 calcium channels, 248 calmodulin, 198, 216, 219, 304 calorimetry, 168, 188 cAMP, 202, 204, 216, 218, 283, 290 campaigns, 166 Canberra, 155

cancer, 153, 187, 191, 226, 242, 287, 296, 297, 298, 299, 300, 302, 303, 304, 305, 306, 308, 319, 321, 322, 323, 327, 328 cancer cells, 153, 287, 302 cancer progression, 308 cancers, 297, 308, 319, 320, 321 candidates, 169 capacity, 8, 188, 201, 261, 268, 308 capillary, 164 carbohydrate, 111, 166, 185 carbohydrates, 271 carbon, 93, 94, 110, 183, 262 carboxyl, 244, 310 carcinogens, 155 carcinoma, 160, 272, 297 cardiac muscle, 130, 264 cardiovascular, 284 cardiovascular risk, 284 carrier, 70, 281 case study, 187 casein, 129 caspase, 243 casting, 126 catabolic, 110, 111, 120, 121, 122 catabolism, 109, 111, 120, 122, 123, 126, 257 catalase, 4 catalysis, 63, 186 catalyst, 185, 186 catalytic, 84, 114, 183, 185, 186, 218, 244, 272, 288, 293 catalytic activity, 272, 293 catalytic properties, 244 catfish, 151 cations, 166 causal relationship, 290 cavities, 174 CD26, 228, 243 cDNA, 20, 211, 243, 244, 245, 246, 247, 248, 268, 269, 273, 274, 280 cell adhesion, 169 cell body, 139, 145, 199, 200 cell culture, 214, 269 cell cycle, 78, 90, 93, 100, 134, 153, 155, 159, 287, 300, 314, 315 cell death, 227, 243, 297, 302, 324 cell differentiation, 270, 272, 302, 318 cell growth, 41, 92, 129, 268, 269, 295, 300, 304, 305, 308, 311, 316, 319, 324, 326, 328 cell line, 134, 152, 247, 272, 273, 274, 275, 280, 296, 310, 321, 323

Index cell lines, 134, 152, 296, 310, 321, 323 cell membranes, 257 cell metabolism, 286 cell organelles, 133, 134, 136, 137, 139, 140, 142, 150, 151, 152 cell signaling, 120, 163, 202, 206 cell surface, 226, 244, 273, 295 cellular homeostasis, 110 central nervous system, 196, 203 cervical, xiii, 297, 305, 308 cervical cancer, 308 cervical carcinoma, 305 chain termination, 24 channels, 198 chaperones, 6, 9, 175 charge density, 170 chemical, 31, 48, 61, 73, 85, 87, 139, 163, 164, 168, 169, 175, 185, 187, 195, 197, 219 chemical energy, 31 chemical interaction, 164 chemical sensing, 163 chemistry, 172, 175 chemokine, 241 chemoresistance, 299, 320 chemotherapeutic agent, 319 chemotherapy, 286, 297, 320 Chicago, 135 chicken, 151, 152, 158, 245 chickens, 134, 153, 155 children, 206, 207, 221 chimera, 79, 270 China, 158 Chinese, 158, 247, 267, 269, 273, 280 chloride, 324 chloroplast, 30, 52, 159 chloroplasts, 71, 78, 91 CHO cells, 273, 274, 275, 276, 277, 278 chondrocytes, 160 chromatin, 139, 140, 202 chromatographic technique, 15 chromatography, 167 chromosome, 102, 205, 298 chronic, 113, 115, 118, 119, 120, 121, 122, 124, 126, 129, 276, 290, 301, 306, 314 chronic hypoxia, 290, 301 chronic myelogenous, 314 chymotrypsin, 180 circular dichroism, 182, 185 circulation, 122 cis, 97, 197, 198, 199, 200, 206, 210

335 cisplatin, 305 cladding, 173 classes, 168, 181 classical, 4, 230, 237 cleavage, 14, 15, 88, 89, 90, 91, 97, 101, 103, 105, 179, 180, 182, 183, 185, 200, 206, 226, 228, 229, 230, 231, 232, 234, 235, 240, 241, 242, 244, 273, 316 cleavages, 56 clinical, 110, 116, 125, 129, 205, 207, 298, 300, 305, 319, 321 clinical symptoms, 205 clinical trial, 298, 321 clinical trials, 298, 321 clone, 268 clones, 273, 274 cloning, 211, 244, 245, 246, 247, 248, 269, 273, 280 closure, 58, 59 Clupea harengus, 253 c-myc, 300, 309, 310, 319, 320, 321, 323, 327 CNS, 9 Co, 63, 134, 135, 187, 204, 280 codes, 29 coding, 69, 70, 73, 78, 84, 86, 198, 199, 200, 206, 244, 245, 273 codon, 2, 23, 24, 25, 31, 33, 35, 36, 39, 40, 45, 46, 50, 51, 53, 54, 55, 57, 58, 59, 60, 64, 66, 69, 75, 78, 79, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 94, 98, 103, 104, 105, 288, 291, 307, 309, 312, 322 codons, 31, 41, 63, 88, 89, 96, 98, 101, 103, 292 cofactors, 112 cognition, 219 collaboration, 84, 94 collagen, 9, 142 colon, 272, 274, 296, 325 colon cancer, 296 colon carcinogenesis, 325 colorectal, 308 colorectal cancer, 308 commercial, 164, 174 common symptoms, 6 communication, 199 compensation, 249, 250, 251, 252, 257 competition, 55, 83, 90, 190, 206, 325 complementarity, 86 complementary, 25, 41, 200, 245, 314 complications, 110, 169, 276, 278, 284

336 components, 3, 4, 92, 118, 130, 168, 186, 198, 200, 204, 213, 214, 216, 235, 273, 313 composite, 235 composition, 111, 196, 197, 217 compounds, 123, 135, 137, 140, 155, 156, 159, 167, 168, 169, 172, 192, 268 computer, 35 concave, 310 concentration, 91, 115, 116, 118, 119, 121, 180, 181, 252, 260, 261, 268, 277, 296 conditioning, 199, 218 conduction, 279 confidence, 181 configuration, 170 conformational, 23, 25, 32, 36, 38, 39, 42, 46, 49, 53, 55, 58, 59, 61, 63, 66, 77, 83, 84, 87, 96, 182, 183, 184, 192, 193, 194, 203, 284, 322 conformational states, 23, 25, 66, 284 Congress, 124 conjugation, 192 connectivity, 46 consensus, 71 conservation, 7, 65, 73, 76, 86, 92, 97, 242, 309, 310 consolidation, 210 consumption, 249, 251, 252, 256, 258, 263 consumption rates, 252, 263 continuing, 122 control, 2, 3, 4, 9, 10, 11, 58, 70, 112, 113, 114, 117, 122, 123, 125, 128, 130, 167, 175, 177, 180, 183, 184, 197, 199, 200, 203, 205, 206, 210, 212, 216, 217, 218, 219, 226, 232, 252, 268, 275, 276, 277, 278, 284, 287, 288, 289, 293, 294, 295, 297, 299, 300, 301, 303, 308, 316, 317, 319, 321, 322, 326, 327, 328 controlled, 96, 99, 100, 111, 124, 197, 199, 259, 285, 287, 300, 302, 309, 316 conversion, 179, 180, 201, 243 convex, 310, 314 cooling, 135 coordination, 86 copper, 135, 185, 186, 243, 248 coronary heart disease, 276 correlation, 115, 168, 179 cortex, 204, 206, 222 cortical, 201, 203, 204, 208, 219, 221, 275 cortical neurons, 201, 203, 221 cortical systems, 208 corticotropin, 229 cost of living, 264

Index costs, 110, 123, 260, 261 couples, 203, 295 coupling, 170, 174, 190, 322 covalent, 167, 168, 178 covalent bond, 167 covalent bonding, 167 crab, 245, 262 Crete, 1 critically ill, 110, 116, 120, 122, 124, 125, 129 crosslinking, 38, 41, 42, 43, 46, 51, 61, 65, 66, 71, 86, 106, 312 crustaceans, 260, 265 crystal, 23, 25, 31, 39, 42, 45, 47, 51, 58, 63, 64, 66, 73, 81, 84, 106, 164, 173, 193, 323 crystal structure, 23, 25, 31, 39, 42, 45, 47, 51, 58, 63, 64, 66, 73, 81, 84, 106, 193 crystal structures, 84 crystallization, 269 crystallographic, 38, 84 crystallographic studies, 84 C-terminal, 69, 71, 75, 78, 81, 82, 83, 87, 90, 92, 93, 94, 105, 228, 229, 232, 234, 235, 239, 240, 242, 270, 296, 305 C-terminus, 69, 75, 232, 239, 311 cues, 1, 319 culture, 89, 92, 93, 115, 122, 151, 152, 155, 209, 269, 275, 284 culture conditions, 89, 92, 93 cyanobacteria, 73, 74, 97 cyclic AMP, 283 cyclin D1, 308, 309, 314, 319, 320, 321, 322, 325 cycling, 244 cycloheximide, 313 cysteine, 118, 181, 227, 239, 242, 296 cytochemistry, 134, 149, 154 cytochrome, 4, 8, 10, 75, 186, 193 cytokine, 6, 115, 121, 199 cytokine response, 115 cytokines, 115, 226, 286, 297, 315 cytoplasm, 92, 134, 136, 137, 138, 139, 140, 141, 142, 145, 147, 153, 154, 178, 199, 288, 292, 309, 312, 313, 315 cytoplasmic membrane, 280 cytosine, 71 cytoskeleton, 196, 198, 202 cytosolic, 178 cytotoxic, 286, 296, 297 cytotoxicity, 169, 324 cytotoxins, 238 Czech Republic, 285, 299, 307, 321

Index

D data analysis, 225 database, 67, 107, 167 de novo, 166, 196, 197, 198, 202, 203, 205, 206 death, 110, 302, 324 deaths, 110, 127 Decade of the Brain, 195 decay, 88, 91, 101, 201, 206, 211, 304, 312, 324 decoding, 24, 46, 48, 50, 51, 54, 57, 58, 59, 70, 75, 79, 82, 83, 84, 85, 86, 87, 89, 90, 94, 101, 175 decompression, 127 deconvolution, 170 defecation, 19 defects, 9, 111, 160, 320 deficiency, 3, 4, 8, 92, 93, 319 deficits, 214, 220 degradation, 2, 6, 8, 9, 10, 11, 69, 70, 78, 80, 88, 89, 90, 91, 92, 93, 94, 96, 97, 99, 100, 106, 107, 111, 118, 121, 122, 123, 163, 164, 166, 178, 179, 183, 186, 191, 192, 198, 199, 200, 202, 210, 211, 226, 250, 254, 257, 258, 259, 261, 286, 296, 303, 310, 318, 324 degradation mechanism, 2 degradation pathway, 254 degradation rate, 2, 250, 258, 259 degrading, 93, 260 degree, 37, 48, 49, 180, 182, 183, 200, 250, 272, 310 dehydrogenase, 10, 118, 119, 309 delivery, 122 delta, 301 demand, 259 dementia, 205, 221, 222 dendrite, 199, 210 dendrites, 196, 197, 198, 199, 200, 201, 203, 204, 205, 207, 209, 210, 212, 218 dendritic spines, 196, 197, 198, 200, 201, 205, 209, 220 density, 165, 169, 170, 196, 201, 203, 205, 208, 212, 221, 268, 283, 289, 304 dentate gyrus, 209, 216, 217 deoxyribonucleic acid, 159, 245 deoxyribose, 159 dephosphorylating, 288 dephosphorylation, 4, 131, 204, 206, 290, 295, 315, 316, 318 depressed, 114, 121

337 depression, 197, 208, 214, 216, 217, 218, 220, 221, 259, 263 deprivation, 286, 315, 316 deregulation, 328 derivatives, 66, 116, 279, 298 desorption, 14, 15, 16, 166 destruction, 6, 321 detection, 17, 89, 94, 163, 164, 166, 167, 168, 169, 170, 172, 173, 178, 179, 182, 186, 187, 189, 190, 191 detoxification, 8 developing brain, 206 dexamethasone, 129 diabetes, 121, 267, 268, 276, 277, 278, 279, 284 diabetic, 126, 129, 276, 279 diabetic neuropathy, 279 diamond, 52, 63, 283 dichotomy, 114 dielectric, 169, 170, 174 dielectric materials, 170 diet, 134, 135, 263, 327 dietary, 262, 263, 319 differential scanning, 164 differential scanning calorimetry, 164 differentiation, 101, 169, 189, 213, 221, 237, 242, 267, 270, 272, 310, 314, 318, 325 digestion, 175, 178, 179, 180, 181, 182, 183, 184, 185, 186, 191, 206, 227 dimeric, 129, 185 dipeptides, 239 diphtheria, 228 direct measure, 260 direct observation, 153 discovery, 245 discrimination, 24, 63, 95 diseases, 195 disorder, 205, 314 displacement, 311, 324 dissatisfaction, 38 dissociation, 83, 84, 88, 91, 99, 120, 166, 183, 187, 204, 289, 293, 317 distal, 268 distilled water, 186 distribution, 196, 230, 237, 238, 272, 280 disulfide, 167, 191, 231, 234, 248, 271 diurnal, 250 diversity, 164, 168, 183, 244 DNA damage, 286, 288, 289, 291, 294 DNA repair, 153, 160 dominance, 204, 219

Index

338 donor, 58 dosage, 134, 135 double-blind trial, 124 Down syndrome, 195, 197 down-regulation, 3, 8, 299 DPP IV, 228 drinking, 118 drinking water, 118 Drosophila, 4, 9, 11, 31, 191, 201, 246 drug discovery, 163, 164, 169, 178, 187, 188, 189, 192, 267 drug interaction, 175 drug resistance, 319 drugs, 95, 179, 188, 268, 276, 279, 297 dry, 135, 137, 155, 159 duration, 110 dust, 174, 190 dyes, 164 dynamin, 282 dysregulated, 314

E E. coli, 17, 24, 28, 29, 30, 35, 41, 51, 62, 64, 70, 71, 72, 73, 74, 75, 77, 78, 79, 80, 81, 86, 87, 88, 90, 91, 92, 93, 97, 99, 102, 115, 188, 193, 252, 270, 273, 281 E2F, 287 ears, 61, 205 earth, 251 ecology, 263 economies, 110, 123 economy, 122 efficacy, 116, 126, 297 egg, 19 EI, 246 elbows, 58 elderly, 207, 222 electric current, 173 electric field, 16 electrical, 164, 169, 196 electrochemical, 173, 190 electrodes, 169 electromagnetic, 170 electromagnetic wave, 170 electromagnetic waves, 170 electron, 8, 25, 38, 64, 65, 73, 78, 80, 81, 84, 85, 103, 106, 133, 134, 135, 136, 138, 139, 141, 142, 150, 151, 152, 153, 155, 156, 157, 158,

159, 160, 161, 164, 166, 170, 187, 196, 291, 292 electron charge, 170 electron density, 38 electron microscopy, 25, 73, 106, 135, 152, 153, 155, 156, 158, 196 electronic, 189 electrons, 166, 170 electrophoresis, 164, 168, 182, 185 electrophysiological, 197, 220, 269 electrophysiological properties, 269 electrostatic, 16 elephant, 61 elongation, 2, 4, 5, 7, 10, 11, 24, 30, 32, 47, 53, 58, 60, 62, 63, 64, 65, 66, 67, 90, 95, 96, 97, 98, 103, 104, 105, 107, 112, 113, 121, 122, 175, 193, 194, 197, 205, 209, 216, 217, 219, 264, 286, 288, 294, 295, 300, 302, 304, 305, 307 email, 1 embryo, 139, 142, 158, 328 embryogenesis, 241, 244, 285, 323 embryonic, 134, 138, 139, 142, 143, 144, 145, 150, 241, 292, 308, 310, 311 embryonic development, 241 embryos, 145, 149, 260, 263 emulsions, 152 encoding, 3, 4, 13, 20, 21, 75, 77, 82, 86, 87, 88, 94, 101, 218, 242, 243, 244, 246, 294, 300, 308, 314, 319 endocrine, 21 endocytosis, 228, 272 endogenous, 13, 15, 17, 18, 21, 103, 170, 178, 273, 296 endometrium, 158 endonuclease, 91 endoplasmic reticulum, 133, 134, 136, 137, 138, 139, 140, 141, 142, 151, 194, 198, 209, 226, 271, 285, 286, 287, 288, 289, 301, 302 endorphins, 232 endothelial cell, 136, 137, 138, 139, 146, 153, 299, 321 endothelial cells, 139, 153, 321 endothermic, 257, 261 endotherms, 257, 260 endotoxemia, 119, 120, 121, 128 energy, 1, 6, 7, 8, 31, 58, 65, 122, 128, 152, 164, 166, 175, 187, 261, 263, 281, 290, 291, 295, 300, 304, 305, 308, 317 energy transfer, 58, 175

Index England, 134, 135, 194 enhancement, 300 enkephalins, 232 enlargement, 197 entropy, 188 envelope, 280 environment, 55, 66, 170, 251 environmental, 93, 106, 250, 261, 288, 296, 314 environmental change, 106 environmental conditions, 314 enzymatic, 13, 14, 15, 73, 163, 166, 172, 173, 178, 179 enzymatic activity, 14, 15 enzyme, 76, 100, 104, 119, 164, 166, 168, 169, 178, 179, 181, 182, 188, 192, 213, 226, 228, 231, 232, 234, 241, 242, 243, 293 enzyme inhibitors, 179, 182 enzymes, 6, 10, 13, 15, 16, 19, 63, 118, 164, 168, 179, 180, 181, 184, 201, 225, 226, 227, 228, 230, 231, 235, 237, 238, 241, 243, 245, 259, 272 ependymal, 153 ependymal cell, 153 epidermal, 247, 297 epidermal growth factor, 297 epidermal growth factor receptor, 297 epigenetic, 202, 208 epilepsy, 207, 222 episodic, 231 epithelia, 283 epithelial cell, 139, 153, 267, 268, 270, 278, 283, 328 epithelium, 284 epitope, 281 epoxy, 135 equilibrium, 281 Erk, 304 erosion, 110 Escherichia coli, 30, 62, 63, 64, 66, 67, 70, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 193, 246, 261, 270, 279, 280, 281 ester, 127, 298 esters, 127 estrogen, 192 ethanol, 93, 186 ethyl acetate, 17 euchromatin, 138, 139, 140, 141, 147 eukaryotes, 1, 73, 90, 91, 92, 175, 279, 307, 312, 314, 322, 325

339 eukaryotic, 3, 4, 5, 10, 11, 25, 30, 51, 66, 67, 70, 71, 91, 97, 106, 112, 113, 114, 121, 125, 126, 127, 128, 129, 130, 131, 190, 193, 194, 209, 212, 213, 241, 267, 268, 269, 272, 273, 278, 280, 285, 288, 294, 295, 298, 301, 304, 307, 319, 322, 323, 324, 325, 326, 327 eukaryotic cell, 269, 272, 273, 307 Europe, 259, 263 European, 8 European Union, 8 evidence, 17, 21, 48, 65, 75, 79, 96, 122, 151, 159, 183, 221, 258, 292, 296, 298, 313, 321 evolution, 24, 52, 65, 76, 92, 93, 234, 248, 319 evolutionary, 52, 60, 92, 234, 239, 246 excitatory synapses, 196, 203, 215 exclusion, 167 excretion, 119, 123, 262, 263, 268 exonuclease, 191 experimental condition, 122, 152, 156, 159 exponential, 209, 257 exposure, 168, 182, 256, 261, 287, 292, 293, 297, 310, 324 extracellular, 115, 142, 170, 196, 206, 295, 311, 314, 315 extraction, 17, 183 extrinsic, 1, 182 eyes, 134, 153

F facial nerve, 160 failure, 55, 109, 110, 119, 125, 127, 130, 169, 183 familial, 207 family, 14, 20, 21, 116, 168, 179, 196, 199, 203, 226, 234, 236, 241, 242, 245, 247, 248, 267, 268, 279, 286, 290, 293, 299, 308, 315, 323 family members, 199, 323 fasting, 111, 257 fat, 4, 19, 110, 139, 243, 307, 316, 317 fats, 111 fax, 1, 225 F-box, 293 fear, 199, 204, 218 fee, 192 feeding, 111, 117, 120, 127, 129, 130, 139, 257, 258, 259 feet, 42, 61 females, 205 Fermi, 183, 193

340 ferritin, 206 fertility, 4 fetal, 133, 135 fever, 128 FGF2, 319, 320 FGF-2, 309 fiber, 111 fibers, 112, 142 fibrillar, 139 fibrinogen, 236, 245 fibroblast, 308, 309 fibroblasts, 11, 139, 151, 152, 159, 211, 292, 308, 311, 314, 318, 328 fidelity, 2, 9, 63, 65, 72 film, 172, 173 fish, 235, 237, 246, 257, 259, 262, 263, 264 fixation, 139, 159 flexibility, 48 flight, 14, 15, 16, 17 flooding, 250, 263 flow, 17, 110, 169, 190 fluctuations, 250, 251 fluid, 135, 173, 187 fluorescence, 25, 55, 58, 65, 169, 173, 175, 182 fluorescent markers, 169 fluorophores, 58 focused ion beam, 174 focusing, 315 foils, 135 folding, 20, 64, 73, 107, 175, 232, 254, 269, 271 food, 117, 249, 251, 252, 256, 257, 258, 259, 261, 265 Food and Drug Administration, 286 food intake, 256, 261 Fox, 127, 246, 284, 326 fragile X syndrome, 214, 215, 217, 219, 220, 221 fragmentation, 166, 226, 228, 231, 234, 237, 239 free radicals, 11 freedom, 37 freeze-dried, 135, 137 freezing, 135, 250 freshwater, 259, 264 frog, 131 functional analysis, 20 functional aspects, 65 functional changes, 270 fungi, 52, 227

Index

G G protein, 13, 270, 282 Gadus morhua, 253, 255, 256, 257, 258, 261 Gamma, 216, 218, 325 gastric, 247 gastrin, 232 gastrocnemius, 113, 115, 120, 122 gastrointestinal, 156 gel, 168, 177, 182, 185 gene, 3, 14, 17, 20, 21, 62, 70, 71, 74, 75, 78, 91, 93, 95, 96, 99, 102, 106, 166, 169, 178, 195, 197, 198, 219, 222, 225, 229, 241, 242, 246, 247, 248, 267, 272, 273, 274, 280, 282, 284, 285, 287, 288, 293, 294, 295, 298, 299, 301, 308, 310, 311, 314, 322, 323, 327 gene expression, 3, 70, 91, 93, 95, 106, 166, 169, 219, 222, 241, 247, 274, 285, 287, 293, 299, 301, 308, 314, 322, 323 gene silencing, 178 gene therapy, 195 generation, 15, 110, 163, 167, 188, 273 genes, 3, 4, 6, 9, 13, 14, 15, 17, 66, 67, 93, 94, 95, 101, 107, 202, 206, 208, 226, 229, 269, 273, 281, 283, 286, 287, 288, 291, 292, 296, 297, 309, 317, 319 genetic, 19, 65, 70, 78, 86, 99, 159, 213, 250, 272, 287, 318 genetic code, 65, 99 genetic control, 287 genetic disorders, 272 genetic information, 70 genome, 3, 74, 75, 78, 95, 99, 202, 239, 246 genomes, 100, 178 genomic, 14, 15, 244 genotype, 250 geriatric, 222 germ line, 7, 213 Germany, 188, 267 Gibbs, 159 gifts, 19 gill, 264 gland, 134, 153, 231, 245, 247 glial, 153, 247 glial cells, 153 glioma, 297 global warming, 259, 261, 263, 264 glomerulus, 268 glucagon, 111 gluconeogenesis, 111

Index glucose, 111, 120, 129, 267, 268, 269, 270, 271, 272, 275, 276, 278, 279, 280, 281, 282, 283, 284, 290, 301 glucose metabolism, 284 glutamate, 196, 203, 204, 208, 216, 220 glutamic acid, 30, 118, 232 glutamine, 126 glutaraldehyde, 135, 136, 137 glutathione, 4, 296 glycine, 13, 15, 118, 133, 134, 137, 139, 154, 198 glycoconjugates, 156 glycogen, 5, 114, 124, 131 glycogen synthase kinase, 114, 131 glycolysis, 286 glycoprotein, 235 glycoproteins, 140 glycoside, 268 glycosylated, 247 glycosylation, 198, 226, 271, 273 glyoxylate cycle, 4 gold, 152, 153, 174, 178 gold nanoparticles, 178 Golgi complex, 271 gonad, 264 gonads, 201 G-protein, 198, 203, 315 gracilis, 30 grain, 136, 138, 139, 142, 145, 147, 150, 151, 153, 160 grains, 133, 136, 137, 138, 139, 140, 141, 142, 144, 146, 147, 150, 151, 152, 153, 154 Gram-positive, 78 grants, 8, 19 granule cells, 209 granules, 200, 201, 209, 210, 212, 213, 214, 215 granzyme, 236, 246 gratings, 170 Greece, 1 Grip strength, 131 groups, 25, 48, 70, 71, 133, 134, 135, 136, 139, 143, 144, 145, 148, 149, 166, 193, 229, 237, 271 growth, 1, 3, 4, 5, 6, 9, 17, 78, 90, 92, 93, 95, 102, 104, 106, 109, 111, 115, 120, 121, 124, 125, 126, 127, 128, 129, 196, 197, 203, 211, 212, 226, 247, 249, 250, 251, 254, 255, 256, 259, 261, 262, 263, 264, 265, 267, 268, 286, 288, 289, 290, 291, 292, 295, 296, 297, 298,

341 303, 309, 310, 314, 315, 317, 319, 320, 323, 327 growth factor, 3, 4, 5, 115, 124, 125, 126, 127, 129, 226, 286, 292, 295, 297, 298, 303, 309, 310, 315, 317 growth factors, 3, 4, 115, 226, 295, 310, 315, 317 growth hormone, 9, 109, 111, 120, 121, 125, 127, 128, 129 growth inhibition, 298 growth rate, 92, 251, 261 GSK-3, 114 guanine, 25, 39, 60, 67, 114, 125, 128, 129, 206, 288, 289 guidance, 207 guidelines, 135 gyrus, 206

H H2, 135, 222 Haj, 264, 265 half-life, 6, 286, 293 handling, 225 head, 32, 59, 78, 297, 308 health, 110, 221 heart, 118, 126, 191, 259 heat, 4, 11, 93, 101, 168, 186, 262, 310, 315 heat loss, 168 helical conformation, 35, 314 helix, 23, 24, 25, 29, 31, 32, 33, 35, 36, 37, 39, 41, 46, 48, 49, 50, 51, 53, 55, 57, 58, 59, 60, 61, 83, 86 hemagglutinin, 228, 244 hematopoietic, 139, 325 hematopoietic cells, 139 heme, 127, 183, 184, 193, 288, 289, 292, 297 heme oxygenase, 292 hemoglobin, 183, 193 hemolymph, 238, 248 hepatocyte, 133, 134, 136, 137, 138, 140, 141, 146, 147, 149, 157, 160, 161, 270 hepatocyte nuclear factor, 270 hepatocytes, 133, 134, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 153, 154, 157, 160, 262, 264 herbicide, 8 herpes, 288 herpes simplex, 288 heterochromatin, 139 heterogeneous, 201, 214, 310

342 hexane, 17 high temperature, 92, 104 high-frequency, 197, 204, 216 high-throughput screening, 189, 268, 276, 278, 321 hippocampal, 200, 203, 204, 208, 209, 210, 212, 213, 216, 217, 219, 220, 222 hippocampus, 197, 198, 202, 203, 204, 205, 206, 209, 216, 217, 218, 219, 221, 327 histidine, 76, 97, 102, 118, 175, 296 histone, 293 HIV, 188, 192, 293 HIV-1, 188, 192, 293 homeostasis, 2, 9, 110, 122, 242, 291 homogenized, 17 homolog, 11, 212, 213, 221, 287, 298 homology, 20, 201, 245, 248, 297, 315 Honda, 194 hormone, 19, 109, 120, 121, 236, 243, 245, 247, 315 hormones, 3, 13, 111, 118, 226, 229, 232, 235, 237, 238, 315 hospital, 110 hospitalization, 110 host, 110, 111, 122 hot spots, 197 human, 11, 21, 66, 120, 122, 124, 125, 126, 151, 152, 160, 168, 169, 172, 180, 183, 188, 191, 192, 193, 195, 217, 228, 241, 243, 244, 267, 270, 271, 272, 273, 274, 275, 276, 277, 278, 280, 281, 282, 284, 286, 297, 300, 302, 305, 308, 309, 310, 321, 323, 324, 328 humans, 1, 2, 121, 122, 127, 128, 195, 205, 207, 229, 257, 262, 319 hunting, 248 hybrid, 32, 36, 37, 39, 48, 58, 84, 85, 92, 94, 166, 222, 245, 293 hybridization, 187 hydrodynamic, 183 hydrofluoric acid, 173 hydrogen, 36, 37, 55, 60, 164, 167 hydrogen atoms, 167 hydrogen bonds, 36, 37, 55 hydrolysis, 6, 23, 24, 25, 33, 35, 39, 46, 48, 52, 53, 54, 56, 57, 58, 60, 66, 80, 84, 91, 104, 227 hydrolyzed, 52, 59, 90 hydrophobic, 227, 310, 314 hydroquinone, 152 hydroxyl, 37, 39, 47, 63, 67, 81, 82, 83, 84, 90, 94, 100, 101

Index hydroxyl groups, 37 hydroxylation, 286, 293, 296 hydroxyproline, 133, 134, 139, 140, 142 hyperglycemia, 268, 276, 277, 278, 279, 284 hyperphosphorylation, 120, 315 hyperreactivity, 223 hypersensitive, 298 hypothalamus, 247 hypothesis, 8, 81, 116, 198, 201, 296 hypoxia, 285, 286, 287, 289, 290, 291, 292, 293, 294, 295, 296, 297, 299, 300, 301, 302, 303, 304, 305 hypoxia-inducible factor, xii, 285, 292, 296, 299, 303, 304, 305 hypoxic, 286, 287, 290, 292, 293, 295, 296, 297, 299, 302, 303 hypoxic cells, 292 hypoxic stress, 297, 302

I ice, 17, 235, 259, 263 identification, 17, 95, 99, 166, 170, 173, 201, 213, 214, 225, 226, 229, 239, 244, 321 identity, 99, 101, 102, 172, 315 IGF-1, 3, 5, 10, 111, 116, 120, 121, 122, 123, 126 IGF-I, ix, 11, 109, 111, 118, 120, 121, 122, 123, 125, 126, 127, 128, 129, 130 IL-1, 115, 119, 122, 124, 127, 206, 236 IL-6, 75, 115 image analysis, 157, 177 images, 177 imaging, 163, 169, 172, 177, 178, 190, 191, 195, 209 immobilization, 168, 175 immortality, 7 immune function, 125 immunity, 226 immunocytochemistry, 18 immunodeficient, 297 immunofluorescence, 297 immunogenicity, 129 immunoglobulin, 286, 288 immunohistochemistry, 270 immunological, 310 immunosuppressive, 315 impairments, 199 implementation, 166 in situ, 20, 151, 159, 178, 209

Index in situ hybridization, 209 in vitro, 9, 63, 72, 73, 74, 75, 76, 77, 79, 80, 81, 83, 85, 86, 89, 90, 91, 99, 101, 102, 103, 121, 129, 134, 140, 153, 155, 160, 191, 193, 206, 216, 217, 226, 228, 241, 243, 268, 272, 290, 297, 311, 312, 315, 319, 321 in vivo, 11, 74, 75, 77, 80, 81, 90, 103, 115, 122, 127, 129, 130, 134, 153, 159, 160, 182, 186, 211, 216, 228, 239, 241, 243, 261, 268, 282, 290, 293, 294, 297, 311, 312, 315, 316, 321 inactivation, 203, 219, 228, 243, 285, 304 inactive, 14, 15, 116, 117, 119, 120, 121, 228, 289, 293 incidence, 123, 207, 319 inclusion, 177 inclusion bodies, 177 incubation, 121, 140, 167, 310 incubation period, 167 indices, 133, 142, 144, 149, 150, 151, 152, 153, 154 inducible protein, 286, 288, 289, 291 induction, 93, 96, 98, 101, 203, 205, 207, 216, 217, 218, 219, 220, 291, 292, 293, 297, 302, 305, 306, 323, 328 infection, 110, 112, 116, 311 infections, 308 inflammation, 115, 129 inflammatory, 112, 114, 115, 119 inflammatory mediators, 115 infusions, 126 inherited, 205 inhibition, 6, 11, 20, 91, 111, 114, 115, 118, 119, 120, 122, 123, 124, 129, 166, 178, 181, 182, 191, 200, 203, 204, 267, 268, 271, 272, 276, 277, 278, 285, 287, 290, 294, 295, 296, 297, 298, 305, 311, 316, 317, 321, 324, 329 inhibitor, 8, 113, 118, 127, 169, 178, 179, 181, 188, 243, 260, 270, 272, 276, 279, 287, 288, 289, 293, 297, 298, 305, 310, 315, 316, 318, 320, 326, 327 inhibitor protein, 327 inhibitors, 175, 178, 181, 186, 187, 190, 192, 205, 228, 243, 244, 260, 267, 268, 276, 278, 279, 284, 286, 296, 297, 305, 306, 307, 310, 315, 321, 328 inhibitory, 6, 112, 203, 217, 222, 232, 268, 270, 276, 288, 291, 294, 296, 317 inhibitory effect, 112, 270, 276, 288, 296, 317 initiation rates, 287 injection, 17, 121, 158, 262, 263, 311

343 injections, 135, 139, 169 injury, iv, 110, 111, 112, 126 inorganic, 185 inositol, 198 insects, 235, 237, 238 insertion, 183, 184, 198, 270, 273 insight, 296 inspection, 24, 239 Inspection, 32 instability, 39, 206, 272 instruments, 172 insulin, 3, 4, 5, 9, 11, 15, 21, 109, 111, 117, 118, 120, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 232, 233, 236, 243, 246, 276, 279, 294, 309, 311, 315, 319, 326, 327 insulin resistance, 120, 276, 327 insulin-like growth factor, 118, 125, 127, 128, 129, 131, 236, 246, 309 insulin-like growth factor I, 118, 125, 236, 246 insults, 112 integration, 122, 164, 170, 171, 172, 273, 284, 301 integrin, 122 integrins, 209 integrity, 233, 287, 327 intensity, 18, 170 intensive care unit, 110, 127 interaction, 6, 25, 32, 39, 41, 47, 51, 54, 56, 59, 60, 69, 71, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 90, 99, 100, 104, 105, 121, 164, 165, 167, 175, 184, 186, 189, 192, 193, 194, 203, 213, 222, 228, 269, 286, 287, 289, 293, 301, 303, 307, 309, 310, 312, 314, 321, 329 interactions, 24, 29, 37, 51, 61, 63, 64, 65, 85, 94, 96, 102, 105, 165, 168, 171, 172, 173, 175, 179, 182, 188, 190, 191, 192, 193, 196, 198, 199, 202, 203, 206, 207, 214, 217, 296 interdependence, 189 interface, 41, 59, 170, 214 interference, 164, 213, 297 interferon, 314, 325 interleukin, 75, 111, 123, 128, 130, 131, 222, 236, 246 interleukin-1, 111, 123, 130, 131, 222, 246 Interleukin-1, 124 interleukin-6, 75, 128 intermolecular, 94, 186 intermolecular interactions, 94, 186 internal ribosome entry site, 199, 286, 292, 300, 303, 322

Index

344 internal ribosome entry site (IRES), 286, 292 internalization, 205 interpretation, 160 interval, 83 intestine, 268 intraperitoneal, 263 intravenous, 121, 125, 321 intrinsic, 1, 182 invertebrates, 250, 258 iodine, 38 ion channels, 202, 203 ionic, 168 ionization, 14, 15, 16, 166 ionizing radiation, 297 ionotropic glutamate receptor, 220 ions, 16, 166, 167, 203 iron, 160, 183, 206 ischemia, 285 ischemic, 286 isoforms, 3, 10, 168, 212, 221, 245, 246, 247, 268, 272, 280, 281 isolation, 245, 251, 326 isoleucine, 111, 116, 118 isomerization, 248 isopentane, 135 isopods, 257 isothermal, 188 isothermal titration calorimetry, 188 isozyme, 226, 242

J January, 234 Japan, 23, 69, 95, 133, 134, 135, 154, 156, 158 Jefferson, 10, 123, 124, 126, 127, 128, 129, 130, 131, 305, 326 jejunum, 282 Jordan, 325 Jun, 4, 193 Jung, 212, 217, 219, 281

K K+, 268, 279 kidney, 118, 134, 151, 152, 155, 157, 257, 262, 268, 269, 272, 273, 283, 310 kidneys, 134 kinase, 3, 4, 5, 11, 114, 115, 117, 118, 119, 121, 124, 125, 126, 127, 129, 131, 168, 172, 196,

198, 202, 203, 204, 208, 216, 217, 218, 219, 272, 283, 285, 286, 287, 288, 289, 290, 293, 294, 295, 297, 298, 300, 301, 302, 304, 305, 306, 308, 311, 313, 315, 317, 319, 324, 325, 326 Kinase, 293, 305 kinase activity, 114, 127, 290, 298, 315 kinases, 4, 5, 203, 204, 272, 288, 289, 295, 311, 312, 316, 324 kinetic studies, 178, 179 kinetics, 122, 169, 188, 192, 269, 270, 276, 282 KL, 190, 221, 245, 303, 304, 322, 323, 325 knockout, 204, 220, 221, 228, 295, 307, 317 knots, 47

L L1, 58, 127 label-free, 163, 164, 165, 166, 168, 169, 170, 172, 173, 175, 176, 177, 178, 181, 184, 185, 186, 187, 189, 190 labeling, 133, 139, 142, 144, 145, 149, 150, 151, 152, 153, 154, 166, 178 labor, 276 lakes, 259 Langmuir, 190, 192 large-scale, 166 laser, 14, 15, 16, 155, 166 lead, 6, 7, 62, 81, 110, 112, 122, 167, 188, 226, 290 lean body mass, 112 learning, 195, 196, 201, 204, 207, 219, 222 left ventricle, 135 lethal factor, 166, 187 leucine, 109, 111, 116, 117, 118, 119, 123, 124, 127, 128, 129, 133, 134, 135, 136, 137, 138, 139, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 158, 290, 326 leukaemia, 306 leukemia, 189, 309, 314, 325 Leydig cells, 158 life cycle, 257 life span, 4 lifespan, 1, 2, 3, 4, 6, 7, 8, 10, 11, 308, 319 lifetime, 197, 207 ligand, 3, 167, 168, 172, 176, 179, 182, 183, 184, 186, 192, 309, 310 ligands, 167, 175, 182, 184 limitation, 94, 122, 259 linear, 17, 115, 121, 166, 232, 234, 248

Index linkage, 167 links, 77 lipid, 111, 191, 193, 298 lipids, 134, 271 lipofuscin, 11 lipolysis, 08, 317 liposomes, 267, 278, 281 liquid chromatography, 13, 16, 17, 18, 20 liquid nitrogen, 135 literature, 254 liver, 11, 118, 121, 126, 133, 134, 135, 139, 149, 151, 152, 154, 155, 156, 242, 257, 259, 262, 264, 305, 311, 321 localization, 20, 133, 134, 136, 137, 150, 151, 152, 159, 197, 198, 199, 200, 201, 207, 209, 210, 211, 214, 217, 226, 231, 242, 244, 270, 271, 273, 281, 301, 312 location, 25, 32, 33, 35, 38, 40, 41, 42, 43, 46, 47, 48, 52, 54, 56, 57, 81, 85, 97, 166, 196, 199, 234, 273 locomotion, 19 locus, 20 London, 67, 127, 159, 262, 263, 264, 325 long period, 297 longevity, 1, 2, 3, 8, 9, 10, 11, 319 long-term, 196, 198, 199, 201, 202, 204, 208, 209, 212, 213, 214, 216, 217, 218, 219, 220, 221, 251, 317 long-term potentiation, 197, 208, 212, 213, 216, 218, 219, 221 losses, 109, 110 low molecular weight, 168, 171, 193 low temperatures, 251, 252, 261 L-shaped, 74, 314 lumen, 19 luminal, 242 lung, 297, 308, 319, 323 lupus, 253, 255, 256, 263 lymphoma, 319 lymphomagenesis, 319, 327 lymphomas, 308, 319 lysine, 20, 30, 180, 241 lysosomal enzymes, 6 lysosomes, 140, 142

M M1, 203

345 machinery, 4, 10, 62, 92, 103, 115, 197, 198, 200, 202, 203, 206, 209, 211, 213, 216, 218, 219, 239, 300, 314 macrolide antibiotics, 175 macromolecules, 137 macrophages, 92, 96 Madison, 195 maintenance, 1, 7, 8, 120, 163, 178, 183, 197, 204, 207, 208, 218, 282, 319, 328 malabsorption, 272, 282 males, 205, 220 malignancy, 242, 308, 319, 321, 327, 328 malignant, 247, 295, 298, 305, 314, 320, 328 maltose, 183 mammal, 9 mammalian, 242, 293 mammalian cell, 152, 153, 155, 156, 219, 268, 270, 271, 273, 284, 296, 304, 308, 312, 314, 324 mammalian cells, 152, 153, 155, 156, 219, 270, 271, 284, 296, 304, 308, 312, 314, 324 mammals, 4, 14, 197, 226, 235, 237, 238, 251, 260 management, 222 mandibular, 236, 245 manipulation, 322 mapping, 167, 206 marine environment, 261 market, 172 mask, 88 masking, 213 mass loss, 179 mass spectrometry, 13, 14, 15, 18, 20, 21, 22, 164, 166, 167, 168, 172, 182, 186, 187, 188, 190, 192, 315 mastery, 220 maternal, 200, 211, 212 mathematical, 284 matrix, 14, 15, 16, 133, 136, 137, 138, 139, 140, 142, 187, 191, 193, 194, 308 matrix metalloproteinase, 191 matrix protein, 194 maturation, 20, 74, 78, 80, 96, 101, 201, 205, 206, 211, 215, 225, 226, 228, 229, 232, 233, 235, 237, 238, 239, 240, 244 maturation process, 226, 229 Mcl-1, 319 meanings, 85 measurement, 169 measures, 168

346 mechanical, 110 media, 17, 273 mediation, 272 mediators, 111, 312 melting, 32, 36, 37, 41, 42, 58 melts, 24 membranes, 146, 151, 198, 278 memory, 195, 196, 198, 199, 201, 202, 204, 207, 208, 209, 210, 215, 218, 219, 220, 241, 327 memory deficiencies, 204 memory formation, 195, 204, 215, 220 men, 117 mental retardation, 205, 212, 213, 214, 215, 217, 219, 220, 221, 222 messages, 96, 199 messenger ribonucleic acid, 246 messenger RNA, 63, 70, 96, 97, 98, 100, 101, 102, 104, 105, 106, 107, 112, 210, 214, 215, 300, 319 meta-analysis, 260 metabolic, 6, 110, 115, 116, 118, 122, 124, 125, 128, 130, 163, 166, 196, 251, 259, 263, 264, 265, 279, 314 metabolic changes, 110 metabolic pathways, 123, 163 metabolic rate, 251, 259, 264 metabolism, 4, 109, 110, 115, 118, 119, 121, 122, 124, 125, 127, 226, 249, 250, 251, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 283, 284, 290, 302, 312, 316 metabolomics, 166 metabotropic glutamate receptor, 201, 208, 212, 215, 217, 220, 222 metabotropic glutamate receptor (mGluR), 201 metabotropic glutamate receptors, 217, 220, 222 metal oxide, 164 metalloproteinase, 181 metals, 170 metaphase, 200 metastases, 303, 327 metastasis, 178, 295, 298, 308, 320, 327 metastatic, 286, 327 metazoa, 242 metazoan, 13, 250 metazoans, 251 methanol, 17, 186 methionine, 79, 87, 288, 307 methyl group, 288 methylation, 202

Index mGluR, 197, 201, 203, 204, 205, 207, 217, 220, 221 mGluRs, 196, 203 mice, 4, 9, 10, 11, 14, 123, 127, 128, 133, 134, 135, 137, 138, 139, 141, 142, 146, 147, 149, 150, 151, 153, 154, 155, 156, 157, 158, 159, 160, 161, 198, 204, 205, 207, 214, 217, 219, 220, 221, 222, 223, 228, 243, 279, 289, 297, 307, 311, 317, 327 microarray, 163, 165, 178, 182, 186, 191, 192 microarray detection, 178, 191 microarray technology, 163 microcalorimetry, 164, 169, 188 microcavity, 174 microchip, 191 microfilaments, 199, 209 microhabitats, 259 micrometer, 174 micropatterns, 190 microRNAs, 191, 200, 213 microscope, 135, 155, 159, 160 microscopy, 61, 135, 153, 155, 164, 169, 172, 179, 190 microtubule, 200, 201, 212, 215 microtubules, 199, 212 microvascular, 284 migration, 169 mimicking, 82, 84, 85, 94 mimicry, 81, 84, 85, 96, 97 Ministry of Education, 95, 299, 321 miRNAs, 178, 191, 200 mirror, 16 misfolded, 1, 289 mitochondria, 30, 52, 56, 71, 73, 78, 91, 133, 134, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 156, 157, 159, 160, 161, 292 mitochondrial, 8, 42, 52, 71, 99, 100, 118, 133, 134, 136, 138, 140, 141, 142, 146, 147, 149, 151, 153, 155, 157, 159, 160, 257, 280, 292 mitochondrial DNA, 99, 140, 153, 155, 157, 159, 160 mitochondrial membrane, 138, 141, 146, 147, 151 mitogen, 5, 6, 127, 196, 218, 295, 310, 311, 324, 325 mitogen activated protein kinase, 5, 127 mitogen-activated protein kinase, 5, 196, 218, 295, 310, 324 mitogenic, 314

Index mitosis, 159 mitotic, 6 MMP-2, 191 modalities, 122, 297 modality, 119, 120, 297 model system, 183, 196 modeling, 96, 242 models, 33, 34, 38, 43, 44, 45, 48, 49, 61, 73, 122, 171, 197, 222, 295, 308 modulation, 97, 163, 183, 193, 197, 204, 218, 303, 316 modules, 4 mold, 151, 152, 159 molecular biology, 70, 195, 208 molecular dynamics, 323 molecular mechanisms, 109 molecular mimicry, 84, 85 molecular weight, 65, 168, 179, 183, 289 molecules, 6, 13, 14, 31, 35, 36, 37, 48, 58, 69, 70, 76, 78, 80, 81, 83, 86, 90, 99, 101, 168, 172, 173, 175, 196, 197, 198, 202, 203, 205, 208, 215, 226, 228, 229, 230, 231, 232, 234, 235, 237, 239, 314, 320 momentum, 174 monolayer, 166, 267, 275 monolayers, 272 monosaccharide, 282 monosaccharides, 283 morbidity, 110, 120, 276 morphogenesis, 212, 220 morphological, 134, 151 morphology, 20, 170, 196, 205 mortality, 9, 109, 110, 116, 120, 127, 129, 223, 276 mortality rate, 110 Moscow, 225 motion, 36, 175 motivation, 169 motor coordination, 214 motors, 212 mouse, 10, 75, 133, 134, 135, 136, 137, 138, 139, 141, 145, 146, 147, 151, 152, 153, 156, 157, 158, 159, 160, 206, 207, 211, 214, 220, 221, 222, 246, 279, 282, 292, 309, 318, 321 mouse model, 207, 220, 221, 222 movement, 32, 36, 37, 46, 47, 56, 57, 58, 60, 83, 85, 196, 314 mucosa, 156 multicellular organisms, 234

347 muscle, 109, 110, 111, 112, 113, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 257, 258, 259 muscle cells, 120, 122 muscle mass, 110, 111, 126 muscle strength, 110 muscle tissue, 259 muscles, 112, 115, 117, 120, 121, 122, 123, 125, 130 mutagenesis, 99 mutant, 9, 11, 15, 16, 17, 19, 21, 32, 74, 75, 78, 90, 92, 160, 269, 273, 281, 293, 301, 311, 314, 315, 319 mutant proteins, 269, 314 mutants, 8, 10, 15, 17, 18, 19, 22, 64, 100, 101, 201, 272, 283, 287, 319 mutation, 10, 41, 64, 80, 81, 95, 198, 199, 201, 215, 243 mutations, 4, 13, 51, 64, 66, 76, 101, 176, 207, 272, 310 myeloid, 306 myocardial ischemia, 285 myoclonus, 222 myofibrillar, 112, 118, 130 myoglobin, 183, 184 myo-inositol, 282 myosin, 112

N Na+, 268, 275, 279, 280, 281, 282, 283, 284 NaCl, 275 nanofabrication, 164, 172 nanometer, 173 nanometer scale, 173 nanoparticles, 187 natural, 39, 104, 166, 226, 250, 251, 253, 259, 300, 320 natural environment, 250 neck, 32 necrosis, 124, 128, 129 nematode, 2, 3, 4, 11, 13, 14, 16, 17, 19, 20, 21, 22, 319 nematodes, 10, 17 Nembutal, 135 neocortex, 220 neonatal, 119, 120, 128 neonate, 120 neonates, 120, 128 neoplastic, 324

348 neovascularization, 286 nephropathy, 276 nervous system, 14, 196, 210, 213, 218 network, 199, 226 neurobiology, 195 neuroendocrine, 11, 14, 15, 16, 19, 20, 244 neurofibrillary tangles, 205 neurofilament, 198 neurohormone, 236 neurological disease, 197 neurological disorder, 195, 207 neuronal cells, 153, 214 neuronal survival, 203 neurons, 196, 197, 200, 201, 203, 205, 207, 208, 209, 210, 211, 212, 213, 214, 216, 217, 218, 219, 220 neuropathological, 220, 221 neuropathy, 276 neuropeptides, 13, 14, 15, 17, 19, 20, 21, 226, 232, 235, 236, 237, 238, 243, 246 neuroscience, 196 neurotensin, 232, 244 neurotoxins, 231, 234, 236, 238 neurotransmission, 203 neurotransmitter, 196, 199, 202, 215 neurotransmitters, 13, 196, 202, 203 neurotrophic, 197, 202, 216, 218, 247 neurotrophic factors, 202 neutralization, 121 New York, 21, 63, 67, 130, 159, 208 New Zealand, 262 nickel, 99, 177 Nielsen, 106, 129 nitric oxide, 160 nitrogen, 110, 112, 116, 119, 120, 122, 124, 129, 186, 262 NMDA receptors, 205 N-methyl-D-aspartate, 217 N-methyl-D-aspartic acid, 196 nonsense mutation, 175 noradrenaline, 202, 215 normal, 6, 88, 89, 92, 93, 101, 121, 128, 134, 135, 151, 152, 159, 180, 182, 195, 205, 206, 207, 247, 285, 286, 292, 309, 321 normal conditions, 151, 152, 285, 309 normalization, 182, 274 Nrf2, 302 N-terminal, 4, 38, 78, 92, 206, 228, 229, 230, 232, 235, 270, 316

Index nuclear, 134, 139, 145, 153, 159, 199, 201, 211, 214, 304, 310, 312, 314, 319, 322, 323, 324 nuclease, 321 nuclei, 133, 134, 136, 137, 139, 140, 142, 145, 146, 147, 150, 151, 153, 154 nucleic acid, 134, 150, 155, 156, 157, 158, 159, 178, 182, 202, 261, 263, 264 nucleic acid synthesis, 155, 156, 157, 158, 159 nucleoli, 137, 139, 140, 155 nucleotide sequence, 23, 24, 62, 239, 272 nucleotides, 23, 25, 28, 29, 32, 35, 36, 38, 40, 41, 42, 43, 45, 46, 48, 49, 50, 51, 54, 57, 59, 61, 73, 74, 79, 80, 86, 87, 95, 97, 98, 178, 206, 273, 308 nucleus, 100, 114, 133, 136, 137, 138, 139, 141, 142, 199, 200, 293, 295, 308, 312, 313, 315, 325 nutrient, 1, 92, 93, 117, 123, 124, 315, 316, 319 nutrients, 3, 10, 109, 110, 111, 117, 123 nutrition, 110, 111, 116, 125, 129, 263

O oat, 227 obese, 243, 308, 317 obesity, 327 object recognition, 199 observations, 118, 259 occipital cortex, 220 octapeptide, 232, 244 old-fashioned, 152 oligomerization, 289 oligomers, 221 oligosaccharide, 77 olive, 41, 46 oncogene, 216, 295, 299, 300, 303, 305, 306, 320, 323, 325, 326, 327, 328 oncogenes, 115 oncogenesis, 328 online, 167, 187 oocyte, 211, 272 oocytes, 200, 267, 268, 269, 270, 272, 273, 278, 281, 283 operon, 91, 93, 98 opioid, 203, 217 optical, 164, 165, 169, 170, 171, 172, 174, 175, 177, 179, 182, 186, 187, 189, 192, 193 optical transmission, 174 optics, 171 optimization, 268

Index oral, 116, 119, 129, 279 organ, ix, 109, 110, 122, 125, 127, 130, 149, 236, 245, 321 organelle, 142 organelles, 133, 136, 137, 140, 142, 178, 198 organic, 185, 280 organism, 3, 13, 15, 18, 151, 226, 236, 251, 252, 254, 308 organization, 21, 97, 196, 199, 202, 208, 244 orientation, 31, 39, 46, 47, 53, 54, 56, 84, 270 ornithine, 280, 308, 309, 325 oscillatory activity, 128 osmium, 135, 136, 137 ovarian, 297 ovariectomized, 158 ovary, 267, 280 oxidation, 11, 119, 302 oxidative, 7, 8, 10, 119, 292, 302, 319 oxidative stress, 7, 8, 10, 292, 302, 319 oxygen, 25, 39, 173, 260, 262, 285, 286, 290, 292, 293, 296, 297, 299, 302, 303 oxygen consumption, 260, 262

P P. falciparum, 30, 52 p38, 4, 10, 311 p53, 316, 327 pairing, 35, 36, 40, 41, 45, 46, 53, 55, 60, 64 pancreas, 134, 153, 157 pancreatic, 157, 246, 297, 301 pancreatic acinar cell, 157 Papain, 242 paper, 24, 25, 31, 48, 61, 134, 183, 185 paradox, 60 parallel processing, 172 parasites, 247 parenteral, 129 Paris, 159 Parkinson, 1, 6 particles, 100, 188, 200, 201 pathogenesis, 100, 103, 194, 197, 248, 304 pathogenic, 276 pathogens, 187 pathology, 6, 195, 197, 205, 242 pathways, 3, 4, 5, 6, 9, 10, 94, 109, 110, 111, 116, 178, 179, 195, 202, 203, 218, 228, 241, 260, 285, 287, 290, 291, 295, 298, 300, 302, 322

349 patients, 109, 110, 111, 112, 116, 119, 120, 121, 123, 124, 125, 128, 129, 131, 151, 207, 222, 272, 277, 286, 296, 297, 306, 314 pediatric, 121 Penn State University, 109 Pennsylvania, 109 peptidase, 15, 92, 228, 229, 236, 243 peptide, 2, 13, 14, 15, 17, 18, 21, 23, 25, 31, 39, 42, 47, 52, 59, 62, 63, 65, 66, 67, 69, 71, 75, 76, 79, 84, 85, 86, 87, 88, 91, 92, 94, 98, 100, 101, 103, 105, 111, 112, 114, 116, 122, 131, 166, 167, 177, 182, 185, 187, 188, 216, 222, 229, 232, 234, 235, 236, 237, 239, 240, 243, 244, 245, 246, 247, 248, 304, 309, 320 peptide chain, 2, 23, 25, 31, 216 peptides, 13, 14, 15, 17, 18, 19, 21, 166, 168, 179, 228, 229, 230, 231, 233, 234, 235, 236, 237, 238, 242, 243, 244, 245, 246, 247, 248, 308, 328 performance, 16, 189, 251, 257 perinatal, 133, 139, 150, 151, 154, 157, 159 periplasm, 92 peritonitis, 121, 128 permissive, 218 peroxisomes, 140, 142, 156 personality, 63 perturbation, 1, 282 pH, 168, 183, 264, 275 phage, 92, 185, 226, 242 pharmacological, 170 pharmacology, 21 phenol, 248 phenotype, 19, 64, 90, 95, 101, 166, 178, 182, 210, 220, 221, 247, 295, 298, 308, 317, 319, 328 phenotypes, 93, 316 phenotypic, 169, 250 phenotypic plasticity, 250 phenylalanine, 25, 63, 75, 118, 262, 263 pheromone, 226 phorbol, 127 phosphatases, 168, 316, 318 phosphate, 25, 39, 105, 127, 198, 271, 309 phosphates, 298 phosphatidylinositol 3 kinase, 3, 5 phospholipids, 298 phosphoprotein, 313 phosphorylates, 3, 4, 5, 131, 295, 313, 316 phosphorylation, 3, 4, 5, 6, 109, 111, 113, 114, 115, 116, 117, 118, 119, 120, 121, 125, 127,

350 128, 130, 197, 201, 203, 204, 206, 208, 209, 217, 218, 226, 283, 285, 287, 288, 289, 290, 291, 292, 293, 294, 295, 297, 298, 301, 303, 304, 305, 306, 308, 309, 310, 311, 312, 313, 315, 316, 317, 318, 324, 326, 327 photographs, 136, 152 photonic, 173, 190 photonic crystals, 190 photonic devices, 190 photons, 170 physical properties, 250 physico-chemical properties, 193 physiological, 4, 9, 13, 19, 90, 95, 104, 118, 123, 128, 169, 201, 251, 290, 296, 311, 312 physiology, 263, 298 PI3K, 3, 5, 202, 204, 215, 287, 298, 303, 305, 315, 317 pigs, 119, 120, 128 pilot study, 124 placental, 246 planar, 183 plants, 150, 227, 241, 243 plaques, 205 plasma, 111, 115, 116, 117, 118, 119, 120, 121, 122, 125, 127, 168, 172, 203, 267, 270, 271, 272, 281, 282 plasma levels, 111, 120 plasma membrane, 203, 267, 270, 271, 272, 281, 282 plasma proteins, 168, 172 plasmid, 177, 273 plasmids, 281 plasmodium falciparum, 30 plasmons, 170, 174 plastic, 196 plasticity, 10, 195, 196, 198, 202, 204, 205, 206, 207, 208, 209, 210, 215, 216, 219, 220 plastid, 30, 280 platelet, 286, 292, 303 platforms, 163, 164, 165, 187, 189 play, 25, 36, 37, 51, 70, 80, 116, 163, 175, 178, 199, 200, 203, 206, 227, 231, 293, 308 plurality, 168 pneumonia, 110 point mutation, 80, 86, 87, 175 polarized, 282 poliovirus, 308 pollutants, 264 polyamine, 50 polymer, 179, 192

Index polymer film, 192 polymer films, 192 polymerase, 79, 268 polymerization, 178 polypeptide, 2, 6, 20, 24, 34, 35, 41, 42, 48, 62, 64, 67, 69, 70, 75, 76, 79, 101, 106, 111, 112, 125, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 236, 238, 239, 240, 245, 307 polypeptides, 69, 75, 93, 225, 226, 228, 232, 235, 238, 239, 241, 247 pools, 250, 271 poor, 110, 286 population, 77, 168, 188, 207, 210, 251 pore, 235, 236 pores, 173 porous, 173, 174, 190 porphyrins, 185, 186 postoperative, 127 postsynaptic, 197, 198, 201, 203, 205, 208, 209, 210, 212, 217, 221 post-translational, 14, 15, 187, 198, 202, 268, 269, 270, 271, 273, 278 post-translational modifications, 187, 202, 268, 269, 270, 271, 273, 278 potassium, 279 potential energy, 49 power, 138, 141, 168, 179, 254 PPARγ, 318 prediction, 48, 192, 225, 229, 239 predictors, 222 preference, 86, 90, 182, 229, 316 pregnant, 158 preparation, 159, 175, 193, 223 pressure, 55, 57, 286 presynaptic, 196, 203, 216, 217 prevention, 295 primary tumor, 303 private, 10 probability, 159, 325 probe, 175, 190, 297 procedures, 135, 151 production, 8, 9, 124, 206, 207, 269, 270, 273, 297 productivity, 228 prognosis, 286, 297, 305, 319 program, 35, 61, 95, 229 programming, 301 progressive, 7, 276 prokaryotes, 51, 175, 322 prokaryotic, 51, 63, 70, 268, 269, 271, 273

Index prokaryotic cell, 70, 269, 271, 273 proliferation, 3, 169, 218, 287, 308, 320, 322 promote, 1, 4, 69, 91, 95, 119, 206, 318, 319 promoter, 74, 78, 273, 282, 303, 310, 324 promyelocytic, 314, 325 propagation, 173 propane, 135 prophase, 200 prostate, 297, 306 prostate cancer, 298, 306 protease inhibitors, 188, 192 proteases, 78, 92, 98, 126, 168, 180, 181, 192, 227, 236, 241, 242, 243 proteasome, 11, 205, 296, 297, 305, 310, 318 protection, 87, 183, 184 protective mechanisms, 6 protein aggregation, 6 protein arrays, 192 protein binding, 172, 311 protein crystallization, 269 protein family, 326 protein folding, 193, 271, 273, 301 protein function, 6, 213 protein kinase C, 204, 217, 218, 272, 282, 283 protein kinase C (PKC), 272 protein kinases, 4, 272, 283, 287, 311, 312 protein sequence, 225, 228 protein structure, 106, 168, 183, 185, 269 proteinase, 242, 246 protein-protein interactions, 192 proteins, 82, 92, 199, 200, 244, 254, 312, 315 proteobacteria, 101 proteolysis, 97, 99, 100, 111, 112, 126, 172, 179, 182, 183, 184, 185, 193, 226, 227, 228, 229, 230, 232, 233, 234, 239, 293 proteolytic enzyme, 180, 182, 226 proteome, 299 proteomics, 188, 216, 295 protocol, 121, 170 protocols, 172 proto-oncogene, 199 prototype, 14 proximal, 268, 275, 284 proxy, 252 pruning, 205, 220 pseudo, 37, 47, 191 Pseudomonas aeruginosa, 31, 243 psyche, 71 public, 10, 228 publishers, 180, 181

351 purification, 15, 64, 75, 167, 178, 243 Purkinje, 153 pyramidal, 153, 210, 212, 213 pyramidal cells, 153, 213 pyrimidine, 29 pyrophosphate, 78, 95

Q quadrupole, 14, 17 quality control, 69, 88, 96, 98, 106, 226, 234 quantum, 168, 173, 190 quantum dot, 173, 190 quantum dots, 173 quartz, 164

R rabies, 194 radical, 39, 47, 63, 67, 81, 82, 83, 84, 85, 90, 94, 100, 101, 166 radio, 79, 250 radiolabeled, 135, 150, 151, 156 radioresistance, 299 radiotherapy, 286, 297 rain, 195 Raman, 164, 182 random, 75, 139, 142, 320 range, 28, 30, 49, 112, 118, 152, 166, 167, 169, 174, 175, 181, 198, 241, 250, 251, 252, 254, 255, 259, 260, 263, 286, 315 rapamycin, 4, 5, 109, 111, 119, 120, 121, 122, 123, 196, 203, 208, 216, 217, 218, 286, 287, 293, 294, 296, 298, 300, 303, 304, 305, 306, 309, 312, 315, 319, 320 ras, 115, 281, 328 rat, 10, 11, 123, 124, 130, 151, 153, 156, 160, 206, 209, 212, 216, 217, 221, 222, 243, 246, 262, 272, 282, 283, 284, 305, 328 rats, 9, 11, 112, 113, 114, 115, 117, 119, 120, 121, 122, 123, 124, 125, 126, 129, 208, 215, 257, 279 reaction rate, 183 reactive oxygen, 292 reactive oxygen species, 292 reactivity, 179 reading, 99, 106, 172, 190, 288, 291 real time, 163, 186, 190 real-time, 177, 189, 190, 267, 284

352 receptor agonist, 203, 315 receptors, 4, 13, 115, 129, 170, 196, 198, 203, 204, 208, 216, 217, 218, 219, 220, 226, 273, 295 recognition, 23, 24, 25, 31, 35, 46, 51, 53, 54, 55, 57, 58, 60, 62, 64, 66, 72, 76, 86, 97, 101, 103, 105, 106, 114, 175, 194, 201, 229, 230, 231, 232, 234, 307, 309, 310, 312, 314 recombination, 89, 284, 286, 299 reconstruction, 53 recovery, 39, 93, 109, 110, 111, 122, 259, 263 recruiting, 211 recycling, 24, 69, 70, 84, 94, 95, 96, 98, 101, 104, 106, 113, 175, 193, 194 red blood cells, 285 redistribution, 110, 122, 210, 220, 295 redox, 113, 302 reduction, 1, 2, 4, 7, 8, 116, 120, 123, 183, 204, 259, 289, 290, 297, 318, 321, 327 redundancy, 73, 316 reflection, 225 refractive index, 170, 172, 173, 179, 183 refractory, 122 regeneration, 242 regression, 253, 254, 255 regression analysis, 253, 255 regression line, 253, 254, 255 regular, 201, 234, 235 regulation, 1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 20, 91, 93, 103, 107, 113, 115, 121, 123, 125, 127, 129, 163, 178, 205, 206, 207, 208, 211, 213, 216, 219, 221, 222, 228, 252, 267, 271, 272, 282, 283, 286, 287, 290, 291, 292, 294, 295, 296, 297, 298, 299, 300, 301, 302, 305, 308, 310, 311, 314, 316, 317, 318, 323, 324, 326 regulations, 95 regulators, 3, 9, 106, 117, 121, 126, 218, 237, 268, 308, 318, 322, 326, 328 relationship, 35, 48, 56, 92, 115, 116, 121, 134, 153, 155, 250, 251, 252, 255, 256, 257, 284 relationships, 123, 279 relevance, 169 remodeling, 196, 222 renal, 122, 267, 268, 275, 279, 282, 283, 284, 297 renal cell carcinoma, 298 reoxygenation, 289, 292, 293, 302 repair, 1, 7, 8, 89 replication, 89, 94, 100, 273, 283

Index repression, 94, 103, 128, 200, 202, 214, 215, 287, 290, 301 repressor, 75, 93, 116, 198, 201, 209, 218, 288, 289, 326, 327 reproduction, 1 research, 15, 21, 95, 135, 164, 178, 179, 195, 196 researchers, 61, 171, 172, 177 reserves, 111 residues, 14, 18, 25, 29, 30, 37, 39, 47, 58, 62, 65, 71, 76, 78, 81, 83, 94, 98, 185, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 238, 239, 242, 243, 290, 310, 315 resin, 135 resistance, 4, 8, 10, 66, 109, 111, 120, 190, 273, 286, 298, 302, 315, 317, 319, 321 resolution, 16, 18, 31, 38, 53, 62, 63, 66, 67, 73, 81, 152, 160, 188, 193, 314 resonator, 173, 174 resources, 95 respiration, 260, 286 respiratory, 8, 160 responsiveness, 121 restoration, 112 restriction enzyme, 273 retardation, 205 retention, 120, 124, 129, 254, 255, 256, 258, 272, 314 reticulum, 133, 136, 137, 138, 140, 142, 285, 289, 301 retina, 158, 159 retinoic acid, 203, 217 retinoic acid receptor, 203 retinopathy, 276 retrovirus, 295 returns, 114, 117 rhythms, 19 ribonucleic acid, 159 ribosomal, 1, 3, 4, 5, 23, 25, 31, 37, 58, 60, 62, 63, 64, 65, 66, 67, 74, 78, 79, 84, 85, 96, 98, 99, 101, 102, 103, 104, 105, 106, 112, 113, 114, 118, 119, 122, 127, 169, 175, 187, 188, 191, 193, 194, 198, 204, 211, 214, 252, 287, 288, 292, 295, 298, 300, 306, 307, 308, 309, 312, 322 ribosomal RNA, 62, 63, 64, 65, 66, 67, 99, 252 ribosomes, 3, 9, 24, 32, 48, 63, 64, 66, 69, 70, 74, 76, 77, 79, 80, 88, 93, 94, 96, 97, 98, 99, 104, 105, 112, 139, 140, 159, 160, 193, 194, 197, 200, 206, 215, 252, 291 rings, 105

Index risk, 110, 207, 298 rivers, 259 RNA processing, 100, 104 RNAi, 3, 170 RNAs, 40, 62, 69, 70, 88, 96, 101, 102, 105, 106, 107, 178, 198, 200, 206, 210, 211, 222 robotic, 195 rodent, 11, 122 room temperature, 186 rotations, 59 routines, 183 Royal Society, 263, 264 Russia, 225 Russian, 225, 240 Russian Academy of Sciences, 225, 240

S S phase, 314, 325 Saccharomyces cerevisiae, 30, 82, 104, 294, 310 saline, 134, 135 salinity, 258 saliva, 228 salmon, 259, 263 salmonella, 31, 92, 96, 100 sample, 17, 169 savings, 8 scaffold, 114, 285, 288, 294, 307, 322 scaffolding, 196, 201, 202, 203, 217, 287, 293 scaling, 253 scarcity, 103 Schmid, 281 science, 164, 166 scientific, 95, 195 sclerosis, 304 sea urchin, 247, 260, 263 search, 21, 268, 276, 278 searching, 53 seasonal pattern, 258 seasonal variations, 258 seasonality, 258 seawater, 250 secretion, 111, 115, 243, 245, 276, 279 sedimentation, 70 seizure, 207 seizures, 197, 205, 207, 208, 222 selecting, 320 selectivity, 59, 182, 190, 231, 242, 273, 276, 279 self, 190 self-assembling, 190

353 senescence, 10, 11, 133, 319 senile, 139, 141, 147, 206 senile plaques, 206 senility, 262 sensing, 171, 187, 189, 286, 299, 302, 303 sensitivity, 62, 171, 172, 173, 250, 260, 320, 327 sensors, 164, 169, 172, 174, 183, 187, 189 separation, 17, 18, 167, 190, 231, 283 sepsis, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 129, 130, 131 sequencing, 61, 166, 248, 280 series, 13, 24, 112, 122, 175, 188, 314 serine, 3, 5, 118, 131, 191, 204, 205, 226, 227, 241, 243, 246, 287, 288, 289, 290, 295, 315 serotonin, 204, 218 serum, 4, 115, 117, 127, 180, 187, 188, 192, 226, 310, 315 serum albumin, 180, 192 services, 229 severity, 111, 207 shape, 32, 36, 51, 84, 85, 169, 173, 196, 201, 205, 310 shaping, 214 shares, 70, 73, 121 shock, 4, 56, 93, 96, 101, 125, 262, 310 short-term, 197, 202, 215 short-term memory, 197 shoulder, 59, 78 signal peptide, 13, 14, 15, 226, 229, 239, 240 signal transduction, 3, 10, 109, 111, 114, 116, 122, 170, 195, 196, 295, 300, 326 signaling, 3, 4, 5, 6, 9, 10, 11, 13, 14, 15, 20, 21, 118, 120, 121, 127, 130, 170, 178, 196, 198, 199, 202, 203, 208, 216, 217, 218, 219, 226, 232, 241, 287, 291, 292, 294, 297, 300, 301, 302, 303, 304, 305, 306, 315, 317, 326 signaling circuits, 178 signaling pathway, 3, 4, 5, 13, 118, 121, 127, 130, 170, 196, 199, 203, 208, 217, 218, 287, 291, 294, 298, 302, 304, 315, 326 signaling pathways, 3, 13, 130, 170, 196, 199, 203, 217, 287 signalling, 9, 10, 216, 296, 304, 305, 319, 328 signals, 24, 51, 62, 83, 168, 179, 182, 186, 195, 198, 201, 214, 216, 244, 287, 288, 289, 291, 304, 314 silica, 173 silicon, 164, 173, 174, 190 silkworm, 247

354 silver, 133, 136, 137, 138, 139, 140, 141, 142, 144, 146, 147, 150, 151, 152, 153, 154 similarity, 14, 91, 92, 235, 283 simulation, 323 simulations, 323 single nucleotide polymorphism, 166 single walled carbon nanotubes, 164 SiO2, 173 sites, 23, 24, 31, 36, 37, 38, 41, 42, 48, 52, 56, 58, 60, 64, 67, 77, 78, 81, 85, 88, 93, 101, 114, 175, 180, 182, 183, 197, 198, 199, 200, 209, 210, 226, 229, 230, 231, 233, 234, 235, 239, 241, 248, 261, 287, 291, 292, 295, 296, 308, 310, 312, 315, 316 skeletal muscle, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 128, 129, 130, 131, 221, 305, 311 skills, 196 skin, 237, 244, 245, 248 slow-twitch, 130 small intestine, 126, 280, 283 snakes, 238 sodium, 8, 248, 267, 268, 275, 279, 280, 284, 310 software, 61, 166 soil, 13 solid phase, 17, 177 solid tumors, 290 solubility, 177 solvent, 17, 168, 183 somata, 200 somatic cells, 3, 11, 159, 327 somatic mutations, 298 somatostatin, 301 sorting, 169 soybean, 227, 243 Spain, 161 spatial, 35, 48, 56, 63, 199, 207, 249, 297 spatial learning, 207 spatial memory, 199 species, 13, 21, 25, 30, 42, 70, 73, 88, 93, 104, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 263, 265, 276 specificity, 18, 58, 63, 98, 99, 142, 167, 170, 181, 182, 227, 229, 242, 243, 244, 284, 290 spectra, 18, 166 spectroscopy, 166, 167, 168, 169, 182 spectrum, 125 speed, 186 spermatogenesis, 246

Index spine, 195, 196, 201, 205, 206, 212, 213, 215, 217, 220 spines, 196, 197, 198, 199, 201, 205, 206, 209, 220 spleen, 134, 153, 158, 311 spore, 93 squamous cell, 305 squamous cell carcinoma, 305 stability, 4, 39, 51, 55, 169, 186, 188, 199, 200, 202, 206, 211, 215, 218, 267, 269, 270, 271, 291, 293, 295, 303, 310, 316, 318, 321, 327 stabilization, 59, 200, 210, 211, 283, 286, 293, 302 stabilize, 37 stages, 99, 133, 139, 140, 142, 144, 145, 149, 150, 151, 153, 169, 175, 226, 227, 229 standard deviation, 143, 144, 148, 149 Staphylococcus aureus, 31 starfish, 99 starvation, 4, 90, 93, 97, 101, 111, 121, 126, 127 statistics, 153 steady state, 206 steel, 16 stellate cells, 139 steric, 37, 178 sterile, 114, 115, 119 steroids, 124 stochastic, 7 stoichiometry, 81, 86, 169 stomatitis, 270, 282 storage, x, 19, 195, 196, 200, 204, 205, 208, 227 strain, 16, 17, 19, 134, 135 strains, 13, 16, 17, 19 strategies, 110, 191, 248, 276 strength, 93, 168, 174, 196, 197 streptomyces, 79, 315 stress, 4, 6, 7, 8, 9, 93, 94, 96, 103, 111, 122, 124, 201, 213, 219, 285, 286, 288, 289, 290, 292, 295, 296, 297, 300, 301, 302, 305, 326 stress granules, 201, 213 stress level, 124 stressors, 9 stromal, 298 stromal cells, 298 strong interaction, 91 structural gene, 20, 241 structural protein, 151, 236 structural transitions, viii, 23 structuring, 235 subcellular, 199

Index substances, 268 substitutes, 69, 83 substitution, 60 substrates, 14, 15, 88, 99, 104, 117, 167, 178, 179, 182, 192, 226, 228, 257, 287, 292, 293, 295, 313 subtilisin, 14, 19, 20, 226, 227, 228, 231, 241, 242, 243, 244 success rate, 167, 188 sucrose, 198 sugar, 79, 273, 279, 281, 283 sugars, 140, 269, 280 summer, 258, 259, 262, 264 sun, 157, 158 supernatant, 177 superoxide, 4 superoxide dismutase, 4 supply, 93, 120, 134, 256, 257 suppression, 51, 175, 259, 314, 328 suppressor, 52, 88, 105, 298, 304, 313, 316, 321 surface chemistry, 168, 171 surgery, 124, 130 surgical, 110, 127, 131 surplus, 1 surveillance, 70, 91, 97, 101 survival, 1, 7, 8, 55, 93, 95, 96, 217, 226, 286, 290, 291, 295, 296, 298, 301, 308, 309, 319, 320 surviving, 297 susceptibility, 207, 223 SV40, 273, 283 Sweden, 135 switching, 56, 312 symbols, 41, 46, 57 symmetry, 46, 47 synapse, 196, 197, 206, 214, 221 synapses, 196, 197, 198, 200, 201, 202, 203, 207, 208, 209, 210, 214, 215, 216, 217, 218 synaptic plasticity, 195, 196, 197, 198, 200, 201, 202, 204, 205, 207, 208, 209, 210, 213, 216, 217, 218, 219, 220, 327 synaptic strength, 196, 197 synaptic transmission, 202, 206, 216 synaptogenesis, 206, 221 syndrome, 130, 195, 197, 220, 221, 272, 279 synthetic, 10, 83, 112, 119, 120, 130, 154, 160, 163, 185, 193, 209, 261, 300 systematic, 246 systematic review, 246

355 systems, 10, 79, 91, 110, 149, 170, 171, 184, 186, 196, 267, 268, 269, 278, 303

T T cell, 246, 310, 323 tandem mass spectrometry, 14, 17 targets, 89, 110, 120, 123, 167, 168, 169, 172, 175, 178, 182, 185, 201, 204, 206, 215, 242, 268, 279, 287, 292, 296, 302, 303, 305, 316 taxonomic, 237 taxonomy, 236, 238, 239 technical assistance, 154 technological, 166 technology, 13, 15, 165, 166, 167, 169, 171, 175, 176, 182, 186, 187, 189, 191, 194 temperature, 78, 90, 93, 95, 159, 168, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 311 temporal, 249 termination codon, 70, 75, 79, 84, 88, 89, 91, 97, 106 ternary complex, 23, 24, 25, 32, 45, 52, 53, 54, 55, 57, 59, 60, 61, 65, 75, 77, 80, 84, 113, 285, 288, 291 territory, 152 testis, 134, 153, 157, 158 tetroxide, 135, 136, 137 textbooks, 70 theoretical, 17, 260 theory, 7, 185 therapeutic, 122, 208, 241, 268, 277, 278, 284, 296, 298, 308 therapeutic agents, 277, 278, 284 therapeutic targets, 208, 308 therapeutics, 175, 182, 207 therapy, 242, 267, 286, 296, 298, 300, 303, 305, 308, 321, 322, 323, 327, 328 thermal, 173, 188, 249, 250, 251, 252, 254, 259, 260, 264 thermal degradation, 188 thermodynamic, 85 thermodynamic stability, 85 thermodynamics, 168 theta, 218 thin film, 179 thin films, 179 three-dimensional, 24, 62, 64, 67, 309 threonine, 3, 5, 118, 204, 287, 288, 289, 295, 315 threshold, 119, 274

356 thymidine, 150, 151, 152, 153, 155, 158 thymine, 71 thyroid, 247 tight junction, 272 time, 14, 15, 16, 17, 48, 58, 61, 114, 166, 167, 172, 175, 177, 179, 180, 181, 183, 184, 185, 191, 193, 194, 200, 206, 235, 251, 257, 291, 293, 312 timing, 100, 176, 200 tissue, 13, 15, 18, 110, 118, 122, 123, 125, 135, 151, 152, 155, 157, 198, 202, 215, 249, 250, 251, 252, 254, 256, 257, 258, 263, 269, 270, 280, 311, 321, 323, 327 tissue plasminogen activator, 202, 215 titration, 168 TNF-alpha, 111, 126 Tokyo, 134, 135, 155, 156, 279, 326 tolerance, 264, 297, 301, 302 tomato, 227, 243 topology, 282 total energy, 1 toxic, 8, 231, 236, 284 toxicity, 169, 228, 276, 324, 328 toxin, 103, 175, 193, 194, 228, 231, 233, 235, 241, 244, 247, 248 toxins, 89, 90, 187, 228, 230, 234, 235, 237, 245, 247, 248 trachea, 134, 153, 157 tracking, 170 traffic, 241 training, 204 trans, 69, 70, 71, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 94, 95, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 197, 198, 199, 203, 217 transcript, 2, 74, 211, 291, 312, 314 transcription, 2, 4, 6, 100, 112, 175, 197, 199, 202, 204, 208, 220, 267, 270, 282, 283, 285, 286, 290, 291, 292, 296, 297, 302, 303, 313, 319 transcription factor, 4, 6, 199, 285, 286, 290, 291, 292, 296, 297, 302, 313, 319 transcription factors, 6, 286, 313 transcriptional, 4, 94, 252, 270, 285, 286, 291, 292, 293, 295, 296, 303, 305, 310, 314, 318, 322, 325 transcriptional upregulation, 295 transcripts, 97, 178, 207, 297, 313, 314 transducer, 163, 164, 296 transduction, 196, 203

Index transfection, 115, 273, 274 transfer, 59, 62, 63, 65, 66, 70, 75, 79, 82, 83, 91, 96, 97, 98, 99, 100, 101, 102, 105, 107, 252, 307 transfer RNA, 62, 63, 65, 99, 252, 307 transformation, 24, 273, 287, 308, 309, 311, 314, 319, 322, 324, 325, 327, 328 transforming growth factor-β, 241 transgenic, 205, 319 transgenic mice, 319 transient precursor, 51 transistor, 187 transistors, 164 transition, 25, 31, 33, 34, 35, 36, 37, 39, 49, 55, 57, 58, 65, 183, 287, 314 transitions, 182, 193, 194, 301 translational, 4, 9, 10, 11, 65, 67, 88, 91, 96, 98, 99, 101, 105, 112, 115, 116, 122, 123, 125, 127, 160, 166, 168, 178, 191, 197, 198, 199, 200, 202, 203, 205, 206, 208, 209, 210, 212, 214, 215, 217, 218, 219, 221, 241, 259, 271, 287, 290, 291, 294, 297, 299, 300, 301, 302, 314, 317, 320, 321, 325, 326, 327, 328 translocation, 23, 24, 32, 39, 41, 42, 46, 47, 48, 50, 51, 53, 54, 56, 57, 61, 62, 63, 64, 65, 66, 67, 75, 76, 82, 83, 85, 86, 91, 94, 197, 209, 295 transmembrane, 205, 246, 270, 290 transmission, 196 transport, 8, 20, 112, 197, 198, 199, 200, 201, 209, 210, 212, 213, 257, 267, 268, 269, 270, 271, 272, 274, 275, 276, 278, 279, 280, 281, 282, 283, 284, 291, 292, 308, 314, 322, 325 transportation, 178, 313 transposon, 99 trauma, 112, 116, 121, 131 travel, 199 trend, 52, 164 triggers, 48, 98, 104, 219, 296, 314 triglycerides, 129 tripeptide, 50, 51, 63 trisomy, 206 trisomy 21, 206 tritium, 152 trout, 259, 261, 263, 264 Trp, 52, 310 trypsin, 168, 179, 180, 181, 183, 184, 185, 186, 236, 246 tryptophan, 52, 63, 91, 98, 107, 118, 182 tuberous sclerosis, 294, 304

Index tubers, 304 tubular, 268, 284 tumor, 111, 115, 125, 129, 242, 286, 290, 291, 294, 295, 296, 297, 299, 301, 302, 303, 304, 305, 319, 320, 321, 323, 327, 328 tumor cells, 286, 290, 294, 297 tumor growth, 286, 291, 301, 321, 328 tumor necrosis factor, 111, 115, 125, 129 tumor progression, 242, 299, 302 tumorigenesis, 285, 298, 308, 319, 323, 328 tumors, 285, 286, 295, 297, 298, 319, 320, 327 tumour, 128, 296, 297, 316, 319 tumours, 297, 305 turnover, 8, 10, 88, 94, 103, 110, 125, 128, 129, 200, 211, 257, 258, 259, 262, 263, 264, 282, 316 two-dimensional, 168, 315 type 2 diabetes, 284 type 2 diabetes mellitus, 284 tyrosine, 25, 118, 203, 204, 219, 290, 298, 301, 306

U ubiquitin, 178, 179, 191, 192, 205, 217, 262, 293, 296, 303, 305, 310 ultrastructure, 158 unfolded, 25, 39, 41, 42, 55, 57, 60, 285, 289, 291, 297, 301, 302 unfolded protein response, 285, 289, 291, 297, 301, 302 unilateral, 206 United States, 110, 123, 168 universal genetic code, 63 untranslated regions, 178, 198, 287 urea, 110, 122 urea nitrogen, 110, 122 uridine, 66, 86, 150, 151, 152, 153, 160, 206, 283 urinary, 268 users, 170 uterus, 134, 153, 158

V Valdez, 247 validation, 178 validity, 81 valine, 111, 116, 118

357 values, 31, 112, 114, 117, 119, 152, 167, 169, 181, 253, 257, 258, 260, 274, 276 variability, 250 variable, 35, 41, 54, 60, 73, 89, 96, 104, 181, 199, 249, 250, 314 variables, 167, 257 variance, 136 variation, 73, 251, 261, 263 vascular, 211, 285, 286, 292, 296, 299, 303, 308, 309 vascular endothelial growth factor (VEGF), xii, xiii, 211, 286, 292, 296, 303, 308, 309 vasodilation, 286 vasopressin, 198 vector, 267, 268, 273 velcade, 178, 286 velocity, 16, 259 vertebrates, 211, 250, 251 vesicle, 221 Victoria, 248 viral, 97, 228, 288, 289, 300, 308, 311, 322, 324 viral infection, 288, 289, 311, 324 virus, 84, 194, 228, 244, 270, 273, 282, 288, 289, 308, 322 virus infection, 288, 289 viruses, 178 visible, 57, 80 visual, 136, 144, 204 visualization, 100, 216

W Washington, 65, 102 water, 17, 110, 118, 134, 135, 168, 174, 186, 245, 252, 254, 257, 258, 259, 260, 262, 263 water-soluble, 168 Watson, 29, 55, 60, 219 waveguide, 172, 173, 174, 179, 180, 190 waveguides, 170, 190 wavelengths, 172, 179 weakness, 110 wealth, 226 weight gain, 121, 129 weight loss, 121, 127 wells, 170, 172, 183, 184 wet, 135, 136, 137, 139, 239, 259 wheat, 191 wheat germ, 191 wild type, 3, 8, 17, 18, 19, 41, 104, 290, 311 windows, 250

Index

358 winter, 258, 259, 263, 264 Wisconsin, 195 workflow, 16, 17 worms, 1 wound healing, 110, 124 writing, 190

X X-axis, 34, 37 xenografts, 297, 305, 321 Xenopus oocytes, 270, 281 X-ray, 25, 31, 32, 33, 35, 36, 41, 44, 48, 52, 61, 84, 106, 188, 314, 323 X-ray analysis, 48, 61 X-ray crystallography, 25, 31, 36, 106, 188, 314

Y Y-axis, 37, 238 yeast, 1, 2, 14, 20, 28, 29, 36, 39, 40, 48, 54, 55, 63, 193, 222, 226, 241, 268, 269, 287, 290, 293, 300, 310 yield, 14, 15, 167, 184, 225, 268

Z Zea mays, 30 zebrafish, 323 zinc, 201, 211 zooplankton, 261