Virus as Populations ­Virus as Populations Composition, Complexity, Dynamics, and Biological Implications Esteban Domingo Centro de Biología Molecular Severo Ochoa (CSIC-UAM) University Automona de Madrid Cantoblanco Madrid, Spain AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier Academic Press is an imprint of Elsevier 125 London Wall, London, EC2Y 5AS, UK 525 B Street, Suite 1800, San Diego, CA 92101–4495, USA 225 Wyman Street,Waltham,MA 02451, USA The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, UK © 2016 Elsevier Inc All rights reserved No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein) Notices Knowledge and best practice in this field are constantly changing As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-12-800837-9 For information on all Academic Press publications visit our website at http://store.elsevier.com/ Publisher: Janice Audet Acquisition Editor: Jill Leonard Editorial Project Manager: Halima Williams Production Project Manager: Julia Haynes Designer: Mark Rogers Typeset by SPi Global, India www.spi-global.com Printed in USA Foreword Viruses are minute organisms that, although mostly invisible, rule the world Scientists may argue whether these obligatory intracellular organisms belong in the tree of life or whether they were the first replicating entities on earth, but all agree that they have decisively influenced evolution The vast majority of the planet’s 1031 viruses live in the oceans, whereas the terrestrial viruses make up only a very small fraction They were first discovered, however, because their “ghosts” were exposed through diseases in plants and mammals (researchers were unable to “see” these ghosts until electron microscopy revealed them in the late 1930s) Following the discovery of tobacco mosaic virus and foot-and-mouth disease virus in 1898, a bewildering number of viruses have been identified many of which cause terrible human diseases, triggering immense fear as well as admiration: How can these minute creatures live so efficiently and, during pandemics, how can they spread so rapidly across an entire globe? In principle, all viruses have the same, simple architecture: a relatively small piece of nucleic acid (the DNA or RNA genome), containing all information for proliferation, that is surrounded by a proteinaceous shell for protection and cell attachment, often in combination with a membranous layer Yet the differences in sizes and shapes of virions for numerous different virus families are astounding Even more mind-boggling is the wealth of genetic information stored in their small genomes, which directs very different strategies of viral proliferation leading to cell transformation, to cell death, or the death of the entire host Throughout his professional life, Esteban Domingo has studied the highly complex issues of viral genetics, which qualifies him second to none to summarize the entire field Domingo begins his narrative with a short course in general virology, worthy of study for anyone involved in teaching or carrying out research in virology This is followed by an introduction to the overwhelming, complex secrets of genetic information hidden in even the smallest viral genomes Domingo’s text is not dogmatic Superbly written, it offers facts and hypotheses and encourages the readers to arrive themselves at the “truth,” however, short-lived that truth may be The reader is pushed to ask questions like: What exactly is a virus and where does it come from? How can we understand infection and viral diseases? How can we prevent their terror? Beyond experimental breakthroughs that have informed our growing understanding of the molecular nature of viruses and their replication in cells and tissues of their respective hosts, the more recent decades have brought forth new concepts in how we perceive viruses A shocking surprise in virus research was the landmark discovery by Hans Eggers and Igor Tamm and by Esteban Domingo and Charles Weissmann of the high mutation rate in viral replication, particularly of RNA viruses The realization of error-prone replication of viruses heralded a paradigm shift in understanding molecular evolution It changed the landscape of all studies regarding viral replication and pathogenesis Rather than fixed entities operating with a single, unique nucleic acid sequence, individual species and serotypes of viruses have come to be viewed as genetically heterogeneous, complex populations comprised of a consensus sequence genotype, called by Manfred Eigen and John Holland “quasispecies.” As a result of the error-prone replication and subsequent selection of mutations that confer virus fitness in response to cell-specific host factors, immune modulation, or environmental factors, viruses have evolved to exist as quasispecies populations With these observations as a backdrop, Esteban Domingo offers a comprehensive, up-to-date treatise on the mutable nature of viruses and how this property affects virus-host interactions, viral fitness and adaptation, viral pathogenesis, and the ever-changing xi xii Foreword prospects for antiviral therapies, including the intriguing possibility of making use of what is called an error catastrophe The narrative on the error-prone replication of viruses is amplified by bringing Darwinian principles to bear on the generation of variant genomes (and, as a result, viral quasispecies) and how these virus populations behave in terms of random drift, competition, and adaptation/selection for fitness in different environments This latter topic is addressed in depth via a discussion of the interactions of virus populations with their hosts and how biological parameters such as receptor usage, codon usage/codon pair frequencies, and the host immune response can provide selective pressure and resultant costs to viral fitness In a subsequent section of this volume, viral fitness is addressed head-on, with a discussion of how genomic sequences of viruses impact the fitness landscape during viral replication and how subpopulations of virus quasispecies may impact the molecular memory of an evolving quasispecies In the second half of this volume, Domingo describes different experimental systems and approaches used to analyze changes in virus population composition resulting from perturbations and selective forces applied during infection and replication For example, persistent viral infections in cell culture allow the study of experimental evolution, while plaque-to-plaque transfers of viruses experimentally recapitulate infectivity bottlenecks that produce low-fitness viruses which may have extreme phenotypes In addition, these experimental systems provide tractable platforms to test more general principles of genetics, for example, Muller’s ratchet or the Red Queen hypothesis, during viral replication The book then moves to describe the study of virus transmission and evolution in nature and the many parameters that impact evolution rates Emergence and reemergence of pathogens is discussed in the context of the complexity of behavior of viral populations intertwined with nonlinear events derived from environmental, sociologic, and ecological factors The final sections of the book are devoted to a discussion of some of the more tangible implications of viral quasispecies/sequence evolution in considering its impact on disease prevention and strategies for vaccine design and antiviral therapeutics This latter topic is analyzed at both the theoretical and pragmatic levels as part of what Domingo calls “virus as moving targets,” due to the dynamic nature of viral genome sequences and the proteins they encode Domingo then concludes this illuminating monograph by bringing the discussion of quasispecies and population dynamics full circle to a focus on nonviral systems (cells, cancer, and other infectious agents) that leave the reader with a number of “big-picture” concepts related to genetic variation, random versus selected replication events, and information theory It is the universal nature of these concepts that makes this volume essential reading for virologists, evolutionary biologists, population geneticists, and any others who wish to be exposed to an intense level of scholarship on a fascinating topic Fiat lux! Bert Semler, Irvine, California Eckard Wimmer, Stony Brook, New York Acknowledgments This book is a long story, with a lot to be acknowledged I begin with the most immediate and then go back in time, with some deviations from linearity The present core team in my laboratory at Centro de Biología Molecular “Severo Ochoa” (CBMSO) in Madrid, composed of Celia Perales, Ana Isabel de Avila, and Isabel Gallego have done an immense job that has permitted the timely completion of the book (photography at the end of the Acknowledgments) In addition to her scientific leadership, Celia has unique skills to convert scientific concepts into images Hers are all the original figures in the book Ana and Isabel have diligently complemented my computer age inabilities by keeping track of end-note and professional typing, always alert to mistakes and inconsistencies in my drafts Celia, Ana, and Isabel have worked on the book while continuing with experiments and acting as a survival brigade in very difficult times for Spanish science due to drastic budget restrictions I am deeply thankful to the three of them I am also indebted to Eckard Wimmer and Bert Semler for taking time to read the book and to write a Foreword I deeply appreciate their help, not only now but also at different stages of my activity as a picornavirologist We shared friendship with John Holland, a decisive name in the scientific contents of the book Many thanks go also to Elsevier staff for their support and involvement In particular, to Elizabeth Gibson in the early stages of book proposal, Jill Leonard for her continuous encouragement, Halima Williams for pushing me the right dose (never beyond a catastrophe threshold), and Julia Haynes for an intelligent and positive attitude during the last stages of book production I am indebted to Elsevier for publishing the book and also for long-time support reflected in the publication of the two editions of “Origin and Evolution of Viruses,” and my involvement in the editorial board of Virus Research initially with Brian Mahy, and recently with Luis Enjuanes, Alina Helsloot, and distinguished colleagues Our laboratory has had the privilege to engage in multiple collaborations that have broadened the scope of our research while maintaining the focus on implications of virus complexity We belong to an active network of experts in liver disease (Spanish acronym CIBERehd) thanks to the interest of Jordi Gomez, Jaume Bosch, Juan Ignacio Esteban, and Josep Quer in our work on viral quasispecies and model studies with hepatitis C virus (HCV) Our current cooperation involves liver disease experts of different institutions, particularly Josep Quer, Josep Gregori, Javier Garcia-Samaniego, Aurora Sanchez-Pacheco, Antonio Madejón, Manuel Leal, Antonio Mas, Pablo Gastaminza, Xavier Forns and their teams Our connection with HCV goes back to the early 1990s when Jordi Gomez and Juan Ignancio Esteban from Hospital Vall d'Hebrón in Barcelona came to our laboratory to discuss the results that became the first evidence of HCV quasispecies in infected patients (the now classic Martell et al., 1992 paper) The cell culture system for HCV was implemented in Madrid with the help of Charles Rice and the efforts of Celia Perales and Julie Sheldon These ongoing studies are a source of knowledge and inspiration for us Before HCV, there were 35 years of research on foot-and-mouth disease virus (FMDV) About 100 students, postdocs, and visitors contributed to the research whose major aim was to explore if quasispecies dynamics applied to animal viruses I cannot mention all people involved, but most of them are coauthors of publications quoted in the book Juan Ortín, the now famous influenza virus (IV) expert, and I organized and shared our first independent laboratory (“down at the corner” of C-V block) at CBMSO, an important institution for Spanish biomedical sciences created in the 1970s under the ­auspices of Eladio Viñuela, Margarita Salas, David Vázquez, Carlos Asensio, Federico Mayor xiii xiv Acknowledgments Zaragoza, Severo Ochoa, and others Eladio suggested to Juan and I to work on IV and FMDV because of the unknowns underlying antigenic variation of these viruses, and the problem of producing effective vaccines And so we did Juan on IV and me on FMDV Mercedes Dávila joined as laboratory assistant and remained in the FMDV laboratory for 31 years (!), only to leave as a result of an appointment to manage a central facility at CBMSO The first graduate students were Francisco Sobrino (Pachi) and Juan Carlos de la Torre They initiated the FMDV quasispecies work at the pre-PCR age Mauricio G Mateu was determinant to expand the scope of our research because at the suggestion and with help of Luis Enjuanes we extended the studies of genetic variation to antigenic variation by producing and using monoclonal antibodies against FMDV In addition to our own antibodies, we received some from Panaftosa, Brasil, and Emiliana Brocchi from Brescia, Italy Collaborations were established with Panaftosa and Centro de Virología Animal and INTA-Castelar from Argentina We also began productive projects with Ernest Giralt and David Andreu on peptide antigens, with Ignasi Fita, Nuria Verdaguer on the structure of antigen-antibody complexes, and David Stuart on the structure of the FMDV serotype used in our research The collaboration with Nuria Verdaguer and her team continues to date on viral polymerases, particularly with the work of Cristina Ferrer-Orta, in a line of work initiated by Armando Arias at the biochemical level The first nucleotide sequences of our FMDV reference virus were obtained by Nieves Villanueva and Encarnación Martínez-Salas In the late 1980s, Cristina Escarmís (my wife and the person who introduced nucleotide sequencing in Spain and in our laboratory) joined our group to expand our sequencing know-how and to work on the molecular basis of Muller's ratchet Using routinely nucleotide sequences rather than T1-fingerprints (a transition facilitated by John Skehel, with a summer visit to Mill Hill) was as exciting a change as we experience nowadays seeing deep sequencing data Additional help to the FMDV research was obtained from Joan Plana, Eduardo L Palma, María Teresa FranzeFernández, Elisa C Carrillo, Alex Donaldson, Joaquín Dopazo, Andrés Moya, Pedro Lowenstein, and María Elisa Piccone, among others In the 1980s, there were two events that led to the connection of our laboratory with those of John Holland and Manfred Eigen One was the publication by John Holland and colleagues in 1982 of the Science (1982) article on “Rapid evolution of RNA genomes.” The paper was brought to me by my colleague from Instituto de Salud Carlos III José Antonio Melero What I thought was the forgotten Qβ work of Zürich suddenly revived in a Science article that proposed a number of biological implications of high mutation rates and rapid RNA evolution Not without hesitation, some years later I wrote a letter to John Since he was extremely receptive, we talked on the phone and met for the first time at the International Congress of Virology in Edmonton, Canada in 1987 Juan Carlos de la Torre went to work with John as a postdoctoral student, and then I spent a sabbatical stay in 1988-1989, followed by several other visits to UC San Diego Our friendship and shared view of how RNA viruses work lasted until his death in 2013 John and his team (which at the time of my visits included David Steinhauer, David Clarke, Elizabeth Duarte, Juan Carlos de la Torre, Isabel Novella, Scott Weaver, and several students, and visits of Santiago Elena and Josep Quer) were pioneers in linking basic concepts of population genetics with viral evolution Some of the experiments marked the beginning of fitness assays and lethal mutagenesis, so important in current virology John was a great support to our work in Madrid in those times of incredulity of high mutation rates and quasispecies I miss his timely and encouraging comments enormously The visits to San Diego opened also links with the Scripps Research Institute at La Jolla, when Juan Carlos de la Torre joined Michael B A Oldstone department Each visit to Scripps is an important scientific stimulus, and the friendship and support of Juan Carlos and Michael remain unforgettable Acknowledgments xv The contact with Manfred Eigen began in a coincidental manner The Colombian physicist Antonio M Rodriguez Vargas invited several European and US scientists to participate in the first Latin American School of Biophysics held in Bogotá in 1984 Invited speakers included the members of Sol Spiegelman's team, Fred Kramer and Donald Mills, and Christof Biebricher from Göttingen This was the first time I met Christof, and our friendship lasted until his death in 2009 He introduced me to Manfred Eigen and I participated in several Max-Planck Winter Seminars that Manfred organizes at Klosters, Switzerland I will never forget the discussions with Christof on the theory-experiment interphase of quasispecies, at freezing temperatures combined with a hot soup at a mountain restaurant hut One of the years, John Drake, the pioneer of mutation rates joined us in extremely lively discussions At Klosters, I met Peter Schuster with whom I have kept contact since The discussions with Peter on quasispecies and error threshold have been extremely helpful and clarifying The Winter Seminars were a key in convincing me that our Madrid research was on the right track, and that I could survive giving a talk in front of Nobel Prize awardees which at the time I perceived as an achievement The trans-disciplinary flavor of the seminars at Klosters revived years later in Madrid when in the 1990s the physicist Juan Perez Mercader, at the suggestion of Federico Morán, invited me to join in the organization of a new center termed Centro de Astrobiología (CAB), in Torrejón de Ardoz, near Madrid Exciting discussions with many scientists conformed a new interest in the nascent science of Astrobiology with participation of noted scientists such as Andrés Moya, Ricard Solé, Federico Morán, Ricardo Amils, David Hochberg, Alvaro Giménez, Luis Vázquez, Ricardo García-Pelayo, Ramón Capote, and Francisco Anguita, among others The science at CAB opened several collaborations with Susanna Manrubia, Ester Lázaro, and Carlos Briones that continue today, with a monthly seminar with Francisco Montero, Cecilio López-Galíndez, and other colleagues as participants The view on viral populations that this book conveys had its origin in work with bacteriophage Qβ in the laboratory of Charles Weissmann in Zürich I firmly believe that despite the great recognition that Charles has had as a scientist due to many achievements in different fields, the early Qβ work that contributed the first site-directed mutagenesis protocols, the birth of reverse genetics, and the first evidence of high mutation rates and quasispecies dynamics, is still underappreciated Perhaps, as the noted molecular biologist and virologist Richard Jackson once put it, the work came 20 years too early Fundamental groundwork on the early genetics of bacteriophage Qβ was performed in Zürich by Martin Billeter, Hans Weber, Eric Bandle, Donna Sabo, Tadatsugu Taniguchi and Richard Flavell Years later, when Weissmann read Holland's 1982 paper in Science, he told me that a new field of research had begun I come back to the present The reason to name so many people in previous paragraphs is not to publicize a biosketch that will interest only my family (and minimally) The reason is that each of the persons, institutions, events, and encounters mentioned has had some influence in the contents of this book The idea of writing a book occurred to me years back when I produced a chapter for Fields Virology that I had to reduce by a factor of five to fit the required length Other incentives came from what would be usually considered inconsequential episodes For example, about 10 years ago, before a talk in France, one of the host scientists told me that he was eager to hear my “new” ideas about virus evolution, when I had been working on quasispecies for almost 30 years! Also, at a meeting on antiviral agents somebody told me that he was unable to select a resistant viral mutant, and he found a good idea my suggestion of increasing the viral population size in the serial passages These and a few other events reinforced in me the thought that perhaps a book could be of some use The book is intended to be an introduction to fundamental concepts related to the role that viral population numbers play in xvi Acknowledgments several features of virus biology Related aspects of a given concept are explained in different chapters This is why many boxes and cross-references among chapters are included In genetics language, I have aimed at complementation among chapters The specific examples (some of which attain a considerable degree of detail and are understandably biased toward my expertise) are just an excuse to illustrate general points Hopefully, the reader will be able to apply them to specific cases Before ending, I have additional names to thank for their support on different occasions At the risk of forgetting some names, they are Simon Wain-Hobson, Noel Tordo, Jean Louis Virelizier, Marco Vignuzzi, Carla Saleh, and other colleagues at Pasteur Institute in Paris, Rafael Nájera, Miguel Angel Martínez, Enrique Tabarés, Albert Bosch, Rosa Pintó, Raul Andino, Craig Cameron, Karla Kirkegaard, Olen Kew, Ernst Peterhans, Etienne Thiry, Paul-Pierre Pastoret, Francisco Rodriguez-Frias, Xavier Forns, Luis Menéndez-Arias, Vincent Soriano, Noemi Sevilla, Steven Tracy, David Rowlands, Louis M Mansky, Roberto Cattaneo, Stefan G Sarafianos, Kamalendra Singh, Alexander Plyusnin, Margarita Salas, Jesús Avila, Antonio García Bellido, Carlos López Otín, and Pedro García Barreno Also, my thanks go to board members of the Spanish Society of Virology and of the Royal Academy of Sciences of Spain Last but not least, colleagues and staff at CBMSO, and funding agencies, that have made our work possible My deepest appreciation goes to all Esteban Domingo Cantoblanco, Madrid, Summer 2015 For Iker, Laia, Héctor, Jorge From left to right Isabel Gallego, Ana Isabel de Avila, Celia Perales, and Esteban Domingo during a discussion of a figure for the book at Centro de Biología Molecular Severo Ochoa Photography by José Antonio Pérez Gracia CHAPTER INTRODUCTION TO VIRUS ORIGINS AND THEIR ROLE IN BIOLOGICAL EVOLUTION CHAPTER CONTENTS 1.1 Considerations on Biological Diversity 1.2 Some Questions of Current Virology and the Scope of This Book 1.3 The Staggering Ubiquity and Diversity of Viruses: Limited Morphotypes 1.4 Origin of Life: A Brief Historical Account and Current Views 1.4.1 Early Synthesis of Oligonucleotides: A Possible Ancestral Positive Selection 10 1.4.2 A Primitive RNA World .11 1.4.3 Life from Mistakes, Information from Noninformation: Origin of Replicons 13 1.4.4 Uptake of Energy and a Second Primitive Positive Selection 15 1.5 Theories of the Origins of Viruses .17 1.5.1 Viruses Are Remnants of Primeval Genetic Elements .18 1.5.2 Viruses Are the Result of Regressive Microbial Evolution 19 1.5.3 Viruses Are Liberated Autonomous Entities 20 1.5.4 Viruses Are Elements for Long-Term Coevolution 20 1.5.5 Viruses from Vesicles 21 1.6 Being Alive Versus Being Part of Life 22 1.7 Role of Viruses in the Evolution of the Biosphere 23 1.7.1 Current Exchanges of Genetic Material 24 1.7.2 Symbiotic Relationships .25 1.8 Virus and Disease 25 1.9 Overview and Concluding Remarks 26 References .27 ABBREVIATIONS AIDS APOBEC CCMV dsRNA E coli acquired immune deficiency syndrome apolipoprotein B mRNA editing complex cowpea chlorotic mottle virus double stranded RNA Escherichia coli Virus as Populations http://dx.doi.org/10.1016/B978-0-12-800837-9.00001-0 © 2016 Elsevier Inc All rights reserved Author Index Worobey, M., 61, 247–248 Wray, S.K., 317–318 Wright, C.F., 94 Wright, P.F., 207t Wright, S., 110, 175–176 Wright, S.G., 75 Wrin, T., 148, 203, 267 Wring, S., 304 Wu, C.C., 105, 106–108, 236–237 Wu, G.Y., 128 Wu, L.L., 237 Wu, N.C., 95 Wu, S., 95 Wu, Z., 139t Wyatt, C.A., 182 Wychowski, C., 146t ­X Xia, E., 94–95 Xia, G.L., 319 Xia, X., 246–247 Xie, X., 319–320, 322 Xie, Z., 246–247 Xing, L., 241 Xu, G., 146t Xu, L., 78 Xu, P., 25 Xu, Y., 353 Xue, W., 146t Xulvi-Brunet, R., 11 ­Y Yamada, A., 144–145 Yamada, Y.K., 146t Yamaguchi, T., 40–41 Yamanashi, H., 9–10 Yamashita, Y., 40–41 Yamshchikov, V.F., 312t, 315 Yan, M., 20 Yanagi, Y., 105, 106–108 Yang, D., 319–320 Yang, H., 140 Yang, L., 136 Yang, X.F., 146t Yang, Y.L., 285 Yang, Z., 43–44, 136, 243–247 Yansura, D.G., 240 Yarus, M., 12–14, 16, 19 Yeates, T.O., 146t Yee, J.K., 305 Yimen, M., 140 Yin, J., 91–92 Ying, T., 146t Yokosuka, O., 317–318 Yokoyama, S., 80, 237 Yoon, J.W., 139t Young, K.C., 319–320 Youngner, J.S., 108–109 Yu, H., 311–312 Yu, Q., 317–318 Yu, S., 232–233 Yuan, J., 282–283 Yunus, Z., 253 Yuste, E., 170–171, 178, 212, 270 Yvon, M., 58 ­Z Zaborsky, J., 59–61 Zagordi, O., 94–95 Zagorevski, D.V., 11 Zaher, H.S., 42 Zaia, J., 305 Zamb, T.J., 145t Zambrana-Torrelio, C.M., Zandomeni, R., 95 Zanghi, G., 305 Zanoli, S., 304 Zarate, S., 42, 200 Zelikovsky, A., 95 Zeng, J., 319–320, 322 Zeuzem, S., 283, 304 Zhang, B., 131 Zhang, C., 139t, 140 Zhang, E.Z., 105, 106–108, 288 Zhang, G., 42 Zhang, J., 79–80, 140, 305–308 Zhang, L., 126–127, 146t Zhang, N., 11 Zhang, X., 353 Zhang, Y., 317–318 Zhao, F., 146t Zhao, Q., 129, 173 Zhong, J., 175, 207t, 285–286 Zhong, W., 306–308, 311–312 Zhou, E.M., 146t Zhou, G., 319–320, 322 Zhou, S., 317–318 Zhou, X., 79–80 Zimmern, D., 61, 62, 248 Zinder, N.D., 85–86 Zondag, G.C., 144–145 Zoulim, F., 235 Zuidema, D., 186 Zylberberg, M., 95–96 397 Subject Index Note: Page numbers followed by f indicate figures, b indicate boxes, and t indicate tables ­A A3, 135, 305 Accumulation of mutations, kinetics, 323 Acquired immune deficiency syndrome (AIDS), 6, 59–61, 140, 186, 266, 269–270, 289–290, 291–292, 302–303 Acute respiratory syndrome (SARS CoV) cororavirus, 139t, 140, 230 Adaptability, 25, 48, 62–63, 99, 101, 102, 102b, 125, 130, 155, 211–212, 228–229, 270, 288–289, 290, 291, 292, 320, 321–322, 340, 341f, 344–345, 346–347, 356 Adaptive pathways, 102, 303 Adenosine deaminase acting on double stranded RNA (ADAR), 25, 52–53 Adenosine deaminase acting on double-stranded RNA (ADAR), 52–53, 327–328 Adenoviruses, 140 Advantage of the flattest, 187–188, 190, 306, 311 Agriculture, 265 AIDS See Acquired immune deficiency syndrome (AIDS) Airborne transmission, 202 All things in moderation hypothesis, 108–109 2-(Alpha-hydroxybenzyl)-benzimidazole, 269–270 Alphavirus, 61, 186 Amantadine, 273f, 284t, 305 Ambiguous pairing, 311–312 Amino acid substitutions, 41–42, 43, 44, 48, 52, 57–58, 62–63, 81, 82, 83, 98, 105–108, 133, 134, 137–138, 139, 139t, 140–143, 141f, 142f, 143f, 145–147, 148–149, 149f, 151–152, 155, 188, 202, 207t, 208, 213–214, 218, 238–239, 240, 241, 242, 246, 248–249, 251, 267, 275–276, 277, 280–281, 282–283, 285–286, 304, 320, 321, 322–323 Antibiotic resistance, 264, 340, 342, 343b, 344 Antibiotics, 264, 340, 342, 344, 356 Antibody binding, 144–145, 146t, 241 neutralizing, 97–98, 133, 144, 146t, 148, 218, 240, 251, 283–284, 305, 329 nonneutralizing, 240 Antibody escape, 79–80, 111, 112–113, 133, 134, 145–147, 148, 242, 267, 283–284 Anticancer therapy, 316 Anti conformation, 37–38 Antigenic diversification, 238–242, 243f, 249f, 256 Antigenic diversity, 239, 240, 242, 267 Antigenic drift, 58, 59–61, 238 Antigenicity-cell tropism coevolution, 145–147 Antigenic shift, 58, 63, 189–190, 203, 238, 266 Antigenic site, 110, 144, 145–147, 145t, 146t, 148–149, 149f, 155, 203, 218, 238–239, 238f, 240, 241, 242, 268 Antigenic stability, 132–133, 239, 242, 267 Antigenic variation, immune selection, 148–149 Antisense nucleic acids, 290 Antiviral activity, broadness, 328 Antiviral agents, 52, 61, 62, 91, 134–135, 137–138, 140, 264, 265–266, 269–270, 271, 272, 278, 283–284, 285–286, 289–290, 291, 291b, 292, 293, 304, 308, 317–318, 327, 329, 340, 342, 343t Antiviral interventions, 88, 134–135, 288–289, 292, 302, 317 Antiviral resistance, 264, 288, 340, 342 disease progression, 288–289 fitness/fitness-associated trait, 285–289 to inhibitors, 269–281 barriers to drug resistance, 275–276 drug efficacy, mutant frequencies, and selection of escape mutants, 277–280 drug-escape mutants, 270 multiple pathways and evolutionary history, 281 phenotypic barrier and selective strength, 280–281 replicative load and antiviral resistance, 271–272 limitations, simplified reagents and small molecules, 289–290 molecular mechanisms, 282–284 viral load, 288–289 without prior exposure to antiviral agents, 285 Antiviral strategies advantages and limitations, 327b atypical proposals, 328 challenges of, 300–302 combination treatments, 302–303 host innate immune system stimulation, 305 immunotherapy and chemotherapy, 305 inhibitors vs mutagenic agents, 324–326 lethal mutagenesis, 327–328 and error threshold, 305–311 in vivo, 317–319 by mutagenic agents, 311–317 mutagenic nucleotide analogs, 316–317 polymerase fidelity and modulation, nucleotide incorporation, 321–323 substitutions, unpredictable effects, 321 split treatments, 303–304 targeting cellular functions, 304 theory and experiment reconciliation, 306–311 399 400 Subject Index Antiviral treatments, 98, 105, 110, 175, 183–184, 190, 302, 303–304, 327b Antiviral vaccines and adaptive potential of viruses, 266–269 design, 266–268, 267b vaccination-induced evolution, 268–269 Aphids, 128–129, 153 APOBEC, 23, 25, 52–53, 327–328 activities, 52–53 APOBEC3G, 316 proteins, 25 Arboviruses, 129, 143, 153, 154f, 155, 200, 210–211, 253–254 Archetypal proteins, 20–21 Arenaviruses, 58, 152 Astrobiology, 14, 16 Autotrophy, 15 Avian bornaviruses (ABVs), 127 Avian H5N1 IV, 202 5-AZA-C resistance, 322–323 5-Azacytidine, 311–312t ­B Baby hamster kidney (BHK-21) cells, 59, 60f, 140–142, 173–174, 206–208 fitness, 173–174, 177 Bacteria, experimental populations, 46 Bacterial adaptive mechanisms, 342 Bacterial biofilms, 344 Bacterial virulence, 344 Bacteriophage, 6–7, 18, 24, 25, 46, 56, 62, 85–86, 125, 204, 248, 344 Bacteriophage ϕ29, 49, 54 Bacteriophage ϕX174, 322–323 Bacteriophage φ6, 199–200, 209–210, 212 Bacteriophage Qβ, 6–7, 10, 49, 84–86, 90–91, 94–95, 126, 189, 204, 315, 322–323 Bacteriophage T7, 6–7, 8f Barriers to drug resistance, 275–276, 275b Base-base interactions, 38 Base, electronic structure, 37 Bayesian methods, 244t, 247 Bequinar, 305 Biodiversity, Biological clone, 45, 59, 78, 79–80, 81, 90–92, 93f, 103, 105, 106, 140–142, 142f, 152, 173–174, 180–182, 186, 199f, 201f, 203–205, 213–214, 218, 286, 319f, 349–350 Biological species, number, 125–126 Biosphere, 3, 3b, 4, 7, 17f, 22, 23–26, 58, 80, 83, 94, 124–125, 209, 228–229, 248, 281 Bipartite genome, 59 BLOSUM matrices, 246 Bluetongue virus, 146t, 151 Borna disease virus (BDV), 127–130 Bottleneck event, 21–22, 99–101, 127–130, 129f, 153, 154–155, 178, 179f, 186, 200, 205, 231, 286 consequences, 80, 106, 129f fitness, 211f, 212 population, 87, 128, 131f, 183, 348 Bottleneck, population, 80, 81, 111, 128–129, 128f, 131f, 151, 154–155, 181f, 183, 209–210 Bovine spongiform encephalopathy, 347–348 Bovine viral diarrhea virus, 24, 62, 95, 146t Broad spectrum antiviral agents, 148, 312t, 319, 329 ­C Cancer dynamics, 345–347 Cancer metastasis, 345, 356 Canyon hypothesis, 241 Cardiovirulent coxsackievirus B (CVB), 140, 185, 186 Carrier cell cultures, 127 Catalysis, 11, 51f Catalytic efficiency, 50–52, 82, 283 Catalytic RNA, 11, 12–14 C-cluster coxsackie A virus, 251 CCR5, 140, 304 CCR5-binding inhibitors, 304 Cell-dependent constraints, 132–134 Cell dynamics, 143 Cell transformation, 208 Cell tropism, 20, 91, 111, 138–144, 139t, 142f, 155, 268, 269 Cell tropism and host range of viruses, 142–144, 268 Cellular differentiation, 24 Cellular genomes, 102, 182 Cellular parasites, 344–345, 350, 356–357 Chemical space, 99 Chemotherapy, 265, 300, 303, 305 Chikungunya virus, 153 Chilarity, 12 Chinese hamster ovary (CHO) cells, 177 Chromosomal instability, 49–50 Chronic wasting disease, 347–348 Circovirus, 25–26 cis-acting element, 53–54 Clock hypothesis, 232–233, 237–238, 255 Clonal evolution, 213, 346, 349, 350, 352f Clonal expansion, 80, 232, 349–350 Clonality in virus evolution, 351b Cloning biological, 88f, 91–92, 93f, 104, 286, 349–350 molecular, 3, 53, 93f, 103–104, 205, 286 c-mos, 80, 237 Codon bias, 42, 53, 135 pairs, 42, 135–138, 155, 268 quasisynonymous, 44 Subject Index rare, 42, 136 synonymous, 42, 135–136, 137–138, 137f, 275–276 usage, 135–138 Coevolution, 12–13, 20–21, 25–26, 124–125, 134, 144–147, 148–149, 155, 203, 205–209, 219, 229, 248, 281 Coevolution, trait, 144–147 Coinfection, 7, 26, 57–58, 110, 174–175, 350–351 Cold spot, 62 Collective dominant-negative mutant, 108–109 Collective population effects, nonviral systems antiviral and antibiotic resistance, 342 cancer dynamics, 345–347 collective behavior of prions, 347–349 concept generalization, 339–340 Darwinian principles and intrapopulation interactions, 343–344 genome size-mutation-time, 340–342 heterogeneity and group behavior, 345–347 two-component theory of cancer, 346–347 unicellular parasites, parasitic disease control, 344–345 variation and clonality in evolution, 349–351 virus vulnerability, 354–356 Colonization-adaptation trade-off (CAT) model, 236, 237 Combination therapy, 302–303, 305 Combined immunotherapeutic approaches, 305 Compartmentalization, 13–14, 15, 21, 24, 126, 138, 172, 271f, 326 Competition, 25, 47, 61, 75, 76–77, 78, 79f, 82, 90, 105–106, 108–109, 110, 114, 170–171, 172–174, 178, 180, 190, 204–205, 214, 216–217, 218, 220, 231f, 237, 254, 286, 339–340, 343, 346, 348, 356 Competition-colonization dynamics, 215–216 Competitive exclusion principle, 180, 205, 216–218, 217f, 219, 220 Complementation, 57, 59, 60f, 77, 82, 98–99, 104–111, 105b, 107f, 114, 137–138, 173, 346 Complement fixation, 240–241 Complex adaptive systems, 77, 180, 346, 351–353 Complex environment, 149, 150–151, 288–289 Complexity, 4, 5f, 10, 16, 18, 27, 49, 50, 77, 91–96, 92b, 98, 99, 103–104, 111–113, 131f, 149, 150f, 177–178, 218, 229, 250f, 255, 256, 290, 292, 310, 318, 319, 320, 345, 351, 357 population, 111, 112 threshold, 10 Computer-assisted design, 99 Computer simulation, 14, 104–105 Conformation heterogeneity, 348 Conformation space, 99 Conjoined RNA, 18–19 Constraint, basal, 131, 132, 155 Contingency in evolution, 208–209 401 Contingent neutrality, 213, 218, 219, 220 Copy choice, 56 Copying fidelity, 12, 46–47, 48, 49–50, 52, 84, 91–94, 98, 150–151, 310f, 320, 340 Coreceptor, 138, 139, 140, 304 Core information, 62–63, 112, 131, 346–347 Coronaviruses, 6, 49, 57 Coronavirus, 3'-5' exonuclease, 49 Coronavirus nonstructural protein 10, 322–323 Covalently closed circular DNA (cccDNA), 235–237 Coxsackievirus A9, 284t Coxsackievirus and adenovirus receptor (CAR), 140 Coxsackievirus B3 (CVB3), 61, 188 Creutzfeldt-Jakob disease, 347–348 Cross-neutralization, 240–241 Cucumber mosaic virus, 128–129 CXCR4, 140, 304 Cyclophilin inhibitor SCY-635, 304 Cytolytic infection, 10, 143, 199–200, 206–208, 213–214 Cytomegaloviruses, 201–202 Cytopathology, 25–26, 151–152, 186, 198, 208 Cytotoxic concentration 50 (CC50), 277, 277f, 278, 328 Cytotoxic T lymphocyte (CTL)-escape mutants, 235, 267, 268 Cytotoxic T lymphocytes, 81, 95, 106–108, 111, 148, 155, 235 ­D Darwinian positive selection, 11 Darwinian principles, 4, 143–144, 178, 300, 339–340, 346, 357 competition, 78 genetic variation, 78 and intrapopulation interactions, 343–344 mutant distributions, DNA and RNA virus infections, 79–81 positive vs negative selection, 81–83 random drift, 83–84 selection, 78, 83–84 viral quasispecies, 84–99 Data banks, 77, 95, 113–114, 243–246, 244t DD264, 135, 305 Decay accelerating factor (DAF), 140 Defective genomes, 36–37, 61, 82, 105–106, 137–138, 308, 311, 318, 322, 323 Defective interfering (DI) particles, 24, 82, 106, 204–205 Defective-interfering RNAs (DI RNAs), 52, 56, 61, 62 Defense mechanism, 23–24, 25, 52, 147 Dengue virus, 146t, 153, 251 Deterministic model, 86–87 DI particles See Defective interfering (DI) particles Disease emergence, 11, 24, 113, 125–126, 185, 291–292, 304 Disease emergence, steps, 252 Disease progression, 4, 183, 201–202, 230, 288–289, 289f, 293 Disease, symptoms, 61 Diversity, biosphere, 402 Subject Index DNA damage, 14, 346 metabolism, 305 mutations in, 40f repair, 46–47 viruses, 4–5, 6, 50 virus evolution rate in nature, 232–238 DNA-dependent DNA polymerase, 6, 248 dn, nonsynonymous substitutions, 43–44 Domestication, 228–229 Dominant-negative effect, 105–106 Double stranded DNA (dsDNA), 5–6, 49, 56, 135, 232t Double stranded RNA (dsRNA), 5–6, 25, 58, 209–210, 240, 327–328 3D PCR, 104 Drake’s rule, 46 Droshophila melanogaster, 2, 182 Drug-escape mutants, 270, 275–276, 283–284, 284t Drug holidays, 290–291 Drug repositioning/drug repurposing, 316–317, 328 Drug resistance, 50, 61, 89f, 95, 111, 172, 175, 244t, 268, 270, 271, 272, 275–276, 275b, 277, 279, 280–281, 283, 285–286, 288, 300–301, 344–345 Drug, selectivity, 134–135, 270 ds, synonymous substitutions, 43–44 Dual infection, 26 Dual-tropic viruses, 304 ­E Earth, primitive, 9–10, 21 Eastern equine encephalitis-like virus, 61 Ebola, 24, 94, 147, 184, 230, 254, 291–292 Echovirus, 25–26 Economo’s disease, 249–251 Effective population size (Ne), 127–130 Electronic structure, and base pairing, 62 Emergent virus, 81–82 Encephalomyocarditis virus (EMCV), 108–109, 239 Endogenous hepadnaviruses, 237 Endogenous hepatitis B viruses (eHBVs), 24 Enterovirus, 61, 233–234, 269–270 Enzyme-linked immunosorbent assay (ELISA) tests, 240 Epidemiological fitness, 24, 184, 189–190, 231f, 252 Epigenetic, 89–90, 346 Epigenetic modifications, 345 Epistasis, 43, 54, 177–178, 272 Epistatic effects, 204, 272 Epitopes continuous, 145–147, 240, 242t discontinuous, 145–147, 240, 242, 242t overlapping, 240 Equine infectious anemia virus (EIAV), 95, 142–143 Error catastrophe, 25, 91, 99–101, 172, 177, 306, 307f, 312t, 327–328 Error catastrophe, in cancer, 346 Error correction, 49, 54 Error-prone replication, 6–7, 14–15, 36–63, 83, 84–85, 104–105, 113, 126–127, 237, 312t, 339–340, 349–350 Error rate, 6–7, 13–14, 46, 48, 49, 50–52, 92–94, 102, 232–233, 240, 305–306, 346 Error threshold, 49, 91, 106, 108, 305–311, 329, 340, 354, 356 Error threshold, in cancer, 346, 347f, 357 Escape, 42, 47, 147–148, 319–323 Escape mutant(s), 23–24, 47, 134–135, 180, 242, 277–280, 283–284 Escape mutant frequencies, 283–284 Escherichia coli, 2, 10, 24, 46, 49, 51f, 85–86, 90–91, 92–94, 93f, 204 Eukaryotic cell nucleus, formation, 24 European Academies Science Advisory Council, 264, 342 Evasion, 112, 147, 148, 155, 300–301, 344–345 Evolution defined, as a deterministic process, 86 prebiotic, 9–10 regressive, 19, 20 Evolutionary events, stochasticity, 209–210 Evolutionary models, 246–248 Evolutionary rates, time dependence, 236–237 Evolutionary stasis, 80, 127, 237 Evolutionary trace (ET) clustering method, 248 Evolutionary trajectory, 186 Evolvability, 13–15, 48–52 Experimental evolution, 85f, 125, 178, 180, 198, 199f, 202–203, 209, 212, 214, 215, 218, 219, 220, 231 Extinction mass, 21–22, 27, 83 threshold, 288–289, 306, 320, 324 viral, 21–22, 172, 305–306, 308, 308b, 324, 325f ­F Faba bean necrotic stunt virus, 58 Fatal familial insomnia, 347–348 Favipiravir, 311–312, 312t, 314f, 317, 319, 328 Fidelity mutants, 48–52, 98, 106–108, 188, 313–315 Fidelity, template copying, 46–47, 48, 50–52, 62–63, 84–85, 151, 320, 321, 322–323, 345–346 Fitness cost, 147–148, 275, 276, 280–281, 280f, 283, 284 definition, 170 dissection, determinants of, 173–174 epidemiological, 189–190 and function, 189 Subject Index gain, 59, 81–82, 175, 178, 180, 183, 184, 190, 210, 215–216, 288–289, 350 gain and loss, population dynamics, 215–216 landscapes, 89, 91, 133, 175–178, 187–188, 190, 218, 305–306 survival, 187–188 limitations, 172–173 measurement, 170–171, 172–173 as a multidrug resistance determinant, 285–288 origin of concept, 170–174 population factors, 178–180 power, 172–173 quasispecies memory implications, 183–184 and recovery, 180–184 ruggedness justification, 177–178 vector, 170–171, 171f, 280–281, 280f in vivo challenge, 174–175 vs virulence, 184–187 Fitness enhancing mutations, 186–187, 242, 320, 321–322 Flaviviridae, 24 Flaviviruses, 24, 153, 206 5-Fluorouracil [5-Fluoro-1H,3H-pyrimidine-2,4-dione (FU)], 308 5-Fluorouridine-triphosphate (FUTP), 318 Foot-and-mouth disease (FMD), 233–234, 266 Foot-and-mouth disease virus (FMDV), 6, 36–37, 59, 95, 125, 139t, 144, 172, 173–174, 177, 203, 206–208, 213, 214b, 233, 242t, 251, 265, 308–310, 312t antigenic diversification, 238–239 experimental evolution in vivo, 203 fitness, 189–190 fitness in vivo, 174–175 lethal mutagenesis, 308–310 long-distance transport, 233–234 quasispecies memory, 180 serological assay, 240–241 virulence, fitness, 186 virus evolution, 235 Foot-and-mouth disease virus (FMDV), long-distance transport, 233–234 Founder event, 130 Founder genome, 80, 128–129, 201f Functional diversification, 15, 20, 23 ­G Geminiviruses, 79–80 Genetic barrier to resistance, 275–276, 282–283 to reversion, 53 Genetic bottleneck, 4, 149f, 269, 349–350 403 Genetic code, 12–13, 18–19, 41–42, 53, 135–136, 137f, 246, 277 Genetic distance, 80, 91–92, 95, 112, 232, 243–246, 247 Genetic flow, 23 Genetic heterogeneity, 47, 95–96, 101, 129, 203, 231, 343, 345 Genetic information, 6, 7, 11, 17, 18, 21, 24, 49, 53–54, 63, 81–82, 99–101, 108, 111–112, 305–306, 307f, 310f, 346–347, 354, 357 Genetic optimization algorithms, 133 Genetic variation, 2–3, 6, 7, 12, 23–24, 36–63, 75, 78, 90, 134–135, 147, 170, 178, 201f, 251–252, 255, 304, 339–340, 343, 346, 349, 356 requirement for, 36–37 Gene transfer, 23–24, 342 Gene transfer, horizontal, 62 Genome bipartite, 5f, 59 complexity, 5f, 36, 50 defective, 36–37, 61, 82, 105–106, 137–138, 308, 311, 318, 322, 323 flexibility, 59 formula, 58 instability, 345–346 minority, 57, 97–98, 104, 182, 209–210, 286 rearrangements, 201–202, 342, 349 size, 25–26, 47, 49, 80, 102, 147, 340–341, 342 Genome segmentation, FMDV, 59, 60f, 215–216 Genome segment reassortment, 36–37, 55f, 58, 63, 78, 238, 266, 302 Genome size-mutation-time, 340–342, 344 Gerstmann-Sträussler-Scheinker disease, 347–348 Global action, 291–292 Group B coxsackieviruses (CVB), 140 Growth-competition experiments, 170, 172, 173 GTP depletion, 318 Guanidine hydrochloride, 151–152, 269–270, 325f Guanosine-5´-triphosphate (GTP), 317–318 Guillain-Barré syndrome, 231 ­H Haldane’s dilemma, 179–180 Hantavirus, 248 Harbinger mutations, 183–184 Hardy-Weinberg law, 87 Hepadnaviruses, endogenous, 237 Hepatitis A virus (HAV), 95, 136, 239, 242t, 265 Hepatitis B virus (HBV), 6, 52, 106–108, 125, 145t, 235, 268–269 Hepatitis C virus (HCV), 6, 26, 125, 239 drug resistance, 276 fitness in vivo, 174–175 Hepatitis delta virus (HDV), 18, 19 404 Subject Index Herpes simplex, 56, 80, 139t, 140, 145t, 207t, 232, 242t Herpesviruses, 6–7, 25–26, 206, 248, 270 Heterogeneity, 27, 80, 81, 178–180, 345–347 Heterogeneity and group behavior, 345–347 Heterotrophy, 15 Highly active anti-cancer treatments, 347 Highly active antiretroviral therapy (HAART), 302–303 HIV-1 See Human immunodeficiency virus type (HIV-1) HIV-1 groups, 248–249 HIV-1, life span, 126–127 H1N1 viruses, 189–190, 312t H3N1 viruses, 189–190 Homo habilis, 341 Homologous genes, 41–42, 75 Homopolymeric tract, 40–41, 41f, 45 Homo sapiens, Horizontal transmission, 228, 255 Host cell tropism and host range modifications, 138–144, 142f Host factor, 85–86, 85f, 108–109, 132, 151–153 Host organisms constraints, 134–135 Host specificity, 140 Hot spot, 40–41, 44–45, 47, 62, 80, 213, 240 Human genome, 23, 42, 47, 49–50, 341 Human immunodeficiency virus type (HIV-1), 2, 6, 23, 61, 94, 125, 126–127, 140, 172, 182, 200, 203, 230, 235, 267, 282–283, 288, 302–303, 312t, 350 antiviral resistance, 282–283 combination therapy, 302–303 experimental evolution in vivo, 203 highly active antiretroviral therapy (HAART), 302–303 inhibitors, 274f quasispecies memory, 182 recombinants, 350 reproductive ratio, 230 virus evolution, 235 Human rhinovirus 14 (HRV14), 146t, 241, 284t Human rhinoviruses (HRVs), 146t, 239 Human T-cell lymphotropic virus, 80, 232, 349–350 Human T-lymphotropic virus types and (HTLV-1 and HTLV-2), 80 Hydrogen bond, 37, 39f, 145–147, 313f, 314f 5-Hydroxydeoxycytidine (5-OH-dC), 305–306 Hypercube, 99–101 Hypermutagenesis, 52–53 Hypermutation biased, 52 somatic, 49–50 ­I IBRS-2 cells, 206–208 Immune response, 147, 148, 268, 288 Immune response, innate, 25, 124–125, 135, 305, 328 Immune surveillance, 147, 205–206 Immunocompromised individuals, 185, 201–202, 253 Immunosuppression, 140, 268–269 Immunotherapy, 264–265, 289–290, 300, 302, 303, 305 Indels, 40–41, 40f, 53–54, 61, 94–95 Infection synapses, 19 Infectious cell, 19 Influenza pandemic, 24, 58, 202, 228, 255 Influenza viruses (IV), 6, 112, 188, 202, 305 avian, 202 experimental evolution, 202 inhibitors, 273f type A, 125 type C, 61, 233 Information core, 62–63, 112, 131, 346–347 inheritable, 11, 13–14, 15 Information theory, 86, 99, 339–340, 357 Inhibitor-mutagen treatments, 317, 327, 329 Inhibitor-resistant mutants, 134–135, 271–272, 271f, 278, 278f, 291, 304, 324–326 Inhibitors, antiviral, 81, 110, 134–135, 137–138, 149, 265, 269–281, 282–283, 290, 302–305, 324–326, 328 Inhibitors vs mutagenic agents, antiviral strategies, 324–326 Inhibitory concentration 50 (IC50), 277, 277f, 278, 328 Innate immune response, 25, 124–125, 135, 305, 328 Innate immune system, 303, 305 Innate viral self, 20 Inosine, 39f, 52–53 Insect-mammalian infection cycles, 153 Insertion element, 46, 342 Integrin, 133, 144 Integrin receptors, 133, 144 Interference, 104–111, 114, 173, 276, 308–311 Interfering activity, collective, 105–106 Interfering interactions, 98–99, 108–109, 276, 308 Interfering mutant, 105–106, 326 Interhost rates of evolution, 235–237 Interhost vs intrahost rate of evolution, 235–237 Internal ribosome entry site (IRES), 38, 132, 213 International Committee on Taxonomy of Viruses (ICTV), 4–5, 243, 246 Intrahost diversity, Intrahost evolution, 43, 97, 236f Intrahost rates of evolution, 235–237 Iridoviruses, 6–7, 244t Irradiation, ultraviolet, 9–10 ­J Japanese encephalitis virus (JEV), 154f Joker substitutions, 151–153, 208 Subject Index ­K 405 KP1461, in lethal mutagenesis, 317 K strategists, 126 Lymphocytic choriomeningitis virus (LCMV), 26, 105, 140, 188, 305, 308, 312t, 317, 326 Lymphotropic minute virus of mice, 206, 207t ­L ­M Lamarckism, 75 Latency, 80, 232 Latent infection, 127 Latent reservoir, 7, 127, 349–350 Lateral gene transfers, 20, 23, 213 Lazarus effect, 101 Leishmania, 344–345 Lentiviruses, 23, 140, 142–143, 288 Lethal defection, 82, 308–310, 310f, 311, 324–326 Lethal mutagenesis, 49, 91, 327–328 advantages and limitations, 327b and coronavirus, 49 and error threshold, 305–311 studies on, 312t theoretical models, 99–101, 306, 311, 329 in vivo, 317–319 Life defined, 22–23 origin, 7, 8–16, 17–18, 26–27, 340 spontaneous generation, Linkage disequilibrium, 349, 350 Lipid bilayer, 15 Lipid membrane, 21 Live-attenuated vaccine, 185, 269 Liver fibrosis, 26 Living matter, 13–14 Long-term coevolution, 20–21, 124–125, 134, 144 Long terminal repeat (LTR), 142–143, 353 Long terminal repeat (LTR) retroelements of eukaryotes, 353 Long-term virus evolution, 213, 269 antigenic diversification, 238–242 complexity revisited, 255 extinction, 248–255 interhost vs intrahost rate of evolution, 235–237 microbial disease, 252b monoclonal antibody-escape mutants, 242 mutant cloud, 248–255 phylogenetic relationships, 246–248 rate discrepancies and clock hypothesis, 237–238 reproductive ratio, 229–231 serotypes, 239–241 survival, 248–255 time of sampling influence, 233–235 viral emergence, 251–254 virus evolution rate in nature, 232–238 vs viral genomes, 243–246 Luxury functions, 26 Mass extinction, 21–22, 27, 83 Master genome, 89–91, 179–180 Master sequence, 89, 90, 104–105, 212, 305–306, 307f, 311, 354, 355f Maximum likelihood (ML), virus evolution, 232–233, 247 Maximum parsimony, 247 Mean pairwise diversity, 246 Measles virus (MV), 52, 105, 106–108, 127, 139t, 230, 242t Mechanical transmission, 153 Medical interventions, 264–265, 292, 293, 327–328, 340 Megavirus, Membrane, 6, 15, 21, 27, 46, 132, 133–134, 138, 151–152 Memory, 99, 180–184, 216–217 Memory, molecular, 99, 180, 182, 184, 190, 235, 351–353 Mendelian genetics, 75 Messenger RNAs (mRNAs), 6, 37, 38, 42 Metabolism, 15, 26–27, 305 Microbial evolution, 4, 19, 21, 75–76, 356–357 Micro-RNA (miRNA), 20–21, 42, 201–202 Middle East respiratory syndrome coronavirus (MERS), 146t, 291–292 Miller’s approach, 9–10 Mimiviruses, 6–7 Mineral(s), 10–11 Mineral-organic complexes, 10–11 miRNA See Micro-RNA (miRNA) Misincorporation, 6, 37, 44–45, 46, 49, 50–52, 53, 91–92, 135, 188, 275–276, 311–312, 312t Mobile genetic element, 23 Modern synthesis, 75, 77 Modulation, 104–105, 110, 147, 152, 155, 205–206, 321–323 Module archetypal, 20–21 functional, 18–19, 20, 132 Molecular basis of fitness decrease, 213–215 of mutation, 37–40 Molecular clock, 232–233, 237, 247, 255 Molecular clone, 78, 91–95, 180–182, 189 Monoclonal antibody (MAb), 47, 110, 111, 144–145, 146t, 170–171, 180, 218, 227, 240, 344–345 Monoclonal antibody-resistant mutants (MARMs), 82, 242, 242t Monotherapy, 289–290, 302–303, 318, 319–320, 324–326, 347 Morphotype, 4–7, 239, 248 Mosaic genomes, 36–37, 56, 350–351 Mosquito vector, 153 406 Subject Index Mother-to-infant transmission, 237 Mouse hepatitis virus (MHV), 61, 207t Muller’s ratchet, 180, 205, 209–210, 212–213, 215, 219, 220, 349 Muller’s ratchet and advantage of sex, 212–213 Multicomponent antiviral state, 148 Multidrug-resistance, 282, 285–288, 344–345, 346 Multiepitopic vaccines, 268, 302 Multifactorial antiviral responses, 135, 305 Multifunctionality, 20–21, 109, 111–112, 147, 148, 151–153, 155, 322 Multipartite virus, 58 Multiplicity of infection (MOI), 110, 172–173, 199–200, 277 Mutagen escape, 321–322, 327 Mutagenesis, 37–38, 86–87 as a dynamic process, 323 enhanced, 61, 151–152, 188, 218, 306, 310f, 312t, 324 hypermutagenesis, 52–53 lethal, 91 misalignment, 40–41, 41f, 46, 180–182 nucleotide analogs, 316–317 Mutagenic nucleotide analogs, 315, 316–317, 328 Mutagenic nucleotide analogs, resistance to, 52, 313–315, 319–320, 320b Mutagenic PCR, 53 Mutant frequency, 92b quasispecies distributions in, 103t spectra, 89–91 spectra, modulating effects, 104–111 Mutant cloud, 43, 86, 99–101, 108, 109, 173, 175–176, 211–212, 216–217, 218, 246–247, 248–255, 300–301, 302, 340–341, 354 Mutant, distribution, 13–14, 79–81, 84, 86, 87, 88f, 89, 90, 103, 103t, 113–114, 126, 140, 148–149, 150f, 204, 306, 307f, 354–356, 355f Mutant spectra/spectrum collective behavior, 105b complexity, 48–49, 80, 92b, 95–96, 98, 99, 102–103, 246, 250f, 293, 308, 318, 319, 320, 321–322 expansion, 309f extrinsic properties, 200 implication, 201f modulating effects, 104–111 negative effects, 109 and neuropathology, 48–49 Mutation in coding regions, 43 compensatory, 53–54, 132, 151–152, 175, 177–178, 214–215, 220, 242, 243f, 268, 275, 276, 280–281 complexity, 149–151 consequences, 48–52 context dependence, 43 deleterious, 58–59, 61, 77, 82, 106–108, 178, 215, 354–356 DNA and RNA frequencies for, 44–48 genomes, 44–48 rates, 44–48 recombination, viruses, 54–58 effects of, 40–43, 43b error-prone replication and maintenance, genetic information, 53–54 evolutionary origins, 48–52 evolution drawn from, 43–44 evolvability, 48–52 frequencies, 45f, 47 functional effects, 43 hitchhiking, 81, 148–149 hypermutagenesis, 52–53 interactions, 38 molecular basis of, 37–40 molecular occurrence vs observed recombination, 56–58 neutral, 41–42, 43, 46, 133, 237–238 in noncoding regions, 43 quasi neutral, 41–42, 83 rate, 149–151 recombination and segment reassortment, 59–62 site and functional barrier, 283 synonymous, 38–40, 41–42, 44, 46, 98, 132, 135, 155, 238–239 transition, 41 transition vs transversion, 43 types, 40–43 Mutational bias, 44, 135, 318 Mutational hot spot, 44–45 Mutational load, 46, 179–180, 218, 302, 308–310, 318, 323–324, 353, 357 Mutation frequency, 44–45, 47, 63, 112–113, 211–212, 285, 312t Mutation rate, 44–52, 76–77, 90–91, 149–151, 345 Mutator bacteria, 343 Mutual information criterion (MIC), 144 Mycobacterium tuberculosis, 264 Mycovirus, 25 Myxococcus xanthus, 46 ­N Nanovirus, 58, 153 Natural selection, 2, 4, 16, 27, 74, 75, 78, 83, 132, 170, 340 Ne See Effective population size (Ne) Near-clades, 349, 350–351 Negative selection, 43–44, 45, 57, 81–83, 106–108, 131, 135, 180–182, 214, 350, 351 Neighbor joining (NJ), 247 Subject Index Network connectivity, 339–340 Neurodegeneration, 347–348 Neutral theory, 41–42, 83 Next generation sequencing (NGS), 2, 57, 81, 94, 129, 170–171, 177–178, 184, 202, 203–204, 249, 265–266, 318, 340 application, 129 HCV analyses, 318 influenza virus screening, 202 mutant spectrum, 249 poliovirus (PV) populations, 203–204 Noncoding control region (NCCR), 201–202 Noncytopathic coxsackievirus B3 (CVB3), 61, 188 Non-Darwinian evolution, 83 Nonhomologous recombination, 24, 55, 62, 188 Nonlinear rates of evolution, 236b Nonnucleotide RT inhibitors (NNRTIs), 282 Non-Watson-Crick base pairs, 37–38, 39f Norovirus, 139t, 317 Nuclear localization signal (NLS), 91, 152, 322 Nucleic acid polymerase, structure, 50, 51f Nucleoprotein (NP), arenaviruses, 152 Nucleoside analogs, 37–38, 104, 175–176, 272, 311–312, 312t, 320 Nucleoside inhibitor, 40–41 Nucleoside/nucleotide reverse transcriptase (RT) inhibitors (NRTIs), 282 Nucleotide discrimination, 41, 48 Nucleotide incorporation kinetic constant, 50–52 modulation, 321–323 Nucleotide misincorporation, 37 See also Mutation ­O Off-target effects, 133–134, 290, 305, 327, 328 Oligonucleotides synthesis, 10–11 Oral poliovirus vaccine (OPV) viruses, 61 Origin of viruses, 2–7, 8–16, 17–27 Orthomyxovirus, 58 Overlapping genes, 133, 152–153 Overt lethality, 308–310, 310f, 311 Oxygen radical, 37, 132 ­P Pandemic, 24, 58, 59–61, 186, 202, 228–229, 230, 232, 241, 248, 249–251, 252, 255, 289–290 Pandoravirus, Pan-genome, in bacteria, 346–347 Panmictic population, 87 Panspermia, 14–15 Papilloma virus, 6, 8f, 112 Paramyxovirinae, 40–41, 327–328 407 Parasitic behavior, 21 Partition analysis of quasispecies (PAQ), 95, 97f, 319f Parvovirus, 79–80, 139t, 140, 141f, 206 Patchy environments, 210–211 Pathogenesis, 97, 98, 113, 143, 202, 288 PCR, error-prone, 53 Pea seed-borne mosaic virus, 128–129 Pegylated IFN-α, 317–318 Percent accepted mutation (PAM), 246 Persistence, 57–58, 61, 98, 147–148, 198, 203, 206, 207t Persistence, long-term, 61 Persistent infection, 26, 61, 85f, 127, 143, 198, 199f, 203, 205–209, 214, 219, 228–229, 265, 291 Persistent infectious, steady-state, 127 Personalized treatments, 291 Phenotypic barrier, 148, 268, 275, 276, 280–281, 303–304, 305 Phenotypic barrier and selective strength, 280–281 Phenotypic hiding-mixing, 47 Phenotypic variant, 98 Phosphodiester bond, 11, 38f, 39f Phylogenetic analysis, 182, 251 Phylogenetic position, 7, 98, 139, 247–248 Phylogenetic tree, 57, 75, 246–247, 248–249, 256 Phylogetic lineages, 7, 43–44 Picornavirus, 56, 59, 111–112, 133, 136, 151–152, 206, 239, 240, 241, 242t, 244t, 251, 270, 273f, 318 Coxsackie A9, 206 inhibitors, 273f Picornavirus protein 2C, 151–152 Plant virus multipartite, 58 RNA, 50 Plaque-to-plaque transfers, 41f, 45, 179f, 180, 186, 187f, 199–200, 201f, 209–215, 216f, 219, 220, 306–308, 323–324 Plasmid, 14, 23, 92–94, 285–286, 289–290, 343t Plasmodium falciparum, 344–345 Point mutation, 6–7, 40–41, 40f, 44, 50, 53–54, 56, 60f, 94–95, 98, 106, 140, 142–143, 178, 277, 311–313, 327–328, 342, 344–345, 346, 349, 350 Poliomyelitis, 25–26, 61, 266, 269 Poliovirus (PV), 6, 36–37, 228 mutagens, 305–306 non-neurotropic mutant, 106–108 vaccine, 61, 269, 292 virulence, fitness, 184–185 Polymerase antiviral strategies fidelity and modulation, nucleotide incorporation, 321–323 substitutions, unpredictable effects, 321 catalytic efficiency, 82, 283 catalytic site, 41, 86–87 408 Subject Index Polymerase (Continued) processivity, 57, 63 slippage, 37, 45, 213 substitutions, 321 viral polymerases, 51f Polymer formation, 11 Polyoma virus, 25–26, 139t, 201–202, 206, 207t Polyprotein, 111–112, 147, 213–214 Population bottleneck, 80, 81, 111, 128–129, 128f, 131f, 151, 154–155, 181f, 183, 209–210 Population disequilibrium, 89–90 Population dynamics in cell culture and in vivo, 199–203 competitive exclusion principle and red queen hypothesis, 216–218 contingency in evolution, 208–209 contingent neutrality in virus, 218 to culture is to disturb, 200–202 experimental evolution, 198 in vivo, 202–203 limits to fitness gain and loss, 215–216 molecular basis of fitness decrease, 213–215 Muller’s ratchet and advantage of sex, 212–213 persistent infections, cell culture, 205–209 plaque-to-plaque transfers, teachings from, 209–215 quasispecies dynamics in cell culture and in vivo, 219 reconstructed, 218 viral dynamics, controlled environments, 203–205 Population equilibrium, 204, 205, 216–217, 219, 344–345 Population size, 77, 87, 101–104, 112–113, 127–130 effective, 41–42, 127–130 limitations, 127–130, 278–279 Population thinking, 74 Positive selection, 10–11, 15–16, 82 episodic, 44 primitive, 15–16 Postreplicative repair, 49 Postweaning multisystemic wasting syndrome (PMWS), 25–26 Potato leaf roll virus, 62 Potato virus Y, 128–129 Power law, 351–354 Poxviruses, 6–7, 111–112, 244t Prebiotic conditions, 10 Prebiotic synthesis, 11 Precellular entities, 209 Predominant clonal evolution, 349 Primary infection, 235 Prion(s), 347–348 adaptability, 99 collective behavior, 347–349 conformers, 348 Prion-associated diseases, 347–348 Prion mutants, 348 3´-5´ Proofreading exonuclease, 48 Proofreading-repair, 46–47, 48, 49, 54, 63, 152, 213 Protease, 20–21, 282–283 Protease inhibitors, 275–276, 282–283, 286 Protein aggregation, 347–349 Protein folding, 136 Protein information resource (PIR), 246 Protein misfolding cyclic amplification assay, 348 Protein multifunctionality, 147, 152–153 Protein sequence space, 99 Protein synthesis, 12–13, 42, 85–86, 132, 133, 137f, 147, 180–182, 213 Protocell, 14–15, 20–21, 26–27 Protoviral element, 21 Protoviruses, 21 Protozoan populations, 345 Proviral reservoirs, 302–303 Provirus, 6, 80, 232, 236 PrPSc protein, 347–348 Pseudoknot structures, 132 Psychological space, 99 Purine and pyrimidine bases, 37–38 PV receptor, 138, 209, 251 Pyrimidine biosynthesis inhibitors, 305 Pyrosequencing, 46 ­Q Qβ replicase, 54, 85–86, 85f Quantum mechanical uncertainties, 40–41, 86–87, 340 Quasi-infectious, 53–54 Quasispecies adaptability, 102b with biological complexity, 111–113 complementation and interference, molecular mechanisms, 108–109 complexity measurement, 91–96, 92b consensus sequences, 89–91 definitions, 90b deterministic vs stochastic quasispecies, 86–88 evolution as movement, 99–101 in finite populations, 87, 89 impact, 97–99 individual vs group selection, 110 master genomes, 89–91 memory, 99, 105, 136, 180–184, 213, 235, 285, 351–353 memory, fitness implications, 183–184 and recovery, 180–184 mutant distributions in, 103t spectra, 89–91 spectra, modulating effects, 104–111 origins of theory, 84–86 Subject Index sequence space exploration and sampling problem, 101–104 and state transitions, 99–104 stochastic effects, 110–111 Quasispecies dynamics, disease prevention antiviral resistance disease progression, 288–289 fitness, 288–289 fitness/fitness-associated trait, 285–288 limitations, simplified reagents and small molecules, 289–290 molecular mechanisms, 282–284 viral load, 288–289 without prior exposure to antiviral agents, 285 antiviral vaccines and adaptive potential of viruses, 266–269 hit early and hit hard proposal, 290–291 information and global action, 291–292 medical interventions, 264–265 resistance to antiviral inhibitors, 269–281 virus evolution, manifestations of, 265–266 Quasispecies, theory, 13–14, 75, 84–87, 88, 89–90, 91, 97–98, 113, 305–306, 307f, 327, 329, 340, 343, 347–348, 356 Quasisynonymous, 44, 137–138 Quorum sensing, 344 ­R Rabies virus (RV), 132–133, 146t, 185, 239, 242t Radiation cosmic, 9–10 UV, 14 Random drift, 41–42, 43, 62–63, 83–84, 87, 97–98, 104, 114, 130, 148–149, 232–233, 302 Random sampling, 7, 78 RANTES, 140, 304 Rare synonymous codons, 136 Rate discrepancies and clock hypothesis, 237–238 Rate of evolution, 127, 232–238 Reassortment, 2–3, 7, 36–37, 58, 59–62, 63, 78, 238, 266, 302 Receptor recognition, 133, 134, 139, 139t, 140–142, 146t, 148–149, 155, 203, 241 Receptor specificity, 20, 140, 143–144, 251 Recombinant intermediates, 57 Recombination, 7, 36–37, 54–58 as biphasic process, 57 homologous, 56, 63 nonhomologous, 24, 55, 62, 188 nonreplicative, 55, 55f, 56 unproductive or inconsequential, 350, 356–357 Recombination, DNA and RNA, 54–58 Recombination-mediated switching, 344–345 Reconstructed quasispecies, 111, 218, 219 Red Queen hypothesis, 136, 180, 205, 216–218, 219, 220 Reoviridae, 58 409 Reoviruses, 146t, 206, 207t Repair error-prone, 46–47 postreplicative, 46–47, 49 Replacement of subpopulations, 237, 323–324 Replication complex (RC), 6, 48, 49, 56, 108, 132, 172–173, 271–272, 318 Replicative intermediate, 5f, 6, 46–47 Replicative load and antiviral resistance, 271–272 Replicons/replicators, 13–15 Reproductive ratio, 189–190 229–231 Resampling methods, 247–248 Resistance to antiviral inhibitors, 269–281 barriers to drug resistance, 275–276 drug efficacy, mutant frequencies, and selection of escape mutants, 277–280 drug-escape mutants, 270 multiple pathways and evolutionary history, 281 phenotypic barrier and selective strength, 280–281 replicative load and antiviral resistance, 271–272 Resistant mutant frequencies, 271–272 Retrovirus, endogenous, 23, 25 Retroviruses, 6–7, 46t, 50, 52, 56, 57, 80, 127, 206, 232, 232t, 302–303, 311–312, 349–350 Reverse genetics, 53–54, 189, 270 Reverse transcriptase (RT), 6, 48, 57, 282 Reverse transcription, 18–19, 24, 80, 350–351 Reversion, 45, 47, 53–54, 148, 204, 214, 235, 242, 269, 275, 276, 280–281, 284t Ribavirin (Rib), 104, 314f, 317–319 Ribavirin-monophosphate (RMP), 317–318, 321, 322 Ribavirin resistance, 281, 320, 321, 322 Ribavirin-triphosphate (RTP), 188, 312t Ribosomal frameshifting, 132, 147 Riboviruses, 6, 52–53, 232t Ribozyme, 11, 12–13, 38, 289–290 Rift valley fever virus, 154f, 317 Rinderpest, 251, 266 RNA genetics, 61 mutations in, 40f secondary structure, 18, 37, 82, 135, 244t, 246 viruses, 6, 7, 18, 54–58, 76–77, 146t virus evolution rate in nature, 232–238 RNA-dependent RNA polymerase (RdRp), 6, 48, 49, 85–86 RNA interference (RNAi), 42, 89–90, 133–134 RNA-like replicon, 18 RNA organisms, 19 RNA-protein interaction, 38, 42 RNA-RNA interactions, 135 RNA world, 6–7, 11–13, 14, 17f, 18, 208–209 Road-block hypothesis, 108–109 Robustness, 53, 187, 188, 306, 323–324 410 Subject Index Rotten apple hypothesis, 108–109 r Strategists, 126–127 Rugged fitness landscapes, 178, 306 Rule of six, 327–328 ­S Sabin poliovirus vaccine, 269 Satellite RNA, 50 Scrapie, 347–348 Selection coefficient, 41–42, 82, 170 individual vs group, viral quasispecies, 110 negative, 43–44, 45, 57, 81–83, 106–108, 131, 135, 180–182, 214, 350, 351 positive, 10–11, 15–16, 44, 61, 78, 81–82, 83, 84, 111, 278–279, 340, 345 positive vs negative, Darwinian principles, 81–83 and random drift, 83–84 translational, 136 Selective constraint, 132, 135–138, 183, 264–265 Self-instructive behavior, 86 Selfish replicating elements, 23 Self-organization, 13–14, 84–85, 86 Self-organized networks, 353, 354 Self-organized systems, 340, 354 Sequence alignment, 243–247, 256 Sequence alignment, structure-based, 246 Sequence space drift in, 59, 99–101, 311 exploration and sampling problem, 101–104 neutral, 138 relocalization, 323 representations, 100f and state transitions, 99–104 theoretical, 101 virus evolution, 99–101 Sequential vs combination treatments, 324–326 Serial passage, 59, 84–85, 85f, 171f, 182, 185, 199, 278, 285–286, 287f, 319f, 325f Setpoint genome formula, 58 Severe acute respiratory syndrome (SARS) coronavirus, 139t, 140, 230, 291–292 Sexual reproduction, 2–3, 36–37, 350–351 Simian immunodeficiency virus (SIV), 140, 142–143, 248–249, 268 Sindbis-like virus, 61 Sindbis virus, 8f, 24, 62, 139t, 146t, 242t, 319–320 Single stranded DNA (ssDNA), 5–6, 46–47, 56 Single stranded RNA (ssRNA), 5–6, 59 Site-directed mutagenesis, 50–52, 53, 315, 321 Small interfering RNA (siRNA), 42 Smallpox, 251, 266 Spanish influenza, 229 Spatial habitats, 253 Speciation, 130 Species, 2–3, 4–5, 24, 125–126, 130 Specific infectivity, 136, 213–214, 306–308, 317 Splits-tree, 247 Spumaviruses, 248 Stacking interactions, 38–40 Starving sex hypothesis, 349, 350 Sterilizing immunity, 266–267, 268 Stochastic component, 174–175 Structural space, 7, 99 Subacute sclerosing panencephalitis, 52, 127 Subviral elements, 6–7 Superinfection exclusion, 25, 57–58, 131, 350 Supershedders, 185 Superspreaders, 185 Survival of the flattest, 306 Swarms dominant-negative, 61 mutant, 79f, 91, 275, 276 Sweeping selection, 81, 111 Symbiosis, 25, 351 Symmetry helical, 4–5 icosahedral, syn conformation, 37–38 Synergistic interference, 105–106 Synonymous codons, 42, 135–136, 137–138, 137f, 275–276 Synonymous codon space, 137–138 Synonymous mutation, 38–40, 41–42, 44, 46, 98, 132, 135, 155, 238–239 ­T T-705 (favipiravir), 311–312, 312t, 314f, 317 Target compartmentalization, 326 Tautomeric change, 37–38 Tautomeric form, 37–38, 46, 86–87 Temperate bacteriophages, 24, 56 Temperature sensitive mutants, 204 Template miscopying, 37 switching, 55f, 56, 57–58 Template-copying fidelity, 46–47, 48, 50–52, 62–63, 84–85, 151, 320, 321, 322–323, 345–346 Template-primer, 48, 50–52, 51f Theories of origin, virus, 17–22 Theory, in virology, 77 Therapeutic index (TI), 277, 277f, 278, 328 Tobacco mosaic virus, 6, 125, 128–129 Trade-off, 14, 48, 131–135, 152, 280–281 Trans-acting proteins, 59, 107f, 310–311 Subject Index Transducing bacteriophages, 24 Transfer RNA (tRNAs), 12–13, 24, 37–38, 42, 132, 135–136, 172–173, 277 Transfer RNA (tRNA), quasispecies, 12–13 Transition-modulating phenotype, 321–322 Transition mutation, 41, 53, 151–152, 275–276 Translational selection, 136 Translation kinetics, 136 Transmissibility, 189–190, 202, 230, 236–237 Transmissible spongiform encephalopathies, 347–348 Transmission chains, 234 synapse-mediated, 19 vertical, 21, 228, 232, 255 Transversion mutation, 43 Treatment splitting, 354–356 Treatment switch, 303–304 Tree of life, 22–23 Tropism, 138, 139t Tropism, expansion, 140–143, 142f Tumor cells, 19, 345, 346, 347, 356 Tumor heterogeneity, 345 Tumor viruses, 6, 24 Turnip crinkle carmovirus, 50 Two-component theory of cancer, 346–347 ­U Unicellular eukaryotes, 344–345, 356 Unicellular parasites, parasitic disease control, 344–345 Uniform resource locator (URL), 243–247, 244t, 248, 256 Unit of selection, 90, 101, 104–111, 114, 344, 347, 351 Unpreferred synonymous codon, 136 Unweighted pair group method with arithmetic mean (UPGMA), 247 UV light, 14 ­V Vaccination, 132, 134–135, 155, 239, 240–241, 264–265, 266, 267, 267b, 268–269, 289–290, 292, 300, 305 Vaccination failure, 264–265 Vaccination-induced evolution, 268–269 Vaccine composition, 265–266 efficacy, 266–267 monovalent, 265 multivalent, 265 Vaccine-escape mutants, 267, 268–269 Vaccinology, basic principle, 266–267 Venezuelan equine encephalitis virus (VEEV), 153, 154f Vertical transmission, 232 genetic information, 21 virus, 228, 255 411 Vesicle, 21–22, 27, 143f, 209 Vesicle, budding, 21 Vesicular stomatitis virus (VSV), 46, 104–105, 125 fitness landscapes, 188 mutagens, 305–306 Viral breakthrough, 276, 283, 302 Viral clearance, 265 Viral disease, 4, 11, 24, 88, 91, 95, 125–126, 153, 185, 190, 219, 228–229, 237, 251–252, 255, 265–266, 268, 270, 281, 291–292, 304, 328, 329, 357 Viral dynamics, controlled environments, 203–205 See also Population dynamics Viral emergence, 228–229, 251–254, 254f, 255, 256 Viral fitness, 170–180, 288–289 Viral genome, 5f, 6–7, 22, 37, 42, 52, 54, 56, 57, 58–59, 62, 78, 90, 101, 103–104, 106, 111–112, 113–114, 126, 132, 142–143, 147, 150–151, 184, 186–187, 187f, 204–205, 207t, 215, 229, 230, 234, 243–246, 272, 278–279, 301f, 340, 349–350 Viral genome segmentation, 58–59 Viral infections, productive power, 126–127 Viral load, 4, 172, 175, 183, 201–202, 230, 270, 283, 288–289, 289f, 291, 293, 303–304, 306–308, 312t, 317, 323, 326, 354–356 Viral pathogenesis, 4, 77, 79, 87, 98, 112, 139, 140 Viral persistence, antibody and cytotoxic T cell responses, 147–148 Viral polymerase, 6, 37–38, 41, 46, 50, 51f, 52, 57, 62–63, 83, 135, 145–147, 180–182, 198, 275–276, 281, 282, 283, 313–315, 317–318, 320, 322–323, 345–346 Viral population(s) "extrinsic" property, 112–113, 200 "intrinsic" property, 112–113, 200 substructuring, 351–354 Viral population numbers, 62–63, 110, 124–126, 143–144, 205–206, 212, 228, 229, 237, 253, 288, 291 Viral quasispecies adaptability, 102b with biological complexity, 111–113 complementation and interference, molecular mechanisms, 108–109 complexity measurement, 91–96, 92b consensus sequences, 89–91 definitions, 90b deterministic vs stochastic quasispecies, 86–88 evolution as movement, 99–101 impact, 97–99 individual vs group selection, 110 master genomes, 89–91 mutant distributions in, 103t mutant spectra, 89–91, 104–111 origins of theory, 84–86 sequence space 412 Subject Index Viral quasispecies (Continued) exploration and sampling problem, 101–104 and state transitions, 99–104 stochastic effects, 110–111 Viral self, 20 Virion, 126–127 three-dimensional structures, turnover, 126–127 Viroid, 6–7, 11, 12–13, 18, 49, 244t VIROME (Viral Informatics Resource for Metagenome Exploration), 125–126 Virulence, 87, 151–152, 184–187, 187f, 190, 202, 207t, 213–214, 215–216, 230, 269, 344 Virulence determinant, 25, 48–49, 184, 186, 187f Virus alive vs not alive, 22–23 attenuation, 135–138, 184–185 biological diversity, 2–3 definitions of, 22b and disease, 25–26 diversity of, 4–7 dynamics, 84, 138, 203–205, 230, 230f, 269, 303, 353 elements for long-term coevolution, 20–21 energy uptake, 15–16 eradication, 251 evolution of biosphere, role in, 23–25 evolution rate in nature, 232–238 extinction, 61, 82, 151–152, 213–214, 302–303, 306, 308, 311–317, 312t, 323–326, 327, 329 genetic material exchanges, 24 giant, 6–7, 19 host range, 138–144, 207t, 268 liberated autonomous entities, 20 as moving targets, 302 nonpathogenic, 25–26, 78, 343t oligonucleotides synthesis, 10–11 origin of life, 8–16 origins, 1–33, 61, 133–134, 209, 228–229, 248, 249–251 primitive RNA world, 11–13 regressive microbial evolution, 19 remnants of primeval genetic elements, 18–19 replicons origin, 13–15 resistance to mutagenic agents, 319–323 second primitive positive selection, 15–16 subpopulations, 104, 113–114, 138, 140–142, 143, 179–180, 185, 190, 203–205, 218, 220, 264–265, 304, 323–324 symbiotic relationships, 25 theories of origin, 17–22 transmission, 19, 128, 228, 229, 231, 255, 256, 291 from vesicles, 21–22 viral particles number of, 3b size, 4–5, 5f vulnerability, 354–356 zoonotic transmission, 253f Virus-cell coevolution, 205–209 Virus evolution manifestations, prevention and treatment, 265–266 theoretical frameworks, 74–77 theory and experiment, 77 Virus extinction, 311–317 See also Antiviral strategies by mutagenic agents, 311–317 tempo and mode of mutation acquisition, 323–324 Virus-host coevolution, 206 Virus-host interactions alternating selective pressures, 153 antibody and cytotoxic T cell responses, 147–148 antigenic variation, immune selection absence, 148–149 cell-dependent constraints, 132–134 codon usage, 135–138 host cell tropism and host range modifications, 138–144, 139t host organisms constraints, 134–135 multifunctional viral proteins, host factors interaction, 151–153 mutation rate levels, 149–151 nonstructural viral proteins, 142–144 receptor usage by viruses, 139b synonymous codon space, 137–138 trade-offs, constraints and evolutionary, 131–135 trait coevolution, 144–147 Virus-receptor interaction, 138 Vitalism, v-mos, 80, 237 VPg uridylylation, 318 ­W Watson-Crick base pairs, 37, 38f Watterson’s estimator, 246 w, dn/ds, 43–44 Weibull distribution, 353 Western equine encephalitis virus, 61 West Nile virus (WNV), 154f, 249, 250f, 312t, 315 White spot syndrome virus, 186 Wobble base pairs, 37, 39f, 74, 311–312 World Wide Web (www), 246, 340, 353, 354 ­Y Yellow fever virus, 146t, 153 ­Z Zoonotic, 153, 154f, 203 reservoir, 249–251, 255 threat, 202 transmissions, 125–126, 253f, 268 Zymograms, 2–3 ... contains most DNA viruses such as herpesviruses, poxviruses and papilloma viruses, and the extremely large viruses (Mimivirus, Megavirus, and Pandoravirus) and their parasitic viruses (La Scola... mottle virus double stranded RNA Escherichia coli Virus as Populations http://dx.doi.org/10.1016/B97 8-0 -1 2-8 0083 7-9 .0000 1-0 © 2016 Elsevier Inc All rights reserved eHBVs HBV HCV HDV HIV-1 ICTV... between viruses and primitive free-living cells rather than between viruses and modern (eukaryotic) cells 1.5.4  VIRUSES ARE ELEMENTS FOR LONG-TERM COEVOLUTION • Viruses are as ancient as cells, and