Virus Bioinformatic 0367558602, 9780367558604
Viruses are the most numerous and deadliest biological entities on the planet, infecting all types of living organisms―f
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English Pages 296 [297] Year 2021
Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
CHAPTER 1 Comparative Genomics of Viruses
1.1 Genomics of Viruses
1.1.1 Genome Types, Sizes, and Nomenclature
1.1.2 Genome Sequences from Cultures
1.1.3 Genomes from Environmental Samples
1.1.4 Proviruses
1.1.5 Annotation of Virus Genomes
1.1.6 Database Resources for Virus Genome Sequences
1.2 Comparison of Virus Genome Sequences
1.3 Protein Families and Orthologous Groups of Viruses
1.4 Evolution of Protein Families within Virus and Host Genomes
1.5 Outlook
References
CHAPTER 2 Current Techniques and Approaches for Metagenomic Exploration of Phage Diversity
2.1 Introduction
2.2 Phage Metagenomics: A Brief History
2.3 Recovering Phage Genomes from Metagenomes
2.4 Identification and Quality Control of Phage Contigs in Metagenome Assembly
2.5 Structural Annotation of Metagenome-Assembled Phage Genomes
2.6 Bringing Meaningful Eco-evolutionary Context to Metagenome-Assembled Phage Genomes
2.7 Conclusion
References
CHAPTER 3 Direct RNA Sequencing for Complete Viral Genomes
3.1 Advantages and Disadvantages for Viruses
3.2 Virus Assembly of the Human Coronavirus 229E
3.3 Long Reads Enable Discovery of Long-Range Interactions and Genome-Wide Compensatory Mutations
3.4 Sequencing Full RNA Viral Transcripts
3.5 Modifications
3.6 Tracking Virus Mutations during Outbreaks
Acknowledgments
References
CHAPTER 4 Computational Methods for Viral Quasispecies Assembly
4.1 Introduction
4.2 Challenges of Global Haplotype Reconstruction
4.3 Overview of Methodological Approaches for Global Haplotype Reconstruction
4.4 Conclusions
References
CHAPTER 5 Functional RNA Structures in the 3' UTR of Mosquito-Borne Flaviviruses
5.1 Introduction
5.2 Flavivirus 3' UTR Background
5.3 Materials and Methods
5.4 Results
5.4.1 Japanese Encephalitis Virus Group
5.4.2 Ntaya Virus Group
5.4.3 Aroa Virus Group
5.4.4 Kokobera Virus Group
5.4.5 Dengue Virus Group
5.4.6 Spondweni/ Kedougou Virus Group
5.4.7 Yellow Fever Virus Group
5.4.8 Structural Diversity of Conserved Elements
5.5 Conclusion
References
CHAPTER 6 Structural Bioinformatics of Influenza Virus RNA Genomes
6.1 Introduction
6.2 Detection of Conserved Structures in Influenza Virus RNA by Comparative Analysis
6.3 Identification of Influenza Virus RNA Structures Using Structure Probing
6.4 Networks of Intersegmental Interactions
6.5 Concluding Remarks
References
CHAPTER 7 Structural Genomics and Interactomics of SARS-COV2: Decoding Basic Building Blocks of the Coronavirus
7.1 Understanding the Molecular Mechanisms of COVID-19: A Current Focus of Scientific Community
7.2 Genomic and Structural Organization of the Novel Coronavirus
7.3 Structural Characterization of the Individual Viral Proteins
7.4 Structural Characterization of Intra-Viral and Viral-Host Protein Complexes
7.5 Molecular Interactions between Viral Proteins and Small Ligands
7.6 Virus-Host Interactions: A Systems View
7.7 Next Steps
References
CHAPTER 8 Computational Tools for Discovery of CD8 T cell Epitopes and CTL Immune Escape in Viruses Causing Persistent Infections
8.1 Impact of Viral Mutations in Amino Acid Sequence of Viral Proteins on Epitope Recognition during Chronic Infection
8.2 HDV as a Model for Detection of Epitopes and Corresponding Immune Escape Mutation in Chronic Viral Infection
8.3 HDV Molecular Biology and Replication
8.4 HDV Genome Variability of a Sequence
8.5 HDV Immunology
8.6 Methods for the Prediction of CTL Epitopes and the Detection of IEMs
8.7 Better Ways of Finding HLA-Associated Mutations (HAMs)
8.8 Conclusion
References
CHAPTER 9 Virus-Host Transcriptomics
9.1 Introduction
9.2 Parallel Read Alignment to Host and Virus
9.3 Incomplete Annotation of Viral Transcriptomes
9.4 Normalization and Differential Gene Expression Analysis
9.5 Be Careful of Your Interpretation
9.6 Conclusion
References
CHAPTER 10 Sequence Classification with Machine Learning at the Example of Viral Hos Prediction
10.1 Machine Learning Applications in Virology
10.2 An Introduction to Neuronal Networks—and When to Use Them
10.3 Machine Learning as a Powerful Method to Classify Viral Sequences
10.3.1 Final Host Prediction From Subsequence Predictions
10.4 The Host of a 400 nt Fragment of Influenza A Virus Can Be Predicted Very Accurately
10.4.1 Varying the Details Yield Similar Predictions
10.5 Final Remarks
References
CHAPTER 11 Master Regulators of Host Response to SARS- CoV-2 as Promising Targets for Drug Repurposing
11.1 Introduction
11.2 Results
11.2.1 Functional Classification of Genes
11.2.2 Analysis of Enriched Transcription Factor Binding Sites and Composite Modules
11.2.3 Finding Master Regulators in Networks
11.2.4 Finding Prospective Drug Targets
11.2.5 Identification of Potential Drugs
11.2.5.1 Drugs Approved in Clinical Trials
11.2.5.2 Repurposing Drugs
11.3 Discussion
11.4 Methods
11.4.1 Databases Used in the Study
11.4.2 Methods for the Analysis of Enriched Transcription Factor Binding Sites and Composite Modules
11.4.3 Methods for Finding Master Regulators in Networks
11.4.4 Methods for Analysis of Pharmaceutical Compounds
11.4.4.1 Method for Analysis of Known Pharmaceutical Compounds
11.4.4.2 Method for Prediction of Pharmaceutical Compounds
References
CHAPTER 12 The Potential of Computational Genomics in the Design of Oncolytic Viruses
12.1 Introduction
12.2 Mathematical Modeling of OV
12.3 Computational Modeling of Heterologous Gene Expression and Live Attenuated Vaccines
12.4 The Potential of Bioinformatics and Genomics in the Development of OV
12.5 Conclusion
References
CHAPTER 13 Sharing Knowledge in Virology
13.1 The Virus Exception
13.2 ViralZone at the Service of Knowledge Sharing
13.3 The Growing Landscape of Virus Databases
13.4 The Predictive Power of Knowledge
13.5 Conclusion
References
INDEX
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Virus Bioinformatics
Chapman & Hall/CRC Computational Biology Series About the Series:
This series aims to capture new developments in computational biology, as well as high-quality work summarizing or contributing to more established topics. Publishing a broad range of reference works, textbooks, and handbooks, the series is designed to appeal to students, researchers, and professionals in all areas of computational biology, including genomics, proteomics, and cancer computational biology, as well as interdisciplinary researchers involved in associated fields, such as bioinformatics and systems biology. PUBLISHED TITLES Clustering in Bioinformatics and Drug Discovery John David MacCuish and Norah E. MacCuish Metabolomics: Practical Guide to Design and Analysis Ron Wehrens and Reza Salek An Introduction to Systems Biology: Design Principles of Biological Circuits Second Edition
Uri Alon
Computational Biology: A Statistical Mechanics Perspective Second Edition
Ralf Blossey
Stochastic Modelling for Systems Biology Third Edition
Darren J. Wilkinson Computational Genomics with R Altuna Akalin, Bora Uyar, Vedran Franke, and Jonathan Ronen An Introduction to Computational Systems Biology: Systems-level Modelling of Cellular Networks Karthik Raman
Virus Bioinformatics Dmitrij Frishman and Manja Marz
For more information about this series please visit: https://www.routledge.com/Chapman--HallCRC-ComputationalBiology-Series/book-series/CRCCBS
Virus Bioinformatics
Edited by
Dmitrij Frishman Manja Marz
First edition published 2022 by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742 and by CRC Press 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN © 2022 Dmitrij Frishman & Manja Marz CRC Press is an imprint of Taylor & Francis Group, LLC Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all m aterial reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any i nformation storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www. copyright.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 9 78-750-8400. For works that are not available on CCC please contact [email protected] Trademark Notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging‑in‑Publication Data Names: Frishman, Dmitrij, editor. | Marz, Manuela, editor. Title: Virus bioinformatics / edited by Dmitrij Frishman, Manuela Marz. Description: First edition. | Boca Raton : CRC Press, 2021. | Series: Chapman & Hall/CRC computational biology series | Includes bibliographical references and index. Identifiers: LCCN 2021008505 | ISBN 9780367558604 (hardback) | ISBN 9780367564193 (paperback) | ISBN 9781003097679 (ebook) Subjects: LCSH: Virology—Data processing. | Virology—Research. | Bioinformatics. Classification: LCC QR370.V57 2021 | DDC 579.0285—dc23 LC record available at https://lccn.loc.gov/2021008505 ISBN: 978-0 -367-55860-4 (hbk) ISBN: 978-0 -367-56419-3 (pbk) ISBN: 978-1-003-09767-9 (ebk) Typeset in Minion Pro by codeMantra
Contents Preface, vii Editors, xi Contributors, xiii CHAPTER 1
◾
Comparative Genomics of Viruses
1
THOMAS R ATTEI
CHAPTER 2
◾
Current Techniques and Approaches for Metagenomic Exploration of Phage Diversity
17
SIMON ROUX AND MARK BORODOVSKY
CHAPTER 3
◾
Direct RNA Sequencing for Complete Viral Genomes
35
SEBASTIAN KRAUTWURST, RONALD DIJKMAN, VOLKER THIEL, ANDI KRUMBHOLZ, AND MANJA MARZ
CHAPTER 4
◾
Computational Methods for Viral Quasispecies Assembly
51
KIM PHILIPP JABLONSKI AND NIKO BEERENWINKEL
CHAPTER 5
◾
Functional RNA Structures in the 3′ UTR of Mosquito-Borne Flaviviruses
65
MICHAEL T. WOLFINGER, ROMAN OCHSENREITER, AND IVO L. HOFACKER
v
vi ◾ Contents
Chapter 6 ◾ Structural Bioinformatics of Influenza Virus RNA Genomes
101
Alexander P. Gultyaev, René C.L. Olsthoorn, Monique I. Spronken, and Mathilde Richard
Chapter 7 ◾ Structural Genomics and Interactomics of SARS-COV2: Decoding Basic Building Blocks of the Coronavirus
121
Ziyang Gao, Senbao Lu, Oleksandr Narykov, Suhas Srinivasan, and Dmitry Korkin
Chapter 8 ◾ Computational Tools for Discovery of CD8 T cell Epitopes and CTL Immune Escape in Viruses Causing Persistent Infections
141
Hadi K arimzadeh, Daniel Habermann, Daniel Hoffmann, and Michael Roggendorf
Chapter 9 ◾ Virus-Host Transcriptomics
157
Caroline C. Friedel
Chapter 10 ◾ Sequence Classification with Machine Learning at the Example of Viral Host Prediction 179 Florian Mock and Manja Marz
Chapter 11 ◾ Master Regulators of Host Response to SARS-CoV-2 as Promising Targets for Drug Repurposing 197 Manasa K alya, K amilya Altynbekova, and Alexander Kel
Chapter 12 ◾ The Potential of Computational Genomics in the Design of Oncolytic Viruses 245 Henni Zommer and Tamir Tuller
Chapter 13 ◾ Sharing Knowledge in Virology Edouard De Castro, Chantal Hulo, Patrick Masson, and Philippe Le Mercier
INDEX, 275
263
Preface
T
his book was conceived long before the start of the COVID-19 pandemic. While there are multiple excellent publications covering various aspects of bioinformatics—from sequence analysis and structural bioinformatics to regulation and genome evolution—we felt that a dedicated book on bioinformatics of viruses would be warranted given their remarkable and very special properties, which render many standard algorithms and methods inefficient and dictate the application of highly specialized tools. As this book progressed toward completion, the actual scale of the COVID-19 pandemic became apparent, giving further emphasis to the importance of the field. Indeed, at least half of the chapters in this book mention the SARS-COV-2 virus, and two chapters are dedicated to it. We have described only a tiny fraction of the estimated total number of viruses (