From Whole-Genome Shotgun Sequencing to Viral Community Profiling: The ViromeScan Tool (original) (raw)
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2007
Preface xv Abbreviations used in this book xvii Greek letters used in this book xxi Colour coding for molecules xxiii Viruses and their importance 1 At a glance 1 1.1 Viruses are ubiquitous on Earth 3 1.2 Reasons for studying viruses 3 1.3 The nature of viruses 4 1.4 The remainder of the book 7 Learning outcomes 7 Sources of further information 7 Methods used in virology 9 At a glance 9 2.1 Introduction to methods used in virology 11 2.2 Cultivation of viruses 12 2.3 Isolation of viruses 13 2.4 Centrifugation 13 2.5 Structural investigations of cells and virions 17 2.6 Electrophoretic techniques 17 2.7 Detection of viruses and virus components 18 2.8 Infectivity assays 22 2.9 Virus genetics 26 Learning outcomes 28 Sources of further information 28 Virus structure 31 At a glance 31 3.1 Introduction to virus structure 32 3.2 Virus genomes 32 3.3 Virus proteins 37 3.4 Capsids 39 3.5 Virion membranes 45 3.6 Occlusion bodies 47 viii CONTENTS 3.7 Other virion components Learning outcomes Sources of further information 4 Virus transmission At a glance 4.1 Introduction to virus transmission 4.2 Transmission of plant viruses xii CONTENTS 21 Emerging viruses At a glance 21.1 Introduction to emerging viruses 21.2 Viruses in new host species 21.3 Viruses in new areas 21.4 Viruses in new host species and in new areas 21.5 New viruses 21.6 Recently discovered viruses 21.7 Re-emerging viruses 21.8 Virus surveillance 21.9 Dealing with outbreaks Learning outcomes Sources of further information 22 Viruses and cancer At a glance 22.1 Introduction to viruses and cancer 22.2 Papillomavirus-linked cancers 22.3 Polyomavirus-linked cancers 22.4 Epstein-Barr virus-linked cancers 22.5 Kaposi's sarcoma 22.6 Adult T cell leukaemia 22.7 Hepatocellular carcinoma 22.8 Virus-associated cancers in animals 22.9 Cell lines derived from virus-associated cancers 22.10 How do viruses cause cancer? 22.11 Prevention of virus-induced cancers Learning outcomes Sources of further information 23 Survival of infectivity At a glance 23.1 Preservation of virus infectivity 23.2 Destruction of virus infectivity 23.3 Inactivation targets in virions 23.4 Inactivation kinetics 23.5 Agents that inactivate virus infectivity Learning outcomes Sources of further information 24 Virus vaccines At a glance 24.1 Introduction to virus vaccines 24.2 Live attenuated virus vaccines 24.3 Inactivated virus vaccines 24.4 Virion subunit vaccines 24.5 Live recombinant virus vaccines 24.6 Mass production of viruses for vaccines CONTENTS xiii 24.7 Virus-like particles 24.8 Synthetic peptide vaccines 24.9 DNA vaccines 24.10 Storage and transport of vaccines Learning outcomes Sources of further information 25 Anti-viral drugs At a glance 25.1 Introduction to anti-viral drugs 25.2 Development of anti-viral drugs 25.3 Examples of anti-viral drugs 25.4 Drug resistance 25.5 Anti-viral drug research Learning outcomes Sources of further information 26 Prions At a glance 26.1 Introduction to prions 26.2 Transmissible spongiform encephalopathies 26.3 The nature of prions 26.4 Prion diseases 26.5 Prion strains 26.6 Prion transmission 26.7 The protein-only hypothesis Learning outcomes Sources of further information Virologists' vocabulary Index
2013
Double-stranded (ds)RNA fungal viruses are currently assigned to six different families. Those from the family Totiviridae are characterized by nonsegmented genomes and single-layer capsids, 300-450 Å in diameter. Helminthosporium victoriae virus 190S (HvV190S), prototype of recently recognized genus Victorivirus, infects the filamentous fungus Helminthosporium victoriae (telomorph: Cochliobolus victoriae), which is the causal agent of Victoria blight of oats. The HvV190S genome is 5179 bp long and encompasses two large, slightly overlapping open reading frames that encode the coat protein (CP, 772 aa) and the RNA-dependent RNA polymerase (RdRp, 835 aa). To our present knowledge, victoriviruses uniquely express their RdRps via a coupled termination-reinitiation mechanism that differs from the well-characterized Saccharomyces cerevisiae virus L-A (ScV-L-A, prototype of genus Totivirus), in which the RdRp is expressed as a CP/RdRp fusion protein due to ribosomal frameshifting. Here, we used transmission electron cryomicroscopy and three-dimensional image reconstruction to determine the structures of HvV190S virions and two types of virus-like particles (capsids lacking dsRNA and capsids lacking both dsRNA and RdRp) at estimated resolutions of 7.1, 7.5, and 7.6 Å , respectively. The HvV190S capsid is thin and smooth, and contains 120 copies of CP arranged in a ''T = 2'' icosahedral lattice characteristic of ScV-L-A and other dsRNA viruses. For aid in our interpretations, we developed and used an iterative segmentation procedure to define the boundaries of the two, chemically identical CP subunits in each asymmetric unit. Both subunits have a similar fold, but one that differs from ScV-L-A in many details except for a core a-helical region that is further predicted to be conserved among many other totiviruses. In particular, we predict the structures of other victoriviruses to be highly similar to HvV190S and the structures of most if not all totiviruses including, Leishmania RNA virus 1, to be similar as well.
InTech eBooks, 2012
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Unraveling the Web of Viroinformatics: Computational Tools and Databases in Virus Research
Journal of Virology, 2014
The beginning of the second century of research in the field of virology (the first virus 27 was discovered in 1898) was marked with its amalgamation with bioinformatics 28 resulting in the birth of a new domain -viroinformatics. The availability of more than 29 100 web servers and databases embracing all or specific viruses (for example dengue, 30 influenza, hepatitis, HIV, HFV, HPV, West Nile etc.) as well as distinct applications 31 (comparative/diversity analysis, viral recombination, siRNA/shRNA/miRNA studies, 32 RNA folding, protein-protein interaction, structural analysis, phylotyping/genotyping) 33 will definitely aid the development of effective drugs and vaccines. However, the 34 information about their access and utility is not available at any single 35 source/platform. Therefore, a compendium of various computational tools/resources 36 dedicated specifically to virology is presented in this article.
ViralZone: recent updates to the virus knowledge resource
Nucleic Acids Research, 2013
ViralZone (http://viralzone.expasy.org) is a knowledge repository that allows users to learn about viruses including their virion structure, replication cycle and host-virus interactions. The information is divided into viral fact sheets that describe virion shape, molecular biology and epidemiology for each viral genus, with links to the corresponding annotated proteomes of UniProtKB. Each viral genus page contains detailed illustrations, text and PubMed references. This new update provides a linked view of viral molecular biology through 133 new viral ontology pages that describe common steps of viral replication cycles shared by several viral genera. This viral cell-cycle ontology is also represented in UniProtKB in the form of annotated keywords. In this way, users can navigate from the description of a replication-cycle event, to the viral genus concerned, and the associated UniProtKB protein records.
PeerJ, 2021
Background. Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). Results. The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer-and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer-and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a How to cite this article