Principles and Practice of Clinical Virology is the bible for all working in the field of clinical virology – from the trainee to the expert because. download Textbook of Medical Virology - 1st Edition. Print Book & E-Book. DRM-free (EPub, PDF, Mobi) Some of the topics covered in the book are the symmetrical arrangements of viruses; introduction to different families of animal viruses. Introduction to modern virology/N. J. Dimmock, A. J. Easton, K. N. Leppard. – 6th ed. .. This book, now in its sixth edition, provides a rounded introduction to.
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𝗣𝗗𝗙 | riapeocaconcou.ml Looking for books on Virology? Check our section of free e-books and guides on Virology now! This page Handbook Of Diagnostic Virology Testing (PDF 41P). technology books. Comparative Plant Virology, Second Edition, by Roger Hull. Revision to Fundamentals of Plant Virology written by R. Matthews. ACADEMIC.
Skip to Main Content. Arie J. Zuckerman Jangu E. Banatvala Barry D. Schoub Paul D. Griffiths Philip Mortimer. First published: Print ISBN: As before, the book provides a detailed account of the diagnosis and treatment of virus infections, with a stronger emphasis on clinical expertise and management. Each chapter deals with a single virus or group or viruses and is written by leading international experts in the field.
Textbook of Medical Virology
Reviews "There is a wealth of useful information in this book. Free Access. Summary PDF Request permissions. There exist several scenarios for sequencing viral genomes such as sequencing of individual strains or population [ 12 ].
Sequencing of individual genomes helps to catalogue the genes encoded in a particular strain and is a vital step for in-depth characterization studies. CRISPR are found in archaea and bacteria that serve as an antiviral mechanism in which viral genomic sequences are integrated as CRISPR spacers into the host, thereby making it immune to viral infection [ 15 ].
Understanding complex dynamics of virus—host interactions in higher organisms using sequencing provides valuable insights into transmission between animal reservoirs [ 16 ]. Sequencing of 'Auxiliary metabolic genes', which are involved in processes like motility and transcriptional repression, enables to unravel the viral genes that influence host machinery in diverse ways [ 17 ]. Data assembly and annotations Output from NGS technologies results in gigabases of raw sequence data per experiment.
Extensive computational analysis using a number of algorithms and applications is required to infer biological significance. Care should be taken in case of paired-end sequences to ensure that the reads trimmed based on the quality is reflected in both the forward and the reverse FASTQ files.
In case of multiplex sequencing data, an additional step of 'de-multiplexing' based on barcodes is mandatory. Filtering of such data ensures that no error is propagated. Following preprocessing, reference-based mapping or de novo assembly of the processed reads can be carried out.
Reference-mapping Alignment with a reference genome is a method of choice for most NGS experiments. Preprocessed reads when mapped to a well-annotated reference genome ensure transfer of annotations to the query genome in a hassle-free manner with statistical confidence, especially in indel-free regions.
Polymorphic regions can also be identified, which account for the isolate-specific variants that may be responsible for the observed phenotype. The algorithms generally rely on indexing of either the query reads or the reference genome using suffix tree or hashing strategy [ 20 — 22 ].
Indexing the reference genome has been proved to be computationally advantageous and is widely preferred. Indexing is followed by gapped or ungapped alignment based on either Smith—Waterman [ 23 ] or Needleman—Wunsch dynamic programming approaches [ 24 ].
The quality of the reference alignment can be improved by using large inserts available in paired-end reads as compared to single-end reads wherein forward and reverse orientation of reads cannot be calculated. Downstream processing of aligned and assembled reads involves delineating the variant regions followed by annotation.
It is also important to remove polymerase chain reaction PCR artefacts before variant calling as the duplicated reads hamper its sensitivity. Discovery of Schmallemberg virus, a new member of genus Orthobunyavirus that causes foetal abnormalities in ruminants [ 25 ], is attributed to a reference-based assembly approach.
Delineation of variant regions: All deviations from reference genome can be delineated as variants, which include SNPs and indels.
Variant regions contribute to the nucleotide diversity in virus populations and hence play a vital role in their evolution and dynamics. One of the main parameters indicative of nucleotide diversity is the comparison of synonymous to non-synonymous codon substitution. Synonymous mutations result in neutral substitution, which enable in maintaining the phenotype, as compared to non-synonymous substitutions, which lead to amino acid alteration and hence may affect phenotype.
It is interesting to note that the existence of overlapping reading frames in viruses often constrains synonymous substitutions. Hence, computation of the magnitude of synonymous and non-synonymous polymorphism within viral populations will provide a handle to assess the role of neutral evolution and genetic drift in viral evolution. A more detailed discussion of the role of these substitution ratios in adaptive evolution of viruses is given in Section 4. Tools like SNPgenie [ 26 ] and VirVarSeq [ 27 ] have been developed with a focus on calling SNPs from pooled viral samples by including codon information in an explicit manner and hence are more sensitive than traditional SNP callers [ 28 , 29 ].
De novo assembly Preprocessed reads are assembled using de novo approaches, when a closely related homologue is unavailable to serve as a reference. It should be mentioned that genome assembly is computationally challenging and also requires trained manpower.
Sequencing depth plays a major role in determining the quality of the assembly as does the length of the reads. Popularly used assemblers are based on de Bruijin graph approach in which reads are divided into subsequences called k-mers of length k [ 30 ]. The k-mers form the nodes of a graph, which are linked when a k-1mer is shared among them. The overall process requires large amounts of computer memory RAM and specialized compute clusters.
The steps involved in assembly process are: Based on Overlap—Layout—Consensus principle, information stored in scattered reads are used to make contiguous regions termed 'contigs', which are generally devoid of polymorphisms. Using insert information, 'contigs' are combined to form 'scaffolds'. Gaps between contigs are usually filled with nucleotides Ns. Scaffolds in conjunction with synteny and geneorder information are used to build larger scaffolds.
Building a draft genome is an iterative process and involves parameter optimization, and it is advised that more than one type of assembler be used as each of them has been built for a definite purpose and has unique features. The final assembled genome is evaluated on the basis of N50 parameter. N50 is the median of assembled sequence lengths, in which longer sequences are given more weightage.
Mis-assemblies due to wrong orientation of reads and low-complexity regions are, however, not accounted for in N50 parameter and tools like amosvalidate, which combines multiple validation procedures, are recommended [ 31 ]. One of the major limitations of de novo assembly using NGS data is its reporting of large proportion of incorrect recombinants. This arises mainly due to overlapping of short reads of varying quality and coverage, which in turn pave way for the introduction of spurious SNPs, ultimately resulting in artefacts in assembly.
The in silico chimeras thus produced amplify diversity estimation and complicate true recombination detection. Efforts are being made to overcome this issue using probabilistic method, which assumes that true SNPs are under selection pressure and hence co-occur within a haplotype as compared to random SNPs [ 32 ]. Novel approaches are also being introduced with special emphasis on viral metagenomic projects, viz. Hence, de novo assembly has tremendous scope in unravelling the vast virome that has been unaddressed previously and there exists need for development of more efficient assembly algorithms, which will make it more tractable for use by larger scientific community.
Genome databases and resources dedicated to viruses were developed subsequently [ 43 — 47 ].
Lists of useful databases, resources and analysis tools have also been compiled previously [ 13 , 48 ]. Most of these resources archive complete genome sequences, their annotations and derived data such as viral variations, multiple sequence alignments MSAs and phylogenetic trees, to name a few. Some of the viral genome resources are briefly described below. It attempts to curate reference genome sequences and leverages on the knowledge of experts to annotate as well as to identify important viral sequences.
The objective of the resource is to link textbook knowledge, fact sheets and images to the genomic and proteomic data with an objective to facilitate the study of viral diversity [ 50 ]. The database currently provides access to molecular data of viruses including complete genomes of 14 viral families.
Analytical and visualization tools for metadata-driven statistical sequence analysis, data filtering, analytical workflows and utility of personal workbench are provided to the users. Such annotations will be highly useful in subsequent analysis and model building. The challenges of managing dedicated resources for viral genomes are relatively different as compared to the genomic databases of model and other organisms. The pace of sequencing and the quantum of genomic data being generated are affecting identification of reference genomes and annotations of genomes of strains and isolates.
Additionally, to study the spatio-temporal evolution and to model the viral populations, it is desirable to tag metadata such as the place and date of isolation of viruses with the corresponding genomic entries.
While understanding the sequence—structure—function relationships, it has also resulted in the development of new areas of research such as phyloinformatics and immunoinformatics, which translates raw data into information. The information generated from these independent yet interlinked areas, when put together fits as pieces of jigsaw puzzle Figure 1 , leading to an improved understanding of the viral diseases and, thereby, the development of antiviral therapies.
Figure 1. Scope of research in virology enabled and augmented due to availability of NGS data. Unravelling mutational landscapes in viral quasispecies Viral quasispecies are mutant swarms generated mainly by RNA viruses during replication, which is known to be error-prone due to the lack of proofreading activity of RNA-dependent RNA polymerase.
The resulting mosaic is a dynamic distribution of non-identical but related replicons that cannot be detected using conventional sequencing approaches. Hence, quasispecies remained unexplored for a considerable time, even though the theoretical concept for quasispecies was put forth by Eigen in [ 55 ].
With the advent of NGS technologies, the generation of large genomic datasets became a reality. Due to the sequencing error issues, it was still tough to demarcate true genetic variations. Circular Sequencing CirSeq , a novel experimental approach that creates template of tandem repeats of circularized genomic RNA fragments has been developed by Andino's group [ 56 ]. CirSeq reduces the sequencing error drastically as the repeats get sequenced in a redundant manner for every genomic fragment.
Medical Virology 9
CirSeq was employed to study seven serial passages of Poliovirus replicated in HeLa cells. Mutation frequency was computed for every passage and their fitness was determined by mapping onto the 3D structure of proteins. As expected, majority of the mutations detected were neutral substitutions, thus highlighting robustness as driving force for adaptation and evolution [ 56 ].
This study clearly delineates the viral mutations responsible for quasispecies structure and highlights the extent of genetic variation that can be maintained in a population.
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Microevolution in an evolving quasispecies population is responsible for the sequence diversity in Porcine reproductive and respiratory syndrome virus PRRSV. PRRSV is the causative agent of late-term reproductive failure in sows and respiratory distress in pigs and hence has large economic impact.
Genomic complexity of PRRSV due to multiple circulating genotypes results in antigenic diversity, which, in turn, is responsible for lack of effective vaccine development [ 57 ]. Sanger sequencing has identified open reading frames ORF5 and ORF7 as the polymorphic regions of the virus genome, encoding major immunogenic epitopes.
By analysing nucleotide substitutions over time followed by comparative genomics with non-pathogenic variants, the role of mutation and selection in preserving the pathogenesis or fitness of PRRSV was well documented in this study. Minority quasispecies refers to the memory genomes that were dominant at an earlier phase of quasispecies evolution and can play an important role in conferring drug resistance in viruses such as Human Immunodeficiency Virus type-1 HIV-1 and Influenza virus.
Minority quasispecies of drug-resistant viruses can rapidly re-emerge as major populations after the reintroduction of drug pressure. In case of HIV-1, presence of such low-frequency variants has been linked with early failure to the antiretroviral therapy [ 59 , 60 ]. Emergence of highly pathogenic subtype of Avian Influenza viruses HPAI has also been explained on the basis of low-frequency variants.
Inter- and intra-host genetic diversity The rate of viral evolution and the effectiveness of its transmission are determined by inter- and intra-host genetic diversity.
Mutation rate and selection pressure ascertain viral diversity. Factors like mixed infections and random processes such as genetic drift and population bottlenecks also contribute to the genetic diversity of viruses both within and among hosts.
Transmission fitness influences the effective spread of viruses and is responsible for its stable maintenance in the environment [ 62 ]. Population bottlenecks were investigated for this aphid-borne virus and are thought to occur during both inter-host vector transmission and systemic movement within an individual plant.
ZYMV populations infecting cucumbers with and without vector were sequenced followed by de novo assembly and variant calling. Analysis revealed that the low-frequency mutants present in the initial population got fixed rapidly in vector-transmitted viruses, whereas the same continued to remain as minor variants in mechanically inoculated viruses. In addition, regions known to be responsible for vector transmission were conserved in all samples.
It is interesting to know that previous studies using Sanger sequencing of the coat protein of ZYMV, which is involved in interaction with aphids, could not detect mutations when transmitted between or within plants.
Such studies provide an insight into the complex dynamics of genetic diversity of an emerging viral infection with implications in disease management. Metagenomics involves sequencing of samples from diverse environments spanning across the biosphere [ 64 ]. The initial attempts at characterizing the viral metagenomes were more of an enumeration nature [ 65 ] and provided a glimpse of the enormous diversity underlying the previously unculturable communities.
NGS has paved way for extensive characterization of the functional role of virome in hosts harbouring them [ 66 , 67 ]. Two major methods based on 'sequence-similarity' and 'sequence composition' are usually used for categorization of samples in metagenomics. In a major study involving analysis of dsDNA viruses from 43 ocean samples obtained from across the globe revealed several intriguing observations [ 69 ]. Genes shared across different samples were used as 'core genes' for comparison.
As viruses rely on the host machinery to replicate, a direct relationship was observed between the community structures of both viruses and hosts. Environmental factors like salinity also influenced the viral persistence and hence their diversity.
Technological advances in viral metagenomics would help to unravel the underlying rules of viral evolution and ecology, the so-called 'Genomic rulebook of viruses' [ 70 ]. Genotype—phenotype correlation studies 3. Receptor switching A key event during any viral infection is the interaction of viruses with the host receptors on the plasma membrane.
This serves as an entry point for viruses to access resources of the host cell and is very crucial for tropism. This interaction is known to be very specific and is responsible for activation of the signalling processes that recruit cellular machinery of the host for viral replication.
The specificity of receptor binding defines host range that a virus can infect and the extent of tissue tropism that a virus can display. HIV-1 enters the target host cell by binding to CD4 receptor along with a co-receptor in majority of cases, chemokine C-C motif receptor 5 CCR5 using its spike protein. However, due to the low resolution of these procedures, this transition could not be captured effectively. NGS of the variable loop region V3 of the envelope gene containing determinants of co-receptor usage revealed the stepwise mutational pathway involved in the transition from CCR5 to CXCR4 [ 71 ].
The observation of the low-frequency intermediate variants provided an insight into the fitness landscape of HIV-1 and provided clues to tackle the disease progression in a rational manner. The amino acid changes in haemagglutinin protein GE and GN were observed to be associated with the immune escape [ 72 ].
Bioinformatics methods for viral genomics Bioinformatics approaches help to estimate and analyse population diversity by studying genetic recombination, mutation, selection and, thereby, assist in correlation of genotype to phenotype. The methods relevant to these aspects are discussed below with emphasis on the analysis of viral populations.
Methods for quasispecies reconstruction Quasispecies reconstruction refers to the estimation of number of viral variants and their frequency. Each viral variant in a quasispecies is considered as a haplotype.
It can detect viral haplotypes with frequencies as low as 0. It performs pairwise alignment of all reads to the reference sequence and generates a multiple sequence alignment MSA.
Error correction local haplotype reconstruction : Using MSA as a starting point, a set of overlapping windows is analysed by employing a model-based probabilistic clustering algorithm to obtain i haplotype sequences, ii their frequencies, iii corrected reads and iv posterior probability of the reconstruction.
Global haplotype reconstruction: The set of corrected reads is analysed under parsimony principle, which results in identification of set of unique reads of maximum length. Frequency estimation: Using maximum likelihood ML and expectation maximization algorithm, the frequencies of the reconstructed haplotypes are estimated.
Algorithm steps: Overlaps between the reference genome and reads are generated in terms of k-mers.
Mapping of k-mers is then carried out to obtain genomic co-ordinates. Generates a multinomial distribution based on the alignment scores of true matches along with the matches with randomly shuffled reads.
Coverage, nucleotide content and entropy of each mapped genomic position are then calculated.
Medical Virology 9
Errors are corrected based on Poisson distribution model, parameterized differently for homopolymeric and non-homopolymeric regions. Reconstruction of quasispecies is carried out using the sliding window approach by calculating maximal coverage and read diversity, which reduces the false positives, i. QuasiRecomb Principle: It employs the jumping Hidden Markov Model HMM -based probabilistic statistics for inference of viral quasispecies, especially for estimating the intra-patient viral haplotype distribution [ 75 ].
This method assumes that the true genetic diversity is generated by a few sequences called generators through mutation and recombination, and that the observed diversity results from additional sequencing errors. Algorithm steps: Distribution of haplotypes in a given population is modelled to account for either point mutation or recombination in the form of probability tables and jumping HMM states respectively. Expectation maximization algorithm is used to estimate posterior probabilities associated with rare events of mutation and recombination.The description and characteristics of viral antigens are covered.
It involves sequential disassembly of the identified recombinant sequences into respective components and iteratively rescanning the resulting expanded dataset until no further recombination signals are evident.
This book covers various aspects of Molecular Virology. It also provides up-to-date reference material for students entering the field of structural virology as well as scientists already familiar with the area. This book provides a collection of in depth reviews broadly related to the mechanisms of viral replication as applied to various viruses of critical relevance for human or animal disease.
Recombination analysis is likely to fail in case of poor alignments, if recombinant sequences are used as reference and sequences having ambiguous characters are included.
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