Sequence variability in clinical and laboratory isolates of herpes simplex virus 1 reveals new mutations.
ABSTRACT Herpes simplex virus 1 (HSV-1) is a well-adapted human pathogen that can invade the peripheral nervous system and persist there as a lifelong latent infection. Despite their ubiquity, only one natural isolate of HSV-1 (strain 17) has been sequenced. Using Illumina high-throughput sequencing of viral DNA, we obtained the genome sequences of both a laboratory strain (F) and a low-passage clinical isolate (H129). These data demonstrated the extent of interstrain variation across the entire genome of HSV-1 in both coding and noncoding regions. We found many amino acid differences distributed across the proteome of the new strain F sequence and the previously known strain 17, demonstrating the spectrum of variability among wild-type HSV-1 proteins. The clinical isolate, strain H129, displays a unique anterograde spread phenotype for which the causal mutations were completely unknown. We have defined the sequence differences in H129 and propose a number of potentially causal genes, including the neurovirulence protein ICP34.5 (RL1). Further studies will be required to demonstrate which change(s) is sufficient to recapitulate the spread defect of strain H129. Unexpectedly, these data also revealed a frameshift mutation in the UL13 kinase in our strain F isolate, demonstrating how deep genome sequencing can reveal the full complement of background mutations in any given strain, particularly those passaged or plaque purified in a laboratory setting. These data increase our knowledge of sequence variation in large DNA viruses and demonstrate the potential of deep sequencing to yield insight into DNA genome evolution and the variation among different pathogen isolates.
Full-textDOI: · Available from: Lynn Enquist, May 30, 2015
SourceAvailable from: Lance R Parsons[Show abstract] [Hide abstract]
ABSTRACT: Herpes simplex virus (HSV) is a widespread pathogen that causes epithelial lesions with recurrent disease that manifests over a lifetime. The lifelong aspect of infection results from latent viral infection of neurons, a reservoir from which the virus reactivates periodically. Recent work has demonstrated the breadth of genetic variation in globally distributed HSV strains. However, the amount of variation or capacity for mutation within one strain has not been well studied. Here we developed and applied a streamlined new approach for assembly and comparison of large DNA viral genomes such as HSV-1. This viral genome assembly (VirGA) workflow incorporates a combination of de novo assembly, alignment, and annotation strategies to automate the generation of draft genomes for large viruses. We applied this approach to quantify the amount of variation between clonal derivatives of a common parental virus stock. In addition, we examined the genetic basis for syncytial plaque phenotypes displayed by a subset of these strains. In each of the syncytial strains, we found an identical DNA change, affecting one residue in the gB (UL27) fusion protein. Since these identical mutations could have appeared after extensive in vitro passaging, we applied the VirGA sequencing and comparison approach to two clinical HSV-1 strains isolated from the same patient. One of these strains was syncytial upon first culturing; its sequence revealed the same gB mutation. These data provide insight into the extent and origin of genome-wide intrastrain HSV-1 variation and present useful methods for expansion to in vivo patient infection studies. Herpes simplex virus (HSV) infects more than 70% of adults worldwide, causing epithelial lesions and recurrent disease that manifests over a lifetime. Prior work has demonstrated that HSV strains vary from country to country and between individuals. However, the amount of variation within one strain has not been well studied. To address this, we developed a new approach for viral genome assembly (VirGA) and analysis. We used this approach to quantify the amount of variation between sister clones of a common parental virus stock and to determine the basis of a unique fusion phenotype displayed by several variants. These data revealed that while sister clones of one HSV stock are more than 98% identical, these variants harbor enough genetic differences to change their observed characteristics. Comparative genomics approaches will allow us to explore the impacts of viral inter- and intrastrain diversity on drug and vaccine efficacy. Copyright © 2015 Parsons et al.mBio 01/2015; 6(2). DOI:10.1128/mBio.02213-14 · 6.88 Impact Factor
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ABSTRACT: Advances in next generation sequencing make it possible to obtain high-coverage sequence data for large numbers of viral strains in a short time. However, since most bioinformatics tools are developed for command line use, the selection and accessibility of computational tools for genome assembly and variation analysis limits the ability of individual labs to perform further bioinformatics analysis. We have developed a multi-step viral genome assembly pipeline named VirAmp, which combines existing tools and techniques and presents them to end users via a web-enabled Galaxy interface. Our pipeline allows users to assemble, analyze, and interpret high coverage viral sequencing data with an ease and efficiency that was not possible previously. Our software makes a large number of genome assembly and related tools available to life scientists and automates the currently recommended best practices into a single, easy to use interface. We tested our pipeline with three different datasets from human herpes simplex virus (HSV). VirAmp provides a user-friendly interface and a complete pipeline for viral genome analysis. We make our software available via an Amazon Elastic Cloud disk image that can be easily launched by anyone with an Amazon web service account. A fully functional demonstration instance of our system can be found at http://viramp.com/. We also maintain detailed documentation on each tool and methodology at http://docs.viramp.com.04/2015; 4(1). DOI:10.1186/s13742-015-0060-y
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ABSTRACT: The development of high-throughput molecular technologies and associated bioinformatics has dramatically changed the capacities of scientists to produce, handle, and analyze large amounts of genomic, transcriptomic, and proteomic data. A clear example of this step-change is represented by the amount of DNA sequence data that can be now produced using next-generation sequencing (NGS) platforms. Similarly, recent improvements in protein and peptide separation efficiencies and highly accurate mass spectrometry have promoted the identification and quantification of proteins in a given sample. These advancements in biotechnology have increasingly been applied to the study of animal infectious diseases and are beginning to revolutionize the way that biological and evolutionary processes can be studied at the molecular level. Studies have demonstrated the value of NGS technologies for molecular characterization, ranging from metagenomic characterization of unknown pathogens or microbial communities to molecular epidemiology and evolution of viral quasispecies. Moreover, high-throughput technologies now allow detailed studies of host-pathogen interactions at the level of their genomes (genomics), transcriptomes (transcriptomics), or proteomes (proteomics). Ultimately, the interaction between pathogen and host biological networks can be questioned by analytically integrating these levels (integrative OMICS and systems biology). The application of high-throughput biotechnology platforms in these fields and their typical low-cost per information content has revolutionized the resolution with which these processes can now be studied.The aim of this chapter is to provide a current and prospective view on the opportunities and challenges associated with the application of massive parallel sequencing technologies to veterinary medicine, with particular focus on applications that have a potential impact on disease control and management.Methods in molecular biology (Clifton, N.J.) 01/2015; 1247:415-36. DOI:10.1007/978-1-4939-2004-4_30 · 1.29 Impact Factor