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Single virus genomics: a new tool for virus discovery.

ABSTRACT: Whole genome amplification and sequencing of single microbial cells has significantly influenced genomics and microbial ecology by facilitating direct recovery of reference genome data. However, viral genomics continues to suffer due to difficulties related to the isolation and characterization of uncultivated viruses. We report here on a new approach called 'Single Virus Genomics', which enabled the isolation and complete genome sequencing of the first single virus particle. A mixed assemblage comprised of two known viruses; E. coli bacteriophages lambda and T4, were sorted using flow cytometric methods and subsequently immobilized in an agarose matrix. Genome amplification was then achieved in situ via multiple displacement amplification (MDA). The complete lambda phage genome was recovered with an average depth of coverage of approximately 437X. The isolation and genome sequencing of uncultivated viruses using Single Virus Genomics approaches will enable researchers to address questions about viral diversity, evolution, adaptation and ecology that were previously unattainable.

SUBMITTER: Allen LZ

PROVIDER: S-EPMC3059205 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Single virus genomics: a new tool for virus discovery.

Allen Lisa Zeigler LZ Ishoey Thomas T Novotny Mark A MA McLean Jeffrey S JS Lasken Roger S RS Williamson Shannon J SJ

PloS one 20110323 3

Whole genome amplification and sequencing of single microbial cells has significantly influenced genomics and microbial ecology by facilitating direct recovery of reference genome data. However, viral genomics continues to suffer due to difficulties related to the isolation and characterization of uncultivated viruses. We report here on a new approach called 'Single Virus Genomics', which enabled the isolation and complete genome sequencing of the first single virus particle. A mixed assemblage ...[more]

PMID: 21436882

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Project description:BackgroundLarge amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity.ResultsatBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis.ConclusionatBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

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Single virus genomics: a new tool for virus discovery.

Publications

Single virus genomics: a new tool for virus discovery.

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