Computational prospecting the great viral unknown

Bonnie L Hurwitz, Jana M. U'Ren, Ken Youens-Clark

Research output: Contribution to journalShort survey

18 Citations (Scopus)

Abstract

Bacteriophages play an important role in host-driven biological processes by controlling bacterial population size, horizontally transferring genes between hosts and expressing host-derived genes to alter host metabolism. Metagenomics provides the genetic basis for understanding the interplay between uncultured bacteria, their phage and the environment. In particular, viral metagenomes (viromes) are providing new insight into phage-encoded host genes (i.e. auxiliary metabolic genes; AMGs) that reprogram host metabolism during infection. Yet, despite deep sequencing efforts of viral communities, the majority of sequences have no match to known proteins. Reference-independent computational techniques, such as protein clustering, contig spectra and ecological profiling are overcoming these barriers to examine both the known and unknown components of viromes. As the field of viral metagenomics progresses, a critical assessment of tools is required as the majority of algorithms have been developed for analyzing bacteria. The aim of this paper is to offer an overview of current computational methodologies for virome analysis and to provide an example of reference-independent approaches using human skin viromes. Additionally, we present methods to carefully validate AMGs from host contamination. Despite computational challenges, these new methods offer novel insights into the diversity and functional roles of phages in diverse environments.

Original languageEnglish (US)
Article numberfnw077
JournalFEMS Microbiology Letters
Volume363
Issue number10
DOIs
StatePublished - May 1 2016

Fingerprint

Bacteriophages
Metagenomics
Genes
Metagenome
Bacteria
Biological Phenomena
High-Throughput Nucleotide Sequencing
Population Density
Cluster Analysis
Proteins
Skin
Infection

Keywords

  • Bacteriophage
  • Bioinformatics
  • Metagenomics
  • Phage
  • Virome
  • Virus

ASJC Scopus subject areas

  • Microbiology
  • Genetics
  • Molecular Biology

Cite this

Computational prospecting the great viral unknown. / Hurwitz, Bonnie L; U'Ren, Jana M.; Youens-Clark, Ken.

In: FEMS Microbiology Letters, Vol. 363, No. 10, fnw077, 01.05.2016.

Research output: Contribution to journalShort survey

Hurwitz, Bonnie L ; U'Ren, Jana M. ; Youens-Clark, Ken. / Computational prospecting the great viral unknown. In: FEMS Microbiology Letters. 2016 ; Vol. 363, No. 10.
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