Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks
Microbiomes from every environment contain a myriad of uncultivated archaeal and bacterial viruses, but studying these viruses is hampered by the lack of a universal, scalable taxonomic framework. We present vConTACT v.2.0, a network-based application utilizing whole genome gene-sharing profiles for...
Saved in:
Published in | Nature biotechnology Vol. 37; no. 6; pp. 632 - 639 |
---|---|
Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.06.2019
Nature Publishing Group Springer Nature |
Subjects | |
Online Access | Get full text |
ISSN | 1087-0156 1546-1696 1546-1696 |
DOI | 10.1038/s41587-019-0100-8 |
Cover
Summary: | Microbiomes from every environment contain a myriad of uncultivated archaeal and bacterial viruses, but studying these viruses is hampered by the lack of a universal, scalable taxonomic framework. We present vConTACT v.2.0, a network-based application utilizing whole genome gene-sharing profiles for virus taxonomy that integrates distance-based hierarchical clustering and confidence scores for all taxonomic predictions. We report near-identical (96%) replication of existing genus-level viral taxonomy assignments from the International Committee on Taxonomy of Viruses for National Center for Biotechnology Information virus RefSeq. Application of vConTACT v.2.0 to 1,364 previously unclassified viruses deposited in virus RefSeq as reference genomes produced automatic, high-confidence genus assignments for 820 of the 1,364. We applied vConTACT v.2.0 to analyze 15,280 Global Ocean Virome genome fragments and were able to provide taxonomic assignments for 31% of these data, which shows that our algorithm is scalable to very large metagenomic datasets. Our taxonomy tool can be automated and applied to metagenomes from any environment for virus classification.
Classification of archaeal and bacterial viruses can be automated with an algorithm that identifies relationships on the basis of shared gene content. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 AC02-05CH11231; HHSN272200700016I; AC52-07NA27344 US National Institute of Allergy and Infectious Diseases (NIAID USDOE Office of Science (SC), Biological and Environmental Research (BER) |
ISSN: | 1087-0156 1546-1696 1546-1696 |
DOI: | 10.1038/s41587-019-0100-8 |