Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks

By Ho Bin Jang, Ben Bolduc, Olivier Zablocki, J. Kuhn, Simon Roux, Evelien M. Adriaenssens, J. R. Brister, Andrew Kropinski, M. Krupovic, Rob Lavigne and 2 more. Nature Biotechnology, 2019

825 citations recorded by the source corpus.

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.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/74a320c7257b9e0539d6ee1171b4a37a960da2cc

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Citations in the corpus

• The human gut virome is highly diverse, stable and individual-specific (2019, methodology): “In the absence of a viral taxonomy framework that supports metagenomic data, de 71 novo sequence clustering approaches such as vConTACT2 (Jang et al., 2019) offer a 72 promising solution by grouping viral sequences across samples, facilitating the analysis of 73 virome dynamics across individuals an”
• INfrastructure for a PHAge REference Database: Identification of Large-Scale Biases in the Current Collection of Cultured Phage Genomes (2021, neutral): “A prebuilt database (https://doi.org/10.25392/leices ter.data.14242085) is provided so gene calling only occurs on newly deposited genomes.”