VICTOR: genome-based phylogeny and classification of prokaryotic viruses

Jan P. Meier‐Kolthoff, Markus Göker

Bioinformatics · 2017 · 676 citations · 49 references

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TL;DR

Bacterial and archaeal viruses play key roles in global biogeochemical cycles and hold promise as therapeutic agents against multi‑resistant pathogens. The study aims to develop a fast, universal, and accurate genome‑based taxonomic classification system for prokaryotic viruses. An in silico framework was built using a large reference set of officially classified viruses and phylogenetic systematics principles. The resulting phylogenetic trees show high agreement with existing taxonomy, support most taxa as monophyletic, reveal numerous novel species and higher‑level taxa, and are accessible via the VICTOR web service. Supplementary data are available online at Bioinformatics.

Abstract

Abstract Motivation Bacterial and archaeal viruses are crucial for global biogeochemical cycles and might well be game-changing therapeutic agents in the fight against multi-resistant pathogens. Nevertheless, it is still unclear how to best use genome sequence data for a fast, universal and accurate taxonomic classification of such viruses. Results We here present a novel in silico framework for phylogeny and classification of prokaryotic viruses, in line with the principles of phylogenetic systematics, and using a large reference dataset of officially classified viruses. The resulting trees revealed a high agreement with the classification. Except for low resolution at the family level, the majority of taxa was well supported as monophyletic. Clusters obtained with distance thresholds chosen for maximizing taxonomic agreement appeared phylogenetically reasonable, too. Analysis of an expanded dataset, containing >4000 genomes from public databases, revealed a large number of novel species, genera, subfamilies and families. Availability and implementation The selected methods are available as the easy-to-use web service ‘VICTOR’ at https://victor.dsmz.de. Supplementary information Supplementary data are available at Bioinformatics online.

References

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