VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences.

Microbiome
Kristopher KieftKarthik Anantharaman

Abstract

Viruses are central to microbial community structure in all environments. The ability to generate large metagenomic assemblies of mixed microbial and viral sequences provides the opportunity to tease apart complex microbiome dynamics, but these analyses are currently limited by the tools available for analyses of viral genomes and assessing their metabolic impacts on microbiomes. Here we present VIBRANT, the first method to utilize a hybrid machine learning and protein similarity approach that is not reliant on sequence features for automated recovery and annotation of viruses, determination of genome quality and completeness, and characterization of viral community function from metagenomic assemblies. VIBRANT uses neural networks of protein signatures and a newly developed v-score metric that circumvents traditional boundaries to maximize identification of lytic viral genomes and integrated proviruses, including highly diverse viruses. VIBRANT highlights viral auxiliary metabolic genes and metabolic pathways, thereby serving as a user-friendly platform for evaluating viral community function. VIBRANT was trained and validated on reference virus datasets as well as microbiome and virome data. VIBRANT showed superior performanc...Continue Reading

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Citations

Jul 17, 2020·FEMS Microbiology Reviews·Christina C SaakRachel J Dutton
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Oct 20, 2020·Nucleic Acids Research·Senying LaiXing-Ming Zhao
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Software Mentioned

VirFinder
Nucmer
p meta
Learn
Bowtie2
CD
Prophage
Scikit
VIBRANT ( Virus Identification By iteRative ANnoTation )
Sickle

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