Studies over the past decade have revealed a role for the gut microbiome in host health and disease. Until recently, most studies have focused on commensal bacteria and not as much on other microorganisms, such as fungi, archaea and viruses1. Current work points to a vital role of the gut virome in host health as a critical modulator of the bacterial diversity within the gut. Discrepancies in and the depth of current viral databases make the study of bacteria–virus and host–virus interactions in the gastrointestinal context difficult. Reporting in Cell Host & Microbe in 2020, Gregory et al. curated a comprehensive human gut virome database, the Gut Virome Database (GVD), and performed bioinformatics analyses to determine the different patterns of virome diversity of the gut during the human lifespan. Viromics is a fast-growing field, so we wanted to highlight how bioinformatic approaches can enable better understanding of the gut virome and its relationship to human health and disease. Gregory et al. presented a comparative study of public databases for virus and virus-like-particle classification, and identified, for the first time, that the human gut virome changes during the human lifespan. Furthermore, the authors present key findings about the gut virome, such as the proportional increase of crAssphage populations from adults to elderly individuals due to their territorial expansion in the gut.
The authors assembled the GVD by collating 2,697 metagenomics samples from 1,986 individuals, reported in 32 studies. Sequence data were from a variety of studies, including analyses of the gut virome of healthy infants and adults, and of the gut virome of individuals with Clostridium difficile infection and faecal microbiota transplant for autism, malnutrition, type 1 and 2 diabetes, human immunodeficiency virus, inflammatory bowel disease, hypertension and chronic fatigue syndrome. To curate the GVD, datasets were recovered from a pool of virus-like particles and whole microbial community (bulk) metagenomes, and reprocessed to identify the viral sequences. Gregory et al. used putative viral contigs assembled using metaSPAdes and cleaned using VirSorter and VirFinder pipelines, followed by viral taxonomic classification, which was assigned using the vConTACT2 pipeline. The authors applied bioinformatics approaches based on percentage similarity for microbial host prediction and identified 57,605 viral contigs and 33,242 viral populations.
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