Host prediction for disease-associated gastrointestinal cressdnaviruses

作者：Cormac M. Kinsella, Martin Deijs, Christin Becker, Patricia Broekhuizen, Tom van Gool, Aldert Bart, Arne S. Schäefer, Lia van der Hoek · 发表于：Virus Evolution · 年份：2022 · DOI：10.1093/ve/veac087 · 被引用次数：23 · 研究领域：Bacteriophages and microbial interactions、Animal Virus Infections Studies、Viral gastroenteritis research and epidemiology

Abstract Metagenomic techniques have facilitated the discovery of thousands of viruses, yet because samples are often highly biodiverse, fundamental data on the specific cellular hosts are usually missing. Numerous gastrointestinal viruses linked to human or animal diseases are affected by this, preventing research into their medical or veterinary importance. Here, we developed a computational workflow for the prediction of viral hosts from complex metagenomic datasets. We applied it to seven lineages of gastrointestinal cressdnaviruses using 1,124 metagenomic datasets, predicting hosts of four lineages. The Redondoviridae, strongly associated to human gum disease (periodontitis), were predicted to infect Entamoeba gingivalis, an oral pathogen itself involved in periodontitis. The Kirkoviridae, originally linked to fatal equine disease, were predicted to infect a variety of parabasalid protists, including Dientamoeba fragilis in humans. Two viral lineages observed in human diarrhoeal disease (CRESSV1 and CRESSV19, i.e. pecoviruses and hudisaviruses) were predicted to infect Blastocystis spp. and Endolimax nana respectively, protists responsible for millions of annual human infections. Our prediction approach is adaptable to any virus lineage and requires neither training datasets nor host genome assemblies. Two host predictions (for the Kirkoviridae and CRESSV1 lineages) could be independently confirmed as virus–host relationships using endogenous viral elements identified in...