Host prediction for disease-associated gastrointestinal cressdnaviruses

Cormac M Kinsella; Martin Deijs; Christin Becker; Patricia Broekhuizen; Tom van Gool; Aldert Bart; Arne S Schaefer; Lia van der Hoek

doi:10.1093/ve/veac087

Host prediction for disease-associated gastrointestinal cressdnaviruses

Virus Evol. 2022 Sep 16;8(2):veac087. doi: 10.1093/ve/veac087. eCollection 2022.

Authors

Cormac M Kinsella^{1

2}, Martin Deijs^{1

2}, Christin Becker³, Patricia Broekhuizen⁴, Tom van Gool^{4

2}, Aldert Bart⁵, Arne S Schaefer³, Lia van der Hoek^{1

2}

Affiliations

¹ Amsterdam UMC, Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands.
² Amsterdam Institute for Infection and Immunity, Postbus 22660, Amsterdam 1100 DD, The Netherlands.
³ Department of Periodontology, Oral Surgery and Oral Medicine, Institute for Dental and Craniofacial Sciences, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
⁴ Amsterdam UMC, Laboratory of Clinical Parasitology, Department of Medical Microbiology and Infection Prevention, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands.
⁵ Department of Medical Microbiology, Tergooi MC, Van Riebeeckweg 212, Hilversum 1213 XZ, The Netherlands.

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 inside host genomes, while a further prediction (for the Redondoviridae) was strongly supported as a virus-host relationship using a case-control screening experiment of human oral plaques.

Keywords: Redondoviridae; cressdnavirus; host identification; metagenomics; periodontitis; protist.