The enigma of picobirnaviruses: viruses of animals, fungi, or bacteria?


Journal

Current opinion in virology
ISSN: 1879-6265
Titre abrégé: Curr Opin Virol
Pays: Netherlands
ID NLM: 101560941

Informations de publication

Date de publication:
06 2022
Historique:
received: 07 03 2022
revised: 23 04 2022
accepted: 25 04 2022
pubmed: 2 6 2022
medline: 15 6 2022
entrez: 1 6 2022
Statut: ppublish

Résumé

Picobirnaviruses are small double-stranded RNA viruses first discovered in 1988 in stool samples from patients with diarrhea. It has generally been assumed that picobirnaviruses infect animal hosts and that they are potential agents of diarrhea, but there is still no direct evidence demonstrating that picobirnaviruses infect animals. In the metagenomic era, virome studies have broadened our understanding of picobirnavirus genetic diversity and genome organization, expanded the types of animals in which they have been detected, and identified novel associations with human disease. Most importantly, from the wealth of new sequencing data and comparative genomic analyses, a provocative new hypothesis has emerged that picobirnaviruses may not infect animals, but rather that they may infect evolutionarily simpler denizens of the gastrointestinal tract: bacteria and/or fungi. Depending on whether the true hosts of picobirnaviruses are animals, fungi, or bacteria, the mechanisms by which they impact animal biology will vary dramatically.

Identifiants

pubmed: 35644066
pii: S1879-6257(22)00041-4
doi: 10.1016/j.coviro.2022.101232
pii:
doi:

Types de publication

Journal Article Review Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

101232

Informations de copyright

Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.

Auteurs

David Wang (D)

Departments of Molecular Microbiology and Pathology & Immunology, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave., Campus Box 8230, St. Louis, MO 63110, USA. Electronic address: davewang@wustl.edu.

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Classifications MeSH