Predicting mammalian hosts in which novel coronaviruses can be generated.

Wardeh, Maya ORCID: 0000-0002-2316-5460, Baylis, Matthew ORCID: 0000-0003-0335-187X and Blagrove, Marcus SC ORCID: 0000-0002-7510-167X (2021) Predicting mammalian hosts in which novel coronaviruses can be generated. Nature Communications, 12 (1). p. 780.

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Official URL: http://dx.doi.org/10.1038/s41467-021-21034-5

Abstract

Novel pathogenic coronaviruses - such as SARS-CoV and probably SARS-CoV-2 - arise by homologous recombination between co-infecting viruses in a single cell. Identifying possible sources of novel coronaviruses therefore requires identifying hosts of multiple coronaviruses; however, most coronavirus-host interactions remain unknown. Here, by deploying a meta-ensemble of similarity learners from three complementary perspectives (viral, mammalian and network), we predict which mammals are hosts of multiple coronaviruses. We predict that there are 11.5-fold more coronavirus-host associations, over 30-fold more potential SARS-CoV-2 recombination hosts, and over 40-fold more host species with four or more different subgenera of coronaviruses than have been observed to date at >0.5 mean probability cut-off (2.4-, 4.25- and 9-fold, respectively, at >0.9821). Our results demonstrate the large underappreciation of the potential scale of novel coronavirus generation in wild and domesticated animals. We identify high-risk species for coronavirus surveillance.

Item Type:	Article
Uncontrolled Keywords:	Animals, Mammals, Humans, Coronavirus, Coronavirus Infections, Reproducibility of Results, Phylogeny, Recombination, Genetic, Models, Biological, Host-Pathogen Interactions
Depositing User:	Symplectic Admin
Date Deposited:	03 Mar 2021 11:31
Last Modified:	18 Jan 2023 22:57
DOI:	10.1038/s41467-021-21034-5
Open Access URL:	http://doi.org/10.1038/s41467-021-21034-5
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3116448