Predicting mammalian hosts in which novel coronaviruses can be generated.
Nat Commun
; 12(1): 780, 2021 02 16.
Article
in English
| MEDLINE | ID: covidwho-1087442
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Coronavirus
/
Host-Pathogen Interactions
/
Mammals
Type of study:
Prognostic study
/
Randomized controlled trials
/
Reviews
Limits:
Animals
/
Humans
Language:
English
Journal:
Nat Commun
Journal subject:
Biology
/
Science
Year:
2021
Document Type:
Article
Affiliation country:
S41467-021-21034-5
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