Genomic determinants of pathogenicity in SARS-CoV-2 and other human coronaviruses
Author(s)
Gussow, Ayal B.; Auslander, Noam; Faure, Guilhem; Wolf, Yuri I.; Zhang, Feng; Koonin, Eugene V.; ... Show more Show less
Download2008176117.full.pdf (2.302Mb)
Publisher Policy
Publisher Policy
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Terms of use
Metadata
Show full item recordAbstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses an immediate, major threat to public health across the globe. Here we report an in-depth molecular analysis to reconstruct the evolutionary origins of the enhanced pathogenicity of SARS-CoV-2 and other coronaviruses that are severe human pathogens. Using integrated comparative genomics and machine learning techniques, we identify key genomic features that differentiate SARS-CoV-2 and the viruses behind the two previous deadly coronavirus outbreaks, SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), from less pathogenic coronaviruses. These features include enhancement of the nuclear localization signals in the nucleocapsid protein and distinct inserts in the spike glycoprotein that appear to be associated with high case fatality rate of these coronaviruses as well as the host switch from animals to humans. The identified features could be crucial contributors to coronavirus pathogenicity and possible targets for diagnostics, prognostication, and interventions.
Date issued
2020-06Department
McGovern Institute for Brain Research at MIT; Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; Massachusetts Institute of Technology. Department of Biological EngineeringJournal
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Citation
Gussow, Ayal B. et al. "Genomic determinants of pathogenicity in SARS-CoV-2 and other human coronaviruses." Proceedings of the National Academy of Sciences (June 2020) © 2020 the Author(s)
Version: Final published version
ISSN
0027-8424
1091-6490