Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses OC43 and 229E
Abstract
Seasonal coronaviruses (OC43, 229E, NL63 and HKU1) are endemic to the human population, regularly infecting and reinfecting humans while typically causing asymptomatic to mild respiratory infections. It is not known to what extent reinfection by these viruses is due to waning immune memory or antigenic drift of the viruses. Here, we address the influence of antigenic drift on immune evasion of seasonal coronaviruses. We provide evidence that at least two of these viruses, OC43 and 229E, are undergoing adaptive evolution in regions of the viral spike protein that are exposed to human humoral immunity. This suggests that reinfection may be due, in part, to positively-selected genetic changes in these viruses that enable them to escape recognition by the immune system. It is possible that, as with seasonal influenza, these adaptive changes in antigenic regions of the virus would necessitate continual reformulation of a vaccine made against them.
Data availability
All data used in this study can be found at https://www.viprbrc.org/ or in the Github repository for this project: https://github.com/blab/seasonal-cov-adaptive-evolution.
Article and author information
Author details
Funding
National Science Foundation (Graduation Research Fellowship Program,DGE-1762114)
- Kathryn E Kistler
Pew Charitable Trusts (Pew Biomedical Scholar,NIH R35 GM119774-01)
- Trevor Bedford
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Daniel B Weissman, Emory University, United States
Version history
- Received: October 31, 2020
- Accepted: December 12, 2020
- Accepted Manuscript published: January 19, 2021 (version 1)
- Version of Record published: February 4, 2021 (version 2)
- Version of Record updated: September 14, 2022 (version 3)
Copyright
© 2021, Kistler & Bedford
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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