Article: Antigenic Evolution on a Global Scale Reveals the Potential Natural Selection of Severe Acute Respiratory Syndrome-Coronavirus 2 by Pre-existing Cross-Reactive T-Cell Immunity.
2021 Volume 12, Page(s) 599562
Abstract: The mutation pattern of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has changed ... of SARS-CoV-2 under natural selection, improved our understanding of the evolution of the virus, and ... the structural protein Spike were most susceptible to mutations. Furthermore, mutations in cross-reactive T-cell epitopes ...
| Abstract | The mutation pattern of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has changed constantly during worldwide community transmission of this virus. However, the reasons for the changes in mutation patterns are still unclear. Accordingly, in this study, we present a comprehensive analysis of over 300 million peptides derived from 13,432 SARS-CoV-2 strains harboring 4,420 amino acid mutations to analyze the potential selective pressure of the host immune system and reveal the driver of mutations in circulating SARS-CoV-2 isolates. The results showed that the nonstructural protein ORF1ab and the structural protein Spike were most susceptible to mutations. Furthermore, mutations in cross-reactive T-cell epitopes between SARS-CoV-2 and seasonal human coronavirus may help SARS-CoV-2 to escape cellular immunity under long-term and large-scale community transmission. Additionally, through homology modeling and protein docking, mutations in Spike protein may enhance the ability of SARS-CoV-2 to invade host cells and escape antibody-mediated B-cell immunity. Our research provided insights into the potential mutation patterns of SARS-CoV-2 under natural selection, improved our understanding of the evolution of the virus, and established important guidance for potential vaccine design. |
|---|---|
| Language | English |
| Publishing date | 2021-05-18 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2587354-4 |
| ISSN | 1664-302X |
| ISSN | 1664-302X |
| DOI | 10.3389/fmicb.2021.599562 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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