» Articles » PMID: 35871556

The Mutation Features and Geographical Distributions of the Surface Glycoprotein (S Gene) in SARS-CoV-2 Strains: A Comparative Analysis of the Early and Current Strains

Overview
Journal J Med Virol
Specialty Microbiology
Date 2022 Jul 24
PMID 35871556
Authors
Affiliations
Soon will be listed here.
Abstract

The surface glycoprotein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was used to develop coronavirus disease 2019 (COVID-19) vaccines. However, SARS-CoV-2, especially the S protein, has undergone rapid evolution and mutation, which has remained to be determined. Here, we analyzed and compared the early (12 237) and the current (more than 10 million) SARS-CoV-2 strains to identify the mutation features and geographical distribution of the S gene and S protein. Results showed that in the early strains, most of the loci were with relative low mutation frequency except S: 23403 (4486 strains), while in the current strains, there was a surge in the mutation strains and frequency, with S: 23403 constantly being the highest one, but tremendously increased to approximately 1050 times. Furthermore, D614 (S: 23403) was one of the most highly frequent mutations in the S protein of Omicron as of March 2022, and most of the mutant strains were still from the United States, and the United Kingdom. Further analysis demonstrated that in the receptor-binding domain, most of the loci with low mutation frequency in the early strains, while S: 22995 was nowadays the most prevalent loci with 3 122 491 strains in the current strains. Overall, we compare the mutation features of the S region in SARS-CoV-2 strains between the early and the current stains, providing insight into further studies in concert with emerging SARS-CoV-2 variants for COVID-19 vaccines.

Citing Articles

The mutation features and geographical distributions of the surface glycoprotein (S gene) in SARS-CoV-2 strains: A comparative analysis of the early and current strains.

Liu R, Lin X, Chen B, Hou Z, Zhang Q, Lin S J Med Virol. 2022; 94(11):5363-5374.

PMID: 35871556 PMC: 9350160. DOI: 10.1002/jmv.28023.

References
1.
Rose A, Hildebrand P . NGL Viewer: a web application for molecular visualization. Nucleic Acids Res. 2015; 43(W1):W576-9. PMC: 4489237. DOI: 10.1093/nar/gkv402. View

2.
Le T, Andreadakis Z, Kumar A, Roman R, Tollefsen S, Saville M . The COVID-19 vaccine development landscape. Nat Rev Drug Discov. 2020; 19(5):305-306. DOI: 10.1038/d41573-020-00073-5. View

3.
Yong C, Ong H, Yeap S, Ho K, Tan W . Recent Advances in the Vaccine Development Against Middle East Respiratory Syndrome-Coronavirus. Front Microbiol. 2019; 10:1781. PMC: 6688523. DOI: 10.3389/fmicb.2019.01781. View

4.
Altmann D, Boyton R . COVID-19 vaccination: The road ahead. Science. 2022; 375(6585):1127-1132. DOI: 10.1126/science.abn1755. View

5.
Hu Y, Sun Q . A booster with SARS-CoV-2 vaccines: protection against Omicron infection. Signal Transduct Target Ther. 2022; 7(1):115. PMC: 8980504. DOI: 10.1038/s41392-022-00973-5. View