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Development of highly adaptable RT-PCR methods for identifying Delta and BA.1 variants in inactivated COVID-19 vaccines.

Authors :
Wang, Zhanhui
He, Yao
He, Zhenyu
Guo, Yancen
Zhao, Yuxiu
Zhang, Yuntao
Source :
Molecular Biology Reports; 8/7/2024, Vol. 51 Issue 1, p1-11, 11p
Publication Year :
2024

Abstract

Background The emergence and rapid spread of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), poses a significant threat to human health and public safety. While next-generation sequencing (NGS) is capable of detecting and tracking new COVID-19 variants for disease diagnosis and prevention, its high cost and time-consuming nature limit its widespread use. In this study, our aim was to develop a highly adaptable and accurate RT-PCR method for identifying the Delta or BA.1 variants in inactivated COVID-19 vaccine. We devised three two-plex RT-PCR methods targeting specific mutation sites: S: Δ156–157, S: N211-, L212I, and S: Δ142–144, Y145D. The RT-PCR method targeting the S: Δ156–157 mutation site was able to distinguish the Delta variant from other COVID-19 virus strains, while the RT-PCR methods targeting the S: N211-, L212I or S: Δ142–144, Y145D mutation sites were able to distinguish the BA.1 variant from other COVID-19 virus strains. We separately validated these three two-plex RT-PCR methods, and the results demonstrated good linearity, repeatability, reproducibility, and specificity for each method. Moreover, all three methods can be applied in the production of SARS-CoV-2 variant inactivated vaccines, enabling the identification of Delta or BA.1 variants in virus cultures as well as in inactivated vaccine stocks. This study presents a systematic approach to identify COVID-19 variants using multiple RT-PCR methods. We successfully developed three two-plex RT-PCR methods that can identify Delta and BA.1 variants based on specific mutation sites, and we completed the validation of these three methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03014851
Volume :
51
Issue :
1
Database :
Complementary Index
Journal :
Molecular Biology Reports
Publication Type :
Academic Journal
Accession number :
178878146
Full Text :
https://doi.org/10.1007/s11033-024-09799-6