An Update on Detection Technologies for SARS-CoV-2 Variants of Concern

Viruses. 2022 Oct 22;14(11):2324. doi: 10.3390/v14112324.

Abstract

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is responsible for the global epidemic of Coronavirus Disease 2019 (COVID-19), with a significant impact on the global economy and human safety. Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2, but because the virus's genome is prone to mutations, the effectiveness of vaccines and the sensitivity of detection methods are declining. Variants of concern (VOCs) include Alpha, Beta, Gamma, Delta, and Omicron, which are able to evade recognition by host immune mechanisms leading to increased transmissibility, morbidity, and mortality of COVID-19. A range of research has been reported on detection techniques for VOCs, which is beneficial to prevent the rapid spread of the epidemic, improve the effectiveness of public health and social measures, and reduce the harm to human health and safety. However, a meaningful translation of this that reduces the burden of disease, and delivers a clear and cohesive message to guide daily clinical practice, remains preliminary. Herein, we summarize the capabilities of various nucleic acid and protein-based detection methods developed for VOCs in identifying and differentiating current VOCs and compare the advantages and disadvantages of each method, providing a basis for the rapid detection of VOCs strains and their future variants and the adoption of corresponding preventive and control measures.

Keywords: CRISPR; PCR; SARS-CoV-2; VOCs.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / diagnosis
  • COVID-19* / prevention & control
  • Epidemics*
  • Humans
  • RNA, Viral / analysis
  • RNA, Viral / genetics
  • SARS-CoV-2 / genetics

Substances

  • RNA, Viral

Supplementary concepts

  • SARS-CoV-2 variants

Grants and funding

This work was funded by the National Natural Science Foundation of China grant number 82002147 and 82073618, China Postdoctoral Science Foundation grant number 2019M662543 and Key Scientific Research Project of Henan Institution of Higher Education grant number 20A330004 and 21A310026.