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Monitoring the SARS-CoV-2 pandemic: screening algorithm with single nucleotide polymorphism detection for the rapid identification of established and emerging variants.
- Source :
-
Clinical Microbiology & Infection . Jan2022, Vol. 28 Issue 1, p124-129. 6p. - Publication Year :
- 2022
-
Abstract
- To evaluate a testing algorithm for the rapid identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that includes the use of PCR-based targeted single nucleotide polymorphism (SNP) detection assays preceded by a multiplex PCR sensitive to S -Gene Target Failure (SGTF). PCR SNP assays targeting SARS-CoV-2 S -gene mutations ΔH69–V70, L452R, E484K, N501Y, H655Y and P681R using melting curve analysis were performed on 567 samples in which SARS-CoV-2 viral RNA was detected by a multiplex PCR. Viral whole-genome sequencing (WGS) was performed to confirm the presence of SNPs and to identify the Pangolin lineage. Additionally, 1133 SARS-CoV-2 positive samples with SGTF were further assessed by WGS to determine the presence of ΔH69–V70. The N501Y-specific assay (n = 567) had an overall percentage agreement (OPA) of 98.5%. The ΔH69-V70-specific (n = 178) and E484K-specific (n = 401) assays had OPA of 96.6% and 99.7%, respectively. Assessment of H655Y (n = 139) yielded a 100.0% concordance when applied in the proposed algorithm. The L452R-specific (n = 67) and P681R-specific (n = 62) assays had an OPA of 98.2% and 98.1%, respectively. The proposed algorithm identified six variants of concern/interest (VOC/VOI)—Alpha (n = 149), Beta (n = 65), Gamma (n = 86), Delta (n = 49), Eta (n = 6), Kappa (n = 6)—and 205 non-VOC/VOI strains—including the variants under monitoring B.1.214.2 (n = 43) and B.1.1.318 (n = 18) and Epsilon (n = 1). An excellent concordance was observed for the identification of all SARS-CoV-2 lineages evaluated. We present a flexible testing algorithm for the rapid detection of current and emerging SARS-CoV-2 VOC/VOIs, which can be easily adapted based on the local endemicity of specific variants. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1198743X
- Volume :
- 28
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Clinical Microbiology & Infection
- Publication Type :
- Academic Journal
- Accession number :
- 154216147
- Full Text :
- https://doi.org/10.1016/j.cmi.2021.09.007