tetano
Editor, Senior Moderator
Sci Rep
. 2024 Nov 15;14(1):28227.
doi: 10.1038/s41598-024-79254-w. Rapid detection of the SARS-CoV-2 omicron variants based on high-resolution melting curve analysis
Yue Cheng[SUP] #[/SUP][SUP] 1 2 [/SUP], Yuzhen Zhou[SUP] #[/SUP][SUP] 1 2 [/SUP], Yuezhu Chen[SUP] 1 2 [/SUP], Wenjun Xie[SUP] 1 2 [/SUP], Jiantong Meng[SUP] 1 2 [/SUP], Danyun Shen[SUP] 1 2 [/SUP], Xun He[SUP] 1 2 [/SUP], Heng Chen[SUP] 3 4 [/SUP]
Affiliations
With the continuous spread of the SARS-CoV-2 globally, viral mutations have accumulated. As a result, SARS-CoV-2 became more contagious, and has a higher risk of immune escape and reinfection. To identify variants and have an awareness of the prevalence of these variants, this study selected four segments containing mutations on the S gene of the SARS-CoV-2. Then a rapid and convenient variants detection method was established using high-resolution melting(HRM) analysis combined with nested polymerase chain reaction(PCR). The total detection process takes about 5 h. Through comprehensive analysis of the results from the four reaction systems, the identification of seven important Omicron variants(BA.2, BA.2.75, BA.5.2, BF.7, BQ.1, XBB.1 and XBB.2) can be achieved, with significant differentiation in the melting curves of each variant group. The method established in this study was used to genotype positive specimens in COVID-19 nucleic acid testing, the overall concordance rate compared to whole genome sequencing results was 88.9%, and the positive concordance rate of each sublineage was greater than 80% and the negative concordance rate was greater than 94.4%. The detection of clinical specimens has demonstrated that the HRM analysis established in this study is an effective, rapid and convenient variant identification method, which can be used for monitoring SARS-CoV-2 variants and has important value in addressing public health issues caused by the ongoing mutations of the SARS-CoV-2.
Keywords: HRM Analysis; Omicron; SARS-CoV-2; Variant detection.
. 2024 Nov 15;14(1):28227.
doi: 10.1038/s41598-024-79254-w. Rapid detection of the SARS-CoV-2 omicron variants based on high-resolution melting curve analysis
Yue Cheng[SUP] #[/SUP][SUP] 1 2 [/SUP], Yuzhen Zhou[SUP] #[/SUP][SUP] 1 2 [/SUP], Yuezhu Chen[SUP] 1 2 [/SUP], Wenjun Xie[SUP] 1 2 [/SUP], Jiantong Meng[SUP] 1 2 [/SUP], Danyun Shen[SUP] 1 2 [/SUP], Xun He[SUP] 1 2 [/SUP], Heng Chen[SUP] 3 4 [/SUP]
Affiliations
- PMID: 39548282
- PMCID: PMC11568129
- DOI: 10.1038/s41598-024-79254-w
With the continuous spread of the SARS-CoV-2 globally, viral mutations have accumulated. As a result, SARS-CoV-2 became more contagious, and has a higher risk of immune escape and reinfection. To identify variants and have an awareness of the prevalence of these variants, this study selected four segments containing mutations on the S gene of the SARS-CoV-2. Then a rapid and convenient variants detection method was established using high-resolution melting(HRM) analysis combined with nested polymerase chain reaction(PCR). The total detection process takes about 5 h. Through comprehensive analysis of the results from the four reaction systems, the identification of seven important Omicron variants(BA.2, BA.2.75, BA.5.2, BF.7, BQ.1, XBB.1 and XBB.2) can be achieved, with significant differentiation in the melting curves of each variant group. The method established in this study was used to genotype positive specimens in COVID-19 nucleic acid testing, the overall concordance rate compared to whole genome sequencing results was 88.9%, and the positive concordance rate of each sublineage was greater than 80% and the negative concordance rate was greater than 94.4%. The detection of clinical specimens has demonstrated that the HRM analysis established in this study is an effective, rapid and convenient variant identification method, which can be used for monitoring SARS-CoV-2 variants and has important value in addressing public health issues caused by the ongoing mutations of the SARS-CoV-2.
Keywords: HRM Analysis; Omicron; SARS-CoV-2; Variant detection.