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Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis

Coronavirus disease 2019 (COVID‐19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has recently posed a significant threat to global public health. The objective of this study was to develop and evaluate a rapid, expandable and sequencing‐free high‐resolution melti...

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Autores principales: Sun, Liying, Xiu, Leshan, Zhang, Chi, Xiao, Yan, Li, Yamei, Zhang, Lulu, Ren, Lili, Peng, Junping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111094/
https://www.ncbi.nlm.nih.gov/pubmed/35233932
http://dx.doi.org/10.1111/1751-7915.14027
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author Sun, Liying
Xiu, Leshan
Zhang, Chi
Xiao, Yan
Li, Yamei
Zhang, Lulu
Ren, Lili
Peng, Junping
author_facet Sun, Liying
Xiu, Leshan
Zhang, Chi
Xiao, Yan
Li, Yamei
Zhang, Lulu
Ren, Lili
Peng, Junping
author_sort Sun, Liying
collection PubMed
description Coronavirus disease 2019 (COVID‐19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has recently posed a significant threat to global public health. The objective of this study was to develop and evaluate a rapid, expandable and sequencing‐free high‐resolution melting (HRM) approach for the direct detection and classification of SARS‐CoV‐2. Thirty‐one common pathogens that can cause respiratory tract infections were used to evaluate the specificity of the method. Synthetic RNA with serial dilutions was utilized to determine the sensitivity of the method. Finally, the clinical performance of the method was assessed using 290 clinical samples. The one‐step multiplex HRM could accurately identify SARS‐CoV‐2 and differentiate mutations in each marker site within approximately 2 h. For each target, the limit of detection was lower than 10 copies/reaction, and no cross‐reactivity was observed among organisms within the specificity testing panel. The method showed good uniformity for SARS‐CoV‐2 detection with a consistency of 100%. Regarding the clade classification performance, the results showed good concordance compared with sequencing, with the rate of agreement being 95.1% (78/82). The one‐step multiplex HRM method is a rapid method for SARS‐CoV‐2 detection and classification.
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spelling pubmed-91110942022-05-17 Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis Sun, Liying Xiu, Leshan Zhang, Chi Xiao, Yan Li, Yamei Zhang, Lulu Ren, Lili Peng, Junping Microb Biotechnol Research Articles Coronavirus disease 2019 (COVID‐19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has recently posed a significant threat to global public health. The objective of this study was to develop and evaluate a rapid, expandable and sequencing‐free high‐resolution melting (HRM) approach for the direct detection and classification of SARS‐CoV‐2. Thirty‐one common pathogens that can cause respiratory tract infections were used to evaluate the specificity of the method. Synthetic RNA with serial dilutions was utilized to determine the sensitivity of the method. Finally, the clinical performance of the method was assessed using 290 clinical samples. The one‐step multiplex HRM could accurately identify SARS‐CoV‐2 and differentiate mutations in each marker site within approximately 2 h. For each target, the limit of detection was lower than 10 copies/reaction, and no cross‐reactivity was observed among organisms within the specificity testing panel. The method showed good uniformity for SARS‐CoV‐2 detection with a consistency of 100%. Regarding the clade classification performance, the results showed good concordance compared with sequencing, with the rate of agreement being 95.1% (78/82). The one‐step multiplex HRM method is a rapid method for SARS‐CoV‐2 detection and classification. John Wiley and Sons Inc. 2022-03-01 /pmc/articles/PMC9111094/ /pubmed/35233932 http://dx.doi.org/10.1111/1751-7915.14027 Text en © 2022 The Authors. Microbial Biotechnology published by Society for Applied Microbiology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Sun, Liying
Xiu, Leshan
Zhang, Chi
Xiao, Yan
Li, Yamei
Zhang, Lulu
Ren, Lili
Peng, Junping
Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis
title Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis
title_full Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis
title_fullStr Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis
title_full_unstemmed Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis
title_short Detection and classification of SARS‐CoV‐2 using high‐resolution melting analysis
title_sort detection and classification of sars‐cov‐2 using high‐resolution melting analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111094/
https://www.ncbi.nlm.nih.gov/pubmed/35233932
http://dx.doi.org/10.1111/1751-7915.14027
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