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

Abstract

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.