| Title |
A high-resolution melt curve toolkit to identify lineage-defining SARS-CoV-2 mutations
|
|---|---|
| Published in |
Scientific Reports, March 2023
|
| DOI | 10.1038/s41598-023-30754-1 |
| Pubmed ID | |
| Authors | |
| Abstract |
The emergence of severe acute respiratory syndrome 2 (SARS-CoV-2) variants of concern (VOCs), with mutations linked to increased transmissibility, vaccine escape and virulence, has necessitated the widespread genomic surveillance of SARS-CoV-2. This has placed a strain on global sequencing capacity, especially in areas lacking the resources for large scale sequencing activities. Here we have developed three separate multiplex high-resolution melting assays to enable the identification of Alpha, Beta, Delta and Omicron VOCs. The assays were evaluated against whole genome sequencing on upper-respiratory swab samples collected during the Alpha, Delta and Omicron [BA.1] waves of the UK pandemic. The sensitivities of the eight individual primer sets were all 100%, and specificity ranged from 94.6 to 100%. The multiplex HRM assays have potential as a tool for high throughput surveillance of SARS-CoV-2 VOCs, particularly in areas with limited genomics facilities. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 75% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 18% |
| Student > Master | 2 | 18% |
| Other | 1 | 9% |
| Student > Doctoral Student | 1 | 9% |
| Researcher | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 4 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 4 | 36% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Business, Management and Accounting | 1 | 9% |
| Agricultural and Biological Sciences | 1 | 9% |
| Medicine and Dentistry | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 3 | 27% |