In silico Thermodynamic Evaluation of the Effectiveness of RT-LAMP Primers for SARS-CoV-2 Variants Detection

Abstract

Background Viral mutations are the primary cause of mismatches in primer-target hybridisation, affecting the sensibility of molecular techniques, and potentially leading to detection dropouts. Despite its importance, little is known about the quantitative effect of mismatches in primer-target hybridisation. We have used up-to-date and highly detailed thermodynamic model parameters of DNA mismatches to evaluate the sensibility to variants of SARS-CoV-2 RT-LAMP primers. Methods We aligned 18 RT-LAMP primer sets, which underwent clinical validation, to the genomes of the wild-type strain (ws), 7 variants and 4 subvariants, and calculated hybridisation temperatures allowing up to three consecutive mismatches. We calculated the coverage when the mismatched melting temperature fell by more than 5°C in comparison to the matched alignments. If no mismatches were considered, the average coverage found was 94% for ws, falling to the lowest value for Omicron, i.e., 84%. Results However, considering mismatches, the coverage was much higher, i.e., 97% (ws) to 88% (Omicron). Stabilizing mismatches (higher melting temperatures) accounted for roughly 1/3 of this increase. The number of primer dropouts increased for each new variant; however, the effect was much less severe if mismatches were considered. Conclusion We suggest using melting temperature calculations to continuously assess the trend of primer dropouts.