A quantitative RT‐qLAMP for the detection of SARS‐CoV‐2 and human gene in clinical application. Issue 10 (13th July 2022) - Yu, Yejiong; Zhou, Johnny X. Y.; Li, Binbin; Ji, Mengmeng; Wang, Yun; Carnaby, Emma; Andersson, Monique I.; Huang, Wei E.; Cui, Zhanfeng
Abstract: Reverse transcription (RT) – loop‐mediated isothermal amplification (LAMP) assay is a rapid and one‐step method to detect SARS‐CoV‐2 in the pandemic. Quantitative estimation of the viral load of SARS‐CoV‐2 in patient samples could help physicians make decisions on clinical treatment and patient management. Here, we propose to use a quantitative LAMP (qLAMP) method to evaluate the viral load of SARS‐CoV‐2 in samples. We used threshold time (TT) values of qLAMP, the isothermal incubation time required for the fluorescent or colorimetric signal to reach the threshold, to indicate the viral load of clinical samples. Similar to the cycle threshold ( C t ) values in conventional qPCR, TT values of qLAMP show a linear relationship to the copy numbers of SARS‐CoV‐2. The higher the viral loadings, the lower qLAMP TT values are. The RT‐qLAMP assay was demonstrated to quantify the viral loads of synthesized full‐length RNA, inactivated viral particles (BBIBP‐CorV), and clinical samples within 15 min by fluorescent reading and 25 min by colorimetric reading. The RT‐qLAMP has been applied to detect Alpha, Beta, Kappa, Delta, and Omicron variants of SARS‐CoV‐2, as well as the human beta‐actin gene, and their TT values showed the linear patterns. The RT‐qLAMP assays were evaluated by 64 clinical samples (25 positives and 39 negatives) for the assessment of viral loads, and it was also used to quantify the human beta‐actin gene, which was used as a control and an indicator of sampling quality in clinical swab samples. The result of RT‐qLAMP was in good agreement with the result of RT‐qPCR. The RT‐qLAMP assay detected all clinical samples, including those with C t  = 35, within 10 min using fluorescent reading. Abstract : A quantitative method of RNA/DNA using a rapid RT‐qLAMP and the application of it to clinical samples.