Clinical validation of optimised RT-LAMP for the diagnosis of SARS-CoV-2 infection

Boon Lim, Jeremy Ratcliff, Dorota A. Nawrot, Yejiong Yu, Harshmeena R. Sanghani, Chia Chen Hsu, Leon Peto, Simon Evans, Susanne H. Hodgson, Aikaterini Skeva, Maria Adam, Maria Panopoulou, Christos E. Zois, Katy Poncin, Sridhar R. Vasudevan, Siqi Dai, Shuai Ren, Hong Chang, Zhanfeng Cui, Peter SimmondsWei E. Huang, Monique I. Andersson

Research output: Contribution to journalArticlepeer-review

Abstract

We have optimised a reverse transcription-loop-mediated isothermal amplification (RT-LAMP) assay for the detection of SARS-CoV-2 from extracted RNA for clinical application. We improved the stability and reliability of the RT-LAMP assay by the addition of a temperature-dependent switch oligonucleotide to reduce self- or off-target amplification. We then developed freeze-dried master mix for single step RT-LAMP reaction, simplifying the operation for end users and improving long-term storage and transportation. The assay can detect as low as 13 copies of SARS-CoV2 RNA per reaction (25-μL). Cross reactivity with other human coronaviruses was not observed. We have applied the new RT-LAMP assay for testing clinical extracted RNA samples extracted from swabs of 72 patients in the UK and 126 samples from Greece and demonstrated the overall sensitivity of 90.2% (95% CI 83.8–94.7%) and specificity of 92.4% (95% CI 83.2–97.5%). Among 115 positive samples which Ct values were less than 34, the RT-LAMP assay was able to detect 110 of them with 95.6% sensitivity. The specificity was 100% when RNA elution used RNase-free water. The outcome of RT-LAMP can be reported by both colorimetric detection and quantifiable fluorescent reading. Objective measures with a digitized reading data flow would allow for the sharing of results for local or national surveillance.

Original languageEnglish
Article number16193
JournalScientific Reports
Volume11
Issue number1
DOIs
Publication statusPublished - 10 Aug 2021
Externally publishedYes

Fingerprint

Dive into the research topics of 'Clinical validation of optimised RT-LAMP for the diagnosis of SARS-CoV-2 infection'. Together they form a unique fingerprint.

Cite this