Multiplex, Real-Time, Point-of-care RT-LAMP for SARS-CoV‑2 Detection Using the HFman Probe

Viral evolution impacts diagnostic test performance through the emergence of variants with sequences affecting the efficiency of primer binding. Such variants that evade detection by nucleic acid-based tests are subject to selective pressure, enabling them to spread more efficiently. Here, we report...

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Bibliographic Details
Published inACS sensors Vol. 7; no. 3; pp. 730 - 739
Main Authors Dong, Yajuan, Zhao, Yongjuan, Li, Shenwei, Wan, Zhenzhou, Lu, Renfei, Yang, Xianguang, Yu, Guoying, Reboud, Julien, Cooper, Jonathan M., Tian, Zhengan, Zhang, Chiyu
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 25.03.2022
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Summary:Viral evolution impacts diagnostic test performance through the emergence of variants with sequences affecting the efficiency of primer binding. Such variants that evade detection by nucleic acid-based tests are subject to selective pressure, enabling them to spread more efficiently. Here, we report a variant-tolerant diagnostic test for SARS-CoV-2 using a loop-mediated isothermal nucleic acid-based amplification (LAMP) assay containing high-fidelity DNA polymerase and a high-fidelity DNA polymerase-medicated probe (HFman probe). In addition to demonstrating a high tolerance to variable SARS-CoV-2 viral sequences, the mechanism also overcomes frequently observed limitations of LAMP assays arising from non-specific amplification within multiplexed reactions performed in a single “pot”. Results showed excellent clinical performance (sensitivity 94.5%, specificity 100%, n = 190) when compared directly to a commercial gold standard reverse transcription quantitative polymerase chain reaction assay for the extracted RNA from nasopharyngeal samples and the capability of detecting a wide range of sequences containing at least alpha and delta variants. To further validate the test with no sample processing, directly from nasopharyngeal swabs, we also detected SARS-CoV-2 in positive clinical samples (n = 49), opening up the possibility for the assay’s use in decentralized testing.
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ISSN:2379-3694
2379-3694
DOI:10.1021/acssensors.1c02079