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Front Cell Infect Microbiol · Jan 2021
Reverse Transcription Recombinase-Aided Amplification Assay With Lateral Flow Dipstick Assay for Rapid Detection of 2019 Novel Coronavirus.
- Yu-Zhong Zheng, Jiang-Tao Chen, Jian Li, Xian-Jing Wu, Jin-Zhou Wen, Xiang-Zhi Liu, Li-Yun Lin, Xue-Yan Liang, Hui-Ying Huang, Guang-Cai Zha, Pei-Kui Yang, Lie-Jun Li, Tian-Yu Zhong, Long Liu, Wei-Jia Cheng, Xiao-Nan Song, and Min Lin.
- School of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, China.
- Front Cell Infect Microbiol. 2021 Jan 1; 11: 613304.
BackgroundThe emerging Coronavirus Disease-2019 (COVID-19) has challenged the public health globally. With the increasing requirement of detection for SARS-CoV-2 outside of the laboratory setting, a rapid and precise Point of Care Test (POCT) is urgently needed.MethodsTargeting the nucleocapsid (N) gene of SARS-CoV-2, specific primers, and probes for reverse transcription recombinase-aided amplification coupled with lateral flow dipstick (RT-RAA/LFD) platform were designed. For specificity evaluation, it was tested with human coronaviruses, human influenza A virus, influenza B viruses, respiratory syncytial virus, and hepatitis B virus, respectively. For sensitivity assay, it was estimated by templates of recombinant plasmid and pseudovirus of SARS-CoV-2 RNA. For clinical assessment, 100 clinical samples (13 positive and 87 negatives for SARS-CoV-2) were tested via quantitative reverse transcription PCR (RT-qPCR) and RT-RAA/LFD, respectively.ResultsThe limit of detection was 1 copies/μl in RT-RAA/LFD assay, which could be conducted within 30 min at 39°C, without any cross-reaction with other human coronaviruses and clinical respiratory pathogens. Compared with RT-qPCR, the established POCT assay offered 100% specificity and 100% sensitivity in the detection of clinical samples.ConclusionThis work provides a convenient POCT tool for rapid screening, diagnosis, and monitoring of suspected patients in SARS-CoV-2 endemic areas.Copyright © 2021 Zheng, Chen, Li, Wu, Wen, Liu, Lin, Liang, Huang, Zha, Yang, Li, Zhong, Liu, Cheng, Song and Lin.
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