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Ultrafast multiplexed detection of SARS-CoV-2 RNA using a rapid droplet digital PCR system.
Yin, Hao; Wu, Zhenhua; Shi, Nan; Qi, Yong; Jian, Xiaoyu; Zhou, Lin; Tong, Yigang; Cheng, Zule; Zhao, Jianlong; Mao, Hongju.
  • Yin H; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Wu Z; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
  • Shi N; Expec-Advanced Research Center, Saudi Aramco, Dhahran, 34464, Saudi Arabia.
  • Qi Y; Huadong Research Institute for Medicine and Biotechniques, Nanjing, Jiangsu, 210000, China.
  • Jian X; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
  • Zhou L; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
  • Tong Y; Beijing Advanced Innovation Center for Soft Matter Science and Engineering (BAIC-SM), College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100049, China.
  • Cheng Z; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China. Electronic address: chengzule@163.com.
  • Zhao J; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
  • Mao H; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China. Electroni
Biosens Bioelectron ; 188: 113282, 2021 Sep 15.
Article in English | MEDLINE | ID: covidwho-1213053
ABSTRACT
We report the first combination of droplet digital and rapid PCR techniques for efficient, accurate, and quantitative detection of SARS-CoV-2 RNA. The presented rapid digital PCR system simultaneously detects two specific targets (ORF1ab and N genes) and one reference gene (RNase P) with a single PCR thermal cycling period around 7 s and the total running time less than 5 min. A clear positive signal could be identified within 115 s via the rapid digital RT-PCR, suggesting its efficiency for the end-point detection. In addition, benchmark tests with serial diluted reference samples of SARS-CoV-2 RNA reveal the excellent accuracy of our system (R2>0.99). More importantly, the rapid digital PCR system gives consistent and accurate detection of low-concentration reference samples, whereas qPCR yields Ct values with significant variations that could lead to false-negative results. Finally, we apply the rapid digital PCR system to analyze clinical samples with both positive and control cases, where results are consistent with qPCR test outcomes. By providing similar accuracy with qPCR while minimizing the detection time-consuming and the false-negative tendency, the presented rapid digital PCR system represents a promising improvement on the rapid diagnosis of COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biosensing Techniques / COVID-19 Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Language: English Journal: Biosens Bioelectron Journal subject: Biotechnology Year: 2021 Document Type: Article Affiliation country: J.bios.2021.113282

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biosensing Techniques / COVID-19 Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Language: English Journal: Biosens Bioelectron Journal subject: Biotechnology Year: 2021 Document Type: Article Affiliation country: J.bios.2021.113282