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CDetection.v2: One-pot assay for the detection of SARS-CoV-2.
Wang, Xinge; Chen, Yangcan; Cheng, Xuejia; Wang, Si-Qi; Hu, Yanping; Feng, Yingmei; Jin, Ronghua; Zhou, Kangping; Liu, Ti; Wang, Jianxing; Pan, Kai; Liu, Bing; Xiang, Jie; Wang, Yanping; Zhou, Qi; Zhang, Ying; Pan, Weiye; Li, Wei.
  • Wang X; State Key Laboratory of Stem Cell and Reproductive Biology, Chinese Academy of Sciences, Institute of Zoology, Beijing, China.
  • Chen Y; Bejing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Cheng X; Chinese Academy of Sciences, Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Wang SQ; Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China.
  • Hu Y; State Key Laboratory of Stem Cell and Reproductive Biology, Chinese Academy of Sciences, Institute of Zoology, Beijing, China.
  • Feng Y; Bejing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Jin R; Chinese Academy of Sciences, Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Zhou K; Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China.
  • Liu T; Beijing SynsorBio Technology Co., Ltd., Beijing, China.
  • Wang J; State Key Laboratory of Stem Cell and Reproductive Biology, Chinese Academy of Sciences, Institute of Zoology, Beijing, China.
  • Pan K; Bejing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Liu B; Chinese Academy of Sciences, Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Xiang J; State Key Laboratory of Stem Cell and Reproductive Biology, Chinese Academy of Sciences, Institute of Zoology, Beijing, China.
  • Wang Y; Bejing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Zhou Q; Chinese Academy of Sciences, Institute for Stem Cell and Regenerative Medicine, Beijing, China.
  • Zhang Y; Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China.
  • Pan W; Department of Science and Technology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
  • Li W; Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Front Microbiol ; 14: 1158163, 2023.
Article in English | MEDLINE | ID: covidwho-2305516
ABSTRACT

Introduction:

The ongoing 2019 coronavirus disease pandemic (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants, is a global public health threat. Early diagnosis and identification of SARS-CoV-2 and its variants plays a critical role in COVID-19 prevention and control. Currently, the most widely used technique to detect SARS-CoV-2 is quantitative reverse transcription real-time quantitative PCR (RT-qPCR), which takes nearly 1 hour and should be performed by experienced personnel to ensure the accuracy of results. Therefore, the development of a nucleic acid detection kit with higher sensitivity, faster detection and greater accuracy is important.

Methods:

Here, we optimized the system components and reaction conditions of our previous detection approach by using RT-RAA and Cas12b.

Results:

We developed a Cas12b-assisted one-pot detection platform (CDetection.v2) that allows rapid detection of SARS-CoV-2 in 30 minutes. This platform was able to detect up to 5,000 copies/ml of SARS-CoV-2 without cross-reactivity with other viruses. Moreover, the sensitivity of this CRISPR system was comparable to that of RT-qPCR when tested on 120 clinical samples.

Discussion:

The CDetection.v2 provides a novel one-pot detection approach based on the integration of RT-RAA and CRISPR/Cas12b for detecting SARS-CoV-2 and screening of large-scale clinical samples, offering a more efficient strategy for detecting various types of viruses.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Prognostic study / Randomized controlled trials Topics: Variants Language: English Journal: Front Microbiol Year: 2023 Document Type: Article Affiliation country: Fmicb.2023.1158163

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Prognostic study / Randomized controlled trials Topics: Variants Language: English Journal: Front Microbiol Year: 2023 Document Type: Article Affiliation country: Fmicb.2023.1158163