10.6084/M9.FIGSHARE.12853673
Yuchang Li
Yuchang
Li
Jing Li
Jing
Li
Ying Zhang
Ying
Zhang
Lizhong Dai
Lizhong
Dai
Lin Li
Lin
Li
Juan Liu
Juan
Liu
Sen Zhang
Sen
Zhang
Xiaoyan Wu
Xiaoyan
Wu
Yi Hu
Yi
Hu
Chengfeng Qin
Chengfeng
Qin
Tao Jiang
Tao
Jiang
Xiaoping Kang
Xiaoping
Kang
Development of an automatic integrated gene detection system for novel severe acute respiratory syndrome-related coronavirus (SARS-CoV2)
<p>In December 2019, Wuhan, China suffered a serious outbreak of a novel coronavirus infectious disease (COVID) caused by novel severe acute respiratory syndrome-related coronavirus (SARS-CoV 2). To quickly identify the pathogen, we designed and screened primer sets, and established a sensitive and specific qRT-PCR assay for SARS-CoV 2; the lower limit of detection (LOD) was 15 (95% CI: 9.8–21) copies per reaction. We combined this qRT-PCR assay with an automatic integration system for nucleic acid extraction and amplification, thereby establishing an automatic integrated gene detection system (AIGS) for SARS-CoV 2. Cross reactive analysis performed in 20 other respiratory viruses and 37 nasopharyngeal swabs confirmed a 100% specificity of the assay. Using two fold diluted SARS-CoV 2 culture, the LOD of AIGS was confirmed to be 365 copies/ml (95% CI: 350–375), which was Comparable to that of conventional qRT-PCR (740 copies/ml, 95% CI: 690–750). Clinical performances of AIGS assay were assessed in 266 suspected COVID-19 clinical respiratory tract samples tested in parallel with a commercial kit. The clinical sensitivity of the AIGS test was 97.62% (95% CI: 0.9320–0.9951) based on the commercial kit test result, and concordance analysis showed a high agreement in SARS-CoV-2 detection between the two assays, Pearson R was 0.9623 (95% CI: 0.9523–0.9703). The results indicated that this AIGS could be used for rapid detection of SARS-CoV 2. With the advantage of simple operation and less time consuming, AIGS could be suitable for SARS-CoV2 detection in primary medical institutions, thus would do a great help to improve detection efficiency and control the spread of COVID-19.</p>
Space Science
Medicine
Microbiology
Genetics
Molecular Biology
Biotechnology
Immunology
Biological Sciences not elsewhere classified
Infectious Diseases
Virology
Taylor & Francis
2020
2020-08-24
2023-10-17
Dataset
374312 Bytes
10.1080/22221751.2020.1782774
CC BY 4.0