Molecular Diagnosis of a Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia

By D. Chu, Yang Pan, Samuel M. S. Cheng, K. P. Hui, P. Krishnan, Yingzhi Liu, D. Ng, Carrie K C Wan, Peng Yang, Quanyi Wang and 2 more. Clinical Chemistry, 2020

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Abstract Background A novel coronavirus of zoonotic origin (2019-nCoV) has recently been identified in patients with acute respiratory disease. This virus is genetically similar to SARS coronavirus and bat SARS-like coronaviruses. The outbreak was initially detected in Wuhan, a major city of China, but has subsequently been detected in other provinces of China. Travel-associated cases have also been reported in a few other countries. Outbreaks in health care workers indicate human-to-human transmission. Molecular tests for rapid detection of this virus are urgently needed for early identification of infected patients. Methods We developed two 1-step quantitative real-time reverse-transcription PCR assays to detect two different regions (ORF1b and N) of the viral genome. The primer and probe sets were designed to react with this novel coronavirus and its closely related viruses, such as SARS coronavirus. These assays were evaluated using a panel of positive and negative controls. In addition, respiratory specimens from two 2019-nCoV-infected patients were tested. Results Using RNA extracted from cells infected by SARS coronavirus as a positive control, these assays were shown to have a dynamic range of at least seven orders of magnitude (2x10−4-2000 TCID50/reaction). Using DNA plasmids as positive standards, the detection limits of these assays were found to be below 10 copies per reaction. All negative control samples were negative in the assays. Samples from two 2019-nCoV-infected patients were positive in the tests. Conclusions The established assays can achieve a rapid detection of 2019n-CoV in human samples, thereby allowing early identification of patients.

Subfields: Infectious Diseases

View Paper: https://www.semanticscholar.org/paper/ab43834edf0db25c9e3f97433db812aac9823f65

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