On-Site Detection of SARS-CoV‑2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations

A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2021-07, Vol.93 (26), p.9174-9182
Main Authors: Huang, Jinglin, Wen, Jiaxing, Zhou, Minjie, Ni, Shuang, Le, Wei, Chen, Guo, Wei, Lai, Zeng, Yong, Qi, Daojian, Pan, Ming, Xu, Jianan, Wu, Yan, Li, Zeyu, Feng, Yuliang, Zhao, Zongqing, He, Zhibing, Li, Bo, Zhao, Songnan, Zhang, Baohan, Xue, Peili, He, Shusen, Fang, Kun, Zhao, Yuanyu, Du, Kai
Format: Article
Language:English
Subjects:
Analytical chemistry
Antigens
Chemistry
Coronaviruses
COVID-19
Deep learning
Diagnosis
Disease control
Epidemics
Onsite
Raman spectroscopy
Severe acute respiratory syndrome
Severe acute respiratory syndrome coronavirus 2
Spectroscopy
Spectrum analysis
Spike protein
Sputum
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Summary:A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.1c01061