SERS-CBP: A Comprehensive SERS Spectral Database of Clinically Important Bacterial Pathogens.
8 affiliations
- 1Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong 510080, China.
- 2School of Medicine, South China University of Technology, Guangzhou, Guangdong 510006, China.
- 3Marshall Research Centre for Medical Microbial Biotechnology, Department of Life Sciences, Faculty of Science, The Hong Kong Polytechnic University (PolyU), Hung Hom, Kowloon, Hong Kong SAR 999077, China.
- 4The Marshall Centre for Interventions in Infectious Disease, The University of Western Australia, Crawley, Western Australia 6009, Australia.
- 5School of Molecular Sciences, School of Biomedical Sciences, The University of Western Australia, Crawley, Western Australia 6009, Australia.
- 6School of Agriculture and Food Sustainability, University of Queensland, Brisbane QLD 4072, Australia.
- 7Nutrition and Health Innovation Research Institute & School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia 6027, Australia.
- 8Shanghai Tengcheng Medical Science & Technology Company, Shanghai 201203, China.
Abstract
Rapid and accurate detection of clinically important bacterial pathogens (CBP) is a public health priority. Over the past decades, the landscape of bacterial identification has experienced substantial transformation, and many diagnosis techniques for bacterial pathogens have been developed. Despite these advancements, precise identification of bacterial pathogens to inform therapeutic decisions for infectious diseases continues to pose a significant clinical hurdle, which urgently requires the development of novel diagnostic methods. As an emerging technique, surface-enhanced Raman spectroscopy (SERS), due to its high sensitivity and rapid response, the technique shows great potential in diagnosing bacterial pathogens. However, the SERS technique is currently not used in clinical settings because of the absence of a comprehensive SERS spectral database of bacterial pathogens. In this study, we manually collected 75,367 SERS spectra for 192 bacterial species belonging to 88 genera. A database web server termed SERS-CBP (http://www.sers-cbp.net/) was constructed to store all the spectral data, which can also automatically predict unknown SERS spectra submitted by anonymous users through pretrained convolutional neural network (CNN) models, which were integrated into the web server. Taken together, we constructed the first comprehensive SERS spectral database for representative bacterial pathogens commonly encountered in clinical laboratories. The SERS-CBP database holds the potential to facilitate the application of Raman spectroscopy for the identification of bacterial pathogens in clinical settings. Continuous enhancements and expansions are set to establish this database as the definitive standard for bacterial SERS spectra, solidifying its role as an essential asset for scientific and diagnostic endeavors.
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BibTeX
@article{wang2026serscbp,
title = {{SERS-CBP: A Comprehensive SERS Spectral Database of Clinically Important Bacterial Pathogens.}},
author = {Liang Wang and Xu-Xia Cui and Jia-Wei Tang and Su-Ling Liu and Er-Zhao Zhang and Ni Zhang and Jing-Fang Zhou and Long Ye and Jie Chen and Yang Pu and Bing Gu},
journal = {ACS measurement science au},
year = {2026},
month = aug,
doi = {10.1021/acsmeasuresciau.6c00063},
url = {https://europepmc.org/article/MED/42921451},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - SERS-CBP: A Comprehensive SERS Spectral Database of Clinically Important Bacterial Pathogens.
AU - Liang Wang
AU - Xu-Xia Cui
AU - Jia-Wei Tang
AU - Su-Ling Liu
AU - Er-Zhao Zhang
AU - Ni Zhang
AU - Jing-Fang Zhou
AU - Long Ye
AU - Jie Chen
AU - Yang Pu
AU - Bing Gu
PY - 2026
DA - 2026/08/03
JO - ACS measurement science au
DO - 10.1021/acsmeasuresciau.6c00063
UR - https://europepmc.org/article/MED/42921451
AB - Rapid and accurate detection of clinically important bacterial pathogens (CBP) is a public health priority. Over the past decades, the landscape of bacterial identification has experienced substantial transformation, and many diagnosis techniques for bacterial pathogens have been developed. Despite these advancements, precise identification of bacterial pathogens to inform therapeutic decisions for infectious diseases continues to pose a significant clinical hurdle, which urgently requires the development of novel diagnostic methods. As an emerging technique, surface-enhanced Raman spectroscopy (SERS), due to its high sensitivity and rapid response, the technique shows great potential in diagnosing bacterial pathogens. However, the SERS technique is currently not used in clinical settings because of the absence of a comprehensive SERS spectral database of bacterial pathogens. In this study, we manually collected 75,367 SERS spectra for 192 bacterial species belonging to 88 genera. A database web server termed SERS-CBP (http://www.sers-cbp.net/) was constructed to store all the spectral data, which can also automatically predict unknown SERS spectra submitted by anonymous users through pretrained convolutional neural network (CNN) models, which were integrated into the web server. Taken together, we constructed the first comprehensive SERS spectral database for representative bacterial pathogens commonly encountered in clinical laboratories. The SERS-CBP database holds the potential to facilitate the application of Raman spectroscopy for the identification of bacterial pathogens in clinical settings. Continuous enhancements and expansions are set to establish this database as the definitive standard for bacterial SERS spectra, solidifying its role as an essential asset for scientific and diagnostic endeavors.
SN - 2694-250X
ER -