Correlation analysis between Raman spectral signature and transcriptomic features of carbapenem-resistant Klebsiella pneumoniae

Guanghui Guo; Chen Guo; Xingwang Qie; Dahui He; Siyu Meng; Liqing Su; Shuqing Liang; Sanjun Yin; Guangchao Yu; Zhiqiang Zhang; Xiaoting Hua; Yizhi Song

doi:10.1016/j.saa.2023.123699

Correlation analysis between Raman spectral signature and transcriptomic features of carbapenem-resistant Klebsiella pneumoniae

Spectrochim Acta A Mol Biomol Spectrosc. 2024 Mar 5:308:123699. doi: 10.1016/j.saa.2023.123699. Epub 2023 Nov 29.

Authors

Guanghui Guo¹, Chen Guo², Xingwang Qie³, Dahui He¹, Siyu Meng⁴, Liqing Su¹, Shuqing Liang⁵, Sanjun Yin⁵, Guangchao Yu⁶, Zhiqiang Zhang², Xiaoting Hua⁷, Yizhi Song⁸

Affiliations

¹ The Third People's Hospital of Longgang District, Shenzhen 518112, China.
² School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou 215163, China.
³ Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou 215163, China; Nanjing Police University, Nanjing 210023, China.
⁴ Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou 215163, China.
⁵ Health Time Gene Institute, Shenzhen 518000, China.
⁶ The first affiliated hospital of Jinan university, Guangzhou 510630, China.
⁷ Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou 310016, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
⁸ School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou 215163, China; Chongqing Guoke Medical Technology Development Co., Ltd, Chongqing 400799, China. Electronic address: songyz@sibet.ac.cn.

PMID: 38043297
DOI: 10.1016/j.saa.2023.123699

Abstract

The Raman microspectroscopy technology has been successfully applied to evaluate the molecular composition of living cells for identifying cell types and states, but the rationale behind it was not well investigated. In this study, we acquired single-cell Raman spectra (SCRS) of three Klebsiella pneumoniae (K. pneumoniae) strains with different Carbapenem resistant mechanisms and analyzed them with machine learning algorithm. Two carbapenem resistant Klebsiella pneumoniae (CRKP) strains can be successfully distinguished from susceptible strain and CRKP with KPC or IMP carbapenemases can be classified with an overall accuracy achieving 100 %. Furthermore, we performed a correlation analysis between transcriptome and Raman spectra, and found that Raman shifts such as 752 and 1039 cm^-1 highly correlated with drug resistance genes expression and could be regarded as Raman biomarkers for CRKP with different mechanisms. The findings of the study provide a theoretical basis for identifying the relationship between Raman spectra and transcriptome of bacteria, as well as a novel method for rapid identification of CRKP and their carbapenemases types.

Keywords: IMP; KPC; Klebsiella Pneumoniae; Raman Microspectroscopy; Transcriptomics.

MeSH terms

Anti-Bacterial Agents / pharmacology
Carbapenem-Resistant Enterobacteriaceae* / genetics
Carbapenems / pharmacology
Gene Expression Profiling
Humans
Klebsiella Infections* / microbiology
Klebsiella pneumoniae / genetics
Microbial Sensitivity Tests
Transcriptome

Substances

Anti-Bacterial Agents
Carbapenems