Abstract
Clostridioides difficile (CD) has emerged as one of the most prevalent nosocomial infections in hospitals and is the primary causative agent of antibiotic-associated diarrhea and pseudomembranous colitis. In recent years, C. difficile-induced infections have resulted in significant morbidity and mortality worldwide, with a particularly rapid increase in incidence observed in China. C. difficile strains are categorized into toxin-producing and non-toxin-producing based on their ability to synthesize toxins, with the pathogenicity of C. difficile being strictly dependent on the protein toxins produced by the toxin-producing strains. Therefore, early and rapid identification of toxin-producing C. difficile is crucial for the diagnosis and prevention of Clostridioides difficile infection (CDI). Currently, the detection methods of C. difficile infection carried out by clinical laboratories in China mainly include C. difficile toxin-producing culture, cell culture toxin assay, toxin assay by immunological methods, glutamate dehydrogenase (GDH) assay and nucleic acid amplification assay.However, current detection methods for CDI in clinical laboratories in China exhibit significant limitations, such as being time-consuming, operationally complex, and lacking in specificity and sensitivity. Raman microspectroscopy has been shown to have the potential for rapid and reliable identification in microbial diagnostics, with the method reducing the time to results to less than 1 hour, including the processing of clinical samples, the measurement of single-cell Raman spectra, and the final diagnosis through the use of training models. In this study, we aimed to predict in situ strain identification and virulent strain identification of 24 raw clinical stool samples by constructing a reference single-cell Raman spectroscopy (SCRS) database of common intestinal flora and C. difficile, as well as a reference SCRS database of toxin-producing and non-toxin-producing C. difficile strains. The results showed that the accuracy of C. difficile strain identification in clinical stool samples was 83%, and the accuracy of virulent strain prediction was 80%. These findings suggest that Raman spectroscopy may be a viable method for the rapid in situ identification of virulent and non-virulent C. difficile strains and holds promise for clinical application in the rapid diagnosis of CDI.