Raman spectroscopy as a comprehensive tool for profiling endospore-forming bacteria †

Abstract

Accurate and reliable bacterial identification at the genus and species levels is essential for effective clinical diagnostics. Pathogens such as Clostridium perfringens , Bacillus cereus , Clostridioides difficile , and Paraclostridium sordellii pose significant challenges due to their unique cultivation requirements and developmental traits. Building on our previous work demonstrating the differentiation of vegetative Clostridium cells from non- Clostridium genera, we now aim to extend this approach to distinguish endospores of the same species. Raman spectroscopy was utilized to develop a comprehensive library of endospore spectra, encompassing both pathogenic and non-pathogenic species. This extensive dataset forms the foundation for advanced analytical capabilities. Chemometric analysis of single-endospore Raman spectra revealed significant discriminatory power across multiple hierarchical levels, facilitating the distinction between vegetative cells and endospores. Furthermore, this method enabled precise genus- and species-level classification of endospores, underscoring its potential for high-resolution bacterial endospore identification. These results highlight the versatility and efficacy of Raman spectroscopy in addressing the challenges associated with the identification of bacterial endospores in diverse clinical and environmental contexts. These findings present the first comprehensive library of endospore Raman spectra, demonstrating that Raman spectroscopy combined with chemometric analysis is a robust and reliable method for differentiating endospores of Clostridium species from those of Bacillus , Clostridioides , and Paraclostridium . This approach holds significant promise as a precise diagnostic tool for bacterial endospore identification in clinical settings.Raman spectroscopy differentiates aerobic and anaerobic metabolism, vegetative cells from endospores, and enables precise genus- and species-level ID of Clostridium and Bacillus species, offering a reliable, and robust tool for diverse applications