Application of raman spectroscopy for studying bacteria of the family enterobacteriaceae

This thesis investigated using Raman spectroscopy for identifying Enterobacteriaceae and their antibiotic resistances. The study aimed to develop a rapid, accurate diagnostic tool, as current methods are costly and inefficient, leading to increased antibiotic resistance due to inappropriate antibiotic use. The research involved collecting a dataset of Enterobacteriaceae, encompassing 8 genera. Measurements were taken using Single-Cell Raman Microspectroscopy (SC-RMS) and Fiber Probe-Based Raman Spectroscopy (FP-RS). Machine learning models were trained to classify the bacteria based on spectral data. SC-RMS showed limited success (47% accuracy), while FP-RS achieved 100% accuracy on the training dataset and 94% on a validation dataset, demonstrating its potential in differentiating Enterobacteriaceae. Subsequently, Raman spectra of 24 clinical isolates were analyzed using UV-Resonance Raman Spectroscopy (UVRRS). The goal was to discriminate between E. coli, K. pneumoniae, and K. oxytoca. While SC-RMS had limited effectiveness, UVRRS achieved high accuracy (92% at the genus level and 90% at the species level), marking the first successful differentiation of K. oxytoca using Raman spectroscopy. The study also explored differentiating antibiotic-resistant and sensitive Enterobacteriaceae. Both SC-RMS and UVRRS correctly classified 70-75% of the isolates, with UVRRS demonstrating a 90% sensitivity for resistant strains. This differentiation may be related to a higher DNA/Protein ratio in resistant bacteria. Overall, the findings enhance the application of Raman spectroscopy in microbiology, particularly for Enterobacteriaceae. The research supports its use in identifying pathogens, determining their genus and species, and assessing antibiotic resistance. The study contributes significantly to the development of Raman-based microbial diagnostics, promising to improve infectious disease diagnostics, patient care, and the fight against antimicrobial resistance.