Comparison of Raman spectroscopy with mass spectrometry for sequence typing of <i>Acinetobacter baumannii</i> strains: a single-center study

The rapid and accurate sequence typing (ST) of bacterial pathogens is pivotal in controlling transmission within healthcare settings. <i>Acinetobacter baumannii</i> infection, known for its high transmissibility and drug resistance, presents a major challenge in nosocomial infection control. In this study, surface-enhanced Raman spectroscopy (SERS) was used to differentiate <i>A. baumannii</i> strains with distinct STs based on unique Raman spectral profiles. We then constructed and compared eight machine-learning models on SERS spectra to quickly identify bacterial STs. The results showed that the support vector machine model outperformed matrix-assisted laser desorption/ionization time-of-flight mass spectrometer in determining <i>A. baumannii</i> STs. This approach enables rapid identification of <i>A. baumannii</i> variants with different STs, supporting the early detection and control of nosocomial infections by this multidrug-resistant pathogen.