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

ABSTRACT: The rapid sequence typing (ST) of bacterial strains is crucial for effective nosocomial infection control and mitigating the spread of nosocomial pathogens, e.g., Acinetobacter baumannii. While accurate in identifying A. baumannii strains, current typing methods are often impractical in clinical settings due to their time-consuming nature. This study developed a novel approach, combining surface-enhanced Raman spectroscopy (SERS) with machine-learning (ML) algorithms, to construct predictive models for A. baumannii sequence typing based on SERS spectra. The objective was to assess the feasibility of this integrated method for efficient sequence typing of A. baumannii strains. Clinically isolated A. baumannii strains (N = 267) were collected from a

SUBMITTER: Liu S 

PROVIDER: S-EPMC11878063 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature