Machine Learning-Assisted SERS Platform for Rapid and Quantitative Discrimination of Shiga Toxin-Producing <i>E. coli</i> Serotypes.

ABSTRACT: Rapid, sensitive, and specific detection of pathogenic Escherichia coli serotypes is crucial for food safety and public health. Here, we present a surface-enhanced Raman scattering (SERS) platform utilizing highly ordered silver nanorod (AgNR) arrays functionalized with vancomycin for efficient and selective bacterial capture. The system enables multiplexed, high-throughput analysis using a portable Raman spectrometer, achieving direct molecular fingerprinting of seven clinically relevant E. coli serotypes. Systematic optimization of AgNR length and vancomycin coating maximized SERS enhancement and capture efficiency. Advanced data analysis with linear discriminant analysis (LDA) provided robust discrimination among all serotypes and concentrations, achieving up to 100% class

SUBMITTER: Liu Y 

PROVIDER: S-EPMC12650715 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature