Rapid antimicrobial susceptibility testing (AST) is essential for managing bloodstream infections with high mortality, yet most current methods require prior identification of bacterial species, limiting their speed and applicability. To address these limitations, we developed SERS-Uni-AST, a species-independent platform based on surface-enhanced Raman scattering (SERS) that monitors the metabolic responses of bacteria to antibiotics through label-free detection. This approach eliminates the need for species identification, simplifying the testing workflow, and expands applicability to rare or previously unknown bacterial species while significantly reducing turnaround time. Validated on 191 clinical blood-culture isolates encompassing 43 bacterial species and 7 clinically relevant antibiotics, SERS-Uni-AST achieved 92% categorical agreement with standard testing within 5 h. The method demonstrated robust performance across Gram-positive and Gram-negative bacteria, including ESKAPE pathogens, using a predefined, species-independent decision threshold. By enabling timely, susceptibility-guided antimicrobial therapy, SERS-Uni-AST supports early treatment optimization and aligns with the goals of the Surviving Sepsis Campaign and WHO antimicrobial stewardship initiatives.
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Han et al. (Thu,) studied this question.
www.synapsesocial.com/papers/6990113f2ccff479cfe57bbb — DOI: https://doi.org/10.1021/acs.analchem.5c04833
Yin-Yi Han
Yu-Tsung Huang
Dai-Feng Li
Analytical Chemistry
National Taiwan University
National Taiwan University Hospital
Academia Sinica
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