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AbstractThis study utilized SERS to characterize and identify Klebsiella pneumonia, Staphylococcus aureus, and Pseudomonas aeruginosa which were collected from pus and confirmed using 16S rRNA sequencing. These bacteria are typically cultured and isolated from human wounds. SERS peaks at 575, 629, 930, 1008, 1038, 1099, 1134, 1221, 1283, 1294, 1374, 1589, and 1707 cm−1 were shown to be distinguishing features of these strains. Principal component analysis (PCA) and partial least squares – discriminant analysis (PLS-DA) was applied to SERS spectral datasets. This study demonstrates that combining SERS with PCA and PLS-DA is effective for recognizing and distinguishing these bacterial isolates. [ABSTRACT FROM AUTHOR]