Abstract

Whole cell MALDI is regularly used for the identification of bacteria to species level in clinical Microbiology laboratories. However, there remains a need to rapidly characterize and differentiate isolates below the species level to support outbreak management. We describe the implementation of a modified preparative approach for MALDI-MS combined with a custom analytical computational pipeline as a rapid procedure for subtyping Shigatoxigenic E. coli (STEC) and accurately identifying strain-specifying biomarkers. The technique was able to differentiate E. coli O157:H7 from other STEC. Within O157 serotype O157:H7 isolates were readily distinguishable from Sorbitol Fermenting O157 isolates. Overall, nine homogeneous groups of isolates were distinguished, each exhibiting distinct profiles of defining mass spectra features. This offers a robust analytical tool useable in reference/diagnostic public health scenarios.

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