AI Article Synopsis
- Whole cell MALDI is a common method in clinical microbiology for identifying bacteria to the species level, but there's a need for quicker sub-species differentiation, especially during outbreaks.
- A new modified MALDI-MS approach combined with custom computational analysis was developed for rapid subtyping of Shigatoxigenic E. coli (STEC), successfully identifying specific strain biomarkers.
- The technique effectively distinguished E. coli O157:H7 from other STEC strains and identified nine distinct groups based on their mass spectral profiles, making it a valuable tool for public health diagnostics.
Article 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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| http://dx.doi.org/10.1016/j.talanta.2018.01.055 | DOI Listing |
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