This study developed and validated a method, based on the coupling of Fourier-transform infrared spectroscopy (FT-IR) and machine learning, for the automated serotyping of serogroup 1, serogroups 2-15 as well as their successful discrimination from non-. As presents significant intra- and inter-species heterogeneities, careful data validation strategies were applied to minimize late-stage performance variations of the method across a large microbial population. A total of 244 isolates were analyzed. In details, the method was validated with a multi-centric approach with isolates from Italian thermal and drinking water ( = 82) as well as with samples from German, Italian, French, and British collections ( = 162). Specifically, robustness of the method was verified over the time-span of 1 year with multiple operators and two different FT-IR instruments located in Italy and Germany. Moreover, different production procedures for the solid culture medium (in-house or commercial) and different culture conditions (with and without 2.5% CO) were tested. The method achieved an overall accuracy of 100, 98.5, and 93.9% on the Italian test set of , an independent batch of from multiple European culture collections, and an extra set of rare non- respectively.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133462PMC
http://dx.doi.org/10.3389/fmicb.2023.1150942DOI Listing

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