Machine Learning Algorithms for Classification of MALDI-TOF MS Spectra from Phylogenetically Closely Related Species , and .

(1) Background: MALDI-TOF mass spectrometry (MS) is the gold standard for microbial fingerprinting, however, for phylogenetically closely related species, the resolution power drops down to the genus level. In this study, we analyzed MALDI-TOF spectra from 44 strains of , and to identify the optimal classification method within popular supervised and unsupervised machine learning (ML) algorithms. (2) Methods: A consensus feature selection strategy was applied to pinpoint from among the 500 MS features those that yielded the best ML model and that may play a role in species differentiation.

Adaptation of Antimicrobial Susceptibility Testing to the ISO 20776 Standard and Validation of the Method.

Brucellosis, mainly caused by (B.) , is associated with a risk of chronification and relapses. Antimicrobial susceptibility testing (AST) standards for are not available, and the agent is not yet listed in the EUCAST breakpoint tables.