In the host, pathogenic microorganisms have developed stress responses to cope with constantly changing environments. Stress responses are directly related to changes in several metabolomic pathways, which could hamper microorganisms' unequivocal identification. We evaluated the effect of various in vitro stress conditions (acidic, basic, oxidative, ethanolic, and saline conditions) on the metabolism of Staphylococcus aureus, Bacillus cereus, and Pseudomonas aeruginosa, which are common lung pathogens. The metabolite profiles of the bacteria were analyzed using liquid chromatography coupled to triple quadrupole and quadrupole time-of-flight mass spectrometry. The advantages of targeted and untargeted analysis combined with univariate and multivariate statistical analysis (principal component analysis, hierarchical cluster analysis, partial least square discriminant analysis, random forest) were combined to unequivocally identify bacterial species. In normal in vitro conditions, the targeted methodology, based on the analysis of primary metabolites, enabled the rapid and efficient discrimination of the three bacteria. In changing in vitro conditions and specifically in presence of the various stressors, the untargeted methodology proved to be more valuable for the global and accurate differentiation of the three bacteria, also considering the type of stress environment within each species. In addition, species-specific metabolites (i.e., fatty acids, polysaccharides, peptides, and nucleotide bases derivatives) were putatively identified. Good intra-day repeatability and inter-day repeatability (< 10% RSD and < 15% RSD, respectively) were obtained for the targeted and the untargeted methods. This untargeted approach highlights its importance in unusual (and less known) bacterial growth environments, being a powerful tool for infectious disease diagnosis, where the accurate classification of microorganisms is sought.
