Differentiation of and by Metabolite Profiles Obtained Using Gold Nanoparticles-Based Surface-Assisted Laser Desorption/Ionization Mass Spectrometry.

and are challenging to differentiate using methods such as phenotyping, 16S rRNA sequencing, or protein profiling through matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) due to their close relatedness. This study explores the potential for identifying and by incorporating reference spectra of metabolite profiles, obtained via surface-assisted laser desorption/ionization mass spectrometry (SALDI MS) employing gold nanoparticles (AuNPs), into the Bruker Biotyper database. Metabolite extracts from and cells were prepared using liquid-liquid extraction in a chloroform-methanol-water system. The extracts were analyzed using Au-SALDI MS in positive ion mode, and reference spectra, compiled from 30 spectra for each bacterium, were added to the database. Identification of bacteria based on metabolite fingerprints in the Biotyper database produced correct results with scores exceeding 2.75. The results of Partial Least Squares-Discriminant Analysis (PLS-DA) demonstrated that the metabolomic approach could accurately differentiate the microorganisms under study. A panel of nine / values was also identified, each with an area under the ROC curve of above 0.8, enabling accurate identification of and . A search of metabolite databases allowed the following compounds to be assigned to the selected / values: -acetylputrescine, arginine, 2-maleylacetate, benzoyl phosphate, 8-acetylspermidine, alanyl-glutamate, 4-hydroxy-2,3,4,5-tetrahydrodipicolinate, and sucrose. The analyses showed that identification of bacteria based on metabolite profiles obtained by the Au-SALDI MS method is feasible and can be useful for distinguishing closely related microorganisms that are difficult to differentiate by other techniques.