Salmonella enterica serovars are prevalent foodborne pathogens responsible for high numbers of salmonellosis each year. Complex Fourier-transform infrared (FTIR) spectra offer unique biochemical fingerprints of bacteria with bands due to major cellular components. Growth media effects on discrimination of Salmonella serovars by FTIR spectroscopy were investigated and a novel sample preparation technique was developed. S. enterica strains from six serovars were grown on xylose lysine desoxycholate (XLD), Miller-Mallinson (MM), and plate count (PCA) agar as a control (37 degrees C, 24 h). Isolated colonies were suspended in 50% acetonitrile and centrifuged; the remaining pellet was placed on an AMTIR (attenuated total reflectance) crystal and dried under vacuum. Classification models (Soft Independent Modeling of Class Analogy, SIMCA), generated from derivatized infrared spectra (1300-900 cm-1 or 1200-900 cm-1), successfully discriminated among Salmonella strains with major discrimination from 1000-970 cm-1 associated to stretching modes of O-specific polysaccharide chains of lipopolysaccharides. Sample treatment with acetonitrile enhanced safe handling of the bacteria, removed interfering signals and improved the discriminating ability of SIMCA. All media were able to discriminate the S. enterica strains studied, varying in discriminating peaks and class distances in SIMCA classification. This methodology, with the production of large libraries of pathogenic bacteria, could be applied for the rapid monitoring of bacterial contamination in food with minimal sample manipulation.

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