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The worldwide increase in antimicrobial resistance is due to antibiotic overuse in agriculture and overprescription in medicine. For appropriate and timely patient support, faster diagnosis of antimicrobial resistance is required. Current methods for bacterial identification rely on genomics and proteomics and use comparisons with databases of known strains, but the diagnostic value of metabolites and lipids has not been explored significantly. Standard mass spectrometry/chromatography methods involve multiple dilutions during sample preparation and separation. To increase the amount of chemical information acquired and the speed of analysis of lipids, multiple reaction monitoring profiling (MRM-Profiling) has been applied. The MRM-Profiling workflow includes a discovery stage and a screening stage. The discovery stage employs precursor (PREC) ion and neutral loss (NL) scans to screen representative pooled samples for functional groups associated with particular lipid classes. The information from the first stage is organized in precursor/product ion pairs, or MRMs, and the screening stage rapidly interrogates individual samples for these MRMs. In this study, we performed MRM-Profiling of lipid extracts from four different strains of Escherichia coli cultured with amoxicillin or amoxicillin/clavulanate, a β-lactam and β-lactamase inhibitor, respectively. t tests, analysis of variance and receiver operating characteristic (ROC) curves were used to determine the significance of each MRM. Principal component analysis was applied to distinguish different strains cultured under conditions that allowed or disallowed development of bacterial resistance. The results demonstrate that MRM-Profiling distinguishes the lipid profiles of resistant and nonresistant E. coli strains.

The worldwide increase in antimicrobial resistance is due to antibiotic overuse in agriculture and overprescription in medicine. For appropriate and timely patient support, faster diagnosis of antimicrobial resistance is required. Current methods for bacterial identification rely on genomics and proteomics and use comparisons with databases of known strains, but the diagnostic value of metabolites and lipids has not been explored significantly. Standard mass spectrometry/chromatography methods involve multiple dilutions during sample preparation and separation. To increase the amount of chemical information acquired and the speed of analysis of lipids, multiple reaction monitoring profiling (MRM-Profiling) has been applied. The MRM-Profiling workflow includes a discovery stage and a screening stage. The discovery stage employs precursor (PREC) ion and neutral loss (NL) scans to screen representative pooled samples for functional groups associated with particular lipid classes. The information from the first stage is organized in precursor/product ion pairs, or MRMs, and the screening stage rapidly interrogates individual samples for these MRMs. In this study, we performed MRM-Profiling of lipid extracts from four different strains of

Imaging mass spectrometry (MS) is a powerful technique for mapping the spatial distributions of a wide range of chemical compounds simultaneously from a tissue section. Co-localization of the distribution of individual molecular species, including particular lipids and proteins, and correlation with the morphological features of a single tissue section are highly desirable for comprehensive tissue analysis and disease diagnosis. We now report on the use, in turn, of desorption electrospray ionization (DESI), matrix assisted laser desorption ionization (MALDI), and then optical microscopy to image lipid and protein distributions in a single tissue section. This is possible through the use of histologically compatible DESI solvent systems, which allow for sequential analyses of the same section by DESI then MALDI. Hematoxylin and eosin (H&E) staining was performed on the same section after removal of the MALDI matrix. This workflow allowed chemical information to be unambiguously matched to histological features in mouse brain tissue sections. The lipid sulfatide (24:1), detected at m/z 888.8 by DESI imaging, was colocalized with the protein MBP isoform 8, detected at m/z 14117 by MALDI imaging, in regions corresponding to the corpus callosum substructure of the mouse brain, as confirmed in the H&E images. Correlation of lipid and protein distributions with histopathological features was also achieved for human brain cancer samples. Higher tumor cell density was observed in regions demonstrating higher relative abundances of oleic acid, detected by DESI imaging at m/z 281.4, and the protein calcyclin, detected by MALDI at m/z 10085, for a human glioma sample. Since correlation between molecular signatures and disease state can be achieved, we expect that this methodology will significantly enhance the value of MS imaging in molecular pathology for diagnosis.