In a time in which the spread of multidrug resistant microorganisms is ever increasing, there is a need for fast and unequivocal identification of suspect organisms to supplement existing techniques in the clinical laboratory, especially in single bacterial colonies. Mass-spectrometry coupled with efficient peptide separation techniques offer great potential for identification of resistant-related proteins in complex microbiological samples in an unbiased manner. Here, we developed a capillary electrophoresis-electrospray ionization-tandem mass spectrometry CE-ESI-MS/MS bottom-up proteomics workflow for sensitive and specific peptide analysis with the emphasis on the identification of β-lactamases (carbapenemases OXA-48 and KPC in particular) in bacterial species. For this purpose, tryptic peptides from whole cell lysates were analyzed by sheathless CE-ESI-MS/MS and proteins were identified after searching of the spectral data against bacterial protein databases. The CE-ESI-MS/MS workflow was first evaluated using a recombinant TEM-1 β-lactamase, resulting in 68% of the amino acid sequence being covered by 20 different unique peptides. Subsequently, a resistant and susceptible Escherichia coli lab strain were analyzed and based on the observed β-lactamase peptides, the two strains could easily be discriminated. Finally, the method was tested in an unbiased setup using a collection of in-house characterized OXA-48 (n = 17) and KPC (n = 10) clinical isolates. The developed CE-ESI-MS/MS method was able to identify the presence of OXA-48 and KPC in all of the carbapenemase positive samples, independent of species and degree of susceptibility. Four negative controls were tested and classified as negative by this method. Furthermore, a number of extended-spectrum beta-lactamases (ESBL) were identified in the same analyses, confirming the multiresistant character in 19 out of 27 clinical isolates. Importantly, the method performed equally well on protein lysates from single colonies. As such, it demonstrates CE-ESI-MS/MS as a potential next generation mass spectrometry platform within the clinical microbiology laboratory.

The introduction of standardized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platforms in the medical microbiological practice has revolutionized the way microbial species identification is performed on a daily basis. To a large extent, this is due to the ease of operation. Acquired spectra are compared to profiles obtained from cultured colonies present in a reference spectra database. It is fast and reliable, and costs are low compared to previous diagnostic approaches. However, the low resolution and dynamic range of the MALDI-TOF profiles have shown limited applicability for the discrimination of different bacterial strains, as achieved with typing based on genetic markers. This is pivotal in cases where certain strains are associated with, e.g., virulence or antibiotic resistance. Ultrahigh resolution MALDI-FTICR MS allows the measurement of small proteins at isotopic resolution and can be used to analyze complex mixtures with increased dynamic range and higher precision than MALDI-TOF MS, while still generating results in a similar time frame. Here, we propose to use ultrahigh resolution 15T MALDI-Fourier transform ion cyclotron resonance (FTICR) MS to discriminate clinically relevant bacterial strains after species identification performed by MALDI-TOF MS. We used a collection of well characterized Pseudomonas aeruginosa strains, featuring distinct antibiotic resistance profiles, and isolates obtained during hospital outbreaks. Following cluster analysis based on amplification fragment length polymorphism (AFLP), these strains were grouped into three different clusters. The same clusters were obtained using protein profiles generated by MALDI-FTICR MS. Subsequent intact protein analysis by electrospray ionization (ESI)-collision-induced dissociation (CID)-FTICR MS was applied to identify protein isoforms that contribute to the separation of the different clusters, illustrating the additional advantage of this analytical platform.

The development of antibiotic resistance during treatment is a threat to patients and their environment. Insight in the mechanisms of resistance development is important for appropriate therapy and infection control. Here, we describe how through the application of mass spectrometry-based proteomics, a novel beta-lactamase Axc was identified as an indicator of acquired carbapenem resistance in a clinical isolate of Achromobacter xylosoxidans. Comparative proteomic analysis of consecutively collected susceptible and resistant isolates from the same patient revealed that high Axc protein levels were only observed in the resistant isolate. Heterologous expression of Axc in Escherichia coli significantly increased the resistance towards carbapenems. Importantly, direct Axc mediated hydrolysis of imipenem was demonstrated using pH shift assays and 1H-NMR, confirming Axc as a legitimate carbapenemase. Whole genome sequencing revealed that the susceptible and resistant isolates were remarkably similar. Together these findings provide a molecular context for the fast development of meropenem resistance in A. xylosoxidans during treatment and demonstrate the use of mass spectrometric techniques in identifying novel resistance determinants.

In this study, we developed an in-line methodology that combines analytical with pharmacological techniques to characterize metabolites of human histamine H4 receptor (hH4R) ligands. Liquid chromatographic separation of metabolic mixtures is coupled to high-resolution fractionation into 96- or 384-well plates and directly followed by a cell-based reporter gene assay to measure receptor signaling. The complete methodology was designed, optimized, validated, and ultimately miniaturized into a high-density well plate format. Finally, the methodology was demonstrated in a metabolic profiling setting for three hH4R lead compounds and the drug clozapine. This new methodology comprises integrated analytical separations, mass spectrometry, and a cell-based signal transduction–driven reporter gene assay that enables the implementation of comprehensive metabolic profiling earlier in the drug discovery process.

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