Optimization of a Top-Down Proteomics Platform for Closely Related Pathogenic Bacterial Discrimination

Area of Science:

• Clinical microbiology
• Proteomics
• Mass spectrometry

Background:

• Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is standard for microbial identification but has limitations with closely related species.
• Existing databases may lack sufficient reference data for accurate identification.

Purpose of the Study:

• To develop and optimize an LC-MS/MS top-down proteomics platform for discriminating closely related pathogenic bacteria.
• To identify specific proteoforms as potential biomarkers for bacterial identification.

Main Methods:

• Optimization of protein extraction, on-line liquid chromatography (LC) separation, MS/MS method, and data analysis using *Escherichia coli* as a model.
• Application of the platform to differentiate enterobacterial pathogens that are indistinguishable by MALDI-TOF MS.

Main Results:

• Identification of approximately 220 proteins and over 500 proteoforms in a single run with optimized parameters.
• Discovery of specific proteoforms for discriminating between enterobacterial pathogens with different clinical outcomes.
• Improved characterization of poorly described bacterial strains.

Conclusions:

• Top-down proteomics, by analyzing proteoforms, offers superior accuracy for bacterial characterization compared to peptide-based methods.
• The developed LC-MS/MS platform shows significant potential as a tool in clinical microbiology for accurate pathogen identification and characterization.