Quantitative proteogenomics of human pathogens using DIA-MS.

Area of Science:

• Microbiology
• Genomics
• Proteomics

Background:

• Bacterial genome and proteome data integration is crucial for understanding virulence.
• Existing methods face challenges in combining diverse genomic and proteomic datasets.

Purpose of the Study:

• To develop a strategy for integrating genome and quantitative proteome data from genetically similar bacterial strains.
• To enable rapid interrogation of combined datasets for insights into bacterial virulence.

Main Methods:

• Construction of a composite genome integrating all genetic data.
• Application of data-independent analysis mass spectrometry (DIA-MS) for quantitative proteome measurements.
• Fusion of genomic data with quantitative peptide and protein information.

Main Results:

• Demonstrated method with 34 clinical isolates of Streptococcus pyogenes using whole genome sequencing, shotgun MS, and DIA-MS.
• Developed a data structure for fast exploration, revealing undetected proteins are more amenable to amino acid substitution.
• Identified significantly differentially expressed proteins between invasive and non-invasive strains.

Conclusions:

• The integrated approach advances the interpretation of genome-proteome-virulence relationships.
• Accurate quantification of proteomes alongside whole genome sequencing enhances understanding of bacterial pathogens.