Automated Proteomics Workflows for High-Throughput Library Generation and Biomarker Detection Using Data-Independent...

Area of Science:

• Proteomics
• Mass Spectrometry
• Bioinformatics

Background:

• Sequential window acquisition of all theoretical mass spectra-mass spectrometry (SWATH-MS) with bioinformatics is powerful for proteome analysis and biomarker discovery.
• Heterogeneous sample sources limit the broad application of SWATH-MS due to a lack of universal sample preparation methods.

Purpose of the Study:

• To develop universal, automated sample preparation workflows for SWATH-MS.
• To assess the efficacy of these workflows in characterizing proteomes from different animal species and disease models.

Main Methods:

• Development of a robotic sample preparation platform for automated workflows.
• Application of the platform to bovine and ovine specimens (healthy and myocardial infarction models).
• Proteomic analysis using SWATH-MS and bioinformatics.

Main Results:

• Achieved in-depth and reproducible proteome coverage and characterization.
• Demonstrated successful application across different animal species (bovine, ovine) and health/disease models.
• Validated findings with high correlation (R² = 0.85) between sheep proteomics and transcriptomics data.

Conclusions:

• Automated workflows provide a universal solution for sample preparation in SWATH-MS.
• The developed platform enhances reproducibility and depth of proteome analysis.
• These automated workflows have broad potential for clinical applications in veterinary medicine and animal research across species and disease states.