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

Selvam Paramasivan1,2, Janna L Morrison3, Mitchell C Lock3

  • 1School of Veterinary Science, The University of Queensland, Gatton, QLD 4343, Australia.

Journal of Proteome Research
|May 23, 2023
PubMed
Summary
This summary is machine-generated.

Automated sample preparation for mass spectrometry enables comprehensive proteome analysis in animals. This robotic platform improves reproducibility and supports diverse clinical applications for health and disease research.

Keywords:
FASPSWATHautomationbiomarker discoverydata-independent acquisitionfilter-aided sample preparationmyocardial infarction

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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.