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

Sequential window acquisition of all theoretical mass spectra-mass spectrometry underpinned by advanced bioinformatics offers a framework for comprehensive analysis of proteomes and the discovery of robust biomarkers. However, the lack of a generic sample preparation platform to tackle the heterogeneity of material collected from different sources may be a limiting factor to the broad application of this technique. We have developed universal and fully automated workflows using a robotic sample preparation platform, which enabled in-depth and reproducible proteome coverage and characterization of bovine and ovine specimens representing healthy animals and a model of myocardial infarction. High correlation ( = 0.85) between sheep proteomics and transcriptomics datasets validated the developments. The findings suggest that automated workflows can be employed for various clinical applications across different animal species and animal models of health and disease.