Blood is an ideal body fluid for the discovery or monitoring of diagnostic and prognostic protein biomarkers. However, discovering robust biomarkers requires the analysis of large numbers of samples to appropriately represent interindividual variability. To address this analytical challenge, we established a high-throughput and cost-effective proteomics workflow for accurate and comprehensive proteomics at an analytical depth applicable for clinical studies. For validation, we processed 1 μL each from 62 plasma samples in 96-well plates and analyzed the product by quantitative data-independent acquisition liquid chromatography/mass spectrometry; the data were queried using feature quantification with Spectronaut. To show the applicability of our workflow to serum, we analyzed a unique set of samples from 48 chronic pancreatitis patients, pre and post total pancreatectomy with islet autotransplantation (TPIAT) surgery. We identified 16 serum proteins with statistically significant abundance alterations, which represent a molecular signature distinct from that of chronic pancreatitis. In summary, we established a cost-efficient high-throughput workflow for comprehensive proteomics using PVDF-membrane-based digestion that is robust, automatable, and applicable to small plasma and serum volumes, e.g., finger stick. Application of this plasma/serum proteomics workflow resulted in the first mapping of the molecular implications of TPIAT on the serum proteome.
Keywords: TPIAT; biomarker; data-independent acquisition; plasma; serum.