A Cost-Effective High-Throughput Plasma and Serum Proteomics Workflow Enables Mapping of the Molecular Impact of Total Pancreatectomy with Islet Autotransplantation

Abstract

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.

Figure 1.

Triplicate analysis of a pooled plasma sample. A) Coefficient of variance (CV) for features found in all three replicates with median CV, number of features, and color-coded point density (light blue, highest density; green, lowest density). B) Proteins ranked on increasing CV. C) Concentration-range of the plasma proteins as represented by intensity-based absolute quantitation (iBAQ) values.

Figure 2.

Absolute concentration of the quantifiable plasma proteins with the workflow, demonstrating a dynamic range covering over 7 orders of magnitude. Averaged data from The Plasma Proteome Database is reported.

Figure 3.

Proteins with a sex-specific abundance. Pregnancy zone protein (PZP, o) and sex hormone-binding protein (SHBG, o) was significantly decreased in male plasma compared to female. + indicates not significantly changed proteins. The black curve represents the statistical significance cutoff (FDR < 0.05)

Figure 4.

Proteins with post vs pre TPIAT specific abundance. The black curve represents the statistical significance cutoff (FDR < 0.05). □: more abundant post; o: less abundant post, +: not significantly changed.