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

Tue Bjerg Bennike, Melena D. Bellin, Yue Xuan, Allan Stensballe, Frederik Trier Møller, Gregory J. Beilman, Ofer Levy, Zobeida Cruz-Monserrate, Vibeke Andersen, Judith Steen, Darwin L. Conwell, Hanno Steen*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

33 Citations (Scopus)

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 dataindependent 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-membranebased 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.
Original languageEnglish
JournalJournal of Proteome Research
Volume17
Issue number5
Pages (from-to)1983-1992
Number of pages10
ISSN1535-3893
DOIs
Publication statusPublished - 19 Apr 2018

Keywords

  • plasma
  • serum
  • TPIAT
  • biomarker
  • data-independent acquisition
  • proteomics

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