Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics

Antoine Lesur, François Bernardin, Eric Koncina, Elisabeth Letellier, Gary Kruppa, Pierre Olivier Schmit, Gunnar Dittmar*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Blood analysis is one of the foundations of clinical diagnostics. In recent years, the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. To demonstrate the method’s full potential, we used an isotope-labeled synthetic peptide mix of 782 peptides, derived from 579 plasma proteins, spiked into blood plasma samples with a prm-PASEF measurement allowing the quantification of 565 plasma proteins by targeted proteomics. As a less time-consuming alternative to the prm-PASEF method, we describe guided data independent acquisition (dia)-PASEF (g-dia-PASEF) and compare its application to prm-PASEF for measuring blood plasma. To demonstrate both methods’ performance in clinical samples, 20 patient plasma samples from a colorectal cancer (CRC) cohort were analyzed. The analysis identified 14 differentially regulated proteins between the CRC patient and control individual plasma samples. This shows the technique’s potential for the rapid and unbiased screening of blood proteins, abolishing the need for the preselection of potential biomarker proteins.

Original languageEnglish
Pages (from-to)1630-1638
Number of pages9
JournalJournal of Proteome Research
Volume22
Issue number6
Early online date3 Apr 2023
DOIs
Publication statusPublished - 2 Jun 2023

Keywords

  • biomarker
  • colorectal cancer
  • CRC
  • DIA
  • PASEF
  • plasma
  • PRM
  • SIL peptides
  • targeted proteomics

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