A proteomic meta-analysis refinement of plasma extracellular vesicles

Sci Data. 2023 Nov 28;10(1):837. doi: 10.1038/s41597-023-02748-1.

Abstract

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

Publication types

  • Meta-Analysis

MeSH terms

  • Animals
  • Antigens, CD / metabolism
  • Biomarkers
  • Datasets as Topic
  • Extracellular Vesicles* / metabolism
  • Humans
  • Proteins
  • Proteomics*
  • Signal Transduction

Substances

  • Antigens, CD
  • Biomarkers
  • Proteins