A proteomic meta-analysis refinement of plasma extracellular vesicles

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 separa...

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Bibliographic Details
Published inScientific data Vol. 10; no. 1; p. 837
Main Authors Vallejo, Milene C., Sarkar, Soumyadeep, Elliott, Emily C., Henry, Hayden R., Powell, Samantha M., Diaz Ludovico, Ivo, You, Youngki, Huang, Fei, Payne, Samuel H., Ramanadham, Sasanka, Sims, Emily K., Metz, Thomas O., Mirmira, Raghavendra G., Nakayasu, Ernesto S.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 28.11.2023
Nature Publishing Group
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Summary: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.
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USDOE
AC05-76RL01830; U01 DK127786; R01 DK060581; R01 DK133881; R01 DK121929; R01 DK126444
National Institutes of Health (NIH)
PNNL-SA-178237
ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-023-02748-1