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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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
Nature Portfolio
Subjects
631/337/475
631/80/313
692/53
Analysis
Animals
Antigens
Antigens, CD - metabolism
Apoptosis
BASIC BIOLOGICAL SCIENCES
Beta cells
Biomarkers
Cell interactions
Contaminants
Datasets as Topic
Diabetes mellitus (insulin dependent)
Extracellular vesicles
Extracellular Vesicles - metabolism
Humanities and Social Sciences
Humans
Macrophages
Membrane trafficking
Meta-analysis
multidisciplinary
Proteins
Proteomics
Science
Science (multidisciplinary)
Signal Transduction
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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.
AbstractList 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.
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.
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.
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.
ArticleNumber 837
Author Nakayasu, Ernesto S.
Sims, Emily K.
Huang, Fei
Vallejo, Milene C.
Payne, Samuel H.
Powell, Samantha M.
Diaz Ludovico, Ivo
Ramanadham, Sasanka
Sarkar, Soumyadeep
Henry, Hayden R.
Elliott, Emily C.
Metz, Thomas O.
Mirmira, Raghavendra G.
You, Youngki
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  surname: Nakayasu
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Snippet Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles...
Abstract Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular...
Abstract Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular...
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SubjectTerms 631/337/475
631/80/313
692/53
Analysis
Animals
Antigens
Antigens, CD - metabolism
Apoptosis
BASIC BIOLOGICAL SCIENCES
Beta cells
Biomarkers
Cell interactions
Contaminants
Datasets as Topic
Diabetes mellitus (insulin dependent)
Extracellular vesicles
Extracellular Vesicles - metabolism
Humanities and Social Sciences
Humans
Macrophages
Membrane trafficking
Meta-analysis
multidisciplinary
Proteins
Proteomics
Science
Science (multidisciplinary)
Signal Transduction
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Title A proteomic meta-analysis refinement of plasma extracellular vesicles
URI https://link.springer.com/article/10.1038/s41597-023-02748-1
https://www.ncbi.nlm.nih.gov/pubmed/38017024
https://www.proquest.com/docview/2894594125
https://search.proquest.com/docview/2895259647
https://www.osti.gov/servlets/purl/2228423
https://pubmed.ncbi.nlm.nih.gov/PMC10684639
https://doaj.org/article/a7d72d2c446c44ff926f2c19bd0e61eb
Volume 10
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