Data · dataset · 2025
Unravelling Plasma Extracellular Vesicle Diversity With Optimised Spectral Flow Cytometry
Listed in San Raffaele Open Research Data Repository and Teesside University Research Data Repository — shown once because both records carry DOI 10.17632/7f2rzyv2zh.1
Extracellular vesicles (EVs) are crucial for intercellular communication and are found in various biological fluids.
Description
The identification and immunophenotyping of such small particles continue to pose significant challenges. Here, we have developed a workflow for the optimisation of a next-generation panel for in-depth immunophenotyping of circulating plasma EVs using spectral flow cytometry.
Our data collection followed a multistep optimisation phase for both instrument setup and 21-colour panel design, thus maximising fluorescent signal recovery. This spectral approach enabled the identification of novel EV subpopulations. Indeed, besides common EVs released by erythrocytes, platelets, leukocytes and endothelial cells, we observed rare and poorly known EV subsets carrying antigens related to cell activation or exhaustion.
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Notably, the unsupervised data analysis of major EV subsets revealed subpopulations expressing up to five surface antigens simultaneously. However, the majority of EVs expressed only a single surface antigen, suggesting they may not fully represent the phenotype of their parent cells. This is likely due to the small surface area or the biogenesis of EVs rather than antibody steric hindrance.
Finally, we tested our workflow by analysing the plasma EV landscape in a cohort of systemic lupus erythematosus (SLE) patients. Interestingly, we observed a significant increase in CD54+ EVs, supporting the notion of elevated circulating ICAM under SLE conditions. To our knowledge, these are the first data highlighting the importance of a spectral flow cytometry approach in deciphering the heterogeneity of plasma EVs paving the way for the routine use of a high-dimensional immunophenotyping in EV research.
Links
Where it is published
- DOI doi.org/10.17632/7f2rzyv2zh.1 ↗
DOI / persistent id · from ordr hsr it
Catalogue records · 2
- OAI-PMH record ordr.hsr.it/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Aordr… ↗
metadata API · from ordr hsr it
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Earth & Environmental Science · Immunology · Immunology
Provenance · 2 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| San Raffaele Open Research Data Repository | oai:ordr.hsr.it/7f2rzyv2zh.1 | 19 h ago | JSON v1 |
| Teesside University Research Data Repository | oai:data.mendeley.com/7f2rzyv2zh.1 | 10 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3204 | mapping · ordr hsr it | vocabulary-mapper@1.0.0 | keywords['Immunology'] |
| concepts[field].anzsrc:group:3204 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Immunology'] |
| concepts[field].local:field:earth-environmental | mapping · ordr hsr it | connector:ordr_hsr_it@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · ordr hsr it | connector:ordr_hsr_it@1.0.0 | /metadata/dc/description |
| license_text | source · ordr hsr it | connector:ordr_hsr_it@1.0.0 | |
| publication_date | source · ordr hsr it | connector:ordr_hsr_it@1.0.0 | |
| title | source · ordr hsr it | connector:ordr_hsr_it@1.0.0 | /metadata/dc/title |