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Cerebrospinal fluid-derived extracellular vesicles: a proteomic and transcriptomics comparative analysis of enrichment protocols

GSE300627 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2025/08/20 Platform GPL24676
Summary
Proteomic and transcriptomic analyses of cerebrospinal fluid (CSF)-derived extracellular vesicles (EVs) offer unique insights into molecular changes associated with central nervous system (CNS) diseases and may result in biomarker identification. No gold standard method to enrich EVs from CSF is established and head-to-head comparisons of outputs of different protocols s’ outputs are scarce. Using a large pool of CSF, we characterized the EV preparations resulting from four enrichment protocols and compared them in terms of yield and purity. We found that particles enriched by ultracentrifugation (UC) or a combination of ultrafiltration and size exclusion chromatography (UF-SEC) bared exhibited the typical morphological and biochemical characteristics of small EVs and were highly enriched in proteins and polyadenylated transcripts associated with EV-related biological processes. UF-SEC preparations had higher particle yields while more proteins were identified in UC preparations. Approximately 40% of the EV preparations’ proteome was not identified in unenriched CSF, among which a core proteome of 45 proteins identified in 30 EV preparations from independent experiments which may serve as CSF-derived EV markers. Enrichment scores to protein contaminants albumin and apolipoprotein E were higher in UF-SEC preparations. In conclusion, all protocols analyzed here resulted in enrichment of particles with small EVs characteristics, with EV enrichments from UF-SEC resulting in highest yield and purity.
Published in
Cerebrospinal Fluid-Derived Extracellular Vesicles: A Proteomic and Transcriptomic Comparative Analysis of Enrichment Protocols
García-Arauzo M, Reymond S, Gruaz L et al. · Journal of extracellular biology 2025 · PMID 40791568 · doi:10.1002/jex2.70076
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Also filed as BioProject PRJNA1281578 and SRA study SRP594353. Searching any of these in the dataset finder brings you back here.

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