Method Matters: A Proteomics-Informed Framework for Selecting Extracellular Vesicle Isolation Methods for Plasma.

Authors

Scheila Julia Werle, Marie Louise Nautrup Therkelsen, Chen Meng, Mads Grønborg, Lise Lotte Gluud, Dres Damgaard

Published in

Journal of extracellular biology. Volume 5. Issue 9. Pages e70180. Epub Aug 29, 2026.

Abstract

Extracellular vesicles (EVs) hold significant promise as biomarkers, but their clinical application is constrained by variability in pre-analytical handling and isolation. EV isolation methods directly shape which plasma-derived EV-containing preparations are captured, yet systematic method comparisons across multiple analytical dimensions are limited. We comprehensively evaluated eleven EV isolation methods in pooled platelet-poor plasma (5 donors; 6 technical replicates/method). We further evaluated selected methods using five individual donors. EVs were quantified by NanoFCM, profiled for tetraspanins (CD9, CD63, CD81) via MSD assays, and further characterized by LC-MS/MS proteomics. We show that different EV isolation methods for plasma produce different EV containing preparation. EV isolation methods broadened proteome coverage in plasma but showed divergent performance. While all methods captured EVs in the 50-150 nm range, centrifugation and ultracentrifugation identified the broadest proteomes (up to 1093 proteins) driven by higher plasma protein carryover. Conversely, ExoEasy and qEV 70 isolated larger EVs and achieved stronger depletion of abundant plasma proteins but showed lower proteome coverage. A total of 117 proteins were detected across all isolation methods. Pre-clearing of samples removed contaminants but at the cost of protein identifications. We demonstrate that method selection must align with the specific analytical goal: centrifugation for comprehensive proteome profiling, affinity/size-exclusion methods for contaminant-sensitive assays, and precipitation for high-throughput applications. This systematic characterization provides an evidence-based framework and look-up resource for matching isolation strategies to downstream applications and research questions.

PMID:
42669007
Bibliographic data and abstract were imported from PubMed on 30 Aug 2026.

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