2. Academic Validation
  3. High-throughput single-vesicle imaging platform for direct extracellular vesicle profiling of human plasma

High-throughput single-vesicle imaging platform for direct extracellular vesicle profiling of human plasma

  • Nat Commun. 2026 Apr 23;17(1):5600. doi: 10.1038/s41467-026-72179-0.
Chungmin Han 1 2 3,  Arek V Melkonian 1 2 3,  Justin C Rolando 1 2 3,  Sara Whiteman 1,  David R Walt 4 5 6
Affiliations

Affiliations

  • 1 Wyss Institute for Biologically Inspired Engineering, Boston, MA, USA.
  • 2 Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
  • 3 Harvard Medical School, Boston, MA, USA.
  • 4 Wyss Institute for Biologically Inspired Engineering, Boston, MA, USA. [email protected].
  • 5 Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA. [email protected].
  • 6 Harvard Medical School, Boston, MA, USA. [email protected].
PMID: 42020418 DOI: 10.1038/s41467-026-72179-0
Abstract

Extracellular vesicles (EVs) are nanoscale particles secreted by cells that carry diverse biomolecules reflecting their cell of origin. Single-EV imaging approaches have enabled precise characterization of heterogeneous EV populations; however, their broader application is limited by low-throughput workflows and cumbersome EV isolation procedures. Here, we introduce a streamlined, high-throughput imaging platform capable of analyzing protein expression of individual intact EVs directly from unprocessed biological samples at the single-vesicle level. Our approach employs a functionalized glass surface optimized for high-throughput single-EV imaging, facilitating specific capture of EVs and enabling integration with existing automation technologies. We evaluate the platform's analytical capabilities by characterizing various recombinant EV samples and demonstrate its clinical utility by analyzing EVs in a total of 191 human plasma samples with high-throughput efficiency. This technology will offer a pathway for high-precision and large-scale characterization of EVs in clinical samples.

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