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Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
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Image Analysis Platform for Comprehensive Quantification of Extracellular Vesicle Morphology.

Alexander Spark1, Nan Jiang2, Benjamin Purnell2

  • 1Nanometrix Ltd, Oxford, UK.

Proteomics
|February 27, 2026
PubMed
Summary

We developed a new pipeline to analyze single extracellular vesicles (EVs) using advanced microscopy. This method classifies EVs into "dense" and "complex" types, revealing their diverse morphology and improving EV characterization for biomedicine.

Keywords:
Extracellular vesicles (EVs)Single Extracellular VEsicle Nanoscopy (SEVEN)Single Extracellular Vesicle AnalysisSingle Molecule Localization Microscopy (SMLM)Transmission electron microscopy (TEM)

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Area of Science:

  • Biomedical research
  • Cell biology
  • Nanotechnology

Background:

  • Extracellular vesicles (EVs) are crucial in cell communication and biomedicine.
  • EV heterogeneity poses significant characterization challenges.
  • Single EV analysis is vital for understanding EV diversity.

Purpose of the Study:

  • To develop a robust pipeline for single EV morphological analysis.
  • To classify EVs into distinct subtypes using multimodal imaging.
  • To compare EV morphology across different sources and marker enrichments.

Main Methods:

  • Developed a single EV analysis pipeline for Transmission Electron Microscopy (TEM) and Single Molecule Localization Microscopy (SMLM) data.
  • Quantified EV morphology, including size, circularity, and elongation.
  • Utilized SMLM to compare total EVs with tetraspanin-enriched EVs.

Main Results:

  • Identified two primary EV classes: dense and complex, with complex EVs being larger and more elongated.
  • Demonstrated good agreement between TEM and SMLM analyses.
  • Found tetraspanin-enriched EVs to be slightly larger and have a higher proportion of complex EVs compared to the total population.

Conclusions:

  • The developed pipeline effectively quantifies single EV morphology, highlighting significant structural diversity.
  • Multimodal imaging and the classification of EVs into dense and complex subtypes advance EV characterization.
  • This work provides a foundation for clarifying EV biogenesis and enhancing their biomedical applications.