ArticleProteomics2026
Image Analysis Platform for Comprehensive Quantification of Extracellular Vesicle Morphology.
Article in Proteomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
Extracellular vesicles (EVs) are membrane-encapsulated nanoparticles with key roles in cell biology and growing importance in biomedicine. However, EVs are challenging to characterize because they are highly heterogeneous. Single EV analysis methods are valuable tools for addressing this challenge. Here, we developed single EV analysis pipeline for assessment of transmission electron microscopy (TEM) and single molecule localization microscopy (SMLM) images. Our analysis of morphology and localization/density patterns from these imaging techniques identified two primary EV classes which we termed dense and complex. Compared to dense EVs, complex EVs were larger, less circular, and more elongated. For recombinant and cell culture-derived EVs, analysis revealed overall good agreement between TEM and SMLM data. Using SMLM, we further compared plasma EVs enriched in common markers, tetraspanins CD9, CD63, and CD81, with the total EV population. While both groups showed similar size and shape properties, tetraspanin-enriched EVs were on average slightly larger and exhibited a higher fraction of complex EVs. Our findings underscore the morphological diversity of EVs; highlight the benefits of multimodal imaging; and demonstrate quantitative performance of the data analysis pipeline. Our comprehensive analysis of EV morphology may ultimately help clarify EV biogenesis and advance their potential in biomedicine. STATEMENT OF SIGNIFICANCE OF THE STUDY: Extracellular vesicles (EVs) have significant roles in biology and biomedicine. However, their inherent heterogeneity in size, shape, and molecular composition presents a major challenge for their characterization. To help address this challenge, we advanced a robust image analysis pipeline. We used this pipeline to analyze transmission electron microscopy and single molecule localization microscopy images, and we comprehensively quantified morphology of single EVs. By classifying EVs into distinct morphological subtypes, dense and complex, we reveal consistent trends across recombinant, cell line-derived, and plasma EVs. Importantly, we demonstrate strong agreement between imaging modalities. Our approach enables high-resolution analysis of individual EVs and offers insights into their structural diversity. This work advances the methodological toolkit for EV research and lays the foundation for improved characterization of EVs in biology and biomedicine.
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