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Direct imaging with multidimensional labelling and high-content analysis allows quantitative categorization and characterizations of individual small extracellular vesicles and nanoparticles (sEVPs). | LitMetric

AI Article Synopsis

  • * The study introduces a method using fluorescent labeling and advanced imaging techniques to categorize sEVPs from the same cell type into seven distinct subpopulations, revealing differences in composition and features.
  • * Findings suggest that this new characterization approach can help differentiate sEVPs from cancerous and normal cells, potentially improving diagnostic and therapeutic strategies related to these vesicles.

Article Abstract

Small extracellular vesicles and nanoparticles (sEVPs) are cell-secreted entities with potential as diagnostic biomarkers and therapeutic vehicles. However, significant intrinsic sEVP heterogeneity impedes analysis and understanding of their composition and functions. We employ multidimensional fluorescent labelling on sEVPs, leveraging the robustness of a newly developed membrane probe-conjugated oligoelectrolytes (COEs), and conduct total internal reflection fluorescence (TIRF) microscopy on sEVP arrays. These arrays comprise single sEVPs anchored to a soft material functionalized surface with little bias. We then develop an enhanced algorithm for colocalization analysis of the multiple labels on individual sEVPs and perform deep profiling of particle content. We categorize sEVPs derived from the same cell type into seven distinct subpopulations-some vesicular whereas others non-vesicular, and we demonstrate that sEVPs from four cell types exhibit quantitatively distinguishable subpopulation distributions. Furthermore, we gain insights into specific particle features within each subpopulation, including CD63 counts, relative particle size, relative concentration of cargoes, and correlations among different cargoes. This high-content analysis reveals common cargo sorting features in sEVP subpopulations across different cell types and suggests new statistics within the sEVP inherent heterogeneity that could differentiate sEVPs from two types of cancer cells and two types of normal cells. Collectively, our study presents a robust single-sEVP characterization platform, combining high-content imaging with comprehensive analysis. This platform is poised to advance sEVP-based theranostic assays and facilitate exploration into disease-associated sEVP biogenesis and sEVP-mediated intercellular communication.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11635478PMC
http://dx.doi.org/10.1002/jev2.12520DOI Listing

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