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

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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Publication Details

Journal
Journal of Extracellular Vesicles
Published
2024-12-01
DOI
https://doi.org/10.1002/jev2.12520
Citations
5
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
1.17

Funders

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article

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

Sarah J. Cox‐Vázquez, Jay T. Groves, Simou Sun, Guillermo Carlos Bazan et al.
5 citations
Journal of Extracellular Vesicles
Extracellular vesicles in disease
1.17
article

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

Sarah J. Cox‐Vázquez, Jay T. Groves, Simou Sun, Guillermo Carlos Bazan, Nam‐Joon Cho
article en
5 citations

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.

Journal of Extracellular VesiclesVol. 13(12)
National University of Singapore (SG), Nanyang Technological University (SG), Stony Brook University (US), University of California, Berkeley (US)
National University of Singapore, Ministry of Education - Singapore, Nanyang Technological University, Ministry of Education, India
Life below water
Openalex Percentile: Top 21%
Extracellular vesicles in disease
1.17
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