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A novel multiplex bead-based platform highlights the diversity of extracellular vesicles
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A novel multiplex bead-based platform highlights the diversity of extracellular vesicles
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A novel multiplex bead-based platform highlights the diversity of extracellular vesicles
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Journal Article
A novel multiplex bead-based platform highlights the diversity of extracellular vesicles
2016
Overview
The surface protein composition of extracellular vesicles (EVs) is related to the originating cell and may play a role in vesicle function. Knowledge of the protein content of individual EVs is still limited because of the technical challenges to analyse small vesicles. Here, we introduce a novel multiplex bead-based platform to investigate up to 39 different surface markers in one sample. The combination of capture antibody beads with fluorescently labelled detection antibodies allows the analysis of EVs that carry surface markers recognized by both antibodies. This new method enables an easy screening of surface markers on populations of EVs. By combining different capture and detection antibodies, additional information on relative expression levels and potential vesicle subpopulations is gained. We also established a protocol to visualize individual EVs by stimulated emission depletion (STED) microscopy. Thereby, markers on single EVs can be detected by fluorophore-conjugated antibodies. We used the multiplex platform and STED microscopy to show for the first time that NK cell-derived EVs and platelet-derived EVs are devoid of CD9 or CD81, respectively, and that EVs isolated from activated B cells comprise different EV subpopulations. We speculate that, according to our STED data, tetraspanins might not be homogenously distributed but may mostly appear as clusters on EV subpopulations. Finally, we demonstrate that EV mixtures can be separated by magnetic beads and analysed subsequently with the multiplex platform. Both the multiplex bead-based platform and STED microscopy revealed subpopulations of EVs that have been indistinguishable by most analysis tools used so far. We expect that an in-depth view on EV heterogeneity will contribute to our understanding of different EVs and functions.
