Large Extracellular Vesicles Can be Characterised by Multiplex Labelling Using Imaging Flow Cytometry

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Abstract

Extracellular vesicles (EVs) are heterogeneous in size (30 nm–10 µm), content (lipid, RNA, DNA, protein), and potential function(s). Many isolation techniques routinely discard the large EVs at the early stages of small EV or exosome isolation protocols. We describe here a standardised method to isolate large EVs from medulloblastoma cells and examine EV marker expression and diameter using imaging flow cytometry. Our approach permits the characterisation of each large EVs as an individual event, decorated with multiple fluorescently conjugated markers with the added advantage of visualising each event to ensure robust gating strategies are applied. Methods: We describe step-wise isolation and characterisation of a subset of large EVs from the medulloblastoma cell line UW228-2 assessed by fluorescent light microscopy, transmission electron microscopy (TEM) and tunable resistance pulse sensing (TRPS). Viability of parent cells was assessed by Annexin V exposure by flow cytometry. Imaging flow cytometry (Imagestream Mark II) identified EVs by direct fluorescent membrane labelling with Cell Mask Orange (CMO) in conjunction with EV markers. A stringent gating algorithm based on side scatter and fluorescence intensity was applied and expression of EV markers CD63, CD9 and LAMP 1 assessed. Results: UW228-2 cells prolifically release EVs of up to 6 µm. We show that the Imagestream Mark II imaging flow cytometer allows robust and reproducible analysis of large EVs, including assessment of diameter. We also demonstrate a correlation between increasing EV size and co-expression of markers screened. Conclusions: We have developed a labelling and stringent gating strategy which is able to explore EV marker expression (CD63, CD9, and LAMP1) on individual EVs within a widely heterogeneous population. Taken together, data presented here strongly support the value of exploring large EVs in clinical samples for potential biomarkers, useful in diagnostic screening and disease monitoring.

Bibliographical metadata

Original languageEnglish
Article number8723
Pages (from-to)1-23
Number of pages23
JournalInternational Journal of Molecular Sciences
Volume21
Issue number22
Early online date18 Nov 2020
DOIs
Publication statusPublished - 18 Nov 2020