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Single extracellular vesicle transmembrane protein characterization by nano-flow cytometry

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posted on 2023-01-05, 09:33 authored by Rebecca Lees, Robert Tempest, Alice Law, Dimitri Aubert, Owen DaviesOwen Davies, Soraya WilliamsSoraya Williams, Nick Peake, Ben Peacock
Single particle characterization has become increasingly relevant for research into extracellular vesicles, progressing from bulk analysis techniques and first-generation particle analysis to comprehensive multi-parameter measurements such as nano-flow cytometry (nFCM). nFCM is a form of flow cytometry that utilizes instrumentation specifically designed for nano-particle analysis, allowing for thousands of EVs to be characterized per minute both with and without the use of staining techniques. High resolution side scatter (SS) detection allows for size and concentration to be determined for all biological particles larger than 45 nm, while simultaneous fluorescence (FL) detection identifies the presence of labeled markers and targets of interest. Labeled subpopulations can then be described in quantitative units of particles/mL or as a percentage of the total particles identified by side scatter. Here, EVs derived from conditioned cell culture media (CCM) are labeled with both a lipid dye, to identify particles with a membrane, and antibodies specific for CD9, CD63, and CD81 as common EV markers. Measurements of comparison material, a concentration standard and a size standard of silica nanospheres, as well as labeled sample material are analyzed in a 1-minute analysis. The software is then used to measure the concentration and size distribution profile of all particles, independent of labeling, before determining the particles that are positive for each of the labels. Simultaneous SS and FL detection can be utilized flexibly with many different EV sources and labeling targets, both external and internal, describing EV samples in a comprehensive and quantitative manner.

History

School

  • Sport, Exercise and Health Sciences

Published in

Journal of Visualized Experiments (JoVE)

Volume

185

Publisher

MyJove Corporation

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by MyJove Corporation under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported Licence (CC BY-NC-ND). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/3.0/

Publication date

2022-07-26

Copyright date

2022

ISSN

1940-087X

eISSN

1940-087X

Language

  • en

Depositor

Dr Owen Davies. Deposit date: 3 January 2023

Article number

e64020

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