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Journal of Extracellular Vesicles







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On separation of EVs (also referred to as isolation, purification or concentration), MISEV2014 acknowledged that there is no consensus on an “optimal” method, such as ultracentrifugation, size exclusion or immunoaffinity. Instead, selection of a method should be guided by the relevant scientific question and downstream applications, and all details of the method should be provided to ensure reproducibility.

MISEV2014 recommended that EVcharacterization be performed at both the population and single vesicle levels. For the former, both positive and negative protein marker characterization was endorsed, following four categories of proteins: (1) transmembrane or lipid-bound EV protein, (2) EV cytosolic protein, (3) intracellular but not associated with plasma membrane or endosomes (i.e. relatively less abundant in exosomal EVs than in cells) and (4) extracellular but not typically EV-associated proteins. Several examples of proteins in each category were provided.

For characterization of single vesicles, as a means to assess population heterogeneity, MISEV2014 called for the use of at least two different but complementary technologies. For example, electron or atomic force microscopy could be paired with one of the single particle tracking methods. Furthermore, close-up images should be accompanied by wide-field views to allow assessment of heterogeneity.

For EV functional studies, MISEV2014 stated that quantitation of EVs and their activity should include dose–response studies. Process controls should be included, since contaminants might contribute activity. Use of density gradients was encouraged to show that any observed activity is intrinsic to EVs and not to closely associated, commonly co-purifying particles; alternatively, this activity should be depletable, e.g. by immunodepletion of EVs. Labelling studies were also recommended.

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Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License