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キーワード:
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要旨:
Extracellular vesicles (EVs) provide a complex means of intercellular
signalling between cells at local and distant sites, both within and
between different organs. According to their cell-type specific
signatures, EVs can function as a novel class of biomarkers for a
variety of diseases, and can be used as drug-delivery vehicles.
Furthermore, EVs from certain cell types exert beneficial effects in
regenerative medicine and for immune modulation. Several techniques are
available to harvest EVs from various body fluids or cell culture
supernatants. Classically, differential centrifugation, density gradient
centrifugation, size-exclusion chromatography and immunocapturing-based
methods are used to harvest EVs from EV-containing liquids. Owing to
limitations in the scalability of any of these methods, we designed and
optimised a polyethylene glycol (PEG)based precipitation method to
enrich EVs from cell culture supernatants. We demonstrate the
reproducibility and scalability of this method and compared its efficacy
with more classical EV-harvesting methods. We show that washing of the
PEG pellet and the re-precipitation by ultracentrifugation remove a huge
proportion of PEG co-precipitated molecules such as bovine serum
albumine (BSA). However, supported by the results of the size exclusion
chromatography, which revealed a higher purity in terms of particles per
milligram protein of the obtained EV samples, PEG-prepared EV samples
most likely still contain a certain percentage of other non-EV
associated molecules. Since PEG-enriched EVs revealed the same
therapeutic activity in an ischemic stroke model than corresponding
cells, it is unlikely that such co-purified molecules negatively affect
the functional properties of obtained EV samples. In summary, maybe not
being the purification method of choice if molecular profiling of pure
EV samples is intended, the optimised PEG protocol is a scalable and
reproducible method, which can easily be adopted by laboratories
equipped with an ultracentrifuge to enrich for functional active EVs.
