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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/173243
A simple method for the analysis of extracellular vesicles enriched for exosomes from human serum by capillary electrophoresis with ultraviolet diode array detection
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Extracellular vesicles (EVs) are membrane enclosed vesicles (<1 µm), such as exosomes (30-150 nm), involved in cell communication, which have important biological implications. In this study, EV preparations were enriched for exosomes from human serum by polyethylene glycol (PEG) precipitation. Different variables of the PEG precipitation method (i.e. concentration of PEG, filtration and centrifugation of the resuspended pellets) were evaluated by measuring the size of the isolated particles by dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA). In addition, a novel capillary electrophoresis-ultraviolet diode array (CE-UV-DAD) method was developed to obtain characteristic multiwavelength electrophoretic profiles of the EV preparations. Using EV preparations precipitated with 10% m/v of PEG, a background electrolyte (BGE) of 0.1 M Tris and 0.25 M boric acid at pH 7.9 with 0.5% m/v of hydroxypropyl cellulose (HPC) allowed reducing the adsorption of the EVs to the inner wall of the fused silica separation capillary. Sodium dodecyl sulfate (SDS) at 0.1% m/v was also necessary to enhance dispersibility, while homogenizing the charge of the particles to improve the size-dependent separation induced by HPC. Under these optimized conditions, a characteristic electrophoretic multiwavelength profile of the EV preparation and a standard of exosomes was obtained, and separation showed excellent reproducibility and appropriate analysis times. The obtained electrophoretic fingerprints are a simple, effective and complementary tool for the quality control of EV preparations.
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EL OUAHABI, Oumaima, et al. A simple method for the analysis of extracellular vesicles enriched for exosomes from human serum by capillary electrophoresis with ultraviolet diode array detection. Journal of Chromatography A. 2020. Vol. 1635, num. 461752. ISSN 0021-9673. [consulted: 12 of October of 2026]. Available at: https://hdl.handle.net/2445/173243