Characterization of extracellular vesicles and artificial nanoparticles with four orthogonal single-particle analysis platforms
We compared four orthogonal technologies for sizing, counting, and phenotyping of extracellular vesicles (EVs) and synthetic particles. The platforms were: single-particle interferometric reflectance imaging sensing (SP-IRIS) with fluorescence, nanoparticle tracking analysis (NTA) with fluorescence, microfluidic resistive pulse sensing (MRPS), and nanoflow cytometry measurement (NFCM). Results were compared with standard EV characterization techniques such as transmission electron microscopy
... ctron microscopy (TEM) and Western blot (WB). EVs from the human T lymphocyte line H9 (high CD81, low CD63) and the promonocytic line U937 (low CD81, high CD63) were separated from culture conditioned medium (CCM) by differential ultracentrifugation (dUC) or a combination of ultrafiltration (UF) and size exclusion chromatography (SEC) and characterized per MISEV2018 guidelines. Mixtures of synthetic particles (silica and polystyrene spheres) with known sizes and/or concentrations were also tested. MRPS and NFCM returned similar particle counts, while NTA detected counts approximately one order of magnitude lower for EVs, but not for synthetic particles. SP-IRIS events could not be used to estimate particle concentrations. For sizing, SP-IRIS, MRPS, and NFCM returned similar size profiles, with smaller sizes predominating (per power law distribution), but with sensitivity typically dropping off below diameters of 60 nm. NTA detected a population of particles with a mode diameter greater than 100 nm. Additionally, SP-IRIS, MRPS, and NFCM were able to identify at least three of four distinct size populations in a mixture of silica or polystyrene nanoparticles. Finally, for tetraspanin phenotyping, the SP-IRIS platform in fluorescence mode and NFCM were able to detect at least two markers on the same particle. Based on the results of this study, we can draw conclusions about existing single-particle analysis capabilities that may be useful for EV biomarker development and mechanistic studies.