Characterization and modulation of surface charges to enhance extracellular vesicle isolation in plasma

Extracellular vesicles (EVs) carry information inherited from parental cells, having significant potential for disease diagnosis. In blood, however, EVs are outnumbered >10(4)-fold by low density lipoproteins (LDLs), yet similar in size and density. These fundamental disadvantages often cause LDL spillover into EV isolates, thus confounding assay results. We hypothesized that EVs can be further separated from LDLs based on electric charge: EVs and LDLs have different lipid composition, which can lead to differential surface charge densities. To test this hypothesis, we modeled and quantified the surface charge of EVs and LDLs, and used the information to optimally separate EVs from LDLs via ion-exchange chromatography. Methods: We built an enhanced dual-mode chromatography (eDMC) device which performed i) size-exclusion to remove particles smaller than EVs and LDLs and ii) cation-exchange in an acidic elution to retain LDLs longer than EVs. The performance of the eDMC, in comparison to size-exclusion only, was evaluated by analyzing the yield and purity of the isolated EVs. Results: By measuring and modeling zeta potentials at different buffer pH, we estimated surface charge densities of EVs (-6.2 mC/m(2)) and LDLs (-3.6 mC/m(2)), revealing that EVs are more negatively charged than LDLs. Furthermore, the charge difference between EVs and LDLs was maximal at a weak acidic condition (pH = 6.4). By applying these findings, we optimized eDMC operation to enrich EVs directly from plasma, depleting >99.8% of LPPs within 30 min. Minimizing LDL contamination improved analytical signals in EV molecular assays, including single vesicle imaging, bulk protein measurements, and mRNA detection. Conclusions: These developments will promote the translational value of the dual-mode separation - a fast, equipment-free, and non-biased way for EV isolation from plasma samples.