Isolation and quantification of human urinary exosomes using a Tween-20 elution solvent from polyester,...

Exosomes, a subset of extracellular vesicles (EVs), are a type of membrane-secreted vesicle essential for intercellular communication. There is a great deal of interest in developing methods to isolate and quantify exosomes to study their role in intercellular processes and as potential therapeutic delivery systems. Polyester, capillary-channeled polymer fiber columns and spin-down tips are highly efficient, low-cost means of exosome isolation. As the methodology evolves, there remain questions as to the optimum elution solvent for specific end-uses of the recovered vesicles; fundamental biochemistry, clinical diagnostics, or therapeutic vectors.

While both acetonitrile and glycerol have been proven highly successful in terms of EV recoveries in the hydrophobic interaction chromatography workflow, many biological studies entail the use of the non-ionic detergent, Tween-20, as a working solvent. Here we evaluate the use of Tween-20 as the elution solvent for the recovery of exosomes. A novel 10-min, two-step gradient elution method, employing 0.1 % v/v Tween-20, efficiently isolated EVs at a concentration of ∼10¹¹ EV mL^-1 from a 100 μL urine injection. Integration of absorbance and multi-angle light scattering detectors in standard HPLC instrumentation enables a comprehensive single-injection determination of eluted exosome concentration and sizes. Transmission electron microscopy verifies the retention of the vesicular structure of the exosomes. The micro-bicinchoninic acid protein quantification assay confirmed high-purity isolations of exosomes (∼99 % removal of background proteins) SIGNIFICANCE: The effective use of Tween-20 as an elution solvent for exosome isolation/purification using capillary-channeled polymer fiber columns adds greater versatility to the portfolio of the approach. The proposed method holds promise for a wide range of fundamental biochemistry, clinical diagnostics, and therapeutic applications, marking a significant advancement in EV-based methodologies.