Researcher(s)
- Vilina Akala, Biomedical Engineering, University of Delaware
Faculty Mentor(s)
- Catherine Fromen, Chemical and Biomolecular Engineering, University of Delaware
Abstract
Research has shown the potential of macrophage-derived extracellular vesicles (EVs) as therapeutic delivery mechanisms. EVs offer several benefits as a drug delivery mechanism over nanoparticle-driven delivery, including non-toxicity, higher stability, low immunogenicity, and targeted active biologics. To realize their potential as novel therapeutics, recent work from the Fromen lab has demonstrated an approach to produce large quantities of macrophage-derived EVs through the administration of poly(ethylene glycol) diacrylate (PEGDA) nanoparticles (NPs). PEGDA NP internalization into macrophages amplifies the production of EVs, allowing NP-cargo to be transferred to the EVs. However, due to their inherent heterogeneity, an improved method to characterize the content and resultant phenotype of the produced EVs is required. To address this, we utilized magnetic bead capture with flow cytometry. EVs are captured from the solution using capture antibodies bound to micron-sized iron beads, which facilitates further antibody staining to assess protein expression on the captured EVs. This approach was successful in evaluating expression of pro- and anti-inflammatory markers (i.e. CD40, CD80, MHCii, CD11b) and enabled direct comparison between source cells and EVs. We report that EVs secreted from inflammatory macrophages showed inconsistent protein expression that differed with the source cells (inflammatory LPS-treated macrophages). Additionally, EVs secreted from macrophages dosed with NP had significantly different amounts of material encapsulation for varying incubation times. Magnetic bead capture showed that NPs internalized by macrophages transfer their fluorescent cargo to EVs, with the highest NP encapsulation shown for the 24-hour incubation time point. These results show a prospective method to load EVs with therapeutics effectively. Future studies could use this technique to identify inflammatory and anti-inflammatory proteins to serve as identifiers for functional EVs.