Functional enzymatic assays to predict the potency of extracellular vesicles
The application of extracellular vesicles (EVs) as therapeutics or nanocarriers in cell-free therapies necessitates meticulous evaluations of different features, including their identity, bioactivity, batch-to-batch reproducibility, and stability. Given the inherent heterogeneity in EV preparations, this assessment demands sensitive functional assays to provide key quality control metrics, complementing established methods to ensure that EV preparations meet the required functionality and quality standards. Here, we introduce the detectEV assay, an enzymatic-based approach for assessing EV luminal cargo bioactivity and membrane integrity. This method is fast, cost-effective, and quantifiable through enzymatic units. Utilizing microalgae-derived EVs, known as nanoalgosomes, as model systems, we optimized the assay parameters and validated its sensitivity and specificity in quantifying the enzymatic activity of esterases within the EV lumen while also evaluating EV membrane integrity. Compared to conventional methods that assess physicochemical features of EVs, our single-step analysis efficiently detects batch-to-batch variations by evaluating changes in luminal cargo bioactivity and integrity across various EV samples, including differences under distinct storage conditions and following diverse isolation and exogenous loading methods, all using small sample sizes. The detectEV assays application to various human-derived EV types demonstrated its versatility and potential universality. Additionally, the assay effectively predicted EV functionality, such as the antioxidant activity of different nanoalgosome batches. Our findings underscore the detectEV assays utility in comprehensive characterization of EV functionality and integrity, enhancing batch-to-batch reproducibility and facilitating their therapeutic applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/563745v3_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1b1c552org.highwire.dtl.DTLVardef@11a70eorg.highwire.dtl.DTLVardef@eec5b7org.highwire.dtl.DTLVardef@1f699dd_HPS_FORMAT_FIGEXP M_FIG C_FIG