Fluorescence-based sorting of extracellular vesicles enables detection and omics

Extracellular vesicles (EVs) are nanosized, lipid bilayer-enclosed particles that mediate intercellular communication and hold considerable promise as biomarkers and therapeutic agents. However, their functional heterogeneity remains incompletely understood, largely due to the absence of reliable methods for isolating specific EV subpopulations. Here, we established a Nanoscale Flow sorting (NanoFACS) workflow and evaluated its potential for EV detection, sorting, and molecular characterization. We assessed critical parameters, including fluorescent staining and labeling approaches, background signal discrimination, dilution and flow-rate effects, and scatter triggering. We achieved high-purity sorting of CFSE-stained and antibody-labeled EVs, preserving vesicle integrity and sufficient RNA yields for small RNA sequencing of sorted populations. We identified EV subtype-specific small RNAs despite partial cargo overlap in single-marker sorted populations. Our results establish a reproducible antibody-based NanoFACS workflow that defines key operational parameters for reliable EV detection and sorting, with potential adaptability across conventional and spectral flow cytometry platforms. By reducing background and non-EV-associated events, the workflow enables the isolation of phenotypically defined EV subpopulations suitable for downstream molecular analysis, providing a practical approach to investigate EV heterogeneity.