High-throughput and multiplex single-molecule quantification and sorting of single EV

Extracellular vesicles (EVs) have gained significant attention for their diagnostic and therapeutic potential due to their unique protein and RNA cargo, which play key roles in cancers and other diseases. However, despite extensive research and investment, the clinical translation of EV biomarkers remains limited. A major challenge is that EVs from diseased tissues often have molecular similarities to those from healthy cells, with only subtle differences in their cargo. The specific packaging of molecular cargo in individual vesicles is believed to be crucial to their function, making bulk analysis methods insufficient. Single EV-level analysis is essential. Current approaches, relying on low-throughput, high-resolution imaging, are hindered by the vast number of EVs in clinical samples like blood (~1010 EVs/mL). To overcome this, we propose Agarose Bead-based Digital Single Molecule-Single EV Sorting (BDEVS), a high- throughput microfluidic platform for ultra-sensitive profiling of individual EVs in plasma. Unlike conventional methods, BDEVS provides single-molecule sensitivity and multiplexing (>5 targets) without compromising throughput, analyzing millions of EVs per minute. The platform uses rolling circle amplification (RCA) of cleaved EV surface proteins, which are amplified in microscale agar droplets, followed by flow cytometry-based readout and sorting. This approach addresses previous limitations such as steric hindrance, non-specific binding, and limited protein quantification on EVs.