ΔBOP最適化によるハイスループット機能細胞選別における大粒子回収率の向上

Flow cytometry is a critical technology for single-cell analysis; however, sorting large particles (> 30 μm) remains challenging owing to low recovery rates. This study investigated the relationship between particle size and the Break-off point (BOP) and assessed the impact of large particles on droplet formation through a combination of simulations and experiments. The results revealed that interference between the particle-induced BOP and vibration-driven BOP leads to droplet instability-identified as the key factor limiting recovery. We introduce ΔBOP as the difference between these two BOPs and propose an optimization strategy to stabilize droplet formation. Implementing this ΔBOP-based approach increased recovery from 72.2% (794/1100) to 92.4% (1016/1100) for 35-µm particles and from 23.0% (115/500) to 75.6% (378/500) for 50-µm particles. This strategy demonstrates broad applicability for high-throughput single-cell functional analyses involving various particle types, including hydrogel particles, double emulsions, and agarose beads, and opens new possibilities for applications such as secretion profiling and intercellular communication research.