C. H. Chen's Lab
Microfluidic Digital Medicine
Time-resolved single-cell secretion analysis via microfluidics
Ying Xu, Mei Tsz Jewel Chan, Ming Yang, Heixu Meng and Chia-Hung Chen*
Lab on a Chip
Revealing how individual cells alter their secretions over time is crucial for understanding their responses to environmental changes. Key questions include: When do cells modify their functions and states? What transitions occur? Insights into the kinetic secretion trajectories of various cell types are essential for unraveling complex biological systems. This review highlights seven microfluidic technologies for timeresolved single-cell secretion analysis: 1. Microwell real-time electrical detection: uses microelectrodes for precise, cell-specific, real-time measurement of secreted molecules. 2. Microwell real-time optical detection: employs advanced optical systems for real-time, multiplexed monitoring of cellular secretions. 3. Microvalve real-time optical detection: dynamically analyzes secretions under controlled in situ stimuli, enabling detailed kinetic studies at the single-cell level. 4. Droplet real-time optical detection: provides superior throughput by generating droplets containing single cells and sensors for high-throughput screening. 5. Microwell time-barcoded optical detection: utilizes sequential barcoding techniques to facilitate scalable assays for tracking multiple secretions over time. 6. Microvalve time-barcoded optical detection: incorporates automated time-barcoding via micro-valves for robust and scalable analysis. 7. Microwell time-barcoded sequencing: captures and labels secretions for sequencing, enabling multidimensional analysis, though currently limited to a few time points and extended intervals. This review specifically addresses the challenges of achieving high-resolution timing measurements with short intervals while maintaining scalability for single-cell screening. Future advancements in microfluidic devices, integrating innovative barcoding technologies, advanced imaging technologies, artificial intelligencepowered decoding and analysis, and automations are anticipated to enable highly sensitive, scalable, highthroughput single-cell dynamic analysis. These developments hold great promise for deepening our understanding of biosystems by exploring single-cell timing responses on a larger scale.