Auto-ICell: An Automated and Cost-Effective Integrated Droplet Microfluidic Platform for Real-Time Analysis of Single-Cell Morphology and Apoptosis

Abstract

Existing single-cell analysis methods based on droplet microfluidics face challenges related to high chip costs and the lack of accurate, time-efficient, and high-throughput analysis techniques. To address these limitations, we present the Auto-ICell, a cost-effective droplet microfluidic system that integrates a 3D-printed microfluidic chip with automated image analysis algorithms. The Auto-ICell enables the generation of uniform droplet reactors and real-time analysis of single-cell morphology and apoptosis. With a throughput of 1,500 droplets per minute and droplet diameters ranging from 70 to 240 μm, the system employs colour-based and deep-learning-enabled algorithms for the analysis of droplet encapsulation and cell morphology, respectively. The Auto-ICell achieves an accuracy of over 91% and processes images in less than 0.03 seconds, eliminating the need for specialized facilities or trained operators. Its versatility extends to applications in cell culture, microreactors, drug carriers, assays, synthetic biology, and diagnostics. This study showcases the potential of the Auto-ICell system in advancing biological research and personalized disease treatment.