Smarter Cell Sorting: Droplet Microfluidics Meets Pick-and-Place Sorting

Abstract

Single-cell manipulation based on image-derived selection criteria is essential for morphology-based screening applications. This requires a fast and robust 'pick-and-place' technology to single-out the identified hits from the rest of the population. However, the overall efficiency of this process is influenced by several parameters, primarily constrained by the limitation of moving only one target at a time per cycle. To overcome this bottleneck, we present a system that employs a microfluidic droplet-based approach, enabling the sequential transfer of multiple objects in each cycle. The core of this system is the microfluidic transfer tool (MTT), which enables selected cells to be sequentially 'picked' and encapsulated into individual nanoliter-scale droplets. The resulting droplet sequence serves as a temporary storage buffer for the picked objects before they are transferred to a designated target. Here, hit-containing droplets can be individually 'placed' requiring just one global movement from source to target. To demonstrate the applicability of this approach, the developed MTT was integrated into an experimental robotic environment. Fluorescent particles of about 45 - 63 µm diameter and different colors were used to benchmark the system. This sequential microfluidic processing resulted in an overall performance improvement by a factor of approximately 20 compared to traditional single-object pick-and-place techniques. Detailed information about the MTT design and the overall workflow are provided.