Building Dynamic Cellular Machineries in Droplet-Based Artificial Cells with Single-Droplet Tracking and Analysis.

Abstract

Although the application of droplet microfluidics has grown exponentially in chemistry and biology over the past decades, robust universal platforms for the routine generation and comprehensive analysis of droplet-based artificial cells are still rare. Here we report using microfluidic droplets to reproduce a variety of types of cellular machinery in in vitro artificial cells. In combination with a unique image-based analysis method, the system enables full automation in tracking single droplets with high accuracy, high throughput, and high sensitivity. These powerful performances allow broad applicability evident in three representative droplet-based analytical prototypes that we develop for (i) droplet digital detection, (ii) in vitro transcription and translation reactions, and (iii) spatiotemporal dynamics of cell-cycle oscillations. The capacities of this platform to generate, incubate, track, and analyze individual microdroplets via real-time, long-term imaging unleash its great potential in accelerating cell-free synthetic biology. Moreover, the wide scope covering from digital to analog to morphological detections makes this droplet analysis technique adaptable for many other divergent types of droplet-based chemical and biological assays.