An Automated Flow-Based/Digital Microfluidic Platform with on-Chip Optical Detection System for High-Throughput Gene Editing Processes

Iwai, K., Joint BioEnergy Institute
Gach, P., Joint BioEnergy Institute
Kim, P. W., Sandia National Laboratories
Raje, M., Joint BioEnergy Institute
Heinemann, J., Joint BioEnergy Institute
A. Duncombe, T., UCSF/UC Berkeley Joint Graduate Group in Bioengineering, University of California
Deng, K., Joint BioEnergy Institute
Northen, T., Joint BioEnergy Institute
Hillson, N. J., Joint BioEnergy Institute
Adams, P. D., Joint BioEnergy Institute
Singh, A. K., Joint Bioenergy Institute
We present a novel hybrid flow-based droplet and digital microfluidic system with integrated optical detection and electroporation functions. Unlike conventional microtiter plate based reactions, the droplet/digital optofluidic platform would allow completely automated genetic engineering steps using drastically smaller amounts of reagents and can be useful for application requiring high-throughput screening and reactions.

In recent years, synthetic biology has drawn significant interest for both scientific research and industrial applications such as biofuel and pharmaceutical production. Synthetic biology process requires multiple molecular biology steps making it a very time-consuming and labor-intensive effort. Using droplets as reaction chambers can be a powerful approach to improve the process with benefits including faster reactions, small volume of reagent consumption required, and better control of experimental environment. Researchers have developed numbers of microfluidic components and systems for microreactors, including flow-based droplet microfluidics [1] and electrical-based digital microfluidics (DMF) [2]. However, technical difficulties still remain to maintain both of efficiency and active control of droplets at the same time.

Here, we propose a hybrid platform of continuous-flow droplet microfluidics and DMF, integrated with on-chip optical detection. The system consists of four main parts; 1) continuous droplet generator to dispense uniform droplets, 2) multi-functional hybrid DMF to actively manipulate large numbers of droplets in a programmable manner, 3) optical detector to add on-chip capability for detection of enzymatic activities in discrete droplets, and 4) a pair of electrodes for on-chip electroporation process. Generated droplets with targets (e.g., cells) are sequentially arrayed at the multi-functional hybrid DMF part, merged with second group of droplets (e.g., DNA parts) with the DMF manipulations, and stored for incubation. Incubated droplets are transferred to the electroporation part for DNA transformation process. Droplets containing transformed cells are excited and detected with a laser beam through the optical fiber at the detection point of the optical detector/sorter. Detected signal initiates the DMF sorting process, and the droplets with fluorescence are captured and transported to the product outlet.

We experimentally verified our system. First, we successfully demonstrated the capability of the multi-functional DMF to trap, transport, and merge multiple aqueous droplets (~10 nl in volume) with Fluorescein in oil (HFE-7500 with 0.5 % PicoSurf surfactant) with 300 µm square chambers and electrodes. Next, we optically detected the droplets with 488nm laser excitation and an avalanche photodiode detector at the optical detector/sorter, and initiated DMF captured the fluorescent droplets. We additionally demonstrate the capability of our system for on-chip gene editing of Saccharomyces cerevisiaeutilizing the CRISPR-Cas9 based cloning-free toolkit we recently developed [3].

Results shown above clearly indicate the high-throughput and on-demand capabilities of the proposed hybrid droplet/digital optofluidic system, and we believe our automated system would significantly accelerate the synthetic biology researches and applications.


  1. S.-Y. The, et al., “Droplet Microfluidics,” Lab Chip, 2008, 8, 198-220. 
  2. P.C. Gach, et al., “A Droplet Microfluidic Platform for Automating Genetic Engineering,” ACS Synth. Biol., 2016, 5, 426-433. 
  3. A.R. Apel, et al., “A Cas9-Based Toolkit to program gene expression in Saccharomyces cerevisiae,” Nucleic Acids Res., 2017, 45, 496-508.