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. 2022 Feb 3;16(1):014102.
doi: 10.1063/5.0064265. eCollection 2022 Jan.

Robotic automation of droplet microfluidics

Affiliations

Robotic automation of droplet microfluidics

Tuan M Tran et al. Biomicrofluidics. .

Abstract

Droplet microfluidics enables powerful analytic capabilities but often requires workflows involving macro- and microfluidic processing steps that are cumbersome to perform manually. Here, we demonstrate the automation of droplet microfluidics with commercial fluid-handling robotics. The workflows incorporate common microfluidic devices including droplet generators, mergers, and sorters and utilize the robot's native capabilities for thermal control, incubation, and plate scanning. The ability to automate microfluidic devices using commercial fluid handling will speed up the integration of these methods into biological workflows.

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Figures

FIG. 1.
FIG. 1.
Main components of the RAD microfluidic setup. (a) Instrument consists of three components: (i) Commercial fluid-handling robot capable of processing, incubating, and analyzing fluids; (ii) a fluidic communication highway consisting of arrays of pumps and valves; (iii) a microfluidic breadboard consisting of common modules like droplet generators, picoinjectors, and sorters. (b) Schematic illustrating the instrument flow process. To use the microfluidic devices, the robot loads the requisite reagents into specialized wells connected to the pump array, aspirating and infusing them into the microfluidic devices at controlled flow rates. The entire instrument is controlled by a master computer. (c) Micrographs showing the microfluidic modules operated by the liquid-handling robot. Scale bar is 50 μm.
FIG. 2.
FIG. 2.
RAD microfluidic automation of ddPCR. (a) The ddPCR workflow consists of three steps, loading of robotically prepared reagents into syringe pumps, encapsulation into monodisperse droplets via flow focusing, and thermocycling of the emulsion aboard the robot. (b) We image samples of the cycled droplets, observing that they are monodisperse and exhibit the characteristic “digital” fluorescence of ddPCR assays. Scale bar is 100 μm.
FIG. 3.
FIG. 3.
Example RAD automation of a multistep workflow usable for in vitro evolution. (a) FITC solution is encapsulated by flow focusing and (b) and (c) the resulting monodispersed droplets are then thermocycled in the PCR machine on the robot. Scale bar is 100 μm. (d) The resulting droplets are merged with CFPRx-containing droplets via the merger device and then incubated. (e) Although the population exhibits polydispersity characteristic of this imperfect process, (f) fluorescence imaging finds a large fraction of the droplets appear to have properly paired and merged. Scale bar is 100 μm. The final population is then (g) sorted via FADS. (h) The pre-sorted droplets exhibit three populations, unmerged, 1:1 merged, and multiply merged, when viewed on a two-color fluorescence scatterplot. (i) By gating specific populations, the instrument recovers droplets with the desired fluorescence properties. Scale bar is 200 μm.

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