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Automating Mammalian Cell Electroporation using Digital Microfluidics


Automating Mammalian Cell Electroporation using Digital Microfluidics

Leung, Ziuwin (2023) Automating Mammalian Cell Electroporation using Digital Microfluidics. Masters thesis, Concordia University.

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To examine a wide range of unique genetic edits, especially for cellular immunotherapy, techniques for automating mammalian cell engineering is needed while working with cell types that are rare and/or difficult to culture and expand. Herein, we introduce a miniaturized digital microfluidic module for electroporation of minimal number of mammalian cells (~40,000) at a time, potentially allowing for genetic engineering on a scalable and automated platform. The system functions by first merging three droplets together to form a continuous droplet chain. We call this the triDrop structure where the outer droplets contain high conductive liquids which are in contact with gold electrodes, while the middle droplet consists of low conductivity liquid containing the cells and target delivery molecule. This effectively creates a liquid cuvette where by applying a voltage, an effective electric field is generated within the triDrop structure with field focusing across the middle droplet. This allows for transient pore formation and insertion of biological payloads into cells without compromising long-term health by isolating cells from harmful electroporation effects. We show the proof-of-concept by successful delivery of a range of biological payloads (plasmid, mRNA, and Cas9 RNP) into adherent and suspension cells, including primary T cells. The flexibility and versatility of the triDrop, a digital microfluidic (DMF) electroporation module, suggests that our platform can be integrated with other DMF devices to allow for end-to-end automation of mammalian cell engineering. Additionally, this platform can potentially be used for the automation of large-scale genetic screens while using a single patient sample and low cell and reagent consumption.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Leung, Ziuwin
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:15 January 2023
Thesis Supervisor(s):Shih, Steve
ID Code:991732
Deposited By: Ziuwin Leung
Deposited On:21 Jun 2023 14:34
Last Modified:21 Jun 2023 14:34
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