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Automating Gene Editing Using Digital Microfluidics to Decipher Cancer Pathways

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Automating Gene Editing Using Digital Microfluidics to Decipher Cancer Pathways

Sinha, Hugo ORCID: https://orcid.org/0000-0003-0284-7195 (2018) Automating Gene Editing Using Digital Microfluidics to Decipher Cancer Pathways. Masters thesis, Concordia University.

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Abstract

Gene-editing techniques such as RNA-guided endonuclease systems are becoming increasingly popular for phenotypic screening. Such screens are normally conducted in arrayed or pooled formats. There has been considerable interest in recent years to find new technological methods for conducting these gene-editing assays. We report here the first digital microfluidic method that can automate arrayed gene-editing in mammalian cells. Functional microfluidic devices were designed and optimized to produce repeatable experiments and validate the relevant biological processes on device. Specifically, this method was useful in culturing lung cancer cells for up to six days, as well as implementing automated gene transfection and knockout procedures. In addition, a standardized imaging pipeline to analyse fluorescently labelled cells was also designed and implemented during these procedures. A gene editing assay for interrogating the MAPK/ERK pathway was performed to show the utility of our platform and to determine the effects of knocking out the RAF1 gene in lung cancer cells. In addition to gene knockout, we also treated the cells with an inhibitor, Sorafenib Tosylate, to determine the effects of enzymatic inhibition. The combination of enzymatic inhibition and guide targeting on device resulted in lower drug concentrations for achieving half-inhibitory effects (IC50) compared to cells treated only with the inhibitor, confirming that lung cancer cells are being successfully edited on the device. We propose that this system will be useful for other types of gene-editing assays and applications related to personalized medicine.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Sinha, Hugo
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:25 May 2018
Thesis Supervisor(s):Shih, Steve
ID Code:984645
Deposited By: HUGO SINHA
Deposited On:31 Oct 2018 16:27
Last Modified:31 Oct 2018 16:27
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