Nellikulam Davis, Alen (2020) Digital Microfluidics Chips for Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions. Masters thesis, Concordia University.
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Abstract
Microfluidics is a technology that facilitates the automation and miniaturization of biochemical experiments on platforms of small footprints. Among the different types of microfluidics platforms, digital microfluidics (DMF) devices execute an experiment by manipulating droplets of small volume (usually between 10-6 and 10-9 L) on an array of electrodes using the principles of electrowetting. These DMF chips provide control over individual droplets which enables users to perform multi-step or entirely different experiments without the need for any chip reconfiguration. DMF platforms can also be reused multiple times and can be integrated with other devices like a plate reader to monitor the progress of reactions in real-time. These advantages of DMF devices make them an ideal choice to automate end-end biochemical experiments.
In this work, we describe the design and performance of two digital microfluidics (DMF) chips capable of executing multiple ribozymatic reactions, with proper controls, in response to short single-stranded DNA inducers. Since the fluorescence output of a reaction is measurable directly from the chip, without the need for gel electrophoresis, a complete experiment, involving up to eight reactions (per chip) can be carried out reliably, relatively quickly and efficiently. The ribozymes can also be used as biosensors of the concentration of oligonucleotide inputs, with high sensitivity, low limits of quantification and of detection, and excellent signal-to-noise ratio. The presented chips are readily usable devices that can be used to automate, speed-up and reduce the costs of ribozymatic reaction experiments.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Nellikulam Davis, Alen |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Electrical and Computer Engineering |
Date: | 23 November 2020 |
Thesis Supervisor(s): | Kharma, Nawwaf and Shih, Steve |
ID Code: | 987692 |
Deposited By: | Alen Nellikulam Davis |
Deposited On: | 23 Jun 2021 16:33 |
Last Modified: | 23 Jun 2021 16:33 |
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