Until recently, complete understanding of the endogenous activity of pathologically relevant genes was out of reach and research was confined to in situ work, plasmid-based constructs and artificial model systems. The development and expansion of the CRISPR/Cas9 genome editing technique has enabled us to explore the molecular underpinnings of gene activation using the cell's own endogenous regulatory environment. In this work, we report on the development of a novel tool to monitor the endogenous activity of a causative gene in Parkinson's disease, a-synuclein. We use CRISPR/Cas9 to insert a highly sensitive engineered luciferase at the C-terminal of a-synuclein and assessed its responses to stimuli. Our system responds to epigenetic stimuli, which was unable to be recapitulated by previously available gene activity assays. After development of a sensitive detection tool for epigenetic stimuli, we focused on developed a modular suite of epigenetic writers and erasers by modification of the SunTag protein tagging system and used catalytically dead Cas9 (dCas9) to direct our modular epigenetic toolkit to individual genes. We show that our toolkit of epigenetic effectors successfully writes epigenetic information in a site-specific manner. Using the sensitive a-synuclein reporter we previously developed, we screen the promoter region of this pathologically relevant gene at high resolution and identify the most effective areas for epigenetic intervention in this cell line. These tools allow us to dissect and understand the endogenous regulatory mechanisms of almost any gene targetable by Cas9 in ways that were not previously available may prove to be an effective strategy for persistently altering pathologic transcriptional activity. This system offers a strong tool for to dissect and understand underlying epigenetic architecture and opens potential new avenues for therapeutic strategies for various disease conditions.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1597 |
| Date | 01 January 2020 |
| Creators | Adams, Levi |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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