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postgraduate thesis: Discovering druggable gene combinations for Parkinson's disease by CombiGEM-CRISPR
Title | Discovering druggable gene combinations for Parkinson's disease by CombiGEM-CRISPR |
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Authors | |
Advisors | |
Issue Date | 2019 |
Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
Citation | Chan, K. C. [陳迦靜]. (2019). Discovering druggable gene combinations for Parkinson's disease by CombiGEM-CRISPR. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. |
Abstract | Parkinson’s disease (PD) is the second most common neurodegenerative disease, affecting 1-2% of the general population aged 60 or above. Its cardinal motor features include resting tremor, rigidity and postural instability. Multigenic perturbations could lead to many human diseases, in which PD exhibits one of the most intricate networks of pathology. Discovering drug combinations that target the perturbed genes may contribute to alleviating motor symptoms and suppressing neurodegeneration in PD. However, conventional methods in identifying promising drug combinations are labor intensive and cost-ineffective. Our newly developed screening platform, combinatorial genetics en masse (CombiGEM)-CRISPR enables rapid assembly of barcoded combinatorial genetic libraries for high-throughput functional characterization of genetic perturbations. To facilitate the discovery of effective drug combinations, here we applied CombiGEM-CRISPR to explore the interactions between druggable genes in two widely used PD cell models. A pairwise guide RNA library comprising 7,569 combinations, targeting 28 druggable genes that are shown to modulate PD-associated toxicity, was assembled. Specific druggable gene knockouts that protect cells from rotenone- and MPP+ -induced toxicities in the two PD models were identified. Validations of specific gene sets were performed via individual assays with CRISPR-Cas-based knockouts and with drug pairs that directed against the identified pairwise hits. Dual knockout of HDAC2 and HSP90B1 were shown to have cell-protecting effect against PD-associated toxicity. We further validated the combinatorial effect by its drug pair in suppressing alpha-synuclein-induced degeneration in vivo using drosophila model. CombiGEM-CRISPR platform revealed potential druggable gene combinations that may ameliorate PD-associated toxicity. The identification of effective druggable gene combinations paves way for exploring therapeutic efficacy of pharmacological interventions for future therapeutic development. |
Degree | Master of Philosophy |
Subject | Parkinson's disease - Treatment |
Dept/Program | Biomedical Sciences |
Persistent Identifier | http://hdl.handle.net/10722/290316 |
DC Field | Value | Language |
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dc.contributor.advisor | Wong, SL | - |
dc.contributor.advisor | Jin, D | - |
dc.contributor.author | Chan, Ka Ching | - |
dc.contributor.author | 陳迦靜 | - |
dc.date.accessioned | 2020-10-27T01:34:29Z | - |
dc.date.available | 2020-10-27T01:34:29Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Chan, K. C. [陳迦靜]. (2019). Discovering druggable gene combinations for Parkinson's disease by CombiGEM-CRISPR. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. | - |
dc.identifier.uri | http://hdl.handle.net/10722/290316 | - |
dc.description.abstract | Parkinson’s disease (PD) is the second most common neurodegenerative disease, affecting 1-2% of the general population aged 60 or above. Its cardinal motor features include resting tremor, rigidity and postural instability. Multigenic perturbations could lead to many human diseases, in which PD exhibits one of the most intricate networks of pathology. Discovering drug combinations that target the perturbed genes may contribute to alleviating motor symptoms and suppressing neurodegeneration in PD. However, conventional methods in identifying promising drug combinations are labor intensive and cost-ineffective. Our newly developed screening platform, combinatorial genetics en masse (CombiGEM)-CRISPR enables rapid assembly of barcoded combinatorial genetic libraries for high-throughput functional characterization of genetic perturbations. To facilitate the discovery of effective drug combinations, here we applied CombiGEM-CRISPR to explore the interactions between druggable genes in two widely used PD cell models. A pairwise guide RNA library comprising 7,569 combinations, targeting 28 druggable genes that are shown to modulate PD-associated toxicity, was assembled. Specific druggable gene knockouts that protect cells from rotenone- and MPP+ -induced toxicities in the two PD models were identified. Validations of specific gene sets were performed via individual assays with CRISPR-Cas-based knockouts and with drug pairs that directed against the identified pairwise hits. Dual knockout of HDAC2 and HSP90B1 were shown to have cell-protecting effect against PD-associated toxicity. We further validated the combinatorial effect by its drug pair in suppressing alpha-synuclein-induced degeneration in vivo using drosophila model. CombiGEM-CRISPR platform revealed potential druggable gene combinations that may ameliorate PD-associated toxicity. The identification of effective druggable gene combinations paves way for exploring therapeutic efficacy of pharmacological interventions for future therapeutic development. | - |
dc.language | eng | - |
dc.publisher | The University of Hong Kong (Pokfulam, Hong Kong) | - |
dc.relation.ispartof | HKU Theses Online (HKUTO) | - |
dc.rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject.lcsh | Parkinson's disease - Treatment | - |
dc.title | Discovering druggable gene combinations for Parkinson's disease by CombiGEM-CRISPR | - |
dc.type | PG_Thesis | - |
dc.description.thesisname | Master of Philosophy | - |
dc.description.thesislevel | Master | - |
dc.description.thesisdiscipline | Biomedical Sciences | - |
dc.description.nature | published_or_final_version | - |
dc.date.hkucongregation | 2019 | - |
dc.identifier.mmsid | 991044178480603414 | - |