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研究生: 杜建達
Tu, Chien-Ta
論文名稱: 慢性投予甲基安非他命與海洛因之動態網路比較
Comparison of Dynamic Networks following Chronic Treatment with Methamphetamine and Heroin
指導教授: 陳博現
Chen, Bor-Sen
口試委員: 呂忠津
林澤
藍忠昱
黃宣誠
阮雪芬
吳謂勝
學位類別: 博士
Doctor
系所名稱: 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 77
中文關鍵詞: 動態網路甲基安非他命海洛因
外文關鍵詞: Dynamic Networks, Methamphetamine, Heroin
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  • 藥物成癮的過程會造成人類腦部永久性且不可逆的傷害,現已成為世界上日益關切的問題。而在眾多違禁藥物中,甲基安非他命(神經興奮性藥物)與海洛因(鴉片類止痛鎮定藥物),會對多巴胺神經傳遞系統產生神經毒性,從而導致藥物使用上的耐受性以及生理上的依賴性。雖然在哺乳動物大腦中許多影響藥物成癮過程的因子及藥物誘導基因表現上的改變已被分析得到,但藉由比較長期藥物濫用之後,蛋白質間交互作用的動態網路,可以從系統的觀點上提供藥物成癮發展過程中新的見識。在本文研究中,我們以蛋白質間交互作用相關資訊以及基因動態表現數據為根據,透過使用動態模型分別建構在慢性投予生理食鹽水,甲基安非他命與海洛因後的三組蛋白質交互作用網路。隨後,我們從投予甲基安非他命與海洛因對比於投予生理食鹽水的蛋白質交互作用網路,比較網路結構與蛋白質之間調控的不同,並且估算每個蛋白質交互作用對象的總改變(TCI)以及交互能力上的差異(DIA),藉此找到分別在甲基安非他命與海洛因成癮過程中可能扮演重要角色的蛋白質。而此比較方法除了可以作為臨床或學術實驗前的篩選工具,用以找出值得更進一步探討的新蛋白質外,並藉此了解藥物成癮過程的相關機制,進而成為藥物成癮干預療法的起點。


    Drug addiction, a growing problem worldwide with recent concerns, results in long-lasting harmful effects to the human brain. Methamphetamine (MA) and Heroin (HER) are illicit drugs known to exert neurotoxic effects on the dopaminergic systems leading to the development of tolerance and physical dependence. Although many factors affecting addictive processes and drug-induced gene expression changes in the brain have been analyzed, comparing protein-protein interaction (PPI) networks exposure to drugs of abuse may provide new insights into the development of addiction from the systematic point of view. In this study, based on PPI information and gene expression profiles, a dynamic model is employed to reconstruct three PPI networks corresponding to chronic treatment with saline (SAL), MA, and HER, respectively. Subsequently, we compare the difference of network structure and compute the total changed interactions (TCI) and differential interactive ability (DIA) from MA-treated and HER-treated PPI networks versus SAL-treated PPI network to discover potential proteins that play critical roles in MA and HER addictive process, respectively. This comparison method can be employed as a pre-experiment screening approach to reveal new potential proteins for further characterization to understand the underlying mechanisms in addictive process, serving as the starting point of therapeutic intervention for drug addiction.

    摘要 i Abstract ii 誌謝 iii Contents iv Lists of Figures vi Lists of Tables vii 1. Introduction 1 2. Materials and Methods 6 2.1 Overview of PPI Network Construction Framework 6 2.2 Data Selection and Process 6 2.3 Constructing the Candidate Protein-Protein Interaction Network (PPIN) 7 2.4 Dynamic Model for Protein Interaction Network 8 2.5 Determination of Significant Interaction Pairings 12 2.6 Comparison Scheme between Two PPI Networks 13 3. Results 18 3.1 Construction of PPI Networks Corresponding to Chronic Treatment with SAL, MA, and HER, Respectively 18 3.2 Differential Networks following Chronic Exposure to MA or HER 19 3.3 Utilization of Dynamic PPI Networks to Identify Common Proteins with Important Roles following Chronic Treatment with MA or HER 20 3.4 Utilization of Dynamic PPI Networks to Identify Proteins with Important Roles after Chronic Exposure to MA 24 3.5 Utilization of Dynamic PPI Networks to Identify Proteins with Important Roles after Chronic Exposure to HER 27 4. Discussion 30 5. Conclusion 35 Bibliography 36 Figure 1- Flowchart of the proposed method to construct the protein-protein interaction network (PPIN) 48 Figure 2- Schematic diagrams in illustration of PPIN comparison by calculation of the total changed interactions (TCI) in the differential PPI network 50 Figure 3- Schematic diagrams in illustration of computing differential interactive ability (DIA) 51 Figure 4- Venn diagram shows the overlap of proteins both involved in the processes of MA and HER addiction 52 Table 1: Refined protein-protein interaction network 53 Table 2: Construction of gain-of-interactions and loss-of-interactions subnetworks 54 Table 3: Proteins with PPI changes and total changed interactions in the differential network of MA and HER, respectively 55 Table 4: Proteins with changed interactions involved in the biological processes following chronic treatment with MA 56 Table 5: Proteins with changed interactions involved in the biological processes following chronic treatment with HER 57 Table 6: Proteins with the largest changes in both PPI number and differential interactive ability (DIA) after chronic treatment with MA 58 Table 7: Proteins with the largest changes in both PPI number and differential interactive ability (DIA) after the chronic treatment with HER 61

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