臺灣博碩士論文加值系統

神經鞘脂類(Sphingolipid)廣泛存於全身細胞中，不只可組成細胞膜結構，亦可傳遞訊號，調控細胞存亡。其代謝途徑中間產物神經醯胺(Ceramide)與鞘氨醇-1-磷酸(Sphingosine 1-phosphate)更分別被稱為抑癌脂質及促癌脂質，目前市面上的化療藥物，如：唐黴素注射劑(Daunorubicin)、醫百幸注射劑(Etoposide)等，皆被證實促使神經醯胺生成，進而使細胞凋亡。
本研究综合文獻及資料庫生物信息，重建整合人體鞘脂代謝途徑，使網路圖譜涵蓋脂肪酸代謝、磷脂代謝及醣解途徑。並運用系統生物學概念，使用軟體工具確認此代謝網路為滿秩矩陣系統，在最大Sphingomyelin phosphodiesterase及最小Sphinganine kinase催化速率此多目標函數情況下，最能夠累積神經醯胺並同時最小生成鞘氨醇-1-磷酸。並於此多目標情況下調控酵素活性，模擬生物體受干擾狀態下的最適通量分布，獲得結果Serine palmitoyltransferase、3-dehydrosphinganine reductase及Hexokinase此三酵素為此系統必須酵素，Ceramide synthase酵素為最具影響神經醯胺生成量的酵素，此模擬結果相符於化療藥物所激活酵素，藉此達到醫療效果。

Sphingolipids are widely existed in the cells, which are not only the composition of cell membrane structure but also transmit signals regulating cell survival. Its metabolic pathway intermediates Ceramide and Sphingosine 1-phosphate are known as Tumor suppressor lipid and Cancer-promoting lipid respectively. Currently chemotherapy drugs, such as: Daunorubicin and Etoposide are known to promote Ceramide generation, thereby enabling apoptosis.
In this research, we integrate literature and biological databases information into the human sphingolipid metabolic pathway, which include fatty acid metabolism, phospholipid metabolism and the glycolytic pathway. We adopt the system biology concept to confirm this system for the full rank matrix, and then we regulate enzyme activity in the case of Maximum Sphingomyelin phosphodiesterase and minimum Sphinganine kinase catalytic rate to learn about organisms' response and meaning. Finally, we conclude that Serine palmitoyltransferase, 3-dehydrosphinganine reductase and Hexokinase are indispensable enzymes in this system, Ceramide synthase is the main Ceramide synthesizer enzyme, consistent with the chemotherapy drug experiment results.

摘要 II
ABSTRACT III
目錄 IV
圖目錄 VII
表目錄 X

第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 4
1.3 研究動機 5
1.4 組織章節 6

第二章 代謝網路建立與分析 7
2.1 生物資料庫簡介 7
2.1-1 Kyoto Encyclopedia of Genes and Genomes (KEGG) 7
2.1-2 BioPath Database 8
2.1-3 BRaunschweig ENzyme DAtabase (BRENDA) 8
2.2 網路分析-使用軟體簡介 11
2.2-1 CellNetAnalyzer (CNA) 11
2.2-2 General Algebraic Modeling Systrm (GAMS) 11
2.3 網路分析-線性最適化 13
2.3-1 問題描述 13
2.3-2 目標函數 15
2.3-3 限制條件 15
2.4 網路模式運算分析 16
2.4-1 通量平衡分析(Flux Balance Analysis, FBA) 16
2.4-2通量變異性分析(Flux Variability Analysis, FVA) 17
2.4-3 FBA突變問題 (FBA for Knockout Mutant, FBA_MUT) 18
2.4-4 最小代謝調控分析 (Minimization Of Metabolic Adjustment, MOMA) 18
2.4-5 最小開關代謝通量調控分析 (Regulatory On/Off Minimization Of Metabolic Flus, ROOM) 19

第三章 重建代謝網路 20
3.1 酵母菌鞘脂代謝途徑 20
3.2 人類鞘脂代謝途徑雛形 24
3.3 重建整合人類鞘脂代謝途徑 26
3.4鞘脂結構及相關疾病 31

第四章 基因調控最適通量分布 40
4.1 引言 40
4.2 利用分析軟體檢測系統 40
4.3通量變異性分析(FVA)結果 43
4.4通量平衡分析(FBA)結果 44
4.5調控酵素通量結果 48
4.5-1調控鞘脂途徑標靶酵素 48
4.5-2 調控神經鞘脂儲積症(Sphingolipidosis)相關酵素 59
4.5-3 調控圖譜各交換反應 61

第五章 結論與未來展望 93
5.1 結論 93
5.2 未來展望與建議 96

文獻回顧 97
附錄A_代謝物資訊 100
附錄B_代謝反應式資訊 103

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