研究生: |
張雅喬 Chang, Ya-Chiao |
---|---|
論文名稱: |
利用iTRAQ化學標定方法分析基因改造和非基因改造黃豆的差異蛋白質體學研究 Differential Proteomics of Genetically Modified and Non-genetically Modified Soybeans by iTRAQ Technology |
指導教授: |
陳頌方
Chen, Sung-Fang |
學位類別: |
碩士 Master |
系所名稱: |
化學系 Department of Chemistry |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 73 |
中文關鍵詞: | 基因改造 、黃豆 、蛋白質體學 、同重元素相對和絕對定量 、鹼性逆向層析 、等電點聚焦分離 、強陽離子交換層析 、液相層析質譜 |
英文關鍵詞: | genetically modified, soybeans, proteomics, iTRAQ, bRP, sIEF, SCX, LC-MS/MS |
DOI URL: | http://doi.org/10.6345/THE.NTNU.DC.040.2018.B05 |
論文種類: | 學術論文 |
相關次數: | 點閱:182 下載:6 |
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由於近年來人口數目增加及氣候的變遷,造成全球糧食的不足,於是促成基因改造作物蓬勃發展。雖然基因改造作物可以大幅改善缺糧現況,相對的也具有尚未無法證實的未知憂慮及安全性爭議。因此本實驗運用同重元素相對和絕對定量(iTRAQ)的化學標記方法搭配質譜技術,分析基因改造黃豆(DAS-81419-2)和非基因改造黃豆兩者的蛋白質相對含量變化。iTRAQ標定的胜肽樣品會先經由等電點聚焦分離儀(sIEF)、強陽離子交換層析法(SCX)以及鹼性逆向層析法(bRP)進行第一維分離,以降低樣品複雜度,同時藉由三種不同分餾方法提供互補性、正交性以利鑑定到更多的蛋白質。而後進行奈米級液相層析連接質譜儀分析。在此實驗中,總共鑑定到2648個蛋白質以及8831個不重複胜肽。在三種分餾方法中,鹼性逆向層析法效果最好。相較於僅使用鹼性逆向層析法,增加兩種分餾方法可多鑑定到34%的蛋白質及32%的不重複胜肽。此外使用生物資訊軟體分析在基因改造黃豆和非基因改造黃豆中,分析具有顯著差異蛋白質的生物路徑及功能,發現與核糖體、營養儲藏活性及細胞質等路徑有關。本研究為基因改造黃豆(DAS-81419-2)提供了新的觀點,並且期望此數據有利於基因改造作物未來發展。
Due to the increase of popularity and the change of global climate environment, the concern on global food crisis is growing. This phenomenon has caused the genetically modified organisms (GMOs) thriving in recent years. Although the GMOs can dramatically solve the global food crisis, there are some unknown anxieties and the safety issues which are suspicious to the public now. In this study, isobaric tags for relative and absolute quantitation (iTRAQ) technology was applied for the investigation of the protein profiles in both the genetically modified (GM, DAS-81419-2) and the non-genetically modified (non-GM) soybeans. The iTRAQ labeled peptides were fractionated by solution isoelectric focusing (sIEF), strong cationic exchange chromatography (SCX) and basic reverse phase chromatography (bRP), followed by nano-LC tandem mass spectrometric analysis. Two-dimensional liquid chromatography technique that employed on iTRAQ labeled peptides gave results with excellent complementarity, orthogonality and more protein identifications. A total of 2648 proteins including 8831 unique peptides were identified. Moreover, differentially expressed proteins were selected between the GM and the non-GM soybeans for the bioinformatics analysis. They were found in ribosome, nutrient reservoir activity, cytoplasmic pathway, and so on. We expect that it can be beneficial on its future development for genetically modified crops.
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