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研究生: 李怡慧
Li, Yi-Hui
論文名稱: 最佳化結合二氧化鈦與免疫親和法豐富化酪胺酸磷酸化蛋白質體之策略
Optimizing the strategy of combining TiO2- and immunoaffinity- based enrichment methods for tyrosine phosphoproteome
指導教授: 廖寶琦
Liao, Pao-Chi
學位類別: 碩士
Master
系所名稱: 醫學院 - 環境醫學研究所
Department of Environmental and Occupational Health
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 46
中文關鍵詞: 酪胺酸磷酸化二氧化鈦豐富化技術免疫親和沉澱豐富化技術
外文關鍵詞: tyrosine phosphorylation, TiO2-based enrichment, immunoaffinity-based enrichment
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  • 在真核細胞中,蛋白質磷酸化是重要的轉譯後修飾之一且調節許多生理功能。由許多文獻指出,酪胺酸殘基磷酸化的蛋白質(P-Tyr)參與癌細胞的生成。因為酪胺酸磷酸化蛋白質的含量僅占人體的總蛋白質體含量的百分之一,所以在複雜樣本基質中鑑定酪胺酸磷酸化蛋白質需要一個有效的方法。文獻回顧中有許多豐富化磷酸化胜肽的程序但只有少數專注於酪胺酸磷酸化胜肽。到目前為止,也尚未提出選擇性地豐富化酪胺酸磷酸化胜肽之標準程序。因此我們提出一個以雷射基質輔助脫附-飛行時間質譜儀分析找出最佳化結合二氧化鈦與免疫親和法豐富化的策略以針對酪胺酸磷酸化蛋白質體之研究。而我們利用豐富化係數來評估不同實驗參數下豐富化酪胺酸磷酸化胜肽的豐富化效率。結果顯示,最佳化的二氧化鈦豐富化方法在載樣溶液pH1.5與流洗溶液pH12.0,此豐富化係數為10305。在免疫親和法豐富化部分,Tris-HCl pH9.0緩衝溶液系統之最佳的豐富化係數為1405較MOPS佳。接著評估結合二氧化鈦接著免疫親和法豐富化為最有效且選擇性豐富化酪胺酸磷酸化胜肽的方法。此外我們也證實在不同實驗條件下,液相層析串聯質譜儀分析所得到的豐富化係數之趨勢與雷射基質輔助脫附-飛行時間質譜儀相同,且所需要分析時間較短且快速。

    Protein phosphorylation is one of the crucial post-translational modifications and regulates many biological functions in eukaryote cells. Several studies revealed that phosphorylation of protein tyrosine residues are involved in carcinogenesis. Thus, the identification of tyrosine phosphorylated proteins require an efficient method from a complex sample matrix since the relative abundance of phosphotyrosine (P-Tyr) proteins only around 1% of the total human phosphoproteome. There are many procedures published for phosphopeptide enrichment, but only a few focusing on tyrosine phosphopeptides. So far there is no standard protocol to be followed for selective enrichment of tyrosine phosphopeptides. Here, we propose an analytical strategy of combining the optimized TiO2- enrichment experimental conditions and immunoaffinity- based enrichment methods for phosphotyrosine-specific phosphoproteomics analysis using MALDI-TOF MS analysis. We applied an enrichment factor to evaluate enrichment efficiency for pTyr peptides in many different parameters. The results showed that the optimized TiO2 enrichment is in loading solution pH 1.5 and elution solution pH 12.0 with enrichment factor 10305. The optimized immunoaffinity enrichment in Tris incubation buffer system pH9.0 with enrichment factor 1450 is higher than MOPS buffer. A combination of sequential TiO2 and immunoaffinity is the most effective and selective enrichment method for phosphotyrosine peptides. Additionally, enrichment factors evaluated by LC-MS yielded similar results as those obtained by MALDI-TOF MS analysis.

    摘要 I Abstract II Content III List of Tables V List of Figures VI Abbreviations VIII Chapter 1 Overview of the research 1 1.1 Background 1 1.2 Objectives 2 Chapter 2 Literatures Review 3 2.1 Post-translational modification (PTMs) 3 2.1.1 Protein phosphorylation 3 2.1.2 Tyrosine-phosphoproteomics in the study of cancer and clinical application 4 2.2 The enrichment techniques for phosphoproteome 5 2.2.1 Metal oxide-affinity purification, TiO2 5 2.2.2 Immunoaffinity enrichment 6 2.3 Previous studies of parameters in TiO2 microcolumn enrichment 7 2.4 Previous studies of parameters in immunoaffinity enrichment 8 Chapter 3 Materials and Methods 9 3.1 Research scheme 9 3.2 Preparation of tryptic digestion BSA 11 3.2.1 Phosphopepetides and peptide mixtures preparation 11 3.3 Phosphopeptide enrichment methods 13 3.3.1 TiO2 micro-columns enrichment 13 3.3.2 Immunoaffinity enrichment by pTyr-specific antibodies 14 3.4 Mass spectrometry analysis 15 3.4.1 MALDI-TOF mass spectrometry 15 3.4.2 Liquid chromatography –mass sepectrometry (LC-MS) analysis 16 Chapter 4 Results and Discussion 17 4.1 Definition of enrichment factor for determining the optimized condition 17 4.2 Optimized phosphopeptide enrichment using TiO2 micro-columns 19 4.3 Optimized phosphopeptides enrichment using immunoaffinity 24 4.3.1 Immunoaffinity enrichment in Tris buffer system 24 4.3.2 Immunoaffinity enrichment in MOPS buffer system 25 4.4 Comparison the combing two optimized enrichment methods 33 4.5 Comparison of the enrichment factor between MADLI-TOF MS analysis and LC-MS analysis 38 Chapter 5 Conclusions 41 Chapter 6 References 42

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