博碩士論文 102284602 詳細資訊




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姓名 羅詩謎(Rashmi Madda)  查詢紙本館藏   畢業系所 生命科學系
論文名稱 用蛋白質組學方法鑑定係統性紅斑狼瘡患者血漿差異表達蛋白及其功能預測
(Using proteomic approach to identify the differentially expressed proteins in plasma from systemic lupus erythematosus and their function prediction)
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摘要(中) 全身紅斑性狼瘡 (SLE) 是一種慢性發炎且病程複雜的自體免疫性疾病,會讓免疫系統產生誤判並錯誤地攻擊健康組織,其發病的原因至今不明,此病不僅會影響皮膚、關節、腎臟、大腦,也會影響其他器官。人體的血漿包含超過十倍濃度的蛋白質與滲漏組織,這些蛋白質的數量及組成的變化在人體各種疾病中扮演著重要角色,血清或血漿中蛋白質表達之差異在疾病診斷和專一性治療的生物標記應用上具有潛力。因此,本研究之目標是用蛋白質體學方法鑑定SLE病患與健康對照組之間的血漿蛋白表現量與轉譯後修飾的差異,並驗證具有顯著之蛋白質。針對 19 位 SLE 病情活動度大於 8 、抗雙股 DNA 之抗體力價 ≥1:640、腎臟損傷的 SLE 病人和 12 名健康組進行對照,使用膠體與非膠體之蛋白質體學方法,比較二組血漿蛋白體的差異。利用高解析液相層析電噴灑離子化串聯質譜儀進行無標記定量以及轉譯後修飾分析,鑑定具有顯著差異之蛋白質。利用二者方法比較兩組蛋白質體變化,總共有29種蛋白質在兩種方法中出現顯著差異,其中有21種蛋白如補體C4 ,補體因子H ,載脂蛋白B-100 ,免疫球蛋白重鏈和輕鏈,糖蛋白和幾種急性反應蛋白,在病人血漿中表現量上升 > 1.5-3倍;8 種蛋白包括甲狀腺結合前蛋白,載脂蛋白 J ,纖维蛋白原γ鏈,血红素 α 亞基,血清轉鐵蛋白、血清白蛋白、α1-抗胰蛋白酶、凝血酶等,表現量則下降 <0.2-0.6倍。 GO 及 DAVID 功能富集分析 (GO and DAVID functional enrichment analysis) 顯示這些蛋白質參與幾項重要的生理代謝,包含急性發炎反應、補體活化、免疫系統的調節與平衡。這些被鑑定出之差異表現蛋白與SLE病患具有相關性,可能誘發免疫系統之失衡與發炎反應,或是影響泌尿系統功能。此外,我們還透過 MODa 和 PEAKS 8.5 軟體分析 SLE 病人血漿蛋白體,與健康對照組相比, SLE 病人中有 3850個獨特的胜肽鏈位在 83 種轉譯後修飾的蛋白質上。這些轉譯後修飾蛋白使用 Universal Protein Resource 資料庫分析,而部分的轉譯後修飾蛋白同時在我們的蛋白質體學分析結果中,如表現量上升的免疫球蛋白重鏈和輕鏈、α2巨球蛋白、血銅藍蛋白、血红素 β 亞基、血紅素結合蛋白、載脂蛋白B、α1酸性糖蛋白;表現量下降的纖维蛋白原γ鏈、補體C4 以及血清轉鐵蛋白。這些蛋白的轉譯後功能修飾包含乙醯化、羧化、甲基化、脱水、磷酸化、羥基化、甲醯化、醯胺化、硫酸化。這些轉譯後修飾可能影響蛋白質在多種生化反應,包含與免疫系統間的調控、定位以及相互作用。本研究方法的建立可以有效提升分析 SLE 病人血漿中蛋白質的量和質的差異,除驗證前人發現的相關蛋白質外,亦發現他人未鑑定與疾病相關的候選蛋白,並首度發現大量的轉錄後修飾,可能扮演病程的角色,這些結果具有作為SLE疾病評估或監測之生物標記。
摘要(英) Systemic lupus erythematosus (SLE) is a complicated chronic inflammatory autoimmune disease with unknown etiology. It distresses the body′s immune system and mistakenly attacks healthy tissues. Consequently, it affects the skin, joints, kidneys, brain, and other organs of the body. Human plasma is comprised of ten orders of magnitude concentration of proteins and tissue leakages. The change of the abundance and modifications of these proteins have been playing important roles in various human diseases. Therefore, the differential expression of proteins in the serum/plasma has potential clinical applications including in serving as diagnosis or treating targets. Thus, the research objective of this study is to identify the significantly altered expressions in both abundance and posttranslational modifications of plasma proteins from SLE patients. We compared those aspects to the healthy controls using proteomics approach. The 19 SLE patients had been shown to be in active disease stage with average systemic lupus erythematosus activity index (SLEDAI) score of more than 8. All the recruited patients showed high titers of anti-ds DNA antibodies along with anti-nuclear antibodies (ANA test of ≥1:640) plus low levels of complement indicating the presence of proteinuria along with nephritis symptoms. In this study, the patient plasma samples were compared to 12 healthy controls. The plasma proteome were analyzed using both gel-based and gel-free proteomic methodologies. The high-resolution electrospray ionization liquid chromatography-tandem mass spectrometry followed by label-free quantification and post-translational modifications (PTMs) analysis was employed to identify the significantly altered proteins. A total of 29 proteins showed a significant level of differential expressions combining the results from both electrophoresis and liquid chromatography separating methods. The 21 proteins including complement C4, complement factor H, apolipoprotein B-100, immunoglobulin heavy and light chains, few glycoproteins and several acute phase reactant proteins had > 1.5-3 fold up-regulation. Eight proteins including transthyretin, clusterin, fibrinogen gamma chain, hemoglobin subunit alpha, serotransferrin, serum albumin, alpha-1 antitrypsin and hemopexin have been shown to be down-regulated with <0.2-0.6 fold. The GO and DAVID functional enrichment analysis revealed that these proteins involved in several important biological processes including acute phase inflammatory responses, complement activation, homeostasis, and immune system regulation. Thus, the identified differentially expressed proteins are relevant to SLE patient’s cohort and that are proposed to be involved in the imbalance of the immune system and inflammatory responses. Some might be potential candidates for the renal system involvement in SLE pathogenesis. In addition, a total of 3,850 unique peptides mapped to 83 proteins with PTMs were identified in SLE plasma compared to healthy controls using both MODa and PEAKS 8.5 software. The annotations of the identified proteins were further confirmed using Universal Protein Resource Website. Furthermore, the PTMs were also found in several up-regulated proteins identified by our proteomics approach. They are immunoglobulin heavy and light chains, alpha-2 macroglobulin, ceruloplasmin, hemoglobin subunit beta, haptoglobin, apolipoprotein B, alpha-1 acid glycoproteins. The PTMs also found in the down-regulated proteins including fibrinogen gamma chain, complement C4, serotransferrin. The modifications include acetylation, carboxylation, methylation, dehydration, phosphorylation, hydroxylation, formylation, amidation and sulfation. The PTMs might play roles in modulating the functions of the proteins in various biological activities including regulation, localization and interactions with other cellular components of the immune system. In summary, these findings have the potential to be further investigated to be used as prognostic/diagnostic markers for SLE.
關鍵字(中) ★ 系統性紅斑狼瘡
★ 蛋白質組學
★ 基於凝膠的蛋白質組學
★ 液相色譜串聯質譜法
★ 蛋白質譜
★ 蛋白質功能預測
關鍵字(英) ★ Systemic lupus erythematosus
★ Proteomics
★ Gel-based proteomics
★ Liquid chromatography tandem mass spectrometry
★ Protein profile
★ Protein function prediction
論文目次 Table of Contents
Abstract: vii
中文摘要 viii
Acknowledgments ix
Chapter I: Introduction 1
1.1 Systemic Lupus Erythematosus 1
1.1.1 SLE Patients manifestations 1
1.1.2 Diagnosis: 2
1.1.3 ACR-SLE diagnostic criteria 2
1.1.4 Imaging studies 3
1.1.5 Pathophysiology 3
1.1.6 Etiology 4
1.1.7 Environmental and exposure-related causes of SLE: 5
1.1.8 Prognosis 5
1.1.9 Mortality 5
1.1.10 Pharmacotherapy 6
1.2 Biomarker discovery pipeline 6
1.3 Objectives 8
1.3.1 Specific aims of this study 8
1.4 Proteomics 10
1.4.1 Plasma Proteomics 11
1.4.2 Challenges of plasma proteomics 12
1.4.3 Depletion of abundant proteins from plasma 14
1.4.4 Gel-based and profiling strategies 14
1.4.5 Sample preparation strategies 14
1.4.6 One-dimensional gel electrophoresis 15
1.4.7 Two-dimensional gel electrophoresis 16
1.4.8 In-gel tryptic digestion 16
1.5 Mass spectrometric analysis 17
1.5.1 Principles of proteomic mass spectrometry 17
1.5.2 Ionization 18
1.5.3 Common mass analyzers 19
1.5.4 Ion mobility separation 21
1.5.5 Quadrupole tandem mass spectrometry 22
1.5.6 Data dependent acquisition 23
1.5.7 MSE tandem fragmentation 24
1.5.8 Liquid chromatographic separations in proteomics 25
1.5.9 Computational proteomics 27
1.5.10 Protein sequence databases 28
1.5.11 Peptide mass fingerprinting 28
1.5.12 MS/MS identification 28
1.5.13 De novo identification 29
1.5.14 MS-based protein quantification 30
1.5.15 Label-free relative quantification 30
1.5.16 From MS data to biological interpretation 32
1.6 Biomarker categories 33
1.6.1 Biomarker discovery to validation 34
1.6.2 Source of protein biomarkers 35
1.7 Mass spectrometry based proteomics in candidate biomarker discovery 35
1.7.1 Label free methods in MS quantification of clinical protein biomarkers 36
1.7.2 Label-free methods in absolute quantitation of clinical protein biomarkers 36
1.7.3 MS detection of PTM biomarkers 37
1.8 Proteomics and SLE 37
1.8.1 Literature review of identified biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics 38
Chapter II Differential expressions of proteins identified from SLE patients plasma using gel-based proteomics 41
2.1 Introduction 41
2.2 Materials and Methods 43
2.2.1 SLE Patients and Healthy Controls 43
2.2.2 Plasma samples: 44
2.2.3 Removal of high-abundance serum albumin from plasma samples 44
2.2.4 Protein quantification 45
2.2.5 SDS-PAGE 45
2.3 Two-dimensional SDS-PAGE 45
2.3.1 Acetone/TCA precipitation: 45
2.3.2 Isoelectric focusing (IEF) 46
2.3.3 Second dimension SDS-PAGE 46
2.3.4 Image analysis: 47
2.3.5 In-gel digestion 48
2.4 Protein identification by electrospray ionization liquid chromatography tandem mass spectrometry (LC-ESI-MS/MS) 48
2.4.1 Protein identification and quantification: 49
2.4.2 Bioinformatics Analysis 49
2.4.3 Statistical Analysis 50
2.5 Results 51
2.5.1 Proteins Identified using 2-DE analysis 51
2.5.2 Functional annotations of protein profile 55
2.5.3 KEGG Pathway Analysis: 56
2.6 Discussion 58
2.7 Conclusion: 60
2.8 Limitations of Gel-based proteomics: 61
Chapter III Gel-free based label-free quantitative proteomic analysis to identify the significantly expressed proteins from patients with SLE and their function prediction 64
3.1 Introduction 64
3.1 Methods: 65
3.1.1 Protein precipitation and in-solution digestion 65
3.1.2 Nano UPLC and mass spectrometry conditions 65
3.2 Label-free quantification 66
3.2.1 Result filtration 67
3.2.2 RT range filter 68
3.2.3 Quality filter 68
3.2.4 Average Area filter 68
3.2.5 Charge filter 68
3.2.6 Confidently detected sample filter 68
3.2.7 Peptide ID filter 68
3.2.8 Peptide feature significance filter 69
3.2.9 Peptide feature fold change 69
3.2.10 Volcano plot to choose proper cutoff 69
3.2.11 Protein unique peptide filter 69
3.2.12 Protein significance filter 69
3.2.13 Protein fold change filter 69
3.2.14 Use volcano plot to choose proper cutoff 69
3.2.15 Normalization 69
3.2.16 Significance 70
3.2.17 Average area 70
3.2.18 RT Alignment 70
3.2.19 Protein significance estimation 70
3.3 Quantification of altered proteins by emPAI 70
3.4 Protein identification 71
3.5 Bioinformatics Analysis 72
3.6 Statistical Analysis 72
3.7 Results 73
3.8 Protein profile of the differentially expressed proteins 75
3.9 Functional annotation of the identified proteins 80
3.10 Kyoto Encyclopedia of Genes and Genomes Analysis (KEGG) 81
3.11 Discussion 83
3.12 Conclusion: 88
3.13 Limitations of gel-free based proteomics: 88
Chapter IV Identification of post-translational modifications in plasma proteome of systemic lupus erythematosus patients without enrichment using mass spectrometry 90
4.1 Importance of PTM identification 90
4.2 Existing methods to identify modified peptides: 90
4.3 Methods: 92
4.4 Protein precipitation and in-solution digestion 92
4.5 Nano UPLC and mass spectrometry conditions 92
4.6 Data analysis: 93
4.6.1 Software operation and data processing: 93
4.6.2 Protein Identification 95
4.6.3 PEAKS Software analysis for PTM searching workflow 95
4.6.4 Peptide Pairs: 96
4.6.5 Estimation of False Discovery Rate: 97
4.6.6 Data base and parameters settings: 98
4.6.7 Manual Searching parameters: 98
4.6.8 PTM Profiling 98
4.7 Results: 99
4.7.1 PTMs identified in SLE patients by PEAKS 8.0 and MODa 99
4.8 Challenges of proteome wide analysis of post-translational modifications 108
4.9 Conclusion: 109
References: 110
Appendix 130
Supplementary Information 130
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指導教授 孫維欣 黃雪莉(Wei-Hsin Sun Shir-Ly Huang) 審核日期 2018-6-19
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