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利用基因組生物信息學(xué)預(yù)測和蛋白組學(xué)對牛支原體分泌蛋白組的研究及分泌性抗原MbovP0581的驗(yàn)證

發(fā)布時(shí)間:2024-05-20 01:52
  牛支原體是牛重要的病原體之一,可引起牛的多種感染,包括肺炎、關(guān)節(jié)炎、中耳炎、乳腺炎、角膜結(jié)膜炎、生殖器疾病和各種臨床相關(guān)疾病,造成了重大的經(jīng)濟(jì)損失。其發(fā)病機(jī)制認(rèn)識(shí)不足對其早期診斷和有效疫苗的研制提出了挑戰(zhàn)。由于分泌蛋白在細(xì)菌發(fā)病機(jī)制中具有重要的作用,因此本研究旨在系統(tǒng)地揭示牛支原體分泌組及其在致病力中的潛在作用。我們結(jié)合基因組預(yù)測和蛋白質(zhì)組學(xué)驗(yàn)證開展研究。利用生物信息學(xué)工具,共預(yù)測出246個(gè)牛支原體分泌蛋白。其中14個(gè)蛋白屬于經(jīng)典通路,154個(gè)蛋白屬于非經(jīng)典通路,78個(gè)蛋白屬于經(jīng)典和非經(jīng)典通路。接著采用雙向凝膠電泳(2-DE)和基質(zhì)輔助激光解吸電離飛行時(shí)間質(zhì)譜(MALDI-TOF-MS)技術(shù),共檢測到169個(gè)蛋白。其中60個(gè)蛋白屬于先前被預(yù)測的分泌蛋白,包括3個(gè)經(jīng)典通路蛋白,43個(gè)非經(jīng)典通路蛋白,14個(gè)經(jīng)典和非經(jīng)典通路蛋白。亞細(xì)胞定位預(yù)測顯示,8.3%(5/60)位于細(xì)胞膜,5.0%(3/60)位于胞外區(qū),31.6%(19/60)位于胞漿,55.0%(33/60)位置未知。對這60種分泌蛋白進(jìn)行KEGG富集了GO和蛋白質(zhì)相互作用分析。利用VFDB數(shù)據(jù)庫進(jìn)行毒力相關(guān)因子分析,其中8個(gè)蛋白...

【文章頁數(shù)】:129 頁

【學(xué)位級別】:博士

【文章目錄】:
摘要
Abstract
Abbreviations
1.Introduction
    1.1 Background of this research
        1.1.1 Bovine Mycoplasmosis in cattle population of China
        1.1.2 Prevention and control strategies of M.bovis
        1.1.3 Role of genomics and proteomics in the study of bacterial cell secretome
        1.1.4 Statement of problems
    1.2 Review of Literature
        1.2.1 Biological characteristics of Mycoplasmas
        1.2.2 Pathogenesis of Mycoplasma bovis
        1.2.3 Diagnosis
        1.2.4 Vaccination
        1.2.5 Bacterial cell secretome
        1.2.6 Secretome of Mycoplasmas
        1.2.7 Methodology to study secretome of Mycoplasmas
2.Aims and objectives
3.Identification of antigenic secreted proteins of Mycoplasma bovis with genome and proteome analyses
    3.1 Introduction
    3.2 Materials and methods
        3.2.1 Ethical statement
        3.2.2 Strain and culture conditions
        3.2.3 Extraction of secretome
        3.2.4 Protocol for using2-D clean-up kit
        3.2.5 2-Dimensional Gel Electrophoresis
        3.2.6 Matrix-assisted laser desorption/ionization time of flight(MALDI-TOF)mass spectrometry(MS)
        3.2.7 Bioinformatics analysis
        3.2.8 Immunoinformatics analysis of secreted proteins
        3.2.9 Cloning and expression of selected secreted proteins
        3.2.10 Transformation of ligated sample into BL21
        3.2.11 Checking protein expression
        3.2.12 Checking solubility of proteins
        3.2.13 Purification of r Mbov581 from supernatant
        3.2.14 Purification of r Mbov674 from pellet
        3.2.15 Extraction of whole cell proteins
        3.2.16 Production of mouse polyclonal antibodies against the selected secreted proteins
        3.2.17 Preparation of cattle antisera to M.bovis
        3.2.18 Western blot assays for verification of secreted nature and antigenicity of selected proteins
        3.2.19 Structure prediction and identification of conserved regions
        3.2.20 Adhesion assay
        3.2.21 Quantitative assay for adhesion
        3.2.22 Statistical analysis
    3.3 Results
        3.3.1 Secretome analysis using M.bovis whole genome
        3.3.2 Identification of secretome using proteomics approach
        3.3.3 Proteins involved in various virulence-associated pathways
        3.3.4 Gene Ontology(GO)Analysis
        3.3.5 Protein-Protein interaction
        3.3.6 Virulence-related factors of proteins identified by VFDB
        3.3.7 Conserved domain Analysis
        3.3.8 Identification of conformational B cell epitopes
        3.3.9 Prediction of T cell epitopes
        3.3.10 Cloning,expression and purification of selected proteins
        3.3.11 Validation of secreted nature and antigenicity
        3.3.12 Structural and functional prediction showed conserved regions in Mbov P0581
        3.3.13 Adhesion of Mbov P581 to EBL cells
    3.4 Discussion
        3.4.1 The number of secreted proteins of M.bovis
        3.4.2 Identification of critical secreted proteins for M.bovis
        3.4.3 Detection of Mbov P0581 as an adhesin to EBL cells
4.Conclusion
5.Statement of novelty of this study
References
Supplementary data
List of publications
Acknowledgement



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