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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91149完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 徐丞志 | zh_TW |
| dc.contributor.advisor | Cheng-Chih Hsu | en |
| dc.contributor.author | 紀舒媚 | zh_TW |
| dc.contributor.author | Shu-Mei Chi | en |
| dc.date.accessioned | 2023-11-20T16:09:05Z | - |
| dc.date.available | 2023-11-21 | - |
| dc.date.copyright | 2023-11-20 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-09-05 | - |
| dc.identifier.citation | 1. El Nahas, A. M.; Bello, A. K., Chronic kidney disease: the global challenge. The lancet 2005, 365 (9456), 331-340.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91149 | - |
| dc.description.abstract | 慢性腎臟病是全世界盛行率高的疾病之一，其病因在於腎臟過濾功能下降。過去的研究結果表明，慢性腎臟病患者體內的腸道菌群為失衡狀態。然而，目前對於腸道菌在慢性腎臟病患者體內代謝活動的全貌仍知之甚少。因此，本研究旨在探討慢性腎臟病患者體內與腸道菌相關的代謝變化。我們採用了多體學分析，包括利用液相層析串聯質譜儀進行非標靶代謝體分析，以及利用散彈槍總體基因體定序技術進行研究。
在代謝體分析中，我們首先透過Kyoto Encyclopedia of Genes (KEGG)資料庫討論代謝途徑，並發現色胺酸路徑失調。為了探討未知代謝物，我們使用分子網路技術，通過計算離子碎片的相似度，將具有相似碎片的物質歸為一組。在分子網路研究中，我們共鑑定出九個代謝物群，其中包括呈現下降趨勢的膽酸群。在膽酸群中，其中一個膽酸被我們鑑定為麩胺膽酸。除了分子網路分析外，我們也透過分子差異分析討論分子之間潛在的酵素反應。在總體基因體分析中，我們探討了菌株分布差異以及與代謝相關的基因差異。我們發現有五個參與次級膽酸代謝的基因在疾病組中為失調情況。最後，通過相關性分析，我們探討了代謝體和總體基因體數據之間的關聯。其中麩胺膽酸與Clostridium sp. OF09-36為顯著正相關，此結果暗示此腸道菌可能參與麩胺膽酸的生成。 本研究的目的在於討論慢性腎臟病中具有變化的糞便代謝物和相關腸道菌。我們的研究結果不僅有助於更深入了解慢性腎臟病和菌群失衡，更重要的是揭示了許多以往未知的現象和關聯。這些發現為未來在此領域的研究和臨床應用提供了潛在方向。 | zh_TW |
| dc.description.abstract | Chronic kidney disease (CKD) is a significant global health concern caused by loss of kidney function. Recent studies have explored the relationship between CKD and dysbiosis, an imbalance in gut bacteria. Integrative analyses have uncovered relationships between specific fecal metabolites, bacteria, and CKD patients. However, many altered fecal metabolites and their corresponding gut microbiota in CKD patients remain poorly understood. To gain further insights into gut microbiota-associated metabolism in CKD patients, we conducted untargeted metabolomic analysis by LC-MS/MS and shotgun metagenomic study.
In our study, we pointed out the altered tryptophan metabolism through the use of KEGG database. To explore unknown compounds, we employed feature-based molecular networking, a powerful tool that clusters molecules based on similar MS/MS spectra. In total, nine clusters were annotated, including the cluster of bile acid, which exhibited down-regulation in the CKD group. Additionally, mass shift analysis was further performed to investigate the mass differences between related molecules, aiding the exploration of potential enzymatic reactions. In addition, shotgun metagenomic sequencing was conducted to analyze the population of gut bacteria and genes about enzymes in secondary bile acid metabolism between the control and the CKD groups. In our results, five genes involved in secondary bile acid metabolism were dysregulated. Finally, through integrated analysis, we established connections between specific metabolites and gut microbiota. Notably, glutamatocholic acid, one of the annotated bile acids, showed a positive correlation with Clostridium sp. OF09-36, suggesting a potential role of bacteria in the biosynthesis. Our research provides novel findings into the altered fecal metabolites and their related gut microbiota in CKD patients. The findings contribute to a deeper understanding of CKD and dysbiosis, potentially paving the way for future research and clinical applications in this field. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-11-20T16:09:04Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-11-20T16:09:05Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 謝誌 i
摘要 iii Abstract iv 目錄 vi 圖目錄 ix 表目錄 xii Chapter 1 Introduction 1 1-1 Chronic kidney disease 1 1-2 Gut bacteria 3 1-3 Metabolomics 8 1-3-1 Metabolomic analysis 8 1-3-2 Molecular networking 9 1-3-3 Mass shift analysis 11 1-4 Aim 14 Chapter 2 Materials and methods 16 2-1 Study participants 16 2-2 Bacterial DNA extraction and shotgun metagenomic sequencing 16 2-3 Read quality control 17 2-4 Metagenome assembly and annotation 17 2-5 Chemicals 18 2-6 Samples extraction and LC-MS/MS analysis 18 2-7 Feature-Based Molecular Networking (FBMN) 19 2-8 Statistical analysis 21 2-9 Mass shift 21 Chapter 3 Results and discussion 22 3-1 KEGG pathway analysis 22 3-2 Featured-based molecular networking (FBMN) analysis 28 3-2-1 Characterization of fecal metabolites in molecular networking 28 3-2-2 Acylcarnitines 29 3-2-3 Glycated amino acids 30 3-2-4 Tryptophan-related compounds 31 3-2-5 Dipeptides 32 3-2-6 Lysophosphatidylserines (LPSs) 33 3-2-7 Lysophosphatidylethanolamines (LPEs) 33 3-2-8 Monoacylglycerols (MGs) 34 3-2-9 Lysophosphatidylcholines (LPCs) 34 3-2-10 Bile acids 35 3-3 Metagenomic analysis 56 3-3-1 Taxonomic analysis 56 3-3-2 Functional analysis of secondary bile acid metabolism 58 3-4 Integrated analysis 64 3-5 Mass shift chemical profiling between the control and the CKD groups 67 3-5-1 Meta-mass shift analysis revealed distinct diversity 67 3-5-2 Mass shifts indicated potential biotransformation 68 Chapter 4 Conclusion 84 References 86 Appendix 100 Appendix 1. Abbreviation 100 Appendix 2. KEGG Pathway 103 Appendix 3. Significantly different nodes in the nine clusters 108 Appendix 4. Significantly different species in the volcano plot 114 Appendix 5. Spearman correlation between gut microbiota and metabolites which have altered levels in the CKD group 120 | - |
| dc.language.iso | en | - |
| dc.title | 利用液相層析串聯質譜儀和總體基因體分析技術探索慢性腎臟病病患中與腸道菌相關之代謝 | zh_TW |
| dc.title | Exploring Gut Microbiota-Associated Metabolism in Chronic Kidney Disease Using Liquid Chromatography Tandem Mass Spectrometry and Metagenomic Sequencing | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 吳秉勳;蔡伊琳;廖志中 | zh_TW |
| dc.contributor.oralexamcommittee | Ping-Hsun Wu;I-Lin Tsai;Chih-Chuang Liaw | en |
| dc.subject.keyword | 慢性腎臟病,非標靶代謝體分析,腸道菌,分子網路,總體基因體分析, | zh_TW |
| dc.subject.keyword | chronic kidney disease,untargeted metabolomic analysis,gut bacteria,molecular networking,shotgun metagenomic sequencing, | en |
| dc.relation.page | 122 | - |
| dc.identifier.doi | 10.6342/NTU202304209 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2023-09-06 | - |
| dc.contributor.author-college | 理學院 | - |
| dc.contributor.author-dept | 化學系 | - |
| dc.date.embargo-lift | 2028-09-05 | - |
| 顯示於系所單位： | 化學系 | |
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| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-112-1.pdf 此日期後於網路公開 2028-09-05 | 12.23 MB | Adobe PDF |
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