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研究生: 吳冠履
Wu, Kuan-Lu
論文名稱: 利用SWATH質譜技術尋找小鼠肝臟中受聚苯乙烯塑膠微粒誘導之差異性代謝體
Differential Metabolomics for Mouse Liver Induced by Microplastics Utilizing SWATH-based Mass Spectrometry
指導教授: 陳頌方
Chen, Sung-Fang
口試委員: 梁恭豪
Liang, Kung-Hao
陳百昇
Chen, Pai-Sheng
蕭伊倫
Hsiao, I-Lun
陳頌方
Chen, Sung-Fang
口試日期: 2023/07/17
學位類別: 碩士
Master
系所名稱: 化學系
Department of Chemistry
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 151
中文關鍵詞: 代謝體學塑膠微粒液相層析-質譜
英文關鍵詞: Metabolomics, Microplastics, LC-MS
研究方法: 實驗設計法主題分析
DOI URL: http://doi.org/10.6345/NTNU202301128
論文種類: 學術論文
相關次數: 點閱:80下載:6
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  • 近年來,塑膠微粒污染引起了國際的關注。 有報導稱塑膠微粒可能對人類產生肝毒性。代謝體學是評估此類污染物威脅的有力策略,可以更直接地反映其表型。 在本研究中,我們應用液相層析-串聯質譜 (LC-MS/MS) 和SWATH 數據獲取模式評估暴露於聚苯乙烯塑膠微粒的小鼠肝臟差異性代謝體學。在差異性代謝體學分析之前, 8 種不同 LC 條件的覆蓋範圍透過使用混合樣品,並使用代謝物標準混合物評估兩個親水相互作用液相層析 (HILIC) 柱的定量性能。結果表明,Amide管柱在ESI(+)和ESI(-)模式下最適合小分子分析,而流動相中含有0.1% FA的PFP柱最適合ESI(-)模式的磷脂分析,總共能夠鑑定923種代謝物。 LC-SWATH-MS 發現了 71 種差異代謝物,並且發現嘌呤和嘧啶代謝、氨基酸代謝和磷脂代謝受到聚苯乙烯塑膠微粒的干擾。這項研究提供了一個通用的代謝體學圖譜,可以揭示聚苯乙烯塑膠微粒暴露對小鼠肝臟的影響,這是血清化學分析和組織學分析無法給出的。

    Microplastic (MP) pollution has gained international attention in recent years. It has also been reported that MPs could induce hepatotoxic in humans. Metabolomics is a powerful strategy for evaluating the threat of such pollutants, which can reflect the phenotype in a more direct way. In this study, we applied liquid chromatography-tandem mass spectrometry (LC-MS/MS) with sequential window acquisition of all theoretical mass spectra (SWATH) data acquisition mode to assess the differential metabolomics in mouse liver exposed to polystyrene MPs. Before differential metabolomics analysis, the coverage of 8 different chromatographic conditions was evaluated using the pooled sample, and the quantitative performance of the two hydrophilic interaction liquid chromatography (HILIC) columns was evaluated using metabolite standard mixtures. The results showed that the amide column was the best for small molecule analysis in the ESI(+) and the ESI(-) mode and the PFP column with 0.1% FA in the mobile phase was the best for phospholipids analysis in the ESI(-) mode. By combining the selected conditions, our method can identify 923 metabolites in summary. There were 70 differential metabolites discovered by the LC-SWATH-MS and the purine and pyrimidine metabolism, amino acid metabolism, and phospholipid metabolism were found to be disturbed by the PS-MPs. This study provides a universal metabolomics profile that can reveal the effects of PS-MPs exposure on the mouse liver that cannot be given by serum chemical analysis and histological analysis.

    Acknowledgement i 中文摘要 ii Abstract iii Table of Content iv List of Figures vi List of Tables ix Abbreviations 1 Chapter 1. Introductions 4 1.1. Microplastic: An Environmental Threat 4 1.2. Metabolomics: Link Between Genotype to Phenotype 7 1.2.1. Targeted Metabolomics 9 1.2.2. Untargeted metabolomics 11 1.3. Data Acquisition Mode of Untargeted Metabolomics 12 1.3.1. DDA: The Most Commonly Used Data Acquisition Mode 13 1.3.2. DIA: The Potential Data Acquisition Mode 14 1.4. The Importance of LC Condition 17 1.5. Motivation 18 Chapter 2. Materials and Methods 19 2.1. Experiment Procedure 19 2.2. Materials 20 2.2.1. Chemicals and Reagents 20 2.2.2. Instruments 22 2.3. Animal Treatment and Sample Preparation 23 2.3.1. Animal Treatment 23 2.3.2. Metabolite Extraction 24 2.4. Chromatographic Conditions Optimization 25 2.5. Evaluating the Quantitation Reliability of SWATH 28 2.5.1. Standard Mixture Preparation 28 2.5.2. LC-SWATH-MS Analysis 28 2.6. Differential Metabolomics Analysis Using SWATH Techniques 29 2.7. Data Processing 30 2.7.1. Data Processing of DDA 30 2.7.2. Data Processing of SWATH 30 2.7.3. Statistical Analysis 32 Chapter 3. Results and Discussion 33 3.1. Evaluating the Toxicity of PS-MPs to Male BALB/c Mice 33 3.1.1. Body Weight Changes of the Male BALB/c Mice 33 3.1.2. Serum Chemical Analyses 35 3.1.3. Histological Analysis 37 3.2. Chromatographic Conditions Optimization 38 3.2.1. ESI(+) mode 40 3.2.2. ESI(-) mode 49 3.2.3. The Quantitative Performance of LC-SWATH-MS 58 3.3. Differential Metabolomics Analysis Using SWATH Techniques 68 3.3.1. Comparison of DDA and SWATH 71 3.3.2. Differential Metabolites in Amide ESI(+) 72 3.3.3. Differential Metabolite in Amide ESI(-) 77 3.3.4. Differential Metabolite in PFP (0.1% FA) ESI(-) 82 3.3.5. Summary 87 3.4. Pathway Analysis and Literature Comparison 93 3.5. Integration of Metabolomics and Proteomics 100 Chapter 4. Conclusions and Future Innovations 102 Chapter 5. References 105 Supporting Information 115

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