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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳示國(Shih-Kuo Chen) | |
| dc.contributor.author | Feng Liang | en |
| dc.contributor.author | 梁風 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:04:02Z | - |
| dc.date.available | 2021-11-08 | |
| dc.date.available | 2022-11-23T09:04:02Z | - |
| dc.date.copyright | 2021-11-08 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-09-17 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79572 | - |
| dc.description.abstract | 帕金森氏症是最普遍的退化性神經疾病之一,其原因是α-突觸核蛋白不正常地堆積在神經細胞中(路易氏體)。帕金森氏症致病因素包括環境、基因背景甚至腸道菌的交互影響。研究顯示帕金森氏症患者的腸道菌會加重小鼠的運動功能障礙。然而在帕金森氏症中腸道菌是什麼時候以及如何發生變化是仍然未知。結合16S基因體定序分析以及運動行為測試,我們發現在過量表現變異人類α-突觸核蛋白帕金森氏症模型小鼠的腸道菌在成年時就已經發生腸道微生態失調,遠早於小鼠發病的年紀。另外,腸道菌的日夜週期性在帕金森氏症模型小鼠中也會漸漸地消失。由於紊亂的光週期如夜晚照光可以消弭腸道菌的週期性,在此研究中我們也證實當帕金森氏症模型小鼠暴露於夜晚低光的環境中運動行為會提早退化。這些研究顯示了生理時鐘-腸軸在帕金森氏症發病的影響,且可能提出一個影響病程的重要環境因素。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:04:02Z (GMT). No. of bitstreams: 1 U0001-1609202116554500.pdf: 14225393 bytes, checksum: ac78c1a214572ad43994bd9ce2fc4329 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "謝 誌 ii 摘 要 iii Abstract iv Contents v Chapter I Introduction 1 1.1 Parkinson’s disease 1 1.1.1 Overview of Parkinson’s disease 1 1.1.2 Braak hypothesis 2 1.1.2 Dysbiosis in Parkinson’s disease 3 1.2 Circadian rhythm 4 1.2.1 Overview of the circadian rhythm 4 1.2.2 Intracellular clock mechanism in the mouse 5 1.2.3 Peripheral clock 7 1.3 Gut microbiota 8 1.3.1 General description of gut microbiota 8 1.3.2 Diurnal oscillatory rhythms of gut microbiota 9 1.3.3 Gut-brain axis 11 Statement of Purpose 13 Chapter II Materials and Methods 14 2.1 Animals 14 2.2 Experimental design 14 2.2.1 The change of gut microbiota before the onset of PD 14 2.2.2 The source of daily microbial oscillation 15 2.2.3 dLAN affects the gut microbiota and the progression of PD 15 2.3 Illumina MiSeq sequencing 16 2.3.1 Total fecal DNA extraction 16 2.3.2 16S metagenomic library preparation 17 2.3.3 Pooling and quality control 20 2.3.4 Next Generation Sequencing (NGS) 20 2.4 Microbiota sequence analysis 20 2.4.1 Sequence assembling and identification 20 2.4.2 Composition analysis 22 2.4.3 Diversity analysis 23 2.4.4 Microbe abundance analysis 23 2.4.5 Circadian analysis of microbial oscillations 24 2.5 Virus injection 24 2.6 Beam balance test 24 2.7 Rotarod test 25 2.8 Immunocytochemistry 26 2.9 Statistical analysis 27 Chapter III Results 28 3.1 PD mice exhibit behavioral motor deficit and reduced TH neuron number around 10.5 months old 28 3.2 Dysbiosis can be observed in young adult PD mice 29 3.3 The daily oscillation of gut microbes is dampened in PD mice 31 3.4 dLAN alters the daily oscillation of gut microbes 32 3.5 Rhythms of gut microbiota oscillation remains robust in Villin-cre cKO mice 34 3.6 Oscillatory rhythm of gut microbes is regulated by light and circadian clock 36 3.7 dLAN accelerates PD progression and advances PD symptoms in brain but not in gut 40 Chapter IV Discussion 43 4.1 Early dysbiosis and dampened gut microbe daily oscillation in animal models of Parkinson's disease 43 4.2 The gut microbiota rhythmicity is controlled by light and the circadian clock 48 4.3 The influence of dLAN on Parkinson’s disease 49 Significance of the Work 51 References 53 Figure 1. Experimental Design of PD gut microbiota longitudinal analysis. 70 Figure 2. Representative mid-brain sections of 2 months old and 10.5 months old SNCA p.A53T and control mice. 71 Figure 3. Results of Beam Balance Test and Rotarod Test of SNCA p.A53T and control mice. 73 Figure 4. Phylum level relative abundance of the gut microbiota and the F/B ratio of SNCA p.A53T and control mice. 75 Figure 5. Composition of the gut microbiota of 2 months old SNCA p.A53T and control mice. 76 Figure 6. Composition of the gut microbiota of 4 months old SNCA p.A53T and control mice. 78 Figure 7. Composition of the gut microbiota of 6.5 months old SNCA p.A53T and control mice. 80 Figure 8. Composition of the gut microbiota of 8.5 months old SNCA p.A53T and control mice. 82 Figure 9. Composition of the gut microbiota of 10.5 months old SNCA p.A53T and control mice. 84 Figure 10. All-age-point pooling PCoA plots of SNCA p.A53T and control mice. 86 Figure 11. Diversity of the gut microbiota of SNCA p.A53T and control mice. 87 Figure 12. Linear discriminant analysis Effect Size (LEfSe) of 2 months old SNCA p.A53T and control mice. 88 Figure 13. Linear discriminant analysis Effect Size (LEfSe) of 4 months old SNCA p.A53T and control mice. 91 Figure 14. Linear discriminant analysis Effect Size (LEfSe) of 6.5 months old SNCA p.A53T and control mice. 93 Figure 15. Linear discriminant analysis Effect Size (LEfSe) of 8.5 months old SNCA p.A53T and control mice. 95 Figure 16. Linear discriminant analysis Effect Size (LEfSe) of 10.5 months old SNCA p.A53T and control mice. 97 Figure 17. Gut microbes’ diurnal oscillatory rhythm of all-age-point SNCA p.A53T and control mice. 98 Figure 18. Experimental Design of WT mice treated with normal light-dark cycle (LD) or dim light at night (dLAN). 100 Figure 19. Composition of the gut microbiota of WT mice treated with normal light-dark cycle (LD) or dim light at night (dLAN). 101 Figure 20. Gut microbiota phylum level relative abundance of mice treated with normal light-dark cycle (LD) or dim light at night (dLAN). 103 Figure 21. Gut microbiota diversity of LD and dLAN mice. 104 Figure 22. Abundance analysis of the gut microbiota of LD and dLAN mice. 106 Figure 23. Gut microbes’ diurnal oscillatory rhythm of LD and dLAN mice. 107 Figure 24. Metabolic status of mice housed under LD and dLAN condition. 108 Figure 25. Representative figures of actogram and the power of the chi-square periodogram of Villin-cre conditional knockout and control mice. 109 Figure 26. Composition of the gut microbiota of Villin-cre conditional knockout and control mice. 110 Figure 27. Gut microbiota phylum level relative abundance of Villin-cre conditional knockout and control mice. 112 Figure 28. Gut microbiota diversity of Villin-cre conditional knockout and control mice. 113 Figure 29. Linear discriminant analysis Effect Size (LEfSe) of Villin-cre conditional knockout and control mice. 114 Figure 30. Gut microbes’ diurnal oscillatory rhythm of Villin-cre conditional knockout and control mice. 116 Figure 31. Metabolic status of Villin-cre conditional knockout and control mice. 118 Figure 32. Representative figures of actogram and the power of the chi-square periodogram of Nestin-cre conditional knockout and control mice. 119 Figure 33. Composition of the gut microbiota of Nestin-cre conditional knockout and control mice. 121 Figure 34. Gut microbiota phylum level relative abundance of Nestin-cre conditional knockout and control mice. 123 Figure 35. Gut microbiota diversity of Nestin-cre conditional knockout and control mice. 124 Figure 36. Linear discriminant analysis Effect Size (LEfSe) of Nestin-cre conditional knockout and control mice. 126 Figure 37. Gut microbes’ diurnal oscillatory rhythm of Nestin-cre conditional knockout and control mice. 127 Figure 38. Experimental design of SCN lesion knockout mice. 129 Figure 39. Representative figures of actogram and the power of the chi-square periodogram of SCN lesion and control mice in DD and LD condition. 131 Figure 40. Coronal mouse mid-brain sections of SCN lesion and control mice. 132 Figure 41. Composition of the gut microbiota of SCN lesion and control mice under LD condition. 133 Figure 42. Composition of the gut microbiota of SCN lesion and control mice under DD condition. 135 Figure 43. Gut microbiota phylum level relative abundance of SCN lesion and control mice. 137 Figure 44. Gut microbiota diversity of SCN lesion and control mice. 138 Figure 45. Linear discriminant analysis Effect Size (LEfSe) of SCN lesion and control mice under LD condition. 140 Figure 46. Linear discriminant analysis Effect Size (LEfSe) of SCN lesion and control mice under DD condition. 142 Figure 47. Gut microbes’ diurnal oscillatory rhythm of SCN lesion and control mice. 143 Figure 48. Vann diagram of oscillating OTUs in control mice under LD or DD condition. 145 Figure 49. Quantification of expression of p-α-synuclein, Occludin, p-LRRK2, LRRK2, NOD2 and p-NF-κB in the colon of SNCA p.A53T and control mice under LD and dLAN conditions. 146 Figure 50. Weighted PCoA plots of SNCA p.A53T and control mice under LD and dLAN conditions from 6.5 months to 10.5 months old. 148 Figure 51. Representative mid-brain sections of 10.5 months old SNCA p.A53T and control mice under LD and dLAN conditions. 150 Figure 52. Results of Beam Balance Test and Rotarod Test of SNCA p.A53T and control mice under dLAN condition from 6.5 months old to 10.5 months old. 152 Table 1. Primers used in metagenomics sample preparation 153 Table 2. Primers of Nextera® Index 154 Appendix I 16S Metagenomic Analysis Pipeline 155 " | |
| dc.language.iso | en | |
| dc.title | 帕金森氏症小鼠發病前腸道菌的長期研究 | zh_TW |
| dc.title | The longitudinal analysis of gut microbiota prior to the onset of motor dysfunctions in Parkinson's disease mouse model | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林靜嫻(Hsin-Tsai Liu),江皓森(Chih-Yang Tseng),朱家瑩 | |
| dc.subject.keyword | 腸道菌,生理時鐘,帕金森氏症, | zh_TW |
| dc.subject.keyword | gut microbiota,circadian rhythm,Parkinson’s disease, | en |
| dc.relation.page | 159 | |
| dc.identifier.doi | 10.6342/NTU202103215 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-09-17 | |
| dc.contributor.author-college | 生命科學院 | zh_TW |
| dc.contributor.author-dept | 生命科學系 | zh_TW |
| 顯示於系所單位: | 生命科學系 | |
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