| 题名 | 代谢网络和比较转录组学在两种人类复杂疾病研究中的应用 |
| 作者 | 张爱娣 |
| 学位类别 | 博士 |
| 答辩日期 | 2014-04 |
| 授予单位 | 中国科学院研究生院 |
| 授予地点 | 北京 |
| 导师 | 黄京飞 |
| 关键词 | 肾脏 代谢网络 流平衡分析 药物靶标 糖尿肾病 生物标记物 心脏衰竭 基因芯片 |
| 其他题名 | The Applications of Metabolic Networks and Comparative Transcriptomics in Human Complex Diseases |
| 学位专业 | 遗传学 |
| 中文摘要 | 代谢的状态最能够反映机体的真实状态，代谢网络模型作为工具，无论在生物体生命活动的理论研究上，还是在指导代谢工程进行工程菌改造上，都具有非常重要的理论和实践意义。随着高通量组学数据的激增，构建组织或者细胞特异的代谢网络能更有利于理解细胞或组织真实的生理与病理状况。本研究以人基因组代谢网络为基础，整合了肾脏组织转录组和蛋白质组数据构建了人类肾脏特异性代谢网络，拓扑结构分析发现大部分酶倾向于参与少数的反应，而小部分的酶连接数高而参与大量的反应。网络模拟结果显示与组织特异基因相比，管家基因可能执行着更重要的生物学功能。基于约束的分析，我们成功地预测了267个对应不同肾脏疾病类型的肾脏相关疾病基因的生物标志物。通过对不同组织的代谢网络比较，发现了不同组织具有不同的代谢行为，比如肾脏的特异酶基因涉及到了胺类代谢以及一些激素代谢的过程。最后我们以糖尿性肾病为例展示了代谢网络在解释疾病机制的能力，通过对糖尿肾病疾病进程的差异表达基因进行代谢模拟发现，这些差异表达基因对网络的适应性影响显著，更有可能在代谢方面对疾病产生重大影响。 人类复杂疾病是遗传因素与环境相互作用的结果，其发病机制复杂。在研究复杂疾病过程中，疾病动物模型发挥着重要的作用，并已经广泛应用于人类疾病或生物学基础研究中，但是随着物种的进化，人类与实验动物之间存在着广泛的功能分化，从而导致实验结果与预期相左。我们以心脏衰竭为例，收集了多种动物模型与人类的表达数据，首先进行了一对一的直系同源基因的比较，发现大部分基因受到强烈的负选择，物种之间表达的相似性与物种树一致。然后我们对不同动物模型进行了心脏衰竭差异表达基因的鉴定，找到了一些物种之间比较保守的基因标签。尽管如此，心脏衰竭在不同的动物模型与人之间涉及的通路差别很大，预示着疾病通路在动物模型与人之间发生了分化。即使同一物种，构建疾病模型方法不同导致的疾病表达改变也不相同。研究结果为选择合适的心衰疾病动物模型提供计算和理论支持。 |
| 英文摘要 | The health and disease states of the human can be described more meaningfully by the metabolic state of human. As the most-used network tool, metabolic network plays a key role in disease research and genetic engineering. With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases. Human complex disease is very tough due to its various disease mechanisms, and involvs extensive interaction between inheridity and environment. Animal models have played a key role in the study of cardiovascular disease and provided important insights into disease pathogenesis and drug development. However, the experiment outcome always belows or contradict our expectations, which may result from the function divergence between human and animal models. To address this issue, we focus on the comparative transcriptomics of heart failure. We compared the gene expression of orthologous genes between human and four animal models(mouse,rat, dog,pig). The results show that the similarity of global expression profiles between animal models and human orthologous genes are consistent with species evolutionary trees. Additionaly, we identified a large number of different expression genes between heart failure and nomal counterpart, and found that they have rare overlap among different animal models except human and mouse, whose different expression genes both participated in extracellular matrix disassemblyand cartilage condensation pathways. GO annotation results indicate that different expression genes of different animal models participated in different pathways. Finally we compared two gene expression data of mice, heart failure of which were indued by different experimental treatment methods, the results indicate that their heart failure still have large difference concerning the expression level and pathways. Our work may provide valuable information for the development of animal models of human complex diseases and personal medicine. |
| 语种 | 中文 |
| 公开日期 | 2014-06-04 |
| 内容类型 | 学位论文 |
| 源URL | [http://159.226.149.42:8088/handle/152453/7878]  |
| 专题 | 昆明动物研究所_结构生物信息学 |
| 推荐引用方式 GB/T 7714 | 张爱娣. 代谢网络和比较转录组学在两种人类复杂疾病研究中的应用[D]. 北京. 中国科学院研究生院. 2014. |
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