發(fā)布時(shí)間：2018-05-04 08:09

  本文選題：人類代謝網(wǎng)絡(luò) + 亞細(xì)胞定位��； 參考：《天津大學(xué)》2010年博士論文

【摘要】：人體代謝系統(tǒng)的實(shí)驗(yàn)研究與人體內(nèi)不同亞細(xì)胞結(jié)構(gòu)和組織的功能是密切相關(guān)的,因而人體蛋白和代謝反應(yīng)的亞細(xì)胞定位及組織分布是人體生物學(xué)研究和藥物開發(fā)的重要研究對象。為了更好地理解人體代謝網(wǎng)絡(luò)的復(fù)雜性,融合亞細(xì)胞和組織信息的人類代謝網(wǎng)絡(luò)不可或缺。本文通過添加亞細(xì)胞定位信息、運(yùn)輸反應(yīng)和組織定位信息對已構(gòu)建的愛丁堡人類代謝網(wǎng)絡(luò)模型(EHMN進(jìn)行了擴(kuò)展,并且在亞細(xì)胞定位的基礎(chǔ)上對網(wǎng)絡(luò)中錯(cuò)誤的蛋白-反應(yīng)關(guān)系進(jìn)行了修正。首先蛋白亞細(xì)胞位置信息來自于不同的數(shù)據(jù)庫,而EHMN中所有反應(yīng)的位置信息則根據(jù)蛋白位置通過蛋白-反應(yīng)關(guān)系獲得,由此初步構(gòu)建了亞細(xì)胞分室網(wǎng)絡(luò);之后,本文通過對每個(gè)途徑中子網(wǎng)絡(luò)的圖論分析確定了網(wǎng)絡(luò)中的空白和孤立反應(yīng)并對其進(jìn)行了修正;此外,本文基于文獻(xiàn)及教科書中對途徑位置的描述進(jìn)一步校正了網(wǎng)絡(luò)中反應(yīng)的位置。最終初步分室網(wǎng)絡(luò)中上百個(gè)反應(yīng)的位置得到了修正,基于修正后反應(yīng)的亞細(xì)胞位置,錯(cuò)誤的蛋白-反應(yīng)關(guān)系也得到了更正。亞細(xì)胞分室完成后,本文基于Recon 1模型、數(shù)據(jù)庫以及代謝末端分析添加了1400多個(gè)運(yùn)輸反應(yīng),使網(wǎng)絡(luò)中的各個(gè)亞細(xì)胞位置連通起來。為了驗(yàn)證分室網(wǎng)絡(luò)的質(zhì)量,本文通過途徑分析檢驗(yàn)了EHMN對近70種重要代謝物的合成和降解能力以及代謝位置,結(jié)果表明EHMN中這些代謝物的代謝過程與文獻(xiàn)或教科書一致。在亞細(xì)胞分室網(wǎng)絡(luò)的基礎(chǔ)上,利用與亞細(xì)胞定位相同的方法,本文將組織信息也融合到EHMN中,從而構(gòu)建了更加完整的包含亞細(xì)胞和組織定位的人類代謝網(wǎng)絡(luò)。最后,本文從拓?fù)浣Y(jié)構(gòu)的角度對定位后的線粒體和腦兩個(gè)子網(wǎng)絡(luò)進(jìn)行了功能驗(yàn)證,表明從拓?fù)浣Y(jié)構(gòu)出發(fā)的網(wǎng)絡(luò)分析結(jié)果與子網(wǎng)絡(luò)的功能特點(diǎn)相符。本文首次將圖論分析的方法用于亞細(xì)胞及組織定位過程中并且利用途徑分析工具對網(wǎng)絡(luò)的可靠性進(jìn)行分析,并開發(fā)了新的將分類樹與模塊化指標(biāo)相結(jié)合的網(wǎng)絡(luò)解耦方法對網(wǎng)絡(luò)進(jìn)行解耦以進(jìn)行進(jìn)一步的功能分析。亞細(xì)胞及組織定位后的網(wǎng)絡(luò)可以從EHMN網(wǎng)站(www.ehmn.bioinformatics.ed.ac.uk)上下載并免費(fèi)提供給學(xué)術(shù)研究。
[Abstract]:The experimental study of human metabolic system is closely related to the function of different subcellular structures and tissues in the human body. Therefore, subcellular localization and tissue distribution of human protein and metabolic reactions are important research objects in human biology and drug development. In order to better understand the complexity of human metabolic networks, it is indispensable to integrate subcellular and tissue information. In this paper, EHMN, an Edinburgh human metabolic network model, was extended by adding subcellular localization information, transport response and tissue localization information. On the basis of subcellular localization, the wrong protein-response relationship in the network was corrected. First of all, the location information of protein subcells comes from different databases, and the location information of all reactions in EHMN is obtained by protein-response relationship, and the subcellular compartment network is constructed. In this paper, the blank and isolated reactions in the network are determined and corrected by the graph theory analysis of each path neutron network. This paper further corrects the response position in the network based on the description of the path location in the literature and textbooks. Finally, the positions of hundreds of reactions in the primary compartment network were corrected, and the wrong protein-response relationship was corrected based on the subcellular position of the modified reaction. After subcell compartmentalization was completed, more than 1400 transport reactions were added to the network based on Recon 1 model, database and metabolic terminal analysis, which connected each subcell position in the network. In order to verify the quality of compartments network, the synthesis and degradation ability and metabolic location of nearly 70 important metabolites of EHMN were tested by means of path analysis. The results showed that the metabolic process of these metabolites in EHMN was consistent with that in literature or textbooks. On the basis of subcellular compartments network and using the same method as subcellular localization, this paper fuses tissue information into EHMN and constructs a more complete human metabolic network containing subcellular and tissue localization. Finally, from the point of view of topological structure, the functional verification of the mtDNA and brain subnetworks after localization is carried out, which shows that the network analysis results based on the topology structure are consistent with the functional characteristics of the subnetworks. In this paper, the method of graph theory analysis is used in subcellular and tissue localization for the first time, and the reliability of network is analyzed by means of path analysis tool. A new decoupling method combining classification tree and modularization index is developed to decouple the network for further functional analysis. The subcellular and tissue localization network can be downloaded from the EHMN website at www.ehmn.bioinformatics.ed.ac.ukand is available for free for academic research.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2010
【分類號】：R341

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本文編號：1842265