| 引用本文: | 杜志成,关鹏,黄德生.基于约束建模法的结核菌H37Rv代谢网络分析[J].生物信息学,2014,12(1):60-64. |
| DU Zhicheng,GUAN Peng,HUANG Desheng.Metabolic network analysis of Mycobacterium tuberculosis H37Rv with constraint-based models[J].Chinese Journal of Bioinformatics,2014,12(1):60-64. |
|
| 摘要: |
| 基于结核分枝杆菌国际标准强毒株H37Rv菌株的基因组尺度代谢网络模型iNJ661进行分析,以寻找代谢网络中培养基的关键成分和必要基因。该研究在Matlab平台上利用COBRA工具箱,采用基于约束的建模方法进行动态生长模拟、解空间抽样在酶活性水平上的具体化和基因删除模拟实验。结果发现培养基成分中铵盐、三价铁盐、磷酸盐、硫酸盐、甘油等可影响H37Rv的生长；培养基中去除磷酸盐后十种酶均在不同程度上受到抑制,其中丙糖磷酸异构酶、3-磷酸甘油醛脱氢酶、磷酸甘油酸变位酶、烯醇酶受限明显。通过基因删除得出188个必要基因以及非必要基因中的16个致死基因对。基于约束建模分析可初步了解结核杆菌H37Rv菌株代谢网络的性质,可为后续相关研究提供参考和借鉴。 |
| 关键词: 代谢网络 系统生物学 建模 结核杆菌 |
| DOI：10.3969/j.issn.1672-5565.2014-01.20140110 |
| 分类号:R378.91+1; TP319 |
| 基金项目:国家自然科学基金资助项目 (71073175)。 |
|
| Metabolic network analysis of Mycobacterium tuberculosis H37Rv with constraint-based models |
|
DU Zhicheng1, GUAN Peng1, HUANG Desheng2
|
|
(1.Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110001, China; 2.Department of Mathematics, College of Basic Medical Sciences, China Medical University, Shenyang 110001, China)
|
| Abstract: |
| To explore the key medium components and essential genes of tuberculosis metabolic network, we used the genome-scale metabolic network model iNJ661 to analyze Mycobacterium tuberculosis H37Rv. The study was conducted on the COBRA toolbox for Matlab. Simulation of dynamic growth, solution space sampling at the level the enzyme activity and gene deletion analysis were performed with the help of constraint-based modeling methods. Ammonium, ferric iron, phosphate, sulfate and glycerol of the medium components could affect the growth of H37Rv. After removing phosphate from the medium, ten enzymes were inhibited in varying degrees, among which triosephosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, phosphoglycerate mutase and enolase were constrained significantly. 188 essential genes and 16 pairs of synthetic lethal genes among nonessential genes were obtained by simulating deletion studies. Constraint-based modeling and analysis can now be used for the preliminary understanding of the nature of Mycobacterium tuberculosis H37Rv strain metabolic network and could provide the reference for future related research. |
| Key words: Metabolic network System biology Modeling Mycobacterium tuberculosis |
