Kim Taehyong, Dreher Kate, Nilo-Poyanco Ricardo, Lee Insuk, Fiehn Oliver, Lange Bernd Markus, Nikolau Basil J, Sumner Lloyd, Welti Ruth, Wurtele Eve S, Rhee Seung Y
Department of Plant Biology, Carnegie Institution for Science, Stanford, California 94305 (T.K., K.D., R.N.-P., S.Y.R.);Department of Biotechnology, Yonsei University, Seoul 120-749, South Korea (I.L.); Genome Center, University of California, Davis, California 95616 (O.F.); M. J. Murdock Metabolomics Laboratory, Institute of Biological Chemistry, Washington State University, Pullman, Washington 99164 (B.M.L.); Center for Metabolic Biology, Department of Biochemistry, Biophysics, and Molecular Biology (B.J.N.), and Department of Genetics, Development, and Cell Biology (E.S.W.), Iowa State University, Ames, Iowa 50011; Plant Biology Division, The Samuel Roberts Noble Foundation, Ardmore, Oklahoma 73401 (L.S.); andDivision of Biology, Kansas State University, Manhattan, Kansas 66506 (R.W.).
Department of Plant Biology, Carnegie Institution for Science, Stanford, California 94305 (T.K., K.D., R.N.-P., S.Y.R.);Department of Biotechnology, Yonsei University, Seoul 120-749, South Korea (I.L.); Genome Center, University of California, Davis, California 95616 (O.F.); M. J. Murdock Metabolomics Laboratory, Institute of Biological Chemistry, Washington State University, Pullman, Washington 99164 (B.M.L.); Center for Metabolic Biology, Department of Biochemistry, Biophysics, and Molecular Biology (B.J.N.), and Department of Genetics, Development, and Cell Biology (E.S.W.), Iowa State University, Ames, Iowa 50011; Plant Biology Division, The Samuel Roberts Noble Foundation, Ardmore, Oklahoma 73401 (L.S.); andDivision of Biology, Kansas State University, Manhattan, Kansas 66506 (R.W.)
Plant Physiol. 2015 Apr;167(4):1685-98. doi: 10.1104/pp.114.252361. Epub 2015 Feb 10.
Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.
代谢组学能够对由遗传或环境扰动引起的代谢变化进行定量评估。然而,对于扰动单个基因如何改变整个代谢系统以及这种反应涉及哪些网络和功能特性,我们却知之甚少。为了回答这个问题,我们研究了136个具有功能各异的拟南芥基因单基因扰动的突变体的代谢物谱。在大多数突变体中,相对于野生型,显著变化的代谢物少于10种,这表明代谢网络对单个代谢基因的扰动具有较强的抗性。在基因组规模的代谢网络中,这些变化的代谢物彼此之间的距离比随机预期的更近,这支持了遗传扰动在局部而非全局改变网络的观点。令人惊讶的是,在特征明确的基因的突变体中,只有30%的突变体中变化的代谢物与扰动反应接近。为了确定导致观察到的代谢变化与网络中扰动位点之间距离的因素,我们研究了扰动基因的九种网络和功能特性。只有同工酶数量影响扰动反应与变化代谢物之间的距离。这项研究揭示了大规模基因扰动引起的代谢变化模式以及扰动基因特征与代谢变化之间的关系。