Sriram Ganesh, Fulton D Bruce, Iyer Vidya V, Peterson Joan Marie, Zhou Ruilian, Westgate Mark E, Spalding Martin H, Shanks Jacqueline V
Department of Chemical Engineering , Iowa State University, Ames, Iowa 50011, USA.
Plant Physiol. 2004 Oct;136(2):3043-57. doi: 10.1104/pp.104.050625. Epub 2004 Oct 1.
Metabolic flux quantification in plants is instrumental in the detailed understanding of metabolism but is difficult to perform on a systemic level. Toward this aim, we report the development and application of a computer-aided metabolic flux analysis tool that enables the concurrent evaluation of fluxes in several primary metabolic pathways. Labeling experiments were performed by feeding a mixture of U-(13)C Suc, naturally abundant Suc, and Gln to developing soybean (Glycine max) embryos. Two-dimensional [(13)C, (1)H] NMR spectra of seed storage protein and starch hydrolysates were acquired and yielded a labeling data set consisting of 155 (13)C isotopomer abundances. We developed a computer program to automatically calculate fluxes from this data. This program accepts a user-defined metabolic network model and incorporates recent mathematical advances toward accurate and efficient flux evaluation. Fluxes were calculated and statistical analysis was performed to obtain sds. A high flux was found through the oxidative pentose phosphate pathway (19.99 +/- 4.39 micromol d(-1) cotyledon(-1), or 104.2 carbon mol +/- 23.0 carbon mol per 100 carbon mol of Suc uptake). Separate transketolase and transaldolase fluxes could be distinguished in the plastid and the cytosol, and those in the plastid were found to be at least 6-fold higher. The backflux from triose to hexose phosphate was also found to be substantial in the plastid (21.72 +/- 5.00 micromol d(-1) cotyledon(-1), or 113.2 carbon mol +/-26.0 carbon mol per 100 carbon mol of Suc uptake). Forward and backward directions of anaplerotic fluxes could be distinguished. The glyoxylate shunt flux was found to be negligible. Such a generic flux analysis tool can serve as a quantitative tool for metabolic studies and phenotype comparisons and can be extended to other plant systems.
植物中的代谢通量定量对于深入理解新陈代谢至关重要,但在系统水平上进行却很困难。为了实现这一目标,我们报告了一种计算机辅助代谢通量分析工具的开发和应用,该工具能够同时评估几种主要代谢途径中的通量。通过向发育中的大豆(Glycine max)胚胎投喂U-(13)C蔗糖、天然丰度的蔗糖和谷氨酰胺的混合物进行标记实验。获取了种子储存蛋白和淀粉水解产物的二维[(13)C, (1)H] NMR光谱,并产生了一个由155个(13)C同位素异构体丰度组成的标记数据集。我们开发了一个计算机程序来自动从这些数据中计算通量。该程序接受用户定义的代谢网络模型,并纳入了近期在准确高效通量评估方面的数学进展。计算了通量并进行了统计分析以获得标准差。发现通过氧化戊糖磷酸途径的通量很高(19.99±4.39 μmol d(-1)子叶(-1),或每100碳摩尔蔗糖摄取量104.2碳摩尔±23.0碳摩尔)。在质体和细胞质中可以区分转酮醇酶和转醛醇酶的单独通量,并且发现质体中的通量至少高6倍。还发现三碳糖向磷酸己糖的反向通量在质体中也很大(21.72±5.00 μmol d(-1)子叶(-1),或每100碳摩尔蔗糖摄取量113.2碳摩尔±26.0碳摩尔)。可以区分回补途径通量的正向和反向方向。发现乙醛酸循环通量可以忽略不计。这样一种通用的通量分析工具可以作为代谢研究和表型比较的定量工具,并可以扩展到其他植物系统。