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From genomes to systems: the path with yeast

机译:从基因组到系统:酵母的路径

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Metabolic Control Analysis (MCA) is a conceptual and mathematical formalism that models the relative contributions of individual effectors in a pathway to both the flux through the pathway and the concentrations of individual intermediates within it. To exploit MCA in an initial Systems Biology analysis of the eukaryotic cell, two categories of experiments are required. In category I experiments, flux is changed and the impact on the levels of the direct and indirect products of gene action is measured. We have measured the impact of changing the flux on the transcriptome, proteome and metabolome of Saccharomyces cerevisiae. In this whole-cell analysis, flux equates to growth rate. In category 2 experiments, the levels of individual gene products are altered, and the impact on the flux is measured. We have used competition analyses between the complete set of heterozygous yeast deletion mutants to reveal genes encoding proteins with high flux control coefficients. These genes may be exploited, in a top-down analysis, to build a coarse-grained model of the eukaryotic cell, as exemplified by yeast. More detailed modelling requires that 'natural' biological systems be identified. The combination of flux balance analysis with both genetics and metabolomics in the definition of metabolic systems is discussed.
机译:代谢控制分析(MCA)是一种概念上和数学上的形式主义,它对路径中各个效应子对通过路径的通量及其中各个中间体的浓度的相对贡献进行建模。为了在真核细胞的初始系统生物学分析中利用MCA,需要进行两类实验。在第一类实验中,改变了通量,并测量了对基因作用的直接和间接产物水平的影响。我们已经测量了改变通量对酿酒酵母的转录组,蛋白质组和代谢组的影响。在这种全细胞分析中,通量等于增长率。在第2类实验中,改变了单个基因产物的水平,并测量了对通量的影响。我们已经使用了完整的杂合酵母缺失突变体之间的竞争分析来揭示编码具有高通量控制系数的蛋白质的基因。在自上而下的分析中,可以利用这些基因来构建真核细胞的粗粒模型,例如酵母。更详细的建模要求确定“天然”生物系统。讨论了代谢系统定义中通量平衡分析与遗传学和代谢组学的结合。

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