From genomes to systems: the path with yeast
From genomes to systems: the path with yeast
复制标题
从基因组到系统：酵母之路
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
S. Oliver
中科院分区：
文献类型：
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作者：
S. Oliver
代谢控制分析（MCA）是一种概念和数学形式，它模拟了途径中单个效应器对通过途径的通量和其中单个中间体浓度的相对贡献。为了在真核细胞的初始系统生物学分析中利用MCA，需要两类实验。在第一类实验中，改变通量，并测量对基因作用的直接和间接产物水平的影响。我们测量了改变通量对酿酒酵母转录组、蛋白质组和代谢组的影响。在这种全细胞分析中，通量等同于生长速率。在第2类实验中，改变单个基因产物的水平，并测量其对通量的影响。我们使用竞争分析在全套杂合酵母缺失突变体之间揭示编码高通量控制系数蛋白的基因。这些基因可以被利用，在自上而下的分析中，建立真核细胞的粗粒度模型，如酵母的例子。更详细的建模需要识别“自然”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。
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 1 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.
影响因子：
7
作者：
Förster, J;Famili, I;Nielsen, J
通讯作者：
Nielsen, J
影响因子：
56.9
作者：
Winzeler, EA;Shoemaker, DD;Davis, RW
通讯作者：
Davis, RW