Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
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DOI：
10.1038/msb.2010.91
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发表时间：
2010-11-30
影响因子：
9.9
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中科院分区：
文献类型：
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在特定条件下，哪些转录因子控制代谢流的分布？我们解决这个问题，通过系统地定量代谢通量在119个转录因子缺失突变体的酿酒酵母在5种生长条件下。虽然大多数基因敲除不影响通量，我们确定了42个条件依赖性的相互作用，共23个转录因子，控制几乎完全呼吸和发酵之间的细胞决策介导。这种相对稀疏的、条件特异性的主动代谢控制网络与从表达和DNA结合数据推断的大得多的基因调控网络形成对比。基于对关键突变体的蛋白质和转录物分析，我们确定了三羧酸循环中的三种酶作为这种转录控制的关键靶点。对于转录因子Gcn 4，我们证明，这种控制是通过PKA和Snf 1信号级联介导的。通量响应预测之间的差异，基于已知的监管网络架构和我们的功能13 C-数据，证明了识别和量化调节效应物改变细胞功能的程度的重要性。
Which transcription factors control the distribution of metabolic fluxes under a given condition? We address this question by systematically quantifying metabolic fluxes in 119 transcription factor deletion mutants of Saccharomyces cerevisiae under five growth conditions. While most knockouts did not affect fluxes, we identified 42 condition-dependent interactions that were mediated by a total of 23 transcription factors that control almost exclusively the cellular decision between respiration and fermentation. This relatively sparse, condition-specific network of active metabolic control contrasts with the much larger gene regulation network inferred from expression and DNA binding data. Based on protein and transcript analyses in key mutants, we identified three enzymes in the tricarboxylic acid cycle as the key targets of this transcriptional control. For the transcription factor Gcn4, we demonstrate that this control is mediated through the PKA and Snf1 signaling cascade. The discrepancy between flux response predictions, based on the known regulatory network architecture and our functional 13C-data, demonstrates the importance of identifying and quantifying the extent to which regulatory effectors alter cellular functions.
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影响因子：
--
作者：
Fendt SM;Sauer U
通讯作者：
Sauer U
影响因子：
2.1
作者：
Irizarry, RA;Hobbs, B;Speed, TP
通讯作者：
Speed, TP
影响因子：
30.8
作者：
Ihmels, J;Friedlander, G;Barkai, N
通讯作者：
Barkai, N
影响因子：
7
作者：
Kuepfer, L;Sauer, U;Blank, LM
通讯作者：
Blank, LM
影响因子：
30.8
作者：
Fischer, E;Sauer, U
通讯作者：
Sauer, U