Regulatory architecture determines optimal regulation of gene expression in metabolic pathways
Regulatory architecture determines optimal regulation of gene expression in metabolic pathways
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DOI：
10.1073/pnas.1114235109
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发表时间：
2012-03-27
影响因子：
11.1
通讯作者：
Li, Hao
中科院分区：
文献类型：
--
作者：
Chubukov, Victor;Zuleta, Ignacio A.;Li, Hao
为了响应环境的变化，基因调控网络中的连接（“箭头”）决定了哪些基因调节它们的表达，但网络的定量参数（“箭头上的数字”）在决定所产生的表型方面同样重要。进化决定这些参数的目标和限制是什么？我们探讨这些问题，通过分析基因表达的变化，在一些酵母代谢途径响应营养耗竭。我们发现，出现了一个惊人的模式，夫妇的调控结构的途径的基因表达反应。特别是，我们发现，控制的中间代谢物激活（IMA）架构，其中一个中间代谢物激活转录的途径基因的途径，表现出以下响应：酶的调节代谢物的下游是最强的转录控制下，而诱导的酶上游的调节中间体是相对较弱的。这种反应模式在不受IMA结构控制的通路中不存在。这种现象可以用网络的基本反馈结构所施加的约束来解释，该结构将下游酶置于负反馈环下，将上游酶置于正反馈环下。这种代谢途径的转录控制的一般设计原则可以从基因表达的简单成本/效益模型中推导出来，其中观察到的模式是最佳解决方案。我们的研究结果表明，调节代谢酶表达的参数优化的进化，在强约束下的基本监管架构。
In response to environmental changes, the connections ("arrows") in gene regulatory networks determine which genes modulate their expression, but the quantitative parameters of the network ("the numbers on the arrows") are equally important in determining the resulting phenotype. What are the objectives and constraints by which evolution determines these parameters? We explore these issues by analyzing gene expression changes in a number of yeast metabolic pathways in response to nutrient depletion. We find that a striking pattern emerges that couples the regulatory architecture of the pathway to the gene expression response. In particular, we find that pathways controlled by the intermediate metabolite activation (IMA) architecture, in which an intermediate metabolite activates transcription of pathway genes, exhibit the following response: the enzyme immediately downstream of the regulatory metabolite is under the strongest transcriptional control, whereas the induction of the enzymes upstream of the regulatory intermediate is relatively weak. This pattern of responses is absent in pathways not controlled by an IMA architecture. The observation can be explained by the constraint imposed by the fundamental feedback structure of the network, which places downstream enzymes under a negative feedback loop and upstream ones under a positive feedback loop. This general design principle for transcriptional control of a metabolic pathway can be derived from a simple cost/benefit model of gene expression, in which the observed pattern is an optimal solution. Our results suggest that the parameters regulating metabolic enzyme expression are optimized by evolution, under the strong constraint of the underlying regulatory architecture.