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Reference: Chubukov V, et al. (2012) Regulatory architecture determines optimal regulation of gene expression in metabolic pathways. Proc Natl Acad Sci U S A 109(13):5127-32

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Abstract


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.

Reference Type
Journal Article | Research Support, Non-U.S. Gov't | Research Support, N.I.H., Extramural
Authors
Chubukov V, Zuleta IA, Li H
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