Regulatory architecture determines optimal regulation of gene expression in metabolic pathways

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.A classic paradigm of gene regulation is the regulation of metabolic enzyme expression in response to changes in external nutrient levels. By regulating enzyme levels, cells not only control the metabolic program, but also save resources and energy by not expressing enzymes that are not needed at a particular time. To achieve this regulation, a variety of strategies can be used, involving different interplay between metabolites, enzymes, and regulatory proteins. In many cases involving model organisms, the regulatory framework that controls this process is known, and research over past decades has revealed a number of different regulatory strategies (1-4).For a linear biosynthetic pathway, a general strategy for controlling the pathway flux is end product feedback inhibition, typically acting on the first enzyme of the pathway (Fig. 1 B-D) and serving as the main sensor of product depletion. In addition, the expression of enzymes is often controlled at the transcriptional level, by transcription factors (TFs) that can sense either the end product or an intermediate metabolite, giving rise to different regulatory architectures (Fig.

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