Metabolic gene regulation in a dynamically changing environment

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Abstract
Living organisms have evolved under pressure to constantly adapt to rapidly changing environmental conditions. Yet cellular functions are usually studied under stable laboratory conditions or abrupt changes at best. Bennett et al. have now developed a microfluidics platform to present yeast cells with smoothly periodic changes in culture conditions. They observe that the yeast metabolic system reliably responds to slowly changing environment but filters out fast fluctuations. They then show that mutant cells that differed when probed in static environments have actually been optimized for similarly robust responses to dynamically changing environments. Finally, coupling this new approach with mathematical modelling, they predict and experimentally confirm a new regulatory link between the glucose and galactose signalling pathways. Natural selection dictates that cells constantly adapt to dynamically changing environments in a context-dependent manner. Gene-regulatory networks often mediate the cellular response to perturbation1,2,3, and an understanding of cellular adaptation will require experimental approaches aimed at subjecting cells to a dynamic environment that mimics their natural habitat4,5,6,7,8,9. Here we monitor the response of Saccharomyces cerevisiae metabolic gene regulation to periodic changes in the external carbon source by using a microfluidic platform that allows precise, dynamic control over environmental conditions. We show that the metabolic system acts as a low-pass filter that reliably responds to a slowly changing environment, while effectively ignoring fast fluctuations. The sensitive low-frequency response was significantly faster than in predictions arising from our computational modelling, and this discrepancy was resolved by the discovery that two key galactose transcripts possess half-lives that depend on the carbon source. Finally, to explore how induction characteristics affect frequency response, we compare two S. cerevisiae strains and show that they have the same frequency response despite having markedly different induction properties. This suggests that although certain characteristics of the complex networks may differ when probed in a static environment, the system has been optimized for a robust response to a dynamically changing environment.