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Metabolic gene regulation in a dynamically changing environment


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.

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Figure 1: Design and implementation of the microfluidic platform developed for our study.
Figure 2: Regulation in the galactose utilization network.
Figure 3: Experimental and computational results for cells of two yeast strains expressing a GAL1–yECFP fusion gene in response to alternating glucose and galactose media.
Figure 4: Experimental and computational comparison of two yeast strains.


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We thank A. Groisman for useful discussions regarding microfluidic design; D. Volfson and C. Grilly for aid in development and testing of image segmentation and tracking algorithms, and M. Ferry for his suggestions on microbiology. This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health.

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Correspondence to Jeff Hasty.

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Supplementary Information 1

The file contains containing specific details on methodology and computational aspects of the study, including Supplementary Figures S1-S6 and Supplementary Tables.S1-S4 (PDF 452 kb)

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Bennett, M., Pang, W., Ostroff, N. et al. Metabolic gene regulation in a dynamically changing environment. Nature 454, 1119–1122 (2008).

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