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PLoS Biol. 2014 Jan;12(1):e1001764. doi: 10.1371/journal.pbio.1001764. Epub 2014 Jan 14.

Different levels of catabolite repression optimize growth in stable and variable environments.

Author information

1
VIB Laboratory of Systems Biology, Leuven, Belgium ; CMPG Laboratory of Genetics and Genomics, KU Leuven, Leuven, Belgium.
2
Program in Computational Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States.

Abstract

Organisms respond to environmental changes by adapting the expression of key genes. However, such transcriptional reprogramming requires time and energy, and may also leave the organism ill-adapted when the original environment returns. Here, we study the dynamics of transcriptional reprogramming and fitness in the model eukaryote Saccharomyces cerevisiae in response to changing carbon environments. Population and single-cell analyses reveal that some wild yeast strains rapidly and uniformly adapt gene expression and growth to changing carbon sources, whereas other strains respond more slowly, resulting in long periods of slow growth (the so-called "lag phase") and large differences between individual cells within the population. We exploit this natural heterogeneity to evolve a set of mutants that demonstrate how the frequency and duration of changes in carbon source can favor different carbon catabolite repression strategies. At one end of this spectrum are "specialist" strategies that display high rates of growth in stable environments, with more stringent catabolite repression and slower transcriptional reprogramming. The other mutants display less stringent catabolite repression, resulting in leaky expression of genes that are not required for growth in glucose. This "generalist" strategy reduces fitness in glucose, but allows faster transcriptional reprogramming and shorter lag phases when the cells need to shift to alternative carbon sources. Whole-genome sequencing of these mutants reveals that mutations in key regulatory genes such as HXK2 and STD1 adjust the regulation and transcriptional noise of metabolic genes, with some mutations leading to alternative gene regulatory strategies that allow "stochastic sensing" of the environment. Together, our study unmasks how variable and stable environments favor distinct strategies of transcriptional reprogramming and growth.

PMID:
24453942
PMCID:
PMC3891604
DOI:
10.1371/journal.pbio.1001764
[Indexed for MEDLINE]
Free PMC Article
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