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MAPK-mediated bimodal gene expression and adaptive gradient sensing in yeast

Author

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  • Saurabh Paliwal

    (and)

  • Pablo A. Iglesias

    (and
    The Johns Hopkins University, Baltimore, Maryland 21218, USA)

  • Kyle Campbell

    (University of California, San Diego, La Jolla, California 92093, USA)

  • Zoe Hilioti

    (and)

  • Alex Groisman

    (University of California, San Diego, La Jolla, California 92093, USA)

  • Andre Levchenko

    (and)

Abstract

The mating pathway in Saccharomyces cerevisiae has been the focus of considerable research effort, yet many quantitative aspects of its regulation still remain unknown. Using an integrated approach involving experiments in microfluidic chips and computational modelling, we studied gene expression and phenotypic changes associated with the mating response under well-defined pheromone gradients. Here we report a combination of switch-like and graded pathway responses leading to stochastic phenotype determination in a specific range of pheromone concentrations. Furthermore, we show that these responses are critically dependent on mitogen-activated protein kinase (MAPK)-mediated regulation of the activity of the pheromone-response-specific transcription factor, Ste12, as well as on the autoregulatory feedback of Ste12. In particular, both the switch-like characteristics and sensitivity of gene expression in shmooing cells to pheromone concentration were significantly diminished in cells lacking Kss1, one of the MAP kinases activated in the mating pathway. In addition, the dynamic range of gradient sensing of Kss1-deficient cells was reduced compared with wild type. We thus provide unsuspected functional significance for this kinase in regulation of the mating response.

Suggested Citation

  • Saurabh Paliwal & Pablo A. Iglesias & Kyle Campbell & Zoe Hilioti & Alex Groisman & Andre Levchenko, 2007. "MAPK-mediated bimodal gene expression and adaptive gradient sensing in yeast," Nature, Nature, vol. 446(7131), pages 46-51, March.
    • Handle: RePEc:nat:nature:v:446:y:2007:i:7131:d:10.1038_nature05561
    DOI: 10.1038/nature05561
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    Cited by:

    1. Yann S Dufour & Sébastien Gillet & Nicholas W Frankel & Douglas B Weibel & Thierry Emonet, 2016. "Direct Correlation between Motile Behavior and Protein Abundance in Single Cells," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-25, September.
    2. Irene Otero-Muras & Pencho Yordanov & Joerg Stelling, 2017. "Chemical Reaction Network Theory elucidates sources of multistability in interferon signaling," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-28, April.
    3. Saka, Yasushi & MacPherson, Murray & Giuraniuc, Claudiu V., 2017. "Generation and precise control of dynamic biochemical gradients for cellular assays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 132-145.

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