Literature DB >> 22024631

Mathematical model of GAL regulon dynamics in Saccharomyces cerevisiae.

Raluca Apostu1, Michael C Mackey.   

Abstract

Genetic switches are prevalent in nature and provide cells with a strategy to adapt to changing environments. The GAL switch is an intriguing example which is not understood in all detail. The GAL switch allows organisms to metabolize galactose, and controls whether the machinery responsible for the galactose metabolism is turned on or off. Currently, it is not known exactly how the galactose signal is sensed by the transcriptional machinery. Here we utilize quantitative tools to understand the S. cerevisiae cell response to galactose challenge, and to analyze the plausible molecular mechanisms underlying its operation. We work at a population level to develop a dynamic model based on the interplay of the key regulatory proteins Gal4p, Gal80p, and Gal3p. To our knowledge, the model presented here is the first to reproduce qualitatively the bistable network behavior found experimentally. Given the current understanding of the GAL circuit induction (Wightman et al., 2008; Jiang et al., 2009), we propose that the most likely in vivo mechanism leading to the transcriptional activation of the GAL genes is the physical interaction between galactose-activated Gal3p and Gal80p, with the complex Gal3p-Gal80p remaining bound at the GAL promoters. Our mathematical model is in agreement with the flow cytometry profiles of wild type, gal3Δ and gal80Δ mutant strains from Acar et al. (2005), and involves a fraction of actively transcribing cells with the same qualitative features as in the data set collected by Acar et al. (2010). Furthermore, the computational modeling provides an explanation for the contradictory results obtained by independent laboratories when tackling experimentally the issue of binary versus graded response to galactose induction.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 22024631     DOI: 10.1016/j.jtbi.2011.10.012

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  5 in total

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Authors:  David I Orozco-Gómez; Juan Eduardo Sosa-Hernández; Óscar Adrián Gallardo-Navarro; Jesús Santana-Solano; Moisés Santillán
Journal:  Sci Rep       Date:  2019-04-01       Impact factor: 4.379

3.  Gene network requirements for regulation of metabolic gene expression to a desired state.

Authors:  Jan Berkhout; Bas Teusink; Frank J Bruggeman
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

4.  A cell size- and cell cycle-aware stochastic model for predicting time-dynamic gene network activity in individual cells.

Authors:  Ruijie Song; Weilin Peng; Ping Liu; Murat Acar
Journal:  BMC Syst Biol       Date:  2015-12-09

5.  Assigning function to natural allelic variation via dynamic modeling of gene network induction.

Authors:  Magali Richard; Florent Chuffart; Hélène Duplus-Bottin; Fanny Pouyet; Martin Spichty; Etienne Fulcrand; Marianne Entrevan; Audrey Barthelaix; Michael Springer; Daniel Jost; Gaël Yvert
Journal:  Mol Syst Biol       Date:  2018-01-15       Impact factor: 11.429

  5 in total

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