Interplay of a Ligand Sensor and an Enzyme in Controlling Expression of the Saccharomyces cerevisiae
            <i>GAL</i>
            Genes

Abramczyk, Dariusz; Holden, Stacey; Page, C. J.; Reece, Richard J.

doi:10.1128/ec.05294-11

Cited by 23 publications

(39 citation statements)

References 34 publications

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“…Of note, Gal3 association with GAL1 in response to high galactose concentrations was transient, although expression of GAL1 occurs for longer times. However, our observation is in agreement with previous findings that report transient Gal3 association with GAL genes only in the early phase of galactose induction (47).…”

Section: Resultssupporting

confidence: 94%

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast

Rienzo

Poveda-Huertes

Aydin

et al. 2015

Molecular and Cellular Biology

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c Cells respond to environmental stimuli by fine-tuned regulation of gene expression. Here we investigated the dose-dependent modulation of gene expression at high temporal resolution in response to nutrient and stress signals in yeast. The GAL1 activity in cell populations is modulated in a well-defined range of galactose concentrations, correlating with a dynamic change of histone remodeling and RNA polymerase II (RNAPII) association. This behavior is the result of a heterogeneous induction delay caused by decreasing inducer concentrations across the population. Chromatin remodeling appears to be the basis for the dynamic GAL1 expression, because mutants with impaired histone dynamics show severely truncated dose-response profiles. In contrast, the GRE2 promoter operates like a rapid off/on switch in response to increasing osmotic stress, with almost constant expression rates and exclusively temporal regulation of histone remodeling and RNAPII occupancy. The Gal3 inducer and the Hog1 mitogen-activated protein (MAP) kinase seem to determine the different dose-response strategies at the two promoters. Accordingly, GAL1 becomes highly sensitive and dose independent if previously stimulated because of residual Gal3 levels, whereas GRE2 expression diminishes upon repeated stimulation due to acquired stress resistance. Our analysis reveals important differences in the way dynamic signals create dose-sensitive gene expression outputs.C ells continuously adapt their protein composition to changing environmental conditions. The regulation of gene expression is one of the fundamental mechanisms to adjust the global protein repertoire of the cell in order to maintain cell function and integrity in response to environmental challenges. Budding yeast is a powerful model to unravel the modes of transcriptional adaptation at the levels both of specific genes and of the whole organism (1, 2). Additionally, the basic structure of the signaling cascades responding to environmental perturbations is conserved from yeast to humans. It implies the alteration of core kinase activities, which modulate the expression of defense genes through a range of specific transcription factors. Extensive knowledge which precisely describes the molecular machinery and its global impact on gene expression in response to many types of stress has accumulated (3-7). However, the vast majority of these studies are performed with harsh environmental insults and therefore saturating stimulation. As a consequence, only very limited information or approaches are available to understand how cells adapt their gene expression programs to small or gradual changes in their environment.It is assumed that cells have acquired mechanisms that ensure a transcriptional response which is finely adjusted according to the strength of the stress or stimulation. However, the nature of the signaling molecules which confer gradual transcription outputs remains to be determined in most cases. Fine-tuning of gene expression responses can occur with different purposes, and th...

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Section: Resultssupporting

confidence: 94%

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast

Rienzo

Poveda-Huertes

Aydin

et al. 2015

Molecular and Cellular Biology

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“…Recently, a two-stage galactose induction model has been proposed whereby the Gal3p-Gal80p complex (C83) dominates initially and the Gal1p-Gal80 complex (C81) dominates at a later stage (18). To check the consequences of including this feature in our model, we scanned a wide range of parameters using the Latin hypercube sampling method (30) (SI Text, section S5) and identified sets of parameters that qualitatively matched all our data in addition to the dynamic ordering response of C83 and C81 (Fig.…”

Section: Bifurcation Analysis Of Gal Model Confirms That Only the Commentioning

confidence: 99%

“…A recent study demonstrated that cells initially grown in galactose and then transferred to glucose exhibit a faster induction response to a second galactose exposure than cells grown only in glucose, and that Gal1p was critical for this decrease in response time (17). Finally, galactose induction was shown to consist of two stages, the first of which is dominated by rapid association of Gal3p to Gal80p and a delayed second stage consisting of dominance of the Gal1p-Gal80p complex (18).…”

mentioning

confidence: 99%

Synergistic dual positive feedback loops established by molecular sequestration generate robust bimodal response

Venturelli

El-Samad

Murray

2012

Proc. Natl. Acad. Sci. U.S.A.

115

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Feedback loops are ubiquitous features of biological networks and can produce significant phenotypic heterogeneity, including a bimodal distribution of gene expression across an isogenic cell population. In this work, a combination of experiments and computational modeling was used to explore the roles of multiple feedback loops in the bimodal, switch-like response of the Saccharomyces cerevisiae galactose regulatory network. Here, we show that bistability underlies the observed bimodality, as opposed to stochastic effects, and that two unique positive feedback loops established by Gal1p and Gal3p, which both regulate network activity by molecular sequestration of Gal80p, induce this bimodality. Indeed, systematically scanning through different single and multiple feedback loop knockouts, we demonstrate that there is always a concentration regime that preserves the system's bimodality, except for the double deletion of GAL1 and the GAL3 feedback loop, which exhibits a graded response for all conditions tested. The constitutive production rates of Gal1p and Gal3p operate as bifurcation parameters because variations in these rates can also abolish the system's bimodal response. Our model indicates that this second loss of bistability ensues from the inactivation of the remaining feedback loop by the overexpressed regulatory component. More broadly, we show that the sequestration binding affinity is a critical parameter that can tune the range of conditions for bistability in a circuit with positive feedback established by molecular sequestration. In this system, two positive feedback loops can significantly enhance the region of bistability and the dynamic response time.gene-regulatory network | phenotypic variation | ultrasensitivity

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“…Gal4p, in turn, promotes the transcription of the GAL genes, including the regulatory genes GAL3, GAL1, and GAL80, the membrane-bound galactose importer gene GAL2, and the enzymes GAL1, GAL7, and GAL10 (Bram et al, 1986;Lohr et al, 1995;Bryant & Ptashne, 2003;Abramczyk et al, 2012). The paralogs GAL1 and GAL3 transduce the galactose signal, acting as positive regulators of the system (Abramczyk et al, 2012), and the network's interlocking positive and negative regulatory feedback loops control induction in the presence of galactose (Lohr et al, 1995;Acar et al, 2005;Ramsey et al, 2006). Abundant glucose represses GAL network activation (Nehlin et al, 1991;Johnston & Carlson, 1992;Bryant et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

A living vector field reveals constraints on galactose network induction in yeast

Stockwell

Rifkin

2016

Preprint

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When a cell encounters a new environment, its transcriptional response can be constrained by its history. For example, yeast cells in galactose induce GAL genes with a speed and unanimity that depends on previous nutrient conditions. Cellular memory of longterm glucose exposure delays GAL induction and makes it highly variable with in a cell population, while other nutrient histories lead to rapid, uniform responses. To investigate how cell-level gene expression dynamics produce population-level phenotypes, we built living vector fields from thousands of single-cell time courses of the proteins Gal3p and Gal1p as cells switched to galactose from various nutrient histories. We show that, after sustained glucose exposure, the lack of these GAL transducers leads to induction delays that are long but also variable; that cellular resources constrain induction; and that bimodally distributed expression levels arise from lineage selection-a subpopulation of cells induces more quickly and outcompetes the rest. Our results illuminate cellular memory in this important model system and illustrate how resources and randomness interact to shape the response of a population to a new environment.

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Interplay of a Ligand Sensor and an Enzyme in Controlling Expression of the Saccharomyces cerevisiae GAL Genes

Cited by 23 publications

References 34 publications

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast

Synergistic dual positive feedback loops established by molecular sequestration generate robust bimodal response

A living vector field reveals constraints on galactose network induction in yeast

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