Stochastic variation in the concentration of a repressor activates GAL genetic switch: implications in evolution of regulatory network

A double role of the Gal80 N terminus in activation of transcription by Gal4p

Activation of gene expression by Gal4p in K. lactis requires an element in the N terminus of KlGal80p that mediates nuclear co-import of KlGal1p and galactokinase inhibition to support the co-inducer function of KlGal1p.

The yeast galactose switch operated by the Gal4p–Gal80p–Gal3p regulatory module is a textbook model of transcription regulation in eukaryotes. The Gal80 protein inhibits Gal4p-mediated transcription activation by binding to the transcription activation domain. In Saccharomyces cerevisiae, inhibition is relieved by formation of an alternative Gal80–Gal3 complex. In yeasts lacking a Gal3p ortholog, such as Kluyveromyces lactis, the Gal1 protein (KlGal1p) combines regulatory and enzymatic activity. The data presented here reveal a yet unknown role of the KlGal80 N terminus in the mechanism of Gal4p activation. The N terminus contains an NLS, which is responsible for nuclear accumulation of KlGal80p and KlGal1p and for KlGal80p-mediated galactokinase inhibition. Herein, we present a model where the N terminus of KlGal80p reaches the catalytic center of KlGal1p causing enzyme inhibition in the nucleus and stabilization of the KlGal1–KlGal80p complex. We corroborate this model by genetic analyses and structural modelling and provide a rationale for the divergent evolution of the mechanism activating Gal4p.

A G-protein subunit translocation embedded network motif underlies GPCR regulation of calcium oscillations

G-protein βγ subunits translocate reversibly from the plasma membrane to internal membranes on receptor activation. Translocation rates differ depending on the γ subunit type. There is limited understanding of the role of the differential rates of Gβγ translocation in modulating signaling dynamics in a cell. Bifurcation analysis of the calcium oscillatory network structure predicts that the translocation rate of a signaling protein can regulate the damping of system oscillation. Here, we examined whether the Gβγ translocation rate regulates calcium oscillations induced by G-protein-coupled receptor activation. Oscillations in HeLa cells expressing γ subunit types with different translocation rates were imaged and quantitated. The results show that differential Gβγ translocation rates can underlie the diversity in damping characteristics of calcium oscillations among cells. Mathematical modeling shows that a translocation embedded motif regulates damping of G-protein-mediated calcium oscillations consistent with experimental data. The current study indicates that such a motif may act as a tuning mechanism to design oscillations with varying damping patterns by using intracellular translocation of a signaling component.

Stochastic galactokinase expression underlies GAL gene induction in a GAL3 mutant of Saccharomyces cerevisiae

GAL1 and GAL3 are paralogous signal transducers that functionally inactivate Gal80p to activate the Gal4p-dependent transcriptional activation of GAL genes in Saccharomyces cerevisiae in response to galactose. Unlike a wild-type strain, the gal3∆ strain shows delayed growth kinetics as a result of the signaling function of GAL1. The mechanism ensuring that GAL1 is eventually expressed to turn on the GAL switch in the gal3∆ strain remains a paradox. Using galactose and histidine growth complementation assays, we demonstrate that 0.3% of the gal3∆ cell population responds to galactose. This is corroborated by flow cytometry and microscopic analysis. The galactose responders and nonresponders isolated from the galactose-adapted population attain the original bimodal state and this phenotype is found to be as hard wired as a genetic trait. Computational analysis suggests that the log-normal distribution in GAL4 synthesis can lead to bimodal expression of GAL80, resulting in the bimodal expression of GAL genes. Heterozygosity at the GAL80 but not at the GAL1, GAL2 or GAL4 locus alters the extent of bimodality of the gal3∆ cell population. We suggest that the asymmetric expression pattern between GAL1 and GAL3 results in the ability of S. cerevisiae to activate the GAL pathway by conferring nongenetic heterogeneity.

Mathematical model of GAL regulon dynamics in Saccharomyces cerevisiae

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.

Epigenetics of the yeast galactose genetic switch

The transcriptional activation of enzymes involved in galactose utilization (GAL genes) in Saccharomyces cerevisiae is regulated by a complex interplay between three regulatory proteins encoded by GAL4 (transcriptional activator), GAL3 (signal transducer) and GAL80 (repressor). The relative concentrations of the signal transducer and the repressor are maintained by autoregulation. Cells disabled for autoregulation exhibit phenotypes distinctly different from that of the wild type cells, enabling us to explore the biological significance of autoregulation. The redundancy in signal transduction due to the presence of GAL1 (alternate signal transducer) also makes it a suitable model to understand the phenomenon of epigenetics. In this article we review some of the recent attempts made to understand the importance of epigenetics in the establishment of cellular and transcriptional memory.

Steady state approach to model gene regulatory networks—Simulation of microarray experiments

Genetic regulatory networks (GRN) represent complex interactions between genes brought about through proteins that they code for. Quantification of expression levels in GRN either through experiments or theoretical modeling is a challenging task. Recently, microarray experiments have gained importance in evaluating GRN at the genome level. Microarray experiments yield log fold change in mRNA abundance which is helpful in deciphering connectivity in GRN. Current approaches such as data mining, Boolean or Bayesian modeling and combined use of expression and location data are useful in analyzing microarray data. However, these methodologies lack underlying mechanistic details present in GRN. We present here a steady state gene expression simulator (SSGES) which sets up steady state equations and simulates the response for a given network structure of a GRN. SSGES includes mechanistic details such as stoichiometry, protein-DNA and protein-protein interactions, translocation of regulatory proteins and autoregulation. SSGES can be used to simulate the response of a GRN in terms of fractional transcription and protein expression. SSGES can also be used to generate log fold change in mRNA abundance and protein expression implying that it is useful to simulate microarray type experiments. We have demonstrated these capabilities of SSGES by modeling the steady state response of GAL regulatory system in Saccharomyces cerevisiae. We have demonstrated that the predicted data qualitatively matched the microarray data obtained experimentally by Ideker et al. [Ideker, T., Thorsson, V., Ranish, J.A., Christmas, R., Buhler, J., Eng, J.K., Bumgarner, R., Goodlett, D.R., Aebersold, R., Hood, L., 2001. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929-934]. SSGES is available from authors upon request.

The regulatory roles of the galactose permease and kinase in the induction response of the GAL network in Saccharomyces cerevisiae

The GAL genetic switch of Saccharomyces cerevisiae exhibits an ultrasensitive response to the inducer galactose as well as the "all-or-none" behavior characteristic of many eukaryotic regulatory networks. We have constructed a strain that allows intermediate levels of gene expression from a tunable GAL1 promoter at both the population and the single cell level by altering the regulation of the galactose permease Gal2p. Similar modifications to other feedback loops regulating the Gal80p repressor and the Gal3p signaling protein did not result in similarly tuned responses, indicating that the level of inducer transport is unique in its ability to control the switch response of the network. In addition, removal of the Gal1p galactokinase from the network resulted in a regimed response due to the dual role of this enzyme in galactose catabolism and transport. These two activities have competing effects on the response of the network to galactose such that the transport effects of Gal1p are dominant at low galactose concentrations, whereas its catabolic effects are dominant at high galactose concentrations. In addition, flow cytometry analysis revealed the unexpected phenomenon of multiple populations in the gal1delta strains, which were not present in the isogenic GAL1 background. This result indicates that Gal1p may play a previously undescribed role in the stability of the GAL network response.

Eukaryotic transcription factors as direct nutrient sensors

The recognition of changes in environmental conditions, and the ability to adapt to these changes, is essential for the viability of cells. There are numerous well-characterized systems by which the presence or absence of an individual metabolite can be recognized by a cell. The recognition of a metabolite is, however, just one step of a process that often results in changes in the expression of sets of genes required to respond to that metabolite. The signalling pathway between metabolite recognition and transcriptional control is often complex. However, recent evidence from yeast suggests that complex signalling pathways might be circumvented via the direct interaction between individual metabolites and regulators of RNA polymerase II transcription.

A hybrid photoreceptor expressing both rod and cone genes in a mouse model of enhanced S-cone syndrome

Rod and cone photoreceptors subserve vision under dim and bright light conditions, respectively. The differences in their function are thought to stem from their different gene expression patterns, morphologies, and synaptic connectivities. In this study, we have examined the photoreceptor cells of the retinal degeneration 7(rd7) mutant mouse, a model for the human enhanced S-cone syndrome (ESCS). This mutant carries a spontaneous deletion in the mouse ortholog of NR2E3, an orphan nuclear receptor transcription factor mutated in ESCS. Employing microarray and in situ hybridization analysis we have found that the rd7 retina contains a modestly increased number of S-opsin-expressing cells that ultrastructurally appear to be normal cones. Strikingly, the majority of the photoreceptors in the rd7 retina represent a morphologically hybrid cell type that expresses both rod- and cone-specific genes. In addition, in situ hybridization screening of genes shown to be up-regulated in the rd7 mutant retina by microarray identified ten new cone-specific or cone-enriched genes with a wide range of biochemical functions, including two genes specifically involved in glucose/glycogen metabolism. We suggest that the abnormal electroretinograms, slow retinal degeneration, and retinal dysmorphology seen in humans with ESCS may, in part, be attributable to the aberrant function of a hybrid photoreceptor cell type similar to that identified in this study. The functional diversity of the novel cone-specific genes identified here indicates molecular differences between rods and cones extending far beyond those previously discovered.

A comparative analysis of the GAL genetic switch between not-so-distant cousins: Saccharomyces cerevisiae versus Kluyveromyces lactis

Despite their close phylogenetic relationship, Kluyveromyces lactis and Saccharomyces cerevisiae have adapted their carbon utilization systems to different environments. Although they share identities in the arrangement, sequence and functionality of their GAL gene set, both yeasts have evolved important differences in the GAL genetic switch in accordance to their relative preference for the utilization of galactose as a carbon source. This review provides a comparative overview of the GAL-specific regulatory network in S. cerevisiae and K. lactis, discusses the latest models proposed to explain the transduction of the galactose signal, and describes some of the particularities that both microorganisms display in their regulatory response to different carbon sources. Emphasis is placed on the potential for improved strategies in biotechnological applications using yeasts.