Gal80-Gal80 interaction on adjacent Gal4p binding sites is required for complete GAL gene repression

Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor

The ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr, GALL, MET3pr, CUP1pr, PHO5pr, tetOpr, terminator-tetOpr, Z₃EV, blue-light inducible optogenetic systems El222-LIP, El222-GLIP, and red-light inducible PhyB-PIF3. We report kinetic parameters, noise scaling, impact on growth, and the fundamental leakiness of each system using an intuitive unit, maxGAL1. We uncover disadvantages of widely used tools, e.g., nonmonotonic activity of MET3pr and GALL, slow off kinetics of the doxycycline- and estradiol-inducible systems tetOpr and Z₃EV, and high variability of PHO5pr and red-light activated PhyB-PIF3 system. We introduce two previously uncharacterized systems: strongLOV, a more light-sensitive El222 mutant, and ARG3pr, which is induced in the absence of arginine or presence of methionine. To demonstrate fine control over gene circuits, we experimentally tune the time between cell cycle Start and mitosis, artificially simulating near-wild-type timing. All strains, constructs, code, and data ( https://promoter-benchmark.epfl.ch/ ) are made available.

Engineering Pheromone-Mediated Quorum Sensing with Enhanced Response Output Increases Fucosyllactose Production in Saccharomyces cerevisiae

Engineering dynamic control of gene expression is desirable because many engineered functions interfere with endogenous cellular processes that have evolved to facilitate growth and survival. Minimizing conflict between growth and production phases can therefore improve product titers in microbial cell factories. We developed an autoinduced gene expression system by rewiring the Saccharomyces cerevisiae pheromone response pathway. To ameliorate growth reduction due to the early onset response at low population densities, α-pheromone of Kluyveromyces lactis (Kα) instead of S. cerevisiae (Sα) was expressed in mating type "a" yeast. Kα-induced expression of pathway genes was further enhanced by the transcriptional activator Gal4p expressed under the control of the pheromone-responsive FUS1 promoter (P_fus1). As a demonstration, the engineered circuit combined with the deletion of the endogenous galactose metabolic pathway genes was applied to the production of human milk oligosaccharides, 2'-fucosyllactose (2'-FL) and 3-fucosllactose (3-FL). The engineered strains produced 3.37 g/L 2'-FL and 2.36 g/L 3-FL on glucose with a volumetric productivity of 0.14 and 0.03 g/L·h^-1 in batch flask cultivation, respectively. These represented 147 and 153% increases over the control strains on galactose wherein the respective pathway genes are expressed under GAL promoters only. Further fed-batch fermentation achieved titers of 32.05 and 20.91 g/L for 2' and 3-FL, respectively. The genetic program developed here thus represents a promising option for implementing dynamic regulation in yeast and could be used for the production of biochemicals that may place a heavy metabolic burden on cell growth.

Enhancement of catabolite regulatory genes in Saccharomyces cerevisiae to increase ethanol production using hydrolysate from red seaweed Gloiopeltis furcata

Glucose and galactose are monosaccharides obtained from Gloiopeltis furcata (Red algae). A total monosaccharide yield of 62.3 g/L was obtained from G. furcata using thermal acid hydrolysis and enzymatic saccharification. Activated carbon was used to eliminate hydroxymethylfurfural (HMF) from the hydrolysate. Previously obtained monosaccharides are used for ethanol production by Saccharomyces cerevisiae. S. cerevisiae consumes glucose first, then galactose. The methods for reducing fermentation time and increasing the ethanol yield coefficient using the simultaneous consumption of glucose and galactose have been evaluated. Gal3p and Gal80p of S. cerevisiae act as signal transducers that govern the galactose inducer Gal4p mediated transcriptional activation of the Gal gene family. Gal80p binds to Gal4p for transcription deactivation. Therefore, Gal80p was deleted for Gal4p expression without interruption.

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.

Monitoring of switches in heterochromatin-induced silencing shows incomplete establishment and developmental instabilities

Position effect variegation (PEV) in Drosophila results from new juxtapositions of euchromatic and heterochromatic chromosomal regions, and manifests as striking bimodal patterns of gene expression. The semirandom patterns of PEV, reflecting clonal relationships between cells, have been interpreted as gene-expression states that are set in development and thereafter maintained without change through subsequent cell divisions. The rate of instability of PEV is almost entirely unexplored beyond the final expression of the modified gene; thus the origin of the expressivity and patterns of PEV remain unexplained. Many properties of PEV are not predicted from currently accepted biochemical and theoretical models. In this work we investigate the time at which expressivity of silencing is set, and find that it is determined before heterochromatin exists. We employ a mathematical simulation and a corroborating experimental approach to monitor switching (i.e., gains and losses of silencing) through development. In contrast to current views, we find that gene silencing is incompletely set early in embryogenesis, but nevertheless is repeatedly lost and gained in individual cells throughout development. Our data support an alternative to locus-specific "epigenetic" silencing at variegating gene promoters that more fully accounts for the final patterns of PEV.

Measurement of In Vivo Protein Binding Affinities in a Signaling Network with Mass Spectrometry

Protein interaction networks play a key role in signal processing. Despite the progress in identifying the interactions, the quantification of their strengths lags behind. Here we present an approach to quantify the in vivo binding of proteins to their binding partners in signaling-transcriptional networks, by the pairwise genetic isolation of each interaction and by varying the concentration of the interacting components over time. The absolute quantification of the protein concentrations was performed with targeted mass spectrometry. The strengths of the interactions, as defined by the apparent dissociation constants, ranged from subnanomolar to micromolar values in the yeast galactose signaling network. The weak homodimerization of the Gal4 activator amplifies the signal elicited by glucose. Furthermore, combining the binding constants in a feedback loop correctly predicted cellular memory, a characteristic network behavior. Thus, this genetic-proteomic binding assay can be used to faithfully quantify how strongly proteins interact with proteins, DNA and metabolites.

Polymorphisms in the yeast galactose sensor underlie a natural continuum of nutrient-decision phenotypes

In nature, microbes often need to "decide" which of several available nutrients to utilize, a choice that depends on a cell’s inherent preference and external nutrient levels. While natural environments can have mixtures of different nutrients, phenotypic variation in microbes’ decisions of which nutrient to utilize is poorly studied. Here, we quantified differences in the concentration of glucose and galactose required to induce galactose-responsive (GAL) genes across 36 wild S. cerevisiae strains. Using bulk segregant analysis, we found that a locus containing the galactose sensor GAL3 was associated with differences in GAL signaling in eight different crosses. Using allele replacements, we confirmed that GAL3 is the major driver of GAL induction variation, and that GAL3 allelic variation alone can explain as much as 90% of the variation in GAL induction in a cross. The GAL3 variants we found modulate the diauxic lag, a selectable trait. These results suggest that ecological constraints on the galactose pathway may have led to variation in a single protein, allowing cells to quantitatively tune their response to nutrient changes in the environment.

In nature, microbes often need to decide which of many potential nutrients to consume. This decision making process is complex, involving both intracellular constraints and the organism’s perception of the environment. To begin to mimic the complexity of natural environments, we grew cells in mixtures of two sugars, glucose and galactose. We find that in mixed environments, the sugar concentration at which cells decides to induce galactose-utilizing (GAL) genes is highly variable in natural isolates of yeast. By analyzing crosses of phenotypically different strains, we identified a locus containing the galactose sensor, a gene that in theory could allow cells to tune their perception of the environment. We confirmed that the galactose sensor can explain upwards of 90% of the variation in the decision to induce GAL genes. Finally, we show that the variation in the galactose sensor can modulate the time required for cells to switch from utilizing glucose to galactose. Our results suggest that signaling pathways can be highly variable across strains and thereby might allow for rapid adaption in fluctuating environments.

Design and Construction of Generalizable RNA-Protein Hybrid Controllers by Level-Matched Genetic Signal Amplification

For synthetic biology applications, protein-based transcriptional genetic controllers are limited in terms of orthogonality, modularity, and portability. Although ribozyme-based switches can address these issues, their current two-stage architectures and limited dynamic range hinder their broader incorporation into systems-level genetic controllers. Here, we address these challenges by implementing an RNA-protein hybrid controller with a three-stage architecture that introduces a transcription-based amplifier between an RNA sensor and a protein actuator. To facilitate the construction of these more complex circuits, we use a model-guided strategy to efficiently match the activities of stages. The presence of the amplifier enabled the three-stage controller to have up to 200-fold higher gene expression than its two-stage counterpart and made it possible to implement higher-order controllers, such as multilayer Boolean logic and feedback systems. The modularity inherent in the three-stage architecture along with the sensing flexibility of RNA devices presents a generalizable framework for designing and building sophisticated genetic control systems.

The binary response of the GAL/MEL genetic switch of Saccharomyces cerevisiae is critically dependent on Gal80p-Gal4p interaction

Studies on the Saccharomyces cerevisiae GAL/MEL genetic switch have revealed that its bistability is dependent on ultrasensitivity that can be altered or abolished by disabling different combinations of nested feedback loops. In contrast, we have previously demonstrated that weakening of the interaction between Gal80p and Gal4p alone is sufficient to abolish the ultrasensitivity (Das Adhikari et al. 2014). Here, we demonstrate that altering the epistatic interaction between Gal80p and Gal4p also abolishes the bistability, and the switch response to galactose becomes graded instead of binary. However, the GAL/MEL switch of wild-type and epistatically altered strains responded in a graded fashion to melibiose. The properties of the epistatically altered strain resemble Kluyveromyces lactis, which separated from the Saccharomyces lineage 100 mya before whole-genome duplication (WGD). Based on the results reported here, we propose that epistatic interactions played a crucial role in the evolution of the fine regulation of S. cerevisiae GAL/MEL switch following WGD.

Hsp90 Maintains Proteostasis of the Galactose Utilization Pathway To Prevent Cell Lethality

Hsp90 is a molecular chaperone that aids in the folding of its metastable client proteins. Past studies have shown that it can exert a strong impact on some cellular pathways by controlling key regulators. However, it is unknown whether several components of a single pathway are collectively regulated by Hsp90. Here, we observe that Hsp90 influences the protein abundance of multiple Gal proteins and the efficiency of galactose utilization even after the galactose utilization pathway (GAL pathway) is fully induced. The effect of Hsp90 on Gal proteins is not at the transcriptional level. Moreover, Gal1 is found to physically interact with Hsp90, and its stability is reduced in low-Hsp90 cells. When Hsp90 is compromised, several Gal proteins form protein aggregates that colocalize with the disaggregase Hsp104. These results suggest that Gal1 and other Gal proteins are probably the clients of Hsp90. An unbalanced GAL pathway has been known to cause fatal growth arrest due to accumulation of toxic galactose metabolic intermediates. It is likely that Hsp90 chaperones multiple Gal proteins to maintain proteostasis and prevent cell lethality especially in a fluctuating environment.

SUMO regulates somatic cyst stem cells maintenance and directly targets hedgehog pathway in adult Drosophila testis

SUMO (Small ubiquitin-related modifier) modification (SUMOylation) is a highly dynamic post-translational modification (PTM) playing important roles in tissue development and disease progression. However, its function in adult stem cell maintenance is largely unknown. Here we report the function of SUMOylation in somatic cyst stem cells (CySCs) self-renewal in adult Drosophila testis. The SUMO pathway cell-autonomously regulates CySCs maintenance. Reduction of SUMOylation promotes premature differentiation of CySCs and impedes the proliferation of CySCs, which finally reduce the number of CySCs. Consistently, CySC clones carrying mutation of the SUMO conjugating enzyme are rapidly lost. Furthermore, inhibition of SUMO pathway phenocopies the disruption of Hedgehog (Hh) pathway, and can block the promoted proliferation of CySCs by Hh activation. Importantly, SUMO pathway directly regulates the SUMOylation of Hh pathway transcriptional factor, Cubitus interruptus (Ci), which is required for promoting CySCs proliferation. Thus, we conclude that SUMO directly targets Hh pathway and regulates CySCs maintenance in adult Drosophila testis.

Perturbation of the interaction between Gal4p and Gal80p of the Saccharomyces cerevisiae GAL switch results in altered responses to galactose and glucose

In S. cerevisiae, following the Whole Genome Duplication (WGD), GAL1-encoded galactokinase retained its signal transduction function but lost basal expression. On the other hand, its paralogue GAL3, lost kinase activity but retained its signalling function and basal expression, thus making it indispensable for the rapid induction of the S. cerevisiae GAL switch. However, a gal3Δ strain exhibits delayed growth kinetics due to the redundant signalling function of GAL1. The subfunctionalization between the paralogues GAL1 and GAL3 is due to expression divergence and is proposed to be due to the alteration in the Upstream Activating Sequences (UASG ). We demonstrate that the GAL switch becomes independent of GAL3 by altering the interaction between Gal4p and Gal80p without altering the configuration of UASG . In addition to the above, the altered switch of S. cerevisiae loses ultrasensitivity and stringent glucose repression. These changes caused an increase in fitness in the disaccharide melibiose at the expense of a decrease in fitness in galactose. The above altered features of the ScGAL switch are similar to the features of the GAL switch of K. lactis that diverged from S. cerevisiae before the WGD.

Self-association of the Gal4 inhibitor protein Gal80 is impaired by Gal3: evidence for a new mechanism in the GAL gene switch

The DNA-binding transcriptional activator Gal4 and its regulators Gal80 and Gal3 constitute a galactose-responsive switch for the GAL genes of Saccharomyces cerevisiae. Gal4 binds to GAL gene UASGAL (upstream activation sequence in GAL gene promoter) sites as a dimer via its N-terminal domain and activates transcription via a C-terminal transcription activation domain (AD). In the absence of galactose, a Gal80 dimer binds to a dimer of Gal4, masking the Gal4AD. Galactose triggers Gal3-Gal80 interaction to rapidly initiate Gal4-mediated transcription activation. Just how Gal3 alters Gal80 to relieve Gal80 inhibition of Gal4 has been unknown, but previous analyses of Gal80 mutants suggested a possible competition between Gal3-Gal80 and Gal80 self-association interactions. Here we assayed Gal80-Gal80 interactions and tested for effects of Gal3. Immunoprecipitation, cross-linking, and denaturing and native PAGE analyses of Gal80 in vitro and fluorescence imaging of Gal80 in live cells show that Gal3-Gal80 interaction occurs concomitantly with a decrease in Gal80 multimers. Consistent with this, we find that newly discovered nuclear clusters of Gal80 dissipate in response to galactose-triggered Gal3-Gal80 interaction. We discuss the effect of Gal3 on the quaternary structure of Gal80 in light of the evidence pointing to multimeric Gal80 as the form required to inhibit Gal4.

Regulations of sugar transporters: insights from yeast

Transport across the plasma membrane is the first step at which nutrient supply is tightly regulated in response to intracellular needs and often also rapidly changing external environment. In this review, I describe primarily our current understanding of multiple interconnected glucose-sensing systems and signal-transduction pathways that ensure fast and optimum expression of genes encoding hexose transporters in three yeast species, Saccharomyces cerevisiae, Kluyveromyces lactis and Candida albicans. In addition, an overview of GAL- and MAL-specific regulatory networks, controlling galactose and maltose utilization, is provided. Finally, pathways generating signals inducing posttranslational degradation of sugar transporters will be highlighted.

Drosophila heparan sulfate 6-O-endosulfatase Sulf1 facilitates wingless (Wg) protein degradation

Heparan sulfate proteoglycans regulate various physiological and developmental processes through interactions with a number of protein ligands. Heparan sulfate (HS)-ligand binding depends on the amount and patterns of sulfate groups on HS, which are controlled by various HS sulfotransferases in the Golgi apparatus as well as extracellular 6-O-endosulfatases called "Sulfs." Sulfs are a family of secreted molecules that specifically remove 6-O-sulfate groups within the highly sulfated regions on HS. Vertebrate Sulfs promote Wnt signaling, whereas the only Drosophila homologue of Sulfs, Sulf1, negatively regulates Wingless (Wg) signaling. To understand the molecular mechanism for the negative regulation of Wg signaling by Sulf1, we studied the effects of Sulf1 on HS-Wg interaction and Wg stability. Sulf1 overexpression strongly inhibited the binding of Wg to Dally, a potential target heparan sulfate proteoglycan of Sulf1. This effect of Drosophila Sulf1 on the HS-Wg interaction is similar to that of vertebrate Sulfs. Using in vitro, in vivo, and ex vivo systems, we show that Sulf1 reduces extracellular Wg protein levels, at least partly by facilitating Wg degradation. In addition, expression of human Sulf1 in the Drosophila wing disc lowers the levels of extracellular Wg protein, as observed for Drosophila Sulf1. Our study demonstrates that vertebrate and Drosophila Sulfs have an intrinsically similar activity and that the function of Sulfs in the fate of Wnt/Wg ligands is context-dependent.

Growth-related model of the GAL system in Saccharomyces cerevisiae predicts behaviour of several mutant strains

The genetic regulatory network responds dynamically to perturbations in the intracellular and extracellular environments of an organism. The GAL system in the yeast Saccharomyces cerevisiae has evolved to utilise galactose as an alternative carbon and energy source, in the absence of glucose in the environment. This work contains a modified dynamic model for GAL system in S. cerevisiae, which includes a novel mechanism for Gal3p activation upon induction with galactose. The modification enables the model to simulate the experimental observation that in absence of galactose, oversynthesis of Gal3p can also induce the GAL system. Subsequently, the model is related to growth on galactose and glucose in a structured manner. The growth-related models are validated with experimental data for growth on individual substrates as well as mixed substrates. Finally, the model is tested for its prediction of a variety of known mutant behaviours. The exercise shows that the authors' model with a single set of parameters is able to capture the rich behaviour of the GAL system in S. cerevisiae. [Includes supplementary material].

Structural bistability of the GAL regulatory network and characterization of its domains of attraction

Bistability is a system-level property, exploited by many biomolecular interaction networks as a key mechanism to accomplish different cellular functions (e.g., differentiation, cell cycle, switch-like response to external stimuli). Bistability has also been experimentally found to occur in the regulatory network of the galactose metabolic pathway in the model organism Saccharomyces cerevisiae. In this yeast, bistability generates a persistent memory of the type of carbon source available in the extracellular medium: under the same experimental conditions, cells previously grown with different nutrients generate different responses and get stably locked into two distinct steady states. The molecular interactions of the GAL regulatory network have been thoroughly dissected through wet-lab experiments; thus, this system provides a formidable benchmark to our ability to characterize and reproduce in silico the behavior of bistable biological systems. To this aim, a number of models have been proposed in the literature; however, we found that they are not able to replicate the persistent memory behavior observed in (Acar et al., 2005 ). The present study proposes a novel model of the GAL regulatory network, which, in addition to reproducing in silico the experimental findings, can be formally analyzed for structural multistability of the network, using chemical reaction network theory (CRNT), and allows the characterization of the domains of attraction (DA). This work provides further insights into the GAL system and proposes an easily generalizable approach to the study of bistability-associated behaviors in biological systems.

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit.

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.

Rapid GAL gene switch of Saccharomyces cerevisiae depends on nuclear Gal3, not nucleocytoplasmic trafficking of Gal3 and Gal80

The yeast transcriptional activator Gal4 localizes to UAS(GAL) sites even in the absence of galactose but cannot activate transcription due to an association with the Gal80 protein. By 4 min after galactose addition, Gal4-activated gene transcription ensues. It is well established that this rapid induction arises through a galactose-triggered association between the Gal80 and Gal3 proteins that decreases the association of Gal80 and Gal4. How this happens mechanistically remains unclear. Strikingly different hypotheses prevail concerning the possible roles of nucleocytoplasmic distribution and trafficking of Gal3 and Gal80 and where in the cell the initial Gal3-Gal80 association occurs. Here we tested two conflicting hypotheses by evaluating the subcellular distribution and dynamics of Gal3 and Gal80 with reference to induction kinetics. We determined that the rates of nucleocytoplasmic trafficking for both Gal80 and Gal3 are slow relative to the rate of induction. We find that depletion of the nuclear pool of Gal3 slows the induction kinetics. Thus, nuclear Gal3 is critical for rapid induction. Fluorescence-recovery-after-photobleaching experiments provided data suggesting that the Gal80-Gal4 complex exhibits kinetic stability in the absence of galactose. Finally, we detect Gal3 at the UAS(GAL) only if Gal80 is covalently linked to the DNA-binding domain. Taken altogether, these new findings lead us to propose that a transient interaction of Gal3 with Gal4-associated Gal80 could explain the rapid response of this system. This notion could also explain earlier observations.

Modeling the evolution of a classic genetic switch

Background

The regulatory network underlying the yeast galactose-use pathway has emerged as a model system for the study of regulatory network evolution. Evidence has recently been provided for adaptive evolution in this network following a whole genome duplication event. An ancestral gene encoding a bi-functional galactokinase and co-inducer protein molecule has become subfunctionalized as paralogous genes (GAL1 and GAL3) in Saccharomyces cerevisiae, with most fitness gains being attributable to changes in cis-regulatory elements. However, the quantitative functional implications of the evolutionary changes in this regulatory network remain unexplored.

Results

We develop a modeling framework to examine the evolution of the GAL regulatory network. This enables us to translate molecular changes in the regulatory network to changes in quantitative network function. We computationally reconstruct an inferred ancestral version of the network and trace the evolutionary paths in the lineage leading to S. cerevisiae. We explore the evolutionary landscape of possible regulatory networks and find that the operation of intermediate networks leading to S. cerevisiae differs substantially depending on the order in which evolutionary changes accumulate; in particular, we systematically explore evolutionary paths and find that some network features cannot be optimized simultaneously.

Conclusions

We find that a computational modeling approach can be used to analyze the evolution of a well-studied regulatory network. Our results are consistent with several experimental studies of the evolutionary of the GAL regulatory network, including increased fitness in Saccharomyces due to duplication and adaptive regulatory divergence. The conceptual and computational tools that we have developed may be applicable in further studies of regulatory network evolution.

New insights into galactose metabolism by Schizosaccharomyces pombe: isolation and characterization of a galactose-assimilating mutant

The fission yeast Schizosaccharomyces pombe cannot use galactose as a carbon or energy source, and little is known about galactose metabolism in this species. Here we report isolation of a galactose-assimilating mutant that grows on a medium containing galactose as a sole carbon source through use of a proofreading-deficient DNA polymerase δ variant encoded by cdc6-1. Based on comparative analysis of gene expression profiles in the wild-type and the mutant (FG2-8), we found that SPBPB2B2.10c (gal7+), SPBPB2B2.12c (gal10+) and SPBPB2B2.13 (gal1+), homologous to Saccharomyces cerevisiae GAL7, GAL10 and GAL1, respectively, and SPBPB2B2.08, SPBPB2B2.09c, and SPBPB2B2.11 that localize close to the gal genes, were highly expressed and dramatically induced by addition of galactose. The gal7Δ strain, carrying an integrated ura4+ marker at the gal7+ locus, grew on 5-fluoroorotic acid (5-FOA)-containing medium. In contrast, the FG2-8 gal7Δ strain could not grow on 5-FOA medium. In addition, expression of gal7+, SPBPB2B2.13, gal10+ and gal1+ genes increased in the wild-type strain when carried on a vector, and these transformants grew on galactose medium. We suggest that gal7+, gal10+, and gal1+ are localized close to a chromosomal terminal repressed by gene silencing in S. pombe. In contrast, gene silencing was defective in the FG2-8 strain making galactose assimilation possible.

A general mechanism for network-dosage compensation in gene circuits

Coping with variations in network dosage is crucial for maintaining optimal function in gene networks. We explored how network structure facilitates network-level dosage compensation. By using the yeast galactose network as a model, we combinatorially deleted one of the two copies of its four regulatory genes and found that network activity was robust to the change in network dosage. A mathematical analysis revealed that a two-component genetic circuit with elements of opposite regulatory activity (activator and inhibitor) constitutes a minimal requirement for network-dosage invariance. Specific interaction topologies and a one-to-one interaction stoichiometry between the activating and inhibiting agents were additional essential elements facilitating dosage invariance. This mechanism of network-dosage invariance could represent a general design for gene network structure in cells.

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.

Gene duplication and the adaptive evolution of a classic genetic switch

How gene duplication and divergence contribute to genetic novelty and adaptation has been of intense interest, but experimental evidence has been limited. The genetic switch controlling the yeast galactose use pathway includes two paralogous genes in Saccharomyces cerevisiae that encode a co-inducer (GAL3) and a galactokinase (GAL1). These paralogues arose from a single bifunctional ancestral gene as is still present in Kluyveromyces lactis. To determine which evolutionary processes shaped the evolution of the two paralogues, here we assess the effects of precise replacement of coding and non-coding sequences on organismal fitness. We suggest that duplication of the ancestral bifunctional gene allowed for the resolution of an adaptive conflict between the transcriptional regulation of the two gene functions. After duplication, previously disfavoured binding site configurations evolved that divided the regulation of the ancestral gene into two specialized genes, one of which ultimately became one of the most tightly regulated genes in the genome.

Combinatorial promoter design for engineering noisy gene expression

Understanding the behavior of basic biomolecular components as parts of larger systems is one of the goals of the developing field of synthetic biology. A multidisciplinary approach, involving mathematical and computational modeling in parallel with experimentation, is often crucial for gaining such insights and improving the efficiency of artificial gene network design. Here we used such an approach and developed a combinatorial promoter design strategy to characterize how the position and multiplicity of tetO(2) operator sites within the GAL1 promoter affect gene expression levels and gene expression noise in Saccharomyces cerevisiae. We observed stronger transcriptional repression and higher gene expression noise as a single operator site was moved closer to the TATA box, whereas for multiple operator-containing promoters, we found that the position and number of operator sites together determined the dose-response curve and gene expression noise. We developed a generic computational model that captured the experimentally observed differences for each of the promoters, and more detailed models to successively predict the behavior of multiple operator-containing promoters from single operator-containing promoters. Our results suggest that the independent binding of single repressors is not sufficient to explain the more complex behavior of the multiple operator-containing promoters. Taken together, our findings highlight the importance of joint experimental-computational efforts and some of the challenges of using a bottom-up approach based on well characterized, isolated biomolecular components for predicting the behavior of complex, synthetic gene networks, e.g., the whole can be different from the sum of its parts.

Desiccation and zinc binding induce transition of tomato abscisic acid stress ripening 1, a water stress- and salt stress-regulated plant-specific protein, from unfolded to folded state

Abscisic acid stress ripening 1 (ASR1) is a low molecular weight plant-specific protein encoded by an abiotic stress-regulated gene. Overexpression of ASR1 in transgenic plants increases their salt tolerance. The ASR1 protein possesses a zinc-dependent DNA-binding activity. The DNA-binding site was mapped to the central part of the polypeptide using truncated forms of the protein. Two additional zinc-binding sites were shown to be localized at the amino terminus of the polypeptide. ASR1 protein is presumed to be an intrinsically unstructured protein using a number of prediction algorithms. The degree of order of ASR1 was determined experimentally using nontagged recombinant protein expressed in Escherichia coli and purified to homogeneity. Purified ASR1 was shown to be unfolded using dynamic light scattering, gel filtration, microcalorimetry, circular dichroism, and Fourier transform infrared spectrometry. The protein was shown to be monomeric by analytical ultracentrifugation. Addition of zinc ions resulted in a global change in ASR1 structure from monomer to homodimer. Upon binding of zinc ions, the protein becomes ordered as shown by Fourier transform infrared spectrometry and microcalorimetry, concomitant with dimerization. Tomato (Solanum lycopersicum) leaf soluble ASR1 is unstructured in the absence of added zinc and gains structure upon binding of the metal ion. The effect of zinc binding on ASR1 folding and dimerization is discussed.

Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements

Background

Many DNA regulatory elements occur as multiple instances within a target promoter. Gibbs sampling programs for finding DNA regulatory elements de novo can be prohibitively slow in locating all instances of such an element in a sequence set.

Results

We describe an improvement to the A-GLAM computer program, which predicts regulatory elements within DNA sequences with Gibbs sampling. The improvement adds an optional "scanning step" after Gibbs sampling. Gibbs sampling produces a position specific scoring matrix (PSSM). The new scanning step resembles an iterative PSI-BLAST search based on the PSSM. First, it assigns an "individual score" to each subsequence of appropriate length within the input sequences using the initial PSSM. Second, it computes an E-value from each individual score, to assess the agreement between the corresponding subsequence and the PSSM. Third, it permits subsequences with E-values falling below a threshold to contribute to the underlying PSSM, which is then updated using the Bayesian calculus. A-GLAM iterates its scanning step to convergence, at which point no new subsequences contribute to the PSSM. After convergence, A-GLAM reports predicted regulatory elements within each sequence in order of increasing E-values, so users have a statistical evaluation of the predicted elements in a convenient presentation. Thus, although the Gibbs sampling step in A-GLAM finds at most one regulatory element per input sequence, the scanning step can now rapidly locate further instances of the element in each sequence.

Conclusion

Datasets from experiments determining the binding sites of transcription factors were used to evaluate the improvement to A-GLAM. Typically, the datasets included several sequences containing multiple instances of a regulatory motif. The improvements to A-GLAM permitted it to predict the multiple instances.

The Galactose Switch in Kluyveromyces lactis Depends on Nuclear Competition between Gal4 and Gal1 for Gal80 Binding

The Gal4 protein represents a universally functional transcription activator, which in yeast is regulated by protein-protein interaction of its transcription activation domain with the inhibitor Gal80. Gal80 inhibition is relieved via galactose-mediated Gal80-Gal1-Gal3 interaction. The Gal4-Gal80-Gal1/3 regulatory module is conserved between Saccharomyces cerevisiae and Kluyveromyces lactis. Here we demonstrate that K. lactis Gal80 (KlGal80) is a nuclear protein independent of the Gal4 activity status, whereas KlGal1 is detected throughout the entire cell, which implies that KlGal80 and KlGal1 interact in the nucleus. Consistently KlGal1 accumulates in the nucleus upon KlGAL80 overexpression. Furthermore, we show that the KlGal80-KlGal1 interaction blocks the galactokinase activity of KlGal1 and is incompatible with KlGal80-KlGal4-AD interaction. Thus, we propose that dissociation of KlGal80 from the AD forms the basis of KlGal4 activation in K. lactis. Quantitation of the dissociation constants for the KlGal80 complexes gives a much lower affinity for KlGal1 as compared with Gal4. Mathematical modeling shows that with these affinities a switch based on competition between Gal1 and Gal4 for Gal80 binding is nevertheless efficient provided two monomeric Gal1 molecules interact with dimeric Gal80. Consistent with such a mechanism, analysis of the sedimentation behavior by analytical ultracentrifugation demonstrates the formation of a heterotetrameric KlGal80-KlGal1 complex of 2:2 stoichiometry.

Biological significance of autoregulation through steady state analysis of genetic networks

Autoregulation of regulatory proteins is a recurring theme in genetic networks. Autoregulation is an important component of a genetic regulatory network besides protein-protein and protein-DNA interactions, stoichiometry, multiple binding sites and cooperativity. Although the biological significance of autoregulation has been studied before, its significance in presence of other mechanisms is not clearly enumerated. We have analyzed at steady state the significance of autoregulation in presence of other molecular mechanisms by considering hypothetical genetic networks. We demonstrate that autoregulation of a regulatory protein can impart amplification to the response. Further, autoregulation of an activator binding to the DNA as a dimer can introduce bistability, thus forcing the system to reside in two distinct steady states. In combination with autoregulation, cooperative binding can further increase the sensitivity and can yield a highly ultrasensitive response. We conclude that autoregulation with the help of other molecular mechanisms can impart distinct system level properties such as amplification, sensitivity and bistability. The results are further discussed in relation to various examples of genetic networks that exist in biological systems.

Effects of different zinc finger transcription factors on genomic targets

We have developed a novel vector system for the efficient assembly of polydactyl zinc fingers. Next to proteins that possess short canonical TGEKP linkers between all constituting zinc fingers we constructed proteins with longer, 12 amino acid linkers between two three-finger (3F) units and between three two-finger (2F) units. Fusions of these zinc finger domains with the VP16 activation domain were tested for their ability to regulate a repressed genomic locus containing contiguous or noncontiguous zinc finger binding sites in yeast. In contrast to other studies, which were mostly confined to in vitro tests, we did not obtain evidence that superior artificial zinc finger transcription factors need to contain longer linkers between individual fingers. For the regulation of genomic loci, canonical linkers within a highly regular backbone in combination with a contiguous 18 base pair DNA target site were found to provide a sound base for polydactyl zinc finger design.

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.

Replacement of a conserved tyrosine by tryptophan in Gal3p of Saccharomyces cerevisiae reduces constitutive activity: implications for signal transduction in the GAL regulon

The ability of Saccharomyces cerevisiae to utilize galactose is regulated by the nucleo-cytoplasmic shuttling of a transcriptional repressor, the Gal80 protein. Gal80 interacts with the transcriptional activator Gal4 in the nucleus and inhibits its function, preventing induction of the GAL genes. In response to galactose, the relative amounts of Gal80 in the cytoplasm and the nucleus are modulated by the action of a signal transducer, Gal3. Although it has been speculated that Gal3 binds galactose, this has not been experimentally demonstrated. In this study, we show that replacement of a conserved tyrosine in Gal3 by tryptophan leads to a reduction of its constitutive activity in the absence of galactose. In addition, this mutant protein was fully functional in vivo only when high concentrations of galactose were present in the medium. When overexpressed, the mutant was found to activate the genes GAL1 and GAL7/10 differentially. The implications of these findings for the fine regulation of GAL genes, and its physiological significance, are discussed.

Contributions of low molecule number and chromosomal positioning to stochastic gene expression

The presence of low-copy-number regulators and switch-like signal propagation in regulatory networks are expected to increase noise in cellular processes. We developed a noise amplifier that detects fluctuations in the level of low-abundance mRNAs in yeast. The observed fluctuations are not due to the low number of molecules expressed from a gene per se but originate in the random, rare events of gene activation. The frequency of these events and the correlation between stochastic expressions of genes in a single cell depend on the positioning of the genes along the chromosomes. Transcriptional regulators produced by such random expression propagate noise to their target genes.

Is the regulation of galactose 1-phosphate tuned against gene expression noise?

The average number of mRNA molecules per active gene in yeast can be remarkably low. Consequently, the relative number of copies of each transcript per cell can vary greatly from moment to moment. When these transcripts are encoding metabolic enzymes, how do the resulting variations in enzyme concentrations affect the regulation of metabolic intermediates? Using a kinetic model of galactose utilization in yeast, we analysed the transmission of noise from transcription and translation on metabolic intermediate regulation. In particular, the effect of the kinetic properties of the galactose-1-phosphate uridylyltransferase reaction on the transmission of noise was analysed.

Mutational hypersensitivity of a gene regulatory protein: Saccharomyces cerevisiae Gal80p

The inhibitor of galactose catabolic (GAL) gene expression in Saccharomyces cerevisiae, Gal80p, interacts with the activator Gal4p and the signal transducer Gal3p and self-associates. Selection for loss of Gal80p inhibitor function yielded gal80 mutants at an extremely high rate. Out of these, 21 nonoverlapping point mutants were identified; each were due to a single-amino-acid exchange in conserved residues. Semiquantitative biochemical analysis of the corresponding mutant proteins revealed that each of the 21 amino acid alterations caused simultaneous defects in every single protein-protein interaction and in Gal80's structural integrity. Thus, Gal80 provides an unprecedented example for a protein's structural sensitivity to minimal sequence alterations.

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.

Steady-state analysis of glucose repression reveals hierarchical expression of proteins under Mig1p control in Saccharomyces cerevisiae

Glucose repression is a global transcriptional regulatory mechanism commonly observed in micro-organisms for the repression of enzymes that are not essential for glucose metabolism. In Saccharomyces cerevisiae, Mig1p, a homologue of Wilms' tumour protein, is a global repressor protein dedicated to glucose repression. Mig1p represses genes either by binding directly to the upstream repression sequence of structural genes or by indirectly repressing a transcriptional activator, such as Gal4p. In addition, some genes are repressed by both of the above mechanisms. This raises a fundamental question regarding the physiological relevance of the varied mechanisms of repression that exist involving Mig1p. We address this issue by comparing two well-known glucose-repression systems, that is, SUC2 and GAL gene expression systems, which encompass all the above three mechanisms. We demonstrate using steady-state analysis that these mechanisms lead to a hierarchical glucose repression profile of different family of genes. This switch over from one carbon source to another is well-calibrated as a function of glucose concentration through this hierarchical transcriptional response. The mechanisms prevailing in this repression system can achieve amplification and sensitivity, as observed in the well-characterized MAPK (mitogen-activated protein kinase) cascade system, albeit through a different structure. A critical feature of repression predicted by our steady-state model for the mutant strain of S. cerevisiae lacking Gal80p agrees well with the data reported here as well as that available in the literature.

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

In Saccharomyces cerevisiae, a recessive mutation in the signal transducer encoded by GAL3 leads to a significant lag in the induction of GAL genes, referred to as long term adaptation phenotype (LTA). Further, gal3 mutation in combination with other genetic defects leads to the non-inducibility of GAL genes. It was shown that the expression of GAL1 encoded galactokinase, a redundant GAL3 like signal transducer, eventually substitutes for the lack of GAL3 signal transduction function. However, how GAL1 gets induced in the absence of GAL3 is not clear. We hypothesize that GAL1 induction in gal3 cells exposed to galactose is due to a stochastic decrease in the repressor, Gal80p concentration, leading to heterogeneity in the population. This observation explains not only LTA observed in gal3 cells but also explains the non-inducibility of gal3 mutants in combination with other genetic defects. By recruiting a dedicated signal transducer, GAL3, S. cerevisiae GAL switch has evolved to overcome the fortuitous induction, which occurs due to low signal to noise ratio in certain mutants of Escherichia coli and Kluveromyces lactis.

Refining GAL4-driven transgene expression in Drosophila with a GAL80 enhancer-trap

We constructed an enhancer-trap element, P[GAL80], that encodes the yeast GAL80 repressor to refine expression of transgenes driven by the binary GAL4/UAS system. GAL80 blocks GAL4 activity by binding to its transcriptional activation domain. We screened GAL80 enhancer-traps for repression of GAL4-induced green fluorescent protein (GFP) in the intact larval nervous system. We selected one line that repressed GFP in a large set of cholinergic neurons. This line was used to refine GFP expression from a set of over 200 neurons to a subset of 20 neurons in a preselected GAL4 line. Expression of tetanus neurotoxin, a potent blocker of neurotransmitter release, in these 20 neurons reproduced an aberrant larval turning behavior previously assigned to the parental set of 200 neurons. Our results suggest that targeted GAL80 expression could become a useful means of spatially refining transgene expression in Drosophila.

Parallel, quantitative measurement of protein binding to a 120-element double-stranded DNA array in real time using surface plasmon resonance microscopy

Quantitative, real-time measurement of kinetics of sequence-specific binding of DNA-binding proteins to double-stranded DNA (dsDNA) immobilized in a 10 x 12 array on a planar gold surface is demonstrated using surface plasmon resonance (SPR) microscopy. This binding of the yeast transcription factor Gal4 to a 120-spot dsDNA array made with alternating 200-microm spots of its dsDNA operator sequence and an unrelated DNA sequence proves that this method could be used to simultaneously monitor the kinetics of binding of proteins to 120 different dsDNA sequences with a sensitivity to approximately 0.5 pg (<2 x 10(7) molecules) of bound protein in each array spot at a time resolution of 1 s. The method is label free and also allows absolute quantitative determination of the binding stoichiometry (i.e., the number of proteins bound per dsDNA) at each time. The dsDNA array was fabricated using a robotic microspotting system to deliver nanoliter droplets of biotinylated dsDNA solutions onto a streptavidin linker layer immobilized with biotinylated alkylthiols on a thin gold film. Simultaneous monitoring of binding to the many array elements allows the use of reference spots (i.e., array elements with unrelated dsDNA sequences) to correct the signal for nonspecific protein-DNA binding and changes in bulk refractive index of the solutions in the SPR microscope's flow cell. This allows high-throughput analyses of the kinetics and equilibrium of protein-dsDNA binding.

Gal80 dimerization and the yeast GAL gene switch

The Saccharomyces cerevisiae Gal80 protein has two binding partners: Gal4 and Gal3. In the absence of galactose, Gal80 binds to and inhibits the transcriptional activation domain (AD) of the GAL gene activator, Gal4, preventing GAL gene expression. Galactose triggers an association between Gal3 and Gal80, relieving Gal80 inhibition of Gal4. We selected for GAL80 mutants with impaired capacity of Gal80 to bind to Gal3 or Gal4AD. Most Gal80 variants selected for impaired binding to Gal4AD retained their capacity to bind to Gal3 and to self-associate, whereas most of those selected for impaired binding to Gal3 lost their ability to bind to Gal4AD and self-associate. Thus, some Gal80 amino acids are determinants for both the Gal80-Gal3 association and the Gal80 self-association, and Gal80 self-association may be required for binding to Gal4AD. We propose that the binding of Gal3 to the Gal80 monomer competes with Gal80 self-association, reducing the amount of the Gal80 dimer available for inhibition of Gal4.

A steady-state modeling approach to validate an in vivo mechanism of the GAL regulatory network in Saccharomyces cerevisiae

Cellular regulation is a result of complex interactions arising from DNA-protein and protein-protein binding, autoregulation, and compartmentalization and shuttling of regulatory proteins. Experiments in molecular biology have identified these mechanisms recruited by a regulatory network. Mathematical models may be used to complement the knowledge-base provided by in vitro experimental methods. Interactions identified by in vitro experiments can lead to the hypothesis of multiple candidate models explaining the in vivo mechanism. The equilibrium dissociation constants for the various interactions and the total component concentration constitute constraints on the candidate models. In this work, we identify the most plausible in vivo network by comparing the output response to the experimental data. We demonstrate the methodology using the GAL system of Saccharomyces cerevisiae for which the steady-state analysis reveals that Gal3p neither dimerizes nor shuttles between the cytoplasm and the nucleus.

Parallel inactivation of multiple GAL pathway genes and ecological diversification in yeasts

Understanding the evolutionary relationship between genome content and ecological niche is one of the fundamental challenges of biology. The distinct physiologies of yeast species provide a window into how genomes evolve in concert with niche. Although the enzymes of the well studied yeast galactose utilization pathway are present in all domains of life, we have found that multiple genes of the GAL pathway are absent from four yeast species that cannot use galactose. Whereas three species lack any trace of the pathway except a single gene, Saccharomyces kudriavzevii, a close relative of Saccharomyces cerevisiae, retains remnants of all seven dedicated GAL genes as syntenic pseudogenes, providing a rare glimpse of an entire pathway in the process of degeneration. An estimate of the timing of gene inactivation suggests that pathway degeneration began early in the lineage and proceeded rapidly. S. kudriavzevii exhibits several other divergent physiological properties that are associated with a shift in ecological niche. These results suggest that rapid and irreversible gene inactivation and pathway degeneration are associated with adaptation to new ecological niches in natural populations. Inactivated genes may generally serve as markers of specific functions made dispensable by recent adaptive shifts.

Using oxidative crosslinking and proximity labeling to quantitatively characterize protein-protein and protein-Peptide complexes

The quantitative analysis of protein-protein and protein-peptide complexes is of fundamental importance in biochemistry. We report here that nickel-catalyzed proximity biotinylation and Ru(II)(bpy)(3)(2+)-mediated oxidative crosslinking can be used to measure the equilibrium dissociation constant and stoichiometry of protein complexes. Only small amounts of protein are required, neither of the binding partners must be immobilized on a surface, and no special instrumentation is necessary. This chemistry should provide a useful complement to existing methods for the analysis of protein-protein and protein-peptide interactions.

Autoregulation of regulatory proteins is key for dynamic operation ofGALswitch inSaccharomyces cerevisiae

Autoregulation and nucleocytoplasmic shuttling play important roles in the operation of the GAL regulatory system. However, the significance of these mechanisms in the overall operation of the switch is unclear. In this work, we develop a dynamic model for the GAL system and further validate the same using steady-state and dynamic experimental expression data. Next, the model is used to delineate the relevance of shuttling and autoregulation in response to inducing, repressing, and non-inducing-non-repressing media. The analysis indicates that autoregulation of the repressor, Gal80p, is key in obtaining three distinct steady states in response to the three media. In particular, the analysis rationalizes the intuitively paradoxical observation that the concentration of repressor, Gal80p, actually increases in response to an increase in the inducer concentration. On the other hand, although nucleocytoplasmic shuttling does not affect the dynamics of the system, it plays a dominant role in obtaining a sensitive response to galactose. The dynamic model was also used to obtain insights on the preculturing effect on the system behavior.

Quantitative Analysis of GAL Genetic Switch of Saccharomyces cerevisiae Reveals That Nucleocytoplasmic Shuttling of Gal80p Results in a Highly Sensitive Response to Galactose

The nucleocytoplasmic shuttling of the repressor Gal80p is known to play a pivotal role in the signal transduction process of GAL genetic switch of Saccharomyces cerevisiae (Peng, G., and Hopper, J. E. (2002) Proc. Natl. Acad. Sci. U. S. A. 99, 8548-8553). We have developed a comprehensive model of this GAL switch to quantify the expression from the GAL promoter containing one or two Gal4p-binding sites and to understand the biological significance of the shuttling process. Our experiments show that the expression of proteins from the GAL promoter containing one and two binding sites for Gal4p is ultrasensitive (a steep response to a given input). Furthermore, the model revealed that the shuttling of Gal80p is the key step in imparting ultrasensitive response to the inducer. During induction, free Gal80p concentration is altered by sequestration, without any change in the distribution coefficient across the nuclear membrane. Furthermore, the estimated concentrations of Gal80p and Gal3p allow basal expression of alpha-galactosidase, but not beta-galactosidase, from the GAL promoter containing one and two binding sites for Gal4p, respectively. Conversely, the expression from genes with two binding sites is more sensitive to inducer concentration as compared with one binding site. We show that autoregulation of Gal80p is coincidental to the autoregulation of Gal3p, and it does not impart ultrasensitivity. We conclude from our analysis that the ultrasensitivity of the GAL genetic switch is solely because of the shuttling phenomena of the repressor Gal80p across the nuclear membrane.