Cellular noise suppression by the regulator of G protein signaling Sst2

Cascaded amplifying circuit enables sensitive detection of fungal pathogens

The rapid and accurate detection of fungal pathogens is of utmost importance in the fields of healthcare, food safety, and environmental monitoring. In this study, we implemented a cascaded amplifying circuit in Saccharomyces cerevisiae to improve the G protein-coupled receptor (GPCR) mediated fungal detection. The GPCR signaling pathway was coupled with the galactose-regulated (GAL) system and a positive feedback loop was implemented to enhance the performance of yeast biosensor. We systematically compared four generations of biosensors for detecting the mating pheromone of Candida albicans, and the best biosensor exhibited the limit of detection (LOD) as low as 0.25 pM and the limit of quantification (LOQ) of 1 pM after 2 h incubation. Subsequently, we developed a betaxanthin-based colorimetric module for the easy visualization of signal outputs, and the resulting biosensors can give reliable naked-eye readouts. In summary, we demonstrated that cascaded amplifying circuits could substantially improve the engineered yeast biosensors with a better sensitivity and signal output magnitude, which will pave the way for their real-world applications in public health.

Design patterns of biological cells

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

Reshaping the yeast galactose regulon via GPCR signaling cascade

Dynamically regulated systems are preferable to control metabolic pathways for an improved strain performance with better productivity. Here, we harnessed to the G protein-coupled receptor (GPCR) signaling pathway to reshape the yeast galactose regulon. The galactose-regulated (GAL) system was coupled with the GPCR signaling pathway for mating pheromone via a synthetic transcription factor. In this study, we refabricated the dynamic range, sensitivity, and response time of the GAL system to α factor by modulating the key components of the GPCR signaling cascade. A series of engineered yeasts with self-secretion of α factor were constructed to achieve quorum-sensing behaviors. In addition, we also repurposed the GAL system to make it responsive to heat shock. Taken together, our work showcases the great potential of synthetic biology in creating user-defined metabolic controls. We envision that the plasticity of our genetic design would be of significant interest for the future fabrication of novel gene expression systems.

The G-alpha Gpa1 directs septin localization in the mating projection of Saccharomyces cerevisiae through its Ubiquitination Domain and Endocytic Machinery

The yeast mating response uses a G-protein coupled receptor (GPCR), Ste2, to detect mating pheromone and initiate mating projection morphogenesis. The septin cytoskeleton plays a key role in the formation of the mating projection, forming structures at the base of the projection. Desensitization of the Gα, Gpa1, by the Regulator of G-protein Signaling (RGS), Sst2, is required for proper septin organization and morphogenesis. In cells where the Gα is hyperactive, septins are mislocalized to the site of polarity, and the cells are unable to track a pheromone gradient. We set out to identify the proteins that mediate Gα control of septins during the Saccharomyces cerevisiae mating response by making mutations to rescue septin localization in cells expressing the hyperactive Gα mutant gpa1G302S. We found that single deletions of the septin chaperone Gic1, the Cdc42 GAP Bem3, and the epsins Ent1 and Ent2 rescued the polar cap accumulation of septins in the hyperactive Gα. We created an agent-based model of vesicle trafficking that predicts how changes in endocytic cargo licensing alters localization of endocytosis that mirrors the septin localization we see experimentally. We hypothesized that hyperactive Gα may increase the rate of endocytosis of a pheromone responsive cargo, thereby altering where septins are localized. Both the GPCR and the Gα are known to be internalized by clathrin-mediated endocytosis during the pheromone response. Deletion of the GPCR C-terminus to block internalization partially rescued septin organization. However, deletion of the Gpa1 ubiquitination domain required for its endocytosis completely abrogated septin accumulation at the polarity site. Our data support a model where the location of endocytosis serves as a spatial mark for septin structure assembly and that desensitization of the Gα delays its endocytosis sufficiently that septins are placed peripheral to the site of Cdc42 polarity.

Phosphorylation of RGS regulates MAP kinase localization and promotes completion of cytokinesis

Phosphorylation of the RGS Sst2 alters its subcellular distribution, MAPK localization, and interaction with Kel1, which promotes coordination of polarized growth with completion of cytokinesis.

Yeast use the G-protein–coupled receptor signaling pathway to detect and track the mating pheromone. The G-protein–coupled receptor pathway is inhibited by the regulator of G-protein signaling (RGS) Sst2 which induces Gα GTPase activity and inactivation of downstream signaling. G-protein signaling activates the MAPK Fus3, which phosphorylates the RGS; however, the role of this modification is unknown. We found that pheromone-induced RGS phosphorylation peaks early; the phospho-state of RGS controls its localization and influences MAPK spatial distribution. Surprisingly, phosphorylation of the RGS promotes completion of cytokinesis before pheromone-induced growth. Completion of cytokinesis in the presence of pheromone is promoted by the kelch-repeat protein, Kel1 and antagonized by the formin Bni1. We found that RGS complexes with Kel1 and prefers the unphosphorylatable RGS mutant. We also found overexpression of unphosphorylatable RGS exacerbates cytokinetic defects, whereas they are rescued by overexpression of Kel1. These data lead us to a model where Kel1 promotes completion of cytokinesis before pheromone-induced polarity but is inhibited by unphosphorylated RGS binding.

Analysis of the pheromone signaling pathway by RT-qPCR in the budding yeast Saccharomyces cerevisiae

FUS3 and STE2 expression levels can be used as reporters for signaling through the pheromone pathway in the budding yeast Saccharomyces cerevisiae. Here, we describe an optimized protocol to measure the expression levels of FUS3 and STE2 using quantitative reverse transcription PCR (RT-qPCR). We describe the steps for comparing untreated and pheromone-treated yeast cells and how to quantify the changes in various deletion strains. The protocol can be applied to determine potential regulators of the pheromone pathway.

For complete details on the use and execution of this protocol, please refer to Garcia et al. (2021).

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Optimized procedure to measure the activity of the mating pathway in S. cerevisiae

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Describes growth conditions in presence or absence of alpha mating factor

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Use of RT-qPCR to quantify the expression of mating pathway genes

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Can be used to reveal potential regulators of the pheromone signaling pathway

Kel1 is a phosphorylation-regulated noise suppressor of the pheromone signaling pathway

Mechanisms have evolved that allow cells to detect signals and generate an appropriate response. The accuracy of these responses relies on the ability of cells to discriminate between signal and noise. How cells filter noise in signaling pathways is not well understood. Here, we analyze noise suppression in the yeast pheromone signaling pathway and show that the poorly characterized protein Kel1 serves as a major noise suppressor and prevents cell death. At the molecular level, Kel1 prevents spontaneous activation of the pheromone response by inhibiting membrane recruitment of Ste5 and Far1. Only a hypophosphorylated form of Kel1 suppresses signaling, reduces noise, and prevents pheromone-associated cell death, and our data indicate that the MAPK Fus3 contributes to Kel1 phosphorylation. Taken together, Kel1 serves as a phospho-regulated suppressor of the pheromone pathway to reduce noise, inhibit spontaneous activation of the pathway, regulate mating efficiency, and prevent pheromone-associated cell death.

Gradient Tracking by Yeast GPCRs in a Microfluidics Chamber

Cells typically exist in a highly dynamic environment, which cannot easily be recreated in culture dishes or microwell plates. Microfluidic devices can provide precise control of the time, dose, and orientation of a stimulus, while simultaneously capturing quantitative single-cell data. The approach is particularly powerful when combined with the genetically tractable yeast model organism. The GPCR pathway in yeast is structurally conserved and functionally interchangeable with those in humans. We describe the implementation of a microfluidic device to investigate morphological and transcriptional responses of yeast to a gradient or pulse administration of a GPCR ligand, the peptide mating pheromone α-factor.

A predictive model of gene expression reveals the role of network motifs in the mating response of yeast

Cells use signaling pathways to receive and process information about their environment. These nonlinear systems rely on feedback and feedforward regulation to respond appropriately to changing environmental conditions. Mathematical models describing signaling pathways often lack predictive power because they are not trained on data that encompass the diverse time scales on which these regulatory mechanisms operate. We addressed this limitation by measuring transcriptional changes induced by the mating response in Saccharomyces cerevisiae exposed to different dynamic patterns of pheromone. We found that pheromone-induced transcription persisted after pheromone removal and showed long-term adaptation upon sustained pheromone exposure. We developed a model of the regulatory network that captured both characteristics of the mating response. We fit this model to experimental data with an evolutionary algorithm and used the parameterized model to predict scenarios for which it was not trained, including different temporal stimulus profiles and genetic perturbations to pathway components. Our model allowed us to establish the role of four architectural elements of the network in regulating gene expression. These network motifs are incoherent feedforward, positive feedback, negative feedback, and repressor binding. Experimental and computational perturbations to these network motifs established a specific role for each in coordinating the mating response to persistent and dynamic stimulation.

Design of a MAPK signalling cascade balances energetic cost versus accuracy of information transmission

Cellular processes are inherently noisy, and the selection for accurate responses in presence of noise has likely shaped signalling networks. Here, we investigate the trade-off between accuracy of information transmission and its energetic cost for a mitogen-activated protein kinase (MAPK) signalling cascade. Our analysis of the pheromone response pathway of budding yeast suggests that dose-dependent induction of the negative transcriptional feedbacks in this network maximizes the information per unit energetic cost, rather than the information transmission capacity itself. We further demonstrate that futile cycling of MAPK phosphorylation and dephosphorylation has a measurable effect on growth fitness, with energy dissipation within the signalling cascade thus likely being subject to evolutionary selection. Considering optimization of accuracy versus the energetic cost of information processing, a concept well established in physics and engineering, may thus offer a general framework to understand the regulatory design of cellular signalling systems.

Cellular signalling networks provide information to the cell, but the trade-off between accuracy of information transfer and energetic cost of doing so has not been assessed. Here, the authors investigate a MAPK signalling cascade in budding yeast and find that information is maximised per unit energetic cost.

Mating yeast cells use an intrinsic polarity site to assemble a pheromone-gradient tracking machine

The mating of budding yeast depends on chemotropism, a fundamental cellular process. The two yeast mating types secrete peptide pheromones that bind to GPCRs on cells of the opposite type. Cells find and contact a partner by determining the direction of the pheromone source and polarizing their growth toward it. Actin-directed secretion to the chemotropic growth site (CS) generates a mating projection. When pheromone-stimulated cells are unable to sense a gradient, they form mating projections where they would have budded in the next cell cycle, at a position called the default polarity site (DS). Numerous models have been proposed to explain yeast gradient sensing, but none address how cells reliably switch from the intrinsically determined DS to the gradient-aligned CS, despite a weak spatial signal. Here we demonstrate that, in mating cells, the initially uniform receptor and G protein first polarize to the DS, then redistribute along the plasma membrane until they reach the CS. Our data indicate that signaling, polarity, and trafficking proteins localize to the DS during assembly of what we call the gradient tracking machine (GTM). Differential activation of the receptor triggers feedback mechanisms that bias exocytosis upgradient and endocytosis downgradient, thus enabling redistribution of the GTM toward the pheromone source. The GTM stabilizes when the receptor peak centers at the CS and the endocytic machinery surrounds it. A computational model simulates GTM tracking and stabilization and correctly predicts that its assembly at a single site contributes to mating fidelity.

Systematic analysis of F-box proteins reveals a new branch of the yeast mating pathway

The mating pathway in yeast Saccharomyces cerevisiae has long been used to reveal new mechanisms of signal transduction. The pathway comprises a pheromone receptor, a heterotrimeric G protein, and intracellular effectors of morphogenesis and transcription. Polarized cell growth, in the direction of a potential mating partner, is accomplished by the G-protein βγ subunits and the small G-protein Cdc42. Transcription induction, needed for cell-cell fusion, is mediated by Gβγ and the mitogen-activated protein kinase (MAPK) scaffold protein Ste5. A potential third pathway is initiated by the G-protein α subunit Gpa1. Gpa1 signaling was shown previously to involve the F-box adaptor protein Dia2 and an endosomal effector protein, the phosphatidylinositol 3-kinase Vps34. Vps34 is also required for proper vacuolar sorting and autophagy. Here, using a panel of reporter assays, we demonstrate that mating pheromone stimulates vacuolar targeting of a cytoplasmic reporter protein and that this process depends on Vps34. Through a systematic analysis of F-box deletion mutants, we show that Dia2 is required to sustain pheromone-induced vacuolar targeting. We also found that other F-box proteins selectively regulate morphogenesis (Ydr306, renamed Pfu1) and transcription (Ucc1). These findings point to the existence of a new and distinct branch of the pheromone-signaling pathway, one that likely leads to vacuolar engulfment of cytoplasmic proteins and recycling of cellular contents in preparation for mating.

Quantitative analysis of the yeast pheromone pathway

The pheromone response pathway of the yeast Saccharomyces cerevisiae is a well-established model for the study of G proteins and mitogen-activated protein kinase (MAPK) cascades. Our longstanding ability to combine sophisticated genetic approaches with established functional assays has provided a thorough understanding of signalling mechanisms and regulation. In this report, we compare new and established methods used to quantify pheromone-dependent MAPK phosphorylation, transcriptional induction, mating morphogenesis, and gradient tracking. These include both single-cell and population-based assays of activity. We describe several technical advances, provide example data for benchmark mutants, highlight important differences between newer and established methodologies, and compare the advantages and disadvantages of each as applied to the yeast model. Quantitative measurements of pathway activity have been used to develop mathematical models and reveal new regulatory mechanisms in yeast. It is our expectation that experimental and computational approaches developed in yeast may eventually be adapted to human systems biology and pharmacology.

A System for Gene Expression Noise Control in Yeast

Gene expression noise arises from stochastic variation in the synthesis and degradation of mRNA and protein molecules and creates differences in protein numbers across populations of genetically identical cells. Such variability can lead to imprecision and reduced performance of both native and synthetic networks. In principle, gene expression noise can be controlled through the rates of transcription, translation and degradation, such that different combinations of those rates lead to the same protein concentrations but at different noise levels. Here, we present a "noise tuner" which allows orthogonal control over the transcription and the mRNA degradation rates by two different inducer molecules. Combining experiments with theoretical analysis, we show that in this system the noise is largely determined by the transcription rate, whereas the mean expression is determined by both the transcription rate and mRNA stability and can thus be decoupled from the noise. This noise tuner enables 2-fold changes in gene expression noise over a 5-fold range of mean protein levels. We demonstrated the efficacy of the noise tuner in a complex regulatory network by varying gene expression noise in the mating pathway of Saccharomyces cerevisiae, which allowed us to control the output noise and the mutual information transduced through the pathway. The noise tuner thus represents an effective tool of gene expression noise control, both to interrogate noise sensitivity of natural networks and enhance performance of synthetic circuits.

Real-Time Genetic Compensation Defines the Dynamic Demands of Feedback Control

Biological signaling networks use feedback control to dynamically adjust their operation in real time. Traditional static genetic methods such as gene knockouts or rescue experiments can often identify the existence of feedback interactions but are unable to determine what feedback dynamics are required. Here, we implement a new strategy, closed-loop optogenetic compensation (CLOC), to address this problem. Using a custom-built hardware and software infrastructure, CLOC monitors, in real time, the output of a pathway deleted for a feedback regulator. A minimal model uses these measurements to calculate and deliver-on the fly-an optogenetically enabled transcriptional input designed to compensate for the effects of the feedback deletion. Application of CLOC to the yeast pheromone response pathway revealed surprisingly distinct dynamic requirements for three well-studied feedback regulators. CLOC, a marriage of control theory and traditional genetics, presents a broadly applicable methodology for defining the dynamic function of biological feedback regulators.

Mitogen-activated protein kinase (MAPK) dynamics determine cell fate in the yeast mating response

In the yeast Saccharomyces cerevisiae, the exposure to mating pheromone activates a prototypic mitogen-activated protein kinase (MAPK) cascade and triggers a dose-dependent differentiation response. Whereas a high pheromone dose induces growth arrest and formation of a shmoo-like morphology in yeast cells, lower pheromone doses elicit elongated cell growth. Previous population-level analysis has revealed that the MAPK Fus3 plays an important role in mediating this differentiation switch. To further investigate how Fus3 controls the fate decision process at the single-cell level, we developed a specific translocation-based reporter for monitoring Fus3 activity in individual live cells. Using this reporter, we observed strikingly different dynamic patterns of Fus3 activation in single cells differentiated into distinct fates. Cells committed to growth arrest and shmoo formation exhibited sustained Fus3 activation. In contrast, most cells undergoing elongated growth showed either a delayed gradual increase or pulsatile dynamics of Fus3 activity. Furthermore, we found that chemically perturbing Fus3 dynamics with a specific inhibitor could effectively redirect the mating differentiation, confirming the causative role of Fus3 dynamics in driving cell fate decisions. MAPKs mediate proliferation and differentiation signals in mammals and are therapeutic targets in many cancers. Our results highlight the importance of MAPK dynamics in regulating single-cell responses and open up the possibility that MAPK signaling dynamics could be a pharmacological target in therapeutic interventions.

Testing the limits of gradient sensing

The ability to detect a chemical gradient is fundamental to many cellular processes. In multicellular organisms gradient sensing plays an important role in many physiological processes such as wound healing and development. Unicellular organisms use gradient sensing to move (chemotaxis) or grow (chemotropism) towards a favorable environment. Some cells are capable of detecting extremely shallow gradients, even in the presence of significant molecular-level noise. For example, yeast have been reported to detect pheromone gradients as shallow as 0.1 nM/μm. Noise reduction mechanisms, such as time-averaging and the internalization of pheromone molecules, have been proposed to explain how yeast cells filter fluctuations and detect shallow gradients. Here, we use a Particle-Based Reaction-Diffusion model of ligand-receptor dynamics to test the effectiveness of these mechanisms and to determine the limits of gradient sensing. In particular, we develop novel simulation methods for establishing chemical gradients that not only allow us to study gradient sensing under steady-state conditions, but also take into account transient effects as the gradient forms. Based on reported measurements of reaction rates, our results indicate neither time-averaging nor receptor endocytosis significantly improves the cell’s accuracy in detecting gradients over time scales associated with the initiation of polarized growth. Additionally, our results demonstrate the physical barrier of the cell membrane sharpens chemical gradients across the cell. While our studies are motivated by the mating response of yeast, we believe our results and simulation methods will find applications in many different contexts.

In order to survive, many organisms must not only be able to detect the presence of a chemical compound, but also in which direction that compound increases or decreases in concentration. For example, bacteria cells prefer to move towards areas with high sugar concentrations. The process by which cells determine the direction of a chemical gradient is called “Gradient Sensing”. Of particular interest is the gradient sensing capability of yeast cells. These cells have been observed detecting the direction of extremely shallow gradients, which produce only a 2% difference in the number of molecules across the cell. Because the molecular-level noise is much larger than this signal, it is unclear what noise-reduction mechanism the cell employs to reduce the noise and detect the signal. We developed a 3D computational simulation platform to calculate and study the exact positions of molecules during this process. Our platform utilizes High Performance Computing clusters and GPGPUs. We find that, of the two prevailing models in the literature, neither time-averaging nor receptor endocytosis sufficiently reduces molecular noise for yeast cells to reliably detect chemical gradients before they initiate polarized growth. This finding implies yeast must possess a mechanism for reorienting the direction of growth after cell polarization has occurred. We also find the cell membrane and similarly, any other physical barrier nearby the cell can improve the cell’s likelihood of detecting the gradient. Our simulation methods and results will be applicable in other areas of research.

Yeast GPCR signaling reflects the fraction of occupied receptors, not the number

According to receptor theory, the effect of a ligand depends on the amount of agonist-receptor complex. Therefore, changes in receptor abundance should have quantitative effects. However, the response to pheromone in Saccharomyces cerevisiae is robust (unaltered) to increases or reductions in the abundance of the G-protein-coupled receptor (GPCR), Ste2, responding instead to the fraction of occupied receptor. We found experimentally that this robustness originates during G-protein activation. We developed a complete mathematical model of this step, which suggested the ability to compute fractional occupancy depends on the physical interaction between the inhibitory regulator of G-protein signaling (RGS), Sst2, and the receptor. Accordingly, replacing Sst2 by the heterologous hsRGS4, incapable of interacting with the receptor, abolished robustness. Conversely, forcing hsRGS4:Ste2 interaction restored robustness. Taken together with other results of our work, we conclude that this GPCR pathway computes fractional occupancy because ligand-bound GPCR-RGS complexes stimulate signaling while unoccupied complexes actively inhibit it. In eukaryotes, many RGSs bind to specific GPCRs, suggesting these complexes with opposing activities also detect fraction occupancy by a ratiometric measurement. Such complexes operate as push-pull devices, which we have recently described.

Variable Dependence of Signaling Output on Agonist Occupancy of Ste2p, a G Protein-coupled Receptor in Yeast

We report here on the relationship between ligand binding and signaling responses in the yeast pheromone response pathway, a well characterized G protein-coupled receptor system. Responses to agonist (α-factor) by cells expressing widely varying numbers of receptors depend primarily on fractional occupancy, not the absolute number of agonist-bound receptors. Furthermore, the concentration of competitive antagonist required to inhibit α-factor-dependent signaling is more than 10-fold higher than predicted based on the known ligand affinities. Thus, responses to a particular number of agonist-bound receptors can vary greatly, depending on whether there are unoccupied or antagonist-bound receptors present on the same cell surface. This behavior does not appear to be due to pre-coupling of receptors to G protein or to the Sst2p regulator of G protein signaling. The results are consistent with a signaling response that is determined by the integration of positive signals from agonist-occupied receptors and inhibitory signals from unoccupied receptors, where the inhibitory signals can be diminished by antagonist binding.

Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While some mutants show enhanced binding affinity to the foreign pheromone, others only display weakened interactions with the network's negative regulators. Importantly, the latter changes have a limited impact on overall pathway regulation, despite their considerable effect on sensitivity. Our results demonstrate that a new receptor–ligand pair can evolve through network-altering mutations independently of receptor–ligand binding, and suggest a potential role for such mutations in disease.

Co-evolution of a new receptor-ligand pair will affect the downstream signal transduction network. Here, the authors use experimental evolution of yeast mating receptor Ste2 to show the effect of enhanced binding affinity and weakened interactions with the network's negative regulators on protein evolution.

Modulation of receptor dynamics by the regulator of G protein signaling Sst2

G protein–coupled receptor signaling is negatively regulated by both receptor internalization and regulator of G protein signaling (RGS) protein–stimulated inactivation of the G protein. The RGS protein can also positively regulate receptor signaling by binding to the receptor, thereby reducing receptor internalization.

G protein–coupled receptor (GPCR) signaling is fundamental to physiological processes such as vision, the immune response, and wound healing. In the budding yeast Saccharomyces cerevisiae, GPCRs detect and respond to gradients of pheromone during mating. After pheromone stimulation, the GPCR Ste2 is removed from the cell membrane, and new receptors are delivered to the growing edge. The regulator of G protein signaling (RGS) protein Sst2 acts by accelerating GTP hydrolysis and facilitating pathway desensitization. Sst2 is also known to interact with the receptor Ste2. Here we show that Sst2 is required for proper receptor recovery at the growing edge of pheromone-stimulated cells. Mathematical modeling suggested pheromone-induced synthesis of Sst2 together with its interaction with the receptor function to reestablish a receptor pool at the site of polarized growth. To validate the model, we used targeted genetic perturbations to selectively disrupt key properties of Sst2 and its induction by pheromone. Together our results reveal that a regulator of G protein signaling can also regulate the G protein–coupled receptor. Whereas Sst2 negatively regulates G protein signaling, it acts in a positive manner to promote receptor retention at the growing edge.

Signal inhibition by a dynamically regulated pool of monophosphorylated MAPK

MAPKs are activated by dual phosphorylation. Much of the MAPK Fus3 is monophosphorylated and acts to inhibit signaling in vivo. Computational models reveal how a kinase scaffold and phosphatase act together to dynamically regulate dual-phosphorylated and monophosphorylated MAPKs and the downstream signal.

Protein kinases regulate a broad array of cellular processes and do so through the phosphorylation of one or more sites within a given substrate. Many protein kinases are themselves regulated through multisite phosphorylation, and the addition or removal of phosphates can occur in a sequential (processive) or a stepwise (distributive) manner. Here we measured the relative abundance of the monophosphorylated and dual-phosphorylated forms of Fus3, a member of the mitogen-activated protein kinase (MAPK) family in yeast. We found that upon activation with pheromone, a substantial proportion of Fus3 accumulates in the monophosphorylated state. Introduction of an additional copy of Fus3 lacking either phosphorylation site leads to dampened signaling. Conversely, cells lacking the dual-specificity phosphatase (msg5Δ) or that are deficient in docking to the MAPK-scaffold (Ste5^ND) accumulate a greater proportion of dual-phosphorylated Fus3. The double mutant exhibits a synergistic, or “synthetic,” supersensitivity to pheromone. Finally, we present a predictive computational model that combines MAPK scaffold and phosphatase activities and is sufficient to account for the observed MAPK profiles. These results indicate that the monophosphorylated and dual-phosphorylated forms of the MAPK act in opposition to one another. Moreover, they reveal a new mechanism by which the MAPK scaffold acts dynamically to regulate signaling.

RGS proteins and septins cooperate to promote chemotropism by regulating polar cap mobility

BACKGROUND

Septins are well known to form a boundary between mother and daughter cells in mitosis, but their role in other morphogenic states is poorly understood.

RESULTS

Using microfluidics and live-cell microscopy, coupled with new computational methods for image analysis, we investigated septin function during pheromone-dependent chemotropic growth in yeast. We show that septins colocalize with the regulator of G protein signaling (RGS) Sst2, a GTPase-activating protein that dampens pheromone receptor signaling. We show further that the septin structure surrounds the polar cap, ensuring that cell growth is directed toward the source of pheromone. When RGS activity is abrogated, septins are partially disorganized. Under these circumstances, the polar cap travels toward septin structures and away from sites of exocytosis, resulting in a loss of gradient tracking.

CONCLUSIONS

Septin organization is dependent on RGS protein activity. When assembled correctly, septins promote turning of the polar cap and proper tracking of a pheromone gradient.