Modeling activation and desensitization of G-protein coupled receptors provides insight into ligand efficacy.

Signaling through G-protein coupled receptors is one of the most prevalent and important methods of transmitting information to the inside of cells. Many mathematical models have been proposed to describe this type of signal transduction, and the ternary complex (ligand/receptor/G-protein) model and its derivatives are among the most widely accepted. Current versions of these equilibrium models include both active (i.e. signaling) and inactive conformations of the receptor, but do not include the dynamics of G-protein activation or receptor desensitization. Yet understanding how these dynamic events effect response behavior is crucial to determining ligand efficacy. We developed a mathematical model for G-protein coupled receptor signaling that includes G-protein activation and receptor desensitization, and used it to predict how activation and desensitization would change if either the conformational selectivity (the effect of ligand binding on the distribution of active and inactive receptor states) or the desensitization rate constant was ligand-specific. In addition, the model was used to explore the implications of measuring responses far downstream from G-protein activation. By comparing the experimental data from the beta(2)-adrenergic, micro-opioid, D(1)dopamine, and neutrophil N -formyl peptide receptors with the predictions of our model, we found that the conformational selectivity is the predominant factor in determining the amounts of activation and desensitization caused by a particular ligand.     

Reorganization of the actin cytoskeleton upon G-protein coupled receptor signaling

The actin cytoskeleton is involved in a multitude of cellular responses besides providing structural support. While the role of the actin cytoskeleton in cellular processes such as trafficking and motility has been extensively studied, reorganization of the actin cytoskeleton upon signaling by G-protein coupled receptors (GPCRs) represents a relatively unexplored area. The G-protein coupled receptor superfamily is an important protein family in mammals, involved in signal transduction across membranes. G-protein coupled receptors act as major signaling hubs and drug targets. The serotonin(1A) receptor is a representative member of the G-protein coupled receptor superfamily and plays a crucial role in the generation and modulation of various cognitive, developmental and behavioral functions. In order to monitor the changes in the actin cytoskeleton upon serotonin(1A) receptor signaling in a quantitative manner, we developed an approach based on high magnification imaging of F-actin in cells, followed by image reconstruction. Our results suggest that the actin cytoskeleton is reorganized in response to serotonin(1A) receptor signaling. In addition, we show that reorganization of the actin cytoskeleton is strongly dependent on adenosine 3',5'-cyclic monophosphate level, and is mediated by the activation of protein kinase A. Our results are consistent with the possibility of a feedback mechanism involving the actin cytoskeleton, adenosine 3',5'-cyclic monophosphate level and the serotonin(1A) receptor.     

Signaling networks in cancer--an interview with Christian Gespach. Interview by Olivier De Wever

The dynamic, innovative temperament of Christian Gespach is ideally suited to unraveling some aspects of the complex molecular networks connected with signal transduction, cancer progression and treatment. He is one of the pioneers who opened, in the early 1980s, new insights into the signaling mechanisms of G-protein coupled receptor (GPCR) activation, desensitization, internalisation and crosstalks. Twenty five years later and in collaboration with Gespach, IPSEN pharmaceuticals designed pan-inhibitors of GPCR signaling, targeting Gα subunits in breast cancer progression and other epithelial cancers. Creativity is of vital importance to understand signal transduction pathways engaged in cancer cell motility, invasion and drug resistance. Christian Gespach has published more than 200 papers in cancer research, a true signal transduction tale.     

A Monte Carlo study of the dynamics of G-protein activation.

To link quantitatively the cell surface binding of ligand to receptor with the production of cellular responses, it may be necessary to explore early events in signal transduction such as G-protein activation. Two different model frameworks relating receptor/ligand binding to G-protein activation are examined. In the first framework, a simple ordinary differential equation model is used to describe receptor/ligand binding and G-protein activation. In the second framework, the events leading to G-protein activation are simulated using a dynamic Monte Carlo model. In both models, reactions between ligand-bound receptors and G-proteins are assumed to be diffusion-limited. The Monte Carlo model predicts two regimes of G-protein activation, depending upon whether the lifetime of a receptor/ligand complex is long or short compared with the time needed for diffusional encounters of complexes and G-proteins. When the lifetime of a complex is relatively short compared with the diffusion time, the movement of ligand among free receptors by binding and unbinding ("switching") significantly enhances G-protein activation. Receptor antagonists dramatically reduce G-protein activation and, thus, signal transduction in this case, and significant clustering of active G-proteins near receptor/ligand complexes results. The simple ordinary differential equation model poorly predicts G-protein activation for this situation. In the alternative case, when diffusion is relatively fast, ligand movement among receptors is less important and the simple ordinary differential equation model and Monte Carlo model results are similar. In this case, there is little clustering of active G-proteins near receptor/ligand complexes. Results also indicate that as the GTPase activity of the alpha-subunit decreases, the steady-state level of alpha-GTP increases, although temporal sensitivity is compromised.     

Impedance-based analysis of mu opioid receptor signaling and underlying mechanisms

The mu opioid receptor is a G-protein coupled receptor able to signal through the Gα_i/o class of G-protein and β-arrestin pathways, stimulating down-stream effector pathways. Signaling bias occurs when different receptor agonists lead to different signaling outcomes. Traditionally these have been studied using end-point assays. Real-time cellular analysis platforms allow for the analysis of the holistic effects of receptor activation as an integrated output. While this allows for different ligands to be compared rapidly, the cellular mechanisms underlying the signal are not well described. Using an impedance based system, the impedance responses for two opioid ligands, morphine and DAMGO were examined.The impedance responses for these two agonists, while showing similar features, were distinct from each other. Some of the mechanisms underlying the mu opioid receptor coupled impedance changes were investigated. It was found that the response is a result of discrete cellular processes, including G-protein signaling and protein kinase phosphorylation.     

Signal Transduction by Growth Factor Receptors: Signaling in an Instant

Phosphorylation-based signaling events happening within the first minute of receptor stimulation have so far only been analyzed by classical cell biological approaches like live-cell microscopy. The development of a quench flow system with a time resolution of one second coupled to a read-out by mass spectrometry-based proteomics has allowed exciting views on the very early events in signal transduction. Activation profiles of regulated phosphorylation sites on epidermal growth factor receptor and downstream signal transducers showed different kinetics within the first ten seconds of stimulation. This new technique opens the perspectives for accurate analysis of rapid cellular processes and will help to establish models describing signal initiation at the plasma membrane.     

Plant signaling in stress: G-protein coupled receptors,heterotrimeric G-proteins and signal coupling via phospholipases

Plant growth and development are coordinalely controlled by several internal factors and environmental signals. To sense these environmental signals, the higher plants have evolved a complex signaling network, which may also cross talk with each other. Plants can respond to the signals as individual cells and as whole organisms. Various receptors including phytochromes, G-proteins coupled receptors (GPCR), kinase and hormone receptors play important role in signal transduction but very few have been characterized in plant system. The heterotrimeric G-proteins mediate the coupling of signal transduction from activated GPCR to appropriate downstream effectors and thereby play an important role in signaling. In this review we have focused on some of the recent work on G-proteins and two of the effectors, PLC and PLD, which have been shown to interact with Gα subunit and also discussed their role in abiotic stress tolerance.Key words: abiotic stress, G-protein couple receptor, heterotrimeric G-protein, phospholipases, plant receptors, signal transduction     

An integrated model of epidermal growth factor receptor trafficking and signal transduction

Endocytic trafficking of many types of receptors can have profound effects on subsequent signaling events. Quantitative models of these processes, however, have usually considered trafficking and signaling independently. Here, we present an integrated model of both the trafficking and signaling pathway of the epidermal growth factor receptor (EGFR) using a probability weighted-dynamic Monte Carlo simulation. Our model consists of hundreds of distinct endocytic compartments and approximately 13,000 reactions/events that occur over a broad spatio-temporal range. By using a realistic multicompartment model, we can investigate the distribution of the receptors among cellular compartments as well as their potential signal transduction characteristics. Our new model also allows the incorporation of physiochemical aspects of ligand-receptor interactions, such as pH-dependent binding in different endosomal compartments. To determine the utility of this approach, we simulated the differential activation of the EGFR by two of its ligands, epidermal growth factor (EGF) and transforming growth factor-alpha (TGF-alpha). Our simulations predict that when EGFR is activated with TGF-alpha, receptor activation is biased toward the cell surface whereas EGF produces a signaling bias toward the endosomal compartment. Experiments confirm these predictions from our model and simulations. Our model accurately predicts the kinetics and extent of receptor downregulation induced by either EGF or TGF-alpha. Our results suggest that receptor trafficking controls the compartmental bias of signal transduction, rather than simply modulating signal magnitude. Our model provides a new approach to evaluating the complex effect of receptor trafficking on signal transduction. Importantly, the stochastic and compartmental nature of the simulation allows these models to be directly tested by high-throughput approaches, such as quantitative image analysis.     

The Silicon Cell initiative: working towards a detailed kinetic description at the cellular level

The Silicon Cell initiative aims to understand cellular systems on the basis of the characteristics of their components. As a tool to achieve this, detailed kinetic models at the network reaction level are being constructed. Such detailed kinetic models are extremely useful for medical and biotechnological applications and form strong tools for fundamental studies. Several recently constructed detailed kinetic models on metabolism (glycolysis), signal transduction (EGF receptor), and the eukaryotic cell cycle (Saccharomyces cerevisiae) have been used to exemplify the Silicon Cell project. These models are stored and made accessible via the JWS Online Cellular Systems Modeling project, a web-based repository of kinetic models. Using a web-browser the models can be interrogated via a user-friendly graphical interface. The goal of the two projects is to combine models on parts of cellular systems and ultimately to construct detailed kinetic models at the cellular level.     

Insulin receptor binding kinetics: modeling and simulation studies

Biological actions of insulin regulate glucose metabolism and other essential physiological functions. Binding of insulin to its cell surface receptor initiates signal transduction pathways that mediate cellular responses. Thus, it is of great interest to understand the mechanisms underlying insulin receptor binding kinetics. Interestingly, negative cooperative interactions are observed at high insulin concentrations while positive cooperativity may be present at low insulin concentrations. Clearly, insulin receptor binding kinetics cannot be simply explained by a classical bimolecular reaction. Mature insulin receptors have a dimeric structure capable of binding two molecules of insulin. The binding affinity of the receptor for the second insulin molecule is significantly lower than for the first bound insulin molecule. In addition, insulin receptor aggregation occurs in response to ligand binding and aggregation may also influence binding kinetics. In this study, we develop a mathematical model for insulin receptor binding kinetics that explicitly represents the divalent nature of the insulin receptor and incorporates receptor aggregation into the kinetic model. Model parameters are based upon published data where available. Computer simulations with our model are capable of reproducing both negative and positive cooperativity at the appropriate insulin concentrations. This model may be a useful tool for helping to understand the mechanisms underlying insulin receptor binding and the coupling of receptor binding to downstream signaling events.     

Cholesterol depletion induces dynamic confinement of the G-protein coupled serotonin1A receptor in the plasma membrane of living cells

Cholesterol is an essential constituent of eukaryotic membranes and plays a crucial role in membrane organization, dynamics, function, and sorting. It is often found distributed non-randomly in domains or pools in biological and model membranes and is thought to contribute to a segregated distribution of membrane constituents. Signal transduction events mediated by seven transmembrane domain G-protein coupled receptors (GPCRs) are the primary means by which cells communicate with and respond to their external environment. We analyzed the role of cholesterol in the plasma membrane organization of the G-protein coupled serotonin_1A receptor by fluorescence recovery after photobleaching (FRAP) measurements with varying bleach spot sizes. Our results show that lateral diffusion parameters of serotonin_1A receptors in normal cells are consistent with models describing diffusion of molecules in a homogenous membrane. Interestingly, these characteristics are altered in cholesterol-depleted cells in a manner that is consistent with dynamic confinement of serotonin_1A receptors in the plasma membrane. Importantly, analysis of ligand binding and downstream signaling of the serotonin_1A receptor suggests that receptor function is affected in a significantly different manner when intact cells or isolated membranes are depleted of cholesterol. These results assume significance in the context of interpreting effects of cholesterol depletion on diffusion characteristics of membrane proteins in particular, and cholesterol-dependent cellular processes in general.     

Cholesterol depletion induces dynamic confinement of the G-protein coupled serotonin(1A) receptor in the plasma membrane of living cells

Cholesterol is an essential constituent of eukaryotic membranes and plays a crucial role in membrane organization, dynamics, function, and sorting. It is often found distributed non-randomly in domains or pools in biological and model membranes and is thought to contribute to a segregated distribution of membrane constituents. Signal transduction events mediated by seven transmembrane domain G-protein coupled receptors (GPCRs) are the primary means by which cells communicate with and respond to their external environment. We analyzed the role of cholesterol in the plasma membrane organization of the G-protein coupled serotonin(1A) receptor by fluorescence recovery after photobleaching (FRAP) measurements with varying bleach spot sizes. Our results show that lateral diffusion parameters of serotonin(1A) receptors in normal cells are consistent with models describing diffusion of molecules in a homogenous membrane. Interestingly, these characteristics are altered in cholesterol-depleted cells in a manner that is consistent with dynamic confinement of serotonin(1A) receptors in the plasma membrane. Importantly, analysis of ligand binding and downstream signaling of the serotonin(1A) receptor suggests that receptor function is affected in a significantly different manner when intact cells or isolated membranes are depleted of cholesterol. These results assume significance in the context of interpreting effects of cholesterol depletion on diffusion characteristics of membrane proteins in particular, and cholesterol-dependent cellular processes in general.     

Opposite Ends of the Spectrum: Plant and Animal G-Protein Signaling

Different classes of biotic (e.g., plant hormones) and abiotic (e.g., different wavelengths of light) signals act through specific signal transduction mechanisms to coordinate all aspects of plant development. Full signal transduction chains have not yet been described for most light or hormonal-mediated events despite the wide range of events early in development which are dependent upon hormonal and light signals. We recently reported a single signal transduction chain which can be initiated by both blue light (BL) and ABA, and which leads to the expression of specific members of the Lhcb gene family in the apical bud of etiolated Arabidopsis seedlings. The signal transduction chain consists of GCR1 (one of two Arabidopsis proteins coding for a potential G-protein coupled receptor), GPA1 (the sole Arabidopsis Ga subunit), PRN1 (Pirin1, one of four members of an iron-containing subgroup of the cupin superfamily), and a Nuclear Factor -Y (NF-Y) heterotrimer comprised of A5, B9 and possibly C9. The same signaling proteins control ABA-mediated delay of germination.Key Words: blue light, G-protein coupled receptor, G-protein sub unit, abscisic acid (ABA)     

AGS proteins, GPR motifs and the signals processed by heterotrimeric G proteins

A long term objective of our research effort is to define factors that influence the specificity and efficiency of signal propagation by heterotrimeric G-proteins (G). G-proteins play a central role in cellular communication mediating the cell response to numerous hormones and neurotransmitters. A major determinant of signalling specificity for heterotrimeric G-proteins is the cell specific expression of the subtypes of the primary signalling entities, receptor, G and effector (E). Another major site for regulating signalling specificity lies at the R-G or G-E interface where these interactions are influenced by cell architecture, the stoichiometry of signalling components and accessory proteins that may segregate the receptor to microdomains of the cell, regulate the efficiency and/or specificity of signal transfer and/or influence the activation state of G-protein independent of a classical G-protein coupled receptor. One strategy to address these issues in our laboratory involves the identification of cellular proteins that regulate the transfer of signal from receptor to G or directly influence the activation state of G independent of a classical G-protein coupled receptor. We identified three proteins, AGS1, AGS2 and AGS3 (for Activators of G-protein Signaling), that activated heterotrimeric G-protein signalling pathways in the absence of a typical receptor. AGS1, 2 and 3 interact with different subunits and/or conformations of heterotrimeric G-proteins, selectively activate different G-proteins, provide unexpected mechanisms for regulation of the G-protein activation cycle and have opened up a new area of research related to the cellular role of G-proteins as signal transducers.     

Simulated Evolution of Signal Transduction Networks

Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.     

Cellular level models as tools for cytokine design

Cytokines and growth factors are critical regulators that connect intracellular and extracellular environments through binding to specific cell‐surface receptors. They regulate a wide variety of immunological, growth, and inflammatory response processes. The overall signal initiated by a population of cytokine molecules over long time periods is controlled by the subtle interplay of binding, signaling, and trafficking kinetics. Building on the work of others, we abstract a simple kinetic model that captures relevant features from cytokine systems as well as related growth factor systems. We explore a large range of potential biochemical behaviors, through systematic examination of the model's parameter space. Different rates for the same reaction topology lead to a dramatic range of biochemical network properties and outcomes. Evolution might productively explore varied and different portions of parameter space to create beneficial behaviors, and effective human therapeutic intervention might be achieved through altering network kinetic properties. Quantitative analysis of the results reveals the basis for tensions among a number of different network characteristics. For example, strong binding of cytokine to receptor can increase short‐term receptor activation and signal initiation but decrease long‐term signaling due to internalization and degradation. Further analysis reveals the role of specific biochemical processes in modulating such tensions. For instance, the kinetics of cytokine binding and receptor activation modulate whether ligand–receptor dissociation can generally occur before signal initiation or receptor internalization. Beyond analysis, the same models and model behaviors provide an important basis for the design of more potent cytokine therapeutics by providing insight into how binding kinetics affect ligand potency. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Monte Carlo simulations of receptor dynamics: Insights into cell signaling

Many receptor-level processes involve the diffusion and reaction of receptors with other membrane-localized molecules. Monte Carlo simulation is a powerful technique that allows us to track the motions and discrete reactions of individual receptors, thus simulating receptor dynamics and the early events of signal transduction. In this paper, we discuss simulations of two receptor processes, receptor dimerization and G-protein activation. Our first set of simulations demonstrates how receptor dimerization can create clusters of receptors via partner switching and the relevance of this clustering for receptor cross-talk and integrin signaling. Our second set of simulations investigates the activation and desensitization of G-protein coupled receptors when either a single agonist or both an agonist and an antagonist are present. For G-protein coupled receptor systems in the presence of an agonist alone, the dissociation rate constant of agonist is predicted to affect the ratio of G-protein activation to receptor phosphorylation. Similarly, this ratio is affected by the antagonist dissociation rate constant when both agonist and antagonist are present. The relationship of simulation predictions to experimental findings and potential applications of our findings are also discussed.