Collision coupling, crosstalk, and compartmentalization in G-protein coupled receptor systems: Can a single model explain disparate results?

https://doi.org/10.1016/j.jtbi.2008.08.003Get rights and content

Abstract

The collision coupling model describes interactions between receptors and G-proteins as first requiring the molecules to find each other by diffusion. A variety of experimental data on G-protein activation have been interpreted as suggesting (or not) the compartmentalization of receptors and/or G-proteins in addition to a collision coupling mechanism. In this work, we use a mathematical model of G-protein activation via collision coupling but without compartmentalization to demonstrate that these disparate observations do not imply the existence of such compartments. In experiments with GTP analogs (commonly GTPγS), the extent of G-protein activation is predicted to be a function of both receptor number and the rate of GTP analog hydrolysis. The sensitivity of G-protein activation to receptor number is shown to be dependent upon the assay used, with the sensitivity of phosphate production assays (GTPase) >GTPγS-binding assays >cAMP inhibition assays. Finally, the amount of competition or crosstalk between receptor species activating the same type of G-proteins is predicted to depend on receptor and G-protein number, but in some (common) experimental regimes this dependence is expected to be minimal. Taken together, these observations suggest that the collision coupling model, without compartments of receptors and/or G-proteins, is sufficient to explain a variety of observations in literature data.

Introduction

The ability of the G-protein-coupled signal transduction system to detect a stimulus depends on interactions between receptors and G-proteins. Such interactions have been described by the collision coupling model (Tolkovsky and Levitzki, 1978), reviewed in Lauffenburger and Linderman (1993), which allows for receptors and G-proteins to diffuse in the membrane and interact if the correct recognition surfaces are present when they collide. When multiple receptor types can activate the same G-proteins, the collision coupling model predicts that there is competition between the receptor types for the same G-protein pool (e.g. Graeser and Neubig, 1993). Such competition is one route to what has broadly been termed crosstalk, or the influence of activation of one receptor type on signaling through a second receptor type. In this paper, we explore the predictions of the collision coupling model for crosstalk and comment on the interpretation of experimental data that has been used previously to suggest there is compartmentalization of receptors and G-proteins.

Several experimental techniques can be used to measure G-protein activation. Activation of G-proteins can be assayed by measuring binding of the slowly hydrolyzable (commonly referred to as “non-hydrolyzable”) GTP analogs GTPγS (as [35S]GTPγS) or GppNHp (as [3H]GppNHp) to determine the rate of G-protein activation and the number of active G-proteins at steady state (Harrison and Traynor, 2003). GTPase experiments measure the rate at which GTP is hydrolyzed to GDP; the number of active GTP-bound G-proteins is directly proportional to the rate of phosphate production. Other methods to assess G-protein activation include measurement of downstream players, e.g. cAMP production, and a FRET-based method to detect separation of α and βγ subunits (Azpiazu and Gautam, 2004).

In experiments with a single receptor type, receptor number may be decreased and the maximum level of G-protein activation (the extent of reaction) measured. If the extent of reaction is independent of the receptor concentration, this is commonly interpreted to mean that receptors are free to diffuse on the membrane, i.e. there is no compartmentalization that limits the access of receptors to the full complement of G-proteins. For example, in an early study of the β-adrenergic receptor and adenylyl cyclase (AC) activation in turkey erythrocytes, when the number of receptors was decreased the extent of cAMP production did not change (Tolkovsky and Levitzki, 1978). Fantozzi et al. (1981) made a similar observation that the extent of cAMP inhibition did not change in NG108-15 cells when opioid receptor number was reduced. This insensitivity in cAMP inhibition to changing receptor concentration means there is a receptor reserve (Brown and Goldstein, 1986).

In other reports, however, the amount of G-protein activation is sensitive to receptor number (Costa et al., 1988; Newman-Tancredi et al., 1999; Remmers et al., 2000; Traynor et al., 2002). For example, upon reducing the number of opioid receptors heterologously expressed in digitonin-permeabilized C6 glioma cells, the degree of G-protein activation decreased (Alt et al., 2001). This has been interpreted to mean that here compartmentalization limits the access of receptors to G-proteins, suggesting that systems may behave quite differently. Indeed, submicroscopic corrals, which may be formed by actin filaments near the membrane (Ritchie et al., 2005), lipid domains or rafts (Daumas et al., 2003) or by other mechanisms (Saxton, 2005) affect diffusion in the membrane and perhaps could play a role in segregating membrane components.

To further test for compartmentalization of receptors and G-proteins and as a quantitative measure of crosstalk, investigators have used multiple agonists that bind to different receptors but activate the same class of G-proteins. If the agonist-occupied receptor species are free to diffuse in the membrane, they will compete for G-proteins, creating crosstalk. Such competition is seen when measuring GTPγS binding in SH-SY5Y (neuroblastoma) cell membranes: activation of both endogenous μ- and δ-opioid receptors results in a maximal level of GTPγS binding equal to activation of just μ-opioid receptors alone (Alt et al., 2002). Similar observations of GTPγS binding are made for δ-opioid and CB1 cannabinoid receptors exogenously expressed in COS-7 cell membranes (Shapira et al., 2000). As measured by Ca2+ current, cannabinoid and adrenergic receptors in superior cervical ganglion neurons cells compete to activate G-proteins (Vasquez and Lewis, 1999). Further, measurements of cAMP production after activation of prostaglandin and adrenergic receptors in frog erythrocytes (Pike and Lefkowitz, 1981) and glucagon and adrenergic receptors in rat and hamster adipocytes (Murayama and Ui, 1984) also show that the two receptor types share and compete for a common pool of G-proteins. These results are in agreement with the expectation of receptors freely diffusing on the membrane in a collision coupling model.

However, in other experimental systems, receptors that activate the same class of G-proteins do not compete with each other and do not display crosstalk. In NG108-15 (neuroblastoma-glioma) cells, endogenous α-adrenergic, muscarinic and δ-opioid receptors all couple to inhibitory G-proteins but simultaneous activation of opioid and muscarinic receptors shows no crosstalk when measured at the level of agonist affinity (a proxy for G-protein activation) (Graeser and Neubig, 1993). In SK-N-SH cells (a parent cell line of SH-SY5Y cells described above), no crosstalk is observed between endogenous μ- and δ-opioid and cannabinoid receptors for GTPγS binding (Shapira et al., 2000); the activation of both receptor types produces as much GTPγS binding as the sum of the amount produced when each receptor type is activated alone. To explain these results it has been proposed that the different receptor types in these cell systems are to some degree segregated from each other in membrane compartments and compartmentalized with their cognate G-proteins.

We questioned whether the disparate results described above are the result of different situations, namely systems in which compartmentalization of receptors is present and systems in which it is not, or whether the results could be explained by a single model. We hypothesized that compartmentalization is not necessary to explain the sensitivity of activation to receptor number nor the absence of crosstalk in some systems. To test this hypothesis, we used a mathematical model of the G-protein activation cycle under conditions of collision coupling but with no compartmentalization. Key model parameters include the number of cell surface receptors and G-proteins and the rate constant for hydrolysis of GTP or GTP analog. By varying these parameters, we are able to explain the range of behaviors seen experimentally without the need to invoke membrane compartments.

Section snippets

Mathematical model

Our model for the G-protein activation cycle is shown in Fig. 1 and is based on previous models of G-protein activation (Riccobene et al., 1998; Yi et al., 2003; Zhong et al., 2003). Receptors and G-proteins diffuse freely in the membrane and bind with rate constant k+, the value of which depends on the diffusivity of the molecules and the probability that a collision between the two is productive. Thus, this model uses a collision coupling mechanism for activation of G-proteins by bound

Results and discussion

With our model of G-protein activation, we simulate three types of assays that measure G-protein activation: GTPγS binding, phosphate production from GTP (GTPase), and inhibition of cAMP.

Conclusions

In this work, we demonstrate using a mathematical model of collision coupling that compartmentalization of receptors and/or G-proteins within the membrane is not necessary to explain literature data on the extent of G-protein activation and receptor crosstalk. First, we show that the slow hydrolysis rate of GTPγS, a GTP analog commonly termed “non-hydrolyzable”, plays an important role in determining the extent of G-protein activation. We predict that two different GTP analogs tested in the

Acknowledgments

We thank Mary J. Clark for helpful discussions and C. Perrin for assistance with calculations. This work was supported by Merck Research Laboratories, NIH R01 GM 062930 and DA04087.

References (47)

  • M.J. Saxton

    Fluorescence correlation spectroscopy

    Biophys. J.

    (2005)
  • M. Shapira et al.

    Diverse pathways mediate delta-opioid receptor down regulation within the same cell

    Brain Res. Mol. Brain Res.

    (2001)
  • L.D. Shea et al.

    Compartmentalization of receptors and enzymes affects activation for a collision coupling mechanism

    J. Theor. Biol.

    (1998)
  • L.D. Shea et al.

    Calculation of diffusion-limited kinetics for the reactions in collision coupling and receptor cross-linking

    Biophys. J.

    (1997)
  • P.J. Woolf et al.

    An algebra of dimerization and its implications for G-protein coupled receptor signaling

    J. Theor. Biol.

    (2004)
  • H. Zhong et al.

    A spatial focusing model for G protein signals. Regulator of G protein signaling (RGS) protien-mediated kinetic scaffolding

    J. Biol. Chem.

    (2003)
  • A. Alt et al.

    Stimulation of guanosine-5′-o-(3-[35S]thio)triphosphate binding in digitonin-permeabilized C6 rat glioma cells: evidence for an organized association of mu-opioid receptors and G protein

    J. Pharmacol. Exp. Ther.

    (2001)
  • A. Alt et al.

    Mu and Delta opioid receptors activate the same G proteins in human neuroblastoma SH-SY5Y cells

    Br. J. Pharmacol.

    (2002)
  • U.S. Bhalla et al.

    Emergent properties of networks of biological signaling pathways

    Science

    (1999)
  • S.J. Bornheimer et al.

    Computational modeling reveals how interplay between components of a GTPase-cycle module regulates signal transduction

    Proc. Natl. Acad. Sci. USA

    (2004)
  • G.E. Breitwieser

    G protein-coupled receptor oligomerization: implications for G protein activation and cell signaling

    Circ. Res.

    (2004)
  • J.H. Brown et al.

    Differences in muscarinic receptor reserve for inhibition of adenylate cyclase and stimulation of phosphoinositide hydrolysis in chick heart cells

    Mol. Pharmacol.

    (1986)
  • B.D. Carter et al.

    Go mediates the coupling of the mu opioid receptor to adenylyl cyclase in cloned neural cells and brain

    Proc. Natl. Acad. Sci. USA

    (1993)
  • Cited by (0)

    View full text