Introduction

Summary Introduction Materials & Methods Results Discussion References

Agonist binding to GPCRs in cell membrane promotes "biological" activation of the receptor protein. Binding of epinephrine to ₂AR, which is a GPCR, leads to the activation of G_s protein, which, in turn, stimulates adenylate cyclase. Stimulation of adenylate cyclase alters the metabolic state of the cell by raising the intracellular concentration of cAMP. In heart, such an alteration results in an increased contractility and excitability of cardiomyocytes. Recently, Tg mice were created with cardiospecific overexpression of ₂AR, which produced an enhanced agonist-independent activation of adenylate cyclase and myocardial function (1, 2). This activity was inhibited by the inverse agonist ICI 118,551. These results were considered in the framework of a two-state receptor model in which the receptor exists in an active and an inactive conformation in equilibrium (2). In this model, agonist shifts the equilibrium toward the active state, inverse agonist does the opposite, and neutral antagonist does not change this equilibrium (see Ref. 3 for a review of the pharmacological implications of the two-state allosteric models).

In this study, we report observations that cannot be explained by the available receptor models in the hearts of Tg mice overexpressing wild-type ₂AR. These observations include an efficacy-dependent, guanine nucleotide-insensitive change in ligand affinity in hearts that overexpress ₂AR. We analyzed the results in the framework of a receptor model that allows the receptor to toggle between an active and an inactive form, the former of which can polymerize as the total concentration of receptors increases. Thus, this model explicitly incorporates receptor/receptor interactions in the membrane. Previously published experimental data that suggest such interactions are also discussed.

	Materials and Methods

Summary Introduction Materials & Methods Results Discussion References

Binding. Crude myocardial membranes were prepared by homogenizing whole hearts in ice-cold lysis buffer (5 mM Tris·HCl, pH 7.4, 5 mM EDTA, 10 µg/ml leupeptin, 20 µg/ml aprotinin). The homogenate was centrifuged at 500 × g for 15 min. The membrane pellets were obtained after centrifugation (45,000 × g for 30 min) of the supernatant. Membranes were washed with binding buffer (50 mM Tris·HCl, pH 7.4, 10 mM MgCl₂, 1 mM EDTA, 0.1 mM ascorbic acid). Competition binding of [¹²⁵I]ICYP (2200 Ci/mmol; New England Nuclear Research Products, Boston, MA) with different cold ligands in the presence or absence of Gpp(NH)p was measured after equilibration of the binding reaction in binding buffer for 60 min at 37°. Reactions were terminated by rapid filtration using a Brandel cell harvester (Montreal, Quebec, Canada) and Whatman (Maidstone, UK) GF/C filters. Filters were washed four times with 4 ml of ice-cold binding buffer. The filter-bound radioactivity was determined in a Beckman Instruments (Palo Alto, CA) -counter. ALP at 1 µM was used to determine nonspecific binding. To eliminate binding to ₁ receptors (especially with nonspecific ligands in control animals), we regularly included 0.1 µM CGP 20712A in the incubation media. For saturation binding experiments, [¹²⁵I]ICYP concentrations ranged between 5 and 400 pM. For competition binding experiments, [¹²⁵I]ICYP concentration was ~80 pM, and the receptor concentration was ~8 pM. Assays were conducted in duplicate.

Immunoprecipitation. Myocardial membranes were solubilized by gentle end-over shaking for 60 min at 4° in 1.5% digitonin, 50 mM Tris·HCl, pH 7.4, 10 mM MgCl₂, 1 mM EDTA, 10 µg/ml leupeptin, 20 µg/ml aprotinin, 25 µg/ml pepstatin. The sample was centrifuged at 100,000 × g for 60 min at 4°, and supernatant was used as the soluble membrane fraction. After solubilization of myocardial membranes, 30-35% of the initial AR was detected in the soluble fraction by measuring [¹²⁵I]ICYP binding as described above, except that reactions were terminated by the addition of 4 ml of ice-cold Tris·HCl buffer (5 mM Tris·HCl, pH 7.4) and rapid filtration using Whatman DE81 filters.

Immunoblots. Myocardial membranes, solubilized membranes, or membrane immunoprecipitates were subjected to 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (6) and then transferred electrophoretically to nitrocellulose. Immunoblotting was performed using antisera RM/1 (G_s), AS/7 (G_i), GC/2 (G_o), and QL (G_q/11) (dilutions, 1:1000; New England Nuclear Research Products) and enhanced chemiluminescence as previously described (5). Briefly, nitrocellulose membranes were incubated overnight at 4° in PBS containing 3% bovine serum albumin and 8% nonfat dry milk. Blots were washed several times with PBS and then incubated with antisera at room temperature for 1-2 hr with shaking. Blots were washed several times with PBS and then incubated with horseradish peroxidase-labeled donkey anti-rabbit IgG (Amersham, Paisley, UK) for 1 hr at room temperature. Blots were washed several times with PBS and then incubated with enhanced chemiluminescence Western blotting reagent (Amersham) for 1 min and exposed to x-ray film for 15-45 sec.

Modeling. The current experimental data suggested a G protein-independent change in the apparent ligand affinity with increased density of receptors in the membranes. Interestingly, change in the ligand affinity was strictly dependent on the efficacy of the ligand used to measure the affinity. More specifically, when we used agonists, the ligand affinity was increased with receptor overexpression, and it was not changed or decreased when we used neutral antagonists or inverse agonists, respectively. To accommodate this phenomenology, we explicitly included receptor/receptor interactions in the two-state receptor model. In this model, we allowed only the active receptors to interact with each other, so the reactivity of the receptor to its ligands changes with its level of expression. Hence, the polymerization state of the receptor is linked to the ability of the ligand to change the distribution of active and inactive states, or, in other words, to the ligand efficacy. The equilibrium scheme given in Fig. 1 summarizes this idea in the most general sense.

View larger version (12K): [in this window] [in a new window]   Fig. 1.   Equilibrium scheme for two-state receptor polymerization model. R and R*, Inactive and active forms of the receptor, respectively.  (the efficacy term), Ability of the ligand to shift the R-R* equilibrium (which is governed by J) or, equivalently, the "preference" of ligand for the two receptor states (K versus K). L, Polymerization affinity in a single step of polymerization reaction, , Allosteric effect in polymerization. H, Ligand.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

	Results

Summary Introduction Materials & Methods Results Discussion References

Immunoprecipitation. Immunoblot analysis of cardiac membranes revealed two bands for G_s (45 and 52 kDa) (Fig. 2). The densities of these bands (assessed by evaluating the densitometric scans of three independent experiments) did not differ between the membranes obtained from control and Tg35 and Tg4 mice.

View larger version (33K): [in this window] [in a new window]   Fig. 2.   Western blot analyses of Gs in myocardial membranes from control (lane 1), Tg35 (lane 2), and Tg4 (lane 3) mice. Results are representative of three to five independent experiments.

View larger version (57K): [in this window] [in a new window]   Fig. 3.   Immunoprecipitation of AR, by antisera to Gs, from solubilized myocardial membranes from control, Tg35, and Tg4 mouse hearts. Values are the mean and standard error of five or six separate experiments. *, Significant difference from preceding bar (Student-Newman-Keuls, p < 0.05).

Ligand binding. Fig. 4 shows the competition binding isotherms of ISO, ALP, and ICI 118,551 obtained in control and Tg35 and Tg4 membranes in the presence or absence of Gpp(NH)p. The binding of ALP was not different when examined in control or Tg35 and Tg4 mice and was not sensitive to the presence of nucleotide. In contrast, IC₅₀ values of ISO or ICI 118,551 increases (828 ± 200 to 98 ± 40 nM) or decreases (0.7 ± 0.2 to 4 ± 1.2 nM), respectively, as the expression level of receptors increases and also becomes insensitive to the presence of the nucleotide. The dependence of log(IC₅₀) on log(receptor density) in the presence of Gpp(NH)p was in the opposite direction for ISO and ICI 118,551, as indicated by their regression coefficients (p < 0.05). The binding of ALP was not affected by receptor density. Incidentally, ALP behaved as a neutral antagonist in this experimental system in the sense that its binding was not sensitive to Gpp(NH)p in control animals (Fig. 4) and it did not inhibit background adenylate cyclase activity (2). To test the generality of this phenomenon [i.e., ligand affinity in the presence of Gpp(NH)p is affected by receptor density in an efficacy-dependent manner], we measured the affinity of some partial agonists (CLE and DOB) and some putative inverse agonists (PRO and TIM).

View larger version (26K): [in this window] [in a new window]   Fig. 4.   Competition binding isotherms of different adrenoceptor ligands in the absence () or presence () of Gpp(NH)p (0.1 mM) in membranes of control, Tg35, or Tg4 mice. The results are representative of three to five independent experiments.

View larger version (31K): [in this window] [in a new window]   Fig. 5.   Competition binding isotherms of ISO (A) and ICI 118551 (B) in the presence of Gpp(NH)p (0.1 mM) in membranes from control () or Tg4 () mice. The results are representative of three to five independent experiments. C, Shift in log(IC50) for the indicated ligands is given as the difference between log(IC50) values in control and Tg mice for each ligand. D, Extent of log(IC50) shifts in Tg4 mice for the indicated ligands given in increasing order of efficacy.

	Discussion

Summary Introduction Materials & Methods Results Discussion References

In this study, we examined ₂AR/G_s coupling by evaluating the coprecipitation of ₂AR and G_s and by determining the binding isotherms of agonists, neutral antagonists, and inverse agonists in heart membranes from control, Tg35, and Tg4 mice. The Tg35 and Tg4 mice seem to be useful experimental models in which to study the effect of overexpression of ₂AR on receptor/G protein coupling in heart. As expected, increased density of ₂AR in myocardial membranes of Tg35 and Tg4 mice led to an increased coprecipitation of ₂AR/G_s complexes. This is consistent with the previous observation that overexpression of ₂AR in the hearts of Tg mice increased adenylate cyclase activity in the absence of agonist stimulation (1). Thus, increased coprecipitation of ₂AR and G_s correlates with increased functional coupling between ₂AR and G_s.

Several models have been proposed to explain the phenomenology in the receptor/G protein coupling. Among many others, equilibrium approaches such as TCM, two-state TCM, cubic TCM, and quinternary complex model admit spontaneous activation of receptor and leads to a classification of receptor ligands as agonist, neutral antagonist, or inverse agonist depending on whether they increase, leave unchanged, or decrease spontaneous activity, respectively (7-10). Such properties of ligands are attributed to their "molecular efficacy," which is defined in a different manner in each model. However, the common property of molecular efficacy defined in these models can be expressed as the strength and direction of the overall allosteric linkage between the ligand binding process and the chemical reactions that lead to the active species. This linkage is formalized as an allosteric coupling factor in the case of TCM or two-state model or is decomposed into different coupling factors in case of the two-state TCM, cubic TCM, or quinternary complex model. These models have been successfully used to explain some ligand binding patterns observed in GPCRs.

The most characteristic observation in the binding of ligands to GPCRs may be the guanine nucleotide sensitivity of the binding of agonists but not of antagonists. In other words, by assuming that the binding of GTP to G opposes the binding of G to receptor, these models provide a sound explanation for the efficacy-dependent sensitivity of ligand binding to the presence of guanine nucleotides (7-10). The common scenario in this explanation can be stated as follows: if the ligand is an agonist, the ligand binding to the receptor is positively coupled to the binding of G protein to the receptor. Binding of a neutral antagonist or an inverse agonist to receptor is uncoupled or negatively coupled to the binding of G protein to the receptor, respectively. Thus, abolishing the binding of G to R by adding guanine nucleotides into the binding environment shifts the binding isotherms of efficacious ligands (agonist and inverse agonist) but not that of the neutral ligands (neutral antagonists). On the other hand, the above models predict a constant apparent ligand affinity with respect to the level of expression of receptor (i.e., its planar concentration) in the presence of guanine nucleotides. The current data, however, show that cardiospecific overexpression of ₂AR in heart membranes shifts the binding isotherm of ₂AR ligands in the presence of Gpp(NH)p in a manner that depends on the efficacy of the ligand. As the density of receptor increases in the membrane, the affinity for agonists (ISO, DOB, CLE), neutral antagonists (ALP, TIM), and inverse agonists (ICI 118,551, PRO) increase, remains constant, and decreases, respectively, despite the presence of Gpp(NH)p, which abolishes the binding of receptor to G protein. This observation is clearly inconsistent with predictions of the models discussed above; therefore, we suggest an extended model to accommodate the binding patterns observed in control and Tg mice.

Any model that intends to explain the current results should envision a receptor-concentration effect on ligand affinity that is dependent on the efficacy of the ligand. This, however, should be independent of the presence of a significant interaction between receptor and G protein. We therefore sought to explain the data and suggest two different models that are consistent with the data. The first one is a simple approach in which a membrane component (e.g., cytoskeleton, G subunit of the G protein, and so on) interacts with the receptor molecule. This interaction is linked to the ligand binding process; receptor, ligand, and a third component (X) in the membrane can form a ternary complex (HRX), on which H and X can interact in the same way as H and G interact on HRG except the stability of this complex (RX or HRX) is not disturbed by the guanine nucleotides. If we assume that the affinity for the formation of RX is low and the abundance of X is high compared with that of the receptor, then increasing the receptor number in the membrane may result in a shift in the ligand affinity depending on the direction and the magnitude of the allosteric coupling (say ) between X and the ligand. To accommodate the efficacy dependence of this effect, one needs to assume a perfect parallelism between  and the coupling factor  (molecular efficacy) that governs the allosteric linkage between H and G in the TCM. In other words, for agonist, neutral antagonist, or inverse agonist, both  and  should be >1, 1, or <1, respectively. Although  and  depend on the same ligand and receptor in two different complexes (i.e., HRG and HRX), they actually originate from the interaction of receptor with two different components (G and X, on which  and  depend, respectively). Therefore, and  need not be correlated in the above sense, which constitutes the weakest part of this model.

The second explanation is based on the hypothesis that the receptor protein can exist in two interconvertible allosteric states (R and R*), one of which is active (R*). This assertion constitutes the main idea behind the two-state TCM in which a part of the efficacy is defined as the ability of the ligand to shift the equilibrium between R and R*. This property of ligand action is given with a coupling factor () that links receptor isomerization to the ligand binding process (or vice versa). When this linkage is positive ( > 1), the ligand is an agonist. According to this model, an agonist tends to possess higher affinity as the fraction of R* in the receptor population increases. This property has been used to explain the efficacy-dependent binding characteristics of a constitutively active ₂AR mutant by assuming that the fraction of R* for the mutant is higher than it is for the wild-type receptor (8). Thus, a shift in the spontaneous equilibrium between R and R* (denoted as the stability constant J in the model) in favor of R* (i.e., increase in J) provides a sound explanation for the shifts in ligand affinities, the magnitude of which depends on the efficacy of the ligand, even in the absence of a significant interaction between receptor and G protein. In the current experiment, however, the internal structure of the receptor (which determines J) was not manipulated; instead, the number of receptors in the membrane was increased, which resulted in an efficacy-dependent shift in ligand affinity.

Therefore, it is impossible to apply the above explanation directly to the current situation because J is theoretically independent of the number (or concentration) of receptors. To accommodate the effect of receptor density on the ligand binding without losing the efficacy dependence of the action, we extended the two-state model into an interacting receptor population. In this model, the active receptors (R*) are allowed to interact with each other in equilibrium with a certain affinity. In this way, the concentration of the receptor directly determines the number of interacting receptors and, consequently, the fraction of R* in the receptor population. Such a process links the "apparent J" to the number of receptors (Fig. 6). This model also successfully predicts the current experimental data. In Fig. 7, the effect of receptor density on ligand binding is shown for an agonist ( > 1) and an inverse agonist ( < 1). We did not show the trivial result for a neutral antagonist ( = 1), in which receptor concentration had no effect on ligand binding. In Fig. 8, we show the effect of receptor density on the apparent affinities of ligands possessing different efficacies () in a wide range of receptor concentrations. We further extracted a range of receptor concentrations (2 orders of magnitude as in control and Tg4) from the original plot and present the data as the log differences from the initial affinities (Fig. 8). The latter picture is compatible with the experimental data depicted in Fig. 5C.

View larger version (15K): [in this window] [in a new window]   Fig. 6.   Dependence of apparent J on receptor concentration. Apparent J is calculated as the proportion of total R* (monomer plus dimer) to the inactive receptor R. Each curve is obtained using indicated (true) J values (stability constant of R  R* equilibrium) indicated in the plot. Dotted lines, prediction of the simple two-state model. The polymerization affinity (L) was 5 × 1010 and  = 1 for all curves. Thus, no allosteric effect was assumed in polymerization. Maximum number of receptor in a cluster (n) was 2. See text for a definition of the model and the parameters.

View larger version (22K): [in this window] [in a new window]   Fig. 7.   Effect of receptor concentration on the ligand binding predicted by the two-state receptor polymerization model. Receptor concentration ranges from 1011 to 107 M. Top,  values for agonist and inverse agonist. Affinity of ligands for the inactive receptor (K) is 107 M1 for all ligands and J = 0.1. All other parameters are as in legend for Fig. 6.

View larger version (26K): [in this window] [in a new window]   Fig. 8.   Effect of receptor concentration on the apparent affinity [log(IC50)] of the binding of ligands that possess different values. IC50 values are given as the log differences (shift) from the values that are obtained for the lowest concentration of receptor used.  values are decreasing logarithmically as indicated in the plots. Bottom, curves are reconstituted from a narrow range of receptor concentration (2 orders of magnitude) as indicated. IC50 values are given relative to the values obtained at the lowest concentration of receptor (9.5). The parameter values used in the simulation are L = 5 × 1010 M1, K = 107 M1, g = 1, J = 0.1, and n = 2. Compare with Fig. 5C.

In all simulations, we set n = 2 (i.e., the active receptor can only dimerize). Increasing the possible number of receptors in an aggregate affected only the shape of the dependencies between variables (e.g., receptor concentration and affinity shift) and did not change the general nature of the results (not shown). Therefore, we used the simplest case (n = 2) to simulate the experimental results, because the present data do not provide sufficient degrees of freedom to make a reliable estimation of n quantitatively by using the polymerization model.

As expected, the effect of polymerization on ligand binding is reciprocal; agonist binding increases the polymerization of the receptor when the concentration of the receptor is fixed (data not shown). Such an aggregation, in which increasing concentrations of GPCRs (including the ₂AR) form clusters, has been suggested in several studies (11, 12), and agonist has been shown to affect this clustering (13). Bacteriorhodopsin molecules, which are structurally similar to the ₂AR, can form a quasicrystal structure by interacting with each other when expressed at sufficiently large density in Halobacterium halobium membranes (14). This may indicate that receptors can cluster by interacting with each other or with a particular structure in the membrane. In a very recent study, it was shown that ₂ARs form homodimers in the cell membranes and that the presence of agonist or inverse agonist increases or decreases the stability of the dimeric state, respectively (15).

In conclusion, the current data show that the overexpression of ₂ARs in rat myocardium results in a G protein-independent shift in a positive or a negative direction, depending on the ligand efficacy, in apparent ligand affinity when the ligand is efficacious,. This phenomenon is explained by assuming an equilibrium interaction between activated receptors. Such a mechanism may be considered a part of the ₂AR-mediated signal transduction.