Real-time optical recording of β₁-adrenergic receptor activation reveals supersensitivity of the Arg389 variant to carvedilol

Antagonists of β-adrenergic receptors (β-ARs) have become a main therapeutic regimen for the treatment of heart failure even though the mechanisms of their beneficial effects are still poorly understood. Here, we used fluorescent resonance energy transfer–based (FRET-based) approaches to directly monitor activation of the β₁-AR and downstream signaling. While the commonly used β-AR antagonists metoprolol, bisoprolol, and carvedilol displayed varying degrees of inverse agonism on the Gly389 variant of the receptor (i.e., actively switching off the β₁-AR), surprisingly, only carvedilol showed very specific and marked inverse agonist effects on the more frequent Arg389 variant. These specific effects of carvedilol on the Arg389 variant of the β₁-AR were also seen for control of beating frequency in rat cardiac myocytes expressing the 2 receptor variants. This FRET sensor permitted direct observation of activation of the β₁-AR in living cells in real time. It revealed that β₁-AR variants dramatically differ in their responses to diverse beta blockers, with possible consequences for their clinical use.

Activation of cardiac β-adrenergic receptors (β-AR) by endogenous catecholamines plays a key role in the regulation of cardiac function. The heart contains at least 2 β-AR subtypes, termed β₁-AR and β₂-AR, and may also contain β₃-ARs (1). Stimulation of the β₁-AR represents the strongest endogenous mechanism for increasing contractility and beating frequency of the mammalian heart (1). In human heart failure, which has become one of the leading causes of death and hospitalization (2), the sympathetic nervous system is chronically activated to overcome the loss of cardiac output (3). While this initially leads to compensation through a short-term increase in cardiac function, chronic stimulation of the cardiac β-AR system contributes to progression of the disease (4, 5). These detrimental effects of chronic β-adrenergic signaling are attributed to the β₁-AR subtype. Transgenic mice with cardiomyocyte-specific expression of the β₁-AR develop progressive cardiac hypertrophy and heart failure in a manner similar to that seen in patients with heart failure (6). Consequently, the development of receptor antagonists (7) has resulted in the single most effective therapeutic regimen to treat heart failure (8).

Several common polymorphisms of the human β₁-AR have been identified. Most importantly, the Arg-Gly polymorphism at amino acid position 389 (9, 10) has been associated with cardiac disease (11). Position 389 is located near the seventh transmembrane domain of the receptor in the cytoplasmic tail, within a putative Gs protein–binding domain, corresponding to helix 8 in rhodopsin (12–14). In vitro experiments indicated greater stimulation of adenylyl cyclase activity through the Arg389 variant of the β₁-AR (10). Recent studies showed that the Arg389 polymorphism is associated with a poor prognosis in heart failure (15) and predisposes to hypertension (16). Moreover, patients carrying both the Arg389 variant of the β₁-AR and a deletion variant of the presynaptic α_2c-AR receptor had a greatly enhanced risk of developing heart failure (11).

While all these data confirm the concept that chronic β₁-AR signaling is detrimental, it is currently unclear how patients with an inherently hyperfunctional β-AR system should be treated and what substances are effective.

Contradictory results have been reported regarding whether the 389 polymorphism determines the sensitivity of the response to beta blocker treatment (for reviews, see refs. 17–19). While some studies found that the presence of the Arg389 allele of the β₁-AR is associated with a greater heart rate or blood pressure response to beta blockers (15, 20–24), others found no association (25–27). These discrepancies may be attributed to the relatively small sizes of the cohorts and the complex and highly regulated physiological parameters that were studied.

To overcome these limitations, we developed a fluorescent resonance energy transfer (FRET) approach to record directly and in real time the conformational changes of the receptor protein that lead to its activation. Based on the resonance energy transfer between fluorophores of overlapping emission spectra, FRET has evolved to become a potent method of studying protein-protein interactions and also, increasingly, dynamic conformational changes within proteins (28, 29). To study G protein–coupled receptor signaling, sensors for receptor and G protein activation (30–33) as well as for the detection of various second messengers have been developed (34, 35). To determine the degree of activation of the β₁-AR in living cells in real time, we measured FRET between a mutant cyan fluorescent protein, Cerulean (Cer), fused to the carboxy terminus of the human β₁-AR and a yellow fluorescent protein (YFP) inserted into the third intracellular loop. A comparison of the activation characteristics of the 2 frequently occurring receptor polymorphisms Arg389 and Gly389 revealed substantial differences in the response of these receptor variants to beta blockers.

Functional characterization of the β₁-AR–FRET sensor. We generated a mutant β₁-AR into which the cyan- and yellow-emitting variants of GFP (Cer and YFP) were inserted at the C terminus and in the third intracellular loop of the receptor, respectively. This FRET receptor construct is referred to as the β₁-AR sensor (Figure 1A). Confocal microscopy showed that the β₁-AR sensor was well expressed and targeted to the cell membrane (Figure 1B). Signals recorded from single HEK293 cells expressing the β₁-AR sensor were then analyzed at emission wavelengths of 480 nm (Cer) and 535 nm (YFP) upon excitation at 436 nm (Cer excitation). Excitation at 436 nm resulted in significant emission at 535 nm, characteristic for FRET. Bleaching of the acceptor YFP with intense light at 480 nm, resulting in an 80% reduction of the 535 nm emission, caused an increase of the emission at 480 nm of 20%, indicating that the emission at 535 nm was indeed due to FRET (Figure 1C). The ratio F₅₃₅/F₄₈₀, where F₅₃₅ and F₄₈₀ are the emission intensities at 535 nm and 480 nm, respectively (corrected for spillover and direct excitation of YFP; refs. 30, 33), was used in subsequent experiments as a measure of FRET. We then investigated the effect of the endogenous agonist norepinephrine (NE) on the FRET signal of the β₁-AR sensor. Superfusion of transiently transfected HEK293 cells with 10 μM NE led to a simultaneous increase in Cer emission and decrease in YFP emission. This amounted to an average decrease of the F₅₃₅/F₄₈₀ FRET ratio by approximately 4% (Figure 1D). This loss of FRET reflects the agonist-induced receptor activation, as has been described for other receptor constructs (33, 36, 37) (Figure 1D).

Figure 1

Development of a β₁-AR–FRET sensor. (A) Overall transmembrane topology of recombinant β₁-AR (Gly/Arg389–β₁-AR sensor) constructs. Using a linker (GlyGlyGlyGlyGly), we fused the cDNA encoding the Cerulean variant of GFP (Cer, blue) (49) to the carboxy terminus of the β₁-AR (position 477). YFP (yellow) was introduced into the third intracellular loop of the β₁-AR at position 273. (B) Visualization of transiently expressed β₁-AR sensor in HEK293 cells by confocal microscopy. Original magnification, ×63. (C) Effect of photobleaching. Emission intensities of YFP (535 nm, yellow) and Cerulean (Cer, 480 nm, blue) were recorded simultaneously from single cells expressing β₁-AR sensor using fluorescence microscopy. Emission intensities were recorded before and after the acceptor fluorophore was photobleached by 5 minutes exposure to light at 480 nm. (D) Time-resolved changes of the FRET ratio F₅₃₅/F₄₈₀ in single HEK293 cells expressing the β₁-AR sensor. Emission intensities of YFP (535 nm, yellow trace), Cer (480 nm, blue trace), and the FRET ratio F₅₃₅/F₄₈₀ (red trace) were recorded simultaneously from single cells. The decrease in FRET ratio is representative of the activation of the β₁-AR. The small arrow indicates the start of superfusion of the cell with 10 μM NE.

We then investigated in detail how closely the β₁-AR–FRET sensor reflected the pharmacological and signaling characteristics of the wild-type receptor. Concentration-response curves of β₁-AR sensor activation for NE and isoproterenol (Iso) yielded half-maximal effective concentration (EC₅₀) of 1.8 ± 0.2 μM and 230 ± 40 nM, respectively (Figure 2A), which is similar to the wild-type receptor characteristics (K_i [NE] 3.6 μM; K_i [Iso] 220 nM) (38). The fast agonist-induced decrease of the FRET signal corresponding to activation of the receptor was rapidly and completely reversed upon application of the receptor antagonist propranolol. Propranolol had no effect on the basal FRET signal when it was applied alone (Figure 2B). Finally, we tested the capacity of the β₁-AR sensor to induce production of cAMP. HEK293 cells were cotransfected with the FRET-based cAMP sensor Epac1-camps and the β₁-AR sensor or with the unlabeled β₁-AR. To block endogenously expressed β₂-ARs, β₁-AR activation with Iso (1 nM) was carried out in the presence of the specific β₂-AR antagonist ICI 118551 (200 nM). We then determined FRET of Epac1-camps, which corresponds to cAMP production (34). As shown in Figure 2C, induction of cAMP production through the β₁-AR sensor closely resembled the signal of the unlabeled receptor with respect to both the kinetics and the extent of cAMP formation. This FRET signal must be entirely due to the cAMP sensor, as 1 nM Iso does not lead to detectable activation of the β₁-AR sensor (see Figure 2A) and also because the cAMP sensor is expressed at higher levels throughout the cytosol and yields a much higher FRET response compared with the β₁-AR sensor. To assess the expression levels of the 2 sensors, we used the YFP signal of Epac1-camps–expressing cells as compared with β₁-AR sensor–expressing cells (Epac1-camps YFP signal versus β₁-AR sensor YFP signal, 440 ± 460 versus 2290 ± 320 AU; n = 6 and 7, respectively). Together, these data indicate that the β₁-AR sensor is properly targeted to the cell surface and retains essential binding and signaling properties of the unlabeled receptor.

Figure 2

Characterization of the FRET sensor. (A) Concentration-response relation for the change in FRET in response to NE (filled squares) and Iso (open squares) in cells expressing the β₁-AR sensor (n = 4–6 per concentration and per group). (B) FRET signal caused by NE (10 μM; n = 10) is reversible by addition of the antagonist propranolol (Prop, 10 μM; n = 10) in HEK293 cells transiently expressing the β₁-AR sensor. (C) Comparison between the signaling properties of the β₁-AR sensor (n = 6) and the respective unlabeled receptor (n = 5) transiently expressed in HEK293 cells. cAMP detection was achieved using the Epac1-camps FRET sensor, and specific β₁-adrenergic stimulation was carried out by simultaneous application of ISO (1 nM) and the specific β₂-AR antagonist ICI 118551 (ICI; 200 nM). (D) Time-resolved changes in the FRET ratio F₅₃₅:F₄₈₀ of the β₁-AR sensor transiently expressed in HEK293 cells at various concentrations of NE. (E) Relationship between time activation constant (τ) and agonist concentration for the Gly389–β₁-AR sensor (filled circles; n = 6–14 per concentration) and for the Arg389–β₁-AR sensor (red circles; n = 5–8 per concentration). At low concentrations of agonist, τ values were directly proportional to the agonist concentration whereas at higher concentrations of agonist, the values approached a maximum of 60 ms. The Arg389 polymorphism did not affect the kinetics of receptor activation.

Dynamics of receptor conformational changes. Determination of FRET signals from single cells after agonist stimulation allowed the analysis of the activation kinetics of the β₁-AR (Figure 2, d and e). Under all conditions, the decrease of the FRET ratio followed a monoexponential time course and was thus fitted to the equation f(t) = A(1 – e^–t/τ), (e is the number of Euler) where f(t) is function of time, A is the magnitude of the signal, and τ is the time constant. Consistent with the law of mass action, increasing concentrations of agonist resulted in shorter activation times (Figure 2E). As shown in Figure 2E, under saturating conditions, the β₁-AR is activated with a time constant of about 60 ms. To determine whether the presence of YFP in the third intracellular loop of the receptor limits the speed of the conformational change, we generated a second β₁-AR sensor (β₁-AR–FlAsH) in which a short sequence of 6 amino acids (CCPGCC) was inserted into the third intracellular loop instead of YFP. This sequence specifically binds a small molecule (fluorescein arsenical hairpin binder, FlAsH) that becomes highly fluorescent after binding and allows the detection of FRET between Cer and FlAsH (36, 39). The FlAsH-based β₁-AR sensor also responded with a decrease of the FRET ratio and a similar time constant of receptor activation (57 ± 3 ms; n = 4) in response to agonist activation, suggesting sterically unhindered receptor activation kinetics of the β₁-AR sensor (data not shown).

Receptor polymorphisms’ impact on receptor conformational changes. To assess the potential role of the naturally occurring Arg389 variants of the β₁-AR in receptor activation, we generated an Arg389–β₁-AR sensor by point mutating position 389 of the β₁-AR sensor from glycine to arginine (see Figure 1A). Upon expression in HEK293 cells, both the Gly389–β₁-AR sensor and the Arg389–β₁-AR sensor showed equal expression levels as determined by radioligand binding (Gly389 versus Arg389, 2.1 ± 0.3 versus 2.2 ± 0.2 pmol/mg membrane protein; n = 4) as well as equal YFP intensity (Gly389 versus Arg389, 2292 ± 316 versus 2052 ± 183 AU; n = 7 and 9, respectively). The Arg389 variant displayed a slightly increased sensitivity to NE (EC₅₀ [Arg389]: 0.85 ± 0.1 μM; EC₅₀ [Gly389]: 1.83 ± 0.25 μM; Supplemental Figure 1A; supplemental material available online with this article; doi:10.1172/JCI30012DS1), with nearly identical time constants of activation for the 2 receptor variants (Figure 2E). NE and Iso induced similar changes in the receptor FRET signal (Supplemental Figure 1B) as well as cAMP formation (Supplemental Figure 1C) for the 2 receptor variants. This was not due to saturation of the Epac1 sensor, as adenylyl cyclase activation and phosphodiesterase inhibition significantly enhanced cAMP levels even after stimulation of the β₁-AR with a high concentration of Iso (100 nM) (Supplemental Figure 2A). In addition, we studied coupling of the β₁-AR to Gs. Again, we used a FRET-based approach based on a YFP-labeled G protein αs subunit, a cyan fluorescent protein (CFP)-labeled γ₂ subunit, and a nonlabeled β₁ subunit (30, 40) (Supplemental Figure 1D). HEK293 cells transfected with the unlabeled Gly389–β₁-AR or Arg389–β₁-AR and with Gαs-YFP, Gβ, and Gγ-CFP, respectively, were simultaneously stimulated with NE (100 μM) plus ICI 118551 (200 nM) to block β₂-ARs. No difference in β₁-AR–mediated Gs activation was observed between the 2 receptor variants (Supplemental Figure 1D). In addition, we determined the basal (i.e., in the absence of agonist) cAMP levels that the 2 receptor variants generated. Both variants exhibited the same basal Epac1-FRET signal calculated from cells expressing the Epac1-camps and the unlabeled β-AR receptor variants (Supplemental Figure 2B). Moreover, we assessed the maximal cAMP-generating capacity of the 2 receptor variants. To this end, we treated Gly389–β₁-AR transfected cells and Arg389–β₁-AR transfected cells with forskolin and the phosphodiesterase inhibitor IBMX (100 μM) (Supplemental Figure 2C). Both cell lines exhibited very similar maximal cAMP levels, confirming our previous notion (the validity of cAMP determination; see Supplemental Figure 2B) that the 2 receptor variants do not differ significantly with respect to their basal constitutive activity in terms of whole cell cAMP generation.

We then compared the FRET signals of the 2 variants due to several antagonists currently in clinical use (Figure 3). In contrast with the agonist, which induced a decrease in the FRET ratio, bisoprolol, metoprolol, and carvedilol led to an increase in the FRET ratio, i.e., an active change of the receptor conformation, suggesting inverse agonist behavior (37). Upon washout, the signals induced by these compounds were slowly reversed, which was compatible with their high affinity to the receptor and, consequently, slow dissociation. As equilibrium conditions regarding ligand receptor interactions cannot be reached within a feasible time frame for low ligand concentrations (Figure 2D), high concentrations of β-AR antagonists were studied. Compared with the modest increases of the β₁-AR–FRET signal induced by bisoprolol and metoprolol, carvedilol induced a more than 2-fold greater increase of the FRET signal of the Gly389–β₁-AR (Figure 3A). The 389-receptor polymorphism did not affect the response to metoprolol and bisoprolol, whereas Arg389-receptors responded more than 2-folds stronger to carvedilol than they did to metoprolol and bisoprolol.

Figure 3

Impact of receptor polymorphisms. (A) Receptor activation in cells expressing the Gly389–β₁-AR sensor (white bars) or the Arg389–β₁-AR sensor (red bars) after beta blocker application (100 μM metoprolol, bisoprolol, or carvedilol) (n = 5–13 per group). (B) Effects of beta blockers (100 μM) on cAMP levels in cells expressing the unlabeled Gly389–β₁-AR (white bars) or the Arg389–β₁-AR (red bars) (n = 8–12 per group). *P < 0.05, statistically significant differences. Biso, bisoprolol; meto, metoprolol; carv, carvedilol.

The differences observed at the receptor level became even more pronounced at the level of the second messenger cAMP, as measured with the cAMP sensor. Whereas bisoprolol and metoprolol induced no decreases of cAMP, carvedilol led to a marked reduction of basal cAMP (Figure 3B), and again, the Arg389 variant of the β₁-AR led to a much stronger basal cAMP reduction.

Studies in primary cardiomyocytes. We next studied the impact of the 389 polymorphism on cardiac rate control in primary cardiac myocytes (Figure 4). We employed adenoviral gene transfer to express equal levels of the 2 variants of the β₁-AR in primary rat cardiac myocytes (2.7 ± 0.2 pmol/mg for the Gly389 variant and 2.8 ± 0.4 pmol/mg for the Arg389 variant; n = 4 per group). Expression of the Arg389 variant led to a higher beating frequency compared with the Gly389 variant already under basal conditions. Cardiac myocytes carrying the Arg389 variant, but not those carrying the Gly389 variant of the β₁-AR, responded to the treatment with carvedilol (1 μM) with a significant reduction (25%) of the beating frequency. The absence of an effect of carvedilol on Gly389-transfected cardiomyocytes is in line with data examining cAMP formation after lower concentrations of carvedilol (data not shown). Under these conditions, only the Arg389, and not Gly389, of the β₁-AR, responded with a decrease of cAMP.

Figure 4

Supersensitivity of the Arg389–β₁-AR polymorphism to carvedilol. (A) Representative tracings of the beating frequency of cardiomyocytes infected with the Gly389–β₁-AR sensor or the Arg389–β₁-AR sensor before and after stimulation with carvedilol (1 μM). The number of beats per minute was determined from the digitized video images by an observer who was blinded to the experimental protocol. (B) Effect of carvedilol (1 μM) on the beating frequency of cardiomyocytes infected with LacZ, the Gly389–β₁-AR sensor, or the Arg389–β₁-AR sensor (5 independent cardiomyocyte isolations each, including 5–10 measurements for each of the 6 groups). **P < 0.01 and ***P < 0.001, statistically significant differences. Ctrl, control.

The β-AR has served as a prototypical receptor in the study of cellular signaling mediated by G protein–coupled receptors (41). Despite this receptor being among the most intensely studied G protein–coupled receptors, it has not been possible to assess the activation of the β₁-AR in a direct manner. Recently, the use of GFP-based FRET has allowed the direct optical recording of G protein–coupled receptor activation (33). Here, we have applied this technology to the human β₁-AR.

This first direct determination of conformational changes of the β₁-AR in living cells revealed several critical characteristics of this GPCR. The β₁-AR is activated at a high speed of approximately 60 ms, thereby resembling several neurotransmitter receptors (33, 36). We provide direct evidence that some beta blockers can induce a very distinct receptor conformation compared to that induced by agonists, which is compatible with inverse agonism at the β₁-AR. Of clinical relevance, the 2 most frequent variants of the β₁-AR (Gly389, 26% allele frequency, and Arg389, 74% allele frequency; ref. 10) differ dramatically in their response to beta blocker treatment, with the Arg389 variant being exquisitely sensitive to carvedilol.

We have investigated whether our β₁-AR–FRET sensor truly retained the behavior of the native receptor. Multiple lines of evidence indicate that this is the case. The β₁-AR sensor was properly targeted to the cell membrane; the vast majority of the FRET signal recorded thus derives from receptors in their native environment. The modified receptors displayed ligand binding affinities similar to those of the unlabeled receptor (38), and their signaling was entirely normal. As an additional control, to rule out the possibility that the activation kinetics of the receptor were not limited by the insertion of YFP into the third intracellular loop, we constructed a β₁-AR sensor, where the YFP was replaced by a 6–amino acid sequence, which allows the binding of a small fluorescent dye (FlAsH). FRET-based analysis of the activation kinetics of this FlAsH receptor showed exactly the same characteristics as the original β₁-AR sensor, effectively excluding a significant influence of the YFP located in the third intracellular loop. Taken together, our results demonstrate that our FRET sensors retain the essential properties of the parent β₁-AR.

The ability to directly assess the activation of the human β₁-AR was then employed to determine the effects of clinically used beta blockers on the receptor protein itself and on downstream signal transduction. Beta blockers are among the most effective therapeutic agents for the treatment of common cardiovascular disorders, such as hypertension, coronary artery disease, and heart failure (8). Three different substances (bisoprolol, carvedilol, and metoprolol) are currently used for the treatment of heart failure, and there is an ongoing debate over whether these substances differ as to their effectiveness and, if so, what the molecular basis of such differences might be (8). Based on second messenger data or complex parameters, such as force of contraction of isolated myocardial tissue, inverse agonist properties have been suggested by some and disputed by others (38, 42–44). The β₁-AR–FRET sensor allowed, for what we believe is the first time, the direct assessment of the effects of various β₁-AR antagonists on receptor conformational changes. We observed that all antagonists studied induced conformational changes (increase of FRET signal) opposite to those of agonist effects, indicating that this differential movement of different receptor domains after ligand binding represents the molecular basis for agonism and inverse agonism at the β₁-AR. Interestingly, the atypical beta blocker carvedilol was markedly more effective than metoprolol and bisoprolol both in inducing the inverse agonist conformation of the receptor protein and in decreasing basal cAMP levels.

These findings are in agreement with respect to the effect of carvedilol on heart rate control in Gly389–β₁-AR–expressing mice (45) as well as cAMP-formation in Gly389–β₁-AR–expressing cells (38). Inverse agonistic properties have been described for metoprolol and bisoprolol, which we cannot confirm with the present study (42, 44). Two recent studies assessed the impact of the 389 polymorphism on cardiac function in heart failure patients. While one study associated the Arg389 polymorphism with the beneficial effects of carvedilol (15), a second study found no significant association (46).

However, these studies often investigated very complex systems, such as human tissue with highly variable catecholamine concentrations from heart failure patients, tissue from patients with unknown receptor polymorphism status, and cell lines or transgenic mice with long-term overexpression of the β-AR. In contrast, our current study is the first, to our knowledge, to directly assess the impact of various beta blockers on the conformational change of the β₁-AR.

This study identified a unique property of carvedilol, which is likely to become clinically relevant. When we directly assessed how the most frequent receptor polymorphism influenced intrinsic properties of receptor activation, we found a dramatic hypersensitivity of the Arg389 variant to carvedilol. The Arg389 variant of the human β₁-AR, which is present in the majority of individuals, displayed a 2-fold greater response to carvedilol than the so-called wild-type Gly389, which really is the second most frequent 389 variant. This pronounced change in receptor conformation transduced into downstream functional effects, as we found in experiments determining myocyte beating rate. In this physiologically relevant model, we also saw an enhanced beating frequency in cells expressing the Arg389 variant of the β₁-AR under basal conditions, which is in line with a previous study (10). Thus, while we did not find a significantly enhanced capacity of the Arg389–β₁-AR variant to form cAMP under basal conditions in HEK cells (Supplemental Figure 2), expression of the 2 receptor variants in primary rat cardiomyocytes revealed differences as to their chronotropic effect. This is most likely due to the cardiomyocyte environment, where localized submembrane cAMP has been shown to regulate channel activity (47, 48), but cannot yet be resolved by Epac1-camps determination.

Both metoprolol and bisoprolol did not markedly affect cAMP of Arg389-β₁-AR–expressing cells. Thus, carvedilol appears to be unique in its ability to suppress the chronically enhanced basal signaling of the Arg389 variant of the β₁-AR. This finding is potentially of great clinical importance, as the presence of the Arg389 polymorphism has been suggested as determining a poor prognosis in heart failure patients.

The present data show, for what we believe is the first time, real-time measurements of β₁-AR activation in living cells and provide evidence for supersensitivity of the frequent Arg389 variant of the β₁-AR toward carvedilol. It will be interesting to investigate whether patients carrying the Arg389 polymorphism may benefit most from treatment with carvedilol as opposed to other beta blockers.

View Supplemental data

These studies were funded by the Rudolf-Virchow-Center/DFG–Research Center for Experimental Biomedicine, supported by the Deutsche Forschungsgemeinschaft, ProCorde/Trigen, Sanofi-Aventis, and the Bavarian Ministry of Economics. We would like to thank the Foundation Leducq for generously supporting this project. F. Rochais was supported by a fellowship of the Bayerische Forschungsstiftung. The expert technical assistance of Silke Oberdorf-Maass, Nadine Hemmrich, and Ursula Keller is gratefully acknowledged. We would like to thank Gisbert Sponer for advice on carvedilol and Carsten Hoffmann for advice on FlAsH.

Address correspondence to: Stefan Engelhardt, Rudolf-Virchow-Center, DFG–Research Center for Experimental Biomedicine, University of Würzburg, Versbacher Strasse 9, 97078 Würzburg, Germany. Phone: 49-931-201-48710; Fax: 49-931-201-48539; E-mail: stefan.engelhardt@virchow.uni-wuerzburg.de.

Nonstandard abbreviations used: β-AR, β-adrenergic receptor; Cer, Cerulean: cyan-emitting variant of GFP; CFP, cyan fluorescent protein; EC₅₀, half-maximal effective concentration; FlAsH, fluorescein arsenical hairpin binder; FRET, fluorescent resonance energy transfer; Iso, isoproterenol; NE, norepinephrine; YFP, yellow fluorescent protein.

Conflict of interest: The authors have declared that no conflict of interest exists.

Reference information: J. Clin. Invest.117:229–235 (2007). doi:10.1172/JCI30012

Jean-Pierre Vilardaga’s present address is: Simches Research Center, Program in Membrane Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

See the related article at Beta blocker specificity: a building block toward personalized medicine.

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