Ligand-specific activation trajectories dictate GPCR signalling in cells

Thomas, Romy; Jacoby, Pauline S.; De Faveri, Chiara; Derieux, Cécile; Liebing, Aenne-Dorothea; Melkes, Barbora; Martini, Hans-Joachim; Bermúdez, Marcel; Stäubert, Claudia; Lohse, Martin J.; Coin, Irene; Bock, Andreas

doi:10.1038/s41586-025-09963-3

Download PDF

Article
Open access
Published: 14 January 2026

Ligand-specific activation trajectories dictate GPCR signalling in cells

Nature (2026)Cite this article

28k Accesses
74 Altmetric
Metrics details

Subjects

Abstract

G-protein-coupled receptors (GPCRs) are key mediators of cell communication and represent the most important class of drug targets^1,2. Biophysical studies with purified GPCRs in vitro have suggested that they exist in an equilibrium of distinct inactive and active states, which is modulated by ligands in an efficacy-dependent manner^{3,4,5,6,7,8,9,10,11}. However, how efficacy is encoded and whether multiple receptor states occur in living cells remain unclear. Here we use genetic code expansion¹² and bioorthogonal labelling^13,14,15,16 to generate a panel of fluorescence-based biosensors for a prototypical GPCR, the M₂ muscarinic acetylcholine receptor (M₂R). These biosensors enable real-time monitoring of agonist-promoted conformational changes across the receptor’s extracellular surface in intact cells. We demonstrate that different agonists produce equilibria of at least four distinct active states of the G-protein-bound M₂R, each with a different ability to activate G proteins. The formation of these M₂R–G-protein complexes occurs over 0.2–5 s along trajectories that involve both common and ligand-specific conformational changes and appear to determine G-protein selectivity. These observations reveal the molecular nature of ligand efficacy in intact cells. Selectively exploiting such different GPCR activation trajectories and conformational equilibria may open new avenues for GPCR drug discovery.

GPCR activation mechanisms across classes and macro/microscales

Article Open access 10 November 2021

Structural and dynamic insights into supra-physiological activation and allosteric modulation of a muscarinic acetylcholine receptor

Article Open access 23 January 2023

Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery

Article 02 January 2025

Main

Activation of cell surface receptors by extracellular ligands is the hallmark of cell–cell communication and controls most physiological functions in humans. GPCRs are the largest class of such receptors^1,2. After ligand activation, GPCRs communicate their message into cells by recruiting and activating intracellular G proteins¹⁷. GPCR ligands can activate (agonist) or inactivate (antagonist/inverse agonist) receptors to various extents, and this diversity in ligand efficacy is exploited in drug therapy¹⁸. However, the molecular nature of ligand efficacy and the mechanisms of GPCR activation in living cells remain largely unclear.

Fluorescence spectroscopy studies with purified β₂-adrenergic receptors^19,20,21,22, and more recent nuclear magnetic resonance (NMR) and double electron–electron resonance (DEER) spectroscopy studies, have established that GPCRs do not operate as simple on/off switches but exist in a dynamic equilibrium of multiple inactive and active states^3,4,23,24,25. Partial agonists are believed to stabilize conformational states that are structurally different from those stabilized by full agonists^6,11,26,27. Likewise, single-molecule Förster resonance energy transfer (FRET) and advanced NMR spectroscopy studies have demonstrated that GPCRs can form distinct signalling complexes with G proteins^28,29, in which the G proteins may possess different nucleotide affinities^5,7. Partial agonists have been proposed to stabilize GPCR–G-protein complexes with reduced efficacy towards nucleotide exchange^5,7,30,31. However, all of these studies were performed in isolated systems using purified receptors reconstituted in detergent micelles or nanodiscs. Whether GPCRs in the physiological environment of a living cell also adopt different conformations and form distinct signalling complexes is essentially unclear.

Here we develop a new type of conformational GPCR biosensors to probe the existence and ligand modulation of such GPCR–G-protein-signalling complexes in intact cells. Using the M₂R as a model, we demonstrate that agonist activation leads to formation of an equilibrium of distinct GPCR signalling complexes along ligand-specific activation trajectories. These distinct activation trajectories and the relative abundances of these distinct receptor–G-protein complexes dictate the type and extent to which specific G proteins are activated.

Development of GPCR biosensors

GPCR activation results in large-scale receptor conformational changes^{1,32,33,34,35}. Most prominently, outward movement of the intracellular part of transmembrane domain 6 enables coupling to and activation of G proteins. In turn, G-protein binding promotes conformational changes in the receptor, including its extracellular domains and the ligand-binding pocket, which stabilize agonist binding^1,32,36. This communication between extra- and intracellular receptor domains represents the principle of allosteric coupling.

To track conformational changes at the extracellular surface of GPCRs at a high spatial resolution, we sought to develop a new type of biosensor. These biosensors should be genetically encoded, equipped with minimally sized labels (similar to those used in NMR, DEER and single-molecule FRET studies on isolated receptors) and retain an unmodified intracellular surface to preserve G-protein coupling. We chose the M₂R as a model because structural studies have shown that its extracellular conformational changes on activation, including closure of the binding pocket, are the most pronounced among all class A GPCRs of which the structures have been solved^36,37,38,39.

The least invasive way to attach probes to a GPCR at the single-residue resolution in living cells is by bioorthogonal chemistry on genetically encoded chemical anchors^12,13,14,15. In brief, a non-canonical amino acid (ncAA), also known as an unnatural amino acid, carrying an anchor for rapid catalyst-free labelling is incorporated into the receptor using genetic code expansion technology (GCE). The label is then attached post-translationally by ultrarapid strain-promoted inverse electron-demand Diels–Alder cycloaddition, which occurs within minutes without interfering with native functional groups. Using this strategy, we previously demonstrated quantitative labelling of GPCRs on the live cell surface⁴⁰.

We screened the entire extracellular surface of the M₂R to identify positions at which the click-ncAA trans-cyclooct-2-ene lysine (TCO*K)⁴¹ was efficiently incorporated and yielded robust labelling with a cell-impermeable, tetrazine-conjugated cyanine dye (Tet–Cy3) (Fig. 1a). Of 72 receptor mutants, 25 displayed good cell surface expression and labelling (Extended Data Fig. 1). The other 47 constructs were not expressed, not trafficked to the cell surface or showed no labelling at all (Fig. 1b and Supplementary Fig. 1). As a control, labelling in the absence of TCO*K produced no fluorescence (Supplementary Fig. 2).

**Fig. 1: An extracellular single-colour conformational GPCR biosensor panel.**

Next, we applied the endogenous M₂R agonist acetylcholine (ACh) to single cells expressing one labelled construct each using a superfusion device (Fig. 1a). Seven of the 25 Cy3-TCO*K-M₂R constructs exhibited robust and reproducible changes in their fluorescence emission intensities (Fig. 1c,d), therefore serving as reporters for M₂R activation. We quantified the labelling efficiency at these M₂R biosensors using fluorescence correlation spectroscopy^40,42. Four M₂R biosensors showed quantitative Cy3 labelling (positions Thr84 (M₂R⁸⁴), Glu175, Ala414 and Pro415) and three reached labelling efficiencies of 60–80% (positions Phe181, Phe188 and Asn419; Extended Data Fig. 1). Importantly, all seven M₂R biosensors robustly activated G proteins and internalized after ACh exposure, indicating full functionality (Extended Data Fig. 2). Notably, labelling position Ala414 with either the rhodamine dye TAMRA or the cyanine dye Cy5 also resulted in M₂R activation biosensors (Supplementary Fig. 3).

Cyanine fluorophores such as Cy3 are environmentally sensitive^23,42,43. We propose that the observed fluorescence changes arise from local microenvironmental changes (such as transitions to either more hydrophobic or to more polar microenvironments) caused by ligand-promoted receptor conformational changes. Mapping the position of ACh-sensitive labels onto high-resolution structures of the inactive and active M₂R (Fig. 1e) shows that all positions featuring ACh-promoted fluorescence changes lie in extracellular receptor domains that move during receptor activation^37,38,39. All seven biosensors retain the ability to respond to the positive allosteric modulator LY2119620 (ref. ³⁸), which binds at the extracellular allosteric binding site (Extended Data Fig. 3). Thus, we infer that the M₂R biosensors report on activation-related conformational changes of the receptor. Supporting this, binding of the antagonist N-methylscopolamine did not induce fluorescence changes at any of these positions (Extended Data Fig. 2).

ACh-stimulated fluorescence changes varied in both direction (fluorescence increase or decrease) and amplitude (ΔF/F₀, −16% to +10%) (Fig. 1c,d and Supplementary Table 1). All changes were strictly dependent on the presence of ACh and returned to the baseline after ACh washout (Fig. 1c). Moreover, ACh-mediated changes in fluorescence were also concentration dependent, with potencies matching reported ACh affinity values (around 1–6 µM; Extended Data Fig. 4), which further supports the specificity of the observed effects.

Ligand-unique conformational states of the M₂R

The M₂R biosensor panel enables monitoring receptor conformational changes across the entire extracellular surface (Fig. 1e) while leaving the intracellular domains, which couple to G proteins, untagged. This makes it an ideal tool for investigating the existence of distinct, ligand-specific GPCR active states and their coupling to G proteins in intact cells. To study agonist effects, we selected M₂R agonists differing in their reported efficacies in classical pharmacological assays: the endogenous full agonist ACh, the superagonist iperoxo^39,44,45,46, and the partial agonists arecoline and pilocarpine. All of the agonists stimulated G-protein activation at all seven biosensors in a concentration-dependent manner, similar to wild-type (WT) M₂ receptors (Extended Data Fig. 5). We noted that higher agonist potency tended to correlate with a smaller dynamic range of the functional response (Extended Data Fig. 4i). This would be compatible with the notion that some biosensors might display slightly different spontaneous activity compared with WT M₂ receptors. Only at the M₂R¹⁸¹ biosensor were all of the agonists less potent and less efficacious. Nonetheless, the rank order of agonist potencies and efficacies at all biosensors matched WT receptors (Extended Data Fig. 5 and Supplementary Table 2). This demonstrates that conformational data obtained with the panel of biosensors can be projected to WT receptors.

Stimulation of the M₂R biosensor family with a saturating concentration of iperoxo changed fluorescence emission at six out of the seven ACh-responsive M₂R biosensors (Fig. 2 and Extended Data Fig. 6). Compared with ACh, iperoxo produced larger responses at five biosensors (M₂R⁸⁴, M₂R¹⁷⁵, M₂R⁴¹⁴, M₂R⁴¹⁵ and M₂R⁴¹⁹), but smaller fluorescence changes at the M₂R¹⁸⁸ biosensor. Notably, the M₂R¹⁸¹ biosensor did not respond at all (Fig. 2a,b and Extended Data Fig. 6) at any of the sequences of agonist addition (Supplementary Fig. 4). Absolute ΔF/F₀ amplitudes after iperoxo exposure (Fig. 2b and Supplementary Table 1) were normalized to ACh at each M₂R biosensor and plotted in a radar plot (Fig. 2c), irrespective of signal direction. We define this visualization of agonist-specific conformational changes of the receptor as the ligand’s conformational fingerprint (Fig. 2c).

**Fig. 2: The M₂R biosensor panel uncovers agonist-specific conformational fingerprints in intact cells.**

The conformational fingerprints of arecoline (Fig. 2f) and pilocarpine (Fig. 2i) differed markedly from those of ACh and iperoxo. Arecoline induced smaller fluorescence changes compared with ACh at all positions (Fig. 2d,e, Extended Data Fig. 6 and Supplementary Table 1). Notably, arecoline activation of M₂R⁸⁴ and M₂R¹⁷⁵ biosensors caused a decrease in fluorescence, in contrast to the increase observed with ACh (Fig. 2d,e and Extended Data Fig. 6). For pilocarpine, M₂R¹⁸¹ and M₂R¹⁸⁸ showed more-pronounced changes in fluorescence compared with ACh, while all of the other biosensors reported significantly smaller changes than with ACh (Fig. 2g,h and Extended Data Fig. 6).

Comparison of the radar plot conformational fingerprints (Fig. 2c,f,i) enables general conclusions: conformational changes at most agonist-sensitive receptor positions (84, 175, 414, 415, 419) scale directly with agonist efficacies, and are largest with the superagonist iperoxo. By contrast, conformational changes at M₂R¹⁸¹ and M₂R¹⁸⁸ biosensors are inversely correlated with agonist efficacies, and are largest with the low-efficacy partial agonist pilocarpine (Fig. 2i). At M₂R¹⁸¹, the superagonist iperoxo does not induce changes in fluorescence intensity at all (Fig. 2c).

These data cannot be explained by a simple two-state model of one inactive and one active receptor conformation. Instead, they suggest the existence of an ensemble of distinct active states of the M₂R in intact cells, consistent with a recent NMR study on purified M₂R receptors²⁴.

Distinct receptor–G-protein complexes

The observation that the extent of conformational changes elicited by agonist activation scales directly with agonist efficacy at some receptor positions but inversely at others suggests that the M₂R adopts multiple active states in living cells, which differ in their ability to stimulate G-protein signalling. To probe the existence of such distinct M₂R–G-protein complexes, we manipulated the equilibrium between different states by increasing G-protein coupling. To shift the receptor equilibrium toward a high-efficacy, high-affinity M₂R–G-protein complex, we overexpressed the Gα_oA(G203T) mutant. This Gα mutant features low affinity towards both GDP and GTP^47,48, and its coupling to agonist-bound receptors yields stable nucleotide-free receptor–Gα_oA-protein complexes⁴⁸. Indeed, comparison of maximal fluorescence changes (relative to ACh) between the individual agonists after Gα_oA(G203T) overexpression reveals differences to the efficacy rank order of agonists in the presence of the endogenous G-protein repertoire of the cell (Supplementary Fig. 6). This is direct evidence that the equilibrium of different receptor states is altered by the presence of the Gα_oA(G203T) mutant.

We compared relative fluorescence changes across all seven M₂R biosensors in presence of the endogenous G-protein repertoire of HEK293 cells and after Gα_oA(G203T) overexpression (Fig. 3). All of the M₂R biosensors except for the biosensor M₂R⁴¹⁹ (Supplementary Fig. 5) were sensitive to Gα_oA(G203T) overexpression, but the responses strongly depended on both the ligand and the tested biosensor (Fig. 3). According to the principle of allosteric coupling, the conformational changes of the M₂R induced by coupling to Gα_oA(G203T) are expected to mirror those initiated by agonist binding from the extracellular side. With G-protein overexpression, these changes occur before agonist addition. As a result, agonist stimulation of biosensors indicating the formation of the high-efficacy M₂R–G-protein complex would result in reduced or no changes in fluorescence emission intensities.

**Fig. 3: M₂ receptor activation results in an equilibrium of distinct M₂R–G-protein signalling complexes in intact cells.**

Most prominently, and for all agonists tested, Gα_oA(G203T) overexpression resulted in a complete loss of agonist-induced changes in fluorescence at the M₂R¹⁷⁵ biosensor (Fig. 3a,c). At many class A GPCRs, formation of the high-affinity complex between a nucleotide-free G protein and the receptor entails conformational rearrangements of extracellular receptor domains^1,8,32,36. In the extreme case, this can result in a complete closure of the ligand-binding pocket, which limits agonist association and dissociation, therefore increasing the lifetime of the high-affinity complex^36,37,38,39. Although not providing direct atomic-level structural insights, our data strongly suggest that the biosensor M₂R¹⁷⁵ indicates conformational changes of the extracellular loops involved in the formation of the high-affinity receptor–G-protein complex. In support of this conclusion, Ala mutation of Tyr426, a key residue involved in this lid closure, led to a complete loss of ACh-induced fluorescence changes in the M₂R¹⁷⁵ biosensor (Extended Data Fig. 7). Furthermore, this is corroborated by the fact that, under endogenous G-protein levels, the fluorescence changes at the M₂R¹⁷⁵ biosensor increase with the efficacy of the agonist (Fig. 2). Similar to the loss of signal at the M₂R¹⁷⁵ biosensor, the changes in fluorescence at the M₂R⁴¹⁵ (Fig. 3b) were reduced by around 30–80% in the presence of overexpressed Gα_oA(G203T) (Fig. 3b,c).

By contrast, for most ligands, Gα_oA(G203T) overexpression resulted in a significant increase in fluorescence emission at M₂R¹⁸¹ (Fig. 3d) and M₂R¹⁸⁸ (Fig. 3e,f) compared with the endogenous G-protein condition. This suggests that the conformational changes induced by receptor coupling to Gα_oA(G203T) at these positions are different from those induced by the agonists alone. This effect was most pronounced for the high-efficacy agonists than for the partial agonists (Fig. 3f). Notably, although iperoxo did not induce any response at the M₂R¹⁸¹ biosensor at endogenous G-protein levels (Fig. 2a–c), it did so in the presence of Gα_oA(G203T) (Fig. 3d–f). Thus, the increase in agonist-promoted changes in fluorescence at M₂R¹⁸¹ (Fig. 3d) and M₂R¹⁸⁸ (Fig. 3e) in the presence of overexpressed Gα_oA(G203T) likely unmasks the stabilization of a M₂R–G-protein complex that is distinct from the one revealed by the loss or decrease of responses at the M₂R¹⁷⁵ and M₂R⁴¹⁵ biosensors.

To determine whether this distinct complex may have low signalling efficacy, we increased the abundance of GDP-bound M₂R–G-protein complexes by pretreating the cells with pertussis toxin (PTX) overnight. Through ADP-ribosylation of Gα_i/o subunits, PTX locks the α subunits of endogenous G_i/o proteins into an inactive GDP-bound state⁴⁹, which hampers productive coupling between receptors and G proteins. In contrast to the effects of Gα_oA(G203T) overexpression, pretreatment with PTX completely abolished the fluorescence intensity changes at the M₂R¹⁸¹ biosensor induced by ACh and arecoline and significantly decreased the pilocarpine-promoted effect (Extended Data Fig. 8). On the basis of these findings, we propose that these biosensors indicate a low-efficacy, likely GDP bound, M₂R–G-protein signalling complex. This is consistent with biophysical experiments using purified proteins in vitro, which suggest the existence of such low-efficacy, GDP-bound receptor complexes at agonist-bound β₂ARs^5,11,50, A₂A receptors^6,7,31 and μORs⁵¹.

The effects of Gα_oA(G203T) overexpression on two other biosensors, M₂R⁸⁴ and M₂R⁴¹⁴, were more heterogeneous and varied strongly with the efficacy of the ligand. Specifically, at M₂R⁸⁴, Gα_oA(G203T) overexpression reduced ligand-promoted fluorescence changes compared with endogenous G-protein levels for all of the tested agonists except arecoline (Fig. 3g,i). The unique behaviour of arecoline is further highlighted by the experiments at endogenous G-protein levels (Fig. 2d,e), where arecoline stimulation resulted in fluorescence intensity changes in the opposite direction compared with all of the other tested ligands.

The M₂R⁴¹⁴ biosensor responded to agonist exposure in a strongly ligand efficacy-dependent manner when the Gα_oA(G203T) mutant was overexpressed (Fig. 3h,i). Similar to the effects observed with the M₂R⁸⁴, M₂R¹⁷⁵ and M₂R⁴¹⁵ biosensors, ACh- and iperoxo-promoted fluorescence changes were diminished relative to endogenous G-protein levels, whereas those of the partial agonists arecoline and pilocarpine were increased (Fig. 3h,i).

In summary, the Gα_oA(G203T) overexpression data suggest the existence of at least two functionally distinct M₂R–G-protein complexes at steady state.

Kinetics of the formation and dynamics of M₂R–G-protein complexes

To assess whether evidence for distinct M₂R–G-protein complexes can also be inferred from the kinetics of the various biosensors, we analysed the time course of their agonist-promoted fluorescence changes. The apparent on-rates of the fluorescence changes promoted by the high-efficacy agonists ACh and iperoxo at the six G-protein sensitive M₂R biosensors lie in the range of 170–2,700 ms (Extended Data Fig. 9a) and 340–3,200 ms (Extended Data Fig. 9b), respectively (Supplementary Table 3). These on-rates are much slower than those obtained with previous intracellular GPCR biosensors (on-rates ≈ 30–50 ms) that were used to monitor activation kinetics⁵². Importantly, the on-rates for the extracellular GPCR biosensors described here agree very well with the kinetics of GPCR-mediated G-protein activation (on-rates ≈ 500–1,000 ms)⁵². Consistent with this, overexpression of Gα_oA(G203T) further increases the apparent on-rates for the vast majority of agonists and biosensors (Extended Data Fig. 9 and Supplementary Table 3). Thus, the conformational changes that we record at the extracellular surface of the receptor probably result from intracellular G-protein coupling, further corroborating that our panel of GPCR biosensors monitors conformational changes in GPCR–G-protein signalling complexes.

By inspecting these rates more closely, we can distinguish two groups of biosensors: one group comprising the M₂R⁸⁴, M₂R⁴¹⁴, M₂R⁴¹⁵ and M₂R¹⁷⁵ biosensors, which displayed the fastest on-kinetics between 160–530 ms (for ACh) and 340–1,000 ms (for iperoxo), and the other group including the M₂R¹⁸¹ and M₂R¹⁸⁸ biosensors, with apparent on-rates of more than 1 s (for ACh) and approximately 3 s (for iperoxo at M₂R¹⁸⁸) (Extended Data Fig. 9a,b). Notably, iperoxo appeared to divide the group of M₂R⁸⁴, M₂R⁴¹⁴, M₂R⁴¹⁵ and M₂R¹⁷⁵ biosensors further into two subgroups (Extended Data Fig. 9b).

Different kinetic patterns were observed when the biosensors were activated with the partial agonists arecoline and pilocarpine. Specifically, on-rates after activation with arecoline yielded three groups of M₂R biosensors: fast biosensors (M₂R⁸⁴, M₂R¹⁷⁵ and M₂R⁴¹⁵; on-rate ≈ 300 ms), an intermediate biosensor (M₂R⁴¹⁴; on-rate ≈ 900 ms) and slow biosensors (M₂R¹⁸¹ and M₂R¹⁸⁸; on-rate ≈ 2 s) (Extended Data Fig. 9c and Supplementary Table 3). Finally, kinetic analysis of pilocarpine-stimulated conformational changes revealed two groups of M₂R biosensors, which reported receptor conformational changes on significantly different timescales. As seen with ACh and iperoxo, pilocarpine triggered fast conformational changes at the M₂R¹⁷⁵, M₂R⁴¹⁴ and M₂R⁴¹⁵ biosensors with apparent on-rates between 180 and 330 ms (Extended Data Fig. 9d). However, in contrast to what was observed with all other agonists, pilocarpine-stimulated conformational changes reported by M₂R⁸⁴ occurred on the same slow timescale as those reported by M₂R¹⁸¹ and M₂R¹⁸⁸ (Extended Data Fig. 9d).

Overall, the kinetic analysis of receptor conformational changes (Extended Data Fig. 9) yielded the same groups that we identified by modulating the activity state of the G protein (Fig. 3): the fast responders include M₂R¹⁷⁵ and M₂R⁴¹⁵ sensors, which report on the formation of the high-efficacy complex, whereas M₂R¹⁸¹ and M₂R¹⁸⁸, which indicate the formation of the low-efficacy complex, responded slower. This strongly corroborates the notion that the activated M₂R can form a minimum of two G-protein signalling complexes in intact cells that differ in their signalling efficacies and suggests that these complexes form at different timepoints. Moreover, the patterns of on-rates suggest that these complexes form along different activation trajectories depending on the type of agonist. In the case of ACh, iperoxo and pilocarpine, activation of the receptor results first in the formation of a high-efficacy GPCR signalling complex (complex 1, C1), primarily indicated by increases in fluorescence at position 175 (and fluorescence decreases at positions 414 and 415) (Figs. 2–4). This process takes about 200 ms to 1 s, depending on the agonist (Fig. 4 and Extended Data Fig. 9). A second, low-efficacy, GPCR signalling complex (C2) forms then after around 2–5 s and is indicated by decreases in fluorescence at positions 181 and 188 (Fig. 4). Modulation of the activity state of the G protein (Fig. 3) has clearly demonstrated that C1 and C2 co-exist in an equilibrium; however, it remains unclear whether C2 develops from C1 or whether C1 and C2 form in parallel.

**Fig. 4: Ligand-specific activation trajectories and equilibria of M₂R–G-protein signalling complexes.**

In addition to the two common receptor signalling complexes C1 and C2, there are important ligand-specific differences: compared with ACh, iperoxo stabilizes a greater fraction of C1 (Figs. 2 and 4). Moreover, iperoxo-activated receptors appear to reach C1 through an intermediate state that forms earlier (300–500 ms) and is indicated by fluorescence changes exclusively at positions 414 and 415 (C1^#). Furthermore, the iperoxo-stabilized complex 2 (C2_ixo) forms to a much smaller extent compared with ACh; and C2_ixo is highly distinct as its stabilization does not involve any conformational rearrangements at position 181. Pilocarpine stabilizes C1 to a much smaller extent than ACh and its formation does not involve fast conformational changes at position 84 (Fig. 4). Furthermore, pilocarpine stabilizes C2 most effectively, which is indicated by the largest conformational changes at positions 181 and 188 among all of the tested agonists (Figs. 2 and 4).

By contrast, arecoline-mediated receptor activation follows a unique trajectory that is highly distinct from the other three agonists (Fig. 4). Arecoline activation stabilizes first the formation of a high efficacy signalling complex (C3) that is primarily characterized by decreases, rather than increases, in fluorescence at positions 84 and 175 (Figs. 2 and 4). This complex forms in about 900 ms through an intermediate state C3^# (Fig. 4). Formation of the low-efficacy signalling complex (C4) takes approximately 2 s and involves fluorescence decreases at positions 181 and 188 that are significantly larger than the ones resulting from ACh activation but smaller than those induced by pilocarpine (Fig. 4).

Equilibria of complexes define ligand efficacy

Our data (Figs. 2–4) have collectively demonstrated that all agonists stabilize the formation of at least two distinct M₂R–G-protein signalling complexes in intact cells at steady state. Common to all agonists is the observation that these signalling complexes co-exist in an equilibrium and feature different efficacies towards G-protein signalling (Fig. 3). However, depending on the specific agonist, the formation of the GPCR signalling complexes occurs at different timescales and follows distinct trajectories (Fig. 4 and Extended Data Fig. 9) that involve ligand-unique conformational changes of the receptor (Fig. 2). Moreover, the position of the signalling-complex equilibrium is highly ligand dependent (Fig. 4).

To assess whether this conformational complexity dictates which specific set of G proteins is activated by each ligand, we profiled all agonists in BRET-based G-protein-activation assays using the TRUPATH biosensor platform⁵³, which comprises 14 different Gα subunits (Fig. 5a). All agonists showed strong selectivity for activating the G_i/o family of G proteins (Fig. 5b–e) and displayed similar potencies across the G_i/o-family members (G_i1, G_i2, G_i3, G_oA, G_oB, G_z) (iperoxo, ~0.2–2 nM; ACh, ~30–300 nM; arecoline, ~0.2–2 µM; pilocarpine, ~2–10 µM; Extended Data Fig. 10 and Supplementary Table 3). Moreover, some small but significant activation of Gα₁₅ was observed (Fig. 5b–e).

**Fig. 5: Activation trajectories and conformational equilibria define ligand efficacy in living cells.**

Importantly, comparing the maximal responses of agonists across the seven G proteins clearly reveals a rich texture of ligand efficacies (Fig. 5f), whereby the partial agonists appear to display more efficacy differences between the individual G-protein subunits than the full agonists. In particular, iperoxo behaved as a superagonist for almost all G proteins and pilocarpine elicited a partial response in all G protein-activation assays. However, arecoline displayed a unique efficacy profile exerting superagonism for G_oA and G_oB while behaving as a partial agonist for all of the other members of the G_i/o-protein family (Fig. 5f).

Linking a ligand’s conformational equilibrium (Fig. 4) to its G-protein signalling profile (Fig. 5) suggests that the position of this equilibrium (C1 versus C2) dictates the strength of agonism across the G-protein subtypes while the ligand-specific trajectory of complex formation has an important role in discriminating between different G-protein subtypes. Specifically, iperoxo stabilizes the high-efficacy complex C1 to a greater extent than ACh (Figs. 2 and 4). However, and in contrast to ACh, it hardly forms any low-efficacy complex C2 (Figs. 2 and 4). Conversely, pilocarpine strongly favours stabilization of C2 over C1 (Figs. 2 and 4). Finally, the unique trajectory of arecoline-mediated complex formation (Fig. 4) results in preferential activation of G_o over G_i proteins (Fig. 5).

Conclusions

Overall, our study reveals that the activation of a GPCR in intact cells may be far more complex than previous biophysical studies with isolated receptors have suggested. By attaching minimal-sized fluorescent labels to a set of activation- and G-protein coupling-sensitive positions on the extracellular receptor surface, we were able to track a receptor’s activation trajectory in real-time with considerable conformational detail directly within the native membrane environment of an intact cell. In contrast to earlier fluorescent GPCR activation biosensors that rely on fusion to large fluorescent proteins, self-labelling tags or, at best, oligomeric epitopes⁵², our sensors report on the movement of single receptor positions labelled with a fluorophore anchored through an ncAA, while leaving the intracellular surface of the receptor completely untouched. Although the method does not reach the atomic-level resolution of biophysical techniques such as NMR or DEER—as fluorophores are attached to the receptor backbone through a relatively large and flexible linker—it offers to our knowledge the highest spatial and temporal resolution currently achievable for tracking conformational changes in receptors within live cells.

Taken together, our data demonstrate that agonist activation of a GPCR results in the formation of an equilibrium of distinct active GPCR states and signalling complexes with various G proteins that differ in their efficacies. We propose that distinct agonists form such signalling complexes along different activation trajectories, involving both common and ligand-specific conformational changes in the receptor that evolve over time in a ligand-dependent manner. These individual activation trajectories may form the molecular basis for G-protein-subtype selectivity, while the position of this signalling complex equilibrium at steady state may define the overall strength of agonism. Thus, our study elucidates the molecular nature of ligand efficacy in intact cells.

It will be interesting to investigate whether and how these GPCR activation trajectories and the resultant formation of signalling complex equilibria can be exploited to expand our ability to manipulate receptors and achieve specific downstream responses and, ultimately, superior therapeutic effects. Moreover, we anticipate that our single-colour conformational sensor technology will be broadly applicable to other receptors, enabling the temporal dissection of conformational changes elicited by structurally distinct ligands, ranging from small molecules to larger peptides with diverse pharmacological profiles. This unique information, derived from the live-cell context, will enhance development of GPCR drug candidates with unique signalling profiles and expand our understanding of the general principles underlying GPCR structural dynamics.

Methods

Biosensor construction

Gibson assembly

All cloning, except for site-directed mutagenesis, was conducted using Gibson assembly (NEBuilder HiFi DNA Assembly Master Mix, New England Biolabs)⁵⁴. All primers were synthesized by BioTeZ. A list of all of the primer sequences is provided in Supplementary Table 5. Primers 1 and 3 were used to cut within the pcDNA3.0 backbone to decrease fragment sizes and increase yields for PCR amplification. All PCR products were obtained using Q5 High-Fidelity DNA Polymerase (New England Biolabs). All constructs were verified by Sanger sequencing (LGC Genomics).

For SP-M₂R-WT, the cDNA of human WT M₂R was cloned into pcDNA3.0 and a cleavable signal peptide (SP)⁵⁵ was cloned N-terminally of WT human M₂R using primers 1 and 2, 3 and 4, and 5 and 6. To obtain SP-M₂R-WT-eGFP, eGFP was fused to the C terminus of SP-M₂R-WT using primers 1 and 7, 3 and 8, and 9 and 10. For the ELISA assay, an HA-tag was cloned N-terminally to the WT receptor, resulting in SP-HA-M₂R-WT, using primers 3 and 11, and 1 and 12.

Site-directed mutagenesis

Receptor mutants were cloned by introducing an amber stop codon (TAG) at the desired positions by site-directed mutagenesis using the AAscan primer design tool⁵⁶. A list of the primer sequences is provided in Supplementary Table 6. Mutagenesis was performed using SP-M₂R-WT, SP-HA-M₂R-WT and SP-M₂R-WT-eGFP as templates. Point mutations were introduced by PCR using Thermo Fisher Scientific Phusion High-Fidelity DNA Polymerase (New England Biolabs). PCR products for QuickChange mutagenesis were incubated for 1 h at 37 °C with 1 µl DpnI restriction enzyme (New England Biolabs) before transformation. The resulting mutants are referred to as SP-M₂R^XXXTAG, SP-HA-SP-M₂R^XXXTAG or SP-M₂R^XXXTAG-eGFP throughout. To introduce the mutation disrupting the tyrosine lid closure (Y426A), the primers 13 and 14, and SP-M₂R^175TAG as a template were used, resulting in SP-M₂R^175TAG-Y426A. The point mutation was introduced using the Q5 Site-Directed Mutagenesis Kit (New England Biolabs).

Cell culture

HEK-tsA201 (Sigma-Aldrich; referred to as HEK293T cells throughout) cells were cultured in T75 flasks at 37 °C, 5% CO₂ in complete DMEM with 4.5 g l⁻¹ glucose (PAN-Biotech). Culture media was supplemented with 10% (v/v) FBS (Biochrom), 100 U ml⁻¹ penicillin, 100 mg ml⁻¹ streptomycin (Biochrom) and 2 mM L-glutamine (PAN-Biotech). Cells were passaged every 2–3 days when reaching a confluency of 80–90%. For passaging and seeding, the culture medium was aspirated, cells were washed with 5 ml Dulbecco’s PBS solution (Sigma-Aldrich), detached with 2 ml trypsin/EDTA (PAN-Biotech), resuspended in 5 ml DMEM and transferred to a new T75 flask. All cell lines were routinely tested for mycoplasma contamination using MycoAlert Mycoplasma Detection Kit (Lonza Group) and were not contaminated with mycoplasma. For the qualitative screen of labelled mutants at the accessible extracellular receptor surface, HEK293T cells were seeded on glass-bottomed 8-well µ-slides (Ibidi) at a density of approximately 7 × 10⁴ cells per well in 300 µl DMEM. For single-cell fluorescence microscopy experiments, HEK293T cells were seeded on 24 mm glass coverslips (Paul Marienfeld) in 6-well plates at a density of approximately 2.5–3 × 10⁵ cells per well in 1.5 ml culture medium. Coverslips and 8-well µ-slides were coated with poly-D-lysine (PDL; Sigma-Aldrich; 25 µg ml⁻¹ in PBS) for 30 min at room temperature and washed with PBS twice before seeding cells. For the quantification of labelling efficiency by temporal brightness experiments, HEK-293AD (BioCat; referred to as HEK-AD cells throughout) cells were seeded on uncoated 24 mm glass coverslips in 6-well plates at a density of approximately 3 × 10⁵ cells per well in 1.5 ml culture medium. To determine the cell-surface expression of M₂R biosensors using a cell-surface enzyme-linked immunosorbent assay (ELISA), 1.6 × 10⁶ HEK293T cells were seeded into a T25 flask and grown for 24 h at 37 °C. For the TRUPATH G-protein activation experiments of WT M₂ receptors, HEK293T cells were seeded into 6-well plates at a density of 3 × 10⁵ cells per well.

For the TRUPATH Gα_oA-activation assay of WT M₂R and each of the seven M₂R biosensors as well as SP-M₂R^175TAG-Y426A, HEK293T cells were seeded into T75 flasks and grown for 24 h at 37 °C to a confluency of 80–85%.

For the internalization experiments, HEK293T cells were seeded onto glass-bottomed 4-well µ-slides (Ibidi) at a density of approximately 5 × 10⁴ cells per well in 300 µl DMEM.

Transfection and ncAA incorporation

Principle and rationale of ncAA incorporation

To genetically encode a ncAA, an orthogonal aminoacyl-tRNA synthetase (AARS)–tRNA pair must be introduced into the host cell. This pair does not crosstalk with the endogenous synthetase–tRNA pairs responsible for incorporating canonical amino acids. Typically, the orthogonal pair is derived from a different organism—for example, bacterial pairs are commonly used for GCE in eukaryotic cells. The ncAARS specifically recognizes the ncAA, while the orthogonal tRNA functions as an amber suppressor: it carries an anticodon complementary to a stop codon (usually the amber stop codon UAG) and competes with termination factors to reassign this natural nonsense codon as a sense codon. The ncAARS charges the orthogonal tRNA with the ncAA, which is then delivered to the ribosome for regular incorporation into the nascent protein. Each ncAA requires a specific AARS, although some AARSs can accommodate more than one amino acid.

In our laboratory, we have established a two-plasmid system to incorporate ncAA into proteins of interest (POIs). One plasmid (typically pcDNA3) carries the gene encoding the POI, in which a TAG stop codon replaces the natural codon at the position targeted for ncAA incorporation. The second plasmid is a bicistronic construct that encodes the translational machinery: the aminoacyl-tRNA synthetase (AARS) and the corresponding tRNA. To ensure proper expression and processing of the procaryotic tRNA in mammalian cells, the tRNA gene—lacking the 3′-CCA sequence—is placed under the control of external Pol III promoters (H1 or U6) and followed by an appropriate trailer. To achieve the high tRNA concentrations required to outcompete the release factor, the tRNA expression cassette is typically repeated in tandem.

The orthogonal pair used for TCO*K incorporation is derived from the system that naturally incorporates pyrrolysine (Pyl) in methanogenic archaea in response to the amber codon (UAG)⁵⁷. Specifically, the plasmid contains one copy of the Methanococcus barkeri pyrrolysyl-tRNA synthetase (MbPylRS) under the control of a CMV promoter, along with four tandem copies of the gene encoding the enhanced M15 tRNA for expression in mammalian cells⁵⁸. The plasmid, which was generated in our lab, is deposited in Addgene, where the complete map and additional information can be found (105830, https://www.addgene.org/105830/).

Protocols

Live-cell epifluorescence microscopy

Cells grown on coverslips in 6-well plates were transfected 12–24 h after seeding when reaching a confluency of 40–60%. Before transfection, the culture medium was changed to DMEM without supplemented antibiotics, FBS and L-glutamine. For bioorthogonal labelling of trans-cyclooct-4-en-lysine (TCO*K, SiChem) a premix of HEPES buffer (1 M, pH 7.4, Sigma-Aldrich) and TCO*K stock solution (100 mM TCO*K in ncAA storage buffer, 0.2 M NaOH, 15% DMSO) was added to a final concentration of 0.25 mM TCO*K per well 1 h before transfection. Cells on coverslips were transfected using Lipofectamine 2000 transfection reagent (Thermo Fisher Scientific) as follows: per well a total amount of 1.5 µg cDNA was diluted with 150 µl Opti-MEM (Thermo Fisher Scientific) and combined after 5 min incubation at room temperature with 3.75 µl Lipofectamine 2000 transfection reagent, diluted in 150 µl Opti-MEM. After 20 min incubation at room temperature, the transfection mixture was added dropwise to each well. To maintain cell viability and to remove remaining excess TCO*K, the medium was changed to complete DMEM 4–6 h after transfection. Cells were grown an additional 18–20 h before single-cell microscopy experiments were conducted.

For ncAA incorporation and subsequent bioorthogonal labelling, the cDNA of SP-M₂R^XXXTAG or SP-M₂R^175TAG-Y426A (for biosensor activation experiments) or SP-M₂R^XXXTAG-eGFP (for expression analysis and quantification of bioorthogonal labelling) and the MbPylRS^AF/4xtRNA^M15 were transfected at a 1:1 ratio. For the labelled control without ncAA incorporation, cells were transfected with SP-M₂R^414TAG/MbPylRS^AF/4xtRNA^M15 as described in the previous section (total amount of cDNA, 1.5 µg) but then not loaded with TCO*K. When overexpressing the Gα_oA(G203T) mutant, a cDNA ratio (total amount of cDNA, 1.5 µg) of 1:1:1 (SP-M₂R^XXXTAG:Gα_oA(G203T):MbPylRS^AF/4xtRNA^M15) was used. For the Gα_i3-FRET activation assay, the cDNA (total amount of cDNA, 1.5 µg) of the SP-M₂R^XXXTAG or SP-M₂R-WT was transiently transfected with MbPylRS^AF/4xtRNA^M15 and the G_i3-FRET biosensor at a ratio of 10:10:1. For the internalization experiments, the cDNA (total amount of cDNA, 1.5 µg) of SP-M₂R^XXXTAG or SP-M₂R-WT-eGFP, MbPylRS^AF/4xtRNA^M15 and GRK3 were transfected at a 5:5:1 ratio.

Cell-surface ELISA

For determining the cell-surface expression of M₂R biosensors using ELISA, the cells were supplemented with TCO*K as described above and transfected with 10 µl Lipofectamine 2000, using a cDNA ratio of 1:1 (SP-HA-M₂R^XXXTAG or SP-HA-M₂R-WT, MbPylRS^AF/4xtRNA^M15) of 4 µg total plasmid 24 h after seeding in a T25 cell culture flask.

BRET-based G-protein activation experiments (TRUPATH)

To assess the G protein-activation profile of M₂ WT receptors, cells were transfected with SP-M₂R-WT, Gα-RLuc8, Gβ and GFP²-Gγ at a ratio of 1:1:1:1 in a total amount of 1.5 µg cDNA per well of a 6-well plate. For each Gα subunit, the combination of Gβ and Gγ used was the one optimized previously⁵³, as listed in Supplementary Table 7. Transfection was performed using the Effectene Transfection Kit (Qiagen) 18–24 h after seeding. For the transfection per well, the cDNA was premixed with 66 µl DNA-condensation buffer (EC-buffer) and 12 µl enhancer was added, mixed and incubated at room temperature for 2 min. After adding 6 µl Effectene, the mix was incubated at room temperature for 20 min. The culture medium was renewed, 350 µl DMEM was added to the transfection mix and the resulting solution applied dropwise to the cells.

For TRUPATH Gα_oA-activation experiments of M₂R WT and each of the seven M₂R biosensors as well as the double mutant SP-M₂R^175TAG-Y426A, per T75 flask cells were transfected with the cDNA of either SP-M₂R-WT (1.5 µg) or SP-M₂R^XXXTAG (3.5 µg) together with MbPylRS^AF/4xtRNA^M15 (3.5 µg), Gα_oA-RLuc8 (1.5 µg), Gβ₈ (1.5 µg) and GFP²-Gγ₃ (1.5 µg). In the case of SP-M₂R-WT the amount of cDNA was lowered to reduce expected expression differences compared with the M₂R biosensors. To ensure equal levels of transfected cDNA among all samples, 2 µg of empty pcDNA3.1 vector was added to the samples containing SP-M₂R-WT. Transfections were performed using Lipofectamine 2000 transfection reagent according to manufacturer recommendations for 16–24 h. In brief, cDNAs were dissolved in 1,200 µl OptiMEM (per flask), incubated for 5 min and 1,200 µl of OptiMEM containing 30 µl of Lipofectamine was added per transfection mixture and incubated with the cDNAs for 20 min at room temperature. The resulting solution was then added into freshly exchanged DMEM containing 100 mM TCO*K, according to the same principle as described above. To avoid transfection variability in between the different M₂Rs, stock solutions containing MbPylRS^AF/4xtRNA^M15, Gα_oA-RLuc8, Gβ₈ and GFP²-Gγ₃ with appropriate cDNAs quantities, as well as Lipofectamine were prepared and divided subsequently for each construct.

Bioorthogonal labelling of M₂R biosensors

Fluorescent labels were attached to the receptor using ultra-rapid click chemistry between dye–tetrazine derivatives and the ncAA TCO*K. While we have experience with other labelling chemistries¹³ in our laboratory, such as copper-catalysed azide–alkyne cycloaddition (CuAAC) on both azide- and alkyne-containing ncAAs, and strain-promoted azide–alkyne cycloaddition (SPAAC) on ncAAs bearing strained alkynes (for example, BCNK)¹⁴, we have consistently achieved the best results in terms of labelling speed, efficiency, cell viability and reproducibility using ultrarapid strain-promoted inverse electron-demand Diels–Alder cycloaddition on TCO*K. This ncAA carries a selected isomer of cyclooctene (trans-2-cyclooctene), which is highly reactive with both tetrazine and methyl-tetrazine dye derivatives yet sufficiently stable over the duration of the experiment (maximum of 2 min)⁴¹.

Cells expressing SP-M₂R^XXXTAG or SP-M₂R^XXXTAG-eGFP, as well as SP-M₂R^175TAG-Y426A, were labelled 30 min to 1 h before microscopy. If not indicated otherwise, cells were labelled with Tet–Cy3-conjugated dye (JenaBioscience) according to our previously published protocol⁵⁹. In brief, Tet-conjugated dyes were dissolved in imaging buffer (144 mM NaCl, 5.4 mM KCl, 1 mM MgCl₂, 2 mM CaCl₂, 10 mM HEPES, pH 7.3), from 0.5 mM stock solutions in DMSO to a final concentration of 1.5 µM. The culture medium was removed from the cells and, subsequently, 0.5 ml (coverslips) or 150 µl (µ-slides) of the solution was applied to the cells and removed after 5 min incubation at 37 °C. Cells were kept in imaging buffer at 37 °C until imaging. For the G_i3-FRET activation assay cells were labelled using Tet-Cy5-conjugated dye (Lumiprobe) according to the same protocol. Cells were labelled with Cy5 (instead of Cy3) to overcome the spectral overlap of Cy3 with the acceptor fluorophore of the G_i3-FRET biosensor (that is, cpVenus). To test the transferability of the biosensor approach using structurally different dyes, cells were labelled with tetrazine-5-TAMRA (JenaBioscience) using the same protocol.

Labelling screen of M₂R mutants

For these experiments, the SP-M₂R^XXXTAG-eGFP constructs were used. For the qualitative evaluation of full-length receptor expression and membrane localization, all cloned constructs of SP-M₂R^XXXTAG-eGFP were expressed in HEK293T cells and labelled at the respective site as described before. Confocal images of the cells expressing SP-M₂R^XXXTAG were taken before and after labelling with Tet–Cy3 to ensure cell viability before labelling. The screen for labelled receptor mutants was done using a LEICA TCS SP8 laser-scanning microscope with an oil-immersion objective (HC PL APO ×63/1.40 NA, oil). A 554 nm laser was used at 5% power to excite Cy3 fluorophores and the respective emission was measured within 590–650 nm. To excite eGFP fluorophores, a 488 nm laser was used at 5% power and the respective emission was measured within 500–555 nm. Images were acquired with a hybrid detector in sequential scan mode to avoid bleedthrough (1,024 × 1,024 pixel, line average 4, 400 Hz, gating 0.3–6 ms) using the Leica Application Suite X (LASX) software (v.3.5.7.23225). Labelling was assessed by considering full-length receptor expression (reflected by C-terminal eGFP) and Cy3-staining of the same cells. M₂R mutants were evaluated as being labelled when Cy3-labelling and eGFP membrane staining could be observed robustly for cells from at least three independent experiments.

Temporal brightness analyses through quantification of labelling efficiencies

For these experiments, the SP-M₂R^XXXTAG-eGFP constructs were used. The labelling efficiency of the selected M₂R biosensors was quantified using molecular brightness analyses according to a previously published protocol⁵⁹. In brief, the seven different SP-M₂R^XXXTAG-eGFP constructs were transfected in HEK-AD cells and bioorthogonally labelled with Tet–Cy3 as described in the ‘Bioorthogonal labelling of M₂R biosensors’ section above. Temporal brightness experiments were conducted on the LEICA TCS SP8 laser-scanning microscope, using the same laser lines and detector settings as described in the ‘Labelling screen of M₂R mutants’ section above. To reduce possible photobleaching, the laser power was reduced to 1% while identifying appropriate cells. Cells were imaged at their basolateral membranes. Suitable cells for the analysis exhibited a homogenous morphology of the basolateral membrane and distribution of fluorescent spots. For each cell, 100 consecutive frames were acquired (256 × 256 pixel, line average 1, zoom factor 22.8).

Temporal brightness analysis was performed in ImageJ (v.1.5.4f) using the Number & Brightness analysis plugin of J. Unruh⁶⁰. Image stack files were converted to 16-bit and appropriate regions with homogenous intensity distribution were selected from single fluorescence channels, opened as interactive 2D histogram. The number of emitters per pixel was extracted from the intensity of that pixel divided by the molecular brightness of the emitters as follows:

N = x_avg / y_avg − 1, where y_avg represents the average apparent brightness of all selected pixels over time and x_avg represents the average intensity of all selected pixels over time. The data were plotted as a scatter dot plot of N obtained from the eGFP channel and N obtained from the Cy3 channel. To determine the labelling efficiency, data were fitted to a linear regression with constraints at x,y = 0. The slope of the regression indicates the resulting labelling efficiency.

Live-cell epifluorescence microscopy

Single-cell kinetic experiments with M₂R biosensors

For these experiments, the SP-M₂R^XXXTAG constructs, as well as SP-M₂R^175TAG-Y426A, were used. Kinetic single-cell fluorescence microscopy experiments using the M₂R biosensors were conducted using an inverted DMi8 epifluorescence microscope (Leica Microsystems), equipped with an oil-immersion objective (HC PL APO ×63/1.40–0.60, oil), a high-speed polychromator (VisiChrome, Visitron Systems), a Xenon-Lamp (75 W, 5.7 A, Hamamatsu Photonics) or a CoolLED pE-800 (40% illumination, CoolLED) for the labelled control without ncAA incorporation and the kinetic experiments with the SP-M₂R^175TAG-Y426A mutant, a Photometrics Prime 95B sCMOS camera (Visitron Systems) with a Optosplit II dual emission image splitter (Cairn research), and the Visiview v.4.0 imaging software (Visitron Systems). A DAPI/FITC/Cy3/Cy5 ET Quadband Filter (ChromaTechnology) was used for imaging Cy3-labelled cells at 555/10 nm. Emission was recorded using a T590lpxr dichroic mirror (ChromaTechnology) and a 595/50 nm emission filter (ChromaTechnology). Coverslips with transfected cells were transferred to imaging chambers (Attofluor, Thermo Fisher Scientific) and washed once with imaging buffer. Cells were kept in imaging buffer throughout the experiment. All single-cell imaging was performed at room temperature. For ligand application, a solenoid valve perfusion system with a 200-µm inner diameter manifold-tip (Octaflow II, ALA Scientific Instruments) was used. Ligands were applied in direct vicinity of the cells after superfusion with imaging buffer for 5–10 s. The superfusion was conducted at a pressure of 50 mbar. Image sequences were recorded at 100-ms excitation time and acquisition intervals or 50 ms when using the CoolLED pE-800 lightsource. Image processing was performed with ImageJ⁶¹. Each cell was analysed individually. Cell membranes were selected as regions of interest using the drawing tool. An area without cells was defined as background. Fluorescence intensity over time of all regions was extracted for each emission channel. The raw data were processed by subtracting the background fluorescence at every timepoint for all recorded emission channels.

Changes in the fluorescence emission intensity were normalized to baseline according to the following formula: ΔF/F₀ = ((F − F₀)/F₀) × 100%, where F₀ is the mean emission intensity of the first ten datapoints of the time series, and F is the mean emission intensity of ten datapoints at the stable plateau of emission intensity changes reached after ligand application. To retrieve the apparent on-rates τ, a plateau followed by one-phase association/decay ordinary fitting was performed as follows: r(t) = F₀ + (Plateau-F₀) × (\(1-{e}^{-K\times (t-{t}_{0})}\)), if t < t₀, where t is time (s), t₀ is the respective timepoint of ligand application and Plateau-F₀ is the amplitude of emission intensity change. From this, τ has been calculated as τ = 1/K. Concentration–response curves were fit using a four-parametric variable slope fit (log(agonist) versus response) by calculating:

Y = Bottom + (Top − Bottom)/(\(1+{10}^{\log ({\rm{E}}{{\rm{C}}}_{50}-X)}\times {\rm{H}}{\rm{i}}{\rm{l}}{\rm{l}}{\rm{S}}{\rm{l}}{\rm{o}}{\rm{p}}{\rm{e}}\)), where X is the log of dose or concentration, Y is the response (Plateau) and Top is the maximum efficacy E_max.

G_i3-FRET activation assay

For the G_i3-FRET activation assay, the SP-M₂R^XXXTAG constructs were used. The FRET assay was performed using an Olympus IX83 Inverted Microscope equipped with an oil-immersion objective (UPLAPO60XOHR ×60/1.5 NA, oil) with an ORCA-Fusion C14440-20UP camera (Hamamatsu Photonics). A Spectra III-LCR-8S-A21 light engine (Lumencore) at 50 mW light intensity and an additional 20% transmission neutral-density filter (Qioptiq Photonics) were used for excitation with the following band-pass filters: CFP, 438/29 nm; YFP, 511/16 nm; Cy5 637/12 nm. The emission light was split into two channels using an OPTOSPLIT II (Cairn research) equipped with the following band-pass filters: CFP, 475/28 nm; YFP, 542/27 nm; and Cy5, 700/75 nm. For FRET measurements only Tet–Cy5-labelled cells were imaged. Sequences of images were acquired with camera scan mode 2, a 30 ms excitation time, 100 ms frame interval and 2 × 2 camera binning, resulting in 1,152 × 1,152 pixel resolution. After each individual FRET-experiment, YFP direct excitation was recorded with the same imaging settings, enabling comparisons of sensor expression. Ligands were applied using a solenoid valve perfusion system with a 100-µm inner diameter manifold-tip (Octaflow II, ALA Scientific Instruments) at a pressure of 350 mbar. In addition to background correction for both donor and acceptor emission, the obtained acceptor emission was corrected for spectral bleedthrough (B) as Acceptor_emission − B × Donor_emission (ref. ⁶²). The spectral bleedthrough was experimentally determined from FRET measurements of HEK293T cells expressing the donor fluorophore mTurquoise2 as the ratios of acceptor/donor emission. A correction factor of 0.22 was determined from three independent experiments. The FRET-ratios were calculated as the ratio of corrected acceptor emission (referred to as FRET) over corrected donor emission as Acceptor_emission/Donor_emission. All datapoints were plotted as ΔFRET (%) = (FRET − FRET₀/FRET₀) × 100%, where FRET₀ is the baseline, which was determined from the average of ten datapoints before ligand application.

Inhibition of endogenous G_i/o proteins with PTX

For these experiments, the SP-M₂R^XXXTAG constructs were used. To inhibit the activation of endogenous G_i/o proteins, cells have been treated overnight with the exotoxin PTX (Tocris Bioscience). To this end, HEK293T cells were seeded and the M₂R biosensors were transfected as described above. After 4–6 h of transfection, the culture medium was exchanged for complete DMEM, and PTX was added to the cells at a final concentration of 0.1 µg µl⁻¹. Cells were grown an additional 18–20 h before single-cell microscopy experiments were conducted. Labelling, fluorescence microscopy and image processing were carried out as described above. For suitable comparability, single-cell microscopy experiments were conducted for cells with and without PTX pretreatment on the same day for the same M₂R biosensor.

Cell-surface expression of M₂R biosensors

For these experiments, the SP-HA-M₂R^XXXTAG and SP-HA-M₂R-WT constructs were used. Cell-surface expression of SP-M₂R-WT and the M₂R biosensors in HEK293T cells was assessed using an indirect cellular ELISA assay as described in a previously published protocol⁶³. In brief, 24 h after transfection, cells were detached using Versene, reseeded into 48-well plates at a density of 1.2 × 10⁵ cells per well and grown at 37 °C for another 24 h. The ELISA assay was performed by fixing the cells with 4% formaldehyde, washing twice with PBS, blocking with DMEM supplemented with 10% FBS. The medium was removed and 50 mU ml⁻¹ anti-HA-peroxidase antibody (1:1,000, Sigma-Aldrich) was applied to the cells. The cells were washed three times with PBS. Subsequently, PBS was removed and detection solution (3.7 mM o-phenylenediamine, 22.65 mM citric acid, 51.4 mM Na₂HPO₄) including H₂O₂ were applied. The reaction was stopped by adding stopping reagent (0.12 M Na₂SO₃, 1 M HCl). Per well, the supernatant was transferred into a clear 96-well plate and the absorbance was measured at 492 nm (620 nm reference wavelength) in an EnVision microplate reader. The data were corrected to the reference wavelength and normalized to the absorbance of M₂R WT (set to 100%).

BRET-based G protein-activation experiments (TRUPATH)

G-protein-activation profile of the M₂R WT

To survey which G proteins are activated by the SP-M₂R-WT, we used the TRUPATH library (Addgene, 1000000163) according to protocols that were published recently^53,64. In brief, 24 h after transfection cells were detached, collected in fresh supplemented DMEM and reseeded into PDL-coated white 96-well plates at a density of 5 × 10⁴ cells per well. Cells were grown at 37 °C for another 24 h. The plates were stored at room temperature for 10 min before starting the assay. The culture medium was removed, and the cells in every well were washed twice with imaging buffer. Cells were kept in 60 µl imaging buffer and 10 µl of freshly prepared Prolume Purple working solution (NanoLight Technology) was added to each well at a final concentration of 5 µM per well. The plates were incubated for 5 min at room temperature in the dark. BRET measurements were performed using the Synergy Neo2 plate reader (Agilent Technologies), equipped with the BRET2 Filter cube (Agilent Technologies, 400/510 nm emission) and using a 50 ms integration time. Before ligand application of 30 µl per well, a baseline was recorded for 5 min. Negative controls were obtained by the addition of 30 µl imaging buffer per well instead of ligand. The BRET measurement was continued for 20 min with a time interval of 45 s between each datapoint. The BRET ratios 510/400 of each well were normalized to the baseline of the negative control (set to 100%). For the G-protein-activation heat map, all datapoints were normalized to the mean plateau value of the wells stimulated with 1 mM ACh. The data were analysed using Microsoft Excel 2016.

Functional characterization of M₂R biosensors

For the TRUPATH Gα_oA-activation assay of WT M₂R and the seven M₂R biosensors, the same batch of cells expressing one of the M₂R biosensors or the WT receptor was seeded into the same plate, and all of the ligands were tested within the same read. BRET measurements were performed using a PHERAstar fsx plate reader (BMG Labtech), equipped with a BRET2 filter cube (BMG Labtech, 410/530 nm emission). The baseline was recorded for 5 min followed by 7 min stimulation with the different ligands with a time interval of 60 s between each datapoint. The inverse BRET ratios 410/530 of each well were normalized to the baseline of negative control (set 0%) and ACh maximum concentration (set 100%) for each mutant. The data were analysed using Microsoft Excel 2016.

Internalization assay

The SP-M₂R-WT-eGFP and the SP-M₂R^XXXTAG constructs were expressed in HEK293T cells and labelled with Tet–Cy3 as described in the previous sections. After addition of ACh (400 µM), cells were incubated for 1 h at 37 °C. Images were acquired using the Axio Observer.Z1/7 microscope (Zeiss), equipped with a C-Apochromat ×63/1.2 NA W Korr DICII objective, an AxioCam 705 mono with Duolink camera and a LED Colibri 5 light source. Filters used (bandpass/bandstop in nm): eGFP, 450–490/495 (excitation), and 500/550 nm (emission); Cy3, 545–565/575 (excitation) and 579–604 nm (emission). Images were acquired using Zen blue 2.3 lite software (Zeiss).

Data analysis and statistics

Plotting, curve fitting and statistical analyses were performed using Prism v.7.0 or newer (GraphPad). Drift corrections in fluorescence imaging was performed using Origin 2022 (OriginLab). A Gaussian distribution of all datapoints was tested using the D’Agostino–Pearson omnibus normality test in Prism 7.0.

Statistic differences of two groups were assessed using two-tailed unpaired Student’s t-tests. A two-tailed paired t-test was performed when comparing various data obtained from the same single cell. In the case of normal distribution, a parametric test was used. Welch’s correction was further performed in the case of unequal variance. Statistic differences of three or more populations have been assessed using a parametric one-way ANOVA. When comparing to a reference group of data, a Tukey’s post hoc test was performed. In the case of multiple comparisons, a Dunnett’s test was used. For all statistical analyses, the confidence interval was set to 95% (P = 0.05). All experiments were performed with samples from independent experiments and repeated at least three times. The number of individually analysed cells is referred to as n. Details about n and the statistical test performed are stated in the appropriate figure legend.

Molecular models of receptors and analyses thereof were performed with UCSF ChimeraX, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from National Institutes of Health R01-GM129325 and the Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases⁶⁵. Schematics were created using BioRender.

For Fig. 2, the ΔF/F₀ of each condition was normalized to the ΔF/F₀ obtained for ACh within the same cell. For Fig. 3c,f,i and Supplementary Fig. 5, data from overexpression of the Gα_oA(G203T) mutant were normalized to data obtained at endogenous G-protein levels using the following equation: Norm ΔΔG_mut = ((G_mut − mean_endo)/mean_endo) × 100%, where G_mut represents the ΔF/F₀ of the respective M₂R biosensor when co-expressed with Gα_oA(G203T), and mean_endo refers to the mean ΔF/F₀ at endogenous G-protein levels (Fig. 2 and Supplementary Table 1). For Supplementary Fig. 6, the ΔF/F₀ of each datapoint obtained from activation of the seven M₂R biosensors with the ligands Ixo, Arec and Pilo was normalized to the mean ΔF/F₀ of ACh at endogenous G-protein expression levels or after overexpression of Gα_oA(G203T).

For Fig. 4, three-dimensional surface plots (Fig. 4) were generated using the NumPy and matplotlib libraries of Python (v.3.7.9)^66,67. The plots were generated as abstract Gaussian peaks modelled using the Gaussian function: \(z(x,y)=A\times {e}^{(-((x-{x}_{0})2+(y-{y}_{0})2)/2\sigma 2)}\) with A as the mean ΔF/F₀ relative to the plane z = 0. M₂R biosensors indicating the same receptor–G-protein complex were assigned similar colours. For each ligand-dependent receptor/G-protein complex at a given timepoint after agonist activation, the colour intensities from all positions were summed, and the respective plane was labelled in that colour.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

All data supporting the findings of this study are available in the Article and its Supplementary Information. Raw videos and images from microscopy experiments are available from the corresponding authors on request. The atomic coordinates used to generate the receptor model in Fig. 1 are available from the Protein Data Bank under accession codes 3UON and 4MQS. Source data are provided with this paper.

References

Weis, W. I. & Kobilka, B. K. The molecular basis of G protein-coupled receptor activation. Annu. Rev. Biochem. 87, 897–919 (2018).
Article PubMed PubMed Central CAS Google Scholar
Pierce, K. L., Premont, R. T. & Lefkowitz, R. J. Seven-transmembrane receptors. Nat. Rev. Mol. Cell Biol. 3, 639–650 (2002).
Article PubMed CAS Google Scholar
Nygaard, R. et al. The dynamic process of β₂-adrenergic receptor activation. Cell 152, 532–542 (2013).
Article PubMed PubMed Central CAS Google Scholar
Manglik, A. et al. Structural insights into the dynamic process of β₂-adrenergic receptor signaling. Cell 161, 1101–1111 (2015).
Article PubMed PubMed Central CAS Google Scholar
Gregorio, G. G. et al. Single-molecule analysis of ligand efficacy in β₂AR-G-protein activation. Nature 547, 68–73 (2017).
Article ADS PubMed PubMed Central CAS Google Scholar
Ye, L., Eps, N. V., Zimmer, M., Ernst, O. P. & Prosser, R. S. Activation of the A_2A adenosine G-protein-coupled receptor by conformational selection. Nature 533, 265–268 (2016).
Article ADS PubMed CAS Google Scholar
Huang, S. K. et al. Delineating the conformational landscape of the adenosine A_2A receptor during G protein coupling. Cell. 184, 1884–1894 (2021).
Article PubMed PubMed Central CAS Google Scholar
Picard, L.-P. et al. Balancing G protein selectivity and efficacy in the adenosine A_2A receptor. Nat. Chem. Biol. 21, 71–79 (2025).
Vafabakhsh, R., Levitz, J. & Isacoff, E. Y. Conformational dynamics of a class C G-protein-coupled receptor. Nature 524, 497–501 (2015).
Article ADS PubMed PubMed Central CAS Google Scholar
Olofsson, L. et al. Fine tuning of sub-millisecond conformational dynamics controls metabotropic glutamate receptors agonist efficacy. Nat. Commun. 5, 5206 (2014).
Article ADS PubMed CAS Google Scholar
Imai, S. et al. Structural equilibrium underlying ligand-dependent activation of β₂-adrenoreceptor. Nat. Chem. Biol. 16, 430–439 (2020).
Article PubMed CAS Google Scholar
Wang, L., Xie, J. & Schultz, P. G. Expanding the genetic code. Annu. Rev. Biophys. Biomol. Struct. 35, 225–249 (2006).
Article PubMed Google Scholar
Lang, K. & Chin, J. W. Cellular incorporation of unnatural amino acids and bioorthogonal labeling of proteins. Chem. Rev. 14, 4764–4806 (2014).
Article Google Scholar
Nikić, I., Kang, J. H., Girona, G. E., Aramburu, I. V. & Lemke, E. A. Labeling proteins on live mammalian cells using click chemistry. Nat. Protoc. 10, 780–791 (2015).
Article PubMed Google Scholar
Faveri, C. D., Mattheisen, J. M., Sakmar, T. P. & Coin, I. Noncanonical amino acid tools and their application to membrane protein studies. Chem. Rev. 27, 12498–12550 (2024).
Article Google Scholar
Plass, T., Milles, S., Koehler, C., Schultz, C. & Lemke, E. A. Genetically encoded copper-free click chemistry. Angew. Chem. Int. Ed. 50, 3878–3881 (2011).
Article CAS Google Scholar
Rosenbaum, D. M., Rasmussen, S. G. F. & Kobilka, B. K. The structure and function of G-protein-coupled receptors. Nature 459, 356–363 (2009).
Article ADS PubMed PubMed Central CAS Google Scholar
Hauser, A. S., Attwood, M. M., Rask-Andersen, M., Schiöth, H. B. & Gloriam, D. E. Trends in GPCR drug discovery: new agents, targets and indications. Nat. Rev. Drug Discov. 16, 829–842 (2017).
Article PubMed PubMed Central CAS Google Scholar
Gether, U., Lin, S. & Kobilka, B. K. Fluorescent labeling of purified β₂ adrenergic receptor: evidence for ligand-specific conformational changes. J. Biol. Chem. 270, 28268–28275 (1995).
Article PubMed CAS Google Scholar
Swaminath, G. et al. Probing the β₂ adrenoceptor binding site with catechol reveals differences in binding and activation by agonists and partial agonists. J. Biol. Chem. 280, 22165–22171 (2005).
Article PubMed CAS Google Scholar
Swaminath, G. et al. Sequential binding of agonists to the β₂ adrenoceptor: kinetic evidence for intermediate conformational states. J. Biol. Chem. 279, 686–691 (2004).
Article PubMed CAS Google Scholar
Ghanouni, P. et al. Functionally different agonists induce distinct conformations in the G protein coupling domain of the β₂adrenergic receptor. J. Biol. Chem. 276, 24433–24436 (2001).
Article PubMed CAS Google Scholar
Lamichhane, R. et al. Single-molecule view of basal activity and activation mechanisms of the G protein-coupled receptor β2AR. Proc. Natl Acad. Sci. USA 112, 14254–14259 (2015).
Article ADS PubMed PubMed Central CAS Google Scholar
Xu, J. et al. Conformational complexity and dynamics in a muscarinic receptor revealed by NMR spectroscopy. Mol. Cell 75, 53–65 (2019).
Article PubMed CAS Google Scholar
Wingler, L. M. et al. Angiotensin analogs with divergent bias stabilize distinct receptor conformations. Cell 176, 468–478 (2019).
Article PubMed PubMed Central CAS Google Scholar
Masureel, M. et al. Structural insights into binding specificity, efficacy and bias of a β2AR partial agonist. Nat. Chem. Biol. 14, 1059–1066 (2018).
Article PubMed PubMed Central CAS Google Scholar
Staus, D. P. et al. Allosteric nanobodies reveal the dynamic range and diverse mechanisms of G-protein-coupled receptor activation. Nature 535, 448–452 (2016).
Article ADS PubMed PubMed Central CAS Google Scholar
Liu, X. et al. Structural insights into the process of GPCR-G protein complex formation. Cell 177, 1243–1251 (2019).
Article PubMed PubMed Central CAS Google Scholar
Du, Y. et al. Assembly of a GPCR-G protein complex. Cell 177, 1232–1242 (2019).
Article PubMed PubMed Central CAS Google Scholar
Furness, S. G. B. et al. Ligand-dependent modulation of G protein conformation alters drug efficacy. Cell 167, 739–749 (2016).
Article PubMed CAS Google Scholar
Wang, X., Neale, C., Kim, S.-K., Goddard, W. A. & Ye, L. Intermediate-state-trapped mutants pinpoint G protein-coupled receptor conformational allostery. Nat. Commun. 14, 1325 (2023).
Article ADS PubMed PubMed Central CAS Google Scholar
Hilger, D., Masureel, M. & Kobilka, B. K. Structure and dynamics of GPCR signaling complexes. Nat. Struct. Mol. Biol. 25, 4–12 (2018).
Article PubMed PubMed Central CAS Google Scholar
Katritch, V., Cherezov, V. & Stevens, R. C. Structure-function of the G protein–coupled receptor superfamily. Annu. Rev. Pharmacol. Toxicol. 53, 531–556 (2013).
Article PubMed CAS Google Scholar
Venkatakrishnan, A. J. et al. Molecular signatures of G-protein-coupled receptors. Nature 494, 185–194 (2013).
Article ADS PubMed CAS Google Scholar
Congreve, M., de Graaf, C., Swain, N. A. & Tate, C. G. Impact of GPCR structures on drug discovery. Cell 181, 81–91 (2020).
Article PubMed CAS Google Scholar
DeVree, B. T. et al. Allosteric coupling from G protein to the agonist-binding pocket in GPCRs. Nature 535, 182–186 (2016).
Article ADS PubMed PubMed Central CAS Google Scholar
Haga, K. et al. Structure of the human M2 muscarinic acetylcholine receptor bound to an antagonist. Nature 482, 547–551 (2012).
Article ADS PubMed PubMed Central CAS Google Scholar
Kruse, A. C. et al. Activation and allosteric modulation of a muscarinic acetylcholine receptor. Nature 504, 101–106 (2013).
Article ADS PubMed PubMed Central CAS Google Scholar
Xu, J. et al. Structural and dynamic insights into supra-physiological activation and allosteric modulation of a muscarinic acetylcholine receptor. Nat. Commun. 14, 376 (2023).
Article ADS PubMed PubMed Central CAS Google Scholar
Serfling, R. et al. Quantitative single-residue bioorthogonal labeling of G protein-coupled receptors in live cells. ACS Chem. Biol. 14, 1141–1149 (2019).
Article PubMed CAS Google Scholar
Nikić, I. et al. Minimal tags for rapid dual-color live-cell labeling and super-resolution microscopy. Angew. Chem. Int. Ed. Engl. 17, 2245–2249 (2014).
Article Google Scholar
Levitus, M. & Ranjit, S. Cyanine dyes in biophysical research: the photophysics of polymethine fluorescent dyes in biomolecular environments. Q. Rev. Biophys. 44, 123–151 (2011).
Article PubMed CAS Google Scholar
Lamichhane, R. et al. Biased signaling of the G-protein-coupled receptor β₂AR is governed by conformational exchange kinetics. Structure 28, 371–377 (2020).
Article PubMed PubMed Central CAS Google Scholar
Schrage, R. et al. Supraphysiological M2 receptor activation. Br. J. Pharmacol. 169, 357–370 (2013).
Article PubMed PubMed Central CAS Google Scholar
Schrage, R. et al. New insight into active muscarinic receptors with the novel radioagonist [³H]iperoxo. Biochem. Pharmacol. 90, 307–319 (2014).
Article PubMed CAS Google Scholar
Maeda, S., Qu, Q., Robertson, M., Skiniotis, G. & Kobilka, B. Structures of the M1 and M2 muscarinic acetylcholine receptor/G-protein complexes. Science 364, 552–557 (2019).
Article ADS PubMed PubMed Central CAS Google Scholar
Barren, B. & Artemyev, N. O. Mechanisms of dominant negative G-protein α subunits. J. Neurosci. Res. 85, 3505–3514 (2007).
Article PubMed CAS Google Scholar
Doumazane, E. et al. Illuminating the activation mechanisms and allosteric properties of metabotropic glutamate receptors. Proc. Natl Acad. Sci. USA 110, E1416–E1425 (2013).
Article PubMed PubMed Central CAS Google Scholar
Mangmool, S. & Kurose, H. G_i/o protein-dependent and -independent actions of pertussis toxin (PTX). Toxins 3, 884–899 (2011).
Article PubMed PubMed Central CAS Google Scholar
Batebi, H. et al. Mechanistic insights into G-protein coupling with an agonist-bound G-protein-coupled receptor. Nat. Struct. Mol. Biol. 31, 1692–1701 (2024).
Article PubMed PubMed Central CAS Google Scholar
Zhao, J. et al. Ligand efficacy modulates conformational dynamics of the µ-opioid receptor. Nature 629, 474–480 (2024).
Article ADS PubMed PubMed Central CAS Google Scholar
Lohse, M. J., Nuber, S. & Hoffmann, C. Fluorescence/bioluminescence resonance energy transfer techniques to study G-protein-coupled receptor activation and signaling. Pharmacol. Rev. 64, 299–336 (2012).
Article PubMed CAS Google Scholar
Olsen, R. H. J. et al. TRUPATH, an open-source biosensor platform for interrogating the GPCR transducerome. Nat. Chem. Biol. 16, 841–849 (2020).
Article PubMed PubMed Central CAS Google Scholar
Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).
Article PubMed CAS Google Scholar
Guan, X. M., Kobilka, T. S. & Kobilka, B. K. Enhancement of membrane insertion and function in a type IIIb membrane protein following introduction of a cleavable signal peptide. J. Biol. Chem. 267, 21995–21998 (1992).
Article PubMed CAS Google Scholar
Sun, D. et al. AAscan, PCRdesign and MutantChecker: a suite of programs for primer design and sequence analysis for high-throughput scanning mutagenesis. PLoS ONE 8, e78878 (2013).
Article ADS PubMed PubMed Central CAS Google Scholar
Dunkelmann, D. L. & Chin, J. W. Engineering pyrrolysine systems for genetic code expansion and reprogramming. Chem. Rev. 19, 11008–11062 (2024).
Article Google Scholar
Serfling, R. et al. Designer tRNAs for efficient incorporation of non-canonical amino acids by the pyrrolysine system in mammalian cells. Nucleic Acids Res. 1, 1–10 (2018).
Article Google Scholar
Işbilir, A. et al. Determination of G-protein-coupled receptor oligomerization by molecular brightness analyses in single cells. Nat. Protoc. 16, 1419–1451 (2021).
Article PubMed Google Scholar
Unruh, J. R. & Gratton, E. Analysis of molecular concentration and brightness from fluorescence fluctuation data with an electron multiplied CCD camera. Biophys. J. 95, 5385–5398 (2008).
Article ADS PubMed PubMed Central CAS Google Scholar
Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).
Article PubMed PubMed Central CAS Google Scholar
Börner, S. et al. FRET measurements of intracellular cAMP concentrations and cAMP analog permeability in intact cells. Nat. Protoc. 6, 427–438 (2011).
Article ADS PubMed Google Scholar
Liebing, A.-D., Krumbholz, P. & Stäubert, C. Protocol to characterize G_i/o and G_s protein-coupled receptors in transiently transfected cells using ELISA and cAMP measurements. STAR Protoc. 4, 102120 (2023).
Article PubMed PubMed Central CAS Google Scholar
DiBerto, J. F., Smart, K., Olsen, R. H. J. & Roth, B. L. Agonist and antagonist TRUPATH assays for G protein-coupled receptors. STAR Protoc. 3, 101259 (2022).
Article PubMed PubMed Central CAS Google Scholar
Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021).
Article PubMed CAS Google Scholar
Harris, C. R. et al. Array programming with NumPy. Nature 585, 357–362 (2020).
Article ADS PubMed PubMed Central CAS Google Scholar
Hunter, J. D. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).
Article Google Scholar

Download references

Acknowledgements

We thank J.-P. Pin for providing the plasmid encoding the Gα_o mutant and B. Kobilka for discussions. This study was funded by the Deutsche Forschungsgemeinschaft (German Research Foundation) through SFB1423, project number 421152132, subprojects C05 (to I.C. and A.B.), C06 (to C.S.) and C08 (to M.J.L. and A.B.); and through project 407707190 (to C.S.) and CO822/5-1 (671228, NanoBelt) (to I.C.). R.T. is supported by an Add-on Fellowship for Interdisciplinary Life Science from the Joachim Herz Foundation; and A.-D.L. by the Pre-Doc Award of Leipzig University. A.B. acknowledges funding by the Else Kröner-Fresenius-Stiftung. Figures 1, 3 and 5 and Extended Data Figs. 1 and 8 were created in part using BioRender with the publication licence LO27JFUF6I.

Funding

Open access funding provided by Johannes Gutenberg-Universität Mainz.

Author information

Romy Thomas
Present address: Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA, USA
Chiara De Faveri
Present address: Department of Molecular Environmental Biotechnology, Helmholtz Centre for Environmental Research–UFZ, Leipzig, Germany

Authors and Affiliations

Rudolf Boehm Institute of Pharmacology and Toxicology, Medical Faculty, Leipzig University, Leipzig, Germany
Romy Thomas, Pauline S. Jacoby, Martin J. Lohse & Andreas Bock
Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
Romy Thomas, Martin J. Lohse & Andreas Bock
Institute of Biochemistry, Leipzig University, Leipzig, Germany
Chiara De Faveri & Irene Coin
Institute of Pharmacology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
Cécile Derieux, Barbora Melkes, Hans-Joachim Martini & Andreas Bock
Rudolf-Schönheimer Institute of Biochemistry, Medical Faculty, Leipzig University, Leipzig, Germany
Aenne-Dorothea Liebing & Claudia Stäubert
Institute for Pharmaceutical and Medical Chemistry, Faculty of Chemistry and Pharmacy, University of Münster, Münster, Germany
Marcel Bermúdez
ISAR Bioscience Institute, Planegg, Germany
Martin J. Lohse
Institute of Regenerative Medicine in Cardiology—Technical University of Munich, Munich, Germany
Martin J. Lohse
Research Center for Immunotherapy (FZI), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
Andreas Bock

Authors

Romy Thomas
View author publications
Search author on:PubMed Google Scholar
Pauline S. Jacoby
View author publications
Search author on:PubMed Google Scholar
Chiara De Faveri
View author publications
Search author on:PubMed Google Scholar
Cécile Derieux
View author publications
Search author on:PubMed Google Scholar
Aenne-Dorothea Liebing
View author publications
Search author on:PubMed Google Scholar
Barbora Melkes
View author publications
Search author on:PubMed Google Scholar
Hans-Joachim Martini
View author publications
Search author on:PubMed Google Scholar
Marcel Bermúdez
View author publications
Search author on:PubMed Google Scholar
Claudia Stäubert
View author publications
Search author on:PubMed Google Scholar
Martin J. Lohse
View author publications
Search author on:PubMed Google Scholar
Irene Coin
View author publications
Search author on:PubMed Google Scholar
Andreas Bock
View author publications
Search author on:PubMed Google Scholar

Contributions

I.C. and A.B. conceptualized the study. R.T. engineered and characterized the biosensor panel and performed most of the experiments. P.S.J. and C.D. established and performed TRUPATH assays. P.S.J. performed G_i-activation assays in single cells. C.D.F. performed the initial expression and labelling screen of M₂R mutants and internalization assays. A.-D.L. and C.S. performed cell-surface expression experiments with the help of P.S.J.; C.D. and B.M. established the biosensor technology in the new laboratory of A.B. in Mainz, Germany during revision of this paper. H.-J.M. performed experiments with the tyrosine lid mutant. R.T., P.S.J., C.D.F., C.D., H.-J.M. and A.B. analysed data and generated figures. M.B. provided valuable support in the structural interpretation and visualization of the biosensor dataset. M.J.L. provided critical ideas and contributed extensively to discussions. I.C. and A.B. supervised the project. A.B. wrote the paper with input from M.J.L. and I.C.

Corresponding authors

Correspondence to Irene Coin or Andreas Bock.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Sivaraj Sivaramakrishnan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Labelling efficiency of M₂ receptor biosensors.

(a) Shown are representative confocal images obtained from the M₂R labelling screen. M₂R constructs (SP-M₂R^XXXTAG) incorporating the non-canonical amino acid TCO*K at the indicated positions (amino acid numbering of the native human M₂ receptor) could be labelled with Tet-Cy3 on at least 3 independent days of experiments. Labelled M₂R constructs that show agonist-induced fluorescence intensity changes (see Fig. 1c), are highlighted in orange. (b) For quantification of labelling efficiencies, M₂R constructs, each comprising a C-terminal EGFP, were transiently expressed in HEK-AD cells (SP-M₂R^XXXTAG-EGFP). The average numbers (N) of counted Tet-Cy3 labelled molecules were obtained using molecular brightness analysis⁴¹. The number of Tet-Cy3 labelled molecules was then compared to the number of molecules counted in the EGFP channel. Created in BioRender. Thomas, R. (2025) https://BioRender.com/loxqlqf. (c-i) The average number N of counted Tet-Cy3 labelled molecules (y-axis) and EGFP (x-axis), obtained from approx. 100 images, is plotted in a log-log-scale. Each data point indicates a single HEK-AD cell analysed from overall 3 independent experiments. The data were fitted by linear regression with constraints at X,Y = 0. The fits are shown as slope ± sd. n, number of cells. R², goodness of fit.

Source data

Extended Data Fig. 2 Functional characterization of M₂R biosensors.

(a) Representative ΔFRET traces from single HEK293T cells transiently expressing the Gα_i3-FRET biosensor with wild-type (SP-M₂R-wt) or mutant receptors (SP-M₂R^XXXTAG) labelled with Tet-Cy5 at the indicated positions before and after activation with 300 µM ACh. (b) Comparison of mean ΔFRET responses (left y-axis) and receptor surface expression (right y-axis) for all seven M₂R biosensors and M₂R-wt. Surface expression was determined by ELISA in 4 independent experiments using N-terminal HA-tagged constructs (SP-HA-M₂R-wt or SP-HA-M₂R^XXXTAG). Unshaded bars indicate absolute ΔFRET from the Gα_i3-FRET assay, dashed bars the ELISA absorbance normalized to wild-type (100%). Reduced receptor expression correlates with decreased maximal G-protein activation. (c) Apparent activation kinetics (Tau (τ), s) derived from the Gα_i3-FRET assay. Bars show mean ± s.e.m.; each point represents one cell. ns, not significant (one-way ANOVA with Dunnett’s post-hoc test vs. M₂R-wt). M₂R^XXX (n = X number of individual cells examined over Y number of independent experiments): M₂R-wt (89; 5), M₂R⁸⁴ (30; 6), M₂R¹⁷⁵ (26; 6), M₂R¹⁸¹ (39; 5), M₂R¹⁸⁸ (52; 5), M₂R⁴¹⁴ (39; 4), M₂R⁴¹⁵ (30; 5), M₂R⁴¹⁹ (30; 4). (d) All seven biosensors internalize upon agonist addition. Representative epifluorescence images of SP-HA-M₂R^XXXTAG constructs labelled with Tet-Cy3 before (top row) and after (bottom row) addition of 400 µM ACh. SP-M₂R-wt-EGFP served as a positive control. Green, GFP channel; orange, Cy3 channel. (e) M₂R biosensors do not respond to the inverse agonist NMS. Representative ΔF/F₀ traces of the indicated SP-HA-M₂R^XXXTAG biosensors labelled with Tet-Cy3 and stimulated with 100 µM NMS. Shaded areas denote NMS exposure; unshaded areas indicate buffer application. M₂R^XXX (n = X number of individual cells examined over Y number of independent experiments): M₂R⁸⁴ (20; 6), M₂R¹⁷⁵ (21; 6), M₂R¹⁸¹ (19; 4), M₂R¹⁸⁸ (25; 3), M₂R⁴¹⁴ (30; 7), M₂R⁴¹⁵ (16; 4), M₂R⁴¹⁹ (20; 5).

Source data

Extended Data Fig. 3 Conformational fingerprint of a positive allosteric modulator.

(a) Representative fluorescence intensity changes (ΔF/F₀) recorded in real-time from single HEK293T cells expressing indicated M₂R biosensors superfused with 30 µM LY2119620 (LY), followed by 1 mM ACh after wash out with buffer. Ligand application is indicated by shaded areas in different colours. Non-shaded areas indicate buffer wash-out. (b) Mean fluorescence intensity changes (ΔF/F₀) at all seven biosensors after addition of LY and ACh. Positive values indicate an increase in fluorescence, negative values indicate a fluorescence decrease. Bars indicate means ± sem, each data point represents a single cell. M₂R^XXX (n = X number of individual cells examined over Y number of independent experiments): M₂R⁸⁴ (12; 3), M₂R¹⁷⁵ (8; 3), M₂R¹⁸¹ (23; 3), M₂R¹⁸⁸ (10; 3), M₂R⁴¹⁴ (35; 8), M₂R⁴¹⁵ (13; 4), M₂R⁴¹⁹ (11; 4). ****p < 0.0001, ***p < 0.001 (T84: 0.0006, F188: 0.0002), **p < 0.01 (F181: 0.0041), *p < 0.05 (E175: 0.0147, N419: 0.0166), according to a two-tailed paired t-test. (c) Radar plot of mean fluorescence intensity changes ΔF/F₀ in response to LY, normalized to ΔF/F₀ of 1 mM ACh in the same cell. The bold line indicates ACh (set to 100%). The direction of ΔF/F₀ is indicated with arrows (decrease, down). The change of direction in fluorescence emission for M₂R⁸⁴ and M₂R¹⁷⁵ upon LY stimulation compared to ACh stimulation is highlighted in red.

Source data

Extended Data Fig. 4 ACh potencies are similar across all seven M₂R biosensors.

(a-g) Representative traces of concentration-dependent changes of fluorescence intensity (ΔF/F₀) of a single cell expressing the indicated M₂R biosensor (SP-M₂R^XXXTAG), stimulated with increasing concentrations of ACh, indicated as log (M) and by a grey colour gradient. (h) Concentration-effect-curves of normalized, mean ACh-mediated fluorescence intensity changes in response to increasing concentrations of ACh. ACh potencies (log_EC50 ± sem): T84, −5.9 ± 0.05; E175, −6.4 ± 0.01; F181, −5.7 ± 0.03; F188, −5.5 ± 0.03; A414, −5.8 ± 0.02; P415, −6.2 ± 0.02; N419, −5.4 ± 0.05. n = 10 (T84), n = 19 (E175), n = 21 (F181), n = 20, n = 20 (188), n = 29 (A414), n = 15 (P415), n = 13 (N419). Data obtained from 3 independent experiments. (i) Plot of maximal ΔFRET responses of the Gα_i3-FRET assay (see Extended Data Fig. 2) and ACh potencies at the seven biosensors. The data were fitted by linear regression. R², goodness of fit.

Source data

Extended Data Fig. 5 Ligand-dependent, M₂R biosensors-mediated activation of G_oA proteins.

(a-h) Concentration-dependent activation of G_oA proteins determined by the TRUPATH BRET assay upon activation of the indicated M₂R variant (SP-M₂R-wt) or (SP-M₂R^XXXXTAG) by Ixo (green), ACh (grey), Arec (purple), and Pilo (pink). Concentration-dependent BRET changes (ΔBRET) were normalized to buffer (set to 0 %) and the maximal response of ACh (set to 100%), indicated by the dotted line. Shown are the means ± sem of 3 (M₂R biosensors) and 4 (M₂R wildtype) independent experiments (see Supp. Table 2).

Source data

Extended Data Fig. 6 M₂R biosensors respond to different agonists to various degrees.

Representative traces of ΔF/F₀ of a single cell expressing the indicated M₂R biosensor (SP-M₂R^XXXTAG) and stimulated with (a) 100 µM Ixo (green), (b) 1 mM Arec (purple), or (c) 10 mM Pilo (pink) and 1 mM ACh (grey) after washout with buffer, respectively (see Supp. Table 1). Shaded areas indicate the addition of the respective agonist, unshaded areas represent buffer application.

Source data

Extended Data Fig. 7 A tyrosine-lid mutation impedes the M₂R¹⁷⁵ biosensor-response to Ach.

(a) Side-view on the X-ray crystal structure of the active M₂R (orange, PDB: 4MQS). A tyrosine lid is formed on top of iperoxo (light grey). The mutated tyrosine residue (Y426^7.39) is highlighted in black. (b) Representative fluorescence intensity changes (ΔF/F₀) recorded in real-time from single HEK293T cells expressing the M₂R¹⁷⁵ (orange) or the M₂R¹⁷⁵-Y426A mutant (black) biosensors superfused with 1 mM ACh (shaded area). Non-shaded areas indicate buffer application. (c) ACh-induced mean fluorescence intensity changes (ΔF/F₀) of the M₂R¹⁷⁵ (orange) or the M₂R¹⁷⁵-Y426A mutant (black) biosensors. Bars indicate means ± sem, each data point represents a single cell. M₂R^XXX (n = X number of cells examined over Y number of independent experiments): M₂R¹⁷⁵ (44; 11), M₂R¹⁷⁵-Y426A (16; 3). ****p < 0.0001, according to an two-tailed unpaired t-test with Welch’s correction. The data for the M₂R¹⁷⁵ biosensor are replotted from Fig. 1c and d. (d) Concentration-response curves of agonist-induced G-protein activation of the M₂R¹⁷⁵ (orange) or the M₂R¹⁷⁵-Y426A mutant (black) biosensors as determined by the TRUPATH BRET-based assay. Concentration-dependent BRET changes (ΔBRET) were normalized to buffer (set to 0 %) and the maximal response of ACh (set to 100%) at the M₂R¹⁷⁵ biosensor. Shown are the means ± sem of 3 independent experiments (see Supp. Table 2). Constructs used: SP-M₂R^E175TAG and SP-M₂R^E175TAG-Y426A.

Source data

Extended Data Fig. 8 PTX-pretreatment decreases or abolishes agonist-promoted fluorescence intensity changes.

(a) Sketch of the experimental procedure: 4–6 h after transfection with SP-M₂R^F181TAG, HEK293T cells were treated with 0.1 µg/µL PTX and grown at 37 °C for 18–20 h before labelling with Tet-Cy3. Created in BioRender. Thomas, R. (2025) https://BioRender.com/f79d908. (b) Epifluorescence image of two representative HEK293T cells expressing the M₂R¹⁸¹ biosensor, treated with PTX, and labelled with Tet-Cy3. (c-f) Representative traces of M₂R¹⁸¹ expressed in HEK293T cells, treated with PTX (black, see Fig. 2) or without PTX-treatment (grey), and stimulated with 100 µM Ixo (c), 1 mM Ach (d), 1 mM Arec (e), or 10 mM Pilo (f). Shaded areas indicate agonist application, unshaded areas represent buffer application. Data were obtained from 3 independent experiments. n (number of single cells, -PTX, +PTX); n = 7, 9 (Ixo), n = 18, 13 (ACh), n = 10, 8 (Arec), n = 10, 13 (Pilo).

Source data

Extended Data Fig. 9 Time-resolved dynamics of M₂R/G protein-signalling complexes.

Comparison of apparent on-rates (Tau in s) obtained from six biosensors (SP-M₂R^XXXTAG) after activation with the indicated ligands 1 mM ACh (a), 100 μM Ixo (b), 1 mM Arec (c), and 10 mM Pilo (d) at endogenous G-protein levels (endo) and after Gα_oA(G203T) overexpression. Bars indicate means ± sem, each data point represents a single cell (see Supp. Table 3). For Gα_oA(G203T) overexpression: M₂R^XXX (per agonist: n = X number of cells examined over Y number of independent experiments): M₂R⁸⁴ (Ixo: 15; 5, ACh: 14; 7, Arec: 10; 3, Pilo: 20; 4), M₂R¹⁷⁵ (Ixo: 11; 3, ACh: 10; 3, Arec: 9; 3, Pilo: 11; 3), M₂R¹⁸¹ (Ixo: 29; 4, ACh: 41; 7, Arec: 34; 4, Pilo: 20; 3), M₂R¹⁸⁸ (Ixo: 16; 3, ACh: 26; 4, Arec: 13; 3, Pilo: 17; 3), M₂R⁴¹⁴ (Ixo: 12; 4, ACh: 31; 9, Arec: 10; 3, Pilo: 16; 3), M₂R⁴¹⁵ (Ixo: 28; 5, ACh: 21; 6, Arec: 19; 5, Pilo: 10; 3). The number of individual cells and independent experiments for the endogenous G-protein condition are listed in the legends of Figs. 1 and 2. P values, according to according to a two-tailed unpaired t-test with Welch’s correction are plotted in (a-d). The biosensors are classified into statistically different groups, according to a one-way analysis of variance (ANOVA multiple comparisons test) with Tukey’s posthoc test; ns, not significantly different. Biosensors that are grouped are not significantly different from each other.

Source data

Extended Data Fig. 10 Concentration-effect curves of agonist-mediated G-protein activation at M₂R-wt.

The concentration-effect curves were generated from experiments as performed in Fig. 5. Concentration-dependent ligand-dependent BRET changes (ΔBRET) were normalized to buffer (set to 0 %) and the agonists’ maximal effects (set to 100 %). (a) ACh, (b) Ixo, (c) Arec, and (d) Pilo. Shown are the means ± sem. n= number of independent experiments (for Ixo, ACh, Arec, Pilo): 4, 6, 4, 6 (G_i1), 4, 7, 4, 6 (G_i2), 4, 6, 4, 5 (G_i3), 6, 5, 3, 6 (G_oA), 5, 8, 3, 5 (G_oB), 5, 6, 4, 4 (G_z), 6, 6, 4, 5 (G₁₅), see Supp. Table 4.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Supplementary Tables 1–7. The Supplementary Figures provide data on biosensor validation (labelling, order of ligand addition, G-protein overexpression). The Supplementary Tables list technical parameters (normalized fluorescence intensities, EC₅₀, E_max, on-rates), primer sequences and G-protein subunits

Reporting Summary

Peer Review file

Supplementary Data 1: source data for Supplementary Fig. 3.

Supplementary Data 2: source data for Supplementary Fig. 4.

Supplementary Data 3: source data for Supplementary Fig. 5.

Supplementary Data 4: source data for Supplementary Fig. 6.

Source data

Source Data Fig. 1

Source Data Fig. 2

Source Data Fig. 3

Source Data Fig. 5

Source Data Extended Data Fig. 1

Source Data Extended Data Fig. 2

Source Data Extended Data Fig. 3

Source Data Extended Data Fig. 4

Source Data Extended Data Fig. 5

Source Data Extended Data Fig. 6

Source Data Extended Data Fig. 7

Source Data Extended Data Fig. 8

Source Data Extended Data Fig. 9

Source Data Extended Data Fig. 10

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Thomas, R., Jacoby, P.S., De Faveri, C. et al. Ligand-specific activation trajectories dictate GPCR signalling in cells. Nature (2026). https://doi.org/10.1038/s41586-025-09963-3

Download citation

Received: 20 November 2024
Accepted: 25 November 2025
Published: 14 January 2026
Version of record: 14 January 2026
DOI: https://doi.org/10.1038/s41586-025-09963-3

Subjects

Abstract

Similar content being viewed by others

Main

Development of GPCR biosensors

Ligand-unique conformational states of the M2R

Distinct receptor–G-protein complexes

Kinetics of the formation and dynamics of M2R–G-protein complexes

Equilibria of complexes define ligand efficacy

Conclusions

Methods

Biosensor construction

Gibson assembly

Site-directed mutagenesis

Cell culture

Transfection and ncAA incorporation

Principle and rationale of ncAA incorporation

Protocols

Live-cell epifluorescence microscopy

Cell-surface ELISA

BRET-based G-protein activation experiments (TRUPATH)

Bioorthogonal labelling of M2R biosensors

Labelling screen of M2R mutants

Temporal brightness analyses through quantification of labelling efficiencies

Live-cell epifluorescence microscopy

Single-cell kinetic experiments with M2R biosensors

Gi3-FRET activation assay

Inhibition of endogenous Gi/o proteins with PTX

Cell-surface expression of M2R biosensors

BRET-based G protein-activation experiments (TRUPATH)

G-protein-activation profile of the M2R WT

Functional characterization of M2R biosensors

Internalization assay

Data analysis and statistics

Reporting summary

Data availability

References

Acknowledgements

Funding

Author information

Authors and Affiliations

Contributions

Corresponding authors

Ethics declarations

Competing interests

Peer review

Peer review information

Additional information

Extended data figures and tables

Supplementary information

Source data

Rights and permissions

About this article

Cite this article

Share this article

Search

Quick links

Ligand-unique conformational states of the M₂R

Kinetics of the formation and dynamics of M₂R–G-protein complexes

Bioorthogonal labelling of M₂R biosensors

Labelling screen of M₂R mutants

Single-cell kinetic experiments with M₂R biosensors

G_i3-FRET activation assay

Inhibition of endogenous G_i/o proteins with PTX

Cell-surface expression of M₂R biosensors

G-protein-activation profile of the M₂R WT

Functional characterization of M₂R biosensors