Real-time visualization of ligand-specific conformational dynamics of GPCR C-terminal domain in living cells

Real-time visualization of ligand-specific conformational dynamics of GPCR C-terminal domain in living cells | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Real-time visualization of ligand-specific conformational dynamics of GPCR C-terminal domain in living cells Zhao Lin , Xinyao Chen , Lijuan Ma , Hang Fu , Hao Wang , Kai Yang , View ORCID Profile Zijian Li , Fangfu Ye , Ying Lu , Shuxin Hu , Ming Li doi: https://doi.org/10.1101/2025.07.17.665247 Zhao Lin 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China 2 University of Chinese Academy of Sciences , Beijing 100049, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xinyao Chen 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China 2 University of Chinese Academy of Sciences , Beijing 100049, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lijuan Ma 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hang Fu 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hao Wang 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China 2 University of Chinese Academy of Sciences , Beijing 100049, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kai Yang 3 School of Physical Science and Technology, Soochow University , Suzhou 215006, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zijian Li 4 Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University , Beijing 100191, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Zijian Li Fangfu Ye 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China 2 University of Chinese Academy of Sciences , Beijing 100049, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ying Lu 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China 2 University of Chinese Academy of Sciences , Beijing 100049, China 5 Songshan Lake Materials Laboratory , Dongguan, Guangdong 523808, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: yinglu{at}iphy.ac.cn hushuxin{at}iphy.ac.cn mingli{at}iphy.ac.cn Shuxin Hu 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: yinglu{at}iphy.ac.cn hushuxin{at}iphy.ac.cn mingli{at}iphy.ac.cn Ming Li 1 Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences , Beijing 100190, China 2 University of Chinese Academy of Sciences , Beijing 100049, China 5 Songshan Lake Materials Laboratory , Dongguan, Guangdong 523808, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: yinglu{at}iphy.ac.cn hushuxin{at}iphy.ac.cn mingli{at}iphy.ac.cn Abstract Full Text Info/History Metrics Preview PDF Abstract The intrinsically disordered C-terminal domain (CTD) serves as a critical regulatory element in GPCR 1 – 3 . However, directly interrogating the CTD responses to different ligands is challenging due to its high flexibility, which renders it invisible to conventional structural biology techniques. To address the challenge, we developed a live-cell fluorescence imaging strategy that enables real-time visualization of CTD conformational transitions under physiological conditions. Our dual-mode approach integrates single-cell fluorescence lifetime imaging microscopy (FLIM) with single-molecule total internal reflection fluorescence microscopy (TIRFM), facilitating multi-scale analysis. Our data revealed that the dynamics of both full-length and truncated CTDs in the β2-adrenergic receptors are ligand-specific. By bridging single-molecule dynamics with ensemble cellular responses, our method uncovered previously inaccessible molecular mechanisms underlying receptor activation. This advance not only elucidates how GPCRs transduce ligand binding into functional outcomes but also establishes a versatile platform for drug discovery, enabling rapid assessment of ligand efficacy and receptor activity in physiological contexts. Introduction G protein-coupled receptors (GPCRs) are targets for nearly 40% of approved drugs, establishing them as fundamental to pharmacological research and therapeutic development 4 – 6 . GPCRs signal through two primary activation pathways: G protein-dependent, which elevates cAMP production, and G protein-independent, mediated by GPCR kinase (GRK)-induced phosphorylation and β-arrestin recruitment 7 , 8 . Interrogating the activity of GPCRs in physiological conditions presents a formidable challenge due to their dynamic and transient interactions that are often dependent on the cellular context 9 – 11 . Addressing this challenge demands innovative experimental approaches and rigorous analytical frameworks to accurately interpret the results. Conventional biochemical and biophysical methods have provided fundamental insights, but are often constrained by their indirect nature and inability to resolve real-time GPCR signaling dynamics 12 . A major advance in GPCR research has been the development of biosensors that probe receptor– effector interactions, offering physiologically relevant platforms for studying GPCR activity in primary cells 13 . These tools monitor receptor activation through fluorescence imaging of G protein subunit biosensors or GRK/β-arrestin biosensors. In these bioluminescence resonance energy transfer (BRET)-based analyses, each sensor detects the activity in one pathway 14 , 15 . There remains a critical need for approaches capable of simultaneously interrogating multiple pathways to directly resolve conformational dynamics of key GPCR domains in living systems 16 . The C-terminal domain (CTD) of GPCR, a highly flexible cytosolic region that interacts with diverse signaling and regulatory proteins, serves as a critical sensor of receptor activation 17 , 18 . Far from being a passive linker, this domain actively participates in receptor signaling and desensitization 19 . Particular interest has focused on the complex phosphorylation patterns or “barcodes” within the GPCR CTD, which dictate the selective recruitment of β-arrestins and subsequent pathway-specific signaling 2 , 3 , 20 – 24 . Recent studies employing fluorescence resonance energy transfer (FRET) in combination with other biophysical approaches have provided preliminary insights into the CTD conformational dynamics during ligand binding and downstream signaling 19 , 25 – 28 . However, single-molecule studies that are necessary to unveil the underlying mechanisms of GPCR activation have not yet been successfully performed in living cells. We previously developed an in vitro fluorescence technique called surface-induced fluorescence attenuation (SIFA), which measures FRET from a fluorescent donor to an ensemble of non-fluorescent quenchers in a 2-dimensional plane 29 – 31 . However, the detection range is limited to evens inside the membranes. Here, we extended the approach by incorporating lipophilic dark quenchers 32 into the membrane, thereby shifting the sensitive detection range from the membrane interior to outside the membrane ( Fig. 1 ). This cell surface-induced fluorescence attenuation method reports donor-to-surface distances between ~1-10 nm. We applied the method to investigate the responses of β 2 AR to ligands with distinct pharmacological profiles. β 2 AR regulates numerous physiological processes including cardiac function, airway tone, metabolic function, and so on. We chose to study this prototypical GPCR because it interacts with a rich repertoire of functionally characterized ligands, being an ideal model system for pathway-specific investigations. Our data revealed ligand-specific conformational dynamics in the β 2 AR CTD, with all ligands inducing biphasic responses consisting of rapid initial phases followed by slower secondary phases. Notably, we observed correlated dynamics between the short helix 8 (H8) and the intrinsically disordered CTD tail. Our single-molecule analysis supports the cell-level results and provides a deeper insight into the molecular mechanism underlying the conformational dynamics of CTD. Download figure Open in new tab Fig. 1. The cell surface-induced fluorescence attenuation technique. a , Schematic of sample preparation (left) and the FRET from individual donors near the membrane to multiple quenchers inside the membrane (middle). The right illustrates the F/F 0 (or τ/τ 0 )–distance relationship. b , Imaging platforms and data analysis. Upper left, single-cell imaging using FLIM. Upper middle, representative FLIM images at different times. Upper right, time course of lifetime averaged over a cell of interest. Lower left, single-molecule imaging using TIRFM. Lower middle, representative image stacks showing fluorescent protein-labeled β 2 ARs diffusing at the cell basal plane. Lower right, fluorescent time trace of a molecule of interest. Scale bar: 10 μm. Results Monitoring the C-terminus-to-membrane distance of CTD by the cell surface-induced fluorescence attenuation We engineered a β 2 AR C-terminal fusion with mNeonGreen (β 2 AR-mNG), selected as the FRET donor due to its exceptional brightness, photostability, and longevity 33 , 34 . Plasma membrane-integrated dark quenchers 32 were employed to induce resonant fluorescence attenuation of the donor molecules ( Fig. 1a ). We prioritized non-fluorescent quenchers to minimize signal channel contamination. While octadecyl rhodamine B (R18) has been previously utilized as a FRET acceptor in studies of integrin and T cell receptor conformational changes 35 – 40 , we found its residual fluorescence precluded single-molecule detection. The black hole quencher-1 (BHQ-1; Biosearch Technologies) has optimal spectral overlap with mNG, high extinction coefficient, broad absorption spectrum, and negligible emission 32 , 41 . Cell viability assays confirmed the non-cytotoxic nature of BHQ-1, with normal growth observed even one day after exposing to the quenchers-containing culture medium ( Extended data Fig. 1 ). Our platform enables complementary experimental approaches: fluorescence lifetime imaging microscopy (FLIM) for single-cell temporal analysis and total internal reflection fluorescence (TIRF) microscopy for single-molecule tracking at the basal membrane ( Fig. 1b ). Download figure Open in new tab Extended Data Fig. 1. Photophysical properties and cytotoxicity of the quenchers. a , Comparison between the absorption spectrum of the quencher BHQ-1 and the emission spectra of RhoB and mNeonGreen use as the donors in the current work. b , The Cell Counting Kit-8 (CCK-8) assay was used to compare the viability of Hela cells in the culturing medium with (black) and without (red) BHQ-1. About 2000 cells in 200 μL medium were dispensed to a 96-well plate. After incubation for overnight, the cells were exposed to 20 μM BHQ-1 for 30 min. At 0 h, 24 h and 48h after the incubation, the CCK-8 reagent was added to the wells and incubated for 4 h. The viability of the cells was analyzed by measuring the optical density (OD) at 450 nm (1510, Thermo Fisher). Our analysis indicated that BHQ-1 does not affect the survival of the cells. In experimental implementation, baseline fluorescence intensity (F 0 ) and lifetime (τ 0 ) measurements must precede quencher loading. The quenching efficiency (E) is calculated as E = 1 −F/F 0 = 1 − τ/τ 0 , enabling determination of donor-to-surface distance (denoted as z hereafter) through the attenuation curve shown in Fig.1a . The attenuation profile can be generated via Monte Carlo simulations when the 2-dimensional quencher density and membrane positioning are given 42 ( Extended Data Fig. 2 and Methods). We estimated the positions of the quenchers in the membrane using molecular dynamic simulations. It turned out that the BHQ-1 molecules wedged into the headgroup regions of both leaflets of a lipid bilayer within 1 μs ( Extended Data Fig. 2 ). Before the actual analysis, we demonstrated the feasibility of our method by measuring the dye-to-surface distances of a series of dye-labeled double-stranded DNA (dsDNA) segments standing on the surfaces of giant unilamellar vesicles (GUV) ( Extended Data Fig. 3 ), followed by quencher density calibration using identical dsDNA construct on cell surfaces ( Extended Data Fig. 4 ). In the current work, we added the quenchers to a final concentration of 15 μM. After 30 min, we observed that the lifetime of the fluorescent protein was attenuated to τ/τ 0 ≈ 0.72, indicating an average C-terminal distance of ~5.7 nm from the plasma membrane inner surface in resting cells. This measurement is comparable with previous in vitro FRET data reporting ~6.2 nm separation between the C-terminus and the TM6 helix cytoplasmic end 19 . Download figure Open in new tab Extended Data Fig. 2. Calculation of τ/τ 0 of F/F 0 as a function of the donor-to-surface distance. a . The molecular dynamics (MD) simulations give the position of the quenchers in the membrane. The BHQ-1 molecules stay in the headgroup region (grey beads) irrespective of the initial conditions: either on the surfaces (upper panel) or in the middle plane (lower panel) of the lipid bilayer. b . The Monte Carlo simulation can be applied to calculate τ/τ 0 of F/F 0 as a function of the donor-to-surface distance given the positions of the quenchers and their 2D density. The cycles are experimental data as measured according to the method in Extended Data Fig. 3 . c . List of DNA sequences used in the calibration. Download figure Open in new tab Extended Data Fig. 3. Demonstration of the method by measuring the dye-to-surface distance of a series of dsDNA on GUV. a , FLIM images of GUVs containing TAMRA-labeled dsDNA segments of various lengths in the presence of 5 μM BHQ-1. The GUVs were tethered on the bottom of the fluidic chamber. b , Histograms of the photon arrival times as measured by TCSPC (see Methods). Each histogram was fitted to an exponential function to obtain the corresponding lifetime. c , Statistic data of τ /τ 0 obtained from different GUVs with dsDNA segment of various lengths. d , Comparison of the F/F 0 (or τ/τ 0 )–distance relationship calculated by using the Monte Carlo simulation presented in Extended Figure 2 to that measured in c . Error bars are standard derivations. Download figure Open in new tab Extended Data Fig. 4. Calibration of the 2D density of BHQ-1 in the plasma membrane. a , FLIM images of cells containing TAMRA-labeled dsDNA segments of various lengths in the presence of 15 μM BHQ-1. b , Histograms of the photon arrival times as measured by TCSPC. c , Statistic data of τ /τ 0 obtained from different cells containing dsDNA segment of various lengths. d , The density of BHQ-1 was determined by comparing the τ/τ 0 –distance curve (red line) as calculated by the Monte Carlo simulation to the experimental data. Also shown is the τ/τ 0 –distance curve (green line) for GPF. Error bars are standard derivations. Distinct responses of the GPCR CTD to different ligands We characterized the β 2 AR CTD conformational evolutions in response to four distinct agonists: carazolol (antagonist), ICL 3-9 (G protein-biased agonist), ICL 1-9 (β arrestin-biased agonist), and isoproterenol (ISO, full agonist) ( Fig. 2 ). Time-lapse FLIM images were collected on each cell selected ( Extended Data Fig. 5 and 6 ). The lifetime of the β 2 AR-mNG averaged over each cell surface was obtained by fitting the fluorescence decay curve to an exponential function. Each ligand elicited distinct temporal patterns. (1) The antagonist carazolol (10 μM) induced immediate distance reduction ( Fig. 2a middle). It was recently reported that various GPCRs exhibit basal activity in resting cells 43 – 45 , 46 , namely, the GPCR might spontaneously switch from the inactive state to the active state. It is also known that carazolol has the ability to suppress the β 2 AR active state. Our results suggest the measured distance represents a population-weighted average between inactive (compact CTD) and active (extended CTD) conformations. (2) The G protein-biased agonist ICL 3-9 (10 μM) produced biphasic CTD movement: rapid initial extension followed by gradual retraction ( Fig. 2b middle). This pattern reflects G protein recruitment (increasing CTD-membrane distance) followed by receptor desensitization 47 , consistent with ICL 3-9’s selective G protein coupling without GRK activation 48 , 49 Again, the explanation requires the assumption that the GPCR C-terminus in the G protein-bound state has a larger distance than that in the G protein-unbound state. (3) The arrestin-biased agonist ICL 1-9 (10 μM) induced opposite CTD movement respect to that induced by the G-biased agonist ( Fig. 2c middle), with immediate membrane approximation (lifetime minimum at ~3 min) persisting throughout observation. This mirrors its β-arrestin-biased activation profile. (4) Full agonists can activate both the G protein-dependent and the G protein-independent pathways. ISO is a well-known full agonist with high efficacy. In contrary to the three ligands investigated above, ISO treatment yielded delayed response kinetics ( Fig. 2d middle). The absence of immediate lifetime changes reflects counterbalancing G protein and GRK actions, with subsequent decline (after ~10 min) indicating net desensitization as G protein coupling diminishes. As demonstrated later, this temporal profile actually reflects robust, coordinated activation of both pathways rather than weak agonism. Download figure Open in new tab Extended Data Figure. 5. FLIM measurements of β 2 AR-mNG upon addition of carazolol. a , Time lapse FLIM. The corresponding cell-level lifetimes were obtained by fitting the histograms of the photon arrival times as determined by TCSPC (see Methods). b , The evolutions of the lifetimes of 4 representative cells. Error bars are standard derivations. Download figure Open in new tab Extended Data Fig. 6. Comparison of the effects of different ligands. The illustrated are representative FLIM images, histograms of the photon arrival time under different conditions. Download figure Open in new tab Fig. 2. Agonists-induced conformational changes of CTD derived from FLIM. a , Time courses of the relative lifetime and the corresponding C-terminus-to-surface distance for β 2 AR (middle) and β 2 AR△CTD (right) upon addition of carazolol whose function is sketched in the left. The ligands were introduced at t=0 min. The depicted CDT conformations inside the figures are just schematic. b , Data for ICL 3-9. c , Data for ICL 1-9. d , Data for ISO. The signal pathways are depicted on the left column. Error bars are standard derivations. Distinct responses of the GPCR H8 helix to different ligands To view the changes of the CTD’s conformation from a different perspective, we engineered a truncated β 2 AR variant (β 2 AR△CTD) where the disordered tail was removed after Ser346, with a 10-residue linker connecting Ser346 to mNG. This construct enabled specific monitoring of the H8 helix dynamics, revealing ligand-specific responses distinct from full-length β 2 AR. (1) Carazolol induced rapid H8 approximation to the membrane ( Fig. 2a right), mirroring but slightly exceeding the displacement observed in full-length β 2 AR. This enhanced response aligns with reported elevated constitutive G protein activity in β 2 AR△CTD 26 , suggesting greater antagonist-mediated suppression of pre-existing G protein binding events. (2) The G-biased agonist ICL 3-9 promoted H8 displacement from the membrane ( Fig. 2b right), though with reduced magnitude compared to full-length β 2 AR. This attenuated response further supports the constitutive activity model 26 , as β 2 AR△CTD’s pre-activated state offers fewer additional G protein coupling opportunities. (3) The arrestin-biased agonist ICL 1-9 elicited no detectable H8 movement ( Fig. 2c right), indicating H8 conformational changes are G pathway-specific. This null result confirms the requirement of an intact CTD for GRK phosphorylation and β-arrestin recruitment 50 . (4) Contrasting with the delayed response in full-length receptors, β 2 AR△CTD-mNG responded immediately to ISO, displaying an apparent increase of the averaged lifetime ( Fig. 2d right). This unambiguous G protein signature confirms that GRK-mediated effects normally counteract early G protein actions in wild-type β 2 AR. Our results revealed two key mechanistic insights into β 2 AR regulation: First, the H8 helix undergoes ligand-dependent conformational changes independently of the disordered C-terminal tail. Second, the coordinated dynamics of β 2 AR-mNG and β 2 AR△CTD-mNG in G protein signaling suggest a hierarchical propagation of conformational changes—from ligand-induced transmembrane domain rearrangements to H8 movement, which subsequently drives C-tail displacement. This model contrasts with previous in vitro proposals that emphasized G protein binding-mediated disruption of electrostatic interactions between the negatively charged C-tail and positively charged receptor core as the primary driver of C-tail mobility 26 , 51 . Inhibition of the basal activity by antagonists at the single-molecule level The single-molecule dynamics of β 2 AR-mNG were monitored using TIRFM combined with fluorescence recovery after photobleaching (FRAP) 52 to achieve optimal molecular densities for tracking 53 ( Fig. 3a ). The receptors in quencher-treated cells exhibited two predominant conformations: a ground state (F/F 0 ≈ 0.65, z ≈ 4.6 nm; blue line) and an occasionally excited state (F/F 0 ≈ 0.85, z ≈ 6.8 nm; magenta line) ( Fig. 3b ). These in vivo observations align with previous in vitro results of spontaneous G protein binding to unstimulated GPCR 46 , 54 , suggesting the excited state represents the transient G protein coupling events. This supports a model where β 2 AR primarily resides in an inactive conformation in resting cells, fluctuating occasionally to the active state. Antagonists inhibit the coupling of GPCRs to G proteins and β-arrestins 55 . As expected, the antagonist carazolol reduced the excited state population from 36% (–5-0 min pre-treatment) to 16% (1-5 min post-treatment) ( Fig. 3c ). Intriguingly, we observed a transient rebound (27% at 5-10 min) before final stabilization at 15% (after 20 min). The population-weighted lifetime calculations (asterisks in Fig. 3d ) demonstrate excellent agreement with the ensemble FLIM measurements ( Fig. 2a ). Notably, this correlation confirms that the small but reproducible lifetime increase at ~10 min in Fig. 2a reflects genuine biological variation rather than measurement artifact. Download figure Open in new tab Fig. 3. Single-molecule analysis of the CTD conformations in resting and antagonist-inhibited cells. a , TIRF images of a Hela cell expressing β 2 AR-mNG before (left), immediate after (middle) and 2 min after photobleaching. Scale bar = 10 μm. b , Representative time traces of F/F 0 of β 2 AR-mNG sketched on the left. Two conformations were observed in both the resting cells and the antagonist-inhibited cells. The grey traces are the intrinsic fluorescence. c , Histograms displaying the relative populations of the membrane-proximal (blue) and the membrane-distal (magenta) conformation at different times after loading carazolol. d , Bar chart of the integrated area of the two conformations and the population-weighted averages of the lifetimes (asterisks) at the time points marked in (c). e-g , The results for β 2 AR△CTD-mNG. The single-molecule analysis of β 2 AR△CTD revealed two distinct conformations of H8 in resting cells: a compact state (F/F 0 ≈ 0.48, z ≈ 2.8 nm; blue) and an extended state (F/F 0 ≈ 0.63, z ≈ 4.3 nm; magenta) ( Fig. 3e ). The 1.5 nm displacement (Δz) between these states corresponds approximately to the length of H8, suggesting a dramatic reorientation from membrane-parallel (inactive) to nearly perpendicular (active) configurations. Again, the population-weighted lifetimes in different time windows (asterisks in Fig. 3g ) after the addition of carazolol agree well with the cell-level results for carazolol in Fig. 2a . Compare of the conformational dynamics of β 2 AR CTD associating with G proteins and β–arrestins We compared the conformational dynamics of CTD in the G protein-dependent and the arrestin-dependent pathways using two biased agonists 49 . As established, ICL 3-9 selectively promotes G protein coupling without inducing GRK phosphorylation or β-arrestin recruitment ( Fig. 4a ) 48 , 49 . Illustrated in Fig. 4b are the fluorescence traces and the relative proportions of the inactive and the active states in different time windows. The single-molecule trajectories revealed that ICL 3-9 (10 μM) rapidly increased the population of the extended conformation (F/F 0 ≈ 0.85, z ≈ 6.8 nm) from 37% (resting state) to 49% within one minute, accounting for the immediate lifetime shift observed in FLIM. The population-weighted lifetimes ( Fig. 4c ) agree with that measured by FLIM at the corresponding time windows. The data suggest an increase of the amount of G proteins recruited to the activated GPCRs and then a decrease of the amount of G proteins due to desensitization of the receptors. Download figure Open in new tab Fig. 4. Biased agonists induce opposite conformational changes of CTD. a , Schematic of the G protein-dependent pathway activated by ICL 3-9. b , Fluorescence traces collected at different time windows indicated in the figures. The histogram for each time window is displayed on the right. c , Bar chart of the integrated area of the Gaussian peaks in the histograms and the population-weighted averages of the lifetimes (asterisks) at the corresponding time windows. d-f , Results for the GRK/β-arrestin-dependent pathway activated by ICL 1-9. By contrast, ICL 1-9 can induce GRK-mediated β 2 AR CTD phosphorylation followed by β-arrestin recruitment without promoting the cAMP production 48 , 56 , 57 ( Fig. 4d ). In line with this, we observed new events in which the fluorescent intensity abruptly jumped from the ground state (F/F 0 ≈ 0.65) to a compact conformation (F/F 0 ≈ 0.35, z ≈ 1.0 nm; green) ( Fig. 4e ). In contrast to the case for G protein binding, we only observe the consequence of the GRK-mediated phosphorylation. That is, we did not observe an intermediate state in which a GRK was in association with a GPCR, which should result in a value of F/F 0 that was different from either F/F 0 ≈ 0.65 or F/F 0 ≈ 0.35. The action of GRK on GPCR might be too fast to be caught by our technique. Our data agree well with an NMR result that the phosphorylated CTD of β 2 AR tends to stick to the cytoplasmic face of the receptor’s transmembrane region and generates the structural motif for β-arrestin binding 51 . Subsequently, a third state emerged (F/F 0 ≈ 0.45, z ≈ 2.5 nm; brown) that was abolished when β-arrestin1 and 2 were knocked down (Extended data Fig.7), confirming its identity as the β-arrestin-bound complex. These results demonstrate fundamentally opposing CTD movements in G protein versus β-arrestin pathways ( Fig. 4a, d ): while G protein coupling extends the CTD (z ≈ 6.8 nm), β-arrestin recruitment drives progressive membrane proximation through phosphorylation-dependent compaction. Concurrent activations of G proteins and GRKs by a full agonist Consistent with ISO’s dual activation of both G protein and β-arrestin pathways, we observed concurrent increases of two distinct states within 1-5 min: the extended conformation (F/F 0 ≈ 0.85, z ≈ 6.8 nm) reflecting G protein binding, and the compact conformation (F/F 0 ≈ 0.35, z ≈ 1.0 nm) indicating phosphorylation ( Fig. 5 ). Quantitative analysis revealed that G protein coupling initially dominated (1-5 min), with its signal attenuation by counterbalancing GRK activity. Subsequently, phosphorylated and β-arrestin-coupled states progressively increased at the expense of the G protein-bound receptors. By 20 min, the G protein-bound population decreased markedly while β-arrestin recruitment continued, causing net lifetime reduction ( Fig. 5c ). Altogether, our observations are consistent with the mechanism that the activated GPCRs recruit G proteins, and then GRKs/β-arrestins can function as regulators to desensitize the receptors 7 . The C-tail moved away from the membrane in the G protein-dependent pathway and toward the membrane in the β-arrestin-dependent pathway. This bidirectional movement explains why the so-far most effective ligand ISO for full-length β 2 AR seemed to result in modest changes in the FLIM assay in Fig. 2 . In contrast, β 2 AR△CTD exhibited unambiguous lifetime increases upon ISO stimulation, reflecting uncompensated G protein activation in the absence of CTD-mediated phosphorylation. Download figure Open in new tab Fig. 5. Concomitant activation of two pathways by ISO. a , Representative fluorescence traces with the states attributed to G protein binding (magenta lines), phosphorylation (green lines) and β-arrestin binding (brown lines) at different time windows after loading the ISO. The corresponding histograms are on the right of the traces (n is the number of the traces in the statistics). b , Bar chart of the integrated area of the Gaussian peaks in the histograms and the population-weighted averages of the lifetimes (asterisks) at the corresponding time windows. c , Schematic of β 2 AR CTD conformations. Discussion The activation of GPCR was often investigated using indirect biosensors involving second messengers which may introduce system cross-talks and lead to overestimation of the efficacy of ligands due to certain amplification mechanisms 58 , 59 . Directly monitoring the CTD’s conformational dynamics can migrate these shortages. In the present work, we imaged the conformational dynamics of GPCR CTD by using the cell surface-induced fluorescence attenuation technique. It enabled us to distinguish the responses of GPCR to different agonists. By selectively evoking different signal pathways, we resolved unique conformations of the β 2 AR CTD in the different states. The β 2 AR CTD in resting cells stay predominately in the auto-inhibited state in which the CTD is proximal to the membrane surface. The CTD may occasionally fluctuate to a distal position upon G protein binding and return to the auto-inhibited state as the G protein dissociates. We found that the downstream effectors induced transient conformational states, exhibiting a feature that the association of an effector to GPCR was always followed by its dissociation after a short time. The GPCR interaction with GRK was more transient such that we even could not discern the GRK binding events due to limited temporal resolution of our single molecule assay. However, we identified a state that was the consequence of the GRK-induced phosphorylation that brings the CTD close to the membrane. The binding of β-arrestin to the phosphorylated β 2 AR resulted in a state in which the C-terminus became slightly further to the membrane than it was in the phosphorylated state. We found that the CTD in the β-arrestin-bound state was closer to the membrane than in the inactive state. This agrees with a model in which the phosphorylation of the C-tail strengthens its interaction with the positively charged cytoplasmic ends of the transmembrane domains, bringing it closer to the plasma membrane 51 . This work establishes CTD dynamics as a direct readout of GPCR activation states, free from downstream signaling veil. The observed conformational spectrum—from extended (G protein-bound) to compact (phosphorylated/β-arrestin-bound) states—provides a structural framework for understanding pathway-specific regulation. Our study revealed two surprising findings that challenge existing GPCR structural models. First, we observed significant outward displacement of the β 2 AR H8 helix upon ligand stimulation—a dramatic conformational change contrasting with crystallographic studies showing membrane-parallel H8 orientations in both active and inactive states 60 – 63 . The dissociation of the amphiphilic helix from the plasma membrane may induce partial unfolding. This model agrees with a report that agonist binding may cause H8 to lose part of its helical structure 64 , 65 . Cell-level FRET studies on mechanosensitive GPCRs such as the histamine H1 and the B2 receptors revealed that mechanical stimulations may lead to increase of the distance between the H8 C-terminal and N-terminal or between the H8 C-terminal and the cytoplasmic end of TM6 27 , 28 . Our data suggest these changes may reflect complete H8 membrane dissociation rather than simple spring-like extension 66 , potentially revising current understanding of H8 dynamics. Second, we identified unexpected slow recovery of FLIM signals following carazolol-induced compaction ( Fig. 2b ), with single-molecule data showing transient repopulation of the F/F 0 ≈ 0.85 state (5-10 min window; Fig. 3 ). Although this phenomenon could be explained by variations in G protein recruitment, we cannot exclude contributions from unidentified interacting proteins that produce similar binding kinetics. Obviously, the subject warrants comprehensive investigations in the future. The ensemble FLIM data in Fig. 2 can be quantitatively modeled by integrating the measured mNG-to-surface distances ( Fig. 6 ) with the corresponding state populations. Resting β 2 AR exhibited basal activity characterized by a small spontaneously active subpopulation N G0 with an average lifetime ratio τ intact /τ 0 ≈ 0.72. ICL 3-9 stimulation enhanced G protein recruitment, rapidly increasing the G protein-bound population, followed by gradual decline due to desensitization mechanisms such as PKA-mediated phosphorylation 47 , 67 , ultimately stabilizing at a lower level 68 . These processes can be described by two kinetic equations ( Eq. S2 and S3 in the Methods), the solutions of which give where P G (t) = α (1 − exp(− k G t )) − β (1 − exp(− k de t )) + P G (0) and P InAct (t) =1 − P G ( t ). The relative lifetime of the inactive GPCRs τ InAct / τ 0 ≈ 0.65 and that of G protein-bound GPCRs τ G / τ 0 ≈ 0.65 were measured by single-molecule TIRF. P G (0) = 35% was measured before the agonists loading. One can consider α as the apparent G protein recruitment efficiency with a rate k G , and β the apparent desensitization efficiency with a rate k de . These parameters can be estimated by fitting τ ( t )/ τ 0 in Eq. (1) to the FLIM curve for ICL 3-9 ( Fig. 6b and Extended data Fig. 8 ). Download figure Open in new tab Fig. 6. Cell-level kinetics of G protein binding, phosphorylation and subsequent β-arrestin binding according to the conformational changes of the β 2 AR-CTD. a , Schematics of the β 2 AR CTD conformations at various states as derived from the single-molecule analysis. b , Time courses of the proportions of GPCRs with bound G proteins (magenta), with the CTD phosphorylated (green), and with the bound β-arrestins (brown) upon additions of the ligands. The blue curves represent the proportion of the GPCRs remained inactive. Download figure Open in new tab Extended Data Fig. 7. Comparison of the fluorescence traces for ICL 1-9 stimulated cells when the arrestin1 and 2 were knocked down (left panel) or not (right panel). The phosphorylation resulted in jumps from the inactive state (blue line) to the phosphorylated state (green line). The state (yellow line) of the arrestin binding were not observed in the arrestin1 and 2 knockdown cells. Download figure Open in new tab Extended Data Figure 8. Fittings of the time evolutions of the population-weighted lifetimes of GFPs in the cells stimulated by ICL 3-9, ICL 1-9 and ISO. a , Experimental data from Fig. 2 were fitted using the equations 1 – 3 in the main text. b , Fitting parameters used to produce the time evolutions of the proportions of the states illustrated in Fig. 6b in the main text. For the β-arrestin biased agonist, the rapid phosphorylation was followed by slow binding of β-arrestin. The processes can also be described by similar kinetic equations ( Eq. S7 and S10 ), the solutions of which can be used to fit the lifetime evolution curve for ICL 1-9 in Fig. 2c ( Fig. 6b and Extended data Fig. 8 ), where P phos ( t ) = γ (1−exp ( −k phost ))−ε(1 − exp( −k Arr t )) and P Arr ( t ) = ε (1 − exp( −k Arr t )), and P intact ( t ) = 1 − P phos ( t ) − P Arr ( t ) represents the GPCRs that were not phosphorylated, hence remained intact. The relative lifetimes of the β-arrestin-bound GPCRs is τArr /τ 0 ≈ 0.45, that of the only phosphorylated is τ phos / τ 0 ≈ 0.35, and that of intact GPCRs is τ intact / τ 0 ≈ 0.72. One can consider γ as the apparent efficiency of GRK-induced phosphorylation with a rate k phos , and ε the apparent efficiency of β-arrestin recruitment with a rate k Arr . In the case of full agonists, it is rational to assume that the G protein binding, the GRK-induced phosphorylation, and the β-arrestin recruitment have features similar to their counterparts in the biased pathways. The time course of the lifetime for ISO-induced activation has the form (see Eq. S16 – S21 for details), where P InAct ( t ) =1 − P G ( t ) − P phos ( t ) − P Arr ( t ), and P G ( t ), P phos ( t ) and P Arr ( t ) have the forms given in Eqs. (1) and (2). Again, the apparent efficiencies and the corresponding rate constants can be estimated by fitting τ ( t )/ τ 0 in Eq. (3) to the FLIM curve for ISO in Fig. 2d (see Fig. 6b and Extended data Fig. 8 ). It is noteworthy that, according to our data fitting, the subpopulations contributed by the GRK/β-arrestin activation induced by ISO seemed almost equal to that induced by ICL 1-9. This is in disagreement with previous reports that ISO may stimulate one third more phosphorylated CTD than ICL 1-9 may do. We can attribute this discrepancy to the fact that ISO may induce a higher number of endosomes than ICL 1-9 56 . The GPCRs not on the plasma membrane were invisible to our technique. The internalized GPCR-mNG molecules on the endosomes have a shorter lifetime ( Extended data Fig. 9 ), but they do not contribute to the averaging of the lifetime. Hence, ISO actually induced stronger GRK/β-arrestin activation than we could detect. Download figure Open in new tab Extended Data Fig. 9. ISO-induced internalization leads to decrease of the number of the activated GPCRs in the cell membrane. a . The number of endosomes increased with time after stimulation by ISO. b . The lifetime of the GFPs associated with the endosomes was shorter than that in the plasma membrane. In summary, we have developed a versatile fluorescence-based method for quantitatively monitoring GPCR CTD conformational dynamics in living cells with single-molecule sensitivity. This technique successfully bridges cellular-scale observations with molecular-level resolution, enabling precise characterization of ligand-specific receptor activation patterns. The approach shows particular promise for drug discovery applications, where its exceptional spatiotemporal resolution can discriminate subtle differences in receptor activation profiles among candidate compounds. More broadly, this platform should prove valuable for studying diverse membrane receptors with dynamic cytoplasmic domains under physiological conditions. It is noteworthy that the plasma membrane of a cell may be heterogenous, resulting in variations of the density of the quenchers in the membrane. If this does occur, one can use standard rulers such as the dye-labeled dsDNA segments ( Extended data Fig. 4 ) to calibrate the local density of the dark quenchers in the membrane. Methods Principle of the method Distance dependence of the fluorescence signal Our method is essentially the FRET between a single fluorophore near the plasma membrane and an ensemble of quenchers integrated in the membrane. The energy transfer kinetics k t is the sum of pairwise transfer rates, where τ 0 is the intrinsic lifetime of the donor, r 0 the F□rster distance between the donor and a quencher molecule, and rj the spatial distance between the donor and the j th quencher. The FRET efficiency is The experimentally measured relative fluorescent intensity F/F 0 and/or the relative lifetime τ /τ 0 are given by Assuming that the quenchers diffuse in the membrane, the energy transfer efficiency can be calculated by using the Monte Carlo simulations proposed in Ref. 69. 69 Molecular dynamic (MD) simulation of the position of quenchers in the membrane The spatial distance rj between the donor and the j th quencher depends on the position of the donor to be measured and the position of the quenchers that can be determined by MD simulations, which was performed by using the GROMACS 2021.4 package ( www.gromacs.org ) with the MARTINI force field 70 . The simulation was carried out in the semi-isotropic ensemble at a temperature of 300 K and a pressure of 1.0 bar. 71 , 72 The all-atom model of BHQ-1 was built by the ChemDraw software and coarse-grained using the method developed by Miller et. al. 73 . A bilayer consisting of 720 1,2-Dioleoyl-sn-glycero-3-phosphocholine (DOPC) lipids was constructed, 4 BHQ-1 molecules were added to both monolayers or the bilayer midplane. At least three independent runs were performed for at least 10 μs with a time step of 20 fs to ensure computational consistency. Sample preparations for imaging The GUVs The GUVs used in the calibration were generated via electro-formation using a Nanion Vesicle Prep Pro setup (Nanion Technologies), following the protocol provided in Ref. 74. 74 The lipid compositions are 20% (by mol/mol) 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine 10% (DOPC), 50% 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC), 0.1% 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine-N-(cap biotinyl) (Biotinyl-cap PE) and 20% cholesterol. The GUVs were added into a flow chamber with a streptavidin-coated glass surface 69 and incubated for 2 min before each measurement. The plasmids The β 2 AR-mNeonGreen fusion construct was generated by PCR amplification of both genes. The β 2 AR sequence was amplified using a forward primer (5′-GCG CGC CAT GGG GTA CCC ATA CGA CGT CCC AGA CTA CGC CCA ACC CGG GAA CGG CA-3′) and a reverse primer (5′-TGG ATC CCG GGC CCG CGG TAC CGT CGA CCA GCA GTG AGT CAT TTG TAC TA-3′) containing BssHII and BamHI restriction sites. mNeonGreen was amplified with a forward primer (5′-GGA TCC ATC GTG AGC AAG GGC GAG GA-3′) incorporating a BamHI site and a reverse primer (5′-TCT AGA TCC GGA TCA CTT GTA CAG CTC GTC CAT-3′) with an XbaI site. The digested PCR products (BssHII/BamHI for β 2 AR; BamHI/XbaI for mNeonGreen) were ligated into the BssHII/XbaI-digested pEGFP vector (Clontech). A truncated β 2 AR variant (after S346) was created by substituting the reverse primer with 5′-GGA TCC CGG GCC CGC GGT ACC GTC GAC AGA AGA CCT GCG CAG G-3′. β-arrestin1 and β-arrestin2-miRFP670nano3 constructs were generated similarly, using pcDNA3.1 as the backbone vector with NheI and BglII restriction sites. All constructs were verified by DNA sequencing (BGI, Shenzhen). The cells Hela cells (ATCC, USA) were cultured in Dulbecco’s modified Eagle medium (DMEM, Corning) with 10% (vol/vol) fetal bovine serum (FBS, Gibco, Life Technologies, USA) and 1% penicillin-streptomycin (Gibco, Life Technologies, USA) medium maintained in a humidified incubator with 5% CO 2 at 37 °C. The cells were routinely tested for mycoplasma. In general, when the cell confluency reached ~80%, the cells were treated with 0.25% trypsin (Gibco, Life Technologies, USA) and passaged or transfected. Transfection was performed with Lipofectamine 3000 (Invitrogen, USA) according to the manufacturer’s instructions. Five hours after transfection, the cells were digested with trypsin and plated onto 35 mm confocal dishes with glass bottoms (Cellvis, USA) and cultured for another 6-24 h before imaging. Before imaging, medium was changed to live cell imaging buffer (Invitrogen, USA). The fluorophore-labeled DNA All DNAs were purchased from Sangon Biotec, China. One of the ssDNA was labeled with tetramethylrhodamine (TAMRA) at the 5′-end. The complementary ssDNA was labeled with cholesterol at the 5′-end. The dsDNA was diluted to 100 nM for the FLIM measurements and 0.1 nM for the TRIF measurements. The imaging and calibration methods The calibration process using the GUVs The 2-dimensional density of the quenchers in the membrane should be determined at first to calculate the distance dependence of the fluorescence signal by using the Monte Carlo simulations. To this end, we calibrated the FRET efficiency at various positions by measuring the lifetimes of fluorophores attached to a series of dsDNA segments with lengths 12, 16, 20 and 24 bp ( Extended data Fig. 3a-d ). The vesicles were immobilized on the bottom of the sample chamber through biotin–streptavidin interaction 69 . The DNA samples were anchored by the cholesterol molecules to the surface of the lipid vesicles. The intrinsic fluorescence lifetime τ 0 . was measured at first. Then the buffer with 0.5 μM BHQ-1 was flowed in. The lifetime τ was measured after incubation for 30 min. The live cell imaging Before the imaging, the cells were transferred into the live-cell imaging buffer (Thermo Fisher Scientific) to maintain the physiological conditions. We first calibrated the density of BHQ-1 in the plasma membrane following the procedure used in the vesicle experiments ( Extended data Fig. 4a-d ). It is worth noting that the lipid vesicles have higher BHQ-1 adsorption than the live cells. We measured the cells transfected with fluorophore-labeled proteins. After measuring the τ 0 and τ (or F 0 and F ), the quenchers were added to the living cell imaging solution (from Thermos Fisher) and incubated for 30 min before each measurement. We then introduced the agonist and monitored the fluorescence changes with time. The cells of interest were imaged with FLIM and/or with TIRF. The TIRF measurements were performed on an objective-based TIRF microscope (IX71, Olympus) at room temperature. An oil-immersion objective (×100, NA 1.49) was used. The fluorescence signals from the cell were collected by an EMCCD (iXON, Andor Technology) with a 50-ms exposure time per frame. The fluorescence molecules were excited by a 488-nm sapphire laser (Coherent Inc.). The imaging process was controlled and recorded by MetaMorph software (Molecular Device, California). The FLIM measurements were performed on a confocal laser scanning microscope (FV3000, Olympus) equipped with a multi-channel picosecond event timer (Hydraharp 400, PicoQuant) with 16 ps time resolution. The excitation unit consisted of a pulsed diode laser (λ exc =488 nm, LDH-D-TA 488, 20 mW, PicoQuant) with a pulse width 70 ps FWHM and a repetition rate 80 MHz. A high numerical aperture objective (UPLSAPO 100× oil, NA 1.49, Olympus) was used to focus the light into the sample and collect the fluorescence emission. The theory for the effector kinetics after addition of the ligands Kinetics of effectors evoked by the G protein-biased agonists Let N 0 be the total number of GPCRs on the cell membrane. All agonists are assumed to bind to the GPCRs at t = 0. We first consider the desensitization, including that mediated by PKA. The change of the number of desensitized GPCRs N de ( t ) follows where K de is the effective desensitization rate and ζ the desensitization efficacy. The solution of Eq. (S1) is Given that the desensitized GPCRs do not recruit the G proteins, the change of the G protein-bound receptors N G ( t ) follows where K G − on is the effective recruitment rate of G proteins, and κ the ligand-induced G protein recruitment efficacy. The solution to Eq. (S3) is with the parameters representing the basal G protein activation prior to the addition of the agonists. The total number of the receptors that are not occupied by the G proteins is given by The ensemble average of the lifetime is then given by where P G-off (t) = N G-off (t) /N 0 and P G (t)N G (t) /N 0 . Our single-molecule measurements identified only two states in the G protein-dependent pathway: the G protein-bound state with τ G /τ 0 = F G /F G ≈ 0.85 and the inactive state with τ InAct /τ 0 = F InAct /F 0 ≈ 0.65. Our results suggested that that the lifetime in the desensitized state is the same as that in the inactive state. Kinetic model for the GRK/βarrestin-biased agonists In this process, the phosphorylation of GPCRs by GRK5 and GRK6 is described by where k GRK5 and K GRK6 are the phosphorylation rates, and γ GRK5 /k GRK6 reflect the phosphorylation efficacy. One has, Since our experiments did not distinguish the lifetimes of the phosphorylated states by GRK5 and GRK6, we approximate the total phosphorylated GPCRs N pho ( t ) as where k pho is the averaged phosphorylation rate and γ represents the combined efficacy of GRK-mediated phosphorylation. The phosphorylated GPCRs recruit β-arrestins, where k Arr is the effective β-arrestin recruitment rate, and η denotes agonist efficacy for β-arrestin binding. One has with . We found by single-molecule measurements that k pho » k Arr . The first term in Eq. (S11) is hence negligibly small. Therefore, Eq. (11) can be simplified to Only a fraction of the phosphorylated GPCRs are bound by β-arrestins. The number of GPCRs that are merely phosphorylated is The number of the intact (unphosphorylated) GPCRs is The ensemble average of the lifetime is where and P intact ( t ) = 1 − P pho ( t ). The lifetime and can be directly measured at the single-molecule level. The lifetime can be calculated assuming that the same proportion of the intact GPCRs have the basal activity (~35%) and the rest remain inactive (~65%). Therefore, one has for β2AR according to our single-molecule measurements. Kinetic model for full agonists In this case, the activation of GPCRs evokes two pathways in parallel. There are desensitization processes in both the pathways. We first consider the desensitization, including the GRK2/3-mediated phosphorylation in the G protein-dependent pathway and the GRK5/6-mediated phosphorylation in the G protein-independent pathway. The total desensitization rate combines these contributions, Give n the fact that the desensitized GPCRs do not recruit G proteins, the agonist-induced G protein recruitment follows It should be noted that the kinetics of the GRK2/3-mediated phosphorylation is proportional to the number of the G protein-bound receptors N G ( t ). The two equations are therefore coupled to each other. If can be proved that, under the condition k G − on 2 ≥ 4 k G − on δk GRK2/3 ζ GRK2/3 (i.e., G protein recruitment is faster than GRK2/3-mediated desensitization), the number of the desensitized receptors is In Eq. (S18) , the fast phosphorylation processes saturate quickly, leaving slow desensitization dominant. One can use a single function to approximate the effective desensitization As a result, the G protein-bound receptors still has the form which is the same as that in Eq. (S4) . In the G protein-independent pathway, one wants to consider the fast phosphorylation and the β-Arrstin recruitment that follows. Again, the number of the phosphorylated receptors can be represented by a single function which is the same as that in Eq. (S9) . For the β-Arrestin-bound receptors, one also has which are the same as Eq. (S12) and Eq. (S13) , respectively. The number of the inactive receptor s is The ensemble average of the lifetimes is where . Author contributions Z.L., X.C. and L.M. contributed equally to this work. M.L., S.H., Y.L. and Z.L. conceptualized the study. Z.L. and L.M. performed the single-cell experiments. X.C., Z.L., L.M., H.F. and H.W. performed the single-molecule experiments, Z.L., X.C., H.F., H.W. and F.Y. analyzed the data. L.M. and Z.L. prepared the cells. Z.L. and K.Y. designed and performed the molecular dynamics simulations. Z.L., M.L., S.H. Y.L., and F.Y. wrote the manuscript. Competing interests The authors declare no competing interest. Acknowledgement This work was supported by the National Key Research and Development Program of China (2019YFA0709304); the National Natural Science Foundation of China (T2221001, 32171228, 32471278); the Chinese Academy of Sciences Project for Young Scientists in Basic Research (YSBR-104). Funder Information Declared National Key Research and Development Program of China , 2019YFA0709304 Reference 1. ↵ Venkatakrishnan , A. J. et al. 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Share Real-time visualization of ligand-specific conformational dynamics of GPCR C-terminal domain in living cells Zhao Lin , Xinyao Chen , Lijuan Ma , Hang Fu , Hao Wang , Kai Yang , Zijian Li , Fangfu Ye , Ying Lu , Shuxin Hu , Ming Li bioRxiv 2025.07.17.665247; doi: https://doi.org/10.1101/2025.07.17.665247 Share This Article: Copy Citation Tools Real-time visualization of ligand-specific conformational dynamics of GPCR C-terminal domain in living cells Zhao Lin , Xinyao Chen , Lijuan Ma , Hang Fu , Hao Wang , Kai Yang , Zijian Li , Fangfu Ye , Ying Lu , Shuxin Hu , Ming Li bioRxiv 2025.07.17.665247; doi: https://doi.org/10.1101/2025.07.17.665247 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Biophysics Subject Areas All Articles Animal Behavior and Cognition (7618) Biochemistry (17636) Bioengineering (13859) Bioinformatics (41847) Biophysics (21401) Cancer Biology (18535) Cell Biology (25423) Clinical Trials (138) Developmental Biology (13353) Ecology (19860) Epidemiology (2067) Evolutionary Biology (24287) Genetics (15582) Genomics (22463) Immunology (17701) Microbiology (40300) Molecular Biology (17141) Neuroscience (88432) Paleontology (666) Pathology (2825) Pharmacology and Toxicology (4813) Physiology (7633) Plant Biology (15107) Scientific Communication and Education (2042) Synthetic Biology (4285) Systems Biology (9808) Zoology (2267)