Quantitative single-residue bioorthogonal labeling of G protein


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Quantitative single-residue bioorthogonal labeling of G protein-coupled receptors in live cells Robert Serfling, Lisa Seidel, Andreas Bock, Martin J. Lohse, Paolo Annibale, and Irene Coin ACS Chem. Biol., Just Accepted Manuscript • DOI: 10.1021/acschembio.8b01115 • Publication Date (Web): 10 May 2019 Downloaded from http://pubs.acs.org on May 11, 2019

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Quantitative single-residue bioorthogonal labeling of G protein-coupled receptors in live cells

Robert Serfling[a], Lisa Seidel[a], Andreas Bock[b], Martin J. Lohse[b], Paolo Annibale*[b] and Irene Coin*[a] [a]Faculty

of Life Sciences, Institute of Biochemistry, University of Leipzig, Brüderstr. 34, 04103 Leipzig, Germany [b]Max-Delbrück-Center

for Molecular Medicine, Robert-Rössle-Str. 10, 13125 Berlin,

Germany *Correspondence to: [email protected], [email protected]

Abstract High-end microscopy studies of G protein-coupled receptors (GPCRs) require installing onto the receptors bright and photostable dyes. Labeling must occur in quantitative yields, to allow stoichiometric data analysis, and in a minimally invasive fashion, to avoid perturbing GPCR function. We demonstrate here that the genetic incorporation of trans-cyclooct-2-ene lysine (TCO*) allows achieving quantitative single-residue labeling of the extracellular loops of the 2-adrenergic and the muscarinic M2 class A GPCRs, as well as of the corticotropin releasing factor class B GPCR. Labeling occurs within a few minutes by reaction with dye-tetrazine conjugates on the surface of live cells and preserves the functionality of the receptors. To precisely quantify the labeling yields, we devise a method based on fluorescence fluctuation microscopy that extracts the number of labeling sites at the single-cell level. Further, we show that single-residue labeling is better suited for studies of GPCR diffusion than fluorescentprotein tags, since the latter can affect the mobility of the receptor. Finally, by performing dualcolor competitive labeling on a single TCO* site, we devise a method to estimate the oligomerization state of a GPCR without the need of a biological monomeric reference, which facilitates the application of fluorescence methods to oligomerization studies. As TCO* and the dye-tetrazines used in this study are commercially available and the described microscopy techniques can be performed on a commercial microscope, we expect our approach to be widely applicable to fluorescence microscopy studies of membrane proteins in general.

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Introduction G protein-coupled receptors (GPCRs) are the largest family of receptors on the eukaryotic cell membrane and form the most important class of drug targets. Fluorescence microscopy is possibly the most powerful technique to investigate trafficking and signaling dynamics of GPCRs directly in intact cells. High-end microscopy techniques are best applied to bright and photostable organic fluorophores, which feature a superior performance compared to classic fluorescent proteins. Such probes are commonly installed post-translationally on tags fused to the GPCR, which include self-labeling enzymes (e.g. SNAP, CLIP and Halo) and shorter peptide tags amenable of either chemical or enzymatic labeling (e.g. the tetracysteine and the ACP tags), all thoroughly reviewed in ref.1. These tags have been implemented to study aspects of GPCR oligomerization,2-4 GPCR activation5-8 and GPCR-G protein interactions,9 but they are considerably large (e.g. SNAP, 20kDa; ACP17, 2 kDa) and can compromise the function of the GPCR when inserted at positions that are critical to the GPCR function (e.g. intracellular loops).5 Moreover, bulky tags are not suitable to build sensitive sensors monitoring small changes of the GPCR conformation, which are at the base of the complexity of GPCR signaling. Organic fluorophores can be installed into proteins in a minimally invasive fashion by genetically incorporating a non-canonical amino acid (ncAA) bearing a chemical anchor, which is selectively modified by a fluorophore substrate in a second step.10-13 GPCR labeling on ncAA anchors has been first achieved on genetically-incorporated p-azido-Phe in vitro.1 However, the slow rates of catalyst-free reactions on azides (several hours to days) limit their use in living cells.12 Last-generation ncAAs for bioorthogonal chemistry bear strained alkene or alkyne anchors for rapid catalyst-free strain-promoted-inverse-electron demand Diels-Alder cycloaddition (SPIEDAC) with tetrazines, which is more amenable to live-cell experiments.12, 14 We and others have recently demonstrated proof of principle SPIEDAC labeling of class B GPCRs, with measured labeling yields up to 70%.15-16 A high to quantitative labeling yield is necessary for studies that would be biased by the presence of dark receptors (e.g. oligomerization studies).17 The efficiency of labeling is not trivial to quantify. Labeling of SNAP or tetracysteine tags is often assumed to be complete when the fluorescence intensity observed upon labeling with increasing concentrations of dyes reaches a plateau.2, 5 Alternatively, the fluorescence signal of the label is compared to the signal obtained with the same fluorophore via immunostaining,18 or normalized to the number of receptors estimated by radioligand binding.3 Labeling of SNAP is sometimes taken as a quantitative reference to evaluate other labeling methods.15 In any case, most of these measurements are extracted from population averages and are based on whole cell readouts that do not select for the plasma membrane. Furthermore, fluorescence intensity alone is not a direct nor reliable indicator of the number of molecules: quenching, bleaching and fluctuations of the optical focus are the most prominent factors affecting this estimate.19 More advanced approaches are needed to reliably ‘count’ molecules in a fluorescence microscope. Thanks to the use of fluorescence correlation spectroscopy (FCS)20 and the broad family of derived techniques, fluorescence fluctuation spectroscopy (FFS) allows precisely estimating the concentration of fluorescent molecules using a commercial confocal microscope. By analyzing the fluctuations of the fluorescent signal in a single pixel of a confocal image, image-based FFS methods allow determining the average number of fluorescent entities diffusing in and out of the pixel and quantifying their brightness.21-24 In particular, fluorescence spectroscopy tools based on the so-called molecular brightness, both in time (i.e. temporal brightness, TB) and in space (i.e. spatial intensity distribution analysis,

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SpIDA), have been extensively employed in the membrane receptors field21 and specifically in the GPCR community.25-27 Here, by using trans-cyclooct-2-ene lysine (TCO*)28 ncAA and tetrazine reagents, we demonstrate that single-residue SPIEDAC labeling is generally applicable to both class A and class B GPCRs. By developing a novel accurate quantification method of labeling efficiency based on molecular brightness measurements, we demonstrate that the yields of TCO* labeling are up to quantitative. Further, we show that single-residue labeling is better suited for studies of GPCR diffusion than fluorescent-protein tags, since the latter can affect the mobility of the receptor. Finally, by performing dual-color competitive TCO* labeling, we devise a novel method to evaluate the oligomerization state of a GPCR that does not need a monomeric protein reference.

Results and discussion Incorporation of TCO* into class A and class B GPCRs We selected two prototypical class A GPCRs, the 2-adrenergic and the muscarinic M2 receptor (2-AR, M2R), and a class B GPCR, the corticotropin releasing factor receptor type 1 (CRF1R). The receptors were fused to a HA epitope at the N-terminus and to the enhanced green fluorescent protein (EGFP) at the C-terminus. TCO* was incorporated in response to the amber stop codon (Figure 1A) at solvent exposed positions on both extracellular loops (ECLs) and intracellular loops (ICLs) (Supplementary Figures 1, 2 and 3). Cell-surface expression of all TCO*-GPCR variants was determined in 293T cells using a whole-cell ELISA detecting the N-terminal HA epitope29 (Figure 1B). The incorporation rates of TCO* differed between the three receptors and were position dependent. The ncAA was smoothly incorporated into the M2R and CRF1R, with TCO*-mutants averaging about 75% and 45% the expression level of the wild type (wt) receptor, respectively. Instead, the surface levels of TCO*-2-AR mutants were less than 5% compared to wt, and averaged about 60% of the wt-2-AR level obtained by transfecting one-tenth of the DNA amount used for the mutants. These results, together with the variable incorporation rates of ncAA into GPCRs reported in the literature, suggest that some GPCRs are better amenable to ncAA mutagenesis than others.15, 29-33 In parallel, all TCO*-GPCR variants were expressed in HEK293AD cells. Live cells were treated with either cyanine-based membrane-impermeable dyes (Cy3-tetrazine, Cy5tetrazine) or rhodamine-based membrane-permeable dyes (SiR-tetrazine or TAMRAtetrazine) and inspected by wide-field fluorescence microscopy both in the green and red/farred channels. The surface expression of the GPCRs inferred from the EGFP fluorescence was in line with the ELISA results. As expected, none of the wt receptors underwent visible labeling (Figure 1C-E, upper panels). Neat labeling of extracellular positions was observed for all M2R and CRF1R mutants, and for some 2-AR mutants (Figure 1C-E, middle panels and Supplementary Figures 1-3B). The analysis of intracellular labeling was biased by a high background of cytosolic fluorescence and ICL labeling was clearly visible only in a few cases (Supplementary Figures 1C, 2C and 3C). The labeling efficiency of each mutant was qualitatively estimated either as “good”, “fair” or “poor” (Table S1). In general, the expression level did not correlate with the labeling efficiency. For instance, 186TCO*-2-AR was well expressed but poorly labeled.

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Quantification of the labeling efficiency A subset of representative TCO*-GPCRs showing variable labeling ratios in the extracellular loops were selected: 98TCO*-, 100TCO*-, 183TCO*-2-AR; 94TCO*-, 186TCO*-M2R; 185TCO*-, 263TCO*-, 266TCO*-CRF1R. The functionality of these receptors was assessed using either cAMP accumulation or Gi3 activation assay, showing that the TCO* mutation was overall well tolerated (Supplementary Table 2 and Supplementary Figure 4). HEK293AD cells expressing each TCO*-GPCR-EGFP were labeled with Cy3-tetrazine. Fluorescence movies of portions of the basolateral membrane of single cells were recorded in the green (EGFP) and red (Cy3) channels. According to the TB method of FFS (Figure 2A), the number of Cy3 and EGFP emitters contained in the excitation beam of the microscope was extracted from the analysis of a temporal series of timeframes. For each cell, the number of Cy3 counts was plotted vs the number of EGFP counts and the labeling efficiency was derived from the slope of the linear regression (Figure 2B-C). Each receptor could be labeled in close-to-quantitative yields (95%) on at least one position. Importantly, the labeled GPCRs internalized upon agonist stimulation (Figure 1C-E, lower panels), showing that they were still functional. Interestingly, while position 98 in ECL1 of the 2-AR was quantitatively labeled, the labeling ratio of the adjacent position 100 was only 20%, meaning that the accessibility of the bioorthogonal anchors is only partially predictable in silico. The labeling efficiency of 263TCO*CRF1R-EFGP was slightly higher than 1, albeit compatible with 1 within the error. As all our quantifications refer to EGFP, non-quantitative folding of EGFP34 or occurrence of EGFP photobleaching during the measurements can lead to a small overestimation of labeling yields. In order to evaluate the background of the measure, CRF1R-EGFP bearing the inert ncAA LysZ at position 263 was labeled with Cy3-tetrazine. The measured labeling ratio was about 6% and was ascribable to Cy3 photoblinking (Supplementary Figure 5A-C). The reliability of the TB measurements was validated using the SpIDA method,23, 25-26 which yielded comparable results (Supplementary Figure 6A-C). As a further validation, dual-color competitive labeling experiments were performed. HEK293AD cells expressing 263TCO*CRF1R-EGFP were labeled with a Cy5-tetrazine solution containing increasing amounts of Cy3-tetrazine (Figure 3A). Within the errors, the extracted sum of Cy3 and Cy5 counts was consistent with a full labeling of the receptor, i.e. (#Cy3 + #Cy5) = #EGFP sites (Figure 3B), both when applying TB and SpIDA (Figure 3C). We then explored the possibility of quantifying intracellular labeling. Functional 149TCO*- and 224TCO*-CRF1R-EGFP constructs (Supplementary Table 1) were expressed in HEK293AD cells. The wt-CRF1R-EGFP and 263TCO*-CRF1R-EGFP were taken as a control for background and quantitative labeling, respectively. Living cells were treated with membrane permeable TAMRA-tetrazine. TAMRA and EGFP sites were determined using TB (Figure 4). For TAMRA imaging, the measure required a very precise focusing of the confocal microscope on the membrane, due to the high background of intracellular fluorescence. The average TAMRA counts obtained in the wt samples were subtracted from the other measurements and plotted against the EGFP counts (Figure 4B). We estimated the labeling yield as 90% for position 263 (compatible with what was previously observed with Cy3, Figure 2C), and an average 30-40% for the intracellular sites, although the small R2 values show that the linear fitting was affected by a large variance. Further experiments were carried out to understand the origin of the high intracellular background. We show that this background is only partially due to the free dye itself, whereas it rather arises from the formation of covalent adducts between the dye-tetrazine and both the 4 ACS Paragon Plus Environment

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TCO* and the tRNA-TCO* conjugates (Supplementary Figure 7). Indeed, the signal to background ratio could be slightly improved by working at lower concentrations of TCO*, but not by using a fluorogenic dye (Supplementary Figure 8). It is possible that the use of easily washable dyes35 might help shuttling at least the TCO*-dye out of the cell. In any case, as GPCRs feature a relatively low expression level, the high intracellular background likely limits both the achievable yield of labeling and the accuracy of the measurements. Indeed, intracellular labeling of ncAA anchors has been demonstrated in the literature only on highly abundant proteins, including histones and structural proteins, which intrinsically give a favorable signal to noise ratio.35-37

Assessing the diffusion of a GPCR labeled on a single residue To demonstrate the advantage of single-residue labeling, we compared the rapidity of motion of a receptor exclusively labeled with an organic dye at a TCO* site to that of the same receptor carrying EGFP either at the N- or C-terminus. HEK293AD cells expressing 263TCO*-CRF1R and 186TCO*-M2R constructs with and without EGFP fusion were labeled with Cy3. Rapid line-scanning confocal microscopy in the Cy3 channel was applied to extract values of molecular Mean Squared Displacement (MSD) from the broadening of the spatial-temporal correlation function.38-41 The diffusion coefficients D were calculated at short timescales from the linear fit of the MSD (Figure 5A). The N-terminally tagged CRF1R (74 kDa) diffused at similar yet slightly slower pace than the EGFP-free receptor (47 kDa). Instead, the diffusion coefficient of the CRF1R bearing the EGFP at the C-terminus was significantly lower (Figure 5B). Based on purely hydrodynamic considerations, the decrease in D for the Cterminally tagged receptor is in line with the value expected for a 1.6-fold increase of the volume/mass ratio of a spherical diffusing particle (31.6  1.2 decrease of D), whereas the larger effect observed for the C-terminally tagged variant is likely attributable to an “anchorlike” effect of the EGFP tag on the receptor dynamics, possible due to molecular crowding.4243

We did not observe the same effect for the M2R. All M2R constructs diffused at the same rate, independently of the presence of the EGFP tag. Overall, the results indicate that the presence of a bulky tag, especially at the C-terminus of a GPCR can influence its rapidity of motion, and that the effect can be receptor-specific. Moreover, bulky N-terminal fusions can interfere with GPCR translocation and folding.44 Single-residue labeling is likely to yield the labeled species that most approximate the behavior of the native GPCR.

Assessing the oligomerization state of the CRF1R Finally, we combined ncAA labeling and TB microscopy to address the oligomerization state of a GPCR. In general, a quantitatively-labeled biological GPCR dimer behaves as a single fluorescent object bearing two fluorophores, featuring a molecular brightness (ɛ) double that of a monomer. Thus, the molecular brightness is indicative of the oligomerization state of a GPCR. However, a cumbersome issue affecting molecular brightness studies of oligomerization is the identification of a proper monomeric reference.21 We reasoned that dualcolor competitive labeling of an ncAA would offer a novel approach to this problem. Indeed, even an oligomeric receptor, if sparsely labeled in a selected imaging channel, will appear as a ‘fluorescence’ monomer (Figure 6A), thus providing an internal control for the monomeric reference of fluorescence.

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263TCO*-CRF1R-EGFP was labeled with a variable ratio of Cy3- and Cy5-tetrazine. The apparent molecular brightness (B) was measured using TB in the three spectral channels (Cy3, Cy5 and EGFP) and plotted as a function of the percentage of Cy3 in the labeling solution (Figure 6B). As expected, B of EGFP was independent of the labeling mixture. Instead, by increasing the Cy3 fraction, the molecular brightness in the Cy3 channel increased progressively, whereas the brightness in the Cy3 channel decreased, indicating that the receptor forms oligomers. As the oligomerization rate depends on the concentration of the receptor2 (Supplementary Figure 9A), the quite large variance of the brightness values is due to sampling of a cell population with a heterogeneous expression profile. The same trends were seen using SpIDA (Supplementary Figure 9B). The apparent brightness value BM=1.34 ± 0.05 obtained at 10% Cy3 was taken as a reference for the Cy3 monomer. The molecular brightness for a constitutive fluorescent dimer equals BD=1.68 ± 0.1 [=1+(0.34*2)], which is very close to the brightness experimentally measured in our sample at full Cy3 labeling (B=1.65 ± 0.05) and is indicative of a dimeric receptor. A second experiment was carried out with EGFP-free 263TCO*-CRF1R, and included brightness measurements starting from 1% Cy3. At %Cy3 ≤ 10% the B values plateaued and were indistinguishable within the error, confirming that the choice of 10% Cy3 for the monomeric reference is appropriate (Supplementary Figure 10A). We did not observe an effect of EGFP on the calculated oligomerization ratio. An indication on the oligomerization state can also be obtained from the relative Cy3/EGFP brightness  at full Cy3 labeling and at equimolar Cy3 to Cy5 labeling (Supplementary Figure 10B and C). Both calculations are indicative of a species displaying an oligomeric fingerprint, in line with previous estimates based on FRET measurements.45-46 Quantifying the oligomeric fraction of CRF1R at physiological concentration clearly awaits a wider range of experiments, nonetheless these results suggest that our approach can well be applied to oligomerization studies. In conclusion, we have demonstrated that GPCRs can be quantitatively labeled on the extracellular loops using SPIEDAC chemistry on genetically-encoded TCO* ncAA. Importantly, TCO* is ten times more stable in physiological milieu28 compared to the transcyclooct-4-ene (TCO) used in other studies.15 The approach is in principle applicable for intracellular labeling, although a major effort still has to be invested to solve the issue of the background. We have designed a rapid method, based on non-perturbing fluorescence fluctuation spectroscopy, to precisely quantify the labeling rate of functional receptors diffusing in the plasma membrane of the intact cells using a commercial confocal microscope. When combined with dual-color competitive labeling on a single ncAA, the approach allows estimating the oligomerization state of a GPCR without the need of a biological monomeric reference. Finally, we have shown that single-residue labeling is less likely to decrease the mobility of a GCPR compared to fluorescent-protein tags. We expect that the approach will be generally applicable to equip GPCRs with bright and photostable dyes for high-end microscopy studies of their function and dynamics in live cells.

Methods Plasmids: Plasmid pNEU-MbPylRSAF/4xtRNAM15 was used for genetic encoding TCO*.16 The genes of HA-GPCR-EGFP constructs were cloned into pcDNA3.1 between EcoRI and NotI restriction sites. The receptors are connected to EGFP by a polyglycine linker containing an AgeI restriction site. The CRF1R gene features its native signal peptide. The β2-AR and M2R genes bear a cleavable signal peptide.47 Amber TAG-codons were introduced via site-directed mutagenesis PCR. 6 ACS Paragon Plus Environment

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General cell culture: HEK293AD and 293T cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM; high glucose 4.5 g/L, 4 mM glutamine, pyruvate; Thermo Fisher Scientific, Rockford, USA) supplemented with 10% FBS (v/v; Thermo Fisher Scientific) and 100 U/mL penicillin and 100 μg/mL streptomycin (Thermo Fisher Scientific) at 37°C under 5% CO2 and 95% humidity. Cells were passaged at 80-90% confluence every 2–4 days. Whole cell surface-ELISA. 15,000 293T cells per well were seeded in poly-D-lysine-coated 96-well plates. The following day, TCO* was added to 250 µM. Cells were co-transfected with 5 ng of plasmid encoding for the stop-codon variants of the GPCR (or wt-GPCR) and 5 ng of the MbPylRSAF/4xtRNAM15 plasmid. The total DNA amount was filled to 100 ng per well with mock DNA. After 24 h, cells were fixed with 4 % formaldehyde in PBS, blocked in DMEM containing 10 % FBS and incubated with a HRP-conjugated rat-anti-HA-antibodies (Roche, clone 3F10) diluted 1:200 in DMEM containing 10 % FBS for 1 h at 37 °C. The read-out was generated using an o-phenylenediamine dihydrochloride (OPD) substrate. The raw data were collected as mean ± s.e.m. from three independent experiments, each performed in triplicate, corrected for the absorption obtained from mock-transfected cells. Transfection for GPCR imaging: Approximately 20 h prior to transfection, cells were plated in 6-well plates on circular high precision cover glasses (25 mm, 1.5H; Marienfeld, LaudaKoenigshofen, Germany) pre-treated with poly-D-lysine hydrobromide (MW 500-550 kDa, 25 µg/mL; BD Biosciences, Heidelberg, Germany). TCO* (SiChem, Bremen, Germany) was added 1 h before transfection to a concentration of 250 µM for extracellular labeling and 50 µM for intracellular labeling experiments. Cells were co-transfected with MbPylRSAF/4xtRNAM15 and receptor constructs in a 1:1 ratio for a total amount of 1.5 µg DNA using Lipofectamine 2000 (Thermo Fisher Scientific) as described48. Labelling procedure: 16-20 h post-transfection, the glass covers were transferred to new 6well plates containing complete dye-free FluoroBrite® medium (Thermo Fisher Scientific) and cells were incubated at least 2h without ncAA at 37°C under CO2 (5%) atmosphere. Fluorophore-tetrazine conjugates were dissolved in complete FluoroBrite® medium from 500 µM stock solutions in DMSO to 0.15 µM – 1.5 µM, and the solution applied to the cells for 5 min at 37°C. Cy3-H-tet or Cy5-H-tet (Jena Biosciences, Jena, Germany) were used for labelling of extracellular sites. SiR-H-tet (Spirochrome, Stein am Rhein, Switzerland) or TAMRA-H-tet (Jena Biosciences, Jena, Germany) were used for intracellular positions. Cells were rinsed once (extracellular labeling) or washed once for 2 h (intracellular labeling) with complete Fluorobrite® medium before imaging. To facilitate the simultaneous handling of many samples in the initial wide-field screening, cells were fixed after labeling using PFA (2% w/v in PBS) for 30 min at room temperature and stored in PBS until imaged. Wide-field microscopy: The glass covers were placed into a support (Thermo Fisher Scientific) and covered with either complete Fluorobrite® growth medium (live cells) or PBS (fixed cells). Cells were visualized at 63x magnification on an inverted Observer.Z1 microscope (Zeiss, Oberkochen, Germany) equipped with an AxioCam MRm camera and HXP120 fluorescence light source. Fluorescence was detected using the following filters: EGFP - Ex: 470/40 nm and Em: 525/50 nm; Cy3 - Ex: 565/30 nm and Em: 620/60 nm; SiR – Ex: 640/30 nm and Em: 690/50 nm. Images were analyzed and prepared with Zen 2 blue edition software (Zeiss). TB microscopy: The glass covers were placed into a steel chamber, covered with complete Fluorobrite® medium and imaged on a Leica SP8 DMi8 inverse confocal laser scanning microscope using Leica LAS X software. Cells were imaged with a 40x/1.10 water immersion 7 ACS Paragon Plus Environment

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objective. Sets of 50 or 100 frames were taken with a scanner speed of 400 Hz at 256x256 pixels resolution and a zoom-factor of 22.8 yielding a pixel size of 50 nm. Fluorescence was detected with a Hybrid detector in photon counting mode (gain 10%). For EGFP detection, the Argon-ion laser was set to 20% and the 488 nm laser line was used at 2-4% power and emission was measured at 500-550 nm. Cy3 emission was measured at 570-650 nm upon excitation with a solid state diode DPSS 561 nm laser at 2-3% power. Cy5 and SiR were excited with a HeNe 633 nm laser set between 0.4% and 3% power and detected at 638-750 nm. The Regions of Interest (ROIs) were drawn in free area selection mode to avoid areas in the membrane showing inhomogeneous distributed fluorescence. Data were analyzed as described previously utilizing a custom-written Igor Pro (Wavemetrics) routine.49 The brightness values were calculated based on the average of the brightness values from each pixel within the ROI using a custom written routine as previously described.50 Receptor diffusion measurements: The same microscope setup was used as for TB analysis. Image sets were taken in xt mode. Line scans were performed at a scanner speed of 8000 Hz with a resonant scanner at a 256x1 resolution and a pixel size of 50 nm. Approximately 2 million lines were collected per set. Cy3 was excited at 561 nm with a laser power of 25%. Analysis of image sets was performed using a custom written Igor Pro routine to calculate the spatial temporal correlation function of the line scan and extract the Mean Squared Displacement (MSD) from the spatial increase over time of the autocorrelation function as previously described.39

Associated content Supporting information Supporting information, including supplementary methods for SpIDA microscopy and functional assays, supplementary figures and tables, is available free of charge via the internet at http://pubs.acs.org.

Acknowledgments We thank the German Research Foundation for funding (Emmy Noether Grant CO822/2-1 to IC and Project Grant in TR166 to MJL), the VMF BioImaging Core Facility of the Leipzig University for supplying the Leica SP8 DMi8 microscope and N. Grunert (MDC, Berlin) for technical assistance.

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References 1. Tian, H.; Furstenberg, A.; Huber, T., Labeling and Single-Molecule Methods To Monitor G Protein-Coupled Receptor Dynamics. Chem. Rev. 2017, 117, 186-245. 2. Calebiro, D.; Rieken, F.; Wagner, J.; Sungkaworn, T.; Zabel, U.; Borzi, A.; Cocucci, E.; Zurn, A.; Lohse, M. J., Single-molecule analysis of fluorescently labeled G-protein-coupled receptors reveals complexes with distinct dynamics and organization. Proc. Natl. Acad. Sci. U S A 2013, 110, 743-748. 3. Maurel, D.; Comps-Agrar, L.; Brock, C.; Rives, M. L.; Bourrier, E.; Ayoub, M. A.; Bazin, H.; Tinel, N.; Durroux, T.; Prezeau, L.; Trinquet, E.; Pin, J. P., Cell-surface protein-protein interaction analysis with time-resolved FRET and snap-tag technologies: application to GPCR oligomerization. Nat. Methods 2008, 5, 561-567. 4. Meral, D.; Provasi, D.; Prada-Gracia, D.; Moller, J.; Marino, K.; Lohse, M. J.; Filizola, M., Molecular details of dimerization kinetics reveal negligible populations of transient micro-opioid receptor homodimers at physiological concentrations. Sci. Rep. 2018, 8, 7705. 5. Hoffmann, C.; Gaietta, G.; Bunemann, M.; Adams, S. R.; Oberdorff-Maass, S.; Behr, B.; Vilardaga, J. P.; Tsien, R. Y.; Ellisman, M. H.; Lohse, M. J., A FlAsH-based FRET approach to determine G protein-coupled receptor activation in living cells. Nat. Methods 2005, 2, 171-176. 6. Lecat-Guillet, N.; Monnier, C.; Rovira, X.; Kniazeff, J.; Lamarque, L.; Zwier, J. M.; Trinquet, E.; Pin, J. P.; Rondard, P., FRET-Based Sensors Unravel Activation and Allosteric Modulation of the GABAB Receptor. Cell Chem. Biol. 2017, 24, 360-370. 7. Lohse, M. J.; Nuber, S.; Hoffmann, C., Fluorescence/bioluminescence resonance energy transfer techniques to study G-protein-coupled receptor activation and signaling. Pharmacol. Rev. 2012, 64, 299-336. 8. Bock, A.; Merten, N.; Schrage, R.; Dallanoce, C.; Batz, J.; Klockner, J.; Schmitz, J.; Matera, C.; Simon, K.; Kebig, A.; Peters, L.; Muller, A.; Schrobang-Ley, J.; Trankle, C.; Hoffmann, C.; De Amici, M.; Holzgrabe, U.; Kostenis, E.; Mohr, K., The allosteric vestibule of a seven transmembrane helical receptor controls G-protein coupling. Nat. Commun 2012, 3, 1044. 9. Sungkaworn, T.; Jobin, M. L.; Burnecki, K.; Weron, A.; Lohse, M. J.; Calebiro, D., Singlemolecule imaging reveals receptor-G protein interactions at cell surface hot spots. Nature 2017, 550, 543-547. 10. Liu, C. C.; Schultz, P. G., Adding new chemistries to the genetic code. Annu. Rev. Biochem. 2010, 79, 413-444. 11. Zhang, G.; Zheng, S.; Liu, H.; Chen, P. R., Illuminating biological processes through sitespecific protein labeling. Chem. Soc. Rev. 2015, 44, 3405-3417. 12. Lang, K.; Chin, J. W., Cellular incorporation of unnatural amino acids and bioorthogonal labeling of proteins. Chem. Rev. 2014, 114, 4764-4806. 13. Zhang, Z. W.; Smith, B. A. C.; Wang, L.; Brock, A.; Cho, C.; Schultz, P. G., A new strategy for the site-specific modification of proteins in vivo. Biochemistry 2003, 42, 6735-6746. 14. Nikic, I.; Kang, J. H.; Girona, G. E.; Aramburu, I. V.; Lemke, E. A., Labeling proteins on live mammalian cells using click chemistry. Nat. Protoc. 2015, 10, 780-791. 15. Ramil, C. P.; Dong, M.; An, P.; Lewandowski, T. M.; Yu, Z.; Miller, L. J.; Lin, Q., SpirohexeneTetrazine Ligation Enables Bioorthogonal Labeling of Class B G Protein-Coupled Receptors in Live Cells. J. Am. Chem. Soc. 2017, 139, 13376-13386. 16. Serfling, R.; Lorenz, C.; Etzel, M.; Schicht, G.; Bottke, T.; Morl, M.; Coin, I., Designer tRNAs for efficient incorporation of non-canonical amino acids by the pyrrolysine system in mammalian cells. Nucleic Acids Res. 2018, 46, 1-10. 17. Felce, J. H.; Davis, S. J.; Klenerman, D., Single-Molecule Analysis of G Protein-Coupled Receptor Stoichiometry: Approaches and Limitations. Trends Pharmacol. Sci. 2018, 39, 96-108. 18. Latty, S. L.; Felce, J. H.; Weimann, L.; Lee, S. F.; Davis, S. J.; Klenerman, D., Referenced SingleMolecule Measurements Differentiate between GPCR Oligomerization States. Biophys. J. 2015, 109, 1798-1806. 9 ACS Paragon Plus Environment

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19. Lakowicz, J. R., Principles of Fluorescence Spectroscopy. In Principles of Fluorescence Spectroscopy, Springer US: Boston, MA, 1999; pp 25-61. 20. Magde, D.; Webb, W. W.; Elson, E., Thermodynamic Fluctuations in a Reacting System Measurement by Fluorescence Correlation Spectroscopy. Phys. Rev. Lett. 1972, 29, 705-708. 21. Hellriegel, C.; Caiolfa, V. R.; Corti, V.; Sidenius, N.; Zamai, M., Number and brightness image analysis reveals ATF-induced dimerization kinetics of uPAR in the cell membrane. FASEB J. 2011, 25, 2883-2897. 22. Nagy, P.; Claus, J.; Jovin, T. M.; Arndt-Jovin, D. J., Distribution of resting and ligand-bound ErbB1 and ErbB2 receptor tyrosine kinases in living cells using number and brightness analysis. Proc. Natl. Acad. Sci. U S A 2010, 107, 16524-16529. 23. Godin, A. G.; Costantino, S.; Lorenzo, L. E.; Swift, J. L.; Sergeev, M.; Ribeiro-da-Silva, A.; De Koninck, Y.; Wiseman, P. W., Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis. Proc. Natl. Acad. Sci. U S A 2011, 108, 7010-7015. 24. Digman, M. A.; Dalal, R.; Horwitz, A. F.; Gratton, E., Mapping the number of molecules and brightness in the laser scanning microscope. Biophys. J. 2008, 94, 2320-2332. 25. Ward, R. J.; Pediani, J. D.; Godin, A. G.; Milligan, G., Regulation of Oligomeric Organization of the Serotonin 5-Hydroxytryptamine 2C (5-HT2C) Receptor Observed by Spatial Intensity Distribution Analysis. J. Biol. Chem. 2015, 290, 12844-12857. 26. Pediani, J. D.; Ward, R. J.; Godin, A. G.; Marsango, S.; Milligan, G., Dynamic Regulation of Quaternary Organization of the M-1 Muscarinic Receptor by Subtype-selective Antagonist Drugs. J. Biol. Chem. 2016, 291, 13132-13146. 27. Moller, T. C.; Hottin, J.; Clerte, C.; Zwier, J. M.; Durroux, T.; Rondard, P.; Prezeau, L.; Royer, C. A.; Pin, J. P.; Margeat, E.; Kniazeff, J., Oligomerization of a G protein-coupled receptor in neurons controlled by its structural dynamics. Sci. Rep. 2018, 8, 10414. 28. Nikic, I.; Plass, T.; Schraidt, O.; Szymanski, J.; Briggs, J. A.; Schultz, C.; Lemke, E. A., Minimal tags for rapid dual-color live-cell labeling and super-resolution microscopy. Angew. Chem. Int. Ed. Engl. 2014, 53, 2245-2249. 29. Seidel, L.; Zarzycka, B.; Zaidi, S. A.; Katritch, V.; Coin, I., Structural insight into the activation of a class B G-protein-coupled receptor by peptide hormones in live human cells. Elife 2017, 6. 30. Koole, C.; Reynolds, C. A.; Mobarec, J. C.; Hick, C.; Sexton, P. M.; Sakmar, T. P., Genetically encoded photocross-linkers determine the biological binding site of exendin-4 peptide in the Nterminal domain of the intact human glucagon-like peptide-1 receptor (GLP-1R). J. Biol. Chem. 2017, 292, 7131-7144. 31. Park, M.; Sivertsen, B. B.; Els-Heindl, S.; Huber, T.; Holst, B.; Beck-Sickinger, A. G.; Schwartz, T. W.; Sakmar, T. P., Bioorthogonal Labeling of Ghrelin Receptor to Facilitate Studies of LigandDependent Conformational Dynamics. Chem. Biol. 2015, 22, 1431-1436. 32. Naganathan, S.; Ye, S.; Sakmar, T. P.; Huber, T., Site-specific epitope tagging of G proteincoupled receptors by bioorthogonal modification of a genetically encoded unnatural amino acid. Biochemistry 2013, 52, 1028-1036. 33. Tian, H.; Naganathan, S.; Kazmi, M. A.; Schwartz, T. W.; Sakmar, T. P.; Huber, T., Bioorthogonal fluorescent labeling of functional G-protein-coupled receptors. ChemBioChem 2014, 15, 1820-1829. 34. Sacchetti, A.; Alberti, S., Protein tags enhance GFP folding in eukaryotic cells. Nat. Biotechnol. 1999, 17, 1046. 35. Alamudi, S. H.; Satapathy, R.; Kim, J.; Su, D.; Ren, H.; Das, R.; Hu, L.; Alvarado-Martinez, E.; Lee, J. Y.; Hoppmann, C.; Pena-Cabrera, E.; Ha, H. H.; Park, H. S.; Wang, L.; Chang, Y. T., Development of background-free tame fluorescent probes for intracellular live cell imaging. Nat. Commun. 2016, 7, 11964. 36. Uttamapinant, C.; Howe, J. D.; Lang, K.; Beranek, V.; Davis, L.; Mahesh, M.; Barry, N. P.; Chin, J. W., Genetic code expansion enables live-cell and super-resolution imaging of site-specifically labeled cellular proteins. J. Am. Chem. Soc. 2015, 137, 4602-4605. 10 ACS Paragon Plus Environment

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37. Aloush, N.; Schvartz, T.; Konig, A. I.; Cohen, S.; Brozgol, E.; Tam, B.; Nachmias, D.; Ben-David, O.; Garini, Y.; Elia, N.; Arbely, E., Live Cell Imaging of Bioorthogonally Labelled Proteins Generated With a Single Pyrrolysine tRNA Gene. Sci. Rep. 2018, 8, 14527. 38. Unruh, J. R.; Slaughter, B. D.; Jaspersen, S. L., Functional Analysis of the Yeast LINC Complex Using Fluctuation Spectroscopy and Super-Resolution Imaging. Methods Mol. Biol. 2018, 1840, 137161. 39. Di Rienzo, C.; Annibale, P., Visualizing the molecular mode of motion from a correlative analysis of localization microscopy datasets. Opt. Lett. 2016, 41, 4503-4506. 40. Di Rienzo, C.; Gratton, E.; Beltram, F.; Cardarelli, F., Fast spatiotemporal correlation spectroscopy to determine protein lateral diffusion laws in live cell membranes. Proc. Natl. Acad. Sci. U S A 2013, 110, 12307-12312. 41. Ries, J.; Chiantia, S.; Schwille, P., Accurate determination of membrane dynamics with linescan FCS. Biophys. J. 2009, 96, 1999-2008. 42. Frick, M.; Schmidt, K.; Nichols, B. J., Modulation of lateral diffusion in the plasma membrane by protein density. Curr. Biol. 2007, 17, 462-467. 43. Dix, J. A.; Verkman, A. S., Crowding effects on diffusion in solutions and cells. Annu. Rev. Biophys. 2008, 37, 247-263. 44. Kochl, R.; Alken, M.; Rutz, C.; Krause, G.; Oksche, A.; Rosenthal, W.; Schulein, R., The signal peptide of the G protein-coupled human endothelin B receptor is necessary for translocation of the N-terminal tail across the endoplasmic reticulum membrane. J. Biol. Chem. 2002, 277, 16131-16138. 45. Kraetke, O.; Wiesner, B.; Eichhorst, J.; Furkert, J.; Bienert, M.; Beyermann, M., Dimerization of corticotropin-releasing factor receptor type 1 is not coupled to ligand binding. J. Recept. Signal. Transduct. Res. 2005, 25, 251-276. 46. Teichmann, A.; Gibert, A.; Lampe, A.; Grzesik, P.; Rutz, C.; Furkert, J.; Schmoranzer, J.; Krause, G.; Wiesner, B.; Schulein, R., The specific monomer/dimer equilibrium of the corticotropin-releasing factor receptor type 1 is established in the endoplasmic reticulum. J. Biol. Chem. 2014, 289, 2425024262. 47. 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. 1992, 267, 21995-21998. 48. Serfling, R.; Seidel, L.; Bottke, T.; Coin, I., Optimizing the Genetic Incorporation of Chemical Probes into GPCRs for Photo-crosslinking Mapping and Bioorthogonal Chemistry in Live Mammalian Cells. J. Vis. Exp. 2018. 49. Trullo, A.; Corti, V.; Arza, E.; Caiolfa, V. R.; Zamai, M., Application limits and data correction in number of molecules and brightness analysis. Microsc. Res. Tech. 2013, 76, 1135-1146. 50. Isbilir, A.; Moeller, J.; Bock, A.; Zabel, U.; Annibale, P.; Lohse, M. J., Visualization of class A GPCR oligomerization by image-based fluorescence fluctuation spectroscopy. bioRxiv 2017.

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Figures captions

Figure 1: Bioorthogonal labeling of TCO*-GPCR-EGFP variants. A) Schematic representation of the protocol for ncAA incorporation and GPCR labeling. B) Surface-ELISA of 293T cells expressing GPCR variants that contain TCO* at the position indicated under each bar. Data represent the mean ± SD of biological triplicates. (#) wt-β2-AR was transfected at 1/10 DNA. C-E) Wide-field images of HEK293AD cells labeled with Cy3-tetrazine (automatic exposure time). Stimulated cells (bottom panels) were imaged either 30 min (β2-AR and CRF1R) or 1 hour (M2R) after agonist treatment. Red: Cy3; Green: EGFP.

Figure 2: Quantification of the labeling rate of TCO*-GPCRs. A) Principle of temporal brightness (TB) measurements. PSF: Point Spread Function, excitation beam. The number of molecules in a pixel fluctuates over time because of molecular diffusion. Experimentally, we measure the fluorescence signal (average photon count per pixel, k) in a series of confocal images of the same spot. From the photon count k and the variance 2 of the fluctuating signal, we derive the apparent brightness B, the molecular brightness 𝜺 and the number N of fluorescent entities per pixel. B) The average number of counted Cy3-labeled sites (ordinate axis) is plotted in log-log scale vs the number of EGFP counts. Each point on the plot represents the results obtained for one cell. Colored lines represent linear regression. Data were collected on at least 8 cells in 3 distinct experiments for each receptor C) Labeling rates derived from B). A slope of 1 correspond to 100% labeling efficiency (relative to EGFP), whereas a slope of 0.1 means 10% labeling efficiency. Data are reported  SD of the slope of the fit, together with the R2 of the linear regressions.

Figure 3: Dual-color competitive labeling at a TCO* site. A) Confocal images of the plasma membrane of HEK293AD cells expressing 263TCO*-CRF1R-EGFP labeled with a mixture of Cy3- and Cy5-tetrazine. Green: EGFP; Red: Cy3; Magenta Cy5; B) The number of Cy3 and Cy5 labeling sites over EGFP sites (Cy3/EGFP, Cy5/EGFP) and of the sum of Cy3 to Cy5 sites over EGFP ((Cy3+Cy5)/EGFP) are plotted as a function %Cy3. Each data point is the average calculated from at least 12 cells examined using TB. C) Comparison of results obtained from temporal and spatial brightness analysis. Error bars represent standard error of the mean (s.e.m.).

Figure 4: Intracellular labeling of TCO*-CRF1R-EGFP mutants. A) Confocal images of the basolateral membrane of HEK293AD cells expressing the indicated receptors labeled with TAMRA-tetrazine (green: EGFP; red: TAMRA). All cells express the PylRSAF/tRNAM15 pair in the presence of TCO*. White arrows highlight aggregates of TAMRA-TCO*-tRNA (compare Supplementary Figure 7). (#) The DNA for wt-CRF1R was transfected at 1/2 the DNA of the mutants. B) Number of TAMRA vs EGFP counts plotted as in Figure 2B (top) corrected for the number of background (BG) counts measured in the TAMRA channel for wt-CRF1R + TCO* (bottom). The slopes of the linear regression are summarized in the adjacent table, together with the R2 of the linear regressions. For 149TCO*-CRF1R-EGFP we imaged 20 cells in four independent experiments and for 224TCO*-CRF1R-EGFP 26 cells in five independent experiments.

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Figure 5: Molecular diffusion of CRF1R and M2R with and without EGFP-tag. A) Average MSD of 263TCO*CRF1R-EGFP (circles) and 263TCO*-CRF1R (crosses) calculated from three experiments. Dashed lines represent fits performed in the 125 𝜇s to 0.1 s range. Points along the time axis are logarithmically binned. The inset shows the MSD plotted against a logarithmic time axis in the 125 𝜇s to 0.1 s range. The y-axis intercepts of the MSD plot are consistent with the typical waist of the PSF in a confocal microscope (about 250 nm). B) The table summarizes the measured diffusion coefficients and intercepts for all analyzed CRF1R and M2R constructs.

Figure 6:

Characterization of the oligomerization state of 263TCO*-CRF1R-EGFP. A) Schematic

representation of a mixed monomeric and dimeric GPCR population labeled with different ratios of two dyes (e.g. red=Cy3; purple=Cy5). Since a monomer cannot bear more than one label, the brightness B of the fluorescent entities in a monomeric receptor sample is independent from the labeling ratio. Instead, the fluorescent entities in a dimeric receptor sample can bear either one or two labels of a given color, so that their brightness in one channel increases with increasing amounts of the corresponding dye in the labeling mixture. When the fraction of a given color (e.g. Cy5) is very low, dimers will bear, if any, only one Cy5 label (species highlighted with black circles), thus yielding in the Cy5 channel the brightness of a monomer. B) Plot of the temporal brightness of Cy3, Cy5 and EGFP for an increasing Cy3 to Cy5 ratio used for labeling 263TCO*-CRF1R-EGFP. Each data point is the average of at least 12 single cell measurements in three independent experiments. Error bars s.e.m.

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Figure 1 163x181mm (300 x 300 DPI)

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