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Molecular mechanism of GPCR spatial organization at the plasma membrane

Nature Chemical Biology volume 20, pages 142–150 (2024)Cite this article

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Abstract

G-protein-coupled receptors (GPCRs) mediate many critical physiological processes. Their spatial organization in plasma membrane (PM) domains is believed to encode signaling specificity and efficiency. However, the existence of domains and, crucially, the mechanism of formation of such putative domains remain elusive. Here, live-cell imaging (corrected for topography-induced imaging artifacts) conclusively established the existence of PM domains for GPCRs. Paradoxically, energetic coupling to extremely shallow PM curvature (<1 µm−1) emerged as the dominant, necessary and sufficient molecular mechanism of GPCR spatiotemporal organization. Experiments with different GPCRs, H-Ras, Piezo1 and epidermal growth factor receptor, suggest that the mechanism is general, yet protein specific, and can be regulated by ligands. These findings delineate a new spatiomechanical molecular mechanism that can transduce to domain-based signaling any mechanical or chemical stimulus that affects the morphology of the PM and suggest innovative therapeutic strategies targeting cellular shape.

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Fig. 1: Topography-corrected imaging of β1AR density reveals PM domains.
Fig. 2: MFT reveals energetic coupling to shallow mean membrane curvature as the molecular mechanism of domain formation.
Fig. 3: Nanoscopic modulation of PM curvature quantitatively regulates β1AR density.
Fig. 4: Curvature-coupled GPCR domains were identified with high statistical significance for different GPCRs and cell types.
Fig. 5: A general mechanism of spatial organization that is protein specific and can be regulated by ligands.

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Data availability

The structure of the inactive β1AR is available from the Protein Data Bank with accession code 2YCW. Source data are provided with this paper.

Code availability

Algorithms used by custom analysis code are described in detail in the Methods. Code is available upon reasonable request.

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Acknowledgements

This work was supported by the Novo Nordisk Foundation (grant NNF17OC0028176; D.S.) and NIGMS R35 GM118167 (O.D.W.). We thank S. Hell, C. Eggeling and E. Sezgin for initial assistance with 3D STED and J. T. Groves, R. Dimova, D. Wustner and K. Madsen for helpful discussions on the project. We are also thankful to P. Lappalainen for the GFP–actin plasmid, P. J. Verveer for the EGFR–SNAP plasmid, N. Schmitt for HL-1 cells and K. L. Madsen for COS-7 cells. We thank T. Izard for pcDNA4-GFP-vinculin (Addgene plasmid 107153). We are grateful to D. Gadella for mNeonGreen–Rab7 (Addgene plasmid 129603), 4xmts-mNeonGreen (Addgene plasmid 98876) and lysozyme(1–31)-KDEL–mNeonGreen (Addgene plasmid 137804). We thank Y. Schwab and A. Kolovou for their help and expertise in cryo-EM.

Author information

Author notes

  1. These authors contributed equally: Gabriele Kockelkoren, Line Lauritsen.

Authors and Affiliations

  1. Center for Geometrically Engineered Cellular Membranes, Department of Chemistry, University of Copenhagen, Copenhagen, Denmark

    Gabriele Kockelkoren, Line Lauritsen, Christopher G. Shuttle, Eleftheria Kazepidou, Ivana Vonkova, Artù Breuer, Mark Uline & Dimitrios Stamou

  2. Howard Hughes Medical Institute, Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA

    Yunxiao Zhang

  3. Department of Chemical Engineering, Biomedical Engineering Program, University of South Carolina, Columbia, SC, USA

    Celeste Kennard & Mark Uline

  4. Cardiovascular Research Institute, University of California, San Francisco, CA, USA

    Rachel M. Brunetti & Orion D. Weiner

  5. Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA

    Rachel M. Brunetti & Orion D. Weiner

  6. Center for Geometrically Engineered Cellular Membranes, University of California, San Francisco, CA, USA

    Rachel M. Brunetti & Orion D. Weiner

  7. Max-Planck-Institute for Medical Research, Optical Microscopy Facility, Heidelberg, Germany

    Elisa D’Este

  8. Atomos Biotech, Copenhagen, Denmark

    Dimitrios Stamou

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  1. Gabriele Kockelkoren
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Contributions

D.S. conceived the strategy and was responsible for project management and supervision. L.L. developed and validated the principle of 3D imaging with help from C.G.S. and G.K. G.K. developed and validated the cell compression assay with help from R.M.B. and O.D.W. G.K. and D.S. designed the experiments. G.K. collected data with help from L.L. G.K. analyzed data with help from L.L. M.U. performed all theoretical calculations. C.G.S. was the principal software developer in the project. I.V. performed thin-section cryo-EM experiments. Y.Z. made constructs and provided help with Piezo1 experiments. C.K. developed visualization of color-coded amino acid residues onto the receptor structure in Fig. 2a,b, A.B. and E.K. contributed to conceptualization and preliminary experiments. E.D. provided help with STED microscopy. D.S. and G.K. wrote the main text. G.K. prepared all main and Supplementary figures with the help of L.L. for several Supplementary figures. M.U. and L.L. contributed to the Supplementary Information. All authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Mark Uline or Dimitrios Stamou.

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Competing interests

D.S. is the founder of Atomos Biotech. The other authors declare no competing interests.

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Nature Chemical Biology thanks Paolo Annibale, Juan Vanegas, and Wade Zeno for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 2D imaging reveals spatial variations in receptor intensity that cannot be interpreted without knowledge of membrane topography.

(a) Cartoons represent slices of membranes imaged by Confocal or total internal fluorescence microscopy (TIRF) microscopy at the cell equator and at the plasma membrane. (b-f) Confocal (b-d) or TIRF (e-f) images of the PM of HEK293 labeled with CellMask and/or the β1AR. All images are recorded at the basolateral membrane except for (B, left) which is at the cell equator. The heterogenous spatial distribution of intensity (domains of high/low intensity) cannot be interpreted as variations in density without prior knowledge of membrane topography. Color scales show relative intensity that is the smallest intensity present in an image is set to black. Data is from nR = 3. Scalebars: (a-b) 5 µm; (c-f) 500 nm.

Extended Data Fig. 2 Quantitative measurement of protein density and diffusion requires imaging of the plasma membrane in 3D to correct topography-induced artifacts that mimic the appearance of domains in 2D projections.

(a) Experimentally obtained 3D membrane topography map of the adherent plasma membrane of a HEK293 cell labelled using CellMask. (b) Illustration of the confocal excitation volume approximated by an ellipsoid (blue) and the tangent plane at a given point of the membrane (green). The membrane tilt angle θ (angle between the tangent plane and the imaging plane) varies between 0° – 90°. (c) The cross-sectional area between the plane and the ellipsoid (approximated by a cylinder for simplicity) scales with sec θ and serves as an approximation of the tilted membrane area. (d) An experimentally obtained 3D membrane topography map to which we computationally assigned a uniform receptor density. (e) Because of the variations in membrane topography, the 2D density projection of the uniform surface in (d) erroneously suggests the existence of GPCR domains. (f) For similar reasons, the spatially homogeneous diffusion in the 3D surface shown in (d) will erroneously appear to be heterogeneous if projected in 2D. (g) Schematic illustrations. The 2D projection of a uniformly labelled membrane of varying topography (left), can erroneously produce the appearance of 2D domains that cannot a priori be distinguished from bona fide variations in membrane label density (right).

Source data

Extended Data Fig. 3 Generation of high-accuracy topography maps of plasma membranes of living cells.

(a, b) Fluorescence confocal image of HEK293 cells over-expressing SNAP-β1AR (a) and CellMask (b). Data β1AR is representative for nR = 4 and CellMask nR = 3 replicates. (c, d) Illustration of an XZY-stack (dz/dx/dy = 30 nm) of the highlighted area in (a) and (b). (e, f) Extracted intensity Z-profiles of linescans highlighted in (c) and (d) and their corresponding Gaussian fits overlaid. The axial position of the Gaussian peak corresponds to the Z position of the membrane, whereas the amplitude of the Gaussian peak is proportional to protein or Cellmask density. (g) Topography map of the area shown in (b) reconstructed from the Z positions obtained from the Gaussian fitting. Color scale represents membrane height in nm. (h) Local error weighted quadric fit for a 3 × 3 pixel, 90 nm x 90 nm, area using Eq. 1 (see Methods). (i) Recovered denoised topography map after quadric fitting (same area as in (g)). Color scale is same as for (g). (j) Localization precision of the Z positions calculated as the error weighed standard error of the mean for a 3 × 3 pixel, 90 nm × 90 nm, area of the denoised topography maps. (k) Topography map from (i) overlaid with mean membrane curvature.

Source data

Extended Data Fig. 4 Validation of recovered membrane topography with RICM.

(a) Illustration of the overlay of the reconstructed 3D topography map with the corresponding reflection interference contrast microscopy (RICM) image. (b) Recovered membrane height plotted against RICM intensity for a representative cell. As predicted analytically by theoretical models, membrane height and RICM intensity follow a co-sinusoidal relationship (see Methods). The correlation is fitted with a cosine function that describes the data with an R2 = 0.999. Data is binned using an error weighted rolling average (10 ± 10 nm) with error bars showing the s.e.m. Data is from N = 59,280 data points, n = 20 cells from n = 4 experiments.

Source data

Extended Data Fig. 5 Assessment of the membrane stability over time imaged with confocal.

(a) Individual XZ images of a HEK293 acquired on the same location at t = 1 s, 20 s, 40 s, and 60 s. Initial visual assessment shows no major membrane displacements occur over t = 60 s. Data is from nR = 3. Scale bar, 1.5 μm. (b) Map of recovered Z position for the same XZ-slice imaged over t = 60 s. (c) To assess membrane movement, a rolling standard deviation is calculated for each X position over a 6 s time window showing the average movement of the membrane within the time frame needed for stable imaging. This allows us to image the spatial distribution of temporal nanoscopic displacements across the plasma membrane. (d) Histograms of rolling standard deviation (grey) as calculated in (c) and accuracy of retrieving Z position of the membrane after quadric fitting (pink) (Extended Data Fig. 7e). (e) Median membrane displacement, that is median of the rolling standard deviation, as a function of the applied time window. Pink dashed line represents the median accuracy in retrieving the Z position of the membrane after quadric fitting. Error bars show s.d.

Source data

Extended Data Fig. 6 Validation of β1AR density by ratio-metric imaging with a cell membrane probe.

(a) Schematic of experimental approach. HEK293 cells express SNAP-β1AR and are labelled with SS488, while the membrane is labelled with CellMask DeepRed. (b) β1AR density normalized by recovered membrane surface area versus β1AR density normalized by CellMask intensity. The dashed purple line is a linear fit to the data. Data is shown as error-weighted bins with equal number of data points per bin. Error bars, s.e.m for y-axis and s.d. for x-axis. (c) Normalized β1AR density versus mean curvature. Recovery of normalized β1AR density by surface normalization (green) or by CellMask intensity (purple) results in the same density-curvature correlation. Data is binned using an error-weighted rolling average (0.1 ± 0.1 μm−1) with error bars showing s.e.m. Data is from n = 7 cells from n = 1 experiment. (d-e) 2D projection of topography-corrected and normalized density of CellMask and β1AR for the same region at the PM. CellMask density is uniform at the PM (d), whereas β1AR forms domains (e). Scalebar, 500 nm.

Source data

Extended Data Fig. 7 Neither high-density nor low-density actin zones associate with domains of well-defined topography or mean curvature.

(a) Actin intensity at the plasma membrane overlaid with boundaries of high- and low-density zones of actin. Scale bar, 500 nm. (b) Density map of normalized β1AR overlaid with the actin boundaries from (a). Domain 1 in (a) and (b) indicates a low-actin-density region that contains both β1AR-enriched and -depleted domains. (c) Colocalization analysis of high- and low-density zones of actin with β1AR-enriched and -depleted domains. The colocalization percentages are compared to those of randomized actin zones. Quantitative correlations between high-/low-density actin regions and β1AR density patterns were either statistically nonsignificant or had low significance (P = 0.06 n.s., P = 0.03). P values are calculated by a two-sided paired t test. Data are the mean ± s.d. for nC = 23, nR = 2. (d) Membrane topography overlaid with the actin boundaries from (a). High- and low actin density zones are not preferentially colocalizing with membrane peaks or valleys. (e) Mean curvature overlaid with actin boundaries from (a). There is no preferential overlap of high- and low actin zones with positive or negative curvatures. Overlays are representative for n = 23 cells and n = 2 experiments.

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Extended Data Fig. 8 Activation by agonist induces clathrin redistribution from receptor-depleted domains to both receptor-enriched and -depleted domains.

(a) Representative XY micrographs of SNAP-β1AR (magenta) and pmKate2-clathrin (green) and a merge in HEK293 cells. (b-c) XZ micrograph of β1AR, clathrin and a merge. Clathrin colocalizes with depleted domains of β1AR (b), but not with β1AR-enriched domains in the apo state (c). (d-f) XZ micrographs of events of β1AR internalization via clathrin-mediated endocytosis (indicated by arrows) after addition of ISO. These events are removed in our image analysis pipeline for recovering membrane topography and GPCR density. For (b-f) β1AR is imaged in 3D STED (magenta), clathrin in confocal (green) and a merge is shown. (g-h) 2D projection of normalized clathrin (g) and β1AR density (h) in the apo state. Arrows indicate regions of clathrin colocalizing with β1AR-depleted and not with β1AR-enriched domains. (i-j) 2D projection of normalized clathrin (i) and β1AR density (j) after activation by ISO. Arrows indicate regions of clathrin colocalizing both with β1AR-enriched and -depleted domains, however β1AR-enriched and -depleted domains do not always colocalize with clathrin (arrow with asterisk). (k) Colocalization analysis of high-density clathrin regions with β1AR-enriched and -depleted domains before and after activation by isoproterenol (ISO). The colocalization percentages are compared to randomized clathrin zones. Under basal conditions, β1AR and clathrin were anticorrelated (P = 0.01), while after activation with the agonist ISO, clathrin colocalization with GPCR-enriched domains was not statistically significant (P = 0.65). P values are calculated by a two-sided paired t test. Data are mean ± s.d. for nC = 18, nR = 3. Scalebar, (a) 1 µm, (b-f) 200 nm, (g-j) 500 nm.

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Extended Data Fig. 9 Changes in membrane topography, curvature and β1AR density after cell flattening with an agarose pad.

Change in height (a), mean membrane curvature (b) and β1AR density (c) calculated by subtracting the values after flattening from the values before flattening (Fig. 3c,e,g and d,f,h). (d) Quantification of absolute change in height after flattening with an agarose pad from data in (a). The red line indicates the average change in membrane height of 14.5 nm. (e) Comparison of histograms of mean curvature of unperturbed (blue) and flattened (orange) for a single, representative HEK293 cell. After flattening the width of the histogram is smaller compared to the unperturbed cells. (f) Histograms of normalized β1AR density before (blue) and after (orange) flattening of the same cell as in (e). Normalized density of compressed cells shifts towards unity and the width of the histogram decreases. Data is representative for n = 10 cells in n = 5 replicates.

Extended Data Fig. 10 Domains of H-Ras, Piezo1 and EGFR at the PM of live cells.

2D projection of H-Ras density (a), overlay of H-Ras density on super-resolved topography map (b) and mean curvature map (c) of membrane topography shown in (b). H-Ras-enriched domains are formed at negative shallow curvature (see also Fig. 5d). (d-f) 2D projection of Piezo1 density (d), overlay of Piezo1 density on super-resolved topography map (e) and mean curvature map (f). Piezo1-enriched domains have high contrast and strongly couple to positive shallow curvature (see Fig. 5e). (g-i) 2D projection of EGFR density (g), overlay of EGFR density on super-resolved topography map (h) and mean curvature map (i). EGFR density variations couple to positive shallow curvature and are similar to those of β1AR and other studied GPCRs (see Supplementary Fig. 23). Black arrows indicate examples of H-Ras-, Piezo1- and EGFR-enriched domains. Scalebar (a,d,g), 500 nm.

Supplementary information

Supplementary Information

Supplementary Figs. 1–24 and Note.

Reporting Summary

Supplementary Video 1

xzy scanning for the reconstruction of superresolved membrane topography. The movie shows the principle of reconstructing membrane topography. The xz frames are scanned along the y axis, and the blue line represents the recovered membrane height for each frame

Supplementary Video 2

Overlay of recovered z position on an xzy stack imaged with confocal and 3D STED microscopy. The xz frames are shown while scanning in the y direction for confocal (top) and 3D STED (bottom) imaging modes. The confocal xz frames are overlaid with the recovered z position of the membrane in confocal (yellow), whereas the 3D STED xz frames are overlaid with the recovered z position in 3D STED (blue) and confocal (yellow). The recovered z position accurately follows the variations of the PM for both confocal and 3D STED imaging modes.

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Kockelkoren, G., Lauritsen, L., Shuttle, C.G. et al. Molecular mechanism of GPCR spatial organization at the plasma membrane. Nat Chem Biol 20, 142–150 (2024). https://doi.org/10.1038/s41589-023-01385-4

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