Modular transient nanoclustering of activated β2-adrenergic receptors revealed by single-molecule tracking of conformation-specific nanobodies

Abstract

None of the current superresolution microscopy techniques can reliably image the changes in endogenous protein nanoclustering dynamics associated with specific conformations in live cells. Single-domain nanobodies have been invaluable tools to isolate defined conformational states of proteins, and we reasoned that expressing these nanobodies coupled to single-molecule imaging-amenable tags could allow superresolution analysis of endogenous proteins in discrete conformational states. Here, we used anti-GFP nanobodies tagged with photoconvertible mEos expressed as intrabodies, as a proof-of-concept to perform single-particle tracking on a range of GFP proteins expressed in live cells, neurons, and small organisms. We next expressed highly specialized nanobodies that target conformation-specific endogenous β₂-adrenoreceptor (β₂-AR) in neurosecretory cells, unveiling real-time mobility behaviors of activated and inactivated endogenous conformers during agonist treatment in living cells. We showed that activated β₂-AR (Nb80) is highly immobile and organized in nanoclusters. The Gαs-GPCR complex detected with Nb37 displayed higher mobility with surprisingly similar nanoclustering dynamics to that of Nb80. Activated conformers are highly sensitive to dynamin inhibition, suggesting selective targeting for endocytosis. Inactivated β₂-AR (Nb60) molecules are also largely immobile but relatively less sensitive to endocytic blockade. Expression of single-domain nanobodies therefore provides a unique opportunity to capture highly transient changes in the dynamic nanoscale organization of endogenous proteins.

Keywords: nanobodies; single-particle−tracking superresolution microscopy; β2-adrenoreceptor.

Fig. 1.

Single-particle detection of PH-PLCδ^WT-EGFP by GBP-Nb-mEos2 using the FiLM technique. (A) Expression of PH-PLCδ^WT-EGFP (GFP target) (Top) together with GBP-mEos2 (Bottom) facilitates single-particle tracking in cellular transfection systems. (B) Illustration of the principle of FiLM using PH-PLCδ^WT-EGFP target at the plasma membrane. (C) A representative PC12 cell in TIRF shows the green fluorescence of PH-PLCδ^WT-mEos2 prior to photoconversion. (Scale bar, 5 μm.) (The region of interest, defined by the white box, is used for D–F.) Superresolution imaging was performed at 50 Hz with analysis of movies generating (D) sptPALM average intensity map, (E) diffusion coefficient distribution (darker colors represent lower mobility), and (F) trajectory map (color coded by time; warmer colors acquired later into the acquisition). (G) PC12 cell expressing PH-PLCδ^WT-EGFP and GBP-mEos2 (H–J as per D–F). (Scale bar, 5 μm.) (K) Analysis of single-particle tracking was expressed as the MSD as a function of time, (L) AUC, (M) frequency distribution of the diffusion coefficient (Inset: trajectory number), and (N) mobile-to-immobile ratio (n = 12 and 17, cells for each condition from three independent experiments, PH-PLCδ^R40L-EGFP n = 10). Protein structures were generated in PyMOL. Statistics of AUC and mobile-to-immobile ratio were performed using an unpaired Student’s t test. The differences between the two conditions were all nonsignificant (NS). Nonparametric ANOVA Kruskal−Wallis test with Dunn’s multiple comparisons test was used to compare trajectory numbers between the three conditions.

Fig. 2.

Single-particle detection of Cav3-GFP in zebrafish by GBP-mEos2 using the FiLM technique. (A) Representative image of a 72-hpf zebrafish embryo. (B) Low-resolution image of the green fluorescence observed within skeletal muscle fibers of a zebrafish expressing Cav3-GFP as well as GBP-mEos2 at the location indicated by the red box in A. (Scale bar, 10μm). Superresolution imaging was performed at 33 Hz with analysis of movies generating (C and D) an average intensity map, (E) a diffusion coefficient map (darker colors represent lower mobility), and (F) a trajectory map (color coded by time; warmer colors acquired later into the acquisition). (Scale bar, C, 2.5 μm). (G) Illustrates the dual confinement trajectories within the region of interest in F. Red box (8 μm × 8 μm). (H) Low-resolution image of mEos2-Cav1 in transfected MDCK cells prior to photoconversion with a 405-nm laser. The region of interest is indicated with a white box (2 μm × 2 μm) in H. Superresolution imaging was performed at 50 Hz and analysis of movies generated (I) average intensity map, (J) diffusion coefficient map, and (K) trajectory map. Analysis of single-particle tracking was expressed as the (L) MSD as a function of time; (M) AUC, and (N) frequency distribution of the diffusion coefficient (n = 12 zebrafish from three independent injections; n = 15 MDCK cells from three independent experiments). Statistics of AUC were performed using an unpaired Student’s t test.

Fig. 3.

Single-particle detection of EFF-1::GFP in C. elegans by GBP-mEos2 using the FiLM technique. (A) Illustration showing the location of the mechanosensory neurons in C. elegans driven by Pmec-4 promoter expression. The portion of the PLM mechanosensory neuron imaged in these experiments is delineated by a red box. (B) Low-resolution image of the tail of a representative animal showing both left and right PLM mechanosensory neurons expressing Pmec-4::eff-1::gfp and Pmec-4::mEos2-N1-GBP-Nb. (C) Representative C. elegans PLM mechanosensory neuron in TIRF, expressing Pmec-4::eff-1::Eos2 taken prior to photoconversion with a 405-nm laser. (Scale bar, 5 µm.) Region of interest defined by the white box is used for D–F. Superresolution imaging was performed at 33 Hz and analysis of the movies generated (D) a trajectory map (color coded by time; warmer colors acquired later into the acquisition), (E) an average intensity map, and (F) a diffusion coefficient map (darker colors represent lower mobility). (G) C. elegans expressing Pmec-4::eff-1::gfp and Pmec-4::mEos2-N1-GBP-Nb (Scale bar as in C) (H–J as per D–F). Analysis of single-particle tracking was expressed as the (K) MSD as a function of time, (L) AUC, (M) frequency distribution of the diffusion coefficient, and (N) mobile to immobile ratio (n = 11 and 9, animals for each condition from three independent experiments). Statistics of AUC were performed using an unpaired Student’s t test, and a nonparametric Mann−Whitney U test was used to compare the mobile-to-immobile ratios.

Fig. 4.

Single-particle detection of β₂-AR-YFP by GBP-mEos2 using the FiLM technique before and after isoprenaline addition. (A) A representative PC12 cell in TIRF shows the green fluorescence of β₂-AR-YFP and GBP-mEos2 prior to photoconversion. (Scale bar, 5 μm.) (The region of interest, defined by the white box, is used for B and D).) Superresolution imaging was performed at 50 Hz and analysis of the movies generating (B) average intensity map; (C) diffusion coefficient distribution (darker colors represent lower mobility) and (D) trajectory map (color coded by time; warmer colors acquired later into the acquisition). (Scale bar, 1 μm.) (E–G) The region of interest of cell above following isoprenaline treatment (10 µM) (E–G as per B–D). (H) Analysis of single-particle tracking was expressed as the MSD as a function of time, (I) AUC, (J) frequency distribution of the diffusion coefficient (Inset: trajectory number); (K) mobile-to-immobile ratios (n = 16, from three independent experiments). (L and M) Hidden Markov modeling to infer mobility parameters of β₂-AR-YFP trajectories. (L) A three-state model with the inferred apparent diffusion coefficients and state occupancies are represented. Each state is illustrated by a colored circle (state 1, immobile, magenta; state 2, intermediate, green; state 3, fast mobile, blue), with the area proportional to the state occupancy. (M) Comparison of state occupancies inferred from β₂-AR-YFP trajectories (n = 16 sets, 16 cells from three independent experiments). Statistics of the AUC, mobile-to-immobile ratio, and state occupancy were performed using a paired Student’s t test, and trajectory number comparison was made using paired nonparametric Wilcox test.

Fig. 5.

Single-particle detection of β₂-AR-YFP by GBP-mEos2 following dynamin inhibition with Dyngo4a before and after isoprenaline treatment. Cells were transfected with β₂-AR-YFP and GBP-mEos2 and pretreated with either DMSO or 30 μM Dyngo4a 20 min prior to imaging before and after 10 µM isoprenaline treatment. (A and B) A DMSO-treated representative PC12 cell depicting the diffusion coefficient distribution of all ₂-AR tracked receptors is shown (A) before and (B) following isoprenaline treatment (10 µM) (outline of cell is shown in black dotted line). (C and D) A representative cell pretreated with Dyngo4a is shown (C) before and (D) after isoprenaline treatment. (Scale bar, 5 µm.) (E) Analysis of single-particle tracking was expressed as the MSD as a function of time, (F) AUC, (G) frequency distribution of the diffusion coefficient, and (H) mobile-to-immobile ratios (n = 13 [DMSO] and 15 [Dyngo4a], from three independent experiments). Statistics of the AUC were performed using a paired Student’s t test. Analysis of the mobile to immobile ratio was performed using a paired Wilcoxon test.

Fig. 6.

FiLM of Nb80-mEos2, Nb37-mEos2, and Nb60-mEos2 in PC12 cells following isoprenaline treatment. Transfected PC12 cells expressing (A–D) Nb80-mEos2, (E–H) Nb37-mEos2, or (I–L) Nb60-mEos2 were imaged and subjected to live FiLM. Cells were imaged before and after isoprenaline treatment (10 µM). Superresolution imaging was performed at 50 Hz. Movies were analyzed and data expressed as (A, E, and I) MSD as a function of time, (B, F, and J) AUC, (C, G, and K) frequency distribution of the diffusion coefficient, and (D, H, and L) mobile-to-immobile ratio (n = 9, 14, and 13, cells, respectively, for each condition from three independent experiments). Statistical analysis of the AUC and mobile-to-immobile ratio was performed using a paired Student’s t test.

Fig. 7.

Single-particle detection of endogenous β₂-AR by Nb80-mEos2, Nb37-mEos2, and Nb60-mEos2 following dynamin inhibition with Dyngo4a before and after isoprenaline treatment. Transfected PC12 cells expressing (A–D) Nb80-mEos2, (E–H) Nb37-mEos2, or (I–L) Nb60-mEos2 were imaged and subjected to live FiLM. Cells were pretreated with either DMSO or Dyngo4a (30 µM) for 20 min, then imaged before and after isoprenaline treatment (10 µM). Superresolution imaging was performed at 50 Hz. Movies were processed and single particle tracking was analyzed and represented as (A, E, and I) MSD as a function of time, (B, F, and J) AUC, (C, G, and K) frequency distribution of the diffusion coefficient, and (D, H, and L) mobile-to-immobile ratio (M/IM). (N [DMSO] = 9, 10, and 10 cells, respectively, and N [Dyngo4a] = 10, 11, and 10 from three to four independent experiments). Statistical analysis of the AUC and mobile-to-immobile ratio was performed using a paired Student’s t test, with the exception of Nb60 Dyngo4a results, which were analyzed by paired Wilcoxon test. (M) Number of trajectories from each 16,000-frame movie was analyzed to estimate the change in trajectories upon Dyngo4a and isoprenaline treatment. Paired Student’s t test was used to compare the number of trajectories before and after isoprenaline treatment.

Fig. 8.

Single-particle detection of Nb80-mEos2 and Nb37-mEos2 in PC12 cells using the FiLM technique. (A) Representative PC12 cell, in TIRF, of the green fluorescent Nb80-mEos2 intrabody that targets the active conformation of β₂-AR taken prior to photoconversion with a 405-nm laser. (Scale bar, 5 μm.) The region of interest is defined by the white box in A Superresolution imaging was performed at 50 Hz, and analysis of movies generated (B) average intensity map, (C) diffusion coefficient map distribution (darker colors represent lower mobility), and (D) trajectory map (color coded by time; warmer colors acquired later into the acquisition). (E) PC12 cell expressing Nb37-mEos2 (E–H as per A–D). Analysis of single-particle tracking was expressed as the (I) MSD as a function of time, (J) AUC, (K) frequency distribution of the diffusion coefficient, and (L) mobile-to-immobile ratio (N = 31 and 41 cells for Nb80 and Nb37, respectively). Statistics of AUC and mobile-to-immobile ratio were performed using a Student’s t test. (M) Distribution of the moment scaling slope of trajectories (n = 6,291 Nb80-mEos2 trajectories from 31 cells and 17,841 Nb37-mEos2 trajectories from 41 cells). (N) Percentage of immobile, confined, and free motion type identified using MSS. (O) Trajectories annotated based on different motion types. (Scale bar, Nb80, 1 μm; Nb37, 0.7 μm.)

Fig. 9.

Dynamics properties of endogenous activated β₂-AR and Gαs-coupled GPCR nanoclusters. (A–C) Individual trajectories of the single-particle tracking data of Nb80-mEos2 and Nb37-mEos2 were analyzed using HMM to infer mobility parameters. (A) A three-state model with the inferred apparent diffusion coefficients and state occupancies represented. Each state is illustrated by a colored circle (state 1, immobile, magenta; state 2, intermediate, green; state 3, fast mobile, blue), with the area proportional to the state occupancy. (B) Comparison of apparent diffusion coefficients of each state inferred from Nb80-mEos2 and Nb37-mEos2 trajectories. (C) Comparison of state occupancies inferred from Nb80-mEos2 and Nb37-mEos2 trajectories (n = 28 sets, 34 cells for Nb37-mEos2, n = 19 sets, 31 cells for Nb80-mEos2). Statistics of apparent diffusion coefficient and state occupancy were performed using a Student’s t test with Welch’s correction. (D–N) The dynamics of individual nanoclusters assessed using a combination of Voronoï-based cluster detection and tcPALM analyses in live PC12 cells. (D and J) Representative superresolution images of (D) Nb80-mEos2 and (J) Nb37-mEos2. (E and K) Voronoï diagrams of (E) Nb80-mEos2 and (K) Nb37-mEos2 detections. (F and L) Nanoclusters (black outline) detected by (F) Nb80-mEos2 and (L) Nb37-mEos2 were identified using Voronoï-based tessellation algorithm. (G) Nb80-mEos2 and (M) Nb37-mEos2 trajectories displaying immobile, intermediate, and fast motion patterns inferred using HMM. (H and N) Representative time series of detections from β₂-AR nanoclusters detected using (H) Nb80-mEos2 and (N) Nb37-mEos2. (I and O) The distribution of apparent burst times of (I) Nb80-mEos2 and (O) Nb37-mEos2 nanoclusters.