Spatial Intensity Distribution Analysis: Studies of G Protein-Coupled Receptor Oligomerisation
Authors: John D. Pediani, Richard J. Ward, Sara Marsango, Graeme Milligan
Journal: Trends in Pharmacological Sciences (2017)

GPCRs may exist and function as monomers: however, abundant evidence suggests they can form dimers/oligomers. This concept has implications for drug discovery as it may offer opportunities to modulate the effects of known pharmaceuticals or identify new drug therapies. A variety of approaches have been applied to this issue from traditional biochemical techniques, via resonance energy transfer approaches to recently developed image analysis-based techniques such as SpIDA. This uses mathematical analysis of confocal microscopy images to generate quantal brightness and density information for a fluorophore-tagged receptor. SpIDA can be applied to live or fixed cells and native tissue. SpIDA has been applied to GPCRs from each of the major subfamilies to explore their oligomerisation status at steady state and their regulation by receptor density and ligand binding. Spatial intensity distribution analysis (SpIDA) is a recently developed approach for determining quaternary structure information on fluorophore-labelled proteins of interest in situ. It can be applied to live or fixed cells and native tissue. Using confocal images, SpIDA generates fluorescence intensity histograms that are analysed by super-Poissonian distribution functions to obtain density and quantal brightness values of the fluorophore-labelled protein of interest. This allows both expression level and oligomerisation state of the protein to be determined. We describe the application of SpIDA to investigate the oligomeric state of G protein-coupled receptors (GPCRs) at steady state and following cellular challenge, and consider how SpIDA may be used to explore GPCR quaternary organisation in pathophysiology and to stratify medicines. Spatial intensity distribution analysis (SpIDA) is a recently developed approach for determining quaternary structure information on fluorophore-labelled proteins of interest in situ. It can be applied to live or fixed cells and native tissue. Using confocal images, SpIDA generates fluorescence intensity histograms that are analysed by super-Poissonian distribution functions to obtain density and quantal brightness values of the fluorophore-labelled protein of interest. This allows both expression level and oligomerisation state of the protein to be determined. We describe the application of SpIDA to investigate the oligomeric state of G protein-coupled receptors (GPCRs) at steady state and following cellular challenge, and consider how SpIDA may be used to explore GPCR quaternary organisation in pathophysiology and to stratify medicines. Spatial intensity distribution analysis (SpIDA) (see Glossary) is a recently developed biophysical approach to interrogate the organisational structure of proteins of interest in situ [1Godin A.G. et al.Revealing protein oligomerisation and densities in situ using spatial intensity distribution analysis.Proc. Natl. Acad. Sci. U. S. A. 2011; 108: 7010-7015Crossref PubMed Scopus (81) Google Scholar, 2Swift J.L. et al.Quantification of receptor tyrosine kinase transactivation through direct dimerization and surface density measurements in single cells.Proc. Natl. Acad. Sci. U. S. A. 2011; 108: 7016-7021Crossref PubMed Scopus (69) Google Scholar, 3Barbeau A. et al.Spatial intensity distribution analysis (SpIDA): a new tool for receptor tyrosine kinase activation and transactivation quantification.Methods Cell Biol. 2013; 117: 1-19Crossref PubMed Scopus (10) Google Scholar, 4Barbeau A. et al.Quantification of receptor tyrosine kinase activation and transactivation by G-protein-coupled receptors using spatial intensity distribution analysis (SpIDA).Methods Enzymol. 2013; 522: 109-131Crossref PubMed Scopus (20) Google Scholar]. SpIDA is based on the generation of pixel-integrated fluorescence intensity histograms, created from regions of interest (RoIs) drawn on recorded confocal images, which are analysed with super-Poissonian distribution functions to obtain density maps and quantal brightness (QB) values of the fluorophore used to label the protein being studied. Normalisation of these values to the QB of the fluorophore label in its monomeric state provides information on both the density (usually expressed as particles per μm2) and the oligomeric state (expressed as monomeric equivalent units, MEUs) of the assessed protein. Here, the advantages and the limitations of SpIDA when compared with other biophysical approaches are briefly considered. This is followed by a description of the use of SpIDA to investigate the oligomeric state of rhodopsin-like (class A) [5Ward R.J. et al.Regulation of oligomeric organisation of the serotonin 5-hydroxytryptamine 2C receptor observed by spatial intensity distribution analysis.J. Biol. Chem. 2015; 290: 12844-12857Crossref PubMed Scopus (49) Google Scholar, 6Pediani J.D. et al.Dynamic regulation of the quaternary organisation of the M1 muscarinic receptor by subtype-selective antagonist drugs.J. Biol. Chem. 2016; 291: 13132-13146Crossref PubMed Scopus (33) Google Scholar, 7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar], secretin-family (class B) [8Ward R.J. et al.Spatial intensity distribution analysis quantifies the extent and regulation of homodimerization of the secretin receptor.Biochem. J. 2017; 474: 1879-1895Crossref PubMed Scopus (22) Google Scholar], and glutamate-like (class C) [1Godin A.G. et al.Revealing protein oligomerisation and densities in situ using spatial intensity distribution analysis.Proc. Natl. Acad. Sci. U. S. A. 2011; 108: 7010-7015Crossref PubMed Scopus (81) Google Scholar] G protein-coupled receptors (GPCRs) and how this may be modulated by receptor expression level and altered by treatment of cells expressing these receptors with antagonist and inverse agonist ligands. Box 1 and Figure 1 provide brief overviews of key steps necessary to establish and analyse SpIDA measurements. A fuller description of technical aspects of SpIDA is available in Ward et al. [9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar].Box 1Important Steps to Perform SpIDA MeasurementsBefore starting to collect laser scanning confocal microscope images, it is necessary to determine certain values specific to the microscope setup in use, such as the laser spot beam waist radius size, to determine the confocal spot resolution, and detector shot noise, to ensure that only the fluorescent intensity fluctuations originating from the excited fluorophore tag are analysed. Recommended image collection parameters for performing SpIDA are detailed in Ward et al. [9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar].Another critical step is to determine the QB of the fluorescent label that is used to tag the receptor of interest. This requires expression in both a cellular system in which the label is expressed in defined monomeric/dimeric forms and, importantly, in the same cellular compartment as the protein of interest; for example, for GPCR studies, at the plasma membrane. In work described by the authors [5Ward R.J. et al.Regulation of oligomeric organisation of the serotonin 5-hydroxytryptamine 2C receptor observed by spatial intensity distribution analysis.J. Biol. Chem. 2015; 290: 12844-12857Crossref PubMed Scopus (49) Google Scholar, 6Pediani J.D. et al.Dynamic regulation of the quaternary organisation of the M1 muscarinic receptor by subtype-selective antagonist drugs.J. Biol. Chem. 2016; 291: 13132-13146Crossref PubMed Scopus (33) Google Scholar, 7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar, 8Ward R.J. et al.Spatial intensity distribution analysis quantifies the extent and regulation of homodimerization of the secretin receptor.Biochem. J. 2017; 474: 1879-1895Crossref PubMed Scopus (22) Google Scholar, 40Zakrys L. et al.Roundabout 1 exists predominantly as a basal dimeric complex and this is unaffected by the binding of ligand Slit2.Biochem. J. 2014; 461: 61-73Crossref PubMed Scopus (25) Google Scholar] this has been achieved in two distinct ways (Figure I). In the first a single copy of monomeric EGFP, or a tandem of monomeric EGFP, was fused to the intracellular carboxyl terminus of the single TM, integral membrane protein, CD86. Many studies, using a variety of techniques, have shown CD86 to be strictly monomeric. When expressed, CD86–EGFP is targeted to the plasma membrane. Alternatively, both single and tandem forms of monomeric EGFP were modified at the N terminus by addition of a consensus sequence, derived from the Lyn non-receptor tyrosine kinase N terminus, that resulted in the co- and post-translational addition of the fatty acids palmitate and myristate. Such dual modification is known to anchor otherwise soluble proteins to the plasma membrane. As the C-terminal region of GPCRs is intracellular, then a copy of monomeric EGFP linked in-frame is anticipated to be in an environment akin to that within the control constructs. Initial studies demonstrated that the tandem forms of monomeric EGFP had QB almost exactly twice the value of the single monomeric EGFP linked forms.Once QB has been calculated for the monomeric/dimeric controls these values are used to normalise experimentally measured QB values for the protein of interest and to generate MEU values that provide information on the oligomeric state of the receptor of interest. In addition, QB values are used to quantify the density of the fluorescent label, often presented as receptors per μm2 [9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar]. Clearly, it is important that the fluorescent label chosen to tag the GPCR of interest does not have inherent tendency to form dimer/oligomers. The web based osFP server (http://codes.bio/osfp/) [45Simeon S. et al.osFP: a web server for predicting the oligomeric states of fluorescent proteins.J. Cheminform. 2016; 8: 72Crossref PubMed Scopus (24) Google Scholar] offers information of this topic and tendency to oligomerise may also be determined as described by Cranfill et al. [46Cranfill P.J. et al.Quantitative assessment of fluorescent proteins.Nat. Methods. 2016; 13: 557-562Crossref PubMed Scopus (268) Google Scholar].Appropriate software to perform SpIDA may be downloaded, in the form of a MATLAB graphical user interface programme, from https://neurophotonics.ca/software. Detailed instructions explaining how to operate the SpIDA software can be obtained by downloading the user guide manual from the neurophotonics website. Briefly, this software runs the SpIDA analysis on the RoIs drawn on the input image and generates an Excel compatible text file containing the various analysed numerical parameter output values, along with a reference output image displaying the RoI analysed and fitted curve through the histogram plot.Figure 1SpIDA Procedure. Schematic representation of the procedure to perform SpIDA measurements as described in Box 1 and in more detail in Ward et al. [9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar]. (A) The G protein-coupled receptor of interest is modified by the incorporation of a fluorophore, for example, monomeric (A206K) enhanced GFP (i) or the SNAP-tag (ii), for which labelled substrates are available [43Keppler A. et al.Labeling of fusion proteins with synthetic fluorophores in live cells.Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 9955-9959Crossref PubMed Scopus (354) Google Scholar, 44Keppler A. et al.A general method for the covalent labeling of fusion proteins with small molecules in vivo.Nat. Biotechnol. 2003; 21: 86-89Crossref PubMed Scopus (1359) Google Scholar], at the carboxyl (intracellular) or amino (extracellular) terminus of the receptor, respectively. (B) The receptor construct is expressed stably in a heterologous mammalian cell system such as Flp-In T-REx 293 or CHO-K1 cells. (C) Laser scanner confocal images are collected from the glass coverslip attached to the basolateral membrane of the cells. (D) RoIs (red square) are selected and analysed using MATLAB graphical user interface programme. (E) Mean fluorescence intensity and QB values are normalised to the QB of the fluorophore label in its monomeric state and provides information on the density (expressed as particles per μm2) and the oligomeric state (expressed as MEUs) of the fluorophore-tagged protein. (i) The expression levels and calculated oligomeric state of human dopamine D3 receptor linked to mEGFP (hD3–mEGFP) expressed in Flp-In T-REx 293 cells is shown as an example [7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar]. The vertical broken line corresponds to the mean receptor number per μm2 and the horizontal dotted line corresponds to 1.406 MEU which represents mean +2 standard deviations of the data set (see Marsango et al. [7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar] for details). (ii) RoIs characterised by QB MEU values >1.406 were considered to contain a prevalence of hD3–mEGFP in a dimeric/oligomeric state. Data are adapted from Marsango et al. [7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar]. Abbreviations: mEGFP, monomeric enhanced GFP; MEU, monomeric equivalent unit; QB, quantal brightness; RoI, region of interest; SpIDA, spatial intensity distribution analysis.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Before starting to collect laser scanning confocal microscope images, it is necessary to determine certain values specific to the microscope setup in use, such as the laser spot beam waist radius size, to determine the confocal spot resolution, and detector shot noise, to ensure that only the fluorescent intensity fluctuations originating from the excited fluorophore tag are analysed. Recommended image collection parameters for performing SpIDA are detailed in Ward et al. [9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar]. Another critical step is to determine the QB of the fluorescent label that is used to tag the receptor of interest. This requires expression in both a cellular system in which the label is expressed in defined monomeric/dimeric forms and, importantly, in the same cellular compartment as the protein of interest; for example, for GPCR studies, at the plasma membrane. In work described by the authors [5Ward R.J. et al.Regulation of oligomeric organisation of the serotonin 5-hydroxytryptamine 2C receptor observed by spatial intensity distribution analysis.J. Biol. Chem. 2015; 290: 12844-12857Crossref PubMed Scopus (49) Google Scholar, 6Pediani J.D. et al.Dynamic regulation of the quaternary organisation of the M1 muscarinic receptor by subtype-selective antagonist drugs.J. Biol. Chem. 2016; 291: 13132-13146Crossref PubMed Scopus (33) Google Scholar, 7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar, 8Ward R.J. et al.Spatial intensity distribution analysis quantifies the extent and regulation of homodimerization of the secretin receptor.Biochem. J. 2017; 474: 1879-1895Crossref PubMed Scopus (22) Google Scholar, 40Zakrys L. et al.Roundabout 1 exists predominantly as a basal dimeric complex and this is unaffected by the binding of ligand Slit2.Biochem. J. 2014; 461: 61-73Crossref PubMed Scopus (25) Google Scholar] this has been achieved in two distinct ways (Figure I). In the first a single copy of monomeric EGFP, or a tandem of monomeric EGFP, was fused to the intracellular carboxyl terminus of the single TM, integral membrane protein, CD86. Many studies, using a variety of techniques, have shown CD86 to be strictly monomeric. When expressed, CD86–EGFP is targeted to the plasma membrane. Alternatively, both single and tandem forms of monomeric EGFP were modified at the N terminus by addition of a consensus sequence, derived from the Lyn non-receptor tyrosine kinase N terminus, that resulted in the co- and post-translational addition of the fatty acids palmitate and myristate. Such dual modification is known to anchor otherwise soluble proteins to the plasma membrane. As the C-terminal region of GPCRs is intracellular, then a copy of monomeric EGFP linked in-frame is anticipated to be in an environment akin to that within the control constructs. Initial studies demonstrated that the tandem forms of monomeric EGFP had QB almost exactly twice the value of the single monomeric EGFP linked forms. Once QB has been calculated for the monomeric/dimeric controls these values are used to normalise experimentally measured QB values for the protein of interest and to generate MEU values that provide information on the oligomeric state of the receptor of interest. In addition, QB values are used to quantify the density of the fluorescent label, often presented as receptors per μm2 [9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar]. Clearly, it is important that the fluorescent label chosen to tag the GPCR of interest does not have inherent tendency to form dimer/oligomers. The web based osFP server (http://codes.bio/osfp/) [45Simeon S. et al.osFP: a web server for predicting the oligomeric states of fluorescent proteins.J. Cheminform. 2016; 8: 72Crossref PubMed Scopus (24) Google Scholar] offers information of this topic and tendency to oligomerise may also be determined as described by Cranfill et al. [46Cranfill P.J. et al.Quantitative assessment of fluorescent proteins.Nat. Methods. 2016; 13: 557-562Crossref PubMed Scopus (268) Google Scholar]. Appropriate software to perform SpIDA may be downloaded, in the form of a MATLAB graphical user interface programme, from https://neurophotonics.ca/software. Detailed instructions explaining how to operate the SpIDA software can be obtained by downloading the user guide manual from the neurophotonics website. Briefly, this software runs the SpIDA analysis on the RoIs drawn on the input image and generates an Excel compatible text file containing the various analysed numerical parameter output values, along with a reference output image displaying the RoI analysed and fitted curve through the histogram plot. SpIDA was developed in response to limitations of other techniques, including fluorescence correlation spectroscopy (FCS) and photon counting histogram (PCH), used to investigate protein quaternary structure. These techniques base analysis upon temporal fluorescence fluctuations and require that the density and oligomerisation state of the protein in question remains constant during image acquisition [3Barbeau A. et al.Spatial intensity distribution analysis (SpIDA): a new tool for receptor tyrosine kinase activation and transactivation quantification.Methods Cell Biol. 2013; 117: 1-19Crossref PubMed Scopus (10) Google Scholar]. By contrast, SpIDA is based upon a spatial domain fluctuation, recorded as single images representing moments in time of receptor density and oligomerisation state. A significant advantage of SpIDA is that there is less susceptibility to potential effects of photobleaching because only a single input image is required, and hence, underestimation of QB and thus the size of protein complexes as such effects are minimised [3Barbeau A. et al.Spatial intensity distribution analysis (SpIDA): a new tool for receptor tyrosine kinase activation and transactivation quantification.Methods Cell Biol. 2013; 117: 1-19Crossref PubMed Scopus (10) Google Scholar]. An important technical challenge when using fluorescent labels in the determination of protein oligomerisation state is that of subquantitative and therefore, imperfect, labelling (which also applies equally to other approaches). This may be due, for example, to misfolding of a fluorescent protein or inefficient covalent incorporation of a fluorophore or antibody-mediated addition of a fluorescent species. Clearly, this will bias the distribution of oligomeric states measured within a cellular system. To alleviate such concerns Godin and co-workers [10Godin A.G. et al.Spatial intensity distribution analysis reveals abnormal oligomerization of proteins in single cells.Biophys. J. 2015; 109: 710-721Abstract Full Text Full Text PDF PubMed Scopus (21) Google Scholar] developed the SpIDA software to include a probability-weighted correction algorithm for nonemitting labels that can be applied when performing SpIDA to correct for nonquantitative labelling. A limitation of SpIDA is its inability to directly quantify rapid, real-time temporal dynamic diffusion information relating to oligomeric complex formation or dissociation within cellular compartments, including the plasma membrane. Moreover, dynamic protein oligomeric complex formation occurs on a spatial resolution distance scale <100 nm and this separation distance is too small to be resolved by conventional diffraction-limited fluorescence microscopy. To circumvent this limitation, the laser spot confocal volume is oversampled and the excitation illumination volume for membrane oligomerisation measurements is quantified as a surface as opposed to a 3D volume [5Ward R.J. et al.Regulation of oligomeric organisation of the serotonin 5-hydroxytryptamine 2C receptor observed by spatial intensity distribution analysis.J. Biol. Chem. 2015; 290: 12844-12857Crossref PubMed Scopus (49) Google Scholar, 6Pediani J.D. et al.Dynamic regulation of the quaternary organisation of the M1 muscarinic receptor by subtype-selective antagonist drugs.J. Biol. Chem. 2016; 291: 13132-13146Crossref PubMed Scopus (33) Google Scholar, 7Marsango S. et al.A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization.Sci. Rep. 2017; 72134Crossref PubMed Scopus (15) Google Scholar, 8Ward R.J. et al.Spatial intensity distribution analysis quantifies the extent and regulation of homodimerization of the secretin receptor.Biochem. J. 2017; 474: 1879-1895Crossref PubMed Scopus (22) Google Scholar, 9Ward R.J. et al.The use of spatial intensity distribution analysis to examine G protein-coupled receptor oligomerization.in: Herrick-Davis K. G Protein-Coupled Receptor Dimers. Springer, 2017: 15-38Crossref Scopus (4) Google Scholar]. That single-polypeptide GPCRs can form and function as dimers and/or higher-order oligomers, rather than simply as monomers, has been hypothesised and then tested over a period of many years [11Ferré S. et al.G protein-coupled receptor oligomerisation revisited: functional and pharmacological perspectives.Pharmacol. Rev. 2014; 66: 413-434Crossref PubMed Scopus (434) Google Scholar]. For example, it is clear that formation of either homo- or heterocomplexes defines the pharmacology and function of members of the family of glutamate-like or class C GPCRs [12Chun L. et al.Structure and ligand recognition of class C GPCRs.Acta Pharmacol. Sin. 2012; 33: 312-323Crossref PubMed Scopus (62) Google Scholar]. Furthermore, a considerable number of studies have been directed at defining the quaternary structure of class B GPCRs, with particular focus on the secretin receptor. Mutagenesis studies and the use of peptides corresponding to each of the transmembrane domains (TMs) of the secretin receptor resulted in the conclusion that it exists as a dimer stabilised by interactions that occur between residues in TM IV [13Harikumar K.G. et al.Transmembrane segment IV contributes a functionally important interface for oligomerization of the Class II G protein-coupled secretin receptor.J. Biol. 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