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      Single-molecule diffusion-based estimation of ligand effects on G protein–coupled receptors

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          Abstract

          G protein–coupled receptors (GPCRs) are major drug targets. Developing a method to measure the activities of GPCRs is essential for pharmacology and drug screening. However, it is difficult to measure the effects of a drug by monitoring the receptor on the cell surface; thus, changes in the concentrations of downstream signaling molecules, which depend on the signaling pathway selectivity of the receptor, are often used as an index of receptor activity. We show that single-molecule imaging analysis provides an alternative method for assessing the effects of ligands on GPCRs. Using total internal reflection fluorescence microscopy (TIRFM), we monitored the dynamics of the diffusion of metabotropic glutamate receptor 3 (mGluR3), a class C GPCR, under various ligand conditions. Our single-molecule tracking analysis demonstrated that increases and decreases in the average diffusion coefficient of mGluR3 quantitatively reflected the ligand-dependent inactivation and activation of receptors, respectively. Through experiments with inhibitors and dual-color single-molecule imaging analysis, we found that the diffusion of receptor molecules was altered by common physiological events associated with GPCRs, including G protein binding, and receptor accumulation in clathrin-coated pits. We also confirmed that agonist also decreased the average diffusion coefficient for class A and B GPCRs, demonstrating that this parameter is a good index for estimating ligand effects on many GPCRs regardless of their phylogenetic groups, the chemical properties of the ligands, or G protein–coupling selectivity.

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          Most cited references38

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          Structural basis of glutamate recognition by a dimeric metabotropic glutamate receptor.

          The metabotropic glutamate receptors (mGluRs) are key receptors in the modulation of excitatory synaptic transmission in the central nervous system. Here we have determined three different crystal structures of the extracellular ligand-binding region of mGluR1--in a complex with glutamate and in two unliganded forms. They all showed disulphide-linked homodimers, whose 'active' and 'resting' conformations are modulated through the dimeric interface by a packed alpha-helical structure. The bi-lobed protomer architectures flexibly change their domain arrangements to form an 'open' or 'closed' conformation. The structures imply that glutamate binding stabilizes both the 'active' dimer and the 'closed' protomer in dynamic equilibrium. Movements of the four domains in the dimer are likely to affect the separation of the transmembrane and intracellular regions, and thereby activate the receptor. This scheme in the initial receptor activation could be applied generally to G-protein-coupled neurotransmitter receptors that possess extracellular ligand-binding sites.
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            Single-molecule imaging of EGFR signalling on the surface of living cells.

            The early events in signal transduction from the epidermal growth factor (EGF) receptor (EGFR) are dimerization and autophosphorylation of the receptor, induced by binding of EGF. Here we observe these events in living cells by visualizing single molecules of fluorescent-dye-labelled EGF in the plasma membrane of A431 carcinoma cells. Single-molecule tracking reveals that the predominant mechanism of dimerization involves the formation of a cell-surface complex of one EGF molecule and an EGFR dimer, followed by the direct arrest of a second EGF molecule, indicating that the EGFR dimers were probably preformed before the binding of the second EGF molecule. Single-molecule fluorescence-resonance energy transfer shows that EGF-EGFR complexes indeed form dimers at the molecular level. Use of a monoclonal antibody specific to the phosphorylated (activated) EGFR reveals that the EGFR becomes phosphorylated after dimerization.
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              Expression of G protein-coupled receptors and related proteins in HEK293, AtT20, BV2, and N18 cell lines as revealed by microarray analysis

              Background G protein coupled receptors (GPCRs) are one of the most widely studied gene superfamilies. Thousands of GPCR research studies have utilized heterologous expression systems such as human embryonic kidney cells (HEK293). Though often treated as 'blank slates', these cell lines nevertheless endogenously express GPCRs and related signaling proteins. The outcome of a given GPCR study can be profoundly influenced by this largely unknown complement of receptors and/or signaling proteins. Little easily accessible information exists that describes the expression profiles of the GPCRs in cell lines. What is accessible is often limited in scope - of the hundreds of GPCRs and related proteins, one is unlikely to find information on expression of more than a dozen proteins in a given cell line. Microarray technology has allowed rapid analysis of mRNA levels of thousands of candidate genes, but though often publicly available, the results can be difficult to efficiently access or even to interpret. Results To bridge this gap, we have used microarrays to measure the mRNA levels of a comprehensive profile of non-chemosensory GPCRs and over a hundred GPCR signaling related gene products in four cell lines frequently used for GPCR research: HEK293, AtT20, BV2, and N18. Conclusions This study provides researchers an easily accessible mRNA profile of the endogenous signaling repertoire that these four cell lines possess. This will assist in choosing the most appropriate cell line for studying GPCRs and related signaling proteins. It also provides a better understanding of the potential interactions between GPCRs and those signaling proteins.
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                Author and article information

                Journal
                Science Signaling
                Sci. Signal.
                American Association for the Advancement of Science (AAAS)
                1945-0877
                1937-9145
                September 18 2018
                September 18 2018
                September 18 2018
                September 18 2018
                : 11
                : 548
                : eaao1917
                Article
                10.1126/scisignal.aao1917
                30228224
                d2635bcd-5486-4ba9-a4bb-0625cbc7cdf1
                © 2018

                http://www.sciencemag.org/about/science-licenses-journal-article-reuse

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