Dynamic tuneable G protein-coupled receptor monomer-dimer populations

Patricia M. Dijkman, Oliver K. Castell, Alan D. Goddard, Juan C. Munoz-Garcia, Chris De Graaf, Mark I. Wallace, Anthony Watts*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

G protein-coupled receptors (GPCRs) are the largest class of membrane receptors, playing a key role in the regulation of processes as varied as neurotransmission and immune response. Evidence for GPCR oligomerisation has been accumulating that challenges the idea that GPCRs function solely as monomeric receptors; however, GPCR oligomerisation remains controversial primarily due to the difficulties in comparing evidence from very different types of structural and dynamic data. Using a combination of single-molecule and ensemble FRET, double electron-electron resonance spectroscopy, and simulations, we show that dimerisation of the GPCR neurotensin receptor 1 is regulated by receptor density and is dynamically tuneable over the physiological range. We propose a "rolling dimer" interface model in which multiple dimer conformations co-exist and interconvert. These findings unite previous seemingly conflicting observations, provide a compelling mechanism for regulating receptor signalling, and act as a guide for future physiological studies.

Original languageEnglish
Article number1710
JournalNature Communications
Volume9
Issue number1
DOIs
Publication statusPublished - 1 Dec 2018

Funding

We thank the Centre of Advanced ESR (CAESR, University of Oxford) for access to EPR equipment, and Jeffrey Harmer and William Myers for technical support. We thank Mark Newton and Christopher Wedge (Physics Department, University of Warwick) for access to Q-band EPR equipment and technical assistance during preliminary measurements. We also thank Gareth Jones (Velindre Cancer Centre) for guidance in the approach to MC simulation, and Stijn van Weezel (School of Economics, University College Dublin) for assistance with the statistical analysis. We thank Huanting Liu and Jim Naismith (University of St. Andrews) for the donation of the TEV-His6 construct. We are grateful to GLISTEN (COST Action CM1207). This work was supported by the BBSRC (BB/G019738/1 to MIW and AW) and EPSRC (EP/D048559/1, to AW as co-PI). O.K.C. is supported by a Cardiff University SBP Research Fellowship. P.M.D. was supported by MRC (G0900076/1 to AW).

FundersFunder number
Cardiff University SBP
Medical Research CouncilG0900076/1
Engineering and Physical Sciences Research CouncilEP/J013501/1, EP/D048559/1
Biotechnology and Biological Sciences Research CouncilBB/G019738/1

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