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Gating and modulation of a hetero-octameric AMPA glutamate receptor

Nature volume 594, pages 454–458 (2021)Cite this article

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Abstract

AMPA receptors (AMPARs) mediate the majority of excitatory transmission in the brain and enable the synaptic plasticity that underlies learning1. A diverse array of AMPAR signalling complexes are established by receptor auxiliary subunits, which associate with the AMPAR in various combinations to modulate trafficking, gating and synaptic strength2. However, their mechanisms of action are poorly understood. Here we determine cryo-electron microscopy structures of the heteromeric GluA1–GluA2 receptor assembled with both TARP-γ8 and CNIH2, the predominant AMPAR complex in the forebrain, in both resting and active states. Two TARP-γ8 and two CNIH2 subunits insert at distinct sites beneath the ligand-binding domains of the receptor, with site-specific lipids shaping each interaction and affecting the gating regulation of the AMPARs. Activation of the receptor leads to asymmetry between GluA1 and GluA2 along the ion conduction path and an outward expansion of the channel triggers counter-rotations of both auxiliary subunit pairs, promoting the active-state conformation. In addition, both TARP-γ8 and CNIH2 pivot towards the pore exit upon activation, extending their reach for cytoplasmic receptor elements. CNIH2 achieves this through its uniquely extended M2 helix, which has transformed this endoplasmic reticulum-export factor into a powerful AMPAR modulator that is capable of providing hippocampal pyramidal neurons with their integrative synaptic properties.

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Fig. 1: Physiology and architecture of the GluA1–A2_γ8–CNIH2 complex.
Fig. 2: Gating transitions of the GluA1–A2_γ8–CNIH2 octamer.
Fig. 3: Mechanism of AMPAR modulation by CNIH2.

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Data availability

Cryo-EM coordinates are deposited in the PDB under the accession codes 7OCA (resting state full-length AMPAR octamer), 7OCC (NTD of the resting state octamer), 7OCD (resting state LBD-TMD with TARP-γ8 only), 7OCE (resting state LBD-TMD of the octamer), 7OCF (active state LBD-TMD of the octamer); the corresponding EM maps are deposited in the EMDB under accession codes EMD-12802, EMD-12803, EMD-12804, EMD-12805 and EMD-12806. Source data are provided with this paper.

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Acknowledgements

We thank members of the Greger laboratory, B. Herguedas, J. Krieger and J.-N. Dohrke for comments on the manuscript; J. Krieger and J.-N. Dohrke for discussion, J. Krieger for help with the normal mode analysis, B. Köhegyi for help with cryo-EM imaging, V. Chang and K. Suzuki for helping to generate the CNIH2-1D4-HA stable cell line, M. Carvalho for assistance at early stages of this project, the LMB scientific computing and the cryo-EM facility for support, P. Emsley for help with model building, T. Nakane for helpful comments with RELION 3.1 and R. Warshamanage for helping with EMDA cryo-EM-map processing. We acknowledge the Diamond Light Source for access and support of the Cryo-EM facilities at the UK national electron bio10 imaging centre (eBIC), proposal EM17434, funded by the Wellcome Trust, MRC and BBSRC. This work was supported by grants from the Medical Research Council, as part of United Kingdom Research and Innovation (also known as UK Research and Innovation) (MC_U105174197) and BBSRC (BB/N002113/1) to I.H.G.

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  1. Jake F. Watson

    Present address: IST Austria, Klosterneuburg, Austria

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  1. Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK

    Danyang Zhang, Jake F. Watson, Peter M. Matthews, Ondrej Cais & Ingo H. Greger

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Contributions

I.H.G. conceptualized and supervised the study, and wrote the paper with input from J.F.W. D.Z. performed protein purification, cryo-EM data collection, data processing and model building. J.F.W. and O.C. designed and performed electrophysiological experiments. P.M.M. and J.F.W. performed confocal imaging and data analysis.

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Correspondence to Ingo H. Greger.

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Peer review information Nature thanks Sudha Chakrapani, Yael Stern-Bach and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Properties of neuronal and recombinant AMPAR complexes.

a, Electrophysiological properties of neuronal and recombinant AMPAR complexes. Top left, hippocampus schematic indicating selected cell types. Bottom left, rise time of fast-application glutamate responses of recombinant and neuronal AMPAR patches. The 20–80% rise time (ms) was as follows. Recombinant receptors: GluA1–GluA2, 0.46 ± 0.03 ms, n = 9; +γ8, 0.55 ± 0.03 ms, n = 11; +γ8+CNIH2, 0.59 ± 0.04 ms, n = 8. Neuronal receptors: CA1 pyramidal (pyr), 0.52 ± 0.02 ms, n = 14; CA3 pyramidal, 0.60 ± 0.05 ms, n = 5; DG granule (gran) cell (GC), 0.42 ± 0.02 ms, n = 6; CA1 stratum pyramidale interneurons (str rad IN), 0.51 ± 0.03 ms, n = 8. Welch’s ANOVA with Dunnett’s multiple comparison tests; recombinant, W2,15.11 = 4.25, P = 0.03; neurons, W3,12.12 = 5.40, P = 0.014 (further details in Supplementary Table 1). Top middle, example trace of rectification index recording from CA1 pyramidal neuron normalized to −100 mV peak amplitude. Bottom middle, quantified rectification index from recorded surface patches. Recombinant receptors: GluA1–GluA2, 0.70 ± 0.04, n = 8; +γ8, 0.60 ± 0.02, n = 12; +γ8+CNIH2, 0.63 ± 0.01, n = 12. Neuronal receptors: CA1 pyramidal, 0.58 ± 0.01, n = 13; CA3 pyramidal, 0.56 ± 0.01, n = 4; DG granule cell, 0.55 ± 0.04, n = 4; CA1 stratum pyramidale interneurons, 0.42 ± 0.08, n = 5. Welch’s ANOVA with Dunnett’s multiple comparisons test; recombinant, W2,15.01 = 2.47, P = 0.12; neurons, W3,7.57 = 1.5, P = 0.29 (further details in Supplementary Table 1). Top right, strong correlation between equilibrium current and desensitization rate are observed (individual neuronal patches plotted). Bottom right, equilibrium current for patch responses show auxiliary protein dependent modulation and neuronal heterogeneity. Percentage of peak current. Recombinant receptors: GluA1–GluA2, 1.81 ± 0.34, n = 9; +γ8, 4.72 ± 1.09, n = 11; +γ8+CNIH2, 10.97 ± 2.03, n = 8. Neuronal receptors: CA1 pyramidal, 4.86 ± 0.71, n = 14; CA3 pyramidal, 5.78 ± 1.00, n = 5; DG granule cell, 0.75 ± 0.22, n = 6; CA1 stratum pyramidale interneurons, 0.59 ± 0.29, n = 8. Welch’s ANOVA tests with Dunnett’s multiple comparisons test; recombinant, W2,12.09 = 11.93, P = 0.002; neurons, W3,12.42 = 16.74, P = 0.0001 (further details in Supplementary Table 1). b, Purification and cryo-EM images of the GluA1–A2_γ8–CNIH2 complex. Left, representative 4–12% Bis-Tris gel stained with Coomassie blue, indicating elution of GluA1–A2_γ8–CNIH2 complex from Flag beads. CNIH2 expression from the same purification is detected by probing for the C-terminal HA tag using western blotting. Purification was performed reproducibly (four times); uncropped blots are shown in Supplementary Fig. 1. Middle, a representative motion-corrected micrograph of the resting state GluA1–A2_γ8–CNIH2 complex among collected data. Scale bar, 50 nm. Right, representative two-dimensional class averages of the resting state GluA1–A2_γ8–CNIH2 complex. c, Left, cryo-EM maps of the full-length AMPAR octamer, depicting the three domain layers—NTD, LBD and TMD—composed of the GluA1 (blue) and GluA2 (red) heteromer associated with TARP-γ8 (green) and CNIH2 (orange). Right, schematic of the plasmid constructs and the secondary protein structure of auxiliary subunits.

Source data

Extended Data Fig. 2 Cryo-EM data-processing workflow of the resting-state GluA1–A2_γ8–CNIH2 complex.

Two datasets were first processed individually to remove particles lacking AMPAR features. Next, classifications focused on the LBD–TMD region were performed to separate CNIH-containing and CNIH-free particles, meanwhile classifications for full-length receptors were conducted to elucidate particles with a stable NTD signal. Subsequently, particles from the two datasets were combined together for refinement. Focused refinements were performed separately on the LBD–TMD gating core and the NTD region. To further improve the resolution, LBD and TMD are refined separately. A structure of A1/A2_γ8 (lacking CNIH2) was also resolved from the same dataset (containing only TARP-γ8 observed in three-dimensional slice). CNIH2 density was further enhanced by first applying symmetry expansion on aligned particles from the TMD reconstruction, following by focused classification and refinement on only CNIH2 and the surrounding receptor transmembrane helices. Inset, top view slices of the GluA1–A2_γ8–CNIH2 (left) and GluA1–A2_γ8 (right). Three-dimensional maps of the TMD region show signal for transmembrane helices of TARP-γ8 (green) and CNIH2 (orange).

Extended Data Fig. 3 Cryo-EM data-processing workflow of the active-state GluA1–A2_γ8–CNIH2 complex.

The overall data-processing procedure for the active-state complex is similar to that of the resting-state complexes. Focused refinement was performed on the LBD–TMD gating core and individual LBD and TMD domain layers of the receptor. CNIH2 density was further improved by first applying symmetry expansion on aligned particles from the TMD reconstruction, followed by focused classification on CNIH2 alone, and finally focused refinement on CNIH2 together with surrounding receptor transmembrane helices. Particles lacking CNIH2 found in these datasets were not of high enough quality to provide a high-resolution structure.

Extended Data Fig. 4 Cryo-EM analysis of GluA1–A2_γ8–CNIH2 and GluA1–A2_γ8 complexes.

a, Local resolution and Fourier shell correlation (FSC) of focused refinement maps at the TMD, CNIH2, LBD and NTD. Euler angle distribution of particles for cryo-EM reconstruction of the resting state GluA1–A2_γ8–CNIH2 complex. Three-dimensional maps are coloured based on the local resolution estimation. Masked (red) or unmasked (blue) FSCs of corresponding maps are both shown where FSC = 0.143 (black line). b, Local resolution and FSC of focused refinements at the TMD and LBD. Euler angle distribution of particles for cryo-EM reconstruction of the resting state GluA1–A2_γ8 complex. c, Local resolution, FSC of focused refinements at the TMD, CNIH2 and LBD. Euler angle distribution of particles for cryo-EM reconstruction of the active state GluA1–A2_γ8–CNIH2 complex. d, Model to map FSCs of GluA1–A2_γ8–CNIH2 LBD-TMD models in resting and active states, resting-state NTD model and resting-state GluA1–A2_γ8 LBD-TMD model.

Extended Data Fig. 5 Features of GluA1–A2_γ8–CNIH2 NTD and LBD layers and quality of the density in the TMD region.

a, Cryo-EM density and model of the resting state GluA1 (blue) and GluA2 (red) NTD dimer. GluA1-specific N-linked glycans are observed at N45 and N239 (green sticks). b, Cryo-EM density and model of GluA1–GluA2 LBD dimer in the resting state. Density and model for the competitive antagonist NBQX bound to its orthosteric site in the LBD cleft. c, Top view of cryo-EM density and model of GluA1–GluA2 LBD tetramer in the resting state. d, Cryo-EM density and model of GluA1–GluA2 LBD dimer in the active state demonstrating a closure of the LBD ‘clamshell’. e, Top view of cryo-EM density and model of GluA1–GluA2 LBD tetramer in the active state. Density and model of desensitization blocker cyclothiazide (CTZ) bound at the LBD dimer interface are shown in the inset. f, Cryo-EM density and model of transmembrane helices of GluA1–A2_γ8–CNIH2 in the resting state.

Extended Data Fig. 6 Cryo-EM data processing workflow of A2_γ8 homomeric complex.

Automatic particle picking was first applied on the raw images which had similar features to the GluA1–A2_γ8–CNIH2 heteromeric complex. Scale bar, 50 nm. Two-dimensional classifications were then performed to remove particles lacking AMPAR features. In several side-view two-dimensional class averages, an additional layer of density (marked by a red arrowhead) beneath the micelle can be observed. Next, selected particles were used for separate three-dimensional classifications on the full-length receptor (left) or on masked-out LBD–TMD regions (right). In each of the two classifications, around 10% of low-quality particles were removed and the remaining AMPAR-shaped class averages are presented (side and bottom views). An additional layer was observed in the full-length classification in all five classes (indicated by a red arrowhead). Three-dimensional refinement was performed on all classes individually, slices of the TMD region from the refined maps are also shown, with TARP-γ8 densities only apparent at the B′/D′ sites (indicated by green arrowheads).

Extended Data Fig. 7 TARP-γ8 and CNIH2 receptor-binding sites and their relevant bound lipids.

a, Overlay of the A′/C′ and B′/D′ binding sites, showing reorientations of five residues along the M1 helices (GluA1 M1, red; GluA2 M1, blue). These changes are likely mediated by TARP-γ8 engaging GluA1 M1. b, Strong lipid densities (light blue, density shown in grey mesh) line the cavity between GluA2 M1 and M4. F515, F517 and L518 from GluA2 pre-M1 interact with the lipids from the upper leaflet. Other residues from GluA2 M1, M2 and GluA1 M3 involved in these interactions are shown as sticks. c, LL1 binds to the TARP-γ8(N224) side chain, connecting TARP-γ8 to the GluA1 M2 pore helix. LL2 bridges between CNIH2 and the GluA2 M1 and M2 helices. d, ‘Open book’ view of the A′/C′ binding site, displaying how the UL1, LL2 and LL3 lipids engage the receptor (left) and the CNIH2 M1 and M2 helices (right). Side chains in close proximity to lipids are shown. e, Superposition of CNIHs and their binding peripheral helices from the resting-state GluA1–A2_γ8–CNIH2 (orange) and GluA2–CNIH3 (grey, PDB 6PEQ) complexes. Although the upper parts of the M1 and M2 helices of the CNIHs are aligned together, the lower part of CNIH2 is kinked away from the receptor relative to CNIH3—this permits the accommodation of three CNIH2 binding-relevant lipids. The distance between W26 (CNIH2) and C811 (GluA1) in GluA1–A2_γ8–CNIH2 and W26 (CNIH3) and C815 (GluA2) in GluA2–CNIH3 are measured. M1 and M4 from GluA1–A2_γ8–CNIH2 resting state are coloured as in Fig. 1. M1 and M4 for GluA2–CNIH3 (PDB 6PEQ) are coloured in grey. Three CNIH2 binding-relevant lipids LL2, LL3 and UL1 are shown as pink sticks. f, A density modelled as cholesterol occupies the pocket between CNIH2 M3 and M4, observed after focused refinement.

Extended Data Fig. 8 Features of the GluA1–A2_γ8–CNIH2 and GluA1–A2_γ8 conduction pore.

a, Density of M2/M3 gating regions and their fit against models in the resting and active state. b, Pore dimensions of resting state GluA1–A2_γ8 (left) and the resting (middle) and active (right) state of GluA1–A2_γ8–CNIH2 depicted by space-filling representation (HOLE program) with relevant side chains indicated as sticks. A comparison of the pore radius across these three structures indicates a similar diameter of the receptor gate in resting state GluA1–A2_γ8 (grey) and GluA1–A2_γ8–CNIH2 (orange), with a clear expansion observed in the active-state GluA1–A2_γ8–CNIH2 (red) complex. Diameter differences at the Q/R site are mainly caused by conformational variations at the R586 side chain among these three models. c, Pore dimensions measured between Cα of GluA1 Q582 and GluA2 R586 in resting-state GluA1–A2_γ8 (left), GluA1–A2_γ8–CNIH2 (middle) and active-state GluA1–A2_γ8–CNIH2 (right). Upon receptor activation, the distance between GluA2 R586 is increased by around 1 Å in GluA1–A2_γ8–CNIH2. d, Distance measured between Cα of GluA1 C585 and GluA2 C589 of GluA1–A2_γ8 resting state (left) and GluA1–A2_γ8–CNIH2 resting (middle) and active (right) state. The corresponding cryo-EM densities are shown as mesh. Upon receptor activation, the distance between the GluA2 subunits at C589 also increased by around 1.5 Å in GluA1–A2_γ8–CNIH2. All diameter labels are measured in ångström. e, Charge distribution maps of the intracellular face of GluA1–A2_γ8–CNIH2 (red: −5 kBT/e; blue, 5 kBT/e) in the resting (top) and active (bottom) state indicate a dilation of the pore entrance in the direction of GluA2, but not GluA1, during receptor activation.

Extended Data Fig. 9 Conformational changes of GluA1–A2_γ8–CNIH2 during receptor activation.

a, The top-view superposition along the pore axis of GluA1–A2_γ8–CNIH2 in resting (grey) and active (red) states shows the dilation of the receptor and rotation of TARP-γ8 and CNIH2 during activation. b, Superposition of GluA1–A2_γ8–CNIH2 in resting (grey) and active (coloured) states along the pore axis shows the conformational change in the GluA2 M1 and M3 linkers as well as the LBD region upon receptor activation. The GluA2 M3 linker moves towards the M1 linker, while the latter approaches the acidic β4 loop in TARP-γ8. The LBD ‘KGK’ motif also moves towards the acidic loop in TARP-γ8. c, d, Conformational change in TARP-γ8 and CNIH2 during receptor activation. Models are aligned along the pore axis. The translation of the Cα atoms from the resting to active state is indicated as arrows for every second residue. Arrows indicate the direction and distance of helical movements; these were determined for all Cα atoms between the two states relative to the centre of mass (COM) of a given auxiliary subunit. Auxiliary subunits come together on the GluA1 pre-M1 side (c), but are separated on the GluA2 pre-M1 side (d). The magnification in c shows a contact between the TARP-γ8 M4 helix and the base of the GluA1 M1/M2 cytoplasmic loop formed during receptor activation.

Extended Data Fig. 10 Flag immunoprecipitation, immunostaining and electrophysiology of CNIH homologues and CNIH2 mutants in complex with GluA1 or GluA2 homomers.

a, Flag immunoprecipitation of CNIH homologues and CNIH2 mutants in complex with Flag-tagged GluA2 homomers. CNIH12CHIM, CNIH1–CNIH2 chimera with a fragment of CNIH2 (51-RERLKNIERICCLLRK-66) inserted into CNIH1 between P50 and L51; F3L, CNIH2 F3L; F5L, CNIH2 F5L; F8L, CNIH2 F8L; CNIH2 3FL, all three phenylalanines at positions 3, 5 and 8 in CNIH2 are mutated to leucine; FT, flow through. Immunoprecipitations were performed reproducibly (three times); uncropped blots are shown in Supplementary Fig. 1. b, Surface CNIH fluorescence (left), total CNIH fluorescence (middle) and surface/total ratio (right) for CNIH homologues and CNIH2 mutants in complex with GluA2. Surface CNIH (AU): no CNIH, 0.21 ± 0.15, n = 80; CNIH1, 6.60 ± 0.63, n = 46; CNIH2, 7.54 ± 0.56, n = 55; CNIH3, 8.07 ± 0.64, n = 61; CNIH12CHIM, 8.56 ± 0.69, n = 61; F3L, 4.42 ± 0.80, n = 17; F5L, 4.25 ± 0.40, n = 50; F8L, 8.36 ± 0.75, n = 34; 3FL, 1.67 ± 0.22, n = 50. Kruskal–Wallis test, H8 = 256.3, P < 0.0001. Total CNIH (AU): no CNIH, 0.02 ± 0.06, n = 80; CNIH1, 21.5 ± 2.03, n = 46; CNIH2, 25.8 ± 2.08, n = 55; CNIH3, 25.2 ± 2.19, n = 61; CNIH12CHIM, 25.0 ± 1.49, n = 61; F3L, 12.7 ± 1.85, n = 17; F5L, 16.2 ± 1.97, n = 50; F8L, 24.6 ± 2.00, n = 34; 3FL, 27.3 ± 2.42, n = 50. Kruskal–Wallis test: H8 = 230.1, P < 0.0001. Surface/Total: CNIH1, 0.34 ± 0.03, n = 46; CNIH2, 0.39 ± 0.04, n = 55; CNIH3, 0.42 ± 0.04, n = 61; CNIH12CHIM, 0.36 ± 0.02, n = 61; F3L, 0.41 ± 0.08, n = 17; F5L, 0.35 ± 0.03, n = 50; F8L, 0.39 ± 0.04, n = 34; 3FL, 0.07 ± 0.01, n = 50. One-sample Wilcoxon signed-rank test (median = 0), P < 0.0001; further details in Supplementary Table 3. Homologues CNIH1, CNIH2 and CNIH3 show robust surface expression. CNIH2 mutants F3L, F5L and F8L, as well as the CNIH12CHIM chimera, also traffic to the cell surface, whereas 3FL does not. F3L and F5L CNIH2 mutants show decreased total and, consequently, surface expression levels; to ensure that the AMPARs in our electrophysiology experiments were still saturated with CNIHs, we used a 1:2 AMPAR:CNIH co-transfection ratio. Increasing this ratio further to 1:4 for F3L and F5L did not affect the gating properties, suggesting that the observed change in AMPAR modulation by these mutants is not caused by their lower (surface) expression. c, Representative images showing surface CNIH (green), total CNIH (magenta) and total GluA2 (blue). d, Equilibrium current (Fig. 3a dataset) (percentage of peak). GluA2 alone: 1.03 ± 0.19, n = 15; CNIH2 wild type (WT), 24.72, ± 4.55, n = 9; F3L, 9.25 ± 1.16, n = 7; F5L, 8.96 ± 1.16, n = 9; F8L, 8.05 ± 1.00, n = 6; 3FL, 2.01 ± 0.28, n = 9. Welch’s ANOVA with Dunnett’s multiple comparisons test; W5,17.48 = 27.95, P < 0.0001. e, Equilibrium current (Fig. 3c dataset). GluA2 alone, 1.33 ± 0.50, n = 6; CNIH1, 3.52 ± 0.56, n = 12; CNIH12CHIM, 10.93 ± 1.16, n = 11; CNIH2, 19.77 ± 1.93, n = 7. Welch’s ANOVA with Dunnett’s multiple comparisons test; W3,15.36 = 40.08, P < 0.0001; further details in Supplementary Table 2.

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Extended Data Table 1 Cryo-EM data collection, refinement and validation statistics
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Supplementary information

Supplementary Information

This file contains Supplementary Fig. 1 (the uncropped gels and immunoblots) and Supplementary Tables 1-4 which list P values from statistical tests used in the study.

Reporting Summary

Video 1

: Cryo-EM map of the full-length A1/2_γ8/C2 complex The complex is composed of the GluA1 (blue), GluA2 (red) heteromer associated with γ8 (green) and CNIH2 (orange).

Video 2

: Conformational changes at gate and selectivity filter of A1/2_γ8/C2 during receptor activation Conformational changes of GluA1 and GluA2 from resting to active state are shown first from side view and then from top view. The model is coloured with the same scheme in Fig1.

Video 3

: Movements of auxiliary subunits in A1/2_γ8/C2 during receptor activation Movements of γ8 and CNIH2 from resting to active state are shown first from side view and then from bottom view. The model is coloured with the same scheme in Fig1.

Video 4

: Normal model analysis of A1/2_γ8/C2 at active state Energetically favorable motion modes of A1/2_γ8/C2 at active state via normal mode analysis are shown from side view (top) and bottom view (bottom). The model is coloured with the same scheme in Fig. 1.

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Zhang, D., Watson, J.F., Matthews, P.M. et al. Gating and modulation of a hetero-octameric AMPA glutamate receptor. Nature 594, 454–458 (2021). https://doi.org/10.1038/s41586-021-03613-0

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