Functional and structural basis of a negative allostery within GABA_B hetero-tetramers

Domain: biology
Published: 2026-03-20
Editorial outcome: major_revision

Abstract
G protein coupled receptors (GPCRs) oligomerization may allow signal integration from different GPCR units. The GABA receptor, activated by the main inhibitory transmitter, GABA, is an obligatory heterodimer. It is the target of two therapeutic drugs, baclofen and GHB, and can form stable oligomers. The existence, roles and possible allosteric interaction of GABA oligomers remain elusive. Here, we show that GABA oligomers exist in neurons. Their function can be specifically affected by human disease-associated mutations, demonstrating their essential role for normal brain function. The cryo-EM structure of a hetero-tetramer in apo state reveals the heterodimers interacting in an asymmetrical way to prevent one unit from being activated. This represents a nice example of a negative allosteric interaction between GPCRs related to human diseases.

Introduction
G protein-coupled receptors (GPCRs) play crucial roles in cell signaling and communication allowing cells to detect and respond to various external signals and, as such, represent the most important drug targets1-3. Most of them function as monomers such as those of class A, B and F, or as constitutive dimers such as the class C receptors4, 5. Accumulating evidences indicate that these GPCRs can form hetero-dimer/oligomer and regulate each other through direct interaction, either transient or stable6-11. Such interactions reveal possible allosteric modulations of their function through formation of GPCR hetero-complexes, leading to the allosteric control12, 13 of one receptor by another14, 15, to signaling bias 16 with changes in signal efficacy and potency17-19. Although a few structures of GPCR homo-oligomers have been reported, such as rhodopsin20, 21, 1-AR22 or CXCR423, the molecular and structural basis of the allosteric control of one GPCR by another within a hetero-oligomer, likely important for signal integration, remains poorly understood.

GABA receptor is activated by γ-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the brain24. GABA receptor plays crucial roles in regulating brain functions and is implicated in locomotion, learning and memory, and cognition25-27. Dysregulation of GABA receptor activity has been implicated in various diseases, such as epilepsy, anxiety, depression, spasticity, addiction and pain28, 29. Human genetic mutations and auto-antibodies targeting the GABA receptor can be responsible for human diseases, including Rett syndrome30, developmental delay, epilepsy and encephalitis31-33. Accordingly, GABA receptor is the target of Baclofen (Lioresal®), a specific GABA receptor agonist used to treat spasticity in multiple sclerosis and alcohol abuse disorder28, 34, and by -hydroxybutyrate (GHB), a drug of abuse, also used for anesthesia35. GABA receptor is a member of the class C GPCRs, and an obligatory heterodimer consisting of two subunits, GB1 where agonists bind, and GB2 that couples to G proteins24, 36, 37, stabilized by a coiled-coil interaction between their intracellular tails38, 39. Each subunit comprises a large extracellular Venus flytrap domain (VFT) that consists of two lobes (LB1 and LB2)40 and seven-transmembrane domains (7TMs). In the inactive state, GB1 and GB2 interact through their LB1s and the intracellular tips of TM3 and TM541. Agonists (GABA, Baclofen) and antagonists (CGP54626) bind to GB1 VFT, whereas the VFT of GB2 does not bind ligands37. Agonists act by stabilizing a closed state of GB1 VFT, bringing the LB2 of each subunit in contact. The interplay between the two VFTs, essential for receptor activation, triggers a rearrangement from the inactive 7TM interface to an active one formed by the TM6 of both subunits40, 42, 43. This active conformation allows the coupling of G proteins to GB2 in a shallow pocket formed by TM3 and three intracellular loops42. Of interest, GABA receptor positive allosteric modulator (PAM) such as rac BHFF, binds at the TM6-TM6 interface to stabilize the active conformation of the receptor42 and also acts as a positive allosteric agonist (ago-PAM)42, 44, 45.

GABA heterodimers can assemble into stable hetero-tetramers or higher-order oligomers7, 17, 18, 46, 47,48. Indirect evidence for the existence of such oligomers in the brain exist17, 49. Our previous results showed that association of GABA heterodimers within hetero-tetramer is mediated by GB1 subunits, an effect leading to a negative control of one heterodimer by the other17, 18, 47. However, the structural basis and functional consequences for this allosteric control within GABA hetero-oligomer remains unknown.

In this study, we develop nanobodies specific to each subunit to provide direct evidence for the existence of GABA hetero-tetramers in primary neurons. We bring further support for a negative control of one GABA receptor over the other in hetero-tetramers and show that some disease-related mutations in GB1 VFT mainly affect the GABA hetero-tetramer function. These data demonstrating the physiological and pathological relevance of GABA hetero-oligomers, prompt us to solve its structure. This reveals an asymmetric assembly of the extracellular domains of each receptor units, such that only one can be activated at a time. This study illustrates how GPCRs can control their activities through allosteric interaction within oligomers and provide insights to develop drugs against GPCR oligomers.

Results
Development of nanobodies targeting the GABA subunits
To identify nanobodies targeting the GABA subunits, HEK293T cells transiently expressing both human and rat GABA receptor were injected into an alpaca and VHH (variable domain of the heavy chain of the camelid heavy-chain antibody) encoding sequences were amplified to generate a phage display library50. Nanobodies were further validated through binding experiments in HEK293T cells transfected with various human and rat GABA receptor constructs, including two GB1 isoforms (human GB1a, human GB1b), a GB1 mutant in which the ER retention signal RSR (Arg-Ser-Arg) at the C-terminal end of the coiled-coil domain was mutated to ASA (Ala-Ser-Ala), allowing cell surface expression of the construct expressed alone (human GB1ASA, rat GB1ASA), GB2 subunit (human GB2, rat GB2) and GB2 truncations that lack the VFT domain (human GB2 ΔVFT, rat GB2ΔVFT) (Extended Data Fig. 1a). Two nanobodies Nb-4C10 and Nb-5E9 were found to bind to GABA receptor with high-affinity (K = 4.0 nM and 6.2 nM, respectively) (Extended Data Fig. 1b, Extended Table 1). At a concentration of 1 M, Nb-4C10 binds to both human and rat GB1aASA, but shows no binding to human GB1b, human GB2 or rat GB2 (Extended Data Fig. 1b). This demonstrates its specific binding to the GB1a subunit isoform. As the GB1b isoform lacks the presence of a pair of sushi repeats in the N-terminal ectodomain of GB1a24, it suggests the epitope of Nb-4C10 is within the sushi domains of GB1a. The Nb-5E9 binds to the human and rat GB2 subunit, but shows no binding to human and rat GB1a or GB1b subunit, or human and rat GB2ΔVFT truncations (Extended Data Fig. 1b), indicating its specific binding to the GB2 subunit, particularly to the VFT of GB2. Both Nb-4C10 and Nb-5E9 display the same affinities for the active (agonist GABA-treated) and inactive (antagonist CGP54626-treated) forms of GABA receptor (Extended Data Fig. 1c, d), indicating that Nb-4C10 and Nb-5E9 bind to both conformational states of GABA receptor. In all, we have identified one nanobody (Nb-4C10) specific of both human and rat GB1a and another one (Nb-5E9) specific of the VFT of both human and rat GB2 subunits.

To address whether the binding of one nanobody affect binding of another, we performed competitive binding assays using HEK293 cells expressing human GABA receptors. Cells were incubated with 10 μM Alexa Fluor 647-conjugated nanobody, followed by increasing concentrations of the corresponding unlabeled nanobody (Extended Data Fig. 2a). We observed that competition occurred in 2 hours after the addition of the competing nanobody only within identical nanobody pairs (Nb-4C10 competed with Nb-4C10AF647 (Extended Data Fig. 2a), and Nb-5E9 competed with Nb-5E9AF647 (Extended Data Fig. 2b)), indicating that Nb-4C10 and Nb-5E9 bind independently to distinct, non-overlapping epitopes. Therefore, the binding of one nanobody does not interfere with the other, ensuring that our dual labeling strategy allows accurate quantification of dimers and tetramers in cells.

We further developed a nanobody toolbox based on the Nb-4C10 and Nb-5E9, including various Fc-fusions such as Nb-4C10Rabbit-Fc (Nb-4C10rFc), Nb-4C10Mouse-Fc (Nb-4C10mFc) and Nb-5E9Mouse-Fc (Nb-5E9mFc) (Extended Data Fig. 1e, f) and bivalent formats (Nb-4C10Bi) (Extended Data Fig. 1g, h), in which two GB1a-targeting nanobodies were linked via a GSG linker. All engineered nanobodies exhibit higher affinity than the monovalent ones (Extended Table 1).

Expression and activation of GABA hetero-tetramers
The nanobody-based proximity ligation assay (PLA) method achieves high-sensitivity detection of protein interactions using specific nanobodies engineered with rabbit-Fc and mouse-Fc domains to target proteins, utilizing a pair of DNA probes conjugated to anti-rabbit and anti-mouse antibodies for spatial proximity ligation and amplification51. Here, we developed a GABA receptor Nb-based PLA assay to evaluate the organization of GABA heterodimer and hetero-tetramer in the cell membrane. The Nb-4C10rFc and Nb-4C10mFc, both targeting GB1a (referred to as GB1 later), were used to detect GABA hetero-tetramer, as these results from a direct interaction between the GB1 subunits. As discussed later, GB1 strict homodimers are not expected to represent a large fraction of the GB1 subunits at the cell surface due to their stable association with GB252, 53, and their retention in the ER in the absence of GB238, 39. Nb-4C10rFc and Nb-5E9mFc targeting GB1 and GB2 respectively, were used to detect GABA heterodimer, either strict heterodimers or heterodimers being part of larger complexes (Fig. 1a). In HEK293 cells transfected with human GB1 and GB2, fluorescence dots were clearly detectable using both pairs of antibodies. The intensity of these signals was significantly higher compared to that of the control antibodies (Nb-4C10rFc and mouse IgG) (Fig. 1b), demonstrating the formation of both human GABA heterodimer and hetero-tetramer in HEK293 cells overexpressing human GABA receptor subunits. As a control for the PLA assay, the mGlu2 homodimer was validated by quantifying PLA-dots obtained with the mGlu2 nanobodies, and were found to represent 138% those obtained with the GB1-GB2 nanobodies, suggesting a higher expression level of the mGlu2 homodimers than GABA heterodimers (Extended Data Fig. 2c). In contrast, the mGlu2-GB1 number of PLA-dots per µm2 represent about 21% of the values measured with GB1-GB2, offering a good estimate of PLA signals resulting from a random proximity between two non-interacting cell surface proteins expressed at this level (Extended Data Fig. 2c). Due to the identical amino acid sequence of the sushi repeats in the GB1 subunit among human, rat and mouse, we extended the use of these nanobodies in primary mouse cerebellar granule neurons to examine the native GABA receptor. Similar fluorescence dots were also observed in neurons (Fig. 1c), providing additional evidence for the presence of both native GABA heterodimer and hetero-tetramers.

To examine the functional properties of both GABA heterodimers and hetero-tetramers, we employed the complemented donor-acceptor bioluminescence resonance energy transfer (CODA-RET)54 technique to measure G protein signal exclusively induced by either heterodimers or hetero-tetramers (Fig. 1d, Extended Data Fig. 3). This method relies on the NanoBiT system in conjunction with a bioluminescence resonance energy transfer (BRET) assay. In our experiments, the two fragments derived from Nluc, the 17.6-kDa subunit (LgBiT) and the modified small 9-amino acid subunit (HiBiT)55, were fused to the C-terminus of either GB1 or GB2. When GB1 LgBiT interacts with GB2 in a heterodimer or with another GB1 in a hetero-tetramer, the LgBiT and HiBiT fragments come into close proximity, enabling efficient complementation and reconstitution of functional Nluc. Additionally, in order to perfectly control the surface expression of both GB1 and GB2 subunits, an ER retention motif KKXX was added at the C-terminal end of the GB2 subunit56. As such, neither GB1, nor GB2 could reach the cell surface alone. With these subunits, the coiled coil interaction between the C terminal tails of GB1 and GB2 being able to mask both the natural and introduced ER retention motifs of GB1 and GB2, respectively, only the GB1-GB2 heterodimers could reach the cell surface. In parallel, we expressed a miniGi protein labeled with the acceptor molecule Venus. Since only the GABA hetero-tetramer and heterodimer containing the complemented Nluc can generate a luminescent signal, this approach allows for the specific measurement of G protein recruitment to these receptor populations (Extended Data Fig. 3). Using this approach, we found that GABA, which binds to the VFT of GB1, induced G protein recruitment in both GABA heterodimer and hetero-tetramer. Meanwhile, rac BHFF, a positive allosteric agonist (ago-PAM), which binds at the 7TM interface between GB1 and GB242, 44, 45, also induced G protein recruitment to both GABA heterodimer and hetero-tetramer (Fig. 1e). However, while the effect of GABA and rac BHFF at 100 M showed no significant difference in GABA heterodimer, the effect of Rac BHFF was significantly stronger in GABA hetero-tetramer by 3-fold of that of GABA, suggesting a distinct mode of G protein activation controlled by GABA hetero-tetramer, with a much lower efficacy of agonists compared to the ago-PAM.

Distinct pharmacogenetic property of GABA hetero-tetramer
Several mutations in the GB1 and GB2 encoded genes, which are located in the GB1 VFT and the TM6 of GB2, have been reported to be associated with Rett syndrome, epileptic encephalopathies and milder forms of developmental delay with absence epilepsy30, 31 (Fig. 2a, Extended Data Fig. 6a). The functional characterization of these variants and the investigation of the drug response were performed using GABA heterodimer as a model42. However, the pharmacological property of these mutations in GABA hetero-tetramers remains unknown. Using the CODA-RET system, we tested seven GABA receptor variants, including E368D, A397V and A535T mutations in GB1 VFT (Fig. 2a, b), and A567T, S695I, I705N and A707T mutations in GB2 TM6 (Extended Data Fig. 6a, b). We found that baclofen-induced G protein coupling by the E368D, A397V and A535T mutants was more profoundly decreased in GABA hetero-tetramer compared to heterodimer. While the A397V and A535T mutations had very limited effect on the heterodimer, they profoundly affect the functional response of the hetero-tetramer. Similarly, while E368D did decrease heterodimer function, this mutation almost suppressed activity of the hetero-tetramer (Fig. 2c, d). Similarly, rac BHFF that showed slight or no decrease in its efficacy at heterodimers mutants E368D and A397V (decrease 21% and 18%, respectively), or A535T (no effect), had a large drop in efficacy at the mutant hetero-tetramers (87%, 47% and 59% decrease, respectively) (Fig. 2c, d). To further quantify ligand efficacy, we reanalyzed the concentration–response curves using the operational model57-59, which yields the parameter logτ as a measure of functional efficacy assuming a similar receptor expression. The resulting logτ values followed a trend consistent with the differences in maximal response (TOP values) observed between wild-type and mutant receptors (Extended Data Fig. 4a). Similar results were observed for GABA in the GABA heterodimer and hetero-tetramer (Extended Data Fig. 4b, c). Most receptors were expressed at a similar level as the WT, except E368D, which showed a two-fold lower expression level compared to WT (Extended Data Fig. 4d). However, E368D of the hetero-tetramer mutant showed significant loss of function (Fig. 2d). Meanwhile, the luminescence signal showed no significant difference between GABA WT and mutants (Extended Data Fig. 4e). The effects of these heterodimer mutants on overall G protein signaling were also confirmed using conventional BRET assay detecting the change between GB2-Nluc and Venus-miniG , which was similar as the result in CODA-RET assay (Extended Data Fig. 5a-e). We found the effect of baclofen on G protein coupling efficacy of mutants A567T, S695I, I705N and A707T in both GABA heterodimer and hetero-tetramer were significantly decreased by 21%-81% compared to the respective WT (Extended Data Fig. 6c, d). The efficacy of rac BHFF at 100 M showed no significant change in GABA heterodimer mutants in A567T, S695I and I705N, while a slight increase was found in A707T (increase 32% respectively) (Extended Data Fig. 6c). In GABA hetero-tetramer, the efficacy of rac BHFF showed slight decrease for A567T, S695I and I705N (decrease 13%, 25% and 40% respectively), while significant increase in A707T by 42% (Extended Data Fig. 6d). Further analysis using the logτ values confirm this difference in receptor efficacy (Extended Data Fig. 6e). And most receptors were expressed at a similar level as the WT (Extended Data Fig. 6f, g). These results showed that the pharmacological and functional properties of GABA heterodimers and hetero-tetramers are differently affected by genetic variations. Some mutations affect mainly the hetero-tetramer, revealing its functional importance for normal brain function in humans. Such data highlight the importance of characterizing both forms of GABA receptor during drug development, and push us to determine the structure of the hetero-tetramer to get more information on the structural basis for the negative control of one receptor by the other.

Structural determination of GABA hetero-tetramer
To determine the structure of the GABA hetero-tetramer, we initially co-expressed human GB1 and GB2 under identical conditions previously established for the GABA heterodimer40, 42. The size-exclusion chromatography (SEC) revealed distinct peaks corresponding to GABA heterodimer and higher-order oligomers. However, the proportion of oligomers was notably low (Extended Data Fig. 7a-c). To address this limitation, we employed a strategy to combine the NanoBiT system55 with the LgBiT or HiBiT fused to the C-terminus of GB1 (GB1LgBiT and GB1HiBit) and the co-incubation of bivalent nanobody60 Nb-4C10Bi in the membrane extracts (Extended Data Fig. 7d) . It significantly facilitated the stabilization of the tetrameric form of GABA receptor during purification (Extended Data Fig. 7e, f), thereby enhancing the efficiency of isolating GABA hetero-tetramer for the determination of its cryo-electron microscopy (cryo-EM) structure.

We successfully determined the structure of the GABA hetero-tetramer in apo state (Fig. 3a). Representative 2D class averages indicated the assembly of two dimeric units (Extended Data Fig. 8a). In total, 55,594 particles were selected for 3D reconstruction, achieving a tetrameric structure with an overall resolution of 3.83 Å (Extended Data Fig. 8, Extended Table 3). To obtain the positioning of another 7TM-unit and enhance the resolution of the VFT region, we performed the local refinement on these two parts respectively based on the overall map. This enabled high-resolution visualization of the VFT domains at 3.70 Å, facilitating accurate placement of most side chains within the VFTs. The density of the sushi domains was not visualized in the cryo-EM structure as reported before40, 43, as well as Nb-4C10, which might be due to their high flexibility. Although the 7TMs were resolved at a lower resolution, this 7TM-unit1 domains at 6.07 Å still permitted unambiguous domain docking, facilitating the construction of the GABA hetero-tetramer model (Fig. 3b, Extended Data Fig. 8).

Our findings reveal that the GABA hetero-tetramer comprises two GABA heterodimers through the interaction between GB1 subunits. However, different from reported GB1 homodimer (PDB: 6W2Y) structure, which is symmetric organized, our data revealed that two GB1s in GABA hetero-tetramer adopts a more complicated asymmetrical structure. If the two GB2 subunits from the GABA heterodimers (PDB: 7C7S) are added to the GB1 homodimer (PDB: 6W2Y) to form a symmetrically organized chimeric hetero-tetramer, significant steric clashes are observed in both the VFT and 7TM domains (Extended Data Fig. 9), also supporting a preference for asymmetric arrangement in the GABA hetero-tetramer. When comparing the tetrameric units with the GABA heterodimer in its apo state, we observed significant conformational changes in unit 1, where GB2 rotated away from GB1, resulting in a translational shift of approximately 30-37 Å in the 7TM region (Fig. 3c). In contrast, the unit 2 exhibited more modest alterations, with minimal changes in the extracellular region, though conformational adjustments in the stalk region led to a 25° rotation of the 7TM (Fig. 3d). Despite the differing extents of conformational change, the integrity of the TM3-5/TM3-5 interface was preserved in each GABA heterodimers.

Asymmetric interaction between GB1 VFTs
The cryo-EM structure of GABA hetero-tetramer revealed an asymmetric interface formed by the GB1 VFTs (Fig. 4a). Notably, the LB2 of one GB1 subunit (GB1) closely interacts with the cleft formed between LB1 and LB2 of the other GB1 subunit (GB1’). Detailed analysis revealed that residues V412-E414 in GB1 form a close contact with residues A397-N399 and S458-E460 in GB1’ (Fig. 4b). They are located in the flexible loops (referred to as loop 1-3) of GB1 and GB1’. We then generated two mutants of GB1: GB1A397N/N399T and GB1E414N. Both mutants then carry an NXS/T sequence to allow the attachment of a bulky N-glycan moiety to the side chain of the Asn residue, creating a steric wedge to interference the GB1 and GB1’ interaction17, 47 (Fig. 4c). We found that the maximal Ca2+ release response induced by GABA increased by 80% for GABA receptor formed with GB1A397N/N399T and GB2 and by 30% for GABA receptor formed with GB1E414N and GB2, compared to the wild type GABA receptor (Fig. 4d). The lower effect observed with the E414N mutant compared with GB1A397N/N399T is likely explained by its 2-fold lower expression level relative to WT (Extended Data Fig. 10a). These results demonstrate that the efficacy of the G protein coupling is negatively controlled within the GABA hetero-tetramer by the asymmetric interactions between the two GB1 VFTs.

Tracing the evolutionary history of GABA receptors shows that while these receptors are found in various species, five species, including Drosophila, have evolved in specific lineages (Extended Data Fig. 10b, c). Structural comparison for three loops linking the LB1 and LB2 between human and Drosophila GABA heterodimer composed by dGB1 and dGB2 reveal that the loop 1 and loop 2 shares high similarity (Fig. 4e). However, loop 3 in Drosophila GB1, which corresponds to E459-E460 in the human ortholog, is longer with six additional residues (EEGYDI) (Extended Data Fig. 10c), likely preventing dGB1-dPGB1 interaction to form hetero-tetramer. The effect of this loop was validated by the PLA assay measured between GB1 and GB1, which showed a lower number of dots/µm2 (Extended Data Fig. 10d). A similar value was obtained with the Drosophila GB1 constructs in which we added the sushi domains to allow the generation of PLA signal with the nanobodies, indicating that the addition of the drosophila loop in the human GABA receptor results in the same PLA signal as that measured with the drosophila receptors (Extended Data Fig. 10d). Taken into account the background signal measured between GB1 and mGlu2, the introduction of the drosophila loop led to a two-fold decrease in the PLA signal, consistent with a lower proportion of GABA hetero-tetramers.

Inserting these six residues into the human GB1, also significantly enhanced the GABA-induced Ca2+ release response by 50% for maximal efficacy (Fig. 4f), further supporting the pivotal role of the asymmetric VFT interaction in the formation of the GABA hetero-tetramer and in the negative control of G protein coupling efficacy. Interestingly, when further comparing the residues of the three loops with the corresponding sequences of other class C family receptors, we found that there are dozens of extra residues near the position of loop 3 for both calcium-sensing receptor and metabotropic glutamate receptors (Extended Data Fig. 11a). Structural comparisons of these class C GPCR dimers also showed that it is very unlikely for these receptors to form tetrameric or multimeric forms through such VFT interaction (Extended Data Fig. 11b, c), consistent with previous studies suggesting that metabotropic glutamate receptors are incapable of forming oligomers in their apo state61.

We further investigated whether both GB1 are able to bind the ligand and whether both sites are required for function. We first performed structural modeling. Specifically, we individually aligned the closed conformation of the GB1 VFT domain (derived from the GABA dimer bound to baclofen) to either the GB1 or GB1’ subunit within our tetrameric structure (Fig. 5a-c). These modeling studies revealed that each GB1 VFT domain could independently adopt a closed conformation without steric clashes, suggesting that each GB1 subunit in the GABA tetramer possesses the potential to bind ligand (Fig. 5a-b). However, when we attempted to simultaneously model two closed GB1 VFT domains onto the two GB1/GB1’ subunits within the tetramer, we observed steric hindrance (Fig. 5c). This indicates that while both GB1 subunits can potentially bind ligand, only one subunit can undergo VFT domain closure at a given time due to these steric constraints. Then, we introduced two mutations (S247A and E466A) into the VFT of one GB1 to prevent GABA binding as previously reported17, to generate a GB1ΔB mutant (Extended Data Figure 12a). We co-transfected GB1 , GB1ΔB and GB2 to express a GABA hetero-tetramer mutant with only one VFT of GB1 able to bind GABA (Fig. 5c). Using the CODA-RET system, we found that this mutant was able to recruit G proteins with GABA stimulation, but the G protein coupling efficacy was significantly decreased by half compared with WT hetero-tetramer, while the potency was not affected (Fig. 5d). Assuming, as indicated above, that a single heterodimer can be activated by agonists within a tetramer, these data are consistent with the view that only one binding site in a tetramer is sufficient to activate the receptor. Indeed, in the tetramer bearing a GB1ΔB mutant subunit, no effect of agonist can be generated when this subunit is the one that can be activated, explaining the 2-fold decrease in efficacy, confirming a coordinated action of GABA hetero-tetramer. The GABA-induced G protein recruitment to either GABA heterodimer or hetero-tetramer were totally blocked by the antagonist CGP 54626 (Extended Data Fig. 13a-c). However, CGP 54626 decreased rac BHFF-induced G protein recruitment to GABA heterodimer and hetero-tetramer only partially (Extended Data Fig. 13d, e), indicating that action at the heterodimer 7TM interface can still lead to G protein recruitment when both GB1 VFTs are maintained in their inactive open state.

GB1 7TM of one heterodimer contacts GB2 of the other dimer
Different from the VFTs, the 7TMs of the GABA hetero-tetramer exhibited an overall symmetric organization in a rhomboidal shape. Both heterodimeric units adopted a TM3/5-TM3/5 interactions between GB1 and GB2, similar to that observed in the apo state of the isolated GABA heterodimer40. Meanwhile, the TM6s from GB1 and GB1’ formed a symmetric interface between two units, consistent with our previous results46 (Fig. 6a). Interestingly, we found another interface between the TM1 and TM7 of GB1 of one unit (referred to as GB1) and the TM4 of GB2 of the other unit (referred to as GB2’) (Fig. 6a). In the GABA hetero-tetramer, the bottom of both TM3 helices of the GB1-GB2 subunits maintain tight binding with a distance of 9 Å (Fig. 6b). At the top of TM5, despite a distance of 17 Å, the corresponding position was found to be occupied by cholesterol in the previous heterodimer, acting as a mediator in the middle of the interface indirectly maintaining TM3/5-TM3/5 interactions62, 63, and was also validated by cross-linking46. We found that the distances between TM1 and TM7 of GB1 and TM4 of GB2' are 22 Å and 26 Å respectively (Fig. 6b). Although about 10 Å longer than the TM3/5-TM3/5 distance, it is much closer than the 37 Å distance between TM6-TM6 of GB1-GB1’ and the 52 Å distance between TM4/5-4/5 of GB2-GB2’ (Fig. 6b), implying that the 7TM regions of GB1 and GB2' may have a greater propensity for coordinated interactions. We applied cross-linking strategy as previously to verify this interface16, 46, 64, 65. We mutated several potential residues into cystine. If these cystines are in close contact, a covalent disulfide bond will form between them under the treatment of oxidative copper-phenanthrolin (CuP), allowing the detection of a high molecular weight band for hetero-tetramer in blots. We observed such a band in cells transfected with GB1-K5901.38C and GB2-A6174.52C, or GB1-D831TM7C and GB2-A6174.52C (Fig. 6c). We also tested four pairs of additional mutant constructs (GB1-S5941.42C and GB2-I6134.48C, GB1-L5981.46C and GB2-C6104.45, GB1-A8357.30C and GB2-C6144.49, GB1-L8397.34C and GB2-L6094.44), and none of these alternative mutants led to crosslinked oligomers (Extended Data Fig. 14a, b)., further indicating that a close proximity between TM1 or TM7 of the GB1 from one unit with the TM4 of GB2 from the other unit. These data confirm that the 7TMs of the GABA hetero-tetramer are arranged in a symmetrical rhomboid shape, following the connection sequence of GB1-GB2’-GB1'-GB2.

Methods
This research complies with all relevant ethical regulations. All animal experiments were approved by the Animal Experimentation Ethics Committee of the College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.

Constructs
For functional experiments, the pCDNA3.1 plasmids encoding the HA-tagged wild-type GB1 and Flag-tagged GB2 from human were used as previously40, 42. A large fragment (LgBiT) and a small fragment (HiBiT) of the NanoBiT luciferase were cloned after the C-terminal of GB1 (WT or mutant). The Venus was fused before miniGi protein as previous reported70. The site-directed mutations of GABA receptor were generated using QuikChange mutagenesis protocol (Agilent Technologies, Santa Clara, CA, USA). All the constructs were confirmed by sequencing.

For protein production, human GB1a (residues 15-860) and GB2 (residues 42-780) cDNAs were cloned into the pEGBacMam vector as previously described. In brief, the original GB1 and GB2 signal peptide was substituted by haemagglutinin (HA) signal sequence. To facilitate expression and purification, an 8× histidine tag and 3C protease cleavage site were inserted at the C-terminus of GB1a subunit, while a Flag epitope tag (DYKDDDD) and a 2×GSG linker were added to the N-terminus of the GB2 subunit. To assist formation of GABA hetero-tetramer, LgBiT or HiBiT were added to the C-terminus of GB1a as previously55, to increase the stability of the hetero-tetramer.

Alpaca immunization, VHH library construction and phage display
The membrane extraction of HEK293 cells overexpressing human GABA receptor were used as the antigen for generation of specific nanobodies as our previously published protocol71. Briefly, a healthy young Alpaca was immunized subcutaneously with a solution of cell membrane extraction. Peripheral blood was collected during and after immunization. The peripheral blood mononuclear cells (PBMCs) were isolated and combined. Total RNA was extracted from the PBMCs and reverse-transcribed into cDNA. VHH genes were amplified from cDNA by a two-step nested PCR, digested with restriction enzymes, and ligated into the pHEN1 phagemid vector. The pelB signal sequence is located at the N-terminus of the VHH gene and leads to the periplasmic expression of nanobodies. The ligated phagemids were transformed into E. coli TG1 competent cells. All transformants were collected and stored as an immune VHH library.

The immune VHH library was used to select and screen nanobodies targeting human GABA receptor. A representative fraction of the VHH library was cultured and rescued using the KM13 helper phage to display nanobodies at the tips of the M13 phage. Phages were extracted from the E. coli TG1 strain and used for phage display biopanning in HEK293 cells overexpressing human GABA receptor. During the bio-panning process, negative phage-displayed VHHs were removed by HEK293 cells depletion with mock transfection. The phage was enriched and eluted with a trypsin solution. After phage infection with E. coli TG1, a representative fraction of the bacteria was plated, and hundreds of colonies were randomly inoculated and cultured for positive clonal VHH screening. These gIIIp-fused VHHs were expressed by isopropyl-β-D-thio galactopyranoside (IPTG) induction, and the periplasmic extracts were screened for specific binding to receptors using flow cytometry. The results of these selected clones were compared with those of negative and non-specific binding controls. Clones with a specific fluorescence intensity distribution of the anti-His-tag antibody detected by flow cytometer were recognized as positive and subjected to Sanger sequencing. The remaining phages were rescued and amplified for the next round of phage display.

Production and purification of nanobodies
DNA sequencing results from the positive clones were translated into amino acids for analysis. All amino acid sequences were aligned, repeated or redundant sequences were removed, and only clones with unique amino acid sequences were retained for further analysis. The pHEN1 phagemids encoding unique VHH genes were extracted from the cultured E. coli TG1 and transformed into E. coli BL21(DE3) competent cells, as the amber codon stops translation before the gIIIp gene72. High-purity soluble nanobodies were extracted from the periplasm of cultured E.coli inducing by IPTG and purified using a His-tagged protein purification protocol, followed by size-exclusion chromatography.

Flow cytometry-based binding assay
HEK293T cells were transiently transfected with HA-tagged GB1 and Flag-tagged GB2. 24 h after transfection, cells were detached with trypsin-EDTA and resuspended in ice-cold assay buffer (PBS, 2%BSA) at 4 million live cells/ ml. Cells were incubated for 1 h at RT with Nb at various concentrations and 1 h anti-His-tag Alexa Fluor® 647-conjugated Antibody (R&D SYSTEMS, catalog no. IC0501R). Cells were washed twice with PBS and resuspended in FACS buffer (PBS, BSA 0.5%). The binding was recorded on viable single cells and on the allophycocyanine (APC) channel using a CytoFLex Flow Cytometer (Beckman Coulter, Brea, CA, USA). Data were analyzed with FlowJoTM v10 software and cells were gated for i) singlets and ii) living cells. The analyzed data was plotted using GraphPad Prism Version 9.2 software.

Conjugation of nanobodies to fluorescent Dye
Nanobodies (1 mg in PBS) were incubated with 5 molar equivalents of Alexa Fluor 647-NHS (Thermo Fisher, USA). Unreacted dye was removed by PD-10 desalting column (Cytiva, USA). Conjugated nanobodies were concentrated and the degree of labeling was calculated per manufacturer’s protocol.

Competition test of nanobodies by flow cytometry
HEK293 cells overexpressing human GABA receptor were incubated with 10 M Alexa Fluor 647-conjugated nanobody, followed by the addition of increasing concentrations of unlabeled nanobody for 2 h to allow competitive binding. The percentage of positive events were recognized as the statistical value to characterize their competitive binding to human GABA receptor.

HEK293 cell culture and transfection
HEK293 cells (ATCC, CRL-1573, lot: 3449904) were cultured in DMEM supplemented with 10% FBS at 37°C in a humidified incubator containing 5% CO2. For transfections, cells were suspended and transfected using Lipofectamine 2000 with the appropriate expression constructs following the instructions.

Primary cerebellar granule neuron culture
For the primary culture of neurons, all experiments were specifically designed to minimize the number of animals used and were approved by the Animal Experimentation Ethics Committee of the College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. Kunming mice were obtained from the Center for Disease Control and Prevention of Hubei Province. The mice were raised in a specific pathogen free (SPF) environment with an ambient temperature of 18-22°C, a humidity of 50%-60%, and a 12 h light-dark cycle.

Primary cerebellar granule neuronal cultures were prepared from one-week-old newborn Kunming mice as previously described73. The dissected tissue was gently triturated after Versene (15040066; Gibco, Shanghai, China) treatment for 5 min at 37°C, and the homogenate was centrifuged at 170 g for 5 min. The pellet was re-suspended in culture medium DMEM-F12 (Ref 11320-033; Gibco) supplemented with 2 mM glutamine, 30 mM KCl, 100 U/mL penicillin, 100 g/mL streptomycin, and 10% fetal bovine serum (FBS) and seeded into dishes previously coated with poly-L-ornithine (Sigma-Aldrich).

Proximity ligation assay (PLA)
For experiments performed in cell cultures, HEK293 cells and primary mouse cerebellar granule neurons were blocked with 10% horse serum and permeabilized with 0.2% Triton X-100 (v/v). Experiments were then performed using PLA kit (Sigma, Cat. No. DUO92101) according to the manufacturer’s instructions (Duolink & PLA Technology, Olink-Bioscience)74. Briefly, cells were incubated with Nb-4C10rFc and Nb-5E9mFc, or Nb-4C10rFc and Nb-4C10mFc, or Nb-4C10rFc and mouse IgG at 37°C for 1 hours. PLA probes anti-rabbit plus and anti-mouse minus, which are secondary antibodies conjugated with oligonucleotides, were added and incubated for 1 hour at 37°C. Amplification template oligonucleotides were hybridized to pairs of PLA and circularized by ligation. The formed DNA circle was then amplified using rolling circle amplification, and detection of the amplicons was carried out using the PLA kit, resulting in red fluorescence signals. Cells were mounted and were analyzed under an oil immersion objective (×100) using a confocal microscope (Olympus FV3000). All acquisitions were made the same day under the same microscope setting and laser power to minimize variability among samples. Distinct bright spots contained within an area of the cells designated by the experimenter were counted using an ImageJ macro. Briefly, regions of interest (ROIs) corresponding to individual cells were defined, and image segmentation was performed by applying a threshold to generate binary images. The Analyze Particles function in ImageJ was then utilized to count particles larger than 0.198 m2 within the binary images, which were identified as the number of PLA dots. The resulting data were imported to Prism software (GraphPad) for further statistical analysis and visualization.

Bioluminescence resonance energy transfer (BRET) assay
HEK293 cells (ATCC, CRL438 1573, lot: 3449904) were transfected with GABA heterodimer (GB1 + GB2 ) or mutants of chimeric NanoBiT GABA receptor (GB1 + GB1 + GB2 ) WT or indicated mutants, together with Venus-miniG . Lipofectamine 2000 was used for the cDNA transfection into HEK293 cells. After 36 h transfection, cells were washed and starved in PBS at 37°C for 1.5 h before the BRET experiments. BRET measurements were performed as previously described using the PHERAstar FS (BMG Labtech, USA)75 with the programme PHERAstar control (Version 4.00 R4). The signals emitted by the donor (460-500 nm band-pass filter, Em 480 nm) and the acceptor (510-550 nm band-pass filter, Em 530 nm) were recorded after the addition of 10 μM furimazine. All measurements were performed at 37 °C. The BRET signal was determined by calculating the ratio between the emission of acceptor and donor (BRET = Em 530 nm / Em 480 nm). The change in BRET ratio (net BRET) was obtained by subtracting the BRET ratio after agonist treatment from the basal BRET (net BRET = BRET - BRET ).

Determining logτ using the Operational Model of Agonism
Concentration-response data were analyzed using the operational model of agonism (Black and Leff, 1983) to quantify agonist efficacy, expressed as logτ. For each experimental batch containing wild-type and mutant receptor data, a global nonlinear least-squares fit was performed. In this approach, the maximum system response (E ) and the transducer slope factor (n) were constrained as shared parameters across all groups, while logτ and logKA were estimated independently for each receptor variant. The fitting was implemented with the Levenberg-Marquardt algorithm via the minpack.lm (v.1.2-4) package in R (V.4.3.0). For mutants exhibiting low responses (e.g., E368D), the upper bound of logKA was constrained to avoid ambiguous parameter solutions, thereby ensuring that the estimated logτ reflected true differences in efficacy rather than artifactual shifts in affinity. From the model fit, logτ and its standard error were extracted directly for subsequent statistical comparison and interpretation of agonist efficacy across receptor constructs.

Cell surface quantification by ELISA
Cell surface and total expression of the indicated constructs were quantified by an enzyme-linked immunosorbent assay (ELISA). Cell culture medium was removed from 96-well plates 48 h after transfection, then cells were washed and fixed with 4% paraformaldehyde (Sigma-Aldrich), then blocked with 10% FBS (for the total expression group, 0.1% Triton X-100 (Thermo Fisher Scientific) was required before this step to increase the permeability of the cell membrane). Flag-tagged constructs were detected with the monoclonal mouse anti-Flag antibody coupled with horseradish peroxidase (1:20,000; F1804, Sigma-Aldrich). HA-tagged constructs were detected with the rat anti HA antibody coupled with horseradish peroxidase (1:20,000; 3F10, Roche, Indianapolis, USA). Bound antibodies were detected by chemoluminescence using a Super Signal substrate (Thermo Fisher Scientific) and a 2103 EnVision Multilabel Plate Reader (Perkin Elmer, Waltham, MA, USA).

Protein expression and purification of GABA hetero-tetramer
The purified plasmids DNA HA-GB1a-Lg Bit-His, HA-GB1a-HiBit -His and HA-flag-GB2 were mixed with PEI in a 3:1 ratio of PEI to DNA (w/w) followed by addition to HEK293F cells when density reached around 3.0 million/ml. 10 mM sodium butyrate was added 16-18 hours post-transfection. Cells were grown for 3 days at 30°C, then harvested. Cells were collected and washed with phosphate-buffered saline buffer. Finally, the cell pellets were rapidly frozen in liquid nitrogen and stored at 80°C for later use.

The cells were centrifuged, washed with PBS, and resuspended in HEPES buffer (pH 7.5) containing NaCl, glycerol, MgCl and CaCl , then homogenized. Membranes were solubilized with 0.5% (w/v) LMNG and 0.1% (w/v) CHS for 3 hours at 4°C. After centrifugation, the supernatant was purified by Ni-NTA and anti-FLAG affinity chromatography. The protein was eluted with HEPES buffer (pH 7.5) containing NaCl, LMNG, CHS, EGTA, and FLAG peptide. The GABA receptor was concentrated and purified by size-exclusion chromatography on a Superose 6 Increase column. The sample was pre-screened for sample quality by negative-stain transmission electron microscopy and then immediately prepared on cryo-EM grids for structural determination. For GABA hetero-tetramer, protein was collected and concentrated to 10 mg/mL for electron microscopy studies.

Cryo-EM grid preparation and data collection
For the preparation of Cryo-EM grids, 3 μl of the purified sample was applied onto a glow-discharged 200 mesh holey carbon grid (Quantifoil R1.2/1.3). The grids were blotted for 3.5 s with a blot force of 10 at 4 °C and 100% humidity, followed by plunge-frozen in liquid ethane using a Vitrobot Mark IV (Thermo Fisher Scientific). Cryo-EM data collection was performed on a Titan Krios microscope (Thermo Fisher Scientific) at 300 kV accelerating voltage equipped with a Falcon 4 direct electron detector and a SelectrisX energy filter performed at 10 eV slit width. Data was automatically collected by EPU software in electron event representation (EER) mode with a raw pixel size of 0.93 Å on the image plane. Image stacks were obtained at a dose rate of ~5.56 electrons per Å 2 per second with a defocus ranging from -0.8 to -2.4 m. The total exposure time was 7.36 s, resulting in a total dose of ~50 electrons per Å 2. A total of 58,261 movies were collected for GABA hetero-tetramer.

Imaging processing and 3D reconstruction
Image stacks were processed by CryoSPARCN software (v 4.4.0)68. The 58,261 movies were subjected to patch motion correction and patch CTF estimation. Particles were picked by Blob picker and selected by multiple rounds of 2D classification. By using 2D classification and the stochastic gradient descent algorithm in CryoSPARC, we obtained five initial models for subsequent processing. The particles in clearly defined 2D classes were then subjected to several rounds of heterogeneous refinement to isolate unique conformational states and eliminate particles in poorly defined class. Final global refinement of the hetero-tetramer maps was performed with the CryoSPARC non-uniform refinement and local refinement with masks including only the VFTs, or TMs. Composite maps were generated with Chimera (v.1.15)76. Map sharpening was performed with CryoSPARC and deepEMhancer77. Validation of cryo-EM maps and models was performed with Phenix (v.1.20.1-4487). UCSF Chimera (v.1.15) and Chimera X (v.1.5 and v1.6.1)78 were used for map/model visualizations and figure preparation.

Model building and refinement
The initial model for the GABA hetero-tetramer was generated based on the structure of antagonist-bound GABA (PDB 7C7S)42. All of the models were docked into the electron microscopy density maps in UCSF Chimera78. The docked model was subjected to flexible fitting using Rosetta79 and was further rebuilt in COOT80, followed by real-space-refinement in Phenix81. The final refinement statistics were validated using the module “comprehensive validation (cryo-EM)” in Phenix81. The goodness-of-fit of the model to the map was determined using a global model-versus-map Fourier shell correlation. Structure figures were created using UCSF Chimera and the UCSF Chimera X package.

Intracellular calcium release measurements
After 36 h transfection with plasmids encoding the indicated GABA receptor subunits and a chimeric protein G , HEK293 cells were loaded with 1 mM Ca2+ -sensitive fluorescent dye Fluo-4 AM (Molecular Probes, Eugene, OR, USA) for 1 h at 37°C. After a wash, cells were incubated with buffer and GABA solution at various concentrations was added after 40 s of recording. Fluorescence signals (excitation 485 nm, emission 525 nm) were measured by using the fluorescence microplate reader FLIPR Tetra (Molecular Devices, Sunnyvale, CA, USA) at sampling intervals of 1 s for 120 s. The response of Ca2+ release was generated by the peak value of fluorescence signals after drug injection subtract the mean value of fluorescence signals before drug injection. All the values of drug treatment were subtracted the value in buffer treatment as the net Ca2+ release. Data were analyzed with the program Soft Max Pro (Molecular Devices, Sunnyvale, CA, USA).

Cross-linking and fluorescent-labeled blot experiments
HEK293 cells were transfected with human HA-Halo-GB1a and Flag-GB2 or indicated mutations by lipofectamine 2000 and plated in 12-well plates for 36 h. Then cells were labeled with 100 nM Halo-660 non-cell permeant reagent in culture medium at 37°C for 2 h. Afterwards, cross-link buffer (1.5 mM Cu (II)-(o-phenanthroline), 1 mM CaCl , 5 mM Mg2+, 16.7 mM Tris HCl, pH 8.0 and 100 mM NaCl) was added at 37°C for 20 min. After incubation with 10 mM N-ethylmaleimide at 4°C for 15 min to stop the crosslinking reaction, cells were lysed with lysis buffer (containing 50 mM Tris pH 7.4, 150 mM NaCl, 1% NP-40 and 0.5% sodium deoxycholate) at 4°C for 1.5 h. After centrifugation at 12,000 × g for 30 min at 4°C, supernatants were mixed with no DTT loading buffer at 37°C for 10 min before loading the samples. Equal amounts of proteins were resolved by 4-12% SDS-PAGE. Proteins were transferred to nitrocellulose membranes (Millipore). Membrane was imaged on an Odyssey CLx imager (LI-COR Bioscience, Lincoln, NE, USA) at 700 nm and 800 nm.

Statistics and Reproducibility
Statistical analysis was performed on at least three individual data sets and analyzed in GraphPad Prism software version 8. Data are present as mean ± s.e.m from at least three independent experiments, with the number of independent experiments indicated in the figure legend. For dose-response curves, data are analyzed using nonlinear curve fitting for the log (agonist) vs. Response (three parameters) curves. Data are analyzed using the one-way ANOVA with Dunnett’s multiple comparison test or unpaired student t test to determine significance. ****P < 0.0001, ***P < 0.001, **P < 0.01, *P < 0.05, not significant (ns) > 0.05.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript “Functional and structural basis of a negative allostery within GABAB hetero-tetramers” describes the investigation of the structural and functional organization of GABAB receptors, a class C GPCR critically involved in inhibitory neurotransmission and implicated in diverse neurological conditions. While GABAB receptors are known to function as obligatory GB1–GB2 heterodimers, emerging evidence suggests they can also form higher-order oligomers with potential roles in signaling integration and disease. Using subunit-specific nanobodies, the authors provide direct evidence for the existence of GABAB hetero-tetramers in neurons and demonstrate that their function can be selectively disrupted by disease-associated mutations, underscoring their physiological significance. Functional assays reveal distinct pharmacological profiles between heterodimers and tetramers, with agonists showing reduced efficacy in tetramers, while positive allosteric modulators remain effective. Structural determination by cryo-EM resolves the GABAB hetero-tetramer, revealing an asymmetric extracellular domain arrangement that enforces negative allosteric control, preventing simultaneous activation of both heterodimers. The work provides new insights into GPCR oligomerization, with important implications for therapeutic strategies targeting GABAB receptors.\nOverall, I find this study interesting, original and of sufficient conceptual novelty to justify publication in Nature communications. I have a couple of comments that should be addressed during revision:\n1) Detection and identity of GABAB oligomers: The authors use the two GB1-recognizing nanobodies Nb-4C10rFc and Nb-4C10mFc to detect GABAB heterotetramers. However, to my understanding, this nanobody combination should also detect GB1 homodimers. How do the authors ensure that their PLA signals specifically and exclusively stem from GABAB heterotetramers?\nAlong this line, the authors use the two nanobodies Nb-4C10rFc (against GB1) and Nb-5E9mFc (against GB2) to detect GABAB heterodimers. However, this nanobody combination would not be able to distinguish between ‘isolated’ GABAB heterodimers (as the authors claim) and heterodimeric units within a GABAB heterotetramer. A revised manuscript should provide more data to strengthen the authors’ conclusion on which oligomers they actually detect.\n2) Expression levels of heterodimers and heterotetramers: For all pharmacological experiments involving receptor mutants (Figs. 2, 4, and 5; Extended Data Fig. 3), the authors need to control cell surface expression levels of the various heterodimer/heterotetramer receptor assemblies. Without equal expression levels of the various oligomers, direct functional comparisons of potencies and efficacies cannot be precisely determined. In addition, quantifying the ligand effects at the various oligomers and mutants using state-of-the-art efficacy measures such as those derived from the operational model, would be more quantitative and deliver statistically testable parameters for ligand efficacies.\nMinor:\na) Ligand concentrations in Figure legends: In some Figure legends, ligand concentrations are given as x mM, whereas in the text it says x microM.\nb) Figure legend: Extended Data Fig. 1: There is an error in this sentence: “ASA: The ER retention signal RSR in the C-terminal coiled-coil domain of GB1 was mutated to RSR that facilitate the cell surface expression.”\nc) Figure 4d: In the manuscript text it says (lines 264-266): “We found that the maximal Ca2+ release response induced by GABA increased by 30% for GABAB receptor formed with GB1A397N/N399T and GB2 and by 80% for GABAB receptor formed with GB1E414N and GB2, compared to the wild type GABAB receptor”. The data displayed in Figure 4d are the other way around: 30% increase for GB1E414N and 80% increase for GB1A397N/N399T.", "reviewer_2": "Review of “Functional and structural basis of a negative allostery within GABAb hetero-tetramers” by Shen et al.\nThe association of individual molecules of GPCRs with other copies of the same receptor, other membrane resident proteins, or molecules of distinct GPCRs has been an intense area of study for multiple decades. Evidence has continued to mount that GPCR oligomer assemblies behave differently than GPCRs evaluated in unassembled form. Studies of such assemblies are further complicated in the study of class C GPCRs which form constitutive dimers (either homomers or heteromers), which is required for function. The heterodimeric GPCR GABAb consists of GB1 and GB2 building blocks, which play separate roles in the mechanism of activation. To further complicate matters, evidence (including past work from these authors) suggests that GABAb undergoes further assembly to form heterotetramers (dimer of heterodimers); however, such higher order assemblies have proven challenging to fully characterize using more traditional biochemical methods. In this manuscript the authors describe the development of new tools (nanobodies) and the application of new pharmacological (BRET), biochemical, and structural analyses (CryoEM) to dissect GABAb assemblies.\nI am enthusiastic about the work overall. The new data generated in these studies is quite interesting and provocative. Providing strong evidence that GPCRs impart allosteric effects on either other via discrete higher order assemblies would be beneficial for pharmacological studies and drug development. The data presented here offer new angles to understand mechanisms by which GABAb can form heterotetrameric assemblies and how such assemblies might differ from the more conventional heterodimers. These data will be of interest to the broader GPCR pharmacological community. However, several aspects of the experimental design and the assumptions that underly interpretation of these data should be addressed before acceptance for publication.\nMajor Comments:\n*For the proximity ligation assays it is unclear to me how the authors account for the bivalent nature of the nanobody-Fc constructs (such as 4F10-Fc) used for receptor binding. Fc constructs are dimeric (as it seems are the reagents used to detect 4F10-Fc). Using a dimeric binding construct (and a dimeric detection reagent) would seem to be a good way to artificially induce dimerization of the target being studies. The authors should consider whether they could perform a similar assay using monomeric nanobody detection reagents. It would also be good to include a nanobody detection reagent that binds to some other target on the cell surface and show that less PLA signal is observed (when mixed with 4F10-Fc).\n*For this same PLA experiment, how do the authors rule out that any of the signal attributed to tetramerization results from GB1-GB1 homodimerization? Design of a probe to measure this species would help strengthen evidence.\n*For experiments measuring heterodimer and heterotetramer signaling with CODA-RET the authors use LgBit and HiBit tagged receptors to allow measurement of activation (Gi recruitment) only at receptor pairs. This is an interesting experimental design, but it also likely affects the oligomeric propensities of the receptors under study (as shown later when attempting to purify hetero-tetramers). Since HiBit has high affinity for LgBit it is hard to discern whether the complexes formed would apply to endogenous receptors or if this is an artefact of introduction of the complementary tags. Could the authors use SmBit (a lower affinity peptide that binds LgBit) instead of HiBit to reduce the contribution of tag-mediated assembly has on the pharmacological responses observed?\n*When performing BRET assays using CODA-RET the authors report BRET ratios for assessing receptor activation. To make these measurements the authors also must record bulk luminescence values (from LgBit + HiBit), which would report on the total amount of nLuc complex formed in a given cell population. This would seem to be valuable information for understanding how much heterodimer vs heterotetramer is formed under analogous conditions. Could the authors report nLuc luminescence in a meaningful format to provide insight into this topic?\n*It seems intuitive that higher older oligomer assembly (such as tetramerization) would be highly dependent on the level of a given protein at the cell surface. This type of consideration would seem to be particularly important for receptor mutants (like data in Figure 2) which might have altered stability (or expression levels). Can any of the altered behavior of any receptor variants be simply explained by alterations in levels of cell surface protein? This could be measured by flow cytometry staining and would seem to be most important for assessment of pathogenic receptor mutants.\n*It seems possible that the LgBit-HiBit interaction could play a role in dictating the geometry observed in the interaction between the two subunits in the heterotetramer structure. Are there observations that would argue against this? If not, I suggest devising alternative mechanisms for promoting assembly to see if this changes the heterotetramer geometry observed.\n*The observation that transplanting the extended loop found in Drosophila loop 3 into human receptor affects calcium signaling is interesting. It seems like this effect should be tested in more direct measurements of heterotetramerization (PLA or CODA-RET).\n*For the data shown in Figure 5d, the observation that heterotetramer efficacy was decreased by 50% when a GB1 subunit that does not bind ligand is introduced was interesting. I think that performing a similar measurement for heterodimer signaling would also be useful.\n*For the data shown in Figure 6c, it seems there is no negative control where dimerization between two Cys containing constructs is not observed. This control is needed to say whether the assembly mechanism described here is needed for covalent heterotetramer formation (or if simply overexpressing two Cys-containing constructs in the same cell is enough to observe these effects)\n*I did not find sequence listings for any of the receptor construct designs or the nanobodies (and nanobody constructs) identified in this study. This data is essential for others to be able to build on these findings. If there are intellectual property considerations restricting sharing of sequence information, then reference must be made to the patent disclosures so relevant information can be obtained once possible.\nMinor Comments:\n*It looks like the binding experiments to determine nanobody affinities (Extended Fig 1 and Extended Table 1) were only performed once. These should be repeated at least once more to provide error bars on the measurements and give a sense of whether different nanobodies and constructs actually have statistically distinguishable binding.\n*Nanobody binding constants are listed as Kd values, but it seems these numbers were derived from flow cytometry staining experiments. Such values are better described as EC50s (and not Kds).\n*In the caption for Ext Figure 1b the concentration of nanobody is listed as 1 mM. This seems high, perhaps double check?\n*In Extended Data Fig. 1 could the authors define “RSR”?\n*On lines 162-164 the authors describe the GB2KKXX receptor, but it is not clear to me when it is applied (in this portion of the text) or how it functions. Based on Ext Data Fig 1 it looks like wild type hGB1a (used as GB1) has an ER retention signal. How can this be combined with GB2KKXX and result in receptor at the cell surface? I am likely just missing some important details, but it would be helpful of the authors could be more explicit about which GB1/GB2 variants are used in what context.\n*For Figure 1e, could the authors add some additional text to the figure legend more clearly explaining what the bar graphs in the inset represent? Same request for Figure 2c-d.\n*Starting at line 188 the authors begin discussion of experiments using baclofen. It seems that baclofen was not used in Figure 1 experiments. Could the authors add text explaining this choice (and whether they might have missed anything by not using baclofen in Fig 1)?\n*Could the authors comment on why they think they don’t see any signal for Nb-4C10-Bi in the CryoEM structure? Is it even important for inducing heterotetramerization?\n*When assessing the functionality of constructs used for structural studies the authors use a calcium mobilization assay. Could the authors comment on why this wasn’t used on constructs described earlier in the paper? It might be good to do a few spot checks to see if calcium mobilization correlates with the G protein assays described earlier in the manuscript.\n*In lines 291-294 the authors write about whether one or both VFTs can bind to ligand. How was this assessed? By modelling? Some additional context would be helpful.\n*This might be addressed in other forms, but it would be useful to provide exact product numbers for some of the unusual reagents (PlA probes, etc).\n*A few small spelling/grammar suggestions:\nTitle: suggest removing word “a”\nLine 47: “evidences” should be “evidence” and “oligomer” should be “oligomers”\nLine 530 “Thers”—unsure what this is supposed to say", "reviewer_3": "GABAB, as a class C GPCR, is known to function as heterodimers. Whether higher-order oligomers exist and their physiological relevance is not clear. In this manuscript, Shen et al. employed multiple approaches to study the role of GABAB hetero-tetramers in cellular signaling. To do so, they first developed nanobodies that could recognize different subunits (GB1 and GB2, for example). Using the nanobody-based PLA assays, they could detect oligomerizations in both overexpressed HEK cells and isolated neurons. Both hetero-dimers and hetero-tetramers can signal through G proteins but with different potency or efficacy. Some clinically relevant mutations may function via the change of hetero-tetramer stability or formation. A cryo-EM structure of GABAB Hetero-tetramers has been determined and displays different symmetry compared to the hetero-dimer structure. This manuscript provides evidence from different aspects to support that GABAB hetero-tetramers may exist physiologically. The other evidence that these tetramers play important roles in GABAB’s function needs more data.\n1. A few major questions related to the physiological relevance of hetero-tetramers. What is the percentage of GABAB hetero-tetramers vs hetero-dimers in neurons and what determines this ratio? Figure 1b quantified both hetero-dimers and tetramers on cell membranes, do they represent all populations of GABAB in cells or neurons? Is the tetramer formation inducible upon condition changes or receptor activation?\n2. The two nanobodies are useful tools in this study. In Figure 1a & 1b, will the binding of the nanobody affect another binding? If yes, this will affect the quantitation of dimers or tetramers in cells. One experiment that can be done is to measure the binding affinity of Nb5E9 after long incubation of GABAB with Nb-4C10.\n3. Line 162-164: Additionally, we introduced an ER retention signal at the C-terminal end of GB2 (GB2KKXX) to regulate its trafficking to the cell membrane, which occurs only upon interaction with GB1. This sentence and the assay are unclear. GB2KKXX can retain GB2 in the ER membrane, why does interaction with GB1 then help its trafficking to the cell membrane? Particularly, the CODA-RET assay will measure bioluminescence from the cell membrane, ERs, and Golgi.\nLine 173 says 100 μM, in the Figure 1e legend it was 100 mM.\n4. When examining the clinical variants, the assay was specifically designed for measuring dimers or tetramers. Those mutations may still affect signaling. A regular BRET including GB2-Nluc and Venus-miniGi1 can be performed to see if the mutants affect G protein signaling compared to WT.\n5. Another major concern is the use of NanoBit and Nanobody in determining the hetero-tetramer structures. Although they were essential for successful structure determination, they weaken the physiological relevance of the hetero-tetramers. Particularly their sample preparation without NanoBit or Nanobody didn’t allow them to get enough hetero-tetramers, which indicates the hetero-tetramers are a very small population compared to hetero-dimers.\n6. Line 255-269. Here the authors tried to introduce glycosylation sites to prevent dimerization or oligomerization. Why did it not work? Was the presence of glycosylation confirmed by mass spec or other approaches? Glycosylation can significantly increase the size of the proteins by introducing a large sugar chain, which is sufficient to disrupt the interface.\nMinor points\nLine 101 says the HEK293T cells expressing the receptors were injected as antigens? Is this true as I see from the Methods, it was cell membrane extraction.\nIs the VFT of GB2 very different from GB1? So Nb-5E9 only binds to GB2’s VFT?"}, "author_response": "Point-by-point answers to reviewers’ comments\nReviewer #1 (Remarks to the Author):\nThe manuscript “Functional and structural basis of a negative allostery within GABA hetero-tetramers”;\nB\ndescribes the investigation of the structural and functional organization of GABA receptors, a class C GPCR\nB\ncritically involved in inhibitory neurotransmission and implicated in diverse neurological conditions. While\nGABA receptors are known to function as obligatory GB1, GB2 heterodimers, emerging evidence suggests\nB\nthey can also form higher-order oligomers with potential roles in signaling integration and disease. Using\nsubunit-specific nanobodies, the authors provide direct evidence for the existence of GABA hetero-tetramers\nB\nin neurons and demonstrate that their function can be selectively disrupted by disease-associated mutations,\nunderscoring their physiological significance. Functional assays reveal distinct pharmacological profiles\nbetween heterodimers and tetramers, with agonists showing reduced efficacy in tetramers, while\npositive allosteric modulators remain effective. Structural determination by cryo-EM resolves the GABA hetero-\nB\ntetramer, revealing an asymmetric extracellular domain arrangement that enforces negative allosteric control,\npreventing simultaneous activation of both heterodimers. The work provides new insights into GPCR\noligomerization, with important implications for therapeutic strategies targeting GABA receptors.\nB\nOverall, I find this study interesting, original and of sufficient conceptual novelty to justify publication in Nature\ncommunications. I have a couple of comments that should be addressed during revision:\nWe wish to thank the referee for his/her very positive general comment. As detailed below, we did our best to\nclarify all the issues that have been raised.\n1) Detection and identity of GABA oligomers: The authors use the two GB1-recognizing nanobodies Nb-\nB\n4C10rFc and Nb-4C10mFc to detect GABA heterotetramers. However, to my understanding, this nanobody\nB\ncombination should also detect GB1 homodimers. How do the authors ensure that their PLA signals specifically\nand exclusively stem from GABA heterotetramers?\nB\nIt is true that the nanobodies used in the PLA assay allow the detection of GB1 proximity. Accordingly, this\napproach cannot exclude that part of the signal measured can be due to the presence of GB1 homodimers at the\ncell surface. However, such homodimers likely represent a very minor fraction of the signal. Indeed, GB1\ncontains an ER retention sequence that prevents it from reaching the trans-golgi network, thanks to its\nrecognition by the ER gatekeeper PRAF2 (Doly et al., 2015). GB1 surface expression is also controlled at a\nlater step by msec7-ARF acting at a second retention site (a di Leucine motif) within its C-terminal tail\n(Restituito et al., Mol Cell Neurosci 2004). These retention systems are prevented by the GB1-GB2 coiled coil\ninteraction, allowing GB1 to reach the cell surface only when associated with GB2 (Couve et al., JBC 1998;\nMargeta-Mitrovic et al., Neuron 2000). Moreover, in the absence of GB2, GB1 is rapidly degraded, leading to\na very low amount of GB1 subunits (Gassmann et al., J Neurosci 2004), further indicating that GB1 homodimers,\nif any, represents a very small fraction of the GB1 subunits at the cell surface. One could propose a possible\ndissociation of GB1-GB2 heterodimers while at the cell surface, enabling the formation of GB1 homodimers.\nthe coiled coil interaction between their C-terminal intracellular domains (Kammerer et al., Bioch 1999; Calver\net al., J Neurosci 2001). Even the tetramers were shown to be very stable and not capable of exchanging subunits\n(Comps-Agrar et al., FASEB J 2012).\nThe possible existence of GB1 homodimers is now indicated in our manuscript (Page 15, Line 369-383), with\nenough explanation to convince the reader that they very likely represent a very minor proportion of the GABA\nB\nreceptors at the cells surface.\nAlong this line, the authors use the two nanobodies Nb-4C10rFc (against GB1) and Nb-5E9mFc (against GB2)\nto detect GABA heterodimers. However, this nanobody combination would not be able to distinguish between\nB\nGABA heterodimers (as the authors claim) and heterodimeric units within a GABA heterotetramer. A revised\nB B\nmanuscript should provide more data to strengthen the authors’conclusion on which oligomers they actually\ndetect.\nYes, the referee is perfectly right, the nanobodies combination detect any GB1-GB2 heterodimers, whether strict\ndimers, or being part of larger complexes. This is now clearly stated in our manuscript (Page 15, Line 384-397).\nAlthough we could not specifically detect strict GB1-GB2 heterodimers, such a determination is not necessary\nfor our conclusion, what being important is the detection of the proximity between these heterodimers.\n2) Expression levels of heterodimers and heterotetramers: For all pharmacological experiments involving\nreceptor mutants (Figs. 2, 4, and 5; Extended Data Fig. 3), the authors need to control cell surface expression\nlevels of the various heterodimer/heterotetramer receptor assemblies. Without equal expression levels of the\nvarious oligomers, direct functional comparisons of potencies and efficacies cannot be precisely determined.\nWe thank the reviewer for the valuable comments. Indeed, we already systematically measured cell-surface\nexpression levels of the GABA receptor mutants in the cells used for the functional assays shown in Figs. 2, 4,\nB\nand 5; Extended Data Fig. 3. These data are shown below (Figure R1). Note that most receptors are expressed\nat a similar level as the wild type, but a few (E368D and E414N) show a two-fold lower expression level. Such\nlower expression has to be taken into account in interpreting the functional data, but clearly, a two-fold lower\nexpression of the E368D mutant cannot per se explain a 2-log shift, in baclofen potency on the heterodimer\nassay, nor a total loss of function in the tetramer assay. Regarding the disruption of the negative cooperativity\nwithin the tetramer, one mutant (A397N/N399T) displays a similar expression as the WT, and this mutation\nresults in an increase of 80% of the maximal effect. The lower effect observed with the E414N mutant compared\nwith GB1A397N/N399T is likely explained by its 2-fold lower expression level relative to WT. This is now described\nand discussed in our revised manuscript (Page 11, Line 271-273).\nB\nreceptors in Figs. 2, 4, 5 and Extended Data Fig. 5. Data are present as mean ± s.e.m. from at least three\nindependent experiments. Data are analyzed using one-way analysis of variance (ANOVA) with a Dunnett’s\npost-hoc multiple comparison test or unpaired t-test (two-tailed) to determine significance (compared with WT\ngroup). ****P < 0.0001, ***P < 0.001, **P < 0.01, *P < 0.05 and not significant (ns).\nThese data are presented in the new Extended Data Fig. 4c, Extended Data Fig. 5e, Extended Data Fig. 9a,\ne and Extended Data Fig. 11b of the revised manuscript.\nIn addition, quantifying the ligand effects at the various oligomers and mutants using state-of-the-art efficacy\n3\nmeasures such as those derived from the operational model, would be more quantitative and deliver statistically\ntestable parameters for ligand efficacies.\nWe thank the reviewer for the valuable suggestion. We have reanalyzed the data using the estimated TOP values\nof the Prism fits. These data have been updated in the inserted panels in Figure 1, Figure 2, Figure 5, Figure\n1, Extended Data Fig. 5, Extended Data Fig. 12.\nMinor:\na) Ligand concentrations in Figure legends: In some Figure legends, ligand concentrations are given as x mM,\nwhereas in the text it says x microM.\nWe thank the reviewer for pointing it out. We have corrected the mM into μM in the revised manuscript.\nb) Figure legend: Extended Data Fig. 1: There is an error in this sentence: ASA: The ER retention signal RSR\nin the C-terminal coiled-coil domain of GB1 was mutated to RSR that facilitate the cell surface expression.;\nWe thank the reviewer for pointing it out. We have corrected sentence as “The ER retention signal RSR (Arg-\nSer-Arg) at the C-terminal end of the coiled-coil domain of GB1 was mutated to ASA (Ala-Ser-Ala) to prevent\nER retention, allowing cell surface expression of the constructs.”.\nc) Figure 4d: In the manuscript text it says (lines 264-266): We found that the maximal Ca2+ release response\ninduced by GABA increased by 30% for GABA receptor formed with GB1A397N/N399T and GB2 and by\nB\n80% for GABA receptor formed with GB1E414N and GB2, compared to the wild type GABA receptor.\nThe data displayed in Figure 4d are the other way around: 30% increase for GB1E414N and 80% increase for\nGB1A397N/N399T.\nWe have corrected this sentence as follow: “Ca2+ release response induced by GABA increased by 80% for\nGABA receptor formed with GB1A397N/N399T and GB2 and by 30% for GABA receptor formed with GB1E414N\nB B\nand GB2”. Furthermore, we added a sentence (Page 11, Line 271-273) to explain that the lower effect observed\nwith the E414N mutant compared with GB1A397N/N399T is likely related to its lower expression, as indicated in\nour answer to the first point above.\nReviewer #2 (Remarks to the Author):\nReview of “Functional and structural basis of a negative allostery within GABAb hetero-tetramers” by Shen et\nal.\nThe association of individual molecules of GPCRs with other copies of the same receptor, other membrane\nresident proteins, or molecules of distinct GPCRs has been an intense area of study for multiple decades.\nEvidence has continued to mount that GPCR oligomer assemblies behave differently than GPCRs evaluated in\n4\nunassembled form. Studies of such assemblies are further complicated in the study of class C GPCRs which\nform constitutive dimers (either homomers or heteromers), which is required for function. The heterodimeric\nGPCR GABAb consists of GB1 and GB2 building blocks, which play separate roles in the mechanism of\nactivation. To further complicate matters, evidence (including past work from these authors) suggests that\nGABAb undergoes further assembly to form heterotetramers (dimer of heterodimers); however, such higher\norder assemblies have proven challenging to fully characterize using more traditional biochemical methods. In\nthis manuscript the authors describe the development of new tools (nanobodies) and the application of new\npharmacological (BRET), biochemical, and structural analyses (CryoEM) to dissect GABAb assemblies.\nI am enthusiastic about the work overall. The new data generated in these studies is quite interesting and\nprovocative. Providing strong evidence that GPCRs impart allosteric effects on either other via discrete higher\norder assemblies would be beneficial for pharmacological studies and drug development. The data presented\nhere offer new angles to understand mechanisms by which GABAb can form heterotetrameric assemblies and\nhow such assemblies might differ from the more conventional heterodimers. These data will be of interest to\nthe broader GPCR pharmacological community. However, several aspects of the experimental design and the\nassumptions that underly interpretation of these data should be addressed before acceptance for publication.\nWe wish to thank the referee for his/her very positive general comment. As detailed bellow, we did our best to\nsatisfy his/her specific comments.\nMajor Comments:\n1) For the proximity ligation assays it is unclear to me how the authors account for the bivalent nature of the\nnanobody-Fc constructs (such as 4F10-Fc) used for receptor binding. Fc constructs are dimeric (as it seems are\nthe reagents used to detect 4F10-Fc). Using a dimeric binding construct (and a dimeric detection reagent) would\nseem to be a good way to artificially induce dimerization of the target being studies. The authors should consider\nwhether they could perform a similar assay using monomeric nanobody detection reagents. It would also be\ngood to include a nanobody detection reagent that binds to some other target on the cell surface and show that\nless PLA signal is observed (when mixed with 4F10-Fc).\nWe thank the reviewer for this comment. As the cells were fixed with 4% formaldehyde before incubation with\n4F10-Fc followed by PLA detection, the dimeric or tetrameric state should be unaffected by the nanobody-Fc.\nThis have now been explained in our revised manuscript.\nWe thank the referee for proposing another negative control, measuring PLA dots between two cell surface\nreceptors not interacting. For this, we used mGlu2 as we do have high affinity nanobodies specific of this\nreceptor (Scholler et al., Nat Comun 2017; Oosterlaken et al., Nature 2025), and GABA is known not to interact\nB\nwith mGluRs (Rives et al., EMBO J 2009). As shown in Figure R2, the expression of the mGlu2 homodimer\nwas validated by quantifying PLA-dots obtained with the mGlu2 nanobodies, and were found to represent 138%\nthose obtained with the GB1-GB2 nanobodies, suggesting a higher expression level of the mGlu2 homodimers\n5\nthan GABA heterodimers. In contrast, the mGlu2-GB1 number of PLA-dots per µm2 represent about 21% of\nB\nthe values measured with GB1-GB2, offering a good estimate of PLA signals resulting from a random proximity\nbetween two non-interacting cell surface proteins expressed at this level.\nFigure R2. Detection of GABA hetero-tetramer expression. Representative images of PLA experiments\nB\nperformed with Nb-4C10rFc and Nb-5E9mFc (anti-GB1/GB2), or Nb-4C10rFc and Nb-4C10mFc (anti-GB1/GB1),\nor DN1rFc and DN1mFc (anti-mGlu2), or Nb-4C10rFc and DN1mFc (anti-GB1/mGlu2) in HEK293 cells expressing\nindicated proteins. PLA signal is shown in red dots, cell nuclei are stained with 4’,6-diamidino-2-phenylindole\n(DAPI) in blue. Scale bar: 10 µm. Data are representative of three independent experiments performed on\ndifferent cultures. The histograms show mean ± s.e.m. of PLA dot number per region of interest from 37 to 61\ncells. Data are analyzed using one-way analysis of variance (ANOVA) with a Dunnett ’s post-hoc multiple\ncomparison test to determine significance (compared with GB1-mGlu2 group). ****P < 0.0001.\nThese data are presented in the new Extended Data Fig. 2 of the revised manuscript.\n2) For this same PLA experiment, how do the authors rule out that any of the signal attributed to tetramerization\nresults from GB1-GB1 homodimerization? Design of a probe to measure this species would help strengthen\nevidence.\nThe referee is right. This point has also been raised by the first referee. See our answer to his/her first point\nabove. In summary, although we cannot exclude this possibility, a number of previously reported data indicate\na very low amount (if any) of GB1 homodimers at the cell surface. Moreover, we don’t see how one could\ndiscriminate a strict GB1 homodimer, from a dimeric GB1 within a GABA tetramer. This point is now clearly\nB\n6\ndiscussed in our revised manuscript (Page 15, Line 369-397).\n3) For experiments measuring heterodimer and heterotetramer signaling with CODA-RET the authors use LgBit\nand HiBit tagged receptors to allow measurement of activation (Gi recruitment) only at receptor pairs. This is\nan interesting experimental design, but it also likely affects the oligomeric propensities of the receptors under\nstudy (as shown later when attempting to purify hetero-tetramers). Since HiBit has high affinity for LgBit it is\nhard to discern whether the complexes formed would apply to endogenous receptors or if this is an artefact of\nintroduction of the complementary tags. Could the authors use SmBit (a lower affinity peptide that binds LgBit)\ninstead of HiBit to reduce the contribution of tag-mediated assembly has on the pharmacological responses\nobserved?\nThis is indeed an interesting point. Our goal was to get information on the functional properties of the GABA\nB\nreceptor tetramers, versus the heterodimers. When analyzing the heterodimer, as the later is strongly stabilized\nby the coiled coil domain, the high affinity interaction between LgBiT and HiBiT will not change much the\ninteraction between the subunits within these already stable dimers. In that situation the number of tetramers,\ninfluencing the functional assay are kept to their natural level based on the surface density of the GABA\nB\nheterodimers. These can eventually be disrupted as illustrated in our previous studies (Maurel et al., Nat\nMethods 2008; Comps-Agrar et al., EMBO J 2011). For the analysis of the functional properties of the tetramer,\none need to have the highest proportion possible of tetramers in order to have a good signal, mainly generated\nby these complexes, with as less as possible contamination by strict heterodimeric responses. This is the reason\nwhy we choose to use the high affinity component of the NanoBiT system. This allowed us to characterize the\npharmacological and functional properties of the tetramers selectively. This is of course, unrelated to what could\noccur in native cells where a mixture of the strict heterodimers and tetramers likely exists, making then the\nfunctional responses difficult to interpret. We have here to admit that our data are more qualitative than\nquantitative, as the responses measured here in the so called “heterodimer assay” are likely contaminated by\nsome generated by natural tetramers. This is well illustrated by the increase in signaling observed with the\nmutant expected to prevent the interaction between the GB1 VFTs within tetramer (Fig. 4).\n4) When performing BRET assays using CODA-RET the authors report BRET ratios for assessing receptor\nactivation. To make these measurements the authors also must record bulk luminescence values (from LgBit +\nHiBit), which would report on the total amount of nLuc complex formed in a given cell population. This would\nseem to be valuable information for understanding how much heterodimer vs heterotetramer is formed under\nanalogous conditions. Could the authors report nLuc luminescence in a meaningful format to provide insight\ninto this topic?\nWe thank the reviewer for raising this important point. Obviously, these data were recorded for any experiments\nshown in our original manuscript, and are now included in the revised version. As shown in Figure R3,\nthe\nluminescence signal showed no significant difference between GABA WT and mutants.\nB\nB\nof indicated recombinant Nluc in both GABA heterodimers or hetero-tetramers. Data are present as mean ±\nB\ns.e.m. from at least three independent experiments, and were analyzed using one-way analysis of variance\n(ANOVA) with a Dunnett’s post-hoc multiple comparison test or unpaired t-test (two-tailed) to determine\nsignificance (compared with WT group). ****P < 0.0001, **P < 0.01, *P < 0.05 and not significant (ns).\nThese data are presented in the new Extended Data Figure 3d, Extended Data Figure 5f and Extended Data\nFigure 11c of the revised manuscript.\nWe also performed a dedicated experiment in which we compared the nLuc signals obtained using the GB1-\nGB2 constructs (heterodimers), with those obtained using the GB1-GB1 constructs (tetramers). We also\nperformed, in the same cells, an ELISA after cell permeabilization to estimate the total amount of GABA\nB\nreceptors, taking advantage of the HA-tagged GB1 subunits. Under such condition, we measured 5.46 ± 0.17\nluminescence unit per Elisa-signal unit for the heterodimer, and 3.67 ± 0.12 for the tetramer (Table R1).\nAssuming there will be half of the Nluc formed if all heterodimers were assembled into tetramers, the value\nobtained for the tetramers if higher than expected. This can be due to the different constructs used, and the likely\nexistence of some GB1 homodimers in the intracellular compartments. Whatever, these data suggest that the\nHiBiT-LgBiT system, as expected and discussed in this rebuttal, very likely stabilizes the tetramers, increasing\nthe proportion of GABA receptors in a tetrameric form.\nB\nB\ntotal expression. Cells expressing NanoBiT-tagged GABA receptor complexes were analyzed to compare\nB\nluminescence signals (Nluc) between heterodimeric and tetrameric forms. Total receptor expression was\nquantified by ELISA after cell permeabilization using an antibody against the HA-tagged GB1 subunit. The\nrelative Nluc-to-GB1 expression ratios reflect differences in receptor assembly states, distinguishing\nheterodimeric from heterotetrameric forms. Data shown are representative of three independent experiments.\nThese data are presented in the new Extended Table 2 of the revised manuscript.\n5) It seems intuitive that higher older oligomer assembly (such as tetramerization) would be highly dependent\non the level of a given protein at the cell surface. This type of consideration would seem to be particularly\nimportant for receptor mutants (like data in Figure 2) which might have altered stability (or expression levels).\nCan any of the altered behavior of any receptor variants be simply explained by alterations in levels of cell\nsurface protein? This could be measured by flow cytometry staining and would seem to be most important for\nassessment of pathogenic receptor mutants.\nThis point has also been raised by the first referee. See our answer to his/her second point above (Figure R1).\nTo summarize: most mutants show very similar expression level as the WT, but two of them are expressed at a\n2-fold lower level, providing explanation for their peculiar functional response, but in perfect line with our\nconclusion.\n6) It seems possible that the LgBit-HiBit interaction could play a role in dictating the geometry observed in the\ninteraction between the two subunits in the heterotetramer structure. Are there observations that would argue\nagainst this? If not, I suggest devising alternative mechanisms for promoting assembly to see if this changes the\nheterotetramer geometry observed.\nThree of our previous studies support the cryoEM structure observed of the GABA tetramer, and the specific\nB\n9\norganization of the subunits. In a first study (Maurel et al., Nat Meth 2008), we revealed a similar, slightly lower\nFRET signal between GB1 and GB1, to that measured between GB1 and GB2, for the same amount of receptors\nat the cell surface. In contrast, a much lower FRET was observed between GB2 and GB2. Based on these data,\ntaking into account the Ro value of the FRET pair used, we proposed a tetramer assembly with a close contact\nbetween GB1 subunits from two GABA heterodimers, and the GB2 subunits on the side, too distant to generate\nB\nhigh FRET. In a second study, we examined the possibility to cross-link 7TM domains of GB1 with either GB1\nor GB2 after inserting Cys at different positions in the TMs (Xue et al., Nat Commun 2019), in either an inactive\nor active state. The data obtained lead to a model that is close, though more compact to that observed in the\ncryoEM structure of the tetramer. At least, the contact zone between each of the 4 subunits proposed, are in line\nwith those observed in the structure. In the third study (Comps-Agrar et al., EMBO J 2009, confirmed in Stewart\net al., Neuropharmacology 2018), we identified a site in the GB1 VFT as possibly being the interacting site at\nthe level in the GABA tetramer. Indeed, mutations at this site resulted in a decrease in FRET between the GB1\nB\nVFTs, and most importantly, in the negative allosteric control of one heterodimer by the other. This site\ncorresponds perfectly to that identified in the cryoEM structure for one GB1 subunit. We however proposed a\nsymmetric association, while the structure revealed an asymmetric GB1-GB1 association. This later finding\nnicely explains that a single binding site was accessible per tetramer (Stewart et al., 2018)\nAs these studies were all performed without the LgBiT-HiBiT system, this is consistent with this system not\ninfluencing the general organization of the tetramer.\n7) The observation that transplanting the extended loop found in Drosophila loop 3 into human receptor affects\ncalcium signaling is interesting. It seems like this effect should be tested in more direct measurements of\nheterotetramerization (PLA or CODA-RET).\nWe previously reported that steric hindrance at the level of the GB1-VFT interaction between the heterodimers\ndid prevent the negative allostery between the heterodimers (leading to higher signaling efficacy, and increasing\nthe number of accessible binding sites: Stewart et al., Neuropharmacology 2018), but did not fully prevent\ntetramer formation. As discuss in this previous study, we assume the tetramers can still form through interactions\nat the level of the 7TM domains, consistent with what is observed in our cryoEM structure. We cannot exclude\nthat the drosophila specific loop does the same. Whatever, we did examine the effect of this loop on the PLA\nsignals measured between GB1 and GB1, and observed a lower number of dots/µm2 (Figure R4). A similar\nvalue was obtained with the DGB1 constructs in which we added the sushi domains to allow the generation of\nPLA signal with our tools, indicating that the addition of the drosophila loop in the human receptor results in\nthe same PLA signal as that measured with the drosophila receptors. Taken into account the background signal\nmeasured between GB1 and mGlu2, the introduction of the drosophila loop led to a two-fold decrease in the\nPLA signal, indicating a lower proportion of tetramers.\nperformed with Nb-4C10rFc and 4C10mFc (anti-GB1WT/GB1WT), or Nb-4C10rFc and Nb-4C10mFc (anti-\nGB16AA/GB16AA), or Nb-4C10rFc and Nb-4C10mFc (anti-sushiDGB1/sushiDGB1), or Nb-4C10rFc and DN1mFc (anti-\nGB1/mGlu2) in HEK293 cells expressing indicated proteins. PLA signal is shown in red dots, cell nuclei are\nstained with 4′,6-diamidino-2-phenylindole (DAPI) in blue. Scale bar: 10 µm. Data are representative of three\nindependent experiments performed on different cultures. The histograms show mean ± s.e.m. of PLA dot\nnumber per region of interest from 37 to 61 cells. Data are analyzed using one-way analysis of variance\n(ANOVA) with a Dunnett ’s post-hoc multiple comparison test to determine significance (compared with GB1-\n6AA group). ****P < 0.0001.\nThese data are presented in the new Extended Data Figure 9d of the revised manuscript.\n8) For the data shown in Figure 5d, the observation that heterotetramer efficacy was decreased by 50% when a\nGB1 subunit that does not bind ligand is introduced was interesting. I think that performing a similar\nmeasurement for heterodimer signaling would also be useful.\nWe thank the reviewer for this suggestion. We have measured G protein activation in the GABA heterodimer\nB\nwith the mutation of S247A-E466A in the GB1 subunit. As shown in Figure R5, and as expected by the mutation\nof the unique GABA binding site in this heterodimer, this mutant totally lost the ability to be activated by GABA.\nThis is consistent with a previous report (Comps-Agrar, L. et al. EMBO J 2011).\nB\nsubunit. The effect of GABA on the G protein recruitment to GABA heterodimer WT or S247A-E466A\nB\nmutant. Data are presented as mean ± s.e.m. from five independent biological replicates each performed in\ntriplicates.\nThese data are presented in the new Extended Data Figure 11a of the revised manuscript.\n9) For the data shown in Figure 6c, it seems there is no negative control where dimerization between two Cys\ncontaining constructs is not observed. This control is needed to say whether the assembly mechanism described\nhere is needed for covalent heterotetramer formation (or if simply overexpressing two Cys-containing constructs\nin the same cell is enough to observe these effects)\nTo address the concern regarding a negative control in Figure 6c, we also generated four additional mutant\nconstructs, none of these alternative mutants led to crosslinked oligomers (Figure R5). These results\ndemonstrate that crosslinking of heterodimers is not simply driven by the presence of cysteines. Rather, covalent\ncrosslinking occurs specifically due to the spatial proximity of residues (GB1-K5901.38C and GB2-A6174.52C,\nor GB1-D831TM7C and GB2-A6174.52C), supporting the idea that the observed heterotetramer formation reflects\na defined assembly mechanism rather than non-specific interactions resulting from the overexpression of two\ncysteine-containing constructs in the same cell.\ninto cysteine, without (CuP-) or with CuP (CuP+). a, Represent blots of the crosslinking experiment. b,\nPercentage of hetero-tetramer are presented as mean ± s.e.m. from three independent biological replicates, and\nanalyzed using unpaired t-test (two-tailed) to determine significance (compared with CuP-). ****P < 0.0001\nand not significant (ns).\nThese data are presented in the new Extended Data Figure 13 of the revised manuscript.\n10) I did not find sequence listings for any of the receptor construct designs or the nanobodies (and nanobody\nconstructs) identified in this study. This data is essential for others to be able to build on these findings. If there\nare intellectual property considerations restricting sharing of sequence information, then reference must be made\nto the patent disclosures so relevant information can be obtained once possible.\nThe amino acid and nucleic acid sequences encoding NB-4C10 and NB-5E9 have been included in Chinese\npatent CN120024449A (State: disclosure). They will then be accessible to everyone for basic research as soon\nas the patent is published.\nMinor Comments:\na) It looks like the binding experiments to determine nanobody affinities (Extended Fig 1 and Extended Table\n1) were only performed once. These should be repeated at least once more to provide error bars on the\nmeasurements and give a sense of whether different nanobodies and constructs actually have statistically\ndistinguishable binding.\nThere experiments have been performed three times. We have clarified it in the figure legend of Extended Data\nFig. 1 and added n numbers in Extended Table 1.\n13\nb) Nanobody binding constants are listed as Kd values, but it seems these numbers were derived from flow\ncytometry staining experiments. Such values are better described as EC50s (and not Kds).\nOur nanobodies specifically target GB1 or GB2 subunit, demonstrating a strict stoichiometric ratio of 1:1\n(nanobody:receptor). Based on this, we measured the binding affinity using flow cytometry staining\nexperiments. We then measured the mean staining value obtained through the fluorescence signal detected by\nthe flow cytometer, and expressed these values as a function of the concentrations of nanobodies used for the\nstaining. The saturation curves were fitted using GraphPad Prism software by the nonlinear dose-response\nmethod to determine the affinity of the nanobodies, which was represented by the equilibrium dissociation\nconstant (K ) between the nanobody and receptor, using a one-site specific binding equation:\nD\n𝑌 =𝐵 ×𝑋/(𝐾𝐷+𝑋),\n𝑚𝑎𝑥\nwhere X is the concentration of nanobodies, Y is the response to the specific binding, B is the maximum\nmax\nspecific binding in the same units as Y, and KD is the equilibrium dissociation constant in the same units as X.\nSaturation curves obtained were already shown in Extended data Fig. 1.\nc) In the caption for Ext Figure 1b the concentration of nanobody is listed as 1 mM. This seems high, perhaps\ndouble check?\nThank you for pointing this typo, the concentration was indeed 1 μM. This has been corrected in the revised\nmanuscript, and we carefully checked other similar mistakes in the text and figure legends.\nd) In Extended Data Fig. 1 could the authors define RSR?\nRSR is now presented as the ER retention motif, and is further indicated as being the Arg-Ser-Arg sequence. It\nhas been modified in Extended Data Fig. 1 to be more clearly.\ne) On lines 162-164 the authors describe the GB2 receptor, but it is not clear to me when it is applied (in\nKKXX\nthis portion of the text) or how it functions. Based on Ext Data Fig 1 it looks like wild type hGB1a (used as\nGB1) has an ER retention signal. How can this be combined with GB2 and result in receptor at the cell\nKKXX\nsurface? I am likely just missing some important details, but it would be helpful of the authors could be more\nexplicit about which GB1/GB2 variants are used in what context.\nThe following sentence: “Additionally, we introduced an ER retention signal at the C-terminal end of GB2\n(GB2 ) to regulate its trafficking to the cell membrane, which occurs only upon interaction with GB1” has\nKKXX\nbeen replaced by:\n“In order to perfectly control the surface expression of both GB1 and GB2 subunits, an ER retention motif\nKKXX was added at the C-terminal end of the GB2 subunit (see Brock et al., JBC 2007). As such, neither GB1,\n14\nnor GB2 could reach the cell surface alone. With these subunits, the coiled coil interaction between the C\nKKXX\nterminal tails of GB1 and GB2 being able to mask both the natural and introduced ER retention motifs of GB1\nand GB2, respectively, only the GB1-GB2 heterodimers could reach the cell surface.” (Page 7, Line 165-170)\nf) For Figure 1e, could the authors add some additional text to the figure legend more clearly explaining what\nthe bar graphs in the inset represent? Same request for Figure 2c-d.\nWe thank the reviewer for the comment. We have added the description in the Y axis. According to the point #2\nof referee #1, the estimated TOP values have been taken from the prism fits for Figure 2c-d.\ng) Starting at line 188 the authors begin discussion of experiments using baclofen. It seems that baclofen was\nnot used in Figure 1 experiments. Could the authors add text explaining this choice (and whether they might\nhave missed anything by not using baclofen in Fig 1)?\nWe thank the reviewer for pointing this mistake. Indeed, experiments use to generate Fig. 1e were performed\nwith both GABA and baclofen. In the first figure we choose to present the data with GABA, as it is the\nendogenous ligand for this receptor. The data obtained with baclofen were shown in Extended data Fig. 4a, b.\nWe now corrected the main text to mention correctly the ligand used: GABA for Figure 1e, and baclofen for\nExtended Fig 4a, b. We think it was important to analyze the effect of baclofen on the disease-associated\nmutation analyses, as it is an approved drug, allowing us to directly assess how these mutations influence\nresponses to a clinically relevant ligand.\nh) Could the authors comment on why they think they don’t see any signal for Nb-4C10-Bi in the CryoEM\nstructure? Is it even important for inducing heterotetramerization?\nWe thank the referee for pointing out this point, as we should have explained it in our original manuscript. This\nis now clarified in the revised version (Page 10, Line 241-243). Indeed, during the characterization of Nb-4C10,\nwe found it binds to the extracellular domain of GB1. Further investigation revealed that it binds to GB1a but\nnot to GB1b, indicating that the pair of sushi domains unique to GB1a are essential for Nb-4C10 binding. In\nour previous cryo-EM structures of the GABA dimer in different states, published in Cell Research (2020) and\nB\nin Nature (2021), we did not observe density for the sushi domains, indicating that they are highly flexible. We\nthen speculate that the position of Nb-4C10 bound to this flexible domain is very different from particles to\nparticles preventing us from detecting clear density in the position where this nanobody is supposed to be.\nAlthough we haven’t visualized the density for Nb-4C10 in the cryo-EM structure, we have found that\nincorporating a sufficiently long linker to connect two 4C10 molecules, forming Nb-4C10-Bi, allows it to bind\nto two GB1a subunits. This approach aids in the enrichment of heterotetramers during protein purification,\nthereby increasing the yield of the tetrameric form.\ni) When assessing the functionality of constructs used for structural studies the authors use a calcium\n15\nmobilization assay. Could the authors comment on why this wasn’t used on constructs described earlier in the\npaper? It might be good to do a few spot checks to see if calcium mobilization correlates with the G protein\nassays described earlier in the manuscript.\nIn the functional and pharmacological analysis of the WT and mutant GABA receptors in cells, we wanted to\nB\ndiscriminate between the activity of heterodimers and tetramers. This is the reason why we used the BRET\napproach associated with the HiBiT-LgBiT reconstitution approach of the Nluc, as illustrated in Figure 1. In\nFigure 4 we however used a Ca2+ assay (with co-expression of a chimeric Gqi protein) as we wanted to see the\nchange in agonist efficacy resulting from a decreased proportion of tetramers.\nj) In lines 291-294 the authors write about whether one or both VFTs can bind to ligand. How was this assessed?\nBy modelling? Some additional context would be helpful.\nPrevious reports have definitively shown that the VFT binding domain of Class C GPCRs, including that of\nGB1, maintain an open conformation in the apo state (Mao et al., Cell Res 2020 and Hamidreza Shaye., Nature\n2020). Agonist binding induces a closed conformation. To assess the ligand-binding capacity of each VFT\ndomain within our GABA tetramer, we performed structural modeling. Specifically, we individually aligned\nB\nthe closed conformation of the GB1 VFT domain (derived from the GABA dimer bound to baclofen) to either\nB\nthe GB1 or GB1' subunit within our tetrameric structure. These modeling studies revealed that each GB1 VFT\ndomain could independently adopt a closed conformation without steric clashes, suggesting that each GB1\nsubunit in the GABA tetramer possesses the potential to bind ligand. However, when we attempted to\nsimultaneously model two closed GB1 VFT domains onto the two GB1/GB1’ subunits within the tetramer, we\nobserved steric hindrance. This indicates that while both GB1 subunits can potentially bind ligand, only one\nsubunit can undergo VFT domain closure at a given time due to these steric constraints. This is now better\nexplained in our revised manuscript (Page 12, Line 303-312).\nk) This might be addressed in other forms, but it would be useful to provide exact product numbers for some of\nthe unusual reagents (PLA probes, etc).\nWe now provide the number in the revised manuscript. (Sigma, Cat. No. DUO92101).\nl) A few small spelling/grammar suggestions:\nTitle: suggest removing word “a”;\nThe revised title is now: “Functional and structural basis of negative allostery within GABA hetero-tetramers”.\nB\nLine 47: evidences should be evidence, and oligomer should be oligomers;\nThese mistakes have been corrected.\n“Thers” has been replaced by “The”.\nGABA , as a class C GPCR, is known to function as heterodimers. Whether higher-order oligomers exist and\nB\ntheir physiological relevance is not clear. In this manuscript, Shen et al. employed multiple approaches to study\nthe role of GABA hetero-tetramers in cellular signaling. To do so, they first developed nanobodies that could\nB\nrecognize different subunits (GB1 and GB2, for example). Using the nanobody-based PLA assays, they could\ndetect oligomerizations in both overexpressed HEK cells and isolated neurons. Both hetero-dimers and hetero-\ntetramers can signal through G proteins but with different potency or efficacy. Some clinically relevant\nmutations may function via the change of hetero-tetramer stability or formation. A cryo-EM structure of GABA\nB\nHetero-tetramers has been determined and displays different symmetry compared to the hetero-dimer structure.\nThis manuscript provides evidence from different aspects to support that GABA hetero-tetramers may exist\nB\nphysiologically. The other evidence that these tetramers play important roles in GABAB’s function needs more\ndata.\n1. A few major questions related to the physiological relevance of hetero-tetramers. What is the percentage of\nGABA hetero-tetramers vs hetero-dimers in neurons and what determines this ratio? Figure 1b quantified both\nB\nhetero-dimers and tetramers on cell membranes, do they represent all populations of GABA in cells or neurons?\nB\nIs the tetramer formation inducible upon condition changes or receptor activation?\nThe referee raised here an important question to which it is difficult to answer with high precision. When studied\nin transfected cells using fluorescence photobleaching step analysis, GABA receptor tetramers can already be\nB\ndetected, representing 30% of the population, at density as low as 0.15 particules/µm2 (Calebiro et al., PNAS\n2013). When the density is increased, more tetramers, and more larger oligomers were observed, with almost\nno strict dimers detected at densities higher than as 0.4 particules/µm2. When analyzed using inter-subunit FRET,\nwe found that the GB1-GB1 FRET, was directly proportional to the expression level, and representing more\nthan 80% of the signal obtained between GB1 and GB2, for a receptor density between 0.1 and 3.0 pmol/mg of\nproteins (Maurel et al., Nat Meth 2008), then in the range of the endogenous GABA receptor density in the\nB\nbrain (0.5 pmol/mg) (Bishoff et al., J Comp Neurol 1999), or in cultured cortical neurons (1.5 pmol/mg)\n(Comps-Agrar et al., EMBO J 2011). We also previously reported that the GB1-GB1 FRET signal resulting\nfrom tetramer formation is not sensitive to agonists (Maurel et al. Nat Meth 2008). Such data already suggest\nthat GABA oligomers do not represent a minor proportion of receptors in neurons, especially considering the\nB\nreceptor density is high in specific sub-compartments. However, one cannot exclude the possibility that\nscaffolding proteins or other GABA receptor partners may prevent the formation of, or stabilize such tetramers.\nB\nAnother important information is that, at least in transfected cells, GABA heterodimers are not exchangeable\nB\nbetween oligomers (Comps-Agrar et al, FASEB J 2012). Indeed, the data reveal that in the cell plasma\nmembrane the oligomers are quite stable. This suggests that, once formed, they may not be dissociated easily,\nand may in contrast accumulate.\nIn our study, we found that the PLA signal (Dots/ROI) measured between GB1 and GB2 is about twice as big\n18\nas that measured between GB1 and GB1, both in transfected cells and in cultured neurons. According to the\nhigh proximity between heterodimers within a tetramer, we can assume that a single dot will be generated by\ntetramer when using the heterodimer detection tools. Accordingly, the number of dots detected with the GB1-\nGB2 detector, very likely represent the total number of strict heterodimers plus the tetramers. In contrast, the\ndots generated by the GB1-GB1 PLA tools, will only reveal tetramers. Such observations suggest that about\nhalf of the GABA complexes are tetramers, the other half being strict heterodimers. However, more work is\nB\nneeded to validate the linearity of the PLA signal under our condition, as a function of the protein expression,\nto make sure such data can be used as a quantification method. Moreover, the GB1-GB1 PLA signal may also\naccount for some heterodimers in close enough proximity, but not assembled into tetramers, as this is allowed\nby the size of the a nanobody + secondary antibody.\nIn conclusion, although we cannot provide a good estimate of the proportion of tetramers, our and previous data\nsuggest that they do represent a significant fraction of the receptors. The present discussion is rapidly mentioned\nin our revised manuscript in the discussion (Page 15, Line 384-397).\n2. The two nanobodies are useful tools in this study. In Figure 1a & 1b, will the binding of the nanobody affect\nanother binding? If yes, this will affect the quantitation of dimers or tetramers in cells. One experiment that can\nbe done is to measure the binding affinity of Nb5E9 after long incubation of GABA with Nb-4C10.\nB\nWe thank the reviewer for this important point. To address this, we performed competitive binding assays using\nHEK293 cells expressing human GABA receptors. Cells were incubated with 10 μM Alexa Fluor 647-\nB\nconjugated nanobody, followed by increasing concentrations of the corresponding unlabeled nanobody (Figure\nR8). We observed that competition occurred in 2 hours after the addition of the competing nanobody only within\nidentical nanobody pairs (Nb-4C10 competed with Nb-4C10AF647 (Figure R8a), and Nb-5E9 competed with\nNb-5E9AF647 (Figure R8b)), indicating that Nb-4C10 and Nb-5E9 bind independently to distinct, non-\noverlapping epitopes. Therefore, the binding of one nanobody does not interfere with the other, ensuring that\nour dual labeling strategy allows accurate quantification of dimers and tetramers in cells.\nB\noverexpressing human GABA receptor were incubated with 10 μM Alexa Fluor 647-conjugated nanobody,\nB\nfollowed by the addition of increasing concentrations of unlabeled nanobody for 2 h to allow competitive\nbinding. The percentage of positive events was used as the statistical parameter to characterize their competitive\nbinding to the human GABA receptor. Data are presented as mean ± s.e.m. from three independent biological\nB\nreplicates.\nThese data are presented in the new Extended Data Fig. 2a, b of the revised manuscript.\n3. Line 162-164: Additionally, we introduced an ER retention signal at the C-terminal end of GB2 (GB2 )\nKKXX\nto regulate its trafficking to the cell membrane, which occurs only upon interaction with GB1. This sentence\nand the assay are unclear. GB2 can retain GB2 in the ER membrane, why does interaction with GB1 then\nKKXX\nhelp its trafficking to the cell membrane? Particularly, the CODA-RET assay will measure bioluminescence\nfrom the cell membrane, ERs, and Golgi.\nThe use of the quality control system, including the addition of KKXX in the GB1 subunit has been clarified in\nour answer to minor point #e of the referee #2 above.\nIt is true that CODA-RET assay will measure bioluminescence from all the cell compartments. However, as\nGABA is known not to penetrate into the cell, only the cell surface receptors will be activated, and then generate\na BRET signal. Accordingly, the intracellular nLuc will influence the Venus/nLuc signal calculated. However,\nwe expressed our data as the netBRET (BRET signal with agonist minus the basal BRET signal), and then\n20\nalways normalize to a positive control. Accordingly, this should not influence much the data presented.\nLine 173 says 100 μM, in the Figure 1e legend it was 100 mM.\nThe mistake. In the figure legend has been corrected (100 µM).\n4. When examining the clinical variants, the assay was specifically designed for measuring dimers or tetramers.\nThose mutations may still affect signaling. A regular BRET including GB2-Nluc and Venus-miniGi1 can be\nperformed to see if the mutants affect G protein signaling compared to WT.\nWe thank the reviewer for this suggestion.\nTo evaluate the effects of clinical variants on overall G protein signaling, we performed conventional BRET\nusing GB2-Nluc and Venus-miniGi1. The results were consistent with those obtained from NanoBiT dimer\nassays (Fig. 2). GABA-induced G protein coupling was more profoundly reduced in the GABA hetero-\nB\ntetramers carrying the E368D, A397V, or A535T mutations compared with the corresponding heterodimers.\nSimilarly, rac-BHFF showed only slight or no reduction in efficacy at heterodimers for E368D and A397V (38%,\nrespectively) and no effect for A397V or A535T (Figure R7). These findings indicate that these mutations still\nimpact overall receptor signaling, particularly in the tetrameric context.\nFigure R8. a, Schematic representation of the G protein recruitment to human GABA heterodimer by regular\nB\nBRET using GB2-Nluc and Venus-miniGi1. b, c, Effects of GABA (left panel) and rac-BHFF (right panel) on\nG protein recruitment to the GABA heterodimer of WT or indicated mutants (with E368D, A397V, A535T in\nB\nrepresent the estimated TOP values of GABA and rac BHFF on G protein recruitment to GABA heterodimer\nB\nWT or indicated mutants. d, Expression of the indicated GB1 WT or indicated mutants (with E368D, A397V,\nA535T in GB1, respectively) and GB2 receptors. e, Total luminescence of indicated recombinant Nluc in both\nGABA heterodimers or hetero-tetramers. Data are presented as mean ± s.e.m. from at four biological\nB\nindependent experiments each performed in triplicates, and analyzed using one-way ANOVA with a Dunnett’s\npost-hoc multiple comparison test to determine significance (compared with WT). ****P < 0.0001, ***P <\n0.001, **P < 0.01, *P < 0.05 and not significant (ns).\nThese data are presented in the new Extended Data Figure 4e-i of the revised manuscript\n5. Another major concern is the use of NanoBit and Nanobody in determining the hetero-tetramer structures.\nAlthough they were essential for successful structure determination, they weaken the physiological relevance\nof the hetero-tetramers. Particularly their sample preparation without NanoBit or Nanobody didn’t allow them\nto get enough hetero-tetramers, which indicates the hetero-tetramers are a very small population compared to\nhetero-dimers.\nWhen preparing membrane proteins, they are solubilized using a combination of detergents. These were\noptimized to get a maximal extraction of the proteins, but not to ensure the preservation of any membrane\ncomplexes. For example, the preparation of GABA dimers deleted of the coiled-coil domain, easily lead to the\nB\nisolation of isolated subunits. Obviously, this does not mean the GB1-GB2 dimers are not stable in the plasma\nmembrane, even in the absence of the coiled coil. In cryoEM experiments one want to have the vast majority of\nthe particles corresponding to the same protein complex. Indeed, even like this, the complexity of the system is\nsuch that sometimes only 25% of the particles can be used to generate a precise 3D model. Then, if the\ncomplexity is increased with additional GABA receptor stoichiometry, the situation may be too complex to\nB\nsolve a structure. This is why we used two tricks to stabilize the GABA tetramer: i) the LgBiT-HiBiT fused to\nB\nthe C-terminal ends of the GB1 subunits, and also our dimerized nanobody Nb-4C10Bi that bind the sushi\ndomains of both GB1a subunits, and then stabilize the tetramer on the extracellular side. Note that tricks to\nstabilize specific protein complexes are always used to solve them. With the structure of the complex solved,\none has access to important information to test if such a complex exists in real life, through mutations expected\nto affect the complex, as is being done commonly. We think our previous data, as well as those mutations\nreported here, plus the crosslinking experiments based on our solved structure, validate our structural data.\nMoreover, the asymmetric organization of the tetramer provides a clear explanation as why only one binding\nsite is available at a time, as our previous data (Stewart et al., Neuropharmacology 2018).\nAdditional arguments illustrating the absence of effect of the Hi-Bit-LgBit system, and the presence of the\nbivalent nanobodies on the geometry of the GABA tetramer can also be found in our answer to the point #6 of\nB\nthe second referee.\n6. Line 255-269. Here the authors tried to introduce glycosylation sites to prevent dimerization or\n22\noligomerization. Why did it not work? Was the presence of glycosylation confirmed by mass spec or other\napproaches? Glycosylation can significantly increase the size of the proteins by introducing a large sugar chain,\nwhich is sufficient to disrupt the interface.\nWe thank the reviewer for this suggestion. To assess whether the introduced NXS/T mutations successfully\nresulted in glycosylation, we compared the electrophoretic mobility of GB1 carrying these mutations with that\nof wild-type GB1. The NXS/T mutant GB1 exhibited a noticeably higher molecular weight band than wild-type\nGB1, consistent with the addition of sugar moieties (Figure R8). Functionally, introduction of these\nglycosylation sites led to a marked enhancement of GABA receptor activity (Fig. 4d). This effect is due to\nB\nsteric hindrance at tetrameric interaction interfaces introduced by the added sugar chains, which reduces the\nnegative allosteric influence of tetramer formation and thereby restores receptor function. However, we think,\nin agreement with our previous data (Stewart et al., Neuropharmacology 2018) that the interactions at the level\nof the TM domains help maintaining the GABA tetramer assembly, even though the asymmetric organization\nB\nof the GB1 VFTs responsible for the negative coupling is prevented.\nFigure R8. Western blot analysis of the indicated GB1 NXS/T mutants comparison to the wild-type construct.\nMinor points\nLine 101 says the HEK293T cells expressing the receptors were injected as antigens? Is this true as I see from\nthe Methods, it was cell membrane extraction.\nWe used HEK293T cell membrane extraction overexpressing GB1 and GB2 as antigens for llama immunization.\nWe corrected in the revised manuscript.\nIs the VFT of GB2 very different from GB1? So Nb-5E9 only binds to GB2’s VFT?\nThe amino acid sequence identities between the VFT of GB1 and GB2 are 31.4%. Our data shows that NB-5E9\nspecifically target the VFT of GB2, not VFT of GB1 (Extended data Figure 1b).\n23"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The revised version of the manuscript “Functional and structural basis of a negative allostery within GABAB heterotetramers” has improved over its original version. I find the new data, clarifications and new discussions overall convincing.\nThere are two (minor) remaining issues that I feel need to be addressed:\n1) GB1-homodimers: I find the authors’ argumentation overall plausible. Nevertheless, I believe it would strengthen the author’s explanation if they provided some experimental data to back-up their key arguments.\n2) Quantification of ligand efficacies: I maintain that the functional effects of the disease-relevant mutations (e.g. on ligand efficacy) should be quantified using state-of-the-art pharmacological methods. For instance, the operational model yields a parameter, i.e. log(τ/K ) - a surrogate for ligand efficacy, that allows to quantify and statistically test differences in ligand efficacies across oligomers and disease-relevant mutations. Comparing TOP values, as done in the current version of the manuscript, is insufficiently quantitative.", "reviewer_2": "The authors have nicely addressed my questions and comments. I have two minor requests for clarification/follow up:\n*I don't see any mention of the relevant patent describing nanobodies (CN120024449A (State: disclosure)) described in either the 'competing interests' or the nanobody methods section. Perhaps it is included somewhere else, but I cannot find it.\n*For new data shown in Extended Data Fig 2d, do all conditions use HEK293 cells transfected to express both mGluR2 and gabaB? Or are different transfection conditions used for the different analyses? This should be clarified in the figure legend.", "reviewer_3": "The authors have addressed my questions. I recommend the publication of the manuscript."}, "author_response": "Reviewer #1 (Remarks to the Author):\nThe revised version of the manuscript “Functional and structural basis of a negative allostery\nwithin GABAB heterotetramers” has improved over its original version. I find the new data,\nclarifications and new discussions overall convincing.\nWe wish to thank the referee for his/her positive feedback\nThere are two (minor) remaining issues that I feel need to be addressed:\n1) GB1-homodimers: I find the authors’ argumentation overall plausible. Nevertheless, I\nbelieve it would strengthen the author’s explanation if they provided some experimental data\nto back-up their key arguments.\nWe understand that the referee would be better convinced that what we observed with the\nPLA assay using nanobodies targeting the GB1 subunit only, corresponds to GABA\nB\ntetramers, rather than just strict GB1 homodimers. We agree that it would be fantastic if one\ncould find a way to discriminate between these two possible species of GABA complexes.\nB\nHowever, we did not find a way to discriminate strict GB1 homodimers from associated GB1s\nwithin GABA tetramers, as is both cases, two GB1 subunits are associated.\nB\nWe would also like to mention our previous arguments. One could quantify GB1-GB1\ncomplexes in the absence of GB2, such that these would only represent GB1 homodimers.\nHowever, the drastic reduction in GB1 in the absence of GB2, as well illustrated in the GB2\nKO animals (Gassmann et al., J Neurosci 2004), prevents any comparison with the wild-type\nanimals.\nIt may also be possible that GB1-GB2 heterodimers, the formation of which is needed for\nGB1 to be targeted to the cell surface, can dissociate, allowing the isolated GB1 subunits to\nassemble into homodimers. However, such a possibility is very unlikely due to the strong\nassociation between these two subunits brought by the coiled coil interaction between their\nC-terminal intracellular domains (Kammerer et al., Bioch 1999; Calver et al., J Neurosci\n2001). Even the tetramers were shown to be very stable and not capable of exchanging\nsubunits (Comps-Agrar et al., FASEB J 2012).\nThe fact that GB1 is targeted to the cell surface only when associated with GB2 is well\ndocumented, and the molecular partners involved have been identified (see the references in\nour previous rebuttal).\nOur view is that most arguments we used to justify that most GB1-GB1 complexes result\nfrom the formation of GABA tetramers, rather than homodimers, are well supported by\nB\nprevious data, all published. We did not find any additional data we could provide, not yet\nreported in the literature, to further support our view.\nHowever, it may be possible to discriminate between the strict GB1 homodimers and the\nassociated GB1 subunits within the GABA tetramer, as they likely do not interact via the\nB\nsame interface. Indeed, the cryoEM structure of the GB1 strict dimer (Papasergi-Scott et al.,\nNature 2020), reveals an interface identical to that involved in the GB1-GB2 interaction, then,\ntotally different from the GB1-GB1 interface within the tetramer. This is expected as the GB1\ninterface contacting GB2 is already occupied in the tetramer. This is consistent with the data\nobtained in transfected cells where mutations affecting the GB1-GB1 interface in the tetramer\naffects the tetramer function, but not that of the heterodimer, as do the 7TM portion of GB1\nused as a competitor (Maurel et al., 2008; Comps-Agrar et al. 2011, Stewart et al., 2018).\nApplying this knowledge to discriminate native GB1 complexes may then be possible, but out\nof the scope of the present study.\nProbably the best argument we have is our estimate of a high proportion of GABA\nB\nheterodimers being associated into tetramers, even in primary neurons, then more than what\none would expect for strict GB1 homodimers, as based on the published arguments provided\nhere and previously.\nWe are sorry not being able to provide further experimental support of this proposal.\nHowever, all the data reported in the present and previous papers we and other published\nnicely fit and can be explained by the tetramer structure we report here: the association via\nGB1 with GB2 on the side (Maurel et al., Nat Meth 2008; Calebiro et al., PNAS 2013), the\nnegative allostery leading to a single heterodimer within such a complex being able to signal\n(Maurel 2008, Comps-Agrar 2011…), the GB1 interacting interfaces (Comps-Agrar 2011;\nXue et al., Nat Commun 2021), the binding of a single ligand per tetramer (Stewart et al.\n2018), the co-IP experiments (Schwenk et al., Nature 2010), the absence of subunit\nexchange (Comps-Agrar 2012)… such a coherence cannot be just an artifact, as it has to be\nthe result of evolution. This is probably the best argument in favor of the validity of our model.\nTo further clarify this issue, in addition to the specific paragraph added in the discussion in\nthe previous version, we now added:\n- Introduction, when mentioning the GABA receptor is a heterodimer: \"stabilized by a\nB\ncoiled-coil interaction between their intracellular tails (Couve et al., JBC 1998;\nMargeta-Mitrovic et al., Neuron 2000).\" (Page 3, Line 62)\n- Results, in the chapter \"Expression and activation of GABA hetero-tetramers\": \" As\nB\ndiscussed later, GB1 strict homodimers are not expected to represent a large fraction\nof the GB1 subunits at the cell surface due to their stable association with GB2\n(Kammerer et al., Bioch 1999; Calver et al., J Neurosci 2001), and their retention in\nthe ER in the absence of GB2 (Couve et al., JBC 1998; Margeta-Mitrovic et al.,\nNeuron 2000).\" (Page 6, Line 139-142)\n2) Quantification of ligand efficacies: I maintain that the functional effects of the disease-\nrelevant mutations (e.g. on ligand efficacy) should be quantified using state-of-the-art\npharmacological methods. For instance, the operational model yields a parameter, i.e.\nlog(τ/K ) - a surrogate for ligand efficacy, that allows to quantify and statistically test\nA\ndifferences in ligand efficacies across oligomers and disease-relevant mutations. Comparing\nTOP values, as done in the current version of the manuscript, is insufficiently quantitative.\nThe referee is right, the maximal response measured, represented by the TOP values from\nthe fitting done using Prism, is not directly related to the maximal receptor efficacy. The use\nof the operational model can indeed take this into account. Not being so familiar with the\noperational model for our data interpretation, I did work on this model to figure out the best\nparameter to represent receptor efficacy. The τ value being the ratio between the total\nnumber of activatable receptors (Rtot), over the K value, log(τ) appears to be a good\nE\nparameter representing receptor efficacy for constant amounts of receptors. As the K is\nA\nrelated to ligand affinity on the receptor (it is the concentration of ligand leading to 50%\nreceptor occupancy), the ratio τ/K , and it log, did not appear in our hands to reflect ligand\nA\nefficacy, and this was confirmed by our calculations (see below).\nAccordingly, we did calculate the log(τ) for our critical experiments using the heterodimer\nsignaling or the tetramer signaling assays for GABA WT and mutants stimulated by either\nB\nthe agonists GABA and baclofen, as well as using the PAM BHFF.\nAn example is given below:\nThese data illustrate the relationship between log(τ) and the receptor efficacy, assuming all\nreceptors are expressed at the same level, which is not the case for the E368D mutant that\nshows a two-fold lower expression.\nThis is also illustrated by the comparison of the Top and log(τ) values determined, as\nillustrated below for the analysis of the baclofen effect on the WT and GABA receptor\nB\nmutants using the heterodimer assay:\nOverall, the analysis made using log(τ) did not change our conclusions. As such, we decided\nnot to change our main figures, as the inserts showing the means of the TOP values will be\nunderstandable by most non specialists, but we added our log(τ) analyses in the extended\ndata (extended data Fig. 4 and 6) (Page 45, Line 1028-1031 and Page 49, Line 1074-1076).\nIndeed, for an accurate use of the operational model, one would need an analysis of the\nsaturation condition for the signaling assay (as measured using various receptor expression\nlevels, as in our case, the receptors carry the system involved in the signal detection).\nWithout such an analysis, the determination of τ may not be optimal.\nReviewer #2 (Remarks to the Author):\nThe authors have nicely addressed my questions and comments. I have two minor requests\nfor clarification/follow up:\n*I don't see any mention of the relevant patent describing nanobodies (CN120024449A\n(State: disclosure)) described in either the 'competing interests' or the nanobody methods\nsection. Perhaps it is included somewhere else, but I cannot find it.\nWe thank the reviewer for pointing it out. The required statement has now been included in\nthe revised manuscript under the “Competing Interests” section. (Page 30, Line 886-888)\n*For new data shown in Extended Data Fig 2d, do all conditions use HEK293 cells\ntransfected to express both mGluR2 and gabaB? Or are different transfection conditions\nused for the different analyses? This should be clarified in the figure legend.\nWe thank the reviewer for raising this important point. The necessary clarification has now\nbeen added to the legend of Extended Data Fig. 2c in the revised manuscript. (Page 43, Line\n1014)\nReviewer #3 (Remarks to the Author):\nThe authors have addressed my questions. I recommend the publication of the manuscript."}, {"round": 3, "reviewer_comments": {"reviewer_1": "I am convinced by the additional work and clarifications that the authors have incorporated into this revised version of the manuscript. The revisions have substantially again strengthened the paper, and the authors now present a clear, compelling, and well-supported case for their conclusions. The experimental data are interpreted with appropriate rigor, now fully warranting publication in Nature Communications.\nParticularly commendable is the authors’ excellent integration of their findings within the existing literature. This careful and comprehensive contextualization greatly enhances its accessibility to non-specialists seeking to understand GABAB receptor biology.\nOverall, this is a high-quality and mature piece of work, and I congratulate the authors on a thoughtful and thorough revision."}, "author_response": ""}]

Decision letter