The desensitization pathway of GABA A receptors, one subunit at a time

Abstract

GABA A receptors mediate most inhibitory synaptic transmission in the brain of vertebrates. Following GABA binding and fast activation, these receptors undergo a slower desensitiza-tion, the conformational pathway of which remains largely elusive. To explore the mechanism of desensitization, we used concatemeric α1β2γ2 GABA A receptors to selectively introduce gain-of-desensitization mutations one subunit at a time. A library of twenty-six mutant combinations was generated and their bi-exponential macroscopic desensitization rates measured. Introducing mutations at the different subunits shows a strongly asymmetric pattern with a key contribution of the γ2 subunit, and combining mutations results in marked synergistic effects indicating a non-concerted mechanism. Kinetic modelling indeed suggests a pathway where subunits move independently, the desensitization of two subunits being required to occlude the pore. Our work thus hints towards a very diverse and labile con-formational landscape during desensitization, with potential implications in physiology and pharmacology.

Full text

ARTICLE
The desensitization pathway of GABA
A
receptors,
one subunit at a time
Marc Gielen 1,2 ✉, Nathalie Barilone1& Pierre-Jean Corringer1
GABA
A
receptors mediate most inhibitory synaptic transmission in the brain of vertebrates.
Following GABA binding and fast activation, these receptors undergo a slower desensitiza-
tion, the conformational pathway of which remains largely elusive. To explore the mechanism
of desensitization, we used concatemeric α1β2γ2 GABA
A
receptors to selectively introduce
gain-of-desensitization mutations one subunit at a time. A library of twenty-six mutant
combinations was generated and their bi-exponential macroscopic desensitization rates
measured. Introducing mutations at the different subunits shows a strongly asymmetric
pattern with a key contribution of the γ2 subunit, and combining mutations results in marked
synergistic effects indicating a non-concerted mechanism. Kinetic modelling indeed suggests
a pathway where subunits move independently, the desensitization of two subunits being
required to occlude the pore. Our work thus hints towards a very diverse and labile con-
formational landscape during desensitization, with potential implications in physiology and
pharmacology.
https://doi.org/10.1038/s41467-020-19218-6 OPEN
1Channel Receptors Unit, Institut Pasteur, CNRS UMR 3571, 25 rue du Docteur Roux, 75015 Paris, France. 2Sorbonne Université, 21 rue de l’École de
Médecine, 75006 Paris, France. ✉email: marc.gielen@pasteur.fr
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GABA
A
receptors (GABA
A
Rs) are the main inhibitory
synaptic receptors in the forebrain of vertebrates, and are
involved in key physiological and pathological processes
such as memory, epilepsy, anxiety, and sedation. This is well
illustrated by their medical significance, since the most prevalent
GABA
A
Rs are the target of the widely used benzodiazepine class
of drugs1.
GABA
A
Rs belong to the pentameric ligand-gated ion channel
(pLGIC) superfamily, which also comprises the anionic glycine
receptor, as well as the excitatory 5HT
3
serotonin receptors and
the nicotinic acetylcholine receptors (nAChRs)2. Upon agonist
binding, their transmembrane pore quickly opens to enable the
selective flow of permeant ions across the plasma membrane,
thereby affecting cell excitability. However, during sustained
binding of the agonist, most pLGICs will gradually enter a shut-
state refractory to activation, called the desensitized state, thereby
preventing excessive activation3. The exact roles of desensitization
in vivo are still debated, but potentially include the reduction of
responses during high-frequency neurotransmitter release4, the
prolongation of synaptic currents5, as well as the modulation of
extra-synaptic receptors subjected to tonic activation by low
ambient concentrations of neurotransmitters6.
Recent functional and structural studies, mostly performed on
anionic pLGICs, provide compelling evidence for a “dual-gate”
model, in which the transmembrane domain (TMD) of pLGICs
contains both an activation-gate, located in the upper half of the
channel, and a desensitization-gate, located at the intracellular
end of the channel3,7–11. Structural work on homopentameric
receptors always showed symmetrical structures7,9,11, while the
recent structures of the heteromeric GABA
A
receptor show
important asymmetric features within the extracellular domain
(ECD)10, but still a strong pseudo-symmetrical organization of
the TMD. The current view of the dual-gate model thus supports
that resting, active, and desensitized states are essentially sym-
metrical at the level of the TMD, desensitization involving, in the
lower part of the channel, a movement of all subunits to occlude
the permeation pathway. However, desensitization is a multi-
phasic process, since the sustained application of agonist elicits
currents that desensitize with several distinct decay time con-
stants, which are usually portrayed by the existence of “fast”and
“slow”desensitized states (noted D
fast
and D
slow
below, respec-
tively)3,12–15. The structural rearrangements underlying these
distinct desensitization components remain elusive. In particular,
it is currently unknown whether subunits rearrange in a con-
certed manner, with D
fast
and D
slow
reflecting distinct states at the
single-subunit level, or whether individual subunits can rearrange
independently with distinct time courses. The first scheme would
predict that pLGICs only visit pseudo-symmetrical states during
desensitization, while the latter would imply that desensitization
involves asymmetrical states.
To examine the contribution of individual subunits, we herein
introduced gain-of-desensitization mutations in each individual
subunit, both one-by-one and in combinations, and assessed their
interplay during desensitization. We selected mutations nearby
the desensitization-gate, which were previously found to specifi-
cally alter the desensitization kinetics and amplitude, without
significant alteration of the upstream activation process. Since
stereotypical synaptic GABA
A
Rs are composed of two α, two β,
and one γsubunits16,17, targeting a single α-orβ-subunit within
the pentamer is out of reach using classical site-directed muta-
genesis approaches. To circumvent this problem, we used a
concatemeric construct, whereby all five subunits are connected
by polyglutamine linkers. Owing to the fixed organization of
subunits within this concatemer, we could introduce and combine
gain-of-desensitization mutations in a defined manner, ensuring
the perfect homogeneity of the resulting recombinant GABA
A
Rs
populations. We generated a library of 26 combinations of
mutated subunits, recorded their macroscopic desensitization
kinetics, and analyzed the data by Markov-chain kinetics
simulations.
Results
A pentameric concatemer recapitulates the biphasic desensiti-
zation profile of the GABA
A
R reconstituted from loose sub-
units. To force the subunit arrangement, we used a previously
described18 concatemer consisting of β2–α1–β2–α1–γ2 subunits
fused together with 15- to 20-residues long polyglutamine linkers.
When assembled in the counter-clockwise orientation as seen
from the extracellular space, it shows a canonical organization
with two GABA binding sites at the β2–α1 interfaces and one
benzodiazepine site at the α1–γ2 interface (Fig. 1a). In contrast, in
the clockwise orientation, the concatemer would carry a single
GABA binding site and no benzodiazepine-binding site. This
orientation, if it occurs, should therefore yield minimal, if any,
GABA-gated currents and no benzodiazepine-potentiation. We
previously showed that expression of the concatemer in oocytes
yields robust GABA-elicited currents with an apparent affinity for
GABA and a potentiation by benzodiazepines similar to that of
GABA
A
Rs expressed from loose subunits18. This shows that the
counter-clockwise assembly largely dominates the electro-
physiological response. This innocuity towards the pharmacology
of extracellular ligands also suggests that the inter-subunit linkers
leave the ECD conformational dynamics unaffected.
To record desensitization kinetics at the best possible temporal
resolution using Two-electrode voltage clamp (TEVC) recordings
of Xenopus laevis oocytes, we minimized the dead volume of our
set-up and applied a supersaturating GABA concentration (10
mM), thereby optimizing the onset of electrophysiological
responses in the 20–25 ms timescale (20–80% current rise times).
As discussed in a previous publication, TEVC recordings of
Xenopus laevis oocytes are well-suited to the study of desensitiza-
tion of pLGICs owing to the robustness of the approach, which
contrasts with the very high inter- and intracellular variability
when using patch-clamp methods3. Recordings of the wild-type
concatemer show robust currents, with desensitization profiles
indistinguishable from that of conventional α1β2γ2 GABA
A
Rs
assembled from unconnected subunits (Fig. 1b, c; Supplementary
Table 1; see ref. 8), further arguing that the linkers do not affect
the conformational changes at play during desensitization.
Desensitization shows two well-separated components that are
perfectly resolved by our procedure, a fast (τ
fast
=4.8 ± 1.2 s) and
a slow one (τ
slow
=24.4 ± 7.8 s). The amplitude of the former
carries about a third of the total desensitization amplitude,
yielding a weighted desensitization time constant (τ
w
) of about
18 s. After one minute of GABA application, the residual current
accounted for about 10% of the peak current (Fig. 1b, c;
Supplementary Table 1).
Single desensitizing mutations show contrasting phenotypes
depending on their location within the pentamer. For gain-of-
desensitization mutations in α1, β2, and γ2 subunits, we chose the
valine mutation at the 5′position of the third transmembrane
segment (M3), namely α1N307V on α1-subunits (SU2 and SU4),
β2N303V on β2-subunits (SU1 and SU3), and γ2H318V on the
single γ2-subunit (SU5) (Fig. 1d–f)—this prime notation, akin the
one largely used for the M2 segment, starts at the cytoplasmic end
of the M3 segment19. Indeed, we previously showed that these
mutations markedly speed up the desensitization of α1β2γ2
GABA
A
Rs8. We also showed that mutations in this region of the
TMD do not alter significantly the concentration–response curve
of the GABA-elicited peak currents, measured before the onset of
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desensitization. This indicates only a weak effect of the mutations
on the resting-to-active state transition, and a major effect on the
active-to-desensitized state transition.
Mutations were introduced one at a time on the concatemer.
We define CWT as the wild-type concatemer, Cithe concatemer
with a single M3-5′valine mutation on subunit number i, and Cij
the concatemer where subunits iand jare both mutated, up to
C12345 where all subunits are mutated (Fig. 2a).
For the single mutations, C1(SU1 =β2) and C2(SU2 =α1)
display desensitization kinetics similar to that of CWT, while
constructs C3,C
4,andC
5displayed robust gain-of-desensitization
phenotypes (Fig. 2; Supplementary Fig. 1 and Supplementary
Table 1), yielding weighted desensitization rates of 6.2, 3.4, and
3.3 s, respectively, as compared to 18 s for CWT. The three
mutations accelerate fast desensitization by about 2-fold and slow
desensitization by about 3-fold (τ
fast
=2.7, 2.9, and 2.9 s; τ
slow
=
7.1, 7.3, and 7.2 s for C3,C
4, and C5, respectively). C4and C5in
addition increase the relative amplitude of the fast component (%
A
fast
=20.0%, 86.7%, and 86.3% for C3,C
4,andC
5, respectively),
explaining their stronger effect. Of note, the C5construct displays
an identical desensitization phenotype compared to the single
mutant α1β2γ2H318V expressed from unconnected subunits8,
which is consistent with the assumption that our concatemeric
design does not affect the desensitization properties of GABA
A
Rs,
GABAAR α1
GlyR α1
nAChR α7
α4
β2
β2
β
γ2
309
305
320
GluCl
5HT3A
GLIC
M3-20′15′10′5′
′
Extracellular view
γ2
α1
α1
β2
β2
a
Wild-type concatemer
CWT
d
SU1
SU3
SU2
SU4
e
SU5
β2
α1
β2
α1
γ2
GABA
GABA
BDZ
b
Wild-type concatemer
CWT
60 nA
10 s
10 mM GABA c
Ipeak
Ipeak
Ires
Ires
Aslow
Afast
slow
fast
10 mM GABA
%Ires %Afast
==Afast + Aslow
Afast
f
Ext.
Int.
M3−M4
loop
M1−M2
linker
M3-5’
M2
M3
M3−M4
loop
M1
M2
M3
M4
M2
M2
M3 M1
Pore
M3-5’
Transmembrane domain
(top view)
Fig. 1 The wild-type α1β2γ2 pentameric GABA
A
R concatemer. a Schematic top view of the concatemer. The two β2/α1 ECD interfaces (SU1/SU2 and
SU3/SU4) harbor the two GABA-binding sites, while the α1/γ2 ECD interface (SU4/SU5) contains the benzodiazepine-binding site. bRepresentative
TEVC recording of a Xenopus laevis oocyte expressing the wild-type concatemer, CWT.cDepiction of the experimental values used to quantify
desensitization: τ
fast
and τ
slow
are the time constants of fast and slow desensitization components, respectively; %A
fast
is the relative amplitude of the fast
component; %I
res
is the relative residual current after 1 min of 10 mM GABA application. Of note, the weighted desensitization time constant can be defined
as τ
w
=%A
fast
*τ
fast
+(1−%A
fast
)*τ
slow
.dCryo-EM structure of the α1β3γ2 GABA
A
R (pdb 6I5317), as seen from the extracellular space. The β2 and β3
GABA
A
subunits are highly homologous, and both display an asparagine residue at the M3-5′position. Note the central pore, lined by the M2 helices of the
five subunits, forming the transmembrane channel. eSequence alignment of the M3 segment of various pLGIC subunits. All sequences are the mouse
orthologs, except GLIC (Gloeobacter violaceus), as well as the α4 and β2 nAChR subunits (human). The M3-5′residues, mutated in the present study, are
highlighted (gray box; bold characters for GABA
A
subunits). fEnlarged view of the α1β3γ2 GABA
A
R structure highlighting the location of the M3-5′residue
at the M2/M3 transmembrane interface as seen from the side of the channel, facing the M1–M2 linker of the adjacent subunit.
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even in the context of receptors harboring M3-5′mutations. This
is unsurprising, since the linkers are located in the extracellular
part, and cannot interact directly with the M3-5′residues located
at the intracellular end of the pore.
It is noteworthy that the mutations are located at the
cytoplasmic end of the TMD, with the side-chain of the mutated
residue facing the M1–M2 linker of the neighboring subunit
(Fig. 1f). Therefore, C1,C
2,C
3,C
4and C5are mutated at β2-α1,
α1-β2, β2-α1, α1-γ2, and γ2-β2 interfaces, respectively. The
different mutations being introduced at different interfaces, it was
expected that they display different phenotypes. However, the
difference between C1and C3is surprising, since they both
correspond to mutations at the β2-α1 interface, showing virtually
identical microenvironment. This indicates that the effect of the
single mutations not only depends on the nature of the mutated
interface, but also on the particular position of the mutated
subunit within the pentamer.
Combining mutated subunits increases desensitization kinetics
and reveals synergistic effects. To investigate the functional
interaction between mutations at the various interfaces, we built
an extensive library of twenty-six cDNAs including concatemers
comprising two mutations (ten different constructs), three
mutations (six constructs), four mutations (four constructs) or
five mutations (one single construct, C12345), and assessed their
desensitization profile as described above (Fig. 2; Supplementary
Fig. 1 and Supplementary Table 1).
Recordings confirmed the modest effect of SU1 and SU2
mutations, which produce small effects when performed on
concatemers with background mutations at other subunits (0.8 to
1.8-fold decrease in τ
w
for SU1 and 1.1 to 2.8-fold for SU2, among
9 background-mutated concatemers for both). They also confirm
the intermediate effect of SU3 (2 to 6.3-fold decrease in τ
w
among
10 background-mutated concatemers), and the marked effect of
SU4 and SU5 (effect of 5–16-fold among 9 and 10 mutated
b
a
e
c
d
CWT
10 s
C3
C1
10 mM GABA
CWT
10 s
C5
C45
C4
C35
10 mM GABA
C34
CWT
500 ms
C5
C45
C345
C12345
C4
C35
10 mM GABA
C34
β2
α1
β2
α1
γ2
C3
SU3-N303V
β2
α1
β2
α1
γ2
C45
SU4-N307V
SU5-H318V
β2α1
β2
α1
γ2
C12345
SU1-N303V
SU2-N307V
SU3-N303V
SU4-N307V
SU5-H318V
C13
C12
C1
Desensitization time constants
30 ms 300 ms 3 s 30 s
fast
slow
w
1 mutation
2 mutations
3 mutations
4 mutations
5 mutations
C5
C4
C3
C25
C24
C23
C15
C14
C125
C123
C45
C35
C34
C1234
C345
C1245
C1235
C235
C145
C134
C2
CWT
C12345
Fig. 2 Desensitization kinetics of α1β2γ2 concatemers harboring combinations of M3-5′valine mutations. a Schematic top views of the C3(left), C45
(middle) and C12345 (right) concatemers. b–dRepresentative TEVC recording of Xenopus laevis oocytes expressing the indicated concatemers. Note the
change in timescale for recordings in panel (d). ePlot indicating the mean values for fast (red squares), slow (blue squares), and weighted (dark gray
diamonds) desensitization time constants for the indicated concatemers. Error bars are standard deviations. See Supplementary Fig. 1 for individual data
points and Supplementary Table 1 for numerical values, the number of cells, and number of independent series of experiments.
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concatemers for SU4 and SU5, respectively; Supplementary
Fig. 2).
In all cases, combining gain-of-desensitization mutations
together adds up to increase desensitization kinetics. For instance,
the double mutant C45 displays a fast desensitization component
(τ
fast
=180 ms) 26-fold faster than CWT, accounting almost
entirely for the overall desensitization (%A
fast
=98.8%), and a
barely measurable steady-state current (%I
res
=0.8%). Such
phenotype is further strengthened by mutating SU3: C345
desensitizes with an even faster desensitization component in
the 70 ms timescale. Mutating all five subunits gave a slightly
more profound phenotype, with a fast desensitization component
of 40 ms (see construct C12345; Fig. 2d, e; Supplementary Table 1).
Of note, for constructs akin C345 and C12345, the fast component
is so fast that we probably miss a sizeable fraction of the peak
current, thereby overestimating the amplitude of the slow
desensitization component and the measurement of the relative
steady-state current. Also, the steady-state current values and the
amplitudes of the slow desensitization components are barely
measurable for such constructs, rendering the related values (%
I
res
and τ
slow
) unreliable.
To investigate the additivity of the various mutations’effects,
we first compared the effect of individual mutations on the
weighted desensitization kinetics of different concatemers with
background mutations (Supplementary Fig. 2). While this
analysis is crude, the series of double mutants already suggests
some level of inter-subunit coupling. Indeed, while the SU1
mutation barely affects the desensitization of CWT, it increases the
weighted desensitization kinetics of C2by 75%, thereby hinting
towards a coupling between SU1 and SU2. More strikingly, SU4
mutation speeds up desensitization about 5-fold on both CWT,
C1,C
2, and C3backgrounds, while it increases the weighted
desensitization kinetics of C5by 15-fold, clearly hinting towards
synergistic effects of SU4 and SU5 mutations.
Second, we compared the desensitization profiles of C34 and
C35. Since mutating SU4 or SU5 yields identical desensitization
phenotypes (Fig. 2c–e; Supplementary Table 1), C34 and C35
should yield identical phenotypes if the effects of mutations were
additive. Our data contradict such hypothesis, since both
desensitization components of C35 are faster than the ones of
C34, resulting in a 55% faster weighted desensitization rate
(Fig. 2c–e; Supplementary Table 1). Thus, the effects of mutating
the M3-5′residues are non-additive, especially for SU3 and SU4
or SU3 and SU5 subunit combinations.
The conformational pathway of desensitization involves
asymmetrical and non-concerted quaternary motions: imple-
mentation of a general model. The present analysis unravels two
key features governing the desensitization kinetics.
First, the markedly different effects observed upon mutation of
SU1 and SU3, which both involve homologous mutations that are
located in identical micro-environments, show that strongly
asymmetrical motions are involved in the desensitization path-
way. Since SU3 mutation has a strong effect on desensitization,
the structural reorganization at this interface appears to be a
limiting process. In contrast, mutation in SU1 has a very weak
effect, suggesting either a small structural reorganization at this
level, or, more likely, that the structural reorganization would not
be rate limiting (see Discussion).
Second, the marked non-additive nature of the mutations, as
discussed above, is not compatible with a concerted mechanism.
Indeed, in such a scheme, the effect of mutations should directly
translate their impact on the free energy landscape of the
receptor, and should thus be additive.
As an illustration, we attempted to fit the whole set of data with
a concerted model, in which the receptors can only visit a handful
of pseudo-symmetrical conformations that include a fast and a
slow desensitized state (Supplementary Fig. 3a–e). Here and
throughout the manuscript, each model was built as a Markov-
chain kinetic scheme and the whole-cell currents activated by a
supersaturating concentration of GABA were simulated using the
software QUB20 (Supplementary Table 2). However, adjusting the
parameters to correctly fit the desensitization of CWT,C
4, and C5,
did not account for their synergistic effect since the simulated C45
τ
fast
and τ
w
values are respectively 4.7 and 4.1-fold higher than the
values observed experimentally (Supplementary Fig. 3f–g).
To implement the asymmetric and non-concerted properties,
we turned to a radically different scheme in which all subunits
can desensitize independently from the other subunits (Fig. 3). In
this model, each subunit can enter its desensitized conformation
while the other subunits are either in their open or desensitized
conformations. For simplicity, we decided to implement only the
desensitization of SU3, SU4, and SU5, since these subunits are by
General asymmetrical non-concerted model
SU5 desensitization
SU4 desensitization
SU3 desensitization
AR
R
kon.[A]
O
koff
AO AD4
AD5AD45
AD3AD34
AD35 AD345


Fig. 3 General scheme for the simulation of desensitization: an asymmetric non-concerted model. The first part in the kinetic scheme is the binding of
the agonist A to the resting state R, which favors the opening of the channel (AO state) with a gating efficacy E=β/α. Of note, unliganded openings do
exist but are not taken into account for our kinetic modeling as they barely contribute to the electrophysiological response (see main text). We also only
include one binding event, even though α1β2γ2 GABA
A
Rs contain two binding sites whose occupation is required for substantial activation. Upon channel
opening, the receptor can then transit from a fully activated AO state to states where only one subunit enters its desensitized conformation (AD
3
,AD
4
, and
AD
5
). From these states, a second subunit can also desensitize, before the final step leading to the state in which all subunits are desensitized.
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far the main contributors to the phenotypes in the dataset. This
enabled us to reduce the model to ten different states, rather than
thirty-four distinct states involving all subunits. We also
simplified the activation transition whereby the resting receptor
(R state) binds the agonist (AR state) and subsequently open (AO
state). The model thus does not account for unliganded receptors
openings (O state) that rarely occur at wild-type α1β2γ2
GABA
A
Rs, with a spontaneous open probability as low as 10−5
in the absence of agonist21, nor does it include the binding of two
GABA molecules: we only considered the gating equilibrium for
fully occupied receptors, as we work with supersaturating
concentrations of GABA. From the AO state, either SU3, SU4,
or SU5 can desensitize, to produce AD
3
,AD
4
,orAD
5
states,
respectively. From these, the receptor can be further driven into
states where two subunits are desensitized, e.g. desensitization of
SU5 from the AD
4
state leads to the AD
45
state, where both SU4
and SU5 are desensitized. Finally, in that instance, SU3 could also
desensitize to yield the AD
345
state, in which all three subunits are
desensitized.
Using this general model, we progressively tuned the kinetic
and functional parameters to best fit the dataset.
Model I, in which desensitization of a single subunit shuts the
channel, shows anti-synergistic behavior.Wefirst postulated
that the receptor is functionally desensitized, i.e. non-conducting,
as soon as one subunit is desensitized, with only the AO state
allowing the passage of ions (Fig. 4a).
In model I, the desensitization and recovery rates (δ+and δ−)
for each subunit do not depend on the state of the other subunits.
For simplicity, the parameters for SU4 and SU5 are set equal,
since C4and C5display similar phenotypes. Thus, only four
parameters (δ+,δ−,δ
3
+, and δ
3
−) are used to constrain the
desensitization of CWT, i.e. exactly the number of independent
numerical constraints provided by the experimental data (τ
fast
,
τ
slow
,%A
fast
,%I
res
). We also assumed that mutating subunit i
simply increases its desensitization rate by a ratio c
i
+(Fig. 4b).
For each set of parameters, we performed kinetic simulations
using QUB (Fig. 4and Supplementary Table 3). Data are then
analyzed using bi-exponential fitting of each virtual recording. In
every simulation, we included all combinations of SU3, SU4 and
SU5 mutants, from CWT to C345.
In simulation “a”, we set up the parameters to reproduce CWT
and single mutant concatemers (Fig. 4c, d, f and Supplementary
Table 3). However, these parameters largely underestimate the
kinetics of the fast desensitization component for the double
mutant C45: simulation apredicts a value of 1.76 s for the τ
fast
of
C45, i.e. 10-fold slower than the experimental value. In simulation
“b”, we used the same parameters for CWT, and set up the c
i
+
ratios to reproduce the C45 phenotype (Fig. 4c, e, f and
Supplementary Table 3). In that situation, we now largely
overestimate the kinetics of the fast desensitization component
for the single mutants C4and C5: simulation bpredicts a value of
0.34 s for the τ
fast
of both C4and C5, i.e. an order of magnitude
faster than the experimental values. In this particular example, it is
striking that model I actually predicts anti-synergistic effects when
mutating SU4 and SU5, with the fast desensitization kinetics of
both the single and double mutants being similar (Fig. 4f).
Model I is thus incompatible with the dataset, and the reason is
actually straightforward: if one desensitized subunit is enough to
shut the pore, there should be a limiting fast subunit, whose
mutation should have a strong effect on the kinetics of the fast
desensitization component. This is not what we observe
experimentally: the single mutant concatemers with the strongest
phenotypes, C4and C5, only display 40% increases in τ
fast
(see
above).
Model II, in which at least two desensitized subunits are
required to shut the pore, accounts for the synergy between
SU4 and SU5 mutations. We consequently modified the kinetic
model to incorporate a key hypothesis: namely, that functional
desensitization of the channel involves the rearrangement of at
least two subunits, i.e. that AO, AD
3
,AD
4,
and AD
5
do conduct
ions (model II, Fig. 5a).
To simulate responses with steady-state currents consistent
with experimental values, we also allowed mutations to increase
the rates for desensitization recovery of the mutated subunits
(Fig. 5b; Supplementary Table 3). Indeed, not enabling this
increase in recovery rates yields overestimated steady-state
desensitization levels (Supplementary Fig. 4). Using this model
II, we could perfectly account for the fast desensitization rate of
C4,C
5, and C45 (Fig. 5c–e). When SU4 is mutated, SU5
desensitization still provides a limiting step for functional
desensitization, acting as a brake, while in C45 both “brakes”
are relieved, enabling the channel to desensitize with fast kinetics,
thereby generating a synergistic effect. This serves as a gentle
reminder for studies using mutant-cycle analysis: it is indeed
possible to have a strong functional coupling between non-
interacting residues located far apart in a receptor’s structure, if
their motions are not concerted.
While model II accounts for the main features of the dataset,
we further refined it to precisely fit some desensitization kinetics.
Indeed, simulation of C3shows a mono-exponential process with
%A
fast
=100% (Fig. 5d, f), and an overestimated residual current
(Fig. 5g; Supplementary Fig. 5). To circumvent this issue, we
assumed that mutating SU3 increases the desensitization and
recovery rates of SU4 (model II-β; Supplementary Fig. 6). From a
structural point of view, such hypothesis seems plausible: the M3-
5′residue mutated in SU3 is located at the interface with SU4
(Fig. 1a, d–f), potentially interfering with conformational
rearrangements of SU4. Using this model II-β, we could correctly
simulate C3with two components for desensitization, (Supple-
mentary Fig. 7a, c and Supplementary Table 3).
Still, for CWT and C3, model II-βproduces an overestimation
of both the fast component amplitude and the residual current
(Supplementary Fig. 7c, d). Increasing the desensitization
equilibrium constant (δ+/δ−) for SU4 and SU5 would reduce
the amount of residual current, but would also lead to an increase
in %A
fast
further out of the experimental range. Moreover, the
rates of the slow desensitization components and the amplitudes
of the fast components are both underestimated for C4and C5,
as well as for multiple mutant combinations (Supplementary
Fig. 7b, c).
Model III: adding inter-subunit coupling provides the best fit
to experimental data.Wefinally improved the model by adding
a degree of structural coupling between adjacent subunits. We
postulated that desensitization of a particular subunit would favor
desensitization of its neighboring subunits. We thus incorporated
coupling constants between subunit pairs in model III. The best
fit was achieved assuming that, first, desensitization of SU4
decreases the recovery rate of SU5 by ε=10-fold—and vice versa,
and second that desensitization of SU4 increases the desensiti-
zation rate of SU3 by γ=100-fold—and vice versa (Fig. 6a,
Supplementary Table 3). Apart from these couplings, model III
retains all features from model II-β(Fig. 6a, b). Of note, we do
not need to include any effect of SU4 or SU5 mutation on the
recovery from desensitization (i.e. c
4
−=c
5
−=1; Supplementary
Table 3).
As shown in Fig. 7, model III largely accounts for experimental
data, with experimental traces and simulated responses overlaying
well (Fig. 7a–h), including for the wild-type situation. The fast
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a
b
Model I
SU5 desensitization
SU4 desensitization
SU3 desensitization
AR
R
kon.[A]
O
koff
AD3AD34
AO AD4
AD5AD45
AD35 AD345
Wild-type SU3 mutant SU4 mutant SU5 mutant
Desensitization rate δ3+c3+.δ3+δ3+δ3+
Recovery rate δ3–δ3–δ3–δ3–
Desensitization rate δ+δ+c4+.δ+δ+
Recovery rate δ–δ–δ–δ–
Desensitization rate δ+δ+δ+c5+.δ+
Recovery rate δ–δ–δ–δ–
SU3
SU4
SU5
Functionally
desensitized
e
f
c
d
0.03
0.1
0.3
1
3
CWT C4C5C45

fast
(s)
2 s
CWT
10 mM GABA
2 s
C45
10 mM GABA
2 s
C4
10 mM GABA
Experiment
(c4+ = c5+ = 10)
Simulation a
(c4+ = c5+ = 100)
Simulation b


Fig. 4 Model I: only the fully open state is conducting, and subunits move independently during desensitization. a We assume in this model that a
single desensitized subunit is enough to shut the pore of the channel, leading to functional desensitization. Moreover, subunits SU3, SU4, and SU5 can
undergo a desensitization rearrangement independent of the other subunits. Thus, desensitization rates (δ
3
+for SU3, δ+for SU4 and SU5) and recovery
rates (δ
3
−for SU3, δ−for SU4 and SU5) do not depend on the conformation of the neighboring subunits. bEffect of M3-5′valine mutations in Model I.
Mutations are hypothesized to specifically increase the desensitization rates of the mutated subunits, without altering any other parameter. c–e
Representative currents for CWT (panel c), C4(panel d) and C45 (panel e), in black, are compared to the outcome of two distinct simulations. In simulation
a(red), the mutation-induced increase in the desensitization rates of SU4 and SU5 is adjusted so that the simulation of single mutants C4and C5broadly
fits the experimental data, as seen in panel (d). In simulation b(blue), the mutation-induced increase in the desensitization rates of SU4 and SU5 is
adjusted so that the simulation of the double mutant C45 accounts for the experimental data, as seen in panel (e). fBar graph summarizing the
experimental data vs the predicted effects of SU4 and/or SU5 mutations on the kinetics of the fast desensitization component in simulations aand b.
Experimental data are shown as means (bar graphs) and standard deviations (error bars), with individual data points indicated as circles. For panels c–f
note that parameters from simulation afail at describing the data for the double mutant C45, while parameters from simulation blargely overestimate the
effect of single mutants. See Supplementary Table 1 for numerical experimental values, the number of cells and number of independent series of
experiments; and Supplementary Table 3 for the numerical values of parameters.
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a
cd
Experiment Simulation
2 s
CWT
C4
C45
10 mM GABA
CWT
CWT
C3
C3
2 s
10 mM GABA
e
C3
CWT C4C45 C3
CWT C4C45 C3
CWT C4C45
0.03
0.1
0.3
1
3
10 f
0
20
40
60
80
100
%A
fast
(%)
%I
res
(%)
g
0.03
0.1
0.3
1
3
10
Model II
SU5 desensitization
SU4 desensitization
SU3 desensitization
AR
R
kon.[A]
O
koff
AD5
AD3
AO
AD45
AD4AD35 AD345
AD34


Functionally
desensitized
bWild-type SU3 mutant SU4 mutant SU5 mutant
Desensitization rate δ3+c3+.δ3+δ3+δ3+
Recovery rate δ3–c3–
.δ3–δ3–δ3–
Desensitization rate δ+δ+c4+.δ+δ+
Recovery rate δ–δ–c4–
.δ–δ–
Desensitization rate δ+δ+δ+c5+.δ+
Recovery rate δ–δ–δ–c5–
.δ–
SU3
SU4
SU5

fast
(s)
Fig. 5 Model II: Two desensitized subunits are required to occlude the pore. a Model II builds upon Model I by adding one key hypothesis: receptors with
only one subunit in its desensitized conformation are still conducting, and desensitization occurs when at least two subunits are desensitized. Thus, states
AD
3
,AD
4,
and AD
5
are open states from a functional point of view. bIn Model II, mutation of a subunit can affect both its desensitization and recovery, as
shown here with an example in which both SU4 and SU5 are mutated (construct C45): c
4
+and c
5
+reflect the increase in desensitization rates, c
4
−and c
5
−
reflecting the increase in recovery rates. cSimulated currents for CWT,C
4and C45.dRepresentative currents for CWT and C3in black, are compared to
their simulation counterparts in red. e–gBar graphs summarizing the experimental data (in black) vs the simulations (in red) for the indicated concatemers
on the kinetics (panel e) and the amplitude (panel f) of the fast desensitization component as well as the residual current after a 1 min long application of
10 mM GABA (panel g). Experimental data are shown as means (bar graphs) and standard deviations (error bars), with individual data points indicated as
circles. Note that the results for the C5construct are not displayed, since the experimental data are almost identical to that of C4(see Fig. 2) and since the
simulations for C4and C5are identical (see Supplementary Table 3). See Supplementary Fig. 5 for all simulation results; Supplementary Table 1 for
numerical experimental values, the number of cells and number of independent series of experiments; and Supplementary Table 3 for the numerical values
of parameters.
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desensitization kinetics, which are the most reliable experimental
constraints in the dataset, are particularly well simulated (Fig. 7i).
The amplitudes of the fast component are overall in good
agreement with the data, even though they are significantly
underestimated for constructs C5,C
34, and C35 (Fig. 7k), while
slow desensitization rates and steady-state currents are also
underestimated for C45 and C345 (Fig. 7j, l). Those minor
discrepancies might reflect the contribution of SU1 and/or SU2 to
the receptors’desensitization, or even additional effects of the
mutations (see “Discussion”).
Altogether, the whole dataset is consistent with a non-
concerted model for GABA
A
Rs’desensitization, characterized
by three main features: (1) subunits can rearrange one at a time
during desensitization, the multiple temporal components of
desensitization reflecting the existence of intermediate asymme-
trical desensitized states; (2) rearrangements of adjacent subunits
during desensitization are nonetheless partially coupled; and (3)
the desensitization of at least two subunits is required to shut the
pore, i.e. to lead to functional desensitization.
Discussion
To illustrate the main features of our model of wild-type α1β2γ2
GABA
A
Rs desensitization, we show in Fig. 8a the time-
dependence of the various desensitized states’occupancies dur-
ing desensitization. Since SU4 and SU5 desensitize the fastest, the
receptors in the active state will transit first through a pre-
desensitized open-pore state, in which either SU4 or SU5 is
desensitized (Supplementary Fig. 8). Functional desensitization,
i.e. loss of electrophysiological response, subsequently occurs
upon desensitization of the second fast subunit to yield the AD
45
state (Fig. 8a). The final step along the desensitization pathway
would correspond to the desensitization of SU3, resulting in the
slow component of desensitization, i.e. the entry in the AD
345
state (Fig. 8a). Like in all kinetic schemes where the slow- and
fast-desensitized states are connected, this final step slowly
depletes receptors from the fast-desensitized pool, which in turn
displaces the overall population away from active conformations.
We can thus extract the kinetically favored pathway and provide a
schematic depiction of the movements of the M2 helices during
desensitization, as shown in Fig. 8b. Interestingly, the require-
ment for two desensitized subunits to occlude the pore provides a
framework to interpret results at α7 nAChRs, whose desensiti-
zation is blocked by PNU-120596. Indeed, at least four
α7 subunits need to be bound by PNU-120596 in order to block
desensitization, meaning that as soon as two subunits are
unbound, the receptors can undergo functional desensitization22.
We thus suggest that our kinetic scheme may be extended to the
entire pLGIC family.
The whole dataset points to the γ2-subunit as a major deter-
minant of the desensitization of α1β2γ2GABA
A
Rs. Interestingly,
the γ2-TMD appears highly flexible in detergent conditions,
collapsing within the pore when α1β3γ2GABA
A
Rs are solubi-
lized in decylmaltoside neopentylglycol23 or n-dodecyl-β-D-
maltopyranoside24,25. The addition of lipids stabilizes the γ2-
TMD in a more physiologically relevant conformation23,butit
still remains highly mobile and necessitates nanodiscs to be well
resolved17. While the lack of the M3–M4 intracellular loop might
Model III
Functionally
desensitized
AR
R
kon.[A]
O
koff
γ.δ+
γ.δ+
γ.δ3+
γ.δ3+
δ–/ε
δ–/ε
δ–/ε
δ–/ε
AO
AD45
AD4
AD3
AD5
AD35 AD345
AD34


 = SU3−SU4 coupling
 = SU4−SU5 coupling
a
bWild-type SU3 mutant SU4 mutant SU5 mutant
Desensitization rate δ3+c3+.δ3+δ3+δ3+
Recovery rate δ3–c3–
.δ3–δ3–δ3–
Desensitization rate δ+c34+.δ+c4+.δ+δ+
Recovery rate δ–c34–.δ–c4–
.δ–δ–
Desensitization rate δ+δ+δ+c5+.δ+
Recovery rate δ–δ–δ–c5
–.δ–
SU3
SU4
SU5
Fig. 6 Model III introduces inter-subunit coupling during desensitization. a For the wild-type receptors, Model III builds upon Model II by adding some
coupling between adjacent subunits during desensitization. On the one hand, desensitization of SU3 accelerates the desensitization of SU4 by a factor γ,
and reciprocally. On the other hand, desensitization of SU4 slows the recovery of SU5 by a factor ε, and reciprocally. bFor mutated concatemers, Model III
incorporates the additional hypothesis that the mutation of SU3 also affects the desensitization of SU4 by increasing both its desensitization and recovery
rates, by ratios c
34
+and c
34
−, respectively.
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impact the structures solved in detergent, it is tempting to
speculate that the dynamic nature of the γ2-TMD during
desensitization is a functional counterpart of this biochemical
instability. It is also interesting to note that the γ2-subunit
contains a phosphorylation site at a serine located at the intra-
cellular end of M3, namely S32726. This residue is located in an
intracellular cassette modulating the desensitization properties of
inhibitory pLGICs8, eight residues downstream of the M
3
−5′
residues that we have targeted in the current study. One could
thus imagine that phosphorylation of γ2-S327 provides a mean
to modulate the desensitization of γ2-containing GABA
A
Rs. This
would be consistent with a recent study showing that GABA
A
Rs’
desensitization promotes a form of long-term potentiation at
inhibitory synapses by increasing the phosphorylation of γ2-
S32727. Last but not least, the prominent role of the γ2-subunit
in shaping the desensitization of α1β2γ2GABA
A
Rs makes it an
interesting target for pharmacological modulation. Modulating
desensitization should barely affect basic synaptic signaling,
potentially leading to fairly safe compounds with a large ther-
apeutic window. Targeting the γ2-subunit specifically, in a
desensitization locus with divergent sequences among pLGICs
such as the intracellular end of the M3 segment, should also
provide an efficient mean to achieve subtype selectivity. The
current γ-selective pharmacology is embodied by the widely used
class of benzodiazepines; unfortunately, benzodiazepines mod-
ulate GABA
A
Rs likely by affecting a preactivation step, upstream
from the ion channel opening18. They impact the overall con-
formational equilibrium of the ECD, as their binding affects
indiscriminately both GABA binding sites18, while desensitiza-
tion per se most probably remains unchanged. Neurosteroids,
which act at the transmembrane level and likely modulate
desensitization3, would be more promising, although their
binding sites have currently been delineated for αand β
subunits28,29.
i
k
j
l
0.03
0.1
0.3
1
3
10
C3
CWT C4C5C34 C35 C45 C345 C3
CWT C4C5C34 C35 C45 C345
C3
CWT C4C5C34 C35 C45 C345 C3
CWT C4C5C34 C35 C45 C345
1
3
10
30
0
20
40
60
80
100
0.03
0.1
0.3
1
3
10
bcd
efgh
a10 mM GABA
10 s
CWT C4
10 s
C5
10 s
10 mM GABA 10 mM GABA10 mM GABA 10 mM GABA
C3
C34 C45 C345
C35
10 s
10 mM GABA10 mM GABA
2 s
10 mM GABA
2 s 500 ms 500 ms
Simulation
Experiment
%A
fast
(%)

fast
(s)
%I
res
(%)

slow
(s)
Fig. 7 Model III simulations are broadly consistent with experimental data. a–hRepresentative currents for the indicated constructs, in black, are overlaid
with their simulation counterparts in red. Note the changes in timescales. i–lBar graphs summarizing the experimental data (in black) vs the simulations (in
red) for the indicated concatemers on the kinetics of the fast (panel i) and slow (panel j) desensitization components, the relative amplitude of the fast
component (panel k) and the residual current after a 1 min long application of 10 mM GABA (panel l). Experimental data are shown as means (bar graphs)
and standard deviations (error bars), with individual data points indicated as circles. See Supplementary Table 1 for numerical experimental values, the
number of cells and number of independent series of experiments; and Supplementary Table 3 for the numerical values of parameters.
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The apparent lack of effect on desensitization when mutating
SU1 or SU2 alone is another striking feature of the dataset. A first
hypothesis might be that these subunits do not desensitize during
the one-minute-long GABA application. This is unlikely: in that
case, mutating SU1 and/or SU2 should not affect the fast
desensitization of concatemers harboring mutations on other
subunits. However, mutating both subunits leads to an almost 2-
fold increase in the fast desensitization kinetics of C345 (Fig. 2;
Supplementary Table 1). An alternative hypothesis would be that
SU1 and/or SU2 display very-fast desensitization, but with a
desensitization equilibrium largely displaced towards their open
conformation (“δ+/δ−«1”), thereby barely contributing to the
macroscopic course of desensitization. Such desensitization
equilibrium would minimally affect the size of currents, nor the
apparent affinity for the agonist. In that event, it is conceivable
that SU1 and/or SU2 mutationsʼeffects could be revealed on a
mutant background owing to inter-subunit coupling. This
potential impact of inter-subunit coupling involving SU1 or SU2
might also explain why our kinetic simulations slightly differ
from experiments for certain mutants—for example leading to an
increased weight of the fast desensitization component (%A
fast
)of
C34 and C35 as compared with our simulations. Such discrepancy
could also be due to an effect of mutations on the inter-subunit
couplings, with the SU3-SU4 coupling (γ) and the SU4–SU5
coupling (ε) being decreased by the SU3 and SU4 mutations,
respectively. Our dataset unfortunately provides too little con-
straint to build a comprehensive scheme for these hypotheses,
preventing their inclusion in our kinetic model. It is also worth
stressing again that the experimental parameters driven by the
slow component (%I
res
,τ
slow
) are difficult to measure reliably for
strongly desensitizing mutants. In those cases, it is near impos-
sible to fully discard the contribution of endogenous currents, or
even the contribution of a tiny conductance from fully desensi-
tized channels, as suggested for AMPA receptors30. One should
thus be careful when interpreting such measurements—our most
reliable measurements being the τ
fast
values. It is noteworthy that
Fast
desensitization
Slow
desensitization
AD45
0 102030405060
Electrophysiological response
= AO + AD3 + AD4 + AD5
10 mM GABA
Relative state occupancy
AD345
AD34
AD35
Time (s)
0%
a
AR
R
γ2
α1
α1
β2
β2
Functionally desensitizedConducting pore
δ-
δ-
δ-/ε
δ-/ε
Dfast Dslow
b
Fig. 8 States occupancies predictions and structural depiction of Model III. a The overall population of wild-type receptors in an active conformation is
compared to the relative occupancies of the various desensitized states. As depicted by the red box, the early phase of desensitization is carried by the
AD
45
state. On longer timescales (blue box), slow desensitization is largely embodied by the entry in the AD
345
state. The analysis of states occupancies
was performed with QuB simulations. bIn this simplified depiction of model III, we extracted the kinetically favored pathway for the desensitization of wild-
type α1β2γ2 GABA
A
Rs. Upon agonist binding, the receptor is transiently stabilized in a fully open pseudo-symmetrical conformation. The two first subunits
to rearrange during desensitization are the α1 and the γ2 subunits involved in the binding of benzodiazepines, namely SU4 and SU5 in our concatemers.
While one desensitized subunit is not enough to occlude the pore, fast desensitization corresponds to the rearrangement of both SU4 and SU5 subunits,
which are coupled. Slow desensitization is then driven by the slower rearrangement of the SU3 subunit, i.e. the β2 subunit opposite to the γ2 subunit.
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our experimental design allows for a 20-80% rise times in the 20-
25 ms timescale. Therefore, very-fast desensitizing mutants may
already desensitize during the onset of activation, compromising
the accurate measurement of their fast desensitization compo-
nent. Yet, we evaluate that our system allows for an accurate
measurement of τ
fast
down to the ∼25 ms timescale (Supple-
mentary Fig. 9), supporting that τ
fast
has been correctly evaluated
for all constructs used here.
Our non-concerted asymmetrical model provides a clear
departure from a classical view in which D
fast
and D
slow
states are
fundamentally different. It raises the possibility that these states
are identical at the single-subunit level, with D
fast
only reflecting
asymmetrical intermediates, mainly AD
45
, along the desensitiza-
tion process. Such scheme might appear surprising given the
widely accepted concerted nature of pLGICs gating, as described
for the muscle-type nAChR31. However, the analysis and concepts
in favor of a concerted gating of pLGICs, like the MWC model
framed more than half a century ago32, have largely focused on
biochemical and electrophysiological data obtained under gating
equilibrium conditions such as concentration-response
curves21,31. In the case of desensitization, the events are slow
enough that intermediate events are directly detectable, namely
the D
fast
state(s). If one could record the activation kinetics with
sufficient temporal precision, it is likely that proper data fitting
would also require the use of non-concerted asymmetric rear-
rangements. This is actually hinted by the prime model of muscle-
type nAChR activation, in which conformational changes can
affect independently either of the two ACh binding sites33, as well
as by rate-equilibrium free energy relationship analyses arguing
for non-concerted rearrangements of M2-helices during nAChR
activation34. Moreover, molecular dynamics studies also pinpoint
the cytoplasmic end of the pore as a locus for asymmetric con-
formations at the µs-timescale: the five −2′M2-residues are often
distributed in a non-symmetrical fashion during simulations of
the open state of the zebrafish α1 Glycine receptor35,36. Of note,
channels and receptors from other families are also known to rely
on asymmetric gating. This is the case of the prokaryotic mag-
nesium channel CorA, whose active state actually stems from an
asymmetric conformation as reported by cryo-electron micro-
scopy37. This is also the case for NMDA receptors, for which the
cryo-electron microscopy of tri-heteromeric GluN1/GluN2A/
GluN2B receptors reveals an asymmetric organization38.
The exact structural underpinnings of desensitization remain
however ill-defined, in particular since the current structures have
been obtained for presumable resting and desensitized con-
formations so far10,17. In the absence of an active conformation,
one can only speculate on the precise molecular events occurring
during the active to desensitized transition.
Methods
Molecular biology.TheGABA
A
concatemeric α1β2γ2 construct was previously
described18, based on the concatenation of mouse GABA
A
subunits. Briefly, the five
subunits were subcloned in the order β2–α1–β2–α1–γ2 into a low copy number
vector pRK5, retaining the peptide signal of the first subunit only. We used the short
splice variant of the γ2 subunit, γ2S. All five subunits are flanked by unique restriction
sites to allow the subcloning of mutated subunits, and separated by 15–20 residues
long polyglutamine linkers, depending on the length of the C-terminus end of the
subunit preceding the linker. The construct thus shows the arrangement ClaI-β2-
20Q-AgeI-α1-15G-SalI-β2-20Q-NheI-α1-15Q-γ2S-Stop-HindIII. Site-directed muta-
genesis was performed on individual subunits as previously described8. Owing to the
unique restriction sites, mutated subunits were then sequentially subcloned in the
concatemer to yield the desired combinations of mutated subunits. We finally
sequenced the resulting mutated concatemers to check for the incorporation of the
desired mutated subunits. We could not use primers annealing anywhere in α1orβ2
for sequencing, as both subunits are present as duplicates in the concatemer. Instead,
we sequenced SU1-4 subunits with primers annealing at their 5′DNA extremity,
centered on the sequence of the unique restriction site preceding the following sub-
unit. Such reverse primers enable the sequencing of the 5′end of the subunits’DNA,
coding for their C-terminus once translated.
Expressing GABA
A
Rs in Xenopus laevis oocytes. Ovaries from Xenopus laevis
were obtained from CRB Xenopes in Rennes. Free oocytes were obtained by
incubating segments of ovary in collagenase type 1 (Sigma) dissolved in a Ca2+-free
OR2 solution, which contained (mM): 85 NaCl, 5 HEPES, 1 MgCl
2
, pH adjusted to
7.6 with KOH. After 2-4 h exposure to collagenase I, defolliculated oocytes were
washed several times with OR2, and thereafter maintained in a Barth’s solution
containing (mM): 88 NaCl, 1 KCl, 0.33 Ca(NO
3
)
2
, 0.41 CaCl
2
, 0.82 MgSO
4
, 2.4
NaHCO
3
, 10 HEPES, pH adjusted to 7.6 with NaOH. Single oocytes were injected
with 27.6 nl of concatemeric GABA
A
R cDNAs (nuclear injection) at a concentra-
tion of 30 ng/µl. Oocytes were incubated at 17 °C in Barth’s solution devoid of
serum or antibiotics.
Two-electrode voltage clamp recording. Oocytes expressing pentameric con-
catemers were recorded 2-4 days after injection. They were superfused with a
solution containing (mM): 100 NaCl, 2 KCl, 2 CaCl
2
, 1 MgCl
2
, 5 HEPES, pH
adjusted to 7.4 with NaOH. Solution flowed at an approximate speed of 12 mL/
min. Currents were recorded using a Warner OC-725C amplifier, a Digidata 1550
A interface and pCLAMP 10 (Molecular Devices). Currents were digitized at 500
Hz and filtered at 100 Hz (30 –60 Hz used for display purposes). Oocytes were
voltage-clamped at −60 mV and experiments conducted at room temperature.
Desensitizing currents were indu ced by 1 min applications of 10 mM GABA.
20–80% current rise times of 20–25 ms were achieved for CWT.
Data analysis. The extent of desensitization was determined as (1−I
res
/I
peak
),
where I
peak
is the peak current and I
res
the residual current remaining at the end of
the agonist application. Weighted decay time constants for desensitization were
determined by fitting the desensitizing phase with two exponential components
(pCLAMP 10.6.0.13), as given by the following equation: τ
w
=%A
fast
*τ
fast
+
(1−%A
fast
)*τ
slow
. All data values are means ± standard deviation.
Drugs and chemicals. All compounds were purchased from Sigma. GABA was
prepared as a 1 M stock solution in recording solution. Aliquots were stored at
−20 °C.
Kinetic modeling. We used QUB20 (QUB Express 1.12.6 and QUB online) to build
Markov-chain kinetic models. Each simulation contained 10,000–30,000 channels.
The binding and gating rate constants are broadly consistent with previously
published values for GABA
A
Rs39. Except for Supplementary Fig. 9, the simulation
protocol consisted in a step application of 10 mM GABA (instantaneous con-
centration change). For each model, we performed iterative rounds of kinetic
simulations by adjusting manually the set of parameters. Binding and gating
constants being fixed, Model I (Fig. 4), Model II (Fig. 5), Model II-β(Supple-
mentary Fig. 6), and the concerted model (Supplementary Fig. 3) only contain four
parameters for the wild-type receptors (δ+,δ−,δ
3
+, and δ
3
−for Models I, II and
II-β; fast and slow desensitization rates and their recovery counterparts for the
concerted model). This equates to the number of independent experimental
measurements related to the two desensitization components (τ
fast
,τ
slow
,%A
fast
,%
I
res
). We could thus be confident that, once we have a set of parameters accounting
for the wild-type data, the model has a good predictive value. We used ballpark
figures to build the initial set of parameters, already having in mind that the fast
desensitization component might be mostly carried by subunits 4 and 5 (due to the
C45 phenotype). For example, taking into account only the two pathways linking
the AO state to the AD
45
state in Model I, the fast desensitization kinetics could be
approximated with τ
fast
∼2.(δ++δ−), while the amplitude of the fast component
would yield estimates for the ratio D =δ+/δ−approximated with the equation
A
fast
/I
peak
∼2.D, resulting in a D value approximated by ∼0.2, as well as δ+
and δ−values of ∼0.2 s−1and 1 s−1, respectively. In Model II, τ
fast
is in the order
2.(δ+/δ−).δ+, while the ratio D is constrained by the fast component amplitude
(A
fast
) with the following approximation: A
fast
/I
peak
∼D2/(1 +2.D). Such
approximation yields D∼0.9 and δ+∼0.14 s−1. Mutation-induced changes in
those parameters (c
3
+,c
3
−,c
4
+,c
4
−,c
5
+,c
5
−) for models Models I, II were then
adjusted manually to account for the effects of individual mutants (C3,C
4, and C5),
Model II-βrequiring the additional adjustment of c
34
+,c
34
−for the effect of SU3
mutation. The effects of mutations in the concerted model (Supplementary Fig. 3)
led to four mutation-related parameters (γ
f
,ε
f
,γ
s,
and ε
s
) for each individual
mutant C3,C
4, and C5. In all cases, mutation-related parameters derived from
individual mutants were then combined to predict the effect of combining and
mutations in constructs C34,C
35,C
45, and C345. The quality of the fit was merely
assessed by visual inspection of the bar graphs illustrating the predictions for τ
fast
,
τ
slow
,%A
fast
, and I
res
. It may thus be possible to obtain better fits to the data. For
Model III, we generated a series of wild-type models with values for coupling
constants (γand ε) in the 1–1000 range (1, 10, 100, and 1000). We next manually
adjusted the mutation-induced changes as described above for Model II-β.
Statistics and reproducibility. As an internal quality control, for each batch of
Xenopus laevis oocytes used to express mutant concatemers, we recorded some
oocytes expressing the wild-ype concatemers, thereby ensuring we could replicate
recordings consistent with overall data for wild-type concatemers. For each con-
struct, we performed at least 2 series of independent experiments (oocytes obtained
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-19218-6
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Content courtesy of Springer Nature, terms of use apply. Rights reserved

from ovaries of two different animals), and recorded at least 2 cells for each series
of recordings, yielding a total of at least 4 cells. See Supplementary Table 1 for the
exact number of cells and animals used for each construct. All attempts were
successful, i.e. each series of Xenopus oocytes DNA injection yielded experimental
data used in the present work.
Reporting summary. Further information on research design is available in the Nature
Research Reporting Summary linked to this article.
Data availability
Data supporting the findings of this manuscript are available from the corresponding
author upon reasonable request. A reporting summary for this Article is available as a
Supplementary Information file. Source data are provided with this paper.
Received: 4 June 2020; Accepted: 17 September 2020;
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Acknowledgements
The authors would like to thank Drs Thomas Boulin, Hugues Nury, Laurie Peverini,
Marie Prevost and Prof Trevor Smart for critical reading of the manuscript; and
acknowledge financial support by the Fondation de la Recherche Médicale (grant
“Équipe FRM”DEQ20140329497 to P.-J.C.) and the European Commission Research
Executive Agency (Marie Sklodowska-Curie Action, Individual Fellowship 659371 to
M.G.; ERC Advanced Grant GA788974 Dynacotine to P.-J.C.). M.G. is grateful to the
Fondation Bettencourt Schueller for their support.
Author contributions
M.G. designed the study; M.G. and N.B. performed molecular biology and TEVC
recordings; M.G. analyzed the data and performed the kinetic modeling; all authors
discussed results; M.G. and P.-J.C. wrote the manuscript; P.-J.C. and M.G. acquired
funding.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https://doi.org/10.1038/s41467-
020-19218-6.
Correspondence and requests for materials should be addressed to M.G.
Peer review information Nature Communications thanks Sudha Chakrapani and Ryan
Hibbs for their contributions to the peer review of this work. Peer review reports are
available.
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