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The Journal of Neuroscience, January 1, 1998, 18(1):119-127
Activation Kinetics of AMPA Receptor Channels Reveal the Number
of Functional Agonist Binding Sites
John D.
Clements1, 2,
Anne
Feltz1, 3,
Yoshinori
Sahara1, 4, and
Gary L.
Westbrook1
1 Vollum Institute, Oregon Health Sciences University,
Portland, Oregon 97201, 2 John Curtin School of Medical
Research, Australian National University, Canberra, New South Wales ACT
0200, Australia, 3 Laboratoire de Neurobiologie Cellulaire,
Centre National de la Recherche Scientifique, 67084 Strasbourg, France,
and 4 Department of Physiology, Faculty of Dentistry, Tokyo
Medical and Dental University, Tokyo 113, Japan
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ABSTRACT |
AMPA and NMDA receptor channels are closely related molecules, yet
they respond to glutamate with distinct kinetics, attributable to
differences in ligand binding and channel gating steps (for review, see
Edmonds et al., 1995 ). We used two complementary approaches to
investigate the number of functional binding sites on AMPA channels on
outside-out patches from cultured hippocampal neurons. The activation
kinetics of agonist binding were measured during rapid steps into low
concentrations of selective AMPA receptor agonists and during steps
from a competitive AMPA receptor antagonist, 6-cyano-7-nitro-quinoxaline-2,3-dione, into a saturating concentration of agonist. Both approaches revealed sigmoidal kinetics, which suggests
that multiple agonist binding steps or antagonist unbinding steps are
needed for channel activation. A kinetic model with two independent
binding sites gave a better fit to the activation phase than models
with one or three independent sites. A more refined analysis
incorporating cooperative interaction between the two binding sites
significantly improved the fits to the responses. The affinity of the
first binding step was two to three times higher than the second step.
These results demonstrate that binding of two agonist molecules are
needed to activate AMPA receptors, but the two binding sites are not
identical and independent. Because NMDA receptors require four ligand
molecules for activation (two glycine and two glutamate; Benveniste and
Mayer, 1991; Clements and Westbrook, 1991), it may be that some binding
sites on AMPA receptors are functionally silent.
Key words:
glutamate receptors; AMPA receptors; cyclothiazide; hippocampus; ion channels; patch clamp
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INTRODUCTION |
At most central excitatory synapses,
release of glutamate activates AMPA and NMDA channels that are
colocalized at postsynaptic sites (Bekkers and Stevens, 1989). These
multisubunit receptors share significant structural homology
(Nakanishi, 1992; Wisden and Seeburg, 1993; Hollmann and Heinemann,
1994). The colocalized receptors are presumably exposed to the same
concentration and duration of free transmitter (Clements, 1996). Yet
their kinetics, channel properties, and their role in synaptic
transmission are quite distinct. NMDA receptors have slow kinetics
(McBain and Mayer, 1994), whereas AMPA currents peak within a few
hundred microseconds and decay in a few milliseconds (Colquhoun et al., 1992; Hestrin, 1992; Silver et al., 1992). These differences in receptor kinetics reflect both the transmitter binding steps and the
channel gating steps of the channel activation process. For example
NMDA receptors have a much higher affinity for L-glutamate than AMPA receptors (Patneau and Mayer, 1990), and the high affinity accounts in part for the longer duration of the NMDA receptor-mediated excitatory postsynaptic current (Lester and Jahr, 1992).
Kinetic studies of the AMPA receptor have focused on desensitization
and agonist dissociation as factors in the decay phase of the response
(Vyklicky et al., 1991; Colquhoun et al., 1992; Jonas and Sakmann,
1992; Trussell et al., 1993). The agonist binding steps have generally
been examined under the steady-state conditions of classical
pharmacological analysis, but such studies are contaminated by receptor
desensitization. The analysis of receptor activation kinetics for
native receptors can provide insights into the number of binding steps
necessary to activate the channel, the cooperativity of agonist
binding, as well as the stoichiometry and subunit interactions for NMDA
and AMPA receptors. The ligand binding site on glutamate channels is
homologous to the bacterial periplasmic binding proteins with the N
terminus and M3-4 loop contributing to two lobes of the binding pocket
(O'Hara et al., 1993; Kuryatov et al., 1994; Stern-Bach et al., 1994;
Bennett and Dingledine, 1995; Laube et al., 1997). This receptor model
suggests that each subunit may contain a ligand binding site. A model
with more than two ligand binding sites on glutamate receptor channels
is supported by activation kinetics of NMDA receptors that suggest
binding of four molecules (two glutamates and two glycines) is
necessary to open the channel (Benveniste and Mayer, 1991; Clements and
Westbrook, 1991). Because AMPA receptors do not require a coagonist,
one possibility is that four or five glutamate molecules can bind to
the receptor; in fact a model with three binding sites has been
proposed (Raman and Trussell, 1992).
We investigated the number of binding steps required for native AMPA
receptor activation using rapid application methods on outside-out
patches from cultured hippocampal neurons. Pre-equilibration with
cyclothiazide (CTZ) was used to block AMPA receptor desensitization selectively (Patneau et al., 1993; Yamada and Tang, 1993). AMPA receptor activation was recorded after a step into agonist at a
concentration at which agonist binding was rate-limiting or after a
step from a saturating concentration of antagonist into a high
concentration of agonist at which antagonist unbinding was
rate-limiting. Ensemble average currents were fitted with kinetic
models incorporating one, two, or three independent binding sites as
well as models with two unequal or cooperative binding sites. Our
results suggest that two molecules of agonist are necessary and
sufficient for AMPA receptor activation, and that the binding steps may
show negative cooperativity.
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MATERIALS AND METHODS |
Cell culture. Hippocampal neurons dissociated from
neonatal Sprague Dawley rats were cultured on a glial feeder layer as
described previously (Legendre and Westbrook, 1990). Growth medium
contained 5% horse serum, 95% minimal essential medium (MEM; Life
Technologies, Gaithersburg, MD), and a supplement including insulin,
transferrin, selenium, triiodothyronine, progesterone, and
corticosterone. Experiments were performed 3-5 d after plating
(density, 5-20 × 103/cm2).
Drug delivery. During experiments, the neurons were
continuously perfused with a bath solution containing (in
mM): NaCl, 170; KCl, 2.5; HEPES, 10; glucose, 10;
CaCl2, 2; and MgCl2, 1; pH was adjusted to 7.3 with NaOH, and osmolarity was adjusted to 325 mOsm. Two
internal solutions were used for recording and contained (in
mM): CsCl, 150; HEPES, 10; EGTA, 10;
CaCl2, 1; MgCl2, 5; and Na-ATP, 5 or alternatively potassium gluconate, 130; HEPES, 10; Cs4-BAPTA, 10; Mg-ATP, 5; and MgCl2, 2. For both solutions, the pH was adjusted to 7.3 by CsOH (or KOH), and
osmolarity was adjusted to 310-320 mOsm. The external control solution
was the same as the bath perfusing solution, except that glucose was
omitted, and the following were added (in µM):
tetrodotoxin, 0.5; picrotoxin, 100; strychnine, 2;
DL-2-amino-5-phosphonovaleric acid (DL-AP5), 100; and 7-chlorokynurenic acid, 1, to inhibit Na channels,
 -aminobutyric acid/glycine receptor channels, and NMDA receptor
channels, respectively. Agonists were prepared as stock solutions and
added at the indicated final concentration. All solutions were filtered
(0.22 µm) before use.
For outside-out patch recording, drugs were delivered by a gravity-fed,
four-pore (four-square pattern) Pyrex tube (Vitrodynamics, Mountain
Lakes, NJ) with a tip diameter of 80 µm. For drug application, excised patches were brought into the flow of the control solution and
then switched to the drug-containing solution by moving the delivery
tube with a piezoelectric bimorph (Vernitron, Bedford, OH) or a piezo
stack translator (P245.30; Physik Instrument, Waldbronn, Germany).
Solution exchange rate was estimated at the end of each patch recording
using changes in tip potential induced by a 2% dilution of the drug
solution. The solution exchange time constant was 200-400 µsec.
Stock solutions were prepared as indicated (stock concentration,
solvent): CTZ (10 mM, DMSO), 7-chlorokynurenate (500 µM, alcohol), DL-AP5 (300 mM,
H2O), 6-cyano-7-nitro-quinoxaline-2,3-dione (CNQX, 40 mM, DMSO), domoate (10 or 100 mM,
H2O), kainate (10 mM, H2O),
L-glutamate (100 mM, H2O), and
quisqualate (10 mM, H2O). CTZ was generously
provided by Lilly Research Laboratories (Indianapolis, IN). Other drugs
were either purchased from Tocris Neuramin (Bristol, UK) or Cambridge
Research Biochemicals (Northwich, UK).
Data acquisition. Patch currents were recorded using an
Axopatch 1C amplifier (Axon Instruments, Foster City, CA). Pipettes for
recording from excised outside-out patches were made of borosilicate glass and pulled in two steps. Inner tip diameter after fire polishing was 2-3 µm. Data were low-pass-filtered at 2 kHz, digitally sampled at 4-8 kHz using pClamp (Axon Instruments), and analyzed on a Macintosh computer using AxoGraph (Axon Instruments). Ensemble average
responses were constructed from 50-100 drug applications lasting
100-250 msec at a holding potential of  50 mV. The average response
at 0 mV was subtracted from the ensemble average to remove the artifact
attributable to the voltage applied to the piezoelectric translator. To
determine patch current onsets precisely, the open tip potential was
recorded after patch rupture; the time when solution exchange reached
90% of maximum was then defined as t = 0. Collected
data were analyzed off-line using a kinetic modeling program
(Benveniste et al., 1990).
Kinetic modeling procedures. The modeling program was based
on a chemical reaction scheme describing agonist binding to one or more
receptors and subsequent transitions of the channels to open and
desensitized states. Agonist responses were initially fitted to an
identical, independent binding site scheme as follows:
where A is agonist, R is the receptor,
AnR* is the open state of the channel,
D is a desensitized state, and n reflects the
number of agonist binding steps. The transition rates are defined as
follows: kb is the binding rate, ku
is the unbinding rate,  is the opening rate,  is the closing
rate, and kd and kr are
the desensitization and resensitization rates, respectively. For
responses to quisqualate, and of the AMPA channels were fixed
to 1000 and 500 sec 1, respectively, giving the
model channels a peak open probability (Po) of ~0.7 and mean open time of 2 msec (Hestrin, 1992; Kullmann, 1993). For responses to domoate, the and were both fixed to 1000 sec1,
respectively, giving the model channels a peak open probability of
~0.5 and mean open time of 1 msec. The lower
Po for domoate corresponds to its lower efficacy
relative to quisqualate (Patneau and Mayer, 1990). For steps into
quisqualate and domoate, the unbinding and binding rates were free
parameters to allow for possible effects of CTZ on agonist binding
(Patneau et al., 1993). For the antagonist unbinding experiments, the
ratio of ligand unbinding rate to binding rate for kainate was
constrained to microscopic Kd values for a
two-agonist site model based on measurements by Patneau and Mayer
(1990). The CNQX binding rate was arbitrarily set to 40 sec1, because it played no role in the response
kinetics when stepping from equilibrium concentrations of CNQX.
However, the CNQX unbinding rate was a free parameter.
For a given set of rate constants, the model iteratively
calculated the evolution of the number of channels in each state. It
predicted the current time course after agonist application from the
evolution of the number of channels in the open state. The free rate
constants in the model were varied using a simplex algorithm to
minimize the sum of squared errors (SSE) between the experimental
current time course and the model prediction. For most data sets the
predominant noise source was not channel noise, so the SSE was not
weighted during the fitting procedure. After each fit, the SSE was
recalculated over a subregion of the response, and this value was
divided by the SD of the noise in a period immediately preceding the
response. This provided a measure of the goodness-of-fit that was
independent of basal recording noise. Statistical comparisons between
subregion SSEs were made using paired t tests; for multiple
comparisons, repeated measures ANOVA with Tukey's post hoc
comparison test was used (p < 0.05 considered
significant). For each patch, the ratio was calculated between the
subregion SSE for a given model and the subregion SSE for the two
identical independent binding site model. This ratio provided a measure
of the relative accuracy of each model.
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RESULTS |
We examined the activation kinetics of native non-NMDA receptor
responses in cultured hippocampal neurons. Although significant heterogeneity exists in the subunit composition of AMPA and kainate responses on hippocampal neurons (Geiger et al., 1995; Ruano et al.,
1995; Fleck et al., 1996), we limited our observations to responses in
pyramidal-shaped neurons that had linear I-V
plots and strongly desensitizing, cyclothiazide-sensitive responses. These criteria are consistent with AMPA receptor-mediated EPSCs in
cultured hippocampal pyramidal neurons (Forsythe and Westbrook, 1988;
Mennerick and Zorumski, 1995; Diamond and Jahr, 1995).
To determine the functional stoichiometry of ligand binding to AMPA
receptors, we examined the activation kinetics evoked by fast agonist
application to outside-out patches. The low-affinity agonists
L-glutamate and AMPA were not useful for these experiments, because the forward reaction rate (kb × [agonist]) at the concentrations required to elicit robust responses
(>200 µM) was too fast to allow resolution of the rising
phase of the response. Thus we used the high-affinity agonist
quisqualate. However, as shown in Figure
1A, fast
desensitization of AMPA receptors activated by quisqualate develops
before agonist binding reaches equilibrium, making it difficult to
follow the underlying time course of agonist-receptor interactions. At
200 µM quisqualate, the response rise time for this patch
was fast (0.9 msec, 20-80%), consistent with rapid delivery of
agonist (Fig. 1A, inset). The response desensitized rapidly in the continued presence of agonist (double exponential, 4.4 and 14 msec time constants, 98.5% desensitization for this patch). At
a lower concentration of quisqualate (2 µM), activation showed an apparent delay at the foot of the response, and the maximum
rate of rise was not achieved until 2-3 msec. However, the rise time
of the response was rapid (2.5 msec, 20-80%). Assuming a binding rate
of 5-10 µM1sec1 similar to
NMDA receptors (Clements and Westbrook, 1991), the response evoked by 2 µM quisqualate should take >100 msec to reach equilibrium. Thus the rapid rise time reflects the onset of fast desensitization. To eliminate desensitization, we used the
benzothiadiazine diuretic cyclothiazide (Patneau et al., 1993; Yamada
and Tang, 1993). Figure 1B shows that CTZ reduced
desensitization in a dose-dependent manner. In the continuous presence
of 100 µM CTZ, a step into quisqualate produced a
response with residual desensitization of <15 ± 5% and a much
longer time constant of 70 msec (n = 9). The use of
cyclothiazide permitted evaluation of the activation kinetics of AMPA
receptors at lower concentrations of quisqualate, at which the onset of
the response was limited by agonist binding.
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Figure 1.
AMPA receptor activation kinetics can be unmasked
when desensitization is blocked by CTZ. A, Quisqualate
was applied to an outside-out patch from a cultured hippocampal neuron
using fast solution exchange. Holding potential was 50 mV. Ensemble
averages of currents evoked by quisqualate (2 and 200 µM)
are shown. The response to 200 µM quisqualate
desensitized rapidly (first time constant, 4.4 msec). The response to 2 µM quisqualate had a rise time of 2.5 msec (20-80%),
much faster than the expected rise time of receptor occupancy at this
concentration (~100 msec; see Results), thus masking the kinetics of
the agonist binding steps. Inset, The solution delivery
as determined from open tip recordings after patch rupture for this
patch is superimposed above the ensemble average current. Calibration
for inset was 10 msec and 20 pA. B, The
ensemble average response to 200 µM quisqualate was
recorded in the continuous presence of CTZ (0, 20, or 100 µM). Pre-equilibration with CTZ removed AMPA receptor
desensitization in a dose-dependent manner. In the presence of 100 µM CTZ, desensitization was <10% in this patch.
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Binding of two agonist molecules is required for AMPA
receptor activation
Ensemble averages of the current evoked by stepping into
quisqualate (2.5, 5, 10, and 300 µM) in the presence of
100 µM CTZ are illustrated in Figure
2A. Peak amplitudes
were normalized to facilitate comparison. The rise time of the response
was dose-dependent, confirming that agonist binding was the
rate-limiting process at lower concentrations. The slower responses had
a sigmoidal activation time course, suggesting that several steps are
required for channel activation. To determine the number of activation steps, we tested three different models with one, two, or three identical independent agonist binding sites. The models incorporated closed, open and desensitized states. The unconstrained reaction rates
(number of binding sites, kb,
ku, kd, and
kr) were adjusted to fit the recorded
quisqualate responses optimally (see Materials and Methods).
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Figure 2.
Quisqualate activation kinetics reveal that
binding of two molecules of agonist are necessary for AMPA receptor
activation. A, Quisqualate (2.5, 5, 10, and 300 µM) was applied to outside-out patches in the continuous
presence of CTZ (100 µM) to block desensitization. Ensemble averages from four different patches are shown, and their peak
amplitudes are normalized to facilitate comparison. The rise times of
the responses are concentration-dependent, which suggests that the
binding of quisqualate is the rate-limiting process at lower
concentrations. The rising phase was clearly sigmoidal at low
quisqualate concentrations, suggesting the presence of more than one
binding step. B. The response to a 100 msec application of quisqualate (Quis; 10 µM)
(dots) was fitted with three different kinetic models
incorporating one, two, or three binding sites (lines).
All three models gave a good fit late in the response when quisqualate
binding was complete. However, the fits diverged during the rising
phase (box). C, An enlargement of the
boxed area in B, highlighting the early
part of the rising phase. The optimally fitted transients are shown as
dashed lines for the one- and three-site models and a
solid line for the two-site model. D, The
SSE was calculated between a fitted transient and the data over the
rising phase of the response. The SSEs for the one- and three-site
models were divided by the SSE for the two-site model. The mean SSE
ratio for the responses from 13 patches are shown in the
histogram. Error bars indicate SEM. The two-site model gave the best fit to the activation phase of the response.
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Not surprisingly, all three models produced a good fit to the data late
in the response when agonist binding was complete (Fig.
2B). To assess the quality of the fit during the
critical period when quisqualate was binding to the receptors, the SSE between the data and the fitted transient was calculated over a
restricted interval during the rising phase of the response (5 µM, first 100 msec; 10 µM, first 50 msec).
The two- and three-site models gave a much better fit to the rising
phase than the one-site model (Fig. 2C). The SSE for the
two-identical-independent-site model was smaller than for other models
by a factor of 9 ± 2 (one-site) and 1.7 ± 0.3 (three-site)
(average ratio, n = 13) (Fig. 2D). The two-site model gave the best fit in 12 of 13 responses, and the
SSEs of the three-site model were significantly larger than for the
two-site model. This result suggests that two functional ligand binding
sites are present per AMPA channel.
The microscopic binding and unbinding rates of quisqualate to the
AMPA receptor were 4.6 ± 0.3 µM1sec1 and 30 ± 3 sec1 (n = 13), corresponding to a
microscopic Kd of 6.5 µM at each binding site. The binding rate is very similar to the binding rate of
L-glutamate to the NMDA receptor (Clements and Westbrook, 1991). Because the high value of Po and the prominent
desensitization (in the absence of CTZ) increase the macroscopic
Kd, our average rate parameters predict a
steady-state EC50 for quisqualate of ~3.6
µM. This value is in relatively good agreement with the
measured steady-state EC50 for quisqualate (0.9 µM; Patneau and Mayer, 1990). The best fit
desensitization and resensitization rates were 4.3 ± 0.8 and
49 ± 19 sec1 (n = 11),
consistent with the small degree of macroscopic desensitization in
CTZ.
The estimated number of binding steps is not affected
by cyclothiazide
CTZ could alter the functional stoichiometry of the AMPA channel.
For example, CTZ could restrict access to one or more agonist binding
sites or alter the channel energetics so that fewer agonist binding
events are required to open the channel. Domoate produces little or no
desensitization when it activates AMPA channels and has a relatively
high affinity (Patneau and Mayer, 1990). Thus we tested whether CTZ
affects the functional stoichiometry by applying domoate in the
presence or absence of CTZ. In the absence of CTZ, the rise time of
ensemble average responses to domoate was dose-dependent (Fig.
3A), consistent with that
observed for quisqualate. Responses to domoate were fitted using three
different kinetic models containing one, two, or three identical
independent binding sites (Fig. 3B,C). Model parameters were
optimized as above, and the goodness of fit was assessed over the
rising phase as domoate was binding to the receptors (5 µM, first 150 msec; 10 µM, first 100 msec;
20 µM, first 40 msec). In the absence of CTZ, the SSEs
for the two-site model were smaller than for other models by factors of
15 ± 4 (one-site) and 2.1 ± 0.3 (three-site) (average
ratio, n = 6) (Fig. 3D). The two-site model
gave the best fit in every case, and the SSEs for this model were
significantly smaller than for the three-site model (n = 6). When CTZ was added, the peak responses were larger as expected,
but the activation kinetics were not altered. In the presence of CTZ,
the SSEs for the two-site model were smaller than for other models by
factors of 14 ± 3 (one-site) and 1.9 ± 0.4 (three-site)
(average ratio, n = 13) (Fig. 3D). The
two-site model gave the best fit in 10 of 13 patches, and the SSEs for
this model were significantly smaller than for the three-site model.
The domoate binding and unbinding rates in the presence of CTZ were:
binding, 2.2 ± 0.2 µM1sec1; and unbinding,
37.3 ± 4 sec1 (n = 13),
corresponding to a Kd of 16.9 µM.
These results suggest that CTZ does not interfere with the number of
binding sites required for channel activation.
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Figure 3.
Activation of AMPA receptors by the
nondesensitizing agonist domoate indicate that CTZ does not distort the
estimated number of agonist binding steps. A, Domoate,
(5, 10, and 20 µM) produced a nondesensitizing response
in outside-out patches. Ensemble averages from three different patches
are shown with their peak amplitudes normalized to facilitate
comparison. As for quisqualate, the rise times of the responses were
concentration-dependent, with sigmoidal activation at low agonist
concentrations. B, The response to a pulse (150 msec) of
domoate (10 µM) (dots) was fitted with
three different kinetic models incorporating one, two, or three binding sites (lines). All three models gave a good fit late in
the response when domoate binding was complete but diverged in the
critical rising phase (box). C, An
enlargement of the boxed area in B, highlighting the early part of the rising phase. The optimally fitted
transients are shown as dashed lines for the one- and
three-site models and a solid line for the two-site
model. D, Domoate responses in the absence or presence
of 100 µM CTZ were compared using the three kinetic
models. The mean SSE in the absence of CTZ (CTZ; n = 6) and presence of CTZ (+CTZ;
n = 13) are shown in the histograms. As for quisqualate, the two-site model gave the best fit to the activation phase, and CTZ did not alter the stoichiometry of agonist binding.
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Antagonist unbinding also predicts two sites
The stoichiometry of ligand binding to AMPA channels was
reexamined using an independent approach based on the dissociation kinetics of a competitive antagonist (Benveniste and Mayer, 1991; Clements and Westbrook, 1994). Outside-out patches were
pre-equilibrated with a saturating concentration of CNQX (20 µM) and then rapidly stepped out of CNQX and into a
saturating concentration of kainate (1 mM). Because the
activation phase after steps into kainate is complete in <1 msec
(0.57 ± 0.04 msec; n = 9) (also see Patneau et
al., 1993), the slower activation after a step out of CNQX and into
kainate reflects the number of antagonist unbinding steps. As shown in
Figure 4A, the rising
phase of the response was sigmoidal and required >100 msec. Three
different models containing one, two, or three identical independent
antagonist binding sites were used to fit the entire time course of the
recorded responses. The goodness of fit was assessed over the first 100 msec of the rising phase, while CNQX was unbinding from the receptors
(Fig. 4B). The SSE for the two-site model was smaller
than for other models by factors of 20 ± 6 (one-site) and
3.3 ± 1.2 (three-site) (average ratio, n = 12)
(Fig. 4C). The two-site model gave the best fit in 9 of 12 patches, and the SSEs were significantly smaller than for the
three-site model.
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Figure 4.
CNQX dissociation kinetics reveal that two
molecules of antagonist bind to the AMPA receptor. A, An
outside-out patch was stepped from a saturating concentration of CNQX
(20 µM) into a saturating concentration of kainate (1 mM). CNQX dissociation is the rate-limiting process for
activation of this response. The early part of the response
(box) is sigmoidal, which suggests a multistep process.
B, An enlargement of the boxed area in
A shows the response (dots) fitted with
three different kinetic models incorporating one, two, or three
antagonist binding sites (lines). All
three models gave a good fit late in the response when CNQX unbinding
was complete (data not shown). However, the fits diverged in the rising
phase. The optimally fitted transients are shown as dashed
lines for the one- and three-antagonist site models and a
solid line for the two-antagonist site model.
C, Responses after a step from CNQX into kainate were
recorded in the absence or presence of 100 µM CTZ and
fitted with the three kinetic models. As shown in the SSE ratios in the
histogram, the two-antagonist-site model gave the best
fit to the activation phase of the response in the absence
(CTZ; n = 7) and in the presence
(+CTZ; n = 12) of CTZ.
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Although kainate or domoate activation of AMPA receptors showed little
desensitization in whole-cell recording, we, as others, observed
desensitization even with these "nondesensitizing" agonists during
rapid application in outside-out patches (39 ± 3%,  = 3.9 msec; n = 9). Thus to exclude the possibility that
receptor desensitization during CNQX dissociation affected the fits, we repeated the experiments in the continuous presence of CTZ. The responses were fitted using the same three models. The SSE for the
two-site model was again smaller than for other models by factors of
3.7 ± 0.7 (one-site) and 1.9 ± 0.2 (three-site) (average ratio, n = 7) (Fig. 4C). The two-site model
gave the best fit in all seven patches, and the SSEs were significantly
smaller than for the three-site model. Thus two different approaches, based on either agonist binding or antagonist unbinding, are consistent with two binding sites per channel.
The two binding sites show negative cooperativity
Although fits to the two identical independent antagonist binding
sites were superior to either one or three sites, there were small but
systematic deviations from the observed responses during the critical
rising phase. Thus we tested several models incorporating a more
detailed description of antagonist dissociation. As agonist and
antagonist binding rates usually fall within a limited range (2-20
µM1sec1), it is often assumed
that the ligand binding rate is "diffusion-limited." In this view
of receptor ligand interaction, affinity is determined predominantly by
the ligand unbinding rate. If two sites on a channel have different
affinities, this implies a difference in the ligand unbinding rate at
the two sites. Similarly, if binding to one site on a channel alters
the affinity of the other site (cooperativity), this will be expressed
through a change in the unbinding rate at the second site. Thus,
antagonist dissociation kinetics would be expected to provide a more
sensitive test for cooperative interactions between binding sites than
agonist binding kinetics (Clements and Westbrook, 1994). Thus we tested
the ability of more detailed kinetic models to fit the response after a
step from CNQX into a saturating concentration of kainate.
The new models were variations on the two-identical-independent (II)
binding site model, which produced the best fit in the first round of
analysis. In one variant, the binding sites were independent and had
the same antagonist binding rates but different antagonist unbinding
rates. This model describes two different, independent (DI) sites (Fig.
5A). In the second variant,
the two sites were identical, but antagonist binding to the first site altered the antagonist unbinding rate at the second site. This model
describes two identical, cooperative (IC) sites (Fig. 5A). For steps from CNQX into kainate, the IC model gave a better fit to the
activation phase than the II model (Fig. 5B). In contrast, the DI model did not give a significantly better fit, although it had
the same number of free parameters as the IC model. The ratio between
the SSE for the II model and for other models was 0.85 ± 0.06 (IC) and 1.01 ± 0.04 (DI) (average ratio, n = 12) (Fig. 5C). The IC model gave the best fit in 10 of 12 patches with SSEs that were significantly smaller than for the II
model. Similar results were obtained in the presence of CTZ (Fig.
5C). The optimum rate constants for the IC model revealed
negative cooperativity in the binding of CNQX to AMPA receptors. When
both sites were occupied the unbinding rate from the first site was 29 ± 2 sec1 and from the second site was
16 ± 1 sec1 (n = 12). Faster
CNQX unbinding rates were observed in the presence of CTZ. When both
sites were occupied, the unbinding rate from the first site was 75 ± 5 sec1 and from the second site was 33 ± 5 sec1 (n = 6). The faster
unbinding of CNQX in CTZ is consistent with the right shift in the CNQX
dose-response curve in the presence of CTZ (128 ± 5.8 to
573 ± 45 µM, respectively, n = 4-10). Thus, occupancy of one site on the AMPA receptor by CNQX
reduced the affinity at the second site by approximately half.
View larger version (17K):
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[in a new window]
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Figure 5.
The two antagonist binding sites on the AMPA
receptor exhibit negative cooperativity. A, The reaction
schemes describe three ways in which the competitive antagonist, CNQX,
can unbind from the AMPA receptor. In all three schemes, the
left state shows a receptor (R)
with two molecules of competitive antagonist (C) bound to it. The first scheme describes unbinding from two identical independent (II) antagonist sites. Two routes are
possible; antagonist unbinds first from site 1, or first from site 2. These two equivalent paths have been collapsed into a single path for
simplicity. In the collapsed scheme, the unbinding rate for the first
step (2k) is twice as fast as the binding rate for the
second step (k). The second scheme describes
unbinding from two different independent (DI)
sites. The unbinding rate from site 1 (k1) is
different from the unbinding rate from site 2 (k2), but there is no interaction between the
sites. The third scheme describes unbinding from two identical
cooperative (IC) sites. The rate of the first unbinding
step from either site 1 or 2 is the identical
(k1), but this step alters the rate of the
second unbinding step (k2) via a cooperative
interaction. When both sites have been vacated by antagonist, the
subsequent steps leading to channel activation are so fast under the
present experimental conditions that they can be combined into a single
kinetic transition with no loss of accuracy. Thus a single step is
shown for the transition from the vacant receptor
(R) to active channel with two molecules of agonist bound (A2R*).
B, The response (dots) after a step from
CNQX (20 µM) into kainate (1 mM) was fitted
with the three different kinetic models shown in A. All
three models gave a good fit late in the response when CNQX unbinding
was complete (not shown) but diverged in the rising phase. The optimal
fits for the II model (dashed line) and the IC model (solid
line) are shown. The IC model provided a better
fit than either the II model or the DI model (data not
shown). C, The SSEs for the DI and
IC models were divided by the SSE for the
II model. The cooperative model (IC) gave
the best fit to the activation phase of the response and was not
affected by the presence of CTZ (100 µM). SSE ratios for
seven responses in the presence of CTZ and 12 responses in the absence
of CTZ are shown.
|
|
The II, IC, and DI models were adapted to describe agonist binding. The
rate constants were optimized to fit the response to quisqualate in 100 µM CTZ over the entire time course of the response (Fig.
6A). As outlined above,
dissociation (deactivation) kinetics are more sensitive to cooperative
interactions between binding sites than are binding kinetics. Thus SSEs
between the data and the fitted transients were calculated during
deactivation (Fig. 6B). Both the DI and IC models
gave significantly better fits to the quisqualate deactivation than the
II model. The ratios between the SSE for the II model and for other
models were 0.54 ± 0.14 (IC) and 0.53 ± 0.14 (DI) (average
ratio, n = 9) (Fig. 6C). There was no
significant difference between the fit obtained with the IC or DI
models, but the agonist deactivation data do provide further evidence
that the agonist binding sites on the AMPA receptor are not identical
and independent.
View larger version (10K):
[in this window]
[in a new window]
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Figure 6.
Quisqualate (Quis) deactivation
kinetics show that the two agonist binding sites are unequal.
A, The response to a pulse (100 msec) of quisqualate (10 µM) (dots) was fitted with three different kinetic models describing identical independent (II), different independent (DI), and identical cooperative (IC) agonist binding sites
(lines). The fits diverged in the early part of the
deactivation phase after the removal of agonist (box).
B, An enlargement of the boxed area in
A during agonist unbinding (deactivation). The optimally
fitted transients are shown as a dashed line for the II model and solid lines for the
DI and IC models. C, The
mean SSE ratios for the responses from 13 patches are shown in the histogram. The IC and DI
models gave better fits to the deactivation phase of the response than
the II model.
|
|
| |
DISCUSSION |
Comparison between kinetic analysis and steady-state
pharmacological analysis
Steady-state dose-response analysis as well as binding
experiments have previously suggested the presence of more than one binding site on AMPA receptor channels, based on Hill coefficients ranging from 1.2 to 1.95 (Verdoorn and Dingledine 1988; Priestley et
al., 1989; Trussell and Fischbach, 1989; Patneau and Mayer 1990; Jonas
and Sakmann, 1992). Similar results have been obtained in
dose-response analysis of the homomeric kainate receptor subunit glutamate receptor 6 (GluR6) and a nondesensitizing GluR3/6 chimera (Heckmann et al., 1996; Rosenmund and Stevens, 1996). In fact kinetic
schemes attempting to describe AMPA channel behavior now use a model
with two agonist binding sites (Jonas et al., 1993; Raman and Trussell,
1995; Häusser and Roth, 1997). These observations suggest a
stoichiometry of at least two agonist binding sites per channel, but
the presence of desensitization and cooperativity complicate
steady-state measurements. Furthermore, in cochlear neurons, the
possibility of more than two sites for AMPA channels has been suggested
by limiting slope analysis (Raman and Trussell, 1992). These authors
modeled a third low-affinity site to account for the roll off in the
dose-response curve at very high agonist concentrations. The kinetic
approach used here provides an alternative to steady-state
pharmacological analysis by explicitly incorporating desensitization
and cooperativity. The use of rapid application methods revealed a
sigmoidal onset to the ensemble average current, providing unequivocal
evidence that there is more than one binding site on AMPA channels.
Fits of the ensemble average currents were best with a two-site model,
but the difference between fits to the two- and three-site models,
although statistically significant, was smaller than the difference
with the one-site model. Thus the possibility of additional binding
sites cannot be excluded completely (see below).
The reliability of our estimate for the number of binding sites depends
on three major factors: any contamination of the activation phase by
desensitization, the adequacy of the kinetic model, and possible
effects of receptor heterogeneity on the number of agonist binding
sites. We addressed the first problem with the use of CTZ, which
greatly reduces AMPA receptor desensitization. Although the principle
macroscopic effect of CTZ is the slowing of entry into the desensitized
state, it also slows deactivation (Patneau et al., 1993), an effect
that cannot be accounted for by changes in the rate into the
desensitized state. In addition, CTZ also produces a left shift
(approximately fourfold change in EC50) in the
kainate dose-response curve (Patneau et al., 1993) (Y. Sahara,
unpublished data) that has been modeled as an increase in agonist
affinity along with a reduction in the entry into the desensitized
state (Partin et al., 1996). Alternatively, CTZ could allow the channel
to open from a desensitized state. In fact preliminary use of a model
containing an "open desensitized" state provided good fits to the
entire time course, including deactivation in the presence of CTZ
(J. D. Clements, unpublished data). However, we obtained similar
estimates for the number of binding sites for the nondesensitizing
agonist domoate in the absence of CTZ, suggesting that cyclothiazide
does not alter the number of functional agonist binding sites. This is
supported by recent molecular analysis of GluR1, which indicated that
the differential modulation by CTZ of the flip/flop splice variant
depends on a single residue at position 750 (Partin et al., 1995,
1996). Models of the glutamate binding site place the flip/flop domain
in an external helix away from the proposed glutamate binding pocket
(Sutcliffe et al., 1996).
To fit the activation time course, we used a simplified kinetic scheme
for the AMPA receptor that incorporates previous measurements of
transition rates between open, closed, and desensitized states. Although the simplified reaction scheme does not account for all experimental details of AMPA receptor activity (e.g., subconductance levels), similar schemes can accurately predict ensemble kinetic properties of ligand-gated channels under a wide range of experimental conditions (e.g., Jonas and Sakmann, 1992; Jonas et al., 1993; Diamond
and Jahr, 1997). Wherever possible we constrained transition rates,
e.g., between open and closed states, based on previous experimental
results. Furthermore, the experiments were structured such that the
binding steps were rate-limiting; thus possible inaccuracies in some of
the rates would not have affected our results. For example the CNQX
binding rate was irrelevant to the fits, because our measurements were
made after CNQX had equilibrated at a high level of receptor occupancy.
As an additional check on the accuracy of the model, the microscopic
binding and unbinding rates generated by the kinetic model gave
estimated steady-state EC50 values that were close to
EC50 values measured for AMPA receptors on hippocampal
neurons (Patneau and Mayer, 1990).
Stoichiometry and structure of AMPA channels
Glutamate receptor channels are heteromers consisting of four or
five subunits with GluR1-4 coassembling to generate AMPA receptors
(Wisden and Seeburg, 1993; Hollmann and Heinemann,
1994). There is considerable heterogeneity in the properties of AMPA receptors because of subunit composition, alternative splicing, and RNA
editing (Sommer et al., 1990; Verdoorn et al., 1991; Burnashev et al.,
1992; Lomeli et al., 1994; Mosbacher et al., 1994; Geiger et al., 1995;
Swanson et al., 1997). Although this is an inevitable problem for all
studies of native receptors, even with a single cell type such as CA1
pyramidal cells (e.g., Mackler and Eberwine, 1993), the CTZ sensitivity
and linear I-V relationships of patch currents
in our experiments are consistent with AMPA receptor heteromers
containing edited GluR2 subunits. The high sensitivity to CTZ is also
most consistent with flip-containing subunits (Fleck et al., 1996).
Consistent with relatively uniform macroscopic channel behavior, the
patch currents in our experiments were well fitted with a relatively
simple kinetic model. However, patch-to-patch variability in response
time course was greater than could be attributed to the recording
noise, resulting in some scatter in the reaction rate constant
estimates. Whether this was attributable to subunit heterogeneity or
post-translational processing is unclear. However, the estimates for
the number and cooperativity of binding sites were consistent from
patch to patch, suggesting that receptor heterogeneity did not
significantly affect our estimates of the number of binding sites per
channel.
Based on the homology of the extracellular domain of glutamate receptor
subunits with bacterial periplasmic binding proteins such as
lysine-arginine-ornithine binding protein (LAOBP), it appears that
each subunit has all the necessary domains for a functional binding
site. The binding site of the glutamate channel subunits incorporates
an LAOBP-like domain split between the N-terminal domain and the M3-M4
extracellular loop (O'Hara et al., 1993; Stern-Bach et al., 1994;
Kuusinen et al., 1995). Thus whatever the exact subunit composition of
the AMPA channels in our experiments, the number of agonist binding
sites might be expected to equal the number of subunits. Such a
hypothesis seems consistent with NMDA receptors, the subunits of which
share homology with the AMPA subunits. In the case of NMDA receptors,
the binding of four agonist molecules (two glutamates and two glycines)
are required to activate the channel (Benveniste and Mayer, 1991;
Clements and Westbrook, 1991, 1994). Furthermore, each NMDA channel
contains two or three NR1 and two NR2 subunits (Behe et al., 1995;
Premkumar and Auerbach, 1996) per channel, with glycine and glutamate
binding to the NR1 and NR2 subunits, respectively (Kuryatov et al.,
1994, Laube et al., 1997). This situation contrasts with the
acetylcholine receptor family, in which the number of binding sites is
less than the number of subunits, presumably because the two agonist binding sites reside at subunit-subunit interfaces (Karlin and Akabas,
1995; Smith and Olsen, 1995, but see Palma et al., 1996).
Are there more than two binding sites per channel?
Our finding that each AMPA channel has only two
functional binding sites raises questions about the status
of the presumed two or three additional binding sites. Either binding
to these sites is restricted, or it does not measurably influence
channel function (a "silent" binding site). Binding at some sites
could be prevented by conformational constraints imposed by
subunit-subunit interactions. For example, a subunit may need to be
held in a "receptive" conformation by two neighboring subunits,
both of which have to be in a "nonreceptive" conformation. Such
subunit interactions could conceivably differ depending on subunit
composition. For example, in a homomeric channel composed of GluR3/6
chimeric subunits, three conductance levels have been observed that are dependent on agonist concentration, implying a relationship between the
conductance level and the number of binding sites (Rosenmund and
Stevens, 1996).
An alternative explanation is that negative cooperativity between the
binding sites could effectively preclude more than two binding events.
When two sites are occupied, cooperative interactions could reduce the
affinity of the remaining sites such that no significant agonist or
antagonist binding occurs. Negative cooperativity is implied by our
results, perhaps as an unavoidable consequence of allosteric
interactions between binding sites on adjacent GluR subunits. For
example, the binding of L-glutamate to NMDA receptors reduces the affinity of glycine binding, resulting in the phenomenon of
glycine-dependent desensitization (Mayer et al., 1989). However, both
quantitative and qualitative aspects of this explanation remain
problematic. First, it was not possible in our experiments to
distinguish unequivocally between models of agonist binding with two
different independent or two identical cooperative sites. However, if
the cooperative model is assumed, the estimated affinities for the two
successive binding steps differ by a factor of 2-3 with a systematic
tendency for a negative allosteric effect. If the twofold to threefold
reduction in affinity from the first to second binding steps were
simply extrapolated, then a third binding step should have been
detectable. It is therefore necessary to assume a dramatic increase in
negative cooperativity beyond the second binding step. This could be
achieved if binding to adjacent subunits was less favored than binding
to nonadjacent subunits. However, it seems surprising that negative
cooperativity would be the same for different agonists and antagonists.
Thus we favor the possibility that one or more binding sites are
silent. Although the functional significance of such sites is unclear, they could influence more subtle aspects of receptor function such as
desensitization or play a role in buffering of glutamate in the
synaptic cleft.
| |
FOOTNOTES |
Received Sept. 4, 1997; revised Oct. 15, 1997; accepted Oct. 20, 1997.
This work was supported by United States Public Health Services Grant
NS26494. J.D.C. was supported in part by a Queen Elizabeth II
Fellowship from the Australian Research Council. We thank Jeff Volk for
the preparation of the cell cultures. Cyclothiazide was generously
provided by Eli Lilly Research Laboratories (Indianapolis, IN).
Correspondence should be addressed to Gary L. Westbrook, Vollum
Institute, L474, Oregon Health Sciences University, Portland, OR 97201.
| |
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Top
Abstract
Introduction
