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Previous Article | Next Article
The Journal of Neuroscience, February 1, 2003, 23(3):847
How AMPA Receptor Desensitization Depends on Receptor Occupancy
Antoine Robert and James R. Howe Department of Pharmacology, Yale University School of Medicine, New Haven, Connecticut 06520-8066
ABSTRACT
TOP
ABSTRACT
Introduction
AMPA-type glutamate receptors mediate fast excitatory transmission at many central synapses, and rapid desensitization of these receptors can shape the decay of synaptic currents and limit the fidelity of high-frequency synaptic transmission. Here we use a combination of fast glutamate application protocols and kinetic simulations to determine how AMPA receptor desensitization depends on the number of subunits occupied by glutamate. We show that occupancy of a single subunit is sufficient to desensitize AMPA-type channels and that receptors with one to four glutamates bound enter desensitization at similar rates. We find that recovery from desensitization follows a similar sigmoid time course for channels with two to four glutamates bound but is faster and exponential for singly occupied channels. The results suggest that desensitization, at intermediate and high glutamate concentrations, is accompanied by two conformational changes that slow glutamate dissociation. We propose a kinetic scheme that accurately predicts several types of experimental results and differs significantly from previous models in the assignment of affinities for binding to closed and desensitized states. We conclude that desensitization involves a rearrangement that stabilizes the binding domains of one subunit in each dimer in a partially closed conformation. This stabilization likely results from an interaction at the dimer-dimer interface between the binding domains of adjacent subunits.
Key words: glutamate; AMPA receptor; desensitization; GluR1; GluR4; kinetic modeling
Introduction
AMPA receptors are tetrameric assemblies (Rosenmund et al., 1998
; Chen et al., 1999
The structure of the ligand-binding core of glutamate receptor (GluR) subunits shows that glutamate binds at the base of a deep cleft between two globular domains (1 and 2) and induces the translation and rotation of domain 2 such that the cleft closes (Armstrong et al., 1998
Here we use a combination of fast glutamate application protocols and kinetic modeling to compare desensitization for the flip splice variants of GluR1 and GluR4, recombinant channels that recover from desensitization at substantially different rates. Measurements of desensitization and recovery from desensitization were made over a range of glutamate concentrations to determine how these channel properties depend on receptor occupancy. The results provide insight into the extent of binding domain closure during desensitization and the relative affinity of glutamate for closed and desensitized states.
Materials and Methods
Cell culture and patch-clamp recording. Human embryonic kidney (HEK) 293 or tsA201 cells were plated onto 12 mm glass coverslips that had been coated with poly-L-lysine (100 µg/ml). The culture medium was modified Eagle's medium (MEM-E; Invitrogen), Gaithersburg, MD) containing 10% fetal bovine serum. The cells were transiently transfected using Lipofectamine 2000 (Invitrogen) with 0.2-1 µg of total cDNA per coverslip. The solution used for transfection consisted of 200 µl of Opti-MEM medium (Invitrogen), 3 µl of Lipofectamine 2000, 0.5 µg of a reporter cDNA encoding green fluorescent protein in pCMVsport, and 1-5 µg of GluR1flip or GluR4flip (unedited at the R/G site), both in a cytomegalovirus-driven mammalian expression vector. The GluR1 and GluR4 plasmids were kindly provided by Derek Bowie (Emory University) and Michael Tang (Yale University). Patch-clamp recordings were performed 24-72 hr after transfection at room temperature with an EPC 9 amplifier (Heka) as described previously (Robert et al., 2001
90 mV, and the series resistance before patch excision was typically 3-5 M
. In patches in which the peak glutamate-activated currents were >1 nA, series resistance compensation was used and set to 80%. The external solution was (in mM): 150 NaCl, 3 KCl, 2 CaCl2, 1 MgCl2, and 5 glucose, buffered with 10 mM HEPES (pH adjusted to 7.4 with NaOH). Patch pipettes (open tip resistance 2-4 M
Fast perfusion. Concentration-response data for glutamate-induced desensitization and steady-state and peak glutamate-evoked currents were obtained with a rapid perfusion system consisting of a theta-glass pipette in which each barrel contained four small-diameter glass capillaries connected to different solution reservoirs. Solutions were switched with a series of solenoid valves controlled by the acquisition software (Pulse) of the patch-clamp amplifier (Robert et al., 2001
Glutamate-evoked currents were analog low-pass filtered at 3 kHz (four-pole Bessel-type,
Recovery data were obtained from two-pulse protocols. In experiments in which 5 mM glutamate was applied during each pulse of the pair, the peak amplitude of the second pulse was expressed as a fraction of the peak amplitude of the paired first pulse. For GluR1 and GluR4, results were pooled from several patches, and the mean data were fitted with the Hodgkin-Huxley equation: It = (Imax1/m
))m, where It is the peak current at a given interpulse interval, t, Imax is the peak current at long interpulse intervals, I0 is the current at zero time (the relative amplitude of the plateau current),
Kinetic modeling and the assignment of values for rate constants. Kinetic modeling was done using Monte Carlo simulations with the software package ChannelLab (Synaptosoft Inc.). All the simulations started in zero glutamate and included the effect of any conditioning pulses. Simulated recovery time courses were calculated as 1
Our goal was to find a kinetic scheme (as simple as possible, yet physically plausible) that would allow us to estimate rate constants for binding to closed and desensitized states and for entry into and exit from desensitization. In addition, we sought to determine how these rate constants depend on receptor occupancy. Because AMPA receptors are tetramers and each subunit contains a binding site for glutamate, any physically plausible model must include a large number of physically discrete states, which in principle could be connected in a very large number of ways. The models that we explored were limited by previous evidence that AMPA receptor desensitization occurs from closed rather than open states (Vyklicky et al., 1991
Despite the above constraints, the large number of states required for any physically realistic model ensured that there would be many sets of rate constants that were equally good solutions for any particular data set. This is so even for our final mechanism in which the number of free parameters was minimized by making many of the rate constants integer multiples of each other. Ideally, estimates of the rate constants for each data set would have been obtained from least-squares or maximum-likelihood fits, and the values from these fits to the various data sets would have converged. However, the large number of free parameters in the models tested renders this ideal approach unrealistic (especially because any given data set depends strongly on only a subset of these parameters). In a previous study (Smith et al., 2000
Our approach to these problems was to limit our comparisons to models that differed primarily in the number of open and desensitized states and in the values assigned for binding to closed and desensitized channels. Our goal was not to find exact values for any set of rate constants but to find plausible values of all the rate constants that accounted well for the results from various different experimental protocols. For the most part, the measurements made here did not give direct estimates of the rate constants for channel opening and closing, nor did we measure single-channel currents. We therefore begin by setting values for channel opening and closing rate constants (
and
) on the basis of published values for apparent open times and burst lengths (Swanson et al., 1997
20 msec) applications of glutamate. The latter measurements also gave initial values for the rate constants for entry into desensitization (
). Rate constants for exit from desensitization,
, were then estimated from measurements of the time-course of recovery from desensitization at different glutamate concentrations. Binding rate constants for association and dissociation to and from closed channels were estimated from the time-course of entry into desensitization at low glutamate concentrations, as well as concentration-response data for desensitization and peak and steady-state glutamate-activated currents. If rate constants were altered during this procedure, simulations of previous data sets were rerun to ensure that the new set of values approximated them well.
We also limited the number of free parameters by interpreting the results in the context of specific physical mechanisms. In the mechanism proposed in Figure 6a, many of the rate constants for sets of similar transitions are integer multiples of each other. The multiples derive from our conclusion that desensitization is correlated with stabilization of binding domain closure for one subunit in each dimer, as well as our proposal that this stabilization is mediated by subunit-subunit interactions across the dimer-dimer interface between loop 1 in one subunit and helices F and G in the adjacent subunit. This interpretation of the data implies that only two equivalent subunits in each tetramer (one pair of those diagonally related to each other across the dimer-dimer interface) can be stabilized in a closed conformation. Our interpretation of the results also implies that occupancy and closure of the binding domain greatly increase the probability of these subunit-subunit interactions (
1 × 106
In summary, our goal was to evaluate our results in light of what we currently know about the structure of AMPA-type glutamate receptors and to try to place the results in the context of a physically plausible kinetic model. The advantage of this approach is that it allows predictions that can be directly tested in future studies. Although the necessary complexity of any such model makes it unlikely that a unique set of rate constants will be found that is clearly better than all others, in total we explored thousands of different sets of rate constants. For some sets of experimental data, the predictions of the model were relatively insensitive to the absolute values of individual rate constants. For example, given the parallel nature of activation and desensitization, the desensitization time constants are defined by the ratio,
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Table 1. Rate constants for GluR1 and GluR4 channels
Results
Concentration-response relationships for glutamate-evoked currents and desensitization
To determine how desensitization and activation depend on receptor occupancy for GluR1 and GluR4 channels, we first compared concentration-response data for glutamate-evoked currents and glutamate-induced desensitization. Figure 1 shows concentration-response data for glutamate-induced desensitization and the steady-state plateau currents for GluR1 (Fig. 1a-c) and GluR4 (Fig. 1d-f). Because the plateau current measurements did not require rapid solution exchange, we measured these currents using whole-cell recordings so that they would be as large as possible. As illustrated in Figure 1, concentrations of glutamate that produced substantial desensitization produced only minimal plateau current. The IC50 values for glutamate-induced desensitization were 0.56 and 7.49 µM for GluR1 and GluR4 channels compared with respective EC50 values for the plateau currents of 12.5 and 32.3 µM. The concentration-response curves for peak currents measured in patches (see Fig. 3b,c) indicate that even higher glutamate concentrations were required to achieve full receptor occupancy. The EC50 values for the peak currents (717 µM for GluR1 and 1800 µM for GluR4) (Fig. 1c,f) were nearly 60 times larger than the corresponding values for the plateau currents. The three sets of data show that full receptor occupancy requires glutamate concentrations that are approximately three orders of magnitude greater than concentrations that produce virtually complete desensitization.
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Figure 1. GluR1 and GluR4 channels desensitize at glutamate concentrations that produce minimal activation. a, d, Currents evoked by 5 mM glutamate in control solution and after equilibrating patches containing GluR1 (a) and GluR4 (d) channels with the indicated concentrations of glutamate. b, e, Steady-state plateau currents evoked in cells expressing GluR1 (b) and GluR4 (e) channels by the indicated applications of glutamate (bars). c, f, Concentration-response curves for glutamate-induced desensitization (squares), the steady-state plateau current (triangles), and the peak current (circles; from results like those shown in Fig. 3b,c) for GluR1 (c) and GluR4 (f) channels. Each symbol is the mean value obtained from measurements in four to nine patches or cells. Results from individual patches or cells were normalized to the amplitude of the peak current evoked by 5 mM glutamate in the absence of preincubation (glutamate-induced desensitization), the plateau current evoked by 1 mM glutamate, and the peak current evoked by 50 mM glutamate. Error bars indicate SEM for each set of data. Some of the error bars in this and subsequent figures are less than one-half the symbol size.
Occupancy of a single subunit is sufficient to desensitize AMPA receptors
We compared several kinetic schemes to determine which could best reproduce the three types of concentration-response data. Because AMPA receptors are tetramers with four binding sites for glutamate, all of the models tested had five closed states (zero to four glutamates bound). Channel activation and desensitization were assumed to proceed in parallel from the same closed states (Vyklicky et al., 1991
Although some native AMPA receptors display four concentration-dependent open levels (Smith and Howe, 2000
To test our conclusion further, we determined the kinetics of entry into desensitization at low glutamate concentrations. If channels with one subunit occupied desensitize, then entry into desensitization should follow a nearly exponential time course and be faster than if occupancy of multiple subunits is required. The protocols for these experiments required rapid switching between three different solutions, which was achieved by mounting pipettes pulled from theta glass with two internal septa on the piezoelectric bimorph (Fig. 2a,b). Outside-out patches containing GluR1 or GluR4 channels were first exposed to concentrations of glutamate that produced little channel activation and >50% steady-state desensitization, and the patches were then switched to 5 mM glutamate at increasing intervals to determine how many channels were available for activation. Examples of results obtained for GluR1 and GluR4 are shown in Figure 2c,d. At glutamate concentrations that produce minimal activation but substantial desensitization, the envelope of the peak currents follows a simple exponential time course (Fig. 2e,f). Hodgkin-Huxley fits to the time course data gave values for the exponent, m, that were indistinguishable from 1.0 for both GluR1 and GluR4 (1.02 ± 0.07 and 0.97 ± 0.09; n = 5 and 6 patches, respectively). The mean results obtained for GluR1 and GluR4 channels are plotted in Figure 2, g and h. Superposed on the results are the predicted time courses for entry into desensitization if singly occupied channels desensitize (thick solid lines). The dotted and thin solid lines are the predictions for models in which desensitization requires the binding of two glutamates (see legend to Fig. 2 for details), both of which give onset kinetics substantially slower than those observed. These results strongly suggest that occupancy of a single subunit is sufficient to desensitize AMPA receptors.
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Figure 2. The time course of entry into desensitization shows that occupancy of a single subunit is sufficient to desensitize AMPA receptors. a, Photomicrographs of the two-septa pipettes used for experiments requiring rapid switching between three solutions (interfaces visualized by adding ethanol to the solution in the middle barrel). The interfaces were moved in sequential steps as shown. b, Currents evoked by 5 mM glutamate 1, 4, 16, and 28 msec after exposing a patch containing GluR4 channels to 10 µM glutamate. The open tip responses measured for the same pre-exposure intervals are shown above the currents. c, d, Peak currents evoked by 5 mM glutamate at various times after exposing a patch containing GluR1 channels to 2 µM glutamate (c) and a patch containing GluR4 channels to 10 µM glutamate (d, same patch as in b). The duration of the first conditioning pulse was 1 msec. Subsequent pulses were incremented in 3 msec steps. e, f, The amplitude of the peak currents in c and d plotted as a function of the duration of the conditioning pulse (e, GluR1; f, GluR4). The results were fitted with single exponential functions (smooth curves) that gave the indicated time constants. To allow averaging of results obtained from different patches, the peak current amplitudes measured at each pre-exposure interval were normalized to the amplitude of the peak current at zero time (obtained from the exponential fits to each set of data). g, h, Mean (±SEM) results obtained for GluR1 (n = 5 patches) (g) and GluR4 (n = 6 patches) (h). The curves are the time courses for entry into desensitization predicted with 2 µM (g) and 10 µM (h) glutamate from kinetic schemes in which occupancy of one or two subunits is required to produce substantial desensitization. The thick solid lines show the kinetics predicted with the model in Figure 6a (black states only) and the rate constants in Table 1. The dotted and thin lines were obtained with models identical to Figure 6a except that states D0, D1, D22, and O2 were eliminated. The dotted lines are the predictions when the first binding step was higher affinity than subsequent ones (two-step model a), and the thin solid lines are the predictions when the first two binding steps are equivalent and higher affinity than the last two (two-step model b). The dissociation rate constants were altered to give the same steady-state desensitization. For model a, this was achieved by decreasing the dissociation rate constant for the first binding step (to 100 sec 1 for GluR1 and 350 sec
Subunit occupancy and the rate and extent of desensitization
The results above suggested to us that the kinetic scheme in Figure 3a might provide a physically plausible model for AMPA receptor gating. The model builds on earlier proposals (Patneau and Mayer, 1991
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Figure 3. The decay of GluR1 and GluR4 currents varies little with subunit occupancy. a, Hypothetical kinetic model for AMPA receptor gating. Each subunit of the tetrameric channel contains a binding site for glutamate. There are therefore five discrete closed states, which differ in the number of subunits occupied by glutamate (0-4, states R0 to R4). Channels with two, three, or four glutamates bound can open to discrete subconductance levels (O2, O3, O4) where unitary conductance increases with receptor occupancy. Channels with one, two, three, or four subunits occupied by glutamate can desensitize (states D1 to D4). b, c, Currents (dotted lines) evoked by sustained applications of the indicated concentrations of glutamate in outside-out patches from cells transfected with the cDNAs encoding GluR1 (b) or GluR4 (c). The decays of the currents have been fitted with single exponential functions (smooth curves) that gave time constants of 1.92-2.18 msec for GluR1 and 2.78-3.27 msec for GluR4. The insets show the currents superimposed after they were normalized to their peak amplitudes. d, Plot of the decay time constants for GluR1 (circles) and GluR4 (squares) channels obtained from single exponential fits to the decay of currents evoked by sustained applications of a range of glutamate concentrations (mean ± SEM values from 6 and 7 patches, respectively). e, f, Currents (dotted lines) through GluR1 (e) and GluR4 (f) channels evoked by sustained applications of 5 mM glutamate before (control) and after equilibrating individual patches in solutions containing 100-500 nM NBQX. The decays of the currents have been fitted with single exponential functions (smooth curves) that gave time constants of 1.88-2.21 msec for GluR1 and 2.71-3.35 msec for GluR4. g, Plot of the decay time constants for GluR1 (circles) and GluR4 (squares) channels as a function of NBQX concentration (mean ± SEM values from 4 and 5 patches, respectively).
One simple explanation for the full desensitization produced by very low glutamate concentrations (Kiskin et al., 1986
For both GluR1 and GluR4, currents evoked by a wide range of glutamate concentrations show similar decays (Fig. 3b-d), suggesting that the rate constants for entry and exit from desensitization (
Recovery from desensitization behaves as a two-step process
For the model in Figure 3a, there are many routes that a fully occupied desensitized channel (state D4) could take to exit from desensitization. To determine which of these possible routes is preferred, and to investigate the possibility that ligand dissociation contributes to the kinetics of recovery, we carefully mapped the time course of recovery with two-pulse protocols. A 20 msec application of 5 mM glutamate was made to desensitize the channels, and the peak current evoked by a second pulse was measured after various times in control solution. Results for GluR1 and GluR4 from single outside-out patches are shown in Figure 4, a and c. Mean results from several patches are shown in Figure 4, b and d. The recovery time course is clearly sigmoid and was poorly described by single exponential fits. To estimate the number of kinetically similar steps that contribute to the time course of recovery, we fitted the mean data with Hodgkin-Huxley equations. The fits gave values for the exponent, m, of 1.56 for GluR1 and 1.86 for GluR4. These results suggest that there are two rate-limiting steps that contribute to the time course of recovery.
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Figure 4. Recovery from desensitization follows a sigmoid time course. a, c, Currents evoked by 5 mM glutamate in outside-patches from cells expressing GluR1 (a) and GluR4 (c) channels. Two-step protocols were used in which an initial application of glutamate (bar) was paired with identical applications made at increasing interpulse intervals. Individual sweeps from the entire series are superimposed. b, d, For each patch, the peak amplitude of the current evoked by the second application of glutamate was expressed as a fraction of the peak amplitude of the current evoked by the first application with which it was paired. Circles show the mean (± SEM) results from five patches for GluR1 (b) and six patches for GluR4 (d) plotted as a function of the interpulse interval. Each set of data was fitted with a Hodgkin-Huxley equation. The fits (smooth curves) gave the indicated values for the time constant of recovery (
Receptor occupancy and the time course of recovery
To determine how the time course of recovery depends on receptor occupancy, we measured recovery from desensitization at concentrations in which most occupied channels would have either one or two subunits occupied by glutamate. To obtain the first condition, outside-out patches containing GluR1 or GluR4 channels were equilibrated with concentrations of glutamate (2 µM for GluR1 and 8 µM for GluR4) that produced substantial desensitization but little channel activation (Fig. 1c,f). To obtain the second condition, outside-out patches containing GluR1 or GluR4 channels were equilibrated with 50 µM glutamate, a concentration that produced substantial plateau, but little peak current, and virtually complete desensitization (Fig. 1c,f). Rapid switching between the three different solutions required for these experiments was achieved by using pipettes pulled from theta glass with two internal septa (Fig. 2a).
The results obtained for 8 and 50 µM glutamate from a patch containing GluR4 channels are shown in Figure 5, a and b. Recovery from desensitization induced by 8 µM glutamate was nearly exponential (mean value of m from Hodgkin-Huxley fits, 0.99 ± 0.06; n = 5 patches), whereas the results obtained for 50 µM glutamate (m = 1.77 ± 0.13; n = 4 patches) were similar to those obtained for recovery from 5 mM glutamate. The time constants obtained at each concentration (20.9 ± 1.6 and 21.4 ± 1.7 msec) were similar to the time constant of recovery from 5 mM glutamate (Fig. 4). The results obtained for GluR1 are presented in Figure 5, c and d. The fits to the mean GluR1 recovery data show that the sigmoid nature of recovery increases in a graded manner as the concentration of glutamate is increased from 2 to 50 µM (Fig. 5d) (
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Figure 5. The time course of recovery from desensitization varies with receptor occupancy. a, Recovery from desensitization caused by 8 and 50 µM glutamate in an outside-out patch containing GluR4 channels. Currents are responses to 50 msec applications of 5 mM glutamate made at increasing intervals after switching from low glutamate to control solution. b, The peak currents were normalized to the Imax values obtained from Hodgkin-Huxley fits to each set of data. These fits (smooth curves) gave m values consistent with there being one and two rate-limiting steps for recovery from desensitization caused by pre-equilibration with 8 and 50 µM glutamate, respectively. c, Recovery from desensitization caused by 10 and 50 µM glutamate in outside-out patches containing GluR1 channels. d, Mean (± SEM) normalized recovery data obtained with 2, 10, and 50 µM glutamate (results from 4, 4, and 5 patches, respectively). The m values from the Hodgkin-Huxley fits to the data (smooth curves) are given on the figure. Time constants are given in Results.
Evidence for two types of desensitized states
We were able to reproduce the time course of recovery for both GluR1 and GluR4 channels with the model in Figure 3a, provided we assumed that the first rate-limiting step during recovery is glutamate dissociation from D2. The same set of rate constants also accurately predicted the concentration dependence of steady-state desensitization and the concentration-response curves for the plateau and peak currents for both channel types.
The model in Figure 3a, however, failed to reproduce two consistent experimental findings. First, over the time scale investigated, recovery was typically incomplete. The Imax values obtained from the Hodgkin-Huxley fits to the recovery data at 5 mM glutamate were <1.0 (GluR1, 0.94; GluR4, 0.98), suggesting that a small fraction of the channels recover on a substantially slower time scale, as found in previous studies on native channels (Patneau and Mayer, 1991
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Figure 6. Kinetic model for recombinant AMPA receptors. a, The model in Figure 3a has been modified to include a constitutive desensitized state D0, as well as additional desensitized states that are progressively further removed from closed states. Each desensitized state differs in the number of subunits occupied by glutamate and the number of subunits with partially closed binding domains. For example, channels in state D24 have four glutamates bound and two partially closed binding domains. Desensitized channels with three or four glutamates bound and more than two binding domains closed are rare or unstable, i.e., either the steady-state occupancy of states D33, D34, and D44 is small or occupancy of these states declines rapidly during recovery. The probability of finding channels in any of the light gray states is very low and decreases as channels move toward the bottom left corner. Closed states (R) have subunits with binding domains that are in the open conformation. Glutamate association and dissociation to and from these subunits are rapid and characterized by the rate constants k1 and k-1. For desensitized channels, dissociation from subunits with open binding domains is rapid. Glutamates dissociate approximately four orders of magnitude slower from subunits with partially closed binding domains. This occurs for a small percentage of channels during recovery, "trapping" them in state D0 (and to a lesser extent D21) and accounting for our findings that Imax values were <1.0 for both channel types (Fig. 4). The values for the rate constants estimated for GluR1 and GluR4 are given in Table 1. Movies depicting how occupancy of the various states changes during and after applications of glutamate similar to those investigated here can be found at http://info.med.yale.edu/pharm/howe/movies.html. b, Simulated currents (dotted lines) during sustained applications of the indicated concentrations of glutamate. The single exponential fits to the decays (solid curves) gave time constants that agreed within 5% of those determined experimentally. c, d, The lines are the recovery time courses predicted from the model in Figure 6a after equilibration in the indicated concentrations of glutamate. The symbols are the corresponding data points for GluR4 (c) and GluR1 (d) channels (mean ± SEM; 4-6 patches at each concentration). Hodgkin-Huxley fits to the simulated time courses gave values for
The second problem with the model in Figure 3a was the predicted decay of the plateau current at the end of a sustained glutamate application. At the end of such an application, most channels are desensitized and will begin to recover from desensitization on returning to control solution. If during this recovery glutamate dissociation is slow from state D2, then channels that linger in D2 will continue to generate plateau current, and the decay of the plateau current will be inversely related to the rate of glutamate dissociation. For glutamate dissociation rate constants (from state D2) that reproduced the rate and shape of the measured recovery time course, simulations predicted that the plateau currents should decay with time constants of 28 and 4.5 msec for GluR1 and GluR4, respectively. These predicted decays are 5-10 times slower than those observed experimentally. This problem can be solved if it is assumed that there is a second type of desensitized state and that recovery from desensitization for channels with two or more glutamate molecules bound requires two resensitization steps. This allows dissociation from state D2 to be rapid, because the sigmoid nature of recovery can be accounted for by two relatively slow resensitization steps. The black states in the kinetic model shown in Figure 6a incorporate this second type of desensitization.
Agreement between simulated and experimental data is often improved by adding states to kinetic schemes. The model in Figure 6a would therefore gain credibility if some physical meaning could be ascribed to the two hypothetical types of desensitization. The two types of desensitized states share the property that glutamate dissociation is rapid until reaching a state in which the number of glutamate molecules bound equals the number of transitions the channel is away from the equivalently occupied closed state. Only then is resensitization favored over glutamate dissociation. This suggests to us that glutamate dissociation is fast from some subunits and slow from others. Because binding domain closure likely precedes desensitization (Armstrong and Gouaux, 2000
Although the kinetic scheme in Figure 6a has a large number of states, it reproduces a wide variety of experimental results with a small set of rate constants. If only the states in black are considered, there are two sets of binding constants (those for association and dissociation to open and partially closed binding domains), one set for channel opening and closing, and three sets for entry and exit from desensitized states. Table 1 gives values for these rate constants that we estimated for GluR1 and GluR4 channels from Monte Carlo simulations. The estimated rate constants give equilibrium dissociation constants for binding to closed states (k-1/k1) of 450 µM for GluR1 and 1 mM for GluR4. The rate at which glutamate dissociates from subunits with partially closed binding domains (k-2) is slowed ~10,000-fold. Although at high glutamate concentrations most desensitized channels will reside in states with more than one closed binding domain, for GluR1 the
As shown in Figure 6, the model accurately predicts the rate at which glutamate-evoked currents decay during sustained applications (Fig. 6b), the time course of recovery from desensitization and its dependence on glutamate concentration (Fig. 6c,d), and the concentration-response relationships for glutamate-induced desensitization and the peak and steady-state glutamate-evoked currents (Fig. 6e,f). As noted above, the model also accounts for the small percentage of channels that recover on a slower time scale and our observation that this percentage is larger for GluR1 than GluR4 channels. Finally, the model reproduces the kinetics of entry into desensitization at low glutamate concentrations (Fig. 2g,h), as well as the deactivation kinetics of both channel types (data not shown). At high glutamate concentrations, the model and the rate constants in Table 1 predict that approximately one-third of the GluR1 channels and one-fourth of the GluR4 channels will desensitize without ever opening. Manipulations that substantially slow entry into desensitization should therefore increase peak glutamate-evoked currents. For GluR1 these currents should be potentiated ~35%, a prediction that agrees well with the effect of cyclothiazide on currents through GluR1 channels (Robert et al., 2001
Although the kinetic model in Figure 6a accurately predicts a wide variety of experimental results, the experimental plateau currents for both GluR1 and GluR4 channels were approximately threefold larger at saturating glutamate concentrations than those for simulated currents. This discrepancy might be explained if desensitized channels conduct ions, as suggested recently for GluR1 channels (Bowie and Lange, 2002
Four features of the model in Figure 6a merit additional discussion. First, it has been proposed that binding domain closure precedes gating and results in short-lived closed states whose instability is relieved by channel opening or desensitization (Sun et al., 2002
Discussion
The model in Figure 6a is the first kinetic mechanism proposed for AMPA receptors that includes desensitization and incorporates four binding sites for glutamate and multiple concentration-dependent open levels. We show here that this model and a small set of rate constants can account for a wide variety of experimental results. In particular, the model clarifies the relationship between the affinity of glutamate for closed and desensitized states, the sensitivity of AMPA-type channels to glutamate-induced desensitization, and the rate of recovery from desensitization. We emphasize, however, that the large number of states and free parameters that the model contains make it likely that there are other sets of rate constants, or constraints on these values, that would account for the results equally well. As a result, our conclusions, although plausible, must be regarded as tentative.
Comparison with previous kinetic mechanisms
Although the model in Figure 6a has more states, it shares certain features with previous kinetic schemes. For example, when receptor occupancy is high, the first transition during recovery from desensitization will typically correspond to glutamate dissociation (Raman and Trussell, 1992
Sensitivity to glutamate desensitization and the rate of recovery
In a previous study we noted that the IC50 for glutamate-induced desensitization was inversely correlated with the speed of recovery (Robert et al., 2001
Binding domain closure and desensitization
We conclude that recovery from desensitization involves two sequential resensitization transitions, a conclusion also reached from recent work on GluR1 channels at high glutamate concentrations (Bowie and Lange, 2002
AMPA receptors are likely dimers of dimers (Armstrong and Gouaux, 2000
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Figure 7. Desensitization stabilizes binding domain closure for one subunit per dimer. a-c, Three possible relationships between occupancy, desensitization, and binding domain closure. In each case, there are two types of desensitized states (those in the box) that are associated with sequential and equivalent changes in binding domain closure within each dimer. a, Binding is required for domain closure, and desensitization occurs after one dimer is doubly occupied. Simulations showed that this class of model requires that the two binding events be equivalent for one dimer and nonequivalent for the other. The double-occupancy requirement is also incompatible with the results in Figure 2. b, Occupancy of one subunit triggers concerted closure of both binding domains in the dimer. The similar desensitization seen in the presence of NBQX (Fig. 3) makes this proposal unlikely. c, Singly occupied channels can desensitize, and desensitization is accompanied by two interactions at the dimer-dimer interface that stabilize domain closure for one subunit in each dimer. d, Diagram illustrating the proposed relationship between binding, desensitization, and domain closure for the kinetic scheme in Figure 6a. For channels with two or more glutamates bound, the sigmoid time course of recovery reflects two sequential resensitization steps (characterized by the rate constants
In the example in Figure 7a, only doubly occupied dimers undergo desensitization, a constraint that is not consistent with the kinetics of entry into desensitization at low glutamate concentrations (Fig. 2). In addition, once channels desensitize, this class of model requires that subsequent glutamate binding to the remaining dimer be high affinity to one monomer and low affinity to the other. If this additional constraint is not introduced, either the separation between the EC50 values for the plateau and peak currents is lost (both steps low affinity) or recovery is too slow (both steps high affinity). In Figure 7b, occupancy of one monomer results in the closure of both binding domains. However, concentrations of NBQX that produced nearly complete blockade of glutamate-evoked currents had little effect on desensitization (Fig. 3). Because NBQX binding is likely associated with minimal closure of the binding domain (Armstrong and Gouaux, 2000
The recent crystallographic results of Sun et al. (2002)
Although our proposal is speculative, previous work on NMDA receptor channels identified loop 1 as a site mediating functionally important intersubunit contacts (Regalado et al., 2001
