Molecular and biophysical basis of glutamate and trace metal modulation of voltage-gated Ca_v2.3 calcium channels

Abstract

Here, we describe a new mechanism by which glutamate (Glu) and trace metals reciprocally modulate activity of the Ca_v2.3 channel by profoundly shifting its voltage-dependent gating. We show that zinc and copper, at physiologically relevant concentrations, occupy an extracellular binding site on the surface of Ca_v2.3 and hold the threshold for activation of these channels in a depolarized voltage range. Abolishing this binding by chelation or the substitution of key amino acid residues in IS1–IS2 (H111) and IS2–IS3 (H179 and H183) loops potentiates Ca_v2.3 by shifting the voltage dependence of activation toward more negative membrane potentials. We demonstrate that copper regulates the voltage dependence of Ca_v2.3 by affecting gating charge movements. Thus, in the presence of copper, gating charges transition into the “ON” position slower, delaying activation and reducing the voltage sensitivity of the channel. Overall, our results suggest a new mechanism by which Glu and trace metals transiently modulate voltage-dependent gating of Ca_v2.3, potentially affecting synaptic transmission and plasticity in the brain.

INTRODUCTION

Voltage-gated calcium channels (VGCCs) play essential roles in all eukaryotes, allowing calcium to enter the cell in response to membrane depolarization. A variety of cellular processes including gene expression, synaptic transmission, and apoptosis are regulated by the dynamic concentration of intracellular calcium (Clapham, 2007). Thus, expression and function of VGCCs are under tight cellular control. The family of VGCCs is heterogeneous and, in mammals, consists of 10 members: L- (Ca_v1.1, Ca_v1.2, Ca_v1.3, and Ca_v1.4), P/Q- (Ca_v2.1), N- (Ca_v2.2), R- (Ca_v2.3), and T-type (Ca_v3.1, Ca_v3.2, and Ca_v3.3) (Catterall et al., 2005). In the brain, these channels mediate the following functions: L-type calcium channels were shown to be mainly responsible for regulating gene expression; N-, P/Q-, and R-type for synaptic transmission and plasticity; and T-type for pacemaker and burst firing of neurons (Zamponi, 2005). Of all the calcium channels, R-type channels are arguably the most mysterious subtype. Despite considerable investigation, its physiological role remains the least understood (Weiergräber et al., 2006). In many cases, they promote neuronal excitability, contributing to the induction of long-term potentiation (LTP) (Dietrich et al., 2003), triggering synaptic transmission (Wu et al., 1998; Gasparini et al., 2001) and generating both bursts of action potentials (APs) and plateau potentials (Kuzmiski et al., 2005; Metz et al., 2005; Tai et al., 2006; Park et al., 2010). In other cases, Ca_v2.3 channels attenuate neuronal excitability by dampening activation of NMDA receptors in the spines of CA1 pyramidal neurons (Bloodgood and Sabatini, 2007) and depressing the induction of LTP after trains of back-propagating APs (Yasuda et al., 2003). Ca_v2.3 channels are widely distributed throughout the brain (Weiergräber et al., 2006) and are considered to be the molecular correlate for R-type current in native cells (Piedras-Rentería and Tsien, 1998; Tottene et al., 2000; Sochivko et al., 2002). These channels were shown to be indirectly modulated by glutamate (Glu) and acetylcholine through a PKC-dependent pathway (Stea et al., 1995; Bannister et al., 2004; Kamatchi et al., 2004; Tai et al., 2006; Park et al., 2010; but see Giessel and Sabatini, 2010).

Transition metals play fundamental roles in a variety of vital cellular processes, serving as cofactors in several enzymes, stabilizers of protein structures, and regulators of neuronal excitability (Mathie et al., 2006). A significant increase in trace metal content in the brain has been detected in association with several pathological conditions, including epilepsy, stroke, Alzheimer’s, Parkinson’s, and Creutzfeldt–Jakob diseases (Frederickson et al., 2005; Barnham and Bush, 2008). Additionally, aging-dependent accumulation of Zn²⁺ and Cu²⁺ in the brain correlates with a higher risk for the development of neurological disorders (Barnham and Bush, 2008). In contrast to other biologically relevant divalent cations, such as Ca²⁺ and Mg²⁺, free concentrations of trace metals in the brain are extremely low and strictly regulated by a variety of metalloproteins (Valko et al., 2005). Concentrations of Zn²⁺ and Cu²⁺ in a healthy brain are estimated to be around 70–150 µM (Mathie et al., 2006). Although most of the ions (>95%) are protein bound, local free, or loosely bound, concentrations of Zn²⁺ and Cu²⁺ can reach 30 µM (Frederickson et al., 2005) and 1.7 µM (Mathie et al., 2006), respectively. Pools of “chelatable” Zn²⁺ and Cu²⁺ have been identified in the synaptic vesicles of specific (gluzinergic and glucupergic) subsets of glutamatergic neurons in the cortex, hippocampus, striatum, and amygdala (Mathie et al., 2006), and are released into the synaptic cleft upon membrane depolarization in a Ca²⁺-dependent manner (Barnham and Bush, 2008). Identification of the molecular targets for these released metal ions will provide novel insights into neuronal viability, synaptic plasticity, and excitability, as well as a deeper understanding of mechanisms of development of various neurological disorders (Frederickson et al., 2005; Barnham and Bush, 2008).

Various proteins and amino acids have submicromolar affinity to Zn²⁺ and Cu²⁺ (Dawson et al., 1986; Karlin, 1993; Regan, 1993). In contrast, only a few ion channels and receptors are reported to possess this capacity, including NMDA receptors (Paoletti et al., 2009), Ca_v3.2 calcium channels (Jeong et al., 2003; Nelson et al., 2007a,b; Traboulsie et al., 2007), GABA_A receptors (Hosie et al., 2003), and BK K⁺ potassium channels (Ma et al., 2008). The sensitivity of Ca_v2.3 channels toward Ni²⁺ has been known since their discovery (Ellinor et al., 1993; Soong et al., 1993; Zhang et al., 1993; Zamponi et al., 1996). However, it is unknown whether these channels are sensitive to physiologically relevant concentrations of zinc and copper. Studying the effect of Zn²⁺ and Cu²⁺ on Ca_v2.3, we discovered, surprisingly, that Glu and glycine (Gly) can substantially potentiate activity of these channels by shifting their gating toward more hyperpolarized voltages. The effect arose from the ability of amino acid residues to chelate trace metals, binding to the extracellular surface of the channel and blunting its voltage sensitivity. As a result of mutagenesis studies and detailed biophysical analysis of ion currents, we have identified a molecular determinant responsible for this sensitivity and described a plausible biophysical mechanism underlying it. Overall, our data reveal previously unknown properties of Ca_v2.3 calcium channels and suggest a new and potentially important mechanism through which these channels might influence synaptic transmission and plasticity in the brain.

MATERIALS AND METHODS

Site-directed mutagenesis

A human Ca_v2.3d cDNA (available from GenBank/EMBL/DDBJ under accession no. L27745) contained in pcDNA3 vector was mutated using the single-overlap extension technique. The primers were obtained from Operon and used without purification. The full-length cDNA contained in pcDNA3 was reassembled using a ClaI/XhoI fragment of the mutated clone. The sequence of this fragment was verified by automated sequencing.

Calibration of free Zn²⁺ and Cu²⁺ concentrations in Tricine solution

Fluorescent signals were measured on a fluorescent reader (FlexStation; Molecular Devices). After recording the baseline for 20 s, 25 µl of solutions containing varying concentrations of Zn²⁺ or Cu²⁺ was added using integrated fluidics to a 96-well plate containing 125 µl of dye. Signals were acquired every 2 s (excitation/emission, nm): 506/550 for Newport Green DCF and 370/520 for Mag-Fura-2. Each experiment was performed in triplicate, and the data represent the mean ± SEM from three experiments. Free Zn²⁺ was measured using 3 µM Newport Green DCF dye. Note that the solutions used for this experiment did not contain TEA and contained either 1 mM HEPES or 10 mM Tricine and KCl to adjust the ionic strength to 0.1 M, pH 7.4. To avoid trace metal contamination, we strictly followed the methods described by Aslamkhan et al. (2002). Because the background fluorescent signals measured in these HEPES and Tricine solutions were similar (Fig. 4), we conclude that this HEPES solution was not contaminated with trace metals, and that concentrations of free and added Zn²⁺ or Cu²⁺ were equal. Fluorescence responses in a range of Zn²⁺ concentrations from ∼1 to 40 µM in HEPES were fitted with the Hill equation (K_d = 10^−5.4 M and n_H = 1.3). Free concentrations of Zn²⁺ in Tricine solution were estimated by rearranging the Hill equation and solving for concentration using the fluorescence signal observed in Tricine and the K_d and n_H values acquired in HEPES solution. We then used the Solver function in the MaxChelator program (Winmaxc version 2.40 available at http://maxchelator.stanford.edu) (Patton et al., 2004) to predict free Zn²⁺ using K₁ = 10⁻⁵ M for the M + L ↔ ML equilibrium and K₂ = 10⁻³ M for the ML + L ↔ ML₂ equilibrium. The predicted values matched the experimentally determined values, indicating that the empirically determined K_d value was correct (Paoletti et al., 1997). Free Cu²⁺ concentrations in Tricine solution were measured using 3 µM Mag-Fura-2. As described for Zn²⁺, free concentrations of Cu²⁺ were calculated using the Hill equation (HEPES, K_d = 10^−6.6 M and n_H = 1.5). We then iteratively changed the K₁ and K₂ of Tricine for Cu²⁺ until Solver’s predictions matched the experimental results. These values converged when K₁ = 10^−6.3 M and K₂ = 10^−3.3 M. Similar results were obtained in MOPS-buffered solutions, so the results were pooled. We also measured the fluorescent responses to free Cu²⁺ concentrations that were calculated by Solver for a 1-mM citrate buffer, pH 7.4. The observed quenching of the Mag-Fura-2 fluorescence by this predicted free Cu²⁺ was similar to that observed in HEPES (K_d = 10^−6.1 M and n_H = 1.0), thereby confirming our estimates of free Cu²⁺.

Figure 4.

Calibration of free Zn²⁺ and Cu²⁺ concentrations in Tricine solution. (A) Fluorescence from Newport Green DCF (3 µM) was measured after the addition of varying concentrations of ZnCl₂ to HEPES- and Tricine-based solutions. HEPES and Tricine solutions used for these experiments only contained 1 mM HEPES and 10 mM Tricine, respectively. KCl was added to adjust the ionic strength to 0.15 M, pH 7.4, KOH. Apparent free concentrations of Zn²⁺ in Tricine solution (Tricine calculated free) were calculated using the Solver function of the MaxChelator program (Patton et al., 2004). (B) Calibration of free Cu²⁺ concentrations in Tricine solution using 3 µM Mag-Fura-2. The addition of CuCl₂ led to a dose-dependent quenching of the fluorescent signal. Solver was used to calculate the apparent free concentration of Cu²⁺ in Tricine solution (Tricine calculated free).

Dorsal root ganglion (DRG) neurons

Acutely dissociated DRG cells were prepared from adolescent (60–150 g, 3–8-wk-old) Sprague Dawley rats as described previously (Todorovic and Lingle, 1998; Nelson et al., 2005). Cells were plated onto uncoated glass coverslips and incubated for 30 min at room temperature. Before the experiments, coverslips were incubated for 10 min in the Tyrode’s solution supplemented with 10 µg/ml IB₄ conjugated to green FITC (Sigma-Aldrich) and subsequently rinsed three times with the external solution. All experiments were performed at room temperature. Currents were recorded using the following external and internal solutions (in mM): 125 NaCl, 20 TEA-Cl, 3 KCl, 2 MgCl₂, 5 BaCl₂, 4 4-AP, and 10 HEPES or Tricine, pH 7.4 with HCl, and 125 CsCl, 10 BAPTA, 2 CaCl₂, 1 MgCl₂, 4 Mg-ATP, 0.3 Li-GDPβ_S, and 10 HEPES, pH 7.2 with CsOH, respectively. The recording chamber was constantly perfused with the extracellular solution at 1 ml/min. To isolate R-type current, the external solution was supplemented with the following blockers: 1.5 µM ω-conotoxin MVIIC, 0.1 µM ω-conotoxin-GVIA, 0.05 µM ω-agatoxin IVA, 10 µM nimodipine, and 0.5 µM TTA-P2 in 0.1 mg/ml cytochrome c.

Currents in these cells were measured at room temperature (∼22°C) using MultiClamp 700B amplifier, Digidata 1322A, and pClamp 9.2 software (Molecular Devices). Data were filtered at 2 kHz and digitized at 5 kHz. Access resistance was in the range of 5 to 10 MΩ. Series resistance was 50–60% compensated. Membrane capacitance and leak current were compensated using the P/5 on-line leak subtraction procedure.

Human embryonic kidney (HEK) cells

HEK-293 cells (CRL-1573; American Type Culture Collection) were grown in DMEM/F-12 (Invitrogen) supplemented with 10% fetal calf serum, 100 U/ml penicillin G, and 0.1 mg/ml streptomycin. Cells were transiently transfected with plasmid DNAs encoding Ca_v2.3d (Schneider et al., 1994), Ca_v2.2 or mutants (1 µg), human β2a (1 µg; available from GenBank/EMBL/DDBJ under accession no. AF423189), rabbit α₂δ1 (1 µg), and green fluorescent protein (GFP; 0.25 µg; pGreen Lantern; Invitrogen), or Ca_v3.2 (3 µg) and GFP (0.25 µg) using JET-PEI (MP Biomedicals). GFP⁺ cells were recorded 24–48 h after transfection.

Electrophysiological experiments were performed using the conventional patch-clamp technique in the whole cell configuration. Currents were recorded at room temperature (∼22°C) using MultiClamp 700B amplifier with Digidata 1322A and pClamp 9.2 software (Molecular Devices). Data were filtered at 2 kHz and digitized at 5 kHz. Access resistance and cell capacitance were measured using the built-in Clampex Membrane Test function. The average access resistance was around 4 MΩ. Data from cells where the access resistance exceeded 5.5 MΩ were discarded. Series resistance was constantly monitored and compensated between protocols to 70% (prediction and correction; 10-µs lag), resulting in maximal residual voltage error below 1.6 mV during measurement of the I-V relationship. In experiments where gating currents were measured, data were filtered at 10 kHz (−3 dB, four-pole Bessel) and digitized at 50–100 kHz, and P/−8 protocol was applied for leak and capacitance compensation. Currents were recorded using the following external solutions (in mM): 1 (or 5) CaCl₂, 171 (or 166) TEA-Cl, and either 10 HEPES or Tricine, pH adjusted to 7.4 with TEA-OH. Pipettes for recordings (2–3 MΩ) were filled with internal solution of the following composition (in mM): 125 CsCl, 10 BAPTA, 2 CaCl₂, 1 MgCl₂, 4 Mg-ATP, 0.3 Li-GDPβ_S, and 10 HEPES, pH adjusted to 7.2 with CsOH. The recording chamber was constantly perfused with the extracellular solution at 1 ml/min. The complete solution exchange was achieved in ∼40–60 s; therefore, the apparent on-rates are dominated by bath exchange.

Data analysis and statistics

Data were analyzed using Clampfit 9.2 (Molecular Devices), MS Excel 2007 (Microsoft), and Prism 5.01 (GraphPad). Smooth curves in the figures represent fits to the average data, whereas the mean values in the table were calculated from fits to individual cells. Data are reported as the mean ± SEM. We used either one-way ANOVA, to compare multiple mean values, or a paired Student’s t test when evaluating the effect of acute application of Tricine or trace metals. The voltage dependence of activation (m_∞; midpoint, V_1/2; slope, k) was determined by fitting the peak I-V data from each cell with a Boltzmann-Goldman–Hodgkin–Katz (GHK) equation:

$$I(V,C{a}_i,C{a}_o)=\frac{P_{Ca}{Z}_{Ca}^2{F}^{2}V}{RT}\frac{(C{a}_i-C{a}_o)\exp (-Z_{Ca}FV/RT)}{1-\exp (-Z_{Ca}FV/RT)}\frac{1}{1+\exp \left[\right(V_{1/2}-V)/k]},$$ (1)

where P_Ca is the permeability to calcium ions (cm/s), Z is their valence (2), F is the Faraday constant, R is the gas constant, T is the temperature (K), V is the test potential (V), and Ca_i and Ca_o are the intracellular and extracellular concentrations of Ca²⁺ (M), respectively. For display purposes, the voltage dependence of activation was calculated as the ratio of peak current amplitudes (I) observed at each voltage to the instantaneous value calculated with the GHK equation (I_GHK), and then fit with the Boltzmann equation. Level of steady-state inactivation at different voltages was calculated as a ratio of currents (I/I_max) measured at +30 mV after 15-s-long conditioning prepulses.

Reagents

Solutions were prepared at the time of the experiments from fresh stocks in distilled water (in mM): 250 CuCl₂, 250 ZnCl₂, 500 diethylenetriamine pentaacetic acid (DTPA), 10 Glu, and 10 Gly. All chemicals were purchased from either Thermo Fisher Scientific or Sigma-Aldrich.

RESULTS

Excitatory amino acids modulate gating of Ca_v2.3 channels acting as trace metal chelators

Although Glu is well known as an excitatory neurotransmitter in the brain, its ability to serve as a trace metal chelator is often neglected (pK_a 5.5 and 7.9 for Zn²⁺ and Cu²⁺, respectively; Dawson et al., 1986). Studying the effect of Glu on calcium channels, we revealed that Glu can profoundly modulate gating of Ca_v2.3 calcium channels, by acting as a chelator (Fig. 1). Supplementation of a standard HEPES-based bath solution with 200 µM Glu led to the significant potentiation of Ca²⁺ currents measured at negative voltages and an ∼15-mV leftward shift of the I-V relationship (Fig. 1, A and B). The maximal increase in current amplitude (4.4-fold) was detected in the range of potentials from −20 to 0 mV and gradually decreased with further depolarization (Fig. 1 C). A similar effect on Ca_v2.3 was recorded upon the application of either 200 µM Gly or 100 µM DTPA in the HEPES bath solution and after substitution of HEPES with Tricine (10 mM; Fig. 1 D). Consistent with its action as a chelator, the effect of Glu was fast, reversible, and abolished by concomitant application of 100 µM DTPA (Fig. 1 E). Because Glu can also modulate the activity of Ca_v2.3 calcium channels indirectly through G protein–coupled receptors (Stea et al., 1995), we used Tricine, which possesses similar chelating properties, to isolate and study the chelation effect of Glu (Fig. 2). As with Glu, Tricine replacement for HEPES produced a strong stimulation of current at negative voltages (5.2-fold at −20 mV; Fig. 2, A–C). Upon Tricine application, activation gating of Ca_v2.3 channels was substantially shifted to more negative potentials (Fig. 2 D and Table 1), with no significant effect on either currents recorded at positive voltages or permeability (P_Ca) (Fig. 2 B and Table 1), and a moderate effect on kinetics of inactivation (Fig. 2 E and Table 1) and steady-state inactivation (Fig. 2 F and Table 1).

Figure 1.

Neurotransmitter amino acids potentiate current through Ca_v2.3 channels by acting as trace metal chelators. (A) Representative current traces recorded in response to the I-V protocol (V_hold = −90 mV; depolarizations to −15, −10, −5, 0, 10, and 20 mV) in a standard HEPES-buffered solution, containing 5 mM Ca²⁺ as a charge carrier, before (a) and after the addition of 200 µM Glu (b). Highlighted current traces elicited in response to 0-mV voltage step. (B) Normalized peak current I-V relationships measured in control HEPES and Glu-containing solutions. Data from each cell were fitted with GHK Eq. 1 (HEPES: V_1/2 = 19.4 ± 1.9 and k = 7.4 ± 0.2 mV; Glu: V_1/2 = 5.4 ± 2.0 and k = 5.9 ± 0.3 mV; **, P < 0.001 by paired Student’s t test for both parameters; n = 5). (C) Voltage dependence of the potentiating effect of Glu on Ca_v2.3. Ratio of peak current amplitudes (I_Glu/I_HEPES) at each potential plotted as a function of potential. (D) Potentiating effect of 200 µM Glu (n = 5), 200 µM Gly (n = 4), 100 µM DTPA (n = 11), and 10 mM Tricine (n = 8) on Ca_v2.3 currents elicited by the test pulses to −15–0 mV (***, P < 0.0001 by one-way ANOVA). (E) Time course of changes in the peak current amplitude induced by the sequential application of the indicated solutions measured at −20 mV. Note that the effect of Glu on Ca_v2.3 is abolished by coapplication of DTPA.

Figure 2.

Tricine selectively affects the activation gating of Ca_v2.3. (A) Representative current traces recorded in response to the I-V protocol (V_hold = −90 mV; depolarizing pulses from −30 to +10 mV) in HEPES (a) and Tricine solutions (b) containing 1 mM Ca²⁺ as a charge carrier. Highlighted current traces recorded in response to a −10-mV voltage step. (B) Peak current I-V relationships obtained in HEPES- or Tricine-based extracellular solutions. Data were fitted with GHK Eq. 1 (Table 1). (C) Voltage dependence of the effect of Tricine on Ca_v2.3. Ratio of peak current amplitudes (I_Tricine/I_HEPES) at each potential plotted as a function of potential. (D) Voltage dependence of activation of Ca_v2.3 measured in HEPES- and Tricine-based extracellular solutions. (E) Normalized and averaged Ca²⁺ currents ± SEM (shaded area) recorded in response to prolonged (3-s) depolarizing pulse to −10 mV in HEPES and Tricine solutions. Recordings were fitted with double-exponential function: I(t) = A_f exp(−t/τ_f) + A_s exp(−t/τ_s) + C. Corresponding values and statistics are in Table 1. (F) Steady-state inactivation curves, measured at +30 mV after 15-s-long conditioning prepulses.

Table 1.

Biophysical properties

Solution	Activation				Inactivation			Kinetics
Cav2.3 WT	PCa(max) ± SEM	V1/2 ± SEM	k ± SEM	n	V1/2 ± SEM	k ± SEM	n	Af ± SEM	τf ± SEM	As ± SEM	τs ± SEM	n
HEPES	0.011 ± 0.003	1.5 ± 1.0a	7.2 ± 0.1a	8	−36.1 ± 1.1b	8.9 ± 0.2	8	−0.24 ± 0.05b	0.17 ± 0.02	−0.59 ± 0.04	1.5 ± 0.2	6
Tricine	0.010 ± 0.002	−15.6 ± 1.8	5.3 ± 0.2	12	−40.2 ± 1.2	8.2 ± 0.3	11	−0.38 ± 0.03	0.13 ± 0.01	−0.44 ± 0.02	1.2 ± 0.1	6
Zn 7 µM	0.005 ± 0.001	−2.4 ± 2.9a	7.1 ± 0.1a	4	−30.4 ± 1.8a	9.8 ± 0.5	6	−0.14 ± 0.01a	0.33 ± 0.08	−0.52 ± 0.06	2.4 ± 0.6	6
Cu 205 nM	0.007 ± 0.002	2.9 ± 1.2a	7.4 ± 0.1a	6	−26.8 ± 1.2a	9.7 ± 0.8	6	−0.18 ± 0.04a	0.21 ± 0.08	−0.48 ± 0.04	3.1 ± 0.4b	6
H179E/H181A
HEPES	0.010 ± 0.002	−12.7 ± 1.0	5.0 ± 0.2	7	−42.9 ± 1.8	9.1 ± 0.4	6	−0.32 ± 0.04	0.14 ± 0.02	−0.59 ± 0.04	1.3 ± 0.1	5
Tricine	0.010 ± 0.001	−12.1 ± 1.1	5.2 ± 0.2	13	−41.2 ± 1.3	8.4 ± 0.2	8	−0.34 ± 0.03	0.14 ± 0.01	−0.55 ± 0.02	1.2 ± 0.1	5
Zn 7 µM	0.008 ± 0.002	−9.4 ± 0.9	6.0 ± 0.3	5	−36.0 ± 2.4	9.2 ± 0.8	4	−0.31 ± 0.04	0.23 ± 0.11	−0.65 ± 0.17	2.8 ± 1.1	3
Cu 205 nM	0.009 ± 0.002	−8.6 ± 1.9	5.6 ± 0.2	8	−37.2 ± 1.1	8.0 ± 0.4	6	−0.33 ± 0.02	0.20 ± 0.06	−0.64 ± 0.12	2.4 ± 0.7	5

All parameters were calculated for each cell and then averaged. Statistically significant differences are noted with footnotes and are by one-way ANOVA, compared to the values obtained in Tricine:

^aP < 0.001.

^bP < 0.5.

We tested the specificity of the effect of trace metal chelators on activation gating of Ca_v2.3 by measuring the effect of Tricine on Ca_v2.2 and Ca_v3.2 channels (Fig. 3). The substitution of Tricine for HEPES produced no effect on either amplitude or voltage dependence of Ca_v2.2 (Fig. 3, A–C). However, it significantly stimulated the amplitude of Ca_v3.2 currents at all tested potentials, with no effect on activation gating (Fig. 3, D–F), similar to what was reported previously by Nelson et al. (2007a). This suggests that the effect of trace metals on activation gating is specific for Ca_v2.3 channels. Interestingly, results of these experiments also revealed the mid-voltage–activated nature of Ca_v2.3 channels (V_1/2 = −15.6 ± 1.8 mV; Fig. 2 B), as under identical recording conditions (1 mM Ca²⁺ as charge carrier in 10 mM Tricine), Ca_v3.2 and Ca_v2.2 channels activated at more negative (V_1/2 = −48.7 ± 1.2 mV; Fig. 3 F) and at more positive (V_1/2 = −3.8 ± 0.9 mV; Fig. 3 C) membrane potentials, respectively.

Figure 3.

Tricine substitution for HEPES produces no effect on activation gating of Ca_v2.2 and Ca_v3.2 cannels. (A and D) Representative Ca_v2.2 (A) and Ca_v3.2 (B) currents recorded at +5 and −30 mV, respectively, in HEPES and Tricine solutions. (B and E) Normalized ratios of peak current amplitudes for Ca_v2.2 (B; n = 6) and Ca_v3.2 (E; n = 9) channels. (C and F) Normalized and averaged I-V relationships measured in HEPES and Tricine solutions for Ca_v2.2 (C; n = 6) and Ca_v3.2 (B) channels. Data acquired from each cell were fitted with GHK Eq. 1 (Ca_v2.2: HEPES V_1/2 = −1.8 ± 1.0 and k = 4.5 ± 0.2 mV; Tricine V_1/2 = −3.8 ± 0.9 and k = 4.6 ± 0.2 mV; n = 6; and Ca_v3.2: HEPES V_1/2 = −47.4 ± 1.7 and k = 6.1 ± 0.2 mV; Tricine V_1/2 = −48.7 ± 1.2 and k = 6.0 ± 0.3 mV; n = 4).

It was shown that Tricine efficiently chelates Zn²⁺ in the concentration range from 1 nM to 1 µM, with an empirically estimated K_d of ∼10⁻⁵ M (Paoletti et al., 1997). Additionally, Tricine is a derivate of Gly (N-Tris(hydroxymethyl)methylglycine), which can bind Cu²⁺ with even higher affinity than Zn²⁺ (K_d of 10^−8.1 M vs. 10⁻⁵ M, respectively; Dawson et al., 1986). This suggests that excitatory amino acids and Tricine could exert their effect on Ca_v2.3 by chelating trace amounts of Zn²⁺ and/or Cu²⁺, which commonly reside in normal bath solutions (Kay, 2004). Indeed, the direct addition of 100 µM Zn²⁺ or Cu²⁺, but not Fe²⁺, to the Tricine-based extracellular solution substantially suppressed currents at negative potentials (not depicted). To study the mechanisms responsible for modulation of Ca_v2.3 calcium channels by trace metals and their chelators, we calibrated free concentrations of Cu²⁺ and Zn²⁺ in Tricine-containing solution using fluorescent dyes Newport Green DCF (Fig. 4 A) and Mag-Fura-2 (Fig. 4 B). These dyes were selected based on their micromolar affinity for Zn²⁺ and Cu²⁺, but low affinity for Ca²⁺ (Haugland, 2005). Free concentrations of Zn²⁺ and Cu²⁺ in Tricine were deduced by comparing the fluorescent signals measured in the absence of trace metal chelators to those obtained in 10 mM Tricine (Fig. 4). From these values, we deduced the K_d for copper and zinc binding to Tricine, and then used the program MaxChelator (http://maxchelator.stanford.edu) to deduce free ion concentrations under a variety of conditions (Table 2).

Table 2.

Free concentrations of Zn²⁺ and Cu²⁺ in 10 mM Tricine

Zn2+	Added, µM	9.7	100	900
	Free, µM	0.08	0.8	8
Cu2+	Added, µM	30	100	269	616	1,100
	Free, nM	13	45	123	293	551

Free concentrations were calculated using the Solver function in the MaxChelator program. Calculations took into account the presence of 1 mM Ca²⁺, ionic strength (0.15 M), and pH (7.4).

We next assessed the effects of calibrated Zn²⁺ and Cu²⁺ concentrations on gating and conductance of Ca_v2.3. To dissociate these two processes, we measured alterations in current amplitudes at −20 and +20 mV, respectively (Fig. 5 A). Changes in the current amplitude measured at +20 largely reflect the effect on conductance, as maximal activation of Ca_v2.3 was achieved at about +20 mV (Fig. 2). On the other hand, changes at −20 mV (∼V_1/2) are primarily associated with the effect on open probability (activation gating), as HEPES to Tricine substitution produced no effect on the channel’s permeability. Both cations exerted approximately 10-fold stronger effects on gating than on conductance of Ca_v2.3 (Fig. 5, B and C). As a result of this sensitivity pattern, zinc and copper profoundly shifted the voltage dependence of activation of Ca_v2.3 toward more positive values (Fig. 5 D and Table 1), also producing a moderate effect on kinetics of inactivation (Table 1) and steady-state inactivation (Fig. 5 E and Table 1). Although gating effects of both trace metals were qualitatively similar, copper was ∼100 times more potent at inhibiting currents at −20 mV than zinc (IC₅₀ = 18.0 ± 0.4 nM; n = 8 vs. 1,300 ± 0.4 nM; n = 6; Fig. 5 B). While studying the effects of Zn²⁺ and Cu²⁺ on the current through Ca_v2.3 channels (Fig. 6), we also noticed that copper almost completely recapitulated the slow kinetics of current activation/inactivation observed in HEPES solution (Fig. 6, A and C), whereas Zn²⁺ failed to reproduce it at any tested concentration (Fig. 6, B and C).

Figure 5.

The effects of calibrated Zn²⁺ and Cu²⁺ concentrations on Ca_v2.3. (A, a) Representative current traces measured in response to a double-pulse protocol (depicted above) in Tricine- and copper-containing solutions. Copper concentrations at which currents were recorded are indicated in (b). (b and c) Time course of the effect of various Cu²⁺ concentrations on the amplitude of Ca²⁺ currents through Ca_v2.3, measured at −20 mV (b) and 20 mV (c). (B) Dose–response curves of the effect of Zn²⁺ and Cu²⁺ on gating of Ca_v2.3. Smooth lines represent the fit to the average data with the Hill equation (Zn²⁺: IC₅₀ = 1.3 ± 0.2 µM and n_H = 1.2; n = 6; and Cu²⁺: IC₅₀ = 18.2 ± 3.7 nM and n_H = 0.7; n = 8). (C) Dose–response curves of the effect of Zn²⁺ and Cu²⁺ on conductance of Ca_v2.3. Smooth lines represent the fit to the average data with the Hill equation (Zn²⁺: IC₅₀ = 8.1 ± 1.4 µM and n_H = 0.60; n = 6; and Cu²⁺: IC₅₀ = 269 ± 101 nM and n_H = 0.5; n = 8). (D and E) Voltage dependence of activation (D) and steady-state inactivation curves (E), measured in Tricine solution and solutions containing either 8 µM Zn²⁺ or 293 nM Cu²⁺. Data were fitted with a Boltzmann equation (Table 1).

Figure 6.

Distinct effects of Cu²⁺ and Zn²⁺ on kinetics of Ca_v2.3 currents. (A and B) Representative current recordings obtained in response to a depolarizing pulse to +10 mV (V_hold = −90 mV) in HEPES, Tricine, and Cu²⁺- or Zn²⁺-containing extracellular solutions. (C) Normalized and averaged current recordings (n = 5).

Finally, we tested the effect of low Cu²⁺ concentration on endogenous residual Ca²⁺ current (R-type; Birnbaumer et al., 1994; Randall and Tsien, 1995), which is believed to be the product of Ca_v2.3 channel activity (Schneider et al., 1994; Piedras-Rentería and Tsien, 1998). We recorded IB4-negative (−), medium-sized DRG neurons (Fig. 7 A), which were shown to express SNX-482 sensitive R-type channels (Fang et al., 2007). R-type current was isolated by the bath perfusion of the blocker cocktail until a steady level was achieved (Fig. 7 B), comprising ∼30% of the initial net calcium current measured at +20 mV (Fig. 7 C). Recapitulating the results with the recombinant channel, the application of 45 nM Cu²⁺ shifted the I-V curve of native channels to more depolarized voltages, producing almost no effect on the amplitude of current measured at positive potentials (Fig. 7, D–F).

Figure 7.

Copper at low concentrations modulates the activation gating of residual (R-type) calcium current in DRG neurons. (A) Bright field and fluorescence images of IB4-positive (+) and IB4-negative (−) DRG neurons, identified by live staining with 10 µg/ml IB4-FITC (Sigma-Aldrich). Bar, 10 µm. (B) Time course of changes in the amplitude of the net Ba²⁺ current through VGCC, recorded from an IB4 (−) neuron in response to a 20-mV voltage step, induced by perfusion of recording chamber with the cocktail of Ca²⁺ channel blockers. (C) In IB4 (−) DRG neurons, ∼30% of the net current at +20 mV is carried through R-type calcium channels (n = 4). (D) Examples of recordings of isolated R-type calcium currents, measured in response to the I-V protocol (V_hold = −90 mV, depolarizations to −30, −20, −10, 0, 10, and 20 mV) in Tricine- and Cu²⁺-containing solutions with 5 mM Ba²⁺ as a charge carrier. (E) Normalized peak current I-V relationships. Data were fit with the standard Boltzmann-Ohm equation (Tricine: V_1/2 = 3.1 ± 4.9 and k = 6.6 ± 1.3 mV; Cu²⁺: V_1/2 = 7.8 ± 3.9* and k = 6.6 ± 1.3 mV; *, P = 0.026 by paired Student’s t test; n = 4). (F) The voltage dependence of the Cu²⁺ effect on endogenous R-type current in DRG neurons. The ratio of peak current amplitudes (I_Tricine/I_Cu) at each potential was plotted as a function of potential.

Collectively, these results suggest that voltage-dependent gating of Ca_v2.3 channels is highly sensitive to trace metals. Copper is a more effective modulator of gating than zinc. Glu and Gly profoundly modulate activity of these channels, acting as trace metal chelators.

Molecular basis of Glu and trace metal sensitivity in Ca_v2.3

Inhibition of Ca_v3.2 channels by transition metals relies heavily on the histidine (H191) in the IS3–IS4 loop (Kang et al., 2006; Nelson et al., 2007a). Alignment of Ca_v2 and Ca_v3 channels reveals that Ca_v2.3 contains two histidines in the IS3–IS4 loop (H179 and H181), whereas Ca_v2.1 and Ca_v2.2 do not have any (Fig. 8 A). Additionally, it was shown that corresponding residues are responsible for the effect of Ni²⁺ on Ca_v2.3 (Kang et al., 2007). To determine whether these histidines are responsible for the effect of chelators and trace metals on Ca_v2.3, we substituted H179 with Glu (H179E), a negatively charged amino acid that resides in the corresponding position of Ca_v2.1, and H181 with alanine (H181A), a neutral amino acid residue (H179E/H181A; Fig. 8 A). As expected from the sequence similarity, the H179E/H181A mutant was completely insensitive to Tricine substitution for HEPES (Fig. 8, B–E). Notably, while in HEPES, H179E/H181A mutants opened in the same voltage range as Ca_v2.3 in Tricine solution (Table 1). Additionally, channels with either single–amino acid substitutions were similarly insensitive to 200 µM Gly, 200 µM Glu, or 100 µM DTPA (not depicted). Single mutants were approximately seven times less sensitive to copper (IC₅₀ = 142 and 115 nM for H183A and H179E, respectively), whereas channels with double substitution (H179E/H181A) demonstrated around 11-fold lower copper sensitivity (IC₅₀ = 203 nM) (Fig. 8 G).

Figure 8.

Histidines in the IS1–IS2 and IS3–IS4 loops underlie the trace metal sensitivity of Ca_v2.3. (A) Alignment of the putative amino acid residues residing in the IS1–IS2 and IS3–IS4 regions of Ca_v2 channels. Triple histidines, responsible for the trace metal sensitivity in Ca_v2.3 (highlighted), were identified by their sequential substitution: H111A/H179E/H181A. (B) Representative current traces recorded from Ca_v2.3 channels bearing the H179E/H181A mutation in response to the I-V protocol depicted above (V_hold = −90 mV, depolarizing pulses from −30 to 10 mV). Highlighted current traces were recorded in response to a −10-mV voltage pulse. (C) Peak current I-V relationships for H179E/H181A mutant obtained in HEPES- or Tricine-based extracellular solutions and normalized to cell capacitance. Data were fitted with GHK Eq. 1 (Table 1). (D) Normalized and averaged Ca²⁺ currents ± SEM (shaded area) recorded in response to prolonged (3-s) depolarizing pulse to −10 mV in HEPES and Tricine solutions. Recordings were fitted with double-exponential function. Corresponding values and statistics are in Table 1. (E) Steady-state inactivation curves for H179E/H181A mutant measured in the HEPES- or Tricine-based extracellular solutions. Data were fitted with a Boltzmann equation (Table 1). (F) Currents through H111A/H179E/H181A mutant channels, measured in response to the voltage pulse depicted above in Tricine- and Cu²⁺-containing solutions. (G) Dose–response curves of the Cu²⁺ effect on currents through Ca_v2.3 channels bearing various point mutations. Smooth lines represent the fit to the average data with the Hill equation (H179E: IC₅₀ = 115 ± 11 nM and n_H = 1.4; n = 4; H183A: IC₅₀ = 142 ± 19 nM and n_H = 1.4; n = 4; H179E/H183A: IC₅₀ = 203 ± 27 nM and n_H = 1.4; n = 9; and H111A: IC₅₀ = 205 ± 75 nM and n_H = 0.6; n = 5). (H) Mean values of inhibition induced by the application of 123 nM Cu²⁺ (***, P < 0.0001; **, P < 0.001; *, P < 0.05 by one-way ANOVA with Bonferroni posthoc correction).

Trace metal–binding amino acids in various ion channels are often scattered along the IS3–IS4 and IS1–IS2 putative extracellular loops (Kang et al., 2006, 2010; Ramsey et al., 2006; Nelson et al., 2007a; Ma et al., 2008). To probe the contribution of His111, residing in the IS1–1S2 loop of Ca_v2.3, we substituted it with alanine (H111A; Fig. 8 A). Apparent copper sensitivity again decreased (IC₅₀ = 205 nM; Fig. 8 G). Strikingly, mutation of all three histidine residues (H111A/H179E/H181A) renders channels practically insensitive to Cu²⁺ (Fig. 8, F–H).

Insights into the biophysical mechanisms of copper action

To gain further insight into the biophysics of copper action on gating of Ca_v2.3, we analyzed the time and voltage dependence of this process in 13 nM Cu²⁺, the concentration at which copper exhibited the effect only on activation gating of Ca_v2.3 (Fig. 9), but not on mutant channels (Fig. 8 G). At negative voltages, below −15 mV, the effect of copper was relatively time and voltage independent (∼40%); however, it diminished quickly (τ = 70–9 ms) at more depolarized voltages (Fig. 10, A and B). As a result, the effect of Cu²⁺ on Ca_v2.3, measured at the peak of current amplitude, was noticeably voltage dependent (Fig. 10 C), counter to the expectation that an extracellular inhibitor should exert a voltage-independent effect.

Figure 9.

Cu²⁺ at low concentrations produces “pure” effect on the activation gating of Ca_v2.3. (A) Tail currents recorded in Tricine- and Cu²⁺-containing solutions in response to the protocol depicted above. (B) Activation curves obtained from the measurements of the amplitudes of tail currents, normalized to the maximum amplitude of the tail current recorded in Tricine.

Figure 10.

Cu²⁺ affects gating of Ca_v2.3 through the extracellular binding site in a state-dependent manner. (A) Time dependence of the inhibitory effect of 13 nM Cu²⁺ on currents through Ca_v2.3 channels, induced by depolarization to −20 or 20 mV (a). The percentage of inhibition at each time point was calculated as a difference in current amplitudes measured in Tricine (black traces) and Cu²⁺ solutions (gray traces), divided by the amplitude in Tricine (b). (B) Voltage dependence of the kinetics of facilitation of Cu²⁺ inhibition. Time constants were determined from A by fitting time dependences with the monoexponential functions (n = 6). (C) Voltage dependence of the inhibition of current through Ca_v2.3 channels by 13 nM Cu²⁺. The percentage of inhibition at each voltage was calculated as a difference between peak current amplitudes measured in Tricine and Cu²⁺ solutions divided by the current amplitude in Tricine (n = 6). (D) Strong depolarization partially reverses the inhibitory effect of Cu²⁺ on Ca_v2.3. Current traces were recorded in response to the protocol depicted above in Tricine- (a) and Cu²⁺-containing (b) solutions (13 nM). (E) Quantification of the Cu²⁺ inhibition of Ca_v2.3 current, recorded before ((T₁−C₁)/T₁) or after ((T₂−C₂)/T₂) the delivery of a depolarizing pulse to 150 mV (n = 5; ***, P < 0.0001 with paired Student’s t test).

To test whether the given pattern of Cu²⁺ inhibition arises from intrinsic changes in the activation/inactivation kinetics of the channel or from state-dependent facilitation, akin to the effect of Gβγ subunit on VGCCs (Elmslie et al., 1990; Boland and Bean, 1993), we tested the effect of a strong depolarizing pulse (+150 mV) on Cu²⁺ inhibition (Fig. 10, D and E). The depolarizing pulse was first delivered in Tricine solution, where it induced an ∼10% decrease in current amplitude (T₂ vs. T₁; Fig. 10 D, a). Next, 13 nM Cu²⁺ was added to the extracellular solution and currents were recorded again. In the presence of Cu²⁺, the +150-mV prepulse completely restored the “fast” kinetics of current activation/inactivation (C₂ vs. C₁; Fig. 10 D, b) and alleviated ∼80% of the inhibition induced by Cu²⁺ (Fig. 10 E). These results suggest that Cu²⁺ induces the strongest effect on Ca_v2.3 when channels are closed; however, transition into an open state partially relieves this inhibition, producing a prominent slowing effect on the activation/inactivation kinetics.

Transition of voltage-gated channels between the closed and open states is associated with significant perturbations in voltage-sensor domains (S1–S4), manifested as gating current in electrophysiological experiments (Swartz, 2008). In K⁺ channels, it was shown that S1–S2 and S3–S4 loops are close to each other in the closed conformation, but move apart upon channel opening (Campos et al., 2007). Therefore, we tested whether Cu²⁺ produces its effects on Ca_v2.3 by affecting gating charge movement. We measured gating current in response to depolarization to the reversal membrane potentials (57 ± 2 mV; n = 7) (Fig. 11 A). Interestingly, the total gating charge displacement across the membrane field stayed the same (Fig. 11 B); however, the amplitude of the gating current and its decay time were significantly different (Fig. 11, C and D). Thus, in Tricine solution, the amplitude was significantly greater (490 ± 98 vs. 440 ± 87 pA), but the kinetics of decay was faster (0.13 ± 0.02 vs. 0.17 ± 0.03 ms). Accordingly, the Cu²⁺-induced positive shift in voltage dependence of Ca_v2.3 could emerge as a result of slower “ON” transitions of gating charges and a decreased fraction of channels open at a given potential.

Figure 11.

A low concentration of Cu²⁺ (13 nM) decelerates gating charge movement in Ca_v2.3. (A) Representative gating current traces (the average of 20 consecutive runs ± SD) recorded in response to the step depolarization to the reversal potential (V_r = 58 ± 2 mV; n = 8) in Tricine- (a and b) and Cu²⁺-containing (c) solutions (13 nM). (b and c) Enlarged view of the region selected with dashed lines on (a). (B) Maximal gating charges transferred across membrane in Tricine- and Cu²⁺-containing solutions (n = 7). (C) Amplitudes of the gating current transients recorded in Tricine- and Cu²⁺-containing solutions (*, P = 0.043, by paired Student’s t test; n = 7). (D) Time constants of the gating current transient decay measured in Tricine and Cu²⁺ solutions (*, P = 0.014, by paired Student’s t test; n = 7).

DISCUSSION

We show that neurotransmitters such as Glu and Gly and trace metals such as Zn²⁺ and Cu²⁺ profoundly modulate activity of Ca_v2.3 calcium channels by influencing their voltage-dependent gating. We identified a trace metal–binding site on the extracellular surface of the channel and demonstrated that, once bound there, trace metals decelerate the transition of gating charges into the “ON” position in response to membrane depolarization. This finding provides a new perspective on the role played by Glu and trace metals, both present within the synaptic clefts of many excitatory synapses, in synaptic transmission and plasticity.

Glu as a potent agonist for Ca_v2.3

Glu and its targets in the brain have been the subject of extensive investigation since their discovery. Once released from the presynaptic terminal, Glu rapidly finds its receptors on the pre-/postsynaptic membranes, conveying information between interconnected neurons. Glu concentration, its spatiotemporal profile, and the identity of the targets of the neurotransmitter are all of high importance for proper signal transduction in the brain. Here, we identified Ca_v2.3 channels as a new target for Glu. Glu substantially potentiated activity of these channels at hyperpolarized potentials by shifting their voltage-dependent activation curve toward more negative voltages (Fig. 1). Remarkably, the effect of Glu on Ca_v2.3 is mechanistically distinct from that reported previously (Stea et al., 1995), as this modulation does not rely on the recruitment of any intracellular cascades. Instead, Glu exerts its action on Ca_v2.3 from the extracellular side, by acting as a trace metal chelator. Although the ability of Glu to bind trace metals is well documented (Dawson et al., 1986), this role has mostly been neglected in the context of physiological experiments. Given that local transient concentration of Glu in the synaptic cleft can reach the millimolar range (Clements et al., 1992), all Glu-sensitive postsynaptic channels and receptors should be considered as potential targets. However, in contrast with Glu receptors, the sensitivity of Ca_v2.3 to Glu relies on the presence of trace metals in the extracellular milieu. Notably, the concentration of free or loosely bound Zn²⁺ and Cu²⁺ is elevated in the brain (Osterberg, 1980; Mathie et al., 2006), and the release of these metals from synaptic vesicles in a voltage- and Ca²⁺-dependent fashion has been detected with various techniques (Assaf and Chung, 1984; Howell et al., 1984; Hartter and Barnea, 1988; Kardos et al., 1989; Hopt et al., 2003; Frederickson et al., 2005).

The trace metal hypersensitivity of Ca_v2.3

The effect of transition metals, mostly zinc, on the activity of VGCCs was investigated previously in several studies (Nam and Hockberger, 1992; Büsselberg et al., 1994; Easaw et al., 1999; Castelli et al., 2003; Magistretti et al., 2003; Sun et al., 2007). It was shown that R-type calcium channels in cortical neurons are sensitive to micromolar concentrations of copper and zinc, which allosterically modulate the activation/deactivation kinetics of the channel (Castelli et al., 2003; Magistretti et al., 2003). Additionally, it was demonstrated that Ni²⁺ at a micromolar concentration inhibits Ca_v2.3 by shifting its gating to more depolarized voltages (Zamponi et al., 1996), and that the Ni²⁺-binding site also contains H179 and H181 at its core (Kang et al., 2007). Although Ca_v2.3 current that activates at relatively depolarized voltages and possesses relatively slow activation/inactivation kinetics has also been observed previously (Page et al., 1998; Jouvenceau et al., 2000), it has never before been reported that the trace amounts of metals that often contaminate extracellular solutions (Kay, 2004) exert a tonic inhibitory effect on Ca_v2.3 voltage-dependent gating. Based on the positions of I-V curve and current kinetics in the presence of various Zn²⁺ and Cu²⁺ concentrations (Fig. 6), we estimated that our HEPES–TEA solution contains ∼50 nM Cu²⁺, which is responsible for the 17-mV negative shift in the activation curve observed upon substitution of HEPES for Tricine. Interestingly, this substitution also accelerated current inactivation kinetics (Fig. 2 E). These effects are similar to what was previously observed after the removal of Gβγ inhibition of Ca_v2 channels (Tedford and Zamponi, 2006). Thus, they might also be a consequence of the slowed activation gating induced by trace metals, as Gβγ activity was suppressed by the presence of GDPβ_S in the internal solution.

Various ion channels including Glu, Gly, GABA_A, acetylcholine, P2X receptors, and Na⁺ (Na_v1.5), K⁺ (K2P, K_v1.3, mSlo1), and Ca²⁺ (Ca_v3.2) channels (Mathie et al., 2006; Traboulsie et al., 2007; Ma et al., 2008) were reported to be sensitive toward zinc and copper at concentrations below 10 µM. However, only NMDA receptors and Ca_v3.2 calcium channels could be tonically blocked by trace amounts of zinc (Paoletti et al., 1997; Nelson et al., 2007b). Our study identifies Ca_v2.3 as the most sensitive target of copper among other channels and receptors (NMDAR: IC₅₀ = 270 nM [Vlachová et al., 1996]; Ca_v3.2: IC₅₀ = 900 nM [Jeong et al., 2003]). To reveal this trace metal hypersensitivity, we followed the approach originally proposed by Paoletti et al. (1997) and used Tricine to chelate contaminating trace metals in our extracellular solution. Furthermore, we used fluorescent dyes to calibrate free concentrations of Zn²⁺ and Cu²⁺ in the Tricine solution. Thus, we discovered that relatively low concentrations of Zn²⁺ and Cu²⁺ (IC₅₀ = 1,300 and 18 nM, respectively) profoundly modulate the activity of Ca_v2.3.

Putative mechanism of copper interaction with Ca_v2.3

To describe the molecular mechanism likely responsible for copper modulation of Ca_v2.3 gating, we produced a model (Fig. 12) that summarizes our results in the context of what is known about the open and closed conformations of voltage-gated channels in general (Swartz, 2008). In a closed conformation, the top portions of the S4 and S1–S2 segments reside in close proximity to each other (Chanda et al., 2005; Campos et al., 2007), such that H111, H179, and H183 residues form a high affinity binding site for trace metals (Fig. 12 A). However, changes in the electric field can induce a translocation of S4 into a second position (Long et al., 2007) and break this binding pocket (Fig. 12 B). Remarkably, a high affinity binding site for trace metals consisting of three histidines is found in a variety of natural proteins and can be artificially introduced into a four-helix bundle protein, by placing two histidines on one helix as His–X₃–His and the third on an adjacent helix (Regan, 1993). Thus, trace metals bind to the IS1–IS4 gating module of Ca_v2.3 in a state-dependent manner and, once bound, decelerate “ON” transitions of gating charges. This modulatory action should decrease the fraction of channels open at a given potential, inducing a positive shift of voltage dependence and slowing the activation kinetics of the current.

Figure 12.

Putative model of Cu²⁺ interaction with the gating machinery of Ca_v2.3. Residues responsible for Cu²⁺ binding in Ca_v2.3 (H111, H179, and H183) were mapped onto the structural model of a voltage-gated potassium channel (Chanda et al., 2005; Campos et al., 2007). Only the S1–S4 segments from the first domain are shown. (A) In closed conformation, histidines of IS1–IS2 and IS3–IS4 loops of Ca_v2.3 are situated close to each other and can bind Cu²⁺ if it is present in the solution. The green sphere illustrates a possible position for Cu²⁺. (B) Upon channel opening, histidines are moved apart by the gating machinery, which apparently disrupts the binding pocket and releases Cu²⁺ from the binding site.

Our hypothetical model is supported by the following observations. First, trace metals selectively modulate voltage-dependent gating of Ca_v2.3, inducing almost no effect on conductance (Table 1). Second, key amino acid residues (H111, H179, and H183) responsible for trace metal binding in Ca_v2.3 reside within the gating module on the extracellular side of the channel (Fig. 8). Third, a high level of inhibition by trace metals was detected for channels in the closed state, whereas a reduction in inhibition was seen upon activation/inactivation (Fig. 10, A–C). Fourth, a significant percentage of inhibition was reversed by a strong depolarizing prepulse, which brings voltage sensors into an open-state position (Fig. 10, D and E). Finally, copper decelerates the transition of gating charges into the “ON” state, rendering the total charge translocation unaffected (Fig. 11).

The presence of a trace metal–binding site within a gating module seems to be a common feature of various voltage-gated channels, including Hv1 (Ramsey et al., 2006), Cav3.2 (Kang et al., 2006; Nelson et al., 2007a), and Slo1 (Ma et al., 2008). Whereas in Hv1 and Cav3.2 His has also been identified at the core of the trace metal–binding site, in Slo1 channels, a copper-binding site with lower affinity (2 µM) is formed by charged amino acid residues. This suggests a common conservative conformation of the closed state across the family of voltage-gated channels.

Physiological implication

Although Ca_v2.3 channels are implicated in several vital physiological processes, arguably the most prominent roles attributed to these channels are to trigger presynaptic LTP at mossy fiber–CA3 synapses (Breustedt et al., 2003; Dietrich et al., 2003) and to regulate membrane depolarization and Ca²⁺ influx in the dendritic spines of CA1 pyramidal neurons (Bloodgood and Sabatini, 2007). LTP at mossy fiber synapses is thought to rely mostly on presynaptic changes after tetanic stimulation (Nicoll and Schmitz, 2005). Two studies have revealed the critical involvement of presynaptic Ca_v2.3 calcium channels in the induction, but not expression, of this form of synaptic plasticity (Breustedt et al., 2003; Dietrich et al., 2003). Notably, it was shown that Ca²⁺ influx through these channels substantially increases in response to AP series, whereas the application of 100 µM Ni²⁺ depresses LTP induction. Based on our findings, we can speculate that Glu released during tetanic stimulation acts as a chelator on presynaptic Ca_v2.3 channels, abrogating their tonic inhibition by trace metals and thereby potentiating Ca²⁺ entry into the mossy fiber terminal through these channels.

R-type calcium channels on the dendritic spines of CA1 pyramidal neurons are involved in a negative feedback loop that regulates NMDAR activity (Bloodgood and Sabatini, 2007; Giessel and Sabatini, 2010). It was shown that these channels can be activated not only in response to back-propagating AP but also upon stimulation of a single spine with uncaged Glu. R-type channels consequently provide an important route for Ca²⁺ entrance into the spine, reducing the amplitude of EPSP and depressing NMDAR activity. Nevertheless, it is unclear how R-type Ca²⁺ channels can be activated by a single transient EPSC with average amplitude of <1 mV measured at the soma. Our findings provide a possible answer for this question. Taking into consideration the high concentration of Glu in the synaptic cleft, we suggest that Glu chelation of trace metals shifts the activation of Ca_v2.3 channels sufficiently to allow them to open in response to a small membrane depolarization.