A rich conformational palette underlies human CaV2.1-channel availability

Wang, Kaiqian; Nilsson, Michelle; Angelini, Marina; Olcese, Riccardo; Elinder, Fredrik; Pantazis, Antonios

doi:10.1038/s41467-025-58884-2

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Published: 23 April 2025

A rich conformational palette underlies human Ca_V2.1-channel availability

Nature Communications volume 16, Article number: 3815 (2025) Cite this article

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Abstract

Depolarization-evoked opening of Ca_V2.1 (P/Q-type) Ca²⁺-channels triggers neurotransmitter release, while voltage-dependent inactivation (VDI) limits channel availability to open, contributing to synaptic plasticity. The mechanism of Ca_V2.1 response to voltage is unclear. Using voltage-clamp fluorometry and kinetic modeling, we optically track and physically characterize the structural dynamics of the four Ca_V2.1 voltage-sensor domains (VSDs). The VSDs are differentially sensitive to voltage changes, both brief and long-lived. VSD-I seems to directly drive opening and convert between two modes of function, associated with VDI. VSD-II is apparently voltage-insensitive. VSD-III and VSD-IV sense more negative voltages and undergo voltage-dependent conversion uncorrelated with VDI. Auxiliary β-subunits regulate VSD-I-to-pore coupling and VSD conversion kinetics. Hence, the central role of Ca_V2.1 channels in synaptic release, and their contribution to plasticity, memory formation and learning, can arise from the voltage-dependent conformational changes of VSD-I.

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Introduction

The Ca_V2.1, or P/Q-type, voltage-gated Ca²⁺ channel, is the predominant Ca_V subtype in the brain, and it plays a crucial role in synaptic transmission^{1,2,3,4,5,6,7,8}. Presynaptic Ca_V2.1 channels convert an electrical signal (action potentials) into a biochemical signal (Ca²⁺ entry), triggering neurotransmitter release (Fig. 1a). A prolonged depolarization or train of action potentials cause Ca_V2.1 voltage-dependent inactivation (VDI)^9,10. During VDI, channels enter a non-conductive state and are not available to mediate Ca²⁺ influx. This contributes to short-term depression, a form of synaptic plasticity that affects informational encoding^11,12,13,14 (Fig. 1b). Ca_V2.1 channels can also undergo voltage-dependent facilitation, which depends on direct channel regulation mediated by neurotransmitters’ action on GPCR and activating G-proteins⁹. Postsynaptic Ca_V2.1 channels generate depolarization-induced local Ca²⁺ transients and are implicated in long-term depression, which underlies cerebellar learning^4,15. Mutational studies in mice suggest a role of Ca_V2.1 in synaptic plasticity, spatial learning, and memory; while variants of CACNA1A, the gene encoding the Ca_V2.1 pore-forming subunit α_1A, are associated with serious neurological disease^16,17,18.

**Fig. 1: Ca_V2.1 function and consequences of inactivation, its pore-forming subunit, and its four non-identical VSDs.**

Ca_V2.1 channels consist of the transmembrane α_1A-subunit, extracellular α₂δ-subunit, and intracellular β-subunits^7,8. Channel voltage regulation stems from voltage-dependent conformational changes in the α_1A voltage-sensing apparatus^19,20. This comprises four transmembrane, homologous but non-identical, voltage-sensor domains (VSDs; Fig. 1c–e), but their roles in voltage-dependent activation and inactivation were not previously studied. Because Ca_V2.1 has four different VSDs, it is possible that each VSD serves different functions to drive neurosecretion and contribute to synaptic plasticity. We have reported such functional heterogeneity among the VSDs of L-type (Ca_V1.1, Ca_V1.2)^21,22,23 and N-type (Ca_V2.2)²⁴ channels.

Here, we optically track the voltage-dependent movements of the individual Ca_V2.1 VSDs under physiologically-relevant conditions by combining the cut-open oocyte vaseline gap voltage clamp^25,26,27 with voltage-clamp fluorometry (VCF)^{27,28,29,30,31}. By “physiologically relevant conditions”, we mean an in-cellula study of the human, conducting, Ca_V2.1 pore-forming isoform, reconstituted with essential auxiliary subunits. We find that each VSD has a different response to brief depolarizations and long-term changes in the holding potential, which is tuned by Ca_Vβ auxiliary subunits. This predicts channel populations with a highly diversified set of VSD conformations, especially near resting voltages relevant to neuronal physiology. The stark exception is VSD-II, which appears to be unresponsive to voltage changes. Our results suggest that activation of the first Ca_V2.1 voltage-sensor domain (VSD-I) drives excitation-evoked presynaptic Ca²⁺ influx. In addition, conversion of VSD-I into a form not compatible with channel opening determines channel availability to conduct and thus underpins VDI—a form of molecular memory that contributes to memory formation and learning in the brain.

Results

Ca_V2.1 VSDs activate with distinct voltage dependencies

To optically track the movements of individual VSDs under physiologically relevant conditions, we used VCF. Briefly, specific amino-acid residues at the extracellular loop between the S3 and S4 transmembrane helices of each repeat were mutated to cysteine (Fig. 1e). During the experiments, the engineered cysteine was modified with the thiol-reactive and environment-sensitive fluorophore, MTS-TAMRA. Thus the conformational rearrangements of the labeled VSDs in response to brief depolarizations were reported as ensemble fluorescence deflections (ΔF). To limit additional regulation (Ca²⁺ regulation or VDI), we (i) used Ba²⁺ as charge carrier, and pre-injected cells with the BAPTA Ca²⁺-chelator²¹; and (ii) studied Ca_V2.1 channels including β_2a, which slows down VDI relative to β-less channels^32,33.

VSD-I activated with a two-part voltage dependence (Fig. 2a, f): one component, F1, had a voltage-dependence very close to that of pore opening (calculated by normalized tail current, I_tail), and the other (F2) was observed at very negative potentials (Table 1).

**Fig. 2: Ca_V2.1 VSDs have diverse voltage-dependent activation properties.**

Table 1 Voltage-dependence parameters of Ca_V2.1 pore opening and VSD activation

Full size table

We only detected faint ΔF/F signals (<0.1%) from VSD-II (Fig. 2b), similar to signals from Ca_V2.1 without a substituted cysteine (Fig. 2e), likely due to non-specific labeling. Lack of ΔF suggested that VSD-II does not undergo voltage-dependent conformational changes. In fact, no ΔF were detected despite (i) probing most of the S3-S4 linker, (ii) trying different fluorophores, (iii) removing a tryptophan that might quench the nearby fluorophore^34,35,36,37; (iv) using a different complement of auxiliary subunits; (v) neutralizing counter-charges that could stabilize the S4_II resting state¹⁹ and (vi) perturbing a PIP₂-binding site, resolved in a Ca_V2.1 structure³⁸ (Fig. S1). Indeed, the numerous VSD-II mutations tested did not result in a consistent or substantial alteration of the voltage-dependence of pore opening (Fig. S2), suggesting that VSD-II does not contribute to Ca_V2.1 voltage sensitivity.

VSD-III and VSD-IV appeared to activate at negative potentials, close to the physiological resting membrane potential (V_rest, Fig. 2c, d, g, h). As in our VCF investigations of Ca_V1.1 and Ca_V2.2 channels^23,24, the ΔF signals from VSD-IV had opposite sign to those resolved from VSD-I and VSD-III (Fig. 2d). A straightforward interpretation is that, when MTS-TAMRA labels VSD-I and VSD-III, it is relatively more quenched in the active state than in the resting state; and vice-versa for VSD-IV. The voltage-dependence of VSD-IV appeared shallower than VSD-III, suggesting that VSD-IV is less sensitive to voltage changes. VCF mutations and labeling did not substantially change the voltage dependence of pore opening (Fig. 2f–h). Figure 2i illustrates the diverse conformational responses of different parts of α_1A to brief depolarizations.

Progressive VSD conversion under VDI-favouring conditions

Ca_V2.1 availability is limited by VDI¹³ (Fig. 1a, b), here recapitulated by changing the holding membrane potential (V_h; Fig. 3a). Which VSD is responsible for VDI? The VSD-I two-part response to membrane depolarization (Fig. 2f) suggested the presence of two Ca_V2.1 populations: one whose VSD-I activated with similar voltage-dependence to pore opening and another whose VSD-I activated at very negative potentials, far (along the voltage axis) from pore opening. The latter process was reminiscent of charge interconversion: the observations that charge movement (i.e., the overall activation of all VSDs measured by gating currents) occurs at more negative potentials as Ca_V channels enter inactivated states during prolonged depolarization^39,40. At negative V_h (−80 mV), a brief pulse to 40 mV produced robust VSD-I activation (Fig. 3b). In contrast, no VSD-I movements were detectable using the same step when V_h was very positive (40 mV, Fig. 3c), when channels were inactivated. In the presence of VDI-accelerating β₃-subunits^32,33, fewer VSD-I could activate at V_h = −80 mV, compared with β_2a (Fig. 3b, d), and no movements were detected at V_h = 40 mV (Fig. 3e). These observations hinted that VSD-I is linked to VDI.

**Fig. 3: VSD-I converts under VDI-favouring conditions.**

To explore V_h-dependent VSD-I conversion in detail we used a broad range of V_h and brief (100-ms) test potentials (V_t). Upon more positive V_h, the proportion of channels with VSD-I with depolarized voltage-dependence (F1) progressively diminished (Fig. 3f; Boltzmann parameters in Table S1), converting to channels whose VSD-I activated at hyperpolarized potentials (F2). Because of the large separation between F1 and F2 (120 mV along the voltage axis), the conversion can be said to drastically alter the biophysical properties of VSD-I. Plots of the first derivatives of the voltage-dependence curves (Fig. 3g) and F1 percentage versus V_h (Fig. 3h) better illustrate F1-F2 interconversion, which occurred around V_rest. In β₃-containing channels, conversion to F2 was favored, occurring at more negative V_h (Fig. 3i–k).

VSD-III and VSD-IV also converted (Fig. 4, Table S1) and their apparently one-part voltage-dependences (Fig. 2g,h) could be reinterpreted as mixtures of two populations. The gap between F1 and F2 VSD-III activations was approximately half as wide as that of VSD-I ( ~ 60 mV), suggesting that VSD-III is less altered by conversion. The F1 and F2 components of VSD-IV had strikingly different apparent voltage sensitivity. β₃ facilitated both VSD-III and VSD-IV conversion.

**Fig. 4: VSD-III and VSD-IV can convert.**

Summarizing our findings so far, the Ca_V2.1 VSDs exhibit diverse responses to both transient depolarization (Fig. 2) and changes in the holding potential (Figs.3,4).

VSD-I conversion is linked to inactivation

Fitting fluorescence data to the sum of two Boltzmann functions provided a good empirical overview, but it had two shortcomings: (i) it implied that channel transitions within F1 and F2 are independent of each-other, and (ii) it did not account for kinetics. To characterize VSD activation and conversion with more mechanistic rigor, VCF data from each VSD were fit to a four-state model (Fig. 5a). The kinetic model combines VSD activation and deactivation (responses to brief potential changes) with interconversion between two modes of gating (responses to holding potential changes). Mode 1 corresponds to the F1 component from the Boltzmann-distribution fits, and mode 2 to F2. However, the four-state model is physically more meaningful, accounting for the kinetics of all transitions while obeying microscopic reversibility, which implies charge conservation. The model fit to the data is shown in Fig. S3, the optimized parameters in Table S2, and the calculated equilibrium constants (the quotients between the forward and backward rates) in Table S3.

**Fig. 5: VSD-I conversion is linked to VDI.**

VSD-I converted from mode 1 to mode 2 spontaneously, i.e., in a voltage-independent manner. Conversion occurred preferentially from state A1 (k_con = 0.77 s⁻¹), while recovery occurred from state R2 (k_rec = 0.16 s⁻¹). Since A1 is visited at depolarized potentials, and R2 at hyperpolarized potentials, the distribution of channels in mode 1 or mode 2 had an apparent voltage dependence, with a V_0.5 ≅ −60 mV (Fig. 5b). VSD-III and VSD-IV also converted spontaneously from the active state but, in contrast to VSD-I, the data were not consistent with a voltage-independent transition between R1 and R2. Instead, an intrinsically-voltage-dependent transition was required (z_R1↔R2 = 1.0 and 0.65 e₀, respectively; Table S2). Their steady-state modal interconversion occurred at more negative potentials (ca. −80 mV Fig. 5b, Table S2) than for VSD-I.

Changing from β_2a- to β₃-subunits altered several biophysical parameters. Of note: First, the voltage dependence of VSD-I activation in mode 1 was shifted to more negative voltages, separating from pore opening by ca. 25 mV (Table S2). The activation transitions of other VSDs, and all activation transitions in mode 2, were relatively less affected. Second, the VSD-I conversion equilibrium constant from the active state increased by 8-fold, which resulted in a shift of the steady-state conversion voltage-dependence by −25 mV. Likewise, the conversions of VSD-III and VSD-IV were facilitated, resulting in similar (but smaller) negative shifts (Fig. 5b, c, Tables S2 & S3).

Most pertinent to VDI, the fraction of channels with a VSD-I in mode 1 and the fraction of channels available to activate (i.e., non-inactivated), were statistically indistinguishable. By contrast, the fraction of channels with VSD-III or VSD-IV in mode 1 was statistically distinct from the fraction of non-inactivated channels (Fig. 5d).

Discussion

We have experimentally and analytically shown that the four Ca_V2.1 VSDs display distinct conformational changes. VSDs undergo activation transitions over a very broad range of voltages (Fig. 2i). A study using gating-current measurements reported charge movement (i.e., VSD transitions) at only depolarized voltages⁴¹; we believe a reason for this discrepancy is that the capacitance compensation and P/N subtraction protocols used to measure gating currents likely hindered the detection of charge movement at negative voltages.

The VSDs do not merely possess quantitatively distinct biophysical properties, but exhibit qualitative differences in their structural dynamics. VSD-I movements closely correlate with channel opening and VDI (Figs. 2f, 5d). VSD-II appears to be voltage-insensitive (Figs. 2, S1, S2). VSD-III and VSD-IV exhibit a voltage-dependent conversion between the resting states (Table S2), which results in a steady-state occupancy of the mode-2 resting state (R2) over physiological V_rest (Fig. 6a, b): a unique feature, as R2 is a metastable state in canonical, spontaneously-converting VSDs^42,43, like VSD-I. To better illustrate the multiplicity of VSD steady-state conformations, we mapped the state occupancies of each VSD into state spectra (Fig. 6a, b), used to color the Ca_V2.1 structure from extremely hyperpolarized voltages, through voltages pertinent to physiological V_rest, to the fully depolarized membrane (Fig. 6c, Suppementary Movie 1).

**Fig. 6: The rich conformational palette of Ca_V2.1 at steady-state.**

Depolarization promotes VSD activation (Fig. 2). While VSD-III and VSD-IV are fastest to activate, a major finding is that VSD-I activation (in mode 1) and pore opening occur over the same membrane potential (Fig. 2, Table S2). We propose that such processes may be called “syntasic”, from classical Greek syn (σύν, together) and tasis (τάσις, tension, or in this case, voltage). The strong connection between VSD-I activation to A1 and pore opening suggests that the former is the first molecular transition that triggers neurotransmitter release in most synapses.

Figure 6 shows that Ca_V2.1 channels exhibit the most conformational diversity around V_rest. At these voltages, Ca_V2.1 channels exist with VSDs either resting in mode 1, active in mode 2, or (in the case of VSD-III and VSD-IV) resting in mode 2; and channels can be closed or inactivated. Yet, certain combinations of conformations are more favored (Fig. 5d): essentially, V_rest bisects the Ca_V2.1 population into channels with VSD-I in mode 1, primed to trigger neurosecretion; and channels with VSD-I in mode 2 and inactivated, but available to be recruited when V_rest becomes more negative.

Since Ca_V2.1 VDI contributes to synaptic plasticity mechanisms^13,14,17,18, another VSD-I transition—in this case conversion—is shown to be linked to processes of a scale well beyond intramolecular structural dynamics: cognition, and memory formation. In addition, presynaptic Ca_V2.1 availability may serve to stabilize synaptic release, similar to the stabilization of firing in axons by sodium-channel slow inactivation⁴⁴. A straightforward mechanism for how VSD-I conversion triggers inactivation is that, since VSD-I A1 is linked to pore opening, inability to achieve A1 would produce channels unavailable to conduct. VSD-I conversion may, as a conformational change, also play an active role in VDI development, engaging cytosolic structures lacking intrinsic voltage dependence yet associated with inactivation, such as the hinged lid⁴⁵ and the W-helix^46,47,48.

Every single spike carries a small probability of pushing more VSD-Is to the converted (mode-2) states: the onset of VSD-I conversion is a rare event for any single Ca_V2.1 channel (k_con = 0.77 or 1.4 s⁻¹ with β_2a or β₃, respectively; Table S2). This translates to a population transition with kinetics of about one second. Recovery from VSD-I mode 2 is about five times slower (k_rec = 0.16 or 0.22 s⁻¹ with β_2a or β₃, respectively; Table S2). Compared to the millisecond kinetics of a neuronal action potential, VSD-I recovery from conversion is a far slower event, so one could describe conversion as a form of molecular memory. And yet, as a process that contributes to acquiring lifelong memories, VSD-I conversion is also one of the fastest events on the brain-wide timescales of learning⁴⁹.

VSD-II appears to consistently lack voltage-dependence, both in Ca_V2.1 (Figs. 2, S1, S2) and Ca_V2.2²⁴. An inability to undergo voltage-dependent movements explains why, in all Ca_V2-channel structures reported, VSD-II was resolved in a resting conformation^{38,46,47,48,50} despite the absence of an electric field (equivalent to V_h = 0 mV). By the same token, VSD-II being locked down in the resolved Ca_V2 structures supports the lack of optical signals reported here and for Ca_V2.2²⁴. In the structures, all other VSDs were resolved in an active state; this is in agreement with our work, which predicts that the majority of VSD-I, VSD-III, and VSD-IV would be in a mode-2 active state at V_h = 0 mV (Fig. 6). Whether VSD-II can activate under different conditions (such as the signaling milieu or additional protein partners) is an outstanding question. Another consideration is that the lipidic composition of the plasma membrane in our heterologous expression system (Xenopus laevis oocytes) differs from that in human neurons^51,52.

Both VSD-III and VSD-IV activate faster than VSD-I and at more negative potentials (Table S2); they could possess regulatory roles in the activation process. In β₃-containing channels, where VSD-I activation and pore opening are “asyntasic” (V_0.5 of −22 and 5 mV, respectively; Table S2), voltage-dependent opening could be a more cooperative process involving VSD-III and VSD-IV. A plasticity of VSD-pore connectivity following auxiliary-subunit changes has been reported in Ca_V1.2²². A common feature of Ca_V-channel VSDs is that, despite their homology, their non-identity translates to functional heterogeneity—there are functional differences both within and between different Ca_V isoforms^21,23,24.

β_2a, relative to β₃, strongly inhibited conversion by shifting the overall steady-state conversion to more positive potentials (Figs. 3–5, Table S2). VSD-I and VSD-III are more affected by changes in β-subunit composition than VSD-IV. The most pronounced effects of β_2a are diminished conversion equilibrium constants from the active state by more than 6-fold in VSD-I and VSD-III (by comparing rates in table S2) and also diminished the conversion equilibrium constant between the resting states by ~6-fold in VSD-III (at −80 mV; calculated from parameter values in table S2 using Eq. 8). β-subunits bind to the cytosolic I-II loop^45,53 (Fig. 1a). While we cannot exclude allosteric effects of β-subunits on VSD structural dynamics, β-subunits may also interact directly with the cytosolic VSD flanks, in a state-dependent manner, similar to the proposed action of G-proteins on Ca_V2.2²⁴. While both β₂ and β₃ subunits are expressed in the brain, a highly abundant Ca_Vβ isoform is β₄⁶. Since the initial rate of inactivation in the presence of β₄ is roughly half-way between β_2a (slowest) and β₃ (fastest)³², we anticipate that the properties of native Ca_V2.1 VSDs are in between those reported here.

Our work here has uncovered a particularly rich gamut of conformations of the Ca_V2.1 VSDs, as they respond to electrical signals both transient and long-lived, tuned to both the resting membrane potential and depolarization, and under the influence of different β-subunits. Yet this is only a part of the regulation Ca_V2.1 is subject to in their presynaptic environment: several molecular partners, including Gβγ^54,55, calmodulin⁵⁶, and CaBP1⁵⁷, as well as neuronal junctophilins⁵⁸ and syntaxin⁵⁹, can modulate Ca_V2.1 voltage-dependent activation and inactivation. It will be of high interest to investigate whether they act via the same pathway as β-subunits or whether the Ca_V2.1 voltage-sensing apparatus possesses specific handles for each regulatory partner. Given the importance of Ca²⁺-signal amplitude and timing for synaptic communication, it is fitting that its principal mediator is a macromolecule with exquisite structural dynamics and regulation.

Methods

Ethical statement

All animal experiments were approved by the Linköping University Animal Care and Use Committee (document number 15839-2018, protocol number 1941).

Molecular biology

The human CACNA1A transcript variant 3 (EFa, NM_001127221.2, Uniprot O00555.3) was codon-optimized for Xenopus laevis expression by Integrated DNA Technologies (IDT) and subcloned into the Z-vector⁶⁰. All site-directed mutagenesis was performed with a high-fidelity Pfu polymerase (Agilent 600850) and confirmed by full-gene DNA sequencing. Molecular biology reagents were obtained from New England Biolabs, and synthetic oligonucleotides from IDT. In vitro cRNA transcription was performed with the AmpliCap-Max T7 High Yield Message Maker Kit (Cellscript); RNA was stored at −80 °C in RNA storage solution (Thermo Fisher Scientific). α_1A subunits were coexpressed with rabbit α₂δ-1 (CACNA2D1, Uniprot P13806) and either rat β_2a (CACNB2A, UniProt Q8VGC3) or rabbit β₃ (CACNB3, Uniprot P54286) subunits.

Oocyte preparation and labeling

Defolliculated Xenopus laevis (Nasco) oocytes (stage V-VI) were purchased from Ecocyte (grade I, defolliculated) or prepared as follows. Oocyte lobes were surgically removed and separated into clusters of up to 5 oocytes. The follicular layer was removed (i) enzymatically with Liberase (Roche) and (ii) mechanically. Both steps were done using an orbital shaker at 88 rpm at room temperature in Ca²⁺-free solution OR-2 (in mM: 82.5 NaCl, 2.5 KCl, 1 MgCl₂, 5 HEPES, pH = 7.0), first with Liberase for approximately 20 min, then in OR-2 for approximately 45-75 min. Cells were stored in SOS (in mM: 100 NaCl, 2 KCl, 1.8 CaCl₂, 1 MgCl, 5 HEPES, pH = 7.0) at 17 °C.

Each oocyte was micro-injected with a 50 nL cRNA mixture of α_1A, α₂δ-1, and either β_2a or β₃ (0.6-0.8 μg/μL of each subunit). Oocytes were incubated at 17 °C in 0.5 × Leibovitz’s L-15 (Corning) diluted in MilliQ H₂O, supplemented with 1% horse serum (Capricorn Scientific), 100 units/mL penicillin and 100 μg/mL streptomycin (Gibco), 100 μg/mL amikacin (Fisher BioReagents) for 4-6 days. Prior to fluorescence staining, oocytes were rinsed in SOS.

Oocytes expressing Cys-substituted Ca_V2.1 channel complexes were labeled with, unless otherwise stated, 20 μM MTS-5(6)-carboxytetramethylrhodamine (MTS-TAMRA; Biotium) for 7 min at 4 °C in a depolarizing solution (in mM: 120 K-Methanesulfonate (MES), 2 Ca(MES)₂, 10 HEPES; pH = 7.0). Alternate fluorophores attempted for VSD-II were: 10 μM tetramethylrhodamine-6-maleimide (TMR6M; AAT Bioquest) for 15 min at 4 °C, 20 μM tetramethylrhodamine-6-maleimide C6 (6-TAMRA C6 maleimide; AAT Bioquest) for 25 min at room temperature, 100 μM Alexa Fluor 488 C₅ maleimide (Alexa-488; Thermo Fisher Scientific) for 30 min on ice. Oocytes were rinsed in dye-free SOS following fluorescence labeling.

Electrophysiological techniques

Oocytes were voltage-clamped under the cut-open oocyte Vaseline Gap (COVG) technique complemented with epifluorescence detection^24,27,29. A CA-1B amplifier (Dagan Corporation) was used in COVG mode. Data were acquired at 25 kHz using a Digidata 1550B1 digitizer and pClamp 11.2.1 software (Molecular Devices). The optical set-up consisted of a BX51WI upright microscope (Olympus) with filters (Semrock BrightLine: exciter: FF01-531/40-25; dichroic: FF562-Di02-25x36; emitter: FF01-593/40-25). The excitation light source was the M530L3 green LED (530 nm, 170 mW, Thorlabs) driven by a Cyclops LED driver (Open Ephys). For Alexa-488 experiments, the following filter set was used (Semrock BrightLine): exciter: FF01-482/35-25; dichroic: FF506-DI03-25x36; emitter: FF01-524/24-25. The light source was a Thorlabs blue LED (490 nm, 205 mW, M490L4). A LUMPLNFL 40XW water immersion objective (Olympus; numerical aperture = 0.8, working distance = 3.3 mm) and SM05PD3A Si photodiode (Thorlabs) were used for fluorescence detection. Photocurrent was amplified with a DLPCA-200 current amplifier (FEMTO). Fluorescence emission and ionic currents were simultaneously recorded from the oocyte membrane isolated by the top chamber and low-pass-filtered at 5 kHz.

Prior to recordings, oocytes were injected with 100 nL of 100 mM BAPTA•4 K, 10 mM HEPES, pH=7.0 to prevent activation of endogenous Ca²⁺- and Ba²⁺-dependent Cl⁻ channels. External solution (in mM): 120 NaMES, 2 Ba(MES)₂, 10 HEPES; pH=7.0. Internal solution (in mM): 120 K-glutamate, 10 HEPES; pH = 7.0. Intracellular micropipette solution: 3 M NaMES, 10 mM NaCl, 10 mM HEPES; pH=7.0. Oocytes were permeabilized using 0.1% saponin to gain low resistance intracellular access. Unless otherwise stated, oocytes were clamped at a holding potential of −80 mV. To evaluate the voltage dependence of channel activation, a series of 50 ms test pulses from −100 mV to 80 mV, in 10 mV increments, was used. P/ − 6 subtraction was performed from −100 mV to reduce capacitive transients. To examine the voltage dependence of VSD-III and VSD-IV activation, 50 ms test pulses within the range of −200 mV to 60 mV, in 20 mV increments, were used. For VSD-I, an activating pulse of 100 ms was used unless otherwise stated, as fluorescence deflections did not achieve steady-state by 50 ms. 4 averages were performed to increase the signal-to-noise ratio of fluorescence signals. To evaluate different holding potentials (V_h), oocytes were clamped to each V_h for 2 min to allow complete conversion of channels prior to running experimental protocols.

Data analysis

The voltage dependence of channel opening was obtained from the peak tail current at V_h = −80 mV and fit to the single Boltzmann function:

$${I}_{{{\rm{tail}}}}(V)={I}_{{{\rm{tail}}},{\max }}/\{1+\exp [z{{\rm{F}}}({V}_{0.5}-V)/({{\rm{R}}}T)]\}$$

(1)

where V was membrane potential, I_tail,max was the maximal I_tail, z was the valence, V_0.5 was the half-activation potential, F was the Faraday constant, R was the gas constant, and T was temperature (294 K).

The voltage dependence of fluorescence deflections (ΔF) was obtained from the averaged fluorescence signal during the last 5 ms of the test pulse. ΔF for VSDs III and IV were fit to a Boltzmann function:

$$\Delta F(V)=(\Delta {F}_{{\max }} - \Delta {F}_{{\min }})/\{1+\exp [z{{\rm{F}}}({V}_{0.5}-V)/({{\rm{R}}}T)]\}+\Delta {F}_{{\min }}$$

(2)

where ΔF_max and ΔF_min were the maximal and minimal ΔF asymptotes, respectively.

In the case of the ΔF(V) curve for VSD-I (Fig. 2f), and subsequent fittings of VSDs I, III, and IV at extended holding potentials (Figs. 3f, i & 4a,d,g,j), the sum of two Boltzmann distributions was used:

$$\Delta F(V)= \Delta {F}_{{{\rm{total}}}}\cdot{F}_{1}/\{1+\exp [z_1{{\rm{F}}}({V}_{0.5\_1}-V)/({{\rm{R}}}T)]\}\\ +\Delta {F}_{{{\rm{total}}}}\cdot(1-{F}_{1})/\{1+\exp [z_2{{\rm{F}}}({V}_{0.5\_2}-V)/({{\rm{R}}}T)]\}+\Delta {F}_{{\min }\_1}\\ +\Delta {F}_{{\min }\_2}$$

(3)

where ΔF_total was the total fluorescence change (ΔF_{max_1}+ΔF_{max_2}−ΔF_{min_1}−ΔF_{min_2}) and F₁ was the fractional amplitude of the depolarized fluorescence component [(ΔF_{max_1}−ΔF_{min_1})/ΔF_total)]. To help define the parameters, only cells with >1 V_h were fit, and the following constraints were placed to reduce the number of free parameters:

1.
Voltage-dependence parameters (V_{0.5_1}, z₁, V_{0.5_2}, and z₂) were constrained to be equal across fits of different V_h for each cell.
2.
ΔF_{min_1} was constrained to be equal to ΔF_{max_2} for each V_h, in each cell.

Fitting was performed by least squares using Solver in Microsoft Excel. Data are represented as mean ± S.E.M.

To determine the apparent voltage-dependence of VSD conversion from the Boltzmann fits (Figs. 3h, k & 4c, f, i, l), F₁ values from all cells and V_h were pooled together and fit to the Boltzmann distribution:

$${F}_{1}(V)={F}_{1\_{\max }}/\{1+\exp [-z{{\rm{F}}}({V}_{0.5}-{V}_{{{\rm{h}}}})/({{\rm{R}}}T)]\}$$

(4)

F_{1_max} was fixed to 1 for VSD-I and VSD-III, and left as a free parameter for VSD-IV. Fitting was perfomed in Mathworks Matlab using fit. 95% confidence intervals were estimated using Mathworks Matlab confint.

To describe kinetic transitions among VSD states, we fit the fluorescence signals to a state-scheme mechanism, as previously^61,62. Specifically here, a four-state model was constructed in MATLAB R2019a (MathWorks) representing transitions between a VSD active and resting states between modes 1 and 2. Activation transition rates (A1→R1 and A2→R2) were modelled as:

$$k={k}_{{{\rm{eq}}}}\cdot\exp [(V-{V}_{{{\rm{eq}}}})\cdot z \cdot \beta \cdot{{\rm{F}}}/({{\rm{R}}}T)]$$

(5)

while deactivation transition rates (A1←R1 and A2←R2) as:

$$k={k}_{{{\rm{eq}}}} \cdot \exp [-(V-{V}_{{{\rm{eq}}}})\cdot z \cdot (1-\beta )\cdot{{\rm{F}}}/({{\rm{R}}}T)]$$

(6)

where k_eq, V_eq, z, and β are shared free parameters. k_eq is the rate at V_eq, V_eq is the voltage where the forward and backward rates are equal, and β is the portion of position of the energy barrier on the electric field.

Conversion rate (R1→R2) was modelled as:

$$k={k}_{{{\rm{con}}}} \cdot \exp [V \cdot z \cdot \beta \cdot {{\rm{F}}}/({{\rm{R}}}T)]$$

(7)

while recovery rates (R1←R2 and A1←A2) were modelled as:

$$k={k}_{{{\rm{rec}}}} \cdot \exp [-V \cdot z \cdot (1-\beta )\cdot{{\rm{F}}}/({{\rm{R}}}T)]$$

(8)

In this way, each conversion/recovery transition pair also shared four free parameters (k_con, k_rec, z, β), but this formulation was more easily adaptable to becoming voltage-independent by fixing z to 0.

To obey microscopic reversibility, conversion rate (A1→A2) was calculated by:

$${k}_{{{\rm{A1}}}\to {{\rm{A2}}}}={k}_{{{\rm{A1}}}\leftarrow {{\rm{A2}}}}\cdot{k}_{{{\rm{R1}}}\leftarrow {{\rm{A1}}}}\cdot{k}_{{{\rm{R2}}}\leftarrow {{\rm{R1}}}}\cdot{k}_{{{\rm{A2}}}\leftarrow {{\rm{R2}}}}/({k}_{{{\rm{A2}}}\to {{\rm{R2}}}}\cdot{k}_{{{\rm{R2}}}\to {{\rm{R1}}}}\cdot{k}_{{{\rm{R1}}}\to {{\rm{A1}}}})$$

(9)

This maneuver also reduced the number of free parameters by one, as k_con did not have to be calculated for the A1↔A2 transitions.

Finally, to obey conservation of charge, the valence of the R2↔A2 transitions was also excluded as a free parameter, and was calculated by:

$$z_{{{\rm{R}}}2\leftrightarrow {{\rm{A2}}}}=z_{{{\rm{R}}}1\leftrightarrow {{\rm{A}}}1}+z_{{{\rm{A1}}}\leftrightarrow {{\rm{A2}}}}-z_{{{\rm{R1}}}\leftrightarrow {{\rm{R2}}}}$$

(10)

The model rates were formulated into a Q-matrix^63,64. Briefly, Q was a square 4 × 4 matrix. Each element q_i,j contained the rate for the transition from state i to state j. If there were no connection between states i and j then q_i,j = 0. Each diagonal element was the negative sum of the off-diagonal elements in its row. In this way,

$${{\rm{d}}}{{\bf{p}}}(t)/{{\rm{d}}}t={{\bf{p}}}(t){{\bf{Q}}}$$

(11)

where p(t) was a 1 × 4 vector of probability (occupancy) for each state. The MATLAB ode15s solver was used to calculate it. The voltage steps had a 43 μs time-constant to both emulate the COVG clamp speed and reduce stiffness. For initial conditions, background fluorescence calculations, and other calculations after fitting, the state occupancies at steady-state were calculated using:

$${{\bf{p}}}(\infty )={{{\bf{u}}}}^{{{\rm{T}}}}{({{\bf{S}}}{{{\bf{S}}}}^{{{\rm{T}}}})}^{-1}$$

(12)

where u was a 4 × 1 unitary vector and S was [Q u].

Finally, 4 × 1 vector f contained fluorescence levels of each state. State R1 fluorescence (F_R1) was fixed to 0. The fluorescence levels of states A1 and A2 (F_A1 and F_A2, respectively) were free parameters. State R2 fluorescence (F_R2) was constrained, thus, to impose conformational conservation:

$${F}_{{{\rm{R}}}2}={F}_{{{\rm{A2}}}-}{F}_{{{\rm{A1}}}}$$

(13)

Fluorescence was then simulated as:

$$\Delta F=[{{\bf{p}}}(V,t)-{{\bf{p}}}({V}_{{{\rm{h}}},{{\rm{n}}}},\infty )]{{\bf{f}}}{b}_{{{\rm{n}}}}$$

(14)

where V_h,n was the holding potential of the nth recording from the cell, and b_n was a factor to account for fluorescence bleaching during the experiments, which reduced the ΔF amplitude. b₁ was fixed to 1, and b_n>1 had bounds 0 and 1.

Data from each cell with >2 V_h were fit simultaneously. Rate optimization was performed by least squares, using the Bayesian adaptive direct search (BADS) machine-learning model-fitting algorithm⁶⁵.

The formulae for the R1-R2 rates did not contain a V_eq parameter (Eqs. 6,7). When the R1-R2 equilibrium was voltage-dependent (z > 0, for VSD-III and VSD-IV), V_eq was calculated after fitting, using:

$${{V}_{{{\rm{eq}}}}=-\,{\mathrm{ln}}({k}_{{{\rm{con}}}}/{k}_{{{\rm{rec}}}}){{\rm{R}}}T/({{{\rm{F}}}}{z})}$$

(15)

Finally, the equilibrium potential of modal shift was calculated iteratively using Matlab’s lsqcurvefit, solving for the voltage where sum of the mode-1 steady-state occupancies was 0.5.

After several cells were fit, optimized, and calculated parameters were averaged: the geometric mean was used for rate-constant parameters (k_eq, k_con, k_rec), while the arithmetic mean was used for all others. 95% confidence intervals were calculated by bootstrapping (Matlab bootci, 10000 iterations).

Mode-1 occupancy and available current correlations (Fig. 5d) were performed as follows: Available current was calculated using test-pulses to 0 mV with different V_h, which produced inward current according to channel availability (red traces in Fig. 3a). For each cell, the currents measured were normalized to the current with V_h = −80 mV, which was available in all recordings. Only cells whose ΔF were fit with the 4-state model were included in this dataset. Mode-1 occupancy was calculated as the sum of occupancies of states R1 and A1 using Eq. 12, and normalized to mode-1 occupancy with V_h = −80 mV. Two-sample Kolmogorov-Smirnov tests were used to compare the distributions of available channels and channels in mode 1.

State occupancies were converted into color information (state spectra, Fig. 6a, b) by first assigning the occupancies of states R2, A1, and A2 as red-green-blue (RGB, respectively) triplets. To encode the fourth state (R1) occupancy, the RGB triplets were converted into the hue-saturation-lightness (HSL) color model. The lightness values were then replaced by:

$$L=0.5{+}{p_{{{\rm{R}}}1}}(\infty )/2$$

(16)

Where p_R1(∞) is the steady-state occupancy of R1. In this way, when p_R1(∞) = 0, the spectrum has medium lightness, allowing the underlying color to show; when p_R1(∞) = 1, the spectrum has maximal lightness (white). The HSL triplets were then converted back into the RGB format, to construct the spectra or annotate the Ca_V2.1 structure (Fig. 6 & Supplementary Movie 1).

Protein structure rendering

Structures of the human Ca_V2.1 α_1A subunit (PDB: 8X90³⁸) were rendered on UCSF ChimeraX^66,67,68 and PyMOL (Schrödinger).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The data that support this study are available from the corresponding authors upon request. The source data underlying Figs. 2–5 are available at Zenodo. [https://doi.org/10.5281/zenodo.14615100]. The previously published structure of the human Ca_V2.1 α_1A subunit was used from PDB: 8X90³⁸

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Acknowledgements

We thank members of the Pantazis group for useful discussions and members of the Elinder, Liin, and Pantazis groups for oocyte preparation. Funding: Lions Forskningsfond mot Folksjukdomar Ph.D. support (M.N.), NIH/NIGMS R35GM131896 (R.O.), start-up funds from the Linköping University Wallenberg Center for Molecular Medicine / the Knut and Alice Wallenberg Foundation (A.P.), Hjärnfonden (The Swedish Brain Foundation) grants and FO2022-0219 (F.E.), FO2022-0003 and FO2023-0025 (A.P.), Hjärt-Lung Fonden (The Swedish Heart-Lung Foundation) 20210596 (F.E.), Vetenskapsrådet (The Swedish Research Council) grants 2020-01019 (F.E.), and 2019-00988 and 2022-00574 (A.P.).

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Authors and Affiliations

Division of Cell and Neurobiology, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
Kaiqian Wang, Michelle Nilsson, Fredrik Elinder & Antonios Pantazis
Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
Marina Angelini & Riccardo Olcese
Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
Riccardo Olcese
Science for Life Laboratory, Linköping University, Linköping, Sweden
Fredrik Elinder
Wallenberg Center for Molecular Medicine, Linköping University, Linköping, Sweden
Antonios Pantazis

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Kaiqian Wang
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Michelle Nilsson
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Marina Angelini
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K.W., M.N., and M.A. performed experiments. K.W., M.N., and A.P. performed analysis. R.O. and F.E. contributed reagents and methods. K.W., M.N., F.E., and A.P. wrote the manuscript. All authors contributed to manuscript review and editing.

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Wang, K., Nilsson, M., Angelini, M. et al. A rich conformational palette underlies human Ca_V2.1-channel availability. Nat Commun 16, 3815 (2025). https://doi.org/10.1038/s41467-025-58884-2

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Received: 17 September 2024
Accepted: 02 April 2025
Published: 23 April 2025
DOI: https://doi.org/10.1038/s41467-025-58884-2

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