Interplay of Na_v1.8 and Na_v1.7 channels drives neuronal hyperexcitability in neuropathic pain

Neuropathic pain, unlike acute pain that serves as a protective mechanism against tissue damage, is a debilitating condition that persists months or even years after completion of the healing process (Costigan et al., 2009; Colloca et al., 2017; Finnerup et al., 2021). Neuropathic pain can also be of genetic origin (Cummins et al., 2004; Faber et al., 2012; Dib-Hajj et al., 2013; Han et al., 2014; Sidaway, 2014; Bennett et al., 2019; Dib-Hajj and Waxman, 2019). Current medications used to treat neuropathic pain, including NSAIDs, antidepressants, antiepileptics, and opioids, often provide only limited pain relief and/or carry a substantial risk of abuse and dependence (Finnerup et al., 2015; Balanaser et al., 2023). Central side-effects such as diplopia, ataxia, and confusion can be dose-limiting, thereby reducing efficacy (Alsaloum et al., 2020). Thus, the development of new therapies for pathological pain represents a significant unmet medical need. Voltage-gated sodium channel Na_v1.8 has been regarded as a promising target for pain therapeutics due to its specific expression in peripheral neurons such as primary nociceptive neurons (Akopian et al., 1996, 1999; Sangameswaran et al., 1996; Rush et al., 2006; Bennett et al., 2019; Waxman, 2023) where it plays a pivotal role in regulating neuronal excitability under healthy (Cummins and Waxman, 1997; Renganathan et al., 2001; Bennett et al., 2019; Waxman, 2023) and pathological (Amir et al., 2006; Faber et al., 2012; Han et al., 2014, 2016; Bennett et al., 2019; Dib-Hajj and Waxman, 2019) conditions. Thus, multiple studies have explored the selective inhibition of Na_v1.8 (Emery et al., 2016; Alsaloum et al., 2020; Alles and Smith, 2021; Jones et al., 2023; Waxman, 2023; Gilchrist et al., 2024), but also see Bennett et al. (2019). Indeed, a recently developed selective Na_v1.8 inhibitor, VX-584, produced a partial but statistically significant decrease in pain in clinical trials of acute postoperative pain and diabetic peripheral neuropathy (Jones et al., 2023), providing proof-of-concept that the strategy of targeted Na_v1.8 inhibition can reduce pain in humans (Waxman, 2023).

Although the function of the Na_v1.8 channel in nociceptive neurons has been extensively studied (Cummins and Waxman, 1997; Renganathan et al., 2001; Blair and Bean, 2002; Han et al., 2015; Bennett et al., 2019), details of the functional interplay of Na_v1.8 with other ion channels has remained relatively unexplored. Dorsal root ganglion (DRG) neurons express a diverse array of ion channels, and hyperexcitability of these cells is a major contributor to neuropathic pain (Waxman, 2012). In particular, functional interactions of Na_v1.8 with Na_v1.7, another peripheral sodium channel expressed preferentially in DRG neurons (Dib-Hajj et al., 2013), are not yet understood. While several studies have begun to dissect the functional interactions of Na_v1.8 with other ion channels expressed in somatosensory neurons in silico (Choi and Waxman, 2011) or with dynamic-clamp (Vasylyev et al., 2014, 2023; Alsaloum et al., 2021; Xie et al., 2022), there is still a need for better understanding of the functional contribution of Na_v1.8 to hyperexcitability of these cells. In this study, we used dynamic clamp (Sharp et al., 1993a, 1993b; Kemenes et al., 2011), a technique enabling in silico addition or subtraction of precisely titrated amounts of a specified ionic current, to evaluate the role of Na_v1.8 in small-diameter rat DRG neurons, which are known to include nociceptors. This method is especially useful because it can explore the functional contribution of graded levels of Na_v1.8 to neuronal hyperexcitability in pain models, providing a quantitative rationale for the development of Na_v1.8 inhibitors (Jones et al., 2023; Gilchrist et al., 2024). Here, we capitalized on dynamic clamp to create a clinically relevant model in which DRG neurons express the L858H Na_v1.7 gain-of-function mutation, which causes inherited erythromelalgia (IEM), a human genetic model of neuropathic pain due to excessive nociceptor activity. Using this model, we analyze the interactions of Na_v1.8 with Na_v1.7, the largest inward current and primary driver of DRG neuron firing, which acts to amplify small subthreshold depolarizations, thus setting the gain on pain-signaling neurons (Cummins et al., 1998; Dib-Hajj et al., 2013). The L858H mutation (Cummins et al., 2004; Waxman and Dib-Hajj, 2005; Han et al., 2006; Rush et al., 2006) shifts Nav1.7 channel steady-state activation to more hyperpolarized voltages and, when studied by current-clamp, causes hyperexcitability of DRG neurons, consistent with the severe pain observed in patients with IEM (Rush et al., 2006; Vasylyev et al., 2014). These findings and subsequent dynamic-clamp studies in small DRG neurons (Vasylyev et al., 2014, 2023) have provided a quantitative basis for elucidating the functional role of Na_v1.7L858H channels in the hyperexcitability of primary nociceptors underlying the pain phenotype in humans carrying this mutation. However, potential interactions of Na_v1.8 with Na_v1.7, and in particular, interactions of Na_v1.8 with the mutant L858H Na_v1.7 channel, have not been explored. In this study, we created a dynamic-clamp L858H Na_v1.7 model of neuron hyperexcitability, which demonstrates that the functional interplay between Na_v1.8 and Na_v1.7 channels is a driving factor of small DRG neuron excitability and shows that the reduction of even a small fraction of Na_v1.8 current can reverse the hyperexcitability of DRG neurons expressing a gain-of-function mutation of Na_v1.7, which can be studied in vitro as a model of neuropathic pain.

Animal studies followed protocol SW0022 approved by the Veterans Administration Connecticut Healthcare System Institutional Animal Care and Use Committee.

Time-pregnant dams were purchased from Envigo and arrived in-house at E17–E18. The pups were maintained with the respective dam that had free access to food and water. DRGs from male postnatal day 4 (P4) Sprague–Dawley rats were harvested and dissociated as reported previously (Dib-Hajj et al., 2009). Briefly, DRGs from neonatal rats were harvested and placed in ice-cold complete saline solution (CSS) (in mM: 137 NaCl, 5.3 KCl, 1 MgCl₂, 25 sorbitol, 3 CaCl₂, and 10 N-2-hydroxyethylpiperazine-N′-2-ethanesulfonic acid (HEPES), adjusted to pH 7.2 with NaOH). DRGs were then incubated at 37°C for 20-min in CSS containing 1.5 mg/ml Collagenase A (Roche) and 0.6 mM EDTA, followed by a 20-min incubation at 37°C in CSS containing 1.5 mg/ml Collagenase D (Roche), 0.6 mM EDTA, and 30 U/ml papain (Worthington Biochemical); the DRGs were then triturated in DRG media (DMEM/F12 [Invitrogen] with 10% fetal bovine serum [Hyclone], 100 U/ml penicillin, 0.1 mg/ml streptomycin [Invitrogen], and 2 mM L-glutamine [Invitrogen]) supplemented with nerve growth factor (NGF, 50 ng/ml) and glial cell line-derived neurotrophic factor (GDNF, 50 ng/ml). After trituration, 100 µl of cell suspension was seeded directly onto each poly-D-lysine/laminin-coated coverslip (Corning; Discovery Labware) and incubated at 37°C in a 95% air/5% CO₂ (vol/vol) incubator. After allowing 45 min for neurons to attach to the coverslips, DRG media supplemented with 50 ng/ml NGF and 50 ng/ml GDNF was added into each well to a final volume of 1.0 ml, and the neurons were maintained at 37°C in a 95% air/5% CO₂ (vol/vol) incubator until used for electrophysiological experiments. Half of the media was changed every other day.

Small DRG neurons at 3–7 DIV (soma diameter 23–30 μm; 26.4 ± 1.4 μm, mean ± SD, n = 20) were dynamically clamped (Sharp et al., 1993a, 1993b; Kemenes et al., 2011; Samu et al., 2012; Vasylyev et al., 2014; Takkala and Prescott, 2018) in whole-cell configuration. Membrane voltages and currents were recorded in dynamic-clamp using HEKA EPC10 USB amplifier and PatchMaster software (Heka Elektronik) interfaced with Cybercyte CIM/V10 run by Cybercyte Commander DC1 with 20–25 µs latency (CytoCybernetics). Dynamic-clamp recordings were carried out using Na_v1.7 and Na_v1.8 model’s maximal conductances equal to the respective native Na_v1.7 and Na_v1.8 conductances experimentally determined for each small DRG neuron. This was established by choosing the model’s conductance that results in a peak amplitude of the Cybercyte dynamic-clamp current (recorded offline in voltage-clamp mode) equivalent to the peak amplitude of the respective native current, providing that the above-mentioned currents (modeled and native) were evoked by (isolated based upon) the same voltage protocol for that particular cell. Using this method, we assume that the amplitude of dynamic clamp current injected into the cell via patch pipette matches the amplitude of the respective native sodium current flowing through the cellular membrane at every time point with 20–25 µs latency when small DRG neurons were dynamically clamped in the current-clamp mode. Thus, we matched the amplitudes of the modeled currents to the amplitude of the native sodium current recorded in each DRG neuron by choosing the model’s maximal conductance as appropriate, while the native sodium channels were still present and functional. Na_v1.7 G_max and Na_v1.8 G_max are denoted in the text for 100% conductance.

Voltage and current traces were filtered at 3 kHz and digitized at 50 kHz, with the exception of 65 s-long recordings of subthreshold oscillations and spontaneous APs that were digitized at 4 kHz. Pipettes were pulled from glass capillaries (catalog number PG52165-4; World Precision Instruments) and had resistance 1.5–3 MΩ when filled with the intracellular solution (in mM): 150 KCl, 0.5 EGTA, 5 HEPES, 3 Mg-ATP, 5.6 glucose, pH 7.3 with KOH, and 286–288 mOsm. The extracellular solution was HBSS (catalog number 14025; Invitrogen) (in mM): 1.3 CaCl₂, 0.5 MgCl₂, 0.4 MgSO₄, 5.3 KCl, 0.4 KH₂PO₄, 4.2 NaHCO₃, 138 NaCl, 0.3 Na₂HPO₄, 5.6 glucose, and 284–286 mOsm. The liquid junction potential (+3.8 mV) between pipette and bath solutions was measured according to Neher (1992) and was not compensated. Recordings were made at room temperature (21–23°C).

Data were analyzed using FitMaster (Heka Elektronik), pCLAMP (Molecular Devices), MS Excel (Microsoft), and OriginPro (OriginLab) software; figures were prepared in OriginPro and finalized in CorelDraw (Corel Corporation). Data are presented as means ± SEM unless specified otherwise. Statistical analysis was performed using One-Way ANOVA followed by post-hoc Tukey’s test when appropriate (*P < 0.05; **P < 0.01, ***P < 0.001).

Kinetic models were based on a Hodgkin-Huxley equation dx/dt = α_x(1−x) − β_xx, where x is the channel gating variable, and α and β are forward and backward rate constants (ms^–1), respectively. Sodium current was described by I_Na = G_max*m³*h*s*(V_m−E_Na), where G_max is the maximal conductance, V_m is membrane voltage, E_Na = 65 mV is sodium reversal potential, m is activation variable, and h and s are inactivation variables (s = 1 for Na_v1.8 channel). We used our previously published models of WT and L858H Na_v sodium channels (Vasylyev et al., 2014). Na_v1.8 sodium channel model was from Sheets et al. (2007). Currents evoked in silico by action potential-clamp (AP-clamp) protocols were calculated off-line in 20 μs precision to match PatchMaster digitization protocols using our custom program APsim written in LabTalk script under Origin framework (Vasylyev et al., 2014). All Hodgkin-Huxley variables, their products (m³hs), and the resultant ionic currents presented on all figures in this study were calculated in silico using APsim software. APsim in silico modeling was performed using Na_v1.7 and Na_v1.8 model maximal conductances equal to the respective native Na_v1.7 and Na_v1.8 conductances experimentally determined for each small DRG neuron. This was established by choosing the model’s conductance that results in the peak amplitude of the modeled current, equivalent to the peak amplitude of the respective native current when evoked by (isolated based upon) the same voltage protocol. Na_v1.7 G_max and Na_v1.8 G_max are denoted in the text for 100% conductance.

Fig. S1 shows a comparative voltage-clamp analysis of previously published Na_v1.7 and Na_v1.8 kinetic models. Table S1 provides amplitudes of native Na_v1.7 and Na_v1.8 sodium currents with their respective maximal conductances (G_max) used in the models, as well as AP parameters of small DRG neurons in control recordings. Table S2 contains amplitudes of Na_v1.7 and Na_v1.8 sodium currents with the respective maximal conductances used in the models, as well as peak frequencies and power spectral densities of subthreshold membrane potential oscillations of the respective Nav1.7WT/LH models.

We used previously published models of sodium channel gating (Sheets et al., 2007; Vasylyev et al., 2014) based on the Hodgkin–Huxley equations (Hodgkin and Huxley, 1952; Vandenberg and Waxman, 2012) to conduct a detailed comparison of the voltage-dependent and kinetic properties of each model to develop hypotheses for how these conductances may interact in functioning small DRG neurons. The kinetics of the model are described as follows: dx/dt = (1/τ)(x∞ − x), where x∞ is the x variable at steady-state and τ is its time constant. Time constants and variables at steady-state were calculated by the following equations: τ = 1/(α+β), x∞ = α/(α+β), where α and β are respective forward and backward rate constants (Fig. 1, A–C). Sodium current was described by the equation I_Na = G_max*m³*h*s*(V_m−E_Na), where m is the activation variable, h and s are inactivation variables (s = 1 for Na_v1.8 channel), G_max is maximal conductance, V_m is membrane voltage, and E_Na = 65 mV is the sodium reversal potential. Here and thereafter, we matched amplitudes of the modeled currents to the amplitude of native sodium current recorded in each DRG neuron by choosing the model’s maximal conductance as appropriate, while the native sodium channels were still present and functional (see Materials and methods for details). In the ensuing text, we interchangeably use the term “dynamic-clamp conductance” and the term “channel” which, in the context of this study, can be considered proxies in the sense of their functional effect on the neuronal membrane potential. The amplitude of dynamic-clamp current injected into the cell via patch pipette matches the amplitude of the respective native sodium current flowing through the cellular membrane via sodium channels, at every time point with 20–25 µs latency, when small DRG neurons were dynamically clamped in the current-clamp mode. Thus, functionally, dynamic-clamp reduction (addition) of sodium conductance is equivalent to blocking (activating) native sodium channels due to the equivalent effect on the membrane potential (but also see limitations of dynamic-clamp in the Discussion section).

The models are summarized in Fig. 1, A–D and Fig. S1. Briefly, at −60 mV membrane voltage, close to neuronal resting membrane potential (RMP), the steady-state open channel probability is lowest in Na_v1.8 channel (3.5 × 10⁻⁷) followed by Na_v1.7WT (P = 5 × 10⁻⁶), while Na_v1.7L858H open channel probability is about three orders of magnitude higher (P = 0.001) and is close to its peak, suggesting a functional contribution of Na_v1.7L858H to the setting of neuronal RMP. Steady-state open channel probability reaches its peak at −21.5 mV (P = 0.01), −34.4 mV (P = 4.8 × 10⁻⁵), and −53.1 mV (P = 0.0013) for Na_v1.8, Na_v1.7WT, and Na_v1.7L858H channels, respectively (Fig. 1 D). Interestingly, Na_v1.8 channel steady-state open probability rises sharply with membrane depolarization, becoming equal to Na_v1.7WT channel open probability at −44.7 mV (P = 3.1 × 10⁻⁵) and −22 mV, an average voltage threshold for AP generation in small DRG neurons under the study, exceeding it 500-fold (Na_v1.8 P = 0.01 versus Na_v1.7WT P = 1.9 × 10⁻⁵). Here and thereafter, we denote channel open probability as the probability of the channel being open, which is the state when all gates determined by the Hodgkin–Huxley models are open, thus allowing the channel to conduct (p = m³*h*s for Na_v1.7 and p = m³*h for Na_v1.8). On the basis of these observations, it is reasonable to suggest that when membrane voltage changes are slow (steady-state conditions for Na_v channels), small DRG neuron excitability at subthreshold membrane voltages between RMP and about −45 mV is mostly affected by basal activity of the Na_v1.7 channel, while the contribution of the Na_v1.8 channel increases with membrane depolarization, becoming predominant at membrane voltages close to threshold of AP generation.

The Na_v1.8 channel, underlying high-threshold tetrodotoxin-resistant sodium current in DRG neurons, is generally characterized as a slow-gating sodium channel. At an RMP of −60 mV, the Na_v1.8 channel activation time constant is 0.16 ms, which is close to 0.12 ms activation time constant of Na_v1.7 channel, pointing to a fast Na_v1.8 channel deactivation on the repolarizing phase of APs. At the same time, at voltages close to and above the threshold for AP generation, Na_v1.8 activation kinetics are significantly slower than Na_v1.7 kinetics (1.1 versus 0.27 ms at −22 mV voltage threshold). The latter, together with 0.47 (Na_v1.7WT) versus 0.14 (Na_v1.8) steady-state activation, points to a delayed onset of Na_v1.8 current during AP. The activation time constant peak is reached at −30 mV (0.31 ms, Na_v1.7WT) and at −18 mV (1.1 ms, Na_v1.8).

Na_v1.8 inactivates relatively slowly with a time constant of 25.6 ms (versus 2 ms for Na_v1.7 channel) at the AP voltage threshold, gradually accelerating its inactivation during AP rising phase to τ ∼ 1.2 ms for Na_v1.8, τ ∼ 0.4 ms for Na_v1.7 in the 20–50 mV voltage range. This slow inactivation allows the Na_v1.8 channel to stay open during all phases of AP up to about −40 mV on the repolarization phase when the Na_v1.8 channel rapidly deactivates. Indeed, when an AP is evoked by a step stimulus the Na_v1.8 channel open probability reaches its peak P = 0.41 at 51.6 mV and falls in the next 1.4 ms twofold to P = 0.21 at 30.4 mV, while the Na_v1.7WT channel open probability reaches its maximum of 0.006 at −26.4 mV subthreshold voltage and rapidly falls 10-fold to 0.0005 at 59 mV AP overshoot (Fig. 1, E and F). At −21.9 mV voltage threshold, the open channel probability was P = 0.048 (Na_v1.8), P = 0.0051 (Na_v1.7WT), and 0.0094 (Na_v1.7L858H). Thus, in dynamic settings, Na_v1.8 channel open probability at voltage threshold exceeds Na_v1.7WT channel open probability ninefold. Sodium currents during the AP in wild-type neuron shown in Fig. 1 E were calculated by the equation G_max* m³*h*s*(V_m−E_r), where G_max is maximal conductance, V_m is membrane voltage, E_r = 65 mV, s = 1 for Na_v1.8, Na_v1.7 G_max = 681 nS, Na_v1.8 G_max = 369 nS; here and thereafter, Na_v1.7 G_max and Na_v1.8 G_max are denoted for 100% conductance (Fig. 1 G). At −21.9 mV, the voltage threshold Na_v1.7 current was −299 pA and Na_v1.8 current was −1,547 pA.

These data suggest that both types of sodium channels are essential for the setting of AP threshold in wild-type neurons; however, Na_v1.7 plays a major role at membrane voltages close to neuronal RMP, while Na_v1.8 is predominant at suprathreshold voltages where it shapes the form of the AP.

In previous studies, we demonstrated that the L858H mutation of Na_v1.7 within DRG neurons, functionally introduced at physiological levels, lowered the rheobase and increased AP firing probability. This finding established a connection between the altered biophysical characteristics of the mutant Na_v1.7 channel and the abnormal excitability of nociceptors, which underlies the pain phenotype in inherited erythromelalgia (Vasylyev et al., 2014, 2023). As a next step, here we investigated the impact of Na_v1.8 dynamic-clamp subtraction in models of DRG neurons expressing the Na_v1.7L858H channel. Dynamic-clamp alterations of sodium currents were introduced at the respective conductances obtained from voltage-clamp recordings of native sodium currents in each DRG neuron. We carried out dynamic-clamp recordings in DRG neurons based on experimentally determined Na_v1.7 gating properties, and our previous data show that Na_v1.7 contributes on average 70% of the TTX-S current in small DRG neurons (Vasylyev et al., 2014, 2023). The Na_v1.8 component of net sodium current was isolated by applying test voltage pulses from −45 mV holding potential where other types of voltage-gated sodium channels were fully inactivated at steady-state, while Na_v1.8 current inactivation was minimal. The average endogenous Na_v1.7 peak current amplitude measured in small neurons (soma diameter 26.4 ± 1.4 μm, mean ± SD, n = 20) from −80 mV holding potential was −9.6 ± 2.7 nA (mean ± SD, n = 20) and Na_v1.8 current was −7.4 ± 3.9 nA (mean ± SD, n = 20) (Table S1). Na_v1.9 peak amplitude measured in small DRG neurons by test voltage pulse to 0 mV from −100 mV holding potential was about 200 pA (Coste et al., 2007). Thus, we estimated a 2–3% contribution of Na_v1.9 to net sodium current in small DRG neurons when evoked by a test voltage to 0 mV from −80 mV holding potential. The observation that Na_v1.7 maximal conductance (G_max) is folds larger than Na_v1.8 G_max, even though amplitudes of Na_v1.7 and Na_v1.8 currents evoked by step voltage to 0 mV are similar, may appear counterintuitive, but is explained by the fact that the Na_v1.7 channel m³hs = 0.27 at the current peak (Vasylyev et al., 2014) is significantly smaller than the respective Na_v1.8 m³h = 0.42 (Fig. S1). This can lead to underestimation of Na_v1.7 G_max relative to Na_v1.8 G_max if calculations are based on the peak current amplitudes.

Membrane input resistance was 146.2 ± 48.8 MΩ (mean ± SD, n = 20) (Table S1). To model the heterozygous state as in humans carrying the Na_v1.7L858H mutation, we created a 50% substitution ratio in the Na_v1.7WT/LH model by replacing 50% of the native Na_v1.7 conductance with an equivalent amount of Na_v1.7L858H channel conductance using dynamic-clamp techniques, denoted as 0.5G_max(LH-WT), where G_max represents the maximum native Na_v1.7 conductance (this model is denoted below as Na_v1.7WT/LH). Table S1 presents a summary of native sodium current amplitudes, their respective maximal conductances used in the models, and AP parameters presented in this study of small DRG neurons.

The dynamic-clamp system (CytoCybernetics) provided recordings of net dynamic-clamp current as a sum of all user-defined conductances. To explore the functional contribution of each ion channel model in more detail, we calculated single modeled conductance using our custom program APsim written in Origin8.5 LabTalk framework (Vasylyev et al., 2014). Here and thereafter, Hodgkin–Huxley variables, their products (m³hs), and the resultant ionic currents shown in all figures were calculated in silico by APsim software using Na_v1.7 G_max and Na_v1.8 G_max values that are identical to the Na_v1.7 G_max and Na_v1.8 G_max used in dynamic-clamp experiments for the respective cells. First, we calculated Na_v1.8 and Na_v1.7 channel open probabilities and the ensuing sodium currents in wild-type, Na_v1.7WT/LH hyperexcitable small DRG neurons and in the Na_v1.7WT/LH neuron after dynamic-clamp subtraction of 25% Na_v1.8 conductance. Representative dynamic-clamp recordings of small DRG neuron APs evoked by 10-ms long step current injections are presented in Fig. 2 A. Dynamic-clamp induction of Na_v1.7WT/LH depolarized RMP in this cell by 2.4 mV from −59.9 to −57.5 mV and reduced the rheobase by 60% (from 500 to 200 pA). Na_v1.7 channel peak open channel probability increased from 0.011 in control to 0.013 (20% increase) in Na_v1.7WT/LH and was reached at subthreshold membrane voltages at 5.46 ms (here and thereafter time is displayed as post-stimulus onset) in control and at 5.08 ms in Na_v1.7WT/LH model (Fig. 2, A and B). We subtracted Na_v1.8 current in 25% increments. Dynamic-clamp subtraction of 25% Na_v1.8 conductance restored the current threshold to 400 pA (80% of its control value); concurrently, Na_v1.7 channel peak open probability increased to 0.019 at subthreshold voltage (at 3.32 ms). At the same time, Na_v1.8 channels began to activate with a significant delay to Na_v1.7 at subthreshold voltages much closer to the threshold for AP generation and with Na_v1.8 channel peak open probability near AP overshoot (Fig. 2, A and C). Na_v1.8 channel peak open probability was not significantly affected by the Na_v1.7WT/LH model: m³h was 0.42 (at 7.78 ms), 0.43 (at 8.76 ms), and 0.44 (at 5.57 ms) in control, the Na_v1.7WT/LH model, and the (Na_v1.7WT/LH – 25% Na_v1.8) model, respectively (Fig. 2 C). The overshoot was 47.4 mV (at 8.1 ms) in control, 41.9 mV (at 9.2 ms) in the Na_v1.7WT/LH model, and 46.7 mV (at 5.9 ms) in (Na_v1.7WT/LH – 25% Na_v1.8) model. Interestingly, the time interval between peak values of Na_v1.7 and Na_v1.8 channel open probabilities increased from 2.32 ms in control to 3.68 ms in the Na_v1.7WT/LH model but was restored back to 2.25 ms after subtraction of 25% Na_v1.8 conductance. Na_v1.7 (Fig. 2 F) and Na_v1.8 (Fig. 2 G) sodium currents (Na_v1.7 G_max = 586 nS and Na_v1.8 G_max = 294 nS) calculated for the respective APs shown in Fig. 2 A are presented in Fig. 2, F and G immediately below plots of rate of change of relevant APs (Fig. 2, D and E).

To further elucidate the functional contribution of the Na_v1.8 channel to small DRG neuron hyperexcitability, we performed a detailed comparative analysis of Na_v1.8 and Na_v1.7 sodium currents in a representative small DRG neuron in response to subthreshold and suprathreshold step stimuli in different dynamic-clamp neuronal models. This neuron had current threshold, voltage threshold, sodium channel conductances, RMP, and AP parameters close to the average parameters recorded from the whole population of small DRG neurons in this study, and thus was chosen to be representative. A stimulus of subthreshold 450 pA magnitude resulted in membrane depolarization and ensuing activation of Na_v1.7 current from −0.4 pA at RMP (−59.1 mV) to −10 pA at −47.6 mV (at 1.18 ms post-stimulus onset), followed by peak current of −405 pA at −29.1 mV (at 5.36 ms) and subsequent current decline to −68 pA at −32.6 mV at stimulus end (at 10 ms). Concurrently, Na_v1.8 current activated with a 1.8 ms delay (compared to Na_v1.7) increasing from −0.01 pA at RMP to −10 pA at −36.9 mV (at 2.96 ms) became equal to Na_v1.7 current (Na_v1.7 = Na_v1.8 = −387 pA) at −27.5 mV (6.16 ms), peaked at −815.3 pA at −26.8 mV (7.98 ms) and subsequently declined to −246 pA at 10 ms (Fig. 3 A, left panels). Sodium currents were calculated based on Na_v1.7 G_max = 586 nS and Na_v1.8 G_max = 294 nS. A subsequent threshold stimulus of 500 pA resulted in the following: Na_v1.7 current activated to −10 pA at −47.5 mV (1.14 ms), peaked at −567 pA at −23.8 mV (5.36 ms) near voltage threshold (V_threshold = −19.5 mV, at 6.08 ms) and rapidly inactivated on the AP rising phase to −9 pA at 47.7 mV AP overshoot (at 8.08 ms). At the same time, Na_v1.8 activated with a 1.6 ms delay (compared to Na_v1.7) reaching −10 pA at −36.4 mV (2.72 ms), became −681 pA at 5.36 ms (at peak of Na_v1.7 current of −567 pA), reached its first peak of −5,927 at 6.6 mV (7.38 ms), reached −1,945 pA at 47.7 mV overshoot (8.08 ms), reached its second peak of −2,918 pA at 16.1 mV (9 ms), persisted during a substantial part of AP repolarization phase before deactivating to −10 pA at around −49 mV (11.48 ms). Na_v1.7 and Na_v1.8 currents became equal Na_v1.7 = Na_v1.8 = −565 pA at −24.2 mV (5.22 ms). At V_threshold of −19.5 mV (6.08 ms) Na_v1.7 current was −503 pA and Na_v1.8 was −1,649 pA (Fig. 3 A, right panels), while Na_v1.7 m³hs = 0.01, Na_v1.8 m³h = 0.066 (not shown).

These results are consistent with a complex interplay in which the Na_v1.7 channel in wild-type neurons, due to its fast kinetics, sharp activation curve, and the ability to activate at hyperpolarized voltages close to RMP produces sodium flux that peaks near voltage threshold and can amplify small membrane depolarizations at subthreshold voltages ranging from RMP up to the voltage threshold. In contrast, Na_v1.8 current activates with a nearly 2 ms delay after Na_v1.7 activation, at −36 mV voltage which is much closer to the threshold of AP generation. While both Na_v1.8 and Na_v1.7 currents contribute to the setting of AP threshold, Na_v1.8 current amplitude at voltage threshold is larger (3.3-fold) than Na_v1.7 amplitude (Na_v1.8 open channel probability is 6.5-fold larger), suggesting a higher functional impact of Na_v1.8. Moreover, Na_v1.8 current greatly exceeds Na_v1.7 at suprathreshold voltages pointing to its predominant functional role in shaping AP waveform at this voltage range.

Dynamic-clamp introduction of the Na_v1.7WT/LH model resulted in the following changes. Na_v1.7WT/LH current had a substantial steady-state component of −38 pA at RMP of −57.5 mV (depolarized by 2.4 mV from RMP in control). A subthreshold stimulus of 150 pA resulted in −48 pA Na_v1.7WT/LH current (activated an additional −10 pA) at −55.3 mV (at 0.48 ms post-stimulus onset), followed by peak current of −662 pA at −27.6 mV (5.8 ms) and subsequent −10 pA current at −53.4 mV (12.8 ms). Na_v1.8 current was −0.03 pA at RMP, activated to −10 pA at −36 mV (4.58 ms), peaked at −2,354 pA at −23.2 mV (9.12 ms), and deactivated to −10 pA at −44.2 mV (11.46 ms). Na_v1.7WT/LH and Na_v1.8 current amplitudes became equal to −588 pA at −24.6 mV (6.6 ms) (Fig. 3 B, left panels). The subsequent threshold stimulus of 200 pA resulted in the following: at RMP (−57.5 mV) Na_v1.7WT/LH current was −39 pA, activated to −49 pA at −55.2 mV (0.42 ms), peaked at −701 pA at −26.3 mV (4.94 ms), and inactivated to −10 pA at 34.9 mV (8.94 ms). At the same time, Na_v1.8 current was −0.03 pA at RMP, activated to −10 pA at −35.8 mV (3.74 ms), reached its first peak of −7,004 pA at 2.3 mV (8.4 ms), became −2,498 pA at 42.1 mV overshoot (9.2 ms), reached its second peak of −2,869 pA at 16.4 mV (10.06 ms), and then deactivated to −10 pA at −48.4 mV (12.72 ms). Na_v1.7WT/LH and Na_v1.8 currents were equal to −638 pA at −23.2 mV (5.56 ms after stimulus onset) (Fig. 3 B, right panels). At the voltage threshold for this cell of −16.3 mV (7.24 ms): Na_v1.7WT/LH current was −268 pA, Na_v1.8 current was −3,562 pA (13-fold Na_v1.8/Na_v1.7 amplitude ratio). Along with 60% reduction of the current threshold (from 500 pA control to 200 pA in the Na_v1.7WT/LH model), the voltage threshold of Na_v1.7WT/LH model was depolarized to −16 mV (by about 3 mV), a voltage where the ratio of current amplitudes Na_v1.8/Na_v1.7WT/LH increased to 13-fold (was 3.3-fold in control).

Thus, in a neuronal model of hyperexcitability, Na_v1.7WT/LH current was primarily responsible for the amplification of the initial phase (from RMP to about −37 mV, a voltage range where Na_v1.8 channel is deactivated) of membrane response to depolarizing stimuli. However, subsequent membrane depolarization above −36 mV resulted in activation of Nav1.8 current which quickly became predominant over Na_v1.7, producing about 90% of the total sodium flux at the threshold of AP generation. This suggests that even small changes in Na_v1.8 conductance can greatly influence the AP threshold. Indeed, dynamic-clamp subtraction of 25% Na_v1.8 conductance in the Na_v1.7WT/LH model restored the current threshold to 400 pA (80% of control value) (Fig. 3 C). A subthreshold stimulus of 350 pA resulted in the following: Na_v1.7WT/LH current increased from steady-state −42 pA at RMP of −57.9 mV to −52 pA at −55.3 mV (0.3 ms) and reached peak amplitude of −949 pA at −23 mV (3.44 ms) and became −10 pA at −52.9 mV (11.16 ms). Na_v1.8 current was −0.02 pA at RMP and activated to −10 pA at −33.7 mV (2.54 ms), peaked at −3,904 pA at −19.5 mV (5.98 ms), and deactivated to −10 pA at −40.1 mV (8.94 ms). Na_v1.7WT/LH and Na_v1.8 currents were equal to −829 pA at −18.9 mV (4.0 ms) (Fig. 3 C, left panels). At threshold stimulus of 400 pA, the (Na_v1.7WT/LH -25% Na_v1.8) model resulted in the following currents: Na_v1.7WT/LH was −42 pA at RMP of −57.8 mV and became −52 pA at −55.3 mV (0.26 ms), reached its peak of −966 pA at −21.8 mV (3.22 ms), and became −10 pA at −44.7 mV (5.88 ms); Na_v1.8 current was −0.02 pA at RMP and activated to −10 pA at −33.6 mV (2.3 ms), reached its first peak of −5,097 pA at 1.5 mV (5.12 ms), became −1,728 pA at 44.8 mV overshoot (5.92 ms) and reached its second peak of −2,360 pA at 15.3 mV (6.76 ms). At −17.8 mV (3.66 ms) amplitude of Na_v1.7WT/LH and Na_v1.8 currents became equal to −859 pA. At voltage threshold of −10.3 mV (4.56 ms): Na_v1.7WT/LH was −415 pA and Na_v1.8 was −3,420 pA (Fig. 3 C, right panels). Dynamic-clamp subtraction of 50% Na_v1.8 conductance in the Na_v1.7WT/LH model resulted in the normalization of the current threshold to 600 pA (20% over its control value). At subthreshold stimulus of 550 pA, Na_v1.7WT/LH peak was −1,022 pA at −20.5 mV (2.56 ms) and Na_v1.8 peak was −2,536 pA at −19.4 mV (4.34 ms); at −15.8 mV (3.12 ms) amplitude of Na_v1.7WT/LH and Na_v1.8 currents became equal to −840 pA (Fig. 3 D, left panels). At threshold stimulus of 600 pA: Na_v1.7WT/LH peak was −1,060 pA at −19.9 mV (2.42 ms) and Na_v1.8 current peak was −3,944 pA at −1 mV (5.72 ms); Na_v1.8 current was −1,859 pA at 27.2 mV overshoot (6.72 ms); Na_v1.7WT/LH = Na_v1.8 = −870 pA (−14.4 mV, 2.96 ms). At a threshold of −13.7 mV (5.02 ms), Na_v1.7WT/LH current was −141 pA and Na_v1.8 current was −3,596 pA (Fig. 3 D, right panels).

Notably, the total (Na_v1.7 plus Na_v1.8) sodium current amplitude at the voltage threshold was about −3.8 nA irrespective of Na_v1.8 subtraction in the Na_v1.7WT/LH model. We speculate that a proportional amplitude (not necessarily the same since there could be contribution of other inward conductances) of outward current needed to be surpassed to exceed the threshold of AP generation. If true, dynamic-clamp subtraction of Na_v1.8 current should be compensated in some way to maintain the net sodium current amplitude at the voltage threshold. Indeed, our calculations suggest that dynamic clamp reduction of Na_v1.8 inward current was compensated by an additional activation of endogenous Na_v1.7 and Na_v1.8 currents in small DRG neurons due to voltage threshold depolarization. A more depolarized (by 6 mV) voltage threshold resulted in augmentation of Na_v1.7 current amplitude from −268 pA at −16.3 mV voltage threshold (Na_v1.7WT/LH model) to −415 pA at −10.3 mV voltage threshold ([Na_v1.7WT/LH - 25% Na_v1.8] model). At the same time, Na_v1.7 peak current increased from −701 pA in Na_v1.7WT/LH to −966 pA in (Na_v1.7WT/LH-25% Na_v1.8) and just to −1,060 pA in (Na_v1.7WT/LH-50% Na_v1.8) model, pointing to Na_v1.7 functional saturation at these stimuli strengths. If Na_v1.7 was functionally saturated, a relatively slow Na_v1.8 activation kinetics represents the rate-limiting step for reaching the AP threshold, especially at larger stimuli strengths (hence fast membrane voltage rises). Thus, an additional delay is required for endogenous Na_v1.8 current to reach the necessary amplitude for AP generation. Indeed, we observed a 0.5-ms additional delay (5.02 versus 4.54 ms) to the threshold of AP generation when Na_v1.8 conductance was dynamic-clamp reduced by half.

To extend this analysis, we further studied the functional role of the Na_v1.8 channel in the hyperexcitability of the Na_v1.7WT/LH model in a population of small DRG neurons. Cells were randomly selected under visual guidance. Average rheobase for AP generation in small DRG neurons (data are means ± SE, n = 19–20) was significantly reduced from 453.5 ± 47.6 pA (varied from 120 to 850 pA) in control to 293 ± 36.9 pA (ranged from 60 to 600 pA) (P = 0.011) in Na_v1.7WT/LH model and was restored to 518 ± 85 pA (ranged from 60 to 1,450 pA) (P = 0.018 versus Na_v1.7WT/LH) and to 730 ± 151.4 pA (ranged from 60 to 2,700 pA) (P = 0.008 versus Na_v1.7WT/LH) after Na_v1.8 conductance was dynamic-clamp reduced by 25% and 50%, respectively (Fig. 4 A). The stability of recordings was assessed at the end of each experiment by repeating rheobase measurements in control (445.3 ± 43.1 pA, P > 0.05 versus original control). On average, AP rheobase was reduced in the Na_v1.7WT/LH model by 34.3 ± 5.2% (n = 20) but was restored to exceed its original control value by 19.2% ± 19.7 (n = 19, P = 0.011 versus Na_v1.7WT/LH) and by 64.8 ± 31.1% (n = 20, P = 0.003 versus Na_v1.7WT/LH) when Na_v1.8 conductance in the Na_v1.7WT/LH model was reduced by 25% and 50%, respectively. To ensure recording stability measurements of AP rheobase in control were repeated at the end of the experiment, rheobase was −4.5 ± 2.2% of its original control value (n = 19, P > 0.05) (Fig. 4 A).

The voltage threshold (means ± SE, n = 17–20) in control wild-type neurons was −22 ± 1.4 mV (ranged from −38.1 to −13.2 mV) and was depolarized in the Na_v1.7WT/LH model by 1.5 mV to −20.5 ± 1.3 mV (ranged from −36 to −12.8 mV). Subtraction of Na_v1.8 conductance resulted in depolarization of voltage threshold to −18.5 ± 1.6 mV (25% Na_v1.8 subtraction, ranged from −35.2 to −9.4 mV) and to −19.1 ± 1.7 mV (50% Na_v1.8 subtraction, ranged from −32.7 to −5.9 mV). Pairwise data analysis of per-cell voltage threshold change (means ± SE, n = 17–20) showed a 1.4 ± 0.4 mV change due to induction of the Na_v1.7WT/LH model that was significantly increased to 3.6 ± 0.5 mV (P = 0.002) after 25% Na_v1.8 subtraction ([Na_v1.7WT/LH - 25% Na_v1.8]) and to 3.7 ± 0.7 mV (P = 0.006) after 50% Na_v1.8 subtraction ([Na_v1.7WT/LH - 50% Na_v1.8] (Fig. 4 B).

RMP of small DRG neurons was −54.3 ± 1.3 mV (mean ± SE, n = 20, ranged from −62.5 to −42.5 mV). Introduction of the Na_v1.7WT/LH model resulted in RMP depolarization by 1.6 ± 0.1 mV (mean ± SE, n = 20) to −52.7 ± 1.3 mV (P > 0.05, n = 20) (ranged from −61.2 to −40.7 mV). Dynamic-clamp reduction of Na_v1.8 conductance in Na_v1.7WT/LH model did not substantially affect neuronal RMP: introduction of the (Na_v1.7WT/LH - 25% Na_v1.8) model resulted in RMP of −52.5 ± 1.4 mV (P > 0.05, n = 20) (ranged from −60.8 to −40.2 mV) and (Na_v1.7WT/LH - 50% Na_v1.8) produced RMP of −52.7 ± 1.7 mV (P > 0.05, n = 20) (ranged from −61 to −40 mV) (Fig. 4 C).

AP overshoot in small DRG neurons was only minimally affected by induction of the Na_v1.7WT/LH model: 42.9 ± 2.3 mV (n = 20, ranged from 21.1 to 59 mV) in control versus 40.5 ± 2.5 mV (n = 20) after induction of Na_v1.7WT/LH model, P > 0.05; −2.4 ± 0.6 mV change). However, the overshoot was notably reduced to 36.3 ± 3.1 mV (P > 0.05, n = 17, −7.2 ± 1.1 mV change) and significantly reduced to 26.4 ± 4.1 mV (P = 0.005, n = 17; −15.4 ± 2.4 mV change) after 25% and 50% reduction of Na_v1.8 conductance, respectively (Fig. 4 D). These observations support the idea that Na_v1.8 is a predominant contributor to the net sodium influx at AP suprathreshold voltages.

Repetitive AP firing of primary nociceptive neurons is driven by Na_v1.8 (Renganathan et al., 2001) and has been implicated in the frequency-dependent encoding of painful stimuli strength (Perl, 2007; Prescott et al., 2014; Sun et al., 2017). To assess the functional role of the Na_v1.8 channel in regulating AP firing probability in small DRG neurons from a human genetic model of neuropathic pain, we recorded neuronal responses to a train of twenty depolarizing current steps (each step was 10 ms-long) applied at 10 Hz. Consistent with the pro-electrogenic effects of Na_v1.8 channel activity on the generation of a single evoked AP, dynamic-clamp reduction of Na_v1.8 conductance reduced AP firing probability when multiple APs were evoked by repetitive stimuli (Figs. 5 and 6). Representative recordings of small DRG neuron APs firing in response to subthreshold 100 pA (Fig. 5 A) and 250 pA (Fig. 5 B), to threshold 400 pA (Fig. 5 C), and to supra-threshold 550 pA (Fig. 5 D) stimuli (stimuli strengths relative to threshold are denoted for control recordings) were applied in 150 pA increments in control (first column), in the Na_v1.7WT/LH model (second column), and in the Na_v1.7WT/LH model after 50% reduction of Na_v1.8 conductance (third column). The stability of recordings was assessed by repeating control recordings at the end of the experiment (fourth column).

In response to a train of twenty depolarizing stimuli applied at current threshold (minimal stimulus to elicit at least single AP in control) wild-type neurons fired 5.3 ± 1.9 APs (mean ± SE, n = 9) (Fig. 6, A and D). The latter (same stimuli strength as in control) was substantially increased to 9 ± 3.3 (n = 9, P = 0.28), after induction of the Na_v1.7WT/LH model (Fig. 6, B and D). This substantial increase, however, did not reach statistical significance due to high cell-to-cell baseline variability, most probably because of the heterogenicity of small DRG neurons. Dynamic-clamp subtraction of 25% Na_v1.8 conductance in the Na_v1.7WT/LH model reduced neuronal firing to 0.8 ± 0.7 APs (P = 0.028, n = 9), while 50% Na_v1.8 subtraction resulted in an additional reduction of AP firing probability at the respective (same stimulus strength as in control) stimulus strength (0 APs, P = 0.016, n = 9) (Fig. 6, C and D). It should be noted that dynamic-clamp subtraction of Na_v1.8 conductance did not eliminate repetitive AP firing but rather resulted in a substantial increase of the current threshold (data not shown). The latter was consistent with a significant increase of the current threshold due to the respective dynamic-clamp reduction of Na_v1.8 conductance when neurons were stimulated by a single current pulse (data presented on Fig. 4 A).

We previously showed that dynamic-clamp–mediated introduction of the Na_v1.7WT/LH model resulted in spontaneous AP firing in a small population of DRG neurons (Vasylyev et al., 2023). To evaluate the contribution of Na_v1.8 channels in spontaneous neuronal firing, we used a dynamic-clamp to alter Na_v1.8 conductance in Na_v1.7WT/LH model neurons that fired spontaneous APs (Figs. 7, 8, and 9). Dynamic-clamp introduction of Na_v1.7WT/LH (Na_v1.7 G_max = 686 nS) resulted in about 4 mV depolarization of RMP from −53.4 to −49.3 mV (Fig. 7, A and D). This depolarization was not significantly affected by dynamic-clamp subtraction of Na_v1.8 conductance (Na_v1.8 G_max = 330 nS): we observed RMP depolarization from −53.3 to −49.3 mV after 50% Na_v1.8 subtraction and from −53.5 to −49.1 mV after 100% Na_v1.8 subtraction (Fig. 7, B and C). For 30-s periods of Na_v1.7WT/LH induction, neurons fired 3–4 bursts of APs with 4–18 s inter-burst intervals, where each burst consisted of 4–6 APs fired at 16–18 Hz (16.5 ± 1 Hz, mean ± SD, n = 4) (Fig. 7 A) and 6–15 APs at 16 Hz (16 ± 0.3 Hz, mean ± SD, n = 3) (Fig. 7 D). Dynamic-clamp subtraction of Na_v1.8 conductance (Fig. 7, B and C) abolished repetitive AP firing, with the exception of a single burst of APs that occurred just after model initiation when 11–13 supra-threshold events with overshoot amplitudes mostly not exceeding 0 mV were still present (13 events at 17.5 Hz average frequency with overshoot ranging from −0.7 to 7.8 mV, when 50% of Na_v1.8 was subtracted and 11 events at 16.8 Hz with overshoot ranging from −8 to 1.6 mV, when 100% of Na_v1.8 was subtracted). Interestingly, small DRG neurons isolated from Na_v1.8 KO mice have previously been reported to fire small-amplitude action potentials that crossed 0 mV (Renganathan et al., 2001; Nascimento de Lima et al., 2024). Our data presented in Fig. 7, B and C are in full agreement with these prior observations. The first burst of APs in the Na_v1.WT/LH model (without Na_v1.8 conductance subtraction) included four APs fired at 15 Hz (Fig. 7 A) and 15 APs fired at 15.9 Hz (Fig. 7 D). At the same time, the dynamic-clamp addition of 50% Na_v1.8 conductance to the neuronal Na_v1.7WT/LH model that did not fire spontaneously resulted in a single burst of 10 APs at 10.7 Hz immediately after model implementation. Moreover, the addition of 100% Na_v1.8 conductance resulted in a burst of seven APs at 11.8 Hz immediately after dynamic-clamp model onset, followed by two additional bursts, consisting of four APs at 10.9 Hz and three APs at 10.6 Hz during 30 s of model implementation (Fig. 9, A–C; Na_v1.7 G_max = 681 nS, Na_v1.8 G_max = 369 nS).

We observed subthreshold membrane potential oscillations at inter-burst intervals (Fig. 7, right panels). The oscillations contained wavelets, a spindle-like event of 0.5–0.7 s duration (Fig. 7, A and C, right panels, shown by arrows), with each wavelet composed of 5–10 fast oscillations (ripples) of different amplitudes at 12–15 Hz. Interestingly, the frequency of ripples (12–15 Hz) was close to the frequency of spontaneous APs firing (16–18 Hz). Dynamic-clamp Na_v1.8 subtraction reduced peak-to-peak amplitudes of subthreshold membrane potential oscillations without affecting their frequency. Power spectral density revealed a peak frequency at 14.4 Hz (2.3 × 10⁻⁷ V²/Hz) of subthreshold membrane potential oscillations in the Na_v1.7WT/LH model presented in Fig. 7. Dynamic-clamp subtraction of Na_v1.8 conductance reduced power of the wave spectrum at peak frequency by 2.3-fold to 9.9 × 10⁻⁸ V²/Hz without affecting the peak frequency. Power spectral density of membrane noise (30 s baseline recordings in control wild-type neurons immediately preceding the induction of dynamic-clamp models) at 14.4 Hz was 1.1 × 10⁻⁹ V²/Hz (Fig. 8 A). Additionally, the introduction of the Na_v1.7WT/LH model increased power spectral density at the 0.3–1 Hz band by threefold, while dynamic-clamp subtraction of Na_v1.8 alleviated this effect. Since this frequency band was close to the observed wavelet frequency (0.7–1.5 Hz), it is reasonable to suggest that the observed alterations in power spectral density at 0.3–1 Hz reflect the respective alterations in wavelet amplitudes (Fig. 7). Concurrently, Na_v1.8 subtraction in the Na_v1.7WT/LH model resulted in the following changes in probability distribution of amplitudes of subthreshold oscillations: amplitude of oscillations at peak density was reduced from 2.3 to 1.4 mV, while number of events with amplitudes exceeding 5 mV was reduced fivefold from 19 to 4 events. Moreover, all events with amplitudes exceeding 6 mV were virtually abolished (Fig. 8 B). Average peak-to-peak amplitude of membrane potential oscillations in the Na_v1.7WT/LH model was 2.8 ± 1.4 mV (mean ± SD, n = 338) in control and was significantly reduced to 2.16 ± 0.95 mV (mean ± SD, n = 323, ***P < 0.001) and 2.17 ± 0.99 mV (mean ± SD, n = 334, ***P < 0.001) after dynamic-clamp subtraction of 50% and 100% Na_v1.8 conductance, respectively (Fig. 8 C). In a population of small DRG neurons, power spectral densities of subthreshold membrane potential oscillations in Na_v1.7WT/LH models varied from 1.2 × 10⁻⁹ V²/Hz to 2.3 × 10⁻⁷ V²/Hz (4.4 × 10⁻⁸ V²/Hz ± 7.6 × 10⁻⁸ V²/Hz, mean ± SD, n = 8), while peak frequencies varied from 10.9 to 27.9 Hz (18. 6 ± 7 Hz, mean ± SD, n = 8). Subtraction of 100% Na_v1.8 conductance in the Na_v1.7WT/LH model reduced mean power spectral density of subthreshold membrane potential oscillations twofold (0.8–3.7-fold, n = 8) to 2.4 × 10⁻⁸ V²/Hz ± 3.4 × 10⁻⁸ V²/Hz (mean ± SD, n = 8, varied from 0.8 × 10⁻⁹ V²/Hz to 9.8 × 10⁻⁸ V²/Hz) (Table S2).

At the same time, dynamic-clamp addition of 50% Na_v1.8 conductance to the neuronal Na_v1.7/WT/LH model (Na_v1.7 G_max = 681 nS) enhanced power spectral density of subthreshold membrane potential oscillations 3.5-fold (from 4.8 × 10⁻⁹ V²/Hz to 1.7 × 10⁻⁸ V²/Hz) at 7.9 Hz peak frequency. The addition of 100% Na_v1.8 conductance (Na_v1.8 G_max = 369 nS) in the same Na_v1.7WT/LH neuron model resulted in an additional increase of power spectral density to 3.4 × 10⁻⁷ V²/Hz (7.1-fold increase compared with the Na_v1.7WT/LH model without Na_v1.8 addition) at 7.9 Hz. Power spectral density of membrane noise recorded when dynamic-clamp all models were OFF (in the native state of the neuron) was 6.2 × 10⁻¹⁰ V²/Hz at 7.9 Hz (Fig. 9 D). Distribution of peak-to-peak amplitudes of spontaneous events in the Na_v1.8WT/LH model of neuronal hyperexcitability with only endogenous Na_v1.8 and after dynamic addition of 100% Na_v1.8 conductance, while endogenous Na_v1.8 is still present is shown in Fig. 9 E. Average peak-to-peak amplitude of membrane potential oscillations in the Na_v1.7WT/LH model was 0.63 ± 0.15 mV (mean ± SD, n = 237) in control and was significantly increased to 0.94 ± 0.32 mV (mean ± SD, n = 179, P < 0.001) and to 1.11 ± 0.52 mV (mean ± SD, n = 190, P < 0.001) after addition of 50% and 100% Na_v1.8 conductance, respectively. Statistical analysis across different conditions was performed by one-way ANOVA followed by post-hoc Tukey’s test.

In the present study, we capitalized on dynamic-clamp to investigate the role of sodium channel Na_v1.8 in regulating excitability of small DRG neurons. This question is especially timely in the context of a recent clinical study showing a reduction in acute and neuropathic pain as a result of treatment with a subtype-specific Na_v1.8 inhibitor (Jones et al., 2023). While only documenting partial pain relief, these clinical results provide a step toward proof-of-concept that inhibition of Na_v1.8 channels can reduce pain in humans (Waxman, 2023). However, the available data do not address questions such as the precise role of Na_v1.8 channels in the firing of pain-signaling neurons or the percentage of channels that need to be blocked to achieve pain relief. Dynamic-clamp analysis permits the addition or subtraction via a current injecting electrode controlled by computerized circuitry, in living cells, of precisely calibrated ionic conductances calculated in silico, thus permitting before-and-after comparisons in the same cell and avoiding the variation in expression levels inherent in the study of transfected neurons. We previously used dynamic-clamp to study the effect on DRG neuron excitability of a gain-of-function Na_v1.7 mutation, L858H, that produces a well-studied inherited pain syndrome, IEM, characterized by very severe pain due to hyperexcitability of DRG neurons. The L858H Na_v1.7 mutation introduced at physiological levels within DRG neurons provided a platform for the study of the link between the altered biophysical properties of a mutant Na_v1.7 channel and nociceptor hyperexcitability underlying the pain phenotype in IEM (Vasylyev et al., 2014, 2023). Here, we used the dynamic clamp to study the effects of sodium current produced by sodium channel Na_v1.8 in small DRG neurons, both native and those expressing L858H Na_v1.7 mutant channels by the dynamic clamp. We used previously published models of sodium channel gating (Rush et al., 2007; Vasylyev et al., 2014) based on the Hodgkin–Huxley equations (Hodgkin and Huxley, 1952; Vandenberg and Waxman, 2012) to analyze the functional contribution of these channels to the excitability of small DRG neurons that are known to include nociceptors. To create a functionally meaningful model of neuronal excitability, we matched the amplitudes of the modeled currents to the amplitudes of native sodium currents recorded in each DRG neuron by choosing the model’s maximal conductance as appropriate. Intuitively, functional subtraction (addition) of an ion channel conductance by the dynamic clamp might be expected to result in the same effect on neuronal excitability as inhibition (activation) of the respective ion channel on the cellular membrane. Like any other dynamic clamp study, this study has limitations, in that a completely accurate functional subtraction (addition) of native currents with dynamic clamp via dynamic clamp may not have been achieved for reasons such as the location of injections and associated space-clamp issues (Spruston and Johnston, 2008; Williams and Mitchell, 2008; Vasylyev and Waxman, 2012), mismatches of the native current and its kinetic model, and variations in the assessment of the maximal conductance. Moreover, the non-linearity of membrane electrical behavior at subthreshold levels introduces additional complexity (Vasylyev et al., 2023). Despite these limitations, our observations provide new lessons about the interplay of Na_v1.8 and Na_v1.7 and the role of Na_v1.8 in driving activity in hyperexcitable DRG neurons.

We observed considerable variability in the measured electrophysiological properties of DRG neurons and for many of these features the consequences of introduction of the modeled currents by dynamic clamp fell along a broad and not always unimodal distribution. It is intriguing to suggest that this variability might be the result, at least in part, of differential expression of endogenous channels in different subtypes of DRG neurons. Recent studies suggest that the number of subtypes in small DRG neurons is much greater than has been previously anticipated (Li et al., 2016; Jung et al., 2023; Xie et al., 2023; Qi et al., 2024). Thus, a simple size-based selection most likely does not necessarily provide a population of cells with similar electrogenic properties. However, dynamic clamp permits the addition or subtraction of precisely calibrated ionic conductances via current injecting electrode, permitting before-and-after comparisons in the same cell, thus reducing the effect of variation in electrogenic properties inherent in the study of the non-uniform population of neurons.

At membrane voltage close to RMP, Na_v1.7L858H channel steady-state open probability was 0.001 pointing to its contribution to the setting of neuronal RMP, while open channel probabilities at steady-state of Na_v1.7WT and Na_v1.8 were two to three orders of magnitude lower. Na_v1.8 channel steady-state open probability rose sharply with membrane depolarization and became equal to Na_v1.7WT steady-state channel open probability at about −45 mV, and at −22 mV, an average voltage threshold for AP generation, Na_v1.8 channel steady-state open probability exceeded Na_v1.7WT steady-state channel open probability 500-fold. In a dynamic setting, when AP was evoked by a step stimulus, Nav1.8 channel open probability at the voltage threshold exceeded the Na_v1.7WT channel open probability ninefold. Thus, it is reasonable to suggest that, when membrane voltage changes are relatively slow (steady-state conditions for Na_v channels), neuronal excitability at membrane voltages between RMP and −45 mV is determined by the basal activity of Na_v1.7 channel, while the functional contribution of Na_v1.8 channel gradually increases with membrane depolarization and becomes predominant over Na_v1.7 at membrane voltages close to the threshold of AP generation.

The Na_v1.8 channel (Akopian et al., 1996, 1999; Sangameswaran et al., 1996), underlying high-threshold tetrodotoxin-resistant sodium current in DRG neurons (Kostyuk et al., 1981; Fedulova et al., 1991; Dib-Hajj et al., 1997; Rush et al., 2007), is generally characterized as a slow-gating sodium channel (Cummins and Waxman, 1997; Bennett et al., 2019). At voltages close to and above the threshold of AP generation Na_v1.8 activation kinetics is an order of magnitude slower than that of Na_v1.7 which points to a delayed onset of Na_v1.8 current during AP electrogenesis. However, the relatively slow inactivation of Na_v1.8 permits the Na_v1.8 channel to stay open during all phases of AP up to about −40 mV on the AP repolarization phase when the channel quickly deactivates. This is consistent with the previously published data on the relative contributions of Na_v1.8 and Na_v1.7 to different phases of AP in nociceptive sensory neurons (Renganathan et al., 2001; Blair and Bean, 2002). The two channels operate sequentially with different but overlapping voltage domains. The Na_v1.7 channel, due to its fast kinetics and ability to activate at hyperpolarized voltages close to RMP, can amplify small membrane depolarizations at a wide range of subthreshold voltages ranging from RMP and up to the voltage threshold. While Na_v1.7 current activates early (about 1 ms after stimulus onset) at about −48 mV and peaks near the voltage threshold, Na_v1.8 current activates at about −36 mV, much closer to the voltage threshold, with about 2 ms delay after Na_v1.7 activation. Notably, while both Na_v1.8 and Na_v1.7 currents contribute to the setting of the threshold of AP generation, Na_v1.8 current amplitude is about 3.3-fold larger than Na_v1.7 current at the voltage threshold in the wild-type neurons, suggesting a higher functional impact of Na_v1.8. Moreover, Na_v1.8 current greatly exceeds Na_v1.7 current at suprathreshold voltages where it shapes AP waveform.

The data show a substantial functional role of Na_v1.8 in driving neuronal hyperexcitability in the Na_v1.7WT/LH model of neuropathic pain. The introduction of Na_v1.7WT/LH resulted in the reduction of AP rheobase and depolarized voltage threshold for AP generation to a voltage range where the relative contribution of Na_v1.8 to the net sodium current increased to about 90%. Thus, in a neuronal model of hyperexcitability, Na_v1.7WT/LH current was primarily responsible for the amplification of the initial phase (from RMP to about −37 mV) of membrane response to depolarizing stimuli. However, subsequent membrane depolarization above −36 mV resulted in activation of Na_v1.8 current which quickly became predominant over Na_v1.7, producing about 90% of the total sodium influx at the threshold of AP generation. Notably, total sodium current amplitude at the voltage threshold remained constant irrespective of the model. We speculate that a proportional amplitude of an outward current, whose amplitude at threshold voltage does not change significantly in different models, needed to be surpassed at the threshold of AP generation. If true, dynamic-clamp subtraction of Na_v1.8 conductance should be compensated in some way to maintain the net sodium influx at the AP threshold. Indeed, our calculations suggest that the dynamic clamp reduction of Na_v1.8 inward current was compensated by an additional activation of endogenous Na_v1.7 and Na_v1.8 currents in small DRG neurons due to voltage threshold depolarization. However, when Na_v1.7 was functionally saturated, the slow Na_v1.8 activation kinetics represented a rate-limiting step, especially at larger stimuli (fast membrane voltage rise). This suggested an additional delay required for endogenous Na_v1.8 current to reach the necessary amplitude for AP generation. Indeed, we observed an additional 0.5 ms delay to the AP threshold when Na_v1.8 conductance was dynamic clamp–reduced by half.

It has been previously shown that a small percentage of nociceptive DRG neurons exhibit subthreshold membrane potential oscillations that contribute to the generation of sustained spike discharge (Amir et al., 1999, 2002). The authors suggested a role for one or more TTX-S Na_v channels in the generation of the depolarizing limb of subthreshold oscillations. Computer simulations based on a Hodgkin–Huxley model have demonstrated a strong contribution of Na_v1.7 and Na_v1.8 to these membrane oscillations (Choi and Waxman, 2011). We have previously observed similar subthreshold membrane potential oscillations in the Na_v1.7WT/LH model of small DRG neuron hyperexcitability and showed that the dynamic clamp addition of I_h reduced peak-to-peak amplitudes of subthreshold membrane potential oscillations. This effect can be explained by the observed accumulation of Na_v1.7 fast inactivation due to I_h-induced membrane potential depolarization and, additionally, by the shunting effect of I_h on membrane input resistance (Vasylyev et al., 2023). Here, we showed that the Na_v1.8 channel regulated amplitude but not frequency of subthreshold membrane potential oscillations in the Na_v1.7WT/LH model of DRG neurons hyperexcitability. We observed subthreshold membrane potential oscillations that contained spindle-like events of 0.5–0.7 s duration with each spindle composed of 5–10 ripples of different amplitudes. It is tempting to speculate that bursts of APs in our model of neuronal hyperexcitability were synchronized by waves of spindle-like events with amplitudes high enough to reach the voltage threshold of AP generation. This suggestion is supported by the fact that the frequency of ripples (12–15 Hz) within spindles was close to the frequency of APs during spontaneous neuronal firing (16–18 Hz) in the Na_v1.7WT/LH model. Dynamic clamp Na_v1.8 subtraction reduced peak-to-peak amplitudes of subthreshold membrane potential oscillations without affecting their frequency. Power spectral density revealed a peak frequency at 14.4 Hz of subthreshold membrane potential oscillations in Na_v1.7WT/LH model. Dynamic clamp subtraction of Na_v1.8 conductance reduced power of the wave spectrum at peak frequency by 2.3-fold without affecting the peak frequency. Concurrently, after Na_v1.8 subtraction, probability distribution of amplitudes of membrane voltage oscillations in Na_v1.7WT/LH model was shifted toward smaller amplitudes and the amplitude of oscillations at peak density was reduced from 2.3 to 1.4 mV. Moreover, the number of events with amplitudes exceeding 5 mV was reduced fivefold, while events with amplitudes exceeding 6 mV were virtually abolished. Thus, it is reasonable to suggest that the Na_v1.8 channel affects spontaneous neuronal firing by driving subthreshold membrane potential oscillations. Therefore, the reduction of Na_v1.8 conductance and the insuring reduction of oscillations’ amplitudes leads to the abrogation of spontaneous AP firing.

In summary, we have studied the functional contribution of Na_v1.8 in DRG neurons in which we used a dynamic clamp to express a gain-of-function Na_v1.7 mutation that causes inherited erythromelalgia (IEM), a human genetic model of neuropathic pain, and demonstrated a profound functional interaction of Na_v1.8 with Na_v1.7 close to the threshold of AP generation. We found that Na_v1.8 open probability exceeds the open probability of Na_v1.7 close to the voltage threshold for AP generation. Dynamic clamp subtraction of Na_v1.8 conductance significantly reduced the firing probability of evoked APs and produced an inhibitory effect on spontaneous AP firing in hyperexcitable small DRG neurons. Additionally, the reduction of Na_v1.8 current significantly reduced amplitudes of subthreshold membrane potential oscillations that have been linked with spontaneous firing in small DRG neurons. In the aggregate, our results show that, within DRG neurons that express the peripheral sodium channel Na_v1.7, the Na_v1.8 channel acts to amplify neuronal (hyper)excitability at a broad range of membrane voltages with the predominant effect at the voltage threshold of AP generation. This amplification action of Na_v1.8 drives spontaneous AP firing of hyperexcitable DRG neurons expressing a gain-of-function Na_v1.7 mutation that causes IEM, a human genetic model of neuropathic pain. Our data show that reduction of Na_v1.8 conductance by 25–50% can reverse the hyperexcitability of DRG neurons expressing a gain-of-function Na_v1.7 mutation that causes pain in humans and suggests, more generally, that full inhibition of Na_v1.8 may not be required for relief of pain due to DRG neuron hyperexcitability.

All data supporting the results in the paper are in the paper itself and the online supplemental information. Original raw data and recordings are available from the corresponding author upon reasonable request.

David A. Eisner served as editor.

We thank Dr. Mark Estacion for his excellent IT support. We thank the editor and reviewers for their helpful feedback and valuable suggestions, which encouraged us to conduct additional experiments and meticulously revise the data. These revisions have strengthened the paper.

This work was supported in part by Center Grant RX002999-01 from the Rehabilitation Research Service, Department of Veterans Affairs and through funding from the Paralyzed Veterans of America, The Erythromelalgia Association, the Crenshaw Fund, and the Bridget Flaherty Endowment. The Center for Neuroscience & Regeneration Research is a Collaboration of the Paralyzed Veterans of America with Yale University.

Author contributions: D.V. Vasylyev: Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing - original draft, Writing - review & editing, P. Zhao: Methodology, Resources, B.R. Schulman: Resources, S.G. Waxman: Conceptualization, Funding acquisition, Project administration, Supervision, Writing - review & editing.