Lidocaine is one of the most widely used local anesthetics in surgical anesthesia and in the management of acute postoperative and chronic pain syndromes.1–3 Its anesthetic action is typically produced by blocking voltage-gated sodium channels that are responsible for neuronal signal propagation.4 Moreover, increasing evidence has indicated that lidocaine affects other channels such as calcium channels,5–7 potassium channels,8–11 and transient receptor potential channels.12–15 Recently, the hyperpolarization-activated cyclic nucleotide (HCN) channel has been identified as a novel target of lidocaine.16–19
HCN channel family (HCN1–4)–mediated current (I h) is a slowly activated, mixed inward current carried by Na+ and K+.20,21 Diverse functions of I h have been described, including modulation of the resting membrane potential (RMP), action potential firing frequency, neuronal network oscillation, and dendritic integration.22–25 These functions contribute to nociception, thalamocortical oscillations, and hippocampal plasticity. Recently, attention has been paid to the effect of the HCN channel on inflammatory, neuropathic, and postoperative pain. For instance, abundant axonal accumulation of HCN channels has been observed after nerve injury.26–29 Concomitantly, systemic administration of ZD7288, a selective inhibitor of HCN channels, has been shown to significantly alleviate mechanical allodynia, likely because of the suppression of ectopic discharges in dorsal root ganglion (DRG) neurons.30,31 In addition, HCN1 gene knockout was observed to partially prevent the development of mouse cold allodynia.32,33 Similarly, in HCN2 genetically deleted mice, neuropathic pain was inhibited because of reduced I h currents and action potential firing rate.34 These observations indicate that HCN channels are involved in pain generation and maintenance.
It has been reported that lidocaine can inhibit I h in Xenopus oocytes,18 DRG,16,19 and thalamocortical neurons.17 In both sciatic nerve block and intrathecal anesthesia experiments, the anesthetic durations of lidocaine in HCN1−/− mice has been observed to be shorter than that in wild-type mice.16 Moreover, studies have shown that the anesthetic duration of lidocaine is prolonged by the coadministration of ZD7288.16,35,36 In contrast, forskolin, a potent nonspecific adenylyl cyclase activator that can enhance I h, has been shown to reduce the pinprick blockade duration of lidocaine.16 Therefore, it is possible that suppression of I h could be another analgesic mechanism of lidocaine.
Rexed laminae II in the spinal dorsal horn, also referred to as the substantia gelatinosa (SG), integrates nociceptive information from the periphery to the brain and plays a crucial role in nociceptive transmission. Neuronal circuitry in the SG is complicated by a predominance of excitatory interneurons and can be classified according to discharge pattern.37–40 Our previous study showed that a substantial proportion of SG neurons expresses the HCN channel.41 Furthermore, it has been demonstrated that systemic administration of lidocaine can suppress spontaneous action potential firings of SG neurons, indicating that SG neurons may be affected by lidocaine through this route of administration.42
Given that HCN channels and spinal SG neurons play important roles in inflammatory and neuropathic pain, we hypothesize that lidocaine can block HCN channels in SG neurons. Thus, the aim of this study was to investigate the effect and molecular mechanisms of lidocaine on the HCN channel and to determine the HCN channel distribution in SG subtypes classified by discharge pattern.
Preparation of Spinal Cord Slices
All experimental procedures were in accordance with protocols approved by the Institutional Animal Care and Use Committee of Nanchang University Guidelines. Spinal cord slices were prepared from male Sprague Dawley rats (3–5 weeks old) as described previously.41,43 Briefly, rats deeply anesthetized with urethane (1.5 g/kg, intraperitoneally) were perfused transcardially with ice-cold carbogenated (95% O2 and 5% CO2) sucrose-substituted artificial cerebrospinal fluid (s-ACSF) containing the following (in millimolar): 240 sucrose, 2.5 KCl, 0.5 CaCl2, 3.5 MgCl2, 1.25 NaH2PO4, 25 NaHCO3, 0.4 ascorbate acid, and 2 pyruvate. The lumbosacral spinal cord was immediately dissected and immersed in the same s-ACSF. Animals were then killed by decapitation after extraction and while still under anesthesia. Parasagittal slices measuring 300 μm in thickness were cut with a microslicer (VT1000S; Leica, Nussloch, Germany). The slices were incubated at 32°C for at least 30 minutes in normal carbogenated ACSF containing the following (in millimolar): 117 NaCl, 3.6 KCl, 2.5 CaCl2, 1.2 MgCl2, 1.2 NaH2PO4, 25 NaHCO3, 11 D-glucose, 0.4 ascorbic acid, and 2 pyruvate (pH = 7.4).
Whole-cell patch-clamp recordings were conducted as in our previous study.41 After incubation, 1 spinal cord slice was transferred to a recording chamber and continuously perfused with ACSF (2–4 mL/min) at room temperature. The SG neurons in lumbar segments L4 to L5 were visualized with an IR-DIC camera (IR-1000; Dage, Michigan City, IN). Patch pipettes were pulled from the borosilicate glass (World Precision Instruments, Sarasota, FL) on a micropipette puller (P-97; Sutter Instrument, Novato, CA). Typical resistances ranged from 3 to 5 MΩ when filled with a solution containing the following (in millimolar): 130 K-gluconate, 5 KCl, 4 Mg-ATP, 10 phosphocreatinine, 0.5 EGTA, 0.3 Li-GTP, 10 HEPES (pH = 7.3, adjusted with KOH, 300 mOsm). Signals were amplified with an EPC-10 amplifier and Patchmaster software (HEKA Electronik, Lambrecht, Germany). Series resistances typically measured between 20 and 30 MΩ and were monitored throughout the recording period. Data were excluded if the series resistance changed by >20%. RMP was measured in the current clamp with no holding current.
All drugs were obtained from Sigma-Aldrich (St. Louis, MO), except for ZD7288 and tetrodotoxin (TTX), which were obtained from Tocris Bioscience (Bristol, UK). Lidocaine, ZD7288, and TTX were dissolved in distilled water at 1000 times the concentration to be used and stored at −20°C. Before application, these drugs were immediately diluted to the respective concentrations in ACSF solution.
I h currents and membrane voltage responses were analyzed using Patchmaster and GraphPad Prism 5.0 software (GraphPad Prism Software, Inc., La Jolla, CA). I h is composed of an instantaneous (I inst) and a steady-state component (I ss).44,45 The amplitude of I h was calculated as the difference between I ss and I inst at the evoked voltage of −130 mV unless indicated otherwise. The current density was calculated by dividing the amplitude of I h by the cell capacitance at every test potential.
To determine IC50, a dose-dependent curve was fitted with the Hill equation as follows: y = I max/(1 + IC50/x), where I max represents the maximal current amplitude, IC50 is the half-maximal inhibitory concentration, and x is the concentration of lidocaine in micromolar.
To estimate V0.5 (the voltage at which the current is one-half of its maximal level), the activation curves were fitted using GraphPad Prism with the Boltzmann sigmoidal equation: I/I max = 1/(1 + exp[(V0.5 − V)/k], where I max represents the maximal current amplitude, V0.5 is the midpoint potential, V is the membrane potential, and k is the slope factor.
The time constant (τ) of I h activation was obtained by fitting the current traces (from instantaneous to 500 milliseconds) with a single exponential equation as follows: I (t) = I h × exp(−t/τ) + I ss, where I (t) is the amplitude of the current at time t, I h represents the current amplitude, and τ is the time constant.46,47
To determine the reversal potential (Vrev), the recorded tail current amplitudes during deactivation were plotted against each test potential to construct I-V curves. Vrev is the intersection of the I-V curve with the x-axis. The input resistance (Rin) was calculated based on the current change during a 10 mV hyperpolarizing pulse.
SPSS version 17.0 (SPSS Inc., Chicago, IL) was used for all the statistical analysis, except where noted. Data are expressed as mean ± SEM unless indicated otherwise, and n represents the number of neurons recorded. Two-sample paired Student t tests were used for comparison between 2 dependent groups, and 2-sample unpaired Student t tests were used for comparison between 2 independent groups. Wilcoxon signed rank tests were used for 2 dependent groups when the normality test failed using Shapiro-Wilk tests; for all pairwise differences tested using Student t test, P ≥ 0.110. One-way analysis of variance with post hoc of Bonferroni correction was used to compare >2 groups. For all the cases, P < 0.05 was considered as statistically significant.
Lidocaine Inhibits I h in SG Neurons
As shown at the bottom of Figure 1A, I h currents were evoked by hyperpolarizing voltage steps from −60 to −130 mV in 10-mV increments (1-second duration) from a holding potential of −50 mV. Lidocaine (100 μM) dramatically decreased I h (Fig. 1A). To test whether the currents recorded in our study were HCN channel mediated, we further applied ZD7288 (10 μM; 7 minutes) to the same neuron. ZD7288 reduced the current amplitude from 319 ± 64 to 19 ± 4 pA (n = 10 neurons from 8 rats; P = 0.001, paired t test), showing an inhibition of approximately 93% relative to the control. This result demonstrates that the current recorded in our study was produced by the HCN channel. To investigate the time course of I h inhibition by lidocaine, we perfused lidocaine for 4 minutes. As illustrated in Figure 1D, the amplitude of the I h currents decreased after lidocaine treatment, reaching a maximal level within 3 to 4 minutes and gradually returned to the control level in 5 to 6 minutes after washout without apparent rundown (Fig. 1, A and D). Thus, in this study, we perfused lidocaine for 4 minutes, and the amplitude of I h under the action of lidocaine was measured after 4 ± 1 minutes.
To investigate whether desensitization is involved in lidocaine-induced inhibition of I h, we applied lidocaine twice to the same neuron (Fig. 1B). The amplitude of I h was significantly reduced to 44% ± 5% that of the control (n = 6 neurons from 6 rats; 146 ± 22 pA; P = 0.007, 1-way analysis of variance with post hoc of Bonferroni) and recovered to 97% ± 1% (143 ± 23 pA; P = 0.911) after washout (Fig. 1, B and E). When applying lidocaine to the same neuron once again, I h was still reduced to 46% ± 6% that of the control (P = 0.009). No significant difference in the I h currents was observed between the 2 perfusions of lidocaine (P = 0.976; Fig. 1, C and E). This finding suggests that lidocaine markedly reduces I h in the SG neurons, and the effect is rapid, reversible, and nondesensitized.
Lidocaine-Induced I h Inhibition Is Not Mediated by Sodium Channels
To examine whether sodium channels could affect lidocaine’s inhibition of I h, we compared the I h alterations under the coapplication of 0.5 μM TTX and 100 μM lidocaine (Fig. 2, A and B). Lidocaine still inhibited the amplitude of I h to 52% ± 3% (n = 9 neurons from 4 rats) that of the control (221 ± 62 pA; P = 0.005, paired t test, Fig. 2, A–D) in the presence of TTX, which was not significantly (P = 0.193, unpaired t test, Fig. 2F) different from the inhibition of I h caused by lidocaine alone (n = 22 neurons from 11 rats; 47% ± 2% that of the control) (296 ± 37 pA; P < 0.0001; paired t test, Fig. 2E). These data confirm that lidocaine directly blocks HCN channels without the involvement of TTX-sensitive voltage-gated sodium channels.
Lidocaine Inhibits I h in SG Neurons in Concentration-Dependent Manner
To determine IC50 for the inhibitory effect of lidocaine on I h, we perfused lidocaine in increasing concentrations (1–1000 μM). As illustrated in Figure 3, lidocaine inhibited I h in a dose-dependent manner (IC50 = 80 μM and Hill coefficient = 0.63).
Lidocaine Shifts I h Activation Curve to More Hyperpolarized Potential
To investigate whether lidocaine modifies the kinetics of HCN channels, I h activation currents were evoked by the protocol shown at the bottom of Figure 4A. Both I h and tail currents were significantly decreased by lidocaine (Fig. 4, A–C). The activation curves were plotted using the Boltzmann equation under the control conditions and during the perfusion of 600 μM lidocaine (Fig. 4D). Lidocaine significantly shifted V0.5 toward more negative values from −109.7 ± 0.9 to −114.9 ± 1.1 mV, a shift of −5.2 mV (n = 23 neurons from 6 rats; P < 0.0001, paired t test; Fig. 4D and Table 1). Moreover, lidocaine significantly decreased the current density by 55% to 73% relative to that measured for the control neurons over the voltage range of −70 to −130 mV (n = 18 neurons from 6 rats; Fig. 4E and Table 1). As shown in Figure 4F, lidocaine increased the time constant to 127% to 148% that of the control (n = 19 neurons from 6 rats). For example, at −130 mV, the time constant was significantly lower in the presence of lidocaine (91.4 ± 9.2 milliseconds) than that of the control (69.8 ± 3.2 milliseconds; P = 0.003, paired t test; Fig. 4F and Table 1).
Lidocaine Shifts the Reversal Potential of I h Current to More Negative Values
To further examine the effects of lidocaine on Vrev of I h, we ran the protocol shown at the bottom of Figure 5A. After the bath application of lidocaine (600 μM), the magnitudes of the tail currents were clearly reduced (Fig. 5, A-C). The I-V curves were plotted by recording the tail currents in 24 SG neurons (Fig. 5D). The values of Vrev were −31.1 ± 1.3 and −38.6 ± 1.1 mV in the absence and presence of lidocaine, respectively (P < 0.0001, paired t test).
Lidocaine Suppresses Burst Firing in SG Neurons
To investigate the effects of lidocaine on firing properties, voltage responses to the current injections were recorded in a current-clamp mode by using the protocol shown at the bottom of Figure 6C, which generates both action potential firing and a rebound spike.17,48 Lidocaine at each concentration tested (100, 600, and 1000 μM) largely decreased the frequency of action potential firing (Fig. 6, A–C, left). In addition, lidocaine prolonged the latency of the rebound depolarization (Fig. 6D and Table 2) and decreased the rebound spike frequencies (Fig. 6E and Table 2). As shown in Figure 6F and Table 2, the variation of RMP toward hyperpolarization increased with the concentration of lidocaine. In addition, lidocaine significantly increased Rin (Fig. 6G and Table 2).
I h Expression Varies with SG Neuron Firing Pattern
To determine I h expression in various types of SG neurons, action potentials were elicited with a depolarizing current (120 pA) injection with a duration of 1 second (Fig. 7, Aa–h). On the basis of previous studies,39,40 we categorized SG neurons (n = 102) into the following 7 groups: tonic firing (63%), delayed firing (14%), single spike (10%), initial burst (8%), phasic firing (5%), gap firing (2%), and reluctant firing (2%) neurons (Fig. 7A). Among these groups of neurons, 64% of tonic-firing neurons, 21% of delayed-firing neurons, 70% of single-spike neurons, 63% of initial-burst neurons, 50% of phasic-firing neurons, 100% of gap-firing neurons and no reluctant-firing neurons were recorded with I h (Fig. 7B). Conversely, HCN channels consisted of 4 subtypes with different time constants.49 To roughly examine the HCN channel subtypes in SG neurons, we measured the time constant of I h at −130 mV, which ranged from 49 to 1289 milliseconds (n = 51; 231 ± 40 milliseconds), with most values being <400 milliseconds (Fig. 7C). These results suggest that most of the HCN channels in SG are probably HCN1 and HCN2 like.
In this study, we demonstrated that lidocaine strongly and rapidly blocks I h in SG neurons of the spinal dorsal horn in a reversible and concentration-dependent manner. Our results show that lidocaine could downregulate the excitability of SG neurons by inhibiting HCN currents, providing new insight into the mechanism underlying the analgesic effect of lidocaine.
It is generally believed that sodium channels are the main target of local anesthetics, including lidocaine. By blocking sodium channels, lidocaine inhibits action potential propagation and neuronal excitability. Recently, lidocaine was found to block HCN channels in oocytes and HEK 293 cells,18 DRG neurons,16,19 and thalamocortical neurons.17 In this study, we demonstrated for the first time that lidocaine can decrease the amplitude of I h in SG neurons. The concentrations of lidocaine used in our study are clinically relevant to spinal and epidural anesthesia, without being toxic to the cardiovascular or central nervous systems.50 The maximal blocking effect of lidocaine on the amplitude of I h in SG neurons was approximately 92%, indicating a high efficacy of lidocaine toward HCN channels. In addition, lidocaine-induced I h inhibition was not affected by TTX. It has been reported that voltage-gated sodium channels in laminae I/II cells of the spinal cord are primarily TTX-sensitive isoforms.51 Thus, it is clear that sodium channels are not involved in lidocaine-induced I h inhibition.
Ion channel activation is an important aspect of channel kinetics. The negative shift of I h activation would decrease the probability that HCN channels are open in the resting state and thus decrease neuronal excitability. In this study, we found that the I h activation curve is shifted toward negative values by lidocaine. Meng et al.18 also reported that, in HEK 293 cells, lidocaine could negatively shift I h activation for homomeric HCN1 channels or heteromeric HCN1 to HCN2 channels. The time constant is another key issue associated with channel kinetics. The speed of HCN channel activation decreases with an increasing time constant. Consistent with its action on the I h activation curve, lidocaine increased the time constant of I h at all test potentials in SG neurons.
Vrev is determined by ion channel selectivity. HCN channel opening allows for a greater influx of Na+ and a lower efflux of K+, with a net inward current.20 Theoretically, the Vrev value of HCN channels can be calculated by using the Goldman-Hodgkin-Katz equation. However, unlike that of cloned cells, the exact ratio of Na+/K+ permeability through HCN channels could not be determined in slice preparations because the distribution of HCN channel subtypes in different cell types is not the same. Therefore, in this and our previous studies,41 the x-intercept of the I h I-V curve is represented as Vrev. Lidocaine shifted the Vrev value of HCN channels from −31.1 to −38.6 mV in SG neurons, which resembles the effect of bupivacaine on HCN channels in DRG.19 Such an effect corresponds to altered Na+ and K+ selectively of HCN channels. Alternately, effects on background currents could be responsible for the apparent alteration of Vrev.
In the nervous system, rebound depolarization plays a pivotal role in neuronal excitability.52,53 The latency of rebound depolarization is determined by I h.54 In our study, lidocaine not only delayed the latency of rebound depolarization but also reduced the number of rebound spikes, in line with previous studies on thalamocortical neurons.5,17,55 These data further indicate that lidocaine can suppress the excitability of SG neurons by blocking HCN channels.
Previous studies have shown that lidocaine can regulate the resting properties of neurons.16,17 Similarly, in this study, lidocaine markedly blocked HCN channels in SG neurons, causing the RMP to more hyperpolarized voltages. In addition, Rin increased significantly with the concentration of lidocaine from 100 to 1000 μM in our study.
The composition of SG neurons is complex and has not been clearly elucidated to date. Our data show that I h can be recorded for approximately 58% of SG neurons. Among these neurons, tonic-firing cells have the highest expression level (64%). It has been reported that most tonic-firing SG neurons are excitatory interneurons.38 Therefore, the blocking of I h by lidocaine may lead to the inhibition of SG neuron excitability. In addition, most of the time constants of the I h currents we recorded here were <400 milliseconds, suggesting higher contents of the HCN1 and HCN2 subtypes in SG neurons. Further experiments, such as immunohistochemistry and single-cell reverse transcription polymerase chain reaction, are required to obtain the exact distribution of HCN channel subtypes in SG neurons.
Taken together, our results demonstrate that lidocaine is an effective blocker of HCN channels in SG neurons. This inhibition may downregulate the excitability of SG neurons by decreasing the rebound depolarization frequency and prolonging rebound depolarization latency. Given that SG neurons play crucial roles in pain modulation, our observations may suggest a novel cellular mechanism underlying the analgesic effects of lidocaine in spinal fluid.
Name: Tao Hu, MD.
Contribution: This author helped conduct the study, collect and analyze the data, and write the manuscript.
Attestation: Tao Hu has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Nana Liu, MD.
Contribution: This author helped conduct the study and analyze the data.
Attestation: Nana Liu has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Minhua Lv, MD.
Contribution: This author helped conduct the study and analyze the data.
Attestation: Minhua Lv has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Longxian Ma, MD.
Contribution: This author helped write the manuscript.
Attestation: Longxian Ma approved the final manuscript.
Name: Huizhen Peng, MD.
Contribution: This author helped write the manuscript.
Attestation: Huizhen Peng approved the final manuscript.
Name: Sicong Peng
Contribution: This author helped review the analysis of the data.
Attestation: Sicong Peng approved the final manuscript.
Name: Tao Liu, PhD, MD.
Contribution: This author helped design the study, review the analysis of the data, and write the manuscript.
Attestation: Tao Liu has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.
This manuscript was handled by: Markus W. Hollmann, MD, PhD, DEAA.
We thank Hua Lu for critical discussion, comments, and/or editing of the manuscript.
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