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The Journal of Neuroscience, July 26, 2006, 26(30):7984-7994; doi:10.1523/JNEUROSCI.2211-06.2006

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Cellular/Molecular
Sodium Channel beta2 Subunits Regulate Tetrodotoxin-Sensitive Sodium Channels in Small Dorsal Root Ganglion Neurons and Modulate the Response to Pain

Luis F. Lopez-Santiago,1 Marie Pertin,2,3 Xavier Morisod,2,3 Chunling Chen,1 Shuangsong Hong,4 John Wiley,4 Isabelle Decosterd,2,3 * and Lori L. Isom1 *

1Department of Pharmacology, University of Michigan, Ann Arbor, Michigan 48109-0632, 2Anesthesiology Pain Research Group, Anesthesiology Department, Lausanne University Hospital (Centre Hospitalier Universitaire Vaudois), CH-1011 Lausanne, Switzerland, 3Department of Cell Biology and Morphology, Faculty of Biology and Medicine, University of Lausanne, CH-1005 Lausanne, Switzerland, and 4Department of Internal Medicine and General Clinical Research Center, University of Michigan, Ann Arbor, Michigan 48109-0108


    Abstract
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Voltage-gated sodium channel (Nav1) beta2 subunits modulate channel gating, assembly, and cell-surface expression in CNS neurons in vitro and in vivo. beta2 expression increases in sensory neurons after nerve injury, and development of mechanical allodynia in the spared nerve injury model is attenuated in beta2-null mice. Thus, we hypothesized that beta2 modulates electrical excitability in dorsal root ganglion (DRG) neurons in vivo. We compared sodium currents (INa) in small DRG neurons from beta2+/+ and beta2–/– mice to determine the effects of beta2 on tetrodotoxin-sensitive (TTX-S) and tetrodotoxin-resistant (TTX-R) Nav1 in vivo. Small-fast DRG neurons acutely isolated from beta2–/– mice showed significant decreases in TTX-S INa compared with beta2+/+ neurons. This decrease included a 51% reduction in maximal sodium conductance with no detectable changes in the voltage dependence of activation or inactivation. TTX-S, but not TTX-R, INa activation and inactivation kinetics in these cells were slower in beta2–/– mice compared with controls. The selective regulation of TTX-S INa was supported by reductions in transcript and protein levels of TTX-S Nav1s, particularly Nav1.7. Low-threshold mechanical sensitivity was preserved in beta2–/– mice, but they were more sensitive to noxious thermal stimuli than wild type whereas their response during the late phase of the formalin test was attenuated. Our results suggest that beta2 modulates TTX-S Nav1 mRNA and protein expression resulting in increased TTX-S INa and increases the rates of TTX-S Nav1 activation and inactivation in small-fast DRG neurons in vivo. TTX-R INa were not significantly modulated by beta2.

Key words: sodium channel; beta subunit; dorsal root ganglion; tetrodotoxin sensitive; nociception; mouse


    Introduction
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Nav1s are composed of a central, pore-forming {alpha} subunit and one or two beta subunits that modulate channel expression levels, voltage dependence, and kinetics (Catterall, 2000Go). beta1, beta1A, beta2, beta3, and beta4 subunits regulate channel gating, assembly, and cell-surface expression in vitro (Goldin, 1993Go; Isom et al., 1994Go; Isom, 2000Go; Yu et al., 2003Go; McEwen et al., 2004Go). beta1 and beta2 also participate in homophilic (Malhotra et al., 2000Go) and/or heterophilic (Ratcliffe et al., 2001Go; Kazarinova-Noyes et al., 2001Go; McEwen et al., 2004Go) cell adhesion. beta1 and beta2 can also interact with extracellular matrix molecules (Srinivasan et al., 1998Go; Xiao et al., 1999Go), ankyrin (Srinivasan et al., 1988Go, 1998Go; Xiao et al., 1999Go; Malhotra et al., 2000Go), and/or receptor tyrosine phosphatase beta (Ratcliffe et al., 2000Go).

The effects of beta2 on Nav1 cell-surface expression have been well established in primary CNS neuronal cultures in vitro (Schmidt et al., 1985Go; Schmidt and Catterall, 1986Go) and in brains of beta2–/– mice in vivo (Chen et al., 2002Go). In primary CNS neuronal cultures, the expression of beta2 results in increased levels of Nav1 at the cell surface. The loss of beta2 results in a negative shift in the voltage dependence of Nav1 inactivation as well as significant decreases in INa density in acutely dissociated hippocampal neurons of beta2–/– mice (Chen et al., 2002Go). 3H-saxitoxin binding experiments showed that, although the total cellular level of channels is similar in beta2+/+ and beta2–/– neurons, there is a 42% reduction in the level of plasma membrane channels in beta2–/– neurons, consistent with the observed decreases in INa density. The integral of the optic nerve compound action potential is reduced 30% in beta2–/– mice compared with control, and its dependence on stimulus strength is shifted to stronger stimuli, consistent with the reduction in channel cell-surface expression. These data clearly demonstrate that beta2 plays a critical role in regulating Nav1 density and functional expression in CNS neurons in vivo.

The purpose of this study was to investigate the role of beta2 in sensory dorsal root ganglion (DRG) neurons. beta2 expression increases in sensory neurons after nerve injury, and beta2–/– mice develop less mechanical allodynia than their wild-type counterparts in the spared nerve injury (SNI) model (Pertin et al., 2005Go). We hypothesized that beta2 may modulate electrical excitability in DRG neurons in vivo. To test this hypothesis, we investigated both tetrodotoxin-sensitive (TTX-S) and tetrodotoxin-resistant (TTX-R) INa in DRG neurons isolated from beta2+/+ and beta2–/– mice. We report that TTX-S but not TTX-R INas are reduced ~50% in "small-fast" DRG neurons isolated from beta2–/– mice compared with wild-type littermates. In addition, the activation and inactivation kinetics of TTX-S INa are slowed significantly. Behavioral studies show acute thermal hypersensitivity and reduced sensitivity to the inflammatory phase of the formalin test in beta2 null mice with no measurable differences in sensitivity to mechanical stimulation. We conclude that beta2 plays critical roles in electrical excitability in sensory neurons. Furthermore, beta2 may differentially affect subclasses of sensory neurons in the DRG.


    Materials and Methods
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Preparation of DRG neurons. The generation of beta2–/– (Scn2b null) mice was described previously (Chen et al., 2002Go). Animals used in the present study were bred from a congenic strain of beta2+/– mice that had been backcrossed repeatedly to C57BL/6 for at least 10 generations. All animal experiments were performed in accordance with the guidelines of the University of Michigan Committee on Use and Care of Animals or the Committee on Animal Experimentation of the Canton of Vaud, Lausanne, Switzerland. DRG neurons were acutely dissociated from adult male (8–12 weeks old) beta2+/+ or beta2–/– littermate mice. Briefly, the mice were killed with 100% CO2 inhalation for 1–2 min in a closed chamber. The vertebral column was then removed and cut longitudinally, and the DRGs on both sides from L4 and L5 spinal cord segments were removed. These ganglia were selected because 98% of sensory fibers in the sciatic nerve have cell bodies in the L4 and L5 DRGs (Swett et al., 1991Go). The DRGs were placed in minimal essential medium plus glutamine (Invitrogen, Carlsbad, CA) supplemented with 16.5 mM NaHCO3, 28.2 mM glucose, and distilled water or in DMEM/F-12 (Invitrogen) supplemented with 22 mM glucose, to give a final osmolarity of 320 mOsm/l. The medium was filtered through a 0.2 µm filter flask. The DRGs were minced two to three times before being incubated in medium with enzymes in a culture dish at 37°C. The total incubation time was 50 min with enzymes added according to the following protocol: collagenase type II (3 mg/ml; Worthington, Lakewood, NJ) was present for the entire 50 min incubation; DNase type I (0.05 mg/ml; Sigma, St. Louis, MO) and trypsin type I (1 mg/ml; Sigma) were added for the last 20 and 10 min of incubation, respectively. The dish was agitated every 10 min during the incubation. The enzymatic digestion was stopped by the addition of medium with BSA (20 mg/ml) before being replaced with fresh medium (0.5 ml) lacking BSA. Cells remaining in tissue fragments were dispersed into the medium using sterile fire-polished and silicon-coated Pasteur pipettes (6–12 strokes up and down). The cellular suspension was plated on collagen-coated 35 mm culture dishes or glass coverslips and incubated at 37°C in a humidified atmosphere of 95% air plua 5% CO2 for 1 h. Finally, 2 ml of medium supplemented with 10% fetal bovine serum were added. The cells were incubated for 2–10 h before recording, with the first 2 h used to allow cells to settle and adhere to the bottom of the culture dishes or coverslips. The remaining 8 h recording period was sufficiently short enough to minimize changes in electrical properties that may occur in long-term cultures.

Voltage-clamp recording. Voltage-clamp recordings were performed in the standard whole-cell configuration (Hamill et al., 1981Go), using an Axopatch 200B voltage-clamp amplifier (Molecular Devices, Union City, CA). The cell capacitance (Cm) was calculated by integrating the area under capacitive transients as described previously (Meza et al., 1994Go) or read directly from the amplifier. Isolated INa were recorded from single small DRG neurons (12 pF < Cm < 42 pF) at 21°C in the presence of a bath solution that contained the following (in mM): 80 NaCl, 50 choline-Cl, 30 TEA-Cl, 2 CaCl2, 0.2 CdCl2, 10 HEPES, and 5 glucose, pH 7.3 with NaOH. For some cells, the solution contained 40 mM NaCl and 90 mM choline-Cl. Fire-polished patch pipettes were generated from borosilicate glass capillaries (Warner Instruments, Hamden, CT) using a Sutter P-87 puller (Sutter Instruments, Novato, CA) and were filled with an internal solution containing the following (in mM): 70 CsCl, 30 NaCl, 30 TEA-Cl, 10 EGTA, 1 CaCl2, 2 MgCl2, 2 Na2ATP, 0.05 GTP, 10 HEPES, and 5 glucose, pH 7.3 with CsOH. Glass coverslips to which the cells were attached were removed from the incubator and placed into a small-volume recording chamber (~250 µl). Alternatively, if the cells were plated directly onto a 35 mm culture dish, 1 ml of bath solution was used. All cells were subsequently examined within 10–60 min.

Currents were low-pass filtered at 5 kHz with a four-pole Bessel filter and digitally sampled at 20 or 40 kHz. Capacitive transients were canceled with the amplifier circuitry, and linear leakage currents were digitally subtracted on-line with P/4 routines (Armstrong and Bezanilla, 1977Go). The use of the transient cancellation feature on the amplifier provided estimates for Cm and series resistance. The Cm estimated in this way was similar to that estimated by the integrating method (see above). Patch electrodes had resistances of 0.8–2.5 M{Omega}, and the series resistance was typically in the range 1–5 M{Omega}. When appropriate, this was reduced by 40–60% using the compensation circuit of the amplifier. The holding potential was always –80 mV. Recordings were performed using pClamp 8 and 9 software (Molecular Devices).

To analyze the voltage dependence of channel activation, the sodium conductance (GNa) was calculated. Peak current data for each cell were divided by the respective driving force (Vm Vrev), plotted against Vm, and fit to a Boltzmann equation of the following form:

Formula
where Gmax is the maximum GNa, V1/2 is the voltage at which 50% of the Nav1 are activated, and k is the slope of the curve. Steady-state inactivation was measured by applying a double-pulse protocol, consisting of a 500 ms prepulse ranging from –120 to 20 mV (in 5 and 10 mV increments), followed by a test pulse to 0 mV. Each data set (a plot of peak INa during the 0 mV test pulse vs prepulse voltage) was fit with the summation of two Boltzmann equations of the following form:

Formula
where F1 and F2 are the fractions of the first and second components of inactivation, respectively. The most negative component (component 1) results from the TTX-S INa whereas the other results from TTX-R INa. V1/2 is the potential at which half of the INa was inactivated, and k is the slope factor for each component. The sum of both fractions is the calculated maximum INa (F1 + F2 = Imax). Data points were then normalized with respect to Imax to obtain the inactivation curve. An alternate calculation method, yielding similar results, is included in the on-line supplemental material (available at www.jneurosci.org).

To examine the rate of channel recovery from inactivation, a protocol was designed comprising a 500 ms prepulse to –120 mV, followed by a test pulse to 0 mV, and then returning to –120 mV for a variable time period (0.25, 0.5, 1, 2, 4, 6, 8, 10, 20, 30, 40, 50, 75, 100, 200, 300, 400, 500, and 750 ms) before application of a second test pulse to 0 mV. The INa amplitude from the second 0 mV pulse was divided by the amplitude of the corresponding first test pulse to obtain the fraction of INa recovered after the recovery time. The data were fit with a double-exponential equation of the following form:

Formula
where INa p2/INa p1 is the fraction of current recovered; f1 and f2 are the fractions of the fast and slow recovery components, respectively; t is recovery time; and {tau}1 and {tau}2 are the time constants for each recovery component.

Analysis of electrophysiological data. Data were analyzed using pClamp 8 and 9 (Molecular Devices) and SigmaPlot 7 (SPSS, Chicago, IL). The statistical significance of differences between mean values for beta2+/+ and beta2–/– neurons was evaluated by Student’s unpaired t test, with p < 0.050 considered significant. Results are presented as means ± SEM.

Real-time reverse transcription-PCR. Unilateral L3–L5 DRGs from beta2+/+ and beta2–/– mice were rapidly dissected and collected in RNA-later solution (Qiagen AG, Basel, Switzerland). Each individual sample consisted of a pool of six DRGs dissected from two animals. Total RNA was isolated from each individual sample using the RNeasy Mini kit (Qiagen AG) with a DNase step (RNase free DNase set; Qiagen AG) on the column. After RNA quality and quantity were assessed by electrophoresis and spectrophotometry, 1.5 µg of RNA for each sample was reverse transcribed using Omniscript reverse transcriptase following the manufacturer’s instructions (Qiagen AG). Beacon Designer 3.0 software (Primer Biosoft International, Palo Alto, CA) was used to design primer and probe sequences (Table 1) according to SYBR green specifications (Vandesompele et al., 2002Go). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was chosen as an endogenous control to normalize expression levels of the different Nav1 {alpha} and beta subunits. Real-time PCRs were performed in a 20 µl total volume containing 50 ng of cDNA, 300 nM of each primer, 10 µl of 2x iQ SYBR green mix containing nucleotides, iTaq DNA polymerase, SYBR green, and fluorescein (Bio-Rad, Reinach, Switzerland) using the MyiQ Single Color Real-Time PCR Detection System (Bio-Rad). The amplification protocol was as follows: 3 min at 95°C, 45 cycles of 10 s at 95°C for denaturation, and 45 s at 60°C for annealing and extension; specificity was assessed using a DNA melting curve by measuring fluorescence during gradual temperature increments (0.5°C) from 55 to 95°C.


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Table 1. Primer and probe sequences used for real-time RT-PCR

 
To determine the profile of expression of different Nav1 subunits (Nav1.1, Nav1.2, Nav1.3, Nav1.6, Nav1.7, Nav1.8, and Nav1.9 and beta1, beta2, beta3, and beta4) in beta2–/– and beta2+/+ mice, a pool of three samples of each cDNA was used. PCR was performed in triplicate.

The level of expression of Nav1 {alpha} and beta subunits detected in beta2–/– and beta2+/+ mice was determined using four individual samples of total RNA from each genotype; each amplification was performed in triplicate for each target mRNA. The efficiency of amplification was determined by serial dilution of starting DNA, and standard curves were constructed from the respective mean critical threshold (CT) value for GAPDH and Nav1 transcripts. The relative expression of each target gene was calculated based on real-time PCR efficiencies and the threshold value of the unknown sample versus the standard sample (Pfaffl, 2001Go).

Western blot analysis of DRG membrane preparations. DRGs were removed and stored in ice-cold dissection medium. After a brief centrifugation at 4°C, the supernatant was discarded and the DRGs were rinsed two times in Tris-EGTA buffer (50 mM Tris, pH 8.0 with NaOH, and 10 mM EGTA) containing Complete protease inhibitors (Roche, Indianapolis, IN) at twice the recommended concentration. The DRGs were homogenized and centrifuged at 3000 x g for 5 min at 4°C to remove nuclei. The supernatant was ultra-centrifuged at 4°C for 10 min at 195,000 x g, and the pellets resuspended in 60 µl of Tris-EGTA buffer containing Complete protease inhibitors. One microliter of the suspension was used for protein assay. Equal amounts of protein (100 µg) were loaded on 4–15% polyacrylamide gradient gels and separated by SDS-PAGE. Proteins were then transferred to nitrocellulose as described previously (McEwen et al., 2004Go). Blots were probed with specific Nav1 {alpha} subunit antibodies. Anti-Nav1.1 (Chemicon, Temecula, CA) was used at a 1:500 dilution, anti-Nav1.7 (Chemicon) was used at a 1:500 dilution, and anti-Nav1.6 (Neuromab) was used at a 1:100 dilution. All blots were subsequently probed with anti-{alpha}-tubulin diluted 1:5000 (Cedarlane Laboratories, Hornby, Ontario, Canada). The immune signal from this housekeeping protein was used to control for loading differences. Densitometric measurement of the immunoreactive Nav1 {alpha} bands was performed using Scion (Frederick, MD) Image. Each Nav1 band was first normalized to the corresponding {alpha}-tubulin band for each lane on the gel. Nav1 expression levels in the beta2–/– lanes were then calculated as a percentage of the corresponding wild-type levels, using the {alpha}-tubulin normalized beta2+/+ Nav1 levels as 100%.

Behavioral tests. Eight-week-old male beta2–/– or beta2+/+ mice were habituated to the environment, the tester, and the apparatus for at least 2 weeks before testing. All behavioral testing was performed by an observer blinded to the mouse genotype.

The hot-plate assay was conducted by placing the animals (n = 9 in each group) on the hot-plate surface set at varying temperatures (49, 52, and 55°C) (Cao et al., 1998Go). The latency of response was determined by a clear hindpaw lick. The cutoff was adjusted for each temperature to avoid tissue damage: 60 s for 49°C, 30 s for 52°C, and 20 s for 55°C.

The tail-flick assay was conducted using a tail-flick analgesia meter (Columbus Instrument, Columbus, OH), and the mice were gently restrained in a conic plastic cloth. The latency of response was recorded manually at two different light-beam intensities (4 and 7; n = 4 in each group) with a cutoff at 20 s (Wilson and Mogil, 2001Go).

Mechanical sensitivity assessment was performed by applying an ascending series of non-noxious Von Frey monofilaments (Stoelting, Wood Dale, IL) to the plantar surface of each hindpaw (n = 9 in each group). For this purpose, mice were placed on an elevated platform with a delicate wire netting floor. The withdrawal threshold (in grams) was defined as the lowest force that evoked a brisk withdrawal response to at least 2 of 10 stimuli (Suter et al., 2003Go).

For the formalin test, 10 µl of 5% formalin (formaldehyde; Sigma, St. Louis, MO) was injected subcutaneously in the left hindpaw (n = 6 in each group). The time the animal spent shaking/flinching and licking the injected paw was recorded for each 5 min interval, from the injection time up to 80 min (Wei et al., 2001Go).

Analysis of behavioral data. Data are represented as mean ± SEM. Differences between groups were compared using one- or two-way ANOVA for unpaired variables, followed by post hoc Bonferroni’s correction when appropriate. Von Frey series present logarithmic differences between hairs, and logarithmic-transformed values were used for the analysis, enabling ANOVA tests (Suter et al., 2003Go). Statistical analyses were performed using JMP statistical software (version 5.01; SAS Institute, Cary, NC). A p value ≤0.05 was considered statistically significant.


    Results
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Identification and definition of neuronal size
Using criteria described in previous studies (Abdulla and Smith, 2001Go, 2002Go), DRG neurons were first assigned to "small," "medium," or "large" groups on the basis of their Cm: <42, 42–72, and >72 pF, respectively (beta2+/+ cells, n = 89; beta2–/– cells, n = 85). There were no differences in the proportions of small, medium, and large cells between the two strains (data not shown). We focused this study on small neurons, with a mean Cm of 24.9 ± 1.7 pF (n = 35) for beta2+/+ neurons and 23.9 ± 1.4 pF (n = 32) for beta2–/– neurons. Assuming a specific Cm of 1 µF/cm2 (Hille, 2001Go), and that the cells have a spherical shape without invaginations, cell-surface area and diameter can be estimated. Thus, the mean Cm corresponds to cell diameters of 28.1 and 27.6 µm, respectively, for beta2+/+ and beta2–/– neurons. Neurons with diameters <30 µm were considered nociceptive neurons, or type C cells (Study and Kral, 1996Go; Flake et al., 2004Go).

Total INa, the sum of TTX-S and TTX-R INa (Roy and Narahashi, 1992Go; Rush et al., 1998Go; Abdulla and Smith, 2002Go; Dib-Hajj et al., 2002Go), was recorded using a series of depolarizing voltage commands from a holding potential of –80 mV. To explore the voltage dependence of INa in DRG neurons of beta2+/+ and beta2–/– mice, we took advantage of the previously described activation and inactivation properties of peripheral nerve Nav1 (Cummins and Waxman, 1997Go; Akopian et al., 1996Go, 1999Go). Thus, a current–voltage (I–V) protocol with a 500 ms prepulse to –120 or –50 mV, followed by a test pulse from –100 to +40 mV was applied, with steps of 5 and 10 mV, waiting 10 s between each step (Fig. 1A, inset). When the I–V protocol with a prepulse to –120 mV was applied, the total INa was obtained (Fig. 1A, top traces). A second I–V protocol was subsequently applied to the same cell, but with a prepulse to –50 mV, to inactivate TTX-S INa and thus record only the TTX-R component (Fig. 1A, middle traces). Finally, the TTX-S component was obtained by digitally subtracting the data obtained with the second protocol from the first (Fig. 1A, bottom traces). Similar results were obtained using 300 nM TTX on some cells (data not shown). This protocol has the advantage of obtaining separate I–V relationships for both TTX-S and TTX-R INa in the absence of TTX, thus saving time and reducing cell deterioration. The two I–V curves allow us to classify the small neurons into two subgroups: small-fast and "small-slow" DRG neurons. When the maximum amplitude of TTX-S INa was >70% of the total INa, the cells were placed in the small-fast subgroup (Abdulla and Smith, 2002Go). These cells made up 49% (17 of 35) of the beta2+/+ small cell population and 53% (17 of 32) of the beta2–/– small neurons. Cells placed in the second subgroup had TTX-R INa >70% of the total INa. These cells made up 46% (16 of 35) of the beta2+/+ and 41% (13 of 32) of the beta2–/– small cells. INa in the 6% of cells remaining from the total cell population, two cells of each genotype, did not clearly fall into either category. Thus, these cells were not included in our analysis.


Figure 1
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Figure 1. Current–voltage relationships. A, Protocol for separation of TTX-R and TTX-S INa. A 500 ms prepulse to –120 or –50 mV was applied before a 50 ms test pulse from –100 to 40 mV with steps of 5 or 10 mV (inset). Currents evoked from one beta2–/– small-fast DRG neuron by test pulses from –50 to 0 mV are shown. Both TTX-S and TTX-R INa were apparent after the –120 mV prepulse (top traces); only TTX-R INa were obtained after the –50 mV prepulse (middle traces), and the TTX-S component was obtained (bottom traces) by digitally subtracting the TTX-R INa from the total INa B, Average peak INa density–voltage relationships for TTX-R INa (circles) and TTX-S INa (squares) of small-fast DRG neurons (means ± SEM), beta2+/+ (closed symbols; n = 15), or beta2–/– (open symbols; n = 14). Smooth lines are I–V curves generated using the Boltzmann fit parameters of the respective activation curves. Inset, I–V curves of total INa from the same cells as in A, beta2+/+ (closed symbols) and beta2–/– (open symbols). C, Similar to B, but for small-slow neurons, beta2+/+ (closed symbols; n = 14), or beta2–/– (open symbols; n = 11).

 
The absence of beta2 results in reduced TTX-S INa
Plots of peak INa density versus command voltage for small-fast and small-slow DRG neurons are shown in Figure 1, B and C, respectively. For both beta2+/+ (n = 15) and beta2–/– (n = 14) small-fast DRG neurons, the main INa was TTX-S, as expected by definition. The activation threshold for this INa was between –55 and –50 mV, and the maximum inward INa fell between –30 and –20 mV. For both beta2+/+ (n = 14) and beta2–/– (n = 11) small-slow neurons, the main INa was TTX resistant, detectable between –40 and –30 mV with maximal inward INa at approximately –10 mV. All currents measured displayed a reversal potential (Vrev) of ~25 mV, corresponding to the calculated equilibrium potential for sodium ions under these recording conditions (ENa = 25 mV). The I–V curves for small-fast neurons from beta2–/– mice show a significant reduction in TTX-S INa density compared with those neurons isolated from beta2+/+ mice (Fig. 1B). This reduction can also be clearly observed directly in the total INa (Fig. 1B, inset).

To better compare the voltage dependence of channel activation, the sodium conductance (GNa) was calculated as described in Materials and Methods. For beta2+/+ and beta2–/– small-slow DRGs neurons (Fig. 2C,D), V1/2 and k were similar for both TTX-R and TTX-S INa; only Gmax for TTX-S INa showed a reduction of ~29% in beta2–/– neurons compared with beta2+/+ neurons, however this reduction was not significant (p = 0.665). For small-fast cells, the mean value of V1/2 and k were also similar for TTX-R and TTX-S INa between groups (Fig. 2B). The Gmax for TTX-R INa was ~30% smaller in beta2–/– cells compared with beta2+/+ (Fig. 2A, dashed lines), but, again, this difference was not significant (p = 0.083). In contrast, the Gmax for TTX-S INa measured in beta2–/– neurons was ~51% smaller than that observed in beta2+/+ cells (Fig. 2A, solid lines), and this reduction was statistically significant (p = 0.001). These results suggest that beta2 subunits regulate cell-surface levels of TTX-S but not TTX-R Nav1 in DRG neurons. Alternatively, it is possible that beta2 alters TTX-S Nav1 single-channel conductance; however, based on our previous results (Isom et al., 1995bGo; Chen et al., 2002Go), we propose that the former is the most likely mechanism of beta2 action.


Figure 2
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Figure 2. Voltage dependence of activation. A, Activation curve of peak sodium conductance: TTX-R (circles) and TTX-S (squares) obtained from the same small-fast cells as in Figure 1B, beta2+/+ (closed symbols), and beta2–/– (open symbols). Smooth lines are fits to a Boltzmann function for TTX-R (dashed lines) and TTX-S (solid lines) currents, respectively. B, Midpoint potential (V1/2) and slope factor (k) of fitted activation curves of small-fast cells. C, D, Same small-slow cells as in Figure 1C with symbols as in A and B. Error bars indicate SEM.

 
beta2 does not affect the voltage dependence of INa inactivation
Steady-state inactivation was measured as described in Materials and Methods. An example of the INa obtained from a typical small-fast beta2+/+ neuron in response to a test pulse to 0 mV is shown in the inset to Figure 3A. In this example, as in practically all small-fast DRG neurons tested, the fast INa (TTX-S) is inactivated at more negative voltages than the slow INa (TTX-R). The mean of the individual curves are shown in Figure 3A for small-fast neurons and in Figure 3C for small-slow neurons. The corresponding V1/2 and k are compared in Figure 3, B and D. The voltage dependence of TTX-S and TTX-R INa inactivation in small beta2–/– neurons was nearly identical to that of TTX-S and TTX-R INa of small beta2+/+ neurons (Fig. 3), therefore the beta2 subunit does not regulate the INa voltage dependence in small DRG neurons.


Figure 3
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Figure 3. Voltage dependence of inactivation. A, Peak INa at 0 mV, normalized to its maximal value (inset), as a function of voltage during a 500 ms prepulse. INa were measured from beta2+/+ (n = 13; closed circles) and beta2–/– (n = 10; open circles) small-fast DRG neurons. Each data set was fit with a double Boltzmann function (lines). The inset is an example of INa at 0 mV, from one small-fast beta2+/+ cell, after 500 ms prepulses from –90 to –10 mV. B, Parameters of fitted inactivation curves shown in A; circles represent the first component (TTX-S), and squares represent the second component (TTX-R). C, D, Inactivation curves and parameters, respectively, for small-slow beta2+/+ (n = 12) and beta2–/– (n = 8) neurons; symbols are as in A and B. Error bars indicate SEM.

 
According to our classification of cells into small-fast and small-slow based on the proportion of TTX-S INa to that of TTX-R INa, the average values of F1 and F2 (the proportion of TTX-S and TTX-R INa) are close to 0.7 and 0.3, respectively, for both beta2+/+ and beta2–/– small-fast cells. For small-slow cells, F1 and F2 are ~0.1 and 0.9, respectively. Thus, the main INa for small-fast cells is TTX-S, whereas for small-slow cells it is TTX-R.

Effects of beta2 on INa kinetics
The rate of channel recovery from inactivation was measured as described in Materials and Methods. A typical set of INa traces obtained using this protocol is shown in the inset of Figure 4. In agreement with previous reports, the recovery from inactivation curve shows two components: the TTX-R INa shows fast recovery, and the TTX-S INa shows slow recovery (Cummins and Waxman, 1997Go; Rush et al., 1998Go). Time constants for beta2+/+ were {tau}1 = 1.3 ± 0.2 ms and {tau}2 = 95.3 ± 17.8 ms (n = 6), and time constants for beta2–/– were {tau}1 = 1.5 ± 0.5 ms and {tau}2 = 83.3 ± 29.4 ms (n = 6); the fraction of TTX-S INa was 0.88 ± 0.03 and 0.80 ± 0.12 for beta2+/+ and beta2–/–, respectively. There were no significant differences between groups.


Figure 4
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Figure 4. Recovery from inactivation. The average time course of recovery from inactivation for total INa from small-fast neurons beta2+/+ (closed symbols; n = 6) and beta2–/– (open symbols; n = 5) is shown. The data were fit with a double exponential (lines) with the following results: for beta2+/+, {tau}1 = 1.3 ± 0.2 ms and {tau}2 = 95.3 ± 17.8 ms; for beta2–/–, {tau}1 = 1.5 ± 0.5 ms and {tau}2 = 83.3 ± 29.4 ms. Inset, A representative record from one beta2+/+ cell shows INa obtained from recovery intervals of 0.25–30 ms to –120 mV. Error bars indicate SEM.

 
Superimposition of INa obtained from small-fast beta2+/+ and beta2–/– neurons suggested different rates of channel activation and inactivation (Fig. 5A). To evaluate the activation kinetics, two points on each time course were measured: the time to achieve 50% of the maximum current after onset of the test pulse to 0 mV (T1/2 peak), and the time to achieve the peak INa with the same test pulse (Tpeak). Comparing both groups of small-fast neurons, these times were significantly different (Fig. 5B) with T1/2peak and Tpeak for beta2–/– (n = 12), 60 and 69% longer than beta2+/+ (n = 16) neurons, respectively. To evaluate the inactivation kinetics for the same INa, the decaying phase of the INa was fit using a double-exponential function, obtaining two inactivation time constants ({tau}fast and {tau}slow). Only {tau}fast was affected by the loss of beta2 expression (Fig. 5C): {tau}fast = 1.25 ± 0.17 ms for beta2+/+ neurons compared with 2.13 ± 0.23 ms for beta2–/– neurons, an increase of ~70%. In contrast, {tau}slow was the same for both groups (Fig. 5C). We performed similar analyses for small-slow beta2+/+ (n = 11) and beta2–/– (n = 9) neurons. Neither activation nor inactivation kinetics were statistically different (data not shown).


Figure 5
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Figure 5. Activation and inactivation kinetics of INa at 0 mV. A, Normalized INa evoked by a test pulse to 0 mV from a holding potential of –80 mV. INa are shown from a typical small-fast beta2+/+ cell and a typical small-fast beta2–/– cell. B, Time to achieve 50 and 100% activation. The data were obtained from small-fast beta2+/+ (n = 16) and small-fast beta2–/– (n = 18) neurons. C, Time constants of INa inactivation for the same cells as in B. The two time constants of inactivation ({tau}fast and {tau}slow) were obtained by fitting the decay phase of the INa with a double-exponential function. *p < 0.05, Significantly different from beta2+/+. Error bars indicate SEM.

 
Nav1 mRNA levels are regulated by beta2
To begin to investigate the molecular basis for the observed reduction in TTX-S INa in beta2–/– neurons, we measured Nav1 {alpha} and beta subunit mRNA levels in DRGs from both wild-type and null mice. The profile of expression and relative abundance of Nav1 subunit transcripts (Nav1.1, Nav1.2, Nav1.3, Nav1.6, Nav1.7, Nav1.8, and Nav1.9 and beta1, beta2, beta3, and beta4) (Table 1) were evaluated independently in beta2+/+ and beta2–/– mice by real-time reverse transcription (RT)-PCR. Nav1 subunit mRNA levels were normalized to the highest Nav1 subunit transcript expressed in beta2+/+ DRGs: Nav1.7 for {alpha} subunits and beta1 for beta subunits (Fig. 6). In both genotypes, the order of the Nav1 subunit transcript expression levels was the same, with the exception of beta2 in the null mice: Nav1.7 > Nav1.8 > Nav1.9 > Nav1.6 > Nav1.1 > Nav1.3 > Nav1.2 and beta1 > beta4 > beta3 > beta2. In beta2+/+ DRGs, the Nav1.7 transcript was the most abundant. It was twice as abundant as Nav1.6, ~7 times more abundant than Nav1.3 or Nav1.1, and ~25 times more abundant than Nav1.2, all TTX-S channels. In addition, Nav1.7 was more abundant than transcripts for the TTX-R channels Nav1.8 and Nav1.9 (Fig. 6A). For mRNA of beta subunits, beta1 was 6–10 times more abundant than the other beta subunits (Fig. 6B). Interestingly, beta2 appeared to be the lowest expressed beta subunit mRNA; however, as shown above, it plays a major functional role in DRG neurons.


Figure 6
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Figure 6. Expression levels of Nav1 mRNAs in DRGs. A, Transcript levels of Nav1 {alpha} subunits expressed in beta2+/+ (filled bars) and beta2–/– (open bars) DRGs; all levels are normalized to Nav1.7 levels measured in beta2+/+ DRGs. B, Normalized transcript levels of beta subunits to beta1 expressed in beta2+/+ DRGs. Data are mean ± SEM from a real-time reverse transcription-PCR experiment performed in triplicate using a mix of three samples.

 
In beta2–/– DRGs, the profile of {alpha} and beta subunit expression did not change, with the exception of beta2. However, the abundance of some subunit transcripts did change, notably Nav1.7 (p = 0.043) (Fig. 6). Experiments were then performed to determine the ratios of specific subunit mRNA expression levels in null versus wild-type neurons. beta2+/+ and beta2–/– DRGs were assessed by real-time RT-PCR and normalized to GAPDH. The ratios of Nav1 {alpha} and beta subunit transcript levels in beta2–/–/beta2+/+ DRGs are shown in Figure 7. The expression levels of three TTX-S Nav1 transcripts, Nav1.3, Nav1.6 and Nav1.7, were significantly reduced (p < 0.05) 20–25% by the beta2 null mutation (Fig. 7A); similar reductions were found for beta3 and beta4 mRNAs (Fig. 7B), whereas no changes were observed for the other subunits.


Figure 7
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Figure 7. Effect of the beta2 null mutation on Nav1 mRNA levels. A, Ratio of beta2–/–/beta2+/+ transcript levels for {alpha} subunit mRNAs. B, Ratio of beta2–/–/beta2+/+ transcript levels for beta subunit mRNAs. Black bars, mRNA level does not change; gray bars, mRNA level is reduced. *p < 0.05.

 
TTX-S Nav1 protein is regulated by beta2
Western blot analyses of membrane preparations of DRG neurons for the TTX-S {alpha} subunits Nav1.7, Nav1.6, and Nav1.1, all normalized to {alpha}-tubulin as a housekeeping protein loading control, were performed to determine whether the observed changes in mRNA expression were reflected at the level of protein. Changes in mRNA levels are not always reflected by altered protein expression, with Nav-beta2 subunits serving as an example of this phenomenon (Malhotra et al., 2001Go; Pertin et al., 2005Go). We observed that Nav1.1 and Nav1.7 protein levels were reduced in beta2–/– DRG neurons compared with beta2+/+, whereas the levels of Nav1.6 did not appear to change (Fig. 8A). Similar results to those shown in the figure were obtained from three or four independent experiments. Immunoreactive bands were normalized to {alpha}-tubulin by densitometry, and changes in beta2–/– levels were expressed as a percentage of wild-type levels for each Nav1 (Fig. 8B). These calculations showed that Nav1.1 (p = 0.082; n = 3) and Nav1.7 (p < 0.001; n = 3) were reduced in the null DRGs compared with wild type. The values for Nav1.6 were not significantly different (p = 0.23; n = 4). We propose that the observed reduction in mRNA and protein levels of Nav1.7 (and possibly the reduction in Nav1.1 protein expression) may underlie the reduction in TTX-S INa measured in beta2–/– neurons.


Figure 8
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Figure 8. Reduction in TTX-S Nav1 protein levels in beta2 null neurons. A, Equal aliquots of DRG protein homogenates were separated by SDS-PAGE, transferred to nitrocellulose, and probed with specific Nav1 {alpha} subunit antibodies as indicated. All blots were subsequently probed with anti-{alpha}-tubulin to control for sample loading. The {alpha}-tubulin blot corresponding to the Nav1.7 blot is shown as an example. B, Immunoreactive bands were quantified using densitometry. Each band density was first normalized to its corresponding {alpha}-tubulin signal, and beta2–/– levels for each Nav1 were expressed as a percentage of beta2+/+ levels. For Nav1.1 and Nav1.7: #p < 0.1; *p < 0.05; n = 3. There was no significant change for Nav1.6 (n = 4). Error bars represent SEM.

 
beta2–/– mice show increased thermal but not mechanical sensitivity
Because TTX-S Nav1s are involved in nociceptive transmission, we hypothesized that beta2–/– mice would exhibit altered responses to noxious stimuli. We showed previously that beta2 expression is upregulated in sensory neurons in neuropathic pain and that development of mechanical allodynia in the SNI model is attenuated in beta2–/– mice compared with wild type (Pertin et al., 2005Go). To determine whether beta2 also plays a role in acute pain pathways, we compared the responses of the beta2–/– mice to acute thermal and mechanical stimuli with those of their wild-type littermates. In the hot-plate test at 49°C (Fig. 9A), beta2+/+ mice exhibited a latency of response of 34.9 ± 3.0 s. In contrast, beta2–/– mice displayed a significantly shorter response latency of 27.4 ± 1.5 s (p < 0.05; n = 9 in each group). At higher temperatures, no difference was observed between groups (p ≥ 0.05). To confirm the hot-plate test results and to determine whether thermal hypersensitivity in beta2–/– mice was induced by spinal processes, we evaluated the simple tail-flick reflex response to a radiant heat beam focused on the tail. At a low-intensity setting (4) of the tail-flick analgesia meter (Fig. 9B), the latency was significantly shorter in beta2–/– mice (5.5 ± 1.1 s) compared with beta2+/+ mice (9.1 ± 1.2 s) (p < 0.01; n = 4 in each group). At a higher intensity (7), a difference between the two groups was not discernible (p ≥ 0.05) (Fig. 9B). To investigate whether compensatory upregulation of heat-sensing genes occurred in the beta2–/– mice and thus could be responsible for the observed thermal hypersensitivity, we measured the levels of TRPV1 and TRPV2 in DRGs isolated from beta2+/+ and beta2–/– mice. No differences were detected between the two genotypes (TRPV1: ratio beta2–/–/beta2+/+ was 0.95, p = 0.57; TRPV2: ratio beta2–/–/beta2+/+ was 0.99, p = 0.95).


Figure 9
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Figure 9. Noxious heat sensitivity. A, In the hot-plate test at 49°C, the latency response was decreased in beta2–/– mice compared with beta2+/+ animals (n = 9 in each group; * p < 0.05). At higher temperatures (52 and 55°C), no statistically significant difference was observable. B, Tail-flick test. Values represent the latency response from the heat source. The latency decreased significantly in beta2–/– mice compared with beta2+/+ (n = 4 in each group; *p < 0.01). No differences were observed at higher intensities. Error bars indicate SEM.

 
Mechanical withdrawal threshold responses to a series of calibrated monofilaments applied to both paws in both groups were also recorded. Deletion of beta2 did not modify the animals’ response, and we did not observe any significant differences between groups (p ≥ 0.05; n = 9 in each group) (Fig. 10). For beta2+/+ mice, the values were 0.246 ± 0.05 g (left hindpaw) and 0.249 ± 0.07 g (right hindpaw) compared with 0.235 ± 0.05 g (left hindpaw) and 0.283 ± 0.08 g (right hindpaw) for beta2–/– mice.


Figure 10
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Figure 10. Basal mechanical sensitivity. Withdrawal mechanical thresholds were similar in beta2+/+ and beta2–/– animals (n = 9 in each group; p > 0.05). Error bars indicate SEM.

 
beta2–/– mice show reduced response to inflammatory pain
We next performed an extended formalin test to determine the role of beta2 in this model of acute and inflammatory pain (Tjolsen et al., 1992Go; Wei et al., 2001Go). During the initial phase of acute pain, the responses of beta2–/– and beta2+/+ mice were similar (Fig. 11). After the initial phase, an early second phase from 10 to 55 min and a later second phase from 55 to 80 min have been described previously (Wei et al., 2001Go). These late phases are considered to be models of inflammatory pain (Tjolsen et al., 1992Go). During the late phase, the behavioral response of beta2–/– mice was significantly attenuated when compared with beta2+/+ mice (Fig. 11).


Figure 11
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Figure 11. Formalin test. A, Time course of the formalin response after intraplantar injection of 10 µl of 5% formalin. B, Cumulative formalin response to the initial phase (0–10 min), early second phase (10–55 min), and late second phase (55–80 min). beta2+/+, filled bars or symbols; beta2–/–, open bars or symbols. n = 6 per group; *p < 0.05. Error bars indicate SEM.

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Nav1s in sensory neurons control membrane excitability and contribute to the transmission of nociceptive information to the spinal cord. Both TTX-S and TTX-R Nav1s are expressed in DRG neurons (Baker and Wood, 2001Go), as are beta1, beta1A, beta2, beta3, and beta4 (Black et al., 1996Go; Kazen-Gillespie et al., 2000Go; Yu et al., 2003Go). The {alpha} subunit cDNAs express functional Nav1 in heterologous expression systems. However, for TTX-S {alpha} subunits, the currents characteristic of these channels expressed in isolation are quite different from native currents. Coexpression of the beta subunits with these channels results in shifts in the voltage dependence of activation and inactivation, changes in channel modal gating behavior resulting in increases in the rates of inactivation and recovery from inactivation (Isom et al., 1994Go), and increases in channel expression at the plasma membrane as assessed by 3H-saxitoxin binding (Isom et al., 1995aGo; Kazarinova-Noyes et al., 2001Go; McEwen et al., 2004Go). The beta subunit-mediated effects on TTX-R Nav1 expressed in heterologous systems are not well understood (Sangameswaran et al., 1996Go; Malhotra et al., 2001Go; Vijayaragavan et al., 2001Go, 2004Go), and the functional effects of Nav beta subunits on {alpha} are dependent on the recipient cell type in vitro (Chen et al., 2002Go; Meadows and Isom, 2005Go). Thus, the use of in vivo models is critical to the understanding of their physiological roles. The present studies using beta2 null mice make important and novel contributions to elucidating the function of beta2 in electrical signal transduction in sensory neurons and are the first report of the differential effects of beta2 on TTX-S versus TTX-R channels.

In the present study, we compared INa in DRG neurons isolated from beta2+/+ and beta2–/– mice to determine the effects of beta2 on TTX-S and TTX-R Nav1s in vivo. Small-fast DRG neurons acutely isolated from beta2–/– mice showed significant decreases in TTX-S but not TTX-R INa compared with DRG neurons isolated from wild-type littermates. This decrease was not a result of changes in the voltage dependence of activation or inactivation of TTX-S Nav1s. TTX-S, but not TTX-R, INa activation and inactivation kinetics in small-fast DRG neurons were significantly slower in beta2–/– mice compared with beta2+/+. Our results predict that beta2 expression results in increased levels of TTX-S Nav1 mRNA and protein expression, particularly Nav1.7, increased levels of TTX-S Nav1 cell-surface expression, and increased rates of TTX-S INa activation and inactivation in small-fast DRG neurons in vivo. TTX-R INa in small-slow and small-fast DRG neurons are insensitive to modulation by beta2.

Interestingly, the beta2 null mutation affects TTX-S INa in small-slow versus small-fast DRG neurons differently. TTX-S INa are dramatically reduced in small-fast neurons but are essentially unaffected in small-slow neurons. A possible explanation for this observation is that small-slow and small-fast DRG neurons may express vastly different levels of beta2 protein. Alternatively, perhaps these two neuronal populations express different profiles of TTX-S Nav1s that are differentially regulated by beta2 in vivo. Previously, we reported that beta2 protein expression is low in normal DRG neurons, although immunocytochemical staining could be detected in small, medium, and large cells (Pertin et al., 2005Go). Unfortunately, this low level of beta2 staining precluded our ability to perform a more complete analysis of differential expression in small neurons in the present study. Because beta2 mRNA levels are poor predictors of beta2 protein levels (Malhotra et al., 2001Go; Pertin et al., 2005