INTRODUCTION

Top Abstract Introduction Materials & Methods Results Discussion Appendix A Appendix B References

SODIUM CHANNELS ARE responsible for the initial rapid increase in membrane permeability for Na⁺, which is essential for the generation and propagation of the action potential. Channel gating is determined by two fundamental channel properties: activation and inactivation. Coupling between activation and inactivation is an important characteristic of the Na⁺ channel, since it determines the functional response of the channels to membrane depolarization. Activation and inactivation mechanisms are the major targets in ongoing molecular studies of Na⁺ channel function (for review see Ref. 9). Activation is thought to involve movement of the highly charged fourth membrane-spanning segment S4 (32, 42). A hydrophobic triplet of amino acid residues in the cytoplasmic III-IV linker was suggested to form a lid that binds to a cytoplasmic region of the channel and occludes the pore, producing fast inactivation of the channel (25, 32, 41). Recently, it has been shown that mutations other than in the III-IV linker can affect inactivation as well. Complex alterations of the channel gating can be produced by mutations in the pore region (34) and in various cytoplasmic or transmembrane domains, e.g., mutations related to inherited heart diseases (4) or skeletal myopathies (28). These data suggest the importance of integrity of all channel molecule parts in the gating process. Furthermore, channel gating is determined also by the state of channel phosphorylation (33, 41), coexpression and association of the - and -subunits (17, 24), and factors that affect the channel environment, including membrane phospholipid composition and the cytoskeleton. Our previous studies showed that membrane partition of an ischemic metabolite, lysophosphatidylcholine, induced bursting activity of the cardiac Na⁺ channel and shifted activation toward negative membrane potentials (36). We also found that cytochalasin D (Cyto-D), a disrupter of the F-actin-based cytoskeleton, and antibodies to integrated proteins of the cytoskeleton, such as F-actin, -spectrin, and ankyrin, altered gating kinetics by increasing open time, inducing a second open state, and causing prolonged bursts of openings (23, 35, 37). These findings indicated that the environment of the channel protein, in addition to the channel protein structure itself, determines the microscopic activation-inactivation coupling.

In the present study we addressed whether the cytoskeleton regulates coupling of Na⁺ channel activation and inactivation in terms of the relationship between steady-state activation and availability from inactivation. We took advantage of the spontaneous shift of availability and conductance curves that occurs for the cardiac Na⁺ channel during whole cell recording (14, 16) to characterize the relationship in a wide range of the half-point potentials of the curves. Cytoskeleton modifiers changed the relationship, indicating a modulating role for the cytoskeleton in activation-inactivation coupling.

	MATERIALS AND METHODS

Top Abstract Introduction Materials & Methods Results Discussion Appendix A Appendix B References

Isolation of Cardiomyocytes

Whole Cell Current Recordings

I_Na was measured in 116 cells obtained from 34 rats. The characteristics of the current were monitored for as long as a stable seal could be maintained, as judged by a total current (I) measured at the holding potential (V_h = 150 mV) so that I > V_h/100 M = 1.5 nA. The duration of the whole cell experiment averaged 63 ± 5 min (maximum duration was 345 min). To attain stable recordings for long periods, we lifted cells from the surface of the recording chamber after recording configuration was established. The absence of vibrations was also an important requirement. To minimize vibrations, our experimental setup was mounted on an air-suspended table (model 63531, TMC, Peabody, MA).

Control and Test Solutions

We used Cyto-D as disrupter and phalloidin as stabilizer of an F-actin-based cytoskeleton. Colchicine was used as microtubule disrupter and taxol as microtubule stabilizer. The final concentration of substances in the incubation medium and pipette solution was 20 µM for Cyto-D and 100 µM for phalloidin, colchicine, and taxol. Fresh test solutions were made each day and sonicated before each experiment. The cells were incubated with the cytoskeleton modifiers at least 4 h before I_Na recording. Experiments with Cyto-D were performed in relative darkness to avoid photodestruction of the Cyto-D molecule. All substances were purchased from Sigma Chemical (St. Louis, MO).

Quality of Voltage Clamp

(1)

(2)

Voltage-Clamp Protocols

Data Analysis

(3)

Normalized voltage-dependent Na⁺ conductance [G(V)] was determined from transformations of I-V curves. The maximum Na⁺ conductance (g_max) and reversal potential (V_rev) were estimated from a linear fit [as a slope and a cross point with test potential (V_t) axis, respectively] of an almost linear ascending portion of the I-V curve. The Na⁺ conductance (g) at each V_t was calculated as

(4)

The data points of normalized conductance (G = g/g_max) were fitted to a third-degree Boltzmann function

(5)

The voltage dependence of steady-state activation was characterized by the half-point conductance potential (V_1/2G) determined for the normalized conductance curve, G(V_1/2G) = 0.5. V_1/2G was calculated as V_1/2G = a  K · ln(  1). We used the third-degree Boltzmann function for the data analysis, since it always fit data points better than a single Boltzmann function. However, these two fitting functions yielded almost the same V_1/2G values for the same data set: difference <0.1 mV.

To analyze the time course of changes in voltage-dependent availability and conductance, V_1/2A and V_1/2G were plotted as a function of experimental time. The initial slope of the negative shift (a shift rate) for V_1/2A and V_1/2G was determined from a linear fit to data points taken for the initial period (first 8 min) of an experiment. The time-dependent shifts of V_1/2A and V_1/2G were fitted with an exponential function (see Eqs. A1 and A2).

To determine the V_1/2G-V_1/2A relationship, we measured these parameters consecutively in the same cell. Because of a minimum delay of ~2 min related to our experimental protocol, it was impossible to measure both parameters simultaneously. Therefore, for every V_1/2A(t_i) measured at time t_i (1 < i < N, where N is total number of measurements made in the cell), we calculated the coupled V_1/2G(t_i) from the previously measured value, V_1/2G(), and the next value, V_1/2G(t_i + 1), assuming a linear time-dependent shift of V_1/2G between and t_i + 1.

Origin software (version 4.1, Microcal Software, Northampton, MA) was used to fit histograms by a Gaussian function

(6)

where A is area, Xc is center, and W is width of the function. Other nonlinear curve fittings were done by pCLAMP (version 6.0, Axon Instruments) and StatMost (version 2.50, DataMost, Salt Lake City, UT) software. The best model describing the V_1/2G-V_1/2A relationship was chosen from exponential, power, linear, and hyperbolic functions as judged by a smaller variance and by parameters of goodness-of-fit statistics given by StatMost software. The parameters included the correlation coefficient, the coefficient of determination, and the model selection criterion defined in APPENDIX B.

Statistical significance when comparing mean values was determined by Student's t-test for unpaired data. If not otherwise stated, the two pools of data were considered to be significantly different at P < 0.01. Results are presented as means ± SE for n cells.

	RESULTS

Top Abstract Introduction Materials & Methods Results Discussion Appendix A Appendix B References

Characterization of the Relationship Between Availability and Activation in Control Cells

Time-dependent shifts of steady-state availability and conductance curves were exponential. We monitored the time-dependent shift of V_1/2G and V_1/2A in 51 control cells with a mean recording time of 70.6 ± 5.2 min. The range for the shift in V_1/2G (from 29 to 76 mV) was significantly smaller than for V_1/2A (from 68 to 128 mV). The time-dependent changes of both parameters exhibited an exponential saturation (Fig. 1A). The time course of the shifts was obviously not parallel, because the change in V_1/2G was smaller and saturated faster. Time constants and saturation values for the exponentials fitted to the shifts are given in Table 1. Generally, the V_1/2G shift was saturated within ~20 min, whereas V_1/2A shifted over 40-60 min. Although the overall shifts were different, the initial shift rate recorded within the first 8 min of the experiment was not significantly different for these parameters (Table 2). Thus we found an almost parallel shift of availability and conductance at the beginning of the recording. In some cells we observed independent changes in V_1/2G and V_1/2A during whole cell recording. This occurred in cells that initially (spontaneously) had a saturation value of V_1/2G or V_1/2A. Once the parameter was found at the saturated level, it did not change, whereas another parameter shifted exponentially (Fig. 1, C and D).

View larger version (28K): [in this window] [in a new window]   Fig. 1.   Relationship between half-points of conductance curve (V1/2G) and availability curve (V1/2A) during long-term recording in whole cell patch clamp. A: representative example of simultaneous monitoring of exponential shift for V1/2A () and V1/2G (). Solid lines, exponential fits with their time constants (). B: V1/2G-V1/2A relationship derived for data points shown in A after time factor was excluded. A power function (solid line) was generated for relationship using Eq. A3. C and D: independent shifts of V1/2G () and V1/2A (). One parameter did not shift during experiment, whereas another parameter shifted exponentially. Vs, saturation potential.

V_1/2G-V_1/2A Relationship Is Described by a Power Function

A theoretical prediction. Because we have found that V_1/2G and V_1/2A have an exponential time course, their relationship after the time factor is excluded can be easily shown to be a power function with a degree equal to the ratio of the time constants ( = _A/_G; see APPENDIX A). The relationship was obviously nonlinear, since the time constants _A and _G were significantly different (  2; Table 1). The suitability of the theoretical prediction to the data points of the V_1/2G-V_1/2A relationship is illustrated in Fig. 1B, which shows the power function determined in one cell from the exponential fits to the V_1/2G and V_1/2A time course.

Experimental evidence. We plotted data points (n = 1,021) measured during whole cell recordings in 51 control cells (Fig. 2). The best fit of the plot was the power function with a degree close to 2 (solid line in Fig. 2). A detailed comparison of the fits obtained by using different models is given in Tables 3 and 4. The data points were spread along the V_1/2G axis, indicating no strict dependence between the parameters. We calculated the histogram of departures of data points from the power function fit. The histogram was fitted to a Gaussian function (Fig. 2, inset). The power function fit and parameters of the Gaussian function were used as a reference to describe effects of cytoskeleton modifiers on the V_1/2G-V_1/2A relationship (see below).

View larger version (34K): [in this window] [in a new window]   Fig. 2.   V1/2G-V1/2A relationship determined in 51 control myocytes (1,021 determinations). Model best describing relationship was a power function [f(x)] shown by solid line. Inset: histogram of deflections of data points from power fit for all data points in plot (bin size = 1.2 mV). Vdep, departure of V1/2G from reference line. Histogram was fitted by a Gaussian function given by Eq. 6 (solid line), with values of Xc (center) and W (width) shown in plot.

View this table: [in this window] [in a new window]   Table 4.   Comparison of different models describing data points in V1/2G  V1/2A relationship in Fig. 2

Effects of Cytoskeleton Modifiers on the Relationship Between Availability and Activation

Effects of cytoskeleton modifiers on the time course of V_1/2G and V_1/2A. The effects of cytoskeleton modifiers were characterized by parameters of exponential fits to the time course of V_1/2G and V_1/2A shifts (Table 1) and by changes in initial rates of the shifts (Table 2). The V_1/2A shift rate was accelerated by an F-actin disrupter, Cyto-D (>2 times) but was slowed by an F-actin stabilizer, phalloidin. Whereas Cyto-D or phalloidin changed the V_1/2G shift rate insignificantly, the V_1/2G shift rate was accelerated by taxol, a microtubule stabilizer (Table 2). Although in the presence of phalloidin the effect of taxol was attenuated, the V_1/2G shift rate remained significantly faster than in control cells. Cyto-D changed the time course of V_1/2A to an almost linear (monotonic) shift (not shown). At the same time, the V_1/2G time course remained exponential, with a time constant similar to that of control cells (Table 1). The net V_1/2G change was less in Cyto-D-treated than in control cells by ~7.5 mV, which resulted from the difference between saturation potentials (V_1/2G; Table 1).

View larger version (23K): [in this window] [in a new window]   Fig. 3.   F-actin stabilizer phalloidin temporally prevented time-dependent shift of availability curve during whole cell recording. Examples of time-dependent shifts of V1/2A and V1/2G in cells treated with 100 µM phalloidin are shown. V1/2G changed exponentially in cells. At the same time, onset of exponential V1/2A shift was delayed (during interval t0, arrows); absolute value of shift rate was <0.1 mV/min. Solid lines, exponential fits with their time constants ().

Effects of cytoskeleton modifiers on the V_1/2G-V_1/2A relationship. To examine the cytoskeleton modulation of the V_1/2G-V_1/2A relationship, we compared the relationships obtained when myocytes were treated with cytoskeleton disrupters (Fig. 4) and with stabilizers (Fig. 5). The reference line of the power function fit established in control cells (Fig. 2) is shown in the plots to visualize the modulation effect. The position of data points was clearly shifted above the reference line in Cyto-D-treated cells (Fig. 4A). To quantify the modulation effects of cytoskeleton modifiers on the V_1/2G-V_1/2A relationship, we calculated the histograms (insets in Figs. 2, 4, and 5) of departure of data points from the reference line along the V_1/2G axis. The parameters of a Gaussian function fitted to the histograms [center (Xc) and width (W); Fig. 4A, inset] in cells treated with cytoskeleton modifiers were compared with those of control cells (Fig. 2, inset). Whereas the center of distribution in control cells was at zero, Xc values were significantly shifted (by 2.5 mV) toward more positive values in Cyto-D-treated cells. A microtubule disrupter, colchicine, however, did not potentiate the Cyto-D effect (Fig. 4B).

View larger version (25K): [in this window] [in a new window]   Fig. 4.   Effect of cytoskeleton disrupters on V1/2G-V1/2A relationship. A: cytochalasin D (Cyto-D, 20 µM) shifted relationship to more positive V1/2G values (243 data points measured in 14 cells). B: colchicine (100 µM) did not potentiate Cyto-D effect (124 data points measured in 4 cells). Effect of cytoskeleton modifiers is shown in comparison to position of parabolic curve (solid line) representing best fit for relationship in control cells (same line as in Fig. 2). Insets: histograms of V1/2G departure from reference line. Histograms were calculated with a bin value of 1.2 mV for overall data points in each plot and fitted by a Gaussian function (solid line) given by Eq. 6, with values of Xc and W shown in plots.

View larger version (27K): [in this window] [in a new window]   Fig. 5.   Effect of cytoskeleton stabilizers on V1/2G-V1/2A relationship. A: phalloidin (100 µM) did not shift relationship (441 determinations in 22 cells). B: taxol (100 µM) significantly shifted relationship toward negative V1/2G values (251 determinations in 12 cells). C: phalloidin + taxol reduced taxol effect (284 determinations in 13 cells). Reference line is parabolic curve representing best fit for relationship in control cells (same line as in Fig. 2). Insets: histograms of V1/2G departure from reference line. Histograms were calculated with a bin value of 1.2 mV for overall data points in each plot and fitted by a Gaussian function (a solid line) given by Eq. 6, with values of Xc and W shown in plots.

Slope factors of G(V) and A(V) curve were not influenced by cytoskeleton modifiers. The slope factor for the G(V) curve increased during whole cell recording from K(t = 0) = 5.65 ± 0.28 mV (measured in 51 cells) to a steady-state level of 7.18 ± 0.14 mV after 40 min of recording. The time course of the change was well described by an exponential function, with a time constant of the best fit to all data points of 15.8 min (not shown). The slope factor for the A(V) curve did not change during the experiment: 5.59 ± 0.09 mV at the beginning of the experiment and 5.61 ± 0.09 mV after 60 min of whole cell recording. Cytoskeleton modifiers did not influence the slope factors for conductance or availability (not shown).

	DISCUSSION

Top Abstract Introduction Materials & Methods Results Discussion Appendix A Appendix B References

An important role for the cytoskeleton in the modulation of gating for Na⁺ channels of different types has been previously described (8, 23, 29, 35, 37). In the present study, using the spontaneous shift of voltage dependence of activation and inactivation gating (16) as a model, we established that 1) the half-points of steady-state activation and availability curves for cardiac Na⁺ channels are coupled by a second-degree power function and 2) the relationship is modulated by F-actin- and tubulin-based cytoskeleton.

Time-Dependent Shift of Availability and Activation Are Modulated by the Cytoskeleton

V_1/2G-V_1/2A Relationship Is Modulated by Cytoskeleton

Our finding that stabilization of F-actin by phalloidin influenced availability but not activation is consistent with single channel data. We previously reported that Cyto-D and antibodies to F-actin modulate channel gating by increasing open time and causing frequent reopenings of the Na⁺ channel observed as prolonged bursts of channel openings (23, 35, 37). The changes mainly related to inactivation state but not to activation. Thus the data of single channel studies together with the present data show a degree of independent changes modulated by the F-actin cytoskeleton on the level of microscopic and macroscopic parameters in inactivation.

Possible Mechanisms of Cytoskeleton Influence on Na⁺ Channel Steady-State Activation and Availability

Physiological Significance

In conclusion, we have shown that coupling between Na⁺ channel voltage-dependent availability and activation is modulated by F-actin-based and microtubular cytoskeleton. The cytoskeleton modulation of cardiac Na⁺ channel gating could be important in maintaining normal myocyte excitability.