Existence of memory in membrane channels: analysis of ion current through a voltage-dependent potassium single channel.

Ion current fluctuation of voltage-dependent potassium channel in LßT2 cells has been investigated by autocorrelation function and DFA (detrended fluctuation analysis) methods. The calculation of the autocorrelation function exponent and DFA exponent of the sample was based on the digital signals or the 0-1 series corresponding to closing and opening of channels after routine evolution, rather than the sequence of sojourn times. The persistent character of the correlation of the time series was evident from the slow decay of the autocorrelation function. DFA exponent α was significantly greater than 0.5. The main outcome has been the demonstration of the existence of memory in this ion channel. Thus, the ion channel current fluctuation provided information about the kinetics of the channel protein. The result suggests the correlation character of the ion channel protein non-linear kinetics indicates whether the channel is open or not.

[Compared Markov with fractal models by using single-channel experimental and simulation data].

The gating mechanical kinetical of ion channels has been modeled as a Markov process. In these models it is assumed that the channel protein has a small number of discrete conformational states and kinetic rate constants connecting these states are constant, the transition rate constants among the states is independent both of time and of the previous channel activity. It is assumed in Liebovitch's fractal model that the channel exists in an infinite number of energy states, consequently, transitions from one conductance state to another would be governed by a continuum of rate constants. In this paper, a statistical comparison is presented of Markov and fractal models of ion channel gating, the analysis is based on single-channel data from ion channel voltage-dependence K+ single channel of neuron cell and simulation data from three-states Markov model.

Gating kinetics of potassium channel in rat dorsal root ganglion neurons analyzed with fractal model.

The kinetics of ion channels have been widely modeled as a Markov process. In these models it is assumed that the channel protein has a small number of discrete conformational states and kinetic rate constants connecting these states are constant. To study the gating kinetics of voltage-dependent K(+) channel in rat dorsal root ganglion neurons, K(+) channel current were recorded using cell-attached patch-clamp technique. The K(+) channel characteristic of kinetics were found to be statistically self-similar at different time scales as predicted by the fractal model. The fractal dimension D for the closed times and for the open times depend on the pipette potential. For the open and closed times of kinetic setpoint, it was found dependent on the applied pipette potential, which indicated that the ion channel gating kinetics had nonlinear kinetic properties. Thus, the open and closed durations, which had the voltage dependence of the gating of this ion channel, were well described by the fractal model.

Rescaled range analysis applied to the study delayed rectifier potassium channel kinetics.

The gating of ion channels has widely been modeled by assuming that the transitions between open and closed states are a memoryless process. Nevertheless, analysis of records of unitary current events suggests that the kinetic process presents long lags (antipersistent correlation). Here, using the patch-voltage clamp technique and the rescaled range method, activity of single-channel delayed rectifier K(+) channels was studied. The experiment result showed that reversal potential was -73.3 mV in cell-attached mode. For the sequences of alternating open and shut time intervals, the Hurst coefficients were calculated for four different pipette potentials in rat dorsal root ganglion neurons. H=0.34169+/-0.00672 (n=4) for V=-30 mV; H=0.34632+/-0.0142 (n=3) for V=-40 mV; H=0.39237+/-0.0113 (n=4) for V=-50 mV; H=0.3954+/-0.0012 (n=4) for V=-60 mV. When the Hurst method was applied to the results from a simulated four-state Markovian model, it showed that it had different experimental data H coefficient, the distribution of the data values had no correlations between them, in particular, H=0.2531+/-0.00403 (n=50) for V=-40 mV. This indicates that open-dwell times and closed-dwell times are long lag (namely, antipersistent correlation) and do not change with the pipette potential applied to the patch.

[Advances in research on ion-channel gating mechanism].

The history and current situation of cell membrane ion-channel gating mechanism study were reviewed, with an emphasis on the application and the latest developments of kinetic model in gating mechanism study; the problems in present study and ion-channel gating mechanism kinetics model for future investigations were finally discussed.

Detrended fluctuation analysis as a statistical method to study ion single channel signal.

The scaling behaviors of ion single channel current signal time series could be analyzed by means of detrended fluctuation analysis. Nevertheless, the statistical analysis of an ionic current signal recorded from voltage dependence K+ single channel is presented. The detrended fluctuation analysis (DFA) exponent alpha is significantly larger than 0.5, as (DFA) exponents were calculated for 4 different pipette potentials in rat dorsal root ganglion neurons. alpha=0.9475+/-0.006 for V=-30 mV; alpha=0.958+/-0.004 for V=-40 mV; alpha=0.966+/-0.005 for V=-50 mV; alpha=0.971+/-0.03 for V=-60 mV. The scaling exponents for different pipette potentials reveal the existence of memory in ion channels, and at the same time, the memory in ion channel depends on the pipette potential. The result of Markovian model data showed that it had different DFA exponent alpha which indicates that long-range correlation effect is present amongst the continued conducting states of the ion channel. Thus a scaling exponent description is found to characterize the fluctuation properties of the non-linear behaviors of ion channel kinetics regardless of whether the channel is in open or closed state.

Effects of nano red elemental selenium on sodium currents in rat dorsal root ganglion neurons.

Nano red elemental selenium (Nano-Se), was demonstrated to be useful in medical and scientific researches. Here, we investigated the effects of Nano-Se on sodium currents on rat dorsal root ganglion neurons (DRG), using the whole-cell patch clamp method. Nano-Se reversibly decrease the I(Na)(TTX-S) in a concentration-dependent, time-dependent and open-channel block manners without affecting I(Na)(TTX-R). It shifted the steady-state activation and inactivation curves for I(Na) to more negative potentials. In the research of recovery from inactivation, the recovery time constant is longer in the present of Nano-Se. Nano-Se had a weaker inhibitory effect on I(Na), compared with marked decrease caused by selenite which indicated that Nano-Se is less neurotoxic than selenite in short-term/large dose treatments and had similar bio availability to sodium selenite. The results of interaction between the effects of Nano-Se and selenite on sodium currents indicated a negative allosteric interaction between the selenite binding site and the Nano-Se binding site or that they have the same competitive binding site.

Modulation of nano-selenium on tetrodotoxin-sensitive voltage-gated sodium currents in rat dorsal root ganglion neurons.

Nano-Selenium, a novel Nano technology production, was demonstrated to be useful in medical and scientific researches. Here, we investigated the effects of Nano-Selenium on tetrodotoxin-sensitive (TTX-S) voltage-dependent Na+channels in isolated rat dorsal root ganglion neurons, using whole-cell patch-clamp method. Nano-Selenium irreversibly decreased TTX-S Na+current (INa) in a concentration-dependent manner and shifted the maximum of the current/voltage relationship from -67mV to -52mV, without modifying the threshold potential of the current. Nano-Selenium shifted the steady-state activation and inactivation curves to the left. In the contrast of Na2SeO3, the inhibition effect of 1nM Nano-Se was much stronger. The cell treated with 1nM Na2SeO3firstly, still respond to futher addition of 1nM Nano-Selenium. These results prove Nano-Selenium to be a novel antiagonist, acted within the channel pore, not on or near the exterior surface of the channel protein where it would experience the membrane electric field, which possesses a distinct binding site from Na2SeO3.

Correlation character of ionic current fluctuations in cell membrane ion channels.

The gating of ion channels has widely been modeled by assuming the transition between open and closed states is a memoryless process. Nevertheless, the statistical analysis of an ionic current signal recorded from voltage dependence K+ single channel is presented. Calculating the sample autocorrelation function of the ionic current based on the digitized signals, rather than the sequence of open and closed states durations time. The result is shown existence memory. For difference voltage, the ion channel current fluctuation has difference correlation attributions. The result suggests the correlation character of the ionic current fluctuations. Also the possible biological implication of the findings have been discussed.