Fast inactivation in Shaker K+ channels. Properties of ionic and gating currents.

Fast inactivating Shaker H4 potassium channels and nonconducting pore mutant Shaker H4 W434F channels have been used to correlate the installation and recovery of the fast inactivation of ionic current with changes in the kinetics of gating current known as "charge immobilization" (Armstrong, C.M., and F. Bezanilla. 1977. J. Gen. Physiol. 70:567-590.). Shaker H4 W434F gating currents are very similar to those of the conducting clone recorded in potassium-free solutions. This mutant channel allows the recording of the total gating charge return, even when returning from potentials that would largely inactivate conducting channels. As the depolarizing potential increased, the OFF gating currents decay phase at -90 mV return potential changed from a single fast component to at least two components, the slower requiring approximately 200 ms for a full charge return. The charge immobilization onset and the ionic current decay have an identical time course. The recoveries of gating current (Shaker H4 W434F) and ionic current (Shaker H4) in 2 mM external potassium have at least two components. Both recoveries are similar at -120 and -90 mV. In contrast, at higher potentials (-70 and -50 mV), the gating charge recovers significantly more slowly than the ionic current. A model with a single inactivated state cannot account for all our data, which strongly support the existence of "parallel" inactivated states. In this model, a fraction of the charge can be recovered upon repolarization while the channel pore is occupied by the NH2-terminus region

Combining polynomial chaos expansions and genetic algorithm for the coupling of electrophysiological models

The number of computational models in cardiac research has grown over the last decades. Every year new models with di erent assumptions appear in the literature dealing with di erences in interspecies cardiac properties. Generally, these new models update the physiological knowledge using new equations which reect better the molecular basis of process. New equations require the fi tting of parameters to previously known experimental data or even, in some cases, simulated data. This work studies and proposes a new method of parameter adjustment based on Polynomial Chaos and Genetic Algorithm to nd the best values for the parameters upon changes in the formulation of ionic channels. It minimizes the search space and the computational cost combining it with a Sensitivity Analysis. We use the analysis of di ferent models of L-type calcium channels to see that by reducing the number of parameters, the quality of the Genetic Algorithm dramatically improves. In addition, we test whether the use of the Polynomial Chaos Expansions improves the process of the Genetic Algorithm search. We conclude that it reduces the Genetic Algorithm execution in an order of 103 times in the case studied here, maintaining the quality of the results. We conclude that polynomial chaos expansions can improve and reduce the cost of parameter adjustment in the development of new models.Peer ReviewedPostprint (author's final draft

Thermal Impact on Spiking Properties in Hodgkin-Huxley Neuron with Synaptic Stimulus

The effect of environmental temperature on neuronal spiking behaviors is investigated by numerically simulating the temperature dependence of spiking threshold of the Hodgkin-Huxley neuron subject to synaptic stimulus. We find that the spiking threshold exhibits a global minimum in a "comfortable temperature" range where spike initiation needs weakest synaptic strength, indicating the occurrence of optimal use of synaptic transmission in neural system. We further explore the biophysical origin of this phenomenon in ion channel gating kinetics and also discuss its possible biological relevance in information processing in neural systems.Comment: 10 pages, 4 figure

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

The selectivity, voltage-dependence and acid sensitivity of the tandem pore potassium channel TASK-1 : contributions of the pore domains

We have investigated the contribution to ionic selectivity of residues in the selectivity filter and pore helices of the P1 and P2 domains in the acid sensitive potassium channel TASK-1. We used site directed mutagenesis and electrophysiological studies, assisted by structural models built through computational methods. We have measured selectivity in channels expressed in Xenopus oocytes, using voltage clamp to measure shifts in reversal potential and current amplitudes when Rb+ or Na+ replaced extracellular K+. Both P1 and P2 contribute to selectivity, and most mutations, including mutation of residues in the triplets GYG and GFG in P1 and P2, made channels nonselective. We interpret the effects of these—and of other mutations—in terms of the way the pore is likely to be stabilised structurally. We show also that residues in the outer pore mouth contribute to selectivity in TASK-1. Mutations resulting in loss of selectivity (e.g. I94S, G95A) were associated with slowing of the response of channels to depolarisation. More important physiologically, pH sensitivity is also lost or altered by such mutations. Mutations that retained selectivity (e.g. I94L, I94V) also retained their response to acidification. It is likely that responses both to voltage and pH changes involve gating at the selectivity filter

Designing all-graphene nanojunctions by covalent functionalization

We investigated theoretically the effect of covalent edge functionalization, with organic functional groups, on the electronic properties of graphene nanostructures and nano-junctions. Our analysis shows that functionalization can be designed to tune electron affinities and ionization potentials of graphene flakes, and to control the energy alignment of frontier orbitals in nanometer-wide graphene junctions. The stability of the proposed mechanism is discussed with respect to the functional groups, their number as well as the width of graphene nanostructures. The results of our work indicate that different level alignments can be obtained and engineered in order to realize stable all-graphene nanodevices

Numerical Solution of Differential Equations by the Parker-Sochacki Method

A tutorial is presented which demonstrates the theory and usage of the Parker-Sochacki method of numerically solving systems of differential equations. Solutions are demonstrated for the case of projectile motion in air, and for the classical Newtonian N-body problem with mutual gravitational attraction.Comment: Added in July 2010: This tutorial has been posted since 1998 on a university web site, but has now been cited and praised in one or more refereed journals. I am therefore submitting it to the Cornell arXiv so that it may be read in response to its citations. See "Spiking neural network simulation: numerical integration with the Parker-Sochacki method:" J. Comput Neurosci, Robert D. Stewart & Wyeth Bair and http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2717378

Deletion of the S3–S4 Linker in theShaker Potassium Channel Reveals Two Quenching Groups near the outside of S4

When attached outside the voltage-sensing S4 segment of the Shaker potassium channel, the fluorescent probe tetramethylrhodamine (TMRM) undergoes voltage-dependent fluorescence changes (ΔF) due to differential interaction with a pH-titratable external protein-lined vestibule (Cha, A., and F. Bezanilla. 1998. J. Gen. Physiol. 112:391–408.). We attached TMRM at the same sites [corresponding to M356C and A359C in the wild-type (wt) channel] in a deletion mutant of Shaker where all but the five amino acids closest to S4 had been removed from the S3–S4 linker. In the deletion mutant, the maximal ΔF/F seen was diminished 10-fold, and the ΔF at M356C became pH independent, suggesting that the protein-lined vestibule is made up in large part by the S3–S4 linker. The residual ΔF showed that the probe still interacted with two putative quenching groups near the S4 segment. One group was detected by M356C-TMRM (located outside of S3 in the deletion mutant) and reported on deactivation gating charge movement when applying hyperpolarizing voltage steps from a holding potential of 0 mV. During activating voltage steps from a holding potential of −90 mV, the fluorescence lagged considerably behind the movement of gating charge over a range of potentials. Another putative quenching group was seen by probes attached closer to the S4 and caused a ΔF at extreme hyperpolarizations (more negative than −90 mV) only. A signal from the interaction with this group in the wt S3–S4 linker channel (at L361C) correlated with gating charge moving in the hyperpolarized part of the Q-V curve. Probe attached at A359C in the deletion mutant and at L361C in wt channel showed a biphasic ΔF as the probe oscillated between the two groups, revealing that there is a transient state of the voltage sensor in between, where the probe has maximal fluorescence. We conclude that the voltage sensor undergoes two distinct conformational changes as seen from probes attached outside the S4 segment