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Bhagavan, D.

Publications and source records attributed to Bhagavan, D..

2 recordsLinked to original sources

Intrinsic Mechanisms in the Gating of Resurgent Na+ Currents

The resurgent component of the voltage-gated sodium current (INaR) is a depolarizing conductance, revealed on membrane hyperpolarizations following brief depolarizing voltage steps, which has been shown to contribute to regulating the firing properties of numerous neuronal cell types throughout the central and peripheral nervous systems. Although mediated by the same voltage-gated sodium (Nav) channels that underlie the transient and persistent Nav current components, the gating mechanisms that contribute to the generation of INaR remain unclear. Here, we characterized Nav currents in mouse cerebellar Purkinje neurons, and used tailored voltage-clamp protocols to define how the voltage and the duration of the initial membrane depolarization affect the amplitudes and kinetics of INaR. Using the acquired voltage-clamp data, we developed a novel Markov kinetic state model with parallel (fast and slow) inactivation pathways and, we show that this model reproduces the properties of the resurgent, as well as the transient and persistent, Nav currents recorded in (mouse) cerebellar Purkinje neurons. Based on the acquired experimental data and the simulations, we propose that resurgent Na+ influx occurs as a result of fast inactivating Nav channels transitioning into an open/conducting state on membrane hyperpolarization, and that the decay of INaR reflects the slow accumulation of recovered/opened Nav channels into a second, alternative and more slowly populated, inactivated state. Additional simulations reveal that extrinsic factors that affect the kinetics of fast or slow Nav channel inactivation and/or impact the relative distribution of Nav channels in the fast- and slow-inactivated states, such as the accessory Nav{beta}4 channel subunit, can modulate the amplitude of INaR. SUMMARYThe resurgent component of the voltage-gated sodium current (INaR) is revealed on membrane hyperpolarizations following brief depolarizing voltage steps that activate the rapidly activating and inactivating, transient Nav current (INaT). To probe the mechanisms contributing to the generation and properties of INaR, we combined whole-cell voltage-clamp recordings from mouse cerebellar Purkinje neurons with computational modeling to develop a novel, blocking particle-independent, model for the gating of INaR that involves two parallel inactivation pathways, and we show that this model recapitulates the detailed biophysical properties of INaR measured in mouse cerebellar Purkinje neurons.

neuroscience↗

Identification of Structures for Ion Channel Kinetic Models

Markov models of ion channel dynamics have evolved as experimental advances have improved our understanding of channel function. Past studies have examined various topologies for Markov models of channel dynamics. We present a systematic method for identification of all possible Markov model topologies using experimental data for two types of native voltage-gated ion channel currents: mouse atrial sodium and human left ventricular fast transient outward potassium currents. In addition to optional biophysically inspired restrictions on the number of connections from a state and elimination of long-range connections, this study further suggests successful models have more than minimum number of connections for set number of states. When working with topologies with more than the minimum number of connections, the topologies with three and four connections to the open state tend to serve well as Markov models of ion channel dynamics. Significance StatementHere, we present a computational routine to thoroughly search for Markov model topologies for simulating whole-cell currents given an experimental dataset. We test this method on two distinct types of voltage-gated ion channels that function in the generation of cardiac action potentials. Particularly successful models have more than one connection between an open state and the rest of the model, and large models may benefit from having even more connections between the open state and the rest of the other states.

biophysics↗