Ionic currents drive cellular function within all living cells to perform highly specific tasks. For excitable cells, such as muscle and neurons, voltage-gated ion channels have finely tuned kinetics that allow the transduction of Action potentials to other cells. Voltage-gated ion channels are molecular machines that open and close depending on electrical potential. Neuronal firing rates are largely determined by the overall availability of voltage-gated Na+ and K+ currents.This work describes new approaches for collecting and analyzing experimental data that can be used to streamline experiments. Ion channels are composed of multimeric complexes regulated by intracellular factors producing complex kinetics. The stochastic behavior of thousands of individual ion hannels coordinates to produce cellular activity. To describe their activity and test hypotheses about the channel, experimenters often fit Markov models to a set of experimental data. Markov models are defined by a set of states, whose transitions described by rate constants. To improve the modeling process, we have developed computational approaches to introduce kinetic constraints that reduces the parameter search space. This work describes the implementation and mathematical transformations required to describe linear and non-linear parameter constraints that govern rate constants. Not all ion channel behaviors can easily be described by rate constants. Therefore, we developed and implemented a penalty-based mechanism that can be used to guide the optimization engine to produce a model with a desired behavior, such as single-channel open probability and use dependent effects. To streamline data collection for experiments in brain slice preparations, we developed a 3D virtual software environment that incorporates data from micro-positioning motors and scientific cameras in real-time. This environment provides positional feedback to the investigator and allows for the creation of data maps including both images and electrical recordings. We have also produced semi-automatic targeting procedures that simplifies the overall experimental experience. Experimentally, this work also examines how the kinetic mechanism of voltage gated Na channels regulates the neuronal firing of brainstem respiratory neurons. These raphe neurons are intrinsic pacemakers that do not rely on synaptic connections to elicit activity. I explored how intracellular calcium regulates the kinetics of TTX-sensitive Na+ currents using whole-cell patch clamp electrophysiology. Established with intracellular Ca2+ buffers, high [Ca2+] levels greater than ~7 [micro]M did not change the voltage dependence of steady-state activation and inactivation, but slightly slowed inactivation time course. However, the recovery from inactivation and use dependence inactivation is slowed by high intracellular [Ca2+]. Overall, these approaches described in this work have improved data acquisition and data analysis to create better ion channel models and enhance the electrophysiology experience.
Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes