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 limited sets of 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 currents and human left ventricular fast transient outward potassium currents. Successful models identified with this approach have certain characteristics in common, suggesting that aspects of the model topology are determined by the experimental data. Incorporating these channel models into cell and tissue simulations to assess model performance within protocols that were not used for training provided validation and further narrowing of the number of acceptable models. The success of this approach suggests a channel model creation pipeline may be feasible where the structure of the model is not specified a priori.

Alternative diastolic function models of ventricular longitudinal filling velocity are mathematically identical.

The spatiotemporal features of normal in vivo cardiac motion are well established. Longitudinal velocity has become a focus of diastolic function (DF) characterization, particularly the tissue Doppler e'-wave, manifesting in early diastole when the left ventricle (LV) is a mechanical suction pump (dP/dV < 0). To characterize DF and elucidate mechanistic features, several models have been proposed and have been previously compared algebraically, numerically, and in their ability to fit physiological velocity data. We analyze two previously noncompared models of early rapid-filling lengthening velocity (Doppler e'-wave): parametrized diastolic filling (PDF) and force balance model (FBM). Our initial numerical experiments sampled FBM-generated e'(t) contours as input to determine PDF model predicted fit. The resulting exact numerical agreement [standard error of regression (SER) = 9.06 × 10-16] was not anticipated. Therefore, we analyzed all published FBM-generated e'(t) contours and observed identical agreement. We re-expressed FBM's algebraic expressions for e'(t) and observed for the first time that model-based predictions for lengthening velocity by the FBM and the PDF model are mathematically identical: e'(t) = γe-αtsinh(ßt), thereby providing exact algebraic relations between the three PDF parameters and the six FBM parameters. Previous pioneering experiments have independently established the unique determinants of e'(t) to be LV relaxation, restoring forces (stiffness), and load. In light of the exact intermodel agreement, we conclude that the three PDF parameters, relaxation, stiffness (restoring forces), and load, are unique determinants of DF and e'(t). Thus, we show that only the PDF formalism can compute the three unique, independent, physiological determinants of long-axis LV myocardial velocity from e'(t).NEW & NOTEWORTHY We show that two separate, independently derived physiological (kinematic) models predict mathematically identical expressions for LV-lengthening velocity (Doppler e'-wave), indicating that damped harmonic oscillatory motion is a physiologically accurate model of diastolic function. Although both models predict the same "overdamped" velocity contour, only one model solves the "inverse problem" and generates unique, lumped parameters of relaxation, stiffness (restoring force), and load from the e'-wave.

Substrate mechanics unveil early structural and functional pathology in iPSC micro-tissue models of hypertrophic cardiomyopathy.

Hypertension is a major cause of morbidity and mortality in patients with hypertrophic cardiomyopathy (HCM), suggesting a potential role for mechanics in HCM pathogenesis. Here, we developed an in vitro physiological model to investigate how mechanics acts together with HCM-linked myosin binding protein C (MYBPC3) mutations to trigger disease. Micro-heart muscles (µHM) were engineered from induced pluripotent stem cell (iPSC)-derived cardiomyocytes bearing MYBPC3+/- mutations and challenged to contract against substrates of different elasticity. µHMs that worked against substrates with stiffness at or exceeding the stiffness of healthy adult heart muscle exhibited several hallmarks of HCM, including cellular hypertrophy, impaired contractile energetics, and maladaptive calcium handling. Remarkably, we discovered changes in troponin C and T localization in MYBPC3+/- µHM that were entirely absent in 2D culture. Pharmacologic studies suggested that excessive Ca2+ intake through membrane-embedded channels underlie the observed electrophysiological abnormalities. These results illustrate the power of physiologically relevant engineered tissue models to study inherited disease with iPSC technology.

Mechanical Resistance to Micro-Heart Tissue Contractility unveils early Structural and Functional Pathology in iPSC Models of Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy is the most common cause of sudden death in the young. Because the disease exhibits variable penetrance, there are likely nongenetic factors that contribute to the manifestation of the disease phenotype. Clinically, hypertension is a major cause of morbidity and mortality in patients with HCM, suggesting a potential synergistic role for the sarcomeric mutations associated with HCM and mechanical stress on the heart. We developed an in vitro physiological model to investigate how the afterload that the heart muscle works against during contraction acts together with HCM-linked MYBPC3 mutations to trigger a disease phenotype. Micro-heart muscle arrays (µHM) were engineered from iPSC-derived cardiomyocytes bearing MYBPC3 loss-of-function mutations and challenged to contract against mechanical resistance with substrates stiffnesses ranging from the of embryonic hearts (0.4 kPa) up to the stiffness of fibrotic adult hearts (114 kPa). Whereas MYBPC3 +/- iPSC-cardiomyocytes showed little signs of disease pathology in standard 2D culture, µHMs that included components of afterload revealed several hallmarks of HCM, including cellular hypertrophy, impaired contractile energetics, and maladaptive calcium handling. Remarkably, we discovered changes in troponin C and T localization in the MYBPC3 +/- µHM that were entirely absent in 2D culture. Pharmacologic studies suggested that excessive Ca 2+ intake through membrane-embedded channels, rather than sarcoplasmic reticulum Ca 2+ ATPase (SERCA) dysfunction or Ca 2+ buffering at myofilaments underlie the observed electrophysiological abnormalities. These results illustrate the power of physiologically relevant engineered tissue models to study inherited disease mechanisms with iPSC technology.

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 Navß4 channel subunit, can modulate the amplitude of INaR.

Robust, Automated Analysis of Electrophysiology in Induced Pluripotent Stem Cell-Derived Micro-Heart Muscle for Drug Toxicity.

Drugs are often removed from clinical trials or market progression owing to their unforeseen effects on cardiac action potential and calcium handling. Induced pluripotent stem cell-derived cardiomyocytes and tissues fabricated from these cells are promising as screening tools for early identification of these potential cardiac liabilities. In this study, we describe an automated, open-source MATLAB-based analysis software for calculating cardiac action potentials and calcium transients from fluorescent reporters. We first identified the most robust manner in which to automatically identify the initiation point for action potentials and calcium transients in a user-independent manner, and used this approach to quantify the duration and morphology of these signals. We then demonstrate the software by assessing changes to action potentials and calcium transients in our micro-heart muscles after exposure to hydroxychloroquine, an antimalarial drug with known cardiac liability. Consistent with clinical observations, our system predicted mild action potential prolongation. However, we also observed marked calcium transient suppression, highlighting the advantage of testing multiple physiologic readouts in cardiomyocytes rather than relying on heterologous overexpression of single channels such as the human ether-a-go-go-related gene channel. This open-source software can serve as a useful, high-throughput tool for analyzing cardiomyocyte physiology from fluorescence imaging.