CELLULAR OPEN RESOURCE (COR): current status and future directions

Functional Heterogeneity of Cell Populations Increases Robustness of Pacemaker Function in a Numerical Model of the Sinoatrial Node Tissue

Each heartbeat is initiated by specialized pacemaker cells operating within the sinoatrial node (SAN). While individual cells within SAN tissue exhibit substantial heterogeneity of their electrophysiological parameters and Ca cycling, the role of this heterogeneity for cardiac pacemaker function remains mainly unknown. Here we investigated the problem numerically in a 25 × 25 square grid of connected coupled-clock Maltsev-Lakatta cell models. The tissue models were populated by cells with different degree of heterogeneity of the two key model parameters, maximum L-type Ca current conductance (g_CaL) and sarcoplasmic reticulum Ca pumping rate (P_up). Our simulations showed that in the areas of P_up-g_CaL parametric space at the edge of the system stability, where action potential (AP) firing is absent or dysrhythmic in SAN tissue models populated with identical cells, rhythmic AP firing can be rescued by populating the tissues with heterogeneous cells. This robust SAN function is synergistic with respect to heterogeneity in g_CaL and P_up and can be further strengthened by clustering of cells with similar properties. The effect of cell heterogeneity is not due to a simple summation of activity of intrinsically firing cells naturally present in heterogeneous SAN; rather AP firing cells locally and critically interact with non-firing/dormant cells. When firing cells prevail, they recruit many dormant cells to fire, strongly enhancing overall SAN function; and vice versa, prevailing dormant cells suppress AP firing in cells with intrinsic automaticity and halt SAN function. The transitions between firing and non-firing states of the system are sharp, resembling phase transitions in statistical physics. Furthermore, robust function of heterogeneous SAN tissue requires weak cell coupling, a known property of the central area of SAN where cardiac impulse emerges; stronger cell coupling reduces AP firing rate and ultimately halts SAN automaticity at the edge of stability.

Ca2+ and Membrane Potential Transitions During Action Potentials Are Self-Similar to Each Other and to Variability of AP Firing Intervals Across the Broad Physiologic Range of AP Intervals During Autonomic Receptor Stimulation

Ca2+ and V m transitions occurring throughout action potential (AP) cycles in sinoatrial nodal (SAN) cells are cues that (1) not only regulate activation states of molecules operating within criticality (Ca2+ domain) and limit-cycle (V m domain) mechanisms of a coupled-clock system that underlies SAN cell automaticity, (2) but are also regulated by the activation states of the clock molecules they regulate. In other terms, these cues are both causes and effects of clock molecular activation (recursion). Recently, we demonstrated that Ca2+ and V m transitions during AP cycles in single SAN cells isolated from mice, guinea pigs, rabbits, and humans are self-similar (obey a power law) and are also self-similar to trans-species AP firing intervals (APFIs) of these cells in vitro, to heart rate in vivo, and to body mass. Neurotransmitter stimulation of β-adrenergic receptor or cholinergic receptor-initiated signaling in SAN cells modulates their AP firing rate and rhythm by impacting on the degree to which SAN clocks couple to each other, creating the broad physiologic range of SAN cell mean APFIs and firing interval variabilities. Here we show that Ca2+ and V m domain kinetic transitions (time to AP ignition in diastole and 90% AP recovery) occurring within given AP, the mean APFIs, and APFI variabilities within the time series of APs in 230 individual SAN cells are self-similar (obey power laws). In other terms, these long-range correlations inform on self-similar distributions of order among SAN cells across the entire broad physiologic range of SAN APFIs, regardless of whether autonomic receptors of these cells are stimulated or not and regardless of the type (adrenergic or cholinergic) of autonomic receptor stimulation. These long-range correlations among distributions of Ca2+ and V m kinetic functions that regulate SAN cell clock coupling during each AP cycle in different individual, isolated SAN cells not in contact with each other. Our numerical model simulations further extended our perspectives to the molecular scale and demonstrated that many ion currents also behave self-similar across autonomic states. Thus, to ensure rapid flexibility of AP firing rates in response to different types and degrees of autonomic input, nature "did not reinvent molecular wheels within the coupled-clock system of pacemaker cells," but differentially engaged or scaled the kinetics of gears that regulate the rate and rhythm at which the "wheels spin" in a given autonomic input context.

Positive Feedback Mechanisms among Local Ca Releases, NCX, and ICaL Ignite Pacemaker Action Potentials

Recent data suggest that cardiac pacemaker cell function is determined by numerous time-, voltage-, and Ca-dependent interactions of cell membrane electrogenic proteins (M-clock) and intracellular Ca cycling proteins (Ca-clock), forming a coupled-clock system. Many aspects of the coupled-clock system, however, remain underexplored. The key players of the system are Ca release channels (ryanodine receptors), generating local Ca releases (LCRs) from sarcoplasmic reticulum, electrogenic Na/Ca exchanger (NCX) current, and L-type Ca current (I_CaL). We combined numerical model simulations with experimental simultaneous recordings of action potentials (APs) and Ca to gain further insight into the complex interactions within the system. Our simulations revealed a positive feedback mechanism, dubbed AP ignition, which accelerates the diastolic depolarization (DD) to reach AP threshold. The ignition phase begins when LCRs begin to occur and the magnitude of inward NCX current begins to increase. The NCX current, together with funny current and T-type Ca current accelerates DD, bringing the membrane potential to I_CaL activation threshold. During the ignition phase, I_CaL-mediated Ca influx generates more LCRs via Ca-induced Ca release that further activates inward NCX current, creating a positive feedback. Simultaneous recordings of membrane potential and confocal Ca images support the model prediction of the positive feedback among LCRs and I_CaL, as diastolic LCRs begin to occur below and continue within the voltage range of I_CaL activation. The ignition phase onset (identified within the fine DD structure) begins when DD starts to notably accelerate (∼0.15 V/s) above the recording noise. Moreover, the timing of the ignition onset closely predicted the duration of each AP cycle in the basal state, in the presence of autonomic receptor stimulation, and in response to specific inhibition of either the M-clock or Ca-clock, thus indicating general importance of the new coupling mechanism for regulation of the pacemaker cell cycle duration, and ultimately the heart rate.

Transmural cellular heterogeneity in myocardial electromechanics

Myocardial heterogeneity is an attribute of the normal heart. We have developed integrative models of cardiomyocytes from the subendocardial (ENDO) and subepicardial (EPI) ventricular regions that take into account experimental data on specific regional features of intracellular electromechanical coupling in the guinea pig heart. The models adequately simulate experimental data on the differences in the action potential and contraction between the ENDO and EPI cells. The modeling results predict that heterogeneity in the parameters of calcium handling and myofilament mechanics in isolated ENDO and EPI cardiomyocytes are essential to produce the differences in Ca2+ transients and contraction profiles via cooperative mechanisms of mechano-calcium-electric feedback and may further slightly modulate transmural differences in the electrical properties between the cells. Simulation results predict that ENDO cells have greater sensitivity to changes in the mechanical load than EPI cells. These data are important for understanding the behavior of cardiomyocytes in the intact heart.

Patch-Clamp Recording from Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes: Improving Action Potential Characteristics through Dynamic Clamp

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) hold great promise for studying inherited cardiac arrhythmias and developing drug therapies to treat such arrhythmias. Unfortunately, until now, action potential (AP) measurements in hiPSC-CMs have been hampered by the virtual absence of the inward rectifier potassium current (I_K1) in hiPSC-CMs, resulting in spontaneous activity and altered function of various depolarising and repolarising membrane currents. We assessed whether AP measurements in "ventricular-like" and "atrial-like" hiPSC-CMs could be improved through a simple, highly reproducible dynamic clamp approach to provide these cells with a substantial I_K1 (computed in real time according to the actual membrane potential and injected through the patch-clamp pipette). APs were measured at 1 Hz using perforated patch-clamp methodology, both in control cells and in cells treated with all-trans retinoic acid (RA) during the differentiation process to increase the number of cells with atrial-like APs. RA-treated hiPSC-CMs displayed shorter APs than control hiPSC-CMs and this phenotype became more prominent upon addition of synthetic I_K1 through dynamic clamp. Furthermore, the variability of several AP parameters decreased upon I_K1 injection. Computer simulations with models of ventricular-like and atrial-like hiPSC-CMs demonstrated the importance of selecting an appropriate synthetic I_K1. In conclusion, the dynamic clamp-based approach of I_K1 injection has broad applicability for detailed AP measurements in hiPSC-CMs.

Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia

Computational modelling, combined with experimental investigations, is a powerful method for investigating complex cardiac electrophysiological behaviour. The use of rabbit-specific models, due to the similarities of cardiac electrophysiology in this species with human, is especially prevalent. In this paper, we first briefly review rabbit-specific computational modelling of ventricular cell electrophysiology, multi-cellular simulations including cellular heterogeneity, and acute ischemia. This mini-review is followed by an original computational investigation of variability in the electrophysiological response of two experimentally-calibrated populations of rabbit-specific ventricular myocyte action potential models to acute ischemia. We performed a systematic exploration of the response of the model populations to varying degrees of ischemia and individual ischemic parameters, to investigate their individual and combined effects on action potential duration and refractoriness. This revealed complex interactions between model population variability and ischemic factors, which combined to enhance variability during ischemia. This represents an important step towards an improved understanding of the role that physiological variability may play in electrophysiological alterations during acute ischemia.

R4496C RyR2 mutation impairs atrial and ventricular contractility

A ryanodine receptor 2 mutation associated with catecholaminergic polymorphic ventricular tachycardia renders cardiomyocytes incapable of mediating a positive inotropic response.

Ryanodine receptor (RyR2) is the major Ca²⁺ channel of the cardiac sarcoplasmic reticulum (SR) and plays a crucial role in the generation of myocardial force. Changes in RyR2 gating properties and resulting increases in its open probability (P_o) are associated with Ca²⁺ leakage from the SR and arrhythmias; however, the effects of RyR2 dysfunction on myocardial contractility are unknown. Here, we investigated the possibility that a RyR2 mutation associated with catecholaminergic polymorphic ventricular tachycardia, R4496C, affects the contractile function of atrial and ventricular myocardium. We measured isometric twitch tension in left ventricular and atrial trabeculae from wild-type mice and heterozygous transgenic mice carrying the R4496C RyR2 mutation and found that twitch force was comparable under baseline conditions (30°C, 2 mM [Ca²⁺]_o, 1 Hz). However, the positive inotropic responses to high stimulation frequency, 0.1 µM isoproterenol, and 5 mM [Ca²⁺]_o were decreased in R4496C trabeculae, as was post-rest potentiation. We investigated the mechanisms underlying inotropic insufficiency in R4496C muscles in single ventricular myocytes. Under baseline conditions, the amplitude of the Ca²⁺ transient was normal, despite the reduced SR Ca²⁺ content. Under inotropic challenge, however, R4496C myocytes were unable to boost the amplitude of Ca²⁺ transients because they are incapable of properly increasing the amount of Ca²⁺ stored in the SR because of a larger SR Ca²⁺ leakage. Recovery of force in response to premature stimuli was faster in R4496C myocardium, despite the unchanged rates of recovery of L-type Ca²⁺ channel current (I_Ca-L) and SR Ca²⁺ content in single myocytes. A faster recovery from inactivation of the mutant R4496C channels could explain this behavior. In conclusion, changes in RyR2 channel gating associated with the R4496C mutation could be directly responsible for the alterations in both ventricular and atrial contractility. The increased RyR2 P_o and fractional Ca²⁺ release from the SR induced by the R4496C mutation preserves baseline contractility despite a slight decrease in SR Ca²⁺ content, but cannot compensate for the inability to increase SR Ca²⁺ content during inotropic challenge.

OpenCOR: a modular and interoperable approach to computational biology

Computational biologists have been developing standards and formats for nearly two decades, with the aim of easing the description and exchange of experimental data, mathematical models, simulation experiments, etc. One of those efforts is CellML (cellml.org), an XML-based markup language for the encoding of mathematical models. Early CellML-based environments include COR and OpenCell. However, both of those tools have limitations and were eventually replaced with OpenCOR (opencor.ws). OpenCOR is an open source modeling environment that is supported on Windows, Linux and OS X. It relies on a modular approach, which means that all of its features come in the form of plugins. Those plugins can be used to organize, edit, simulate and analyze models encoded in the CellML format. We start with an introduction to CellML and two of its early adopters, which limitations eventually led to the development of OpenCOR. We then go onto describing the general philosophy behind OpenCOR, as well as describing its openness and its development process. Next, we illustrate various aspects of OpenCOR, such as its user interface and some of the plugins that come bundled with it (e.g., its editing and simulation plugins). Finally, we discuss some of the advantages and limitations of OpenCOR before drawing some concluding remarks.

Images as drivers of progress in cardiac computational modelling

Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.

The cardiac muscle duplex as a method to study myocardial heterogeneity

This paper reviews the development and application of paired muscle preparations, called duplex, for the investigation of mechanisms and consequences of intra-myocardial electro-mechanical heterogeneity. We illustrate the utility of the underlying combined experimental and computational approach for conceptual development and integration of basic science insight with clinically relevant settings, using previously published and new data. Directions for further study are identified.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K⁺, inward rectifying K⁺, L-type Ca²⁺, and Na⁺/K⁺ pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Integrating multi-scale data to create a virtual physiological mouse heart

While the virtual physiological human (VPH) project has made great advances in human modelling, many of the tools and insights developed as part of this initiative are also applicable for facilitating mechanistic understanding of the physiology of a range of other species. This process, in turn, has the potential to provide human relevant insights via a different scientific path. Specifically, the increasing use of mice in experimental research, not yet fully complemented by a similar increase in computational modelling, is currently missing an important opportunity for using and interpreting this growing body of experimental data to improve our understanding of cardiac function. This overview describes our work to address this issue by creating a virtual physiological mouse model of the heart. We describe the similarities between human- and mouse-focused modelling, including the reuse of VPH tools, and the development of methods for investigating parameter sensitivity that are applicable across species. We show how previous results using this approach have already provided important biological insights, and how these can also be used to advance VPH heart models. Finally, we show an example application of this approach to test competing multi-scale hypotheses by investigating variations in length-dependent properties of cardiac muscle.

Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies

Since the development of the first mathematical cardiac cell model 50 years ago, computational modelling has become an increasingly powerful tool for the analysis of data and for the integration of information related to complex cardiac behaviour. Current models build on decades of iteration between experiment and theory, representing a collective understanding of cardiac function. All models, whether computational, experimental, or conceptual, are simplified representations of reality and, like tools in a toolbox, suitable for specific applications. Their range of applicability can be explored (and expanded) by iterative combination of 'wet' and 'dry' investigation, where experimental or clinical data are used to first build and then validate computational models (allowing integration of previous findings, quantitative assessment of conceptual models, and projection across relevant spatial and temporal scales), while computational simulations are utilized for plausibility assessment, hypotheses-generation, and prediction (thereby defining further experimental research targets). When implemented effectively, this combined wet/dry research approach can support the development of a more complete and cohesive understanding of integrated biological function. This review illustrates the utility of such an approach, based on recent examples of multi-scale studies of cardiac structure and mechano-electric function.

Application of cardiac electrophysiology simulations to pro-arrhythmic safety testing

Concerns over cardiac side effects are the largest single cause of compound attrition during pharmaceutical drug development. For a number of years, biophysically detailed mathematical models of cardiac electrical activity have been used to explore how a compound, interfering with specific ion-channel function, may explain effects at the cell-, tissue- and organ-scales. With the advent of high-throughput screening of multiple ion channels in the wet-lab, and improvements in computational modelling of their effects on cardiac cell activity, more reliable prediction of pro-arrhythmic risk is becoming possible at the earliest stages of drug development. In this paper, we review the current use of biophysically detailed mathematical models of cardiac myocyte electrical activity in drug safety testing, and suggest future directions to employ the full potential of this approach.

An updated computational model of rabbit sinoatrial action potential to investigate the mechanisms of heart rate modulation

The cellular basis of cardiac pacemaking is still debated. Reliable computational models of the sinoatrial node (SAN) action potential (AP) may help gain a deeper understanding of the phenomenon. Recently, novel models incorporating detailed Ca(2+)-handling dynamics have been proposed, but they fail to reproduce a number of experimental data, and more specifically effects of 'funny' (I(f)) current modifications. We therefore developed a SAN AP model, based on available experimental data, in an attempt to reproduce physiological and pharmacological heart rate modulation. Cell compartmentalization and intracellular Ca(2+)-handling mechanisms were formulated as in the Maltsev-Lakatta model, focusing on Ca(2+)-cycling processes. Membrane current equations were revised on the basis of published experimental data. Modifications of the formulation of currents/pumps/exchangers to simulate I(f) blockers, autonomic modulators and Ca(2+)-dependent mechanisms (ivabradine, caesium, acetylcholine, isoprenaline, BAPTA) were derived from experimental data. The model generates AP waveforms typical of rabbit SAN cells, whose parameters fall within the experimental ranges: 352 ms cycle length, 80 mV AP amplitude, -58 mV maximum diastolic potential (MDP), 108 ms APD(50), and 7.1 Vs(-1) maximum upstroke velocity. Rate modulation by I(f) -blocking drugs agrees with experimental findings: 20% and 22% caesium-induced (5mM) and ivabradine-induced (3 μM) rate reductions, respectively, due to changes in diastolic depolarization (DD) slope, with no changes in either MDP or take-off potential (TOP). The model consistently reproduces the effects of autonomic modulation: 20% rate decrease with 10 nM acetylcholine and 28%increase with 1 μM isoprenaline, again entirely due to increase in the DD slope,with no changes in either MDP or TOP. Model testing of BAPTA effects showed slowing of rate, -26%, without cessation of beating. Our up-to-date model describes satisfactorily experimental data concerning autonomic stimulation, funny-channel blockade and inhibition of the Ca(2+)-related system by BAPTA, making it a useful tool for further investigation. Simulation results suggest that a detailed description of the intracellular Ca(2+) fluxes is fully compatible with the observation that I(f) is a major component of pacemaking and rate modulation.

How the Hodgkin-Huxley equations inspired the Cardiac Physiome Project

Early modelling of cardiac cells (1960-1980) was based on extensions of the Hodgkin-Huxley nerve axon equations with additional channels incorporated, but after 1980 it became clear that processes other than ion channel gating were also critical in generating electrical activity. This article reviews the development of models representing almost all cell types in the heart, many different species, and the software tools that have been created to facilitate the cardiac Physiome Project.

Graphical approach to model reduction for nonlinear biochemical networks

Model reduction is a central challenge to the development and analysis of multiscale physiology models. Advances in model reduction are needed not only for computational feasibility but also for obtaining conceptual insights from complex systems. Here, we introduce an intuitive graphical approach to model reduction based on phase plane analysis. Timescale separation is identified by the degree of hysteresis observed in phase-loops, which guides a “concentration-clamp” procedure for estimating explicit algebraic relationships between species equilibrating on fast timescales. The primary advantages of this approach over Jacobian-based timescale decomposition are that: 1) it incorporates nonlinear system dynamics, and 2) it can be easily visualized, even directly from experimental data. We tested this graphical model reduction approach using a 25-variable model of cardiac β₁-adrenergic signaling, obtaining 6- and 4-variable reduced models that retain good predictive capabilities even in response to new perturbations. These 6 signaling species appear to be optimal “kinetic biomarkers” of the overall β₁-adrenergic pathway. The 6-variable reduced model is well suited for integration into multiscale models of heart function, and more generally, this graphical model reduction approach is readily applicable to a variety of other complex biological systems.

Partial restoration of the long QT syndrome associated KCNQ1 A341V mutant by the KCNE1 β-subunit

BACKGROUND

The A341V mutation in the pore-forming KCNQ1 subunit of the slowly activating delayed-rectifier potassium current (IKs) underlies a common form of the long QT syndrome, and is associated with an unusually severe phenotype. However, there is controversy regarding the underlying mechanism responsible for the clinically observed phenotype. We investigated the biophysical characteristics of A341V in a cardiac environment by utilizing a cardiac cell line, and in particular the impact of the KCNE1 β-subunit.

METHODS

Whole-cell current were recorded from transiently transfected HL-1 cells, a cardiac cell line. Mutant KCNQ1 and KCNE1 were constructed by site-directed mutagenesis.

RESULTS

The A341V mutant resulted in a non-functional channel when expressed alone. When co-expressed with wild type KCNE1, A341V produced a slowly activating current, with a smaller current density, slower rates of activation, and a depolarized shift in its activation curve compared to the wild type KCNQ1+KCNE1. Confocal microscopy confirmed the surface expression of GFP-tagged A341V, suggesting a functionally defective protein. A T58A mutation in KCNE1 abolished functional restoration of A341V. Under heterozygous conditions, the expression of A341V+KCNQ1+KCNE1 reduced but did not abolish the electrophysiological changes observed in A341V+KCNE1. A dominant negative effect of A341V was also observed. Action potential simulations revealed that the A341V mutation is arrhythmogenic.

CONCLUSIONS

The KCNE1 β-subunit partially rescued the non-functional A341V mutant, with electrophysiological properties distinct from the wild type IKs.

GENERAL SIGNIFICANCE

The severity of the A341V phenotype may be due to a combination of a significant suppression of the IKs with altered biophysical characteristics.

Protein dynamics: Moore's law in molecular biology

The millisecond barrier has been broken in molecular dynamics simulations of proteins. Such simulations are increasingly revealing the inner workings of biological systems by generating atomic-level descriptions of their behaviour that make testable predictions about key molecular processes.

Successes and failures in modeling heart cell electrophysiology

Mathematical models of the electrical activity of the heart using equations for protein ion channels and other transporters began with the Noble 1962 model. These models then developed over a period of about 50 years. Cell types in all regions have been modeled and now are available for download from the CellML website (www.cellml.org). Simulation is a necessary tool of analysis in attempting to understand biological complexity. We often learn as much from the failures as from the successes of mathematical models. It is the iterative interaction between experiment and simulation that is important.

Ca²⁺-induced delayed afterdepolarizations are triggered by dyadic subspace Ca2²⁺ affirming that increasing SERCA reduces aftercontractions

Ca(2+)-induced delayed afterdepolarizations (DADs) are depolarizations that occur after full repolarization. They have been observed across multiple species and cell types. Experimental results have indicated that the main cause of DADs is Ca(2+) overload. The main hypothesis as to their initiation has been Ca(2+) overflow from the overloaded sarcoplasmic reticulum (SR). Our results using 37 previously published mathematical models provide evidence that Ca(2+)-induced DADs are initiated by the same mechanism as Ca(2+)-induced Ca(2+) release, i.e., the modulation of the opening of ryanodine receptors (RyR) by Ca(2+) in the dyadic subspace; an SR overflow mechanism was not necessary for the induction of DADs in any of the models. The SR Ca(2+) level is better viewed as a modulator of the appearance of DADs and the magnitude of Ca(2+) release. The threshold for the total Ca(2+) level within the cell (not only the SR) at which Ca(2+) oscillations arise in the models is close to their baseline level (∼1- to 3-fold). It is most sensitive to changes in the maximum sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA) pump rate (directly proportional), the opening probability of RyRs, and the Ca(2+) diffusion rate from the dyadic subspace into the cytosol (both indirectly proportional), indicating that the appearance of DADs is multifactorial. This shift in emphasis away from SR overload as the trigger for DADs toward a multifactorial analysis could explain why SERCA overexpression has been shown to suppress DADs (while increasing contractility) and why DADs appear during heart failure (at low SR Ca(2+) levels).

Carvedilol inhibits Kir2.3 channels by interference with PIP₂-channel interaction

Carvedilol, a β- and α-adrenoceptor blocker, is used to treat congestive heart failure, mild to moderate hypertension, and myocardial infarction. It has been proposed to block K(ATP) channels by binding to the bundle crossing region at a domain including cysteine at position 166, and thereby plugging the pore region. However, carvedilol was reported not to affect Kir2.1 channels, which lack 166 Cys. Here, we demonstrate that carvedilol inhibits Kir2.3 carried current by an alternative mechanism. Carvedilol inhibited Kir2.3 channels with at least 100 fold higher potency (IC(50)=0.49 μM) compared to that for Kir2.1 (IC(50)>50 μM). Kir2.3 channel inhibition was concentration-dependent and voltage-independent. Increasing Kir2.3 channel affinity for PIP(2), by a I213L point mutation, decreased the inhibitory effect of carvedilol more than twentyfold (IC(50)=11.1 μM). In the presence of exogenous PIP(2), Kir2.3 channel inhibition by carvedilol was strongly reduced (80 vs. 2% current inhibition). These results suggest that carvedilol, as other cationic amphiphilic drugs, inhibits Kir2.3 channels by interfering with the PIP(2)-channel interaction.

The mammalian K(IR)2.x inward rectifier ion channel family: expression pattern and pathophysiology

Inward rectifier currents based on K(IR)2.x subunits are regarded as essential components for establishing a stable and negative resting membrane potential in many excitable cell types. Pharmacological inhibition, null mutation in mice and dominant positive and negative mutations in patients reveal some of the important functions of these channels in their native tissues. Here we review the complex mammalian expression pattern of K(IR)2.x subunits and relate these to the outcomes of functional inhibition of the resultant channels. Correlations between expression and function in muscle and bone tissue are observed, while we recognize a discrepancy between neuronal expression and function.

Differential expression of hERG1 channel isoforms reproduces properties of native I(Kr) and modulates cardiac action potential characteristics

BACKGROUND

The repolarizing cardiac rapid delayed rectifier current, I(Kr), is composed of ERG1 channels. It has been suggested that two isoforms of the ERG1 protein, ERG1a and ERG1b, both contribute to I(Kr). Marked heterogeneity in the kinetic properties of native I(Kr) has been described. We hypothesized that the heterogeneity of native I(Kr) can be reproduced by differential expression of ERG1a and ERG1b isoforms. Furthermore, the functional consequences of differential expression of ERG1 isoforms were explored as a potential mechanism underlying native heterogeneity of action potential duration (APD) and restitution.

METHODOLOGY/PRINCIPAL FINDINGS

The results show that the heterogeneity of native I(Kr) can be reproduced in heterologous expression systems by differential expression of ERG1a and ERG1b isoforms. Characterization of the macroscopic kinetics of ERG1 currents demonstrated that these were dependent on the relative abundance of ERG1a and ERG1b. Furthermore, we used a computational model of the ventricular cardiomyocyte to show that both APD and the slope of the restitution curve may be modulated by varying the relative abundance of ERG1a and ERG1b. As the relative abundance of ERG1b was increased, APD was gradually shortened and the slope of the restitution curve was decreased.

CONCLUSIONS/SIGNIFICANCE

Our results show that differential expression of ERG1 isoforms may explain regional heterogeneity of I(Kr) kinetics. The data demonstrate that subunit dependent changes in channel kinetics are important for the functional properties of ERG1 currents and hence I(Kr). Importantly, our results suggest that regional differences in the relative abundance of ERG1 isoforms may represent a potential mechanism underlying the heterogeneity of both APD and APD restitution observed in mammalian hearts.

The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms

The field of synthetic biology holds an inspiring vision for the future; it integrates computational analysis, biological data and the systems engineering paradigm in the design of new biological machines and systems. These biological machines are built from basic biomolecular components analogous to electrical devices, and the information flow among these components requires the augmentation of biological insight with the power of a formal approach to information management. Here we review the informatics challenges in synthetic biology along three dimensions: in silico, in vitro and in vivo. First, we describe state of the art of the in silico support of synthetic biology, from the specific data exchange formats, to the most popular software platforms and algorithms. Next, we cast in vitro synthetic biology in terms of information flow, and discuss genetic fidelity in DNA manipulation, development strategies of biological parts and the regulation of biomolecular networks. Finally, we explore how the engineering chassis can manipulate biological circuitries in vivo to give rise to future artificial organisms.

What can metabolomics learn from genomics and proteomics?

After nearly a decade, metabolomics has begun to acquire some credence in the scientific community although its acceptance cannot be compared with that of its forerunners, genomics and proteomics. The legitimization of metabolomics as a valid scientific entity depends on the size of the research community it influences. By far the most effective medium for inoculation is the web infrastructure: public servers that accommodate experimental data, simple formats and guidelines for their interpretation, and connectivity between data and tools for analysis. When these elements satisfy the condition to initiate a social epidemic, metabolomics will be accepted as a fundamental data-driven science that can unite hitherto independently conducted research disciplines.

A method for visualizing CellML models

MOTIVATION

The Physiome Project was established in 1997 to develop tools to facilitate international collaboration in the physiological sciences and the sharing of biological models and experimental data. The CellML language was developed to represent and exchange mathematical models of biological processes. CellML models can be very complicated, making it difficult to interpret the underlying physical and biological concepts and relationships captured/described in the mathematical model.

RESULTS

To address this issue a set of ontologies was developed to explicitly annotate the biophysical concepts represented in the CellML models. This article presents a framework that combines a visual language, together with CellML ontologies, to support the visualization of the underlying physical and biological concepts described by the mathematical model and also their relationships with the CellML model. Automated CellML model visualization assists in the interpretation of model concepts and facilitates model communication and exchange between different communities.

CellML metadata standards, associated tools and repositories

The development of standards for encoding mathematical models is an important component of model building and model sharing among scientists interested in understanding multi-scale physiological processes. CellML provides such a standard, particularly for models based on biophysical mechanisms, and a substantial number of models are now available in the CellML Model Repository. However, there is an urgent need to extend the current CellML metadata standard to provide biological and biophysical annotation of the models in order to facilitate model sharing, automated model reduction and connection to biological databases. This paper gives a broad overview of a number of new developments on CellML metadata and provides links to further methodological details available from the CellML website.