Local signaling domains and numerous interacting molecular pathways and substrates contribute to the whole-cell response of myocytes during β-adrenergic stimulation (βARS). We aimed to elucidate the quantitative contribution of substrates and their local signaling environments during βARS to the canine epicardial ventricular myocyte electrophysiology and calcium transient (CaT). We present a computational compartmental model of βARS and its electrophysiological effects. Novel aspects of the model include localized signaling domains, incorporation of β1 and β2 receptor isoforms, a detailed population-based approach to integrate the βAR and Ca 2+ / Calmodulin kinase (CaMKII) signaling pathways and their effects on a wide range of substrates that affect whole-cell electrophysiology and CaT. The model identifies major roles for phosphodiesterases, adenylyl cyclases, PKA and restricted diffusion in the control of local cAMP levels and shows that activation of specific cAMP domains by different receptor isoforms allows for specific control of action potential and CaT properties. In addition, the model predicts increased CaMKII activity during βARS due to rate-dependent accumulation and increased Ca 2+ cycling. CaMKII inhibition, reduced compartmentation, and selective blockade of β1AR are predicted to reduce the occurrence of delayed afterdepolarizations during βARS. Finally, the relative contribution of each PKA substrate to whole-cell electrophysiology is quantified by comparing simulations with and without phosphorylation of each target. In conclusion, this model enhances our understanding of localized βAR signaling and its whole-cell effects in ventricular myocytes by incorporating receptor isoforms, multiple pathways and a detailed representation of multiple-target phosphorylation; it provides a basis for further studies of βARS under pathological conditions.

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Beat-to-beat variability of repolarization duration (BVR) is an intrinsic characteristic of cardiac function and a better marker of proarrhythmia than repolarization prolongation alone. The ionic mechanisms underlying baseline BVR in physiological conditions, its rate dependence, and the factors contributing to increased BVR in pathologies remain incompletely understood. Here, we employed computer modeling to provide novel insights into the subcellular mechanisms of BVR under physiological conditions and during simulated drug-induced repolarization prolongation, mimicking long-QT syndromes type 1, 2, and 3. We developed stochastic implementations of 13 major ionic currents and fluxes in a model of canine ventricular-myocyte electrophysiology. Combined stochastic gating of these components resulted in short- and long-term variability, consistent with experimental data from isolated canine ventricular myocytes. The model indicated that the magnitude of stochastic fluctuations is rate dependent due to the rate dependence of action-potential (AP) duration (APD). This process (the “active” component) and the intrinsic nonlinear relationship between membrane current and APD (“intrinsic component”) contribute to the rate dependence of BVR. We identified a major role in physiological BVR for stochastic gating of the persistent Na+ current (INa) and rapidly activating delayed-rectifier K+ current (IKr). Inhibition of IKr or augmentation of INa significantly increased BVR, whereas subsequent β-adrenergic receptor stimulation reduced it, similar to experimental findings in isolated myocytes. In contrast, β-adrenergic stimulation increased BVR in simulated long-QT syndrome type 1. In addition to stochastic channel gating, AP morphology, APD, and beat-to-beat variations in Ca2+ were found to modulate single-cell BVR. Cell-to-cell coupling decreased BVR and this was more pronounced when a model cell with increased BVR was coupled to a model cell with normal BVR. In conclusion, our results provide new insights into the ionic mechanisms underlying BVR and suggest that BVR reflects multiple potentially proarrhythmic parameters, including increased ion-channel stochasticity, prolonged APD, and abnormal Ca2+ handling.

Electrical activity at the level of the heart muscle can be noninvasively reconstructed from body-surface electrocardiograms (ECGs) and patient-specific torso-heart geometry. This modality, coined electrocardiographic imaging, could fill the gap between the noninvasive (low-resolution) 12-lead ECG and invasive (high-resolution) electrophysiology studies. Much progress has been made to establish electrocardiographic imaging, and clinical studies appear with increasing frequency. However, many assumptions and model choices are involved in its execution, and only limited validation has been performed. In this article, we will discuss the technical details, clinical applications and current limitations of commonly used methods in electrocardiographic imaging. It is important for clinicians to realise the influence of certain assumptions and model choices for correct and careful interpretation of the results. This, in combination with more extensive validation, will allow for exploitation of the full potential of noninvasive electrocardiographic imaging as a powerful clinical tool to expedite diagnosis, guide therapy and improve risk stratification.

BackgroundGain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spectrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1.7.ResultsWe used homology modeling to build an atomic model of NaV1.7 and a network-based theoretical approach, which can predict interatomic interactions and connectivity arrangements, to investigate how pain-related NaV1.7 mutations may alter specific interatomic bonds and cause connectivity rearrangement, compared to benign variants and polymorphisms. For each amino acid substitution, we calculated the topological parameters betweenness centrality (Bct), degree (D), clustering coefficient (CCct), closeness (Cct), and eccentricity (Ect), and calculated their variation (Δvalue = mutant value-WT value). Pathogenic NaV1.7 mutations showed significantly higher variation of |ΔBct| compared to benign variants and polymorphisms. Using the cut-off value ±0.26 calculated by receiver operating curve analysis, we found that ΔBct correctly differentiated pathogenic NaV1.7 mutations from variants not causing biophysical abnormalities (nABN) and homologous SNPs (hSNPs) with 76% sensitivity and 83% specificity.ConclusionsOur in-silico analyses predict that pain-related pathogenic NaV1.7 mutations may affect the network topological properties of the protein and suggest |ΔBct| value as a potential in-silico marker.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0382-0) contains supplementary material, which is available to authorized users.