The small diffusible second messenger 3',5'-cyclic adenosine monophosphate (cAMP) is found in virtually every cell in our bodies, where it mediates responses to a variety of different G protein coupled receptors (GPCRs). In the heart, cAMP plays a critical role in regulating many different aspects of cardiac myocyte function, including gene transcription, cell metabolism, and excitation-contraction coupling. Yet, not all GPCRs that stimulate cAMP production elicit the same responses. Subcellular compartmentation of cAMP is essential to explain how different receptors can utilize the same diffusible second messenger to elicit unique functional responses. However, the mechanisms contributing to this behaviour and its significance in producing physiological and pathological responses are incompletely understood. Mathematical modelling has played an essential role in gaining insight into these questions. This review discusses what we currently know about cAMP compartmentation in cardiac myocytes and questions that are yet to be answered.

Although numerous receptors stimulate cAMP production in a wide array of cells, many elicit distinct, highly localized responses, implying that the subcellular distribution of cAMP is not uniform. One often used explanation is that phosphodiesterases, which breakdown cAMP, act as functional barriers limiting diffusion. However, several studies refute the notion that this is sufficient, suggesting that phosphodiesterase-independent movement of cAMP must occur at rates slower than free diffusion. But, until now this has never been demonstrated. Using Raster Image Correlation Spectroscopy (RICS), we measured the diffusion coefficient of a fluorescently-labeled cAMP derivative (φ450-cAMP) as well as other fluorescent molecules in order to investigate the role that molecular size, cell morphology, and buffering by protein kinase A (PKA) play in restricting cAMP mobility in different cell types. Our results demonstrate that cytosolic movement of cAMP is indeed much slower than the rate of free diffusion and that interactions with PKA, especially type II PKA associated with mitochondria, play a significant role. These findings have important implications with respect to cAMP signaling in all cells.

Aim: Confining cAMP production to discrete subcellular locations makes it possible for this ubiquitous second messenger to elicit unique functional responses. Yet, factors that determine how and where the production of this diffusible signaling molecule occurs are incompletely understood. The fluid mosaic model originally proposed that signal transduction occurs through random interactions between proteins diffusing freely throughout the plasma membrane. However, it is now known that the movement of membrane proteins is restricted, suggesting that the plasma membrane is segregated into distinct microdomains where different signaling proteins can be concentrated. In this study, we examined what role lipid raft and non-raft membrane domains play in compartmentation of cAMP signaling in adult ventricular myocytes. Methods and Results: The freely diffusible fluorescence resonance energy transfer-based biosensor Epac2-camps was used to measure global cytosolic cAMP responses, while versions of the probe targeted to lipid raft (Epac2-MyrPalm) and non-raft (Epac2-CAAX) domains were used to monitor local cAMP production near the plasma membrane. We found that β-adrenergic receptors, which are expressed in lipid raft and non-raft domains, produce cAMP responses near the plasma membrane that are distinctly different from those produced by E-type prostaglandin receptors, which are expressed exclusively in non-raft domains. We also found that there are differences in basal cAMP levels associated with lipid raft and non-raft domains, and that this can be explained by differences in basal adenylyl cyclase activity associated with each of these membrane environments. In addition, we found evidence that phosphodiesterases 2, 3, and 4 work together in regulating cAMP activity associated with both lipid raft and non-raft domains, while phosphodiesterase 3 plays a more prominent role in the bulk cytoplasmic compartment. Conclusion: These results suggest that different membrane domains contribute to the formation of distinct pools of cAMP under basal conditions as well as following receptor stimulation in adult ventricular myocytes.

Spatially restricting cAMP production to discrete subcellular locations permits selective regulation of specific functional responses. But exactly where and how cAMP signaling is confined is not fully understood. Different receptors and adenylyl cyclase isoforms responsible for cAMP production are not uniformly distributed between lipid raft and non-lipid raft domains of the plasma membrane. We sought to determine the role that these membrane domains play in organizing cAMP responses in HEK293 cells. The freely diffusible FRET-based biosensor Epac2-camps was used to measure global cAMP responses, while versions of the probe targeted to lipid raft (Epac2-MyrPalm) and non-raft (Epac2-CAAX) domains were used to monitor local cAMP production near the plasma membrane. Disruption of lipid rafts by cholesterol depletion selectively altered cAMP responses produced by raft-associated receptors. The results indicate that receptors associated with lipid raft as well as non-lipid raft domains can contribute to global cAMP responses. In addition, basal cAMP activity was found to be significantly higher in non-raft domains. This was supported by the fact that pharmacologic inhibition of adenylyl cyclase activity reduced basal cAMP activity detected by Epac2-CAAX but not Epac2-MyrPalm or Epac2-camps. Responses detected by Epac2-CAAX were also more sensitive to direct stimulation of adenylyl cyclase activity, but less sensitive to inhibition of phosphodiesterase activity. Quantitative modeling was used to demonstrate that differences in adenylyl cyclase and phosphodiesterase activities are necessary but not sufficient to explain compartmentation of cAMP associated with different microdomains of the plasma membrane.

Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain unique receptor-dependent functional responses. How exactly compartmentation is achieved, however, has remained a mystery for more than 40 years. In this study, we developed computational and mathematical models to represent a subcellular sarcomeric space in a cardiac myocyte with varying detail. We then used these models to predict the contributions of various mechanisms that establish subcellular cAMP microdomains. We used the models to test the hypothesis that phosphodiesterases act as functional barriers to diffusion, creating discrete cAMP signaling domains. We also used the models to predict the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Finally, we modeled the anatomical structures in a cardiac myocyte diad, to predict the effects of anatomical diffusion barriers on cAMP compartmentation. When we incorporated experimentally informed model parameters to reconstruct an in silico subcellular sarcomeric space with spatially distinct cAMP production sites linked to caveloar domains, the models predict that under realistic conditions phosphodiesterases alone were insufficient to generate significant cAMP gradients. This prediction persisted even when combined with slow cAMP diffusion. When we additionally considered the effects of anatomic barriers to diffusion that are expected in the cardiac myocyte dyadic space, cAMP compartmentation did occur, but only when diffusion was slow. Our model simulations suggest that additional mechanisms likely contribute to cAMP gradients occurring in submicroscopic domains. The difference between the physiological and pathological effects resulting from the production of cAMP may be a function of appropriate compartmentation of cAMP signaling. Therefore, understanding the contribution of factors that are responsible for coordinating the spatial and temporal distribution of cAMP at the subcellular level could be important for developing new strategies for the prevention or treatment of unfavorable responses associated with different disease states.

Key points

This study represents a first step toward predicting mechanisms of sex-based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening. We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias. Using the recently solved cryo-EM structure for the Eag-family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S). Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore.

Abstract

Female sex is a risk factor for inherited and acquired long-QT associated torsade de pointes (TdP) arrhythmias, and sympathetic discharge is a major factor in triggering TdP in female long-QT syndrome patients. We used a combined experimental and computational approach to predict 'the perfect storm' of hormone concentration, I_Kr block and sympathetic stimulation that induces arrhythmia in females with inherited and acquired long-QT. More specifically, we developed mathematical models of acquired and inherited long-QT syndrome in male and female ventricular human myocytes by combining effects of a hormone and a hERG blocker, dofetilide, or hERG mutations. These 'male' and 'female' model myocytes and tissues then were used to predict how various sex-based differences underlie arrhythmia risk in the setting of acute sympathetic nervous system discharge. The model predicted increased risk for arrhythmia in females when acute sympathetic nervous system discharge was applied in the settings of both inherited and acquired long-QT syndrome. Females were predicted to have protection from arrhythmia induction when progesterone is high. Males were protected by the presence of testosterone. Structural modelling points towards two plausible and distinct mechanisms of oestrogen action enhancing torsadogenic effects: oestradiol interaction with hERG mutations in the pore loop containing G604 or with common TdP-related blockers in the intra-cavity binding site. Our study presents findings that constitute the first evidence linking structure to function mechanisms underlying female dominance of arousal-induced arrhythmias.

Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the β-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.