Virtual cardiac monolayers for electrical wave propagation

The local mechanosensitive response of primary cardiac fibroblasts is influenced by the microenvironment mechanics

Cardiac fibroblasts (CFs) are essential for preserving myocardial integrity and function. They can detect variations in cardiac tissue stiffness using various cellular mechanosensors, including the Ca2+ permeable mechanosensitive channel Piezo1. Nevertheless, how CFs adapt the mechanosensitive response to stiffness changes remains unclear. In this work we adopted a multimodal approach, combining the local mechanical stimulation (from 10 pN to 350 nN) with variations of culture substrate stiffness. We found that primary rat CFs cultured on stiff (GPa) substrates showed a broad Piezo1 distribution in the cell with particular accumulation at the mitochondria membrane. CFs displayed a force-dependent behavior in both calcium uptake and channel activation probability, showing a threshold at 300 nN, which involves both cytosolic and mitochondrial Ca2+ mobilization. This trend decreases as the myofibroblast phenotype within the cell population increases, following a possible Piezo1 accumulation at focal adhesion sites. In contrast, the inhibition of fibroblasts to myofibroblasts transition with soft substrates (kPa) considerably reduces both mechanically- and chemically-induced Piezo1 activation and expression. Our findings shed light on how Piezo1 function and expression are regulated by the substrate stiffness and highlight its involvement in the environment-mediated modulation of CFs mechanosensitivity.

Biomimetic Cardiac Tissue Models for In Vitro Arrhythmia Studies

Cardiac arrhythmias are a major cause of cardiovascular mortality worldwide. Many arrhythmias are caused by reentry, a phenomenon where excitation waves circulate in the heart. Optical mapping techniques have revealed the role of reentry in arrhythmia initiation and fibrillation transition, but the underlying biophysical mechanisms are still difficult to investigate in intact hearts. Tissue engineering models of cardiac tissue can mimic the structure and function of native cardiac tissue and enable interactive observation of reentry formation and wave propagation. This review will present various approaches to constructing cardiac tissue models for reentry studies, using the authors' work as examples. The review will highlight the evolution of tissue engineering designs based on different substrates, cell types, and structural parameters. A new approach using polymer materials and cellular reprogramming to create biomimetic cardiac tissues will be introduced. The review will also show how computational modeling of cardiac tissue can complement experimental data and how such models can be applied in the biomimetics of cardiac tissue.

The role of the Cx43/Cx45 gap junction voltage gating on wave propagation and arrhythmogenic activity in cardiac tissue

Gap junctions (GJs) formed of connexin (Cx) protein are the main conduits of electrical signals in the heart. Studies indicate that the transitional zone of the atrioventricular (AV) node contains heterotypic Cx43/Cx45 GJ channels which are highly sensitive to transjunctional voltage (Vj). To investigate the putative role of Vj gating of Cx43/Cx45 channels, we performed electrophysiological recordings in cell cultures and developed a novel mathematical/computational model which, for the first time, combines GJ channel Vj gating with a model of membrane excitability to simulate a spread of electrical pulses in 2D. Our simulation and electrophysiological data show that Vj transients during the spread of cardiac excitation can significantly affect the junctional conductance (gj) of Cx43/Cx45 GJs in a direction- and frequency-dependent manner. Subsequent simulation data indicate that such pulse-rate-dependent regulation of gj may have a physiological role in delaying impulse propagation through the AV node. We have also considered the putative role of the Cx43/Cx45 channel gating during pathological impulse propagation. Our simulation data show that Vj gating-induced changes in gj can cause the drift and subsequent termination of spiral waves of excitation. As a result, the development of fibrillation-like processes was significantly reduced in 2D clusters, which contained Vj-sensitive Cx43/Cx45 channels.

Polymer Kernels as Compact Carriers for Suspended Cardiomyocytes

Induced pluripotent stem cells (iPSCs) constitute a potential source of patient-specific human cardiomyocytes for a cardiac cell replacement therapy via intramyocardial injections, providing a major benefit over other cell sources in terms of immune rejection. However, intramyocardial injection of the cardiomyocytes has substantial challenges related to cell survival and electrophysiological coupling with recipient tissue. Current methods of manipulating cell suspensions do not allow one to control the processes of adhesion of injected cells to the tissue and electrophysiological coupling with surrounding cells. In this article, we documented the possibility of influencing these processes using polymer kernels: biocompatible fiber fragments of subcellular size that can be adsorbed to a cell, thereby creating the minimum necessary adhesion foci to shape the cell and provide support for the organization of the cytoskeleton and the contractile apparatus prior to adhesion to the recipient tissue. Using optical excitation markers, the restoration of the excitability of cardiomyocytes in suspension upon adsorption of polymer kernels was shown. It increased the likelihood of the formation of a stable electrophysiological coupling in vitro. The obtained results may be considered as a proof of concept that the stochastic engraftment process of injected suspension cells can be controlled by smart biomaterials.

Anisotropic conduction in the myocardium due to fibrosis: the effect of texture on wave propagation

Cardiac fibrosis occurs in many forms of heart disease. It is well established that the spatial pattern of fibrosis, its texture, substantially affects the onset of arrhythmia. However, in most modelling studies fibrosis is represented by multiple randomly distributed short obstacles that mimic only one possible texture, diffuse fibrosis. An important characteristic feature of other fibrosis textures, such as interstitial and patchy textures, is that fibrotic inclusions have substantial length, which is suggested to have a pronounced effect on wave propagation. In this paper, we study the effect of the elongation of inexcitable inclusions (obstacles) on wave propagation in a 2D model of cardiac tissue described by the TP06 model for human ventricular cells. We study in detail how the elongation of obstacles affects various characteristics of the waves. We quantify the anisotropy induced by the textures, its dependency on the obstacle length and the effects of the texture on the shape of the propagating wave. Because such anisotropy is a result of zig-zag propagation we show, for the first time, quantification of the effects of geometry and source-sink relationship, on the zig-zag nature of the pathway of electrical conduction. We also study the effect of fibrosis in the case of pre-existing anisotropy and introduce a procedure for scaling of the fibrosis texture. We show that fibrosis can decrease or increase the preexisting anisotropy depending on its scaled texture.

Unravelling the ultrastructural details of αT-catenin-deficient cell-cell contacts between heart muscle cells by the use of FIB-SEM

The intercalated disc is an important structure in cardiomyocytes, as it is essential to maintain correct contraction and proper functioning of the heart. Adhesion and communication between cardiomyocytes are mediated by three main types of intercellular junctions, all residing in the intercalated disc: gap junctions, desmosomes and the areae compositae. Mutations in genes that encode junctional proteins, including αT-catenin (encoded by CTNNA3), have been linked to arrhythmogenic cardiomyopathy and sudden cardiac death. In mice, the loss of αT-catenin in cardiomyocytes leads to impaired heart function, fibrosis, changed expression of desmosomal proteins and increased risk for arrhythmias following ischemia-reperfusion. Currently, it is unclear how the intercalated disc and the intercellular junctions are organised in 3D in the hearts of this αT-catenin knockout (KO) mouse model. In order to scrutinise this, ventricular cardiac tissue of αT-catenin KO mice was used for volume electron microscopy (VEM), making use of Focused Ion Beam Scanning Electron Microscopy (FIB-SEM), allowing a careful 3D reconstruction of the intercalated disc, including gap junctions and desmosomes. Although αT-catenin KO and control mice display a comparable organisation of the sarcomere and the different intercalated disc regions, the folds of the plicae region of the intercalated disc are longer and more narrow in the KO heart, and the pale region between the sarcomere and the intercalated disc is larger. In addition, αT-catenin KO intercalated discs appear to have smaller gap junctions and desmosomes in the plicae region, while gap junctions are larger in the interplicae region of the intercalated disc. Although the reason for this remodelling of the ultrastructure after αT-catenin deletion remains unclear, the excellent resolution of the FIB-SEM technology allows us to reconstruct details that were not reported before. LAY DESCRIPTION: Cardiomyocytes are cells that make up the heart muscle. As the chief cell type of the heart, cardiomyocytes are primarily involved in the contractile function of the heart that enables the pumping of blood around the body. Cardiac muscle cells are connected to each other at their short end by numerous intercellular junctions forming together a structure called the intercalated disc. These intercellular junctions comprise specific protein complexes, which are crucial for both intercellular adhesion and correct contraction of the heart. Imaging by conventional electron microscopy (EM) revealed a heavily folded intercalated disc with apparently random organization of the intercellular junctions. However, this conclusion was based on analysis in two dimensions (2D). 3D information of these structures is needed to unravel their true organization and function. In the present study, we used a more contemporary technique, called volume EM, to image and reconstruct the intercalated discs in 3D. By this approach, EM images are made from a whole block of tissue what differs significantly from classical EM methods that uses only one very thin slice for imaging. Further, we analyzed in comparison to normal mice also a mouse model for cardiomyopathy in which a specific protein of the cardiac intercellular junctions, αT-catenin, is absent. Volume EM revealed that in the hearts of these mice with cardiomyopathy, the finger-like folds of the intercalated disc are longer and thinner compared to control hearts. Also the intercellular junctions on the folded parts of the intercalated disc are smaller and their connection to the striated cytoskeleton seems further away. In conclusion, our volume EM study has expanded our understanding of 3D structures at the intercalated discs and will pave the way for more detailed models of disturbed cell-cell contacts associated with heart failure.

Adapting a Plant Tissue Model to Animal Development: Introducing Cell Sliding into VirtualLeaf

Cell-based, mathematical modeling of collective cell behavior has become a prominent tool in developmental biology. Cell-based models represent individual cells as single particles or as sets of interconnected particles and predict the collective cell behavior that follows from a set of interaction rules. In particular, vertex-based models are a popular tool for studying the mechanics of confluent, epithelial cell layers. They represent the junctions between three (or sometimes more) cells in confluent tissues as point particles, connected using structural elements that represent the cell boundaries. A disadvantage of these models is that cell-cell interfaces are represented as straight lines. This is a suitable simplification for epithelial tissues, where the interfaces are typically under tension, but this simplification may not be appropriate for mesenchymal tissues or tissues that are under compression, such that the cell-cell boundaries can buckle. In this paper, we introduce a variant of VMs in which this and two other limitations of VMs have been resolved. The new model can also be seen as on off-the-lattice generalization of the Cellular Potts Model. It is an extension of the open-source package VirtualLeaf, which was initially developed to simulate plant tissue morphogenesis where cells do not move relative to one another. The present extension of VirtualLeaf introduces a new rule for cell-cell shear or sliding, from which cell rearrangement (T1) and cell extrusion (T2) transitions emerge naturally, allowing the application of VirtualLeaf to problems of animal development. We show that the updated VirtualLeaf yields different results than the traditional vertex-based models for differential adhesion-driven cell sorting and for the neighborhood topology of soft cellular networks.

Self-organization of conducting pathways explains electrical wave propagation in cardiac tissues with high fraction of non-conducting cells

Cardiac fibrosis occurs in many forms of heart disease and is considered to be one of the main arrhythmogenic factors. Regions with a high density of fibroblasts are likely to cause blocks of wave propagation that give rise to dangerous cardiac arrhythmias. Therefore, studies of the wave propagation through these regions are very important, yet the precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Particularly, it is not clear how wave propagation is organized at the cellular level, as experiments show that the regions with a high percentage of fibroblasts (65-75%) are still conducting electrical signals, whereas geometric analysis of randomly distributed conducting and non-conducting cells predicts connectivity loss at 40% at the most (percolation threshold). To address this question, we used a joint in vitro-in silico approach, which combined experiments in neonatal rat cardiac monolayers with morphological and electrophysiological computer simulations. We have shown that the main reason for sustainable wave propagation in highly fibrotic samples is the formation of a branching network of cardiomyocytes. We have successfully reproduced the morphology of conductive pathways in computer modelling, assuming that cardiomyocytes align their cytoskeletons to fuse into cardiac syncytium. The electrophysiological properties of the monolayers, such as conduction velocity, conduction blocks and wave fractionation, were reproduced as well. In a virtual cardiac tissue, we have also examined the wave propagation at the subcellular level, detected wavebreaks formation and its relation to the structure of fibrosis and, thus, analysed the processes leading to the onset of arrhythmias.

Cardiac arrhythmias are one of the major causes of death in the industrialized world. The most dangerous ones are often caused by the blocks of propagation of electrical signals. One of the common factors that contribute to the likelihood of these blocks, is a condition called cardiac fibrosis. In fibrosis, excitable cardiac tissue is partially replaced with the inexcitable and non-conducting connective tissue. The precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Therefore, it is important to study wave propagation in fibrosis from cellular to tissue level. In this paper, we study tissues with high densities of non-conducting cells in experiments and computer simulations. We have observed a paradoxical ability of the tissue with extremely high portion of non-conducting cells (up to 75%) to conduct electrical signals and contract synchronously, whereas geometric analysis of randomly distributed cells predicted connectivity loss at 40% at the most. To explain this phenomenon, we have studied the patterns that cardiac cells form in the tissue and reproduced their self-organisation in a computer model. Our virtual model also took into account the polygonal shapes of the spreading cells and explained high arrhythmogenicity of fibrotic tissue.

Microheterogeneity-induced conduction slowing and wavefront collisions govern macroscopic conduction behavior: A computational and experimental study

The incidence of cardiac arrhythmias is known to be associated with tissue heterogeneities including fibrosis. However, the impact of microscopic structural heterogeneities on conduction in excitable tissues remains poorly understood. In this study, we investigated how acellular microheterogeneities affect macroscopic conduction under conditions of normal and reduced excitability by utilizing a novel platform of paired in vitro and in silico studies to examine the mechanisms of conduction. Regular patterns of nonconductive micro-obstacles were created in confluent monolayers of the previously described engineered-excitable Ex293 cell line. Increasing the relative ratio of obstacle size to intra-obstacle strand width resulted in significant conduction slowing up to 23.6% and a significant increase in wavefront curvature anisotropy, a measure of spatial variation in wavefront shape. Changes in bulk electrical conductivity and in path tortuosity were insufficient to explain these observed macroscopic changes. Rather, microscale behaviors including local conduction slowing due to microscale branching, and conduction acceleration due to wavefront merging were shown to contribute to macroscopic phenomena. Conditions of reduced excitability led to further conduction slowing and a reversal of wavefront curvature anisotropy due to spatially non-uniform effects on microscopic slowing and acceleration. This unique experimental and computation platform provided critical mechanistic insights in the impact of microscopic heterogeneities on macroscopic conduction, pertinent to settings of fibrotic heart disease.

It is well known that perturbations in the heart structure are associated with the initiation and maintenance of clinically significant cardiac arrhythmia. While previous studies have examined how single structural perturbations affect local electrical conduction, our understanding of how numerous microscopic heterogeneities act in aggregate to alter macroscopic electrical behavior is limited. In this study, we utilized simplified engineered excitable cells that contain the minimal machinery of excitability and can be directly computationally modeled. By pairing experimental and computational studies, we showed that the microscopic branching and collisions of electrical waves slow and speed conduction, respectively, resulting in macroscopic changes in the speed and pattern of electrical activation. These microscale behaviors are significantly altered under reduced excitability, resulting in exaggerated collision effects. Overall, this study helps improve our understanding of how microscopic structural heterogeneities in excitable tissue lead to abnormal action potential propagation, conducive to arrhythmias.

Scalable and Accurate ECG Simulation for Reaction-Diffusion Models of the Human Heart

Realistic electrocardiogram (ECG) simulation with numerical models is important for research linking cellular and molecular physiology to clinically observable signals, and crucial for patient tailoring of numerical heart models. However, ECG simulation with a realistic torso model is computationally much harder than simulation of cardiac activity itself, so that many studies with sophisticated heart models have resorted to crude approximations of the ECG. This paper shows how the classical concept of electrocardiographic lead fields can be used for an ECG simulation method that matches the realism of modern heart models. The accuracy and resource requirements were compared to those of a full-torso solution for the potential and scaling was tested up to 14,336 cores with a heart model consisting of 11 million nodes. Reference ECGs were computed on a 3.3 billion-node heart-torso mesh at 0.2 mm resolution. The results show that the lead-field method is more efficient than a full-torso solution when the number of simulated samples is larger than the number of computed ECG leads. While the initial computation of the lead fields remains a hard and poorly scalable problem, the ECG computation itself scales almost perfectly and, even for several hundreds of ECG leads, takes much less time than the underlying simulation of cardiac activity.