Computational Analysis of Complex Beat-to-Beat Dynamics in Heart Cells

Contrary to the popular belief that the heart maintains a regular rhythm, healthy heartbeats fluctuate in a chaotic way. We now know that the fluctuations do not display uncorrelated randomness, but they contain long-range correlations and can be characterized by a fractal. This behavior supports the adaptability of the heart and may thus protect it from external stress. The fractal complexity is also found in the smallest parts of the heart: the cells. In the dawn of advanced pluripotent stem cell technology, producing independently beating cardiomyocytes in a laboratory, the beat-rate fluctuations of heart cells can be directly studied. In this thesis, we investigate the complex fluctuations in the field potentials generated by clusters of human cardiomyocytes. We show that the heart cells exhibit similar correlation properties in the beat-to-beat intervals and field potential durations comparable to RR and QT intervals, i.e., time between consecutive R waves and time from Q wave to the end of T wave, respectively, in an electrocardiogram of a heart. The cells are studied under conditions resembling real-life situations such as cardiac disorders, application of cardioactive drugs, and injuries. The results show significant alteration of the scaling properties in the beat rates, reflecting the changes in the intrinsic mechanism at the cellular level. By employing a set of nonlinear time series analysis tools, we explore their powerful applicability as well as their limitations. Our main method of choice throughout the work is detrended fluctuation analysis, which is designed to detect the degree of correlation in nonstationary time series. We demonstrate that detrended fluctuation analysis and its extensions are extremely useful in dealing with the field potential data of the heart cells despite the presence of abnormalities and irregular trends. The study of heartbeat dynamics at the cellular level using computational methods has important advantages. In particular, the methods provide non-invasive and versatile ways to improve our understanding of the intrinsic firing patterns of the heart cells, which play a crucial role in the future applications of in vitro human cardiomyocytes

A dynamic clamping approach using in silico IK1 current for discrimination of chamber-specific hiPSC-derived cardiomyocytes

: Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CM) constitute a mixed population of ventricular-, atrial-, nodal-like cells, limiting the reliability for studying chamber-specific disease mechanisms. Previous studies characterised CM phenotype based on action potential (AP) morphology, but the classification criteria were still undefined. Our aim was to use in silico models to develop an automated approach for discriminating the electrophysiological differences between hiPSC-CM. We propose the dynamic clamp (DC) technique with the injection of a specific IK1 current as a tool for deriving nine electrical biomarkers and blindly classifying differentiated CM. An unsupervised learning algorithm was applied to discriminate CM phenotypes and principal component analysis was used to visualise cell clustering. Pharmacological validation was performed by specific ion channel blocker and receptor agonist. The proposed approach improves the translational relevance of the hiPSC-CM model for studying mechanisms underlying inherited or acquired atrial arrhythmias in human CM, and for screening anti-arrhythmic agents

Electrophysiological and cellular analysis of filamin-C mutations causing cardiomyopathy using human iPSC-derived cardiomyocytes

Background: Arrhythmogenic Cardiomyopathy (AC) is a genetic cardiac disease resulting from different mutations within proteins constituting the intercalated disc, including desmosomal and nondesmosomal proteins. Recent studies have revealed that mutations in filamin-C (FLNC) may lead to AC. The arrhythmogenesis and electrophysiological effects of FLNC-related AC are incompletely understood. Therefore, the aim of this study is to assess the potential electrophysiological consequences of FLNC loss as occurs in AC in human induced pluripotent stem cell-derived cardiomyocytes (hiPSCCMs). Specifically, I aimed to characterise abnormal electrical activity and the expression and function of key proteins in cardiac electrical activity such as gap junction protein connexin 43 (Cx43).// Methods: hiPSC-CMs were differentiated and observed by immunofluorescence microscopy. Small interfering RNA (siRNA) transfection was utilised to knockdown the expression of FLNC in hiPSC-CMs. Protein analysis was performed using western blotting to confirm the knockdown efficiency. Electrophysiological properties were recorded using a multielectrode array and manual patch clamping. Optical recording of membrane potential and calcium activity from hiPSC-CMs were also carried out using parameter sensitive dyes.// Results: Silencing of FLNC led to markedly decreased immunofluorescence signals of FLNC, Cx43, desmoplakin, and junctional plakoglobin. No significant reductions were noted in the immunofluorescence signals of voltage-gated sodium channel (Nav1.5) and plakophilin-2 compared with control hiPSC-CMs. Western blotting showed the reduction of FLNC and Cx43 expression following silencing of FLNC. Knockdown of FLNC resulted in disturbances to the recorded action and field potential signals of hiPSC-CMs and arrhythmic likeevents. Transfected hiPSC-CMs with siRNA-FLNC were associated with prolongation of calcium transient durations, optical action potential duration, and action potentials measured with patch clamping.// Conclusion: The current findings indicated that loss of FLNC resulted in a complex arrhythmogenic phenotype in hiPSC-CM

Cardiac organoid technology and computational processing of cardiac physiology for advanced drug screening applications

Stem cell technology has gained considerable recognition since its inception to advance disease modeling and drug screening. This is especially true for tissues that are difficult to study due to tissue sensitivity and limited regenerative capacity, such as the heart. Previous work in stem cell-derived cardiac tissue has exploited how we can engineer biologically functional heart tissue by providing the appropriate external stimuli to facilitate tissue development. The goal of this dissertation is to explore the potentials of stem cell cardiac organoid models to recapitulate heart development and implement analytical computational tools to study cardiac physiology. These new tools were implemented as potential advancements in drug screening applications for better predictions of drug-related cardiotoxicity. Cardiac organoids, generated via micropatterning techniques, were explored to determine how controlling engineering parameters, specifically the geometry, direct tissue fate and organoid function. The advantage of cardiac organoid models is the ability to recapitulate and study human tissue morphogenesis and development, which has currently been restricted through animal models. The cardiac organoids demonstrated responsiveness manifested as impairments to tissue formation and contractile functions as a result of developmental drug toxicity. Single-cell genomic characterization of cardiac organoids unveiled a co-emergence of cardiac and endoderm tissue, which is seen in vivo through paracrine signaling between the liver and heart. We then implemented computational tools based on nonlinear mathematical analysis to evaluate the cardiac physiological drug response of stem cell-derived cardiomyocytes. This dissertation discusses in vitro tissue platforms as well as computational tools to study drug-induced cardiotoxicity. Using these tools, we can extend current toolboxes of understanding cardiac physiology for advanced investigations of stem-cell based cardiac tissue engineering

The Effects of Pharmacological Compounds on Beat Rate Variations in Human Long QT-Syndrome Cardiomyocytes

Healthy human heart rate fluctuates overtime showing long-range fractal correlations. In contrast, various cardiac diseases and normal aging show the breakdown of fractal complexity. Recently, it was shown that human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) intrinsically exhibit fractal behavior as in humans. Here, we investigated the fractal complexity of hiPSC-derived long QT-cardiomyocytes (LQT-CMs). We recorded extracellular field potentials from hiPSC-CMs at baseline and under the effect of various compounds including β-blocker bisoprolol, ML277, a specific and potent IKs current activator, as well as JNJ303, a specific IKs blocker. From the peak-to-peak-intervals, we determined the long-range fractal correlations by using detrended fluctuation analysis. Electrophysiologically, the baseline corrected field potential durations (cFPDs) were more prolonged in LQT-CMs than in wildtype (WT)-CMs. Bisoprolol did not have significant effects to the cFPD in any CMs. ML277 shortened cFPD in a dose-dependent fashion by 11 % and 5-11 % in WT- and LQT-CMs, respectively. JNJ303 prolonged cFPD in a dose-dependent fashion by 22 % and 7-13 % in WT- and LQT-CMs, respectively. At baseline, all CMs showed fractal correlations as determined by short-term scaling exponent α. However, in all CMs, the α was increased when pharmacological compounds were applied indicating of breakdown of fractal complexity. These findings suggest that the intrinsic mechanisms contributing to the fractal complexity are not altered in LQT-CMs. The modulation of IKs channel and β1-adrenoreceptors by pharmacological compounds may affect the fractal complexity of the hiPSC-CMs

Cardiomyocytes from human pluripotent stem cells: from laboratory curiosity to industrial biomedical platform

Cardiomyocytes from human pluripotent stem cells (hPSCs-CMs) could revolutionise biomedicine. Global burden of heart failure will soon reach USD $90bn, while unexpected cardiotoxicity underlies 28% of drug withdrawals. Advances in hPSC isolation, Cas9/CRISPR genome engineering and hPSC-CM differentiation have improved patient care, progressed drugs to clinic and opened a new era in safety pharmacology. Nevertheless, predictive cardiotoxicity using hPSC-CMs contrasts from failure to almost total success. Since this likely relates to cell immaturity, efforts are underway to use biochemical and biophysical cues to improve many of the ~ 30 structural and functional properties of hPSC-CMs towards those seen in adult CMs. Other developments needed for widespread hPSC-CM utility include subtype specification, cost reduction of large scale differentiation and elimination of the phenotyping bottleneck. This review will consider these factors in the evolution of hPSC-CM technologies, as well as their integration into high content industrial platforms that assess structure, mitochondrial function, electrophysiology, calcium transients and contractility. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Integration of Developmental and Environmental Cues in the Heart edited by Marcus Schaub and Hughes Abriel

Syncytial Model of Human Pluripotent Stem Cell-Derived Cardiomyocytes for Electrophysiology Studies

Human pluripotent stem cells (hPSCs) are a valuable resource for generating human cardiomyocytes and modeling human cardiac physiology in vitro. In this thesis, the electrophysiology of hPSC derived cardiomyocytes was studied in large populations of cells in syncytial models. It was found that heterogeneity in electrophysiology, as represented by action potential variability, is common in small clusters of hPSC-derived cardiomyocytes. A waveform-based automated algorithm was used to identify groups of cardiomyocytes based on similarity of their action potentials. It was found that, unlike in small cell clusters, action potential variability in monolayer culture was relatively low, resembling mainly a single electrophysiological phenotype. The utility of a monolayer hPSC-CM model was explored in two applications: 1) modeling the monogenic disease, type 2 Long QT syndrome (LQT2), using a human induced pluripotent stem cell (hiPSC) line carrying a hERG-A422T mutation, and 2) studying responses to cardioactive drugs using hiPSC-derived cardiomyocytes. The monolayer model with LQT2 hiPSC-derived cardiomyocytes had prolonged action potentials and an increased sensitivity to IKr block compared to that of non-disease cardiomyocytes, consistent with the expected LQT2 phenotype. The prolonged action potentials could be normalized by activation of IKr with ML-T531, a compound that delays the inactivation of the hERG channel. However, ectopic activity, such as early-afterdepolarizations (EADs), were mostly absent in LQT2 monolayers, in contrast to the frequent occurrence reported in smaller cell cultures or single cells. For drug testing, monolayers of hiPSC-derived cardiomyocytes responded to a panel of eight cardioactive drugs in a manner consistent with the mechanism of the drugs: blockers of repolarizing currents prolonged the action potentials, while blockers of depolarizing currents shortened them. At a tissue level, blockers of excitatory INa slowed propagation of action potentials. Computational modeling showed that a drug can alter the repolarization gradient, a proarrhythmia biomarker, in monolayers having a defined electrophysiological gradient